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Chain of Thought Prompting in Python: Step-by-Step Reasoning Demo
This demo shows how to structure a function that explains its own reasoning step-by-step, mimicking chain-of-thought prompting for AI systems.
def solve_math_step_by_step(expression: str) -> str:
"""Solves a simple expression, showing each reasoning step."""
# Step 1: Parse the expression (assume "a + b" or "a - b")
parts = expression.split()
a = int(parts[0])
op = parts[1]
b = int(parts[2])
steps = []
steps.append(f"Step…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)
…Create Mock Watermarked Image Bytes in Python Without PIL
Builds a mock image-like byte stream with an embedded watermark using only stdlib modules, for testing pipelines without PIL.
from io import BytesIO
import zlib
import struct
def create_watermarked_bytes(width: int, height: int, watermark: bytes) -> bytes:
"""Create a mock image-like byte stream with a watermark (no PIL)."""
header = struct.pack("<2I", width, height)
payload = watermark * max(1, (width * height // max(1, len(wa…How to Automatically Download Every Favicon from a List of Websites in Python
Download each website's favicon.ico file by constructing its URL, making a GET request, and saving the binary content locally.
import requests
from urllib.parse import urlparse
import os
websites = [
"https://www.google.com",
"https://www.github.com",
"https://www.stackoverflow.com"
]
def download_favicon(url):
parsed = urlparse(url)
favicon_url = f"{parsed.scheme}://{parsed.netloc}/favicon.ico"
response = requests.g…How to Compress a Folder in Python While Preserving Directory Structure
A Python function that uses zipfile to recursively compress a folder, maintaining the original directory hierarchy inside the zip archive.
import os
import zipfile
from pathlib import Path
def compress_folder(source_dir: str, output_zip: str):
"""
Compress a folder into a zip file, preserving the directory structure.
Args:
source_dir: Path to the source directory to compress
output_zip: Path for the output zip file
"…How to Mock FFmpeg subprocess Calls in Python
Compress a video with ffmpeg while mocking subprocess.run to test the command construction without executing the actual encoder.
import subprocess
from unittest.mock import Mock, patch
def compress_video(input_path: str, output_path: str, crf: int = 23) -> None:
"""Compress a video using ffmpeg with a given CRF (quality) value."""
command = [
"ffmpeg",
"-i", input_path,
"-c:v", "libx264",
"-crf", str(cr…How to Mock a Whisper API Transcription Stub in Python
Simulate an OpenAI Whisper-style transcription response with a dataclass request model and a mock function that returns structured audio transcription output.
import json
from dataclasses import dataclass
from typing import Optional
@dataclass
class AudioRequest:
file_path: str
language: Optional[str] = None
def to_api_payload(self) -> dict:
return {"file": self.file_path, "language": self.language}
def mock_whisper_transcribe(payload: dict) -> dict:
…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 Split PDF Pages into Ranges in Python
Simulates splitting a PDF into page ranges by validating and returning structured range splits for automation workflows.
import os
def split_pdf_ranges(pdf_name, num_pages, ranges):
"""
Simulates splitting a PDF by returning the page ranges that would be split.
Args:
pdf_name (str): Name of the PDF file.
num_pages (int): Total number of pages in the PDF.
ranges (list of tuple): List of (start, end) …ETL in Python: Extract CSV, Transform Dicts, Load JSON
Build a simple ETL pipeline that reads a CSV, normalizes keys and converts price to float, then writes structured JSON.
import csv
import json
from pathlib import Path
def etl_csv_to_json(csv_path: str, json_path: str) -> None:
"""Extract CSV, transform rows to dicts, load to JSON."""
with open(csv_path, mode='r', newline='', encoding='utf-8') as f:
reader = csv.DictReader(f)
records = list(reader)
# Trans…How to Convert Data Types in a Python Data Pipeline
Demonstrates a simple Python data pipeline that converts string values to proper types (bool, int, float, datetime) and outputs structured JSON.
import json
from datetime import datetime
def convert_value(value):
"""Convert string values to appropriate Python types."""
if value.lower() == "true":
return True
if value.lower() == "false":
return False
if value.isdigit():
return int(value)
try:
return float(val…How to Count JSON Records in Python
Read a JSON file and count the number of top-level records, handling both list and dictionary structures.
import json
from pathlib import Path
def count_records(json_file):
"""Count top-level records in a JSON file."""
with open(json_file, "r") as f:
data = json.load(f)
# Handle both list of records and dict of records
if isinstance(data, list):
return len(data)
elif isinstance(da…How to Build a Git Helper Class in Python
A beginner-friendly GitHelper class that wraps common git commands (status, log, branch) into reusable Python methods with structured output.
import subprocess
import json
from pathlib import Path
class GitHelper:
def __init__(self, repo_path="."):
self.repo = Path(repo_path)
def run(self, *args):
result = subprocess.run(
["git", *args],
cwd=self.repo,
capture_output=True,
text=True,…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…How to Mock GCP Cloud Functions HTTP Events in Python
Simulate a GCP Cloud Functions HTTP event with a Python mock handler that constructs a realistic event payload and returns a JSON response.
import json
from datetime import datetime, timezone
def mock_http_event(data):
"""Simulate a GCP Cloud Function HTTP event."""
event = {
"event_id": "mock-event-12345",
"timestamp": datetime.now(timezone.utc).isoformat(),
"event_type": "google.cloud.functions.http",
"resource"…How to Parse and Extract Nested Data in Python
Load JSON files with Path and recursively extract values by key from nested Python structures using modern typing and standard library.
import json
from pathlib import Path
from typing import Any, Dict, List, Union
def load_data(filepath: Union[str, Path]) -> Union[Dict[str, Any], List[Any]]:
"""Load JSON data from a file with modern Path handling."""
path = Path(filepath)
if not path.exists():
raise FileNotFoundError(f"File not f…How to build a tox multi-env matrix with mock config in Python
Simulate a tox multi-environment matrix by validating environment names and grouping extras into a readable matrix structure.
```python
import tox
def run_tox_matrix(mock_envs):
"""Simulate a tox multi-env configuration and verify mock choices."""
config = {
"tox": {
"envlist": mock_envs,
"config": {
"basepython": "python3.9",
"deps": ["pytest", "mock"],
},
…How to Parse Data with Type Hints in Python
A beginner-friendly helper that parses simple dictionary- or list-like strings into typed Python structures using modern typing annotations.
from typing import Any, Dict, List, Union
def parse_data(raw: str) -> Union[Dict[str, Any], List[Any], str]:
"""Parse a simple string into structured data using type hints."""
cleaned = raw.strip()
if not cleaned:
return {}
if cleaned.startswith("{") and cleaned.endswith("}"):
…How to Use TypedDict and Dataclasses in Python
Create typed data structures with TypedDict and dataclasses, then use them as helper functions for describing objects in a type-safe way.
from typing import TypedDict, NotRequired, Optional
from dataclasses import dataclass
class User(TypedDict):
name: str
age: NotRequired[int]
email: Optional[str]
@dataclass
class Product:
id: int
title: str
price: float = 0.0
def describe_user(user: User) -> str:
age = user.get("age",…How to Use TypedDict for Structured Dict Typing in Python
Define and use TypedDict to add type hints to dictionaries, improving code clarity and enabling static type checking in your Python projects.
from typing import TypedDict
class User(TypedDict):
name: str
age: int
email: str
def greet(user: User) -> str:
return f"Hello {user['name']}, age {user['age']}, contact {user['email']}"
if __name__ == "__main__":
alice: User = {"name": "Alice", "age": 30, "email": "alice@example.com"}
pr…How to Use setUp and tearDown in Python unittest TestCase
Demonstrates how to structure unit tests with setUp and tearDown methods in Python's unittest framework for reusable test fixtures.
import unittest
class ExampleTest(unittest.TestCase):
def setUp(self):
self.data = [1, 2, 3]
def tearDown(self):
self.data = None
def test_length(self):
self.assertEqual(len(self.data), 3)
def test_contains(self):
self.assertIn(2, self.data)
if __name__ == "__main…Builder pattern for mocking complex objects in Python
Use a fluent Builder to construct realistic mock objects with defaults, enabling readable test data setup.
class User:
def __init__(self):
self.name = "default"
self.age = 0
self.email = "unknown@example.com"
self.address = "unknown"
def __repr__(self):
return f"User(name={self.name!r}, age={self.age}, email={self.email!r}, address={self.address!r})"
class UserBuilder:
…How to Aggregate Mock API Routes by Method in Python
Groups mock API routes by path and method, collecting response bodies and counts into a nested dictionary structure.
from collections import defaultdict
def aggregate_mock_routes(routes):
"""Aggregate mock API routes by method and aggregate their response bodies."""
aggregated = defaultdict(lambda: defaultdict(list))
for route in routes:
method = route["method"]
path = route["path"]
response = …Browse by section
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