A more robust method is to wrap the returned value in Promise.resolve. Given a finite Iterable(arrays are Iterable), or a promise of an Iterable, which produces promises (or a mix of promises and values), iterate over all the values in the Iterable into an array and map the array to another using the given mapper function..

The trick to implementing Promise.map with native Promise.all is to call Promise.all on not a mapped version of the input array but a smaller array containing threads that are basically copies of the waterfall pattern shown earlier.

Bluebird is a fully featured JavaScript promises library with unmatched performance. What concurrency does is it lets you set the maximum number of “threads” at any one time. If all iterations resolve successfully, the Promise.mapSeries call resolves to a new array containing the results of each mapper execution, in order. For example: To rate limit, you can introduce a timed delay: There is a subtle difference between the two delay implementations. A common use of Promise.map is to replace the .push+Promise.all boilerplate: You may optionally specify a concurrency limit: The concurrency limit applies to Promises returned by the mapper function and it basically limits the number of Promises created.

In general, something with a map is called a functor, the guarantees a map function must hold are basically only that Promise.resolve([1,2,3]).map(x => x) resolves to the same values, and that Promise.resolve([1,2,3]).map(f).map(g) is the same as Promise.resolve([1,2,3]).map(x => g(f(x))).. For bluebird 2.x documentation and files, see the 2.x tree. Promises returned by the mapper function are awaited for and the returned promise doesn't fulfill until all mapped promises have fulfilled as well. So I figured, “Why not write my own Promise.map?”. It ensures that the .then method is always present and avoids the need for type checking and separate handling. The answer is yes. Promise.mapSeries resolves with an array as explained above, while Promise.each resolves with an array containing the resolved values of the input elements (ignoring the outputs of the iteration steps). The mapper function has signature (value, index, arrayLength) where value is the current element (or its resolved value if it is a promise). Promise.map, on the other hand, is free to schedule invocations any way it wants since it operates on an array of inputs and the mapper function to transform input to output. ", "3.txt!

Since you do not pass in a function with Promise.all, all the pending promises must have been generated somewhere else (by invoking the API call function). Given an Iterable (an array, for example), or a promise of an Iterable, iterates serially over all the values in it, executing the given mapper on each element. At one extreme, if concurrency is set to 1, it behaves exactly the same as the simple waterfall pattern. Line 18 replaces array indexing with an iterator object. Thank you for reading! You simply .then all your invocations so they occur one after another. So by the time Promise.all receives the collection of pending promises, all the invocations will have already started. npm install bluebird. Promise.mapSeries is very similar to Promise.each. Bluebird is a fully featured JavaScript promises library with unmatched performance. With that said, it is not impossible to implement Promise.map behavior using Promise.all.

JavaScript’s Promise lends itself well to staggering because it is easy to create waterfall behavior from Promise.

This doesn't mean that the result array has items in random order, it means that .map can be used for concurrency coordination unlike .all. The basic implementation above has two outstanding issues: How can you ensure that a thenable is returned from mapper? Data scraping on the web is usually done in two steps: It is certainly a bad idea to wrap all the step 2 API calls in a giant Promise.all. I added an explicit note in the docs for .map.. If you need to do more operations per file, they should be chained in the map.

// If one of the promises in the original array rejects, // the iteration will stop once it reaches it.

@naartjie. The magic here is the concurrency option. When all the returned promises resolve. If an element is a promise, the mapper will wait for it before proceeding. Calls itself again if there are items left in the input array. So the mapper function will be called three times and it will be called again only after at least one of the Promises resolves. Usually, you do not want to fire all your API calls in one go, as doing so is likely to overwhelm other people’s servers, trigger their DDoS protection, or worse, take them offline. The mapper function has signature (value, index, arrayLength) where value is the current element (or its resolved value if it is a promise). If an element is a promise, the mapper will wait for it before proceeding. The current element of the iteration is a pending promise, that promise will be awaited before running the mapper. The mapper returns a promise or a thenable, it is awaited before continuing to the next iteration. For example, if concurrency is 3 and the mapper callback has been called enough so that there are three returned Promises currently pending, no further callbacks are called until one of the pending Promises resolves. Code Explanation:-The require command is used to include the Bluebird library. If any promise in the array is rejected, or any promise returned by the mapper function is rejected, the returned promise is rejected as well. // The return value of .map is a promise that is fulfilled with an array of the mapped values, // That means we only get here after all the files have been statted and their contents read, // into memory. Promises in Node.js 10 are significantly faster than before. We can use the same logic to implement Promise.filter: That wraps up today’s article on asynchronous programming in JS. If concurrency is not set, it defaults to the other extreme, which is Infinity. Playing with the first example with and without limits, and seeing how it affects the duration when reading 20 files: The order map calls the mapper function on the array elements is not specified, there is no guarantee on the order in which it'll execute the maper on the elements.

Given an Iterable (an array, for example), or a promise of an Iterable, iterates serially over all the values in it, executing the given mapper on each element. The correct approach is to use staggering and/or a rate limit. The website might organize the property information by location or every property might have its own page. Promise.all sets no limit on the number of “threads.” If my list consists of 1,000 items, 1,000 API calls will be fired all at the same time.

See the bluebird website for further documentation, references and instructions.

", "5.txt!"]. Preferring to use native Promise as much as I can, I find installing a whole bluebird module for a single function uneconomical. Learn how Promise.map can be implemented in native Promise API without importing bluebird. The mapper function for a given item is called as soon as possible, that is, when the promise for that item's index in the input array is fulfilled.

Dequeues the next item in the input array. ", "2.txt! Places the resolved item in the output array (at the corresponding index). The difference between Promise.each and Promise.mapSeries is their resolution value. Take the example of a property portal. The iterator function has signature (value, index, arrayLength) where value is the current element (or its resolved value if it is a promise). Waits for the promise returned by the invocation to resolve. Then it behaves similarly to Promise.all, invoking mapper upfront on the entire input array. The mapper function will be invoked on every item in the array, returning a pending promise each time. One possible way is to check for the existence of the .then method and handle thenable vs. non-thenable separately.

And it is using Promise.map, one of the Promise API extensions in bluebird. By promisify, we mean that bluebird will ensure that each and every method defined in the MongoDB library returns a promise. Invokes the mapper function on the input.

The size of this array is governed by the concurrency option.

I do a lot of web scraping with Node.js in my work. // The iteration will be performed sequentially, awaiting for any, // This will run after the last step is done, // ["1.txt!

The problem of staggering API calls for web scraping can be addressed with Promise.map. Step 2) The next step is to include the bluebird module in your code and promisify the entire MongoDB module. This difference is made obvious in the diagram below: While the waterfall pattern is useful when the list of items is small, it can be really slow on larger lists, as you are effectively running on a “single thread.” Can we do better? // Promise.map awaits for returned promises as well. ). This way, Promise.each is meant to be mainly used for side-effect operations (since the outputs of the iterator are essentially discarded), just like the native .forEach() method of arrays, while Promise.map is meant to be used as an async version of the native .map() method of arrays. ", "4.txt! Create a Passwordless Login System for Your Chrome Extension, Create a ASP .NET Core Web App With Docker, Letters From the Dark World of React Boilerplate.

For order guarantee in sequential execution - see Promise.mapSeries. Note.

The first method waits 1000ms before invoking, while the second method invokes first and waits 1000ms to deliver the result. If an element is a promise, the iterator will wait for it before proceeding. // The code above outputs the following after 12 seconds (not 16!

Given an Iterable (an array, for example), or a promise of an Iterable, iterates serially over all the values in it, executing the given iterator on each element.

The current element of the iteration is a rejected promise, the iteration will stop and be rejected as well (with the same reason). If concurrency is such a useful option, why is it not implemented in Promise.all in the first place?

You visit an index page where you find a “listing” of all the sub-resources you can call to fetch some details. Bluebird is a fully featured promise library with focus on innovative features and performance. On the other hand, if I use the waterfall pattern shown above, I end up working on a single “thread.” Promise.map provides a middle ground. Here’s a visual representation: Every time wrappedMapper is invoked, it does the following: One can see the Promise.map function is a more general implementation of the waterfall pattern. Given a finite Iterable(arrays are Iterable), or a promise of an Iterable, which produces promises (or a mix of promises and values), iterate over all the values in the Iterable into an array and map the array to another using the given mapper function. See the API reference here. Example with a rejected promise in the array: // The array to be mapped over can be a mix of values and promises. One by one, you will visit the items on the list from step 1 to fetch out the details.