(Imagine having to keep all of these updated and working compatibly with one another on your computer! This is the true utility of a conda environment it takes care of this for you. These are all the packages that conda installed to get NCO on my computer. This is an example for the ncl_stable environment. In Windows 8.1 and later versions, devices that include firmware to support specific TPM measurements for PCR7 the TPM can validate that Windows RE is a trusted operating environment and unlock any BitLocker-protected drives if Windows RE hasnt been modified. For NCO and other fairly specific software packages, conda will typically need the conda-forge channel. For packages with nothing under the “Channel” column, they were installed using the defaults channel. In the future, there will be new releases of Python and its modules, and the people in charge of the Anaconda distribution will work. This conveniently lists the packages installed in the current environment, their version and build information, and the channel used to install them. To see which channels were used to install your conda packages, type conda list. Note the -c in -c conda-forge means “channel.” What this does is tells conda to look in the “conda-forge” channel (which hosts a broader range of user-created packages and unofficial versions of packages within the defaults channel). You can name them anything you like, though. I just upgraded from Windows 10 to Windows 11 and wondered if I should update my version of Anaconda (installed in December 2020). I like to use the _stable suffix because it helps me mentally separate an environment related to NCO from the language itself. To create these environments yourself (base is the default, so no need to make that), follow the steps below. conda environmentīasmap (assuming you have cartopy in your base environment) I’ve learned the setup below works best for me. You could get away with combining some of them into the same one below (and I encourage you to try, because you’ll learn a lot about conda when you run into issues and have to resolve them). I typically keep at least four separate environments on a machine (in addition to the default), described below. That’s at least what I did, and I was able to finish projects that I had started with basemap but start new ones in cartopy. The solution: Install a separate cartopy environment to get used to it, and once you feel confident, change your base environment to cartopy and create a basemap_stable environment for basemap-specific tasks. Its replacement is officially cartopy, but when you try to install them both, their packages can conflict. For example, if you use basemap for plotting maps, you may have heard it’s being retired in the next couple years (see also this discussion). Installing an environment is also a great way to make the switch to a new Python library or package without breaking your installation for all your current scripts. This tells me that I currently only have a base environment, and it’s installed on my home directory at /Users/baird/miniconda3. The question had originally asked about StackOverflow. Below is a question that gets asked so mostly that I decidedly e would be helpful to publish an answer explaining the various ways in which Anaconda can be kept upward to date. Vcv076219:python-for-climate-scientists baird$ Found the answers in this useful station by Anaconda.
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