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How to Find Duplicate Files by Size and Hash in Python
Recursively scan a directory, group files by size, then hash candidates to identify exact duplicate files.
import hashlib
from pathlib import Path
def hash_file(path, chunk_size=8192):
hasher = hashlib.md5()
with open(path, 'rb') as f:
while chunk := f.read(chunk_size):
hasher.update(chunk)
return hasher.hexdigest()
def find_duplicates(directory):
size_map = {}
for path in Path(dir…How to Sync Two Folders in Python (Lightweight Backup)
A Python script that synchronizes a source folder to a destination folder, copying new or updated files and removing files that no longer exist in the source.
import os
import shutil
import sys
from pathlib import Path
def sync_folders(src: Path, dst: Path):
"""Sync src folder to dst folder, copying missing/updated files."""
dst.mkdir(parents=True, exist_ok=True)
for src_path in src.rglob("*"):
relative = src_path.relative_to(src)
dst_path = ds…How to Validate JSON Schema Shape in Python
Validate JSON data against a schema using manual checks for required fields, types, and constraints.
import json
from typing import Any, Dict
def validate_person_schema(data: Dict[str, Any]) -> bool:
"""Validate a person object against expected schema shape."""
if not isinstance(data, dict):
return False
# Required fields check
required_fields = {"name", "age", "email"}
if not requir…How to Validate a JSON File in Python
A beginner-friendly Python helper that reads a JSON file, catches common errors, and returns a status dictionary.
import json
from pathlib import Path
def get_valid_json_data(file_path: str) -> dict:
file = Path(file_path)
if not file.exists():
return {"status": "error", "message": f"File not found: {file_path}"}
try:
data = json.loads(file.read_text())
except json.JSONDecodeError as e:
…Normalize CSV Column Names to snake_case in Python
Convert CSV header names to snake_case using a regular expression and write the updated file in place.
import csv
import re
import sys
def to_snake_case(header):
header = re.sub(r"(?<=[a-z0-9])(?=[A-Z])", "_", header)
header = re.sub(r"[^a-zA-Z0-9]+", "_", header).strip("_").lower()
return header
def normalize_csv_headers(input_path, output_path=None):
with open(input_path, newline="", encoding="utf…Build an OrderedDict insertion order demo in Python 3
Demonstrate how OrderedDict preserves insertion order, how updates keep position, and how re-insertion moves keys to the end.
from collections import OrderedDict
def demo_ordered_dict():
# Create an OrderedDict and insert items in a specific order
ordered = OrderedDict()
ordered['banana'] = 3
ordered['apple'] = 2
ordered['cherry'] = 5
ordered['date'] = 1
print("Insertion order preserved:")
for key, value in …How to Build a Two-Way Dictionary in Python
Implement a BiDict class that supports both forward key-to-value and reverse value-to-key lookups with a simple add, delete, and update API.
class BiDict:
def __init__(self, data=None):
self.forward = {}
self.backward = {}
if data:
self.update(data)
def update(self, data):
for key, value in data.items():
self[key] = value
def __setitem__(self, key, value):
self.forward[key] = val…How to Compute Set Union of Tags from Multiple Items in Python
Collect all unique tags from a list of dictionaries using set union with update() in Python.
items = [
{"id": 1, "tags": {"python", "web"}},
{"id": 2, "tags": {"web", "api", "sql"}},
{"id": 3, "tags": {"python", "data"}},
]
def get_union_of_tags(item_list):
all_tags = set()
for item in item_list:
all_tags.update(item["tags"])
return all_tags
if __name__ == "__main__":
u…How to Merge Dictionaries and Find Unique Keys in Python
Merge two dictionaries with update(), then use sets to find all unique keys and the keys shared between both dictionaries.
def merge_and_unique(dict1, dict2):
merged = dict1.copy()
merged.update(dict2)
unique_keys = set(merged.keys())
common_keys = set(dict1.keys()) & set(dict2.keys())
return merged, unique_keys, common_keys
if __name__ == "__main__":
fruits = {"apple": 3, "banana": 5, "orange": 2}
more_fruit…How to Validate JSON Types per Key in Python
Load a JSON object and validate the type of each key against an expected schema, reporting missing or mismatched fields.
import json
from typing import Any, Dict, Type
def validate_json_types(data: Dict[str, Any], schema: Dict[str, Type]) -> Dict[str, str]:
"""Validate that each key in data matches the expected type in schema."""
errors = {}
for key, expected_type in schema.items():
if key not in data:
e…How to Validate Required Dict Keys in Python
Check whether a dictionary contains all required keys and return the list of missing ones using a simple list comprehension.
def find_missing_keys(data: dict, required_keys: list) -> list:
"""Return a list of required keys that are missing from the dictionary."""
return [key for key in required_keys if key not in data]
if __name__ == "__main__":
user_data = {
"name": "Alice",
"email": "alice@example.com",
…How to Validate Text and Count Words in Python
Count word frequencies, find unique and repeated words in a text using Python dictionaries and sets for beginner text validation.
def validate_text(text):
words = text.lower().split()
word_counts = {}
for word in words:
cleaned = word.strip('.,!?;:"\'')
if cleaned:
word_counts[cleaned] = word_counts.get(cleaned, 0) + 1
unique_words = set(word_counts.keys())
repeated_words = {word for word…Multiset with Counter update and elements in Python
Demonstrates using collections.Counter as a multiset: updating counts with update() and iterating elements() to get repeated items.
from collections import Counter
multiset = Counter(['apple', 'banana', 'apple'])
multiset.update(['banana', 'cherry', 'apple'])
print("Elements after update:", sorted(multiset.elements()))
print("Counts:", dict(multiset))
print("Most common:", multiset.most_common(2))Serialize Python dict to JSON with custom default for datetime
Convert a Python dict containing datetime and set objects into JSON by providing a custom default serializer.
import json
from datetime import datetime
def custom_serializer(obj):
if isinstance(obj, datetime):
return obj.isoformat()
if isinstance(obj, set):
return list(obj)
return str(obj)
data = {
"name": "Alice",
"created_at": datetime(2024, 3, 15, 10, 30, 45),
"tags": {"python", "j…Validate dictionary data with sets in Python
Validate a dictionary against required keys and allowed value sets, returning a list of validation errors.
def validate_data(data, required_keys, allowed_values=None):
"""
Validate a dictionary against required keys and optional allowed value sets.
Returns a list of validation errors (empty list if valid).
"""
errors = []
# Check for missing required keys
missing = set(required_keys) - set(…Add property getter setter validation in Python
Shows how to use @property with a setter to validate values before assigning them in a Python class.
class Temperature:
def __init__(self, celsius=0):
self._celsius = celsius # Use underscore to avoid recursion
@property
def celsius(self):
"""Getter returns the stored value."""
return self._celsius
@celsius.setter
def celsius(self, value):
"""Setter valid…How to Build an In-Memory CRUD Repository Class in Python
Define a Python Repository class that stores objects in a dictionary and supports create, read, update, delete, and list operations.
class Repository:
def __init__(self):
self._data = {}
def create(self, key, value):
self._data[key] = value
return key
def read(self, key):
return self._data.get(key)
def update(self, key, value):
if key not in self._data:
raise KeyError(f"Key '{ke…How to Validate Data Types in Python with a Class
A beginner-friendly Python class that checks if a value is a string, integer, float, list, or empty, using simple methods and isinstance checks.
class DataValidator:
"""A simple data validation helper for beginners."""
def __init__(self, data):
self.data = data
def is_string(self):
return isinstance(self.data, str)
def is_integer(self):
return isinstance(self.data, int) and not isinstance(self.data, bool)
…How to Validate User Input with a Dataclass in Python
A dataclass stores name, age, and email, and a validator class checks each field, returning a dictionary of boolean results.
from dataclasses import dataclass
@dataclass
class UserInput:
name: str
age: int
email: str
def is_valid_name(self) -> bool:
return bool(self.name.strip()) and len(self.name.strip()) >= 2
def is_valid_age(self) -> bool:
return isinstance(self.age, int) and 0 < self.age < 150
…Validate dataclass fields with __post_init__ in Python
Add custom validation to a Python dataclass inside __post_init__, raising ValueError or TypeError for invalid field values.
from dataclasses import dataclass, field
from typing import Optional
@dataclass
class Product:
name: str
price: float
quantity: int = 1
category: Optional[str] = None
def __post_init__(self):
if not self.name or not isinstance(self.name, str):
raise ValueError("name must be a…Validate Sudoku Board Rows Columns and Boxes in Python
Validate a 9x9 Sudoku board by checking that each row, column, and 3x3 box contains the numbers 1 through 9 exactly once.
def validate_sudoku(board):
def is_valid_group(group):
return sorted(group) == list(range(1, 10))
def get_columns():
return [[board[r][c] for r in range(9)] for c in range(9)]
def get_boxes():
boxes = []
for box_row in range(0, 9, 3):
for box_col in range(0, 9,…How to Validate Data with Python Comprehensions and Generators
Use list, generator, and dictionary comprehensions to filter and transform data for quick validation in Python.
def validate_integer(data):
return [item for item in data if isinstance(item, int)]
def validate_positive(numbers):
return (num for num in numbers if num > 0)
def validate_string_lengths(data, min_length=3):
return {item: len(item) for item in data if isinstance(item, str) and len(item) >= min_length}
i…How to Build a Zero-Shot Classification Prompt in Python
Creates a prompt for zero-shot text classification by pairing input text with candidate labels and a hypothesis template.
from typing import Dict, List
def build_zero_shot_prompt(
text: str,
candidate_labels: List[str],
hypothesis_template: str = "This is about {}.",
) -> Dict[str, List[str]]:
"""Build a prompt ready for zero-shot classification."""
return {
"sequences": text,
"candidate_labels": can…How to Validate JSON Output Against a Dict Schema in Python
Validate JSON-like data against a simple dict schema with type checking and descriptive error messages using only the Python standard library.
from typing import Dict, Any, List, Union
def validate_json(data: Any, schema: Dict[str, str]) -> List[str]:
"""
Validate JSON-like data against a simple dict schema.
Schema format: {field_name: expected_type} where type is one of:
'str', 'int', 'float', 'bool', 'list', 'dict', 'any'
Returns list …Browse by section
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