Tasdik, Thank you for your input. I think that totally makes sense. I will still like to go ahead and try with Flask because of one solid reason. To call myself at least theoretically comfortable with python, it took more than a year of self-learning. I am sure JavaScript, while syntactically a little easier to learn, but has a learning curve when it comes to learning the way it does the background. And my experiments with HTML, CSS code has been very minimal so far.
But I came across similar quote generators developed by JS more than python in the last couple days. So you are right. I will keep your idea in mind and soon will give it a try for sure. Thank you Anand On Mon, Aug 29, 2016 at 4:18 PM, Tasdik Rahman <prodi...@outlook.com> wrote: > Hey Anand, > > I will not be the best person to answer this so if I say something wrong. > Please do point it out. > > I have heard good things about text generation using Markov chains. But I > think python would not come into picture here as you mentioned you are > using github pages to host that app. > > A client side language like JS should do the trick. As github pages would > not allow any server side code to be run there (only static files are > allowed). > > Best, > Tasdik > ------------------------------ > *From:* Chennaipy <chennaipy-bounces+prodicus=outlook....@python.org> on > behalf of Anand Surampudi <asin...@zoho.com> > *Sent:* Monday, August 29, 2016 3:59:50 PM > *To:* Chennai Python User Group Mailing List > *Subject:* Re: [Chennaipy] August Meetup - Minutes > > Sure Azeeze. I will work on that. Thanks for your constant push. > > Meanwhile, can you or anybody suggest a resource for learning how to > achieve a small task in python. What I want to do is to build a web page > that randomly generates a quote on every click of a button. Lets just say I > want to host this page on github pages. I know how content-based github > pages work since I maintain my blog there. But this is something I want to > learn using github pages and python. This is it. > > I am sure this sounds pretty silly. But as a beginner, I would like to > give myself this kind of tasks for my learning. > > On script level, I can do it. I mean I run the script on terminal and it > definitely throws the random quote as an output. But I want the same thing > to happen on a web page, but random printing should happen on every click > of a button, say something like, "Surprise me!" or something. > > Thanks. > Anand > > On Mon, Aug 29, 2016 at 2:50 PM, hafizul azeez <hafizul.az...@gmail.com> > wrote: > >> Anand, >> >> Hope you are getting well now! >> >> I gave my first talk (ah.. finally) after 3 meetups - though it was >> unprepared. I encourage you to do the talks sometime. We would love to hear >> from you - your thoughts and experiments with python. >> >> Azeez >> >> >> On 29 August 2016 at 14:31, Anand Surampudi <asin...@zoho.com> wrote: >> >>> Azeez, >>> >>> You really made me feel so bad. You forced me to see how much I missed. >>> Just kidding! ;-) >>> >>> But from your minutes, I seriously regret not making it yesterday as I >>> was down with fever. That was very elaborate record of minutes and thanks a >>> lot for initiating this. I will try to make use of the material that is >>> hopefully going on github soon. >>> >>> Anand >>> >>> On Mon, Aug 29, 2016 at 10:57 AM, hafizul azeez <hafizul.az...@gmail.com >>> > wrote: >>> >>>> The non-stop drizzle, the quiet IMSc environment and vibrant >>>> pythonistas set the context and expectations for the August meetup. >>>> However, plans took unexpected turns when the speakers got delayed due to >>>> the drizzling rain outside and the traffic created by it. Vijay took the >>>> stage to engage the audience with round of introductions and a generic Q&A >>>> session on python and the community. All of them took the opportunity to >>>> introduce themselves and a few asked some interesting questions. With the >>>> speakers not turning up yet, Vijay announced a lightning talk session. >>>> >>>> Rengaraj from Zilogic systems took the opportunity to present an idea >>>> he was working with (DBus), explained the design and asked for feedback and >>>> contributions. Kudos to Rengaraj - though it was a lighting talk, taking to >>>> the stage with no slides and preparation within few minutes summons respect >>>> and appreciation. >>>> >>>> An introduction to Flask by Hafizul Azeez >>>> >>>> As an emergency talk, Azeez gave a brief description of Flask and how >>>> it can be used for rapid application development. Azeez highlighted the >>>> difference between the micro web framework, Flask and how it is compared >>>> with a batteries included framework like Django. He gave a brief demo of >>>> how a simple Flask web app looks like and explained the code behind the >>>> app. >>>> >>>> He also made slight changes to the code with the inclusion of html >>>> templates and how parameters can be passed from the client side to the >>>> server side thru Flask routes a.k.a end points. In the process, he said how >>>> the Flask framework supports a design pattern called MVT (Models, Views and >>>> Templates) and how it all works in orchestration to make the web app. >>>> >>>> He also gave additional inputs on extending the Flask app with Plugins >>>> and highlighted a few prominent plugins like FlaskWTF (for Forms), >>>> Flask-SQLAlchemy (for databases), Flask-Login (for managing user logins, >>>> authentications, session management and cookies) and few additional modules >>>> (like Jsonify). Overall, the session received positive inputs considering >>>> that it was planned to be a filler (till speakers arrive) lightning talk >>>> but turned to be a 20 minute talk. >>>> >>>> This talk was followed by tea and networking. The cool weather outside >>>> (something Chennai misses too often) and the hot tea and coffee inside >>>> added energy to the already pumped up pythonistas. Getting to know new >>>> people, shaking hands, answering queries, taking feedback accompanied with >>>> good weather - whoa, just awesome! Speakers turned up sometime back and two >>>> more talks to go as per schedule. >>>> >>>> Computer Vision with Deep Learning by Manish Shivanandhan >>>> >>>> Manish started with an introduction of deep learning and how machine >>>> learning and deep learning differs. Machine learning is more of recognising >>>> patterns and deep learning is more of learning about patterns. Manish >>>> covered the different types of learning - supervised, unsupervised and >>>> reinforcement and gave examples for each of these types; along with >>>> classification and regression and provided real life examples (housing >>>> prices, stock prices etc) to compliment the understanding. >>>> >>>> Coming to neural networks, Manish hinted various algorithms are used >>>> for deep learning and one of them being Neural networks. He also deciphered >>>> as to why Neural networks is getting so much traction these days!? - and >>>> attributed it to the increasing computer processing power and the exploding >>>> amounts of data. >>>> >>>> He also highlighted the use cases of Neural networks and its advantages >>>> and limitations. Prominent examples being: >>>> Computer vision - pattern recognition in images >>>> Creative usage - generating text/music/speech >>>> >>>> One interesting exampling Manish gave is the JK Rowling (Author of >>>> Harry Potter series) case and how Neural networks helped identify when one >>>> of her books was written in another pen name (which was not JK Rowling). >>>> This captivated the audience much more as this is some thing almost all of >>>> the audience can correlate with. He also stressed the importance of Neural >>>> networks in the health care domain in finding cure for diseases. >>>> >>>> He covered how neural networks can be used in Computer vision and deep >>>> learning. He gave insights into how to take a problem and represent it in >>>> numbers so that deep learning can be used. He also hinted that if any >>>> problem can be represented in numbers, deep learning can be used. He demoed >>>> with an image, flattening it and showing the numbers behind it and >>>> highlighted that with enough numbers and processing power, patterns can be >>>> learnt by Neural networks. He complimented that with the Prisma case study >>>> where researchers took a lot of art manually, scanned it and fed neural >>>> networks to learn how the great artists like Picaso would have painted the >>>> picture (the brush strokes, the pressure applied etc). So when an image >>>> (like selfie) is fed into the Prisma application, the computer generates >>>> the art form of the image- i.e. how the image would look like if it was a >>>> painting from Picaso and the likes. This further stressed how deep learning >>>> can be used and how neural networks can be trained provided sufficient >>>> clean data is fed into it. >>>> >>>> Finally, he gave an introduction to TensorFlow and its distinct >>>> abilities when compared to other frameworks like Theano. Manish finished >>>> his talk with resources and references for further exploration of Neural >>>> networks and details about his upcoming webinar. Oh yes, he answered a lot >>>> of questions on deep learning from an inquisitive audience who were awed by >>>> the potential of deep learning and bitten by Manish's enthusiasm. >>>> >>>> Behaviour Driven Development by Naren Ravi >>>> >>>> Naren provided the background of the talk with a short description of >>>> what Behaviour Driven Development (BDD) is all about - i.e. testing the >>>> code with the user in mind and meeting the expectation of the stakeholders >>>> rather than just testing the code. >>>> >>>> He started with the waterfall model, the advantages and it's >>>> limitations. He gave insights into why testing in the later stages of the >>>> cycle makes life difficult - if bugs encountered and to finally discover >>>> that the design itself is flawed bringing up frustrations. >>>> >>>> He then covered how the first optimisation on the waterfall model was >>>> done with testing the code and informing the development and how further >>>> optimisation was done to the waterfall model with both testing and >>>> construction (coding) done parallely. Though these optimisations were done, >>>> Naren stated that there was an inherent disadvantage that was left with - >>>> i.e. the design cannot be tested. The solution is to bring the design into >>>> the development i.e testing, coding and design all tested parallely which >>>> is the Test Driven Development (TDD). >>>> >>>> Naren then added that even TDD won't suffice as the requirement >>>> analysis stage is completely left out. He then questioned the possibility >>>> of scope (requirements) change and how the SDLC model would adopt it!? >>>> Bringing the analysis cycle into the above cycle of testing, code and >>>> design becomes the BDD, he concluded. This gave an overall picture of the >>>> BDD - testing (test cases) first, construction (coding) and the design and >>>> finally checking if all of it matches the requirements. >>>> >>>> He added that in some context, this is how lean startup works. Develop >>>> a product with a new feature, send it to market, get feedback and then add >>>> a new feature, send it to market, gauge the reactions and the cycle goes >>>> on. Overall, it was a well structured talk starting with the traditional >>>> waterfall model to TDD to BDD and what optimisations were made on the way. >>>> He answered a few questions later to help bring more clarity into BDD. >>>> >>>> The meetup ended with Vijay thanking the venue and networking over tea >>>> sponsors, speakers and the rest who made the meetup a successful event. He >>>> also asked attendees to register in the mailing list to keep abreast of the >>>> happenings in the Chennaipy community. >>>> >>>> Regards >>>> Azeez >>>> >>>> _______________________________________________ >>>> Chennaipy mailing list >>>> Chennaipy@python.org >>>> https://mail.python.org/mailman/listinfo/chennaipy >>>> >>>> >>> >>> _______________________________________________ >>> Chennaipy mailing list >>> Chennaipy@python.org >>> https://mail.python.org/mailman/listinfo/chennaipy >>> >>> >> >> _______________________________________________ >> Chennaipy mailing list >> Chennaipy@python.org >> https://mail.python.org/mailman/listinfo/chennaipy >> >> > > _______________________________________________ > Chennaipy mailing list > Chennaipy@python.org > https://mail.python.org/mailman/listinfo/chennaipy > >
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