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width=\"400px\"\u003e\n\u003cbr /\u003e\u003cbr /\u003e\nA simple yet powerful SDK for the YouTube Analytics API.\n\u003cbr /\u003e\u003cbr /\u003e\n\u003ca href=\"https://pypi.python.org/pypi/analytix\"\u003e\u003cimg alt=\"PyPI - Version\" src=\"https://img.shields.io/pypi/v/analytix\"\u003e\u003c/a\u003e\n\u003ca href=\"https://pypi.python.org/pypi/analytix\"\u003e\u003cimg alt=\"PyPI - Python Version\" src=\"https://img.shields.io/pypi/pyversions/analytix\"\u003e\u003c/a\u003e\n\u003ca href=\"https://pypi.python.org/pypi/analytix\"\u003e\u003cimg alt=\"PyPI - Implementation\" src=\"https://img.shields.io/pypi/implementation/analytix\"\u003e\u003c/a\u003e\n\u003chr /\u003e\n\u003c/div\u003e\n\n## Features\n\n* Pythonic syntax lets you feel right at home\n* Dynamic error handling saves hours of troubleshooting and makes sure only valid requests count toward your API quota\n* A clever interface allows you to make multiple requests across multiple sessions without reauthorising\n* Extra support enables you to export reports in a variety of filetypes and to a number of DataFrame formats\n* Easy enough for beginners, but powerful enough for advanced users\n\n## Installation\n\n### Installing analytix\n\nTo install the latest stable version of analytix, use the following command:\n\n```sh\npip install analytix\n```\n\nYou can also install the latest development version using the following command:\n\n```sh\npip install git+https://github.com/parafoxia/analytix\n```\n\nYou may need to prefix these commands with a call to the Python interpreter depending on your OS and Python configuration.\n\n### Dependencies\n\nBelow is a list of analytix's dependencies.\nNote that the minimum version assumes you're using CPython 3.8.\nThe latest versions of each library are always supported.\n\n| Name              | Min. version | Required? | Usage                                                         | \n|-------------------|--------------|-----------|---------------------------------------------------------------|\n| `urllib3`         | 2.2.0        | Yes       | Making HTTP requests                                          |\n| `jwt`             | 1.2.0        | No        | Decoding JWT ID tokens (from v5.1)                            |\n| `openpyxl`        | 3.0.0        | No        | Exporting report data to Excel spreadsheets                   |\n| `pandas`          | ~1.3.0       | No        | Exporting report data to pandas DataFrames                    |\n| `polars`          | 0.15.17      | No        | Exporting report data to Polars DataFrames                    |\n| `pyarrow`         | ~5.0.0       | No        | Exporting report data to Apache Arrow tables and file formats |\n\n## OAuth authentication\n\nAll requests to the YouTube Analytics API need to be authorised through OAuth 2.\nIn order to do this, you will need a Google Developers project with the YouTube Analytics API enabled.\nYou can find instructions on how to do that in the [API setup guide](https://parafoxia.github.io/analytix/starting/googleapp/).\n\nOnce a project is set up, analytix handles authorisation — including token refreshing — for you.\n\nMore details regarding how and when refresh tokens expire can be found on the [Google Identity documentation](https://developers.google.com/identity/protocols/oauth2#expiration).\n\n## Usage\n\n### Retrieving reports\n\nThe following example creates a CSV file containing basic info for the 10 most viewed videos, from most to least viewed, in the US in 2022:\n\n```py\nfrom datetime import date\n\nfrom analytix import Client\n\nclient = Client(\"secrets.json\")\nreport = client.fetch_report(\n    dimensions=(\"video\",),\n    filters={\"country\": \"US\"},\n    metrics=(\"estimatedMinutesWatched\", \"views\", \"likes\", \"comments\"),\n    sort_options=(\"-estimatedMinutesWatched\",),\n    start_date=date(2022, 1, 1),\n    end_date=date(2022, 12, 31),\n    max_results=10,\n)\nreport.to_csv(\"analytics.csv\")\n```\n\nIf you want to analyse this data using additional tools such as *pandas*, you can directly export the report as a DataFrame or table using the `to_pandas()`, `to_arrow()`, and `to_polars()` methods of the report instance.\nYou can also save the report as a `.tsv`, `.json`, `.xlsx`, `.parquet`, or `.feather` file.\n\nThere are more examples in the [GitHub repository](https://github.com/parafoxia/analytix/tree/main/examples).\n\n### Fetching group information\n\nYou can also fetch groups and group items:\n\n```py\nfrom analytix import Client\n\n# You can also use the client as context manager!\nwith Client(\"secrets.json\") as client:\n    groups = client.fetch_groups()\n    group_items = client.fetch_group_items(groups[0].id)\n```\n\n### Logging\n\nIf you want to see what analytix is doing, you can enable the packaged logger:\n\n```py\nimport analytix\n\nanalytix.enable_logging()\n```\n\nThis defaults to showing all log messages of level INFO and above.\nTo show more (or less) messages, pass a logging level as an argument.\n\n## Compatibility\n\nCPython versions 3.8 through 3.14 and PyPy versions 3.9 through 3.11 are officially supported\\*.\nCPython 3.15-dev is provisionally supported\\*.\nWindows, MacOS, and Linux are all supported.\n\n*For base analytix functionality; support cannot be guaranteed for functionality requiring external libraries.\n\n## Contributing\n\nContributions are very much welcome! To get started:\n\n* Familiarise yourself with the [code of conduct](https://github.com/parafoxia/analytix/blob/main/CODE_OF_CONDUCT.md)\n* Have a look at the [contributing guide](https://github.com/parafoxia/analytix/blob/main/CONTRIBUTING.md)\n\n## License\n\nThe analytix module for Python is licensed under the [BSD 3-Clause License](https://github.com/parafoxia/analytix/blob/main/LICENSE).\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fparafoxia%2Fanalytix","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fparafoxia%2Fanalytix","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fparafoxia%2Fanalytix/lists"}