How do I uninstall xgboost python package? - pip

I have built and installed XGBoost on my system (Ubuntu 16.04) following the provided instructions. Specifically, I have installed it running
python3 setup.py install --user
in its python-package directory.
How can I now uninstall it?
When I try with pip3 I get:
-> pip3 uninstall xgboost
Not uninstalling xgboost at /home/fanta/.local/lib/python3.5/site-packages/xgboost-0.7-py3.5.egg, outside environment /home/fanta/.local/python3.5
I am using virtualenv under Ubuntu 16.04.

Packages installed manually with python setup.py install shouldn't be uninstalled with pip uninstall. You have to remove files and directories yourself. Remove /home/fanta/.local/lib/python3.5/site-packages/xgboost-0.7-py3.5.egg.
Next time you could install things with pip install . in the source code directory.

Related

How to avoid pip install package again while conda install was done before?

guys:
I use conda install tensorflow-gputo install tensorflow 2.0 , and
numpy=1.20.2 would be one of the package installed, and then I use python3 -m pip install SOMEPACKAGE ,this SOMEPACKAGE needs numpy to be installed as well , but pip seems does not check or realize the package numpy has already installed...
I would like to show everything I know so far :
1.I know the packages installed via conda install would go to anaconda3/envs/YOUR_ENV/lib/site-packages
2.I use python3 -m pip install -t anaconda3/envs/YOUR_ENV/lib/site-packages to force the package would be installed to the place where conda install would be.
However,pip still tries to dwonload *.whl file and install package again,I do not want this package installation process happen again ,while it did mention that I can use --upgrade to replace the existed package...
So I would like to know
How does pip and conda install check if the target package has already existed before they actually to through install process?
I think using python3 you are not using interpreter from your current conda environment so it gets installed elsewhere
python -m pip install (or simply pip install) from your activated environment should work and ignore dependencies installed by conda if they satisfy the requirements

how to install opencv and run first program in anaconda3 5.0.0 python 3.6.2 version?

I tried using
pip install opencv-python
It says to not break the installation rules and that I should use the conda command. How to install opencv and run first program on it in anaconda3 5.0.0 and python 3.6.2?
Ideall you shouldn't mix conda installed and pip installed packages - it confuses the dependencies when it comes to updates. Although you can use pip install opencv-python and opencv will work perfectly well within anaconda.
Instead you need to select opencv3 (assuming you want v3) from a specific repository
conda install -c menpo opencv3
ps. I don't know why it isn't included as standard and why have to know/search for the specific repository!

Tensorflow installation on Windows 10, error 'Not a supported wheel on this platform'

This question is for a Windows 10 laptop. I'm currently trying to install tensorflow, however, when I run:
pip install --ignore-installed --upgrade https://storage.googleapis.com/tensorflow/windows/cpu/tensorflow-1.0.0-cp35-cp35m-win_x86_64.whl
I get the following error:
tensorflow-1.0.0-cp35-cp35m-win_x86_64.whl is not a supported wheel on this platform.
I am trying to install the cpu-version only of tensorflow in an Anaconda 4.3.0 version. I had python 3.6.0 and then I downgraded to 3.5.0, none of them worked.
I also had same problem when I installed anaconda 4.3 version
Here is my solution.
Instead of using Anaconda3 4.3, install Anaconda3 4.2(Anaconda3-4.2.0-Windows-x86_64.exe)
Type on command line(If you are using GPU version)
pip install -U --ignore-installed --upgrade https://storage.googleapis.com/tensorflow/windows/gpu/tensorflow_gpu-1.0.0-cp35-cp35m-win_amd64.whl
Typeon command line(If you are using CPU only)
pip install -U --ignore-installed --upgrade https://storage.googleapis.com/tensorflow/windows/cpu/tensorflow-1.0.0-cp35-cp35m-win_amd64.whl
I'm working on win10 with python version=3.5.2, 64 bit
You can use same version of anaconda and execute this command
conda create -n tensorflow python=3.5
activate tensorflow
pip install tensorflow-gpu
It worked for conda 4.0.8
So are you sure you correctly downgraded your python? Run this command on command line pip -V. This should print the pip version and the python version.
Inside your Anaconda environment, try running this:
pip install --upgrade tensorflow
This will do the job. The issue was discussed here also.
Here is the screenshot of how this helped me:
If you have python3 on Windows insatalled, you can use the following command(non GPU):
pip install --upgrade https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-0.10.0-py3-none-any.whl
Worked for me.

Tensorflow installation error: not a supported wheel on this platform

when I try to install TensorFlow by cloning from Git, I run into the error "no module named copyreg," so I tried installing using a virtualenv. However, I then run into this error:
pip install https://storage.googleapis.com/tensorflow/mac/tensorflow-0.5.0-py2-none-any.whl
tensorflow-0.5.0-py2-none-any.whl is not a supported wheel on this platform.
I don't see this under the common problems section.
I am using OS X v10.10.5 (Yosemite) and Python 3.4.3, but I also have Python 2.7 (I am unsure if pip differentiates between these or how to switch between them).
I too got the same problem.
I downloaded get-pip.py from https://bootstrap.pypa.io/get-pip.py and then ran python2.7 get-pip.py for installing pip2.7.
And then ran the pip install command with python2.7 as follows.
For Ubuntu/Linux:
python2.7 -m pip install https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.5.0-cp27-none-linux_x86_64.whl
For Mac OS X:
python2.7 -m pip install https://storage.googleapis.com/tensorflow/mac/tensorflow-0.5.0-py2-none-any.whl
This should work just fine as it did for me :)
I followed these instructions from here.
After activating the virtualenv, be sure to upgrade pip to the latest version.
(your_virtual_env)$ pip install --upgrade pip
And now you'll be able to install TensorFlow correctly (for Linux):
(your_virtual_env)$ pip install --upgrade https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.7.0-py2-none-linux_x86_64.whl
I was trying to do the Windows-based install and kept getting this error.
It turns out you have to have Python 3.5.2. Not 2.7, not 3.6.x-- nothing other than 3.5.2.
After installing Python 3.5.2, the pip install worked.
Make sure that the wheel is, well, supported by your platform. Pip uses the wheel's filename to determine compatibility. The format is:
tensorflow-{version}-{python version}-none-{your platform}.whl
I didn't realize that x86_64 refers to x64, I thought it meant either x86 or x64, so I banged my head against this futilely for some time. TensorFlow is not available for 32-bit systems, unless you want to compile it yourself.
It seems that TensorFlow only works on Python 3.5 at the moment. Try to run this command before running the pip install
conda create --name tensorflow python=3.5
After this, run the following lines:
For CPU:
pip install --ignore-installed --upgrade https://storage.googleapis.com/tensorflow/windows/cpu/tensorflow-1.1.0-cp35-cp35m-win_amd64.whl
For GPU:
pip install --ignore-installed --upgrade https://storage.googleapis.com/tensorflow/windows/gpu/tensorflow_gpu-1.1.0-cp35-cp35m-win_amd64.whl
It should work like a charm.
On Windows 10, with Python 3.6.X version I was facing the same. Then after checking deliberately, I noticed I had Python-32 bit installation on my 64-bit machine. Remember TensorFlow is only compatible with a 64-bit installation of Python. Not 32 bit of Python
If we download Python from python.org, the default installation would be 32 bit. So we have to download the 64 bit installer manually to install Python 64 bit. And then add
C:\Users<username>\AppData\Local\Programs\Python\Python36
C:\Users<username>\AppData\Local\Programs\Python\Python36\Scripts
Then run gpupdate /Force on the command prompt. If the Python command doesn’t work for 64 bit, restart your machine.
Then run the Python interpreter on the command prompt. It should show 64 bit
python
Python 3.6.3 (v3.6.3:2c5fed8, Oct 3 2017, 18:11:49) [MSC v.1900 64 bit (AMD64)] on win32
Type "help", "copyright", "credits" or "license" for more information.
Then run the below command to install the TensorFlow CPU version (recommended)
pip3 install --upgrade tensorflow
The pip wheel file contains the Python version in its name (cp34-cp34m). If you download the .whl file and rename it to say py3-none or instead, it should work. Can you try that?
The installation won't work for Anaconda users that choose Python 3 support, because the installation procedure is asking to create a Python 3.5 environment and the file is currently called cp34-cp34m. So renaming it would do the job for now.
sudo pip3 install --upgrade https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow-0.7.0-cp34-cp34m-linux_x86_64.whl
This will produce the exact error message you got above. However, when you will download the file yourself and rename it to "tensorflow-0.7.0-py3-none-linux_x86_64.whl", then execute the command again with the changed filename, it should work fine.
For Windows 10 64 bit:
I have tried all the suggestions here, but finally I got it running as follows:
Uninstall all current versions of Python
Remove all Python references in the PATH system and user environment variables
Download the latest 64-bit version of Python 3.8: Python 3.8.7 currently, not the latest 3.9.x version which is the one I was using, and not 32 bit.
Install with all options selected, including pip, and including the PATH environment variable
pip install tensorflow (in an administrator CMD prompt)
Upgrade pip if prompted (optional)
Actually, you can use Python 3.5.*.
I successfully solved this problem with Python 3.5.3. Modify the Python version to 3.5.* in Conda. See Managing Python.
Then go to https://www.tensorflow.org/install/install_windows, and repeat from "Create a Conda environment named tensorflow by invoking the following command" bla, bla...
Maybe you are installing the wrong pre-build binary?
Check on https://github.com/lakshayg/tensorflow-build
For my Coffee Lake processor on Ubuntu 18.04 (Bionic Beaver) the download URL was:
https://github.com/lakshayg/tensorflow-build/releases/download/tf1.12.0-ubuntu18.04-py2-py3/tensorflow-1.12.0-cp36-cp36m-linux_x86_64.whl
pip install --ignore-installed --upgrade <PATH>
resolved the issue for me.
I was trying to install from source and got that error. (Why would a wheel built on this machine not be compatible with it?)
For me, the tag --ignore-installed made all the difference.
pip install --ignore-installed /tmp/tensorflow_pkg/tensorflow-1.8.0-cp36-cp36m-linux_x86_64.whl
worked, while
pip install /tmp/tensorflow_pkg/tensorflow-1.8.0-cp36-cp36m-linux_x86_64.whl
threw the abovementioned error.
Context: Conda environment; it might have been a problem specific to this
I was trying to install CPU TensorFlow on Ubuntu 18.04 (Bionic Beaver), and the best way (for me...) I found for it was using it on top of Conda, for that:
To create a Conda ‘tensorflow’ environment. Follow How to Install Anaconda on Ubuntu 18.04
After all is installed, see Getting started with conda. And use it according to Managing environments
conda create --name tensorflow
source activate tensorflow
pip install --upgrade pip
pip uninstall tensorflow
For CPU: pip install tensorflow-cpu, for GPU: pip install tensorflow
pip install --ignore-installed --upgrade tensorflow
Test TF E.g. on 'Where' with:
python
import tensorflow as tf
>>> tf.where([[True, False], [False, True]])
Expected result:
<tf.Tensor: shape=(2, 2), dtype=int64, numpy=
array([[0, 0],
[1, 1]])>
After the Conda upgrade, I got:
DeprecationWarning: 'source deactivate' is deprecated. Use 'conda deactivate'.
So you should use:
‘conda activate tensorflow’ / ‘conda deactivate’
I faced the same issue and tried all the solutions that folks suggested here and other links (like Platform not supported for TensorFlow on Ubuntu 14.04.2).
It was so frustrating because using print(wheel.pep425tags.get_supported()) I could see that my Ubuntu supported ('cp37', 'cp37m', 'linux_x86_64') and that was exactly what I was trying to install (from https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.14.0-cp37-cp37m-linux_x86_64.whl).
What at the end fixed it was to simply download the package first and then
pip install tensorflow-1.14.0-cp37-cp37m-linux_x86_64.whl
It means that the version of your default Python interpreter (python -V) and the version of your default pip (pip -V) do not match. You have built TensorFlow with your default Python interpreter and trying to use a different pip version to install it.
In Mac, delete /usr/local/bin/pip and rename (copy) pipx.y (whatever x.y version that matches your Python version) to pip in that folder.
This worked for me.
system requirement Python 3.7–3.10
macOS 10.12.6 (Sierra) or later (no GPU support)
pip install tensorflow-macos

I have installed virtualenv 1.9 which includes pip, but cannot install nltk

I have installed virtualenv 1.9 which includes pip, but cannot install nltk on my Mac. First it does not recognize pip as a command. Second how do I install nltk?
You should be able to run the following command to setup the virtual environment:
$ virtualenv venv
New python executable in venv/bin/python
Installing setuptools.............done.
Installing pip...............done.
Then activate the virtual environment using:
$ source venv/bin/activate
Then install nltk:
(venv)$ pip install nltk
When you are done with the virtual environment run:
$ deactivate
You may want to try installing Python using Homebrew rather than using the Python version included with the OS. With 'brew' you will not need to use virtualenv (unless you want to) because brew installs packages to /usr/local owned by you. So you can simply run 'pip install '.
Follow the installation instructions here for Homebrew. Then run:
$ brew install python
$ pip install nltk
You can install virtualenv as well if you want it.
$ pip install virtualenv

Resources