def __init__(self, master=None): super().__init__(master) self.master = master self.master.title(CONST_APP_TITLE) self.master.geometry('600x400+400+100') self.master.resizable(0, 0) self.config(width=500, height=500) self.place(x=50, y=0) self.application_widgets() self.processor = Processor()
def __init__(self, config): self.executor = ReadFactory(config).get_executor() self.processor = Processor(config) self.writer = WriterFactory().instance_writer(config, self.processor.aggregation_output_struct, self.processor.enumerate_output_aggregation_field) self._isAnalysis = False if ("analysis" in config.content.keys()): self._isAnalysis = True self.analysis = AnalysisFactory(config, self.processor.aggregation_output_struct, self.processor.enumerate_output_aggregation_field)
def show_solution(self): top = tk.Toplevel(self) top.geometry('500x400+400+100') top.title(RESULT_TITLE) scroll = tk.Scrollbar(top) c = tk.Canvas(top, yscrollcommand=scroll.set) scroll.config(command=c.yview) scroll.pack(side='right', fill='y') top_frame = tk.Frame(c) top_frame.config(width=500) c.pack(side='left', fill='both', expand=True) c.create_window(0, 0, window=top_frame, anchor='nw') top.update() c.config(scrollregion=c.bbox('all')) response = self.run_data() self.processor = Processor() tk.Label(top_frame, text=CONST_TOPIC_NAME).grid(padx=(70, 80), pady=(5, 30), row=0, column=0) tk.Label(top_frame, text=CONST_RESULT_PAGES).grid(padx=(70, 80), pady=(5, 30), row=0, column=1) for i in range(len(response[TOPICS_RESPONSE])): if response[INCLUDE_RESPONSE][i] == 'true': tk.Label(top_frame, text=response[TOPICS_RESPONSE][i]).grid(padx=(70, 80), pady=(5, 30), row=i + 1, column=0) tk.Label(top_frame, text=response[PAGES_RESPONSE][i]).grid(padx=(70, 80), pady=(5, 30), row=i + 1, column=1) tk.Label(top_frame, text=CONST_READERS).grid( padx=(70, 80), pady=(5, 30), row=len(response[TOPICS_RESPONSE]) + 1, column=0) tk.Label(top_frame, text=response[READERS_RESPONSE]).grid( padx=(70, 80), pady=(5, 30), row=len(response[TOPICS_RESPONSE]) + 1, column=1)
def main(): """ Usage: python3 app.py input.txt' or 'python3 < input.txt' """ log.info('Begin processing...') t = process_time() processor = Processor() # Accept input from two types of sources: # a filename passed in command line arguments or STDIN. with open(sys.argv[1], 'r') if len(sys.argv) > 1 else sys.stdin as f: for line in f: processor.parse_event(line) log.info('Finished processing in {0:.3f} seconds'.format(process_time() - t)) summary = processor.generate_summary() processor.write_output(summary)
import sys import torch from torch.backends import cudnn from processor.processor import Processor torch.backends.cudnn.deterministic = False cudnn.benchmark = True # https://discuss.pytorch.org/t/what-does-torch-backends-cudnn-benchmark-do/5936 torch.cuda.empty_cache() # release cache if __name__ == '__main__': proc = Processor(sys.argv[1:]) proc.start()
def run_processor(): self.processor = Processor(get_projectdb(), self.in_queue, self.status_queue, self.newtask_queue, self.result_queue) self.processor.CHECK_PROJECTS_INTERVAL = 0.1 self.processor.run()
def setUp(self): self.processor = Processor()
import os from processor.processor import Processor if __name__ == "__main__": current_path = os.path.dirname(os.path.abspath(__file__)) data_path = os.path.join(current_path, "data") resource_path = os.path.join(data_path, "resources") input_path = os.path.join(data_path, "inputs", "1984.txt") output_path = os.path.join(data_path, "outputs") processor = Processor(resource_path=resource_path, config={}) processor.process(input_path=input_path, output_path=output_path)
parser.add_argument('--num_of_vertices', type=int, default=358, help='The number of vertices') parser.add_argument('--gen_config_args', type=dict, default=dict(), help='The config of data generate') return parser if __name__ == '__main__': parser = get_parser() # load arg form config file p = parser.parse_args() if p.config is not None: with open(p.config, 'r') as f: default_arg = yaml.load(f) key = vars(p).keys() for k in default_arg.keys(): if k not in key: print('WRONG ARG: {}'.format(k)) assert (k in key) parser.set_defaults(**default_arg) arg = parser.parse_args() init_seed(0) processor = Processor(arg) processor.start()
def test__number__(self): config = Config(CONFIG_PATH_NUM) p = Processor(config) self.assertIsInstance( p.transformation, types.LambdaType, "Processor#transformation should be a lambda object")