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Enterprise feature


Please see the File API Reference for more details.

It is often necessary to make use of non-code assets such as datasets, models, or files when generating reports. In many situations, deploying these alongside your script is not ideal.

  1. If they are deployed on a different cadence to your script; for instance, you want to make use of a model which is trained on a daily cadence, even though the code of your script remains static.
  2. If they are deployed from a different environment than your script; for instance, you may train a model on Sagemaker and want to use it in your script.
  3. If they are large, and re-uploading them each time you deploy your script is cumbersome.

For these use-cases, Datapane provides a File API which allows you to upload files from any Python or CLI environment, and access them inside your scripts or through the CLI. See the Python API Docs for more information on using Files.



Upload a file and return an id and a url which you can use to retrieve the file.

datapane file upload <name> <filename> [--project project-name]


Download a file and save it on your local machine.

datapane file download <name> <filename> [--project project-name]


upload_df, upload_file, upload_obj


All upload methods take the object to upload as the first parameter. Depending on the method, this can be a file path, DataFrame, or a Python object.

All methods have the additional parameters:

Parameter Description Required
name The value of your variable True
import datapane as dp

# Upload a DataFrame
f = dp.File.upload_df(df, name='my_df')

# Upload a file
f = dp.File.upload_file("~/my_dataset.csv", name='my_ds')

# Upload an object
f = dp.File.upload_obj([1,2,3], name='my_list')

download_df, download_file, download_obj

Download a DataFrame, file, or object. All download operations have the following parameters:

Parameter Description Required
name The name of your file True
project The project to upload the file to. False


If you want other people inside your organization to run your apps which access a file which you created, you must specify yourself as the owner in this method. When someone runs your app, it runs under their name, and if you do not set an explicitly specify the owner , it will try and look for the file under their name and fail.

dp.File.get(name='foo', owner='john')
import datapane as dp

# Download a DataFrame
file = dp.File.get(name="file_id")

# Download a DataFrame
f = file.download_df()

# Download a file
f = file.download_file("~/my_dataset.csv")

# Download an object
f = file.download_obj()

If your teammates within your private workspace want to access your file, they need to specifying the name of the file and project name(provided they are a member of that project) in project

file = dp.File.get(name='myfile', owner='john')

# Retrieve file
f = file.download_df() # Or download_file(), download_obj()

Now others can use your file for their code!