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Lodash _.pullAllBy


lodash's _.pullAllBy method is a powerful utility that allows developers to quickly and easily remove specified items from an array based on a provided comparator function. This method is particularly useful when working with large datasets or when dealing with complex data structures that require a bit more specificity when filtering.

The _.pullAllBy method takes three arguments:

  1. The first argument is the array from which the items will be removed.
  2. The second argument is an array of items to be removed from the first array.
  3. The third argument is a comparator function that will be used to determine whether or not each item in the first array should be removed.

The comparator function that is passed as the third argument to _.pullAllBy takes two arguments: the first is the current value being processed, and the second is the index of that value in the array. The function must return a value that will be used to determine whether or not the item should be removed from the array.

For example, let's say we have an array of objects that represent different people, and we want to remove all objects from the array that have a specific name. We could use the _.pullAllBy method to accomplish this task with the following code:

const people = [
  { name: 'Alice', age: 25 },
  { name: 'Bob', age: 30 },
  { name: 'Charlie', age: 35 },
  { name: 'Alice', age: 40 },

_.pullAllBy(people, [{ name: 'Alice' }], 'name');

// Output: [{ name: 'Bob', age: 30 }, { name: 'Charlie', age: 35 }]

In this example, we use the _.pullAllBy method to remove all objects from the people array that have a name property equal to { name: 'Alice' }. We pass 'name' as the third argument to indicate that we want to compare the name property of each object. The resulting array contains only the objects that do not have a name property equal to { name: 'Alice' }.

Overall, _.pullAllBy is a powerful tool for quickly and easily removing specific items from an array based on a custom comparator function. Whether you're working with large datasets or complex data structures, this method is sure to save you time and effort in your development work.