Great Expectations 数据验证管道

使用 Great Expectations Python 库验证数据质量。将期望定义为数据的单元测试，运行验证套件，并生成人类可读的数据质量报告。

Great Expectations 数据验证管道

Validate data quality using the Great Expectations Python library. Define expectations as unit tests for your data, run validation suites, and generate human-readable data quality reports.

Installation

Use the upstream install or setup path that matches your environment:

pip install great_expectations

Requirements and caveats from upstream:

GX Core supports Python 3.10 through 3.13.
Experimental support for Python 3.14 and later can be enabled by setting a GX_PYTHON_EXPERIMENTAL environment variable when installing great_expectations.

Basic usage or getting-started notes:

GX recommends deploying GX Core within a virtual environment. For more information about getting started with GX Core, see Introduction to GX Core.
Run the following command to import the great_expectations module and create a Data Context:
Source: https://github.com/1991513ccie-png/skills
Extracted from upstream docs: https://raw.githubusercontent.com/great-expectations/great_expectations/HEAD/README.md