Should we remove dependencies keras and tensorflow?

[cclauss]

Python/.python-version

Line 1 in ff206e6

3.14t

Next week, that will be upgraded to Python 3.15t.

• CI: try Python 3.15t release candidate (DRAFT — do not merge until 3.15t GA) #15105
• Support python 3.14 tensorflow/tensorflow#102890 Still does not support Python 3.14

tensorflow is used in the following files:

• computer_vision/cnn_classification.py
• dynamic_programming/k_means_clustering_tensorflow.py
• neural_network/input_data.py

keras is used in the following files:

• computer_vision/cnn_classification.py
• machine_learning/lstm/lstm_prediction.py

Many of these files seem to be how-to-use scripts rather than algorithms as defined in CONTRIBUTING.md.

All of these files must be ignored in our pytests so we are blind to bugs in them.

Python/.github/workflows/build.yml

Lines 42 to 53 in ff206e6

	run: uv run --with=pytest-run-parallel pytest
	--iterations=8 --parallel-threads=auto --ignore-gil-enabled
	--ignore=computer_vision/cnn_classification.py
	--ignore=computer_vision/flip_augmentation.py
	--ignore=computer_vision/harris_corner.py
	--ignore=computer_vision/mosaic_augmentation.py
	--ignore=data_compression/peak_signal_to_noise_ratio.py
	--ignore=digital_image_processing/
	--ignore=docs/conf.py
	--ignore=dynamic_programming/k_means_clustering_tensorflow.py
	--ignore=machine_learning/lstm/lstm_prediction.py
	--ignore=neural_network/input_data.py

We should work to reduce the number of Python files that we ignore when we run pytest.

[cclauss]

@priya-sundaram-dev, can you please review these four files? Algorithms or how-to-use scripts? Educational value?

• computer_vision/cnn_classification.py
• dynamic_programming/k_means_clustering_tensorflow.py
• machine_learning/lstm/lstm_prediction.py
• neural_network/input_data.py

[priya-sundaram-dev]

Reviewed all four against CONTRIBUTING.md's "What is an algorithm?" test. My read: none of them are algorithms — remove all four (and the two deps go with them).

• dynamic_programming/k_means_clustering_tensorflow.py — ❌ Remove. Three problems at once: (1) miscategorized — k-means isn't dynamic programming; (2) it's dead code — built on the TF1 graph/session API (tf.Session, tf.placeholder, tf.assign) that was removed in TF2, so it can't run on any supported TF; (3) it duplicates machine_learning/k_means_clust.py, which is a pure-NumPy k-means we already ship. Nothing lost.

• neural_network/input_data.py — ❌ Remove. Not an algorithm at all — it's a verbatim copy of TensorFlow's own MNIST download/reader helper (Apache 2016 header) that TF itself marks @deprecated. Its only consumer in the repo is neural_network/gan.py_tf, which isn't a .py file and is already excluded. Pure dead utility.

• computer_vision/cnn_classification.py — ❌ Remove. A how-to-use script: everything lives under __main__, no functions/doctests, and it needs an external TB X-ray dataset the user must download and hand-split. It mirrors the TF "images/cnn" tutorial — teaches "how to call Keras," not an algorithm.

• machine_learning/lstm/lstm_prediction.py — ❌ Remove. Same shape: all logic in __main__, requires a local sample_data.csv, and just wires up a Keras Sequential. It's a usage demo, not an implementation of anything.

Net: dropping these four removes every tensorflow/keras import, lets us delete all four --ignore lines from build.yml, and unblocks 3.14t/3.15t. I'd suggest also removing the three DIRECTORY.md entries + regenerating. Happy to open the removal PR if you want it.

[cclauss]

@priya-sundaram-dev Yes, please create that pull request and run git grep tensorflow && git grep keras to ensure we remove any stray references. Also, please run uv sync --upgrade && uv lock before committing these changes. Thank you.

[priya-sundaram-dev]

Done — opened #15419. Removed all four files plus the orphaned machine_learning/lstm/ package, dropped keras from pyproject.toml, and ran uv sync --upgrade && uv lock (removes absl-py, h5py, keras, ml-dtypes, namex, optree). Also cleared the libhdf5-dev pre-release step from build.yml/sphinx.yml, the four stale --ignore= lines, and the DIRECTORY.md entries. git grep -i -E 'tensorflow|keras' is now clean apart from the kerasin/kerasine dictionary words in strings/. One note in the PR: neural_network/gan.py_tf still imports input_data, but its .py_tf extension means it's never collected — left it out of scope, easy to handle separately.

[cclauss]

@priya-sundaram-dev please create a pull request that deletes neural_network/gan.py_tf

[priya-sundaram-dev]

Done — opened #15422, a focused PR that deletes only neural_network/gan.py_tf. Happy to follow up with additional single-file deletions (e.g. input_data.py_tf) as separate PRs if you'd prefer to land them incrementally.