I have Anaconda installed on my computer and I'd like to update it. 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. How do I proceed?
14 Answers
rootis the old (pre-conda 4.4) name for the main environment; after conda 4.4, it was renamed to bebase. source
What 95% of people actually want
In most cases what you want to do when you say that you want to update Anaconda is to execute the command:
conda update --all(But this should be preceeded by conda update -n base conda so you have the latest conda version installed)
This will update all packages in the current environment to the latest version -- with the small print being that it may use an older version of some packages in order to satisfy dependency constraints (often this won't be necessary and when it is necessary the package plan solver will do its best to minimize the impact).
This needs to be executed from the command line, and the best way to get there is from Anaconda Navigator, then the "Environments" tab, then click on the triangle beside the base environment, selecting "Open Terminal":
This operation will only update the one selected environment (in this case, the base environment). If you have other environments you'd like to update you can repeat the process above, but first click on the environment. When it is selected there is a triangular marker on the right (see image above, step 3). Or from the command line you can provide the environment name (-n envname) or path (-p /path/to/env), for example to update your dspyr environment from the screenshot above:
conda update -n dspyr --allUpdate individual packages
If you are only interested in updating an individual package then simply click on the blue arrow or blue version number in Navigator, e.g. for astroid or astropy in the screenshot above, and this will tag those packages for an upgrade. When you are done you need to click the "Apply" button:
Or from the command line:
conda update astroid astropyUpdating just the packages in the standard Anaconda Distribution
If you don't care about package versions and just want "the latest set of all packages in the standard Anaconda Distribution, so long as they work together", then you should take a look at this gist.
Why updating the Anaconda package is almost always a bad idea
In most cases updating the Anaconda package in the package list will have a surprising result: you may actually downgrade many packages (in fact, this is likely if it indicates the version as custom). The gist above provides details.
Leverage conda environments
Your base environment is probably not a good place to try and manage an exact set of packages: it is going to be a dynamic working space with new packages installed and packages randomly updated. If you need an exact set of packages then create a conda environment to hold them. Thanks to the conda package cache and the way file linking is used doing this is typically i) fast and ii) consumes very little additional disk space. E.g.
conda create -n myspecialenv -c bioconda -c conda-forge python=3.5 pandas beautifulsoup seaborn nltkThe conda documentation has more details and examples.
pip, PyPI, and setuptools?
None of this is going to help with updating packages that have been installed from PyPI via pip or any packages installed using python setup.py install. conda list will give you some hints about the pip-based Python packages you have in an environment, but it won't do anything special to update them.
Commercial use of Anaconda or Anaconda Enterprise
It is pretty much exactly the same story, with the exception that you may not be able to update the base environment if it was installed by someone else (say to /opt/anaconda/latest). If you're not able to update the environments you are using you should be able to clone and then update:
conda create -n myenv --clone base
conda update -n myenv --allIf you are trying to update your Anaconda version to a new one, you'll notice that running the new installer wouldn't work, as it complains the installation directory is non-empty.
So you should use conda to upgrade as detailed by the official docs:
conda update conda
conda update anacondaIn Windows, if you made a "for all users" installation, it might be necessary to run from an Anaconda prompt with Administrator privileges.
This prevents the error:
2ERROR conda.core.link:_execute(502): An error occurred while uninstalling package 'defaults::conda-4.5.4-py36_0'. PermissionError(13, 'Access is denied')
Open "command or conda prompt" and run:
conda update conda
conda update anacondaIt's a good idea to run both command twice (one after the other) to be sure that all the basic files are updated.
This should put you back on the latest 'releases', which contains packages that are selected by the people at Continuum to work well together.
If you want the last version of each package run (this can lead to an unstable environment):
conda update --all Hope this helps.
Sources:
6This is what the official Anaconda documentation recommends:
conda update conda
conda install anaconda=2021.11You can find the current and past version codes here.
The command will update to a specific release of the Anaconda meta-package.
I feel like (contrary to the claim made in the accepted answer) this is more what 95% of Anaconda users want imho: Upgrading to the latest version of the Anaconda meta-package (put together and tested by the Anaconda Distributors) and ignoring the update status of individual packages, which would be issued by conda update --all.
Here's the best practice (in my humble experience). Selecting these four packages will also update all other dependencies to the appropriate versions that will help you keep your environment consistent. The latter is a common problem others have expressed in earlier responses. This solution doesn't need the terminal.
Open Anaconda cmd in base mode:
Then use conda update conda to update Anaconda.
You can then use conda update --all to update all the requirements for Anaconda:
conda update conda
conda update --allIf you have trouble to get e.g. from 3.3.x to 4.x (conda update conda "does not work" to get to the next version) than try it more specific like so:
conda install conda=4.0 (or conda install anaconda=4.0)You should know what you do, because conda could break due to the forced installation. If you would like to get more flexibility/security you could use pkg-manager like nix(-pkgs) [with nix-shell] / NixOS.
9Yet, another answer:
conda update -n base conda -c anacondawhere -c your preferred channel or simply leave out.
I'm using Windows 10. The following updates everything and also installs some new packages, including a Python update (for me it was 3.7.3).
At the shell, try the following (be sure to change where your Anaconda 3 Data is installed). It takes some time to update everything.
conda update --prefix X:\XXXXData\Anaconda3 anacondaTo update your installed version to the latest version, say 2019.07, run:
conda install anaconda=2019.07In most cases, this method can meet your needs and avoid dependency problems.
Intro
This answer wraps up many answers and comments, it does not add new code, all credits go to the other answers, especially this answer that shows how to install the official release, fully in line with the docs.
In the following, the "docs" mean the official Anaconda documentation at Updating from older versions. It makes sense to read the docs, it is a short overview.
And since it will be used quite often, here is the definition of metapackage:
A metapackage is a very simple package that has at least a name and a version. It need not have any dependencies or build steps. Metapackages may list dependencies to several core, low-level libraries and may contain links to software files that are automatically downloaded when executed.
First step
As a first step before the anaconda install, you update conda:
conda update condaSecond step
As a second step, you have three choices: custom or official metapackage, or conda update --all.
1. Custom metapackage
If you are allowed to have the most recent custom metapackage (mind that this might not always be the best choice for standard packages with constrained dependencies), then you can use
conda install anacondaDocs:
There is a special “custom” version of the Anaconda metapackage that has all the package dependencies, but none of them are constrained. The “custom” version is lower in version ordering than any actual release number.
The starting point for the tests was the installed release 2021.05. After this, conda update anaconda and conda install anaconda both lead to the same new "downgraded custom version" of custom-py38_1, see at the bottom of the code blocks: version change of anaconda = 2021.05-py38_0 --> custom-py38_1. But using update leads to far more installed packages than install here:
update leads to more installation steps than install
(base) C:\WINDOWS\system32>conda update anaconda
Collecting package metadata (current_repodata.json): done
Solving environment: done
## Package Plan ## environment location: C:\Users\toeft\anaconda3 added / updated specs: - anaconda
The following packages will be downloaded: package | build ---------------------------|----------------- _anaconda_depends-2020.07 | py38_0 6 KB anaconda-custom | py38_1 36 KB anaconda-client-1.8.0 | py38haa95532_0 170 KB anaconda-project-0.10.1 | pyhd3eb1b0_0 218 KB astroid-2.6.6 | py38haa95532_0 314 KB astropy-4.3.1 | py38hc7d831d_0 6.1 MB attrs-21.2.0 | pyhd3eb1b0_0 46 KB babel-2.9.1 | pyhd3eb1b0_0 5.5 MB ... xlsxwriter-3.0.1 | pyhd3eb1b0_0 111 KB xlwings-0.24.7 | py38haa95532_0 887 KB zeromq-4.3.4 | hd77b12b_0 4.2 MB zipp-3.5.0 | pyhd3eb1b0_0 13 KB zope.interface-5.4.0 | py38h2bbff1b_0 305 KB zstd-1.4.9 | h19a0ad4_0 478 KB ------------------------------------------------------------ Total: 218.2 MB
The following NEW packages will be INSTALLED: _anaconda_depends pkgs/main/win-64::_anaconda_depends-2020.07-py38_0 cfitsio pkgs/main/win-64::cfitsio-3.470-he774522_6 charset-normalizer pkgs/main/noarch::charset-normalizer-2.0.4-pyhd3eb1b0_0 conda-pack pkgs/main/noarch::conda-pack-0.6.0-pyhd3eb1b0_0 debugpy pkgs/main/win-64::debugpy-1.4.1-py38hd77b12b_0 fonttools pkgs/main/noarch::fonttools-4.25.0-pyhd3eb1b0_0 gmpy2 pkgs/main/win-64::gmpy2-2.0.8-py38h7edee0f_3 libllvm9 pkgs/main/win-64::libllvm9-9.0.1-h21ff451_0 matplotlib-inline pkgs/main/noarch::matplotlib-inline-0.1.2-pyhd3eb1b0_2 mpc pkgs/main/win-64::mpc-1.1.0-h7edee0f_1 mpfr pkgs/main/win-64::mpfr-4.0.2-h62dcd97_1 mpir pkgs/main/win-64::mpir-3.0.0-hec2e145_1 munkres pkgs/main/noarch::munkres-1.1.4-py_0
The following packages will be REMOVED: jupyter-packaging-0.7.12-pyhd3eb1b0_0
The following packages will be UPDATED: anaconda-client 1.7.2-py38_0 --> 1.8.0-py38haa95532_0 anaconda-project 0.9.1-pyhd3eb1b0_1 --> 0.10.1-pyhd3eb1b0_0 astroid 2.5-py38haa95532_1 --> 2.6.6-py38haa95532_0 astropy 4.2.1-py38h2bbff1b_1 --> 4.3.1-py38hc7d831d_0 attrs 20.3.0-pyhd3eb1b0_0 --> 21.2.0-pyhd3eb1b0_0 babel 2.9.0-pyhd3eb1b0_0 --> 2.9.1-pyhd3eb1b0_0 bitarray 1.9.2-py38h2bbff1b_1 --> 2.3.0-py38h2bbff1b_1 bleach 3.3.0-pyhd3eb1b0_0 --> 4.0.0-pyhd3eb1b0_0 bokeh 2.3.2-py38haa95532_0 --> 2.3.3-py38haa95532_0 ca-certificates 2021.4.13-haa95532_1 --> 2021.7.5-haa95532_1 certifi 2020.12.5-py38haa95532_0 --> 2021.5.30-py38haa95532_0 cffi 1.14.5-py38hcd4344a_0 --> 1.14.6-py38h2bbff1b_0 click 7.1.2-pyhd3eb1b0_0 --> 8.0.1-pyhd3eb1b0_0 comtypes 1.1.9-py38haa95532_1002 --> 1.1.10-py38haa95532_1002 curl 7.71.1-h2a8f88b_1 --> 7.78.0-h86230a5_0 cython 0.29.23-py38hd77b12b_0 --> 0.29.24-py38hd77b12b_0 dask 2021.4.0-pyhd3eb1b0_0 --> 2021.8.1-pyhd3eb1b0_0 dask-core 2021.4.0-pyhd3eb1b0_0 --> 2021.8.1-pyhd3eb1b0_0 decorator 5.0.6-pyhd3eb1b0_0 --> 5.0.9-pyhd3eb1b0_0 distributed 2021.4.0-py38haa95532_0 --> 2021.8.1-py38haa95532_0 docutils 0.17-py38haa95532_1 --> 0.17.1-py38haa95532_1 et_xmlfile pkgs/main/noarch::et_xmlfile-1.0.1-py~ --> pkgs/main/win-64::et_xmlfile-1.1.0-py38haa95532_0 fsspec 0.9.0-pyhd3eb1b0_0 --> 2021.7.0-pyhd3eb1b0_0 gevent 21.1.2-py38h2bbff1b_1 --> 21.8.0-py38h2bbff1b_1 greenlet 1.0.0-py38hd77b12b_2 --> 1.1.1-py38hd77b12b_0 idna 2.10-pyhd3eb1b0_0 --> 3.2-pyhd3eb1b0_0 imagecodecs 2021.3.31-py38h5da4933_0 --> 2021.6.8-py38h5da4933_0 intel-openmp 2021.2.0-haa95532_616 --> 2021.3.0-haa95532_3372 ipykernel 5.3.4-py38h5ca1d4c_0 --> 6.2.0-py38haa95532_1 ipython 7.22.0-py38hd4e2768_0 --> 7.26.0-py38hd4e2768_0 isort 5.8.0-pyhd3eb1b0_0 --> 5.9.3-pyhd3eb1b0_0 itsdangerous 1.1.0-pyhd3eb1b0_0 --> 2.0.1-pyhd3eb1b0_0 jinja2 2.11.3-pyhd3eb1b0_0 --> 3.0.1-pyhd3eb1b0_0 json5 0.9.5-py_0 --> 0.9.6-pyhd3eb1b0_0 jupyterlab 3.0.14-pyhd3eb1b0_1 --> 3.1.7-pyhd3eb1b0_0 jupyterlab_server 2.4.0-pyhd3eb1b0_0 --> 2.7.1-pyhd3eb1b0_0 keyring 22.3.0-py38haa95532_0 --> 23.0.1-py38haa95532_0 krb5 1.18.2-hc04afaa_0 --> 1.19.2-h5b6d351_0 libcurl 7.71.1-h2a8f88b_1 --> 7.78.0-h86230a5_0 libxml2 2.9.10-hb89e7f3_3 --> 2.9.12-h0ad7f3c_0 lz4-c 1.9.3-h2bbff1b_0 --> 1.9.3-h2bbff1b_1 markupsafe 1.1.1-py38he774522_0 --> 2.0.1-py38h2bbff1b_0 matplotlib 3.3.4-py38haa95532_0 --> 3.4.2-py38haa95532_0 matplotlib-base 3.3.4-py38h49ac443_0 --> 3.4.2-py38h49ac443_0 mkl 2021.2.0-haa95532_296 --> 2021.3.0-haa95532_524 mkl-service 2.3.0-py38h2bbff1b_1 --> 2.4.0-py38h2bbff1b_0 mkl_random 1.2.1-py38hf11a4ad_2 --> 1.2.2-py38hf11a4ad_0 more-itertools 8.7.0-pyhd3eb1b0_0 --> 8.8.0-pyhd3eb1b0_0 nbconvert 6.0.7-py38_0 --> 6.1.0-py38haa95532_0 networkx 2.5-py_0 --> 2.6.2-pyhd3eb1b0_0 nltk 3.6.1-pyhd3eb1b0_0 --> 3.6.2-pyhd3eb1b0_0 notebook 6.3.0-py38haa95532_0 --> 6.4.3-py38haa95532_0 numpy 1.20.1-py38h34a8a5c_0 --> 1.20.3-py38ha4e8547_0 numpy-base 1.20.1-py38haf7ebc8_0 --> 1.20.3-py38hc2deb75_0 openjpeg 2.3.0-h5ec785f_1 --> 2.4.0-h4fc8c34_0 openssl 1.1.1k-h2bbff1b_0 --> 1.1.1l-h2bbff1b_0 packaging 20.9-pyhd3eb1b0_0 --> 21.0-pyhd3eb1b0_0 pandas 1.2.4-py38hd77b12b_0 --> 1.3.2-py38h6214cd6_0 path 15.1.2-py38haa95532_0 --> 16.0.0-py38haa95532_0 pathlib2 2.3.5-py38haa95532_2 --> 2.3.6-py38haa95532_2 pillow 8.2.0-py38h4fa10fc_0 --> 8.3.1-py38h4fa10fc_0 pkginfo 1.7.0-py38haa95532_0 --> 1.7.1-py38haa95532_0 prometheus_client 0.10.1-pyhd3eb1b0_0 --> 0.11.0-pyhd3eb1b0_0 pydocstyle 6.0.0-pyhd3eb1b0_0 --> 6.1.1-pyhd3eb1b0_0 pyerfa 1.7.3-py38h2bbff1b_0 --> 2.0.0-py38h2bbff1b_0 pygments 2.8.1-pyhd3eb1b0_0 --> 2.10.0-pyhd3eb1b0_0 pylint 2.7.4-py38haa95532_1 --> 2.9.6-py38haa95532_1 pyodbc 4.0.30-py38ha925a31_0 --> 4.0.31-py38hd77b12b_0 pytest 6.2.3-py38haa95532_2 --> 6.2.4-py38haa95532_2 python-dateutil 2.8.1-pyhd3eb1b0_0 --> 2.8.2-pyhd3eb1b0_0 pywin32 227-py38he774522_1 --> 228-py38hbaba5e8_1 pyzmq 20.0.0-py38hd77b12b_1 --> 22.2.1-py38hd77b12b_1 qtconsole 5.0.3-pyhd3eb1b0_0 --> 5.1.0-pyhd3eb1b0_0 qtpy 1.9.0-py_0 --> 1.10.0-pyhd3eb1b0_0 regex 2021.4.4-py38h2bbff1b_0 --> 2021.8.3-py38h2bbff1b_0 requests 2.25.1-pyhd3eb1b0_0 --> 2.26.0-pyhd3eb1b0_0 rope 0.18.0-py_0 --> 0.19.0-pyhd3eb1b0_0 scikit-learn 0.24.1-py38hf11a4ad_0 --> 0.24.2-py38hf11a4ad_1 seaborn 0.11.1-pyhd3eb1b0_0 --> 0.11.2-pyhd3eb1b0_0 singledispatch 3.6.1-pyhd3eb1b0_1001 --> 3.7.0-pyhd3eb1b0_1001 six pkgs/main/win-64::six-1.15.0-py38haa9~ --> pkgs/main/noarch::six-1.16.0-pyhd3eb1b0_0 sortedcontainers 2.3.0-pyhd3eb1b0_0 --> 2.4.0-pyhd3eb1b0_0 sphinx 4.0.1-pyhd3eb1b0_0 --> 4.0.2-pyhd3eb1b0_0 sphinxcontrib-htm~ 1.0.3-pyhd3eb1b0_0 --> 2.0.0-pyhd3eb1b0_0 sphinxcontrib-ser~ 1.1.4-pyhd3eb1b0_0 --> 1.1.5-pyhd3eb1b0_0 sqlalchemy 1.4.7-py38h2bbff1b_0 --> 1.4.22-py38h2bbff1b_0 sqlite 3.35.4-h2bbff1b_0 --> 3.36.0-h2bbff1b_0 testpath 0.4.4-pyhd3eb1b0_0 --> 0.5.0-pyhd3eb1b0_0 threadpoolctl 2.1.0-pyh5ca1d4c_0 --> 2.2.0-pyhbf3da8f_0 tifffile 2021.4.8-pyhd3eb1b0_2 --> 2021.7.2-pyhd3eb1b0_2 tqdm 4.59.0-pyhd3eb1b0_1 --> 4.62.1-pyhd3eb1b0_1 typed-ast 1.4.2-py38h2bbff1b_1 --> 1.4.3-py38h2bbff1b_1 typing_extensions 3.7.4.3-pyha847dfd_0 --> 3.10.0.0-pyh06a4308_0 urllib3 1.26.4-pyhd3eb1b0_0 --> 1.26.6-pyhd3eb1b0_1 wheel 0.36.2-pyhd3eb1b0_0 --> 0.37.0-pyhd3eb1b0_0 xlsxwriter 1.3.8-pyhd3eb1b0_0 --> 3.0.1-pyhd3eb1b0_0 xlwings 0.23.0-py38haa95532_0 --> 0.24.7-py38haa95532_0 zeromq 4.3.3-ha925a31_3 --> 4.3.4-hd77b12b_0 zipp 3.4.1-pyhd3eb1b0_0 --> 3.5.0-pyhd3eb1b0_0 zope.interface 5.3.0-py38h2bbff1b_0 --> 5.4.0-py38h2bbff1b_0 zstd 1.4.5-h04227a9_0 --> 1.4.9-h19a0ad4_0
The following packages will be DOWNGRADED: anaconda 2021.05-py38_0 --> custom-py38_1install leads to less installation steps than update:
(base) C:\WINDOWS\system32>conda install anaconda
Collecting package metadata (current_repodata.json): done
Solving environment: done
## Package Plan ## environment location: C:\Users\toeft\anaconda3 added / updated specs: - anaconda
The following packages will be downloaded: package | build ---------------------------|----------------- _anaconda_depends-2020.07 | py38_0 6 KB anaconda-custom | py38_1 36 KB ca-certificates-2021.7.5 | haa95532_1 113 KB certifi-2021.5.30 | py38haa95532_0 140 KB gmpy2-2.0.8 | py38h7edee0f_3 145 KB libllvm9-9.0.1 | h21ff451_0 61 KB mpc-1.1.0 | h7edee0f_1 260 KB mpfr-4.0.2 | h62dcd97_1 1.5 MB mpir-3.0.0 | hec2e145_1 1.3 MB openssl-1.1.1l | h2bbff1b_0 4.8 MB ------------------------------------------------------------ Total: 8.4 MB
The following NEW packages will be INSTALLED: _anaconda_depends pkgs/main/win-64::_anaconda_depends-2020.07-py38_0 gmpy2 pkgs/main/win-64::gmpy2-2.0.8-py38h7edee0f_3 libllvm9 pkgs/main/win-64::libllvm9-9.0.1-h21ff451_0 mpc pkgs/main/win-64::mpc-1.1.0-h7edee0f_1 mpfr pkgs/main/win-64::mpfr-4.0.2-h62dcd97_1 mpir pkgs/main/win-64::mpir-3.0.0-hec2e145_1
The following packages will be UPDATED: ca-certificates 2021.4.13-haa95532_1 --> 2021.7.5-haa95532_1 certifi 2020.12.5-py38haa95532_0 --> 2021.5.30-py38haa95532_0 openssl 1.1.1k-h2bbff1b_0 --> 1.1.1l-h2bbff1b_0
The following packages will be DOWNGRADED: anaconda 2021.05-py38_0 --> custom-py38_12. Official metapackage (= release)
In the following code snippets, update and install lead to the same results. I use install like in the docs.
If you do not want to install a custom version of the metapackage but rather need the most recent official release, install with
conda install anaconda=VersionNumberFind the VersionNumber
At the time of writing, in 09/2021, the latest available release (Anaconda individual edition) is
conda install anaconda=2021.05But how to get hold of this VersionNumber?
Have a look at the Anaconda Release notes of the individual edition. If you need an older version, you need to scroll down that page, for example to find 2020.11. The most recent is always on top of the page. If you use a commercial edition, you need to check other release notes.
Thus, something like the 2021.05 version code is the latest release shortcut that you need to find. You can also find the full version name of your OS like for example Anaconda3-2021.05-Windows-x86_64.exe in the list of available Anaconda versions that is directly linked in the docs. It is sorted by name and date, thus, you need to search for the year like "YYYY-MM" / "YYYY-" or scroll through the whole list to find the most recent versions:
For the example of Windows 10 64 bit, the command could as well be:
conda update anaconda=Anaconda3-2021.05-Windows-x86_64.exeIf you install a release after having installed the most recent custom metapackage, you will see some packages to be removed and quite many to be downgraded slightly. This is because the release is slightly back in time, but therefore also fully trusted.
Docs:
conda update anaconda=VersionNumbergrabs the specific release of the Anaconda metapackage, for exampleconda update anaconda=2019.10. That metapackage represents a pinned state that has undergone testing as a collection.
3. Do not use conda update --all
As to the docs (last sentence of the following quote below), installing the custom (= most recent) metapackage of 2019.07 can be done as well by running
conda update --alland if you have virtual environments, you need:
conda update -n myenv --allYET: This was probably an exception for 2019.07. It does not seem to hold for higher metapackage versions. I checked the differences of conda update --all against conda update anaconda on a row to row comparison (see below, after the quote). Although they seem like twins at first, there were enough small differences to say that you should keep your hands off conda update --all since possible conflicting constraints are even mentioned in the docs.
Docs:
conda update --allwill unpin everything. This updates all packages in the current environment to the latest version. In doing so, it drops all the version constraints from the history and tries to make everything as new as it can.This has the same behavior with removing packages. If any packages are orphaned by an update, they are removed. conda update --all may not be able to make everything the latest versions because you may have conflicting constraints in your environment.
With Anaconda 2019.07’s newer Anaconda metapackage, conda update --all will make the metapackage go to the custom version in order to update other specs.
The whole output, put against each other on a row to row base, reveals the following remaining row differences. This proves that conda update --all is not just the custom metapackage:
conda update --all output lines not found in conda update anaconda
(base) C:\WINDOWS\system32>conda update --all
The following packages will be downloaded: anaconda-navigator-2.0.4 | py38_0 5.2 MB conda-build-3.21.4 | py38haa95532_0 552 KB conda-content-trust-0.1.1 | pyhd3eb1b0_0 56 KB conda-repo-cli-1.0.4 | pyhd3eb1b0_0 47 KB conda-token-0.3.0 | pyhd3eb1b0_0 10 KB menuinst-1.4.17 | py38h59b6b97_0 96 KB python-3.8.11 | h6244533_1 16.0 MB Total: 224.8 MB
The following NEW packages will be INSTALLED: conda-content-tru~ pkgs/main/noarch::conda-content-trust-0.1.1-pyhd3eb1b0_0 conda-repo-cli pkgs/main/noarch::conda-repo-cli-1.0.4-pyhd3eb1b0_0 conda-token pkgs/main/noarch::conda-token-0.3.0-pyhd3eb1b0_0
The following packages will be UPDATED: anaconda-navigator 1.10.0-py38_0 --> 2.0.4-py38_0 conda-build 3.20.5-py38_1 --> 3.21.4-py38haa95532_0 et_xmlfile pkgs/main/noarch::et_xmlfile-1.0.1-py~ --> pkgs/main/win-64::et_xmlfile-1.1.0-py38haa95532_0 menuinst 1.4.16-py38he774522_1 --> 1.4.17-py38h59b6b97_0 python 3.8.8-hdbf39b2_5 --> 3.8.11-h6244533_1 six pkgs/main/win-64::six-1.15.0-py38haa9~ --> pkgs/main/noarch::six-1.16.0-pyhd3eb1b0_0 sphinxcontrib-htm~ 1.0.3-pyhd3eb1b0_0 --> 2.0.0-pyhd3eb1b0_0 sphinxcontrib-ser~ 1.1.4-pyhd3eb1b0_0 --> 1.1.5-pyhd3eb1b0_0conda update anaconda output lines not found in conda update --all
(base) C:\WINDOWS\system32>conda update anaconda added / updated specs: - anaconda
The following packages will be downloaded: cfitsio-3.470 | he774522_6 512 KB imagecodecs-2021.6.8 | py38h5da4933_0 6.1 MB jinja2-3.0.1 | pyhd3eb1b0_0 110 KB tifffile-2021.7.2 | pyhd3eb1b0_2 135 KB typed-ast-1.4.3 | py38h2bbff1b_1 135 KB Total: 209.8 MB
The following NEW packages will be INSTALLED: cfitsio pkgs/main/win-64::cfitsio-3.470-he774522_6
The following packages will be UPDATED: et_xmlfile pkgs/main/noarch::et_xmlfile-1.0.1-py~ --> pkgs/main/win-64::et_xmlfile-1.1.0-py38haa95532_0 imagecodecs 2021.3.31-py38h5da4933_0 --> 2021.6.8-py38h5da4933_0 jinja2 2.11.3-pyhd3eb1b0_0 --> 3.0.1-pyhd3eb1b0_0 six pkgs/main/win-64::six-1.15.0-py38haa9~ --> pkgs/main/noarch::six-1.16.0-pyhd3eb1b0_0 sphinxcontrib-htm~ 1.0.3-pyhd3eb1b0_0 --> 2.0.0-pyhd3eb1b0_0 sphinxcontrib-ser~ 1.1.4-pyhd3eb1b0_0 --> 1.1.5-pyhd3eb1b0_0 tifffile 2021.4.8-pyhd3eb1b0_2 --> 2021.7.2-pyhd3eb1b0_2 typed-ast 1.4.2-py38h2bbff1b_1 --> 1.4.3-py38h2bbff1b_1Therefore, conda update --all is not recommended, better stick to the custom metapackage if you need the highest possible update, or take the official metapackage if you are fine with a lag of a couple of months and a collection of packages without any conflicts is most important (for example, if you are in a production environment).
Result: Which to install: official or custom metapackage?
Some answers or comments say that the custom metapackage install might need to be run twice to get to a proper state. I cannot confirm this (tested with conda install anaconda and conda update anaconda, but I am also in a fresh Python installation). This is still a hint that it might be more stable to install the most recent official metapackage (= release, conda install anaconda=VersionNumber = conda update anaconda=VersionNumber) which can have a lag of some months.
On the other hand, the custom metapackage (the most recent trusted package collection) might be good if you want the most recent versions available. Then run conda install anaconda or the even stronger command conda update anaconda.
This is also the way to update Spyder:
They do not even use conda update conda before conda update anaconda, the latter seems enough.
Small "proof": I used conda update conda at first, and after that, conda update anaconda had nothing to do anymore, conda update conda had done all or the tasks.
conda update anaconda
Collecting package metadata (current_repodata.json): done Solving environment: done
# All requested packages already installed.That again sounds as if both commands are made the same now, perhaps they have not been the same only in the past.
The choice is up to you, it depends on how urgently you need to be up-to-date with some packages. Just start the installer to see what would happen, you can still enter n to cancel the installation. I am going to take
conda update anacondawithout conda update conda.
And do not take conda update --all unless you need the most recent update of some package, for example as a requirement for another package to be installed. I ran into that when testing --all, only after that, a new tensorflow add-on was suggested for download, but not after the other commands. Normally, you will not need to be up to date on the point, therefore do not use --all.
On Mac, open a terminal and run the following two commands.
conda update conda
conda update anacondaMake sure to run each command multiple times to update to the current version.
3Use:
conda create -n py37 -c anaconda anaconda=5.3.1
conda env export -n py37 --file env.yamlLocate the env.yaml file in C:\Windows\System32 and run the cmd as administrator:
conda env update -n root -f env.yamlThen it works!
This can update the Python instance only:
conda update python
