oxedyne/fe2o3 — fe2o3_text/tests/detect_corpus/python/comprehensions.txt

1.5 KiB, 1 run

created by r1870400018:12026, which is this file's identity for as long as the history lasts, whatever it is later renamed to

1	from collections import Counter
2	from typing import Dict, List, Set
3
4
5	def word_lengths(words: List[str]) -> Dict[str, int]:
6	return {w: len(w) for w in words}
7
8
9	def unique_chars(text: str) -> Set[str]:
10	return {c.lower() for c in text if c.isalpha()}
11
12
13	def flatten(nested: List[List]) -> List:
14	return [item for sublist in nested for item in sublist]
15
16
17	def matrix_transpose(matrix: List[List[float]]) -> List[List[float]]:
18	if not matrix:
19	return []
20	return [[row[i] for row in matrix] for i in range(len(matrix[0]))]
21
22
23	def group_by_length(words: List[str]) -> Dict[int, List[str]]:
24	result: Dict[int, List[str]] = {}
25	for word in words:
26	length = len(word)
27	if length not in result:
28	result[length] = []
29	result[length].append(word)
30	return result
31
32
33	def top_n_words(text: str, n: int = 10) -> List[tuple]:
34	words = text.lower().split()
35	cleaned = [''.join(c for c in w if c.isalnum()) for w in words]
36	counts = Counter(w for w in cleaned if w)
37	return counts.most_common(n)
38
39
40	def chunk(lst: List, size: int) -> List[List]:
41	return [lst[i:i + size] for i in range(0, len(lst), size)]
42
43
44	if __name__ == '__main__':
45	text = "the quick brown fox jumps over the lazy dog the fox"
46	print(f"unique chars: {sorted(unique_chars(text))}")
47	print(f"top words: {top_n_words(text, 3)}")
48
49	matrix = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]
50	print(f"transpose: {matrix_transpose(matrix)}")
51	print(f"chunks: {chunk(list(range(10)), 3)}")