[Chennaipy] August Meetup - Minutes

hafizul azeez hafizul.azeez at gmail.com
Mon Aug 29 06:43:31 EDT 2016


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
>>>>
>>>> _______________________________________________
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>>>> Chennaipy at python.org
>>>> https://mail.python.org/mailman/listinfo/chennaipy
>>>>
>>>>
>>>
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