Thank you Azeez. I began learning Flask. I have been wanting to learn Flask & Django since I learned about RoR becaming so famous and industry application. I did not imagine my idea could make use of it.
Will update you once I find myself stuck. Anand On Mon, Aug 29, 2016 at 4:13 PM, hafizul azeez <hafizul.az...@gmail.com> wrote: > Anand, > > It's easily doable. You can use Flask web framework to do it. You can send > a request via ajax from the client (browser) to the server with the input > being a random number between 1 and 100 (or the max number of quotes) you > have in your db or for that matter in a text file. > > The server takes the request, checks the paramater (the random number) and > picks the appropriate row id from the database and return it as json or as > a python object which you can format (using jinja templates) and write to > the DOM of the browser. > > I suggest you start with a Flask tutorial - which will give you a general > idea : http://code.tutsplus.com/tutorials/creating-a-web-app- > from-scratch-using-python-flask-and-mysql--cms-22972 > > > Thanks > Azeez > > On 29 August 2016 at 15:59, Anand Surampudi <asin...@zoho.com> wrote: > >> 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 >> >> > > _______________________________________________ > Chennaipy mailing list > Chennaipy@python.org > https://mail.python.org/mailman/listinfo/chennaipy > >
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