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Deduplicate events by ID within a window in Python
Deduplicate event streams by ID within sliding time windows, keeping the newest occurrence per window using heaps and sets.
import heapq
from collections import defaultdict
def deduplicate_events(events, window_size):
"""Return events deduplicated by id, keeping newest within each sliding window."""
# Index events by (timestamp, id) for deterministic ordering
events_by_id = defaultdict(list)
for ts, eid, *payload in events…Enrich Events with Geo IP Data in Python
Returns a copy of each event dictionary, enriched with a geo-location dict from a mock IP-to-geo lookup table, with a fallback for unknown IPs.
import ipaddress
GEO_IP_DB = {
"192.168.1.10": {"country": "US", "city": "New York", "lat": 40.7128, "lon": -74.0060},
"10.0.0.5": {"country": "DE", "city": "Berlin", "lat": 52.5200, "lon": 13.4050},
"172.16.0.8": {"country": "JP", "city": "Tokyo", "lat": 35.6762, "lon": 139.6503},
}
EVENTS = [
{"id…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 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 Group Rows by Key into Nested Arrays in Python
This code groups rows in a list of dictionaries by a specified key and returns a dictionary with each key mapped to a list of values from another key.
from collections import defaultdict
def implode_rows(rows, key, value_key):
grouped = defaultdict(list)
for row in rows:
grouped[row[key]].append(row[value_key])
return dict(grouped)
if __name__ == "__main__":
data = [
{"category": "fruit", "item": "apple"},
{"category": "fr…How to List Failed Records in a Dead Letter Queue Mock in Python
A mock Dead Letter Queue stores failed processing records with error details and timestamps, lists them, and exports to JSON.
import json
from datetime import datetime, timedelta
import random
class DeadLetterQueue:
def __init__(self):
self.failed_records = []
def add_failed_record(self, record_id, payload, error_message):
self.failed_records.append({
"record_id": record_id,
"payload": paylo…How to Merge Incremental Snapshot Upsert Dict in Python
Merge a snapshot dict into a base dict, recursively updating nested dictionaries while preferring snapshot values on conflicts.
def merge_upsert(base: dict, snapshot: dict) -> dict:
"""
Merge a snapshot dict into a base dict, preferring snapshot values
on key conflicts (upsert semantics). Nested dicts are merged recursively.
"""
result = dict(base)
for key, value in snapshot.items():
if key in result and i…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__":
…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 =…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 sync a fork with upstream in Python
Run git fetch and merge commands from Python with subprocess to sync a forked repository with upstream/main.
import subprocess
import sys
def sync_fork_with_upstream():
"""Simulate syncing a forked repo with upstream via git commands."""
# Mock git operations: pretend to fetch from upstream and merge into main
fetch_result = subprocess.run(
["git", "fetch", "upstream"],
capture_output=True, tex…Generate Mock CloudFormation Stack Events in Python
Generate a list of mock AWS CloudFormation stack events with random resources, statuses, and timestamps, and print them as JSON.
import json
import random
from datetime import datetime, timedelta
def generate_mock_stack_events(stack_name="MyTestStack", num_events=10):
"""Generate a list of mock CloudFormation stack events."""
resources = [
("AWS::S3::Bucket", "MyBucket"),
("AWS::EC2::Instance", "MyInstance"),
("…How to Create a JSON Data Helper in Python
A beginner-friendly DataHelper class that safely reads and writes JSON files with timestamps to a local data directory.
from datetime import datetime
from pathlib import Path
import json
class DataHelper:
"""Simple helper for reading/writing JSON files safely."""
def __init__(self, base_dir="data"):
self.base_dir = Path(base_dir)
self.base_dir.mkdir(exist_ok=True)
def save(self, filename, data):
…How to Mock RDS Snapshot Create and Restore in Python
Mock AWS RDS snapshot creation and restore operations in Python tests using moto and boto3 without hitting real AWS services.
import boto3
from moto import mock_rds
@mock_rds
def create_and_restore_snapshot():
client = boto3.client("rds", region_name="us-east-1")
client.create_db_instance(
DBInstanceIdentifier="my-db",
DBInstanceClass="db.t3.micro",
Engine="postgres",
AllocatedStorage=20,
Mas…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…Mock GCP Secret Manager access version in Python
A minimal mock of GCP Secret Manager that stores secret versions, retrieves payloads by version, and logs access timestamps.
import json
import time
from datetime import datetime, timezone
class MockSecretManager:
"""Minimal mock of GCP Secret Manager access/version behavior."""
def __init__(self):
self._secrets = {}
self._access_log = []
def create_secret(self, secret_id: str, payload: str) -> dict:
…Build a Recipe Runner Mock in Python
A Python script that mocks a command runner recipe system: maps recipe names to shell commands, executes them with subprocess, and prints the output and exit code.
import subprocess
import sys
def run_recipe(recipe: str) -> None:
"""Simulate a command runner recipe by printing the command and exit code."""
print(f"Running recipe: {recipe}")
result = subprocess.run(recipe, shell=True, capture_output=True, text=True)
print(f"Exit code: {result.returncode}")
i…How to Generate a Mock Rollbar Error Report in Python
Create a realistic fake Rollbar error report with random timestamps, levels, messages, and counts for testing and demos.
import json
import random
import time
from datetime import datetime, timedelta
def mock_rollbar_report(n_errors=5):
messages = [
"TypeError: unsupported operand type(s) for +: 'int' and 'str'",
"KeyError: 'user_id'",
"ValueError: invalid literal for int() with base 10: 'abc'",
"At…How to Mock docker compose up Healthcheck in Python
Simulate docker compose up with a healthcheck cycle using Python loops, delays, and simulated service statuses.
import subprocess
import time
def run_healthcheck():
"""Mock a docker compose up with a healthcheck cycle."""
services = ["web", "db", "cache"]
print("Starting docker compose services...")
for service in services:
print(f"[{service}] starting...")
time.sleep(0.1)
print(f"[…How to Parse Taskfile YAML in Python
Load a Taskfile.yaml with PyYAML and simulate task execution by returning each task's commands.
import yaml
from pathlib import Path
def load_taskfile(taskfile_path: str) -> dict:
"""Load and parse a Taskfile.yaml file into a dict."""
data = Path(taskfile_path).read_text()
return yaml.safe_load(data)
def run_task(taskfile: dict, task_name: str) -> dict:
"""Simulate running a task by returning i…Build a Python Performance Profiler That Generates Readable Reports
Use cProfile and pstats to profile Python functions and print a sorted performance report showing the top time-consuming calls.
import cProfile
import pstats
import io
from pathlib import Path
def slow_function():
total = 0
for i in range(500_000):
total += i ** 2
return total
def fast_function():
total = sum(i * i for i in range(500_000))
return total
def profile_functions():
profiler = cProfile.Profile()
…Graceful Shutdown Executor Context Manager in Python
A context manager that starts a background thread and ensures it stops gracefully on exit, handling timeouts and exceptions.
import signal
import threading
import time
from contextlib import contextmanager
@contextmanager
def graceful_shutdown_executor(timeout=5.0):
"""Context manager that runs a task and gracefully stops it on timeout or exception."""
stop_event = threading.Event()
def task():
print("Task started")
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