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Obelisk-Python\n\nAfter years of copy-pasting and modifying Obelisk client implementations all over,\nwe've had enough of hearing \"construct additional obelisks\".\nThus, we have decided to build the one client to rule them all.\n\nThis project is licensed according to the LICENSE file included with the source.\nYou should have received a copy alongside the code bundle,\notherwise you can get it for the most recent version [here](https://github.com/predict-idlab/obelisk-python/blob/main/LICENSE).\n\n## Usage\n\nTake your pick of asynchronous or sync,\nimport the relevant Producer or Consumer and go crazy.\nThere is explicitly minimal documentation on actual filter values,\nread the [Obelisk docs](https://obelisk.docs.apiary.io/) for that.\nDocumentation for the Python API can be found [here](https://predict-idlab.github.io/obelisk-python/).\n\nPlease never copy the repo into your own project,\nrather use `pip install obelisk-py`.\n\n### Retry strategies\n\nObelisk-py provides first class support for retry behaviours.\nThese are defined in `strategies/retry.py`,\nwe provide `NoRetryStrategy`, `ImmediateRetryStrategy`, \nand `ExponentialBackoffRetryStrategy.`\nThese do exactly what it says on the tin,\nwhen provided in the constructor of your producer, consumer or client,\nthey will cause the client to retry requests according to the strategy\nwhenever the response status is not in the 2XX range.\n\nThe default strategy is no retry,\nwe do recommend setting at least some form of retry\nas the token validity behaviour sometimes encounters edge cases.\n\n### Async and Sync support\n\nThe library has an async and blocking edition.\nThe async edition is contained in the module `asynchronous` \ndue to `async` being a reserved keyword and invalid package name,\nsynchronous can be found in `sync`. \nThe `sync` edition is simply a wrapper around `asynchronous`, \nmaintaining an own event loop.\n\n### HFS and Classic support\n\nAll constructors take an optional `kind` argument,\nset this to the appropriate variety for you.\n\nThere is no special handling for HFS userId / patientId fields as those are never\ndirectly touched by the library.\nThe only exception is that `Datapoint` has explicit support for userId\nand allows extra fields to provide naive support for other field names.\n\n## Building and Docs\n\n`uv` is used to manage this project.\nTests can be run using `uv run pytest`, building and deployment are handled by `uv build` and `uv publish`.\n\nDocumentation uses the classic `sphinx` setup, with numpydoc for their lovely layouts and conventions.\nBuilding is as follows:\n\n``` sh\n# uv run sphinx-build -M html docs/source/ docs/build/\n```\n\nIn case of major restructuring, it may be needed to clean up the contents of `docs/_autosummary` and potentially other rst files in `docs`,\nfollowed by re-running the build.\nManually triggering sphinx-apidoc is unnecessary.\n\n### Hooks\n\nWe use some simple Git hooks to avoid fighting the CI too often.\nThese are stored in the `hooks/` directory, and can be enabled by setting `git config core.hooksPath hooks/`.\n\n## Credits\n\nBase implementation originally by Pieter Moens \u003cPieter.Moens@ugent.be\u003e,\nmodified by Kyana Bosschaerts \u003cKyana.Bosschaerts@ugent.be\u003e\nand finally consolidated by Stef Pletinck \u003cStef.Pletinck@ugent.be\u003e.\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpredict-idlab%2Fobelisk-python","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fpredict-idlab%2Fobelisk-python","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpredict-idlab%2Fobelisk-python/lists"}