gyliu513 / langX101

Apache License 2.0
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streamlit example #187

Closed gyliu513 closed 4 months ago

gyliu513 commented 4 months ago

PR Type

enhancement


Description


Changes walkthrough πŸ“

Relevant files
Enhancement
streamlit-example.py
Add a simple Streamlit application example                             

streamlit-test/streamlit-example.py
  • Added a new Streamlit application example.
  • Displayed a title and introductory text.
  • Created a DataFrame and displayed it.
  • Generated and displayed a random line chart.
  • +19/-0   

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    Summary by CodeRabbit

    coderabbitai[bot] commented 4 months ago

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    Walkthrough

    This update introduces a new Streamlit application, showcasing its core functionalities. The app features a title and introductory text, displays a DataFrame with two columns, and visualizes random data through a line chart. This implementation highlights Streamlit's capabilities for interactive data presentation and analysis.

    Changes

    Files Change Summary
    streamlit-test/streamlit-example.py Introduced a simple Streamlit app with title, text, DataFrame display, and line chart visualization.

    Poem

    🐰 In a garden of code where the data blooms,
    A Streamlit app dances, dispelling the glooms.
    With charts that wiggle and DataFrames neat,
    Jump in, dear user, and feel the sweet beat!
    Let numbers and colors together play,
    In this wondrous world, come join the display! 🌼


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    github-actions[bot] commented 4 months ago

    PR Reviewer Guide πŸ”

    ⏱️ Estimated effort to review: 2 πŸ”΅πŸ”΅βšͺβšͺβšͺ
    πŸ§ͺ No relevant tests
    πŸ”’ No security concerns identified
    ⚑ No key issues to review
    github-actions[bot] commented 4 months ago

    PR Code Suggestions ✨

    CategorySuggestion                                                                                                                                    Score
    Enhancement
    Use np.random.normal to explicitly set the distribution parameters ___ **Replace the use of np.random.randn with np.random.normal to specify mean and
    standard deviation explicitly for clarity and control.** [streamlit-test/streamlit-example.py [15]](https://github.com/gyliu513/langX101/pull/187/files#diff-4e28ef1c28664b82a744a29c1dba8326307e03a73c1b048daa3c407c4854c44bR15-R15) ```diff -np.random.randn(20, 3), +np.random.normal(loc=0, scale=1, size=(20, 3)), ```
    Suggestion importance[1-10]: 8 Why: This suggestion provides better clarity and control over the random data generation by explicitly setting the mean and standard deviation, which is a meaningful enhancement.
    8
    Maintainability
    Refactor hardcoded DataFrame into a function for better modularity ___ **Replace the hardcoded DataFrame with a function that generates the DataFrame. This
    will make the code more modular and easier to update or reuse.** [streamlit-test/streamlit-example.py [8-11]](https://github.com/gyliu513/langX101/pull/187/files#diff-4e28ef1c28664b82a744a29c1dba8326307e03a73c1b048daa3c407c4854c44bR8-R11) ```diff -st.write(pd.DataFrame({ - 'Column A': [1, 2, 3, 4], - 'Column B': [10, 20, 30, 40] -})) +def create_dataframe(): + return pd.DataFrame({ + 'Column A': [1, 2, 3, 4], + 'Column B': [10, 20, 30, 40] + }) +st.write(create_dataframe()) ```
    Suggestion importance[1-10]: 7 Why: This suggestion improves code modularity and reusability by refactoring the hardcoded DataFrame into a function. However, it is not crucial for the functionality of the code.
    7
    Readability
    Store DataFrame in a variable before using it to improve readability ___ **Use a variable to store the DataFrame before passing it to st.write to enhance
    readability and debugging.** [streamlit-test/streamlit-example.py [8-11]](https://github.com/gyliu513/langX101/pull/187/files#diff-4e28ef1c28664b82a744a29c1dba8326307e03a73c1b048daa3c407c4854c44bR8-R11) ```diff -st.write(pd.DataFrame({ +data = pd.DataFrame({ 'Column A': [1, 2, 3, 4], 'Column B': [10, 20, 30, 40] -})) +}) +st.write(data) ```
    Suggestion importance[1-10]: 6 Why: Storing the DataFrame in a variable enhances readability and makes debugging easier, but it is a minor improvement and not essential for the code's functionality.
    6