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* add chart to correlation matrix * lint * handling for data.results without chart --------- Co-authored-by: Igor Radovanovic <74266147+IgorWounds@users.noreply.github.com>
279 lines
7.9 KiB
Python
279 lines
7.9 KiB
Python
"""Test econometrics extension."""
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import base64
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import json
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import random
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from typing import Dict, Literal
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import pytest
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import requests
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from openbb_core.env import Env
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from openbb_core.provider.utils.helpers import get_querystring
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data: Dict = {}
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def get_headers():
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"""Get the headers for the API request."""
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if "headers" in data:
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return data["headers"]
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userpass = f"{Env().API_USERNAME}:{Env().API_PASSWORD}"
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userpass_bytes = userpass.encode("ascii")
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base64_bytes = base64.b64encode(userpass_bytes)
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data["headers"] = {"Authorization": f"Basic {base64_bytes.decode('ascii')}"}
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return data["headers"]
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def request_data(menu: str, symbol: str, provider: str):
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"""Randomly pick a symbol and a provider and get data from the selected menu."""
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url = f"http://0.0.0.0:8000/api/v1/{menu}/price/historical?symbol={symbol}&provider={provider}"
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result = requests.get(url, headers=get_headers(), timeout=10)
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return result.json()["results"]
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def get_equity_data():
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"""Get equity data."""
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if "equity_data" in data:
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return data["equity_data"]
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symbol = random.choice(["AAPL", "NVDA", "MSFT", "TSLA", "AMZN", "V"]) # noqa: S311
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provider = random.choice(["fmp", "intrinio", "polygon"]) # noqa: S311
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data["equity_data"] = request_data("equity", symbol=symbol, provider=provider)
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return data["equity_data"]
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def get_crypto_data():
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"""Get crypto data."""
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if "crypto_data" in data:
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return data["crypto_data"]
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# TODO : add more crypto providers and symbols
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symbol = random.choice(["BTCUSD"]) # noqa: S311
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provider = random.choice(["fmp"]) # noqa: S311
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data["crypto_data"] = request_data(
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menu="crypto",
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symbol=symbol,
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provider=provider,
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)
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return data["crypto_data"]
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def get_data(menu: Literal["equity", "crypto"]):
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"""Get data based on the selected menu."""
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funcs = {"equity": get_equity_data, "crypto": get_crypto_data}
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return funcs[menu]()
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@pytest.mark.parametrize(
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"params, data_type",
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[
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({"data": "", "method": "pearson"}, "equity"),
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({"data": "", "method": "pearson"}, "crypto"),
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],
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)
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@pytest.mark.integration
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def test_econometrics_correlation_matrix(params, data_type):
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"""Test the correlation matrix endpoint."""
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params = {p: v for p, v in params.items() if v}
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body = json.dumps(get_data(data_type))
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query_str = get_querystring(params, [])
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url = f"http://0.0.0.0:8000/api/v1/econometrics/correlation_matrix?{query_str}"
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result = requests.post(url, headers=get_headers(), timeout=10, data=body)
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assert isinstance(result, requests.Response)
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assert result.status_code == 200
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@pytest.mark.parametrize(
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"params, data_type",
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[
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(
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{"data": "", "y_column": "close", "x_columns": ["high"]},
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"equity",
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),
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(
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{"data": "", "y_column": "close", "x_columns": ["high"]},
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"crypto",
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),
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],
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)
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@pytest.mark.integration
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def test_econometrics_ols_regression_summary(params, data_type):
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"""Test the OLS regression summary endpoint."""
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params = {p: v for p, v in params.items() if v}
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body = json.dumps(
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{
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"data": get_data(data_type),
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"x_columns": params.pop("x_columns"),
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}
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)
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query_str = get_querystring(params, [])
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url = f"http://0.0.0.0:8000/api/v1/econometrics/ols_regression_summary?{query_str}"
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result = requests.post(url, headers=get_headers(), timeout=20, data=body)
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assert isinstance(result, requests.Response)
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assert result.status_code == 200
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@pytest.mark.parametrize(
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"params, data_type",
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[
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(
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{"data": "", "y_column": "volume", "x_columns": ["close"]},
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"equity",
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),
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(
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{"data": "", "y_column": "volume", "x_columns": ["close"]},
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"crypto",
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),
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],
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)
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@pytest.mark.integration
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def test_econometrics_autocorrelation(params, data_type):
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"""Test the autocorrelation endpoint."""
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params = {p: v for p, v in params.items() if v}
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body = json.dumps(
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{
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"data": get_data(data_type),
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"x_columns": params.pop("x_columns"),
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}
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)
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query_str = get_querystring(params, [])
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url = f"http://0.0.0.0:8000/api/v1/econometrics/autocorrelation?{query_str}"
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result = requests.post(url, headers=get_headers(), timeout=10, data=body)
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assert isinstance(result, requests.Response)
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assert result.status_code == 200
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@pytest.mark.parametrize(
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"params, data_type",
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[
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(
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{
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"data": "",
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"y_column": "volume",
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"x_columns": ["close"],
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"lags": "",
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},
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"equity",
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),
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(
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{
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"data": "",
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"y_column": "volume",
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"x_columns": ["close"],
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"lags": "2",
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},
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"crypto",
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),
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],
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)
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@pytest.mark.integration
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def test_econometrics_residual_autocorrelation(params, data_type):
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"""Test the residual autocorrelation endpoint."""
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params = {p: v for p, v in params.items() if v}
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body = json.dumps(
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{
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"data": get_data(data_type),
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"x_columns": params.pop("x_columns"),
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}
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)
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query_str = get_querystring(params, [])
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url = (
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f"http://0.0.0.0:8000/api/v1/econometrics/residual_autocorrelation?{query_str}"
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)
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result = requests.post(url, headers=get_headers(), timeout=10, data=body)
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assert isinstance(result, requests.Response)
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assert result.status_code == 200
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@pytest.mark.parametrize(
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"params, data_type",
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[
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(
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{
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"data": "",
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"columns": ["close", "volume"],
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},
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"equity",
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),
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(
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{
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"data": "",
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"columns": ["close", "volume"],
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},
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"crypto",
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),
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],
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)
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@pytest.mark.integration
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def test_econometrics_cointegration(params, data_type):
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"""Test the cointegration endpoint."""
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params = {p: v for p, v in params.items() if v}
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body = json.dumps(
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{
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"data": get_data(data_type),
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"columns": params.pop("columns"),
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}
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)
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query_str = get_querystring(params, [])
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url = f"http://0.0.0.0:8000/api/v1/econometrics/cointegration?{query_str}"
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result = requests.post(url, headers=get_headers(), timeout=10, data=body)
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assert isinstance(result, requests.Response)
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assert result.status_code == 200
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@pytest.mark.parametrize(
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"params, data_type",
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[
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(
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{"data": "", "y_column": "volume", "x_column": "close", "lag": ""},
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"equity",
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),
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(
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{"data": "", "y_column": "volume", "x_column": "close", "lag": "2"},
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"crypto",
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),
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],
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)
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@pytest.mark.integration
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def test_econometrics_causality(params, data_type):
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"""Test the causality endpoint."""
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params = {p: v for p, v in params.items() if v}
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body = json.dumps(get_data(data_type))
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query_str = get_querystring(params, [])
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url = f"http://0.0.0.0:8000/api/v1/econometrics/causality?{query_str}"
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result = requests.post(url, headers=get_headers(), timeout=10, data=body)
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assert isinstance(result, requests.Response)
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assert result.status_code == 200
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@pytest.mark.parametrize(
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"params, data_type",
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[({"data": "", "column": "high", "regression": "c"}, "equity")],
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)
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@pytest.mark.integration
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def test_econometrics_unit_root(params, data_type):
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"""Test the unit root endpoint."""
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params = {p: v for p, v in params.items() if v}
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body = json.dumps(get_data(data_type))
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query_str = get_querystring(params, [])
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url = f"http://0.0.0.0:8000/api/v1/econometrics/unit_root?{query_str}"
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result = requests.post(url, headers=get_headers(), timeout=10, data=body)
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assert isinstance(result, requests.Response)
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assert result.status_code == 200
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