CVXPY supports Python 3 on Linux, macOS, and Windows. You can usepip or conda for installation. You may want to isolateyour installation in a virtualenv,or a conda environment.
pip¶
Miniconda is a free minimal installer for conda. It is a small, bootstrap version of Anaconda that includes only conda, Python, the packages they depend on, and a small number of other useful packages, including pip, zlib and a few others. Use the conda install command to install 720+ additional conda packages from the Anaconda repository.
(Windows only) Download the Visual Studio build tools for Python 3(download,install instructions).
(macOS only) Install the Xcode command line tools.
(optional) Create and activate a virtual environment
conda¶
conda is a system for package and environment management.
(Windows only) Download the Visual Studio build tools for Python 3.
Install from source¶
We strongly recommend using a fresh virtual environment (virtualenv or conda) when installing CVXPY from source.
CVXPY has the following dependencies:
To test the CVXPY installation, you additionally need Nose.
CVXPY automatically installs OSQP, ECOS, SCS. NumPy andSciPy will need to be installed manually,as will Swig . Once you’ve installed these dependencies, perform the following steps:
Install with CVXOPT and GLPK support¶
CVXPY supports the CVXOPT solver.Additionally, through CVXOPT, CVXPY supports the GLPK solver. On mostplatforms,CVXOPT comes with GLPK bundled. On such platforms, installing CVXOPT with
should suffice to get support for both CVXOPT and GLPK.
On other platforms, to install CVXPY and its dependencies with GLPK support, follow these instructions:
Install with GUROBI support¶
CVXPY supports the GUROBI solver.Install GUROBI version 7.5.2 or greater such that you can
importgurobipy in Python.See the GUROBI website for installation instructions.
Install with MOSEK support¶
CVXPY supports the MOSEK solver.Simply install MOSEK such that you can
importmosek in Python.See the MOSEK website for installation instructions.
Install with XPRESS support¶
CVXPY supports the FICO Xpress solver.Simply install XPRESS such that you can
importxpress in Python.See the Xpress Python documentation pages for installation instructions.
Install with Cbc (Clp, Cgl) support¶
CVXPY supports the Cbc solver (which includes Clp and Cgl) with the help of cylp.Simply install cylp (you will need the Cbc sources which includes Cgl) such you can import this library in Python.See the cylp documentation for installation instructions.
Install with CPLEX support¶
CVXPY supports the CPLEX solver.Simply install CPLEX such that you can
importcplex in Python.See the CPLEX website for installation instructions.
Install with SDPT3 support¶
The sdpt3glue package allows you to model problems with CVXPY and solve them with SDPT3.
Install with NAG support¶
CVXPY supports the NAG solver.Simply install NAG such that you can
importnaginterfaces in Python.See the NAG website for installation instructions.
Install with SCIP support¶
CVXPY supports the SCIP solver.Simply install SCIP such that you can
frompyscipopt.scipimportModel in Python.See the PySCIPOpt github for installation instructions.
CVXPY’s SCIP interface does not reliably recover dual variables for constraints. If you require dual variables for a continuous problem, you will need to use another solver. We welcome additional contributions to the SCIP interface, to recover dual variables for constraints in continuous problems.
PyRosetta is available for Mac (64-bit OS X v10.5+) and Linux (64-bit Red Hat and 64-bit Ubuntu) platforms in continuous release versions (usually we have a fresh builds available daily). Running on Windows-10 (thought Unix layer) is are also supported. Additionally, both Python 2.7 and 3.5 is supported.
A PyRosetta license is required in order to download and use PyRosetta. Licensing is free for academic and non-profit institutions and is available to commercial users for a fee. Academic and commercial licensing of PyRosetta is handled the license similar to standard Rosetta license through Rosetta Commons. Please click [HERE] for more information.
Please use our forums for technical support and assistance or if you have any questions or problems with installing PyRosetta.
PyRosetta Build Information:
Release
Speed optimized build, use it for production runs.
Build optimized to reduce memory footprint. Use this build with low-memory systems.
Debug
Binaries compiled in debug mode with additional asserts enabled and with debug-info compiled-in. Use this build for debugging.
Python-x.x versions
On CentOS and on Ubuntu Linux we provide binaries for both Python-2.7 and Python-3.5.
Latest PyRosetta VersionsMacMac OS X 10.7 'Lion/MountainLion' (64-bit)
[Python-2.7.Release] [Python-2.7.MinSizeRel] [Python-2.7.Debug]
[Python-3.6.Release] [Python-3.6.MinSizeRel] [Python-3.6.Debug] [Python-3.6.Release.wheel]
[Python-3.7.Release] [Python-3.7.MinSizeRel] [Python-3.7.Debug] [Python-3.7.Release.wheel]
[Python-3.8.Release] [Python-3.8.MinSizeRel] [Python-3.8.Debug] [Python-3.8.Release.wheel]
[Python-2.7.Release] [Python-2.7.MinSizeRel] [Python-2.7.Debug]
[Python-3.6.Release] [Python-3.6.MinSizeRel] [Python-3.6.Debug] [Python-3.6.Release.wheel]
Update Python 3 Conda
[Python-3.7.Release] [Python-3.7.MinSizeRel] [Python-3.7.Debug] [Python-3.7.Release.wheel]
[Python-3.8.Release] [Python-3.8.MinSizeRel] [Python-3.8.Debug] [Python-3.8.Release.wheel]
[Python-2.7.Release] [Python-2.7.MinSizeRel] [Python-2.7.Debug]
[Python-3.6.Release] [Python-3.6.MinSizeRel] [Python-3.6.Debug] [Python-3.6.Release.wheel]
[Python-3.7.Release] [Python-3.7.MinSizeRel] [Python-3.7.Debug] [Python-3.7.Release.wheel]
[Python-3.8.Release] [Python-3.8.MinSizeRel] [Python-3.8.Debug] [Python-3.8.Release.wheel]
Windows 10PyRosetta-4 Linux build work natively thought Win10 Linux layer. For installation details please see: Instructions for Installing PyRosetta on Windows 10PyMOL-RosettaServer scripts[PyMOL-RosettaServer.python2][PyMOL-RosettaServer.python3]RosettaCommons Conda ChannelThe RosettaCommons conda channel provides conda packages for each weekly releases. Currently PyRosetta.release packages for Python 3.6 and 3.7 provided for both Mac and Linux platforms. Note that when possible we intend to keep all released packagesavailable(i.e old releases packages will not be deleted), so it should be safe to publish your results and use explicit PyRosetta version to ensure reproducibility. To use RosettaCommons channel edit your local ~/.condarc and add https://conda.graylab.jhu.eduinto your channels list. Then run conda install pyrosetta (or conda install pyrosetta=<version> if you want to install specific version of PyRosetta).Example ~/.condarc:
channels: - https://USERNAME:[email protected]
PyRosetta Binaries in Git repositories use this if you want to frequently update PyRosetta version. (To upgrade simply run 'git pull' on checked out repository. Please note that Git history automatically truncated to store only ~2 last revisions to save disk space.)
To checkout repository with PyRosetta binaries use following command line (replacing 'login' with your user name):
% git clone https://login@git-repository-address
So for example Mac command line will be:
% git clone https://login@graylab.jhu.edu/download/PyRosetta4/git/release/PyRosetta4.Release.python27.mac.release.git
In order to update these repositories, you must use:
% git fetch && git reset --hard origin/master && git clean -fd
For a full list of available git repositories please see: [PyRosetta-4, Git repositories] (you will need to enter your user name and password to access this page)
Install Python 3 CondaOther PyRosetta builds
Our release archive: [full list of available releases]
Binaries for older PyRosetta releases could be downloaded at: [PyRosetta3 Download]
System RequirementsBuild Support Information
PyRosetta is currently only supported on the platforms listed above. Users have sometimes been successful at installing PyRosetta on other platforms; please see the forums for more information, for example, the topic: Building PyRosetta for Linux Mint.
GNU/LinuxPython 2.7 or 3.5 for 64-bit LinuxMac OS Xv10.6+ and any Intel-based chipset MacWindowsWindows-10 or laterGNU/Linux and Mac OS X
PyRosetta is distributed as a standard Python 'distutils' package, which is compatible with most Python package management systems. (Though due to licensing issues, it is not available through
pip .) There are two major ways to install PyRosetta: either into your standard system Python, or using a Python environment manager. Installation into the system Python is easier and makes PyRosetta available at all times, though it makes upgrading PyRosetta more difficult and may require administrator access. Using an environment manager is more flexible and permits installation as a normal (non-admin) user, but requires more effort in understanding the system.
In addition to standard 'setup.py' package we provide Python wheel packages (use '.wheel' download links). Wheel package significantly reduce install time but requires `pip` to be present on your system. To install PyRosetta from wheel use `pip install pyrosetta-<version>.whl` command.
Conda Python 3.7
Installation with an environment manager:
Windows:Conda Python 3 Environment
Comments are closed.
|
AuthorWrite something about yourself. No need to be fancy, just an overview. Archives
December 2020
Categories |