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Metadata-Version: 2.1 |
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Name: sqlitedict |
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Version: 2.1.0 |
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Summary: Persistent dict in Python, backed up by sqlite3 and pickle, multithread-safe. |
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Home-page: https://github.com/piskvorky/sqlitedict |
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Author: Radim Rehurek, Victor R. Escobar, Andrey Usov, Prasanna Swaminathan, Jeff Quast |
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Author-email: [email protected] |
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Maintainer: Radim Rehurek |
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Maintainer-email: [email protected] |
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License: Apache 2.0 |
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Download-URL: http://pypi.python.org/pypi/sqlitedict |
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Keywords: sqlite,persistent dict,multithreaded |
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Platform: any |
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Classifier: Development Status :: 5 - Production/Stable |
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Classifier: Environment :: Console |
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Classifier: Intended Audience :: Developers |
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Classifier: License :: OSI Approved :: Apache Software License |
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Classifier: Operating System :: OS Independent |
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Classifier: Programming Language :: Python :: 3.7 |
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Classifier: Programming Language :: Python :: 3.8 |
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Classifier: Programming Language :: Python :: 3.9 |
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Classifier: Programming Language :: Python :: 3.10 |
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Classifier: Topic :: Database :: Front-Ends |
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License-File: LICENSE.md |
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=================================================== |
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sqlitedict -- persistent ``dict``, backed by SQLite |
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=================================================== |
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|GithubActions|_ |
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|License|_ |
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.. |GithubActions| image:: https://github.com/RaRe-Technologies/sqlitedict/actions/workflows/python-package.yml/badge.svg |
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.. |Downloads| image:: https://img.shields.io/pypi/dm/sqlitedict.svg |
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.. |License| image:: https://img.shields.io/pypi/l/sqlitedict.svg |
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.. _GithubActions: https://github.com/RaRe-Technologies/sqlitedict/actions/workflows/python-package.yml |
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.. _Downloads: https://pypi.python.org/pypi/sqlitedict |
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.. _License: https://pypi.python.org/pypi/sqlitedict |
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A lightweight wrapper around Python's sqlite3 database with a simple, Pythonic |
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dict-like interface and support for multi-thread access: |
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Usage |
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===== |
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Write |
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----- |
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.. code-block:: python |
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>>> from sqlitedict import SqliteDict |
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>>> db = SqliteDict("example.sqlite") |
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>>> |
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>>> db["1"] = {"name": "first item"} |
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>>> db["2"] = {"name": "second item"} |
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>>> db["3"] = {"name": "yet another item"} |
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>>> |
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>>> # Commit to save the objects. |
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>>> db.commit() |
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>>> |
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>>> db["4"] = {"name": "yet another item"} |
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>>> # Oops, forgot to commit here, that object will never be saved. |
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>>> # Always remember to commit, or enable autocommit with SqliteDict("example.sqlite", autocommit=True) |
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>>> # Autocommit is off by default for performance. |
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>>> |
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>>> db.close() |
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Read |
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---- |
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.. code-block:: python |
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>>> from sqlitedict import SqliteDict |
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>>> db = SqliteDict("example.sqlite") |
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>>> |
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>>> print("There are %d items in the database" % len(db)) |
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There are 3 items in the database |
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>>> |
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>>> # Standard dict interface. items() values() keys() etc... |
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>>> for key, item in db.items(): |
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... print("%s=%s" % (key, item)) |
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1={'name': 'first item'} |
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2={'name': 'second item'} |
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3={'name': 'yet another item'} |
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>>> |
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>>> db.close() |
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Efficiency |
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---------- |
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By default, sqlitedict's exception handling favors verbosity over efficiency. |
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It extracts and outputs the outer exception stack to the error logs. |
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If you favor efficiency, then initialize the DB with outer_stack=False. |
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.. code-block:: python |
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>>> from sqlitedict import SqliteDict |
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>>> db = SqliteDict("example.sqlite", outer_stack=False) # True is the default |
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>>> db[1] |
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{'name': 'first item'} |
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Context Manager |
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--------------- |
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.. code-block:: python |
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>>> from sqlitedict import SqliteDict |
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>>> |
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>>> # The database is automatically closed when leaving the with section. |
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>>> # Uncommitted objects are not saved on close. REMEMBER TO COMMIT! |
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>>> |
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>>> with SqliteDict("example.sqlite") as db: |
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... print("There are %d items in the database" % len(db)) |
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There are 3 items in the database |
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Tables |
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------ |
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A database file can store multiple tables. |
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A default table is used when no table name is specified. |
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Note: Writes are serialized, having multiple tables does not improve performance. |
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.. code-block:: python |
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>>> from sqlitedict import SqliteDict |
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>>> |
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>>> products = SqliteDict("example.sqlite", tablename="product", autocommit=True) |
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>>> manufacturers = SqliteDict("example.sqlite", tablename="manufacturer", autocommit=True) |
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>>> |
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>>> products["1"] = {"name": "first item", "manufacturer_id": "1"} |
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>>> products["2"] = {"name": "second item", "manufacturer_id": "1"} |
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>>> |
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>>> manufacturers["1"] = {"manufacturer_name": "afactory", "location": "US"} |
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>>> manufacturers["2"] = {"manufacturer_name": "anotherfactory", "location": "UK"} |
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>>> |
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>>> tables = products.get_tablenames('example.sqlite') |
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>>> print(tables) |
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['unnamed', 'product', 'manufacturer'] |
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>>> |
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>>> products.close() |
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>>> manufacturers.close() |
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In case you're wondering, the unnamed table comes from the previous examples, |
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where we did not specify a table name. |
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Serialization |
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------------- |
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Keys are strings. Values are any serializeable object. |
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By default Pickle is used internally to (de)serialize the values. |
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It's possible to use a custom (de)serializer, notably for JSON and for compression. |
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.. code-block:: python |
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>>> # Use JSON instead of pickle |
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>>> import json |
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>>> with SqliteDict("example.sqlite", encode=json.dumps, decode=json.loads) as mydict: |
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... pass |
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>>> |
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>>> # Apply zlib compression after pickling |
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>>> import zlib, pickle, sqlite3 |
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>>> |
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>>> def my_encode(obj): |
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... return sqlite3.Binary(zlib.compress(pickle.dumps(obj, pickle.HIGHEST_PROTOCOL))) |
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>>> |
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>>> def my_decode(obj): |
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... return pickle.loads(zlib.decompress(bytes(obj))) |
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>>> |
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>>> with SqliteDict("example.sqlite", encode=my_encode, decode=my_decode) as mydict: |
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... pass |
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It's also possible to use a custom (de)serializer for keys to allow non-string keys. |
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.. code-block:: python |
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>>> # Use key encoding instead of default string keys only |
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>>> from sqlitedict import encode_key, decode_key |
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>>> with SqliteDict("example.sqlite", encode_key=encode_key, decode_key=decode_key) as mydict: |
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... pass |
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More |
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---- |
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Functions are well documented, see docstrings directly in ``sqlitedict.py`` or call ``help(sqlitedict)``. |
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**Beware**: because of Python semantics, ``sqlitedict`` cannot know when a mutable |
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SqliteDict-backed entry was modified in RAM. You'll need to |
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explicitly assign the mutated object back to SqliteDict: |
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.. code-block:: python |
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>>> from sqlitedict import SqliteDict |
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>>> db = SqliteDict("example.sqlite") |
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>>> db["colors"] = {"red": (255, 0, 0)} |
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>>> db.commit() |
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>>> |
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>>> colors = db["colors"] |
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>>> colors["blue"] = (0, 0, 255) # sqlite DB not updated here! |
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>>> db["colors"] = colors # now updated |
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>>> |
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>>> db.commit() # remember to commit (or set autocommit) |
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>>> db.close() |
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Features |
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======== |
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* Values can be **any picklable objects** (uses ``pickle`` with the highest protocol). |
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* Support for **multiple tables** (=dicts) living in the same database file. |
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* Support for **access from multiple threads** to the same connection (needed by e.g. Pyro). |
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Vanilla sqlite3 gives you ``ProgrammingError: SQLite objects created in a thread can |
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only be used in that same thread.`` |
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Concurrent requests are still serialized internally, so this "multithreaded support" |
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**doesn't** give you any performance benefits. It is a work-around for sqlite limitations in Python. |
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* Support for **custom serialization or compression**: |
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.. code-block:: python |
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# use JSON instead of pickle |
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>>> import json |
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>>> mydict = SqliteDict('./my_db.sqlite', encode=json.dumps, decode=json.loads) |
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# apply zlib compression after pickling |
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>>> import zlib, pickle, sqlite3 |
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>>> def my_encode(obj): |
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... return sqlite3.Binary(zlib.compress(pickle.dumps(obj, pickle.HIGHEST_PROTOCOL))) |
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>>> def my_decode(obj): |
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... return pickle.loads(zlib.decompress(bytes(obj))) |
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>>> mydict = SqliteDict('./my_db.sqlite', encode=my_encode, decode=my_decode) |
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* sqlite is efficient and can work effectively with large databases (multi gigabytes), not limited by memory. |
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* sqlitedict is mostly a thin wrapper around sqlite. |
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* ``items()`` ``keys()`` ``values()`` are iterating one by one, the rows are loaded in a worker thread and queued in memory. |
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* ``len()`` is calling sqlite to count rows, that is scanning the whole table. |
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* For better performance, write objects in batch and ``commit()`` once. |
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Installation |
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============ |
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The module has no dependencies beyond Python itself. |
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The minimum supported Python version is 3.7, continuously tested on Python 3.7, 3.8, 3.9, and 3.10 `on Travis <https://travis-ci.org/RaRe-Technologies/sqlitedict>`_. |
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Install or upgrade with:: |
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pip install -U sqlitedict |
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or from the `source tar.gz <http://pypi.python.org/pypi/sqlitedict>`_:: |
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python setup.py install |
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Contributions |
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============= |
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Testing |
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------- |
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Install:: |
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$ pip install pytest coverage pytest-coverage |
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To perform all tests:: |
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$ mkdir -p tests/db |
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$ pytest tests |
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$ python -m doctest README.rst |
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To perform all tests with coverage:: |
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$ pytest tests --cov=sqlitedict |
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Comments, bug reports |
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--------------------- |
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``sqlitedict`` resides on `github <https://github.com/RaRe-Technologies/sqlitedict>`_. You can file |
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issues or pull requests there. |
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License |
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======= |
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``sqlitedict`` is open source software released under the `Apache 2.0 license <http://opensource.org/licenses/apache2.0.php>`_. |
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Copyright (c) 2011-now `Radim Řehůřek <http://radimrehurek.com>`_ and contributors. |
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Housekeeping |
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============ |
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Clean up the test database to keep each doctest run idempotent: |
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.. code-block:: python |
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>>> import os |
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>>> if __name__ == '__main__': |
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... os.unlink('example.sqlite') |
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