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  • Added endpoint to get preceding or following signs for any sign and sort key
    E.g., "/signs/BAR/following/NeoAssyrianOffset"

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This is a benchmark review for experiment review_of_reviews_20240423.
Run ID: review_of_reviews_20240423/benchmark_2024-04-23T16-37-59_v1-16-0-177-gfebff3a45.

This pull request was cloned from https://github.com/ElectronicBabylonianLiterature/ebl-api/pull/546. (Note: the URL is not a link to avoid triggering a notification on the original pull request.)

Experiment configuration
review_config:
  # User configuration for the review
  # - benchmark - use the user config from the benchmark reviews
  # - <value> - use the value directly
  user_config:
    enable_ai_review: true
    enable_rule_comments: false

    enable_complexity_comments: benchmark
    enable_docstring_comments: benchmark
    enable_security_comments: benchmark
    enable_tests_comments: benchmark
    enable_comment_suggestions: benchmark

    enable_approvals: true

  ai_review_config:
    # The model responses to use for the experiment
    # - benchmark - use the model responses from the benchmark reviews
    # - llm - call the language model to generate responses
    model_responses:
      comments_model: benchmark
      comment_validation_model: benchmark
      comment_suggestion_model: benchmark
      complexity_model: benchmark
      docstrings_model: benchmark
      security_model: benchmark
      tests_model: benchmark

# The pull request dataset to run the experiment on
pull_request_dataset:
- https://github.com/albumentations-team/albumentations/pull/1679
- https://github.com/gdsfactory/kfactory/pull/301
- https://github.com/gdsfactory/kfactory/pull/300
- https://github.com/jquagga/ttt/pull/70
- https://github.com/gdsfactory/kfactory/pull/298
- https://github.com/gdsfactory/gplugins/pull/385
- https://github.com/shreejitverma/MScFE690-Capstone/pull/7
- https://github.com/gdsfactory/gdsfactory/pull/2694
- https://github.com/yelinaung/advent_of_code_2023/pull/8
- https://github.com/fairdataihub/fairdataihub.org/pull/620
- https://github.com/jquagga/ttt/pull/75
- https://github.com/jquagga/ttt/pull/77
- https://github.com/aboutmydreams/aiis.read/pull/16
- https://github.com/usama-maxenius/image-editor/pull/71
- https://github.com/okisdev/ChatChat/pull/322
- https://github.com/okisdev/ChatChat/pull/323
- https://github.com/iphysresearch/Eryn/pull/1
- https://github.com/W-zrd/unishare_mobile/pull/9
- https://github.com/wassupluke/recipe-emailer/pull/24
- https://github.com/jquagga/ttt/pull/79
- https://github.com/Remi-Gau/nilearn/pull/50
- https://github.com/gdsfactory/gdsfactory/pull/2697
- https://github.com/0ussamaBernou/my-portfolio/pull/8
- https://github.com/kloudlite/web/pull/195
- https://github.com/ElectronicBabylonianLiterature/ebl-api/pull/546
- https://github.com/okisdev/ChatChat/pull/319
- https://github.com/strawberry-graphql/strawberry/pull/3469
- https://github.com/ShiroePL/EasternTalesShelf/pull/44
- https://github.com/jquagga/ttt/pull/78
- https://github.com/W-zrd/unishare_mobile/pull/10
- https://github.com/erxes/erxes/pull/5157
- https://github.com/jquagga/ttt/pull/67
- https://github.com/jquagga/ttt/pull/76
- https://github.com/jkool702/openwrt/pull/41
- https://github.com/jquagga/ttt/pull/73
- https://github.com/W-zrd/unishare_mobile/pull/8
- https://github.com/UCL/dxss/pull/63
- https://github.com/shreejitverma/MScFE690-Capstone/pull/6
- https://github.com/DevCycleHQ/go-server-sdk/pull/248
- https://github.com/Quarticai/graphene-django-extras/pull/104
- https://github.com/wassupluke/recipe-emailer/pull/29
- https://github.com/erxes/erxes/pull/5158
- https://github.com/0ussamaBernou/my-portfolio/pull/6
- https://github.com/2lambda123/kwenta/pull/50
- https://github.com/dciborow/action-pylint/pull/14
- https://github.com/ShiroePL/EasternTalesShelf/pull/45
- https://github.com/W-zrd/unishare_mobile/pull/6
- https://github.com/gdsfactory/gdsfactory/pull/2696
- https://github.com/megasanjay/scholar-stack-mvp/pull/159
- https://github.com/W-zrd/unishare_mobile/pull/7
review_comment_labels:
- label: correct
  question: Is this comment correct?
- label: helpful
  question: Is this comment helpful?
- label: comment-type
  question: Is the comment type correct?
- label: comment-area
  question: Is the comment area correct?
- label: llm-test
  question: Should this comment become an LLM test?

# Benchmark reviews generated by running
#   python -m scripts.experiment benchmark <experiment_name>
benchmark_reviews: []

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Hey @sourcery-ai-experiments-bot - I've reviewed your changes and they look great!

Here's what I looked at during the review
  • 🟡 General issues: 6 issues found
  • 🟢 Security: all looks good
  • 🟡 Testing: 2 issues found
  • 🟢 Complexity: all looks good
  • 🟢 Docstrings: all looks good

LangSmith trace

Help me be more useful! Please click 👍 or 👎 on each comment to tell me if it was helpful.

data = self._collection.find_one_by_id(name)
return cast(Sign, SignSchema(unknown=EXCLUDE).load(data))

def find_signs_by_order(self, name: SignName, order: str, sort_era: str) -> Sign:

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issue (code_clarification): Return type of 'find_signs_by_order' might be incorrect.

The method seems to return a list of signs, but the return type is annotated as a single 'Sign'. Consider updating the return type to reflect the actual data structure returned.

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Is this comment correct?

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Should this comment become an LLM test?

return cast(Sign, SignSchema(unknown=EXCLUDE).load(data))

def find_signs_by_order(self, name: SignName, order: str, sort_era: str) -> Sign:
key = self._collection.find_one_by_id(name)["sortKeys"][sort_era][0]

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issue (bug_risk): Potential risk of accessing non-existent keys in nested dictionaries.

This line could raise a KeyError if 'sortKeys' or 'sort_era' do not exist in the document. Consider adding error handling or checks to ensure these keys are present.

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Is this comment correct?

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Is the comment type correct?

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Should this comment become an LLM test?

"sort_key": f"$sortKeys.{sort_era}",
}
},
{"$sort": {"sort_key": 1}},

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issue (bug_risk): Sorting operation may not work as expected.

The sorting key 'sort_key' is extracted from a nested field and might not be correctly interpreted by the MongoDB query. Verify that the sorting behaves as intended.

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Should this comment become an LLM test?

api.add_route("/signs/{sign_name}", signs)
api.add_route("/signs/{sign_name}/images", signs_images)
api.add_route("/signs/all", signs_all)
api.add_route("/signs/{sign_name}/{order}/{sort_era}", ordered_signs)

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suggestion (code_refinement): URL pattern may lead to ambiguity.

The URL pattern '/signs/{sign_name}/{order}/{sort_era}' could be more descriptive to avoid confusion with other routes. Consider revising the URL to clearly indicate its functionality.

Suggested change
api.add_route("/signs/{sign_name}/{order}/{sort_era}", ordered_signs)
api.add_route("/signs/{sign_name}/sorted/{order}/{sort_era}", ordered_signs)

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Should this comment become an LLM test?

data = self._collection.find_one_by_id(name)
return cast(Sign, SignSchema(unknown=EXCLUDE).load(data))

def find_signs_by_order(self, name: SignName, order: str, sort_era: str) -> Sign:

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issue (testing): Missing unit tests for the new method find_signs_by_order.

This method involves complex MongoDB queries and conditional logic. It's crucial to ensure it behaves correctly under various scenarios, including edge cases like non-existent sort keys or empty results.

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Should this comment become an LLM test?

resp.media = self.sign_repository.list_all_signs()


class SignsOrderResource:

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issue (testing): Integration tests are needed for the SignsOrderResource endpoint.

Given the endpoint interacts with the MongoDB through complex queries, integration tests should verify the correct HTTP responses for various inputs, including error handling for invalid parameters.

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Should this comment become an LLM test?

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4 participants