I downloaded spyder using the standalone installer and have since been using miniconda to install packages that don't already come pre-installed (e.g. astropy, matplotlib etc). The way I've been doing this is using the following block of code in the anaconda prompt and then changing the default environment in Spyder to the one I've set up
conda create -n spyder-env -y
conda activate spyder-env
conda install spyder-kernels MODULE -y
However, when I tried to install lmfit in a similar fashion, the prompt said the lmfit package was not available. I then tried using conda install -c conda-forge lmfit, which seemed to work, but when I tried to change the environment and subsequently restart the kernel, there was an issue matching the kernel to the environment. I was wondering if there was a standard way of installing lmfit using miniconda that allows the package to be imported?
Thanks
The recommended way to install lmfit is pip install lmfit.
I have no idea what is going on with the conda environment running your spyder kernel might be.
Related
This may be a silly simple question, but I couldn't find an answer in the documentation of Anaconda or elsewhere. I am a bit of a noob when it comes to Python and I am trying to install a package. The problem is generalizable to other packages.
specs
I am working on a macOS Catalina (10.15.5) and using Anaconda as my python environment (python2.7).
problem
I am attempting to install the package pyLDAvis in my python environment, but the package isn't available on Anaconda's environment manager, and pip or conda install isn't working on the Spyder shell. Do pip and conda installs only work on the Anaconda Prompt? The problem is that I have read that the Anaconda Prompt only exists on Windows, and I am on mac. How could I install packages (pip, conda, or else) on Anaconda?
Am I missing something?
Any help or pointers to documentation would be great! Thanks
Assuming you have conda already installed and your shell is properly configured, you can activate the base environment via
conda activate
You can also create a new environment, see manage-environments docs.
For more information than given below, see manage-pkgs docs.
In case of conda, after your environment is activated, you can then install a package via conda install <package name>, e.g. the package numpy
conda install numpy
In case of pip, after your environment is activated, you can then install a package via pip install <package name>, e.g. the package numpy
pip install numpy
I only do this if the package is not available via a conda channel.
If the package is also not available via pip, you can download the source and set the package up your self. Usually the package author describes how to set up his/her package.
Thanks Stefan for the suggestion! I struggled a bit because although conda was "already installed", my shell was indeed not "properly configured." I am writing here my solution because it may be a recurring theme for macOS users and had an easy fix.
Starting with macOS Catalina, macOS uses zsh and not bash as the default shell, and so calling conda on zsh had no effect. The error message was: -zsh: conda: command not found. I solved this by changing the default shell to bash by running the following command: chsh -s /bin/bash.
Now that the shell and conda are properly configured, I managed to use conda activate as you suggested Stefan.
Finally, the package pyLDAvis could not be installed by conda install pyldavis but was installed with pip install pyldavis.
Solved!
I need to use the pymc3 module which relies on theano. However, I witnessed some weird behavior for which I could not find a solution in the documentation and from general web-search.
When using pymc3, I got several problems with missing compilers. Using multiple web searches I found that I need to install:
conda install -c conda-forge m2w64-toolchain_win-64
conda install -c anaconda libpython
conda install mkl-service
Then pymc3 works. I would like to setup up a virtual environment. However, I would like my base environment to be clean and run my projects on virtual environments. So from a clean base, if I create a new environment, e.g. conda create -n temp python=3.7 and run the three lines above, then I get the following warning, when importing pymc3:
WARNING (theano.tensor.blas): Using NumPy C-API based implementation for BLAS functions.
If I instead run the line:
conda install -c conda-forge m2w64-toolchain_win-64
in my base environment and then setup a virtual environment and install these two in the venv:
conda install -c anaconda libpython
conda install mkl-service
The warning disappears.
Could someone give me an explanation of why this warning persistent if I do not run the tool-chain install in my base environment?
Any help is appreciated. I only use Python for data analysis and I am not very knowledgeable regarding the technical-stuff.
I am stuck on this installation of scikit-image (aka skimage). I tried multiple ways:
Installation from a git hub folder (using the requirements.txt)
Installation from a whl file
Installation with pip install scikit-image
All three trials failed during the import: import skimage
ImportError: cannot import name 'geometry'
It seems that scikit-image has not been built correctly.
Your install of scikit-image appears to be broken.
Try re-installing the package following the instructions at:
https://scikit-image.org/docs/stable/install.html
I went through internet but did not find solutions besides the ones above.
Does anyone went through that before?
One possibility seems to be to pip install with -egg, but I found that for Mac rather than Windows.
EDIT:
Hi everyone, so I found a solution but this is kind of very hard and I still don't understand why it did not work before.
I just:
uninstall anaconda
uninstall python
install python (3.8)
install Anaconda (I have trouble with Spyder now^^)
If you want to code for computer vision/Image processing/machine learning tasks, then it can be done in pycharm with conda environment very easily. There is no need to install python separately to run Anaconda.
First, download and install pycharm. Next, If you use windows then download Anaconda 64 bit python 3.7 version from here,
https://www.anaconda.com/distribution/#windows
You can find some details about managing environment and helpful links here,
How to create some environments for tensorflow in anaconda?
https://docs.conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html
Create a conda environment first using Anaconda Prompt command line,
conda create -n cvenv python=3.7
Now activate that environment using. By default base is activated.
conda activate cvenv
Next, install the packages you want,
conda install -c conda-forge scikit-learn
conda install -c conda-forge scikit-image
conda install -c conda-forge pillow
conda install -c conda-forge opencv
I use conda-forge packages as they are more recent. Finally, open pycharm and create a new project by selecting existing python interpreter in conda environment. If none exists then select,
Browse > Add Python Interpreter > Conda Environment > Interpreter > Browse > Anaconda3 installation folder > envs folder > cvenv folder > Python.exe
You can test by creating a python file and writing import skimage.
I have installed a fresh anaconda v4.4. I realized that python packages can be installed using both conda and pip. What is the effect of using pip to install python packages instead of conda when using anaconda? Will the pip-installed libraries cease to function? I am using python v3
EDIT: I don't think the question is a duplicate of What is the difference between pip and conda?
That question explains the difference between pip and conda but does not talk about the effect of using pip when conda can be used.
Everything might keep working if you use pip to install vs conda. However, Conda cannot manage dependencies that pip has installed - it cannot upgrade them, or remove them. More importantly, conda will install a package even if its already been installed with pip! Try this test:
conda create -n testenv python=3
conda activate testenv
pip install numpy
conda install scipy
You will see from the third command that conda will want to re-install NumPy, even though it has already been installed with pip. This can cause problems if there are C libraries whose linking is different, or something like that. In general, whenever possible, use conda to install packages into conda environments.
I know that there exists a link for installing Tensorflow for python 3.5 on
Windows Installation link. There also a similar question on StackOverflow link also, but it case when I use this command:
pip install --ignore-installed --upgrade https://storage.googleapis.com/tensorflow/windows/cpu/tensorflow-1.0.0-cp35-cp35m-win_x86_64.whl
But it said Wheel package needs to be updated. So I updated it using pip and ran the application once again. The output was
tensorflow-1.0.0-cp35-cp35m-win_x86_64.whl is not a supported wheel on this platform.
So how do I solve this problem ? Please help.
I've tried to install the cpu version of TensorFlow.
conda upgrade conda
conda upgrade --all
conda create -n tensorflow python=3.5.
activate tensorflow
conda install -c conda-forge tensorflow
This will create an "environment" that will contain all of your packages you need (the example above is just tensorflow) and you will be able to import that library while you are in that environment anaconda is really just used to manage packages and segregate projects that require different packages
When your finished with your environment, to close out use:
deactivate
these commands are slightly different on OSX/Linux so be sure to look them up if you are on a different operating system
If you are using TF for some machine learning then you will probably want these packages in your environment as well:
conda install pandas matplotlib jupyter notebook scipy scikit-learn
Place that line between (activate tensorflow) and (conda install)
The executable, Anaconda for python 3.5 is not available on the official website.
An alternative to downloading that version is to download the latest version of Anaconda(3.6 as of 9 May, 2017), open your cmd shell in windows and execute the following commands. Note that the activate command is not fully supported in Windows Powershell. Click here to see why.
conda create --name tensorflow python=3.5
activate tensorflow
conda install -c conda-forge tensorflow=1.0.0
The answer has been borrowed from Anaconda Public Google Group.