I'm using JetBrains PyCharm Community Edition 2016.3.2 (64). My Project Interpreter is either Python 3.4 or 3.5. I'm trying to install the Matplotlib package but failed every time. I succeeded on installing Networkx though.
On this site https://networkx.github.io/documentation/networkx-1.10/tutorial/tutorial.html, in the "Drawing graphs" section, it says
Note that the drawing package in NetworkX is not yet compatible with Python versions 3.0 and above.
Someone please confirm this? Should I install Python 2.x to use this package?
I'm doing graph modelling, if anyone can suggest other packages or advise whatever I should use, I would really appreciate. But it needs to be related to Networkx.
Regarding Matplotlib, I don't see why the installation would fail.
try:
sudo apt-get install python3-matplotlib
Depending on your installation, you'll also have to install several libraries that matplotlib depends on:
sudo apt-get install python3.5-dev python3.5-tk tk-dev
sudo apt-get install libfreetype6-dev g++
sudo apt install python3-pip
pip3 install --user matplotlib
In addition, you will need one other package - nose. You can install it using the same syntax:
sudo pip3 install nose
Networkx installation is simple as:
sudo pip3 install networkx
Good luck!
Related
I am unable to install module pandas in my linux vm. I tried all ways to install it, but it says it has version 1.1.5 requirement already satistied. But when I try running the code, it says, no module found. The latest version of python in it is 2.7.3, but I want to install 3.8 or 3.7, but I'm unable to. Where am I going wrong?
Did you try installing python3 from your package manager? You can install python 3.9 from apt using the below command
apt install python3 pip -y
You can also install the below package to use python in the terminal instead of python3 every time
apt install python-is-python3 -y
I cant comment yet so using the answer section, kindly give me an upvote so I can start using the comment feature, sorry for the trouble
Whenever I run:
pip install fastai
I get the error
"Command "python setup.py egg_info" failed with error code 1 in C:\Users\seja9890\AppData\Local\Temp\pip-install-_cw7ve61\torch\".
Can someone please guide me where I might be going wrong?
Ps.: I have tried updating setuptools and it doesn't help in my case.
Fastai doesn't work with Python 2 so make sure you installed pip3 (sudo apt install python3-pip on Ubuntu).
Make sure Python3 is at least 3.6 this may change since Fastai may need 3.7. soon.
and then:
pip3 install git+https://github.com/fastai/fastai.git
or use pip3 install fastai, or in some cases you may need:
pip3 install --no-deps fastai
Note: At the moment I am writing this: PyTorch v1 and Python 3.6 are the minimal version requirements.
For official website, you should install it with conda.
anaconda
fast.ai
To install
# Prerequisites
Anaconda, manages Python environment and dependencies
# Normal installation
Download project: git clone https://github.com/fastai/fastai.git
Move into root folder: cd fastai
Set up Python environment: conda env update
Activate Python environment: conda activate fastai
If this fails, use instead: source activate fastai
# Install as pip package (not recommend)
You can also install this library in the local environment using pip
pip install fastai
However this is not currently the recommended approach, since the library is being updated much more frequently than the pip release, fewer people are using and testing the pip version, and pip needs to compile many libraries from scratch (which can be slow).
An alternative is to use the latest Github version with pip
pip install git+https://github.com/fastai/fastai.git
I am trying to install tables package in Ubuntu 14.04 but sems like it is complaining.
I am trying to install it using PyCharm and its package installer, however seems like it is complaining about HDF5 package.
However, seems like I cannnot find any hdf5 package to install before tables.
Could anyone explain the procedure to follow?
I found that installing the libhdf5-serial-dev with
sudo apt-get install libhdf5-serial-dev
did the trick.
Search for the HDF5 library in the ubuntu package repository.
apt-cache search hdf5
The command will show the packages relating to hdf5.
install the relevant package to you.
sudo apt-get install package-name.
mostly you have to install the hdf5-tools, h5utils, python-tables.
Try to install libhdf5-7 and python-tables via apt
To be more precise, do two steps on Ubuntu
1) install hdf5
sudo apt-get install libhdf5-serial-dev
2) install pytables
pip install tables
Many python packages have build dependencies on non-Python packages. I'm specifically thinking of lxml and cffi, but this dilemma applies to a lot of packages on PyPI. Both of these packages have unadvertised build dependencies on non-Python packages like libxml2-dev, libxslt-dev, zlib1g-dev, and libffi-dev. The websites for lxml and cffi declare some of these dependencies, but it appears that there is no way to do figure this out from a command line.
As a result, there are hundreds of questions on SO that take this general form:
pip install foo fails with an error: "fatal error: bar.h: No such file or directory". How do I fix it?
Is this a misuse of pip or is this how it is intended to work? Is there a sane way to know what build dependencies to install before running pip? My current approach is:
I want to install a package called foo.
pip install foo
foo has a dependency on a Python package bar.
If bar build fails, then look at error message and guess/google what non-Python dependency I need to install.
sudo apt-get install libbaz-dev
sudo pip install bar
Repeat until bar succeeds.
sudo pip uninstall foo
Repeat entire process until no error messages.
Step #4 is particularly annoying. Apparently pip (version 1.5.4) installs the requested package first, before any dependencies. So if any dependencies fail, you can't just ask pip to install it again, because it thinks its already installed. There's also no option to install just the dependencies, so you must uninstall the package and then reinstall it.
Is there some more intelligent process for using pip?
This is actually a comment about the answer suggesting using apt-get but I don't have enough reputation points to leave one.
If you use virtualenv a lot, then installing the python-packages through apt-get can become a pain, as you can get mysterious errors when the python packages installed system-wide and the python packages installed in your virtualenv try to interact with each other. One thing that I have found that does help is to use the build-dep feature. To build the matplotlib dependencies, for example:
sudo apt-get build-dep python-matplotlib
And then activate your virtual environment and do pip install matplotlib. It will still go through the build process but many of the dependencies will be taken care of for you.
This is sort what the cran repositories suggest when installing R packages in ubuntu.
For most popular packages, There is a workaround for recent ubuntu systems. For example, I want to install matplotlib. When you order pip install matplotlib, it usually fails because of a missing dependency.
You can use apt-get install python-matplotlib instead. For python3, you can use apt-get install python3-matplotlib
I'm trying to upgrade Scipy from 0.9.0 to 0.12.0. I use the command:
sudo pip install --upgrade scipy
and I get all sorts of errors which can be seen in the pip.log file here and I'm unfortunately not python-savvy enough to understand what's wrong. Any help will be appreciated.
The error messages all state the same: You lack BLAS (Basic Linear Algebra Subroutines) on your system, or scipy cannot find it. When installing packages from source in ubuntu, as you are effectively trying to do with pip, one of the easiest ways to make sure dependencies are in place is by the command
$ sudo apt-get build-dep python-scipy
which will install all packages needed to build the package python-scipy. You may in some cases run into the problem that the version of the source package you are trying to install have different dependencies than the version included with ubuntu, but in your case, I think chances are good that the above command will be sufficient to fetch BLAS for you, headers included.
I had the same problem upgrading from scipy 0.9 to 0.13.3, and I solved it using the following answer and installing:
sudo apt-get install libblas-dev
sudo apt-get install liblapack-dev
sudo apt-get install gfortran
Make sure libatlas-base-dev and libatlas-sse2-dev are installed, it seems like it can't find your atlas library. Also, see this question:
Does Python SciPy need BLAS?
I found Adam Klein's instructions for setting up scipy (and friends) in a virtual environment very useful.
One problem I ran into (which was probably my own fault): After all was said and done, I found importing scipy still loaded version 0.9.0, not 0.12.0. The problem was that my sys.path was finding the old system version before the new version.
The fix was to make
/path/to/.virtualenvs/arthur/local/lib/python2.7/site-packages
appear before
/usr/lib/python2.7/dist-packages
in sys.path. If you have virtualenvwrapper installed, then
you can add the path using
add2virtualenv /path/to/.virtualenvs/arthur/lib/python2.7/site-packages