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How to generate website performance reports from HTTP requests in Python
Measure and report website load time, status code, and content size using Python's standard library.
import urllib.request
import time
def measure_website_load_time(url):
"""Measures total loading time of a website."""
start_time = time.time()
try:
with urllib.request.urlopen(url, timeout=10) as response:
content = response.read()
status_code = response.status
…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…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 Clean and Format Data in Python
This code loads JSON data, cleans records by removing empty fields and normalizing text, then summarizes the results with counts and unique keys.
import json
from pathlib import Path
def load_data(filepath: str) -> dict:
"""Load JSON data from a file."""
with Path(filepath).open("r", encoding="utf-8") as f:
return json.load(f)
def clean_records(records: list[dict]) -> list[dict]:
"""Remove empty fields and normalize text to lowercase."""…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 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 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…Upload Assets to GitHub Release with Python Mock
Simulates uploading binary and text assets to a GitHub release using a mock server, returning structured metadata for each upload.
import json
import os
import tempfile
from datetime import datetime
class ReleaseUploader:
"""Simulates uploading assets to a release with a mock server."""
def __init__(self, owner: str, repo: str, tag: str):
self.owner = owner
self.repo = repo
self.tag = tag
self.uploade…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…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 Check an SCP Deny List in Python
Load a JSON SCP policy file, extract the deny_list, and check if a target ARN is denied.
import json
from pathlib import Path
def evaluate_scp_deny_list(policy_path: Path, target_path: str) -> bool:
policy = json.loads(policy_path.read_text())
deny_list = policy.get("deny_list", [])
return target_path in deny_list
if __name__ == "__main__":
policy_file = Path("scp_policy.json")
pol…How to Design a Cloud Data Helper Class in Python
A beginner-friendly Python helper class that saves, loads, and aggregates JSON records locally, simulating cloud-style data handling.
import json
from pathlib import Path
from datetime import datetime
class CloudDataHelper:
"""Beginner-friendly helper for working with cloud-based JSON data."""
def __init__(self, base_dir="cloud_data"):
self.base_dir = Path(base_dir)
self.base_dir.mkdir(exist_ok=True)
def save_record(s…How to Evaluate Mock NACL Rules in Python
Simulate numbered AWS Network ACL rule evaluation with HMAC integrity checks on request payloads.
import base64
import json
import hmac
import hashlib
def evaluate_mock_rule(rule_number, request_data, secret):
"""
Simulates evaluating an NACL-like numbered rule by:
1. Checking if the rule number exists in the mock policy.
2. Computing an HMAC over the request payload for integrity.
"""
# M…How to Mock ELB Target Health Status in Python
Simulate AWS Elastic Load Balancer target health checks with a Python dict that mutates status and healthy host counts.
from random import randint
def elb_target_mock_status(target_id, healthy=True):
targets = {
1: {"Id": "i-001", "Status": "healthy", "Port": 80, "HealthyHostCount": 1},
2: {"Id": "i-002", "Status": "unhealthy", "Port": 80, "HealthyHostCount": 0},
3: {"Id": "i-003", "Status": "healthy", "Por…How to Mock GCP Cloud Functions HTTP Events in Python
Simulate a GCP Cloud Functions HTTP event with a Python mock handler that constructs a realistic event payload and returns a JSON response.
import json
from datetime import datetime, timezone
def mock_http_event(data):
"""Simulate a GCP Cloud Function HTTP event."""
event = {
"event_id": "mock-event-12345",
"timestamp": datetime.now(timezone.utc).isoformat(),
"event_type": "google.cloud.functions.http",
"resource"…How to Parse Cloud JSON Data in Python
A helper function that safely parses JSON payloads from cloud services into a clean dict with defaults and error handling.
import json
from typing import Dict, Any
def parse_cloud_data(payload: str) -> Dict[str, Any]:
"""Parse a JSON payload from a cloud service into a clean dict."""
try:
data = json.loads(payload)
return {
"status": data.get("status", "unknown"),
"region": data.get("region…How to plan reserved capacity from a CSV in Python
Read a CSV of workloads with csv.DictReader and compute a mock reserved capacity plan with headroom per service.
import csv
import io
def plan_reserved_capacity(workloads_csv: str) -> list[dict]:
"""Read a CSV of workloads and return a plan for reserved capacity per service."""
reader = csv.DictReader(io.StringIO(workloads_csv))
plan = []
for row in reader:
service = row["service"]
avg_load = fl…Mock Azure Blob Upload and Download in Python
Simulate Azure Blob Storage upload and download operations with a lightweight in-memory mock class for testing.
import io
import json
from datetime import datetime, timezone
class MockBlob:
def __init__(self, name):
self.name = name
self.content = b""
self.properties = {
"last_modified": datetime.now(timezone.utc).isoformat(),
"size": 0,
}
def upload(self, data, …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:
…How to Load and Inspect CSV Data with a Dataclass Helper in Python
This code defines a DataHelper dataclass that reads a CSV file into a list of dictionaries and prints basic dataset information.
from pathlib import Path
from dataclasses import dataclass
from typing import Any
@dataclass
class DataHelper:
"""Simple helper for loading and inspecting CSV data."""
filepath: Path
def load_csv(self, *, delimiter: str = ",") -> list[dict[str, Any]]:
"""Read CSV into a list of dictionaries."""
…How to Load and Inspect Data Files in Python
A beginner-friendly DataLoader dataclass that loads JSON or text files and provides methods to preview and inspect the data.
from dataclasses import dataclass, field
from pathlib import Path
import json
from typing import Any, Dict, List
@dataclass
class DataLoader:
"""Simple helper to load and inspect data files for beginners."""
path: Path
data: Any = field(init=False, default=None)
def __post_init__(self) -> None:
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