Comments (1)
Nice idea, but it does not really fit the import usecase in my opinion. I see checking existing data as a fundamentally different usecase, in contrast to importing new data, which is what the smart_importer addresses. Also outlier detection is probably/maybe (?) a different machine learning task than classification, which is what is used in the smart_importer project.
For these reasons, if that's ok for you, I would like to propose: Please feel free to create a script that performs such checks, but let's keep it separate from the smart_importer codebase. Feel free, of course, to use and abuse the existing smart_importer source code for your script :-)
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Related Issues (20)
- pylint fails, tox depends on wrong version of beancount? HOT 3
- Expose ImporterHook interface HOT 4
- Allow custom getters for attributes HOT 2
- Predict postings with amounts HOT 3
- Predict metadata (and tags) HOT 3
- Package working with python 3.6.12 but not with python 3.9 HOT 26
- ImportError undefined symbol _PyGen_Send HOT 2
- Unable to use smart_importer with beangulp Importers HOT 8
- release a v0.4 to pypi HOT 2
- How to pass in existing entries as training data other than the current bean file HOT 10
- Using `file_account()` to filter training data doesn't work for certain use cases HOT 4
- TAGS HOT 2
- Predictions might lead to original posting being switched to 2nd place after prediction HOT 1
- Smart importer give duplicate asset postings
- Passing too many arguments to extract() HOT 1
- I can't manage to have smart_importer working HOT 6
- Remove suggestions because suggest=True adds list as metadata which is invalid HOT 7
- Bypass specific transactions. HOT 4
- please provide the hook helpers as an own package HOT 2
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