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Python

Backend Since Jan 2016
L4
76/100

Other technologies

Flask Python

Evidence

  • Why this level

    Summary

    Python has been practiced continuously since 2019 — 7 years of active use. L4 is defensible because the skill spans several demanding registers: contributions to a production open-source ecosystem (GeoNature: Flask, SQLAlchemy, GeoAlchemy2, Marshmallow, Alembic, Celery), a configuration-driven scraping pipeline (ERON: Selenium, Pandas, Pygsheets, dynamic column detection), and industrialization of a scientific analysis chain (ISM Chaire4: scipy, multi-format I/O, biomechanical event detection). Regular practice includes code review, understanding of architectural patterns, and the ability to produce well-structured implementations independently.

  • Current ceiling

    Summary

    The public corpus does not yet show a published Python library or a reusable cross-product architecture. Advanced patterns (async Python, typing Protocol, metaclasses, large-scale memory optimization) are not publicly documented.

  • Incremental imports and validation

    PR Source

    The incremental import update added in GeoNature handles file validation, field mapping and execution context.

  • Admin backend and permissions

    PR Source

    The admin-side filter added in gn_module_export targets users and groups attached to the GeoNature application.

  • Monitoring backend optimization

    PR Source

    The route rewrite in gn_module_monitoring reduces an overly heavy query and covers the fix with tests.

  • Bulk processing and idempotence

    PR Source

    The bulk-import logic in TaxHub optimizes cd_nom processing with batch validation, idempotent insertion and admin statistics.

  • Centralized error handling

    PR Source

    The utility layer in UsersHub centralizes backend error handling in a reusable way.

  • Automation scripts

    Project Source

    Scripts developed during the past experience at ERON Santé use Python for scraping, Google Sheets automation and data transformation.