import os, json, random, io, logging from pulp import LpProblem, LpVariable, LpMinimize, LpMaximize, LpAffineExpression, LpConstraint, LpStatus, lpSum from helpers import aws_helper, tar_helper, csv_helper, service_helper, solver_helper from lib.errors.item_generation_error import ItemGenerationError from models.solver_run import SolverRun from models.solution import Solution from models.form import Form from models.item import Item from services.base import Base class LoftService(Base): def process(self): try: self.solver_run = self.create_solver_run_from_attributes() self.solver_run.generate_bundles() self.solution = self.generate_solution() self.result = self.stream_to_s3_bucket() except ItemGenerationError as error: self.result = self.stream_to_s3_bucket(error) except TypeError as error: logging.error(error) self.result = self.stream_to_s3_bucket( ItemGenerationError( "Provided params causing error in calculation results")) def create_solver_run_from_attributes(self) -> SolverRun: logging.info('Retrieving attributes from message...') # get s3 object self.key = aws_helper.get_key_from_message(self.source) s3_object = aws_helper.get_object( self.key, aws_helper.get_bucket_from_message(self.source)) # convert to tar self.tar = tar_helper.raw_to_tar(s3_object) # get attributes file and convert to dict attributes = json.loads( tar_helper.extract_file_from_tar( self.tar, 'solver_run_attributes.json').read()) # create solver run solver_run = SolverRun.parse_obj(attributes) # get items file and convert to dict items_csv = tar_helper.extract_file_from_tar(self.tar, 'items.csv') items_csv_reader = csv_helper.file_stream_reader(items_csv) # add items to solver run for item in service_helper.items_csv_to_dict(items_csv_reader, solver_run): solver_run.items.append(Item.parse_obj(item)) logging.info('Processed Attributes...') return solver_run def generate_solution(self) -> Solution: logging.info('Generating Solution...') # unsolved solution solution = Solution(response_id=random.randint(100, 5000), forms=[]) # counter for number of forms f = 0 # iterate for number of forms that require creation # currently creates distinct forms with no item overlap while f < self.solver_run.total_forms: # setup vars items = LpVariable.dicts( "Item", [item.id for item in self.solver_run.items], cat='Binary') bundles = LpVariable.dicts( "Bundle", [bundle.id for bundle in self.solver_run.bundles], cat='Binary') # create problem problem = LpProblem("ata-form-generate", LpMinimize) problem_objective_functions = [] # dummy objective function, because it just makes things easier™ problem += lpSum( [items[item.id] for item in self.solver_run.items]) # constraints # problem += lpSum([items[item.id] # for item in self.solver_run.items]) == self.solver_run.total_form_items, 'Total form items' problem += lpSum( [ bundle.count * bundles[bundle.id] for bundle in self.solver_run.bundles ] + [ 1 * items[item.id] for item in self.solver_run.unbundled_items() ] ) == self.solver_run.total_form_items, 'Total bundle form items for form' # dynamic constraints problem = solver_helper.build_constraints(self.solver_run, problem, items, bundles) # multi-objective constraints logging.info('Creating TIF and TCC constraints') for target in self.solver_run.objective_function.tif_targets: tif = lpSum([ bundle.tif(self.solver_run.irt_model, target.theta) * bundles[bundle.id] for bundle in self.solver_run.bundles ] + [ item.iif(self.solver_run, target.theta) * items[item.id] for item in self.solver_run.items ]) problem_objective_functions.append(tif) e = LpAffineExpression( [(bundles[bundle.id], bundle.tif(self.solver_run.irt_model, target.theta)) for bundle in self.solver_run.bundles] + [(items[item.id], item.iif(self.solver_run, target.theta)) for item in self.solver_run.items]) constraint = LpConstraint( e=e, sense=0, name=f'tif theta ({target.theta}) @{target.value}', rhs=target.value) elastized_constraint = constraint.makeElasticSubProblem( penalty=1, proportionFreeBound=0.25) if int(target.value) == 20: print(elastized_constraint) problem.extend(elastized_constraint) for target in self.solver_run.objective_function.tcc_targets: tcc = lpSum([ bundle.trf(self.solver_run.irt_model, target.theta) * bundles[bundle.id] for bundle in self.solver_run.bundles ] + [ item.irf(self.solver_run, target.theta) * items[item.id] for item in self.solver_run.items ]) problem_objective_functions.append(tcc) e = LpAffineExpression( [(bundles[bundle.id], bundle.trf(self.solver_run.irt_model, target.theta)) for bundle in self.solver_run.bundles] + [(items[item.id], item.irf(self.solver_run, target.theta)) for item in self.solver_run.items]) constraint = LpConstraint( e=e, sense=0, name=f'tcc theta ({target.theta}) @{target.value}', rhs=target.value) elastized_constraint = constraint.makeElasticSubProblem( penalty=1, proportionFreeBound=0.25) problem.extend(elastized_constraint) # solve problem logging.info('Solving...') # print(problem) problem.solve() # problem.sequentialSolve(problem_objective_functions) logging.info('Solved...generating form and adding to solution') # add return items and create as a form form_items = service_helper.solution_items(problem.variables(), self.solver_run) # add form to solution solution.forms.append( Form.create(form_items, self.solver_run, LpStatus[problem.status])) logging.info('Form generated and added to solution...') # successfull form, increment f += 1 logging.info('Solution Generated.') # print(problem) return solution def stream_to_s3_bucket(self, error=None): self.file_name = f'{service_helper.key_to_uuid(self.key)}.csv' solution_file = None # setup writer buffer and write processed forms to file buffer = io.StringIO() if error: logging.info('Streaming %s error response to s3 bucket - %s', self.file_name, os.environ['S3_PROCESSED_BUCKET']) solution_file = service_helper.error_to_file(buffer, error) else: logging.info('Streaming %s to s3 bucket - %s', self.file_name, os.environ['S3_PROCESSED_BUCKET']) solution_file = service_helper.solution_to_file( buffer, self.solver_run.total_form_items, self.solution.forms) # upload generated file to s3 and return result return aws_helper.file_stream_upload(solution_file, self.file_name, os.environ['S3_PROCESSED_BUCKET'])