{"id":53299,"date":"2019-11-28T00:00:00","date_gmt":"2019-11-27T21:00:00","guid":{"rendered":"https:\/\/prohoster.info\/blog\/blog_prohoster\/56-proektov-na-python-s-otkrytym-ishodnym-kodom"},"modified":"2020-02-18T14:01:11","modified_gmt":"2020-02-18T11:01:11","slug":"56-proektov-na-python-s-otkrytym-ishodnym-kodom","status":"publish","type":"post","link":"https:\/\/prohoster.info\/sq\/blog\/novosti-interneta\/56-proektov-na-python-s-otkrytym-ishodnym-kodom","title":{"rendered":"56 projekte n\u00eb Python me kod t\u00eb hapur","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"<p><img decoding=\"async\" alt=\"56 projekte n\u00eb Python me kod t\u00eb hapur\" src=\"\/wp-content\/uploads\/2019\/11\/424ea06c178ea7e7823676a1119763e9.jpeg\" style=\"display:block;margin: 0 auto;\" \/><br \/>\n<\/p>\n<h3>1. Flask<\/h3>\n<p>\nFlask \u00ebsht\u00eb nj\u00eb mikro-framework i shkruar n\u00eb Python. Ai nuk ka verifikime p\u00ebr format dhe nivelin e abstraksionit t\u00eb baz\u00ebs s\u00eb t\u00eb dh\u00ebnave, por ju lejon t\u00eb p\u00ebrdorni biblioteka t\u00eb jashtme p\u00ebr funksione t\u00eb zakonshme. Pik\u00ebrisht kjo e b\u00ebn at\u00eb nj\u00eb mikro-framework. Flask \u00ebsht\u00eb i destinuar p\u00ebr krijimin e shpejt\u00eb dhe t\u00eb thjesht\u00eb t\u00eb aplikacioneve, si dhe \u00ebsht\u00eb i shkall\u00ebzuesh\u00ebm dhe i leht\u00eb. Ai bazohet n\u00eb projektet Werkzeug dhe Jinja2. Mund t\u00eb m\u00ebsoni m\u00eb shum\u00eb rreth tij n\u00eb artikullin m\u00eb t\u00eb fundit t\u00eb DataFlair mbi <noindex><a rel=\"nofollow\" href=\"https:\/\/data-flair.training\/blogs\/python-flask-tutorial\/\">Python Flask<\/a><\/noindex>.<\/p>\n<h3>2. Keras<\/h3>\n<p>\nKeras \u00ebsht\u00eb nj\u00eb bibliotek\u00eb p\u00ebr rrjete nervore me kod t\u00eb hapur, e shkruar n\u00eb Python. Ajo \u00ebsht\u00eb miq\u00ebsore ndaj p\u00ebrdoruesve, modular dhe e zgjerueshme, si dhe mund t\u00eb funksionoj\u00eb sip\u00ebr TensorFlow, Theano, PlaidML ose Microsoft Cognitive Toolkit (CNTK). Keras ka gjith\u00e7ka: skema, funksione t\u00eb synuara dhe transferimi, optimizues dhe shum\u00eb m\u00eb tep\u00ebr. Ajo gjithashtu mb\u00ebshtet rrjete nervore konvencionale dhe rekurrente.<\/p>\n<p>Puna mbi projektin m\u00eb t\u00eb fundit me kod t\u00eb hapur mbi Keras \u00ebsht\u00eb <noindex><a rel=\"nofollow\" href=\"https:\/\/data-flair.training\/blogs\/project-in-python-breast-cancer-classification\/\">Klasifikimi i kancerit t\u00eb gjirit<\/a><\/noindex>.<br \/>\n<noindex><a rel=\"nofollow\" name=\"habracut\"><\/a><\/noindex><\/p>\n<blockquote><p><noindex><a rel=\"nofollow\" href=\"https:\/\/www.edsd.ru\/\" title=\"EDISON Software - zhvillim web\"><img decoding=\"async\" alt=\"56 projekte n\u00eb Python me kod t\u00eb hapur\" src=\"\/wp-content\/uploads\/2019\/11\/4b13d579a890b450683f1a60ba814766.jpeg\" style=\"display:block;margin: 0 auto;\" \/><\/a><\/noindex><br clear=\"right\"><br \/>\nArtikulli \u00ebsht\u00eb p\u00ebrkthyer me mb\u00ebshtetje nga kompania EDISON Software, e cila <noindex><a rel=\"nofollow\" href=\"https:\/\/www.edsd.ru\/diagnostika-hranilishha-dokumentov-vivaldi\">n\u00eb zhvillimin e nj\u00eb sistemi diagnostik p\u00ebr ruajtjen e dokumenteve Vivaldi<\/a><\/noindex>, dhe gjithashtu <noindex><a rel=\"nofollow\" href=\"https:\/\/www.edsd.ru\/ru\/princypy\/investiruem-v-produkty\">investon n\u00eb startup-e<\/a><\/noindex>.<\/p><\/blockquote>\n<h3>3. SpaCy<\/h3>\n<p>\nKjo \u00ebsht\u00eb nj\u00eb bibliotek\u00eb me kod t\u00eb hapur p\u00ebr <noindex><a rel=\"nofollow\" href=\"https:\/\/data-flair.training\/blogs\/nlp-natural-language-processing\/\">punimin e gjuh\u00ebs natyrore (NLP)<\/a><\/noindex> e shkruar n\u00eb Python dhe Cython. Nd\u00ebrsa NLTK \u00ebsht\u00eb m\u00eb e p\u00ebrshtatshme p\u00ebr q\u00ebllime m\u00ebsimore dhe k\u00ebrkimore, puna e spaCy p\u00ebrqendrohet n\u00eb ofrimin e softuerit p\u00ebr prodhim. P\u00ebr m\u00eb tep\u00ebr, Thinc \u00ebsht\u00eb nj\u00eb bibliotek\u00eb e m\u00ebsimit t\u00eb makinerive t\u00eb spaCy q\u00eb ofron modele CNN p\u00ebr etiketat e pjes\u00ebve t\u00eb foljes, p\u00ebrpunimin e var\u00ebsive dhe njohjen e objekteve t\u00eb em\u00ebruara.<\/p>\n<h3>4. Sentry<\/h3>\n<p>\nSentry ofron monitorimin e gabimeve me kod t\u00eb hapur, n\u00eb m\u00ebnyr\u00eb q\u00eb t\u00eb mund t\u00eb zbulojn\u00eb dhe klasifikojn\u00eb gabimet n\u00eb koh\u00eb reale. Thjesht instaloni SDK p\u00ebr gjuh\u00ebn(e) ose framework-un(e) tuaj dhe filloni pun\u00ebn. Ai lejon kapjen e p\u00ebrjashtimeve t\u00eb paqasuara, shqyrtimin e shtigjeve t\u00eb gabimeve, analizimin e ndikimit t\u00eb \u00e7do problemi, ndjekjen e gabimeve n\u00eb projekte t\u00eb ndryshme, d\u00ebrgimin e problemeve dhe shum\u00eb m\u00eb tep\u00ebr. P\u00ebrdorimi i Sentry do t\u00eb thot\u00eb m\u00eb pak gabime dhe m\u00eb shum\u00eb kod t\u00eb d\u00ebrguar.<\/p>\n<h3>5. OpenCV<\/h3>\n<p>\nOpenCV \u00ebsht\u00eb nj\u00eb bibliotek\u00eb p\u00ebr vizionin kompjuterik dhe m\u00ebsimin e makinerive me kod t\u00eb hapur. Biblioteka ka mbi 2500 algoritme t\u00eb optimizuar p\u00ebr detyrat e vizionit kompjuterik, si zbulesa dhe njohja e objekteve, klasifikimi i aktiviteteve t\u00eb ndryshme njer\u00ebzore, ndjekja e l\u00ebvizjeve me kamer\u00eb, nd\u00ebrtimi i modeleve 3D t\u00eb objekteve, p\u00ebrbashkimi i imazheve p\u00ebr t\u00eb krijuar imazhe me definicion t\u00eb lart\u00eb dhe shum\u00eb detyra t\u00eb tjera. Biblioteka \u00ebsht\u00eb e disponueshme p\u00ebr shum\u00eb gjuh\u00eb, t\u00eb tilla si Python, C++, Java, etj.<\/p>\n<p>Numri i yjeve n\u00eb Github: 39585<\/p>\n<p>A keni punuar ndonj\u00ebher\u00eb mbi ndonj\u00eb projekt OpenCV? K\u00ebtu \u00ebsht\u00eb nj\u00eb \u2014 <noindex><a rel=\"nofollow\" href=\"https:\/\/data-flair.training\/blogs\/python-project-gender-age-detection\/\">Projekti i p\u00ebrcaktimit t\u00eb gjinis\u00eb dhe mosh\u00ebs<\/a><\/noindex><\/p>\n<h3>6. Nilearn<\/h3>\n<p>\nKy \u00ebsht\u00eb nj\u00eb modul p\u00ebr implementimin e shpejt\u00eb dhe t\u00eb thjesht\u00eb t\u00eb m\u00ebsimit statistik mbi t\u00eb dh\u00ebnat NeuroImaging. Ai lejon p\u00ebrdorimin e scikit-learn p\u00ebr statistika multi-dimensionale p\u00ebr modelimin parashikues, klasifikimin, dekodimin dhe analizimin e lidhjeve. Nilearn \u00ebsht\u00eb pjes\u00eb e ekosistemit NiPy, q\u00eb p\u00ebrb\u00ebn nj\u00eb komunitet t\u00eb dedikuar n\u00eb p\u00ebrdorimin e Python p\u00ebr analiz\u00ebn e t\u00eb dh\u00ebnave t\u00eb neuroimazhit.<\/p>\n<p>Numri i yjeve n\u00eb <noindex><a rel=\"nofollow\" href=\"https:\/\/github.com\/nilearn\/nilearn\">Github<\/a><\/noindex>: 549<\/p>\n<h3>7. scikit-Learn<\/h3>\n<p>\nScikit-learn \u00ebsht\u00eb nj\u00eb tjet\u00ebr projekt i Python me kod t\u00eb hapur. \u00cbsht\u00eb nj\u00eb bibliotek\u00eb shum\u00eb e njohur p\u00ebr m\u00ebsimin e makinerive n\u00eb Python. Shpesh p\u00ebrdoret me NumPy dhe SciPy, SciPy ofron klasifikimin, regresionin dhe grumbullimin \u2014 mb\u00ebshtet <noindex><a rel=\"nofollow\" href=\"https:\/\/data-flair.training\/blogs\/svm-support-vector-machine-tutorial\/\">SVM (Support Vector Machines)<\/a><\/noindex>, pyje t\u00eb rast\u00ebsishme, grumbullim gradient, k-mesatare dhe DBSCAN. Kjo bibliotek\u00eb \u00ebsht\u00eb e shkruar n\u00eb gjuh\u00ebt Python dhe Cython.<\/p>\n<p>Numri i yjeve n\u00eb Github: 37,144<\/p>\n<h3>8. PyTorch<\/h3>\n<p>\nPyTorch \u00ebsht\u00eb nj\u00eb tjet\u00ebr bibliotek\u00eb e hapur p\u00ebr m\u00ebsimin e makinerive, e shkruar n\u00eb Python dhe p\u00ebr Python. Ai \u00ebsht\u00eb nd\u00ebrtuar mbi bibliotek\u00ebn Torch dhe p\u00ebrshtatet shum\u00eb mir\u00eb p\u00ebr fusha t\u00eb tilla si vizioni kompjuterik dhe p\u00ebrpunimi i gjuh\u00ebs natyrore (NLP). Ai gjithashtu ka nj\u00eb front-end C++. <\/p>\n<p>Mes shum\u00eb ve\u00e7orive t\u00eb tjera, PyTorch ofron dy karakteristika t\u00eb larta:<\/p>\n<ul>\n<li>Llogaritjet tensoriale me p\u00ebrshpejtim t\u00eb fuqish\u00ebm me GPU<\/li>\n<li>Rrjetet nervore t\u00eb thella<\/li>\n<\/ul>\n<p>Numri i yjeve n\u00eb Github: 31 779<\/p>\n<h3>9. Librosa<\/h3>\n<p>\nLibrosa \u00ebsht\u00eb nj\u00eb nga bibliotekat m\u00eb t\u00eb mira p\u00ebr Python p\u00ebr analiz\u00ebn e muzik\u00ebs dhe audio. Ajo p\u00ebrmban komponent\u00ebt e nevojsh\u00ebm q\u00eb p\u00ebrdoren p\u00ebr t\u00eb marr\u00eb informacione nga muzika. Biblioteka \u00ebsht\u00eb e dokumentuar mir\u00eb dhe p\u00ebrmban disa udh\u00ebzime dhe shembuj q\u00eb do ta leht\u00ebsojn\u00eb p\u00ebrmbushjen e detyr\u00ebs tuaj.<\/p>\n<p>Numri i yjeve n\u00eb Github: 3107<\/p>\n<p>Implementimi i projektit me kod t\u00eb hapur n\u00eb Python dhe Librosa \u00ebsht\u00eb <noindex><a rel=\"nofollow\" href=\"https:\/\/data-flair.training\/blogs\/python-mini-project-speech-emotion-recognition\/\">p\u00ebr njohjen e emocioneve t\u00eb z\u00ebrit<\/a><\/noindex>. <\/p>\n<h3>10. Gensim<\/h3>\n<p>\nGensim \u2014 \u00ebsht\u00eb nj\u00eb bibliotek\u00eb Python p\u00ebr modelimin e temave, indeksimin e dokumenteve dhe k\u00ebrkimin e ngjashm\u00ebrive me kompanit\u00eb e m\u00ebdha. Ajo fokusohet n\u00eb komunitetet e NLP dhe k\u00ebrkimin e informacionit. Gensim \u00ebsht\u00eb shkurtim nga \"gjenar similar\". M\u00eb par\u00eb, ajo krijonte nj\u00eb list\u00eb t\u00eb shkurt\u00ebr t\u00eb artikujve t\u00eb ngjash\u00ebm me k\u00ebt\u00eb artikull. Gensim \u00ebsht\u00eb e qart\u00eb, efektive dhe e shkall\u00ebzueshme. Gensim implementon nj\u00eb zbatim efektiv dhe t\u00eb thjesht\u00eb t\u00eb modelimit semantik t\u00eb paudhur nga teksti i thjesht\u00eb.<\/p>\n<p>Numri i yjeve n\u00eb Github: 9 870<\/p>\n<h3>11. Django<\/h3>\n<p>\n<noindex><a rel=\"nofollow\" href=\"https:\/\/data-flair.training\/blogs\/django-tutorials-home\/\">Django<\/a><\/noindex> \u2014 nj\u00eb framework i nivelit t\u00eb lart\u00eb Python, i cili inkurajon zhvillimin e shpejt\u00eb dhe beson n\u00eb parimin DRY (mos e p\u00ebrs\u00ebrit). Ai \u00ebsht\u00eb nj\u00eb nga framework-et m\u00eb t\u00eb fuqishme dhe m\u00eb t\u00eb p\u00ebrdorura p\u00ebr Python. Bazohet n\u00eb modelin MTV (Model-Template-View).<\/p>\n<p>Numri i yjeve n\u00eb Github: 44 214<\/p>\n<h3>12. Njohja e fytyr\u00ebs<\/h3>\n<p>\nNjohja e fytyr\u00ebs \u00ebsht\u00eb nj\u00eb projekt popullor n\u00eb GitHub. Ai njeh leht\u00ebsisht fytyrat dhe manipuluar ato duke p\u00ebrdorur Python \/ komand\u00ebn dhe p\u00ebrdor bibliotek\u00ebn m\u00eb t\u00eb thjesht\u00eb p\u00ebr njohjen e fytyr\u00ebs. P\u00ebrdor dlib me m\u00ebsim t\u00eb thell\u00eb p\u00ebr detektimin e fytyrave me sakt\u00ebsi 99.38% n\u00eb testin Wild benchmark.<\/p>\n<p>Numri i yjeve n\u00eb Github: 28,267<\/p>\n<h3>13. Cookiecutter<\/h3>\n<p>\nCookiecutter \u00ebsht\u00eb nj\u00eb utilitary komand\u00eb q\u00eb mund t\u00eb p\u00ebrdoret p\u00ebr t\u00eb krijuar projekte nga shabllone (cookiecutters). Nj\u00eb nga shembujt mund t\u00eb jet\u00eb krijimi i nj\u00eb projekti pakoje nga nj\u00eb shabllon projekti pakoje. K\u00ebto jan\u00eb shabllone nd\u00ebr-platform\u00eb, dhe shabllonet e projekteve mund t\u00eb jen\u00eb n\u00eb \u00e7do gjuh\u00eb apo format p\u00ebrgatitjeje, si Python, JavaScript, HTML, Ruby, CoffeeScript, RST dhe Markdown. Ai gjithashtu lejon p\u00ebrdorimin e disa gjuh\u00ebve n\u00eb t\u00eb nj\u00ebjtin shabllon projekti.<\/p>\n<p>Numri i yjeve n\u00eb Github: 10 291<\/p>\n<h3>14. Pandas<\/h3>\n<p>\nPandas \u00ebsht\u00eb nj\u00eb bibliotek\u00eb p\u00ebr analiz\u00ebn dhe manipulimin e t\u00eb dh\u00ebnave p\u00ebr Python, e cila ofron struktura t\u00eb dh\u00ebnash t\u00eb etiketuar dhe funksione statistikore.<\/p>\n<p>Numri i yjeve n\u00eb Github: 21,404<\/p>\n<p>Projekti Python me burim t\u00eb hapur p\u00ebr t\u00eb provuar Pandas \u2014 <noindex><a rel=\"nofollow\" href=\"https:\/\/data-flair.training\/blogs\/python-machine-learning-project-detecting-parkinson-disease\/\">zbulimi i s\u00ebmundjes s\u00eb Parkinsonit<\/a><\/noindex><\/p>\n<h3>15. Pipenv<\/h3>\n<p>\nPipenv premton t\u00eb jet\u00eb nj\u00eb mjet i gatsh\u00ebm p\u00ebr prodhim, i orientuar p\u00ebr t\u00eb sjell\u00eb t\u00eb mirat e t\u00eb gjith\u00eb bot\u00ebve t\u00eb paketave n\u00eb bot\u00ebn e Python. Terminali i tij ka ngjyra t\u00eb bukura dhe bashkon Pipfile, pip dhe virtualenv n\u00eb nj\u00eb komand\u00eb. Ai automatikisht krijon dhe menaxhon nj\u00eb ambient virtual p\u00ebr projektet tuaja dhe ofron p\u00ebrdoruesve nj\u00eb m\u00ebnyr\u00eb t\u00eb thjesht\u00eb p\u00ebr t\u00eb vendosur nj\u00eb ambient pune.<\/p>\n<p>Numri i yjeve n\u00eb Github: 18,322<\/p>\n<h3>16. SimpleCoin<\/h3>\n<p>\nKjo \u00ebsht\u00eb nj\u00eb implementim i Blockchain p\u00ebr kriptovalutat, e krijuar n\u00eb Python, por \u00ebsht\u00eb e thjesht\u00eb, e pasigurt dhe e paplot\u00eb. SimpleCoin nuk \u00ebsht\u00eb p\u00ebr p\u00ebrdorim n\u00eb prodhim. Nuk \u00ebsht\u00eb p\u00ebr p\u00ebrdorim n\u00eb prodhim, SimpleCoin \u00ebsht\u00eb p\u00ebr q\u00ebllime edukative dhe vet\u00ebm p\u00ebr t\u00eb b\u00ebr\u00eb nj\u00eb zinxhir t\u00eb pun\u00ebs blockchain t\u00eb disponuesh\u00ebm dhe t\u00eb thjesht\u00eb. Ajo lejon ruajtjen e hash-\u00ebve t\u00eb nxjerr\u00eb dhe shk\u00ebmbimin e tyre p\u00ebr \u00e7do monedh\u00eb t\u00eb mb\u00ebshtetur.<br \/>\nNumri i yjeve n\u00eb Github: 1343<\/p>\n<h3>17. Pyray<\/h3>\n<p>\nKjo \u00ebsht\u00eb nj\u00eb bibliotek\u00eb 3D-renderimi, e shkruar n\u00eb Python t\u00eb past\u00ebr. Ajo vizualizon objekte dhe skena 2D, 3D m\u00eb shum\u00eb t\u00eb m\u00ebdha n\u00eb Python dhe animacion. Ajo na gjen n\u00eb fush\u00ebn e videove t\u00eb krijuara, videoloj\u00ebrave, simulimeve fizike dhe madje edhe imazheve t\u00eb bukura. K\u00ebrkesat p\u00ebr k\u00ebt\u00eb jan\u00eb: PIL, numpy dhe scipy.<\/p>\n<p>Numri i yjeve n\u00eb Github: 451<\/p>\n<h3>18. MicroPython<\/h3>\n<p>\nMicroPython \u00ebsht\u00eb Python p\u00ebr mikro-kontrollor\u00ebt. \u00cbsht\u00eb nj\u00eb zbatim efektiv i Python3, i cili vjen me shum\u00eb paketa nga biblioteka standarde Python dhe \u00ebsht\u00eb optimizuar p\u00ebr t\u00eb punuar n\u00eb mikro-kontrollor\u00eb dhe n\u00eb kushte t\u00eb kufizuara. Pyboard \u00ebsht\u00eb nj\u00eb pllak\u00eb elektronike e vog\u00ebl q\u00eb run MicroPython mbi metalin e zhveshur, k\u00ebshtu q\u00eb ajo mund t\u00eb kontrolloj\u00eb t\u00eb gjitha llojet e projekteve elektronike.<\/p>\n<p>Numri i yjeve n\u00eb <noindex><a rel=\"nofollow\" href=\"https:\/\/github.com\/micropython\/micropython\">Github<\/a><\/noindex>: 9,197<\/p>\n<h3>19. Kivy<\/h3>\n<p>\nKivy \u00ebsht\u00eb nj\u00eb bibliotek\u00eb Python p\u00ebr zhvillimin e aplikacioneve mobile dhe aplikacioneve t\u00eb tjera me prekje t\u00eb natyrshme (NUI). Ajo ka nj\u00eb bibliotek\u00eb grafike, disa mund\u00ebsi widget, nj\u00eb gjuh\u00eb nd\u00ebrmjet\u00ebsuese Kv p\u00ebr krijimin e widget-eve t\u00eb veta, mb\u00ebshtetje p\u00ebr miun, tastier\u00ebn, TUIO dhe ngjarjet e hyrjes shum\u00ebshkruese. Ky \u00ebsht\u00eb nj\u00eb bibliotek\u00eb me burim t\u00eb hapur p\u00ebr zhvillimin e shpejt\u00eb t\u00eb aplikacioneve me nd\u00ebrfaqe inovative p\u00ebr p\u00ebrdoruesit. Ai \u00ebsht\u00eb nd\u00ebrlidh\u00ebs, miq\u00ebsor me biznesin dhe ka GPU-accelerim.<\/p>\n<p>Numri i yjeve n\u00eb Github: 9 930<\/p>\n<h3>20. Dash<\/h3>\n<p>\nDash by Plotly \u00ebsht\u00eb nj\u00eb framework p\u00ebr aplikacione web. I nd\u00ebrtuar mbi Flask, Plotly.js, React dhe React.js, ai na lejon t\u00eb p\u00ebrdorim Python p\u00ebr t\u00eb nd\u00ebrtuar panelet e kontrollit. Ai siguron funksionimin e modeleve Python dhe R n\u00eb shkall\u00eb. Dash lejon krijimin, testimin, vendosjen dhe raportimin pa p\u00ebrdorimin e DevOps, JavaScript, CSS ose CronJobs. Dash \u00ebsht\u00eb efikas, i personalizuesh\u00ebm, i leht\u00eb dhe i leht\u00eb p\u00ebr t'u menaxhuar. Po ashtu ka burim t\u00eb hapur.<\/p>\n<p>Numri i yjeve n\u00eb Github: 9,883<\/p>\n<h3>21. Magenta<\/h3>\n<p>\nMagenta \u2014 \u00ebsht\u00eb nj\u00eb projekt hulumtues me kod t\u00eb hapur q\u00eb fokusohet n\u00eb m\u00ebsimin e makinerive si mjet n\u00eb procesin krijues. Kjo lejon krijimin e muzik\u00ebs dhe artit duke p\u00ebrdorur m\u00ebsimin e makinerive. Magenta \u2014 \u00ebsht\u00eb nj\u00eb bibliotek\u00eb Python e bazuar n\u00eb TensorFlow, me mjete p\u00ebr pun\u00ebn me t\u00eb dh\u00ebna burimore, p\u00ebrdorimin e saj p\u00ebr trajnim modeli dhe krijimin e p\u00ebrmbajtjes s\u00eb re.<\/p>\n<h3>22. Mask R-CNN<\/h3>\n<p>\nKjo \u00ebsht\u00eb nj\u00eb implementim i mask\u00ebs R-CNN n\u00eb Python 3, TensorFlow dhe Keras. Modeli merr \u00e7do instanc\u00eb objekti n\u00eb nj\u00eb imazh dhe krijon kufij dhe maska segmentimi p\u00ebr t\u00eb. P\u00ebrdor nj\u00eb rrjet Feature Pyramid Network (FPN) dhe nj\u00eb arkitektur\u00eb ResNet101. Kodi \u00ebsht\u00eb leht\u00ebsisht i zgjeruesh\u00ebm. Ky projekt gjithashtu ofron nj\u00eb t\u00eb dh\u00ebnat Matterport3D p\u00ebr hap\u00ebsirat 3D t\u00eb rikonstruktuara, t\u00eb kapura nga klient\u00ebt\u2026<br \/>\nNumri i yjeve n\u00eb Github: 14 055<\/p>\n<h3>23. Modelet TensorFlow<\/h3>\n<p>\nKy \u00ebsht\u00eb nj\u00eb repo me modele t\u00eb ndryshme, t\u00eb implementuara n\u00eb TensorFlow \u2014 modele t\u00eb zyrta dhe hulumtuese. Ka gjithashtu mostra dhe udh\u00ebzime. Modelet zyrtare p\u00ebrdorin API t\u00eb nivelit t\u00eb lart\u00eb t\u00eb TensorFlow. Modelet hulumtuese jan\u00eb modele t\u00eb implementuara n\u00eb TensorFlow nga hulumtuesit p\u00ebr ta mb\u00ebshtetur ose p\u00ebr t\u00eb ndihmuar me pyetje dhe k\u00ebrkesat.<\/p>\n<p>Numri i yjeve n\u00eb Github: 57 745<\/p>\n<h3>24. Snallygaster<\/h3>\n<p>\nSnallygaster \u2014 \u00ebsht\u00eb nj\u00eb m\u00ebnyr\u00eb organizimi e problemeve n\u00ebp\u00ebrmjet bordit t\u00eb projekteve. Me t\u00eb mund t\u00eb konfiguroni nj\u00eb panel menaxhimi projektesh n\u00eb GitHub, t\u00eb optimizoni dhe automatizoni procesin e pun\u00ebs. Lejon q\u00eb t\u00eb renditni detyrat, t\u00eb planifikoni projekte, t\u00eb automatizoni procesin e pun\u00ebs, t\u00eb ndiqni p\u00ebrparimin, t\u00eb ndani statusin dhe, n\u00eb fund, ta p\u00ebrfundoni at\u00eb. Snallygaster mund t\u00eb skanoj p\u00ebr skedar\u00eb sekret\u00eb n\u00eb serverat HTTP \u2014 k\u00ebrkon skedar\u00eb q\u00eb jan\u00eb t\u00eb aksesuesh\u00ebm n\u00eb server\u00ebt web, t\u00eb cil\u00ebt nuk duhet t\u00eb jen\u00eb t\u00eb qassh\u00ebm publikisht dhe mund t\u00eb p\u00ebrb\u00ebjn\u00eb nj\u00eb k\u00ebrc\u00ebnim p\u00ebr sigurin\u00eb.<\/p>\n<p>Numri i yjeve n\u00eb Github: 1 477<\/p>\n<h3>25. Statsmodels<\/h3>\n<p>\nKjo <noindex><a rel=\"nofollow\" href=\"https:\/\/data-flair.training\/blogs\/python-packages\/\">pako Python<\/a><\/noindex>, e cila plot\u00ebson scipy p\u00ebr llogaritjet statistikore, duke p\u00ebrfshir\u00eb statistikat p\u00ebrshkruese, si dhe vler\u00ebsimet dhe p\u00ebrfundimet p\u00ebr modelet statistikore. Ai ka klasa dhe funksione p\u00ebr k\u00ebt\u00eb. Gjithashtu na lejon t\u00eb kryejm\u00eb teste statistikore dhe studime statistikore.<br \/>\nNumri i yjeve n\u00eb Github: 4 246<\/p>\n<h3>26. WhatWaf<\/h3>\n<p>\nKy \u00ebsht\u00eb nj\u00eb mjet i avancuar p\u00ebr zbulimin e firewall-it q\u00eb mund ta p\u00ebrdorim p\u00ebr t\u00eb kuptuar n\u00ebse ekziston nj\u00eb firewall aplikacioni web. Zbulon firewall-in n\u00eb aplikacionin web dhe p\u00ebrpiqet t\u00eb zbuloj\u00eb nj\u00eb ose m\u00eb shum\u00eb m\u00ebnyra p\u00ebr t\u00eb anashkaluar at\u00eb n\u00eb objektin e caktuar.<\/p>\n<p>Numri i yjeve n\u00eb Github: 1300<\/p>\n<h3>27. Chainer<\/h3>\n<p>\nChainer \u2014 <noindex><a rel=\"nofollow\" href=\"https:\/\/data-flair.training\/blogs\/deep-learning-with-python-libraries\/\">\u00ebsht\u00eb nj\u00eb ambient p\u00ebr m\u00ebsimin e thell\u00eb<\/a><\/noindex>, i orientuar drejt fleksibilitetit. Bazohet n\u00eb Python dhe ofron API t\u00eb diferencuar t\u00eb bazuar n\u00eb qasjen define-by-run. Chainer gjithashtu ofron API me objekt t\u00eb nivelit t\u00eb lart\u00eb p\u00ebr nd\u00ebrtimin dhe trajnimet e rrjeteve nervore. \u00cbsht\u00eb nj\u00eb struktur\u00eb e fuqishme, fleksib\u00ebl dhe intuitiv p\u00ebr rrjetet nervore.<br \/>\nNumri i yjeve n\u00eb Github: 5 054<\/p>\n<h3>28. Rebound<\/h3>\n<p>\nRebound \u2014 \u00ebsht\u00eb nj\u00eb mjet komande. Kur merrni nj\u00eb mesazh gabimi kompajleri, ai menj\u00ebher\u00eb merr rezultatet nga mbushja e sip\u00ebrme t\u00eb stack-ut. P\u00ebr ta p\u00ebrdorur k\u00ebt\u00eb, mund t\u00eb p\u00ebrdorni komand\u00ebn rebound p\u00ebr t\u00eb ekzekutuar skedarin tuaj. Ky \u00ebsht\u00eb nj\u00eb nga 50 projektet m\u00eb t\u00eb njohura t\u00eb kodit t\u00eb hapur Python t\u00eb vitit 2018. P\u00ebr m\u00eb tep\u00ebr, k\u00ebrkon Python 3.0 ose m\u00eb lart. Llojet e skedareve t\u00eb mb\u00ebshtetura: Python, Node.js, Ruby, Golang dhe Java.<\/p>\n<p>Numri i yjeve n\u00eb Github: 2 913<\/p>\n<h3>29. Detectron<\/h3>\n<p>\nDetectron realizon zbulimin modern t\u00eb objekteve (po ashtu implementon mask\u00ebn R-CNN). Ky \u00ebsht\u00eb nj\u00eb softuer i Facebook AI Research (FAIR), i shkruar n\u00eb Python dhe q\u00eb punon n\u00eb platform\u00ebn Caffe2 Deep Learning. Q\u00ebllimi i Detectron \u00ebsht\u00eb t\u00eb ofroj\u00eb nj\u00eb kod t\u00eb cil\u00ebsis\u00eb s\u00eb lart\u00eb dhe t\u00eb performanc\u00ebs s\u00eb lart\u00eb p\u00ebr hulumtimin e zbulimit t\u00eb objekteve. Ai \u00ebsht\u00eb fleksib\u00ebl dhe implementon algoritmet e m\u00ebposhtme \u2014 maska R-CNN, RetinaNet, R-CNN m\u00eb t\u00eb shpejt\u00eb, RPN, R-CNN t\u00eb shpejt\u00eb, R-FCN.<\/p>\n<p>Numri i yjeve n\u00eb Github: 21 873<\/p>\n<h3>30. Python-fire<\/h3>\n<p>\nKy \u00ebsht\u00eb nj\u00eb bibliotek\u00eb p\u00ebr gjenerimin automatik t\u00eb CLI (interfeshave t\u00eb komand\u00ebs) nga (\u00e7do) objekt Python. Ai gjithashtu ju lejon t\u00eb zhvilloni dhe debugger kodin tuaj, si dhe t\u00eb eksploroni kodin ekzistues ose t\u00eb ktheni kodin e dikujt tjet\u00ebr n\u00eb CLI. Python Fire e b\u00ebn kalimin midis Bash dhe Python m\u00eb t\u00eb leht\u00eb, si dhe e leht\u00ebson p\u00ebrdorimin e REPL.<br \/>\nNumri i yjeve n\u00eb Github: 15 299<\/p>\n<h3>31. Pylearn2<\/h3>\n<p>\nPylearn2 \u2014 \u00ebsht\u00eb nj\u00eb bibliotek\u00eb p\u00ebr m\u00ebsimin e makinerive, t\u00eb nd\u00ebrtuar kryesisht mbi Theano. Q\u00ebllimi i saj \u00ebsht\u00eb t\u00eb leht\u00ebsoj\u00eb hulumtimin e ML. Lejon t\u00eb shkruani algoritme dhe modele t\u00eb reja.<br \/>\nNumri i yjeve n\u00eb Github: 2 681<\/p>\n<h3>32. Matplotlib<\/h3>\n<p>\n<noindex><a rel=\"nofollow\" href=\"https:\/\/data-flair.training\/blogs\/python-matplotlib-tutorial\/\">Matplotlib<\/a><\/noindex> \u2014 \u00ebsht\u00eb nj\u00eb bibliotek\u00eb p\u00ebr skicimin 2D p\u00ebr Python \u2014 gjeneron publikime me cil\u00ebsi n\u00eb formate t\u00eb ndryshme.<\/p>\n<p>Numri i yjeve n\u00eb Github: 10 072<\/p>\n<h3>33. Theano<\/h3>\n<p>\nTheano \u2014 \u00ebsht\u00eb nj\u00eb bibliotek\u00eb p\u00ebr manipulimin e shprehjeve matematikore dhe matricore. Ajo \u00ebsht\u00eb gjithashtu nj\u00eb kompajler optimizues. Theano p\u00ebrdor <noindex><a rel=\"nofollow\" href=\"https:\/\/data-flair.training\/blogs\/python-numpy-tutorial\/\">NumPy<\/a><\/noindex>-nj\u00eb sintaks\u00eb t\u00eb ngjashme p\u00ebr t\u00eb shprehur llogaritjet dhe i kompilon ato p\u00ebr t\u00eb punuar n\u00eb arkitektur\u00eb CPU ose GPU. Ajo \u00ebsht\u00eb nj\u00eb bibliotek\u00eb e m\u00ebsimit t\u00eb makinerive Python me burim t\u00eb hapur, e shkruar n\u00eb Python dhe CUDA dhe funksionon n\u00eb Linux, macOS dhe Windows.<\/p>\n<p>Numri i yjeve n\u00eb <noindex><a rel=\"nofollow\" href=\"https:\/\/github.com\/Theano\/Theano\">Github<\/a><\/noindex>: 8,922<\/p>\n<h3>34. Multidiff<\/h3>\n<p>\nMultidiff \u00ebsht\u00eb zhvilluar p\u00ebr t\u00eb leht\u00ebsuar kuptimin e t\u00eb dh\u00ebnave t\u00eb orientuara nga makinat. Ai ndihmon n\u00eb shikimin e ndryshimeve midis nj\u00eb numri t\u00eb madh objektesh, duke kryer diferencat midis objekteve p\u00ebrkat\u00ebse dhe m\u00eb pas i paraqet ato. Kjo vizualizim na lejon t\u00eb k\u00ebrkojm\u00eb modele n\u00eb protokollet tona ose formate t\u00eb pazakonta skedar\u00ebsh. Ai gjithashtu p\u00ebrdoret kryesisht p\u00ebr inxhinierin\u00eb e prapme dhe analiz\u00ebn e t\u00eb dh\u00ebnave binar\u00eb.<\/p>\n<p>Numri i yjeve n\u00eb Github: 262<\/p>\n<h3>35. Som-tsp<\/h3>\n<p>\nKy projekt i kushtohet p\u00ebrdorimit t\u00eb hartave q\u00eb vet\u00eb-organizohen p\u00ebr zgjidhjen e problemit t\u00eb tregtarit. Duke p\u00ebrdorur SOM, ne gjejm\u00eb zgjidhje suboptimal p\u00ebr problemin TSP dhe e p\u00ebrdorim formatin .tsp p\u00ebr k\u00ebt\u00eb. TSP \u00ebsht\u00eb nj\u00eb problem NP-i plot\u00eb dhe me rritjen e numrit t\u00eb qyteteve b\u00ebhet gjithnj\u00eb e m\u00eb e v\u00ebshtir\u00eb t\u00eb zgjidhet.<\/p>\n<p>Numri i yjeve n\u00eb Github: 950<\/p>\n<h3>36. Photon<\/h3>\n<p>\nPhoton \u00ebsht\u00eb nj\u00eb skanues web jasht\u00ebzakonisht i shpejt\u00eb, i dizajnuar p\u00ebr OSINT. Ai mund t\u00eb marr\u00eb URL-t\u00eb, URL-t\u00eb me parametra, t\u00eb dh\u00ebna Intel, skedar\u00eb, \u00e7el\u00ebsa sekrete, skedar\u00eb JavaScript, p\u00ebrputhje me shprehje normale dhe n\u00ebn-domena. Informacioni i nxjerr\u00eb mund t\u00eb ruhet dhe exportohet n\u00eb formatin json. Photon \u00ebsht\u00eb fleksib\u00ebl dhe brilant. Ju gjithashtu mund t\u00eb shtoni disa shtesa n\u00eb t\u00eb.<\/p>\n<p>Numri i yjeve n\u00eb Github: 5714<\/p>\n<h3>37. Social Mapper<\/h3>\n<p>\nSocial Mapper \u00ebsht\u00eb nj\u00eb mjet p\u00ebr hartimin e rrjeteve sociale, i cili korrelaton profile duke p\u00ebrdorur njohjen e fytyr\u00ebs. Ai e b\u00ebn k\u00ebt\u00eb n\u00eb faqet e ndryshme t\u00eb internetit n\u00eb nj\u00eb shkall\u00eb t\u00eb madhe. Social Mapper automatizon k\u00ebrkimin e emrave dhe fotografive n\u00eb rrjetet sociale dhe m\u00eb pas p\u00ebrpiqet t\u00eb identifikoj\u00eb me precizitet dhe t\u00eb grupoj\u00eb pranin\u00eb e dikujt. M\u00eb pas, ai krijon nj\u00eb raport p\u00ebr verifikim nga ana e njeriut. Kjo \u00ebsht\u00eb e dobishme n\u00eb industrin\u00eb e siguris\u00eb (p.sh., p\u00ebr peshkimin). Ai mb\u00ebshtet platformat LinkedIn, Facebook, Twitter, Google Plus, Instagram, \u0412\u041a\u043e\u043d\u0442\u0430\u043a\u0442\u0435, Weibo dhe Douban.<\/p>\n<p>Numri i yjeve n\u00eb Github: 2,396<\/p>\n<h3>38. Camelot<\/h3>\n<p>\nCamelot \u00ebsht\u00eb nj\u00eb bibliotek\u00eb Python q\u00eb ndihmon n\u00eb nxjerrjen e tabelave nga skedar\u00eb PDF. Ajo punon me PDF-t\u00eb tekstual, por jo me dokumente t\u00eb skanuara. \u00c7do tabel\u00eb k\u00ebtu \u00ebsht\u00eb nj\u00eb pandas DataFrame. P\u00ebrve\u00e7 k\u00ebsaj, ju mund t\u00eb eksportoni tabelat n\u00eb .json, .xls, .html ose .sqlite.<\/p>\n<p>Numri i yjeve n\u00eb Github: 2415<\/p>\n<h3>39. Lector<\/h3>\n<p>\nKy \u00ebsht\u00eb nj\u00eb lexues Qt p\u00ebr t\u00eb lexuar libra elektronik\u00eb. Ai mb\u00ebshtet formatet e skedar\u00ebve .pdf, .epub, .djvu, .fb2, .mobi, .azw \/.azw3 \/.azw4, .cbr \/.cbz dhe .md. N\u00eb Lector ka nj\u00eb dritare kryesore, shikim tabele, shikim librash, shikim pa shp\u00ebrq\u00ebndrime, mb\u00ebshtetje p\u00ebr annotime, shikim komikesh dhe nj\u00eb dritare caktimi. Ai gjithashtu mb\u00ebshtet sh\u00ebnimet, shikimin e profileve, redaktorin e metadata dhe fjalorin e integruar.<\/p>\n<p>Numri i yjeve n\u00eb Github: 835<\/p>\n<h3>40. m00dbot<\/h3>\n<p>\nKy \u00ebsht\u00eb nj\u00eb bot Telegram p\u00ebr vet\u00eb-testimin e depresionit dhe ankthit.<\/p>\n<p>Numri i yjeve n\u00eb Github: 145<\/p>\n<h3>41. Manim<\/h3>\n<p>\nKy \u00ebsht\u00eb nj\u00eb motor animacioni p\u00ebr shpjegimin e videove matematikore, i cili mund t\u00eb p\u00ebrdoret p\u00ebr t\u00eb krijuar animacione t\u00eb sakta n\u00eb m\u00ebnyr\u00eb programore. Ai p\u00ebrdor Python p\u00ebr k\u00ebt\u00eb.<\/p>\n<p>Numri i yjeve n\u00eb Github: 13,491<\/p>\n<h3>42. Douyin-Bot<\/h3>\n<p>\nNj\u00eb bot, e shkruar n\u00eb Python p\u00ebr nj\u00eb aplikacion t\u00eb ngjash\u00ebm me Tinder. Zhvilluesit nga Kina.<\/p>\n<p>Numri i yjeve n\u00eb Github: 5,959<\/p>\n<h3>43. XSStrike<\/h3>\n<p>\nKy \u00ebsht\u00eb nj\u00eb paket\u00eb e zbulimit t\u00eb skripteve nd\u00ebr-situs me kat\u00ebr parser\u00eb t\u00eb shkruar nga duar. Ai gjithashtu vjen me nj\u00eb gjenerator inteligjent t\u00eb t\u00eb dh\u00ebnave t\u00eb dobishme, nj\u00eb mekaniz\u00ebm t\u00eb fuqish\u00ebm fuzzing dhe nj\u00eb module k\u00ebrkimi jasht\u00ebzakonisht t\u00eb shpejt\u00eb. N\u00eb vend q\u00eb t\u00eb futni t\u00eb dh\u00ebna t\u00eb dobishme dhe t'i kontrolloni ato si t\u00eb gjitha mjetet e tjera, XSStrike e njoh p\u00ebrgjigjen p\u00ebrmes disa parser\u00ebve dhe m\u00eb pas p\u00ebrpunon t\u00eb dh\u00ebnat e dobishme, t\u00eb cilat do t\u00eb funksionojn\u00eb me siguri p\u00ebrmes nj\u00eb analize konteksti t\u00eb integruar n\u00eb mekanizmin e fuzzingut.<\/p>\n<p>Numri i yjeve n\u00eb Github: 7050<\/p>\n<h3>44. PythonRobotics<\/h3>\n<p>\nKy projekt p\u00ebrb\u00ebn nj\u00eb koleksion kodi n\u00eb algoritmet e robotik\u00ebs Python, si dhe algoritme p\u00ebr navigimin autonom.<\/p>\n<p>Numri i yjeve n\u00eb Github: 6,746<\/p>\n<h3>45. Google Images Download<\/h3>\n<p>\nGoogle Images Download \u00ebsht\u00eb nj\u00eb program Python p\u00ebr linj\u00ebn e komand\u00ebs, q\u00eb k\u00ebrkon fjal\u00eb ky\u00e7e n\u00eb imazhet e Google dhe merr imazhe p\u00ebr ju. Ky \u00ebsht\u00eb nj\u00eb program i vog\u00ebl pa var\u00ebsi, n\u00ebse keni nevoj\u00eb vet\u00ebm p\u00ebr t\u00eb shkarkuar deri n\u00eb 100 imazhe p\u00ebr \u00e7do fjal\u00eb ky\u00e7e.<\/p>\n<p>Numri i yjeve n\u00eb Github: 5749<\/p>\n<h3>46. \u200b\u200bTrape<\/h3>\n<p>\nLejon ndihmon n\u00eb ndjekjen dhe realizimin e sulmeve inteligjente t\u00eb ingjenieris\u00eb sociale n\u00eb koh\u00eb reale. Kjo ndihmon n\u00eb zb\u00ebrthimin e m\u00ebnyrave se si kompanit\u00eb e m\u00ebdha t\u00eb internetit mund t\u00eb fitojn\u00eb informacion t\u00eb ndjesh\u00ebm dhe t\u00eb kontrollojn\u00eb p\u00ebrdoruesit pa dijenin\u00eb e tyre. Trape gjithashtu mund t\u00eb ndihmoj\u00eb p\u00ebr t\u00eb ndjekur kriminel\u00ebt kibernetik\u00eb.<\/p>\n<p>Numri i yjeve n\u00eb Github: 4256<\/p>\n<h3>47. Xonsh<\/h3>\n<p>\nXonsh \u00ebsht\u00eb nj\u00eb gjuh\u00eb komande dhe nj\u00eb shell nd\u00ebr-platform\u00eb e bazuar n\u00eb Python. Ai \u00ebsht\u00eb nj\u00eb supersets i Python 3.5+ me primitivat shtes\u00eb t\u00eb shell, t\u00eb ngjashme me ato n\u00eb Bash dhe IPython. Xonsh funksionon n\u00eb Linux, Max OS X, Windows dhe sisteme t\u00eb tjera kryesore.<\/p>\n<p>Numri i yjeve n\u00eb Github: 3426<\/p>\n<h3>48. GIF p\u00ebr CLI<\/h3>\n<p>\nKjo k\u00ebrkon nj\u00eb GIF ose nj\u00eb video t\u00eb shkurt\u00ebr ose k\u00ebrkes\u00eb, dhe me ndihm\u00ebn e API-s\u00eb Tenor GIF, ajo kthehet n\u00eb grafik\u00eb t\u00eb animuar ASCII. Ai p\u00ebrdor sekuenca escape ANSI p\u00ebr animacion dhe ngjyr\u00eb.<\/p>\n<p>Numri i yjeve n\u00eb Github: 2,547<\/p>\n<h3>49. Cartoonify<\/h3>\n<p>\nDraw This \u00ebsht\u00eb nj\u00eb kamer\u00eb polaroid q\u00eb mund t\u00eb vizatoj\u00eb karikaturat. Ajo p\u00ebrdor nj\u00eb rrjet nervor p\u00ebr t\u00eb njohur objektet, nj\u00eb grup t\u00eb dh\u00ebnash nga Google Quickdraw, nj\u00eb termoprinter dhe Raspberry Pi. Quick, Draw! \u00ebsht\u00eb nj\u00eb loj\u00eb nga Google ku lojtar\u00ebt duhet t\u00eb vizatojn\u00eb imazhin e nj\u00eb objekti\/idee, dhe pastaj ajo p\u00ebrpiqet t\u00eb gjykoj\u00eb se \u00e7far\u00eb p\u00ebrfaq\u00ebson brenda 20 sekondave.<\/p>\n<p>Numri i yjeve n\u00eb Github: 1760<\/p>\n<h3>50. Zulip<\/h3>\n<p>\nZulip \u00ebsht\u00eb nj\u00eb aplikacion p\u00ebr biseda grupore q\u00eb funksionon n\u00eb koh\u00eb reale dhe \u00ebsht\u00eb produktiv fal\u00eb bisedave me shum\u00eb rrjedha. Shum\u00eb nga kompanit\u00eb n\u00eb list\u00ebn e Fortune 500 dhe projektet me kod t\u00eb hapur e p\u00ebrdorin p\u00ebr biseda n\u00eb koh\u00eb reale, q\u00eb mund t\u00eb kryejn\u00eb mij\u00ebra mesazhe n\u00eb dit\u00eb.<\/p>\n<p>Numri i yjeve n\u00eb Github: 10,432<\/p>\n<h3>51. YouTube-dl<\/h3>\n<p>\nKy \u00ebsht\u00eb nj\u00eb program i komandave q\u00eb mund t\u00eb shkarkoj\u00eb video nga YouTube dhe disa faqe t\u00eb tjera. Ai nuk \u00ebsht\u00eb i lidhur me nj\u00eb platform\u00eb specifike.<\/p>\n<p>Numri i yjeve n\u00eb Github: 55 868<\/p>\n<h3>52. Ansible<\/h3>\n<p>\nKjo \u00ebsht\u00eb nj\u00eb sistem i thjesht\u00eb automatizimi IT q\u00eb mund t\u00eb menaxhoj\u00eb funksione t\u00eb tilla si: menaxhimi i konfigurimeve, shp\u00ebrndarja e aplikacioneve, infrastrukturimi i cloud, ekzekutimi i detyrave t\u00eb ve\u00e7anta, automatizimi i rrjetit dhe orkestrimi me shum\u00eb nodulesh.<\/p>\n<p>Numri i yjeve n\u00eb Github: 39,443<\/p>\n<h3>53. HTTPie<\/h3>\n<p>\nHTTPie \u00ebsht\u00eb nj\u00eb klient HTTP p\u00ebr linj\u00ebn e komand\u00ebs. Ai e thjeshton nd\u00ebrveprimin e CLI me sh\u00ebrbimet web. Me komand\u00ebn http, ai na lejon t\u00eb d\u00ebrgojm\u00eb k\u00ebrkesa HTTP t\u00eb rastit me sintaks\u00eb t\u00eb thjesht\u00eb dhe t\u00eb marrim dalje me ngjyr\u00eb. Ne mund ta p\u00ebrdorim at\u00eb p\u00ebr testimin, debugging dhe nd\u00ebrveprimin me server\u00ebt HTTP.<\/p>\n<p>Numri i yjeve n\u00eb Github: 43 199<\/p>\n<h3>54. Tornado Web Server<\/h3>\n<p>\nKy \u00ebsht\u00eb nj\u00eb framework web, nj\u00eb bibliotek\u00eb rrjet\u00ebsore asinkrone p\u00ebr Python. Ai p\u00ebrdor IO pa bllokim p\u00ebr t\u00eb shkall\u00ebzuar deri n\u00eb m\u00eb shum\u00eb se nj\u00eb mij\u00eb lidhje t\u00eb hapura. Kjo e b\u00ebn at\u00eb nj\u00eb zgjedhje t\u00eb mir\u00eb p\u00ebr k\u00ebrkesa t\u00eb gjata dhe WebSockets.<\/p>\n<p>Numri i yjeve n\u00eb Github: 18 306<\/p>\n<h3>55. Requests<\/h3>\n<p>\nRequests \u00ebsht\u00eb nj\u00eb bibliotek\u00eb q\u00eb lejon d\u00ebrgimin e leht\u00eb t\u00eb k\u00ebrkesave HTTP\/1.1. Ju nuk keni nevoj\u00eb t\u00eb shtoni manualisht parametra n\u00eb URL-t\u00eb ose t\u00eb kodoni t\u00eb dh\u00ebnat PUT dhe POST.<br \/>\nNumri i yjeve n\u00eb Github: 40 294<\/p>\n<h3>56. Scrapy<\/h3>\n<p>\nScrapy \u00ebsht\u00eb nj\u00eb framework i shpejt\u00eb dhe me nivel t\u00eb lart\u00eb p\u00ebr shfletimin e faqeve web \u2014 mund ta p\u00ebrdorni p\u00ebr t\u00eb shfletuar web faqe p\u00ebr t\u00eb nxjerr\u00eb t\u00eb dh\u00ebna t\u00eb strukturuara. Ju gjithashtu mund ta p\u00ebrdorni p\u00ebr analiz\u00ebn e t\u00eb dh\u00ebnave, monitorimin dhe testimin automatizuar.<\/p>\n<p>Numri i yjeve n\u00eb Github: 34,493<br \/>\n<br \/>Burimi: <a content=\"nofollow\" rel=\"nofollow\" href=\"https:\/\/habr.com\/ru\/company\/edison\/blog\/477442\/\">habr.com<\/a><\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"<p>1. 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[&hellip;]<\/p>\n","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[702],"tags":[],"class_list":["post-53299","post","type-post","status-publish","format-standard","hentry","category-novosti-interneta"],"aioseo_notices":[],"aioseo_head":"\n\t\t<!-- All in One SEO 5.0.0.1 - aioseo.com -->\n\t<meta name=\"description\" content=\"1.\" \/>\n\t<meta name=\"robots\" content=\"max-image-preview:large\" \/>\n\t<meta name=\"author\" content=\"Yuri Gagarin\"\/>\n\t<link rel=\"canonical\" href=\"https:\/\/prohoster.info\/sq\/blog\/novosti-interneta\/56-proektov-na-python-s-otkrytym-ishodnym-kodom\" \/>\n\t<meta name=\"generator\" content=\"All in One SEO (AIOSEO) 5.0.0.1\" \/>\n\t\t<meta property=\"og:locale\" content=\"sq_AL\" \/>\n\t\t<meta property=\"og:site_name\" content=\"ProHoster | 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