(20241224) MCX data test.

models/finstitutions/trading/ticks.py

@@ -40,6 +40,7 @@ from pydantic import BaseModel, Field, field_validator, PastDatetime, model_vali
 from typing import Optional, Literal, Union, List
 
 # My utils:
+from utils_v2.string import json
 from utils_v2.string import regex
 from utils_v2.date_time import date_time
 
@@ -78,20 +79,24 @@ class OneMarketDepth(BaseModel):
 
     price: float = Field(
         description = "a price at which trader(s) are willing to trade this instrument",
-        frozen = True
+        frozen = True,
+        alias = "price"
     )
 
     qty: int = Field(
         description = "the no. of shares available at the above price",
-        frozen = True
+        frozen = True,
+        alias = "quantity"
     )
 
     orders: int = Field(
-        description = "how many orders have contributed to the above quantity"
+        description = "how many orders have contributed to the above quantity",
+        frozen = True,
+        alias = "orders"
     )
 
     @computed_field
-    def liquidity(self) -> float:
+    def lqdty(self) -> float:
         return self.price * self.qty
 
     # ┏┓    ┏•
@@ -194,6 +199,10 @@ class TradingTick(BaseModel):
         frozen = True
     )
 
+    qty: int = Field(
+        description = "how many units were traded in this tick"
+    )
+
     chg: float = Field(
         description = "the absolute change since the previous close",
         frozen=True
@@ -255,13 +264,12 @@ class TradingTick(BaseModel):
     )
 
     oiDayLow: int | None = Field(
-        description="this session's lowest open interest of this instrument (if derivative)",
-        frozen=True
+        description = "this session's lowest open interest of this instrument (if derivative)",
+        frozen = True
     )
 
-    tradeTs: AwareDatetime | None = Field(
+    tradeTs: AwareDatetime = Field(
         description = "the last trade time (utc) of this instrument",
-        default = None,
         frozen = True
     )
 
@@ -271,9 +279,8 @@ class TradingTick(BaseModel):
         examples = ["UTC", "Asia/Kolkata"]
     )
 
-    exchgTs: AwareDatetime | None = Field(
+    exchgTs: AwareDatetime = Field(
         description = "the time (utc) at which this update was received from the exchange",
-        default = None,
         frozen = True
     )
 
@@ -287,6 +294,19 @@ class TradingTick(BaseModel):
         description = "the market depth data for this instrument at the time of this update"
     )
 
+    # ┏┓       ┏┓             ┓  ┏┓•  ┓ ┓
+    # ┣┫┓┏╋┏┓━━┃ ┏┓┏┳┓┏┓┓┏╋┏┓┏┫  ┣ ┓┏┓┃┏┫┏
+    # ┛┗┗┻┗┗┛  ┗┛┗┛┛┗┗┣┛┗┻┗┗ ┗┻  ┻ ┗┗ ┗┗┻┛
+    #                 ┛
+
+    @computed_field
+    def tickCashflow(self) -> float:
+        return self.qty * self.ltp
+
+    @computed_field
+    def totCashflow(self) -> float:
+        return self.totVol * self.vwap
+
     # ┏┓    ┏•
     # ┃ ┏┓┏┓╋┓┏┓
     # ┗┛┗┛┛┗┛┗┗┫
@@ -302,7 +322,7 @@ class TradingTick(BaseModel):
     @staticmethod
     def from_zerodha_kite(
             ticks: dict | List[dict],
-            lookup: dict
+            instrument_lookup: dict
     ) -> list:
 
         # Ensure that we are working with a list:
@@ -311,9 +331,14 @@ class TradingTick(BaseModel):
         # Iterate through the ticks and fit them into the model:
         modelled_ticks = []
         for tick in ticks:
+
+            # Stash frequently needed vars:
             broker_token = tick["instrument_token"]
-            tick_lookup = lookup[broker_token]
+            tick_lookup = instrument_lookup[broker_token]
             change = tick["change"]
+            last_price = tick["last_price"]
+
+            # Model the currently picked tick:
             modelled_ticks.append(
                 TradingTick(
                     symbol = tick_lookup["symbol"],
@@ -321,14 +346,32 @@ class TradingTick(BaseModel):
                     exchangeToken = tick_lookup["exchangeToken"],
                     broker = "zerodhaKite",
                     brokerToken = broker_token,
-                    tradeable = tick["tradeable"],
+                    tradeable = tick["tradable"],
                     segment = tick_lookup["segment"],
                     type = tick_lookup["type"],
+                    strike = tick_lookup.get("strike"),
                     expiryTs = tick_lookup["expiryTs"],
                     expiryTz = tick_lookup["expiryTz"],
-                    ltp = ,
+                    ltp = last_price,
+                    qty = tick["last_traded_quantity"],
                     chg = change,
-                    pChg =
+                    pChg = change / (last_price - change),
+                    o = tick["ohlc"]["open"],
+                    h = tick["ohlc"]["high"],
+                    l = tick["ohlc"]["low"],
+                    c = tick["ohlc"]["close"],
+                    totVol = tick["volume_traded"],
+                    vwap = tick["average_traded_price"],
+                    totBuyQty = tick["total_buy_quantity"],
+                    totSellQty = tick["total_sell_quantity"],
+                    oi = tick["oi"],
+                    oiDayHigh = tick["oi_day_high"],
+                    oiDayLow = tick["oi_day_low"],
+                    tradeTs = tick["last_trade_time"],
+                    tradeTz = "Asia/Kolkata",
+                    exchgTs = tick["exchange_timestamp"],
+                    exchgTz = "Asia/Kolkata",
+                    depth = tick["depth"]
                 )
             )
 
@@ -355,7 +398,11 @@ class TradingTick(BaseModel):
             value = value.strip()
             value = date_time.parse_date_time(
                 input_value = value,
-                timezone = date_time.TIMEZONE_UTC
+                timezone = date_time.TIMEZONE_UTC,
+                date_formats = [
+                    "%Y-%m-%d",
+                    "%Y-%m-%d %H:%M:%S",
+                ]
             )
 
         # When the input is a datetime obj.,
@@ -464,13 +511,15 @@ if __name__ == "__main__":
             "exchange": "NSE",
             "exchangeToken": 12345678,
             "segment": "NFO-OPT",
-            "type": "CE"
+            "type": "CE",
+            "expiryTs": "2024-12-20",
+            "expiryTz": "Asia/Kolkata"
         }
     }
 
     my_ticks = TradingTick.from_zerodha_kite(
-        ticks = zerodha_tick,
+        ticks = [zerodha_tick] * 10_000,
         instrument_lookup = zerodha_lookup
     )
 
-    print(my_ticks[0])
+    print(json.to_string(my_ticks[0].model_dump(), default = str))