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#!/usr/bin/env python
from __future__ import print_function
"""
draw_specified_dependency_tree.py
"""
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# options
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from optparse import OptionParser
import sys, os
import os.path
try:
import StringIO as io
except:
import io as io
# add self to search path for testing
exe_path = os.path.split(os.path.abspath(sys.argv[0]))[0]
if __name__ == '__main__':
module_name = os.path.split(sys.argv[0])[1]
module_name = os.path.splitext(module_name)[0];
else:
module_name = __name__
# graph, task etc are one directory down
if __name__ == '__main__':
sys.path.append(os.path.abspath(os.path.join(exe_path,"..", "..")))
from ruffus import *
parser = OptionParser(version="%prog 1.0")
parser.add_option("-i", "--input_dot_file", dest="dot_file",
metavar="FILE",
default = os.path.join(exe_path, "dependency_data", "simple.dag"),
type="string",
help="name and path of tree file in modified DOT format used to generate "
"test script dependencies.")
parser.add_option("-o", "--output_file", dest="output_file",
metavar="FILE",
default = os.path.join(exe_path, "pipelines", "simple.py"),
type="string",
help="name and path of output python test script.")
parser.add_option("-v", "--verbose", dest = "verbose",
action="count", default=0,
help="Print more verbose messages for each additional verbose level.")
parser.add_option( "-J", "--jumble_task_order", dest = "jumble_task_order",
action="store_true", default=False,
help="Do not define task functions in order of dependency.")
parameters = [
]
mandatory_parameters = ["dot_file"]
#88888888888888888888888888888888888888888888888888888888888888888888888888888888888888888
# imports
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import re
import operator
import sys
from collections import defaultdict
import random
# use simplejson in place of json for python < 2.6
try:
import json
except ImportError:
import simplejson
json = simplejson
dumps = json.dumps
#88888888888888888888888888888888888888888888888888888888888888888888888888888888888888888
# Functions
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#_________________________________________________________________________________________
# make_tree_from_dotfile
#_________________________________________________________________________________________
from adjacent_pairs_iterate import adjacent_pairs_iterate
#_________________________________________________________________________________________
# task_dependencies_from_dotfile
#_________________________________________________________________________________________
def task_dependencies_from_dotfile(stream):
"""
Read programme task specified in dot file format
"""
decorator_regex = re.compile(r"([a-z_]+) *(\(.*)")
attributes_regex = re.compile(r"\[.*\]")
which_task_follows = defaultdict(list)
task_decorators = defaultdict(list)
task_descriptions = dict()
#
# remember node
#
all_tasks = dict()
io_tasks = set()
for linenum, line in enumerate(stream):
# remove heading and trailing spaces
line = line.strip()
if "digraph" in line:
continue;
if not len(line):
continue
#
# decorators
#
if line[0:2] == '#@':
fields = line[2:].split('::', 2)
if len(fields) != 3:
raise Exception("Unexpected task specification on line# %d\n(%s)" %
(linenum, line))
task_name, decorators, description = fields
if decorators[0] != '@':
raise Exception("Task decorator missing starting ampersand '@' on line# %d\n(%s)" %
(linenum, line))
for d in decorators[1:].split("@"):
m = decorator_regex.match(d)
if not m:
raise Exception("Task decorator (%s) missing parentheses on line# %d\n(%s)" %
(d, linenum, line))
task_decorators[task_name].append((m.group(1), m.group(2)))
if m.group(1)[0:5] == "files" or m.group(1) == "parallel":
io_tasks.add(task_name)
task_descriptions[task_name] = description
continue
#
# other comments
#
if line[0] in '#{}/':
continue;
line = line.strip(';')
line = attributes_regex.sub("", line)
#
# ignore assignments
#
if "=" in line:
continue;
nodes = [x.strip() for x in line.split('->')]
for name1, name2 in adjacent_pairs_iterate(nodes):
which_task_follows[name2].append(name1)
all_tasks[name1] = 1
all_tasks[name2] = 1
for task in task_decorators:
if task not in all_tasks:
raise Exception("Decorated task %s not in dependencies")
# order tasks by precedence the dump way: iterating until true
disordered = True
while (disordered):
disordered = False
for to_task, from_tasks in which_task_follows.items():
for f in from_tasks:
if all_tasks[to_task] <= all_tasks[f]:
all_tasks[to_task] += all_tasks[f]
disordered = True
sorted_task_names = list(sorted(list(all_tasks.keys()), key=lambda x:all_tasks[x]))
return which_task_follows, sorted_task_names, task_decorators, io_tasks, task_descriptions
#_________________________________________________________________________________________
# generate_program_task_file
#_________________________________________________________________________________________
def generate_program_task_file(stream, task_dependencies, task_names,
task_decorators, io_tasks, task_descriptions):
print("task_decorators = ", dumps(task_decorators, indent = 4), file=sys.stderr)
print("task_names = ", dumps(task_names), file=sys.stderr)
print("task_dependencies = ", dumps(task_dependencies), file=sys.stderr)
print("io_tasks = ", dumps(list(io_tasks)), file=sys.stderr)
if options.jumble_task_order:
random.shuffle(task_names)
defined_tasks = set()
#
# iterate through tasks
#
for task_name in task_names:
defined_tasks.add(task_name)
stream.write("\n#\n# %s\n#\n" % task_name)
#
# write task decorators
#
if task_name in task_decorators:
for decorator, decorator_parameters in task_decorators[task_name]:
stream.write("@" + decorator + decorator_parameters + "\n")
#
# write task dependencies
#
if task_name in task_dependencies:
params = ", ".join(t if t in defined_tasks else '"%s"' % t
for t in task_dependencies[task_name])
stream.write("@follows(%s)\n" % params)
#
# Function body
#
#if task_name in io_tasks:
if 1:
stream.write("def %s(infiles, outfiles, *extra_params):\n" % task_name)
stream.write(' """\n')
description = task_descriptions[task_name]
description = description.replace("\n", " \n")
stream.write(' %s\n' % description)
stream.write(' """\n')
stream.write(" test_job_io(infiles, outfiles, extra_params)\n")
#else:
# stream.write("def %s(*params):\n" % task_name)
stream.write("\n\n")
stream.write(
"""
#
# Necessary to protect the "entry point" of the program under windows.
# see: http://docs.python.org/library/multiprocessing.html#multiprocessing-programming
#
if __name__ == '__main__':
try:
if options.just_print:
pipeline_printout(sys.stdout, options.target_tasks, options.forced_tasks,
long_winded=True,
gnu_make_maximal_rebuild_mode = not options.minimal_rebuild_mode)
elif options.dependency_file:
pipeline_printout_graph ( open(options.dependency_file, "w"),
options.dependency_graph_format,
options.target_tasks,
options.forced_tasks,
draw_vertically = not options.draw_horizontally,
gnu_make_maximal_rebuild_mode = not options.minimal_rebuild_mode,
no_key_legend = options.no_key_legend_in_graph)
else:
pipeline_run(options.target_tasks, options.forced_tasks, multiprocess = options.jobs,
gnu_make_maximal_rebuild_mode = not options.minimal_rebuild_mode,
pipeline= "main")
except Exception, e:
print e.args
\n""")
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# Main logic
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# get help string
f =io.StringIO()
parser.print_help(f)
helpstr = f.getvalue()
(options, remaining_args) = parser.parse_args()
# mandatory options
for parameter in mandatory_parameters:
if options.__dict__[parameter] is None:
die_error("Please specify a file in --%s.\n\n" % parameter + helpstr)
(task_dependencies, task_names,
task_decorators, io_tasks,
task_descriptions) = task_dependencies_from_dotfile(open(options.dot_file))
output_file = open(options.output_file, "w")
#
# print template for python file output
#
output_file.write(open(os.path.join(exe_path,"test_script.py_template")).read().
replace("PYPER_PATH",
os.path.abspath(os.path.join(exe_path, "..", ".."))))
generate_program_task_file(output_file, task_dependencies, task_names,
task_decorators, io_tasks, task_descriptions)
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