Fix strptime failure with non-zero-padded format codes

[stephen-zhao]

Summary

• Fixes Non-zero padding formats #4: DatetimeExtractor fails to parse datetimes when using non-zero-padded format codes like %-d, %-m, etc. on Linux CPython, where strptime doesn't accept the - modifier.
• Normalizes format codes by stripping the - modifier (e.g. %-d → %d) before passing to strptime, since strptime can already handle non-zero-padded values with the standard directives.
• Adds unit tests for non-zero-padded date extraction using TEST_MINUS_SIGNS and TEST_DATE_LONG_FORM pipelines.

Test plan

• All 32 tests pass, including 5 new tests covering non-zero-padded format codes
• Verified %-m/%-d extraction works (e.g. 1/11/2017 with %-d/%m/%Y)
• Verified %-d in long-form dates works (e.g. Wednesday January 5, 2022)
• Existing tests unchanged and still passing

https://claude.ai/code/session_0137rpSUUxos1kRYsMtH8jiE

Summary by Sourcery

Handle non-zero-padded datetime format codes in DatetimeExtractor and add regression tests to cover them.

Bug Fixes:

• Fix datetime parsing failures when using non-zero-padded strptime format codes (e.g. '%-d', '%-m') on platforms that do not support the '-' modifier.

Tests:

• Add tests for non-zero-padded date components in filename-based extraction using the TEST_MINUS_SIGNS pipeline.
• Add tests for non-zero-padded day components in long-form date strings using the TEST_DATE_LONG_FORM pipeline.

[sourcery-ai]

Reviewer's Guide

Normalizes datetime format tokens by stripping unsupported '%-' modifiers before calling strptime, and adds regression tests to ensure non-zero-padded date formats are correctly parsed in existing pipelines.

Sequence diagram for datetime parsing with format code normalization

sequenceDiagram
    actor Client
    participant DatetimeExtractor
    participant Match
    participant DfregexToken
    participant Strptime

    Client->>DatetimeExtractor: extract_datetime(text, pipeline)
    DatetimeExtractor->>Match: finditer on text
    loop for each match
        DatetimeExtractor->>Match: groupdict()
        Match-->>DatetimeExtractor: groups
        DatetimeExtractor->>DfregexToken: get df_tokens[datetime_group_num]
        DfregexToken-->>DatetimeExtractor: format_code
        DatetimeExtractor->>DatetimeExtractor: __normalize_format_code(format_code)
        DatetimeExtractor-->>DatetimeExtractor: normalized_format_code
        DatetimeExtractor->>Strptime: strptime(datetime_string_value, normalized_format_code)
        Strptime-->>DatetimeExtractor: datetime_object or error
    end
    DatetimeExtractor-->>Client: parsed datetimes

Loading

Class diagram for updated DatetimeExtractor format normalization

classDiagram
    class DatetimeExtractor {
        +__finditer_with_limit(pattern, text, limit)
        +__parse_match_into_maybe_datetime(match, df_tokens)
        +__normalize_format_code(format_code) static
    }

    class DfregexToken {
        +value
    }

    class Match {
        +groupdict()
    }

    DatetimeExtractor ..> DfregexToken : uses
    DatetimeExtractor ..> Match : parses

Loading

File-Level Changes

Change	Details	Files
Normalize datetime format codes before passing them to strptime to support non-zero-padded directives on platforms that reject '%-' modifiers.	Introduce a private static helper to strip the '-' modifier from all '%-' sequences in format codes Use the new normalizer when building the list of datetime format codes from df_tokens in __parse_match_into_maybe_datetime Preserve existing error handling for problematic tokens while ensuring normalized codes are passed to strptime	src/datetime_matcher/datetime_extractor.py
Add regression tests verifying extraction of non-zero-padded dates in existing pipelines.	Add parametrized tests covering non-zero-padded month/day parsing in TEST_MINUS_SIGNS pipeline Add parametrized tests covering non-zero-padded day parsing in long-form date strings in TEST_DATE_LONG_FORM pipeline Assert that only a single datetime is produced per input and that iteration stops afterward to match existing extractor behavior	test/test_datetime_extractor.py

Assessment against linked issues

Issue	Objective	Addressed	Explanation
#4	Ensure DatetimeExtractor can parse datetimes when using non-zero-padded format codes (e.g. '%-d', '%-m') by adjusting the format string before calling strptime so it works on platforms where strptime does not accept the '-' modifier.	✅
#4	Add automated tests that cover extraction of dates using non-zero-padded format codes to prevent regressions.	✅

---

Tips and commands

Interacting with Sourcery

• Trigger a new review: Comment @sourcery-ai review on the pull request.
• Continue discussions: Reply directly to Sourcery's review comments.
• Generate a GitHub issue from a review comment: Ask Sourcery to create an
  issue from a review comment by replying to it. You can also reply to a
  review comment with @sourcery-ai issue to create an issue from it.
• Generate a pull request title: Write @sourcery-ai anywhere in the pull
  request title to generate a title at any time. You can also comment
  @sourcery-ai title on the pull request to (re-)generate the title at any time.
• Generate a pull request summary: Write @sourcery-ai summary anywhere in
  the pull request body to generate a PR summary at any time exactly where you
  want it. You can also comment @sourcery-ai summary on the pull request to
  (re-)generate the summary at any time.
• Generate reviewer's guide: Comment @sourcery-ai guide on the pull
  request to (re-)generate the reviewer's guide at any time.
• Resolve all Sourcery comments: Comment @sourcery-ai resolve on the
  pull request to resolve all Sourcery comments. Useful if you've already
  addressed all the comments and don't want to see them anymore.
• Dismiss all Sourcery reviews: Comment @sourcery-ai dismiss on the pull
  request to dismiss all existing Sourcery reviews. Especially useful if you
  want to start fresh with a new review - don't forget to comment
  @sourcery-ai review to trigger a new review!

Customizing Your Experience

Access your dashboard to:

• Enable or disable review features such as the Sourcery-generated pull request
  summary, the reviewer's guide, and others.
• Change the review language.
• Add, remove or edit custom review instructions.
• Adjust other review settings.

Getting Help

• Contact our support team for questions or feedback.
• Visit our documentation for detailed guides and information.
• Keep in touch with the Sourcery team by following us on X/Twitter, LinkedIn or GitHub.

[sourcery-ai]

Hey - I've left some high level feedback:

• The __normalize_format_code implementation currently does a blanket replace("%-", "%"); if any format token can contain %− in a non-directive context this will silently alter the semantics—consider constraining the replacement (e.g., only when followed by known directive characters) or adding a brief comment explaining why a global replace is safe here.
• Since __normalize_format_code is logically a pure helper, you might consider making it a module-level function or a @staticmethod with single underscore naming to avoid name mangling and keep it more easily testable/reusable if other components ever need the same normalization.

Prompt for AI Agents

Please address the comments from this code review:

## Overall Comments
- The `__normalize_format_code` implementation currently does a blanket `replace("%-", "%")`; if any format token can contain `%−` in a non-directive context this will silently alter the semantics—consider constraining the replacement (e.g., only when followed by known directive characters) or adding a brief comment explaining why a global replace is safe here.
- Since `__normalize_format_code` is logically a pure helper, you might consider making it a module-level function or a `@staticmethod` with single underscore naming to avoid name mangling and keep it more easily testable/reusable if other components ever need the same normalization.

---

Sourcery is free for open source - if you like our reviews please consider sharing them ✨

• X
• Mastodon
• LinkedIn
• Facebook

_{Help me be more useful! Please click 👍 or 👎 on each comment and I'll use the feedback to improve your reviews.}