week 1 (Part-1) : Folder Structure

Folder Structure

Since this project is not built on top of a predefined framework, the folder structure was designed intentionally to keep the codebase modular, scalable, and easy to maintain.
Each directory has a clear responsibility, making the project easy to understand and extend.

├── 📁 log
├── 📁 src
│   ├── 📁 mycli.egg-info
│   │   ├── 📄 PKG-INFO
│   │   ├── 📄 SOURCES.txt
│   │   ├── 📄 dependency_links.txt
│   │   ├── 📄 entry_points.txt
│   │   └── 📄 top_level.txt
│   └── 📁 setfile
│       ├── 📁 GoogleOAuth
│       │   ├── 🐍 auth_server.py
│       │   ├── 🐍 db.py
│       │   └── 🐍 gmail_api.py
│       ├── 📁 commands
│       │   ├── 🐍 gmail_auth.py
│       │   ├── 🐍 organize.py
│       │   └── 🐍 revert.py
│       ├── 📁 core
│       │   └── 🐍 prediction.py
│       ├── 📁 model
│       │   ├── 📄 doc_classifier_svm.pkl
│       │   └── 🐍 model.py
│       ├── 📁 utils
│       │   ├── 🐍 file_rules.py
│       │   ├── 🐍 history.py
│       │   ├── 🐍 logger.py
│       │   └── 🐍 reader.py
│       ├── 🐍 __main__.py
│       └── 🐍 cli.py
├── ⚙️ .gitignore
├── 📝 README.md
├── ⚙️ pyproject.toml
└── 📄 requirements.txt

🗂 logs/

This directory stores all runtime logs generated by the application.

Purpose:

• Helps with debugging

• Tracks user actions

• Provides traceability when something goes wrong

Keeping logs separate prevents clutter in the main project and makes troubleshooting easier.

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🗂 src/

The src directory contains the actual application code.
This follows a best practice used in professional Python projects to prevent import issues and keep the project clean.

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🗂 mycli.egg-info/

This folder is auto-generated by Python packaging tools.

Purpose:

• Stores metadata about the package

• Includes dependency information and entry points

It allows the project to behave like a real, installable CLI tool.

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🗂 setfile/

This is the core application package.
Everything related to the CLI and file organization logic lives here.

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🗂 commands/

Each command supported by the CLI is implemented in a separate file.

Why this design?

• Each file handles exactly one command

• Follows the Separation of Concerns principle

• Makes it easy to add new commands in the future

For example:

• organize.py handles file organization

• revert.py handles undoing previous operations

This keeps the CLI logic clean and easy to extend.

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🗂 core/

This folder contains the heart of the project.

core/
└── prediction.py

prediction.py is responsible for making intelligent decisions about where files should go.
All higher-level features depend on this logic, which is why it lives in core.

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🗂 model/

This directory contains everything related to machine learning.

model/
├── doc_classifier_svm.pkl
└── model.py

• model.py loads and manages the ML model

• doc_classifier_svm.pkl is the trained SVM model used to classify documents

Using a separate folder for ML assets makes the project easier to manage and retrain.

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🗂 utils/

This directory contains reusable helper code used across the project.

These utilities:

• Handle logging

• Track file history

• Read file metadata

• Apply file organization rules

This avoids code duplication and keeps the main logic clean.

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🗂 GoogleOAuth/

This is an advanced feature of the project.

GoogleOAuth/
├── auth_server.py
├── db.py
└── gmail_api.py

It allows the CLI to:

• Authenticate with Google

• Access Gmail

• Download email attachments

These attachments can then be organized automatically using the same ML-powered system.

This feature is isolated in its own folder so it doesn’t interfere with the main CLI logic.

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🐍 cli.py

This is the main entry point of the application.

It:

• Parses command-line arguments

• Dispatches the correct command from the commands/ folder

• Connects user input to the internal logic

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🐍 main.py

This allows the project to be executed as:

python -m setfile

It makes the package behave like a real CLI application.

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📄 pyproject.toml & requirements.txt

These files define:

• Project metadata

• Dependencies

• Build configuration

They allow the project to be installed and run reliably on any system.

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🧠 Why this structure works

This structure was chosen to ensure:

• Scalability – new commands and features can be added easily

• Maintainability – logic is cleanly separated

• Professional packaging – the project behaves like a real Python CLI tool

• AI integration – ML and prediction logic are cleanly isolated

Even without a framework, this design follows industry-level software architecture principles.

You Can see my project on and suggestions are welcomed :

Github Link : https://github.com/VivekPrajapati-Git/setfile

“That’s all for today. This concludes Part 1 of this week’s series. In Part 2, we’ll dive deeper into the project workflow and explore how all the components come together.”