Code Style & Documentation

Q&A

Q: What is the difference between assertEqual and assertTrue?
A: assertEqual takes in two inputs and checks that the first input is equal to the second; assertTrue expects that whatever is in the parentheses evaluates to True

Course Announcements

Due this week:

• CL9 (optional, for 2 pts EC…but you should do it to get testing practice)

• E1 or E2 retake (optional)

• Final Exam (6/7-6/13)

• Post-course assessement (due 6/13; required; will be available Friday)

Notes:

• Please complete your SETs

• Handful of questions about exam retake:

  • Your final E1/E2 score after retake is 75% of your highest and 25% of your lowest?

  • What does that math look like? Well, let’s say you got a 9/12.5 originally and you get 11.5/12.5 on the retake: 0.25*9 + 0.75*11.5 == 10.88 (+1.88 to your final grade)

  • Could my score go down? Yes

  • Sign up on PrairieTest; take in same location (TTC-CBTF)

• E2 Summary:

  • Class Average: 70%

  • 31/580 (5%) earned perfect marks

  • 11% higher average for those coming to class than those who didn’t

• Do you have to take the final exam if you took the course P/NP and already have >=70 pts? No.

  • If you have a 70% currently, do you have to take the exam? YES!

• Canvas Gradebook will be updated by EOD Friday with Lecture EC and Oral Exam 2 score

• Office Hours end this Friday (no office hours during finals week; I will monitor Ed/email)

Final Exam (13 pts; 1h50min)

• 13 MC (6.5 pts total; 0.5 pt each)

  • Topics: Variables, Operators, Functions, Conditionals, Loops, Classes, Command Line, Imports/File Paths, Scientific Computing (2), Code Testing, Documentation, Code Style

• 2 Code Reading & Debugging Qs (3.5 pts)

  • Function (1.5 pts)

  • Class (2 pts)

• Testing Questions (3pts; 1.5 pt each unittest)

  • 1 uses pandas

Notes:

• No mini-project

• Practice exam will be very good practice for all of these

• Information Provided:

  • pandas functions/methods

  • unittest framework w/ list of assert statements discussed in class

Today’s Plan

• Code Style

  • readability

  • PEP8 (style guides)

  • linters

• Documentation

  • code comments

  • docstrings

• (Revisiting) testing

• versioning

Code Style

Code Readability (API)

“Code is more often read than written” - Guido van Rossum

So: code should be written to be readable by humans.

Note: one of those humans is future you.

The Zen of Python

import this

Writing Readable Code

So how do we write good code for humans?

• Use good structure

• Use good naming

• Use code comments and include documentation

Good Structure

If you design your program using separate functions for each task, avoid copying + pasting (functions and loops instead), and consider structure beforehand, you’ll be set up for success

Good Naming

Clear names are for humans. The computer doesn’t care, but you and others reading your code do.

Code comments & Documentation

Helpful comments and documentation take your code to the next level. The final piece in the trifecta of readable code!

Good code has good documentation - but code documentation should not be used to try and fix unclear names, or bad structure.

Rather, comments should add any additional context and information that helps explain what the code is, how it works, and why it works that way.

Motivation: Think-Pair-Share

What does the following code do?

def ff(jj):
    oo = []; jj = list(jj) 
    for ii in jj: oo.append(str(ord(ii)))
    return '+'.join(oo)
ff('Hello World.')

• A) Returns unicode code points, as a list

• B) Encodes a string as a cypher, returning a string of alphabetical characters

• C) Returns unicode code points, as a string

• D) Encodes inputs alphabetical characters, returned as a list

• E) This code will fail

Improvement Considerations (Style)

• Structural considerations: indentations & spacing

• Improved naming: functions & variables

def convert_to_unicode(input_string):
    string = []
    input_list = list(input_string)
      
    for character in input_list: 
        string.append(str(ord(character)))
        
    output_string = '+'.join(string)
    return output_string

convert_to_unicode('Hello World.')

• A) Returns unicode code points, as a list

• B) Encodes a string as a cypher, returning a string of alphabetical characters

• C) Returns unicode code points, as a string

• D) Encodes inputs alphabetical characters, returned as a list

• E) This code will fail

Code Style Review

Or: How to be Pythonic

Reasons to be Pythonic:

• user friendly for humans

• extra work up-front on the developers (pays off on the long run)

• best to practice this early on (I promise!)

Style Guides

Coding style refers to a set of conventions for how to write good code.

Consistency is the goal. Rules help us achieve consistency.

Much of this will apply to other programming languages, so it’s good to learn…regardless of language.

Some of these Code Style notes will be more specific to Python, however.

Python Enhancement Proposals (PEPs)

Python PEPs are proposals for how something should be / work in the Python programming language.

These are written by the people responsible for the Python Programming language.

PEP are voted on before incorporation.

PEP8

PEP8 is an accepted proposal that outlines the style guide for Python.

Defines the style guide for Pythonistas (people who code in Python).

Code Style: Structure

• blank lines

• indentaion

• spacing

• length <- NEW

• imports

Blank Lines

• Use 2 blank lines between functions & classes, and 1 between methods

• Use 1 blank line between segments to indicate logical structure

Indentation

Use spaces to indicate indentation levels, with each level defined as 4 spaces.

Spacing

• Put one (and only one) space between each element

• Index and assignment don’t have a space between opening & closing ‘()’ or ‘[]’

my_list = ['a', 'b', 'c']
# avoid having space after list and before square brackets
my_list [0]
# instead do this:
my_list[0]

Line Length (NEW)

• PEP8 recommends that each line be at most 79 characters long

Computers used to require this.

But, super long lines are hard to read at a glance.

Multi-Line

my_long_list = [1, 2, 3, 4, 5,
                6, 7, 8, 9, 10]

# Note: you can explicitly indicate a new line with '\'
my_string = 'Python is ' + \
            'a pretty great language.'

One Statement Per Line

• While you can condense multiple statements into one line, you usually shouldn’t.

# Badness
for i in [1, 2, 3]: print(i**2 + i%2)

# Goodness
for i in [1, 2, 3]:
    print(i**2 + i%2)

Imports

• Import one module per line

• Avoid * imports

• Use the import order: standard library; 3rd party packages; local / custom code

# Badness
from numpy import *

import os, sys

# Goodness
import os
import sys

import numpy as np

Note: If you don’t know how to import a local/custom module, figure that out this week in office hours.

Naming (review)

Valid Names

• Use descriptive names for all modules, variables, functions and classes, that are longer than 1 character

Naming Style

• CapWords (leading capitals, no separation) for Classes

• snake_case (all lowercase, underscore separator) for variables, functions, and modules

Code Comments

Inline code comments

Inline code comments should use #, and be written at the same indentation level of the code it describes.

How to use comments:

• Generally:

  • focus on the how and why, over literal ‘what is the code’

  • explain any context needed to understand the task at hand

  • give a broad overview of what approach you are taking to perform the task

  • if you’re using any unusual approaches, explain what they are, and why you’re using them

• Comments need to be maintained - make sure to keep them up to date

Bad Comments

# This is a loop that iterates over elements in a list
for element in list_of_elements:
    pass

Good Comments

# Because of X, we will use approach Y to do Z
for element in list_of_elements:
    # comment for code block
    pass

Code Style: Comments

Out-of-date comments are worse than no comments at all.

Keep your comments up-to-date.

Block comments

• apply to some (or all) code that follows them

• are indented to the same level as that code.

• Each line of a block comment starts with a # and a single space

# Badness
import random

def week_10():
# help try to destress students by picking one thing from the following list using random
    statements = ["You've totally got this!","You're so close!","You're going to do great!","Remember to take breaks!","Sleep, water, and food are really important!"]
    out = random.choice(statements)
    return out

week_10()

# Goodness
def week_10():
    
    # Randomly pick from list of de-stressing statements
    # to help students as they finish the quarter.
    statements = ["You've totally got this!", 
                  "You're so close!", 
                  "You're going to do great!",
                  "Remember to take breaks!",
                  "Sleep, water, and food are really important!"]
    
    out = random.choice(statements)
    
    return out

week_10()

Inline comments

• to be used sparingly

• to be separated by at least two spaces from the statement

• start with a # and a single space

# Badness
week_10()#words of encouragement

# Goodness
week_10()  # words of encouragement

Activity: Code Style

Complete the Google Form: https://forms.gle/aS3VoiKuT8vNHEgK9

Improve the code style of the provided class, using PEP8 guidelines:

#original
class CoffeeTracker:
    def __init__(self,n):
        self.n=n
        self.ts=0.0
        self.tc=0
        self.ap=0.0
    def buy_coffee(self,p):
        for p1 in p:self.ts+=p1;self.tc+=1
        if self.tc>0:self.ap=self.ts/self.tc
        print(f"{self.n} bought {self.tc} coffees.")
        print(f"Average price per coffee: ${self.ap:.2f}")

Suggested improvements:

• meaningful variable names (n -> name; ts -> total_spent; tc -> total_coffees)

• line spacing between methods

• multi-line statements (for/if) -> more than one line

• spacing operators (self,n -> self, n; around other operators )

#improved
class CoffeeTracker:
    
    def __init__(self, name):
        self.name = name
        self.total_spent = 0.0
        self.total_coffees = 0
        self.avg_price = 0.0
        
    def buy_coffee(self, prices):
        
        for price in prices:
            self.total_spent += price
            self.total_coffees += 1
            
        if self.tc>0:
            self.avg_price = self.total_spent/self.total_coffees
            
        print(f"{self.name} bought {self.total_coffees} coffees.")
        print(f"Average price per coffee: ${self.avg_price:.2f}")

Code Documentation

Code documentation is text that accompanies and/or is embedded within a software project, that explains what the code is and how to use it.

Stuff written for humans in human language to help the humans.

Code Comments vs. Documentation

Comments

Comments are string literals written directly in the code, typically directed at developers - people reading and potentially writing the code.

Documentation

Documentation are descriptions and guides written for code users.

Returning to convert_to_unicode()

That example from before…Improvement Considerations:

• Structural considerations: indentations & spacing

• Improved naming: functions & variables

• Add Comments within code

• Proper Documentation!

def convert_to_unicode(input_string):
    """Converts an input string into a string containing the unicode code points.
    
    Parameters
    ----------
    input_string : string
        String to convert to code points
        
    Returns
    -------
    output_string : string
        String containing the code points for the input string.
    """ 
    
    string = []
    # converting input string to list to make it iterable
    input_list = list(input_string)

    for character in input_list: 
        string.append(str(ord(character)))
        
    output_string = '+'.join(string)
    return output_string

convert_to_unicode('Hello World.')

Docstrings

Docstrings are in-code text that describe modules, classes and functions. They describe the operation of the code.

Numpy style docs

Numpy style docs are a particular specification for docstrings.

Example Docstring

def add(num1, num2):
    """Add two numbers together. 
    
    Parameters
    ----------
    num1 : int or float
        The first number, to be added. 
    num2 : int or float
        The second number, to be added.
    
    Returns
    -------
    answer : float
        The result of the addition. 
    """
    
    answer = num1 + num2
    
    return answer

Docstrings

• multi-line string that describes what’s going on

• starts and ends with triple quotes """

• one sentence overview at the top - the task/goal of function

• Parameters : description of function arguments, keywords & respective types

• Returns : explanation of returned values and their types

Docstrings are available to you outside of the source code.

Note: ChatGPT is pretty good at generating docstrings…

Docstrings are available through the code

add?

# The `help` function prints out the `docstring` 
# of an object (module, function, class)
help(add)

__doc__

# Docstrings get stored as the `__doc__` attribute
# can also be accessed from there
print(add.__doc__)

class Person:

    def __init__(self, name, age):
        self.name = name
        self.age = age

    def birthday(self):
        self.age += 1
        return 'Happy Birthday!'

# with docstring
class Person:
    """
    A class to represent a person with a name and age.

    Attributes
    ----------
    name : str
        The name of the person.
    age : int
        The age of the person.

    Methods
    -------
    birthday():
        Increments the person's age by one and returns a birthday greeting.
    """

    def __init__(self, name, age):
        self.name = name
        self.age = age

    def birthday(self):
        """
        Increments the person's age by one year.

        Returns
        -------
        str
            A birthday greeting message.
        """
        self.age += 1
        return 'Happy Birthday!'

Final Exam & Documentation

Will I need to write docstrings on the final exam?

No…not from scratch (but you need to know what they are and be able to read/understand one). LLMs are really good at this, so I won’t make you write them by hand on the exam.

Activity: Code Testing (Revisited)

Complete the Google Form: https://forms.gle/jWDmi5Zokg5uXD197

We now have this nicely-styled and documented function. How could we use unittest for this?

def convert_to_unicode(input_string):
    """Converts an input string into a string containing the unicode code points.
    
    Parameters
    ----------
    input_string : string
        String to convert to code points
        
    Returns
    -------
    output_string : string
        String containing the code points for the input string.
    """ 
    
    string = []
    # coverting input string to list to make it iterable
    input_list = list(input_string)
      
    for character in input_list: 
        string.append(str(ord(character)))
        
    output_string = '+'.join(string)
    return output_string

convert_to_unicode('abc')

'97+98+99'

Below is an example of the unittest framework I'd provide on the final exam:

import unittest

class TestConvertToUnicode(unittest.TestCase):

    output = convert_to_unicode('abc')
    
    def test_output_type(self):
        self.assertIsInstance(self.output, str)
        
    def test_length(self):
        self.assertEqual(8, len(convert_to_unicode('abc')))
            
    def test_output(self):
        self.assertEqual('97+98+99', convert_to_unicode('abc'))
        
if __name__ == '__main__':
    suite = unittest.TestLoader().loadTestsFromTestCase(TestConvertToUnicode)
    unittest.TextTestRunner(verbosity=2).run(suite)

test_length (__main__.TestConvertToUnicode.test_length) ... ok
test_output (__main__.TestConvertToUnicode.test_output) ... ok
test_output_type (__main__.TestConvertToUnicode.test_output_type) ... ok

----------------------------------------------------------------------
Ran 3 tests in 0.003s

OK

NOTE: Below this is not tested on your final exam.

Documentation for a Software Project

Documentation Files:

• A README is a file that provides an overview of the project to potential users and developers

• A LICENSE file specifies the license under which the code is available (the terms of use)

• An API Reference is a collection of the docstrings, listing public interfaces, parameters and return values

• Tutorials and/or Examples show examples and tutorials for using the codebase

Documentation Sites

Documentation sites are a host of a package's documentation, for code users.

Example: Function Documentation

numpy.array : https://docs.scipy.org/doc/numpy/reference/generated/numpy.array.html

Example: Package Documentation

scikit learn (sklearn) : https://scikit-learn.org/stable/index.html

Linters

A linter is a tool that analyzes code for both programmatic errors and stylistic issues.

pylint is available from Anaconda to check this for you. (Not available on PrairieLearn.)

# to install on your computer
!pip install --user pylint

Think-Pair-Share

How many PEP8 violations can you find in this code?

def MyFunction(input_num):
    
    my_list = [0,1,2,3]
    if 1 in my_list: ind = 1
    else:
      ind = 0
    qq = []
    for i in my_list [ind:]:
        qq.append(input_num/i)
    return qq

list here

• conditional (if) -> multiline

• spacing with indexing

• qq -> good variable naming

• spacing for value in my_list (spaces after commas)

• function name is not snake case

# Let's fix this code
def output_nums(input_num):
    
    my_list = [0, 1, 2, 3]
    
    if 1 in my_list: 
        ind = 1
    else:
        ind = 0
        
    output_list = []
    for i in my_list[ind:]:
        output_list.append(input_num/i)
        
    return output_list

# check using pylint
!pylint linter_example.py

Software Versioning

When you make changes to the software you’ve released into the world, you have to change the version of that software to let people know changes have occurred.

Versioning Schemes

The rules, if you’re new to this can be dizzying, so we’ll simplify for now:

• <MAJOR>.<MINOR>

  • i.e. 1.3

• <MAJOR>.<MINOR>.<MAINTENANCE>

  • i.e. 1.3.1

• <MAJOR> - increase by 1 w/ incompatible API changes

• <MINOR> - increase by 1 w/ added functionality in a backwards-compatible manner

• <MAINTENANCE> - (aka patch) increase by 1 w/ backwards-compatible bug fixes.

# see version information
import pandas as pd
pd.__version__

'2.2.3'

In Python package development… when <MAJOR> == 0, suggests a package in development

# see version information
!pip show pandas

Name: pandas
Version: 2.2.3
Summary: Powerful data structures for data analysis, time series, and statistics
Home-page: https://pandas.pydata.org
Author: 
Author-email: The Pandas Development Team <pandas-dev@python.org>
License: BSD 3-Clause License

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--------------------------------------------------------------------------------
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----------------------------------------------------------------------
Copyright © 2005-2020 Rich Felker, et al.

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"Software"), to deal in the Software without restriction, including
without limitation the rights to use, copy, modify, merge, publish,
distribute, sublicense, and/or sell copies of the Software, and to
permit persons to whom the Software is furnished to do so, subject to
the following conditions:

The above copyright notice and this permission notice shall be
included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.
IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY
CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,
TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE
SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
----------------------------------------------------------------------

Authors/contributors include:

A. Wilcox
Ada Worcester
Alex Dowad
Alex Suykov
Alexander Monakov
Andre McCurdy
Andrew Kelley
Anthony G. Basile
Aric Belsito
Arvid Picciani
Bartosz Brachaczek
Benjamin Peterson
Bobby Bingham
Boris Brezillon
Brent Cook
Chris Spiegel
Clément Vasseur
Daniel Micay
Daniel Sabogal
Daurnimator
David Carlier
David Edelsohn
Denys Vlasenko
Dmitry Ivanov
Dmitry V. Levin
Drew DeVault
Emil Renner Berthing
Fangrui Song
Felix Fietkau
Felix Janda
Gianluca Anzolin
Hauke Mehrtens
He X
Hiltjo Posthuma
Isaac Dunham
Jaydeep Patil
Jens Gustedt
Jeremy Huntwork
Jo-Philipp Wich
Joakim Sindholt
John Spencer
Julien Ramseier
Justin Cormack
Kaarle Ritvanen
Khem Raj
Kylie McClain
Leah Neukirchen
Luca Barbato
Luka Perkov
M Farkas-Dyck (Strake)
Mahesh Bodapati
Markus Wichmann
Masanori Ogino
Michael Clark
Michael Forney
Mikhail Kremnyov
Natanael Copa
Nicholas J. Kain
orc
Pascal Cuoq
Patrick Oppenlander
Petr Hosek
Petr Skocik
Pierre Carrier
Reini Urban
Rich Felker
Richard Pennington
Ryan Fairfax
Samuel Holland
Segev Finer
Shiz
sin
Solar Designer
Stefan Kristiansson
Stefan O'Rear
Szabolcs Nagy
Timo Teräs
Trutz Behn
Valentin Ochs
Will Dietz
William Haddon
William Pitcock

Portions of this software are derived from third-party works licensed
under terms compatible with the above MIT license:

The TRE regular expression implementation (src/regex/reg* and
src/regex/tre*) is Copyright © 2001-2008 Ville Laurikari and licensed
under a 2-clause BSD license (license text in the source files). The
included version has been heavily modified by Rich Felker in 2012, in
the interests of size, simplicity, and namespace cleanliness.

Much of the math library code (src/math/* and src/complex/*) is
Copyright © 1993,2004 Sun Microsystems or
Copyright © 2003-2011 David Schultz or
Copyright © 2003-2009 Steven G. Kargl or
Copyright © 2003-2009 Bruce D. Evans or
Copyright © 2008 Stephen L. Moshier or
Copyright © 2017-2018 Arm Limited
and labelled as such in comments in the individual source files. All
have been licensed under extremely permissive terms.

The ARM memcpy code (src/string/arm/memcpy.S) is Copyright © 2008
The Android Open Source Project and is licensed under a two-clause BSD
license. It was taken from Bionic libc, used on Android.

The AArch64 memcpy and memset code (src/string/aarch64/*) are
Copyright © 1999-2019, Arm Limited.

The implementation of DES for crypt (src/crypt/crypt_des.c) is
Copyright © 1994 David Burren. It is licensed under a BSD license.

The implementation of blowfish crypt (src/crypt/crypt_blowfish.c) was
originally written by Solar Designer and placed into the public
domain. The code also comes with a fallback permissive license for use
in jurisdictions that may not recognize the public domain.

The smoothsort implementation (src/stdlib/qsort.c) is Copyright © 2011
Valentin Ochs and is licensed under an MIT-style license.

The x86_64 port was written by Nicholas J. Kain and is licensed under
the standard MIT terms.

The mips and microblaze ports were originally written by Richard
Pennington for use in the ellcc project. The original code was adapted
by Rich Felker for build system and code conventions during upstream
integration. It is licensed under the standard MIT terms.

The mips64 port was contributed by Imagination Technologies and is
licensed under the standard MIT terms.

The powerpc port was also originally written by Richard Pennington,
and later supplemented and integrated by John Spencer. It is licensed
under the standard MIT terms.

All other files which have no copyright comments are original works
produced specifically for use as part of this library, written either
by Rich Felker, the main author of the library, or by one or more
contibutors listed above. Details on authorship of individual files
can be found in the git version control history of the project. The
omission of copyright and license comments in each file is in the
interest of source tree size.

In addition, permission is hereby granted for all public header files
(include/* and arch/*/bits/*) and crt files intended to be linked into
applications (crt/*, ldso/dlstart.c, and arch/*/crt_arch.h) to omit
the copyright notice and permission notice otherwise required by the
license, and to use these files without any requirement of
attribution. These files include substantial contributions from:

Bobby Bingham
John Spencer
Nicholas J. Kain
Rich Felker
Richard Pennington
Stefan Kristiansson
Szabolcs Nagy

all of whom have explicitly granted such permission.

This file previously contained text expressing a belief that most of
the files covered by the above exception were sufficiently trivial not
to be subject to copyright, resulting in confusion over whether it
negated the permissions granted in the license. In the spirit of
permissive licensing, and of not having licensing issues being an
obstacle to adoption, that text has been removed.Copyright (c) 2005-2023, NumPy Developers.
All rights reserved.

Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are
met:

    * Redistributions of source code must retain the above copyright
       notice, this list of conditions and the following disclaimer.

    * Redistributions in binary form must reproduce the above
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    * Neither the name of the NumPy Developers nor the names of any
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THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
                                 Apache License
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Copyright (c) Donald Stufft and individual contributors.
All rights reserved.

Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:

    1. Redistributions of source code must retain the above copyright notice,
       this list of conditions and the following disclaimer.

    2. Redistributions in binary form must reproduce the above copyright
       notice, this list of conditions and the following disclaimer in the
       documentation and/or other materials provided with the distribution.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.A. HISTORY OF THE SOFTWARE
==========================

Python was created in the early 1990s by Guido van Rossum at Stichting
Mathematisch Centrum (CWI, see https://www.cwi.nl) in the Netherlands
as a successor of a language called ABC.  Guido remains Python's
principal author, although it includes many contributions from others.

In 1995, Guido continued his work on Python at the Corporation for
National Research Initiatives (CNRI, see https://www.cnri.reston.va.us)
in Reston, Virginia where he released several versions of the
software.

In May 2000, Guido and the Python core development team moved to
BeOpen.com to form the BeOpen PythonLabs team.  In October of the same
year, the PythonLabs team moved to Digital Creations, which became
Zope Corporation.  In 2001, the Python Software Foundation (PSF, see
https://www.python.org/psf/) was formed, a non-profit organization
created specifically to own Python-related Intellectual Property.
Zope Corporation was a sponsoring member of the PSF.

All Python releases are Open Source (see https://opensource.org for
the Open Source Definition).  Historically, most, but not all, Python
releases have also been GPL-compatible; the table below summarizes
the various releases.

    Release         Derived     Year        Owner       GPL-
                    from                                compatible? (1)

    0.9.0 thru 1.2              1991-1995   CWI         yes
    1.3 thru 1.5.2  1.2         1995-1999   CNRI        yes
    1.6             1.5.2       2000        CNRI        no
    2.0             1.6         2000        BeOpen.com  no
    1.6.1           1.6         2001        CNRI        yes (2)
    2.1             2.0+1.6.1   2001        PSF         no
    2.0.1           2.0+1.6.1   2001        PSF         yes
    2.1.1           2.1+2.0.1   2001        PSF         yes
    2.1.2           2.1.1       2002        PSF         yes
    2.1.3           2.1.2       2002        PSF         yes
    2.2 and above   2.1.1       2001-now    PSF         yes

Footnotes:

(1) GPL-compatible doesn't mean that we're distributing Python under
    the GPL.  All Python licenses, unlike the GPL, let you distribute
    a modified version without making your changes open source.  The
    GPL-compatible licenses make it possible to combine Python with
    other software that is released under the GPL; the others don't.

(2) According to Richard Stallman, 1.6.1 is not GPL-compatible,
    because its license has a choice of law clause.  According to
    CNRI, however, Stallman's lawyer has told CNRI's lawyer that 1.6.1
    is "not incompatible" with the GPL.

Thanks to the many outside volunteers who have worked under Guido's
direction to make these releases possible.


B. TERMS AND CONDITIONS FOR ACCESSING OR OTHERWISE USING PYTHON
===============================================================

Python software and documentation are licensed under the
Python Software Foundation License Version 2.

Starting with Python 3.8.6, examples, recipes, and other code in
the documentation are dual licensed under the PSF License Version 2
and the Zero-Clause BSD license.

Some software incorporated into Python is under different licenses.
The licenses are listed with code falling under that license.


PYTHON SOFTWARE FOUNDATION LICENSE VERSION 2
--------------------------------------------

1. This LICENSE AGREEMENT is between the Python Software Foundation
("PSF"), and the Individual or Organization ("Licensee") accessing and
otherwise using this software ("Python") in source or binary form and
its associated documentation.

2. Subject to the terms and conditions of this License Agreement, PSF hereby
grants Licensee a nonexclusive, royalty-free, world-wide license to reproduce,
analyze, test, perform and/or display publicly, prepare derivative works,
distribute, and otherwise use Python alone or in any derivative version,
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CNRI LICENSE AGREEMENT FOR PYTHON 1.6.1
---------------------------------------

1. This LICENSE AGREEMENT is between the Corporation for National
Research Initiatives, having an office at 1895 Preston White Drive,
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DISCLAIMS ANY REPRESENTATION OR WARRANTY OF MERCHANTABILITY OR FITNESS
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5. CNRI SHALL NOT BE LIABLE TO LICENSEE OR ANY OTHER USERS OF PYTHON
1.6.1 FOR ANY INCIDENTAL, SPECIAL, OR CONSEQUENTIAL DAMAGES OR LOSS AS
A RESULT OF MODIFYING, DISTRIBUTING, OR OTHERWISE USING PYTHON 1.6.1,
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7. This License Agreement shall be governed by the federal
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U.S. federal law does not apply, by the law of the Commonwealth of
Virginia, excluding Virginia's conflict of law provisions.
Notwithstanding the foregoing, with regard to derivative works based
on Python 1.6.1 that incorporate non-separable material that was
previously distributed under the GNU General Public License (GPL), the
law of the Commonwealth of Virginia shall govern this License
Agreement only as to issues arising under or with respect to
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License Agreement shall be deemed to create any relationship of
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8. By clicking on the "ACCEPT" button where indicated, or by copying,
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        ACCEPT


CWI LICENSE AGREEMENT FOR PYTHON 0.9.0 THROUGH 1.2
--------------------------------------------------

Copyright (c) 1991 - 1995, Stichting Mathematisch Centrum Amsterdam,
The Netherlands.  All rights reserved.

Permission to use, copy, modify, and distribute this software and its
documentation for any purpose and without fee is hereby granted,
provided that the above copyright notice appear in all copies and that
both that copyright notice and this permission notice appear in
supporting documentation, and that the name of Stichting Mathematisch
Centrum or CWI not be used in advertising or publicity pertaining to
distribution of the software without specific, written prior
permission.

STICHTING MATHEMATISCH CENTRUM DISCLAIMS ALL WARRANTIES WITH REGARD TO
THIS SOFTWARE, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND
FITNESS, IN NO EVENT SHALL STICHTING MATHEMATISCH CENTRUM BE LIABLE
FOR ANY SPECIAL, INDIRECT OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES
WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER IN AN
ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT
OF OR IN CONNECTION WITH THE USE OR PERFORMANCE OF THIS SOFTWARE.

ZERO-CLAUSE BSD LICENSE FOR CODE IN THE PYTHON DOCUMENTATION
----------------------------------------------------------------------

Permission to use, copy, modify, and/or distribute this software for any
purpose with or without fee is hereby granted.

THE SOFTWARE IS PROVIDED "AS IS" AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH
REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY
AND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT,
INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM
LOSS OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR
OTHER TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR
PERFORMANCE OF THIS SOFTWARE.
Copyright (c) 2014, Al Sweigart
All rights reserved.

Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:

* Redistributions of source code must retain the above copyright notice, this
  list of conditions and the following disclaimer.

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----

Portions of code from MODP_ASCII - Ascii transformations (upper/lower, etc)
https://github.com/client9/stringencoders

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----

Numeric decoder derived from from TCL library
https://opensource.apple.com/source/tcl/tcl-14/tcl/license.terms
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Location: /Users/shannonellis/.local/lib/python3.11/site-packages
Requires: numpy, python-dateutil, pytz, tzdata
Required-by: CanvasGroupy, geopandas, seaborn, statsmodels