Source code for snakemake.utils

__author__ = "Johannes Köster"
__copyright__ = "Copyright 2021, Johannes Köster"
__email__ = ""
__license__ = "MIT"

import os
import json
import re
import inspect
from snakemake.sourcecache import LocalSourceFile, infer_source_file
import textwrap
import platform
from itertools import chain
import collections
import multiprocessing
import string
import shlex
import sys
from urllib.parse import urljoin
from urllib.request import url2pathname

from import regex, Namedlist, Wildcards, _load_configfile
from snakemake.logging import logger
from snakemake.common import ON_WINDOWS, is_local_file, smart_join
from snakemake.exceptions import WorkflowError
import snakemake

[docs]def validate(data, schema, set_default=True): """Validate data with JSON schema at given path. Args: data (object): data to validate. Can be a config dict or a pandas data frame. schema (str): Path to JSON schema used for validation. The schema can also be in YAML format. If validating a pandas data frame, the schema has to describe a row record (i.e., a dict with column names as keys pointing to row values). See The path is interpreted relative to the Snakefile when this function is called. set_default (bool): set default values defined in schema. See for more information """ frame = inspect.currentframe().f_back workflow = frame.f_globals.get("workflow") if workflow and workflow.modifier.skip_validation: # skip if a corresponding modifier has been defined return try: import jsonschema from jsonschema import validators, RefResolver except ImportError: raise WorkflowError( "The Python 3 package jsonschema must be installed " "in order to use the validate directive." ) schemafile = infer_source_file(schema) if isinstance(schemafile, LocalSourceFile) and not schemafile.isabs() and workflow: # if workflow object is not available this has not been started from a workflow schemafile = workflow.current_basedir.join(schemafile) source = ( if workflow else schemafile.get_path_or_uri() ) schema = _load_configfile(source, filetype="Schema") if isinstance(schemafile, LocalSourceFile): resolver = RefResolver( urljoin("file:", schemafile.get_path_or_uri()), schema, handlers={ "file": lambda uri: _load_configfile(re.sub("^file://", "", uri)) }, ) else: resolver = RefResolver( schemafile.get_path_or_uri(), schema, ) # Taken from def extend_with_default(validator_class): validate_properties = validator_class.VALIDATORS["properties"] def set_defaults(validator, properties, instance, schema): for property, subschema in properties.items(): if "default" in subschema: instance.setdefault(property, subschema["default"]) for error in validate_properties(validator, properties, instance, schema): yield error return validators.extend(validator_class, {"properties": set_defaults}) Validator = validators.validator_for(schema) if Validator.META_SCHEMA["$schema"] != schema["$schema"]: logger.warning( "No validator found for JSON Schema version identifier '{}'".format( schema["$schema"] ) ) logger.warning( "Defaulting to validator for JSON Schema version '{}'".format( Validator.META_SCHEMA["$schema"] ) ) logger.warning("Note that schema file may not be validated correctly.") DefaultValidator = extend_with_default(Validator) if not isinstance(data, dict): try: import pandas as pd recordlist = [] if isinstance(data, pd.DataFrame): for i, record in enumerate(data.to_dict("records")): record = {k: v for k, v in record.items() if not pd.isnull(v)} try: if set_default: DefaultValidator(schema, resolver=resolver).validate(record) recordlist.append(record) else: jsonschema.validate(record, schema, resolver=resolver) except jsonschema.exceptions.ValidationError as e: raise WorkflowError( "Error validating row {} of data frame.".format(i), e ) if set_default: newdata = pd.DataFrame(recordlist, data.index) newcol = ~newdata.columns.isin(data.columns) n = len(data.columns) for col in newdata.loc[:, newcol].columns: data.insert(n, col, newdata.loc[:, col]) n = n + 1 return except ImportError: pass raise WorkflowError("Unsupported data type for validation.") else: try: if set_default: DefaultValidator(schema, resolver=resolver).validate(data) else: jsonschema.validate(data, schema, resolver=resolver) except jsonschema.exceptions.ValidationError as e: raise WorkflowError("Error validating config file.", e)
[docs]def simplify_path(path): """Return a simplified version of the given path.""" relpath = os.path.relpath(path) if relpath.startswith("../../"): return path else: return relpath
[docs]def linecount(filename): """Return the number of lines of given file. Args: filename (str): the path to the file """ with open(filename) as f: return sum(1 for l in f)
[docs]def listfiles(pattern, restriction=None, omit_value=None): """Yield a tuple of existing filepaths for the given pattern. Wildcard values are yielded as the second tuple item. Args: pattern (str): a filepattern. Wildcards are specified in snakemake syntax, e.g. "{id}.txt" restriction (dict): restrict to wildcard values given in this dictionary omit_value (str): wildcard value to omit Yields: tuple: The next file matching the pattern, and the corresponding wildcards object """ pattern = os.path.normpath(pattern) first_wildcard ="{[^{]", pattern) if first_wildcard: dirname = os.path.dirname(pattern[: first_wildcard.start()]) if not dirname: dirname = "." else: dirname = os.path.dirname(pattern) pattern = re.compile(regex(pattern)) for dirpath, dirnames, filenames in os.walk(dirname): for f in chain(filenames, dirnames): if dirpath != ".": f = os.path.normpath(os.path.join(dirpath, f)) match = re.match(pattern, f) if match: wildcards = Namedlist(fromdict=match.groupdict()) if restriction is not None: invalid = any( omit_value not in v and v != wildcards[k] for k, v in restriction.items() ) if not invalid: yield f, wildcards else: yield f, wildcards
[docs]def makedirs(dirnames): """Recursively create the given directory or directories without reporting errors if they are present. """ if isinstance(dirnames, str): dirnames = [dirnames] for dirname in dirnames: os.makedirs(dirname, exist_ok=True)
[docs]def report( text, path, stylesheet=None, defaultenc="utf8", template=None, metadata=None, **files ): """Create an HTML report using python docutils. This is deprecated in favor of the --report flag. 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: .. code:: python 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) Args: text (str): The "restructured text" as it is expected by python docutils. path (str): The path to the desired output file stylesheet (str): An optional path to a css file that defines the style of the document. This defaults to <your snakemake install>/report.css. Use the default to get a hint how to create your own. defaultenc (str): The encoding that is reported to the browser for embedded text files, defaults to utf8. template (str): An optional path to a docutils HTML template. metadata (str): E.g. an optional author name or email address. """ if stylesheet is None: os.path.join(os.path.dirname(__file__), "report.css") try: import except ImportError: raise WorkflowError( "Python 3 package docutils needs to be installed to use the report function." ) text, path, stylesheet=stylesheet, defaultenc=defaultenc, template=template, metadata=metadata, **files )
[docs]def R(code): """Execute R code. This is deprecated in favor of the ``script`` directive. This function executes the R code given as a string. The function requires rpy2 to be installed. Args: code (str): R code to be executed """ try: import rpy2.robjects as robjects except ImportError: raise ValueError( "Python 3 package rpy2 needs to be installed to use the R function." ) robjects.r(format(textwrap.dedent(code), stepout=2))
[docs]class SequenceFormatter(string.Formatter): """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). """ def __init__( self, separator=" ", element_formatter=string.Formatter(), *args, **kwargs ): self.separator = separator self.element_formatter = element_formatter
[docs] def format_element(self, elem, format_spec): """Format a single element For sequences, this is called once for each element in a sequence. For anything else, it is called on the entire object. It is intended to be overridden in subclases. """ return self.element_formatter.format_field(elem, format_spec)
[docs] def format_field(self, value, format_spec): if isinstance(value, Wildcards): return ",".join( "{}={}".format(name, value) for name, value in sorted(value.items(), key=lambda item: item[0]) ) if isinstance(value, (list, tuple, set, frozenset)): return self.separator.join( self.format_element(v, format_spec) for v in value ) else: return self.format_element(value, format_spec)
[docs]class QuotedFormatter(string.Formatter): """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. """ def __init__(self, quote_func=None, *args, **kwargs): if quote_func is None: quote_func = shlex.quote self.quote_func = quote_func super().__init__(*args, **kwargs)
[docs] def format_field(self, value, format_spec): if format_spec.endswith("u"): format_spec = format_spec[:-1] do_quote = False else: do_quote = format_spec.endswith("q") if do_quote: format_spec = format_spec[:-1] formatted = super().format_field(value, format_spec) if do_quote and formatted != "": formatted = self.quote_func(formatted) return formatted
[docs]class AlwaysQuotedFormatter(QuotedFormatter): """Subclass of QuotedFormatter that always quotes. Usage is identical to QuotedFormatter, except that it *always* acts like "q" was appended to the format spec, unless u (for unquoted) is appended. """
[docs] def format_field(self, value, format_spec): if not format_spec.endswith("q") and not format_spec.endswith("u"): format_spec += "q" return super().format_field(value, format_spec)
[docs]def format(_pattern, *args, stepout=1, _quote_all=False, quote_func=None, **kwargs): """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. """ frame = inspect.currentframe().f_back while stepout > 1: if not frame.f_back: break frame = frame.f_back stepout -= 1 variables = dict(frame.f_globals) # add local variables from calling rule/function variables.update(frame.f_locals) if "self" in variables and sys.version_info < (3, 5): # self is the first arg of fmt.format as well. Not removing it would # cause a multiple values error on Python <=3.4.2. del variables["self"] variables.update(kwargs) fmt = SequenceFormatter(separator=" ") if _quote_all: fmt.element_formatter = AlwaysQuotedFormatter(quote_func) else: fmt.element_formatter = QuotedFormatter(quote_func) try: return fmt.format(_pattern, *args, **variables) except KeyError as ex: if str(ex).strip("'") in variables["wildcards"].keys(): raise NameError( "The name '{0}' is unknown in this context. " "Did you mean 'wildcards.{0}'?".format(str(ex).strip("'")) ) raise NameError( "The name {} is unknown in this context. Please " "make sure that you defined that variable. " "Also note that braces not used for variable access " "have to be escaped by repeating them, " "i.e. {{{{print $1}}}}".format(str(ex)) )
[docs]class Unformattable: def __init__(self, errormsg="This cannot be used for formatting"): self.errormsg = errormsg def __str__(self): raise ValueError(self.errormsg)
[docs]def read_job_properties( jobscript, prefix="# properties", pattern=re.compile("# properties = (.*)") ): """Read the job properties defined in a snakemake jobscript. This function is a helper for writing custom wrappers for the snakemake --cluster functionality. Applying this function to a jobscript will return a dict containing information about the job. """ with open(jobscript) as jobscript: for m in map(pattern.match, jobscript): if m: return json.loads(
[docs]def min_version(version): """Require minimum snakemake version, raise workflow error if not met.""" import pkg_resources if pkg_resources.parse_version(snakemake.__version__) < pkg_resources.parse_version( version ): raise WorkflowError( "Expecting Snakemake version {} or higher (you are currently using {}).".format( version, snakemake.__version__ ) )
[docs]def update_config(config, overwrite_config): """Recursively update dictionary config with overwrite_config. See for details. Args: config (dict): dictionary to update overwrite_config (dict): dictionary whose items will overwrite those in config """ def _update(d, u): for (key, value) in u.items(): if isinstance(value, d[key] = _update(d.get(key, {}), value) else: d[key] = value return d _update(config, overwrite_config)
[docs]def available_cpu_count(): """ Return the number of available virtual or physical CPUs on this system. The number of available CPUs can be smaller than the total number of CPUs when the cpuset(7) mechanism is in use, as is the case on some cluster systems. Adapted from """ try: with open("/proc/self/status") as f: status = m ="(?m)^Cpus_allowed:\s*(.*)$", status) if m: res = bin(int(",", ""), 16)).count("1") if res > 0: return min(res, multiprocessing.cpu_count()) except IOError: pass return multiprocessing.cpu_count()
[docs]def argvquote(arg, force=True): """Returns an argument quoted in such a way that that CommandLineToArgvW on Windows will return the argument string unchanged. This is the same thing Popen does when supplied with an list of arguments. Arguments in a command line should be separated by spaces; this function does not add these spaces. This implementation follows the suggestions outlined here: """ if not force and len(arg) != 0 and not any([c in arg for c in ' \t\n\v"']): return arg else: n_backslashes = 0 cmdline = '"' for c in arg: if c == "\\": # first count the number of current backslashes n_backslashes += 1 continue if c == '"': # Escape all backslashes and the following double quotation mark cmdline += (n_backslashes * 2 + 1) * "\\" else: # backslashes are not special here cmdline += n_backslashes * "\\" n_backslashes = 0 cmdline += c # Escape all backslashes, but let the terminating # double quotation mark we add below be interpreted # as a metacharacter cmdline += +n_backslashes * 2 * "\\" + '"' return cmdline
[docs]def cmd_exe_quote(arg): """Quotes an argument in a cmd.exe compliant way.""" arg = argvquote(arg) cmd_exe_metachars = '^()%!"<>&|' for char in cmd_exe_metachars: arg.replace(char, "^" + char) return arg
[docs]def os_sync(): """Ensure flush to disk""" if not ON_WINDOWS: os.sync()
[docs]def find_bash_on_windows(): """ Find the path to a usable bash on windows. First attempt is to look for bash installed with a git conda package. alternatively try bash installed with 'Git for Windows'. """ if not ON_WINDOWS: return None # First look for bash in git's conda package bashcmd = os.path.join(os.path.dirname(sys.executable), r"Library\bin\bash.exe") if not os.path.exists(bashcmd): # Otherwise try bash installed with "Git for Windows". import winreg try: key = winreg.OpenKey(winreg.HKEY_LOCAL_MACHINE, "SOFTWARE\\GitForWindows") gfwp, _ = winreg.QueryValueEx(key, "InstallPath") bashcmd = os.path.join(gfwp, "bin\\bash.exe") except FileNotFoundError: bashcmd = "" return bashcmd if os.path.exists(bashcmd) else None
[docs]class Paramspace: """A wrapper for pandas dataframes that provides helpers for using them as a parameter space in Snakemake. This is heavily inspired by @soumitrakp work on JUDI ( By default, a directory structure with on folder level per parameter is created (e.g. column1~{column1}/column2~{column2}/***). The exact behavior can be tweeked with two parameters: - ``filename_params`` takes a list of column names of the passed dataframe. These names are used to build the filename (separated by '_') in the order in which they are passed. All remaining parameters will be used to generate a directoty structure. Example for a data frame with four columns named column1 to column4: | ``Paramspace(df, filename_params=["column3", "column2"])`` -> | column1~{value1}/column4~{value4}/column3~{value3}_column2~{value2} If ``filename_params="*"``, all columns of the dataframe are encoded into the filename instead of parent directories. - ``param_sep`` takes a string which is used to join the column name and column value in the genrated paths (Default: '~'). Example: | ``Paramspace(df, param_sep=":")`` -> | column1:{value1}/column2:{value2}/column3:{value3}/column4:{value4} """ def __init__(self, dataframe, filename_params=None, param_sep="~"): self.dataframe = dataframe self.param_sep = param_sep if filename_params is None or not filename_params: # create a pattern of the form {}/{}/{} with one entry for each # column in the dataframe self.pattern = "/".join([r"{}"] * len(self.dataframe.columns)) self.ordered_columns = self.dataframe.columns else: if isinstance(filename_params, str) and filename_params == "*": filename_params = dataframe.columns if any((param not in dataframe.columns for param in filename_params)): raise KeyError( "One or more entries of filename_params are not valid coulumn names for the param file." ) elif len(set(filename_params)) != len(filename_params): raise ValueError("filename_params must be unique") # create a pattern of the form {}/{}_{} with one entry for each # column in the dataframe. The number of underscore-separated # fields is equal to the number filename_params self.pattern = "/".join( [r"{}"] * (len(self.dataframe.columns) - len(filename_params) + 1) ) self.pattern = "_".join( [self.pattern] + [r"{}"] * (len(filename_params) - 1) ) self.ordered_columns = [ param for param in self.dataframe.columns if param not in filename_params ] self.ordered_columns.extend(list(filename_params)) self.dataframe = self.dataframe[self.ordered_columns] @property def wildcard_pattern(self): """Wildcard pattern over all columns of the underlying dataframe of the form column1~{column1}/column2~{column2}/*** or of the provided custom pattern. """ return self.pattern.format( *map(self.param_sep.join(("{0}", "{{{0}}}")).format, self.ordered_columns) ) @property def instance_patterns(self): """Iterator over all instances of the parameter space (dataframe rows), formatted as file patterns of the form column1~{value1}/column2~{value2}/... or of the provided custom pattern. """ return ( self.pattern.format( *( self.param_sep.join(("{}", "{}")).format(name, value) for name, value in row.items() ) ) for index, row in self.dataframe.iterrows() )
[docs] def instance(self, wildcards): """Obtain instance (dataframe row) with the given wildcard values.""" import pandas as pd def convert_value_dtype(name, value): if self.dataframe.dtypes[name] == bool and value == "False": # handle problematic case when boolean False is returned as # boolean True because the string "False" is misinterpreted return False else: return pd.Series([value]).astype(self.dataframe.dtypes[name])[0] return { name: convert_value_dtype(name, value) for name, value in wildcards.items() if name in self.ordered_columns }
def __getattr__(self, name): import pandas as pd ret = getattr(self.dataframe, name) if isinstance(ret, pd.DataFrame): return Paramspace(ret) return ret def __getitem__(self, key): import pandas as pd ret = self.dataframe[key] if isinstance(ret, pd.DataFrame): return Paramspace(ret) return ret