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34 changes: 34 additions & 0 deletions cbrain_cli/data/readme.md
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# Welcome to the CBRAIN CLI Data Layer! 👋

This directory is the core engine connecting our command-line tools to **CBRAIN**—a powerful web-enabled platform built to manage large, distributed research datasets and mediate high-performance computing (HPC) tasks.

Whenever the CLI needs to talk to CBRAIN's architecture (specifically the **BrainPortal** API), it happens right here.

## How It Is Used 🛠️

Think of these Python modules as your direct bridge to CBRAIN's resources. They handle all the API calls, data fetching, and object modeling. If a user command needs to interact with the CBRAIN database, these modules do the heavy lifting.

### The Modules at a Glance (with Example Commands!):

* **`background_activities.py`**: Tracks backend jobs in progress (`cbrain background`).
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Do we want to hyperlink of this file or this is okay?

* *Example:* `cbrain background list`
* **`data_providers.py`**: Connects to the systems storing your research data (`cbrain dataprovider`).
* *Example:* `cbrain dataprovider show 15`
* **`files.py`**: Manages data uploads, caching, and transfers across CBRAIN (`cbrain file`).
* *Example:* `cbrain file move --file-id 2 --dp-id 15`
* **`projects.py`**: Keeps user research organized (`cbrain project`).
* *Example:* `cbrain project switch 10`
* **`remote_resources.py`**: Interfaces with external network capabilities (`cbrain remote-resource`).
* *Example:* `cbrain remote-resource list`
* **`tags.py`**: Organizes and categorizes files and tasks (`cbrain tag`).
* *Example:* `cbrain tag create --name NewTag1 --user-id 2 --group-id 3`
* **`tasks.py`**: Orchestrates intensive compute jobs on remote HPCs (`cbrain task`).
* *Example:* `cbrain task show 2`
* **`tools.py` & `tool_configs.py`**: Manages the scientific tools available on CBRAIN (`cbrain tool` / `cbrain tool-config`).
* *Example:* `cbrain tool list`

## How It Fits Together 🧩

**Data here, Display there.**

This folder is strictly for fetching raw objects from the CBRAIN server. Once we pull the data, we hand it off to the `formatter/` directory, which takes those raw responses and turns them into clean, human-readable outputs for your terminal!
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# Welcome to the CBRAIN CLI Formatter Layer! 🎨

This directory is all about **presentation**. Once the CLI fetches raw data objects from the CBRAIN backend (using the `data/` modules), it hands them over to these formatter scripts to make them look great in your terminal.

These formatters are responsible for creating the clean tables, organized summaries, and human-readable text you see when you run a command.

## How It Fits Together 🧩

**Data there, Display here.**

While the `data/` directory handles backend API interactions, the `formatter/` directory focuses exclusively on presenting that info. Every `_fmt.py` file here perfectly matches a corresponding data module. For example, `tasks.py` gets the data, and `tasks_fmt.py` decides how to draw it on your screen!

## What the Formatter Actually Does 🪄

Imagine you ask CBRAIN for a list of your files using `cbrain file list`. The raw data coming from the server is a dense machine-readable bundle filled with IDs, timestamps, and metadata.

Instead of throwing that raw JSON at you, the formatter layer catches the data and turns it into a beautiful, easy-to-read table right in your terminal. Here is exactly what these scripts do:

**The Raw Data (what `data/` gets):**
```json
{"id": 1024, "name": "my_mri_scan.nii.gz", "size": 47185920, "status": "synced"}
```

**The Formatted Output (what `formatter/` shows you):**
```text
+---------+----------------------+---------+-------------+
| File ID | Name | Size | Status |
+---------+----------------------+---------+-------------+
| 1024 | my_mri_scan.nii.gz | 45.0 MB | Synced |
+---------+----------------------+---------+-------------+
```

*(Fun fact: We don't use heavy external libraries like `PrettyTable` or `Rich` for this! The CLI uses a custom-built, lightweight, dynamic table formatter powered completely by Python's built-in `textwrap` and `shutil` libraries. That means zero extra dependencies to slow you down!)*

Every `_fmt.py` script in this folder is basically a tiny artist that knows exactly how to draw its specific type of data so it's perfectly readable for you!