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Python Code Samples

Easy snippets you can copy, study, and run in the browser editor.

31 matches
Observability & SRE easy

How to Redact Secrets from Log Messages in Python

Build a lightweight RedactingFormatter class that replaces sensitive tokens like passwords and API keys with [REDACTED] before log messages are printed.

redaction logging secrets
Python
class RedactingFormatter:
    def __init__(self, secrets):
        self.secrets = secrets

    def redact(self, message):
        for secret in self.secrets:
            message = message.replace(secret, "[REDACTED]")
        return message

    def format(self, record):
        message = record["message"]
        ret…
12 0 Open
Observability & SRE easy

How to Ship Logs to an Aggregator Endpoint in Python

Ship batched log entries to a mock HTTP aggregator endpoint with proper error handling and response status.

logging requests json
Python
import json
import requests
from datetime import datetime, timezone

LOG_ENTRIES = [
    {"timestamp": "2024-01-15T10:00:00Z", "level": "INFO", "message": "Server started"},
    {"timestamp": "2024-01-15T10:00:05Z", "level": "WARN", "message": "High memory usage"},
    {"timestamp": "2024-01-15T10:00:10Z", "level": "E…
13 0 Open
Observability & SRE easy

How to Use Log Levels DEBUG INFO WARNING ERROR in Python

Demonstrates Python's logging levels (DEBUG, INFO, WARNING, ERROR) with basicConfig and a logger, showing how severity filtering controls output.

logging log-levels observability
Python
import logging

# Configure a mock logger to demonstrate log levels
logging.basicConfig(level=logging.DEBUG, format="%(levelname)s: %(message)s")
logger = logging.getLogger("mock_logger")

# Simulate events at each severity level
logger.debug("Detailed diagnostic info")
logger.info("General system operation")
logger.w…
13 0 Open
Observability & SRE easy

Python Observability Data Helper for Beginners

A beginner-friendly Python helper to log events, record metrics, summarize observability data, and export it as JSON.

observability logging metrics
Python
import json
from datetime import datetime
from collections import defaultdict


class ObservabilityDataHelper:
    """Helper for exploring basic observability data patterns."""

    def __init__(self):
        self.events = []
        self.metrics = defaultdict(list)

    def log_event(self, service, level, message):
…
14 0 Open
Microservices patterns easy

Mock a Sidecar Logger with Python Metrics

Simulate a sidecar logger that tracks request counts, error rates, and endpoint hits, producing a metrics snapshot.

microservices monitoring metrics
Python
import random
import time
from collections import defaultdict


class SidecarLogger:
    def __init__(self):
        self.metrics = defaultdict(int)
        self.total_requests = 0
        self.error_count = 0

    def log_request(self, endpoint, status_code):
        """Simulate logging a request and updating metrics…
16 0 Open
Big data & Spark easy

How to Mock a User-Defined Function (UDF) in Python

Wrap a real UDF implementation with call logging to simulate and track invocations in a data pipeline.

udf mock testing
Python
from typing import Any, Callable


# Mock a user-defined function (UDF) that was previously complex or external
def mock_udf(name: str, implementation: Callable[..., Any], *, calls: list[Any]) -> Callable[..., Any]:
    """Wrap a real implementation with call logging to simulate a UDF."""
    def wrapper(*args: Any, *…
13 0 Open
ML engineering pipelines easy

How to Mock MLflow log_params and log_metrics in Python

Use unittest.mock to patch MLflow's log_param and log_metric, run the training function, and verify logging calls without touching a real tracking server.

mlflow mock testing
Python
from unittest.mock import Mock, patch
import mlflow


def train_model():
    mlflow.log_param("learning_rate", 0.01)
    mlflow.log_param("epochs", 10)
    mlflow.log_metric("accuracy", 0.95)
    mlflow.log_metric("loss", 0.05)
    return "Training completed"


if __name__ == "__main__":
    with patch("mlflow.log_par…
15 0 Open

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Samples are quick reference — one concept per page. For step-by-step teaching, use our Python tutorials. To test yourself, try quizzes or coding challenges. Clean up style with the Python formatter.