import base64 import json import random from typing import Literal import pytest import requests from extensions.tests.conftest import parametrize from openbb_core.env import Env from openbb_core.provider.utils.helpers import get_querystring # pylint:disable=redefined-outer-name data: dict = {} def get_headers(): if "headers" in data: return data["headers"] userpass = f"{Env().API_USERNAME}:{Env().API_PASSWORD}" userpass_bytes = userpass.encode("ascii") base64_bytes = base64.b64encode(userpass_bytes) data["headers"] = {"Authorization": f"Basic {base64_bytes.decode('ascii')}"} return data["headers"] def request_data( menu: str, symbol: str, provider: str, start_date: str = "", end_date: str = "" ): """Randomly pick a symbol and a provider and get data from the selected menu.""" url = f"http://0.0.0.0:8000/api/v1/{menu}/price/historical?symbol={symbol}&provider={provider}&start_date={start_date}&end_date={end_date}" result = requests.get(url, headers=get_headers(), timeout=10) return result.json()["results"] def get_stocks_data(): if "stocks_data" in data: return data["stocks_data"] symbol = random.choice(["AAPL", "NVDA", "MSFT", "TSLA", "AMZN", "V"]) # noqa: S311 provider = random.choice(["fmp", "polygon", "yfinance"]) # noqa: S311 data["stocks_data"] = request_data( menu="equity", symbol=symbol, provider=provider, start_date="2023-01-01", end_date="2023-12-31", ) return data["stocks_data"] def get_crypto_data(): if "crypto_data" in data: return data["crypto_data"] # TODO : add more crypto providers and symbols symbol = random.choice(["BTCUSD"]) # noqa: S311 provider = random.choice(["fmp"]) # noqa: S311 data["crypto_data"] = request_data( menu="crypto", symbol=symbol, provider=provider, start_date="2023-01-01", end_date="2023-12-31", ) return data["crypto_data"] def get_data(menu: Literal["equity", "crypto"]): funcs = {"equity": get_stocks_data, "crypto": get_crypto_data} return funcs[menu]() @parametrize( "params, data_type", [ ({"data": "", "target": "close"}, "equity"), ({"data": "", "target": "high"}, "crypto"), ], ) @pytest.mark.integration def test_quantitative_normality(params, data_type): params = {p: v for p, v in params.items() if v} data = json.dumps(get_data(data_type)) query_str = get_querystring(params, []) url = f"http://0.0.0.0:8000/api/v1/quantitative/normality?{query_str}" result = requests.post(url, headers=get_headers(), timeout=10, data=data) assert isinstance(result, requests.Response) assert result.status_code == 200 @parametrize( "params, data_type", [ ({"data": "", "target": "high"}, "equity"), ({"data": "", "target": "high"}, "crypto"), ], ) @pytest.mark.integration def test_quantitative_capm(params, data_type): params = {p: v for p, v in params.items() if v} data = json.dumps(get_data(data_type)) query_str = get_querystring(params, []) url = f"http://0.0.0.0:8000/api/v1/quantitative/capm?{query_str}" result = requests.post(url, headers=get_headers(), timeout=10, data=data) assert isinstance(result, requests.Response) assert result.status_code == 200 @parametrize( "params, data_type", [ ( { "data": "", "target": "close", "threshold_start": "", "threshold_end": "", }, "equity", ), ( { "data": "", "target": "high", "threshold_start": "0.1", "threshold_end": "1.6", }, "crypto", ), ], ) @pytest.mark.integration def test_quantitative_performance_omega_ratio(params, data_type): params = {p: v for p, v in params.items() if v} data = json.dumps(get_data(data_type)) query_str = get_querystring(params, []) url = f"http://0.0.0.0:8000/api/v1/quantitative/performance/omega_ratio?{query_str}" result = requests.post(url, headers=get_headers(), timeout=10, data=data) assert isinstance(result, requests.Response) assert result.status_code == 200 @parametrize( "params, data_type", [ ({"data": "", "target": "close", "window": "5", "index": "date"}, "equity"), ({"data": "", "target": "high", "window": "10", "index": "date"}, "crypto"), ], ) @pytest.mark.integration def test_quantitative_rolling_kurtosis(params, data_type): params = {p: v for p, v in params.items() if v} data = json.dumps(get_data(data_type)) query_str = get_querystring(params, []) url = f"http://0.0.0.0:8000/api/v1/quantitative/rolling/kurtosis?{query_str}" result = requests.post(url, headers=get_headers(), timeout=10, data=data) assert isinstance(result, requests.Response) assert result.status_code == 200 @parametrize( "params, data_type", [ ( { "data": "", "target": "close", "fuller_reg": "c", "kpss_reg": "ct", }, "equity", ), ( { "data": "", "target": "high", "fuller_reg": "ct", "kpss_reg": "c", }, "crypto", ), ], ) @pytest.mark.integration def test_quantitative_unitroot_test(params, data_type): params = {p: v for p, v in params.items() if v} data = json.dumps(get_data(data_type)) query_str = get_querystring(params, []) url = f"http://0.0.0.0:8000/api/v1/quantitative/unitroot_test?{query_str}" result = requests.post(url, headers=get_headers(), timeout=10, data=data) assert isinstance(result, requests.Response) assert result.status_code == 200 @parametrize( "params, data_type", [ ( {"data": "", "target": "close", "rfr": "", "window": "", "index": "date"}, "equity", ), ( { "data": "", "target": "high", "rfr": "0.5", "window": "250", "index": "date", }, "crypto", ), ], ) @pytest.mark.integration def test_quantitative_performance_sharpe_ratio(params, data_type): params = {p: v for p, v in params.items() if v} data = json.dumps(get_data(data_type)) query_str = get_querystring(params, []) url = ( f"http://0.0.0.0:8000/api/v1/quantitative/performance/sharpe_ratio?{query_str}" ) result = requests.post(url, headers=get_headers(), timeout=10, data=data) assert isinstance(result, requests.Response) assert result.status_code == 200 @parametrize( "params, data_type", [ ( { "data": "", "target": "close", "target_return": "", "window": "", "adjusted": "", "index": "date", }, "equity", ), ( { "data": "", "target": "close", "target_return": "0.5", "window": "150", "adjusted": "true", "index": "date", }, "crypto", ), ], ) @pytest.mark.integration def test_quantitative_performance_sortino_ratio(params, data_type): params = {p: v for p, v in params.items() if v} data = json.dumps(get_data(data_type)) query_str = get_querystring(params, []) url = ( f"http://0.0.0.0:8000/api/v1/quantitative/performance/sortino_ratio?{query_str}" ) result = requests.post(url, headers=get_headers(), timeout=10, data=data) assert isinstance(result, requests.Response) assert result.status_code == 200 @parametrize( "params, data_type", [ ({"data": "", "target": "close", "window": "220", "index": "date"}, "equity"), ], ) @pytest.mark.integration def test_quantitative_rolling_skew(params, data_type): params = {p: v for p, v in params.items() if v} data = json.dumps(get_data(data_type)) query_str = get_querystring(params, []) url = f"http://0.0.0.0:8000/api/v1/quantitative/rolling/skew?{query_str}" result = requests.post(url, headers=get_headers(), timeout=60, data=data) assert isinstance(result, requests.Response) assert result.status_code == 200 @parametrize( "params, data_type", [ ({"data": "", "target": "close", "window": "220", "index": "date"}, "equity"), ], ) @pytest.mark.integration def test_quantitative_rolling_variance(params, data_type): params = {p: v for p, v in params.items() if v} data = json.dumps(get_data(data_type)) query_str = get_querystring(params, []) url = f"http://0.0.0.0:8000/api/v1/quantitative/rolling/variance?{query_str}" result = requests.post(url, headers=get_headers(), timeout=60, data=data) assert isinstance(result, requests.Response) assert result.status_code == 200 @parametrize( "params, data_type", [ ({"data": "", "target": "close", "window": "220", "index": "date"}, "equity"), ], ) @pytest.mark.integration def test_quantitative_rolling_stdev(params, data_type): params = {p: v for p, v in params.items() if v} data = json.dumps(get_data(data_type)) query_str = get_querystring(params, []) url = f"http://0.0.0.0:8000/api/v1/quantitative/rolling/stdev?{query_str}" result = requests.post(url, headers=get_headers(), timeout=60, data=data) assert isinstance(result, requests.Response) assert result.status_code == 200 @parametrize( "params, data_type", [ ({"data": "", "target": "close", "window": "220", "index": "date"}, "equity"), ], ) @pytest.mark.integration def test_quantitative_rolling_mean(params, data_type): params = {p: v for p, v in params.items() if v} data = json.dumps(get_data(data_type)) query_str = get_querystring(params, []) url = f"http://0.0.0.0:8000/api/v1/quantitative/rolling/mean?{query_str}" result = requests.post(url, headers=get_headers(), timeout=60, data=data) assert isinstance(result, requests.Response) assert result.status_code == 200 @parametrize( "params, data_type", [ ( { "data": "", "target": "close", "window": "10", "quantile_pct": "", "index": "date", }, "equity", ), ( { "data": "", "target": "high", "window": "50", "quantile_pct": "0.6", "index": "date", }, "crypto", ), ], ) @pytest.mark.integration def test_quantitative_rolling_quantile(params, data_type): params = {p: v for p, v in params.items() if v} data = json.dumps(get_data(data_type)) query_str = get_querystring(params, []) url = f"http://0.0.0.0:8000/api/v1/quantitative/rolling/quantile?{query_str}" result = requests.post(url, headers=get_headers(), timeout=10, data=data) assert isinstance(result, requests.Response) assert result.status_code == 200 @parametrize( "params, data_type", [ ({"data": "", "target": "close"}, "equity"), ({"data": "", "target": "high"}, "crypto"), ], ) @pytest.mark.integration def test_quantitative_summary(params, data_type): params = {p: v for p, v in params.items() if v} data = json.dumps(get_data(data_type)) query_str = get_querystring(params, []) url = f"http://0.0.0.0:8000/api/v1/quantitative/summary?{query_str}" result = requests.post(url, headers=get_headers(), timeout=10, data=data) assert isinstance(result, requests.Response) assert result.status_code == 200 ############ # quantitative/stats ############ @parametrize( "params, data_type", [ ({"data": "", "target": "close", "index": "date"}, "equity"), ], ) @pytest.mark.integration def test_quantitative_stats_skew(params, data_type): params = {p: v for p, v in params.items() if v} data = json.dumps(get_data(data_type)) query_str = get_querystring(params, []) url = f"http://0.0.0.0:8000/api/v1/quantitative/stats/skew?{query_str}" result = requests.post(url, headers=get_headers(), timeout=60, data=data) assert isinstance(result, requests.Response) assert result.status_code == 200 @parametrize( "params, data_type", [ ({"data": "", "target": "close", "index": "date"}, "equity"), ], ) @pytest.mark.integration def test_quantitative_stats_kurtosis(params, data_type): params = {p: v for p, v in params.items() if v} data = json.dumps(get_data(data_type)) query_str = get_querystring(params, []) url = f"http://0.0.0.0:8000/api/v1/quantitative/stats/kurtosis?{query_str}" result = requests.post(url, headers=get_headers(), timeout=60, data=data) assert isinstance(result, requests.Response) assert result.status_code == 200 @parametrize( "params, data_type", [ ({"data": "", "target": "close", "index": "date"}, "equity"), ], ) @pytest.mark.integration def test_quantitative_stats_mean(params, data_type): params = {p: v for p, v in params.items() if v} data = json.dumps(get_data(data_type)) query_str = get_querystring(params, []) url = f"http://0.0.0.0:8000/api/v1/quantitative/stats/mean?{query_str}" result = requests.post(url, headers=get_headers(), timeout=60, data=data) assert isinstance(result, requests.Response) assert result.status_code == 200 @parametrize( "params, data_type", [ ({"data": "", "target": "close", "index": "date"}, "equity"), ], ) @pytest.mark.integration def test_quantitative_stats_stdev(params, data_type): params = {p: v for p, v in params.items() if v} data = json.dumps(get_data(data_type)) query_str = get_querystring(params, []) url = f"http://0.0.0.0:8000/api/v1/quantitative/stats/stdev?{query_str}" result = requests.post(url, headers=get_headers(), timeout=60, data=data) assert isinstance(result, requests.Response) assert result.status_code == 200 @parametrize( "params, data_type", [ ({"data": "", "target": "close", "index": "date"}, "equity"), ], ) @pytest.mark.integration def test_quantitative_stats_variance(params, data_type): params = {p: v for p, v in params.items() if v} data = json.dumps(get_data(data_type)) query_str = get_querystring(params, []) url = f"http://0.0.0.0:8000/api/v1/quantitative/stats/variance?{query_str}" result = requests.post(url, headers=get_headers(), timeout=60, data=data) assert isinstance(result, requests.Response) assert result.status_code == 200 @parametrize( "params, data_type", [ ( { "data": "", "target": "close", "quantile_pct": "", "index": "date", }, "equity", ), ( { "data": "", "target": "high", "quantile_pct": "0.6", "index": "date", }, "crypto", ), ], ) @pytest.mark.integration def test_quantitative_stats_quantile(params, data_type): params = {p: v for p, v in params.items() if v} data = json.dumps(get_data(data_type)) query_str = get_querystring(params, []) url = f"http://0.0.0.0:8000/api/v1/quantitative/stats/quantile?{query_str}" result = requests.post(url, headers=get_headers(), timeout=10, data=data) assert isinstance(result, requests.Response) assert result.status_code == 200