Build systems like GNU Make are frequently used to create complicated workflows, e.g. in bioinformatics. This project aims to reduce the complexity of creating workflows by providing a fast and comfortable execution environment, together with a clean and modern domain specific specification language (DSL) in python style.
Apart from being a command line tool, Snakemake can also be called from withing other python code and hence serve as a framework for organizing workflows withing your software. These pages describe the public parts of the Snakemake api.
For the user documentation and general information, see http://snakemake.bitbucket.org.
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snakemake.snakemake(snakefile, listrules=False, list_target_rules=False, cores=1, nodes=1, local_cores=1, resources={}, config={}, configfile=None, config_args=None, workdir=None, targets=None, dryrun=False, touch=False, forcetargets=False, forceall=False, forcerun=[], until=[], omit_from=[], prioritytargets=[], stats=None, printreason=False, printshellcmds=False, printdag=False, printrulegraph=False, printd3dag=False, nocolor=False, quiet=False, keepgoing=False, cluster=None, cluster_config=None, cluster_sync=None, drmaa=None, jobname='snakejob.{rulename}.{jobid}.sh', immediate_submit=False, standalone=False, ignore_ambiguity=False, snakemakepath=None, lock=True, unlock=False, cleanup_metadata=None, force_incomplete=False, ignore_incomplete=False, list_version_changes=False, list_code_changes=False, list_input_changes=False, list_params_changes=False, list_resources=False, summary=False, detailed_summary=False, latency_wait=3, benchmark_repeats=1, wait_for_files=None, print_compilation=False, debug=False, notemp=False, keep_remote_local=False, nodeps=False, keep_target_files=False, keep_shadow=False, allowed_rules=None, jobscript=None, timestamp=False, greediness=None, no_hooks=False, overwrite_shellcmd=None, updated_files=None, log_handler=None, keep_logger=False, max_jobs_per_second=None, verbose=False, force_use_threads=False, use_conda=False, mode=0, wrapper_prefix=None)[source]¶Run snakemake on a given snakefile.
This function provides access to the whole snakemake functionality. It is not thread-safe.
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| Returns: | True if workflow execution was successful. |
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| Return type: | bool |
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snakemake.utils.AlwaysQuotedFormatter(quote_func=<function quote>, *args, **kwargs)[source]¶Subclass of QuotedFormatter that always quotes.
Usage is identical to QuotedFormatter, except that it always acts like “q” was appended to the format spec.
snakemake.utils.QuotedFormatter(quote_func=<function quote>, *args, **kwargs)[source]¶Subclass of string.Formatter that supports quoting.
Using this formatter, any field can be quoted after formatting by appending “q” to its format string. By default, shell quoting is performed using “shlex.quote”, but you can pass a different quote_func to the constructor. The quote_func simply has to take a string argument and return a new string representing the quoted form of the input string.
Note that if an element after formatting is the empty string, it will not be quoted.
snakemake.utils.R(code)[source]¶Execute R code
This function executes the R code given as a string. The function requires rpy2 to be installed.
| Parameters: | code (str) – R code to be executed |
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snakemake.utils.SequenceFormatter(separator=' ', element_formatter=<string.Formatter object>, *args, **kwargs)[source]¶string.Formatter subclass with special behavior for sequences.
This class delegates formatting of individual elements to another formatter object. Non-list objects are formatted by calling the delegate formatter’s “format_field” method. List-like objects (list, tuple, set, frozenset) are formatted by formatting each element of the list according to the specified format spec using the delegate formatter and then joining the resulting strings with a separator (space by default).
snakemake.utils.available_cpu_count()[source]¶Return the number of available virtual or physical CPUs on this system. The number of available CPUs can be smaller than the total number of CPUs when the cpuset(7) mechanism is in use, as is the case on some cluster systems.
Adapted from http://stackoverflow.com/a/1006301/715090
snakemake.utils.format(_pattern, *args, stepout=1, _quote_all=False, **kwargs)[source]¶Format a pattern in Snakemake style.
This means that keywords embedded in braces are replaced by any variable values that are available in the current namespace.
snakemake.utils.linecount(filename)[source]¶Return the number of lines of given file.
| Parameters: | filename (str) – the path to the file |
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snakemake.utils.listfiles(pattern, restriction=None, omit_value=None)[source]¶Yield a tuple of existing filepaths for the given pattern.
Wildcard values are yielded as the second tuple item.
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| Yields: | tuple – The next file matching the pattern, and the corresponding wildcards object |
snakemake.utils.makedirs(dirnames)[source]¶Recursively create the given directory or directories without reporting errors if they are present.
snakemake.utils.min_version(version)[source]¶Require minimum snakemake version, raise workflow error if not met.
snakemake.utils.read_job_properties(jobscript, prefix='# properties', pattern=re.compile('# properties = (.*)'))[source]¶Read the job properties defined in a snakemake jobscript.
This function is a helper for writing custom wrappers for the snakemake –cluster functionality. Applying this function to a jobscript will return a dict containing information about the job.
snakemake.utils.report(text, path, stylesheet='/home/docs/checkouts/readthedocs.org/user_builds/snakemake/checkouts/v3.9.0/snakemake/report.css', defaultenc='utf8', template=None, metadata=None, **files)[source]¶Create an HTML report using python docutils.
Attention: This function needs Python docutils to be installed for the python installation you use with Snakemake.
All keywords not listed below are intepreted as paths to files that shall be embedded into the document. They keywords will be available as link targets in the text. E.g. append a file as keyword arg via F1=input[0] and put a download link in the text like this:
report('''
==============
Report for ...
==============
Some text. A link to an embedded file: F1_.
Further text.
''', outputpath, F1=input[0])
Instead of specifying each file as a keyword arg, you can also expand
the input of your rule if it is completely named, e.g.:
report('''
Some text...
''', outputpath, **input)
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snakemake.utils.update_config(config, overwrite_config)[source]¶Recursively update dictionary config with overwrite_config.
See http://stackoverflow.com/questions/3232943/update-value-of-a-nested-dictionary-of-varying-depth for details.
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