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osmnx.utils_graph
get_digraph
Do not use: deprecated. Use the `convert.to_digraph` function instead. Parameters ---------- G : networkx.MultiDiGraph deprecated, do not use weight : string deprecated, do not use Returns ------- networkx.DiGraph
def get_digraph(G, weight="length"): """ Do not use: deprecated. Use the `convert.to_digraph` function instead. Parameters ---------- G : networkx.MultiDiGraph deprecated, do not use weight : string deprecated, do not use Returns ------- networkx.DiGraph """ msg = ( "The `get_digraph` function is deprecated and will be removed in the " "v2.0.0 release. Replace it with `convert.to_digraph` instead. " "See the OSMnx v2 migration guide: https://github.com/gboeing/osmnx/issues/1123" ) warn(msg, FutureWarning, stacklevel=2) return convert.to_digraph(G, weight)
(G, weight='length')
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52,228
osmnx.utils_graph
get_undirected
Do not use: deprecated. Use the `convert.to_undirected` function instead. Parameters ---------- G : networkx.MultiDiGraph deprecated, do not use Returns ------- networkx.MultiGraph
def get_undirected(G): """ Do not use: deprecated. Use the `convert.to_undirected` function instead. Parameters ---------- G : networkx.MultiDiGraph deprecated, do not use Returns ------- networkx.MultiGraph """ msg = ( "The `get_undirected` function is deprecated and will be removed in the " "v2.0.0 release. Replace it with `convert.to_undirected` instead. " "See the OSMnx v2 migration guide: https://github.com/gboeing/osmnx/issues/1123" ) warn(msg, FutureWarning, stacklevel=2) return convert.to_undirected(G)
(G)
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52,230
osmnx.graph
graph_from_address
Download and create a graph within some distance of an address. You can use the `settings` module to retrieve a snapshot of historical OSM data as of a certain date, or to configure the Overpass server timeout, memory allocation, and other custom settings. Parameters ---------- address : string the address to geocode and use as the central point around which to construct the graph dist : int retain only those nodes within this many meters of the center of the graph dist_type : string {"network", "bbox"} if "bbox", retain only those nodes within a bounding box of the distance parameter. if "network", retain only those nodes within some network distance from the center-most node. network_type : string {"all", "all_public", "bike", "drive", "drive_service", "walk"} what type of street network to get if custom_filter is None simplify : bool if True, simplify graph topology with the `simplify_graph` function retain_all : bool if True, return the entire graph even if it is not connected. otherwise, retain only the largest weakly connected component. truncate_by_edge : bool if True, retain nodes outside bounding box if at least one of node's neighbors is within the bounding box return_coords : bool deprecated, do not use clean_periphery : bool deprecated, do not use custom_filter : string a custom ways filter to be used instead of the network_type presets e.g., '["power"~"line"]' or '["highway"~"motorway|trunk"]'. Also pass in a network_type that is in settings.bidirectional_network_types if you want graph to be fully bi-directional. Returns ------- networkx.MultiDiGraph or optionally (networkx.MultiDiGraph, (lat, lon)) Notes ----- Very large query areas use the `utils_geo._consolidate_subdivide_geometry` function to automatically make multiple requests: see that function's documentation for caveats.
def graph_from_address( address, dist=1000, dist_type="bbox", network_type="all", simplify=True, retain_all=False, truncate_by_edge=False, return_coords=None, clean_periphery=None, custom_filter=None, ): """ Download and create a graph within some distance of an address. You can use the `settings` module to retrieve a snapshot of historical OSM data as of a certain date, or to configure the Overpass server timeout, memory allocation, and other custom settings. Parameters ---------- address : string the address to geocode and use as the central point around which to construct the graph dist : int retain only those nodes within this many meters of the center of the graph dist_type : string {"network", "bbox"} if "bbox", retain only those nodes within a bounding box of the distance parameter. if "network", retain only those nodes within some network distance from the center-most node. network_type : string {"all", "all_public", "bike", "drive", "drive_service", "walk"} what type of street network to get if custom_filter is None simplify : bool if True, simplify graph topology with the `simplify_graph` function retain_all : bool if True, return the entire graph even if it is not connected. otherwise, retain only the largest weakly connected component. truncate_by_edge : bool if True, retain nodes outside bounding box if at least one of node's neighbors is within the bounding box return_coords : bool deprecated, do not use clean_periphery : bool deprecated, do not use custom_filter : string a custom ways filter to be used instead of the network_type presets e.g., '["power"~"line"]' or '["highway"~"motorway|trunk"]'. Also pass in a network_type that is in settings.bidirectional_network_types if you want graph to be fully bi-directional. Returns ------- networkx.MultiDiGraph or optionally (networkx.MultiDiGraph, (lat, lon)) Notes ----- Very large query areas use the `utils_geo._consolidate_subdivide_geometry` function to automatically make multiple requests: see that function's documentation for caveats. """ if return_coords is None: return_coords = False else: warn( "The `return_coords` argument has been deprecated and will be removed in " "the v2.0.0 release. Future behavior will be as though `return_coords=False`. " "If you want the address's geocoded coordinates, use the `geocode` function. " "See the OSMnx v2 migration guide: https://github.com/gboeing/osmnx/issues/1123", FutureWarning, stacklevel=2, ) # geocode the address string to a (lat, lon) point point = geocoder.geocode(query=address) # then create a graph from this point G = graph_from_point( point, dist, dist_type, network_type=network_type, simplify=simplify, retain_all=retain_all, truncate_by_edge=truncate_by_edge, clean_periphery=clean_periphery, custom_filter=custom_filter, ) utils.log(f"graph_from_address returned graph with {len(G):,} nodes and {len(G.edges):,} edges") if return_coords: return G, point # otherwise return G
(address, dist=1000, dist_type='bbox', network_type='all', simplify=True, retain_all=False, truncate_by_edge=False, return_coords=None, clean_periphery=None, custom_filter=None)
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52,231
osmnx.graph
graph_from_bbox
Download and create a graph within some bounding box. You can use the `settings` module to retrieve a snapshot of historical OSM data as of a certain date, or to configure the Overpass server timeout, memory allocation, and other custom settings. Parameters ---------- north : float deprecated, do not use south : float deprecated, do not use east : float deprecated, do not use west : float deprecated, do not use bbox : tuple of floats bounding box as (north, south, east, west) network_type : string {"all", "all_public", "bike", "drive", "drive_service", "walk"} what type of street network to get if custom_filter is None simplify : bool if True, simplify graph topology with the `simplify_graph` function retain_all : bool if True, return the entire graph even if it is not connected. otherwise, retain only the largest weakly connected component. truncate_by_edge : bool if True, retain nodes outside bounding box if at least one of node's neighbors is within the bounding box clean_periphery : bool deprecated, do not use custom_filter : string a custom ways filter to be used instead of the network_type presets e.g., '["power"~"line"]' or '["highway"~"motorway|trunk"]'. Also pass in a network_type that is in settings.bidirectional_network_types if you want graph to be fully bi-directional. Returns ------- G : networkx.MultiDiGraph Notes ----- Very large query areas use the `utils_geo._consolidate_subdivide_geometry` function to automatically make multiple requests: see that function's documentation for caveats.
def graph_from_bbox( north=None, south=None, east=None, west=None, bbox=None, network_type="all", simplify=True, retain_all=False, truncate_by_edge=False, clean_periphery=None, custom_filter=None, ): """ Download and create a graph within some bounding box. You can use the `settings` module to retrieve a snapshot of historical OSM data as of a certain date, or to configure the Overpass server timeout, memory allocation, and other custom settings. Parameters ---------- north : float deprecated, do not use south : float deprecated, do not use east : float deprecated, do not use west : float deprecated, do not use bbox : tuple of floats bounding box as (north, south, east, west) network_type : string {"all", "all_public", "bike", "drive", "drive_service", "walk"} what type of street network to get if custom_filter is None simplify : bool if True, simplify graph topology with the `simplify_graph` function retain_all : bool if True, return the entire graph even if it is not connected. otherwise, retain only the largest weakly connected component. truncate_by_edge : bool if True, retain nodes outside bounding box if at least one of node's neighbors is within the bounding box clean_periphery : bool deprecated, do not use custom_filter : string a custom ways filter to be used instead of the network_type presets e.g., '["power"~"line"]' or '["highway"~"motorway|trunk"]'. Also pass in a network_type that is in settings.bidirectional_network_types if you want graph to be fully bi-directional. Returns ------- G : networkx.MultiDiGraph Notes ----- Very large query areas use the `utils_geo._consolidate_subdivide_geometry` function to automatically make multiple requests: see that function's documentation for caveats. """ if not (north is None and south is None and east is None and west is None): msg = ( "The `north`, `south`, `east`, and `west` parameters are deprecated and " "will be removed in the v2.0.0 release. Use the `bbox` parameter instead. " "See the OSMnx v2 migration guide: https://github.com/gboeing/osmnx/issues/1123" ) warn(msg, FutureWarning, stacklevel=2) bbox = (north, south, east, west) # convert bounding box to a polygon polygon = utils_geo.bbox_to_poly(bbox=bbox) # create graph using this polygon geometry G = graph_from_polygon( polygon, network_type=network_type, simplify=simplify, retain_all=retain_all, truncate_by_edge=truncate_by_edge, clean_periphery=clean_periphery, custom_filter=custom_filter, ) utils.log(f"graph_from_bbox returned graph with {len(G):,} nodes and {len(G.edges):,} edges") return G
(north=None, south=None, east=None, west=None, bbox=None, network_type='all', simplify=True, retain_all=False, truncate_by_edge=False, clean_periphery=None, custom_filter=None)
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52,232
osmnx.convert
graph_from_gdfs
Convert node and edge GeoDataFrames to a MultiDiGraph. This function is the inverse of `graph_to_gdfs` and is designed to work in conjunction with it. However, you can convert arbitrary node and edge GeoDataFrames as long as 1) `gdf_nodes` is uniquely indexed by `osmid`, 2) `gdf_nodes` contains `x` and `y` coordinate columns representing node geometries, 3) `gdf_edges` is uniquely multi-indexed by `u`, `v`, `key` (following normal MultiDiGraph structure). This allows you to load any node/edge shapefiles or GeoPackage layers as GeoDataFrames then convert them to a MultiDiGraph for graph analysis. Note that any `geometry` attribute on `gdf_nodes` is discarded since `x` and `y` provide the necessary node geometry information instead. Parameters ---------- gdf_nodes : geopandas.GeoDataFrame GeoDataFrame of graph nodes uniquely indexed by osmid gdf_edges : geopandas.GeoDataFrame GeoDataFrame of graph edges uniquely multi-indexed by u, v, key graph_attrs : dict the new G.graph attribute dict. if None, use crs from gdf_edges as the only graph-level attribute (gdf_edges must have crs attribute set) Returns ------- G : networkx.MultiDiGraph
def graph_from_gdfs(gdf_nodes, gdf_edges, graph_attrs=None): """ Convert node and edge GeoDataFrames to a MultiDiGraph. This function is the inverse of `graph_to_gdfs` and is designed to work in conjunction with it. However, you can convert arbitrary node and edge GeoDataFrames as long as 1) `gdf_nodes` is uniquely indexed by `osmid`, 2) `gdf_nodes` contains `x` and `y` coordinate columns representing node geometries, 3) `gdf_edges` is uniquely multi-indexed by `u`, `v`, `key` (following normal MultiDiGraph structure). This allows you to load any node/edge shapefiles or GeoPackage layers as GeoDataFrames then convert them to a MultiDiGraph for graph analysis. Note that any `geometry` attribute on `gdf_nodes` is discarded since `x` and `y` provide the necessary node geometry information instead. Parameters ---------- gdf_nodes : geopandas.GeoDataFrame GeoDataFrame of graph nodes uniquely indexed by osmid gdf_edges : geopandas.GeoDataFrame GeoDataFrame of graph edges uniquely multi-indexed by u, v, key graph_attrs : dict the new G.graph attribute dict. if None, use crs from gdf_edges as the only graph-level attribute (gdf_edges must have crs attribute set) Returns ------- G : networkx.MultiDiGraph """ if not ("x" in gdf_nodes.columns and "y" in gdf_nodes.columns): # pragma: no cover msg = "gdf_nodes must contain x and y columns" raise ValueError(msg) # if gdf_nodes has a geometry attribute set, drop that column (as we use x # and y for geometry information) and warn the user if the geometry values # differ from the coordinates in the x and y columns if hasattr(gdf_nodes, "geometry"): try: all_x_match = (gdf_nodes.geometry.x == gdf_nodes["x"]).all() all_y_match = (gdf_nodes.geometry.y == gdf_nodes["y"]).all() assert all_x_match assert all_y_match except (AssertionError, ValueError): # pragma: no cover # AssertionError if x/y coords don't match geometry column # ValueError if geometry column contains non-point geometry types warn( "discarding the gdf_nodes geometry column, though its " "values differ from the coordinates in the x and y columns", stacklevel=2, ) gdf_nodes = gdf_nodes.drop(columns=gdf_nodes.geometry.name) # create graph and add graph-level attribute dict if graph_attrs is None: graph_attrs = {"crs": gdf_edges.crs} G = nx.MultiDiGraph(**graph_attrs) # add edges and their attributes to graph, but filter out null attribute # values so that edges only get attributes with non-null values attr_names = gdf_edges.columns.to_list() for (u, v, k), attr_vals in zip(gdf_edges.index, gdf_edges.to_numpy()): data_all = zip(attr_names, attr_vals) data = {name: val for name, val in data_all if isinstance(val, list) or pd.notna(val)} G.add_edge(u, v, key=k, **data) # add any nodes with no incident edges, since they wouldn't be added above G.add_nodes_from(set(gdf_nodes.index) - set(G.nodes)) # now all nodes are added, so set nodes' attributes for col in gdf_nodes.columns: nx.set_node_attributes(G, name=col, values=gdf_nodes[col].dropna()) utils.log("Created graph from node/edge GeoDataFrames") return G
(gdf_nodes, gdf_edges, graph_attrs=None)
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52,233
osmnx.graph
graph_from_place
Download and create a graph within the boundaries of some place(s). The query must be geocodable and OSM must have polygon boundaries for the geocode result. If OSM does not have a polygon for this place, you can instead get its street network using the graph_from_address function, which geocodes the place name to a point and gets the network within some distance of that point. If OSM does have polygon boundaries for this place but you're not finding it, try to vary the query string, pass in a structured query dict, or vary the which_result argument to use a different geocode result. If you know the OSM ID of the place, you can retrieve its boundary polygon using the geocode_to_gdf function, then pass it to the graph_from_polygon function. You can use the `settings` module to retrieve a snapshot of historical OSM data as of a certain date, or to configure the Overpass server timeout, memory allocation, and other custom settings. Parameters ---------- query : string or dict or list the query or queries to geocode to get place boundary polygon(s) network_type : string {"all", "all_public", "bike", "drive", "drive_service", "walk"} what type of street network to get if custom_filter is None simplify : bool if True, simplify graph topology with the `simplify_graph` function retain_all : bool if True, return the entire graph even if it is not connected. otherwise, retain only the largest weakly connected component. truncate_by_edge : bool if True, retain nodes outside boundary polygon if at least one of node's neighbors is within the polygon which_result : int which geocoding result to use. if None, auto-select the first (Multi)Polygon or raise an error if OSM doesn't return one. buffer_dist : float deprecated, do not use clean_periphery : bool deprecated, do not use custom_filter : string a custom ways filter to be used instead of the network_type presets e.g., '["power"~"line"]' or '["highway"~"motorway|trunk"]'. Also pass in a network_type that is in settings.bidirectional_network_types if you want graph to be fully bi-directional. Returns ------- G : networkx.MultiDiGraph Notes ----- Very large query areas use the `utils_geo._consolidate_subdivide_geometry` function to automatically make multiple requests: see that function's documentation for caveats.
def graph_from_place( query, network_type="all", simplify=True, retain_all=False, truncate_by_edge=False, which_result=None, buffer_dist=None, clean_periphery=None, custom_filter=None, ): """ Download and create a graph within the boundaries of some place(s). The query must be geocodable and OSM must have polygon boundaries for the geocode result. If OSM does not have a polygon for this place, you can instead get its street network using the graph_from_address function, which geocodes the place name to a point and gets the network within some distance of that point. If OSM does have polygon boundaries for this place but you're not finding it, try to vary the query string, pass in a structured query dict, or vary the which_result argument to use a different geocode result. If you know the OSM ID of the place, you can retrieve its boundary polygon using the geocode_to_gdf function, then pass it to the graph_from_polygon function. You can use the `settings` module to retrieve a snapshot of historical OSM data as of a certain date, or to configure the Overpass server timeout, memory allocation, and other custom settings. Parameters ---------- query : string or dict or list the query or queries to geocode to get place boundary polygon(s) network_type : string {"all", "all_public", "bike", "drive", "drive_service", "walk"} what type of street network to get if custom_filter is None simplify : bool if True, simplify graph topology with the `simplify_graph` function retain_all : bool if True, return the entire graph even if it is not connected. otherwise, retain only the largest weakly connected component. truncate_by_edge : bool if True, retain nodes outside boundary polygon if at least one of node's neighbors is within the polygon which_result : int which geocoding result to use. if None, auto-select the first (Multi)Polygon or raise an error if OSM doesn't return one. buffer_dist : float deprecated, do not use clean_periphery : bool deprecated, do not use custom_filter : string a custom ways filter to be used instead of the network_type presets e.g., '["power"~"line"]' or '["highway"~"motorway|trunk"]'. Also pass in a network_type that is in settings.bidirectional_network_types if you want graph to be fully bi-directional. Returns ------- G : networkx.MultiDiGraph Notes ----- Very large query areas use the `utils_geo._consolidate_subdivide_geometry` function to automatically make multiple requests: see that function's documentation for caveats. """ if buffer_dist is not None: warn( "The buffer_dist argument has been deprecated and will be removed " "in the v2.0.0 release. Buffer your query area directly, if desired. " "See the OSMnx v2 migration guide: https://github.com/gboeing/osmnx/issues/1123", FutureWarning, stacklevel=2, ) # create a GeoDataFrame with the spatial boundaries of the place(s) if isinstance(query, (str, dict)): # if it is a string (place name) or dict (structured place query), # then it is a single place gdf_place = geocoder.geocode_to_gdf( query, which_result=which_result, buffer_dist=buffer_dist ) elif isinstance(query, list): # if it is a list, it contains multiple places to get gdf_place = geocoder.geocode_to_gdf(query, buffer_dist=buffer_dist) else: # pragma: no cover msg = "query must be dict, string, or list of strings" raise TypeError(msg) # extract the geometry from the GeoDataFrame to use in API query polygon = gdf_place["geometry"].unary_union utils.log("Constructed place geometry polygon(s) to query API") # create graph using this polygon(s) geometry G = graph_from_polygon( polygon, network_type=network_type, simplify=simplify, retain_all=retain_all, truncate_by_edge=truncate_by_edge, clean_periphery=clean_periphery, custom_filter=custom_filter, ) utils.log(f"graph_from_place returned graph with {len(G):,} nodes and {len(G.edges):,} edges") return G
(query, network_type='all', simplify=True, retain_all=False, truncate_by_edge=False, which_result=None, buffer_dist=None, clean_periphery=None, custom_filter=None)
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52,234
osmnx.graph
graph_from_point
Download and create a graph within some distance of a (lat, lon) point. You can use the `settings` module to retrieve a snapshot of historical OSM data as of a certain date, or to configure the Overpass server timeout, memory allocation, and other custom settings. Parameters ---------- center_point : tuple the (lat, lon) center point around which to construct the graph dist : int retain only those nodes within this many meters of the center of the graph, with distance determined according to dist_type argument dist_type : string {"network", "bbox"} if "bbox", retain only those nodes within a bounding box of the distance parameter. if "network", retain only those nodes within some network distance from the center-most node. network_type : string, {"all", "all_public", "bike", "drive", "drive_service", "walk"} what type of street network to get if custom_filter is None simplify : bool if True, simplify graph topology with the `simplify_graph` function retain_all : bool if True, return the entire graph even if it is not connected. otherwise, retain only the largest weakly connected component. truncate_by_edge : bool if True, retain nodes outside bounding box if at least one of node's neighbors is within the bounding box clean_periphery : bool, deprecated, do not use custom_filter : string a custom ways filter to be used instead of the network_type presets e.g., '["power"~"line"]' or '["highway"~"motorway|trunk"]'. Also pass in a network_type that is in settings.bidirectional_network_types if you want graph to be fully bi-directional. Returns ------- G : networkx.MultiDiGraph Notes ----- Very large query areas use the `utils_geo._consolidate_subdivide_geometry` function to automatically make multiple requests: see that function's documentation for caveats.
def graph_from_point( center_point, dist=1000, dist_type="bbox", network_type="all", simplify=True, retain_all=False, truncate_by_edge=False, clean_periphery=None, custom_filter=None, ): """ Download and create a graph within some distance of a (lat, lon) point. You can use the `settings` module to retrieve a snapshot of historical OSM data as of a certain date, or to configure the Overpass server timeout, memory allocation, and other custom settings. Parameters ---------- center_point : tuple the (lat, lon) center point around which to construct the graph dist : int retain only those nodes within this many meters of the center of the graph, with distance determined according to dist_type argument dist_type : string {"network", "bbox"} if "bbox", retain only those nodes within a bounding box of the distance parameter. if "network", retain only those nodes within some network distance from the center-most node. network_type : string, {"all", "all_public", "bike", "drive", "drive_service", "walk"} what type of street network to get if custom_filter is None simplify : bool if True, simplify graph topology with the `simplify_graph` function retain_all : bool if True, return the entire graph even if it is not connected. otherwise, retain only the largest weakly connected component. truncate_by_edge : bool if True, retain nodes outside bounding box if at least one of node's neighbors is within the bounding box clean_periphery : bool, deprecated, do not use custom_filter : string a custom ways filter to be used instead of the network_type presets e.g., '["power"~"line"]' or '["highway"~"motorway|trunk"]'. Also pass in a network_type that is in settings.bidirectional_network_types if you want graph to be fully bi-directional. Returns ------- G : networkx.MultiDiGraph Notes ----- Very large query areas use the `utils_geo._consolidate_subdivide_geometry` function to automatically make multiple requests: see that function's documentation for caveats. """ if dist_type not in {"bbox", "network"}: # pragma: no cover msg = 'dist_type must be "bbox" or "network"' raise ValueError(msg) # create bounding box from center point and distance in each direction bbox = utils_geo.bbox_from_point(center_point, dist) # create a graph from the bounding box G = graph_from_bbox( bbox=bbox, network_type=network_type, simplify=simplify, retain_all=retain_all, truncate_by_edge=truncate_by_edge, clean_periphery=clean_periphery, custom_filter=custom_filter, ) if dist_type == "network": # if dist_type is network, find node in graph nearest to center point # then truncate graph by network dist from it node = distance.nearest_nodes(G, X=[center_point[1]], Y=[center_point[0]])[0] G = truncate.truncate_graph_dist(G, node, max_dist=dist) utils.log(f"graph_from_point returned graph with {len(G):,} nodes and {len(G.edges):,} edges") return G
(center_point, dist=1000, dist_type='bbox', network_type='all', simplify=True, retain_all=False, truncate_by_edge=False, clean_periphery=None, custom_filter=None)
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52,235
osmnx.graph
graph_from_polygon
Download and create a graph within the boundaries of a (multi)polygon. You can use the `settings` module to retrieve a snapshot of historical OSM data as of a certain date, or to configure the Overpass server timeout, memory allocation, and other custom settings. Parameters ---------- polygon : shapely.geometry.Polygon or shapely.geometry.MultiPolygon the shape to get network data within. coordinates should be in unprojected latitude-longitude degrees (EPSG:4326). network_type : string {"all", "all_public", "bike", "drive", "drive_service", "walk"} what type of street network to get if custom_filter is None simplify : bool if True, simplify graph topology with the `simplify_graph` function retain_all : bool if True, return the entire graph even if it is not connected. otherwise, retain only the largest weakly connected component. truncate_by_edge : bool if True, retain nodes outside boundary polygon if at least one of node's neighbors is within the polygon clean_periphery : bool deprecated, do not use custom_filter : string a custom ways filter to be used instead of the network_type presets e.g., '["power"~"line"]' or '["highway"~"motorway|trunk"]'. Also pass in a network_type that is in settings.bidirectional_network_types if you want graph to be fully bi-directional. Returns ------- G : networkx.MultiDiGraph Notes ----- Very large query areas use the `utils_geo._consolidate_subdivide_geometry` function to automatically make multiple requests: see that function's documentation for caveats.
def graph_from_polygon( polygon, network_type="all", simplify=True, retain_all=False, truncate_by_edge=False, clean_periphery=None, custom_filter=None, ): """ Download and create a graph within the boundaries of a (multi)polygon. You can use the `settings` module to retrieve a snapshot of historical OSM data as of a certain date, or to configure the Overpass server timeout, memory allocation, and other custom settings. Parameters ---------- polygon : shapely.geometry.Polygon or shapely.geometry.MultiPolygon the shape to get network data within. coordinates should be in unprojected latitude-longitude degrees (EPSG:4326). network_type : string {"all", "all_public", "bike", "drive", "drive_service", "walk"} what type of street network to get if custom_filter is None simplify : bool if True, simplify graph topology with the `simplify_graph` function retain_all : bool if True, return the entire graph even if it is not connected. otherwise, retain only the largest weakly connected component. truncate_by_edge : bool if True, retain nodes outside boundary polygon if at least one of node's neighbors is within the polygon clean_periphery : bool deprecated, do not use custom_filter : string a custom ways filter to be used instead of the network_type presets e.g., '["power"~"line"]' or '["highway"~"motorway|trunk"]'. Also pass in a network_type that is in settings.bidirectional_network_types if you want graph to be fully bi-directional. Returns ------- G : networkx.MultiDiGraph Notes ----- Very large query areas use the `utils_geo._consolidate_subdivide_geometry` function to automatically make multiple requests: see that function's documentation for caveats. """ if clean_periphery is None: clean_periphery = True else: warn( "The clean_periphery argument has been deprecated and will be removed in " "the v2.0.0 release. Future behavior will be as though clean_periphery=True. " "See the OSMnx v2 migration guide: https://github.com/gboeing/osmnx/issues/1123", FutureWarning, stacklevel=2, ) # verify that the geometry is valid and is a shapely Polygon/MultiPolygon # before proceeding if not polygon.is_valid: # pragma: no cover msg = "The geometry to query within is invalid" raise ValueError(msg) if not isinstance(polygon, (Polygon, MultiPolygon)): # pragma: no cover msg = ( "Geometry must be a shapely Polygon or MultiPolygon. If you " "requested graph from place name, make sure your query resolves " "to a Polygon or MultiPolygon, and not some other geometry, like " "a Point. See OSMnx documentation for details." ) raise TypeError(msg) if clean_periphery: # create a new buffered polygon 0.5km around the desired one buffer_dist = 500 poly_proj, crs_utm = projection.project_geometry(polygon) poly_proj_buff = poly_proj.buffer(buffer_dist) poly_buff, _ = projection.project_geometry(poly_proj_buff, crs=crs_utm, to_latlong=True) # download the network data from OSM within buffered polygon response_jsons = _overpass._download_overpass_network( poly_buff, network_type, custom_filter ) # create buffered graph from the downloaded data bidirectional = network_type in settings.bidirectional_network_types G_buff = _create_graph(response_jsons, retain_all=True, bidirectional=bidirectional) # truncate buffered graph to the buffered polygon and retain_all for # now. needed because overpass returns entire ways that also include # nodes outside the poly if the way (that is, a way with a single OSM # ID) has a node inside the poly at some point. G_buff = truncate.truncate_graph_polygon(G_buff, poly_buff, True, truncate_by_edge) # simplify the graph topology if simplify: G_buff = simplification.simplify_graph(G_buff) # truncate graph by original polygon to return graph within polygon # caller wants. don't simplify again: this allows us to retain # intersections along the street that may now only connect 2 street # segments in the network, but in reality also connect to an # intersection just outside the polygon G = truncate.truncate_graph_polygon(G_buff, polygon, retain_all, truncate_by_edge) # count how many physical streets in buffered graph connect to each # intersection in un-buffered graph, to retain true counts for each # intersection, even if some of its neighbors are outside the polygon spn = stats.count_streets_per_node(G_buff, nodes=G.nodes) nx.set_node_attributes(G, values=spn, name="street_count") # if clean_periphery=False, just use the polygon as provided else: # download the network data from OSM response_jsons = _overpass._download_overpass_network(polygon, network_type, custom_filter) # create graph from the downloaded data bidirectional = network_type in settings.bidirectional_network_types G = _create_graph(response_jsons, retain_all=True, bidirectional=bidirectional) # truncate the graph to the extent of the polygon G = truncate.truncate_graph_polygon(G, polygon, retain_all, truncate_by_edge) # simplify the graph topology after truncation. don't truncate after # simplifying or you may have simplified out to an endpoint beyond the # truncation distance, which would strip out the entire edge if simplify: G = simplification.simplify_graph(G) # count how many physical streets connect to each intersection/deadend # note this will be somewhat inaccurate due to periphery effects, so # it's best to parameterize function with clean_periphery=True spn = stats.count_streets_per_node(G) nx.set_node_attributes(G, values=spn, name="street_count") warn( "the graph-level street_count attribute will likely be inaccurate " "when you set clean_periphery=False", stacklevel=2, ) utils.log(f"graph_from_polygon returned graph with {len(G):,} nodes and {len(G.edges):,} edges") return G
(polygon, network_type='all', simplify=True, retain_all=False, truncate_by_edge=False, clean_periphery=None, custom_filter=None)
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52,236
osmnx.graph
graph_from_xml
Create a graph from data in a .osm formatted XML file. Do not load an XML file generated by OSMnx: this use case is not supported and may not behave as expected. To save/load graphs to/from disk for later use in OSMnx, use the `io.save_graphml` and `io.load_graphml` functions instead. Parameters ---------- filepath : string or pathlib.Path path to file containing OSM XML data bidirectional : bool if True, create bi-directional edges for one-way streets simplify : bool if True, simplify graph topology with the `simplify_graph` function retain_all : bool if True, return the entire graph even if it is not connected. otherwise, retain only the largest weakly connected component. encoding : string the XML file's character encoding Returns ------- G : networkx.MultiDiGraph
def graph_from_xml( filepath, bidirectional=False, simplify=True, retain_all=False, encoding="utf-8" ): """ Create a graph from data in a .osm formatted XML file. Do not load an XML file generated by OSMnx: this use case is not supported and may not behave as expected. To save/load graphs to/from disk for later use in OSMnx, use the `io.save_graphml` and `io.load_graphml` functions instead. Parameters ---------- filepath : string or pathlib.Path path to file containing OSM XML data bidirectional : bool if True, create bi-directional edges for one-way streets simplify : bool if True, simplify graph topology with the `simplify_graph` function retain_all : bool if True, return the entire graph even if it is not connected. otherwise, retain only the largest weakly connected component. encoding : string the XML file's character encoding Returns ------- G : networkx.MultiDiGraph """ # transmogrify file of OSM XML data into JSON response_jsons = [osm_xml._overpass_json_from_file(filepath, encoding)] # create graph using this response JSON G = _create_graph(response_jsons, bidirectional=bidirectional, retain_all=retain_all) # simplify the graph topology as the last step if simplify: G = simplification.simplify_graph(G) utils.log(f"graph_from_xml returned graph with {len(G):,} nodes and {len(G.edges):,} edges") return G
(filepath, bidirectional=False, simplify=True, retain_all=False, encoding='utf-8')
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52,237
osmnx.convert
graph_to_gdfs
Convert a MultiDiGraph to node and/or edge GeoDataFrames. This function is the inverse of `graph_from_gdfs`. Parameters ---------- G : networkx.MultiDiGraph input graph nodes : bool if True, convert graph nodes to a GeoDataFrame and return it edges : bool if True, convert graph edges to a GeoDataFrame and return it node_geometry : bool if True, create a geometry column from node x and y attributes fill_edge_geometry : bool if True, fill in missing edge geometry fields using nodes u and v Returns ------- geopandas.GeoDataFrame or tuple gdf_nodes or gdf_edges or tuple of (gdf_nodes, gdf_edges). gdf_nodes is indexed by osmid and gdf_edges is multi-indexed by u, v, key following normal MultiDiGraph structure.
def graph_to_gdfs(G, nodes=True, edges=True, node_geometry=True, fill_edge_geometry=True): """ Convert a MultiDiGraph to node and/or edge GeoDataFrames. This function is the inverse of `graph_from_gdfs`. Parameters ---------- G : networkx.MultiDiGraph input graph nodes : bool if True, convert graph nodes to a GeoDataFrame and return it edges : bool if True, convert graph edges to a GeoDataFrame and return it node_geometry : bool if True, create a geometry column from node x and y attributes fill_edge_geometry : bool if True, fill in missing edge geometry fields using nodes u and v Returns ------- geopandas.GeoDataFrame or tuple gdf_nodes or gdf_edges or tuple of (gdf_nodes, gdf_edges). gdf_nodes is indexed by osmid and gdf_edges is multi-indexed by u, v, key following normal MultiDiGraph structure. """ crs = G.graph["crs"] if nodes: if not G.nodes: # pragma: no cover msg = "graph contains no nodes" raise ValueError(msg) uvk, data = zip(*G.nodes(data=True)) if node_geometry: # convert node x/y attributes to Points for geometry column node_geoms = (Point(d["x"], d["y"]) for d in data) gdf_nodes = gpd.GeoDataFrame(data, index=uvk, crs=crs, geometry=list(node_geoms)) else: gdf_nodes = gpd.GeoDataFrame(data, index=uvk) gdf_nodes.index = gdf_nodes.index.rename("osmid") utils.log("Created nodes GeoDataFrame from graph") if edges: if not G.edges: # pragma: no cover msg = "Graph contains no edges" raise ValueError(msg) u, v, k, data = zip(*G.edges(keys=True, data=True)) if fill_edge_geometry: # subroutine to get geometry for every edge: if edge already has # geometry return it, otherwise create it using the incident nodes x_lookup = nx.get_node_attributes(G, "x") y_lookup = nx.get_node_attributes(G, "y") def _make_edge_geometry(u, v, data, x=x_lookup, y=y_lookup): if "geometry" in data: return data["geometry"] # otherwise return LineString((Point((x[u], y[u])), Point((x[v], y[v])))) edge_geoms = map(_make_edge_geometry, u, v, data) gdf_edges = gpd.GeoDataFrame(data, crs=crs, geometry=list(edge_geoms)) else: gdf_edges = gpd.GeoDataFrame(data) if "geometry" not in gdf_edges.columns: # if no edges have a geometry attribute, create null column gdf_edges = gdf_edges.set_geometry([None] * len(gdf_edges)) gdf_edges = gdf_edges.set_crs(crs) # add u, v, key attributes as index gdf_edges["u"] = u gdf_edges["v"] = v gdf_edges["key"] = k gdf_edges = gdf_edges.set_index(["u", "v", "key"]) utils.log("Created edges GeoDataFrame from graph") if nodes and edges: return gdf_nodes, gdf_edges if nodes: return gdf_nodes if edges: return gdf_edges # otherwise msg = "you must request nodes or edges or both" raise ValueError(msg)
(G, nodes=True, edges=True, node_geometry=True, fill_edge_geometry=True)
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52,239
osmnx.routing
k_shortest_paths
Solve `k` shortest paths from an origin node to a destination node. Uses Yen's algorithm. See also `shortest_path` to solve just the one shortest path. Parameters ---------- G : networkx.MultiDiGraph input graph orig : int origin node ID dest : int destination node ID k : int number of shortest paths to solve weight : string edge attribute to minimize when solving shortest paths. default is edge length in meters. Yields ------ path : list a generator of `k` shortest paths ordered by total weight. each path is a list of node IDs.
def k_shortest_paths(G, orig, dest, k, weight="length"): """ Solve `k` shortest paths from an origin node to a destination node. Uses Yen's algorithm. See also `shortest_path` to solve just the one shortest path. Parameters ---------- G : networkx.MultiDiGraph input graph orig : int origin node ID dest : int destination node ID k : int number of shortest paths to solve weight : string edge attribute to minimize when solving shortest paths. default is edge length in meters. Yields ------ path : list a generator of `k` shortest paths ordered by total weight. each path is a list of node IDs. """ _verify_edge_attribute(G, weight) paths_gen = nx.shortest_simple_paths(convert.to_digraph(G, weight), orig, dest, weight) yield from itertools.islice(paths_gen, 0, k)
(G, orig, dest, k, weight='length')
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52,240
osmnx.io
load_graphml
Load an OSMnx-saved GraphML file from disk or GraphML string. This function converts node, edge, and graph-level attributes (serialized as strings) to their appropriate data types. These can be customized as needed by passing in dtypes arguments providing types or custom converter functions. For example, if you want to convert some attribute's values to `bool`, consider using the built-in `ox.io._convert_bool_string` function to properly handle "True"/"False" string literals as True/False booleans: `ox.load_graphml(fp, node_dtypes={my_attr: ox.io._convert_bool_string})`. If you manually configured the `all_oneway=True` setting, you may need to manually specify here that edge `oneway` attributes should be type `str`. Note that you must pass one and only one of `filepath` or `graphml_str`. If passing `graphml_str`, you may need to decode the bytes read from your file before converting to string to pass to this function. Parameters ---------- filepath : string or pathlib.Path path to the GraphML file graphml_str : string a valid and decoded string representation of a GraphML file's contents node_dtypes : dict dict of node attribute names:types to convert values' data types. the type can be a python type or a custom string converter function. edge_dtypes : dict dict of edge attribute names:types to convert values' data types. the type can be a python type or a custom string converter function. graph_dtypes : dict dict of graph-level attribute names:types to convert values' data types. the type can be a python type or a custom string converter function. Returns ------- G : networkx.MultiDiGraph
def load_graphml( filepath=None, graphml_str=None, node_dtypes=None, edge_dtypes=None, graph_dtypes=None ): """ Load an OSMnx-saved GraphML file from disk or GraphML string. This function converts node, edge, and graph-level attributes (serialized as strings) to their appropriate data types. These can be customized as needed by passing in dtypes arguments providing types or custom converter functions. For example, if you want to convert some attribute's values to `bool`, consider using the built-in `ox.io._convert_bool_string` function to properly handle "True"/"False" string literals as True/False booleans: `ox.load_graphml(fp, node_dtypes={my_attr: ox.io._convert_bool_string})`. If you manually configured the `all_oneway=True` setting, you may need to manually specify here that edge `oneway` attributes should be type `str`. Note that you must pass one and only one of `filepath` or `graphml_str`. If passing `graphml_str`, you may need to decode the bytes read from your file before converting to string to pass to this function. Parameters ---------- filepath : string or pathlib.Path path to the GraphML file graphml_str : string a valid and decoded string representation of a GraphML file's contents node_dtypes : dict dict of node attribute names:types to convert values' data types. the type can be a python type or a custom string converter function. edge_dtypes : dict dict of edge attribute names:types to convert values' data types. the type can be a python type or a custom string converter function. graph_dtypes : dict dict of graph-level attribute names:types to convert values' data types. the type can be a python type or a custom string converter function. Returns ------- G : networkx.MultiDiGraph """ if (filepath is None and graphml_str is None) or ( filepath is not None and graphml_str is not None ): # pragma: no cover msg = "You must pass one and only one of `filepath` or `graphml_str`." raise ValueError(msg) # specify default graph/node/edge attribute values' data types default_graph_dtypes = {"simplified": _convert_bool_string} default_node_dtypes = { "elevation": float, "elevation_res": float, "lat": float, "lon": float, "osmid": int, "street_count": int, "x": float, "y": float, } default_edge_dtypes = { "bearing": float, "grade": float, "grade_abs": float, "length": float, "oneway": _convert_bool_string, "osmid": int, "reversed": _convert_bool_string, "speed_kph": float, "travel_time": float, } # override default graph/node/edge attr types with user-passed types, if any if graph_dtypes is not None: default_graph_dtypes.update(graph_dtypes) if node_dtypes is not None: default_node_dtypes.update(node_dtypes) if edge_dtypes is not None: default_edge_dtypes.update(edge_dtypes) if filepath is not None: # read the graphml file from disk source = filepath G = nx.read_graphml( Path(filepath), node_type=default_node_dtypes["osmid"], force_multigraph=True ) else: # parse the graphml string source = "string" G = nx.parse_graphml( graphml_str, node_type=default_node_dtypes["osmid"], force_multigraph=True ) # convert graph/node/edge attribute data types utils.log("Converting node, edge, and graph-level attribute data types") G = _convert_graph_attr_types(G, default_graph_dtypes) G = _convert_node_attr_types(G, default_node_dtypes) G = _convert_edge_attr_types(G, default_edge_dtypes) utils.log(f"Loaded graph with {len(G)} nodes and {len(G.edges)} edges from {source!r}") return G
(filepath=None, graphml_str=None, node_dtypes=None, edge_dtypes=None, graph_dtypes=None)
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52,241
osmnx.utils
log
Write a message to the logger. This logs to file and/or prints to the console (terminal), depending on the current configuration of settings.log_file and settings.log_console. Parameters ---------- message : string the message to log level : int one of Python's logger.level constants name : string name of the logger filename : string name of the log file, without file extension Returns ------- None
def log(message, level=None, name=None, filename=None): """ Write a message to the logger. This logs to file and/or prints to the console (terminal), depending on the current configuration of settings.log_file and settings.log_console. Parameters ---------- message : string the message to log level : int one of Python's logger.level constants name : string name of the logger filename : string name of the log file, without file extension Returns ------- None """ if level is None: level = settings.log_level if name is None: name = settings.log_name if filename is None: filename = settings.log_filename # if logging to file is turned on if settings.log_file: # get the current logger (or create a new one, if none), then log # message at requested level logger = _get_logger(level=level, name=name, filename=filename) if level == lg.DEBUG: logger.debug(message) elif level == lg.INFO: logger.info(message) elif level == lg.WARNING: logger.warning(message) elif level == lg.ERROR: logger.error(message) # if logging to console (terminal window) is turned on if settings.log_console: # prepend timestamp then convert to ASCII for Windows command prompts message = f"{ts()} {message}" message = ud.normalize("NFKD", message).encode("ascii", errors="replace").decode() try: # print explicitly to terminal in case Jupyter has captured stdout if getattr(sys.stdout, "_original_stdstream_copy", None) is not None: # redirect the Jupyter-captured pipe back to original os.dup2(sys.stdout._original_stdstream_copy, sys.__stdout__.fileno()) sys.stdout._original_stdstream_copy = None with redirect_stdout(sys.__stdout__): print(message, file=sys.__stdout__, flush=True) except OSError: # handle pytest on Windows raising OSError from sys.__stdout__ print(message, flush=True) # noqa: T201
(message, level=None, name=None, filename=None)
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52,242
osmnx.distance
nearest_edges
Find the nearest edge to a point or to each of several points. If `X` and `Y` are single coordinate values, this will return the nearest edge to that point. If `X` and `Y` are lists of coordinate values, this will return the nearest edge to each point. This function uses an R-tree spatial index and minimizes the euclidean distance from each point to the possible matches. For accurate results, use a projected graph and points. Parameters ---------- G : networkx.MultiDiGraph graph in which to find nearest edges X : float or list points' x (longitude) coordinates, in same CRS/units as graph and containing no nulls Y : float or list points' y (latitude) coordinates, in same CRS/units as graph and containing no nulls interpolate : float deprecated, do not use return_dist : bool optionally also return distance between points and nearest edges Returns ------- ne or (ne, dist) : tuple or list nearest edges as (u, v, key) or optionally a tuple where `dist` contains distances between the points and their nearest edges
def nearest_edges(G, X, Y, interpolate=None, return_dist=False): """ Find the nearest edge to a point or to each of several points. If `X` and `Y` are single coordinate values, this will return the nearest edge to that point. If `X` and `Y` are lists of coordinate values, this will return the nearest edge to each point. This function uses an R-tree spatial index and minimizes the euclidean distance from each point to the possible matches. For accurate results, use a projected graph and points. Parameters ---------- G : networkx.MultiDiGraph graph in which to find nearest edges X : float or list points' x (longitude) coordinates, in same CRS/units as graph and containing no nulls Y : float or list points' y (latitude) coordinates, in same CRS/units as graph and containing no nulls interpolate : float deprecated, do not use return_dist : bool optionally also return distance between points and nearest edges Returns ------- ne or (ne, dist) : tuple or list nearest edges as (u, v, key) or optionally a tuple where `dist` contains distances between the points and their nearest edges """ is_scalar = False if not (hasattr(X, "__iter__") and hasattr(Y, "__iter__")): # make coordinates arrays if user passed non-iterable values is_scalar = True X = np.array([X]) Y = np.array([Y]) if np.isnan(X).any() or np.isnan(Y).any(): # pragma: no cover msg = "`X` and `Y` cannot contain nulls" raise ValueError(msg) geoms = convert.graph_to_gdfs(G, nodes=False)["geometry"] # if no interpolation distance was provided if interpolate is None: # build an r-tree spatial index by position for subsequent iloc rtree = STRtree(geoms) # use the r-tree to find each point's nearest neighbor and distance points = [Point(xy) for xy in zip(X, Y)] pos, dist = rtree.query_nearest(points, all_matches=False, return_distance=True) # if user passed X/Y lists, the 2nd subarray contains geom indices if len(pos.shape) > 1: pos = pos[1] ne = geoms.iloc[pos].index # otherwise, if interpolation distance was provided else: warn( "The `interpolate` parameter has been deprecated and will be " "removed in the v2.0.0 release. " "See the OSMnx v2 migration guide: https://github.com/gboeing/osmnx/issues/1123", FutureWarning, stacklevel=2, ) # interpolate points along edges to index with k-d tree or ball tree uvk_xy = [] for uvk, geom in zip(geoms.index, geoms.to_numpy()): uvk_xy.extend((uvk, xy) for xy in utils_geo.interpolate_points(geom, interpolate)) labels, xy = zip(*uvk_xy) vertices = pd.DataFrame(xy, index=labels, columns=["x", "y"]) if projection.is_projected(G.graph["crs"]): # if projected, use k-d tree for euclidean nearest-neighbor search if cKDTree is None: # pragma: no cover msg = "scipy must be installed to search a projected graph" raise ImportError(msg) dist, pos = cKDTree(vertices).query(np.array([X, Y]).T, k=1) ne = vertices.index[pos] else: # if unprojected, use ball tree for haversine nearest-neighbor search if BallTree is None: # pragma: no cover msg = "scikit-learn must be installed to search an unprojected graph" raise ImportError(msg) # haversine requires lat, lon coords in radians vertices_rad = np.deg2rad(vertices[["y", "x"]]) points_rad = np.deg2rad(np.array([Y, X]).T) dist, pos = BallTree(vertices_rad, metric="haversine").query(points_rad, k=1) dist = dist[:, 0] * EARTH_RADIUS_M # convert radians -> meters ne = vertices.index[pos[:, 0]] # convert results to correct types for return ne = list(ne) dist = list(dist) if is_scalar: ne = ne[0] dist = dist[0] if return_dist: return ne, dist # otherwise return ne
(G, X, Y, interpolate=None, return_dist=False)
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52,243
osmnx.distance
nearest_nodes
Find the nearest node to a point or to each of several points. If `X` and `Y` are single coordinate values, this will return the nearest node to that point. If `X` and `Y` are lists of coordinate values, this will return the nearest node to each point. If the graph is projected, this uses a k-d tree for euclidean nearest neighbor search, which requires that scipy is installed as an optional dependency. If it is unprojected, this uses a ball tree for haversine nearest neighbor search, which requires that scikit-learn is installed as an optional dependency. Parameters ---------- G : networkx.MultiDiGraph graph in which to find nearest nodes X : float or list points' x (longitude) coordinates, in same CRS/units as graph and containing no nulls Y : float or list points' y (latitude) coordinates, in same CRS/units as graph and containing no nulls return_dist : bool optionally also return distance between points and nearest nodes Returns ------- nn or (nn, dist) : int/list or tuple nearest node IDs or optionally a tuple where `dist` contains distances between the points and their nearest nodes
def nearest_nodes(G, X, Y, return_dist=False): """ Find the nearest node to a point or to each of several points. If `X` and `Y` are single coordinate values, this will return the nearest node to that point. If `X` and `Y` are lists of coordinate values, this will return the nearest node to each point. If the graph is projected, this uses a k-d tree for euclidean nearest neighbor search, which requires that scipy is installed as an optional dependency. If it is unprojected, this uses a ball tree for haversine nearest neighbor search, which requires that scikit-learn is installed as an optional dependency. Parameters ---------- G : networkx.MultiDiGraph graph in which to find nearest nodes X : float or list points' x (longitude) coordinates, in same CRS/units as graph and containing no nulls Y : float or list points' y (latitude) coordinates, in same CRS/units as graph and containing no nulls return_dist : bool optionally also return distance between points and nearest nodes Returns ------- nn or (nn, dist) : int/list or tuple nearest node IDs or optionally a tuple where `dist` contains distances between the points and their nearest nodes """ is_scalar = False if not (hasattr(X, "__iter__") and hasattr(Y, "__iter__")): # make coordinates arrays if user passed non-iterable values is_scalar = True X = np.array([X]) Y = np.array([Y]) if np.isnan(X).any() or np.isnan(Y).any(): # pragma: no cover msg = "`X` and `Y` cannot contain nulls" raise ValueError(msg) nodes = convert.graph_to_gdfs(G, edges=False, node_geometry=False)[["x", "y"]] if projection.is_projected(G.graph["crs"]): # if projected, use k-d tree for euclidean nearest-neighbor search if cKDTree is None: # pragma: no cover msg = "scipy must be installed to search a projected graph" raise ImportError(msg) dist, pos = cKDTree(nodes).query(np.array([X, Y]).T, k=1) nn = nodes.index[pos] else: # if unprojected, use ball tree for haversine nearest-neighbor search if BallTree is None: # pragma: no cover msg = "scikit-learn must be installed to search an unprojected graph" raise ImportError(msg) # haversine requires lat, lon coords in radians nodes_rad = np.deg2rad(nodes[["y", "x"]]) points_rad = np.deg2rad(np.array([Y, X]).T) dist, pos = BallTree(nodes_rad, metric="haversine").query(points_rad, k=1) dist = dist[:, 0] * EARTH_RADIUS_M # convert radians -> meters nn = nodes.index[pos[:, 0]] # convert results to correct types for return nn = nn.tolist() dist = dist.tolist() if is_scalar: nn = nn[0] dist = dist[0] if return_dist: return nn, dist # otherwise return nn
(G, X, Y, return_dist=False)
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0.045751672238111496, 0.0007611697074025869, 0.11971291899681091 ]
52,244
osmnx.bearing
orientation_entropy
Calculate undirected graph's orientation entropy. Orientation entropy is the entropy of its edges' bidirectional bearings across evenly spaced bins. Ignores self-loop edges as their bearings are undefined. For more info see: Boeing, G. 2019. "Urban Spatial Order: Street Network Orientation, Configuration, and Entropy." Applied Network Science, 4 (1), 67. https://doi.org/10.1007/s41109-019-0189-1 Parameters ---------- Gu : networkx.MultiGraph undirected, unprojected graph with `bearing` attributes on each edge num_bins : int number of bins; for example, if `num_bins=36` is provided, then each bin will represent 10 degrees around the compass min_length : float ignore edges with `length` attributes less than `min_length`; useful to ignore the noise of many very short edges weight : string if not None, weight edges' bearings by this (non-null) edge attribute. for example, if "length" is provided, this will return 1 bearing observation per meter per street, which could result in a very large `bearings` array. Returns ------- entropy : float the graph's orientation entropy
def orientation_entropy(Gu, num_bins=36, min_length=0, weight=None): """ Calculate undirected graph's orientation entropy. Orientation entropy is the entropy of its edges' bidirectional bearings across evenly spaced bins. Ignores self-loop edges as their bearings are undefined. For more info see: Boeing, G. 2019. "Urban Spatial Order: Street Network Orientation, Configuration, and Entropy." Applied Network Science, 4 (1), 67. https://doi.org/10.1007/s41109-019-0189-1 Parameters ---------- Gu : networkx.MultiGraph undirected, unprojected graph with `bearing` attributes on each edge num_bins : int number of bins; for example, if `num_bins=36` is provided, then each bin will represent 10 degrees around the compass min_length : float ignore edges with `length` attributes less than `min_length`; useful to ignore the noise of many very short edges weight : string if not None, weight edges' bearings by this (non-null) edge attribute. for example, if "length" is provided, this will return 1 bearing observation per meter per street, which could result in a very large `bearings` array. Returns ------- entropy : float the graph's orientation entropy """ # check if we were able to import scipy if scipy is None: # pragma: no cover msg = "scipy must be installed to calculate entropy" raise ImportError(msg) bin_counts, _ = _bearings_distribution(Gu, num_bins, min_length, weight) return scipy.stats.entropy(bin_counts)
(Gu, num_bins=36, min_length=0, weight=None)
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52,247
osmnx.plot
plot_figure_ground
Plot a figure-ground diagram of a street network. Parameters ---------- G : networkx.MultiDiGraph input graph, must be unprojected address : string deprecated, do not use point : tuple deprecated, do not use dist : numeric how many meters to extend north, south, east, west from center point network_type : string deprecated, do not use street_widths : dict dict keys are street types and values are widths to plot in pixels default_width : numeric fallback width in pixels for any street type not in street_widths color : string color of the streets edge_color : string deprecated, do not use smooth_joints : bool deprecated, do not use pg_kwargs keyword arguments to pass to plot_graph Returns ------- fig, ax : tuple matplotlib figure, axis
def plot_figure_ground( G=None, address=None, point=None, dist=805, network_type="drive_service", street_widths=None, default_width=4, color="w", edge_color=None, smooth_joints=None, **pg_kwargs, ): """ Plot a figure-ground diagram of a street network. Parameters ---------- G : networkx.MultiDiGraph input graph, must be unprojected address : string deprecated, do not use point : tuple deprecated, do not use dist : numeric how many meters to extend north, south, east, west from center point network_type : string deprecated, do not use street_widths : dict dict keys are street types and values are widths to plot in pixels default_width : numeric fallback width in pixels for any street type not in street_widths color : string color of the streets edge_color : string deprecated, do not use smooth_joints : bool deprecated, do not use pg_kwargs keyword arguments to pass to plot_graph Returns ------- fig, ax : tuple matplotlib figure, axis """ _verify_mpl() if edge_color is None: edge_color = color else: msg = ( "The `edge_color` parameter is deprecated and will be removed in the " "v2.0.0 release. Use `color` instead. " "See the OSMnx v2 migration guide: https://github.com/gboeing/osmnx/issues/1123" ) warn(msg, FutureWarning, stacklevel=2) if smooth_joints is None: smooth_joints = True else: msg = ( "The `smooth_joints` parameter is deprecated and will be removed in the " "v2.0.0 release. In the future this function will behave as though True. " "See the OSMnx v2 migration guide: https://github.com/gboeing/osmnx/issues/1123" ) warn(msg, FutureWarning, stacklevel=2) # if user did not pass in custom street widths, create a dict of defaults if street_widths is None: street_widths = { "footway": 1.5, "steps": 1.5, "pedestrian": 1.5, "service": 1.5, "path": 1.5, "track": 1.5, "motorway": 6, } multiplier = 1.2 dep_msg = ( "The `address`, `point`, and `network_type` parameters are deprecated " "and will be removed in the v2.0.0 release. Pass `G` instead. " "See the OSMnx v2 migration guide: https://github.com/gboeing/osmnx/issues/1123" ) # if G was passed in, plot it centered on its node centroid if G is not None: gdf_nodes = convert.graph_to_gdfs(G, edges=False, node_geometry=True) lonlat_point = gdf_nodes.unary_union.centroid.coords[0] point = tuple(reversed(lonlat_point)) # otherwise get network by address or point (whichever was passed) using a # dist multiplier to ensure we get more than enough network. simplify in # non-strict mode to not combine multiple street types into single edge elif address is not None: warn(dep_msg, FutureWarning, stacklevel=2) G, point = graph.graph_from_address( address, dist=dist * multiplier, dist_type="bbox", network_type=network_type, simplify=False, truncate_by_edge=True, return_coords=True, ) G = simplification.simplify_graph(G, edge_attrs_differ=["osmid"]) elif point is not None: warn(dep_msg, FutureWarning, stacklevel=2) G = graph.graph_from_point( point, dist=dist * multiplier, dist_type="bbox", network_type=network_type, simplify=False, truncate_by_edge=True, ) G = simplification.simplify_graph(G, edge_attrs_differ=["osmid"]) else: # pragma: no cover msg = "You must pass an address or lat-lon point or graph." raise ValueError(msg) # we need an undirected graph to find every edge incident on a node Gu = convert.to_undirected(G) # for each edge, get a linewidth according to street type edge_linewidths = [] for _, _, d in Gu.edges(keys=False, data=True): street_type = d["highway"][0] if isinstance(d["highway"], list) else d["highway"] if street_type in street_widths: edge_linewidths.append(street_widths[street_type]) else: edge_linewidths.append(default_width) if smooth_joints: # for each node, get a nodesize according to the narrowest incident edge node_widths = {} for node in Gu.nodes: # first, identify all the highway types of this node's incident edges ie_data = [Gu.get_edge_data(node, nbr) for nbr in Gu.neighbors(node)] edge_types = [d[min(d)]["highway"] for d in ie_data] if not edge_types: # if node has no incident edges, make size zero node_widths[node] = 0 else: # flatten the list of edge types et_flat = [] for et in edge_types: if isinstance(et, list): et_flat.extend(et) else: et_flat.append(et) # lookup corresponding width for each edge type in flat list edge_widths = [street_widths.get(et, default_width) for et in et_flat] # node diameter should equal largest edge width to make joints # perfectly smooth. alternatively use min(?) to prevent # anything larger from extending past smallest street's line. # circle marker sizes are in area, so use diameter squared. circle_diameter = max(edge_widths) circle_area = circle_diameter**2 node_widths[node] = circle_area # assign the node size to each node in the graph node_sizes = [node_widths[node] for node in Gu.nodes] else: node_sizes = 0 # define the view extents of the plotting figure bbox = utils_geo.bbox_from_point(point, dist, project_utm=False) # plot the figure overrides = {"bbox", "node_size", "node_color", "edge_linewidth"} kwargs = {k: v for k, v in pg_kwargs.items() if k not in overrides} fig, ax = plot_graph( G=Gu, bbox=bbox, node_size=node_sizes, node_color=edge_color, edge_color=edge_color, edge_linewidth=edge_linewidths, **kwargs, ) return fig, ax
(G=None, address=None, point=None, dist=805, network_type='drive_service', street_widths=None, default_width=4, color='w', edge_color=None, smooth_joints=None, **pg_kwargs)
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52,248
osmnx.plot
plot_footprints
Visualize a GeoDataFrame of geospatial features' footprints. Parameters ---------- gdf : geopandas.GeoDataFrame GeoDataFrame of footprints (shapely Polygons and MultiPolygons) ax : axis if not None, plot on this preexisting axis figsize : tuple if ax is None, create new figure with size (width, height) color : string color of the footprints edge_color : string color of the edge of the footprints edge_linewidth : float width of the edge of the footprints alpha : float opacity of the footprints bgcolor : string background color of the plot bbox : tuple bounding box as (north, south, east, west). if None, will calculate from the spatial extents of the geometries in gdf save : bool if True, save the figure to disk at filepath show : bool if True, call pyplot.show() to show the figure close : bool if True, call pyplot.close() to close the figure filepath : string if save is True, the path to the file. file format determined from extension. if None, use settings.imgs_folder/image.png dpi : int if save is True, the resolution of saved file Returns ------- fig, ax : tuple matplotlib figure, axis
def plot_footprints( gdf, ax=None, figsize=(8, 8), color="orange", edge_color="none", edge_linewidth=0, alpha=None, bgcolor="#111111", bbox=None, save=False, show=True, close=False, filepath=None, dpi=600, ): """ Visualize a GeoDataFrame of geospatial features' footprints. Parameters ---------- gdf : geopandas.GeoDataFrame GeoDataFrame of footprints (shapely Polygons and MultiPolygons) ax : axis if not None, plot on this preexisting axis figsize : tuple if ax is None, create new figure with size (width, height) color : string color of the footprints edge_color : string color of the edge of the footprints edge_linewidth : float width of the edge of the footprints alpha : float opacity of the footprints bgcolor : string background color of the plot bbox : tuple bounding box as (north, south, east, west). if None, will calculate from the spatial extents of the geometries in gdf save : bool if True, save the figure to disk at filepath show : bool if True, call pyplot.show() to show the figure close : bool if True, call pyplot.close() to close the figure filepath : string if save is True, the path to the file. file format determined from extension. if None, use settings.imgs_folder/image.png dpi : int if save is True, the resolution of saved file Returns ------- fig, ax : tuple matplotlib figure, axis """ _verify_mpl() if ax is None: fig, ax = plt.subplots(figsize=figsize, facecolor=bgcolor, frameon=False) ax.set_facecolor(bgcolor) else: fig = ax.figure # retain only Polygons and MultiPolygons, then plot gdf = gdf[gdf["geometry"].type.isin({"Polygon", "MultiPolygon"})] ax = gdf.plot( ax=ax, facecolor=color, edgecolor=edge_color, linewidth=edge_linewidth, alpha=alpha ) # determine figure extents if bbox is None: west, south, east, north = gdf.total_bounds else: north, south, east, west = bbox # configure axis appearance, save/show figure as specified, and return ax = _config_ax(ax, gdf.crs, (north, south, east, west), 0) fig, ax = _save_and_show(fig, ax, save, show, close, filepath, dpi) return fig, ax
(gdf, ax=None, figsize=(8, 8), color='orange', edge_color='none', edge_linewidth=0, alpha=None, bgcolor='#111111', bbox=None, save=False, show=True, close=False, filepath=None, dpi=600)
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osmnx.plot
plot_graph
Visualize a graph. Parameters ---------- G : networkx.MultiDiGraph input graph ax : matplotlib axis if not None, plot on this preexisting axis figsize : tuple if ax is None, create new figure with size (width, height) bgcolor : string background color of plot node_color : string or list color(s) of the nodes node_size : int size of the nodes: if 0, then skip plotting the nodes node_alpha : float opacity of the nodes, note: if you passed RGBA values to node_color, set node_alpha=None to use the alpha channel in node_color node_edgecolor : string color of the nodes' markers' borders node_zorder : int zorder to plot nodes: edges are always 1, so set node_zorder=0 to plot nodes below edges edge_color : string or list color(s) of the edges' lines edge_linewidth : float width of the edges' lines: if 0, then skip plotting the edges edge_alpha : float opacity of the edges, note: if you passed RGBA values to edge_color, set edge_alpha=None to use the alpha channel in edge_color show : bool if True, call pyplot.show() to show the figure close : bool if True, call pyplot.close() to close the figure save : bool if True, save the figure to disk at filepath filepath : string if save is True, the path to the file. file format determined from extension. if None, use settings.imgs_folder/image.png dpi : int if save is True, the resolution of saved file bbox : tuple bounding box as (north, south, east, west). if None, will calculate from spatial extents of plotted geometries. Returns ------- fig, ax : tuple matplotlib figure, axis
def plot_graph( G, ax=None, figsize=(8, 8), bgcolor="#111111", node_color="w", node_size=15, node_alpha=None, node_edgecolor="none", node_zorder=1, edge_color="#999999", edge_linewidth=1, edge_alpha=None, show=True, close=False, save=False, filepath=None, dpi=300, bbox=None, ): """ Visualize a graph. Parameters ---------- G : networkx.MultiDiGraph input graph ax : matplotlib axis if not None, plot on this preexisting axis figsize : tuple if ax is None, create new figure with size (width, height) bgcolor : string background color of plot node_color : string or list color(s) of the nodes node_size : int size of the nodes: if 0, then skip plotting the nodes node_alpha : float opacity of the nodes, note: if you passed RGBA values to node_color, set node_alpha=None to use the alpha channel in node_color node_edgecolor : string color of the nodes' markers' borders node_zorder : int zorder to plot nodes: edges are always 1, so set node_zorder=0 to plot nodes below edges edge_color : string or list color(s) of the edges' lines edge_linewidth : float width of the edges' lines: if 0, then skip plotting the edges edge_alpha : float opacity of the edges, note: if you passed RGBA values to edge_color, set edge_alpha=None to use the alpha channel in edge_color show : bool if True, call pyplot.show() to show the figure close : bool if True, call pyplot.close() to close the figure save : bool if True, save the figure to disk at filepath filepath : string if save is True, the path to the file. file format determined from extension. if None, use settings.imgs_folder/image.png dpi : int if save is True, the resolution of saved file bbox : tuple bounding box as (north, south, east, west). if None, will calculate from spatial extents of plotted geometries. Returns ------- fig, ax : tuple matplotlib figure, axis """ _verify_mpl() max_node_size = max(node_size) if hasattr(node_size, "__iter__") else node_size max_edge_lw = max(edge_linewidth) if hasattr(edge_linewidth, "__iter__") else edge_linewidth if max_node_size <= 0 and max_edge_lw <= 0: # pragma: no cover msg = "Either node_size or edge_linewidth must be > 0 to plot something." raise ValueError(msg) # create fig, ax as needed utils.log("Begin plotting the graph...") if ax is None: fig, ax = plt.subplots(figsize=figsize, facecolor=bgcolor, frameon=False) ax.set_facecolor(bgcolor) else: fig = ax.figure if max_edge_lw > 0: # plot the edges' geometries gdf_edges = convert.graph_to_gdfs(G, nodes=False)["geometry"] ax = gdf_edges.plot(ax=ax, color=edge_color, lw=edge_linewidth, alpha=edge_alpha, zorder=1) if max_node_size > 0: # scatter plot the nodes' x/y coordinates gdf_nodes = convert.graph_to_gdfs(G, edges=False, node_geometry=False)[["x", "y"]] ax.scatter( x=gdf_nodes["x"], y=gdf_nodes["y"], s=node_size, c=node_color, alpha=node_alpha, edgecolor=node_edgecolor, zorder=node_zorder, ) # get spatial extents from bbox parameter or the edges' geometries padding = 0 if bbox is None: try: west, south, east, north = gdf_edges.total_bounds except NameError: west, south = gdf_nodes.min() east, north = gdf_nodes.max() bbox = north, south, east, west padding = 0.02 # pad 2% to not cut off peripheral nodes' circles # configure axis appearance, save/show figure as specified, and return ax = _config_ax(ax, G.graph["crs"], bbox, padding) fig, ax = _save_and_show(fig, ax, save, show, close, filepath, dpi) utils.log("Finished plotting the graph") return fig, ax
(G, ax=None, figsize=(8, 8), bgcolor='#111111', node_color='w', node_size=15, node_alpha=None, node_edgecolor='none', node_zorder=1, edge_color='#999999', edge_linewidth=1, edge_alpha=None, show=True, close=False, save=False, filepath=None, dpi=300, bbox=None)
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52,250
osmnx.folium
plot_graph_folium
Do not use: deprecated. You can generate and explore interactive web maps of graph nodes, edges, and/or routes automatically using GeoPandas.GeoDataFrame.explore instead, for example like: `ox.graph_to_gdfs(G, nodes=False).explore()`. See the OSMnx examples gallery for complete details and demonstrations. Parameters ---------- G : networkx.MultiDiGraph deprecated graph_map : folium.folium.Map deprecated popup_attribute : string deprecated tiles : string deprecated zoom : int deprecated fit_bounds : bool deprecated kwargs deprecated Returns ------- folium.folium.Map
def plot_graph_folium( G, graph_map=None, popup_attribute=None, tiles="cartodbpositron", zoom=1, fit_bounds=True, **kwargs, ): """ Do not use: deprecated. You can generate and explore interactive web maps of graph nodes, edges, and/or routes automatically using GeoPandas.GeoDataFrame.explore instead, for example like: `ox.graph_to_gdfs(G, nodes=False).explore()`. See the OSMnx examples gallery for complete details and demonstrations. Parameters ---------- G : networkx.MultiDiGraph deprecated graph_map : folium.folium.Map deprecated popup_attribute : string deprecated tiles : string deprecated zoom : int deprecated fit_bounds : bool deprecated kwargs deprecated Returns ------- folium.folium.Map """ warn( "The `folium` module has been deprecated and will be removed in the v2.0.0 release. " "You can generate and explore interactive web maps of graph nodes, edges, " "and/or routes automatically using GeoPandas.GeoDataFrame.explore instead, " "for example like: `ox.graph_to_gdfs(G, nodes=False).explore()`. See the " "OSMnx examples gallery for complete details and demonstrations.", FutureWarning, stacklevel=2, ) # create gdf of all graph edges gdf_edges = convert.graph_to_gdfs(G, nodes=False) return _plot_folium(gdf_edges, graph_map, popup_attribute, tiles, zoom, fit_bounds, **kwargs)
(G, graph_map=None, popup_attribute=None, tiles='cartodbpositron', zoom=1, fit_bounds=True, **kwargs)
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52,251
osmnx.plot
plot_graph_route
Visualize a route along a graph. Parameters ---------- G : networkx.MultiDiGraph input graph route : list route as a list of node IDs route_color : string color of the route route_linewidth : int width of the route line route_alpha : float opacity of the route line orig_dest_size : int size of the origin and destination nodes ax : matplotlib axis if not None, plot route on this preexisting axis instead of creating a new fig, ax and drawing the underlying graph pg_kwargs keyword arguments to pass to plot_graph Returns ------- fig, ax : tuple matplotlib figure, axis
def plot_graph_route( G, route, route_color="r", route_linewidth=4, route_alpha=0.5, orig_dest_size=100, ax=None, **pg_kwargs, ): """ Visualize a route along a graph. Parameters ---------- G : networkx.MultiDiGraph input graph route : list route as a list of node IDs route_color : string color of the route route_linewidth : int width of the route line route_alpha : float opacity of the route line orig_dest_size : int size of the origin and destination nodes ax : matplotlib axis if not None, plot route on this preexisting axis instead of creating a new fig, ax and drawing the underlying graph pg_kwargs keyword arguments to pass to plot_graph Returns ------- fig, ax : tuple matplotlib figure, axis """ _verify_mpl() if ax is None: # plot the graph but not the route, and override any user show/close # args for now: we'll do that later overrides = {"show", "save", "close"} kwargs = {k: v for k, v in pg_kwargs.items() if k not in overrides} fig, ax = plot_graph(G, show=False, save=False, close=False, **kwargs) else: fig = ax.figure # scatterplot origin and destination points (first/last nodes in route) x = (G.nodes[route[0]]["x"], G.nodes[route[-1]]["x"]) y = (G.nodes[route[0]]["y"], G.nodes[route[-1]]["y"]) ax.scatter(x, y, s=orig_dest_size, c=route_color, alpha=route_alpha, edgecolor="none") # assemble the route edge geometries' x and y coords then plot the line x = [] y = [] for u, v in zip(route[:-1], route[1:]): # if there are parallel edges, select the shortest in length data = min(G.get_edge_data(u, v).values(), key=lambda d: d["length"]) if "geometry" in data: # if geometry attribute exists, add all its coords to list xs, ys = data["geometry"].xy x.extend(xs) y.extend(ys) else: # otherwise, the edge is a straight line from node to node x.extend((G.nodes[u]["x"], G.nodes[v]["x"])) y.extend((G.nodes[u]["y"], G.nodes[v]["y"])) ax.plot(x, y, c=route_color, lw=route_linewidth, alpha=route_alpha) # save and show the figure as specified, passing relevant kwargs sas_kwargs = {"save", "show", "close", "filepath", "file_format", "dpi"} kwargs = {k: v for k, v in pg_kwargs.items() if k in sas_kwargs} fig, ax = _save_and_show(fig, ax, **kwargs) return fig, ax
(G, route, route_color='r', route_linewidth=4, route_alpha=0.5, orig_dest_size=100, ax=None, **pg_kwargs)
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52,252
osmnx.plot
plot_graph_routes
Visualize several routes along a graph. Parameters ---------- G : networkx.MultiDiGraph input graph routes : list routes as a list of lists of node IDs route_colors : string or list if string, 1 color for all routes. if list, the colors for each route. route_linewidths : int or list if int, 1 linewidth for all routes. if list, the linewidth for each route. pgr_kwargs keyword arguments to pass to plot_graph_route Returns ------- fig, ax : tuple matplotlib figure, axis
def plot_graph_routes(G, routes, route_colors="r", route_linewidths=4, **pgr_kwargs): """ Visualize several routes along a graph. Parameters ---------- G : networkx.MultiDiGraph input graph routes : list routes as a list of lists of node IDs route_colors : string or list if string, 1 color for all routes. if list, the colors for each route. route_linewidths : int or list if int, 1 linewidth for all routes. if list, the linewidth for each route. pgr_kwargs keyword arguments to pass to plot_graph_route Returns ------- fig, ax : tuple matplotlib figure, axis """ _verify_mpl() # check for valid arguments if not all(isinstance(r, list) for r in routes): # pragma: no cover msg = "routes must be a list of route lists" raise ValueError(msg) if len(routes) <= 1: # pragma: no cover msg = "You must pass more than 1 route" raise ValueError(msg) if isinstance(route_colors, str): route_colors = [route_colors] * len(routes) if len(routes) != len(route_colors): # pragma: no cover msg = "route_colors list must have same length as routes" raise ValueError(msg) if isinstance(route_linewidths, int): route_linewidths = [route_linewidths] * len(routes) if len(routes) != len(route_linewidths): # pragma: no cover msg = "route_linewidths list must have same length as routes" raise ValueError(msg) # plot the graph and the first route overrides = {"route", "route_color", "route_linewidth", "show", "save", "close"} kwargs = {k: v for k, v in pgr_kwargs.items() if k not in overrides} fig, ax = plot_graph_route( G, route=routes[0], route_color=route_colors[0], route_linewidth=route_linewidths[0], show=False, save=False, close=False, **kwargs, ) # plot the subsequent routes on top of existing ax overrides.update({"ax"}) kwargs = {k: v for k, v in pgr_kwargs.items() if k not in overrides} r_rc_rlw = zip(routes[1:], route_colors[1:], route_linewidths[1:]) for route, route_color, route_linewidth in r_rc_rlw: fig, ax = plot_graph_route( G, route=route, route_color=route_color, route_linewidth=route_linewidth, show=False, save=False, close=False, ax=ax, **kwargs, ) # save and show the figure as specified, passing relevant kwargs sas_kwargs = {"save", "show", "close", "filepath", "file_format", "dpi"} kwargs = {k: v for k, v in pgr_kwargs.items() if k in sas_kwargs} fig, ax = _save_and_show(fig, ax, **kwargs) return fig, ax
(G, routes, route_colors='r', route_linewidths=4, **pgr_kwargs)
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52,253
osmnx.plot
plot_orientation
Plot a polar histogram of a spatial network's bidirectional edge bearings. Ignores self-loop edges as their bearings are undefined. For more info see: Boeing, G. 2019. "Urban Spatial Order: Street Network Orientation, Configuration, and Entropy." Applied Network Science, 4 (1), 67. https://doi.org/10.1007/s41109-019-0189-1 Parameters ---------- Gu : networkx.MultiGraph undirected, unprojected graph with `bearing` attributes on each edge num_bins : int number of bins; for example, if `num_bins=36` is provided, then each bin will represent 10 degrees around the compass min_length : float ignore edges with `length` attributes less than `min_length` weight : string if not None, weight edges' bearings by this (non-null) edge attribute ax : matplotlib.axes.PolarAxesSubplot if not None, plot on this preexisting axis; must have projection=polar figsize : tuple if ax is None, create new figure with size (width, height) area : bool if True, set bar length so area is proportional to frequency, otherwise set bar length so height is proportional to frequency color : string color of histogram bars edgecolor : string color of histogram bar edges linewidth : float width of histogram bar edges alpha : float opacity of histogram bars title : string title for plot title_y : float y position to place title title_font : dict the title's fontdict to pass to matplotlib xtick_font : dict the xtick labels' fontdict to pass to matplotlib Returns ------- fig, ax : tuple matplotlib figure, axis
def plot_orientation( Gu, num_bins=36, min_length=0, weight=None, ax=None, figsize=(5, 5), area=True, color="#003366", edgecolor="k", linewidth=0.5, alpha=0.7, title=None, title_y=1.05, title_font=None, xtick_font=None, ): """ Plot a polar histogram of a spatial network's bidirectional edge bearings. Ignores self-loop edges as their bearings are undefined. For more info see: Boeing, G. 2019. "Urban Spatial Order: Street Network Orientation, Configuration, and Entropy." Applied Network Science, 4 (1), 67. https://doi.org/10.1007/s41109-019-0189-1 Parameters ---------- Gu : networkx.MultiGraph undirected, unprojected graph with `bearing` attributes on each edge num_bins : int number of bins; for example, if `num_bins=36` is provided, then each bin will represent 10 degrees around the compass min_length : float ignore edges with `length` attributes less than `min_length` weight : string if not None, weight edges' bearings by this (non-null) edge attribute ax : matplotlib.axes.PolarAxesSubplot if not None, plot on this preexisting axis; must have projection=polar figsize : tuple if ax is None, create new figure with size (width, height) area : bool if True, set bar length so area is proportional to frequency, otherwise set bar length so height is proportional to frequency color : string color of histogram bars edgecolor : string color of histogram bar edges linewidth : float width of histogram bar edges alpha : float opacity of histogram bars title : string title for plot title_y : float y position to place title title_font : dict the title's fontdict to pass to matplotlib xtick_font : dict the xtick labels' fontdict to pass to matplotlib Returns ------- fig, ax : tuple matplotlib figure, axis """ _verify_mpl() if title_font is None: title_font = {"family": "DejaVu Sans", "size": 24, "weight": "bold"} if xtick_font is None: xtick_font = { "family": "DejaVu Sans", "size": 10, "weight": "bold", "alpha": 1.0, "zorder": 3, } # get the bearings' distribution's bin counts and edges bin_counts, bin_edges = bearing._bearings_distribution(Gu, num_bins, min_length, weight) # positions: where to center each bar. ignore the last bin edge, because # it's the same as the first (i.e., 0 degrees = 360 degrees) positions = np.radians(bin_edges[:-1]) # width: make bars fill the circumference without gaps or overlaps width = 2 * np.pi / num_bins # radius: how long to make each bar. set bar length so either the bar area # (ie, via sqrt) or the bar height is proportional to the bin's frequency bin_frequency = bin_counts / bin_counts.sum() radius = np.sqrt(bin_frequency) if area else bin_frequency # create ax (if necessary) then set N at top and go clockwise if ax is None: fig, ax = plt.subplots(figsize=figsize, subplot_kw={"projection": "polar"}) else: fig = ax.figure ax.set_theta_zero_location("N") ax.set_theta_direction("clockwise") ax.set_ylim(top=radius.max()) # configure the y-ticks and remove their labels ax.set_yticks(np.linspace(0, radius.max(), 5)) ax.set_yticklabels(labels="") # configure the x-ticks and their labels xticklabels = ["N", "", "E", "", "S", "", "W", ""] ax.set_xticks(ax.get_xticks()) ax.set_xticklabels(labels=xticklabels, fontdict=xtick_font) ax.tick_params(axis="x", which="major", pad=-2) # draw the bars ax.bar( positions, height=radius, width=width, align="center", bottom=0, zorder=2, color=color, edgecolor=edgecolor, linewidth=linewidth, alpha=alpha, ) if title: ax.set_title(title, y=title_y, fontdict=title_font) fig.tight_layout() return fig, ax
(Gu, num_bins=36, min_length=0, weight=None, ax=None, figsize=(5, 5), area=True, color='#003366', edgecolor='k', linewidth=0.5, alpha=0.7, title=None, title_y=1.05, title_font=None, xtick_font=None)
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52,254
osmnx.folium
plot_route_folium
Do not use: deprecated. You can generate and explore interactive web maps of graph nodes, edges, and/or routes automatically using GeoPandas.GeoDataFrame.explore instead, for example like: `ox.graph_to_gdfs(G, nodes=False).explore()`. See the OSMnx examples gallery for complete details and demonstrations. Parameters ---------- G : networkx.MultiDiGraph deprecated route : list deprecated route_map : folium.folium.Map deprecated popup_attribute : string deprecated tiles : string deprecated zoom : int deprecated fit_bounds : bool deprecated kwargs deprecated Returns ------- folium.folium.Map
def plot_route_folium( G, route, route_map=None, popup_attribute=None, tiles="cartodbpositron", zoom=1, fit_bounds=True, **kwargs, ): """ Do not use: deprecated. You can generate and explore interactive web maps of graph nodes, edges, and/or routes automatically using GeoPandas.GeoDataFrame.explore instead, for example like: `ox.graph_to_gdfs(G, nodes=False).explore()`. See the OSMnx examples gallery for complete details and demonstrations. Parameters ---------- G : networkx.MultiDiGraph deprecated route : list deprecated route_map : folium.folium.Map deprecated popup_attribute : string deprecated tiles : string deprecated zoom : int deprecated fit_bounds : bool deprecated kwargs deprecated Returns ------- folium.folium.Map """ warn( "The `folium` module has been deprecated and will be removed in the v2.0.0 release. " "You can generate and explore interactive web maps of graph nodes, edges, " "and/or routes automatically using GeoPandas.GeoDataFrame.explore instead, " "for example like: `ox.graph_to_gdfs(G, nodes=False).explore()`. See the " "OSMnx examples gallery for complete details and demonstrations.", FutureWarning, stacklevel=2, ) # create gdf of the route edges in order node_pairs = zip(route[:-1], route[1:]) uvk = ((u, v, min(G[u][v].items(), key=lambda k: k[1]["length"])[0]) for u, v in node_pairs) gdf_edges = convert.graph_to_gdfs(G.subgraph(route), nodes=False).loc[uvk] return _plot_folium(gdf_edges, route_map, popup_attribute, tiles, zoom, fit_bounds, **kwargs)
(G, route, route_map=None, popup_attribute=None, tiles='cartodbpositron', zoom=1, fit_bounds=True, **kwargs)
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52,255
osmnx.projection
project_gdf
Project a GeoDataFrame from its current CRS to another. If `to_latlong` is `True`, this projects the GeoDataFrame to the CRS defined by `settings.default_crs`, otherwise it projects it to the CRS defined by `to_crs`. If `to_crs` is `None`, it projects it to the CRS of an appropriate UTM zone given `gdf`'s bounds. Parameters ---------- gdf : geopandas.GeoDataFrame the GeoDataFrame to be projected to_crs : string or pyproj.CRS if None, project to an appropriate UTM zone, otherwise project to this CRS to_latlong : bool if True, project to `settings.default_crs` and ignore `to_crs` Returns ------- gdf_proj : geopandas.GeoDataFrame the projected GeoDataFrame
def project_gdf(gdf, to_crs=None, to_latlong=False): """ Project a GeoDataFrame from its current CRS to another. If `to_latlong` is `True`, this projects the GeoDataFrame to the CRS defined by `settings.default_crs`, otherwise it projects it to the CRS defined by `to_crs`. If `to_crs` is `None`, it projects it to the CRS of an appropriate UTM zone given `gdf`'s bounds. Parameters ---------- gdf : geopandas.GeoDataFrame the GeoDataFrame to be projected to_crs : string or pyproj.CRS if None, project to an appropriate UTM zone, otherwise project to this CRS to_latlong : bool if True, project to `settings.default_crs` and ignore `to_crs` Returns ------- gdf_proj : geopandas.GeoDataFrame the projected GeoDataFrame """ if gdf.crs is None or len(gdf) < 1: # pragma: no cover msg = "GeoDataFrame must have a valid CRS and cannot be empty" raise ValueError(msg) # if to_latlong is True, project the gdf to the default_crs if to_latlong: to_crs = settings.default_crs # else if to_crs is None, project gdf to an appropriate UTM zone elif to_crs is None: to_crs = gdf.estimate_utm_crs() # project the gdf gdf_proj = gdf.to_crs(to_crs) crs_desc = f"{gdf_proj.crs.to_string()} / {gdf_proj.crs.name}" utils.log(f"Projected GeoDataFrame to {crs_desc!r}") return gdf_proj
(gdf, to_crs=None, to_latlong=False)
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52,256
osmnx.projection
project_graph
Project a graph from its current CRS to another. If `to_latlong` is `True`, this projects the GeoDataFrame to the CRS defined by `settings.default_crs`, otherwise it projects it to the CRS defined by `to_crs`. If `to_crs` is `None`, it projects it to the CRS of an appropriate UTM zone given `G`'s bounds. Parameters ---------- G : networkx.MultiDiGraph the graph to be projected to_crs : string or pyproj.CRS if None, project to an appropriate UTM zone, otherwise project to this CRS to_latlong : bool if True, project to `settings.default_crs` and ignore `to_crs` Returns ------- G_proj : networkx.MultiDiGraph the projected graph
def project_graph(G, to_crs=None, to_latlong=False): """ Project a graph from its current CRS to another. If `to_latlong` is `True`, this projects the GeoDataFrame to the CRS defined by `settings.default_crs`, otherwise it projects it to the CRS defined by `to_crs`. If `to_crs` is `None`, it projects it to the CRS of an appropriate UTM zone given `G`'s bounds. Parameters ---------- G : networkx.MultiDiGraph the graph to be projected to_crs : string or pyproj.CRS if None, project to an appropriate UTM zone, otherwise project to this CRS to_latlong : bool if True, project to `settings.default_crs` and ignore `to_crs` Returns ------- G_proj : networkx.MultiDiGraph the projected graph """ if to_latlong: to_crs = settings.default_crs # STEP 1: PROJECT THE NODES gdf_nodes = convert.graph_to_gdfs(G, edges=False) # create new lat/lon columns to preserve lat/lon for later reference if # cols do not already exist (ie, don't overwrite in later re-projections) if "lon" not in gdf_nodes.columns or "lat" not in gdf_nodes.columns: gdf_nodes["lon"] = gdf_nodes["x"] gdf_nodes["lat"] = gdf_nodes["y"] # project the nodes GeoDataFrame and extract the projected x/y values gdf_nodes_proj = project_gdf(gdf_nodes, to_crs=to_crs) gdf_nodes_proj["x"] = gdf_nodes_proj["geometry"].x gdf_nodes_proj["y"] = gdf_nodes_proj["geometry"].y to_crs = gdf_nodes_proj.crs gdf_nodes_proj = gdf_nodes_proj.drop(columns=["geometry"]) # STEP 2: PROJECT THE EDGES if "simplified" in G.graph and G.graph["simplified"]: # if graph has previously been simplified, project the edge geometries gdf_edges = convert.graph_to_gdfs(G, nodes=False, fill_edge_geometry=False) gdf_edges_proj = project_gdf(gdf_edges, to_crs=to_crs) else: # if not, you don't have to project these edges because the nodes # contain all the spatial data in the graph (unsimplified edges have # no geometry attributes) gdf_edges_proj = convert.graph_to_gdfs(G, nodes=False, fill_edge_geometry=False).drop( columns=["geometry"] ) # STEP 3: REBUILD GRAPH # turn projected node/edge gdfs into a graph and update its CRS attribute G_proj = convert.graph_from_gdfs(gdf_nodes_proj, gdf_edges_proj, G.graph) G_proj.graph["crs"] = to_crs utils.log(f"Projected graph with {len(G)} nodes and {len(G.edges)} edges") return G_proj
(G, to_crs=None, to_latlong=False)
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52,259
osmnx.io
save_graph_geopackage
Save graph nodes and edges to disk as layers in a GeoPackage file. Parameters ---------- G : networkx.MultiDiGraph input graph filepath : string or pathlib.Path path to the GeoPackage file including extension. if None, use default data folder + graph.gpkg encoding : string the character encoding for the saved file directed : bool if False, save one edge for each undirected edge in the graph but retain original oneway and to/from information as edge attributes; if True, save one edge for each directed edge in the graph Returns ------- None
def save_graph_geopackage(G, filepath=None, encoding="utf-8", directed=False): """ Save graph nodes and edges to disk as layers in a GeoPackage file. Parameters ---------- G : networkx.MultiDiGraph input graph filepath : string or pathlib.Path path to the GeoPackage file including extension. if None, use default data folder + graph.gpkg encoding : string the character encoding for the saved file directed : bool if False, save one edge for each undirected edge in the graph but retain original oneway and to/from information as edge attributes; if True, save one edge for each directed edge in the graph Returns ------- None """ # default filepath if none was provided filepath = Path(settings.data_folder) / "graph.gpkg" if filepath is None else Path(filepath) # if save folder does not already exist, create it filepath.parent.mkdir(parents=True, exist_ok=True) # convert graph to gdfs and stringify non-numeric columns if directed: gdf_nodes, gdf_edges = convert.graph_to_gdfs(G) else: gdf_nodes, gdf_edges = convert.graph_to_gdfs(convert.to_undirected(G)) gdf_nodes = _stringify_nonnumeric_cols(gdf_nodes) gdf_edges = _stringify_nonnumeric_cols(gdf_edges) # save the nodes and edges as GeoPackage layers gdf_nodes.to_file(filepath, layer="nodes", driver="GPKG", index=True, encoding=encoding) gdf_edges.to_file(filepath, layer="edges", driver="GPKG", index=True, encoding=encoding) utils.log(f"Saved graph as GeoPackage at {filepath!r}")
(G, filepath=None, encoding='utf-8', directed=False)
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52,260
osmnx.io
save_graph_shapefile
Do not use: deprecated. Use the save_graph_geopackage function instead. The Shapefile format is proprietary and outdated. Instead, use the superior GeoPackage file format via the save_graph_geopackage function. See http://switchfromshapefile.org/ for more information. Parameters ---------- G : networkx.MultiDiGraph input graph filepath : string or pathlib.Path path to the shapefiles folder (no file extension). if None, use default data folder + graph_shapefile encoding : string the character encoding for the saved files directed : bool if False, save one edge for each undirected edge in the graph but retain original oneway and to/from information as edge attributes; if True, save one edge for each directed edge in the graph Returns ------- None
def save_graph_shapefile(G, filepath=None, encoding="utf-8", directed=False): """ Do not use: deprecated. Use the save_graph_geopackage function instead. The Shapefile format is proprietary and outdated. Instead, use the superior GeoPackage file format via the save_graph_geopackage function. See http://switchfromshapefile.org/ for more information. Parameters ---------- G : networkx.MultiDiGraph input graph filepath : string or pathlib.Path path to the shapefiles folder (no file extension). if None, use default data folder + graph_shapefile encoding : string the character encoding for the saved files directed : bool if False, save one edge for each undirected edge in the graph but retain original oneway and to/from information as edge attributes; if True, save one edge for each directed edge in the graph Returns ------- None """ warn( "The `save_graph_shapefile` function is deprecated and will be removed " "in the v2.0.0 release. Instead, use the `save_graph_geopackage` function " "to save graphs as GeoPackage files for subsequent GIS analysis. " "See the OSMnx v2 migration guide: https://github.com/gboeing/osmnx/issues/1123", FutureWarning, stacklevel=2, ) # default filepath if none was provided filepath = ( Path(settings.data_folder) / "graph_shapefile" if filepath is None else Path(filepath) ) # if save folder does not already exist, create it (shapefiles # get saved as set of files) filepath.mkdir(parents=True, exist_ok=True) filepath_nodes = filepath / "nodes.shp" filepath_edges = filepath / "edges.shp" # convert graph to gdfs and stringify non-numeric columns if directed: gdf_nodes, gdf_edges = convert.graph_to_gdfs(G) else: gdf_nodes, gdf_edges = convert.graph_to_gdfs(convert.to_undirected(G)) gdf_nodes = _stringify_nonnumeric_cols(gdf_nodes) gdf_edges = _stringify_nonnumeric_cols(gdf_edges) # save the nodes and edges as separate ESRI shapefiles gdf_nodes.to_file(filepath_nodes, driver="ESRI Shapefile", index=True, encoding=encoding) gdf_edges.to_file(filepath_edges, driver="ESRI Shapefile", index=True, encoding=encoding) utils.log(f"Saved graph as shapefiles at {filepath!r}")
(G, filepath=None, encoding='utf-8', directed=False)
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52,261
osmnx.io
save_graph_xml
Save graph to disk as an OSM-formatted XML .osm file. This function exists only to allow serialization to the .osm file format for applications that require it, and has constraints to conform to that. As such, this function has a limited use case which does not include saving/loading graphs for subsequent OSMnx analysis. To save/load graphs to/from disk for later use in OSMnx, use the `io.save_graphml` and `io.load_graphml` functions instead. To load a graph from a .osm file that you have downloaded or generated elsewhere, use the `graph.graph_from_xml` function. Parameters ---------- data : networkx.MultiDiGraph the input graph filepath : string or pathlib.Path do not use, deprecated node_tags : list do not use, deprecated node_attrs: list do not use, deprecated edge_tags : list do not use, deprecated edge_attrs : list do not use, deprecated oneway : bool do not use, deprecated merge_edges : bool do not use, deprecated edge_tag_aggs : tuple do not use, deprecated api_version : float do not use, deprecated precision : int do not use, deprecated way_tag_aggs : dict Keys are OSM way tag keys and values are aggregation functions (anything accepted as an argument by pandas.agg). Allows user to aggregate graph edge attribute values into single OSM way values. If None, or if some tag's key does not exist in the dict, the way attribute will be assigned the value of the first edge of the way. Returns ------- None
def save_graph_xml( data, filepath=None, node_tags=None, node_attrs=None, edge_tags=None, edge_attrs=None, oneway=None, merge_edges=None, edge_tag_aggs=None, api_version=None, precision=None, way_tag_aggs=None, ): """ Save graph to disk as an OSM-formatted XML .osm file. This function exists only to allow serialization to the .osm file format for applications that require it, and has constraints to conform to that. As such, this function has a limited use case which does not include saving/loading graphs for subsequent OSMnx analysis. To save/load graphs to/from disk for later use in OSMnx, use the `io.save_graphml` and `io.load_graphml` functions instead. To load a graph from a .osm file that you have downloaded or generated elsewhere, use the `graph.graph_from_xml` function. Parameters ---------- data : networkx.MultiDiGraph the input graph filepath : string or pathlib.Path do not use, deprecated node_tags : list do not use, deprecated node_attrs: list do not use, deprecated edge_tags : list do not use, deprecated edge_attrs : list do not use, deprecated oneway : bool do not use, deprecated merge_edges : bool do not use, deprecated edge_tag_aggs : tuple do not use, deprecated api_version : float do not use, deprecated precision : int do not use, deprecated way_tag_aggs : dict Keys are OSM way tag keys and values are aggregation functions (anything accepted as an argument by pandas.agg). Allows user to aggregate graph edge attribute values into single OSM way values. If None, or if some tag's key does not exist in the dict, the way attribute will be assigned the value of the first edge of the way. Returns ------- None """ osm_xml._save_graph_xml( data, filepath, node_tags, node_attrs, edge_tags, edge_attrs, oneway, merge_edges, edge_tag_aggs, api_version, precision, way_tag_aggs, )
(data, filepath=None, node_tags=None, node_attrs=None, edge_tags=None, edge_attrs=None, oneway=None, merge_edges=None, edge_tag_aggs=None, api_version=None, precision=None, way_tag_aggs=None)
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52,262
osmnx.io
save_graphml
Save graph to disk as GraphML file. Parameters ---------- G : networkx.MultiDiGraph input graph filepath : string or pathlib.Path path to the GraphML file including extension. if None, use default data folder + graph.graphml gephi : bool if True, give each edge a unique key/id to work around Gephi's interpretation of the GraphML specification encoding : string the character encoding for the saved file Returns ------- None
def save_graphml(G, filepath=None, gephi=False, encoding="utf-8"): """ Save graph to disk as GraphML file. Parameters ---------- G : networkx.MultiDiGraph input graph filepath : string or pathlib.Path path to the GraphML file including extension. if None, use default data folder + graph.graphml gephi : bool if True, give each edge a unique key/id to work around Gephi's interpretation of the GraphML specification encoding : string the character encoding for the saved file Returns ------- None """ # default filepath if none was provided filepath = Path(settings.data_folder) / "graph.graphml" if filepath is None else Path(filepath) # if save folder does not already exist, create it filepath.parent.mkdir(parents=True, exist_ok=True) if gephi: # for gephi compatibility, each edge's key must be unique as an id uvkd = ((u, v, k, d) for k, (u, v, d) in enumerate(G.edges(keys=False, data=True))) G = nx.MultiDiGraph(uvkd) else: # make a copy to not mutate original graph object caller passed in G = G.copy() # stringify all the graph attribute values for attr, value in G.graph.items(): G.graph[attr] = str(value) # stringify all the node attribute values for _, data in G.nodes(data=True): for attr, value in data.items(): data[attr] = str(value) # stringify all the edge attribute values for _, _, data in G.edges(keys=False, data=True): for attr, value in data.items(): data[attr] = str(value) nx.write_graphml(G, path=filepath, encoding=encoding) utils.log(f"Saved graph as GraphML file at {filepath!r}")
(G, filepath=None, gephi=False, encoding='utf-8')
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52,264
osmnx.routing
shortest_path
Solve shortest path from origin node(s) to destination node(s). Uses Dijkstra's algorithm. If `orig` and `dest` are single node IDs, this will return a list of the nodes constituting the shortest path between them. If `orig` and `dest` are lists of node IDs, this will return a list of lists of the nodes constituting the shortest path between each origin-destination pair. If a path cannot be solved, this will return None for that path. You can parallelize solving multiple paths with the `cpus` parameter, but be careful to not exceed your available RAM. See also `k_shortest_paths` to solve multiple shortest paths between a single origin and destination. For additional functionality or different solver algorithms, use NetworkX directly. Parameters ---------- G : networkx.MultiDiGraph input graph orig : int or list origin node ID, or a list of origin node IDs dest : int or list destination node ID, or a list of destination node IDs weight : string edge attribute to minimize when solving shortest path cpus : int how many CPU cores to use; if None, use all available Returns ------- path : list list of node IDs constituting the shortest path, or, if orig and dest are lists, then a list of path lists
def shortest_path(G, orig, dest, weight="length", cpus=1): """ Solve shortest path from origin node(s) to destination node(s). Uses Dijkstra's algorithm. If `orig` and `dest` are single node IDs, this will return a list of the nodes constituting the shortest path between them. If `orig` and `dest` are lists of node IDs, this will return a list of lists of the nodes constituting the shortest path between each origin-destination pair. If a path cannot be solved, this will return None for that path. You can parallelize solving multiple paths with the `cpus` parameter, but be careful to not exceed your available RAM. See also `k_shortest_paths` to solve multiple shortest paths between a single origin and destination. For additional functionality or different solver algorithms, use NetworkX directly. Parameters ---------- G : networkx.MultiDiGraph input graph orig : int or list origin node ID, or a list of origin node IDs dest : int or list destination node ID, or a list of destination node IDs weight : string edge attribute to minimize when solving shortest path cpus : int how many CPU cores to use; if None, use all available Returns ------- path : list list of node IDs constituting the shortest path, or, if orig and dest are lists, then a list of path lists """ _verify_edge_attribute(G, weight) # if neither orig nor dest is iterable, just return the shortest path if not (hasattr(orig, "__iter__") or hasattr(dest, "__iter__")): return _single_shortest_path(G, orig, dest, weight) # if only 1 of orig or dest is iterable and the other is not, raise error if not (hasattr(orig, "__iter__") and hasattr(dest, "__iter__")): msg = "orig and dest must either both be iterable or neither must be iterable" raise ValueError(msg) # if both orig and dest are iterable, ensure they have same lengths if len(orig) != len(dest): # pragma: no cover msg = "orig and dest must be of equal length" raise ValueError(msg) # determine how many cpu cores to use if cpus is None: cpus = mp.cpu_count() cpus = min(cpus, mp.cpu_count()) utils.log(f"Solving {len(orig)} paths with {cpus} CPUs...") # if single-threading, calculate each shortest path one at a time if cpus == 1: paths = [_single_shortest_path(G, o, d, weight) for o, d in zip(orig, dest)] # if multi-threading, calculate shortest paths in parallel else: args = ((G, o, d, weight) for o, d in zip(orig, dest)) with mp.get_context("spawn").Pool(cpus) as pool: paths = pool.starmap_async(_single_shortest_path, args).get() return paths
(G, orig, dest, weight='length', cpus=1)
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52,266
osmnx.simplification
simplify_graph
Simplify a graph's topology by removing interstitial nodes. This simplifies graph topology by removing all nodes that are not intersections or dead-ends, by creating an edge directly between the end points that encapsulate them while retaining the full geometry of the original edges, saved as a new `geometry` attribute on the new edge. Note that only simplified edges receive a `geometry` attribute. Some of the resulting consolidated edges may comprise multiple OSM ways, and if so, their multiple attribute values are stored as a list. Optionally, the simplified edges can receive a `merged_edges` attribute that contains a list of all the (u, v) node pairs that were merged together. Use the `edge_attrs_differ` parameter to relax simplification strictness. For example, `edge_attrs_differ=['osmid']` will retain every node whose incident edges have different OSM IDs. This lets you keep nodes at elbow two-way intersections (but be aware that sometimes individual blocks have multiple OSM IDs within them too). You could also use this parameter to retain nodes where sidewalks or bike lanes begin/end in the middle of a block. Parameters ---------- G : networkx.MultiDiGraph input graph strict : bool deprecated, do not use edge_attrs_differ : iterable An iterable of edge attribute names for relaxing the strictness of endpoint determination. If not None, a node is an endpoint if its incident edges have different values then each other for any of the edge attributes in `edge_attrs_differ`. endpoint_attrs : iterable deprecated, do not use remove_rings : bool if True, remove isolated self-contained rings that have no endpoints track_merged : bool if True, add `merged_edges` attribute on simplified edges, containing a list of all the (u, v) node pairs that were merged together Returns ------- G : networkx.MultiDiGraph topologically simplified graph, with a new `geometry` attribute on each simplified edge
def simplify_graph( # noqa: C901 G, strict=None, edge_attrs_differ=None, endpoint_attrs=None, remove_rings=True, track_merged=False, ): """ Simplify a graph's topology by removing interstitial nodes. This simplifies graph topology by removing all nodes that are not intersections or dead-ends, by creating an edge directly between the end points that encapsulate them while retaining the full geometry of the original edges, saved as a new `geometry` attribute on the new edge. Note that only simplified edges receive a `geometry` attribute. Some of the resulting consolidated edges may comprise multiple OSM ways, and if so, their multiple attribute values are stored as a list. Optionally, the simplified edges can receive a `merged_edges` attribute that contains a list of all the (u, v) node pairs that were merged together. Use the `edge_attrs_differ` parameter to relax simplification strictness. For example, `edge_attrs_differ=['osmid']` will retain every node whose incident edges have different OSM IDs. This lets you keep nodes at elbow two-way intersections (but be aware that sometimes individual blocks have multiple OSM IDs within them too). You could also use this parameter to retain nodes where sidewalks or bike lanes begin/end in the middle of a block. Parameters ---------- G : networkx.MultiDiGraph input graph strict : bool deprecated, do not use edge_attrs_differ : iterable An iterable of edge attribute names for relaxing the strictness of endpoint determination. If not None, a node is an endpoint if its incident edges have different values then each other for any of the edge attributes in `edge_attrs_differ`. endpoint_attrs : iterable deprecated, do not use remove_rings : bool if True, remove isolated self-contained rings that have no endpoints track_merged : bool if True, add `merged_edges` attribute on simplified edges, containing a list of all the (u, v) node pairs that were merged together Returns ------- G : networkx.MultiDiGraph topologically simplified graph, with a new `geometry` attribute on each simplified edge """ if endpoint_attrs is not None: msg = ( "The `endpoint_attrs` parameter has been deprecated and will be removed " "in the v2.0.0 release. Use the `edge_attrs_differ` parameter instead. " "See the OSMnx v2 migration guide: https://github.com/gboeing/osmnx/issues/1123" ) warn(msg, FutureWarning, stacklevel=2) edge_attrs_differ = endpoint_attrs if strict is not None: msg = ( "The `strict` parameter has been deprecated and will be removed in " "the v2.0.0 release. Use the `edge_attrs_differ` parameter instead to " "relax simplification strictness. For example, `edge_attrs_differ=None` " "reproduces the old `strict=True` behvavior and `edge_attrs_differ=['osmid']` " "reproduces the old `strict=False` behavior. " "See the OSMnx v2 migration guide: https://github.com/gboeing/osmnx/issues/1123" ) warn(msg, FutureWarning, stacklevel=2) # maintain old behavior if strict is passed during deprecation edge_attrs_differ = None if strict else ["osmid"] if "simplified" in G.graph and G.graph["simplified"]: # pragma: no cover msg = "This graph has already been simplified, cannot simplify it again." raise GraphSimplificationError(msg) utils.log("Begin topologically simplifying the graph...") # define edge segment attributes to sum upon edge simplification attrs_to_sum = {"length", "travel_time"} # make a copy to not mutate original graph object caller passed in G = G.copy() initial_node_count = len(G) initial_edge_count = len(G.edges) all_nodes_to_remove = [] all_edges_to_add = [] # generate each path that needs to be simplified for path in _get_paths_to_simplify(G, edge_attrs_differ): # add the interstitial edges we're removing to a list so we can retain # their spatial geometry merged_edges = [] path_attributes = {} for u, v in zip(path[:-1], path[1:]): if track_merged: # keep track of the edges that were merged merged_edges.append((u, v)) # there should rarely be multiple edges between interstitial nodes # usually happens if OSM has duplicate ways digitized for just one # street... we will keep only one of the edges (see below) edge_count = G.number_of_edges(u, v) if edge_count != 1: utils.log(f"Found {edge_count} edges between {u} and {v} when simplifying") # get edge between these nodes: if multiple edges exist between # them (see above), we retain only one in the simplified graph # We can't assume that there exists an edge from u to v # with key=0, so we get a list of all edges from u to v # and just take the first one. edge_data = list(G.get_edge_data(u, v).values())[0] for attr in edge_data: if attr in path_attributes: # if this key already exists in the dict, append it to the # value list path_attributes[attr].append(edge_data[attr]) else: # if this key doesn't already exist, set the value to a list # containing the one value path_attributes[attr] = [edge_data[attr]] # consolidate the path's edge segments' attribute values for attr in path_attributes: if attr in attrs_to_sum: # if this attribute must be summed, sum it now path_attributes[attr] = sum(path_attributes[attr]) elif len(set(path_attributes[attr])) == 1: # if there's only 1 unique value in this attribute list, # consolidate it to the single value (the zero-th): path_attributes[attr] = path_attributes[attr][0] else: # otherwise, if there are multiple values, keep one of each path_attributes[attr] = list(set(path_attributes[attr])) # construct the new consolidated edge's geometry for this path path_attributes["geometry"] = LineString( [Point((G.nodes[node]["x"], G.nodes[node]["y"])) for node in path] ) if track_merged: # add the merged edges as a new attribute of the simplified edge path_attributes["merged_edges"] = merged_edges # add the nodes and edge to their lists for processing at the end all_nodes_to_remove.extend(path[1:-1]) all_edges_to_add.append( {"origin": path[0], "destination": path[-1], "attr_dict": path_attributes} ) # for each edge to add in the list we assembled, create a new edge between # the origin and destination for edge in all_edges_to_add: G.add_edge(edge["origin"], edge["destination"], **edge["attr_dict"]) # finally remove all the interstitial nodes between the new edges G.remove_nodes_from(set(all_nodes_to_remove)) if remove_rings: G = _remove_rings(G, edge_attrs_differ) # mark the graph as having been simplified G.graph["simplified"] = True msg = ( f"Simplified graph: {initial_node_count:,} to {len(G):,} nodes, " f"{initial_edge_count:,} to {len(G.edges):,} edges" ) utils.log(msg) return G
(G, strict=None, edge_attrs_differ=None, endpoint_attrs=None, remove_rings=True, track_merged=False)
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52,270
osmnx.utils
ts
Return current local timestamp as a string. Parameters ---------- style : string {"datetime", "date", "time"} format the timestamp with this built-in style template : string if not None, format the timestamp with this format string instead of one of the built-in styles Returns ------- ts : string local timestamp string
def ts(style="datetime", template=None): """ Return current local timestamp as a string. Parameters ---------- style : string {"datetime", "date", "time"} format the timestamp with this built-in style template : string if not None, format the timestamp with this format string instead of one of the built-in styles Returns ------- ts : string local timestamp string """ if template is None: if style == "datetime": template = "{:%Y-%m-%d %H:%M:%S}" elif style == "date": template = "{:%Y-%m-%d}" elif style == "time": template = "{:%H:%M:%S}" else: # pragma: no cover msg = f"unrecognized timestamp style {style!r}" raise ValueError(msg) return template.format(dt.datetime.now().astimezone())
(style='datetime', template=None)
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52,274
flexget.manager
Manager
Manager class for FlexGet Fires events: * manager.initialize The first time the manager is initialized, before config is loaded * manager.before_config_load Before the config file is loaded from disk * manager.before_config_validate When updating the config, before the validator is run on it * manager.config_updated After a configuration file has been loaded or changed (and validated) this event is fired * manager.startup After manager has been initialized. This is when application becomes ready to use, however no database lock is present, so the database must not be modified on this event. * manager.lock_acquired The manager does not always require a lock on startup, if one is requested, this event will run when it has been acquired successfully * manager.upgrade If any plugins have declared a newer schema version than exists in the database, this event will be fired to allow plugins to upgrade their tables * manager.shutdown_requested When shutdown has been requested. Any plugins which might add to execution queue should stop when this is fired. * manager.shutdown When the manager is exiting * manager.execute.completed If execution in current process was completed * manager.daemon.started * manager.daemon.completed * manager.db_cleanup
class Manager: """Manager class for FlexGet Fires events: * manager.initialize The first time the manager is initialized, before config is loaded * manager.before_config_load Before the config file is loaded from disk * manager.before_config_validate When updating the config, before the validator is run on it * manager.config_updated After a configuration file has been loaded or changed (and validated) this event is fired * manager.startup After manager has been initialized. This is when application becomes ready to use, however no database lock is present, so the database must not be modified on this event. * manager.lock_acquired The manager does not always require a lock on startup, if one is requested, this event will run when it has been acquired successfully * manager.upgrade If any plugins have declared a newer schema version than exists in the database, this event will be fired to allow plugins to upgrade their tables * manager.shutdown_requested When shutdown has been requested. Any plugins which might add to execution queue should stop when this is fired. * manager.shutdown When the manager is exiting * manager.execute.completed If execution in current process was completed * manager.daemon.started * manager.daemon.completed * manager.db_cleanup """ unit_test = False options: argparse.Namespace def __init__(self, args: List[str]) -> None: """ :param args: CLI args """ global manager if not self.unit_test: assert not manager, 'Only one instance of Manager should be created at a time!' elif manager: logger.info('last manager was not torn down correctly') self.args = args self.autoreload_config = False self.config_file_hash: Optional[str] = None self.config_base: str = '' self.config_name: str = '' self.config_path: str = '' self.log_filename: str = '' self.db_filename: str = '' self.engine: Optional[Engine] = None self.lockfile: str = '' self.database_uri: str = '' self.db_upgraded = False self._has_lock = False self.is_daemon = False self.ipc_server: IPCServer self.task_queue: TaskQueue self.persist: SimplePersistence self.initialized = False self.config: Dict = {} self.options = self.parse_initial_options(args) self._init_config(create=False) # When we are in test mode, we use a different lock file and db if self.options.test: self.lockfile = os.path.join(self.config_base, f'.test-{self.config_name}-lock') self._init_logging() manager = self logger.debug('sys.defaultencoding: {}', sys.getdefaultencoding()) logger.debug('sys.getfilesystemencoding: {}', sys.getfilesystemencoding()) logger.debug('flexget detected io encoding: {}', io_encoding) logger.debug('os.path.supports_unicode_filenames: {}', os.path.supports_unicode_filenames) if ( codecs.lookup(sys.getfilesystemencoding()).name == 'ascii' and not os.path.supports_unicode_filenames ): logger.warning( 'Your locale declares ascii as the filesystem encoding. Any plugins reading filenames from ' 'disk will not work properly for filenames containing non-ascii characters. Make sure your ' 'locale env variables are set up correctly for the environment which is launching FlexGet.' ) def _add_tray_icon_items(self, tray_icon: 'TrayIcon'): tray_icon.add_menu_item(text='Shutdown', action=self.shutdown, index=2) tray_icon.add_menu_item(text='Reload Config', action=self.load_config, index=3) tray_icon.add_menu_separator(index=4) @staticmethod def parse_initial_options(args: List[str]) -> argparse.Namespace: """Parse what we can from cli args before plugins are loaded.""" try: options = CoreArgumentParser().parse_known_args(args, do_help=False)[0] except ParserError as exc: try: # If a non-built-in command was used, we need to parse with a parser that # doesn't define the subparsers options = manager_parser.parse_known_args(args, do_help=False)[0] except ParserError: manager_parser.print_help() print(f'\nError: {exc.message}') sys.exit(1) return options def _init_logging(self) -> None: """Initialize logging variables""" log_file = os.path.expanduser(self.options.logfile) # If an absolute path is not specified, use the config directory. if not os.path.isabs(log_file): log_file = os.path.join(self.config_base, log_file) self.log_filename = log_file def initialize(self) -> None: """ Load plugins, database, and config. Also initializes (but does not start) the task queue and ipc server. This should only be called after obtaining a lock. """ if self.initialized: raise RuntimeError('Cannot call initialize on an already initialized manager.') plugin.load_plugins( extra_plugins=[os.path.join(self.config_base, 'plugins')], extra_components=[os.path.join(self.config_base, 'components')], ) # Reparse CLI options now that plugins are loaded self.options = get_parser().parse_args(self.args) self.task_queue = TaskQueue() self.ipc_server = IPCServer(self, self.options.ipc_port) self.setup_yaml() self.init_sqlalchemy() fire_event('manager.initialize', self) try: self.load_config() except ValueError as e: logger.critical('Failed to load config file: {}', e.args[0]) raise # cannot be imported at module level because of circular references from flexget.utils.simple_persistence import SimplePersistence self.persist = SimplePersistence('manager') if db_schema.upgrade_required(): logger.info('Database upgrade is required. Attempting now.') fire_event('manager.upgrade', self) if manager.db_upgraded: fire_event('manager.db_upgraded', self) fire_event('manager.startup', self) self.initialized = True @property def tasks(self) -> List[str]: """A list of tasks in the config""" if not self.config: return [] return list(self.config.get('tasks', {}).keys()) @property def has_lock(self) -> bool: return self._has_lock def execute( self, options: Optional[Union[dict, argparse.Namespace]] = None, priority: int = 1, suppress_warnings: Optional[Sequence[str]] = None, ) -> List[Tuple[str, str, threading.Event]]: """ Run all (can be limited with options) tasks from the config. :param options: Either an :class:`argparse.Namespace` instance, or a dict, containing options for execution :param priority: If there are other executions waiting to be run, they will be run in priority order, lowest first. :param suppress_warnings: Allows suppressing log warning about missing plugin in key phases :returns: a list of :class:`threading.Event` instances which will be set when each respective task has finished running """ if options is None: options = copy.copy(self.options.execute) elif isinstance(options, dict): options_namespace = copy.copy(self.options.execute) options_namespace.__dict__.update(options) options = options_namespace task_names = self.tasks # Only reload config if daemon config_hash = self.hash_config() if self.is_daemon and self.autoreload_config and self.config_file_hash != config_
(args: List[str]) -> None
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52,275
flexget.manager
__init__
:param args: CLI args
def __init__(self, args: List[str]) -> None: """ :param args: CLI args """ global manager if not self.unit_test: assert not manager, 'Only one instance of Manager should be created at a time!' elif manager: logger.info('last manager was not torn down correctly') self.args = args self.autoreload_config = False self.config_file_hash: Optional[str] = None self.config_base: str = '' self.config_name: str = '' self.config_path: str = '' self.log_filename: str = '' self.db_filename: str = '' self.engine: Optional[Engine] = None self.lockfile: str = '' self.database_uri: str = '' self.db_upgraded = False self._has_lock = False self.is_daemon = False self.ipc_server: IPCServer self.task_queue: TaskQueue self.persist: SimplePersistence self.initialized = False self.config: Dict = {} self.options = self.parse_initial_options(args) self._init_config(create=False) # When we are in test mode, we use a different lock file and db if self.options.test: self.lockfile = os.path.join(self.config_base, f'.test-{self.config_name}-lock') self._init_logging() manager = self logger.debug('sys.defaultencoding: {}', sys.getdefaultencoding()) logger.debug('sys.getfilesystemencoding: {}', sys.getfilesystemencoding()) logger.debug('flexget detected io encoding: {}', io_encoding) logger.debug('os.path.supports_unicode_filenames: {}', os.path.supports_unicode_filenames) if ( codecs.lookup(sys.getfilesystemencoding()).name == 'ascii' and not os.path.supports_unicode_filenames ): logger.warning( 'Your locale declares ascii as the filesystem encoding. Any plugins reading filenames from ' 'disk will not work properly for filenames containing non-ascii characters. Make sure your ' 'locale env variables are set up correctly for the environment which is launching FlexGet.' )
(self, args: List[str]) -> NoneType
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52,276
flexget.manager
_add_tray_icon_items
null
def _add_tray_icon_items(self, tray_icon: 'TrayIcon'): tray_icon.add_menu_item(text='Shutdown', action=self.shutdown, index=2) tray_icon.add_menu_item(text='Reload Config', action=self.load_config, index=3) tray_icon.add_menu_separator(index=4)
(self, tray_icon: 'TrayIcon')
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52,277
flexget.manager
_handle_sigterm
null
def _handle_sigterm(self, signum, frame) -> None: logger.info('Got SIGTERM. Shutting down.') self.shutdown(finish_queue=False)
(self, signum, frame) -> NoneType
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52,278
flexget.manager
_init_config
Find and load the configuration file. :param bool create: If a config file is not found, and create is True, one will be created in the home folder :raises: `OSError` when no config file could be found, and `create` is False.
def _init_config(self, create: bool = False) -> None: """ Find and load the configuration file. :param bool create: If a config file is not found, and create is True, one will be created in the home folder :raises: `OSError` when no config file could be found, and `create` is False. """ home_path = os.path.join(os.path.expanduser('~'), '.flexget') options_config = os.path.expanduser(self.options.config) possible = [] if os.path.isabs(options_config): # explicit path given, don't try anything config = options_config possible = [config] else: logger.debug('Figuring out config load paths') try: possible.append(os.getcwd()) except OSError: logger.debug('current directory invalid, not searching for config there') # for virtualenv / dev sandbox if hasattr(sys, 'real_prefix'): logger.debug('Adding virtualenv path') possible.append(sys.prefix) # normal lookup locations possible.append(home_path) if sys.platform.startswith('win'): # On windows look in ~/flexget as well, as explorer does not let you create a folder starting with a dot home_path = os.path.join(os.path.expanduser('~'), 'flexget') possible.append(home_path) else: # The freedesktop.org standard config location xdg_config = os.environ.get( 'XDG_CONFIG_HOME', os.path.join(os.path.expanduser('~'), '.config') ) possible.append(os.path.join(xdg_config, 'flexget')) for path in possible: config = os.path.join(path, options_config) if os.path.exists(config): logger.debug('Found config: {}', config) break else: config = None if create and not (config and os.path.exists(config)): config = os.path.join(home_path, options_config) logger.info('Config file {} not found. Creating new config {}', options_config, config) with open(config, 'w') as newconfig: # Write empty tasks to the config newconfig.write(yaml.dump({'tasks': {}})) elif not config: logger.critical('Failed to find configuration file {}', options_config) logger.info('Tried to read from: {}', ', '.join(possible)) raise OSError('No configuration file found.') if not os.path.isfile(config): raise OSError(f'Config `{config}` does not appear to be a file.') logger.debug('Config file {} selected', config) self.config_path = config self.config_name = os.path.splitext(os.path.basename(config))[0] self.config_base = os.path.normpath(os.path.dirname(config)) self.lockfile = os.path.join(self.config_base, f'.{self.config_name}-lock') self.db_filename = os.path.join(self.config_base, f'db-{self.config_name}.sqlite')
(self, create: bool = False) -> NoneType
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52,279
flexget.manager
_init_logging
Initialize logging variables
def _init_logging(self) -> None: """Initialize logging variables""" log_file = os.path.expanduser(self.options.logfile) # If an absolute path is not specified, use the config directory. if not os.path.isabs(log_file): log_file = os.path.join(self.config_base, log_file) self.log_filename = log_file
(self) -> NoneType
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52,280
flexget.manager
_read_lock
Read the values from the lock file. Returns None if there is no current lock file.
def _read_lock(self) -> Optional[dict]: """ Read the values from the lock file. Returns None if there is no current lock file. """ if self.lockfile and os.path.exists(self.lockfile): result: Dict[str, Union[str, int]] = {} with open(self.lockfile, encoding='utf-8') as f: lines = [line for line in f.readlines() if line] for line in lines: try: key, value = line.split(':', 1) except ValueError: logger.debug('Invalid line in lock file: {}', line) continue result[key.strip().lower()] = value.strip() for key in result: if result[key].isdigit(): result[key] = int(result[key]) result.setdefault('pid', None) if not result['pid']: logger.error( 'Invalid lock file. Make sure FlexGet is not running, then delete it.' ) elif not pid_exists(result['pid']): return None return result return None
(self) -> Optional[dict]
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52,281
flexget.manager
_shutdown
Runs when the manager is done processing everything.
def _shutdown(self) -> None: """Runs when the manager is done processing everything.""" if self.ipc_server: self.ipc_server.shutdown() fire_event('manager.shutdown', self) if not self.unit_test: # don't scroll "nosetests" summary results when logging is enabled logger.debug('Shutting down') self.engine.dispose() # remove temporary database used in test mode if self.options.test: if 'test' not in self.db_filename: raise Exception('trying to delete non test database?') if self._has_lock: os.remove(self.db_filename) logger.info('Removed test database') global manager manager = None
(self) -> NoneType
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52,282
flexget.manager
acquire_lock
:param bool event: If True, the 'manager.lock_acquired' event will be fired after a lock is obtained
def execute( self, options: Optional[Union[dict, argparse.Namespace]] = None, priority: int = 1, suppress_warnings: Optional[Sequence[str]] = None, ) -> List[Tuple[str, str, threading.Event]]: """ Run all (can be limited with options) tasks from the config. :param options: Either an :class:`argparse.Namespace` instance, or a dict, containing options for execution :param priority: If there are other executions waiting to be run, they will be run in priority order, lowest first. :param suppress_warnings: Allows suppressing log warning about missing plugin in key phases :returns: a list of :class:`threading.Event` instances which will be set when each respective task has finished running """ if options is None: options = copy.copy(self.options.execute) elif isinstance(options, dict): options_namespace = copy.copy(self.options.execute) options_namespace.__dict__.update(options) options = options_namespace task_names = self.tasks # Only reload config if daemon config_hash = self.hash_config() if self.is_daemon and self.autoreload_config and self.config_file_hash != config_hash: logger.info('Config change detected. Reloading.') try: self.load_config(output_to_console=False, config_file_hash=config_hash) logger.info('Config successfully reloaded!') except Exception as e: logger.error('Reloading config failed: {}', e) # Handle --tasks if options.tasks: # Consider '*' the same as not specifying any tasks. # (So manual plugin doesn't consider them explicitly enabled.) if options.tasks == ['*']: options.tasks = None else: task_names = [] for task in options.tasks: try: task_names.extend( m for m in self.matching_tasks(task) if m not in task_names ) except ValueError as e: logger.error(e) continue options.tasks = task_names # TODO: 1.2 This is a hack to make task priorities work still, not sure if it's the best one task_names = sorted( task_names, key=lambda t: self.config['tasks'][t].get('priority', 65535) ) finished_events = [] for task_name in task_names: task = Task( self, task_name, options=options, output=get_console_output(), session_id=flexget.log.get_log_session_id(), priority=priority, suppress_warnings=suppress_warnings, ) self.task_queue.put(task) finished_events.append((task.id, task.name, task.finished_event)) return finished_events
(self, event: bool = True) -> Iterator
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0.0028679710812866688, 0.006316543556749821, 0.035536814481019974 ]
52,283
flexget.manager
backup_config
null
def backup_config(self) -> str: backup_path = os.path.join( self.config_base, f'{self.config_name}-{datetime.now().strftime("%y%m%d%H%M%S")}.bak', ) logger.debug(f'backing up old config to {backup_path} before new save') try: shutil.copy(self.config_path, backup_path) except OSError as e: logger.warning(f'Config backup creation failed: {e}') raise return backup_path
(self) -> str
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52,284
flexget.manager
check_ipc_info
If a daemon has a lock on the database, return info to connect to IPC.
def check_ipc_info(self) -> Optional[dict]: """If a daemon has a lock on the database, return info to connect to IPC.""" lock_info = self._read_lock() if lock_info and 'port' in lock_info: return lock_info return None
(self) -> Optional[dict]
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52,285
flexget.manager
check_lock
Returns True if there is a lock on the database.
def check_lock(self) -> bool: """Returns True if there is a lock on the database.""" lock_info = self._read_lock() if not lock_info: return False # Don't count it if we hold the lock if os.getpid() == lock_info['pid']: return False return True
(self) -> bool
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52,286
flexget.manager
config_changed
Makes sure that all tasks will have the config_modified flag come out true on the next run. Useful when changing the db and all tasks need to be completely reprocessed.
def config_changed(self) -> None: """Makes sure that all tasks will have the config_modified flag come out true on the next run. Useful when changing the db and all tasks need to be completely reprocessed.""" from flexget.task import config_changed config_changed() fire_event('manager.config_updated', self)
(self) -> NoneType
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52,287
flexget.manager
crash_report
This should be called when handling an unexpected exception. Will create a new log file containing the last 50 debug messages as well as the crash traceback.
def crash_report(self) -> str: """ This should be called when handling an unexpected exception. Will create a new log file containing the last 50 debug messages as well as the crash traceback. """ if not self.unit_test: log_dir = os.path.dirname(self.log_filename) filename = os.path.join( log_dir, datetime.now().strftime('crash_report.%Y.%m.%d.%H%M%S%f.log') ) with codecs.open(filename, 'w', encoding='utf-8') as outfile: outfile.writelines(flexget.log.debug_buffer) traceback.print_exc(file=outfile) logger.critical( 'An unexpected crash has occurred. Writing crash report to {}. ' 'Please verify you are running the latest version of flexget by using "flexget -V" ' 'from CLI or by using version_checker plugin' ' at https://flexget.com/Plugins/version_checker. ' 'You are currently using version {}', filename, get_current_flexget_version(), ) logger.opt(exception=True).debug('Traceback:') return traceback.format_exc()
(self) -> str
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52,288
flexget.manager
daemon_command
Handles the 'daemon' CLI command. Fires events: * manager.daemon.started * manager.daemon.completed :param options: argparse options
def daemon_command(self, options: argparse.Namespace) -> None: """ Handles the 'daemon' CLI command. Fires events: * manager.daemon.started * manager.daemon.completed :param options: argparse options """ # Import API so it can register to daemon.started event if options.action == 'start': if self.is_daemon: logger.error('Daemon already running for this config.') return elif self.task_queue.is_alive(): logger.error( 'Non-daemon execution of FlexGet is running. Cannot start daemon until it is finished.' ) return if options.daemonize: self.daemonize() if options.autoreload_config: self.autoreload_config = True try: signal.signal(signal.SIGTERM, self._handle_sigterm) except ValueError as e: # If flexget is being called from another script, e.g. windows service helper, and we are not the # main thread, this error will occur. logger.debug('Error registering sigterm handler: {}', e) self.is_daemon = True def run_daemon(tray_icon: 'TrayIcon' = None): fire_event('manager.daemon.started', self) self.task_queue.start() self.ipc_server.start() self.task_queue.wait() fire_event('manager.daemon.completed', self) if tray_icon: tray_icon.stop() if options.tray_icon: from flexget.tray_icon import tray_icon self._add_tray_icon_items(tray_icon) # Tray icon must be run in the main thread. m = threading.Thread(target=run_daemon, args=(tray_icon,)) m.start() tray_icon.run() m.join() else: run_daemon() elif options.action in ['stop', 'reload-config', 'status']: if not self.is_daemon: console('There does not appear to be a daemon running.') return if options.action == 'status': logger.debug('`daemon status` called. Daemon running. (PID: {})', os.getpid()) console(f'Daemon running. (PID: {os.getpid()})') elif options.action == 'stop': tasks = ( 'all queued tasks (if any) have' if options.wait else 'currently running task (if any) has' ) logger.info( 'Daemon shutdown requested. Shutdown will commence when {} finished executing.', tasks, ) self.shutdown(options.wait) elif options.action == 'reload-config': logger.info('Reloading config from disk.') try: self.load_config() except ValueError as e: logger.error('Error loading config: {}', e.args[0]) else: logger.info('Config successfully reloaded from disk.')
(self, options: argparse.Namespace) -> NoneType
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52,289
flexget.manager
daemonize
Daemonizes the current process. Returns the new pid
def daemonize(self) -> None: """Daemonizes the current process. Returns the new pid""" if sys.platform.startswith('win'): logger.error('Cannot daemonize on windows') return if threading.active_count() != 1: logger.critical( 'There are {!r} active threads. Daemonizing now may cause strange failures.', threading.enumerate(), ) logger.info('Daemonizing...') try: pid = os.fork() if pid > 0: # Don't run the exit handlers on the parent atexit._exithandlers = [] # exit first parent sys.exit(0) except OSError as e: sys.stderr.write(f'fork #1 failed: {e.errno} ({e.strerror})\n') sys.exit(1) # decouple from parent environment os.chdir('/') os.setsid() os.umask(0) # do second fork try: pid = os.fork() if pid > 0: # Don't run the exit handlers on the parent atexit._exithandlers = [] # exit from second parent sys.exit(0) except OSError as e: sys.stderr.write(f'fork #2 failed: {e.errno} ({e.strerror})\n') sys.exit(1) logger.info(f'Daemonize complete. New PID: {os.getpid()}') # redirect standard file descriptors sys.stdout.flush() sys.stderr.flush() si = open(os.devnull) so = open(os.devnull, 'ab+') se = open(os.devnull, 'ab+', 0) os.dup2(si.fileno(), sys.stdin.fileno()) os.dup2(so.fileno(), sys.stdout.fileno()) os.dup2(se.fileno(), sys.stderr.fileno()) # If we have a lock, update the lock file with our new pid if self._has_lock: self.write_lock()
(self) -> NoneType
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52,290
flexget.manager
db_cleanup
Perform database cleanup if cleanup interval has been met. Fires events: * manager.db_cleanup If interval was met. Gives session to do the cleanup as a parameter. :param bool force: Run the cleanup no matter whether the interval has been met.
def db_cleanup(self, force: bool = False) -> None: """ Perform database cleanup if cleanup interval has been met. Fires events: * manager.db_cleanup If interval was met. Gives session to do the cleanup as a parameter. :param bool force: Run the cleanup no matter whether the interval has been met. """ expired = ( self.persist.get('last_cleanup', datetime(1900, 1, 1)) < datetime.now() - DB_CLEANUP_INTERVAL ) if force or expired: logger.info('Running database cleanup.') with Session() as session: fire_event('manager.db_cleanup', self, session) # Try to VACUUM after cleanup fire_event('manager.db_vacuum', self) # Just in case some plugin was overzealous in its cleaning, mark the config changed self.config_changed() self.persist['last_cleanup'] = datetime.now() else: logger.debug('Not running db cleanup, last run {}', self.persist.get('last_cleanup'))
(self, force: bool = False) -> NoneType
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52,291
flexget.manager
execute
Run all (can be limited with options) tasks from the config. :param options: Either an :class:`argparse.Namespace` instance, or a dict, containing options for execution :param priority: If there are other executions waiting to be run, they will be run in priority order, lowest first. :param suppress_warnings: Allows suppressing log warning about missing plugin in key phases :returns: a list of :class:`threading.Event` instances which will be set when each respective task has finished running
def execute( self, options: Optional[Union[dict, argparse.Namespace]] = None, priority: int = 1, suppress_warnings: Optional[Sequence[str]] = None, ) -> List[Tuple[str, str, threading.Event]]: """ Run all (can be limited with options) tasks from the config. :param options: Either an :class:`argparse.Namespace` instance, or a dict, containing options for execution :param priority: If there are other executions waiting to be run, they will be run in priority order, lowest first. :param suppress_warnings: Allows suppressing log warning about missing plugin in key phases :returns: a list of :class:`threading.Event` instances which will be set when each respective task has finished running """ if options is None: options = copy.copy(self.options.execute) elif isinstance(options, dict): options_namespace = copy.copy(self.options.execute) options_namespace.__dict__.update(options) options = options_namespace task_names = self.tasks # Only reload config if daemon config_hash = self.hash_config() if self.is_daemon and self.autoreload_config and self.config_file_hash != config_hash: logger.info('Config change detected. Reloading.') try: self.load_config(output_to_console=False, config_file_hash=config_hash) logger.info('Config successfully reloaded!') except Exception as e: logger.error('Reloading config failed: {}', e) # Handle --tasks if options.tasks: # Consider '*' the same as not specifying any tasks. # (So manual plugin doesn't consider them explicitly enabled.) if options.tasks == ['*']: options.tasks = None else: task_names = [] for task in options.tasks: try: task_names.extend( m for m in self.matching_tasks(task) if m not in task_names ) except ValueError as e: logger.error(e) continue options.tasks = task_names # TODO: 1.2 This is a hack to make task priorities work still, not sure if it's the best one task_names = sorted( task_names, key=lambda t: self.config['tasks'][t].get('priority', 65535) ) finished_events = [] for task_name in task_names: task = Task( self, task_name, options=options, output=get_console_output(), session_id=flexget.log.get_log_session_id(), priority=priority, suppress_warnings=suppress_warnings, ) self.task_queue.put(task) finished_events.append((task.id, task.name, task.finished_event)) return finished_events
(self, options: Union[dict, argparse.Namespace, NoneType] = None, priority: int = 1, suppress_warnings: Optional[Sequence[str]] = None) -> List[Tuple[str, str, threading.Event]]
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52,292
flexget.manager
execute_command
Handles the 'execute' CLI command. If there is already a task queue running in this process, adds the execution to the queue. If FlexGet is being invoked with this command, starts up a task queue and runs the execution. Fires events: * manager.execute.started * manager.execute.completed :param options: argparse options
def execute_command(self, options: argparse.Namespace) -> None: """ Handles the 'execute' CLI command. If there is already a task queue running in this process, adds the execution to the queue. If FlexGet is being invoked with this command, starts up a task queue and runs the execution. Fires events: * manager.execute.started * manager.execute.completed :param options: argparse options """ fire_event('manager.execute.started', self, options) if self.task_queue.is_alive() or self.is_daemon: if not self.task_queue.is_alive(): logger.error( 'Task queue has died unexpectedly. Restarting it. Please open an issue on Github and include' ' any previous error logs.' ) self.task_queue = TaskQueue() self.task_queue.start() if len(self.task_queue): logger.verbose('There is a task already running, execution queued.') finished_events = self.execute(options) if not options.cron: # Wait until execution of all tasks has finished for _, _, event in finished_events: event.wait() else: self.task_queue.start() self.ipc_server.start() self.execute(options) self.shutdown(finish_queue=True) self.task_queue.wait() fire_event('manager.execute.completed', self, options)
(self, options: argparse.Namespace) -> NoneType
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52,293
flexget.manager
handle_cli
Dispatch a cli command to the appropriate function. * :meth:`.execute_command` * :meth:`.daemon_command` * CLI plugin callback function The manager should have a lock and be initialized before calling this method. :param options: argparse options for command. Defaults to options that manager was instantiated with.
def handle_cli(self, options: Optional[argparse.Namespace] = None) -> None: """ Dispatch a cli command to the appropriate function. * :meth:`.execute_command` * :meth:`.daemon_command` * CLI plugin callback function The manager should have a lock and be initialized before calling this method. :param options: argparse options for command. Defaults to options that manager was instantiated with. """ if not options: options = self.options command = options.cli_command if command is None: raise Exception('Command missing') command_options = getattr(options, command) # First check for built-in commands if command in ['execute', 'daemon']: if command == 'execute': self.execute_command(command_options) elif command == 'daemon': self.daemon_command(command_options) else: # Otherwise dispatch the command to the callback function options.cli_command_callback(self, command_options)
(self, options: Optional[argparse.Namespace] = None) -> NoneType
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52,294
flexget.manager
hash_config
null
def hash_config(self) -> Optional[str]: if not self.config_path: return None sha1_hash = hashlib.sha1() with open(self.config_path, 'rb') as f: while True: data = f.read(65536) if not data: break sha1_hash.update(data) return sha1_hash.hexdigest()
(self) -> Optional[str]
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52,295
flexget.manager
init_sqlalchemy
Initialize SQLAlchemy
def init_sqlalchemy(self) -> None: """Initialize SQLAlchemy""" try: if [int(part) for part in sqlalchemy.__version__.split('.')] < [0, 7, 0]: print( 'FATAL: SQLAlchemy 0.7.0 or newer required. Please upgrade your SQLAlchemy.', file=sys.stderr, ) sys.exit(1) except ValueError: logger.critical('Failed to check SQLAlchemy version, you may need to upgrade it') # SQLAlchemy if not self.database_uri: # in case running on windows, needs double \\ filename = self.db_filename.replace('\\', '\\\\') self.database_uri = f'sqlite:///{filename}' if self.db_filename and not os.path.exists(self.db_filename): logger.verbose('Creating new database {} - DO NOT INTERRUPT ...', self.db_filename) # fire up the engine logger.debug('Connecting to: {}', self.database_uri) try: self.engine = sqlalchemy.create_engine( self.database_uri, echo=self.options.debug_sql, connect_args={'check_same_thread': False, 'timeout': 10}, ) except ImportError as e: print( 'FATAL: Unable to use SQLite. Are you running Python 2.7, 3.3 or newer ?\n' 'Python should normally have SQLite support built in.\n' 'If you\'re running correct version of Python then it is not equipped with SQLite.\n' 'You can try installing `pysqlite`. If you have compiled python yourself, ' 'recompile it with SQLite support.\n' f'Error: {e}', file=sys.stderr, ) sys.exit(1) Session.configure(bind=self.engine) # create all tables, doesn't do anything to existing tables try: Base.metadata.create_all(bind=self.engine) except OperationalError as e: if os.path.exists(self.db_filename): print( f'{e.message} - make sure you have write permissions to file {self.db_filename}', file=sys.stderr, ) else: print( f'{e.message} - make sure you have write permissions to directory {self.config_base}', file=sys.stderr, ) raise
(self) -> NoneType
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52,296
flexget.manager
initialize
Load plugins, database, and config. Also initializes (but does not start) the task queue and ipc server. This should only be called after obtaining a lock.
def initialize(self) -> None: """ Load plugins, database, and config. Also initializes (but does not start) the task queue and ipc server. This should only be called after obtaining a lock. """ if self.initialized: raise RuntimeError('Cannot call initialize on an already initialized manager.') plugin.load_plugins( extra_plugins=[os.path.join(self.config_base, 'plugins')], extra_components=[os.path.join(self.config_base, 'components')], ) # Reparse CLI options now that plugins are loaded self.options = get_parser().parse_args(self.args) self.task_queue = TaskQueue() self.ipc_server = IPCServer(self, self.options.ipc_port) self.setup_yaml() self.init_sqlalchemy() fire_event('manager.initialize', self) try: self.load_config() except ValueError as e: logger.critical('Failed to load config file: {}', e.args[0]) raise # cannot be imported at module level because of circular references from flexget.utils.simple_persistence import SimplePersistence self.persist = SimplePersistence('manager') if db_schema.upgrade_required(): logger.info('Database upgrade is required. Attempting now.') fire_event('manager.upgrade', self) if manager.db_upgraded: fire_event('manager.db_upgraded', self) fire_event('manager.startup', self) self.initialized = True
(self) -> NoneType
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52,297
flexget.manager
load_config
Loads the config file from disk, validates and activates it. :raises: `ValueError` if there is a problem loading the config file
def load_config( self, output_to_console: bool = True, config_file_hash: Optional[str] = None ) -> None: """ Loads the config file from disk, validates and activates it. :raises: `ValueError` if there is a problem loading the config file """ fire_event('manager.before_config_load', self) with open(self.config_path, encoding='utf-8') as f: try: raw_config = f.read() except UnicodeDecodeError: logger.critical('Config file must be UTF-8 encoded.') raise ValueError('Config file is not UTF-8 encoded') try: self.config_file_hash = config_file_hash or self.hash_config() config = yaml.safe_load(raw_config) or {} except yaml.YAMLError as e: msg = str(e).replace('\n', ' ') msg = ' '.join(msg.split()) logger.critical(msg) if output_to_console: print('') print('-' * 79) print(' Malformed configuration file (check messages above). Common reasons:') print('-' * 79) print('') print(' o Indentation error') print(' o Missing : from end of the line') print(' o Non ASCII characters (use UTF8)') print( ' o If text contains any of :[]{}% characters it must be single-quoted ' '(eg. value{1} should be \'value{1}\')\n' ) # Not very good practice but we get several kind of exceptions here, I'm not even sure all of them # At least: ReaderError, YmlScannerError (or something like that) if isinstance(e, yaml.MarkedYAMLError): lines = 0 if e.problem is not None: print(f' Reason: {e.problem}\n') if e.problem == 'mapping values are not allowed here': print(' ----> MOST LIKELY REASON: Missing : from end of the line!') print('') if e.context_mark is not None: print( f' Check configuration near line {e.context_mark.line}, column {e.context_mark.column}' ) lines += 1 if e.problem_mark is not None: print( f' Check configuration near line {e.problem_mark.line}, column {e.problem_mark.column}' ) lines += 1 if lines: print('') if lines == 1: print(' Fault is almost always in this or previous line\n') if lines == 2: print(' Fault is almost always in one of these lines or previous ones\n') # When --debug escalate to full stacktrace if self.options.debug or not output_to_console: raise raise ValueError('Config file is not valid YAML') # config loaded successfully logger.debug('config_name: {}', self.config_name) logger.debug('config_base: {}', self.config_base) # Install the newly loaded config self.update_config(config)
(self, output_to_console: bool = True, config_file_hash: Optional[str] = None) -> NoneType
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52,298
flexget.manager
matching_tasks
Create list of tasks to run, preserving order
def matching_tasks(self, task: str) -> Optional[List[str]]: """Create list of tasks to run, preserving order""" task_names = [t for t in self.tasks if fnmatch.fnmatchcase(str(t).lower(), task.lower())] if not task_names: raise ValueError(f'`{task}` does not match any tasks') return task_names
(self, task: str) -> Optional[List[str]]
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52,299
flexget.manager
parse_initial_options
Parse what we can from cli args before plugins are loaded.
@staticmethod def parse_initial_options(args: List[str]) -> argparse.Namespace: """Parse what we can from cli args before plugins are loaded.""" try: options = CoreArgumentParser().parse_known_args(args, do_help=False)[0] except ParserError as exc: try: # If a non-built-in command was used, we need to parse with a parser that # doesn't define the subparsers options = manager_parser.parse_known_args(args, do_help=False)[0] except ParserError: manager_parser.print_help() print(f'\nError: {exc.message}') sys.exit(1) return options
(args: List[str]) -> argparse.Namespace
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52,300
flexget.manager
release_lock
null
def release_lock(self) -> None: try: os.remove(self.lockfile) except OSError as e: if e.errno != errno.ENOENT: raise logger.debug(f'Lockfile {self.lockfile} not found') else: logger.debug(f'Removed {self.lockfile}')
(self) -> NoneType
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52,301
flexget.manager
save_config
Dumps current config to yaml config file
def save_config(self) -> None: """Dumps current config to yaml config file""" # TODO: Only keep x number of backups.. # Back up the user's current config before overwriting try: self.backup_config() except OSError: return with open(self.config_path, 'w') as config_file: config_file.write(yaml.dump(self.user_config, default_flow_style=False))
(self) -> NoneType
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52,302
flexget.manager
setup_yaml
Customize the yaml loader/dumper behavior
def setup_yaml(self) -> None: """Customize the yaml loader/dumper behavior""" # Represent OrderedDict as a regular dict (but don't sort it alphabetically) # This lets us order a dict in a yaml file for easier human consumption def represent_dict_order(self, data): return self.represent_mapping('tag:yaml.org,2002:map', data.items()) yaml.add_representer(collections.OrderedDict, represent_dict_order) # Set up the dumper to increase the indent for lists def increase_indent_wrapper(func): def increase_indent(self, flow=False, indentless=False): func(self, flow, False) return increase_indent yaml.Dumper.increase_indent = increase_indent_wrapper(yaml.Dumper.increase_indent) yaml.SafeDumper.increase_indent = increase_indent_wrapper(yaml.SafeDumper.increase_indent)
(self) -> NoneType
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52,303
flexget.manager
shutdown
Request manager shutdown. :param bool finish_queue: Should scheduler finish the task queue
def shutdown(self, finish_queue: bool = True) -> None: """ Request manager shutdown. :param bool finish_queue: Should scheduler finish the task queue """ if not self.initialized: raise RuntimeError('Cannot shutdown manager that was never initialized.') fire_event('manager.shutdown_requested', self) self.task_queue.shutdown(finish_queue)
(self, finish_queue: bool = True) -> NoneType
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52,304
flexget.manager
start
Starting point when executing from commandline, dispatch execution to correct destination. If there is a FlexGet process with an ipc server already running, the command will be sent there for execution and results will be streamed back. If not, this will attempt to obtain a lock, initialize the manager, and run the command here.
def start(self) -> None: """ Starting point when executing from commandline, dispatch execution to correct destination. If there is a FlexGet process with an ipc server already running, the command will be sent there for execution and results will be streamed back. If not, this will attempt to obtain a lock, initialize the manager, and run the command here. """ # If another process is started, send the execution to the running process ipc_info = self.check_ipc_info() # If we are connecting to a running daemon, we don't want to log to the log file, # the daemon is already handling that. if ipc_info: console( 'There is a FlexGet process already running for this config, sending execution there.' ) logger.debug('Sending command to running FlexGet process: {}', self.args) try: client = IPCClient(ipc_info['port'], ipc_info['password']) except ValueError as e: logger.error(e) else: try: client.handle_cli(self.args) except KeyboardInterrupt: logger.error( 'Disconnecting from daemon due to ctrl-c. Executions will still continue in the ' 'background.' ) except EOFError: logger.error('Connection from daemon was severed.') return if self.options.test: logger.info('Test mode, creating a copy from database ...') db_test_filename = os.path.join(self.config_base, f'test-{self.config_name}.sqlite') if os.path.exists(self.db_filename): shutil.copy(self.db_filename, db_test_filename) logger.info('Test database created') self.db_filename = db_test_filename # No running process, we start our own to handle command with self.acquire_lock(): self.initialize() self.handle_cli() self._shutdown()
(self) -> NoneType
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52,305
flexget.manager
update_config
Provide a new config for the manager to use. :raises: `ValueError` and rolls back to previous config if the provided config is not valid.
def update_config(self, config: dict) -> None: """ Provide a new config for the manager to use. :raises: `ValueError` and rolls back to previous config if the provided config is not valid. """ new_user_config = config old_config = self.config try: self.config = self.validate_config(config) except ConfigError as e: for error in getattr(e, 'errors', []): logger.critical('[{}] {}', error.json_pointer, error.message) logger.debug('invalid config, rolling back') self.config = old_config raise logger.debug('New config data loaded.') self.user_config = copy.deepcopy(new_user_config) fire_event('manager.config_updated', self)
(self, config: dict) -> NoneType
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52,306
flexget.manager
validate_config
Check all root level keywords are valid. Config may be modified by before_config_validate hooks. Modified config will be returned. :param config: Config to check. If not provided, current manager config will be checked. :raises: `ValueError` when config fails validation. There will be an `errors` attribute with the schema errors. :returns: Final validated config.
def validate_config(self, config: Optional[dict] = None) -> dict: """ Check all root level keywords are valid. Config may be modified by before_config_validate hooks. Modified config will be returned. :param config: Config to check. If not provided, current manager config will be checked. :raises: `ValueError` when config fails validation. There will be an `errors` attribute with the schema errors. :returns: Final validated config. """ conf = config if config else self.config conf = fire_event('manager.before_config_validate', conf, self) errors = config_schema.process_config(conf) if errors: err = ConfigError('Did not pass schema validation.') err.errors = errors raise err else: return conf
(self, config: Optional[dict] = None) -> dict
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52,307
flexget.manager
write_lock
null
def write_lock(self, ipc_info: Optional[dict] = None) -> None: assert self._has_lock with open(self.lockfile, 'w', encoding='utf-8') as f: f.write(f'PID: {os.getpid()}\n') if ipc_info: for key in sorted(ipc_info): f.write(f'{key}: {ipc_info[key]}\n')
(self, ipc_info: Optional[dict] = None) -> NoneType
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52,308
flexget
_is_debug
null
def _is_debug() -> bool: return any( arg in ['debug', '--debug', '--loglevel=trace', '--loglevel=debug'] for arg in [a.lower() for a in sys.argv] )
() -> bool
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52,317
flexget
main
Main entry point for Command Line Interface
def main(args: Optional[Sequence[str]] = None): """Main entry point for Command Line Interface""" if args is None: args = sys.argv[1:] try: log.initialize() try: manager = Manager(args) except (OSError, ValueError) as e: options = Manager.parse_initial_options(args) log.start(level=options.loglevel, to_file=False) if _is_debug(): import traceback traceback.print_exc() else: print('Could not instantiate manager: %s' % e, file=sys.stderr) sys.exit(1) else: log.start( manager.log_filename, manager.options.loglevel, to_file=manager.check_ipc_info() is None, to_console=not manager.options.cron, ) try: if manager.options.profile: try: import cProfile as profile except ImportError: import profile profile.runctx( 'manager.start()', globals(), locals(), os.path.join(manager.config_base, manager.options.profile), ) else: manager.start() except (OSError, ValueError) as e: if _is_debug(): import traceback traceback.print_exc() else: print('Could not start manager: %s' % e, file=sys.stderr) sys.exit(1) except KeyboardInterrupt: if _is_debug(): import traceback traceback.print_exc() print('Killed with keyboard interrupt.', file=sys.stderr) sys.exit(1)
(args: Optional[Sequence[str]] = None)
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52,329
pgeocode
GeoDistance
Distance calculation from a city name or a postal code Parameters ---------- data_path: str path to the dataset error: str, default='ignore' how to handle not found elements. One of 'ignore' (return NaNs), 'error' (raise an exception), 'nearest' (find from nearest valid points)
class GeoDistance(Nominatim): """Distance calculation from a city name or a postal code Parameters ---------- data_path: str path to the dataset error: str, default='ignore' how to handle not found elements. One of 'ignore' (return NaNs), 'error' (raise an exception), 'nearest' (find from nearest valid points) """ def __init__(self, country: str = "fr", errors: str = "ignore"): super().__init__(country) def query_postal_code(self, x, y): """Get distance (in km) between postal codes Parameters ---------- x: array, list or int a list of postal codes y: array, list or int a list of postal codes Returns ------- d : array or int the calculated distances """ if isinstance(x, int): x = str(x) if isinstance(y, int): y = str(y) if isinstance(x, str): x = [x] single_x_entry = True else: single_x_entry = False df_x = super().query_postal_code(x) if isinstance(y, str): y = [y] single_y_entry = True else: single_y_entry = False df_y = super().query_postal_code(y) x_coords = df_x[["latitude", "longitude"]].values y_coords = df_y[["latitude", "longitude"]].values if x_coords.shape[0] == y_coords.shape[0]: pass elif x_coords.shape[0] == 1: x_coords = np.repeat(x_coords, y_coords.shape[0], axis=0) elif y_coords.shape[0] == 1: y_coords = np.repeat(y_coords, x_coords.shape[0], axis=0) else: raise ValueError("x and y must have the same number of elements") dist = haversine_distance(x_coords, y_coords) if single_x_entry and single_y_entry: return dist[0] else: return dist
(country: str = 'fr', errors: str = 'ignore')
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52,330
pgeocode
__init__
null
def __init__(self, country: str = "fr", errors: str = "ignore"): super().__init__(country)
(self, country: str = 'fr', errors: str = 'ignore')
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52,331
pgeocode
_fuzzy_search
null
def _fuzzy_search(self, text: str, col: str, threshold: float = 80) -> pd.DataFrame: try: # thefuzz is not required to install pgeocode, # it is an optional dependency for enabling fuzzy search from thefuzz import fuzz except ModuleNotFoundError as err: raise ModuleNotFoundError( "Cannot use fuzzy search without 'thefuzz' package. " "It can be installed with: pip install thefuzz[speedup]" ) from err fuzzy_scores = self._data[col].apply(lambda x: fuzz.ratio(str(x), text)) return self._data[fuzzy_scores >= threshold]
(self, text: str, col: str, threshold: float = 80) -> pandas.core.frame.DataFrame
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52,332
pgeocode
_get_data
Load the data from disk; otherwise download and save it
@staticmethod def _get_data(country: str) -> tuple[str, pd.DataFrame]: """Load the data from disk; otherwise download and save it""" data_path = os.path.join(STORAGE_DIR, country.upper() + ".txt") if os.path.exists(data_path): data = pd.read_csv( data_path, dtype={"postal_code": str}, na_values=NA_VALUES, keep_default_na=False, ) else: download_urls = [val.format(country=country) for val in DOWNLOAD_URL] with _open_extract_cycle_url(download_urls, country) as fh: data = pd.read_csv( fh, sep="\t", header=None, names=DATA_FIELDS, dtype={"postal_code": str}, na_values=NA_VALUES, keep_default_na=False, ) os.makedirs(STORAGE_DIR, exist_ok=True) data.to_csv(data_path, index=None) return data_path, data
(country: str) -> tuple[str, pandas.core.frame.DataFrame]
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52,333
pgeocode
_index_postal_codes
Create a dataframe with unique postal codes
def _index_postal_codes(self) -> pd.DataFrame: """Create a dataframe with unique postal codes""" data_path_unique = self._data_path.replace(".txt", "-index.txt") if os.path.exists(data_path_unique): data_unique = pd.read_csv( data_path_unique, dtype={"postal_code": str}, na_values=NA_VALUES, keep_default_na=False, ) else: # group together places with the same postal code df_unique_cp_group = self._data.groupby("postal_code") data_unique = df_unique_cp_group[["latitude", "longitude"]].mean() valid_keys = set(DATA_FIELDS).difference( ["place_name", "latitude", "longitude", "postal_code"] ) data_unique["place_name"] = df_unique_cp_group["place_name"].apply( lambda x: ", ".join([str(el) for el in x]) ) for key in valid_keys: data_unique[key] = df_unique_cp_group[key].first() data_unique = data_unique.reset_index()[DATA_FIELDS] data_unique.to_csv(data_path_unique, index=None) return data_unique
(self) -> pandas.core.frame.DataFrame
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52,334
pgeocode
_normalize_postal_code
Normalize postal codes to the values contained in the database For instance, take into account only first letters when applicable. Takes in a pd.DataFrame
def _normalize_postal_code(self, codes: pd.DataFrame) -> pd.DataFrame: """Normalize postal codes to the values contained in the database For instance, take into account only first letters when applicable. Takes in a pd.DataFrame """ codes["postal_code"] = codes.postal_code.str.upper() if self.country in ["GB", "IE", "CA"]: codes["postal_code"] = codes.postal_code.str.split().str.get(0) else: pass return codes
(self, codes: pandas.core.frame.DataFrame) -> pandas.core.frame.DataFrame
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52,335
pgeocode
_str_contains_search
null
def _str_contains_search(self, text: str, col: str) -> pd.DataFrame: match_mask = self._data[col].str.lower().str.contains(text.lower()) match_mask.fillna(False, inplace=True) return self._data[match_mask]
(self, text: str, col: str) -> pandas.core.frame.DataFrame
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52,336
pgeocode
query_location
Get location information from a place name Parameters ---------- name: str string containing place names to search for. The search is case insensitive. top_k: int maximum number of results (rows in DataFrame) to return fuzzy_threshold: Optional[int] threshold (lower bound) for fuzzy string search for finding the place name, default None (=no fuzzy search) pass an integer value between 70 and 100 to enable fuzzy search (the lower the value, the more results) requires 'thefuzz' package to be installed: pip install thefuzz[speedup] (for more info: https://github.com/seatgeek/thefuzz) col: str which column in the internal data to search through Returns ------- df : pandas.DataFrame a DataFrame with the relevant information for all matching place names (or empty if no match was found)
def query_location( self, name: str, top_k: int = 100, fuzzy_threshold: int | None = None, col: str = "place_name", ) -> pd.DataFrame: """Get location information from a place name Parameters ---------- name: str string containing place names to search for. The search is case insensitive. top_k: int maximum number of results (rows in DataFrame) to return fuzzy_threshold: Optional[int] threshold (lower bound) for fuzzy string search for finding the place name, default None (=no fuzzy search) pass an integer value between 70 and 100 to enable fuzzy search (the lower the value, the more results) requires 'thefuzz' package to be installed: pip install thefuzz[speedup] (for more info: https://github.com/seatgeek/thefuzz) col: str which column in the internal data to search through Returns ------- df : pandas.DataFrame a DataFrame with the relevant information for all matching place names (or empty if no match was found) """ contains_matches = self._str_contains_search(name, col) if len(contains_matches) > 0: return contains_matches.iloc[:top_k] if fuzzy_threshold is not None: fuzzy_matches = self._fuzzy_search(name, col, threshold=fuzzy_threshold) if len(fuzzy_matches) > 0: return fuzzy_matches.iloc[:top_k] return pd.DataFrame(columns=self._data.columns)
(self, name: str, top_k: int = 100, fuzzy_threshold: Optional[int] = None, col: str = 'place_name') -> pandas.core.frame.DataFrame
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52,337
pgeocode
query_postal_code
Get distance (in km) between postal codes Parameters ---------- x: array, list or int a list of postal codes y: array, list or int a list of postal codes Returns ------- d : array or int the calculated distances
def query_postal_code(self, x, y): """Get distance (in km) between postal codes Parameters ---------- x: array, list or int a list of postal codes y: array, list or int a list of postal codes Returns ------- d : array or int the calculated distances """ if isinstance(x, int): x = str(x) if isinstance(y, int): y = str(y) if isinstance(x, str): x = [x] single_x_entry = True else: single_x_entry = False df_x = super().query_postal_code(x) if isinstance(y, str): y = [y] single_y_entry = True else: single_y_entry = False df_y = super().query_postal_code(y) x_coords = df_x[["latitude", "longitude"]].values y_coords = df_y[["latitude", "longitude"]].values if x_coords.shape[0] == y_coords.shape[0]: pass elif x_coords.shape[0] == 1: x_coords = np.repeat(x_coords, y_coords.shape[0], axis=0) elif y_coords.shape[0] == 1: y_coords = np.repeat(y_coords, x_coords.shape[0], axis=0) else: raise ValueError("x and y must have the same number of elements") dist = haversine_distance(x_coords, y_coords) if single_x_entry and single_y_entry: return dist[0] else: return dist
(self, x, y)
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52,338
pgeocode
Nominatim
Query geographical location from a city name or a postal code Parameters ---------- country: str, default='fr' country code. See the documentation for a list of supported countries. unique: bool, default=True Create unique postcode index, merging all places with the same postcode into a single entry
class Nominatim: """Query geographical location from a city name or a postal code Parameters ---------- country: str, default='fr' country code. See the documentation for a list of supported countries. unique: bool, default=True Create unique postcode index, merging all places with the same postcode into a single entry """ def __init__(self, country: str = "fr", unique: bool = True): country = country.upper() if country not in COUNTRIES_VALID: raise ValueError( f"country={country} is not a known country code. " "See the README for a list of supported " "countries" ) if country == "AR": warnings.warn( "The Argentina data file contains 4-digit postal " "codes which were replaced with a new system " "in 1999." ) self.country = country self._data_path, self._data = self._get_data(country) if unique: self._data_frame = self._index_postal_codes() else: self._data_frame = self._data self.unique = unique @staticmethod def _get_data(country: str) -> tuple[str, pd.DataFrame]: """Load the data from disk; otherwise download and save it""" data_path = os.path.join(STORAGE_DIR, country.upper() + ".txt") if os.path.exists(data_path): data = pd.read_csv( data_path, dtype={"postal_code": str}, na_values=NA_VALUES, keep_default_na=False, ) else: download_urls = [val.format(country=country) for val in DOWNLOAD_URL] with _open_extract_cycle_url(download_urls, country) as fh: data = pd.read_csv( fh, sep="\t", header=None, names=DATA_FIELDS, dtype={"postal_code": str}, na_values=NA_VALUES, keep_default_na=False, ) os.makedirs(STORAGE_DIR, exist_ok=True) data.to_csv(data_path, index=None) return data_path, data def _index_postal_codes(self) -> pd.DataFrame: """Create a dataframe with unique postal codes""" data_path_unique = self._data_path.replace(".txt", "-index.txt") if os.path.exists(data_path_unique): data_unique = pd.read_csv( data_path_unique, dtype={"postal_code": str}, na_values=NA_VALUES, keep_default_na=False, ) else: # group together places with the same postal code df_unique_cp_group = self._data.groupby("postal_code") data_unique = df_unique_cp_group[["latitude", "longitude"]].mean() valid_keys = set(DATA_FIELDS).difference( ["place_name", "latitude", "longitude", "postal_code"] ) data_unique["place_name"] = df_unique_cp_group["place_name"].apply( lambda x: ", ".join([str(el) for el in x]) ) for key in valid_keys: data_unique[key] = df_unique_cp_group[key].first() data_unique = data_unique.reset_index()[DATA_FIELDS] data_unique.to_csv(data_path_unique, index=None) return data_unique def _normalize_postal_code(self, codes: pd.DataFrame) -> pd.DataFrame: """Normalize postal codes to the values contained in the database For instance, take into account only first letters when applicable. Takes in a pd.DataFrame """ codes["postal_code"] = codes.postal_code.str.upper() if self.country in ["GB", "IE", "CA"]: codes["postal_code"] = codes.postal_code.str.split().str.get(0) else: pass return codes def query_postal_code(self, codes): """Get locations information from postal codes Parameters ---------- codes: array, list or int an array of strings containing postal codes Returns ------- df : pandas.DataFrame a pandas.DataFrame with the relevant information """ if isinstance(codes, int): codes = str(codes) if isinstance(codes, str): codes = [codes] single_entry = True else: single_entry = False if not isinstance(codes, pd.DataFrame): codes = pd.DataFrame(codes, columns=["postal_code"]) codes = self._normalize_postal_code(codes) response = pd.merge(codes, self._data_frame, on="postal_code", how="left") if self.unique and single_entry: response = response.iloc[0] return response def query_location( self, name: str, top_k: int = 100, fuzzy_threshold: int | None = None, col: str = "place_name", ) -> pd.DataFrame: """Get location information from a place name Parameters ---------- name: str string containing place names to search for. The search is case insensitive. top_k: int maximum number of results (rows in DataFrame) to return fuzzy_threshold: Optional[int] threshold (lower bound) for fuzzy string search for finding the place name, default None (=no fuzzy search) pass an integer value between 70 and 100 to enable fuzzy search (the lower the value, the more results) requires 'thefuzz' package to be installed: pip install thefuzz[speedup] (for more info: https://github.com/seatgeek/thefuzz) col: str which column in the internal data to search through Returns ------- df : pandas.DataFrame a DataFrame with the relevant information for all matching place names (or empty if no match was found) """ contains_matches = self._str_contains_search(name, col) if len(contains_matches) > 0: return contains_matches.iloc[:top_k] if fuzzy_threshold is not None: fuzzy_matches = self._fuzzy_search(name, col, threshold=fuzzy_threshold) if len(fuzzy_matches) > 0: return fuzzy_matches.iloc[:top_k] return pd.DataFrame(columns=self._data.columns) def _str_contains_search(self, text: str, col: str) -> pd.DataFrame: match_mask = self._data[col].str.lower().str.contains(text.lower()) match_mask.fillna(False, inplace=True) return self._data[match_mask] def _fuzzy_search(self, text: str, col: str, threshold: float = 80) -> pd.DataFrame: try: # thefuzz is not required to install pgeocode, # it is an optional dependency for enabling fuzzy search from thefuzz import fuzz except ModuleNotFoundError as err: raise ModuleNotFoundError( "Cannot use fuzzy search without 'thefuzz' package. " "It can be installed with: pip install thefuzz[speedup]" ) from err fuzzy_scores = self._data[col].apply(lambda x: fuzz.ratio(str(x), text)) return self._data[fuzzy_scores >= threshold]
(country: str = 'fr', unique: bool = True)
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52,339
pgeocode
__init__
null
def __init__(self, country: str = "fr", unique: bool = True): country = country.upper() if country not in COUNTRIES_VALID: raise ValueError( f"country={country} is not a known country code. " "See the README for a list of supported " "countries" ) if country == "AR": warnings.warn( "The Argentina data file contains 4-digit postal " "codes which were replaced with a new system " "in 1999." ) self.country = country self._data_path, self._data = self._get_data(country) if unique: self._data_frame = self._index_postal_codes() else: self._data_frame = self._data self.unique = unique
(self, country: str = 'fr', unique: bool = True)
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52,346
pgeocode
query_postal_code
Get locations information from postal codes Parameters ---------- codes: array, list or int an array of strings containing postal codes Returns ------- df : pandas.DataFrame a pandas.DataFrame with the relevant information
def query_postal_code(self, codes): """Get locations information from postal codes Parameters ---------- codes: array, list or int an array of strings containing postal codes Returns ------- df : pandas.DataFrame a pandas.DataFrame with the relevant information """ if isinstance(codes, int): codes = str(codes) if isinstance(codes, str): codes = [codes] single_entry = True else: single_entry = False if not isinstance(codes, pd.DataFrame): codes = pd.DataFrame(codes, columns=["postal_code"]) codes = self._normalize_postal_code(codes) response = pd.merge(codes, self._data_frame, on="postal_code", how="left") if self.unique and single_entry: response = response.iloc[0] return response
(self, codes)
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52,347
zipfile
ZipFile
Class with methods to open, read, write, close, list zip files. z = ZipFile(file, mode="r", compression=ZIP_STORED, allowZip64=True, compresslevel=None) file: Either the path to the file, or a file-like object. If it is a path, the file will be opened and closed by ZipFile. mode: The mode can be either read 'r', write 'w', exclusive create 'x', or append 'a'. compression: ZIP_STORED (no compression), ZIP_DEFLATED (requires zlib), ZIP_BZIP2 (requires bz2) or ZIP_LZMA (requires lzma). allowZip64: if True ZipFile will create files with ZIP64 extensions when needed, otherwise it will raise an exception when this would be necessary. compresslevel: None (default for the given compression type) or an integer specifying the level to pass to the compressor. When using ZIP_STORED or ZIP_LZMA this keyword has no effect. When using ZIP_DEFLATED integers 0 through 9 are accepted. When using ZIP_BZIP2 integers 1 through 9 are accepted.
class ZipFile: """ Class with methods to open, read, write, close, list zip files. z = ZipFile(file, mode="r", compression=ZIP_STORED, allowZip64=True, compresslevel=None) file: Either the path to the file, or a file-like object. If it is a path, the file will be opened and closed by ZipFile. mode: The mode can be either read 'r', write 'w', exclusive create 'x', or append 'a'. compression: ZIP_STORED (no compression), ZIP_DEFLATED (requires zlib), ZIP_BZIP2 (requires bz2) or ZIP_LZMA (requires lzma). allowZip64: if True ZipFile will create files with ZIP64 extensions when needed, otherwise it will raise an exception when this would be necessary. compresslevel: None (default for the given compression type) or an integer specifying the level to pass to the compressor. When using ZIP_STORED or ZIP_LZMA this keyword has no effect. When using ZIP_DEFLATED integers 0 through 9 are accepted. When using ZIP_BZIP2 integers 1 through 9 are accepted. """ fp = None # Set here since __del__ checks it _windows_illegal_name_trans_table = None def __init__(self, file, mode="r", compression=ZIP_STORED, allowZip64=True, compresslevel=None, *, strict_timestamps=True): """Open the ZIP file with mode read 'r', write 'w', exclusive create 'x', or append 'a'.""" if mode not in ('r', 'w', 'x', 'a'): raise ValueError("ZipFile requires mode 'r', 'w', 'x', or 'a'") _check_compression(compression) self._allowZip64 = allowZip64 self._didModify = False self.debug = 0 # Level of printing: 0 through 3 self.NameToInfo = {} # Find file info given name self.filelist = [] # List of ZipInfo instances for archive self.compression = compression # Method of compression self.compresslevel = compresslevel self.mode = mode self.pwd = None self._comment = b'' self._strict_timestamps = strict_timestamps # Check if we were passed a file-like object if isinstance(file, os.PathLike): file = os.fspath(file) if isinstance(file, str): # No, it's a filename self._filePassed = 0 self.filename = file modeDict = {'r' : 'rb', 'w': 'w+b', 'x': 'x+b', 'a' : 'r+b', 'r+b': 'w+b', 'w+b': 'wb', 'x+b': 'xb'} filemode = modeDict[mode] while True: try: self.fp = io.open(file, filemode) except OSError: if filemode in modeDict: filemode = modeDict[filemode] continue raise break else: self._filePassed = 1 self.fp = file self.filename = getattr(file, 'name', None) self._fileRefCnt = 1 self._lock = threading.RLock() self._seekable = True self._writing = False try: if mode == 'r': self._RealGetContents() elif mode in ('w', 'x'): # set the modified flag so central directory gets written # even if no files are added to the archive self._didModify = True try: self.start_dir = self.fp.tell() except (AttributeError, OSError): self.fp = _Tellable(self.fp) self.start_dir = 0 self._seekable = False else: # Some file-like objects can provide tell() but not seek() try: self.fp.seek(self.start_dir) except (AttributeError, OSError): self._seekable = False elif mode == 'a': try: # See if file is a zip file self._RealGetContents() # seek to start of directory and overwrite self.fp.seek(self.start_dir) except BadZipFile: # file is not a zip file, just append self.fp.seek(0, 2) # set the modified flag so central directory gets written # even if no files are added to the archive self._didModify = True self.start_dir = self.fp.tell() else: raise ValueError("Mode must be 'r', 'w', 'x', or 'a'") except: fp = self.fp self.fp = None self._fpclose(fp) raise def __enter__(self): return self def __exit__(self, type, value, traceback): self.close() def __repr__(self): result = ['<%s.%s' % (self.__class__.__module__, self.__class__.__qualname__)] if self.fp is not None: if self._filePassed: result.append(' file=%r' % self.fp) elif self.filename is not None: result.append(' filename=%r' % self.filename) result.append(' mode=%r' % self.mode) else: result.append(' [closed]') result.append('>') return ''.join(result) def _RealGetContents(self): """Read in the table of contents for the ZIP file.""" fp = self.fp try: endrec = _EndRecData(fp) except OSError: raise BadZipFile("File is not a zip file") if not endrec: raise BadZipFile("File is not a zip file") if self.debug > 1: print(endrec) size_cd = endrec[_ECD_SIZE] # bytes in central directory offset_cd = endrec[_ECD_OFFSET] # offset of central directory self._comment = endrec[_ECD_COMMENT] # archive comment # "concat" is zero, unless zip was concatenated to another file concat = endrec[_ECD_LOCATION] - size_cd - offset_cd if endrec[_ECD_SIGNATURE] == stringEndArchive64: # If Zip64 extension structures are present, account for them concat -= (sizeEndCentDir64 + sizeEndCentDir64Locator) if self.debug > 2: inferred = concat + offset_cd print("given, inferred, offset", offset_cd, inferred, concat) # self.start_dir: Position of start of central directory self.start_dir = offset_cd + concat if self.start_dir < 0: raise BadZipFile("Bad offset for central directory") fp.seek(self.start_dir, 0) data = fp.read(size_cd) fp = io.BytesIO(data) total = 0 while total < size_cd: centdir = fp.read(sizeCentralDir) if len(centdir) != sizeCentralDir: raise BadZipFile("Truncated central directory") centdir = struct.unpack(structCentralDir, centdir) if centdir[_CD_SIGNATURE] != stringCentralDir: raise BadZipFile("Bad magic number for central directory") if self.debug > 2: print(centdir) filename = fp.read(centdir[_CD_FILENAME_LENGTH]) flags = centdir[5] if flags & 0x800: # UTF-8 file names extension filename = filename.decode('utf-8') else: # Historical ZIP filename encoding filename = filename.decode('cp437') # Create ZipInfo instance to store file information x = ZipInfo(filename) x.extra = fp.read(centdir[_CD_EXTRA_FIELD_LENGTH]) x.comment = fp.read(centdir[_CD_COMMENT_LENGTH]) x.header_offset = centdir[_CD_LOCAL_HEADER_OFFSET] (x.create_version, x.create_system, x.extract_version, x.reserved, x.flag_bits, x.compress_type, t, d, x.CRC, x.compress_size, x.file_size) = centdir[1:12] if x.extract_version > MAX_EXTRAC
(file, mode='r', compression=0, allowZip64=True, compresslevel=None, *, strict_timestamps=True)
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52,348
zipfile
_RealGetContents
Read in the table of contents for the ZIP file.
def _RealGetContents(self): """Read in the table of contents for the ZIP file.""" fp = self.fp try: endrec = _EndRecData(fp) except OSError: raise BadZipFile("File is not a zip file") if not endrec: raise BadZipFile("File is not a zip file") if self.debug > 1: print(endrec) size_cd = endrec[_ECD_SIZE] # bytes in central directory offset_cd = endrec[_ECD_OFFSET] # offset of central directory self._comment = endrec[_ECD_COMMENT] # archive comment # "concat" is zero, unless zip was concatenated to another file concat = endrec[_ECD_LOCATION] - size_cd - offset_cd if endrec[_ECD_SIGNATURE] == stringEndArchive64: # If Zip64 extension structures are present, account for them concat -= (sizeEndCentDir64 + sizeEndCentDir64Locator) if self.debug > 2: inferred = concat + offset_cd print("given, inferred, offset", offset_cd, inferred, concat) # self.start_dir: Position of start of central directory self.start_dir = offset_cd + concat if self.start_dir < 0: raise BadZipFile("Bad offset for central directory") fp.seek(self.start_dir, 0) data = fp.read(size_cd) fp = io.BytesIO(data) total = 0 while total < size_cd: centdir = fp.read(sizeCentralDir) if len(centdir) != sizeCentralDir: raise BadZipFile("Truncated central directory") centdir = struct.unpack(structCentralDir, centdir) if centdir[_CD_SIGNATURE] != stringCentralDir: raise BadZipFile("Bad magic number for central directory") if self.debug > 2: print(centdir) filename = fp.read(centdir[_CD_FILENAME_LENGTH]) flags = centdir[5] if flags & 0x800: # UTF-8 file names extension filename = filename.decode('utf-8') else: # Historical ZIP filename encoding filename = filename.decode('cp437') # Create ZipInfo instance to store file information x = ZipInfo(filename) x.extra = fp.read(centdir[_CD_EXTRA_FIELD_LENGTH]) x.comment = fp.read(centdir[_CD_COMMENT_LENGTH]) x.header_offset = centdir[_CD_LOCAL_HEADER_OFFSET] (x.create_version, x.create_system, x.extract_version, x.reserved, x.flag_bits, x.compress_type, t, d, x.CRC, x.compress_size, x.file_size) = centdir[1:12] if x.extract_version > MAX_EXTRACT_VERSION: raise NotImplementedError("zip file version %.1f" % (x.extract_version / 10)) x.volume, x.internal_attr, x.external_attr = centdir[15:18] # Convert date/time code to (year, month, day, hour, min, sec) x._raw_time = t x.date_time = ( (d>>9)+1980, (d>>5)&0xF, d&0x1F, t>>11, (t>>5)&0x3F, (t&0x1F) * 2 ) x._decodeExtra() x.header_offset = x.header_offset + concat self.filelist.append(x) self.NameToInfo[x.filename] = x # update total bytes read from central directory total = (total + sizeCentralDir + centdir[_CD_FILENAME_LENGTH] + centdir[_CD_EXTRA_FIELD_LENGTH] + centdir[_CD_COMMENT_LENGTH]) if self.debug > 2: print("total", total) end_offset = self.start_dir for zinfo in sorted(self.filelist, key=lambda zinfo: zinfo.header_offset, reverse=True): zinfo._end_offset = end_offset end_offset = zinfo.header_offset
(self)
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52,352
zipfile
__init__
Open the ZIP file with mode read 'r', write 'w', exclusive create 'x', or append 'a'.
def __init__(self, file, mode="r", compression=ZIP_STORED, allowZip64=True, compresslevel=None, *, strict_timestamps=True): """Open the ZIP file with mode read 'r', write 'w', exclusive create 'x', or append 'a'.""" if mode not in ('r', 'w', 'x', 'a'): raise ValueError("ZipFile requires mode 'r', 'w', 'x', or 'a'") _check_compression(compression) self._allowZip64 = allowZip64 self._didModify = False self.debug = 0 # Level of printing: 0 through 3 self.NameToInfo = {} # Find file info given name self.filelist = [] # List of ZipInfo instances for archive self.compression = compression # Method of compression self.compresslevel = compresslevel self.mode = mode self.pwd = None self._comment = b'' self._strict_timestamps = strict_timestamps # Check if we were passed a file-like object if isinstance(file, os.PathLike): file = os.fspath(file) if isinstance(file, str): # No, it's a filename self._filePassed = 0 self.filename = file modeDict = {'r' : 'rb', 'w': 'w+b', 'x': 'x+b', 'a' : 'r+b', 'r+b': 'w+b', 'w+b': 'wb', 'x+b': 'xb'} filemode = modeDict[mode] while True: try: self.fp = io.open(file, filemode) except OSError: if filemode in modeDict: filemode = modeDict[filemode] continue raise break else: self._filePassed = 1 self.fp = file self.filename = getattr(file, 'name', None) self._fileRefCnt = 1 self._lock = threading.RLock() self._seekable = True self._writing = False try: if mode == 'r': self._RealGetContents() elif mode in ('w', 'x'): # set the modified flag so central directory gets written # even if no files are added to the archive self._didModify = True try: self.start_dir = self.fp.tell() except (AttributeError, OSError): self.fp = _Tellable(self.fp) self.start_dir = 0 self._seekable = False else: # Some file-like objects can provide tell() but not seek() try: self.fp.seek(self.start_dir) except (AttributeError, OSError): self._seekable = False elif mode == 'a': try: # See if file is a zip file self._RealGetContents() # seek to start of directory and overwrite self.fp.seek(self.start_dir) except BadZipFile: # file is not a zip file, just append self.fp.seek(0, 2) # set the modified flag so central directory gets written # even if no files are added to the archive self._didModify = True self.start_dir = self.fp.tell() else: raise ValueError("Mode must be 'r', 'w', 'x', or 'a'") except: fp = self.fp self.fp = None self._fpclose(fp) raise
(self, file, mode='r', compression=0, allowZip64=True, compresslevel=None, *, strict_timestamps=True)
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52,354
zipfile
_extract_member
Extract the ZipInfo object 'member' to a physical file on the path targetpath.
def _extract_member(self, member, targetpath, pwd): """Extract the ZipInfo object 'member' to a physical file on the path targetpath. """ if not isinstance(member, ZipInfo): member = self.getinfo(member) # build the destination pathname, replacing # forward slashes to platform specific separators. arcname = member.filename.replace('/', os.path.sep) if os.path.altsep: arcname = arcname.replace(os.path.altsep, os.path.sep) # interpret absolute pathname as relative, remove drive letter or # UNC path, redundant separators, "." and ".." components. arcname = os.path.splitdrive(arcname)[1] invalid_path_parts = ('', os.path.curdir, os.path.pardir) arcname = os.path.sep.join(x for x in arcname.split(os.path.sep) if x not in invalid_path_parts) if os.path.sep == '\\': # filter illegal characters on Windows arcname = self._sanitize_windows_name(arcname, os.path.sep) targetpath = os.path.join(targetpath, arcname) targetpath = os.path.normpath(targetpath) # Create all upper directories if necessary. upperdirs = os.path.dirname(targetpath) if upperdirs and not os.path.exists(upperdirs): os.makedirs(upperdirs) if member.is_dir(): if not os.path.isdir(targetpath): os.mkdir(targetpath) return targetpath with self.open(member, pwd=pwd) as source, \ open(targetpath, "wb") as target: shutil.copyfileobj(source, target) return targetpath
(self, member, targetpath, pwd)
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52,356
zipfile
_open_to_write
null
def _open_to_write(self, zinfo, force_zip64=False): if force_zip64 and not self._allowZip64: raise ValueError( "force_zip64 is True, but allowZip64 was False when opening " "the ZIP file." ) if self._writing: raise ValueError("Can't write to the ZIP file while there is " "another write handle open on it. " "Close the first handle before opening another.") # Size and CRC are overwritten with correct data after processing the file zinfo.compress_size = 0 zinfo.CRC = 0 zinfo.flag_bits = 0x00 if zinfo.compress_type == ZIP_LZMA: # Compressed data includes an end-of-stream (EOS) marker zinfo.flag_bits |= 0x02 if not self._seekable: zinfo.flag_bits |= 0x08 if not zinfo.external_attr: zinfo.external_attr = 0o600 << 16 # permissions: ?rw------- # Compressed size can be larger than uncompressed size zip64 = self._allowZip64 and \ (force_zip64 or zinfo.file_size * 1.05 > ZIP64_LIMIT) if self._seekable: self.fp.seek(self.start_dir) zinfo.header_offset = self.fp.tell() self._writecheck(zinfo) self._didModify = True self.fp.write(zinfo.FileHeader(zip64)) self._writing = True return _ZipWriteFile(self, zinfo, zip64)
(self, zinfo, force_zip64=False)
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_write_end_record
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def _write_end_record(self): for zinfo in self.filelist: # write central directory dt = zinfo.date_time dosdate = (dt[0] - 1980) << 9 | dt[1] << 5 | dt[2] dostime = dt[3] << 11 | dt[4] << 5 | (dt[5] // 2) extra = [] if zinfo.file_size > ZIP64_LIMIT \ or zinfo.compress_size > ZIP64_LIMIT: extra.append(zinfo.file_size) extra.append(zinfo.compress_size) file_size = 0xffffffff compress_size = 0xffffffff else: file_size = zinfo.file_size compress_size = zinfo.compress_size if zinfo.header_offset > ZIP64_LIMIT: extra.append(zinfo.header_offset) header_offset = 0xffffffff else: header_offset = zinfo.header_offset extra_data = zinfo.extra min_version = 0 if extra: # Append a ZIP64 field to the extra's extra_data = _strip_extra(extra_data, (1,)) extra_data = struct.pack( '<HH' + 'Q'*len(extra), 1, 8*len(extra), *extra) + extra_data min_version = ZIP64_VERSION if zinfo.compress_type == ZIP_BZIP2: min_version = max(BZIP2_VERSION, min_version) elif zinfo.compress_type == ZIP_LZMA: min_version = max(LZMA_VERSION, min_version) extract_version = max(min_version, zinfo.extract_version) create_version = max(min_version, zinfo.create_version) filename, flag_bits = zinfo._encodeFilenameFlags() centdir = struct.pack(structCentralDir, stringCentralDir, create_version, zinfo.create_system, extract_version, zinfo.reserved, flag_bits, zinfo.compress_type, dostime, dosdate, zinfo.CRC, compress_size, file_size, len(filename), len(extra_data), len(zinfo.comment), 0, zinfo.internal_attr, zinfo.external_attr, header_offset) self.fp.write(centdir) self.fp.write(filename) self.fp.write(extra_data) self.fp.write(zinfo.comment) pos2 = self.fp.tell() # Write end-of-zip-archive record centDirCount = len(self.filelist) centDirSize = pos2 - self.start_dir centDirOffset = self.start_dir requires_zip64 = None if centDirCount > ZIP_FILECOUNT_LIMIT: requires_zip64 = "Files count" elif centDirOffset > ZIP64_LIMIT: requires_zip64 = "Central directory offset" elif centDirSize > ZIP64_LIMIT: requires_zip64 = "Central directory size" if requires_zip64: # Need to write the ZIP64 end-of-archive records if not self._allowZip64: raise LargeZipFile(requires_zip64 + " would require ZIP64 extensions") zip64endrec = struct.pack( structEndArchive64, stringEndArchive64, 44, 45, 45, 0, 0, centDirCount, centDirCount, centDirSize, centDirOffset) self.fp.write(zip64endrec) zip64locrec = struct.pack( structEndArchive64Locator, stringEndArchive64Locator, 0, pos2, 1) self.fp.write(zip64locrec) centDirCount = min(centDirCount, 0xFFFF) centDirSize = min(centDirSize, 0xFFFFFFFF) centDirOffset = min(centDirOffset, 0xFFFFFFFF) endrec = struct.pack(structEndArchive, stringEndArchive, 0, 0, centDirCount, centDirCount, centDirSize, centDirOffset, len(self._comment)) self.fp.write(endrec) self.fp.write(self._comment) if self.mode == "a": self.fp.truncate() self.fp.flush()
(self)
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52,360
zipfile
extract
Extract a member from the archive to the current working directory, using its full name. Its file information is extracted as accurately as possible. `member' may be a filename or a ZipInfo object. You can specify a different directory using `path'.
def extract(self, member, path=None, pwd=None): """Extract a member from the archive to the current working directory, using its full name. Its file information is extracted as accurately as possible. `member' may be a filename or a ZipInfo object. You can specify a different directory using `path'. """ if path is None: path = os.getcwd() else: path = os.fspath(path) return self._extract_member(member, path, pwd)
(self, member, path=None, pwd=None)
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52,361
zipfile
extractall
Extract all members from the archive to the current working directory. `path' specifies a different directory to extract to. `members' is optional and must be a subset of the list returned by namelist().
def extractall(self, path=None, members=None, pwd=None): """Extract all members from the archive to the current working directory. `path' specifies a different directory to extract to. `members' is optional and must be a subset of the list returned by namelist(). """ if members is None: members = self.namelist() if path is None: path = os.getcwd() else: path = os.fspath(path) for zipinfo in members: self._extract_member(zipinfo, path, pwd)
(self, path=None, members=None, pwd=None)
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52,365
zipfile
open
Return file-like object for 'name'. name is a string for the file name within the ZIP file, or a ZipInfo object. mode should be 'r' to read a file already in the ZIP file, or 'w' to write to a file newly added to the archive. pwd is the password to decrypt files (only used for reading). When writing, if the file size is not known in advance but may exceed 2 GiB, pass force_zip64 to use the ZIP64 format, which can handle large files. If the size is known in advance, it is best to pass a ZipInfo instance for name, with zinfo.file_size set.
def open(self, name, mode="r", pwd=None, *, force_zip64=False): """Return file-like object for 'name'. name is a string for the file name within the ZIP file, or a ZipInfo object. mode should be 'r' to read a file already in the ZIP file, or 'w' to write to a file newly added to the archive. pwd is the password to decrypt files (only used for reading). When writing, if the file size is not known in advance but may exceed 2 GiB, pass force_zip64 to use the ZIP64 format, which can handle large files. If the size is known in advance, it is best to pass a ZipInfo instance for name, with zinfo.file_size set. """ if mode not in {"r", "w"}: raise ValueError('open() requires mode "r" or "w"') if pwd and not isinstance(pwd, bytes): raise TypeError("pwd: expected bytes, got %s" % type(pwd).__name__) if pwd and (mode == "w"): raise ValueError("pwd is only supported for reading files") if not self.fp: raise ValueError( "Attempt to use ZIP archive that was already closed") # Make sure we have an info object if isinstance(name, ZipInfo): # 'name' is already an info object zinfo = name elif mode == 'w': zinfo = ZipInfo(name) zinfo.compress_type = self.compression zinfo._compresslevel = self.compresslevel else: # Get info object for name zinfo = self.getinfo(name) if mode == 'w': return self._open_to_write(zinfo, force_zip64=force_zip64) if self._writing: raise ValueError("Can't read from the ZIP file while there " "is an open writing handle on it. " "Close the writing handle before trying to read.") # Open for reading: self._fileRefCnt += 1 zef_file = _SharedFile(self.fp, zinfo.header_offset, self._fpclose, self._lock, lambda: self._writing) try: # Skip the file header: fheader = zef_file.read(sizeFileHeader) if len(fheader) != sizeFileHeader: raise BadZipFile("Truncated file header") fheader = struct.unpack(structFileHeader, fheader) if fheader[_FH_SIGNATURE] != stringFileHeader: raise BadZipFile("Bad magic number for file header") fname = zef_file.read(fheader[_FH_FILENAME_LENGTH]) if fheader[_FH_EXTRA_FIELD_LENGTH]: zef_file.read(fheader[_FH_EXTRA_FIELD_LENGTH]) if zinfo.flag_bits & 0x20: # Zip 2.7: compressed patched data raise NotImplementedError("compressed patched data (flag bit 5)") if zinfo.flag_bits & 0x40: # strong encryption raise NotImplementedError("strong encryption (flag bit 6)") if fheader[_FH_GENERAL_PURPOSE_FLAG_BITS] & 0x800: # UTF-8 filename fname_str = fname.decode("utf-8") else: fname_str = fname.decode("cp437") if fname_str != zinfo.orig_filename: raise BadZipFile( 'File name in directory %r and header %r differ.' % (zinfo.orig_filename, fname)) if (zinfo._end_offset is not None and zef_file.tell() + zinfo.compress_size > zinfo._end_offset): raise BadZipFile(f"Overlapped entries: {zinfo.orig_filename!r} (possible zip bomb)") # check for encrypted flag & handle password is_encrypted = zinfo.flag_bits & 0x1 if is_encrypted: if not pwd: pwd = self.pwd if not pwd: raise RuntimeError("File %r is encrypted, password " "required for extraction" % name) else: pwd = None return ZipExtFile(zef_file, mode, zinfo, pwd, True) except: zef_file.close() raise
(self, name, mode='r', pwd=None, *, force_zip64=False)
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52,367
zipfile
read
Return file bytes for name.
def read(self, name, pwd=None): """Return file bytes for name.""" with self.open(name, "r", pwd) as fp: return fp.read()
(self, name, pwd=None)
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52,370
zipfile
write
Put the bytes from filename into the archive under the name arcname.
def write(self, filename, arcname=None, compress_type=None, compresslevel=None): """Put the bytes from filename into the archive under the name arcname.""" if not self.fp: raise ValueError( "Attempt to write to ZIP archive that was already closed") if self._writing: raise ValueError( "Can't write to ZIP archive while an open writing handle exists" ) zinfo = ZipInfo.from_file(filename, arcname, strict_timestamps=self._strict_timestamps) if zinfo.is_dir(): zinfo.compress_size = 0 zinfo.CRC = 0 else: if compress_type is not None: zinfo.compress_type = compress_type else: zinfo.compress_type = self.compression if compresslevel is not None: zinfo._compresslevel = compresslevel else: zinfo._compresslevel = self.compresslevel if zinfo.is_dir(): with self._lock: if self._seekable: self.fp.seek(self.start_dir) zinfo.header_offset = self.fp.tell() # Start of header bytes if zinfo.compress_type == ZIP_LZMA: # Compressed data includes an end-of-stream (EOS) marker zinfo.flag_bits |= 0x02 self._writecheck(zinfo) self._didModify = True self.filelist.append(zinfo) self.NameToInfo[zinfo.filename] = zinfo self.fp.write(zinfo.FileHeader(False)) self.start_dir = self.fp.tell() else: with open(filename, "rb") as src, self.open(zinfo, 'w') as dest: shutil.copyfileobj(src, dest, 1024*8)
(self, filename, arcname=None, compress_type=None, compresslevel=None)
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52,371
zipfile
writestr
Write a file into the archive. The contents is 'data', which may be either a 'str' or a 'bytes' instance; if it is a 'str', it is encoded as UTF-8 first. 'zinfo_or_arcname' is either a ZipInfo instance or the name of the file in the archive.
def writestr(self, zinfo_or_arcname, data, compress_type=None, compresslevel=None): """Write a file into the archive. The contents is 'data', which may be either a 'str' or a 'bytes' instance; if it is a 'str', it is encoded as UTF-8 first. 'zinfo_or_arcname' is either a ZipInfo instance or the name of the file in the archive.""" if isinstance(data, str): data = data.encode("utf-8") if not isinstance(zinfo_or_arcname, ZipInfo): zinfo = ZipInfo(filename=zinfo_or_arcname, date_time=time.localtime(time.time())[:6]) zinfo.compress_type = self.compression zinfo._compresslevel = self.compresslevel if zinfo.filename[-1] == '/': zinfo.external_attr = 0o40775 << 16 # drwxrwxr-x zinfo.external_attr |= 0x10 # MS-DOS directory flag else: zinfo.external_attr = 0o600 << 16 # ?rw------- else: zinfo = zinfo_or_arcname if not self.fp: raise ValueError( "Attempt to write to ZIP archive that was already closed") if self._writing: raise ValueError( "Can't write to ZIP archive while an open writing handle exists." ) if compress_type is not None: zinfo.compress_type = compress_type if compresslevel is not None: zinfo._compresslevel = compresslevel zinfo.file_size = len(data) # Uncompressed size with self._lock: with self.open(zinfo, mode='w') as dest: dest.write(data)
(self, zinfo_or_arcname, data, compress_type=None, compresslevel=None)
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52,372
pgeocode
_open_extract_cycle_url
Same as _open_extract_url but cycle through URLs until one works We start by opening the first URL in the list, and if fails move to the next, until one works or the end of list is reached.
def _index_postal_codes(self) -> pd.DataFrame: """Create a dataframe with unique postal codes""" data_path_unique = self._data_path.replace(".txt", "-index.txt") if os.path.exists(data_path_unique): data_unique = pd.read_csv( data_path_unique, dtype={"postal_code": str}, na_values=NA_VALUES, keep_default_na=False, ) else: # group together places with the same postal code df_unique_cp_group = self._data.groupby("postal_code") data_unique = df_unique_cp_group[["latitude", "longitude"]].mean() valid_keys = set(DATA_FIELDS).difference( ["place_name", "latitude", "longitude", "postal_code"] ) data_unique["place_name"] = df_unique_cp_group["place_name"].apply( lambda x: ", ".join([str(el) for el in x]) ) for key in valid_keys: data_unique[key] = df_unique_cp_group[key].first() data_unique = data_unique.reset_index()[DATA_FIELDS] data_unique.to_csv(data_path_unique, index=None) return data_unique
(urls: list[str], country: str) -> Any
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52,373
pgeocode
_open_extract_url
Download contents for a URL If the file has a .zip extension, open it and extract the country Returns the opened file object.
def _index_postal_codes(self) -> pd.DataFrame: """Create a dataframe with unique postal codes""" data_path_unique = self._data_path.replace(".txt", "-index.txt") if os.path.exists(data_path_unique): data_unique = pd.read_csv( data_path_unique, dtype={"postal_code": str}, na_values=NA_VALUES, keep_default_na=False, ) else: # group together places with the same postal code df_unique_cp_group = self._data.groupby("postal_code") data_unique = df_unique_cp_group[["latitude", "longitude"]].mean() valid_keys = set(DATA_FIELDS).difference( ["place_name", "latitude", "longitude", "postal_code"] ) data_unique["place_name"] = df_unique_cp_group["place_name"].apply( lambda x: ", ".join([str(el) for el in x]) ) for key in valid_keys: data_unique[key] = df_unique_cp_group[key].first() data_unique = data_unique.reset_index()[DATA_FIELDS] data_unique.to_csv(data_path_unique, index=None) return data_unique
(url: str, country: str) -> Any
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52,375
pgeocode
haversine_distance
Haversine (great circle) distance Calculate the great circle distance between two points on the earth (specified in decimal degrees) Parameters ---------- x : array, shape=(n_samples, 2) the first list of coordinates (degrees) y : array: shape=(n_samples, 2) the second list of coordinates (degress) Returns ------- d : array, shape=(n_samples,) the distance between corrdinates (km) References ---------- https://en.wikipedia.org/wiki/Great-circle_distance
def haversine_distance(x, y): """Haversine (great circle) distance Calculate the great circle distance between two points on the earth (specified in decimal degrees) Parameters ---------- x : array, shape=(n_samples, 2) the first list of coordinates (degrees) y : array: shape=(n_samples, 2) the second list of coordinates (degress) Returns ------- d : array, shape=(n_samples,) the distance between corrdinates (km) References ---------- https://en.wikipedia.org/wiki/Great-circle_distance """ x_rad = np.radians(x) y_rad = np.radians(y) d = y_rad - x_rad dlat, dlon = d.T x_lat = x_rad[:, 0] y_lat = y_rad[:, 0] a = ( np.sin(dlat / 2.0) ** 2 + np.cos(x_lat) * np.cos(y_lat) * np.sin(dlon / 2.0) ** 2 ) c = 2 * np.arcsin(np.sqrt(a)) return EARTH_RADIUS * c
(x, y)
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52,381
zabbix_utils.exceptions
APINotSupported
Exception class when object/action is not supported by Zabbix API. Args: message (str): Not supported object/action message. version (str): Current version of Zabbix API.
class APINotSupported(ModuleBaseException): """Exception class when object/action is not supported by Zabbix API. Args: message (str): Not supported object/action message. version (str): Current version of Zabbix API. """ def __init__(self, message: str, version: str = None): if version: message = f"{message} is unsupported for Zabbix {version} version" super().__init__(message)
(message: str, version: str = None)
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52,382
zabbix_utils.exceptions
__init__
null
def __init__(self, message: str, version: str = None): if version: message = f"{message} is unsupported for Zabbix {version} version" super().__init__(message)
(self, message: str, version: Optional[str] = None)
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52,383
zabbix_utils.exceptions
APIRequestError
Exception class when Zabbix API returns error by request. Args: api_error (str|dict): Raw error message from Zabbix API.
class APIRequestError(ModuleBaseException): """Exception class when Zabbix API returns error by request. Args: api_error (str|dict): Raw error message from Zabbix API. """ def __init__(self, api_error: Union[str, dict]): if isinstance(api_error, dict): api_error['body'] = ModuleUtils.hide_private(api_error['body']) super().__init__("{message} {data}".format(**api_error)) for key, value in api_error.items(): setattr(self, key, value) else: super().__init__(api_error)
(api_error: Union[str, dict])
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52,384
zabbix_utils.exceptions
__init__
null
def __init__(self, api_error: Union[str, dict]): if isinstance(api_error, dict): api_error['body'] = ModuleUtils.hide_private(api_error['body']) super().__init__("{message} {data}".format(**api_error)) for key, value in api_error.items(): setattr(self, key, value) else: super().__init__(api_error)
(self, api_error: Union[str, dict])
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