Source code for snakemake.script

__author__ = "Johannes Köster"
__copyright__ = "Copyright 2021, Johannes Köster"
__email__ = "johannes.koester@uni-due.de"
__license__ = "MIT"

import inspect
import itertools
import os
import tempfile
import textwrap
import sys
import pickle
import subprocess
import collections
import re
from abc import ABC, abstractmethod
from urllib.request import urlopen, pathname2url
from urllib.error import URLError

from snakemake.utils import format
from snakemake.logging import logger
from snakemake.exceptions import WorkflowError
from snakemake.shell import shell
from snakemake.common import (
    MIN_PY_VERSION,
    SNAKEMAKE_SEARCHPATH,
    ON_WINDOWS,
    smart_join,
)
from snakemake.io import git_content, split_git_path
from snakemake.deployment import singularity


# TODO use this to find the right place for inserting the preamble
PY_PREAMBLE_RE = re.compile(r"from( )+__future__( )+import.*?(?P<end>[;\n])")


[docs]class Snakemake: def __init__( self, input_, output, params, wildcards, threads, resources, log, config, rulename, bench_iteration, scriptdir=None, ): # convert input and output to plain strings as some remote objects cannot # be pickled self.input = input_._plainstrings() self.output = output._plainstrings() self.params = params self.wildcards = wildcards self.threads = threads self.resources = resources self.log = log._plainstrings() self.config = config self.rule = rulename self.bench_iteration = bench_iteration self.scriptdir = scriptdir
[docs] def log_fmt_shell(self, stdout=True, stderr=True, append=False): """ Return a shell redirection string to be used in `shell()` calls This function allows scripts and wrappers support optional `log` files specified in the calling rule. If no `log` was specified, then an empty string "" is returned, regardless of the values of `stdout`, `stderr`, and `append`. Parameters --------- stdout : bool Send stdout to log stderr : bool Send stderr to log append : bool Do not overwrite the log file. Useful for sending output of multiple commands to the same log. Note however that the log will not be truncated at the start. The following table describes the output: -------- -------- -------- ----- ------------- stdout stderr append log return value -------- -------- -------- ----- ------------ True True True fn >> fn 2>&1 True False True fn >> fn False True True fn 2>> fn True True False fn > fn 2>&1 True False False fn > fn False True False fn 2> fn any any any None "" -------- -------- -------- ----- ----------- """ if not self.log: return "" lookup = { (True, True, True): " >> {0} 2>&1", (True, False, True): " >> {0}", (False, True, True): " 2>> {0}", (True, True, False): " > {0} 2>&1", (True, False, False): " > {0}", (False, True, False): " 2> {0}", } return lookup[(stdout, stderr, append)].format(self.log)
[docs]class REncoder: """Encoding Pyton data structures into R."""
[docs] @classmethod def encode_numeric(cls, value): if value is None: return "as.numeric(NA)" return str(value)
[docs] @classmethod def encode_value(cls, value): if value is None: return "NULL" elif isinstance(value, str): return repr(value) elif isinstance(value, dict): return cls.encode_dict(value) elif isinstance(value, bool): return "TRUE" if value else "FALSE" elif isinstance(value, int) or isinstance(value, float): return str(value) elif isinstance(value, collections.abc.Iterable): # convert all iterables to vectors return cls.encode_list(value) else: # Try to convert from numpy if numpy is present try: import numpy as np if isinstance(value, np.number): return str(value) except ImportError: pass raise ValueError("Unsupported value for conversion into R: {}".format(value))
[docs] @classmethod def encode_list(cls, l): return "c({})".format(", ".join(map(cls.encode_value, l)))
[docs] @classmethod def encode_items(cls, items): def encode_item(item): name, value = item return '"{}" = {}'.format(name, cls.encode_value(value)) return ", ".join(map(encode_item, items))
[docs] @classmethod def encode_dict(cls, d): d = "list({})".format(cls.encode_items(d.items())) return d
[docs] @classmethod def encode_namedlist(cls, namedlist): positional = ", ".join(map(cls.encode_value, namedlist)) named = cls.encode_items(namedlist.items()) source = "list(" if positional: source += positional if named: source += ", " + named source += ")" return source
[docs]class JuliaEncoder: """Encoding Pyton data structures into Julia."""
[docs] @classmethod def encode_value(cls, value): if value is None: return "nothing" elif isinstance(value, str): return repr(value) elif isinstance(value, dict): return cls.encode_dict(value) elif isinstance(value, bool): return "true" if value else "false" elif isinstance(value, int) or isinstance(value, float): return str(value) elif isinstance(value, collections.abc.Iterable): # convert all iterables to vectors return cls.encode_list(value) else: # Try to convert from numpy if numpy is present try: import numpy as np if isinstance(value, np.number): return str(value) except ImportError: pass raise ValueError( "Unsupported value for conversion into Julia: {}".format(value) )
[docs] @classmethod def encode_list(cls, l): return "[{}]".format(", ".join(map(cls.encode_value, l)))
[docs] @classmethod def encode_items(cls, items): def encode_item(item): name, value = item return '"{}" => {}'.format(name, cls.encode_value(value)) return ", ".join(map(encode_item, items))
[docs] @classmethod def encode_positional_items(cls, namedlist): encoded = "" for index, value in enumerate(namedlist): encoded += "{} => {}, ".format(index + 1, cls.encode_value(value)) return encoded
[docs] @classmethod def encode_dict(cls, d): d = "Dict({})".format(cls.encode_items(d.items())) return d
[docs] @classmethod def encode_namedlist(cls, namedlist): positional = cls.encode_positional_items(namedlist) named = cls.encode_items(namedlist.items()) source = "Dict(" if positional: source += positional if named: source += named source += ")" return source
[docs]class ScriptBase(ABC): editable = False def __init__( self, path, source, basedir, input_, output, params, wildcards, threads, resources, log, config, rulename, conda_env, container_img, singularity_args, env_modules, bench_record, jobid, bench_iteration, cleanup_scripts, shadow_dir, ): self.path = path self.source = source self.basedir = basedir self.input = input_ self.output = output self.params = params self.wildcards = wildcards self.threads = threads self.resources = resources self.log = log self.config = config self.rulename = rulename self.conda_env = conda_env self.container_img = container_img self.singularity_args = singularity_args self.env_modules = env_modules self.bench_record = bench_record self.jobid = jobid self.bench_iteration = bench_iteration self.cleanup_scripts = cleanup_scripts self.shadow_dir = shadow_dir
[docs] def evaluate(self, edit=False): assert not edit or self.editable fd = None try: # generate preamble preamble = self.get_preamble() # write script dir_ = ".snakemake/scripts" os.makedirs(dir_, exist_ok=True) with tempfile.NamedTemporaryFile( suffix="." + os.path.basename(self.path), dir=dir_, delete=False ) as fd: self.write_script(preamble, fd) # execute script self.execute_script(fd.name, edit=edit) except URLError as e: raise WorkflowError(e) finally: if fd and self.cleanup_scripts: os.remove(fd.name) else: if fd: logger.warning("Not cleaning up %s" % fd.name) else: # nothing to clean up (TODO: ??) pass
@property def local_path(self): path = self.path[7:] if not os.path.isabs(path): return smart_join(self.basedir, path) return path
[docs] @abstractmethod def get_preamble(self): ...
[docs] @abstractmethod def write_script(self, preamble, fd): ...
[docs] @abstractmethod def execute_script(self, fname, edit=False): ...
def _execute_cmd(self, cmd, **kwargs): return shell( cmd, bench_record=self.bench_record, conda_env=self.conda_env, container_img=self.container_img, shadow_dir=self.shadow_dir, env_modules=self.env_modules, singularity_args=self.singularity_args, **kwargs )
[docs]class PythonScript(ScriptBase):
[docs] @staticmethod def generate_preamble( path, source, basedir, input_, output, params, wildcards, threads, resources, log, config, rulename, conda_env, container_img, singularity_args, env_modules, bench_record, jobid, bench_iteration, cleanup_scripts, shadow_dir, preamble_addendum="", ): wrapper_path = path[7:] if path.startswith("file://") else path snakemake = Snakemake( input_, output, params, wildcards, threads, resources, log, config, rulename, bench_iteration, os.path.dirname(wrapper_path), ) snakemake = pickle.dumps(snakemake) # Obtain search path for current snakemake module. # The module is needed for unpickling in the script. # We append it at the end (as a fallback). searchpath = SNAKEMAKE_SEARCHPATH if container_img is not None: searchpath = singularity.SNAKEMAKE_MOUNTPOINT searchpath = repr(searchpath) # For local scripts, add their location to the path in case they use path-based imports if path.startswith("file://"): searchpath += ", " + repr(os.path.dirname(path[7:])) return textwrap.dedent( """ ######## snakemake preamble start (automatically inserted, do not edit) ######## import sys; sys.path.extend([{searchpath}]); import pickle; snakemake = pickle.loads({snakemake}); from snakemake.logging import logger; logger.printshellcmds = {printshellcmds}; {preamble_addendum} ######## snakemake preamble end ######### """ ).format( searchpath=searchpath, snakemake=snakemake, printshellcmds=logger.printshellcmds, preamble_addendum=preamble_addendum, )
[docs] def get_preamble(self): wrapper_path = self.path[7:] if self.path.startswith("file://") else self.path preamble_addendum = ( "__real_file__ = __file__; __file__ = {file_override};".format( file_override=repr(os.path.realpath(wrapper_path)) ) ) return PythonScript.generate_preamble( self.path, self.source, self.basedir, self.input, self.output, self.params, self.wildcards, self.threads, self.resources, self.log, self.config, self.rulename, self.conda_env, self.container_img, self.singularity_args, self.env_modules, self.bench_record, self.jobid, self.bench_iteration, self.cleanup_scripts, self.shadow_dir, preamble_addendum=preamble_addendum, )
[docs] def write_script(self, preamble, fd): fd.write(preamble.encode()) fd.write(self.source)
def _is_python_env(self): if self.conda_env is not None: prefix = os.path.join(self.conda_env, "bin") elif self.env_modules is not None: prefix = self._execute_cmd("echo $PATH", read=True).split(":")[0] else: raise NotImplementedError() return os.path.exists(os.path.join(prefix, "python")) def _get_python_version(self): out = self._execute_cmd( "python -c \"import sys; print('.'.join(map(str, sys.version_info[:2])))\"", read=True, ) return tuple(map(int, out.strip().split(".")))
[docs] def execute_script(self, fname, edit=False): py_exec = sys.executable if self.container_img is not None: # use python from image py_exec = "python" elif self.conda_env is not None or self.env_modules is not None: if self._is_python_env(): py_version = self._get_python_version() # If version is None, all fine, because host python usage is intended. if py_version is not None: if py_version >= MIN_PY_VERSION: # Python version is new enough, make use of environment # to execute script py_exec = "python" else: logger.warning( "Environment defines Python " "version < {0}.{1}. Using Python of the " "master process to execute " "script. Note that this cannot be avoided, " "because the script uses data structures from " "Snakemake which are Python >={0}.{1} " "only.".format(*MIN_PY_VERSION) ) if ON_WINDOWS: # use forward slashes so script command still works even if # bash is configured as executable on Windows py_exec = py_exec.replace("\\", "/") # use the same Python as the running process or the one from the environment self._execute_cmd("{py_exec} {fname:q}", py_exec=py_exec, fname=fname)
[docs]class RScript(ScriptBase):
[docs] @staticmethod def generate_preamble( path, source, basedir, input_, output, params, wildcards, threads, resources, log, config, rulename, conda_env, container_img, singularity_args, env_modules, bench_record, jobid, bench_iteration, cleanup_scripts, shadow_dir, preamble_addendum="", ): return textwrap.dedent( """ ######## snakemake preamble start (automatically inserted, do not edit) ######## library(methods) Snakemake <- setClass( "Snakemake", slots = c( input = "list", output = "list", params = "list", wildcards = "list", threads = "numeric", log = "list", resources = "list", config = "list", rule = "character", bench_iteration = "numeric", scriptdir = "character", source = "function" ) ) snakemake <- Snakemake( input = {}, output = {}, params = {}, wildcards = {}, threads = {}, log = {}, resources = {}, config = {}, rule = {}, bench_iteration = {}, scriptdir = {}, source = function(...){{ wd <- getwd() setwd(snakemake@scriptdir) source(...) setwd(wd) }} ) {preamble_addendum} ######## snakemake preamble end ######### """ ).format( REncoder.encode_namedlist(input_), REncoder.encode_namedlist(output), REncoder.encode_namedlist(params), REncoder.encode_namedlist(wildcards), threads, REncoder.encode_namedlist(log), REncoder.encode_namedlist( { name: value for name, value in resources.items() if name != "_cores" and name != "_nodes" } ), REncoder.encode_dict(config), REncoder.encode_value(rulename), REncoder.encode_numeric(bench_iteration), REncoder.encode_value( os.path.dirname(path[7:]) if path.startswith("file://") else os.path.dirname(path) ), preamble_addendum=preamble_addendum, )
[docs] def get_preamble(self): return RScript.generate_preamble( self.path, self.source, self.basedir, self.input, self.output, self.params, self.wildcards, self.threads, self.resources, self.log, self.config, self.rulename, self.conda_env, self.container_img, self.singularity_args, self.env_modules, self.bench_record, self.jobid, self.bench_iteration, self.cleanup_scripts, self.shadow_dir, )
[docs] def write_script(self, preamble, fd): fd.write(preamble.encode()) fd.write(self.source)
[docs] def execute_script(self, fname, edit=False): if self.conda_env is not None and "R_LIBS" in os.environ: logger.warning( "R script job uses conda environment but " "R_LIBS environment variable is set. This " "is likely not intended, as R_LIBS can " "interfere with R packages deployed via " "conda. Consider running `unset R_LIBS` or " "remove it entirely before executing " "Snakemake." ) self._execute_cmd("Rscript --vanilla {fname:q}", fname=fname)
[docs]class RMarkdown(ScriptBase):
[docs] def get_preamble(self): return textwrap.dedent( """ ######## snakemake preamble start (automatically inserted, do not edit) ######## library(methods) Snakemake <- setClass( "Snakemake", slots = c( input = "list", output = "list", params = "list", wildcards = "list", threads = "numeric", log = "list", resources = "list", config = "list", rule = "character", bench_iteration = "numeric", scriptdir = "character", source = "function" ) ) snakemake <- Snakemake( input = {}, output = {}, params = {}, wildcards = {}, threads = {}, log = {}, resources = {}, config = {}, rule = {}, bench_iteration = {}, scriptdir = {}, source = function(...){{ wd <- getwd() setwd(snakemake@scriptdir) source(...) setwd(wd) }} ) ######## snakemake preamble end ######### """ ).format( REncoder.encode_namedlist(self.input), REncoder.encode_namedlist(self.output), REncoder.encode_namedlist(self.params), REncoder.encode_namedlist(self.wildcards), self.threads, REncoder.encode_namedlist(self.log), REncoder.encode_namedlist( { name: value for name, value in self.resources.items() if name != "_cores" and name != "_nodes" } ), REncoder.encode_dict(self.config), REncoder.encode_value(self.rulename), REncoder.encode_numeric(self.bench_iteration), REncoder.encode_value( os.path.dirname(self.path[7:]) if self.path.startswith("file://") else os.path.dirname(self.path) ), )
[docs] def write_script(self, preamble, fd): # Insert Snakemake object after the RMarkdown header code = self.source.decode() pos = next(itertools.islice(re.finditer(r"---\n", code), 1, 2)).start() + 3 fd.write(str.encode(code[:pos])) preamble = textwrap.dedent( """ ```{r, echo=FALSE, message=FALSE, warning=FALSE} %s ``` """ % preamble ) fd.write(preamble.encode()) fd.write(str.encode(code[pos:]))
[docs] def execute_script(self, fname, edit=False): if len(self.output) != 1: raise WorkflowError( "RMarkdown scripts (.Rmd) may only have a single output file." ) out = os.path.abspath(self.output[0]) self._execute_cmd( 'Rscript --vanilla -e \'rmarkdown::render("{fname}", output_file="{out}", quiet=TRUE, knit_root_dir = "{workdir}", params = list(rmd="{fname}"))\'', fname=fname, out=out, workdir=os.getcwd(), )
[docs]class JuliaScript(ScriptBase):
[docs] def get_preamble(self): return textwrap.dedent( """ ######## snakemake preamble start (automatically inserted, do not edit) ######## struct Snakemake input::Dict output::Dict params::Dict wildcards::Dict threads::Int64 log::Dict resources::Dict config::Dict rule::String bench_iteration scriptdir::String #source::Any end snakemake = Snakemake( {}, #input::Dict {}, #output::Dict {}, #params::Dict {}, #wildcards::Dict {}, #threads::Int64 {}, #log::Dict {}, #resources::Dict {}, #config::Dict {}, #rule::String {}, #bench_iteration::Int64 {}, #scriptdir::String #, #source::Any ) ######## snakemake preamble end ######### """.format( JuliaEncoder.encode_namedlist(self.input), JuliaEncoder.encode_namedlist(self.output), JuliaEncoder.encode_namedlist(self.params), JuliaEncoder.encode_namedlist(self.wildcards), JuliaEncoder.encode_value(self.threads), JuliaEncoder.encode_namedlist(self.log), JuliaEncoder.encode_namedlist( { name: value for name, value in self.resources.items() if name != "_cores" and name != "_nodes" } ), JuliaEncoder.encode_dict(self.config), JuliaEncoder.encode_value(self.rulename), JuliaEncoder.encode_value(self.bench_iteration), JuliaEncoder.encode_value( os.path.dirname(self.path[7:]) if self.path.startswith("file://") else os.path.dirname(self.path) ), ).replace( "'", '"' ) )
[docs] def write_script(self, preamble, fd): fd.write(preamble.encode()) fd.write(self.source)
[docs] def execute_script(self, fname, edit=False): self._execute_cmd("julia {fname:q}", fname=fname)
[docs]def get_source(path, basedir=".", wildcards=None, params=None): source = None if not path.startswith("http") and not path.startswith("git+file"): if path.startswith("file://"): path = path[7:] elif path.startswith("file:"): path = path[5:] if not os.path.isabs(path): path = smart_join(basedir, path, abspath=True) path = "file://" + path if wildcards is not None and params is not None: # Format path if wildcards are given. path = format(path, wildcards=wildcards, params=params) if path.startswith("file://"): sourceurl = "file:" + pathname2url(path[7:]) elif path.startswith("git+file"): source = git_content(path).encode() (root_path, file_path, version) = split_git_path(path) path = path.rstrip("@" + version) else: sourceurl = path if source is None: with urlopen(sourceurl) as source: source = source.read() language = get_language(path, source) return path, source, language
[docs]def get_language(path, source): import nbformat language = None if path.endswith(".py"): language = "python" elif path.endswith(".ipynb"): language = "jupyter" elif path.endswith(".R"): language = "r" elif path.endswith(".Rmd"): language = "rmarkdown" elif path.endswith(".jl"): language = "julia" # detect kernel language for Jupyter Notebooks if language == "jupyter": nb = nbformat.reads(source, as_version=nbformat.NO_CONVERT) try: kernel_language = nb["metadata"]["language_info"]["name"] except KeyError as e: raise WorkflowError( "Notebook metadata is corrupt. Please delete notebook " "and recreate it via --edit-notebook." ) language += "_" + kernel_language.lower() return language
[docs]def script( path, basedir, input, output, params, wildcards, threads, resources, log, config, rulename, conda_env, container_img, singularity_args, env_modules, bench_record, jobid, bench_iteration, cleanup_scripts, shadow_dir, ): """ Load a script from the given basedir + path and execute it. """ path, source, language = get_source(path, basedir, wildcards, params) exec_class = { "python": PythonScript, "r": RScript, "rmarkdown": RMarkdown, "julia": JuliaScript, }.get(language, None) if exec_class is None: raise ValueError( "Unsupported script: Expecting either Python (.py), R (.R), RMarkdown (.Rmd) or Julia (.jl) script." ) executor = exec_class( path, source, basedir, input, output, params, wildcards, threads, resources, log, config, rulename, conda_env, container_img, singularity_args, env_modules, bench_record, jobid, bench_iteration, cleanup_scripts, shadow_dir, ) executor.evaluate()