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Build a Data Helper Class in Python for ML Pipelines
A beginner-friendly Python class that summarizes, filters, and exports ML dataset rows as JSON.
from typing import List, Dict, Any
import json
class DataHelper:
"""Beginner-friendly helpers for ML data pipelines."""
def __init__(self, data: List[Dict[str, Any]]):
self.data = data
self.keys = list(data[0].keys()) if data else []
def summary(self) -> Dict[str, Any]:
"…Build a Mock Random Forest Classifier in Python
Create a simple random-forest-like classifier with random majority voting between trees, including fit, predict, and predict_proba methods.
import random
class MockRandomForest:
def __init__(self, n_trees=10, random_state=42):
self.n_trees = n_trees
self.random_state = random_state
self.classes_ = None
self._class_counts = None
random.seed(random_state)
def fit(self, X, y):
self.classes_ = sorted(…Create a Minimal Great Expectations Suite Mock in Python
Build a small Python class that mimics a Great Expectations suite, storing and serializing column expectations as JSON.
import json
class GreatExpectationsSuite:
"""A minimal mock of a Great Expectations suite."""
def __init__(self, suite_name, expectations=None):
self.suite_name = suite_name
self.expectations = expectations or []
def add_expectation(self, expectation_type, column=None, kwargs=None):
…How to Build a Data Validation Schema in Python
Create a lightweight validation schema using dataclasses and lambda validators to check fields in a dictionary.
import re
from dataclasses import dataclass, field
from typing import Any, Callable
@dataclass
class Field:
name: str
validator: Callable[[Any], bool]
required: bool = True
def validate(self, value: Any) -> bool:
if not self.required and value is None:
return True
return …How to Build a Mock Offline Feature Store in Python
Build an in-memory mock of an offline feature store with a dict-based FeatureStore class for storing and retrieving ML features by entity ID.
from datetime import datetime
from collections import defaultdict
class FeatureStore:
"""Simple in-memory mock of an offline feature store."""
def __init__(self):
self._features = defaultdict(dict)
def ingest(self, entity_id, feature_name, value, timestamp=None):
ts = timestamp or datet…How to Compute a Confusion Matrix in Python
Compute a multi-class confusion matrix from true and predicted labels using pure Python dictionaries and nested lists, then format it for readable output.
from collections import defaultdict
def compute_confusion_matrix(y_true, y_pred, labels):
"""Compute confusion matrix using Python dicts and nested lists."""
label_index = {label: i for i, label in enumerate(labels)}
matrix = [[0] * len(labels) for _ in range(len(labels))]
for true, pred in zip(y…How to Evaluate Accuracy, Precision, and Recall in Python
Compute accuracy, precision, and recall for a binary classification model using scikit-learn's metrics functions.
from sklearn.metrics import accuracy_score, precision_score, recall_score
if __name__ == "__main__":
y_true = [0, 1, 1, 0, 1, 0, 1, 1]
y_pred = [0, 1, 0, 0, 1, 0, 1, 1]
accuracy = accuracy_score(y_true, y_pred)
precision = precision_score(y_true, y_pred)
recall = recall_score(y_true, y_pred)
…How to Run Batch Predictions with a Mock Model in Python
Build a lightweight mock model class and run predictions across a batch of samples, returning results as a plain Python list.
import numpy as np
class MockModel:
def __init__(self, weights):
self.weights = np.array(weights)
def predict(self, X):
return X @ self.weights
def predict_batch(model, batch):
"""Run predictions for a batch of samples and return results as a list."""
return model.predict(np.array(ba…StandardScaler mock in Python
A pure-Python StandarScaler class that standardizes features to zero mean and unit variance without sklearn.
import math
class StandardScaler:
def __init__(self):
self.mean_ = None
self.std_ = None
def fit(self, X):
n = len(X)
self.mean_ = [sum(col) / n for col in zip(*X)]
self.std_ = []
for col in zip(*X):
variance = sum((x - self.mean_[i]) ** 2 for i, x …How to Define a Mock Primary Metric in Python
Define a mock primary metric object with a name, value, and unit, and serialize it to a dictionary for experimentation and testing.
class Metric:
def __init__(self, name, value, unit=None):
self.name = name
self.value = value
self.unit = unit
def to_dict(self):
result = {"name": self.name, "value": self.value}
if self.unit:
result["unit"] = self.unit
return result
def __repr…Hash index equality mock concept in Python
A simple hash index class in Python that stores key-value pairs in buckets and demonstrates basic equality-based lookup.
class HashIndex:
def __init__(self):
self._buckets = {}
def insert(self, key, value):
"""Insert a key-value pair into the hash index."""
index = hash(key) % 10
if index not in self._buckets:
self._buckets[index] = []
self._buckets[index].append((key, value))…How to Create a Data Helper Class in Python for JSON Files
Build a beginner-friendly Python helper class to read, write, filter, and summarize JSON data files with clean, reusable methods.
import json
from pathlib import Path
class DataHelper:
"""Simple beginner-friendly helper for reading and writing JSON data files."""
@staticmethod
def read_json(filename):
file_path = Path(filename)
if file_path.exists():
with file_path.open("r", encoding="utf-8") as f:
…How to Create a Database Helper Class for Beginners in Python
Build a beginner-friendly SQLite helper class with indexing and batch inserts to optimize database queries in Python.
import sqlite3
class DatabaseHelper:
def __init__(self, db_path):
self.connection = sqlite3.connect(db_path)
self.cursor = self.connection.cursor()
def create_table_with_index(self, table_name, columns, indexed_column):
columns_sql = ", ".join(f"{name} {dtype}" for name, dtype in col…How to Mock Replica Lag Monitoring in Python
Simulates database replica lag with a mock monitor class that generates realistic lag metrics and health statuses.
import time
import random
from datetime import datetime, timedelta
class MockReplicaLagMonitor:
def __init__(self, replicas=3, base_lag=0.5, jitter=0.2):
self.replicas = [f"replica-{i}" for i in range(replicas)]
self.base_lag = base_lag
self.jitter = jitter
self.last_write = dateti…How to Replicate Data Across All Shards in Python
Mocks a global table that replicates a key-value pair to every shard, ensuring reads return the same value from any shard.
from dataclasses import dataclass
from typing import Dict, List
@dataclass
class Shard:
id: str
data: Dict[str, int]
class GlobalTable:
def __init__(self, shards: List[Shard]):
self._shards = {s.id: s for s in shards}
def set_value(self, key: str, value: int) -> None:
"""Replicate …Rebalance Shard Ranges Across Nodes in Python
A mock rebalancing function that shuffles shard ranges and distributes them evenly across nodes using round-robin assignment.
import random
from dataclasses import dataclass
@dataclass
class Shard:
id: int
start: int
end: int
def rebalance_shards(shards: list[Shard], node_count: int) -> dict[int, list[Shard]]:
"""Mock rebalancing of shard ranges across nodes."""
all_ranges = [(s.start, s.end) for s in shards]
random…Simulate PostgreSQL Vacuum to Reclaim Space in Python
A Python class that safely rewrites a data file to remove deleted rows and reclaim physical space, mimicking PostgreSQL's VACUUM operation.
import shutil
import os
class VacuumCleaner:
"""Simulates PostgreSQL-style vacuum reclaiming dead space in a file."""
def __init__(self, filepath, fill_ratio=0.7, dead_marker="[DELETED]"):
self.filepath = filepath
self.fill_ratio = fill_ratio
self.dead_marker = dead_marker
…How to Mock a Permissions Policy in Python
A lightweight Python class that simulates a browser Permissions-Policy header by tracking allowed/ denied feature permissions with get, set, reset, and bulk operations.
class PermissionsPolicy:
def __init__(self):
self._features = {
"geolocation": "self",
"camera": "self",
"microphone": "self",
"payment": "self",
"usb": "self",
}
def get_feature_policy(self, feature):
return self._features.ge…How to Mock a TLS Certificate Rotation Schedule in Python
Simulate a TLS certificate rotation schedule with a Python class that tracks last and next rotation dates and decides when to rotate.
import datetime
import random
import time
class CertRotator:
def __init__(self, cert_name, rotation_days=30):
self.cert_name = cert_name
self.rotation_days = rotation_days
self.last_rotated = datetime.date.today() - datetime.timedelta(days=random.randint(10, 25))
self.next_rotatio…How to Revoke Tokens with a Blacklist Set in Python
A minimal TokenBlacklist class using a Python set to revoke, batch-revoke, check, and remove expired tokens for simple token invalidation.
import time
class TokenBlacklist:
def __init__(self):
self.blacklisted_tokens = set()
def revoke(self, token):
self.blacklisted_tokens.add(token)
print(f"Token {token} revoked. Blacklist size: {len(self.blacklisted_tokens)}")
def revoke_batch(self, tokens):
before = len(s…How to Set a SameSite Cookie in Python
Set a SameSite cookie attribute in Python using the standard library's SimpleCookie class.
from http.cookies import SimpleCookie
def set_same_site_cookie(name, value, same_site="Lax"):
cookie = SimpleCookie()
cookie[name] = value
cookie[name]["path"] = "/"
cookie[name]["samesite"] = same_site
return cookie[name].OutputString()
if __name__ == "__main__":
print(set_same_site_cookie("…Design a Data Helper for Beginners in Python
Build a beginner-friendly DataHelper class that loads, saves, appends, and summarizes JSON data with atomic file writes.
import json
from datetime import datetime
from pathlib import Path
class DataHelper:
"""A beginner-friendly helper for common data operations."""
def __init__(self, data=None, filepath=None):
self.data = data if data is not None else []
self.filepath = Path(filepath) if filepath else None
…How to Build a Data Helper for Production Deployment in Python
Build a reusable DataHelper class that loads configs, validates required keys, normalizes string values, and logs schema details — a production-ready data processing pattern.
import json
from pathlib import Path
from typing import Any, Dict
class DataHelper:
"""Common data processing patterns for production deployment."""
def __init__(self, config_path: str | Path):
self.config_path = Path(config_path)
self.config = self._load_config()
def _load_confi…How to Build a Simple Data Helper Class in Python
A beginner-friendly DataHelper class that safely saves and loads JSON files with automatic directory creation, perfect for production-style file handling.
from pathlib import Path
import json
class DataHelper:
"""Simple production-style helper for loading and saving JSON data."""
def __init__(self, data_dir="data"):
self.data_dir = Path(data_dir)
self.data_dir.mkdir(exist_ok=True)
def save(self, filename, data):
filepath = self.da…Browse by section
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