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Getting Started

1. Explore the Frontend​

Browse available data at the production data platform.

2. Install the Python Client​

pixi add vxp_client

3. Configure Credentials​

Create the ~/.virdx.config file with the following contents:

API_URL=http://192.168.10.101:2800/
S3_ACCESS_KEY=<your access key>
S3_SECRET_KEY=<your secret key>

Use the same S3 keys as your ClearML/MinIO setup.

4. Connect​

from vxp_client import PlatformClient

client = PlatformClient()

This logs a successful connection and shows where credentials were loaded from. Connection configuration and credentials are attempted to be loaded from the following sources in order:

  1. Passed explicitly to PlatformClient (e.g. PlatformClient("http://demo.data.virdx.dev/api"))
  2. Passed as environment variables (API_URL=...)
  3. Stored in ~/.virdx.config.

5. Load Data​

The easiest way to start exploring data stored on the data platform is by pulling all dataframes at once and analyzing them with the typical polars dataframe workflows:

dfs = client.get_all_dataframes()  # this may take a few moments

patients = dfs["Patient"]
volumes = dfs["Volume"]

These are Polars DataFrames. Blob data (MRIs, etc.) appears as S3 paths — see accessing data for how to download files.

Next Steps​