What is molfeat ?¶
Molfeat is a hub of molecular featurizers. It supports a wide variety of out-of-the-box molecular featurizers and can be easily extended to include your own custom featurizers.
- 🚀 Fast, with a simple and efficient API.
- 🔄 Unify pre-trained molecular embeddings and hand-crafted featurizers in a single package.
- âž• Easily add your own featurizers through plugins.
- 📈 Benefit from increased performance through a trouble-free caching system.
Visit our website at https://molfeat.datamol.io.
Installation¶
Installing Molfeat¶
Use mamba:
mamba install -c conda-forge molfeat
Tips: You can replace mamba
by conda
.
Note: We highly recommend using a Conda Python distribution to install Molfeat. The package is also pip installable if you need it: pip install molfeat
.
Installing Plugins¶
The functionality of molfeat can be extended through plugins. The use of a plugin system ensures that the core package remains easy to install and as light as possible, while making it easy to extend its functionality with plug-and-play components. Additionally, it ensures that plugins can be developed independently from the core package, removing the bottleneck of a central party that reviews and approves new plugins. Consult the molfeat documentation for more details on how to create your own plugins.
However, this does imply that the installation of a plugin is plugin-dependent: please consult the relevant documentation to learn more.
Optional dependencies¶
Not all featurizers in Molfeat core package are supported by default. Some featurizers require additional dependencies. If you try to use a featurizer that requires additional dependencies, Molfeat will raise an error and tell you which dependencies are missing and how to install them.
- To install
dgl
: runmamba install -c dglteam "dgl<=2.0"
# there is some issue with "dgl>2.0.0" related to graphbolt - To install
dgllife
: runmamba install -c conda-forge dgllife
- To install
fcd_torch
: runmamba install -c conda-forge fcd_torch
- To install
pyg
: runmamba install -c conda-forge pytorch_geometric
- To install
graphormer-pretrained
: runmamba install -c conda-forge graphormer-pretrained
- To install
map4
: see https://github.com/reymond-group/map4 - To install
bio-embeddings
: runmamba install -c conda-forge 'bio-embeddings >=0.2.2'
If you install Molfeat using pip, there are optional dependencies that can be installed with the main package. For example, pip install "molfeat[all]"
allows installing all the compatible optional dependencies for small molecule featurization. There are other options such as molfeat[dgl]
, molfeat[graphormer]
, molfeat[transformer]
, molfeat[viz]
, and molfeat[fcd]
.