Squashed 'utils_v2/' content from commit 8bb584e4
git-subtree-dir: utils_v2 git-subtree-split: 8bb584e4734606740c0b42d51bc7fd458c39031a
This commit is contained in:
@@ -0,0 +1,132 @@
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"""
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AUTHOR:
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Khushal P Soonderji
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DATE:
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Wednesday, 30th Oct., 2024.
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OBJECTIVE:
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To provide a data model for describing the API response from Google's APIs.
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REFERENCES:
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N/A
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DOWNLOADS:
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||||
|
||||
N/A
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||||
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"""
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# *****************************************************************************************************************
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# ***** ****
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# *** IMPORT ***
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# ***** ****
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# *****************************************************************************************************************
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|
||||
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# To make sibling directories accessible for imports:
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import sys
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sys.path.append(".")
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sys.path.append("..")
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# For making data behaviour_models:
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from pydantic import BaseModel, Field, field_validator, model_validator
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from typing import Optional, Literal, Union, Dict, List, Any
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# My utils:
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from utils_v2.string import json
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from utils_v2.string import regex
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# *****************************************************************************************************************
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# ***** ****
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||||
# *** MACROS / ONE-TIME INIT ***
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# ***** ****
|
||||
# *****************************************************************************************************************
|
||||
|
||||
|
||||
# --- Nothing Yet
|
||||
|
||||
|
||||
# *****************************************************************************************************************
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||||
# ***** ****
|
||||
# *** VARIABLES ***
|
||||
# ***** ****
|
||||
# *****************************************************************************************************************
|
||||
|
||||
|
||||
# --- Nothing Yet
|
||||
|
||||
|
||||
# *****************************************************************************************************************
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# ***** ****
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# *** FUNCTIONS ***
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# ***** ****
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# *****************************************************************************************************************
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class NSEApiResponse(BaseModel):
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action: str = Field(frozen = False, default = None)
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url: str | None = Field(frozen = True)
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method: str | None = Field(frozen = True)
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inputs: Any | None = Field(frozen = True)
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response: Any = None
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httpCode: int = None
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success: bool = False
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message: str = None
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data: Any = None
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exception: Any = None
|
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|
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# ┏┓ ┏•
|
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# ┃ ┏┓┏┓╋┓┏┓
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# ┗┛┗┛┛┗┛┗┗┫
|
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# ┛
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class Config:
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extra = "forbid"
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# ┏┓ ┏┓
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# ┃ ┓┏┏╋┏┓┏┳┓ ┣ ┓┏┏┓┏┏
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# ┗┛┗┻┛┗┗┛┛┗┗ ┻ ┗┻┛┗┗┛
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def to_markdown(self):
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if self.exception: message = "❌ *NSE API EXCEPTION:* ❌\n\n"
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else: message = "*NSE API RESPONSE:*\n\n"
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message += f"*ACTION:*\n`{self.action}`\n\n"
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message += f"*URL:*\n`{self.url}`\n\n"
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message += f"*METHOD:*\n`{self.method}`\n\n"
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message += f"*RESPONSE:*\n`{self.response}`\n\n"
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message += f"*SUCCESS:*\n`{self.success}`\n\n"
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message += f"*MESSAGE:*\n`{self.message}`\n\n"
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message += f"*EXCEPTION:*\n`{self.exception.__class__.__name__}: {str(self.exception)}`\n\n"
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return message
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async def get_json(self):
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try: return self.response.json()
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except: return {}
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async def get_content(self):
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try: return self.response.content
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except: return b""
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|
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# *****************************************************************************************************************
|
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# ***** ****
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# *** MAIN PROGRAM ***
|
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# ***** ****
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# *****************************************************************************************************************
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|
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if __name__ == "__main__":
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pass
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@@ -0,0 +1,396 @@
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"""
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AUTHOR:
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Khushal P Soonderji
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DATE:
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Thursday, 9th Jan., 2025.
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OBJECTIVE:
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To provide data models for NSE's calendar events.
|
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|
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REFERENCES:
|
||||
|
||||
N/A
|
||||
|
||||
DOWNLOADS:
|
||||
|
||||
N/A
|
||||
|
||||
"""
|
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|
||||
|
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# *****************************************************************************************************************
|
||||
# ***** ****
|
||||
# *** IMPORT ***
|
||||
# ***** ****
|
||||
# *****************************************************************************************************************
|
||||
|
||||
|
||||
# To make sibling directories accessible for imports:
|
||||
import sys
|
||||
sys.path.append(".")
|
||||
sys.path.append("..")
|
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|
||||
# For making data behaviour_models:
|
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from pydantic import BaseModel, Field, field_validator, AwareDatetime, computed_field
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from typing import Optional, Literal, List
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# My utils:
|
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from utils_v2.string import regex
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from utils_v2.date_time import date_time
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# To work with date and time:
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import datetime
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|
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# *****************************************************************************************************************
|
||||
# ***** ****
|
||||
# *** MACROS / ONE-TIME INIT ***
|
||||
# ***** ****
|
||||
# *****************************************************************************************************************
|
||||
|
||||
|
||||
# --- Nothing Yet
|
||||
|
||||
|
||||
# *****************************************************************************************************************
|
||||
# ***** ****
|
||||
# *** VARIABLES ***
|
||||
# ***** ****
|
||||
# *****************************************************************************************************************
|
||||
|
||||
|
||||
# --- Nothing Yet
|
||||
|
||||
|
||||
# *****************************************************************************************************************
|
||||
# ***** ****
|
||||
# *** FUNCTIONS ***
|
||||
# ***** ****
|
||||
# *****************************************************************************************************************
|
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class NSEHoliday(BaseModel):
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scrapeTs: AwareDatetime = Field(
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description = "The time (UTC) at which this this data was scraped.",
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frozen = True,
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default_factory = lambda: date_time.get_current_utc_date_time(as_string = False)
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)
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ts: AwareDatetime = Field(
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description = "The date which is to be recorded as a holiday.",
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frozen = True
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)
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tz: str = Field(
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description = "The timezone in which the date has to be interpreted.",
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frozen = True,
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default = "Asia/Kolkata"
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)
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event: str = Field(
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description = "The name of the event/occasion.",
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frozen = True
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)
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type: List[str] = Field(
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description = "One or more types of holiday for this event.",
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frozen = True,
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examples = ["CBM", "CD", "CM", "CMOT", "COM", "FO", "IRD", "MF", "NDM", "NTRP", "SLBS"]
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)
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# ┏┓ ┏•
|
||||
# ┃ ┏┓┏┓╋┓┏┓
|
||||
# ┗┛┗┛┛┗┛┗┗┫
|
||||
# ┛
|
||||
|
||||
class Config:
|
||||
extra = "ignore"
|
||||
|
||||
# ┏┓ ┏┓ ┓ ┏┓• ┓ ┓
|
||||
# ┣┫┓┏╋┏┓━━┃ ┏┓┏┳┓┏┓┓┏╋┏┓┏┫ ┣ ┓┏┓┃┏┫┏
|
||||
# ┛┗┗┻┗┗┛ ┗┛┗┛┛┗┗┣┛┗┻┗┗ ┗┻ ┻ ┗┗ ┗┗┻┛
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# ┛
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||||
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@computed_field
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def year(self) -> int:
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return self.ts.year
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# ┓┏ ┓• ┓ •
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||||
# ┃┃┏┓┃┓┏┫┏┓╋┓┏┓┏┓┏
|
||||
# ┗┛┗┻┗┗┗┻┗┻┗┗┗┛┛┗┛
|
||||
|
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@field_validator("ts", "scrapeTs", mode = "before")
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def parse_date_time(cls, value):
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if isinstance(value, datetime.datetime):
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value = date_time.to_timezone(value, date_time.TIMEZONE_UTC)
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return value
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|
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# ┏┓ ┏┓
|
||||
# ┃ ┓┏┏╋┏┓┏┳┓ ┣ ┓┏┏┓┏┏
|
||||
# ┗┛┗┻┛┗┗┛┛┗┗ ┻ ┗┻┛┗┗┛
|
||||
|
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def to_json(self) -> dict:
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return {
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"event": self.event,
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"ts": self.ts.timestamp(),
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"tz": self.tz,
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"type": self.type
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}
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# ---------------------------------------------------------------------------------------------------------------------
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class NSECorporateEvent(BaseModel):
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scrapeTs: AwareDatetime = Field(
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description = "The time (UTC) at which this this data was scraped.",
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frozen = True,
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default_factory = lambda: date_time.get_current_utc_date_time(as_string = False)
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)
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kind: str | None = Field(
|
||||
description = "The type of 'index'.",
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frozen = True,
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default = None
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)
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symbol: str = Field(
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description = "The trading symbol of the listed entity.",
|
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frozen = True
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||||
)
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||||
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||||
name: str = Field(
|
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description = "The full name of the listed entity.",
|
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frozen = True
|
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)
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ts: AwareDatetime = Field(
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description = "The date (UTC) of the corporate event.",
|
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frozen = True
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)
|
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tz: str = Field(
|
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description = "The timezone in which the date has to be interpreted.",
|
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frozen = True,
|
||||
default = "Asia/Kolkata"
|
||||
)
|
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|
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purpose: str = Field(
|
||||
description = "The type of the event.",
|
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frozen = True
|
||||
)
|
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|
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description: str = Field(
|
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description = "A brief description of the event.",
|
||||
frozen = True
|
||||
)
|
||||
|
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attachment: str | None = Field(
|
||||
description = "Any file attachment with the event announcement.",
|
||||
frozen = True,
|
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default = None
|
||||
)
|
||||
|
||||
# ┏┓ ┏•
|
||||
# ┃ ┏┓┏┓╋┓┏┓
|
||||
# ┗┛┗┛┛┗┛┗┗┫
|
||||
# ┛
|
||||
|
||||
class Config:
|
||||
extra = "ignore"
|
||||
|
||||
# ┏┓ ┏┓ ┓ ┏┓• ┓ ┓
|
||||
# ┣┫┓┏╋┏┓━━┃ ┏┓┏┳┓┏┓┓┏╋┏┓┏┫ ┣ ┓┏┓┃┏┫┏
|
||||
# ┛┗┗┻┗┗┛ ┗┛┗┛┛┗┗┣┛┗┻┗┗ ┗┻ ┻ ┗┗ ┗┗┻┛
|
||||
# ┛
|
||||
|
||||
pass
|
||||
|
||||
# ┓┏ ┓• ┓ •
|
||||
# ┃┃┏┓┃┓┏┫┏┓╋┓┏┓┏┓┏
|
||||
# ┗┛┗┻┗┗┗┻┗┻┗┗┗┛┛┗┛
|
||||
|
||||
@field_validator("ts", "scrapeTs", mode = "before")
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def parse_date_time(cls, value):
|
||||
if isinstance(value, datetime.datetime):
|
||||
value = date_time.to_timezone(value, date_time.TIMEZONE_UTC)
|
||||
return value
|
||||
|
||||
# ┏┓ ┏┓
|
||||
# ┃ ┓┏┏╋┏┓┏┳┓ ┣ ┓┏┏┓┏┏
|
||||
# ┗┛┗┻┛┗┗┛┛┗┗ ┻ ┗┻┛┗┗┛
|
||||
|
||||
def to_json(self) -> dict:
|
||||
return {
|
||||
"symbol": self.symbol,
|
||||
"name": self.name,
|
||||
"kind": self.kind,
|
||||
"purpose": self.purpose,
|
||||
"description": self.description,
|
||||
"attachment": self.attachment,
|
||||
"ts": self.ts.timestamp(),
|
||||
"tz": self.tz
|
||||
}
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------------------------------------------------
|
||||
|
||||
|
||||
class NSECorporateAction(BaseModel):
|
||||
|
||||
scrapeTs: AwareDatetime = Field(
|
||||
description = "The time (UTC) at which this this data was scraped.",
|
||||
frozen = True,
|
||||
default_factory = lambda: date_time.get_current_utc_date_time(as_string = False)
|
||||
)
|
||||
|
||||
kind: str | None = Field(
|
||||
description = "The type of 'index'.",
|
||||
frozen = True,
|
||||
default = None
|
||||
)
|
||||
|
||||
symbol: str = Field(
|
||||
description = "The trading symbol of the listed entity.",
|
||||
frozen = True
|
||||
)
|
||||
|
||||
name: str = Field(
|
||||
description = "The full name of the listed entity.",
|
||||
frozen = True
|
||||
)
|
||||
|
||||
isin: str = Field(
|
||||
description = "The ISIN code of the listed entity.",
|
||||
frozen = True
|
||||
)
|
||||
|
||||
series: str = Field(
|
||||
description = "The series code of the listed entity.",
|
||||
frozen = True
|
||||
)
|
||||
|
||||
exTs: AwareDatetime | None = Field(
|
||||
description = "The ex-date/ex-dividend-date (UTC) ",
|
||||
frozen = True
|
||||
)
|
||||
|
||||
recTs: AwareDatetime | None = Field(
|
||||
description = "The record date (UTC).",
|
||||
frozen = True
|
||||
)
|
||||
|
||||
bcStartTs: AwareDatetime | None = Field(
|
||||
description = "The book-closure start date (UTC).",
|
||||
frozen = True
|
||||
)
|
||||
|
||||
bcEndTs: AwareDatetime | None = Field(
|
||||
description = "The book-closure end date (UTC).",
|
||||
frozen = True
|
||||
)
|
||||
|
||||
ndStartTs: AwareDatetime | None = Field(
|
||||
description = "The notice-date (start) date (UTC).",
|
||||
frozen = True
|
||||
)
|
||||
|
||||
ndEndTs: AwareDatetime | None = Field(
|
||||
description = "The notice-date (end) date (UTC).",
|
||||
frozen = True
|
||||
)
|
||||
|
||||
caBroadcastTs: AwareDatetime | None = Field(
|
||||
description = "The corporate-action broadcast date (UTC).",
|
||||
frozen = True
|
||||
)
|
||||
|
||||
tz: str = Field(
|
||||
description = "The timezone in which all dates have to be interpreted.",
|
||||
frozen = True,
|
||||
default = "Asia/Kolkata"
|
||||
)
|
||||
|
||||
action: str = Field(
|
||||
description = "The subject of the corporate action.",
|
||||
frozen = True
|
||||
)
|
||||
|
||||
faceVal: float | int = Field(
|
||||
description = "The face-value of the share of the entity.",
|
||||
frozen = True
|
||||
)
|
||||
|
||||
# ┏┓ ┏•
|
||||
# ┃ ┏┓┏┓╋┓┏┓
|
||||
# ┗┛┗┛┛┗┛┗┗┫
|
||||
# ┛
|
||||
|
||||
class Config:
|
||||
extra = "ignore"
|
||||
|
||||
# ┏┓ ┏┓ ┓ ┏┓• ┓ ┓
|
||||
# ┣┫┓┏╋┏┓━━┃ ┏┓┏┳┓┏┓┓┏╋┏┓┏┫ ┣ ┓┏┓┃┏┫┏
|
||||
# ┛┗┗┻┗┗┛ ┗┛┗┛┛┗┗┣┛┗┻┗┗ ┗┻ ┻ ┗┗ ┗┗┻┛
|
||||
# ┛
|
||||
|
||||
pass
|
||||
|
||||
# ┓┏ ┓• ┓ •
|
||||
# ┃┃┏┓┃┓┏┫┏┓╋┓┏┓┏┓┏
|
||||
# ┗┛┗┻┗┗┗┻┗┻┗┗┗┛┛┗┛
|
||||
|
||||
@field_validator(
|
||||
"scrapeTs",
|
||||
"exTs", "recTs",
|
||||
"bcStartTs", "bcEndTs",
|
||||
"ndStartTs", "ndEndTs",
|
||||
"caBroadcastTs",
|
||||
mode = "before"
|
||||
)
|
||||
def parse_date_time(cls, value):
|
||||
if isinstance(value, datetime.datetime):
|
||||
value = date_time.to_timezone(value, date_time.TIMEZONE_UTC)
|
||||
return value
|
||||
|
||||
# ┏┓ ┏┓
|
||||
# ┃ ┓┏┏╋┏┓┏┳┓ ┣ ┓┏┏┓┏┏
|
||||
# ┗┛┗┻┛┗┗┛┛┗┗ ┻ ┗┻┛┗┗┛
|
||||
|
||||
def to_json(self) -> dict:
|
||||
return {
|
||||
"symbol": self.symbol,
|
||||
"name": self.name,
|
||||
"isin": self.isin,
|
||||
"series": self.series,
|
||||
"kind": self.kind,
|
||||
"action": self.action,
|
||||
"faceVal": self.faceVal,
|
||||
"exTs": self.exTs.timestamp() if isinstance(self.exTs, datetime.datetime) else self.exTs,
|
||||
"recTs": self.recTs.timestamp()if isinstance(self.recTs, datetime.datetime) else self.recTs,
|
||||
"bcStartTs": self.bcStartTs.timestamp()if isinstance(self.bcStartTs, datetime.datetime) else self.bcStartTs,
|
||||
"bcEndTs": self.bcEndTs.timestamp()if isinstance(self.bcEndTs, datetime.datetime) else self.bcEndTs,
|
||||
"ndStartTs": self.ndStartTs.timestamp()if isinstance(self.ndStartTs, datetime.datetime) else self.ndStartTs,
|
||||
"ndEndTs": self.ndEndTs.timestamp()if isinstance(self.ndEndTs, datetime.datetime) else self.ndEndTs,
|
||||
"caBroadcastTs": self.caBroadcastTs.timestamp()if isinstance(self.caBroadcastTs, datetime.datetime) else self.caBroadcastTs,
|
||||
"tz": self.tz
|
||||
}
|
||||
|
||||
|
||||
# *****************************************************************************************************************
|
||||
# ***** ****
|
||||
# *** MAIN PROGRAM ***
|
||||
# ***** ****
|
||||
# *****************************************************************************************************************
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
|
||||
pass
|
||||
@@ -0,0 +1,319 @@
|
||||
"""
|
||||
|
||||
AUTHOR:
|
||||
|
||||
Khushal P Soonderji
|
||||
|
||||
DATE:
|
||||
|
||||
Tuesday, 14th Jan., 2025.
|
||||
|
||||
OBJECTIVE:
|
||||
|
||||
To provide data model(s) for NSE's index information.
|
||||
|
||||
REFERENCES:
|
||||
|
||||
N/A
|
||||
|
||||
DOWNLOADS:
|
||||
|
||||
N/A
|
||||
|
||||
"""
|
||||
|
||||
|
||||
# *****************************************************************************************************************
|
||||
# ***** ****
|
||||
# *** IMPORT ***
|
||||
# ***** ****
|
||||
# *****************************************************************************************************************
|
||||
|
||||
|
||||
# To make sibling directories accessible for imports:
|
||||
import sys
|
||||
sys.path.append(".")
|
||||
sys.path.append("..")
|
||||
|
||||
# For making data behaviour_models:
|
||||
from pydantic import BaseModel, Field, field_validator, AwareDatetime, computed_field
|
||||
from typing import Optional, Literal, List
|
||||
|
||||
# My utils:
|
||||
from utils_v2.string import regex
|
||||
from utils_v2.date_time import date_time
|
||||
|
||||
# To work with date and time:
|
||||
import datetime
|
||||
|
||||
|
||||
# *****************************************************************************************************************
|
||||
# ***** ****
|
||||
# *** MACROS / ONE-TIME INIT ***
|
||||
# ***** ****
|
||||
# *****************************************************************************************************************
|
||||
|
||||
|
||||
# --- Nothing Yet
|
||||
|
||||
|
||||
# *****************************************************************************************************************
|
||||
# ***** ****
|
||||
# *** VARIABLES ***
|
||||
# ***** ****
|
||||
# *****************************************************************************************************************
|
||||
|
||||
|
||||
# --- Nothing Yet
|
||||
|
||||
|
||||
# *****************************************************************************************************************
|
||||
# ***** ****
|
||||
# *** FUNCTIONS ***
|
||||
# ***** ****
|
||||
# *****************************************************************************************************************
|
||||
|
||||
|
||||
class NSEIndexInfo(BaseModel):
|
||||
|
||||
scrapeTs: AwareDatetime = Field(
|
||||
description = "The time (UTC) at which this this data was scraped.",
|
||||
frozen = True,
|
||||
default_factory = lambda: date_time.get_current_utc_date_time(as_string = False)
|
||||
)
|
||||
|
||||
tz: str = Field(
|
||||
description = "The timezone in which the dates have to be interpreted.",
|
||||
frozen = True,
|
||||
default = "Asia/Kolkata"
|
||||
)
|
||||
|
||||
symbol: str = Field(
|
||||
description = "The symbol of this index.",
|
||||
frozen = True
|
||||
)
|
||||
|
||||
name: str = Field(
|
||||
description = "The display name of this index.",
|
||||
frozen = True
|
||||
)
|
||||
|
||||
kind: str = Field(
|
||||
description = "The category/type of this index.",
|
||||
frozen = True
|
||||
)
|
||||
|
||||
open: float | None = Field(
|
||||
description = "The opening price of this index.",
|
||||
frozen = True
|
||||
)
|
||||
|
||||
high: float | None = Field(
|
||||
description = "The highest price of this index.",
|
||||
frozen = True
|
||||
)
|
||||
|
||||
low: float | None = Field(
|
||||
description = "The lowest price of this index.",
|
||||
frozen = True
|
||||
)
|
||||
|
||||
close: float | None = Field(
|
||||
description = "The LTP of this index.",
|
||||
frozen = True
|
||||
)
|
||||
|
||||
prevClose: float | None = Field(
|
||||
description = "The previous session's closing price of this index.",
|
||||
frozen = True
|
||||
)
|
||||
|
||||
yearHigh: float | None = Field(
|
||||
description = "The year-high value of this symbol.",
|
||||
frozen = True
|
||||
)
|
||||
|
||||
yearLow: float | None = Field(
|
||||
description = "The year-low value of this symbol.",
|
||||
frozen = True
|
||||
)
|
||||
|
||||
pChg: float | None = Field(
|
||||
description = "The percent change since the last trading session.",
|
||||
frozen = True
|
||||
)
|
||||
|
||||
advances: int | None = Field(
|
||||
description = "The no. of constituent symbols that are running positive.",
|
||||
frozen = True
|
||||
)
|
||||
|
||||
declines: int | None = Field(
|
||||
description = "The no. of constituent symbols that are running negative.",
|
||||
frozen = True
|
||||
)
|
||||
|
||||
unchanged: int | None = Field(
|
||||
description = "The no. of constituent symbols that are running flat.",
|
||||
frozen = True
|
||||
)
|
||||
|
||||
pChg30d: float | None = Field(
|
||||
description = "The percent change in the last month.",
|
||||
frozen = True
|
||||
)
|
||||
|
||||
pChg365d: float | None = Field(
|
||||
description = "The percent change in the last year.",
|
||||
frozen = True
|
||||
)
|
||||
|
||||
# ┏┓ ┏•
|
||||
# ┃ ┏┓┏┓╋┓┏┓
|
||||
# ┗┛┗┛┛┗┛┗┗┫
|
||||
# ┛
|
||||
|
||||
class Config:
|
||||
extra = "ignore"
|
||||
|
||||
# ┏┓ ┏┓ ┓ ┏┓• ┓ ┓
|
||||
# ┣┫┓┏╋┏┓━━┃ ┏┓┏┳┓┏┓┓┏╋┏┓┏┫ ┣ ┓┏┓┃┏┫┏
|
||||
# ┛┗┗┻┗┗┛ ┗┛┗┛┛┗┗┣┛┗┻┗┗ ┗┻ ┻ ┗┗ ┗┗┻┛
|
||||
# ┛
|
||||
|
||||
@computed_field()
|
||||
def chg(self) -> float:
|
||||
return self.close - self.prevClose
|
||||
|
||||
# ┓┏ ┓• ┓ •
|
||||
# ┃┃┏┓┃┓┏┫┏┓╋┓┏┓┏┓┏
|
||||
# ┗┛┗┻┗┗┗┻┗┻┗┗┗┛┛┗┛
|
||||
|
||||
@field_validator("scrapeTs", mode = "before")
|
||||
def parse_date_time(cls, value):
|
||||
if isinstance(value, datetime.datetime):
|
||||
value = date_time.to_timezone(value, date_time.TIMEZONE_UTC)
|
||||
return value
|
||||
|
||||
# ┏┓ ┏┓
|
||||
# ┃ ┓┏┏╋┏┓┏┳┓ ┣ ┓┏┏┓┏┏
|
||||
# ┗┛┗┻┛┗┗┛┛┗┗ ┻ ┗┻┛┗┗┛
|
||||
|
||||
def to_json(self) -> dict:
|
||||
model_json = self.model_dump()
|
||||
model_json["scrapeTs"] = model_json["scrapeTs"].timestamp()
|
||||
return model_json
|
||||
|
||||
|
||||
# # ---------------------------------------------------------------------------------------------------------------------
|
||||
#
|
||||
#
|
||||
# class NSEPreMarketData(BaseModel):
|
||||
#
|
||||
# scrapeTs: AwareDatetime = Field(
|
||||
# description = "The time (UTC) at which this this data was scraped.",
|
||||
# frozen = True,
|
||||
# default_factory = lambda: date_time.get_current_utc_date_time(as_string = False)
|
||||
# )
|
||||
#
|
||||
# ts: AwareDatetime = Field(
|
||||
# description = "The time (UTC) at which this data was made available by NSE.",
|
||||
# frozen = True
|
||||
# )
|
||||
#
|
||||
# tz: str = Field(
|
||||
# description = "The timezone in which the dates have to be interpreted.",
|
||||
# frozen = True,
|
||||
# default = "Asia/Kolkata"
|
||||
# )
|
||||
#
|
||||
# key: str | None = Field(
|
||||
# description = "The kind of list that was fetched.",
|
||||
# frozen = True,
|
||||
# default = None,
|
||||
# examples = ["NIFTY", "BANKNIFTY", "SME", "FO", "OTHERS", "ALL"]
|
||||
# )
|
||||
#
|
||||
# advances: int = Field(
|
||||
# description = "The no. of symbols that will be opening positive.",
|
||||
# frozen = True
|
||||
# )
|
||||
#
|
||||
# declines: int = Field(
|
||||
# description = "The no. of symbols that will be opening negative.",
|
||||
# frozen = True
|
||||
# )
|
||||
#
|
||||
# unchanged: int = Field(
|
||||
# description = "The no. of symbols that will be opening flat.",
|
||||
# frozen = True
|
||||
# )
|
||||
#
|
||||
# totalMarketCap: float | int | None = Field(
|
||||
# description = "The total market cap. of all of the listed symbols.",
|
||||
# frozen = True
|
||||
# )
|
||||
#
|
||||
# totalTradedValue: float | int | None = Field(
|
||||
# description = "The total value in Rupees that was traded in this pre-market session.",
|
||||
# frozen = True
|
||||
# )
|
||||
#
|
||||
# totalTradedVolume: int | None = Field(
|
||||
# description = "The total volume that was traded in the pre-market session.",
|
||||
# frozen = True
|
||||
# )
|
||||
#
|
||||
# symbols: List[NSEPreMarketSymbol] = Field(
|
||||
# description = "The actual symbol-wise data.",
|
||||
# frozen = True
|
||||
# )
|
||||
#
|
||||
# # ┏┓ ┏•
|
||||
# # ┃ ┏┓┏┓╋┓┏┓
|
||||
# # ┗┛┗┛┛┗┛┗┗┫
|
||||
# # ┛
|
||||
#
|
||||
# class Config:
|
||||
# extra = "ignore"
|
||||
#
|
||||
# # ┏┓ ┏┓ ┓ ┏┓• ┓ ┓
|
||||
# # ┣┫┓┏╋┏┓━━┃ ┏┓┏┳┓┏┓┓┏╋┏┓┏┫ ┣ ┓┏┓┃┏┫┏
|
||||
# # ┛┗┗┻┗┗┛ ┗┛┗┛┛┗┗┣┛┗┻┗┗ ┗┻ ┻ ┗┗ ┗┗┻┛
|
||||
# # ┛
|
||||
#
|
||||
# @computed_field()
|
||||
# def dateIst(self) -> str:
|
||||
# return date_time.to_timezone(self.ts, timezone = date_time.TIMEZONE_IST).strftime("%Y%m%d")
|
||||
#
|
||||
# # ┓┏ ┓• ┓ •
|
||||
# # ┃┃┏┓┃┓┏┫┏┓╋┓┏┓┏┓┏
|
||||
# # ┗┛┗┻┗┗┗┻┗┻┗┗┗┛┛┗┛
|
||||
#
|
||||
# @field_validator("scrapeTs", "ts", mode = "before")
|
||||
# def parse_date_time(cls, value):
|
||||
# if isinstance(value, datetime.datetime):
|
||||
# value = date_time.to_timezone(value, date_time.TIMEZONE_UTC)
|
||||
# return value
|
||||
#
|
||||
# # ┏┓ ┏┓
|
||||
# # ┃ ┓┏┏╋┏┓┏┳┓ ┣ ┓┏┏┓┏┏
|
||||
# # ┗┛┗┻┛┗┗┛┛┗┗ ┻ ┗┻┛┗┗┛
|
||||
#
|
||||
# def to_json(self) -> dict:
|
||||
# model_json = self.model_dump()
|
||||
# model_json["scrapeTs"] = model_json["scrapeTs"].timestamp()
|
||||
# for s in model_json["symbols"]: s["scrapeTs"].timestamp()
|
||||
# return model_json
|
||||
|
||||
|
||||
# *****************************************************************************************************************
|
||||
# ***** ****
|
||||
# *** MAIN PROGRAM ***
|
||||
# ***** ****
|
||||
# *****************************************************************************************************************
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
|
||||
pass
|
||||
@@ -0,0 +1,208 @@
|
||||
"""
|
||||
|
||||
AUTHOR:
|
||||
|
||||
Khushal P Soonderji
|
||||
|
||||
DATE:
|
||||
|
||||
Thursday, 9th Jan., 2025.
|
||||
|
||||
OBJECTIVE:
|
||||
|
||||
To provide data models for NSE's calendar events.
|
||||
|
||||
REFERENCES:
|
||||
|
||||
N/A
|
||||
|
||||
DOWNLOADS:
|
||||
|
||||
N/A
|
||||
|
||||
"""
|
||||
|
||||
|
||||
# *****************************************************************************************************************
|
||||
# ***** ****
|
||||
# *** IMPORT ***
|
||||
# ***** ****
|
||||
# *****************************************************************************************************************
|
||||
|
||||
|
||||
# To make sibling directories accessible for imports:
|
||||
import sys
|
||||
sys.path.append(".")
|
||||
sys.path.append("..")
|
||||
|
||||
# For making data behaviour_models:
|
||||
from pydantic import BaseModel, Field, field_validator, AwareDatetime, computed_field
|
||||
from typing import Optional, Literal, List
|
||||
|
||||
# My utils:
|
||||
from utils_v2.string import regex
|
||||
from utils_v2.date_time import date_time
|
||||
|
||||
# To work with date and time:
|
||||
import datetime
|
||||
|
||||
|
||||
# *****************************************************************************************************************
|
||||
# ***** ****
|
||||
# *** MACROS / ONE-TIME INIT ***
|
||||
# ***** ****
|
||||
# *****************************************************************************************************************
|
||||
|
||||
|
||||
# --- Nothing Yet
|
||||
|
||||
|
||||
# *****************************************************************************************************************
|
||||
# ***** ****
|
||||
# *** VARIABLES ***
|
||||
# ***** ****
|
||||
# *****************************************************************************************************************
|
||||
|
||||
|
||||
# --- Nothing Yet
|
||||
|
||||
|
||||
# *****************************************************************************************************************
|
||||
# ***** ****
|
||||
# *** FUNCTIONS ***
|
||||
# ***** ****
|
||||
# *****************************************************************************************************************
|
||||
|
||||
|
||||
class NSEIPO(BaseModel):
|
||||
|
||||
scrapeTs: AwareDatetime = Field(
|
||||
description = "The time (UTC) at which this this data was scraped.",
|
||||
frozen = True,
|
||||
default_factory = lambda: date_time.get_current_utc_date_time(as_string = False)
|
||||
)
|
||||
|
||||
issueStartTs: AwareDatetime = Field(
|
||||
description = "The start date (UTC) of the issue.",
|
||||
frozen = True
|
||||
)
|
||||
|
||||
issueEndTs: AwareDatetime = Field(
|
||||
description = "The end date (UTC) of the issue.",
|
||||
frozen = True
|
||||
)
|
||||
|
||||
listingTs: AwareDatetime | None = Field(
|
||||
description = "The date when the company was listed on the exchange.",
|
||||
frozen = True,
|
||||
default = None
|
||||
)
|
||||
|
||||
tz: str = Field(
|
||||
description = "The timezone in which the dates have to be interpreted.",
|
||||
frozen = True,
|
||||
default = "Asia/Kolkata"
|
||||
)
|
||||
|
||||
symbol: str = Field(
|
||||
description = "The trading symbol of this listing.",
|
||||
frozen = True
|
||||
)
|
||||
|
||||
name: str = Field(
|
||||
description = "The name of the parent company of this listing.",
|
||||
frozen = True
|
||||
)
|
||||
|
||||
status: Literal["Past", "Active", "Forthcoming"] | str = Field(
|
||||
description = "Whether this IPO is active or has closed.",
|
||||
frozen = True,
|
||||
default = "Past"
|
||||
)
|
||||
|
||||
kind: str | None = Field(
|
||||
description = "The category under which this IPO falls.",
|
||||
frozen = True,
|
||||
default = None,
|
||||
examples = ["SME", "EQ", "DEBT"]
|
||||
)
|
||||
|
||||
upperBand: float | None = Field(
|
||||
description = "The upper price of the price band.",
|
||||
frozen = True,
|
||||
default = None
|
||||
)
|
||||
|
||||
lowerBand: float | None = Field(
|
||||
description = "The lower price of the price band.",
|
||||
frozen = True,
|
||||
default = None
|
||||
)
|
||||
|
||||
issuePrice: float | None = Field(
|
||||
description = "The final price at which the shares were sold.",
|
||||
frozen = True,
|
||||
default = None
|
||||
)
|
||||
|
||||
offerQty: int | None = Field(
|
||||
description = "How many shares are being offered for sale by the parent.",
|
||||
frozen = True,
|
||||
default = None
|
||||
)
|
||||
|
||||
bidQty: int | None = Field(
|
||||
description = "How many shares investors are willing to buy.",
|
||||
frozen = True,
|
||||
default = None
|
||||
)
|
||||
|
||||
bidFactor: float | None = Field(
|
||||
description = "How many times over has the IPO been subscribed.",
|
||||
frozen = True,
|
||||
default = None
|
||||
)
|
||||
|
||||
# ┏┓ ┏•
|
||||
# ┃ ┏┓┏┓╋┓┏┓
|
||||
# ┗┛┗┛┛┗┛┗┗┫
|
||||
# ┛
|
||||
|
||||
class Config:
|
||||
extra = "ignore"
|
||||
|
||||
# ┏┓ ┏┓ ┓ ┏┓• ┓ ┓
|
||||
# ┣┫┓┏╋┏┓━━┃ ┏┓┏┳┓┏┓┓┏╋┏┓┏┫ ┣ ┓┏┓┃┏┫┏
|
||||
# ┛┗┗┻┗┗┛ ┗┛┗┛┛┗┗┣┛┗┻┗┗ ┗┻ ┻ ┗┗ ┗┗┻┛
|
||||
# ┛
|
||||
|
||||
pass
|
||||
|
||||
# ┓┏ ┓• ┓ •
|
||||
# ┃┃┏┓┃┓┏┫┏┓╋┓┏┓┏┓┏
|
||||
# ┗┛┗┻┗┗┗┻┗┻┗┗┗┛┛┗┛
|
||||
|
||||
@field_validator("scrapeTs", "issueStartTs", "issueEndTs", mode = "before")
|
||||
def parse_date_time(cls, value):
|
||||
if isinstance(value, datetime.datetime):
|
||||
value = date_time.to_timezone(value, date_time.TIMEZONE_UTC)
|
||||
return value
|
||||
|
||||
# ┏┓ ┏┓
|
||||
# ┃ ┓┏┏╋┏┓┏┳┓ ┣ ┓┏┏┓┏┏
|
||||
# ┗┛┗┻┛┗┗┛┛┗┗ ┻ ┗┻┛┗┗┛
|
||||
|
||||
def to_json(self) -> dict:
|
||||
return self.model_dump()
|
||||
|
||||
|
||||
# *****************************************************************************************************************
|
||||
# ***** ****
|
||||
# *** MAIN PROGRAM ***
|
||||
# ***** ****
|
||||
# *****************************************************************************************************************
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
|
||||
pass
|
||||
@@ -0,0 +1,300 @@
|
||||
"""
|
||||
|
||||
AUTHOR:
|
||||
|
||||
Khushal P Soonderji
|
||||
|
||||
DATE:
|
||||
|
||||
Monday, 13th Jan., 2025.
|
||||
|
||||
OBJECTIVE:
|
||||
|
||||
To provide data model(s) for NSE's pre-market data. This will be useful for catching gap-ups and gap-downs.
|
||||
|
||||
REFERENCES:
|
||||
|
||||
N/A
|
||||
|
||||
DOWNLOADS:
|
||||
|
||||
N/A
|
||||
|
||||
"""
|
||||
|
||||
|
||||
# *****************************************************************************************************************
|
||||
# ***** ****
|
||||
# *** IMPORT ***
|
||||
# ***** ****
|
||||
# *****************************************************************************************************************
|
||||
|
||||
|
||||
# To make sibling directories accessible for imports:
|
||||
import sys
|
||||
sys.path.append(".")
|
||||
sys.path.append("..")
|
||||
|
||||
# For making data behaviour_models:
|
||||
from pydantic import BaseModel, Field, field_validator, AwareDatetime, computed_field
|
||||
from typing import Optional, Literal, List
|
||||
|
||||
# My utils:
|
||||
from utils_v2.string import regex
|
||||
from utils_v2.date_time import date_time
|
||||
|
||||
# To work with date and time:
|
||||
import datetime
|
||||
|
||||
|
||||
# *****************************************************************************************************************
|
||||
# ***** ****
|
||||
# *** MACROS / ONE-TIME INIT ***
|
||||
# ***** ****
|
||||
# *****************************************************************************************************************
|
||||
|
||||
|
||||
# --- Nothing Yet
|
||||
|
||||
|
||||
# *****************************************************************************************************************
|
||||
# ***** ****
|
||||
# *** VARIABLES ***
|
||||
# ***** ****
|
||||
# *****************************************************************************************************************
|
||||
|
||||
|
||||
# --- Nothing Yet
|
||||
|
||||
|
||||
# *****************************************************************************************************************
|
||||
# ***** ****
|
||||
# *** FUNCTIONS ***
|
||||
# ***** ****
|
||||
# *****************************************************************************************************************
|
||||
|
||||
|
||||
class NSEPreMarketSymbol(BaseModel):
|
||||
|
||||
scrapeTs: AwareDatetime = Field(
|
||||
description = "The time (UTC) at which this this data was scraped.",
|
||||
frozen = True,
|
||||
default_factory = lambda: date_time.get_current_utc_date_time(as_string = False)
|
||||
)
|
||||
|
||||
tz: str = Field(
|
||||
description = "The timezone in which the dates have to be interpreted.",
|
||||
frozen = True,
|
||||
default = "Asia/Kolkata"
|
||||
)
|
||||
|
||||
symbol: str = Field(
|
||||
description = "The trading symbol of this listing.",
|
||||
frozen = True
|
||||
)
|
||||
|
||||
ffmc: float | None = Field(
|
||||
description = "The free-floating market cap. of this symbol.",
|
||||
frozen = True
|
||||
)
|
||||
|
||||
trigger: str | None = Field(
|
||||
description = "Any known trigger.",
|
||||
frozen = True,
|
||||
default = None
|
||||
)
|
||||
|
||||
yearHigh: float | None = Field(
|
||||
description = "The year-high value of this symbol.",
|
||||
frozen = True
|
||||
)
|
||||
|
||||
yearLow: float | None = Field(
|
||||
description = "The year-low value of this symbol.",
|
||||
frozen = True
|
||||
)
|
||||
|
||||
prevClose: float | None = Field(
|
||||
description = "The previous trading session's closing price of this symbol.",
|
||||
frozen = True
|
||||
)
|
||||
|
||||
preMarketPrice: float | None = Field(
|
||||
description = "The pre-market decided price of this symbol.",
|
||||
frozen = True
|
||||
)
|
||||
|
||||
chg: float | None = Field(
|
||||
description = "The absolute change between last closing price and the pre-market price.",
|
||||
frozen = True
|
||||
)
|
||||
|
||||
pChg: float | None = Field(
|
||||
description = "The percent change between last closing price and the pre-market price.",
|
||||
frozen = True
|
||||
)
|
||||
|
||||
totalTradedVolume: int | None = Field(
|
||||
description = "The total volume that was traded in the pre-market session.",
|
||||
frozen = True
|
||||
)
|
||||
|
||||
totalBuyVolume: int | None = Field(
|
||||
description = "The total buying volume that was punched-in in the pre-market session.",
|
||||
frozen = True
|
||||
)
|
||||
|
||||
totalSellVolume: int | None = Field(
|
||||
description = "The total selling volume that was punched-in in the pre-market session.",
|
||||
frozen = True
|
||||
)
|
||||
|
||||
# ┏┓ ┏•
|
||||
# ┃ ┏┓┏┓╋┓┏┓
|
||||
# ┗┛┗┛┛┗┛┗┗┫
|
||||
# ┛
|
||||
|
||||
class Config:
|
||||
extra = "ignore"
|
||||
|
||||
# ┏┓ ┏┓ ┓ ┏┓• ┓ ┓
|
||||
# ┣┫┓┏╋┏┓━━┃ ┏┓┏┳┓┏┓┓┏╋┏┓┏┫ ┣ ┓┏┓┃┏┫┏
|
||||
# ┛┗┗┻┗┗┛ ┗┛┗┛┛┗┗┣┛┗┻┗┗ ┗┻ ┻ ┗┗ ┗┗┻┛
|
||||
# ┛
|
||||
|
||||
@computed_field()
|
||||
def dateIst(self) -> str:
|
||||
return date_time.to_timezone(self.scrapeTs, timezone = date_time.TIMEZONE_IST).strftime("%Y%m%d")
|
||||
|
||||
# ┓┏ ┓• ┓ •
|
||||
# ┃┃┏┓┃┓┏┫┏┓╋┓┏┓┏┓┏
|
||||
# ┗┛┗┻┗┗┗┻┗┻┗┗┗┛┛┗┛
|
||||
|
||||
@field_validator("scrapeTs", mode = "before")
|
||||
def parse_date_time(cls, value):
|
||||
if isinstance(value, datetime.datetime):
|
||||
value = date_time.to_timezone(value, date_time.TIMEZONE_UTC)
|
||||
return value
|
||||
|
||||
# ┏┓ ┏┓
|
||||
# ┃ ┓┏┏╋┏┓┏┳┓ ┣ ┓┏┏┓┏┏
|
||||
# ┗┛┗┻┛┗┗┛┛┗┗ ┻ ┗┻┛┗┗┛
|
||||
|
||||
def to_json(self) -> dict:
|
||||
model_json = self.model_dump()
|
||||
model_json["scrapeTs"] = model_json["scrapeTs"].timestamp()
|
||||
return model_json
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------------------------------------------------
|
||||
|
||||
|
||||
class NSEPreMarketData(BaseModel):
|
||||
|
||||
scrapeTs: AwareDatetime = Field(
|
||||
description = "The time (UTC) at which this this data was scraped.",
|
||||
frozen = True,
|
||||
default_factory = lambda: date_time.get_current_utc_date_time(as_string = False)
|
||||
)
|
||||
|
||||
ts: AwareDatetime = Field(
|
||||
description = "The time (UTC) at which this data was made available by NSE.",
|
||||
frozen = True
|
||||
)
|
||||
|
||||
tz: str = Field(
|
||||
description = "The timezone in which the dates have to be interpreted.",
|
||||
frozen = True,
|
||||
default = "Asia/Kolkata"
|
||||
)
|
||||
|
||||
key: str | None = Field(
|
||||
description = "The kind of list that was fetched.",
|
||||
frozen = True,
|
||||
default = None,
|
||||
examples = ["NIFTY", "BANKNIFTY", "SME", "FO", "OTHERS", "ALL"]
|
||||
)
|
||||
|
||||
advances: int = Field(
|
||||
description = "The no. of symbols that will be opening positive.",
|
||||
frozen = True
|
||||
)
|
||||
|
||||
declines: int = Field(
|
||||
description = "The no. of symbols that will be opening negative.",
|
||||
frozen = True
|
||||
)
|
||||
|
||||
unchanged: int = Field(
|
||||
description = "The no. of symbols that will be opening flat.",
|
||||
frozen = True
|
||||
)
|
||||
|
||||
totalMarketCap: float | int | None = Field(
|
||||
description = "The total market cap. of all of the listed symbols.",
|
||||
frozen = True
|
||||
)
|
||||
|
||||
totalTradedValue: float | int | None = Field(
|
||||
description = "The total value in Rupees that was traded in this pre-market session.",
|
||||
frozen = True
|
||||
)
|
||||
|
||||
totalTradedVolume: int | None = Field(
|
||||
description = "The total volume that was traded in the pre-market session.",
|
||||
frozen = True
|
||||
)
|
||||
|
||||
symbols: List[NSEPreMarketSymbol] = Field(
|
||||
description = "The actual symbol-wise data.",
|
||||
frozen = True
|
||||
)
|
||||
|
||||
# ┏┓ ┏•
|
||||
# ┃ ┏┓┏┓╋┓┏┓
|
||||
# ┗┛┗┛┛┗┛┗┗┫
|
||||
# ┛
|
||||
|
||||
class Config:
|
||||
extra = "ignore"
|
||||
|
||||
# ┏┓ ┏┓ ┓ ┏┓• ┓ ┓
|
||||
# ┣┫┓┏╋┏┓━━┃ ┏┓┏┳┓┏┓┓┏╋┏┓┏┫ ┣ ┓┏┓┃┏┫┏
|
||||
# ┛┗┗┻┗┗┛ ┗┛┗┛┛┗┗┣┛┗┻┗┗ ┗┻ ┻ ┗┗ ┗┗┻┛
|
||||
# ┛
|
||||
|
||||
@computed_field()
|
||||
def dateIst(self) -> str:
|
||||
return date_time.to_timezone(self.ts, timezone = date_time.TIMEZONE_IST).strftime("%Y%m%d")
|
||||
|
||||
# ┓┏ ┓• ┓ •
|
||||
# ┃┃┏┓┃┓┏┫┏┓╋┓┏┓┏┓┏
|
||||
# ┗┛┗┻┗┗┗┻┗┻┗┗┗┛┛┗┛
|
||||
|
||||
@field_validator("scrapeTs", "ts", mode = "before")
|
||||
def parse_date_time(cls, value):
|
||||
if isinstance(value, datetime.datetime):
|
||||
value = date_time.to_timezone(value, date_time.TIMEZONE_UTC)
|
||||
return value
|
||||
|
||||
# ┏┓ ┏┓
|
||||
# ┃ ┓┏┏╋┏┓┏┳┓ ┣ ┓┏┏┓┏┏
|
||||
# ┗┛┗┻┛┗┗┛┛┗┗ ┻ ┗┻┛┗┗┛
|
||||
|
||||
def to_json(self) -> dict:
|
||||
model_json = self.model_dump()
|
||||
model_json["scrapeTs"] = model_json["scrapeTs"].timestamp()
|
||||
for s in model_json["symbols"]: s["scrapeTs"].timestamp()
|
||||
return model_json
|
||||
|
||||
|
||||
# *****************************************************************************************************************
|
||||
# ***** ****
|
||||
# *** MAIN PROGRAM ***
|
||||
# ***** ****
|
||||
# *****************************************************************************************************************
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
|
||||
pass
|
||||
Reference in New Issue
Block a user