python3-data
Python Data
Load python3-core for standing defaults. Load python3-typing for boundary schemas. Load python3-testing for parser and edge-case tests.
Quality Checklist
- Schema validated at first stable ingress point — not deep in transforms
-
dtype=explicit inpd.read_csv()/pd.read_excel()— never rely on inference - No raw
pd.DataFramecrossing module boundaries without documented column contract - Merge/join results checked for unexpected nulls and row count changes
-
model_config = {"strict": True}on all Pydantic boundary models - No
inplace=True— deprecated, returnsNone, causes silent bugs - Notebook logic that survived 3+ uses extracted into tested modules
Gotchas
| Trap | What to do instead |
|---|---|
df["a"]["b"] = x (chained indexing) |
df.loc[:, "b"] = x — chained indexing silently fails |
.apply(lambda) on large frames |
Vectorized ops first; .apply() only when no vectorized path exists |
pd.merge() without post-check |
Assert no unexpected nulls or duplicate keys after merge |
df.drop(..., inplace=True) |
df = df.drop(...) — inplace is deprecated and returns None |
Bare pd.read_csv(path) |
Always pass dtype= to prevent silent type inference errors |
Decision Table
| Task | Use | Not |
|---|---|---|
| Tabular < 1M rows | pandas | Polars (overhead not justified) |
| Tabular > 1M rows or need speed | Polars | pandas |
| SQL-like analytics on local files | DuckDB | Loading everything into pandas |
| Read-only TOML config | tomllib (stdlib, binary mode "rb") |
tomlkit |
| Read/write TOML preserving comments | tomlkit (text mode) |
tomllib |
Module Layout
etl/
├── ingest.py # raw data loading (boundary)
├── validate.py # schema validation (boundary)
├── transform.py # business logic (typed core)
├── load.py # output writing (boundary)
└── types.py # shared typed models
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