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Fourth, download a GDAL wheel file and install it with pip. Third, try to reconcile any dependency issues. First, create a new environment and install GDAL before any other packages. If that doesn’t work there are few more things you can try to reconcile these problems.

#Conda install package for specific version of python code#

For example, the following code would create a conda environment with python version 3.8. The first thing I would try is to create a new conda environment and specify a python version.

There is a problem with your Anaconda installation.

There is a problem with your conda environment.

You are using a python version that doesn’t support the current GDAL release.

You have other modules installed that conflict with GDAL.

There are instances where the above method may not install GDAL correctly, or where GDAL may not work after being installed. Unfortunately, this method is not 100% foolproof. The GDAL distribution from conda-forge installs GDAL as part of the OSGEO library, which includes GDAL, OGR, and OSR. ModuleNotFoundError: No module named 'gdal' Your first instinct will be to type import gdal this will produce the following error. You will now see this symbol >, which indicates you have started the interactive session. From the command prompt type python (or python3 if you also have a version of Python 2 on your machine). Make sure you can import GDAL into an interactive session to confirm it has been appropriately installed.

If I ever get messages like this I either create a new environment to install GDAL or, if that doesn’t work, reinstall Anaconda. In my experience, it’s not worth trying to resolve these errors or resolve conflicts with any incompatible packages. Solving environment: failed with repodata from current_repodata.json, will retry with next repodata source.Ĭollecting package metadata (repodata.json): doneįound conflicts! Looking for incompatible packages.

Solving environment: failed with initial frozen solve. Collecting package metadata (current_repodata.json): done If you do not specify the channel and just use conda install gdal you will probably get something like the following. Make sure you specify the conda-forge channel using the -c flag. It is important to note that depending on the other modules you are using there could be discrepancies with GDAL’s requirements that prevent a successful install. Select the ‘yes’ option and GDAL will be installed in your environment. You should be given a prompt asking if you want to install/upgrade/downgrade the listed packages. Type the following code to perform the install. At the time of writing, GDAL is not available from the main install channel, so we’ll specify the conda-forge channel which contains a GDAL distribution. GDAL can be installed using the conda install command. At this point you’re ready to perform the GDAL installation. You should see (pygdal), or your environment’s name, to the left of the current working directory in the command prompt. Make sure your pygdal environment has been activated. conda activate pygdal Install GDAL with conda install Now activate the environment using conda activate env-name. Here, pygdal is the name of the environment that was created. To create an anaconda environment, enter the following code. I’ve run into trouble installing GDAL to the base environment, but haven’t had issues when I’ve created a new conda environment. Now, make sure you’re installing GDAL to an environment. If using Windows, you’ll need to have the Anaconda distribution directories added to your path variable or open the Anaconda Prompt (recommended).

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If you’re using Mac or Linux this will probably be your regular terminal window. You can check out the video at the end of this article for a demonstration.

#Conda install package for specific version of python how to#

This guide will demonstrate how to successfully install GDAL from the conda-forge channel to an Anaconda ( conda) environment. There are two reliable ways to install the GDAL python package: from the conda-forge channel using the conda installer or using pip to install a precompiled wheel. However, it is notoriously difficult to install. GDAL is a powerful package with a lot of functionality. The Geospatial Data Abstraction Library (GDAL) is a fundamental package for spatial analysis with Python.