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 > >
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