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vickumar1981vickumar1981
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Commit initial notebook.
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‎Functional Python.ipynb‎

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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"!pip install pyeffects"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## What is functional programming?\n",
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"\n",
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"> Functional programming ( FP ) is based on a simple premise with far-reaching implications: we construct our programs using only pure functions—in other words, functions that have no side effects. What are side effects? A function has a side effect if it\n",
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"does something other than simply return a result, for example:\n",
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"\n",
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"- Modifying a variable\n",
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"- Modifying a data structure in place\n",
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"- Setting a field on an object\n",
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"- Throwing an exception or halting with an error\n",
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"- Printing to the console or reading user input\n",
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"- Reading from or writing to a file\n",
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"- Drawing on the screen"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## What is referential transparency?\n",
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"\n",
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"> An expression e is referentially transparent if, for all programs p, all occurrences of e in p can be replaced by the result of evaluating e without affecting the meaning of p. A function f is pure if the expression f(x) is referentially transparent for all referentially transparent x.\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"from typing import List\n",
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"\n",
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"def add_numbers(numbers: List[int]) -> int:\n",
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" sum = 0\n",
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" for n in numbers:\n",
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" sum = sum + n\n",
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" return sum\n",
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"\n",
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"add_numbers([1, 5, 6, 8])"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"from typing import List\n",
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"\n",
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"def add_numbers(numbers: List[int]) -> int:\n",
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" # if sum = 0, we should be able to replace sum on the RHS with 0 and get the same result\n",
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" sum = 0\n",
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" for n in numbers:\n",
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" sum = 0 + n\n",
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" return sum\n",
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"\n",
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"add_numbers([1, 5, 6, 8])"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# Exercise: Re-write w/o using state"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Dealing with Emptiness: Option"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"from pyeffects.Option import *\n",
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" \n",
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"class Name:\n",
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" def __init__(self, first_name: str = None, last_name: str = None):\n",
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" self.first_name = first_name\n",
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" self.last_name = last_name\n",
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" \n",
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" def get_last_name(self) -> Option:\n",
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" return Option.of(self.last_name)\n",
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" \n",
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" def get_first_name(self) -> Option:\n",
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" return Option.of(self.first_name)\n",
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" \n",
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"\n",
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"class Parent:\n",
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" def __init__(self, name: Name = None, relationship: str = \"mother\"):\n",
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" self.name = name\n",
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" self.relationship = relationship\n",
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" \n",
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" def get_name(self) -> Option:\n",
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" return Option.of(self.name)\n",
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" \n",
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"class Child:\n",
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" def __init__(self, name: Name = None, mother: Parent = None, father: Parent = None):\n",
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" self.name = name\n",
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" self.mother = mother\n",
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" self.father = father\n",
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" \n",
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" def get_name(self) -> Option:\n",
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" return Option.of(self.name)\n",
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" \n",
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" def get_father(self) -> Option:\n",
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" return Option.of(self.father)\n",
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" \n",
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" def get_mother(self) -> Option:\n",
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" return Option.of(self.mother)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"def get_mothers_first_name(child: Child) -> str:\n",
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" if child and child.mother and child.mother.name:\n",
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" return child.mother.name.first_name\n",
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" else:\n",
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" return None\n",
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" \n",
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"c = Child(\"child 1\", Parent(Name(\"Mom\", \"1\"), \"mother\"), Parent(Name(\"Dad\", \"1\"), \"father\"))\n",
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"\n",
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"get_mothers_first_name(c)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"def get_mothers_first_name2(child: Child) -> str:\n",
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" return child.get_mother()\\\n",
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" .flat_map(Parent.get_name)\\\n",
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" .flat_map(Name.get_first_name)\\\n",
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" .get_or_else(\"No name\")\n",
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" \n",
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"c = Child(\"child 1\", Parent(Name(\"Mom\", \"Mother\"), \"mother\"), Parent(Name(\"Dad\", \"Father\"), \"father\"))\n",
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"c1 = Child(\"child 2\")\n",
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"# get_mothers_first_name2(c)\n",
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"get_mothers_first_name2(c1)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Dealing with Exceptions: Try"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"c1_str = \"\"\"\n",
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"{\n",
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" \"name\": {\n",
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" \"first_name\": \"1st\",\n",
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" \"last_name\": \"Child\"\n",
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" },\n",
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" \"mother\": {\n",
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" \"name\": {\n",
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" \"first_name\": \"Mother\",\n",
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" \"last_name\": \"1\"\n",
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" }\n",
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" }\n",
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"}\n",
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"\"\"\"\n",
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"\n",
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"# c2_str = \"\"\"\n",
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"# {\n",
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"# \"name\": {\n",
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"# \"first_name\": \"1st\",\n",
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"# \"last_name\": \"Child\"\n",
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"# },\n",
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"# \"mother\": {\n",
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"# \"name\": {\n",
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"# \"first_name_wrong\": \"Mother\",\n",
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"# \"last_name\": \"1\"\n",
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"# }\n",
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"# }\n",
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"# }\n",
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"# \"\"\""
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"import json\n",
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"\n",
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"def load_name(name_dict: dict) -> Name:\n",
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" try:\n",
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" n = Name(**name_dict)\n",
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" return n\n",
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" except TypeError as te:\n",
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" raise TypeError(\"Couldn't deserialize Name: \" + str(te))\n",
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"\n",
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"def load_parent_obj(parent_dict: dict, relationship: str) -> Parent:\n",
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" n = None\n",
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" if 'name' in parent_dict:\n",
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" n = load_name(parent_dict['name'])\n",
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" return Parent(name = n, relationship = relationship)\n",
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" \n",
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"def load_child_obj(json_str: str) -> Child:\n",
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" attributes = json.loads(json_str)\n",
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" n, m, f = (None, None, None)\n",
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" if 'name' in attributes:\n",
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" n = load_name(attributes['name'])\n",
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" if 'mother' in attributes:\n",
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" m = load_parent_obj(attributes['mother'], 'mother')\n",
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" if 'father' in attributes:\n",
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" f = load_parent_obj(attributes['father'], 'father')\n",
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" return Child(n, m, f)\n",
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"\n",
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"c1 = load_child_obj(c1_str)\n",
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"c1.mother.name.first_name\n",
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"\n",
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"# c2 = load_child_obj(c2_str)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"import json\n",
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"\n",
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"from pyeffects.Try import *\n",
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"\n",
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"def load_name(name_dict: dict) -> Try:\n",
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" return Try.of(lambda: Name(**name_dict['name']))\n",
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"\n",
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"def load_parent_obj(parent_dict: dict, relationship: str) -> Parent:\n",
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" return load_name(parent_dict)\\\n",
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" .map(lambda n: Parent(name = n, relationship = relationship))\\\n",
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" .get_or_else(Parent(relationship = relationship))\n",
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" \n",
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"def load_child_obj(json_str: str) -> Child:\n",
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" attributes = json.loads(json_str)\n",
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" n = load_name(attributes).get_or_else(None)\n",
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" m = Try.of(lambda: load_parent_obj(attributes['mother'], 'mother')).get_or_else(None)\n",
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" f = Try.of(lambda: load_parent_obj(attriutes['father'], 'father')).get_or_else(None)\n",
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" return Child(n, m, f)\n",
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"\n",
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"c1 = load_child_obj(c1_str)\n",
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"c1.mother.name.first_name\n",
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"\n",
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"c2 = load_child_obj(c2_str)\n",
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"print(c2.mother.name)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.6.11"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 4
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}

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