Common Standard Library

Python · 8 entries

datetime Module

syntax

from datetime import datetime, date, timedelta

example

from datetime import datetime, timedelta

now = datetime.now()
print(now.strftime("%Y-%m-%d %H:%M"))

deadline = now + timedelta(days=7, hours=3)
print(f"Due: {deadline:%B %d, %Y}")

parsed = datetime.strptime("2026-04-04", "%Y-%m-%d")
print(parsed.date())

output

2026-04-04 14:30
Due: April 11, 2026
2026-04-04

Note For timezone-aware datetimes, use datetime.now(tz=timezone.utc) instead of datetime.utcnow() which is naive and deprecated since 3.12.

datetimecurrent dateformat dateparse datetimedeltadate arithmetic

collections Module

syntax

from collections import deque, OrderedDict, ChainMap

example

from collections import deque, ChainMap

# deque: efficient append/pop from both ends
buffer = deque(maxlen=3)
for n in range(5):
    buffer.append(n)
print(list(buffer))

# ChainMap: layered dict lookup
defaults = {"color": "blue", "size": 10}
overrides = {"color": "red"}
config = ChainMap(overrides, defaults)
print(config["color"], config["size"])

output

[2, 3, 4]
red 10

Note deque with maxlen auto-discards oldest items when full (ring buffer). ChainMap searches dicts in order, first match wins. Both are in collections.

dequeChainMapcollectionsring bufferlayered config

functools Module

syntax

from functools import lru_cache, partial, reduce

example

from functools import lru_cache, partial

@lru_cache(maxsize=128)
def fibonacci(n: int) -> int:
    if n < 2:
        return n
    return fibonacci(n - 1) + fibonacci(n - 2)

print(fibonacci(30))
print(fibonacci.cache_info())

# partial: pre-fill arguments
def power(base, exp):
    return base ** exp

square = partial(power, exp=2)
print(square(7))

output

832040
CacheInfo(hits=28, misses=31, maxsize=128, currsize=31)
49

Note lru_cache requires hashable arguments. For unhashable args, consider cachetools or a manual cache. partial is great for adapting callback signatures.

lru_cachememoizecache functionpartialfunctoolsreduce

re (Regular Expressions)

syntax

import re
re.search(pattern, string)
re.findall(pattern, string)

example

import re

text = "Contact: [email protected] or [email protected]"
emails = re.findall(r"[\w.]+@[\w.]+\.\w+", text)
print(emails)

# Named groups
log = "2026-04-04 ERROR: Connection timeout"
match = re.match(r"(?P<date>[\d-]+) (?P<level>\w+): (?P<msg>.+)", log)
if match:
    print(match.group("level"), match.group("msg"))

output

['[email protected]', '[email protected]']
ERROR Connection timeout

Note Always use raw strings (r'...') for regex patterns. For repeated use, compile with re.compile() for performance. Use re.VERBOSE for readable multi-line patterns.

regexregular expressionpattern matchingfindallsearch textre module

typing Module Essentials

syntax

from typing import Optional, Union, TypeVar, Generic

example

from typing import TypeVar, Generic

T = TypeVar("T")

class Stack(Generic[T]):
    def __init__(self) -> None:
        self._items: list[T] = []

    def push(self, item: T) -> None:
        self._items.append(item)

    def pop(self) -> T:
        return self._items.pop()

stack = Stack[int]()
stack.push(42)
print(stack.pop())

output

Note Since 3.10, use X | Y instead of Union[X, Y]. Since 3.12, use the type parameter syntax: class Stack[T]: instead of TypeVar + Generic.

typing modulegenericsTypeVarOptionalUniontype checking

os and os.path

syntax

import os
os.path.join()
os.environ

example

import os

# Environment variables
db_host = os.environ.get("DB_HOST", "localhost")
print(f"DB: {db_host}")

# Path operations (prefer pathlib for new code)
print(os.path.expanduser("~"))
print(os.path.splitext("report.pdf"))
print(os.getcwd())

output

DB: localhost
/Users/username
('report', '.pdf')
/current/directory

Note Prefer pathlib.Path for path manipulation in new code. os.environ provides direct access to environment variables. Use os.getenv() for safe access with defaults.

os moduleenvironment variablefile pathos.pathworking directory

json Module (Detailed)

syntax

json.dumps(obj, indent=2)
json.loads(string)

example

import json
from datetime import datetime

# Custom serializer for non-JSON types
def custom_encoder(obj):
    if isinstance(obj, datetime):
        return obj.isoformat()
    raise TypeError(f"Not serializable: {type(obj)}")

event = {"name": "Launch", "when": datetime(2026, 4, 4, 12, 0)}
print(json.dumps(event, default=custom_encoder, indent=2))

output

{
  "name": "Launch",
  "when": "2026-04-04T12:00:00"
}

Note json.dumps raises TypeError for non-serializable types. Pass default= for custom serialization. For complex cases, subclass json.JSONEncoder.

json dumpsjson loadsserializecustom json encoderjson datetime

subprocess Module

syntax

import subprocess
subprocess.run([cmd, args], capture_output=True)

example

import subprocess

result = subprocess.run(
    ["echo", "Hello from subprocess"],
    capture_output=True, text=True
)
print(result.stdout.strip())
print(f"Return code: {result.returncode}")

output

Hello from subprocess
Return code: 0

Note Always pass commands as a list, not a string. Use shell=True only when absolutely necessary — it introduces shell injection risks.

subprocessrun commandshell commandexecute processcapture output