我们从Python开源项目中,提取了以下6个代码示例,用于说明如何使用humanize.intcomma()。
def mount_app_blueprints(app): app.template_filter()(humanize.intcomma) app.template_filter()(country) app.template_filter()(date) app.template_filter()(cleanurl) app.template_filter()(normalizeaddress) app.register_blueprint(base) app.register_blueprint(auth) app.register_blueprint(datasets) compile_assets(app)
def hashfile(request, hashfile_id, error_msg=''): context = {} context["Section"] = "Hashfile" hashfile = get_object_or_404(Hashfile, id=hashfile_id) context['hashfile'] = hashfile context['lines'] = humanize.intcomma(hashfile.line_count) context['recovered'] = "%s (%.2f%%)" % (humanize.intcomma(hashfile.cracked_count), hashfile.cracked_count/hashfile.line_count*100) context['hash_type'] = Hashcat.get_hash_types()[hashfile.hash_type]["name"] template = loader.get_template('Hashcat/hashfile.html') return HttpResponse(template.render(context, request))
def get_wordlists(self, detailed=True): res = [] if not detailed: path = os.path.join(os.path.dirname(__file__), "..", "Files", "Wordlistfiles") res = [{"name": f} for f in listdir(path) if isfile(join(path, f)) and f.endswith(".wordlist")] else: path = os.path.join(os.path.dirname(__file__), "..", "Files", "Wordlistfiles", "*") # use md5sum instead of python code for performance issues on a big file result = subprocess.run('md5sum %s' % path, shell=True, stdout=subprocess.PIPE).stdout.decode() for line in result.split("\n"): items = line.split() if len(items) == 2: info = { "name": items[1].split("/")[-1], "md5": items[0], "path": items[1], } try: info["lines"] = humanize.intcomma(sum(1 for _ in open(items[1], errors="backslashreplace"))) except UnicodeDecodeError: print("Unicode decode error in file %s" % items[1]) info["lines"] = "error" res.append(info) return sorted(res, key=itemgetter('name'))
def cli_total_repos(): print(humanize.intcomma(Crawler().num_repos()))
def cli_total_features(): print(humanize.intcomma(Crawler().num_features()))
def build_streamer_json(stream, user_info): """Compile useful streamer information from a stream object. :param user: The username of the streamer :param stream: The complete stream JSON object :param participant_id: The user's Extra Life participant ID :return: A subset object of relevant streamer info """ participant_id = user_info.get('EXTRALIFE') user = user_info.get('TWITCH') donate_url = 'https://www.extra-life.org/index.cfm?fuseaction=donorDrive.' \ 'participant&participantID={}'.format(participant_id) s = { 'dispname': user_info['NAME'], 'username': user_info['TWITCH'], 'playing': 'Offline', 'viewers': 0, 'url': 'https://www.twitch.tv/{}'.format(user), 'preview': 'http://placehold.it/640x360', 'participant_id': participant_id, 'donate': donate_url if participant_id else None, 'fps': 0, 'views': 0, } if not stream['stream']: return s mapping = [ ('pubg', 'PUBG', "PLAYERUNKNOWN'S BATTLEGROUNDS", ), ('overwatch', 'BLIZZARD', 'Overwatch', ), ('rocketleague', 'STEAM', 'Rocket League', ), ('destiny2', 'DESTINY2', 'Destiny 2', ) ] for key, lookup, twitch_name in mapping: module = importlib.import_module('games.{}'.format(key)) if user_info.get(lookup): if stream['stream'].get('game') != twitch_name: continue try: s[key] = module.stats(user_info[lookup]) except KeyError as exc: s[key] = {} s['username'] = stream['stream']['channel']['display_name'] s['playing'] = stream['stream']['game'] s['viewers'] = humanize.intcomma(int(stream['stream']['viewers'])) s['preview'] = stream['stream']['preview']['large'] s['fps'] = stream['stream']['average_fps'] s['views'] = humanize.intword(int(stream['stream']['channel']['views'])) return s