SlideShare a Scribd company logo
1 of 119
Download to read offline
90% of Python in 90 Minutes
@__mharrison__
Copyright 2013
About Me
●

●

●

12+ years Python
Worked in Data Analysis, HA, Search,
Open Source, BI, and Storage
Author of multiple Python Books
Goal
●

Read Python

●

Write Python
Book
Book
Treading on Python Volume 1 covers this
talk in much more detail.
Begin
Disclaimer
●

Assume some programming experience

●

Not covering all api's, just syntax
Warning
●

Starting from ground zero

●

Hands-on at end
Three Python'isms to Remember
●

dir

●

help

●

colon/indent shuffle
Why Python?
Python is a powerful, multi-paradigm,
interpreted language popular with
start-ups and large Co’s
Python 2 or 3?
For beginners there is no real difference
between Python 2 & 3. The basics are the
same (except for print)
Hello World
hello world
print "hello world"
from interpreter
$ python
>>> print "hello world"
hello world
REPL
Read, Eval, Print, Loop
REPL
$ python
>>> 2 + 2
4
>>>

#
#
#

read, eval
print
repeat (loop)
REPL (2)
Many developers keep a REPL handy
during programming
From script
Make file hello.py with
print "hello world"
Run with:
python hello.py
(unix) script
Make file hello with
#!/usr/bin/env python
print "hello world"
Run with:
chmod +x hello
./hello
Python 3 hello world
print is no longer a statement, but a
function
print("hello world")
Objects
Objects
Everything in Python is an object that has:
●

an identity (id)

●

a value (mutable or immutable)
id
>>> a = 4
>>> id(a)
6406896
Value
●

●

Mutable:When you alter the item, the
id is still the same. Dictionary, List
Immutable:String, Integer, Tuple
Mutable
>>> b = []
>>> id(b)
140675605442000
>>> b.append(3)
>>> b
[3]
>>> id(b)
140675605442000

# SAME!
Immutable
>>> a = 4
>>> id(a)
6406896
>>> a = a + 1
>>> id(a)
6406872
# DIFFERENT!
Variables
a
b
c
a

=
=
=
=

4
# Integer
5.6
# Float
"hello" # String
"4"
# rebound to String
Naming
●

lowercase

●

underscore_between_words

●

don't start with numbers

See PEP 8
PEP
Python Enhancement Proposal (similar to
JSR in Java)
Math
Math
+, -, *, /, ** (power), % (modulo)
Careful with integer division
>>> 3/4
0
>>> 3/4.
0.75
(In Python 3 // is integer division
operator)
What happens when you
raise 10 to the 100th?
Long
>>> 10**100
10000000000000000000000000000000
00000000000000000000000000000000
00000000000000000000000000000000
00000L
Long (2)
>>> import sys
>>> sys.maxint
9223372036854775807
>>> sys.maxint + 1
9223372036854775808L
Strings
Strings
name = 'matt'
with_quote = "I ain't gonna"
longer = """This string has
multiple lines
in it"""
How do I print?
He said, “I’m sorry”
String escaping
Escape with 
>>> print 'He said, "I'm sorry"'
He said, "I'm sorry"
>>> print '''He said, "I'm sorry"'''
He said, "I'm sorry"
>>> print """He said, "I'm sorry""""
He said, "I'm sorry"
String escaping (2)
Escape Sequence

Output



Backslash

'

Single quote

"

Double quote

b

ASCII Backspace

n

Newline

t

Tab

u12af

Unicode 16 bit

U12af89bc

Unicode 32 bit

o84

Octal character

xFF

Hex character
String formatting
c-like
>>> "%s %s" %('hello', 'world')
'hello world'

PEP 3101 style
>>> "{0} {1}".format('hello', 'world')
'hello world'
Methods & dir
dir
Lists attributes and methods:
>>> dir("a string")
['__add__', '__class__', ... 'startswith',
'swapcase', 'title', 'translate', 'upper',

'strip',
'zfill']
Whats with all the
'__blah__'?
dunder methods
dunder (double under) or "special/magic"
methods determine what will happen
when + (__add__) or / (__div__) is
called.
help
>>> help("a string".startswith)
Help on built-in function startswith:
startswith(...)
S.startswith(prefix[, start[, end]]) -> bool
Return True if S starts with the specified prefix, False
otherwise.
With optional start, test S beginning at that position.
With optional end, stop comparing S at that position.
prefix can also be a tuple of strings to try.
String methods
●

s.endswith(sub)
Returns True if endswith sub

●

s.find(sub)
Returns index of sub or -1

●

s.format(*args)
Places args in string
String methods (2)
●

s.index(sub)
Returns index of sub or exception

●

s.join(list)
Returns list items separated by string

●

s.strip()
Removes whitespace from start/end
Comments
comments
Comments follow a #
comments
No multi-line comments
More Types
None
Pythonic way of saying NULL. Evaluates
to False.
c = None
booleans
a = True
b = False
sequences
●

lists

●

tuples

●

sets
lists
Hold sequences.
How would we find out the attributes &
methods of a list?
lists
>>> dir([])
['__add__', '__class__', '__contains__',...
'__iter__',... '__len__',... , 'append', 'count',
'extend', 'index', 'insert', 'pop', 'remove',
'reverse', 'sort']
lists
>>>
>>>
>>>
>>>
>>>
>>>
[1,

a = []
a.append(4)
a.append('hello')
a.append(1)
a.sort() # in place
print a
4, 'hello']
lists
How would we find out documentation
for a method?
lists
help function:
>>> help([].append)
Help on built-in function append:
append(...)
L.append(object) -- append object to end
List methods
●

l.append(x)
Insert x at end of list

●

l.extend(l2)
Add l2 items to list

●

l.sort()
In place sort
List methods (2)
●

l.reverse()
Reverse list in place

●

l.remove(item)
Remove first item found

●

l.pop()
Remove/return item at end of list
Dictionaries
dictionaries
Also called hashmap or associative array
elsewhere
>>>
>>>
>>>
>>>
>>>
10

age = {}
age['george'] = 10
age['fred'] = 12
age['henry'] = 10
print age['george']
dictionaries (2)
Find out if 'matt' in age
>>> 'matt' in age
False
in statement
Uses __contains__ dunder method to
determine membership. (Or __iter__ as
fallback)
.get
>>> print age['charles']
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
KeyError: 'charles'
>>> print age.get('charles', 'Not found')
Not found
deleting keys
Removing 'charles' from age
>>> del age['charles']
deleting keys
del not in dir. .pop is an alternative
Functions
functions
def add_2(num):
""" return 2
more than num
"""
return num + 2
five = add_2(3)
functions (2)
●

def

●

function name

●

(parameters)

●

: + indent

●

optional documentation

●

body

●

return
whitespace
Instead of { use a : and indent
consistently (4 spaces)
whitespace (2)
invoke python -tt to error out during
inconsistent tab/space usage in a file
default (named) parameters
def add_n(num, n=3):
"""default to
adding 3"""
return num + n
five = add_n(2)
ten = add_n(15, -5)
__doc__
Functions have docstrings. Accessible
via .__doc__ or help
__doc__
>>> def echo(txt):
...
"echo back txt"
...
return txt
>>> help(echo)
Help on function echo in module __main__:
<BLANKLINE>
echo(txt)
echo back txt
<BLANKLINE>
naming
●

lowercase

●

underscore_between_words

●

don't start with numbers

●

verb

See PEP 8
Conditionals
conditionals
if grade > 90:
print "A"
elif grade > 80:
print "B"
elif grade > 70:
print "C"
else:
print "D"
Remember the
colon/whitespace!
Booleans
a = True
b = False
Comparison Operators
Supports (>, >=, <, <=, ==, !=)
>>> 5 > 9
False
>>> 'matt' != 'fred'
True
>>> isinstance('matt',
basestring)
True
Boolean Operators
and, or, not (for logical), &, |, and ^ (for
bitwise)
>>> x = 5
>>> x < -4 or x > 4
True
Boolean note
Parens are only required for precedence
if (x > 10):
print "Big"
same as
if x > 10:
print "Big"
Chained comparisons
if 3 < x < 5:
print "Four!"
Same as
if x > 3 and x < 5:
print "Four!"
Iteration
iteration
for number in [1,2,3,4,5,6]:
print number
for number in range(1, 7):
print number
range note
Python tends to follow half-open interval
([start,end)) with range and slices.
●

end - start = length

●

easy to concat ranges w/o overlap
iteration (2)
Java/C-esque style of object in array
access (BAD):
animals = ["cat", "dog", "bird"]
for index in range(len(animals)):
print index, animals[index]
iteration (3)
If you need indices, use enumerate
animals = ["cat", "dog", "bird"]
for index, value in enumerate(animals):
print index, value
iteration (4)
Can break out of nearest loop
for item in sequence:
# process until first negative
if item < 0:
break
# process item
iteration (5)
Can continue to skip over items
for item in sequence:
if item < 0:
continue
# process all positive items
iteration (6)
Can loop over lists, strings, iterators,
dictionaries... sequence like things:
my_dict = { "name": "matt", "cash": 5.45}
for key in my_dict.keys():
# process key
for value in my_dict.values():
# process value
for key, value in my_dict.items():
# process items
pass
pass is a null operation
for i in
# do
pass

range(10):
nothing 10 times
Hint
Don't modify list or dictionary contents
while looping over them
Slicing
Slicing
Sequences (lists, tuples, strings, etc) can
be sliced to pull out a single item
my_pets = ["dog", "cat", "bird"]
favorite = my_pets[0]
bird = my_pets[-1]
Negative Indexing
Proper way to think of [negative
indexing] is to reinterpret a[-X] as
a[len(a)-X]
@gvanrossum
Slicing (2)
Slices can take an end index, to pull out a
list of items
my_pets = ["dog", "cat", "bird"]
# a list
cat_and_dog = my_pets[0:2]
cat_and_dog2 = my_pets[:2]
cat_and_bird = my_pets[1:3]
cat_and_bird2 = my_pets[1:]
Slicing (3)
Slices can take a stride
my_pets = ["dog", "cat", "bird"]
# a list
dog_and_bird = [0:3:2]
zero_three_etc = range(0,10)
[::3]
Slicing (4)
Just to beat it in
veg = "tomatoe"
correct = veg[:-1]
tmte = veg[::2]
eotamot = veg[::-1]
File IO
File Input
Open a file to read from it (old style):
fin = open("foo.txt")
for line in fin:
# manipulate line
fin.close()
File Output
Open a file using 'w' to write to a file:
fout = open("bar.txt", "w")
fout.write("hello world")
fout.close()
Always remember to
close your files!
closing with with
implicit close (new 2.5+ style)
with open('bar.txt') as fin:
for line in fin:
# process line
Classes
Classes
class Animal(object):
def __init__(self, name):
self.name = name
def talk(self):
print "Generic Animal Sound"
animal = Animal("thing")
animal.talk()
Classes (2)
notes:
●

object (base class) (fixed in 3.X)

●

dunder init (constructor)

●

all methods take self as first parameter
Classes(2)
Subclassing
class Cat(Animal):
def talk(self):
print '%s says, "Meow!"' % (self.name)
cat = Cat("Groucho")
cat.talk() # invoke method
Classes(3)
class Cheetah(Cat):
"""classes can have
docstrings"""
def talk(self):
print "Growl"
naming
●

CamelCase

●

don't start with numbers

●

Nouns
Debugging
Poor mans
print works a lot of the time
Remember
Clean up print statements. If you really
need them, use logging or write to
sys.stdout
pdb
import pdb; pdb.set_trace()
pdb commands
●

h - help

●

s - step into

●

n - next

●

c - continue

●

w - where am I (in stack)?

●

l - list code around me
That's all
Questions? Tweet me
For more details see
Treading on Python Volume 1
@__mharrison__
http://hairysun.com

More Related Content

What's hot

Python Seaborn Data Visualization
Python Seaborn Data Visualization Python Seaborn Data Visualization
Python Seaborn Data Visualization Sourabh Sahu
 
Python Pandas
Python PandasPython Pandas
Python PandasSunil OS
 
Python: Modules and Packages
Python: Modules and PackagesPython: Modules and Packages
Python: Modules and PackagesDamian T. Gordon
 
Python - An Introduction
Python - An IntroductionPython - An Introduction
Python - An IntroductionSwarit Wadhe
 
Python 101: Python for Absolute Beginners (PyTexas 2014)
Python 101: Python for Absolute Beginners (PyTexas 2014)Python 101: Python for Absolute Beginners (PyTexas 2014)
Python 101: Python for Absolute Beginners (PyTexas 2014)Paige Bailey
 
Basic Python Programming: Part 01 and Part 02
Basic Python Programming: Part 01 and Part 02Basic Python Programming: Part 01 and Part 02
Basic Python Programming: Part 01 and Part 02Fariz Darari
 
Python dictionary
Python dictionaryPython dictionary
Python dictionarySagar Kumar
 
Python iteration
Python iterationPython iteration
Python iterationdietbuddha
 
Iterarators and generators in python
Iterarators and generators in pythonIterarators and generators in python
Iterarators and generators in pythonSarfaraz Ghanta
 
Python Lambda Function
Python Lambda FunctionPython Lambda Function
Python Lambda FunctionMd Soyaib
 
Python Exception Handling
Python Exception HandlingPython Exception Handling
Python Exception HandlingMegha V
 
Python - Numpy/Pandas/Matplot Machine Learning Libraries
Python - Numpy/Pandas/Matplot Machine Learning LibrariesPython - Numpy/Pandas/Matplot Machine Learning Libraries
Python - Numpy/Pandas/Matplot Machine Learning LibrariesAndrew Ferlitsch
 

What's hot (20)

6-Python-Recursion PPT.pptx
6-Python-Recursion PPT.pptx6-Python-Recursion PPT.pptx
6-Python-Recursion PPT.pptx
 
Python programming
Python programmingPython programming
Python programming
 
Python Seaborn Data Visualization
Python Seaborn Data Visualization Python Seaborn Data Visualization
Python Seaborn Data Visualization
 
Python Pandas
Python PandasPython Pandas
Python Pandas
 
Python: Modules and Packages
Python: Modules and PackagesPython: Modules and Packages
Python: Modules and Packages
 
Python dictionary
Python   dictionaryPython   dictionary
Python dictionary
 
Python - An Introduction
Python - An IntroductionPython - An Introduction
Python - An Introduction
 
Python 101: Python for Absolute Beginners (PyTexas 2014)
Python 101: Python for Absolute Beginners (PyTexas 2014)Python 101: Python for Absolute Beginners (PyTexas 2014)
Python 101: Python for Absolute Beginners (PyTexas 2014)
 
Basic Python Programming: Part 01 and Part 02
Basic Python Programming: Part 01 and Part 02Basic Python Programming: Part 01 and Part 02
Basic Python Programming: Part 01 and Part 02
 
Python dictionary
Python dictionaryPython dictionary
Python dictionary
 
File handling-c
File handling-cFile handling-c
File handling-c
 
Python iteration
Python iterationPython iteration
Python iteration
 
Iterarators and generators in python
Iterarators and generators in pythonIterarators and generators in python
Iterarators and generators in python
 
Python Lambda Function
Python Lambda FunctionPython Lambda Function
Python Lambda Function
 
File in C language
File in C languageFile in C language
File in C language
 
Python
PythonPython
Python
 
Python GUI
Python GUIPython GUI
Python GUI
 
Data Analysis in Python
Data Analysis in PythonData Analysis in Python
Data Analysis in Python
 
Python Exception Handling
Python Exception HandlingPython Exception Handling
Python Exception Handling
 
Python - Numpy/Pandas/Matplot Machine Learning Libraries
Python - Numpy/Pandas/Matplot Machine Learning LibrariesPython - Numpy/Pandas/Matplot Machine Learning Libraries
Python - Numpy/Pandas/Matplot Machine Learning Libraries
 

Viewers also liked

Build Your Own SaaS using Docker
Build Your Own SaaS using DockerBuild Your Own SaaS using Docker
Build Your Own SaaS using DockerJulien Barbier
 
Embedded C programming based on 8051 microcontroller
Embedded C programming based on 8051 microcontrollerEmbedded C programming based on 8051 microcontroller
Embedded C programming based on 8051 microcontrollerGaurav Verma
 
Fast ALS-Based Matrix Factorization for Recommender Systems
Fast ALS-Based Matrix Factorization for Recommender SystemsFast ALS-Based Matrix Factorization for Recommender Systems
Fast ALS-Based Matrix Factorization for Recommender SystemsDavid Zibriczky
 
Introduction to python for Beginners
Introduction to python for Beginners Introduction to python for Beginners
Introduction to python for Beginners Sujith Kumar
 
Python PPT
Python PPTPython PPT
Python PPTEdureka!
 
Understanding AntiEntropy in Cassandra
Understanding AntiEntropy in CassandraUnderstanding AntiEntropy in Cassandra
Understanding AntiEntropy in CassandraJason Brown
 
Cassandra London March 2016 - Lightening talk - introduction to incremental ...
Cassandra London March 2016  - Lightening talk - introduction to incremental ...Cassandra London March 2016  - Lightening talk - introduction to incremental ...
Cassandra London March 2016 - Lightening talk - introduction to incremental ...aaronmorton
 
Real World Tales of Repair (Alexander Dejanovski, The Last Pickle) | Cassandr...
Real World Tales of Repair (Alexander Dejanovski, The Last Pickle) | Cassandr...Real World Tales of Repair (Alexander Dejanovski, The Last Pickle) | Cassandr...
Real World Tales of Repair (Alexander Dejanovski, The Last Pickle) | Cassandr...DataStax
 
Spotify: Automating Cassandra repairs
Spotify: Automating Cassandra repairsSpotify: Automating Cassandra repairs
Spotify: Automating Cassandra repairsDataStax Academy
 
Linux Performance Analysis and Tools
Linux Performance Analysis and ToolsLinux Performance Analysis and Tools
Linux Performance Analysis and ToolsBrendan Gregg
 
Advance OOP concepts in Python
Advance OOP concepts in PythonAdvance OOP concepts in Python
Advance OOP concepts in PythonSujith Kumar
 
Python Tricks That You Can't Live Without
Python Tricks That You Can't Live WithoutPython Tricks That You Can't Live Without
Python Tricks That You Can't Live WithoutAudrey Roy
 
Basics of Object Oriented Programming in Python
Basics of Object Oriented Programming in PythonBasics of Object Oriented Programming in Python
Basics of Object Oriented Programming in PythonSujith Kumar
 
LISA17 Container Performance Analysis
LISA17 Container Performance AnalysisLISA17 Container Performance Analysis
LISA17 Container Performance AnalysisBrendan Gregg
 
Python的50道陰影
Python的50道陰影Python的50道陰影
Python的50道陰影Tim (文昌)
 
連淡水阿嬤都聽得懂的 機器學習入門 scikit-learn
連淡水阿嬤都聽得懂的機器學習入門 scikit-learn 連淡水阿嬤都聽得懂的機器學習入門 scikit-learn
連淡水阿嬤都聽得懂的 機器學習入門 scikit-learn Cicilia Lee
 

Viewers also liked (20)

Python Presentation
Python PresentationPython Presentation
Python Presentation
 
Build Your Own SaaS using Docker
Build Your Own SaaS using DockerBuild Your Own SaaS using Docker
Build Your Own SaaS using Docker
 
Embedded C
Embedded CEmbedded C
Embedded C
 
Embedded C programming based on 8051 microcontroller
Embedded C programming based on 8051 microcontrollerEmbedded C programming based on 8051 microcontroller
Embedded C programming based on 8051 microcontroller
 
Fast ALS-Based Matrix Factorization for Recommender Systems
Fast ALS-Based Matrix Factorization for Recommender SystemsFast ALS-Based Matrix Factorization for Recommender Systems
Fast ALS-Based Matrix Factorization for Recommender Systems
 
Introduction to python for Beginners
Introduction to python for Beginners Introduction to python for Beginners
Introduction to python for Beginners
 
Python PPT
Python PPTPython PPT
Python PPT
 
Understanding AntiEntropy in Cassandra
Understanding AntiEntropy in CassandraUnderstanding AntiEntropy in Cassandra
Understanding AntiEntropy in Cassandra
 
Cassandra London March 2016 - Lightening talk - introduction to incremental ...
Cassandra London March 2016  - Lightening talk - introduction to incremental ...Cassandra London March 2016  - Lightening talk - introduction to incremental ...
Cassandra London March 2016 - Lightening talk - introduction to incremental ...
 
Real World Tales of Repair (Alexander Dejanovski, The Last Pickle) | Cassandr...
Real World Tales of Repair (Alexander Dejanovski, The Last Pickle) | Cassandr...Real World Tales of Repair (Alexander Dejanovski, The Last Pickle) | Cassandr...
Real World Tales of Repair (Alexander Dejanovski, The Last Pickle) | Cassandr...
 
Spotify: Automating Cassandra repairs
Spotify: Automating Cassandra repairsSpotify: Automating Cassandra repairs
Spotify: Automating Cassandra repairs
 
Linux Performance Analysis and Tools
Linux Performance Analysis and ToolsLinux Performance Analysis and Tools
Linux Performance Analysis and Tools
 
Advance OOP concepts in Python
Advance OOP concepts in PythonAdvance OOP concepts in Python
Advance OOP concepts in Python
 
Python 2 vs. Python 3
Python 2 vs. Python 3Python 2 vs. Python 3
Python 2 vs. Python 3
 
Python Tricks That You Can't Live Without
Python Tricks That You Can't Live WithoutPython Tricks That You Can't Live Without
Python Tricks That You Can't Live Without
 
Basics of Object Oriented Programming in Python
Basics of Object Oriented Programming in PythonBasics of Object Oriented Programming in Python
Basics of Object Oriented Programming in Python
 
Python 2-基本語法
Python 2-基本語法Python 2-基本語法
Python 2-基本語法
 
LISA17 Container Performance Analysis
LISA17 Container Performance AnalysisLISA17 Container Performance Analysis
LISA17 Container Performance Analysis
 
Python的50道陰影
Python的50道陰影Python的50道陰影
Python的50道陰影
 
連淡水阿嬤都聽得懂的 機器學習入門 scikit-learn
連淡水阿嬤都聽得懂的機器學習入門 scikit-learn 連淡水阿嬤都聽得懂的機器學習入門 scikit-learn
連淡水阿嬤都聽得懂的 機器學習入門 scikit-learn
 

Similar to Learn 90% of Python in 90 Minutes

Introduction to Python 01-08-2023.pon by everyone else. . Hence, they must be...
Introduction to Python 01-08-2023.pon by everyone else. . Hence, they must be...Introduction to Python 01-08-2023.pon by everyone else. . Hence, they must be...
Introduction to Python 01-08-2023.pon by everyone else. . Hence, they must be...DRVaibhavmeshram1
 
Becoming a Pythonist
Becoming a PythonistBecoming a Pythonist
Becoming a PythonistRaji Engg
 
python chapter 1
python chapter 1python chapter 1
python chapter 1Raghu nath
 
Python chapter 2
Python chapter 2Python chapter 2
Python chapter 2Raghu nath
 
GE8151 Problem Solving and Python Programming
GE8151 Problem Solving and Python ProgrammingGE8151 Problem Solving and Python Programming
GE8151 Problem Solving and Python ProgrammingMuthu Vinayagam
 
python beginner talk slide
python beginner talk slidepython beginner talk slide
python beginner talk slidejonycse
 
Introduction to python
Introduction to pythonIntroduction to python
Introduction to pythonAhmed Salama
 
Beautiful python - PyLadies
Beautiful python - PyLadiesBeautiful python - PyLadies
Beautiful python - PyLadiesAlicia Pérez
 
Python_Cheat_Sheet_Keywords_1664634397.pdf
Python_Cheat_Sheet_Keywords_1664634397.pdfPython_Cheat_Sheet_Keywords_1664634397.pdf
Python_Cheat_Sheet_Keywords_1664634397.pdfsagar414433
 
Python_Cheat_Sheet_Keywords_1664634397.pdf
Python_Cheat_Sheet_Keywords_1664634397.pdfPython_Cheat_Sheet_Keywords_1664634397.pdf
Python_Cheat_Sheet_Keywords_1664634397.pdfsagar414433
 
Python tutorial
Python tutorialPython tutorial
Python tutorialRajiv Risi
 
Python fundamentals - basic | WeiYuan
Python fundamentals - basic | WeiYuanPython fundamentals - basic | WeiYuan
Python fundamentals - basic | WeiYuanWei-Yuan Chang
 
Τα Πολύ Βασικά για την Python
Τα Πολύ Βασικά για την PythonΤα Πολύ Βασικά για την Python
Τα Πολύ Βασικά για την PythonMoses Boudourides
 
Python in 90mins
Python in 90minsPython in 90mins
Python in 90minsLarry Cai
 

Similar to Learn 90% of Python in 90 Minutes (20)

Introduction to Python 01-08-2023.pon by everyone else. . Hence, they must be...
Introduction to Python 01-08-2023.pon by everyone else. . Hence, they must be...Introduction to Python 01-08-2023.pon by everyone else. . Hence, they must be...
Introduction to Python 01-08-2023.pon by everyone else. . Hence, they must be...
 
Python Workshop
Python  Workshop Python  Workshop
Python Workshop
 
Becoming a Pythonist
Becoming a PythonistBecoming a Pythonist
Becoming a Pythonist
 
python chapter 1
python chapter 1python chapter 1
python chapter 1
 
Python chapter 2
Python chapter 2Python chapter 2
Python chapter 2
 
GE8151 Problem Solving and Python Programming
GE8151 Problem Solving and Python ProgrammingGE8151 Problem Solving and Python Programming
GE8151 Problem Solving and Python Programming
 
python beginner talk slide
python beginner talk slidepython beginner talk slide
python beginner talk slide
 
Introduction to python
Introduction to pythonIntroduction to python
Introduction to python
 
Beautiful python - PyLadies
Beautiful python - PyLadiesBeautiful python - PyLadies
Beautiful python - PyLadies
 
Python
PythonPython
Python
 
Python 101 1
Python 101   1Python 101   1
Python 101 1
 
Python_Cheat_Sheet_Keywords_1664634397.pdf
Python_Cheat_Sheet_Keywords_1664634397.pdfPython_Cheat_Sheet_Keywords_1664634397.pdf
Python_Cheat_Sheet_Keywords_1664634397.pdf
 
Python_Cheat_Sheet_Keywords_1664634397.pdf
Python_Cheat_Sheet_Keywords_1664634397.pdfPython_Cheat_Sheet_Keywords_1664634397.pdf
Python_Cheat_Sheet_Keywords_1664634397.pdf
 
Python tutorial
Python tutorialPython tutorial
Python tutorial
 
Python material
Python materialPython material
Python material
 
Python fundamentals - basic | WeiYuan
Python fundamentals - basic | WeiYuanPython fundamentals - basic | WeiYuan
Python fundamentals - basic | WeiYuan
 
Python course Day 1
Python course Day 1Python course Day 1
Python course Day 1
 
Python 1
Python 1Python 1
Python 1
 
Τα Πολύ Βασικά για την Python
Τα Πολύ Βασικά για την PythonΤα Πολύ Βασικά για την Python
Τα Πολύ Βασικά για την Python
 
Python in 90mins
Python in 90minsPython in 90mins
Python in 90mins
 

Recently uploaded

08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking Men08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking MenDelhi Call girls
 
🐬 The future of MySQL is Postgres 🐘
🐬  The future of MySQL is Postgres   🐘🐬  The future of MySQL is Postgres   🐘
🐬 The future of MySQL is Postgres 🐘RTylerCroy
 
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptxHampshireHUG
 
Tata AIG General Insurance Company - Insurer Innovation Award 2024
Tata AIG General Insurance Company - Insurer Innovation Award 2024Tata AIG General Insurance Company - Insurer Innovation Award 2024
Tata AIG General Insurance Company - Insurer Innovation Award 2024The Digital Insurer
 
Boost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdfBoost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdfsudhanshuwaghmare1
 
Powerful Google developer tools for immediate impact! (2023-24 C)
Powerful Google developer tools for immediate impact! (2023-24 C)Powerful Google developer tools for immediate impact! (2023-24 C)
Powerful Google developer tools for immediate impact! (2023-24 C)wesley chun
 
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...Igalia
 
Presentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreterPresentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreternaman860154
 
Artificial Intelligence: Facts and Myths
Artificial Intelligence: Facts and MythsArtificial Intelligence: Facts and Myths
Artificial Intelligence: Facts and MythsJoaquim Jorge
 
Factors to Consider When Choosing Accounts Payable Services Providers.pptx
Factors to Consider When Choosing Accounts Payable Services Providers.pptxFactors to Consider When Choosing Accounts Payable Services Providers.pptx
Factors to Consider When Choosing Accounts Payable Services Providers.pptxKatpro Technologies
 
Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024
Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024
Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024The Digital Insurer
 
Exploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone ProcessorsExploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone Processorsdebabhi2
 
Advantages of Hiring UIUX Design Service Providers for Your Business
Advantages of Hiring UIUX Design Service Providers for Your BusinessAdvantages of Hiring UIUX Design Service Providers for Your Business
Advantages of Hiring UIUX Design Service Providers for Your BusinessPixlogix Infotech
 
Finology Group – Insurtech Innovation Award 2024
Finology Group – Insurtech Innovation Award 2024Finology Group – Insurtech Innovation Award 2024
Finology Group – Insurtech Innovation Award 2024The Digital Insurer
 
CNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of ServiceCNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of Servicegiselly40
 
Handwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed textsHandwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed textsMaria Levchenko
 
How to convert PDF to text with Nanonets
How to convert PDF to text with NanonetsHow to convert PDF to text with Nanonets
How to convert PDF to text with Nanonetsnaman860154
 
08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking Men08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking MenDelhi Call girls
 
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdfThe Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdfEnterprise Knowledge
 
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...Drew Madelung
 

Recently uploaded (20)

08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking Men08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking Men
 
🐬 The future of MySQL is Postgres 🐘
🐬  The future of MySQL is Postgres   🐘🐬  The future of MySQL is Postgres   🐘
🐬 The future of MySQL is Postgres 🐘
 
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
 
Tata AIG General Insurance Company - Insurer Innovation Award 2024
Tata AIG General Insurance Company - Insurer Innovation Award 2024Tata AIG General Insurance Company - Insurer Innovation Award 2024
Tata AIG General Insurance Company - Insurer Innovation Award 2024
 
Boost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdfBoost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdf
 
Powerful Google developer tools for immediate impact! (2023-24 C)
Powerful Google developer tools for immediate impact! (2023-24 C)Powerful Google developer tools for immediate impact! (2023-24 C)
Powerful Google developer tools for immediate impact! (2023-24 C)
 
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
 
Presentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreterPresentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreter
 
Artificial Intelligence: Facts and Myths
Artificial Intelligence: Facts and MythsArtificial Intelligence: Facts and Myths
Artificial Intelligence: Facts and Myths
 
Factors to Consider When Choosing Accounts Payable Services Providers.pptx
Factors to Consider When Choosing Accounts Payable Services Providers.pptxFactors to Consider When Choosing Accounts Payable Services Providers.pptx
Factors to Consider When Choosing Accounts Payable Services Providers.pptx
 
Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024
Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024
Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024
 
Exploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone ProcessorsExploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone Processors
 
Advantages of Hiring UIUX Design Service Providers for Your Business
Advantages of Hiring UIUX Design Service Providers for Your BusinessAdvantages of Hiring UIUX Design Service Providers for Your Business
Advantages of Hiring UIUX Design Service Providers for Your Business
 
Finology Group – Insurtech Innovation Award 2024
Finology Group – Insurtech Innovation Award 2024Finology Group – Insurtech Innovation Award 2024
Finology Group – Insurtech Innovation Award 2024
 
CNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of ServiceCNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of Service
 
Handwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed textsHandwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed texts
 
How to convert PDF to text with Nanonets
How to convert PDF to text with NanonetsHow to convert PDF to text with Nanonets
How to convert PDF to text with Nanonets
 
08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking Men08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking Men
 
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdfThe Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
 
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
 

Learn 90% of Python in 90 Minutes