When using python 3.9, there appears to be an explicit conflict with gdal. This is just to let you know that I am once again having problems installing the most recent version of gmt (6.2.0) and cartopy at the same time using conda. Output in format: Requested package -> Available versionsĬartopy=0.18 -> numpy Here is the simplest way to reproduce this problem: conda create -n test python=3.8 cartopy=0.18 gmt=6.1.1Īnd if you care, here is the long output describing the dependencies UnsatisfiableError: The following specifications were found to be incompatible with each other: Some python packages install both cartopy and gmt, so this is a major nuisance. Cartopy and (py-)gmt are both popular packages for map projections, so it would be good to ensure that these can co-habitate together. It doesn’t look like the conda-forge feedstocks have changed for either of these packages, so it’s not obvious to me what has changed. However, about two days ago, dependency problems started to appear, and the only solution I found is to downgrade cartopy to v0.17. Overwrite the entire pip section of conda dependencies.I used to be able to install both gmt (v6.1.1) and cartopy (v0.18) using conda without any problems. Serialize conda dependencies object into a string. Save the conda dependencies object to file. If pin_sdk_version is set to true, pip dependencies of the packages distributed as a part of Azure Machine Learning Python SDK will be pinned to the SDK version installed in the current environment. User specified pip_packages dependencies will override the default values. If pip_packages is not specified, azureml-defaults will be added as the default dependencies. _dependencies=conda_depĪdd a Microsoft Cognitive Toolkit (CNTK) package. Print("Found workspace ".format(ws.name, ws.location))Ī pip package can also be added and the dependencies set in the Environment object.Ĭonda_dep.add_pip_package("pillow=6.2.1") Ws = Workspace(subscription_id="my-subscription-id",
The following example shows how to add a package using theįrom import MsiAuthentication See the repository for details on base image dependencies. For more information, see Understanding Conda Use the Conda version, as Conda packages typically come with pre-built binaries that make If your dependency is available through both Conda and pip (from PyPi), Which creates and caches a conda environment within which the experiment executes. During experiment submission, a preparation step is executed You can load an existing conda environment file or choose to configure and manage
0 kommentar(er)
