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Copy-ready Python snippets by topic and difficulty — short, focused, and runnable in the browser editor.
Generate a Mock CDC Changelog in Python
Simulate a CDC changelog with INSERT, UPDATE, and DELETE operations, timestamps, and record snapshots for testing data pipelines.
import json
from datetime import datetime, timedelta
def generate_mock_changelog(records, operations=("INSERT", "UPDATE", "DELETE")):
"""Simulate a CDC changelog from a list of record snapshots."""
base_time = datetime(2025, 1, 1, 8, 0, 0)
changelog = []
for idx, record in enumerate(records):
…Group Python Events into Sessions with a Gap Timeout
Groups timestamped events into sessions, starting a new session when the time gap exceeds a specified timeout.
from itertools import groupby
from datetime import datetime, timedelta
def session_window_group(events, gap_seconds=300):
"""Group events into sessions where gap > gap_seconds starts a new session."""
if not events:
return []
events = sorted(events, key=lambda x: x[0])
sessions = []
c…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 Count Events by Minute with a Tumbling Window in Python
Group timestamps into fixed 60-second tumbling windows and count events per bucket using a dict.
from collections import defaultdict
from datetime import datetime, timedelta
def tumbling_window_count(events, window_seconds=60):
buckets = defaultdict(int)
for event in events:
ts = datetime.fromisoformat(event["timestamp"])
bucket_start = ts - timedelta(seconds=ts.second % window_seconds,
…How to Implement Incremental Load with Watermark by updated_at in Python
Load only new or changed rows into SQLite by comparing an updated_at timestamp against a stored watermark, returning counts and the new watermark.
import sqlite3
from datetime import datetime, timedelta
def watermark_incremental_load(db_path, table_name, last_watermark, source_data):
"""Load only rows with updated_at greater than the last watermark."""
conn = sqlite3.connect(db_path)
cursor = conn.cursor()
# Create table if it doesn't exist
…How to Implement SCD Type 1 Overwrite in Python with SQLite
Implement SCD Type 1 dimension updates in Python using SQLite — overwrite existing rows with new data while preserving keys.
import sqlite3
# Simulate a dimension table with SCD Type 1 (overwrite)
conn = sqlite3.connect(":memory:")
cursor = conn.cursor()
# Create dimension table
cursor.execute("""
CREATE TABLE customer_dim (
customer_id INTEGER PRIMARY KEY,
customer_name TEXT,
city TEXT,
updated_at TEXT…How to Parse Data in Python: A Beginner's Helper
This helper parses a JSON payload, extracts user names, emails, and signup dates, then summarizes the results.
import json
from datetime import datetime
from typing import Dict, List
def parse_data(payload: str) -> Dict[str, List]:
"""Parse a JSON payload and extract useful fields."""
raw = json.loads(payload)
users = raw.get("users", [])
parsed = {
"names": [],
"emails": [],
"signup_…How to Partition Output Files by Date Key in Python
Group output files into a dictionary partitioned by a YYYYMMDD date key extracted from the filename prefix.
from pathlib import Path
from collections import defaultdict
def partition_files_by_date(directory: str) -> dict:
"""Partition output files by date key extracted from filename (YYYYMMDD prefix)."""
path = Path(directory)
partitions = defaultdict(list)
for file in path.iterdir():
if file.i…How to Validate Data in a Python Pipeline
A helper module to validate common record types — email, positive integer, and non-empty string list — before processing data in a pipeline.
from typing import Any, Iterable
def is_valid_email(email: str) -> bool:
"""Basic email check: one '@', no spaces, dot after '@'."""
if "@" not in email or " " in email:
return False
local, _, domain = email.partition("@")
return bool(local) and "." in domain
def is_positive_int(value: Any)…How to Validate Fact Table Grain Row Counts in Python
Validate fact table grain by checking dimension key references, unique grain combinations, duplicate rows, and dimension cardinality from a CSV file.
import csv
import hashlib
from pathlib import Path
def validate_fact_grain(fact_file: Path, expected_dim_keys: dict[str, set[str]]) -> dict:
"""
Validate fact table grain by checking each row's dimension keys exist
in expected dimension tables and row count consistency.
"""
dim_references = {}
…How to create a dated snapshot path for a dataset in Python
Generate a versioned directory path combining a base directory, dataset name, and today's date, ready for creating snapshots in data pipelines.
import datetime
import os
from pathlib import Path
def snapshot_path(base_dir: str, dataset_name: str) -> Path:
"""Return a dated snapshot path for a dataset under a base directory."""
today = datetime.date.today().isoformat()
return Path(base_dir) / dataset_name / today
if __name__ == "__main__":
…How to perform a star schema join in Python
Denormalize mock fact and dimension tables by building lookup dicts and enriching each sales fact with customer, product, and date attributes.
from datetime import date
# Mock dimension tables
customers = [
{"customer_id": 1, "name": "Alice", "city": "New York"},
{"customer_id": 2, "name": "Bob", "city": "Los Angeles"},
{"customer_id": 3, "name": "Carol", "city": "Chicago"},
]
products = [
{"product_id": 101, "name": "Laptop", "category": "…Idempotent Pipeline Dedupe by Record ID Set in Python
Filters records against a persistent set of seen IDs, returning only new ones and the updated set for idempotent pipeline processing.
def dedupe_records(records, seen_ids=None):
"""Return records whose id has not been seen before."""
if seen_ids is None:
seen_ids = set()
unique = []
for record in records:
record_id = record.get("id")
if record_id not in seen_ids:
seen_ids.add(record_id)
…Normalize Timestamps to UTC DateTime in Python
Convert timestamps in multiple formats to UTC-aware datetime objects using datetime.strptime and astimezone.
from datetime import datetime, timezone
raw_timestamps = [
"2024-01-15 14:30:00+02:00",
"17/05/2024 09:15:00 -0500",
"2024-03-01T22:45:00Z",
"2024-06-20 08:00:00+09:30"
]
def parse_and_convert(ts: str) -> datetime:
normalized_ts = ts.strip().replace("Z", "+00:00")
formats = [
"%Y-%m-%…Rollback dataset to previous snapshot pointer in Python
A SnapshotManager class stores timestamped data snapshots and rolls back to the most recent snapshot at or before a target time.
from datetime import datetime, timedelta
class SnapshotManager:
def __init__(self):
self.snapshots = {} # timestamp -> data
self.current_pointer = None
def create_snapshot(self, data):
timestamp = datetime.now()
self.snapshots[timestamp] = data
self.current_pointer =…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")
…Amend Last Commit Message in Python
This script uses subprocess to run `git commit --amend` and update the most recent commit's message in your repository.
import subprocess
import sys
def amend_last_commit_message(new_message: str) -> None:
"""Change the message of the most recent commit."""
result = subprocess.run(
["git", "commit", "--amend", "-m", new_message],
capture_output=True,
text=True,
check=False,
)
if result.…How to Generate Release Notes from Git Commit Messages in Python
This script fetches recent Git commit messages using conventional commit prefixes (feat, fix, etc.), categorizes them, and prints formatted release notes with today's date.
import subprocess
import re
from datetime import datetime
def get_git_log(since_tag="HEAD~10", format_str="%s"):
"""Retrieve commit messages from git log."""
try:
result = subprocess.run(
["git", "log", f"--since={since_tag}", f"--format={format_str}"],
capture_output=True,
…How to Make a Git Commit Heatmap by Hour in Python
Parse a git log output and count commits by weekday and hour, then print a compact heatmap table.
import re
from collections import Counter
from datetime import datetime
def parse_commits(log_text):
"""Parse git log lines and count commits by (weekday, hour)."""
pattern = re.compile(r"^Date:\s+(.+)$")
counts = Counter()
for line in log_text.splitlines():
match = pattern.match(line)
…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…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 Validate AWS Security Group Ingress Rules in Python
Validates AWS security group ingress rules (protocol, port ranges, CIDR, description) and returns a list of errors or OK.
from dataclasses import dataclass
from typing import List, Optional
@dataclass
class SecurityGroupRule:
protocol: str
port_range: tuple
cidr: str
description: str = ""
def validate_ingress_rule(rule: SecurityGroupRule) -> List[str]:
"""Validate a security group ingress rule against common AWS pat…How to Validate Data Fields and Types in Python
Validate required fields and type correctness in a Python dictionary with small helper functions, returning a list of clear error messages.
import json
from typing import Any, Dict, List
def validate_data(data: Dict[str, Any], required_fields: List[str]) -> List[str]:
"""Check required fields exist and are non-empty. Return list of errors."""
errors = []
for field in required_fields:
value = data.get(field)
if value is None o…Mock ECS Task Run Stop Status Dict in Python
Build a mock ECS task status dictionary with RUNNING/STOPPED states using the standard library.
from datetime import datetime, timezone
def mock_ecs_task_status(task_id: str, state: str = "RUNNING") -> dict:
"""Return a mock ECS task status dictionary."""
return {
"taskArn": f"arn:aws:ecs:us-east-1:123456789012:task/cluster/{task_id}",
"taskDefinition": "arn:aws:ecs:us-east-1:1234567890…Browse by section
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