跟读练习: 2.2k - 通过YouTube学习英语口语
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Hey friends, welcome back to the channel.
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Hey friends, welcome back to the channel.
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So when designing an API,
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it's easy to think about the happy path of your application.
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But if you want to build a robust application and keep your users happy,
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then you need to consider the unhappy path as well.
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What happens if your user's internet connection cuts out just after making a request?
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Or maybe your server's struggling under load and the client times out before it can receive a response?
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Usually errors are handled by the client by doing retries.
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If there's an error or the request times out,
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then the client will retry a number of times,
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either automatically or by a frustrated user hitting that submit button.
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If the user sends multiple requests to the server and more than one of them gets through,
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then you'll likely end up with duplicates on your end.
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Depending on the application, this might not be a big deal.
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If the user is just writing a comment on a blog post or reviewing a product,
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then it's not the end of the world if they end up with multiple posts.
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But what if they're sending an email?
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Is it okay for the recipients to receive multiple copies of the same email?
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What if they were buying something online?
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Would the customer be happy if they got charged twice or maybe even 10 times for the same product.
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This is where idempotency comes in but what does it actually mean?
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If we have a look at the internet standards it says the following.
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A request method is considered idempotent
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if the intended effect on the server of multiple identical requests with
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that method is the same as the effect for a single such request.
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So if we call an API multiple times with the same request then it's considered idempotent
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if it has the same effect on the server as if we had only called it once.
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Now let's have a look at the most common methods and see whether they're idempotent or not.
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The get method is read only,
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it doesn't affect the server in any way.
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Nothing gets created or updated so we can call the get method multiple times without it having any adverse effects.
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So a get method is always idempotent.
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With a put request we're going to be performing updates.
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So let's say we're updating a user's email address.
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No matter how many times we call this method we should always get the same response
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and the user's details are always going to get updated to the same thing.
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So a put request is always idempotent as well.
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With a post request we're creating something on the server.
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So if we call this method multiple times then we should expect to get multiple copies of the same thing.
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Or in some cases we might get an error if we're trying to create something that can only be one of.
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For example if we're trying to create a new user with a post request.
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Then the first request will go through but a second request for the same username will fail because the user already exists.
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Technically this is still idempotent but it's not a very nice experience for the user user.
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Let's say when they make their first request they then have an internet connection failure and therefore don't get a response.
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When they try and retry it will tell them
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that the username order exists but in fact it was their first request that created that user.
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If we take the example of making a payment then generally
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there aren't any unique identifiers on a payment like there are with creating a user.
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This is what we typically might send through on a platform like Stripe if someone's buying something for $20.
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However there is nothing unique about this request that links it to a particular purchase.
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If a payment platform receives two of these then it'll just think it's two separate payments and charge the customer twice
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which is not what we want.
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So post requests are generally not idempotent.
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With patch requests it depends on how you use them.
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If you're just using it to update an email address of a user then that could be considered idempotent.
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However you can also use a patch request to do things like copy,
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move, add and remove and therefore it's not considered idempotent.
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Finally we have the delete method which deletes an object on the server.
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If you run delete multiple times it's going to have the same effect on the server as
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if you'd only run it once.
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Sure the second time you might run it you might get an error
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but the actual server doesn't change its state therefore delete is also considered to be idempotent.
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In the cases where you're making a payment or some other Crisco operation
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that needs to happen exactly once then you need to make those other methods such as post and patch idempotent as well.
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The only way that you can really do this is to have some form of unique identifier.
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That way you can distinguish that request from some otherwise identical requests.
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You may have something like this already in place.
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Let's go back to the payment analogy.
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Let's say you have a saved basket of items and that basket has an ID.
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That ID is therefore unique to that order and you could use that ID for the idempotency key.
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Another option is to hash the body of the request.
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However if you're doing this you need to make sure
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that there's no reason for that person to ever send exactly the same request.
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There should be something about the combination of fields in the request that makes it unique.
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For example if someone orders a Spongebob beach towel
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and then 30 seconds later orders another Spongebob beach towel you don't know that that's a duplicate order.
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They might just really like Spongebob.
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Generally the way this is normally done is to add an idempotency key to a header.
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Stripe for example have a header called idempotency-key but really this could be anything.
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So you now have some form of key that makes this request unique.
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However with a user supplied key you can't guarantee that it's going to be globally unique.
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The user could send you the same key as another user or even the same key from multiple endpoints.
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So it's important you always combine
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that user supply key with something like a user id as well as the API path that's being used.
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To implement idempotency you need to store your combined idempotency key along with the successful response that you send to the user.
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If a request with the same idempotency key comes in instead of actually performing the operation,
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you just send them back a response that you sent out before.
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As far as the user is concerned,
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the operation was successful and they don't need to know that you're sending out a previous response.
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Typically this is done using some form of key value storage such as Redis or DynamoDB.
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Technically you could store your idempotency keys in an in-memory storage such as a dictionary.
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However this won't work if you have multiple copies of your API running behind the load balancer,
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as each API won't be able to see the keys in the other copies.
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You will also lose your idempotency keys whenever you have to restart your application.
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This is why we don't store them in memory.
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So when a request comes in you need to first check to see whether
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that idempotency key that's been sent is in your storage.
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And if it is then you just send back the response that you have stored.
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If the idempotency key doesn't exist then you carry on with the normal operation
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and if it's successful then you store the idempotency key along with the response before sending it back to the user.
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How long you store your idempotency keys for really depends on the application.
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If you have idempotency enabled just to protect yourself from a
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user clicking on something multiple times then you might only need to store them for say 10 minutes.
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But if you have some sort of retry mechanism in place then you might need to store them for longer.
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Typically we store idempotency keys for anywhere between 24 and 48 hours
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but you need to check with your application and see if it makes sense to store them for longer.
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If you are using something like redis
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or dynamo db to store your keys then you can use the time to live
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or ttl so that your keys are automatically deleted for you.
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You may also want to consider idempotency validation in your API.
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If a request comes in with the same idempotency key from
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the same user for the same endpoint then we're just going to assume
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that that's the same request and send them out the same response.
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However there is a chance
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that the user has just used the same idempotency key by mistake and the request body is actually very different.
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If you need to protect yourself against this sort of scenario then you can take a hash of the request
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and store that alongside the idempotency key and then
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when the request comes in you can check to see whether it matches the hash as well
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and if it doesn't return an error to the user.
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If you want to implement this in the .NET Core API then you can make use of the distributed caching library
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and then store your keys in redis and then you can create a filter
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which you can then add to each of the endpoints where
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you want idempotency to make this even easier there is a new get package called idempotent api
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that does all the heavy lifting for you
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if you want to support this channel
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and also get access to the code shown in my videos
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and you can subscribe on patreon patreon members also get access
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to exclusive content from me as well as a private discord community and generous discounts to my courses once I release them.
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Thank you for watching this video and I'll hopefully see you in the next one.
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为什么要通过这个视频练习口语？
在学习英语时，口语表达是一个重要的环节。利用这样的教学视频进行练习，不仅能够帮助你提高语言的流利度，还能让你感受真实的对话场景和语境。当你观看并模仿视频中的讲解时，你将能更好地理解如何在不同情况下使用英语，从而增强你的沟通能力。
通过影子跟读（shadow speak）技术，你可以有效地提升你的发音和语调。这样的方法强调了模仿和重复，通过不断复制说话者的表达，你将能更自然地运用这些语句。因此，利用这类视频，尤其是涉及实际应用的内容，将为你的英语学习带来直接的好处。
语法和表达在语境中的应用
- 条件句: 视频提到“如果用户的互联网连接断开...”，这一句强调了在编程和应用设计中条件句的使用，这种句型在日常对话中也非常常见。
- 被动语态: 讲解中使用了“用户的细节会一直更新”，被动语态在英语中是用来强调动作的承受者，而不是执行者，这对于初学者尤其重要。
- 情态动词: 如“用户可能会...”这类表达不仅丰富了句子结构，还能让你学会如何含蓄地表达可能性或能力。
这些语法结构在实际英语使用场景中非常常见，通过这段视频的练习，你可以更深入地理解它们的用法，并在对话中更加自信。
常见发音陷阱
在视频中，有些单词的发音对学习者来说可能会带来挑战。例如，“互联网连接”（internet connection）这个词组，常常导致非母语者发音不清晰。此外，过去式动词“更新”（updated）也可能在快速语速下让人听不清。这些发音问题会影响到听者的理解，因此在跟读时要特别注意。
为了帮助你克服这些发音陷阱，建议在影子跟读（英语影子跟读，shadowing site）时多多关注音节的重音和连读现象。通过多次重复练习，你可以逐步改善你的发音，提高你的听说能力。
什么是跟读法？
跟读法 (Shadowing) 是一种有科学依据的语言学习技巧，最初开发用于专业口译员的培训，并由多语言者Alexander Arguelles博士普及。这个方法简单而强大：您在听英语母语原声的同时立即大声重复——就像是一个延迟1-2秒紧跟说话者的影子。与被动听力或语法练习不同，跟读法强迫您的大脑和口腔肌肉同时处理并模仿真实的讲话模式。研究表明它能显着提高发音准确性，语调，节奏，连读，听力理解和口语流利度——使其成为雅思口语备考和真实英语交流最有效的方法之一。