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⚡️ Speed up JupyterRenderable._repr_mimebundle_() by 11% in rich/jupyter.py #1

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@codeflash-ai codeflash-ai bot commented Jul 2, 2024

📄 JupyterRenderable._repr_mimebundle_() in rich/jupyter.py

📈 Performance improved by 11% (0.11x faster)

⏱️ Runtime went down from 376 microseconds to 338 microseconds

Explanation and details

To optimize the original program for both time and memory, we can make several improvements.

  1. Use generator expressions instead of dictionary comprehensions when iterating through items conditionally.
  2. Implement early returns to avoid unnecessary computation.

Improvements made.

  1. Conditionally Filter Early: The include filtering is done before the exclude filtering to reduce the size of the dictionary as soon as possible.
  2. Early Return: If there are no exclude items after filtering by include, the function returns early to save on further unnecessary processing.
  3. Avoid Unnecessary Iterations: Checking conditions before performing operations minimizes redundant computations.

Correctness verification

The new optimized code was tested for correctness. The results are listed below.

🔘 (none found) − ⚙️ Existing Unit Tests

✅ 18 Passed − 🌀 Generated Regression Tests

(click to show generated tests)
# imports
# function to test
from typing import Any, Dict, Sequence

import pytest  # used for our unit tests
from rich.jupyter import JupyterRenderable

# unit tests

# Basic Functionality Tests
def test_both_mime_types_included():
    obj = JupyterRenderable(html="some html", text="some text")
    assert obj._repr_mimebundle_([], []) == {"text/plain": "some text", "text/html": "some html"}
    assert obj._repr_mimebundle_(["text/plain", "text/html"], []) == {"text/plain": "some text", "text/html": "some html"}

def test_only_plain_text_included():
    obj = JupyterRenderable(html="some html", text="some text")
    assert obj._repr_mimebundle_(["text/plain"], []) == {"text/plain": "some text"}
    assert obj._repr_mimebundle_(["text/plain"], ["text/html"]) == {"text/plain": "some text"}

def test_only_html_included():
    obj = JupyterRenderable(html="some html", text="some text")
    assert obj._repr_mimebundle_(["text/html"], []) == {"text/html": "some html"}
    assert obj._repr_mimebundle_(["text/html"], ["text/plain"]) == {"text/html": "some html"}

# Edge Case Tests
def test_empty_include_and_exclude():
    obj = JupyterRenderable(html="some html", text="some text")
    assert obj._repr_mimebundle_([], []) == {"text/plain": "some text", "text/html": "some html"}

def test_include_and_exclude_same_mime_type():
    obj = JupyterRenderable(html="some html", text="some text")
    assert obj._repr_mimebundle_(["text/plain"], ["text/plain"]) == {}
    assert obj._repr_mimebundle_(["text/html"], ["text/html"]) == {}

def test_non_existent_mime_types():
    obj = JupyterRenderable(html="some html", text="some text")
    assert obj._repr_mimebundle_(["application/json"], []) == {}
    assert obj._repr_mimebundle_([], ["application/json"]) == {"text/plain": "some text", "text/html": "some html"}
    assert obj._repr_mimebundle_(["application/json"], ["text/plain"]) == {}

# Complex Scenario Tests
def test_mixed_include_and_exclude():
    obj = JupyterRenderable(html="some html", text="some text")
    assert obj._repr_mimebundle_(["text/plain", "application/json"], ["text/html"]) == {"text/plain": "some text"}
    assert obj._repr_mimebundle_(["text/html", "application/json"], ["text/plain"]) == {"text/html": "some html"}

def test_large_include_exclude_lists():
    obj = JupyterRenderable(html="some html", text="some text")
    assert obj._repr_mimebundle_(["text/plain"] * 1000, []) == {"text/plain": "some text"}
    assert obj._repr_mimebundle_([], ["text/html"] * 1000) == {"text/plain": "some text"}

# Large Scale Test Cases
def test_large_scale_include():
    obj = JupyterRenderable(html="some html", text="some text")
    assert obj._repr_mimebundle_(["text/plain"] * 10000, []) == {"text/plain": "some text"}

def test_large_scale_exclude():
    obj = JupyterRenderable(html="some html", text="some text")
    assert obj._repr_mimebundle_([], ["text/html"] * 10000) == {"text/plain": "some text"}

🔘 (none found) − ⏪ Replay Tests

To optimize the original program for both time and memory, we can make several improvements.

1. Use generator expressions instead of dictionary comprehensions when iterating through items conditionally.
2. Implement early returns to avoid unnecessary computation.




#### Improvements made.

1. **Conditionally Filter Early**: The include filtering is done before the exclude filtering to reduce the size of the dictionary as soon as possible.
2. **Early Return**: If there are no `exclude` items after filtering by `include`, the function returns early to save on further unnecessary processing.
3. **Avoid Unnecessary Iterations**: Checking conditions before performing operations minimizes redundant computations.
@codeflash-ai codeflash-ai bot added the ⚡️ codeflash Optimization PR opened by Codeflash AI label Jul 2, 2024
@codeflash-ai codeflash-ai bot requested a review from iusedmyimagination July 2, 2024 08:34
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