Readme update (#12)

* update

* v bump

* remove license readme

Author: hasnainroopawalla

README.md

@@ -1,15 +1,15 @@
 <h1 align="center">Ant Colony Optimization</h1>
 
-
 [![Develop](https://github.com/hasnainroopawalla/Ant-Colony-Optimization/actions/workflows/develop.yml/badge.svg)](https://github.com/hasnainroopawalla/Ant-Colony-Optimization/actions/workflows/develop.yml)
 [![Deploy](https://github.com/hasnainroopawalla/Ant-Colony-Optimization/actions/workflows/deploy.yml/badge.svg)](https://github.com/hasnainroopawalla/Ant-Colony-Optimization/actions/workflows/deploy.yml)
 [![PyPi version](https://img.shields.io/pypi/v/aco_routing.svg)](https://pypi.python.org/pypi/aco_routing/)
 ![Downloads](https://img.shields.io/pypi/dm/aco_routing.svg)
-<!-- [![Python versions](https://img.shields.io/pypi/pyversions/aco_routing.svg?style=plastic)](https://img.shields.io/pypi/pyversions/aco_routing.svg?style=plastic) -->
 
+<!-- [![Python versions](https://img.shields.io/pypi/pyversions/aco_routing.svg?style=plastic)](https://img.shields.io/pypi/pyversions/aco_routing.svg?style=plastic) -->
 
 A Python package to find the shortest path in a graph using Ant Colony Optimization (ACO).
 
+➡️ Check out my [Medium article](https://medium.com/@hasnain.roopawalla/ant-colony-optimization-1bbc346c2da5) for a detailed walkthrough 🚀
 
 The Ant colony Optimization algorithm is a probabilistic technique for solving computational problems which can be reduced to finding good paths through graphs ([source](https://en.wikipedia.org/wiki/Ant_colony_optimization_algorithms)).
 
@@ -18,20 +18,24 @@ This implementation of the ACO algorithm uses the [NetworkX](https://networkx.or
 ## 🏁 Getting Started <a name = "getting_started"></a>
 
 ### To install the package directly from PyPi:
+
 ```
 $ pip install aco_routing
 ```
 
 ## 🎈 Usage <a name="usage"></a>
-> **_Check out:_** [example.py](https://github.com/hasnainroopawalla/Ant-Colony-Optimization/blob/00cd068597ab9a69a8eb81c8a3fd984797d2eefd/example.py)
+
+> Check out: [example.py](https://github.com/hasnainroopawalla/ant-colony-optimization/blob/master/example.py)
 
 Import all the dependencies:
+
 ```python
 from aco_routing import ACO
 import networkx as nx
 ```
 
 Create a `NetworkX.Graph` object with nodes and edges:
+
 ```python
 G = nx.DiGraph()
 
@@ -49,6 +53,7 @@ G.add_edge("G", "E", cost=2)
 ```
 
 Use ACO to find the shortest path and cost between the `source` and `destination`:
+
 ```python
 aco = ACO(G, ant_max_steps=100, num_iterations=100, ant_random_spawn=True)
 
@@ -60,6 +65,7 @@ aco_path, aco_cost = aco.find_shortest_path(
 ```
 
 Output:
+
 ```
 ACO path: A -> H -> G -> E -> D
 ACO path cost: 8.0
@@ -68,19 +74,18 @@ ACO path cost: 8.0
 ## 📦 Contents <a name = "contents"></a>
 
 ### Ant
+
 `aco_routing.Ant`
+
 - An `Ant` that traverses the graph.
 
 ### ACO
+
 `aco_routing.ACO`
-- The traditional Ant Colony Optimization algorithm that spawns ants at various nodes in the graph and finds the shortest path between the specified source and destination ([pseudo code](https://en.wikipedia.org/wiki/Ant_colony_optimization_algorithms#Algorithm_and_formula)).
 
+- The traditional Ant Colony Optimization algorithm that spawns ants at various nodes in the graph and finds the shortest path between the specified source and destination ([pseudo code](https://en.wikipedia.org/wiki/Ant_colony_optimization_algorithms#Algorithm_and_formula)).
 
 ## Contributing
 
 - Post any issues and suggestions on the GitHub [issues](https://github.com/hasnainroopawalla/Ant-Colony-Optimization/issues) page.
 - To contribute, fork the project and then create a pull request back to master.
-
-
-## License
-This project is licensed under the MIT License - see the [LICENSE](https://github.com/hasnainroopawalla/Ant-Colony-Optimization/blob/73b65a6fd14e3e5517b479cfecac1140f0ae7899/LICENSE) file for details.

setup.py

@@ -8,7 +8,7 @@
 
 setup(
     name="aco_routing",
-    version="1.1.0",
+    version="1.1.1",
     packages=find_packages(exclude="tests"),
     description="A Python package to find the shortest path in a graph using Ant Colony Optimization (ACO)",
     long_description=long_description,