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I am trying to run an mlflow server locally.

To do so, I am using:

mlflow server --backend-store-uri="sqlite:///C:\\path\\to\\project_folder\\backend\\mlflow_data.db" 
              --default-artifact-root="file:///C:\\path\\to\\project_folder\\artifact_store\\"

Where 

- backend-store-uri: URI to which to persist experiment and run data (sqlite database in our case).
- default-artifact-root: Local or S3 URI to store artifacts, for new experiments (local folder in our case).

I have already install the packages: 

numpy==1.17.3
pandas==0.25.3
jupyterlab==1.0.10 
scikit-learn==0.21.3
matplotlib==3.1.2
mlflow==1.4.0
torch==1.3.1+cpu 
torchvision==0.4.2+cpu 
xgboost==0.90

The problem is that I am getting this error: 

Fatal error in launcher: Unable to create process using "d:\bld\mlflow_1572494804636\_h_env\python.exe" "C:\Users\user\AppData\Local\Continuum\miniconda3\envs\mlflow-tut orial\Scripts\mlflow.exe" server --backend-store-uri=sqlite:///C:\\projects\\user\\mlflow_tutorial\\backend\\mlflow_ui_data.db --default-artifact-root=file:///C:\\projects \\user\\mlflow_tutorial\\artifact_store\\

When I run the mlflow server command. Any ideas ?

quant
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  • you should include username, password, ip address in your backend-store-uri, here is an example. https://docs.sqlalchemy.org/en/13/core/engines.html#database-urls – Kevin Su Dec 30 '19 at 09:00

1 Answers1

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It seems that there is a space in the path: enter image description here

Boris Modylevsky
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