[Chennaipy] Chennaipy Digest, Vol 36, Issue 12

[hafizul azeez]

@sairam, you can get the presentations from the meetup page (chennaipy
meetup.com)

On 30 August 2016 at 11:08, Sairam Murali <isairamm at gmail.com> wrote:

> Hi All,
>
> Went through the meeting notes, it would be great if there is a place
> where can i get the presentation or recordings of the talks?
>
> Thanks!
> Sai
>
> On Mon, Aug 29, 2016 at 4:13 PM, <chennaipy-request at python.org> wrote:
>
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>> Today's Topics:
>>
>>    1. Re: August Meetup - Minutes (hafizul azeez)
>>
>>
>> ----------------------------------------------------------------------
>>
>> Message: 1
>> Date: Mon, 29 Aug 2016 16:13:31 +0530
>> From: hafizul azeez <hafizul.azeez at gmail.com>
>> To: Chennai Python User Group Mailing List <chennaipy at python.org>
>> Subject: Re: [Chennaipy] August Meetup - Minutes
>> Message-ID:
>>         <CAAAE1MpFJjB3t3m6fKrBn2qkd30o8RWnV4SH-y+1MBA-_-pT+A at mail.gm
>> ail.com>
>> Content-Type: text/plain; charset="utf-8"
>>
>> 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 <asinode at 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.azeez at 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 <asinode at 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.azeez at 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 at python.org
>> >>>> https://mail.python.org/mailman/listinfo/chennaipy
>> >>>>
>> >>>>
>> >>>
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