# Microsoft Clarity API
*Version: 0.0.3*
**Microsoft Clarity Data Export API**
This Python library allows you to work with the dashboard data. The data can be structured over a specified date range
and can break down insights by up to three dimensions.
Find out more about the [Clarity Data Export API](https://learn.microsoft.com/en-us/clarity/setup-and-installation/clarity-data-export-api)
This repository is actively maintained - Contributions are welcome!
<details>
<summary><b>Getting Started:</b></summary>
### Prerequisites
- An active Microsoft Clarity account. [Learn how to sign up for Clarity](https://clarity.microsoft.com).
- An API access token generated by the project's admin from the settings page.
- Python3.8+
### Obtaining Access Tokens
**Note**: Only project admins can manage access tokens.
1. Go to your Clarity project. Select `Settings` -> `Data Export` -> `Generate new API token`.
2. Provide a descriptive name for the token for easy identification.
## Parameters
- `numOfDays`: (1, 2, or 3) The number of days for the data export since the API call, relating to the last 24, 48, or 72 hours, respectively.
- `dimension1`: The first dimension to break down insights.
- `dimension2`: The second dimension to break down insights.
- `dimension3`: The third dimension to break down insights.
#### Dimension Options:
- Browser
- Device
- Country
- OS
- Source
- Medium
- Campaign
- Channel
- URL
</details>
<details>
<summary><b>Usage:</b></summary>
```python
#!/usr/bin/python
# coding: utf-8
import clarity_api
# Use token generated from the steps above
token = "<TOKEN>"
url = "https://www.clarity.ms"
client = clarity_api.Api(url=url, token=token)
data = client.get_data_export(number_of_days=2, dimension_1="OS", dimension_2="Channel")
print("Pydantic Object:", data)
print("Raw Request Output:", data.raw_output)
print("JSON Request Output:", data.json_output)
print("Pydantic Object Model Dump:", data.model_dump())
print("Request Status Code:", data.status_code)
print("Request Error:", data.error)
```
</details>
<details>
<summary><b>Installation Instructions:</b></summary>
Install Python Package
```bash
python -m pip install clarity-api
```
</details>
<details>
<summary><b>Tests:</b></summary>
pre-commit check
```bash
pre-commit run --all-files
```
pytest
```bash
pytest ./test/test_clarity_models.py
```
</details>
<details>
<summary><b>Repository Owners:</b></summary>
<img width="100%" height="180em" src="https://github-readme-stats.vercel.app/api?username=Knucklessg1&show_icons=true&hide_border=true&&count_private=true&include_all_commits=true" />
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"description": "# Microsoft Clarity API\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n*Version: 0.0.3*\n\n**Microsoft Clarity Data Export API**\n\nThis Python library allows you to work with the dashboard data. The data can be structured over a specified date range \nand can break down insights by up to three dimensions.\n\nFind out more about the [Clarity Data Export API](https://learn.microsoft.com/en-us/clarity/setup-and-installation/clarity-data-export-api)\n\nThis repository is actively maintained - Contributions are welcome!\n\n<details>\n <summary><b>Getting Started:</b></summary>\n\n### Prerequisites\n- An active Microsoft Clarity account. [Learn how to sign up for Clarity](https://clarity.microsoft.com).\n- An API access token generated by the project's admin from the settings page.\n- Python3.8+\n\n### Obtaining Access Tokens\n**Note**: Only project admins can manage access tokens.\n\n1. Go to your Clarity project. Select `Settings` -> `Data Export` -> `Generate new API token`.\n2. Provide a descriptive name for the token for easy identification.\n\n## Parameters\n- `numOfDays`: (1, 2, or 3) The number of days for the data export since the API call, relating to the last 24, 48, or 72 hours, respectively.\n- `dimension1`: The first dimension to break down insights.\n- `dimension2`: The second dimension to break down insights.\n- `dimension3`: The third dimension to break down insights.\n\n#### Dimension Options:\n- Browser\n- Device\n- Country\n- OS\n- Source\n- Medium\n- Campaign\n- Channel\n- URL\n\n</details>\n\n<details>\n <summary><b>Usage:</b></summary>\n\n```python\n#!/usr/bin/python\n# coding: utf-8\nimport clarity_api\n\n# Use token generated from the steps above\ntoken = \"<TOKEN>\"\nurl = \"https://www.clarity.ms\"\nclient = clarity_api.Api(url=url, token=token)\n\ndata = client.get_data_export(number_of_days=2, dimension_1=\"OS\", dimension_2=\"Channel\")\nprint(\"Pydantic Object:\", data)\nprint(\"Raw Request Output:\", data.raw_output)\nprint(\"JSON Request Output:\", data.json_output)\nprint(\"Pydantic Object Model Dump:\", data.model_dump())\nprint(\"Request Status Code:\", data.status_code)\nprint(\"Request Error:\", data.error)\n```\n\n</details>\n\n<details>\n <summary><b>Installation Instructions:</b></summary>\n\nInstall Python Package\n\n```bash\npython -m pip install clarity-api\n```\n\n</details>\n\n<details>\n <summary><b>Tests:</b></summary>\n\npre-commit check\n```bash\npre-commit run --all-files\n```\n\npytest\n```bash\npytest ./test/test_clarity_models.py\n```\n</details>\n\n\n<details>\n <summary><b>Repository Owners:</b></summary>\n\n\n<img width=\"100%\" height=\"180em\" src=\"https://github-readme-stats.vercel.app/api?username=Knucklessg1&show_icons=true&hide_border=true&&count_private=true&include_all_commits=true\" />\n\n\n\n</details>\n\n\n",
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