Updated datasets.py #31
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thanks for the PR 🥳 comments in the files! |
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And add the 3 datasets in pytest: |
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| CARE_SITE_ID,CARE_SITE_NAME,PLACE_OF_SERVICE_CONCEPT_ID,LOCATION_ID,CARE_SITE_SOURCE_VALUE,PLACE_OF_SERVICE_SOURCE_VALUE | |||
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no csv files stored here, rather download from external :)
| @@ -62,7 +62,7 @@ def mimic_iv_omop(backend_handle: DuckDBPyConnection, data_path: Path | None = N | |||
| >>> con.execute("SHOW TABLES;").fetchall() | |||
| """ | |||
| if data_path is None: | |||
| data_path = "ehrapy_data/mimic-iv-demo-data-in-the-omop-common-data-model-0.9" | |||
| data_path = Path("ehrapy_data/mimic-iv-demo-data-in-the-omop-common-data-model-0.9") | |||
| extracted_folder = next( | ||
| (folder for folder in data_path.iterdir() if folder.is_dir() and "_csv" in folder.name), data_path | ||
| ) | ||
| return _set_up_duckdb(extracted_folder, backend_handle) | ||
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| def gibleed_omop(backend_handle: DuckDBPyConnection, data_path: Path | None = None) -> None: |
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Adding more information to the docstrings would be great; see e.g. other ehrapy datasets that we already have, with links to where the data is from, and that this is in the omop data format with maybe a link to the omop data description
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for more information, see https://pre-commit.ci
for more information, see https://pre-commit.ci
for more information, see https://pre-commit.ci
for more information, see https://pre-commit.ci
for more information, see https://pre-commit.ci
for more information, see https://pre-commit.ci
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Fixed in #62. Worked locally, failed on CI; best guess is that Ubuntu acts more strictly than macOS on capitalization of files to read. |
| shutil.rmtree(TEST_DATA_DIR) | ||
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| if __name__ == "__main__": |
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Don't think that this is necessary?
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don't think so either, thx for the looking over, appreciate!
| if data_path is None: | ||
| data_path = Path("ehrapy_data/Synthea27Nj") | ||
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| if data_path.exists(): |
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I'd have a general downloading function that you can reuse. Just steal the one from ehrapy. Consider not printing but use proper logging.
Datasets implementation