Hi all,

Galaxy 16.07 was just released:
and the IUC has some news to share with you.

For a more readable version please see:


Galaxy tools (also called wrappers) traditionally use Tool Shed package
recipes to install their dependencies. At the tool’s installation time
the recipe is downloaded and executed in order to provide the underlying
software executables. Introduction of these Galaxy-specific recipes was
a necessary step at the time, however nowadays there are other more
mature and stable options to install software in a similar manner. The
Galaxy community has taken steps to improve the tool dependency system
in order to enable new features and expand its reach. This document aims
to describe these and answer the FAQ.

It is a pleasure to announce the adoption of a new standard for tool
dependencies in Galaxy which has been integrated over the last six
months: Conda packages!
Not only do Conda packages make tool dependencies more reliable and
stable, they are also easier to test and faster to develop than the
traditional Tool Shed package recipes .

Conda is a package manager like apt-get, yum, pip, brew or guix. We
don’t want to argue about the relative merits of various package
managers here, in fact Galaxy supports multiple package managers and we
welcome community contributions (such as implementing a Guix package
manager or enhancing the existing brew support to bring it on par with

As a community, we have decided that Conda is the one that best fulfills
our needs. The following are some of the crucial Conda features that led
to this decision:

* Installation of packages does not require root privileges
(Installation at any location  the Galaxy user has write access to)
* Multiple versions of software can be installed in parallel
* HPC-ready
* Faster and more robust package installations through pre-compiled
packages (no build environment complications)
* Independent of programming language (R, Perl, Python, Julia, Java,
pre-compiled binaries, and more)
* Easy to write recipes (1 YAML description file + 1 Bash install script)
* An active, large and growing community (with more and more software
authors managing their own recipes)
* Extensive documentation: Conda documentation
(http://conda.pydata.org/docs/building/build.html) and Conda quick-start

Below we answer some common questions (collected by Lance Parsons):

1. How do I enable Conda dependency resolution for existing Galaxy

Most Galaxy administrators have not set up a dependency resolvers
configuration file (dependency_resolvers_conf.xml) which means they are
using Galaxy’s default (dependency_resolvers_conf.xml.sample). Galaxy
has enabled Conda dependency resolution by default since release 16.04
(if Conda was installed already), so many existing installations can use
Conda dependencies. Having Conda enabled in
dependency_resolvers_conf.xml means that Galaxy will look for
dependencies using the Conda system when it attempts to run tools. If
conda_auto_install is True, and a dependency is not found, Galaxy will
attempt to install it using the configured Conda channels. A graphical
user interface that allows administrators install Conda packages
directly from Galaxy when tools are installed from the Tool Shed is
available in the 16.07 release of Galaxy.

2. How do Conda dependencies work? Where do things get installed?
In contrast to the old dependency system, which was used exclusively by
Galaxy, Conda is a pre-existing, independent project. With Conda it is
possible for an admin to install packages without touching Galaxy at all
– managing your dependencies independently from Galaxy. Galaxy can
handle these dependencies for you, but admins are not required to use
Galaxy for dependency management.

There are a few new config options in the galaxy.ini file, but by
default Galaxy will install Conda (the package manager) and the required
packages in the <tool_dependency_dir>/_conda/ directory. In this
directory, Galaxy will create an envs folder with all of the
environments managed by Galaxy. Every environment contains a lib, bin,
share, and include subdirectory, depending on the tool, and is
sufficient to get a Galaxy tool up and running. Galaxy simply sources
this folder via Conda and makes everything available before the tool is
executed on your cluster.

To summarize, there are four ways to manage Conda dependencies for use
with Galaxy. For all of these options, Conda dependency management must
be configured in the dependency_resolvers_conf.xml and the galaxy.ini file.

a) Manual Install - Conda dependencies may be installed by
administrators from the command line. Conda (and thus the conda
environments) should be installed in the location specified by  the
conda_prefix path (defined in galaxy.ini and by default
<tool_dependency_dir>/_conda/ directory). Galaxy will search these
environments for required packages when tools are run. Conda environment
names have to follow a specific naming pattern. As an example, to
install samtools in version 0.1.19, the administrator can run the command:
$ conda create --name __package__samtools@__version__0.1.19
samtools==0.1.19 --channel bioconda
Tools that require samtools version 0.1.19 will then be able to find and
use the installed conda package.

b) Galaxy Admin Interface (>= 16.07) - Galaxy will install Conda tool
dependencies when tools are installed from the Tool Shed if the option
“When available, install externally managed dependencies (e.g. conda)?
Beta” is checked. Admins may also view and manage Conda dependencies via
the Admin interface.

c) Automatically at tool run time - When a tool is run and a dependency
is not found, Galaxy will attempt to install the dependency using Conda
if conda_auto_install is activated in the configuration.

d) Via the API, upon tool installation (>= 16.07) - The Galaxy community
maintains an ansible role
(https://github.com/galaxyproject/ansible-galaxy-tools) that uses
BioBlend (https://github.com/galaxyproject/bioblend/) and the Galaxy API
to install tools.

3. What is required to make use of this? Any specific packages, Galaxy
revision, OS version, etc.?
The minimum required version of Galaxy to use Conda is 16.01, however
version 16.07 or greater is recommended. The 16.07 release of Galaxy has
a nice graphical user interface to manage packages, but this is not
required to have Conda dependencies managed and used by Galaxy.

Conda packages should work on all compatible operating systems with
glibc version (2.5) or newer (this includes Centos 5). We will most
likely switch soon to glibc version 2.12 as minimum requirement (this
includes CentOS 6). So all packages will run on all *nix operating
systems newer than 2007.

4. How do I know what system is being used by a given tool?
The Galaxy log will tell you which dependency resolution system is used
to satisfy each tool dependency and you can specify priorities using the
config/dependency_resolution_conf.xml file. If you put Conda on top,
Galaxy will at first try to use Conda to resolve a tool dependency; if
this does not work, the following dependency resolvers is used, as
specified. See
for detailed documentation. Starting from galaxy release 16.07, you can
see which dependency will be used (“resolved”) in the admin panel.

5. How do I go about specifying conda dependencies for a tool? All the
docs still seem to recommend (or exclusively discuss) the
tool_dependencies.xml method.
The simple answer is: you don‘t need to do much to make Conda work for a
The <requirement> tag in the tool XML file is enough. The name and the
version should correspond to a Conda package in the `default`, `r`,
`bioconda` or `iuc` Conda channel (you can extend this list if you like
in your galaxy.ini). If this is the case you are ready to go. Read more
about Conda channels here:
http://conda.pydata.org/docs/custom-channels.html and browse their
packages on https://anaconda.org/ url followed by the channel name (e.g.
We need to adjust the documentation about tool_dependencies.xml and
deprecate them everywhere.

6. During tool installation what if there is no Conda package available
for given requirement? What if the requirement is resolved in a
different software than the original wrapper author meant to use?
If there is no Conda package available during tool installation the tool
will install successfully, and can be used if its dependencies are
satisfied by another dependency system such as Tool Shed package
recipes, Docker containers or modules.
If there is a package of correct name and version it will be used. There
is no equivalent of the “owner” concept used in Galaxy packages
installed from the Tool Shed.

7. Where can I find a list of existing Conda packages that I can point
to, so I don't have to reinvent the wheel for common dependencies?
With Conda installed run:
$ conda search <package_name> -c bioconda -c iuc

This will search in all channels that are activated by default in
Galaxy. If you find your package your are ready to go. If not please
a Conda package and submit
(https://bioconda.github.io/#step-4-join-the-team) it to BioConda
(https://bioconda.github.io) or get in contact with the IUC

8. How can I create a new conda package for a dependency?
Adding a package to the bioconda or iuc conda channels will make it
available for Galaxy tools to use as a dependency. To learn how, get in
touch with the awesome BioConda community. They have great documentation
and assist with all development. You will also see a few of us at this
project to get you started :)
Don’t be scared! Conda recipes are really simple to write. Conda also
offers you, so called `skeleton` generators, generating recipes from
pypi, cran, cpan for you (mostly) automatically.

9. Is there a way to convert traditional Tool Shed package recipes that
are not yet in a Conda channel?
First, you do not need to do anything to your wrapper as long as the
package name in the requirement tag is matches the name of correct Conda
package. (You may want to mention in the README or a comment the Conda
channel that contains the package).
We have developed scripts for conversion of Tool Shed package recipes to
Conda, but have not followed up and they are not ready for production.
If you want to migrate some recipes from XML to Conda, we are happy to
give you a hand. We are trying to get all new versions under Conda and
leave the old versions as they are – simply because of time.

10. What is the recommendation for existing installations? Will I
continue to maintain both systems or migrate to the new Conda system
Old tools will use the traditional installation system, this system will
stay and will be supported to install old tools. This we promised to our
community to guarantee sustainability and reproducibility. New tools
from the IUC, may be Conda only.

11. If I have Conda enabled, what do I need to do to install tools using
it? For example, how can I install the latest Trinity? And how will I
know dependencies are installed?
This depends on your galaxy.ini setting. Galaxy will install Conda for
you if you have enabled conda_auto_init. If conda_auto_install is
enabled, Galaxy will install Trinity via Conda when a Trinity job is
launched and Trinity is not yet installed. With the latest 16.07 release
you can see which dependencies are being used in the “Manage installed
tools” section of the admin panel and you can select whether or not to
install Conda packages or Tool Shed package recipes when you install new
tools, even if conda_auto_install is disabled.
More improvements to the UI will be coming with 16.10. To see if Galaxy
has created a Trinity environment for you have a look at folder under

12. Can I mix traditional Galaxy packages and Conda packages?
Yes, the way this works is that Galaxy goes through the list of
requirements for a tool, and then determines for each requirement if it
can be satisfied by any of the active resolver systems.
The order in which resolvers are tried is listed in the
dependency_resolvers_conf.xml file, and the default order is
Tool Shed packages
Packages manually installed by administrators
Conda packages
The first system that satisfies a requirement will be used.

13. What can I do if conda doesn’t work for me?
There is currently a limitation in the way conda packages are being
built. This limitation will be addressed shortly by the Conda community,
however this requires all packages to be rebuilt.
To work around this limitation, please make sure that the total length
of the conda_prefix and job_working_directory path is less than 50
characters long.
If this is your problem, you should see a warning similar to the
following in your galaxy log files:
ERROR: placeholder
too short
In rare cases conda may not have been properly installed by galaxy. A
symptom for this is if there is no activate script in conda_prefix/bin.
In that case you can delete the conda_prefix folder and restart galaxy,
which will again attempt to install conda.

If this does not solve your problem or you have any trouble following
the instructions, please ask on the galaxy mailing list or the galaxy
IRC channel.

One last thing that is important to me: the entire Galaxy-Conda project
is an amazing community effort - not only within the Galaxy community,
but we team up with the Conda community as well, in particular with the
BioConda folks. Thanks to Johannes Köster, Ryan Dale and the entire
community around this package manager which have created around 1500
bioinformatics packages just in the last year.

Thanks to John Chilton who has written the Galaxy Conda integration last
December and is pushing tool development in Galaxy to a new level. Many
thanks to Nicola Soranzo for his constant support and reviews in all
mentioned projects, he is everywhere to help - you will see! Thanks also
to Peter van Heusden, Marius van den Beek and Brad Langhorst – they have
worked hard on Conda-Galaxy Integration to make it shine in 16.07. I
want to thank Lance Parsons for his questions that inspired me to write
this down and his constant support in making tools better in Galaxy –
Lance I hope with Conda you will have less pain with dependencies in

Last but not least I would like to thank the entire IUC and the over 50
IUC contributors that have migrated most of the IUC tools to Conda
packages over the last 6 months.

You all did a truly amazing work here – and I‘m sure it will benefit the
tool development in Galaxy tremendously.

Enjoy Galaxy + Conda,
Björn, on behalf of the IUC

P.S. As soon as you have a Conda package, we have a system for you to
generate Docker containers out of it: https://github.com/mulled/mulled.
These containers can than be used by Galaxy to resolve dependencies as
well, if you prefer Docker containers over Conda packages.
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