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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
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dependencies :
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# 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
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+ - python=3.7.5
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# 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
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+ - psutil=5.6 # latest
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- pip :
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# Required packages for AzureML execution, history, and data preparation.
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- - azureml-sdk[notebooks] # add the version to lock it ==0.1.74
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- - scipy==1.0.0
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+ - azureml-sdk==1.0.72
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+ - scipy==1.3.1
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- scikit-learn==0.21.3
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- - pandas==0.23.1
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- - numpy==1.14.5
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- - joblib==0.13.2
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- - gunicorn==19.9.0
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+ - pandas==0.25.3
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+ - numpy==1.17.3
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+ - joblib==0.14.0
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+ - gunicorn==19.9.0
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- flask==1.1.1
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- - azure-ml-api-sdk
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