
Version Controlling the Query Behind an Excel Report
Keep the SQL behind an Excel report in Git: one file per query, parameters, reviewed changes, tests, and the commit hash written into the workbook.
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Keep the SQL behind an Excel report in Git: one file per query, parameters, reviewed changes, tests, and the commit hash written into the workbook.

Add a README sheet to every generated workbook with the period, source, definitions, checks and version, written by the same code that builds the report.

Turn a repository of YAML into tables and ask SQL: Compose fleets, version drift, Kubernetes audits, dbt coverage and duplicate keys, with tested results.

Handle currency and locale in generated workbooks: store numbers, set format codes, name the currency and know what the reader's settings change.

Round and format numbers for finance readers: store exact values, round once on purpose, use number formats for display and make displayed totals add up.

Produce a monthly management pack from SQL: fixed sheets, prior month and budget comparisons, checks that tie out, and a scheduled build with sign off.

Write Excel conditional formatting from Python with XlsxWriter or openpyxl: value rules, color scales, data bars and formula rules, with tests.

Send charts from a SQL query to an Excel sheet by script: write the data, add a native chart with XlsxWriter or openpyxl, size it and label it.

Design a report query before opening Excel: fix the grain, avoid join fan-out, put rules in SQL, bind parameters and test totals against a trusted number.

Build Excel reports from SQL that readers trust: design the query, write sheets, formats and charts from code, check totals, version the query, schedule it.

pandas read_json turned the zip "01234" into 1234. How orient, lines, dtype and the pyarrow backend change the result, and what changed in pandas 3.

Move a fragile Excel model into a SQL view: map inputs, calculations and outputs, translate formulas, run both in parallel and keep Excel as the front end.
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