本系列分為兩篇：

1、【轉】windows和linux中搭建python集成開發環境IDE

2、【轉】linux和windows下安裝python集成開發環境及其python包

3、windows和linux中搭建python集成開發環境IDE——如何設置多個python環境

Install Python packages on Ubuntu 14.04

from?chris' sandbox

In this post I will document my setup of Python 2.7.6 in Ubuntu 14.04. Of course, the base Python is installed by default, both Python 2.7.6 and Python 3.4. Try the following in the terminal:

$ python --version Python 2.7.6 $ python2 --version Python 2.7.6 $ python3 --version Python 3.4.0

As you can see, using?python?points to Python 2.7.6 by default. However,?python2?and?python3?can be used to access the desired version. I will focus on installing packages for Python 2.7.6 here.

Strategy

In the past I have installed Python packages:

Using the Ubuntu repository:

$ sudo apt-get install packagename

Or, from a git/svn repository:

$ sudo python setup.py install

Approach 1?has many advantages for Python users that don’t need to have the latest versions of every package. In particular, all of the package dependencies including other Python packages, linear algebra libraries, etc. are also installed automatically. As a result, if you are new to Ubuntu and Python, strategy 1 is the way to go.

I will take a different tact, using?pip?to install, upgrade, and remove packages. Also, I will install all Python packages as a?user, that is, no use of?sudo. This makes it easy to use the same install procedure on a machine where I don’t have sudo privileges–say an Ubuntu cluster. However, I will need?sudo?to install non-Python libraries, Fortran compilers, etc. that the Python packages employ. On a cluster, the SysAdmin would have to to do this part for me and other users.

–start edit: 2015, June 1st –

Recently use of pip on Ubuntu 14.04 has started to issue a warning that ends with?InsecurePlatformWarning. After some searching around, I’ve found that this is related to SSL and the urllib3 in Python 2.7.6, the version on Ubuntu 14.04–?see here if you want the details. As suggested in the discussion linked above, this can be fixed with the following installs (I’ll use the –user switch, as in the examples below)

$ pip install --user pyopenssl ndg-httpsclient pyasn1

With that we’re secured and the warnings go away. If you are just starting out, try installing pip, as below, and return to this install if use of pip gives you warnings.

–end edit: 2015, June 1st –

pip

Of course, the starting point is to get?pip?installed. Official instructions are also available for?installing pip.?pip?depends on setuptools, but we can install both using the?get-pip.py?script, as described at the install link. To be concrete, I did the following:

$ cd ~/Downloads $ curl -O https://bootstrap.pypa.io/get-pip.py $ python get-pip.py --user

If you don’t have?curl?installed, this can be remedied using:

$ sudo apt-get install curl

Because we have chosen local installation, the path?~/.local/bin?has to be added to our path. To do that, add the following to the end of your?~/.bashrc?file:

# include .local/bin for local python scripts export PATH=~/.local/bin:$PATH

Then, source?~/.bashrc:

$ source ~/.bashrc

Try the following to see if you get similar results and to make sure the basic setup is working:

$ which pip /home/cstrelioff/.local/bin/pip $ pip --version pip 1.5.6 from /home/cstrelioff/.local/lib/python2.7/site-packages (python 2.7)

Of course,?your username?should be in the path, but the output should look something like the above.

virtualenv

Another major tool for Python 2.7 project management is?virtualenv. This package allows the user to create many?virtual?Python environments, with different packages installed, and to?activate?anddeactive?these environments whenever the user desires. This is extremely useful for developers who want to create a minimal environment for their application.

The?virtualenv?installation is simple with?pip?(again, I’m doing a user install with no sudo):

$ pip install --user virtualenv

To test it out, see if you get something like the following:

$ virtualenv --version 1.11.6 $ pip show virtualenv --- Name: virtualenv Version: 1.11.6 Location: /home/cstrelioff/.local/lib/python2.7/site-packages Requires:

Now that?virtualenv?is installed, there will be two paths forward for the rest of the Python installs:

Keep installing as a user –?I’ll use this approach?for the reasons discussed above.

If you have admin permissions you can install all packages globally using a command like:

$ sudo pip install packagename

Create a virtual environment and install everything there to have a completely isolated Python environment – see?virtualenv and virtualenvwrapper on Ubuntu 14.04?for an example of how to take this approach.

Ubuntu dependencies

A variety of Ubuntu-specific packages are needed by Python packages. These are libraries, compilers, fonts, etc. I’ll detail these here along with install commands. Depending on what you want to install you might not need all of these.

• General development/build:

$ sudo apt-get install build-essential python-dev

• Compilers/code integration:

$ sudo apt-get install gfortran $ sudo apt-get install swig

• Numerical/algebra packages:

$ sudo apt-get install libatlas-dev $ sudo apt-get install liblapack-dev

• Fonts (for matplotlib)

$ sudo apt-get install libfreetype6 libfreetype6-dev

• More fonts (for matplotlib on Ubuntu Server 14.04– see comment at end of post) – added 2015/03/06

$ sudo apt-get install libxft-dev

• Graphviz for pygraphviz, networkx, etc.

$ sudo apt-get install graphviz libgraphviz-dev

• IPython require pandoc for document conversions, printing, etc.

$ sudo apt-get install pandoc

• Tinkerer dependencies

$ sudo apt-get install libxml2-dev libxslt-dev zlib1g-dev

That’s it, now we start installing the Python packages.

numpy

numpy?is one of the fundamental numerical packages in Python. To install using?pip?type:

$ pip install --user numpy

This will result in a fair amount of compiling followed by a note that the package was successfully installed. If not, make a note of the error. Often this results from not having libraries and/or compilers installed (see above).

Information about the installation location and the version can be obtained with the following:

$ pip show numpy --- Name: numpy Version: 1.8.1 Location: /home/cstrelioff/.local/lib/python2.7/site-packages Requires:

You should also be able to start python at the terminal and?importnumpy?without complaint:

Python 2.7.6 (default, Mar 22 2014, 22:59:56) [GCC 4.8.2] on linux2 Type "help", "copyright", "credits" or "license" for more information. >>> import numpy as np >>> print np.__version__ 1.8.1 >>> exit()

scipy

scipy?has many useful mathematical utilities, complementing?numpy. Installation is accomplished with:

$ pip install --user scipy

Again, expect lots of compiling! As with?numpy, try:

$ pip show scipy --- Name: scipy Version: 0.14.0 Location: /home/cstrelioff/.local/lib/python2.7/site-packages Requires:

and, loading python:

Python 2.7.6 (default, Mar 22 2014, 22:59:56) [GCC 4.8.2] on linux2 Type "help", "copyright", "credits" or "license" for more information. >>> import scipy >>> print scipy.__version__ 0.14.0 >>> exit()

matplotlib

matplotlib?is one of the main plotting packages for Python and many other packages use the utilities. Install with:

$ pip install --user matplotlib

matplotlib復雜一點，可能直接上面的操作會失敗：需要先安裝其依賴的包libpng和freetype，根據提示缺啥就補安裝啥即可：

安裝libpng:sudo apt-get install libpng-dev

安裝freetype:

cd ~/Downloads

wget http://download.savannah.gnu.org/releases/freetype/freetype-2.4.10.tar.gz

tar zxvf freetype-2.4.10.tar.gz

cd freetype-2.4.10/

./congfigure

make

sudo make install ?

If you look carefully, the completion of the installation will say:

Successfully installed matplotlib python-dateutil tornado pyparsing nose backports.ssl-match-hostname Cleaning up...

So,?matplotlib?installs a variety of Python-dependencies. As usual, try:

$ pip show matplotlib --- Name: matplotlib Version: 1.3.1 Location: /home/cstrelioff/.local/lib/python2.7/site-packages Requires: numpy, python-dateutil, tornado, pyparsing, nose

Finally try a simple plot:

Python 2.7.6 (default, Mar 22 2014, 22:59:56) [GCC 4.8.2] on linux2 Type "help", "copyright", "credits" or "license" for more information. >>> import matplotlib.pyplot as plt >>> plt.plot([1,2,3,4]) [<matplotlib.lines.Line2D object at 0x7f13a8571890>] >>> plt.ylabel('some numbers') <matplotlib.text.Text object at 0x7f13a85c47d0> >>> plt.show() >>> exit()

A plot should open in a new window when?plot.show()?is executed.

sympy

sympy?is a computer algebra system for Python. Install with?pipusing:

$ pip install --user sympy

Again, installation information from?pip?is obtained with:

$ pip show sympy --- Name: sympy Version: 0.7.5 Location: /home/cstrelioff/.local/lib/python2.7/site-packages Requires:

Finally, following the?sympy tutorial, start Python and try:

Python 2.7.6 (default, Mar 22 2014, 22:59:56) [GCC 4.8.2] on linux2 Type "help", "copyright", "credits" or "license" for more information. >>> from sympy import symbols >>> x, y = symbols('x y') >>> expr = x + 2*y >>> expr x + 2*y >>> expr + 1 x + 2*y + 1 >>> expr - x 2*y >>> exit()

Cool!

IPython

Next, we install?IPython?(including notebooks), which has become a major tool for sharing python projects in an interactive format. To install we use:

$ pip install --user ipython[notebook]

At the end, we get the message:

Successfully installed ipython jinja2 pyzmq markupsafe Cleaning up...

showing that jinja2, pyzmq and markupsafe have also been installed. Get install information from?pip:

$ pip show ipython --- Name: ipython Version: 2.1.0 Location: /home/cstrelioff/.local/lib/python2.7/site-packages Requires:

Now, try:

$ ipython

which launches the?IPython?terminal. Notice the?IPython?version is provided and the prompt looks different from the normal?>>>Python prompt (see the?IPython?documentation for more information):

Python 2.7.6 (default, Mar 22 2014, 22:59:56) Type "copyright", "credits" or "license" for more information.IPython 2.1.0 -- An enhanced Interactive Python. ? -> Introduction and overview of IPython's features. %quickref -> Quick reference. help -> Python's own help system. object? -> Details about 'object', use 'object??' for extra details.In [1]: import numpy as npIn [2]: print np.__version__ 1.8.1In [3]: exit()

Finally,?IPython?notebook can be launched with the command:

$ ipython notebook

This launches a web browser and you should see the?IPythonnotebook interface. You can create a new notebook and work away. To shutdown the server, back at the terminal where you launched the notebook, type?cntrl-C?and then?y?when prompted:

Shutdown this notebook server (y/[n])? y 2014-06-04 16:29:04.033 [NotebookApp] CRITICAL | Shutdown confirmed 2014-06-04 16:29:04.033 [NotebookApp] Shutting down kernels

That’s it, you’re now an?IPython?notebook user!

pygraphviz

pygraphviz?is a Python interface to the?graphviz?visualization code that can be used by itself but is also employed by?networkx?and other packages. Be sure that?graphviz?and its developer libraries are installed (see Ubuntu Dependencies above) and install?pygraphvizusing:

$ pip install --user pygraphviz

Get install information from?pip:

$ pip show pygraphviz --- Name: pygraphviz Version: 1.2 Location: /home/cstrelioff/.local/lib/python2.7/site-packages Requires:

Also, try:

Python 2.7.6 (default, Mar 22 2014, 22:59:56) [GCC 4.8.2] on linux2 Type "help", "copyright", "credits" or "license" for more information. >>> import pygraphviz >>> print pygraphviz.__version__ 1.2 >>> exit()

networkx

networkx?is a Python package for building, analyzing, and visualizing graphs/networks. There are a variety of dependencies, all of which we have installed above. So, install with:

$ pip install --user networkx

Get install information from?pip:

$ pip show networkx --- Name: networkx Version: 1.8.1 Location: /home/cstrelioff/.local/lib/python2.7/site-packages Requires:

Try a simple example:

Python 2.7.6 (default, Mar 22 2014, 22:59:56) [GCC 4.8.2] on linux2 Type "help", "copyright", "credits" or "license" for more information. >>> import networkx as nx >>> G = nx.Graph() >>> G.add_edge(1,2) >>> G.add_edge(2,3) >>> import matplotlib.pyplot as plt >>> nx.draw(G) >>> plt.show() >>> exit()

With?matplotlib?and?pygraphviz?installed (see above), this code should create a very simple graph and show it in a new window whenplt.show()?is executed.

pandas

pandas?is a Python packaged focused on data – reading, writing, manipulating, etc. There are a variety of?pandas dependencies: required, recommended and optional. We’ll focus on the first two categories.

The required dependencies are?numpy?(installed above),?python-dateutil?(installed above with?matplotlib), and?pytz?(we will let?pipinstall with?pandas). However, let’s install the recommended dependencies:

• numexpr

$ pip install --user numexpr

After install we get:

$ pip show numexpr --- Name: numexpr Version: 2.4 Location: /home/cstrelioff/.local/lib/python2.7/site-packages Requires: numpy

• bottleneck

$ pip install --user Bottleneck

After install we get:

$ pip show Bottleneck --- Name: Bottleneck Version: 0.8.0 Location: /home/cstrelioff/.local/lib/python2.7/site-packages Requires:

We can also import both packages in Python and print the package version to make sure that basic usage seems okay:

$ python -c "import numexpr;print numexpr.__version__" 2.4 $ python -c "import bottleneck;print bottleneck.__version__" 0.8.0

Finally, for?pandas, we install the main package:

$ pip install --user pandas

After some downloading and compiling we get (showing that both pandas?and?pytz were installed, as expected):

Successfully installed pandas pytz Cleaning up...

Use?pip?to check the installation information:

$ pip show pandas --- Name: pandas Version: 0.14.0 Location: /home/cstrelioff/.local/lib/python2.7/site-packages Requires: python-dateutil, pytz, numpy

Note: if you import?pandas, an error about?openpyxl?(a package for working with Excel 2007 files) will be issued:

Python 2.7.6 (default, Mar 22 2014, 22:59:56) [GCC 4.8.2] on linux2 Type "help", "copyright", "credits" or "license" for more information. >>> import pandas /home/cstrelioff/.local/lib/python2.7/site-packages/pandas/io/excel.py:626: UserWarning: Installed openpyxl is not supported at this time. Use >=1.6.1 and <2.0.0. .format(openpyxl_compat.start_ver, openpyxl_compat.stop_ver)) >>> exit()

The error says that?openpyxl?needs to be at least version 1.6.1 and less than 2.0.0.?Strange, this package is listed as optional. Oh well, let’s install an appropriate version. If we just use?pip?to install the current version it will be too high. So, I installed as follows:

• openpyxl 1.8.6

$ pip install --user openpyxl==1.8.6

This install forces the use an appropriate version. Now, try importingpandas?and we get:

Python 2.7.6 (default, Mar 22 2014, 22:59:56) [GCC 4.8.2] on linux2 Type "help", "copyright", "credits" or "license" for more information. >>> import pandas >>> print pandas.__version__ 0.14.0 >>> import openpyxl >>> print openpyxl.__version__ 1.8.6 >>> exit()

Yay(!) we can import?pandas?(and openpyxl) without complaints.

Finally, before leaving?pandas, I will mention that there are a variety of?optional pandas dependencies?that you might want to consider as well. I won’t consider them in this post.

pymc

pymc?is a really nice MCMC package for Python. I have used it on several projects with great success. Installation with?pip?follows the usual format:

$ pip install --user pymc

Get install information:

$ pip show pymc --- Name: pymc Version: 2.3.2 Location: /home/cstrelioff/.local/lib/python2.7/site-packages Requires:

Starting Python you should also be able to get:

Python 2.7.6 (default, Mar 22 2014, 22:59:56) [GCC 4.8.2] on linux2 Type "help", "copyright", "credits" or "license" for more information. >>> import pymc >>> print pymc.__version__ 2.3.2 >>> exit()

statsmodels

statsmodels?provides some nice statistics methods. Before installingstatsmodels?itself, we must install dependencies, which will likely be usesul in any case:?patsy?and?cython.

• patsy?: is a package for describing statistical models in R-like format. Install with:

$ pip install --user patsy

We can see where?pip?installed?patsy:

$ pip show patsy --- Name: patsy Version: 0.2.1 Location: /home/cstrelioff/.local/lib/python2.7/site-packages Requires: numpy

and try importing?patsy?in a Python session:

Python 2.7.6 (default, Mar 22 2014, 22:59:56) [GCC 4.8.2] on linux2 Type "help", "copyright", "credits" or "license" for more information. >>> import patsy >>> print patsy.__version__ 0.2.1 >>> exit()

• cython?: allows for wrapping of c++ code. Install with:

$ pip install --user Cython

Check with?pip:

$ pip show Cython --- Name: Cython Version: 0.20.1 Location: /home/cstrelioff/.local/lib/python2.7/site-packages Requires:

and importing in a Python session:

Python 2.7.6 (default, Mar 22 2014, 22:59:56) [GCC 4.8.2] on linux2 Type "help", "copyright", "credits" or "license" for more information. >>> import cython >>> print cython.__version__ 0.20.1 >>> exit()

• Finally, install?statsmodels?with?pip:

$ pip install --user statsmodels

Show install info with?pip:

$ pip show statsmodels --- Name: statsmodels Version: 0.5.0 Location: /home/cstrelioff/.local/lib/python2.7/site-packages Requires:

and try an import:

Python 2.7.6 (default, Mar 22 2014, 22:59:56) [GCC 4.8.2] on linux2 Type "help", "copyright", "credits" or "license" for more information. >>> import statsmodels >>> print statsmodels.__version__ 0.5.0 >>> exit()

Okay, that’s?patsy,?cython?and?statsmodels.

CMPy

CMPy?is a package for Computational Mechanics in Python developed in the Crutchfield Lab at UC Davis. Currently the package is developed, using git for version control, but is not publicly available. However, I will document the install here because:

It’s useful for people at UCD (or collaborating with people at UCD)

This is an example of installation of a Python package in a folder on the local machine

I start by showing that I have cloned the?CMPy?package to the~/gitlocal/cmpy/?directory. You can see the?setup.py?file when I show the directory contents:

$ ls ~/gitlocal/cmpy/ apps build CHANGES.txt cmpy data docs gallery LICENSE.txt MANIFEST.in old_doc pylintrc README.txt scripts setup.py src

We do the install with?pip, using the?-e?switch to show the location of the package code:

$ pip install --user -e ~/gitlocal/cmpy/ Obtaining file:///home/cstrelioff/gitlocal/cmpyRunning setup.py (path:/home/cstrelioff/gitlocal/cmpy/setup.py) egg_info for package from file:///home/cstrelioff/gitlocal/cmpyInstalling collected packages: CMPyRunning setup.py develop for CMPyCreating /home/cstrelioff/.local/lib/python2.7/site-packages/CMPy.egg-link (link to .) Adding CMPy 1.0dev to easy-install.pth file Installed /home/cstrelioff/gitlocal/cmpy Successfully installed CMPy Cleaning up...

Note that the path to the?CMPy?directory is added to?easy-install.pth, a file that Python consults to find?CMPy. Finally, we show the?pipinformation:

$ pip show cmpy --- Name: CMPy Version: 1.0dev Location: /home/cstrelioff/gitlocal/cmpy Requires:

Again, note that the location is?~/gitlocal/cmpy/, instead of~/.local/lib/python2.7/site-packages/, due to the?-e?tag. This is why the addition to the?easy_install.pth?file (above) was needed.

Edit:?Aug 21st, 2014

A note on updating this local installation is in order. Recently a change in code was made that affected underlying?c code?that is incorporated using cython. I pulled the repository changes using:

$ cd ~/gitlocal/cmpy/ $ git pull

To try and update the install I did:

$ pip install --user -e ~/gitlocal/cmpy/

This ran the?setup.py?file but did?not?recompile the modified c code. To get this to work I had to remove the?build?directory, build in place and install again:

$ cd ~/gitlocal/cmpy/ $ rm -r build/ $ python setup.py build_ext -i --cython $ pip install --user -e ~/gitlocal/cmpy/

Is there a better way to do this? Let me know in the comments below.

restview

restview?is a Python package that processes?reStructuredText?and launches a web browser for viewing. Each time the browser is refreshed, the underlying?rst?document will be re-processed and displayed– very nice for working on Python docmentation or any?rstdocument. Installation goes as usual:

$ pip install --user restview

We can see what was installed:

$ pip show restview --- Name: restview Version: 2.0.5 Location: /home/cstrelioff/.local/lib/python2.7/site-packages Requires: docutils, pygments

As you can see from above,?docutils?and?pygments?will be installed if they are not already installed.

To process an?rst?document named?test.rst?type:

$ restview test.rst

Check?restview?for more examples.

tinkerer

tinkerer?is a blogging environment for Pythonistas that is built onSphinx, a Python documentation tool. Blog entries are written inreStructuredText?and rendered as static html. Of course, this is also the tool I use for this blog. Before moving to our usual?pip?install, we have to take care of some?Ubuntu 14.04 Python dependencies. Assuming these requirements are available,?tinkerer?is installed with the usual:

$ pip install --user tinkerer

We can check the install information with:

$ pip show tinkerer --- Name: Tinkerer Version: 1.4.2 Location: /home/cstrelioff/.local/lib/python2.7/site-packages Requires: Jinja2, Sphinx, Babel, pyquery

Note that requirements?Jinja2,?Sphinx,?Babel?and?pyquery?are also installed automatically. A quick start to getting a blog up and running (at least the generation of posts, pages and generating the html output) is available?here.

Pweave

Pweave?is a tool for literate programming with Python. This tool allows me to write blog posts about Python using a?.Pnw?file that contains?reStructuredText, along with special?Pweave?commands, and have the Python code evaluated and output included in the?.rstoutput file–?see the example here. This is a really nice tool to avoid typos in code and to make sure that what you’re talking about actually works! I should note that?IPython?notebooks can also do this by exporting to?reStructuredText. In any case, I will trying out both of these tools for future posts.

The install of?Pweave?goes as usual:

$ pip install --user Pweave

Check the install with:

$ pip show Pweave --- Name: Pweave Version: 0.21.2 Location: /home/cstrelioff/.local/lib/python2.7/site-packages Requires:

scikit-learn

scikit-learn?is the probably the most well-known and feature-complete package for machine learning tasks in Python. There are a number of dependencies that need to be installed (numpy,?scipy, python-dev, etc see?scikit-learn installation?for more information) that have already been installed above. So, we install using?pip, as usual:

$ pip install --user scikit-learn

Then we can check the installed version and location using:

$ pip show scikit-learn --- Name: scikit-learn Version: 0.15.1 Location: /home/cstrelioff/.local/lib/python2.7/site-packages Requires:

That’s it, machine-learn away!

Posted by Chris Strelioff Tags:?python 2.7,?ubuntu 14.04,?python,?my ubuntu setup,?pip,virtualenv,?numpy,?scipy,?matplotlib,?sympy,?ipython,?pygraphviz,networkx,?pandas,?numexpr,?bottleneck,?openpyxl,?pymc,statsmodels,?patsy,?cython,?cmpy,?restview,?tinkerer,?pweave,?scikit-learn

• ??Installing Octave on Ubuntu 14.04

轉載于:https://www.cnblogs.com/mo-wang/p/5175026.html

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