def create_asset(self, **kwargs): asset = Asset(**kwargs) asset.project = self if asset.template.meta.get('tasks', None): for task_tmpl_name in asset.template.meta['tasks']: tmpl = TaskTemplate.find_by_name(task_tmpl_name) if tmpl: task = asset.TaskFromTemplate(tmpl) asset.tasks.append(task) if self.module_dir: project_module_path = os.path.join(self.module_dir, 'project.py') if os.path.exists(project_module_path): module = imp.load_source('action_module', project_module_path) if hasattr(module, 'create_asset_callback'): func = getattr(module, 'create_asset_callback') func(asset) if asset.template: attr = 'create_asset_callback_' + asset.template.name if hasattr(module, attr): func = getattr(module, attr) func(asset) del module else: print 'WARNING: Could not find module [%s]' % project_module_path return asset
def __init__(self, game, id, twoStage=False): self.game = game if twoStage: self.low = Asset.load('ship%i_low' % id) self.high = Asset.load('ship%i_high' % id) else: self.low = self.high = Asset.load('ship%i') self.fixedPos = None self.pos = (0, 0) self.rot = 0 self.enginesOn = False
def customer_with_assets(customer_id): if request.method == 'GET': data={"error":"Something went wrong. Please try again later."} responseStatusCode = 500 try: assets = collection_assets.find({"customer_guid":customer_id}) response = [] for asset_dict in assets: asset_obj = Asset.fromDict(asset_dict) response.append(asset_obj) data = {'assets':response} responseStatusCode = 200 except Exception as e: data = data={"error":"Something went wrong. Please try again later. "+str(e)} responseStatusCode = 500 (data,mime) = (jsonParser.DateTimeJSONEncoder().encode(data),'application/json') return Response(data, status=responseStatusCode, mimetype=mime) if request.method == 'POST': data={"error":"Something went wrong. Please try again later."} responseStatusCode = 500 try: asset_obj = Asset.fromJson(request.data) collection_assets.insert(asset_obj.toDict()) data = {'asset':asset_obj} (data,mime) = (jsonParser.DateTimeJSONEncoder().encode(data),'application/json') responseStatusCode = 200 job = startTranscodingjob("2014-03-06 20.45.17.mp4",customer_id + "/" + asset_obj.guid) if job == 0: app.logger.error('Changing status for asset from init to transcoded with guid ' + asset_obj.guid) collection_assets.update({'guid': asset_obj.guid},{"$set": {"status": "transcoded"}}) app.logger.error('Transcoding job finished successfully') Notifications() else: app.logger.error('Sth went wrong with the transcoding') except TypeError as e: data = {"error":"Customer could not be created because the data in the body of the request was bad." + str(e)} responseStatusCode = 400 except Exception as e: data = {"error":"Something went wrong. Please try again later."+ str(e)} app.logger.error('Error in POST /customers: '+str(e)) responseStatusCode = 500 (data,mime) = (jsonParser.DateTimeJSONEncoder().encode(data),'application/json') return Response(data, status=responseStatusCode, mimetype=mime)
def __init__(self, game, type, pos, rot, accel, friendly): self.game = game self.pos = (pos[0]-game.worldOff[0])/2, (pos[1]-game.worldOff[1])/2 self.rot = rot x, y = rotatePoint(self.rot, 10) self.accel = (-accel[0]-x, -accel[1]-y) self.friendly = friendly self.im = Asset.load('bullet%i' % type)
def fromFilepath(self, path): # split into absolute save path and file base name file_save_path, file_basename = os.path.split(path) self.fromFilename(file_basename) # get asset path from path # remove segments from path that belong to the file save path asset_path_list = file_save_path.split(os.path.sep)[0:-len(self.getSaveDir().split('/'))] asset_path = os.path.join('/'.join(asset_path_list)) # split into asset root path and asset name asset_root_path, asset_name = os.path.split(asset_path) new_asset = Asset() new_asset.setRootPath(asset_root_path) new_asset.setName(asset_name) self.setAsset(new_asset) return self
def __init__(self): Asset.__init__(self) dict.__init__({})
def __init__(self, folder): Asset.__init__(self) self.__root = self.__browsefolder(folder)
def unload(self): Asset.unload(self) for item in self.__root.values(): item.unload()
def __init__(self, game): self.game = game self.bg = Asset.load('layer2_outline', mask='layer2_mask') # % self.levelNumber) stars.maskOff(self.bg) self.i = 0
def create_asset(): _assets = Asset.get_list() _idcs = Asset.get_idcs_list() return render_template('asset_create.html', idcs=_idcs)
def update_list(self): Asset.update_list(self, uri_keys=('flt_phase', 'list'), uri_args=self._ems_id) self._rename_datacol('description', 'name')
# configure logger Log.init_instance(config().logfile(), config().loglevel(), config().logformat()) assets = {} correlations = {} if __name__ == "__main__": for path in config().input_path(): Log.info("Searching in %s", path) for filename in os.listdir(path): if fnmatch.fnmatch(filename, "*.csv"): Log.info("File %s", filename) asset = Asset() asset.read_csv(os.path.join(path, filename)) if len(asset.data["Volume"][ asset.data["Volume"] > 10000]) < args.min_data_points: Log.info( "Ignoring data set since it has too few entries ({} instead of {})" .format( len(asset.data["Volume"][ asset.data["Volume"] > 10000]), args.min_data_points)) continue if asset.exchange is None or asset.symbol is None: Log.info( "Ignoring data set since exchange or symbol is missing" ) continue
def __init__(self, name, keypair): self.name = name self.keypair = keypair self.amount = Asset(0)
] df = pd.read_csv(filename, usecols=columns, delimiter='\t', encoding='utf-16') print(df.to_string()) pf = Portfolio() for index, row in df.iterrows(): ticker = row['Verdipapir'] amount = float(row['Antall'].replace(',', '.').replace(' ', '')) kurs = float(row['Kurs'].replace(',', '.').replace(' ', '')) vekslingskurs = float(row['Vekslingskurs'].replace(',', '.').replace(' ', '')) transaksjonstype = row['Transaksjonstype'] belop = float(row['Beløb'].replace(',', '.').replace(' ', '')) if transaksjonstype == 'KJØPT' or transaksjonstype == 'SALG': a = Asset(ticker) pf.add_asset(a) pf_asset = pf.get_asset(ticker) pf_asset.buy(amount, kurs * vekslingskurs) if belop < 0 else pf_asset.sell( amount, kurs * vekslingskurs) if transaksjonstype == 'INNSKUDD' or transaksjonstype == 'UTTAK INTERNET': if transaksjonstype == 'INNSKUDD': print(f"DEPOSIT: {belop}") pf.deposit(belop) for a in pf.get_assets(): print(a) print(pf)
def __init__(self, conn): Asset.__init__(self, conn, "EMS") self.update_list()
def update_list(self): Asset.update_list(self, uri_keys=('ems_sys', 'list'))
else: raise ValueError data = {} for asset_id in allocate_asset_ids: data[asset_id] = self.assets[asset_id].nav(reindex=reindex) df_nav = pd.DataFrame(data).fillna(method='pad') df_inc = df_nav.pct_change().iloc[1:] return df_nav, df_inc, bound if __name__ == '__main__': asset = Asset('120000001') print(asset.nav().tail()) asset = WaveletAsset('120000013', 2) print(asset.nav('1900-01-01', datetime.now()).tail()) trade_date = ATradeDate.week_trade_date(begin_date='2012-01-01') print(trade_date[-5:]) asset_globalids = [ '120000001', '120000002', '120000013', '120000014', '120000015' ] assets = {} for asset_id in asset_globalids: assets[asset_id] = Asset(asset_id)
def command_asset(): _id = request.args.get('id', '') _asset = Asset.get_by_id(_id) return render_template('asset_command.html', asset=_asset)
def delete_assets(): id = request.args.get('id') Asset.delete(id) return redirect('/assets/')
from asset import Asset grid = Asset.load('layer0') stars = Asset.load('layer1') class Level(object): levels = {} def __init__(self, game): self.game = game self.bg = Asset.load('layer2_outline', mask='layer2_mask')# % self.levelNumber) stars.maskOff(self.bg) self.i = 0 @staticmethod def spawn(game, number, *args, **kwargs): return Level.levels[number](game, *args, **kwargs) @staticmethod def register(level): Level.levels[level.levelNumber] = level def draw(self, surface): grid.draw(surface, (0, 0), center=False) stars.draw(surface, self.game.worldOff, center=True) self.bg.draw(surface, self.game.worldOff, center=True) self.i += 1 @Level.register class LevelZero(Level): levelNumber = 0
def load_assets(self): for asset in Game.load_json_objects(self.PATH_ASSETS): self._assets.add(Asset.from_json(asset))
"svm=SVM regressor, " "knn=KNN regressor, " "nn=neural network regressor") parser.add_argument("filename", metavar="FILE", nargs='*', help="Stock data input files to process") args = parser.parse_args() # configuration files Configuration.init_instance(args.config, args) # configure logger Log.init_instance(config().logfile(), config().loglevel(), config().logformat()) if __name__ == "__main__": for filename in config().input_filenames(): Log.info("Running models for %s", filename) asset = Asset() asset.read_csv(filename) for model in args.models.split(","): if model == "lstm": lstm_model.fit_LSTM_models(asset) elif model == "clf": models.fit_classifiers(asset, classifiers=args.clf.split(",")) elif model == "reg": models.fit_regressors(asset, regressors=args.reg.split(","))
def __init__(self, game): self.game = game self.bg = Asset.load('layer2_outline', mask='layer2_mask')# % self.levelNumber) stars.maskOff(self.bg) self.i = 0
def __init__(self, conn, ems_id=7): Asset.__init__(self, conn, "FlightPhase") self._ems_id = ems_id self.update_list()
import os import pytest from airtable_client import AirtableClient from asset import Asset registerable_asset = Asset( title="PlayStation 5 (CFI-1000A01)", asin="B08GGGBKRQ", url="https://www.amazon.co.jp/ソニー・インタラクティブエンタテインメント-PlayStation-5-CFI-1000A01/dp/B08GGGBKRQ/", images=[{"url": "https://images-na.ssl-images-amazon.com/images/I/61YYOeZy9aL.AC_SL1500.jpg"}], manufacture="ソニー・インタラクティブエンタテインメント", contributor=None, product_group="Video game", publication_date=None, features="圧巻のスピード:統合I/O(Integrated I/O)により、カスタムされたCPU・GPU・SSDがその力を発揮。", default_position="sforzando 川崎", current_position="渡邉宅", note="リモートゲーム大会用に購入。", registrant_name="yusuke-sforzando") @pytest.fixture def airtable_client(): airtable_client = AirtableClient() return airtable_client def test_api_key(): assert os.getenv("airtable_base_id")
from asset import Asset grid = Asset.load('layer0') stars = Asset.load('layer1') class Level(object): levels = {} def __init__(self, game): self.game = game self.bg = Asset.load('layer2_outline', mask='layer2_mask') # % self.levelNumber) stars.maskOff(self.bg) self.i = 0 @staticmethod def spawn(game, number, *args, **kwargs): return Level.levels[number](game, *args, **kwargs) @staticmethod def register(level): Level.levels[level.levelNumber] = level def draw(self, surface): grid.draw(surface, (0, 0), center=False) stars.draw(surface, self.game.worldOff, center=True) self.bg.draw(surface, self.game.worldOff, center=True) self.i += 1
def load(self): Asset.load(self) for item in self.values(): item.load()
filehandle= open(path, "r") filelines = filehandle.readlines() filehandle.close() #create asset objects assetList = [None]*(len(filelines)-1) #initialize a list of assets assetCounter = 0 #auxiliar idx for assetList for line in filelines: #get asset name, sector, return data = line.split('\t') if(not(data[0] == 'CODE') ): #jump the header counter = 0 #element counter pMembership = [None]*nPeriods #boolean values that indicates if this asset is included in the benchmark at period p colcounter = 0 #membership matrix column counter for element in data[5:len(data)-1]: #get membership line pMembership[colcounter] = element colcounter = colcounter + 1 assetList[assetCounter] = Asset(data[0], data[1], data[2], data[3], data[4], pMembership) assetCounter = assetCounter + 1 counter = 0 #get some rebalance dates in Yahoo finance #sampleDates = getSampleDates('https://finance.yahoo.com/quote/BRFS3.SA/history?period1=1448938800&period2=1517367600&interval=1d&filter=history&frequency=1d') #sampleDates = formatDate(sampleDates) #adjust dates according to COTAHISTFile sampleDates = adjustForCOTAHISTFile2(['2015','10','06'],['2018','02','06']) relative_path = "IbovespaData/returns/sampledates.txt" path = os.path.join(script_dir, relative_path) filehandle= open(path, "w") for date in sampleDates: filehandle.write(date + '\n') filehandle.close()
def assets(): _assets = Asset.get_list() _idcs = Asset.get_idcs_list() return render_template('assets.html', assets=_assets, idcs=_idcs)
def fc_rolling(ctx, optid): engine = database.connection('asset') Session = sessionmaker(bind=engine) session = Session() blacklist = [24, 40] asset_ids = ['1200000%02d' % i for i in range(1, 40) if i not in blacklist] assets = {} for asset_id in asset_ids: # assets[asset_id] = load_nav_series(asset_id) assets[asset_id] = Asset.load_nav_series(asset_id) layer_result = {} layer_result['date'] = [] layer_result['layer'] = [] layer_result['factor'] = [] lookback_days = 365 forecast_days = 90 df_result = pd.DataFrame(columns=['date', 'factor_id', 'layer']) start_date = '2017-01-01' trade_dates = ATradeDate.month_trade_date(begin_date=start_date) for date in trade_dates: print(date) sdate = (date - datetime.timedelta(lookback_days)).strftime('%Y-%m-%d') edate = date.strftime('%Y-%m-%d') fdate = (date + datetime.timedelta(forecast_days)).strftime('%Y-%m-%d') ''' init_num = 5 fc = FactorCluster(assets, init_num, sdate, edate, fdate) fc.handle() while fc.inner_score < 0.88: init_num += 1 fc = FactorCluster(assets, init_num, sdate, edate, fdate) fc.handle() ''' method = 'beta' scores = {} models = {} for i in range(7, 12): fc = FactorCluster(assets, i, sdate, edate, fdate, method=method, bf_ids=None) fc.handle() print(i, 'silhouette_samples_value:', fc.silhouette_samples_value) score = fc.silhouette_samples_value scores[score] = i models[score] = fc best_score = np.max(list(scores.keys())) best_model = models[best_score] fc = best_model print('best cluster num:', fc.n_clusters) factor_name = base_ra_index.load() for k, v in fc.asset_cluster.items(): v = np.array(v).astype('int') print(factor_name.loc[v]) for vv in v: df_result.loc[len(df_result)] = [date, vv, k] print() session.commit() session.close()
def asset_loader(): ## Retrieve asset and categories from server if fetch_assets_from_server: response = requests.get("https://homefuly.com:3443/api/assets?limit=2078", headers=header) assets_json = response.json().get('data') with open("input_data/assets.json", "wb") as write_file: json.dump(assets_json, write_file) response = requests.get("https://homefuly.com:3443/api/asset_categorys", headers=header) asset_categorys_json = response.json().get('data') with open("input_data/categorys.json", "wb") as write_file: json.dumps(asset_categorys_json, write_file) else: with open("input_data/categorys.json", "r") as read_file: asset_categorys_json = json.loads(read_file.read()) with open("input_data/assets.json", "r") as read_file: assets_json = json.loads(read_file.read()) ## Convert json data to python interpretable format # format = { type id : type name } asset_type = {} for category in asset_categorys_json['asset_categorys']: asset_type[category['_id']] = category['name'] for subcategory in category['subcategories']: asset_type[subcategory['_id']] = subcategory['name'] for vertical in subcategory['verticals']: asset_type[vertical['_id']] = vertical['name'] # PICKLE with open('dumps/asset_categories', 'wb') as fp: pickle.dump(asset_type, fp) # asset info list asset_data = {} asset_count = assets_json['count'] i = 0 for asset in assets_json['assets']: # categories if asset['category'] != '': asset_category = asset_type[asset['category']] else: continue # price if 'customer' in asset['price']: asset_price = asset['price']['customer'] else: continue # convert INR to Dollars if asset['currency'] == 'INR' and asset_price != None: asset_price *= 0.014 # dimension if 'dimension' in asset: d = asset['dimension'] asset_dimension = { 'depth' : d['depth'], 'width' : d['width'], 'height' : d['height']} # subcategories if asset['subcategory'] != '': if asset['subcategory'] in asset_type: asset_subcategory = asset_type[asset['subcategory']] else: continue else: continue # verticals if asset['vertical'] != '': asset_vertical = asset_type[asset['vertical']] else: asset_vertical = '' # style/theme asset_theme = asset['theme'] if asset_theme != None: asset_theme = asset['theme']['name'] # brand asset_brand = asset['designedBy'] #print asset_brand if asset_brand != '': if 'organizationInternalLink' in asset_brand: if asset_brand['organizationInternalLink'] != None: asset_brand = asset['designedBy']['organizationInternalLink']['name'] else: continue else: continue # room fit asset_room_type = asset['roomType'] if asset_room_type != None: asset_room_type = asset['roomType']['name'] # name asset_name = asset['name'] # id asset_id = asset['_id'] # Create asset if asset_category != 'Non Shoppable': if asset_price != None and asset_theme != None and asset_room_type != None: if asset_dimension['width'] <= 10 and asset_dimension['depth'] <= 10 and asset_dimension['height'] < 8: if asset_price > 0 and asset_brand in brands and asset_theme in themes: asset_name = re.sub('[^a-zA-Z0-9 \n\.]', '', asset_name) asset_data[i] = Asset(asset_id, asset_name, asset_category, asset_subcategory, asset_vertical, asset_price, asset_dimension, asset_theme, asset_brand, asset_room_type) #print [asset_category, asset_subcategory, asset_vertical, asset_name, asset_price, # asset_dimension, asset_theme, asset_brand, asset_room_type] i += 1 print i ## dump asset data to pickle file with open('dumps/asset_database', 'wb') as fp: pickle.dump(asset_data, fp)