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Convert Natural Language Dates to Datetime in Python
Parse common natural language date phrases like 'tomorrow' or 'in 3 days' into Python datetime objects using regex and timedelta.
from datetime import datetime, timedelta
import re
def parse_natural_date(text: str) -> datetime:
"""Convert common natural language date expressions to datetime objects."""
now = datetime.now()
text = text.lower().strip()
# Handle relative dates
patterns = {
r"today": now,
r"…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 a traceback to get the last frame in Python
Extracts the innermost frame's file, line, and function name from a Python traceback object.
import sys
import traceback
def parse_traceback_last_frame(exc_info):
"""Return the file, line, and function of the last (innermost) frame."""
_, _, tb = exc_info
last_tb = tb
while last_tb.tb_next is not None:
last_tb = last_tb.tb_next
filename = last_tb.tb_frame.f_code.co_filename
l…Calculate Working Hours Between Two Dates in Python
Compute total business hours (Mon-Fri, 09:00-17:00) between two datetime objects, excluding weekends and non-working hours.
from datetime import datetime, timedelta
def work_hours_between(start: datetime, end: datetime) -> float:
"""Calculate total working hours between two datetimes (Mon-Fri, 09:00-17:00)."""
def is_workday(d: datetime) -> bool:
return d.weekday() < 5
total_hours = 0.0
current = start
whi…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…How to Implement the Command Pattern with Undo in Python
Python code demonstrating the Command design pattern with undo and redo support using action objects and a history manager.
class Command:
def execute(self):
raise NotImplementedError
def undo(self):
raise NotImplementedError
class AddTextCommand(Command):
def __init__(self, document, text):
self.document = document
self.text = text
def execute(self):
self.document.append(self.tex…How to Implement the State Pattern in Python
Implement the State design pattern in Python by delegating behavior to state objects, letting a media player change actions dynamically without if-else chains.
class State:
def play(self, player): pass
def pause(self, player): pass
def stop(self, player): pass
class PlayingState(State):
def play(self, player):
return "Already playing"
def pause(self, player):
player.state = PausedState()
return "Pausing playback"
def stop(self…How to Use __getstate__ and __setstate__ for Pickle in Python
Customize Python object serialization with the pickle __getstate__ and __setstate__ hooks to control exactly what data is stored and how it is restored.
import pickle
class Temperature:
def __init__(self, celsius):
self.celsius = celsius
def __getstate__(self):
"""Customize what gets pickled."""
state = self.__dict__.copy()
# Convert to Fahrenheit for storage (simulate transformation)
state['fahrenheit'] = (self.celsiu…Memento Pattern in Python: Save and Restore Object State
Implement the Memento design pattern to snapshot and restore an object's state, demonstrated with a text editor undo feature.
class TextEditor:
def __init__(self, text="", cursor_pos=0):
self.text = text
self.cursor_pos = cursor_pos
def type_text(self, new_text):
self.text += new_text
self.cursor_pos += len(new_text)
def move_cursor(self, pos):
self.cursor_pos = max(0, min(pos, len(self.t…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…Visitor Pattern in Python: Double Dispatch Demo
Demonstrates the Visitor design pattern with double dispatch so operations on Dog and Cat objects are selected at runtime without modifying their classes.
class Animal:
def accept(self, visitor):
visitor.visit(self)
class Dog(Animal):
def speak(self):
return "Woof!"
class Cat(Animal):
def speak(self):
return "Meow!"
class SoundVisitor:
def visit(self, animal):
if isinstance(animal, Dog):
return self.visit_do…How to stream parse JSON arrays in Python
This code demonstrates two generators: one that streams a JSON array as individual chunks, and another that incrementally parses those chunks into Python objects using json.JSONDecoder.
import json
def json_array_stream(items):
"""Generator that yields JSON-encoded values one at a time."""
yield "["
for i, item in enumerate(items):
if i > 0:
yield ","
yield json.dumps(item)
yield "]"
def parse_json_stream(stream):
"""Consumes a stream of JSON fragme…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.
"""
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