.. contents:: **df-diskcache**
:backlinks: top
:depth: 2
Summary
============================================
``df-diskcache`` is a Python library for caching ``pandas.DataFrame`` objects to local disk.
.. image:: https://badge.fury.io/py/df-diskcache.svg
:target: https://badge.fury.io/py/df-diskcache
:alt: PyPI package version
.. image:: https://img.shields.io/pypi/pyversions/df-diskcache.svg
:target: https://pypi.org/project/df-diskcache
:alt: Supported Python versions
.. image:: https://github.com/thombashi/df-diskcache/actions/workflows/ci.yml/badge.svg
:target: https://github.com/thombashi/df-diskcache/actions/workflows/ci.yml
:alt: CI status of Linux/macOS/Windows
.. image:: https://coveralls.io/repos/github/thombashi/df-diskcache/badge.svg?branch=master
:target: https://coveralls.io/github/thombashi/df-diskcache?branch=master
:alt: Test coverage: coveralls
.. image:: https://github.com/thombashi/df-diskcache/actions/workflows/github-code-scanning/codeql/badge.svg
:target: https://github.com/thombashi/df-diskcache/actions/workflows/github-code-scanning/codeql
:alt: CodeQL
Installation
============================================
::
pip install df-diskcache
Features
============================================
Supports the following methods:
- ``get``: Get a cache entry (``pandas.DataFrame``) for the key. Returns ``None`` if the key is not found.
- ``set``: Create a cache entry with an optional time-to-live (TTL) for the key-value pair.
- ``update``
- ``touch``: Update the last accessed time of a cache entry to extend the TTL.
- ``delete``
- ``prune``: Delete expired cache entries.
- Dictionary-like operations:
- ``__getitem__``
- ``__setitem__``
- ``__contains__``
- ``__delitem__``
Usage
============================================
:Sample Code:
.. code-block:: python
import pandas as pd
from dfdiskcache import DataFrameDiskCache
cache = DataFrameDiskCache()
url = "https://raw.githubusercontent.com/pandas-dev/pandas/v2.1.3/pandas/tests/io/data/csv/iris.csv"
df = cache.get(url)
if df is None:
print("cache miss")
df = pd.read_csv(url)
cache.set(url, df)
else:
print("cache hit")
print(df)
You can also use operations like a dictionary:
:Sample Code:
.. code-block:: python
import pandas as pd
from dfdiskcache import DataFrameDiskCache
cache = DataFrameDiskCache()
url = "https://raw.githubusercontent.com/pandas-dev/pandas/v2.1.3/pandas/tests/io/data/csv/iris.csv"
df = cache[url]
if df is None:
print("cache miss")
df = pd.read_csv(url)
cache[url] = df
else:
print("cache hit")
print(df)
Set TTL for cache entries
--------------------------------------------
:Sample Code:
.. code-block:: python
import pandas as pd
from dfdiskcache import DataFrameDiskCache
DataFrameDiskCache.DEFAULT_TTL = 10 # you can override the default TTL (default: 3600 seconds)
cache = DataFrameDiskCache()
url = "https://raw.githubusercontent.com/pandas-dev/pandas/v2.1.3/pandas/tests/io/data/csv/iris.csv"
df = cache.get(url)
if df is None:
df = pd.read_csv(url)
cache.set(url, df, ttl=60) # you can set a TTL for the key-value pair
print(df)
Dependencies
============================================
- Python 3.7+
- `Python package dependencies (automatically installed) <https://github.com/thombashi/df-diskcache/network/dependencies>`__
Raw data
{
"_id": null,
"home_page": "https://github.com/thombashi/df-diskcache",
"name": "df-diskcache",
"maintainer": "",
"docs_url": null,
"requires_python": ">=3.7",
"maintainer_email": "",
"keywords": "cache,disk,dataframe,library,pandas",
"author": "Tsuyoshi Hombashi",
"author_email": "tsuyoshi.hombashi@gmail.com",
"download_url": "https://files.pythonhosted.org/packages/b5/c1/a951201dbe93782f8c3b84a2b303240f05b4d6af3c6c3636d3aa9d8b183e/df-diskcache-0.0.2.tar.gz",
"platform": null,
"description": ".. contents:: **df-diskcache**\n :backlinks: top\n :depth: 2\n\n\nSummary\n============================================\n\n``df-diskcache`` is a Python library for caching ``pandas.DataFrame`` objects to local disk.\n\n.. image:: https://badge.fury.io/py/df-diskcache.svg\n :target: https://badge.fury.io/py/df-diskcache\n :alt: PyPI package version\n\n.. image:: https://img.shields.io/pypi/pyversions/df-diskcache.svg\n :target: https://pypi.org/project/df-diskcache\n :alt: Supported Python versions\n\n.. image:: https://github.com/thombashi/df-diskcache/actions/workflows/ci.yml/badge.svg\n :target: https://github.com/thombashi/df-diskcache/actions/workflows/ci.yml\n :alt: CI status of Linux/macOS/Windows\n\n.. image:: https://coveralls.io/repos/github/thombashi/df-diskcache/badge.svg?branch=master\n :target: https://coveralls.io/github/thombashi/df-diskcache?branch=master\n :alt: Test coverage: coveralls\n\n.. image:: https://github.com/thombashi/df-diskcache/actions/workflows/github-code-scanning/codeql/badge.svg\n :target: https://github.com/thombashi/df-diskcache/actions/workflows/github-code-scanning/codeql\n :alt: CodeQL\n\n\nInstallation\n============================================\n::\n\n pip install df-diskcache\n\n\nFeatures\n============================================\n\nSupports the following methods:\n\n- ``get``: Get a cache entry (``pandas.DataFrame``) for the key. Returns ``None`` if the key is not found.\n- ``set``: Create a cache entry with an optional time-to-live (TTL) for the key-value pair.\n- ``update``\n- ``touch``: Update the last accessed time of a cache entry to extend the TTL.\n- ``delete``\n- ``prune``: Delete expired cache entries.\n- Dictionary-like operations:\n - ``__getitem__``\n - ``__setitem__``\n - ``__contains__``\n - ``__delitem__``\n\n\nUsage\n============================================\n\n:Sample Code:\n .. code-block:: python\n\n import pandas as pd\n from dfdiskcache import DataFrameDiskCache\n\n cache = DataFrameDiskCache()\n url = \"https://raw.githubusercontent.com/pandas-dev/pandas/v2.1.3/pandas/tests/io/data/csv/iris.csv\"\n\n df = cache.get(url)\n if df is None:\n print(\"cache miss\")\n df = pd.read_csv(url)\n cache.set(url, df)\n else:\n print(\"cache hit\")\n\n print(df)\n\nYou can also use operations like a dictionary:\n\n:Sample Code:\n .. code-block:: python\n\n import pandas as pd\n from dfdiskcache import DataFrameDiskCache\n\n cache = DataFrameDiskCache()\n url = \"https://raw.githubusercontent.com/pandas-dev/pandas/v2.1.3/pandas/tests/io/data/csv/iris.csv\"\n\n df = cache[url]\n if df is None:\n print(\"cache miss\")\n df = pd.read_csv(url)\n cache[url] = df\n else:\n print(\"cache hit\")\n\n print(df)\n\n\nSet TTL for cache entries\n--------------------------------------------\n\n:Sample Code:\n .. code-block:: python\n\n import pandas as pd\n from dfdiskcache import DataFrameDiskCache\n\n DataFrameDiskCache.DEFAULT_TTL = 10 # you can override the default TTL (default: 3600 seconds)\n\n cache = DataFrameDiskCache()\n url = \"https://raw.githubusercontent.com/pandas-dev/pandas/v2.1.3/pandas/tests/io/data/csv/iris.csv\"\n\n df = cache.get(url)\n if df is None:\n df = pd.read_csv(url)\n cache.set(url, df, ttl=60) # you can set a TTL for the key-value pair\n\n print(df)\n\n\nDependencies\n============================================\n- Python 3.7+\n- `Python package dependencies (automatically installed) <https://github.com/thombashi/df-diskcache/network/dependencies>`__\n",
"bugtrack_url": null,
"license": "MIT License",
"summary": "df-diskcache is a Python library for caching pandas.DataFrame objects to local disk.",
"version": "0.0.2",
"project_urls": {
"Changlog": "https://github.com/thombashi/df-diskcache/releases",
"Homepage": "https://github.com/thombashi/df-diskcache",
"Source": "https://github.com/thombashi/df-diskcache",
"Tracker": "https://github.com/thombashi/df-diskcache/issues"
},
"split_keywords": [
"cache",
"disk",
"dataframe",
"library",
"pandas"
],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "5a0a471991d408b270b052b2b0aaf5734856cc65ff4177db57c8b32800b6634d",
"md5": "7584273beae391cc4456ae12d55fedc1",
"sha256": "dcb6c9b1ea31d18aa51e26db23468cb1a5f97b37943172951812352138a106b8"
},
"downloads": -1,
"filename": "df_diskcache-0.0.2-py3-none-any.whl",
"has_sig": false,
"md5_digest": "7584273beae391cc4456ae12d55fedc1",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": ">=3.7",
"size": 6489,
"upload_time": "2023-11-26T23:51:26",
"upload_time_iso_8601": "2023-11-26T23:51:26.821002Z",
"url": "https://files.pythonhosted.org/packages/5a/0a/471991d408b270b052b2b0aaf5734856cc65ff4177db57c8b32800b6634d/df_diskcache-0.0.2-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "b5c1a951201dbe93782f8c3b84a2b303240f05b4d6af3c6c3636d3aa9d8b183e",
"md5": "2b9e049211e1df05b3f04d3703b81fb7",
"sha256": "d050bf3f4eb4f1f141a2f0ac5fc160fbeb880098c13e411d5357ea48d2d36f0f"
},
"downloads": -1,
"filename": "df-diskcache-0.0.2.tar.gz",
"has_sig": false,
"md5_digest": "2b9e049211e1df05b3f04d3703b81fb7",
"packagetype": "sdist",
"python_version": "source",
"requires_python": ">=3.7",
"size": 8290,
"upload_time": "2023-11-26T23:51:28",
"upload_time_iso_8601": "2023-11-26T23:51:28.756630Z",
"url": "https://files.pythonhosted.org/packages/b5/c1/a951201dbe93782f8c3b84a2b303240f05b4d6af3c6c3636d3aa9d8b183e/df-diskcache-0.0.2.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2023-11-26 23:51:28",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "thombashi",
"github_project": "df-diskcache",
"travis_ci": false,
"coveralls": false,
"github_actions": true,
"tox": true,
"lcname": "df-diskcache"
}
JSON
