<commit_before>﻿# DeepChem
[![Build Status](https://travis-ci.org/deepchem/deepchem.svg?branch=master)](https://travis-ci.org/deepchem/deepchem)
[![Coverage Status](https://coveralls.io/repos/github/deepchem/deepchem/badge.svg?branch=master)](https://coveralls.io/github/deepchem/deepchem?branch=master)

DeepChem aims to provide a high quality open-source toolchain that
democratizes the use of deep-learning in drug discovery, materials science, and quantum
chemistry. DeepChem is a package developed by the [Pande group](https://pande.stanford.edu/) at
Stanford and originally created by [<NAME>](http://rbharath.github.io/).

### Table of contents:

* [Requirements](#requirements)
* [Installation from Source](#installation)
* [FAQ](#faq)
* [Getting Started](#getting-started)
    * [Input Formats](#input-formats)
    * [Data Featurization](#data-featurization)
    * [Performances](#performances)
* [Contributing to DeepChem](#contributing-to-deepchem)
    * [Code Style Guidelines](#code-style-guidelines)
    * [Documentation Style Guidelines](#documentation-style-guidelines)
    * [Gitter](#gitter)
* [DeepChem Publications](#deepchem-publications)
* [Examples](/examples)
* [About Us](#about-us)
    
## Requirements
* [openbabel](http://openbabel.org/wiki/Main_Page)
* [pandas](http://pandas.pydata.org/)
* [rdkit](http://www.rdkit.org/docs/Install.html)
* [boost](http://www.boost.org/)
* [joblib](https://pypi.python.org/pypi/joblib)
* [sklearn](https://github.com/scikit-learn/scikit-learn.git)
* [numpy](https://store.continuum.io/cshop/anaconda/)
* [six](https://pypi.python.org/pypi/six)
* [mdtraj](http://mdtraj.org/)
* [tensorflow](https://www.tensorflow.org/)

## Installation

Installation from source is the only currently supported format. ```deepchem``` currently supports both Python 2.7 and Python 3.5, but is not supported on any OS'es except 64 bit linux. Please make sure you follow the directions below precisely. While you may already have system versions of some of these packages, there is no guarantee that `deepchem` will work with alternate versions than those specified below.

### Full Anaconda distribution

1. Download the **64-bit** Python 2.7 or Python 3.5 versions of Anaconda for linux [here](https://www.continuum.io/downloads#_unix). 
   
   Follow the [installation instructions](http://docs.continuum.io/anaconda/install#linux-install)

2. `openbabel`
   ```bash
   conda install -c omnia openbabel=2.4.0
   ``` 

3. `rdkit`
   ```bash
   conda install -c rdkit rdkit
   ```

4. `joblib`
   ```bash
   conda install joblib 
   ```

5. `six`
   ```bash
   pip install six
   ```
      
6. `mdtraj`
   ```bash
   conda install -c omnia mdtraj
   ```

7. `tensorflow`: Installing `tensorflow` on older versions of Linux (which
    have glibc < 2.17) can be very challenging. For these older Linux versions,
    contact your local sysadmin to work out a custom installation. If your
    version of Linux is recent, then the following command will work:
    ```
    pip install tensorflow-gpu==0.12.1
    ```

8. `deepchem`: Clone the `deepchem` github repo:
   ```bash
   git clone https://github.com/deepchem/deepchem.git<commit_msg>Add openmm and pdbfixer installation instruction.<commit_after>﻿# DeepChem
[![Build Status](https://travis-ci.org/deepchem/deepchem.svg?branch=master)](https://travis-ci.org/deepchem/deepchem)
[![Coverage Status](https://coveralls.io/repos/github/deepchem/deepchem/badge.svg?branch=master)](https://coveralls.io/github/deepchem/deepchem?branch=master)

DeepChem aims to provide a high quality open-source toolchain that
democratizes the use of deep-learning in drug discovery, materials science, and quantum
chemistry. DeepChem is a package developed by the [Pande group](https://pande.stanford.edu/) at
Stanford and originally created by [<NAME>](http://rbharath.github.io/).

### Table of contents:

* [Requirements](#requirements)
* [Installation from Source](#installation)
* [FAQ](#faq)
* [Getting Started](#getting-started)
    * [Input Formats](#input-formats)
    * [Data Featurization](#data-featurization)
    * [Performances](#performances)
* [Contributing to DeepChem](#contributing-to-deepchem)
    * [Code Style Guidelines](#code-style-guidelines)
    * [Documentation Style Guidelines](#documentation-style-guidelines)
    * [Gitter](#gitter)
* [DeepChem Publications](#deepchem-publications)
* [Examples](/examples)
* [About Us](#about-us)
    
## Requirements
* [openbabel](http://openbabel.org/wiki/Main_Page)
* [pandas](http://pandas.pydata.org/)
* [rdkit](http://www.rdkit.org/docs/Install.html)
* [boost](http://www.boost.org/)
* [joblib](https://pypi.python.org/pypi/joblib)
* [sklearn](https://github.com/scikit-learn/scikit-learn.git)
* [numpy](https://store.continuum.io/cshop/anaconda/)
* [six](https://pypi.python.org/pypi/six)
* [mdtraj](http://mdtraj.org/)
* [tensorflow](https://www.tensorflow.org/)

## Installation

Installation from source is the only currently supported format. ```deepchem``` currently supports both Python 2.7 and Python 3.5, but is not supported on any OS'es except 64 bit linux. Please make sure you follow the directions below precisely. While you may already have system versions of some of these packages, there is no guarantee that `deepchem` will work with alternate versions than those specified below.

### Full Anaconda distribution

1. Download the **64-bit** Python 2.7 or Python 3.5 versions of Anaconda for linux [here](https://www.continuum.io/downloads#_unix). 
   
   Follow the [installation instructions](http://docs.continuum.io/anaconda/install#linux-install)

2. `openbabel`
   ```bash
   conda install -c omnia openbabel=2.4.0
   ``` 

3. `rdkit`
   ```bash
   conda install -c rdkit rdkit
   ```

4. `joblib`
   ```bash
   conda install joblib 
   ```

5. `six`
   ```bash
   pip install six
   ```
      
6. `mdtraj`
   ```bash
   conda install -c omnia mdtraj
   ```

7. `openmm`
   ```bash
   conda install -c omnia openmm
   ```

8. `pdbfixer`
   ```bash
   pip install git+https://github.com/pandegroup/pdbfixer.git
   ```

7. `tensorflow`: Installing `tensorflow` on older versions of Linux (which
    have glibc < 2.17) can be very challenging. For these older Linux versions,
    contact your local sysadmin to work out a custom installation. If your
    version of Linux is recent, then the following command will work:
    ```
    pip install tensorflow-gpu==0.12.1
    ```

8. `deepchem`: Clone the `deepchem` github repo:
   ```bash
   git clone https://github.com/deepchem/deepchem.git
{'fraction_non_alphanumeric': 0.14370709382151028, 'fraction_numerical': 0.009458428680396643, 'mean_word_length': 4.261637239165329, 'pattern_counts': {'":': 0, '<': 7, '<?xml version=': 0, '>': 5, 'https://': 25, 'lorem ipsum': 0, 'www.': 8, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 4, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'dir': 'git-commits-cleaned', 'id': '1576545', 'n_tokens_mistral': 2215, 'n_tokens_neox': 2080, 'n_words': 556}