学习笔记之Problem Solving with Algorithms and Data Structures using Python

Problem Solving with Algorithms and Data Structures using Python — Problem Solving with Algorithms and Data Structures

  • By Brad Miller and David Ranum, Luther College
  • http://interactivepython.org/runestone/static/pythonds/index.html
  • https://runestone.academy/runestone/static/pythonds/index.html

Introduction · python-data-structure-cn

  • https://facert.gitbooks.io/python-data-structure-cn/

Problem Solving with Algorithms and Data Structures Using Python SECOND EDITION: Bradley N. Miller, David L. Ranum: 9781590282571: Amazon.com: Books

  • https://www.amazon.com/Problem-Solving-Algorithms-Structures-Python/dp/1590282574
  • THIS TEXTBOOK is about computer science. It is also about Python. However, there is much more. The study of algorithms and data structures is central to understanding what computer science is all about. Learning computer science is not unlike learning any other type of difficult subject matter. The only way to be successful is through deliberate and incremental exposure to the fundamental ideas. A beginning computer scientist needs practice so that there is a thorough understanding before continuing on to the more complex parts of the curriculum. In addition, a beginner needs to be given the opportunity to be successful and gain confidence. This textbook is designed to serve as a text for a first course on data structures and algorithms, typically taught as the second course in the computer science curriculum. Even though the second course is considered more advanced than the first course, this book assumes you are beginners at this level. You may still be struggling with some of the basic ideas and skills from a first computer science course and yet be ready to further explore the discipline and continue to practice problem solving. We cover abstract data types and data structures, writing algorithms, and solving problems. We look at a number of data structures and solve classic problems that arise. The tools and techniques that you learn here will be applied over and over as you continue your study of computer science.

  • 1.8.2. Built-in Collection Data Types 
Table 3: Methods Provided by Lists in Python
Method Name Use Explanation
append alist.append(item) Adds a new item to the end of a list
insert alist.insert(i,item) Inserts an item at the ith position in a list
pop alist.pop() Removes and returns the last item in a list
pop alist.pop(i) Removes and returns the ith item in a list
sort alist.sort() Modifies a list to be sorted
reverse alist.reverse() Modifies a list to be in reverse order
del del alist[i] Deletes the item in the ith position
index alist.index(item) Returns the index of the first occurrence of item
count alist.count(item) Returns the number of occurrences of item
remove alist.remove(item) Removes the first occurrence of item

 

Table 4: Methods Provided by Strings in Python
Method Name Use Explanation
center astring.center(w) Returns a string centered in a field of size w
count astring.count(item) Returns the number of occurrences of item in the string
ljust astring.ljust(w) Returns a string left-justified in a field of size w
lower astring.lower() Returns a string in all lowercase
rjust astring.rjust(w) Returns a string right-justified in a field of size w
find astring.find(item) Returns the index of the first occurrence of item
split astring.split(schar) Splits a string into substrings at schar

 

Table 5: Operations on a Set in Python
Operation Name Operator Explanation
membership in Set membership
length len Returns the cardinality of the set
| aset otherset Returns a new set with all elements from both sets
& aset otherset Returns a new set with only those elements common to both sets
- aset otherset Returns a new set with all items from the first set not in second
<= aset <= otherset Asks whether all elements of the first set are in the second

 

Table 6: Methods Provided by Sets in Python
Method Name Use Explanation
union aset.union(otherset) Returns a new set with all elements from both sets
intersection aset.intersection(otherset) Returns a new set with only those elements common to both sets
difference aset.difference(otherset) Returns a new set with all items from first set not in second
issubset aset.issubset(otherset) Asks whether all elements of one set are in the other
add aset.add(item) Adds item to the set
remove aset.remove(item) Removes item from the set
pop aset.pop() Removes an arbitrary element from the set
clear aset.clear() Removes all elements from the set

 

Table 7: Operators Provided by Dictionaries in Python
Operator Use Explanation
[] myDict[k] Returns the value associated with k, otherwise its an error
in key in adict Returns True if key is in the dictionary, False otherwise
del del adict[key] Removes the entry from the dictionary

 

Table 8: Methods Provided by Dictionaries in Python
Method Name Use Explanation
keys adict.keys() Returns the keys of the dictionary in a dict_keys object
values adict.values() Returns the values of the dictionary in a dict_values object
items adict.items() Returns the key-value pairs in a dict_items object
get adict.get(k) Returns the value associated with kNone otherwise
get adict.get(k,alt) Returns the value associated with kalt otherwise
  • 1.9. Input and Output
    • aName = input('Please enter your name: ')

转载于:https://www.cnblogs.com/pegasus923/p/10454395.html

你可能感兴趣的:(学习笔记之Problem Solving with Algorithms and Data Structures using Python)