index
int64 0
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| package
stringlengths 2
98
⌀ | name
stringlengths 1
76
| docstring
stringlengths 0
281k
⌀ | code
stringlengths 4
8.19k
| signature
stringlengths 2
42.8k
⌀ | embed_func_code
listlengths 768
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31,424 | prefect.blocks.core | _save |
Saves the values of a block as a block document with an option to save as an
anonymous block document.
Args:
name: User specified name to give saved block document which can later be used to load the
block document.
is_anonymous: Boolean value specifying whether the block document is anonymous. Anonymous
blocks are intended for system use and are not shown in the UI. Anonymous blocks do not
require a user-supplied name.
overwrite: Boolean value specifying if values should be overwritten if a block document with
the specified name already exists.
Raises:
ValueError: If a name is not given and `is_anonymous` is `False` or a name is given and
`is_anonymous` is `True`.
| def _collect_nested_reference_strings(obj: Dict):
"""
Collects all nested reference strings (e.g. #/definitions/Model) from a given object.
"""
found_reference_strings = []
if isinstance(obj, dict):
if obj.get("$ref"):
found_reference_strings.append(obj.get("$ref"))
for value in obj.values():
found_reference_strings.extend(_collect_nested_reference_strings(value))
if isinstance(obj, list):
for item in obj:
found_reference_strings.extend(_collect_nested_reference_strings(item))
return found_reference_strings
| (self, name: Optional[str] = None, is_anonymous: bool = False, overwrite: bool = False, client: 'PrefectClient' = None) | [
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|
31,425 | prefect.blocks.core | _to_block_document |
Creates the corresponding block document based on the data stored in a block.
The corresponding block document name, block type ID, and block schema ID must
either be passed into the method or configured on the block.
Args:
name: The name of the created block document. Not required if anonymous.
block_schema_id: UUID of the corresponding block schema.
block_type_id: UUID of the corresponding block type.
is_anonymous: if True, an anonymous block is created. Anonymous
blocks are not displayed in the UI and used primarily for system
operations and features that need to automatically generate blocks.
Returns:
BlockDocument: Corresponding block document
populated with the block's configured data.
| def _to_block_document(
self,
name: Optional[str] = None,
block_schema_id: Optional[UUID] = None,
block_type_id: Optional[UUID] = None,
is_anonymous: Optional[bool] = None,
) -> BlockDocument:
"""
Creates the corresponding block document based on the data stored in a block.
The corresponding block document name, block type ID, and block schema ID must
either be passed into the method or configured on the block.
Args:
name: The name of the created block document. Not required if anonymous.
block_schema_id: UUID of the corresponding block schema.
block_type_id: UUID of the corresponding block type.
is_anonymous: if True, an anonymous block is created. Anonymous
blocks are not displayed in the UI and used primarily for system
operations and features that need to automatically generate blocks.
Returns:
BlockDocument: Corresponding block document
populated with the block's configured data.
"""
if is_anonymous is None:
is_anonymous = self._is_anonymous or False
# name must be present if not anonymous
if not is_anonymous and not name and not self._block_document_name:
raise ValueError("No name provided, either as an argument or on the block.")
if not block_schema_id and not self._block_schema_id:
raise ValueError(
"No block schema ID provided, either as an argument or on the block."
)
if not block_type_id and not self._block_type_id:
raise ValueError(
"No block type ID provided, either as an argument or on the block."
)
# The keys passed to `include` must NOT be aliases, else some items will be missed
# i.e. must do `self.schema_` vs `self.schema` to get a `schema_ = Field(alias="schema")`
# reported from https://github.com/PrefectHQ/prefect-dbt/issues/54
data_keys = self.schema(by_alias=False)["properties"].keys()
# `block_document_data`` must return the aliased version for it to show in the UI
block_document_data = self.dict(by_alias=True, include=data_keys)
# Iterate through and find blocks that already have saved block documents to
# create references to those saved block documents.
for key in data_keys:
field_value = getattr(self, key)
if (
isinstance(field_value, Block)
and field_value._block_document_id is not None
):
block_document_data[key] = {
"$ref": {"block_document_id": field_value._block_document_id}
}
return BlockDocument(
id=self._block_document_id or uuid4(),
name=(name or self._block_document_name) if not is_anonymous else None,
block_schema_id=block_schema_id or self._block_schema_id,
block_type_id=block_type_id or self._block_type_id,
data=block_document_data,
block_schema=self._to_block_schema(
block_type_id=block_type_id or self._block_type_id,
),
block_type=self._to_block_type(),
is_anonymous=is_anonymous,
)
| (self, name: Optional[str] = None, block_schema_id: Optional[uuid.UUID] = None, block_type_id: Optional[uuid.UUID] = None, is_anonymous: Optional[bool] = None) -> prefect.client.schemas.objects.BlockDocument | [
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|
31,426 | prefect_sqlalchemy.credentials | block_initialization |
Initializes the engine.
| def block_initialization(self):
"""
Initializes the engine.
"""
warnings.warn(
"DatabaseCredentials is now deprecated and will be removed March 2023; "
"please use SqlAlchemyConnector instead.",
DeprecationWarning,
)
if isinstance(self.driver, AsyncDriver):
drivername = self.driver.value
self._driver_is_async = True
elif isinstance(self.driver, SyncDriver):
drivername = self.driver.value
self._driver_is_async = False
else:
drivername = self.driver
self._driver_is_async = drivername in AsyncDriver._value2member_map_
url_params = dict(
drivername=drivername,
username=self.username,
password=self.password.get_secret_value() if self.password else None,
database=self.database,
host=self.host,
port=self.port,
query=self.query,
)
if not self.url:
required_url_keys = ("drivername", "database")
if not all(url_params[key] for key in required_url_keys):
required_url_keys = ("driver", "database")
raise ValueError(
f"If the `url` is not provided, "
f"all of these URL params are required: "
f"{required_url_keys}"
)
self.rendered_url = URL.create(
**{
url_key: url_param
for url_key, url_param in url_params.items()
if url_param is not None
}
) # from params
else:
if any(val for val in url_params.values()):
raise ValueError(
f"The `url` should not be provided "
f"alongside any of these URL params: "
f"{url_params.keys()}"
)
self.rendered_url = make_url(str(self.url))
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]
|
31,427 | pydantic.v1.main | copy |
Duplicate a model, optionally choose which fields to include, exclude and change.
:param include: fields to include in new model
:param exclude: fields to exclude from new model, as with values this takes precedence over include
:param update: values to change/add in the new model. Note: the data is not validated before creating
the new model: you should trust this data
:param deep: set to `True` to make a deep copy of the model
:return: new model instance
| import warnings
from abc import ABCMeta
from copy import deepcopy
from enum import Enum
from functools import partial
from pathlib import Path
from types import FunctionType, prepare_class, resolve_bases
from typing import (
TYPE_CHECKING,
AbstractSet,
Any,
Callable,
ClassVar,
Dict,
List,
Mapping,
Optional,
Tuple,
Type,
TypeVar,
Union,
cast,
no_type_check,
overload,
)
from typing_extensions import dataclass_transform
from .class_validators import ValidatorGroup, extract_root_validators, extract_validators, inherit_validators
from .config import BaseConfig, Extra, inherit_config, prepare_config
from .error_wrappers import ErrorWrapper, ValidationError
from .errors import ConfigError, DictError, ExtraError, MissingError
from .fields import (
MAPPING_LIKE_SHAPES,
Field,
ModelField,
ModelPrivateAttr,
PrivateAttr,
Undefined,
is_finalvar_with_default_val,
)
from .json import custom_pydantic_encoder, pydantic_encoder
from .parse import Protocol, load_file, load_str_bytes
from .schema import default_ref_template, model_schema
from .types import PyObject, StrBytes
from .typing import (
AnyCallable,
get_args,
get_origin,
is_classvar,
is_namedtuple,
is_union,
resolve_annotations,
update_model_forward_refs,
)
from .utils import (
DUNDER_ATTRIBUTES,
ROOT_KEY,
ClassAttribute,
GetterDict,
Representation,
ValueItems,
generate_model_signature,
is_valid_field,
is_valid_private_name,
lenient_issubclass,
sequence_like,
smart_deepcopy,
unique_list,
validate_field_name,
)
if TYPE_CHECKING:
from inspect import Signature
from .class_validators import ValidatorListDict
from .types import ModelOrDc
from .typing import (
AbstractSetIntStr,
AnyClassMethod,
CallableGenerator,
DictAny,
DictStrAny,
MappingIntStrAny,
ReprArgs,
SetStr,
TupleGenerator,
)
Model = TypeVar('Model', bound='BaseModel')
__all__ = 'BaseModel', 'create_model', 'validate_model'
_T = TypeVar('_T')
def validate_custom_root_type(fields: Dict[str, ModelField]) -> None:
if len(fields) > 1:
raise ValueError(f'{ROOT_KEY} cannot be mixed with other fields')
| (self: 'Model', *, include: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny'), NoneType] = None, exclude: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny'), NoneType] = None, update: Optional[ForwardRef('DictStrAny')] = None, deep: bool = False) -> 'Model' | [
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|
31,428 | prefect_sqlalchemy.credentials | dict |
Convert to a dictionary.
| def dict(self, *args, **kwargs) -> Dict:
"""
Convert to a dictionary.
"""
# Support serialization of the 'URL' type
d = super().dict(*args, **kwargs)
d["rendered_url"] = SecretStr(
self.rendered_url.render_as_string(hide_password=False)
)
return d
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|
31,429 | prefect.blocks.core | get_block_placeholder |
Returns the block placeholder for the current block which can be used for
templating.
Returns:
str: The block placeholder for the current block in the format
`prefect.blocks.{block_type_name}.{block_document_name}`
Raises:
BlockNotSavedError: Raised if the block has not been saved.
If a block has not been saved, the return value will be `None`.
| def block_schema_to_key(schema: BlockSchema) -> str:
"""
Defines the unique key used to lookup the Block class for a given schema.
"""
return f"{schema.block_type.slug}"
| (self) -> str | [
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|
31,430 | prefect_sqlalchemy.credentials | get_engine |
Returns an authenticated engine that can be
used to query from databases.
Returns:
The authenticated SQLAlchemy Connection / AsyncConnection.
Examples:
Create an asynchronous engine to PostgreSQL using URL params.
```python
from prefect import flow
from prefect_sqlalchemy import DatabaseCredentials, AsyncDriver
@flow
def sqlalchemy_credentials_flow():
sqlalchemy_credentials = DatabaseCredentials(
driver=AsyncDriver.POSTGRESQL_ASYNCPG,
username="prefect",
password="prefect_password",
database="postgres"
)
print(sqlalchemy_credentials.get_engine())
sqlalchemy_credentials_flow()
```
Create a synchronous engine to Snowflake using the `url` kwarg.
```python
from prefect import flow
from prefect_sqlalchemy import DatabaseCredentials, AsyncDriver
@flow
def sqlalchemy_credentials_flow():
url = (
"snowflake://<user_login_name>:<password>"
"@<account_identifier>/<database_name>"
"?warehouse=<warehouse_name>"
)
sqlalchemy_credentials = DatabaseCredentials(url=url)
print(sqlalchemy_credentials.get_engine())
sqlalchemy_credentials_flow()
```
| def get_engine(self) -> Union["Connection", "AsyncConnection"]:
"""
Returns an authenticated engine that can be
used to query from databases.
Returns:
The authenticated SQLAlchemy Connection / AsyncConnection.
Examples:
Create an asynchronous engine to PostgreSQL using URL params.
```python
from prefect import flow
from prefect_sqlalchemy import DatabaseCredentials, AsyncDriver
@flow
def sqlalchemy_credentials_flow():
sqlalchemy_credentials = DatabaseCredentials(
driver=AsyncDriver.POSTGRESQL_ASYNCPG,
username="prefect",
password="prefect_password",
database="postgres"
)
print(sqlalchemy_credentials.get_engine())
sqlalchemy_credentials_flow()
```
Create a synchronous engine to Snowflake using the `url` kwarg.
```python
from prefect import flow
from prefect_sqlalchemy import DatabaseCredentials, AsyncDriver
@flow
def sqlalchemy_credentials_flow():
url = (
"snowflake://<user_login_name>:<password>"
"@<account_identifier>/<database_name>"
"?warehouse=<warehouse_name>"
)
sqlalchemy_credentials = DatabaseCredentials(url=url)
print(sqlalchemy_credentials.get_engine())
sqlalchemy_credentials_flow()
```
"""
engine_kwargs = dict(
url=self.rendered_url,
connect_args=self.connect_args or {},
poolclass=NullPool,
)
if self._driver_is_async:
engine = create_async_engine(**engine_kwargs)
else:
engine = create_engine(**engine_kwargs)
return engine
| (self) -> Union[sqlalchemy.engine.base.Connection, sqlalchemy.ext.asyncio.engine.AsyncConnection] | [
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]
|
31,431 | prefect.blocks.core | is_block_class | null | @staticmethod
def is_block_class(block) -> bool:
return _is_subclass(block, Block)
| (block) -> bool | [
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|
31,432 | pydantic.v1.main | json |
Generate a JSON representation of the model, `include` and `exclude` arguments as per `dict()`.
`encoder` is an optional function to supply as `default` to json.dumps(), other arguments as per `json.dumps()`.
| import warnings
from abc import ABCMeta
from copy import deepcopy
from enum import Enum
from functools import partial
from pathlib import Path
from types import FunctionType, prepare_class, resolve_bases
from typing import (
TYPE_CHECKING,
AbstractSet,
Any,
Callable,
ClassVar,
Dict,
List,
Mapping,
Optional,
Tuple,
Type,
TypeVar,
Union,
cast,
no_type_check,
overload,
)
from typing_extensions import dataclass_transform
from .class_validators import ValidatorGroup, extract_root_validators, extract_validators, inherit_validators
from .config import BaseConfig, Extra, inherit_config, prepare_config
from .error_wrappers import ErrorWrapper, ValidationError
from .errors import ConfigError, DictError, ExtraError, MissingError
from .fields import (
MAPPING_LIKE_SHAPES,
Field,
ModelField,
ModelPrivateAttr,
PrivateAttr,
Undefined,
is_finalvar_with_default_val,
)
from .json import custom_pydantic_encoder, pydantic_encoder
from .parse import Protocol, load_file, load_str_bytes
from .schema import default_ref_template, model_schema
from .types import PyObject, StrBytes
from .typing import (
AnyCallable,
get_args,
get_origin,
is_classvar,
is_namedtuple,
is_union,
resolve_annotations,
update_model_forward_refs,
)
from .utils import (
DUNDER_ATTRIBUTES,
ROOT_KEY,
ClassAttribute,
GetterDict,
Representation,
ValueItems,
generate_model_signature,
is_valid_field,
is_valid_private_name,
lenient_issubclass,
sequence_like,
smart_deepcopy,
unique_list,
validate_field_name,
)
if TYPE_CHECKING:
from inspect import Signature
from .class_validators import ValidatorListDict
from .types import ModelOrDc
from .typing import (
AbstractSetIntStr,
AnyClassMethod,
CallableGenerator,
DictAny,
DictStrAny,
MappingIntStrAny,
ReprArgs,
SetStr,
TupleGenerator,
)
Model = TypeVar('Model', bound='BaseModel')
__all__ = 'BaseModel', 'create_model', 'validate_model'
_T = TypeVar('_T')
def validate_custom_root_type(fields: Dict[str, ModelField]) -> None:
if len(fields) > 1:
raise ValueError(f'{ROOT_KEY} cannot be mixed with other fields')
| (self, *, include: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny'), NoneType] = None, exclude: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny'), NoneType] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) -> str | [
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|
31,433 | prefect.blocks.core | save |
Saves the values of a block as a block document.
Args:
name: User specified name to give saved block document which can later be used to load the
block document.
overwrite: Boolean value specifying if values should be overwritten if a block document with
the specified name already exists.
| @staticmethod
def schema_extra(schema: Dict[str, Any], model: Type["Block"]):
"""
Customizes Pydantic's schema generation feature to add blocks related information.
"""
schema["block_type_slug"] = model.get_block_type_slug()
# Ensures args and code examples aren't included in the schema
description = model.get_description()
if description:
schema["description"] = description
else:
# Prevent the description of the base class from being included in the schema
schema.pop("description", None)
# create a list of secret field names
# secret fields include both top-level keys and dot-delimited nested secret keys
# A wildcard (*) means that all fields under a given key are secret.
# for example: ["x", "y", "z.*", "child.a"]
# means the top-level keys "x" and "y", all keys under "z", and the key "a" of a block
# nested under the "child" key are all secret. There is no limit to nesting.
secrets = schema["secret_fields"] = []
for field in model.__fields__.values():
_collect_secret_fields(field.name, field.type_, secrets)
# create block schema references
refs = schema["block_schema_references"] = {}
for field in model.__fields__.values():
if Block.is_block_class(field.type_):
refs[field.name] = field.type_._to_block_schema_reference_dict()
if get_origin(field.type_) is Union:
for type_ in get_args(field.type_):
if Block.is_block_class(type_):
if isinstance(refs.get(field.name), list):
refs[field.name].append(
type_._to_block_schema_reference_dict()
)
elif isinstance(refs.get(field.name), dict):
refs[field.name] = [
refs[field.name],
type_._to_block_schema_reference_dict(),
]
else:
refs[
field.name
] = type_._to_block_schema_reference_dict()
| (self, name: Optional[str] = None, overwrite: bool = False, client: 'PrefectClient' = None) | [
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|
31,434 | prefect_sqlalchemy.database | SqlAlchemyConnector |
Block used to manage authentication with a database.
Upon instantiating, an engine is created and maintained for the life of
the object until the close method is called.
It is recommended to use this block as a context manager, which will automatically
close the engine and its connections when the context is exited.
It is also recommended that this block is loaded and consumed within a single task
or flow because if the block is passed across separate tasks and flows,
the state of the block's connection and cursor could be lost.
Attributes:
connection_info: SQLAlchemy URL to create the engine;
either create from components or create from a string.
connect_args: The options which will be passed directly to the
DBAPI's connect() method as additional keyword arguments.
fetch_size: The number of rows to fetch at a time.
Example:
Load stored database credentials and use in context manager:
```python
from prefect_sqlalchemy import SqlAlchemyConnector
database_block = SqlAlchemyConnector.load("BLOCK_NAME")
with database_block:
...
```
Create table named customers and insert values; then fetch the first 10 rows.
```python
from prefect_sqlalchemy import (
SqlAlchemyConnector, SyncDriver, ConnectionComponents
)
with SqlAlchemyConnector(
connection_info=ConnectionComponents(
driver=SyncDriver.SQLITE_PYSQLITE,
database="prefect.db"
)
) as database:
database.execute(
"CREATE TABLE IF NOT EXISTS customers (name varchar, address varchar);",
)
for i in range(1, 42):
database.execute(
"INSERT INTO customers (name, address) VALUES (:name, :address);",
parameters={"name": "Marvin", "address": f"Highway {i}"},
)
results = database.fetch_many(
"SELECT * FROM customers WHERE name = :name;",
parameters={"name": "Marvin"},
size=10
)
print(results)
```
| class SqlAlchemyConnector(CredentialsBlock, DatabaseBlock):
"""
Block used to manage authentication with a database.
Upon instantiating, an engine is created and maintained for the life of
the object until the close method is called.
It is recommended to use this block as a context manager, which will automatically
close the engine and its connections when the context is exited.
It is also recommended that this block is loaded and consumed within a single task
or flow because if the block is passed across separate tasks and flows,
the state of the block's connection and cursor could be lost.
Attributes:
connection_info: SQLAlchemy URL to create the engine;
either create from components or create from a string.
connect_args: The options which will be passed directly to the
DBAPI's connect() method as additional keyword arguments.
fetch_size: The number of rows to fetch at a time.
Example:
Load stored database credentials and use in context manager:
```python
from prefect_sqlalchemy import SqlAlchemyConnector
database_block = SqlAlchemyConnector.load("BLOCK_NAME")
with database_block:
...
```
Create table named customers and insert values; then fetch the first 10 rows.
```python
from prefect_sqlalchemy import (
SqlAlchemyConnector, SyncDriver, ConnectionComponents
)
with SqlAlchemyConnector(
connection_info=ConnectionComponents(
driver=SyncDriver.SQLITE_PYSQLITE,
database="prefect.db"
)
) as database:
database.execute(
"CREATE TABLE IF NOT EXISTS customers (name varchar, address varchar);",
)
for i in range(1, 42):
database.execute(
"INSERT INTO customers (name, address) VALUES (:name, :address);",
parameters={"name": "Marvin", "address": f"Highway {i}"},
)
results = database.fetch_many(
"SELECT * FROM customers WHERE name = :name;",
parameters={"name": "Marvin"},
size=10
)
print(results)
```
"""
_block_type_name = "SQLAlchemy Connector"
_logo_url = "https://cdn.sanity.io/images/3ugk85nk/production/3c7dff04f70aaf4528e184a3b028f9e40b98d68c-250x250.png" # noqa
_documentation_url = "https://prefecthq.github.io/prefect-sqlalchemy/database/#prefect_sqlalchemy.database.SqlAlchemyConnector" # noqa
connection_info: Union[ConnectionComponents, AnyUrl] = Field(
default=...,
description=(
"SQLAlchemy URL to create the engine; either create from components "
"or create from a string."
),
)
connect_args: Optional[Dict[str, Any]] = Field(
default=None,
title="Additional Connection Arguments",
description=(
"The options which will be passed directly to the DBAPI's connect() "
"method as additional keyword arguments."
),
)
fetch_size: int = Field(
default=1, description="The number of rows to fetch at a time."
)
_engine: Optional[Union[AsyncEngine, Engine]] = None
_exit_stack: Union[ExitStack, AsyncExitStack] = None
_unique_results: Dict[str, CursorResult] = None
class Config:
"""Configuration of pydantic."""
# Support serialization of the 'URL' type
arbitrary_types_allowed = True
json_encoders = {URL: lambda u: u.render_as_string()}
def dict(self, *args, **kwargs) -> Dict:
"""
Convert to a dictionary.
"""
# Support serialization of the 'URL' type
d = super().dict(*args, **kwargs)
d["_rendered_url"] = SecretStr(
self._rendered_url.render_as_string(hide_password=False)
)
return d
def block_initialization(self):
"""
Initializes the engine.
"""
super().block_initialization()
if isinstance(self.connection_info, ConnectionComponents):
self._rendered_url = self.connection_info.create_url()
else:
# make rendered url from string
self._rendered_url = make_url(str(self.connection_info))
drivername = self._rendered_url.drivername
try:
AsyncDriver(drivername)
self._driver_is_async = True
except ValueError:
self._driver_is_async = False
if self._unique_results is None:
self._unique_results = {}
if self._exit_stack is None:
self._start_exit_stack()
def _start_exit_stack(self):
"""
Starts an AsyncExitStack or ExitStack depending on whether driver is async.
"""
self._exit_stack = AsyncExitStack() if self._driver_is_async else ExitStack()
def get_engine(
self, **create_engine_kwargs: Dict[str, Any]
) -> Union[Engine, AsyncEngine]:
"""
Returns an authenticated engine that can be
used to query from databases.
If an existing engine exists, return that one.
Returns:
The authenticated SQLAlchemy Engine / AsyncEngine.
Examples:
Create an asynchronous engine to PostgreSQL using URL params.
```python
from prefect import flow
from prefect_sqlalchemy import (
SqlAlchemyConnector, ConnectionComponents, AsyncDriver
)
@flow
def sqlalchemy_credentials_flow():
sqlalchemy_credentials = SqlAlchemyConnector(
connection_info=ConnectionComponents(
driver=AsyncDriver.POSTGRESQL_ASYNCPG,
username="prefect",
password="prefect_password",
database="postgres"
)
)
print(sqlalchemy_credentials.get_engine())
sqlalchemy_credentials_flow()
```
Create a synchronous engine to Snowflake using the `url` kwarg.
```python
from prefect import flow
from prefect_sqlalchemy import SqlAlchemyConnector, AsyncDriver
@flow
def sqlalchemy_credentials_flow():
url = (
"snowflake://<user_login_name>:<password>"
"@<account_identifier>/<database_name>"
"?warehouse=<warehouse_name>"
)
sqlalchemy_credentials = SqlAlchemyConnector(url=url)
print(sqlalchemy_credentials.get_engine())
sqlalchemy_credentials_flow()
```
"""
if self._engine is not None:
self.logger.debug("Reusing existing engine.")
return self._engine
engine_kwargs = dict(
url=self._rendered_url,
connect_args=self.connect_args or {},
**create_engine_kwargs,
)
if self._driver_is_async:
# no need to await here
engine = create_async_engine(**engine_kwargs)
else:
engine = create_engine(**engine_kwargs)
self.logger.info("Created a new engine.")
if self._engine is None:
self._engine = engine
return engine
def get_connection(
self, begin: bool = True, **connect_kwargs: Dict[str, Any]
) -> Union[Connection, AsyncConnection]:
"""
Returns a connection that can be used to query from databases.
Args:
begin: Whether to begin a transaction on the connection; if True, if
any operations fail, the entire transaction will be rolled back.
**connect_kwargs: Additional keyword arguments to pass to either
`engine.begin` or engine.connect`.
Returns:
The SQLAlchemy Connection / AsyncConnection.
Examples:
Create an synchronous connection as a context-managed transaction.
```p | (*args, connection_info: Union[prefect_sqlalchemy.credentials.ConnectionComponents, pydantic.v1.networks.AnyUrl], connect_args: Optional[Dict[str, Any]] = None, fetch_size: int = 1, **kwargs) -> None | [
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|
31,435 | prefect_sqlalchemy.database | __aenter__ |
Start an asynchronous database engine upon entry.
| @sync_compatible
async def execute_many(
self,
operation: str,
seq_of_parameters: List[Dict[str, Any]],
**execution_options: Dict[str, Any],
) -> None:
"""
Executes many operations on the database. This method is intended to be used
for operations that do not return data, such as INSERT, UPDATE, or DELETE.
Unlike the fetch methods, this method will always execute the operation
upon calling.
Args:
operation: The SQL query or other operation to be executed.
seq_of_parameters: The sequence of parameters for the operation.
**execution_options: Options to pass to `Connection.execution_options`.
Examples:
Create a table and insert two rows into it.
```python
from prefect_sqlalchemy import SqlAlchemyConnector
with SqlAlchemyConnector.load("MY_BLOCK") as database:
database.execute("CREATE TABLE IF NOT EXISTS customers (name varchar, address varchar);")
database.execute_many(
"INSERT INTO customers (name, address) VALUES (:name, :address);",
seq_of_parameters=[
{"name": "Ford", "address": "Highway 42"},
{"name": "Unknown", "address": "Space"},
{"name": "Me", "address": "Myway 88"},
],
)
```
""" # noqa
async with self._manage_connection(begin=False) as connection:
await self._async_sync_execute(
connection,
text(operation),
seq_of_parameters,
execution_options=execution_options,
)
self.logger.info(
f"Executed {len(seq_of_parameters)} operations based off {operation!r}."
)
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|
31,436 | prefect_sqlalchemy.database | __aexit__ |
Dispose the asynchronous database engine upon exit.
| @sync_compatible
async def execute_many(
self,
operation: str,
seq_of_parameters: List[Dict[str, Any]],
**execution_options: Dict[str, Any],
) -> None:
"""
Executes many operations on the database. This method is intended to be used
for operations that do not return data, such as INSERT, UPDATE, or DELETE.
Unlike the fetch methods, this method will always execute the operation
upon calling.
Args:
operation: The SQL query or other operation to be executed.
seq_of_parameters: The sequence of parameters for the operation.
**execution_options: Options to pass to `Connection.execution_options`.
Examples:
Create a table and insert two rows into it.
```python
from prefect_sqlalchemy import SqlAlchemyConnector
with SqlAlchemyConnector.load("MY_BLOCK") as database:
database.execute("CREATE TABLE IF NOT EXISTS customers (name varchar, address varchar);")
database.execute_many(
"INSERT INTO customers (name, address) VALUES (:name, :address);",
seq_of_parameters=[
{"name": "Ford", "address": "Highway 42"},
{"name": "Unknown", "address": "Space"},
{"name": "Me", "address": "Myway 88"},
],
)
```
""" # noqa
async with self._manage_connection(begin=False) as connection:
await self._async_sync_execute(
connection,
text(operation),
seq_of_parameters,
execution_options=execution_options,
)
self.logger.info(
f"Executed {len(seq_of_parameters)} operations based off {operation!r}."
)
| (self, *args) | [
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|
31,437 | prefect_sqlalchemy.database | __enter__ |
Start an synchronous database engine upon entry.
| def __enter__(self):
"""
Start an synchronous database engine upon entry.
"""
if self._driver_is_async:
raise RuntimeError(
f"{self._rendered_url.drivername} cannot be run synchronously. "
f"Please use the `async with` syntax."
)
return self
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|
31,439 | prefect_sqlalchemy.database | __exit__ |
Dispose the synchronous database engine upon exit.
| def __exit__(self, *args):
"""
Dispose the synchronous database engine upon exit.
"""
self.close()
| (self, *args) | [
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|
31,440 | prefect_sqlalchemy.database | __getstate__ | Allows the block to be pickleable. | def __getstate__(self):
"""Allows the block to be pickleable."""
data = self.__dict__.copy()
data.update({k: None for k in {"_engine", "_exit_stack", "_unique_results"}})
return data
| (self) | [
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|
31,451 | prefect_sqlalchemy.database | __setstate__ | Upon loading back, restart the engine and results. | def __setstate__(self, data: dict):
"""Upon loading back, restart the engine and results."""
self.__dict__.update(data)
if self._unique_results is None:
self._unique_results = {}
if self._exit_stack is None:
self._start_exit_stack()
| (self, data: <function SqlAlchemyConnector.dict at 0x7f57a0c0feb0>) | [
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|
31,453 | prefect_sqlalchemy.database | _async_sync_execute |
Execute the statement asynchronously or synchronously.
| def get_client(
self,
client_type: Literal["engine", "connection"],
**get_client_kwargs: Dict[str, Any],
) -> Union[Engine, AsyncEngine, Connection, AsyncConnection]:
"""
Returns either an engine or connection that can be used to query from databases.
Args:
client_type: Select from either 'engine' or 'connection'.
**get_client_kwargs: Additional keyword arguments to pass to
either `get_engine` or `get_connection`.
Returns:
The authenticated SQLAlchemy engine or connection.
Examples:
Create an engine.
```python
from prefect_sqlalchemy import SqlalchemyConnector
sqlalchemy_connector = SqlAlchemyConnector.load("BLOCK_NAME")
engine = sqlalchemy_connector.get_client(client_type="engine")
```
Create a context managed connection.
```python
from prefect_sqlalchemy import SqlalchemyConnector
sqlalchemy_connector = SqlAlchemyConnector.load("BLOCK_NAME")
with sqlalchemy_connector.get_client(client_type="connection") as conn:
...
```
""" # noqa: E501
if client_type == "engine":
client = self.get_engine(**get_client_kwargs)
elif client_type == "connection":
client = self.get_connection(**get_client_kwargs)
else:
raise ValueError(
f"{client_type!r} is not supported; choose from engine or connection."
)
return client
| (self, connection: Union[sqlalchemy.engine.base.Connection, sqlalchemy.ext.asyncio.engine.AsyncConnection], *execute_args: Tuple[Any], **execute_kwargs: Dict[str, Any]) -> sqlalchemy.engine.cursor.CursorResult | [
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|
31,459 | prefect_sqlalchemy.database | _get_result_set |
Returns a new or existing result set based on whether the inputs
are unique.
Args:
*execute_args: Args to pass to execute.
**execute_kwargs: Keyword args to pass to execute.
Returns:
The result set from the operation.
| @asynccontextmanager
async def _manage_connection(self, **get_connection_kwargs: Dict[str, Any]):
if self._driver_is_async:
async with self.get_connection(**get_connection_kwargs) as connection:
yield connection
else:
with self.get_connection(**get_connection_kwargs) as connection:
yield connection
| (self, *execute_args: Tuple[Any], **execute_kwargs: Dict[str, Any]) -> sqlalchemy.engine.cursor.CursorResult | [
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|
31,462 | prefect_sqlalchemy.database | _manage_connection | null | def block_initialization(self):
"""
Initializes the engine.
"""
super().block_initialization()
if isinstance(self.connection_info, ConnectionComponents):
self._rendered_url = self.connection_info.create_url()
else:
# make rendered url from string
self._rendered_url = make_url(str(self.connection_info))
drivername = self._rendered_url.drivername
try:
AsyncDriver(drivername)
self._driver_is_async = True
except ValueError:
self._driver_is_async = False
if self._unique_results is None:
self._unique_results = {}
if self._exit_stack is None:
self._start_exit_stack()
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|
31,463 | prefect_sqlalchemy.database | _reset_cursor_results |
Closes all the existing cursor results.
| def _reset_cursor_results(self) -> None:
"""
Closes all the existing cursor results.
"""
input_hashes = tuple(self._unique_results.keys())
for input_hash in input_hashes:
try:
cursor_result = self._unique_results.pop(input_hash)
cursor_result.close()
except Exception as exc:
self.logger.warning(
f"Failed to close connection for input hash {input_hash!r}: {exc}"
)
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|
31,465 | prefect_sqlalchemy.database | _start_exit_stack |
Starts an AsyncExitStack or ExitStack depending on whether driver is async.
| def _start_exit_stack(self):
"""
Starts an AsyncExitStack or ExitStack depending on whether driver is async.
"""
self._exit_stack = AsyncExitStack() if self._driver_is_async else ExitStack()
| (self) | [
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|
31,467 | prefect_sqlalchemy.database | aclose |
Closes async connections and its cursors.
| @sync_compatible
async def execute_many(
self,
operation: str,
seq_of_parameters: List[Dict[str, Any]],
**execution_options: Dict[str, Any],
) -> None:
"""
Executes many operations on the database. This method is intended to be used
for operations that do not return data, such as INSERT, UPDATE, or DELETE.
Unlike the fetch methods, this method will always execute the operation
upon calling.
Args:
operation: The SQL query or other operation to be executed.
seq_of_parameters: The sequence of parameters for the operation.
**execution_options: Options to pass to `Connection.execution_options`.
Examples:
Create a table and insert two rows into it.
```python
from prefect_sqlalchemy import SqlAlchemyConnector
with SqlAlchemyConnector.load("MY_BLOCK") as database:
database.execute("CREATE TABLE IF NOT EXISTS customers (name varchar, address varchar);")
database.execute_many(
"INSERT INTO customers (name, address) VALUES (:name, :address);",
seq_of_parameters=[
{"name": "Ford", "address": "Highway 42"},
{"name": "Unknown", "address": "Space"},
{"name": "Me", "address": "Myway 88"},
],
)
```
""" # noqa
async with self._manage_connection(begin=False) as connection:
await self._async_sync_execute(
connection,
text(operation),
seq_of_parameters,
execution_options=execution_options,
)
self.logger.info(
f"Executed {len(seq_of_parameters)} operations based off {operation!r}."
)
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|
31,468 | prefect_sqlalchemy.database | block_initialization |
Initializes the engine.
| def block_initialization(self):
"""
Initializes the engine.
"""
super().block_initialization()
if isinstance(self.connection_info, ConnectionComponents):
self._rendered_url = self.connection_info.create_url()
else:
# make rendered url from string
self._rendered_url = make_url(str(self.connection_info))
drivername = self._rendered_url.drivername
try:
AsyncDriver(drivername)
self._driver_is_async = True
except ValueError:
self._driver_is_async = False
if self._unique_results is None:
self._unique_results = {}
if self._exit_stack is None:
self._start_exit_stack()
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|
31,469 | prefect_sqlalchemy.database | close |
Closes sync connections and its cursors.
| def close(self):
"""
Closes sync connections and its cursors.
"""
if self._driver_is_async:
raise RuntimeError(
f"{self._rendered_url.drivername} is not synchronous. "
f"Please use the `aclose` method instead."
)
try:
self.reset_connections()
finally:
if self._engine is not None:
self._engine.dispose()
self._engine = None
self.logger.info("Disposed the engine.")
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|
31,471 | prefect_sqlalchemy.database | dict |
Convert to a dictionary.
| def dict(self, *args, **kwargs) -> Dict:
"""
Convert to a dictionary.
"""
# Support serialization of the 'URL' type
d = super().dict(*args, **kwargs)
d["_rendered_url"] = SecretStr(
self._rendered_url.render_as_string(hide_password=False)
)
return d
| (self, *args, **kwargs) -> Dict | [
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|
31,472 | prefect_sqlalchemy.database | execute |
Executes an operation on the database. This method is intended to be used
for operations that do not return data, such as INSERT, UPDATE, or DELETE.
Unlike the fetch methods, this method will always execute the operation
upon calling.
Args:
operation: The SQL query or other operation to be executed.
parameters: The parameters for the operation.
**execution_options: Options to pass to `Connection.execution_options`.
Examples:
Create a table and insert one row into it.
```python
from prefect_sqlalchemy import SqlAlchemyConnector
with SqlAlchemyConnector.load("MY_BLOCK") as database:
database.execute("CREATE TABLE IF NOT EXISTS customers (name varchar, address varchar);")
database.execute(
"INSERT INTO customers (name, address) VALUES (:name, :address);",
parameters={"name": "Marvin", "address": "Highway 42"},
)
```
| @flow
def sqlalchemy_query_flow():
sqlalchemy_credentials = DatabaseCredentials(
driver=AsyncDriver.SQLITE_AIOSQLITE,
database="prefect.db",
)
result = sqlalchemy_query(
"SELECT * FROM customers WHERE name = :name;",
sqlalchemy_credentials,
params={"name": "Marvin"},
)
return result
| (self, operation: str, parameters: Optional[Dict[str, Any]] = None, **execution_options: Dict[str, Any]) -> NoneType | [
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|
31,473 | prefect_sqlalchemy.database | execute_many |
Executes many operations on the database. This method is intended to be used
for operations that do not return data, such as INSERT, UPDATE, or DELETE.
Unlike the fetch methods, this method will always execute the operation
upon calling.
Args:
operation: The SQL query or other operation to be executed.
seq_of_parameters: The sequence of parameters for the operation.
**execution_options: Options to pass to `Connection.execution_options`.
Examples:
Create a table and insert two rows into it.
```python
from prefect_sqlalchemy import SqlAlchemyConnector
with SqlAlchemyConnector.load("MY_BLOCK") as database:
database.execute("CREATE TABLE IF NOT EXISTS customers (name varchar, address varchar);")
database.execute_many(
"INSERT INTO customers (name, address) VALUES (:name, :address);",
seq_of_parameters=[
{"name": "Ford", "address": "Highway 42"},
{"name": "Unknown", "address": "Space"},
{"name": "Me", "address": "Myway 88"},
],
)
```
| @flow
def sqlalchemy_query_flow():
sqlalchemy_credentials = DatabaseCredentials(
driver=AsyncDriver.SQLITE_AIOSQLITE,
database="prefect.db",
)
result = sqlalchemy_query(
"SELECT * FROM customers WHERE name = :name;",
sqlalchemy_credentials,
params={"name": "Marvin"},
)
return result
| (self, operation: str, seq_of_parameters: List[Dict[str, Any]], **execution_options: Dict[str, Any]) -> NoneType | [
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|
31,474 | prefect_sqlalchemy.database | fetch_all |
Fetch all results from the database.
Repeated calls using the same inputs to *any* of the fetch methods of this
block will skip executing the operation again, and instead,
return the next set of results from the previous execution,
until the reset_cursors method is called.
Args:
operation: The SQL query or other operation to be executed.
parameters: The parameters for the operation.
**execution_options: Options to pass to `Connection.execution_options`.
Returns:
A list of tuples containing the data returned by the database,
where each row is a tuple and each column is a value in the tuple.
Examples:
Create a table, insert three rows into it, and fetch all where name is 'Me'.
```python
from prefect_sqlalchemy import SqlAlchemyConnector
with SqlAlchemyConnector.load("MY_BLOCK") as database:
database.execute("CREATE TABLE IF NOT EXISTS customers (name varchar, address varchar);")
database.execute_many(
"INSERT INTO customers (name, address) VALUES (:name, :address);",
seq_of_parameters=[
{"name": "Ford", "address": "Highway 42"},
{"name": "Unknown", "address": "Space"},
{"name": "Me", "address": "Myway 88"},
],
)
results = database.fetch_all("SELECT * FROM customers WHERE name = :name", parameters={"name": "Me"})
```
| @flow
def sqlalchemy_query_flow():
sqlalchemy_credentials = DatabaseCredentials(
driver=AsyncDriver.SQLITE_AIOSQLITE,
database="prefect.db",
)
result = sqlalchemy_query(
"SELECT * FROM customers WHERE name = :name;",
sqlalchemy_credentials,
params={"name": "Marvin"},
)
return result
| (self, operation: str, parameters: Optional[Dict[str, Any]] = None, **execution_options: Dict[str, Any]) -> List[Tuple[Any]] | [
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|
31,475 | prefect_sqlalchemy.database | fetch_many |
Fetch a limited number of results from the database.
Repeated calls using the same inputs to *any* of the fetch methods of this
block will skip executing the operation again, and instead,
return the next set of results from the previous execution,
until the reset_cursors method is called.
Args:
operation: The SQL query or other operation to be executed.
parameters: The parameters for the operation.
size: The number of results to return; if None or 0, uses the value of
`fetch_size` configured on the block.
**execution_options: Options to pass to `Connection.execution_options`.
Returns:
A list of tuples containing the data returned by the database,
where each row is a tuple and each column is a value in the tuple.
Examples:
Create a table, insert three rows into it, and fetch two rows repeatedly.
```python
from prefect_sqlalchemy import SqlAlchemyConnector
with SqlAlchemyConnector.load("MY_BLOCK") as database:
database.execute("CREATE TABLE IF NOT EXISTS customers (name varchar, address varchar);")
database.execute_many(
"INSERT INTO customers (name, address) VALUES (:name, :address);",
seq_of_parameters=[
{"name": "Ford", "address": "Highway 42"},
{"name": "Unknown", "address": "Space"},
{"name": "Me", "address": "Myway 88"},
],
)
results = database.fetch_many("SELECT * FROM customers", size=2)
print(results)
results = database.fetch_many("SELECT * FROM customers", size=2)
print(results)
```
| @flow
def sqlalchemy_query_flow():
sqlalchemy_credentials = DatabaseCredentials(
driver=AsyncDriver.SQLITE_AIOSQLITE,
database="prefect.db",
)
result = sqlalchemy_query(
"SELECT * FROM customers WHERE name = :name;",
sqlalchemy_credentials,
params={"name": "Marvin"},
)
return result
| (self, operation: str, parameters: Optional[Dict[str, Any]] = None, size: Optional[int] = None, **execution_options: Dict[str, Any]) -> List[Tuple[Any]] | [
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|
31,476 | prefect_sqlalchemy.database | fetch_one |
Fetch a single result from the database.
Repeated calls using the same inputs to *any* of the fetch methods of this
block will skip executing the operation again, and instead,
return the next set of results from the previous execution,
until the reset_cursors method is called.
Args:
operation: The SQL query or other operation to be executed.
parameters: The parameters for the operation.
**execution_options: Options to pass to `Connection.execution_options`.
Returns:
A list of tuples containing the data returned by the database,
where each row is a tuple and each column is a value in the tuple.
Examples:
Create a table, insert three rows into it, and fetch a row repeatedly.
```python
from prefect_sqlalchemy import SqlAlchemyConnector
with SqlAlchemyConnector.load("MY_BLOCK") as database:
database.execute("CREATE TABLE IF NOT EXISTS customers (name varchar, address varchar);")
database.execute_many(
"INSERT INTO customers (name, address) VALUES (:name, :address);",
seq_of_parameters=[
{"name": "Ford", "address": "Highway 42"},
{"name": "Unknown", "address": "Space"},
{"name": "Me", "address": "Myway 88"},
],
)
results = True
while results:
results = database.fetch_one("SELECT * FROM customers")
print(results)
```
| @flow
def sqlalchemy_query_flow():
sqlalchemy_credentials = DatabaseCredentials(
driver=AsyncDriver.SQLITE_AIOSQLITE,
database="prefect.db",
)
result = sqlalchemy_query(
"SELECT * FROM customers WHERE name = :name;",
sqlalchemy_credentials,
params={"name": "Marvin"},
)
return result
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|
31,478 | prefect_sqlalchemy.database | get_client |
Returns either an engine or connection that can be used to query from databases.
Args:
client_type: Select from either 'engine' or 'connection'.
**get_client_kwargs: Additional keyword arguments to pass to
either `get_engine` or `get_connection`.
Returns:
The authenticated SQLAlchemy engine or connection.
Examples:
Create an engine.
```python
from prefect_sqlalchemy import SqlalchemyConnector
sqlalchemy_connector = SqlAlchemyConnector.load("BLOCK_NAME")
engine = sqlalchemy_connector.get_client(client_type="engine")
```
Create a context managed connection.
```python
from prefect_sqlalchemy import SqlalchemyConnector
sqlalchemy_connector = SqlAlchemyConnector.load("BLOCK_NAME")
with sqlalchemy_connector.get_client(client_type="connection") as conn:
...
```
| def get_client(
self,
client_type: Literal["engine", "connection"],
**get_client_kwargs: Dict[str, Any],
) -> Union[Engine, AsyncEngine, Connection, AsyncConnection]:
"""
Returns either an engine or connection that can be used to query from databases.
Args:
client_type: Select from either 'engine' or 'connection'.
**get_client_kwargs: Additional keyword arguments to pass to
either `get_engine` or `get_connection`.
Returns:
The authenticated SQLAlchemy engine or connection.
Examples:
Create an engine.
```python
from prefect_sqlalchemy import SqlalchemyConnector
sqlalchemy_connector = SqlAlchemyConnector.load("BLOCK_NAME")
engine = sqlalchemy_connector.get_client(client_type="engine")
```
Create a context managed connection.
```python
from prefect_sqlalchemy import SqlalchemyConnector
sqlalchemy_connector = SqlAlchemyConnector.load("BLOCK_NAME")
with sqlalchemy_connector.get_client(client_type="connection") as conn:
...
```
""" # noqa: E501
if client_type == "engine":
client = self.get_engine(**get_client_kwargs)
elif client_type == "connection":
client = self.get_connection(**get_client_kwargs)
else:
raise ValueError(
f"{client_type!r} is not supported; choose from engine or connection."
)
return client
| (self, client_type: Literal['engine', 'connection'], **get_client_kwargs: Dict[str, Any]) -> Union[sqlalchemy.engine.base.Engine, sqlalchemy.ext.asyncio.engine.AsyncEngine, sqlalchemy.engine.base.Connection, sqlalchemy.ext.asyncio.engine.AsyncConnection] | [
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|
31,479 | prefect_sqlalchemy.database | get_connection |
Returns a connection that can be used to query from databases.
Args:
begin: Whether to begin a transaction on the connection; if True, if
any operations fail, the entire transaction will be rolled back.
**connect_kwargs: Additional keyword arguments to pass to either
`engine.begin` or engine.connect`.
Returns:
The SQLAlchemy Connection / AsyncConnection.
Examples:
Create an synchronous connection as a context-managed transaction.
```python
from prefect_sqlalchemy import SqlAlchemyConnector
sqlalchemy_connector = SqlAlchemyConnector.load("BLOCK_NAME")
with sqlalchemy_connector.get_connection(begin=False) as connection:
connection.execute("SELECT * FROM table LIMIT 1;")
```
Create an asynchronous connection as a context-managed transacation.
```python
import asyncio
from prefect_sqlalchemy import SqlAlchemyConnector
sqlalchemy_connector = SqlAlchemyConnector.load("BLOCK_NAME")
async with sqlalchemy_connector.get_connection(begin=False) as connection:
asyncio.run(connection.execute("SELECT * FROM table LIMIT 1;"))
```
| def get_connection(
self, begin: bool = True, **connect_kwargs: Dict[str, Any]
) -> Union[Connection, AsyncConnection]:
"""
Returns a connection that can be used to query from databases.
Args:
begin: Whether to begin a transaction on the connection; if True, if
any operations fail, the entire transaction will be rolled back.
**connect_kwargs: Additional keyword arguments to pass to either
`engine.begin` or engine.connect`.
Returns:
The SQLAlchemy Connection / AsyncConnection.
Examples:
Create an synchronous connection as a context-managed transaction.
```python
from prefect_sqlalchemy import SqlAlchemyConnector
sqlalchemy_connector = SqlAlchemyConnector.load("BLOCK_NAME")
with sqlalchemy_connector.get_connection(begin=False) as connection:
connection.execute("SELECT * FROM table LIMIT 1;")
```
Create an asynchronous connection as a context-managed transacation.
```python
import asyncio
from prefect_sqlalchemy import SqlAlchemyConnector
sqlalchemy_connector = SqlAlchemyConnector.load("BLOCK_NAME")
async with sqlalchemy_connector.get_connection(begin=False) as connection:
asyncio.run(connection.execute("SELECT * FROM table LIMIT 1;"))
```
""" # noqa: E501
engine = self.get_engine()
if begin:
connection = engine.begin(**connect_kwargs)
else:
connection = engine.connect(**connect_kwargs)
self.logger.info("Created a new connection.")
return connection
| (self, begin: bool = True, **connect_kwargs: Dict[str, Any]) -> Union[sqlalchemy.engine.base.Connection, sqlalchemy.ext.asyncio.engine.AsyncConnection] | [
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|
31,480 | prefect_sqlalchemy.database | get_engine |
Returns an authenticated engine that can be
used to query from databases.
If an existing engine exists, return that one.
Returns:
The authenticated SQLAlchemy Engine / AsyncEngine.
Examples:
Create an asynchronous engine to PostgreSQL using URL params.
```python
from prefect import flow
from prefect_sqlalchemy import (
SqlAlchemyConnector, ConnectionComponents, AsyncDriver
)
@flow
def sqlalchemy_credentials_flow():
sqlalchemy_credentials = SqlAlchemyConnector(
connection_info=ConnectionComponents(
driver=AsyncDriver.POSTGRESQL_ASYNCPG,
username="prefect",
password="prefect_password",
database="postgres"
)
)
print(sqlalchemy_credentials.get_engine())
sqlalchemy_credentials_flow()
```
Create a synchronous engine to Snowflake using the `url` kwarg.
```python
from prefect import flow
from prefect_sqlalchemy import SqlAlchemyConnector, AsyncDriver
@flow
def sqlalchemy_credentials_flow():
url = (
"snowflake://<user_login_name>:<password>"
"@<account_identifier>/<database_name>"
"?warehouse=<warehouse_name>"
)
sqlalchemy_credentials = SqlAlchemyConnector(url=url)
print(sqlalchemy_credentials.get_engine())
sqlalchemy_credentials_flow()
```
| def get_engine(
self, **create_engine_kwargs: Dict[str, Any]
) -> Union[Engine, AsyncEngine]:
"""
Returns an authenticated engine that can be
used to query from databases.
If an existing engine exists, return that one.
Returns:
The authenticated SQLAlchemy Engine / AsyncEngine.
Examples:
Create an asynchronous engine to PostgreSQL using URL params.
```python
from prefect import flow
from prefect_sqlalchemy import (
SqlAlchemyConnector, ConnectionComponents, AsyncDriver
)
@flow
def sqlalchemy_credentials_flow():
sqlalchemy_credentials = SqlAlchemyConnector(
connection_info=ConnectionComponents(
driver=AsyncDriver.POSTGRESQL_ASYNCPG,
username="prefect",
password="prefect_password",
database="postgres"
)
)
print(sqlalchemy_credentials.get_engine())
sqlalchemy_credentials_flow()
```
Create a synchronous engine to Snowflake using the `url` kwarg.
```python
from prefect import flow
from prefect_sqlalchemy import SqlAlchemyConnector, AsyncDriver
@flow
def sqlalchemy_credentials_flow():
url = (
"snowflake://<user_login_name>:<password>"
"@<account_identifier>/<database_name>"
"?warehouse=<warehouse_name>"
)
sqlalchemy_credentials = SqlAlchemyConnector(url=url)
print(sqlalchemy_credentials.get_engine())
sqlalchemy_credentials_flow()
```
"""
if self._engine is not None:
self.logger.debug("Reusing existing engine.")
return self._engine
engine_kwargs = dict(
url=self._rendered_url,
connect_args=self.connect_args or {},
**create_engine_kwargs,
)
if self._driver_is_async:
# no need to await here
engine = create_async_engine(**engine_kwargs)
else:
engine = create_engine(**engine_kwargs)
self.logger.info("Created a new engine.")
if self._engine is None:
self._engine = engine
return engine
| (self, **create_engine_kwargs: Dict[str, Any]) -> Union[sqlalchemy.engine.base.Engine, sqlalchemy.ext.asyncio.engine.AsyncEngine] | [
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|
31,483 | prefect_sqlalchemy.database | reset_async_connections |
Tries to close all opened connections and their results.
Examples:
Resets connections so `fetch_*` methods return new results.
```python
import asyncio
from prefect_sqlalchemy import SqlAlchemyConnector
async def example_run():
async with SqlAlchemyConnector.load("MY_BLOCK") as database:
results = await database.fetch_one("SELECT * FROM customers")
await database.reset_async_connections()
results = await database.fetch_one("SELECT * FROM customers")
asyncio.run(example_run())
```
| @sync_compatible
async def reset_connections(self) -> None:
"""
Tries to close all opened connections and their results.
Examples:
Resets connections so `fetch_*` methods return new results.
```python
from prefect_sqlalchemy import SqlAlchemyConnector
with SqlAlchemyConnector.load("MY_BLOCK") as database:
results = database.fetch_one("SELECT * FROM customers")
database.reset_connections()
results = database.fetch_one("SELECT * FROM customers")
```
"""
if self._driver_is_async:
raise RuntimeError(
f"{self._rendered_url.drivername} has no synchronous connections. "
f"Please use the `reset_async_connections` method instead."
)
if self._exit_stack is None:
self.logger.info("There were no connections to reset.")
return
self._reset_cursor_results()
self._exit_stack.close()
self.logger.info("Reset opened connections and their results.")
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|
31,484 | prefect_sqlalchemy.database | reset_connections |
Tries to close all opened connections and their results.
Examples:
Resets connections so `fetch_*` methods return new results.
```python
from prefect_sqlalchemy import SqlAlchemyConnector
with SqlAlchemyConnector.load("MY_BLOCK") as database:
results = database.fetch_one("SELECT * FROM customers")
database.reset_connections()
results = database.fetch_one("SELECT * FROM customers")
```
| @flow
def sqlalchemy_query_flow():
sqlalchemy_credentials = DatabaseCredentials(
driver=AsyncDriver.SQLITE_AIOSQLITE,
database="prefect.db",
)
result = sqlalchemy_query(
"SELECT * FROM customers WHERE name = :name;",
sqlalchemy_credentials,
params={"name": "Marvin"},
)
return result
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|
31,486 | prefect_sqlalchemy.credentials | SyncDriver |
Known dialects with their corresponding sync drivers.
Attributes:
POSTGRESQL_PSYCOPG2 (Enum): [postgresql+psycopg2](https://docs.sqlalchemy.org/en/14/dialects/postgresql.html#module-sqlalchemy.dialects.postgresql.psycopg2)
POSTGRESQL_PG8000 (Enum): [postgresql+pg8000](https://docs.sqlalchemy.org/en/14/dialects/postgresql.html#module-sqlalchemy.dialects.postgresql.pg8000)
POSTGRESQL_PSYCOPG2CFFI (Enum): [postgresql+psycopg2cffi](https://docs.sqlalchemy.org/en/14/dialects/postgresql.html#module-sqlalchemy.dialects.postgresql.psycopg2cffi)
POSTGRESQL_PYPOSTGRESQL (Enum): [postgresql+pypostgresql](https://docs.sqlalchemy.org/en/14/dialects/postgresql.html#module-sqlalchemy.dialects.postgresql.pypostgresql)
POSTGRESQL_PYGRESQL (Enum): [postgresql+pygresql](https://docs.sqlalchemy.org/en/14/dialects/postgresql.html#module-sqlalchemy.dialects.postgresql.pygresql)
MYSQL_MYSQLDB (Enum): [mysql+mysqldb](https://docs.sqlalchemy.org/en/14/dialects/mysql.html#module-sqlalchemy.dialects.mysql.mysqldb)
MYSQL_PYMYSQL (Enum): [mysql+pymysql](https://docs.sqlalchemy.org/en/14/dialects/mysql.html#module-sqlalchemy.dialects.mysql.pymysql)
MYSQL_MYSQLCONNECTOR (Enum): [mysql+mysqlconnector](https://docs.sqlalchemy.org/en/14/dialects/mysql.html#module-sqlalchemy.dialects.mysql.mysqlconnector)
MYSQL_CYMYSQL (Enum): [mysql+cymysql](https://docs.sqlalchemy.org/en/14/dialects/mysql.html#module-sqlalchemy.dialects.mysql.cymysql)
MYSQL_OURSQL (Enum): [mysql+oursql](https://docs.sqlalchemy.org/en/14/dialects/mysql.html#module-sqlalchemy.dialects.mysql.oursql)
MYSQL_PYODBC (Enum): [mysql+pyodbc](https://docs.sqlalchemy.org/en/14/dialects/mysql.html#module-sqlalchemy.dialects.mysql.pyodbc)
SQLITE_PYSQLITE (Enum): [sqlite+pysqlite](https://docs.sqlalchemy.org/en/14/dialects/sqlite.html#module-sqlalchemy.dialects.sqlite.pysqlite)
SQLITE_PYSQLCIPHER (Enum): [sqlite+pysqlcipher](https://docs.sqlalchemy.org/en/14/dialects/sqlite.html#module-sqlalchemy.dialects.sqlite.pysqlcipher)
ORACLE_CX_ORACLE (Enum): [oracle+cx_oracle](https://docs.sqlalchemy.org/en/14/dialects/oracle.html#module-sqlalchemy.dialects.oracle.cx_oracle)
MSSQL_PYODBC (Enum): [mssql+pyodbc](https://docs.sqlalchemy.org/en/14/dialects/mssql.html#module-sqlalchemy.dialects.mssql.pyodbc)
MSSQL_MXODBC (Enum): [mssql+mxodbc](https://docs.sqlalchemy.org/en/14/dialects/mssql.html#module-sqlalchemy.dialects.mssql.mxodbc)
MSSQL_PYMSSQL (Enum): [mssql+pymssql](https://docs.sqlalchemy.org/en/14/dialects/mssql.html#module-sqlalchemy.dialects.mssql.pymssql)
| class SyncDriver(Enum):
"""
Known dialects with their corresponding sync drivers.
Attributes:
POSTGRESQL_PSYCOPG2 (Enum): [postgresql+psycopg2](https://docs.sqlalchemy.org/en/14/dialects/postgresql.html#module-sqlalchemy.dialects.postgresql.psycopg2)
POSTGRESQL_PG8000 (Enum): [postgresql+pg8000](https://docs.sqlalchemy.org/en/14/dialects/postgresql.html#module-sqlalchemy.dialects.postgresql.pg8000)
POSTGRESQL_PSYCOPG2CFFI (Enum): [postgresql+psycopg2cffi](https://docs.sqlalchemy.org/en/14/dialects/postgresql.html#module-sqlalchemy.dialects.postgresql.psycopg2cffi)
POSTGRESQL_PYPOSTGRESQL (Enum): [postgresql+pypostgresql](https://docs.sqlalchemy.org/en/14/dialects/postgresql.html#module-sqlalchemy.dialects.postgresql.pypostgresql)
POSTGRESQL_PYGRESQL (Enum): [postgresql+pygresql](https://docs.sqlalchemy.org/en/14/dialects/postgresql.html#module-sqlalchemy.dialects.postgresql.pygresql)
MYSQL_MYSQLDB (Enum): [mysql+mysqldb](https://docs.sqlalchemy.org/en/14/dialects/mysql.html#module-sqlalchemy.dialects.mysql.mysqldb)
MYSQL_PYMYSQL (Enum): [mysql+pymysql](https://docs.sqlalchemy.org/en/14/dialects/mysql.html#module-sqlalchemy.dialects.mysql.pymysql)
MYSQL_MYSQLCONNECTOR (Enum): [mysql+mysqlconnector](https://docs.sqlalchemy.org/en/14/dialects/mysql.html#module-sqlalchemy.dialects.mysql.mysqlconnector)
MYSQL_CYMYSQL (Enum): [mysql+cymysql](https://docs.sqlalchemy.org/en/14/dialects/mysql.html#module-sqlalchemy.dialects.mysql.cymysql)
MYSQL_OURSQL (Enum): [mysql+oursql](https://docs.sqlalchemy.org/en/14/dialects/mysql.html#module-sqlalchemy.dialects.mysql.oursql)
MYSQL_PYODBC (Enum): [mysql+pyodbc](https://docs.sqlalchemy.org/en/14/dialects/mysql.html#module-sqlalchemy.dialects.mysql.pyodbc)
SQLITE_PYSQLITE (Enum): [sqlite+pysqlite](https://docs.sqlalchemy.org/en/14/dialects/sqlite.html#module-sqlalchemy.dialects.sqlite.pysqlite)
SQLITE_PYSQLCIPHER (Enum): [sqlite+pysqlcipher](https://docs.sqlalchemy.org/en/14/dialects/sqlite.html#module-sqlalchemy.dialects.sqlite.pysqlcipher)
ORACLE_CX_ORACLE (Enum): [oracle+cx_oracle](https://docs.sqlalchemy.org/en/14/dialects/oracle.html#module-sqlalchemy.dialects.oracle.cx_oracle)
MSSQL_PYODBC (Enum): [mssql+pyodbc](https://docs.sqlalchemy.org/en/14/dialects/mssql.html#module-sqlalchemy.dialects.mssql.pyodbc)
MSSQL_MXODBC (Enum): [mssql+mxodbc](https://docs.sqlalchemy.org/en/14/dialects/mssql.html#module-sqlalchemy.dialects.mssql.mxodbc)
MSSQL_PYMSSQL (Enum): [mssql+pymssql](https://docs.sqlalchemy.org/en/14/dialects/mssql.html#module-sqlalchemy.dialects.mssql.pymssql)
""" # noqa
POSTGRESQL_PSYCOPG2 = "postgresql+psycopg2"
POSTGRESQL_PG8000 = "postgresql+pg8000"
POSTGRESQL_PSYCOPG2CFFI = "postgresql+psycopg2cffi"
POSTGRESQL_PYPOSTGRESQL = "postgresql+pypostgresql"
POSTGRESQL_PYGRESQL = "postgresql+pygresql"
MYSQL_MYSQLDB = "mysql+mysqldb"
MYSQL_PYMYSQL = "mysql+pymysql"
MYSQL_MYSQLCONNECTOR = "mysql+mysqlconnector"
MYSQL_CYMYSQL = "mysql+cymysql"
MYSQL_OURSQL = "mysql+oursql"
MYSQL_PYODBC = "mysql+pyodbc"
SQLITE_PYSQLITE = "sqlite+pysqlite"
SQLITE_PYSQLCIPHER = "sqlite+pysqlcipher"
ORACLE_CX_ORACLE = "oracle+cx_oracle"
MSSQL_PYODBC = "mssql+pyodbc"
MSSQL_MXODBC = "mssql+mxodbc"
MSSQL_PYMSSQL = "mssql+pymssql"
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|
31,490 | laspy.copc | Bounds | Bounds(mins: numpy.ndarray, maxs: numpy.ndarray) | class Bounds:
mins: np.ndarray
maxs: np.ndarray
def overlaps(self, other: "Bounds") -> bool:
return bool(np.all((self.mins <= other.maxs) & (self.maxs >= other.mins)))
def ensure_3d(self, mins: np.ndarray, maxs: np.ndarray) -> "Bounds":
new_mins = np.zeros(3, dtype=np.float64)
new_maxs = np.zeros(3, dtype=np.float64)
new_mins[: len(self.mins)] = self.mins[:]
new_mins[len(self.mins) :] = mins[len(self.mins) :]
new_maxs[: len(self.maxs)] = self.maxs[:]
new_maxs[len(self.maxs) :] = maxs[len(self.maxs) :]
return Bounds(new_mins, new_maxs)
| (mins: numpy.ndarray, maxs: numpy.ndarray) -> None | [
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|
31,491 | laspy.copc | __eq__ | null | import io
import multiprocessing
import os
import struct
from concurrent.futures import ThreadPoolExecutor
from dataclasses import dataclass
from math import ceil, log2
from operator import attrgetter
from queue import Queue, SimpleQueue
from threading import Thread
from typing import Dict, Iterator, List, Optional, Tuple, Union
try:
import requests
except ModuleNotFoundError:
requests = None
else:
from requests.adapters import HTTPAdapter
from requests.packages.urllib3.util.retry import Retry
try:
import lazrs
except ModuleNotFoundError:
lazrs = None
import numpy as np
from .compression import DecompressionSelection
from .errors import LaspyException, LazError
from .header import LasHeader
from .point.record import PackedPointRecord, ScaleAwarePointRecord
from .vlrs.known import BaseKnownVLR
DEFAULT_HTTP_WORKERS_NUM = multiprocessing.cpu_count() * 5
def requests_retry_session(
retries=3,
backoff_factor=0.3,
status_forcelist=(500, 502, 504),
session=None,
):
session = session or requests.Session()
retry = Retry(
total=retries,
read=retries,
connect=retries,
backoff_factor=backoff_factor,
status_forcelist=status_forcelist,
)
adapter = HTTPAdapter(max_retries=retry)
session.mount("http://", adapter)
session.mount("https://", adapter)
return session
| (self, other) | [
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31,493 | laspy.copc | __repr__ | null | def __hash__(self):
return hash((self.level, self.x, self.y, self.z))
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|
31,494 | laspy.copc | ensure_3d | null | def ensure_3d(self, mins: np.ndarray, maxs: np.ndarray) -> "Bounds":
new_mins = np.zeros(3, dtype=np.float64)
new_maxs = np.zeros(3, dtype=np.float64)
new_mins[: len(self.mins)] = self.mins[:]
new_mins[len(self.mins) :] = mins[len(self.mins) :]
new_maxs[: len(self.maxs)] = self.maxs[:]
new_maxs[len(self.maxs) :] = maxs[len(self.maxs) :]
return Bounds(new_mins, new_maxs)
| (self, mins: numpy.ndarray, maxs: numpy.ndarray) -> laspy.copc.Bounds | [
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|
31,495 | laspy.copc | overlaps | null | def overlaps(self, other: "Bounds") -> bool:
return bool(np.all((self.mins <= other.maxs) & (self.maxs >= other.mins)))
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|
31,496 | laspy.copc | CopcReader |
Class allowing to do queries over a `COPC`_ LAZ
In short, COPC files are LAZ 1.4 files organized in a particular way
(Octree) making it possible to do spatial queries
as well as queries with a level of details.
CopcReader **requires** the ``lazrz`` backend to work.
Optionaly, if ``requests`` is installed, CopcReader can handle
Copc files that are on a remote HTTP server
This class *only* reads COPC files, it does not support normal
LAS/LAZ files.
To create an instance of it you'll likely
want to use the :meth:`.CopcReader.open` constructor
.. versionadded:: 2.2
.. _COPC: https://github.com/copcio/copcio.github.io
| class CopcReader:
"""
Class allowing to do queries over a `COPC`_ LAZ
In short, COPC files are LAZ 1.4 files organized in a particular way
(Octree) making it possible to do spatial queries
as well as queries with a level of details.
CopcReader **requires** the ``lazrz`` backend to work.
Optionaly, if ``requests`` is installed, CopcReader can handle
Copc files that are on a remote HTTP server
This class *only* reads COPC files, it does not support normal
LAS/LAZ files.
To create an instance of it you'll likely
want to use the :meth:`.CopcReader.open` constructor
.. versionadded:: 2.2
.. _COPC: https://github.com/copcio/copcio.github.io
"""
def __init__(
self,
stream,
close_fd: bool = True,
http_num_threads: int = DEFAULT_HTTP_WORKERS_NUM,
_http_strategy: str = "queue",
decompression_selection: DecompressionSelection = DecompressionSelection.all(),
):
"""
Creates a CopcReader.
Parameters
---------
stream: the stream from where data can be read.
It must have the following file object methods:
read, seek, tell
http_num_threads: int, optional, default num cpu * 5
Number of worker threads to do concurent HTTP requests,
ignored when reading non-HTTP file
close_fd: optional, default bool
Whether the stream/file object shall be closed, this only work
when using the CopcReader in a with statement.
decompression_selection: DecompressionSelection,
see :func:`laspy.open`
.. versionadded:: 2.4
The ``decompression_selection`` parameter.
"""
if lazrs is None:
raise LazError("COPC support requires the 'lazrs' backend")
self.source = stream
self.close_fd = close_fd
self.http_num_threads = http_num_threads
self.http_strategy = _http_strategy
self.decompression_selection: lazrs.DecompressionSelection = (
decompression_selection.to_lazrs()
)
self.header = LasHeader.read_from(self.source)
self.copc_info: CopcInfoVlr = self.header.vlrs[0]
if not isinstance(self.copc_info, CopcInfoVlr):
copc_info_exists = any(
isinstance(vlr, CopcInfoVlr) for vlr in self.header.vlrs
)
if copc_info_exists:
raise LaspyException(
"This file is not a valid COPC, "
"it does have a COPC VLR, however it is not the first VLR "
"as it should"
)
else:
raise LaspyException(
"This file is not a valid COPC, " "it does not have a COPC VLR"
)
if self.copc_info.hierarchy_root_offset < self.header.offset_to_point_data:
self.hierarchy = self.header.vlrs.extract("CopcHierarchyVlr")[0]
else:
# TODO maybe we could read the whole EVLR's byte
# so we could load the octree without having any more requests to do
# since everything would be in memory
self.source.seek(self.copc_info.hierarchy_root_offset)
# This only contains the record_data_bytes
root_hierarchy_vlr_bytes = self.source.read(
self.copc_info.hierarchy_root_size
)
hierarchy = CopcHierarchyVlr()
hierarchy.parse_record_data(root_hierarchy_vlr_bytes)
self.laszip_vlr = self.header.vlrs.pop(self.header.vlrs.index("LasZipVlr"))
self.source.seek(self.copc_info.hierarchy_root_offset)
root_page_bytes = self.source.read(self.copc_info.hierarchy_root_size)
# At first the hierary only contains the root page entries
# but it will get updated as the queries may need more pages
self.root_page = HierarchyPage.from_bytes(root_page_bytes)
@classmethod
def open(
cls,
source: Union[str, os.PathLike, io.IOBase],
http_num_threads: int = DEFAULT_HTTP_WORKERS_NUM,
_http_strategy: str = "queue",
decompression_selection: DecompressionSelection = DecompressionSelection.all(),
) -> "CopcReader":
"""
Opens the COPC file.
Parameters
----------
source: str, io.IOBase, uri or file-like object of the COPC file.
Supported sources are:
- 'local' files accesible with a path.
- HTTP / HTTPS endpoints. The pyhon package ``requests`` is
required in order to be able to work with HTTP endpoints.
- file-like objects, e.g. fsspec io.IOBase objects.
http_num_threads: int, optional, default num cpu * 5
Number of worker threads to do concurent HTTP requests,
ignored when reading non-HTTP file
decompression_selection: DecompressionSelection,
see :func:`laspy.open`
Opening a local file
.. code-block:: Python
from laspy import CopcReader
with CopcReader.open("some_file.laz") as reader:
...
Opening a file on a remite HTTP server
(``requests`` package required)
.. code-block:: Python
from laspy import CopcReader
url = "https://s3.amazonaws.com/hobu-lidar/autzen-classified.copc.laz"
with CopcReader.open(url) as reader:
...
.. versionadded:: 2.4
The ``decompression_selection`` parameter.
"""
if isinstance(source, (str, os.PathLike)):
source = str(source)
if source.startswith("http"):
source = HttpRangeStream(source)
else:
source = open(source, mode="rb")
return cls(
source,
http_num_threads=http_num_threads,
decompression_selection=decompression_selection,
)
def query(
self,
bounds: Optional[Bounds] = None,
resolution: Optional[Union[float, int]] = None,
level: Optional[Union[int, range]] = None,
) -> ScaleAwarePointRecord:
""" "
Query the COPC file to retrieve the points matching the
requested bounds and level.
Parameters
----------
bounds: Bounds, optional, default None
The bounds for which you wish to aquire points.
If None, the whole file's bounds will be considered
2D bounds are suported, (No point will be filtered on its Z coordinate)
resolution: float or int, optional, default None
Limits the octree levels to be queried in order to have
a point cloud with the requested resolution.
- The unit is the one of the data.
- If None, the resulting cloud will be at the
full resolution offered by the COPC source
- Mutually exclusive with level parameter
level: int or range, optional, default None
The level of detail (LOD).
- If None, all LOD are going to be considered
- If it is an int, only points that are of the requested LOD
will be returned.
- If it is a range, points for which the LOD is within the range
will be returned
"""
if resolution is not None and level is not None:
raise ValueError("Cannot specify both level and resolution")
elif resolution is not None and level is None:
level_max = max(1, ceil(log2(self.copc_info.spacing / resolution)) + 1)
level = range(0, level_max)
if isinstance(level, int):
level = range(level, level + 1)
if bounds is not None:
bounds = bounds.ensure_3d(self.header.mins, self.header.maxs)
nodes = load_octree_for_query(
self.source,
self.copc_info,
self.root_page,
query_bounds=bounds,
level_range=level,
| (stream, close_fd: bool = True, http_num_threads: int = 300, _http_strategy: str = 'queue', decompression_selection: laspy._compression.selection.DecompressionSelection = <DecompressionSelection.ALL_EXTRA_BYTES|WAVEPACKET|NIR|RGB|GPS_TIME|POINT_SOURCE_ID|USER_DATA|SCAN_ANGLE|INTENSITY|FLAGS|CLASSIFICATION|Z|XY_RETURNS_CHANNEL: 8191>) | [
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|
31,497 | laspy.copc | __enter__ | null | def __enter__(self) -> "CopcReader":
return self
| (self) -> laspy.copc.CopcReader | [
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|
31,498 | laspy.copc | __exit__ | null | def __exit__(self, _exc_type, _exc_val, _exc_tb) -> None:
if self.close_fd:
self.source.close()
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|
31,499 | laspy.copc | __init__ |
Creates a CopcReader.
Parameters
---------
stream: the stream from where data can be read.
It must have the following file object methods:
read, seek, tell
http_num_threads: int, optional, default num cpu * 5
Number of worker threads to do concurent HTTP requests,
ignored when reading non-HTTP file
close_fd: optional, default bool
Whether the stream/file object shall be closed, this only work
when using the CopcReader in a with statement.
decompression_selection: DecompressionSelection,
see :func:`laspy.open`
.. versionadded:: 2.4
The ``decompression_selection`` parameter.
| def __init__(
self,
stream,
close_fd: bool = True,
http_num_threads: int = DEFAULT_HTTP_WORKERS_NUM,
_http_strategy: str = "queue",
decompression_selection: DecompressionSelection = DecompressionSelection.all(),
):
"""
Creates a CopcReader.
Parameters
---------
stream: the stream from where data can be read.
It must have the following file object methods:
read, seek, tell
http_num_threads: int, optional, default num cpu * 5
Number of worker threads to do concurent HTTP requests,
ignored when reading non-HTTP file
close_fd: optional, default bool
Whether the stream/file object shall be closed, this only work
when using the CopcReader in a with statement.
decompression_selection: DecompressionSelection,
see :func:`laspy.open`
.. versionadded:: 2.4
The ``decompression_selection`` parameter.
"""
if lazrs is None:
raise LazError("COPC support requires the 'lazrs' backend")
self.source = stream
self.close_fd = close_fd
self.http_num_threads = http_num_threads
self.http_strategy = _http_strategy
self.decompression_selection: lazrs.DecompressionSelection = (
decompression_selection.to_lazrs()
)
self.header = LasHeader.read_from(self.source)
self.copc_info: CopcInfoVlr = self.header.vlrs[0]
if not isinstance(self.copc_info, CopcInfoVlr):
copc_info_exists = any(
isinstance(vlr, CopcInfoVlr) for vlr in self.header.vlrs
)
if copc_info_exists:
raise LaspyException(
"This file is not a valid COPC, "
"it does have a COPC VLR, however it is not the first VLR "
"as it should"
)
else:
raise LaspyException(
"This file is not a valid COPC, " "it does not have a COPC VLR"
)
if self.copc_info.hierarchy_root_offset < self.header.offset_to_point_data:
self.hierarchy = self.header.vlrs.extract("CopcHierarchyVlr")[0]
else:
# TODO maybe we could read the whole EVLR's byte
# so we could load the octree without having any more requests to do
# since everything would be in memory
self.source.seek(self.copc_info.hierarchy_root_offset)
# This only contains the record_data_bytes
root_hierarchy_vlr_bytes = self.source.read(
self.copc_info.hierarchy_root_size
)
hierarchy = CopcHierarchyVlr()
hierarchy.parse_record_data(root_hierarchy_vlr_bytes)
self.laszip_vlr = self.header.vlrs.pop(self.header.vlrs.index("LasZipVlr"))
self.source.seek(self.copc_info.hierarchy_root_offset)
root_page_bytes = self.source.read(self.copc_info.hierarchy_root_size)
# At first the hierary only contains the root page entries
# but it will get updated as the queries may need more pages
self.root_page = HierarchyPage.from_bytes(root_page_bytes)
| (self, stream, close_fd: bool = True, http_num_threads: int = 300, _http_strategy: str = 'queue', decompression_selection: laspy._compression.selection.DecompressionSelection = <DecompressionSelection.ALL_EXTRA_BYTES|WAVEPACKET|NIR|RGB|GPS_TIME|POINT_SOURCE_ID|USER_DATA|SCAN_ANGLE|INTENSITY|FLAGS|CLASSIFICATION|Z|XY_RETURNS_CHANNEL: 8191>) | [
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|
31,500 | laspy.copc | _fetch_all_chunks | null | def _fetch_all_chunks(
self, grouped_nodes: List[List[OctreeNode]]
) -> Tuple[bytearray, int, List[Tuple[int, int]]]:
num_points = 0
num_compressed_bytes = 0
chunk_table: List[Tuple[int, int]] = []
byte_queries: List[Tuple[int, int]] = []
for group in grouped_nodes:
num_compressed_group_bytes = 0
for node in group:
chunk_table.append((node.point_count, node.byte_size))
num_compressed_group_bytes += node.byte_size
num_points += node.point_count
num_compressed_bytes += num_compressed_group_bytes
byte_queries.append((group[0].offset, num_compressed_group_bytes))
compressed_bytes = bytearray(num_compressed_bytes)
if isinstance(self.source, HttpRangeStream):
if self.http_strategy == "queue":
http_queue_strategy(
self.source, byte_queries, compressed_bytes, self.http_num_threads
)
else:
http_thread_executor_strategy(
self.source, byte_queries, compressed_bytes, self.http_num_threads
)
elif hasattr(self.source, "readinto"):
citer = ChunkIter(compressed_bytes)
for offset, size in byte_queries:
self.source.seek(offset)
cc = citer.next(size)
self.source.readinto(cc)
else:
citer = ChunkIter(compressed_bytes)
for offset, size in byte_queries:
self.source.seek(offset)
cc = citer.next(size)
cc[:] = self.source.read(size)
return compressed_bytes, num_points, chunk_table
| (self, grouped_nodes: List[List[laspy.copc.OctreeNode]]) -> Tuple[bytearray, int, List[Tuple[int, int]]] | [
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-0.06337902694940567,
-0.12720152735710144,
0.03658614307641983,
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|
31,501 | laspy.copc | _fetch_and_decrompress_points_of_nodes | null | def _fetch_and_decrompress_points_of_nodes(
self, nodes_to_read: List[OctreeNode]
) -> ScaleAwarePointRecord:
if not nodes_to_read:
return ScaleAwarePointRecord.empty(header=self.header)
# Group together contiguous nodes
# so that we minimize the number of
# read requests (seek + read) / http requests
nodes_to_read = sorted(nodes_to_read, key=attrgetter("offset"))
grouped_nodes: List[List[OctreeNode]] = []
current_group: List[OctreeNode] = []
last_node_end = nodes_to_read[0].offset
for node in nodes_to_read:
if node.offset == last_node_end:
current_group.append(node)
last_node_end += node.byte_size
else:
grouped_nodes.append(current_group)
current_group = [node]
last_node_end = node.offset + node.byte_size
if current_group:
grouped_nodes.append(current_group)
compressed_bytes, num_points, chunk_table = self._fetch_all_chunks(
grouped_nodes
)
points_array = np.zeros(
num_points * self.header.point_format.size, dtype=np.uint8
)
lazrs.decompress_points_with_chunk_table(
compressed_bytes,
self.laszip_vlr.record_data,
points_array,
chunk_table,
self.decompression_selection,
)
r = PackedPointRecord.from_buffer(points_array, self.header.point_format)
points = ScaleAwarePointRecord(
r.array, r.point_format, self.header.scales, self.header.offsets
)
return points
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|
31,502 | laspy.copc | level_query | null | def level_query(self, level: Union[int, range]) -> ScaleAwarePointRecord:
return self.query(bounds=None, level=level)
| (self, level: Union[int, range]) -> laspy.point.record.ScaleAwarePointRecord | [
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|
31,503 | laspy.copc | query | "
Query the COPC file to retrieve the points matching the
requested bounds and level.
Parameters
----------
bounds: Bounds, optional, default None
The bounds for which you wish to aquire points.
If None, the whole file's bounds will be considered
2D bounds are suported, (No point will be filtered on its Z coordinate)
resolution: float or int, optional, default None
Limits the octree levels to be queried in order to have
a point cloud with the requested resolution.
- The unit is the one of the data.
- If None, the resulting cloud will be at the
full resolution offered by the COPC source
- Mutually exclusive with level parameter
level: int or range, optional, default None
The level of detail (LOD).
- If None, all LOD are going to be considered
- If it is an int, only points that are of the requested LOD
will be returned.
- If it is a range, points for which the LOD is within the range
will be returned
| def query(
self,
bounds: Optional[Bounds] = None,
resolution: Optional[Union[float, int]] = None,
level: Optional[Union[int, range]] = None,
) -> ScaleAwarePointRecord:
""" "
Query the COPC file to retrieve the points matching the
requested bounds and level.
Parameters
----------
bounds: Bounds, optional, default None
The bounds for which you wish to aquire points.
If None, the whole file's bounds will be considered
2D bounds are suported, (No point will be filtered on its Z coordinate)
resolution: float or int, optional, default None
Limits the octree levels to be queried in order to have
a point cloud with the requested resolution.
- The unit is the one of the data.
- If None, the resulting cloud will be at the
full resolution offered by the COPC source
- Mutually exclusive with level parameter
level: int or range, optional, default None
The level of detail (LOD).
- If None, all LOD are going to be considered
- If it is an int, only points that are of the requested LOD
will be returned.
- If it is a range, points for which the LOD is within the range
will be returned
"""
if resolution is not None and level is not None:
raise ValueError("Cannot specify both level and resolution")
elif resolution is not None and level is None:
level_max = max(1, ceil(log2(self.copc_info.spacing / resolution)) + 1)
level = range(0, level_max)
if isinstance(level, int):
level = range(level, level + 1)
if bounds is not None:
bounds = bounds.ensure_3d(self.header.mins, self.header.maxs)
nodes = load_octree_for_query(
self.source,
self.copc_info,
self.root_page,
query_bounds=bounds,
level_range=level,
)
# print("num nodes to query:", len(nodes));
points = self._fetch_and_decrompress_points_of_nodes(nodes)
if bounds is not None:
MINS = np.round(
(bounds.mins - self.header.offsets) / self.header.scales
).astype(np.int32)
MAXS = np.round(
(bounds.maxs - self.header.offsets) / self.header.scales
).astype(np.int32)
x_keep = (MINS[0] <= points.X) & (points.X <= MAXS[0])
y_keep = (MINS[1] <= points.Y) & (points.Y <= MAXS[1])
z_keep = (MINS[2] <= points.Z) & (points.Z <= MAXS[2])
# using scaled coordinates
# x, y, z = np.array(points.x), np.array(points.y), np.array(points.z)
# x_keep = (bounds.mins[0] <= x) & (x <= bounds.maxs[0])
# y_keep = (bounds.mins[1] <= y) & (y <= bounds.maxs[1])
# z_keep = (bounds.mins[2] <= z) & (z <= bounds.maxs[2])
keep_mask = x_keep & y_keep & z_keep
points.array = points.array[keep_mask].copy()
return points
| (self, bounds: Optional[laspy.copc.Bounds] = None, resolution: Union[float, int, NoneType] = None, level: Union[int, range, NoneType] = None) -> laspy.point.record.ScaleAwarePointRecord | [
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|
31,504 | laspy.copc | spatial_query | null | def spatial_query(self, bounds: Bounds) -> ScaleAwarePointRecord:
return self.query(bounds=bounds, level=None)
| (self, bounds: laspy.copc.Bounds) -> laspy.point.record.ScaleAwarePointRecord | [
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|
31,505 | laspy._compression.selection | DecompressionSelection |
Holds which fields to decompress or not.
Only used for files with version >= 1.4 && point format id >= 6.
Ignored on other cases.
Each flag in the enum has a corresponding ``decompress_$name`` and
``skip_$name`` methods to easily create a selection.
>>> import laspy
>>> # Creating a selection that decompresses the base + z field
>>> selection = laspy.DecompressionSelection.base().decompress_z()
>>> selection.is_set(laspy.DecompressionSelection.Z)
True
>>> selection.is_set(laspy.DecompressionSelection.INTENSITY)
False
>>> # Creating a selection that decompresses all fields but the intensity
>>> selection = laspy.DecompressionSelection.all().skip_intensity()
>>> selection.is_set(laspy.DecompressionSelection.INTENSITY)
False
>>> selection.is_set(laspy.DecompressionSelection.Z)
True
.. versionadded:: 2.4
| class DecompressionSelection(enum.IntFlag):
"""
Holds which fields to decompress or not.
Only used for files with version >= 1.4 && point format id >= 6.
Ignored on other cases.
Each flag in the enum has a corresponding ``decompress_$name`` and
``skip_$name`` methods to easily create a selection.
>>> import laspy
>>> # Creating a selection that decompresses the base + z field
>>> selection = laspy.DecompressionSelection.base().decompress_z()
>>> selection.is_set(laspy.DecompressionSelection.Z)
True
>>> selection.is_set(laspy.DecompressionSelection.INTENSITY)
False
>>> # Creating a selection that decompresses all fields but the intensity
>>> selection = laspy.DecompressionSelection.all().skip_intensity()
>>> selection.is_set(laspy.DecompressionSelection.INTENSITY)
False
>>> selection.is_set(laspy.DecompressionSelection.Z)
True
.. versionadded:: 2.4
"""
#: Flag to decompress x, y, return number, number of returns and scanner channel
XY_RETURNS_CHANNEL = enum.auto()
#: Flag to decompress z
Z = enum.auto()
#: Flag to decompress the classification
CLASSIFICATION = enum.auto()
#: Flag to decompress the classification flags (withheld, key point, overlap, etc)
FLAGS = enum.auto()
#: Flag to decompress the intensity
INTENSITY = enum.auto()
#: Flag to decompress the scan angle
SCAN_ANGLE = enum.auto()
#: Flag to decompress the user data
USER_DATA = enum.auto()
#: Flag to decompress the point source id
POINT_SOURCE_ID = enum.auto()
#: Flag to decompress the gps time
GPS_TIME = enum.auto()
#: Flag to decompress the red, green, blue
RGB = enum.auto()
#: Flag to decompress the nir
NIR = enum.auto()
#: Flag to decompress the wavepacket
WAVEPACKET = enum.auto()
#: Flag to decompress all the extra bytes
ALL_EXTRA_BYTES = enum.auto()
@classmethod
def all(cls) -> "DecompressionSelection":
"""Returns a selection where all fields will be decompressed"""
selection = cls.base()
for flag in cls:
selection = selection._set(flag)
return selection
@classmethod
def base(cls) -> "DecompressionSelection":
"""
Returns a decompression selection where only the base
x, y, return number, number of returns and scanner channel will be decompressed
"""
return cls.xy_returns_channel()
@classmethod
def xy_returns_channel(cls) -> "DecompressionSelection":
"""
Returns a decompression selection where only the base
x, y, return number, number of returns and scanner channel will be decompressed
"""
return cls.XY_RETURNS_CHANNEL
def to_lazrs(self) -> "lazrs.DecompressionSelection":
import lazrs
variant_mapping = {
DecompressionSelection.XY_RETURNS_CHANNEL: lazrs.SELECTIVE_DECOMPRESS_XY_RETURNS_CHANNEL,
DecompressionSelection.Z: lazrs.SELECTIVE_DECOMPRESS_Z,
DecompressionSelection.CLASSIFICATION: lazrs.SELECTIVE_DECOMPRESS_CLASSIFICATION,
DecompressionSelection.FLAGS: lazrs.SELECTIVE_DECOMPRESS_FLAGS,
DecompressionSelection.INTENSITY: lazrs.SELECTIVE_DECOMPRESS_INTENSITY,
DecompressionSelection.SCAN_ANGLE: lazrs.SELECTIVE_DECOMPRESS_SCAN_ANGLE,
DecompressionSelection.USER_DATA: lazrs.SELECTIVE_DECOMPRESS_USER_DATA,
DecompressionSelection.POINT_SOURCE_ID: lazrs.SELECTIVE_DECOMPRESS_POINT_SOURCE_ID,
DecompressionSelection.GPS_TIME: lazrs.SELECTIVE_DECOMPRESS_GPS_TIME,
DecompressionSelection.RGB: lazrs.SELECTIVE_DECOMPRESS_RGB,
DecompressionSelection.NIR: lazrs.SELECTIVE_DECOMPRESS_NIR,
DecompressionSelection.WAVEPACKET: lazrs.SELECTIVE_DECOMPRESS_WAVEPACKET,
DecompressionSelection.ALL_EXTRA_BYTES: lazrs.SELECTIVE_DECOMPRESS_ALL_EXTRA_BYTES,
}
lazrs_selection = lazrs.SELECTIVE_DECOMPRESS_XY_RETURNS_CHANNEL
for variant in DecompressionSelection:
lazrs_selection |= variant_mapping[variant] if self.is_set(variant) else 0
return lazrs.DecompressionSelection(lazrs_selection)
def to_laszip(self) -> int:
import laszip
variant_mapping = {
DecompressionSelection.XY_RETURNS_CHANNEL: laszip.DECOMPRESS_SELECTIVE_CHANNEL_RETURNS_XY,
DecompressionSelection.Z: laszip.DECOMPRESS_SELECTIVE_Z,
DecompressionSelection.CLASSIFICATION: laszip.DECOMPRESS_SELECTIVE_CLASSIFICATION,
DecompressionSelection.FLAGS: laszip.DECOMPRESS_SELECTIVE_FLAGS,
DecompressionSelection.INTENSITY: laszip.DECOMPRESS_SELECTIVE_INTENSITY,
DecompressionSelection.SCAN_ANGLE: laszip.DECOMPRESS_SELECTIVE_SCAN_ANGLE,
DecompressionSelection.USER_DATA: laszip.DECOMPRESS_SELECTIVE_USER_DATA,
DecompressionSelection.POINT_SOURCE_ID: laszip.DECOMPRESS_SELECTIVE_POINT_SOURCE,
DecompressionSelection.GPS_TIME: laszip.DECOMPRESS_SELECTIVE_GPS_TIME,
DecompressionSelection.RGB: laszip.DECOMPRESS_SELECTIVE_RGB,
DecompressionSelection.NIR: laszip.DECOMPRESS_SELECTIVE_NIR,
DecompressionSelection.WAVEPACKET: laszip.DECOMPRESS_SELECTIVE_WAVEPACKET,
DecompressionSelection.ALL_EXTRA_BYTES: laszip.DECOMPRESS_SELECTIVE_EXTRA_BYTES,
}
laszip_selection = laszip.DECOMPRESS_SELECTIVE_CHANNEL_RETURNS_XY
for variant in DecompressionSelection:
laszip_selection |= variant_mapping[variant] if self.is_set(variant) else 0
return laszip_selection
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|
31,506 | laspy.point.dims | DimensionInfo | Tuple that contains information of a dimension | class DimensionInfo(NamedTuple):
"""Tuple that contains information of a dimension"""
name: str
kind: DimensionKind
num_bits: int
num_elements: int = 1
is_standard: bool = True
description: str = ""
offsets: Optional[np.ndarray] = None
scales: Optional[np.ndarray] = None
@classmethod
def from_extra_bytes_param(cls, params):
me = cls(
params.name,
DimensionKind.from_letter(params.type.base.kind),
params.type.itemsize * 8,
params.type.shape[0] if params.type.ndim == 1 else 1,
False,
params.description,
params.offsets,
params.scales,
)
me._validate()
return me
@classmethod
def from_dtype(
cls,
name: str,
dtype: np.dtype,
is_standard: bool = True,
description: str = "",
offsets: Optional[np.ndarray] = None,
scales: Optional[np.ndarray] = None,
) -> "DimensionInfo":
if dtype.ndim != 0:
num_elements = dtype.shape[0]
else:
num_elements = 1
kind = DimensionKind.from_letter(dtype.base.kind)
num_bits = dtype.itemsize * 8
self = cls(
name,
kind,
num_bits,
num_elements,
is_standard,
description=description,
offsets=offsets,
scales=scales,
)
self._validate()
return self
@classmethod
def from_bitmask(
cls, name: str, bit_mask: int, is_standard: bool = False
) -> "DimensionInfo":
kind = DimensionKind.BitField
bit_size = num_bit_set(bit_mask)
return cls(name, kind, bit_size, is_standard=is_standard)
@property
def num_bytes(self) -> int:
return int(self.num_bits // 8)
@property
def num_bytes_singular_element(self) -> int:
return int(self.num_bits // (8 * self.num_elements))
@property
def is_scaled(self) -> bool:
return self.scales is not None or self.offsets is not None
@property
def max(self):
if self.kind == DimensionKind.BitField:
return (2**self.num_bits) - 1
elif self.kind == DimensionKind.FloatingPoint:
return np.finfo(self.type_str()).max
else:
return np.iinfo(self.type_str()).max
@property
def min(self):
if (
self.kind == DimensionKind.BitField
or self.kind == DimensionKind.UnsignedInteger
):
return 0
elif self.kind == DimensionKind.FloatingPoint:
return np.finfo(self.type_str()).min
else:
return np.iinfo(self.type_str()).min
def type_str(self) -> Optional[str]:
if self.kind == DimensionKind.BitField:
return None
if self.num_elements == 1:
return f"{self.kind.letter()}{self.num_bytes_singular_element}"
return (
f"{self.num_elements}{self.kind.letter()}{self.num_bytes_singular_element}"
)
@property
def dtype(self) -> Optional[np.dtype]:
type_str = self.type_str()
if type_str is not None:
return np.dtype(type_str)
return None
def __eq__(self, other: "DimensionInfo") -> bool:
# Named Tuple implements that for us, but
# when scales and offset are not None (thus are array)
# The default '==' won't work
# (ValueError, value of an array with more than one element is ambiguous)
return (
self.name == other.name
and self.kind == other.kind
and self.num_bits == other.num_bits
and self.is_standard == other.is_standard
and self.description == other.description
and np.all(self.offsets == other.offsets)
and np.all(self.scales == other.scales)
)
def __ne__(self, other: "DimensionInfo") -> bool:
return not self == other
def _validate(self):
if (self.offsets is not None and self.scales is None) or (
self.offsets is None and self.scales is not None
):
raise ValueError("Cannot provide scales without offsets and vice-versa")
if self.offsets is not None and len(self.offsets) != self.num_elements:
raise ValueError(
f"len(offsets) ({len(self.offsets)}) is not the same as the number of elements ({self.num_elements})"
)
if self.scales is not None and len(self.scales) != self.num_elements:
raise ValueError(
f"len(scales) ({len(self.scales)}) is not the same as the number of elements ({self.num_elements})"
)
| (name: str, kind: laspy.point.dims.DimensionKind, num_bits: int, num_elements: int = 1, is_standard: bool = True, description: str = '', offsets: Optional[numpy.ndarray] = None, scales: Optional[numpy.ndarray] = None) | [
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|
31,507 | laspy.point.dims | __eq__ | null | def __eq__(self, other: "DimensionInfo") -> bool:
# Named Tuple implements that for us, but
# when scales and offset are not None (thus are array)
# The default '==' won't work
# (ValueError, value of an array with more than one element is ambiguous)
return (
self.name == other.name
and self.kind == other.kind
and self.num_bits == other.num_bits
and self.is_standard == other.is_standard
and self.description == other.description
and np.all(self.offsets == other.offsets)
and np.all(self.scales == other.scales)
)
| (self, other: laspy.point.dims.DimensionInfo) -> bool | [
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|
31,509 | laspy.point.dims | __ne__ | null | def __ne__(self, other: "DimensionInfo") -> bool:
return not self == other
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|
31,510 | namedtuple_DimensionInfo | __new__ | Create new instance of DimensionInfo(name, kind, num_bits, num_elements, is_standard, description, offsets, scales) | from builtins import function
| (_cls, name: str, kind: laspy.point.dims.DimensionKind, num_bits: int, num_elements: int = 1, is_standard: bool = True, description: str = '', offsets: Optional[numpy.ndarray] = None, scales: Optional[numpy.ndarray] = None) | [
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|
31,513 | collections | _replace | Return a new DimensionInfo object replacing specified fields with new values | def namedtuple(typename, field_names, *, rename=False, defaults=None, module=None):
"""Returns a new subclass of tuple with named fields.
>>> Point = namedtuple('Point', ['x', 'y'])
>>> Point.__doc__ # docstring for the new class
'Point(x, y)'
>>> p = Point(11, y=22) # instantiate with positional args or keywords
>>> p[0] + p[1] # indexable like a plain tuple
33
>>> x, y = p # unpack like a regular tuple
>>> x, y
(11, 22)
>>> p.x + p.y # fields also accessible by name
33
>>> d = p._asdict() # convert to a dictionary
>>> d['x']
11
>>> Point(**d) # convert from a dictionary
Point(x=11, y=22)
>>> p._replace(x=100) # _replace() is like str.replace() but targets named fields
Point(x=100, y=22)
"""
# Validate the field names. At the user's option, either generate an error
# message or automatically replace the field name with a valid name.
if isinstance(field_names, str):
field_names = field_names.replace(',', ' ').split()
field_names = list(map(str, field_names))
typename = _sys.intern(str(typename))
if rename:
seen = set()
for index, name in enumerate(field_names):
if (not name.isidentifier()
or _iskeyword(name)
or name.startswith('_')
or name in seen):
field_names[index] = f'_{index}'
seen.add(name)
for name in [typename] + field_names:
if type(name) is not str:
raise TypeError('Type names and field names must be strings')
if not name.isidentifier():
raise ValueError('Type names and field names must be valid '
f'identifiers: {name!r}')
if _iskeyword(name):
raise ValueError('Type names and field names cannot be a '
f'keyword: {name!r}')
seen = set()
for name in field_names:
if name.startswith('_') and not rename:
raise ValueError('Field names cannot start with an underscore: '
f'{name!r}')
if name in seen:
raise ValueError(f'Encountered duplicate field name: {name!r}')
seen.add(name)
field_defaults = {}
if defaults is not None:
defaults = tuple(defaults)
if len(defaults) > len(field_names):
raise TypeError('Got more default values than field names')
field_defaults = dict(reversed(list(zip(reversed(field_names),
reversed(defaults)))))
# Variables used in the methods and docstrings
field_names = tuple(map(_sys.intern, field_names))
num_fields = len(field_names)
arg_list = ', '.join(field_names)
if num_fields == 1:
arg_list += ','
repr_fmt = '(' + ', '.join(f'{name}=%r' for name in field_names) + ')'
tuple_new = tuple.__new__
_dict, _tuple, _len, _map, _zip = dict, tuple, len, map, zip
# Create all the named tuple methods to be added to the class namespace
namespace = {
'_tuple_new': tuple_new,
'__builtins__': {},
'__name__': f'namedtuple_{typename}',
}
code = f'lambda _cls, {arg_list}: _tuple_new(_cls, ({arg_list}))'
__new__ = eval(code, namespace)
__new__.__name__ = '__new__'
__new__.__doc__ = f'Create new instance of {typename}({arg_list})'
if defaults is not None:
__new__.__defaults__ = defaults
@classmethod
def _make(cls, iterable):
result = tuple_new(cls, iterable)
if _len(result) != num_fields:
raise TypeError(f'Expected {num_fields} arguments, got {len(result)}')
return result
_make.__func__.__doc__ = (f'Make a new {typename} object from a sequence '
'or iterable')
def _replace(self, /, **kwds):
result = self._make(_map(kwds.pop, field_names, self))
if kwds:
raise ValueError(f'Got unexpected field names: {list(kwds)!r}')
return result
_replace.__doc__ = (f'Return a new {typename} object replacing specified '
'fields with new values')
def __repr__(self):
'Return a nicely formatted representation string'
return self.__class__.__name__ + repr_fmt % self
def _asdict(self):
'Return a new dict which maps field names to their values.'
return _dict(_zip(self._fields, self))
def __getnewargs__(self):
'Return self as a plain tuple. Used by copy and pickle.'
return _tuple(self)
# Modify function metadata to help with introspection and debugging
for method in (
__new__,
_make.__func__,
_replace,
__repr__,
_asdict,
__getnewargs__,
):
method.__qualname__ = f'{typename}.{method.__name__}'
# Build-up the class namespace dictionary
# and use type() to build the result class
class_namespace = {
'__doc__': f'{typename}({arg_list})',
'__slots__': (),
'_fields': field_names,
'_field_defaults': field_defaults,
'__new__': __new__,
'_make': _make,
'_replace': _replace,
'__repr__': __repr__,
'_asdict': _asdict,
'__getnewargs__': __getnewargs__,
'__match_args__': field_names,
}
for index, name in enumerate(field_names):
doc = _sys.intern(f'Alias for field number {index}')
class_namespace[name] = _tuplegetter(index, doc)
result = type(typename, (tuple,), class_namespace)
# For pickling to work, the __module__ variable needs to be set to the frame
# where the named tuple is created. Bypass this step in environments where
# sys._getframe is not defined (Jython for example) or sys._getframe is not
# defined for arguments greater than 0 (IronPython), or where the user has
# specified a particular module.
if module is None:
try:
module = _sys._getframe(1).f_globals.get('__name__', '__main__')
except (AttributeError, ValueError):
pass
if module is not None:
result.__module__ = module
return result
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|
31,514 | laspy.point.dims | _validate | null | def _validate(self):
if (self.offsets is not None and self.scales is None) or (
self.offsets is None and self.scales is not None
):
raise ValueError("Cannot provide scales without offsets and vice-versa")
if self.offsets is not None and len(self.offsets) != self.num_elements:
raise ValueError(
f"len(offsets) ({len(self.offsets)}) is not the same as the number of elements ({self.num_elements})"
)
if self.scales is not None and len(self.scales) != self.num_elements:
raise ValueError(
f"len(scales) ({len(self.scales)}) is not the same as the number of elements ({self.num_elements})"
)
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|
31,515 | laspy.point.dims | type_str | null | def type_str(self) -> Optional[str]:
if self.kind == DimensionKind.BitField:
return None
if self.num_elements == 1:
return f"{self.kind.letter()}{self.num_bytes_singular_element}"
return (
f"{self.num_elements}{self.kind.letter()}{self.num_bytes_singular_element}"
)
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|
31,516 | laspy.point.dims | DimensionKind | An enumeration. | class DimensionKind(Enum):
SignedInteger = 0
UnsignedInteger = 1
FloatingPoint = 2
BitField = 3
@classmethod
def from_letter(cls, letter: str) -> "DimensionKind":
if letter == "u":
return cls.UnsignedInteger
elif letter == "i":
return cls.SignedInteger
elif letter == "f":
return cls.FloatingPoint
else:
raise ValueError(f"Unknown type letter '{letter}'")
def letter(self) -> Optional[str]:
if self == DimensionKind.UnsignedInteger:
return "u"
elif self == DimensionKind.SignedInteger:
return "i"
elif self == DimensionKind.FloatingPoint:
return "f"
else:
return None
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|
31,517 | laspy.point.format | ExtraBytesParams | All parameters needed to create extra bytes | class ExtraBytesParams:
"""All parameters needed to create extra bytes"""
def __init__(
self,
name: str,
type: Union[str, np.dtype, Type[np.uint8]],
description: str = "",
offsets: Optional[Iterable[Number]] = None,
scales: Optional[Iterable[Number]] = None,
) -> None:
self.name = name
""" The name of the extra dimension """
if isinstance(type, str):
# Work around numpy deprecating support
# for '1type' strings
n = "".join(takewhile(lambda c: c.isdigit(), type))
if n == "1":
type = type[1:]
self.type = np.dtype(type)
""" The type of the extra dimension """
self.description = description
""" A description of the extra dimension """
self.offsets = np.array(offsets) if offsets is not None else offsets
""" The offsets to use if its a 'scaled dimension', can be none """
self.scales = np.array(scales) if scales is not None else scales
""" The scales to use if its a 'scaled dimension', can be none """
| (name: str, type: Union[str, numpy.dtype, Type[numpy.uint8]], description: str = '', offsets: Optional[Iterable[Union[numpy.number, float, int]]] = None, scales: Optional[Iterable[Union[numpy.number, float, int]]] = None) -> None | [
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|
31,518 | laspy.point.format | __init__ | null | def __init__(
self,
name: str,
type: Union[str, np.dtype, Type[np.uint8]],
description: str = "",
offsets: Optional[Iterable[Number]] = None,
scales: Optional[Iterable[Number]] = None,
) -> None:
self.name = name
""" The name of the extra dimension """
if isinstance(type, str):
# Work around numpy deprecating support
# for '1type' strings
n = "".join(takewhile(lambda c: c.isdigit(), type))
if n == "1":
type = type[1:]
self.type = np.dtype(type)
""" The type of the extra dimension """
self.description = description
""" A description of the extra dimension """
self.offsets = np.array(offsets) if offsets is not None else offsets
""" The offsets to use if its a 'scaled dimension', can be none """
self.scales = np.array(scales) if scales is not None else scales
""" The scales to use if its a 'scaled dimension', can be none """
| (self, name: str, type: Union[str, numpy.dtype, Type[numpy.uint8]], description: str = '', offsets: Optional[Iterable[Union[numpy.number, float, int]]] = None, scales: Optional[Iterable[Union[numpy.number, float, int]]] = None) -> NoneType | [
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|
31,519 | laspy.lasdata | LasData | Class synchronizing all the moving parts of LAS files.
It connects the point record, header, vlrs together.
To access points dimensions using this class you have two possibilities
.. code:: python
las = laspy.read('some_file.las')
las.classification
# or
las['classification']
| class LasData:
"""Class synchronizing all the moving parts of LAS files.
It connects the point record, header, vlrs together.
To access points dimensions using this class you have two possibilities
.. code:: python
las = laspy.read('some_file.las')
las.classification
# or
las['classification']
"""
def __init__(
self,
header: LasHeader,
points: Optional[
Union[record.PackedPointRecord, record.ScaleAwarePointRecord]
] = None,
) -> None:
if points is None:
points = record.ScaleAwarePointRecord.zeros(
header.point_count, header=header
)
if points.point_format != header.point_format:
raise errors.LaspyException("Incompatible Point Formats")
if isinstance(points, record.PackedPointRecord):
points = record.ScaleAwarePointRecord(
points.array,
header.point_format,
scales=header.scales,
offsets=header.offsets,
)
else:
assert np.all(header.scales, points.scales)
assert np.all(header.offsets, points.offsets)
self.__dict__["_points"] = points
self.points: record.ScaleAwarePointRecord
self.header: LasHeader = header
@property
def point_format(self) -> PointFormat:
"""Shortcut to get the point format"""
return self.points.point_format
@property
def xyz(self) -> np.ndarray:
"""Returns a **new** 2D numpy array with the x,y,z coordinates
>>> import laspy
>>> las = laspy.read("tests/data/simple.las")
>>> xyz = las.xyz
>>> xyz.ndim
2
>>> xyz.shape
(1065, 3)
>>> np.all(xyz[..., 0] == las.x)
True
"""
return np.vstack((self.x, self.y, self.z)).transpose()
@xyz.setter
def xyz(self, value) -> None:
self.points[("x", "y", "z")] = value
@property
def points(self) -> record.PackedPointRecord:
"""Returns the point record"""
return self._points
@points.setter
def points(self, new_points: record.PackedPointRecord) -> None:
if new_points.point_format != self.point_format:
raise errors.IncompatibleDataFormat(
"Cannot set points with a different point format, convert first"
)
self._points = new_points
self.update_header()
# make sure both point format point to the same object
self._points.point_format = self.header.point_format
@property
def vlrs(self) -> VLRList:
return self.header.vlrs
@vlrs.setter
def vlrs(self, vlrs) -> None:
self.header.vlrs = vlrs
@property
def evlrs(self) -> Optional[VLRList]:
return self.header.evlrs
@evlrs.setter
def evlrs(self, evlrs: VLRList) -> None:
self.header.evlrs = evlrs
def add_extra_dim(self, params: ExtraBytesParams) -> None:
"""Adds a new extra dimension to the point record
.. note::
If you plan on adding multiple extra dimensions,
prefer :meth:`.add_extra_dims` as it will
save re-allocations and data copy
Parameters
----------
params : ExtraBytesParams
parameters of the new extra dimension to add
"""
self.add_extra_dims([params])
def add_extra_dims(self, params: List[ExtraBytesParams]) -> None:
"""Add multiple extra dimensions at once
Parameters
----------
params: list of parameters of the new extra dimensions to add
"""
self.header.add_extra_dims(params)
new_point_record = record.ScaleAwarePointRecord.zeros(
len(self.points), header=self.header
)
new_point_record.copy_fields_from(self.points)
self.points = new_point_record
def remove_extra_dims(self, names: Iterable[str]) -> None:
"""Remove multiple extra dimensions from this object
Parameters
----------
names: iterable,
names of the extra dimensions to be removed
Raises
------
LaspyException: if you try to remove an extra dimension that do not exist.
"""
extra_dimension_names = list(self.point_format.extra_dimension_names)
not_extra_dimension = [
name for name in names if name not in extra_dimension_names
]
if not_extra_dimension:
raise errors.LaspyException(
f"'{not_extra_dimension}' are not extra dimensions and cannot be removed"
)
self.header.remove_extra_dims(names)
new_point_record = record.ScaleAwarePointRecord.zeros(
len(self.points), header=self.header
)
new_point_record.copy_fields_from(self.points)
self.points = new_point_record
def remove_extra_dim(self, name: str) -> None:
"""Remove an extra dimensions from this object
.. note::
If you plan on removing multiple extra dimensions,
prefer :meth:`.remove_extra_dims` as it will
save re-allocations and data copy
Parameters
----------
name: str,
name of the extra dimension to be removed
Raises
------
LaspyException: if you try to remove an extra dimension that do not exist.
"""
self.remove_extra_dims([name])
def update_header(self) -> None:
"""Update the information stored in the header
to be in sync with the actual data.
This method is called automatically when you save a file using
:meth:`laspy.lasdatas.base.LasBase.write`
"""
self.header.update(self.points)
self.header.point_format_id = self.points.point_format.id
self.header.point_data_record_length = self.points.point_size
if self.header.version.minor >= 4:
if self.evlrs is not None:
self.header.number_of_evlrs = len(self.evlrs)
self.header.start_of_waveform_data_packet_record = 0
# TODO
# if len(self.vlrs.get("WktCoordinateSystemVlr")) == 1:
# self.header.global_encoding.wkt = 1
else:
self.header.number_of_evlrs = 0
@overload
def write(
self,
destination: str,
laz_backend: Optional[Union[LazBackend, Sequence[LazBackend]]] = ...,
) -> None:
...
@overload
def write(
self,
destination: BinaryIO,
do_compress: Optional[bool] = ...,
laz_backend: Optional[Union[LazBackend, Sequence[LazBackend]]] = ...,
) -> None:
...
def write(self, destination, do_compress=None, laz_backend=None):
"""Writes to a stream or file
.. note::
When destination is a string, it will be interpreted as the path were the file should be written to,
and whether the file will be compressed depends on the extension used (case insensitive):
- .laz -> compressed
- .las -> uncompressed
And the do_compress option will be ignored
Parameters
----------
destination: str or file object
filename or stream to write to
do_compress: bool, optional
Flags to indicate if you want to compress the data
laz_backend: optional, the laz backend to use
By default, laspy detect available backends
"""
if isinstance(destination, (str, pathlib.Path)):
do_compress = pathlib.Path(destination).suffix.lower() == ".laz"
with open(destination, mode="wb+") as out:
self._write_to(out, do_compress=do_compress, laz_backend=laz_backend)
else:
self._write_to(
destination, do_compress=do_compress, laz_backend=laz_backend
)
def _write_to(
self,
out_stream: BinaryIO,
do_compress: Optional[bool] = None,
laz_backend: Optional[Union[LazBackend, Sequence[La | (header: laspy.header.LasHeader, points: Union[laspy.point.record.PackedPointRecord, laspy.point.record.ScaleAwarePointRecord, NoneType] = None) -> None | [
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|
31,520 | laspy.lasdata | __getattr__ | Automatically called by Python when the attribute
named 'item' is no found. We use this function to forward the call the
point record. This is the mechanism used to allow the users to access
the points dimensions directly through a LasData.
Parameters
----------
item: str
name of the attribute, should be a dimension name
Returns
-------
The requested dimension if it exists
| def __getattr__(self, item):
"""Automatically called by Python when the attribute
named 'item' is no found. We use this function to forward the call the
point record. This is the mechanism used to allow the users to access
the points dimensions directly through a LasData.
Parameters
----------
item: str
name of the attribute, should be a dimension name
Returns
-------
The requested dimension if it exists
"""
try:
return self.points[item]
except ValueError:
raise AttributeError(
f"{self.__class__.__name__} object has no attribute '{item}'"
) from None
| (self, item) | [
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|
31,521 | laspy.lasdata | __getitem__ | null | def __getitem__(self, item):
try:
item_is_list_of_str = all(isinstance(el, str) for el in iter(item))
except TypeError:
item_is_list_of_str = False
if isinstance(item, str) or item_is_list_of_str:
return self.points[item]
else:
las = LasData(deepcopy(self.header), points=self.points[item])
las.update_header()
return las
| (self, item) | [
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|
31,522 | laspy.lasdata | __init__ | null | def __init__(
self,
header: LasHeader,
points: Optional[
Union[record.PackedPointRecord, record.ScaleAwarePointRecord]
] = None,
) -> None:
if points is None:
points = record.ScaleAwarePointRecord.zeros(
header.point_count, header=header
)
if points.point_format != header.point_format:
raise errors.LaspyException("Incompatible Point Formats")
if isinstance(points, record.PackedPointRecord):
points = record.ScaleAwarePointRecord(
points.array,
header.point_format,
scales=header.scales,
offsets=header.offsets,
)
else:
assert np.all(header.scales, points.scales)
assert np.all(header.offsets, points.offsets)
self.__dict__["_points"] = points
self.points: record.ScaleAwarePointRecord
self.header: LasHeader = header
| (self, header: laspy.header.LasHeader, points: Union[laspy.point.record.PackedPointRecord, laspy.point.record.ScaleAwarePointRecord, NoneType] = None) -> NoneType | [
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|
31,523 | laspy.lasdata | __len__ | null | def __len__(self):
return len(self.points)
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|
31,524 | laspy.lasdata | __repr__ | null | def __repr__(self) -> str:
return "<LasData({}.{}, point fmt: {}, {} points, {} vlrs)>".format(
self.header.version.major,
self.header.version.minor,
self.points.point_format,
len(self.points),
len(self.vlrs),
)
| (self) -> str | [
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|
31,525 | laspy.lasdata | __setattr__ | This is called on every access to an attribute of the instance.
Again we use this to forward the call the the points record
But this time checking if the key is actually a dimension name
so that an error is raised if the user tries to set a valid
LAS dimension even if it is not present in the field.
eg: user tries to set the red field of a file with point format 0:
an error is raised
| def __setattr__(self, key, value):
"""This is called on every access to an attribute of the instance.
Again we use this to forward the call the the points record
But this time checking if the key is actually a dimension name
so that an error is raised if the user tries to set a valid
LAS dimension even if it is not present in the field.
eg: user tries to set the red field of a file with point format 0:
an error is raised
"""
if key in ("x", "y", "z"):
# It is possible that user created a `LasData` object
# via `laspy.create`, and changed the headers offsets and scales
# values afterwards. So we need to sync the points's record.
self.points.offsets = self.header.offsets
self.points.scales = self.header.scales
self.points[key] = value
return
name_validity = self.points.validate_dimension_name(key)
if name_validity == DimensionNameValidity.Valid:
self[key] = value
elif name_validity == DimensionNameValidity.Unsupported:
raise ValueError(
f"Point format {self.point_format} does not support {key} dimension"
)
else:
super().__setattr__(key, value)
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|
31,526 | laspy.lasdata | __setitem__ | null | def __setitem__(self, key, value):
self.points[key] = value
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|
31,527 | laspy.lasdata | _write_to | null | def _write_to(
self,
out_stream: BinaryIO,
do_compress: Optional[bool] = None,
laz_backend: Optional[Union[LazBackend, Sequence[LazBackend]]] = None,
) -> None:
with LasWriter(
out_stream,
self.header,
do_compress=do_compress,
closefd=False,
laz_backend=laz_backend,
) as writer:
writer.write_points(self.points)
if self.header.version.minor >= 4 and self.evlrs is not None:
writer.write_evlrs(self.evlrs)
| (self, out_stream: <class 'BinaryIO'>, do_compress: Optional[bool] = None, laz_backend: Union[laspy._compression.backend.LazBackend, Sequence[laspy._compression.backend.LazBackend], NoneType] = None) -> NoneType | [
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|
31,528 | laspy.lasdata | add_extra_dim | Adds a new extra dimension to the point record
.. note::
If you plan on adding multiple extra dimensions,
prefer :meth:`.add_extra_dims` as it will
save re-allocations and data copy
Parameters
----------
params : ExtraBytesParams
parameters of the new extra dimension to add
| def add_extra_dim(self, params: ExtraBytesParams) -> None:
"""Adds a new extra dimension to the point record
.. note::
If you plan on adding multiple extra dimensions,
prefer :meth:`.add_extra_dims` as it will
save re-allocations and data copy
Parameters
----------
params : ExtraBytesParams
parameters of the new extra dimension to add
"""
self.add_extra_dims([params])
| (self, params: laspy.point.format.ExtraBytesParams) -> NoneType | [
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|
31,529 | laspy.lasdata | add_extra_dims | Add multiple extra dimensions at once
Parameters
----------
params: list of parameters of the new extra dimensions to add
| def add_extra_dims(self, params: List[ExtraBytesParams]) -> None:
"""Add multiple extra dimensions at once
Parameters
----------
params: list of parameters of the new extra dimensions to add
"""
self.header.add_extra_dims(params)
new_point_record = record.ScaleAwarePointRecord.zeros(
len(self.points), header=self.header
)
new_point_record.copy_fields_from(self.points)
self.points = new_point_record
| (self, params: List[laspy.point.format.ExtraBytesParams]) -> NoneType | [
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|
31,530 | laspy.lasdata | change_scaling | This changes the scales and/or offset used for the x,y,z
dimensions.
It recomputes the internal, non-scaled X,Y,Z dimensions
to match the new scales and offsets.
It also updates the header with the new values of scales and offsets.
Parameters
----------
scales: optional
New scales to be used. If not provided, the scales won't change.
offsets: optional
New offsets to be used. If not provided, the offsets won't change.
Example
-------
>>> import laspy
>>> header = laspy.LasHeader()
>>> header.scales = np.array([0.1, 0.1, 0.1])
>>> header.offsets = np.array([0, 0 ,0])
>>> las = laspy.LasData(header=header)
>>> las.x = [10.0]
>>> las.y = [20.0]
>>> las.z = [30.0]
>>> # X = (x - x_offset) / x_scale
>>> assert np.all(las.xyz == [[10.0, 20., 30]])
>>> assert np.all(las.X == [100])
>>> assert np.all(las.Y == [200])
>>> assert np.all(las.Z == [300])
We change the scales (only changing x_scale here)
but not the offsets.
The xyz coordinates (double) are the same (minus possible rounding with actual coordinates)
However the integer coordinates changed
>>> las.change_scaling(scales=[0.01, 0.1, 0.1])
>>> assert np.all(las.xyz == [[10.0, 20., 30]])
>>> assert np.all(las.X == [1000])
>>> assert np.all(las.Y == [200])
>>> assert np.all(las.Z == [300])
Same idea if we change the offsets, the xyz do not change
but XYZ does
>>> las.change_scaling(offsets=[0, 10, 15])
>>> assert np.all(las.xyz == [[10.0, 20., 30]])
>>> assert np.all(las.X == [1000])
>>> assert np.all(las.Y == [100])
>>> assert np.all(las.Z == [150])
| def change_scaling(self, scales=None, offsets=None) -> None:
"""This changes the scales and/or offset used for the x,y,z
dimensions.
It recomputes the internal, non-scaled X,Y,Z dimensions
to match the new scales and offsets.
It also updates the header with the new values of scales and offsets.
Parameters
----------
scales: optional
New scales to be used. If not provided, the scales won't change.
offsets: optional
New offsets to be used. If not provided, the offsets won't change.
Example
-------
>>> import laspy
>>> header = laspy.LasHeader()
>>> header.scales = np.array([0.1, 0.1, 0.1])
>>> header.offsets = np.array([0, 0 ,0])
>>> las = laspy.LasData(header=header)
>>> las.x = [10.0]
>>> las.y = [20.0]
>>> las.z = [30.0]
>>> # X = (x - x_offset) / x_scale
>>> assert np.all(las.xyz == [[10.0, 20., 30]])
>>> assert np.all(las.X == [100])
>>> assert np.all(las.Y == [200])
>>> assert np.all(las.Z == [300])
We change the scales (only changing x_scale here)
but not the offsets.
The xyz coordinates (double) are the same (minus possible rounding with actual coordinates)
However the integer coordinates changed
>>> las.change_scaling(scales=[0.01, 0.1, 0.1])
>>> assert np.all(las.xyz == [[10.0, 20., 30]])
>>> assert np.all(las.X == [1000])
>>> assert np.all(las.Y == [200])
>>> assert np.all(las.Z == [300])
Same idea if we change the offsets, the xyz do not change
but XYZ does
>>> las.change_scaling(offsets=[0, 10, 15])
>>> assert np.all(las.xyz == [[10.0, 20., 30]])
>>> assert np.all(las.X == [1000])
>>> assert np.all(las.Y == [100])
>>> assert np.all(las.Z == [150])
"""
self.points.change_scaling(scales, offsets)
if scales is not None:
self.header.scales = scales
if offsets is not None:
self.header.offsets = offsets
| (self, scales=None, offsets=None) -> NoneType | [
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|
31,531 | laspy.lasdata | remove_extra_dim | Remove an extra dimensions from this object
.. note::
If you plan on removing multiple extra dimensions,
prefer :meth:`.remove_extra_dims` as it will
save re-allocations and data copy
Parameters
----------
name: str,
name of the extra dimension to be removed
Raises
------
LaspyException: if you try to remove an extra dimension that do not exist.
| def remove_extra_dim(self, name: str) -> None:
"""Remove an extra dimensions from this object
.. note::
If you plan on removing multiple extra dimensions,
prefer :meth:`.remove_extra_dims` as it will
save re-allocations and data copy
Parameters
----------
name: str,
name of the extra dimension to be removed
Raises
------
LaspyException: if you try to remove an extra dimension that do not exist.
"""
self.remove_extra_dims([name])
| (self, name: str) -> NoneType | [
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|
31,532 | laspy.lasdata | remove_extra_dims | Remove multiple extra dimensions from this object
Parameters
----------
names: iterable,
names of the extra dimensions to be removed
Raises
------
LaspyException: if you try to remove an extra dimension that do not exist.
| def remove_extra_dims(self, names: Iterable[str]) -> None:
"""Remove multiple extra dimensions from this object
Parameters
----------
names: iterable,
names of the extra dimensions to be removed
Raises
------
LaspyException: if you try to remove an extra dimension that do not exist.
"""
extra_dimension_names = list(self.point_format.extra_dimension_names)
not_extra_dimension = [
name for name in names if name not in extra_dimension_names
]
if not_extra_dimension:
raise errors.LaspyException(
f"'{not_extra_dimension}' are not extra dimensions and cannot be removed"
)
self.header.remove_extra_dims(names)
new_point_record = record.ScaleAwarePointRecord.zeros(
len(self.points), header=self.header
)
new_point_record.copy_fields_from(self.points)
self.points = new_point_record
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|
31,533 | laspy.lasdata | update_header | Update the information stored in the header
to be in sync with the actual data.
This method is called automatically when you save a file using
:meth:`laspy.lasdatas.base.LasBase.write`
| def update_header(self) -> None:
"""Update the information stored in the header
to be in sync with the actual data.
This method is called automatically when you save a file using
:meth:`laspy.lasdatas.base.LasBase.write`
"""
self.header.update(self.points)
self.header.point_format_id = self.points.point_format.id
self.header.point_data_record_length = self.points.point_size
if self.header.version.minor >= 4:
if self.evlrs is not None:
self.header.number_of_evlrs = len(self.evlrs)
self.header.start_of_waveform_data_packet_record = 0
# TODO
# if len(self.vlrs.get("WktCoordinateSystemVlr")) == 1:
# self.header.global_encoding.wkt = 1
else:
self.header.number_of_evlrs = 0
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|
31,534 | laspy.lasdata | write | Writes to a stream or file
.. note::
When destination is a string, it will be interpreted as the path were the file should be written to,
and whether the file will be compressed depends on the extension used (case insensitive):
- .laz -> compressed
- .las -> uncompressed
And the do_compress option will be ignored
Parameters
----------
destination: str or file object
filename or stream to write to
do_compress: bool, optional
Flags to indicate if you want to compress the data
laz_backend: optional, the laz backend to use
By default, laspy detect available backends
| def write(self, destination, do_compress=None, laz_backend=None):
"""Writes to a stream or file
.. note::
When destination is a string, it will be interpreted as the path were the file should be written to,
and whether the file will be compressed depends on the extension used (case insensitive):
- .laz -> compressed
- .las -> uncompressed
And the do_compress option will be ignored
Parameters
----------
destination: str or file object
filename or stream to write to
do_compress: bool, optional
Flags to indicate if you want to compress the data
laz_backend: optional, the laz backend to use
By default, laspy detect available backends
"""
if isinstance(destination, (str, pathlib.Path)):
do_compress = pathlib.Path(destination).suffix.lower() == ".laz"
with open(destination, mode="wb+") as out:
self._write_to(out, do_compress=do_compress, laz_backend=laz_backend)
else:
self._write_to(
destination, do_compress=do_compress, laz_backend=laz_backend
)
| (self, destination, do_compress=None, laz_backend=None) | [
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|
31,535 | laspy.header | LasHeader | Contains the information from the header of as LAS file
with 'implementation' field left out and 'users' field
stored in more ergonomic classes.
This header also contains the VLRs
Examples
--------
Creating a default header:
>>> header = LasHeader()
>>> header
<LasHeader(1.2, <PointFormat(3, 0 bytes of extra dims)>)>
Creating a header with the wanted version and point format:
>>> header = LasHeader(version=Version(1, 4), point_format=PointFormat(6))
>>> header
<LasHeader(1.4, <PointFormat(6, 0 bytes of extra dims)>)>
>>> header = LasHeader(version="1.4", point_format=6)
>>> header
<LasHeader(1.4, <PointFormat(6, 0 bytes of extra dims)>)>
| class LasHeader:
"""Contains the information from the header of as LAS file
with 'implementation' field left out and 'users' field
stored in more ergonomic classes.
This header also contains the VLRs
Examples
--------
Creating a default header:
>>> header = LasHeader()
>>> header
<LasHeader(1.2, <PointFormat(3, 0 bytes of extra dims)>)>
Creating a header with the wanted version and point format:
>>> header = LasHeader(version=Version(1, 4), point_format=PointFormat(6))
>>> header
<LasHeader(1.4, <PointFormat(6, 0 bytes of extra dims)>)>
>>> header = LasHeader(version="1.4", point_format=6)
>>> header
<LasHeader(1.4, <PointFormat(6, 0 bytes of extra dims)>)>
"""
#: The default version used when None is given to init
DEFAULT_VERSION = Version(1, 2)
#: The default point format Used when None is given to init
DEFAULT_POINT_FORMAT = PointFormat(3)
_OLD_LASPY_NAMES = {
"max": "maxs",
"min": "mins",
"scale": "scales",
"offset": "offsets",
"filesource_id": "file_source_id",
"system_id": "system_identifier",
"date": "creation_date",
"point_return_count": "number_of_points_by_return",
"software_id": "generating_software",
"point_records_count": "point_count",
}
def __init__(
self,
*,
version: Optional[Union[Version, str]] = None,
point_format: Optional[Union[PointFormat, int]] = None,
) -> None:
if isinstance(point_format, int):
point_format = PointFormat(point_format)
if isinstance(version, str):
version = Version.from_str(version)
if version is None and point_format is None:
version = LasHeader.DEFAULT_VERSION
point_format = LasHeader.DEFAULT_POINT_FORMAT
elif version is not None and point_format is None:
point_format = PointFormat(dims.min_point_format_for_version(str(version)))
elif version is None and point_format is not None:
version = Version.from_str(
dims.preferred_file_version_for_point_format(point_format.id)
)
dims.raise_if_version_not_compatible_with_fmt(point_format.id, str(version))
#: File source id
self.file_source_id: int = 0
self.global_encoding: GlobalEncoding = GlobalEncoding()
#: Project ID
#: Initialized to null UUID
self.uuid: UUID = UUID(bytes_le=b"\0" * 16)
self._version: Version = version
#: System identifier
#: Initialized to 'OTHER'
self.system_identifier: Union[str, bytes] = "OTHER"
#: The software which generated the file
#: Initialized to 'laspy'
self.generating_software: Union[str, bytes] = DEFAULT_GENERATING_SOFTWARE
self._point_format: PointFormat = point_format
#: Day the file was created, initialized to date.today
self.creation_date: Optional[date] = date.today()
#: The number of points in the file
self.point_count: int = 0
#: The numbers used to scale the x,y,z coordinates
self.scales: np.ndarray = np.array([0.01, 0.01, 0.01], dtype=np.float64)
#: The numbers used to offset the x,y,z coordinates
self.offsets: np.ndarray = np.zeros(3, dtype=np.float64)
# The max values for x,y,z
self.maxs: np.ndarray = np.zeros(3, dtype=np.float64)
# The min values for x,y,z
self.mins: np.ndarray = np.zeros(3, dtype=np.float64)
#: Number of points by return
#: for las <= 1.2 only the first 5 elements matters
self.number_of_points_by_return: np.ndarray = np.zeros(15, dtype=np.uint32)
#: The VLRS
self._vlrs: VLRList = VLRList()
#: Extra bytes between end of header and first vlrs
self.extra_header_bytes: bytes = b""
#: Extra bytes between end of vlr end first point
self.extra_vlr_bytes: bytes = b""
#: Las >= 1.3
self.start_of_waveform_data_packet_record: int = 0
#: Las >= 1.4
#: Offset to the first evlr in the file
self.start_of_first_evlr: int = 0
#: The number of evlrs in the file
self.number_of_evlrs: int = 0
#: EVLRs, even though they are not stored in the 'header'
#: part of the file we keep them in this class
#: as they contain same information as vlr.
#: None when the file does not support EVLR
self.evlrs: Optional[VLRList] = None
# Info we keep because it's useful for us but not the user
self.offset_to_point_data: int = 0
self.are_points_compressed: bool = False
self._sync_extra_bytes_vlr()
@property
def point_format(self) -> PointFormat:
"""The point format"""
return self._point_format
@point_format.setter
def point_format(self, new_point_format: PointFormat) -> None:
dims.raise_if_version_not_compatible_with_fmt(
new_point_format.id, str(self.version)
)
self._point_format = new_point_format
self._sync_extra_bytes_vlr()
@property
def version(self) -> Version:
"""The version"""
return self._version
@version.setter
def version(self, version: Version) -> None:
dims.raise_if_version_not_compatible_with_fmt(
self.point_format.id, str(version)
)
self._version = version
# scale properties
@property
def x_scale(self) -> float:
return self.scales[0]
@x_scale.setter
def x_scale(self, value: float) -> None:
self.scales[0] = value
@property
def y_scale(self) -> float:
return self.scales[1]
@y_scale.setter
def y_scale(self, value: float) -> None:
self.scales[1] = value
@property
def z_scale(self) -> float:
return self.scales[2]
@z_scale.setter
def z_scale(self, value: float) -> None:
self.scales[2] = value
# offset properties
@property
def x_offset(self) -> float:
return self.offsets[0]
@x_offset.setter
def x_offset(self, value: float) -> None:
self.offsets[0] = value
@property
def y_offset(self) -> float:
return self.offsets[1]
@y_offset.setter
def y_offset(self, value: float) -> None:
self.offsets[1] = value
@property
def z_offset(self) -> float:
return self.offsets[2]
@z_offset.setter
def z_offset(self, value: float) -> None:
self.offsets[2] = value
# max properties
@property
def x_max(self) -> float:
return self.maxs[0]
@x_max.setter
def x_max(self, value: float) -> None:
self.maxs[0] = value
@property
def y_max(self) -> float:
return self.maxs[1]
@y_max.setter
def y_max(self, value: float) -> None:
self.maxs[1] = value
@property
def z_max(self) -> float:
return self.maxs[2]
@z_max.setter
def z_max(self, value: float) -> None:
self.maxs[2] = value
# min properties
@property
def x_min(self) -> float:
return self.mins[0]
@x_min.setter
def x_min(self, value: float) -> None:
self.mins[0] = value
@property
def y_min(self) -> float:
return self.mins[1]
@y_min.setter
def y_min(self, value: float) -> None:
self.mins[1] = value
@property
def z_min(self) -> float:
return self.mins[2]
@z_min.setter
def z_min(self, value: float) -> None:
self.mins[2] = value
@property
def vlrs(self) -> VLRList:
return self._vlrs
@vlrs.setter
def vlrs(self, vlrs: typing.Iterable[VLR]) -> None:
self._vlrs = VLRList(vlrs)
try:
self.vlrs.extract("LaszipVlr")
except ValueError:
pass
self._sync_extra_bytes_vlr()
def add_extra_dims(self, params: List[ExtraBytesParams]) -> None:
for param in params:
self.point_format.add_extra_dimension(param)
self._sync_extra_bytes_vlr()
def add_extra_dim(self, params: Extra | (*, version: Union[laspy.header.Version, str, NoneType] = None, point_format: Union[laspy.point.format.PointFormat, int, NoneType] = None) -> None | [
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|
31,536 | laspy.header | __getattr__ | null | def __getattr__(self, item):
try:
return getattr(self, self._OLD_LASPY_NAMES[item])
except KeyError:
raise AttributeError(f"No attribute {item} in LasHeader") from None
| (self, item) | [
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|
31,537 | laspy.header | __init__ | null | def __init__(
self,
*,
version: Optional[Union[Version, str]] = None,
point_format: Optional[Union[PointFormat, int]] = None,
) -> None:
if isinstance(point_format, int):
point_format = PointFormat(point_format)
if isinstance(version, str):
version = Version.from_str(version)
if version is None and point_format is None:
version = LasHeader.DEFAULT_VERSION
point_format = LasHeader.DEFAULT_POINT_FORMAT
elif version is not None and point_format is None:
point_format = PointFormat(dims.min_point_format_for_version(str(version)))
elif version is None and point_format is not None:
version = Version.from_str(
dims.preferred_file_version_for_point_format(point_format.id)
)
dims.raise_if_version_not_compatible_with_fmt(point_format.id, str(version))
#: File source id
self.file_source_id: int = 0
self.global_encoding: GlobalEncoding = GlobalEncoding()
#: Project ID
#: Initialized to null UUID
self.uuid: UUID = UUID(bytes_le=b"\0" * 16)
self._version: Version = version
#: System identifier
#: Initialized to 'OTHER'
self.system_identifier: Union[str, bytes] = "OTHER"
#: The software which generated the file
#: Initialized to 'laspy'
self.generating_software: Union[str, bytes] = DEFAULT_GENERATING_SOFTWARE
self._point_format: PointFormat = point_format
#: Day the file was created, initialized to date.today
self.creation_date: Optional[date] = date.today()
#: The number of points in the file
self.point_count: int = 0
#: The numbers used to scale the x,y,z coordinates
self.scales: np.ndarray = np.array([0.01, 0.01, 0.01], dtype=np.float64)
#: The numbers used to offset the x,y,z coordinates
self.offsets: np.ndarray = np.zeros(3, dtype=np.float64)
# The max values for x,y,z
self.maxs: np.ndarray = np.zeros(3, dtype=np.float64)
# The min values for x,y,z
self.mins: np.ndarray = np.zeros(3, dtype=np.float64)
#: Number of points by return
#: for las <= 1.2 only the first 5 elements matters
self.number_of_points_by_return: np.ndarray = np.zeros(15, dtype=np.uint32)
#: The VLRS
self._vlrs: VLRList = VLRList()
#: Extra bytes between end of header and first vlrs
self.extra_header_bytes: bytes = b""
#: Extra bytes between end of vlr end first point
self.extra_vlr_bytes: bytes = b""
#: Las >= 1.3
self.start_of_waveform_data_packet_record: int = 0
#: Las >= 1.4
#: Offset to the first evlr in the file
self.start_of_first_evlr: int = 0
#: The number of evlrs in the file
self.number_of_evlrs: int = 0
#: EVLRs, even though they are not stored in the 'header'
#: part of the file we keep them in this class
#: as they contain same information as vlr.
#: None when the file does not support EVLR
self.evlrs: Optional[VLRList] = None
# Info we keep because it's useful for us but not the user
self.offset_to_point_data: int = 0
self.are_points_compressed: bool = False
self._sync_extra_bytes_vlr()
| (self, *, version: Union[laspy.header.Version, str, NoneType] = None, point_format: Union[laspy.point.format.PointFormat, int, NoneType] = None) -> NoneType | [
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|
31,538 | laspy.header | __repr__ | null | def __repr__(self) -> str:
return f"<LasHeader({self.version.major}.{self.version.minor}, {self.point_format})>"
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|
31,539 | laspy.header | __setattr__ | null | def __setattr__(self, key, value):
try:
return setattr(self, self._OLD_LASPY_NAMES[key], value)
except KeyError:
super().__setattr__(key, value)
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|
31,540 | laspy.header | _prefetch_header_data |
reads (and returns) from the source all the bytes that
are between the beginning of the file and the start of point data
(which corresponds to Header + VLRS).
It is done in two calls to the source's `read` method
This is done because `LasHeader.read_from`
does a bunch of read to the source, so we prefer to
prefetch data in memory in case the original source
is not buffered (like a http source could be)
| @staticmethod
def _prefetch_header_data(source) -> bytes:
"""
reads (and returns) from the source all the bytes that
are between the beginning of the file and the start of point data
(which corresponds to Header + VLRS).
It is done in two calls to the source's `read` method
This is done because `LasHeader.read_from`
does a bunch of read to the source, so we prefer to
prefetch data in memory in case the original source
is not buffered (like a http source could be)
"""
header_bytes = source.read(LAS_HEADERS_SIZE["1.1"])
file_sig = header_bytes[: len(LAS_FILE_SIGNATURE)]
if not file_sig:
raise LaspyException(f"Source is empty")
if file_sig != LAS_FILE_SIGNATURE:
raise LaspyException(f'Invalid file signature "{file_sig}"')
if len(header_bytes) < LAS_HEADERS_SIZE["1.1"]:
raise LaspyException("File is to small to be a valid LAS")
offset_to_data = int.from_bytes(
header_bytes[96 : 96 + 4], byteorder="little", signed=False
)
rest = source.read(offset_to_data - len(header_bytes))
return header_bytes + rest
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|
31,541 | laspy.header | _sync_extra_bytes_vlr | null | def _sync_extra_bytes_vlr(self) -> None:
try:
self._vlrs.extract("ExtraBytesVlr")
except IndexError:
pass
extra_dimensions = list(self.point_format.extra_dimensions)
if not extra_dimensions:
return
eb_vlr = ExtraBytesVlr()
for extra_dimension in extra_dimensions:
dtype = extra_dimension.dtype
assert dtype is not None
eb_struct = ExtraBytesStruct(
name=extra_dimension.name.encode(),
description=extra_dimension.description.encode(),
)
if extra_dimension.num_elements > 3 and dtype.base == np.uint8:
type_id = 0
eb_struct.options = extra_dimension.num_elements
else:
type_id = extradims.get_id_for_extra_dim_type(dtype)
eb_struct.data_type = type_id
eb_struct.scale = extra_dimension.scales
eb_struct.offset = extra_dimension.offsets
eb_vlr.extra_bytes_structs.append(eb_struct)
self._vlrs.append(eb_vlr)
| (self) -> NoneType | [
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|
31,542 | laspy.header | add_crs | Add a Coordinate Reference System VLR from a pyproj CRS object.
The type of VLR created depends on the las version and point format
version. Las version >= 1.4 use WKT string, las version < 1.4 and point
format < 6 use GeoTiff tags.
.. warning::
This requires `pyproj`.
.. warning::
Not all CRS are supported when adding GeoTiff tags.
For example, custom CRS.
Typically, if the CRS has an EPSG code it will be supported.
| def add_crs(self, crs: "pyproj.CRS", keep_compatibility: bool = True) -> None:
"""Add a Coordinate Reference System VLR from a pyproj CRS object.
The type of VLR created depends on the las version and point format
version. Las version >= 1.4 use WKT string, las version < 1.4 and point
format < 6 use GeoTiff tags.
.. warning::
This requires `pyproj`.
.. warning::
Not all CRS are supported when adding GeoTiff tags.
For example, custom CRS.
Typically, if the CRS has an EPSG code it will be supported.
"""
import pyproj
# check and remove any existing crs vlrs
for crs_vlr_name in (
"WktCoordinateSystemVlr",
"GeoKeyDirectoryVlr",
"GeoAsciiParamsVlr",
"GeoDoubleParamsVlr",
):
try:
self._vlrs.extract(crs_vlr_name)
except IndexError:
pass
new_ver = self._version >= Version(1, 4)
new_pt = self.point_format.id >= 6
if new_pt or (new_ver and not keep_compatibility):
self._vlrs.append(WktCoordinateSystemVlr(crs.to_wkt()))
self.global_encoding.wkt = True
else:
self._vlrs.extend(create_geotiff_projection_vlrs(crs))
| (self, crs: 'pyproj.CRS', keep_compatibility: bool = True) -> None | [
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|
31,543 | laspy.header | add_extra_dim | null | def add_extra_dim(self, params: ExtraBytesParams):
self.add_extra_dims([params])
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|
31,544 | laspy.header | add_extra_dims | null | def add_extra_dims(self, params: List[ExtraBytesParams]) -> None:
for param in params:
self.point_format.add_extra_dimension(param)
self._sync_extra_bytes_vlr()
| (self, params: List[laspy.point.format.ExtraBytesParams]) -> NoneType | [
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|
31,545 | laspy.header | grow | null | def grow(self, points: PackedPointRecord) -> None:
self.x_max = max(
self.x_max,
(points["X"].max() * self.x_scale) + self.x_offset,
)
self.y_max = max(
self.y_max,
(points["Y"].max() * self.y_scale) + self.y_offset,
)
self.z_max = max(
self.z_max,
(points["Z"].max() * self.z_scale) + self.z_offset,
)
self.x_min = min(
self.x_min,
(points["X"].min() * self.x_scale) + self.x_offset,
)
self.y_min = min(
self.y_min,
(points["Y"].min() * self.y_scale) + self.y_offset,
)
self.z_min = min(
self.z_min,
(points["Z"].min() * self.z_scale) + self.z_offset,
)
for return_number, count in zip(
*np.unique(points.return_number, return_counts=True)
):
if return_number == 0:
continue
if return_number > len(self.number_of_points_by_return):
break # np.unique sorts unique values
self.number_of_points_by_return[return_number - 1] += count
self.point_count += len(points)
| (self, points: laspy.point.record.PackedPointRecord) -> NoneType | [
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|
31,546 | laspy.header | max_point_count | null | def max_point_count(self) -> int:
if self.version <= Version(1, 3):
return np.iinfo(np.uint32).max
else:
return np.iinfo(np.uint64).max
| (self) -> int | [
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|
31,547 | laspy.header | parse_crs |
Method to parse OGC WKT or GeoTiff VLR keys into a pyproj CRS object
Returns None if no CRS VLR is present, or if the CRS specified
in the VLRS is not understood.
Parameters
----------
prefer_wkt: Optional, default True,
If True the WKT VLR will be preferred in case
both the WKT and Geotiff VLR are present
.. warning::
This requires `pyproj`.
.. versionadded:: 2.5
The ``prefer_wkt`` parameters.
| def parse_crs(self, prefer_wkt=True) -> Optional["pyproj.CRS"]:
"""
Method to parse OGC WKT or GeoTiff VLR keys into a pyproj CRS object
Returns None if no CRS VLR is present, or if the CRS specified
in the VLRS is not understood.
Parameters
----------
prefer_wkt: Optional, default True,
If True the WKT VLR will be preferred in case
both the WKT and Geotiff VLR are present
.. warning::
This requires `pyproj`.
.. versionadded:: 2.5
The ``prefer_wkt`` parameters.
"""
geo_vlr = self._vlrs.get_by_id("LASF_Projection")
if self.evlrs is not None:
geo_vlr.extend(self.evlrs.get_by_id("LASF_Projection"))
parsed_crs = {}
for rec in geo_vlr:
if isinstance(rec, (WktCoordinateSystemVlr, GeoKeyDirectoryVlr)):
crs = rec.parse_crs()
if crs is not None:
parsed_crs[type(rec)] = crs
# Could not parse anything / there was nothing to parse
if not parsed_crs:
return None
if prefer_wkt:
preferred, other = WktCoordinateSystemVlr, GeoKeyDirectoryVlr
else:
preferred, other = GeoKeyDirectoryVlr, WktCoordinateSystemVlr
try:
return parsed_crs[preferred]
except KeyError:
return parsed_crs[other]
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|
31,548 | laspy.header | partial_reset | null | def partial_reset(self) -> None:
f64info = np.finfo(np.float64)
self.maxs = np.ones(3, dtype=np.float64) * f64info.min
self.mins = np.ones(3, dtype=np.float64) * f64info.max
self.start_of_first_evlr = 0
self.number_of_evlrs = 0
self.point_count = 0
self.number_of_points_by_return = np.zeros(15, dtype=np.uint32)
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|
31,549 | laspy.header | read_evlrs |
Reads EVLRs from the stream and sets them in the
data property.
The evlrs are accessed from the `evlrs` property
Does nothing if either of these is true:
- The file does not support EVLRS (version < 1.4)
- The file has no EVLRS
- The stream does not support seeking
Leaves/restores the stream position to where it was before the call
| def read_evlrs(self, stream):
"""
Reads EVLRs from the stream and sets them in the
data property.
The evlrs are accessed from the `evlrs` property
Does nothing if either of these is true:
- The file does not support EVLRS (version < 1.4)
- The file has no EVLRS
- The stream does not support seeking
Leaves/restores the stream position to where it was before the call
"""
if self.version.minor >= 4:
if self.number_of_evlrs > 0 and stream.seekable():
saved_pos = stream.tell()
stream.seek(self.start_of_first_evlr, io.SEEK_SET)
self.evlrs = VLRList.read_from(
stream, self.number_of_evlrs, extended=True
)
stream.seek(saved_pos)
elif self.number_of_evlrs > 0 and not stream.seekable():
self.evlrs = None
else:
self.evlrs = VLRList()
else:
self.evlrs = None
| (self, stream) | [
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|
31,550 | laspy.header | remove_extra_dim | null | def remove_extra_dim(self, name: str) -> None:
self.remove_extra_dims([name])
| (self, name: str) -> NoneType | [
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|
31,551 | laspy.header | remove_extra_dims | null | def remove_extra_dims(self, names: Iterable[str]) -> None:
for name in names:
self.point_format.remove_extra_dimension(name)
self._sync_extra_bytes_vlr()
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|
31,552 | laspy.header | set_compressed | null | def set_compressed(self, state: bool) -> None:
self.are_points_compressed = state
| (self, state: bool) -> NoneType | [
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|
31,553 | laspy.header | set_version_and_point_format | null | def set_version_and_point_format(
self, version: Version, point_format: PointFormat
) -> None:
dims.raise_if_version_not_compatible_with_fmt(point_format.id, str(version))
self._version = version
self.point_format = point_format
| (self, version: laspy.header.Version, point_format: laspy.point.format.PointFormat) -> NoneType | [
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|
31,554 | laspy.header | update | null | def update(self, points: PackedPointRecord) -> None:
self.partial_reset()
if not points:
self.maxs = [0.0, 0.0, 0.0]
self.mins = [0.0, 0.0, 0.0]
else:
self.grow(points)
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|
31,555 | laspy.header | write_to |
ensure_same_size: if true this function will raise an internal error
if the written header would change the offset to point data
it originally had (meaning the file could become broken),
Used when rewriting a header to update the file (new point count, mins, maxs, etc)
| def write_to(
self,
stream: BinaryIO,
ensure_same_size: bool = False,
encoding_errors: str = "strict",
) -> None:
"""
ensure_same_size: if true this function will raise an internal error
if the written header would change the offset to point data
it originally had (meaning the file could become broken),
Used when rewriting a header to update the file (new point count, mins, maxs, etc)
"""
if self.point_count > self.max_point_count():
raise LaspyException(
f"Version {self.version} cannot save clouds with more than"
f" {self.max_point_count()} points (current: {self.point_count})"
)
little_endian = "little"
with io.BytesIO() as tmp:
self._vlrs.write_to(tmp, encoding_errors=encoding_errors)
vlr_bytes = tmp.getvalue()
header_size = LAS_HEADERS_SIZE[str(self.version)]
header_size += len(self.extra_header_bytes)
new_offset_to_data = header_size + len(vlr_bytes) + len(self.extra_vlr_bytes)
if ensure_same_size and new_offset_to_data != self.offset_to_point_data:
raise LaspyException(
"Internal error, writing header would change original offset to data"
"and break the file"
)
self.offset_to_point_data = new_offset_to_data
stream.write(LAS_FILE_SIGNATURE)
stream.write(self.file_source_id.to_bytes(2, little_endian, signed=False))
self.global_encoding.write_to(stream)
stream.write(self.uuid.bytes_le)
stream.write(self.version.major.to_bytes(1, little_endian, signed=False))
stream.write(self.version.minor.to_bytes(1, little_endian, signed=False))
was_truncated = write_string(
stream,
self.system_identifier,
SYSTEM_IDENTIFIER_LEN,
encoding_errors=encoding_errors,
)
if was_truncated:
logger.warning(
f"system identifier does not fit into the {SYSTEM_IDENTIFIER_LEN} maximum bytes,"
f" it will be truncated"
)
was_truncated = write_string(
stream,
self.generating_software,
GENERATING_SOFTWARE_LEN,
encoding_errors=encoding_errors,
)
if was_truncated:
logger.warning(
f"generating software does not fit into the {GENERATING_SOFTWARE_LEN} maximum bytes,"
f" it will be truncated"
)
if self.creation_date is None:
self.creation_date = date.today()
stream.write(
self.creation_date.timetuple().tm_yday.to_bytes(
2, little_endian, signed=False
)
)
stream.write(self.creation_date.year.to_bytes(2, little_endian, signed=False))
stream.write(header_size.to_bytes(2, little_endian, signed=False))
stream.write(self.offset_to_point_data.to_bytes(4, little_endian, signed=False))
stream.write(len(self._vlrs).to_bytes(4, little_endian, signed=False))
point_format_id = self.point_format.id
if self.are_points_compressed:
point_format_id = uncompressed_id_to_compressed(point_format_id)
stream.write(point_format_id.to_bytes(1, little_endian, signed=False))
stream.write(self.point_format.size.to_bytes(2, little_endian, signed=False))
# Point Count
if self.version.minor >= 4:
stream.write(int(0).to_bytes(4, little_endian, signed=False))
for i in range(5):
stream.write(int(0).to_bytes(4, little_endian, signed=False))
else:
stream.write(self.point_count.to_bytes(4, little_endian, signed=False))
for i in range(5):
stream.write(
int(self.number_of_points_by_return[i]).to_bytes(
4, little_endian, signed=False
)
)
for i in range(3):
stream.write(struct.pack("<d", self.scales[i]))
for i in range(3):
stream.write(struct.pack("<d", self.offsets[i]))
for i in range(3):
stream.write(struct.pack("<d", self.maxs[i]))
stream.write(struct.pack("<d", self.mins[i]))
if self.version.minor >= 3:
stream.write(
self.start_of_waveform_data_packet_record.to_bytes(
8, little_endian, signed=False
)
)
if self.version.minor >= 4:
stream.write(
self.start_of_first_evlr.to_bytes(8, little_endian, signed=False)
)
stream.write(self.number_of_evlrs.to_bytes(4, little_endian, signed=False))
stream.write(self.point_count.to_bytes(8, little_endian, signed=False))
for i in range(15):
stream.write(
int(self.number_of_points_by_return[i]).to_bytes(
8, little_endian, signed=False
)
)
stream.write(self.extra_header_bytes)
stream.write(vlr_bytes)
stream.write(self.extra_vlr_bytes)
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|
31,556 | laspy.lasreader | LasReader | The reader class handles LAS and LAZ via one of the supported backend | class LasReader:
"""The reader class handles LAS and LAZ via one of the supported backend"""
def __init__(
self,
source: BinaryIO,
closefd: bool = True,
laz_backend: Optional[Union[LazBackend, Iterable[LazBackend]]] = None,
read_evlrs: bool = True,
decompression_selection: DecompressionSelection = DecompressionSelection.all(),
):
"""
Initialize the LasReader
Parameters
----------
source: file_object
closefd: bool, default True
laz_backend: LazBackend or list of LazBackend, optional
read_evlrs: bool, default True
only applies to __init__ phase, and for files
that support evlrs
decompression_selection: optional, DecompressionSelection
Selection of fields to decompress, only works form point format >= 6 <= 10
Ignored on other point formats
.. versionadded:: 2.4
The ``read_evlrs`` and ``decompression_selection`` parameters.
"""
self.closefd = closefd
if laz_backend is None:
laz_backend = LazBackend.detect_available()
self.laz_backend = laz_backend
self.header = LasHeader.read_from(source, read_evlrs=read_evlrs)
self.decompression_selection = decompression_selection
# The point source is lazily instanciated.
# Because some reader implementation may
# read informations that require to seek towards the end of
# the file (eg: chunk table), and we prefer to limit opening
# to reading the header
self._point_source: Optional["IPointReader"] = None
self._source = source
self.points_read = 0
@property
def evlrs(self) -> Optional[VLRList]:
return self.header.evlrs
@evlrs.setter
def evlrs(self, evlrs: VLRList) -> None:
self.header.evlrs = evlrs
@property
def point_source(self) -> "IPointReader":
if self._point_source is None:
self._point_source = self._create_point_source(self._source)
return self._point_source
def read_points(self, n: int) -> record.ScaleAwarePointRecord:
"""Read n points from the file
Will only read as many points as the header advertise.
That is, if you ask to read 50 points and there are only 45 points left
this function will only read 45 points.
If there are no points left to read, returns an empty point record.
Parameters
----------
n: The number of points to read
if n is less than 0, this function will read the remaining points
"""
points_left = self.header.point_count - self.points_read
if points_left <= 0:
return record.ScaleAwarePointRecord.empty(
self.header.point_format,
self.header.scales,
self.header.offsets,
)
if n < 0:
n = points_left
else:
n = min(n, points_left)
r = record.PackedPointRecord.from_buffer(
self.point_source.read_n_points(n), self.header.point_format
)
if len(r) < n:
logger.error(f"Could only read {len(r)} of the requested {n} points")
points = record.ScaleAwarePointRecord(
r.array, r.point_format, self.header.scales, self.header.offsets
)
self.points_read += n
return points
def read(self) -> LasData:
"""
Reads all the points that are not read and returns a LasData object
This will also read EVLRS
"""
points = self.read_points(-1)
las_data = LasData(header=self.header, points=points)
shall_read_evlr = (
self.header.version.minor >= 4
and self.header.number_of_evlrs > 0
and self.evlrs is None
)
if shall_read_evlr:
# If we have to read evlrs by now, it either means:
# - the user asked for them not to be read during the opening phase.
# - and/or the stream is not seekable, thus they could not be read during opening phase
#
if self.point_source.source.seekable():
self.read_evlrs()
else:
# In that case we are still going to
# try to read the evlrs by relying on the fact that they should generally be
# right after the last point, which is where we are now.
if self.header.are_points_compressed:
if not isinstance(self.point_source, LazrsPointReader):
raise errors.LaspyException(
"Reading EVLRs from a LAZ in a non-seekable stream "
"can only be done with lazrs backend"
)
# Few things: If the stream is non seekable, only a LazrsPointReader
# could have been created (parallel requires ability to seek)
#
# Also, to work, the next lines of code assumes that:
# 1) We actually are just after the last point
# 2) The chunk table _starts_ just after the last point
# 3) The first EVLR starts just after the chunk table
# These assumptions should be fine for most of the cases
# and non seekable sources are probably not that common
_ = self.point_source.read_chunk_table_only()
# Since the LazrsDecompressor uses a buffered reader
# the python file object's position is not at the position we
# think it is.
# So we have to read data from the decompressor's
# buffered stream.
class LocalReader:
def __init__(self, source: LazrsPointReader) -> None:
self.source = source
def read(self, n: int) -> bytes:
return self.source.read_raw_bytes(n)
self.evlrs = VLRList.read_from(
LocalReader(self.point_source),
self.header.number_of_evlrs,
extended=True,
)
else:
# For this to work, we assume that the first evlr
# start just after the last point
self.header.evlrs = VLRList.read_from(
self.point_source.source,
self.header.number_of_evlrs,
extended=True,
)
return las_data
def seek(self, pos: int, whence: int = io.SEEK_SET) -> int:
"""Seeks to the start of the point at the given pos
Parameters
----------
pos: index of the point to seek to
whence: optional, controls how the pos parameter is interpreted:
io.SEEK_SET: (default) pos is the index of the point from the beginning
io.SEEK_CUR: pos is the point_index relative to the point_index of the last point read
io.SEEK_END: pos is the point_index relative to last point
Returns
-------
The index of the point the reader seeked to, relative to the first point
"""
if whence == io.SEEK_SET:
allowed_range = range(0, self.header.point_count)
point_index = pos
elif whence == io.SEEK_CUR:
allowed_range = range(
-self.points_read, self.header.point_count - self.points_read
)
point_index = self.points_read + pos
elif whence == io.SEEK_END:
allowed_range = range(-self.header.point_count, 0)
point_index = self.header.point_count + pos
else:
raise ValueError(f"Invalid value for whence: {whence}")
if pos not in allowed_range:
whence_str = ["start", "current point", "end"]
raise IndexError(
f"When seeking from | (source: <class 'BinaryIO'>, closefd: bool = True, laz_backend: Union[laspy._compression.backend.LazBackend, Iterable[laspy._compression.backend.LazBackend], NoneType] = None, read_evlrs: bool = True, decompression_selection: laspy._compression.selection.DecompressionSelection = <DecompressionSelection.ALL_EXTRA_BYTES|WAVEPACKET|NIR|RGB|GPS_TIME|POINT_SOURCE_ID|USER_DATA|SCAN_ANGLE|INTENSITY|FLAGS|CLASSIFICATION|Z|XY_RETURNS_CHANNEL: 8191>) | [
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|
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