data collection

.vscode/launch.json

@@ -8,7 +8,7 @@
             "name": "Python: Current File",
             "type": "python",
             "request": "launch",
-            "program": "C:\\Users\\ASUS\\OneDrive\\Project\\ScrAbm\\Dissertation\\IIabm\\model.py",
+            "program": "C:\\Users\\ASUS\\OneDrive\\Project\\ScrAbm\\Dissertation\\IIabm\\main.py",
             "console": "integratedTerminal",
             "justMyCode": true
         }

computation.py

@@ -0,0 +1,52 @@
+import os
+import datetime
+
+from model import Model
+
+from typing import TYPE_CHECKING
+if TYPE_CHECKING:
+    from controller_db import ControllerDB
+    
+
+class Computation:
+
+    def __init__(self, c_db: 'ControllerDB'):
+        self.c_db = c_db
+        self.pid = os.getpid()
+
+    def run(self, str_code='0', s_id=None):
+        sample_random = self.c_db.fetch_a_sample(s_id)
+        if sample_random is None:
+            return True
+
+        # lock this row by update is_done_flag to 0
+        self.c_db.lock_the_sample(sample_random)
+        print(f"Pid {self.pid} ({str_code}) is running sample {sample_random.id} at {datetime.datetime.now()}")
+
+        dct_exp = {column: getattr(sample_random.experiment, column)
+                   for column in sample_random.experiment.__table__.c.keys()}
+        del dct_exp['id']
+
+        dct_sample_para = {'sample': sample_random,
+                           'seed': sample_random.seed,
+                           **dct_exp}
+        model = Model(dct_sample_para)
+        results = model.run(display=False)
+        return False
+
+
+if __name__ == '__main__':
+    str_exp = 'test'
+
+    from controller_db import ControllerDB
+
+    controller_db = ControllerDB(str_exp)
+    controller_db.reset_db()
+    # print(controller_db.dct_parameter)
+    exp = Computation(controller_db)
+    is_all_done = exp.run('999', 87)
+    # while 1:
+    #     # time.sleep(random.uniform(0, 10))
+    #     is_all_done = exp.run(str_exp)
+    #     if is_all_done:
+    #         break

conf_db.yaml

@@ -0,0 +1,16 @@
+# read by orm
+is_local_db: True
+
+local:
+  user_name: iiabm_yz
+  password: iiabm_yz
+  db_name: iiabmdb
+  address: 'localhost'
+  port: 3306
+
+remote:
+  user_name: iiabm_yz
+  password: iiabm_yz
+  db_name: iiabmdb
+  address: 'localhost'
+  port: 3307

conf_db_prefix.yaml

@@ -0,0 +1 @@
+db_name_prefix: test

conf_experiment.yaml

@@ -0,0 +1,38 @@
+# read by ControllerDB
+
+# run settings
+meta_seed: 0
+
+fixed:  # unchanged all the time
+  int_n_country: 2
+  max_int_n_supplier: 3  # make firms heterogeneous
+  flt_bm_price_ratio: 20.0
+  flt_beta_developing: 0.5
+
+test:  # only for test scenarios
+  int_n_product: 12
+  int_n_firm_per_product_per_country: 2
+  flt_demand_total: 1000.0
+  n_sample: 5
+  n_iter: 100
+
+not_test:  # normal scenarios
+  int_n_product: 50
+  int_n_firm_per_product_per_country: 10
+  flt_demand_total: 10000.0
+  n_sample: 50
+  n_iter: 10000
+
+default:
+  is_eliminated: 0  # add when all positive profits and keep max n supplier; remove the worst when all negative wealth
+  flt_beta_developed: 0.5  # benchmarks flt_beta_developed
+  tariff_percentage: 0
+
+experiment:
+  1:
+    range_lambda_tier: 0, 1, 0.1  # describe the network. 0: chain 1: one iter
+  2:
+    is_eliminated: 1
+  3:
+    range_flt_beta_developed: 0.5, 0.9, 0.1
+    range_tariff_percentage: 0, 1, 0.1

controller_db.py

@@ -0,0 +1,237 @@
+# -*- coding: utf-8 -*-
+from orm import db_session, engine, Base, ins
+from orm import Experiment, Sample, Product, Firm
+from sqlalchemy.exc import OperationalError
+import yaml
+import random
+import numpy as np
+import platform
+
+
+class ControllerDB:
+    dct_parameter = None
+    is_test: bool = None
+    db_name_prefix: str = None
+    reset_flag: int
+
+    lst_saved_s_id_3: list
+    lst_saved_s_id_1_2: list
+    # n_sample_1_2: int
+
+    def __init__(self, prefix, reset_flag=0):
+        with open('conf_experiment.yaml') as yaml_file:
+            dct_conf_experiment = yaml.full_load(yaml_file)
+        self.is_test = prefix == 'test'
+        self.db_name_prefix = prefix
+        dct_para_in_test = dct_conf_experiment['test'] if self.is_test else dct_conf_experiment['not_test']
+        self.dct_parameter = {'meta_seed': dct_conf_experiment['meta_seed'],
+                              'experiment': dct_conf_experiment['experiment'],
+                              **dct_conf_experiment['fixed'], **dct_conf_experiment['default'], **dct_para_in_test}
+        self.reset_flag = reset_flag  # 0, not reset; 1, reset self; 2, reset all
+        self.lst_saved_s_id_1_2, self.lst_saved_s_id_3 = [], []
+
+    def init_tables(self):
+        self.fill_experiment_table()
+        self.fill_sample_table()
+
+    @staticmethod
+    def get_lst_of_range(str_range: str):
+        s1, s2, s3 = tuple(str_range.split(','))
+        return list(np.linspace(float(s1), float(s2), num=int((float(s2) - float(s1)) / float(s3)) + 1))
+
+    def fill_experiment_table(self):
+        # prepare the list of lambda tier
+        lst_lambda = self.get_lst_of_range(self.dct_parameter['experiment'][1]['range_lambda_tier'])
+        # prepare the list of alpha_2nd_country
+        lst_beta_developed = self.get_lst_of_range(self.dct_parameter['experiment'][3]['range_flt_beta_developed'])
+        # prepare the list of tariff_percentage
+        lst_tariff = self.get_lst_of_range(self.dct_parameter['experiment'][3]['range_tariff_percentage'])
+        # prepare the default values
+        is_eliminated = int(self.dct_parameter['is_eliminated'])
+        beta_developed = float(self.dct_parameter['flt_beta_developed'])
+        tariff_percentage_1 = tariff_percentage_2 = float(self.dct_parameter['tariff_percentage'])
+        for idx_scenario in self.dct_parameter['experiment'].keys():
+            n_exp = 0
+            # if idx_scenario == 1:  # add S1 experiments
+            #     n_exp = self.add_experiment_1(idx_scenario, lst_lambda, is_eliminated,
+            #                                   beta_developed, tariff_percentage_1, tariff_percentage_2)
+            # if idx_scenario == 2:  # add S2 experiments
+            #     n_exp = self.add_experiment_1(idx_scenario, lst_lambda,
+            #                                   int(self.dct_parameter['experiment'][idx_scenario]['is_eliminated']),
+            #                                   beta_developed, tariff_percentage_1, tariff_percentage_2)
+            if idx_scenario == 3:
+                # int_eliminated = int(self.dct_parameter['experiment'][idx_scenario-1]['is_eliminated'])
+                int_eliminated = is_eliminated  # is_eliminated is 0 at default, so stop eliminating under S3
+                for beta_developed in lst_beta_developed:
+                # for beta_developed in [0.5]:  # fix beta as 0.5
+                    for tariff_percentage_1 in lst_tariff:
+                        for tariff_percentage_2 in lst_tariff:
+                            # fix lambda as 0.5
+                            n_exp += self.add_experiment_1(idx_scenario, [0.5], int_eliminated,
+                                                           beta_developed, tariff_percentage_1, tariff_percentage_2)
+            print(f'Inserted {n_exp} experiments for exp {idx_scenario}!')
+
+    def add_experiment_1(self, idx_exp, lst_lambda, is_eliminated, flt_beta_developed,
+                         tariff_percentage_1: float, tariff_percentage_2: float):
+        lst_exp = []
+        for lambda_tier in lst_lambda:
+            e = Experiment(idx_exp=idx_exp,
+                           int_n_country=int(self.dct_parameter['int_n_country']),
+                           max_int_n_supplier=int(self.dct_parameter['max_int_n_supplier']),
+                           int_n_product=int(self.dct_parameter['int_n_product']),
+                           int_n_firm_per_product_per_country=int(
+                               self.dct_parameter['int_n_firm_per_product_per_country']),
+                           flt_demand_total=float(self.dct_parameter['flt_demand_total']),
+                           flt_bm_price_ratio=float(self.dct_parameter['flt_bm_price_ratio']),
+                           flt_beta_developing=float(self.dct_parameter['flt_beta_developing']),
+                           n_sample=int(self.dct_parameter['n_sample']),
+                           n_iter=int(self.dct_parameter['n_iter']),
+                           is_eliminated=is_eliminated,
+                           flt_beta_developed=flt_beta_developed,
+                           tariff_percentage_1=tariff_percentage_1,
+                           tariff_percentage_2=tariff_percentage_2,
+                           lambda_tier=float(lambda_tier))
+            lst_exp.append(e)
+        db_session.bulk_save_objects(lst_exp)
+        db_session.commit()
+        return len(lst_exp)
+
+    def fill_sample_table(self):
+        rng = random.Random(self.dct_parameter['meta_seed'])
+        lst_seed = [rng.getrandbits(32) for _ in range(int(self.dct_parameter['n_sample']))]
+        lst_exp = db_session.query(Experiment).all()
+        lst_sample = []
+        for experiment in lst_exp:
+            for idx_sample in range(int(experiment.n_sample)):
+                s = Sample(e_id=experiment.id,
+                           idx_sample=idx_sample+1,
+                           seed=lst_seed[idx_sample],
+                           is_done_flag=-1)
+                lst_sample.append(s)
+        db_session.bulk_save_objects(lst_sample)
+        db_session.commit()
+        print(f'Inserted {len(lst_sample)} samples!')
+
+    def reset_db(self, force_drop=False):
+        # first, check if tables exist
+        lst_table_obj = [Base.metadata.tables[str_table] for str_table in ins.get_table_names()
+                         if str_table.startswith(self.db_name_prefix)]
+        is_exist = len(lst_table_obj) > 0
+        if force_drop:
+            while is_exist:
+                a_table = random.choice(lst_table_obj)
+                try:
+                    Base.metadata.drop_all(bind=engine, tables=[a_table])
+                except KeyError:
+                    pass
+                except OperationalError:
+                    pass
+                else:
+                    lst_table_obj.remove(a_table)
+                    print(f"Table {a_table.name} is dropped for exp: {self.db_name_prefix}!!!")
+                finally:
+                    is_exist = len(lst_table_obj) > 0
+
+        if is_exist:
+            print(f"All tables exist. No need to reset for exp: {self.db_name_prefix}.")
+            # change the is_done_flag from 0 to -1, to rerun the in-finished tasks
+            if self.reset_flag > 0:
+                if self.reset_flag == 2:
+                    result = db_session.query(Sample).filter(Sample.is_done_flag == 0)
+                elif self.reset_flag == 1:
+                    result = db_session.query(Sample).filter(Sample.is_done_flag == 0,
+                                                             Sample.computer_name == platform.node())
+                else:
+                    raise ValueError('Wrong reset flag')
+                if result.count() > 0:
+                    for res in result:
+                        qry_product = db_session.query(Product).filter_by(s_id=res.id)
+                        if qry_product.count() > 0:
+                            for p in qry_product:
+                                db_session.query(Firm).filter(Firm.p_id == p.id).delete()
+                                db_session.commit()
+                                db_session.query(Product).filter(Product.id == p.id).delete()
+                                db_session.commit()
+                        res.is_done_flag = -1
+                        db_session.commit()
+                        print(f"Reset the task id {res.id} flag from 0 to -1")
+        else:
+            Base.metadata.create_all()
+            self.init_tables()
+            print(f"All tables are just created and initialized for exp: {self.db_name_prefix}.")
+
+    def prepare_list_sample(self):
+        res = db_session.execute(f'''SELECT count(*) FROM {self.db_name_prefix}_sample s, 
+        {self.db_name_prefix}_experiment e WHERE s.e_id=e.id and e.idx_exp < 3''').scalar()
+        n_sample_1_2 = 0 if res is None else res
+        print(f'There are {n_sample_1_2} sample for exp 1 and 2.')
+        res = db_session.execute(f'SELECT id FROM {self.db_name_prefix}_sample WHERE is_done_flag = -1')
+        for row in res:
+            s_id = row[0]
+            if s_id <= n_sample_1_2:
+                self.lst_saved_s_id_1_2.append(s_id)
+            else:
+                self.lst_saved_s_id_3.append(s_id)
+        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')
+
+    @staticmethod
+    def select_random_sample(lst_s_id):
+        while 1:
+            if len(lst_s_id) == 0:
+                return None
+            s_id = random.choice(lst_s_id)
+            lst_s_id.remove(s_id)
+            res = db_session.query(Sample).filter(Sample.id == int(s_id), Sample.is_done_flag == -1)
+            if res.count() == 1:
+                return res[0]
+
+    def fetch_a_sample(self, s_id=None):
+        if s_id is not None:
+            res = db_session.query(Sample).filter(Sample.id == int(s_id))
+            if res.count() == 0:
+                return None
+            else:
+                return res[0]
+
+        sample = self.select_random_sample(self.lst_saved_s_id_1_2)
+        if sample is not None:
+            return sample
+
+        sample = self.select_random_sample(self.lst_saved_s_id_3)
+        if sample is not None:
+            return sample
+
+        return None
+
+    @staticmethod
+    def lock_the_sample(sample: Sample):
+        sample.is_done_flag, sample.computer_name = 0, platform.node()
+        db_session.commit()
+
+
+if __name__ == '__main__':
+    # pprint.pprint(dct_exp_config)
+    # pprint.pprint(dct_conf_problem)
+    db = ControllerDB('first')
+    ratio = db_session.execute('SELECT COUNT(*) / 332750 FROM first_sample s WHERE s.is_done_flag = 1').scalar()
+    print(ratio)
+    # db.fill_experiment_table()
+    # print(db.dct_parameter)
+    # db.init_tables()
+    # 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

firm.py

@@ -41,7 +41,7 @@ class FirmAgent(ap.Agent):
                 ]
                 # print(select_edges)
                 if len(select_edges) == 0:
-                    print('affect', customer.name, remove_product.code)
+                    print(self.name, remove_product.code, 'affect', customer.name)
                     if remove_product not in \
                             customer.a_list_up_product_removed:
                         customer.a_list_up_product_removed.append(
@@ -136,3 +136,7 @@ class FirmAgent(ap.Agent):
 
     def clean_before_trial(self):
         self.dct_request_prod_from_firm = {}
+
+    def clean_before_time_step(self):
+        self.dct_num_trial_up_product_removed = {}
+        self.a_list_up_product_removed = ap.AgentList(self.model, [])

main.py

@@ -0,0 +1,52 @@
+import os
+import random
+import time
+from multiprocessing import Process
+import argparse
+from computation import Computation
+from sqlalchemy.orm import close_all_sessions
+
+import yaml
+
+
+def do_computation(c_db):
+    exp = Computation(c_db)
+
+    while 1:
+        time.sleep(random.uniform(0, 10))
+        is_all_done = exp.run()
+        if is_all_done:
+            break
+
+
+if __name__ == '__main__':
+    parser = argparse.ArgumentParser(description='setting')
+    parser.add_argument('--exp', type=str, default='test')
+    parser.add_argument('--job', type=int, default='3')
+    parser.add_argument('--reset', type=int, default='0')
+
+    args = parser.parse_args()
+    assert args.job >= 1, 'Number of jobs should >= 1'
+
+    prefix_file_name = 'conf_db_prefix.yaml'
+    if os.path.exists(prefix_file_name):
+        os.remove(prefix_file_name)
+    with open(prefix_file_name, 'w', encoding='utf-8') as file:
+        yaml.dump({'db_name_prefix': args.exp}, file)
+
+    from controller_db import ControllerDB
+    controller_db = ControllerDB(args.exp, reset_flag=args.reset)
+    controller_db.reset_db()
+
+    controller_db.prepare_list_sample()
+
+    close_all_sessions()
+
+    process_list = []
+    for i in range(int(args.job)):
+        p = Process(target=do_computation, args=(controller_db,))
+        p.start()
+        process_list.append(p)
+
+    for i in process_list:
+        i.join()

model.py

@@ -8,9 +8,15 @@ from product import ProductAgent
 
 sample = 0
 seed = 0
-n_iter = 3
+n_iter = 10
 # dct_list_init_remove_firm_prod = {133: ['1.4.4.1'], 2: ['1.1.3']}
+# dct_list_init_remove_firm_prod = {
+#     135: ['1.3.2.1'],
+#     133: ['1.4.4.1'],
+#     2: ['1.1.3']
+# }
 dct_list_init_remove_firm_prod = {
+    140: ['1.4.5.1'],
     135: ['1.3.2.1'],
     133: ['1.4.4.1'],
     2: ['1.1.3']
@@ -177,6 +183,7 @@ class Model(ap.Model):
         self.draw_network()
 
     def update(self):
+        self.a_list_total_firms.clean_before_time_step()
         # stop simulation if reached terminal number of iteration
         if self.t == self.int_n_iter or len(
                 self.dct_list_remove_firm_prod) == 0:
@@ -232,6 +239,7 @@ class Model(ap.Model):
         self.dct_list_remove_firm_prod = {}
         for firm in self.a_list_total_firms:
             if len(firm.a_list_up_product_removed) > 0:
+                print(firm.name, 'a_list_up_product_removed', [product.code for product in firm.a_list_up_product_removed])
                 for product in firm.a_list_product:
                     n_up_product_removed = 0
                     for up_product_removed in firm.a_list_up_product_removed:
@@ -251,8 +259,9 @@ class Model(ap.Model):
                                     1) / (max(list_revenue_log) -
                                           min(list_revenue_log) + 1)
                         p_remove = 1 - std_size * (1 - lost_percent)
-                        flag = self.nprandom.choice([1, 0],
-                                                    p=[p_remove, 1 - p_remove])
+                        # flag = self.nprandom.choice([1, 0],
+                        #                             p=[p_remove, 1 - p_remove])
+                        flag = 1
                         if flag == 1:
                             firm.a_list_product_removed.append(product)
                             # if firm in
@@ -315,5 +324,5 @@ class Model(ap.Model):
         plt.savefig("network.png")
 
 
-model = Model(dct_sample_para)
-model.run()
+# model = Model(dct_sample_para)
+# model.run()

orm.py

@@ -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()

requirements.txt

@@ -8,6 +8,7 @@ cycler==0.11.0
 decorator==5.1.1
 dill==0.3.6
 docutils==0.19
+greenlet==2.0.2
 idna==3.4
 imagesize==1.4.1
 importlib-metadata==6.0.0
@@ -18,6 +19,7 @@ MarkupSafe==2.1.2
 matplotlib==3.3.4
 matplotlib-inline==0.1.6
 multiprocess==0.70.14
+mysqlclient==2.1.1
 networkx==2.5
 numpy==1.20.3
 numpydoc==1.1.0
@@ -26,10 +28,11 @@ pandas==1.4.1
 pandas-stubs==1.2.0.39
 Pillow==9.4.0
 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
 python-dateutil==2.8.2
 pytz==2022.7.1
+PyYAML==6.0
 requests==2.28.2
 SALib==1.4.7
 scipy==1.10.1
@@ -42,7 +45,10 @@ sphinxcontrib-htmlhelp==2.0.1
 sphinxcontrib-jsmath==1.0.1
 sphinxcontrib-qthelp==1.0.3
 sphinxcontrib-serializinghtml==1.1.5
+SQLAlchemy==2.0.5.post1
 traitlets==5.9.0
+typing_extensions==4.5.0
 urllib3==1.26.14
 wincertstore==0.2
+yapf @ file:///tmp/build/80754af9/yapf_1615749224965/work
 zipp==3.15.0