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* update dependencies * cleanup spaces
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# Conda environment specification. The dependencies defined in this file will | ||
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# be automatically provisioned for managed runs. These include runs against | ||
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# the localdocker, remotedocker, and cluster compute targets. | ||
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# Note that this file is NOT used to automatically manage dependencies for the | ||
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# local compute target. To provision these dependencies locally, run: | ||
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# conda env update --file conda_dependencies.yml | ||
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# Details about the Conda environment file format: | ||
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# https://conda.io/docs/using/envs.html#create-environment-file-by-hand | ||
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# For managing Spark packages and configuration, see spark_dependencies.yml. | ||
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# Version of this configuration file's structure and semantics in AzureML. | ||
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# This directive is stored in a comment to preserve the Conda file structure. | ||
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# [AzureMlVersion] = 2 | ||
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name: project_environment | ||
dependencies: | ||
# The python interpreter version. | ||
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# Currently Azure ML Workbench only supports 3.5.2 and later. | ||
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- python=3.6.2 | ||
- python=3.7.5 | ||
# Required by azureml-defaults, installed separately through Conda to | ||
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# get a prebuilt version and not require build tools for the install. | ||
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- psutil=5.3 | ||
- psutil=5.6 #latest | ||
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- pip: | ||
# Required packages for AzureML execution, history, and data preparation. | ||
- azureml-sdk[notebooks] # add the version to lock it ==0.1.74 | ||
- scipy==1.0.0 | ||
- azureml-sdk==1.0.72 | ||
- scipy==1.3.1 | ||
- scikit-learn==0.21.3 | ||
- pandas==0.23.1 | ||
- numpy==1.14.5 | ||
- joblib==0.13.2 | ||
- gunicorn==19.9.0 | ||
- pandas==0.25.3 | ||
- numpy==1.17.3 | ||
- joblib==0.14.0 | ||
- gunicorn==19.9.0 | ||
- flask==1.1.1 | ||
- azure-ml-api-sdk | ||
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