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Generate Timesheet Reports from Daily Logs in Python
Aggregate daily log entries by project and produce a formatted timesheet report using Python's standard library.
import json
from pathlib import Path
from collections import defaultdict
def generate_timesheet_report(daily_logs: list[dict]) -> str:
"""
Generate a timesheet report from daily log entries.
Args:
daily_logs: List of dicts with 'date', 'project', 'hours', 'task' keys
Returns:
…How to Convert Images Between Formats in Python
Use the Pillow library to open an image from one file format and save it to another, with error handling for missing files or conversion issues.
from PIL import Image
import sys
def convert_image_format(input_path, output_path):
try:
img = Image.open(input_path)
img.save(output_path)
print(f"Converted {input_path} to {output_path}")
except FileNotFoundError:
print(f"Error: File {input_path} not found")
sys.exit(…How to List File Information in a Directory with Python
A helper that walks a directory and returns each file's name, size, and extension as a list of dictionaries.
from pathlib import Path
def get_files_data(directory: str) -> list[dict]:
"""Return basic info about all files in a directory."""
files = []
for path in Path(directory).iterdir():
if path.is_file():
files.append({
"name": path.name,
"size": path.stat()…How to Load and Save JSON Files in Python
Load and save JSON files with pretty formatting using Python's standard library json module and pathlib.
import json
from pathlib import Path
def load_json(filepath: str) -> dict:
"""Load JSON data from a file."""
path = Path(filepath)
with path.open("r", encoding="utf-8") as f:
return json.load(f)
def save_json(filepath: str, data: dict) -> None:
"""Save data to a JSON file with pretty format…How to Map Dictionary Values with a Transformation Function in Python
Create a reusable function that applies a transformation to every value in a dictionary and returns a new dict.
def transform_dict_values(d, func):
"""Apply a transformation function to every value in a dictionary."""
return {key: func(value) for key, value in d.items()}
if __name__ == "__main__":
original = {"a": 1, "b": 2, "c": 3}
doubled = transform_dict_values(original, lambda x: x * 2)
print(doubled)
…Group Data Helper Class in Python
A simple Python class that stores items under named groups, retrieves groups, items, and counts, and formats them as a readable summary.
class GroupData:
"""A simple helper class to store and group data for beginners."""
def __init__(self):
self.items = []
def add(self, item, group):
"""Add an item under a given group name."""
self.items.append({"item": item, "group": group})
def get_groups(self):
"""R…How to Create a Data Formatter Class in Python
A beginner-friendly helper class to format lists, dictionaries, and stored records into readable strings.
class DataFormatter:
"""Helper class for beginners to format common data types."""
def __init__(self, name="data"):
self.name = name
self.records = []
def add_record(self, key, value):
"""Add a key-value record to the formatter."""
self.records.append({"key": key, …Python Adapter Class: Wrap Legacy Interface
Convert a legacy system's interface into a modern one using the Adapter pattern in Python, translating method calls and data formats.
class LegacySystem:
"""Legacy interface - old method names and parameter format."""
def query_employee_info(self, emp_id, emp_name):
return f"Legacy: {emp_id} - {emp_name}"
def update_employee_department(self, emp_id, department_code):
return f"Legacy: Updated {emp_id} to dept {department_…How to Use List Comprehensions and Generators to Format Data in Python
A beginner-friendly helper that formats dictionaries into strings using a list comprehension and generates squared numbers lazily with a generator.
def format_data(items):
"""Format a list of dictionaries into readable strings."""
formatted = [
f"{item.get('name', 'Unknown')}: {item.get('value', 0)} units"
for item in items
if item.get('value', 0) > 0
]
return formatted if formatted else ["No positive values found"]
def g…How to Use List Comprehensions and Generators to Transform Data in Python
Transform a list of integers by squaring even numbers with a list comprehension and cubing odd numbers with a generator.
def transform_data(data):
"""
Transform a list of integers:
- squares of even numbers using a list comprehension
- cubes of odd numbers using a generator
"""
squares = [num ** 2 for num in data if num % 2 == 0]
cubes = (num ** 3 for num in data if num % 2 != 0)
return squares, cubes
i…How to Append Few-Shot Examples to a Prompt in Python
This code builds a complete LLM prompt by appending few-shot examples in alternating user/assistant format using a simple loop.
def append_few_shot_examples(prompt: str, examples: list[tuple[str, str]], separator: str = "\n\n") -> str:
"""Append few-shot examples to a prompt in alternating user/assistant format."""
full_prompt = prompt
for user_input, assistant_output in examples:
full_prompt = f"{full_prompt}{separator}Use…How to Mock OpenAI Tool Call Messages in Python
Create an assistant message with a function tool call in OpenAI's chat format, useful for testing and mocking.
from openai import OpenAI
def mock_tool_call(tool_name: str, arguments: dict) -> dict:
"""Simulate a tool call message in OpenAI style."""
return {
"role": "assistant",
"content": None,
"tool_calls": [
{
"id": "call_" + "a1b2c3d4e5f6",
"type…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 ICS Calendar Invites in Python
This script generates a batch of calendar invites in the ICS format using the ics library.
import ics
from datetime import datetime, timedelta
def create_invites(batch):
calendar = ics.Calendar()
for event_data in batch:
event = ics.Event()
event.name = event_data["name"]
event.begin = event_data["start"]
event.end = event_data["end"]
event.description = even…Fill PDF Form Fields from a Mock Template in Python
Fills a PDF-style form template dictionary with user data, preserving template fields and formatting output as JSON.
import json
template = {
"first_name": "",
"last_name": "",
"email": "",
"phone": "",
"date_of_birth": "",
"address": "",
"city": "",
"state": "",
"zip_code": "",
"agree_to_terms": False
}
def fill_pdf_form(template: dict, data: dict) -> dict:
for key, value in data.items…How to Create a Mock Headless Browser Screenshot Stub in Python
This code provides a deterministic stub that simulates capturing webpage screenshots with a headless browser, returning formatted output without real browser dependencies.
import subprocess
import sys
def mock_screenshot_webpage(url: str, width: int = 1280, height: int = 800) -> str:
"""Stub that simulates taking a screenshot of a webpage using headless browser."""
# In real implementation, you would use playwright/selenium/headless chrome
result = {
"url": url,
…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 Explode an Array Field into Multiple Rows in Python
This code flattens a list of dictionaries by exploding each array field value into its own row, duplicating the other fields as needed.
from collections import defaultdict
data = [
{"id": 1, "name": "Alice", "tags": ["python", "data", "ai"]},
{"id": 2, "name": "Bob", "tags": ["web", "devops"]},
{"id": 3, "name": "Carol", "tags": []},
]
def explode_array_field(records, array_field):
result = []
for record in records:
for v…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…How to Unpivot Wide to Long with pandas melt in Python
This code demonstrates how to use pandas.melt to unpivot a wide DataFrame into a tidy long format, converting subject columns into rows.
import pandas as pd
# Sample wide-format data
df_wide = pd.DataFrame({
'id': [1, 2, 3],
'name': ['Alice', 'Bob', 'Charlie'],
'math': [90, 85, 95],
'science': [80, 92, 88]
})
print("Original wide DataFrame:")
print(df_wide)
# Melt: unpivot subject columns into rows
df_long = pd.melt(
df_wide,
…Generate Mock CloudFormation Stack Events in Python
Generate a list of mock AWS CloudFormation stack events with random resources, statuses, and timestamps, and print them as JSON.
import json
import random
from datetime import datetime, timedelta
def generate_mock_stack_events(stack_name="MyTestStack", num_events=10):
"""Generate a list of mock CloudFormation stack events."""
resources = [
("AWS::S3::Bucket", "MyBucket"),
("AWS::EC2::Instance", "MyInstance"),
("…Mock CloudWatch put_metric_data in Python
Simulate AWS CloudWatch put_metric_data with validation and formatted output for local testing without AWS.
import json
from datetime import datetime, timezone
def put_metric_data(namespace, metric_data_list):
"""
Mock AWS CloudWatch put_metric_data.
Validates and prints the metrics that would be sent.
"""
timestamp = datetime.now(timezone.utc).isoformat()
print(f"[MockCloudWatch] Received request …How to Format Data with Python's datetime and JSON Helpers
A beginner-friendly set of helper functions to format dates and safely read/write JSON files in Python.
from datetime import datetime
from pathlib import Path
import json
def format_today(pattern: str = "%Y-%m-%d") -> str:
"""Return today's date formatted with the given pattern."""
return datetime.now().strftime(pattern)
def load_json(file_path: str) -> dict:
"""Read and parse a JSON file safely."""
…How to Load and Inspect CSV Data with a Dataclass Helper in Python
This code defines a DataHelper dataclass that reads a CSV file into a list of dictionaries and prints basic dataset information.
from pathlib import Path
from dataclasses import dataclass
from typing import Any
@dataclass
class DataHelper:
"""Simple helper for loading and inspecting CSV data."""
filepath: Path
def load_csv(self, *, delimiter: str = ",") -> list[dict[str, Any]]:
"""Read CSV into a list of dictionaries."""
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