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Copy-ready Python snippets by topic and difficulty — short, focused, and runnable in the browser editor.
How to Truncate Text to a Token Budget in Python
Truncate a string to a maximum token budget for LLM context using the tiktoken library and OpenAI's tokenizer.
import tiktoken
def truncate_to_token_budget(text, max_tokens, model="gpt-3.5-turbo"):
enc = tiktoken.encoding_for_model(model)
tokens = enc.encode(text)
if len(tokens) <= max_tokens:
return text
truncated_tokens = tokens[:max_tokens]
return enc.decode(truncated_tokens)
if __name__ == "__…How to cache embeddings with a Python dict to avoid recomputation
Caches embeddings computed from text in a dictionary keyed by SHA-256 hash, returning cached results for repeated calls.
import hashlib
import time
class EmbeddingCache:
def __init__(self):
self.cache = {}
def _hash_text(self, text):
return hashlib.sha256(text.encode()).hexdigest()
def get_embedding(self, text, compute_func):
key = self._hash_text(text)
if key not in self.cache:
…How to compute ROUGE recall in Python
Compute ROUGE recall by counting token overlap between a reference and candidate summary with pure Python.
def rouge_recall(reference, candidate):
ref_tokens = reference.lower().split()
cand_tokens = candidate.lower().split()
ref_counts = {}
for token in ref_tokens:
ref_counts[token] = ref_counts.get(token, 0) + 1
cand_counts = {}
for token in cand_tokens:
cand_counts[token] = cand…How to compute exact match metric in Python
Computes the exact match (EM) metric for LLM outputs by normalizing text and comparing predictions against references.
def compute_exact_match(predictions, references):
def normalize(text):
import re
text = text.lower().strip()
text = re.sub(r'\b(a|an|the)\b', ' ', text)
text = re.sub(r'[^a-z0-9\s]', '', text)
text = ' '.join(text.split())
return text
matches = sum(1 for pred, r…Parse ReAct Logs into Thought Action Observation Steps in Python
Parse a ReAct agent's textual log into structured steps with thought, action, and observation using regex and named tuples.
import re
from collections import namedtuple
ReActStep = namedtuple("ReActStep", ["thought", "action", "observation"])
def parse_react_log(log: str) -> list[ReActStep]:
"""Parse a ReAct log into structured thought/action/observation steps."""
pattern = re.compile(
r"Thought:\s*(?P<thought>.+?)\s*"
…Prepare LLM prompt data with a Python helper class
A beginner-friendly Python class that collects records, converts them to JSON, and produces a quick summary for building LLM prompt context.
import json
from typing import Any, Dict, List
class DataHelper:
"""Simple helper to prepare data for LLM prompts."""
def __init__(self):
self.data = []
def add(self, item: Dict[str, Any]) -> "DataHelper":
self.data.append(item)
return self
def to_json(self) -> s…Serialize and Format Data for LLM Prompts in Python
Use dataclasses and the json module to convert Python objects to JSON strings, parse them back, and format structured data into prompt-friendly text for LLM calls.
import json
from dataclasses import dataclass, asdict
@dataclass
class Recipe:
"""Simple data model to represent a recipe."""
name: str
cuisine: str
prep_minutes: int
def to_json(recipe: Recipe) -> str:
"""Serialize a Recipe to a JSON string."""
return json.dumps(asdict(recipe), indent=2)
…Build a Website Accessibility Scanner Using Python
Scans a webpage for common accessibility issues like missing alt text, headings, labels, and landmarks using only Python.
import requests
from urllib.parse import urljoin
from html.parser import HTMLParser
import re
class AccessibilityParser(HTMLParser):
def __init__(self):
super().__init__()
self.images_without_alt = []
self.missing_headings = True
self.has_main_tag = False
self.label_for_inp…Convert DOCX to Text by Unzipping XML in Python
Extract plain text from a .docx file by unzipping the container and parsing word/document.xml with regex, using only Python's standard library.
import zipfile
import re
from pathlib import Path
def docx_to_text_unzip_xml(docx_path: str) -> str:
"""Extract plain text from a .docx file by unzipping and parsing document.xml."""
docx_path = Path(docx_path)
if not docx_path.exists():
raise FileNotFoundError(f"File not found: {docx_path}")
…How to Build a Simple argparse CLI in Python
Build a beginner-friendly command-line tool with argparse that greets a user, with optional greeting text and uppercase output.
import argparse
def greet(name, greeting="Hello", uppercase=False):
message = f"{greeting}, {name}!"
if uppercase:
message = message.upper()
return message
if __name__ == "__main__":
parser = argparse.ArgumentParser(description="Simple CLI greeting tool")
parser.add_argument("name", help=…How to Build an argparse CLI That Filters File Lines by Keyword in Python
This Python script is a command-line tool built with argparse that reads a text file and prints only the lines that contain (or don't contain) a given keyword.
import argparse
import sys
def main():
parser = argparse.ArgumentParser(description="Filter lines from a file by keyword.")
parser.add_argument("input", type=str, help="File to read")
parser.add_argument("keyword", type=str, help="Keyword to filter lines")
parser.add_argument("--contains", action="sto…How to Parse Terraform Plan Output in Python
Parse mock Terraform plan output text into structured add, change, and destroy lists using Python.
import json
from typing import Dict, List
def parse_terraform_plan_output(plan_output_text: str) -> Dict[str, List[str]]:
"""
Parses a mock Terraform plan output text into a structured dictionary.
"""
parsed: Dict[str, List[str]] = {"add": [], "change": [], "destroy": []}
for line in plan_output_…How to Run Tesseract OCR from Python with subprocess
This script uses Python's subprocess module to invoke the Tesseract OCR engine from the command line and return the extracted text.
import subprocess
def ocr_image(image_path):
command = ["tesseract", image_path, "stdout"]
result = subprocess.run(command, capture_output=True, text=True)
return result.stdout.strip()
if __name__ == "__main__":
# Stub: call the actual tesseract (must be installed)
text = ocr_image("sample.png")
…Pin Python package versions in requirements.txt
Pin package versions in requirements.txt-style text by adding ==version when no specifier is present, while preserving existing version constraints and comments.
import re
from pathlib import Path
def pin_versions(requirements_text: str) -> str:
"""
Pin package versions in requirements.txt-style text.
Adds ==version if no version specifier is present.
Keeps existing specifiers (>=, <=, ~=, etc.) unchanged.
"""
lines = requirements_text.strip().splitli…How to Clean and Format Data in Python
This code loads JSON data, cleans records by removing empty fields and normalizing text, then summarizes the results with counts and unique keys.
import json
from pathlib import Path
def load_data(filepath: str) -> dict:
"""Load JSON data from a file."""
with Path(filepath).open("r", encoding="utf-8") as f:
return json.load(f)
def clean_records(records: list[dict]) -> list[dict]:
"""Remove empty fields and normalize text to lowercase."""…How to Hash Email Addresses in a PII Masking Pipeline in Python
Replaces every email address in a text string with its SHA-256 hash to protect personally identifiable information (PII).
import hashlib
import re
def hash_email(email: str) -> str:
"""Mask an email address by hashing it with SHA-256."""
normalized = email.strip().lower()
return hashlib.sha256(normalized.encode("utf-8")).hexdigest()
def mask_pii_emails(text: str) -> str:
"""Replace all email addresses in text with their…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…Detect Merge Conflict Markers in a File with Python
Scan a file line by line to detect Git merge conflict markers (<<<<<<<, =======, >>>>>>>) and report their line numbers with context.
from pathlib import Path
def detect_merge_conflicts(file_path):
conflicts = []
with open(file_path, 'r') as f:
lines = f.readlines()
for i, line in enumerate(lines, 1):
if line.startswith('<<<<<<<'):
conflict_marker = 'conflict start'
conflicts.append((i, confl…How to compute diff stats (insertions, deletions) in Python
Parses a git diff text and counts the number of added and removed lines to produce insertion and deletion stats.
import re
from collections import Counter
def parse_diff(diff_text):
insertions = 0
deletions = 0
for line in diff_text.splitlines():
if line.startswith("+") and not line.startswith("+++"):
insertions += 1
elif line.startswith("-") and not line.startswith("---"):
d…Upload Assets to GitHub Release with Python Mock
Simulates uploading binary and text assets to a GitHub release using a mock server, returning structured metadata for each upload.
import json
import os
import tempfile
from datetime import datetime
class ReleaseUploader:
"""Simulates uploading assets to a release with a mock server."""
def __init__(self, owner: str, repo: str, tag: str):
self.owner = owner
self.repo = repo
self.tag = tag
self.uploade…How to Convert Python Dict to JSON and Back
Convert Python dictionaries to JSON text and back with a simple helper that serializes and deserializes data structures.
import json
from datetime import datetime, timezone
def convert_data(data, source_format=None, target_format="json"):
"""
Convert Python data structures to txt/json and back.
For beginners: shows how to serialize/deserialize.
"""
if source_format == "json" and target_format == "dict":
ret…Mock Lambda handler event context dict in Python
Simulates an AWS Lambda invocation by passing a mock event dict and context object to a handler, then prints the response.
import json
def lambda_handler(event, context):
"""
A mock AWS Lambda handler that processes an event dict and context object.
Demonstrates the typical Lambda function signature and basic event/context usage.
"""
print("Received event:", json.dumps(event, indent=2))
print("Function name:", co…Build a Textual TUI App Skeleton in Python
Create a minimal Textual terminal UI app with a header, label, button, and footer, ready for interactive mock demonstrations.
from textual.app import App, ComposeResult
from textual.widgets import Header, Footer, Button, Label
class MockApp(App):
"""A minimal Textual TUI app skeleton."""
BINDINGS = [("q", "quit", "Quit")]
def compose(self) -> ComposeResult:
"""Create child widgets."""
yield Header()
yie…How to Bind and Mock structlog Context in Python
Shows how to bind persistent key-value context to a structlog logger, unbind keys, and mock the logger in tests to verify context is passed correctly.
import structlog
from unittest.mock import patch
logger = structlog.get_logger()
def demo():
logger = structlog.get_logger()
logger = logger.bind(user_id=42, request_id="abc123")
logger.info("user logged in", action="login")
# Unbind a key
logger = logger.unbind("user_id")
logger.info("r…Browse by section
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Guide: free Python code samples library
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- Pick a topic section — strings, lists, files, functions, and more
- Open a sample, read How it works, and copy the code block
- Run it in the IDE, tweak values, then take a related quiz or tutorial lesson
Samples vs tutorials and challenges
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.