saswata-dutta

Overview

When you're working on multiple coding projects, you might want a couple different version of Python and/or modules installed. That way you can keep each project in its own sandbox instead of trying to juggle multiple projects (each with different dependencies) on your system's version of Python. This intermediate guide covers one way to handle multiple Python versions and Python environments on your own (i.e., without a package manager like conda). See the Using the workflow section to view the end result.

Use cases

1. Working on 2+ projects that each have their own dependencies; e.g., a Python 2.7 project and a Python 3.6 project, or developing a module that needs to work across multiple versions of Python. It's not reasonable to uninstall/reinstall modules every time you want to switch environments.
2. If you want to execute code on the cloud, you can set up a Python environment that mirrors the relevant

saswata-dutta

function unary(type, rhs) {
    return {
        type : type,
        rhs: rhs
    };
}

function binary(type, lhs, rhs) {
    return {
        type : type,

saswata-dutta

Vim

Finding Your Way Around

Download MacVim (optional)

MacVim

Set up Oh-my-zsh (optional)

saswata-dutta

Python - comparing JSON data structures

A function compare_json_data(source_data_a,source_data_b), accepting structures populated with data loaded from json.load() and comparing for equality.

Example

$ python compare.py 
Compare JSON result is: True

JSON files a.json and b.json are loaded via load_json() function and structures passed into compare_json_data() for comparison.

saswata-dutta

Introduction

An introduction to curl using GitHub's API.

The Basics

Makes a basic GET request to the specifed URI

curl https://api.github.com/users/caspyin

saswata-dutta

Introduction

An introduction to curl using GitHub's API

The Basics

Makes a basic GET request to the specifed URI

curl https://api.github.com/users/caspyin

saswata-dutta

// The expression problem is a new name for an old problem.  The goal is to
// define a datatype by cases, where one can add new cases to the datatype and
// new functions over the datatype, without recompiling existing code, and while
// retaining static type safety (e.g., no casts).
//                                                               (Philip Wadler)

import scala.language.implicitConversions

object ExpressionProblem extends App {

saswata-dutta

/** GADTs in Scala and their limitations */

/** Background: what is an algebraic data type (ADT) ? 
  * ADT: (possibly) recursive datatype with sums and products
  * In scala - a trait with case classes (case class is product, subtyping is sum) 
  */

/** Motivation: untyped embedded DSL doesn't prevent nonsensical expressions */
sealed trait Expr { 
  def apply(other: Expr) = Ap(this, other)

saswata-dutta

# -*- coding: utf-8 -*-

import avro.schema

def get_schema_children(avro_schema):
    children = []
    if isinstance(avro_schema, avro.schema.UnionSchema):
        children = avro_schema.schemas
    
    if isinstance(avro_schema, avro.schema.RecordSchema):

saswata-dutta

// ...
		Request request = new Request.Builder()
			.url(url)
			.tag(TAG)
			.build();

        // Cancel previous call(s) if they are running or queued
        OkHttpUtils.cancelCallWithTag(client, TAG);    
        
        // New call