examples/dlt/README.md

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# dlt

This example shows dlt + Apache Hamilton can help you cover the full ELT cycle using portable Python code. It is a companion to this [documentation page](https://hamilton.apache.org/integrations/dlt/).

# Content
It includes a pipeline to ingest messages from Slack channels and generate threads summaries.

- `slack/` is the code imported from dlt for the Slack `Source`
- `.dlt/` contains the source's version, config, and secrets for the dlt `Pipeline`
- `transform.py` contains the Apache Hamilton code to transform data and build the `threads` table
- `run.py` contains the code to execution the dlt `Pipeline` and the Apache Hamilton dataflow.
- `notebook.ipynb` contains the equivalent of both `transform.py` and `run.py` allowing you to explore the code interactively.

# Set up
1. Create a virtual environment and activate it
    ```console
    python -m venv venv && . venv/bin/active
    ```

2. Install requirements
    ```console
    pip install -r requirements.txt
    ```
3. Follow this dlt [guide to ingest Slack data](https://dlthub.com/docs/dlt-ecosystem/verified-sources/slack). Make sure to invite your Slack app to your channel!

4. Execute the code. Use `--help` to learn about accepted arguments.
    ```console
    python run.py --help
    python run.py general dlt
    ```

# References
- dlt to ingest [Slack data](https://dlthub.com/docs/dlt-ecosystem/verified-sources/slack)
- Reconstructing Slack threads [docs](https://api.slack.com/messaging/retrieving#finding_threads)