2 pip are installed one is v 9 and other is v 19
how to update the pip to the latest version 19?
I m unable to download some packages due to this version conflict.
and I want only one latest pip version should be instaled, and it will be used in all the packages.
You have two different versions of python and pip installed. This is common.
/usr/local/lib/python2.7/dist-packages/pip was most likely installed by the operating system, and allows you to sudo pip install Python 2.7 packages.
/home/manish/.local/lib/python3.5/site-packages/pip is in your home folder, which means you shouldn't have to elevate your user privileges to pip install a package. This is for Python 3.5.
Managing Python versions and dependencies can be massively confusing, especially if you're just trying to follow along with a tutorial.
The best tool I can recommend to make sense of this is pyenv. It lets you install any version of python in your home folder, and allows you to switch between on a per-project (folder) basis by creating a .python-version file. pyenv.
Related
In my environments created with anaconda, the same packages installed with conda are not compatible when I try to install with pip.
Is there a difference how pip and conda handle dependencies?
Here an example of requirements.txt
# Python version 3.9.13
django==2.2.5
djangorestframework==3.14.0
gensim==4.1.2
joblib==1.1.1
nltk==3.7
numpy==1.21.5
openpyxl==3.0.9
pandas==1.4.4
pickleshare==0.7.5
scikit-learn==1.1.3
seaborn==0.12.0
spacy==3.3.1
tensorflow==2.9.1
unidecode==1.2.0
conda allows you to create the environment, pip reports incompatibility between django and djangorestframework.
Conda checks, if all packages that will end up in the environment are compatible with each other and tries to find the optimal solution - considering all package versions.
Pip is less strict and only checks, if the new package is compatible with the existing ones. It doesn't change versions of the previously installed packeages.
Pip installs packages from from pypi.org, while conda installs from anaconda.org. The packages are not exactly the same, since the Anaconda staff authors new packages and tries to increase their compatibility with the older ones.
However, sometimes you are not interested in 100% compatibility but just want to use the latest features. Then pip is good enough because your unit tests will tell you if something goes wrong.
libdoc2testbench is a tool of Robot Framework which supports importing test results to imbus testbench. Due to Robot Framework documentation, it is to be installed by
pip install robotframework-libdoc2testbench
I want to install it on Ubuntu 18.04; there I get the error:
Could not find a version that satisfies the requirement robotframework-libdoc2testbench (from versions: )
No matching distribution found for robotframework-libdoc2testbench
Best regards
Gerhard
You are probably calling pip from Python 2.7.
Make sure you use Python 3, for example with:
python3 -m pip install robotframework-libdoc2testbench
EDIT: You can download the .wheel or source tar from pypi.org and install with pip pointing to it (and then if needed, download other required packages).
However the solution to your problem is the Python version. From the project page, we see it needs Python 3.7.
I tried to install a certain python module that required python 3.6 minimum to work properly so I checked my version using python --version which gave me the output of Python 2.7.17 and then used python3 --version giving me Python 3.6.9. Now, I know for a fact that i have Python 3.8 installed because I ran apt install python3.8 just before checking the version.
If someone wants to know what my system is running; I am currently running Elementary OS 5.1.7 Hera.
EDIT:
(IDK what term to use, I want to say I am done going through answers, and I liked none.)
After a while of whacking my brain, I decided not to uninstall the 3.6 version as It may have version specific modules which if removed may cause other installed programs to break.
Since I just use Linux for my college-work, It wont matter if more than one versions are installed anyway.
Sorry for any mistakes I may have made, I was never good at this kind of things.
Use conda to install and manage different versions of Python (or lots of other software, for that matter). Install different Python versions in separate conda environments. For example:
Find what python versions are available:
conda search python
Output (as of the time of writing, in the future I expect that the latest Python versions will be higher):
Loading channels: done
# Name Version Build Channel
python 1.0.1 0 conda-forge
python 1.2 0 conda-forge
...
python 3.9.0 h88f2d9e_1 pkgs/main
python 3.9.0 ha017127_4_cpython conda-forge
Install the Python versions you need in separate environments. Here, install Python 3.9.0 in environment named python39:
conda create --name python39 python=3.9.0
Switching environments is easy:
conda activate python39
# python is now 3.9.0
conda deactivate
# back to the default python
or (deprecated now):
source activate python39
source deactivate
SEE ALSO:
conda docs: Managing environments
This question is more appropriate for Unix & Linux.
Python installations (more generally, versioned installations of software) co-exist on linux using version numbers. You can likely run Python 3.8 using the python3.8 command (or else, locate where you installed it and run from there / add the location to the PATH environment variable to run directly).
Likewise, for each python version you can install its own package manager (e.g. install pip3.8 by python3.8 -m pip install pip) and use it to install packages for that python version. (As different projects require different sets of packages, the general practice is to create a "virtual environment", i.e. a separate copy of the needed version of python, pip and their package installation folders for each project, and install the required packages there - for more information see e.g. this excellent answer).
Regarding the command python3 (usually /usr/bin/python3) is just a symbolic link, you can replace it with the version you like (as long as it remains compatible with what the system expects - i.e. python3 of version no less than your built-in python3/python3-minimal, otherwise you will probably break something), e.g. assuming which python3 gives you /usr/bin/python3, you can
sudo rm /usr/bin/python3 #remove existing link
sudo ln /usr/bin/python3.8 /usr/bin/python3 # create a new link to the version of your choice
(although a better alternative could be instead aliasing it alias python3='/usr/bin/python3.8' and adding this to ~/.bashrc).
Whatever you do, do not uninstall python3-minimal as it is - at least, on Ubuntu - required by the system and uninstalling or changing it will likely break the system.
The GPU cluster I'm working off of includes both python 2.7 and python 3.5. pip and easy_install are both provided to allow local modules to be installed to a .local directory. For whatever reason, pip3 is not installed.
How can I install python 3 modules without root access given that pip3 is unavailable?
Thanks
Pycharm community is a free IDE. You can install pycharm first. And then, use pycharm to install other modules.
Some things you should know before I ask my question:
I am utterly new to both Linux & Python, and have a hard time understanding official documentation and technical answers (but have a burning desire to deeply understand both)
I am running elementary OS 0.4.1 Loki
My Python 3 version is 3.5.2. When I search the online documentation on the venv module for python 3.5.2, I get the documentation for the 3.5.6 version. I don't understand why there is no documentation for the .2 version.
So, here's my problem. I was trying to create a virtual environment using venv and proceeded thusly:
According to Python's 3.5.6 venv module documentation, a virtual environment is created using the command pyvenv /path/to/new/virtual/environment. I tried that command and got:
The program 'pyvenv' is currently not installed. You can install it by typing: sudo apt install python3-venv
I then searched documentation for newer Python versions and tried the new venv command python3 -m venv /path/to/new/virtual/environment and got the following result:
The virtual environment was not created successfully because ensurepip is not available. On Debian/Ubuntu systems, you need to install the python3-venv package using the following command. apt-get install python3-venv
In both cases, the solution seems to be to install python3-venv. My question is: What exactly am I installing by installing python3-venv: Isn't venv already part of the Standard Library? Furthermore, why do I have to install it via apt-get if it is a Python module? It is my understanding that standard library modules are imported, not installed; and that modules external to the standard library are installed via pip. Related to this, why is ensurepip not available?
Second part of my question: if installing python3-venv is the way to go, what is the proper way to create a virtual environment using venv in Python 3.5.2: pyvenv my_virtual_environment or python3 -m venv my_virtual_environment?
Don't worry about the documentation not matching the micro version number – increments in that place are only for bugfixes, so the documentation stays the same.
Your question is interesting since venv is indeed not an optional module. My guess is that the Python version shipped with your OS (or that you installed yourself) seems to come with a stripped down or no standard library. For instance, the python3.5-minimal package doesn't appear to have it. Does your Python have the other modules in the standard library?
Edit: See also this question.
Installation can be described as "putting files onto your computer, in the right place". Importing a module, however, means that you tell Python to make available some functionality. To import a module, it must be installed (e.g. in /usr/lib/python3.5 for Python 3 on my computer), and one method for installing additional modules is via apt.
The python3 -m venv my_virtual_environment method should work in 3.5 as well and is the future-proof version, so you should probably go with that.