From 0fc285927928342b389621a524e6f3cbe6a3e135 Mon Sep 17 00:00:00 2001 From: Lavisha Kapoor Date: Fri, 18 Apr 2025 01:20:10 +0530 Subject: [PATCH] backtesting improvement --- backend/app/data/sample_data.csv | 87 +--- .../__pycache__/backtest.cpython-312.pyc | Bin 1446 -> 1526 bytes backend/app/routes/backtest.py | 36 +- .../__pycache__/backtester.cpython-312.pyc | Bin 4664 -> 9178 bytes backend/app/services/backtester.py | 404 +++++++++++++++--- .../bs4/__pycache__/__init__.cpython-312.pyc | Bin 39616 -> 39616 bytes .../bs4/__pycache__/element.cpython-312.pyc | Bin 107371 -> 107371 bytes .../bs4/__pycache__/filter.cpython-312.pyc | Bin 28605 -> 28605 bytes .../builder/__pycache__/_lxml.cpython-312.pyc | Bin 18385 -> 18385 bytes .../__pycache__/__config__.cpython-312.pyc | Bin 5243 -> 5243 bytes .../__pycache__/__init__.cpython-312.pyc | Bin 574 -> 574 bytes .../__pycache__/decoders.cpython-312.pyc | Bin 8322 -> 8322 bytes .../__pycache__/exceptions.cpython-312.pyc | Bin 1743 -> 1743 bytes .../__pycache__/multipart.cpython-312.pyc | Bin 67784 -> 67784 bytes frontend/src/App.js | 119 +----- frontend/src/components/BlocklyEditor.js | 72 +--- frontend/src/components/StrategySelector.js | 65 --- frontend/src/components/customBlocks.js | 105 ++--- frontend/src/generators/jsonGenerator.js | 106 +---- 19 files changed, 459 insertions(+), 535 deletions(-) diff --git a/backend/app/data/sample_data.csv b/backend/app/data/sample_data.csv index 5f7a6439..f4076925 100644 --- a/backend/app/data/sample_data.csv +++ b/backend/app/data/sample_data.csv @@ -1,67 +1,24 @@ Date,Close,High,Low,Open,Volume ,AAPL,AAPL,AAPL,AAPL,AAPL -2024-11-11,223.98373413085938,225.45212091614073,221.25673663335022,224.7528927426808,42005600 -2024-11-12,223.98373413085938,225.34224111445195,223.11469448970428,224.30339000560164,40398300 -2024-11-13,224.8727569580078,226.4010754152989,222.5153482196322,223.76397540644066,48566200 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-2024-11-29,237.06935119628906,237.5488197625333,233.71304074851764,234.55211454995276,28481400 -2024-12-02,239.3268585205078,240.52553753151284,236.89953466637493,237.00941446483552,48137100 -2024-12-03,242.3834991455078,242.49337894569658,238.6376176509325,239.54662188503684,38861000 -2024-12-04,242.74310302734375,243.84190102311462,240.9850414761411,242.60325739533934,44383900 -2024-12-05,242.7730712890625,244.2714238935446,241.86408229295347,243.72204013219255,40033900 -2024-12-06,242.5732879638672,244.3613305629988,241.8141281502541,242.6432183998472,36870600 -2024-12-09,246.47900390625,246.96847124510987,241.48449521514058,241.56440918324205,44649200 -2024-12-10,247.4978790283203,247.93739821602466,245.0705399660552,246.61884065291167,36914800 -2024-12-11,246.2192840576172,250.52454792031958,245.98952569372008,247.68767076725757,45205800 -2024-12-12,247.68768310546875,248.46682524629017,245.41017310687806,246.61885092340057,32777500 -2024-12-13,247.85748291015625,249.01619729452798,245.96955931284188,247.54782582286595,33155300 -2024-12-16,250.7642822265625,251.10392039685559,247.3780059899919,247.71764416028498,51694800 -2024-12-17,253.20159912109375,253.5512208135588,249.50566587259755,249.80533943156328,51356400 -2024-12-18,247.77757263183594,254.0007260278641,247.46791553993853,251.88305927654196,56774100 -2024-12-19,249.51565551757812,251.72323503929724,246.81862390484895,247.22817727073837,60882300 -2024-12-20,254.21051025390625,254.71994465608725,245.42017186050566,247.76758181309805,147495300 -2024-12-23,254.98965454101562,255.36922684225433,253.17164603591402,254.49020366493687,40858800 -2024-12-24,257.91644287109375,257.92641115938613,255.0096198916901,255.2094124344067,23234700 -2024-12-26,258.7355041503906,259.81433504408284,257.34704665632455,257.90642916266114,27237100 -2024-12-27,255.30929565429688,258.41589596104086,252.78207543596488,257.54682582842287,42355300 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-2025-01-15,237.60874938964844,238.6975638581554,234.17252500331003,234.38230107288462,39832000 -2025-01-16,228.00930786132812,237.74859991927732,227.7795647267042,237.089336348529,71759100 -2025-01-17,229.7274169921875,232.03487756376998,228.22906438809179,231.86506609768284,68488300 -2025-01-21,222.39547729492188,224.17352112887505,219.13906319002535,223.75398423747347,98070400 -2025-01-22,223.58416748046875,223.87384226456615,219.54859611049605,219.54859611049605,64126500 -2025-01-23,223.41436767578125,226.78066167492807,222.05586069453574,224.493183388126,60234800 -2025-01-24,222.5353240966797,225.38220009721186,221.16683361690275,224.53312753788666,54697900 -2025-01-27,229.6075439453125,231.89502211760887,223.73399710835045,223.77396171163917,94863400 -2025-01-28,237.99832153320312,239.9262098046868,230.55650666713984,230.59647127201654,75707600 -2025-01-29,239.0971221923828,239.5965730646729,233.75299176206667,233.86287156365174,45486100 -2025-01-30,237.3290557861328,240.52553823889048,236.94948349745044,238.40787147181928,55658300 -2025-01-31,235.74081420898438,246.91852728753366,233.18362815459494,246.91852728753366,101075100 -2025-02-03,227.75958251953125,231.5753945205246,225.45212191586603,229.73741895869952,73063300 -2025-02-04,232.54432678222656,232.87396618357337,226.40107197135944,227.00041910872287,45067300 -2025-02-05,232.21469116210938,232.4144684638066,228.0193068583431,228.27901582634638,39620300 -2025-02-06,232.9638671875,233.54323203112875,230.17692277145878,231.0359788855247,29925300 -2025-02-07,227.3800048828125,233.74300400322835,227.0104008794231,232.3445476829273,39707200 -2025-02-10,227.64999389648438,230.58999633789062,227.1999969482422,229.57000732421875,33115600 -2025-02-11,232.6199951171875,235.22999572753906,228.1300048828125,228.1999969482422,53718400 -2025-02-12,236.8699951171875,236.9600067138672,230.67999267578125,231.1999969482422,45243300 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str - -# @router.post("/backtest") -# def run_backtest_route(payload: StrategyPayload): -# try: -# strategy_json = convert_xml_to_json(payload.strategy_xml) -# result = run_backtest(strategy_json) -# return result -# except Exception as e: -# raise HTTPException(status_code=500, detail=str(e)) - - -# from fastapi import APIRouter, Request -# from pydantic import BaseModel -# from typing import Any, Dict -# from app.services.backtester import run_backtest - -# router = APIRouter() - -# # ✅ Request model # class BacktestRequest(BaseModel): # symbol: str # start_date: str # end_date: str -# code: Dict[str, Any] +# code: List[Dict[str, Any]] # ✅ code is a list of rule dictionaries # @router.post("/backtest") # async def backtest(request_data: BacktestRequest): # try: +# print("Received request:", request_data) # result = run_backtest( # symbol=request_data.symbol, # start_date=request_data.start_date, @@ -47,6 +26,7 @@ # except Exception as e: # return {"error": str(e)} + from fastapi import APIRouter from pydantic import BaseModel from typing import List, Dict, Any @@ -58,7 +38,8 @@ class BacktestRequest(BaseModel): symbol: str start_date: str end_date: str - code: List[Dict[str, Any]] # ✅ code is a list of rule dictionaries + initial_balance: float # ✅ Added balance + code: List[Dict[str, Any]] @router.post("/backtest") async def backtest(request_data: BacktestRequest): @@ -68,7 +49,8 @@ async def backtest(request_data: BacktestRequest): symbol=request_data.symbol, start_date=request_data.start_date, end_date=request_data.end_date, - strategy_json=request_data.code + strategy_json=request_data.code, + initial_balance=request_data.initial_balance # ✅ Pass to backend ) return result except Exception as e: diff --git a/backend/app/services/__pycache__/backtester.cpython-312.pyc b/backend/app/services/__pycache__/backtester.cpython-312.pyc index 3a791d2283cc68ecaa4af09fed6dce485851ef43..6f6879285b6677d22ef5ab0bf55c5647b4163427 100644 GIT binary patch literal 9178 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get_data, fetch_and_save_data + +# def calculate_rsi(df, period=14): +# delta = df['Close'].diff() +# gain = delta.where(delta > 0, 0) +# loss = -delta.where(delta < 0, 0) +# avg_gain = gain.rolling(window=period).mean() +# avg_loss = loss.rolling(window=period).mean() +# rs = avg_gain / avg_loss +# df['RSI'] = 100 - (100 / (1 + rs)) +# return df + +# def calculate_ema(df, period=20): +# df[f'EMA_{period}'] = df['Close'].ewm(span=period, adjust=False).mean() +# return df + +# def calculate_macd(df, fast=12, slow=26, signal=9): +# exp1 = df['Close'].ewm(span=fast, adjust=False).mean() +# exp2 = df['Close'].ewm(span=slow, adjust=False).mean() +# macd = exp1 - exp2 +# signal_line = macd.ewm(span=signal, adjust=False).mean() +# df['MACD'] = macd - signal_line +# return df + +# def calculate_bollinger(df, period=20): +# sma = df['Close'].rolling(window=period).mean() +# std = df['Close'].rolling(window=period).std() +# df['Bollinger_Upper'] = sma + (2 * std) +# df['Bollinger_Lower'] = sma - (2 * std) +# return df + +# def calculate_atr(df, period=14): +# high_low = df['High'] - df['Low'] +# high_close = abs(df['High'] - df['Close'].shift()) +# low_close = abs(df['Low'] - df['Close'].shift()) +# tr = pd.concat([high_low, high_close, low_close], axis=1).max(axis=1) +# df['ATR'] = tr.rolling(window=period).mean() +# return df + +# def evaluate_condition(row, condition): +# if condition["type"] != "LOGIC_COMPARE": +# return False + +# op = condition.get("operator") +# left = condition.get("left", {}) +# right = condition.get("right") +# typ = left.get("type") +# period = left.get("period", 14) + +# if typ == "RSI": +# value = row.get("RSI") +# elif typ == "SMA": +# value = row.get("SMA") +# elif typ == "EMA": +# value = row.get(f"EMA_{period}") +# elif typ == "MACD": +# value = row.get("MACD") +# elif typ == "BOLLINGER": +# band = left.get("band", "upper").upper() +# value = row.get("Bollinger_Upper" if band == "UPPER" else "Bollinger_Lower") +# elif typ == "ATR": +# value = row.get("ATR") +# else: +# return False + +# if pd.isna(value): +# return False + +# if isinstance(right, dict): +# r_typ = right.get("type") +# r_period = right.get("period", 14) +# if r_typ == "RSI": +# right_val = row.get("RSI") +# elif r_typ == "SMA": +# right_val = row.get("SMA") +# elif r_typ == "EMA": +# right_val = row.get(f"EMA_{r_period}") +# elif r_typ == "MACD": +# right_val = row.get("MACD") +# elif r_typ == "ATR": +# right_val = row.get("ATR") +# else: +# right_val = None +# else: +# right_val = right + +# if op == "GT": +# return value > right_val +# elif op == "GTE": +# return value >= right_val +# elif op == "LT": +# return value < right_val +# elif op == "LTE": +# return value <= right_val +# elif op == "EQ": +# return value == right_val + +# return False + +# def process_rule(row, rule): +# if rule["type"] == "IF": +# condition = rule.get("condition") +# if evaluate_condition(row, condition): +# return process_rule(row, rule.get("do", {})) # recurse +# elif rule["type"] == "BUY": +# return "BUY" +# elif rule["type"] == "SELL": +# return "SELL" +# return None + +# def run_backtest(symbol, start_date, end_date, strategy_json, initial_balance): +# fetch_and_save_data(symbol, start_date, end_date) +# df = get_data(symbol, start_date, end_date) + +# if "Date" not in df.columns: +# raise ValueError("'Date' column not found in the data") + +# df["Close"] = pd.to_numeric(df["Close"], errors="coerce") +# df["High"] = pd.to_numeric(df["High"], errors="coerce") +# df["Low"] = pd.to_numeric(df["Low"], errors="coerce") +# df.dropna(subset=["Close", "High", "Low"], inplace=True) +# df["Date"] = pd.to_datetime(df["Date"]) +# df.set_index("Date", inplace=True) + +# # Precompute all required indicators +# for rule in strategy_json: +# def collect_indicators(r): +# if r["type"] == "IF": +# cond = r["condition"] +# left = cond.get("left", {}) +# typ = left.get("type") +# period = left.get("period", 14) + +# if typ == "RSI": +# calculate_rsi(df, period) +# elif typ == "SMA": +# df["SMA"] = df["Close"].rolling(window=period).mean() +# elif typ == "EMA": +# calculate_ema(df, period) +# elif typ == "MACD": +# calculate_macd(df) +# elif typ == "BOLLINGER": +# calculate_bollinger(df, period) +# elif typ == "ATR": +# calculate_atr(df, period) + +# return collect_indicators(r["do"]) +# collect_indicators(rule) + +# balance = initial_balance +# position = None +# entry_price = 0 +# trades = [] + +# for i in range(len(df)): +# row = df.iloc[i] +# date = row.name +# close = row["Close"] + +# for rule in strategy_json: +# signal = process_rule(row, rule) + +# if signal == "BUY" and position is None: +# entry_price = close +# position = close +# trades.append({ +# "date": str(date.date()), +# "action": "BUY", +# "price": round(close, 2) +# }) + +# elif signal == "SELL" and position is not None: +# profit = close - entry_price +# balance += profit +# trades.append({ +# "date": str(date.date()), +# "action": "SELL", +# "price": round(close, 2), +# "pnl": round(profit, 2) +# }) +# position = None + +# final_balance = round(balance, 2) +# returns = df["Close"].pct_change().dropna() +# sharpe = (returns.mean() / returns.std()) * (252 ** 0.5) if returns.std() else 0 + +# return { +# "final_balance": float(final_balance), +# "starting_balance": float(initial_balance), +# "total_trades": len(trades), +# "sharpe_ratio": round(sharpe, 2), +# "trades": [ +# { +# "date": t["date"], +# "action": t["action"], +# "price": float(t["price"]), +# **({"pnl": float(t["pnl"])} if "pnl" in t else {}) +# } for t in trades +# ] +# } import pandas as pd -from .data_fetcher import get_data -from .data_fetcher import fetch_and_save_data +from .data_fetcher import get_data, fetch_and_save_data + +# === Indicator Calculations === -# 📈 RSI calculation def calculate_rsi(df, period=14): delta = df['Close'].diff() gain = delta.where(delta > 0, 0) @@ -13,33 +217,157 @@ def calculate_rsi(df, period=14): df['RSI'] = 100 - (100 / (1 + rs)) return df -# 🚀 Main backtesting function -def run_backtest(symbol, start_date, end_date, strategy_json): - # ✅ Load and clean data +def calculate_sma(df, period=20): + df["SMA"] = df["Close"].rolling(window=period).mean() + return df + +def calculate_ema(df, period=20): + df[f'EMA_{period}'] = df['Close'].ewm(span=period, adjust=False).mean() + return df + +def calculate_macd(df, fast=12, slow=26, signal=9): + exp1 = df['Close'].ewm(span=fast, adjust=False).mean() + exp2 = df['Close'].ewm(span=slow, adjust=False).mean() + macd = exp1 - exp2 + signal_line = macd.ewm(span=signal, adjust=False).mean() + df['MACD'] = macd - signal_line + return df + +def calculate_bollinger(df, period=20): + sma = df['Close'].rolling(window=period).mean() + std = df['Close'].rolling(window=period).std() + df['Bollinger_Upper'] = sma + (2 * std) + df['Bollinger_Lower'] = sma - (2 * std) + return df + +def calculate_atr(df, period=14): + high_low = df['High'] - df['Low'] + high_close = abs(df['High'] - df['Close'].shift()) + low_close = abs(df['Low'] - df['Close'].shift()) + tr = pd.concat([high_low, high_close, low_close], axis=1).max(axis=1) + df['ATR'] = tr.rolling(window=period).mean() + return df + +# === Condition Evaluation === + +def evaluate_condition(row, condition): + if condition["type"] != "LOGIC_COMPARE": + return False + + op = condition.get("operator") + left = condition.get("left", {}) + right = condition.get("right") + typ = left.get("type") + period = left.get("period", 14) + + # Extract left-side value + if typ == "RSI": + value = row.get("RSI") + elif typ == "SMA": + value = row.get("SMA") + elif typ == "EMA": + value = row.get(f"EMA_{period}") + elif typ == "MACD": + value = row.get("MACD") + elif typ == "BOLLINGER": + band = left.get("band", "upper").upper() + value = row.get("Bollinger_Upper" if band == "UPPER" else "Bollinger_Lower") + elif typ == "ATR": + value = row.get("ATR") + else: + return False + + if pd.isna(value): + return False + + # Extract right-side value + if isinstance(right, dict): + r_typ = right.get("type") + r_period = right.get("period", 14) + if r_typ == "RSI": + right_val = row.get("RSI") + elif r_typ == "SMA": + right_val = row.get("SMA") + elif r_typ == "EMA": + right_val = row.get(f"EMA_{r_period}") + elif r_typ == "MACD": + right_val = row.get("MACD") + elif r_typ == "ATR": + right_val = row.get("ATR") + else: + right_val = None + else: + right_val = right + + if right_val is None or pd.isna(right_val): + return False + + if op == "GT": + return value > right_val + elif op == "GTE": + return value >= right_val + elif op == "LT": + return value < right_val + elif op == "LTE": + return value <= right_val + elif op == "EQ": + return value == right_val + + return False + +# === Strategy Rule Processing === + +def process_rule(row, rule): + if rule["type"] == "IF": + condition = rule.get("condition") + if evaluate_condition(row, condition): + return process_rule(row, rule.get("do", {})) + elif rule["type"] == "BUY": + return "BUY" + elif rule["type"] == "SELL": + return "SELL" + return None + +# === Backtest Engine === + +def run_backtest(symbol, start_date, end_date, strategy_json, initial_balance): fetch_and_save_data(symbol, start_date, end_date) df = get_data(symbol, start_date, end_date) - if "Date" not in df.columns: - raise ValueError("'Date' column not found in the data") - df["Close"] = pd.to_numeric(df["Close"], errors="coerce") - df.dropna(subset=["Close"], inplace=True) + df["High"] = pd.to_numeric(df["High"], errors="coerce") + df["Low"] = pd.to_numeric(df["Low"], errors="coerce") + df.dropna(subset=["Close", "High", "Low"], inplace=True) + df["Date"] = pd.to_datetime(df["Date"]) df.set_index("Date", inplace=True) - # 🛠 Apply indicators (SMA/RSI) + # Precompute indicators for rule in strategy_json: - if rule["type"] == "IF": - cond = rule["condition"] - if cond["type"] == "SMA": - period = cond["period"] - df["SMA"] = df["Close"].rolling(window=period).mean() - elif cond["type"] == "RSI": - period = cond.get("period", 14) - df = calculate_rsi(df, period) - - # 💼 Simulate trades - balance = 10000 + def collect_indicators(r): + if r["type"] == "IF": + cond = r["condition"] + left = cond.get("left", {}) + typ = left.get("type") + period = left.get("period", 14) + + if typ == "RSI": + calculate_rsi(df, period) + elif typ == "SMA": + calculate_sma(df, period) + elif typ == "EMA": + calculate_ema(df, period) + elif typ == "MACD": + calculate_macd(df) + elif typ == "BOLLINGER": + calculate_bollinger(df, period) + elif typ == "ATR": + calculate_atr(df, period) + + collect_indicators(r.get("do", {})) + collect_indicators(rule) + + balance = initial_balance position = None entry_price = 0 trades = [] @@ -50,32 +378,8 @@ def run_backtest(symbol, start_date, end_date, strategy_json): close = row["Close"] for rule in strategy_json: - if rule["type"] != "IF": - continue - - cond = rule["condition"] - action = rule["do"]["type"] - signal = None - - # ➕ SMA condition - if cond["type"] == "SMA": - sma = row.get("SMA") - if pd.isna(sma): continue - op, val = cond["operator"], cond.get("right", 0) - if op == "GT" and close > sma: signal = action - elif op == "LT" and close < sma: signal = action - elif op == "EQ" and close == sma: signal = action - - # ➕ RSI condition - elif cond["type"] == "RSI": - rsi = row.get("RSI") - if pd.isna(rsi): continue - op, val = cond["operator"], cond.get("right", 0) - if op == "GT" and rsi > val: signal = action - elif op == "LT" and rsi < val: signal = action - elif op == "EQ" and rsi == val: signal = action - - # 🟢 BUY + signal = process_rule(row, rule) + if signal == "BUY" and position is None: entry_price = close position = close @@ -85,7 +389,6 @@ def run_backtest(symbol, start_date, end_date, strategy_json): "price": round(close, 2) }) - # 🔴 SELL elif signal == "SELL" and position is not None: profit = close - entry_price balance += profit @@ -97,14 +400,13 @@ def run_backtest(symbol, start_date, end_date, strategy_json): }) position = None - # 📊 Metrics final_balance = round(balance, 2) returns = df["Close"].pct_change().dropna() sharpe = (returns.mean() / returns.std()) * (252 ** 0.5) if returns.std() else 0 return { "final_balance": float(final_balance), - "starting_balance": 10000.0, + "starting_balance": float(initial_balance), "total_trades": len(trades), "sharpe_ratio": round(sharpe, 2), "trades": [ diff --git a/backend/venv/Lib/site-packages/bs4/__pycache__/__init__.cpython-312.pyc b/backend/venv/Lib/site-packages/bs4/__pycache__/__init__.cpython-312.pyc index 4417f548cf42bde234d94775e5b75608a44faa3b..8d7afdca326f1727a9b69e3a20ea6150eb63e960 100644 GIT binary patch delta 23 dcmX@GmFd7%CZ5y0yj%=Gps&W5v5{xXEC5!M2D1PF delta 23 dcmX@GmFd7%CZ5y0yj%=G;B@(a`bM5DvjAb$2yg%Z diff --git a/backend/venv/Lib/site-packages/bs4/__pycache__/element.cpython-312.pyc b/backend/venv/Lib/site-packages/bs4/__pycache__/element.cpython-312.pyc index 0d8161c86f8207dfdd949f11e536a2245c50eb35..0be70790ad398406c6340ececb0b3aecc67d890e 100644 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a/backend/venv/Lib/site-packages/python_multipart/__pycache__/exceptions.cpython-312.pyc b/backend/venv/Lib/site-packages/python_multipart/__pycache__/exceptions.cpython-312.pyc index 0d83a87a3106641d9fb750670a2e03cbf0570d1e..035b782b0ae87f8d460e14f5c7a4904398a15ea2 100644 GIT binary patch delta 21 bcmX@ld!Co)G%qg~0}vRhF=lM!Im`wCI_3oW delta 21 bcmX@ld!Co)G%qg~0}yy#{-3^)=P(-pMoxk>$ih7M|0*yj%=GV5r8J(a5uvhj9-F0AvUTi2wiq delta 26 gcmX>xk>$ih7M|0*yj%=G;CcCfdLz$P9>zT!0CczrO8@`> diff --git a/frontend/src/App.js b/frontend/src/App.js index 371178d7..0b37c1a5 100644 --- a/frontend/src/App.js +++ b/frontend/src/App.js @@ -1,93 +1,5 @@ -// import React, { useState } from 'react'; -// import BlocklyEditor from './components/BlocklyEditor'; -// function App() { -// const [code, setCode] = useState(""); -// return ( -//
-//

AlgoBlocks 🔥

-// -//

Generated Code:

-// 
{code}
-//
-// ); -// } - -// export default App; - -// import React, { useState } from 'react'; -// import BlocklyEditor from './components/BlocklyEditor'; - -// import axios from 'axios'; - -// function App() { -// const [codeJson, setCodeJson] = useState(''); -// const [startDate, setStartDate] = useState(''); -// const [endDate, setEndDate] = useState(''); -// const [stockSymbol, setStockSymbol] = useState(''); - -// const handleBacktest = async () => { -// if (!stockSymbol || !startDate || !endDate || !codeJson) { -// alert("Please fill in stock symbol, dates, and strategy blocks."); -// return; -// } - -// try { -// // Ensure codeJson is a valid object, not a string. -// // If it's a string, parse it to a valid object. -// const parsedCode = typeof codeJson === 'string' ? JSON.parse(codeJson) : codeJson; - -// const payload = { -// symbol: stockSymbol.trim(), -// start_date: startDate.trim(), -// end_date: endDate.trim(), -// code: parsedCode, // Send the parsed codeJson as an object -// }; - -// console.log("Sending payload:", payload); - -// const response = await axios.post('http://localhost:8000/api/backtest', payload); - -// alert("✅ Backtest complete:\n" + JSON.stringify(response.data, null, 2)); -// } catch (error) { -// console.error('❌ Backtest failed:', error); -// if (error.response) { -// console.log("Response error data:", error.response.data); -// alert("❌ " + JSON.stringify(error.response.data, null, 2)); -// } else { -// alert("❌ Network or JSON parse error."); -// } -// } -// }; - -// return ( -//
-//

AlgoBlocks 🔥

- -//
-// -// setStockSymbol(e.target.value)} placeholder="AAPL" /> -//
-// -// setStartDate(e.target.value)} /> -//
-// -// setEndDate(e.target.value)} /> -//
- -// - -//
-// -//
- -// 
Generated Code:
{codeJson}
-//
-// ); -// } - -// export default App; import React, { useState } from 'react'; import BlocklyEditor from './components/BlocklyEditor'; @@ -98,10 +10,12 @@ function App() { const [startDate, setStartDate] = useState(''); const [endDate, setEndDate] = useState(''); const [stockSymbol, setStockSymbol] = useState(''); + const [initialBalance, setInitialBalance] = useState(10000); // ✅ New state + const [result, setResult] = useState(null); const handleBacktest = async () => { - if (!stockSymbol || !startDate || !endDate || !codeJson) { - alert("Please fill in stock symbol, dates, and strategy blocks."); + if (!stockSymbol || !startDate || !endDate || !codeJson || !initialBalance) { + alert("Please fill in all fields including balance."); return; } @@ -112,23 +26,18 @@ function App() { symbol: stockSymbol.trim(), start_date: startDate.trim(), end_date: endDate.trim(), + initial_balance: parseFloat(initialBalance), // ✅ Send balance code: parsedCode, }; - console.log("🔄 Parsed codeJson:", parsedCode); console.log("📦 Sending payload:", JSON.stringify(payload, null, 2)); const response = await axios.post('http://localhost:8000/api/backtest', payload); console.log("✅ Backtest success:", response.data); - alert("✅ Backtest complete:\n" + JSON.stringify(response.data, null, 2)); + setResult(response.data); } catch (error) { console.error('❌ Backtest failed:', error); - if (error.response) { - console.log("🧾 Response error data:", error.response.data); - alert("❌ " + JSON.stringify(error.response.data, null, 2)); - } else { - alert("❌ Network or JSON parse error."); - } + setResult({ error: error.response?.data || "Network or parsing error." }); } }; @@ -138,13 +47,16 @@ function App() {
- setStockSymbol(e.target.value)} placeholder="AAPL" /> + setStockSymbol(e.target.value)} placeholder="e.g. AAPL" />
setStartDate(e.target.value)} />
setEndDate(e.target.value)} /> +
+ + setInitialBalance(e.target.value)} />
@@ -153,9 +65,14 @@ function App() { - 
Generated Code:
{codeJson}
+ {result && ( +
+ 📊 Backtest Result:
+ {typeof result === 'object' ? JSON.stringify(result, null, 2) : result} +
+ )} ); } -export default App; +export default App; \ No newline at end of file diff --git a/frontend/src/components/BlocklyEditor.js b/frontend/src/components/BlocklyEditor.js index a20ce7c4..d49a8be6 100644 --- a/frontend/src/components/BlocklyEditor.js +++ b/frontend/src/components/BlocklyEditor.js @@ -1,74 +1,4 @@ -// import React, { useRef, useEffect } from "react"; -// import * as Blockly from "blockly"; -// import { javascriptGenerator } from "blockly/javascript"; -// import { jsonGenerator } from '../generators/jsonGenerator'; -// import { defineCustomBlocks } from './customBlocks'; - -// function BlocklyEditor({ onCodeChange }) { -// const blocklyDiv = useRef(null); - -// // ✅ Toolbox with Categories -// const toolbox = { -// kind: "categoryToolbox", -// contents: [ -// { -// kind: "category", -// name: "Logic", -// colour: "#5C81A6", -// contents: [ -// { kind: "block", type: "controls_if" }, -// { kind: "block", type: "logic_compare" }, -// ], -// }, -// { -// kind: "category", -// name: "Math", -// colour: "#5CA65C", -// contents: [ -// { kind: "block", type: "math_number" }, -// ], -// }, -// { -// kind: "category", -// name: "Indicators", -// colour: "#A65C81", -// contents: [ -// { kind: "block", type: "rsi_block" }, -// { kind: "block", type: "sma_block" }, -// ], -// }, -// { -// kind: "category", -// name: "Actions", -// colour: "#A6745C", -// contents: [ -// { kind: "block", type: "buy_block" }, -// { kind: "block", type: "sell_block" }, -// ], -// }, -// ], -// }; - -// useEffect(() => { -// defineCustomBlocks(); // ✅ Register custom blocks before injecting Blockly - -// const workspace = Blockly.inject(blocklyDiv.current, { -// toolbox: toolbox, -// }); - -// workspace.addChangeListener(() => { -// const json = jsonGenerator.workspaceToJson(workspace); -// onCodeChange(JSON.stringify(json, null, 2)); // ✅ send JSON to parent -// }); - -// return () => workspace.dispose(); -// }, [onCodeChange]); - -// return
; -// } - -// export default BlocklyEditor; import React, { useRef, useEffect } from "react"; import * as Blockly from "blockly"; @@ -111,7 +41,7 @@ function BlocklyEditor({ onCodeChange }) { { kind: "block", type: "macd_block" }, { kind: "block", type: "bollinger_block" }, { kind: "block", type: "atr_block" }, - { kind: "block", type: "stochastic_block" }, + // { kind: "block", type: "stochastic_block" }, ], }, { diff --git a/frontend/src/components/StrategySelector.js b/frontend/src/components/StrategySelector.js index 26433e35..64ba8a32 100644 --- a/frontend/src/components/StrategySelector.js +++ b/frontend/src/components/StrategySelector.js @@ -1,69 +1,4 @@ -// import React, { useState } from 'react'; -// function StrategySelector({ onSubmit }) { -// const [indicator, setIndicator] = useState('SMA'); -// const [condition, setCondition] = useState('>'); -// const [value, setValue] = useState(20); -// const [stock, setStock] = useState('AAPL'); - -// const handleSubmit = (e) => { -// e.preventDefault(); - -// const strategy = { -// stock, -// conditions: [ -// { -// indicator: indicator.toLowerCase(), -// condition, -// value: parseFloat(value), -// }, -// ], -// }; - -// onSubmit(strategy); -// }; - -// return ( -//
-//

Build Your Strategy 🧱

- -// -// setStock(e.target.value)} -// placeholder="e.g. AAPL" -// /> -//

- -// -// -//

- -// -// -//

- -// -// setValue(e.target.value)} -// /> -//

- -// -//
-// ); -// } - -// export default StrategySelector; import React, { useState } from 'react'; diff --git a/frontend/src/components/customBlocks.js b/frontend/src/components/customBlocks.js index 055a4ad9..d522e8c3 100644 --- a/frontend/src/components/customBlocks.js +++ b/frontend/src/components/customBlocks.js @@ -1,60 +1,3 @@ -// import * as Blockly from 'blockly'; - -// export function defineCustomBlocks() { -// // RSI Block -// Blockly.Blocks['rsi_block'] = { -// init: function () { -// this.appendDummyInput() -// .appendField("RSI") -// .appendField("Period") -// .appendField(new Blockly.FieldNumber(14, 1), "PERIOD"); -// this.setOutput(true, "Number"); -// this.setColour(230); -// this.setTooltip("Calculates RSI"); -// this.setHelpUrl(""); -// }, -// }; - -// // ✅ SMA Block -// Blockly.Blocks['sma_block'] = { -// init: function () { -// this.appendDummyInput() -// .appendField("SMA") -// .appendField("Period") -// .appendField(new Blockly.FieldNumber(20, 1), "PERIOD"); -// this.setOutput(true, "Number"); -// this.setColour(230); -// this.setTooltip("Simple Moving Average"); -// this.setHelpUrl(""); -// }, -// }; - -// // ✅ Buy Block -// Blockly.Blocks['buy_block'] = { -// init: function () { -// this.appendDummyInput() -// .appendField("BUY"); -// this.setPreviousStatement(true, null); -// this.setNextStatement(true, null); -// this.setColour(120); -// this.setTooltip("Place a buy order"); -// this.setHelpUrl(""); -// }, -// }; - -// // ✅ Sell Block -// Blockly.Blocks['sell_block'] = { -// init: function () { -// this.appendDummyInput() -// .appendField("SELL"); -// this.setPreviousStatement(true, null); -// this.setNextStatement(true, null); -// this.setColour(0); -// this.setTooltip("Place a sell order"); -// this.setHelpUrl(""); -// }, -// }; -// } import * as Blockly from 'blockly'; @@ -149,21 +92,39 @@ export function defineCustomBlocks() { }, }; - // ✅ Stochastic Oscillator Block - Blockly.Blocks['stochastic_block'] = { - init: function () { - this.appendDummyInput() - .appendField("Stochastic") - .appendField("K Period") - .appendField(new Blockly.FieldNumber(14, 1), "KPERIOD") - .appendField("D Period") - .appendField(new Blockly.FieldNumber(3, 1), "DPERIOD"); - this.setOutput(true, "Number"); - this.setColour(230); - this.setTooltip("Stochastic Oscillator"); - this.setHelpUrl(""); - }, - }; + // // ✅ Stochastic Oscillator Block + // Blockly.Blocks['stochastic_block'] = { + // init: function () { + // this.appendDummyInput() + // .appendField("Stochastic") + // .appendField("K Period") + // .appendField(new Blockly.FieldNumber(14, 1), "KPERIOD") + // .appendField("D Period") + // .appendField(new Blockly.FieldNumber(3, 1), "DPERIOD"); + // this.setOutput(true, "Number"); + // this.setColour(230); + // this.setTooltip("Stochastic Oscillator"); + // this.setHelpUrl(""); + // }, + // }; + + // Blockly.Blocks['stochastic_block'] = { + // init: function () { + // this.appendDummyInput() + // .appendField("Stochastic") + // .appendField("K Period") + // .appendField(new Blockly.FieldNumber(14, 1), "KPERIOD") + // .appendField("D Period") + // .appendField(new Blockly.FieldNumber(3, 1), "DPERIOD") + // .appendField("Target") + // .appendField(new Blockly.FieldNumber(80, 1, 100), "TARGET"); // Added target with default value + // this.setOutput(true, "Number"); + // this.setColour(230); + // this.setTooltip("Stochastic Oscillator"); + // this.setHelpUrl(""); + // }, + // }; + // ✅ Buy Block Blockly.Blocks['buy_block'] = { diff --git a/frontend/src/generators/jsonGenerator.js b/frontend/src/generators/jsonGenerator.js index 0e03b963..4476a08e 100644 --- a/frontend/src/generators/jsonGenerator.js +++ b/frontend/src/generators/jsonGenerator.js @@ -1,81 +1,4 @@ -// import * as Blockly from 'blockly'; - -// export const jsonGenerator = { -// workspaceToJson(workspace) { -// const topBlocks = workspace.getTopBlocks(true); -// return topBlocks.map(block => parseBlock(block)).filter(b => b !== null); -// } -// }; - -// function parseBlock(block) { -// if (!block) return null; - -// switch (block.type) { -// case 'controls_if': { -// const conditionBlock = block.getInputTargetBlock('IF0'); -// const doBlock = block.getInputTargetBlock('DO0'); - -// return { -// type: 'IF', -// condition: parseBlock(conditionBlock), -// do: parseBlock(doBlock), -// }; -// } - -// case 'logic_compare': { -// const operator = block.getFieldValue('OP'); -// const left = parseBlock(block.getInputTargetBlock('A')); -// const right = parseBlock(block.getInputTargetBlock('B')); - -// return { -// type: 'LOGIC_COMPARE', -// operator: operator, -// left: left, -// right: right -// }; -// } - -// case 'rsi_block': { -// const period = block.getFieldValue('PERIOD'); -// return { -// type: 'RSI', -// period: parseInt(period, 10) -// }; -// } - -// case 'sma_block': { -// const period = block.getFieldValue('PERIOD'); -// return { -// type: 'SMA', -// period: parseInt(period, 10) -// }; -// } - -// case 'ema_block': { -// const period = block.getFieldValue('PERIOD'); -// return { -// type: 'EMA', -// period: parseInt(period, 10) -// }; -// } - -// case 'buy_block': -// return { type: 'BUY' }; - -// case 'sell_block': -// return { type: 'SELL' }; - -// case 'math_number': { -// const num = block.getFieldValue('NUM'); -// return parseFloat(num); -// } - -// default: -// return { -// type: block.type -// }; -// } -// } + import * as Blockly from 'blockly'; @@ -166,16 +89,33 @@ function parseBlock(block) { }; } + // case 'stochastic_block': { + // const kPeriod = parseInt(block.getFieldValue('K_PERIOD')); + // const dPeriod = parseInt(block.getFieldValue('D_PERIOD')); + // const target = block.getFieldValue('TARGET'); // "%K" or "%D" + // return { + // type: 'STOCHASTIC', + // kPeriod: parseInt(kPeriod), + // dPeriod: parseInt(dPeriod), + // target: target + // }; + // } case 'stochastic_block': { - const kPeriod = parseInt(block.getFieldValue('K_PERIOD'), 10); - const dPeriod = parseInt(block.getFieldValue('D_PERIOD'), 10); + const kPeriod = block.getFieldValue('KPERIOD'); + const dPeriod = block.getFieldValue('DPERIOD'); + const target = block.getFieldValue('TARGET'); // Capture the target value + + // Use a fallback if target is invalid + const parsedTarget = (target && !isNaN(target)) ? parseInt(target, 10) : 80; // Default to 80 if invalid + return { type: 'STOCHASTIC', - kPeriod, - dPeriod, + kPeriod: parseInt(kPeriod, 10), + dPeriod: parseInt(dPeriod, 10), + target: parsedTarget // Ensure target is not null }; } - + case 'buy_block': return { type: 'BUY' };