Python

Python 3.11 Best Practices

Comprehensive performance optimization guide for Python 3.11+ applications. Contains 42 rules across 8 categories, prioritized by impact to guide automated refactoring and code generation.

When to Apply

Reference these guidelines when:

• Writing new Python async I/O code
• Choosing data structures for collections
• Optimizing memory usage in data-intensive applications
• Implementing concurrent or parallel processing
• Reviewing Python code for performance issues

Rule Categories by Priority

| Priority | Category | Impact | Prefix | |----------|----------|--------|--------| | 1 | I/O & Async Patterns | CRITICAL | io- | | 2 | Data Structure Selection | CRITICAL | ds- | | 3 | Memory Optimization | HIGH | mem- | | 4 | Concurrency & Parallelism | HIGH | conc- | | 5 | Loop & Iteration | MEDIUM | loop- | | 6 | String Operations | MEDIUM | str- | | 7 | Function & Call Overhead | LOW-MEDIUM | func- | | 8 | Python Idioms & Micro | LOW | py- |

Table of Contents

1. [I/O & Async Patterns](references/_sections.md#1-io--async-patterns) — CRITICAL

• 1.1 [Defer await Until Value Needed](references/io-defer-await.md) — CRITICAL (2-5× faster for dependent operations)
• 1.2 [Use aiofiles for Async File Operations](references/io-aiofiles.md) — CRITICAL (prevents event loop blocking)
• 1.3 [Use asyncio.gather() for Concurrent I/O](references/io-async-gather.md) — CRITICAL (2-10× throughput improvement)
• 1.4 [Use Connection Pooling for Database Access](references/io-connection-pooling.md) — CRITICAL (100-200ms saved per connection)
• 1.5 [Use Semaphores to Limit Concurrent Operations](references/io-semaphore.md) — CRITICAL (prevents resource exhaustion)
• 1.6 [Use uvloop for Faster Event Loop](references/io-uvloop.md) — CRITICAL (2-4× faster async I/O)

1. [Data Structure Selection](references/_sections.md#2-data-structure-selection) — CRITICAL

• 2.1 [Use bisect for O(log n) Sorted List Operations](references/ds-bisect-sorted.md) — CRITICAL (O(n) to O(log n) search)
• 2.2 [Use defaultdict to Avoid Key Existence Checks](references/ds-defaultdict.md) — CRITICAL (eliminates redundant lookups)
• 2.3 [Use deque for O(1) Queue Operations](references/ds-deque-for-queue.md) — CRITICAL (O(n) to O(1) for popleft)
• 2.4 [Use Dict for O(1) Key-Value Lookup](references/ds-dict-for-lookup.md) — CRITICAL (O(n) to O(1) lookup)
• 2.5 [Use frozenset for Hashable Set Keys](references/ds-frozenset-for-hashable.md) — CRITICAL (enables set-of-sets patterns)
• 2.6 [Use Set for O(1) Membership Testing](references/ds-set-for-membership.md) — CRITICAL (O(n) to O(1) lookup)

1. [Memory Optimization](references/_sections.md#3-memory-optimization) — HIGH

• 3.1 [Intern Repeated Strings to Save Memory](references/mem-intern-strings.md) — HIGH (reduces duplicate string storage)
• 3.2 [Use __slots__ for Memory-Efficient Classes](references/mem-slots.md) — HIGH (20-50% memory reduction per instance)
• 3.3 [Use array.array for Homogeneous Numeric Data](references/mem-array-for-numeric.md) — HIGH (4-8× memory reduction for numbers)
• 3.4 [Use Generators for Large Sequences](references/mem-generators.md) — HIGH (100-1000× memory reduction)
• 3.5 [Use weakref for Caches to Prevent Memory Leaks](references/mem-weak-references.md) — HIGH (prevents unbounded cache growth)

1. [Concurrency & Parallelism](references/_sections.md#4-concurrency--parallelism) — HIGH

• 4.1 [Use asyncio for I/O-Bound Concurrency](references/conc-asyncio-for-io.md) — HIGH (300% throughput improvement for I/O)
• 4.2 [Use multiprocessing for CPU-Bound Parallelism](references/conc-multiprocessing-cpu.md) — HIGH (4-8× speedup on multi-core systems)
• 4.3 [Use Queue for Thread-Safe Communication](references/conc-queue-communication.md) — HIGH (prevents race conditions)
• 4.4 [Use TaskGroup for Structured Concurrency](references/conc-taskgroup.md) — HIGH (prevents resource leaks on failure)
• 4.5 [Use ThreadPoolExecutor for Blocking Calls in Async](references/conc-threadpool-blocking.md) — HIGH (prevents event loop blocking)

1. [Loop & Iteration](references/_sections.md#5-loop--iteration) — MEDIUM

• 5.1 [Hoist Loop-Invariant Computations](references/loop-hoist-invariants.md) — MEDIUM (avoids N× redundant work)
• 5.2 [Use any() and all() for Boolean Aggregation](references/loop-any-all.md) — MEDIUM (O(n) to O(1) best case)
• 5.3 [Use dict.items() for Key-Value Iteration](references/loop-dict-items.md) — MEDIUM (single lookup vs double lookup)
• 5.4 [Use enumerate() for Index-Value Iteration](references/loop-enumerate.md) — MEDIUM (cleaner code, avoids index errors)
• 5.5 [Use itertools for Efficient Iteration Patterns](references/loop-itertools.md) — MEDIUM (2-3× faster iteration patterns)
• 5.6 [Use List Comprehensions Over Explicit Loops](references/loop-comprehension.md) — MEDIUM (2-3× faster iteration)

1. [String Operations](references/_sections.md#6-string-operations) — MEDIUM

• 6.1 [Use f-strings for Simple String Formatting](references/str-fstring.md) — MEDIUM (20-30% faster than .format())
• 6.2 [Use join() for Multiple String Concatenation](references/str-join-concatenation.md) — MEDIUM (4× faster for 5+ strings)
• 6.3 [Use str.startswith() with Tuple for Multiple Prefixes](references/str-startswith-tuple.md) — MEDIUM (single call vs multiple comparisons)
• 6.4 [Use str.translate() for Character-Level Replacements](references/str-translate.md) — MEDIUM (10× faster than chained replace())

1. [Function & Call Overhead](references/_sections.md#7-function--call-overhead) — LOW-MEDIUM

• 7.1 [Reduce Function Calls in Tight Loops](references/func-reduce-calls.md) — LOW-MEDIUM (100ms savings per 1M iterations)
• 7.2 [Use functools.partial for Pre-Filled Arguments](references/func-partial.md) — LOW-MEDIUM (50% faster debugging via introspection)
• 7.3 [Use Keyword-Only Arguments for API Clarity](references/func-keyword-only.md) — LOW-MEDIUM (prevents positional argument errors)
• 7.4 [Use lru_cache for Expensive Function Memoization](references/func-lru-cache.md) — LOW-MEDIUM (avoids repeated computation)

1. [Python Idioms & Micro](references/_sections.md#8-python-idioms--micro) — LOW

• 8.1 [Leverage Zero-Cost Exception Handling](references/py-zero-cost-exceptions.md) — LOW (zero overhead in happy path (Python 3.11+))
• 8.2 [Prefer Local Variables Over Global Lookups](references/py-local-variables.md) — LOW (faster name resolution)
• 8.3 [Use dataclass for Data-Holding Classes](references/py-dataclass.md) — LOW (reduces boilerplate by 80%)
• 8.4 [Use Lazy Imports for Faster Startup](references/py-lazy-import.md) — LOW (10-15% faster startup)
• 8.5 [Use match Statement for Structural Pattern Matching](references/py-match-statement.md) — LOW (reduces branch complexity)
• 8.6 [Use Walrus Operator for Assignment in Expressions](references/py-walrus-operator.md) — LOW (eliminates redundant computations)

References

1. Python 3.11 Release Notes
2. PEP 8 Style Guide
3. Python Wiki - Performance Tips
4. Real Python - Async IO
5. Real Python - LEGB Rule
6. Real Python - String Concatenation
7. Python Tutorial - Data Structures
8. CPython Exception Handling
9. DataCamp - Python Generators
10. JetBrains - Performance Hacks

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: pproenca
• Source: pproenca/dot-skills
• License: MIT

Install and usage instructions live in the source repository linked above.