Merge pull request #26 from sanjaradylov/first-release

Introduce the first release of moleculegen (#26)

README.md

@@ -1,5 +1,6 @@
 # moleculegen
 
+![example workflow name](https://github.com/sanjaradylov/moleculegen-ml/workflows/moleculegen/badge.svg)
 ![PythonVersion](https://img.shields.io/badge/python-3.7-blue)
 
 This project is an attempt to create a Python package for the complete *de novo* drug design
@@ -13,6 +14,7 @@ In [Stage 2](https://github.com/sanjaradylov/moleculegen-ml/projects/2), we choo
 targets of interest to create a predictive model, and then perform transfer learning on a
 focused set of active molecules.
 
+
 ## Documentation
 For now, our [wiki](https://github.com/sanjaradylov/moleculegen-ml/wiki) serves as a
 documentation (or rather a user guide) for the project.
@@ -25,6 +27,7 @@ current state of the project.
 It is convenient to set up dependencies using environment management systems like
 [conda](https://conda.io/en/latest/index.html) or
 [virtualenv](https://virtualenv.pypa.io/en/stable/).
+We use the latest stable version of Ubuntu to test our project.
 
 Download, install, and set up [Miniconda](https://conda.io/en/latest/miniconda.html).
 
@@ -34,19 +37,33 @@ $ conda env create -f environment.yml
 $ conda activate moleculegen
 ```
 
-Clone the repository:
+If you wish to run experiments on GPU (recommended), please install [CUDA](https://developer.nvidia.com/cuda-toolkit)
+(we use version 10.1) and run
+```bash
+$ pip install -r requirements.txt
+```
+
+And finally, install the package:
 
 ```bash
-$ mkdir moleculegen-ml && cd moleculegen-ml
-$ git clone https://github.com/sanjaradylov/moleculegen-ml.git
+$ pip install git+https://github.com/sanjaradylov/moleculegen-ml.git
 ```
 
+
 ## Usage
 
-Download [ChEMBL database](https://www.ebi.ac.uk/chembl/).
+See [wiki](https://github.com/sanjaradylov/moleculegen-ml/wiki) for feature overview and documentation.
+
+We also provide an example script `scripts/run.py`. To observe the command line arguments print a help message:
+```bash
+$ python3 run.py --help
+```
+
+If you do not have your own data set, please download [ChEMBL database](https://www.ebi.ac.uk/chembl/) and
+follow the instructions above.
 
-Create a text file from ChEMBL database according to a specified SQL query
-(note [issues](#issues)). You can create a dataset manually (without post-processing):
+Create a text file from ChEMBL database according to a specified SQL query.
+You can create a dataset manually (without post-processing):
 
 ```bash
 $ cd data
@@ -59,22 +76,6 @@ $ export DB_FILENAME=YourChEMBL.db
 $ python3 process_stage1_data.py -o ../data/stage1_compounds_post_processed.csv
 ```
 
-The main module is `run.py`. To observe the command line arguments including parameter
-loading/saving and hyperparameters, print a help message:
-```bash
-$ python3 run.py --help
-``` 
-
-Run the main module (currently, it only trains and evaluates an RNN):
-```
-$ cd ..
-$ python3 run.py data/stage1_compounds.csv
-```
-
-## Issues
-The project is in development stage. The author is currently concerned with the implementation
-of [Stage 1](https://github.com/sanjaradylov/moleculegen-ml/projects/1), which has several
-pending [issues](https://github.com/sanjaradylov/moleculegen-ml/issues).
 
 ## Reference
 

setup.py

@@ -11,8 +11,8 @@
 
 setup(
     name='moleculegen',
-    description='Generate novel molecules using recurrent neural networks',
-    version='1.0.dev',
+    description='Generate novel molecules using encoder-decoder networks',
+    version='1.0.0',
     author='Sanjar Ad[iy]lov',
     url=PACKAGE_URL,
     project_urls={