I have created a Azure Compute target and using the notebooks from it. I want to create a conda environment using Notebook Terminal and install my own packages and use it in AzureML experiment environment.
I had the same question and the answer can be found here: https://learn.microsoft.com/en-us/azure/machine-learning/how-to-access-terminal#add-new-kernels
The basic steps are:
Create your conda environment with the terminal
Activate the environment
conda install pip
conda install ipykernel
python -m ipykernel install --user --name newenv --display-name "Python (newenv)"
After reloading the portal you can select the kernel in the list.
Fist make sure we install conda using Notebook Terminal.
We can create an environment from existing conda environment. This make it easy to reuse your local interactive environment in Azure ML remote runs. For example, if we've created conda environment using
conda create -n mycondaenv
We can create Azure ML environment out of that conda environment using
myenv = Environment.from_existing_conda_environment(name="myenv", conda_environment_name="mycondaenv")
Related
I created a new python env using Anaconda Prompt by using the following steps:
conda create --name py3-TF2.0 python=3
conda activate py3-TF2.0
conda install tensorflow
pip install --upgrade tensorflow
pip install ipykernel
then i restarted anaconda and opened jupyter notebook.
The problem is when i open a new notebook and go to kernel to choose the new env i could not find the env i created (p3-TF2.0)
however, when I use conda info --envs, i find the new env created.
what is missing here?
thanks in advance
After activating the environment, try running:
python -m ipykernel install --user --name py3-TF2.0 --display-name "py3-TF2.0"
If this still isn't pointing to the correct environment (i.e. you can't import packages you know you installed in that environment), remove the py3-TF2.0 kernel that's broken with jupyter kernelspec remove py3-TF2.0.
Then run <your_path_to>/anaconda3/envs/py3-TF2.0/bin/python -m ipykernel install --user --name py3-TF2.0 --display-name "py3_TF2.0".
Additional help on Jupyter Kernels.
I have used !{sys.executable} -m pip install to install packages i want to use in my jupyter notebooks.
Now i also want to install some packaged by conda and use in the same notebooks.
This is the command i run and the error message
They ask us to create a separate conda environment. I am confused about this.
Do we need to create a new conda enviroment everytime we need new packages?
What is the correct way to install and access conda packages on jupyter python notebook?
You shouldn't in principle install from the jupyter notebook but from the terminal/cmd.
You can create an enviroment >conda create --name myenv
And activate it: >conda activate myenv
now everything you install will be restricted to myenv. for example conda install numpy
To use the packages in myenv in jupyter simply open jupyter with your enviroment active:
>conda activate myenv
>jupyter notebook
Note that you have to install jupyter in your enviroment too: conda install jupyter
I am about to program 2 different python projects on my computer, each of them is using a different version of a specific module (PyTorch), as well as modules from the latest anaconda.
I have already installed anaconda and found out that the solution is a virtual environment, however, I don't want to install all anaconda modules for each one of them, but use the already installed anaconda for both of them.
How do I do it?
You can use virtual environment which allows you to install specific packages (with specific version) and/or specific python version.
From the docs,
To create virutal environment called myenv
conda create -n myenv
# Create with specific python version
conda create -n myenv python=3.6
# Create with specific version of python and package
conda carete -n myenv python=3.5 pytorch=1.2
To use a virtual env, you have to activate it.
# Activating myenv
conda activate myenv
To deactivate a env, and fall back to default anaconda env,
# myenv
conda deactivate
conda activate base
# Anaconda default env is called base
To list available virtual env
conda env list
or
conda info --envs
I am trying to create a new empty evironment with conda using the command:
conda create -n name python=3.6
Then I activate the environment and export it with
conda env export > environment.yml
I have noticed that the generated yml files contains a lot of pip packages that I guess are installed system wide. I am a ROS user and all the python packages installed by ROS appear there. Is there a way to ensure that those pip packages are not included in my new environment?
Thanks a lot for your help.
Make sure that you created the environment not using
conda env create -n name python=3.6
but using instead the command
conda create -n name python=3.6
Using the first command will link all packages from your base environment.
Also note that your new environment will contain several default packages (such as Python 3.6, pip, etc.) if you use the flag python=3.6 when creating the environment.
I use conda created an environment called testEnv and activated it, after that I use the command jupyter notebook to call the jupyter editor. It works, but the problem is that, I can only create file in the root environment. How can I create file in testEnv environment?
Here are the steps what I have done:
$ conda create -n testEnv python=3.5 # create environmet
$ source activate testEnv # activate the environmet
(testEnv)$ jupyter notebook # start the jupyter notebook
Here are the result, which shows I can only create file with in "root" but not in "testEnv" (There is only Root, but no testEnv):
In the Tab Conda, I can see the testEnv, but how can I switch to it?
You have two options. You can install the Jupyter Notebook into each environment, and run the Notebook from that environment:
conda create -n testEnv python=3.5 notebook
source activate testEnv
jupyter notebook
or you need to install the IPython kernel from testEnv into the environment from which you want to run Jupyter Notebook. Instructions are here: http://ipython.readthedocs.io/en/stable/install/kernel_install.html#kernels-for-different-environments To summarize:
conda create -n testEnv python=3.5
source activate testEnv
python -m ipykernel install --user --name testEnv --display-name "Python (testEnv)"
source deactivate
jupyter notebook
The answer is that you probably shouldn't do this. Python virtualenvs and Conda environments are intended to determine the resources available to the Python system, which are completely independent of your working directory.
You can use the same environment to work on multiple projects, as long as they have the same dependencies. The minute you start tweaking the environment you begin messing with something that is normally automatically maintained.
So perhaps the real question you should ask yourself is "why do I think it's a good idea to store my notebooks inside the environment used to execute them."