365 lines
7.4 KiB
Plaintext
365 lines
7.4 KiB
Plaintext
{
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"cells": [
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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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"# Python Lambda Functions\n",
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"Anonymous, single-use, or throw-away functions. \n",
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"**lambda arguments : expression** \n",
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"Here are some single-argument lambdas:"
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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": 59,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"12\n"
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]
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}
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],
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"source": [
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"add5 = lambda x: x + 5\n",
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"print(add5(7))"
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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": 58,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"64\n"
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]
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}
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],
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"source": [
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"square = lambda x: x * x\n",
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"print(square(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": 67,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"4\n",
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"3\n"
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]
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}
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],
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"source": [
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"get_tens = lambda p: int(p/10)%10\n",
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"print(get_tens(749))\n",
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"print(get_tens(836.21))"
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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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"**Lambdas as an argument in other functions** \n",
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"One of the most popular uses for lambda functions is as an argument inside sort, or filter functions. \n",
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"### Sorting a List of Tuples using Lambda"
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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": 80,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"[('carrots', 1.1), ('peaches', 2.45), ('eggs', 5.25), ('honey', 9.7)]\n"
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]
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}
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],
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"source": [
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"list1 = [('eggs', 5.25), ('honey', 9.70), ('carrots', 1.10), ('peaches', 2.45)]\n",
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"list1.sort(key = lambda x: x[1])\n",
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"print(list1)"
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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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"### Sorting a List of Dictionaries using Lambda"
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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": 63,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"[{'make': 'Tesla', 'model': 'X', 'year': 1999},\n",
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" {'make': 'Mercedes', 'model': 'C350E', 'year': 2008},\n",
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" {'make': 'Ford', 'model': 'Focus', 'year': 2013}]\n"
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]
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}
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],
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"source": [
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"import pprint as pp\n",
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"list1 = [{'make':'Ford', 'model':'Focus', 'year':2013}, {'make':'Tesla', 'model':'X', 'year':1999}, {'make':'Mercedes', 'model':'C350E', 'year':2008}]\n",
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"list2 = sorted(list1, key = lambda x: x['year'])\n",
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"pp.pprint(list2)"
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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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"### Filtering a List of Integers using Lambda"
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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": 64,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"[2, 4, 6]\n"
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]
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}
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],
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"source": [
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"list1 = [1, 2, 3, 4, 5, 6]\n",
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"list2 = list(filter(lambda x: x%2 == 0, list1))\n",
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"print(list2)"
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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": 49,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"[1, 3, 5]\n"
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]
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}
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],
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"source": [
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"odds = lambda x: x%2 == 1\n",
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"list1 = [1, 2, 3, 4, 5, 6]\n",
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"list2 = list(filter(odds, list1))\n",
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"print(list2)"
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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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"### Lambda Function on a List using Map\n",
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"Python's map function applies the lambda to every element in the list."
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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": 74,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"[1, 4, 9, 16, 25, 36]\n"
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]
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}
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],
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"source": [
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"list1 = [1, 2, 3, 4, 5, 6]\n",
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"list2 = list(map(lambda x: x ** 2, list1))\n",
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"print(list2)"
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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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"### Lambda Conditionals\n",
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"**lambda args: a if boolean_expression else b** "
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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": 70,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"True\n"
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]
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}
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],
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"source": [
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"starts_with_J = lambda x: True if x.startswith('J') else False\n",
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"print(starts_with_J('Joey'))"
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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": 81,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"and\n"
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]
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}
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],
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"source": [
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"wordb4 = lambda s, w: s.split()[s.split().index(w)-1] if w in s else None\n",
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"sentence = 'Four score and seven years ago'\n",
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"print(wordb4(sentence, 'seven'))"
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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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"### Lambdas on DataTime Objects\n",
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"You sometimes want to get just the year, month, date or time for comparision. \n",
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"This would typically be most useful as a parameter in sort or filter functions."
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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": 82,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"2019-03-07 19:36:58.442863\n",
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"2019\n"
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]
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}
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],
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"source": [
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"import datetime\n",
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"\n",
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"now = datetime.datetime.now()\n",
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"print(now)\n",
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"year = lambda x: x.year\n",
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"print(year(now))"
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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": 79,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"4096\n",
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"125\n"
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]
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}
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],
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"source": [
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"def do_something(f, val):\n",
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" return f(val)\n",
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"\n",
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"func = lambda x: x**3\n",
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"print(func(16))\n",
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"print(do_something(func, 5))"
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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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"### Extreme Lambdas\n",
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"This is probably a stretch -- you shouldn't be trying to do this much with Lambdas. \n",
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"Some things are better done in a regular function. But this shows what's possible with Lambdas."
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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": 66,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"True\n",
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"True\n",
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"False\n",
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"False\n",
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"True\n",
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"-1\n",
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"-21.67 <class 'float'>\n"
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]
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}
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],
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"source": [
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"isnum = lambda q: q.replace('.','',1).isdigit()\n",
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"print(isnum('25983'))\n",
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"print(isnum('3.1415'))\n",
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"print(isnum('T57'))\n",
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"print(isnum('-16'))\n",
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"\n",
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"is_num = lambda r: isnum(r[1:]) if r[0]=='-' else isnum(r)\n",
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"print(is_num('-16.4'))\n",
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"\n",
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"tonum = lambda s: float(s) if is_num(s) else -1\n",
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"print(tonum('30y'))\n",
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"print(tonum('-21.67'), type(tonum('-21.67')))"
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]
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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": "3.7.0"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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