Benchmark: Lodash vs Native map, find, filter

HTML Preparation code:

<script src="https://cdn.jsdelivr.net/npm/lodash@4.17.21/lodash.min.js"></script>

Script Preparation code:

var data = Array.from(Array(100000).keys()).map(x => { return { value: x }; });

Tests:

Lodash Find
var x = _.find(data, x => x.value === data.length - 2);
Native Find
var x = data.find(x => x.value === data.length - 2);
Lodash Filter
var x = _.filter(data, x => x.value % 2 === 0);
Native Filter
var x = data.filter(x => x.value % 2 === 0);
Lodash Map Trivial
var x = _.map(data, x => x.value);
Native Map Trivial
var x = data.map(x => x.value);
Lodash Map Hard
var x = _.map(data, x => Math.sqrt(x.value));
Native Map Hard
var x = data.map(x => Math.sqrt(x.value));
Lodash Map Str
var x = _.map(data, x => x.value + "str");
Native Map Str
var x = data.map( x => x.value + "str");
Lodash Find Old style
var x = _.find(data, function(x){ return x.value === data.length - 2});
Native Find Old style
var x = data.find(function(x){ return x.value === data.length - 2});

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Lodash Find
Native Find
Lodash Filter
Native Filter
Lodash Map Trivial
Native Map Trivial
Lodash Map Hard
Native Map Hard
Lodash Map Str
Native Map Str
Lodash Find Old style
Native Find Old style

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 2 years ago)

User agent: Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 YaBrowser/24.1.0.0 Safari/537.36

Browser/OS: Yandex Browser 24 on Linux

View result in a separate tab

Lodash Map Trivial

3K/s

Native Map Trivial

3K/s

Lodash Filter

1K/s

Native Filter

1K/s

Lodash Find

259/s

Lodash Find Old style

256/s

Lodash Map Str

251/s

Native Find Old style

248/s

Native Find

244/s

Native Map Str

215/s

Lodash Map Hard

122/s

Native Map Hard

114/s

View exact numbers

Test name	Executions per second
✓ Lodash Map Trivial	3,269 Ops/sec
Native Map Trivial	2,604 Ops/sec
Lodash Filter	1,348 Ops/sec
Native Filter	1,147 Ops/sec
Lodash Find	259 Ops/sec
Lodash Find Old style	256 Ops/sec
Lodash Map Str	251 Ops/sec
Native Find Old style	248 Ops/sec
Native Find	244 Ops/sec
Native Map Str	215 Ops/sec
Lodash Map Hard	122 Ops/sec
Native Map Hard	114 Ops/sec

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

LLMs can make mistakes. Check important info.

It seems like you want to parse the provided JSON data and extract some insights from it.

Here's an example of how you can achieve this using Python:

```python
import json

# Load the JSON data
json_data = """[
    {"RawUAString": "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 YaBrowser/24.1.0.0 Safari/537.36", 
     "Browser": "Yandex Browser 24", 
     "DevicePlatform": "Desktop", 
     "OperatingSystem": "Linux",
     "ExecutionsPerSecond": 1146.60791015625,
     "TestName": "Native Filter"
    },
    ...
]"""

# Parse the JSON data
data = json.loads(json_data)

# Extract insights
browsers = [row['Browser'] for row in data]
device_platforms = [row['DevicePlatform'] for row in data]
operating_systems = [row['OperatingSystem'] for row in data]

print(f"Unique Browsers: {len(set(browsers))}")
print(f"Browsers with most executions: {[browsers.count(x) for x in set(browsers)]}")
print(f"Most common DevicePlatform: {device_platforms.count(device_platforms[0])} ({device_platforms[0]})")
print(f"Most common OperatingSystem: {operating_systems.count(operating_systems[0])} ({operating_systems[0]})")

# You can also calculate the average executions per second
executions_per_second = [row['ExecutionsPerSecond'] for row in data]
average_executions_per_second = sum(executions_per_second) / len(executions_per_second)
print(f"Average executions per second: {average_executions_per_second}")
```

This script loads the JSON data, extracts the relevant columns, and calculates some basic insights. You can adjust it to fit your specific use case.

Please note that this is a simplified example and might not cover all possible scenarios.

Lodash vs Native map, find, filter (version: 3) Benchmark.js

Comparing performance of: `Lodash Find vs Native Find vs Lodash Filter vs Native Filter vs Lodash Map Trivial vs Native Map Trivial vs Lodash Map Hard vs Native Map Hard vs Lodash Map Str vs Native Map Str vs Lodash Find Old style vs Native Find Old style`

Created: 3 years ago by: Registered User

Go to the latest result

Lodash Find

Native Find

Lodash Filter

Native Filter

Lodash Map Trivial

Native Map Trivial

Lodash Map Hard

Native Map Hard

Lodash Map Str

Native Map Str

Lodash Find Old style

Native Find Old style

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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

Lodash vs Native map, find, filter (version: 3) Benchmark.js

Comparing performance of: Lodash Find vs Native Find vs Lodash Filter vs Native Filter vs Lodash Map Trivial vs Native Map Trivial vs Lodash Map Hard vs Native Map Hard vs Lodash Map Str vs Native Map Str vs Lodash Find Old style vs Native Find Old style

Created: 3 years ago by: Registered User

Go to the latest result

Lodash Find

Native Find

Lodash Filter

Native Filter

Lodash Map Trivial

Native Map Trivial

Lodash Map Hard

Native Map Hard

Lodash Map Str

Native Map Str

Lodash Find Old style

Native Find Old style

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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

Related benchmarks

Comparing performance of: `Lodash Find vs Native Find vs Lodash Filter vs Native Filter vs Lodash Map Trivial vs Native Map Trivial vs Lodash Map Hard vs Native Map Hard vs Lodash Map Str vs Native Map Str vs Lodash Find Old style vs Native Find Old style`