Update readme to include useful badges

README.md

@@ -1,37 +1,63 @@
-## NVCC Plugin for Jupyter notebook
+# nvcc4jupyter: CUDA C++ plugin for Jupyter Notebook
 
-### V2 is available
+| | |
+| --- | --- |
+| Testing | ![Python Versions][python-version] [![CI - Test][test-badge]][test-workflow] [![Coverage][coverage-badge]][coverage-results] |
+| Package | [![PyPI Latest Release][pypi-latest-version]][pypi-project-url] [![PyPI Downloads][pypi-downloads]][pypi-project-url] |
 
-V2 brings support of multiple source and header files.
 
-##### Usage
+[python-version]: https://img.shields.io/pypi/pyversions/nvcc4jupyter
+[test-badge]: https://github.com/cosminc98/nvcc4jupyter/actions/workflows/test.yml/badge.svg
+[test-workflow]: https://github.com/cosminc98/nvcc4jupyter/actions/workflows/test.yml
+[coverage-badge]: https://codecov.io/github/cosminc98/nvcc4jupyter/coverage.svg?branch=master
+[coverage-results]: https://codecov.io/gh/cosminc98/nvcc4jupyter
+[pypi-project-url]: https://pypi.org/project/nvcc4jupyter/
+[pypi-latest-version]: https://img.shields.io/pypi/v/nvcc4jupyter.svg
+[pypi-downloads]: https://img.shields.io/pypi/dd/nvcc4jupyter.svg?label=PyPI%20downloads
 
-- Install and load extension
+
-```
+## What is it?
-!pip install git+https://github.com/andreinechaev/nvcc4jupyter.git
+
-%load_ext nvcc_plugin
+**nvcc4jupyter** is a Jupyter Notebook plugin that provides cell and line
+[magics](https://ipython.readthedocs.io/en/stable/interactive/magics.html)
+to allow running CUDA C++ code from a notebook. This is especially
+useful when combined with a hosted service such a Google's
+[Colab](https://colab.research.google.com/) which provide CUDA capable GPUs
+and you can start learning CUDA C++ without having to install anything or even
+to own a GPU yourself.
+
+## Table of Contents
+
+- [Main Features](#main-features)
+- [Install](#install)
+- [Dependencies](#dependencies)
+- [Installation from sources](#installation-from-sources)
+- [License](#license)
+- [Documentation](#documentation)
+
+## Main Features
+Here are just a few of the things that nvcc4jupyter does well:
+
+  - TODO1
+  - TODO2
+
+## Install
+The installer for the latest released version is available at the [Python
+Package Index (PyPI)](https://pypi.org/project/nvcc4jupyter).
+
+```sh
+pip install nvcc4jupyter
 ```
 
-- Mark a cell to be treated as cuda cell
+## Usage
-> `%%cuda --name example.cu --compile false`
+TODO
->> NOTE: The cell must contain either code or comments to be run successfully. 
->> It accepts 2 arguments. `-n` | `--name`  - which is the name of either CUDA source or Header
->> The name parameter must have extension `.cu` or `.h`
->> Second argument `-c` | `--compile`; default value is `false`. The argument is a flag to specify
->> if the cell will be compiled and run right away or not. It might be usefull if you're playing in
->> the `main` function
 
-- To compile and run all CUDA files you need to run
+## Documentation
-```
+The official documentation is hosted on [TODO](TODO).
-%%cuda_run
-# This line just to bypass an exeption and can contain any text
-```
 
-- To profile your CUDA kernels using NVIDIA Nsight Compute CLI profiler you need to run
+## License
-```
+[TODO](LICENSE)
-%%cu --profile
+
-```
+<hr>
-- You can add options to the profiler. Keep in mind that any argument after "--profiler-args" will be considered as a profiler argument. For example, to select which sections to collect metrics for you need to run
+
-```
+[Go to Top](#table-of-contents)
-%%cu --profile --profiler-args --section SpeedOfLight --section MemoryWorkloadAnalysis --section Occupancy
-```