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How to List File Metadata in Python
This code walks a directory and returns a list of JSON-ready dicts with each file's name, size, and modification time.
from pathlib import Path
import json
def format_files_data(directory_path):
"""Return a list of JSON-serializable dicts with file metadata."""
base = Path(directory_path)
if not base.is_dir():
raise ValueError(f"Not a directory: {directory_path}")
files_data = []
for file_path in base.ite…How to Load and Save JSON Files in Python
Load and save JSON files with pretty formatting using Python's standard library json module and pathlib.
import json
from pathlib import Path
def load_json(filepath: str) -> dict:
"""Load JSON data from a file."""
path = Path(filepath)
with path.open("r", encoding="utf-8") as f:
return json.load(f)
def save_json(filepath: str, data: dict) -> None:
"""Save data to a JSON file with pretty format…How to Parse JSON, TXT, and CSV Files in Python
This code provides simple functions to read and parse JSON, text, and CSV files using Python's standard library, returning native data structures.
import json
from pathlib import Path
def parse_json_file(filepath):
"""Read and parse a JSON file, returning its contents."""
path = Path(filepath)
with path.open('r', encoding='utf-8') as f:
return json.load(f)
def parse_txt_lines(filepath):
"""Read a text file and return non-empty stripped …How to Parse NDJSON Lines into a List in Python
Reads a JSON-lines (NDJSON) file line by line and converts each non-empty line into a Python object, returning a list.
import json
from pathlib import Path
def parse_ndjson(file_path: str) -> list:
data = []
with Path(file_path).open("r", encoding="utf-8") as f:
for line in f:
line = line.strip()
if line:
data.append(json.loads(line))
return data
if __name__ == "__main__"…How to Sum a CSV Column by Group in Python
This code reads a CSV string and sums a specified column for each unique value of a group key using the csv module and defaultdict.
import csv
from collections import defaultdict
from io import StringIO
def aggregate_csv(csv_data, group_key, sum_column):
totals = defaultdict(float)
reader = csv.DictReader(StringIO(csv_data))
for row in reader:
key = row[group_key]
totals[key] += float(row[sum_column])
return dict(t…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 Write Bytes to a File in Python with 'wb'
Write a bytearray buffer to a binary file using Python's open() in 'wb' mode, then read it back to confirm the data.
data = bytearray([0x48, 0x65, 0x6c, 0x6c, 0x6f, 0x20, 0x57, 0x6f, 0x72, 0x6c, 0x64])
with open("output.bin", "wb") as f:
f.write(data)
with open("output.bin", "rb") as f:
content = f.read()
print(f"Written {len(data)} bytes: {content}")
print(f"As string: {content.decode('ascii')}")How to Write Simple XML Documents with ElementTree in Python
Create well-structured XML documents in memory using Python's built-in ElementTree module, complete with nested elements, attributes, and text content.
import xml.etree.ElementTree as ET
def create_xml_document():
# Create root element
root = ET.Element("catalog")
# Create a book element with attributes and children
book1 = ET.SubElement(root, "book", id="bk101")
ET.SubElement(book1, "author").text = "Gambardella, Matthew"
ET.SubElement(…How to check file data in Python
Check if a file exists and is a regular file, then return its name, size, line count, and first line.
def check_file_data(file_path):
from pathlib import Path
path = Path(file_path)
if not path.exists():
return f"File '{file_path}' does not exist."
if not path.is_file():
return f"'{file_path}' is not a regular file."
size = path.stat().st_size
lines = path.read_text(encodin…Parameterize SQL queries in Python to prevent SQL injection
Safely fetch users from a SQLite database using parameterized queries to prevent SQL injection attacks.
import sqlite3
def get_users_by_name(name):
"""Fetch users safely using parameterized query."""
conn = sqlite3.connect(':memory:')
cursor = conn.cursor()
# Create sample table and data
cursor.execute('CREATE TABLE users (id INTEGER, name TEXT)')
cursor.executemany('INSERT INTO users (name…Parse Fixed Width Data File by Column Slices in Python
Extract fields from fixed-width text by slicing each line at defined column offsets, with a dictionary describing the boundaries.
from pathlib import Path
def parse_fixed_width(data: str, slices: dict[str, tuple[int, int]]) -> list[dict[str, str]]:
lines = data.strip().splitlines()
records = []
for line in lines:
record = {}
for name, (start, end) in slices.items():
record[name] = line[start:end].strip()…Read Parquet-Like Columnar CSV Chunks in Python
A Python generator that reads a CSV file column-by-column, yielding dictionary chunks where each key points to a list of values—mirroring how Parquet stores data columnar.
```python
import csv
from pathlib import Path
from typing import Iterator, List
def read_parquet_like_columnar(csv_path: str, column_names: List[str], chunk_size: int = 2) -> Iterator[dict]:
"""Read CSV data in columnar chunks, similar to how parquet stores columns."""
csv_file = Path(csv_path)
with csv_f…Read SQLite database with sqlite3 module in Python
Connect to a SQLite database and query rows with the standard library sqlite3 module, returning results as dictionaries.
import sqlite3
from pathlib import Path
# Create an in-memory database and a sample table
connection = sqlite3.connect(":memory:")
cursor = connection.cursor()
cursor.execute("""
CREATE TABLE employees (
id INTEGER PRIMARY KEY,
name TEXT NOT NULL,
department TEXT NOT NULL,
salary REAL
)
""")
# Inser…Read a CSV File with csv.DictReader in Python
Read a CSV file as a list of dictionaries, using csv.DictReader to map each row to column names.
import csv
from pathlib import Path
def read_csv_with_dictreader(file_path):
data = []
with open(file_path, mode='r', newline='', encoding='utf-8') as csvfile:
reader = csv.DictReader(csvfile)
for row in reader:
data.append(row)
return data
if __name__ == "__main__":
# Cre…Scrape HTML Tables and Convert Them to CSV Using Beautiful Soup in Python
Scrape a Wikipedia table with Beautiful Soup and write the data to a CSV file using the csv module.
import requests
from bs4 import BeautifulSoup
import csv
url = "https://en.wikipedia.org/wiki/List_of_countries_by_GDP_(nominal)"
response = requests.get(url)
soup = BeautifulSoup(response.text, 'html.parser')
tables = soup.find_all('table', {'class': 'wikitable'})
if tables:
target_table = tables[2]
rows =…Build a Case-Insensitive Dict with a Wrapper Class in Python
Create a custom dict subclass that treats keys as case-insensitive by normalizing them to lowercase, with a full set of common dict methods.
class CaseInsensitiveDict:
def __init__(self, data=None):
self._data = {}
if data:
self.update(data)
def __setitem__(self, key, value):
self._data[str(key).lower()] = value
def __getitem__(self, key):
return self._data[str(key).lower()]
def __delitem__(sel…Compare Two Dictionaries in Python
Compare two dictionaries by finding common keys, unique keys, and value differences using Python's set operations.
def compare_data(dict1, dict2):
"""Compare two dictionaries and summarize similarities/differences."""
keys1 = set(dict1.keys())
keys2 = set(dict2.keys())
common_keys = keys1 & keys2
only_in_first = keys1 - keys2
only_in_second = keys2 - keys1
print(f"Common keys ({len(common_keys…Find All Leaf Paths in a Nested Dict in Python
Recursively traverse a nested dictionary and yield every leaf path as a list of keys, including paths to empty dictionaries.
def find_leaf_paths(data, path=None):
if path is None:
path = []
if not isinstance(data, dict) or not data:
yield path
return
for key, value in data.items():
yield from find_leaf_paths(value, path + [key])
if __name__ == "__main__":
nested = {
"a": 1,
…Group Data by Key in Python with Dictionaries and Sets
Group items into a dictionary of sets using a key function, a beginner-friendly pattern for organizing data by categories.
def group_data(items, key_func):
"""Group items into a dictionary of sets based on a key function."""
grouped = {}
for item in items:
key = key_func(item)
if key not in grouped:
grouped[key] = set()
grouped[key].add(item)
return grouped
if __name__ == "__main__":
…How to Aggregate Order Data with Sets and Dictionaries in Python
Combine sets and dictionaries to find unique products and total quantities from a list of orders in Python.
def find_unique_products(orders):
"""Return set of all products ordered across multiple orders."""
all_products = set()
for order in orders:
all_products.update(order.get("items", []))
return all_products
def product_summary(orders):
"""Build a dictionary mapping each product to its total…How to Build a Gradebook with Python Dictionaries and Sets
Create a gradebook dictionary from student names and grades, find top students with a set comprehension, and add extra credit with a dict comprehension.
def build_gradebook(students, grades):
"""Create a dictionary mapping student names to their grades."""
return dict(zip(students, grades))
def find_top_students(gradebook, passing_grade=60):
"""Return a set of students with grades at or above the passing grade."""
return {name for name, grade in grad…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 Check Data Type and Inspect Dictionaries and Sets in Python
Inspect dictionaries and sets by printing their contents, types, and sizes using a small helper function.
def check_data(data):
"""Helper to inspect dictionaries and sets."""
if isinstance(data, dict):
print(f"Dictionary with {len(data)} keys")
for key, value in data.items():
print(f" {key}: {value} ({type(value).__name__})")
elif isinstance(data, set):
print(f"Set with {le…How to Count Tags with Sets and Dictionaries in Python
Count tag frequencies and collect unique tags from a list of dictionaries using Counter and sets in Python.
from collections import Counter
import json
def count_tags(entries):
"""Count tag frequencies across a list of entry dicts, using sets/dicts."""
tag_counter = Counter()
all_tags = set()
for entry in entries:
tags = set(entry["tags"])
all_tags.update(tags)
tag_counter.update(ta…Browse by section
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Samples are quick reference — one concept per page. For step-by-step teaching, use our Python tutorials. To test yourself, try quizzes or coding challenges. Clean up style with the Python formatter.