Scilab - 30 metriek en AHP-score
Inleiding
Scilab is een Multi-paradigm-programmeertaal die voor het eerst verscheen in 1990, ontworpen door INRIA. Belangrijkste toepassingen: Data Science, Scientific Computing, Statistics.
30 metriek
| Metriek | Waarde | Rang |
|---|---|---|
| GitHub Stars | 18419 | 175 |
| Stack Overflow Tags | 326663 | 140 |
| TIOBE Rank | 133 | |
| RedMonk Rank | 132 | |
| PYPL Rank | 131 | |
| Average Salary (USD) | 76817 | 122 |
| Job Postings | 16275 | 142 |
| Benchmarks Score | 0.27 | 185 |
| Learning Curve | Easy | |
| Community Size | Small | |
| Documentation Quality | 4 | |
| Ecosystem Maturity | 2 | |
| Industry Adoption | 3 | |
| Type System Complexity | 2 | |
| Concurrency Support | 1 | |
| Performance - Execution Speed | 2 | |
| Performance - Memory Usage | 3 | |
| Performance - Startup Time | 1 | |
| Tooling Quality | 4 | |
| Package Manager Quality | 1 | |
| IDE Support | 3 | |
| Debugging Experience | 3 | |
| GitHub Stars Rank | 175 | |
| Stack Overflow Tags Rank | 140 | |
| Average Salary Rank | 122 | |
| Job Postings Rank | 142 | |
| Benchmarks Rank | 185 | |
| Learning Curve Score | 9 | |
| Community Size Score | 2 | |
| AHP Score | 3.44 | 166 |
Hello World voorbeeld
disp('Hello, World!')
Belangrijkste toepassingen
- Data Science
- Scientific Computing
- Statistics
- Visualization
Populaire frameworks
- Scicos
AHP-score
Scilab AHP-score: 3.44 (#166)