IICTI Certified Python Developer

Holders demonstrate that they can apply and evaluate cPython runtime internals and memory model, advanced static typing and type-system design, concurrency, asyncio and structured concurrency architecture and performance profiling and native acceleration, plus 7 further areas, in realistic professional scenarios, as defined in the AQSCERT scheme for Python Developer.

Who it is for: Professionals working, or preparing to work, in software development roles.

1. 01CPython runtime internals and memory model13% of the exam

   • Diagnose behavioural and performance anomalies by reasoning about how CPython executes and manages objects.
   • Scope: Bytecode and the specialising adaptive interpreter (PEP 659), reference counting and cyclic GC, object layout and descriptor protocol, GIL behaviour, free-threaded builds (PEP 703), experimental JIT (PEP 744) and subinterpreters (PEP 734).
2. 02Advanced static typing and type-system design6% of the exam

   • Design type-safe public APIs and lead the incremental adoption of strict typing across large codebases.
   • Scope: PEP 695 generic syntax and type aliases, variance, ParamSpec and TypeVarTuple, Protocols, TypedDict with Required/ReadOnly, TypeIs narrowing (PEP 742), overloads, dataclass_transform, mypy/pyright strict mode and gradual adoption strategies.
3. 03Concurrency, asyncio and structured concurrency architecture9% of the exam

   • Architect concurrent Python services that remain correct under cancellation, failure and load.
   • Scope: asyncio event loop internals, TaskGroup and structured concurrency, cancellation and timeout semantics, anyio/trio, backpressure and bounded queues, threads vs processes vs free-threading, concurrent.futures, uvloop.
4. 04Performance profiling and native acceleration7% of the exam

   • Evaluate performance bottlenecks with evidence and select the optimisation or native-acceleration strategy with the best cost-benefit.
   • Scope: Statistical and deterministic profiling (py-spy, Scalene, cProfile), memory profiling (memray, tracemalloc), Linux perf integration, NumPy vectorisation, Cython, mypyc, Rust extensions with PyO3/maturin, benchmarking discipline (pyperf).
5. 05Metaprogramming and language extension mechanisms9% of the exam

   • Design framework-level abstractions with metaprogramming while preserving debuggability, typing and maintainability.
   • Scope: Descriptors and __set_name__, __init_subclass__, metaclasses, signature-preserving decorators, context managers and contextvars, import hooks and module finders, AST inspection and transformation, framework-style declarative APIs.
6. 06Packaging, dependency resolution and distribution engineering10% of the exam

   • Architect reproducible build, release and distribution pipelines for libraries and applications, including native extensions.
   • Scope: pyproject.toml (PEP 621), build backends (hatchling, setuptools, scikit-build-core), wheels, manylinux and cibuildwheel, lockfiles with uv and PEP 751 pylock.toml, PEP 723 inline script metadata, PyPI trusted publishing and PEP 740 attestations.
7. 07Test architecture and quality engineering for Python systems13% of the exam

   • Design test strategies that give high confidence in correctness across Python versions, platforms and dependency sets.
   • Scope: pytest fixture and plugin architecture, property-based testing (Hypothesis), mutation testing (mutmut), contract and snapshot testing, branch coverage analysis, nox/tox matrices across interpreters, Ruff-based static quality gates.
8. 08High-performance API and service design13% of the exam

   • Architect Python web and RPC services that meet latency, throughput and reliability targets in production.
   • Scope: ASGI internals (Starlette, FastAPI), Pydantic v2 validation core, Django async views and ORM, SQLAlchemy 2.0 async sessions and N+1 avoidance, gRPC services, connection pooling, caching layers, OpenTelemetry instrumentation.
9. 09Data-intensive and distributed Python engineering6% of the exam

   • Evaluate and design data-processing pipelines that scale from a single node to clusters with predictable memory use.
   • Scope: Apache Arrow memory model, Polars lazy and streaming execution, pandas 2 with Arrow-backed dtypes, DuckDB, out-of-core processing, distributed execution with Dask and Ray, serialisation formats (Parquet).
10. 10Secure coding and supply chain security in Python8% of the exam

    • Assess Python code and dependency trees for security weaknesses and define enforceable secure-development controls.
    • Scope: Unsafe deserialisation (pickle, YAML), injection and SSRF, secrets handling, Bandit and Semgrep rules, pip-audit and OSV, hash-pinned installs, dependency confusion and typosquatting defences, OWASP ASVS 5.0 alignment.
11. 11Large codebase architecture and Python engineering leadership6% of the exam

    • Lead the architectural evolution of large Python codebases and the engineering standards of the teams that own them.
    • Scope: Modular monolith boundaries enforced with import-linter, hexagonal architecture, entry-point plugin systems, API deprecation and versioning policy, interpreter upgrade programmes, code review standards, engagement with the PEP process.

Question types

Single choice 100%

Delivery

Online (remote proctored), Test centre, On-site (corporate)

Retakes

Up to three attempts within any 12-month period. A 14-day waiting period applies after a first unsuccessful attempt and 30 days after a second. Each retake requires a new booking and fee. Retakes draw a different randomised form from the question bank.

Provisional cut score — psychometric validation is required before live delivery. Blueprint v1.0.

1. 1

   Register

   Create a free account and start the programme.

2. 2

   Practice

   Online practice test (coming soon).

3. 3

   Training

   Optional

   Online course or classroom — or skip it.

4. 4

   Certification

   Independent exam and certification decision.

Training is optional and does not by itself confer certification. Find a training partner