Feb 2017 Meetup Minutes

A Gentle Intro to Types by Shrayas Rajagopal

Shrayas Presenting his Talk

Shrayas started by building on the basics to introduce more advanced concepts later on. - What are types? - Class of value - Set of operations

  • Why Types?

    • Humans make a lot of errors
    • Computers are very good at repeating things
    • Types help them to bring it together. Helps reduce the number of mistakes
  • Type Systems

    • Think of them like magic boxes
    • They run through the source code
    • Check if the program makes sense given the set of operations (rules)
  • Dynamic Typing vs Static Typing

    • General myth that static has types and dynamic means no types
    • He explained that both actually have types.
    • Static languages get to know about the type at compile time
    • Dynamic languages get to know about the type at runtime
    • He then showed examples where errors where caught during compile time in C# but went undetected until runtime in Python
  • Advantages and Disadvantages of both based on the following criteria

    • Hackable or not (easy to get started and build things)
    • Readability
    • Iteration speed
    • Enforces tests or not
    • Size of code base
  • Gradual Typing

    • Advantages of both
    • Runtime fluidity marries compile time rigidity
    • Some languages / frameworks with gradual typing
      • Hack
      • Typescript
      • mypy
  • Why Gradual Typing?

    • Rigidity
    • Better dev tools
    • Readability
    • Conscise code base
    • It is possible to migrate your codebase to gradual typing in part

GUI Using Python by Gaurav Sehrawat

Gaurav went over the following:-

  • Basic Info

    • tkinter is a Python interface to Tcl/Tk
    • Tcl/Tk is cross platform
    • Tcl is a dynamic language. Tk is an extension provided for development of GUIs
    • Uses native system APIs
    • Each GUI is basically a collection of frames. Each frame has a layout manager
    • The IDLE editor is built using Tkinter
  • Python 2 vs Python 3

    • Very easy to port Tkinter code. It's very similar across both 2 & 3
    • Letter casing is different or it is has a prefix
  • Geometry Manager or Layout Manager

    • Specify relations with respect to other elements
    • Pack (simple layout manager)
    • Grid (table like)
  • When to Use Pack

    • Simple geometry like up, down etc
    • Side by Side
    • Element go on top of each other
  • If you need something more complex and specific it's always better to go with grid.

  • Widget List

    • Labels
    • Buttons
    • Dialog Boxes etc
  • He showed the following examples

    • Hello, World
    • Pack
    • Grid
    • Events and bindings
    • Dialog Boxes
    • Matplot lib
    • Matplot lib dynamic plots using changes in real time data
    • opencv

Networking Tea Break sponsored by InkMonk

Section of members gathered

YAML Validation in Python by Vijay Kumar

  • He quicly went over the basics

    • Different methods of representing data
    • Impacts of representation
  • Benefits of text representation

    • Easy to create
    • Easy to use Version Control Systems
    • Easy to review
  • Explained about Asciidoc. Humans can enter text. It then converts it to other formats using toolchains

  • Types of Data

    • Structured Data
      • Structures that are easy for computers to understand but difficult for humans
      • They can be manipulated by the computer easily
      • Example arrays, Databases
    • Unstructured Data
      • Human oriented
      • Harder for machines to work with such data
      • Eg Word Documents
    • Semi Structured Data
      • Easy for both computers and humans
      • Eg:- XML, JSON, YAML
      • It undergoes an additional step like parsing
  • YAML

    • Superset of JSON
    • Syntax and things possible
    • Examples of YAML that helps him organise ChennaiPy
  • Roadblocks to using YAML

    • Human input prone to errors
    • Proper validation is key
  • Difficulties in validation YAML

    • Writing code that handles verification is hard
    • No schema available for YAML
    • Examples of nasty error messages thrown when validation fails
  • Using jsonschema to validate YAML thus giving better error checking and friendlier prompts

Lightning Talk by Ashok Govindarajan

He spoke about his broad top level views on Machine Learning.

  • Born out of pattern recognition
  • Mostly comprises of curve fitting, adapt, predict and recommend
  • Why the sudden rise in Machine Learning?
    • There from quite a long time
    • Sudden rise due to faster hardware, more storage and lots of good sources of data
  • Role of low cost sensors
  • Machine learning preceeds / enables decision making
  • Helps in intuition to data driven decisions


Vijay thanked Inkmonk for sponsoring the venue and Zilogic Systems for sponsoring the projector.

Group Photo

Group Photo

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