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main
..
experiment
| Author | SHA1 | Date | |
|---|---|---|---|
 Hykilpikonna
|
4262c86d26 |
@@ -103,13 +103,9 @@ class GameTree:
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The indentation level is specified by the <depth> parameter.
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"""
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if self.is_white_move:
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turn_desc = "White's move"
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else:
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turn_desc = "Black's move"
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move_desc = f'{self.move} -> {turn_desc}\n'
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s = ' ' * depth + move_desc
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if self._subtrees == []:
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move_desc = f'{self.move}-{self.white_win_probability}\n'
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s = '| ' * depth + move_desc
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if not self._subtrees:
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return s
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else:
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for subtree in self._subtrees:
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@@ -220,14 +216,6 @@ class GameTree:
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if __name__ == '__main__':
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import python_ta.contracts
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python_ta.contracts.check_all_contracts()
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import doctest
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doctest.testmod()
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import python_ta
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python_ta.check_all(config={
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'max-line-length': 100,
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'disable': ['E1136'],
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})
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g = GameTree()
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g.insert_move_sequence(['a1b1', 'a2b1'], 1.0)
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print(g)
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@@ -181,4 +181,4 @@ if __name__ == '__main__':
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})
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# Sample call to part1_runner (you can change this, just keep it in the main block!)
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part1_runner('data/white_wins.csv', 50, True)
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part1_runner('data/white_wins.csv', 50, False)
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@@ -1,118 +0,0 @@
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\documentclass[11pt]{article}
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\usepackage{amsmath}
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\usepackage[utf8]{inputenc}
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\usepackage[margin=0.75in]{geometry}
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\title{CSC111 Assignment 3: Graphs, Recommender Systems, and Clustering}
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\author{Azalea Gui \& Peter Lin}
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\date{\today}
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\newcommand{\N}{\mathbb{N}}
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\newcommand{\Z}{\mathbb{Z}}
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\newcommand{\R}{\mathbb{R}}
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\newcommand{\cO}{\mathcal{O}}
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\newcommand{\floor}[1]{\left\lfloor #1 \right\rfloor}
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\newcommand{\code}[1]{\texttt{#1}}
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\begin{document}
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\maketitle
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\section*{Part 1: The book review graph and simple recommendations}
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\begin{enumerate}
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\item[1.]
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Complete this part in the provided \texttt{a3\_part1.py} starter file.
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Do \textbf{not} include your solution in this file.
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\item[2.]
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Running Time Analysis for \texttt{load\_review\_graph}:
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Let $n$ be the number of lines in \texttt{book\_names\_file}, let $m$ be the number of lines in \texttt{reviews\_file}.
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There are two operations that involves iteration in the function, one reads the book names file and creates the \texttt{mp} dictionary, and the other one reads the reviews file and adds vertices to the graph.
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In creating $mp$, the program first opened the file and created a \texttt{csv.reader}, which are both constant-time operations. Then, the dictionary comprehension statement loops through all $n$ lines, running only constant-time operations in each iteration for adding the book id and name pair into the dictionary, resulting in a running time of $\Theta(n)$. Summing up all the operations for creating $mp$ and ignoring constant-time operations, the running time would be $\in \Theta(n)$.
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For adding the vertices, it also opened the file and created a \texttt{csv.reader} in constant time. Then, the loop iterates through all $m$ lines. In each iteration, two vertices and one edge are added, and it also accessed $mp$ to retrieve the book name, which are all constant time operations. Therefore, the total running time would be $\in \Theta(m)$.
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Since there are only constant-time operations outside the two iterating operations, the total running time of the function would be $\in \Theta(m + n)$
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\item[3.]
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Complete this part in the provided \texttt{a3\_part1.py} starter file.
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Do \textbf{not} include your solution in this file.
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\item[4.]
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Complete this part in the provided \texttt{a3\_part1.py} starter file.
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Do \textbf{not} include your solution in this file.
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\end{enumerate}
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\section*{Part 2: Weighted graphs, recommendations, review prediction}
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Complete this part in the provided \texttt{a3\_part2\_recommendations.py} and \texttt{a3\_part2\_predictions.py} starter files.
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Do \textbf{not} include your solution in this file.
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\newpage
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\section*{Part 3: Finding book clusters}
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\begin{enumerate}
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\item[1.]
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Complete this part in the provided \texttt{a3\_part3.py} starter file.
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Do \textbf{not} include your solution in this file.
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\item[2.]
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Complete this part in the provided \texttt{a3\_part3.py} starter file.
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Do \textbf{not} include your solution in this file.
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\item[3.]
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\begin{enumerate}
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\item[(a)]
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Running Time Analysis for \texttt{cross\_cluster\_weight}:
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Let $m_1$ be the size of \texttt{cluster1}, and let $m_2$ be the size of \texttt{cluster2}.
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There is one nested loop in the function. The inner loop iterates $m_2$ times through all values in \texttt{cluster2}, and the outer loop iterates $m_1$ times through all values in \texttt{cluster1}. Inside the inner loop, there is only one function call \texttt{get\_weight}, which is constant-time because it only involves constant-time operations like dictionary accessing and variable assignment. After the function call, the returned value is added to \texttt{sw}, which is one constant-time operation. Let $c$ be a constant representing the number of constant time operations inside the inner loop. The nested loop will run $m_1 * m_2 * c$ operations in total, which is $\in \Theta(m_1 * m_2)$
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Since there are only constant-time operations such as \texttt{len(set)}, variable assignment, and multiplication or division outside the nested loop, the running time of the function will be $\in \Theta(m_1 * m_2)$
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\item[(b)]
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Running Time Analysis for the inner loop in \texttt{find\_clusters\_random}:
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Let $n$ be the number of vertices of \texttt{graph}.
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There is one nested loop in the function.
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For iteration $i$ of the outer loop, the inner loop iterates through all books in the \texttt{clusters} array, which has $n - i$ entires since each iteration of the outer loop removes an entry at the end. Inside the inner loop, the \texttt{if}, \texttt{is not}, comparisons, and variable assignment operations are all constant-time. For iteration $j$ of the inner loop, the \texttt{cross\_cluster\_weight} function call inside the inner loop has a running time of $\Theta(m_1 * m_j)$ as previously analyzed, where $m_1$ is the size of cluster $c_1$, and $m_j$ is the size of cluster $c_j$ (or $c_2$ for iteration $j$). Therefore, the running time of the function will be:
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\begin{align}
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RT_{\text{inner\_loop}} &= \sum_j^{n-i} m_1 * m_j \\
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&= m_1 * \sum_j^{n-i} m_j
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\end{align}
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Since the if statement inside the inner loop ensures $m_1 \neq m_j$, and since we know that $\sum_c |c| = n$, the previously stated $\sum_j^{n-i} m_j$ will be equal to $n - |c_1| = n - m_1$. Therefore, the running time of the function is $m_1 * (n - m_1)$
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Since every cluster is initialized to have one element, we know that $m_1 > 0$, and $n - m_1 < n$. Then, since $m_1$ is also $< n$, the running time $m_1 * (n - m_1)$ is bounded by $\cO(n^2)$.
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\item[(c)]
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Running Time Analysis for \texttt{find\_clusters\_random}:
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Let $n$ be the number of vertices of graph, and let $k$ be the value of \texttt{num\_clusters}.
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In the worst case scenario: Since the outer loop iterates over a range from $0$ to $n - k$, it iterates $n - k$ times. For each iteration, the inner loop have a running time of $\cO(n^2)$ as previously analyzed. Besides from the inner loop, other statements inside the outer loop includes constant-time operations print, f-string creation, \texttt{random.choice}, and varaible assignment. After that, all elements in the set $c_1$ are added to \texttt{best\_c2}, which has a worst-case running time of $\cO(n)$ because $|c_1| <= n$. Also, $c_1$ is removed from the list \texttt{clusters}, which also has a worst-case running time of $\cO(n)$ because \texttt{len(clusters)} $<= n$. Combining all of these operations, the running time of one iteration of the outer loop will be $\in \cO(n^2)$, and the runninng time of $n - k$ iterations will be $\in \cO(n^2 \cdot (n - k))$.
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Outside the outer loop, there is only a return statement (constant-time) and a list comprehension that initializes the \texttt{clusters} array, which goes through $n$ iterations, executing a constant-time operation of creating a set for each iteration.
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Therefore, the running time of the entire function would be $\in \cO(n^2 \cdot (n - k))$.
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\item[(d)]
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\emph{Not to be handed in.}
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\end{enumerate}
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\end{enumerate}
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\end{document}
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@@ -1,329 +0,0 @@
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"""CSC111 Winter 2022 Assignment 3: Graphs, Recommender Systems, and Clustering (Part 1)
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Instructions (READ THIS FIRST!)
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===============================
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This Python module contains the modified graph and vertex classes you'll be using as the basis
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for this assignment, as well as additional functions for you to complete in this part.
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Copyright and Usage Information
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===============================
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This file is provided solely for the personal and private use of students
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taking CSC111 at the University of Toronto St. George campus. All forms of
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distribution of this code, whether as given or with any changes, are
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expressly prohibited. For more information on copyright for CSC111 materials,
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please consult our Course Syllabus.
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This file is Copyright (c) 2022 Mario Badr, David Liu, and Isaac Waller.
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"""
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from __future__ import annotations
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import csv
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from typing import Any, Literal
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# Make sure you've installed the necessary Python libraries (see assignment handout
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# "Installing new libraries" section)
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import networkx as nx # Used for visualizing graphs (by convention, referred to as "nx")
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class _Vertex:
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"""A vertex in a book review graph, used to represent a user or a book.
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Each vertex item is either a user id or book title. Both are represented as strings,
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even though we've kept the type annotation as Any to be consistent with lecture.
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Instance Attributes:
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- item: The data stored in this vertex, representing a user or book.
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- kind: The type of this vertex: 'user' or 'book'.
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- neighbours: The vertices that are adjacent to this vertex.
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Representation Invariants:
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- self not in self.neighbours
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- all(self in u.neighbours for u in self.neighbours)
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- self.kind in {'user', 'book'}
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"""
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item: Any
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kind: str
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neighbours: set[_Vertex]
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def __init__(self, item: Any, kind: str) -> None:
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"""Initialize a new vertex with the given item and kind.
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This vertex is initialized with no neighbours.
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Preconditions:
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- kind in {'user', 'book'}
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"""
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self.item = item
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self.kind = kind
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self.neighbours = set()
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def degree(self) -> int:
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"""Return the degree of this vertex."""
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return len(self.neighbours)
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############################################################################
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# Part 1, Q3
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############################################################################
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def similarity_score(self, other: _Vertex) -> float:
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"""Return the similarity score between this vertex and other.
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See Assignment handout for definition of similarity score.
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"""
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if self.degree() == 0 or other.degree() == 0:
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return 0.0
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intersection = len(self.neighbours.intersection(other.neighbours))
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union = len(self.neighbours) + len(other.neighbours) - intersection # inclusion-exclusion
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return intersection / union
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class Graph:
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"""A graph used to represent a book review network.
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"""
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# Private Instance Attributes:
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# - _vertices:
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# A collection of the vertices contained in this graph.
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# Maps item to _Vertex object.
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_vertices: dict[Any, _Vertex]
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def __init__(self) -> None:
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"""Initialize an empty graph (no vertices or edges)."""
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self._vertices = {}
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def add_vertex(self, item: Any, kind: str) -> None:
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"""Add a vertex with the given item and kind to this graph.
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The new vertex is not adjacent to any other vertices.
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Do nothing if the given item is already in this graph.
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Preconditions:
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- kind in {'user', 'book'}
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"""
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if item not in self._vertices:
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self._vertices[item] = _Vertex(item, kind)
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def add_edge(self, item1: Any, item2: Any) -> None:
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"""Add an edge between the two vertices with the given items in this graph.
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Raise a ValueError if item1 or item2 do not appear as vertices in this graph.
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Preconditions:
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- item1 != item2
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"""
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if item1 in self._vertices and item2 in self._vertices:
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v1 = self._vertices[item1]
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v2 = self._vertices[item2]
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v1.neighbours.add(v2)
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v2.neighbours.add(v1)
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else:
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raise ValueError
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def adjacent(self, item1: Any, item2: Any) -> bool:
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"""Return whether item1 and item2 are adjacent vertices in this graph.
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Return False if item1 or item2 do not appear as vertices in this graph.
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"""
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if item1 in self._vertices and item2 in self._vertices:
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v1 = self._vertices[item1]
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return any(v2.item == item2 for v2 in v1.neighbours)
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else:
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return False
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def get_neighbours(self, item: Any) -> set:
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"""Return a set of the neighbours of the given item.
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Note that the *items* are returned, not the _Vertex objects themselves.
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Raise a ValueError if item does not appear as a vertex in this graph.
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"""
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if item in self._vertices:
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v = self._vertices[item]
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return {neighbour.item for neighbour in v.neighbours}
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else:
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raise ValueError
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def get_all_vertices(self, kind: Literal['', 'user', 'book'] = '') -> set:
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"""Return a set of all vertex items in this graph.
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If kind != '', only return the items of the given vertex kind.
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Preconditions:
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- kind in {'', 'user', 'book'}
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"""
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if kind != '':
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return {v.item for v in self._vertices.values() if v.kind == kind}
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else:
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return set(self._vertices.keys())
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def to_networkx(self, max_vertices: int = 5000) -> nx.Graph:
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"""Convert this graph into a networkx Graph.
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max_vertices specifies the maximum number of vertices that can appear in the graph.
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(This is necessary to limit the visualization output for large graphs.)
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Note that this method is provided for you, and you shouldn't change it.
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"""
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graph_nx = nx.Graph()
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for v in self._vertices.values():
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graph_nx.add_node(v.item, kind=v.kind)
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for u in v.neighbours:
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if graph_nx.number_of_nodes() < max_vertices:
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graph_nx.add_node(u.item, kind=u.kind)
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if u.item in graph_nx.nodes:
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graph_nx.add_edge(v.item, u.item)
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if graph_nx.number_of_nodes() >= max_vertices:
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break
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return graph_nx
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############################################################################
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# Part 1, Q3
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############################################################################
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def get_similarity_score(self, item1: Any, item2: Any) -> float:
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"""Return the similarity score between the two given items in this graph.
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Raise a ValueError if item1 or item2 do not appear as vertices in this graph.
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>>> g = Graph()
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>>> for i in range(0, 6):
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... g.add_vertex(str(i), kind='user')
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>>> g.add_edge('0', '2')
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>>> g.add_edge('0', '3')
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>>> g.add_edge('0', '4')
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>>> g.add_edge('1', '3')
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>>> g.add_edge('1', '4')
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>>> g.add_edge('1', '5')
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>>> g.get_similarity_score('0', '1')
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0.5
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"""
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if item1 not in self._vertices or item2 not in self._vertices:
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raise ValueError
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return self._vertices[item1].similarity_score(self._vertices[item2])
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############################################################################
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# Part 1, Q4
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############################################################################
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def recommend_books(self, book: str, limit: int) -> list[str]:
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"""Return a list of up to <limit> recommended books based on similarity to the given book.
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The return value is a list of the titles of recommended books, sorted in
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*descending order* of similarity score. Ties are broken in descending order
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of book title. That is, if v1 and v2 have the same similarity score, then
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v1 comes before v2 if and only if v1.item > v2.item.
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The returned list should NOT contain:
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- the input book itself
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- any book with a similarity score of 0 to the input book
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- any duplicates
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- any vertices that represents a user (instead of a book)
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Up to <limit> books are returned, starting with the book with the highest similarity score,
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then the second-highest similarity score, etc. Fewer than <limit> books are returned if
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and only if there aren't enough books that meet the above criteria.
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Preconditions:
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- book in self._vertices
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- self._vertices[book].kind == 'book'
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- limit >= 1
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>>> my_graph = load_review_graph('data/reviews_full.csv', 'data/book_names.csv')
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>>> title = "Harry Potter and the Sorcerer's Stone (Book 1)"
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>>> import pprint
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>>> pprint.pprint(my_graph.recommend_books(title, 10))
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['The Casual Vacancy',
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'Harry Potter and the Chamber of Secrets',
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'Harry Potter and the Prisoner of Azkaban',
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'Harry Potter and the Chamber of Secrets, Book 2',
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'Harry Potter and the Deathly Hallows, Book 7',
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'Harry Potter And The Goblet Of Fire',
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'Harry Potter And The Order Of The Phoenix',
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'Harry Potter and the Half-Blood Prince (Book 6)',
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"The Cuckoo's Calling (Cormoran Strike)",
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'Fellowship of the Ring (Lord of the Rings Part 1)']
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"""
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book = self._vertices[book] # vertex is more useful here
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books = set() # all books distance == 2 away from self
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for neighbour in book.neighbours:
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books.update(neighbour.neighbours)
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books.remove(book)
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arr = [(book.similarity_score(x), x.item) for x in books]
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arr = sorted(arr, reverse=True)[:limit]
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return [x[1] for x in arr]
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################################################################################
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# Part 1, Q1
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################################################################################
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def load_review_graph(reviews_file: str, book_names_file: str) -> Graph:
|
||||
"""Return a book review graph corresponding to the given datasets.
|
||||
|
||||
The book review graph stores one vertex for each user and book in the datasets.
|
||||
Each vertex stores as its item either a user ID or book TITLE (the latter is why
|
||||
you need the book_names_file). Use the "kind" _Vertex attribute to differentiate
|
||||
between the two vertex types.
|
||||
|
||||
Edges represent a review between a user and a book. In this graph, each edge
|
||||
only represents the existence of a review---IGNORE THE REVIEW SCORE in the
|
||||
datasets, as we don't have a way to represent these scores (yet).
|
||||
|
||||
Preconditions:
|
||||
- reviews_file is the path to a CSV file corresponding to the book review data
|
||||
format described on the assignment handout
|
||||
- book_names_file is the path to a CSV file corresponding to the book data
|
||||
format described on the assignment handout
|
||||
|
||||
>>> g = load_review_graph('data/reviews_small.csv', 'data/book_names.csv')
|
||||
>>> len(g.get_all_vertices(kind='book'))
|
||||
4
|
||||
>>> len(g.get_all_vertices(kind='user'))
|
||||
5
|
||||
>>> user1_reviews = g.get_neighbours('user1')
|
||||
>>> len(user1_reviews)
|
||||
3
|
||||
>>> "Harry Potter and the Sorcerer's Stone (Book 1)" in user1_reviews
|
||||
True
|
||||
"""
|
||||
g = Graph()
|
||||
|
||||
# mp[book_id] = book_name
|
||||
mp: dict[str, str]
|
||||
|
||||
# Read book names file and create id-name mapping
|
||||
with open(book_names_file, 'r', newline='', encoding='UTF-8') as f:
|
||||
reader = csv.reader(f)
|
||||
mp = dict(reader)
|
||||
|
||||
# Read user review file and link user and reviews in the graph
|
||||
with open(reviews_file, 'r', newline='', encoding='UTF-8') as f:
|
||||
reader = csv.reader(f)
|
||||
for user_id, book_id, rating in reader:
|
||||
g.add_vertex(user_id, 'user')
|
||||
g.add_vertex(mp[book_id], 'book')
|
||||
g.add_edge(user_id, mp[book_id])
|
||||
|
||||
return g
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
# You can uncomment the following lines for code checking/debugging purposes.
|
||||
# However, we recommend commenting out these lines when working with the large
|
||||
# datasets, as checking representation invariants and preconditions greatly
|
||||
# increases the running time of the functions/methods.
|
||||
# import python_ta.contracts
|
||||
# python_ta.contracts.check_all_contracts()
|
||||
|
||||
import doctest
|
||||
doctest.testmod()
|
||||
|
||||
import python_ta
|
||||
python_ta.check_all(config={
|
||||
'max-line-length': 100,
|
||||
'disable': ['E1136'],
|
||||
'extra-imports': ['csv', 'networkx'],
|
||||
'allowed-io': ['load_review_graph'],
|
||||
'max-nested-blocks': 4
|
||||
})
|
||||
@@ -1,241 +0,0 @@
|
||||
"""CSC111 Winter 2022 Assignment 3: Graphs, Recommender Systems, and Clustering (Part 2)
|
||||
|
||||
Instructions (READ THIS FIRST!)
|
||||
===============================
|
||||
|
||||
This Python module contains classes responsible for making predictions of book review scores.
|
||||
We've provided the abstract class and some example subclasses, and you'll complete one new
|
||||
subclass and a new function to evaluate the different classes.
|
||||
|
||||
Copyright and Usage Information
|
||||
===============================
|
||||
|
||||
This file is provided solely for the personal and private use of students
|
||||
taking CSC111 at the University of Toronto St. George campus. All forms of
|
||||
distribution of this code, whether as given or with any changes, are
|
||||
expressly prohibited. For more information on copyright for CSC111 materials,
|
||||
please consult our Course Syllabus.
|
||||
|
||||
This file is Copyright (c) 2022 Mario Badr, David Liu, and Isaac Waller.
|
||||
"""
|
||||
from __future__ import annotations
|
||||
import csv
|
||||
from typing import Union
|
||||
|
||||
import a3_part2_recommendations
|
||||
|
||||
|
||||
class ReviewScorePredictor:
|
||||
"""A graph-based entity that predicts scores for book reviews.
|
||||
|
||||
This is an abstract class, and should be subclasses to implement different review
|
||||
prediction algorithms.
|
||||
|
||||
Instance Attributes:
|
||||
- graph: The book review graph that this entity uses to make predictions.
|
||||
"""
|
||||
graph: a3_part2_recommendations.WeightedGraph
|
||||
|
||||
def __init__(self, graph: a3_part2_recommendations.WeightedGraph) -> None:
|
||||
"""Initialize a new ReviewScorePredictor."""
|
||||
self.graph = graph
|
||||
|
||||
def predict_review_score(self, user: str, book: str) -> int:
|
||||
"""Predict the score (1-5) that the given user would give the given book.
|
||||
|
||||
If there is already an edge between the given user and book in the graph,
|
||||
return that score. Otherwise, return a predicted score.
|
||||
|
||||
Preconditions:
|
||||
- user in self.graph._vertices
|
||||
- book in self.graph._vertices
|
||||
"""
|
||||
raise NotImplementedError
|
||||
|
||||
|
||||
class FiveStarPredictor(ReviewScorePredictor):
|
||||
"""A book review predictor that always predicts a five-star review,
|
||||
ignoring the actual book and user.
|
||||
"""
|
||||
def predict_review_score(self, user: str, book: str) -> int:
|
||||
"""Predict the score that the given user would give the given book.
|
||||
|
||||
If there is already an edge between the given user and book in the graph,
|
||||
return that score. Otherwise, return 5 as the predicted score.
|
||||
|
||||
Preconditions:
|
||||
- user in self.graph._vertices
|
||||
- book in self.graph._vertices
|
||||
"""
|
||||
if self.graph.adjacent(user, book):
|
||||
return self.graph.get_weight(user, book)
|
||||
else:
|
||||
return 5
|
||||
|
||||
|
||||
class BookAverageScorePredictor(ReviewScorePredictor):
|
||||
"""A book review predictor that always predicts based on the book's average score,
|
||||
ignoring any user preferences.
|
||||
"""
|
||||
def predict_review_score(self, user: str, book: str) -> int:
|
||||
"""Predict the score that the given user would give the given book.
|
||||
|
||||
If there is already an edge between the given user and book in the graph,
|
||||
return that score. Otherwise, return the book's average review score in
|
||||
the graph, rounded to the nearest integer (using the built-in `round` function).
|
||||
|
||||
Preconditions:
|
||||
- user in self.graph._vertices
|
||||
- book in self.graph._vertices
|
||||
- the given book has at least one review
|
||||
"""
|
||||
if self.graph.adjacent(user, book):
|
||||
return self.graph.get_weight(user, book)
|
||||
else:
|
||||
return round(self.graph.average_weight(book))
|
||||
|
||||
|
||||
################################################################################
|
||||
# Part 2, Q3
|
||||
################################################################################
|
||||
class SimilarUserPredictor(ReviewScorePredictor):
|
||||
"""A book review predictor that makes a prediction based on how similar users rated the book.
|
||||
|
||||
Representation Invariants:
|
||||
- self._score_type in {'unweighted', 'strict'}
|
||||
"""
|
||||
# Private Instance Attributes:
|
||||
# - _score_type: the type of similarity score to use when computing similarity score
|
||||
_score_type: str
|
||||
|
||||
def __init__(self, graph: a3_part2_recommendations.WeightedGraph,
|
||||
score_type: str = 'unweighted') -> None:
|
||||
"""Initialize a new SimilarUserPredictor.
|
||||
|
||||
You may want to review Section 10.4 of the Course Notes for a reminder on
|
||||
how to properly override a superclass initializer. To avoid a python_ta.contracts error,
|
||||
initialize self._score_type at the TOP of this method body.
|
||||
"""
|
||||
self._score_type = score_type
|
||||
ReviewScorePredictor.__init__(self, graph)
|
||||
|
||||
def predict_review_score(self, user: str, book: str) -> int:
|
||||
"""Predict the score that the given user would give the given book.
|
||||
|
||||
If there is already an edge between the given user and book in the graph,
|
||||
return that score. Otherwise, return the book's WEIGHTED review score among
|
||||
all users who have read the book, where the weight used is the similarity
|
||||
score of the reviewing user with the given user. self._score_type is used
|
||||
to determine which similarity score to use for the weights
|
||||
|
||||
As usual, round this score using the built-in `round` function.
|
||||
|
||||
For example, suppose there are three users A, B, C who have read the book,
|
||||
and one, D, who has not. We want to use the review scores of A, B, and C to predict
|
||||
the rating for D. The three user ratings and weighted similarity score with D
|
||||
are shown in this table:
|
||||
|
||||
| User | Review score | Weighted similarity score with D |
|
||||
| ---- | ------------ | -------------------------------- |
|
||||
| A | 3 | 0.4 |
|
||||
| B | 5 | 0.1 |
|
||||
| C | 2 | 0.3 |
|
||||
|
||||
Then the predicted review for D equals:
|
||||
|
||||
(3 * 0.4 + 5 * 0.1 + 2 * 0.3) / (0.4 + 0.1 + 0.3) = 2.875
|
||||
|
||||
and so this function would return 3.
|
||||
|
||||
If the total similarity score from all of the book's reviewers is 0,
|
||||
then instead return the book's average review score (same as BookAverageScorePredictor).
|
||||
|
||||
Preconditions:
|
||||
- user in self.graph._vertices
|
||||
- book in self.graph._vertices
|
||||
"""
|
||||
if self.graph.adjacent(user, book): # if the user already made a review, use that score
|
||||
return self.graph.get_weight(user, book)
|
||||
users = self.graph.get_neighbours(book)
|
||||
total_weighted = 0
|
||||
total = 0
|
||||
all_zero = True
|
||||
for u in users:
|
||||
weight = self.graph.get_similarity_score(u, book, 'strict')
|
||||
score = self.graph.get_weight(u, book)
|
||||
if weight > 0:
|
||||
all_zero = False
|
||||
total_weighted += score * weight
|
||||
total += score
|
||||
if all_zero:
|
||||
return round(total / len(users))
|
||||
return round(total_weighted / len(users))
|
||||
|
||||
|
||||
################################################################################
|
||||
# Part 2, Q4
|
||||
################################################################################
|
||||
def evaluate_predictor(predictor: ReviewScorePredictor,
|
||||
test_file: str, book_names_file: str) -> dict[str, Union[int, float]]:
|
||||
"""Evaluate the given ReviewScorePredictor on the given test file.
|
||||
|
||||
Read in each row of the given test_file (which contains a book, user, and
|
||||
review score). For each row, use the given predictor to make a prediction of the review
|
||||
score, and compare that prediction against the actual given review score from the file.
|
||||
|
||||
Return a dictionary summarizing the performance of the predictor. This dictionary
|
||||
has the following keys:
|
||||
- 'num_reviews': the total number of predicted review scores (equal to the
|
||||
number of lines in the CSV file)
|
||||
- 'num_correct': the number of predicted review scores that exactly matched the
|
||||
actual review score
|
||||
- 'average_error': the average of the *absolute value difference* between
|
||||
predicted and actual review scores across all reviews in the test file
|
||||
|
||||
Preconditions:
|
||||
- test_file is the path to a CSV file corresponding to the book review data
|
||||
format described on the assignment handout
|
||||
- book_names_file is the path to a CSV file corresponding to the book data
|
||||
- test_file has at least one row
|
||||
- all users and books in test_file are in predictor.graph
|
||||
format described on the assignment handout
|
||||
"""
|
||||
num_reviews = 0
|
||||
num_correct = 0
|
||||
total_error = 0
|
||||
mp: dict[str, str] # maps book ID to book name
|
||||
with open(book_names_file, 'r', newline='', encoding='UTF-8') as f:
|
||||
reader = csv.reader(f)
|
||||
mp = dict(reader)
|
||||
with open(test_file, 'r', newline='', encoding='UTF-8') as f:
|
||||
reader = csv.reader(f)
|
||||
for book, user, score in reader:
|
||||
book = mp[book]
|
||||
num_reviews += 1
|
||||
actual = predictor.predict_review_score(user, book)
|
||||
if actual == score:
|
||||
num_correct += 1
|
||||
total_error += abs(score - actual)
|
||||
return {
|
||||
'num_reviews': num_reviews,
|
||||
'num_correct': num_correct,
|
||||
'average_error': total_error / num_reviews,
|
||||
}
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
# You can uncomment the following lines for code checking/debugging purposes.
|
||||
# However, we recommend commenting out these lines when working with the large
|
||||
# datasets, as checking representation invariants and preconditions greatly
|
||||
# increases the running time of the functions/methods.
|
||||
# import python_ta.contracts
|
||||
# python_ta.contracts.check_all_contracts()
|
||||
|
||||
import python_ta
|
||||
python_ta.check_all(config={
|
||||
'max-line-length': 1000,
|
||||
'disable': ['E1136'],
|
||||
'extra-imports': ['csv', 'a3_part2_recommendations'],
|
||||
'allowed-io': ['evaluate_predictor'],
|
||||
'max-nested-blocks': 4
|
||||
})
|
||||
@@ -1,298 +0,0 @@
|
||||
"""CSC111 Winter 2022 Assignment 3: Graphs, Recommender Systems, and Clustering (Part 2)
|
||||
|
||||
Instructions (READ THIS FIRST!)
|
||||
===============================
|
||||
|
||||
This Python module contains new classes to represent *weighted graphs and vertices*,
|
||||
which we'll use to represent a book review network with scores of reviews as well.
|
||||
This file is structured very similarly to a3_part1.py.
|
||||
|
||||
Copyright and Usage Information
|
||||
===============================
|
||||
|
||||
This file is provided solely for the personal and private use of students
|
||||
taking CSC111 at the University of Toronto St. George campus. All forms of
|
||||
distribution of this code, whether as given or with any changes, are
|
||||
expressly prohibited. For more information on copyright for CSC111 materials,
|
||||
please consult our Course Syllabus.
|
||||
|
||||
This file is Copyright (c) 2022 Mario Badr, David Liu, and Isaac Waller.
|
||||
"""
|
||||
from __future__ import annotations
|
||||
import csv
|
||||
from typing import Any, Union, Literal
|
||||
|
||||
from a3_part1 import Graph
|
||||
|
||||
|
||||
class _WeightedVertex:
|
||||
"""A vertex in a weighted book review graph, used to represent a user or a book.
|
||||
|
||||
Same documentation as _Vertex from Part 1, except now neighbours is a dictionary mapping
|
||||
a neighbour vertex to the weight of the edge to from self to that neighbour.
|
||||
Note that in Part 2, the weights will be integers between 1 and 5, but in Part 3 the
|
||||
weights will be floats.
|
||||
|
||||
Instance Attributes:
|
||||
- item: The data stored in this vertex, representing a user or book.
|
||||
- kind: The type of this vertex: 'user' or 'book'.
|
||||
- neighbours: The vertices that are adjacent to this vertex, and their corresponding
|
||||
edge weights.
|
||||
|
||||
Representation Invariants:
|
||||
- self not in self.neighbours
|
||||
- all(self in u.neighbours for u in self.neighbours)
|
||||
- self.kind in {'user', 'book'}
|
||||
"""
|
||||
item: Any
|
||||
kind: str
|
||||
neighbours: dict[_WeightedVertex, Union[int, float]]
|
||||
|
||||
def __init__(self, item: Any, kind: str) -> None:
|
||||
"""Initialize a new vertex with the given item and kind.
|
||||
|
||||
This vertex is initialized with no neighbours.
|
||||
|
||||
Preconditions:
|
||||
- kind in {'user', 'book'}
|
||||
"""
|
||||
self.item = item
|
||||
self.kind = kind
|
||||
self.neighbours = {}
|
||||
|
||||
def degree(self) -> int:
|
||||
"""Return the degree of this vertex."""
|
||||
return len(self.neighbours)
|
||||
|
||||
############################################################################
|
||||
# Part 2, Q2
|
||||
############################################################################
|
||||
def similarity_score_unweighted(self, other: _WeightedVertex) -> float:
|
||||
"""Return the unweighted similarity score between this vertex and other.
|
||||
|
||||
The unweighted similarity score is calculated in the same way as the
|
||||
similarity score for _Vertex (from Part 1). That is, just look at edges,
|
||||
and ignore the weights.
|
||||
"""
|
||||
if self.degree() == 0 or other.degree() == 0:
|
||||
return 0.0
|
||||
a = set(self.neighbours.keys())
|
||||
b = set(other.neighbours.keys())
|
||||
intersection = len(a.intersection(b))
|
||||
union = len(a) + len(b) - intersection # inclusion-exclusion
|
||||
return intersection / union
|
||||
|
||||
def similarity_score_strict(self, other: _WeightedVertex) -> float:
|
||||
"""Return the strict weighted similarity score between this vertex and other.
|
||||
|
||||
See Assignment handout for details.
|
||||
"""
|
||||
if self.degree() == 0 or other.degree() == 0:
|
||||
return 0.0
|
||||
a = set(self.neighbours.keys())
|
||||
b = set(other.neighbours.keys())
|
||||
generator = (x for x in a if x in b and x.neighbours[self] == x.neighbours[other])
|
||||
intersection = sum(1 for _ in generator)
|
||||
union = len(a.union(b))
|
||||
return intersection / union
|
||||
|
||||
|
||||
class WeightedGraph(Graph):
|
||||
"""A weighted graph used to represent a book review network that keeps track of review scores.
|
||||
|
||||
Note that this is a subclass of the Graph class from Part 1, and so inherits any methods
|
||||
from that class that aren't overridden here.
|
||||
"""
|
||||
# Private Instance Attributes:
|
||||
# - _vertices:
|
||||
# A collection of the vertices contained in this graph.
|
||||
# Maps item to _WeightedVertex object.
|
||||
_vertices: dict[Any, _WeightedVertex]
|
||||
|
||||
def __init__(self) -> None:
|
||||
"""Initialize an empty graph (no vertices or edges)."""
|
||||
self._vertices = {}
|
||||
|
||||
# This call isn't necessary, except to satisfy PythonTA.
|
||||
Graph.__init__(self)
|
||||
|
||||
def add_vertex(self, item: Any, kind: str) -> None:
|
||||
"""Add a vertex with the given item and kind to this graph.
|
||||
|
||||
The new vertex is not adjacent to any other vertices.
|
||||
Do nothing if the given item is already in this graph.
|
||||
|
||||
Preconditions:
|
||||
- kind in {'user', 'book'}
|
||||
"""
|
||||
if item not in self._vertices:
|
||||
self._vertices[item] = _WeightedVertex(item, kind)
|
||||
|
||||
def add_edge(self, item1: Any, item2: Any, weight: Union[int, float] = 1) -> None:
|
||||
"""Add an edge between the two vertices with the given items in this graph,
|
||||
with the given weight.
|
||||
|
||||
Raise a ValueError if item1 or item2 do not appear as vertices in this graph.
|
||||
|
||||
Preconditions:
|
||||
- item1 != item2
|
||||
"""
|
||||
if item1 in self._vertices and item2 in self._vertices:
|
||||
v1 = self._vertices[item1]
|
||||
v2 = self._vertices[item2]
|
||||
|
||||
# Add the new edge
|
||||
v1.neighbours[v2] = weight
|
||||
v2.neighbours[v1] = weight
|
||||
else:
|
||||
# We didn't find an existing vertex for both items.
|
||||
raise ValueError
|
||||
|
||||
def get_weight(self, item1: Any, item2: Any) -> Union[int, float]:
|
||||
"""Return the weight of the edge between the given items.
|
||||
|
||||
Return 0 if item1 and item2 are not adjacent.
|
||||
|
||||
Preconditions:
|
||||
- item1 and item2 are vertices in this graph
|
||||
"""
|
||||
v1 = self._vertices[item1]
|
||||
v2 = self._vertices[item2]
|
||||
return v1.neighbours.get(v2, 0)
|
||||
|
||||
def average_weight(self, item: Any) -> float:
|
||||
"""Return the average weight of the edges adjacent to the vertex corresponding to item.
|
||||
|
||||
Raise ValueError if item does not corresponding to a vertex in the graph.
|
||||
"""
|
||||
if item in self._vertices:
|
||||
v = self._vertices[item]
|
||||
return sum(v.neighbours.values()) / len(v.neighbours)
|
||||
else:
|
||||
raise ValueError
|
||||
|
||||
############################################################################
|
||||
# Part 2, Q2
|
||||
############################################################################
|
||||
def get_similarity_score(self, item1: Any, item2: Any,
|
||||
score_type: Literal['unweighted', 'strict'] = 'unweighted') -> float:
|
||||
"""Return the similarity score between the two given items in this graph.
|
||||
|
||||
score_type is one of 'unweighted' or 'strict', corresponding to the
|
||||
different ways of calculating weighted graph vertex similarity, as described
|
||||
on the assignment handout.
|
||||
|
||||
Raise a ValueError if item1 or item2 do not appear as vertices in this graph.
|
||||
|
||||
Preconditions:
|
||||
- score_type in {'unweighted', 'strict'}
|
||||
"""
|
||||
if item1 not in self._vertices or item2 not in self._vertices:
|
||||
raise ValueError
|
||||
if score_type == 'unweighted':
|
||||
return self._vertices[item1].similarity_score_unweighted(self._vertices[item2])
|
||||
return self._vertices[item1].similarity_score_strict(self._vertices[item2])
|
||||
|
||||
def recommend_books(self, book: str, limit: int,
|
||||
score_type: Literal['unweighted', 'strict'] = 'unweighted') -> list[str]:
|
||||
"""Return a list of up to <limit> recommended books based on similarity to the given book.
|
||||
|
||||
score_type is one of 'unweighted' or 'strict', corresponding to the
|
||||
different ways of calculating weighted graph vertex similarity, as described
|
||||
on the assignment handout. The corresponding similarity score formula is used
|
||||
in this method (whenever the phrase "similarity score" appears below).
|
||||
|
||||
The return value is a list of the titles of recommended books, sorted in
|
||||
*descending order* of similarity score. Ties are broken in descending order
|
||||
of book title. That is, if v1 and v2 have the same similarity score, then
|
||||
v1 comes before v2 if and only if v1.item > v2.item.
|
||||
|
||||
The returned list should NOT contain:
|
||||
- the input book itself
|
||||
- any book with a similarity score of 0 to the input book
|
||||
- any duplicates
|
||||
- any vertices that represents a user (instead of a book)
|
||||
|
||||
Up to <limit> books are returned, starting with the book with the highest similarity score,
|
||||
then the second-highest similarity score, etc. Fewer than <limit> books are returned if
|
||||
and only if there aren't enough books that meet the above criteria.
|
||||
|
||||
Preconditions:
|
||||
- book in self._vertices
|
||||
- self._vertices[book].kind == 'book'
|
||||
- limit >= 1
|
||||
- score_type in {'unweighted', 'strict'}
|
||||
"""
|
||||
book = self._vertices[book] # vertex is more useful here
|
||||
books = set() # all books distance == 2 away from self
|
||||
for neighbour in book.neighbours:
|
||||
books.update(neighbour.neighbours.keys())
|
||||
books.remove(book)
|
||||
arr = []
|
||||
for x in books:
|
||||
if score_type == 'strict':
|
||||
score = book.similarity_score_strict(x)
|
||||
if score == 0:
|
||||
continue
|
||||
else:
|
||||
score = book.similarity_score_unweighted(x)
|
||||
arr.append((score, x.item))
|
||||
arr = sorted(arr, reverse=True)[:limit]
|
||||
return [y[1] for y in arr]
|
||||
|
||||
|
||||
################################################################################
|
||||
# Part 2, Q1
|
||||
################################################################################
|
||||
def load_weighted_review_graph(reviews_file: str, book_names_file: str) -> WeightedGraph:
|
||||
"""Return a book review WEIGHTED graph corresponding to the given datasets.
|
||||
|
||||
This should be very similar to the corresponding function Part 1, except now
|
||||
the book review scores are used as edge weights.
|
||||
|
||||
Preconditions:
|
||||
- reviews_file is the path to a CSV file corresponding to the book review data
|
||||
format described on the assignment handout
|
||||
- book_names_file is the path to a CSV file corresponding to the book data
|
||||
format described on the assignment handout
|
||||
"""
|
||||
g = WeightedGraph()
|
||||
|
||||
# mp[book_id] = book_name
|
||||
mp: dict[str, str]
|
||||
|
||||
# Read book names file and create id-name mapping
|
||||
with open(book_names_file, 'r', newline='', encoding='UTF-8') as f:
|
||||
reader = csv.reader(f)
|
||||
mp = dict(reader)
|
||||
|
||||
# Read user review file and link user and reviews in the graph
|
||||
with open(reviews_file, 'r', newline='', encoding='UTF-8') as f:
|
||||
reader = csv.reader(f)
|
||||
for user_id, book_id, rating in reader:
|
||||
g.add_vertex(user_id, 'user')
|
||||
g.add_vertex(mp[book_id], 'book')
|
||||
g.add_edge(user_id, mp[book_id], int(rating))
|
||||
|
||||
return g
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
# You can uncomment the following lines for code checking/debugging purposes.
|
||||
# However, we recommend commenting out these lines when working with the large
|
||||
# datasets, as checking representation invariants and preconditions greatly
|
||||
# increases the running time of the functions/methods.
|
||||
# import python_ta.contracts
|
||||
# python_ta.contracts.check_all_contracts()
|
||||
|
||||
import doctest
|
||||
doctest.testmod()
|
||||
|
||||
import python_ta
|
||||
python_ta.check_all(config={
|
||||
'max-line-length': 1000,
|
||||
'disable': ['E1136', 'W0221'],
|
||||
'extra-imports': ['csv', 'a3_part1'],
|
||||
'allowed-io': ['load_weighted_review_graph'],
|
||||
'max-nested-blocks': 4
|
||||
})
|
||||
@@ -1,207 +0,0 @@
|
||||
"""CSC111 Winter 2022 Assignment 3: Graphs, Recommender Systems, and Clustering (Part 3)
|
||||
|
||||
Instructions (READ THIS FIRST!)
|
||||
===============================
|
||||
|
||||
This Python module contains the functions you'll write for determining *clusters* of vertices
|
||||
in a graph.
|
||||
|
||||
Copyright and Usage Information
|
||||
===============================
|
||||
|
||||
This file is provided solely for the personal and private use of students
|
||||
taking CSC111 at the University of Toronto St. George campus. All forms of
|
||||
distribution of this code, whether as given or with any changes, are
|
||||
expressly prohibited. For more information on copyright for CSC111 materials,
|
||||
please consult our Course Syllabus.
|
||||
|
||||
This file is Copyright (c) 2022 Mario Badr, David Liu, and Isaac Waller.
|
||||
"""
|
||||
import random
|
||||
from typing import Literal
|
||||
|
||||
from a3_part2_recommendations import WeightedGraph
|
||||
|
||||
|
||||
################################################################################
|
||||
# Part 3, Q1
|
||||
################################################################################
|
||||
def create_book_graph(review_graph: WeightedGraph,
|
||||
threshold: float = 0.05,
|
||||
score_type: Literal['unweighted', 'strict'] = 'unweighted') -> WeightedGraph:
|
||||
"""Return a book graph based on the given review_graph.
|
||||
|
||||
The score_type parameter plays the same role as in WeightedGraph.get_similarity_score.
|
||||
|
||||
The returned book graph has the following properties:
|
||||
1. Its vertex set is exactly the set of book vertices in review_graph
|
||||
(items are book titles).
|
||||
2. For every two distinct books b1 and b2, let s(b1, b2) be their similarity score,
|
||||
where score_type specifies which similarity score to use.
|
||||
|
||||
- If s(b1, b2) > threshold, there is an edge between b1 and b2 in the book graph
|
||||
with weight equal to s(b1, b2). Unlike Part 2, these weights will be floats,
|
||||
not ints!
|
||||
- Otherwise, there is no edge between b1 and b2.
|
||||
|
||||
Preconditions:
|
||||
- score_type in {'unweighted', 'strict'}
|
||||
"""
|
||||
# Add all books as vertices
|
||||
book_graph = WeightedGraph()
|
||||
book_names: set[str] = review_graph.get_all_vertices('book')
|
||||
for b in book_names:
|
||||
book_graph.add_vertex(b, 'book')
|
||||
|
||||
# Add all edges
|
||||
for b1 in book_names:
|
||||
for b2 in book_names:
|
||||
if b1 == b2:
|
||||
continue
|
||||
|
||||
# Calculate similarity score
|
||||
score = review_graph.get_similarity_score(b1, b2, score_type)
|
||||
if score <= threshold:
|
||||
continue
|
||||
|
||||
# Add edge
|
||||
book_graph.add_edge(b1, b2, score)
|
||||
|
||||
# Done
|
||||
return book_graph
|
||||
|
||||
|
||||
################################################################################
|
||||
# Part 3, Q2
|
||||
################################################################################
|
||||
def cross_cluster_weight(book_graph: WeightedGraph, cluster1: set, cluster2: set) -> float:
|
||||
"""Return the cross-cluster weight between cluster1 and cluster2.
|
||||
|
||||
See assignment handout for the definition of cross-cluster weight.
|
||||
|
||||
Preconditions:
|
||||
- cluster1 != set() and cluster2 != set()
|
||||
- cluster1.isdisjoint(cluster2)
|
||||
- Every item in cluster1 and cluster2 is a vertex in book_graph
|
||||
|
||||
>>> bg = WeightedGraph()
|
||||
>>> for b in range(4): \
|
||||
bg.add_vertex(f'B{b}', 'book')
|
||||
>>> bg.add_edge('B0', 'B1', .5)
|
||||
>>> bg.add_edge('B0', 'B2', .4)
|
||||
>>> bg.add_edge('B1', 'B2', .3)
|
||||
>>> bg.get_weight('B0', 'B1')
|
||||
0.5
|
||||
>>> cross_cluster_weight(bg, {'B0', 'B1'}, {'B2', 'B3'}) == (.4 + .3) / 4
|
||||
True
|
||||
"""
|
||||
# sw = sum(book_graph.get_weight(v1, v2) for v1 in cluster1 for v2 in cluster2)
|
||||
sw = 0
|
||||
for v1 in cluster1:
|
||||
for v2 in cluster2:
|
||||
sw += book_graph.get_weight(v1, v2)
|
||||
|
||||
return sw / (len(cluster1) * len(cluster2))
|
||||
|
||||
|
||||
################################################################################
|
||||
# Part 3, Q3 (don't modify this code)
|
||||
################################################################################
|
||||
def find_clusters_random(graph: WeightedGraph, num_clusters: int) -> list[set]:
|
||||
"""Return a list of <num_clusters> vertex clusters for the given graph.
|
||||
|
||||
At each iteration, this algorithm first chooses a random cluster, and then chooses
|
||||
the cluster that has the highest cross-cluster weight to the randomly-chose cluster
|
||||
to merge.
|
||||
|
||||
Preconditions:
|
||||
- num_clusters >= 1
|
||||
"""
|
||||
# Each book starts in its own cluster
|
||||
clusters = [{book} for book in graph.get_all_vertices()]
|
||||
|
||||
for _ in range(0, len(clusters) - num_clusters):
|
||||
print(f'{len(clusters)} clusters')
|
||||
|
||||
c1 = random.choice(clusters)
|
||||
# Pick the best cluster to merge c1 into.
|
||||
best = -1
|
||||
best_c2 = None
|
||||
|
||||
for c2 in clusters:
|
||||
if c1 is not c2:
|
||||
score = cross_cluster_weight(graph, c1, c2)
|
||||
if score > best:
|
||||
best = score
|
||||
best_c2 = c2
|
||||
|
||||
best_c2.update(c1)
|
||||
clusters.remove(c1)
|
||||
|
||||
return clusters
|
||||
|
||||
|
||||
def find_clusters_greedy(graph: WeightedGraph, num_clusters: int) -> list[set]:
|
||||
"""Return a list of <num_clusters> vertex clusters for the given graph.
|
||||
|
||||
At each iteration, this algorithm chooses the pair of clusters with the highest
|
||||
cross-cluster weight to merge.
|
||||
|
||||
Preconditions:
|
||||
- num_clusters >= 1
|
||||
"""
|
||||
# Each book starts in its own cluster
|
||||
clusters = [{book} for book in graph.get_all_vertices()]
|
||||
|
||||
for _ in range(0, len(clusters) - num_clusters):
|
||||
print(f'{len(clusters)} clusters')
|
||||
|
||||
# Merge the two communities with the most links
|
||||
best = -1
|
||||
best_c1, best_c2 = None, None
|
||||
|
||||
for i1 in range(0, len(clusters)):
|
||||
for i2 in range(i1 + 1, len(clusters)):
|
||||
c1, c2 = clusters[i1], clusters[i2]
|
||||
score = cross_cluster_weight(graph, c1, c2)
|
||||
if score > best:
|
||||
best, best_c1, best_c2 = score, c1, c2
|
||||
|
||||
best_c2.update(best_c1)
|
||||
clusters.remove(best_c1)
|
||||
|
||||
return clusters
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
# You can uncomment the following lines for code checking/debugging purposes.
|
||||
# However, we recommend commenting out these lines when working with the large
|
||||
# datasets, as checking representation invariants and preconditions greatly
|
||||
# increases the running time of the functions/methods.
|
||||
# import python_ta.contracts
|
||||
# python_ta.contracts.check_all_contracts()
|
||||
|
||||
import doctest
|
||||
doctest.testmod()
|
||||
|
||||
import python_ta
|
||||
python_ta.check_all(config={
|
||||
'max-line-length': 1000,
|
||||
'disable': ['E1136'],
|
||||
'extra-imports': ['random', 'a3_part2_recommendations'],
|
||||
'allowed-io': ['find_clusters_greedy', 'find_clusters_random'],
|
||||
'max-nested-blocks': 4
|
||||
})
|
||||
|
||||
# Q1 Test
|
||||
# review_graph = load_weighted_review_graph('data/reviews_full.csv', 'data/book_names.csv')
|
||||
# book_graph = create_book_graph(review_graph, 0.03)
|
||||
# from a3_visualization import visualize_graph
|
||||
# visualize_graph(book_graph)
|
||||
|
||||
# Q3 Test
|
||||
# review_graph = load_weighted_review_graph('data/reviews_full.csv', 'data/book_names.csv')
|
||||
# book_graph = create_book_graph(review_graph, threshold=0.01, score_type='strict')
|
||||
# clusters = find_clusters_random(book_graph, 15)
|
||||
# from a3_visualization import visualize_graph_clusters
|
||||
# visualize_graph_clusters(book_graph, clusters)
|
||||
@@ -1,175 +0,0 @@
|
||||
"""CSC111 Winter 2022 Assignment 3: Graphs, Recommender Systems, and Clustering (Visualization)
|
||||
|
||||
Module Description
|
||||
==================
|
||||
|
||||
This module contains some Python functions that you can use to visualize the graphs
|
||||
you're working with on this assignment. You should not modify anything in this file.
|
||||
It will not be submitted for grading.
|
||||
|
||||
Disclaimer: we didn't have time to make this file fully PythonTA-compliant!
|
||||
|
||||
Copyright and Usage Information
|
||||
===============================
|
||||
|
||||
This file is provided solely for the personal and private use of students
|
||||
taking CSC111 at the University of Toronto St. George campus. All forms of
|
||||
distribution of this code, whether as given or with any changes, are
|
||||
expressly prohibited. For more information on copyright for CSC111 materials,
|
||||
please consult our Course Syllabus.
|
||||
|
||||
This file is Copyright (c) 2022 Mario Badr, David Liu, and Isaac Waller.
|
||||
"""
|
||||
import networkx as nx
|
||||
from plotly.graph_objs import Scatter, Figure
|
||||
|
||||
import a3_part1
|
||||
|
||||
|
||||
# Colours to use when visualizing different clusters.
|
||||
COLOUR_SCHEME = [
|
||||
'#2E91E5', '#E15F99', '#1CA71C', '#FB0D0D', '#DA16FF', '#222A2A', '#B68100',
|
||||
'#750D86', '#EB663B', '#511CFB', '#00A08B', '#FB00D1', '#FC0080', '#B2828D',
|
||||
'#6C7C32', '#778AAE', '#862A16', '#A777F1', '#620042', '#1616A7', '#DA60CA',
|
||||
'#6C4516', '#0D2A63', '#AF0038'
|
||||
]
|
||||
|
||||
LINE_COLOUR = 'rgb(210,210,210)'
|
||||
VERTEX_BORDER_COLOUR = 'rgb(50, 50, 50)'
|
||||
BOOK_COLOUR = 'rgb(89, 205, 105)'
|
||||
USER_COLOUR = 'rgb(105, 89, 205)'
|
||||
|
||||
|
||||
def visualize_graph(graph: a3_part1.Graph,
|
||||
layout: str = 'spring_layout',
|
||||
max_vertices: int = 5000,
|
||||
output_file: str = '') -> None:
|
||||
"""Use plotly and networkx to visualize the given graph.
|
||||
|
||||
Optional arguments:
|
||||
- layout: which graph layout algorithm to use
|
||||
- max_vertices: the maximum number of vertices that can appear in the graph
|
||||
- output_file: a filename to save the plotly image to (rather than displaying
|
||||
in your web browser)
|
||||
"""
|
||||
graph_nx = graph.to_networkx(max_vertices)
|
||||
|
||||
pos = getattr(nx, layout)(graph_nx)
|
||||
|
||||
x_values = [pos[k][0] for k in graph_nx.nodes]
|
||||
y_values = [pos[k][1] for k in graph_nx.nodes]
|
||||
labels = list(graph_nx.nodes)
|
||||
kinds = [graph_nx.nodes[k]['kind'] for k in graph_nx.nodes]
|
||||
|
||||
colours = [BOOK_COLOUR if kind == 'book' else USER_COLOUR for kind in kinds]
|
||||
|
||||
x_edges = []
|
||||
y_edges = []
|
||||
for edge in graph_nx.edges:
|
||||
x_edges += [pos[edge[0]][0], pos[edge[1]][0], None]
|
||||
y_edges += [pos[edge[0]][1], pos[edge[1]][1], None]
|
||||
|
||||
trace3 = Scatter(x=x_edges,
|
||||
y=y_edges,
|
||||
mode='lines',
|
||||
name='edges',
|
||||
line=dict(color=LINE_COLOUR, width=1),
|
||||
hoverinfo='none',
|
||||
)
|
||||
trace4 = Scatter(x=x_values,
|
||||
y=y_values,
|
||||
mode='markers',
|
||||
name='nodes',
|
||||
marker=dict(symbol='circle-dot',
|
||||
size=5,
|
||||
color=colours,
|
||||
line=dict(color=VERTEX_BORDER_COLOUR, width=0.5)
|
||||
),
|
||||
text=labels,
|
||||
hovertemplate='%{text}',
|
||||
hoverlabel={'namelength': 0}
|
||||
)
|
||||
|
||||
data1 = [trace3, trace4]
|
||||
fig = Figure(data=data1)
|
||||
fig.update_layout({'showlegend': False})
|
||||
fig.update_xaxes(showgrid=False, zeroline=False, visible=False)
|
||||
fig.update_yaxes(showgrid=False, zeroline=False, visible=False)
|
||||
|
||||
if output_file == '':
|
||||
fig.show()
|
||||
else:
|
||||
fig.write_image(output_file)
|
||||
|
||||
|
||||
def visualize_graph_clusters(graph: a3_part1.Graph, clusters: list[set],
|
||||
layout: str = 'spring_layout',
|
||||
max_vertices: int = 5000,
|
||||
output_file: str = '') -> None:
|
||||
"""Visualize the given graph, using different colours to illustrate the different clusters.
|
||||
|
||||
Hides all edges that go from one cluster to another. (This helps the graph layout algorithm
|
||||
positions vertices in the same cluster close together.)
|
||||
|
||||
Same optional arguments as visualize_graph (see that function for details).
|
||||
"""
|
||||
graph_nx = graph.to_networkx(max_vertices)
|
||||
all_edges = list(graph_nx.edges)
|
||||
for edge in all_edges:
|
||||
# Check if edge is within the same cluster
|
||||
if any((edge[0] in cluster) != (edge[1] in cluster) for cluster in clusters):
|
||||
graph_nx.remove_edge(edge[0], edge[1])
|
||||
|
||||
pos = getattr(nx, layout)(graph_nx)
|
||||
|
||||
x_values = [pos[k][0] for k in graph_nx.nodes]
|
||||
y_values = [pos[k][1] for k in graph_nx.nodes]
|
||||
labels = list(graph_nx.nodes)
|
||||
|
||||
colors = []
|
||||
for k in graph_nx.nodes:
|
||||
for i, c in enumerate(clusters):
|
||||
if k in c:
|
||||
colors.append(COLOUR_SCHEME[i % len(COLOUR_SCHEME)])
|
||||
break
|
||||
else:
|
||||
colors.append(BOOK_COLOUR)
|
||||
|
||||
x_edges = []
|
||||
y_edges = []
|
||||
for edge in graph_nx.edges:
|
||||
x_edges += [pos[edge[0]][0], pos[edge[1]][0], None]
|
||||
y_edges += [pos[edge[0]][1], pos[edge[1]][1], None]
|
||||
|
||||
trace3 = Scatter(x=x_edges,
|
||||
y=y_edges,
|
||||
mode='lines',
|
||||
name='edges',
|
||||
line=dict(color=LINE_COLOUR, width=1),
|
||||
hoverinfo='none'
|
||||
)
|
||||
trace4 = Scatter(x=x_values,
|
||||
y=y_values,
|
||||
mode='markers',
|
||||
name='nodes',
|
||||
marker=dict(symbol='circle-dot',
|
||||
size=5,
|
||||
color=colors,
|
||||
line=dict(color=VERTEX_BORDER_COLOUR, width=0.5)
|
||||
),
|
||||
text=labels,
|
||||
hovertemplate='%{text}',
|
||||
hoverlabel={'namelength': 0}
|
||||
)
|
||||
|
||||
data1 = [trace3, trace4]
|
||||
fig = Figure(data=data1)
|
||||
fig.update_layout({'showlegend': False})
|
||||
fig.update_xaxes(showgrid=False, zeroline=False, visible=False)
|
||||
fig.update_yaxes(showgrid=False, zeroline=False, visible=False)
|
||||
fig.show()
|
||||
|
||||
if output_file == '':
|
||||
fig.show()
|
||||
else:
|
||||
fig.write_image(output_file)
|
||||
@@ -1,985 +0,0 @@
|
||||
0027676463,The Night Before Christmas
|
||||
0060557818,Neverwhere: A Novel
|
||||
0425284689,Before We Were Yours: A Novel
|
||||
0804192898,Make Me: A Jack Reacher Novel
|
||||
0061992259,The One and Only Ivan
|
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0141022043,Blink - The Power Of Thinking Without Thinking
|
||||
0312352557,Still Life: A Chief Inspector Gamache Novel
|
||||
0743554450,A Thousand Splendid Suns: A Novel
|
||||
0986842222,The Color of Heaven
|
||||
1471118630,Never Too Far (Tempting Too Far Novel)
|
||||
1476753180,Ugly Love: A Novel
|
||||
1944083014,Judgment Cometh: and That Right Soon (Joe Dillard Series) (Volume 8)
|
||||
0002171856,The Sas Survival Handbook
|
||||
0147520762,"The Girl in the Spider's Web: A Lisbeth Salander novel, continuing Stieg Larsson's Millennium Series"
|
||||
0312577230,The Great Alone: A Novel
|
||||
1468139339,Wait For Me
|
||||
0151008116,Life of Pi
|
||||
0316175676,The Snow Child: A Novel
|
||||
0615953948,Mind's Eye
|
||||
1477826580,The American Lady (The Glassblower Trilogy)
|
||||
1503935310,Everything We Keep: A Novel
|
||||
0143121707,The Invention of Wings
|
||||
0375433392,"The Hard Way (Jack Reacher, No. 10"
|
||||
0544025830,Coming Clean: A Memoir
|
||||
1476707634,Drinking and Tweeting: And Other Brandi Blunders
|
||||
1477819967,Mrs. Saint and the Defectives: A Novel
|
||||
1477822585,The Last Town (Wayward Pines)
|
||||
1503953319,The Queen's Poisoner (Kingfountain)
|
||||
6077547328,"Maze Runner. Correr o Morir / Maze Runner, Run or die (Spanish Edition)"
|
||||
0006545793,Brave New World
|
||||
0983398038,The Rockstar's Daughter: (Treadwell Academy Series #1)
|
||||
0099557266,Playing for Pizza
|
||||
B003156C4E,Fellowship of the Ring (Lord of the Rings Part 1)
|
||||
0028180054,A Wrinkle in Time
|
||||
0099580470,Shift (Wool Trilogy)
|
||||
0143106708,Twelve Years a Slave (Penguin Classics)
|
||||
B00714PZMQ,Quiet: The Power of Introverts in a World That Can't Stop Talking
|
||||
0316228532,The Casual Vacancy
|
||||
074356619X,"The Secret (Unabridged, 4-CD Set)"
|
||||
1455576506,The Coincidence of Callie & Kayden
|
||||
1463514581,Twenty-Eight and a Half Wishes (A Rose Gardner Mystery)
|
||||
1477808663,The Game Changer: A Novel
|
||||
1491598778,The Good Neighbor
|
||||
1503939308,Exhume (Dr. Schwartzman)
|
||||
1503935183,The Last Woman Standing: A Novel
|
||||
0061997161,The Pioneer Woman: Black Heels to Tractor Wheels--A Love Story
|
||||
0147525071,Extreme Prey (A Prey Novel)
|
||||
0739453939,90 Minutes in Heaven
|
||||
1477822593,Dead Certain: A Novel (Broden Legal)
|
||||
1534640150,Earth Alone: Earthrise Book 1
|
||||
0140285628,The Man in the High Castle (Essential Penguin)
|
||||
0425246043,The Perfect Hope (The Inn Boonsboro Trilogy)
|
||||
0307967115,My Name Is Lucy Barton: A Novel
|
||||
0375969020,Wonder
|
||||
0763644765,Potty (Leslie Patricelli board books)
|
||||
0765326264,A Dog's Purpose: A Novel for Humans
|
||||
1410493415,The Life We Bury (Wheeler Large Print Book Series)
|
||||
1476755590,Real (The REAL series)
|
||||
0375434542,Origin: A Novel (Robert Langdon)
|
||||
1478288892,Sentence of Marriage: Promises to Keep (Volume 1)
|
||||
1536690872,All the Little Children
|
||||
0345539788,Red Rising
|
||||
0399179135,Lilac Girls
|
||||
0141328290,Thirteen Reasons Why
|
||||
0060539836,Kill the Competition
|
||||
B00EJQY4BM,The First Phone Call from Heaven: A Novel
|
||||
0385346859,The Dinner
|
||||
1520396074,Inheritance: A Psychological Mystery and Suspense Thriller
|
||||
B0002P0FFS,Lies My Teacher Told Me: Everything Your American History Textbook Got Wrong
|
||||
0028180062,The Call of the Wild with related readings
|
||||
0060794410,Good to Great CD: Why Some Companies Make the Leap.And Others Don't
|
||||
1542722829,Silent Child
|
||||
B00CYZC5S4,Anne Of Green Gables
|
||||
0060391448,Wicked: The Life and Times of the Wicked Witch of the West
|
||||
0615351913,Once We Were Brothers
|
||||
1433688670,"Fervent: A Woman's Battle Plan to Serious, Specific and Strategic Prayer"
|
||||
1472229959,The Letter
|
||||
B017WJ5PR4,"Harry Potter and the Deathly Hallows, Book 7"
|
||||
0062409883,Go Set a Watchman: A Novel
|
||||
0140434186,Wuthering Heights (Penguin Classics)
|
||||
0142428280,Fall of Giants (The Century Trilogy)
|
||||
0192831992,Ben-Hur (Oxford World's Classics)
|
||||
1475070306,UnEnchanted: An Unfortunate Fairy Tale (Unfortunate Fairy Tale;[bk. 1])
|
||||
0143170104,The Girl Who Played with Fire (Millennium Series)
|
||||
0451414128,Missing You
|
||||
0800757181,Daughter of Joy (Brides of Culdee Creek)
|
||||
0143142364,World Without End (Kingsbridge)
|
||||
1581344368,"The Holy Bible: English Standard Version, Reference Edition"
|
||||
0312364083,Firefly Lane
|
||||
1410447863,"An Invisible Thread: The True Story of an 11-Year-Old Panhandler, a Busy Sales Executive, and an Unlikely Meeting with Destiny (Wheeler Large Print Book Series)"
|
||||
0091900212,Think and Grow Rich
|
||||
0230755062,The Language of Flowers
|
||||
0692213740,In Between (A Katie Parker Production) (Volume 1)
|
||||
0975599518,Natural Cures "They" Don't Want You To Know About
|
||||
0310515025,"Seeking Allah, Finding Jesus: A Devout Muslim Encounters Christianity"
|
||||
0316346624,The Tipping Point: How Little Things Can Make a Big Difference
|
||||
1250034469,Be Careful What You Wish For: A Novel (The Clifton Chronicles)
|
||||
1250158060,Fire and Fury: Inside the Trump White House
|
||||
140883233X,Throne of Glass
|
||||
1501132938,The Woman in Cabin 10
|
||||
0062378082,The Nazi Officer's Wife: How One Jewish Woman Survived the Holocaust
|
||||
0099619105,Trump - The Art Of The Deal
|
||||
0230749259,Innocent (Will Robie series)
|
||||
0345486455,"Healthy Sleep Habits, Happy Child: A Step-by-Step Program for a Good Night's Sleep, 3rd Edition"
|
||||
1477809783,Terms of Enlistment (Frontlines)
|
||||
1484009290,Noble Beginnings: A Jack Noble Novel
|
||||
1501188291,Gwendy's Button Box: A Novella
|
||||
0132268310,The Lost Symbol (Dan Brown)
|
||||
1410478750,The Wright Brothers (Thorndike Press Large Print Popular and Narrative Nonfiction Series)
|
||||
151738799X,The Air He Breathes (Elements)
|
||||
0140283331,Lord of the Flies
|
||||
B015QPEV9E,The Call of the Wild eBook
|
||||
1477823832,The Paper Magician
|
||||
1503953866,The Secret Healer
|
||||
0061441848,Eat Right for Your Type
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B000X1MX7E,The Pillars of the Earth
|
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0340822775,Cloud Atlas
|
||||
1455134767,The Amateur: Barack Obama in the White House
|
||||
1463717091,Abducted
|
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1501110365,It Ends with Us: A Novel
|
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0062065246,The Round House
|
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0141339578,Prodigy
|
||||
0991677196,CyberStorm
|
||||
1477829865,Bum Rap (Jake Lassiter Legal Thrillers)
|
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0007350783,Emma (Collins Classics)
|
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0140390197,The Scarlet Letter: A Romance (The Penguin American Library)
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0345528670,The Aviator's Wife: A Novel
|
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0988348268,Jane's Melody
|
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1455530093,13 Hours: The Inside Account of What Really Happened In Benghazi
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0312641893,Cinder
|
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0316376469,"The Food Babe Way: Break Free from the Hidden Toxins in Your Food and Lose Weight, Look Years Younger, and Get Healthy in Just 21 Days!"
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0739474979,Water For Elephants
|
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1478230096,"Les Miserables In Plain and Simple English: Includes Study Guide, Historical Context, Biography, and Character Index"
|
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0061928178,Beautiful Ruins: A Novel
|
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0091923530,"The 4-hour Workweek: Escape the 9-5, Live Anywhere and Join the New Rich"
|
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0718077296,"Same Kind of Different As Me Movie Edition: A Modern-Day Slave, an International Art Dealer, and the Unlikely Woman Who Bound Them Together"
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1501228722,Crazy Little Thing (A Bell Harbor Novel)
|
||||
0143109464,Me Before You: A Novel (Movie Tie-In) (Me Before You Trilogy)
|
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0529120887,Jesus Calling: Enjoying Peace in His Presence
|
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B000LP5E8M,The God Delusion
|
||||
069289344X,Dangerous
|
||||
0857207113,A Stolen Life: A Memoir
|
||||
1460995457,The Soulkeepers (The Soulkeepers Series) (Volume 1)
|
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0857208691,Kill Shot (The Mitch Rapp Series)
|
||||
1442369213,Rush Revere and the First Patriots: Time-Travel Adventures With Exceptional Americans (Audio CD)
|
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1477829822,The Prettiest One: A Thriller
|
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0345807294,The Circle
|
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0385336667,"Persuader (Jack Reacher, No. 7)"
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0399157565,The Bone Bed (Scarpetta)
|
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081298840X,When Breath Becomes Air
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141047383X,Revival (Thorndike Press Large Pring Basic)
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1477830812,The Girl from Krakow: A Novel
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1896350542,Squall
|
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0027164403,Dear Zoo (Dear Zoo & Friends)
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0307341577,Dark Places
|
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0310205719,The Purpose Driven Life
|
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0349410828,Apprentice in Death: 43
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0449012751,The Unlikely Pilgrimage of Harold Fry: A Novel
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0451417054,The King: A Novel of the Black Dagger Brotherhood
|
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1943893179,Craving (Steel Brothers Saga Book 1)
|
||||
0525955100,"Home (Myron Bolitar, No. 11)"
|
||||
0615581927,Reason to Breathe: The Breathing Series (Volume 1)
|
||||
125000098X,Best Kept Secret (The Clifton Chronicles)
|
||||
147782314X,One Lavender Ribbon
|
||||
1543644325,Pandemic (Extinction Files)
|
||||
1912106949,NO EXIT a gripping thriller full of heart-stopping twists
|
||||
006226835X,Yes Please
|
||||
0307476073,Wild: From Lost to Found on the Pacific Crest Trail
|
||||
0470560770,Better Homes and Gardens New Cook Book
|
||||
148231780X,Tongue Twisters for Kids
|
||||
0141976144,"Wreck This Journal: To Create is to Destroy, Now With Even More Ways to Wreck!"
|
||||
0316225983,The Late Show
|
||||
1611735270,The Harbinger: The Ancient Mystery That Holds the Secret of America's Future (Thorndike Christian Mystery)
|
||||
0142800422,Alexander Hamilton
|
||||
0307943232,The Racketeer
|
||||
0385349947,"Lean In: Women, Work, and the Will to Lead"
|
||||
1455568872,"Crisis of Character: A White House Secret Service Officer Discloses His Firsthand Experience with Hillary, Bill, and How They Operate"
|
||||
1780674880,Enchanted Forest: An Inky Quest & Coloring Book
|
||||
0062060554,Before I Go to Sleep: A Novel
|
||||
0099134012,Time to Kill Paper If Available
|
||||
1101911921,Our Souls at Night (Vintage Contemporaries)
|
||||
1447259297,The Target
|
||||
1477820280,P.S. from Paris (US edition)
|
||||
0425273865,Captivated by You (Crossfire)
|
||||
0062454943,"The Rainbow Comes and Goes: A Mother and Son On Life, Love, and Loss"
|
||||
0143127500,One Plus One: A Novel
|
||||
0310209749,"Boundaries: When To Say Yes, How to Say No"
|
||||
0316206857,The Cuckoo's Calling (Cormoran Strike)
|
||||
0486789640,Creative Haven Creative Cats Coloring Book (Adult Coloring)
|
||||
0505527847,Trouble in Mudbug
|
||||
0060890681,The Last Anniversary: A Novel
|
||||
0393072231,The Big Short: Inside the Doomsday Machine
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0764218913,"The Essential Tozer Collection: The Pursuit of God, The Purpose of Man, and The Crucified Life"
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||||
1494557223,Archer's Voice
|
||||
1623363586,Thug Kitchen: The Official Cookbook: Eat Like You Give a F*ck (Thug Kitchen Cookbooks)
|
||||
0001048767,Othello: Complete & Unabridged
|
||||
0099576457,"Merry Christmas, Alex Cross: (Alex Cross 19)"
|
||||
0141034262,Three Cups of Tea
|
||||
0307275639,"Tuesdays with Morrie: An Old Man, a Young Man, and Life's Greatest Lesson"
|
||||
0743572203,Liberty and Tyranny: A Conservative Manifesto
|
||||
099047982X,Fluency (Confluence)
|
||||
1410482596,Killing Reagan: The Violent Assault That Changed A Presidenc (Wheeler Publishing Large Print Hardcover)
|
||||
1477809732,The Line (Witching Savannah)
|
||||
1503936864,Blood on the Tracks (Sydney Rose Parnell)
|
||||
1939457319,The 20/20 Diet: Turn Your Weight Loss Vision Into Reality
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||||
0446580856,Radiant Angel (A John Corey Novel)
|
||||
045141411X,Six Years
|
||||
060637387X,You Are A Badass (Turtleback School & Library Binding Edition)
|
||||
1477825975,The Neon Lawyer
|
||||
0060125314,The Odyssey of Homer
|
||||
B00006JO24,The 48 Laws of Power
|
||||
0230748228,Only Time Will Tell
|
||||
0307282961,"Twilight (The Twilight Saga, Book 1)"
|
||||
0385393938,X (A Kinsey Millhone Novel)
|
||||
0606256725,Out Of My Mind (Turtleback School & Library Binding Edition)
|
||||
0988667908,Go Pro: 7 Steps to Becoming a Network Marketing Professional
|
||||
1536617636,D DAY Through German Eyes: The Hidden Story of June 6th 1944
|
||||
0142800376,"The Gunslinger (The Dark Tower, Book 1)"
|
||||
0329258400,Harry Potter and the Prisoner of Azkaban
|
||||
0374374562,Little Humans
|
||||
0811877825,"Goodnight, Goodnight Construction Site"
|
||||
B0016L6KZ6,"City of Ashes: The Mortal Instruments, Book Two"
|
||||
0310081122,"NIV, Thinline Bible, Large Print, Imitation Leather, Brown, Red Letter Edition"
|
||||
0399173358,Full Force and Effect (Jack Ryan)
|
||||
0575081406,"The Name of the Wind (Kingkiller Chronicles, Day 1)"
|
||||
0989768414,Hardwired (The Hacker Series)
|
||||
1490527516,Nora Roberts Land (Dare Valley)
|
||||
1503941892,The Night Bird (Frost Easton)
|
||||
0143108867,After You: A Novel (Me Before You Trilogy)
|
||||
0151010196,Those Who Save Us
|
||||
031623480X,"Grain Brain: The Surprising Truth about Wheat, Carbs, and Sugar--Your Brain's Silent Killers"
|
||||
0718077954,The Wedding Dress
|
||||
080509668X,Killing Patton: The Strange Death of World War II's Most Audacious General (Bill O'Reilly's Killing Series)
|
||||
1492123595,30 Pieces of Silver
|
||||
1503935205,The Body Reader (Detective Jude Fontaine Mysteries)
|
||||
0004244079,Little Women
|
||||
0007444117,Allegiant
|
||||
0062110845,The Golem and the Jinni: A Novel (P.S.)
|
||||
0345542924,Top Secret Twenty-One (Stephanie Plum)
|
||||
0446520594,"Many Lives, Many Masters: The True Story of a Prominent Psychiatrist, His Young Patient, and the Past Life Therapy That Changed Both Their Lives"
|
||||
0553393235,The Happiest Baby on the Block; Fully Revised and Updated Second Edition: The New Way to Calm Crying and Help Your Newborn Baby Sleep Longer
|
||||
0743572750,City of Ashes (The Mortal Instruments)
|
||||
0993862500,Blood and Justice: A Private Investigator Mystery Series (A Jake & Annie Lincoln Thriller) (Volume 1)
|
||||
1629982423,"The Mystery of the Shemitah: The 3,000-Year-Old Mystery That Holds the Secret of America's Future, the World's Future, and Your Future!"
|
||||
0345534530,Empty Mansions: The Mysterious Life of Huguette Clark and the Spending of a Great American Fortune
|
||||
0345539869,Morning Star: Book 3 of the Red Rising Saga (Red Rising Series)
|
||||
1451649320,The Lake House: A Novel
|
||||
1613757808,Four Blood Moons: Something Is About to Change
|
||||
0316069515,The Gods of Guilt (A Lincoln Lawyer Novel)
|
||||
B00COF9TL0,Dad Is Fat
|
||||
0843961449,First to Kill
|
||||
1468161660,Slammed
|
||||
1503936171,Interference
|
||||
0385296479,Daughters
|
||||
030794963X,Duty: Memoirs of a Secretary at War
|
||||
031060530X,The Hiding Place
|
||||
000735083X,The Adventures of Sherlock Holmes (Collins Classics)
|
||||
006195070X,Orphan Train: A Novel
|
||||
0316176494,Life After Life: A Novel
|
||||
1477820450,The Gemini Effect
|
||||
0307886263,Is Everyone Hanging Out Without Me? (And Other Concerns)
|
||||
0316026697,The Host
|
||||
1455584916,And the Good News Is...: Lessons and Advice from the Bright Side
|
||||
1477824944,Hello Love
|
||||
0345533666,Defending Jacob: A Novel
|
||||
0451230825,Injustice For All (Joe Dillard)
|
||||
0615553028,A Hidden Fire: Elemental Mysteries Book 1
|
||||
144238820X,The Survivor (A Mitch Rapp Novel)
|
||||
1475031904,Breakthrough
|
||||
1477829407,The Einstein Prophecy
|
||||
147813223X,Louisiana Longshot: A Miss Fortune Mystery (Volume 1)
|
||||
0385541171,The Rooster Bar
|
||||
0761463275,Angelfall (Penryn & the End of Days)
|
||||
B000FK9M18,Hobbit
|
||||
0062347268,America's First Daughter: A Novel
|
||||
0316211273,Unlucky 13 (Women's Murder Club)
|
||||
0393609391,Astrophysics for People in a Hurry
|
||||
0991379667,Hudson (Fixed Series) (Volume 4)
|
||||
1481882902,Rushed
|
||||
B001HDIE3O,"What to Expect When You're Expecting, Third Edition"
|
||||
0307706591,The Scorch Trials
|
||||
0425259862,Shadow Spell (Cousins O'Dwyer)
|
||||
0230754902,Zero Day (John Puller series)
|
||||
0385353308,Station Eleven
|
||||
0544272994,What If?: Serious Scientific Answers to Absurd Hypothetical Questions
|
||||
060632416X,Joyland (Turtleback School & Library Binding Edition) (Hcc)
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||||
0671315285,7 Habits Of Highly Effective People
|
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0692282343,Quantum Lens
|
||||
1503936805,Tier One (Tier One Thrillers)
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||||
0003302245,Dracula (Collins Drama)
|
||||
0316011770,The Historian
|
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0307273571,A Week in Winter
|
||||
1455536253,The Guilty (Will Robie series)
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||||
0142001740,The Secret Life of Bees
|
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0552778478,The Light Between Oceans: The heartbreaking Richard and Judy bestseller
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0805098542,Killing Jesus (Bill O'Reilly's Killing Series)
|
||||
0842384898,Holy Bible Text Edition NLT (Hardcover)
|
||||
1469208504,Hidden (A Bone Secrets Novel)
|
||||
0399170871,Obsession in Death
|
||||
1477824243,The Naturalist
|
||||
0007350961,Frankenstein (Collins Classics)
|
||||
0007449313,Pride & Prejudice (Collins Classics)
|
||||
0316001821,The Lovely Bones: Deluxe Edition
|
||||
1477848665,Stillhouse Lake
|
||||
1531865313,StrengthsFinder 2.0
|
||||
B017V4IPPO,"Harry Potter and the Chamber of Secrets, Book 2"
|
||||
0024181900,"The Elements of Style, Third Edition"
|
||||
0099521296,The Water's Edge
|
||||
0099911701,Cross Stitch
|
||||
030770663X,"The Death Cure (Maze Runner, Book Three) (The Maze Runner Series)"
|
||||
0312495412,First 100 Words (Bright Baby)
|
||||
0553526936,Special Circumstances
|
||||
1442360941,Walking Disaster
|
||||
1479147109,Lily Lemon Blossom Welcome to Lily's Room
|
||||
0307346609,World War Z: An Oral History of the Zombie War
|
||||
0345543246,Sycamore Row (The Jake Brigance)
|
||||
0399159347,The Husband's Secret
|
||||
0615437850,The Gray and Guilty Sea: A Garrison Gage Mystery
|
||||
0989104400,Falling Into You
|
||||
1503937461,"Sisters One, Two, Three"
|
||||
1503943925,Beach Lawyer
|
||||
0141188936,Atlas Shrugged
|
||||
0307730697,Fearless: The Undaunted Courage and Ultimate Sacrifice of Navy SEAL Team SIX Operator Adam Brown
|
||||
0375432329,The Five People You Meet in Heaven (Random House Large Print)
|
||||
0891097287,The Message: The New Testament in Contemporary English
|
||||
1477830049,The Perfect Son
|
||||
0139357432,The Underground Railroad
|
||||
0425263908,Bared to You
|
||||
0544320832,My Mother Was Nuts
|
||||
144238493X,MONEY Master the Game: 7 Simple Steps to Financial Freedom
|
||||
148261376X,The Arrangement
|
||||
1628600543,It Starts With Food: Discover the Whole30 and Change Your Life in Unexpected Ways
|
||||
0340835451,My Sister's Keeper
|
||||
0544838262,Dust (Silo Trilogy) (Volume 3)
|
||||
1449966128,A Child of A Crack Head
|
||||
0606322639,The Hit (Turtleback School & Library Binding Edition)
|
||||
1477665412,Barely Breathing: The Breathing Series (Volume 2)
|
||||
1501180126,Reasons to Vote for Democrats: A Comprehensive Guide
|
||||
0007351054,The Picture of Dorian Gray (Collins Classics)
|
||||
0316405388,Invisible
|
||||
0785289623,"Love & Respect, Special edition w/DVD"
|
||||
1477820884,The Mermaid's Sister
|
||||
0316335614,The Last Lecture
|
||||
0345505336,Hotel on the Corner of Bitter and Sweet: A Novel
|
||||
0385336675,"The Enemy (Jack Reacher, No. 8)"
|
||||
0385368267,Eleanor & Park
|
||||
054774501X,The Hangman's Daughter (Hangman's Daughter Tales) (A Hangman's Daughter Tale)
|
||||
1478121734,Love Yourself Like Your Life Depends On It
|
||||
B0000DYXQZ,The Namesake
|
||||
0007173156,"Oh, the Thinks You Can Think! Green Back Book"
|
||||
1476765340,Collide: Book One in the Collide Series
|
||||
0001050230,"Love's Labour's Lost: Performed by Derek Jacobi, Geraldine McEwan & Cast"
|
||||
0140440410,Anna Karenin
|
||||
0143129430,Thomas Jefferson and the Tripoli Pirates: The Forgotten War That Changed American History
|
||||
0143144391,The Magicians: A Novel (Magicians Trilogy)
|
||||
B002DY9LZQ,"The Devil in the White City: Murder, Magic, and Madness at the Fair That Changed America"
|
||||
1420146874,Maid for Love (Gansett Island)
|
||||
1477828737,A Dark Lure
|
||||
1503945545,The Professor (McMurtrie and Drake Legal Thrillers)
|
||||
0061257095,The Shoemaker's Wife: A Novel
|
||||
0143038419,"Eat, Pray, Love: One Woman's Search for Everything Across Italy, India and Indonesia"
|
||||
0230749283,The Forgotten
|
||||
0385349173,"Things That Matter: Three Decades of Passions, Pastimes and Politics [Deckled Edge]"
|
||||
0671447866,The Official Scrabble Players Dictionary
|
||||
0765309408,Old Man's War
|
||||
1469216051,Pines (Wayward Pines)
|
||||
1501200267,Her Final Breath (The Tracy Crosswhite Series)
|
||||
1503934993,The Temporary Agent (The Agent)
|
||||
0007433298,Portrait of a Spy
|
||||
0141043768,"What Alice Forgot: From the bestselling author of Big Little Lies, now an award winning TV series"
|
||||
0307277674,The Da Vinci Code (Robert Langdon)
|
||||
0349407762,The Obsession
|
||||
0399159894,Whiskey Beach
|
||||
0297833936,The Illustrated Hitch-hiker's Guide to the Galaxy
|
||||
034612557X,Teach Your Child to Read in 100 Easy Lessons
|
||||
1469228009,The One That Got Away
|
||||
1477820272,The Glassblower (The Glassblower Trilogy)
|
||||
0143170090,The Girl with the Dragon Tattoo
|
||||
031604461X,Breaking Dawn Special Edition (The Twilight Saga)
|
||||
0399159010,Let's Pretend This Never Happened: (A Mostly True Memoir)
|
||||
1455521299,King and Maxwell (King & Maxwell)
|
||||
0099664313,Drums of Autumn
|
||||
0140861750,"The Invisible Man (Classic, 20th-Century, Audio)"
|
||||
0141033576,"Thinking, Fast and Slow"
|
||||
0544609719,The Whole30: The 30-Day Guide to Total Health and Food Freedom
|
||||
1439199353,The Boston Girl: A Novel
|
||||
1501099027,The Mating: The Original Law of the Lycans story
|
||||
0099464462,Time Traveler's Wife
|
||||
0385257406,A Breath Of Snow And Ashes
|
||||
0525492127,Night School: A Jack Reacher Novel
|
||||
1432842323,Untitled Personal Essays (Thorndike Press Large Print Popular and Narrative Nonfiction)
|
||||
1941695078,The Vampire's Mail Order Bride (Nocturne Falls) (Volume 1)
|
||||
B00ZX99WE8,The Moonlit Garden eBook
|
||||
0316278157,The Girl With All the Gifts
|
||||
0385340559,"Bad Luck and Trouble (Jack Reacher, No. 11)"
|
||||
1476741182,Wallbanger (The Cocktail Series)
|
||||
1477827021,Tucker's Way
|
||||
1500697974,Leap
|
||||
B0082QFEZ0,Further Chronicles of Avonlea - Kindle edition
|
||||
0061042536,Gifted Hands: The Ben Carson Story
|
||||
0140373535,The Count of Monte Cristo (Puffin Classics) : Abridged
|
||||
0307877183,The Paris Wife: A Novel
|
||||
1469227886,The Bloodletter's Daughter: A Novel of Old Bohemia (Novels of Old Bohemia)
|
||||
1683990021,And Then She Was GONE: A riveting new suspense novel
|
||||
0143144626,"Lover Avenged (Black Dagger Brotherhood, Book 7)"
|
||||
0316027650,Eclipse (Twilight Sagas)
|
||||
1442369183,Rush Revere and the Brave Pilgrims: Time-Travel Adventures with Exceptional Americans
|
||||
1503947874,A Death in Sweden
|
||||
0312537409,Abandon
|
||||
141433625X,The Auschwitz Escape
|
||||
0091937523,With the Old Breed: The World War Two Pacific Classic
|
||||
0140143491,The Storyteller
|
||||
0143127527,The Book of Life: A Novel (All Souls Trilogy)
|
||||
034554305X,The Heist: A Novel (Fox and O'Hare)
|
||||
0439064864,Harry Potter and the Chamber of Secrets
|
||||
0982618492,Wired
|
||||
7208061645,The Kite Runner (Chinese Edition)
|
||||
0062073184,The English Girl
|
||||
0062316869,The Girl Who Came Home: A Novel of the Titanic (P.S.)
|
||||
0316225940,The Wrong Side of Goodbye (A Harry Bosch Novel)
|
||||
1592983073,Deadly Stillwater
|
||||
0545582881,Harry Potter and the Sorcerer's Stone (Book 1)
|
||||
0805096663,Killing Kennedy: The End of Camelot
|
||||
0307749495,The Affair: A Jack Reacher Novel
|
||||
0451216954,"Dark Lover (Black Dagger Brotherhood, Book 1)"
|
||||
0486796647,Creative Haven Owls Coloring Book (Adult Coloring)
|
||||
1439173249,Ameritopia: The Unmaking of America
|
||||
1495307352,Raw
|
||||
0008102147,The Secret Wife
|
||||
0091955106,"The Life-Changing Magic of Tidying: A simple, effective way to banish clutter forever"
|
||||
0316225886,The Crossing (A Harry Bosch Novel)
|
||||
0446691437,The War of Art: Break Through the Blocks and Win Your Inner Creative Battles
|
||||
088070909X,"On Becoming Baby Wise, Book 1"
|
||||
1477827226,Flirting with Felicity
|
||||
1503938719,"Evelyn, After: A Novel"
|
||||
1503943941,Little Boy Lost
|
||||
0451468740,No Easy Day: The Firsthand Account of the Mission that Killed Osama Bin Laden
|
||||
0671715445,What to Expect When You're Expecting
|
||||
145558651X,No Man's Land (John Puller Series)
|
||||
1477819681,The Man of Legends
|
||||
1503938778,Ocean of Storms
|
||||
B00Y21VGYW,A Death in Sweden - Kindle edition
|
||||
0099481685,Skipping Christmas
|
||||
0316210870,12th of Never (Women's Murder Club)
|
||||
1500986194,The Lost Starship
|
||||
B000BGS8T8,The Complete Sherlock Holmes (Volume One)
|
||||
0060558121,American Gods
|
||||
0345504992,The Twelve (Passage)
|
||||
0385683421,A Spool of Blue Thread
|
||||
0399168796,Gathering Prey (A Prey Novel)
|
||||
0451239350,Lover At Last: A Novel of the Black Dagger Brotherhood
|
||||
0575097418,Words of Radiance: The Stormlight Archive Book Two
|
||||
0802407692,The 5 Love Languages Military Edition: The Secret to Love That Lasts
|
||||
1410483673,Theres More To Life Than This (Thorndike Press Large Print Lifestyles)
|
||||
006019832X,Hope to Die (Matthew Scudder Mysteries)
|
||||
0091906814,How to Win Friends and Influence People
|
||||
0756410576,The Slow Regard of Silent Things (Kingkiller Chronicle)
|
||||
1492718475,Innocent in Las Vegas: A Humorous Tiffany Black Mystery (Tiffany Black Mysteries) (Volume 1)
|
||||
1683247353,Beneath a Scarlet Sky (Center Point Large Print)
|
||||
0030565073,"Holt McDougal Library, High School with Connections: Individual Reader 1984"
|
||||
0615824285,Maid for Love (The McCarthys of Gansett Island Series) (Volume 1)
|
||||
1477818243,Moving Day: A Thriller
|
||||
0061658197,The Pioneer Woman Cooks: Recipes from an Accidental Country Girl
|
||||
0062457713,The Subtle Art of Not Giving a F*ck: A Counterintuitive Approach to Living a Good Life
|
||||
0141185627,The Little Prince" and "Letter to a Hostage" (Penguin Modern Classics Translated Texts S.)
|
||||
0143127551,Everything I Never Told You
|
||||
0307582884,"The Maze Runner (Maze Runner, Book One) (The Maze Runner Series)"
|
||||
0385537859,Inferno
|
||||
0385541198,The Whistler
|
||||
1503953386,When I'm Gone: A Novel
|
||||
1939416205,A Quest of Heroes: Book #1 in the Sorcerer's Ring
|
||||
014014773X,The Things They Carried (Contemporary American Fiction)
|
||||
0141027126,War Brides
|
||||
0312850093,"The Eye of the World (The Wheel of Time, Book 1)"
|
||||
0345544978,Small Great Things: A Novel
|
||||
0395083664,The Armada (The American Heritage Library)
|
||||
0544334485,Johnny Carson
|
||||
0553418025,The Martian
|
||||
0062320084,The Heist (Gabriel Allon)
|
||||
0307749649,Never Go Back: A Jack Reacher Novel
|
||||
0316055433,The Goldfinch: A Novel (Pulitzer Prize for Fiction)
|
||||
0679444327,The Warmth of Other Suns: The Epic Story of America's Great Migration
|
||||
0988301318,Fallen Too Far
|
||||
1503948706,Say You're Sorry (Morgan Dane)
|
||||
0007925565,Moby Dick (Collins Classics)
|
||||
0140434917,The Hunting of the Snark : An Agony in Eight Fits (Penguin Classics)
|
||||
0307885151,A Short History of Nearly Everything: Special Illustrated Edition
|
||||
1444798847,The One Thing: The Surprisingly Simple Truth Behind Extraordinary Results
|
||||
1477818065,The Unwanted Wife
|
||||
1492747890,Secrets of a Side Bitch
|
||||
0007368658,The Great Gatsby (Collins Classics)
|
||||
0060786469,Love Medicine (Perennial Modern Classics)
|
||||
0143105531,The Book of Mormon (Penguin Classics)
|
||||
0310419034,"NIV, Life Application Study Bible, Large Print, Leathersoft, Pink/Purple"
|
||||
0316306797,Hollow City
|
||||
0425259854,Dark Witch (Cousins O'Dwyer)
|
||||
0241003636,Flash Boys
|
||||
0385344430,Written in My Own Heart's Blood (Outlander)
|
||||
147674355X,Hopeless
|
||||
1477818294,In Farleigh Field: A Novel of World War II
|
||||
0316056871,Bossypants
|
||||
0374360960,The Pout-Pout Fish (A Pout-Pout Fish Adventure)
|
||||
1609580834,"The Care and Keeping of You: The Body Book for Younger Girls, Revised Edition (American Girl Library)"
|
||||
0062200585,NOS4A2: A Novel
|
||||
0307932540,Notorious Nineteen: A Stephanie Plum Novel
|
||||
0316210900,Cross My Heart (Alex Cross)
|
||||
0385341008,The Guernsey Literary and Potato Peel Pie Society
|
||||
0399128298,As a Man Thinketh (Family Inspirational Library)
|
||||
1463604815,The Good Lawyer: A Novel
|
||||
1469217090,Apocalypse Z: The Beginning of the End
|
||||
1467917109,The Last Call: A Bill Travis Mystery
|
||||
147782801X,Crow Hollow
|
||||
1939962315,"The Billionaire's Obsession: The Complete Collection: Mine For Tonight, Mine For Now, Mine Forever, Mine Completely"
|
||||
0307987647,A Clash of Kings: A Song of Ice and Fire: Book Two
|
||||
141046668X,Field Of Prey (Thorndike Press Large Print Basic)
|
||||
1442365528,Red Sparrow: A Novel
|
||||
1477848150,Timebound (The Chronos Files)
|
||||
009917961X,The Rainmaker
|
||||
0345504976,The Passage: A Novel (Book One of The Passage Trilogy)
|
||||
0425259870,Blood Magick (Cousins O'Dwyer)
|
||||
1477820876,The Dead Key
|
||||
1611749271,The Art Forger
|
||||
B00Y68O6WK,Cross Justice: (Alex Cross 23) - Kindle edition
|
||||
006017322X,To Kill a Mockingbird
|
||||
0140437681,Treasure Island (Penguin Classics)
|
||||
1475143389,Bigger Leaner Stronger: The Simple Science of Building the Ultimate Male Body (The Build Healthy Muscle Series)
|
||||
1480504246,Brilliance (The Brilliance Trilogy)
|
||||
0141036249,"Outliers, The Story of Success"
|
||||
0307939693,The Orphan Master's Son: A Novel
|
||||
B017LGAKEQ,The Temporary Agent (The Agent Book 1) eBook
|
||||
1442381221,Beautiful Bastard
|
||||
0007230206,Wolf Hall (Thomas Cromwell)
|
||||
0030845742,"Brown bear, brown bear, what do you see? (A Bill Martin instant reader)"
|
||||
0060194480,A People's History of the United States: 1492 to the Present
|
||||
0310428041,"NIV Study Bible, Leathersoft, Tan/Blue, Indexed, Red Letter Edition"
|
||||
0399144676,"Tripwire (Jack Reacher, No. 3)"
|
||||
0764202677,"The Widow of Larkspur Inn (The Gresham Chronicles, Book 1)"
|
||||
0996135669,Vicious (Sinners of Saint) (Volume 1)
|
||||
000711835X,The Hobbit
|
||||
0060175400,The Poisonwood Bible
|
||||
0061969559,"I Am Number Four (Lorien Legacies, Book 1)"
|
||||
0099771519,Memoirs of a Geisha Uk
|
||||
0316098329,Room
|
||||
0399162380,Field of Prey
|
||||
0931432820,The Complete Book of Essential Oils and Aromatherapy
|
||||
1441766073,"Bonhoeffer: Pastor, Martyr, Prophet, Spy: A Righteous Gentile vs. the Third Reich"
|
||||
1503943429,A Criminal Defense (Philadelphia Legal)
|
||||
B001180MB2,Dune
|
||||
0151015392,The Princess Bride (Fox): S. Morgenstern's Classic Tale of True Love and High Adventure
|
||||
0385316917,Special Delivery
|
||||
0786965606,Player's Handbook (Dungeons & Dragons)
|
||||
1410440478,11/22/63 (Thorndike Press Large Print Core)
|
||||
0007181701,Fahrenheit 451
|
||||
0007378033,Unbroken: An Extraordinary True Story of Courage and Survival
|
||||
0062325388,Flesh and Blood CD: A Scarpetta Novel (Kay Scarpetta Series)
|
||||
0356502481,Blood Song: Book 1 of Raven's Shadow
|
||||
0385660073,The Kite Runner
|
||||
0684824906,Team of Rivals: The Political Genius of Abraham Lincoln
|
||||
0989450252,Crashed (The Driven Trilogy)
|
||||
B00ES25FBA,Night
|
||||
0091939526,"4-Hour Body An Uncommon Guide to Rapid Fat-Loss, Incredible Sex and Becoming Superhuman"
|
||||
0297859382,Gone Girl
|
||||
0571179924,Casino
|
||||
147003655X,Deadly Offerings (Volume 1)
|
||||
1491591846,Follow You Home
|
||||
B001C4VLZQ,Hobbit and Lord of the Rings Trilogy - Boxed Set of 4 Books
|
||||
0307962520,Prince Lestat
|
||||
0310330718,America the Beautiful: Rediscovering What Made This Nation Great
|
||||
0439228905,Black Beauty (Scholastic Classics)
|
||||
0446568813,Rich Dad Poor Dad (What the Rich Teach Their Kids About Money - That the Poor and Middle Class Do Not!)
|
||||
0957652232,Sleep Tight
|
||||
1477808701,Wayward (Wayward Pines)
|
||||
0007554850,The Girl with Seven Names
|
||||
0307475255,Into Thin Air: A Personal Account of the Mt. Everest Disaster
|
||||
034551162X,Aftermath: Star Wars: Journey to Star Wars: The Force Awakens
|
||||
0399159371,The Witness
|
||||
0399162372,Deadline (A Virgil Flowers Novel)
|
||||
0671015206,The Millionaire Next Door
|
||||
0758605323,"The Holy Bible: English Standard Version, Concordia Deluxe Reference Edition, ESV"
|
||||
1623156122,The Instant Pot Electric Pressure Cooker Cookbook: Easy Recipes for Fast & Healthy Meals
|
||||
0007119550,"A Storm of Swords: Part 2 Blood and Gold (A Song of Ice and Fire, Book 3)"
|
||||
0061728985,"Act Like a Lady, Think Like a Man: What Men Really Think About Love, Relationships, Intimacy, and Commitment"
|
||||
0140390316,The Jungle (The Penguin American Library)
|
||||
0641866240,The Glass Castle
|
||||
1476753164,Maybe Someday
|
||||
0062205579,A Prayer for Owen Meany
|
||||
044630557X,Upstairs at the White House
|
||||
0446547654,The Best of Me
|
||||
0451412729,In Good Faith (Joe Dillard)
|
||||
0785262180,Total Money Makeover
|
||||
1442362383,Doctor Sleep: A Novel
|
||||
B0000547HM,On Writing: A Memoir of the Craft
|
||||
031612091X,"Eat to Live: The Amazing Nutrient-Rich Program for Fast and Sustained Weight Loss, Revised Edition"
|
||||
0991140230,Bright Side
|
||||
1250010713,The Silent Sister: A Novel
|
||||
1910751774,The Girl in the Ice: A gripping serial killer thriller (Detective Erika Foster crime thriller novel) (Volume 1)
|
||||
0007271239,The Art of Racing in the Rain
|
||||
006058405X,Motor Mouth (Alex Barnaby Series #2)
|
||||
0307272591,Bad Monkey
|
||||
031218008X,One Thousand White Women: The Journals of May Dodd
|
||||
0613171373,A Child Called It: One Child's Courage To Survive (Turtleback School & Library Binding Edition)
|
||||
0800788036,Laugh-Out-Loud Jokes for Kids
|
||||
1477849734,No Ordinary Billionaire (The Sinclairs)
|
||||
000720924X,Looking for Alaska
|
||||
006073132X,Freakonomics: A Rogue Economist Explores the Hidden Side of Everything - by Steven D. Levitt & Stephen J. Dubner
|
||||
0062301233,"Elon Musk: Tesla, SpaceX, and the Quest for a Fantastic Future"
|
||||
0399157573,Dust
|
||||
0849946158,Heaven is for Real: A Little Boy's Astounding Story of His Trip to Heaven and Back
|
||||
0985777338,A Family Affair (Truth in Lies) (Volume 1)
|
||||
1492976423,Making Faces
|
||||
0002247399,A Dance with Dragons
|
||||
0982717105,Storm Clouds Rolling In
|
||||
0989450201,Driven ((The Driven Trilogy))
|
||||
0312356854,Sarah's Key
|
||||
0312655479,How the Light Gets In: A Chief Inspector Gamache Novel
|
||||
0373266154,Murder on the Mind: A Jeff Resnick Mystery
|
||||
0544264975,Hidden
|
||||
0805093079,Killing Lincoln: The Shocking Assassination that Changed America Forever (Bill O'Reilly's Killing Series)
|
||||
1439152802,The Secret Keeper: A Novel
|
||||
0061992704,Sh*t My Dad Says
|
||||
0143130609,George Washington's Secret Six: The Spy Ring That Saved the American Revolution
|
||||
0345539834,Golden Son: Book 2 of the Red Rising Saga (Red Rising Series)
|
||||
0374264260,The Silver Linings Playbook: A Novel
|
||||
1502446936,Stepbrother Dearest
|
||||
0140434968,Bleak House
|
||||
1455571156,The Fix (Memory Man series)
|
||||
0340824255,Land of Painted Caves
|
||||
1410472922,A Man Called Ove (Thorndike Press Large Print Core Series)
|
||||
1451621388,Brain on Fire: My Month of Madness
|
||||
0316349895,Career of Evil (A Cormoran Strike Novel)
|
||||
0762454970,E-Squared: Nine Do-It-Yourself Energy Experiments that Prove Your Thoughts Create Your Reality [Miniature Edition] (Miniature Editions)
|
||||
1416502491,7 Habits of Highly Effective People
|
||||
1878424319,The Four Agreements: A Practical Guide to Personal Freedom (A Toltec Wisdom Book)
|
||||
B0006EVIKG,The Armada (Easton Press)
|
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0007141424,The Giver (Collins Modern Classics)
|
||||
0062225448,Reconstructing Amelia: A Novel
|
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037543075X,The Rescue (Random House Large Print)
|
||||
0399146237,Running Blind
|
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0441008534,"Dead Until Dark (Sookie Stackhouse/True Blood, Book 1)"
|
||||
0451211634,Hostile Witness
|
||||
1477823476,Vanished (Callahan & McLane)
|
||||
1616440724,To Train Up a Child: Child Training for the 21st Century
|
||||
0002247437,A Feast for Crows (Song of Ice and Fire)
|
||||
0060740221,Shakespeare: The World as Stage (Eminent Lives)
|
||||
0062265423,"10% Happier: How I Tamed the Voice in My Head, Reduced Stress Without Losing My Edge, and Found Self-Help That Actually Works--A True Story"
|
||||
0340943831,Battlefield of the Mind: Winning the Battle in Your Mind
|
||||
1492291560,The Mind Readers (The Mind Readers Series)
|
||||
1503939448,Say Goodbye for Now
|
||||
1979172846,Betrayal
|
||||
0316225908,Two Kinds of Truth (A Harry Bosch Novel)
|
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0385689225,Born a Crime
|
||||
1250022118,A Great Reckoning: A Novel (Chief Inspector Gamache Novel)
|
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1477825576,My Sister's Grave (Tracy Crosswhite)
|
||||
0307743659,The Shining
|
||||
0385523394,Orange Is the New Black: My Year in a Women's Prison
|
||||
0762454873,I Declare: 31 Promises to Speak Over Your Life Running Press Miniature Edition (Miniature Editions)
|
||||
1477848355,Secondborn
|
||||
000755236X,Daniel Silva Thriller 6
|
||||
0140177388,Cannery Row
|
||||
030788743X,Ready Player One
|
||||
0062218832,Etched in Sand: A True Story of Five Siblings Who Survived an Unspeakable Childhood on Long Island
|
||||
006226303X,The Ocean at the End of the Lane CD: A Novel
|
||||
0143125842,The Signature of All Things: A Novel
|
||||
0307283666,Harry Potter and the Half-Blood Prince (Book 6)
|
||||
0312354355,The Long Way Home
|
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0316245283,Miss Peregrine's Home for Peculiar Children: The Graphic Novel (Miss Peregrine's Peculiar Children: The Graphic Novel)
|
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0030664128,Holes
|
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0062678418,The Woman in the Window: A Novel
|
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0091816971,Who Moved My Cheese?: An A-Mazing Way to Deal with Change in Your Work and in Your Life
|
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0399593489,The Midnight Line: A Jack Reacher Novel
|
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0613237528,The Perks Of Being A Wallflower (Turtleback School & Library Binding Edition)
|
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0765317583,One Second After (A John Matherson Novel)
|
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1408839121,Heir of Fireno. 3 (Throne of Glass)
|
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1484076249,A Shade Of Vampire 2: A Shade Of Blood
|
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0553292587,Dark Matter
|
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1556114931,Green Lake
|
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0062433229,Departure
|
||||
0356500950,Cold Days: A Dresden Files Novel (The Dresden Files)
|
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0385539258,A Little Life: A Novel
|
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1440072035,"Typee: A Peep at Polynesian Life, During a Four Months Residence in a Valley of the Marquesas, Vol. 1 (Classic Reprint)"
|
||||
1441731326,"The China Study, Revised and Expanded Edition: The Most Comprehensive Study of Nutrition Ever Conducted and the Startling Implications for Diet, Weight Loss, and Long-Term Health"
|
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1503281981,The Irish Cottage (Travel Romance Series BETH)
|
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1503954064,"White Rose, Black Forest"
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B0076JPX46,Where the Red Fern Grows
|
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0297851527,Sharp Objects
|
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0345542975,Tricky Twenty-Two: A Stephanie Plum Novel
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0060094273,Goodnight Moon Board Book & Baby Socks
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014242613X,Theodore Boone: The Accused
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0316225932,The Burning Room (A Harry Bosch Novel)
|
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0439249546,Harry Potter (4 Volumes set)
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1477822089,Trail of Broken Wings
|
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B001L7RCGG,Gone with the Wind
|
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0025853503,"Gone With the Wind, The Margaret Mitchell Anniversary Edition"
|
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006085880X,The Pact: A Love Story
|
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0399164456,The Collector
|
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1480522813,Guns
|
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0786012668,Cold Fear
|
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1101946342,Grey: Fifty Shades of Grey as Told by Christian (Fifty Shades of Grey Series)
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1910751243,The Girl With No Past: A gripping psychological thriller
|
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0006064922,The Holy Bible from the ancient Eastern text : George M. Lamsa's translations from the Aramaic of the Peshitta
|
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0451417089,The Shadows (Black Dagger Brotherhood)
|
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0525497145,A Column of Fire (Kingsbridge)
|
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0788844164,Sing Along Songs:Lion King - Circle
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1477820469,Miramont's Ghost
|
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1930448384,"The CalorieKing Calorie, Fat, & Carbohydrate Counter 2012 Larger Print Edition (Calorieking Calorie, Fat & Carbohydrate Counter (Larger Print Edition))"
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0143125478,The Boys in the Boat: Nine Americans and Their Epic Quest for Gold at the 1936 Berlin Olympics
|
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0307749606,A Wanted Man: A Jack Reacher Novel
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0007420412,Divergent
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097901977X,The Miracle Morning: The Not-So-Obvious Secret Guaranteed to Transform Your Life (Before 8am)
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1503933385,We're All Damaged
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0062491792,Commonwealth
|
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0136879721,The Power of Your Subconcious Mind
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0446612774,Long Time Coming
|
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0452296366,This Is Where I Leave You: A Novel
|
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1628600020,"Practical Paleo, 2nd Edition (Updated and Expanded): A Customized Approach to Health and a Whole-Foods Lifestyle"
|
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0140385622,The Diary of a Young Girl: Definitive Edition
|
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0307989909,Circling the Sun: A Novel
|
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141046900X,Mr. Mercedes
|
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1410493547,Killing The Rising Sun: How America Vanquished World War II Japan (Wheeler Publishing Large Print Book Series)
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B00FJ3AC10,Natchez Burning: A Novel (Penn Cage Book 4) - Kindle edition
|
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0307245934,The Miraculous Journey of Edward Tulane
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0751541184,The Time Keeper
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006056492X,Slaughterhouse Five
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0307280721,"Eldest (Inheritance, Book 2)"
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0425266060,Bared to You / Reflected in You / Entwined with You
|
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1401940676,"Dying To Be Me: My Journey from Cancer, to Near Death, to True Healing"
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1470381788,Finding Me
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1501257544,The Atlantis Plague (The Origin Mystery)
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1934193798,Great Food Fast : Bob Warden's Ultimate Pressure Cooker Recipes
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0307731715,"To Heaven and Back: A Doctor's Extraordinary Account of Her Death, Heaven, Angels, and Life Again: A True Story"
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0310435609,"NIV, Thinline Craft Collection Bible, Hardcover, Tan/Purple, Red Letter Edition"
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0316408751,14th Deadly Sin (Women's Murder Club)
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0345514408,I Know Why the Caged Bird Sings
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0345543254,Gray Mountain: A Novel
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0778316556,The Good Girl (English Edition)
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1477848827,I Am Livia
|
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1517028817,The Grave Man - A Sam Prichard Novel (The Sam Prichard Series) (Volume 1)
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1530126894,"The Pursuit of God: AW Tozer, Christian classics: The Pursuit of God"
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0099740915,The Handmaid's Tale (Contemporary Classics)
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0134374940,Night: With Connected Readings
|
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0525955097,Fool Me Once
|
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1455124176,The Art of Hearing Heartbeats: A Novel
|
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1461085977,Flat-Out Love
|
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1503945626,Life and Other Near-Death Experiences
|
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1612185304,Supreme Justice (Reeder and Rogers Thriller)
|
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0060899220,Kitchen Confidential Updated Edition: Adventures in the Culinary Underbelly (P.S.)
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0451414136,The Stranger
|
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0595440096,Still Alice
|
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0890425558,"Diagnostic and Statistical Manual of Mental Disorders, 5th Edition: DSM-5"
|
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1503933547,The Light of the Fireflies
|
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0263234541,Waking Up Married (Mills & Boon Hardback Romance)
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0606371192,Secret Garden: An Inky Treasure Hunt And Coloring Book (Turtleback School & Library Binding Edition)
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0615590586,The Pecan Man
|
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0718079183,The Magnolia Story
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0749958790,Proof of Heaven: A Neurosurgeon's Journey into the Afterlife
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1250066115,How Not to Die: Discover the Foods Scientifically Proven to Prevent and Reverse Disease
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0030554179,Animal Farm with Connections (HRW Library Study Guides)
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0743566572,City of Bones (The Mortal Instruments)
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0140277633,Easy Way to Stop Smoking
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0340820462,On Writing
|
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0982301820,10-Day Green Smoothie Cleanse: Lose Up to 15 Pounds in 10 Days!
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1466287047,Russo's Gold
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1501086138,Maude
|
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0399167447,Somewhere Safe with Somebody Good (Mitford)
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0692312374,A Crime of Passion (Joe Dillard Series Book 7) (Volume 7)
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0758278454,What She Left Behind
|
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1250000971,The Sins of the Father (The Clifton Chronicles)
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0006895492,Essentials of Human Anatomy and Physiology- Text Only 8th edition by Elaine N. Marieb (2006) Paperback
|
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0060518049,The Secret History
|
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0147524210,One Nation: What We Can All Do to Save America's Future
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1987987039,Code Name Camelot - A Noah Wolf Thriller (Volume 1)
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0307408868,Dead Wake: The Last Crossing of the Lusitania
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0316557994,Extinction Horizon(The Extinction Cycle Book 1)
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0340364777,It
|
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1592642195,The Misremembered Man
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0399160477,Command Authority (Jack Ryan)
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0425256391,Dead Ever After (Sookie Stackhouse/True Blood)
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0451482212,Between the World and Me
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0671449028,The Going-To-Bed Book
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0062270486,Spider Woman's Daughter (A Leaphorn and Chee Novel)
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0399160450,"Threat Vector (Jack Ryan, Jr.)"
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1410470997,Act Of War (Thorndike Press Large Print Core)
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1503937623,Walk Into Silence (Jo Larsen)
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1452605165,The Untethered Soul: The Journey Beyond Yourself
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1250109302,One with You (Crossfire)
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1442367636,The Liberty Amendments: Restoring the American Republic
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1499616015,"77 Days in September: A Novel of Survival, Dedication, and Love (The Kyle Tait Series) (Volume 1)"
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1501260235,The New Jim Crow: Mass Incarceration in the Age of Colorblindness
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0091948177,The Fast Metabolism Diet: Lose Up to 20 Pounds in 28 Days: Eat More Food & Lose More Weight
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144235948X,Beautiful Disaster
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1442384344,Finders Keepers: A Novel
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1492707872,Girl Jacked
|
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B011UNEZN8,The Last Girl (The Dominion Trilogy Book 1) eBook
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0007450664,A Song of Ice and Fire: The Story So Far (5 Volumes)
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0030554543,"Holt McDougal Library, High School with Connections: Individual Reader Narrative of the Life of Frederick Douglas"
|
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0671207822,"Man's Search for Meaning: An Introduction to Logotherapy, Revised and Enlarged Edition"
|
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0805448659,The Love Dare
|
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0989450236,Fueled (The Driven Trilogy)
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140885788X,A Court of Mist and Fury (Court of Thorns and Roses)
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1477817182,Out of Breath (Breathing)
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1491534583,The Afterlife of Billy Fingers: How My Bad-Boy Brother Proved to Me There's Life After Death
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1503936724,The Buried Book
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0385393997,Y is for Yesterday (A Kinsey Millhone Novel)
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0385543026,Camino Island: A Novel
|
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1503942767,Wives of War
|
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0345544943,Leaving Time (with bonus novella Larger Than Life): A Novel
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0451412656,AN Innocent Client (Joe Dillard)
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0786224681,Left Behind: A Novel of the Earth's Last Days (Left Behind #1)
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1442391235,The Japanese Lover
|
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0739438069,redeeming Love
|
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014219672X,On the Island
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0345543017,Turbo Twenty-Three: A Stephanie Plum Novel
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1469290103,Walk Me Home
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B00F8F3J2S,Duty
|
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0061351415,The Art of War: The New Translation (Harper Perennial Modern Classics)
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0062561723,Commonwealth CD
|
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0312069782,Battlefield Earth: A Saga of the Year 3000
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0316199869,NYPD Red
|
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0880801441,The Constitution of the United States
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0984502203,Yellow Crocus: A Novel
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1503936198,Blood Defense (Samantha Brinkman)
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1503936902,A River in Darkness: One Man's Escape from North Korea
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1786811138,The Missing Ones: An absolutely gripping thriller with a jaw-dropping twist (Detective Lottie Parker) (Volume 1)
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0345542894,Takedown Twenty (Stephanie Plum)
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091585600X,Alcoholics Anonymous: The Story of How Many Thousands of Men and Women Have Recovered from Alcoholism
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1482066300,"The Lake: (The Lake Series, Book 1)"
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1602600155,Know Your Bible: All 66 Books Explained and Applied (Value Books)
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B000K5THYU,"THE LORD OF THE RINGS Trilogy - (The Fellowship of the Ring, The Return of the Ring, The Two Towers) - 3 BOOK SET (MOVIE COVERS)"
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0988234807,"Saving Grace (What Doesn't Kill You, #1): A Katie Romantic Mystery"
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1400116554,"Empire of the Summer Moon: Quanah Parker and the Rise and Fall of the Comanches, the Most Powerful Indian Tribe in American History"
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1455540412,"Al Franken, Giant of the Senate"
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B00CLMX0D4,The Miracle Morning: The Not-So-Obvious Secret Guaranteed to Transform Your Life - Before 8AM
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0307408841,"In the Garden of Beasts: Love, Terror, and an American Family in Hitler's Berlin"
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0316339377,The Murder House
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034554398X,A Storm of Swords (HBO Tie-in Edition): A Song of Ice and Fire: Book Three
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B00005TZY5,The Universe in a Nutshell
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B00V731OIG,The English Spy
|
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0755361881,Until Tuesday
|
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0937611468,You Can Heal Your Life (Unabridged)
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1542046599,I Am Watching You
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1612181953,The Barkeep
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1943591024,The True Story of Fake News: How Mainstream Media Manipulates Millions
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0062124277,Flight Behavior: A Novel
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0312853238,Ender's Game (The Ender Quintet)
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1484015800,Dark Space
|
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B004N58TYW,"The Hiding Place Publisher: Blackstone Audio, Inc.; Unabridged edition"
|
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1986566854,Of Mice and Men
|
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B000GVWRVS,"Purpose-driven Life [Paperback] by Warren , Rick"
|
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B00A9WRH3M,Great Expectations By Charles Dickens - The Franklin Library (Hardcover - 1979)
|
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0143111582,Dune (Penguin Galaxy)
|
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0307594882,My Beloved World
|
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0312577222,The Nightingale: A Novel
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0316044695,Lone Survivor: The Eyewitness Account of Operation Redwing and the Lost Heroes of SEAL Team 10
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037032921X,The BOOK THIEF
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0451165209,The Richest Man in Babylon
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0553212737,Emma (Bantam Classics)
|
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1410458229,Ordinary Grace (Thorndike Press Large Print Mystery)
|
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147781826X,A Merciful Death (Mercy Kilpatrick)
|
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0307743683,The Stand
|
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0316404152,The Remaining
|
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1503934152,The House by the Lake
|
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0006280544,Mere Christianity
|
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0316407046,Cross Justice (Alex Cross)
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0739462911,Younger Next Year for Women - LARGE PRINT
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1433805596,Publication Manual of the American Psychological Association
|
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1503950255,The Short Drop (Gibson Vaughn)
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0439804078,Chicka Chicka Boom Boom
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1442384433,Code of Conduct: A Thriller
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1503939324,From Sand and Ash
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0007447868,A Feast for Crows
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0060099402,The Giving Tree with Gift Card
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0307266303,"Born to Run: A Hidden Tribe, Superathletes, and the Greatest Race the World Has Never Seen"
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0307747441,Killers of the Flower Moon: The Osage Murders and the Birth of the FBI
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044654759X,Safe Haven
|
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1503936821,Doubt (Caroline Auden)
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B0061YX9MU,The Book Case: A Short Story Featuring Detective John Corey
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B01CIYURJE,Instant Pot Electric Pressure Cooker Cookbook
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0316069434,The Black Box (A Harry Bosch Novel)
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0451419707,On Dublin Street (On Dublin Street Series)
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0001844423,Magician's Nephew - Folio Society Hardcover
|
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000726755X,Odd Hours
|
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0345472322,Mindset: The New Psychology of Success
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0439139600,Harry Potter And The Goblet Of Fire
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0781414024,Crazy Love: Overwhelmed by a Relentless God
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0142800805,Shadow of the Wind
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0439287197,Giraffes Can't Dance
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0547744943,Elizabeth Street
|
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0983492700,Irreparable Harm (Sasha McCandless Legal Thriller) (Volume 1)
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1503950778,Ghost Gifts (A Ghost Gifts Novel)
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0140012486,The Catcher in the Rye (Modern Classics S.)
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0140324623,Anne of Green Gables
|
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0439358078,Harry Potter And The Order Of The Phoenix
|
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0739431234,"Candle in the Darkness (Refiner's Fire, Book 1)"
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1410491161,My Brilliant Friend (The Neapolitan Novels)
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0099553473,Zoo (Zoo Series)
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0307387178,Into the Wild
|
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0439023521,The Hunger Games (Book 1)
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0451218043,"Lover Eternal (Black Dagger Brotherhood, Book 2)"
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1400203759,Love Does: Discover a Secretly Incredible Life in an Ordinary World
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1455883549,The Gifts of Imperfection: Let Go of Who You Think You're Supposed to Be and Embrace Who You Are
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0385342462,An Echo in the Bone: A Novel (Outlander)
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0425252868,A Higher Call: An Incredible True Story of Combat and Chivalry in the War-Torn Skies of World War II
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1477821937,Wreckage
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0399142533,"Killing Floor (Jack Reacher, No. 1)"
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1442360925,Agenda 21
|
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1514792400,Blindsided - A Thriller
|
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0062320165,The English Spy (Gabriel Allon)
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0307010856,The Monster at the End of This Book
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0310708257,The Jesus Storybook Bible: Every Story Whispers His Name
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0316206873,The Silkworm (A Cormoran Strike Novel)
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0812976894,Still Life with Bread Crumbs: A Novel
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0857208748,The Last Man (Mitch Rapp)
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110188696X,Troublemaker: Surviving Hollywood and Scientology
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1501215213,The Atlantis World (The Origin Mystery)
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1607105551,Sense and Sensibility (Word Cloud Classics)
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0060586133,Three Wishes: A Novel
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0307941515,The Litigators
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1503934713,The Butterfly Garden (The Collector)
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1503943372,Beneath a Scarlet Sky: A Novel
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0062107321,The Valley of Amazement
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0152056610,Little Blue Truck
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038568231X,The Girl on the Train
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0399167064,Big Little Lies
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0606365273,The Escape (Turtleback School & Library Binding Edition) (John Puller)
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0812469496,Love You Forever
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1433524724,ESV New Classic Reference Bible (Black)
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1442378182,Rush Revere and the American Revolution: Time-Travel Adventures With Exceptional Americans
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1477826106,Finding Rebecca
|
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1503950646,The Moonlit Garden
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1503952088,The Last Girl (The Dominion Trilogy)
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1514193159,Dawn of Wonder (The Wakening) (Volume 1)
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B00OPAJ7VO,A Shade of Vampire 2: A Shade of Blood
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0099579936,Fifty Shades of Grey
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0312330529,Shantaram: A Novel
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0312857055,"Wizard's First Rule (Sword of Truth, Book 1)"
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0007350856,The Jungle Book (Collins Classics)
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0147524199,Winter of the World: Book Two of the Century Trilogy
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0307265439,The Road
|
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0356500276,Storm Front (Dresden Files (Unnumbered Paperback))
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1250132363,Behind Closed Doors: A Novel
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1535197722,The Gender Game (Volume 1)
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0007155662,The Alchemist
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0099302780,"GUNS, GERMS AND STEEL - A Short History of Everybody for the Last 13,000 Years"
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0099456761,The Curious Incident of the Dog in the Night-Time
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0312169787,The Red Tent: A Novel
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0340979496,The Shack
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0340992565,Under the Dome
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0385539436,Rogue Lawyer: A Novel
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080419257X,Zealot: The Life and Times of Jesus of Nazareth
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014312577X,The Girl You Left Behind: A Novel
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0345546881,The One & Only: A Novel
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1455548987,The Edge of Never
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1477820019,Take Me With You
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1495179400,The Tumor: A Non-Legal Thriller
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014241493X,Paper Towns
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0307957837,His Dark Materials: The Golden Compass / The Subtle Knife / The Amber Spyglass
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037543318X,Angels & Demons (Random House Large Print)
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0425280101,Stars of Fortune (Guardians Trilogy)
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1410445224,Steve Jobs: A Biography
|
||||
1442366109,"Happy, Happy, Happy: My Life and Legacy as the Duck Commander"
|
||||
1479370118,Awakened (Vampire Awakenings 1) (Volume 1)
|
||||
0062429078,Pretty Girls
|
||||
0310325501,Praying Circles around Your Children
|
||||
1503950549,Justice Redeemed (Darren Street)
|
||||
1503952231,While You Were Mine
|
||||
1785770527,Silent Scream (D.I. Kim Stone)
|
||||
0007350899,A Tale of Two Cities (Collins Classics)
|
||||
0140569324,The Very Hungry Caterpillar (Picture Puffins)
|
||||
0027701301,Hatchet
|
||||
0030624266,The Wizard of Oz
|
||||
0316290033,15th Affair (Women's Murder Club)
|
||||
0374214913,Mr. Penumbra's 24-Hour Bookstore: A Novel
|
||||
0446580848,The Panther (A John Corey Novel)
|
||||
1439153663,The Kitchen House: A Novel
|
||||
144947425X,Milk and Honey
|
||||
1469291118,The Sisterhood
|
||||
0141192496,Oliver Twist (Penguin Clothbound Classics)
|
||||
0307966666,"Power of Habit, the (Lib)(CD)"
|
||||
0310321913,One Thousand Gifts: A Dare to Live Fully Right Where You Are
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||||
0547745524,Awol on the Appalachian Trail
|
||||
1469984202,Wool - Omnibus Edition
|
||||
1517153158,Split Second
|
||||
0062372106,Down the Rabbit Hole: Curious Adventures and Cautionary Tales of a Former Playboy Bunny
|
||||
0375434321,"One Summer: America, 1927 (Random House Large Print)"
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||||
194205209X,The Housewife Assassin's Handbook (The Housewife Assassin Series) (Volume 1)
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|
||||
A32XDVGUL7D3M9,B017V4IPPO,5
|
||||
A33C26IKKXA1G,0141043768,5
|
||||
A33NDI6YIK6HQX,0142428280,5
|
||||
A33P1TUQM63UUM,0307408868,5
|
||||
A33RRGPKVBWTXC,0345514408,5
|
||||
A33V0DALFQ1B54,054774501X,4
|
||||
|
@@ -1,201 +0,0 @@
|
||||
"""CSC111 Winter 2022 Prep 10: Programming Exercises
|
||||
|
||||
Instructions (READ THIS FIRST!)
|
||||
===============================
|
||||
|
||||
This module contains the mergesort algorithm from the prep readings, as well as a few
|
||||
additional functions for you to implement.
|
||||
|
||||
We have marked each place you need to write code with the word "TODO".
|
||||
As you complete your work in this file, delete each TODO comment.
|
||||
|
||||
You may add additional doctests, but they will not be graded. You should test your work
|
||||
carefully before submitting it!
|
||||
|
||||
Copyright and Usage Information
|
||||
===============================
|
||||
|
||||
This file is provided solely for the personal and private use of students
|
||||
taking CSC111 at the University of Toronto St. George campus. All forms of
|
||||
distribution of this code, whether as given or with any changes, are
|
||||
expressly prohibited. For more information on copyright for CSC111 materials,
|
||||
please consult our Course Syllabus.
|
||||
|
||||
This file is Copyright (c) 2022 Mario Badr and David Liu.
|
||||
"""
|
||||
|
||||
|
||||
def mergesort(lst: list) -> list:
|
||||
"""Return a new sorted list with the same elements as lst.
|
||||
|
||||
This is a *non-mutating* version of mergesort; it does not mutate the
|
||||
input list.
|
||||
|
||||
>>> mergesort([10, 2, 5, -6, 17, 10])
|
||||
[-6, 2, 5, 10, 10, 17]
|
||||
"""
|
||||
if len(lst) < 2:
|
||||
return lst.copy() # Use the list.copy method to return a new list object
|
||||
else:
|
||||
# Divide the list into two parts, and sort them recursively.
|
||||
mid = len(lst) // 2
|
||||
left_sorted = mergesort(lst[:mid])
|
||||
right_sorted = mergesort(lst[mid:])
|
||||
|
||||
# Merge the two sorted halves. Using a helper here!
|
||||
return _merge(left_sorted, right_sorted)
|
||||
|
||||
|
||||
def _merge(lst1: list, lst2: list) -> list:
|
||||
"""Return a sorted list with the elements in lst1 and lst2.
|
||||
|
||||
Preconditions:
|
||||
- is_sorted(lst1)
|
||||
- is_sorted(lst2)
|
||||
|
||||
>>> _merge([-1, 3, 7, 10], [-3, 0, 2, 6])
|
||||
[-3, -1, 0, 2, 3, 6, 7, 10]
|
||||
"""
|
||||
i1, i2 = 0, 0
|
||||
sorted_so_far = []
|
||||
|
||||
while i1 < len(lst1) and i2 < len(lst2):
|
||||
# Loop invariant:
|
||||
# sorted_so_far is a merged version of lst1[:i1] and lst2[:i2]
|
||||
assert sorted_so_far == sorted(lst1[:i1] + lst2[:i2])
|
||||
|
||||
if lst1[i1] <= lst2[i2]:
|
||||
sorted_so_far.append(lst1[i1])
|
||||
i1 += 1
|
||||
else:
|
||||
sorted_so_far.append(lst2[i2])
|
||||
i2 += 1
|
||||
|
||||
# When the loop is over, either i1 == len(lst1) or i2 == len(lst2)
|
||||
assert i1 == len(lst1) or i2 == len(lst2)
|
||||
|
||||
# In either case, the remaining unmerged elements can be concatenated to sorted_so_far.
|
||||
if i1 == len(lst1):
|
||||
return sorted_so_far + lst2[i2:]
|
||||
else:
|
||||
return sorted_so_far + lst1[i1:]
|
||||
|
||||
|
||||
################################################################################
|
||||
# Prep exercises
|
||||
################################################################################
|
||||
def merge_indexed(lst: list, m: int) -> list:
|
||||
"""Return a sorted list containing the items in lst.
|
||||
|
||||
This function should use the same algorithm as the _merge helper function,
|
||||
with the two "sorted lists" being lst[:m] and lst[m:].
|
||||
Don't use built-in sorting functions or other list operations; follow the
|
||||
implementation of _merge as closely as possible. You don't need to copy over
|
||||
the loop invariant, although you may find it helpful to do so.
|
||||
|
||||
Note that this function is public, as we are importing and testing it directly.
|
||||
|
||||
Preconditions:
|
||||
- 0 <= m < len(lst)
|
||||
- is_sorted_sublist(lst, 0, m)
|
||||
- is_sorted_sublist(lst, m, len(lst))
|
||||
|
||||
(You're welcome to copy over your implementation of is_sorted_sublist from last week's
|
||||
prep; if you don't, PythonTA will just ignore the last two preconditions.)
|
||||
|
||||
>>> lst = [10, 20, 30, 4, 15, 16, 99]
|
||||
>>> merge_indexed(lst, 3) # sorted sublists are lst[:3] and lst[3:]
|
||||
[4, 10, 15, 16, 20, 30, 99]
|
||||
"""
|
||||
i1, i2 = 0, m
|
||||
sorted_so_far = []
|
||||
|
||||
while i1 < m and i2 < len(lst):
|
||||
# Loop invariant:
|
||||
# sorted_so_far is a merged version of lst1[:i1] and lst2[:i2]
|
||||
assert sorted_so_far == sorted(lst[:i1] + lst[m:i2])
|
||||
|
||||
if lst[i1] <= lst[i2]:
|
||||
sorted_so_far.append(lst[i1])
|
||||
i1 += 1
|
||||
else:
|
||||
sorted_so_far.append(lst[i2])
|
||||
i2 += 1
|
||||
|
||||
# When the loop is over, either i1 or i2 reached the end
|
||||
assert i1 == m or i2 == len(lst)
|
||||
|
||||
# In either case, the remaining unmerged elements can be concatenated to sorted_so_far.
|
||||
return sorted_so_far + (lst[i2:] if i1 == m else lst[i1:m])
|
||||
|
||||
|
||||
def merge_sublists(lst: list, b: int, m: int, e: int) -> None:
|
||||
"""Merge two sorted sublists in lst into one sorted sublist.
|
||||
|
||||
This is similar to merge_indexed, except:
|
||||
- The two sublists are now lst[b:m] and lst[m:e]
|
||||
- Rather than returning a new list, this function mutates lst so that
|
||||
lst[b:e] is a sorted version of the two previous sublists.
|
||||
|
||||
Preconditions:
|
||||
- 0 <= b <= m <= e < len(lst)
|
||||
- is_sorted_sublist(lst, b, m)
|
||||
- is_sorted_sublist(lst, m, e)
|
||||
|
||||
>>> lst = [100, 3, 10, 16, 2, 11, 20, 30, -1]
|
||||
>>> merge_sublists(lst, 1, 4, 8) # sorted sublists are lst[1:4] and lst[4:8]
|
||||
>>> lst # Note that the 100 and -1 aren't affected.
|
||||
[100, 2, 3, 10, 11, 16, 20, 30, -1]
|
||||
>>> merge_sublists(lst, 3, 3, 3)
|
||||
>>> lst # No change
|
||||
[100, 2, 3, 10, 11, 16, 20, 30, -1]
|
||||
>>> lst = [100, 10, 20, 30, 4, 15, 16, 99, -1]
|
||||
>>> merge_sublists(lst, 1, 4, 8)
|
||||
>>> lst
|
||||
[100, 4, 10, 15, 16, 20, 30, 99, -1]
|
||||
|
||||
IMPORTANT implementation note: even though this function doesn't return a new list,
|
||||
you can still create a new local list object to do the merging, and then copy the
|
||||
contents back to lst[b:e] when you're done. This means that this algorithm won't be
|
||||
in-place (since it creates a list object of non-constant size), but that's okay.
|
||||
It's actually very complex to try to implement this function in an in-place way,
|
||||
just like it's hard to implement an in-place mergesort.
|
||||
|
||||
As with merge_indexed, you should not use built-in sorting functions or other list
|
||||
methods, but instead follow the implementation of _merge as closely as possible.
|
||||
You may, but are not required to, assign to a list slice, e.g. lst[0:10] = ...
|
||||
"""
|
||||
i1, i2 = b, m
|
||||
sorted_so_far = []
|
||||
|
||||
while i1 < m and i2 < e:
|
||||
# Loop invariant:
|
||||
# sorted_so_far is a merged version of lst1[:i1] and lst2[:i2]
|
||||
assert sorted_so_far == sorted(lst[b:i1] + lst[m:i2])
|
||||
|
||||
if lst[i1] <= lst[i2]:
|
||||
sorted_so_far.append(lst[i1])
|
||||
i1 += 1
|
||||
else:
|
||||
sorted_so_far.append(lst[i2])
|
||||
i2 += 1
|
||||
|
||||
# When the loop is over, either i1 or i2 reached the end
|
||||
assert i1 == m or i2 == e
|
||||
|
||||
# Assign slice
|
||||
lst[b:e] = sorted_so_far + (lst[i2:e] if i1 == m else lst[i1:m])
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
import python_ta.contracts
|
||||
python_ta.contracts.check_all_contracts()
|
||||
|
||||
import doctest
|
||||
doctest.testmod()
|
||||
|
||||
import python_ta
|
||||
python_ta.check_all(config={
|
||||
'max-line-length': 100,
|
||||
'disable': ['E1136']
|
||||
})
|
||||
@@ -1,254 +0,0 @@
|
||||
"""CSC111 Winter 2022 Prep 8: Programming Exercises
|
||||
|
||||
Instructions (READ THIS FIRST!)
|
||||
===============================
|
||||
|
||||
This module contains the graph implementation we studied in lecture, with a few
|
||||
additional methods for you to implement on this exercise.
|
||||
|
||||
We have marked each place you need to write code with the word "TODO".
|
||||
As you complete your work in this file, delete each TODO comment.
|
||||
|
||||
You may add additional doctests, but they will not be graded. You should test your work
|
||||
carefully before submitting it!
|
||||
|
||||
Copyright and Usage Information
|
||||
===============================
|
||||
|
||||
This file is provided solely for the personal and private use of students
|
||||
taking CSC111 at the University of Toronto St. George campus. All forms of
|
||||
distribution of this code, whether as given or with any changes, are
|
||||
expressly prohibited. For more information on copyright for CSC111 materials,
|
||||
please consult our Course Syllabus.
|
||||
|
||||
This file is Copyright (c) 2022 Mario Badr and David Liu.
|
||||
"""
|
||||
from __future__ import annotations
|
||||
from typing import Any
|
||||
|
||||
|
||||
class Graph:
|
||||
"""A graph.
|
||||
"""
|
||||
# Private Instance Attributes:
|
||||
# - _vertices:
|
||||
# A collection of the vertices contained in this graph.
|
||||
# Maps item to _Vertex object.
|
||||
_vertices: dict[Any, _Vertex]
|
||||
|
||||
def __init__(self) -> None:
|
||||
"""Initialize an empty graph (no vertices or edges)."""
|
||||
self._vertices = {}
|
||||
|
||||
def add_vertex(self, item: Any) -> None:
|
||||
"""Add a vertex with the given item to this graph.
|
||||
|
||||
The new vertex is not adjacent to any other vertices.
|
||||
"""
|
||||
self._vertices[item] = _Vertex(item, set())
|
||||
|
||||
def add_edge(self, item1: Any, item2: Any) -> None:
|
||||
"""Add an edge between the two vertices with the given items in this graph.
|
||||
|
||||
Raise a ValueError if item1 or item2 do not appear as vertices in this graph.
|
||||
|
||||
Preconditions:
|
||||
- item1 != item2
|
||||
"""
|
||||
if item1 in self._vertices and item2 in self._vertices:
|
||||
v1 = self._vertices[item1]
|
||||
v2 = self._vertices[item2]
|
||||
|
||||
# Add the new edge
|
||||
v1.neighbours.add(v2)
|
||||
v2.neighbours.add(v1)
|
||||
else:
|
||||
# We didn't find an existing vertex for both items.
|
||||
raise ValueError
|
||||
|
||||
def connected(self, item1: Any, item2: Any) -> bool:
|
||||
"""Return whether item1 and item2 are connected vertices in this graph.
|
||||
|
||||
Return False if item1 or item2 do not appear as vertices in this graph.
|
||||
|
||||
>>> g = Graph()
|
||||
>>> g.add_vertex(1)
|
||||
>>> g.add_vertex(2)
|
||||
>>> g.add_vertex(3)
|
||||
>>> g.add_vertex(4)
|
||||
>>> g.add_edge(1, 2)
|
||||
>>> g.add_edge(2, 3)
|
||||
>>> g.connected(1, 3)
|
||||
True
|
||||
>>> g.connected(1, 4)
|
||||
False
|
||||
"""
|
||||
if item1 in self._vertices and item2 in self._vertices:
|
||||
v1 = self._vertices[item1]
|
||||
return v1.check_connected(item2, set()) # Pass in an empty "visited" set
|
||||
else:
|
||||
return False
|
||||
|
||||
def get_connected_component(self, item: Any) -> set:
|
||||
"""Return a set of all ITEMS connected to the given item in this graph.
|
||||
|
||||
Raise a ValueError if item does not appears as a vertex in this graph.
|
||||
|
||||
>>> g = Graph()
|
||||
>>> for i in range(0, 5):
|
||||
... g.add_vertex(i)
|
||||
>>> g.add_edge(0, 1)
|
||||
>>> g.add_edge(1, 2)
|
||||
>>> g.add_edge(1, 3)
|
||||
>>> g.add_edge(2, 3)
|
||||
>>> g.get_connected_component(0) == {0, 1, 2, 3}
|
||||
True
|
||||
|
||||
Note: we've implemented this method for you, and you should not change it.
|
||||
Instead, your task is to implement _Vertex.get_connected_component below.
|
||||
"""
|
||||
if item not in self._vertices:
|
||||
raise ValueError
|
||||
else:
|
||||
return self._vertices[item].get_connected_component(set())
|
||||
|
||||
def in_cycle(self, item: Any) -> bool:
|
||||
"""Return whether the given item is in a cycle in this graph.
|
||||
|
||||
Return False if item does not appears as a vertex in this graph.
|
||||
|
||||
KEY OBSERVATION. A vertex v is in a cycle if and only if:
|
||||
v has two distinct neighbours u and w that are connected to each other
|
||||
by a path that doesn't use v.
|
||||
|
||||
>>> g = Graph()
|
||||
>>> for i in range(0, 5):
|
||||
... g.add_vertex(i)
|
||||
>>> g.add_edge(0, 1)
|
||||
>>> g.add_edge(1, 2)
|
||||
>>> g.add_edge(1, 3)
|
||||
>>> g.add_edge(2, 3)
|
||||
>>> g.in_cycle(1)
|
||||
True
|
||||
>>> g.in_cycle(0)
|
||||
False
|
||||
>>> g.add_edge(4, 0)
|
||||
>>> g.in_cycle(0)
|
||||
False
|
||||
|
||||
Implementation notes:
|
||||
1. This method should call _Vertex.check_connected (following the above
|
||||
description).
|
||||
2. Don't try to make this method recursive, or copy and paste the implementation
|
||||
of _Vertex.check_connected! That's not necessary here.
|
||||
"""
|
||||
# Does not exist
|
||||
if item not in self._vertices:
|
||||
return False
|
||||
v = self._vertices[item]
|
||||
|
||||
# Combinations
|
||||
for u in v.neighbours:
|
||||
for w in v.neighbours:
|
||||
# Distinct combinations
|
||||
if u == w or u == v or w == v:
|
||||
continue
|
||||
|
||||
if u.check_connected(w.item, {v}):
|
||||
return True
|
||||
return False
|
||||
|
||||
|
||||
class _Vertex:
|
||||
"""A vertex in a graph.
|
||||
|
||||
Instance Attributes:
|
||||
- item: The data stored in this vertex.
|
||||
- neighbours: The vertices that are adjacent to this vertex.
|
||||
|
||||
Representation Invariants:
|
||||
- self not in self.neighbours
|
||||
- all(self in u.neighbours for u in self.neighbours)
|
||||
"""
|
||||
item: Any
|
||||
neighbours: set[_Vertex]
|
||||
|
||||
def __init__(self, item: Any, neighbours: set[_Vertex]) -> None:
|
||||
"""Initialize a new vertex with the given item and neighbours."""
|
||||
self.item = item
|
||||
self.neighbours = neighbours
|
||||
|
||||
def check_connected(self, target_item: Any, visited: set[_Vertex]) -> bool:
|
||||
"""Return whether this vertex is connected to a vertex corresponding to the target_item,
|
||||
WITHOUT using any of the vertices in visited.
|
||||
|
||||
Preconditions:
|
||||
- self not in visited
|
||||
"""
|
||||
if self.item == target_item:
|
||||
# Our base case: the target_item is the current vertex
|
||||
return True
|
||||
else:
|
||||
visited.add(self) # Add self to the set of visited vertices
|
||||
for u in self.neighbours:
|
||||
if u not in visited: # Only recurse on vertices that haven't been visited
|
||||
if u.check_connected(target_item, visited):
|
||||
return True
|
||||
|
||||
return False
|
||||
|
||||
def get_connected_component(self, visited: set[_Vertex]) -> set:
|
||||
"""Return a set of all ITEMS connected to self by a path that does not use
|
||||
any vertices in visited.
|
||||
|
||||
The items of the vertices in visited CANNOT appear in the returned set.
|
||||
|
||||
Preconditions:
|
||||
- self not in visited
|
||||
|
||||
Implementation notes:
|
||||
1. This can be implemented in a similar way to _Vertex.check_connected.
|
||||
2. This method must be recursive, and will have an implicit base case:
|
||||
when all vertices in self.neighbours are already in visited.
|
||||
3. Use a loop accumulator to store a set of the vertices connected to self.
|
||||
|
||||
>>> g = Graph()
|
||||
>>> for i in range(0, 7):
|
||||
... g.add_vertex(i)
|
||||
>>> g.add_edge(0, 1)
|
||||
>>> g.add_edge(1, 2)
|
||||
>>> g.add_edge(1, 3)
|
||||
>>> g.add_edge(2, 3)
|
||||
>>> g.get_connected_component(1) == {0, 1, 2, 3}
|
||||
True
|
||||
>>> g.add_edge(4, 0)
|
||||
>>> g.get_connected_component(0) == {0, 1, 2, 3, 4}
|
||||
True
|
||||
>>> g.get_connected_component(5)
|
||||
{5}
|
||||
>>> g._vertices[5].get_connected_component({g._vertices[5]})
|
||||
set()
|
||||
>>> g._vertices[6].get_connected_component(set())
|
||||
{6}
|
||||
"""
|
||||
if self in visited:
|
||||
return set()
|
||||
visited.add(self)
|
||||
nums = {self.item}
|
||||
for u in self.neighbours:
|
||||
nums = nums.union(u.get_connected_component(visited))
|
||||
return nums
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
# Note: we are NOT using python_ta.contracts for this prep.
|
||||
# (Feel free to ask why in office hours/Campuswire.)
|
||||
import doctest
|
||||
doctest.testmod()
|
||||
|
||||
import python_ta
|
||||
python_ta.check_all(config={
|
||||
'max-line-length': 100,
|
||||
'disable': ['E1136'],
|
||||
'max-nested-blocks': 4
|
||||
})
|
||||
@@ -1,191 +0,0 @@
|
||||
"""CSC111 Winter 2022 Prep 9: Programming Exercises
|
||||
|
||||
Instructions (READ THIS FIRST!)
|
||||
===============================
|
||||
|
||||
This module contains some functions related to sorting and/or Python lists for practice.
|
||||
In particular, some of these functions give you practice with *index parameters*,
|
||||
which we commonly use to specify that a function should only operate on a part of a list.
|
||||
(This is generally more efficient than requiring the user to create a new list. We'll explor
|
||||
this idea further in lecture this week.)
|
||||
|
||||
Do NOT use recursion for any of these functions.
|
||||
|
||||
We have marked each place you need to write code with the word "TODO".
|
||||
As you complete your work in this file, delete each TODO comment.
|
||||
|
||||
You may add additional doctests, but they will not be graded. You should test your work
|
||||
carefully before submitting it!
|
||||
|
||||
Copyright and Usage Information
|
||||
===============================
|
||||
|
||||
This file is provided solely for the personal and private use of students
|
||||
taking CSC111 at the University of Toronto St. George campus. All forms of
|
||||
distribution of this code, whether as given or with any changes, are
|
||||
expressly prohibited. For more information on copyright for CSC111 materials,
|
||||
please consult our Course Syllabus.
|
||||
|
||||
This file is Copyright (c) 2022 Mario Badr and David Liu.
|
||||
"""
|
||||
|
||||
|
||||
def is_sorted(lst: list) -> bool:
|
||||
"""Return whether lst is sorted.
|
||||
|
||||
Formally, a list `lst` is sorted when for every index i between 0 and len(lst),
|
||||
lst[i] <= lst[i + 1]. Note that empty lists and lists of length 1 are always sorted.
|
||||
|
||||
Do not call `sorted` or `list.sort`, or otherwise sort `lst` in this function.
|
||||
|
||||
>>> is_sorted([2, 7, 3, 4, 5])
|
||||
False
|
||||
>>> is_sorted([2, 3, 4, 5, 7])
|
||||
True
|
||||
>>> is_sorted([-1, 0, 0, 1])
|
||||
True
|
||||
>>> is_sorted([-1, 0, 0, -1])
|
||||
False
|
||||
"""
|
||||
return all(lst[i] <= lst[i + 1] for i in range(len(lst) - 1))
|
||||
|
||||
|
||||
def is_sorted_sublist(lst: list, b: int, e: int) -> bool:
|
||||
"""Return whether the sublist lst[b:e] is sorted.
|
||||
|
||||
Do not create a new list or call is_sorted. Instead, adapt the definition from
|
||||
is_sorted to complete this function.
|
||||
|
||||
Note that if b >= e, then lst[b:e] is an empty list, and so is sorted.
|
||||
|
||||
Preconditions:
|
||||
- 0 <= b < len(lst)
|
||||
- 0 <= e <= len(lst)
|
||||
|
||||
>>> is_sorted_sublist([2, 7, 3, 4, 5], 0, 5) # Equivalent to is_sorted([2, 7, 3, 4, 5])
|
||||
False
|
||||
>>> is_sorted_sublist([2, 7, 3, 4, 5], 2, 5) # Equivalent to is_sorted([2, 7, 3, 4, 5][2:5])
|
||||
True
|
||||
>>> is_sorted_sublist([-1, 0, 0, -1], 0, 3)
|
||||
True
|
||||
>>> is_sorted_sublist([-1, 0, 0, -1], 0, 4)
|
||||
False
|
||||
"""
|
||||
return all(lst[i] <= lst[i + 1] for i in range(b, e - 1))
|
||||
|
||||
|
||||
def min_index(lst: list) -> int:
|
||||
"""Return the index of the smallest element of lst.
|
||||
|
||||
In the case of ties, return the smaller index (i.e., the index that appears first).
|
||||
|
||||
Preconditions:
|
||||
- lst != []
|
||||
|
||||
>>> min_index([-10, 7, 3, 5])
|
||||
0
|
||||
>>> min_index([7, 7, 7, 7])
|
||||
0
|
||||
>>> min_index([8, 7, 7, 7])
|
||||
1
|
||||
>>> min_index([8, 7, 7, -1])
|
||||
3
|
||||
>>> min_index([99999999])
|
||||
0
|
||||
"""
|
||||
lowest = lst[0]
|
||||
index = 0
|
||||
|
||||
for i in range(len(lst)):
|
||||
if lst[i] < lowest:
|
||||
lowest = lst[i]
|
||||
index = i
|
||||
|
||||
return index
|
||||
|
||||
|
||||
def min_index_sublist(lst: list, b: int, e: int) -> int:
|
||||
"""Return the index of the smallest item in lst[b:e].
|
||||
|
||||
In the case of ties, return the smaller index (i.e., the index that appears first).
|
||||
|
||||
This is similar to min_index, except we are only considering the elements
|
||||
with indexes between b and e - 1, inclusive.
|
||||
|
||||
Preconditions:
|
||||
- 0 <= b < e <= len(lst)
|
||||
|
||||
>>> min_index_sublist([-10, 7, 3, 5], 0, 4)
|
||||
0
|
||||
>>> min_index_sublist([-10, 7, 3, 5], 1, 3)
|
||||
2
|
||||
"""
|
||||
lowest = lst[b]
|
||||
index = b
|
||||
|
||||
for i in range(b, e):
|
||||
if lst[i] < lowest:
|
||||
lowest = lst[i]
|
||||
index = i
|
||||
|
||||
return index
|
||||
|
||||
|
||||
def cycle(lst: list) -> None:
|
||||
"""Rearrange the elements of lst by shifting every element one spot to the right.
|
||||
|
||||
The last list element moves to the front of the list.
|
||||
|
||||
Preconditions:
|
||||
- lst != []
|
||||
|
||||
>>> lst = [10, 3, 5, 7, 9000]
|
||||
>>> cycle(lst)
|
||||
>>> lst
|
||||
[9000, 10, 3, 5, 7]
|
||||
|
||||
Implementation notes:
|
||||
- Do NOT call any list methods; instead, move the elements by assigning to indexes
|
||||
(e.g., lst[1] = list[0] or lst[i] = lst[i + 1]).
|
||||
"""
|
||||
last = lst[-1]
|
||||
for i in reversed(range(len(lst))):
|
||||
lst[i] = lst[i - 1]
|
||||
lst[0] = last
|
||||
|
||||
|
||||
def cycle_sublist(lst: list, b: int, e: int) -> None:
|
||||
"""Rearrange the elements of lst[b:e] by shifting every element one spot to the right.
|
||||
|
||||
The element lst[e - 1] moves to index b.
|
||||
|
||||
Preconditions:
|
||||
- 0 <= b < e <= len(lst)
|
||||
|
||||
>>> lst = [10, 3, 5, 7, 9000]
|
||||
>>> cycle_sublist(lst, 0, 5) # Equivalent to cycle(lst)
|
||||
>>> lst
|
||||
[9000, 10, 3, 5, 7]
|
||||
>>> lst2 = [10, 3, 5, 7, 9000]
|
||||
>>> cycle_sublist(lst2, 1, 4)
|
||||
>>> lst2
|
||||
[10, 7, 3, 5, 9000]
|
||||
"""
|
||||
last = lst[e - 1]
|
||||
for i in reversed(range(b, e)):
|
||||
lst[i] = lst[i - 1]
|
||||
lst[b] = last
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
import python_ta.contracts
|
||||
python_ta.contracts.check_all_contracts()
|
||||
|
||||
import doctest
|
||||
doctest.testmod()
|
||||
|
||||
import python_ta
|
||||
python_ta.check_all(config={
|
||||
'max-line-length': 100,
|
||||
'disable': ['E1136']
|
||||
})
|
||||
Reference in New Issue
Block a user