Merge pull request #38 from Schefflera-Arboricola/styling_fixes

MAINT : styling fixes

README.md

@@ -18,39 +18,41 @@ nx-parallel provides parallelized implementations for the following NetworkX fun
 
 See the `/timing` folder for more heatmaps and code for heatmap generation!
 
-
 ### Development install
 
 To setup a local development:
 
 - Fork this repository.
 - Clone the forked repository locally.
+
 ```
 git clone [email protected]:<your_username>/networkx.git
 ```
+
 - Create a fresh conda/mamba virtualenv and install the dependencies
+
 ```
 pip install -e ".[developer]"
 ```
+
 - Install pre-commit actions that will run the linters before making a commit
+
 ```
 pre-commit install
 ```
 
-
 ## Usage
 
 Here's an example of how to use nx-parallel:
 
 ```python
-In [1]: import networkx as nx; import nx_parallel
-
-In [2]: G = nx.path_graph(4)
-
-In [3]: H = nx_parallel.ParallelGraph(G)
+import networkx as nx
+import nx_parallel
 
-In [4]: nx.betweenness_centrality(H)
-Out[4]: {0: 0.0, 1: 0.6666666666666666, 2: 0.6666666666666666, 3: 0.0}
+G = nx.path_graph(4)
+H = nx_parallel.ParallelGraph(G)
+nx.betweenness_centrality(H)
+# output : {0: 0.0, 1: 0.6666666666666666, 2: 0.6666666666666666, 3: 0.0}
 ```
 
 ## Testing

benchmarks/README.md

@@ -3,20 +3,20 @@
 1. clone this repo
 2. `cd benchmarks`
 3. If you are working on a different branch then update the `branches` in the `asv.conf.json` file.
-4. `asv run` will run the benchmarks on the last commit 
-    - or use `asv continuous base_commit_hash test_commit_hash` to run the benchmark to compare two commits
-    - or `asv run -b <benchmark_file_name> -k <benchmark_name>` to run a particular benchmark.
-    - if you are running benchmarks for the first time, you will be asked to enter your machine information after this command.
+4. `asv run` will run the benchmarks on the last commit
+   - or use `asv continuous base_commit_hash test_commit_hash` to run the benchmark to compare two commits
+   - or `asv run -b <benchmark_file_name> -k <benchmark_name>` to run a particular benchmark.
+   - if you are running benchmarks for the first time, you will be asked to enter your machine information after this command.
 5. `asv publish` will create a `html` folder with the results
 6. `asv preview` will host the results locally at http://127.0.0.1:8080/
 
 <hr>
 
 ## Structure of benchmarks
 
-* Each `bench_` file corresponds to a folder/file in the [networkx/algorithms](https://github.com/networkx/networkx/tree/main/networkx/algorithms) directory in NetworkX
-* Each class inside a `bench_` file corresponds to every file in a folder(one class if it’s a file) in networkx/algorithms
-* The class name corresponds to the file name and the `x` in `bench_x` corresponds to the folder name(class name and `x` are the same if it’s a file in networkx/algorithms)
-* Each `time_` function corresponds to each function in the file.
-* For other folders in [networkx/networkx](https://github.com/networkx/networkx/tree/main/networkx) like `generators`, `classes`, `linalg`, `utils` etc. we can have different `bench_` files for each of them having different classes corresponding to different files in each of these folders.
-* For example: `bench_centrality.py` corresponds to `networkx/algorithms/centrality` folder in NetworkX and the `Betweenness` class inside it corresponds to the `betweenness.py` file in `networkx/algorithms/centrality` folder in NetworkX. And the `time_betweenness_centrality` function corresponds to the `betweenness_centrality` function.
+- Each `bench_` file corresponds to a folder/file in the [networkx/algorithms](https://github.com/networkx/networkx/tree/main/networkx/algorithms) directory in NetworkX
+- Each class inside a `bench_` file corresponds to every file in a folder(one class if it’s a file) in networkx/algorithms
+- The class name corresponds to the file name and the `x` in `bench_x` corresponds to the folder name(class name and `x` are the same if it’s a file in networkx/algorithms)
+- Each `time_` function corresponds to each function in the file.
+- For other folders in [networkx/networkx](https://github.com/networkx/networkx/tree/main/networkx) like `generators`, `classes`, `linalg`, `utils` etc. we can have different `bench_` files for each of them having different classes corresponding to different files in each of these folders.
+- For example: `bench_centrality.py` corresponds to `networkx/algorithms/centrality` folder in NetworkX and the `Betweenness` class inside it corresponds to the `betweenness.py` file in `networkx/algorithms/centrality` folder in NetworkX. And the `time_betweenness_centrality` function corresponds to the `betweenness_centrality` function.