I am trying to update the h2o package. When I run conda list h2o, this package is shown as
Name Version Build Channel
h2o 3.34.0.3 pypi_0 pypi
When I run conda update h2o it tells me.
PackageNotInstalledError: Package is not installed in prefix.
prefix: /opt/conda/anaconda
package name: h2o
How do I update this package?
#cel has correctly answered in his comment, all the credit goes to her/him!
You can see the conda list output that the package channel is pypi, this means that the package has been installed using pip.
If you want to upgrade it in place. This seems to be the simplest solution however mixing conda and pip packages in a conda environment is not advised since it can lead to dependency issues.
pip install --upgrade h2o
# check your installation
pip check
# No broken requirements found.
If you wan to uninstall it and replace it by a conda package.
# uninstall it
pip uninstall h2o
# install it with conda
conda install -c conda-forge h2o
Note: I've used the conda-forge channel but you can choose to use the default channel.
Maybe a better / safer solution could be to create a new conda environment from scratch with a fresh version of the package.
# will create a new env called my-env and containing the latest
conda create -c conda-forge -n my-env h2o
You will need to add also the other packages you need.
I was trying to install pycryptodome, python-jose-cryptodome using pip within anaocnda3 environment.
I got this error:
ERROR: Failed building wheel for pycryptodome
I have tried many versions many solutions(latest versions, specified version, with python 3.8 or 3.7, using requirements text without cache and even alone installation) but nothing worked for me :(. Any solution?
While using pip in an anaconda environment is allowed and fine, issues may arise when using pip and conda together, this was clearly mentioned in the conda docs.
One of the best practices when installing packages in an anaconda environment is to use conda for search and install before using pip.
So instead of directly using pip, try to :
Search for pycryptodome in anaconda packages repo
conda search pycryptodome
pycryptodome is available in anaconda repo .
The next step is to install pycryptodome :
conda install -c anaconda pycryptodome
or if you want to use conda-foge channel :
conda install -c conda-forge pycryptodome
this should get pycryptodome installed into your env
To use a requirements.txt file with conda :
conda install --yes --file requirements.txt
Summary : Best Practices Checklist When Using Pip in a Conda Environment
Use pip only after conda
install as many requirements as possible with conda, then use pip
pip should be run with –upgrade-strategy only-if-needed (the default)
Do not use pip with the –user argument, avoid all “users” installs
Use conda environments for isolation
create a conda environment to isolate any changes pip makes
environments take up little space thanks to hard links
care should be taken to avoid running pip in the “root” environment
Recreate the environment if changes are needed
once pip has been used conda will be unaware of the changes
to install additional conda packages it is best to recreate the
environment
Store conda and pip requirements in text files
package requirements can be passed to conda via the –file argument
pip accepts a list of Python packages with -r or –requirements
conda env will export or create environments based on a file with
conda and pip requirements .
you can read more about this topic here on anaconda website, and on conda docs
This error raised while installing geopandas. I've looking for its solution on the web, but none of them really explain what happened and how to solve it..
This is the full error:
Collecting geopandas
Using cached https://files.pythonhosted.org/packages/24/11/d77c157c16909bd77557d00798b05a5b6615ed60acb5900fbe6a65d35e93/geopandas-0.4.0-py2.py3-none-any.whl
Requirement already satisfied: shapely in c:\users\alvaro\anaconda3\envs\tfdeeplearning\lib\site-packages (from geopandas) (1.6.4.post2)
Requirement already satisfied: pandas in c:\users\alvaro\anaconda3\envs\tfdeeplearning\lib\site-packages (from geopandas) (0.20.3)
Collecting fiona (from geopandas)
Using cached https://files.pythonhosted.org/packages/3a/16/84960540e9fce61d767fd2f0f1d95f4c63e99ab5d8fddc308e8b51b059b8/Fiona-1.8.4.tar.gz
Complete output from command python setup.py egg_info:
A GDAL API version must be specified. Provide a path to gdal-config using a GDAL_CONFIG environment variable or use a GDAL_VERSION environment variable.
----------------------------------------
Command "python setup.py egg_info" failed with error code 1 in C:\Users\Alvaro\AppData\Local\Temp\pip-install-oxgkjg8l\fiona\
pip install wheel
pip install pipwin
pipwin install numpy
pipwin install pandas
pipwin install shapely
pipwin install gdal
pipwin install fiona
pipwin install pyproj
pipwin install six
pipwin install rtree
pipwin install geopandas
here are the source links:
http://geopandas.org/install.html#installation
https://pip.pypa.io/en/latest/user_guide/#installing-from-wheels
https://www.lfd.uci.edu/~gohlke/pythonlibs/#numpy
If you still have problems, consider uninstalling the above (pip uninstall) and reinstalling.
I solved this problem by running the following commands:
pip install pipwin
pipwin install gdal
pipwin install fiona
pip install geopandas
Works successfully on Windows.
Geospatial Data Abstraction Library (GDAL) is a library designed for vector geospatial data formats. It's a prerequisite for installing Fiona, the Python API for OGR (which doesn't really stand for anything), which is in turn a prerequisite for Geopandas. On UNIX-like systems the gdal-config script tells Fiona stuff about your particular gdal installation.
It seems that your gdal-config is not in one of the usual places on your PATH, so Fiona was unable to find it.
If you're using Anaconda, best is to remove gdal with conda remove gdal and then do a fresh conda install geopandas.
As a general rule, if you're using Conda you should never use pip to install something inside it unless you're absolutely sure conda offers no support for it. (Many package can be found on conda by specifying the right channel - -c argument.) And specifically in the case of geopandas, the maintainers recommend using conda over pip, since pip requires you to install the dependencies correctly.
I had a lot of issues myself installing geopandas, mostly showing error when downloading fiona and gdal. I did every step above and did a conda install geopandas but failed. The only thing worked for me is to install fiona and gdal wheel separately.
go to the link by Christoph: gohlke:https://www.lfd.uci.edu/~gohlke/pythonlibs/#fiona
You can search for fiona and gdal wheel files. Make sure you choose the file as per your python version, if it is 3.7 then there would be cp37.
Download the file
go to command prompt, put cd and then pip install , install GDAL wheel file, then fiona, then just do pip install geopandas.
This solution worked for me.
To install gdal, I followed the following steps:
downloaded the version that satisfies my computer (64 bit) from
https://www.lfd.uci.edu/~gohlke/pythonlibs/ . The file was GDAL-3.1.4-cp37-cp37m-win_amd64.whl
Put the file in a folder on the desktop.
From cmd, i moved to that directory and executed python -m pip install GDAL-3.1.4-cp37-cp37m-win_amd64.whl
This is followed by installing fiona the same way: python -m pip install Fiona-1.8.18-cp37-cp37m-win_amd64.whl
For shapely, i executed conda install -c conda-forge shapely
After that, i was able to install keplergl as usual: pip install keplergl
install descartes: conda install -c conda-forge descartes (or python -m pip install descartes).
In this way, i didn't have to play around with the 'Environmental Variables' as this may affect other programs
Cheers..
Installing geopandas
Geopandas has very complex multi-language dependencies, some of which need to be built with consistent compiler versions across packages. Because of this, the geopandas docs recommend installing using conda in a new environment using conda-forge only. Here are some general best practices to keep in mind:
conda is the recommended installation method. You can install geopandas from pip or source, but it's going to be a bumpy ride and it's not recommended. If you're installing conda for the first time, I recommend you start with miniconda (or better yet miniforge, a conda-forge-first miniconda variant), not anaconda, to keep your base env lean.
When using conda, you should not mix and match conda channels.
When installing geopandas, try creating a fresh environment rather than installing into your base environment. If you have anaconda installed, it comes with a large number of packages from the "defaults" channel installed in your base environment. I recommend deleting anaconda and installing miniconda, then installing into a new environment.
Try to create a new environment with everything you plan to use all at once rather than iteratively modifying the environment. In other words, if you want to use geopandas with scikit_learn, folium, and rasterio, install them together with a single conda create command
As a last resort, delete your conda installation and re-install miniconda. Desperate times call for desperate measures, and this usually resolves gnarly installation nightmares.
To create a fresh conda environment in which you install all necessary dependencies at the same time, using the conda-forge channel:
conda create -n my-geopandas-env -c conda-forge geopandas [all other packages you need]
For example, I might set up an environment with something along the lines of...
conda create -n my-geopandas-env -c conda-forge python=3.9 \
ipython ipykernel geopandas scipy seaborn fiona matplotlib cartopy
Bundling your installations into a single environment creation step like this reduces the chance of packages falling out of sync. To speed this process up, you could first install mamba or mambaforge, a faster drop-in replacement for conda, into your base environment and then run the above commands with mamba instead of conda.
Generally, it's best to avoid installing much of anything in your base environment (cross-environment system utilities like mamba are some of the few exceptions). If you already have a complex base environment (maybe you started with anaconda rather than miniconda) this may be the time to delete your entire conda installation and start from scratch (I know that's terrifying... sorry! but it'll save you heartache in the future). mamba is great for speeding this process up.
Connecting your editor to the conda environment
Once you have installed all of the packages you need, activate your environment with conda activate my-geopandas-env. See the conda guide to managing environments for more info.
Jupyter/ipython
Some editors/IDEs including jupyter require additional packages - jupyter requires that ipython and ipykernel be installed in order to load the environment within the notebook or editor - that's why I included ipykernel in my list above. See the ipykernel docs for more info.
Other IDES
To link this environment to an IDE such as VSCODE, spider, etc., find the location of this python version with conda run -n my-geopandas-env which python then point your editor to this python executable. Check the docs of your specific editor to get more targeted info about how to set up a conda environment for use with your editor:
Spider: FAQ on using an existing environment and Spider wiki guide to working with packages and environments
VSCode: Using python environments in vscode
PyCharm: Configure a conda virtual environment
I don't have conda installed, then using just pip I followed these steps:
Download GDAL and Fiona wheels directly on:
GDAL: https://www.lfd.uci.edu/~gohlke/pythonlibs/#gdal
FIONA: https://www.lfd.uci.edu/~gohlke/pythonlibs/#fiona
Then:
pip install <gdal.whl>
pip install <fiona.whl>
In my case I did pip install GDAL-3.4.1-cp38-cp38-win_amd64.whl and Fiona-1.8.21-cp38-cp38-win_amd64.whl. Where cp38 stands for python 3.8.
After that you are able to install geopandas with pip as well.
pip install geo pandas
For me, the only solution was to install the ready binaries from here
https://www.lfd.uci.edu/~gohlke/pythonlibs/#gdal
Then just install locally
pip install GDAL-3.1.4-cp38-cp38-win_amd64.whl
One way in which I could install geopandas was through the Anaconda Navigator. Get into the environment and install the package 'geopandas'. After that I could import the geopandas package in spyder
I will add
!pip install descartes
to #JDOaktown list.
I started with pip install geopandas and got the error, but later tried with conda install --channel conda-forge geopandas and the error disappeared.
Successfully installed in RHEL 7.8.
It automatically downloaded the required packages. This might be helpful
Installing collected packages: certifi, pyproj, shapely, attrs, click, click-plugins, munch, cligj, fiona, geopandas
Successfully installed attrs-20.3.0 certifi-2020.11.8 click-7.1.2 click-plugins-1.1.1 cligj-0.7.0 fiona-1.8.17 geopandas-0.8.1 munch-2.5.0 pyproj-3.0.0.post1 shapely-1.7.1
If you want to install GDAL, Geopandas, Shapely, Fiona etc in a windows Virtual Environment download .whl files for all of them and first install GDAL using
pip install gdal-.whl
Following this command edit the activate.bat file in you venv\Scripts folder and add
GDAL_CONFIG = \venv\Lib\site-packages\osgeo
Then you can install rest using pip install
I started off with a clean environment gdal_test in Conda environments, but made the mistake of using the old activate gdal_test instead of conda activate gdal_test. This made Conda Environment resolving take forever, which is why I resolved to other methods at first.
Takeaway: let conda handle it, with a proper new environment.
I ran into this problem not with anaconda/windows, but with python:3.6 Docker image. Google search always led me to this question, so I think I will share how I resolve my issue in case others also end up here.
Based on here, you need to install system relevant packages in the Dockerfile before running pip install geopandas or pip install requirements.txt:
RUN apt-get update && apt-get install -y --no-install-recommends \
build-essential \
libatlas-base-dev \
libgdal-dev \
gfortran
The following worked on macOS:
brew install gdal --HEAD
Verify the installation by running gdal-config --version
Following that pip installation as normal worked without a problem.
I installed PyTorch with:
conda install pytorch torchvision cuda80 -c soumith
How do I uninstall and remove all PyTorch dependencies?
From the anaconda docs, you can uninstall with conda uninstall
Try
conda uninstall pytorch torchvision cuda80 -c soumith
Alternatively, the pytorch docs suggest
conda uninstall pytorch
pip uninstall torch
pip uninstall torch # run this command twice
Here's the correct set of commands according to CONTRIBUTING.md from the pytorch github repo:
Uninstall all existing pytorch installs
conda uninstall pytorch
pip uninstall torch
pip uninstall torch # run this command twice
You can also use
conda remove torch torchvision
Please note that this will remove the specified packages (here: torch and torchvision) and any other package which depends on torch and torchvision, if there're any.
P.S. conda uninstall is an alias to conda remove.
Perhaps #Schütze meant with "This does not remove all the files." that there are still files in the Anaconda\pkgs folder.
Mind that you can remove the tar.b2 and the folder of the now unused packages in Anaconda\pkgs. I uninstalled pytorch cuda version (because my display driver does not support cuda) and there were huge files there:
pytorch-1.5.0-py3.7_cuda102_cudnn7_0.tar.bz2
pytorch-1.5.0-py3.7_cuda102_cudnn7_0
cudatoolkit-10.2.89-h74a9793_1.conda
cudatoolkit-10.2.89-h74a9793_1
This makes 3 GB altogether! Either do this manually, or with a command:
to delete all unneeded packages:
conda clean --yes --packages --dry-run
to delete all unneeded tar.bz2 / conda
conda clean --yes --tarballs --dry-run
to delete all together
conda clean --yes --all --dry-run
First use parameter --dry-run to see what will happen. Afterwards, run without --dry-run.
This has cleaned about 3.5 GB of the used 7 GB disk space that was used by Anaconda\pkgs.
References:
How to uninstall all unused packages in a conda virtual environment? and
Anaconda Python: Delete .tar.gz in pkgs
You can safely delete the pytorch installation using the following conda command:
conda uninstall pytorch-cpu torchvision-cpu pytorch
I recently found a good tool!
pip install pip-autoremove
This tool can delete all the tools you need to delete. For example, if you need to delete the torch, then it can delete torchvision as well!
Usage: pip-autoremove [OPTION]... [NAME]...
Options:
--version show program's version number and exit
-h, --help show this help message and exit
-l, --list list unused dependencies, but don't uninstall them.
-L, --leaves list leaves (packages which are not used by any others).
-y, --yes don't ask for confirmation of uninstall deletions.
I need to run an older verion of PyTables, that is 2.3.1, in and Anaconda environment on Linux. But I cannot install it.
conda install -n myenv pytables=2.3.1
fails finding the appropriate version.
conda install -n myenv pytables=2
installs PyTables 2.4.0 successfully. But I need 2.3.1.
Also activating the environment and installing via pip does not work.
pip install tables==2.3.1
fails with the following error:
.. ERROR:: Could not find a local HDF5 installation.
You may need to explicitly state where your local HDF5 headers and
library can be found by setting the HDF5_DIR environment
variable or by using the --hdf5 command-line option.
Where can I find the HDF5 installation of Anaconda? And how do I pass the --hdf5 option to pip? I already tried
pip install tables==2.3.1 --install-option="--hdf5=/home/me/Programme/anaconda"
But it also fails with the same error as above.
You can try
env HDF5_DIR="/home/me/Programme/anaconda" pip install tables==2.3.1
It worked for me.
I was trying to install a completely different package with pip on a new conda environment when I got the same error.
conda install -c conda-forge pytables
This helped me to get rid of the error and successfully install the package.