The command line program conda is both a package manager and an environment manager, to help data scientists ensure that each version of each package has all the dependencies it requires and works correctly. That is, it can downgrade a package, if it leads to the overall satisfiability of packages. It no longer hangs or bails with no hint. I have a collection of packages that cannot be installed together. This is combinatorially a lot of possibilities. The problem is that after update the Conda I try get Updates I get only old versions of packages even in Intel channel : conda: 4.
So, please try the statement above to install the specific conda version you want and send us the response if it is unsuccessful. In your Terminal window or an Anaconda Prompt, run: If a package is not available from conda or Anaconda. This problem is already solved pretty well, although I of course am always interested in learning about new ways to solve it or similar problems. Once closed, if there are problems in future, is there a way to re-open the thread so it helps with the context? Anaconda is for people who want a stable set of packages that just work. If all else fails, a hackish way use a python package installed in any directory is to add it to sys. In Navigator I can see that there are several individual packages that can be updated, but also an anaconda package that sometimes has a version number and sometimes says custom. Thanks to the conda package cache and the way file linking is used, doing this is typically fast and consumes very little additional disk space.
I do plan on implementing some stuff which should make this whole issue go away basically, allow update --all to decide that a package should be removed instead of updated , but it will take some time to complete. In order to run, many scientific packages depend on specific versions of other packages. If there are instances of pip installed both inside and outside the current conda environment, the instance of pip installed inside the current conda environment is used. So my question is, is there a miniconda equivalent to updating all packages, or am I stuck with conda update --all which takes all of eternity to run. You can install pip in the current conda environment with the command conda install pip, as discussed in.
You can use it to find the packages you want, install them in an environment, run the packages and update them, all inside Navigator. But I guess the discussion is about how to generate a hint as to which constraint s is are causing the problem. But I guess the discussion is about how to generate a hint as to which constraint s is are causing the problem. An example of this is the anaconda metapackage, which specifies the exact versions in the Anaconda installer. Jupyter Notebooks are an increasingly popular system that combine your code, descriptive text, output, images and interactive interfaces into a single notebook file that is edited, viewed and used in a web browser.
Andre, It is difficult to troubleshoot without a list of the exact commands you are issuing and the conda environment that is active. There is a way to generate an alternate hint, which is more difficult to read, but which can be generated much faster, even when there are a lot of packages to be installed. Assuming that it is a linear programming problem which I think it is. Because of the way conda works, this will normally be an impossible task if your environment has more than a few dozen packages in it. Best, Todd Thanks for help me.
To gain the benefits of conda integration, be sure to install pip inside the currently active conda environment, and then install packages with that instance of pip. The question was originally asked on. Conda attempts to install the newest versions of the requested packages. When you are using Intel Distribution for Python, I would advise to have the latest versions available only in intel channel, although the package versions are older than that ones available in defaults to avoid any conflicts in dependencies. The answer by sounds like it should work.
When re-installing it, I decided to try mini-conda instead of Anaconda. If you need an exact set of packages, create a conda environment to hold them. You can use 'defaults' to get the default packages for conda, and 'system' to get the system packages, which also takes. Follow me at to learn more on Raspberry Pi, Hadoop, Spring, Java, Windows, Spring Boot topics. The detail page displays the name of the channel. The simplest way is with Spyder.
But I guess long term, I will then probably only use that 2nd branch. I get this sample of Matplotlib site: import numpy as np import matplotlib. When I actually ran conda update --all on a system with just numpy, ipython, scipy, pandas and a few other packages, it ran in quite quickly. Can I for the future go for this strategy: pip install whatever conda update conda conda update --all and if I really run into problems, then do conda update conda conda update anaconda to downgrade everything to a consistent set? When it is selected there is a triangular marker on the right see image above, step 3. In iPython the Script works very well! The hint generation tries every combination of package removal until it finds one that works. It looks like it might be stuck at 57%.