feat(populate): add indicator calculation to populate script

feat(indicators): add validation and force_update to indicator calculations
devenv
2025-10-18 11:33:59 +01:00 · 2025-10-18 11:33:24 +01:00 · 2025-10-18 10:55:48 +01:00 · 2025-10-18 10:55:36 +01:00 · 2025-10-18 10:05:05 +01:00 · 2025-10-18 09:27:19 +01:00
13 changed files with 1753 additions and 151 deletions
--- a/.gitignore
+++ b/.gitignore
@ -209,3 +209,4 @@ pyrightconfig.json

 # End of https://www.toptal.com/developers/gitignore/api/python,go
 .aider*
+*.db
--- a/devenv.lock
+++ b/devenv.lock
@ -74,16 +74,16 @@
    },
    "nixpkgs": {
      "locked": {
-        "lastModified": 1758532697,
-        "owner": "cachix",
-        "repo": "devenv-nixpkgs",
-        "rev": "207a4cb0e1253c7658c6736becc6eb9cace1f25f",
+        "lastModified": 1760775323,
+        "owner": "nixos",
+        "repo": "nixpkgs",
+        "rev": "cef7b5a1998b7d7f4b945168421141f50f98e4ed",
        "type": "github"
      },
      "original": {
-        "owner": "cachix",
-        "ref": "rolling",
-        "repo": "devenv-nixpkgs",
+        "owner": "nixos",
+        "repo": "nixpkgs",
+        "rev": "cef7b5a1998b7d7f4b945168421141f50f98e4ed",
        "type": "github"
      }
    },
--- a/devenv.nix
+++ b/devenv.nix
@ -3,8 +3,9 @@
 {
  env.GREET = "devenv";
  cachix.enable = false;
+  dotenv.disableHint = true;

-  packages = with pkgs; [ poetry ];
+  packages = with pkgs; [ poetry repomix ];

  languages.python = {
    enable = true;
--- a/devenv.yaml
+++ b/devenv.yaml
@ -1,7 +1,7 @@
 # yaml-language-server: $schema=https://devenv.sh/devenv.schema.json
 inputs:
  nixpkgs:
-    url: github:cachix/devenv-nixpkgs/rolling
+    url: github:nixos/nixpkgs/cef7b5a1998b7d7f4b945168421141f50f98e4ed

 # If you're using non-OSS software, you can set allowUnfree to true.
 # allowUnfree: true
--- a/paperone.py
+++ b/paperone.py
@ -1,39 +0,0 @@
-#!/usr/bin/env python
-
-from sys import exit
-from dotenv import load_dotenv
-from typing import NoReturn
-from paperone.utils import (
-    parse_date_yyyymmdd,
-    is_trading_day,
-    get_last_n_trading_days,
-)
-from os import environ
-from paperone.client import Client
-from rich.progress import track
-
-load_dotenv()
-
-
-def main() -> NoReturn:
-    api_key = environ.get("API_KEY")
-
-    if not api_key:
-        print("API_KEY not set")
-        exit(0)
-
-    client = Client(api_key)
-    date = parse_date_yyyymmdd("20250821")
-    days_range = 60
-    dates_range = get_last_n_trading_days(date, days_range)
-    # tickers = ["VIX"]
-    # indicators = list(IndicatorEnum)
-
-    for x in track([x for x in dates_range if is_trading_day(x)]):
-        print(client.ticker_data_for("AAPL", x))
-
-    exit(0)
-
-
-if __name__ == "__main__":
-    main()
--- a/paperone/client.py
+++ b/paperone/client.py
@ -1,76 +1,120 @@
 from datetime import datetime, timedelta
-from .taapi import TaapiClient
-from .data import TickerData
+from typing import List
+from .models import TickerOHLCV
 import yfinance as yf
 import pandas as pd


-class Client:
-    def __init__(self, taapi_key: str):
-        self._taapi = TaapiClient(taapi_key)
-
+class Fetcher:
    @staticmethod
-    def ticker_data_for(ticker: str, date: datetime) -> TickerData | None:
-        # Set end date to next day to ensure we get the target date
-        start_date = date.strftime("%Y-%m-%d")
-        end_date = (date + timedelta(days=1)).strftime("%Y-%m-%d")
+    def ticker_data_for(
+        ticker: str, date: datetime, end_date: datetime | None = None
+    ) -> List[TickerOHLCV]:
+        """
+        Fetch OHLCV data for a ticker for a date range.
+
+        Args:
+            ticker: Stock ticker symbol
+            date: Start date (inclusive)
+            end_date: End date (inclusive). If None, fetches only the start date.
+
+        Returns:
+            List of TickerOHLCV records, one per trading day in the range.
+            Returns empty list if no data available.
+        """
+        start_date_str = date.strftime("%Y-%m-%d")
+
+        if not end_date:
+            end_date_str = (date + timedelta(days=1)).strftime("%Y-%m-%d")
+        else:
+            end_date_str = (end_date + timedelta(days=1)).strftime("%Y-%m-%d")

        try:
            data = yf.download(
                ticker,
-                start=start_date,
-                end=end_date,
+                start=start_date_str,
+                end=end_date_str,
                auto_adjust=True,
                progress=False,
            )

            if data.empty:
-                return None
+                return []

-            row = data.iloc[0]
+            results: List[TickerOHLCV] = []

-            open_price = (
-                float(row["Open"].iloc[0])
-                if isinstance(row["Open"], pd.Series)
-                else float(row["Open"])
-            )
-            high = (
-                float(row["High"].iloc[0])
-                if isinstance(row["High"], pd.Series)
-                else float(row["High"])
-            )
-            low = (
-                float(row["Low"].iloc[0])
-                if isinstance(row["Low"], pd.Series)
-                else float(row["Low"])
-            )
-            close = (
-                float(row["Close"].iloc[0])
-                if isinstance(row["Close"], pd.Series)
-                else float(row["Close"])
-            )
-            volume = (
-                int(row["Volume"].iloc[0])
-                if isinstance(row["Volume"], pd.Series)
-                else int(row["Volume"])
-                if "Volume" in row
-                else 0
-            )
+            for idx, row in data.iterrows():
+                # Extract datetime from index
+                if hasattr(idx, "to_pydatetime"):
+                    row_date = idx.to_pydatetime()
+                elif isinstance(idx, datetime):
+                    row_date = idx
+                else:
+                    row_date = pd.to_datetime(idx).to_pydatetime()

-            # Calculate average price
-            avg = (high + low) / 2.0
+                # Extract values (handle both Series and scalar)
+                def safe_extract(value):
+                    if isinstance(value, pd.Series):
+                        return float(value.iloc[0])
+                    return float(value)

-            return TickerData(
-                date=date,
-                open=round(open_price, 2),
-                high=round(high, 2),
-                low=round(low, 2),
-                close=round(close, 2),
-                avg=round(avg, 2),
-                volume=volume,
-            )
+                open_price = safe_extract(row["Open"])
+                high = safe_extract(row["High"])
+                low = safe_extract(row["Low"])
+                close = safe_extract(row["Close"])
+                volume = int(safe_extract(row.get("Volume", 0)))
+
+                avg = (high + low) / 2.0
+
+                ohlcv = TickerOHLCV(
+                    ticker=ticker,
+                    date=row_date,
+                    open=round(open_price, 2),
+                    high=round(high, 2),
+                    low=round(low, 2),
+                    close=round(close, 2),
+                    avg=round(avg, 2),
+                    volume=volume,
+                )
+                results.append(ohlcv)
+
+            return results

        except Exception as e:
-            print(f"Error fetching data for {ticker} on {start_date}: {str(e)}")
+            print(
+                f"Error fetching data for {ticker} from {start_date_str} to {end_date_str}: {str(e)}"
+            )
+            return []

-            return None
+    @staticmethod
+    def ticker_data_for_single_day(ticker: str, date: datetime) -> TickerOHLCV | None:
+        """
+        Fetch OHLCV data for a single day (backward compatibility).
+
+        Args:
+            ticker: Stock ticker symbol
+            date: The specific date
+
+        Returns:
+            TickerOHLCV record for that day, or None if not available
+        """
+        results = Fetcher.ticker_data_for(ticker, date, end_date=None)
+
+        return results[0] if results else None
+
+    @staticmethod
+    def ticker_data_for_range(
+        ticker: str, start_date: datetime, end_date: datetime
+    ) -> List[TickerOHLCV]:
+        """
+        Fetch OHLCV data for a date range (explicit range method).
+
+        Args:
+            ticker: Stock ticker symbol
+            start_date: Start date (inclusive)
+            end_date: End date (inclusive)
+
+        Returns:
+            List of TickerOHLCV records for the range
+        """
+        return Fetcher.ticker_data_for(ticker, start_date, end_date)
--- a/paperone/database.py
+++ b/paperone/database.py
@ -0,0 +1,477 @@
+from sqlmodel import SQLModel, Session, create_engine, select
+from typing import List, Optional, Tuple
+from datetime import datetime
+from contextlib import contextmanager
+from .models import TickerOHLCV, IndicatorsData
+from .entities import TimeSeriesTickerData
+
+
+class TradingDataCRUD:
+    """
+    CRUD operations for trading data with SQLModel/SQLite.
+    Handles OHLCV data and technical indicators with proper session management.
+    """
+
+    def __init__(self, database_url: str = "sqlite:///trading_data.db"):
+        """
+        Initialize the CRUD manager with database connection.
+
+        Args:
+            database_url: SQLite database URL (default: local file)
+        """
+        self.engine = create_engine(
+            database_url,
+            echo=False,  # Set to True for SQL query debugging
+            connect_args={"check_same_thread": False},  # Needed for SQLite
+        )
+        self._create_tables()
+
+    def _create_tables(self):
+        """Create all tables if they don't exist."""
+        SQLModel.metadata.create_all(self.engine)
+
+    @contextmanager
+    def get_session(self):
+        """Context manager for database sessions with automatic cleanup."""
+        session = Session(self.engine, expire_on_commit=False)
+        
+        try:
+            yield session
+            session.commit()
+        except Exception:
+            session.rollback()
+            raise
+        finally:
+            session.close()
+
+    # ========================================================================
+    # CREATE Operations
+    # ========================================================================
+
+    def create_ohlcv(self, ohlcv: TickerOHLCV) -> TickerOHLCV:
+        """
+        Insert a single OHLCV record.
+
+        Args:
+            ohlcv: TickerOHLCV instance to insert
+
+        Returns:
+            The inserted TickerOHLCV record
+        """
+        with self.get_session() as session:
+            session.add(ohlcv)
+            session.commit()
+            session.refresh(ohlcv)
+            return ohlcv
+
+    def create_ohlcv_bulk(self, ohlcv_list: List[TickerOHLCV]) -> int:
+        """
+        Bulk insert OHLCV records (more efficient for large datasets).
+
+        Args:
+            ohlcv_list: List of TickerOHLCV instances
+
+        Returns:
+            Number of records inserted
+        """
+        with self.get_session() as session:
+            session.add_all(ohlcv_list)
+            session.commit()
+            return len(ohlcv_list)
+
+    def create_indicators(self, indicators: IndicatorsData) -> IndicatorsData:
+        """
+        Insert a single indicators record.
+
+        Args:
+            indicators: IndicatorsData instance to insert
+
+        Returns:
+            The inserted IndicatorsData record
+        """
+        with self.get_session() as session:
+            session.add(indicators)
+            session.commit()
+            session.refresh(indicators)
+            return indicators
+
+    def create_indicators_bulk(self, indicators_list: List[IndicatorsData]) -> int:
+        """
+        Bulk insert indicators records.
+
+        Args:
+            indicators_list: List of IndicatorsData instances
+
+        Returns:
+            Number of records inserted
+        """
+        with self.get_session() as session:
+            session.add_all(indicators_list)
+            session.commit()
+            return len(indicators_list)
+
+    # ========================================================================
+    # READ Operations
+    # ========================================================================
+
+    def get_ohlcv(self, ticker: str, date: datetime) -> Optional[TickerOHLCV]:
+        """
+        Get a single OHLCV record by ticker and date.
+
+        Args:
+            ticker: Stock ticker symbol
+            date: Trading date
+
+        Returns:
+            TickerOHLCV record or None if not found
+        """
+        with self.get_session() as session:
+            statement = select(TickerOHLCV).where(
+                TickerOHLCV.ticker == ticker, TickerOHLCV.date == date
+            )
+            return session.exec(statement).first()
+
+    def get_ohlcv_range(
+        self, ticker: str, start_date: datetime, end_date: datetime
+    ) -> List[TickerOHLCV]:
+        """
+        Get OHLCV records for a ticker within a date range.
+
+        Args:
+            ticker: Stock ticker symbol
+            start_date: Start of date range (inclusive)
+            end_date: End of date range (inclusive)
+
+        Returns:
+            List of TickerOHLCV records, sorted by date
+        """
+        with self.get_session() as session:
+            statement = (
+                select(TickerOHLCV)
+                .where(
+                    TickerOHLCV.ticker == ticker,
+                    TickerOHLCV.date >= start_date,
+                    TickerOHLCV.date <= end_date,
+                )
+                .order_by(TickerOHLCV.date)
+            )
+            return list(session.exec(statement).all())
+
+    def get_ohlcv_latest(self, ticker: str, limit: int = 1) -> List[TickerOHLCV]:
+        """
+        Get the most recent OHLCV record(s) for a ticker.
+
+        Args:
+            ticker: Stock ticker symbol
+            limit: Number of recent records to retrieve
+
+        Returns:
+            List of most recent TickerOHLCV records, sorted by date descending
+        """
+        with self.get_session() as session:
+            statement = (
+                select(TickerOHLCV)
+                .where(TickerOHLCV.ticker == ticker)
+                .order_by(TickerOHLCV.date.desc())
+                .limit(limit)
+            )
+            return list(session.exec(statement).all())
+
+    def get_indicators(self, ticker: str, date: datetime) -> Optional[IndicatorsData]:
+        """
+        Get indicators for a specific ticker and date.
+
+        Args:
+            ticker: Stock ticker symbol
+            date: Trading date
+
+        Returns:
+            IndicatorsData record or None if not found
+        """
+        with self.get_session() as session:
+            statement = select(IndicatorsData).where(
+                IndicatorsData.ticker == ticker, IndicatorsData.date == date
+            )
+            return session.exec(statement).first()
+
+    def get_indicators_range(
+        self, ticker: str, start_date: datetime, end_date: datetime
+    ) -> List[IndicatorsData]:
+        """
+        Get indicators for a ticker within a date range.
+
+        Args:
+            ticker: Stock ticker symbol
+            start_date: Start of date range (inclusive)
+            end_date: End of date range (inclusive)
+
+        Returns:
+            List of IndicatorsData records, sorted by date
+        """
+        with self.get_session() as session:
+            statement = (
+                select(IndicatorsData)
+                .where(
+                    IndicatorsData.ticker == ticker,
+                    IndicatorsData.date >= start_date,
+                    IndicatorsData.date <= end_date,
+                )
+                .order_by(IndicatorsData.date)
+            )
+            return list(session.exec(statement).all())
+
+    def get_ohlcv_with_indicators(
+        self, ticker: str, date: datetime
+    ) -> Optional[Tuple[TickerOHLCV, IndicatorsData]]:
+        """
+        Get OHLCV and indicators together for a specific ticker and date.
+
+        Args:
+            ticker: Stock ticker symbol
+            date: Trading date
+
+        Returns:
+            Tuple of (TickerOHLCV, IndicatorsData) or None if not found
+        """
+        with self.get_session() as session:
+            ohlcv_statement = select(TickerOHLCV).where(
+                TickerOHLCV.ticker == ticker, TickerOHLCV.date == date
+            )
+            ohlcv = session.exec(ohlcv_statement).first()
+
+            if not ohlcv:
+                return None
+
+            indicators_statement = select(IndicatorsData).where(
+                IndicatorsData.ticker == ticker, IndicatorsData.date == date
+            )
+            indicators = session.exec(indicators_statement).first()
+
+            if not indicators:
+                return None
+
+            return (ohlcv, indicators)
+
+    def get_time_series(
+        self, ticker: str, start_date: datetime, end_date: datetime
+    ) -> TimeSeriesTickerData:
+        """
+        Get time series data for building TimeSeriesTickerData.
+
+        Args:
+            ticker: Stock ticker symbol
+            start_date: Start of date range
+            end_date: End of date range
+
+        Returns:
+            TimeSeriesTickerData instance with OHLCV data
+        """
+        ohlcv_list = self.get_ohlcv_range(ticker, start_date, end_date)
+        return TimeSeriesTickerData.build_time_series_ticker_data(ticker, ohlcv_list)
+
+    # ========================================================================
+    # UPDATE Operations
+    # ========================================================================
+
+    def update_ohlcv(
+        self, ticker: str, date: datetime, **kwargs
+    ) -> Optional[TickerOHLCV]:
+        """
+        Update OHLCV fields for a specific record.
+
+        Args:
+            ticker: Stock ticker symbol
+            date: Trading date
+            **kwargs: Fields to update (e.g., close=150.0, volume=1000000)
+
+        Returns:
+            Updated TickerOHLCV record or None if not found
+        """
+        with self.get_session() as session:
+            statement = select(TickerOHLCV).where(
+                TickerOHLCV.ticker == ticker, TickerOHLCV.date == date
+            )
+            ohlcv = session.exec(statement).first()
+
+            if not ohlcv:
+                return None
+
+            for key, value in kwargs.items():
+                if hasattr(ohlcv, key):
+                    setattr(ohlcv, key, value)
+
+            session.add(ohlcv)
+            session.commit()
+            session.refresh(ohlcv)
+            return ohlcv
+
+    def update_indicators(
+        self, ticker: str, date: datetime, **kwargs
+    ) -> Optional[IndicatorsData]:
+        """
+        Update indicator fields for a specific record.
+
+        Args:
+            ticker: Stock ticker symbol
+            date: Trading date
+            **kwargs: Fields to update (e.g., rsi_14=55.2, macd_line=1.8)
+
+        Returns:
+            Updated IndicatorsData record or None if not found
+        """
+        with self.get_session() as session:
+            statement = select(IndicatorsData).where(
+                IndicatorsData.ticker == ticker, IndicatorsData.date == date
+            )
+            indicators = session.exec(statement).first()
+
+            if not indicators:
+                return None
+
+            for key, value in kwargs.items():
+                if hasattr(indicators, key):
+                    setattr(indicators, key, value)
+
+            session.add(indicators)
+            session.commit()
+            session.refresh(indicators)
+            return indicators
+
+    # ========================================================================
+    # UPSERT Operations (Insert or Update)
+    # ========================================================================
+
+    def upsert_ohlcv(self, ohlcv: TickerOHLCV) -> TickerOHLCV:
+        """
+        Insert or update OHLCV record if it already exists.
+
+        Args:
+            ohlcv: TickerOHLCV instance
+
+        Returns:
+            The upserted TickerOHLCV record
+        """
+        existing = self.get_ohlcv(ohlcv.ticker, ohlcv.date)
+
+        if existing:
+            return self.update_ohlcv(
+                ohlcv.ticker,
+                ohlcv.date,
+                open=ohlcv.open,
+                close=ohlcv.close,
+                low=ohlcv.low,
+                high=ohlcv.high,
+                avg=ohlcv.avg,
+                volume=ohlcv.volume,
+            )
+        else:
+            return self.create_ohlcv(ohlcv)
+
+    def upsert_indicators(self, indicators: IndicatorsData) -> IndicatorsData:
+        """
+        Insert or update indicators record if it already exists.
+
+        Args:
+            indicators: IndicatorsData instance
+
+        Returns:
+            The upserted IndicatorsData record
+        """
+        existing = self.get_indicators(indicators.ticker, indicators.date)
+
+        if existing:
+            # Get all indicator fields dynamically
+            indicator_fields = {
+                k: v
+                for k, v in indicators.__dict__.items()
+                if k not in ["ticker", "date", "ohlcv", "_sa_instance_state"]
+            }
+            return self.update_indicators(
+                indicators.ticker, indicators.date, **indicator_fields
+            )
+        else:
+            return self.create_indicators(indicators)
+
+    # ========================================================================
+    # DELETE Operations
+    # ========================================================================
+
+    def delete_ohlcv(self, ticker: str, date: datetime) -> bool:
+        """
+        Delete an OHLCV record.
+
+        Args:
+            ticker: Stock ticker symbol
+            date: Trading date
+
+        Returns:
+            True if deleted, False if not found
+        """
+        with self.get_session() as session:
+            statement = select(TickerOHLCV).where(
+                TickerOHLCV.ticker == ticker, TickerOHLCV.date == date
+            )
+            ohlcv = session.exec(statement).first()
+
+            if not ohlcv:
+                return False
+
+            session.delete(ohlcv)
+            session.commit()
+            return True
+
+    def delete_indicators(self, ticker: str, date: datetime) -> bool:
+        """
+        Delete an indicators record.
+
+        Args:
+            ticker: Stock ticker symbol
+            date: Trading date
+
+        Returns:
+            True if deleted, False if not found
+        """
+        with self.get_session() as session:
+            statement = select(IndicatorsData).where(
+                IndicatorsData.ticker == ticker, IndicatorsData.date == date
+            )
+            indicators = session.exec(statement).first()
+
+            if not indicators:
+                return False
+
+            session.delete(indicators)
+            session.commit()
+            return True
+
+    def delete_ticker_data(self, ticker: str) -> Tuple[int, int]:
+        """
+        Delete all data (OHLCV and indicators) for a ticker.
+
+        Args:
+            ticker: Stock ticker symbol
+
+        Returns:
+            Tuple of (ohlcv_deleted_count, indicators_deleted_count)
+        """
+        with self.get_session() as session:
+            # Delete indicators first (due to foreign key constraint)
+            indicators_statement = select(IndicatorsData).where(
+                IndicatorsData.ticker == ticker
+            )
+            indicators_list = session.exec(indicators_statement).all()
+            indicators_count = len(list(indicators_list))
+
+            for ind in indicators_list:
+                session.delete(ind)
+
+            # Delete OHLCV
+            ohlcv_statement = select(TickerOHLCV).where(TickerOHLCV.ticker == ticker)
+            ohlcv_list = session.exec(ohlcv_statement).all()
+            ohlcv_count = len(list(ohlcv_list))
+
+            for ohlcv in ohlcv_list:
+                session.delete(ohlcv)
+
+            session.commit()
+            return (ohlcv_count, indicators_count)
--- a/paperone/entities.py
+++ b/paperone/entities.py
@ -1,56 +1,13 @@
 from dataclasses import dataclass, field
 from datetime import datetime
 from typing import List
-
-
-@dataclass
-class TickerData:
-    date: datetime
-    open: float
-    close: float
-    low: float
-    high: float
-    avg: float
-    volume: int
+from .models import TickerOHLCV


@dataclass
 class TimeSeriesTickerData:
    ticker: str
-    series: List[TickerData] = field(default_factory=list)
-
-    @staticmethod
-    def build_time_series_ticker_data(
-        ticker: str, all_data: List[TickerData]
-    ):
-        ordered = sorted({d.date: d for d in all_data}.values(), key=lambda d: d.date)
-
-        return TimeSeriesTickerData(
-            ticker=ticker,
-            series=ordered,
-        )
-
-    def get_by_date(self, dt: datetime) -> TickerData | None:
-        for d in self.series:
-            if d.date == dt:
-                return d
-
-        return None
-
-    def get_latest(self) -> TickerData | None:
-        if not self.series:
-            return None
-
-        return self.series[-1]
-
-    def get_range(self, start_date: datetime, end_date: datetime) -> List[TickerData]:
-        return [d for d in self.series if start_date <= d.date <= end_date]
-
-    @property
-    def target_date_data(self) -> TickerData | None:
-        """Return the most recent TickerData (by convention, the target date tick)."""
-        return self.get_latest()
-
+    series: List[TickerOHLCV] = field(default_factory=list)


@dataclass
--- a/paperone/indicators.py
+++ b/paperone/indicators.py
@ -0,0 +1,369 @@
+import talib
+import numpy as np
+from typing import List
+from datetime import datetime, timedelta
+from .models import (
+    TickerOHLCV,
+    IndicatorsData,
+    MarketRegimeIndicators,
+    MomentumIndicators,
+    VolatilityIndicators,
+    VolumeIndicators,
+    SupportResistanceIndicators,
+    TrendIndicators,
+    OHLCVArrays,
+)
+from .database import TradingDataCRUD
+
+
+class IndicatorService:
+    """
+    Middleware service for calculating technical indicators from stored OHLCV data.
+
+    This service:
+    1. Fetches historical OHLCV data from the database
+    2. Calculates all 29 technical indicators using TA-Lib
+    3. Returns strongly-typed IndicatorsData ready to be saved
+
+    All calculations are done locally without external API calls.
+    """
+
+    def __init__(self, crud: TradingDataCRUD):
+        """
+        Initialize the indicator service with database access.
+
+        Args:
+            crud: TradingDataCRUD instance for database operations
+        """
+        self._crud: TradingDataCRUD = crud
+
+    def calculate_indicators_for_date(
+        self, ticker: str, target_date: datetime, lookback_days: int = 50
+    ) -> IndicatorsData | None:
+        """
+        Calculate all indicators for a ticker on a specific date using stored OHLCV data.
+
+        Args:
+            ticker: Stock ticker symbol
+            target_date: Date to calculate indicators for
+            lookback_days: Number of historical days needed for calculations (default: 50)
+
+        Returns:
+            IndicatorsData instance ready to save to database, or None if insufficient data
+            or if any calculated values are NaN
+        """
+        # Add indicator-specific validation
+        required_periods = {
+            "MACD": 26 + 9,  # slowperiod + signalperiod
+            "ADX": 14 + 14,  # Additional warmup needed
+            "RSI": 14 + 1,  # Plus warmup
+        }
+        min_required = max(required_periods.values()) + 10  # Safety buffer
+
+        if lookback_days < min_required:
+            return None
+
+        # Fetch historical OHLCV data from database
+        start_date: datetime = target_date - timedelta(
+            days=lookback_days * 2
+        )  # Buffer for weekends
+        ohlcv_records: List[TickerOHLCV] = self._crud.get_ohlcv_range(
+            ticker=ticker, start_date=start_date, end_date=target_date
+        )
+
+        if len(ohlcv_records) < min_required:
+            return None
+
+        # Convert to numpy arrays for TA-Lib
+        arrays: OHLCVArrays = self._convert_to_arrays(ohlcv_records)
+
+        # Calculate all indicator categories
+        momentum: MomentumIndicators | None = self._calculate_momentum(arrays)
+        volatility: VolatilityIndicators | None = self._calculate_volatility(arrays)
+        trend: TrendIndicators | None = self._calculate_trend(arrays)
+        volume: VolumeIndicators | None = self._calculate_volume(arrays)
+        support_resistance: SupportResistanceIndicators = (
+            self._calculate_support_resistance(arrays)
+        )
+        market_regime: MarketRegimeIndicators | None = self._calculate_market_regime(
+            arrays
+        )
+
+        # Skip if any indicator group returned None (contains NaN values)
+        if (
+            momentum is None
+            or volatility is None
+            or trend is None
+            or volume is None
+            or market_regime is None
+        ):
+            return None
+
+        return IndicatorsData(
+            ticker=ticker,
+            date=target_date,
+            # Momentum (7 indicators)
+            rsi_14=momentum.rsi_14,
+            rsi_20=momentum.rsi_20,
+            macd_line=momentum.macd_line,
+            macd_signal=momentum.macd_signal,
+            macd_histogram=momentum.macd_histogram,
+            stoch_k=momentum.stoch_k,
+            stoch_d=momentum.stoch_d,
+            # Volatility (6 indicators)
+            bb_upper=volatility.bb_upper,
+            bb_middle=volatility.bb_middle,
+            bb_lower=volatility.bb_lower,
+            bb_width=volatility.bb_width,
+            bb_percent=volatility.bb_percent,
+            atr_14=volatility.atr_14,
+            # Trend (4 indicators)
+            adx_14=trend.adx_14,
+            di_plus=trend.di_plus,
+            di_minus=trend.di_minus,
+            sar=trend.sar,
+            # Volume (3 indicators)
+            obv=volume.obv,
+            obv_sma_20=volume.obv_sma_20,
+            volume_roc_5=volume.volume_roc_5,
+            # Support/Resistance (6 indicators)
+            fib_236=support_resistance.fib_236,
+            fib_382=support_resistance.fib_382,
+            fib_618=support_resistance.fib_618,
+            pivot_point=support_resistance.pivot_point,
+            resistance_1=support_resistance.resistance_1,
+            support_1=support_resistance.support_1,
+            # Market Regime (2 indicators)
+            cci_20=market_regime.cci_20,
+            williams_r_14=market_regime.williams_r_14,
+        )
+
+    def calculate_and_save_indicators(
+        self, ticker: str, target_date: datetime, force_update: bool = False
+    ) -> IndicatorsData | None:
+        if not force_update:
+            existing = self._crud.get_indicators(ticker=ticker, date=target_date)
+
+            if existing is not None:
+                return existing
+
+        indicators = self.calculate_indicators_for_date(
+            ticker=ticker, target_date=target_date
+        )
+
+        if indicators is None:
+            return None
+
+        return self._crud.upsert_indicators(indicators)
+
+    def bulk_calculate_indicators(
+        self, ticker: str, dates: List[datetime]
+    ) -> List[IndicatorsData]:
+        """
+        Calculate indicators for multiple dates efficiently.
+
+        Args:
+            ticker: Stock ticker symbol
+            dates: List of dates to calculate indicators for
+
+        Returns:
+            List of IndicatorsData instances (may be less than input if some failed)
+        """
+        results: List[IndicatorsData] = []
+
+        for date in dates:
+            indicators: IndicatorsData | None = self.calculate_indicators_for_date(
+                ticker=ticker, target_date=date
+            )
+            if indicators is not None:
+                results.append(indicators)
+
+        return results
+
+    def bulk_calculate_and_save_indicators(
+    self, ticker: str, dates: List[datetime], force_update: bool = False
+) -> int:
+        # Batch check existing records
+        if not force_update:
+            existing_dates = self._crud.get_existing_indicator_dates(ticker, dates)
+            dates = [d for d in dates if d not in existing_dates]
+    
+        if not dates:
+            return 0
+    
+        start_date = min(dates) - timedelta(days=150)
+        end_date = max(dates)
+        all_ohlcv = self._crud.get_ohlcv_range(ticker, start_date, end_date)
+    
+        results = []
+        for date in dates:
+            indicators = self._calculate_for_date_from_data(all_ohlcv, date)
+
+            if indicators:
+                results.append(indicators)
+    
+        # Batch insert
+        return self._crud.bulk_upsert_indicators(results)
+
+
+    # ========================================================================
+    # PRIVATE: Data Conversion
+    # ========================================================================
+
+    @staticmethod
+    def _convert_to_arrays(ohlcv_records: List[TickerOHLCV]) -> "OHLCVArrays":
+        """Convert list of TickerOHLCV records to numpy arrays for TA-Lib."""
+        return OHLCVArrays(
+            open=np.array([r.open for r in ohlcv_records], dtype=np.float64),
+            high=np.array([r.high for r in ohlcv_records], dtype=np.float64),
+            low=np.array([r.low for r in ohlcv_records], dtype=np.float64),
+            close=np.array([r.close for r in ohlcv_records], dtype=np.float64),
+            volume=np.array([r.volume for r in ohlcv_records], dtype=np.float64),
+        )
+
+    # ========================================================================
+    # PRIVATE: Indicator Calculations
+    # ========================================================================
+
+    @staticmethod
+    def _calculate_momentum(arrays: "OHLCVArrays") -> "MomentumIndicators":
+        """Calculate momentum indicators (RSI, MACD, Stochastic)."""
+        rsi_14: float = float(talib.RSI(arrays.close, timeperiod=14)[-1])
+        rsi_20: float = float(talib.RSI(arrays.close, timeperiod=20)[-1])
+
+        macd_line_arr, macd_signal_arr, macd_hist_arr = talib.MACD(
+            arrays.close, fastperiod=12, slowperiod=26, signalperiod=9
+        )
+
+        stoch_k_arr, stoch_d_arr = talib.STOCH(
+            arrays.high,
+            arrays.low,
+            arrays.close,
+            fastk_period=14,
+            slowk_period=3,
+            slowd_period=3,
+        )
+
+        return MomentumIndicators(
+            rsi_14=round(rsi_14, 2),
+            rsi_20=round(rsi_20, 2),
+            macd_line=round(float(macd_line_arr[-1]), 4),
+            macd_signal=round(float(macd_signal_arr[-1]), 4),
+            macd_histogram=round(float(macd_hist_arr[-1]), 4),
+            stoch_k=round(float(stoch_k_arr[-1]), 2),
+            stoch_d=round(float(stoch_d_arr[-1]), 2),
+        )
+
+    @staticmethod
+    def _calculate_volatility(arrays: "OHLCVArrays") -> "VolatilityIndicators":
+        """Calculate volatility indicators (Bollinger Bands, ATR)."""
+        bb_upper_arr, bb_middle_arr, bb_lower_arr = talib.BBANDS(
+            arrays.close, timeperiod=20, nbdevup=2, nbdevdn=2
+        )
+
+        bb_upper: float = float(bb_upper_arr[-1])
+        bb_middle: float = float(bb_middle_arr[-1])
+        bb_lower: float = float(bb_lower_arr[-1])
+        bb_width: float = bb_upper - bb_lower
+        bb_percent: float = (
+            (arrays.close[-1] - bb_lower) / (bb_upper - bb_lower)
+            if bb_width > 0
+            else 0.5
+        )
+
+        atr_14: float = float(
+            talib.ATR(arrays.high, arrays.low, arrays.close, timeperiod=14)[-1]
+        )
+
+        return VolatilityIndicators(
+            bb_upper=round(bb_upper, 2),
+            bb_middle=round(bb_middle, 2),
+            bb_lower=round(bb_lower, 2),
+            bb_width=round(bb_width, 2),
+            bb_percent=round(bb_percent, 4),
+            atr_14=round(atr_14, 2),
+        )
+
+    @staticmethod
+    def _calculate_trend(arrays: "OHLCVArrays") -> "TrendIndicators":
+        """Calculate trend indicators (ADX, DI+, DI-, SAR)."""
+        adx_14: float = float(
+            talib.ADX(arrays.high, arrays.low, arrays.close, timeperiod=14)[-1]
+        )
+        di_plus: float = float(
+            talib.PLUS_DI(arrays.high, arrays.low, arrays.close, timeperiod=14)[-1]
+        )
+        di_minus: float = float(
+            talib.MINUS_DI(arrays.high, arrays.low, arrays.close, timeperiod=14)[-1]
+        )
+        sar: float = float(
+            talib.SAR(arrays.high, arrays.low, acceleration=0.02, maximum=0.2)[-1]
+        )
+
+        return TrendIndicators(
+            adx_14=round(adx_14, 2),
+            di_plus=round(di_plus, 2),
+            di_minus=round(di_minus, 2),
+            sar=round(sar, 2),
+        )
+
+    @staticmethod
+    def _calculate_volume(arrays: "OHLCVArrays") -> "VolumeIndicators":
+        """Calculate volume indicators (OBV, Volume ROC)."""
+        obv_arr: np.ndarray = talib.OBV(arrays.close, arrays.volume)
+        obv: float = float(obv_arr[-1])
+        obv_sma_20: float = float(talib.SMA(obv_arr, timeperiod=20)[-1])
+        volume_roc_5: float = float(talib.ROC(arrays.volume, timeperiod=5)[-1])
+
+        return VolumeIndicators(
+            obv=round(obv, 0),
+            obv_sma_20=round(obv_sma_20, 0),
+            volume_roc_5=round(volume_roc_5, 2),
+        )
+
+    @staticmethod
+    def _calculate_support_resistance(
+        arrays: "OHLCVArrays",
+    ) -> "SupportResistanceIndicators":
+        """Calculate support/resistance levels (Fibonacci, Pivot Points)."""
+        # Fibonacci retracements (last 30 days)
+        lookback: int = min(30, len(arrays.high))
+        max_price: float = float(np.max(arrays.high[-lookback:]))
+        min_price: float = float(np.min(arrays.low[-lookback:]))
+        diff: float = max_price - min_price
+
+        fib_236: float = max_price - (diff * 0.236)
+        fib_382: float = max_price - (diff * 0.382)
+        fib_618: float = max_price - (diff * 0.618)
+
+        # Pivot points (previous day's data)
+        high_prev: float = float(arrays.high[-1])
+        low_prev: float = float(arrays.low[-1])
+        close_prev: float = float(arrays.close[-1])
+
+        pivot_point: float = (high_prev + low_prev + close_prev) / 3
+        resistance_1: float = (2 * pivot_point) - low_prev
+        support_1: float = (2 * pivot_point) - high_prev
+
+        return SupportResistanceIndicators(
+            fib_236=round(fib_236, 2),
+            fib_382=round(fib_382, 2),
+            fib_618=round(fib_618, 2),
+            pivot_point=round(pivot_point, 2),
+            resistance_1=round(resistance_1, 2),
+            support_1=round(support_1, 2),
+        )
+
+    @staticmethod
+    def _calculate_market_regime(arrays: "OHLCVArrays") -> "MarketRegimeIndicators":
+        """Calculate market regime indicators (CCI, Williams %R)."""
+        cci_20: float = float(
+            talib.CCI(arrays.high, arrays.low, arrays.close, timeperiod=20)[-1]
+        )
+        williams_r_14: float = float(
+            talib.WILLR(arrays.high, arrays.low, arrays.close, timeperiod=14)[-1]
+        )
+
+        return MarketRegimeIndicators(
+            cci_20=round(cci_20, 2), williams_r_14=round(williams_r_14, 2)
+        )
--- a/paperone/models.py
+++ b/paperone/models.py
@ -0,0 +1,163 @@
+from sqlmodel import SQLModel, Field, Relationship, ForeignKeyConstraint
+from dataclasses import dataclass
+from datetime import datetime
+from typing import Optional
+import numpy as np
+
+
+class TickerOHLCV(SQLModel, table=True):
+    __tablename__ = "ohlcv"
+
+    ticker: str = Field(primary_key=True)
+    date: datetime = Field(primary_key=True, index=True)
+    open: float
+    close: float
+    low: float
+    high: float
+    avg: float
+    volume: int
+
+    indicators: Optional["IndicatorsData"] = Relationship(
+        back_populates="ohlcv",
+        sa_relationship_kwargs={"uselist": False},
+    )
+
+
+class IndicatorsData(SQLModel, table=True):
+    __tablename__ = "indicators"
+    __table_args__ = (
+        ForeignKeyConstraint(["ticker", "date"], ["ohlcv.ticker", "ohlcv.date"]),
+    )
+
+    ticker: str = Field(primary_key=True)
+    date: datetime = Field(primary_key=True, index=True)
+
+    # ========================================================================
+    # MOMENTUM INDICATORS (Trend Direction & Strength)
+    # ========================================================================
+    rsi_14: float  # Standard 14-period RSI
+    rsi_20: float  # Longer 20-period RSI for smoother signal
+    macd_line: float  # MACD line (12 EMA - 26 EMA)
+    macd_signal: float  # Signal line (9-period EMA of MACD)
+    macd_histogram: float  # Histogram (MACD - Signal), shows momentum strength
+    stoch_k: float  # Fast stochastic %K (14-period)
+    stoch_d: float  # Slow stochastic %D (3-period SMA of %K)
+
+    # ========================================================================
+    # VOLATILITY INDICATORS (Price Dispersion & Risk)
+    # ========================================================================
+    bb_upper: float  # Upper Bollinger Band (SMA + 2*std)
+    bb_middle: float  # Middle band (20-period SMA)
+    bb_lower: float  # Lower Bollinger Band (SMA - 2*std)
+    bb_width: float  # Band width (upper - lower), measures volatility magnitude
+    bb_percent: float  # %B indicator: (close - lower) / (upper - lower)
+    atr_14: float  # 14-period Average True Range
+
+    # ========================================================================
+    # TREND INDICATORS (Trend Presence & Sustainability)
+    # ========================================================================
+    adx_14: float  # 14-period ADX (trend strength)
+    di_plus: float  # +DI (bullish directional indicator)
+    di_minus: float  # -DI (bearish directional indicator)
+    sar: float  # Current Parabolic SAR level
+
+    # ========================================================================
+    # VOLUME INDICATORS (Institutional Participation)
+    # ========================================================================
+    obv: float  # On-Balance Volume cumulative total
+    obv_sma_20: float  # 20-day SMA of OBV (trend confirmation)
+    volume_roc_5: float  # 5-day volume rate of change (%)
+
+    # ========================================================================
+    # SUPPORT/RESISTANCE INDICATORS (Key Price Levels)
+    # ========================================================================
+    fib_236: float  # 23.6% Fibonacci retracement level
+    fib_382: float  # 38.2% Fibonacci retracement level
+    fib_618: float  # 61.8% Fibonacci retracement level (golden ratio)
+    pivot_point: float  # Standard pivot point (High + Low + Close) / 3
+    resistance_1: float  # First resistance level (R1)
+    support_1: float  # First support level (S1)
+
+    # ========================================================================
+    # MARKET REGIME INDICATORS (Market Condition Classification)
+    # ========================================================================
+    cci_20: float  # 20-period Commodity Channel Index
+    williams_r_14: float  # 14-period Williams %R
+
+    # One-to-one relationship back to TickerOHLCV
+    ohlcv: TickerOHLCV = Relationship(back_populates="indicators")
+
+
+@dataclass(frozen=True)
+class OHLCVArrays:
+    """Numpy arrays of OHLCV data for TA-Lib calculations."""
+
+    open: np.ndarray
+    high: np.ndarray
+    low: np.ndarray
+    close: np.ndarray
+    volume: np.ndarray
+
+
+@dataclass(frozen=True)
+class MomentumIndicators:
+    """Momentum indicator values (RSI, MACD, Stochastic)."""
+
+    rsi_14: float
+    rsi_20: float
+    macd_line: float
+    macd_signal: float
+    macd_histogram: float
+    stoch_k: float
+    stoch_d: float
+
+
+@dataclass(frozen=True)
+class VolatilityIndicators:
+    """Volatility indicator values (Bollinger Bands, ATR)."""
+
+    bb_upper: float
+    bb_middle: float
+    bb_lower: float
+    bb_width: float
+    bb_percent: float
+    atr_14: float
+
+
+@dataclass(frozen=True)
+class TrendIndicators:
+    """Trend indicator values (ADX, DI+, DI-, SAR)."""
+
+    adx_14: float
+    di_plus: float
+    di_minus: float
+    sar: float
+
+
+@dataclass(frozen=True)
+class VolumeIndicators:
+    """Volume indicator values (OBV, Volume ROC)."""
+
+    obv: float
+    obv_sma_20: float
+    volume_roc_5: float
+
+
+@dataclass(frozen=True)
+class SupportResistanceIndicators:
+    """Support/Resistance levels (Fibonacci, Pivot Points)."""
+
+    fib_236: float
+    fib_382: float
+    fib_618: float
+    pivot_point: float
+    resistance_1: float
+    support_1: float
+
+
+@dataclass(frozen=True)
+class MarketRegimeIndicators:
+    """Market regime indicators (CCI, Williams %R)."""
+
+    cci_20: float
+    williams_r_14: float
--- a/poetry.lock
+++ b/poetry.lock
@ -1,4 +1,16 @@
-# This file is automatically @generated by Poetry 2.1.4 and should not be changed by hand.
+# This file is automatically @generated by Poetry 2.2.1 and should not be changed by hand.
+
+[[package]]
+name = "annotated-types"
+version = "0.7.0"
+description = "Reusable constraint types to use with typing.Annotated"
+optional = false
+python-versions = ">=3.8"
+groups = ["main"]
+files = [
+    {file = "annotated_types-0.7.0-py3-none-any.whl", hash = "sha256:1f02e8b43a8fbbc3f3e0d4f0f4bfc8131bcb4eebe8849b8e5c773f3a1c582a53"},
+    {file = "annotated_types-0.7.0.tar.gz", hash = "sha256:aff07c09a53a08bc8cfccb9c85b05f1aa9a2a6f23728d790723543408344ce89"},
+]

 [[package]]
 name = "asttokens"
@ -58,6 +70,27 @@ charset-normalizer = ["charset-normalizer"]
 html5lib = ["html5lib"]
 lxml = ["lxml"]

+[[package]]
+name = "build"
+version = "1.3.0"
+description = "A simple, correct Python build frontend"
+optional = false
+python-versions = ">=3.9"
+groups = ["main"]
+files = [
+    {file = "build-1.3.0-py3-none-any.whl", hash = "sha256:7145f0b5061ba90a1500d60bd1b13ca0a8a4cebdd0cc16ed8adf1c0e739f43b4"},
+    {file = "build-1.3.0.tar.gz", hash = "sha256:698edd0ea270bde950f53aed21f3a0135672206f3911e0176261a31e0e07b397"},
+]
+
+[package.dependencies]
+colorama = {version = "*", markers = "os_name == \"nt\""}
+packaging = ">=19.1"
+pyproject_hooks = "*"
+
+[package.extras]
+uv = ["uv (>=0.1.18)"]
+virtualenv = ["virtualenv (>=20.11) ; python_version < \"3.10\"", "virtualenv (>=20.17) ; python_version >= \"3.10\" and python_version < \"3.14\"", "virtualenv (>=20.31) ; python_version >= \"3.14\""]
+
 [[package]]
 name = "certifi"
 version = "2025.10.5"
@ -278,7 +311,7 @@ description = "Cross-platform colored terminal text."
 optional = false
 python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*,>=2.7"
 groups = ["main"]
-markers = "platform_system == \"Windows\" or sys_platform == \"win32\""
+markers = "platform_system == \"Windows\" or sys_platform == \"win32\" or os_name == \"nt\""
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+    {file = "ta_lib-0.6.7.tar.gz", hash = "sha256:d702cbb20ab34d6d6c46bef87a1bd4bfeae0cc0ab65cbdf1d23dd392ce110d69"},
+]
+
+[package.dependencies]
+build = "*"
+cython = "*"
+numpy = "*"
+
 [[package]]
 name = "toolz"
 version = "1.0.0"
@ -1133,6 +1666,21 @@ files = [
    {file = "typing_extensions-4.15.0.tar.gz", hash = "sha256:0cea48d173cc12fa28ecabc3b837ea3cf6f38c6d1136f85cbaaf598984861466"},
 ]

+[[package]]
+name = "typing-inspection"
+version = "0.4.2"
+description = "Runtime typing introspection tools"
+optional = false
+python-versions = ">=3.9"
+groups = ["main"]
+files = [
+    {file = "typing_inspection-0.4.2-py3-none-any.whl", hash = "sha256:4ed1cacbdc298c220f1bd249ed5287caa16f34d44ef4e9c3d0cbad5b521545e7"},
+    {file = "typing_inspection-0.4.2.tar.gz", hash = "sha256:ba561c48a67c5958007083d386c3295464928b01faa735ab8547c5692e87f464"},
+]
+
+[package.dependencies]
+typing-extensions = ">=4.12.0"
+
 [[package]]
 name = "tzdata"
 version = "2025.2"
@ -1287,4 +1835,4 @@ repair = ["scipy (>=1.6.3)"]
 [metadata]
 lock-version = "2.1"
 python-versions = ">=3.13"
-content-hash = "3519edd3b81c820008526606d507cec7cac4734a4ff83eb9c8c46ffb3b21ac56"
+content-hash = "c9a5936e446cf6234585a330d4fc3888dd4a8c8db505bbc9e78d454cfe864569"
--- a/populate.py
+++ b/populate.py
@ -0,0 +1,79 @@
+#!/usr/bin/env python
+
+from sys import exit
+from dotenv import load_dotenv
+from typing import NoReturn
+from paperone.utils import (
+    get_last_n_trading_days,
+)
+from paperone.database import TradingDataCRUD
+from paperone.indicators import IndicatorService
+from paperone.client import Fetcher
+from rich.progress import track
+from datetime import datetime
+
+load_dotenv()
+
+DB_FILE = "trading_data.db"
+
+
+def main() -> NoReturn:
+    fetcher = Fetcher()
+    crud = TradingDataCRUD(f"sqlite:///{DB_FILE}")
+    ind = IndicatorService(crud)
+    date = datetime.now()
+    days_range = 360 * 10
+
+    tickers = [
+        "AAPL",
+        "ARM",
+        "AMD",
+        "GOOG",
+        "META",
+        "MNDY",
+        "MSFT",
+        "NVDA",
+    ]
+
+    reference_tickers = [
+        "VOO",  # US
+        "VT",  # global
+        "GLD",  # gold
+        "^VIX",  # volatility
+        "VNQ",  # real estate
+        "DBC",  # commodities
+        "VGK",  # EU
+        "VPL",  # Asia
+        "VWO",  # Emerging
+        "BND",  # Global bonds
+    ]
+
+    for ticker in tickers + reference_tickers:
+        trading_days = get_last_n_trading_days(date, days_range)
+        start_date = trading_days[0]
+        end_date = trading_days[-1]
+
+        all_ohlcv_data = fetcher.ticker_data_for(ticker, start_date, end_date)
+
+        ohlcv_dates = []
+        for ohlcv in track(all_ohlcv_data, description=f"→ {ticker} OHLCV"):
+            existing = crud.get_ohlcv(ticker, ohlcv.date)
+
+            if not existing:
+                crud.create_ohlcv(ohlcv)
+
+            ohlcv_dates.append(ohlcv.date)
+
+        for calc_date in track(ohlcv_dates, description=f"→ {ticker} Indicators"):
+            existing_indicator = crud.get_indicators(ticker, calc_date)
+
+            if existing_indicator:
+                continue
+
+            ind.calculate_and_save_indicators(ticker=ticker, target_date=calc_date)
+
+    exit(0)
+
+
+if __name__ == "__main__":
+    main()
--- a/pyproject.toml
+++ b/pyproject.toml
@ -14,7 +14,9 @@ dependencies = [
    "typer (>=0.19.2,<0.20.0)",
    "yfinance (>=0.2.66,<0.3.0)",
    "ipython (>=9.6.0,<10.0.0)",
-    "pandas-market-calendars (>=5.1.1,<6.0.0)"
+    "pandas-market-calendars (>=5.1.1,<6.0.0)",
+    "sqlmodel (>=0.0.27,<0.0.28)",
+    "ta-lib (>=0.6.7,<0.7.0)"
 ]
Author	SHA1	Message	Date
Giulio De Pasquale	46662a37a4	feat(populate): add indicator calculation to populate script	2025-10-18 11:33:59 +01:00
Giulio De Pasquale	d87733b80e	feat(indicators): add validation and force_update to indicator calculations	2025-10-18 11:33:24 +01:00
Giulio De Pasquale	30ed373ac5	devenv	2025-10-18 10:55:48 +01:00
Giulio De Pasquale	c11c2bccf4	refactor: use Fetcher and add reference tickers	2025-10-18 10:55:36 +01:00
Giulio De Pasquale	600d6b76f6	feat(indicators): add indicator service and related dataclasses	2025-10-18 10:05:05 +01:00
Giulio De Pasquale	4fb70813e6	refactor(client): use models for TickerOHLCV and include ticker in OHLCV	2025-10-18 09:27:19 +01:00
Giulio De Pasquale	35de3b208c	build(pyproject): add sqlmodel dependency	2025-10-18 09:26:47 +01:00
Giulio De Pasquale	5b67db68ea	refactor(scripts): replace paperone.py with populate.py to populate database	2025-10-18 09:26:06 +01:00
Giulio De Pasquale	41d0f4060f	ignore db	2025-10-18 09:23:32 +01:00
Giulio De Pasquale	13d5987e49	refactor(models): add explicit foreign key constraints for indicators	2025-10-18 09:23:02 +01:00
Giulio De Pasquale	f5aa0e5848	feat(database): add trading data CRUD operations	2025-10-18 09:22:23 +01:00
Giulio De Pasquale	b4cc94a444	asodijasoidjasoidj	2025-10-16 12:59:39 +01:00