Vesti – Python programiranje

Tehnologija se razvija neverovatnom brzinom, a sa njom i zahtevi za veštinama koje programeri treba da poseduju kako bi ostali konkurentni na tržištu rada. U 2025. godini, programski jezici nisu samo alatke za pisanje koda, već ključ za otključavanje inovacija, automatizacije i razvoja aplikacija koje oblikuju budućnost. Bilo da ste iskusni programer, početnik koji tek ulazi u svet kodiranja, ili poslovni lider koji želi da razume trendove, razumevanje popularnih jezika može vam pomoći da donosite bolje odluke. Ovaj članak istražuje 20 najpopularnijih programskih jezika u 2025. godini, njihove ključne karakteristike, oblasti primene i kako vam mogu pomoći da razvijate svoje projekte i karijeru. Bez obzira na to da li se bavite razvojem mobilnih aplikacija, naukom o podacima, veštačkom inteligencijom ili web razvojem, poznavanje pravih jezika predstavlja osnov za uspeh u savremenom digitalnom svetu. 1. Python Popularnost: Jedan od najčešće korišćenih jezika zbog jednostavne sintakse i široke primene. Primena: Mašinsko učenje, veštačka inteligencija, web razvoj, nauka o podacima, automatizacija. Najvažnije karakteristike: Dinamičko tipiziranje. Veliki broj biblioteka (npr. NumPy, Pandas, TensorFlow). Jednostavan za početnike. 2. JavaScript (JS) Popularnost: Nezaobilazan za web razvoj. Primena: Frontend i backend razvoj (Node. js), izrada dinamičkih i interaktivnih web stranica. Najvažnije karakteristike: Brzina izvršenja u preglednicima. Podrška za asinhrone operacije. Velika zajednica i dostupni okviri (npr. React, Angular). 3. Java Popularnost: Koristi se decenijama u različitim industrijama. Primena: Razvoj aplikacija za preduzeća, mobilne aplikacije (Android), serverske aplikacije. Najvažnije karakteristike: Pisanje jednom, izvršavanje svuda (WORA – Write Once, Run Anywhere). Robusna bezbednost. Veliki ekosistem (npr. Spring, Hibernate). 4. Ruby Popularnost: Poznat po svom jednostavnom učenju i Ruby on Rails framework-u. Primena: Web razvoj, prototipovi aplikacija. Najvažnije karakteristike: Fokus na programersku produktivnost. Čitljiv i prirodan kod. Dinamičko tipiziranje. 5. C Popularnost: Osnova za mnoge moderne jezike. Primena: Sistemski softver, upravljanje hardverom, ugrađeni sistemi. Najvažnije karakteristike: Visoka efikasnost. Direktan pristup memoriji. Koristi se za razvoj operativnih sistema. 6. C++ Popularnost: Široko korišćen za visokoperformantne aplikacije. Primena: Igračke mašine, softver u realnom vremenu, finansijska industrija. Najvažnije karakteristike: Podrška za objekte. Kompatibilnost sa C kodom. Izuzetna brzina izvršenja. 7. C# Popularnost: Ključan za Microsoft okruženje. Primena: Razvoj Windows aplikacija, igre (Unity), poslovne aplikacije. Najvažnije karakteristike: Jednostavniji u poređenju sa C++. Integracija sa . NET framework-om. Podrška za moderne funkcije kao što su Lambda izrazi. 8. PHP Popularnost: Omiljen u razvoju web stranica. Primena: Backend razvoj, sistemi za upravljanje sadržajem (npr. WordPress). Najvažnije karakteristike: Jednostavna integracija sa HTML-om. Veliki broj biblioteka i okvira (npr. Laravel). Izuzetno dobar za male i srednje projekte. 9. Swift Popularnost: Razvijen od strane Apple-a za njihov ekosistem. Primena: Razvoj iOS i macOS aplikacija. Najvažnije karakteristike: Sigurnost i brzina. Intuitivna sintaksa. Moderna alternativa Objective-C jeziku. 10. Go (Golang) Popularnost: Brzo postaje popularan za serverski razvoj. Primena: Cloud aplikacije, serverski softver, distribuirani sistemi. Najvažnije karakteristike: Konkurentnost i efikasnost. Minimalna sintaksa. Pogodan za velike sisteme. 11. Kotlin Popularnost: Glavni jezik za Android razvoj (naslednik Jave u ovoj oblasti). Primena: Android aplikacije, server-side razvoj. Najvažnije karakteristike: Kompatibilan sa Javom. Fokus na jednostavnost i bezbednost. Smanjuje broj linija koda u poređenju s Javom. 12. Rust Popularnost: Brzo raste zahvaljujući svojoj sigurnosti i performansama. Primena: Sistemski softver, visokoperformantni aplikativni razvoj. Najvažnije karakteristike: Upravljanje memorijom bez grešaka (memory safety). Velika efikasnost. Idealno za kritične sisteme. 13. TypeScript Popularnost: Nadogradnja JavaScript-a za veće projekte. Primena: Frontend i backend razvoj, aplikacije koje zahtevaju tipizaciju. Najvažnije karakteristike: Statička tipizacija. Lak prelazak za JavaScript developere. Podrška za velike projekte i timove. 14. Scala Popularnost: Često korišćen u velikim sistemima i analitici podataka. Primena: Big Data, distribuirane aplikacije, funkcionalno programiranje. Najvažnije karakteristike: Kombinuje objekte i funkcionalne paradigme. Snažna kompatibilnost s JVM (Java Virtual Machine). Pogodan za rad s Apache Spark-om. 15. R Popularnost: Najbolji izbor za statističare i naučnike podataka. Primena: Analitika podataka, vizualizacija, statističko modeliranje. Najvažnije karakteristike: Velika biblioteka statističkih funkcija. Moćne grafičke mogućnosti. Fokusiran na akademsku i naučnu zajednicu. 16. Perl Popularnost: Poznat kao "švajcarski nož" programskih jezika. Primena: Tekstualna obrada, administracija sistema, skriptni jezik. Najvažnije karakteristike: Ekstremna fleksibilnost. Bogata biblioteka modula. Koristi se za automatizaciju i mrežno programiranje. 17. Dart Popularnost: Razvijen od Google-a, poznat po Flutter framework-u. Primena: Razvoj mobilnih i web aplikacija. Najvažnije karakteristike: Brz kompajler. Idealno za aplikacije s jedinstvenim korisničkim interfejsom. Efikasan za multiplatformske aplikacije. 18. MATLAB Popularnost: Standard za inženjere i naučnike. Primena: Numerička analiza, obrada signala, vizualizacija podataka. Najvažnije karakteristike: Integrisane funkcije za matematiku i statistiku. Prikladan za simulacije. Visoka cena, ali snažan alat za istraživanje. 19. Shell (Bash) Popularnost: Osnovni alat za administraciju sistema i automatizaciju. Primena: Skriptovanje za Linux/Unix sisteme, upravljanje serverima. Najvažnije karakteristike: Pristup komandnoj liniji. Efikasno za automatizaciju zadataka. Jednostavan, ali moćan za administrativne poslove. 20. SQL Popularnost: Ključni jezik za rad s bazama podataka. Primena: Upravljanje relacijskim bazama podataka. Najvažnije karakteristike: Standard za upite i manipulaciju podacima. Podržan u svim glavnim bazama podataka (MySQL, PostgreSQL, Oracle). Neophodan za analitičare podataka i programere backend-a. Najbolje prakse i saveti: Fokusirajte se na jezike koji odgovaraju vašim ciljevima (mobilni razvoj, analitika podataka, backend). Kombinujte znanje više jezika za širinu veština. Razvijajte projekte u zajednici kako biste unapredili praktične veštine. Redovno pratite ažuriranja jezika i novitete u njihovim okruženjima.

Skidanje podataka sa interneta, ili web scraping, predstavlja naprednu tehniku automatizovanog izvlačenja informacija sa web stranica. Kroz treće, ažurirano izdanje knjige posvećene ovoj temi, čitaoci se uvode u sveobuhvatni svet skidanja podataka, obuhvatajući niz tehnika i alata za efikasno prikupljanje podataka sa različitih tipova web resursa. Prvi deo knjige detaljno razmatra osnove web scrapinga, uključujući: Korišćenje Python-a za postavljanje upita web serverima: Python, kao moćan i fleksibilan programski jezik, igra ključnu ulogu u procesu skidanja podataka, omogućavajući automatizovanu interakciju sa web serverima i zahtevanje informacija. Osnovna obrada odgovora servera: Nakon što serveri odgovore na upite, potrebno je adekvatno obraditi dobijene podatke, što može uključivati analizu HTML koda i izvlačenje relevantnih informacija. Automatizovana interakcija sa sajtovima: Web scraping često zahteva simuliranje ljudskih akcija poput kliktanja na linkove ili popunjavanja formi, što se postiže kroz specijalizovane skripte i botove. Napredna analiza HTML stranica: Složene web stranice koje koriste dinamički sadržaj i JavaScript zahtevaju napredne tehnike scrapinga da bi se efikasno izvukli traženi podaci. Razvoj crawler-a sa Scrapy okvirom: Scrapy predstavlja popularan open-source okvir za ekstrakciju podataka, koji nudi bogat set funkcionalnosti za kreiranje efikasnih crawler-a. Metode čuvanja skupljenih podataka: Efikasno upravljanje i čuvanje izvučenih podataka ključno je za uspeh projekata skidanja podataka, uključujući upotrebu baza podataka i datotečnih sistema. Obrada i normalizacija nepravilno formatiranih podataka: Često je potrebno očistiti i standardizovati podatke pre njihove dalje analize ili čuvanja. Izbegavanje zamki za skidanje podataka: Web sajtovi često koriste različite mehanizme za detekciju i blokiranje botova, što zahteva sofisticirane tehnike za izbegavanje detekcije. Drugi deo knjige detaljno se bavi različitim specifičnim alatima i aplikacijama koje su od suštinskog značaja za efikasno skidanje podataka sa interneta. Evo nekih ključnih aspekata koji su obrađeni: Razumevanje i analiza složenih HTML stranica: Upotreba alata kao što je BeautifulSoup za navigaciju i izvlačenje podataka iz HTML-a. Primena regularnih izraza za filtriranje i pretragu specifičnih informacija. Razvoj crawler-a sa Scrapy okvirom: Koraci za inicijalizaciju i konfiguraciju Scrapy spider-a. Definisanje pravila za scraping i upravljanje izlaznim podacima. Metode čuvanja sakupljenih podataka: Različiti formati za skladištenje podataka, uključujući CSV, baze podataka kao što je MySQL, i rad sa medijima. Integracija sa Python-om za upravljanje podacima. Obrada i ekstrakcija podataka iz dokumenata: Tehnike za rad sa različitim formatima dokumenata, uključujući PDF i Microsoft Word. Alati i biblioteke za manipulaciju i ekstrakciju teksta. Čišćenje i normalizacija loše formatiranih podataka: Upotreba alata poput Pandas za transformaciju i pripremu podataka za analizu. Tehnike za rad sa nekonzistentnim i nepotpunim podacima. Čitanje i pisanje prirodnih jezika: Alati i tehnike za obradu prirodnog jezika, uključujući sumiranje podataka i leksikografsku analizu. Primena Natural Language Toolkit-a (NLTK) za statističku i leksičku analizu. Navigacija kroz forme i prijave: Tehnike za automatizaciju interakcija sa veb formama i upravljanje autentifikacijom. Rad sa cookies i sesijama za održavanje stanja tokom scraping-a. Skidanje JavaScript-a i crawling kroz API-je: Upotreba alata poput Selenium-a za interakciju sa JavaScript-om i dinamičkim sadržajem. Tehnike za rad sa API-jima i ekstrakciju podataka iz JSON odgovora. Upotreba i pisanje softvera za prepoznavanje teksta na slikama: Alati kao što je Tesseract za OCR (Optical Character Recognition) i ekstrakciju teksta iz slika. Primene u čitanju CAPTCHA i drugih vizuelnih prepreka. Izbegavanje zamki za skidanje podataka i blokatora botova: Strategije za mimikriju ljudskog ponašanja i izbegavanje detekcije kao bot. Saveti za upravljanje zaglavljima zahteva, kolačićima i TLS fingerprinting-om. Ovaj deo knjige pruža sveobuhvatan pregled alata, tehnika i najboljih praksi koji su potrebni za uspešno skidanje podataka sa interneta, čineći ga neophodnim resursom za svakog ko se bavi ili želi da se bavi ovom oblašću.  

Grafikon “Top five languages in 2025” na prvi pogled deluje kao još jedna trka linija. Ali u suštini, on govori nešto jednostavno: 2025 je godina u kojoj su web i veštačka inteligencija progutali jezički rat. Nije više pitanje “koji je jezik najbolji”, nego ko najbrže pretvara ideju u proizvod — i ko ostaje kičma sistema koji već donose novac. 2025: web i veštačka inteligencija su progutali jezički rat Python je postao jezik razmišljanja. Brz je, fleksibilan, idealan za eksperimente, prototipove i rad sa modelima. U eri gde se ideje testiraju za sat vremena, a ne za mesec dana, Python je prirodan izbor za prvu fazu: da shvatiš problem i proveriš hipotezu. Ali vrednost se na kraju skoro uvek isporučuje kroz proizvod: aplikaciju, servis, interfejs, alat. I tu počinje dominacija drugog sloja. TypeScript stiže Python: prava priča iza grafikona TypeScript ne raste zato što je “odjednom bolji”. Raste zato što je postao najkraći put od funkcije do korisnika. U 2025. godini nije dovoljno da nešto radi — mora da radi stabilno, čitljivo, održivo i u timu. A TypeScript upravo to donosi: brz razvoj, ali uz više kontrole. Zato je TypeScript “priča” koju mnogi tek sada shvataju: on je standard za isporuku. Od ideje do proizvoda: zato TypeScript eksplodira U praksi, sve češće se radi ovako: Python – istražiš, izmeriš, razumeš, brzo napraviš probno rešenje TypeScript – spakuješ, urediš, isporučiš, povežeš sa korisnikom, pratiš metrike Zato TypeScript raste: većina dobrih ideja, čim pređu prag “radi”, mora da postane nešto što ljudi koriste svaki dan. Zašto JavaScript ne umire — već postaje infrastruktura JavaScript na grafikonu nekome može da izgleda kao da je “stao”. Ali to je pogrešno čitanje. JavaScript nije u padu — JavaScript je postao infrastruktura. Kad je nešto svuda, prestane da bude vest. Kao struja: ne razmišljaš o njoj dok ne nestane. Drugim rečima: JavaScript nije izgubio — on je postao podloga. Dosadni jezici prave pare: Java i C# u 2025 Java i C# su jezici stabilnosti. Njihove linije deluju mirno, ali to je često znak stvarnog sveta: banke, osiguranja, državne institucije, velike korporacije, sistemi koji ne smeju da stanu. Taj svet ne pravi buku. Taj svet radi posao. Zato ovi jezici rastu tiho — kao kamata: neprimetno, ali uporno. Popularnost nije poenta: 2025 je godina brzine isporuke Popularnost je indikator sa zakašnjenjem. Važniji je smer: gde ide energija tržišta i gde se skraćuje put od ideje do korisnika. U 2025, prednost nije “znati više”, nego isporučiti brže i pouzdanije. Šta iz ovoga da uzmeš kao praktično pravilo Python biraj ako želiš da misliš, istražuješ, radiš sa podacima i modelima, brzo testiraš ideje. TypeScript biraj ako želiš da gradiš proizvode, interfejse i sisteme koji žive kod korisnika. Java/C# biraj ako ti je bitna stabilnost i rad na velikim sistemima koji već nose ozbiljan promet i odgovornost. Najbolje prakse i saveti: Ne biraj jezik po “hajpu”, nego po tome gde želiš da se tvoj rad završi: u prototipu ili u proizvodu. Dobra kombinacija za 2025: Python za prototip, TypeScript za isporuku. Ako ciljaš korporacije i dugoročne projekte, ne potcenjuj “dosadno”: Java i C# često znače stabilan posao i dug životni ciklus.

NewsPEP 0508 -- Dependency specification for Python Software PackagesThis PEP specifies the language used to describe dependencies for packages. It draws a border at the edge of describing a single dependency - the different sorts of dependencies and when they should be installed is a higher level problem. The intent is to provide a building block for higher layer specifications. Articles, Tutorials and TalksA Python Interpreter Written in PythonByterun is a Python interpreter implemented in Python. This chapter will walk through the structure of the interpreter and give you enough context to explore it further. The goal is not to explain everything there is to know about interpreters --- like so many interesting areas of programming and computer science, you could devote years to developing a deep understanding of the topic. Pyston Talk A talk about the current status of Pyston and some of it's internal workings, such as our mini tracing-JIT. Episode #35: Turbogears and the future of Python web frameworksDo you have a new web project coming up? Are you thinking of choosing Django or maybe Flask? Those are excellent frameworks, but you might also want to check out TurboGears. It was created and released around the same time as Django. It lets you starts your project as a microframework (like Flask) and yet can scale up to a fullstack solution (like Django). It also has built-in support both relational DBs (via SQLAlchemy) and MongoDB. This week Alessandro Molina is here to tell us all about TurboGears! Podcast. __init__ Episode 32 - Erik Tollerud on AstroPyErik Tollerud is an astronomer with a background in software engineering. He leverages these backgrounds to help build and maintain the AstroPy framework and its associated modules. AstroPy is a set of Python libraries that provide useful mechanisms for astronomers and astrophysicists to perform analyses on the data that they receive from observational equipment such as the mountain observatory that Erik was preparing to visit when we talked to him about his work. If you like Python and space then you should definitely give this episode a listen!Python 3. 5 type hinting in PyCharm 5Python 3. 5 introduces type hinting to help code-writing during development. Let's take a look at this feature and show it in action. Of Interneting Trees with Python and PiBlot're. py is a thin Blot're client for Python. This library has similar capabilities to Blot're. js and makes it easy to connect all sorts of good stuff to Blot're. Good stuff like your household plants. This post provides a quick introduction to Blot're. py by example. We'll hook a plant up to Blot're using a Raspberry Pi and a simple moisture sensor.  BDD Testing a Restful Web Application in PythonThis post is an introduction to behaviour-driven development (BDD) in Python, of a RESTful application using Flask web framework. Covers the syntax, structure and goals of BDD. Getting started with Docker, Compose and DjangoThis guide shows you how to set up a Django application and development environment using Docker. How to setup a data science environment in minutes using Docker and JupyterIn this post, we'll cover the basics of Docker, how to install it, and how to leverage Docker containers to quickly get started with data science on your own machine. Flappy Bird in 87 Lines of PythonPython's Hidden Regular Expression GemsOptimizing Slow Django REST Framework PerformanceDjango Under The Hood TalksSpace Invaders created in 1. 5 hours with Pygame PyCon Ireland 2015 VideosBooksMastering PyCharm If you know PyCharm but want to understand it better and leverage its more powerful but less obvious tool set, this is the book for you. Serving as a launch pad for those who want to master PyCharm and completely harness its best features, it would be helpful if you were familiar with some of Python's most prominent tools such as virtualenv and Python's popular docstring formats such as reStructuredText and EpyType. How to Make Mistakes in Python Even the best programmers make mistakes, and experienced programmer Mike Pirnat has made his share during 15+ years with Python. Some have been simple and silly; others were embarrassing and downright costly. In this O'Reilly report, he dissects some of his most memorable blunders, peeling them back layer-by-layer to reveal just what went wrong. Interesting Projects, Tools and LibrariesCacheBrowserA proxy-less censorship resistance tool.  The core idea of CacheBrowser is to grab censored content cached by Content Delivery Networks such as Akamai and CloudFlare directly from their CDN edge servers, therefore, foiling censors' DNS interference. Hacker ScriptsBased on a true story. FINDThe Framework for Internal Navigation and Discovery (FIND) allows you to use your smartphone or laptop to determine your position within your home or office. You can easily use this system in place of motion sensors as its resoltion will allow your phone to distinguish whether you are in the living room, the kitchen or the bedroom, etc. The position information can then be used in a variety of ways including home automation, way-finding, or tracking!ButterflyNetButterflyNet is an server-side batteries-included secure networking framework built upon asyncio. Scikit FlowThis is a simplified interface for TensorFlow, to get people started on predictive analytics and data mining. RefineryA locally deployable open-source web platform for analysis of large document collections. Flask-BloggingA Markdown Based Python Blog Engine as a Flask Extension.  neural-art-tf"A neural algorithm of Artistic style" in tensorflow. dcgan_codeDeep Convolutional Generative Adversarial Networks. ABlogABlog is a Sphinx extension that converts any documentation or personal website project into a full-fledged blog. ImageColorThemeExtract Color Themes from Images. New Releasespandas 0. 17. 1This is a minor bug-fix release from 0. 17. 0 and includes a large number of bug fixes along several new features, enhancements, and performance improvementsMicroPython 1. 5Python 3. 5. 1rc1 ReleaseDjango security releases issued: 1. 9rc2, 1. 8. 7, 1. 7. 11

News Swiss Python Conference Call for Proposals The call for proposals for the first Swiss Python conference is open! The deadline for sending proposals is October 31st. The organizing committee will review all proposals and will post a definitive schedule latest November 30th. 2015. Articles, Tutorials and Talks Hacking the Random Walk Hypothesis Random number generators are used everyday to encrypt data and communications but if the random number generators are flawed then they stop being cryptographically secure and hackers can exploit those vulnerabilities to decrypt the encrypted data and communications. For this reason random number generators need to pass robust sets of statistical tests for randomness, such as the NIST suite of cryptographic tests for randomness, to determine whether they are sufficient for cryptographic uses. In this post we are going to subject various financial market returns to the NIST suite of tests and see whether or not we should be able to, in theory, hack the market. Analyzing 1. 7 Billion Reddit Comments with Blaze and Impala In this post, we'll use Blaze and Impala to interactively query and explore a data set of approximately 1. 7 billion comments (975 GB uncompressed) from the reddit website from October 2007 to May 2015. This data set was made available on July 2015 in a reddit post. The data set is in JSON format (one comment per line) and consists of the comment body, author, subreddit, timestamp of creation and other fields. Let's Build A Simple Interpreter. Part 4. In this part, you're going to learn how to parse and interpret arithmetic expressions with any number of multiplication and division operators in them. I will also talk quite a bit about another widely used notation for specifying the syntax of a programming language. It's called context-free grammars (grammars, for short) or BNF (Backus-Naur Form). For the purpose of this article I will not use pure BNF notation but more like a modified EBNF notation. Straightening Loops: How to Vectorize Data Aggregation with pandas and NumPy This notebook demonstrates alternatives to loops in your code that offer performance and readability improvements of multiple orders of magnitude. It compares native Python loop performance to NumPy and pandas vectorized operations and provides recipes for performing efficient aggregation and transformation with pandas. Episode #25: Effective Python What if you could bottle up all the wisdom and hard-fought experience of many expert Python developers and power up your own skills? That's what Brett Slatkin did and he put it in his book Effective Python. Brett has had a unique opportunity to learn the correct and efficient ways to write Python. He has worked at Google on Google App Engine (GAE) alongside greats such as Guido van Rossum and Alex Martelli. Join the conversation where we discuss some of that wisdom when we talk about Brett's book "Effective Python".   Adding a Simple GUI to Your Pandas Script This article shows you an example of how to easily create an end-user-friendly GUI using the Gooey library. This interface is based on wxWindows so it looks like a "native" application on Windows, Mac and Linux.   Introduction to Python UDFs in Amazon Redshift This post serves as a tutorial to get you started with Python UDFs, showcasing how they can accelerate and enhance your data analytics. You'll explore the CMS Open Payments Dataset as an example. Ball Tracking with OpenCV After reading this post, you'll have a good idea on how to track balls (and other objects) in video streams using Python and OpenCV. How to Create Webkit Browser with Python In this tutorial we’ll create simple web browser using Python PyQt framework. A Web Crawler With asyncio Coroutines Sharks, Landsharks, Geoplotting, and KDTrees! Modern Methods for Sentiment Analysis      Test Fixtures: Setup, Teardown, and so much more (PT004) Books Doing Math with Python Doing Math with Python shows you how to use Python to delve into high school--level math topics like statistics, geometry, probability, and calculus. You'll start with simple projects, like a factoring program and a quadratic-equation solver, and then create more complex projects once you've gotten the hang of things. Creative coding challenges and applied examples help you see how you can put your new math and coding skills into practice. You'll write an inequality solver, plot gravity's effect on how far a bullet will travel, shuffle a deck of cards, estimate the area of a circle by throwing 100,000 "darts" at a board, explore the relationship between the Fibonacci sequence and the golden ratio, and more. Interesting Projects, Tools and Libraries GDB dashboard Modular visual interface for GDB in Python. This comes as a standalone single-file . gdbinit which, among the other things, enables a configurable dashboard showing the most relevant information during the program execution. Its main goal is to reduce the number of GDB commands issued to inspect the current program status allowing the programmer to focus on the control flow instead. Twittor A fully featured backdoor that uses Twitter as a C&C server. sshuttle Transparent proxy server that works as a poor man's VPN. Forwards over ssh. Doesn't require admin. Works with Linux and MacOS. Supports DNS tunneling. Videodigest Videodigest is a command-line utility for generating summaries of videos by (1) applying an automatic summarization algorithm to their subtitles to find the N most important sentences, then (2) compiling the video regions where those sentences appear. c8d A Chip-8 disassembler in Python. The disassembly is based on Cowgod's Chip-8 technical reference document. Armada   Armada is a complete solution for development, deployment, configuration and discovery of microservices. Armada is more than just a tool, it defines conventions and good practices designed towards making your platform more service oriented. Nylas Sync Engine  The Nylas Sync Engine provides a RESTful API on top of a powerful email sync platform, making it easy to build apps on top of email. pyramid_blogr Pyramid_blogr is an example implementation of Flaskr app with Pyramid Web Framework. PyScaffold Python project generator with batteries included. Snaql Raw SQL queries from Python without pain.   New Releases Python 3. 5. 0  Python 3. 5. 0 is the newest version of the Python language, and it contains many exciting new features and optimizations. Jython 2. 7. 1 beta1

News PyCon 2016 Call For Proposals The Call For Proposals is now open -- the PyCon 2016 conference in Portland, Oregon, is accepting talks, tutorial, and poster proposals! Articles, Tutorials and Talks Recurrent Neural Networks Tutorial, Part 2 - Implementing a RNN with Python, Numpy and Theano This the second part of the Recurrent Neural Network Tutorial. In this part we will implement a full Recurrent Neural Network from scratch using Python and optimize our implementation using Theano, a library to perform operations on a GPU.   Episode #27: Four Years of Python for High Schoolers Often people complain about the lack of developer skills in western countries like the United States and that problem is amplified when you consider typically under represented groups such as women and minorities. This week you'll meet Laura Blankenship who is doing more than her share to widen the appeal of programming in general and Python in particular.   Natural Language Basics with TextBlob The aim of this post is to introduce a few simple concepts and techniques from NLP--just the stuff that'll help you do creative things quickly, and maybe open the door for you to understand more sophisticated NLP concepts that you might encounter elsewhere. We'll use a Python library called TextBlob to perform simple natural language processing tasks. Podcast. __init__ Episode 24 - Griatch on Evennia Griatch is an incredibly talented digital artist, professional astronomer and the maintainer of the Evennia project for creating MUDs in Python. We got the opportunity to speak with him about what MUDs are, why they're interesting and how Evennia simplifies the process of creating and extending them. If you're interested in building your own virtual worlds, this episode is a great place to start. Graph Databases for Python Users In this talk, you'll learn how to use Python to collect data from Twitter's API, Neo4j to easily and reliably store this highly-connected data, and Python again for quick analysis and visualization. Memory layout of multi-dimensional arrays When working with multi-dimensional arrays, one important decision programmers have to make fairly early on in the project is what memory layout to use for storing the data, and how to access such data in the most efficient manner. Since computer memory is inherently linear - a one-dimensional structure, mapping multi-dimensional data on it can be done in several ways. In this article I want to examine this topic in detail, talking about the various memory layouts available and their effect on the performance of the code. Using Gabbi and Hypothesis to Test Django APIs In the world of testing it is important to write tests that are both easy to read and covering a wide range of scenarios. Often one of these will be sacrificed to facilitate the other, such as hard coding your examples so that your test logic remains clear or by creating an overly complicated setup so that multiple scenarios can be explored. Here we discuss two tools that, when combined, will allow you to explore more of the test surface of your web API while still creating clear and maintainable tests. Python 3. 5 and multitasking Books Python Machine Learning Python Machine Learning gives you access to the world of predictive analytics and demonstrates why Python is one of the world's leading data science languages. If you want to ask better questions of data, or need to improve and extend the capabilities of your machine learning systems, this practical data science book is invaluable. Covering a wide range of powerful Python libraries, including scikit-learn, Theano, and Keras, and featuring guidance and tips on everything from sentiment analysis to neural networks, you'll soon be able to answer some of the most important questions facing you and your organization. Interesting Projects, Tools and Libraries Zulip Zulip is a powerful, open source group chat application. Written in Python and using the Django framework, Zulip supports both private messaging and group chats via conversation streams. Zulip also supports fast search, drag-and-drop file uploads, image previews, group private messages, audible notifications, missed-message emails, desktop apps, and much more. dnsteal DNS Exfiltration tool for stealthily sending files over DNS requests. voc A transpiler that converts Python bytecode into Java bytecode. procedural_city_generation Procedural City Generation program implemented in Python and Visualized with Blender. Flask-Potion Flask-Potion is a RESTful API framework for Flask and SQLAlchemy. Graphene This is a library to use GraphQL in Python in a easy way. It will map the models/fields to internal GraphQL-py objects without effort. flask-scaffolding Flask Scaffolding featuring Python 3. 4, SQLALCHEMY, BackboneJS, RequireJS & Sass (Bootstrap 3) spectrogram. py ANSI art spectrogram viewer that reads audio from a microphone. Foresight A tool for predicting the output of random number generators. Malfunction Malfunction is a set of tools for cataloging and comparing malware at a function level. Uses Radare2 internally for finding function locations. New Releases Plone 5 Plone 5 is fifteen years of stability wrapped in a modern, powerful user-centric package. It continues to set the pace for content management systems by offering the most functionality and customization out of the box.

Articles, Tutorials and Talks Probability, Paradox, and the Reasonable Person Principle In this notebook, Peter Norvig covers the basics of probability theory, and show how to implement the theory in Python.  Then he shows how to solve some particularly perplexing paradoxical probability problems. Episode #28: Making Python Fast: Profiling Python Code Is that Python code of yours running a little slow? Are you thinking of rewriting the algorithm or maybe even in another language? Well, before you do, you'll want to listen to what Davis Silverman has to say about speeding up Python code using Profiling.   Podcast. __init__ Episode 25 - uWSGI Core Developers uWSGI is one of the most versatile application servers available. It was originally written for running Python applications and has since gained functionality to support Perl, Ruby, PHP, and more in addition to the incredible feature set. In this episode Tobias got to interview three of the core developers of this project and find out more about how the different pieces of it fit together and what its future holds. Learn how to use RethinkDB with Jupyter This talk demonstrates how to perform ReQL queries in a Jupyter notebook, integrating with matplotlib and other libraries to generate data visualizations. A Primer on Neural Network Models for Natural Language Processing Over the past few years, neural networks have re-emerged as powerful machine-learning models, yielding state-of-the-art results in fields such as image recognition and speech processing. More recently, neural network models started to be applied also to textual natural language signals, again with very promising results. This tutorial surveys neural network models from the perspective of natural language processing research, in an attempt to bring natural-language researchers up to speed with the neural techniques. The tutorial covers input encoding for natural language tasks, feed-forward networks, convolutional networks, recurrent networks and recursive networks, as well as the computation graph abstraction for automatic gradient computation. Getting started with Pandas This post covers some introductory tips and tricks to help one get started with Pandas. What Python Tools should I be using on every python project? A good discussion on Reddit. LinkedIn Social Authentication in Django In this tutorial, we'll demonstrate in detail how to integrate Python Social Auth library into your Django Project to provide user authentication through LinkedIn using OAuth 2. 0. PyPy memory and warmup improvements (2) - Sharing of Guards Books Mastering Flask If you are a Flask user who knows the basics of the library and how to create basic web pages with HTML and CSS, and you want to take your applications to the next level, this is the book for you. Harnessing the full power of Flask will allow you to create complex web applications with ease. Numerical Python: A Practical Techniques Approach for Industry  Numerical Python by Robert Johansson shows you how to leverage the numerical and mathematical capabilities in Python, its standard library, and the extensive ecosystem of computationally oriented Python libraries, including popular packages such as NumPy, SciPy, SymPy, Matplotlib, Pandas, and more, and how to apply these software tools in computational problem solving. Python Jobs of the Week Full Stack Developer at Mailgun Mailgun is hiring a full stack developer to work on our control panel team. As a member of this team, you will be responsible for helping build a great customer experience for each and every customer who uses our product.   Interesting Projects, Tools and Libraries Weeman HTTP Server for phishing in Python. pythonize Download, install, and configure Python in one line. intro2stats Introduction to Statistics using Python. safe-commit-hook pre-commit hook for Git that checks for suspicious files.   jupyter-themer Apply custom CSS styling to your jupyter notebooks. DiffPy  A free and open source software project to provide python software for diffraction analysis and the study of the atomic structure of materials. Invatar Invatar provides an "API" for generating fully customizable SVG and image avatars with small text. Inspired from many messaging apps. receipt-parser A fuzzy (supermarket) receipt parser written in Python using tesseract. bqplot Plotting library for IPython/Jupyter Notebooks. Pew A tool to manage multiple virtual environments written in pure python rc-data A script to generate question/answer pairs using CNN and Daily Mail articles downloaded from the Wayback Machine. New Releases Django Bugfix release issued: 1. 8. 5 Numpy 1. 10. 0 PyDev 4. 4. 0

Articles, Tutorials and Talks Podcast. __init__ Episode 29 - Anthony Scopatz on Xonsh Anthony Scopatz is the creator of the Python shell Xonsh in addition to his work as a professor of nuclear physics. In this episode we talked to him about why he created Xonsh, how it works, and what his goals are for the project. It is definitely worth trying out Xonsh as it greatly simplifies the day-to-day use of your terminal environment by adding easily accessible python interoperability. Advanced Jupyter Notebook Tricks -- Part I The Part 1 describes how to use Jupyter to create pipelines and reports. Teardown: Refactoring Search from Monolith to Microservice This post explains the technical choices we made while refactoring our search feature from a component within a monolithic Django project into a microservice. It explores our efforts to break dependence on a shared database, use central authentication and plan for redundancy, among other things. Building Data Pipelines with Python and Luigi This post will discuss some experience in building data pipelines, e. g. extraction, cleaning, integration, pre-processing of data, in general all the steps that are necessary to prepare your data for your data-driven product. In particular, the focus in on data plumbing, and how a workflow manager like Luigi can come to the rescue, without getting in your way. With a minimal effort, the transition from prototype to production can be smoother. The Geography of Basketball: Mapping NBA Shotcharts in ArcGIS There are a lot of great blog posts out there about techniques to get and plot basketball data using the NBA stats API. This post shows how you can use Python to push this data into a Geographic Information System, ArcGIS. From there, you can leverage concepts, tools, and applications that are generally reserved for geography and geographers to make some great visuals from NBA player shot chart data. Deep Learning for Visual Question Answering This post talks about the Visual Question Answering problem, and also present neural network based approaches for same. Five Hundred Deep Learning Papers, Graphviz and Python Let's Build A Simple Interpreter. Part 6. Getting Started with OpenCV and Python: Featuring The Martian Building Simple Command Line Interfaces in Python Books Getting Started with Python and Raspberry Pi Learn to design and implement reliable Python applications on the Raspberry Pi using a range of external libraries, the Raspberry Pis GPIO port, and the camera module. Interesting Projects, Tools and Libraries curio Curio is a modern library for performing reliable concurrent I/O using Python coroutines and the explicit async/await syntax introduced in Python 3. 5. Its programming model is based on cooperative multitasking and common system programming abstractions such as threads, sockets, files, subprocesses, locks, and queues. Under the covers, it is based on a task queuing system that is small, fast, and powerful. confidant Confidant is a open source secret management service that provides user-friendly storage and access to secrets in a secure way, from the developers at Lyft. worldengine World generator using simulation of plates, rain shadow, erosion, etc. dive-into-machine-learning Dive into Machine Learning with Jupyter and scikit-learn. neural-storyteller A recurrent neural network for generating little stories about images. Harvey Harvey is a command line legal expert who manages license for your open source project. RemI Python REMote Interface library. Platform indipendent. In less than 100 Kbytes, perfect for your diet. aioodbc A library for accessing a ODBC databases from the asyncio. sklearn-deap Use evolutionary algorithms instead of gridsearch in scikit-learn. This allows you to exponentially reduce the time required to find the best parameters for your estimator. Instead of trying out every possible combination of parameters, evolve only the combinations that give the best results. oscrypto Compilation-free, always-patched, Python crypto library for OS X, Windows and Linux/BSD. sentimentAPI A fast python scikit-learn text sentiment API server. sops sop is an editor of encrypted files that supports YAML, JSON and TEXT formats and encrypts with AWS KMS and PGP (via GnuPG).   New Releases PyCharm 5 PyCharm 5 brings an outstanding lineup of new features, including full Python 3. 5 support, Docker integration, Thread Concurrency Visualization, code insight for Django ORM methods, Conda integration, and IPython Notebook v4 support, just to name a few. Django 1. 8. 6 Django 1. 8. 6 adds official support for Python 3. 5 and fixes several bugs in 1. 8. 5. Anaconda 2. 4 matplotlib-1. 5 // Getting Started with OpenCV and Python: Featuring The Martian Building Simple Command Line Interfaces in Python Books Getting Started with Python and Raspberry Pi Learn to design and implement reliable Python applications on the Raspberry Pi using a range of external libraries, the Raspberry Pis GPIO port, and the camera module. Interesting Projects, Tools and Libraries curio Curio is a modern library for performing reliable concurrent I/O using Python coroutines and the explicit async/await syntax introduced in Python 3. 5. Its programming model is based on cooperative multitasking and common system programming abstractions such as threads, sockets, files, subprocesses, locks, and queues. Under the covers, it is based on a task queuing system that is small, fast, and powerful. confidant Confidant is a open source secret management service that provides user-friendly storage and access to secrets in a secure way, from the developers at Lyft. worldengine World generator using simulation of plates, rain shadow, erosion, etc. dive-into-machine-learning Dive into Machine Learning with Jupyter and scikit-learn. neural-storyteller A recurrent neural network for generating little stories about images. Harvey Harvey is a command line legal expert who manages license for your open source project. RemI Python REMote Interface library. Platform indipendent. In less than 100 Kbytes, perfect for your diet. aioodbc A library for accessing a ODBC databases from the asyncio. sklearn-deap Use evolutionary algorithms instead of gridsearch in scikit-learn. This allows you to exponentially reduce the time required to find the best parameters for your estimator. Instead of trying out every possible combination of parameters, evolve only the combinations that give the best results. oscrypto Compilation-free, always-patched, Python crypto library for OS X, Windows and Linux/BSD. sentimentAPI A fast python scikit-learn text sentiment API server. sops sop is an editor of encrypted files that supports YAML, JSON and TEXT formats and encrypts with AWS KMS and PGP (via GnuPG). // ]]>

Articles, Tutorials and Talks Anyone Can Learn To Code an LSTM-RNN in Python (Part 1: RNN) This tutorial teaches Recurrent Neural Networks via a very simple toy example, a short python implementation. Asynchronous Programming with Python 3 Python 3. 5 introduced the new keywords, async and await to Python. This change solidifies a strong commitment towards writing asynchronous programs in Python. Before in Python 3. 4, we needed to use parts of the standard library (using the decorator asyncio. coroutine). So, what does this all mean? In this tutorial, we are going to try and answer that question. Episode #34: Continuum: Scientific Python and The Business of Open Source What if you built a product that dramatically improved how hundreds of free, open source Python libraries worked together, gave it to the world for free, and then built a thriving business on it? It's the open-source dream really, isn't it? In this episode, we talk with Travis Oliphant from Continuum who did exactly that!  Comparing 7 Python data visualization tools In this post, we'll use a real-world dataset, and use each of these 7 libraries to make visualizations. As we do that, we'll discover what areas each library is best in, and how to leverage the Python data visualization ecosystem most effectively. Build a simple distributed system using AWS Lambda, Python, and DynamoDB In this post, we'll present a complete example of a data aggregation system using Python-based Lambda functions, S3 events, and DynamoDB triggers; and configured using the AWS command-line tools (awscli) wherever possible.   Podcast. __init__ Episode 31 -  Dariusz Suchojad on Zato Service integration platforms have traditionally been the realm of Java projects. Zato is a project that shows Python is a great choice for systems integration due to its flexibility and wealth of useful libraries. In this episode we had the opportunity to speak with Dariusz Suchojad, the creator of Zato about why he decided to make it and what makes it interesting. Listen to the episode and then take it for a spin. Machine Learning with a Data-Unfriendly Stack Stripe processes billions of dollars in payments a year on behalf of tens of thousands of businesses, using machine learning to detect and stop fraudulent transactions and fraudulent merchants. Our modeling workflow involves the typical "data science" tools: R and IPython for exploratory analysis, Hadoop for batch data processing, and scikit-learn for model building. However, Stripe's production backend is written in Ruby and uses MongoDB as its data store, and this has introduced difficulties for both model training and production scoring. In this talk, I'll describe the various choices we've made to bridge "main land" and "data land" and how, in the process, our model development process has gone from terrible to "ok. " Digging Into the Pronto Data Release In October Seattle's bike sharing service, Pronto, turned one year old and released a treasure-trove of data on the 140,000 individual trips during the first year. Here I want to dig into this data and answer a few questions. Profiling Python using cProfile: a concrete case Writing programs is fun, but making them fast can be a pain. Python programs are no exception to that, but the basic profiling toolchain is actually not that complicated to use. Here, I would like to show you how you can quickly profile and analyze your Python code to find what part of the code you should optimize. Bayesian Modelling in Python A tutorial for those interested in learning how to apply bayesian modelling techniques in python (PYMC3). This tutorial doesn't aim to be a bayesian statistics tutorial - but rather a programming cookbook for those who understand the fundamental of bayesian statistics and want to learn how to build bayesian models using python.   Z algorithm in Python  There are few algorithms for exact substring searching (e. g. Knuth-Morris-Pratt, Boyer-Moore etc. ) This post explains one of them which is called Z algorithm. The Geography of Basketball, Part II: Watching the Game in ArcGIS A real Python "wat" Practical Natural Language Processing with Hostel Reviews Visualising Markov Chains with NetworkX Books Getting Started with Python Data Analysis This is an easy-to-follow, step-by-step guide to get you familiar with data analysis and the libraries supported by Python. Topics are explained with real-world examples wherever required. Interesting Projects, Tools and Libraries tpot A Python tool that automatically creates and optimizes Machine Learning pipelines using genetic programming. Mining Georeferenced Data A hands on guide on using Python to collect, analyse and mine geo-referenced data from location based services (e. g. Foursquare, Twitter) and the Sharing Economy (Uber, Airbnb etc. ). mailur Mailur aims to become the future open source replacement for Gmail. It is already usable as an alternative Gmail interface with a set of unique features. ElastAlert  ElastAlert is a simple framework for alerting on anomalies, spikes, or other patterns of interest from data in Elasticsearch. birdseed birdseed is a utility to create pseudo and/or "real" random numbers from tweets based on a particular search query over Twitter's API. Zerotest Lazy guy's testing tool, test your API server like a boss. Zerotest makes it easy to test API server, start a micro proxy, send requests, and generate test code by these behaviours. Talisman Talisman is a small Flask extension that handles setting HTTP headers that can help protect against a few common web application security issues. Spinnaker Spinnaker is an open source, multi-cloud continuous delivery platform for releasing software changes with high velocity and confidence. tensorflow-deepq A deep Q learning demonstration using Google Tensorflow. Orator The Orator ORM provides a simple yet beautiful ActiveRecord implementation. rc Redis cache cluster system in Python. New Releases Django 1. 9 release candidate 1

​Šta obuhvata ova knjiga U Poglavlju 1, „Izrada aplikacije za blog“, upoznaćete radni okvir, koristeći aplikaciju za blog. Kreiraćete osnovne modele bloga, prikaze (views), šablone (templates) i URL-ove za prikazivanje postova na blogu. Naučićete kako da izradite QuerySets pomoću Django objektnog-relacionog mapera (ORM – Object-Relational Mapper) i kako da konfigurišete Django administratorski sajt. U Poglavlju 2, „Poboljšanje bloga pomoću naprednih funkcija“, naučićete kako da upravljate obrascima i ModelFormsima, da šaljete e-poštu pomoću Djangoa i da integrišete nezavisne aplikacije. Primenićete sistem za komentare na svoje blogove i omogućićete korisnicima da dele postove pomoću e-pošte. Ovo poglavlje će vas takođe voditi kroz proces kreiranja sistema za označavanje. U Poglavlju 3, „Proširenje aplikacije za blog“, istražujemo kako se kreiraju prilagođene oznake šablona i filteri. Takođe će biti prikazano kako se koristi radni okvir mape sajta (sitemap) i kako se kreira RSS feed za postove. Završićete svoju aplikaciju za blog izradom pretraživača koji ima mogućnost PostgreSQL-ovog pretraživanja punog teksta. U Poglavlju 4, „Izrada društvenog veb sajta“, objašnjeno je kako se kreira društveni veb sajt. Koristićete Django radni okvir za autentifikaciju da biste kreirali prikaz korisničkih naloga. Takođe ćete naučiti kako da kreirate prilagođeni model korisničkog profila i kako da ugradite društvenu autentifikaciju u svoj projekat, koristeći glavne društvene mreže. U Poglavlju 5, „Deljenje sadržaja na veb sajtu“, naučićete kako da transformišete svoju društvenu aplikaciju u veb sajt za merenje popularnosti slika. Definisaćete veze tipa „više prema više“ i kreiraćete AJAX aktivni obeleživač (bookmarklet) u JavaScriptu koji ćete integrisati u svoj projekat. U ovom poglavlju će biti prikazano kako se generiše umanjeni prikaz slika i kako se kreiraju prilagođeni dekoratori za prikaze. U Poglavlju 6, „Praćenje korisničkih radnji“, prikazano je kako se izrađuje sistem praćenja za korisnike. Završićete veb sajt za merenje popularnosti slika, tako što ćete kreirati aplikaciju za tok korisničkih aktivnosti. Naučićete kako da optimizujete QuerySets i koristićete signale. Na kraju ćete integrisati Redis u svoj projekat da biste izbrojali prikaze slika. U Poglavlju 7, „Izrada internet prodavnice“, istražujemo kako se kreira internet prodavnica. Izradićete modele kataloga i kreiraćete korpu za kupovinu, koristeći Django sesije. Izradićete kontekstni procesor za korpu za kupovinu i naučićete kako da primenite slanje asinhronih obaveštenja korisnicima koji koriste Celery. U Poglavlju 8, „Upravljanje plaćanjem i narudžbenicama“, objašnjeno je kako možete da integrišete platni mrežni prolaz u svoju prodavnicu. Takođe ćete prilagoditi administratorski sajt za izvoz narudžbenica u CSV datoteke i dinamički ćete generisati PDF fakture. U Poglavlju 9, „Proširenje prodavnice“, naučićete kako da kreirate sistem za kupone za primenu popusta na porudžbine. Takođe ćemo prikazati kako da dodate internacionalizaciju svom projektu i kako da prevedete modele. Na kraju ćete kreirati mehanizam za preporuku proizvoda pomoću Redisa. Poglavlje 10, „Izrada platforme za elektronsko učenje“, vodiće vas kroz kreiranje platforme za elektronsko učenje. U projektu ćete da dodate fixture (skup podataka), da koristite nasleđivanje modela, da kreirate polja prilagođenih modela, da koristite prikaze zasnovane na klasama i da upravljate grupama i dozvolama. Takođe ćete da kreirate sistem za upravljanje sadržajem i da upravljate skupovima obrazaca (formsets). U Poglavlju 11, „Renderovanje i keširanje sadržaja“, biće prikazano kako možete da kreirate sistem za registraciju učenika i kako da upravljate upisom učenika na kurseve. Renderovaćete različite sadržaje kursa i naučićete kako da koristite radni okvir keš memorije. U Poglavlju 12, „Izrada API-a“, naučićete postupak izrade RESTful API-a za svoj projekat, koristeći Django REST radni okvir. U Poglavlju 13, „Izrada servera za ćaskanje“, objasnićemo kako se koriste Django kanali za kreiranje servera za ćaskanje u realnom vremenu za učenike. Naučićete kako da primenite funkcije koje se oslanjaju na asinhronu komunikaciju pomoću WebSocketsa. U Poglavlju 14, „Akcija“, biće prikazano kako da podesite proizvodno okruženje, koristeći uWSGI, NGINX i Daphne. Naučićete kako da obezbedite okruženje pomoću HTTPS-a. U ovom poglavlju je takođe objašnjeno kako se kreiraju prilagođeni posrednički softver i prilagođene komande za upravljanje. NARUČITE KNJIGU: KORPA

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Da li ste ikada razmišljali o tome da postanete registrovani član Kompjuter biobliteke? Ako niste, vreme je da razmislite! Postati član naše biblioteke donosi mnoge prednosti koje će obogatiti vašu ljubav prema knjigama i tehnologiji. Evo nekoliko razloga zašto je to odlična odluka. 1. Jednostavan proces registracije Postati registrovani član je neverovatno jednostavno i pristupačno. Sve što treba da uradite je da kupite bilo koju našu knjigu - preko sajta ili lično u knjižari. Registracija zahteva samo osnovne podatke: ime i prezime, adresu prebivališta, telefon i email adresu. Ovim jednostavnim korakom otvarate vrata mnogobrojnim mogućnostima i pogodnostima koje pruža članstvo. 2. Rođendanski popusti Kao registrovani član, svake godine na svoj rođendan imate pravo na poseban poklon od nas - kupovinu bilo koje naše knjige po specijalnoj rođendanskoj ceni od samo 1. 000 dinara. Ovo je naš način da vam zahvalimo što ste deo naše zajednice i da proslavimo vaš poseban dan sa vama. 3. Ekskluzivne akcije i popusti Jedna od glavnih prednosti članstva su ekskluzivni mejlovi koje šaljemo samo našim registrovanim članovima. U ovim mejlovima se nalaze specijalni kodovi za popuste i informacije o akcijama koje nisu dostupne onima koji nisu članovi. To znači da imate pristup najboljim ponudama i priliku da prvi saznate za naše posebne akcije. 4. Status "PRETPLATNIK" i dodatni popusti Ako se odlučite da se pretplatite na novu knjigu, automatski stičete status "PRETPLATNIK". Ovo ne samo da vam garantuje da ćete među prvima dobiti najnovija izdanja, već i omogućava kupovinu još jedne knjige sa neverovatnim popustom od 40% u odnosu na redovnu knjižarsku cenu. Ovo je savršena prilika da proširite svoju kolekciju knjiga po znatno povoljnijim cenama. NAPOMENA: Trenutno je u pretplati najnovija knjiga "ujka Boba": "Funkcionalan dizajn" Koja izlazi iz štampe 24. januara. Ukoliko se pretplatite na ovu knjigu, možete bilo koju drugu našu knjigu da kupite sa 40% popusta.