Python os.makedirs() Examples
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Example #1
Source File: demo.py From svviz with MIT License | 30 votes |
def downloadDemo(which): try: downloadDir = tempfile.mkdtemp() archivePath = "{}/svviz-data.zip".format(downloadDir) # logging.info("Downloading...") downloadWithProgress("http://svviz.github.io/svviz/assets/examples/{}.zip".format(which), archivePath) logging.info("Decompressing...") archive = zipfile.ZipFile(archivePath) archive.extractall("{}".format(downloadDir)) if not os.path.exists("svviz-examples"): os.makedirs("svviz-examples/") shutil.move("{temp}/{which}".format(temp=downloadDir, which=which), "svviz-examples/") except Exception as e: print("error downloading and decompressing example data: {}".format(e)) return False if not os.path.exists("svviz-examples"): print("error finding example data after download and decompression") return False return True
Example #2
Source File: ssm.py From aegea with Apache License 2.0 | 9 votes |
def ensure_session_manager_plugin(): session_manager_dir = os.path.join(config.user_config_dir, "bin") PATH = os.environ.get("PATH", "") + ":" + session_manager_dir if shutil.which("session-manager-plugin", path=PATH): subprocess.check_call(["session-manager-plugin"], env=dict(os.environ, PATH=PATH)) else: os.makedirs(session_manager_dir, exist_ok=True) target_path = os.path.join(session_manager_dir, "session-manager-plugin") if platform.system() == "Darwin": download_session_manager_plugin_macos(target_path=target_path) elif platform.linux_distribution()[0] == "Ubuntu": download_session_manager_plugin_linux(target_path=target_path) else: download_session_manager_plugin_linux(target_path=target_path, pkg_format="rpm") os.chmod(target_path, stat.S_IRUSR | stat.S_IWUSR | stat.S_IXUSR) subprocess.check_call(["session-manager-plugin"], env=dict(os.environ, PATH=PATH)) return shutil.which("session-manager-plugin", path=PATH)
Example #3
Source File: utils.py From incubator-spot with Apache License 2.0 | 8 votes |
def create_oa_folders(cls, type, date): # create date and ingest summary folder structure if they don't' exist. root_path = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) data_type_folder = "{0}/data/{1}/{2}" if not os.path.isdir(data_type_folder.format(root_path, type, date)): os.makedirs( data_type_folder.format(root_path, type, date)) if not os.path.isdir(data_type_folder.format(root_path, type, "ingest_summary")): os.makedirs( data_type_folder.format(root_path, type, "ingest_summary")) # create ipynb folders. ipynb_folder = "{0}/ipynb/{1}/{2}".format(root_path, type, date) if not os.path.isdir(ipynb_folder): os.makedirs(ipynb_folder) # retun path to folders. data_path = data_type_folder.format(root_path, type, date) ingest_path = data_type_folder.format(root_path, type, "ingest_summary") return data_path, ingest_path, ipynb_folder
Example #4
Source File: web.py From wechat-alfred-workflow with MIT License | 8 votes |
def save_to_path(self, filepath): """Save retrieved data to file at ``filepath``. .. versionadded: 1.9.6 :param filepath: Path to save retrieved data. """ filepath = os.path.abspath(filepath) dirname = os.path.dirname(filepath) if not os.path.exists(dirname): os.makedirs(dirname) self.stream = True with open(filepath, 'wb') as fileobj: for data in self.iter_content(): fileobj.write(data)
Example #5
Source File: utils.py From pytorch_NER_BiLSTM_CNN_CRF with Apache License 2.0 | 7 votes |
def save_model_all(model, save_dir, model_name, epoch): """ :param model: nn model :param save_dir: save model direction :param model_name: model name :param epoch: epoch :return: None """ if not os.path.isdir(save_dir): os.makedirs(save_dir) save_prefix = os.path.join(save_dir, model_name) save_path = '{}_epoch_{}.pt'.format(save_prefix, epoch) print("save all model to {}".format(save_path)) output = open(save_path, mode="wb") torch.save(model.state_dict(), output) # torch.save(model.state_dict(), save_path) output.close()
Example #6
Source File: os_utils.py From godot-mono-builds with MIT License | 6 votes |
def mkdir_p(path): if not os.path.exists(path): print('creating directory: ' + path) os.makedirs(path) # Remove files and/or directories recursively
Example #7
Source File: __init__.py From aegea with Apache License 2.0 | 6 votes |
def initialize(): global config, parser from .util.printing import BOLD, RED, ENDC config = AegeaConfig(__name__, use_yaml=True, save_on_exit=False) if not os.path.exists(config.config_files[2]): config_dir = os.path.dirname(os.path.abspath(config.config_files[2])) try: os.makedirs(config_dir) except OSError as e: if not (e.errno == errno.EEXIST and os.path.isdir(config_dir)): raise shutil.copy(os.path.join(os.path.dirname(__file__), "user_config.yml"), config.config_files[2]) logger.info("Wrote new config file %s with default values", config.config_files[2]) config = AegeaConfig(__name__, use_yaml=True, save_on_exit=False) parser = argparse.ArgumentParser( description="{}: {}".format(BOLD() + RED() + __name__.capitalize() + ENDC(), fill(__doc__.strip())), formatter_class=AegeaHelpFormatter ) parser.add_argument("--version", action="version", version="%(prog)s {}\n{} {}\n{}".format( __version__, platform.python_implementation(), platform.python_version(), platform.platform() )) def help(args): parser.print_help() register_parser(help)
Example #8
Source File: _qemu.py From ALF with Apache License 2.0 | 6 votes |
def _remote_init(working_dir): global pickle import pickle import sys import shutil import os if not os.path.isdir(working_dir): os.mkdir(working_dir) sys.path.append(working_dir) shutil.move("_common.py", working_dir) shutil.move("_gdb.py", working_dir) shutil.move("cmds.gdb", working_dir) # setup CERT exploitable exp_lib_dir = os.path.join(working_dir, "exploitable", "lib") os.makedirs(exp_lib_dir) shutil.move("exploitable.py", os.path.join(working_dir, "exploitable")) shutil.move("__init__.py", exp_lib_dir) shutil.move("analyzers.py", exp_lib_dir) shutil.move("classifier.py", exp_lib_dir) shutil.move("elf.py", exp_lib_dir) shutil.move("gdb_wrapper.py", exp_lib_dir) shutil.move("rules.py", exp_lib_dir) shutil.move("tools.py", exp_lib_dir) shutil.move("versions.py", exp_lib_dir) os.chdir(working_dir) global _common global _gdb import _common import _gdb
Example #9
Source File: build.py From Traffic_sign_detection_YOLO with MIT License | 6 votes |
def savepb(self): """ Create a standalone const graph def that C++ can load and run. """ darknet_pb = self.to_darknet() flags_pb = self.FLAGS flags_pb.verbalise = False flags_pb.train = False # rebuild another tfnet. all const. tfnet_pb = TFNet(flags_pb, darknet_pb) tfnet_pb.sess = tf.Session(graph = tfnet_pb.graph) # tfnet_pb.predict() # uncomment for unit testing name = 'built_graph/{}.pb'.format(self.meta['name']) os.makedirs(os.path.dirname(name), exist_ok=True) #Save dump of everything in meta with open('built_graph/{}.meta'.format(self.meta['name']), 'w') as fp: json.dump(self.meta, fp) self.say('Saving const graph def to {}'.format(name)) graph_def = tfnet_pb.sess.graph_def tf.train.write_graph(graph_def,'./', name, False)
Example #10
Source File: worker.py From neural-fingerprinting with BSD 3-Clause "New" or "Revised" License | 6 votes |
def fetch_attacks_data(self): """Initializes data necessary to execute attacks. This method could be called multiple times, only first call does initialization, subsequent calls are noop. """ if self.attacks_data_initialized: return # init data from datastore self.submissions.init_from_datastore() self.dataset_batches.init_from_datastore() self.adv_batches.init_from_datastore() # copy dataset locally if not os.path.exists(LOCAL_DATASET_DIR): os.makedirs(LOCAL_DATASET_DIR) eval_lib.download_dataset(self.storage_client, self.dataset_batches, LOCAL_DATASET_DIR, os.path.join(LOCAL_DATASET_COPY, self.dataset_name, 'images')) # download dataset metadata self.read_dataset_metadata() # mark as initialized self.attacks_data_initialized = True
Example #11
Source File: isodump3.py From multibootusb with GNU General Public License v2.0 | 6 votes |
def writeDir_r(self, det_dir, dire, pp, r, all_type): #gen.log "writeDir_r:(%s)"%(det_dir) dirs = self.readDirItems(dire.locExtent, dire.lenData) for d in dirs: if not d.fIdentifier in [".", ".."]: if (pp != None) and (pp.search(d.fIdentifier) == None): match = False else: match = True #gen.log "mathing %s, %s, (%x)"%(match, d.fIdentifier, d.fFlag) p = det_dir + "/" + d.fIdentifier if d.fFlag & 0x02 == 0x02: if not os.path.exists(p): os.makedirs(p, 0o777) if r: if match: self.writeDir_r(p, d, None, r, all_type) # Don't need to match subdirectory. else: self.writeDir_r(p, d, pp, r, all_type) elif match: self.writeFile(d, p, all_type) # if not d.fIdentifier end # # for d in dirs end #
Example #12
Source File: demo_letter_duvenaud.py From nmp_qc with MIT License | 6 votes |
def plot_examples(data_loader, model, epoch, plotter, ind = [0, 10, 20]): # switch to evaluate mode model.eval() for i, (g, h, e, target) in enumerate(data_loader): if i in ind: subfolder_path = 'batch_' + str(i) + '_t_' + str(int(target[0][0])) + '/epoch_' + str(epoch) + '/' if not os.path.isdir(args.plotPath + subfolder_path): os.makedirs(args.plotPath + subfolder_path) num_nodes = torch.sum(torch.sum(torch.abs(h[0, :, :]), 1) > 0) am = g[0, 0:num_nodes, 0:num_nodes].numpy() pos = h[0, 0:num_nodes, :].numpy() plotter.plot_graph(am, position=pos, fig_name=subfolder_path+str(i) + '_input.png') # Prepare input data if args.cuda: g, h, e, target = g.cuda(), h.cuda(), e.cuda(), target.cuda() g, h, e, target = Variable(g), Variable(h), Variable(e), Variable(target) # Compute output model(g, h, e, lambda cls, id: plotter.plot_graph(am, position=pos, cls=cls, fig_name=subfolder_path+ id))
Example #13
Source File: dump_model_files.py From models with MIT License | 6 votes |
def get_models_overall(exp_name, rbp): print("RBP: " + rbp) out_h5 = "{rbp}/model_files/model.h5".format(rbp=rbp) os.makedirs(os.path.dirname(out_h5), exist_ok=True) trials = CMongoTrials(DB_NAME, exp_name + "_" + rbp, ip=HOST) # no trials yet - return None if trials.n_ok() == 0: trials = CMongoTrials(DB_NAME[:-2], exp_name + "_" + rbp, ip=HOST) if trials.n_ok() == 0: raise Exception("No trials") print("N trials: {0}".format(trials.n_ok())) # get best trial parameters tid = trials.best_trial_tid() model_path = trials.get_trial(tid)["result"]["path"]["model"] copyfile(model_path, out_h5)
Example #14
Source File: utils.py From pytorch_NER_BiLSTM_CNN_CRF with Apache License 2.0 | 6 votes |
def save_best_model(model, save_dir, model_name, best_eval): """ :param model: nn model :param save_dir: save model direction :param model_name: model name :param best_eval: eval best :return: None """ if best_eval.current_dev_score >= best_eval.best_dev_score: if not os.path.isdir(save_dir): os.makedirs(save_dir) model_name = "{}.pt".format(model_name) save_path = os.path.join(save_dir, model_name) print("save best model to {}".format(save_path)) # if os.path.exists(save_path): os.remove(save_path) output = open(save_path, mode="wb") torch.save(model.state_dict(), output) # torch.save(model.state_dict(), save_path) output.close() best_eval.early_current_patience = 0 # adjust lr
Example #15
Source File: dataset.py From spleeter with MIT License | 6 votes |
def cache(self, dataset, cache, wait): """ Cache the given dataset if cache is enabled. Eventually waits for cache to be available (useful if another process is already computing cache) if provided wait flag is True. :param dataset: Dataset to be cached if cache is required. :param cache: Path of cache directory to be used, None if no cache. :param wait: If caching is enabled, True is cache should be waited. :returns: Cached dataset if needed, original dataset otherwise. """ if cache is not None: if wait: while not exists(f'{cache}.index'): get_logger().info( 'Cache not available, wait %s', self.WAIT_PERIOD) time.sleep(self.WAIT_PERIOD) cache_path = os.path.split(cache)[0] os.makedirs(cache_path, exist_ok=True) return dataset.cache(cache) return dataset
Example #16
Source File: dataset.py From vergeml with MIT License | 5 votes |
def download_files(self, urls, env, headers=None, dir=None): if dir is None: dir = env.get('cache-dir') dest_directory = os.path.join(dir, "tmp_" + str(uuid.uuid4())) if not os.path.exists(dest_directory): os.makedirs(dest_directory) for data_url in urls: if isinstance(data_url, tuple): data_url, download_file = data_url else: download_file = data_url.split('/')[-1] download_path = os.path.join(dest_directory, download_file) if headers: opener = urllib.request.build_opener() opener.addheaders = headers urllib.request.install_opener(opener) try: urllib.request.urlretrieve(data_url, filename=download_path, reporthook=self._report_hook(download_file), data=None) except Exception as e: raise VergeMLError("Could not download {}: {}".format(data_url, e)) finally: if headers: urllib.request.install_opener(urllib.request.build_opener()) return dest_directory
Example #17
Source File: request.py From mlbv with GNU General Public License v3.0 | 5 votes |
def _get_cachedir(): cachedir = os.path.join(util.get_tempdir(), 'cache') if not os.path.exists(cachedir): LOG.debug('Creating cache directory: ' + cachedir) if not os.path.exists(cachedir): os.makedirs(cachedir) return cachedir
Example #18
Source File: config.py From mlbv with GNU General Public License v3.0 | 5 votes |
def generate_config(username=None, password=None, servicename="MLB.tv"): """Creates config file from template + user prompts.""" script_name = os.path.splitext(os.path.basename(sys.argv[0]))[0] # use the script name minus any extension for the config directory config_dir = None config_dir = os.path.join(Config.config_dir_roots[1], script_name) if not os.path.exists(config_dir): print("Creating config directory: {}".format(config_dir)) os.makedirs(config_dir) config_file = os.path.join(config_dir, 'config') if os.path.exists(config_file): print("Aborting: The config file already exists at '{}'".format(config_file)) return False # copy the template config file print("Generating basic config file at: {}".format(config_dir)) current_dir = os.path.dirname(inspect.getfile(inspect.currentframe())) template_config_path = os.path.abspath(os.path.join(current_dir, '../../..', 'config.template')) if not os.path.exists(template_config_path): print("Could not find template config file [expected at: {}]".format(template_config_path)) return False if username is None: username = input('Enter {} username: '.format(servicename)) if password is None: password = input('Enter {} password: '.format(servicename)) with open(template_config_path, 'r') as infile, open(config_file, 'w') as outfile: for line in infile: if line.startswith('# username='): outfile.write("username={}\n".format(username)) elif line.startswith('# password='): outfile.write("password={}\n".format(password)) else: outfile.write(line) print("Finished creating config file: {}".format(config_file)) print("You may want to edit it now to set up favourites, etc.") return True
Example #19
Source File: from_xueqiu.py From Financial-NLP with Apache License 2.0 | 5 votes |
def download(x): count=0 article_link=x.find_elements_by_class_name('home__timeline__item') logfp=open(log_file,'a') for l in article_link: try: time=l.find_element_by_class_name('timestamp').text.split(' ')[0] time=sdtime(time) l.find_element_by_xpath('h3/a').click() t=l.find_element_by_xpath('h3/a').text title,flag=clean_invalid(t) if flag: logfp.writelines(t) logfp.write('\n') windows = x.window_handles x.switch_to.window(windows[-1]) txt=x.find_element_by_xpath('//div[@class="article__bd__detail"]').text if not os.path.exists(work_space+'/article/'+time+'/'): os.makedirs(work_space+'/article/'+time+'/') txt_filename=work_space+'/article/'+time+'/'+title+'.txt' fp=open(txt_filename,'w',encoding='utf-8') fp.writelines(txt) fp.close() x.close() count+=1 x.switch_to.window(windows[0]) except: windows = x.window_handles x.switch_to.window(windows[0]) continue logfp.close() print('downloaded %d articles.' % count)
Example #20
Source File: compat.py From aegea with Apache License 2.0 | 5 votes |
def makedirs(name, mode=0o777, exist_ok=False): try: os.makedirs(name, mode) except OSError as e: if not (exist_ok and e.errno == errno.EEXIST and os.path.isdir(name)): raise
Example #21
Source File: download.py From arm_now with MIT License | 5 votes |
def download_from_github(arch): templates = str(Path.home()) + "/.config/arm_now/templates/" os.makedirs(templates) filename = arch + ".tar.xz" URL = "https://github.com/nongiach/arm_now_templates/raw/master/" download(URL + filename, templates + filename, Config.DOWNLOAD_CACHE_DIR)
Example #22
Source File: arm_now.py From arm_now with MIT License | 5 votes |
def do_offline(): URL = "https://github.com/nongiach/arm_now_templates/archive/master.zip" templates = str(Path.home()) + "/.config/arm_now/templates/" master_zip = str(Path.home()) + "/.config/arm_now/templates/master.zip" os.makedirs(templates) # download_from_github(arch) download(URL, master_zip, Config.DOWNLOAD_CACHE_DIR) os.chdir(templates) check_call("unzip master.zip", shell=True) check_call("mv arm_now_templates-master/* .", shell=True) check_call("rm -rf arm_now_templates-master/ README.md master.zip", shell=True)
Example #23
Source File: calc.py From aospy with Apache License 2.0 | 5 votes |
def _save_files(self, data, dtype_out_time): """Save the data to netcdf files in direc_out.""" path = self.path_out[dtype_out_time] if not os.path.isdir(self.dir_out): os.makedirs(self.dir_out) if 'reg' in dtype_out_time: try: reg_data = xr.open_dataset(path) except (EOFError, RuntimeError, IOError): reg_data = xr.Dataset() reg_data.update(data) data_out = reg_data else: data_out = data if isinstance(data_out, xr.DataArray): data_out = xr.Dataset({self.name: data_out}) data_out.to_netcdf(path, engine='netcdf4')
Example #24
Source File: workflow.py From wechat-alfred-workflow with MIT License | 5 votes |
def _create(self, dirpath): """Create directory `dirpath` if it doesn't exist. :param dirpath: path to directory :type dirpath: ``unicode`` :returns: ``dirpath`` argument :rtype: ``unicode`` """ if not os.path.exists(dirpath): os.makedirs(dirpath) return dirpath
Example #25
Source File: train_val.py From Collaborative-Learning-for-Weakly-Supervised-Object-Detection with MIT License | 5 votes |
def __init__(self, network, imdb, roidb, valroidb, output_dir, tbdir, pretrained_model=None, wsddn_premodel=None): self.net = network self.imdb = imdb self.roidb = roidb self.valroidb = valroidb self.output_dir = output_dir self.tbdir = tbdir # Simply put '_val' at the end to save the summaries from the validation set self.tbvaldir = tbdir + '_val' if not os.path.exists(self.tbvaldir): os.makedirs(self.tbvaldir) self.pretrained_model = pretrained_model self.wsddn_premodel = wsddn_premodel
Example #26
Source File: train_val.py From Collaborative-Learning-for-Weakly-Supervised-Object-Detection with MIT License | 5 votes |
def snapshot(self, iter): net = self.net if not os.path.exists(self.output_dir): os.makedirs(self.output_dir) # Store the model snapshot filename = cfg.TRAIN.SNAPSHOT_PREFIX + '_iter_{:d}'.format(iter) + '.pth' filename = os.path.join(self.output_dir, filename) torch.save(self.net.state_dict(), filename) print('Wrote snapshot to: {:s}'.format(filename)) if iter % 10000 == 0: shutil.copyfile(filename, filename + '.{:d}_cache'.format(iter)) # Also store some meta information, random state, etc. nfilename = cfg.TRAIN.SNAPSHOT_PREFIX + '_iter_{:d}'.format(iter) + '.pkl' nfilename = os.path.join(self.output_dir, nfilename) # current state of numpy random st0 = np.random.get_state() # current position in the database cur = self.data_layer._cur # current shuffled indexes of the database perm = self.data_layer._perm # current position in the validation database cur_val = self.data_layer_val._cur # current shuffled indexes of the validation database perm_val = self.data_layer_val._perm # Dump the meta info with open(nfilename, 'wb') as fid: pickle.dump(st0, fid, pickle.HIGHEST_PROTOCOL) pickle.dump(cur, fid, pickle.HIGHEST_PROTOCOL) pickle.dump(perm, fid, pickle.HIGHEST_PROTOCOL) pickle.dump(cur_val, fid, pickle.HIGHEST_PROTOCOL) pickle.dump(perm_val, fid, pickle.HIGHEST_PROTOCOL) pickle.dump(iter, fid, pickle.HIGHEST_PROTOCOL) return filename, nfilename
Example #27
Source File: config.py From Collaborative-Learning-for-Weakly-Supervised-Object-Detection with MIT License | 5 votes |
def get_output_dir(imdb, weights_filename): """Return the directory where experimental artifacts are placed. If the directory does not exist, it is created. A canonical path is built using the name from an imdb and a network (if not None). """ outdir = osp.abspath(osp.join(__C.ROOT_DIR, 'output', __C.EXP_DIR, imdb.name)) if weights_filename is None: weights_filename = 'default' outdir = osp.join(outdir, weights_filename) if not os.path.exists(outdir): os.makedirs(outdir) return outdir
Example #28
Source File: config.py From Collaborative-Learning-for-Weakly-Supervised-Object-Detection with MIT License | 5 votes |
def get_output_tb_dir(imdb, weights_filename): """Return the directory where tensorflow summaries are placed. If the directory does not exist, it is created. A canonical path is built using the name from an imdb and a network (if not None). """ outdir = osp.abspath(osp.join(__C.ROOT_DIR, 'tensorboard', __C.EXP_DIR, imdb.name)) if weights_filename is None: weights_filename = 'default' outdir = osp.join(outdir, weights_filename) if not os.path.exists(outdir): os.makedirs(outdir) return outdir
Example #29
Source File: imdb.py From Collaborative-Learning-for-Weakly-Supervised-Object-Detection with MIT License | 5 votes |
def cache_path(self): cache_path = osp.abspath(osp.join(cfg.DATA_DIR, 'cache')) if not os.path.exists(cache_path): os.makedirs(cache_path) return cache_path
Example #30
Source File: main.py From controllable-text-attribute-transfer with Apache License 2.0 | 5 votes |
def preparation(): # set model save path if args.if_load_from_checkpoint: timestamp = args.checkpoint_name else: timestamp = str(int(time.time())) print("create new model save path: %s" % timestamp) args.current_save_path = 'save/%s/' % timestamp args.log_file = args.current_save_path + time.strftime("log_%Y_%m_%d_%H_%M_%S.txt", time.localtime()) args.output_file = args.current_save_path + time.strftime("output_%Y_%m_%d_%H_%M_%S.txt", time.localtime()) print("create log file at path: %s" % args.log_file) if os.path.exists(args.current_save_path): add_log("Load checkpoint model from Path: %s" % args.current_save_path) else: os.makedirs(args.current_save_path) add_log("Path: %s is created" % args.current_save_path) # set task type if args.task == 'yelp': args.data_path = '../../data/yelp/processed_files/' elif args.task == 'amazon': args.data_path = '../../data/amazon/processed_files/' elif args.task == 'imagecaption': pass else: raise TypeError('Wrong task type!') # prepare data args.id_to_word, args.vocab_size, \ args.train_file_list, args.train_label_list = prepare_data( data_path=args.data_path, max_num=args.word_dict_max_num, task_type=args.task ) return