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# tensorflowjs: The Python Package for TensorFlow.js

The tensorflowjs pip package contains libraries and tools for [TensorFlow.js](

Use following command to install the library with support of interactive CLI: `bash pip install tensorflowjs[wizard] `

Then, run the following to see a list of CLI options

`bash tensorflowjs_converter --help `

or, use the wizard

`bash tensorflowjs_wizard `

Alternatively, run the converter via its Bazel target. This must be run from withing the tfjs repo:

`bash yarn bazel run //tfjs-converter/python/tensorflowjs/converters:converter -- --help `

## Development

The python tests are run with Bazel.

`bash yarn bazel test //tfjs-converter/python/... `

Alternatively, run yarn run-python-tests to run the above command.

To debug a specific test case, use the –test_filter option. For example,

`bash yarn bazel test //tfjs-converter/python/tensorflowjs/converters:tf_saved_model_conversion_v2_test --test_filter=ConvertTest.test_convert_saved_model_v1 `

Interactive debugging with breakpoints is supported by debugpy in VSCode. To enable debugging, put this code at the top of the test file you want to debug.

`python import debugpy debugpy.listen(('localhost', 5724)) print("Waiting for debugger to connect. See tfjs-converter python README") debugpy.wait_for_client() `

You may also need to add the following dependency to the test target in the Bazel BUILD file if it’s not already present. `starlark "//tfjs-converter/python/tensorflowjs:expect_debugpy_installed" `

Then, run the test with bazel run –config=debugpy and connect the VSCode debugger by selecting the Python: Attach (Converter) option.

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