Benchmark: Conso duplicates solution 2

HTML Preparation code:

<!--your preparation HTML code goes here-->

Script Preparation code:

const consommations = [{"annee":2023,"mois":2,"fiabilite_conso":"A"},{"annee":2023,"mois":3,"fiabilite_conso":"E","consommation":{"litre":19624,"m3":19.624,"prix_m3_estime":64.37},"index":{"litre":553554,"m3":553.554}},{"annee":2023,"mois":4,"fiabilite_conso":"M","consommation":{"litre":20380,"m3":20.38,"prix_m3_estime":66.85},"index":{"litre":573178,"m3":573.178}},{"annee":2023,"mois":5,"fiabilite_conso":"M","consommation":{"litre":19293,"m3":19.293,"prix_m3_estime":63.28},"index":{"litre":593558,"m3":593.558}},{"annee":2023,"mois":6,"fiabilite_conso":"M","consommation":{"litre":20048,"m3":20.048,"prix_m3_estime":65.76},"index":{"litre":612851,"m3":612.851}},{"annee":2023,"mois":7,"fiabilite_conso":"E","consommation":{"litre":22635,"m3":22.635,"prix_m3_estime":74.24},"index":{"litre":632899,"m3":632.899}},{"annee":2023,"mois":8,"fiabilite_conso":"M","consommation":{"litre":23212,"m3":23.212,"prix_m3_estime":76.14},"index":{"litre":655534,"m3":655.534}},{"annee":2023,"mois":9,"fiabilite_conso":"M","consommation":{"litre":18667,"m3":18.667,"prix_m3_estime":61.23},"index":{"litre":678746,"m3":678.746}},{"annee":2023,"mois":10,"fiabilite_conso":"E","consommation":{"litre":3319,"m3":3.319,"prix_m3_estime":10.89},"index":{"litre":697413,"m3":697.413}},{"annee":2023,"mois":11,"fiabilite_conso":"M","consommation":{"litre":481,"m3":0.481,"prix_m3_estime":1.58},"index":{"litre":700732,"m3":700.732}},{"annee":2023,"mois":12,"fiabilite_conso":"M","consommation":{"litre":1418,"m3":1.418,"prix_m3_estime":4.65},"index":{"litre":701213,"m3":701.213}},{"annee":2024,"mois":1,"fiabilite_conso":"M","consommation":{"litre":2283,"m3":2.283,"prix_m3_estime":7.49},"index":{"litre":702631,"m3":702.631}},{"annee":2024,"mois":2,"fiabilite_conso":"M","consommation":{"litre":4054,"m3":4.054,"prix_m3_estime":13.3},"index":{"litre":704914,"m3":704.914}},{"annee":2024,"mois":3,"fiabilite_conso":"E","consommation":{"litre":7894,"m3":7.894,"prix_m3_estime":25.89},"index":{"litre":708968,"m3":708.968}},{"annee":2024,"mois":4,"fiabilite_conso":"M","consommation":{"litre":9116,"m3":9.116,"prix_m3_estime":29.9},"index":{"litre":716862,"m3":716.862}},{"annee":2024,"mois":5,"fiabilite_conso":"E","consommation":{"litre":9993,"m3":9.993,"prix_m3_estime":32.78},"index":{"litre":725978,"m3":725.978}},{"annee":2024,"mois":6,"fiabilite_conso":"E","consommation":{"litre":5710,"m3":5.71,"prix_m3_estime":18.73},"index":{"litre":735971,"m3":735.971}},{"annee":2024,"mois":6,"fiabilite_conso":"E","consommation":{"litre":972,"m3":0.972,"prix_m3_estime":3.19},"index":{"litre":619,"m3":0.619}},{"annee":2024,"mois":7,"fiabilite_conso":"E","consommation":{"litre":7604,"m3":7.604,"prix_m3_estime":24.94},"index":{"litre":1591,"m3":1.591}},{"annee":2024,"mois":8,"fiabilite_conso":"M","consommation":{"litre":8279,"m3":8.279,"prix_m3_estime":27.16},"index":{"litre":9195,"m3":9.195}},{"annee":2024,"mois":9,"fiabilite_conso":"M","consommation":{"litre":7006,"m3":7.006,"prix_m3_estime":22.98},"index":{"litre":17474,"m3":17.474}},{"annee":2024,"mois":10,"fiabilite_conso":"E","consommation":{"litre":6036,"m3":6.036,"prix_m3_estime":19.8},"index":{"litre":24480,"m3":24.48}},{"annee":2024,"mois":11,"fiabilite_conso":"A"},{"annee":2024,"mois":12,"fiabilite_conso":"A"},{"annee":2025,"mois":1,"fiabilite_conso":"A"},{"annee":2025,"mois":2,"fiabilite_conso":"A"}]

Tests:

test on loop for each
const getConsommationObjectDate = ( annee, mois, jour, ) => ({ annee, mois, jour, }); const consommationIndisponibleObjectData = {state: 'INDISPONIBLE'} const fusionState = ( actual, added, ) => added === 'A' ? actual ?? 'INDISPONIBLE' : actual === 'ESTIMEE' || added === 'E' ? 'ESTIMEE' : 'MESUREE'; const fusionConsommationObjectData = ( actual, added, ) => ({ volume: (actual?.volume ?? 0) + (added?.litre ?? 0), prix: actual?.prix || added?.prix_m3_estime ? (actual?.prix ?? 0) + (added?.prix_m3_estime ?? 0) : undefined, }); const fusionData = ( actual, added, ) => ({ state: fusionState(actual.state, added.fiabilite_conso), consommation: actual.consommation || added.consommation ? fusionConsommationObjectData(actual.consommation, added.consommation) : undefined, ecoulement: actual.ecoulement || added.ecoulement ? fusionConsommationObjectData(actual.ecoulement, added.ecoulement) : undefined, unit: 'L', }); const result= []; let currentYear; let currentMonth; let currentData = {state: 'INDISPONIBLE'}; consommations.forEach((conso, index) => { if (index === 0) { currentYear = conso.annee; currentMonth = conso.mois; currentData = fusionData(consommationIndisponibleObjectData, conso); } else if (conso.annee === currentYear && conso.mois === currentMonth) { currentData = fusionData(currentData, conso); } else { result.push({ date: getConsommationObjectDate(currentYear, currentMonth - 1), data: currentData, }); currentYear = conso.annee; currentMonth = conso.mois; currentData = fusionData(consommationIndisponibleObjectData, conso); } if (index === consommations.length - 1) { result.push({ date: getConsommationObjectDate(currentYear, currentMonth - 1), data: currentData, }); } });
test two loop
const getConsommationObjectDate = ( annee, mois, jour, ) => ({ annee, mois, jour, }); const getConsommationObjectData = ( consommation, ) => consommation ? { volume: consommation.litre, prix: consommation?.prix_m3_estime, } : undefined; const getConsommationMensuelleObjectData = ( consommation, ) => ({ state: consommation.fiabilite_conso === 'M' ? 'MESUREE' : 'ESTIMEE', consommation: getConsommationObjectData(consommation.consommation), ecoulement: getConsommationObjectData(consommation.ecoulement), unit: 'L', }); const consommationIndisponibleObjectData = {state: 'INDISPONIBLE'} const fusionState = ( actual, added, ) => added === 'A' ? actual : actual === 'E' || added === 'E' ? 'E' : 'M'; const fusionConsommationObjectData = ( actual, added, ) => ({ litre: (actual?.litre ?? 0) + (added?.litre ?? 0), prix_m3_estime: actual?.prix_m3_estime || added?.prix_m3_estime ? (actual?.prix_m3_estime ?? 0) + (added?.prix_m3_estime ?? 0) : undefined, }); const fusionData = ( actual, added, ) => ({ ...actual, fiabilite_conso: fusionState(actual.fiabilite_conso, added.fiabilite_conso), consommation: actual.consommation || added.consommation ? fusionConsommationObjectData(actual.consommation, added.consommation) : undefined, ecoulement: actual.ecoulement || added.ecoulement ? fusionConsommationObjectData(actual.ecoulement, added.ecoulement) : undefined, }); const result= []; let currentYear; let currentMonth; let currentData; consommations.forEach((conso, index) => { if (index === 0) { currentYear = conso.annee; currentMonth = conso.mois; currentData = conso; } else if (conso.annee === currentYear && conso.mois === currentMonth) { currentData = fusionData(currentData, conso); } else { result.push(currentData); currentYear = conso.annee; currentMonth = conso.mois; currentData = conso; } if (index === consommations.length - 1) { result.push(currentData); } }); result.map(conso => ({ date: getConsommationObjectDate(conso.annee, conso.mois - 1), data: conso.fiabilite_conso === 'A' ? {state: 'INDISPONIBLE'} : getConsommationMensuelleObjectData(conso), }))

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
test on loop for each
test two loop

Fastest: N/A

Slowest: N/A

Latest run results:

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

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/605.1.15 (KHTML, like Gecko) Version/18.3 Safari/605.1.15

Browser/OS: Safari 18 on Mac OS X 10.15.7

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Test name	Executions per second
test on loop for each	1199979.4 Ops/sec
test two loop	1085761.0 Ops/sec

Autogenerated LLM Summary (model gpt-4o-mini, generated 2 months ago):

LLMs can make mistakes. Check important info.

### Benchmark Overview

#### Benchmark Name
**Conso duplicates solution 2**

This benchmark is concerned with testing the performance of two different coding approaches that handle the manipulation and consolidation of consumption data represented in a specific format. The consomation data contains monthly consumption figures for various years, indicating the reliability of the consumption measurements with several attributes.

### Comparison of Approaches

1. **Test Case 1: `test on loop for each`**

This method processes the `consommations` array with a single loop where it checks if the current entry belongs to the same year and month as the previous one. If it does, the data is combined; otherwise, it creates an entry in the result array and resets the data for the new month.

- **Pros:**
     - Simplified logic that compactly consolidates consumption data.
     - Memory efficient, as it uses a single accumulator for the current data.

- **Cons:**
     - The complexity increases if the number of properties to check and combine grows. 
     - If additional attributes needed to be tracked, the logic might become more convoluted.

2. **Test Case 2: `test two loop`**

This approach executes two loops: the first one aggregates consumption data, while the second one transforms consolidated entries into a final structure that includes dates.

- **Pros:**
     - Separates data aggregation from data transformation, which enhances readability and maintainability.
     - More explicit handling of different types of consumption statistics (like estimates vs measures).

- **Cons:**
     - It may introduce overhead due to traversing the `consommations` array twice, which could lead to a performance hit especially with a large dataset.
     - Increased memory usage as intermediate data structures may be created for each pass.

### Performance Results

- **Executions per Second:**
  - `test on loop for each`: **1,199,979** executions/second
  - `test two loop`: **1,085,761** executions/second

From the benchmark results, the first method (`test on loop for each`) performs significantly better than the second method in terms of raw execution speed.

### Libraries and Syntax Considerations

There are no special JavaScript libraries or advanced JavaScript syntax being employed in the benchmark cases. The JavaScript language features utilized include:

- **Arrow Functions:** Using syntactical shorthand for function expressions.
- **Optional Chaining (`?.`):** This allows for safe access to nested object properties, returning `undefined` instead of throwing an error if a property is `undefined` or `null`.

### Alternative Approaches

- **Map and Reduce:** Instead of manually managing states within loops, the `Array.prototype.map` and `Array.prototype.reduce` methods could be applied for a more functional approach to data transformations and consolidations. This may lead to cleaner code, albeit at the cost of performance.
  
- **Libraries like Lodash:** Utilizing utility libraries can greatly simplify operations like merging objects, deep cloning, and data manipulation while improving code readability.

- **Typed Arrays:** If the data structure were large, using typed arrays could provide a performance enhancement by leveraging the lower-level memory storage structure of uniform types.

- **Web Workers:** For particularly heavy computations or larger datasets, offloading operations to Web Workers could improve responsiveness if you're working within a browser environment.

### Conclusion

This benchmark underscores the importance of method selection in coding practices to achieve better performance and maintainability. While the first approach demonstrates superior performance, the second method's clearer structure may ultimately be advantageous for teams prioritizing code maintainability over raw execution speed. Software engineers should weigh these factors according to their specific project needs and constraints.

Related benchmarks:

Conso duplicates solution 2 (version: 1)

Comparing performance of: test on loop for each vs test two loop

Created: 2 months ago by: Guest

Jump to the latest result

test on loop for each

test two loop

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model gpt-4o-mini, generated 2 months ago):