Files & data
Read and write files safely; parse JSON, CSV, and common text formats.
Compress and Extract ZIP Files Programmatically in Python
Create a ZIP archive with in-memory files and extract its contents to a directory using Python's stdlib zipfile and pathlib modules.
import zipfile
from pathlib import Path
import tempfile
import os
def create_sample_zip(zip_path: str, files: dict) -> None:
"""Create a ZIP file containing the given files (name -> content mapping)."""
with zipfile.ZipFile(zip_path, 'w', zipfile.ZIP_DEFLATED) as zf:
for filename, content in files.ite…Create an In-Memory SQLite Table and Query It in Python
This code creates an in-memory SQLite database, defines an employees table, inserts sample rows, and runs a filtered query with sorted results.
import sqlite3
conn = sqlite3.connect(":memory:")
cursor = conn.cursor()
cursor.execute("""
CREATE TABLE employees (
id INTEGER PRIMARY KEY,
name TEXT NOT NULL,
department TEXT NOT NULL,
salary REAL
)
""")
employees = [
(1, "Alice", "Engineering", 95000),
(2, "Bob", "…How to Compress a String to Gzip Bytes in Python
Compress a string into gzip-compressed bytes entirely in memory using the standard library gzip module.
import gzip
def compress_to_gzip_bytes(data: str, encoding: str = "utf-8") -> bytes:
"""Compress a string to gzip-compressed bytes in memory."""
return gzip.compress(data.encode(encoding))
if __name__ == "__main__":
original = "Hello, world! " * 10
compressed = compress_to_gzip_bytes(original)
pr…How to Memory Map Large Files Read-Only in Python
This code demonstrates reading only the tail of a large file using a read-only memory map (mmap) to avoid loading the entire file into memory.
import mmap
import os
def read_tail_with_mmap(filepath, bytes_from_end=64):
"""Read the last bytes of a large file using a read-only mmap."""
file_size = os.path.getsize(filepath)
start = max(0, file_size - bytes_from_end)
with open(filepath, "rb") as f:
with mmap.mmap(f.fileno(), length=0, a…How to Serialize a Python Object to Pickle Bytes in Memory
Serialize a Python object to pickle bytes in memory with pickle.dumps, then deserialize it back with pickle.loads and verify the roundtrip.
import pickle
class Person:
def __init__(self, name, age, skills):
self.name = name
self.age = age
self.skills = skills
def main():
person = Person("Alice", 30, ["Python", "SQL", "Docker"])
# Serialize to bytes in memory
pickle_bytes = pickle.dumps(person)
print(…How to Stream Large CSV Files in Python
Process a large CSV file in memory-efficient chunks using Python's csv module, yielding batches of rows instead of loading everything at once.
import csv
from pathlib import Path
def process_csv_in_chunks(file_path, chunk_size=1000):
"""Yield rows from a large CSV file in chunks without loading all into memory."""
with open(file_path, 'r', newline='') as f:
reader = csv.DictReader(f)
chunk = []
for row in reader:
…How to Write Simple XML Documents with ElementTree in Python
Create well-structured XML documents in memory using Python's built-in ElementTree module, complete with nested elements, attributes, and text content.
import xml.etree.ElementTree as ET
def create_xml_document():
# Create root element
root = ET.Element("catalog")
# Create a book element with attributes and children
book1 = ET.SubElement(root, "book", id="bk101")
ET.SubElement(book1, "author").text = "Gambardella, Matthew"
ET.SubElement(…Browse by section
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Files & data — Python code examples
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