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tensorflow/tfx

TFX is an end-to-end platform for deploying production ML pipelines

Python

2,191

4,911 commits

updated Oct 7, 2026

tensorflow.github.io/tfx

See the code

README

TFX

Python PyPI TensorFlow

TensorFlow Extended (TFX) is a Google-production-scale machine learning platform based on TensorFlow. It provides a configuration framework to express ML pipelines consisting of TFX components. TFX pipelines can be orchestrated using Apache Airflow and Kubeflow Pipelines. Both the components themselves as well as the integrations with orchestration systems can be extended.

TFX components interact with a ML Metadata backend that keeps a record of component runs, input and output artifacts, and runtime configuration. This metadata backend enables advanced functionality like experiment tracking or warmstarting/resuming ML models from previous runs.

TFX Components

Documentation

User Documentation

Please see the TFX User Guide.

Development References

Roadmap

The TFX Roadmap, which is updated quarterly.

Release Details

For detailed previous and upcoming changes, please check here

Requests For Comment

TFX is an open-source project and we strongly encourage active participation by the ML community in helping to shape TFX to meet or exceed their needs. An important component of that effort is the RFC process. Please see the listing of current and past TFX RFCs. Please see the TensorFlow Request for Comments (TF-RFC) process page for information on how community members can contribute.

Examples

Compatible versions

The following table describes how the tfx package versions are compatible with its major dependency PyPI packages. This is determined by our testing framework, but other untested combinations may also work.

tfxPythonapache-beam[gcp]ml-metadatapyarrowtensorflowtensorflow-data-validationtensorflow-metadatatensorflow-model-analysistensorflow-serving-apitensorflow-transformtfx-bsl
GitHub master>=3.10,<3.132.73.01.21.018.1.0nightly (2.x)1.21.01.21.00.52.02.19.11.21.01.21.0
1.21.0>=3.10,<3.132.73.01.21.018.1.02.211.21.01.21.00.52.02.19.11.21.01.21.0
1.17.2>=3.9,<3.112.59.01.17.110.0.12.171.17.01.17.10.48.02.17.11.17.01.17.1
1.17.1>=3.9,<3.112.59.01.17.110.0.12.171.17.01.17.10.48.02.17.11.17.01.17.1
1.17.0>=3.9,<3.112.59.01.17.110.0.12.171.17.01.17.10.48.02.17.11.17.01.17.1
1.16.0>=3.9,<3.112.59.01.16.010.0.12.161.16.11.16.10.47.02.16.11.16.01.16.1
1.15.0>=3.9,<3.112.47.01.15.010.0.02.151.15.11.15.00.46.02.15.11.15.01.15.1
1.14.0>=3.8,<3.112.47.01.14.010.0.02.131.14.01.14.00.45.02.9.01.14.01.14.0
1.13.0>=3.8,<3.102.40.01.13.16.0.02.121.13.01.13.10.44.02.9.01.13.01.13.0
1.12.0>=3.7,<3.102.40.01.12.06.0.02.111.12.01.12.00.43.02.9.01.12.01.12.0
1.11.0>=3.7,<3.102.40.01.11.06.0.01.15.5 / 2.10.01.11.01.11.00.42.02.9.01.11.01.11.0
1.10.0>=3.7,<3.102.40.01.10.06.0.01.15.5 / 2.9.01.10.01.10.00.41.02.9.01.10.01.10.0
1.9.0>=3.7,<3.102.38.01.9.05.0.01.15.5 / 2.9.01.9.01.9.00.40.02.9.01.9.01.9.0
1.8.0>=3.7,<3.102.38.01.8.05.0.01.15.5 / 2.8.01.8.01.8.00.39.02.8.01.8.01.8.0
1.7.0>=3.7,<3.92.36.01.7.05.0.01.15.5 / 2.8.01.7.01.7.00.38.02.8.01.7.01.7.0
1.6.2>=3.7,<3.92.35.01.6.05.0.01.15.5 / 2.8.01.6.01.6.00.37.02.7.01.6.01.6.0
1.6.0>=3.7,<3.92.35.01.6.05.0.01.15.5 / 2.7.01.6.01.6.00.37.02.7.01.6.01.6.0
1.5.0>=3.7,<3.92.34.01.5.05.0.01.15.2 / 2.7.01.5.01.5.00.36.02.7.01.5.01.5.0
1.4.0>=3.7,<3.92.33.01.4.05.0.01.15.0 / 2.6.01.4.01.4.00.35.02.6.01.4.01.4.0
1.3.4>=3.6,<3.92.32.01.3.02.0.01.15.0 / 2.6.01.3.01.2.00.34.12.6.01.3.01.3.0
1.3.3>=3.6,<3.92.32.01.3.02.0.01.15.0 / 2.6.01.3.01.2.00.34.12.6.01.3.01.3.0
1.3.2>=3.6,<3.92.32.01.3.02.0.01.15.0 / 2.6.01.3.01.2.00.34.12.6.01.3.01.3.0
1.3.1>=3.6,<3.92.32.01.3.02.0.01.15.0 / 2.6.01.3.01.2.00.34.12.6.01.3.01.3.0
1.3.0>=3.6,<3.92.32.01.3.02.0.01.15.0 / 2.6.01.3.01.2.00.34.12.6.01.3.01.3.0
1.2.1>=3.6,<3.92.31.01.2.02.0.01.15.0 / 2.5.01.2.01.2.00.33.02.5.11.2.01.2.0
1.2.0>=3.6,<3.92.31.01.2.02.0.01.15.0 / 2.5.01.2.01.2.00.33.02.5.11.2.01.2.0
1.0.0>=3.6,<3.92.29.01.0.02.0.01.15.0 / 2.5.01.0.01.0.00.31.02.5.11.0.01.0.0
0.30.0>=3.6,<3.92.28.00.30.02.0.01.15.0 / 2.4.00.30.00.30.00.30.02.4.00.30.00.30.0
0.29.0>=3.6,<3.92.28.00.29.02.0.01.15.0 / 2.4.00.29.00.29.00.29.02.4.00.29.00.29.0
0.28.0>=3.6,<3.92.28.00.28.02.0.01.15.0 / 2.4.00.28.00.28.00.28.02.4.00.28.00.28.1
0.27.0>=3.6,<3.92.27.00.27.02.0.01.15.0 / 2.4.00.27.00.27.00.27.02.4.00.27.00.27.0
0.26.4>=3.6,<3.92.28.00.26.00.17.01.15.0 / 2.3.00.26.10.26.00.26.02.3.00.26.00.26.0
0.26.3>=3.6,<3.92.25.00.26.00.17.01.15.0 / 2.3.00.26.00.26.00.26.02.3.00.26.00.26.0
0.26.1>=3.6,<3.92.25.00.26.00.17.01.15.0 / 2.3.00.26.00.26.00.26.02.3.00.26.00.26.0
0.26.0>=3.6,<3.92.25.00.26.00.17.01.15.0 / 2.3.00.26.00.26.00.26.02.3.00.26.00.26.0
0.25.0>=3.6,<3.92.25.00.24.00.17.01.15.0 / 2.3.00.25.00.25.00.25.02.3.00.25.00.25.0
0.24.1>=3.6,<3.92.24.00.24.00.17.01.15.0 / 2.3.00.24.10.24.00.24.32.3.00.24.10.24.1
0.24.0>=3.6,<3.92.24.00.24.00.17.01.15.0 / 2.3.00.24.10.24.00.24.32.3.00.24.10.24.1
0.23.1>=3.5,<42.24.00.23.00.17.01.15.0 / 2.3.00.23.10.23.00.23.02.3.00.23.00.23.0
0.23.0>=3.5,<42.23.00.23.00.17.01.15.0 / 2.3.00.23.00.23.00.23.02.3.00.23.00.23.0
0.22.2>=3.5,<42.21.00.22.10.16.01.15.0 / 2.2.00.22.20.22.20.22.22.2.00.22.00.22.1
0.22.1>=3.5,<42.21.00.22.10.16.01.15.0 / 2.2.00.22.20.22.20.22.22.2.00.22.00.22.1
0.22.0>=3.5,<42.21.00.22.00.16.01.15.0 / 2.2.00.22.00.22.00.22.12.2.00.22.00.22.0
0.21.5>=2.7,<3 or >=3.5,<42.17.00.21.20.15.01.15.0 / 2.1.00.21.50.21.10.21.52.1.00.21.20.21.4
0.21.4>=2.7,<3 or >=3.5,<42.17.00.21.20.15.01.15.0 / 2.1.00.21.50.21.10.21.52.1.00.21.20.21.4
0.21.3>=2.7,<3 or >=3.5,<42.17.00.21.20.15.01.15.0 / 2.1.00.21.50.21.10.21.52.1.00.21.20.21.4
0.21.2>=2.7,<3 or >=3.5,<42.17.00.21.20.15.01.15.0 / 2.1.00.21.50.21.10.21.52.1.00.21.20.21.4
0.21.1>=2.7,<3 or >=3.5,<42.17.00.21.20.15.01.15.0 / 2.1.00.21.40.21.10.21.42.1.00.21.20.21.3
0.21.0>=2.7,<3 or >=3.5,<42.17.00.21.00.15.01.15.0 / 2.1.00.21.00.21.00.21.12.1.00.21.00.21.0
0.15.0>=2.7,<3 or >=3.5,<42.16.00.15.00.15.01.15.00.15.00.15.00.15.21.15.00.15.00.15.1
0.14.0>=2.7,<3 or >=3.5,<42.14.00.14.00.14.01.14.00.14.10.14.00.14.01.14.00.14.0n/a
0.13.0>=2.7,<3 or >=3.5,<42.12.00.13.2n/a1.13.10.13.10.13.00.13.21.13.00.13.0n/a
0.12.0>=2.7,<32.10.00.13.2n/a1.12.00.12.00.12.10.12.11.12.00.12.0n/a

Resources

apache-beam
machine-learning
tensorflow

Project health

Overall

6.8/10

Maintained

9/10

Code review

10/10
OpenSSF Scorecard

PyPI

tfx

Latest release

1.21.0 · Jun 18, 2026

Releases this year

4

Significant stargazers

Albert Villanova del Moral

644 followers · starred Oct 2020

Stefan He

154 followers · starred Dec 2023

Dylan Cutler

248 followers · starred Aug 2021

Quanjie Lin

20 followers · starred Aug 2019

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tensorflow/tfx

TFX is an end-to-end platform for deploying production ML pipelines

Python

2,191

4,911 commits

updated Oct 7, 2026

tensorflow.github.io/tfx

See the code

README

TFX

Python PyPI TensorFlow

TensorFlow Extended (TFX) is a Google-production-scale machine learning platform based on TensorFlow. It provides a configuration framework to express ML pipelines consisting of TFX components. TFX pipelines can be orchestrated using Apache Airflow and Kubeflow Pipelines. Both the components themselves as well as the integrations with orchestration systems can be extended.

TFX components interact with a ML Metadata backend that keeps a record of component runs, input and output artifacts, and runtime configuration. This metadata backend enables advanced functionality like experiment tracking or warmstarting/resuming ML models from previous runs.

TFX Components

Documentation

User Documentation

Please see the TFX User Guide.

Development References

Roadmap

The TFX Roadmap, which is updated quarterly.

Release Details

For detailed previous and upcoming changes, please check here

Requests For Comment

TFX is an open-source project and we strongly encourage active participation by the ML community in helping to shape TFX to meet or exceed their needs. An important component of that effort is the RFC process. Please see the listing of current and past TFX RFCs. Please see the TensorFlow Request for Comments (TF-RFC) process page for information on how community members can contribute.

Examples

Compatible versions

The following table describes how the tfx package versions are compatible with its major dependency PyPI packages. This is determined by our testing framework, but other untested combinations may also work.

tfxPythonapache-beam[gcp]ml-metadatapyarrowtensorflowtensorflow-data-validationtensorflow-metadatatensorflow-model-analysistensorflow-serving-apitensorflow-transformtfx-bsl
GitHub master>=3.10,<3.132.73.01.21.018.1.0nightly (2.x)1.21.01.21.00.52.02.19.11.21.01.21.0
1.21.0>=3.10,<3.132.73.01.21.018.1.02.211.21.01.21.00.52.02.19.11.21.01.21.0
1.17.2>=3.9,<3.112.59.01.17.110.0.12.171.17.01.17.10.48.02.17.11.17.01.17.1
1.17.1>=3.9,<3.112.59.01.17.110.0.12.171.17.01.17.10.48.02.17.11.17.01.17.1
1.17.0>=3.9,<3.112.59.01.17.110.0.12.171.17.01.17.10.48.02.17.11.17.01.17.1
1.16.0>=3.9,<3.112.59.01.16.010.0.12.161.16.11.16.10.47.02.16.11.16.01.16.1
1.15.0>=3.9,<3.112.47.01.15.010.0.02.151.15.11.15.00.46.02.15.11.15.01.15.1
1.14.0>=3.8,<3.112.47.01.14.010.0.02.131.14.01.14.00.45.02.9.01.14.01.14.0
1.13.0>=3.8,<3.102.40.01.13.16.0.02.121.13.01.13.10.44.02.9.01.13.01.13.0
1.12.0>=3.7,<3.102.40.01.12.06.0.02.111.12.01.12.00.43.02.9.01.12.01.12.0
1.11.0>=3.7,<3.102.40.01.11.06.0.01.15.5 / 2.10.01.11.01.11.00.42.02.9.01.11.01.11.0
1.10.0>=3.7,<3.102.40.01.10.06.0.01.15.5 / 2.9.01.10.01.10.00.41.02.9.01.10.01.10.0
1.9.0>=3.7,<3.102.38.01.9.05.0.01.15.5 / 2.9.01.9.01.9.00.40.02.9.01.9.01.9.0
1.8.0>=3.7,<3.102.38.01.8.05.0.01.15.5 / 2.8.01.8.01.8.00.39.02.8.01.8.01.8.0
1.7.0>=3.7,<3.92.36.01.7.05.0.01.15.5 / 2.8.01.7.01.7.00.38.02.8.01.7.01.7.0
1.6.2>=3.7,<3.92.35.01.6.05.0.01.15.5 / 2.8.01.6.01.6.00.37.02.7.01.6.01.6.0
1.6.0>=3.7,<3.92.35.01.6.05.0.01.15.5 / 2.7.01.6.01.6.00.37.02.7.01.6.01.6.0
1.5.0>=3.7,<3.92.34.01.5.05.0.01.15.2 / 2.7.01.5.01.5.00.36.02.7.01.5.01.5.0
1.4.0>=3.7,<3.92.33.01.4.05.0.01.15.0 / 2.6.01.4.01.4.00.35.02.6.01.4.01.4.0
1.3.4>=3.6,<3.92.32.01.3.02.0.01.15.0 / 2.6.01.3.01.2.00.34.12.6.01.3.01.3.0
1.3.3>=3.6,<3.92.32.01.3.02.0.01.15.0 / 2.6.01.3.01.2.00.34.12.6.01.3.01.3.0
1.3.2>=3.6,<3.92.32.01.3.02.0.01.15.0 / 2.6.01.3.01.2.00.34.12.6.01.3.01.3.0
1.3.1>=3.6,<3.92.32.01.3.02.0.01.15.0 / 2.6.01.3.01.2.00.34.12.6.01.3.01.3.0
1.3.0>=3.6,<3.92.32.01.3.02.0.01.15.0 / 2.6.01.3.01.2.00.34.12.6.01.3.01.3.0
1.2.1>=3.6,<3.92.31.01.2.02.0.01.15.0 / 2.5.01.2.01.2.00.33.02.5.11.2.01.2.0
1.2.0>=3.6,<3.92.31.01.2.02.0.01.15.0 / 2.5.01.2.01.2.00.33.02.5.11.2.01.2.0
1.0.0>=3.6,<3.92.29.01.0.02.0.01.15.0 / 2.5.01.0.01.0.00.31.02.5.11.0.01.0.0
0.30.0>=3.6,<3.92.28.00.30.02.0.01.15.0 / 2.4.00.30.00.30.00.30.02.4.00.30.00.30.0
0.29.0>=3.6,<3.92.28.00.29.02.0.01.15.0 / 2.4.00.29.00.29.00.29.02.4.00.29.00.29.0
0.28.0>=3.6,<3.92.28.00.28.02.0.01.15.0 / 2.4.00.28.00.28.00.28.02.4.00.28.00.28.1
0.27.0>=3.6,<3.92.27.00.27.02.0.01.15.0 / 2.4.00.27.00.27.00.27.02.4.00.27.00.27.0
0.26.4>=3.6,<3.92.28.00.26.00.17.01.15.0 / 2.3.00.26.10.26.00.26.02.3.00.26.00.26.0
0.26.3>=3.6,<3.92.25.00.26.00.17.01.15.0 / 2.3.00.26.00.26.00.26.02.3.00.26.00.26.0
0.26.1>=3.6,<3.92.25.00.26.00.17.01.15.0 / 2.3.00.26.00.26.00.26.02.3.00.26.00.26.0
0.26.0>=3.6,<3.92.25.00.26.00.17.01.15.0 / 2.3.00.26.00.26.00.26.02.3.00.26.00.26.0
0.25.0>=3.6,<3.92.25.00.24.00.17.01.15.0 / 2.3.00.25.00.25.00.25.02.3.00.25.00.25.0
0.24.1>=3.6,<3.92.24.00.24.00.17.01.15.0 / 2.3.00.24.10.24.00.24.32.3.00.24.10.24.1
0.24.0>=3.6,<3.92.24.00.24.00.17.01.15.0 / 2.3.00.24.10.24.00.24.32.3.00.24.10.24.1
0.23.1>=3.5,<42.24.00.23.00.17.01.15.0 / 2.3.00.23.10.23.00.23.02.3.00.23.00.23.0
0.23.0>=3.5,<42.23.00.23.00.17.01.15.0 / 2.3.00.23.00.23.00.23.02.3.00.23.00.23.0
0.22.2>=3.5,<42.21.00.22.10.16.01.15.0 / 2.2.00.22.20.22.20.22.22.2.00.22.00.22.1
0.22.1>=3.5,<42.21.00.22.10.16.01.15.0 / 2.2.00.22.20.22.20.22.22.2.00.22.00.22.1
0.22.0>=3.5,<42.21.00.22.00.16.01.15.0 / 2.2.00.22.00.22.00.22.12.2.00.22.00.22.0
0.21.5>=2.7,<3 or >=3.5,<42.17.00.21.20.15.01.15.0 / 2.1.00.21.50.21.10.21.52.1.00.21.20.21.4
0.21.4>=2.7,<3 or >=3.5,<42.17.00.21.20.15.01.15.0 / 2.1.00.21.50.21.10.21.52.1.00.21.20.21.4
0.21.3>=2.7,<3 or >=3.5,<42.17.00.21.20.15.01.15.0 / 2.1.00.21.50.21.10.21.52.1.00.21.20.21.4
0.21.2>=2.7,<3 or >=3.5,<42.17.00.21.20.15.01.15.0 / 2.1.00.21.50.21.10.21.52.1.00.21.20.21.4
0.21.1>=2.7,<3 or >=3.5,<42.17.00.21.20.15.01.15.0 / 2.1.00.21.40.21.10.21.42.1.00.21.20.21.3
0.21.0>=2.7,<3 or >=3.5,<42.17.00.21.00.15.01.15.0 / 2.1.00.21.00.21.00.21.12.1.00.21.00.21.0
0.15.0>=2.7,<3 or >=3.5,<42.16.00.15.00.15.01.15.00.15.00.15.00.15.21.15.00.15.00.15.1
0.14.0>=2.7,<3 or >=3.5,<42.14.00.14.00.14.01.14.00.14.10.14.00.14.01.14.00.14.0n/a
0.13.0>=2.7,<3 or >=3.5,<42.12.00.13.2n/a1.13.10.13.10.13.00.13.21.13.00.13.0n/a
0.12.0>=2.7,<32.10.00.13.2n/a1.12.00.12.00.12.10.12.11.12.00.12.0n/a

Resources

apache-beam
machine-learning
tensorflow

Project health

Overall

6.8/10

Maintained

9/10

Code review

10/10
OpenSSF Scorecard

PyPI

tfx

Latest release

1.21.0 · Jun 18, 2026

Releases this year

4

Significant stargazers

Albert Villanova del Moral

644 followers · starred Oct 2020

Stefan He

154 followers · starred Dec 2023

Dylan Cutler

248 followers · starred Aug 2021

Quanjie Lin

20 followers · starred Aug 2019

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