| """Integration tests for the quantitative extension.""" |
|
|
| 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 |
|
|
| |
|
|
| data: dict = {} |
|
|
|
|
| def get_headers(): |
| """Get the headers for the API request.""" |
| 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(): |
| """Get stocks data.""" |
| if "stocks_data" in data: |
| return data["stocks_data"] |
|
|
| symbol = random.choice(["AAPL", "NVDA", "MSFT", "TSLA", "AMZN", "V"]) |
| provider = random.choice(["fmp", "polygon", "yfinance"]) |
|
|
| 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(): |
| """Get crypto data.""" |
| if "crypto_data" in data: |
| return data["crypto_data"] |
|
|
| |
| symbol = random.choice(["BTCUSD"]) |
| provider = random.choice(["fmp"]) |
|
|
| 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"]): |
| """Get data based on the selected menu.""" |
| 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): |
| """Test the normality endpoint.""" |
| 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): |
| """Test the CAPM endpoint.""" |
| 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): |
| """Test the Omega Ratio endpoint.""" |
| 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): |
| """Test the rolling kurtosis endpoint.""" |
| 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): |
| """Test the unit root test endpoint.""" |
| 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": "100", |
| "index": "date", |
| }, |
| "equity", |
| ), |
| ( |
| { |
| "data": "", |
| "target": "high", |
| "rfr": "0.5", |
| "window": "150", |
| "index": "date", |
| }, |
| "crypto", |
| ), |
| ], |
| ) |
| @pytest.mark.integration |
| def test_quantitative_performance_sharpe_ratio(params, data_type): |
| """Test the Sharpe Ratio endpoint.""" |
| 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": "100", |
| "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): |
| """Test the Sortino Ratio endpoint.""" |
| 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): |
| """Test the rolling skew endpoint.""" |
| 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): |
| """Test the rolling variance endpoint.""" |
| 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): |
| """Test the rolling standard deviation endpoint.""" |
| 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): |
| """Test the rolling mean endpoint.""" |
| 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): |
| """Test the rolling quantile endpoint.""" |
| 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): |
| """Test the summary endpoint.""" |
| 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 |
|
|
|
|
| |
| |
| |
|
|
|
|
| @parametrize( |
| "params, data_type", |
| [ |
| ({"data": "", "target": "close", "index": "date"}, "equity"), |
| ], |
| ) |
| @pytest.mark.integration |
| def test_quantitative_stats_skew(params, data_type): |
| """Test the skew endpoint.""" |
| 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): |
| """Test the kurtosis endpoint.""" |
| 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): |
| """Test the mean endpoint.""" |
| 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): |
| """Test the standard deviation endpoint.""" |
| 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): |
| """Test the variance endpoint.""" |
| 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): |
| """Test the quantile endpoint.""" |
| 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 |
|
|