anaconda update all possible packages

Question

I tried the conda search --outdated  there are lots of outdated packages  for example the scipy is 0 17 1 but the latest is 0 18 0  However  when I do the conda update --all  It will not update any packages   update 1  conda update --all --alt-hint  Fetching package metadata         Solving package specifications                All requested packages already installed    packages in environment at  home user opt anaconda2      update 2  I can update those packages separately  I can do conda update scipy  But why I cannot update all of them in one go

User · Answer

if working in MS windows  you can use Anaconda navigator  click on the environment  in the drop-down box  it s  installed  by default  You can select  updatable  and start from there

User · Answer

To update all possible packages I used conda update --update-all  It works

User · Answer

To answer more precisely to the question:

conda (which is conda for miniconda as for Anaconda) updates all but ONLY within a specific version of a package -> major and minor. That's the paradigm.

In the documentation you will find "NOTE: Conda updates to the highest version in its series, so Python 2.7 updates to the highest available in the 2.x series and 3.6 updates to the highest available in the 3.x series." doc

If Wang does not gives a reproducible example, one can only assist. e.g. is it really the virtual environment he wants to update or could Wang get what he/she wants with

conda update -n ENVIRONMENT --all

*PLEASE read the docs before executing "update --all"! This does not lead to an update of all packages by nature. Because conda tries to resolve the relationship of dependencies between all packages in your environment, this can lead to DOWNGRADED packages without warnings.

If you only want to update almost all, you can create a pin file

echo "conda ==4.0.0" >> ~/miniconda3/envs/py35/conda-meta/pinned
echo "numpy 1.7.*" >> ~/miniconda3/envs/py35/conda-meta/pinned

before running the update. conda issues not pinned

If later on you want to ignore the file in your env for an update, you can do:

conda update --all --no-pin

You should not do update --all. If you need it nevertheless you are saver to test this in a cloned environment.

First step should always be to backup your current specification:

conda list -n py35 --explicit

(but even so there is not always a link to the source available - like for jupyterlab extensions)

Next you can clone and update:

conda create -n py356 --clone py35

conda activate py356
conda config --set pip_interop_enabled True # for conda>=4.6
conda update --all

conda config

update:

Because the idea of conda is nice but it is not working out very well for complex environments I personally prefer the combination of nix-shell (or lorri) and poetry [as superior pip/conda .-)] (intro poetry2nix).

Alternatively you can use nix and mach-nix (where you only need you requirements file. It resolves and builds environments best.

On Linux / macOS you could use nix like

nix-env -iA nixpkgs.python37

to enter an environment that has e.g. in this case Python3.7 (for sure you can change the version)

or as a very good Python (advanced) environment you can use mach-nix (with nix) like

mach-nix env ./env -r requirements.txt

(which even supports conda [but currently in beta])

or via api like

nix-shell -p nixFlakes --run "nix run github:davhau/mach-nix#with.ipython.pandas.seaborn.bokeh.scikit-learn "

Finally if you really need to work with packages that are not compatible due to its dependencies, it is possible with technologies like NixOS/nix-pkgs.

User · Answer

TL DR  dependency conflicts  Updating one requires  by it s requirements  to downgrade another  You are right   conda update --all   is actually the way to go1  Conda always tries to upgrade the packages to the newest version in the series  say Python 2 x or 3 x     Dependency conflicts  But it is possible that there are dependency conflicts  which prevent a further upgrade   Conda usually warns very explicitly if they occur   e g  X requires Y  lt 5 0  so Y will never be    5 0  That s why you  cannot  upgrade them all   Resolving  To add  maybe it could work but a newer version of X working with Y   5 0 is not available in conda  It is possible to install with pip  since more packages are available in pip  But be aware that pip also installs packages if dependency conflicts exist and that it usually breaks your conda environment in the sense that you cannot reliably install with conda anymore  If you do that  do it as a last resort and after all packages have been installed with conda  It s rather a hack   A safe way you can try is to add conda-forge as a channel when upgrading  add -c conda-forge as a flag  or any other channel you find that contains your package if you really need this new version  This way conda does also search in this places for available packages   Considering your update  You can upgrade them each separately  but doing so will not only include an upgrade but also a downgrade of another package as well  Say  to add to the example above   X   2 0 requires Y  lt  5 0  X  lt  2 0 requires Y   5 0  So upgrading Y   5 0 implies downgrading X to  lt  2 0 and vice versa    this is a pedagogical example  of course  but it s the same in reality  usually just with more complicated dependencies and sub-dependencies   So you still cannot upgrade them all by doing the upgrades separately  the dependencies are just not satisfiable so earlier or later  an upgrade will downgrade an already upgraded package again  Or break the compatibility of the packages  which you usually don t want    which is only possible by explicitly invoking an ignore-dependencies and force-command  But that is only to hack your way around issues  definitely not the normal-user case     1 If you actually want to update the packages of your installation  which you usually don t  The command run in the base environment will update the packages in this  but usually you should work with virtual environments  conda create -n myenv and then conda activate myenv   Executing conda update --all inside such an environment will update the packages inside this environment  However  since the base environment is also an environment  the answer applies to both cases in the same way

User · Answer

Imagine the dependency graph of packages, when the number of packages grows large, the chance of encountering a conflict when upgrading/adding packages is much higher. To avoid this, simply create a new environment in Anaconda.

Be frugal, install only what you need. For me, I installed the following packages in my new environment:

pandas
scikit-learn
matplotlib
notebook
keras

And I have 84 packages in total.

User · Answer

I solved this problem with conda and pip    Firstly  I run   conda uninstall qt  and conda uninstall matplotlib and conda uninstall PyQt5  After that  I opened the cmd and run this code that   pip uninstall qt    pip uninstall matplotlib   pip uninstall PyQt5  Lastly  You should install matplotlib in pip by this code that pip install matplotlib

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