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Handling the possible errors
I know I'll change the API, so not many details in the documentation for now.
Moving back to a flat generic features table to allow a proof of concept. This is certainly not the way of storing this, but it allows to move the other parts forwards before thinking about the best schema.
Custom Result is based on custom Errors for this crate, so it has a better and consistem error handling along the full crate.
It is too early for integration tests. The API will change, so it's not worth to harness sampling data yet. Note that I'm still running locally with real data, so it won't be too off.
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Only a proof of concept to parse the features from a standard CSV and load into the internal database. The features table is still poorly defined, but developing the output should guide it better. |
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A proof of concept on parsing features from the default output from Paul's model.
This is the most unclear part in the pipeline for me, so better handle this early to shape the following decisions. Read the CSV is not a problem, but how to have an actionable database with such heterogenous records while keeping it flexible for future changes.
The goal here is to load the features in the database, thus modify the table features as needed to have actionable records. For now, don't worry on having version controlled data.