Practicing Python 3

Websites
➤ Pinkoi
➤ Google search engine
➤ Instagram
➤ MAU: 700M @ 2017/5
➤ Uber
➤ Pinterest
3

Desktop Applications
➤ Dropbox
➤ Disney
➤ For animation studio tools.
➤ Blender
➤ A 3D graphics software.
4

Science
➤ NASA
➤ LIGO
➤ Gravitational waves @ 2016
➤ LHC
➤ Higgs boson @ 2013
➤ MMTK
➤ Molecular Modelling Toolkit
5

Embedded System
➤ iRobot uses Python.
➤ Raspberry Pi supports Python.
➤ Linux has built-in Python.
6

Why?
➤ Python is slower than C, Java,
➤ But much faster to write,
➤ And easy to speed up.
➤ Numba | Cython
➤ Has the rich libraries.
➤ Emphasizes code readability.
➤ Easier to learn.
➤ Easier to co-work.
➤ “Time is money.”
7

A Website in a Minute
from flask import Flask
app = Flask(__name__)
@app.route("/")
def hello():
return "Hello World!"
if __name__ == "__main__":
app.run()
9

Symbolic Mathematics
from sympy import symbols
from sympy import diff 
x = symbols('x')
x**2
diff(x**2)
10

Data Visualization
import pandas as pd
import numpy as np
ts = pd.Series(
np.random.randn(1000),
index=pd.date_range(
'1/1/2000', periods=1000
)
)
ts = ts.cumsum()
ts.plot()
11

Mosky
➤ Python Charmer at Pinkoi.
➤ Has spoken at
➤ PyCons in  
TW, MY, KR, JP, SG, HK, 
COSCUPs, and TEDx, etc.
➤ Countless hours  
on teaching Python.
➤ Own the Python packages:
➤ ZIPCodeTW,  
MoSQL, Clime, etc.
➤ http://mosky.tw/
12

➤ The Foundation Part:
➤ Primitives
➤ If & While
➤ Composites
➤ For, Try, Def
➤ Common Functions
➤ Input & Output
➤ Command Line
Arguments
➤ The Fascinating Part:
➤ Yield
➤ Comprehensions
➤ Functional Tricks
➤ Import Antigravity***
➤ Module & Package
➤ Class
➤ And the checkpoints!
The Outline
13

(a terminal) Master the machine.
Python 3 Not Python 2.
Jupyter Notebook Learn Python with browsers.
Visual Studio Code A full-featured source code editor.
(other libs) Will be introduced in this slides.
We Will Use
15

➤ Open a terminal:
➤ Spotlight (Cmd-Space) / “terminal”
➤ Install Homebrew by executing the command:
➤ $ /usr/bin/ruby -e "$(curl -fsSL https://
raw.githubusercontent.com/Homebrew/install/master/
install)"
➤ Execute the commands:
➤ $ brew install python3
➤ $ pip3 install jupyter numpy scipy sympy matplotlib
ipython pandas flask beautifulsoup4 requests seaborn
statsmodels scikit-learn
➤ Note the above commands are just a single line.
On Mac
16

➤ Open a terminal:
➤ Spotlight (Cmd-Space) / “terminal”
➤ Install Homebrew by executing the command:
➤ $ /usr/bin/ruby -e "$(curl -fsSL https://
raw.githubusercontent.com/Homebrew/install/master/
install)"
➤ $ brew install python3
➤ $ pip3 install jupyter numpy scipy sympy matplotlib
Hint to talk to macOS. Enter
the command without $.
On Mac
17

➤ Install Python 3 with Miniconda:
➤ http://conda.pydata.org/miniconda.html
➤ Python 3.6 / Windows / 64-bit (exe installer)
➤ Open Anaconda's terminal:
➤ Start Menu / Search / Type “Anaconda Prompt”
➤ Right-click the item and choose “Run as administrator”.
➤ > conda install jupyter numpy scipy sympy matplotlib
On Windows
18

➤ Install Python 3 with Miniconda:
➤ http://conda.pydata.org/miniconda.html
➤ Python 3.6 / Windows / 64-bit (exe installer)
➤ Open Anaconda's terminal:
➤ Start Menu / Search / Type “Anaconda Prompt”
➤ Right-click the item and choose “Run as administrator”.
➤ > conda install jupyter numpy scipy sympy matplotlib
Hint to talk to Windows. Enter
the command without >.
On Windows
19

If You Already Have Python
➤ Try to install the packages:
➤ The Jupyter Notebook
➤ jupyter
➤ The SciPy Stack
➤ numpy scipy sympy matplotlib ipython pandas
➤ The web-related libs
➤ flask beautifulsoup4 requests
➤ The data-related libs
➤ seaborn statsmodels scikit-learn
➤ If fail, clean uninstall Python, and follow the previous slides.
20

Common MS-DOS Commands
21
C: Go C: drive.
cd PATH
Change directory to PATH. 
PATH can be /Users/python/, python/, etc.
dir Display the contents of a directory.
cls Clear the terminal screen.
python PATH
python3 PATH
Execute a Python program.
exit Exit the current command processor.

Common Unix-like (Mac) Commands
22
cd PATH
Change Directory to PATH. 
PATH can be /Users/python/, python/, etc.
ls List the contents of a directory.
<Ctrl-L> Clear the terminal screen.
python PATH 
python3 PATH
Execute a Python program.
<Ctrl-D> Exit the current terminal.

Common Terminal Shortcuts
23
<Tab> Complete the command.
<Up> Show the last command.
<Down> Show the next command.
<Ctrl-C>
Enter new command, or
interrupt a running program.

Start Jupyter Notebook
➤ Mac:
➤ $ jupyter notebook
➤ Windows:
➤ Search /  
“Jupyter Notebook”
24

Install Visual Studio Code
➤ If you already have a source code editor, it's okay to skip.
➤ Install:
➤ https://code.visualstudio.com/download
➤ Open an integrated terminal:
➤ Visual Studio Code / View / Integrated Terminal
➤ Execute a Python program:
➤ $ cd PROJECT_DIR
➤ $ python hello.py
➤ or
➤ $ python3 hello.py
25

Checkpoint: Say Hi to Python
print('Hello, Python!')
27

Checkpoint: Say Hi to Python – on a Notebook
➤ Type the code into a notebook's cell.
➤ Press <Ctrl-Enter>.
➤ The output should be “Hello, Python!”
28

Checkpoint: Say Hi to Python – on an Editor
➤ Save a “hello.py” file into your project folder.
➤ Write the code into the file.
➤ Open up a new terminal, or use the integrated terminal.
➤ Change directory ($ cd ...) to your project folder.
➤ Execute ($ python ... or $ python3 ...) the file.
➤ The output should be “Hello, Python!”
29

Common Jupyter Notebook Shortcuts
30
Esc Edit mode → command mode.
Ctrl-Enter Run the cell.
B Insert cell below.
D, D Delete the current cell.
M To Markdown cell.
Cmd-/ Comment the code.
H Show keyboard shortcuts.
P Open the command palette.

Common Markdown Syntax
31
# Header 1 Header 1
## Header 2 Header 2.
> Block quote Block quote.
* Item 1 
* Item 2
Unordered list.
1. Item 1 
2. Item 2
Ordered list.
*emphasis* Emphasis.
**strong emp** Strong emphasis.
Markdown Cheatsheet | markdown.tw

How Jupyter Notebook Works?
32
1. Connect to a Python kernel.
2. Calculate and return the output.
3. Store the output.

A. When kernel halts or restart,
notebook remembers the outputs.
B. “Run All”  
to refresh the new kernel.
But when connect to a new kernel, 
kernel remember nothing.

The Numbers
➤ In [n]
➤ n is the execution order, 
like the line number.
➤ It may be:
➤ 1, 2, 3, 4
➤ 3, 5, 2, 4
➤ Depends on how you run it.
➤ “Restart & Run All”  
to reorder the numbers.
34

Programming?
➤ Programming  
is abstracting.
➤ Abstract the world with:
➤ Data types: 1.
➤ Operations: 1+1.
➤ Control ﬂow: if ... else.
➤ They are from:
➤ Libraries.
➤ Your own code.
36

The Common Primitives
37
int Integer: 3
float Floating-point numbers: 3.14
str Text Sequence: '3.14'
bytes Binary Sequence: b'xe4xb8xadxe6x96x87'
bool True or False
None Represents the absence of a value.

Variables
➤ Points to an “object”.
➤ Everything in Python is an
object, including class.
➤ The object:
➤ Has a (data) type.
➤ Supports an operation set.
➤ Lives in the memory.
38

“01_data_types_primitives.ipynb
-The Notebook Time
39

➤ del x
➤ Now the x points to nothing.
➤ The object will be collected if no variable points to it.
Delete the “Pointing”
40

Checkpoint: Calculate BMR
➤ The Miﬄin St Jeor Equation:
➤
➤ Where:
➤ P: kcal / day
➤ m: weight in kg
➤ h: height in cm
➤ a: age in year
➤ s: +5 for males, -161 for females
➤ Just simply calculate it in notebook.
41
P = 10m + 6.25h − 5a + s

If & While
➤ if <condition>: ...
➤ Run inner block if true.
➤ while <condition>: ...
➤ The while-loop.
➤ Run inner block while true.
➤ I.e. run until false.
43

“02_control_ﬂow_if_while.ipynb
-The Notebook Time
44

The Domains
➤ Web
➤ Django Girls Tutorial
➤ The Taipei Version
➤ Data / Data Visualization
➤ Seaborn Tutorial
➤ The Python Graph Gallery
➤ Matplotlib Gallery
➤ Data / Machine Learning
➤ Scikit-learn Tutorials
➤ Standford CS229
➤ Hsuan-Tien Lin
➤ Data / Deep Learning
➤ TensorFlow Getting Started
➤ Standford CS231n
➤ Standford CS224n
➤ Data / Statistics
➤ Good handout + Google
➤ Handbook of Biological
Statistics
➤ scipy.stats + StatsModels
➤ Not so good in Python.
➤ Ask or google  
for your own domain!
46

The Language Itself
➤ All the “Dig More”.
➤ Understand the built-in batteries and their details:
➤ The Python Standard Library – Python Documentation
➤ Understand the language:
➤ The Python Language Reference – Python Documentation
➤ Data model
47

If You Need a Book
➤ “Introducing Python –  
Modern Computing in Simple
Packages”
➤ “精通Python： 
運⽤用簡單的套件進⾏行行現代運算”
48

The Learning Tips
➤ Problem → project → learn things!
➤ Make it work, make it right, and ﬁnally make it fast!
➤ Learn from the great people in our communities:
➤ Taipei.py
➤ PyHUG
➤ PyCon TW
➤ Python Taiwan
➤ And sleep well, seriously.
➤ Anyway, have fun with Python!
49

The Common Composites
51
list Contains objects.
tuple
A compound objects has an unique meaning, 
e.g., a point: (3, 1).
dict Maps an object to another object.
set Contains non-repeated objects.

“03_data_types_composites.ipynb
-The Notebook Time
52

Recap
➤ list []
➤ tuple ()
➤ dict {:}
➤ set {}
53

For & Loop Control Statements
➤ for
➤ The for-loop.
➤ In each iteration,  
get the next item  
of a collection.
➤ Supports str, list, tuple,
set, and dict, etc.
➤ I.e. iterate an iterable.
➤ break
➤ Leave the loop.
➤ continue
➤ Go the next iteration.
➤ loop … else
➤ If no break happens,  
execute the else.
55

Pass
➤ pass
➤ Do nothing.
➤ The compound statements must have one statement.
➤ The if, while, for, etc.
56

“04_control_ﬂow_for.ipynb
-The Notebook Time
57

Checkpoint: Calculate Average BMR
58
height_cm weight_kg age male
152 48 63 1
157 53 41 1
140 37 63 0
137 32 65 0

“05_control_ﬂow_try.ipynb
-The Notebook Time
60

Raise Your Exception
➤ raise RuntimeError('should not be here')
➤ Raise an customized exception.
➤ Use class to customize exception class.
➤ raise
➤ Re-raise the last exception.
61

The Guidelines of Using Try
➤ An exception stops the whole program.
➤ However sometimes stop is better than a bad output.
➤ Only catch the exceptions you expect.
➤ But catch everything before raise to user.
➤ And transform the exception into log, email, etc.
62

Functions
➤ Reuse statements.
➤ def
➤ Take the inputs.
➤ return
➤ Give an output.
➤ If no return, returns None.
➤ Method
➤ Is just a function  
belonging to an object.
64

“06_control_ﬂow_def.ipynb
-The Notebook Time
65

Recap
➤ When calling function:
➤ Keyword arguments: f(a=3.14)
➤ Unpacking argument list: f(*list_like, **dict_like)
➤ When deﬁning function:
➤ Default values: def f(a=None): ...
➤ Arbitrary argument list: def f(*args, **kwargs): ...
➤ Using docstrings to cooperate.
66

Docs – the Web Way
➤ The Python Standard Library
➤ Tip: Search with a leading and a trailing space.
➤ “ sys ”
➤ DevDocs
➤ Tip: Set it as one of Chrome's search engine.
➤ seaborn API reference
➤ For an example of 3rd libs.
67

The Guidelines of Designing Functions
➤ Use the simplest form ﬁrst.
➤ Unless the calling code looks superﬂuous.
68

Checkpoint: Calculate Average BMR With Functions
69
height_cm weight_kg age male
152 48 63 1
157 53 41 1
140 37 63 0
137 32 65 0

“07_libraries_ 
common_functions.ipynb
-The Notebook Time
71

Input & Output
➤ IO: input & output.
➤ Standard IOs:
➤ stdout: standard output.
➤ stderr: standard error.
➤ stdin: standard input.
➤ File IOs:
➤ Including networking.
➤ Command line arguments
➤ Always validate user's inputs.
73

“08_libraries_input_output.ipynb
-The Notebook Time
74

Checkpoint: Calculate Average BMR From the Dataset
➤ Read the dataset_howell1.csv in.
➤ Skip the ﬁrst line which doesn't contain data.
➤ Transform the datatypes.
➤ Calculate the average BMR from the dataset.
75

Command Line
Arguments
Libraries

“09_libraries_ 
command_line_arguments.py
-The Notebook Time
77

Recap
➤ open(…) → file object for read or write.
➤ The with will close file after the suite.
➤ The Inputs:
➤ stdin → input()
➤ for line in <file object>: ...
➤ <file object>.read()
➤ The outputs:
➤ print(…) → stdout
➤ print(…, file=sys.stderr) → stderr
➤ <file object>.write(…)
78

Checkpoint: Calculate BMR From Command Line
➤ The requirement:
➤ $ python3 calc_bmr.py 152 48 63 M
➤ 1120
➤ The hints:
➤ Read the inputs from sys.argv.
➤ Transform, calculate, and print it out!
➤ Get the extra bonus:
➤ Organize code into functions by functionality.
➤ Let user see nice error message when exception raises.
➤ Refer to 09_libraries_command_line_arguments.py.
79

“10_control_ﬂow_yield.ipynb
-The Notebook Time
81

“Yield” Creates a Generator
➤ If a function uses yield, it returns a generator.
➤ Save memory.
➤ Simplify code.
82

“11_control_ﬂow_ 
comprehensions.ipynb
-The Notebook Time
84

Comprehensions & Generator Expression
➤ List Comprehension []
➤ Set Comprehension {}
➤ Dict Comprehension {:}
➤ Generator Expression ()
85

The Functional Tricks
➤ The functional programming:
➤ Is a programming paradigm.
➤ Avoids changing-state and mutable data.
➤ Sometimes makes code clean, sometimes doesn't.
➤ Use it wisely.
➤ Python is not a functional language.
➤ But provides some useful tools.
87

“12_libraries_functional_tricks.ipynb
-The Notebook Time
88

➤ Recommend:
➤ https://github.com/Suor/funcy
➤ Not so recommend:
➤ https://github.com/pytoolz/toolz
➤ https://github.com/EntilZha/PyFunctional
The Popular Functional Libs
89

Checkpoint: Calculate Average BMR With Comprehensions
➤ Either the table or the CSV is okay.
➤ Use at least one comprehension.
90

The Useful Packages in Standard Library
➤ sys
➤ os and os.path
➤ glob
➤ math
➤ random
➤ decimal
➤ datetime
➤ collections
➤ re
➤ urllib
➤ smtplib
➤ json
➤ csv
➤ pickle
➤ gzip and many others
➤ threading
➤ multiprocessing
➤ asyncio
➤ pprint
➤ logging
➤ doctest
➤ sqlite3
92

The Useful Third-Party Packages
➤ Requests
➤ Beautiful Soup
➤ csvkit
➤ seaborn
➤ Pillow
➤ Flask
➤ Django
➤ pytest
➤ Sphinx
➤ pipenv
➤ The SciPy Stack
➤ NumPy
➤ SciPy
➤ SymPy
➤ Matplotlib
➤ IPython
➤ pandas
➤ python3wos.appspot.com
93

“13_*_libraries_ 
import_antigravity_*.ipynb
-The Notebook Time
94

Install Third-Party Package
➤ When using pip:
➤ pip install <package name>
➤ When using Conda:
➤ conda install <package name>
95

Checkpoint: Visualization
➤ Explore from 13_7_libraries_import_antigravity_seaborn.ipynb .
➤ Refer to Seaborn API Reference to plot diﬀerent graphs.
➤ Refer to StatsModels Datasets for diﬀerent datasets.
➤ Tip: “fair” in http://www.statsmodels.org/stable/datasets/
generated/fair.html is the name of the dataset.
➤ Share your interesting insights with us!
96

Import Module
➤ A Python ﬁle is just a Python module:
import ma
import mb
➤ A module has a namespace:
ma.var
mb.var
➤ The vars are diﬀerent variables.
99

Import Package
➤ A directory containing a __init__.py is just a package:
import p
➤ It executes the __init__.py.
➤ Usually import  
the common function or module of the whole package.
➤ Import modules in a package:
import p.ma
import p.mb
101

Make Them Shorter
➤ Import variables from a module:
from ma import x, y
# or
from ma import x
from ma import y
➤ Import modules from a package:
from p import ma, mb
# or
from p import ma
from p import mb
102

➤ Give an alias:
from ma import var as _var
➤ Mix them up:
from p.ma import var as _var
103

“14_libraries_moudle_and_package
-The Notebook Time
104

The Object-Oriented Programming
➤ Class makes objects.
➤ Customize your:
➤ Data type.
➤ And its operations.
➤ A powerful tool to abstract the world.
106

The Object-Oriented Terms in Python
107
object Everything in Python is an object, e.g., str, 'str'.
class Makes instances, e.g., str.
instance Made from class, e.g., 'str'.
attribute Anything an object owns.
method A function an object owns.

“15_data_types_class.ipynb
-The Notebook Time
109

object
Google
mosky andy
Yahoo
Site

Duck-Typing & Protocol
➤ Duck-Typing
➤ “If it looks like a duck and quacks like a duck,  
it must be a duck.”
➤ Avoids tests using type() or isinstance().
➤ Employs hasattr() tests or EAFP programming.
➤ EAFP: easier to ask for forgiveness than permission.
➤ Iterator Protocol
➤ __iter__() returns itself.
➤ __next__() returns the next element.
➤ The for-loops use the iterator protocol to iterate an object.
112

The Guidelines of Designing Classes
➤ Don't use class.
➤ Unless many functions have the same arguments, e.g.,:
➤ def create_user(uid, ...): ...
➤ def retrieve_user(uid, ...): ...
➤ def update_user(uid, ...): ...
➤ When design or implementation.
➤ Don't use class method, etc.
➤ Unless you're sure the method is only associate with class.
➤ Let's keep code simple!
113

The Fun Facts
➤ import this
➤ Python’s easter eggs and hidden jokes – Hacker Noon
114

Checkpoint: Classification
➤ Extend 13_8_libraries_import_antigravity_scikitlearn.ipynb .
➤ Refer to Scikit-Learn Random Forest for the arguments.
➤ Share your awesome metrics with us!
115

Practicing Python 3

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