def main():
amo = AddonsService(login_prompter=login_prompter_impl)
cookiedefault = os.path.expanduser('~/.amo_cookie')
def load_context(args):
amo.session.load(args.cookies)
amo.session.timeout = args.timeout
return amo
handler = ArgumentHandler(use_subcommand_help=True)
handler.add_argument('-c',
'--cookies',
default=cookiedefault,
help='the file to save the session cookies to')
handler.add_argument('--timeout',
type=int,
default=None,
help='timeout for http requests')
handler.set_logging_argument('-d',
'--debug',
default_level=logging.WARNING,
config_fxn=init_logging)
try:
handler.run(sys.argv[1:], context_fxn=load_context)
amo.persist()
except KeyboardInterrupt:
pass
def main(args=None):
handler = ArgumentHandler()
handler.set_subcommands(
{'sample': sample,
'download': download,
'canvas': canvas,
'atvec': atvec} )
handler.run()
def train_model(parser, context, args):
"""Emit the path to the autocomplete script for use with eval $(snap autocomplete)"""
handler = ArgumentHandler(
usage="Method to train the model",
description="Trains the model manually from the cli",
epilog="Train the model manually")
handler.add_argument('-o', '--output', dest='model_path', default='out')
handler.add_argument('-f', '--file', dest='training_file', default=None)
out, file = handler.parse_known_args(args)
if not check_path_validity(out.model_path):
try:
os.mkdir(out.model_path)
except TypeError:
raise Exception("Please provide a valid path to create the model.")
if not check_path_validity(out.training_file):
raise Exception(
"Training file doesn't exists please provide full path.")
main(output_dir=out.model_path, training_file=out.training_file)
def main():
amo = AddonsService(login_prompter=login_prompter_impl)
cookiedefault = os.path.expanduser('~/.amo_cookie')
def load_context(args):
amo.session.load(args.cookies)
return amo
handler = ArgumentHandler()
handler.add_argument('-c', '--cookies', default=cookiedefault,
help='the file to save the session cookies to')
handler.set_logging_argument('-d', '--debug', default_level=logging.WARNING,
config_fxn=init_logging)
handler.run(sys.argv[1:], context_fxn=load_context)
amo.persist()
def main(args=None):
handler = ArgumentHandler()
handler.set_subcommands({
'sample': sample,
'download': download,
'atvec': atvec
})
handler.run()
def main():
handler = ArgumentHandler(
use_subcommand_help=True,
epilog='Get help on a subcommand: igen subcommand -h')
handler.add_argument('-v',
'--version',
action='version',
version=__version__,
help='show the version number and exit')
handler.run()
def main():
amo = AddonsService(login_prompter=login_prompter_impl)
cookiedefault = os.path.expanduser('~/.amo_cookie')
def load_context(args):
amo.session.load(args.cookies)
return amo
handler = ArgumentHandler()
handler.add_argument('-c', '--cookies', default=cookiedefault,
help='the file to save the session cookies to')
handler.set_logging_argument('-d', '--debug', default_level=logging.WARNING,
config_fxn=init_logging)
handler.run(sys.argv[1:], context_fxn=load_context)
amo.persist()
def main():
handler = ArgumentHandler(
use_subcommand_help=True,
enable_autocompletion=True,
epilog='Get help on a subcommand: igen subcommand -h'
)
handler.add_argument(
'-v', '--version',
action='version',
version=__version__,
help='show the version number'
)
# if no parameters are provided, show help
if len(sys.argv) == 1:
handler.run(['-h'])
else:
handler.run()
def classifier_model_cli(parser, context, args):
"""Emit the path to the autocomplete script for use with eval $(snap autocomplete)"""
handler = ArgumentHandler(
usage="Method to train the model",
description="Trains the model manually from the cli",
epilog="Train the model manually")
handler.set_subcommands({
'train': train_model,
})
handler.run(args, context_fxn={})
def main(args=sys.argv[1:]): # noqa pragma: no cover
"""Parse the args, run the commands."""
handler = ArgumentHandler(
epilog="description",
formatter_class=RawDescriptionHelpFormatter,
)
handler.set_subcommands({
'classifier': classifier_model_cli,
'help': subcmd_help
})
handler.run(args, context_fxn={})
def main():
def load_context(args):
if args.input == sys.stdin:
data = codecs.getreader('utf8')(sys.stdin).read()
else:
data = codecs.open(args.input, encoding="utf-8").read()
return {"gargs": args, "patch": PatchSet(data)}
handler = ArgumentHandler()
handler.add_argument('-f',
'--file',
default=sys.stdin,
dest='input',
help="The file to input from")
try:
handler.run(sys.argv[1:], context_fxn=load_context)
except KeyboardInterrupt:
pass
def main():
handler = ArgumentHandler()
handler.run()
def main():
# load basic config info
config_info = config.load_default_config_info()
# run the program
handler = ArgumentHandler('enchant', use_subcommand_help=True)
handler.set_logging_argument('-L')
handler.add_argument('-H',
'--host',
default=config_info.host,
help='the host for the enchant server')
handler.add_argument('-P',
'--port',
type=int,
default=config_info.port,
help='the port for the enchant server')
handler.add_argument('-u',
'--username',
default=config_info.username,
help='the username to use')
handler.add_argument('-p',
'--password',
default=config_info.password,
help='the password to use')
handler.run()
source_tokenizer = tokenizer(config['source_tokenizer'],
lowercase=config['source_lowercase'])
source_eval = read(args.source_eval, source_tokenizer, config['backwards'])
log.info('Loading Target Evaluation data')
target_tokenizer = tokenizer('word',
lowercase=config['target_lowercase'])
references = read(args.target_eval, target_tokenizer, False)
log.info('Translating...')
output_file = open(os.path.dirname(args.source_eval) + '/result.data.eval',
'w', encoding='utf-8')
for i, sent in enumerate(model.translate(source_eval, encode=True, nbest=nbest)):
print(sent, file=output_file, flush=True)
hypotheses.append(word_tokenize(sent))
output_file.close()
log.info('Process finished')
if __name__ == '__main__':
with open('logo.txt', 'r') as f:
text = f.read()
for line in text.split('\n'):
print(line)
f.close()
handler = ArgumentHandler(enable_autocompletion=True,
description='FILIPINEU: Filipino - English Neural Machine Translation')
handler.run()
#!/usr/bin/python
# PYTHON_ARGCOMPLETE_OK
from arghandler import ArgumentHandler, subcmd
@subcmd('echo')
def echo(parser, context, args):
print args
@subcmd('add')
def add(parser, context, args):
print sum(args)
if __name__ == '__main__':
handler = ArgumentHandler(enable_autocompletion=True)
handler.run()
print("")
def delete_stuff(path, confirm_path):
""" Deletes path and logs deleted stuff
"""
if os.path.exists(path):
if os.path.isfile(path):
jmt.delete_file(path, confirm_path)
elif os.path.isdir(path):
jmt.delete_tree(path, confirm_path)
else:
raise Exception("File is neither a directory nor a file: %s" %
path)
deleted.append(path)
delete_stuff(eld_admin, "_private/%s" % ld)
delete_stuff(pubeld, "exams/%s" % ld)
delete_stuff(pubeldzip,
'_static/generated/%s-%s-exam.zip' % (jm.filename, ld))
if len(deleted) == 0:
fatal("COULDN'T FIND ANY EXAM FILE TO DELETE FOR DATE: " + ld)
handler = ArgumentHandler(description='Manages ' + jm.filename + ' exams.',
use_subcommand_help=True)
handler.run()
print("")
info("DONE.\n")
def main():
handler = ArgumentHandler()
handler.run()
#!/usr/bin/python
# PYTHON_ARGCOMPLETE_OK
from arghandler import ArgumentHandler, subcmd
@subcmd('echo')
def echo(parser,context,args):
print args
@subcmd('add')
def add(parser,context,args):
print sum(args)
if __name__ == '__main__':
handler = ArgumentHandler(enable_autocompletion=True)
handler.run()
