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(): 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")
#!/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()