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westrheim merged 2 commits into from
Apr 10, 2025
Merged

Feature/remove secrets from readme #31

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remove secrets from readme
westrheim Apr 10, 2025
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minor changes to readme
westrheim Apr 10, 2025
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24 changes: 1 addition & 23 deletions README.md
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Expand Up @@ -15,7 +15,7 @@
# DataWorkbench

## What is it?
Veracity DataWorkbench is a Python SDK designed to bridge your Python environment with Veracity DataWorkbench services. It simplifies access to data cataloging, lineage tracking, and APIs — supporting efficient data workflows across local and cloud environments such as Databricks
Veracity DataWorkbench is a Python SDK designed to bridge your Databricks environment with Veracity Data Workbench. It simplifies access to data cataloging, lineage tracking, and APIs.


## Table of Contents
Expand Down Expand Up @@ -62,28 +62,6 @@ datacatalogue = DataCatalogue() # Naming subject to change
datacatalogue.save(df, "Dataset Name", "Description", tags={"environment": ["test"]})
```

## Configuration

When using Dataworkbench locally, you need to configure the following environment variables:

```python
# Required for local machine setup
import os

os.environ["ApimClientId"] = "your-apim-client-id"
os.environ["ApimClientSecret"] = "your-apim-client-secret"
os.environ["ApimScope"] = "your-apim-scope"
```

Alternatively, create a `.env` file or use a configuration file:

```
# .env file example
ApimClientId=your-apim-client-id
ApimClientSecret=your-apim-client-secret
ApimScope=your-apim-scope
```

## Examples

### Saving a Spark DataFrame to the Data Catalogue
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