57 lines
1.7 KiB
Python
57 lines
1.7 KiB
Python
import json
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import os
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import sys
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sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..")))
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import pytest
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from doi2dataset import MetadataProcessor
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class FakeResponse:
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"""
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A fake response object to simulate an API response.
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"""
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def __init__(self, json_data, status_code=200):
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self._json = json_data
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self.status_code = status_code
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def json(self):
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return self._json
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def raise_for_status(self):
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pass
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@pytest.fixture
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def fake_openalex_response():
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"""
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Load the saved JSON response from the file 'srep45389.json'
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located in the same directory as this test file.
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"""
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json_path = os.path.join(os.path.dirname(__file__), "srep45389.json")
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with open(json_path, "r", encoding="utf-8") as f:
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data = json.load(f)
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return data
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def test_fetch_doi_data_with_file(mocker, fake_openalex_response):
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"""
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Test fetching DOI metadata by simulating the API call with a locally saved JSON response.
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The APIClient.make_request method is patched to return a fake response based on
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the contents of 'srep45389.json', so that no actual network request is performed.
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"""
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doi = "10.1038/srep45389"
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fake_response = FakeResponse(fake_openalex_response, 200)
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# Patch the make_request method of APIClient to return our fake_response.
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mocker.patch("doi2dataset.APIClient.make_request", return_value=fake_response)
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# Instantiate MetadataProcessor without upload and progress.
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processor = MetadataProcessor(doi=doi, upload=False)
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# Call _fetch_data(), which should now return our fake JSON data.
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data = processor._fetch_data()
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# Verify that the fetched data matches the fake JSON data.
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assert data == fake_openalex_response
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