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https://github.com/madhurimarawat/learning-codacy
This repository is dedicated to learning about the code review automation tool Codacy, which helps improve code quality by analyzing codebases and providing actionable feedback.
https://github.com/madhurimarawat/learning-codacy
automation beginner codacy codacy-badge codacy-integration code-review code-review-automation codes detailed-readme discussions documentation installation-guide learning-tool markdown open-source output-explained python snapshots software-engineering study-materials
Last synced: 1 day ago
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This repository is dedicated to learning about the code review automation tool Codacy, which helps improve code quality by analyzing codebases and providing actionable feedback.
- Host: GitHub
- URL: https://github.com/madhurimarawat/learning-codacy
- Owner: madhurimarawat
- License: mit
- Created: 2024-11-24T05:45:34.000Z (3 months ago)
- Default Branch: main
- Last Pushed: 2024-11-24T12:52:37.000Z (3 months ago)
- Last Synced: 2024-12-17T00:37:26.844Z (about 2 months ago)
- Topics: automation, beginner, codacy, codacy-badge, codacy-integration, code-review, code-review-automation, codes, detailed-readme, discussions, documentation, installation-guide, learning-tool, markdown, open-source, output-explained, python, snapshots, software-engineering, study-materials
- Language: Python
- Homepage: https://www.codacy.com/
- Size: 871 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Learning Codacy
This repository is dedicated to learning about the code review automation tool **Codacy**, which helps improve code quality by analyzing codebases and providing actionable feedback.
---
## **Introduction**
**Codacy** is an automated code review tool that integrates seamlessly with GitHub and other version control platforms. It performs static code analysis, identifies code smells, and enforces best practices to streamline development workflows.
## **Steps to Set Up Codacy**
### **1. Create an Account**
1. Visit [Codacy](https://www.codacy.com/) and sign up using your **GitHub** account.
- Grant the necessary permissions for Codacy to access your repositories.
2. After authorization, you will be redirected to the Codacy dashboard.
---
### **2. Add Your Repository**
1. On the Codacy dashboard, click **"Add a repository"**.
2. Select the repository (**Learning-Codacy**) you want Codacy to analyze.
- Ensure Codacy has the required access permissions.
3. Codacy will perform an initial scan and generate a baseline report.
---
### **3. Test with Deliberate Code Issues**
To test Codacy’s capabilities, include intentional errors in your code, such as naming inconsistencies, duplication, or missing error handling. Observe how Codacy detects and reports these issues.
---
### **4. Integrate Codacy with GitHub**
1. Enable GitHub integration in Codacy:
- Go to **Settings > Integrations** in your Codacy dashboard.
- Activate **GitHub Status Checks** to view analysis results directly in your pull requests.
2. Once integrated, Codacy will provide feedback automatically during your development process.
---
## Analysis and Evaluation
### **Benefits of Integration**
- **Automatic Code Reviews**: Save time by automating style and complexity checks.
- **Feedback in Pull Requests**: View issues directly in GitHub pull requests.
- **Customizable Rules**: Focus on the metrics that matter most for your project.
- **Improved Code Quality**: Maintain consistent standards across your team.
### **Example Workflow**
1. Developer submits a pull request.
2. CodeFactor/Codacy analyzes the code changes.
3. Issues and suggestions are displayed directly in the pull request.
4. Developer resolves the issues before merging.
### **Troubleshooting**
- **Analysis Not Triggering**: Ensure the repository is public or that the service has access to your private repository.
---
## Directory Structure
```
📂 Learning-Codacy
├── 📁 Codes
│ ├── 📄 sample_code_corrected.py # Testing script for the corrected workflow, ensuring proper functionality of the Streamlit app.
│ ├── 📄 sample_code_with_errors.py # Script demonstrating the erroneous workflow for analysis and debugging.
│ ├── 📄 sample_code_with_errors_codefactor.py # Script showcasing the error-prone workflow updated for CodeFactor review and improvements.
│
├── 📁 Documentation Files
│ ├── 📄 Code Review Automation.md # Sprint planning document outlining the development process and project timeline.
│ ├── 📄 Code Review Automation.pdf # A formatted PDF report summarizing project outputs and features for sharing and printing.
│
├── 📁 Output
│ ├── 📄 Experiment 9 Output.docx # Word document explaining the experiment's results in detail.
│ ├── 📄 Experiment 9 Output.pdf # PDF version of the experiment's outputs for easy distribution.
│
├── 📄 README.md # Overview of the project, including purpose, setup instructions, and key features.
├── 📄 LICENSE.md # License information governing the usage, distribution, and modification of the project.
```
---
## Thanks for Visiting 😄
- Drop a 🌟 if you find this repository useful.
- If you have any doubts or suggestions, feel free to reach me.
📫 How to reach me: [](https://www.linkedin.com/in/madhurima-rawat/)
- **Contribute and Discuss:** Feel free to open issues 🐛, submit pull requests 🛠️, or start discussions 💬 to help improve this repository!