What level of proficiency in Python do you consider your professional competence?

Professional competence in Python usually implies a confident mastery of the language's core features, including:

• Knowledge of syntax and basic constructs (loops, conditions, functions).
• Working with primary data types and structures (lists, dictionaries, sets).
• Understanding object-oriented programming in Python.
• Ability to use standard libraries and write readable, maintainable code.
• Experience with popular frameworks or tools depending on specialization (e.g., Django, Flask, Pandas).

For DevOps specialists, skills in automation, scripting for deployment and monitoring are also important.

Regarding self-assessment, professional competence means being able to independently solve tasks, optimize code, and understand best practices in Python, rather than just performing basic exercises.