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Chunk Large File Upload Simulation by Blocks in Python
A Python script reads a large binary file in fixed-size chunks and simulates a block-by-block upload with per-chunk SHA256 hashing.
import os
import hashlib
from pathlib import Path
def read_file_in_chunks(file_path, chunk_size=8196):
"""Yield chunks of a file as bytes."""
with open(file_path, 'rb') as f:
while chunk := f.read(chunk_size):
yield chunk
def simulate_chunked_upload(file_path, chunk_size=8196):
"""S…Download Files from Internet with Progress Bar in Python
Download a file from the internet while displaying a text progress bar in the terminal.
import urllib.request
import sys
def download_with_progress(url, filename):
"""Download a file with a simple text progress bar."""
def report_hook(block_count, block_size, total_size):
downloaded = block_count * block_size
if total_size > 0:
percent = min(100, int(downloaded * 100 …How to Load Pickle Files Safely in Python
This code demonstrates how to load pickle files safely in Python by using a restricted unpickler that only allows specific, trusted classes, preventing arbitrary code execution from untrusted pickles.
import pickle
# Default pickle.load is unsafe: it executes arbitrary code when unpickling.
class Unsafe:
def __reduce__(self):
return (eval, ("open('/tmp/pickle_demo.txt', 'w').write('pwned')",))
# Create a malicious payload (simulating untrusted source)
malicious_data = pickle.dumps(Unsafe())
# Safe ap…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 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:
…Composable Predicates with the &, |, ~ Operators in Python
Define a reusable Predicate class that combines boolean checks with & (AND), | (OR), and ~ (NOT) operators.
class Predicate:
def __init__(self, func, name=None):
self.func = func
self.name = name or getattr(func, "__name__", "predicate")
def __call__(self, value):
return self.func(value)
def __and__(self, other):
return Predicate(lambda v: self(v) and other(v), f"({self.name} AN…How to Lazy Load an Expensive Attribute with a Proxy in Python
This code shows a Proxy class that lazily loads an ExpensiveResource only when first accessed, caching it for subsequent uses.
class ExpensiveResource:
def __init__(self, name):
self.name = name
print(f"Expensive resource '{name}' created (e.g., DB connection)")
def use(self):
return f"Using {self.name}"
class Proxy:
def __init__(self, name):
self._name = name
self._resource = None
@p…Automatically Download the Latest Software Release from GitHub with Python
Use the GitHub API to fetch the latest release metadata and download the first asset (binary or archive) to a local directory.
import requests
import sys
from pathlib import Path
def download_latest_release(owner: str, repo: str, output_dir: str = ".") -> None:
"""Download the latest release asset from a GitHub repository."""
url = f"https://api.github.com/repos/{owner}/{repo}/releases/latest"
response = requests.get(url)
res…Download Images from a Web Page Automatically in Python
Scrape all images from a webpage, filter by extension, and save them to a local folder using requests and BeautifulSoup.
import requests
from bs4 import BeautifulSoup
from urllib.parse import urljoin
import os
def download_images(url, output_folder="downloaded_images"):
"""Download all images from a given URL."""
os.makedirs(output_folder, exist_ok=True)
response = requests.get(url)
response.raise_for_status()
…How to Download All Assets from GitHub Releases in Python
Downloads every asset attached to the latest GitHub release of a repository, saving them locally using the GitHub API and Python's requests and pathlib libraries.
import requests
import os
import zipfile
from pathlib import Path
def download_github_release_assets(owner: str, repo: str, output_dir: str = "release_assets") -> None:
"""Downloads all assets from the latest release of a GitHub repository."""
releases_url = f"https://api.github.com/repos/{owner}/{repo}/relea…How to Download a GitHub Repository as a ZIP File in Python
Download any public GitHub repository as a ZIP file using the GitHub API and Python's requests and zipfile modules.
import requests
import zipfile
import io
import os
def download_github_repo_as_zip(repo_url, output_path='.'):
"""
Download a GitHub repository as a ZIP file.
Args:
repo_url (str): Full GitHub repository URL (e.g., 'https://github.com/username/repo')
output_path (str): Directory to sa…How to Implement a Weighted DNS Resolver with Failover in Python
Simulates a weighted DNS load balancer that distributes traffic across IPs by weight and automatically fails over when a server is marked unhealthy.
import random
import time
class WeightedDNSResolver:
def __init__(self, records):
self.records = records # list of (ip, weight)
self.total_weight = sum(weight for _, weight in records)
self.failed_ips = set()
def resolve(self):
available = [(ip, weight) for ip, weight in self…How to Stream a Large JSONL File Line by Line in Python
Process a large JSON-lines file incrementally using streaming techniques to avoid loading the entire file into memory.
import json
def process_large_file(filepath, chunk_size=8192):
"""
Stream a large JSON-lines file line by line, processing each record
without loading the entire file into memory.
"""
total_count = 0
total_sum = 0
with open(filepath, 'r') as f:
while True:
chunk = …How to mock boto3 S3 upload file wrapper in Python
Wrap an S3 put_object call in a testable function that returns metadata, and mock boto3 to verify the upload without touching AWS.
import boto3
import io
def upload_file_to_s3(file_obj, bucket, key, object_metadata=None):
"""Upload a file-like object to S3 and return a metadata dict."""
s3 = boto3.client("s3")
content = file_obj.read()
s3.put_object(
Bucket=bucket,
Key=key,
Body=content,
Metadata=…How to mock boto3 S3 upload in Python
Shows how to mock the boto3 S3 client with unit tests and wrap an upload function to return a dictionary with status details.
import boto3
from unittest.mock import Mock, patch
class S3Uploader:
def __init__(self, bucket_name):
self.bucket_name = bucket_name
self.s3 = boto3.client("s3", region_name="us-east-1")
def upload_file(self, local_path, s3_key):
self.s3.upload_file(local_path, self.bucket_name, s3_ke…Mock GCP storage bucket blob upload in Python
Simulate uploading a blob to a GCP Storage bucket for testing without hitting the cloud.
import io
from datetime import datetime
from unittest.mock import MagicMock, patch
class MockBlob:
"""Simulates a GCP storage blob for unit testing."""
def __init__(self, name):
self.name = name
self.uploaded_at = None
self.content = b""
def upload_from_file(self, file_obj):
…How to Parse JSON Files in Parallel with Python ThreadPoolExecutor
Load and transform JSON records from multiple files concurrently using ThreadPoolExecutor for faster I/O-bound parsing.
import time
from concurrent.futures import ThreadPoolExecutor
import json
def load_json_file(path):
with open(path, 'r') as f:
return json.load(f)
def transform_record(record):
record['full_name'] = f"{record.pop('first_name', '')} {record.pop('last_name', '')}".strip()
record['score'] = int(reco…How to Run Blocking Code in an Executor with asyncio in Python
This code runs blocking functions concurrently without stalling the event loop by offloading them to thread pool executors via asyncio.
import asyncio
import time
def blocking_task(name: str, duration: float) -> str:
"""Simulate a blocking operation."""
time.sleep(duration)
return f"Finished {name} after {duration}s"
async def main() -> None:
loop = asyncio.get_running_loop()
results = await asyncio.gather(
loop.run_in_…How to Speed Up Downloads with ThreadPoolExecutor in Python
Compare sequential and thread-pool download loops to measure real speedup when I/O s bound.
import time
import threading
from concurrent.futures import ThreadPoolExecutor
def download_file(file_id):
"""Simulate fetching a file by sleeping briefly."""
time.sleep(0.2) # pretend network latency
return f"file_{file_id}"
def sequential_downloads(num_files):
"""Process files one at a time."""
…How to Load Test a Local API with Locust in Python
Defines a Locust load test that simulates traffic to local endpoints, enabling manual load testing against a development server.
from locust import HttpUser, task, between
class WebsiteUser(HttpUser):
wait_time = between(1, 3)
@task
def home_page(self):
self.client.get("/")
@task(3)
def about_page(self):
self.client.get("/about")
if __name__ == "__main__":
print("Run with: locust -f this_file.py --h…How to Snapshot Test JSON with Mock in Python
Use pytest-snapshot to capture the exact output of a JSON-loading function, with and without mocking json.loads, so future changes are automatically detected.
import json
from unittest.mock import Mock, patch
import pytest
def load_config(data):
config = json.loads(data)
return {"host": config["host"], "port": config["port"]}
def test_load_config_snapshot(snapshot):
mock_data = json.dumps({"host": "localhost", "port": 8080, "extra": "ignored"})
result = …How to Limit Concurrent Requests with a Semaphore in Python
Use threading.Semaphore with a ThreadPoolExecutor to cap how many worker threads run simultaneously, preventing resource overload.
import threading
import time
from concurrent.futures import ThreadPoolExecutor
def worker(name, semaphore, results):
with semaphore:
results.append(f"start {name}")
time.sleep(0.5) # simulate async work
results.append(f"done {name}")
def main():
sem = threading.Semaphore(2) # max 2 …Implement a Consistent Hash Ring in Python
Build a minimal consistent hash ring with virtual nodes to map keys to servers stably as nodes are added or removed.
import hashlib
import bisect
class ConsistentHashRing:
def __init__(self, nodes=None, replicas=3):
self.replicas = replicas
self.ring = {}
self.sorted_keys = []
if nodes:
for node in nodes:
self.add_node(node)
def _hash(self, key):
return i…Lazy loading with a proxy in Python: defer expensive service creation
A lazy proxy defers creating an expensive service object until its method is first called, then caches it for reuse.
import time
import random
class ExpensiveService:
def __init__(self, name):
self.name = name
print(f"Creating expensive service: {self.name}")
def fetch_data(self):
time.sleep(1)
return f"Data from {self.name}: {random.randint(1, 100)}"
class LazyProxy:
def __init__(sel…Browse by section
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