data collection
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commit
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"name": "Python: Current File",
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"name": "Python: Current File",
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"type": "python",
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"type": "python",
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"request": "launch",
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"request": "launch",
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// "program": "C:\\Users\\ASUS\\OneDrive\\Project\\ScrAbm\\Dissertation\\IIabm\\model.py",
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"program": "C:\\Users\\ASUS\\OneDrive\\Project\\ScrAbm\\Dissertation\\IIabm\\main.py",
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"console": "integratedTerminal",
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"console": "integratedTerminal",
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"justMyCode": true
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"justMyCode": true
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}
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}
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import os
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import datetime
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from model import Model
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from typing import TYPE_CHECKING
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if TYPE_CHECKING:
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from controller_db import ControllerDB
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class Computation:
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def __init__(self, c_db: 'ControllerDB'):
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self.c_db = c_db
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self.pid = os.getpid()
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def run(self, str_code='0', s_id=None):
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sample_random = self.c_db.fetch_a_sample(s_id)
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if sample_random is None:
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return True
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# lock this row by update is_done_flag to 0
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self.c_db.lock_the_sample(sample_random)
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print(f"Pid {self.pid} ({str_code}) is running sample {sample_random.id} at {datetime.datetime.now()}")
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dct_exp = {column: getattr(sample_random.experiment, column)
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for column in sample_random.experiment.__table__.c.keys()}
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del dct_exp['id']
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dct_sample_para = {'sample': sample_random,
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'seed': sample_random.seed,
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**dct_exp}
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model = Model(dct_sample_para)
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results = model.run(display=False)
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return False
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if __name__ == '__main__':
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str_exp = 'test'
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from controller_db import ControllerDB
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controller_db = ControllerDB(str_exp)
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controller_db.reset_db()
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# print(controller_db.dct_parameter)
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exp = Computation(controller_db)
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is_all_done = exp.run('999', 87)
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# while 1:
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# # time.sleep(random.uniform(0, 10))
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# is_all_done = exp.run(str_exp)
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# if is_all_done:
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# break
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# read by orm
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is_local_db: True
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local:
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user_name: iiabm_yz
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password: iiabm_yz
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db_name: iiabmdb
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address: 'localhost'
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port: 3306
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remote:
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user_name: iiabm_yz
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password: iiabm_yz
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db_name: iiabmdb
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address: 'localhost'
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port: 3307
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db_name_prefix: test
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# read by ControllerDB
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# run settings
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meta_seed: 0
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fixed: # unchanged all the time
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int_n_country: 2
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max_int_n_supplier: 3 # make firms heterogeneous
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flt_bm_price_ratio: 20.0
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flt_beta_developing: 0.5
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test: # only for test scenarios
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int_n_product: 12
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int_n_firm_per_product_per_country: 2
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flt_demand_total: 1000.0
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n_sample: 5
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n_iter: 100
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not_test: # normal scenarios
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int_n_product: 50
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int_n_firm_per_product_per_country: 10
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flt_demand_total: 10000.0
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n_sample: 50
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n_iter: 10000
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default:
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is_eliminated: 0 # add when all positive profits and keep max n supplier; remove the worst when all negative wealth
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flt_beta_developed: 0.5 # benchmarks flt_beta_developed
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tariff_percentage: 0
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experiment:
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1:
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range_lambda_tier: 0, 1, 0.1 # describe the network. 0: chain 1: one iter
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2:
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is_eliminated: 1
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3:
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range_flt_beta_developed: 0.5, 0.9, 0.1
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range_tariff_percentage: 0, 1, 0.1
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# -*- coding: utf-8 -*-
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from orm import db_session, engine, Base, ins
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from orm import Experiment, Sample, Product, Firm
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from sqlalchemy.exc import OperationalError
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import yaml
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import random
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import numpy as np
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import platform
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class ControllerDB:
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dct_parameter = None
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is_test: bool = None
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db_name_prefix: str = None
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reset_flag: int
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lst_saved_s_id_3: list
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lst_saved_s_id_1_2: list
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# n_sample_1_2: int
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def __init__(self, prefix, reset_flag=0):
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with open('conf_experiment.yaml') as yaml_file:
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dct_conf_experiment = yaml.full_load(yaml_file)
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self.is_test = prefix == 'test'
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self.db_name_prefix = prefix
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dct_para_in_test = dct_conf_experiment['test'] if self.is_test else dct_conf_experiment['not_test']
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self.dct_parameter = {'meta_seed': dct_conf_experiment['meta_seed'],
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'experiment': dct_conf_experiment['experiment'],
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**dct_conf_experiment['fixed'], **dct_conf_experiment['default'], **dct_para_in_test}
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self.reset_flag = reset_flag # 0, not reset; 1, reset self; 2, reset all
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self.lst_saved_s_id_1_2, self.lst_saved_s_id_3 = [], []
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def init_tables(self):
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self.fill_experiment_table()
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self.fill_sample_table()
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@staticmethod
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def get_lst_of_range(str_range: str):
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s1, s2, s3 = tuple(str_range.split(','))
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return list(np.linspace(float(s1), float(s2), num=int((float(s2) - float(s1)) / float(s3)) + 1))
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def fill_experiment_table(self):
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# prepare the list of lambda tier
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lst_lambda = self.get_lst_of_range(self.dct_parameter['experiment'][1]['range_lambda_tier'])
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# prepare the list of alpha_2nd_country
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lst_beta_developed = self.get_lst_of_range(self.dct_parameter['experiment'][3]['range_flt_beta_developed'])
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# prepare the list of tariff_percentage
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lst_tariff = self.get_lst_of_range(self.dct_parameter['experiment'][3]['range_tariff_percentage'])
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# prepare the default values
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is_eliminated = int(self.dct_parameter['is_eliminated'])
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beta_developed = float(self.dct_parameter['flt_beta_developed'])
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tariff_percentage_1 = tariff_percentage_2 = float(self.dct_parameter['tariff_percentage'])
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for idx_scenario in self.dct_parameter['experiment'].keys():
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n_exp = 0
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# if idx_scenario == 1: # add S1 experiments
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# n_exp = self.add_experiment_1(idx_scenario, lst_lambda, is_eliminated,
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# beta_developed, tariff_percentage_1, tariff_percentage_2)
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# if idx_scenario == 2: # add S2 experiments
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# n_exp = self.add_experiment_1(idx_scenario, lst_lambda,
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# int(self.dct_parameter['experiment'][idx_scenario]['is_eliminated']),
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# beta_developed, tariff_percentage_1, tariff_percentage_2)
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if idx_scenario == 3:
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# int_eliminated = int(self.dct_parameter['experiment'][idx_scenario-1]['is_eliminated'])
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int_eliminated = is_eliminated # is_eliminated is 0 at default, so stop eliminating under S3
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for beta_developed in lst_beta_developed:
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# for beta_developed in [0.5]: # fix beta as 0.5
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for tariff_percentage_1 in lst_tariff:
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for tariff_percentage_2 in lst_tariff:
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# fix lambda as 0.5
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n_exp += self.add_experiment_1(idx_scenario, [0.5], int_eliminated,
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beta_developed, tariff_percentage_1, tariff_percentage_2)
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print(f'Inserted {n_exp} experiments for exp {idx_scenario}!')
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def add_experiment_1(self, idx_exp, lst_lambda, is_eliminated, flt_beta_developed,
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tariff_percentage_1: float, tariff_percentage_2: float):
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lst_exp = []
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for lambda_tier in lst_lambda:
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e = Experiment(idx_exp=idx_exp,
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int_n_country=int(self.dct_parameter['int_n_country']),
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max_int_n_supplier=int(self.dct_parameter['max_int_n_supplier']),
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int_n_product=int(self.dct_parameter['int_n_product']),
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int_n_firm_per_product_per_country=int(
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self.dct_parameter['int_n_firm_per_product_per_country']),
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flt_demand_total=float(self.dct_parameter['flt_demand_total']),
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flt_bm_price_ratio=float(self.dct_parameter['flt_bm_price_ratio']),
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flt_beta_developing=float(self.dct_parameter['flt_beta_developing']),
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n_sample=int(self.dct_parameter['n_sample']),
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n_iter=int(self.dct_parameter['n_iter']),
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is_eliminated=is_eliminated,
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flt_beta_developed=flt_beta_developed,
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tariff_percentage_1=tariff_percentage_1,
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tariff_percentage_2=tariff_percentage_2,
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lambda_tier=float(lambda_tier))
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lst_exp.append(e)
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db_session.bulk_save_objects(lst_exp)
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db_session.commit()
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return len(lst_exp)
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def fill_sample_table(self):
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rng = random.Random(self.dct_parameter['meta_seed'])
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lst_seed = [rng.getrandbits(32) for _ in range(int(self.dct_parameter['n_sample']))]
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lst_exp = db_session.query(Experiment).all()
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lst_sample = []
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for experiment in lst_exp:
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for idx_sample in range(int(experiment.n_sample)):
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s = Sample(e_id=experiment.id,
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idx_sample=idx_sample+1,
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seed=lst_seed[idx_sample],
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is_done_flag=-1)
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lst_sample.append(s)
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db_session.bulk_save_objects(lst_sample)
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db_session.commit()
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print(f'Inserted {len(lst_sample)} samples!')
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def reset_db(self, force_drop=False):
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# first, check if tables exist
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lst_table_obj = [Base.metadata.tables[str_table] for str_table in ins.get_table_names()
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if str_table.startswith(self.db_name_prefix)]
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is_exist = len(lst_table_obj) > 0
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if force_drop:
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while is_exist:
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a_table = random.choice(lst_table_obj)
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try:
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Base.metadata.drop_all(bind=engine, tables=[a_table])
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except KeyError:
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pass
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except OperationalError:
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pass
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else:
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lst_table_obj.remove(a_table)
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print(f"Table {a_table.name} is dropped for exp: {self.db_name_prefix}!!!")
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finally:
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is_exist = len(lst_table_obj) > 0
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if is_exist:
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print(f"All tables exist. No need to reset for exp: {self.db_name_prefix}.")
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# change the is_done_flag from 0 to -1, to rerun the in-finished tasks
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if self.reset_flag > 0:
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if self.reset_flag == 2:
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result = db_session.query(Sample).filter(Sample.is_done_flag == 0)
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elif self.reset_flag == 1:
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result = db_session.query(Sample).filter(Sample.is_done_flag == 0,
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Sample.computer_name == platform.node())
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else:
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raise ValueError('Wrong reset flag')
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if result.count() > 0:
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for res in result:
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qry_product = db_session.query(Product).filter_by(s_id=res.id)
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if qry_product.count() > 0:
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for p in qry_product:
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db_session.query(Firm).filter(Firm.p_id == p.id).delete()
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db_session.commit()
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db_session.query(Product).filter(Product.id == p.id).delete()
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db_session.commit()
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res.is_done_flag = -1
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db_session.commit()
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print(f"Reset the task id {res.id} flag from 0 to -1")
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else:
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Base.metadata.create_all()
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self.init_tables()
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print(f"All tables are just created and initialized for exp: {self.db_name_prefix}.")
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def prepare_list_sample(self):
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res = db_session.execute(f'''SELECT count(*) FROM {self.db_name_prefix}_sample s,
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{self.db_name_prefix}_experiment e WHERE s.e_id=e.id and e.idx_exp < 3''').scalar()
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n_sample_1_2 = 0 if res is None else res
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print(f'There are {n_sample_1_2} sample for exp 1 and 2.')
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res = db_session.execute(f'SELECT id FROM {self.db_name_prefix}_sample WHERE is_done_flag = -1')
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for row in res:
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s_id = row[0]
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if s_id <= n_sample_1_2:
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self.lst_saved_s_id_1_2.append(s_id)
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else:
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self.lst_saved_s_id_3.append(s_id)
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print(f'Left: {len(self.lst_saved_s_id_1_2)} for exp 1 and 2; {len(self.lst_saved_s_id_3)} for exp 3')
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@staticmethod
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def select_random_sample(lst_s_id):
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while 1:
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if len(lst_s_id) == 0:
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return None
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s_id = random.choice(lst_s_id)
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lst_s_id.remove(s_id)
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res = db_session.query(Sample).filter(Sample.id == int(s_id), Sample.is_done_flag == -1)
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if res.count() == 1:
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return res[0]
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def fetch_a_sample(self, s_id=None):
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if s_id is not None:
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res = db_session.query(Sample).filter(Sample.id == int(s_id))
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if res.count() == 0:
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return None
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else:
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return res[0]
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sample = self.select_random_sample(self.lst_saved_s_id_1_2)
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if sample is not None:
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return sample
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sample = self.select_random_sample(self.lst_saved_s_id_3)
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if sample is not None:
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return sample
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return None
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@staticmethod
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def lock_the_sample(sample: Sample):
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sample.is_done_flag, sample.computer_name = 0, platform.node()
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db_session.commit()
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if __name__ == '__main__':
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# pprint.pprint(dct_exp_config)
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# pprint.pprint(dct_conf_problem)
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db = ControllerDB('first')
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ratio = db_session.execute('SELECT COUNT(*) / 332750 FROM first_sample s WHERE s.is_done_flag = 1').scalar()
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print(ratio)
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# db.fill_experiment_table()
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# print(db.dct_parameter)
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# db.init_tables()
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|
# db.fill_sample_table()
|
||||||
|
# pprint.pprint(dct_conf_exp)
|
||||||
|
# db.update_bi()
|
||||||
|
# db.reset_db(force_drop=True)
|
||||||
|
# db.prepare_list_sample()
|
||||||
|
#
|
||||||
|
# for i in range(1000):
|
||||||
|
# if i % 10 == 0:
|
||||||
|
# print(i)
|
||||||
|
# print(len(db.lst_saved_s_id_1_2), len(db.lst_saved_s_id_3))
|
||||||
|
# r = db.fetch_a_sample()
|
||||||
|
# if i % 10 == 0:
|
||||||
|
# print(len(db.lst_saved_s_id_1_2), len(db.lst_saved_s_id_3))
|
||||||
|
# print(r, r.experiment.idx_exp)
|
||||||
|
# if i == 400:
|
||||||
|
# print()
|
||||||
|
# pass
|
48
main.py
48
main.py
|
@ -19,34 +19,34 @@ def do_computation(c_db):
|
||||||
break
|
break
|
||||||
|
|
||||||
|
|
||||||
# if __name__ == '__main__':
|
if __name__ == '__main__':
|
||||||
# parser = argparse.ArgumentParser(description='setting')
|
parser = argparse.ArgumentParser(description='setting')
|
||||||
# parser.add_argument('--exp', type=str, default='test')
|
parser.add_argument('--exp', type=str, default='test')
|
||||||
# parser.add_argument('--job', type=int, default='3')
|
parser.add_argument('--job', type=int, default='3')
|
||||||
# parser.add_argument('--reset', type=int, default='0')
|
parser.add_argument('--reset', type=int, default='0')
|
||||||
|
|
||||||
# args = parser.parse_args()
|
args = parser.parse_args()
|
||||||
# assert args.job >= 1, 'Number of jobs should >= 1'
|
assert args.job >= 1, 'Number of jobs should >= 1'
|
||||||
|
|
||||||
# prefix_file_name = 'conf_db_prefix.yaml'
|
prefix_file_name = 'conf_db_prefix.yaml'
|
||||||
# if os.path.exists(prefix_file_name):
|
if os.path.exists(prefix_file_name):
|
||||||
# os.remove(prefix_file_name)
|
os.remove(prefix_file_name)
|
||||||
# with open(prefix_file_name, 'w', encoding='utf-8') as file:
|
with open(prefix_file_name, 'w', encoding='utf-8') as file:
|
||||||
# yaml.dump({'db_name_prefix': args.exp}, file)
|
yaml.dump({'db_name_prefix': args.exp}, file)
|
||||||
|
|
||||||
# from controller_db import ControllerDB
|
from controller_db import ControllerDB
|
||||||
# controller_db = ControllerDB(args.exp, reset_flag=args.reset)
|
controller_db = ControllerDB(args.exp, reset_flag=args.reset)
|
||||||
# controller_db.reset_db()
|
controller_db.reset_db()
|
||||||
|
|
||||||
# controller_db.prepare_list_sample()
|
controller_db.prepare_list_sample()
|
||||||
|
|
||||||
# close_all_sessions()
|
close_all_sessions()
|
||||||
|
|
||||||
# process_list = []
|
process_list = []
|
||||||
# for i in range(int(args.job)):
|
for i in range(int(args.job)):
|
||||||
# p = Process(target=do_computation, args=(controller_db,))
|
p = Process(target=do_computation, args=(controller_db,))
|
||||||
# p.start()
|
p.start()
|
||||||
# process_list.append(p)
|
process_list.append(p)
|
||||||
|
|
||||||
# for i in process_list:
|
for i in process_list:
|
||||||
# i.join()
|
i.join()
|
||||||
|
|
4
model.py
4
model.py
|
@ -324,5 +324,5 @@ class Model(ap.Model):
|
||||||
plt.savefig("network.png")
|
plt.savefig("network.png")
|
||||||
|
|
||||||
|
|
||||||
model = Model(dct_sample_para)
|
# model = Model(dct_sample_para)
|
||||||
model.run()
|
# model.run()
|
||||||
|
|
|
@ -0,0 +1,151 @@
|
||||||
|
# -*- coding: utf-8 -*-
|
||||||
|
from sqlalchemy import create_engine, inspect
|
||||||
|
from sqlalchemy.ext.declarative import declarative_base
|
||||||
|
from sqlalchemy import Column, Integer, String, ForeignKey, BigInteger, DECIMAL, DateTime, Text
|
||||||
|
from sqlalchemy.sql import func
|
||||||
|
from sqlalchemy.orm import relationship, Session
|
||||||
|
from sqlalchemy.pool import NullPool
|
||||||
|
import yaml
|
||||||
|
|
||||||
|
|
||||||
|
with open('conf_db.yaml') as file:
|
||||||
|
dct_conf_db_all = yaml.full_load(file)
|
||||||
|
is_local_db = dct_conf_db_all['is_local_db']
|
||||||
|
if is_local_db:
|
||||||
|
dct_conf_db = dct_conf_db_all['local']
|
||||||
|
else:
|
||||||
|
dct_conf_db = dct_conf_db_all['remote']
|
||||||
|
|
||||||
|
with open('conf_db_prefix.yaml') as file:
|
||||||
|
dct_conf_db_prefix = yaml.full_load(file)
|
||||||
|
db_name_prefix = dct_conf_db_prefix['db_name_prefix']
|
||||||
|
|
||||||
|
|
||||||
|
str_login = 'mysql://{}:{}@{}:{}/{}'.format(dct_conf_db['user_name'], dct_conf_db['password'],
|
||||||
|
dct_conf_db['address'], dct_conf_db['port'], dct_conf_db['db_name'])
|
||||||
|
print('DB is {}:{}/{}'.format(dct_conf_db['address'], dct_conf_db['port'], dct_conf_db['db_name']))
|
||||||
|
|
||||||
|
engine = create_engine(str_login, poolclass=NullPool) # must be null pool to avoid connection lost error
|
||||||
|
ins = inspect(engine)
|
||||||
|
|
||||||
|
Base = declarative_base(constructor=engine)
|
||||||
|
|
||||||
|
db_session = Session(bind=engine)
|
||||||
|
|
||||||
|
|
||||||
|
class Experiment(Base):
|
||||||
|
__tablename__ = f"{db_name_prefix}_experiment"
|
||||||
|
id = Column(Integer, primary_key=True, autoincrement=True)
|
||||||
|
|
||||||
|
idx_exp = Column(Integer, nullable=False)
|
||||||
|
|
||||||
|
# fixed parameters
|
||||||
|
int_n_country = Column(Integer, nullable=False)
|
||||||
|
max_int_n_supplier = Column(Integer, nullable=False) # uni(1, max), random parameter 1 of firm
|
||||||
|
int_n_product = Column(Integer, nullable=False)
|
||||||
|
int_n_firm_per_product_per_country = Column(Integer, nullable=False)
|
||||||
|
flt_demand_total = Column(DECIMAL(10, 2), nullable=False) # tri(0, total_demand, mean), to compute random para a
|
||||||
|
flt_bm_price_ratio = Column(DECIMAL(10, 2), nullable=False) # benchmark value of b, same for both countries
|
||||||
|
flt_beta_developing = Column(DECIMAL(10, 2), nullable=False) # benchmark value of c(beta), for developing countries
|
||||||
|
n_sample = Column(Integer, nullable=False)
|
||||||
|
n_iter = Column(Integer, nullable=False)
|
||||||
|
|
||||||
|
# variables
|
||||||
|
is_eliminated = Column(Integer, nullable=False)
|
||||||
|
flt_beta_developed = Column(DECIMAL(10, 2), nullable=False) # larger, for developed countries
|
||||||
|
lambda_tier = Column(DECIMAL(10, 2), nullable=False)
|
||||||
|
tariff_percentage_1 = Column(DECIMAL(10, 2), nullable=False)
|
||||||
|
tariff_percentage_2 = Column(DECIMAL(10, 2), nullable=False)
|
||||||
|
|
||||||
|
sample = relationship('Sample', back_populates='experiment', lazy='dynamic')
|
||||||
|
|
||||||
|
def __repr__(self):
|
||||||
|
return f'<Experiment: {self.id}>'
|
||||||
|
|
||||||
|
|
||||||
|
class Sample(Base):
|
||||||
|
__tablename__ = f"{db_name_prefix}_sample"
|
||||||
|
id = Column(Integer, primary_key=True, autoincrement=True)
|
||||||
|
e_id = Column(Integer, ForeignKey('{}.id'.format(f"{db_name_prefix}_experiment")), nullable=False)
|
||||||
|
|
||||||
|
idx_sample = Column(Integer, nullable=False)
|
||||||
|
seed = Column(BigInteger, nullable=False)
|
||||||
|
is_done_flag = Column(Integer, nullable=False) # -1, waiting; 0, running; 1, done
|
||||||
|
computer_name = Column(String(64), nullable=True)
|
||||||
|
ts_done = Column(DateTime(timezone=True), onupdate=func.now())
|
||||||
|
stop_t = Column(Integer, nullable=True)
|
||||||
|
|
||||||
|
c1_wealth = Column(DECIMAL(20, 2), nullable=True) # country 1, developing countries
|
||||||
|
c2_wealth = Column(DECIMAL(20, 2), nullable=True) # country 2, developed countries
|
||||||
|
c1_wealth_dgt = Column(Integer, nullable=True)
|
||||||
|
c2_wealth_dgt = Column(Integer, nullable=True)
|
||||||
|
c1_tariff = Column(DECIMAL(20, 2), nullable=True) # country 1, developing countries
|
||||||
|
c2_tariff = Column(DECIMAL(20, 2), nullable=True) # country 2, developed countries
|
||||||
|
c1_tariff_dgt = Column(Integer, nullable=True)
|
||||||
|
c2_tariff_dgt = Column(Integer, nullable=True)
|
||||||
|
c1_n_firms = Column(Integer, nullable=True)
|
||||||
|
c2_n_firms = Column(Integer, nullable=True)
|
||||||
|
c1_n_positive_firms = Column(Integer, nullable=True)
|
||||||
|
c2_n_positive_firms = Column(Integer, nullable=True)
|
||||||
|
network = Column(Text(4294000000), nullable=True)
|
||||||
|
network_order = Column(Text(4294000000), nullable=True)
|
||||||
|
network_country = Column(Text(4294000000), nullable=True)
|
||||||
|
|
||||||
|
experiment = relationship('Experiment', back_populates='sample', uselist=False)
|
||||||
|
product = relationship('Product', back_populates='sample', lazy='dynamic')
|
||||||
|
|
||||||
|
def __repr__(self):
|
||||||
|
return f'<Sample id: {self.id}>'
|
||||||
|
|
||||||
|
|
||||||
|
class Product(Base):
|
||||||
|
__tablename__ = f"{db_name_prefix}_product"
|
||||||
|
id = Column(Integer, primary_key=True, autoincrement=True)
|
||||||
|
s_id = Column(Integer, ForeignKey('{}.id'.format(f"{db_name_prefix}_sample")), nullable=False)
|
||||||
|
|
||||||
|
int_name = Column(Integer, nullable=False)
|
||||||
|
int_tier = Column(Integer, nullable=False)
|
||||||
|
n_up_products = Column(Integer, nullable=False)
|
||||||
|
n_peer_products = Column(Integer, nullable=False)
|
||||||
|
n_positive_firms = Column(Integer, nullable=False)
|
||||||
|
n_all_firms = Column(Integer, nullable=False)
|
||||||
|
gini_acc_demand_per_age = Column(DECIMAL(10, 2), nullable=False)
|
||||||
|
gini_acc_wealth_per_age = Column(DECIMAL(10, 2), nullable=False)
|
||||||
|
gini_acc_demand_per_age_all = Column(DECIMAL(10, 2), nullable=False)
|
||||||
|
gini_acc_wealth_per_age_all = Column(DECIMAL(10, 2), nullable=False)
|
||||||
|
# lst_n_positive_firms = Column(Text(4294000000), nullable=False)
|
||||||
|
# lst_n_all_firms = Column(Text(4294000000), nullable=False)
|
||||||
|
# lst_gini_acc_demand_per_age = Column(Text(4294000000), nullable=False)
|
||||||
|
# lst_gini_acc_wealth_per_age = Column(Text(4294000000), nullable=False)
|
||||||
|
# lst_gini_acc_demand_per_age_all = Column(Text(4294000000), nullable=False)
|
||||||
|
# lst_gini_acc_wealth_per_age_all = Column(Text(4294000000), nullable=False)
|
||||||
|
|
||||||
|
sample = relationship('Sample', back_populates='product', uselist=False)
|
||||||
|
firm = relationship('Firm', back_populates='product', lazy='dynamic')
|
||||||
|
|
||||||
|
def __repr__(self):
|
||||||
|
return f'<Product id: {self.id}>'
|
||||||
|
|
||||||
|
|
||||||
|
class Firm(Base):
|
||||||
|
__tablename__ = f"{db_name_prefix}_firm"
|
||||||
|
id = Column(Integer, primary_key=True, autoincrement=True)
|
||||||
|
p_id = Column(Integer, ForeignKey('{}.id'.format(f"{db_name_prefix}_product")), nullable=False)
|
||||||
|
|
||||||
|
idx_firm = Column(Integer, nullable=False)
|
||||||
|
int_n_supplier = Column(Integer, nullable=False)
|
||||||
|
flt_fix_cost = Column(DECIMAL(20, 2), nullable=False)
|
||||||
|
flt_q_star = Column(DECIMAL(20, 2), nullable=False)
|
||||||
|
acc_demand_per_age = Column(DECIMAL(20, 2), nullable=False)
|
||||||
|
acc_wealth_per_age = Column(DECIMAL(20, 2), nullable=False)
|
||||||
|
std_demand_per_age = Column(DECIMAL(20, 2), nullable=False)
|
||||||
|
|
||||||
|
product = relationship('Product', back_populates='firm', uselist=False)
|
||||||
|
|
||||||
|
def __repr__(self):
|
||||||
|
return f'<Firm id: {self.id}>'
|
||||||
|
|
||||||
|
|
||||||
|
if __name__ == '__main__':
|
||||||
|
Base.metadata.drop_all()
|
||||||
|
Base.metadata.create_all()
|
|
@ -8,6 +8,7 @@ cycler==0.11.0
|
||||||
decorator==5.1.1
|
decorator==5.1.1
|
||||||
dill==0.3.6
|
dill==0.3.6
|
||||||
docutils==0.19
|
docutils==0.19
|
||||||
|
greenlet==2.0.2
|
||||||
idna==3.4
|
idna==3.4
|
||||||
imagesize==1.4.1
|
imagesize==1.4.1
|
||||||
importlib-metadata==6.0.0
|
importlib-metadata==6.0.0
|
||||||
|
@ -18,6 +19,7 @@ MarkupSafe==2.1.2
|
||||||
matplotlib==3.3.4
|
matplotlib==3.3.4
|
||||||
matplotlib-inline==0.1.6
|
matplotlib-inline==0.1.6
|
||||||
multiprocess==0.70.14
|
multiprocess==0.70.14
|
||||||
|
mysqlclient==2.1.1
|
||||||
networkx==2.5
|
networkx==2.5
|
||||||
numpy==1.20.3
|
numpy==1.20.3
|
||||||
numpydoc==1.1.0
|
numpydoc==1.1.0
|
||||||
|
@ -26,10 +28,11 @@ pandas==1.4.1
|
||||||
pandas-stubs==1.2.0.39
|
pandas-stubs==1.2.0.39
|
||||||
Pillow==9.4.0
|
Pillow==9.4.0
|
||||||
Pygments==2.14.0
|
Pygments==2.14.0
|
||||||
pygraphviz @ file:///C:/Users/ASUS/OneDrive/Project/ScrAbm/Dissertation/IIabm/pygraphviz-1.9-cp38-cp38-win_amd64.whl
|
pygraphviz @ file:///C:/Users/ASUS/Downloads/pygraphviz-1.9-cp38-cp38-win_amd64.whl
|
||||||
pyparsing==3.0.9
|
pyparsing==3.0.9
|
||||||
python-dateutil==2.8.2
|
python-dateutil==2.8.2
|
||||||
pytz==2022.7.1
|
pytz==2022.7.1
|
||||||
|
PyYAML==6.0
|
||||||
requests==2.28.2
|
requests==2.28.2
|
||||||
SALib==1.4.7
|
SALib==1.4.7
|
||||||
scipy==1.10.1
|
scipy==1.10.1
|
||||||
|
@ -42,7 +45,10 @@ sphinxcontrib-htmlhelp==2.0.1
|
||||||
sphinxcontrib-jsmath==1.0.1
|
sphinxcontrib-jsmath==1.0.1
|
||||||
sphinxcontrib-qthelp==1.0.3
|
sphinxcontrib-qthelp==1.0.3
|
||||||
sphinxcontrib-serializinghtml==1.1.5
|
sphinxcontrib-serializinghtml==1.1.5
|
||||||
|
SQLAlchemy==2.0.5.post1
|
||||||
traitlets==5.9.0
|
traitlets==5.9.0
|
||||||
|
typing_extensions==4.5.0
|
||||||
urllib3==1.26.14
|
urllib3==1.26.14
|
||||||
wincertstore==0.2
|
wincertstore==0.2
|
||||||
|
yapf @ file:///tmp/build/80754af9/yapf_1615749224965/work
|
||||||
zipp==3.15.0
|
zipp==3.15.0
|
||||||
|
|
Loading…
Reference in New Issue