Every <p>(This page is automatically generated, please contact Python Engine maintainers to change this page)</p><p>Every version of the Python Engine comes with 3 flavours:
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Image
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Description
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pyfx
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</p><div class="table-wrap"><table data-layout="default" data-local-id="e4b0d83c-beab-48c0-a7ac-86ee2847e05a" class="confluenceTable"><colgroup><col style="width: 380.0px;"/><col style="width: 380.0px;"/></colgroup><tbody><tr><th class="confluenceTh"><p><strong>Image</strong></p></th><th class="confluenceTh"><p><strong>Description</strong></p></th></tr><tr><td class="confluenceTd"><p><code>pyfx</code></p></td><td class="confluenceTd"><p>Minimal image containing only the <code>pyfx</code> Python module and required dependencies.
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datascience
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</p></td></tr><tr><td class="confluenceTd"><p><code>datascience</code></p></td><td class="confluenceTd"><p>Image containing <code>pyfx</code> and common data science Python libraries.
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neural
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</p></td></tr><tr><td class="confluenceTd"><p><code>neural</code></p></td><td class="confluenceTd"><p>Image containing <code>pyfx</code>, common data science libraries and neural network related libraries.
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For </p></td></tr></tbody></table></div><p>For v4, those flavours contains the following libraries (and their dependencies):
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pyfx contains:
python= "3.10."setuptoolsfilelocknumpypandasfastavrorequestsrequests-toolbeltSecretStorage
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</p><ul><li><p><code>pyfx</code> contains:</p><ul><li><p><code>fastavro</code>= 1.7.</p></li><li><p><code>filelock</code>= 3.</p></li><li><p><code>joblib</code>= 1.2.</p></li><li><p><code>numpy</code>= 1.23.</p></li><li><p><code>pandas</code>= 1.5.</p></li><li><p><code>python</code>= 3.10.</p></li><li><p><code>requests</code>= 2.</p></li><li><p><code>requests-toolbelt</code>= 0.10.</p></li><li><p><code>SecretStorage</code>= 3.3.</p></li><li><p><code>setuptools</code>= 65.6.</p></li></ul></li><li><p><code>datascience</code> contains </code>pyfx</code> libraries and dependencies, plus the following:
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dython,eli5,graphviz,igraph,imbalanced-learn,jpmml-evaluator,leidenalg,lightgbm,matplotlib,onnxmltools,onnxruntime,optuna,pynndescent,umap-learn,sacred,scipy,shap,SQLAlchemy,scikit-learn,sklearn-pandas,sklearn2pmml,statsmodels,sympy,xgboost,
neural contains pyfx and datascience libraries and dependencies, plus the following:
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BERTopic,
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darts,
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neuralprophet,
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sentence-transformers,
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tensorflow,
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torch,
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</p><ul><li><p><code>dython</code>= 0.7.</p></li><li><p><code>eli5</code>= 0.13.</p></li><li><p><code>graphviz</code>= 0.20.</p></li><li><p><code>igraph</code>= ^0.10.4</p></li><li><p><code>imbalanced-learn</code>= 0.10.</p></li><li><p><code>jpmml-evaluator</code>= 0.7.</p></li><li><p><code>leidenalg</code>= ^0.9.1</p></li><li><p><code>lightgbm</code>= 3.3.</p></li><li><p><code>matplotlib</code>= 3.6.</p></li><li><p><code>onnxmltools</code>= 1.11.</p></li><li><p><code>onnxruntime</code>= 1.13.</p></li><li><p><code>optuna</code>= 3.1.</p></li><li><p><code>pynndescent</code>= 0.5.</p></li><li><p><code>sacred</code>= 0.8.</p></li><li><p><code>scikit-learn</code>= 1.2.</p></li><li><p><code>scipy</code>= 1.9.</p></li><li><p><code>shap</code>= 0.41.</p></li><li><p><code>sklearn-pandas</code>= 2.2.</p></li><li><p><code>sklearn2pmml</code>= 0.89.</p></li><li><p><code>SQLAlchemy</code>= 1.4.</p></li><li><p><code>statsmodels</code>= 0.13.</p></li><li><p><code>sympy</code>= 1.11.</p></li><li><p><code>umap-learn</code>= ^0.5.3</p></li><li><p><code>xgboost</code>= 1.7.</p></li></ul></li><li><p><code>neural</code> contains <code>pyfx</code> and <code>datascience</code> libraries and dependencies, plus the following:</p><ul><li><p><code>bertopic</code>= ^0.14.1</p></li><li><p><code>darts</code>= 0.23.</p></li><li><p><code>neuralprophet</code>= 0.5.</p></li><li><p><code>sentence-transformers</code>= 2.2.</p></li><li><p><code>tensorflow</code>= ^2.11.1</p></li><li><p><code>torch</code>= 1.13.*</p></li><li><p><code>torchviz</code>= ^0.0.2</p></li></ul></li></ul>