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Hey friends, welcome back to the channel.

So when designing an API,

it's easy to think about the happy path of your application.

But if you want to build a robust application and keep your users happy,

then you need to consider the unhappy path as well.

What happens if your user's internet connection cuts out just after making a request?

Or maybe your server's struggling under load and the client times out before it can receive a response?

Usually errors are handled by the client by doing retries.

If there's an error or the request times out,

then the client will retry a number of times,

either automatically or by a frustrated user hitting that submit button.

If the user sends multiple requests to the server and more than one of them gets through,

then you'll likely end up with duplicates on your end.

Depending on the application, this might not be a big deal.

If the user is just writing a comment on a blog post or reviewing a product,

then it's not the end of the world if they end up with multiple posts.

But what if they're sending an email?

Is it okay for the recipients to receive multiple copies of the same email?

What if they were buying something online?

Would the customer be happy if they got charged twice or maybe even 10 times for the same product.

This is where idempotency comes in but what does it actually mean?

If we have a look at the internet standards it says the following.

A request method is considered idempotent

if the intended effect on the server of multiple identical requests with

that method is the same as the effect for a single such request.

So if we call an API multiple times with the same request then it's considered idempotent

if it has the same effect on the server as if we had only called it once.

Now let's have a look at the most common methods and see whether they're idempotent or not.

The get method is read only,

it doesn't affect the server in any way.

Nothing gets created or updated so we can call the get method multiple times without it having any adverse effects.

So a get method is always idempotent.

With a put request we're going to be performing updates.

So let's say we're updating a user's email address.

No matter how many times we call this method we should always get the same response

and the user's details are always going to get updated to the same thing.

So a put request is always idempotent as well.

With a post request we're creating something on the server.

So if we call this method multiple times then we should expect to get multiple copies of the same thing.

Or in some cases we might get an error if we're trying to create something that can only be one of.

For example if we're trying to create a new user with a post request.

Then the first request will go through but a second request for the same username will fail because the user already exists.

Technically this is still idempotent but it's not a very nice experience for the user user.

Let's say when they make their first request they then have an internet connection failure and therefore don't get a response.

When they try and retry it will tell them

that the username order exists but in fact it was their first request that created that user.

If we take the example of making a payment then generally

there aren't any unique identifiers on a payment like there are with creating a user.

This is what we typically might send through on a platform like Stripe if someone's buying something for $20.

However there is nothing unique about this request that links it to a particular purchase.

If a payment platform receives two of these then it'll just think it's two separate payments and charge the customer twice

which is not what we want.

So post requests are generally not idempotent.

With patch requests it depends on how you use them.

If you're just using it to update an email address of a user then that could be considered idempotent.

However you can also use a patch request to do things like copy,

move, add and remove and therefore it's not considered idempotent.

Finally we have the delete method which deletes an object on the server.

If you run delete multiple times it's going to have the same effect on the server as

if you'd only run it once.

Sure the second time you might run it you might get an error

but the actual server doesn't change its state therefore delete is also considered to be idempotent.

In the cases where you're making a payment or some other Crisco operation

that needs to happen exactly once then you need to make those other methods such as post and patch idempotent as well.

The only way that you can really do this is to have some form of unique identifier.

That way you can distinguish that request from some otherwise identical requests.

You may have something like this already in place.

Let's go back to the payment analogy.

Let's say you have a saved basket of items and that basket has an ID.

That ID is therefore unique to that order and you could use that ID for the idempotency key.

Another option is to hash the body of the request.

However if you're doing this you need to make sure

that there's no reason for that person to ever send exactly the same request.

There should be something about the combination of fields in the request that makes it unique.

For example if someone orders a Spongebob beach towel

and then 30 seconds later orders another Spongebob beach towel you don't know that that's a duplicate order.

They might just really like Spongebob.

Generally the way this is normally done is to add an idempotency key to a header.

Stripe for example have a header called idempotency-key but really this could be anything.

So you now have some form of key that makes this request unique.

However with a user supplied key you can't guarantee that it's going to be globally unique.

The user could send you the same key as another user or even the same key from multiple endpoints.

So it's important you always combine

that user supply key with something like a user id as well as the API path that's being used.

To implement idempotency you need to store your combined idempotency key along with the successful response that you send to the user.

If a request with the same idempotency key comes in instead of actually performing the operation,

you just send them back a response that you sent out before.

As far as the user is concerned,

the operation was successful and they don't need to know that you're sending out a previous response.

Typically this is done using some form of key value storage such as Redis or DynamoDB.

Technically you could store your idempotency keys in an in-memory storage such as a dictionary.

However this won't work if you have multiple copies of your API running behind the load balancer,

as each API won't be able to see the keys in the other copies.

You will also lose your idempotency keys whenever you have to restart your application.

This is why we don't store them in memory.

So when a request comes in you need to first check to see whether

that idempotency key that's been sent is in your storage.

And if it is then you just send back the response that you have stored.

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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為什麼要通過這個影片練習口語？

在學習英語時，口語表達是一個重要的環節。利用這樣的教學影片進行練習，不僅能夠幫助你提高語言的流利度，還能讓你感受真實的對話場景和語境。當你觀看並模仿影片中的講解時，你將能更好地理解如何在不同情況下使用英語，從而增強你的溝通能力。

通過影子跟讀（shadow speak）技術，你可以有效地提升你的發音和語調。這樣的方法強調了模仿和重複，通過不斷複製說話者的表達，你將能更自然地運用這些語句。因此，利用這類影片，尤其是涉及實際應用的內容，將為你的英語學習帶來直接的好處。

語法和表達在語境中的應用

條件句: 影片提到“如果使用者的網際網路連線斷開...”，這一句強調了在程式設計和應用設計中條件句的使用，這種句型在日常對話中也非常常見。
被動語態: 講解中使用了“使用者的細節會一直更新”，被動語態在英語中是用來強調動作的承受者，而不是執行者，這對於初學者尤其重要。
情態動詞: 如“使用者可能會...”這類表達不僅豐富了句子結構，還能讓你學會如何含蓄地表達可能性或能力。

這些語法結構在實際英語使用場景中非常常見，通過這段影片的練習，你可以更深入地理解它們的用法，並在對話中更加自信。

常見發音陷阱

在影片中，有些單詞的發音對學習者來說可能會帶來挑戰。例如，“網際網路連線”（internet connection）這個片語，常常導致非母語者發音不清晰。此外，過去式動詞“更新”（updated）也可能在快速語速下讓人聽不清。這些發音問題會影響到聽者的理解，因此在跟讀時要特別注意。

為了幫助你克服這些發音陷阱，建議在影子跟讀（英語影子跟讀，shadowing site）時多多關注音節的重音和連讀現象。通過多次重複練習，你可以逐步改善你的發音，提高你的聽說能力。

影片中的語法

說話人最常用的結構，並附上影片中的原話：

結構	影片中的用法
被動語態 be + 過去分詞 — 強調發生了什麼，而不是誰做的	are handled · is considered · is read
現在完成時 have/has + 過去分詞 — 過去發生但與現在仍有關聯的事	that's been sent · have stored

什麼是跟讀法？

跟讀法 (Shadowing) 是一種有科學依據的語言學習技巧，最初開發用於專業口譯員的培訓，並由多語言者Alexander Arguelles博士普及。這個方法簡單而強大：您在聽英語母語原聲的同時立即大聲重複——就像是一個延遲1-2秒緊跟說話者的影子。與被動聽力或語法練習不同，跟讀法強迫您的大腦和口腔肌肉同時處理並模模擬實的講話模式。研究表明它能顯著提高發音準確性，語調，節奏，連讀，聽力理解和口語流利度——使其成為雅思口語備考和真實英語交流最有效的方法之一。

影子跟讀法: 閱讀完整分步指南 →

跟讀練習: 2.2k - 通過影片學習英語口語

選擇練習模式

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為什麼要通過這個影片練習口語？

語法和表達在語境中的應用

常見發音陷阱

影片中的語法

什麼是跟讀法？