πΒ A ranked list of awesome projects. Updated weekly.
This curated list contains 38 awesome open-source projects with a total of 3.6K stars grouped into 0 categories. All projects are ranked by a project-quality score, which is calculated based on various metrics automatically collected from GitHub and different package managers. If you like to add or update projects, feel free to open an issue, submit a pull request, or directly edit the projects.yaml. Contributions are very welcome!
π§ββοΈ Discover other best-of lists or create your own.
- Others 38 projects
- π₯π₯π₯Β Combined project-quality score
- βοΈΒ Star count from GitHub
- π£Β New project (less than 6 months old)
- π€Β Inactive project (6 months no activity)
- πΒ Dead project (999999999 months no activity)
- ππΒ Project is trending up or down
- βΒ Project was recently added
- π¨βπ»Β Contributors count from GitHub
- πΒ Fork count from GitHub
- πΒ Issue count from GitHub
- β±οΈΒ Last update timestamp on package manager
- π₯Β Download count from package manager
- π¦Β Number of dependent projects
DeePMD-kit (π₯29 Β· β 1.5K Β· π) - A deep learning package for many-body potential energy representation and molecular dynamics. LGPL-3.0
-
GitHub (π¨βπ» 73 Β· π 500 Β· π₯ 44K Β· π¦ 22 Β· π 840 - 9% open Β· β±οΈ 23.11.2024):
git clone https://github.com/deepmodeling/deepmd-kit
-
PyPi (π₯ 7.7K / month):
pip install deepmd-kit
-
Conda (π₯ 1.2M Β· β±οΈ 23.11.2024):
conda install -c conda-forge deepmd-kit
-
npm (π₯ 3 / month):
npm install deepmd-kit
-
Docker Hub (π₯ 3K Β· β 1 Β· β±οΈ 25.11.2024):
docker pull deepmodeling/deepmd-kit
ABACUS (π₯26 Β· β 170) - An electronic structure package based on either plane wave basis or numerical atomic orbitals. LGPL-3.0
dpdata (π₯25 Β· β 200) - A Python package for manipulating atomistic data of software in computational science. LGPL-3.0
-
GitHub (π¨βπ» 61 Β· π 130 Β· π¦ 130 Β· π 100 - 20% open Β· β±οΈ 20.09.2024):
git clone https://github.com/deepmodeling/dpdata
-
PyPi (π₯ 61K / month):
pip install dpdata
-
Conda (π₯ 82K Β· β±οΈ 21.09.2024):
conda install -c conda-forge dpdata
-
Docker Hub (π₯ 640 Β· β±οΈ 02.06.2023):
docker pull dptechnology/dpdata
DP-GEN (π₯24 Β· β 310 Β· π) - The deep potential generator to generate a deep-learning based model of interatomic potential energy and force field. LGPL-3.0
dpdispatcher (π₯23 Β· β 45 Β· π) - generate HPC scheduler systems jobs input scripts and submit these scripts to HPC systems and poke until they finish. LGPL-3.0
-
GitHub (π¨βπ» 47 Β· π 54 Β· π¦ 53 Β· π 80 - 21% open Β· β±οΈ 27.11.2024):
git clone https://github.com/deepmodeling/dpdispatcher
-
PyPi (π₯ 4.9K / month):
pip install dpdispatcher
-
Conda (π₯ 17K Β· β±οΈ 31.08.2024):
conda install -c conda-forge dpdispatcher
-
Docker Hub (π₯ 110K Β· β±οΈ 30.08.2024):
docker pull dptechnology/dpdispatcher
reacnetgenerator (π₯21 Β· β 67) - an automatic reaction network generator for reactive molecular dynamics simulation. LGPL-3.0
dflow (π₯19 Β· β 66) - Dflow is a Python framework for constructing scientific computing workflows (e.g. concurrent learning workflows).. LGPL-3.0
-
GitHub (π¨βπ» 22 Β· π 26 Β· π 36 - 38% open Β· β±οΈ 31.10.2024):
git clone https://github.com/deepmodeling/dflow
-
PyPi:
pip install dflow
-
conda install -c conda-forge dflow
-
Docker Hub (π₯ 9.4K Β· β±οΈ 31.10.2024):
docker pull dptechnology/dflow
DPGEN2 (π₯17 Β· β 33) - 2nd generation of the Deep Potential GENerator. LGPL-3.0
-
GitHub (π¨βπ» 14 Β· π 26 Β· π¦ 5 Β· π 34 - 32% open Β· β±οΈ 26.11.2024):
git clone https://github.com/deepmodeling/dpgen2
-
PyPi (π₯ 390 / month):
pip install dpgen2
-
Docker Hub (π₯ 3.6K Β· β±οΈ 26.11.2024):
docker pull dptechnology/dpgen2
DeepFlame (π₯15 Β· β 140 Β· π) - A deep learning empowered open-source platform for reacting flow simulations. GPL-3.0
-
GitHub (π¨βπ» 24 Β· π 62 Β· π 49 - 40% open Β· β±οΈ 23.11.2024):
git clone https://github.com/deepmodeling/deepflame-dev
DeePTB (π₯15 Β· β 55) - DeePTB: A deep learning package for tight-binding approach with ab initio accuracy. LGPL-3.0
DMFF (π₯14 Β· β 160 Β· π€) - DMFF (Differentiable Molecular Force Field) is a Jax-based python package that provides a full differentiable.. LGPL-3.0
deepmodeling_sphinx (π₯13 Β· β 3) - Sphinx extension for DeepModeling projects. LGPL-3.0
GPUMD (π₯11 Β· β 3 Β· π£) - Graphics Processing Units Molecular Dynamics. GPL-3.0
-
GitHub (π¨βπ» 39 Β· β±οΈ 26.11.2024):
git clone https://github.com/deepmodeling/GPUMD
DeePKS-kit (π₯10 Β· β 100 Β· π€) - a package for developing machine learning-based chemically accurate energy and density functional models. LGPL-3.0
-
GitHub (π¨βπ» 7 Β· π 35 Β· π 22 - 36% open Β· β±οΈ 13.04.2024):
git clone https://github.com/deepmodeling/deepks-kit
dpti (π₯10 Β· β 22) - A Python Package to Automate Thermodynamic Integration Calculations for Free Energy. LGPL-3.0
Blog (π₯9 Β· β 1 Β· π) - DeepModeling Blog. LGPL-3.0
-
GitHub (π¨βπ» 9 Β· π 8 Β· β±οΈ 28.11.2024):
git clone https://github.com/deepmodeling/blog
community (π₯8 Β· β 84) - DeepModeling community content. Unlicensed
-
GitHub (π¨βπ» 17 Β· π 21 Β· β±οΈ 26.09.2024):
git clone https://github.com/deepmodeling/community
AIS-Square (π₯8 Β· β 12) - LGPL-3.0
-
GitHub (π¨βπ» 8 Β· π 8 Β· π 6 - 83% open Β· β±οΈ 19.11.2024):
git clone https://github.com/deepmodeling/AIS-Square
fealpy (π₯8 Β· β 4 Β· π€) - Finite Element Analysis Library in Python. Unlicensed
Uni-Fold (π₯7 Β· β 91 Β· π€) - Apache-2
-
GitHub (π¨βπ» 3 Β· π 18 Β· β±οΈ 18.08.2022):
git clone https://github.com/deepmodeling/Uni-Fold
-
Docker Hub (π₯ 780 Β· β±οΈ 08.01.2024):
docker pull dptechnology/unifold
tbplas (π₯6 Β· β 8 Β· π€) - Repository of TBPLaS (tight-binding package for large-scale simulation). Unlicensed
-
GitHub (π¨βπ» 10 Β· π 4 Β· β±οΈ 17.01.2024):
git clone https://github.com/deepmodeling/tbplas
DeePDih (π₯6 Β· β 5 Β· π€) - Deep Potential driven molecular dihedral scan toolkit. MIT
-
GitHub (π 3 Β· β±οΈ 19.04.2024):
git clone https://github.com/deepmodeling/DeePDih
docs (π₯6 Β· β 3) - The home page of DeepModeling documentation. LGPL-3.0
-
GitHub (π¨βπ» 8 Β· π 7 Β· β±οΈ 28.10.2024):
git clone https://github.com/deepmodeling/docs
AI4Science101 (π₯5 Β· β 84 Β· π€) - AI for Science. Unlicensed
-
GitHub (π¨βπ» 5 Β· π 13 Β· β±οΈ 04.09.2022):
git clone https://github.com/deepmodeling/AI4Science101
tutorials (π₯5 Β· β 14) - Tutorials for DeepModeling projects. Unlicensed
-
GitHub (π¨βπ» 10 Β· π 23 Β· π 3 - 33% open Β· β±οΈ 21.08.2024):
git clone https://github.com/deepmodeling/tutorials
DeepH-pack (π₯4 Β· β 12 Β· π€) - Deep neural networks for density functional theory Hamiltonian. LGPL-3.0
-
GitHub (π¨βπ» 6 Β· π 6 Β· π 6 - 66% open Β· β±οΈ 28.12.2023):
git clone https://github.com/deepmodeling/DeepH-pack
tutorials-cn (π₯4 Β· β 3 Β· π€) - LGPL-2.1
-
GitHub (π¨βπ» 4 Β· π 7 Β· β±οΈ 29.12.2022):
git clone https://github.com/deepmodeling/tutorials-cn
ADMP (π₯2 Β· β 2 Β· π€) - Automatic Differentiation Multipole Moment Molecular Forcefield. Unlicensed
-
GitHub (π¨βπ» 7 Β· π 2 Β· β±οΈ 15.02.2022):
git clone https://github.com/deepmodeling/ADMP
LibRI (π₯1 Β· β 6 Β· π€) - GPL-3.0
-
GitHub (π¨βπ» 2 Β· π 1 Β· π 3 - 66% open Β· β±οΈ 10.04.2023):
git clone https://github.com/deepmodeling/LibRI
openfinite ( β 1 Β· π€) - LGPL-3.0
-
GitHub (π¨βπ» 2 Β· π 1 Β· β±οΈ 06.10.2021):
git clone https://github.com/deepmodeling/openfinite
dflow-op-cutter (π€) - Unlicensed
-
GitHub (π¨βπ» 2 Β· π 1 Β· β±οΈ 06.07.2022):
git clone https://github.com/deepmodeling/dflow-op-cutter
- Best-of lists: Discover other best-of lists with awesome open-source projects on all kinds of topics.
Contributions are encouraged and always welcome! If you like to add or update projects, choose one of the following ways:
- Open an issue by selecting one of the provided categories from the issue page and fill in the requested information.
- Modify the projects.yaml with your additions or changes, and submit a pull request. This can also be done directly via the Github UI.
If you like to contribute to or share suggestions regarding the project metadata collection or markdown generation, please refer to the best-of-generator repository. If you like to create your own best-of list, we recommend to follow this guide.
For more information on how to add or update projects, please read the contribution guidelines. By participating in this project, you agree to abide by its Code of Conduct.