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How to Encode and Decode UTF-8 in Python
Convert a Python string to UTF-8 bytes with .encode() and back to text with .decode(), with a simple demo function.
def encode_decode_demo(text: str):
encoded = text.encode("utf-8")
decoded = encoded.decode("utf-8")
print(f"Original string: {text}")
print(f"Encoded bytes: {encoded}")
print(f"Decoded string: {decoded}")
print(f"Match: {text == decoded}")
if __name__ == "__main__":
encode_decode_demo("Hel…How to Escape HTML in Python
This code demonstrates how to use Python's `html.escape` function to safely encode user input for display in HTML, preventing XSS attacks.
import html
def escape_user_input(user_input: str) -> str:
"""Escape HTML-sensitive characters for safe display."""
return html.escape(user_input)
if __name__ == "__main__":
sample_user_input = '<script>alert("XSS")</script> & \'quotes\''
safe_output = escape_user_input(sample_user_input)
print("…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.
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'
…How to Transcode a File from Latin-1 to UTF-8 in Python
Read a latin1-encoded text file and rewrite it as UTF-8 using Python's pathlib and encoding parameters.
from pathlib import Path
def transcode_to_utf8(input_path, output_path):
"""Read a latin1-encoded file and write it as UTF-8."""
source = Path(input_path)
target = Path(output_path)
with source.open(encoding='latin1') as infile:
content = infile.read()
with target.open('w', encod…How to Serialize a Dictionary to a Query String in Python
Convert a Python dictionary into a URL-encoded query string using the standard library's urllib.parse.urlencode function.
import urllib.parse
def dict_to_query_string(params):
"""Serialize a dictionary to a URL query string."""
return urllib.parse.urlencode(params)
if __name__ == "__main__":
data = {
"name": "Alice Johnson",
"age": 30,
"city": "New York",
"interests": ["coding", "hiking"]
…How to Batch Embed a List of Strings in Python
Batch embed a list of strings into deterministic pseudo-random vectors using a mock encoder class.
class MockEncoder:
def __init__(self, dim=8, seed=42):
self.dim = dim
self.seed = seed
def embed(self, text):
# Deterministic pseudo-random embedding based on text content
hash_val = hash(text)
import random
rng = random.Random(hash_val + self.seed)
retu…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 Content-Disposition and Extract Filename in Python
Parse and mock Content-Disposition headers in Python to extract filenames, handling both plain and RFC 5987 encoded values.
import os
from pathlib import Path
import re
from unittest.mock import patch
def get_filename_from_content_disposition(header_value):
"""
Extract filename from a Content-Disposition header value.
Supports both filename and filename* parameters (RFC 5987).
"""
if not header_value:
return No…How to Mock a Schema Registry Avro Record in Python
Encode a Python dict into Avro binary using an inline schema, mimicking a schema registry record for tests or mocks.
import io
from avro.schema import parse
from avro.io import DatumWriter, BinaryEncoder
schema_json = """
{
"type": "record",
"name": "User",
"fields": [
{"name": "name", "type": "string"},
{"name": "age", "type": "int"},
{"name": "email", "type": ["null", "string"], "default": null}
]
}
"""
schem…How to ordinal encode categorical data in Python with sklearn
Convert job title categories into ordinal numeric labels using sklearn's OrdinalEncoder with explicit ordering.
from sklearn.preprocessing import OrdinalEncoder
import numpy as np
# Mock data: small job title categories with known ordering
data = np.array([
["intern"],
["junior"],
["mid"],
["senior"],
["lead"]
])
# Define the ordinal order (lowest to highest)
categories = [["intern", "junior", "mid", "seni…One Hot Encode Categories in Python
Convert a list of categorical strings into one-hot encoded numeric vectors using pure Python and NumPy.
import numpy as np
categories = ["red", "green", "blue", "red", "blue", "green", "red"]
unique = sorted(set(categories))
lookup = {cat: i for i, cat in enumerate(unique)}
one_hot = []
for cat in categories:
row = [0] * len(unique)
row[lookup[cat]] = 1
one_hot.append(row)
print("Categories:", categories…Browse by section
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