Library of Wonderful Things
A library of wonderful Python things!
This library is born from my version of the
utils library every project has.
Only, instead of being utilities that are specific to the task, these utilities
are for multiple projects: They assume logs should be structured,
all data should be JSONizable, and OO is preferred, and more.
Python is a Little Crufty
Python is awesome now, but it was originally a procedural language invented before pure functional semantics, before OO, and even before the discovery of vowels. As a consequence there are many procedures that alter their own parameters, or have disemvoweled names. This library puts a facade over these relics of the past and uses convention to name methods.
Python packages are easy to install, assuming you have Python (see below).
pip install pyLibrary
Installing for Development
Download from Github:
git clone https://github.com/klahnakoski/pyLibrary.git
python setup.py develop
Windows 7 Install Instructions for Python
Updated November 2014, for Python 2.7.8
Python was really made for Linux, and installation will be easier there. Technically, Python works on Windows too, but there are a few gotchas you can avoid by following these instructions.
Download Python 2.7
- 32bit ONLY!!! Many native libs are 32 bit
- Varsion 2.7.8 or higher (includes pip, so install is easier)
Install Python at
c:\Python27(The space in the "Program Files" may screw up installs of native libs)
Add to you path:
CALL python get-pip.py CALL pip install virtualenv
Many "Python Powered" native installs require a pointer to the python installation, but they have no idea where to look in 64bit windows. You must alter the registry (http://stackoverflow.com/questions/3652625/installing-setuptools-on-64-bit-windows):
SET HKEY_LOCAL_MACHINE\SOFTWARE\Wow6432Node\Python\PythonCore\2.7\InstallPath = "C:\Python27"
virtualenv allows you to have multiple python projects on the same
machine, even if they use different versions of the same libraries.
virtualenv does this by making a copy of the main python directory and
using it to hold the specific versions required.
- New environment:
- Activate environment:
- Exit environment:
If you have more than one project on your dev box I suggest you do all your work inside a virtual environment.
PyPy and Virtual Environments
virtualenv can be used with PyPy, but it is a bit more involved. The
paths must be explict, and some copying is required.
The first call to virtualenv will make the directory, to which you copy the PyPy core libraries, and the second call finishes the install.
c:\PyPy27\bin\virtualenv <name_of_dir> copy c:\PyPy27\bin\lib_pypy <name_of_dir> copy c:\PyPy27\bin\lib_python <name_of_dir> c:\PyPy27\bin\virtualenv <name_of_dir>
virtualenv places it's executables in
PyPy version uses
Using PIP in PyPy:
PyPy does not share any libraries with CPython. You must install the PyPy libraries using
pip found in your
%PATH% probably points to
Using PIP in PyPy virtualenv:
Do NOT use the
<name_of_dir>\Scripts directory: It installs to your
main PyPy installation. Pip install is done using the
Deactivation is like normal
CPython Binaries and Virtual Environments
If you plan to use any binary packages,
virtualenv will not work
directly. Instead, install the binary (32 bit only!!) to the main python
installation. Then copy any newly installed files/directories from
Binaries and PyPy
This strategy for installing binaries into Virtual Environments is almost
identical to installing binaries into your PyPy environment: Install Numpy
and Scipy to your CPython installation using a windows installer (which has
pre-compiled binaries), and then copy the
c:\PyPy\site-packages\; note lack of
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