You can install deepchem in a new conda environment using the conda commands in `scripts/install_deepchem_conda.sh.` Installing via this script will ensure that you are **installing from the source**.
The following script requires `conda>=4.4` because it uses the `conda activate` command. (Please see the detail from [here](https://github.com/conda/conda/blob/a4c4feae404b2b378e106bd25f62cc8be15c768f/CHANGELOG.md#440-2017-12-20))
First, please clone the deepchem repository from GitHub.
You install the nightly build version via pip. Nightly version is built by the HEAD of DeepChem.
```bash
bash scripts/install_deepchem_conda.sh deepchem
```
If you are using the Windows and the PowerShell:
```ps1
.\scripts\install_deepchem_conda.ps1 deepchem
pip install tensorflow==2.2
pip install--pre deepchem
```
Before activating deepchem environment, make sure conda has been initialized.
Check if there is a `(base)` in your command line. If not, use `conda init <YOUR_SHELL_NAME>` to activate it, then:
RDKit is a soft requirement package, but many useful methods like molnet depend on it. We recommend installing RDKit with deepchem if you use conda.
```bash
conda activate deepchem
python setup.py install
pytest -m"not slow" deepchem # optional
conda install-y-c rdkit rdkit
```
Check [this link](https://conda.io/projects/conda/en/latest/user-guide/install/index.html) for more information about the installation of conda environments.
### Install using a Docker
### Docker
If you want to install using a docker, you can pull two kinds of images.
If you want to install deepchem using a docker, you can pull two kinds of images.
- The latest image is built every time we commit to the master branch
- Dockerfile is put in `docker/master` directory
First, you pull the image you want to use.
You pull the image like this.
```bash
docker pull deepchemio/deepchem:2.3.0
```
Then, you create a container based on the image.
If you want to know docker usages with deepchem in more detail, please check [the document](https://deepchem.readthedocs.io/en/latest/installation.html#docker).
```bash
docker run --rm-it deepchemio/deepchem:2.3.0
```
If you want GPU support:
```bash
# If nvidia-docker is installed
nvidia-docker run --rm-it deepchemio/deepchem:2.3.0
docker run --runtime nvidia --rm-it deepchemio/deepchem:2.3.0
# If nvidia-container-toolkit is installed
docker run --gpus all --rm-it deepchemio/deepchem:2.3.0
```
You are now in a docker container which deepchem was installed. You can start playing with it in the command line.
```
(deepchem) root@xxxxxxxxxxxxx:~/mydir# python
Python 3.6.10 |Anaconda, Inc.| (default, May 8 2020, 02:54:21)
[GCC 7.3.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import deepchem as dc
```
### From source
If you want to check the tox21 benchmark:
If you try install all soft dependencies at once or contribute to deepchem, we recommend you should install deepchem from source.
(deepchem) root@xxxxxxxxxxxxx:~/mydir# python benchmark.py -d tox21 -m graphconv -s random
```
## FAQ and Troubleshooting
1. DeepChem currently supports Python 3.5 through 3.7, and is supported on 64 bit Linux and Mac OSX. Note that DeepChem is not currently maintained for older versions of Python or with other operating systems.
2. Question: I'm seeing some failures in my test suite having to do with MKL
`Intel MKL FATAL ERROR: Cannot load libmkl_avx.so or libmkl_def.so.`
Answer: This is a general issue with the newest version of `scikit-learn` enabling MKL by default. This doesn't play well with many linux systems. See [BVLC/caffe#3884](https://github.com/BVLC/caffe/issues/3884) for discussions. The following seems to fix the issue
@@ -32,14 +32,16 @@ If you're new, you can install DeepChem on a new machine with the following comm
.. code-block:: bash
pip install tensorflow
pip install deepchem-nightly
pip install tensorflow==2.2
pip install --pre deepchem
DeepChem is under very active development at present, so we recommend using our nightly build until we release a next major release. Note that to use DeepChem for chemistry applications, you will have to also install RDKit using conda.
