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) 2. [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) 3. [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) 4. [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) 5. [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) 6. [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()) 7. [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) 8. [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](https://docs.python.org/3/whatsnew/3.11.html) 2. [PEP 8 Style Guide](https://peps.python.org/pep-0008/) 3. [Python Wiki - Performance Tips](https://wiki.python.org/moin/PythonSpeed/PerformanceTips) 4. [Real Python - Async IO](https://realpython.com/async-io-python/) 5. [Real Python - LEGB Rule](https://realpython.com/python-scope-legb-rule/) 6. [Real Python - String Concatenation](https://realpython.com/python-string-concatenation/) 7. [Python Tutorial - Data Structures](https://docs.python.org/3/tutorial/datastructures.html) 8. [CPython Exception Handling](https://github.com/python/cpython/blob/main/InternalDocs/exception_handling.md) 9. [DataCamp - Python Generators](https://www.datacamp.com/tutorial/python-generators) 10. [JetBrains - Performance Hacks](https://blog.jetbrains.com/pycharm/2025/11/10-smart-performance-hacks-for-faster-python-code/)