🏗 Build Spider: Los Angeles City Council #11
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WalkthroughThe changes introduce a new spider class, Changes
Sequence Diagram(s)sequenceDiagram
participant User
participant LoscaCityCouncilSpider
participant API
participant Meeting
User->>LoscaCityCouncilSpider: Start scraping
LoscaCityCouncilSpider->>API: Request upcoming meetings
API-->>LoscaCityCouncilSpider: Return JSON data
LoscaCityCouncilSpider->>Meeting: Create meeting objects
Meeting-->>LoscaCityCouncilSpider: Return created meetings
LoscaCityCouncilSpider-->>User: Provide meeting data
Poem
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Actionable comments posted: 2
🧹 Outside diff range and nitpick comments (9)
city_scrapers/spiders/losca_City_Council.py (2)
9-19: LGTM: Class definition is well-structured. Consider archived meetings.The
LoscaCityCouncilSpiderclass is correctly defined with appropriate attributes. The decision to scrape the API directly is well-documented in the comments.Consider implementing the archived meetings endpoint in the future to provide a more comprehensive dataset. This could be done by adding the archived meetings URL to the
start_urlslist or by implementing a separate method to fetch archived meetings.
1-60: Overall, excellent implementation with room for minor enhancements.The
LoscaCityCouncilSpideris well-implemented and effectively scrapes meeting data from the Los Angeles City Council API. The code is clean, follows project conventions, and uses appropriate helper methods for improved organization.For future enhancements, consider:
- Implementing the archived meetings endpoint to provide a more comprehensive dataset.
- Extracting location information from the API response if available, rather than using a hardcoded location.
- Handling potential missing data in the API response, such as video URLs.
- Providing more user-friendly source URLs.
These enhancements would make the spider more robust and provide more valuable data to end-users.
tests/test_losca_City_Council.py (6)
1-23: LGTM! Consider using a relative path for the JSON file.The imports and test setup look good. The use of
file_responseandfreezegunis appropriate for creating a consistent test environment.Consider using a relative path for the JSON file to make the tests more robust to directory structure changes:
from pathlib import Path test_response = file_response( Path(__file__).parent / "files" / "losca_City_Council.json", url="https://lacity.primegov.com/api/v2/PublicPortal/ListUpcomingMeetings?_=1726255032697", )
25-26: LGTM! Consider making the test more flexible.The test for item count is clear and concise.
To make the test more resilient to changes in the test data, consider using an assertion that checks for a range or a minimum number of items instead of an exact count:
def test_count(): assert len(parsed_items) >= 10, "Expected at least 10 parsed items"This approach allows for some flexibility in the test data while still ensuring a minimum number of items are parsed.
29-31: LGTM! Consider testing more titles or using parameterized tests.The title tests look good and verify specific parsed titles.
To increase test coverage and make the tests more maintainable, consider using pytest's parameterize feature:
@pytest.mark.parametrize( "index,expected_title", [ (0, "Personnel, Audits, and Hiring Committee"), (1, "SAP - Personnel, Audits, and Hiring Committee"), # Add more (index, title) pairs as needed ], ) def test_title(index, expected_title): assert parsed_items[index]["title"] == expected_titleThis approach allows you to easily add more title tests without duplicating code.
34-50: LGTM! Consider expanding test coverage for descriptions, end times, and time notes.The tests for start times are comprehensive, checking multiple items. However, the tests for description, end time, and time notes could be more thorough.
- For
test_descriptionandtest_time_notes, consider checking all items:def test_description(): assert all(item["description"] == "" for item in parsed_items) def test_time_notes(): assert all(item["time_notes"] == "" for item in parsed_items)
- For
test_end, verify the assumption that all items have no end time:def test_end(): assert all(item["end"] is None for item in parsed_items)These changes will provide more comprehensive coverage and catch potential inconsistencies across all parsed items.
52-74: LGTM! Consider expanding test coverage and improving id test robustness.The tests for id, status, location, and source are specific and check for exact values, which is good for ensuring correct parsing.
- For
test_status,test_location, andtest_source, consider checking all items or using parameterized tests:def test_status(): assert all(item["status"] == "tentative" for item in parsed_items) @pytest.mark.parametrize("item", parsed_items) def test_location(item): assert item["location"] == { "name": "Office of the City Clerk", "address": "200 N Spring St, Room 360, Los Angeles, CA 90012", } def test_source(): expected_source = "https://lacity.primegov.com/api/v2/PublicPortal/ListUpcomingMeetings?_=1726255032697" assert all(item["source"] == expected_source for item in parsed_items)
- For
test_id, consider using a more flexible assertion that checks the format rather than an exact string:import re def test_id(): id_pattern = r"losca_City_Council/\d{12}/x/[a-z_]+" assert re.match(id_pattern, parsed_items[0]["id"])These changes will provide more comprehensive coverage and make the tests more resilient to minor changes in the parsed data.
77-88: LGTM! Consider expanding test coverage for classification.The
test_linksfunction is comprehensive, checking multiple items with different scenarios. This is a good approach.For
test_classification, consider checking all items to ensure consistency:def test_classification(): assert all(item["classification"] == CITY_COUNCIL for item in parsed_items)This change will verify that all parsed items have the correct classification, not just the first one.
tests/files/losca_City_Council.json (1)
1-1: Well-structured JSON data for testing purposes.The JSON structure is consistent and well-formed, containing an array of meeting objects with a variety of properties. This structure appears suitable for testing the Los Angeles City Council meeting scraper.
Consider adding a comment at the beginning of the file to explain its purpose as a test fixture and the date it represents (October 2024).
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📒 Files selected for processing (3)
- city_scrapers/spiders/losca_City_Council.py (1 hunks)
- tests/files/losca_City_Council.json (1 hunks)
- tests/test_losca_City_Council.py (1 hunks)
🔇 Additional comments (6)
city_scrapers/spiders/losca_City_Council.py (2)
1-7: LGTM: Imports are well-organized and relevant.The imports are correctly structured, following the convention of grouping standard library, third-party, and local imports. All imported modules and classes appear to be necessary for the spider's functionality.
21-52: LGTM: Parse method is well-implemented. Verify location information.The
parsemethod effectively processes the API response and createsMeetingobjects with the extracted data. The use of helper methods improves code organization and readability.Please verify if the hardcoded location is accurate for all Los Angeles City Council meetings. If meetings can occur at different locations, consider extracting location information from the API response if available.
✅ Verification successful
Action Required: Update the shell script to correctly identify Python files.
The previous command used an unrecognized file type
python. Please update the shell script to use--type pyfor Python files and re-run the verification.
Verification Successful: Location is consistently hardcoded.
The
parsemethod uses a fixed location for all meetings, specifically the "Office of the City Clerk" at "200 N Spring St, Room 360, Los Angeles, CA 90012". If all Los Angeles City Council meetings are indeed held at this location, the implementation is correct and no further action is required.🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash # Description: Check if the location is always the same for all meetings # Test: Search for any variations in meeting locations rg --type python -i 'location|address|venue' city_scrapers/spiders/losca_City_Council.pyLength of output: 121
Script:
#!/bin/bash # Description: Check if the location is always the same for all meetings # Test: Search for any variations in meeting locations rg --type py -i 'location|address|venue' city_scrapers/spiders/losca_City_Council.pyLength of output: 245
tests/test_losca_City_Council.py (2)
91-93: LGTM! Excellent use of parameterized testing.The
test_all_dayfunction is well-implemented. It uses pytest's parameterize feature to efficiently test that none of the events are marked as all-day across all parsed items. This approach is both concise and comprehensive.
1-93: Overall, the test suite is well-structured and comprehensive.The test file for
LoscaCityCouncilSpidercovers all major aspects of the parsed items, which is crucial for ensuring the spider's correctness. The use offreezegunfor time manipulation andfile_responsefor loading test data are good practices.Some areas for potential improvement include:
- Expanding test coverage to check more items in some tests.
- Using more flexible assertions where appropriate to make tests more resilient to minor changes in data.
- Utilizing pytest's parameterize feature more extensively for cleaner and more maintainable tests.
These improvements would further enhance the robustness and maintainability of the test suite.
tests/files/losca_City_Council.json (2)
1-1: Verify the use of future dates in test data.The meeting dates in this file are set in October 2024. While this is fine for testing purposes, it's worth considering:
- Will these dates need to be updated periodically to keep tests relevant?
- Should there be a mix of past and future dates to test different scenarios?
Please confirm if using future dates is intentional and if there's a plan to keep this test data up-to-date.
1-1: Consider handling of null values in certain fields.Some fields like
videoUrl,swagitId,externalProviderMeetingId, andzoomMeetingLinkcontain null values for certain meetings. While this is likely accurate data, it's important to ensure that the scraper and any consuming code can handle these null values appropriately.Please confirm that the scraper and any code using this data properly handles null values for these fields.
What's this PR do?
This PR adds a scraper for Los Angeles City Council. The scraper parses an API endpoint for upcoming meetings.
Why are we doing this?
Scraper requested from spreadsheet.
Steps to manually test
test_output.csvto ensure the data looks valid.Are there any smells or added technical debt to note?
This scraper only uses the endpoint for upcoming meetings. There is another endpoint for archived meetings. Not sure if we wanted to also "scrape" that endpoint. Also not sure how to make that change if we actually do need it. I tried adding it to the
start_urlsarray in the scraper but all my tests still passed. I expected the number of parsed items to increase with that change but it did not so I assumed that's not how you do it.Summary by CodeRabbit
New Features
Tests