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How to Convert Data Types in Python with a Helper Class
This code defines a beginner-friendly OOP helper class for common data conversions like string to list, list to dict, JSON string, and CSV row, with an advanced subclass for numeric casting.
class DataConverter:
"""A beginner-friendly helper class for common data conversions."""
def __init__(self, data):
self.data = data
def to_list(self):
"""Convert string data (comma-separated) to a list."""
if isinstance(self.data, str):
return [item.strip() for…How to Implement Iterator Protocol on a Custom Class in Python
Create a custom iterable class by defining the __iter__ and __next__ methods, enabling use in for loops and list conversions.
class Countdown:
"""Iterator that counts down from start to 0."""
def __init__(self, start):
self.start = start
self.current = start
def __iter__(self):
return self
def __next__(self):
if self.current < 0:
raise StopIteration
value = self.current
…Convert Data in Python with Comprehensions and Generators
Convert mixed data to integers, filter and transform numbers, and extract fields from dicts using list comprehensions and generator expressions.
def convert_numbers(data):
"""Convert a list of mixed values into integers using a comprehension."""
return [int(item) for item in data if item is not None]
def double_even_numbers(numbers):
"""Double only even numbers using a generator expression."""
return (n * 2 for n in numbers if n % 2 == 0)
d…How to Convert Data to JSON and Back in Python
Convert a Python dict into a JSON string with indentation, then parse it back into a dict, demonstrating a common round-trip conversion for beginners.
import json
from datetime import datetime
def convert_data(data):
"""Convert a dict into a JSON string and back to dict."""
json_str = json.dumps(data, indent=2)
parsed = json.loads(json_str)
return json_str, parsed
def main():
sample_data = {
"user": "alice",
"message": "hello",
…Convert Markdown to HTML in Python (Batch)
Convert every Markdown file in a directory to HTML with the Python markdown library, saving each result with an .html extension.
import markdown
from pathlib import Path
def convert_md_to_html(source_dir: str, dest_dir: str) -> list[str]:
src = Path(source_dir)
dst = Path(dest_dir)
dst.mkdir(parents=True, exist_ok=True)
converted_files = []
for md_file in src.glob("*.md"):
html_content = markdown.markdown(md_file.…How to Build a CLI with argparse in Python
Create a beginner-friendly command-line tool in Python that processes multiple filenames with optional flags for verbose output and uppercase conversion.
import argparse
def main():
parser = argparse.ArgumentParser(
description="A simple CLI to process files with optional verbose mode."
)
parser.add_argument("filenames", nargs="+", help="Files to process")
parser.add_argument("-v", "--verbose", action="store_true", help="Print extra details")
…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 Safely Coerce Strings to Numbers in Python
A safe conversion function that turns strings into integers or floats, returning a fallback value when conversion fails.
import math
def to_number(value, fallback=None):
"""Safely coerce a string to int or float, returning fallback on failure."""
if isinstance(value, (int, float)):
return value
try:
# Try int first for clean whole numbers
return int(value)
except (ValueError, TypeError):
…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…Data Conversion Helper Functions in Python
A set of beginner-friendly helper functions to convert between JSON strings and Python data, parse dates, and read/write files using pathlib.
from datetime import datetime
from pathlib import Path
import json
def to_json(data, indent=2):
"""Convert Python data to pretty-printed JSON string."""
return json.dumps(data, indent=indent, default=str)
def from_json(json_string):
"""Parse JSON string back into Python data."""
return json.loads(jso…How to Convert Strings to Types in Python Using TypeVar
A beginner-friendly helper that converts a string to int, float, bool, or str with type hints and graceful failure handling.
from typing import TypeVar, Optional
T = TypeVar("T")
def convert_data(value: str, target_type: type[T]) -> Optional[T]:
"""Convert string value to target type; return None on failure."""
try:
if target_type is int:
return int(value)
elif target_type is float:
return f…Convert Protobuf to JSON and Dict in Python
Provides static helper methods to convert between protobuf messages, JSON strings, and Python dictionaries using the google.protobuf library.
from google.protobuf.json_format import MessageToJson, Parse
import json
class DataConverter:
"""Helper class to convert between protobuf messages and common formats."""
@staticmethod
def to_json(message, indent=2):
"""Convert a protobuf message to JSON string."""
return MessageToJson(me…Chi-Square Test in Python for Conversion Mock Data
Compute the chi-square statistic and approximate p-value for a mock A/B conversion test using the standard library.
import math
from collections import Counter
def chi_square_statistic(observed):
"""
Compute chi-square statistic for a mock conversion test.
observed: dict mapping outcomes to observed frequencies.
"""
observed = Counter(observed)
n = sum(observed.values())
expected = n / len(observed) if …How to Convert Data with Scaling for Database Optimization in Python
A beginner-friendly helper that normalizes and scales numeric fields in a list of dicts, reducing storage footprint for database efficiency.
import json
from datetime import datetime
def convert_data(data: list[dict], scale_factor: int = 1) -> list[dict]:
"""Convert a list of dicts to a scaled, normalized format for database efficiency."""
converted = []
for row in data:
normalized = {}
for key, value in row.items():
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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.