runner · normalize_events.py

# normalize raw payment eventsdef normalize(event: dict) -> dict:    amount = float(event["amount"].replace(",", "."))    ts = parse_ts(event["ts"].strip())    country = event.get("country") or "unknown"    return {"amount": amount, "ts": ts, "country": country} clean = [normalize(e) for e in raw_events]

rawclean

"amount": "12,5"→amount: 12.5

"ts": " 2024-01-03 "→ts: 2024-01-03T00:00Z

"country": null→country: "unknown"

✓ 3 records · 0 dropped

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Python for Data Engineering — the MindsetWhat DE Python optimizes for (and what it ignores).Start here Records, Collections & Keyed DataDicts, sets, and grouping — the shapes every job is made of.Foundations Files, Paths & Payload IngestionRead CSV, JSON, and messy drops without corrupting them.Foundations Validation, Contracts & Error HandlingFail loudly, quarantine bad rows, keep the job alive.Building Incremental, Idempotent & Orchestrated PipelinesState, watermarks, and safe re-runs — production Python.Production

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Events normalization job

Clean and normalize raw event payloads into a stable analytics-ready structure.

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