Convert engineering Excel workbooks to Python code using Claude Desktop cowork on Windows. Proven superior quality vs Linux openpyxl extraction (24 vs 7 functions, 81 vs 53 tests). Validated on Ballymore jumper installation analysis.
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name
excel-workbook-to-python-v2
description
Convert engineering Excel workbooks to Python code using Claude Desktop cowork on Windows. Proven superior quality vs Linux openpyxl extraction (24 vs 7 functions, 81 vs 53 tests). Validated on Ballymore jumper installation analysis.
trigger
User asks to convert an Excel workbook to Python code, or references workbook conversion (#1934,
effort
medium
model
any
context
7/12/10
Excel Workbook to Python — Claude Cowork on Windows (v2)
Benchmark Results
Metric
Windows Cowork
Linux openpyxl
Functions
24
7
Tests passing
81
53
OrcaFlex breakdown
27-section
Basic counts
COG calcs
Insulated + uninsulated
Not implemented
Architecture docs
ASCII diagram, formula table
Basic README
Code quality
__post_init__, typed
Good but fewer features
Execution Machine
ws014 (licensed-win-2): Claude Desktop with cowork mode + MCP
Excel installed, openpyxl and pytest available in Python environment
client-c repo cloned to ws014
Step-by-Step Workflow
Step 1: Open Excel workbook on Windows
Open the workbook in Excel. Launch Claude Desktop cowork session.
Step 2: Copy workbook path
Locate workbook path in client-c/engineering_workbooks/.
Copy full Windows path (e.g., C:\path\to\client-c\engineering_workbooks\ballymore\...).
Step 3: Prompt in Claude Desktop cowork
Convert this workbook to Python:
Workbook: {full Windows path to .xlsx/.xlsm}
Module name: {snake_case_module_name}
RULES:
1. Read EVERY sheet with openpyxl — extract all cell values, formulas,
cross-sheet refs, constants, and named ranges. Map dependency graph.
2. Create {module_name}.py in the SAME FOLDER as the workbook:
- Python 3.11+ with dataclasses, typing, math (no external deps)
- Use __post_init__ for derived fields that auto-compute from inputs
- Separate dataclass per logical input group (pipe, buoyancy, rigging, etc.)
- One function per calculation step — at least one per sheet
- Dedicated function for OrcaFlex section breakdown if workbook has it
- Dedicated functions for COG (insulated + uninsulated)
- Dedicated functions for pipe weight estimation
- Dedicated connector/clamp dataclasses as separate entities
- Every unit conversion is a named constant (INCH_TO_M = 0.0254, etc.)
- Every derived value has a cell reference comment: # Source: Sheet!Cell -- description
- CRITICAL: Every function must return its result (no missing returns!)
- run_all() pipeline function that returns dict of all results
- generate_orcaflex_line_sections_yaml() for 27-section line-type breakdown
- if __name__ == "__main__" block that prints summary
3. Create test_{module_name}.py in the same folder:
- Use pytest (NOT unittest)
- One test class per sheet
- Test every intermediate and final value against spreadsheet formulas
- Expected values traced to cell references in docstrings
- Test cross-sheet data flow (e.g. bend_radius from Bare pipe → GA)
- test_all_sheets_pipeline end-to-end test
- Target 80+ tests per workbook
4. Create README.md in the same folder:
- Engineering purpose
- Architecture data flow diagram (ASCII)
- Table: Sheet → Function → Dataclass mapping
- Key formulas with cell references
- Quick start: how to run module and tests
5. Run: pytest test_{module_name}.py -v — fix ALL failures before finishing
6. CRITICAL PITFALLS — avoid these:
- ALWAYS return props/results from functions that create them
- Use os.path.dirname(__file__) for sys.path, NOT hardcoded /tmp
- Never use unittest — only pytest
- Handle both dict and dataclass result types
Create docs/domains/orcaflex/subsea/{domain}/spec.yml following the pattern
from existing docs/domains/orcaflex/pipeline/installation/ specs.
Critical Pitfalls
1. Missing return statements
Claude sometimes omits return in functions that use __post_init__:
defcompute_buoyancy(props=None):
if props isNone:
props = BuoyancyModuleProperties()
return props # <--- EASY TO MISS
Fix: Verify EVERY function returns its result. Check the test file for
AttributeError like 'NoneType' object has no attribute — this means a return was missed.
2. sys.path hardcoded to /tmp
Test file may have: sys.path.insert(0, "/tmp")Fix: Change to sys.path.insert(0, os.path.dirname(__file__))
3. unittest vs pytest
Prompt explicitly says pytest. If unittest appears, convert:
unittest.TestCase → plain class
setUp(self) → self.setup_method()
self.assertAlmostEqual(a, b, places=N) → assert a == pytest.approx(b, abs=1e-N)
self.assertEqual(a, b) → assert a == b
self.assertTrue(x) → assert x
4. Code in Excel cells
If code ends up as Excel column A text (one line per cell), extract with openpyxl:
import openpyxl
wb = openpyxl.load_workbook("workbook.xlsx")
for sheet_name in ["module.py", "test_module.py", "README.md"]:
ws = wb[sheet_name]
lines = [str(row[0].value) if row[0].value else""for row in ws.iter_rows(max_col=1)]
open(sheet_name, "w").write("\n".join(lines) + "\n")
5. pyproject.toml conflicts
Run tests with -o addopts= to override repo pytest config that adds coverage.
Conversion Checklist
For each workbook:
All sheets have at least one function
OrcaFlex line-type section breakdown (if workbook has it)
