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ramalhoramalho
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ch01-12: clean up by @eumiro 
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-86
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‎01-data-model/vector2d.doctest

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>>> from vector2d import Vector
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>>> v1 = Vector(2, 4)
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>>> v2 = Vector(2, 1)
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>>> v1 + v2
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Vector(4, 5)
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>>> v = Vector(3, 4)
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>>> abs(v)
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5.0
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>>> v * 3
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Vector(9, 12)
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>>> abs(v * 3)
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15.0

‎01-data-model/vector2d.py

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"""
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from math import hypot
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import math
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class Vector:
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@@ -41,7 +41,7 @@ def __repr__(self):
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return f'Vector({self.x!r}, {self.y!r})'
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def __abs__(self):
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return hypot(self.x, self.y)
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return math.hypot(self.x, self.y)
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def __bool__(self):
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return bool(abs(self))

‎02-array-seq/.gitignore

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‎02-array-seq/README.md

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‎02-array-seq/README.rst

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Sample code for Chapter 2 - "An array of sequences"
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From the book "Fluent Python 2e" by Luciano Ramalho (O'Reilly)
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http://shop.oreilly.com/product/0636920032519.do

‎02-array-seq/bisect_demo.py

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"""
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# BEGIN BISECT_DEMO
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# tag::BISECT_DEMO[]
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import bisect
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import sys
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@@ -62,4 +62,4 @@ def demo(bisect_fn):
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print('haystack ->', ' '.join(f'{n:2}' for n in HAYSTACK))
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demo(bisect_fn)
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# END BISECT_DEMO
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# end::BISECT_DEMO[]

‎02-array-seq/bisect_insort.py

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for i in range(SIZE):
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new_item = random.randrange(SIZE * 2)
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bisect.insort(my_list, new_item)
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print(f'{new_item:2} ->', my_list)
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print(f'{new_item:2d} -> {my_list}')

‎02-array-seq/memoryviews.ipynb

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{
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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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"# memoryviews\n",
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"\n",
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"## References\n",
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"\n",
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"* [PEP-3118](https://www.python.org/dev/peps/pep-3118/) Revising the buffer protocol (2006)\n",
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"* [issue14130](https://bugs.python.org/issue14130) memoryview: add multi-dimensional indexing and slicing (2012)"
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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": 1,
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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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"3.7.1 (default, Dec 14 2018, 13:28:58) \n",
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"[Clang 4.0.1 (tags/RELEASE_401/final)]\n"
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]
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}
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],
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"source": [
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"import sys\n",
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"print(sys.version)"
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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": 2,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"<memory at 0x1045a31c8>"
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]
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},
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"execution_count": 2,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"mv1d = memoryview(bytes(range(35, 50)))\n",
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"mv1d"
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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": 3,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"[35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49]"
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]
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},
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"execution_count": 3,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"list(mv1d)"
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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": 4,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"<memory at 0x10464a120>"
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]
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},
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"execution_count": 4,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"mv2d = mv1d.cast('B', [3, 5])\n",
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"mv2d"
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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": 5,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"(3, 5)"
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]
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},
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"execution_count": 5,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"mv2d.shape"
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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": 6,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"3"
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]
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},
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"execution_count": 6,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"len(mv2d)"
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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": 7,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"[[35, 36, 37, 38, 39], [40, 41, 42, 43, 44], [45, 46, 47, 48, 49]]"
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]
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},
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"execution_count": 7,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"mv2d.tolist()"
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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": 8,
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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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"[35, 36, 37, 38, 39]\n",
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"[40, 41, 42, 43, 44]\n",
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"[45, 46, 47, 48, 49]\n"
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]
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}
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],
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"source": [
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"for row in mv2d.tolist():\n",
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" print(row)"
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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": 9,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"42"
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]
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},
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"execution_count": 9,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"mv2d[1, 2]"
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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": 10,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"42"
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]
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},
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"execution_count": 10,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"mv2d.tolist()[1][2]"
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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": "3.7.1"
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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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}

‎02-array-seq/slice-assign.rst

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‎03-dict-set/index0.py

+1-1
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@@ -15,7 +15,7 @@
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for line_no, line in enumerate(fp, 1):
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for match in WORD_RE.finditer(line):
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word = match.group()
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column_no = match.start()+1
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column_no = match.start() + 1
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location = (line_no, column_no)
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# this is ugly; coded like this to make a point
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occurrences = index.get(word, []) # <1>

‎03-dict-set/index_default.py

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for line_no, line in enumerate(fp, 1):
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for match in WORD_RE.finditer(line):
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word = match.group()
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column_no = match.start() + 1
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column_no = match.start()+1
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location = (line_no, column_no)
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index[word].append(location) # <2>
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‎03-dict-set/transformdict.py

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@@ -56,7 +56,7 @@ def getitem(self, key):
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@property
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def transform_func(self):
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"""This TransformDict's transformation function"""
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"""This is TransformDict's transformation function"""
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return self._transform
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# Minimum set of methods required for MutableMapping

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