Hello,
I'm getting into Python now after years of Perl, and as part of my
research I must understand how to do some common tasks I need.
I have a bunch of Windows PCs at work to which I want to distribute an
application I've developed on my PC. All these PCs have Python 2.5
installed.
If my application contains only code I've developed, I simply zip its
directory with .py files and send it to everyone, who can then use it
by running the entry-point .py file. However, what if I've installed
some 3rd party modules on my PC, and my application uses them (for
example pyparsing, PiYAML and some others) ? I don't want to manually
install all these packages (there may be dozens of them) on all those
PCs (there may be dozens of those too). What is the best method I can
use ? Naturally, I want all the non-standard packages my app uses to
be detected automatically and collected into some kind of convenient
distributable that is easy to pass around and run.
I'm aware of py2exe - tried it and it works fine. But it creates huge
executables, and I don't want to distribute those all the time. I much
prefer a zipped directory of .py scripts that takes some 10s of KBs.
Thanks in advance,
Eli
Hello,
If anyone is interested, I've implemented such a utility - called
libcollect.py, downloadable at:
http://eli.thegreenplace.net/files/prog_code/libcollect.py.txt
Here's its description from the embedded docstring:
Motivation:
Imagine that you've written a script that uses several libraries, some
of
which you've written and some you've downloaded and installed (for
example
PyYAML). You want to distribute the script to your friends and co-
workers,
who already have Python installed with all the standard library. But
your
script won't run on their machines, because they have neither your
personal
libraries, nor PyYAML installed. So what can you do ?
* You can ask them to install PyYAML and other libraries your script
uses,
and send them your own libraries. This is a lengthy and
inconvenient
process.
* You can use a tool like py2exe to package your delivery. This has a
downside, however. py2exe produces large files (several MBs) and you
may
not want that.
* You can painstakingly collect the libraries into a directory where
your
script can find them, and package the directory together with the
script.
LibCollect makes the third option trivial, by doing all the dirty work
for you.
Example:
Suppose your script is named script.py, and is located in directory
$DIR
(although I'm using Unix-y notation here, it is for convenience only.
LibCollect works similarly well on Windows platforms). Follow these
steps
to prepare a self-contained distribution with LibCollect:
Create a distribution setup script in the same directory. Lets assume
you call it distrib_script.py. You can easily place it in any
directory
you like, I'm using the same one to make the example simpler.
Add the following to distrib_script.py (assuming that libcollect.py is
in your sys.path):
**************************************************************
import libcollect
# Create a LibCollect object
lc = libcollect.LibCollect()
# Prepare arguments for do_collect
#
# Path to the script (can be absolute or relative)
scriptname = 'script.py'
# Ask the resulting distribution to be placed in
# directory distrib
targetdir = 'distrib'
# Specify which libraries to exclude from the
# distribution (because you know they're installed
# on the target machine)
excludes = ["wx",
"pywin",
"win32api",
"win32com"]
# Zip the libraries used by the script to reduce
# clutter and save space
zip_lib = True
# This does the actual work
lc.do_collect( scriptname,
targetdir,
excludes,
zip_lib=zip_lib)
**************************************************************
Now run distrib_script.py.
When it finishes running, you will see that the distrib directory
has been created in $DIR. In $DIR/distrib you will see two files,
script.py and distlib.zip
* script.py is a loader that replaces your original script.py - this
is the program your users should run. All it does (look at the
code, it's short!) is prepare the sys.path to include the
packaged libraries, and runs your own script.py that was also
packaged into the .zip file
* distlib.zip is the distribution library, containing all the code
your script needs to run on any machine with Python installed,
and nothing else (except the modules you specified in the exclusion
list). You may choose to pass on the zip file creation and leave
your distribution library as a directory by providing False
to the zip_lib argument of LibCollect.do_collect (take a look at
its documentation, there are some other options there)
How to use LibCollect:
* It is most convenient to use LibCollect in the way demonstrated
in the example above. You may want to update your application from
time to time, and having a distribution script handy will turn
the preparation of a new distribution into a 5-second process.
* If you don't want to create a distribution script, you can use
a more direct method of invoking libcollect.py as a program on
your script. Call it without arguments and it will print
a usage string that will explain what you need to do.
How it works:
* LibCollect uses the standard modulefinder module to find out which
libraries are used by your script. It categorizes them into two
types: standard libraries that came with Python, and non-standard
libraries you've installed or written.
* Only libraries of the second type are included in the distribution
(bar the libraries you've explicitly asked to exclude).
* It then builds a directory with all the included libraries, in a
way that your script will be able to find them. The script itself
is also packaged into the same place.
* On request, this directory can be zipped into a single file, to
employ Python's built-in zip import facility.
* In the distribution directory, a new file with the name of your
script is created. It is a simple loader that uses the runpy module
to transparently load your script from the distribution library.
This way your script is not being modified (sys.path is rigged
from the loader).
Compatibility:
Python 2.5
Tested on Windows and Linux, but should work on other platforms
where the standard Python distribution works.