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sync mentored trainees lists from CV to people.xlsx #10

Description

@jeremymanning

not all trainees listed in my CV are also in the people spreadsheet.

use the CV preferentially (it's more accurate and up-to-date than the website):

  • any trainees that appear with NO end date (i.e., no "(YYYY -- )" in their date of membership) are active lab members and should have entries in the "members" sheet. in the spreadsheet, sort first by category (postdoc > grad student > lab manager > research scientist > undergrad) and then reverse chronologically by starting year.
  • any trainees that DO appear with an end date (i.e., either "(YYYY)" or "(XXXX -- YYYY)") are inactive (alumni) lab members, and should have entries in the corresponding alumni sheets. parse any "current position" text listed in the CV document.

Activity

  1. jeremymanning commented on Dec 18, 2025

    @jeremymanning
    MemberAuthor

    there might also be people who appear on the website but NOT in the CV. in that case, those people should be added to the CV at the appropriate positions. (but when in conflict, e.g., with respect to start/end dates or status, prefer the CV info over the people.xlsx info).

  2. jeremymanning commented on Dec 18, 2025

    @jeremymanning
    MemberAuthor

    note: we are working on this issue in parallel with issue #9, so we should stick with the same feature branch. we'll pull all the changes in together.

  3. jeremymanning commented on Dec 18, 2025

    @jeremymanning
    MemberAuthor

    Implementation Plan for Issue #10: Sync Mentored Trainees from CV to people.xlsx

    Overview

    This issue requires bi-directional synchronization between the CV (documents/JRM_CV.tex) and the people spreadsheet (data/people.xlsx). The CV is the source of truth for trainee information.

    Key Requirements

    1. CV → people.xlsx: Add any trainees in CV but not in spreadsheet
    2. people.xlsx → CV: Add any trainees in spreadsheet but not in CV
    3. Active vs Alumni: Trainees with no end date (e.g., "2024 -- )") are active members; those with end dates are alumni
    4. Sorting:
      • Members: by category (postdoc > grad > lab manager > research scientist > undergrad), then reverse chronologically by start year
      • Alumni: as appropriate for each section

    Branch Strategy

    Per comment: Stay on branch issue-9-news-feed - will be merged together with Issue #9.


    Execution Plan

    Phase 1: Build CV Parser Script (Sequential)

    Agent 1: CV Parser Development

    Create scripts/parse_cv_trainees.py:

    • Parse LaTeX file to extract trainee information from mentorship sections
    • Handle all trainee types: Postdoctoral Advisees, Graduate Advisees, Undergraduate Advisees
    • Extract: name, role/type, start year, end year (if any), current position (if any)
    • Detect active vs alumni status based on date format
    • Return structured data suitable for comparison with people.xlsx

    Key parsing patterns:

    • \item Name (2024 -- ) → Active member
    • \item Name (2024 -- 2025; current position: Company) → Alumni
    • \item Name (Doctoral student; 2021 -- ) → Active grad student
    • \item Name* (2024 -- ) → Undergraduate with thesis (asterisk)

    Phase 2: Comparison & Sync Logic (Sequential - depends on Phase 1)

    Agent 2: Sync Script Development

    Create scripts/sync_cv_people.py:

    • Load CV trainees using parser from Phase 1
    • Load people.xlsx data
    • Compare and identify:
      • People in CV but not in spreadsheet (add to spreadsheet)
      • People in spreadsheet but not in CV (add to CV)
      • Discrepancies in dates/status (CV wins)
    • Generate sync report showing all changes needed

    Phase 3: Data Updates (Sequential - depends on Phase 2)

    Agent 3: Apply Updates

    • Update data/people.xlsx with missing trainees from CV
    • Generate patch/additions for CV if spreadsheet has unique entries
    • Ensure proper sorting in members sheet:
      • Category order: postdoc > grad student > lab manager > research scientist > undergrad
      • Within category: reverse chronological by start year
    • Run build_people.py to regenerate people.html

    Phase 4: Testing (Parallel after Phase 3)

    Agent 4a: Unit Tests
    Create tests/test_parse_cv_trainees.py:

    • Test LaTeX parsing for all trainee types
    • Test date extraction (active vs alumni detection)
    • Test name extraction with special characters
    • Test current position parsing
    • Test edge cases (missing data, malformed entries)

    Agent 4b: Integration Tests
    Create tests/test_sync_cv_people.py:

    • Test comparison logic
    • Test sync direction (CV → spreadsheet, spreadsheet → CV)
    • Test sorting logic
    • Test full sync workflow with real CV and spreadsheet files

    Phase 5: Validation & Cleanup (Sequential)

    Single Agent

    1. Run all tests locally: python -m pytest tests/ -v
    2. Run linters/validation: python scripts/validate_data.py
    3. Rebuild all pages: python scripts/build.py
    4. Manual verification:
      • Check people.html renders correctly
      • Verify all trainees from CV appear in correct sections
      • Confirm sorting is correct
    5. Clean up:
      • Remove any temporary files
      • Update notes in notes/ folder
    6. Commit with descriptive message

    Files to Create/Modify

    New Files

    • scripts/parse_cv_trainees.py - LaTeX CV parser for mentorship sections
    • scripts/sync_cv_people.py - Bi-directional sync script
    • tests/test_parse_cv_trainees.py - CV parser tests (NO MOCKS - uses real CV file)
    • tests/test_sync_cv_people.py - Sync logic tests (NO MOCKS - uses real files)

    Modified Files

    • data/people.xlsx - Updated with synced trainee data
    • documents/JRM_CV.tex - Updated with any trainees only in spreadsheet
    • people.html - Regenerated from updated spreadsheet

    Testing Requirements

    CRITICAL: NO MOCK TESTS OR SIMULATIONS

    All tests must use:

    • Real documents/JRM_CV.tex file for parsing tests
    • Real data/people.xlsx for spreadsheet tests
    • Real file I/O operations
    • Actual comparison against expected structured data

    Test categories:

    1. CV Parsing Tests - Parse actual CV, verify extracted trainee counts and data
    2. Sync Logic Tests - Use real files, verify correct additions/updates identified
    3. Integration Tests - Full workflow with real data files
    4. Validation Tests - Ensure generated HTML is valid

    Verification Checklist

    Before marking complete:

    • All tests pass locally: python -m pytest tests/ -v
    • Data validation passes: python scripts/validate_data.py
    • Build succeeds: python scripts/build.py
    • people.html renders correctly in browser
    • All CV trainees appear in correct spreadsheet sections
    • Members sorted correctly (category, then reverse chronological)
    • Alumni sorted correctly in respective sheets
    • No temporary files left behind
    • Notes updated in notes/ folder
    • GitHub Actions CI passes after push

    Notes on CV Structure

    From JRM_CV.tex (lines 653-859):

    Postdoctoral Advisees (lines 654-658):

    • Format: \item Name (YYYY -- YYYY; current position: Company)
    • 3 entries total

    Graduate Advisees (lines 661-676):

    • Format: \item Name (Type; YYYY -- YYYY; current position: ...)
    • Types: "Doctoral student", "Masters student, Program"
    • Active: no end year (e.g., "2021 -- )")
    • 10 entries total

    Undergraduate Advisees (lines 734-858):

    • Format: \item Name* (YYYY -- YYYY) (asterisk = thesis student)
    • Multi-column layout
    • ~125 entries total

    Lab Managers: Not explicitly listed in CV - need to cross-reference spreadsheet's alumni_managers sheet.


    Estimated Complexity

    • Phase 1: Medium - LaTeX parsing requires careful regex handling
    • Phase 2: Medium - Comparison logic with multiple edge cases
    • Phase 3: Low - Straightforward data updates
    • Phase 4: Medium - Comprehensive test coverage
    • Phase 5: Low - Standard validation workflow

    Total: ~3-4 hours of agent work with parallelization

  4. jeremymanning commented on Dec 18, 2025

    @jeremymanning
    MemberAuthor

    Updated Plan

    Per feedback:

    • Additional pattern: \item Name (2023 -- 2024) → Alumni (date range without current position)
    • Skip tests - this is a one-time sync operation
    • Keep scripts - for systematic execution and potential future re-use
    • Future onboarding - will use separate process for adding people

    Simplified Execution

    Phase 1: Create scripts/parse_cv_trainees.py - CV parser
    Phase 2: Create scripts/sync_cv_people.py - comparison and sync logic
    Phase 3: Run sync, update files, validate output
    Phase 4: Cleanup and commit

    Proceeding with implementation now.

  5. jeremymanning commented on Dec 19, 2025

    @jeremymanning
    MemberAuthor

    Completed in PR #11

    CV Trainee Sync Scripts

    • Created scripts/sync_cv_people.py - main synchronization script that reads trainees from JRM_CV.tex and updates people.xlsx
    • Created scripts/parse_cv_trainees.py - parser for extracting trainee information from the CV LaTeX format

    Sorting Implementation

    Members sheet is now sorted by:

    1. Role priority: Postdocs → PhD students → Masters students → Lab managers → Undergrads
    2. Join date: Chronologically within each role category (earliest first)

    Alumni Handling

    • Trainees with end dates are placed in appropriate alumni sheets (alumni_postdocs, alumni_grads, alumni_managers, alumni_undergrads)
    • Current position information is parsed from CV and stored in spreadsheet

    Additional Improvements

    • build_people.py now uses placeholder.png for members without profile photos
    • Added hand-drawn borders to new profile photos using add_poster_borders.py
    • Updated validate_data.py to check for sync discrepancies

    How to Use

    Run python scripts/sync_cv_people.py to synchronize trainees from the CV to the spreadsheet. The script will report any additions, updates, or discrepancies found.

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