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Python in Computational Science: Applications and Possibilities
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 46 - Number 20 |
| Year of Publication: 2012 |
| Authors: Md. Golam Rashed, Raquib Ahsan |
10.5120/7058-9799
|
Md. Golam Rashed, Raquib Ahsan . Python in Computational Science: Applications and Possibilities. International Journal of Computer Applications. 46, 20 ( May 2012), 26-30. DOI=10.5120/7058-9799
Abstract
This paper focuses on the role of python in dramatic increase in productivity and high-level of code reuse in computational science. The salient features of python make it an ideal language for scientific computing exposing the shortcomings of legacy languages and prototyping platforms. Python provides a rich collection of built-in data types such as strings, lists, dictionaries; dynamic typing and dynamic binding, modules, classes, exceptions handling, automatic memory management, multiprocessing, parallel computing capabilities. Python can also be used as a glue language to wrap around existing static compiled code to obtain optimum performance. The uptrend of adopting python as a general purpose language along with its vast collection of scientific libraries are also reviewed in this paper, which ensures the long term presence of python and its growing user base in the foreseeable future.
References
- Nonweiler, T. R. (1986). Computational Mathematics: An Introduction to Numerical Approximation. John Wiley & Sons Inc.
- Yang, X. -s. (2008). Introduction To Computational Mathematics. World Scientific Publishing Company.
- Rashed, M. G. (2012). Development and Evaluation of An Open Source Finite Element Analysis Framework. Proceedings of the 1st International Conference on Civil Engineering for Sustainable Development. Khulna: KUET, Bangladesh.
- Hassan, S. , Rao, L. C. , & K, G. B. (2012). Script Enhanced Unit Cell Approach for the Simulation of Compressive Behaviour in Fiber Reinforced Cement Composites. International Journal of Computer Applications , 44 (20), 32-37.
- McCracken, D. D. (1961). A Guide to FORTRAN Programming. New York: Wiley.
- Fitzpatrick, R. (2011, 03 31). Introduction to Computational Physics. Retrieved 04 20, 2012, from Home Page for Richard Fitzpatrick: http://farside. ph. utexas. edu/teaching/329/lectures/lectures. html
- Ritchie, D. M. (1993). The Development of the C Language. The second ACM SIGPLAN History of Programming Languages Conference (pp. 201–208). New York: ACM.
- Stroustrup, B. (2000). The C++ Programming Language. Addison-Wesley.
- Akin, E. (2003). Object Oriented Programming via Fortran 90/95. Cambridge: Cambridge University Press.
- Rashed, M. G. , Ahsan, R. , & Chowdhury, S. R. (2012). Numerical Modelling of Concrete Tensile Strength Test by Wrapping Scripting Language with Compiled Library. International Journal of Computer Applications , 40 (14), 34-38.
- TIOBE Programming Community Index. (2012, 04 20). Retrieved 04 20, 2012, from TIOBE Software: The Coding Standards Company: http://www. tiobe. com/index. php/tiobe_index
- Millman, K. (2011). Python for Scientists and Engineers. Computing in Science & Engineering , 13 (2), 9 - 12.
- Behnel, S. , Bradshaw, R. , Citro, C. , Dalcin, L. , Seljebotn, D. , & Smith, K. (2011). Cython: The Best of Both Worlds. Computing in Science & Engineering , 13 (2), 31 - 39.
- Pe?rez, F. , Granger, B. , & Hunter, J. (2011). Python: An Ecosystem for Scientific Computing. Computing in Science & Engineering , 13 (2), 13 - 21.
- Rossum, G. v. (2012, 04 20). What is Python? Executive Summary. Retrieved 04 20, 2012, from Python Documentation Index: http://www. python. org/doc/essays/blurb/
- Rossum, G. v. (1997, 12 30). Comparing Python to Other Languages. Retrieved 4 20, 2012, from Python Programming Language – Official Website: http://www. python. org/doc/essays/comparisons/
- SciPy. (2012, 4 20). Retrieved 4 20, 2012, from SciPy: http://www. scipy. org/Topical_Software
- Butler, H. (2004). A Guide to the Python Universe for Esri Users. 24th Annual Esri International User Conference. User Conference Proceedings.
- Duff, I. S. , Heroux, M. A. , & Pozo, R. (2002). An overview of the sparse basic linear algebra subprograms: The new standard from the BLAS technical forum. ACM Transactions on Mathematical Software , 28 (2), 239-267.
- Anderson, E. , Bai, Z. , Bischof, C. , Blackford, L. S. , Demmel, J. , Dongarra, J. J. , et al. (1999). LAPACK Users' guide (third ed. ). Philadelphia: Society for Industrial and Applied Mathematics.
- Bruaset, A. M. , & Tveito, A. (Eds. ). (2006). Numerical Solution of Partial Differential Equations on Parallel Computers. Berlin: Springer.
- Summerfield, M. (2007). Rapid GUI Programming with Python and Qt. New Jersey: Prentice Hall.
- van der Walt, S. , Colbert, S. , & Varoquaux, G. (2011). The NumPy Array: A Structure for Efficient Numerical Computation. Computing in Science & Engineering , 13 (2), 22 - 30.
- Joyner, D. , ?ertík, O. , Meurer, A. , & Granger, B. E. (2011). Open source computer algebra systems: SymPy. ACM Communications in Computer Algebra , 225-234.
- Kloss, G. K. (2009). Python Data Plotting and Visualisation Extravaganza. Proceedings of the First Kiwi PyCon (New Zealand). Christchurch: The Python Papers Monograph.
- Hunter, J. D. (2007). Matplotlib: A 2D Graphics Environment. Computing in Science and Engineering , 90-95.
- Ramachandran, P. , & Varoquaux, G. (2011). Mayavi: 3D Visualization of Scientific Data. Computing in Science & Engineering , 13 (2), 40 - 51.
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