
Data Validation Lists and Their Limits in Excel Sheets
How Excel data validation lists behave and where they stop: the 255 character typed list, range sources, long lists, dependent dropdowns and pasting.
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How Excel data validation lists behave and where they stop: the 255 character typed list, range sources, long lists, dependent dropdowns and pasting.

50,000 orders in four formats: protobuf was 5.1 MB, JSON 10.8 MB, XML 14.2 MB, and it parsed in 9 ms against 161 for XML. What that buys and costs.

csvkit and Miller timed on the same 200,000-row file. Type inference makes csvkit's sort, stat and JSON commands 100 times slower and can rewrite your dates.

Measured heap needs for 36.6 MB of XML in Java: DOM fails at 256 MB, StAX with JAXB per record runs in 16 MB, and the memory is flat whatever the file size.

Pick CSV upload limits from measured parse and load speed, enforce each where it is cheapest, and reject bad shapes with a script that names the line.

Measure what a YAML pipeline file costs to load, validate and order from 100 to 50,000 steps, then see where the file stops being the right place for logic.

pandas needed 3.9 GB of peak memory to load a 1.3 GB CSV, and 0.18 GB to keep two typed columns. Measure it yourself with memory_usage and a rule of thumb.

What Sheets IMPORTDATA can and cannot do as a live feed from a CSV URL: format, refresh, auth, size, parsing quirks and a way to measure it for your data.

Export a 2,000,000 row table to CSV six ways: peak memory ranged from 11 MB to 2 GB, time from 1.6 s to 14 s. fetchall and pandas are the ones that run out.

An expression index on xpath turned a 245 ms scan into 1 ms on 50,000 documents and made loading 2.8 times slower. A generated column does the same.

orjson wrote a 35 MB document 6 times faster than json and parsed it 1.7 times faster. What it returns, what it rejects and what to check before migrating.

Four ways to sum 1.2 million order lines from a 127 MB XML file, with time and peak memory, plus the clearing pattern that keeps streaming flat.