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import pytest_asyncio
import requests
from httpx import ASGITransport, AsyncClient
from app.main import app
@pytest_asyncio.fixture(scope="session")
def mock_recognition_image(tmpdir_factory):
url = "https://user-images.githubusercontent.com/76527547/117133599-c073fa00-ada4-11eb-831b-412de4d28341.jpeg"
return requests.get(url).content
@pytest_asyncio.fixture(scope="session")
def mock_detection_image(tmpdir_factory):
url = "https://user-images.githubusercontent.com/76527547/117319856-fc35bf00-ae8b-11eb-9b51-ca5aba673466.jpg"
return requests.get(url).content
@pytest_asyncio.fixture(scope="session")
def mock_txt_file(tmpdir_factory):
txt_file = tmpdir_factory.mktemp("data").join("mock.txt")
txt_file.write("mock text")
return txt_file.read("rb")
@pytest_asyncio.fixture(scope="function")
async def test_app_asyncio():
# for httpx>=20, follow_redirects=True (cf. https://github.com/encode/httpx/releases/tag/0.20.0)
async with AsyncClient(transport=ASGITransport(app=app), base_url="http://test", follow_redirects=True) as ac:
yield ac # testing happens here
@pytest_asyncio.fixture(scope="function")
def mock_detection_response():
return {
"box": {
"name": "117319856-fc35bf00-ae8b-11eb-9b51-ca5aba673466.jpg",
"geometries": [
[0.8203927977629988, 0.181640625, 0.9087770178355502, 0.2041015625],
[0.7471996155154171, 0.1806640625, 0.8245358080788996, 0.2060546875],
],
},
"poly": {
"name": "117319856-fc35bf00-ae8b-11eb-9b51-ca5aba673466.jpg",
"geometries": [
[
0.8203927977629988,
0.181640625,
0.906015010958283,
0.181640625,
0.906015010958283,
0.2021484375,
0.8203927977629988,
0.2021484375,
],
[
0.7482568619833604,
0.17938309907913208,
0.8208542842026056,
0.1819499135017395,
0.8193355512950555,
0.2034294307231903,
0.7467381290758103,
0.20086261630058289,
],
],
},
}
@pytest_asyncio.fixture(scope="function")
def mock_kie_response():
return {
"box": {
"name": "117319856-fc35bf00-ae8b-11eb-9b51-ca5aba673466.jpg",
"orientation": {"value": None, "confidence": None},
"language": {"value": None, "confidence": None},
"dimensions": [2339, 1654],
"predictions": [
{
"class_name": "words",
"items": [
{
"value": "world!",
"geometry": [0.8203927977629988, 0.181640625, 0.9087770178355502, 0.2041015625],
"objectness_score": 0.46,
"confidence": 0.94,
"crop_orientation": {"value": 0, "confidence": None},
},
{
"value": "Hello",
"geometry": [0.7471996155154171, 0.1806640625, 0.8245358080788996, 0.2060546875],
"objectness_score": 0.46,
"confidence": 0.66,
"crop_orientation": {"value": 0, "confidence": None},
},
],
}
],
},
"poly": {
"name": "117319856-fc35bf00-ae8b-11eb-9b51-ca5aba673466.jpg",
"orientation": {"value": None, "confidence": None},
"language": {"value": None, "confidence": None},
"dimensions": [2339, 1654],
"predictions": [
{
"class_name": "words",
"items": [
{
"value": "world!",
"geometry": [
0.8203927977629988,
0.181640625,
0.906015010958283,
0.181640625,
0.906015010958283,
0.2021484375,
0.8203927977629988,
0.2021484375,
],
"objectness_score": 0.52,
"confidence": 1,
"crop_orientation": {"value": 0, "confidence": 1},
},
{
"value": "Hello",
"geometry": [
0.7482568619833604,
0.17938309907913208,
0.8208542842026056,
0.1819499135017395,
0.8193355512950555,
0.2034294307231903,
0.7467381290758103,
0.20086261630058289,
],
"objectness_score": 0.57,
"confidence": 0.65,
"crop_orientation": {"value": 0, "confidence": 1},
},
],
}
],
},
}
@pytest_asyncio.fixture(scope="function")
def mock_ocr_response():
return {
"box": {
"name": "117319856-fc35bf00-ae8b-11eb-9b51-ca5aba673466.jpg",
"orientation": {"value": None, "confidence": None},
"language": {"value": None, "confidence": None},
"dimensions": [2339, 1654],
"items": [
{
"blocks": [
{
"geometry": [0.7471996155154171, 0.1806640625, 0.9087770178355502, 0.2060546875],
"objectness_score": 0.46,
"lines": [
{
"geometry": [0.7471996155154171, 0.1806640625, 0.9087770178355502, 0.2060546875],
"objectness_score": 0.46,
"words": [
{
"value": "Hello",
"geometry": [
0.7471996155154171,
0.1806640625,
0.8245358080788996,
0.2060546875,
],
"objectness_score": 0.46,
"confidence": 0.66,
"crop_orientation": {"value": 0, "confidence": None},
},
{
"value": "world!",
"geometry": [
0.8203927977629988,
0.181640625,
0.9087770178355502,
0.2041015625,
],
"objectness_score": 0.46,
"confidence": 0.94,
"crop_orientation": {"value": 0, "confidence": None},
},
],
}
],
}
]
}
],
},
"poly": {
"name": "117319856-fc35bf00-ae8b-11eb-9b51-ca5aba673466.jpg",
"orientation": {"value": None, "confidence": None},
"language": {"value": None, "confidence": None},
"dimensions": [2339, 1654],
"items": [
{
"blocks": [
{
"geometry": [
0.7460642457008362,
0.2017778754234314,
0.7464945912361145,
0.17868199944496155,
0.9056554436683655,
0.18164771795272827,
0.9052250981330872,
0.20474359393119812,
],
"objectness_score": 0.54,
"lines": [
{
"geometry": [
0.7460642457008362,
0.2017778754234314,
0.7464945912361145,
0.17868199944496155,
0.9056554436683655,
0.18164771795272827,
0.9052250981330872,
0.20474359393119812,
],
"objectness_score": 0.54,
"words": [
{
"value": "Hello",
"geometry": [
0.7482568619833604,
0.17938309907913208,
0.8208542842026056,
0.1819499135017395,
0.8193355512950555,
0.2034294307231903,
0.7467381290758103,
0.20086261630058289,
],
"objectness_score": 0.57,
"confidence": 0.65,
"crop_orientation": {"value": 0, "confidence": 1},
},
{
"value": "world!",
"geometry": [
0.8203927977629988,
0.181640625,
0.906015010958283,
0.181640625,
0.906015010958283,
0.2021484375,
0.8203927977629988,
0.2021484375,
],
"objectness_score": 0.52,
"confidence": 1,
"crop_orientation": {"value": 0, "confidence": 1},
},
],
}
],
}
]
}
],
},
}
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