I'm using anaconda for manage my Python's environments and I want to create an env with a python executable file as interpreter. I didn't find similar question on other topic.
To be more precise, I don't want to create an env like this :
conda create --name my_env python=3.6.9
I want to create an env with a pre-installed python interpreter, tell to anaconda where to find the python executable file in my machine (in my case /usr/bin/python3) and use it as the interpreter for the env. Is it possible?
The only way I can imagine accomplishing this would be to make your own build of the python package. Perhaps having a look at how Conda Forge does this might be informative, though you can likely do a very trimmed down version depending on where you expect to run it.
Otherwise, no, not possible, AFAIK.
Related
I need to downgrade from python 3.8 to python 3.6 for Tensorflow in a virtual environment
I usually create environment with python -m tempenv /path/to/venv
I noted from this article that you can specify the interpreter when creating a virtual environment
https://www.freecodecamp.org/news/installing-multiple-python-versions-on-windows-using-virtualenv/
But this requires downloading the interpreter separately
Is there a way to automatically do this in an elegant command or set of commands? So that it would download the needed version of Python (3.6) and the appropriate pip installation in the virtual environment folder?
You can only create a virtual environment for the version of Python you're using to create it with.
Having said that, if you need virtual environments for different version of Python (e.g. 3.8.x and 2.7.x), you can simply install both version of Python and use the appropriate one to create new virtual environments with that version of Python in it.
As suggested by #flakes, you can also package managers to further automate the process and avoid having to manually pick and install versions of Python to use - to your preference. Tools like pyenv can then make your life easier switching between versions of Python. However, then we're getting into opinions on what's better or easier - you can make it work with stock Python as suggested.
I have two pieces of code that require different versions of python and versions of packages. I have two conda environments that allow each piece of code to work separately. It seems impossible to create an environment that will support both of them. Is there a way to switch conda environment during the run (in python code), so that I could execute one part using one environment and the second part using the second environment in the same script? The form and format of the result of the first part is definitely supported by the second part, so I don't see a reason why it can't work.
I have had success using conda within a shell script that calls the python process. e.g. something along these lines
conda activate my_env_1
python some_process.py
conda deactivate
conda activate my_env_2
python some_process_2.py
conda deactivate
You will have to enable your shell to use conda. See this Python - Activate conda env through shell script
If you want to change the environments in the same code at the same time, unfortunately as far as I know that will be painful, or just impossible with one word. In order to fix this issue, just add the libraries that your other environment has into the one that you use mainly.
You can achieve this by opening either your cmd (commnand line prompt), or just anaconda prompt:
activate yourenvironment name
pip/pip3 install modulename
I was suggested to conda create a new environment for installing tensorflow
First question, in general:
Why do environment exist in conda or in Python ? (Why) is it preferable to install a new library in a new environment ?
Here, in practice:
After install conda shell says $conda activate test will activate the test environment. Does it mean i can't access the lib in Spyder unless i activate test in conda shell ? Do i need to restart python shell to see the lib ? I can't access the lib (no module named tensorflow) and I assume it has to do with python not finding the path.
After install conda shell says $conda activate test will activate the
test environment. Does it mean i can't access the lib in Spyder unless
i activate test in conda shell ? Do i need to restart python shell to
see the lib ? I can't access the lib (no module named tensorflow) and
I assume it has to do with python not finding the path.
Have you installed TF within the environment?
I haven't used Spyder in a while, but what usually happens is that you can start a program (like Spyder or Jupyter) from an environment if you have installed the application within it and the environment is active. (Some editors/IDE like VS Code lets you choose the environment for a specific project, once it is able to discover all the environments.)
And, also usually, though perhaps not always, you will not need to restart the shell to import a library, after installing it. It's best to refer to the specific library's installation instructions for details like this.
Virtual Environment is used to manage Python packages for different projects. Using virtual environment allows you to avoid installing Python packages globally which could break system tools or other projects. You can install virtual environment using pip.
For example, say you have two projects, and each requires a different version of Tensorflow. This is a real problem for Python since it can’t differentiate between versions in the “site-packages” directory. So both say V1.1 and V2.1 would reside in the same directory with the same name.
This also allows easy clean up, once you are done with the project just delete the virtual environment.
Checkout more, https://packaging.python.org/guides/installing-using-pip-and-virtual-environments/
I was required to install anaconda for a CS course and used spyder and Rstudio.
Then, for a different class I used pycharm.
When I type on the command line "python -V" I get:
Python 3.6.1 :: Anaconda 4.4.0 (x86_64)
and I have no idea why it relates the python version I have installed with Anaconda (and why not pycharm?). I understand that the OS runs python 2.7 (shouldn't I get that instead? and when I type python3 -V get which version of python 3 I have?) and when I use something like Pycharm or Spyder I can choose which version I want from the ones I have installed and use it within the program, not for the terminal.
I just want to have everything in order and under control. I don't think I understand what Anaconda really is (to me is like a program that has more programs in it...). How do I keep anaconda to itself ? 1313
Also, should the packages I installed through Terminal work on both pycharm and spyder/anaconda even though when I used pycharm I used python 3.5 and anaconda 3.6?
I think I need definitions and help to get everything in order in my head and the computer.
Pycharm is just an application to help you write code. Pycharm itself does not run python code. This is why in PyCharm, you need to set the interpreter for a project, which could be any python binary. In PyCharm, go to Preferences > Project > Project Interpreter to see where you would set the python environment being used for a given project. This could point to any python installation on your machine, whether that is the python 2.7 located at /usr/bin/python or a virtual environment in your project dir.
The industry standard way to "keep things in order" is to use what are called virtual environments. See here: https://docs.python.org/3/library/venv.html. A virtual environment is literally just a copy of a python environment (binaries and everything) so whatever directory you specify. This allows you to configure your environment to however you need in your project without interfering with other projects you might have. For example, say project A requires django 1.9.2 but project b requires 1.5.3. By having a virtual environment for each project, dependencies won't conflict.
Since you have python3.6, I would recommend going to you project directory in a terminal window. Running python -m venv .venv to create a hidden directory which contains a local python environment of whatever your 3.6 python installation. You could then set your project interpret to use that environment. to connect to it on the command line, run source .venv/bin/activate from where you created your virtual environment. run which python again and see that python is now referencing your virtual environment :)
If you are using a mac (which I believe you are from what you said about python2.7), what likely happened is that your anaconda installer put the Python bin directory on your PATH environment variable. Type in which python to see what the python alias is referencing. You can undo this if you want by editing your ~/.bash_profile file if you really want.
You are more or less correct about anaconda. It is itself another distribution of python and contains a load of common libraries/dependencies that tend to make life easier. For a lot of data analysis, you likely won't even need to install another dependency with pip after downloading anaconda.
I suspect this won't be all too helpful at first as it is a lot to learn, but hopefully this points you in the right direction.
Let me first outline my desired solution and then elaborate on a specific question how to achieve this state.
I'm soon starting two coding projects in python. I've used python before but never on such big projects. My ideal scenario would be to have a setup where I can run virtual environments and different python version for various project. Some research pointed me to virtualenv / virtualenvwrapper and pyenv. It seems using pyenv-virtualenv or pyenv-virtualenvwrapper there is a nice way to specify the virtualenvironment and python version for a specific project.
Question: Once I've setup a virtualenvironment and python version for a specific project, how easily could I switch in a later stage to a newer python version? Let's say I've started project A with python 3.4 and in one year in the future I would like to move everything to python 3.6. Is this possible in a neat way?
Sure:
$ rm -r my-python-3.4-env
$ virtualenv -p python3.6 my-python-3.6-env
$ source my-python-3.6-env/bin/activate
In other words, each virtual environment is just a folder with the necessary files in it. You "activate" an environment with the source .../activate command (in case of virtualenv) and you leave it just as easily. To switch to a different environment you simply create a new one with a specific Python executable and activate it.
What you want to be careful about is to keep your installation repeatable, meaning if you depend on external modules (which modern projects typically do), you don't want to install each dependency by hand and instead automate that. For instance, you create a setuptools setup.py file which lists your dependencies, and then have it install them into your new environment automatically:
$ source my-python-3.6-env/bin/activate
(my-python-3.6-env) $ python setup.py develop