Q# - 30 métriques et score AHP
Introduction
Q# est un langage de programmation Multi-paradigm apparu en 2017, conçu par Microsoft. Cas d’usage principaux : Data Science, Scientific Computing, Statistics.
30 métriques
| Métrique | Valeur | Rang |
|---|---|---|
| GitHub Stars | 15390 | 186 |
| Stack Overflow Tags | 186259 | 191 |
| TIOBE Rank | 148 | |
| RedMonk Rank | 155 | |
| PYPL Rank | 147 | |
| Average Salary (USD) | 56671 | 191 |
| Job Postings | 12207 | 177 |
| Benchmarks Score | 0.4 | 145 |
| Learning Curve | Easy | |
| Community Size | Small | |
| Documentation Quality | 3 | |
| Ecosystem Maturity | 4 | |
| Industry Adoption | 2 | |
| Type System Complexity | 2 | |
| Concurrency Support | 4 | |
| Performance - Execution Speed | 4 | |
| Performance - Memory Usage | 5 | |
| Performance - Startup Time | 2 | |
| Tooling Quality | 2 | |
| Package Manager Quality | 1 | |
| IDE Support | 3 | |
| Debugging Experience | 1 | |
| GitHub Stars Rank | 186 | |
| Stack Overflow Tags Rank | 191 | |
| Average Salary Rank | 191 | |
| Job Postings Rank | 177 | |
| Benchmarks Rank | 145 | |
| Learning Curve Score | 10 | |
| Community Size Score | 2 | |
| AHP Score | 3.53 | 164 |
Exemple Hello World
namespace Hello { @EntryPoint() operation HelloQ() : Unit { Message("Hello, World!") } }
Cas d’usage principaux
- Data Science
- Scientific Computing
- Statistics
- Visualization
Frameworks populaires
- Microsoft QDK
- Azure Quantum
Score AHP
Q# Score AHP: 3.53 (#164)