我们从Python开源项目中，提取了以下10个代码示例，用于说明如何使用utils.mkdir()。
def parse_testing_data(dataset, output): rm_postag = re.compile(r'/[\w\-\.\,\?\"\':\!\@\#\$%%\^\&\*\(\)\[\]_\+\=\\\`\~]+') utils.mkdir(output) stack = os.listdir(dataset) print 'loading data in ' + dataset while (len(stack) > 0): file_name = stack.pop() file_path = dataset + '/' + file_name if (os.path.isdir(file_path)): # neu la thu muc thi day vao strong stack utils.push_data_to_stack(stack, file_path, file_name) else: # nguoc lai tien hanh readfile with open(file_path, 'r', encoding='utf-8') as ff: content = ff.read() content = rm_postag.sub(u'', content) content = content.replace(u'/“', u'').replace(u'/”', u'')\ .replace(u'/…', u'').replace(u'…', u'...') with open(output + '/' + file_name, 'w', encoding='utf-8') as f: f.write(content)
def save_model(self, model, path): print('saving %s ...' % (path)) utils.mkdir('model') joblib.dump(model, path) return
def save_training(self, X_train, y_train, X_test, y_test): utils.mkdir('model') self.save_model(X_train, 'model/X_train.pkl') self.save_model(X_test, 'model/X_test.pkl') self.save_model(y_train, 'model/y_train.pkl') self.save_model(y_test, 'model/y_test.pkl')
def parse_training_data(dataset, output): utils.mkdir(output) stack = os.listdir(dataset) print 'loading data in ' + dataset while (len(stack) > 0): file_name = stack.pop() file_path = dataset + '/' + file_name if (os.path.isdir(file_path)): # neu la thu muc thi day vao strong stack utils.push_data_to_stack(stack, file_path, file_name) else: # nguoc lai tien hanh readfile with open(file_path, 'r', encoding='utf-8') as ff: content = ff.read() bs = BeautifulSoup(content) with open(output + '/' + file_name, 'w', encoding='utf-8') as f: f.write(bs.text)
def init_logging(args, conf): '''Initialize the logging system. Uses argdir and id from args, adds 'trackfile' to conf as a file object to which track data should be written.''' # setup log files filetimestamp = time.strftime("%Y%m%d-%H%M%S") if args.id: name = "%s-%s" % (filetimestamp, args.id) else: name = filetimestamp conf['name'] = name # ensure log and image directories exist utils.mkdir(config.TRACKDIR, config.REMOTE_USER) debugframe_dir = "%s/%s" % (config.DBGFRAMEDIR, name) # Make debugframedir world-writable so rsync can delete it. oldmask = os.umask(0) utils.mkdir(debugframe_dir, config.REMOTE_USER) os.umask(oldmask) conf['debugframe_dir'] = debugframe_dir trackfilename = "%s/%s-track.csv" % (config.TRACKDIR, name) logfilename = "%s/%s.log" % (config.TRACKDIR, name) # Setup the ROOT level logger to send to a log file and console both logger = logging.getLogger() logger.setLevel(logging.INFO) fh = logging.FileHandler(filename=logfilename) fh.setFormatter( logging.Formatter(fmt="%(asctime)s [%(levelname)s] %(message)s")) sh = logging.StreamHandler() sh.setFormatter( logging.Formatter(fmt="[%(levelname)s] %(message)s")) logger.addHandler(fh) logger.addHandler(sh) logging.info("Logging started.") conf['trackfile'] = open(trackfilename, 'w')
def _relative_move(srcroot, srcrel, destroot): ''' Move a file relative to a given root to a given destination. E.g. relative_move('foo/', 'bar/baz', 'bob/') will move foo/bar/baz into bob/bar/baz, creating bob/bar if needed. ''' srcfile = srcroot / srcrel destfile = destroot / srcrel utils.mkdir(destfile.parent) # make sure directory exists shutil.move(str(srcfile), str(destfile))
def init_db(): utils.mkdir(config.db_dir) conn = sqlite3.connect("%s/%s" % (config.db_dir, config.db_file)) c = conn.cursor() c.execute('''Create table features (digest text, content text, currency text, t text, size INTEGER, n INTEGER, increase real, feature_size INTEGER, point INTEGER)''') c.execute('''Create table trade (tid INTEGER PRIMARY KEY, created_at INTEGER default 0, updated_at INTEGER default 0, digest text, buy real default 0.0, sell real default 0.0)''') c.execute('''Create table training (tid INTEGER PRIMARY KEY, created_at INTEGER default 0, updated_at INTEGER default 0, digest text, buy real default 0.0, sell real default 0.0)''') conn.commit() conn.close()
def set_name(self, name): if name is not None: self.name = name self.path = directories.MODELS + name + '/' utils.mkdir(self.path)
def __init__(self, name='clusterer', # model initialization load_weights_from=None, weights_file=None, randomize_weights=False, # network architecture top_layers=3, learnable_layers=3, pooling='maxavg', risk_objective=True, # dropout and learning rates input_dropout=0, dropout=0.0, learning_rate=1e-7): assert pooling in ['max', 'avg', 'maxavg'] self.name = name self.path = directories.CLUSTERERS + '/' utils.mkdir(self.path) self.load_weights_from = load_weights_from self.weights_file = weights_file self.randomize_weights = randomize_weights self.top_layers = top_layers self.learnable_layers = learnable_layers self.pooling = pooling self.risk_objective = risk_objective self.input_dropout = input_dropout self.dropout = dropout self.learning_rate = learning_rate self.single_size = 855 if directories.CHINESE else 674 self.pair_size = 1733 if directories.CHINESE else 1370 self.static_layers = top_layers - learnable_layers if self.static_layers == 0: self.anaphoricity_input_size = self.single_size self.pair_input_size = self.pair_size elif self.static_layers == 1: self.anaphoricity_input_size = self.pair_input_size = 1000 else: self.anaphoricity_input_size = self.pair_input_size = 500
