[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"project-70781":3},{"id":4,"name":5,"fullName":6,"owner":7,"repo":5,"description":8,"homepage":9,"htmlUrl":10,"language":11,"languages":10,"totalLinesOfCode":10,"stars":12,"forks":13,"watchers":14,"openIssues":15,"contributorsCount":16,"subscribersCount":16,"size":16,"stars1d":17,"stars7d":18,"stars30d":19,"stars90d":16,"forks30d":16,"starsTrendScore":20,"compositeScore":21,"rankGlobal":10,"rankLanguage":10,"license":22,"archived":23,"fork":23,"defaultBranch":24,"hasWiki":25,"hasPages":23,"topics":26,"createdAt":10,"pushedAt":10,"updatedAt":47,"readmeContent":48,"aiSummary":49,"trendingCount":16,"starSnapshotCount":16,"syncStatus":50,"lastSyncTime":51,"discoverSource":52},70781,"great_expectations","great-expectations\u002Fgreat_expectations","great-expectations","Always know what to expect from your data.","https:\u002F\u002Fdocs.greatexpectations.io\u002F",null,"Python",11549,1757,101,25,0,4,19,61,12,93.34,"Apache License 2.0",false,"develop",true,[27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46],"cleandata","data-engineering","data-profilers","data-profiling","data-quality","data-science","data-unit-tests","datacleaner","datacleaning","dataquality","dataunittest","eda","exploratory-analysis","exploratory-data-analysis","exploratorydataanalysis","mlops","pipeline","pipeline-debt","pipeline-testing","pipeline-tests","2026-06-12 04:00:57","[![Python Versions](https:\u002F\u002Fimg.shields.io\u002Fpypi\u002Fpyversions\u002Fgreat_expectations.svg)](https:\u002F\u002Fpypi.python.org\u002Fpypi\u002Fgreat_expectations)\n[![PyPI](https:\u002F\u002Fimg.shields.io\u002Fpypi\u002Fv\u002Fgreat_expectations)](https:\u002F\u002Fpypi.org\u002Fproject\u002Fgreat-expectations\u002F#history)\n[![PyPI Downloads](https:\u002F\u002Fimg.shields.io\u002Fpypi\u002Fdm\u002Fgreat-expectations)](https:\u002F\u002Fpypistats.org\u002Fpackages\u002Fgreat-expectations)\n[![Build Status](https:\u002F\u002Fimg.shields.io\u002Fazure-devops\u002Fbuild\u002Fgreat-expectations\u002Fbedaf2c2-4c4a-4b37-87b0-3877190e71f5\u002F1)](https:\u002F\u002Fdev.azure.com\u002Fgreat-expectations\u002Fgreat_expectations\u002F_build\u002Flatest?definitionId=1&branchName=develop)\n[![pre-commit.ci Status](https:\u002F\u002Fresults.pre-commit.ci\u002Fbadge\u002Fgithub\u002Fgreat-expectations\u002Fgreat_expectations\u002Fdevelop.svg)](https:\u002F\u002Fresults.pre-commit.ci\u002Flatest\u002Fgithub\u002Fgreat-expectations\u002Fgreat_expectations\u002Fdevelop)\n[![codecov](https:\u002F\u002Fcodecov.io\u002Fgh\u002Fgreat-expectations\u002Fgreat_expectations\u002Fgraph\u002Fbadge.svg?token=rbHxgTxYTs)](https:\u002F\u002Fcodecov.io\u002Fgh\u002Fgreat-expectations\u002Fgreat_expectations)\n[![DOI](https:\u002F\u002Fzenodo.org\u002Fbadge\u002FDOI\u002F10.5281\u002Fzenodo.5683574.svg)](https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.5683574)\n[![Twitter Follow](https:\u002F\u002Fimg.shields.io\u002Ftwitter\u002Ffollow\u002Fexpectgreatdata?style=social)](https:\u002F\u002Ftwitter.com\u002Fexpectgreatdata)\n[![Slack Status](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002Fslack-join_chat-white.svg?logo=slack&style=social)](https:\u002F\u002Fgreatexpectations.io\u002Fslack)\n[![Contributors](https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Fcontributors\u002Fgreat-expectations\u002Fgreat_expectations)](https:\u002F\u002Fgithub.com\u002Fgreat-expectations\u002Fgreat_expectations\u002Fgraphs\u002Fcontributors)\n[![Ruff](https:\u002F\u002Fimg.shields.io\u002Fendpoint?url=https:\u002F\u002Fraw.githubusercontent.com\u002Fastral-sh\u002Fruff\u002Fmain\u002Fassets\u002Fbadge\u002Fv2.json)](https:\u002F\u002Fgithub.com\u002Fastral-sh\u002Fruff)\n\n\u003C!-- \u003C\u003C\u003CSuper-quickstart links go here>>> -->\n\n\u003Cimg align=\"right\" src=\".\u002Fdocs\u002Fdocusaurus\u002Fstatic\u002Fimg\u002Fgx-mark-160.png\">\n\n## About GX Core\n\nGX Core combines the collective wisdom of thousands of community members with a proven track record in data quality deployments worldwide, wrapped into a super-simple package for data teams.\n\nIts powerful technical tools start with Expectations: expressive and extensible unit tests for your data. Expectations foster collaboration by giving teams a common language to express data quality tests in an intuitive way. You can automatically generate documentation for each set of validation results, making it easy for everyone to stay on the same page. This not only simplifies your data quality processes, but helps preserve your organization’s institutional knowledge about its data.\n\nLearn more about how data teams are using GX Core in our featured [case studies](https:\u002F\u002Fgreatexpectations.io\u002Fcase-studies\u002F).\n\n## Integration support policy\n\nGX Core supports Python `3.10` through `3.13`.\nExperimental support for Python `3.14` and later can be enabled by setting a `GX_PYTHON_EXPERIMENTAL` environment variable when installing `great_expectations`.\n\nFor data sources and other integrations that GX supports, see the [compatibility reference](https:\u002F\u002Fdocs.greatexpectations.io\u002Fdocs\u002Fhelp\u002Fcompatibility_reference) for additional information.\n\n## Get started\n\nGX recommends deploying GX Core within a virtual environment. For more information about getting started with GX Core, see [Introduction to GX Core](https:\u002F\u002Fdocs.greatexpectations.io\u002Fdocs\u002Fcore\u002Fintroduction\u002F).\n\n1. Run the following command in an empty base directory inside a Python virtual environment to install GX Core:\n\n\t```bash title=\"Terminal input\"\n\tpip install great_expectations\n\t```\n2. Run the following command to import the `great_expectations module` and create a Data Context:\n\n\t```python\n\timport great_expectations as gx\n\n\tcontext = gx.get_context()\n\t```\n\n## Get support from GX and the community\n\nThey are listed in the order in which GX is prioritizing the support issues:\n\n1. Issues and PRs in the [GX GitHub repository](https:\u002F\u002Fgithub.com\u002Fgreat-expectations)\n2. Questions posted to the [GX Core Discourse forum](https:\u002F\u002Fdiscourse.greatexpectations.io\u002Fc\u002Foss-support\u002F11)\n3. Questions posted to the [GX Slack community channel](https:\u002F\u002Fgreatexpectationstalk.slack.com\u002Farchives\u002FCUTCNHN82)\n\n## Contribute\nWe truly value the contributions of our community and always welcome pull requests. PRs are encouraged for both bug fixes and new features. For feature requests, we ask that you first open an issue for discussion to ensure the feature fits within the vision for GX Core and to align on the approach so that your time and effort are well spent. Thank you for being a crucial part of GX Core!\n\n## Code of conduct\nEveryone interacting in GX Core project codebases, Discourse forums, Slack channels, and email communications is expected to adhere to the [GX Community Code of Conduct](https:\u002F\u002Fdiscourse.greatexpectations.io\u002Ft\u002Fgx-community-code-of-conduct\u002F1199).\n","Great Expectations 是一个用于数据质量管理和验证的Python库。它通过提供可表达和可扩展的数据单元测试（称为Expectations），使团队能够以直观的方式定义和检查数据质量标准。此外，该工具支持自动生成文档来记录每次验证的结果，有助于保持团队间的信息同步，并促进机构内部对于数据理解的一致性。Great Expectations 适用于需要保证数据质量和一致性的各种场景，比如数据科学项目、ETL管道以及任何涉及大量数据处理的工作流中。",2,"2026-06-11 03:34:10","high_star"]