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filtermap vs flatmap
(version: 0)
Comparing performance of:
filtermap vs flatmap vs proc
Created:
5 years ago
by:
Guest
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Tests:
filtermap
const arr = Array.from(new Array(10000), (_, i) => i) const result = arr.filter(n => n % 2 === 0).map(n => n / 2)
flatmap
const arr = Array.from(new Array(10000), (_, i) => i) const result = arr.flatMap(n => n % 2 === 0 ? [n / 2] : [])
proc
const arr = Array.from(new Array(10000), (_, i) => i) const result = [] for (const i of arr) { if (i % 2 === 0) result.push(i/2) }
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Suite status:
<idle, ready to run>
Run tests (3)
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Test case name
Result
filtermap
flatmap
proc
Fastest:
N/A
Slowest:
N/A
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Autogenerated LLM Summary
(model
llama3.2:3b
, generated one year ago):
I'd be happy to help explain the JavaScript benchmark. **What is being tested?** The provided JSON represents three test cases for comparing the performance of three different approaches to filtering and mapping an array: 1. `filtermap`: Using the `Array.prototype.filter()` method to filter out odd numbers, followed by `Array.prototype.map()` to divide each remaining number by 2. 2. `flatmap`: Using the `Array.prototype.flatMap()` method to directly map over the array of numbers, where each odd number is mapped to an array containing the divided result. 3. `proc`: Using a simple for loop to filter out odd numbers and then map each even number to its half. **Options compared** The three options are compared in terms of their execution time, measured as "ExecutionsPerSecond". **Pros and cons of each approach:** 1. `filtermap`: * Pros: Simple and concise code; leverages built-in methods for filtering and mapping. * Cons: May have overhead due to the extra function calls and iterations. 2. `flatmap`: * Pros: Directly maps over the array, potentially avoiding extra iterations or function calls. * Cons: May be less readable than other approaches, as it uses an arrow function with a conditional statement; also, some browsers may not support `flatMap()` at all. 3. `proc`: * Pros: Avoids built-in methods and potential overhead from function calls; potentially faster due to direct iteration. * Cons: More verbose code; requires manual filtering and mapping logic. **Library usage** None of the test cases explicitly uses any external libraries, but it's worth noting that some browsers may have specific optimizations or implementations for certain methods (e.g., `flatMap()`). **Special JS feature/syntax** The benchmark tests modern JavaScript features like: * Arrow functions (`=>`) * Template literals (`\r\n` for line breaks) * Spread syntax (`new Array(10000)`) These features are widely supported by modern browsers and can affect the execution time of certain code paths. **Alternatives** Other approaches to filtering and mapping arrays might include: 1. Using `Array.prototype.reduce()` with a custom accumulator function. 2. Utilizing third-party libraries like Lodash or Ramda for more expressive filtering and mapping operations. 3. Implementing a custom loop-based solution using bitwise operations (e.g., `x & 1`) to filter out odd numbers. However, the specific test cases provided on MeasureThat.net focus on comparing built-in methods (`filtermap`, `flatMap`, and `proc`) rather than alternative approaches.
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