import nltk
from collections import defaultdict
nltk.download('words')
from nltk.corpus import words
# Get the English words
english_words = words.words()
# Filter the words to get only five-letter words
five_letter_words = [word for word in english_words if len(word) == 5]
# Create a dictionary to store the count of words with the same first three letters
words_dict = defaultdict(int)
# Count the words with the same first three letters
for word in five_letter_words:
key = word[:3]
words_dict[key] += 1
# Calculate the number of pairs with the same first three letters
same_first_three_letter_pairs = sum((count * (count - 1)) // 2 for count in words_dict.values())
# Calculate the total number of pairs from the five-letter words list
total_pairs = (len(five_letter_words) * (len(five_letter_words) - 1)) // 2
# Calculate the probability
probability = same_first_three_letter_pairs / total_pairs
print(f"Probability: {probability:.4f} or {probability * 100:.2f}%")
- https://pypistats.org/packages/poetry - https://pypistats.org/packages/uv
In the 2024 Python developer survey, 18% of the ecosystem used Poetry. When I opened this manifold question[0], I'm pretty sure uv was about half of Poetry downloads.
Estimating from these numbers, probably about 30% of the ecosystem is using `uv` now. We'll get better numbers when the 2025 Python developer survey is published.
Also see this: https://biggo.com/news/202510140723_uv-overtakes-pip-in-ci-u...
[0]: https://manifold.markets/JeremiahEngland/will-uv-surpass-poe...