ClassicComputerScienceProblemsInPython | Source Code for the Book Classic Computer Science Problems in Python | Learning library

by davecom Python Version: Current License: Apache-2.0

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | ClassicComputerScienceProblemsInPython Summary

ClassicComputerScienceProblemsInPython is a Python library typically used in Tutorial, Learning, Deep Learning, Example Codes applications. ClassicComputerScienceProblemsInPython has no vulnerabilities, it has a Permissive License and it has medium support. However ClassicComputerScienceProblemsInPython has 2 bugs and it build file is not available. You can download it from GitHub.

You can find general questions and descriptive information about the book on the Classic Computer Science Problems website. Also, feel free to reach out to me on Twitter, @davekopec. If you think you found an error in the source code, please open an issue up here on GitHub.

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Quality

Security

License

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Support

ClassicComputerScienceProblemsInPython has a medium active ecosystem.

It has 866 star(s) with 355 fork(s). There are 42 watchers for this library.

It had no major release in the last 6 months.

There are 1 open issues and 12 have been closed. On average issues are closed in 4 days. There are 1 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of ClassicComputerScienceProblemsInPython is current.

Quality

ClassicComputerScienceProblemsInPython has 2 bugs (1 blocker, 0 critical, 1 major, 0 minor) and 31 code smells.

Security

ClassicComputerScienceProblemsInPython has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

ClassicComputerScienceProblemsInPython code analysis shows 0 unresolved vulnerabilities.

There are 14 security hotspots that need review.

License

ClassicComputerScienceProblemsInPython is licensed under the Apache-2.0 License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

ClassicComputerScienceProblemsInPython releases are not available. You will need to build from source code and install.

ClassicComputerScienceProblemsInPython has no build file. You will be need to create the build yourself to build the component from source.

ClassicComputerScienceProblemsInPython saves you 887 person hours of effort in developing the same functionality from scratch.

It has 2029 lines of code, 231 functions and 51 files.

It has medium code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed ClassicComputerScienceProblemsInPython and discovered the below as its top functions. This is intended to give you an instant insight into ClassicComputerScienceProblemsInPython implemented functionality, and help decide if they suit your requirements.

Generate a directed graph from a directed graph
Compute the MST shortest path of a graph
Explore an ASTAR
Generate a knapsack table
BFS search
Perform the DFS search
Returns the backtracking search
Returns whether the given variable is consistent with the given assignment
Decompress the bitstring
Run the iteration
Replaces the population and replace the population
Mutate individual individuals
Checks if the given gene contains the given key
Run clustering
Generate centroids
Assign the points to the closest centroids
Clear the grid
Calculate the pi
Convert a path to a list of weighted edges
Find the best move in the given board
Convert a string to a list of codons
Validate inputs against expecteds
Normalize the zscore
Hanoi index
Return a random data point
Return Fibonacci fibonacci

Get all kandi verified functions for this library.

ClassicComputerScienceProblemsInPython Key Features

No Key Features are available at this moment for ClassicComputerScienceProblemsInPython.

ClassicComputerScienceProblemsInPython Examples and Code Snippets

No Code Snippets are available at this moment for ClassicComputerScienceProblemsInPython.

Community Discussions

Trending Discussions on ClassicComputerScienceProblemsInPython

Nested List Comprehension - Double Iteration - Classic CS Problems in Python - Chapter 3 - Word Search

QUESTION

Nested List Comprehension - Double Iteration - Classic CS Problems in Python - Chapter 3 - Word Search

Asked 2019-Sep-15 at 06:28

I am going through David Kopec's Classic Computer Science Problems in Python and in chapter 3 - came across this list comprehension.

https://github.com/davecom/ClassicComputerScienceProblemsInPython/blob/master/Chapter3/word_search.py

...

ANSWER

Answered 2019-Sep-15 at 06:28

test_list_comp = [locs for values in test.values() for locs in values]

Source https://stackoverflow.com/questions/57941578

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install ClassicComputerScienceProblemsInPython

You can download it from GitHub.
You can use ClassicComputerScienceProblemsInPython like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

You can find general questions and descriptive information about the book on the Classic Computer Science Problems website. Also, feel free to reach out to me on Twitter, @davekopec. If you think you found an error in the source code, please open an issue up here on GitHub.

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