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How to use create_folder method in SeleniumBase

Best Python code snippet using SeleniumBase

factory.py

Source:factory.py

...8from . import cars1969from . import stanford_online_products10from . import afew11from . import affect12def create_folder(pathname, name):    13    # create path name dir        14    pathname = os.path.join(pathname, name )15    if not os.path.exists(pathname):16        os.makedirs(pathname)17    return pathname18class FactoryDataset(object):19    20    training = 'train'21    validation = 'val'22    test = 'test'23    mnist='mnist'24    fashion='fashion'25    emnist='emnist'26    cifar10='cifar10'27    cifar100='cifar100'28    stl10='stl10'29    svhn='svhn'30    imaterialist='imaterialist'31    32    ferp='ferp'33    ck='ck'34    jaffe='jaffe'35    bu3dfe='bu3dfe'36    afew='afew'37    affect='affectnet'38    affectdark='affectnetdark'39    cub2011='cub2011'40    cars196='cars196'41    stanford_online_products='stanford_online_products'42    cub2011metric='cub2011metric'43    cars196metric='cars196metric'44    45    @classmethod46    def _checksubset(self, subset): 47        return subset=='train' or subset=='val' or subset=='test'48    @classmethod49    def factory(self,         50        pathname,51        name,52        subset='train',53        download=False,54        transform=None,55        ):56        """Factory dataset57        """58        assert( self._checksubset(subset) )59        pathname = os.path.expanduser(pathname)60        61        # pythorch vision dataset soported62        if name == 'mnist':   63            btrain=(subset=='train')64            pathname = create_folder(pathname, name)65            data = datasets.MNIST( pathname, train=btrain, transform=transform, download=download)       66            data.labels = np.array( data.targets )        67        elif name == 'fashion':68            btrain=(subset=='train')69            pathname = create_folder(pathname, name)70            data = datasets.FashionMNIST(pathname, train=btrain, transform=transform, download=download)71            data.labels = np.array( data.targets )72        elif name == 'emnist':            73            btrain=(subset=='train')74            pathname = create_folder(pathname, name)75            data = datasets.EMNIST(pathname, split='byclass', train=btrain, transform=transform, download=download)76            data.labels = np.array( data.targets )  77        elif name == 'cifar10':     78            btrain=(subset=='train')  79            pathname = create_folder(pathname, name)     80            data = datasets.CIFAR10(pathname, train=btrain, transform=transform, download=download)81            data.labels = np.array( data.targets )  82        elif name == 'cifar100':  83            btrain=(subset=='train')  84            pathname = create_folder(pathname, name)          85            data = datasets.CIFAR100(pathname, train=btrain, transform=transform, download=download)86            data.labels = np.array( data.targets )87        elif name == 'stl10':  88            split= 'train' if (subset=='train')  else 'test'89            pathname = create_folder(pathname, name)          90            data = datasets.STL10(pathname, split=split, transform=transform, download=download)91        elif name == 'svhn':92            split= 'train' if (subset=='train')  else 'test'93            pathname = create_folder(pathname, name)          94            data = datasets.SVHN(pathname, split=split, transform=transform, download=download)95            data.classes = np.unique( data.labels )96        # internet dataset97   98        elif name == 'cub2011':  99            btrain=(subset=='train')100            pathname = create_folder(pathname, name)         101            data = cub2011.CUB2011(pathname, train=btrain, download=download)102            data.labels = np.array( data.targets )  103        elif name == 'cars196':  104            btrain=(subset=='train')105            pathname = create_folder(pathname, name)         106            data = cars196.Cars196(pathname, train=btrain, download=download)107            data.labels = np.array( data.targets ) 108        elif name == 'stanford_online_products':  109            btrain=(subset=='train')110            pathname = create_folder(pathname, name)       111            data = stanford_online_products.StanfordOnlineProducts(pathname, train=btrain, download=download)112            data.labels = np.array( data.targets )  113            data.btrain = btrain114        # kaggle dataset115        elif name == 'imaterialist':116            pathname = create_folder(pathname, name)117            data = imaterialist.IMaterialistDatset(pathname, subset, 'jpg')118        # fer datasets119        elif name == 'ferp':120            pathname = create_folder(pathname, name)            121            if subset=='train':   subfolder = ferp.train 122            elif subset=='val':   subfolder = ferp.valid123            elif subset=='test':  subfolder = ferp.test124            else:                 assert(False)    125            data = ferp.FERPDataset(pathname, subfolder, download=download)126        elif name == 'ck':127            btrain=(subset=='train') 128            pathname = create_folder(pathname, name)129            data = fer.FERClassicDataset(pathname, 'ck', idenselect=[], train=btrain)130        elif name == 'ckp':131            btrain=(subset=='train')132            pathname = create_folder(pathname, name)133            data = fer.FERClassicDataset(pathname, 'ckp', idenselect=[], train=btrain)134        elif name == 'jaffe':135            btrain=(subset=='train')136            pathname = create_folder(pathname, name)137            data = fer.FERClassicDataset(pathname, 'jaffe', idenselect=[], train=btrain)138 139        elif name == 'bu3dfe':140            btrain=(subset=='train')141            pathname = create_folder(pathname, name) 142            data = fer.FERClassicDataset(pathname, 'bu3dfe', idenselect=[], train=btrain)143        elif name == 'afew':  144            btrain=(subset=='train')145            pathname = create_folder(pathname, name)         146            data = afew.Afew(pathname, train=btrain, download=download)147            data.labels = np.array( data.targets )   148    149        elif name == 'affectnet':150            btrain=(subset=='train')151            pathname = create_folder(pathname, name)152            data = affect.create_affect(path=pathname, train=btrain)153        elif name == 'affectnetdark':154            btrain=(subset=='train')155            pathname = create_folder(pathname, 'affectnet')156            data = affect.create_affectdark(path=pathname, train=btrain)157        # metric learning dataset158        elif name == 'cub2011metric':  159            btrain=(subset=='train')       160            pathname = create_folder(pathname, 'cub2011')161            data = cub2011.CUB2011MetricLearning(pathname, train=btrain, download=download)162            data.labels = np.array( data.targets )  163        elif name == 'cars196metric':  164            btrain=(subset=='train')       165            pathname = create_folder(pathname, 'cars196')166            data = cars196.Cars196MetricLearning(pathname, train=btrain, download=download)167            data.labels = np.array( data.targets ) 168            169        else: 170            assert(False)171        data.btrain = (subset=='train')...

migrations.py

Source:migrations.py

2import utils3print(os.getcwd())4os.chdir('..')5CONSTANTS = utils.Defaults()6utils.create_folder(directory=os.getcwd(), name='log')7utils.create_folder(directory=os.getcwd(), name='data')8utils.create_folder(directory=os.path.join(os.getcwd(), 'data'), name='raw')9utils.create_folder(directory=os.path.join(os.getcwd(), 'data'), name='swamp')10utils.create_folder(directory=os.path.join(os.getcwd(), 'data'), name='lake')11utils.create_folder(directory=os.path.join(os.getcwd(), 'data', 'raw'), name='megasena')12utils.create_folder(directory=os.path.join(os.getcwd(), 'data', 'raw'), name='quina')13utils.create_folder(directory=os.path.join(os.getcwd(), 'data', 'raw'), name='lotofacil')14utils.create_folder(directory=os.path.join(os.getcwd(), 'data', 'swamp'), name='megasena')15utils.create_folder(directory=os.path.join(os.getcwd(), 'data', 'swamp'), name='quina')16utils.create_folder(directory=os.path.join(os.getcwd(), 'data', 'swamp'), name='lotofacil')17utils.create_folder(directory=os.path.join(os.getcwd(), 'data', 'lake'), name='megasena')18utils.create_folder(directory=os.path.join(os.getcwd(), 'data', 'lake'), name='quina')...

config.py

Source:config.py

1import os.path2def create_folder(name):3    if not os.path.exists(name):4        os.makedirs(name)5    return name6home_folder = os.path.expanduser("~")7root_folder = create_folder(os.path.join(home_folder, ".raireplay"))8data_folder = create_folder(os.path.join(root_folder, "data"))9replay_folder = create_folder(os.path.join(data_folder, "replay"))10raiplay_folder = create_folder(os.path.join(data_folder, "raiplay"))11raiplayradio_folder = create_folder(os.path.join(data_folder, "raiplayradio"))12item_folder = create_folder(os.path.join(data_folder, "items"))13page_folder = create_folder(os.path.join(data_folder, "pages"))14demand_folder = create_folder(os.path.join(data_folder, "demand"))15tg_folder = create_folder(os.path.join(data_folder, "tg"))16mediaset_folder = create_folder(os.path.join(data_folder, "mediaset"))17pluzz_folder = create_folder(os.path.join(data_folder, "pluzz"))18tf1_folder = create_folder(os.path.join(data_folder, "tf1"))19m6_folder = create_folder(os.path.join(data_folder, "m6"))...

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