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How to Dump a Debugging Repr for Unknown Types in Python
Build a fallback repr that shows dataclass fields or object attributes for any value, handy when debugging unknown types.
import dataclasses
from typing import Any
@dataclasses.dataclass
class Sample:
name: str
values: list[int]
def dump_repr(obj: Any) -> str:
"""Return a concise but complete repr for debugging unknown types."""
if dataclasses.is_dataclass(obj):
fields = ", ".join(
f"{field.name}={…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 Serialize a Python Object to Pickle Bytes in Memory
Serialize a Python object to pickle bytes in memory with pickle.dumps, then deserialize it back with pickle.loads and verify the roundtrip.
import pickle
class Person:
def __init__(self, name, age, skills):
self.name = name
self.age = age
self.skills = skills
def main():
person = Person("Alice", 30, ["Python", "SQL", "Docker"])
# Serialize to bytes in memory
pickle_bytes = pickle.dumps(person)
print(…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…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…Design a Data Helper Class in Python
Create a simple Object-Oriented data helper with DataPoint and Dataset classes that store, describe, and summarize coordinate points.
class DataPoint:
def __init__(self, x, y):
self.x = x
self.y = y
self.label = None
def describe(self):
"""Return a human-readable description of the data point."""
base = f"DataPoint(x={self.x}, y={self.y})"
return f"{base}, label='{self.label}'" if self.label e…How to Build a Data Helper Class in Python with OOP
Create a beginner-friendly Python class that loads CSV data, filters records by field, and counts entries using object-oriented programming.
class DataHelper:
"""A beginner-friendly OOP helper for handling simple datasets."""
def __init__(self, filename):
self.filename = filename
self.data = self._load_data()
def _load_data(self):
"""Load data from a CSV file into a list of dictionaries."""
import csv
…How to Build a Fluent Interface with the Builder Pattern in Python
Learn to implement a fluent builder pattern in Python by chaining methods that return self, enabling readable object construction.
class Pizza:
def __init__(self):
self.size = None
self.toppings = []
self.crust = None
def set_size(self, size):
self.size = size
return self
def add_topping(self, topping):
self.toppings.append(topping)
return self
def set_crust(self, crust):
…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 Copy Class Instances in Python: Shallow vs Deep Copy
Use copy.copy and copy.deepcopy to clone class instances, showing how nested objects are shared or duplicated.
import copy
class Config:
def __init__(self):
self.settings = {"theme": "dark", "language": "en"}
if __name__ == "__main__":
original = Config()
shallow_copy = copy.copy(original)
deep_copy = copy.deepcopy(original)
shallow_copy.settings["theme"] = "light"
deep_copy.settings["them…How to Define a Simple Class with __init__ and __repr__ in Python
Defines a Person class with __init__ to store name and age, and __repr__ to give a readable string representation.
class Person:
def __init__(self, name, age):
self.name = name
self.age = age
def __repr__(self):
return f"Person(name='{self.name}', age={self.age})"
if __name__ == "__main__":
p1 = Person("Alice", 30)
p2 = Person("Bob", 25)
print(p1)
print(p2)How to Define a Simple Python Class with __init__ and __repr__
Define a basic Python class with an __init__ method to set instance attributes and a __repr__ method for a readable representation of objects.
class Person:
def __init__(self, name, age):
self.name = name
self.age = age
def __repr__(self):
return f"Person(name={self.name!r}, age={self.age!r})"
if __name__ == "__main__":
person = Person("Alice", 30)
print(person)How to Implement Rich Comparison Ordering in Python Classes
This code demonstrates how to implement rich comparison operators (like <, <=, >, >=, ==, !=) in a Python class by defining __lt__ and __eq__, enabling sorting and ordering of custom objects.
class Task:
def __init__(self, priority, name):
self.priority = priority
self.name = name
def __lt__(self, other):
if not isinstance(other, Task):
return NotImplemented
return self.priority < other.priority
def __eq__(self, other):
if not isinstance(oth…Python object equality: id vs value comparison
Demonstrates the difference between default identity comparison and custom equality, with a value-based class implementing __eq__ and __hash__.
import copy
class IdOnly:
def __init__(self, name):
self.name = name
class ValueId:
def __init__(self, name):
self.name = name
def __eq__(self, other):
return isinstance(other, ValueId) and self.name == other.name
def __hash__(self):
return hash(self.name)
def…How to Parse JSON from LLM Model Output Fence in Python
Extract and parse a JSON object from a language model's output that may be wrapped in triple-backtick fences with an optional language tag.
import json
import re
def parse_json_from_fence(text):
"""
Extract JSON object from a model output that may be wrapped in
triple-backtick fences with optional language tag.
"""
# Match content insideJSON Mode Prompt Schema Output in Python
Extract a user object to JSON with explicit schema keys, ready for LLM JSON-mode prompts.
import json
from typing import Any, Dict
def extract_user_as_json(user: Dict[str, Any]) -> str:
"""Extract a user object and return it as JSON using explicit schema keys."""
schema_fields = ("id", "name", "email", "is_active")
user_subset = {key: user[key] for key in schema_fields if key in user}
ret…Serialize and Format Data for LLM Prompts in Python
Use dataclasses and the json module to convert Python objects to JSON strings, parse them back, and format structured data into prompt-friendly text for LLM calls.
import json
from dataclasses import dataclass, asdict
@dataclass
class Recipe:
"""Simple data model to represent a recipe."""
name: str
cuisine: str
prep_minutes: int
def to_json(recipe: Recipe) -> str:
"""Serialize a Recipe to a JSON string."""
return json.dumps(asdict(recipe), indent=2)
…How to Make a Shallow Clone of an Object in Python
Demonstrates using copy.copy() to create a shallow clone of a Python object, showing how nested mutable data is shared while top-level attributes are independent.
import copy
class Config:
def __init__(self):
self.settings = {"volume": 50}
self.user = "admin"
def demonstrate_shallow_copy():
original = Config()
shallow = copy.copy(original)
# Mutating nested object is visible in both (shallow copy share it)
shallow.settings["volume"] = 90…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…Mock Lambda handler event context dict in Python
Simulates an AWS Lambda invocation by passing a mock event dict and context object to a handler, then prints the response.
import json
def lambda_handler(event, context):
"""
A mock AWS Lambda handler that processes an event dict and context object.
Demonstrates the typical Lambda function signature and basic event/context usage.
"""
print("Received event:", json.dumps(event, indent=2))
print("Function name:", co…How to Use TypedDict and Dataclasses in Python
Create typed data structures with TypedDict and dataclasses, then use them as helper functions for describing objects in a type-safe way.
from typing import TypedDict, NotRequired, Optional
from dataclasses import dataclass
class User(TypedDict):
name: str
age: NotRequired[int]
email: Optional[str]
@dataclass
class Product:
id: int
title: str
price: float = 0.0
def describe_user(user: User) -> str:
age = user.get("age",…Builder pattern for mocking complex objects in Python
Use a fluent Builder to construct realistic mock objects with defaults, enabling readable test data setup.
class User:
def __init__(self):
self.name = "default"
self.age = 0
self.email = "unknown@example.com"
self.address = "unknown"
def __repr__(self):
return f"User(name={self.name!r}, age={self.age}, email={self.email!r}, address={self.address!r})"
class UserBuilder:
…How to Implement a Factory Method by Type String in Python
A factory method maps a type string to a class, creating and returning the appropriate object instance while handling unknown types gracefully.
class Animal:
def speak(self):
raise NotImplementedError
class Dog(Animal):
def speak(self):
return "Woof!"
class Cat(Animal):
def speak(self):
return "Meow!"
class AnimalFactory:
@staticmethod
def create(animal_type: str) -> Animal:
animal_types = {
…How to Implement the Prototype Pattern with Deep Copy in Python
Implements the Prototype design pattern using copy.deepcopy to clone complex objects without sharing mutable state.
import copy
from dataclasses import dataclass, field
from typing import List
@dataclass
class Engine:
horsepower: int
@dataclass
class Car:
brand: str
engine: Engine
accessories: List[str] = field(default_factory=list)
def clone_prototype(car: Car) -> Car:
return copy.deepcopy(car)
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