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Last update: Kubová Petra Ing. (16.02.2018)
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Last update: Kubová Petra Ing. (16.02.2018)
Thanks to Python's uniqueness students will be able to apply such diversified techniques as iterators, closures and functional constructs to name just a few. Also they will learn principles of program testing and debugging and distributed version control systems (DVCS) which are essential parts of every serious programming work. |
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Last update: Kubová Petra Ing. (16.02.2018)
R: Pilgrim, Mark: Dive Into Python 3. Apress, 2009. ISBN 978-1430224150 R: Stevens, Tim J.; Boucher, Wayne: Python Programming for Biology. Cambridge University Press, 2015. ISBN 978-0-521-89583-5 (hardback), 978-0-521-72009-0 (paperback) A: Necaise, Rance D.: Data Structures and Algorithms Using Python. John Wiley & Sons, Inc, 2011. ISBN 978-0470618295 A: Lee, Kent D.; Hubbart, Steve: Data Structures and Algorithms with Python. Springer, 2015. ISBN 978-3-319-13071-2 A: Bassi, Sebastian: Python for Bioinformatics. Chapman & Hall/CRC, 2009. ISBN 978-1-58488-929-8 |
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Last update: Kubová Petra Ing. (16.02.2018)
web pages of the course at http://vyuka.ookami.cz |
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Last update: Kubová Petra Ing. (16.02.2018)
A credit: homeworks and a semestral work An exam: a written test |
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Last update: Kubová Petra Ing. (16.02.2018)
1. History and overview of Python. 2-4. Basic data structures and control flow tools. Exceptions. 5-6. Functions and their special role in Python. 7. Modules and their usage. 8-9. Classes. Magic methods. 10. Textual and binary input/output. Serialization of data structures. 11. User input. Subprocess handling. Foreign function interface. 12. Testing and debugging. 13-14. Selected internal and external libraries. |
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Last update: Kubová Petra Ing. (16.02.2018)
Basic knowladge of algorithm development and programming (such as BI-PA1 or similar) is assumed. |
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Last update: Kubová Petra Ing. (16.02.2018)
A credit will be given based on home exercises and a semestral work. The exam is in the form of a written test. Each of these three course requirements contributes one third to the final classification. |
Teaching methods | ||||
Activity | Credits | Hours | ||
Účast na přednáškách | 1 | 28 | ||
Příprava na přednášky, semináře, laboratoře, exkurzi nebo praxi | 1.2 | 34 | ||
Práce na individuálním projektu | 1.2 | 34 | ||
Příprava na zkoušku a její absolvování | 0.6 | 16 | ||
Účast na seminářích | 1 | 28 | ||
5 / 5 | 140 / 140 |