CoCalc -- get_account

GitHub Repository: wiseplat/python-code
Path: blob/master/ invest-robot-contest_trading_bot-master/trading/get_account_info.py
⁵⁹³² views
1
from tinkoff.invest import Client, Quotation
2
from trading.trade_help import quotation_to_float
3
import pandas as pd
4
from config.personal_data import get_token, get_account_type, get_account
5
import sqlite3 as sl
6
import dataframe_image as dfi
7
from trading.trade_help import get_exchange_rate, get_currency_sing
8
from trading.get_securities import security_name_by_figi
9

10
'''
11

12
    Тут представлены все функции, которые позволяют получить какую-либо информацию о счёте
13
    
14
    Все данные будут храниться в pandas DataFrame для дальнейшей обработки
15
    
16
    Все значения, где количество или суммы представлены с помощью units (целая часть) и nano (дробная часть),
17
        сразу переводятся в дробные числа для удобства с помощью функции total_quantity.
18
    
19
'''
20

21
'''
22
    Функция для получения информации о свободной валюте на счёте
23
'''
24

25

26
def get_all_currency(user_id, account_id="", account_type=""):
27
    with Client(get_token(user_id)) as client:
28

29
        if account_id == "":
30
            account_id = get_account(user_id=user_id)
31

32
        if account_type == "":
33
            account_type = get_account_type(user_id=user_id)
34

35
        if account_type == "sandbox":
36
            positions = client.sandbox.get_sandbox_positions(account_id=account_id)
37
        else:
38
            positions = client.operations.get_positions(account_id=account_id)
39

40
        currency_df = pd.DataFrame(
41
            {
42
                "currency": i.currency,
43
                "name": get_currency_name(user_id=user_id, currency=i.currency),
44
                "sign": get_currency_sing(currency=i.currency),
45
                "exchange_rate": get_exchange_rate(currency=i.currency),
46
                "sum": quotation_to_float(Quotation(units=i.units, nano=i.nano)),
47
                "sum_in_ruble": quotation_to_float(Quotation(units=i.units, nano=i.nano)) * get_exchange_rate(
48
                    currency=i.currency),
49
                "units": i.units,
50
                "nano": i.nano,
51
            } for i in positions.money
52
        )
53

54
    return currency_df
55

56

57
'''
58
    Функция для получения названия валюты
59
    Необходима для вывода информации по доступной валюте, так Тинькофф предоставляет только 
60
'''
61

62

63
def get_currency_name(user_id, currency):
64
    with Client(get_token(user_id)) as client:
65
        pos = client.instruments.currencies()
66

67
        for i in pos.instruments:
68
            if i.nominal.currency == currency:
69
                return i.name
70

71
    return ""
72

73

74
'''
75
    Функция для получения информации о всех купленных бумагах
76
'''
77

78

79
def get_all_securities(user_id, account_id="", account_type=""):
80
    with Client(get_token(user_id)) as client:
81

82
        if account_id == "":
83
            account_id = get_account(user_id=user_id)
84

85
        if account_type == "":
86
            account_type = get_account_type(user_id=user_id)
87

88
        if account_type == "sandbox":
89
            portfolio = client.sandbox.get_sandbox_portfolio(account_id=account_id)
90
        else:
91
            portfolio = client.operations.get_portfolio(account_id=account_id)
92

93
        portfolio_df = pd.DataFrame(
94
            {
95
                "figi": i.figi,
96
                "instrument": i.instrument_type,
97
                "security_name": security_name_by_figi(figi=i.figi,user_id=user_id),
98
                "quantity": quotation_to_float(i.quantity),
99
                "average_price": quotation_to_float(i.average_position_price),
100
                "exp_yield": quotation_to_float(i.expected_yield),
101
                "nkd": quotation_to_float(i.current_nkd),
102
                "average_price_pt": quotation_to_float(i.average_position_price_pt),
103
                "current_price": quotation_to_float(i.current_price),
104
                "average_price_fifo": quotation_to_float(i.average_position_price_fifo),
105
                "lots": quotation_to_float(i.quantity_lots),
106
                "currency": i.average_position_price.currency,
107
                "currency_sign": get_currency_sing(i.average_position_price.currency)
108
            } for i in portfolio.positions
109
        )
110

111
    return portfolio_df
112

113

114
'''
115
    Функция для получения статистики по счёту
116
    Суммы по всем активам и предполагаемый доход/убыток
117
'''
118

119

120
def get_all_stat(user_id, account_id="", account_type=""):
121
    with Client(get_token(user_id)) as client:
122

123
        if account_id == "":
124
            account_id = get_account(user_id=user_id)
125

126
        if account_type == "":
127
            account_type = get_account_type(user_id=user_id)
128

129
        if account_type == "sandbox":
130
            portfolio = client.sandbox.get_sandbox_portfolio(account_id=account_id)
131
        else:
132
            portfolio = client.operations.get_portfolio(account_id=account_id)
133

134
        stat_df = pd.DataFrame(
135
            {
136
                "sum_shares": quotation_to_float(portfolio.total_amount_shares),
137
                "sum_bonds": quotation_to_float(portfolio.total_amount_bonds),
138
                "sum_etf": quotation_to_float(portfolio.total_amount_etf),
139
                "sum_curr": quotation_to_float(portfolio.total_amount_currencies),
140
                "sum_fut": quotation_to_float(portfolio.total_amount_futures),
141
                "sum_total": quotation_to_float(portfolio.total_amount_shares) + quotation_to_float(
142
                    portfolio.total_amount_bonds) + quotation_to_float(portfolio.total_amount_etf) + quotation_to_float(
143
                    portfolio.total_amount_currencies) + quotation_to_float(portfolio.total_amount_futures),
144
                "exp_yield": quotation_to_float(portfolio.expected_yield),
145

146
            }, index=[0]
147
        )
148

149
    return stat_df
150

151

152
'''
153
    Функция для получения информации о количестве доступных лотов по figi
154
    
155
    Данная функция используется для проверки в боте, можно ли продать указанное количество акций
156
'''
157

158

159
def get_lots_portfolio(figi, user_id, account_id="", account_type=""):
160
    with Client(get_token(user_id)) as client:
161

162
        if account_id == "":
163
            account_id = get_account(user_id=user_id)
164

165
        if account_type == "":
166
            account_type = get_account_type(user_id=user_id)
167

168
        if account_type == "sandbox":
169
            portfolio = client.sandbox.get_sandbox_portfolio(account_id=account_id)
170
        else:
171
            portfolio = client.operations.get_portfolio(account_id=account_id)
172

173
        for i in portfolio.positions:
174
            if i.figi == figi:
175
                lots = int(quotation_to_float(i.quantity_lots))
176
                return int(lots)
177

178
    return 0
179

180

181
'''
182
    Функция для получения информации о цене бумаги в портфеле
183
'''
184

185

186
def get_price_in_portfolio(figi, user_id, account_id="", account_type=""):
187
    with Client(get_token(user_id)) as client:
188

189
        if account_id == "":
190
            account_id = get_account(user_id=user_id)
191

192
        if account_type == "":
193
            account_type = get_account_type(user_id=user_id)
194

195
        if account_type == "sandbox":
196
            portfolio = client.sandbox.get_sandbox_portfolio(account_id=account_id)
197
        else:
198
            portfolio = client.operations.get_portfolio(account_id=account_id)
199

200
        for i in portfolio.positions:
201
            if i.figi == figi:
202
                price = quotation_to_float(i.current_price)
203
                if price == 0.0:
204
                    price = quotation_to_float(i.average_position_price)
205
                return price
206

207
    return 0.0
208

209

210
'''
211
    Функция для получения списка открытых ордеров
212
'''
213

214

215
def get_my_order(user_id, account_id="", account_type=""):
216
    with Client(get_token(user_id)) as client:
217

218
        if account_id == "":
219
            account_id = get_account(user_id=user_id)
220

221
        if account_type == "":
222
            account_type = get_account_type(user_id=user_id)
223

224
        if account_type == "sandbox":
225
            orders = client.sandbox.get_sandbox_orders(account_id=account_id).orders
226
        else:
227
            orders = client.orders.get_orders(account_id=account_id).orders
228

229
        order_df = pd.DataFrame(
230
            {
231
                "order_id": i.order_id,
232
                "lots_req": i.lots_requested,
233
                "lots_ex": i.lots_executed,
234
                "sum_req": quotation_to_float(i.initial_order_price),
235
                "sum_ex": quotation_to_float(i.executed_order_price),
236
                "sum_total": quotation_to_float(i.total_order_amount),  # сумма после всех комиссий
237
                "commission": quotation_to_float(i.initial_commission),
238
                "serv_commission": quotation_to_float(i.service_commission),
239
                "currency": i.currency,
240
                "currency_sign": get_currency_sing(i.currency),
241
                "figi": i.figi,
242
                "direction": i.direction,
243
                "price_one": quotation_to_float(i.initial_security_price),
244
                "order_date": i.order_date,
245
            } for i in orders
246
        )
247

248
    return order_df
249

250

251
'''
252
    Функция для получения списка всех операций пользователя
253
'''
254

255

256
def get_my_operations(user_id, account_id="", figi=""):
257
    connection = sl.connect("db/BotDB.db")
258
    cursor = connection.cursor()
259

260
    if account_id == "":
261
        account_id = get_account(user_id=user_id)
262

263
    if figi == "":
264
        operations = cursor.execute(
265
            'SELECT id, user_id, account_id, account_type, order_id, date_op, time_op, direction, figi, name, ticker, '
266
            'quantity_lots, in_lot, quantity_total, price_position, price_total, commission, currency, message, '
267
            'via FROM operations WHERE user_id = ? AND account_id = ?',
268
            (user_id, account_id)).fetchall()
269
    else:
270
        operations = cursor.execute(
271
            'SELECT id, user_id, account_id, account_type, order_id, date_op, time_op, direction, figi, name, ticker, '
272
            'quantity_lots, in_lot, quantity_total, price_position, price_total, commission, currency, message, '
273
            'via FROM operations WHERE user_id = ? AND account_id = ? AND figi = ?',
274
            (user_id, account_id, figi)).fetchall()
275

276
    if not operations:
277
        return False
278

279
    operations_df = pd.DataFrame(
280
        {
281
            "id": line[0],
282
            "user_id": user_id,
283
            "account_id": account_id,
284
            "account_type": line[3],
285
            "order_id": line[4],
286
            "date": line[5],
287
            "time": line[6],
288
            "direction": line[7],
289
            "figi": line[8],
290
            "name": line[9],
291
            "ticker": line[10],
292
            "quantity_lots": line[11],
293
            "in_lot": line[12],
294
            "quantity_total": line[13],
295
            "price_position": line[14],
296
            "price_total": line[15],
297
            "commission": line[16],
298
            "currency": line[17],
299
            "message": line[18],
300
            "via": line[19]
301
        } for line in operations
302
    )
303

304
    style_df = operations_df.drop(['id', 'user_id', 'order_id', 'figi', 'ticker'], axis=1)
305
    # style_df = style_df.style.apply(color_macd)
306

307
    dfi.export(style_df, f"img/operations/all_operations_{user_id}.png")
308

309
    return True
310

311
Product

Resources

Company
