There are two basic options for installing
msprime: either through
pre-built binary packages using conda or
by compiling locally using pip. We recommend using
for most users, although
pip can be more convenient in certain cases.
Pre-built binary packages for
msprime are available through
conda, and built using conda-forge.
Packages for Python 2.7, 3.5 and 3.6 are available for Linux and OSX.
For Windows, only Python 3.5 and 3.6 are supported.
We strongly recommend using Python 3.
condausing miniconda. Make sure you follow the instructions to fully activate your
- Set up the conda-forge channel using
conda config --add channels conda-forge.
- Install msprime:
conda install msprime.
- Try it out:
There are several different ways to obtain
conda. Please see the
anaconda installation documentation
for full details.
In this example we create a
msprime into it on an OSX machine.
We assume that
conda has been installed and bash shell is being used (Windows users will need to modify the
$ conda create --name msprime-env Solving environment: done ## Package Plan ## environment location: /Users/jk/miniconda3/envs/msprime-env Proceed ([y]/n)? y Preparing transaction: done Verifying transaction: done Executing transaction: done # # To activate this environment, use # # $ conda activate msprime-env # # To deactivate an active environment, use # # $ conda deactivate $ source activate msprime-env (msprime-env) $ conda install -c conda-forge msprime Solving environment: done ## Package Plan ## environment location: /Users/jk/miniconda3/envs/msprime-env added / updated specs: - msprime The following NEW packages will be INSTALLED: ca-certificates: 2018.1.18-0 conda-forge certifi: 2018.1.18-py36_0 conda-forge gsl: 1.16-0 conda-forge hdf5: 1.10.1-2 conda-forge intel-openmp: 2018.0.0-h8158457_8 libgfortran: 3.0.1-h93005f0_2 mkl: 2018.0.1-hfbd8650_4 msprime: 0.5.0b2-py36_3 conda-forge ncurses: 5.9-10 conda-forge numpy: 1.14.1-py36h8a80b8c_1 openssl: 1.0.2n-0 conda-forge pip: 9.0.1-py36_1 conda-forge pyparsing: 2.2.0-py36_0 conda-forge python: 3.6.4-0 conda-forge readline: 7.0-0 conda-forge setuptools: 38.5.1-py36_0 conda-forge six: 1.11.0-py36_1 conda-forge sqlite: 3.20.1-2 conda-forge svgwrite: 1.1.12-py_0 conda-forge tk: 8.6.7-0 conda-forge wheel: 0.30.0-py36_2 conda-forge xz: 5.2.3-0 conda-forge zlib: 1.2.11-0 conda-forge Proceed ([y]/n)? y Preparing transaction: done Verifying transaction: done Executing transaction: done (msprime-env) $ python Python 3.6.4 | packaged by conda-forge | (default, Dec 23 2017, 16:54:01) [GCC 4.2.1 Compatible Apple LLVM 6.1.0 (clang-602.0.53)] on darwin Type "help", "copyright", "credits" or "license" for more information. >>> import msprime >>> tree = msprime.simulate(5).first() >>> print(tree.draw(format="unicode")) 8 ┏━┻━━┓ ┃ 7 ┃ ┏━┻━┓ ┃ ┃ 6 ┃ ┃ ┏┻┓ ┃ 5 ┃ ┃ ┃ ┏┻┓ ┃ ┃ 1 0 4 2 3
Please see the conda documentation for more details on managing packages and environments.
pip is more flexible than
conda as it
can support more versions of Python, and the locations of the
various dependencies can be specified.
To install and run
msprime on a fresh Ubuntu 15.10 installation, do the
$ sudo apt-get install pkg-config python-dev python-pip libgsl0-dev hdf5-tools libhdf5-serial-dev $ sudo pip install msprime $ mspms 2 1 -t 1 /usr/local/bin/mspms 2 1 -t 1 5338 8035 23205 // segsites: 3 positions: 0.014 0.045 0.573 100 011
If you do not wish to install
msprime to your system, you can try
it out in a virtualenv as
$ virtualenv msprime-env $ source msprime-env/bin/activate (msprime-env) $ pip install msprime (msprime-env) $ mspms
See below for installation instructions for Macs.
Msprime requires Python 2.7+ (Python 3 versions are fully supported from 3.1 onwards), the GNU Scientific Library, and HDF5 version 1.8 or later. These packages are available for all major platforms. For example, to install on Debian/Ubuntu use (as root):
$ apt-get install python-dev libgsl0-dev libhdf5-serial-dev pkg-config
For Redhat/Fedora use:
$ yum install gsl-devel hdf5-devel
On FreeBSD we can use
pkg to install the requirements:
$ pkg install gsl hdf5-18
To install the dependencies on OS X, we can use Homebrew:
$ brew update $ brew install gsl homebrew/science/hdf5
The simplest method of installation is to use PyPI and pip:
$ pip install msprime
This will work in most cases, once the Requirements have been satisfied. See below for platform specific build instructions when this fails.
If you do not have root access to your machine, you can install
msprime into your local Python installation as follows:
$ pip install msprime --user
To use the
mspms program you must ensure
~/.local/bin directory is in your
simply run it using:
msprime, simply run:
$ pip uninstall msprime
Platform specific installation¶
This section contains instructions to build on platforms that require build time flags for GSL and HDF5.
Install the prerequisitites, and build
msprime as follows:
$ pkg install gsl hdf5-18 $ CFLAGS=-I/usr/local/include LDFLAGS=-L/usr/local/lib pip install msprime
This assumes that root is logged in using a bash shell. For other shells,
different methods are need to set the
First, ensure that Homebrew is installed and up-to-date:
$ brew update
We need to ensure that the version of Python we used is installed via Homebrew (there can be issues with linking to HDF5 if we use the built-in version of Python or a version from Anaconda). Therefore, we install Python 3 using homebrew:
$ brew install python3 $ pip3 install --upgrade pip setuptools
The previous step can be skipped if you wish to use your own Python installation, and already have a working pip.
Now install the dependencies and msprime:
$ brew install gsl homebrew/science/hdf5 $ pip3 install msprime
Check if it works:
$ mspms 10 1 -T