feat(telemetry): add anonymous opt-out PostHog telemetry #115
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Add lightweight, privacy-preserving usage telemetry to understand which engines, functions, and features are actually used. Zero new dependencies (stdlib urllib.request only). Fire-and-forget daemon threads ensure zero latency impact. - Create datafog/telemetry.py with PostHog /capture/ integration - Instrument detect, process, detect_pii, anonymize_text, scan_text, get_supported_entities, DataFog class, TextService, and CLI commands - Wire track_error() into exception handlers for error visibility - Opt-out via DATAFOG_NO_TELEMETRY=1 or DO_NOT_TRACK=1 - Anonymous ID via SHA-256 of machine info (no PII) - Text lengths bucketed, error messages never sent - Thread-local dedup prevents double-counting nested calls - Fix services/__init__.py to lazy-import ImageService and SparkService, so TextService works on minimal installs without aiohttp/PIL/pyspark - Fix pre-existing NameError in __init__.py detect() for RegexAnnotator - 44 tests covering opt-out, privacy, non-blocking, payloads, integration, error tracking, and edge cases Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
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Summary
datafog/telemetry.py: Anonymous, opt-out usage telemetry via PostHog's/capture/API using only stdlib (urllib.request) — zero new dependenciesdetect(),process(),DataFogclass,TextService, core functions, and all 5 CLI commandstrack_error()into exception handlers acrosscore.py,main.py, andclient.pyservices/__init__.py: Bare imports of heavy deps now wrapped intry/exceptdetect()in__init__.pyreferencedRegexAnnotatorwithout calling lazy importTest plan
DATAFOG_NO_TELEMETRY=1disables all telemetry