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Debugging Data Pipelines: From Memory to File with WebDAV
- Debugging complex data pipelines often involves tracking short-lived data like Excel buffers and transformed data frames.
- The post suggests turning transient data into inspectable artifacts with almost zero friction to enhance the developer experience.
- The solution outlined involves treating in-memory data as a file, uploading it to a WebDAV server, and inspecting it with Filestash.
- WebDAV, a widely supported HTTP-based standard, is chosen for its simplicity and various server implementations like Jackrabbit and Apache Server.
- Filestash, a web UI for storage backends like WebDAV or S3, is preferred for its clean interface and integration with Collabora Online for previewing office files.
- The implementation involves setting up a WebDAV server, writing code for the client, and configuring Filestash using Docker Compose.
- Benefits include simplified debugging, improved transparency, and easy integration with existing logging infrastructure.
- Challenges discussed include file name conflicts, data retention policies, and considerations for sending data to the server.
- Conclusion highlights WebDAV + Filestash as an elegant debugging solution for data-heavy applications, with room for enhancements like data retention mechanisms and improved Docker setup.
- The experiment repository for this setup is available at https://github.com/djalilhebal/debugging-data-pipelines-demo.
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