Question

我有一个项目使用aiohttp和aiobotocore来处理AWS中的资源。我正在尝试测试适用于AWS S3的类，我正在使用moto来模拟AWS。使用同步代码的示例（来自moto docs的示例），Mocking可以正常工作

import boto3
from moto import mock_s3


class MyModel(object):
    def __init__(self, name, value):
        self.name = name
        self.value = value

    def save(self):
        s3 = boto3.client('s3', region_name='us-east-1')
        s3.put_object(Bucket='mybucket', Key=self.name, Body=self.value)


def test_my_model_save():
    with mock_s3():
        conn = boto3.resource('s3', region_name='us-east-1')
        conn.create_bucket(Bucket='mybucket')

        model_instance = MyModel('steve', 'is awesome')
        model_instance.save()
        body = conn.Object('mybucket', 'steve').get()['Body'].read().decode("utf-8")

        assert body == 'is awesome'

但是，在重写之后使用aiobotocore模拟不起作用 - 它在我的示例中连接到真正的AWS S3。

import aiobotocore
import asyncio

import boto3
from moto import mock_s3


class MyModel(object):
    def __init__(self, name, value):
        self.name = name
        self.value = value

    async def save(self, loop):
        session = aiobotocore.get_session(loop=loop)
        s3 = session.create_client('s3', region_name='us-east-1')
        await s3.put_object(Bucket='mybucket', Key=self.name, Body=self.value)


def test_my_model_save():
    with mock_s3():
        conn = boto3.resource('s3', region_name='us-east-1')
        conn.create_bucket(Bucket='mybucket')
        loop = asyncio.get_event_loop()

        model_instance = MyModel('steve', 'is awesome')
        loop.run_until_complete(model_instance.save(loop=loop))
        body = conn.Object('mybucket', 'steve').get()['Body'].read().decode("utf-8")

        assert body == 'is awesome'

所以我的假设是moto与aiobotocore无法正常工作。如果我的源代码在第二个示例中看起来如何，我如何有效地模拟AWS资源？

Answer 1

来自moto的模拟不起作用，因为它们使用的是同步API。但您可以启动moto服务器并配置aiobotocore以连接到此测试服务器。看看aiobotocore测试的灵感。

Answer 2

来自没有pytest的aiobotocore的mock_server.py：

# Initially from https://raw.githubusercontent.com/aio-libs/aiobotocore/master/tests/mock_server.py

import shutil
import signal
import subprocess as sp
import sys
import time
import requests


_proxy_bypass = {
  "http": None,
  "https": None,
}


def start_service(service_name, host, port):
    moto_svr_path = shutil.which("moto_server")
    args = [sys.executable, moto_svr_path, service_name, "-H", host,
            "-p", str(port)]
    process = sp.Popen(args, stdin=sp.PIPE, stdout=sp.PIPE, stderr=sp.DEVNULL)
    url = "http://{host}:{port}".format(host=host, port=port)

    for _ in range(30):
        if process.poll() is not None:
            break

        try:
            # we need to bypass the proxies due to monkeypatches
            requests.get(url, timeout=0.1, proxies=_proxy_bypass)
            break
        except requests.exceptions.RequestException:
            time.sleep(0.1)
    else:
        stop_process(process)
        raise AssertionError("Can not start service: {}".format(service_name))

    return process


def stop_process(process, timeout=20):
    try:
        process.send_signal(signal.SIGTERM)
        process.communicate(timeout=timeout / 2)
    except sp.TimeoutExpired:
        process.kill()
        outs, errors = process.communicate(timeout=timeout / 2)
        exit_code = process.returncode
        msg = "Child process finished {} not in clean way: {} {}" \
            .format(exit_code, outs, errors)
        raise RuntimeError(msg)

Answer 3

使用AWS的存根即可解决问题。这是我在龙卷风应用程序中对aws读取操作的处理方式：

import aiobotocore
from botocore.stub import Stubber
from tornado.testing import AsyncTestCase
from aiobotocore.response import StreamingBody


class RawStream(io.BytesIO):

    async def __aenter__(self):
        return self

    async def __aexit__(self, exc_type, exc_val, exc_tb):
        pass

    async def read(self, n):
        return super().read(n)

class S3TestCase(AsyncTestCase):

    def setUp(self):
        super().setUp()
        session = aiobotocore.get_session()
        self.client = session.create_client("s3", region_name="AWS_S3_REGION",
                                    aws_secret_access_key="AWS_SECRET_ACCESS_KEY",
                                    aws_access_key_id="AWS_ACCESS_KEY_ID")

    @tornado.testing.gen_test
    def test_read(self):
        stubber = Stubber(self.client)
        stubber.add_response("get_object",
                          {"Body": StreamingBody(raw_stream=RawStream(self.binary_content), content_length=128),
                          "ContentLength": 128},
                         expected_params={"Bucket": "AWS_S3_BUCKET",
                                          "Key": "filename"})
        stubber.activate()

        response = await client.get_object(Bucket="AWS_S3_BUCKET", Key="filename")

对于写操作应该是相似的。希望这会指引您正确的方向。

有关存根的更多信息：https://botocore.amazonaws.com/v1/documentation/api/latest/reference/stubber.html

Answer 4

我认为塞巴斯蒂安·布雷斯廷斯的答案应该是被接受的答案。我将发布此新答案，因为自发布之日起有些变化。 python 3.8现在支持异步测试用例，而aioboto3客户端现在是上下文管理器。

使用python 3.8的一个最小示例如下：

from unittest import IsolatedAsyncioTestCase

import aioboto3
from botocore.stub import Stubber

class Test(IsolatedAsyncioTestCase):

    async def asyncSetUp(self):
        self._s3_client = await aioboto3.client('s3').__aenter__()
        self._s3_stub = Stubber(self._s3_client)

    async def asyncTearDown(self):
        await self._s3_client.__aexit__(None, None, None)

    async def test_case(self):
        self._s3_stub.add_response(
            "get_object",
            {"Body": "content"},
            expected_params={"Bucket": "AWS_S3_BUCKET", "Key": "filename"}
        )
        self._s3_stub.activate()

        response = await self._s3_client.get_object(Bucket="AWS_S3_BUCKET", Key="filename")

        self.assertEquals(response, "content")

Answer 5

我们可以使用moto [server]创建S3服务器，然后根据其中的内容创建一个pytest固定装置，类似于aioboto3

@pytest.yield_fixture(scope='session')
def s3_server():
    host = 'localhost'
    port = 5002
    url = 'http://{host}:{port}'.format(host=host, port=port)
    process = start_service('s3', host, port)
    yield url
    stop_process(process)

，然后使用patch('aiobotocore.AioSession.create_client')的{{1}} return_value

aiobotocore.get_session().create_client('s3', region_name='us-east-1', end_point_url=s3_server)

如何使用aiobotocore

5 个答案: