Scilab - 30 Metriken & AHP-Score
Einleitung
Scilab ist eine Multi-paradigm-Programmiersprache, die erstmals 1990 erschien und von INRIA entworfen wurde. Hauptanwendungen: Data Science, Scientific Computing, Statistics.
30 Metriken
| Metrik | Wert | Rang |
|---|---|---|
| GitHub Stars | 19156 | 166 |
| Stack Overflow Tags | 254091 | 165 |
| TIOBE Rank | 130 | |
| RedMonk Rank | 130 | |
| PYPL Rank | 137 | |
| Average Salary (USD) | 71426 | 139 |
| Job Postings | 15210 | 149 |
| Benchmarks Score | 0.49 | 111 |
| Learning Curve | Easy | |
| Community Size | Medium | |
| Documentation Quality | 2 | |
| Ecosystem Maturity | 4 | |
| Industry Adoption | 3 | |
| Type System Complexity | 4 | |
| Concurrency Support | 1 | |
| Performance - Execution Speed | 2 | |
| Performance - Memory Usage | 2 | |
| Performance - Startup Time | 1 | |
| Tooling Quality | 3 | |
| Package Manager Quality | 4 | |
| IDE Support | 4 | |
| Debugging Experience | 2 | |
| GitHub Stars Rank | 166 | |
| Stack Overflow Tags Rank | 165 | |
| Average Salary Rank | 139 | |
| Job Postings Rank | 149 | |
| Benchmarks Rank | 111 | |
| Learning Curve Score | 8 | |
| Community Size Score | 4 | |
| AHP Score | 3.59 | 152 |
Hello-World-Beispiel
disp('Hello, World!')
Hauptanwendungsfälle
- Data Science
- Scientific Computing
- Statistics
- Visualization
Beliebte Frameworks
- Scicos
AHP-Score
Scilab AHP-Score: 3.59 (#152)