prikaz prve stranice dokumenta Optimizacija Python koda
  Download
PDF 318.44 KB
undergraduate thesis
Optimizacija Python koda
2017. urn:nbn:hr:126:939901
Blažević, Lucija
Josip Juraj Strossmayer University of Osijek
Department of Mathematics
Chair of Applied Mathematics
Computer Science Research Group

Cite this document

Blažević, L. (2017). Optimizacija Python koda (Undergraduate thesis). Retrieved from https://urn.nsk.hr/urn:nbn:hr:126:939901

Blažević, Lucija. "Optimizacija Python koda." Undergraduate thesis, Josip Juraj Strossmayer University of Osijek, Department of Mathematics, 2017. https://urn.nsk.hr/urn:nbn:hr:126:939901

Blažević, Lucija. "Optimizacija Python koda." Undergraduate thesis, Josip Juraj Strossmayer University of Osijek, Department of Mathematics, 2017. https://urn.nsk.hr/urn:nbn:hr:126:939901

Blažević, L. (2017). 'Optimizacija Python koda', Undergraduate thesis, Josip Juraj Strossmayer University of Osijek, Department of Mathematics, accessed 17 May 2022, https://urn.nsk.hr/urn:nbn:hr:126:939901

Blažević L. Optimizacija Python koda [Undergraduate thesis]. Osijek: Josip Juraj Strossmayer University of Osijek, Department of Mathematics; 2017 [cited 2022 May 17] Available at: https://urn.nsk.hr/urn:nbn:hr:126:939901

L. Blažević, "Optimizacija Python koda", Undergraduate thesis, Josip Juraj Strossmayer University of Osijek, Department of Mathematics, Osijek, 2017. Available at: https://urn.nsk.hr/urn:nbn:hr:126:939901

Please login to the repository to save this object to your list.
Metadata
TitleOptimizacija Python koda
Title (english)Optimizing Python Code
AuthorLucija Blažević
MentorDomagoj Matijević (mentor)
GranterJosip Juraj Strossmayer University of Osijek
Department of Mathematics
(Chair of Applied Mathematics)
(Computer Science Research Group)
Osijek
Defense date and country2017-03-30, Croatia
Scientific / art field,
discipline and subdiscipline		NATURAL SCIENCES
Mathematics
Abstract
Optimizacija koda ( code tuning) je vrlo korisna stvar kada se bavimo ozbiljnijim programiranjem. Zahvaljujući njoj naš kod postaje brži i efikasniji. Upravo time ćemo se u ovome radu baviti. Naučit ćemo kako optimizirati pojedine dijelove programskog koda napisanog u programskom jeziku Python. Kroz primjere ćemo vidjeti koje dijelove je potrebno optimizirati, a koji su, već sami po sebi, dovoljno brzi i nemaju potrebe za optimizacijom. Proučit ćemo optimizaciju regularnih izraza, stringova, lista te rječnika. Na kraju samog rada, donijet ćemo konkretne zaključke i smjernice koje će vam reći čega se trebate pridržavati te što trebate izbjegavati kada je riječ o optimizaciji. Nadam se kako će vam one biti korisne u daljnjem radu ukoliko se budete susretali s optimizacijom
Abstract (english)
Code tuning is a very usefull thing when dealing with some serious programming. Thanks to code tuning, our code becomes faster and more efficient. That is exactly what we’re gonna deal with in this paper. We will learn how to optimize individual parts of program code written in Python Programming Language. Through examples we will see which parts need to be optimized, and which themselves are already fast enough and do not have any need for optimization. Also, we will study the optimization of regular expressions, strings, lists and dictionaries. At the end of this paperwork, we’ll get concrete conclusions and guidelines that will tell you what you should comply with and what you should avoid when it comes to optimization. I hope that they will be useful in further work if you encounter optimization.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:126:939901
Study programmeTitle: University undergraduate study programme in mathematics
Study programme type: university
Study level: undergraduate
Academic / professional title: sveučilišni/a prvostupnik/prvostupnica (baccalaureus/baccalaurea) matematike (sveučilišni/a prvostupnik/prvostupnica (baccalaureus/baccalaurea) matematike)
Type of resourceText
File originBorn digital
Access conditionsOpen access
Terms of useLicence In copyright icon
Created on2017-04-26 10:38:05