Mainframe-Pro update

data/note.txt

@@ -0,0 +1,66 @@
+Soooo, lets think about it.
+在银河系，一个离银心不近也不远的地方，诞生了希尔文明。
+他们蹒跚起步，征服了陆地，迈向了海洋。他们很幸运，
+
+一个路过的黑洞扯碎了希尔文明的母星系，但是希尔文明没有心灰气馁，他们抢在灾难降临之前，倾尽全部的智慧，把文明的种子播撒了出去。
+现在，距离希尔舰队启航，已经过去了15个千年。新生的希尔人已经习惯了在群星中的生活。他们出生在星舰，在星河间穿行，以探索为荣耀。
+舰队偶尔会在某个星系落脚，补充星际旅行所必需的燃料和物质。但他们不会长久的停留。
+为了保证舰队的出现不会干涉到孕育中的文明种子，在舰队泊入一个恒星系之前，需要派出探险队确认目标星系没有生命诞生。
+这是一个重要而有趣的工作，在年轻人中很受欢迎，但只有最优秀的探星者才能参与这项充满荣耀的工作，驾驶着【星火】级星系探索飞船，在舰载AI的帮助下对恒星系展开细致而全面的探索。
+以及为后续舰队补充资源建立前哨基地。
+这是严垣从小就梦寐以求的工作。能够离开【此处需要插入某个形容狭小的形容词】的星舰，前往未知的世界探索，这样的生活实在是令人心潮澎湃。
+在经过了10余年的勤学苦读，12个月的艰苦训练后，严垣如愿以偿，成为了一名光荣的探星者。
+
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+
+We need to ensure a 1600 arrival in the destination, leaving us with around 30 minutes of redundancy.
+The current estimation of travel time is around 90 minutes.
+Which means a 1400 departure is optimal.
+
+We need to check the traffic status 10 minutes before departure. Anything longer than 120 minutes will forbid the driving plan.
+In which case we will transition into public traffic.
+
+We will need to pack the consumables, including water and necessary food. Which I intend to be prepared before lunchtime.
+We also need to pack 2 set of personal terminals, power bank, Etc
+
+1200 Consumables preparation complete
+1350 Final travel plan decision point.
+    In the event of the selection of public transportation, the plan is bike-9-1-5-bus. With a 1400 departure we should catch the 1540 bus.
+1355 Donning the Doctor's gear.
+1400 Departure.
+
+
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+
+I am listening to the OST of Lone-trail while I type this down.
+Kristen.
+I'm not going to deny, that I like her.
+I like the idea of exploration. I like the idea of pushing the boundary. And she managed to do just that.
+Comparing to her colleague, she is just a mortal. She is not as indestructible as Seria. She does not have the noble blood like Muelsyse.
+But her none-stopping spirit of advance is the purest of them all. And under such spirit, Rhine Lab was found and united.
+Her sins cannot be neglected, that I admit. But I can not resist my desire to salute her.
+I salute to a pioneer, a scientist, a visionary, who gave all, risk all to challenge the unknown.
+And now, even sky is not the limit.
+Mortals are weak, but in that weakness, greatness is born. I find this phrase very suitable for her.
+Ad astra, to the stars. Kristen, good night.
+
+And about Lone-trail, there's more I enjoy.
+Kristen is a great character that I like so much, but the storyline did not just focus on how great her is.
+It did not just shape a great character and call her sins necessary evil.

src/KSP-tools/EngineDataProcess_DB_upload.py

@@ -0,0 +1,49 @@
+import pandas as pd
+from src.PostgresSQL.databaseHandler import DatabaseHandler
+
+
+def process_excel():
+    path = 'C://Users//26549//OneDrive//文档//KSP Engine Tweak Chart.xlsx'
+    excel_content = pd.read_excel(path)
+    data_list = []
+    for row, content in excel_content.iterrows():
+        if isinstance(content['Vac-ISP'], str) and '-' in content['Vac-ISP']:
+            content['SL-ISP'], content['Vac-ISP'] = float(content['Vac-ISP'].split('-')[0]), float(
+                content['Vac-ISP'].split('-')[1])
+        else:
+            content['SL-ISP'] = content['Vac-ISP']
+        data_list.append(dict(content))
+
+    df = pd.DataFrame(data_list, columns=[item for item in data_list[0]])
+    df.to_excel('data//KSP Engine Tweak Chart_NEW.xlsx')
+
+
+def upload_to_database(database_config):
+    path = 'C://Users//26549//OneDrive//文档//KSP Engine Tweak Chart.xlsx'
+    excel_content = pd.read_excel(path, keep_default_na=False)
+
+    table_structure = dict(excel_content.loc[1])
+    data_content_list = [dict(values) for _key, values in excel_content.iterrows()]
+    for key, values in table_structure.items():
+        if str(values) in ('nan', 'nat'):
+            table_structure[key] = 'TEXT'
+        elif isinstance(values, float):
+            table_structure[key] = 'FLOAT4'
+        else:
+            table_structure[key] = 'TEXT'
+    handler = DatabaseHandler(database_config)
+
+    handler.create_table(table_structure, 'Engine_Data', force_create=True)
+    handler.insert_into_table('Engine_Data', data_content_list)
+
+    handler.close()
+
+
+if __name__ == '__main__':
+    # process_excel()
+    config = {'database': 'KSP', 'user': 'postgres', 'password': 'Armor17909', 'host': '127.0.0.1', 'port': '5432'}
+    upload_to_database(config)
+
+
+
+    print('done')

src/KSP-tools/SRB_plot.py

@@ -0,0 +1,156 @@
+import numpy as np
+from matplotlib import pyplot as plt
+
+
+def cal_fuel_consumption_ratio(thrust, ISP):
+    return float(thrust) / (9.80665 * float(ISP))
+
+
+def get_thrust(fuel_percentage):
+    global thrust_curve
+    fuel_level = [i for i in thrust_curve]
+    for i in range(len(fuel_level) - 1):
+        if fuel_level[i] >= fuel_percentage > fuel_level[i + 1]:
+            prev_fuel = fuel_level[i]
+            nex_fuel = fuel_level[i + 1]
+            prev_thrust = thrust_curve[prev_fuel]
+            next_thrust = thrust_curve[nex_fuel]
+            if prev_thrust == next_thrust:
+                return prev_thrust
+            k = (prev_thrust - next_thrust) / (prev_fuel - nex_fuel)
+            result = prev_thrust - k * abs(prev_fuel - fuel_percentage)
+            return result
+    return 0
+
+
+def output_thrust_curve():
+    global thrust_curve
+    print("thrustCurve")
+    print("{")
+    for item in thrust_curve:
+        print(f'    key = {item} {thrust_curve[item]}')
+    print("}")
+
+"""
+thrust_curve = {
+    1.0000: 0.95,
+    0.9997: 0.95,
+    0.9500: 0.98,
+    0.8000: 1.0,
+    0.7500: 0.98,
+    0.7000: 0.95,
+    0.6500: 0.9,
+    0.6000: 0.85,
+    0.5500: 0.8,
+    0.5000: 0.75,
+    0.4700: 0.764,
+    0.4400: 0.778,
+    0.4000: 0.7966666666666666,
+    0.3500: 0.82,
+    0.3200: 0.826,
+    0.3000: 0.83,
+    0.2700: 0.826,
+    0.2500: 0.84,
+    0.2300: 0.824,
+    0.2000: 0.80,
+    0.1700: 0.77,
+    0.1500: 0.75,
+    0.1300: 0.67,
+    0.1000: 0.55,
+    0.0900: 0.5,
+    0.0800: 0.45,
+    0.0700: 0.40,
+    0.0600: 0.35714285714285715,
+    0.0500: 0.3142857142857143,
+    0.0400: 0.27142857142857146,
+    0.0350: 0.25,
+    0.0300: 0.23,
+    0.0200: 0.19,
+    0.0150: 0.17,
+    0.0100: 0.15,
+    0.0050: 0.12916666666666665,
+    0.0028: 0.12,
+    0.0018: 0.08,
+    0.0005: 0.05,
+    0.0000: 0.03}
+"""
+f = open('data/thrust_curve.txt', 'r')
+char = f.readlines()
+f.close()
+
+thrust_curve = {}
+for line in char:
+    temp = line.strip().replace('key = ', '').split(' ')
+    thrust_curve[float(temp[0])] = float(temp[1])
+    # print(temp)
+
+
+print(thrust_curve)
+
+
+dry_mass = 90
+fuel_mass = 500
+thrust = 14750
+ISP = 268
+
+plt.subplot(2, 2, 1)
+plt.title("Thrust Level to Fuel Comsumption")
+x = [1 - i for i in thrust_curve]
+y = [thrust_curve[i] for i in thrust_curve]
+
+plt.plot(x, y)
+
+plt.ylabel('Thrust Level')
+
+plt.subplot(2, 2, 2)
+plt.title("Acceleraion to Fuel Comsumption")
+twr = [thrust * thrust_curve[i] / (dry_mass + i * fuel_mass) for i in thrust_curve]
+
+plt.plot(x, twr)
+
+plt.xlabel('Fuel Consumed')
+plt.ylabel('Acceleraion')
+
+remaining_fuel_mass = fuel_mass
+
+time_list = []
+thrust_list = []
+acc_list = []
+
+now_step_time = 0
+now_step_thrust = 1
+now_step_fuel_percentage = 1
+while remaining_fuel_mass >= 0:
+    time_list.append(now_step_time)
+    thrust_list.append(get_thrust(now_step_fuel_percentage))
+    now_step_acc = thrust_list[-1] * thrust / (dry_mass + fuel_mass * now_step_fuel_percentage)
+    acc_list.append(now_step_acc)
+    # print(now_step_time, now_step_thrust, now_step_fuel_percentage, now_step_acc, remaining_fuel_mass)
+    now_step_time += 0.01
+    remaining_fuel_mass -= cal_fuel_consumption_ratio(thrust * now_step_thrust, ISP) * 0.01
+    now_step_fuel_percentage = remaining_fuel_mass / fuel_mass
+    now_step_thrust = get_thrust(now_step_fuel_percentage)
+    if now_step_acc == 0:
+        print('error')
+        print('remaining_fuel_mass', remaining_fuel_mass)
+        print('now_step_fuel_percentage', now_step_fuel_percentage)
+        break
+plt.subplot(2, 2, 4)
+plt.title("Acceleraion to Time")
+
+plt.plot(time_list, acc_list)
+
+plt.xlabel('Time in second')
+plt.ylabel('Acceleraion')
+
+plt.subplot(2, 2, 3)
+plt.title("Thrust to Time")
+
+plt.plot(time_list, thrust_list)
+
+plt.xlabel('Time in second')
+plt.ylabel('Thrust level')
+
+plt.show()
+print(time_list[-1])
+output_thrust_curve()

src/KSP-tools/antenna_patch_generator.py

@@ -69,6 +69,7 @@ def gen_single_patch(antenna):
     # print(result_str)
     return result_str
 
+
 if __name__ == '__main__':
     path = 'D://OneDrive//文档//KSP Engine Tweak Chart.xlsx'
     excel_content = pd.read_excel(path, sheet_name='Communication')

src/KSP-tools/data/thrust_curve.txt

@@ -0,0 +1,129 @@
+key = 1.00000 0.945
+key = 0.98942 0.945
+key = 0.97888 0.942
+key = 0.96834 0.942
+key = 0.95773 0.948
+key = 0.947 0.959
+key = 0.93618 0.967
+key = 0.92524 0.978
+key = 0.91426 0.981
+key = 0.90323 0.986
+key = 0.89216 0.989
+key = 0.8811 0.989
+key = 0.87 0.992
+key = 0.8589 0.992
+key = 0.84777 0.994
+key = 0.83665 0.994
+key = 0.82552 0.994
+key = 0.81439 0.994
+key = 0.80323 0.997
+key = 0.79207 0.997
+key = 0.78088 1
+key = 0.7697 1
+key = 0.75851 1
+key = 0.74744 0.989
+key = 0.73665 0.964
+key = 0.7261 0.942
+key = 0.71568 0.932
+key = 0.70544 0.915
+key = 0.69526 0.91
+key = 0.68518 0.901
+key = 0.67521 0.89
+key = 0.66537 0.88
+key = 0.65562 0.871
+key = 0.64599 0.86
+key = 0.63649 0.849
+key = 0.62711 0.838
+key = 0.61782 0.83
+key = 0.60862 0.822
+key = 0.59952 0.814
+key = 0.59047 0.808
+key = 0.58152 0.8
+key = 0.57269 0.789
+key = 0.56392 0.784
+key = 0.55527 0.773
+key = 0.54672 0.765
+key = 0.53823 0.759
+key = 0.52976 0.756
+key = 0.52136 0.751
+key = 0.51302 0.745
+key = 0.5048 0.734
+key = 0.49671 0.723
+key = 0.48868 0.718
+key = 0.4807 0.713
+key = 0.47273 0.713
+key = 0.46476 0.713
+key = 0.45675 0.715
+key = 0.44869 0.721
+key = 0.44056 0.726
+key = 0.43241 0.729
+key = 0.42422 0.732
+key = 0.416 0.734
+key = 0.40772 0.74
+key = 0.39941 0.743
+key = 0.39107 0.745
+key = 0.3827 0.748
+key = 0.3743 0.751
+key = 0.36586 0.754
+key = 0.3574 0.756
+key = 0.34891 0.759
+key = 0.34035 0.765
+key = 0.33176 0.767
+key = 0.32315 0.77
+key = 0.31453 0.77
+key = 0.30588 0.773
+key = 0.29723 0.773
+key = 0.28855 0.776
+key = 0.27987 0.776
+key = 0.2712 0.776
+key = 0.26252 0.776
+key = 0.25387 0.773
+key = 0.24531 0.765
+key = 0.23682 0.759
+key = 0.22841 0.751
+key = 0.2201 0.743
+key = 0.21185 0.737
+key = 0.20376 0.724
+key = 0.19575 0.715
+key = 0.18781 0.71
+key = 0.18005 0.694
+key = 0.17241 0.683
+key = 0.16493 0.669
+key = 0.1575 0.663
+key = 0.15011 0.661
+key = 0.14278 0.655
+key = 0.13548 0.652
+key = 0.12824 0.647
+key = 0.12115 0.633
+key = 0.11416 0.625
+key = 0.10726 0.617
+key = 0.10045 0.609
+key = 0.0937 0.603
+key = 0.08704 0.595
+key = 0.08051 0.584
+key = 0.07406 0.576
+key = 0.06771 0.568
+key = 0.06155 0.551
+key = 0.05556 0.535
+key = 0.0497 0.524
+key = 0.04387 0.521
+key = 0.03804 0.521
+key = 0.03231 0.513
+key = 0.0269 0.483
+key = 0.02193 0.444
+key = 0.01751 0.395
+key = 0.0138 0.332
+key = 0.01085 0.264
+key = 0.00863 0.198
+key = 0.00682 0.162
+key = 0.00528 0.138
+key = 0.00396 0.118
+key = 0.00294 0.091
+key = 0.0022 0.066
+key = 0.00164 0.05
+key = 0.00126 0.033
+key = 0.00098 0.025
+key = 0.00073 0.023
+key = 0.00051 0.02
+key = 0.00041 0.009
+key = 0.0 0.005

src/KSP-tools/engine_auto_price.py

@@ -0,0 +1,134 @@
+import pandas as pd
+import numpy as np
+import copy
+import time
+import json
+
+
+class Queue:
+    def __init__(self, length):
+        self.queue = []
+        self.length = length
+
+    def in_queue(self, item):
+        self.queue.append(item)
+        if len(self.queue) > self.length:
+            self.queue.pop(0)
+
+    def content(self):
+        return self.queue
+
+
+def cal_price(engine, factor_dict):
+    result = 0
+    for key, value in factor_dict.items():
+        x = value * engine[key]
+        result += x if str(x) != 'nan' else 0
+    return result
+
+
+def generate_full_config(single_config, full_config_list):
+    new_dimension = list(np.arange(single_config[0], single_config[1], single_config[2]).round(4))
+    if not full_config_list:
+        return [[item] for item in new_dimension]
+    new_full_config_list = []
+    for og_list in full_config_list:
+        for item in new_dimension:
+            new_full_config_list.append(copy.deepcopy(og_list + [item]))
+    return new_full_config_list
+
+
+def generate_full_config_dict_list(single_config, full_config_list, key):
+    new_dimension = list(np.arange(single_config[0], single_config[1], single_config[2]).round(4))
+    if not full_config_list:
+        return [{key: float(val)} for val in new_dimension]
+    new_full_config_list = []
+    for og_dict in full_config_list:
+        for item in new_dimension:
+            new_dict = copy.deepcopy(og_dict)
+            new_dict[key] = float(item)
+            new_full_config_list.append(new_dict)
+    return new_full_config_list
+
+
+def calculate_config_factor(local_config_dict, target_list):
+    gen_config_start_time = time.time()
+    full_config = []
+    for key, content in local_config_dict.items():
+        # full_config = generate_full_config(content, full_config)
+        full_config = generate_full_config_dict_list(content, full_config, key)
+    with open('data/full_config.txt', 'w', encoding='utf-8') as file:
+        file.write(json.dumps(full_config))
+    # file = open('data/full_config.txt', 'r', encoding='utf-8')
+    # full_config = json.loads(file.read())
+    print('Config Time:', time.time() - gen_config_start_time)
+
+    calculation_start = time.time()
+    min_div = 999999999999999999999
+    best_config = None
+    best_config_queue = Queue(10)
+    for config in full_config:
+        div = 0
+        for engine in target_list:
+            if engine['SL-ISP'] >= 200:
+                # auto_price = (engine['SL-ISP'] / 260) * (engine["Vac-ISP"] / 290) * engine['TWR'] * engine['Max Thrust'] * (1 - engine['Throttle Range']) * (1 + 0.01*engine['TVC']) / 4
+                auto_price = cal_price(engine, config)
+                price = engine['Price KD']
+                div += abs(auto_price - price)
+                # print(auto_price, price, auto_price - price, auto_price / price)
+                # if auto_price / price >= 2:
+                #     raise ValueError
+        if min_div > div:
+            min_div = div
+            best_config = config
+            best_config_queue.in_queue([min_div, config])
+    print('Calculation Time:', time.time() - calculation_start)
+    return best_config_queue
+
+
+def cal_single_div(target_list, config):
+    div = 0
+    for engine in target_list:
+        if engine['SL-ISP'] >= 200:
+            auto_price = cal_price(engine, config)
+            price = engine['Price KD']
+            div += abs(auto_price - price)
+    return div
+
+
+if __name__ == '__main__':
+    path = 'D://OneDrive//文档//KSP Engine Tweak Chart.xlsx'
+    excel_content = pd.read_excel(path, sheet_name='Engine Database')
+    full_list = []
+    for key, content in excel_content.iterrows():
+        if content['Fuel Type'] == 'Kerolox' and content['Cycle'] == 'Gas Generator':
+            full_list.append(dict(content))
+
+    tmp_config = {'Max Thrust': 1.7, 'SL-ISP': 0.2, 'TR Adjusted': 0.2, 'TVC Adjusted': 0.5, 'TWR': 0.5, 'Vac-ISP': 0.2}
+    div = cal_single_div(full_list, tmp_config)
+
+    config_dict = {
+        'SL-ISP': (0.01, 0.51, 0.05),
+        'Vac-ISP': (0.01, 0.51, 0.05),
+        'TWR': (0.01, 1.01, 0.1),
+        'Max Thrust': (1.5, 2.0, 0.05),
+        'TR Adjusted': (0.01, 1.01, 0.1),
+        'TVC Adjusted': (0.01, 1.01, 0.1),
+    }
+
+    factor_result = calculate_config_factor(config_dict, full_list)
+
+    auto_dict = {'Max Thrust': 0.3, 'SL-ISP': 0.0012, 'TR Adjusted': 0.9, 'TVC Adjusted': 0.52, 'TWR': 0.5, 'Vac-ISP': 0.0013}
+    div = 0
+    for engine in full_list:
+        if engine['SL-ISP'] >= 200:
+            auto_price = cal_price(engine, auto_dict)
+            price = engine['Price KD']
+            print(auto_price, price, auto_price - price, auto_price / price)
+
+            # if auto_price / price >= 2:
+            #     raise ValueError
+    print('done')
+
+
+

src/My_Logger/logger.py

@@ -0,0 +1,62 @@
+import logging
+import datetime
+
+
+class Logger:
+    def __init__(self, level="DEBUG"):
+        # 创建日志器对象
+        self.logger = logging.getLogger(__name__)
+        self.logger.setLevel(level)
+        self.format = logging.Formatter(f'[%(filename)s: %(funcName)s:%(lineno)4d][%(asctime)s][%(levelname)-.5s]: '
+                                        f'%(message)s',
+                                        datefmt='%Y-%m-%d %H:%M:%S')
+
+    def console_handler(self, level="DEBUG"):
+        # 创建控制台的日志处理器
+        console_handler = logging.StreamHandler()
+        console_handler.setLevel(level)
+
+        # 处理器添加输出格式
+        console_handler.setFormatter(self.format)
+
+        # 返回控制器
+        return console_handler
+
+    def file_handler(self, level="DEBUG"):
+        # 创建文件的日志处理器
+        file_handler = logging.FileHandler(f"../logs/log.txt", mode="a", encoding="utf-8")
+        file_handler.setLevel(level)
+
+        # 处理器添加输出格式
+        file_handler.setFormatter(self.format)
+
+        # 返回控制器
+        return file_handler
+
+    def get_log(self):
+        # 日志器中添加控制台处理器
+        self.logger.addHandler(self.console_handler())
+        # 日志器中添加文件处理器
+        self.logger.addHandler(self.file_handler())
+
+        # 返回日志实例对象
+        return self.logger
+
+
+if __name__ == '__main__':
+    print('111')
+
+    # class TestLog():
+    #     def __init__(self):
+    #         log = My_Logger()
+    #         self.logger = log.get_log()
+    #
+    #     def test_baili_01(self):
+    #         self.logger.info("开始执行")
+    #         self.logger.warning("结束执行")
+    #
+    #
+    # # 实例化
+    # test = TestLog()
+    # # 调用类中的方法
+    # test.test_baili_01()

src/PostgresSQL/databaseHandler.py

@@ -0,0 +1,77 @@
+import psycopg2
+from src.My_Logger.logger import Logger
+
+
+class DatabaseHandler:
+    def __init__(self, config, logger=None):
+        if not logger:
+            log = Logger()
+            self.logger = log.get_log()
+        self.config = config
+        # {database="postgres", user="postgres", password="123456", host="localhost", port="5432"}
+        self.connection = psycopg2.connect(database=config['database'], user=config['user'],
+                                           password=config['password'], host=config['host'], port=config['port'])
+        self.cursor = self.connection.cursor()
+        self.cursor.execute(f"select tablename from pg_tables where schemaname='public'")
+        self.table_list = [item[0] for item in self.cursor.fetchall()]
+
+    def create_table(self, table_structure, table_name, force_create=False):
+        table_name = table_name.lower()
+        if force_create and self.exists_table(table_name):
+            self.drop_table(table_name)
+        sql = f'Create Table {table_name}('
+        content_list = []
+        for key, values in table_structure.items():
+            content_list.append(f'{key.replace(" ", "_").replace("-", "_")}           {values}')
+        sql += ',\n'.join(content_list)
+        sql += ');'
+        self.connection.cursor().execute(sql)
+        self.connection.commit()
+
+    def exists_table(self, table_name):
+        table_name = table_name.lower()
+        if table_name in self.table_list:
+            return True
+        else:
+            return False
+
+    def drop_table(self, table_name, info_flag=False):
+        table_name = table_name.lower()
+        if not self.exists_table(table_name):
+            if info_flag:
+                self.logger.error(f'table: {table_name} not exists in database.')
+            return
+        self.cursor.execute(f'drop table {table_name}')
+        self.connection.commit()
+        if info_flag:
+            self.logger.info(f'table: {table_name} dropped')
+        return
+
+    def insert_into_table(self, table_name, data_dict_list, batch=1000):
+        """
+
+        :param batch:
+        :param table_name:
+        :param data_dict_list:
+        :return:
+        """
+        table_name = table_name.lower()
+        if not self.exists_table(table_name):
+            self.logger.error(f'table: {table_name} not exists in database.')
+            return
+
+        table_structure = data_dict_list[0]
+        content_list = []
+        for key, values in table_structure.items():
+            content_list.append(f'{key.replace(" ", "_").replace("-", "_")}'.lower())
+
+        sql = f"INSERT INTO {table_name}({','.join(content_list)}) VALUES({','.join(['%s'] * len(content_list))})"
+        target = [list(item.values()) for item in data_dict_list]
+
+        for i in range(0, len(target), batch):
+            self.cursor.executemany(sql, target[i: i+batch])
+            self.connection.commit()
+            self.logger.info(f'Inserted into table {table_name}, rows: {min(i+batch, len(target))}/{len(target)}')
+
+    def close(self):
+        self.connection.close()