After setting up a simple virtualenv and installing a few packages, when I yolk -l I get
Python - 2.7.5 - active development (/System/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/lib-dynload)
ipython - 1.1.0 - active
pip 1.5 has no metadata
readline - 6.2.4.1 - active
setuptools 2.1 has no metadata
wsgiref - 0.1.2 - active development (/System/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7)
yolk - 0.4.3 - active
What does "has no metadata" mean for pip and setuptools (both, I believe, installed when the virtualenv is created)? Can I do something (e.g. with pip) to "fix" this?
Some (newer) Python packages store their package metadata in a different file than expected by yolk; yolk3k will knows how to handle that though. Just
pip install --upgrade yolk3k
Related
I am using Anaconda (latest version of september). I have executed 'conda update --all' to get the latest packages, in particular Scipy. But when I import scipy from a python shell, it's only importing the 1.7.3 version, not the latest one (1.9.1).
I am not fluent with the conda framework. I tried running conda install scipy which did not change anything, and conda install scipy=1.9.1 (which seems to hang).
I am using the base environment. This is a fresh isntall of the latest Anconda (with package update via conda, not any use of pip that could interfere).
Listing the packages via conda yields:
>>> conda list scipy
# packages in environment at /home/***/anaconda3:
#
# Name Version Build Channel
scipy 1.7.3 py39hc147768_0
However, when I look at the content of the anaconda3/pkgs folder:
>>> ls anaconda3/pkgs/ | grep scipy
anaconda3/pkgs/scipy-1.7.3-py39hc147768_0.conda
anaconda3/pkgs/scipy-1.9.1-py39h14f4228_0.conda
anaconda3/pkgs/scipy-1.7.3-py39hc147768_0 (contains Scipy 1.7.3)
anaconda3/pkgs/scipy-1.9.1-py39h14f4228_0 (contains Scipy 1.9.1)
anaconda3/pkgs/scipy-1.9.1-py39h14f4228_09jfxaf1g (empty folder)
anaconda3/pkgs/scipy-1.9.1-py39h14f4228_0dydy5wnw (empty folder)
So I am assuming that conda has both Scipy 1.7.3 and 1.9.1. But why can't I import the lastest one ?
How may I correct this situation ?
EDIT: creating a new environment and reinstalling the packages as needed solves my problem. However, how come the base environment is stuck with the earlier version ?
How to install TensorFlow on Python 3.7
Trying:
D:\Users\Downloads>pip install tensorflow
ERROR: Could not find a version that satisfies the requirement tensorflow (from versions: none)
ERROR: No matching distribution found for tensorflow
Windows 10 OS
And with vent error, too
(venv) C:\Users\KvaksManYT>pip install --upgrade tensorflow
ERROR: Could not find a version that satisfies the requirement tensorflow (from versions: none)
ERROR: No matching distribution found for tensorflow
I would recommend using a virtual environment using pip install vitualenv. Then, depending on your OS, you want to create and activate an environment.
python3 -m venv /path/to/new/virtual/environment
Then, activate this environment using,
source ./venv/bin/activate
Now, you can install any Python packages you want.
pip install tensorflow==2.0.0
you can install Tensorflow follow those steps
Ubuntu/Linux /mac os /windows
virtualenv does not require a mention pip version
for system install, you need to mention pip version
upgrade pip version
pip install --upgrade pip
#virtualenv install
pip install --upgrade tensorflow
#system install
pip3 install --user --upgrade tensorflow
reference https://www.tensorflow.org/install/pip
I had the same problem with Windows 10 x64, and it was caused because I was using the wrong Python version, both globally and in the venv. I found questions on the issue multiple times on the internet, including yours.
Be sure to use Python versions 3.5-3.8, as per requirements, but also x64, not x32.
Namely, I ran into this error using both
a venv with 3.9.1 x64 (python --version),
and my globally installed 3.8.2 x32 (python3 --version).
So, I downloaded the x64-version of Python 3.8.6 from here.
Note that the command venv does not allow specifying the python version used in the virtual environment,
as per an answer on this question. So I used virtualenv, which I obviously had to install in my global Python version first.
To specify the Python version used in the venv, I used the command virtualenv, as in:
virtualenv --python="C:\Users\me\AppData\Local\Programs\Python\Python38\python.exe myvenv
where you have to give the path to the newly downloaded Python distribution you want to use, if there are several on your PC (for example, I had Python38-32 and Python39 folders in that directory).
Check Python versions in virtual environment
After I activate my myvenv, created as above, I verify the Python versions as follows:
python3 --version
> Python 3.8.2
python --version
> Python 3.8.6
Then, using the command
import struct
print(struct.calcsize("P") * 8)
Within either python3 or python, shows me whether the version is 32bit or 64bit, as per this answer. The python returns a 64, so that is the one you want to use (not python3).
Finally, within the virtual environment, you can run
pip install --upgrade tensorflow
and it will download and install. (Meanwhile, pip3 install --upgrade tensorflow would still return your error inside and outside the virtual enviroment.)
When trying to import SkewT into my python3 code on a Mac (Mojave 10.14.6):
from metpy.plots import SkewT
I get the error:
ModuleNotFoundError: No module named 'cartopy'
pip3 install cartopy gives the output
Collecting cartopy
Downloading https://files.pythonhosted.org/packages/e5/92/fe8838fa8158931906dfc4f16c5c1436b3dd2daf83592645b179581403ad/Cartopy-0.17.0.tar.gz (8.9MB)
|████████████████████████████████| 8.9MB 616kB/s
Installing build dependencies ... done
Getting requirements to build wheel ... error
ERROR: Complete output from command /usr/local/opt/python/bin/python3.7 /usr/local/lib/python3.7/site-packages/pip/_vendor/pep517/_in_process.py get_requires_for_build_wheel /tmp/tmpj50b1vfe:
ERROR: setup.py:171: UserWarning: Unable to determine GEOS version. Ensure you have 3.3.3 or later installed, or installation may fail.
'.'.join(str(v) for v in GEOS_MIN_VERSION), ))
Proj 4.9.0 must be installed.
----------------------------------------
ERROR: Command "/usr/local/opt/python/bin/python3.7 /usr/local/lib/python3.7/site-packages/pip/_vendor/pep517/_in_process.py get_requires_for_build_wheel /tmp/tmpj50b1vfe" failed with error code 1 in /private/tmp/pip-install-b5cu8485/cartopy
To start, I tried to install Proj and geos, but pip3 only lists version 0.1.0 for proj and 0.2.2 for geos. Before I get too far down this rabbit hole, I thought I'd see if anyone else has encountered this problem. Thanks!
So it looks like MetPy 0.10 accidentally picked up a hard dependency on CartoPy, which we did not really plan. You can track our resolution of that here.
CartoPy depends on a lot of compiled libraries that are not pip-installable unfortunately. Your best bet is to look at CartoPy's install instructions. If you're using Anaconda or Canopy, those distributions have pre-built CartoPy packages available.
One option to work around this is to install MetPy 0.9:
pip install metpy==0.9
Do you use Conda? The easiest way to remedy this problem is to install CartoPy (or MetPy for that manner) via conda, so that all of the right dependencies are also downloaded: conda install -c conda-forge cartopy or conda install -c conda-forge metpy. Pip doesn't bring all of them together, so that leads to this problem being raised.
Thanks. Without conda, I was also able to complete this (more painful) installation:
- brew install geos
- brew install proj
- pip3 install cython
- pip3 install git+https://github.com/SciTools/cartopy.git#master
(see http://louistiao.me/posts/installing-cartopy-on-mac-osx-1011/)
I am trying to install setuptools 20.4 or greater as it is a requirement for CKAN. I have tried downloading the rpm files and installing it but CKAN does not recognize the python2 rpm.
I am running a virtualenv for the ckan server under use ckan with the bash shell.
Does anybody have advice on how to properly install setuptools 20.4 or greater on centos?
If not using pip to upgrade setuptools, install/upgrade setuptools before you create the virtualenv.
I believe the rpm will update the system python's setuptools. When you create the virtualenv it copies the system setuptools into the virtualenv.
I had to update python to version 2.7.13 and then download setuptools from the python repository. Centos doesn't have official support for any python above 2.7.5 which is problematic as I have to add exclusions to yum update. Ckan does require setuptools installed this is not optional, on install it is listed as a critical error.
Is it possible to specify the minor version of the JDK for jobs running on Travis? I have a JavaFX project which is failing because JDK 1.8.0_31 is being used to perform the build where as the project uses some classes that were only shipped in Java 1.8.0_40 (specifically Alert and Spinner).
Currently my .travis.yml file looks like below:
language: java
jdk:
- oraclejdk8
Here's a link to the failed build just in case it's useful.
This solution based on apt addon works for me:
language: java
jdk:
- oraclejdk8
addons:
apt:
packages:
- oracle-java8-installer
In result I have java version "1.8.0_91". The solution source is here
I finally got it working. This solution is not really reccommended as it uses linuxbrew to install Oracle JDK 8.0_40. Thanks to zrcoder on Github I ended up with this .travis.yml:
language: java
branches:
only:
- master
notifications:
email: false
before_install:
- rm -rf ~/.linuxbrew
- yes | ruby -e "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/linuxbrew/go/install)"
- export PATH="$HOME/.linuxbrew/bin:$PATH"
- export MANPATH="$HOME/.linuxbrew/share/man:$MANPATH"
- export INFOPATH="$HOME/.linuxbrew/share/info:$INFOPATH"
- brew install jdk
- export JAVA_HOME=/home/travis/.linuxbrew/Cellar/jdk/1.8.0-40
Although this works, Travis-CI should be updated by next month, so update your config for shorter build times.
I recommend using Travis CI's Trusty build environment which uses newer software than the default Precise environment. It's quicker and more reliable than redownloading the newest JDK on each build.
Just add the following to the top level of .travis.yml
dist: trusty