I installed freetype-2.4.10, libpng-1.5.12, and zlib-1.2.7 into local directories. Now, in matplotlib I would like to do:
python setup.py install
When I did this for lxml I did something like:
python setup.py install --with-xml2-config=/home/test/libxml2/bin/xml2-config --with-xslt-config=/home/test/libxslt/bin/xslt-config
How can I point matplotlib to the proper freetype, libpng and zlib libraries?
From the INSTALL file:
If you have installed prerequisites to nonstandard places and need to
inform matplotlib where they are, edit setupext.py and add the
base dirs to the basedir dictionary entry for your
sys.platform. e.g., if the header to some required library is in
/some/path/include/someheader.h, put /some/path in the
basedir list for your platform.
Related
I have a python package fmdt-python that anyone can install with pip install fmdt-python. I want to configure this package so that I can call import fmdt anywhere. Despite my best efforts, after successfully installing fmdt-python python can't actually find the package fmdt. How do I configure the project.toml of my pypi project fmdt-python to be imported as fmdt in python?
For reference, the pypi package ffmpeg-python is imported in python as ffmpeg We can inspect the local path pip uses to install packages to see that there is a long versioned name of the package alongside a shorter name used in the import statement:
but for my package fmdt-python pip only installs the directory with the long name:
I would like to configure my package so that pip installs the proper fmdt folder alongside fmdt_python-0.0.12.dist-info.
I am using hatchling as the build system and use a pyproject.toml file to configure this package. For reference, here's the github of the package and this is the pypi index.
The "problem" with my directory structure is that I had a python package fmdt in which I placed all of the configuration files like pyproject.toml, LICENCE, setup.py, etc.
Rearranging the structure to:
with the config files outside of the fmdt folder, I was able to configure my build to make the fmdt package available for import when downloading the pypi distribution fmdt-python
I am working in WIN10 , with python 2.7.15
I am try to install package, during the installation process I received the following error .
Cannot uninstall 'PyYAML'. It is a distutils installed project and thus we cannot accurately determine which files belong to it which would lead to only a partial uninstall.
I try to uninstall with pip (18.1) command and I received the same error.
pip uninstall PyYAML
How I can uninstall/upgrade distutils packge in win10 OS.
Base distutils functionality doesn't leave any information about which files belong to a package -- thus it cannot be reliably uninstalled. That's what the message is telling you. Moreover, it doesn't have dependency metadata, so it can't be "upgraded" reliably, either. All those features are additions by setuptools (and some by wheel and pip itself).
This can happen if you installed the package directly from source with setup.py install if setup.py is distutils- rather than setuptools-based. Or if you installed it manually from some types of packages by copying/extracting files.
Unless the way you installed it provides an own uninstaller, you'll have to manually figure out which files belong to the package and delete them from Python directories.
Usually, these are:
site-packages\<package_name>* directories and/or
site-packages\<package_name>*.py for standalone modules
optionally, a site-packages\<package_name>.pth file
Generally, look for anything that bears the package's name on it.
If you can build the same package from source, you can use the build process to get a hint: build a binaly package that you can look into (e.g. setup.py bdist_wheel -- .whl is a ZIP archive) and see what files it has in it.
I've been trying to get a working fast numpy with BLAS on Windows, and so far, the only method that seems feasible is downloading the precompiled library with MKL from http://www.lfd.uci.edu/~gohlke/pythonlibs/#numpy.
So far ok, but chekcing later numpy.__config__.show(), I see it points to directories that don't exist, such as C:\program files (x86)\IntelSWTools
I assume numpy is trying to place the MKL libraries in this directory, but I have no administration privileges for creating files in C:\program files (x86).
Is there any simple way to use this numpy distribution and install the MKL libs in another directory? Such as a pip install filename.whl --some_option_to_install_mkl_in_another_dir?
(Windows 7 64bit, python 3.5.2)
Already attempted:
Use pip install <package> --user: it seems to install everything exactly the same way as the same command without --user. (My default installation folder is aldready the user folder)
User pip install <package> --root <some_path>: installs everything in the passed path, but Numpy config still points to C:\program files (x86)\IntelSWTools, and python cannot find numpy, even if I add <some_path> to both PATH and PYTHONPATH environment vars
Tried to create the pip.ini file, with the lines [global] and target=E:\destination. The destination folder remains untouched.
Rename the wheels file to zip, find all files containing the IntelSWTools folder, change all these folders to one that I have access to. Make it a wheels file again and pip install. Absolutely no file appears in the folder I chose, but numpy config is pointing to that folder. -- This makes me wonder: does this distribution really installs MKL?
Numpy+MKL does not place (or try to place) MKL libraries in C:\program files (x86)\IntelSWTools. The MKL runtime DLLs necessary to use numpy+MKL are copied to sys.prefix\Lib\site-packages\numpy\core during installation with pip.
C:\program files (x86)\IntelSWTools is the location of the MKL development files (link libraries, header files, DLLs, documentation) that were used to build numpy+MKL. If you want to build other software from source that relies on MKL development files, you need to download MKL from Intel.
I have tried something like this:
pip install --install-option="--prefix=$PREFIX_PATH" package_name
I the above line:
$PREFIX_PATH ---- Change the path you want to specify.
package_name ---- Change the Package name with the desired package name or the wheel file.
On Windows, I tried the above and it is not working. But the below answer will work:
python.exe -m pip install --target=c:\data\ pandas
The pandas got stored in the data folder. Only the thing we need to do is we have to specify the path to our Python, so that it will fetch the proper library. You can go in the data folder and run python. You will be able to access the library.
Hope this helps you.
I'm trying to install Pandas using pip, but I'm having a bit of trouble. I just ran sudo pip install pandas which successfully downloaded pandas. However, it did not get downloaded to the location that I wanted. Here's what I see when I use pip show pandas:
---
Name: pandas
Version: 0.14.0
Location: /Library/Python/2.7/site-packages/pandas-0.14.0-py2.7-macosx-10.9-intel.egg
Requires: python-dateutil, pytz, numpy
So it is installed. But I was confused when I created a new Python Project and searched under System Libs/lib/python for pandas, because it didn't show up. Some of the other packages that I've downloaded in the past did show up, however, so I tried to take a look at where those were. Running pip show numpy (which I can import with no problem) yielded:
---
Name: numpy
Version: 1.6.2
Location: /System/Library/Frameworks/Python.framework/Versions/2.7/Extras/lib/python
Requires:
Which is in a completely different directory. For the sake of confirming my error, I ran pip install pyquery to see where it would be downloaded to, and got:
Name: pyquery
Version: 1.2.8
Location: /Library/Python/2.7/site-packages
Requires: lxml, cssselect
So the same place as pandas...
How do I change the default download location for pip so that these packages are downloaded to the same location that numpy is in?
Note: There were a few similar questions that I saw when searching for a solution, but I didn't see anything that mentioned permanently changing the default location.
According to pip documentation at
http://pip.readthedocs.org/en/stable/user_guide/#configuration
You will need to specify the default install location within a pip.ini file, which, also according to the website above is usually located as follows
On Unix and Mac OS X the configuration file is: $HOME/.pip/pip.conf
On Windows, the configuration file is: %HOME%\pip\pip.ini
The %HOME% is located in C:\Users\Bob on windows assuming your name is Bob
On linux the $HOME directory can be located by using cd ~
You may have to create the pip.ini file when you find your pip directory. Within your pip.ini or pip.config you will then need to put (assuming your on windows) something like
[global]
target=C:\Users\Bob\Desktop
Except that you would replace C:\Users\Bob\Desktop with whatever path you desire. If you are on Linux you would replace it with something like /usr/local/your/path
After saving the command would then be
pip install pandas
However, the program you install might assume it will be installed in a certain directory and might not work as a result of being installed elsewhere.
You can set the following environment variable:
PIP_TARGET=/path/to/pip/dir
https://pip.pypa.io/en/stable/user_guide/#environment-variables
Open Terminal and type:
pip config set global.target /Users/Bob/Library/Python/3.8/lib/python/site-packages
except instead of
/Users/Bob/Library/Python/3.8/lib/python/site-packages
you would use whatever directory you want.
Follow these steps
pip config set global.target D:\site-packages to change install path
or py -m pip config --user --editor notepad edit
[global]
target = D:\site-packages
set environment variable to use download import xxx
PIP_TARGET=site-packages
PYTHONPATH=site-packages
3.pip config unset global.target, to upgrade pip py -m pip install --upgrade pip
#Austin's answer is outdated, here for more up-to-date solution:
According to pip documentation at
https://pip.pypa.io/en/stable/topics/configuration/
You will need to specify the default install location within a configuration file, which, also according to the website above is usually located as follows
Mac OS
$HOME/Library/Application Support/pip/pip.conf if directory $HOME/Library/Application Support/pip exists else $HOME/.config/pip/pip.conf.
The legacy “per-user” configuration file is also loaded, if it exists: $HOME/.pip/pip.conf.
The $HOME folder can be located by navigating to ~/ (cmd+shift+G in Finder; cmd+shift+. to show hidden files).
Windows
%APPDATA%\pip\pip.ini
The legacy “per-user” configuration file is also loaded, if it exists: %HOME%\pip\pip.ini
The %HOME% is located in C:\Users\Bob on windows assuming your username is Bob
Unix
$HOME/.config/pip/pip.conf, which respects the XDG_CONFIG_HOME environment variable.
The legacy “per-user” configuration file is also loaded, if it exists: $HOME/.pip/pip.conf.
On linux the $HOME directory can be located by using cd ~
You may have to create the configuration file when you find your pip directory. Put something like
[global]
target = /Library/Frameworks/Python.framework/Versions/Current/lib/python3.10/site-packages/
if you are on a Mac. Except that you would replace /Library/Frameworks/Python.framework/Versions/Current/lib/python3.10/site-packages/ with whatever path you desire. If you are on Linux you would replace it with something like /usr/local/your/path
After saving the command would then be
pip install pandas
However, the program you install might assume it will be installed in a certain directory and might not work as a result of being installed elsewhere.
Please note that
pip3 install pandas
might be the solution if your packages gets installed in the Python2 folder vs Python3.
I'm using NumPy built against Intel's Math Kernel Library. I use virtualenv, and typically use pip to install packages.
However, in order for NumPy to find the MKL libraries, it's necessary to create a site.cfg file in the NumPy source directory prior to compiling it, then manually build and install. I could script this whole process, but I was hoping for a simpler solution.
I have a standard site.cfg file that can be used for this purpose under version control. Are there any pip command line options that will tell it to copy a particular file to the source directory before building a package?
Alternatively, are there any environment variables that can be set instead of supplying the library paths in a site.cfg file? Here is the site.cfg file that I use. It was taken almost verbatim from Intel's site.
[mkl]
library_dirs = /opt/intel/composer_xe_2013.1.117/mkl/lib/intel64
include_dirs = /opt/intel/composer_xe_2013.1.117/mkl/include
mkl_libs = mkl_rt
lapack_libs =
For reference, I'm running Ubuntu, Python 2.7, and NumPy 1.6.
From the source (https://github.com/numpy/numpy/blob/master/site.cfg.example):
To assist automatic installation like easy_install, the user's home directory
will also be checked for the file ~/.numpy-site.cfg .
Is that a workable solution? You'd still need to preload the home directories with the global .numpy-site.cfg, but you wouldn't have to muck with the build or installation after that.
I ended up putting together a script to automate this. Here it is, in case it can help someone else. I've tested it in Python 2.7, but it should work elsewhere without significant modifications.
from __future__ import unicode_literals
import io
import os.path
import re
import subprocess
import urllib2
# This downloads, builds, and installs NumPy against the MKL in the
# currently active virtualenv
file_name = 'numpy-1.6.2.tar.gz'
url = ('http://sourceforge.net/projects/numpy/files/NumPy/1.6.2/'
'numpy-1.6.2.tar.gz/download')
def main():
# download NumPy and unpack it
file_data = urllib2.urlopen(url).read()
with io.open(file_name, 'wb') as fobj:
fobj.write(file_data)
subprocess.check_call('tar -xvf {0}'.format(file_name), shell=True)
base_name = re.search(r'(.*)\.tar\.gz$', file_name).group(1)
os.chdir(base_name)
# write out a site.cfg file in the build directory
site_cfg = (
'[mkl]\n'
'library_dirs = /opt/intel/composer_xe_2013.1.117/mkl/lib/intel64\n'
'include_dirs = /opt/intel/composer_xe_2013.1.117/mkl/include\n'
'mkl_libs = mkl_rt\n'
'lapack_libs =\n')
with io.open('site.cfg', 'wt', encoding='UTF-8') as fobj:
fobj.write(site_cfg)
# build and install NumPy
subprocess.check_call('python setup.py build', shell=True)
subprocess.check_call('python setup.py install', shell=True)
if __name__ == '__main__':
main()
Your goal of installing NumPy to use Intel's Math Kernel Library is now much easier since Intel created pips to install MKL + NumPy:
pip uninstall numpy -y # if the standard numpy is present
pip install intel-numpy
as well as intel-scipy, intel-scikit-learn, pydaal, tbb4py, mkl_fft, mkl_random, and the lower level packages if you need just them. Again, you must first uninstall the standard packages if they're already installed in your virtualenv.
NOTE:
If standard NumPy, SciPy and Scikit-Learn packages are already installed, the packages must be uninstalled before installing the Intel® variants of these packages(intel-numpy etc) to avoid any conflicts. As mentioned earlier, pydaal uses intel-numpy, hence it is important to first remove the standard Numpy library (if installed) and then install pydaal.
Alternatively, are there any environment variables that can be set instead of supplying the library paths in a site.cfg file?
NumPy 1.21 introduces environment variables for this purpose.
E.g.
NPY_BLAS_ORDER=MKL NPY_LAPACK_ORDER=MKL pip install numpy --no-binary numpy
to auto-detect the MKL library when installing NumPy from source code. If needed, you can set the environment variables NPY_BLAS_LIBS, NPY_CBLAS_LIBS, and NPY_LAPACK_LIBS to linker CLI options which put your chosen libraries on the linker path.
This is easier for a script to do than creating a ~/.numpy-site.cfg file,
[openblas]
libraries = openblas
library_dirs = /usr/local/opt/openblas/lib
include_dirs = /usr/local/opt/openblas/include
runtime_library_dirs = /usr/local/opt/openblas/lib
then running
pip install numpy --no-binary numpy
BTW, the file ~/.numpy-site.cfg also works when installing scipy from source code:
pip install scipy --no-binary scipy
NOTE: If you're still using Python 2.7, install numpy then install scipy. Attempting to install them together will:
invoke a SciPy easy_install installer that requests NumPy,
load the latest NumPy installer (even if you specifically asked pip to install numpy==1.14.6 scipy==1.0.1 --no-binary numpy,scipy), then
fail with RuntimeError: Python version >= 3.5 required because the latest NumPy does not support Python 2.7.