Guidelines for bioconda recipes

bioconda recipe checklist

  • Source URL is stable (details)
  • md5 or sha256 hash included for source download (details)
  • Appropriate build number (details)
  • .bat file for Windows removed (details)
  • Remove unnecessary comments (details)
  • Adequate tests included (details)
  • Files created by the recipe follow the FSH (details)
  • License allows redistribution and license is indicated in meta.yaml
  • Package does not already exist in the defaults, r, or conda-forge channels with some exceptions (details)
  • Package is appropriate for bioconda (details)
  • If the recipe installs custom wrapper scripts, usage notes should be added to extra -> notes in the meta.yaml.
  • Update 12 Jun 2017: If the recipe is a pure Python package, it is marked as a “noarch” package (details).

Stable urls

While supported by conda, git_url and git_rev are not as stable as a git tarball. Ideally a github repo should have tagged releases that are accessible as tarballs from the “releases” section of the github repo.

TODO: additional info on the various R and bioconductor URLs


Use md5sum (Linux) or md5 (OSX) on a file to compute its md5 hash, and copy this into the recipe. A quick way of doing this is:

wget -O- $URL | md5sum

Build numbers

The build number (see conda docs) can be used to trigger a new build for a package whose version has not changed. This is useful for fixing errors in recipes. The first recipe for a new version should always have a build number of 0.

.bat files

When creating a recipe using one of the conda skeleton tools, a .bat file for Windows will be created. Since bioconda does not support Windows and to reduce clutter, please remove these files

Comments in recipes

When creating a recipe using one of the conda skeleton tools, often many comments are included, for example, to point out sections that can be uncommented and used. Please delete all auto-generated comments in meta.yaml and But please add any comments that you feel could help future maintainers of the recipe, especially if there’s something non-standard.

Filesystem Hierarchy Standard

Recipes should conform to the Filesystem Hierarchy Standard (FSH). This is most important for libraries and Java packages; for these cases use one of the recipes below as a guideline.

Existing package exceptions

If a package already exists in one of the dependent channels but is broken or cannot be used as-is, please first consider fixing the package in that channel. If this is not possible, please indicate this in the PR and notify @bioconda/core in the PR.

Packages appropriate for bioconda

bioconda is a bioinformatics channel, so we prefer to host packages specific to this domain. If a bioinformatics recipe has more general dependencies, please consider opening a pull request with conda-forge which hosts general packages.

The exception to this is with R packages. We are still coordinating with anaconda and conda-forge about the best place to keep general R packages. In the meantime, R packages that are not specific to bioinformatics and that aren’t already in the conda-forge channel can be added to bioconda.

If uploading of an unreleased version is necessary, please follow the versioning scheme of conda for pre- and post-releases (e.g. using a, b, rc, and dev suffixes, see here).

“Noarch” packages

A noarch package can be created for pure Python packages, data packages, or packages that do not require compilation. This single noarch package can be used across multiple platforms, which saves on build time and saves on storage space on the bioconda channel.

For pure Python packages, add noarch: python to the build section.

For other generic packages (like a data package), add noarch: generic to the build section.

See here for more details.


There is currently no mechanism to define, in the meta.yaml file, that a particular dependency should come from a particular channel. This means that a recipe must have its dependencies in one of the following:

  • as-yet-unbuilt recipes in the repo but that will be included in the PR
  • bioconda channel
  • conda-forge channel
  • default Anaconda channel

Otherwise, you will have to write the recipes for those dependencies and include them in the PR. One shortcut is to use anaconda search -t conda <dependency name> to look for other packages built by others. Inspecting those recipes can give some clues into building a version of the dependency for bioconda.


If a Python package is available on PyPI, use conda skeleton pypi <packagename> to create a recipe, then remove the bld.bat and any extra comments in meta.yaml and The test that is automatically added is probably sufficient. The exception is when the package also installs a command-line tool, in which case that should be tested as well.

  • typical import check: pysam
  • import and command-line tests: chanjo

By default, Python recipes (those that have python listed as a dependency) must be successfully built and tested on Python 2.7, 3.4, and 3.5 in order to pass. However, many Python packages are not fully compatible across all Python versions. Use the preprocessing selectors in the meta.yaml file along with the build/skip entry to indicate that a recipe should be skipped.

For example, a recipe that only runs on Python 2.7 should include the following:

  skip: True  # [not py27]

Or a package that only runs on Python 3.4 and 3.5:

  skip: True # [py27]

Alternatively, for straightforward compatibility fixes you can apply a patch in the meta.yaml <>`_.


Use conda skeleton cran <packagename> where packagename is a package available on CRAN and is case-sensitive. Either run that command in the recipes dir or move the recipe it creates to recipes. The recipe name will have an r- prefix and will be converted to lowercase. Typically can be used without modification, though dependencies may also need recipes.

Please remove any unnecessary comments and delete the bld.bat file which is used only on Windows.

If the recipe was created using conda skeleton cran or the scripts/ script, the default test is probably sufficient. Otherwise see the examples below to see how tests are performed for R packages.

  • typical R recipe from CRAN: r-locfit
  • recipe for R package not on CRAN, also with patch: spp

R (Bioconductor)

Use scripts/bioconductor/ <packagename> where packagename is a case-sensitive package available on Bioconductor. The recipe name will have a bioconductor- prefix and will be converted to lowercase. Typically can be used without modification, though dependencies may also need recipes. Recipes for dependencies with an r- prefix should be created using conda skeleton cran; see above.


Add a wrapper script if the software is typically called via java -jar .... Sometimes the software already comes with one; for example, fastqc already had a wrapper script, but peptide-shaker did not.

New recipes should use the openjdk package from conda-forge , the java-jdk package from bioconda is deprecated.

JAR files should go in $PREFIX/share/$PKG_NAME-$PKG_VERSION-$PKG_BUILDNUM. A wrapper script should be placed here as well, and symlinked to $PREFIX/bin.


Use conda skeleton cpan <packagename> to build a recipe for Perl and place the recipe in the recipes dir. The recipe will have the perl- prefix.

An example of such a package is perl-module-build.

Alternatively, you can additionally ensure the build requirements for the recipe include perl-app-cpanminus, and then the script can be simplified. An example of this simplification is perl-time-hires.

If the recipe was created with conda skeleton cpan, the tests are likely sufficient. Otherwise, test the import of modules (see the imports section of the meta.yaml files in above examples).


Build tools (e.g., autoconf) and compilers (e.g., gcc) should be specified in the build requirements.

We have decided that to optimize compatibility, gcc needs to be added as a dependency rather than assume it is in the build environment. However there is still discussion on how best to do this on OSX. For now, please add gcc (for Linux packages) and llvm (for OSX packages) to the meta.yaml as follows:

    - gcc   # [not osx]
    - llvm  # [osx]

    - libgcc    # [not osx]

If the package uses zlib, then please see the troubleshooting section on zlib.

If your package links dynamically against a particular library, it is often necessary to pin the version against which it was compiled, in order to avoid ABI incompatibilities. Instead of hardcoding a particular version in the recipe, we use jinja templates to achieve this. This helps ensure that all bioconda packages are binary-compatible with each other. For example, bioconda provides an environnmnet variable CONDA_BOOST that contains the current major version of Boost. You should pin your boost dependency against that version. An example is the salmon recipe. You find the libraries you can currently pin in scripts/env_matrix.yml. If you need to pin another library, please notify @bioconda/core, and we will set up a corresponding environment variable.

It’s not uncommon to have difficulty compiling package into a portable conda package. Since there is no single solution, here are some examples of how bioconda contributors have solved compiling issues to give you some ideas on what to try:

  • ococo edits the source in to accommodate the C++ compiler on OSX
  • muscle patches the makefile on OSX so it doesn’t use static libs
  • metavelvet, eautils, preseq have several patches to their makefiles to fix LIBS and INCLUDES, INCLUDEARGS, and CFLAGS
  • mapsplice includes an older version of samtools; the included samtools’ makefile is patched to work in conda envs.
  • mosaik has platform-specific patches – one removes -static on linux, and the other sets BLD_PLATFORM correctly on OSX
  • mothur and soapdenovo have many fixes to makefiles

General command-line tools

If a command-line tool is installed, it should be tested. If it has a shebang line, it should be patched to use /usr/bin/env for more general use. An example of this is fastq-screen.

For command-line tools, running the program with no arguments, checking the programs version (e.g. with -v) or checking the command-line help is sufficient if doing so returns an exit code 0. Often the output is piped to /dev/null to avoid output during recipe builds.


If a package depends on Python and has a custom build string, then py{{CONDA_PY}} must be contained in that build string. Otherwise Python will be automatically pinned to one minor version, resulting in dependency conflicts with other packages. See mapsplice for an example of this.


Metapackages tie together other packages. All they do is define dependencies. For example, the hubward-all metapackage specifies the various other conda packages needed to get full hubward installation running just by installing one package. Other metapackages might tie together conda packages with a theme. For example, all UCSC utilities related to bigBed files, or a set of packages useful for variant calling.

For packages that are not anchored to a particular package (as in the last example above), we recommended semantic versioning starting at 1.0.0 for metapackages.

Other examples of interest

Packaging is hard. Here are some examples, in no particular order, of how contributors have solved various problems:

  • blast has an OS-specific installation – OSX copies binaries while on Linux it is compiled.
  • graphviz has an OS-specific option to configure
  • crossmap removes libs that are shipped with the source distribution
  • hisat2 runs 2to3 to make it Python 3 compatible, and copies over individual scripts to the bin dir
  • krona has a script that gets called after installation to alert the user a manual step is required
  • htslib has a small test script that creates example data and runs multiple programs on it
  • spectacle runs 2to3 to make the wrapper script Python 3 compatible, patches the wrapper script to have a shebang line, deletes example data to avoid taking up space in the bioconda channel, and includes a script for downloading the example data separately.
  • gatk is a package for licensed software that cannot be redistributed. The package installs a placeholder script (in this case doubling as the jar wrapper) to alert the user if the program is not installed, along with a separate script (gatk-register) to copy in a user-supplied archive/binary to the conda environment

Name collisions

In some cases, there may be a name collision when writing a recipe. For example the wget recipe is for the standard command-line tool. There is also a Python package called wget on PyPI. In this case, we prefixed the Python package with python- (see python-wget). A similar collision was resolved with weblogo and python-weblogo.

If in doubt about how to handle a naming collision, please submit an issue.


An adequate test must be included in the recipe. An “adequate” test depends on the recipe, but must be able to detect a successful installation. While many packages may ship their own test suite (unit tests or otherwise), including these in the recipe is not recommended since it may timeout the build system on Travis-CI. We especially want to avoid including any kind of test data in the repository.

Note that a test must return an exit code of 0. The test can be in the test field of meta.yaml, or can be a separate script (see the relevant conda docs for testing).

It is recommended to pipe unneeded stdout/stderr to /dev/null to avoid cluttering the output in the Travis-CI build environment.

Link and unlink scripts (pre- and post- install hooks)

It is possible to include scripts that are executed before or after installing a package, or before uninstalling a package. These scripts can be helpful for alerting the user that manual actions are required after adding or removing a package. For example, a script may be used to alert the user that he or she will need to create a database or modify a settings file. Any package that requires a manual preparatory step before it can be used should consider alerting the user via an echo statement in a script. These scripts may be added at the same level as meta.yaml and

  • is executed prior to linking (installation). An error causes conda to stop.
  • is executed after linking (installation). When the post-link step fails, no package metadata is written, and the package is not considered installed.
  • is executed prior to unlinking (uninstallation). Errors are ignored. Used for cleanup.

These scripts have access to the following environment variables:

  • $PREFIX The install prefix
  • $PKG_NAME The name of the package
  • $PKG_VERSION The version of the package
  • $PKG_BUILDNUM The build number of the package


In general, recipes can be updated in-place. The older package[s] will continue to be hosted and available on while the recipe will reflect just the most recent package.

However, if an older version of a packages is required but has not yet had a package built, create a subdirectory of the recipe named after the old version and put the recipe there. Examples of this can be found in bowtie2, bx-python, and others.