Files
OpenBB/openbb_platform/extensions/quantitative/integration/test_quantitative_api.py
Igor Radovanovic 3d2a9cdb9a Introduce integration test modularity (#5865)
* Introduce integration test modularity

* Fix Python 3.9 error

* Add TODO

* Update generators

* Handle endpoints that only feature one provider that is not installed

* Fix failing unit test
2023-12-06 19:39:39 +00:00

321 lines
9.2 KiB
Python

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):
"""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}"
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("equity", symbol=symbol, provider=provider)
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(["BTC"]) # noqa: S311
provider = random.choice(["fmp"]) # noqa: S311
data["crypto_data"] = request_data(
menu="crypto",
symbol=symbol,
provider=provider,
)
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_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/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"}, "equity"),
({"data": "", "target": "high", "window": "10"}, "crypto"),
],
)
@pytest.mark.integration
def test_quantitative_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/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": ""}, "equity"),
({"data": "", "target": "high", "rfr": "0.5", "window": "250"}, "crypto"),
],
)
@pytest.mark.integration
def test_quantitative_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/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": "",
},
"equity",
),
(
{
"data": "",
"target": "close",
"target_return": "0.5",
"window": "275",
"adjusted": "true",
},
"crypto",
),
],
)
@pytest.mark.integration
def test_quantitative_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/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"}, "equity"),
],
)
@pytest.mark.integration
def test_quantitative_skewness(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/skewness?{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": "",
},
"equity",
),
(
{
"data": "",
"target": "high",
"window": "50",
"quantile_pct": "0.6",
},
"crypto",
),
],
)
@pytest.mark.integration
def test_quantitative_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/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