SXXXXXXX_PyUCC/doc/English-manual.md
2025-12-01 09:49:28 +01:00

149 lines
8.0 KiB
Markdown

# PyUCC User Manual
**Document Version:** 1.0
**Application:** PyUCC (Python Unified Code Counter)
---
## 1. Introduction
**PyUCC** is an advanced static code analysis tool. Its primary objective is to provide quantitative metrics on software development and, crucially, to track code evolution over time through a powerful **Differing** system.
### What is it for?
1. **Counting:** Knowing exactly how many lines of code, comments, and blank lines make up your project.
2. **Measuring:** Calculating software complexity and maintainability.
3. **Comparing:** Understanding exactly what changed between two versions (added/removed/modified files and how complexity has shifted).
---
## 2. Core Concepts
Before starting, it is useful to understand the key terms used in the application.
### 2.1 Baseline
A **Baseline** is an instant "snapshot" of your project at a specific moment in time.
* When you create a baseline, PyUCC saves a copy of the files and calculates all metrics.
* Baselines serve as reference points (benchmarks) for future comparisons.
### 2.2 Supported Metrics
* **SLOC (Source Lines of Code):**
* *Physical Lines:* Total lines in the file.
* *Code Lines:* Lines containing executable code.
* *Comment Lines:* Documentation lines.
* *Blank Lines:* Empty lines (often used for formatting).
* **Cyclomatic Complexity (CC):** Measures the complexity of the control flow (how many `if`, `for`, `while` statements, etc.). **Lower is better.**
* **Maintainability Index (MI):** An index from 0 to 100 estimating how easy the code is to maintain. **Higher is better** (above 85 is excellent, below 65 is problematic).
### 2.3 Profile
A **Profile** is a saved configuration that tells PyUCC:
* Which folders to analyze.
* Which languages to include (e.g., Python and C++ only).
* What to ignore (e.g., `venv`, `build` folders, temporary files).
---
## 3. User Interface (GUI)
The interface is divided into functional zones to keep the workflow organized.
1. **Top Bar:**
* **Profile** selection.
* Access to **Settings** and Profile Manager (**Manage**).
2. **Actions Bar:** The main buttons to start operations (`Scan`, `Countings`, `Metrics`, `Differing`).
3. **Progress Area:** Progress bar and file counter.
4. **Results Table:** The large central table where data appears.
5. **Log & Status:** At the bottom, a log panel to see what is happening and a status bar monitoring system resources (CPU/RAM).
---
## 4. Step-by-Step Guide
### 4.1 First Run & Profile Configuration
The first thing to do upon opening PyUCC is to define *what* to analyze.
1. Click on **⚙️ Manage...** in the top bar.
2. Click on **📝 New** to clear the fields.
3. Enter a **Name** for the profile (e.g., "My Backend Project").
4. In the **Paths** section, use **Add Folder** to select your code's root directory.
5. In the **Filter Extensions** section, select the languages you are interested in (e.g., Python, Java).
6. In the **Ignore patterns** box, you can keep the defaults (which already exclude `.git`, `__pycache__`, etc.).
7. Click **💾 Save**.
### 4.2 Simple Analysis (Scan, Countings, Metrics)
If you only want to analyze the current state without comparisons:
* **🔍 Scan:** Simply verifies which files are found based on the profile filters. Useful to check if you are including the right files.
* **🔢 Countings:** Analyzes every file and reports how many code, comment, and blank lines exist.
* **📊 Metrics:** Calculates Cyclomatic Complexity and Maintainability Index for each file.
> **Tip:** You can double-click on a file in the results table to open it in the built-in **File Viewer**, which provides syntax highlighting and a colored minimap (blue=code, green=comments).
### 4.3 The "Differing" Workflow (Comparison)
This is PyUCC's most powerful feature.
**Step A: Create the First Baseline**
1. Select your profile.
2. Click on **🔀 Differing**.
3. If this is the first time you analyze this project, PyUCC will notify you: *"No baseline found"*.
4. Confirm creation. PyUCC will take a "snapshot" of the project (Baseline).
**Step B: Work on the Code**
Now you can close PyUCC and work on your code (modify files, add new ones, delete old ones).
**Step C: Compare**
1. Reopen PyUCC and select the same profile.
2. Click on **🔀 Differing**.
3. This time, PyUCC detects an existing previous Baseline and asks which one to compare against (if you have multiple).
4. The result will be a table with specific color coding:
* **Green:** Added files or improved metrics.
* **Red:** Deleted files or worsened metrics (e.g., increased complexity).
* **Yellow/Orange:** Modified files.
* **Δ (Delta) Columns:** Show numerical differences (e.g., `+50` code lines, `-2` complexity).
> **Diff Viewer:** If you double-click a row in the Differing results, a window will open showing the two files side-by-side, highlighting exactly which lines changed.
---
## 5. Exemplary Use Cases
### Case 1: Refactoring
* **Goal:** You want to clean up code and ensure you haven't increased complexity.
* **Action:** Create a Baseline before starting. Perform refactoring. Run *Differing*.
* **Verification:** Check the **Δ avg_cc** column. If it is negative (e.g., `-0.5`), great! You reduced complexity. If **Δ comment_lines** is positive, you improved documentation.
### Case 2: Code Review
* **Goal:** A colleague added a new feature. What changed?
* **Action:** Run *Differing* against the previous master/main version.
* **Verification:** Sort by "Status". Immediately see **Added** (A) and **Modified** (M) files. Open the Diff Viewer on modified files to inspect specific lines.
---
## 6. Development Philosophy (For Developers)
PyUCC was built following rigorous software engineering principles, reflected in its stability and usage.
### 6.1 Clean Code & PEP8 Standards
The code adheres to the Python **PEP8** standard. This ensures that if you ever want to extend the tool or write automation scripts using the `core` modules, you will find readable, standardized, and predictable code.
### 6.2 Separation of Concerns (SoC)
The application is strictly divided into two parts:
1. **Core (`pyucc.core`):** Contains pure logic (scanning, metric calculation, diff algorithms). It knows nothing about the GUI.
2. **GUI (`pyucc.gui`):** Handles only visualization and user interaction.
**Philosophy:** This allows changing the interface without breaking the logic, or using the logic via command line without launching the GUI.
### 6.3 Non-Blocking UI (Worker Manager)
You may notice the interface never freezes, even when analyzing thousands of files.
This is thanks to the **WorkerManager**. All heavy operations are executed in separate background threads. The GUI receives updates via a thread-safe `queue`.
* **User Benefit:** You can always press "Cancel" if an operation takes too long.
### 6.4 Intelligent Matching Algorithm (Gale-Shapley)
In *Differing*, PyUCC doesn't just check if filenames are identical. It uses an algorithm inspired by the "Stable Marriage Problem" (Gale-Shapley) combined with Levenshtein distance on paths.
* **Philosophy:** If you move a file from one folder to another, the system attempts to recognize it as the *same* file moved, rather than marking one as "Deleted" and one as "Added".
### 6.5 Determinism
The system uses content hashing (SHA1/MD5) to optimize calculations (caching) and to determine if a file has *truly* changed, ignoring the filesystem modification timestamp if the content remains identical.
---
## 7. Troubleshooting Common Issues
* **Program finds no files:** Check the Profile Manager to see if the file extension is selected in the language list or if the folder is covered by "Ignore patterns".
* **Extreme slowness:** If you included folders with thousands of small non-code files (e.g., `node_modules` or image assets), add them to "Ignore patterns".
* **Empty Diff Viewer:** Ensure the source files still exist on disk. If you deleted the project folder after creating the baseline, the viewer cannot display the current file.