Reference library

Python Code Samples

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

11 matches
Strings & text easy

Automatically Detect Weak Passwords from Large Password Lists in Python

This Python script identifies weak passwords from a list by checking length, common patterns, sequential characters, and uniform characters, returning those that fail the security checks.

password security validation
Python
import re

COMMON_PASSWORDS_FILE = "common_passwords.txt"

def is_weak(password):
    # Check length
    if len(password) < 8:
        return True
    # Check for common patterns
    if password.lower() in {"password", "123456", "qwerty", "letmein", "admin", "welcome"}:
        return True
    # Check for sequential c…
55 0 Open
Files & data easy

Automatically Detect Corrupted Files Using SHA-256 Checksums in Python

Compute SHA-256 checksums of files and compare them to detect corruption in Python.

checksum file-integrity hashlib
Python
import hashlib
import os

def compute_sha256(filepath: str) -> str:
    """Compute SHA-256 checksum of a file."""
    sha256 = hashlib.sha256()
    with open(filepath, 'rb') as f:
        for chunk in iter(lambda: f.read(4096), b''):
            sha256.update(chunk)
    return sha256.hexdigest()

def validate_file_int…
60 1 Open
Files & data easy

Detect Outliers in CSV Data Using Z-Score in Python

Read a CSV file and detect outliers in a numeric column by computing z-scores, flagging those exceeding a given threshold — no machine learning required.

outlier-detection z-score csv
Python
import csv
import statistics
from math import sqrt

def detect_outliers(csv_path, column_name, threshold=2.0):
    """Detect outliers in a numeric column using z-score method."""
    values = []
    with open(csv_path, 'r', newline='') as f:
        reader = csv.DictReader(f)
        if column_name not in reader.field…
51 0 Open
Files & data easy

How to Detect File Encoding: UTF-8 vs Latin-1 in Python

Detect whether a file is UTF-8 or Latin-1 encoded by attempting a UTF-8 decode and falling back to Latin-1.

file-encoding utf-8 latin-1
Python
import sys

def detect_encoding(file_path):
    with open(file_path, 'rb') as f:
        raw = f.read()
    
    try:
        raw.decode('utf-8')
        return 'UTF-8'
    except UnicodeDecodeError:
        return 'latin1'

if __name__ == "__main__":
    file_path = sys.argv[1] if len(sys.argv) > 1 else 'sample.txt'
…
13 0 Open
Algorithms & data structures easy

How to Find Gaps Between Sorted Intervals in Python

This code finds gap ranges between sorted intervals using pairwise iteration, returning ranges where no interval covers.

intervals pairwise sorting
Python
from itertools import pairwise

def find_gaps(intervals):
    intervals = sorted(intervals)
    gaps = []
    for prev, curr in pairwise(intervals):
        if prev[1] < curr[0]:
            gaps.append((prev[1] + 1, curr[0] - 1))
    return gaps

if __name__ == "__main__":
    intervals = [(1, 3), (5, 7), (10, 12), (…
14 0 Open
Data pipelines & processing easy

How to detect anomalies in a column using z-score in Python

Detect outliers in a list of numbers using z-score statistics, flagging values that deviate significantly from the mean.

anomaly-detection z-score statistics
Python
import random

def z_score_anomaly_detection(data, threshold=2.0):
    """
    Detect anomalies in a list of numbers using z-score.
    """
    mean = sum(data) / len(data)
    variance = sum((x - mean) ** 2 for x in data) / len(data)
    std_dev = variance ** 0.5
    
    if std_dev == 0:
        return []
    
    a…
14 0 Open
Modern tooling easy

How to Load and Save CSV and JSON Files in Python

A beginner-friendly data helper that loads or saves CSV and JSON files using only the Python standard library, with automatic format detection from the file extension.

csv json file-io
Python
from pathlib import Path
import json
import csv


def load_data(file_path):
    """Load CSV or JSON data from disk based on file extension."""
    path = Path(file_path)
    if path.suffix == ".json":
        with path.open() as f:
            return json.load(f)
    elif path.suffix == ".csv":
        with path.open(…
13 0 Open
System design patterns easy

Create a Data Helper Class in Python

A reusable DataHelper class that saves and loads JSON and CSV files from a configurable base directory, with automatic header detection for CSV.

data-helper json csv
Python
import json
import csv
from pathlib import Path

class DataHelper:
    def __init__(self, base_path="."):
        self.base_path = Path(base_path)
        self.base_path.mkdir(exist_ok=True)

    def save_json(self, data, filename):
        path = self.base_path / filename
        with open(path, "w") as f:
          …
17 0 Open
System design patterns easy

Idempotent Consumer: Store Processed IDs in Python

Implement an idempotent consumer that persists processed message IDs to a JSON file, skipping duplicates on restart.

idempotency duplicate-detection state-persistence
Python
import json
from pathlib import Path


class IdempotentStore:
    def __init__(self, storage_path: str = "processed_ids.json"):
        self.storage_path = Path(storage_path)
        self.processed_ids = self._load()

    def _load(self) -> set:
        if self.storage_path.exists():
            with self.storage_path…
15 0 Open
Microservices patterns easy

Strangler Fig Migration Pattern in Python

Gradually reroute calls from a legacy service to a modern replacement using a runtime switch and feature detection.

migration facade microservices
Python
from dataclasses import dataclass

@dataclass
class PaymentService:
    def process(self, amount: float) -> str:
        return f"Legacy processed ${amount:.2f}"

class StranglerFig:
    def __init__(self):
        self._new_service = None

    def attach_new(self, service):
        self._new_service = service

    de…
15 0 Open
ML engineering pipelines easy

How to Trigger Model Retraining on Drift in Python

Automatically detects accuracy drift in a mock ML model and triggers retraining when performance falls below a threshold.

ml drift-detection retraining
Python
import random
import time

class MockModel:
    def __init__(self, name):
        self.name = name
        self.accuracy = 0.85
        self.version = 1

    def train(self, data_size):
        # Simulate training time and accuracy improvement
        time.sleep(0.1)
        drift = random.uniform(-0.02, 0.02)
       …
16 0 Open

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