The Python version currently installed is v3.8, running on Ubuntu 18.04.
While the Ubuntu repositories provided a vast array of Python modules, many of them are a few versions behind the latest one, and some modules commonly used in astronomy are missing. We maintain an up-to-date list of Pyhton 3 modules, which can be enabled by loading the Python 3.8 module: module load Python/3.8.
Here goes a (partial) list of the most important modules installed here in our
Linux network. A complete list of all installed modules can be obtained
by typing /usr/bin/python3.8 -m pip list --format=columns
If you need a module not yet installed, or wish to upgrade some
of those listed here, please just let us know.
Note on Python 2.7: We also maintain a Python 2.7
installation, in order to run PyRAF.
Only basic Python 2.7 modules are available, and no upgrades are
being done.
Package | Version | Description |
---|---|---|
APLpy | 2.1.0 | Python module aimed at producing publication-quality
plots of astronomical imaging data in FITS format. Usage: import aplpy |
astropy | 5.1 | Community effort to develop a single core package for
Astronomy in Python and foster interoperability between Python astronomy
packages. Usage: import astropy |
beautifulsoup4 | 4.11.1 | Library that makes it easy to scrape information from web pages. It sits atop
an HTML or XML parser, providing Pythonic idioms for iterating, searching, and modifying the parse tree. Usage: from bs4 import BeautifulSoup |
Cython | 0.29.30 | Language that makes writing C extensions
for the Python language as easy as Python itself.
Cython is the ideal language for wrapping external
C libraries, and for fast C modules that speed
up the execution of Python code. Usage: import cython |
emcee | 3.1.2 | emcee is an extensible, pure-Python implementation of
of Goodman & Weare's Affine Invariant Markov chain Monte Carlo (MCMC)
Ensemble sampler. Usage: import emcee |
Ginga | 3.3.0 | Toolkit designed for building viewers for scientific image data in Python, visualizing
2D pixel data in NumPy arrays. Usage: at the command prompt type ginga |
Glueviz | 1.2.0 | Python library to explore relationships within and among related datasets. Usage: at the command prompt type /usr/pkg/python/python3.6/bin/glue |
h5py | 3.7.0 | General-purpose
Python interface to the Hierarchical
Data Format library, version 5 (HDF5 is a versatile, mature
scientific software library designed for the fast, flexible storage of
enormous amounts of data). Usage: import h5py |
healpy | 1.15.2 | Package to manipulate healpix maps. Usage: import healpy |
IPython | 8.4.0 | Provide an interactive shell superior to Python's default.
IPython has many features for object introspection, system shell access,
and its own special command system for adding functionality when working
interactively. It tries to be a very efficient environment both for Python
code development and for exploration of problems using Python objects (in
situations like data analysis). Usage: at the command prompt type ipython |
Keras | 2.8.0 | High-level neural networks API. Usage: import keras |
lmfit | 1.0.2 | Library for least-squares minimization and data fitting
in Python. Usage: import lmfit |
matplotlib | 3.4.1 | Python 2D plotting library which produces publication quality
figures in a variety of hardcopy formats and
interactive environments across platforms. Usage: see the matplotlib User's Guide and other documentation in http://matplotlib.sourceforge.net/ |
MDP | 3.6 | The Modular toolkit for Data Processing is a collection of
supervised and unsupervised learning algorithms and other
data processing units that can be combined into data processing
sequences and more complex feed-forward network architectures. Usage: import mdp |
mpi4py | 3.1.3 | Package that provides bindings of the Message
Passing Interface (MPI) standard for the Python programming language,
allowing any Python program to exploit multiple processors. Usage: import mpi4py |
NetworkX | 2.5.1 | Python package for the creation, manipulation, and study
of the structure, dynamics, and functions of complex networks. Usage: import networkx |
nose | 1.3.7 | Alternate test discovery and running process
for unittest, one that is intended to mimic the behavior of py.test as
much as is reasonably possible without resorting to too much magic. Usage: import nose |
numdifftools | 0.9.40 | Suite of tools to solve automatic numerical
differentiation problems in one or more variables. Usage: import numdifftools |
numexpr | 2.8.1 | The numexpr package evaluates multiple-operator array expressions
many times faster than NumPy can. Usage: import numexpr |
NumPy | 1.22.4 | Numerical Python adds a fast and sophisticated array facility
to the Python language. Usage: import numpy |
pandas | 1.4.2 | Open source, BSD-licensed library providing high-performance,
easy-to-use data structures and data analysis tools for the
Python programming language. Usage: import pandas |
paramiko | 2.11.0 | module for python that implements the SSH2 protocol for secure
(encrypted and authenticated) connections to remote machines Usage: import paramiko |
pep8 | 1.7.1 | Tool to check your Python code against some of the style
conventions in PEP 8. Usage: type pep8 --help for usage help |
pexpect | 4.8.0 | Pexpect is a pure Python module for spawning child applications;
controlling them; and responding to expected patterns in their output.
Pexpect works like Don Libes' Expect. Pexpect allows your script to spawn
a child application and control it as if a human were typing commands. Usage: import pexpect |
photutils | 1.3.0 | Affiliated package of Astropy to provide tools for detecting and performing photometry
of astronomical sources. Usage: import photutils |
Pycairo | 1.16.2 | Set of Python bindings for the cairo graphics library. Usage: import cairo |
pyds9 | 1.8.1 | The pyds9 module uses a Python interface
to XPA to communicate with ds9. It supports communication with all of ds9’s
XPA access points. Usage: import ds9 |
PyEphem | 4.1.3 | PyEphem provides scientific-grade astronomical computations for
the Python programming language. Usage: import ephem |
PyFITS | 3.4 | PyFITS provides an interface to FITS formatted files under
the Python scripting language and PyRAF, the Python-based interface to
IRAF. It is useful both for interactive data analysis and for writing analysis
scripts in Python using FITS files as either input or output. Usage: import pyfits |
PyGObject | 3.26.1 | Python dynamic module that enables developers to use
the power of GObject, which is part of the GNOME platform. Usage: import gi |
pylint | 2.8.2 | Python tool that checks if a module satisfies a coding
standard. Usage: at the comman prompt type pylint --help (or pylint-gui to work with a GUI) |
PyMC | 3.11.5 | Package that implements the Metropolis-Hastings algorithm
as a python class Usage: import pymc3 |
PyNeb | 1.1.15 | The last in a lineage of tools dedicated to the analysis
of emission lines, which includes FIVEL and
nebular. Usage: import pyneb |
pyparsing | 2.4.7 | Alternative approach to creating and executing simple
grammars, vs. the traditional lex/yacc approach, or the use of regular
expressions. Usage: import pyparsing |
PyQt | 5.12.3 | Set of Python bindings for the Qt
application framework. Usage: import PyQt5 |
pyregion | 2.0 | Python module to parse ds9 region files. It also supports
ciao region files. Usage: import pyregion |
PyTables | 3.6.1 | Package for managing hierarchical datasets and designed to efficiently
and easily cope with extremely large amounts of data. Usage: import tables |
PyWavelets | 1.1.1 | Free Open Source wavelet transform software for Python
programming language. Usage: import pywt |
rdiff-backup | 1.2.8 | rdiff-backup backs up one directory to another,
possibly over a network. The target directory ends up a copy of the source
directory, but extra reverse diffs are stored in a special subdirectory
of that target directory, so you can still recover files lost some time
ago. Usage: at the command prompt type rdiff-backup |
ReportLab | 3.6.10 | Industry-strength PDF generating solution. Usage: please see the ReportLab User Guide |
RPy2 | 3.5.2 | Very simple, yet robust, Python interface to the R Programming
Language. It can manage all kinds of R objects and can execute arbitrary
R functions (including the graphic functions). All errors from the R language
are converted to Python exceptions. Usage: import rpy2 (be careful, import rpy2, nor rpy). |
scikit-image | 0.19.3 | Collection of algorithms for image processing. Usage: import skimage |
scikit-learn | 1.1.1 | Simple and efficient tools for data mining and data analysis. Usage: import sklearn |
SciPy | 1.8.1 | Set of Open Source scientific and numeric tools for Python, layered on top of NumPy. Usage: see the Scipy Documentation |
Sphinx | 5.0.2 | Tool that makes it easy to create intelligent
and beautiful documentation. Usage: from the unix prompt type sphinx-build, sphinx-autogen or sphinx-quickstart |
Spyder | 5.3.1 | Powerful interactive development environment for the Python
language with advanced editing, interactive testing, debugging and introspection
features. Usage: type spyder3 |
statsmodels | 0.12.2 | Module that allows users to explore data, estimate statistical models, and
perform statistical tests. Usage: import statsmodels |
SymPy | 1.10.1 | Python library for symbolic mathematics. Usage: at the command prompt type isympy |
tensorflow | 2.8.0 | Open-source software library for Machine Intelligence Usage: import tensorflow |
testtools | 2.5.0 | Extensions to the Python standard library
unit testing framework Usage: import testtools |
uncertainties | 3.1.6 | Free, cross-platform program that transparently handles
calculations with numbers with uncertainties Usage: import uncertainties |
Urwid | 2.0.1 | Console user interface library for Python. Usage: import urwid |
wxPython | 4.0.1 | GUI toolkit for the Python programming language that allows Python programmers to create programs with a robust, highly functional graphical user interface, simply and easily. Usage: import wx |