Benchmark: Omit in loop vs Delete

Script Preparation code:

data = { a:'koko',b:'koko',c:'koko',d:'koko',e:'koko',f:'koko',g:'koko',h:'koko',i:'koko',x:'asd' }

Tests:

Omit
function removeByOmit(entities,itemId) { const out = {}; Object.keys(entities).forEach(k => { if (k !== itemId) { out[k] = entities[k]; } }); return out; }; removeByOmit(data, 'f');
Delete
function removeByDelete(entities,itemId) { delete entities[itemId]; }; removeByDelete(data, 'f');

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Omit
Delete

Fastest: N/A

Slowest: N/A

Latest run results:

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Autogenerated LLM Summary (model llama3.2:3b, generated one year ago):

LLMs can make mistakes. Check important info.

The provided benchmark measures the performance difference between two approaches: omitting items from an object in a loop versus deleting individual items directly.

**Omitting items from an object in a loop**

In this approach, the `removeByOmit` function iterates over each key in the object, checks if it's not equal to the specified item ID, and assigns the corresponding value to a new object. This process is repeated for all keys, effectively removing the specified item from the original object.

**Deleting individual items directly**

In this approach, the `removeByDelete` function simply deletes the specified item ID from the object using the `delete` operator.

Now, let's discuss the pros and cons of each approach:

**Omitting items in a loop:**

Pros:

*   More flexible, as it allows for custom logic to be applied before or after removing items.
*   Can handle cases where an item is not found in the object, as the loop will simply skip over it.

Cons:

*   May be slower due to the overhead of iterating over each key and creating a new object.
*   Requires more memory allocation, as a new object is created for every iteration.

**Deleting individual items directly:**

Pros:

*   Faster, as it only involves deleting an item from the existing object, without the need for additional memory allocation or loops.
*   More efficient in terms of memory usage, as it doesn't require creating a new object.

Cons:

*   Less flexible, as it only provides the basic `delete` operation and does not allow for custom logic before or after removal.
*   May not work correctly if an item is not found in the object, resulting in undefined behavior.

In general, omitting items in a loop can be beneficial when you need more control over the removal process or when handling cases where an item is not present. However, it may come at the cost of slower performance and increased memory usage.

On the other hand, deleting individual items directly is faster and more efficient but may lack flexibility in certain scenarios.

**Library usage:**

There is no explicit library mentioned in the benchmark definitions. However, some JavaScript features used here include:

*   `Object.keys()` to iterate over object keys.
*   `forEach()` to iterate over each key.

These are built-in JavaScript methods and do not require any external libraries for their functionality.

**Special JS feature or syntax:**

There is no special JS feature or syntax mentioned in the benchmark definitions. However, it's worth noting that some browsers may have specific optimizations or features enabled by default (e.g., `--expose-globals` flag in Chrome) which could potentially affect benchmark results.

**Other alternatives:**

Alternative approaches to removing items from an object might include:

*   Using a `Set` data structure to store unique keys, and then iterating over the set to remove items.
*   Utilizing a library like Lodash or Underscore.js that provides utility functions for working with objects, including removal methods.

However, these alternatives may not be as straightforward or efficient as the approaches demonstrated in the benchmark definitions.

Related benchmarks:

Omit in loop vs Delete (version: 0)

Comparing performance of: Omit vs Delete

Created: 2 years ago by: Guest

Jump to the latest result

Omit

Delete

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

No previous run results

Autogenerated LLM Summary (model llama3.2:3b, generated one year ago):