Jupyter - 30 métriques et score AHP
Introduction
Jupyter est un langage de programmation Multi-paradigm apparu en 2014, conçu par Project Jupyter. Cas d’usage principaux : Interactive Computing, Data Exploration, Reproducible Research.
30 métriques
| Métrique | Valeur | Rang |
|---|---|---|
| GitHub Stars | 48176 | 38 |
| Stack Overflow Tags | 576229 | 53 |
| TIOBE Rank | 58 | |
| RedMonk Rank | 64 | |
| PYPL Rank | 57 | |
| Average Salary (USD) | 105158 | 44 |
| Job Postings | 32130 | 37 |
| Benchmarks Score | 0.59 | 71 |
| Learning Curve | Medium | |
| Community Size | Medium | |
| Documentation Quality | 5 | |
| Ecosystem Maturity | 6 | |
| Industry Adoption | 6 | |
| Type System Complexity | 6 | |
| Concurrency Support | 6 | |
| Performance - Execution Speed | 6 | |
| Performance - Memory Usage | 6 | |
| Performance - Startup Time | 4 | |
| Tooling Quality | 7 | |
| Package Manager Quality | 5 | |
| IDE Support | 8 | |
| Debugging Experience | 7 | |
| GitHub Stars Rank | 38 | |
| Stack Overflow Tags Rank | 53 | |
| Average Salary Rank | 44 | |
| Job Postings Rank | 37 | |
| Benchmarks Rank | 71 | |
| Learning Curve Score | 6 | |
| Community Size Score | 6 | |
| AHP Score | 6.11 | 55 |
Exemple Hello World
# In a notebook cell:
print('Hello, World!')
Cas d’usage principaux
- Interactive Computing
- Data Exploration
- Reproducible Research
Frameworks populaires
- JupyterLab
- JupyterHub
- nbconvert
Score AHP
Jupyter Score AHP: 6.11 (#55)