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Collect Multiple Validation Errors in Python Before Raising
A chainable Validator class that accumulates all validation errors and raises them together in a single exception.
class ValidationError(Exception):
pass
class Validator:
def __init__(self):
self.errors = []
def validate_required(self, value, field_name):
if not value:
self.errors.append(f"{field_name} is required")
return self
def validate_email(self, email):
…How to Print an Exception Chain in Python for Debugging
A helper that walks an exception's __cause__ and __context__ chain, printing each level with indentation to make debugging nested errors clearer.
import sys
import traceback
def pretty_exception_chain(exc):
"""Print the full exception chain with cause/context details."""
chain = []
current = exc
seen = set()
while current is not None and id(current) not in seen:
seen.add(id(current))
chain.append(current)
curren…How to Re-raise Exceptions with 'raise from' in Python
Shows how to re-raise an exception with explicit context chaining using the 'raise ... from ...' syntax, so the original cause is preserved for debugging.
def divide_with_chain(a, b):
try:
result = a / b
return result
except ZeroDivisionError as original_error:
# Re-raise with explicit chaining context
raise ValueError("Cannot divide by zero") from original_error
def explain_chain():
try:
divide_with_chain(10, 0)
…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…Build a Generator Pipeline in Python: Filter Then Map
Create a lazy data pipeline by chaining generator functions that read, filter, map, and write data step by step.
def read_data():
return ["a", "bb", "ccc", "dd", "eeeee", "f"]
def filter_short(words):
return (word for word in words if len(word) >= 2)
def map_to_upper(words):
return (word.upper() for word in words)
def write_data(words):
for word in words:
print(word)
if __name__ == "__main__":
…Detect Circular Imports Across Python Projects Automatically
This script walks through all .py files in a directory, builds an import graph, and uses depth-first search to find cycles—printing each circular dependency chain.
import ast
import sys
from pathlib import Path
from collections import defaultdict, deque
def find_imports(filepath):
"""Return set of module names imported by a Python file."""
imports = set()
try:
with open(filepath) as f:
tree = ast.parse(f.read())
except (SyntaxError, UnicodeDe…Cross Account Role Chaining Mock Credentials in Python
Simulate AWS STS AssumeRole with mock credentials for cross-account role chaining in Python.
import json
class CredentialChain:
def __init__(self, account_id, role_name):
self.account_id = account_id
self.role_name = role_name
self.credentials = {}
def assume_role(self, session_name="mock_session"):
"""Simulate STS AssumeRole, returning mock credentials with expiry.""…How to Build a Pipe and Filter Text Processing Chain in Python
A functional pipe-and-filter chain that transforms text through uppercase, whitespace normalization, number removal, stopword filtering, and file export.
import re
import sys
def pipe_filter_chain(stream):
def uppercase(text):
return text.upper()
def strip_whitespace(text):
return " ".join(text.split())
def remove_numbers(text):
return re.sub(r"\d+", "", text)
def remove_stopwords(text, stopwords={"the", "and", "of", "in"}):…How to Build an sklearn Pipeline with ColumnTransformer in Python
A mock example showing how to chain preprocessing and a regression model into a single sklearn Pipeline, scaling numeric features and one-hot encoding categorical features with ColumnTransformer.
import numpy as np
from sklearn.compose import ColumnTransformer
from sklearn.preprocessing import StandardScaler, OneHotEncoder
from sklearn.pipeline import Pipeline
from sklearn.linear_model import LinearRegression
# Mock dataset
X = np.array([[1, 'red'], [2, 'blue'], [3, 'red'], [4, 'green'], [5, 'blue']], dtype=o…How to Mock a Kubeflow Pipeline in Python
Build a minimal in-memory mock of a Kubeflow pipeline DAG using dataclasses and OrderedDict to chain component functions.
from typing import Dict, Any
from dataclasses import dataclass, field
from collections import OrderedDict
@dataclass
class KubeflowPipelineMock:
"""A minimal mock of a Kubeflow pipeline DAG."""
name: str
components: OrderedDict[str, callable] = field(default_factory=OrderedDict)
def add_component(se…Browse by section
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