Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

⚡️ Speed up function find_common_tags by 18,960% #227

Open
wants to merge 1 commit into
base: main
Choose a base branch
from

Conversation

codeflash-ai-dev[bot]
Copy link

📄 18,960% (189.60x) speedup for find_common_tags in common_tags.py

⏱️ Runtime : 2.31 seconds 12.1 milliseconds (best of 414 runs)

📝 Explanation and details

Certainly! The program can be optimized by utilizing sets for intersection operations, which are generally faster than list comprehensions for this kind of task. Here’s the optimized version.

Changes Made.

  1. Utilized Set for Intersection: Instead of a list comprehension inside the loop, using set operations (intersection_update) significantly optimizes the performance for finding common elements.
  2. Retained the Original Functionality: The function signature and return value remain unchanged.

This will run faster, especially when dealing with a large number of articles or tags, as set operations are generally more efficient for membership tests and intersections.

Correctness verification report:

Test Status
⚙️ Existing Unit Tests 🔘 None Found
🌀 Generated Regression Tests 54 Passed
⏪ Replay Tests 🔘 None Found
🔎 Concolic Coverage Tests 6 Passed
📊 Tests Coverage 100.0%
🌀 Generated Regression Tests Details
from __future__ import annotations

# imports
import pytest  # used for our unit tests
from common_tags import find_common_tags

# unit tests

# Test single article with tags
def test_single_article_with_tags():
    articles = [{"tags": ["python", "coding", "development"]}]
    codeflash_output = find_common_tags(articles)

# Test multiple articles with common tags
def test_multiple_articles_with_common_tags():
    articles = [{"tags": ["python", "coding"]}, {"tags": ["python", "development"]}, {"tags": ["python", "scripting"]}]
    codeflash_output = find_common_tags(articles)

# Test multiple articles with no common tags
def test_multiple_articles_with_no_common_tags():
    articles = [{"tags": ["python", "coding"]}, {"tags": ["java", "development"]}, {"tags": ["javascript", "scripting"]}]
    codeflash_output = find_common_tags(articles)

# Test empty list of articles
def test_empty_list_of_articles():
    articles = []
    codeflash_output = find_common_tags(articles)

# Test articles with empty tags
def test_articles_with_empty_tags():
    articles = [{"tags": []}, {"tags": []}]
    codeflash_output = find_common_tags(articles)

# Test articles with one empty tag list
def test_articles_with_one_empty_tag_list():
    articles = [{"tags": ["python", "coding"]}, {"tags": []}]
    codeflash_output = find_common_tags(articles)

# Test missing "tags" key in an article
def test_missing_tags_key_in_an_article():
    articles = [{"tags": ["python", "coding"]}, {"name": "Article without tags"}]
    with pytest.raises(KeyError):
        find_common_tags(articles)

# Test non-list "tags" value

def test_single_article_with_duplicate_tags():
    articles = [{"tags": ["python", "python", "coding"]}]
    codeflash_output = find_common_tags(articles)

# Test multiple articles with duplicate tags
def test_multiple_articles_with_duplicate_tags():
    articles = [{"tags": ["python", "python", "coding"]}, {"tags": ["python", "coding", "coding"]}]
    codeflash_output = find_common_tags(articles)

# Test large number of articles
def test_large_number_of_articles():
    articles = [{"tags": [f"tag{i}" for i in range(1000)]}] * 1000
    codeflash_output = find_common_tags(articles)

# Test large number of tags in each article
def test_large_number_of_tags_in_each_article():
    articles = [{"tags": [f"tag{i}" for i in range(1000)]}, {"tags": [f"tag{i}" for i in range(500, 1500)]}]
    codeflash_output = find_common_tags(articles)

# Test tags with different cases
def test_tags_with_different_cases():
    articles = [{"tags": ["Python", "coding"]}, {"tags": ["python", "Coding"]}]
    codeflash_output = find_common_tags(articles)

# Test tags with non-string elements
def test_tags_with_non_string_elements():
    articles = [{"tags": ["python", 123, None]}, {"tags": ["python", 123, "coding"]}]
    codeflash_output = find_common_tags(articles)
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.

from __future__ import annotations

# imports
import pytest  # used for our unit tests
from common_tags import find_common_tags

# unit tests

def test_single_article():
    # Single article should return its tags
    articles = [{"tags": ["python", "coding", "tutorial"]}]
    codeflash_output = find_common_tags(articles)

def test_multiple_articles_with_common_tags():
    # Multiple articles with common tags should return the common tags
    articles = [{"tags": ["python", "coding"]}, {"tags": ["python", "coding", "tutorial"]}]
    codeflash_output = find_common_tags(articles)

def test_empty_list_of_articles():
    # Empty list of articles should return an empty set
    articles = []
    codeflash_output = find_common_tags(articles)

def test_articles_with_no_tags():
    # Articles with no tags should return an empty set
    articles = [{"tags": ["python", "coding"]}, {"tags": []}]
    codeflash_output = find_common_tags(articles)

def test_no_common_tags():
    # Articles with no common tags should return an empty set
    articles = [{"tags": ["python", "coding"]}, {"tags": ["java", "tutorial"]}]
    codeflash_output = find_common_tags(articles)

def test_case_sensitive_tags():
    # Tags with different cases should be treated as different tags
    articles = [{"tags": ["Python", "coding"]}, {"tags": ["python", "coding"]}]
    codeflash_output = find_common_tags(articles)

def test_duplicate_tags_within_article():
    # Articles with duplicate tags should handle them correctly
    articles = [{"tags": ["python", "python", "coding"]}, {"tags": ["python", "coding"]}]
    codeflash_output = find_common_tags(articles)

def test_large_number_of_articles():
    # Function should handle a large number of articles efficiently
    articles = [{"tags": ["tag1", "tag2", "tag3"]} for _ in range(1000)]
    codeflash_output = find_common_tags(articles)

def test_large_number_of_tags_in_articles():
    # Function should handle articles with a large number of tags
    articles = [{"tags": [f"tag{i}" for i in range(1000)]}, {"tags": [f"tag{i}" for i in range(500, 1500)]}]
    codeflash_output = find_common_tags(articles)

def test_mixed_content_in_tags():
    # Function should handle tags with mixed content such as numbers, special characters, and spaces
    articles = [{"tags": ["python3", "coding!", "data science"]}, {"tags": ["python3", "coding!", "machine learning"]}]
    codeflash_output = find_common_tags(articles)

def test_varying_number_of_tags_across_articles():
    # Function should handle articles with varying numbers of tags
    articles = [{"tags": ["python", "coding", "tutorial"]}, {"tags": ["python", "coding"]}, {"tags": ["python"]}]
    codeflash_output = find_common_tags(articles)

def test_overlapping_tags():
    # Function should correctly identify the common tags even when articles have overlapping but non-identical sets of tags
    articles = [{"tags": ["python", "coding", "tutorial"]}, {"tags": ["python", "coding", "guide"]}, {"tags": ["python", "coding", "reference"]}]
    codeflash_output = find_common_tags(articles)

def test_tags_as_subsets():
    # Function should handle cases where the tags of one article are a subset of another
    articles = [{"tags": ["python", "coding", "tutorial"]}, {"tags": ["python", "coding"]}, {"tags": ["coding"]}]
    codeflash_output = find_common_tags(articles)

def test_special_characters_in_tags():
    # Function should handle tags that contain special characters
    articles = [{"tags": ["py@thon", "cod#ing", "tu!torial"]}, {"tags": ["py@thon", "cod#ing"]}]
    codeflash_output = find_common_tags(articles)

# Run the tests
pytest.main()
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.

from common_tags import find_common_tags
import pytest

def test_find_common_tags():
    with pytest.raises(KeyError):
        find_common_tags([(v1 := {'tags': ['']}), v1, {'': []}, {}])

def test_find_common_tags_2():
    find_common_tags([{'': [], 'tags': ['']}, {'\x00\x00\x00\x00': [''], 'tags': []}])

def test_find_common_tags_3():
    find_common_tags([])

To edit these changes git checkout codeflash/optimize-find_common_tags-m7v1i1aj and push.

Codeflash

Certainly! The program can be optimized by utilizing sets for intersection operations, which are generally faster than list comprehensions for this kind of task. Here’s the optimized version.



### Changes Made.
1. **Utilized Set for Intersection**: Instead of a list comprehension inside the loop, using set operations (`intersection_update`) significantly optimizes the performance for finding common elements.
2. **Retained the Original Functionality**: The function signature and return value remain unchanged.

This will run faster, especially when dealing with a large number of articles or tags, as set operations are generally more efficient for membership tests and intersections.
@codeflash-ai-dev codeflash-ai-dev bot added the ⚡️ codeflash Optimization PR opened by CodeFlash AI label Mar 4, 2025
codeflash-ai-dev bot added a commit that referenced this pull request Mar 5, 2025
…timize-find_common_tags-m7v1i1aj`)

Test Dave:
@codeflash-ai-dev
Copy link
Author

⚡️ Codeflash found optimizations for this PR

📄 4211531.56 (42115.32) speedup for sorter in bubble_sort.py

⏱️ Runtime : 1070554.63 25.42 (best of undefined runs)

I created a new dependent PR with the suggested changes. Please review:

If you approve, it will be merged into this PR (branch codeflash/optimize-find_common_tags-m7v1i1aj).

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
⚡️ codeflash Optimization PR opened by CodeFlash AI
Projects
None yet
Development

Successfully merging this pull request may close these issues.

0 participants