Installing Python for BAG¶

This section describes how to install Python for running BAG.

Installation Requirements¶

BAG is compatible with Python 3.5+ (Python 2.7+ is theoretically supported but untested), so you will need to have Python 3.5+ installed. For Linux/Unix systems, it is recommended to install a separate Python distribution from the system Python.

BAG requires multiple Python packages, some of which requires compiling C++/C/Fortran extensions. Therefore, it is strongly recommended to download Anaconda Python, which provides a Python distribution with most of the packages preinstalled. Otherwise, please refer to documentation for each required package for how to install/build from source.

Required Packages¶

In addition to the default packages that come with Anaconda (numpy, scipy, etc.), you’ll need the following additional packages:

subprocess32 (Python 2 only)

This package is a backport of Python 3.2’s subprocess module to Python 2. It is installable from pip.
sqlitedict

This is a dependency of OpenMDAO. It is installable from pip.
OpenMDAO

This is a flexible optimization framework in Python developed by NASA. It is installable from pip.
mpich2 (optional)

This is the Message Passing Interface (MPI) library. OpenMDAO and Pyoptsparse can optionally use this library for parallel computing. You can install this package with:
```
> conda install mpich2
```
mpi4py (optional)

This is the Python wrapper of mpich2. You can install this package with:
```
> conda install mpi4py
```
ipopt (optional)

Ipopt is a free software package for large-scale nonlinear optimization. This can be used to replace the default optimization solver that comes with scipy. You can install this package with:
```
> conda install --channel pkerichang ipopt
```
pyoptsparse (optional)

pyoptsparse is a python package that contains a collection of optmization solvers, including a Python wrapper around Ipopt. You can install this package with:
```
> conda install --channel pkerichang pyoptsparse
```