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id,label,modality,language,content,source,generator
code_human_000,human,code,python,"def parse_csv(fname):
# quick and dirty, assumes first row is header
rows = []
with open(fname) as f:
headers = f.readline().strip().split(',')
for line in f:
vals = line.strip().split(',')
if len(vals) != len(headers):
continue # skip malformed rows, happens more than you'd think
rows.append(dict(zip(headers, vals)))
return rows
# TODO: handle quoted fields with commas inside them
# TODO: maybe just use pandas lol",human_written,human
code_human_001,human,code,python,"class Node:
def __init__(self, val):
self.val = val
self.left = None
self.right = None
class BST:
def __init__(self):
self.root = None
def insert(self, val):
if not self.root:
self.root = Node(val)
return
cur = self.root
while True:
if val < cur.val:
if cur.left is None:
cur.left = Node(val)
break
cur = cur.left
else:
if cur.right is None:
cur.right = Node(val)
break
cur = cur.right
def search(self, val):
cur = self.root
while cur:
if val == cur.val: return True
cur = cur.left if val < cur.val else cur.right
return False",human_written,human
code_human_002,human,code,javascript,"// lifted this from stackoverflow and tweaked it
function debounce(fn, wait) {
let timer;
return function(...args) {
clearTimeout(timer);
timer = setTimeout(() => fn.apply(this, args), wait);
}
}
// usage: const handleResize = debounce(() => doThing(), 200)
// window.addEventListener('resize', handleResize)",human_written,human
code_human_003,human,code,python,"import re
# regex I've tested against like 50 addresses, probably not perfect
EMAIL_RE = re.compile(r'^[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}$')
def valid_email(s):
return bool(EMAIL_RE.match(s.strip()))
if __name__ == '__main__':
tests = ['user@example.com', 'bad@', 'also.bad', 'ok+filter@sub.domain.org']
for t in tests:
print(t, '->', valid_email(t))",human_written,human
code_human_004,human,code,python,"from collections import OrderedDict
class LRUCache:
def __init__(self, cap):
self.cap = cap
self.cache = OrderedDict()
def get(self, key):
if key not in self.cache:
return -1
self.cache.move_to_end(key)
return self.cache[key]
def put(self, key, val):
if key in self.cache:
self.cache.move_to_end(key)
self.cache[key] = val
if len(self.cache) > self.cap:
self.cache.popitem(last=False) # evict oldest",human_written,human
code_ai_000,ai,code,python,"import pandas as pd
import numpy as np
import os
def compute_summary_statistics(file_path: str) -> dict:
""""""
Reads a CSV file and computes summary statistics for each numeric column.
Args:
file_path: Path to the CSV file
Returns:
Dictionary containing summary statistics for each numeric column
""""""
if not os.path.exists(file_path):
raise FileNotFoundError(f""File not found: {file_path}"")
df = pd.read_csv(file_path)
numeric_df = df.select_dtypes(include=[np.number])
if numeric_df.empty:
return {""message"": ""No numeric columns found in the CSV file""}
summary = {}
for column in numeric_df.columns:
col_data = numeric_df[column]
summary[column] = {
""count"": int(col_data.count()),
""missing_values"": int(col_data.isna().sum()),
""mean"": round(float(col_data.mean()), 4),
""median"": round(float(col_data.median()), 4),
""mode"": round(float(col_data.mode()[0]), 4) if not col_data.mode().empty else None,
""std_dev"": round(float(col_data.std()), 4),
""variance"": round(float(col_data.var()), 4),
""min"": round(float(col_data.min()), 4),
""max"": round(float(col_data.max()), 4),
""range"": round(float(col_data.max() - col_data.min()), 4),
""25th_percentile"": round(float(col_data.quantile(0.25)), 4),
""50th_percentile"": round(float(col_data.quantile(0.50)), 4),
""75th_percentile"": round(float(col_data.quantile(0.75)), 4),
""iqr"": round(float(col_data.quantile(0.75) - col_data.quantile(0.25)), 4),
""skewness"": round(float(col_data.skew()), 4),
""kurtosis"": round(float(col_data.kurtosis()), 4),
""sum"":",claude-sonnet-4-6,claude
code_ai_001,ai,code,python,"class Node:
def __init__(self, value):
self.value = value
self.left = None
self.right = None
class BinarySearchTree:
def __init__(self):
self.root = None
def insert(self, value):
if self.root is None:
self.root = Node(value)
else:
self._insert_recursive(self.root, value)
def _insert_recursive(self, node, value):
if value < node.value:
if node.left is None:
node.left = Node(value)
else:
self._insert_recursive(node.left, value)
elif value > node.value:
if node.right is None:
node.right = Node(value)
else:
self._insert_recursive(node.right, value)
def search(self, value):
return self._search_recursive(self.root, value)
def _search_recursive(self, node, value):
if node is None:
return False
if value == node.value:
return True
elif value < node.value:
return self._search_recursive(node.left, value)
else:
return self._search_recursive(node.right, value)
def delete(self, value):
self.root = self._delete_recursive(self.root, value)
def _delete_recursive(self, node, value):
if node is None:
return None
if value < node.value:
node.left = self._delete_recursive(node.left, value)
elif value > node.value:
node.right = self._delete_recursive(node.right, value)
else:
# Node to delete found
if node.left is None:
return node.right
elif node.right is None:
return node.left
# Node has two children: find in-order successor (smallest in right subtree)
successor = self._find_min(node.right)
node.value = successor.value
node.right = self._delete_recursive(node.right, successor.value)
return node
def _find_min(self, node):
current = node
while current.left is not None:
current = current.left
return current
def inorder_traversal(self):
result = []
self._inorder_recursive(self.root, result)",claude-sonnet-4-6,claude
code_ai_002,ai,code,python,"import requests
from bs4 import BeautifulSoup
from datetime import datetime
import json
import re
def scrape_news_articles(url=None):
""""""
Scrapes article titles and dates from a news website.
Default target: BBC News
""""""
if url is None:
url = ""https://www.bbc.com/news""
headers = {
""User-Agent"": ""Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 ""
""(KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36"",
""Accept"": ""text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,*/*;q=0.8"",
""Accept-Language"": ""en-US,en;q=0.5"",
""Accept-Encoding"": ""gzip, deflate, br"",
""Connection"": ""keep-alive"",
}
articles = []
try:
print(f""Fetching articles from: {url}"")
response = requests.get(url, headers=headers, timeout=15)
response.raise_for_status()
soup = BeautifulSoup(response.text, ""html.parser"")
# Try multiple selectors for different news sites
scrapers = [
scrape_bbc,
scrape_generic_time_tags,
scrape_generic_article_tags,
]
for scraper in scrapers:
articles = scraper(soup, url)
if articles:
break
if not articles:
print(""No articles found with standard selectors. Trying fallback method..."")
articles = scrape_fallback(soup)
except requests.exceptions.RequestException as e:
print(f""Error fetching URL: {e}"")
return []
return articles
def scrape_bbc(soup, url):
""""""Scrape BBC News articles.""""""
articles = []
if ""bbc"" not in url.lower():
return articles
# BBC News selectors
article_selectors = [
""h3[data-testid='card-headline']"",
""h1[data-testid='headline']"",
"".gs-c-promo-heading__title"",
""",claude-sonnet-4-6,claude
code_ai_003,ai,code,javascript,"function debounce(callback, n) {
let timer;
return function(...args) {
clearTimeout(timer);
timer = setTimeout(() => {
callback.apply(this, args);
}, n);
};
}
// Example usage:
const handleInput = debounce((value) => {
console.log(""Input value:"", value);
}, 500);
handleInput(""H"");
handleInput(""He"");
handleInput(""Hel"");
handleInput(""Hell"");
handleInput(""Hello"");
// Only logs ""Input value: Hello"" after 500ms",claude-sonnet-4-6,claude
code_ai_004,ai,code,javascript,"class EventEmitter {
constructor() {
this.events = {};
}
on(event, listener) {
if (!this.events[event]) {
this.events[event] = [];
}
this.events[event].push(listener);
return this;
}
off(event, listener) {
if (!this.events[event]) {
return this;
}
this.events[event] = this.events[event].filter(l => l !== listener);
if (this.events[event].length === 0) {
delete this.events[event];
}
return this;
}
emit(event, ...args) {
if (!this.events[event]) {
return false;
}
this.events[event].forEach(listener => {
listener(...args);
});
return true;
}
}
// Example usage
const emitter = new EventEmitter();
const greet = (name) => console.log(`Hello, ${name}!`);
const farewell = (name) => console.log(`Goodbye, ${name}!`);
emitter.on('greet', greet);
emitter.on('greet', farewell);
console.log('Emitting greet event:');
emitter.emit('greet', 'Alice');
console.log('\nRemoving farewell listener:');
emitter.off('greet', farewell);
emitter.emit('greet', 'Bob');
console.log('\nEmitting unknown event:');
const result = emitter.emit('unknown', 'Charlie');
console.log('Event emitted:', result);",claude-sonnet-4-6,claude
code_ai_005,ai,code,python,"import re
def is_valid_email(email: str) -> bool:
pattern = r'^[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}$'
return bool(re.match(pattern, email))
if __name__ == ""__main__"":
test_emails = [
""user@example.com"",
""user.name+tag@example.co.uk"",
""user@subdomain.example.com"",
""invalid-email"",
""missing@domain"",
""@nodomain.com"",
""spaces in@email.com"",
""user@.com"",
""user@domain."",
""user123@example.org""
]
for email in test_emails:
result = is_valid_email(email)
print(f""{email}: {'Valid' if result else 'Invalid'}"")",claude-sonnet-4-6,claude
code_ai_006,ai,code,python,"from collections import OrderedDict
class LRUCache:
def __init__(self, capacity: int):
self.capacity = capacity
self.cache = OrderedDict()
def get(self, key: int) -> int:
if key not in self.cache:
return -1
self.cache.move_to_end(key)
return self.cache[key]
def put(self, key: int, value: int) -> None:
if key in self.cache:
self.cache.move_to_end(key)
self.cache[key] = value
if len(self.cache) > self.capacity:
self.cache.popitem(last=False)
if __name__ == ""__main__"":
cache = LRUCache(2)
cache.put(1, 1)
print(f""Put (1, 1): cache = {dict(cache.cache)}"")
cache.put(2, 2)
print(f""Put (2, 2): cache = {dict(cache.cache)}"")
print(f""Get 1: {cache.get(1)}"")
cache.put(3, 3)
print(f""Put (3, 3): cache = {dict(cache.cache)}"")
print(f""Get 2 (evicted): {cache.get(2)}"")
cache.put(4, 4)
print(f""Put (4, 4): cache = {dict(cache.cache)}"")
print(f""Get 1 (evicted): {cache.get(1)}"")
print(f""Get 3: {cache.get(3)}"")
print(f""Get 4: {cache.get(4)}"")",claude-sonnet-4-6,claude
code_ai_007,ai,code,javascript,"function deepClone(obj, visited = new WeakMap()) {
// Handle null, undefined, and primitive types
if (obj === null || obj === undefined) {
return obj;
}
if (typeof obj !== ""object"" && typeof obj !== ""function"") {
return obj;
}
// Handle circular references
if (visited.has(obj)) {
return visited.get(obj);
}
// Handle Date
if (obj instanceof Date) {
return new Date(obj.getTime());
}
// Handle RegExp
if (obj instanceof RegExp) {
return new RegExp(obj.source, obj.flags);
}
// Handle Map
if (obj instanceof Map) {
const clonedMap = new Map();
visited.set(obj, clonedMap);
obj.forEach((value, key) => {
clonedMap.set(deepClone(key, visited), deepClone(value, visited));
});
return clonedMap;
}
// Handle Set
if (obj instanceof Set) {
const clonedSet = new Set();
visited.set(obj, clonedSet);
obj.forEach((value) => {
clonedSet.add(deepClone(value, visited));
});
return clonedSet;
}
// Handle Array
if (Array.isArray(obj)) {
const clonedArray = [];
visited.set(obj, clonedArray);
obj.forEach((item, index) => {
clonedArray[index] = deepClone(item, visited);
});
return clonedArray;
}
// Handle Function
if (typeof obj === ""function"") {
return obj;
}
// Handle Symbol keys
const clonedObj = Object.create(Object.getPrototypeOf(obj));
visited.set(obj, clonedObj);
// Clone regular keys
for (const key of Object.keys(obj)) {
clonedObj[key] = deepClone(obj[key], visited);
}
// Clone Symbol keys
for (const sym of Object.getOwnPropertySymbols(obj)) {
clonedObj[sym] = deepClone(obj[sym], visited);
}
return clonedObj;
}
// Test the function
const original = {
name: """,claude-sonnet-4-6,claude
code_ai_008,ai,code,python,"def generate_permutations(lst):
if len(lst) <= 1:
return [lst]
permutations = []
for i, element in enumerate(lst):
remaining = lst[:i] + lst[i+1:]
for perm in generate_permutations(remaining):
permutations.append([element] + perm)
return permutations
if __name__ == ""__main__"":
sample_list = [1, 2, 3]
result = generate_permutations(sample_list)
print(f""All permutations of {sample_list}:"")
for perm in result:
print(perm)
print(f""Total permutations: {len(result)}"")",claude-sonnet-4-6,claude
code_ai_009,ai,code,python,"import time
import logging
from contextlib import contextmanager
logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
logger = logging.getLogger(__name__)
@contextmanager
def timer(name=""Code block""):
start_time = time.perf_counter()
try:
yield
finally:
end_time = time.perf_counter()
elapsed_time = end_time - start_time
logger.info(f""{name} executed in {elapsed_time:.6f} seconds"")
if __name__ == ""__main__"":
with timer(""Sleep example""):
time.sleep(1.5)
with timer(""List comprehension""):
result = [x ** 2 for x in range(100000)]
with timer(""String concatenation""):
text = """"
for i in range(10000):
text += str(i)",claude-sonnet-4-6,claude
code_ai_010,ai,code,python,"import pandas as pd
import numpy as np
import csv
import os
def compute_summary_statistics(file_path: str) -> dict:
""""""
Reads a CSV file and computes summary statistics for each numeric column.
Args:
file_path: Path to the CSV file
Returns:
Dictionary with column names as keys and statistics as values
""""""
if not os.path.exists(file_path):
raise FileNotFoundError(f""File not found: {file_path}"")
df = pd.read_csv(file_path)
numeric_columns = df.select_dtypes(include=[np.number]).columns
if len(numeric_columns) == 0:
return {""message"": ""No numeric columns found in the CSV file""}
summary = {}
for col in numeric_columns:
col_data = df[col].dropna()
summary[col] = {
""count"": int(col_data.count()),
""missing_values"": int(df[col].isnull().sum()),
""mean"": round(float(col_data.mean()), 4),
""median"": round(float(col_data.median()), 4),
""mode"": round(float(col_data.mode()[0]), 4) if not col_data.mode().empty else None,
""std_dev"": round(float(col_data.std()), 4),
""variance"": round(float(col_data.var()), 4),
""min"": round(float(col_data.min()), 4),
""max"": round(float(col_data.max()), 4),
""range"": round(float(col_data.max() - col_data.min()), 4),
""25th_percentile"": round(float(col_data.quantile(0.25)), 4),
""75th_percentile"": round(float(col_data.quantile(0.75)), 4),
""iqr"": round(float(col_data.quantile(0.75) - col_data.quantile(0.25)), 4),
""skewness"": round(float(col_data.skew()), 4),
""kurtosis"": round(float(col_data.kurtosis()), 4),
""sum"": round(float(col_data.sum()), 4),
}",claude-sonnet-4-6,claude
code_ai_011,ai,code,python,"class Node:
def __init__(self, value):
self.value = value
self.left = None
self.right = None
class BinarySearchTree:
def __init__(self):
self.root = None
def insert(self, value):
if self.root is None:
self.root = Node(value)
else:
self._insert_recursive(self.root, value)
def _insert_recursive(self, node, value):
if value < node.value:
if node.left is None:
node.left = Node(value)
else:
self._insert_recursive(node.left, value)
elif value > node.value:
if node.right is None:
node.right = Node(value)
else:
self._insert_recursive(node.right, value)
def search(self, value):
return self._search_recursive(self.root, value)
def _search_recursive(self, node, value):
if node is None:
return False
if value == node.value:
return True
elif value < node.value:
return self._search_recursive(node.left, value)
else:
return self._search_recursive(node.right, value)
def delete(self, value):
self.root = self._delete_recursive(self.root, value)
def _delete_recursive(self, node, value):
if node is None:
return None
if value < node.value:
node.left = self._delete_recursive(node.left, value)
elif value > node.value:
node.right = self._delete_recursive(node.right, value)
else:
# Node with only one child or no child
if node.left is None:
return node.right
elif node.right is None:
return node.left
# Node with two children: get inorder successor (smallest in right subtree)
min_larger_node = self._get_min(node.right)
node.value = min_larger_node.value
node.right = self._delete_recursive(node.right, min_larger_node.value)
return node
def _get_min(self, node):
current = node
while current.left is not None:
current = current.left
return current
def inorder_traversal(self):
result = []",claude-sonnet-4-6,claude
code_ai_012,ai,code,python,"import requests
from bs4 import BeautifulSoup
from datetime import datetime
import json
import re
def scrape_news_articles(url=None):
""""""
Scrapes article titles and dates from a news website.
Uses BBC News as the default example.
""""""
if url is None:
url = ""https://www.bbc.com/news""
headers = {
""User-Agent"": ""Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 ""
""(KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36"",
""Accept-Language"": ""en-US,en;q=0.9"",
""Accept-Encoding"": ""gzip, deflate, br"",
""Accept"": ""text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,*/*;q=0.8"",
""Connection"": ""keep-alive"",
}
articles = []
try:
response = requests.get(url, headers=headers, timeout=10)
response.raise_for_status()
soup = BeautifulSoup(response.content, ""html.parser"")
# Strategy 1: Look for time elements with article titles
time_elements = soup.find_all(""time"")
for time_el in time_elements:
date_text = (
time_el.get(""datetime"") or
time_el.get(""data-datetime"") or
time_el.get_text(strip=True)
)
# Try to find associated title by traversing parent elements
parent = time_el.parent
title = None
for _ in range(5): # Look up to 5 levels up
if parent is None:
break
heading = parent.find([""h1"", ""h2"", ""h3"", ""h4""])
if heading:
title = heading.get_text(strip=True)
break
parent = parent.parent
if title and date_text:
articles.append({
""title"": title,
""date"": date_text,
""source"": url
})
# Strategy 2: Look for article tags
if not articles:
article_tags = soup.find_all(""article",claude-sonnet-4-6,claude
code_ai_013,ai,code,javascript,"function debounce(callback, n) {
let timeoutId;
return function (...args) {
clearTimeout(timeoutId);
timeoutId = setTimeout(() => {
callback.apply(this, args);
}, n);
};
}
// Example usage
const debouncedFn = debounce((message) => {
console.log(`Called with: ${message}`);
}, 500);
debouncedFn(""first"");
debouncedFn(""second"");
debouncedFn(""third"");
// Only ""Called with: third"" will be logged after 500ms",claude-sonnet-4-6,claude
code_ai_014,ai,code,javascript,"class EventEmitter {
constructor() {
this.events = {};
}
on(event, listener) {
if (!this.events[event]) {
this.events[event] = [];
}
this.events[event].push(listener);
return this;
}
off(event, listener) {
if (!this.events[event]) {
return this;
}
this.events[event] = this.events[event].filter((l) => l !== listener);
if (this.events[event].length === 0) {
delete this.events[event];
}
return this;
}
emit(event, ...args) {
if (!this.events[event]) {
return false;
}
this.events[event].forEach((listener) => {
listener(...args);
});
return true;
}
}
// Example usage
const emitter = new EventEmitter();
const greet = (name) => console.log(`Hello, ${name}!`);
const farewell = (name) => console.log(`Goodbye, ${name}!`);
emitter.on(""greeting"", greet);
emitter.on(""greeting"", farewell);
console.log(""Emitting greeting event:"");
emitter.emit(""greeting"", ""Alice"");
console.log(""\nRemoving farewell listener:"");
emitter.off(""greeting"", farewell);
console.log(""Emitting greeting event again:"");
emitter.emit(""greeting"", ""Bob"");
console.log(""\nEmitting non-existent event:"");
console.log(emitter.emit(""nonExistent""));",claude-sonnet-4-6,claude
code_ai_015,ai,code,python,"import re
def is_valid_email(email):
pattern = r'^[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}$'
return bool(re.match(pattern, email))
# Test the function
test_emails = [
""user@example.com"",
""user.name+tag@example.co.uk"",
""user@subdomain.example.com"",
""invalid-email"",
""missing@domain"",
""@nodomain.com"",
""user@.com"",
""user@domain.c"",
""user name@domain.com"",
""user@domain..com""
]
for email in test_emails:
print(f""{email}: {'Valid' if is_valid_email(email) else 'Invalid'}"")",claude-sonnet-4-6,claude
code_ai_016,ai,code,python,"from collections import OrderedDict
class LRUCache:
def __init__(self, capacity: int):
self.capacity = capacity
self.cache = OrderedDict()
def get(self, key: int) -> int:
if key not in self.cache:
return -1
self.cache.move_to_end(key)
return self.cache[key]
def put(self, key: int, value: int) -> None:
if key in self.cache:
self.cache.move_to_end(key)
self.cache[key] = value
if len(self.cache) > self.capacity:
self.cache.popitem(last=False)
if __name__ == ""__main__"":
cache = LRUCache(2)
cache.put(1, 1)
print(f""Put (1, 1): cache = {dict(cache.cache)}"")
cache.put(2, 2)
print(f""Put (2, 2): cache = {dict(cache.cache)}"")
print(f""Get 1: {cache.get(1)}"")
cache.put(3, 3)
print(f""Put (3, 3): cache = {dict(cache.cache)}"")
print(f""Get 2: {cache.get(2)}"")
cache.put(4, 4)
print(f""Put (4, 4): cache = {dict(cache.cache)}"")
print(f""Get 1: {cache.get(1)}"")
print(f""Get 3: {cache.get(3)}"")
print(f""Get 4: {cache.get(4)}"")",claude-sonnet-4-6,claude
code_ai_017,ai,code,javascript,"function deepClone(obj, visited = new WeakMap()) {
// Handle null and non-object types
if (obj === null || typeof obj !== ""object"") {
return obj;
}
// Handle circular references
if (visited.has(obj)) {
return visited.get(obj);
}
// Handle Date
if (obj instanceof Date) {
return new Date(obj.getTime());
}
// Handle RegExp
if (obj instanceof RegExp) {
return new RegExp(obj.source, obj.flags);
}
// Handle Map
if (obj instanceof Map) {
const clonedMap = new Map();
visited.set(obj, clonedMap);
obj.forEach((value, key) => {
clonedMap.set(deepClone(key, visited), deepClone(value, visited));
});
return clonedMap;
}
// Handle Set
if (obj instanceof Set) {
const clonedSet = new Set();
visited.set(obj, clonedSet);
obj.forEach((value) => {
clonedSet.add(deepClone(value, visited));
});
return clonedSet;
}
// Handle Array
if (Array.isArray(obj)) {
const clonedArray = [];
visited.set(obj, clonedArray);
obj.forEach((item, index) => {
clonedArray[index] = deepClone(item, visited);
});
return clonedArray;
}
// Handle ArrayBuffer
if (obj instanceof ArrayBuffer) {
return obj.slice(0);
}
// Handle TypedArrays
if (ArrayBuffer.isView(obj)) {
return new obj.constructor(obj);
}
// Handle plain objects
const clonedObj = Object.create(Object.getPrototypeOf(obj));
visited.set(obj, clonedObj);
// Copy all own properties (including non-enumerable)
for (const key of Reflect.ownKeys(obj)) {
const descriptor = Object.getOwnPropertyDescriptor(obj, key);
if (descriptor.value !== undefined) {
descriptor.value = deepClone(descriptor.value, visited);
}
Object.defineProperty(clonedObj, key, descriptor);
}
return cloned",claude-sonnet-4-6,claude
code_ai_018,ai,code,python,"def generate_permutations(lst):
if len(lst) <= 1:
return [lst]
permutations = []
for i, element in enumerate(lst):
remaining = lst[:i] + lst[i+1:]
for perm in generate_permutations(remaining):
permutations.append([element] + perm)
return permutations
if __name__ == ""__main__"":
sample_list = [1, 2, 3]
result = generate_permutations(sample_list)
print(f""All permutations of {sample_list}:"")
for perm in result:
print(perm)
print(f""Total permutations: {len(result)}"")",claude-sonnet-4-6,claude
code_ai_019,ai,code,python,"import time
import logging
from contextlib import contextmanager
logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
logger = logging.getLogger(__name__)
@contextmanager
def timer(name: str = ""Code block""):
start_time = time.perf_counter()
try:
yield
finally:
end_time = time.perf_counter()
elapsed_time = end_time - start_time
logger.info(f""{name} executed in {elapsed_time:.4f} seconds"")
if __name__ == ""__main__"":
with timer(""Sleep test""):
time.sleep(1.5)
with timer(""List comprehension""):
result = [x ** 2 for x in range(1000000)]
with timer(""String concatenation""):
text = """"
for i in range(10000):
text += str(i)",claude-sonnet-4-6,claude
code_ai_020,ai,code,python,"import pandas as pd
import numpy as np
import csv
import os
def compute_summary_statistics(file_path: str) -> dict:
""""""
Reads a CSV file and computes summary statistics for each numeric column.
Args:
file_path: Path to the CSV file
Returns:
Dictionary containing summary statistics for each numeric column
""""""
if not os.path.exists(file_path):
raise FileNotFoundError(f""File not found: {file_path}"")
df = pd.read_csv(file_path)
numeric_df = df.select_dtypes(include=[np.number])
if numeric_df.empty:
return {""message"": ""No numeric columns found in the CSV file""}
summary = {}
for column in numeric_df.columns:
col_data = numeric_df[column].dropna()
if len(col_data) == 0:
summary[column] = {""message"": ""Column contains no valid numeric data""}
continue
q1 = col_data.quantile(0.25)
q3 = col_data.quantile(0.75)
iqr = q3 - q1
summary[column] = {
""count"": len(col_data),
""missing_values"": numeric_df[column].isna().sum(),
""mean"": round(col_data.mean(), 4),
""median"": round(col_data.median(), 4),
""mode"": round(col_data.mode()[0], 4) if not col_data.mode().empty else None,
""std_dev"": round(col_data.std(), 4),
""variance"": round(col_data.var(), 4),
""min"": round(col_data.min(), 4),
""max"": round(col_data.max(), 4),
""range"": round(col_data.max() - col_data.min(), 4),
""q1"": round(q1, 4),
""q3"": round(q3, 4),
""iqr"": round(iqr, 4),
""skewness"": round(col_data.skew(), 4),
""kurtosis"": round(col_data.kurtosis(), 4),
""sum"": round(col_data.sum(), 4),
}",claude-sonnet-4-6,claude
code_ai_021,ai,code,python,"class Node:
def __init__(self, value):
self.value = value
self.left = None
self.right = None
class BinarySearchTree:
def __init__(self):
self.root = None
def insert(self, value):
if self.root is None:
self.root = Node(value)
else:
self._insert_recursive(self.root, value)
def _insert_recursive(self, node, value):
if value < node.value:
if node.left is None:
node.left = Node(value)
else:
self._insert_recursive(node.left, value)
elif value > node.value:
if node.right is None:
node.right = Node(value)
else:
self._insert_recursive(node.right, value)
else:
print(f""Value {value} already exists in the tree."")
def search(self, value):
return self._search_recursive(self.root, value)
def _search_recursive(self, node, value):
if node is None:
return False
if value == node.value:
return True
elif value < node.value:
return self._search_recursive(node.left, value)
else:
return self._search_recursive(node.right, value)
def delete(self, value):
self.root = self._delete_recursive(self.root, value)
def _delete_recursive(self, node, value):
if node is None:
print(f""Value {value} not found in the tree."")
return node
if value < node.value:
node.left = self._delete_recursive(node.left, value)
elif value > node.value:
node.right = self._delete_recursive(node.right, value)
else:
# Node with only one child or no child
if node.left is None:
return node.right
elif node.right is None:
return node.left
# Node with two children
# Get the inorder successor (smallest in the right subtree)
min_larger_node = self._get_min(node.right)
node.value = min_larger_node.value
node.right = self._delete_recursive(node.right, min_larger_node.value)
return node
def _get_min(self, node):
current",claude-sonnet-4-6,claude
code_ai_022,ai,code,python,"import requests
from bs4 import BeautifulSoup
from datetime import datetime
import json
import re
def scrape_news_articles(url: str, headers: dict = None) -> list[dict]:
""""""
Scrape article titles and dates from a news website.
Args:
url: The URL of the news website to scrape
headers: Optional HTTP headers for the request
Returns:
List of dictionaries containing article titles and dates
""""""
if headers is None:
headers = {
""User-Agent"": (
""Mozilla/5.0 (Windows NT 10.0; Win64; x64) ""
""AppleWebKit/537.36 (KHTML, like Gecko) ""
""Chrome/91.0.4472.124 Safari/537.36""
)
}
articles = []
try:
response = requests.get(url, headers=headers, timeout=10)
response.raise_for_status()
soup = BeautifulSoup(response.text, ""html.parser"")
# Try multiple common HTML patterns for news articles
articles = (
extract_schema_articles(soup) or
extract_article_tags(soup) or
extract_common_class_patterns(soup)
)
if not articles:
print(""No articles found with standard patterns. Trying generic extraction..."")
articles = extract_generic_content(soup)
except requests.exceptions.RequestException as e:
print(f""Error fetching URL: {e}"")
return articles
def extract_schema_articles(soup: BeautifulSoup) -> list[dict]:
""""""Extract articles using JSON-LD schema markup.""""""
articles = []
for script in soup.find_all(""script"", type=""application/ld+json""):
try:
data = json.loads(script.string)
if isinstance(data, list):
items = data
elif isinstance(data, dict):
items = data.get(""@graph"", [data])
else:
continue
for item in items:
if isinstance(item, dict) and item.get(""@type"") in [""NewsArticle"", ""Article"", ""BlogPosting""]:
title = item.get(""headline"", """")
date = item.get(""datePublished"", """") or item.get(""dateCreated"", """")",claude-sonnet-4-6,claude
code_ai_023,ai,code,javascript,"function debounce(callback, n) {
let timer;
return function (...args) {
clearTimeout(timer);
timer = setTimeout(() => {
callback.apply(this, args);
}, n);
};
}",claude-sonnet-4-6,claude
code_ai_024,ai,code,javascript,"class EventEmitter {
constructor() {
this.events = {};
}
on(event, listener) {
if (!this.events[event]) {
this.events[event] = [];
}
this.events[event].push(listener);
return this;
}
off(event, listener) {
if (!this.events[event]) {
return this;
}
this.events[event] = this.events[event].filter((l) => l !== listener);
if (this.events[event].length === 0) {
delete this.events[event];
}
return this;
}
emit(event, ...args) {
if (!this.events[event]) {
return false;
}
this.events[event].forEach((listener) => {
listener(...args);
});
return true;
}
}
// Example usage
const emitter = new EventEmitter();
const greet = (name) => console.log(`Hello, ${name}!`);
const farewell = (name) => console.log(`Goodbye, ${name}!`);
emitter.on(""greet"", greet);
emitter.on(""greet"", farewell);
console.log(""Emitting 'greet' event:"");
emitter.emit(""greet"", ""Alice"");
console.log(""\nRemoving 'farewell' listener:"");
emitter.off(""greet"", farewell);
console.log(""Emitting 'greet' event again:"");
emitter.emit(""greet"", ""Bob"");
console.log(""\nEmitting non-existent event:"");
const result = emitter.emit(""nonExistent"");
console.log(`Event emitted: ${result}`);",claude-sonnet-4-6,claude
code_ai_025,ai,code,python,"import re
def is_valid_email(email: str) -> bool:
pattern = r'^[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}$'
return bool(re.match(pattern, email))
if __name__ == ""__main__"":
test_emails = [
""user@example.com"",
""user.name+tag@domain.co.uk"",
""user@subdomain.domain.com"",
""invalid-email"",
""missing@domain"",
""@nodomain.com"",
""spaces in@email.com"",
""user@.com"",
""user@domain."",
""valid_email123@company.org""
]
for email in test_emails:
result = is_valid_email(email)
print(f""{email}: {'Valid' if result else 'Invalid'}"")",claude-sonnet-4-6,claude
code_ai_026,ai,code,python,"from collections import OrderedDict
class LRUCache:
def __init__(self, capacity: int):
self.capacity = capacity
self.cache = OrderedDict()
def get(self, key: int) -> int:
if key not in self.cache:
return -1
self.cache.move_to_end(key)
return self.cache[key]
def put(self, key: int, value: int) -> None:
if key in self.cache:
self.cache.move_to_end(key)
self.cache[key] = value
if len(self.cache) > self.capacity:
self.cache.popitem(last=False)
if __name__ == ""__main__"":
cache = LRUCache(2)
cache.put(1, 1)
print(f""Put (1, 1): cache = {dict(cache.cache)}"")
cache.put(2, 2)
print(f""Put (2, 2): cache = {dict(cache.cache)}"")
print(f""Get 1: {cache.get(1)}"")
cache.put(3, 3)
print(f""Put (3, 3): cache = {dict(cache.cache)}"")
print(f""Get 2: {cache.get(2)}"")
cache.put(4, 4)
print(f""Put (4, 4): cache = {dict(cache.cache)}"")
print(f""Get 1: {cache.get(1)}"")
print(f""Get 3: {cache.get(3)}"")
print(f""Get 4: {cache.get(4)}"")",claude-sonnet-4-6,claude
code_ai_027,ai,code,javascript,"function deepClone(obj, visited = new WeakMap()) {
// Handle null and non-object types
if (obj === null || typeof obj !== 'object') {
return obj;
}
// Handle circular references
if (visited.has(obj)) {
return visited.get(obj);
}
// Handle Date
if (obj instanceof Date) {
return new Date(obj.getTime());
}
// Handle RegExp
if (obj instanceof RegExp) {
return new RegExp(obj.source, obj.flags);
}
// Handle Map
if (obj instanceof Map) {
const mapClone = new Map();
visited.set(obj, mapClone);
obj.forEach((value, key) => {
mapClone.set(deepClone(key, visited), deepClone(value, visited));
});
return mapClone;
}
// Handle Set
if (obj instanceof Set) {
const setClone = new Set();
visited.set(obj, setClone);
obj.forEach((value) => {
setClone.add(deepClone(value, visited));
});
return setClone;
}
// Handle Array
if (Array.isArray(obj)) {
const arrayClone = [];
visited.set(obj, arrayClone);
obj.forEach((item, index) => {
arrayClone[index] = deepClone(item, visited);
});
return arrayClone;
}
// Handle ArrayBuffer
if (obj instanceof ArrayBuffer) {
return obj.slice(0);
}
// Handle TypedArrays
if (ArrayBuffer.isView(obj)) {
return new obj.constructor(obj);
}
// Handle Symbol keys
const clone = Object.create(Object.getPrototypeOf(obj));
visited.set(obj, clone);
// Clone regular string keys
for (const key of Object.keys(obj)) {
clone[key] = deepClone(obj[key], visited);
}
// Clone symbol keys
for (const sym of Object.getOwnPropertySymbols(obj)) {
clone[sym] = deepClone(obj[sym], visited);
}
return clone;
}
// Example usage:
const original = {
name: 'John',
age: 30,",claude-sonnet-4-6,claude
code_ai_028,ai,code,python,"def generate_permutations(lst):
if len(lst) <= 1:
return [lst]
permutations = []
for i, element in enumerate(lst):
remaining = lst[:i] + lst[i+1:]
for perm in generate_permutations(remaining):
permutations.append([element] + perm)
return permutations
if __name__ == ""__main__"":
sample_list = [1, 2, 3]
result = generate_permutations(sample_list)
print(f""All permutations of {sample_list}:"")
for perm in result:
print(perm)
print(f""Total permutations: {len(result)}"")",claude-sonnet-4-6,claude
code_ai_029,ai,code,python,"import time
import logging
from contextlib import contextmanager
logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
logger = logging.getLogger(__name__)
@contextmanager
def timer(label=""Code block""):
start_time = time.perf_counter()
try:
yield
finally:
end_time = time.perf_counter()
elapsed_time = end_time - start_time
logger.info(f""{label} executed in {elapsed_time:.6f} seconds"")
if __name__ == ""__main__"":
with timer(""Sleep example""):
time.sleep(1.5)
with timer(""List comprehension""):
result = [x ** 2 for x in range(100000)]
with timer(""String concatenation""):
text = """"
for i in range(10000):
text += str(i)",claude-sonnet-4-6,claude
code_ai_030,ai,code,python,"import pandas as pd
import numpy as np
import csv
import os
def compute_summary_statistics(file_path: str) -> dict:
""""""
Reads a CSV file and computes summary statistics for each numeric column.
Args:
file_path: Path to the CSV file
Returns:
A dictionary with column names as keys and statistics as values
""""""
if not os.path.exists(file_path):
raise FileNotFoundError(f""File not found: {file_path}"")
df = pd.read_csv(file_path)
numeric_columns = df.select_dtypes(include=[np.number]).columns
if len(numeric_columns) == 0:
print(""No numeric columns found in the CSV file."")
return {}
summary = {}
for col in numeric_columns:
col_data = df[col].dropna()
summary[col] = {
""count"": len(col_data),
""missing_values"": df[col].isna().sum(),
""mean"": col_data.mean(),
""median"": col_data.median(),
""mode"": col_data.mode()[0] if not col_data.mode().empty else None,
""std"": col_data.std(),
""variance"": col_data.var(),
""min"": col_data.min(),
""max"": col_data.max(),
""range"": col_data.max() - col_data.min(),
""25th_percentile"": col_data.quantile(0.25),
""75th_percentile"": col_data.quantile(0.75),
""iqr"": col_data.quantile(0.75) - col_data.quantile(0.25),
""skewness"": col_data.skew(),
""kurtosis"": col_data.kurt(),
""sum"": col_data.sum()
}
return summary
def print_summary_statistics(file_path: str) -> None:
""""""
Prints formatted summary statistics for each numeric column in a CSV file.
Args:
file_path: Path to the CSV file
""""""
summary = compute_summary_statistics(file_path)
if not summary:
return
print(f""\n{'='*60}"")
print(f""Summary Statistics for: {os.path",claude-sonnet-4-6,claude
code_ai_031,ai,code,python,"class Node:
def __init__(self, value):
self.value = value
self.left = None
self.right = None
class BinarySearchTree:
def __init__(self):
self.root = None
def insert(self, value):
if self.root is None:
self.root = Node(value)
else:
self._insert_recursive(self.root, value)
def _insert_recursive(self, node, value):
if value < node.value:
if node.left is None:
node.left = Node(value)
else:
self._insert_recursive(node.left, value)
elif value > node.value:
if node.right is None:
node.right = Node(value)
else:
self._insert_recursive(node.right, value)
def search(self, value):
return self._search_recursive(self.root, value)
def _search_recursive(self, node, value):
if node is None:
return False
if value == node.value:
return True
elif value < node.value:
return self._search_recursive(node.left, value)
else:
return self._search_recursive(node.right, value)
def delete(self, value):
self.root = self._delete_recursive(self.root, value)
def _delete_recursive(self, node, value):
if node is None:
return None
if value < node.value:
node.left = self._delete_recursive(node.left, value)
elif value > node.value:
node.right = self._delete_recursive(node.right, value)
else:
# Node with only one child or no child
if node.left is None:
return node.right
elif node.right is None:
return node.left
# Node with two children: get inorder successor (smallest in right subtree)
min_larger_node = self._get_min(node.right)
node.value = min_larger_node.value
node.right = self._delete_recursive(node.right, min_larger_node.value)
return node
def _get_min(self, node):
current = node
while current.left is not None:
current = current.left
return current
def inorder_traversal(self):
result = []",claude-sonnet-4-6,claude
code_ai_032,ai,code,python,"import requests
from bs4 import BeautifulSoup
from datetime import datetime
import json
import re
def scrape_news_articles(url: str, headers: dict = None) -> list[dict]:
""""""
Scrape article titles and dates from a news website.
Args:
url: The URL of the news website to scrape
headers: Optional HTTP headers for the request
Returns:
List of dictionaries containing article titles and dates
""""""
if headers is None:
headers = {
'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 '
'(KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36'
}
try:
response = requests.get(url, headers=headers, timeout=10)
response.raise_for_status()
except requests.RequestException as e:
print(f""Error fetching URL: {e}"")
return []
soup = BeautifulSoup(response.content, 'html.parser')
articles = []
# Common patterns for article titles and dates
title_selectors = [
'h1', 'h2', 'h3',
'article h1', 'article h2', 'article h3',
'.article-title', '.post-title', '.entry-title',
'.headline', '.news-title', '.story-title',
'[class*=""title""]', '[class*=""headline""]',
'a[href*=""/article""]', 'a[href*=""/news""]',
'a[href*=""/story""]', 'a[href*=""/post""]'
]
date_selectors = [
'time', '.date', '.published', '.post-date',
'.article-date', '.entry-date', '.timestamp',
'[class*=""date""]', '[class*=""time""]', '[class*=""published""]',
'[datetime]', 'span[class*=""date""]', 'p[class*=""date""]'
]
# Try to find article containers first
article_containers = soup.find_all(['article', 'div'],
class_=re.compile(r'article|post|news|story|card', re.I))
if article_containers:
for",claude-sonnet-4-6,claude
code_ai_033,ai,code,javascript,"function debounce(callback, n) {
let timeoutId;
return function (...args) {
clearTimeout(timeoutId);
timeoutId = setTimeout(() => {
callback.apply(this, args);
}, n);
};
}
// Example usage
const debouncedFunction = debounce((message) => {
console.log(`Called with: ${message}`);
}, 500);
debouncedFunction(""Hello"");
debouncedFunction(""Hello again"");
debouncedFunction(""Final call""); // Only this will execute after 500ms",claude-sonnet-4-6,claude
code_ai_034,ai,code,javascript,"class EventEmitter {
constructor() {
this.events = {};
}
on(event, listener) {
if (!this.events[event]) {
this.events[event] = [];
}
this.events[event].push(listener);
return this;
}
off(event, listener) {
if (!this.events[event]) {
return this;
}
this.events[event] = this.events[event].filter(l => l !== listener);
if (this.events[event].length === 0) {
delete this.events[event];
}
return this;
}
emit(event, ...args) {
if (!this.events[event]) {
return false;
}
this.events[event].forEach(listener => listener(...args));
return true;
}
}
// Example usage
const emitter = new EventEmitter();
const greet = (name) => console.log(`Hello, ${name}!`);
const farewell = (name) => console.log(`Goodbye, ${name}!`);
emitter.on('greet', greet);
emitter.on('greet', farewell);
emitter.emit('greet', 'Alice');
// Output:
// Hello, Alice!
// Goodbye, Alice!
emitter.off('greet', farewell);
emitter.emit('greet', 'Bob');
// Output:
// Hello, Bob!",claude-sonnet-4-6,claude
code_ai_035,ai,code,python,"import re
def is_valid_email(email):
pattern = r'^[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}$'
return bool(re.match(pattern, email))
# Test examples
test_emails = [
""user@example.com"",
""user.name+tag@domain.co.uk"",
""invalid-email"",
""missing@domain"",
""@nodomain.com"",
""user@.com"",
""user@domain.c"",
""user123@sub.domain.com""
]
for email in test_emails:
print(f""{email}: {is_valid_email(email)}"")",claude-sonnet-4-6,claude
code_ai_036,ai,code,python,"from collections import OrderedDict
class LRUCache:
def __init__(self, capacity: int):
self.capacity = capacity
self.cache = OrderedDict()
def get(self, key: int) -> int:
if key not in self.cache:
return -1
self.cache.move_to_end(key)
return self.cache[key]
def put(self, key: int, value: int) -> None:
if key in self.cache:
self.cache.move_to_end(key)
self.cache[key] = value
if len(self.cache) > self.capacity:
self.cache.popitem(last=False)
if __name__ == ""__main__"":
cache = LRUCache(2)
cache.put(1, 1)
print(f""Put (1, 1): cache = {dict(cache.cache)}"")
cache.put(2, 2)
print(f""Put (2, 2): cache = {dict(cache.cache)}"")
print(f""Get 1: {cache.get(1)}"")
cache.put(3, 3)
print(f""Put (3, 3): cache = {dict(cache.cache)}"")
print(f""Get 2 (evicted): {cache.get(2)}"")
cache.put(4, 4)
print(f""Put (4, 4): cache = {dict(cache.cache)}"")
print(f""Get 1 (evicted): {cache.get(1)}"")
print(f""Get 3: {cache.get(3)}"")
print(f""Get 4: {cache.get(4)}"")",claude-sonnet-4-6,claude
code_ai_037,ai,code,javascript,"function deepClone(obj, visited = new WeakMap()) {
// Handle null and non-object types
if (obj === null || typeof obj !== 'object') {
return obj;
}
// Handle circular references
if (visited.has(obj)) {
return visited.get(obj);
}
// Handle Date
if (obj instanceof Date) {
return new Date(obj.getTime());
}
// Handle RegExp
if (obj instanceof RegExp) {
return new RegExp(obj.source, obj.flags);
}
// Handle Map
if (obj instanceof Map) {
const mapClone = new Map();
visited.set(obj, mapClone);
obj.forEach((value, key) => {
mapClone.set(deepClone(key, visited), deepClone(value, visited));
});
return mapClone;
}
// Handle Set
if (obj instanceof Set) {
const setClone = new Set();
visited.set(obj, setClone);
obj.forEach((value) => {
setClone.add(deepClone(value, visited));
});
return setClone;
}
// Handle Array
if (Array.isArray(obj)) {
const arrClone = [];
visited.set(obj, arrClone);
obj.forEach((item, index) => {
arrClone[index] = deepClone(item, visited);
});
return arrClone;
}
// Handle ArrayBuffer
if (obj instanceof ArrayBuffer) {
return obj.slice(0);
}
// Handle TypedArrays
if (ArrayBuffer.isView(obj)) {
return new obj.constructor(obj.buffer.slice(0));
}
// Handle plain objects
const objClone = Object.create(Object.getPrototypeOf(obj));
visited.set(obj, objClone);
// Copy all own properties including non-enumerable ones
[...Object.getOwnPropertyNames(obj), ...Object.getOwnPropertySymbols(obj)].forEach((key) => {
const descriptor = Object.getOwnPropertyDescriptor(obj, key);
if (descriptor.value !== undefined) {
descriptor.value = deepClone(descriptor.value, visited);
}
Object.defineProperty(objClone, key, descriptor);",claude-sonnet-4-6,claude
code_ai_038,ai,code,python,"def get_permutations(lst):
if len(lst) <= 1:
return [lst]
permutations = []
for i, element in enumerate(lst):
remaining = lst[:i] + lst[i+1:]
for perm in get_permutations(remaining):
permutations.append([element] + perm)
return permutations
if __name__ == ""__main__"":
sample_list = [1, 2, 3]
result = get_permutations(sample_list)
print(f""All permutations of {sample_list}:"")
for perm in result:
print(perm)
print(f""Total permutations: {len(result)}"")",claude-sonnet-4-6,claude
code_ai_039,ai,code,python,"import time
import logging
from contextlib import contextmanager
logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
logger = logging.getLogger(__name__)
@contextmanager
def timer(name: str = ""Code block""):
start_time = time.perf_counter()
try:
yield
finally:
end_time = time.perf_counter()
elapsed_time = end_time - start_time
logger.info(f""{name} executed in {elapsed_time:.4f} seconds"")
# Example usage
if __name__ == ""__main__"":
with timer(""Sleep example""):
time.sleep(1.5)
with timer(""List comprehension""):
result = [x ** 2 for x in range(1000000)]
with timer(""String concatenation""):
text = """"
for i in range(10000):
text += str(i)",claude-sonnet-4-6,claude
code_ai_040,ai,code,python,"import pandas as pd
import numpy as np
import csv
import os
def compute_summary_statistics(file_path: str) -> dict:
""""""
Reads a CSV file and computes summary statistics for each numeric column.
Args:
file_path: Path to the CSV file
Returns:
Dictionary with column names as keys and statistics as values
""""""
if not os.path.exists(file_path):
raise FileNotFoundError(f""File not found: {file_path}"")
df = pd.read_csv(file_path)
numeric_columns = df.select_dtypes(include=[np.number]).columns
if len(numeric_columns) == 0:
print(""No numeric columns found in the CSV file."")
return {}
summary = {}
for col in numeric_columns:
col_data = df[col].dropna()
summary[col] = {
""count"": len(col_data),
""missing_values"": df[col].isna().sum(),
""mean"": col_data.mean(),
""median"": col_data.median(),
""mode"": col_data.mode()[0] if not col_data.mode().empty else None,
""std_dev"": col_data.std(),
""variance"": col_data.var(),
""min"": col_data.min(),
""max"": col_data.max(),
""range"": col_data.max() - col_data.min(),
""25th_percentile"": col_data.quantile(0.25),
""75th_percentile"": col_data.quantile(0.75),
""iqr"": col_data.quantile(0.75) - col_data.quantile(0.25),
""skewness"": col_data.skew(),
""kurtosis"": col_data.kurt(),
""sum"": col_data.sum()
}
return summary
def print_summary_statistics(summary: dict) -> None:
""""""
Prints the summary statistics in a formatted way.
Args:
summary: Dictionary containing summary statistics per column
""""""
if not summary:
print(""No statistics to display."")
return
for col, stats in summary.items():
print(f""\n{'='*50}"")
print(f""Column: {col}"")
print(f",claude-sonnet-4-6,claude
code_ai_041,ai,code,python,"class Node:
def __init__(self, value):
self.value = value
self.left = None
self.right = None
class BinarySearchTree:
def __init__(self):
self.root = None
def insert(self, value):
if self.root is None:
self.root = Node(value)
else:
self._insert_recursive(self.root, value)
def _insert_recursive(self, node, value):
if value < node.value:
if node.left is None:
node.left = Node(value)
else:
self._insert_recursive(node.left, value)
elif value > node.value:
if node.right is None:
node.right = Node(value)
else:
self._insert_recursive(node.right, value)
def search(self, value):
return self._search_recursive(self.root, value)
def _search_recursive(self, node, value):
if node is None:
return False
if value == node.value:
return True
elif value < node.value:
return self._search_recursive(node.left, value)
else:
return self._search_recursive(node.right, value)
def delete(self, value):
self.root = self._delete_recursive(self.root, value)
def _delete_recursive(self, node, value):
if node is None:
return None
if value < node.value:
node.left = self._delete_recursive(node.left, value)
elif value > node.value:
node.right = self._delete_recursive(node.right, value)
else:
# Node with only one child or no child
if node.left is None:
return node.right
elif node.right is None:
return node.left
# Node with two children: get inorder successor (smallest in right subtree)
min_larger_node = self._get_min(node.right)
node.value = min_larger_node.value
node.right = self._delete_recursive(node.right, min_larger_node.value)
return node
def _get_min(self, node):
current = node
while current.left is not None:
current = current.left
return current
def inorder_traversal(self):
result = []",claude-sonnet-4-6,claude
code_ai_042,ai,code,python,"import requests
from bs4 import BeautifulSoup
from datetime import datetime
import json
import time
import re
def scrape_news_articles(url: str, headers: dict = None) -> list[dict]:
""""""
Scrape article titles and dates from a news website.
Args:
url: The URL of the news website to scrape
headers: Optional HTTP headers to use for the request
Returns:
List of dictionaries containing article titles and dates
""""""
if headers is None:
headers = {
""User-Agent"": ""Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 ""
""(KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36""
}
try:
response = requests.get(url, headers=headers, timeout=10)
response.raise_for_status()
except requests.RequestException as e:
print(f""Error fetching URL: {e}"")
return []
soup = BeautifulSoup(response.text, ""html.parser"")
articles = []
# Try multiple common patterns for news articles
articles = (
_extract_from_article_tags(soup) or
_extract_from_common_classes(soup) or
_extract_from_headings(soup)
)
return articles
def _extract_from_article_tags(soup: BeautifulSoup) -> list[dict]:
""""""Extract articles from <article> HTML tags.""""""
articles = []
article_tags = soup.find_all(""article"")
for article in article_tags:
title = _extract_title(article)
date = _extract_date(article)
if title:
articles.append({
""title"": title,
""date"": date or ""Date not found"",
""url"": _extract_url(article)
})
return articles
def _extract_from_common_classes(soup: BeautifulSoup) -> list[dict]:
""""""Extract articles using common CSS class patterns.""""""
articles = []
# Common class patterns used by news websites
class_patterns = [
""article"", ""post"", ""news-item"", ""story"", ""entry"",
""card"", ""list-item"", ""news-article"", ""article-item""
]",claude-sonnet-4-6,claude
code_ai_043,ai,code,javascript,"function debounce(callback, n) {
let timer;
return function (...args) {
clearTimeout(timer);
timer = setTimeout(() => {
callback.apply(this, args);
}, n);
};
}
// Example usage:
const debouncedFn = debounce((value) => {
console.log(""Debounced value:"", value);
}, 500);
debouncedFn(""first"");
debouncedFn(""second"");
debouncedFn(""third"");
// Only ""third"" will be logged after 500ms",claude-sonnet-4-6,claude
code_ai_044,ai,code,javascript,"class EventEmitter {
constructor() {
this.events = {};
}
on(event, listener) {
if (!this.events[event]) {
this.events[event] = [];
}
this.events[event].push(listener);
return this;
}
off(event, listener) {
if (!this.events[event]) {
return this;
}
this.events[event] = this.events[event].filter(l => l !== listener);
if (this.events[event].length === 0) {
delete this.events[event];
}
return this;
}
emit(event, ...args) {
if (!this.events[event]) {
return false;
}
this.events[event].forEach(listener => listener(...args));
return true;
}
}
// Example usage
const emitter = new EventEmitter();
const greet = (name) => console.log(`Hello, ${name}!`);
const farewell = (name) => console.log(`Goodbye, ${name}!`);
emitter.on('greet', greet);
emitter.on('greet', farewell);
emitter.emit('greet', 'Alice');
// Output:
// Hello, Alice!
// Goodbye, Alice!
emitter.off('greet', farewell);
emitter.emit('greet', 'Bob');
// Output:
// Hello, Bob!",claude-sonnet-4-6,claude
code_ai_045,ai,code,python,"import re
def is_valid_email(email):
pattern = r'^[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}$'
return bool(re.match(pattern, email))
# Test the function
test_emails = [
""user@example.com"",
""user.name+tag@domain.co.uk"",
""invalid-email"",
""missing@domain"",
""@nodomain.com"",
""user@.com"",
""user@domain."",
""user name@domain.com"",
""user@domain.c"",
""test.email@subdomain.domain.com""
]
for email in test_emails:
print(f""{email}: {'Valid' if is_valid_email(email) else 'Invalid'}"")",claude-sonnet-4-6,claude
code_ai_046,ai,code,python,"class LRUCache:
def __init__(self, capacity: int):
self.capacity = capacity
self.cache = {} # key -> (value, node)
# Doubly linked list with dummy head and tail
self.head = Node(0, 0) # Most recently used end
self.tail = Node(0, 0) # Least recently used end
self.head.next = self.tail
self.tail.prev = self.head
def get(self, key: int) -> int:
if key in self.cache:
node = self.cache[key]
self._remove(node)
self._insert_front(node)
return node.value
return -1
def put(self, key: int, value: int) -> None:
if key in self.cache:
self._remove(self.cache[key])
node = Node(key, value)
self.cache[key] = node
self._insert_front(node)
if len(self.cache) > self.capacity:
# Remove least recently used (node before tail)
lru_node = self.tail.prev
self._remove(lru_node)
del self.cache[lru_node.key]
def _remove(self, node):
node.prev.next = node.next
node.next.prev = node.prev
def _insert_front(self, node):
node.next = self.head.next
node.prev = self.head
self.head.next.prev = node
self.head.next = node
class Node:
def __init__(self, key: int, value: int):
self.key = key
self.value = value
self.prev = None
self.next = None
# Example usage
if __name__ == ""__main__"":
cache = LRUCache(2)
cache.put(1, 1)
print(f""Put (1, 1)"")
cache.put(2, 2)
print(f""Put (2, 2)"")
print(f""Get 1: {cache.get(1)}"") # returns 1
cache.put(3, 3) # evicts key 2
print(f""Put (3, 3) - evicts key 2"")",claude-sonnet-4-6,claude
code_ai_047,ai,code,javascript,"function deepClone(obj, visited = new WeakMap()) {
// Handle null, undefined, and primitive types
if (obj === null || obj === undefined) {
return obj;
}
if (typeof obj !== ""object"" && typeof obj !== ""function"") {
return obj;
}
// Handle circular references
if (visited.has(obj)) {
return visited.get(obj);
}
// Handle Date
if (obj instanceof Date) {
return new Date(obj.getTime());
}
// Handle RegExp
if (obj instanceof RegExp) {
return new RegExp(obj.source, obj.flags);
}
// Handle Map
if (obj instanceof Map) {
const mapClone = new Map();
visited.set(obj, mapClone);
obj.forEach((value, key) => {
mapClone.set(deepClone(key, visited), deepClone(value, visited));
});
return mapClone;
}
// Handle Set
if (obj instanceof Set) {
const setClone = new Set();
visited.set(obj, setClone);
obj.forEach((value) => {
setClone.add(deepClone(value, visited));
});
return setClone;
}
// Handle Array
if (Array.isArray(obj)) {
const arrayClone = [];
visited.set(obj, arrayClone);
obj.forEach((item, index) => {
arrayClone[index] = deepClone(item, visited);
});
return arrayClone;
}
// Handle Function
if (typeof obj === ""function"") {
return obj;
}
// Handle ArrayBuffer
if (obj instanceof ArrayBuffer) {
return obj.slice(0);
}
// Handle TypedArray (e.g., Int8Array, Uint8Array, Float32Array, etc.)
if (ArrayBuffer.isView(obj)) {
return new obj.constructor(obj.buffer.slice(0));
}
// Handle Error
if (obj instanceof Error) {
const errorClone = new obj.constructor(obj.message);
errorClone.stack = obj.stack;
return errorClone;
}
// Handle Symbol keys
const symbolKeys = Object.getOwnPropertySymbols(obj);
// Handle plain objects",claude-sonnet-4-6,claude
code_ai_048,ai,code,python,"def get_permutations(lst):
if len(lst) <= 1:
return [lst]
permutations = []
for i, element in enumerate(lst):
remaining = lst[:i] + lst[i+1:]
for perm in get_permutations(remaining):
permutations.append([element] + perm)
return permutations
if __name__ == ""__main__"":
sample_list = [1, 2, 3]
result = get_permutations(sample_list)
print(f""All permutations of {sample_list}:"")
for perm in result:
print(perm)
print(f""Total permutations: {len(result)}"")",claude-sonnet-4-6,claude
code_ai_049,ai,code,python,"import time
import logging
from contextlib import contextmanager
logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
logger = logging.getLogger(__name__)
@contextmanager
def timer(name=""Code block""):
start_time = time.perf_counter()
try:
yield
finally:
end_time = time.perf_counter()
elapsed_time = end_time - start_time
logger.info(f""{name} executed in {elapsed_time:.4f} seconds"")
if __name__ == ""__main__"":
with timer(""Sleep example""):
time.sleep(1.5)
with timer(""List comprehension""):
result = [x ** 2 for x in range(100000)]
with timer(""String concatenation""):
text = """"
for i in range(10000):
text += str(i)",claude-sonnet-4-6,claude
code_human_ext_000,human,code,python,"# wrote this in like 20 min, probably not the cleanest
def merge_sort(arr):
if len(arr) <= 1:
return arr, 0
mid = len(arr) // 2
left, lc = merge_sort(arr[:mid])
right, rc = merge_sort(arr[mid:])
merged = []
comparisons = lc + rc
i = j = 0
while i < len(left) and j < len(right):
comparisons += 1
if left[i] <= right[j]:
merged.append(left[i]); i += 1
else:
merged.append(right[j]); j += 1
merged += left[i:] + right[j:]
return merged, comparisons",human_written_extended,human
code_human_ext_001,human,code,python,"import time
from functools import wraps
def ttl_cache(seconds=60):
cache = {}
def decorator(fn):
@wraps(fn)
def wrapper(*args):
now = time.time()
if args in cache:
result, ts = cache[args]
if now - ts < seconds:
return result
result = fn(*args)
cache[args] = (result, now)
return result
wrapper.cache = cache # expose for testing
return wrapper
return decorator
# usage: @ttl_cache(seconds=300)",human_written_extended,human
code_human_ext_002,human,code,javascript,"// exponential backoff retry - learned this pattern from a blog post
// doubles wait time each attempt, adds jitter to avoid thundering herd
async function retry(fn, maxAttempts = 3, baseDelay = 1000) {
let lastErr;
for (let attempt = 0; attempt < maxAttempts; attempt++) {
try {
return await fn();
} catch (err) {
lastErr = err;
if (attempt === maxAttempts - 1) break;
const delay = baseDelay * Math.pow(2, attempt) + Math.random() * 100;
await new Promise(r => setTimeout(r, delay));
}
}
throw lastErr;
}",human_written_extended,human
code_human_ext_003,human,code,python,"# simple rate limiter using a sliding window
import time
from collections import deque
class RateLimiter:
def __init__(self, max_calls, period):
self.max_calls = max_calls
self.period = period
self.calls = deque()
def allow(self):
now = time.time()
# drop old calls outside window
while self.calls and now - self.calls[0] > self.period:
self.calls.popleft()
if len(self.calls) < self.max_calls:
self.calls.append(now)
return True
return False",human_written_extended,human
code_human_ext_004,human,code,javascript,"function flatten(arr, depth = Infinity) {
// could use arr.flat(depth) but writing it out for clarity
if (depth === 0) return arr.slice();
return arr.reduce((acc, val) => {
if (Array.isArray(val)) {
acc.push(...flatten(val, depth - 1));
} else {
acc.push(val);
}
return acc;
}, []);
}
// flatten([1,[2,[3,[4]]]], 1) => [1,2,[3,[4]]]
// flatten([1,[2,[3,[4]]]]) => [1,2,3,4]",human_written_extended,human
code_ai_ext_000,ai,code,python,"def merge_sort(arr):
comparisons = [0]
def merge(left, right):
result = []
i = j = 0
while i < len(left) and j < len(right):
comparisons[0] += 1
if left[i] <= right[j]:
result.append(left[i])
i += 1
else:
result.append(right[j])
j += 1
result.extend(left[i:])
result.extend(right[j:])
return result
def sort(arr):
if len(arr) <= 1:
return arr
mid = len(arr) // 2
left = sort(arr[:mid])
right = sort(arr[mid:])
return merge(left, right)
sorted_arr = sort(arr)
return sorted_arr, comparisons[0]
if __name__ == ""__main__"":
test_cases = [
[64, 34, 25, 12, 22, 11, 90],
[1, 2, 3, 4, 5],
[5, 4, 3, 2, 1],
[1],
[],
[3, 3, 3, 1, 1],
]
for test in test_cases:
sorted_list, num_comparisons = merge_sort(test)
print(f""Original: {test}"")
print(f""Sorted: {sorted_list}"")
print(f""Number of comparisons: {num_comparisons}"")
print(""-"" * 40)",claude-sonnet-4-6,claude
code_ai_ext_001,ai,code,python,"from collections import defaultdict, deque
import heapq
from typing import Optional
class DirectedGraph:
def __init__(self):
self.graph = defaultdict(list)
self.vertices = set()
self.weights = {}
def add_vertex(self, vertex):
""""""Add a vertex to the graph.""""""
self.vertices.add(vertex)
if vertex not in self.graph:
self.graph[vertex] = []
def add_edge(self, source, destination, weight=1):
""""""Add a directed edge from source to destination with optional weight.""""""
self.vertices.add(source)
self.vertices.add(destination)
if destination not in self.graph[source]:
self.graph[source].append(destination)
if destination not in self.graph:
self.graph[destination] = []
self.weights[(source, destination)] = weight
def remove_edge(self, source, destination):
""""""Remove a directed edge from source to destination.""""""
if source in self.graph and destination in self.graph[source]:
self.graph[source].remove(destination)
self.weights.pop((source, destination), None)
def remove_vertex(self, vertex):
""""""Remove a vertex and all its associated edges.""""""
if vertex in self.graph:
del self.graph[vertex]
for v in self.graph:
if vertex in self.graph[v]:
self.graph[v].remove(vertex)
self.vertices.discard(vertex)
keys_to_remove = [key for key in self.weights if vertex in key]
for key in keys_to_remove:
del self.weights[key]
def has_cycle(self):
""""""
Detect if the directed graph contains a cycle using DFS.
Returns True if a cycle exists, False otherwise.
""""""
WHITE, GRAY, BLACK = 0, 1, 2
color = {v: WHITE for v in self.vertices}
def dfs(vertex):
color[vertex] = GRAY
for neighbor in self.graph[vertex]:
if color[neighbor] == GRAY:
return True
if color[neighbor] == WHITE and dfs(neighbor):
return True
color[vertex] = BLACK
return False
for vertex in self.vertices:
if color[vertex] == WHITE:
if dfs(vertex):
return True
return False
def find_cycle(self):
""""""
Find and return a cycle in the graph if one exists.
Returns the cycle as a list of vertices, or None if no cycle exists.
""""""
WHITE, GRAY, BLACK = 0, 1, 2
color",claude-sonnet-4-6,claude
code_ai_ext_002,ai,code,python,"import time
import functools
from typing import Any, Callable, Optional
from collections import OrderedDict
def ttl_cache(ttl: float = 60.0, maxsize: Optional[int] = None):
""""""
A decorator that caches function results with a configurable TTL expiration.
Args:
ttl: Time-to-live in seconds for cached results (default: 60 seconds)
maxsize: Maximum number of entries in cache (default: None = unlimited)
""""""
def decorator(func: Callable) -> Callable:
cache: OrderedDict = OrderedDict()
cache_times: dict = {}
@functools.wraps(func)
def wrapper(*args, **kwargs) -> Any:
# Create a hashable cache key from arguments
key = _make_cache_key(args, kwargs)
current_time = time.time()
# Check if result is in cache and not expired
if key in cache:
if current_time - cache_times[key] < ttl:
# Move to end to maintain LRU order
cache.move_to_end(key)
return cache[key]
else:
# Entry has expired, remove it
del cache[key]
del cache_times[key]
# Call the function and cache the result
result = func(*args, **kwargs)
# If maxsize is set and cache is full, remove oldest entry
if maxsize is not None and len(cache) >= maxsize:
oldest_key = next(iter(cache))
del cache[oldest_key]
del cache_times[oldest_key]
cache[key] = result
cache_times[key] = current_time
return result
def _make_cache_key(args, kwargs):
""""""Create a hashable key from function arguments.""""""
try:
key_parts = [args]
if kwargs:
key_parts.append(tuple(sorted(kwargs.items())))
return hash(tuple(key_parts))
except TypeError:
# Fallback for unhashable types
return hash(str(args) + str(sorted(kwargs.items()) if kwargs else """"))
def cache_info() -> dict:
""""""Return information about the cache.""""""
current_time = time.time()
valid_entries = sum(
1 for key in cache
if current_time - cache_times[key] < ttl
)
return {
""total_entries"": len(cache),
""valid_entries"": valid_entries,
""expired_entries"": len(cache) - valid_entries,
""maxsize"": maxsize,
""ttl"": ttl
}
def cache_clear() -> None:",claude-sonnet-4-6,claude
code_ai_ext_003,ai,code,python,"import re
from dataclasses import dataclass
from enum import Enum
from typing import List
class TokenType(Enum):
SENTENCE = ""SENTENCE""
WORD = ""WORD""
PUNCTUATION = ""PUNCTUATION""
WHITESPACE = ""WHITESPACE""
NUMBER = ""NUMBER""
@dataclass
class Token:
type: TokenType
value: str
position: int
def __repr__(self):
return f""Token(type={self.type.value}, value={self.value!r}, position={self.position})""
class Tokenizer:
def __init__(self):
self.sentence_endings = re.compile(r'(?<=[.!?])\s+(?=[A-Z])|(?<=[.!?])\s*$')
self.word_pattern = re.compile(r""[a-zA-Z]+(?:'[a-zA-Z]+)*"")
self.number_pattern = re.compile(r'\d+(?:\.\d+)?')
self.punctuation_pattern = re.compile(r'[^\w\s]')
self.whitespace_pattern = re.compile(r'\s+')
def tokenize_into_sentences(self, text: str) -> List[str]:
""""""Split text into sentences.""""""
sentence_pattern = re.compile(r'(?<=[.!?])\s+')
sentences = sentence_pattern.split(text.strip())
return [s.strip() for s in sentences if s.strip()]
def tokenize_into_words(self, text: str) -> List[Token]:
""""""Split text into word tokens.""""""
tokens = []
for match in self.word_pattern.finditer(text):
tokens.append(Token(
type=TokenType.WORD,
value=match.group(),
position=match.start()
))
return tokens
def tokenize(self, text: str) -> dict:
""""""
Full tokenization returning sentences, words, and punctuation tokens.
""""""
result = {
'sentences': [],
'tokens': []
}
sentences = self.tokenize_into_sentences(text)
result['sentences'] = sentences
position = 0
i = 0
while i < len(text):
char = text[i]
word_match = self.word_pattern.match(text, i)
if word_match:
result['tokens'].append(Token(
type=TokenType.WORD,
value=word_match.group(),
position=i
))
i = word_match.end()
continue
number_match = self.number_pattern.match(text, i)
if number_match:
result['tokens'].append(Token(
type=TokenType.NUMBER,",claude-sonnet-4-6,claude
code_ai_ext_004,ai,code,javascript,"function retry(asyncOperation, maxAttempts = 3, baseDelay = 1000) {
return new Promise((resolve, reject) => {
const attempt = (attemptNumber) => {
asyncOperation()
.then(resolve)
.catch((error) => {
if (attemptNumber >= maxAttempts) {
reject(
new Error(
`Operation failed after ${maxAttempts} attempts. Last error: ${error.message}`
)
);
return;
}
const delay = baseDelay * Math.pow(2, attemptNumber - 1);
console.log(
`Attempt ${attemptNumber} failed. Retrying in ${delay}ms...`
);
setTimeout(() => {
attempt(attemptNumber + 1);
}, delay);
});
};
attempt(1);
});
}
// ==================== USAGE EXAMPLES ====================
// Example 1: Simulating a flaky API call
function createFlakyOperation(failTimes = 2) {
let callCount = 0;
return function flakyOperation() {
callCount++;
return new Promise((resolve, reject) => {
if (callCount <= failTimes) {
reject(new Error(`Simulated failure on attempt ${callCount}`));
} else {
resolve(`Success on attempt ${callCount}`);
}
});
};
}
// Example 2: With jitter (randomized delay to prevent thundering herd)
function retryWithJitter(
asyncOperation,
maxAttempts = 3,
baseDelay = 1000,
jitterFactor = 0.1
) {
return new Promise((resolve, reject) => {
const attempt = (attemptNumber) => {
asyncOperation()
.then(resolve)
.catch((error) => {
if (attemptNumber >= maxAttempts) {
reject(
new Error(
`Operation failed after ${maxAttempts} attempts. Last error: ${error.message}`
)
);
return;
}
const exponentialDelay = baseDelay * Math.pow(2, attemptNumber - 1);
const jitter = exponentialDelay * jitterFactor * Math.random();
const delay = exponentialDelay + jitter;
console.log(
`Attempt ${attemptNumber} failed. Retrying in ${Math.round(delay)}ms (with jitter)...`
);
setTimeout(() => {
attempt(attemptNumber + 1);
}, delay);
});
};
attempt(1);
});
}
// Example 3: With abort signal support
function retryWithAbort(
asyncOperation,
maxAttempts = 3,
baseDe",claude-sonnet-4-6,claude
code_ai_ext_005,ai,code,javascript,"class Observable {
constructor() {
this.subscribers = {};
}
subscribe(event, callback) {
if (!this.subscribers[event]) {
this.subscribers[event] = [];
}
this.subscribers[event].push(callback);
// Return unsubscribe function
return {
unsubscribe: () => {
this.subscribers[event] = this.subscribers[event].filter(
(cb) => cb !== callback
);
},
};
}
publish(event, data) {
if (!this.subscribers[event]) {
return;
}
this.subscribers[event].forEach((callback) => {
callback(data);
});
}
unsubscribeAll(event) {
if (event) {
delete this.subscribers[event];
} else {
this.subscribers = {};
}
}
}
// Example usage
const observable = new Observable();
// Subscribe to events
const subscription1 = observable.subscribe(""userLoggedIn"", (data) => {
console.log(`Subscriber 1: User logged in - ${data.username}`);
});
const subscription2 = observable.subscribe(""userLoggedIn"", (data) => {
console.log(`Subscriber 2: Welcome, ${data.username}!`);
});
const subscription3 = observable.subscribe(""dataUpdated"", (data) => {
console.log(`Data updated: ${JSON.stringify(data)}`);
});
// Publish events
console.log(""--- Publishing userLoggedIn event ---"");
observable.publish(""userLoggedIn"", { username: ""JohnDoe"" });
console.log(""\n--- Publishing dataUpdated event ---"");
observable.publish(""dataUpdated"", { id: 1, value: ""new value"" });
// Unsubscribe subscriber 1
console.log(""\n--- Unsubscribing subscriber 1 ---"");
subscription1.unsubscribe();
console.log(""\n--- Publishing userLoggedIn event after unsubscribe ---"");
observable.publish(""userLoggedIn"", { username: ""JaneDoe"" });
// Unsubscribe all from userLoggedIn
console.log(""\n--- Unsubscribing all from userLoggedIn ---"");
observable.unsubscribeAll(""userLoggedIn"");
console.log(""\n--- Publishing userLoggedIn event after unsubscribeAll ---"");
observable.publish(""userLoggedIn"", { username: ""TestUser"" });
console.log(""\n--- Publishing dataUpdated event (should still work) ---"");
observable.publish(""dataUpdated"", { id: 2, value: ""another value"" });",claude-sonnet-4-6,claude
code_ai_ext_006,ai,code,python,"def parse_and_evaluate(expression: str) -> float:
""""""
Parses and evaluates a simple arithmetic expression string
without using eval().
Supports: +, -, *, /, parentheses, and floating point numbers.
""""""
tokens = tokenize(expression)
pos = 0
def peek():
nonlocal pos
if pos < len(tokens):
return tokens[pos]
return None
def consume():
nonlocal pos
token = tokens[pos]
pos += 1
return token
def parse_expression():
""""""Handle + and - (lowest precedence)""""""
left = parse_term()
while peek() in ('+', '-'):
op = consume()
right = parse_term()
if op == '+':
left += right
else:
left -= right
return left
def parse_term():
""""""Handle * and / (higher precedence)""""""
left = parse_factor()
while peek() in ('*', '/'):
op = consume()
right = parse_factor()
if op == '*':
left *= right
else:
if right == 0:
raise ZeroDivisionError(""Division by zero"")
left /= right
return left
def parse_factor():
""""""Handle numbers, parentheses, and unary operators""""""
token = peek()
if token is None:
raise ValueError(""Unexpected end of expression"")
# Handle unary minus and plus
if token == '-':
consume()
return -parse_factor()
if token == '+':
consume()
return parse_factor()
# Handle parentheses
if token == '(':
consume() # consume '('
result = parse_expression()
if peek() != ')':
raise ValueError(""Missing closing parenthesis"")
consume() # consume ')'
return result
# Handle numbers
try:
consume()
return float(token)
except ValueError:
raise ValueError(f""Unexpected token: {token}"")
result = parse_expression()
if pos < len(tokens):
raise ValueError(f""Unexpected token: {tokens[pos]}"")
return result
def tokenize(expression: str) -> list:
""""""
Converts expression string into list of tokens (numbers and operators).
""""""
tokens = []
i = 0
expression = expression.replace(' ', '') # Remove spaces
while i < len(expression):
char = expression[i]
# Handle numbers (including decimals)
if char.isdigit() or (char == '.' and i + 1 < len(expression)",claude-sonnet-4-6,claude
code_ai_ext_007,ai,code,python,"import threading
from typing import Any, Optional
class ThreadSafeQueue:
def __init__(self, maxsize: int = 0):
self._queue = []
self._maxsize = maxsize
self._mutex = threading.Lock()
self._not_empty = threading.Condition(self._mutex)
self._not_full = threading.Condition(self._mutex)
self._size = 0
def put(self, item: Any, block: bool = True, timeout: Optional[float] = None) -> None:
with self._not_full:
if self._maxsize > 0:
if not block:
if self._size >= self._maxsize:
raise QueueFull(""Queue is full"")
elif timeout is None:
while self._size >= self._maxsize:
self._not_full.wait()
elif timeout < 0:
raise ValueError(""'timeout' must be a non-negative number"")
else:
end_time = threading.Event()
remaining = timeout
while self._size >= self._maxsize:
if not self._not_full.wait(remaining):
raise QueueFull(""Queue is full"")
remaining = timeout - remaining
self._queue.append(item)
self._size += 1
self._not_empty.notify()
def get(self, block: bool = True, timeout: Optional[float] = None) -> Any:
with self._not_empty:
if not block:
if self._size == 0:
raise QueueEmpty(""Queue is empty"")
elif timeout is None:
while self._size == 0:
self._not_empty.wait()
elif timeout < 0:
raise ValueError(""'timeout' must be a non-negative number"")
else:
import time
end_time = time.monotonic() + timeout
while self._size == 0:
remaining = end_time - time.monotonic()
if remaining <= 0:
raise QueueEmpty(""Queue is empty"")
self._not_empty.wait(remaining)
item = self._queue.pop(0)
self._size -= 1
self._not_full.notify()
return item
def put_nowait(self, item: Any) -> None:
self.put(item, block=False)
def get_nowait(self) -> Any:
return self.get(block=False)
def empty(self) -> bool:
with self._mutex:
return self._size == 0
def full(self) -> bool:
with self._mutex:
if self._maxsize <= 0:
return False
return self._size >= self._maxsize
def qsize(self) -> int:",claude-sonnet-4-6,claude
code_ai_ext_008,ai,code,javascript,"function flattenArray(arr, depth = Infinity) {
if (depth === 0) {
return arr.slice();
}
return arr.reduce((result, item) => {
if (Array.isArray(item) && depth > 0) {
result.push(...flattenArray(item, depth - 1));
} else {
result.push(item);
}
return result;
}, []);
}
// Test examples
const nestedArray = [1, [2, [3, [4, [5]]]]];
console.log(""Original array:"", JSON.stringify(nestedArray));
console.log(""Flatten depth 1:"", JSON.stringify(flattenArray(nestedArray, 1)));
console.log(""Flatten depth 2:"", JSON.stringify(flattenArray(nestedArray, 2)));
console.log(""Flatten depth 3:"", JSON.stringify(flattenArray(nestedArray, 3)));
console.log(""Flatten fully (Infinity):"", JSON.stringify(flattenArray(nestedArray)));
const complexArray = [1, [2, 3], [4, [5, 6]], [7, [8, [9, [10]]]]];
console.log(""\nComplex array:"", JSON.stringify(complexArray));
console.log(""Flatten depth 1:"", JSON.stringify(flattenArray(complexArray, 1)));
console.log(""Flatten depth 2:"", JSON.stringify(flattenArray(complexArray, 2)));
console.log(""Flatten fully:"", JSON.stringify(flattenArray(complexArray)));
// Alternative using built-in Array.flat() for comparison
console.log(""\nUsing built-in Array.flat():"");
console.log(""Flatten depth 1:"", JSON.stringify(nestedArray.flat(1)));
console.log(""Flatten fully:"", JSON.stringify(nestedArray.flat(Infinity)));",claude-sonnet-4-6,claude
code_ai_ext_009,ai,code,python,"import time
from collections import deque
from threading import Lock
class RateLimiter:
""""""A simple rate limiter that allows n calls per time window.""""""
def __init__(self, max_calls: int, time_window: float):
""""""
Initialize the rate limiter.
Args:
max_calls: Maximum number of calls allowed per time window
time_window: Time window in seconds
""""""
self.max_calls = max_calls
self.time_window = time_window
self.calls = deque()
self.lock = Lock()
def is_allowed(self) -> bool:
""""""
Check if a call is allowed based on the rate limit.
Returns:
True if the call is allowed, False otherwise
""""""
with self.lock:
now = time.time()
# Remove calls outside the time window
while self.calls and self.calls[0] <= now - self.time_window:
self.calls.popleft()
# Check if we're within the rate limit
if len(self.calls) < self.max_calls:
self.calls.append(now)
return True
return False
def wait_and_call(self) -> float:
""""""
Wait until a call is allowed and record it.
Returns:
The time waited in seconds
""""""
start_time = time.time()
while not self.is_allowed():
with self.lock:
if self.calls:
# Calculate how long to wait
wait_time = self.calls[0] + self.time_window - time.time()
if wait_time > 0:
time.sleep(wait_time)
else:
time.sleep(0.001)
return time.time() - start_time
def remaining_calls(self) -> int:
""""""
Get the number of remaining calls allowed in the current window.
Returns:
Number of remaining calls
""""""
with self.lock:
now = time.time()
# Remove calls outside the time window
while self.calls and self.calls[0] <= now - self.time_window:
self.calls.popleft()
return self.max_calls - len(self.calls)
def reset(self):
""""""Reset the rate limiter by clearing all recorded calls.""""""
with self.lock:
self.calls.clear()
def __repr__(self) -> str:
return f""RateLimiter(max_calls={self.max_calls}, time_window={self.time_window}s)""
def rate_limited(max_calls: int, time_window: float):
""""""
Decorator that",claude-sonnet-4-6,claude
code_human_v2_000,human,code,python,"# min heap - wrote this for an interview prep session
# probably not the cleanest but it works
class MinHeap:
def __init__(self):
self.h = []
def insert(self, val):
self.h.append(val)
i = len(self.h) - 1
# bubble up
while i > 0:
parent = (i - 1) // 2
if self.h[parent] > self.h[i]:
self.h[parent], self.h[i] = self.h[i], self.h[parent]
i = parent
else:
break
def extract_min(self):
if not self.h: return None
if len(self.h) == 1: return self.h.pop()
min_val = self.h[0]
self.h[0] = self.h.pop()
self._sink(0)
return min_val
def _sink(self, i):
n = len(self.h)
while True:
smallest = i
l, r = 2*i+1, 2*i+2
if l < n and self.h[l] < self.h[smallest]: smallest = l
if r < n and self.h[r] < self.h[smallest]: smallest = r
if smallest == i: break
self.h[i], self.h[smallest] = self.h[smallest], self.h[i]
i = smallest",human_written_v2,human
code_human_v2_001,human,code,python,"from collections import defaultdict
import heapq
# dijkstra - took me a while to get the visited set right
def shortest_path(graph, start, end):
dist = {start: 0}
pq = [(0, start)]
prev = {}
visited = set()
while pq:
d, node = heapq.heappop(pq)
if node in visited:
continue
visited.add(node)
if node == end:
# reconstruct path
path = []
cur = end
while cur in prev:
path.append(cur)
cur = prev[cur]
path.append(start)
return d, path[::-1]
for neighbor, weight in graph[node]:
new_dist = d + weight
if neighbor not in dist or new_dist < dist[neighbor]:
dist[neighbor] = new_dist
prev[neighbor] = node
heapq.heappush(pq, (new_dist, neighbor))
return float('inf'), [] # no path found",human_written_v2,human
code_human_v2_002,human,code,javascript,"// LRU cache using Map (Maps preserve insertion order in JS)
// O(1) get and put - the trick is moving accessed keys to end
class LRUCache {
constructor(capacity) {
this.cap = capacity
this.cache = new Map()
}
get(key) {
if (!this.cache.has(key)) return -1
// move to end (most recently used)
const val = this.cache.get(key)
this.cache.delete(key)
this.cache.set(key, val)
return val
}
put(key, val) {
if (this.cache.has(key)) this.cache.delete(key)
else if (this.cache.size >= this.cap) {
// delete least recently used (first item)
this.cache.delete(this.cache.keys().next().value)
}
this.cache.set(key, val)
}
}",human_written_v2,human
code_human_v2_003,human,code,python,"# bloom filter - built this for a distributed dedup project
# false positive rate is approximate, real impl would tune m and k more carefully
import math, hashlib
class BloomFilter:
def __init__(self, capacity, fp_rate=0.01):
self.capacity = capacity
self.fp_rate = fp_rate
# standard formula for optimal m and k
m = -capacity * math.log(fp_rate) / (math.log(2) ** 2)
self.m = int(m)
self.k = int((self.m / capacity) * math.log(2))
self.bits = bytearray(self.m)
def _hashes(self, item):
# use two hash functions to simulate k
h1 = int(hashlib.md5(item.encode()).hexdigest(), 16)
h2 = int(hashlib.sha1(item.encode()).hexdigest(), 16)
return [(h1 + i * h2) % self.m for i in range(self.k)]
def add(self, item):
for pos in self._hashes(item):
self.bits[pos] = 1
def __contains__(self, item):
return all(self.bits[pos] for pos in self._hashes(item))",human_written_v2,human
code_human_v2_004,human,code,javascript,"// deep merge - handles the annoying array edge cases
// arrays are replaced not merged (change concat to ... if you want merge behavior)
function deepMerge(target, source) {
const result = { ...target }
for (const key of Object.keys(source)) {
if (source[key] && typeof source[key] === 'object' && !Array.isArray(source[key])) {
if (target[key] && typeof target[key] === 'object' && !Array.isArray(target[key])) {
result[key] = deepMerge(target[key], source[key])
} else {
result[key] = deepMerge({}, source[key])
}
} else {
result[key] = source[key]
}
}
return result
}
// test: deepMerge({a:{b:1},c:3}, {a:{d:2},e:4}) => {a:{b:1,d:2},c:3,e:4}",human_written_v2,human
code_human_v2_005,human,code,python,"# run length encoding - simple but surprisingly useful for compression
def rle_encode(s):
if not s:
return ''
result = []
count = 1
for i in range(1, len(s)):
if s[i] == s[i-1]:
count += 1
else:
result.append(f'{count}{s[i-1]}' if count > 1 else s[i-1])
count = 1
result.append(f'{count}{s[-1]}' if count > 1 else s[-1])
return ''.join(result)
def rle_decode(s):
result = []
i = 0
while i < len(s):
if s[i].isdigit():
j = i
while j < len(s) and s[j].isdigit():
j += 1
result.append(s[j] * int(s[i:j]))
i = j + 1
else:
result.append(s[i])
i += 1
return ''.join(result)",human_written_v2,human
code_human_v2_006,human,code,javascript,"// simple event emitter - written from scratch, not using Node's EventEmitter
// supports multiple handlers per event, returns unsubscribe function
class EventEmitter {
#handlers = new Map() // private field
on(event, handler) {
if (!this.#handlers.has(event)) {
this.#handlers.set(event, new Set())
}
this.#handlers.get(event).add(handler)
// return cleanup fn
return () => this.off(event, handler)
}
off(event, handler) {
this.#handlers.get(event)?.delete(handler)
}
emit(event, ...args) {
this.#handlers.get(event)?.forEach(h => h(...args))
}
once(event, handler) {
const wrapper = (...args) => {
handler(...args)
this.off(event, wrapper)
}
return this.on(event, wrapper)
}
}",human_written_v2,human
code_human_v2_007,human,code,python,"# topological sort - Kahn's algorithm
# used this in a build system dependency resolver
from collections import deque, defaultdict
def topo_sort(nodes, edges):
""""""
nodes: list of node ids
edges: list of (from, to) tuples meaning 'from' must come before 'to'
returns sorted list or raises ValueError on cycle
""""""
in_degree = defaultdict(int)
adj = defaultdict(list)
for u, v in edges:
adj[u].append(v)
in_degree[v] += 1
for n in nodes:
in_degree.setdefault(n, 0)
queue = deque(n for n in nodes if in_degree[n] == 0)
result = []
while queue:
node = queue.popleft()
result.append(node)
for neighbor in adj[node]:
in_degree[neighbor] -= 1
if in_degree[neighbor] == 0:
queue.append(neighbor)
if len(result) != len(nodes):
raise ValueError(""Graph has a cycle"")
return result",human_written_v2,human
code_human_v2_008,human,code,python,"# flatten nested dict - useful for logging and config diffing
def flatten_dict(d, prefix='', sep='.'):
items = {}
for k, v in d.items():
new_key = f""{prefix}{sep}{k}"" if prefix else k
if isinstance(v, dict) and v:
items.update(flatten_dict(v, new_key, sep))
else:
items[new_key] = v
return items
def unflatten_dict(d, sep='.'):
result = {}
for key, val in d.items():
parts = key.split(sep)
cur = result
for part in parts[:-1]:
cur = cur.setdefault(part, {})
cur[parts[-1]] = val
return result",human_written_v2,human
code_human_v2_009,human,code,javascript,"// priority queue backed by binary heap
// used min-heap by default (smaller priority = higher priority)
class PriorityQueue {
#heap = []
#compare
constructor(compare = (a, b) => a - b) {
this.#compare = compare
}
get size() { return this.#heap.length }
peek() { return this.#heap[0] }
push(val) {
this.#heap.push(val)
this.#bubbleUp(this.#heap.length - 1)
}
pop() {
const top = this.#heap[0]
const last = this.#heap.pop()
if (this.#heap.length > 0) {
this.#heap[0] = last
this.#sinkDown(0)
}
return top
}
#bubbleUp(i) {
while (i > 0) {
const parent = (i - 1) >> 1
if (this.#compare(this.#heap[i], this.#heap[parent]) < 0) {
;[this.#heap[i], this.#heap[parent]] = [this.#heap[parent], this.#heap[i]]
i = parent
} else break
}
}
#sinkDown(i) {
const n = this.#heap.length
while (true) {
let smallest = i
const l = 2*i+1, r = 2*i+2
if (l < n && this.#compare(this.#heap[l], this.#heap[smallest]) < 0) smallest = l
if (r < n && this.#compare(this.#heap[r], this.#heap[smallest]) < 0) smallest = r
if (smallest === i) break
;[this.#heap[i], this.#heap[smallest]] = [this.#heap[smallest], this.#heap[i]]
i = smallest
}
}
}",human_written_v2,human