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Lecture 2: Python Basics

Lecture 2: Python Basics

In this lecture, you will learn

  • advanced data types

  • basic file read/write operations.

Advanced data types

The most attractive part of Python is its advanced data types including list, tuple and dict. These are in common use during modern programming languages but Python provides an extremely elegant way to deal with them.

Tip

Since Python borrowed pretty much grammars from other languages, people who are familiar with MATLAB/Mathematica would be also familiar with these part.

list

A list in Python is a sequence of objects, which may be integers, string or others. These objects are referenced with its names and seperated with comma in a pair of brackets:

[obj1, obj2, obj3, ... ]

Here are examples of list and you can try define new list by combining the data types you have learned in previous lecture.

list_of_numbers = [1,2,3,4]
list_of_strings = ['hello', 'world']

Note

We usually use same type in a single list, but it is also possible to hybrid different types in a list like [1, 'hello', 2, 'world'].

list of list is also useful in some cases:

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

A more simple way to define a list is list comprehension, which has a standard form as below

[expr for index in collection]

where expr is an expression, index is a index taken from collection. Python will calculate the values of expression for each inedx in the collection and collect them together as a new list.

list_square = [i**2 for i in range(10)]
print(list_square)

[0, 1, 4, 9, 16, 25, 36, 49, 64, 81]

List comprehension can be used with a condition, which would filter the elements in the list.

l = [i for i in range(100) if i % 2 == 1]
print(l)

[1, 3, 5, 7, 9, 11, 13, 15, 17, 19, 21, 23, 25, 27, 29, 31, 33, 35, 37, 39, 41, 43, 45, 47, 49, 51, 53, 55, 57, 59, 61, 63, 65, 67, 69, 71, 73, 75, 77, 79, 81, 83, 85, 87, 89, 91, 93, 95, 97, 99]

Access elements in list

list is an ordered sequence, which means indices are naturally binded with each element. Therefore, we can access single element in the list by the index following the list name:

l = [1, 2, 3, 4]
print(l[1])

2

Important

In Python, the indices start with zero and stop at \(n-1\) where \(n\) is the length of the list. So, l[0] is the first element in l and l[1] is the second element in l.

Warning

Please make sure the indices are not out of bound. If you try to access such an element, Python would complain with an error.

l = [1, 2, 3, 4]
l[4]

---------------------------------------------------------------------------
IndexError                                Traceback (most recent call last)
Input In [6], in <module>
      1 l = [1, 2, 3, 4]
----> 2 l[4]

IndexError: list index out of range

Python also provides negative index which start from the last element with index \(-1\) in an reversed ordered.

l = [1, 2, 3, 4]
print(l[-1], l[-2], l[-3], l[-4])

Tip

You can use list() to cast a range() object into an list, e.g., list(range(5)) returns a [0, 1, 2, 3, 4].

Slice operations

To access part of list, slice operation provides an elegant and concise way, i.e., it requires three parameters start, end and step to get a sub-list from the list. For example,

list_name[start:end:step]

represents a sub-list contains elements:

\[ start, start+step, start+2\times step, \ldots, start+k\times step < end \]

where

\[ k = \lfloor \frac{end-start}{step} \rfloor \]

such that \(start+k\times step < end\).

In general, we do not give all three parameters but only two or one of them. By default, Python will treat

  • start=0 and end=-1 when step>1 or

  • start=-1 and end=0 when step<1.

Suppose l=[0,1,2,3,4], here are some examples:

  • l[1:3] = l[1:3:1] = [0, 1, 2]

  • l[:3] = l[1:3:1] = [0, 1, 2]

  • l[::2] = l[0:-1:2] = [0, 2, 4]

  • l[::-1] = l[-1:0:-1] = [4, 3, 2, 1, 0]

To modify an existing list, you need to select one or more elements and assign them with a list or value.

To change single element:

l = [1, 2, 3, 4]
l[1] = -1
print(l)

To changes multiple elements:

l = [1, 2, 3, 4]
l[:2] = [-1, 0]
print(l)

Note

Other operations for list:

  • l.append(x) will append a new element x at the tail of the l.

  • l.insert(pos, value) will insert a new element value at index of pos.

  • l1 + l2 will concatenate two lists l1 and l2.

  • l * n will repeat l for \(n\) times.

We can also use for-loop to travel a list:

p = [1, 2, 3, 4, 5]
for i in p:
    print(i)

See also

Please refer to lecture 1 to recall for-loop statement.

tuple

tuple is baisically same as list except it is contained in () and its elements are unchangeable. It shares the majority of features that list also have. For example,

  • hybrid data types: (1, 'hello') is a tuple.

  • slice operation: t[::-1], t[0:2], t[:1:] are okay.

  • repeating: t * 3 return tuple containing t for three times.

Packing and Unpacking are common operations in Python when you deal with list or tuple, i.e., we can explicitly assign elements to multiple variables, vice versa.

a = 1
b = 2
c = 3
t = a, b, c # note here, we do not need brackets ()
print(t)
c, d, e = t
print(c, d)

Tip

Sometimes, we do not want to assign all elements, please use underscore _, i.e., _, b = s is equivalent to assign b with s[1] and drop s[0] for two-element tuple or list s.

The packing and unpacking are often used to define multi-value functions:

def mutli_value_func(x):
    return x-1, x+1
a, b = mutli_value_func(20)
print(a, b)

dict

Both list and tuple can be accessed with its indices. However, in some cases, number-based indices are not convinient to remember and understand. More general data types as indices are employed in dict data type. In fact, integers, string or even tuple can be the indices (named key) of dict.

The standard form of a dict is

{key1:value1, key2:value2, ...}

For example, here is a dict:

d = {1:'apple', 2:'banana', 3:'orange'}

Note

Be careful with the type of key because some types cannot be a key of dict, e.g., list. Following code would give an error.

wrong_dict = {[1,2]:2, [1,2,3]:3}

To access element in the dict, try

d[1]

where 1 is one of the key of d.

dict provide function keys() get all keys:

d.keys()

Note

Please try values() and items() to learn by yourself.

print(d.values())
print(d.items())

To check if an value is in the dict, you can use in keyword:

d = {'apple':1, 'banana':2, 'orange':3}
'something' in d

Also, you can travel dict by for-loop and this will pick all keys in the dict:

for key in d:
    print(key, d[key])

We can also define a dict comprehension like list comprehension, and the way

dd = {fruit:d[fruit]+1 for fruit in d]}

will define a new dict.

File operations

In most operating systems(Windows/macOS/Linux), there are two different ways to locate a file or a directory:

  • absolute path, e.g., C:\Windows\System32

  • related path, e.g., ../notebooks/lec2.ipynb Absolute path means a fixed way to access files wherever you current directory(i.e., path to your Python script) is, while related path could be change regarding current directory.

Some symbols are used for constructing related path:

  • . means the current directory

  • . means the parent directory, which is the directory containing ..

  • ~ means the home directory. For Windows, it should be like C:\Users\[your user name], for Linux, it should be like /home/[your user name] and for macOS, it should be like /Users/[your user name].

Read/write file

To read or write file is just simple with open() function:

file = open('data.txt', 'w')
file.write('hello world.')
file.close()

Here, the first parameter in open() is the path to your file and both related/absolute path is okay. w as the second parameter to open() represents write mode, as r means read mode. So please try following code:

file = open('data.txt', 'r')
s = file.readlines()
print(s)

Tip

It is recommended to use close() function to close your file. However, if you forget to do so, Python will automatically close file after the program is finished.

try-except statement

Sometimes, the file you want to access may not exist on the disk. If that happens, the Python script might exit exceptly. A standard way to process such caes is using try-except structure in Python:

try:
    file = open('not-existed-file.txt', 'r')
except:
    print("File does not exist.")

Directoray

You may want to access all files in the specific directory. Python provides some packges to do this and here is just a sample:

import os

You can check if some files/directories exist by following code:

os.path.exists('index.html')

Also, you can get a list of all files in the current directory:

os.listdir('.')

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Lecture 1: Python Basics

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Lecture 3: Data Analysis