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How to Build a Simple Decorator That Logs Function Calls in Python
This code shows how to create a reusable decorator that logs each function call, including arguments, return value, and execution time.
import functools
import time
def log_calls(func):
@functools.wraps(func)
def wrapper(*args, **kwargs):
print(f"Calling {func.__name__} with args={args}, kwargs={kwargs}")
start = time.time()
result = func(*args, **kwargs)
end = time.time()
print(f"{func.__name__} return…How to Configure Python Logging with File Rotation
A complete demo that sets up a logger with a rotating file handler, writes several log entries, and shows the contents of the current log file.
import logging
from logging.handlers import RotatingFileHandler
logger = logging.getLogger("rotating_logger")
logger.setLevel(logging.DEBUG)
file_handler = RotatingFileHandler(
"app.log",
maxBytes=100,
backupCount=3
)
file_handler.setFormatter(
logging.Formatter("%(asctime)s - %(levelname)s - %(messa…How to Debug Print Behind a DEBUG Environment Flag in Python
Create a debug_print function that only outputs when the DEBUG environment variable is set to a truthy value like 1, true, yes, or on.
import os
def debug_print(*args, **kwargs):
"""Print only when DEBUG environment variable is set to a truthy value."""
if os.environ.get("DEBUG", "").lower() in ("1", "true", "yes", "on"):
print(*args, **kwargs)
if __name__ == "__main__":
# Example usage: run as `DEBUG=1 python script.py` to se…How to Log Exceptions with traceback.format_exc in Python
Capture and log a full traceback string when an exception occurs using Python's traceback.format_exc() and logging module.
import traceback
import logging
def risky_operation(value):
return 10 / value
logging.basicConfig(level=logging.ERROR, format='%(asctime)s - %(levelname)s - %(message)s')
def main():
try:
result = risky_operation(0)
print(f"Result: {result}")
except ZeroDivisionError:
error_msg =…How to Serialize an Exception to a JSON-Safe Dict in Python
Convert any Python exception into a JSON-safe dictionary with type, message, and the last few traceback lines for logging.
import json
import traceback
from typing import Any
def exception_to_dict(exc: Exception) -> dict[str, Any]:
"""Convert an exception into a JSON-safe dictionary."""
return {
"type": type(exc).__name__,
"message": str(exc),
"traceback": traceback.format_exc().strip().split("\n")[-3:],
…Log to stderr with Python logging basicConfig
Configure Python's logging module to send all log messages to standard error (stderr) instead of the default stderr, with a readable timestamped format.
import logging
def main():
logging.basicConfig(
level=logging.DEBUG,
format="%(asctime)s — %(name)s — %(levelname)s — %(message)s",
stream=__import__("sys").stderr,
)
logger = logging.getLogger("example")
logger.debug("Debug message")
logger.info("Info message")
logger.…Append a Line to a Log File in Python
Append a line to a file using a context manager and Path.open().
from pathlib import Path
def append_to_log(filepath, message):
with Path(filepath).open("a") as log_file:
log_file.write(f"{message}\n")
if __name__ == "__main__":
log_path = "log.txt"
append_to_log(log_path, "First entry")
append_to_log(log_path, "Second entry")
# Verify contents
…How to Implement the Decorator Pattern in Python to Add Behavior
This Python code demonstrates the decorator pattern by wrapping a function to add logging behavior without modifying the original function.
import functools
def logger(func):
@functools.wraps(func)
def wrapper(*args, **kwargs):
print(f"Calling {func.__name__} with {args} {kwargs}")
result = func(*args, **kwargs)
print(f"{func.__name__} returned {result}")
return result
return wrapper
@logger
def add(a, b):
…How to Log Prompts and Completions as JSONL Audit Files in Python
Read a JSONL file of LLM prompt–completion pairs, compute totals and averages, then write an audit summary with timestamps.
import json
from pathlib import Path
from datetime import datetime
def audit_jsonl(filepath):
logs = []
with open(filepath, encoding="utf-8") as f:
for line in f:
line = line.strip()
if not line:
continue
entry = json.loads(line)
logs.ap…How to Serialize Chat Messages to a JSON File in Python
Writes a list of chat message dicts to a JSON file with metadata like export time and message count.
import json
from pathlib import Path
from datetime import datetime
def serialize_messages(messages, output_path):
data = {
"exported_at": datetime.now().isoformat(),
"count": len(messages),
"messages": messages
}
Path(output_path).write_text(
json.dumps(data, indent=2, ensu…How to Tail and Colorize Error Lines in Python
Reads the last N lines of a log file and prints error lines in red using ANSI color codes.
import sys
import time
from pathlib import Path
def tail_colorize(filename: str, lines: int = 20) -> None:
"""Read last N lines of a file, printing errors in red."""
path = Path(filename)
if not path.exists():
print(f"File '{filename}' not found.", file=sys.stderr)
return
# Read last …Monitor Website Uptime with Python
Periodically check if a website is reachable and its HTTP status is 200, logging the status with timestamps.
import requests
import time
def check_website(url):
try:
response = requests.get(url, timeout=5)
if response.status_code == 200:
return True
else:
return False
except requests.ConnectionError:
return False
except requests.Timeout:
return Fals…How to List Failed Records in a Dead Letter Queue Mock in Python
A mock Dead Letter Queue stores failed processing records with error details and timestamps, lists them, and exports to JSON.
import json
from datetime import datetime, timedelta
import random
class DeadLetterQueue:
def __init__(self):
self.failed_records = []
def add_failed_record(self, record_id, payload, error_message):
self.failed_records.append({
"record_id": record_id,
"payload": paylo…Build a Simple Log Graph in Python
Create a basic one-dimensional bar chart from log lines by counting occurrences of leading numeric keys.
import heapq
def log_graph(log_lines: list[str]) -> str:
"""Build a simple per-line, one-dimensional visual graph from log entries."""
counts: dict[int, int] = {}
for line in log_lines:
tokens = line.split()
if tokens:
try:
idx = int(tokens[0])
exce…Mock AWS Spot Instance Interruption Handler in Python
A Python class that simulates AWS Spot instance interruption checks, handling the 10% chance of termination, logging state-saving, and storing notice details.
import time
import random
class SpotInstanceHandler:
def __init__(self, instance_id):
self.instance_id = instance_id
self.interruption_notices = []
def start(self):
print(f"Spot instance {self.instance_id} started")
def check_interruption(self):
# Simulate random interrup…How to Capture Logging Records with pytest caplog in Python
Capture and assert on logging records in pytest using the built-in caplog fixture.
import logging
import pytest
def divide(a, b):
"""Divide two numbers and log an error if b is zero."""
if b == 0:
logging.error("Division by zero attempted")
return None
logging.info(f"Dividing {a} by {b}")
return a / b
def test_divide_logs_error(caplog):
with caplog.at_level(logg…How to Add a Correlation ID Tracing Header in Python
A mock middleware generates or preserves a correlation ID header and logs structured JSON messages with it for API request tracing.
import uuid
import json
from dataclasses import dataclass, field
from typing import Optional
@dataclass
class Request:
headers: dict = field(default_factory=dict)
def get(self, key, default=None):
return self.headers.get(key, default)
class CorrelationIdMiddleware:
def __init__(self, header_name…Calculate Error Rate from Log Stream in Python
Parses a mock log stream to count errors and compute the error percentage using a rolling window of recent entries.
import re
from collections import deque
def error_rate_from_log_stream(message):
log_pattern = r'^\[(\d{4}-\d{2}-\d{2} \d{2}:\d{2}:\d{2})\] (ERROR|INFO|DEBUG): (.*)$'
recent_entries = deque(maxlen=100)
error_count = 0
total_count = 0
for line in message.strip().split('\n'):
match = re.mat…How to Add Metadata Attributes to a Span in Python
Create a lightweight dataclass-based Span mock that stores key-value metadata attributes for tracing or event logging.
from dataclasses import dataclass, field
from typing import Dict, Any
@dataclass
class Span:
name: str
attributes: Dict[str, Any] = field(default_factory=dict)
def set_attribute(self, key: str, value: Any) -> None:
self.attributes[key] = value
def get_attribute(self, key: str) -> Any…How to Compute SRE Metrics Like Error Rate and Availability in Python
Tracks log events in a sliding time window and calculates error rate per second and availability percentage using an easy-to-follow class.
from collections import deque
from datetime import datetime, timedelta
from typing import Dict, Deque
class LogMetrics:
"""Simple observability helper to track log events and calculate SRE metrics."""
def __init__(self, window_seconds: int = 60):
self.window_seconds = window_seconds
self.eve…How to Do Structured JSON Line Logging in Python
Create a simple JSON-lines logger that writes one JSON object per line to stdout with timestamp, level, message, and custom context fields.
import json
import sys
from datetime import datetime
class JsonLineLogger:
def __init__(self, stream=sys.stdout):
self.stream = stream
def log(self, level, message, **context):
record = {
"timestamp": datetime.utcnow().isoformat() + "Z",
"level": level,
"me…How to Do Structured JSON Logging in Python
Create a custom logging formatter that outputs each log entry as a single JSON line with timestamp, level, logger name, and message.
import json
import logging
from datetime import datetime
class JsonFormatter(logging.Formatter):
def format(self, record):
log_entry = {
"timestamp": datetime.utcnow().isoformat() + "Z",
"level": record.levelname,
"logger": record.name,
"message": record.ge…How to Model Span Events in Python
Define a Span class with timestamped milestone events and a completion marker to track operation lifecycle.
import time
from dataclasses import dataclass, field
from enum import Enum
from typing import List
class SpanStatus(Enum):
STARTED = "started"
COMPLETED = "completed"
@dataclass
class SpanEvent:
name: str
timestamp: float = field(default_factory=time.time)
attributes: dict = field(default_facto…How to Parse Log Lines with Regex in Python
Extracts timestamp, log level, service name, and message from a log line using compiled regex named groups.
import re
LOG_PATTERN = re.compile(
r'^(?P<timestamp>\d{4}-\d{2}-\d{2} \d{2}:\d{2}:\d{2}) '
r'\[(?P<level>\w+)\] '
r'\((?P<service>[^)]+)\) '
r'(?P<message>.*)$'
)
def parse_log_line(line: str) -> dict:
match = LOG_PATTERN.match(line)
if not match:
return {"error": "invalid log format…Browse by section
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