# Datadog Checks Base
[![Latest PyPI version][1]][7]
[![Supported Python versions][2]][7]
## Overview
This package provides the Python bits needed by the [Datadog Agent][4]
to run Agent-based Integrations (also known as _Checks_).
This package is used in two scenarios:
1. When used from within the Python interpreter embedded in the Agent, it
provides all the base classes and utilities needed by any Check.
2. When installed in a local environment with a regular Python interpreter, it
mocks the presence of a running Agent so checks can work in standalone mode,
mostly useful for testing and development.
Please refer to the [docs][5] for details.
## Installation
Checks from [integrations-core][6] already
use the toolkit in a transparent way when you run the tests but you can
install the toolkit locally and play with it:
```shell
pip install datadog-checks-base
```
## Performance Optimizations
We strive to balance lean resource usage with a "batteries included" user experience.
We employ a few tricks to achieve this.
One of them is the [lazy-loader][9] library that allows us to expose a nice API (simple, short imports) without the baseline memory overhead of importing everything all the time.
Another trick is to import some of our dependencies inside functions that use them instead of the more conventional import section at the top of the file. We rely on this the most in the `AgentCheck` base class.
## Troubleshooting
Need help? Contact [Datadog support][8].
[1]: https://img.shields.io/pypi/v/datadog-checks-base.svg
[2]: https://img.shields.io/pypi/pyversions/datadog-checks-base.svg
[4]: https://github.com/DataDog/datadog-agent
[5]: https://datadoghq.dev/integrations-core/base/about/
[6]: https://github.com/DataDog/integrations-core
[7]: https://pypi.org/project/datadog-checks-base/
[8]: https://docs.datadoghq.com/help/
[9]: https://github.com/scientific-python/lazy-loader
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"description": "# Datadog Checks Base\n\n[![Latest PyPI version][1]][7]\n[![Supported Python versions][2]][7]\n\n## Overview\n\nThis package provides the Python bits needed by the [Datadog Agent][4]\nto run Agent-based Integrations (also known as _Checks_).\n\nThis package is used in two scenarios:\n\n1. When used from within the Python interpreter embedded in the Agent, it\nprovides all the base classes and utilities needed by any Check.\n\n2. When installed in a local environment with a regular Python interpreter, it\nmocks the presence of a running Agent so checks can work in standalone mode,\nmostly useful for testing and development.\n\nPlease refer to the [docs][5] for details.\n\n## Installation\n\nChecks from [integrations-core][6] already\nuse the toolkit in a transparent way when you run the tests but you can\ninstall the toolkit locally and play with it:\n\n```shell\npip install datadog-checks-base\n```\n\n## Performance Optimizations\n\nWe strive to balance lean resource usage with a \"batteries included\" user experience.\nWe employ a few tricks to achieve this.\n\nOne of them is the [lazy-loader][9] library that allows us to expose a nice API (simple, short imports) without the baseline memory overhead of importing everything all the time.\n\nAnother trick is to import some of our dependencies inside functions that use them instead of the more conventional import section at the top of the file. We rely on this the most in the `AgentCheck` base class.\n\n## Troubleshooting\n\nNeed help? Contact [Datadog support][8].\n\n[1]: https://img.shields.io/pypi/v/datadog-checks-base.svg\n[2]: https://img.shields.io/pypi/pyversions/datadog-checks-base.svg\n[4]: https://github.com/DataDog/datadog-agent\n[5]: https://datadoghq.dev/integrations-core/base/about/\n[6]: https://github.com/DataDog/integrations-core\n[7]: https://pypi.org/project/datadog-checks-base/\n[8]: https://docs.datadoghq.com/help/\n[9]: https://github.com/scientific-python/lazy-loader\n",
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