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How to use stop_chunk method in Playwright Python

Best Python code snippet using playwright-python

sources.py

Source:sources.py

1import os2import pickle3import re4import zipfile5from abc import ABC6from typing import List, Tuple7from Tools import ImageLoader8from container import Container9class Source(ABC):10    _chunk = -111    _chunks = []12    _dumping = True13    _chunk_size = 100014    def __init__(self, app: Container, chunk_size: int = 1000):15        self._chunk_size = chunk_size16        self.data = []17        self.length = 018        self.app = app19        self.loader = app.resolve(ImageLoader)20    def __iter__(self):21        self._current = 022        return self23    def __next__(self):24        index = self._current25        self._current += 126        if index >= self.length:27            raise StopIteration28        return self[index]29    def _slice_impl(self, item):30        full_list = []31        for chunk in self._chunks:32            full_list.extend(chunk)33        new_list = full_list[item.start:item.stop]34        source = Source(self.app)35        source._chunks = list(self.app.helper.list_chunk(new_list, self._chunk_size))36        source.length = len(new_list)37        return source38    def _item_impl(self, item):39        if self._chunk == -1 or self._chunk != int(item / self._chunk_size):40            self._chunk = int(item / self._chunk_size)41            self.data = self.loader(42                self._chunks[self._chunk]43            )44        image = self.data[item % self._chunk_size]45        return image.grayscale, image.thermal46    def __getitem__(self, item):47        if isinstance(item, slice):48            return self._slice_impl(item)49        return self._item_impl(item)50    def __len__(self):51        return self.length52    def dump(self, path: str):53        with open(path, 'wb') as bin_file:54            pickle.dump(self.data, bin_file)55    def load(self, path: str):56        with open(path, 'rb') as bin_file:57            self.data = pickle.load(bin_file)58    def chunks_dump(self):59        name = self.app.helper.time_name()60        os.mkdir(self.app.config('data.cache') + name)61        meta = []62        for i, datum in enumerate(self._chunks):63            self.data = self.loader(datum)64            self.dump(self.app.config('data.cache') + name + '/' + str(i) + '.pkl')65            meta.append((str(i) + '.pkl', len(self.data)))66        self.app.helper.dump_json(self.app.config('data.cache') + name + '/meta.json', meta)67class FileSource(Source):68    def __init__(self, app: Container, dir_name: str, dump: bool = True):69        super(FileSource, self).__init__(app)70        self.dir_name = dir_name71        self._dumping = dump72        self.fetch()73    def fetch(self):74        # Detect the zip files presented in given dir75        zip_files = []76        for file in os.listdir(self.dir_name):77            if re.match(r'(.*)\.zip', file):78                zip_files.append(79                    zipfile.ZipFile(self.dir_name + '/' + file)80                )81        manifest = []82        # Load data from each zip file83        for zip_file in zip_files:84            manifest += self.load_list(zip_file)85        self.length = len(manifest)86        # å è½½åè¡¨åå87        self._chunks = list(self.app.helper.list_chunk(manifest, self._chunk_size))88        if self._dumping:89            self.chunks_dump()90    @staticmethod91    def load_list(file: zipfile.ZipFile) -> list:92        nums = []93        # Determine the first file in zip file94        for name in file.namelist():95            # Extract every file from zip file96            file.extract(name, path='./storage/images')97            num = re.search(r'GS(.*)\.png', name)98            if num:99                nums.append(100                    int(num.group(1))101                )102        start = min(nums)103        # Determine the name of extract dir104        dir_name = file.namelist()[0].split('/')[0]105        # Transform the result file into a load list106        with open('./storage/images/' + dir_name + '/result.txt', 'r') as results_file:107            results = results_file.readlines()108        manifest = []109        for i, result in enumerate(results, start):110            result = result.split()111            manifest.append((112                file.filename + ':{GS|RGB}' + str(i) + '.png',113                './storage/images/' + dir_name + '/GS' + str(i) + '.png',114                './storage/images/' + dir_name + '/RGB' + str(i) + '.png',115                float(result[0]),116                float(result[1]),117            ))118        return manifest119class DBSource(Source):120    _chunk = -1121    _chunks = []122    _dumping = True123    def __init__(124            self,125            app: Container,126            db_hostname: str,127            db_username: str,128            db_password: str,129            db_name: str,130            base_url: str,131            dump: bool = True132    ):133        """134        Database Source Implementation135        Args:136            db_hostname: The hostname of database server137            db_username: The username of database server138            db_password: The password of database user139            db_name: The name of database to use140            base_url: The base url prefix append before images path141        """142        super(DBSource, self).__init__(app)143        import pymysql144        import threading145        self._dumping = dump146        self.base_url = base_url147        self.download_tasks = []148        self.manifest = []149        self.downloading = False150        # Init the connection to database151        self.connection = pymysql.Connection(152            user=db_username,153            password=db_password,154            host=db_hostname,155            database=db_name156        )157        self.base_db_url = 'mysql://' + self.connection.get_host_info().split()[-1] + '/' + db_name + '/'158        # Init two task threads159        self.fetcher = threading.Thread(target=self.fetch)160        self.downloader = threading.Thread(target=self.download)161        self.fetcher.start()162        self.downloader.start()163        # Wait both threads exit164        while True:165            if self.fetcher.is_alive():166                continue167            elif self.download_tasks:168                continue169            else:170                self.downloading = False171                break172        self._chunks = list(self.app.helper.list_chunk(self.manifest, self._chunk_size))173        self.length = len(self.manifest)174    def fetch(self) -> None:175        # Two cursors to perform different queries176        cursor_1 = self.connection.cursor()177        cursor_2 = self.connection.cursor()178        course = 'SELECT * from `mtrl_info`'  # Query all materials179        cursor_1.execute(course)180        materials = []181        while True:182            result = cursor_1.fetchone()183            if not result:184                break185            material_id = result[0]186            # Query all params belongs to current material187            course = 'SELECT * from `mtrl_para` where `mtrl_id` = %d' % material_id188            cursor_2.execute(course)189            params = cursor_2.fetchall()190            # Init a material param list and fill it191            material = [None, None, None, None, None]192            for param in params:193                material[194                    param[2]195                ] = (param[3] if param[2] in [1, 2] else (self.base_url + param[7]))196            urls = material[3:]197            material[0] = self.base_db_url + 'mtrl_info/' + str(material_id)198            material[3] = 'images/' + material[3].split('/')[-1]199            material[4] = 'images/' + material[4].split('/')[-1]200            # Push download task into the download tasks list201            self.download_tasks.append({'url': urls[0], 'path': 'images/'})202            self.download_tasks.append({'url': urls[1], 'path': 'images/'})203            # Push the material params list into the materials list204            materials.append(material)205        self._chunks = list(self.app.helper.list_chunk(materials, self._chunk_size))206        self.length = len(materials)207        if self._dumping:208            self.chunks_dump()209    def download(self):210        import requests211        # Downloading signal212        self.downloading = True213        while self.downloading:214            if self.download_tasks:215                task = self.download_tasks.pop()216                url = task['url']217                path = task['path']218                response = requests.get(url)219                filename = url.split('/')[-1]220                with open(path + filename, 'wb') as file:221                    file.write(response.content)222            else:223                continue224class SavedSource(Source):225    def __init__(self, app: Container, dir_name: str):226        """227        Load data from a previously bin source.228        Args:229            dir_name: The path to saves file230        """231        super(SavedSource, self).__init__(app)232        self.path = dir_name233        self.fetch()234        self.loader = self.load_chunk235    def refresh(self):236        length = 0237        for chunk in self._chunks:238            length += chunk[1] - chunk[2]239        self.length = length240        self._chunk = -1241        self.data = []242        return self243    def fetch(self):244        meta = self.app.helper.load_json(self.path + '/meta.json')245        self._chunks = []246        for chunk_desc in meta:247            self._chunks.append(tuple(chunk_desc) + (0,))248            self.length += chunk_desc[1]249    def load_chunk(self, chunk_desc):250        return self.load(self.path + '/' + chunk_desc[0])251    def locate_chunk(self, item):252        for _i, _chunk in enumerate(self._chunks):253            item -= _chunk[1] - _chunk[2]254            if item < 0:255                return _i, item + _chunk[1]256    def _slice_impl(self, item):257        new_source = SavedSource(self.app, self.path)258        if item.start is None:259            start_chunk, start_offset = 0, self._chunks[0][2]260        else:261            start_chunk, start_offset = self.locate_chunk(item.start)262        if item.stop is None:263            stop_chunk, stop_offset = len(self._chunks) - 1, self._chunks[-1][1]264        else:265            stop_chunk, stop_offset = self.locate_chunk(item.stop)266            if stop_offset == 0:267                stop_chunk -= 1268                stop_offset = self._chunks[stop_chunk][1]269        new_chunks = list(map(lambda x: list(x), self._chunks[start_chunk:stop_chunk + 1]))270        new_chunks[0][2] = start_offset271        new_chunks[-1][1] = stop_offset272        new_source._chunks = list(map(lambda x: tuple(x), new_chunks))273        new_source.refresh()274        return new_source275    def _item_impl(self, item):276        chunk, offset = self.locate_chunk(item)277        if self._chunk == -1 or self._chunk != chunk:278            self._chunk = chunk279            self.loader(self._chunks[self._chunk])280        image = self.data[offset]281        return image.grayscale, image.thermal282class TestSource(Source):283    resources = [284        ('tests/train-images-idx3-ubyte', 'tests/train-labels-idx1-ubyte'),285        ('tests/t10k-images-idx3-ubyte', 'tests/t10k-labels-idx1-ubyte')286    ]287    def __init__(self, app: Container):288        super(TestSource, self).__init__(app)289        self.data = self.fetch()290        pass291    def fetch(self) -> List[Tuple]:292        import struct293        from PIL import Image294        data = []295        for images, labels in self.resources:296            with open(images, 'br') as img_files, open(labels, 'br') as lab_files:297                # Read the magic number298                img_files.read(4)299                lab_files.read(8)300                # Read the file number301                num = img_files.read(4)302                num = struct.unpack('>i', num)[0]303                # Read the size of image304                height = struct.unpack('>i', img_files.read(4))[0]305                width = struct.unpack('>i', img_files.read(4))[0]306                size = width * height307                padding = b'\x00\x00\x00'308                # Read the images309                for i in range(num):310                    img = img_files.read(size)311                    lab = lab_files.read(1)312                    # Convert format313                    label = struct.unpack('>i', padding + lab)[0]314                    image = Image.frombytes(315                        mode='L',316                        size=(28, 28),317                        data=img318                    )319                    data.append((320                        self.loader.loader(image).unsqueeze(0).cuda(),321                        label322                    ))...

artist.py.svn-base

Source:artist.py.svn-base

1#!/usr/bin/env python2# encoding: utf-83"""4A Python interface to the The Echo Nest's web API.  See5http://developer.echonest.com/ for details.6"""7from config import CACHE8import document9import util10class Artist(object):11    def __init__(self, identifier, name=None):12        if len(identifier)==18:13            identifier = 'music://id.echonest.com/~/AR/' + identifier14        self._identifier = identifier15        self._name = name16        self._audio = document.WebDocumentSet(identifier, 'get_audio')17        self._image = document.WebDocumentSet(identifier, 'get_images')18        self._biographies = document.WebDocumentSet(identifier, 'get_biographies')19        self._blogs = document.WebDocumentSet(identifier, 'get_blogs')20        self._news = document.WebDocumentSet(identifier, 'get_news')21        self._reviews = document.WebDocumentSet(identifier, 'get_reviews')22        self._similar = SimilarDocumentSet(identifier)23        self._video = document.WebDocumentSet(identifier, 'get_video')24        self._familiarity = None25        self._hotttnesss = None26        self._urls = None27        self._terms = None28    def audio(self, rows=15, start=0, refresh=False):29        if refresh or not CACHE:30            self._audio = document.WebDocumentSet(self._identifier, 'get_audio')31        return self._audio[start:start + rows]32    def images(self, rows=15, start=0, refresh=False):33        if refresh or not CACHE:34            self._images = document.WebDocumentSet(self._identifier, 'get_images')35        return self._image[start:start + rows]36    37    def biographies(self, rows=15, start=0, refresh=False):38        if refresh or not CACHE:39            self._biographies = document.WebDocumentSet(self._identifier, 'get_biographies')40        return self._biographies[start:start + rows]41    def blogs(self, rows=15, start=0, refresh=False):42        if refresh or not CACHE:43            self._blogs = document.WebDocumentSet(self._identifier, 'get_blogs')44        return self._blogs[start:start + rows]45        46    def news(self, rows=15, start=0, refresh=False):47        if refresh or not CACHE:48            self._news = document.WebDocumentSet(self._identifier, 'get_news')49        return self._news[start:start + rows]50    51    def reviews(self, rows=15, start=0, refresh=False):52        if refresh or not CACHE:53            self._reviews = document.WebDocumentSet(self._identifier, 'get_reviews')54        return self._reviews[start:start + rows]55    56    def similar(self, rows=15, start=0, refresh=False):57        if refresh or not CACHE:58            self._similar = SimilarDocumentSet(self._identifier)59        return self._similar[start:start + rows]60    61    def video(self, rows=15, start=0, refresh=False):62        if refresh or not CACHE:63            self._video = document.WebDocumentSet(self._identifier, 'get_video')64        return self._video[start:start + rows]65    def familiarity(self, refresh=False):66        """Returns our numerical estimation of how 67        familiar an artist currently is to the world."""68        if self._familiarity is None or not CACHE:69            try:70                params = {'id': self.identifier}71                response = util.call('get_familiarity', params).findtext('artist/familiarity')72                self._familiarity = float(response)73            except:74                self._familiarity = 075        return self._familiarity76    def hotttnesss(self, refresh=False):77        """Returns our numerical description of how 78        hottt an artist currently is."""79        if self._hotttnesss is None or not CACHE:80            try:81                params = {'id': self.identifier}82                response = util.call('get_hotttnesss', params).findtext('artist/hotttnesss')83                self._hotttnesss = float(response)84            except:85                self._hotttnesss = 086        return self._hotttnesss87    @property88    def name(self):89        if self._name is None or not CACHE:90            self._name = util.call('get_profile', {'id': self.identifier}).findtext('artist/name')91        return self._name92        93    @property94    def identifier(self):95        """A unique identifier for an artist.96        See http://developer.echonest.com/docs/datatypes/97        for more information"""98        return self._identifier99    100    @property101    def urls(self):102        """Get links to the artist's official site, MusicBrainz site, 103        MySpace site, Wikipedia article, Amazon list, and iTunes page."""104        if self._urls is None or not CACHE:105            response = util.call('get_urls', {'id': self.identifier}).find('artist').getchildren()106            self._urls =  dict((url.tag[:-4], url.text) for url in response if url.tag[-4:] == '_url')107        return self._urls108    def terms(self):109        if self._terms is None or not CACHE:110            response = util.call('get_top_terms', {'id': self.identifier}).findall('terms/term')111            self._terms = [e.text for e in response]112        return self._terms113    def __repr__(self):114        return "<Artist '%s'>" % str(self)115    116    def __str__(self):117        return self.name if isinstance(self.name, str) else self.name.encode('utf-8')118        119    def clear_cache(self):120        pass121TRUTH = {True: 'Y', False: 'N'}122SEARCH_ARTISTS_CACHE = {}123def search_artists(name, exact=False, sounds_like=True, rows=15, refresh=False):124    """Search for an artist using a query on the artist name.125    This may perform a sounds-like search to correct common 126    spelling mistakes."""127    global SEARCH_ARTISTS_CACHE128    if CACHE and not refresh:129        try:130            return SEARCH_ARTISTS_CACHE[(name, exact, sounds_like, rows)]131        except KeyError:132            pass133    params = {'query': name, 'exact': TRUTH[exact], 134                'sounds_like': TRUTH[sounds_like], 'rows': rows}135    response = util.call('search_artists', params).findall('artists/artist')136    value = [Artist(a.findtext('id'), a.findtext('name')) for a in response]137    SEARCH_ARTISTS_CACHE[(name, exact, sounds_like, rows)] = value138    return value139TOP_HOTTT_ARTISTS_CACHE = []140def get_top_hottt_artists(rows=15, refresh=False):141    """Retrieves a list of the top hottt artists.142    Do not request this more than once an hour."""143    global TOP_HOTTT_ARTISTS_CACHE144    if TOP_HOTTT_ARTISTS_CACHE==[] or refresh or not CACHE:145        response = util.call('get_top_hottt_artists', {'rows': rows}).findall('artists/artist')146        TOP_HOTTT_ARTISTS_CACHE = [Artist(a.findtext('id'), a.findtext('name')) for a in response]147    return TOP_HOTTT_ARTISTS_CACHE148class SimilarDocumentSet(document.DocumentSet):149    def __init__(self, identifier):150        super(SimilarDocumentSet, self).__init__(identifier, 'get_similar', 'similar/artist')151    def __len__(self):152        if self._len is None:153            self._len = 100154        return self._len155    def __getitem__(self, k):156        if k.stop > 100:157            raise util.EchoNestAPIError(5, 'Invalid parameter: "rows" must be less than or equal to 100')158        chunk_and_index = lambda i: (i / self._cache.chunk_size, i % self._cache.chunk_size)159        start, start_chunk, start_index, stop = self.chunk_magic(k)160        if (stop + 1) > self._cache.chunk_size:161            self.__init__(self.identifier)162            self._cache.chunk_size = stop + 1163            chunk_and_index = lambda i: (i / self._cache.chunk_size, i % self._cache.chunk_size)164            start, start_chunk, start_index, stop = self.chunk_magic(k)165        stop_chunk, stop_index = chunk_and_index(stop)166        items = []167        for chunk in xrange(start_chunk, stop_chunk + 1):168            elements = self._cache[chunk].findall(self.element_path)169            if chunk == start_chunk and chunk == stop_chunk:170                elements = elements[start_index:stop_index + 1]171            elif chunk == start_chunk:172                elements = elements[start_index:]173            elif chunk == stop_chunk:174                elements = elements[:stop_index + 1]175            items.extend([self._parse_element(e) for e in elements])176        return items177    def chunk_magic(self, k):178        chunk_and_index = lambda i: (i / self._cache.chunk_size, i % self._cache.chunk_size)179        if not isinstance(k, slice):180            raise TypeError181        start = k.start or 0182        start_chunk, start_index = chunk_and_index(start)183        stop = min(k.stop or len(self), len(self)) - 1 # use inclusive to simplify logic184        return start, start_chunk, start_index, stop185    def _parse_element(self, element):...

artist.py

Source:artist.py

1#!/usr/bin/env python2# encoding: utf-83"""4A Python interface to the The Echo Nest's web API.  See5http://developer.echonest.com/ for details.6"""7from config import CACHE8import document9import util10class Artist(object):11    def __init__(self, identifier, name=None):12        if len(identifier)==18:13            identifier = 'music://id.echonest.com/~/AR/' + identifier14        self._identifier = identifier15        self._name = name16        self._audio = document.WebDocumentSet(identifier, 'get_audio')17        self._image = document.WebDocumentSet(identifier, 'get_images')18        self._biographies = document.WebDocumentSet(identifier, 'get_biographies')19        self._blogs = document.WebDocumentSet(identifier, 'get_blogs')20        self._news = document.WebDocumentSet(identifier, 'get_news')21        self._reviews = document.WebDocumentSet(identifier, 'get_reviews')22        self._similar = SimilarDocumentSet(identifier)23        self._video = document.WebDocumentSet(identifier, 'get_video')24        self._familiarity = None25        self._hotttnesss = None26        self._urls = None27        self._terms = None28    def audio(self, rows=15, start=0, refresh=False):29        if refresh or not CACHE:30            self._audio = document.WebDocumentSet(self._identifier, 'get_audio')31        return self._audio[start:start + rows]32    def images(self, rows=15, start=0, refresh=False):33        if refresh or not CACHE:34            self._images = document.WebDocumentSet(self._identifier, 'get_images')35        return self._image[start:start + rows]36    37    def biographies(self, rows=15, start=0, refresh=False):38        if refresh or not CACHE:39            self._biographies = document.WebDocumentSet(self._identifier, 'get_biographies')40        return self._biographies[start:start + rows]41    def blogs(self, rows=15, start=0, refresh=False):42        if refresh or not CACHE:43            self._blogs = document.WebDocumentSet(self._identifier, 'get_blogs')44        return self._blogs[start:start + rows]45        46    def news(self, rows=15, start=0, refresh=False):47        if refresh or not CACHE:48            self._news = document.WebDocumentSet(self._identifier, 'get_news')49        return self._news[start:start + rows]50    51    def reviews(self, rows=15, start=0, refresh=False):52        if refresh or not CACHE:53            self._reviews = document.WebDocumentSet(self._identifier, 'get_reviews')54        return self._reviews[start:start + rows]55    56    def similar(self, rows=15, start=0, refresh=False):57        if refresh or not CACHE:58            self._similar = SimilarDocumentSet(self._identifier)59        return self._similar[start:start + rows]60    61    def video(self, rows=15, start=0, refresh=False):62        if refresh or not CACHE:63            self._video = document.WebDocumentSet(self._identifier, 'get_video')64        return self._video[start:start + rows]65    def familiarity(self, refresh=False):66        """Returns our numerical estimation of how 67        familiar an artist currently is to the world."""68        if self._familiarity is None or not CACHE:69            try:70                params = {'id': self.identifier}71                response = util.call('get_familiarity', params).findtext('artist/familiarity')72                self._familiarity = float(response)73            except:74                self._familiarity = 075        return self._familiarity76    def hotttnesss(self, refresh=False):77        """Returns our numerical description of how 78        hottt an artist currently is."""79        if self._hotttnesss is None or not CACHE:80            try:81                params = {'id': self.identifier}82                response = util.call('get_hotttnesss', params).findtext('artist/hotttnesss')83                self._hotttnesss = float(response)84            except:85                self._hotttnesss = 086        return self._hotttnesss87    @property88    def name(self):89        if self._name is None or not CACHE:90            self._name = util.call('get_profile', {'id': self.identifier}).findtext('artist/name')91        return self._name92        93    @property94    def identifier(self):95        """A unique identifier for an artist.96        See http://developer.echonest.com/docs/datatypes/97        for more information"""98        return self._identifier99    100    @property101    def urls(self):102        """Get links to the artist's official site, MusicBrainz site, 103        MySpace site, Wikipedia article, Amazon list, and iTunes page."""104        if self._urls is None or not CACHE:105            response = util.call('get_urls', {'id': self.identifier}).find('artist').getchildren()106            self._urls =  dict((url.tag[:-4], url.text) for url in response if url.tag[-4:] == '_url')107        return self._urls108    def terms(self):109        if self._terms is None or not CACHE:110            response = util.call('get_top_terms', {'id': self.identifier}).findall('terms/term')111            self._terms = [e.text for e in response]112        return self._terms113    def __repr__(self):114        return "<Artist '%s'>" % str(self)115    116    def __str__(self):117        return self.name if isinstance(self.name, str) else self.name.encode('utf-8')118        119    def clear_cache(self):120        pass121TRUTH = {True: 'Y', False: 'N'}122SEARCH_ARTISTS_CACHE = {}123def search_artists(name, exact=False, sounds_like=True, rows=15, refresh=False):124    """Search for an artist using a query on the artist name.125    This may perform a sounds-like search to correct common 126    spelling mistakes."""127    global SEARCH_ARTISTS_CACHE128    if CACHE and not refresh:129        try:130            return SEARCH_ARTISTS_CACHE[(name, exact, sounds_like, rows)]131        except KeyError:132            pass133    params = {'query': name, 'exact': TRUTH[exact], 134                'sounds_like': TRUTH[sounds_like], 'rows': rows}135    response = util.call('search_artists', params).findall('artists/artist')136    value = [Artist(a.findtext('id'), a.findtext('name')) for a in response]137    SEARCH_ARTISTS_CACHE[(name, exact, sounds_like, rows)] = value138    return value139TOP_HOTTT_ARTISTS_CACHE = []140def get_top_hottt_artists(rows=15, refresh=False):141    """Retrieves a list of the top hottt artists.142    Do not request this more than once an hour."""143    global TOP_HOTTT_ARTISTS_CACHE144    if TOP_HOTTT_ARTISTS_CACHE==[] or refresh or not CACHE:145        response = util.call('get_top_hottt_artists', {'rows': rows}).findall('artists/artist')146        TOP_HOTTT_ARTISTS_CACHE = [Artist(a.findtext('id'), a.findtext('name')) for a in response]147    return TOP_HOTTT_ARTISTS_CACHE148class SimilarDocumentSet(document.DocumentSet):149    def __init__(self, identifier):150        super(SimilarDocumentSet, self).__init__(identifier, 'get_similar', 'similar/artist')151    def __len__(self):152        if self._len is None:153            self._len = 100154        return self._len155    def __getitem__(self, k):156        if k.stop > 100:157            raise util.EchoNestAPIError(5, 'Invalid parameter: "rows" must be less than or equal to 100')158        chunk_and_index = lambda i: (i / self._cache.chunk_size, i % self._cache.chunk_size)159        start, start_chunk, start_index, stop = self.chunk_magic(k)160        if (stop + 1) > self._cache.chunk_size:161            self.__init__(self.identifier)162            self._cache.chunk_size = stop + 1163            chunk_and_index = lambda i: (i / self._cache.chunk_size, i % self._cache.chunk_size)164            start, start_chunk, start_index, stop = self.chunk_magic(k)165        stop_chunk, stop_index = chunk_and_index(stop)166        items = []167        for chunk in xrange(start_chunk, stop_chunk + 1):168            elements = self._cache[chunk].findall(self.element_path)169            if chunk == start_chunk and chunk == stop_chunk:170                elements = elements[start_index:stop_index + 1]171            elif chunk == start_chunk:172                elements = elements[start_index:]173            elif chunk == stop_chunk:174                elements = elements[:stop_index + 1]175            items.extend([self._parse_element(e) for e in elements])176        return items177    def chunk_magic(self, k):178        chunk_and_index = lambda i: (i / self._cache.chunk_size, i % self._cache.chunk_size)179        if not isinstance(k, slice):180            raise TypeError181        start = k.start or 0182        start_chunk, start_index = chunk_and_index(start)183        stop = min(k.stop or len(self), len(self)) - 1 # use inclusive to simplify logic184        return start, start_chunk, start_index, stop185    def _parse_element(self, element):...

support.py

Source:support.py

1from numpy import ndarray, array2def fix_slicing(index, logical_length, allow_column=True):3    """4    Checks, and caps, the slices being used.5    :param index: The initial index, which may be int or slice.6    :param logical_length: The current logical length of the data. It is used to cap the indices.7      If None, indices will not be capped.8    :param allow_column: Tells whether allowing 1 or 2 dimensions indexing.9    :return: The fixed slicing, if no exception occurs.10    """11    column_index = None12    if isinstance(index, tuple):13        if allow_column:14            if len(index) == 2:15                index, column_index = index16            else:17                raise IndexError("At most two indices/slices (bi-dimensional indexing) are supported")18        else:19            raise IndexError("Only one index/slice (one-dimensional indexing) is supported")20    if isinstance(index, slice):21        start = index.start22        stop = index.stop23        step = index.step24        if start is None:25            start = 026        if stop is None:27            stop = logical_length28        if step and step != 1:29            raise IndexError("Slices with step != 1 are not supported")30        if start < 0 or (stop is not None and stop < 0):31            raise IndexError("Negative indices in slices are not supported")32        if stop is not None and stop < start:33            raise IndexError("Slices must have start <= stop indices")34        elif logical_length is None:35            return start, stop, column_index36        else:37            # Here, start will be <= stop. We will limit both by the logical_length, silently.38            return min(start, logical_length), min(stop, logical_length), column_index39    elif isinstance(index, int):40        if index < 0:41            raise IndexError("Negative indices are not supported")42        if logical_length is None:43            return index, None, column_index44        else:45            return min(index, logical_length), None, column_index46    else:47        raise TypeError("Only slices (non-negative, growing, and with step 1) or non-negative integer indices are "48                        "supported")49def fix_input(index, expected_width, expected_length, expected_type, value):50    """51    Checks and fixes the value according to the given index type.52    :param index: The initial index, which may be int or slice.53    :param expected_width: The expected width of the value.54    :param expected_length: The expected length of the data. It will be ignored if the index is a number.55    :param expected_type: The expected type for array input.56    :param value: The given value, which may be scalar or array.57    :return: The fixed value, if no exception occurs.58    """59    # If the input is an iterable, convert it to an 1-dimensional array.60    if isinstance(value, (tuple, list)):61        value = array(value)62    if isinstance(index, slice):63        if not isinstance(value, ndarray) and value.dtype != expected_type:64            raise TypeError("When setting a slice, the value must be a numpy array of (stop - start)x(width) "65                            "elements (if the width is 1, an uni-dimensional array of (stop-start) elements is "66                            "also allowed)")67        if expected_width == 1 and len(value.shape) == 1:68            value = value[:]69            value.shape = (value.size, 1)70        if value.shape != (expected_length, expected_width):71            raise TypeError("When setting a slice, the value must be a numpy array of (stop - start)x(width) "72                            "elements (if the width is 1, an uni-dimensional array of (stop-start) elements is "73                            "also allowed)")74    elif isinstance(index, int):75        if expected_width > 1 and (not isinstance(value, ndarray) or value.shape != (expected_width,)):76            raise TypeError("When setting an index, the value must be a 1-dimensional numpy array of the appropriate "77                            "size (=width), if the expected width is > 1")78        if expected_width == 1 and not isinstance(value, ndarray):79            value = array((value,))80    else:81        raise TypeError("Only slices (non-negative, growing, and with step 1) or non-negative integer indices are "82                        "supported")83    return value84def chunked_slicing(slice_start, slice_stop, chunk_size):85    """86    Iterator that yields, every time, a data structure like this:87      - Current chunk index88      - Start index in chunk89      - Stop index in chunk90      - Start index in source/destination91      - Stop index in source/destination92    It is guaranteed: 0 <= slice_start <= slice_stop <= logical length <= chunk_size * chunk_count.93    The algorithm goes like this:94      - Before: we know the starter bin, and the end bin.95    :param slice_start: The overall start.96    :param slice_stop: The overall stop.97    :param chunk_size: The chunk size.98    :return: A generator.99    """100    start_chunk = slice_start // chunk_size101    stop_chunk = slice_stop // chunk_size102    if start_chunk == stop_chunk:103        # This is the easiest case.104        # The data indices will be 0 and stop_chunk - start_chunk.105        # The chunk index will be start_chunk.106        # the start index in chunk, and end index in chunk, will both involve modulo.107        data_indices = (0, slice_stop - slice_start)108        chunk_indices = (slice_start % chunk_size, slice_stop % chunk_size)109        yield data_indices, start_chunk, chunk_indices110    else:111        # In this case, start chunk will always be lower than end chunk.112        chunk_start_index = slice_start % chunk_size113        chunk_stop_index = slice_stop % chunk_size114        first_iteration = True115        data_index = 0116        current_chunk = start_chunk117        # We know that, in the first iteration:118        # - chunk_start_index >= 0119        # - start_chunk < stop_chunk, strictly120        # And in further iterations:121        # - chunk_start_index == 0122        # - start_chunk <= stop_chunk123        while True:124            # The chunk upper bound will be:125            # - The chunk stop index, if in last chunk.126            # - The chunk size, otherwise.127            if current_chunk == stop_chunk:128                # Another check here: if the chunk stop index is 0, just break.129                if chunk_stop_index == 0:130                    return131                current_chunk_ubound = chunk_stop_index132            else:133                current_chunk_ubound = chunk_size134            # The chunk lower bound will be:135            # - The chunk start index, if in first chunk.136            # - 0, otherwise.137            if first_iteration:138                current_chunk_lbound = chunk_start_index139            else:140                current_chunk_lbound = 0141            # Now we know the chunk start and chunk end bounds.142            # We also know the current chunk index.143            # We also know the current data index.144            # Also we can compute the current data length145            length = current_chunk_ubound - current_chunk_lbound146            # We can yield all the data now.147            data_indices = (data_index, data_index + length)148            chunk_indices = (current_chunk_lbound, current_chunk_ubound)149            yield data_indices, current_chunk, chunk_indices150            # If this is the last chunk, we must exit.151            if current_chunk == stop_chunk:152                return153            # If not, then we move the data index and the current chunk.154            current_chunk += 1155            data_index += length156            # Finish the first iteration....

Playwright tutorial

LambdaTest’s Playwright tutorial will give you a broader idea about the Playwright automation framework, its unique features, and use cases with examples to exceed your understanding of Playwright testing. This tutorial will give A to Z guidance, from installing the Playwright framework to some best practices and advanced concepts.

Chapters:

What is Playwright : Playwright is comparatively new but has gained good popularity. Get to know some history of the Playwright with some interesting facts connected with it.
How To Install Playwright : Learn in detail about what basic configuration and dependencies are required for installing Playwright and run a test. Get a step-by-step direction for installing the Playwright automation framework.
Playwright Futuristic Features: Launched in 2020, Playwright gained huge popularity quickly because of some obliging features such as Playwright Test Generator and Inspector, Playwright Reporter, Playwright auto-waiting mechanism and etc. Read up on those features to master Playwright testing.
What is Component Testing: Component testing in Playwright is a unique feature that allows a tester to test a single component of a web application without integrating them with other elements. Learn how to perform Component testing on the Playwright automation framework.
Inputs And Buttons In Playwright: Every website has Input boxes and buttons; learn about testing inputs and buttons with different scenarios and examples.
Functions and Selectors in Playwright: Learn how to launch the Chromium browser with Playwright. Also, gain a better understanding of some important functions like “BrowserContext,” which allows you to run multiple browser sessions, and “newPage” which interacts with a page.
Handling Alerts and Dropdowns in Playwright : Playwright interact with different types of alerts and pop-ups, such as simple, confirmation, and prompt, and different types of dropdowns, such as single selector and multi-selector get your hands-on with handling alerts and dropdown in Playright testing.
Playwright vs Puppeteer: Get to know about the difference between two testing frameworks and how they are different than one another, which browsers they support, and what features they provide.
Run Playwright Tests on LambdaTest: Playwright testing with LambdaTest leverages test performance to the utmost. You can run multiple Playwright tests in Parallel with the LammbdaTest test cloud. Get a step-by-step guide to run your Playwright test on the LambdaTest platform.
Playwright Python Tutorial: Playwright automation framework support all major languages such as Python, JavaScript, TypeScript, .NET and etc. However, there are various advantages to Python end-to-end testing with Playwright because of its versatile utility. Get the hang of Playwright python testing with this chapter.
Playwright End To End Testing Tutorial: Get your hands on with Playwright end-to-end testing and learn to use some exciting features such as TraceViewer, Debugging, Networking, Component testing, Visual testing, and many more.
Playwright Video Tutorial: Watch the video tutorials on Playwright testing from experts and get a consecutive in-depth explanation of Playwright automation testing.