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How to Sort Command-Line Arguments in Python
Build a beginner-friendly argparse CLI that sorts numbers or words passed as arguments, with an optional reverse flag.
import argparse
def main():
parser = argparse.ArgumentParser(description="Sort numbers or words from the command line.")
parser.add_argument("items", nargs="+", help="Items to sort (numbers or words)")
parser.add_argument("--reverse", "-r", action="store_true", help="Sort in descending order")
args =…How to validate argparse CLI commands in Python
Build a beginner-friendly command-line argument parser with argparse, including required and optional arguments, plus simple validation for age.
import argparse
def main():
parser = argparse.ArgumentParser(description="Validate CLI arguments for beginners.")
parser.add_argument("name", type=str, help="Your name.")
parser.add_argument("--age", type=int, default=None, help="Your age (optional).")
parser.add_argument("--verbose", action="store_t…Pin Python package versions in requirements.txt
Pin package versions in requirements.txt-style text by adding ==version when no specifier is present, while preserving existing version constraints and comments.
import re
from pathlib import Path
def pin_versions(requirements_text: str) -> str:
"""
Pin package versions in requirements.txt-style text.
Adds ==version if no version specifier is present.
Keeps existing specifiers (>=, <=, ~=, etc.) unchanged.
"""
lines = requirements_text.strip().splitli…Add a UUID Surrogate Key to Each Row in a CSV with Python
Generate a unique UUID string for every row in a CSV file using the standard-library uuid and csv modules.
import uuid
import csv
def add_surrogate_key(filename):
with open(filename, newline='') as f_in:
reader = csv.DictReader(f_in)
rows = list(reader)
for row in rows:
row['surrogate_key'] = str(uuid.uuid4())
with open(filename, 'w', newline='') as f_out:
writer = csv.DictWri…Create Data Helper Functions in Python for Beginners
Build reusable Python helper functions to load, filter, sort, summarize, and save JSON data — a beginner-friendly starting point for small data pipelines.
import json
from pathlib import Path
from typing import Any, Dict, List
def load_json_file(filepath: str) -> Dict[str, Any]:
"""Load JSON data from a file."""
with Path(filepath).open("r", encoding="utf-8") as file:
return json.load(file)
def filter_by_key(
data: List[Dict[str, Any]], key: str,…ETL in Python: Extract CSV, Transform Dict, Load JSON
Build a simple ETL pipeline in Python that reads a CSV file, transforms each row (stripping whitespace and converting numeric fields), and writes the result to JSON.
import csv
import json
from pathlib import Path
def extract_csv(file_path):
"""Read CSV file and return list of row dictionaries."""
with Path(file_path).open('r', newline='', encoding='utf-8') as f:
reader = csv.DictReader(f)
return list(reader)
def transform_dicts(rows):
"""Transform ro…ETL in Python: Extract CSV, Transform Dicts, Load JSON
Build a simple ETL pipeline that reads a CSV, normalizes keys and converts price to float, then writes structured JSON.
import csv
import json
from pathlib import Path
def etl_csv_to_json(csv_path: str, json_path: str) -> None:
"""Extract CSV, transform rows to dicts, load to JSON."""
with open(csv_path, mode='r', newline='', encoding='utf-8') as f:
reader = csv.DictReader(f)
records = list(reader)
# Trans…Filter Records by Required Fields in Python
Filter a list of dictionaries, keeping only records where every required field is present and not None.
def filter_records(records, required_fields):
"""Return only records that have all required fields non-null."""
return [
record for record in records
if all(record.get(field) is not None for field in required_fields)
]
if __name__ == "__main__":
sample_records = [
{"name": "Al…How to Build Data Processing Functions in Python
Create reusable helper functions to load, filter, transform, and aggregate CSV data in Python.
import csv
from pathlib import Path
def load_data(filepath):
"""Load CSV data into a list of dicts."""
with open(filepath, "r", newline="", encoding="utf-8") as f:
return list(csv.DictReader(f))
def filter_rows(rows, column, value):
"""Keep rows where column equals value."""
return [row for…How to Build a Simple Data Pipeline in Python
A beginner-friendly data pipeline that loads JSON, filters records by a field value, and aggregates counts per category.
import json
from pathlib import Path
def load_json(filepath: str | Path) -> list[dict]:
"""Load a JSON file containing a list of records."""
with Path(filepath).open("r", encoding="utf-8") as f:
return json.load(f)
def filter_records(records: list[dict], field: str, value) -> list[dict]:
"""Kee…How to Process CSV Data in Python with a Data Helper
Build a beginner-friendly data helper in Python that loads a CSV file, filters rows by a condition, and summarizes numeric fields.
import csv
from pathlib import Path
DATA = [
{"name": "Alice", "score": 88, "passed": True},
{"name": "Bob", "score": 42, "passed": False},
{"name": "Carol", "score": 95, "passed": True},
]
def load_csv(file_path: Path) -> list[dict]:
with file_path.open(newline="", encoding="utf-8") as f:
r…Test a Python Pipeline with Fixture Sample Rows
Test pipeline functions with sample rows provided by a pytest fixture, verifying required keys and value constraints.
import pytest
def get_value(data: dict, key: str):
return data.get(key)
def sample_rows():
return [
{"name": "Alice", "age": 30, "city": "London"},
{"name": "Bob", "age": 25, "city": "Paris"},
{"name": "Charlie", "age": 35, "city": "Berlin"},
]
@pytest.fixture
def sample_data(…Validate dict schema at pipeline boundary in Python
This code validates a dictionary against a TypedDict schema at a pipeline boundary, enforcing required fields and types with custom error messages.
from typing import Any, TypedDict
class Person(TypedDict):
name: str
age: int
email: str
def validate_person(data: dict[str, Any]) -> Person:
errors: list[str] = []
if not isinstance(data.get("name"), str) or not data["name"].strip():
errors.append("name must be a non-empty string")
…Build a Simple Log Graph in Python
Create a basic one-dimensional bar chart from log lines by counting occurrences of leading numeric keys.
import heapq
def log_graph(log_lines: list[str]) -> str:
"""Build a simple per-line, one-dimensional visual graph from log entries."""
counts: dict[int, int] = {}
for line in log_lines:
tokens = line.split()
if tokens:
try:
idx = int(tokens[0])
exce…Create a Mock GitHub Release API in Python for Testing gh CLI
Build an in-memory GitHub Releases API mock that mimics create_release and list_releases for unit testing gh CLI stubs without network calls.
import json
from unittest.mock import patch, Mock
class GitHubReleaseAPI:
"""Mock GitHub Releases API for testing gh CLI stub behavior."""
def __init__(self):
self.releases = {}
self.counter = 1
def create_release(self, repo, tag, name=None, notes=None):
release_id = self…How to Build a Git Helper Class in Python
A beginner-friendly GitHelper class that wraps common git commands (status, log, branch) into reusable Python methods with structured output.
import subprocess
import json
from pathlib import Path
class GitHelper:
def __init__(self, repo_path="."):
self.repo = Path(repo_path)
def run(self, *args):
result = subprocess.run(
["git", *args],
cwd=self.repo,
capture_output=True,
text=True,…How to Create a Git Commit with Message Template in Python
Run a git commit from Python using a standardized message template built from a commit type and description.
import subprocess
import sys
def commit_with_template(commit_type: str, description: str) -> None:
message = f"{commit_type}: {description}"
try:
subprocess.run(["git", "commit", "-m", message], check=True)
print(f"Committed: {message}")
except subprocess.CalledProcessError as e:
…How to Generate Git LFS Extension Patterns in Python
This script builds mock Git LFS file patterns for common geospatial extensions and filters them based on compression suffixes.
import itertools
import re
LFS_EXTENSIONS = {".csv", ".geojson", ".tif", ".shp", ".gpkg"}
def build_mock_lfs_pattern(base_name="data_usgs_lidar"):
patterns = []
for ext in sorted(LFS_EXTENSIONS):
for variant in (("", ".lz4"), (".compressed",), (".b", ".a"), ("_v1", ".zip")):
full_pattern …How to Mock subprocess.run in Python Tests
Mock subprocess.run to test a Git submodule update command without executing it in your test suite.
import subprocess
from unittest.mock import Mock, patch
def update_submodules():
subprocess.run(["git", "submodule", "update", "--init", "--recursive"], check=True)
with patch("subprocess.run") as mock_run:
mock_run.return_value = Mock(returncode=0)
update_submodules()
mock_run.assert_called_once_wit…Create a Cloud Storage Helper Class in Python
Build a simple local file-based helper class that mimics cloud storage operations like save, load, and list JSON objects.
import datetime
import json
from pathlib import Path
class CloudDataHelper:
"""Simple helper for reading/writing JSON files in a cloud-style folder."""
def __init__(self, base_dir: str = "cloud_storage"):
self.base_dir = Path(base_dir)
self.base_dir.mkdir(exist_ok=True)
def save_json(se…Generate an Idempotency-Key header mock with UUID in Python
This code provides a mock idempotency service that generates a UUID-based Idempotency-Key header token and validates it, useful for simulating production API behavior in tests.
import uuid
class MockIdempotencyService:
def __init__(self):
self._tokens = {}
def get_token(self, header_name="Idempotency-Key"):
token = str(uuid.uuid4())
self._tokens[header_name] = token
return token
def validate(self, header_name="Idempotency-Key"):
return s…How to Build a Budget Alert Threshold with Mock Notifications in Python
This code calculates budget usage percentage and triggers a mock alert notification when the usage exceeds a defined threshold.
budget = 500.0
spent = 620.0
alert_threshold = 0.8
def mock_notify(percent_used):
if percent_used >= alert_threshold:
return f"ALERT: Budget usage at {percent_used * 100:.1f}% — over {alert_threshold * 100:.0f}% threshold!"
return f"OK: Budget usage at {percent_used * 100:.1f}% — under threshold."
pe…How to Build a Multi-Cloud Config Loader with Provider Switching in Python
Load cloud provider configurations (AWS, Azure, GCP) from JSON files using a provider dispatch pattern in Python.
import json
from pathlib import Path
from dataclasses import dataclass
from typing import Dict, Any
@dataclass
class CloudConfig:
provider: str
region: str
settings: Dict[str, Any]
class ConfigLoader:
def __init__(self, config_dir: str = "configs"):
self.config_dir = Path(config_dir)
…How to Create a Mock STS AssumeRole Credentials Dict in Python
Build a realistic AWS STS AssumeRole response dict with temporary credentials, expiry time, and assumed role ARN for local testing.
import json
from datetime import datetime, timedelta, timezone
def mock_sts_credentials(role_arn, session_name, duration=3600):
now = datetime.now(timezone.utc)
expiration = now + timedelta(seconds=duration)
credentials = {
"Credentials": {
"AccessKeyId": "ASIAEXAMPLEACCESSKEY",
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