When developing a PHP application, you may encounter situations where you need to interact with remote resources or services. To extend the functionality of your application, you can use various API services to obtain remote data, connect to user accounts of other websites, or convert resources shared by your application. ProgrammableWeb website points out that there are currently more than 10,000 APIs available on the web, so you can find many services to extend the functionality of your PHP application. However, incorrect use of the API can quickly cause performance issues and extend the execution time of the script. If you want to avoid this, consider implementing some of the solutions described in this article.
Typical PHP scripts execute commands in code sequentially. This seems logical, because you may want to get the results of a previous operation (such as a database query or variable operation) to proceed to the next step of the script. The same rules apply when you make an API call. You must send a request, waiting for a response from the remote host before you can perform any action on the received data. However, if your application makes multiple API calls and you need data from each source to continue execution, you don't have to perform each request separately. Remember that the server responsible for handling API calls is ready to process multiple queries at once. All you need to do is create a script that executes API calls in parallel, rather than one after another. Fortunately, PHP provides a set of curl_multi functions designed to do this.
Using the curl_multi function is similar to using the cURL library to make typical requests in PHP. The only difference is that you need to prepare a set of requests to be performed (not just one), use the curl_init function and pass it to the curl_multi_add_handle function. Then, calling the curl_multi_exec function will execute the request simultaneously, and curl_multi_getcontent will allow you to get the results of each API call. Please read here to see a code example that implements the logic.
If you want to use the curl_multi function in your PHP application, there are some important things to note. First, the execution time of the curl_multi_exec function will be as long as the slowest API call in the request set passed to the curl_multi_add_handle function. Therefore, it only makes sense to use curl_multi when the time taken for each API call is about the same. If there is a request in the curl_multi set that is significantly slower than the others, your script will not be able to continue execution until the slowest request is completed.
It is also important that you need to determine the number of parallel requests that can be executed at one time. Remember that if your website handles a lot of traffic and each user triggers a concurrent API call to a remote server, the total number of requests executed at one time can quickly get high. Be sure to check the restrictions stated in the API documentation and learn how the service will respond when you reach these restrictions. When you reach the limit, the remote server may send a specific HTTP response code or error message. Your application should handle such situations correctly or put them in a log so that you can diagnose the problem and reduce the number of requests.
If you want to keep your web application responsive and avoid serving slow-loading pages, a large number of API calls to remote servers may make this task more difficult. If all requests are made in the main application flow, the end user will not see the rendered page until the PHP script receives the API response and processes the data. Of course, there are many API services hosted on fast servers and can handle requests quickly. However, your application may still be occasionally slowed down by connection delays or some random factor affecting the connection process or the remote server itself.
If you want to protect the end user from such problems, you need to separate the part of the application responsible for handling the request from the main process into a separate script. This means that the API call will be executed in a separate thread that does not interfere with the part of the code responsible for displaying the site.
To implement such a solution, you can write a separate PHP script and execute it using the exec() function, just like any command line application. Different PHP frameworks often provide modules that simplify writing command-line scripts and allow you to easily integrate them into existing application models or components. Just check the Symfony2 or CakePHP console components to see some examples. Various PHP platforms (not just frameworks) may also provide tools that make writing command-line scripts easier, such as WP CLI (the command-line interface for WordPress).
If you are looking for a more powerful way to handle API calls in a separate process, consider setting up a job server, such as Gearman. A Job Server is a complete solution that performs all the operations required to separate a specific task (job) into a separate process. Read Alireza Rahmani Khalili's Getting Started with Gearman article to learn how it works and how to implement it in PHP. If you work on the Zend Server platform, you can use the Zend Job Queue component, which provides similar functionality. Examples of its functionality and usage are described in the article "Scheduling with Zend Job Queue" written by Alex Stetsenko.
No matter which solution you choose to separate API calls, you have to consider how different parts of your application communicate with each other. First, you should place the data you receive from the API call where the entire part of the application is accessible (such as a database table or file). You must also share the status of individual script execution. The main application must know if the externally executed API call is in progress, if it has been completed long ago or if it has failed. If you are considering using a job server solution, it may provide the ability to monitor job status. However, if you just want to stick to writing simple PHP command line scripts, you have to implement this kind of logic yourself.
Multiple HTTP requests or multiple threads?
So, which solution is better - to execute multiple HTTP requests at once using the curl_multi function, or to separate API calls from the main application process? It depends on the context of querying the remote server. You may find that the entire API call takes a long time to process scripts, not only because of the request. There may also be a large amount of code responsible for processing received data, especially when processing transformed files or performing large amounts of database writes. In this case, using the curl_multi function may not be enough to speed up the application. Running a separate thread responsible for the entire operation and processing data received from the remote host may result in better results in application performance. On the other hand, if you need to execute many simple API calls that don't involve the heavy data processing on your side, sticking with the curl_multi function might be enough to make your application faster.
Of course, there is a third solution - mixing the above two methods. So you can run a separate thread responsible for handling API calls and then try to make it run faster by making multiple requests at once. This may be more efficient than executing a separate script for each request. However, it may also require a deeper analysis of how the flow of scripts is designed so that different script executions and different API calls executed at one time do not interfere with each other and do not repeat each other's work.
Another solution to speed up applications that rely heavily on API usage is to build a smart cache engine. It prevents your script from making unnecessary calls, as the content located on different servers has not changed. Correct cache can also reduce the amount of data transferred between servers in a single API call.
To write a working cache engine and return valid data, you need to make sure the remote server's response remains unchanged, so you don't need to get it every time. This may vary by specific API service, but the overall idea is to find a set of parameters (those are being passed in the request) that give the same response over a given time period. For example, if you get the daily currency exchange rate from a remote service, you can determine that the exchange rate for a given currency (this is a parameter) remains unchanged for a day. Therefore, the cache key used to store the data received from this particular API must contain both the currency and the date. If your application must get this specific exchange rate next time, you can refer to the data saved in the cache (such as a database or file) and avoid HTTP requests.
The above scenario assumes that your application assumes all the responsibility of checking the situation where data received by the remote service can be cached, so you need to implement the correct caching logic yourself. However, there are also cases where the API service tracks changes to its shared data and returns additional fields containing metadata linked to a specific resource. Metadata may consist of values such as the last modified date, the revision number, or hash value calculated based on the resource content. Using this kind of data can be a great way to improve the performance of PHP applications, especially when dealing with large amounts of data. Instead of getting the entire resource every time you connect to the API, you just have to compare the timestamp or hash value to the last received value. If they are equal, it only means that you can use the data you fetched earlier, because the remote content has not changed. Such solutions assume that you do use a cache engine in your application, but you don't need to worry about whether the data stored in the cache is valid. Since you rely on the metadata returned by the API service, you just need to compare the metadata values provided by the remote server.
Using remote resource metadata is especially beneficial when using the file hosting service API. Handling remote folders and files often means transferring large amounts of data, which can cause performance issues. To give an example of how to avoid this, let me describe the solution used in the Dropbox API. The Dropbox API service returns specific data that is applied to check if the remote file has been changed. First, the metadata method (returns folder and file information, such as its name, size, or path) contains a hash field representing the hash value of the returned resource. If you provide a hash value from a previous request as a parameter in a new request and the remote data has not changed between requests, the API will only return an HTTP 304 (unmodified) response. The Drobox API also provides a delta method that is specifically used to inform changes to a specific folder or file. The hash value and delta method are recommended in the API documentation because it can significantly improve the performance of your application.
This may sound obvious, but in some cases, a careful reading of the API documentation may give you some specific solutions on how to make API calls more efficiently. The usage of the Dropbox API described above is a very clear example. However, there may be other ways to reduce the amount of data transmitted in the response (e.g., select a few specific fields returned by the API instead of receiving the entire dataset). You can also check if the actions you performed in a separate request can be performed at once. For example, the translation method of the Google Translate API (used to get text translations in different languages) can return multiple translations in one request. By passing some text strings to process in one API call, you can avoid making multiple requests, which may save some application execution time.
As you can see, there are many ways to improve the performance of PHP applications that rely heavily on using remote APIs. You can perform multiple requests at once—either using the curl_multi function, or run a separate application thread. Another solution is to implement a caching engine that prevents you from making unnecessary API calls or reduces the amount of data transferred between servers. Finally, the approach provided by API services can provide you with some out-of-the-box solutions to improve performance, such as performing multiple operations in one request.
I hope this post provides you with some insight on how to handle API requests effectively. If you have any comments on the key points raised in the article or other tips on how to speed up the use of the API, feel free to post them below. You can also contact me directly via Google Plus.
API performance is affected by a variety of factors. First of all, the server's processing speed, which determines the speed at which the server processes requests and returns responses. Network latency (i.e., the time it takes for data to return from the client to the server) also plays an important role. Other factors include the efficiency of API code, the load on the server, and the number of API usage According to the format. Optimizing these factors can significantly improve API performance.
There are several strategies to optimize your API for better performance. First, you can use efficient coding practices to reduce processing time on the server. Second, you can use a Content Delivery Network (CDN) to reduce network latency. Third, you can use caches to store frequently accessed data and reduce the load on the server. Finally, you can use data compression to reduce the size of the data transmitted, thus reducing the time it takes to send and receive data.
Using APIs means using third-party-provided APIs in your application. This includes sending requests to the API and processing responses. The API provides a set of functions that your application can use to interact with a system or service represented by the API.
There are several ways to speed up the application's API usage. First, you can use asynchronous calls to prevent blocking the main thread. Second, you can use paging to limit the amount of data returned by the API. Third, you can use cache to store frequently accessed data and reduce the number of requests to the API. Finally, you can use data compression to reduce the size of the data transmitted, thus reducing the time it takes to send and receive data.
Content Distribution Network (CDN) plays a crucial role in improving API performance. It reduces network latency by distributing content to multiple servers located in different geographic locations. When a client sends a request, the CDN directs it to the nearest server, reducing the time it takes for data to return from the client to the server.
Cache improves API performance by storing frequently accessed data in the cache. When the client sends a data request, the server first checks the cache. If the data is in cache, the server returns it immediately, reducing processing time and load on the server. If the data is not in the cache, the server retrieves it from the database, processes it, and stores it in the cache for future requests.
Data compression improves API performance by reducing the transmitted data size. This reduces the time it takes to send and receive data, thereby increasing the speed of the API. Data compression is especially advantageous when processing large amounts of data.
Best practices for using APIs include using asynchronous calls to prevent blocking the main thread, using paging to limit the amount of data returned by the API, using cache to store frequently accessed data, and using data compression to reduce the transmitted data size.
You can use various metrics to measure the performance of your API, such as response time, error rate, and throughput. The response time is the time it takes for the API to return a response. Error rate is the percentage of requests that result in error. Throughput is the number of requests the API can process per unit time. These metrics can be measured using API monitoring tools.
API performance has a significant impact on user experience. If the API is slow, it will cause slow loading times, which can frustrate users and cause them to abandon the application. On the other hand, a fast and responsive API can provide a smooth and pleasing user experience. Therefore, optimizing API performance is crucial to improving user experience.
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