Python

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Master python closure with 3 real-world examples

Introduction

Python closure is a technique for binding function with an environment where the function gets access to all the variables defined in the enclosing scope. Closure typically appears in the programming language with first class function, which means functions are allowed to be passed as arguments, return value or assigned to a variable.

This definition sounds confusing to the python beginners, and sometimes the examples found from online also not intuitive enough in the way that most of the examples are trying to illustrate with some printing statement, so the readers may not get the whole idea of why and how the closure should be used. In this article, I will be using some real-world example to explain how to use closure in your code.

Nested function in Python

To understand closure, we must first know that Python has nested function where one function can be defined inside another. For instance, the below inner_func is the nested function and the outer_func returns it’s nested function as return value.

def outer_func():    
    print("starting outer func")
    def inner_func():
        pi = 3.1415926
        print(f"pi is : {pi}")
    return inner_func

When you invoke the outer_func, it returns the reference to the inner_func, and subsequently you can call the inner_func. Below is the output when you run in Jupyter Notebook:

python closure nested function example

After you have got some feeling about the nested function, let’s continue to explore how nested function is related to closure. If we modify our previous function and move the pi variable into outer function, surprisedly it generates the same result as previously.

def outer_func():    
    print("starting outer func")
    #move pi variable definition to outer function
    pi = 3.1415926
    def inner_func():
        print(f"pi is : {pi}")
    return inner_func

You may wonder the pi variable is defined in outer function which is a local variable to outer_func, why inner_func is able access it since it’s not a global scope? This is exactly where closure happens, the inner_func has the full access to the environment (variables) in it’s enclosing scope. The inner_func refers to pi variable as nonlocal variable since there is no other local variable called pi.

If you want to modify the value of the pi inside the inner_func, you will have to explicitly specify “nonlocal pi” before you modify it since it’s immutable data type.

With the above understanding, now let’s walk through some real-world examples to see how we can use closure in our code.

Hide data with Python closure

Let’s say we want to implement a counter to record how many time the word has been repeated. The first thing you may want to do is to define a dictionary in global scope, and then create a function to add in the words as key into this dictionary and also update the number of times it repeated. Below is the sample code:

counter = {}

def count_word(word):    
    global counter
    counter[word] = counter.get(word, 0) + 1
    return counter[word]

To make sure the count_word function updates the correct “counter”, we need to put the global keyword to explicitly tell Python interpreter to use the “counter” defined in global scope, not any variable we accidentally defined with the same name in the local scope (within this function).

Sample output:

python closure word counter sample output

The above code works as expected, but there are two potential issues: Firstly, the global variable is accessible to any of the other functions and you cannot guarantee your data won’t be modified by others. Secondly, the global variable exists in the memory as long as the program is still running, so you may not want to create so many global variables if not necessary.

To address these two issues, let’s re-implement it with closure:

def word_counter():
    counter = {}
    def count(word):
        counter[word] = counter.get(word, 0) + 1
        return counter[word]
    return count

If we run it from Jupyter Notebook, you will see the below output:

python closure word counter example output

With this implementation, the counter dictionary is hidden from the public access and the functionality remains the same. (you may notice it works even after the word_counter function is deleted)

Convert small class to function with Python closure

Occasionally in your project, you may want to implement a small utility class to do some simple task. Let’s take a look at the below example:

import requests

class RequestMaker:
    def __init__(self, base_url):
        self.url = base_url
    def request(self, **kwargs):
        return requests.get(self.url.format_map(kwargs))

You can see the below output when you call the make_request from an instance of RequestMaker:

python closure small class example

Since you’ve already seen in the word counter example, the closure can also hold the data for your later use, the above class can be converted into a function with closure:

import requests

def request_maker(url):
    def make_request(**kwargs):
        return requests.get(url.format_map(kwargs))
    return make_request

The code becomes more concise and achieves the same result. Take note that in the above code, we are able to pass in the arguments into the nested function with **kwargs (or *args).

python closure convert small class to closure

Replace text with case matching

When you use regular express to find and replace some text, you may realize if you are trying to match text in case insensitive mode, you will not able to replace the text with proper case. For instance:

import re

paragraph = 'To start Python programming, you need to install python and configure PYTHON env.'
re.sub("python", "java", paragraph, flags=re.I)

Output from above:

python closure replace with case

It indeed replaced all the occurrence of the “python”, but the case does not match with the original text. To solve this problem, let’s implement the replace function with closure:

def replace_case(word):
    def replace(m):
        text = m.group()
        if text.islower():
            return word.lower()
        elif text.isupper():
            return word.upper()
        elif text[0].isupper():
            return word.capitalize()
        else:
            return word
    return replace

In the above code, the replace function has the access to the original text we intend to replace with, and when we detect the case of the matched text, we can convert the case of original text and return it back.

So in our original substitute function, let’s pass in a function replace_case(“java”) as the second argument. (You may refer to Python official doc in case you want to know what is the behavior when passing in function to re.sub)

re.sub("python", replace_case("java"), paragraph, flags=re.IGNORECASE)

If we run the above again, you should be able to see the case has been retained during the replacement as per below:

python closure replace with case

Conclusion

In this article, we have discussed about the general reasons why Python closure is used and also demonstrated how it can be used in your code with 3 real-world examples. In fact, Python decorator is also a use case of closure, I will be discussing this topic in the next article.

 

Pyinstaller upxdir and icon options

In previous article, we have discussed about most of the commonly used options for PyInstaller library. There are two more very useful options but you may encounter some issues when you use them for the first time. In this article, we will discuss about the common issues for using PyInstaller –icon and –upxdir options.

Customize icon for your exe file with –icon

PyInstaller has the –icon option to specify your own icon when creating the executable file. If this option is not given, the exe files will be generated with default icon as per below.

pyinstaller logo

You can use –icon followed by image file name to let PyInstaller to use your own icon. You may see errors when you try to use a normal image format as icon, in this case you can convert your image file into .ico format and run the command again.

For demo purpose, I downloaded an icon from this website into my project folder to use it for my app. And with the below command, I shall be able to get new look for my exe file.

pyinstaller --onefile hello.py --name "SuperHero" --add-data "test.config;." --icon "superhero.icon" --clean

Below is how it looks like when the new exe file generated:

Pyinstaller generate exe with icon

Sometimes, you may also find that the icon did not get changed after you rebuilt the executable file, but when checking the “General” tab in file properties, you are able to see the new icon displayed. This is due to the window icon cache, you may try to delete the cache files from the below directory and retry.

User\AppData\Local\Microsoft\Windows\Explorer\IconCacheToDelete

Or if you specify a new name for your exe file, you shall be able to see the new icon applied.

 

Reduce file size with PyInstaller –upx-dir option

When you used a lot of libraries or resource files, your executable file can grow very big and become difficult for distribution. In this case, you can use upx to compress your exe file.

You can download the upx executable file into your PC and copy the full path as the parameter value for –upx-dir option. E.g.:

pyinstaller --onefile hello.py --name "SuperHero" --add-data "test.config;." --icon "superhero.icon" --upx-dir "c:\upx-3.96-win64" --clean

Sometimes you may find even there is no error when you build the executable file, there can be a runtime error such as the below, which showing that VCRUNTIME140.dll is either not designed to run on Windows or it contains an error.

pyinstaller-VCRUNTIME140.dll-error

This issue is due to PyInstaller modified the dll files during packing and compressing. The workaround is that you use the –upx-exclude to exclude the particular dll files. (No need to specify the path for the dll)

pyinstaller --onefile hello.py --name "SuperHero" --add-data "test.config;." --icon "superhero.icon" --upx-dir "c:\upx-3.96-win64" --upx-exclude "VCRUNTIME140.dll" --clean

Conclusion

Beside the above issues we discussed, you may occasional encounter some other errors, you will need to check  both your Python and PyInstaller versions to see if is it some compatibility issues. And also not all the Python libraries are supported by PyInstaller, you will need to check this list to see if you have used any libraries not in supported by PyInstaller.

python split text with multiple delimiters

Python split text with multiple delimiters

There are cases you want to split a text which possibly use different symbols (delimiters) for separating the different elements, for instance, if the given text is in csv or tsv format, each field can be separated with comma (,) or tab (\t). You will need to write your code logic to support both delimiters. In this article, I will be sharing with you a few possible ways to split text with multiple delimiters in Python.

Checking if certain delimiter exists before splitting

If you are pretty sure the text will only contains one type of delimiter at a time, you can check if such delimiter exists before splitting. e.g. 

text = 'field1,field2,field3,field4'
#or 
text = 'field1;field2;field3;field4'

You can write a one-liner to check if comma exists before splitting by comma, otherwise splitting by semicolon.

text.split(",") if text.find(",") > -1 else text.split(";")

But if there are a lot of possible delimiters can be used in the text, or different delimiters can be mixed in the text, then writing the above if else logic will become very tedious work.  You might have thought about to use the replace function (see the full list of string functions from this article) to replace all the different delimiters into a single delimiter. It may work for your case, but it is far from a elegant solution.

So for such case, let’s move to the second option.

Using re to split text with multiple delimiters

In regular expression module, there is a split function which allows to split by pattern. You can specify all the possible delimiters with “|” to split the text with multiple delimiters at one time.

For instance, the below will extract the field1 to field5 into a list.

import re

text1 = "field1\tfield2,field3;field4 field5"
fields = re.split(r",|;|\s|\t", text1)

The result of fields will be list with all the data fields we want:

['field1', 'field2', 'field3', 'field4', 'field5']

What if you want to also keep these delimiters in the list for later use (e.g. reform back the text) ? You can use the capture groups () in the regular expression, so that the matched patterns will be also showing in the result.

fields = re.split(r'(,|;|\s|\t)', text1)

Result of fields variable:

['field1', '\t', 'field2', ',', 'field3', ';', 'field4', ' ', 'field5']

Conclusion

This quite common that we need write code to split text with multiple delimiters, and there are possibly other ways to solve this problem, but so far using the re.split still the most straightforward and efficient way.

pyinstaller pack python program into exe

How to pack python program into exe file

After you have built your python program, you may want to distribute this program to your users to run by themselves. However, in most of the cases, your uses either may not have the access to install Python for executing the script nor have the knowledge to run script from command line. In this case, you will need to find a way to pack your program into some executable file, so that it can be run with a simply click like other apps. In this article, I will be sharing with you how to pack python program into exe file with PyInstaller library for Windows users.

Prerequisite

You will need to create a virtual environment for your python program and activate it with the below command. I will explain why this is needed later.

python -m venv test
test\Scripts\activate.bat

Then install PyInstaller library:

pip install pyinstaller

Let’s get started

Let me first explain why we need to set up a virtual environment for your program. If you are concurrently working on different projects, and each of them are using a different set of python libraries, sometimes these libraries may conflict with each other due the version difference or other dependencies. In this case, you will need to use venv module to create a isolated python environment for each of your projects, so that each virtual environment only has the necessary libraries for running that particular python project.

Same comes when packing your program with PyInstaller, the virtual environment will ensure only the necessary libraries will be packed generating the executable file.

Build your Python program

For this article, our main objective is to demonstrate how to pack python program into exe file, so let’s just include some random library and write some dummy code.

pip install requests

And create a hello.py with the below code:

import requests
import sys, time

result = requests.get("https://www.google.com")
print(f"Google responded {result.status_code}")

with open("test.config") as f:
    print(f.read())

for i in range(15, 0, -1):
    sys.stdout.write("\r")
    sys.stdout.write(f"Window will be closed in {i:2d} seconds")
    sys.stdout.flush()
    time.sleep(1)

Let’s also create a file at the current directory called “test.config” and write some random words, saying “some configurations”.

If you run it with python hello.py, you shall get something similar output to the below:

Google responded 200
some configuration
Window will be closed in  1 seconds

Everything is ready, let’s move to the next step to pack python program into exe file.

Pack python program into exe file with PyInstaller

The PyInstaller program is actually quite easy to use, everything comes with a default option. E.g., If you do not specify any parameter and just run the below:

pyinstaller hello.py

You will be able to get a folder (onedir mode) under dist\hello, where you can find a hello.exe. But if you click to run it, it probably will auto close after a few seconds before you can see any error message.

The problem here is that, inside our program, we have some code to read some external file “test.config”, and this file was not packed into the dist\hello folder. Of course you can manually copy this file to dist\hello every time after you built the Python program, but there is a option you can use to tell PyInstaller to include the additional files.

–add-data option

This –add-data option can be used to include the additional file or directory. e.g.:

–add-data “src file or folder;dest file or folder”

If you have multiple files to be added, you can use this option multiple times. (for binary file, you may consider to use –add-binary option)

So you can re-run the below command to include the additional file, and also use –clean to clean up the directory before generating the files again.

pyinstaller hello.py --add-data "test.config;." --clean
–noconfirm option

You may see the warning similar to below to ask your confirmation to delete the old files, you can just key in “y” to confirm. This question can be avoided if you put the option –noconfirm.

WARNING: The output directory “c:\test\dist\hello” and ALL ITS CONTENTS will be REMOVED! Continue? (y/n)

So once the new exe file generated, you shall be able to run and see the below result:

pack python program into exe file

So far so good, but still can be better. Let’s specify the name of the exe file, and make it one file rather than a directory.

–onefile vs –onedir

With the below extra options : –onefile and –name “SuperHero”, we shall expect to pack the Python program into a single SuperHero.exe file.

pyinstaller --onefile hello.py --name "SuperHero" --add-data "test.config;." --clean

When we try to execute this exe file, you would see some error like below. This is because when running the exe, PyInstaller unpack your data into a temp folder, and the temp folder path is set to sys._MEIPASS, which will be different from your original file path.

pack python program into exe file

In this case, let’s modify our code again to cater for this:

import os

def get_resource_path(relative_path):
    try:
        # PyInstaller creates a temp folder and set the path in _MEIPASS
        base_path = sys._MEIPASS
    except Exception:
        base_path = os.path.abspath(".")

    return os.path.join(base_path, relative_path)

with open(get_resource_path("test.config")) as f:
    print(f.read())

When you rebuild the SuperHero.exe, this time you shall be able to execute it without any issue. And it also works perfectly if you rebuild your exe with –onedir mode.

–log-level

If you do not wish to see so many output messages when packing the program, you can turn it off by using the –log-level, the log level option can be one of TRACE, DEBUG, INFO, WARN, ERROR, CRITICAL. For instance, –log-level=”ERROR” will only show any output with error, and you do not even see a “Building completed successfully” message after build completion as it is logged as INFO.

–noconsole

If you are working with some automation program like auto sending emails or auto save some attachments, which does not necessarily interact with users, you can use –noconsole option, so when you click to run your exe file, it does not show up any console window.

PyInstaller specification file

You may noticed after you run the pyinstaller command, there is a .spec file generated. This file keeps all the options you have used for your last build. So if you just want to rebuild your executable files without changing any option, you may use the below command:

pyinstaller - D SuperHero.spec

Conclusion

With the options covered in above, it should meet your basic needs to pack python program into exe file. You may also refer to the official document for the other options PyInstaller offers.

python string data type

Python String Data Type

In the previous article, we have discussed about the Python variables including string variables. String is a Python built-in data type which holds a sequence of characters, you will need to use it whenever you need to do any text processing. In this article, I will be sharing with you the various operations you can perform with the Python string data type.

Python string data type

In python, you can define a string variable with single quote, double quotes or triple quotes. And use type() function to verify the data type of your variable. E.g.:

text1 = 'hello \n world!'
text2 = "bac;def,what$ is"
text3 = """this is also fine"""
print(type(text1), text1)
print(type(text2), text2)
print(type(text3), text3)

You should be able to see the below output, and the data type is showing as “str”.

<class 'str'> hello 
 world!
<class 'str'> bac;def,what$ is
<class 'str'> this is also fine
Slice Operation

As per the definition for Python string data type, it is a sequence of characters, which means you can access each of the character with the index. (index starts from 0 for the first element)

print(text1[0], text2[1], text3[2])
h a i

And you can use slice operation to get a sub set of your string variable:

#get a sub string starting from index 0 and ending at index 5 (exclusive)
print(text1[0:5])
#get a sub string starting from index 5 and ending at index 7 (exclusive)
print(text3[5:7])
#get a sub string starting from default index 0 and ending at index 4 (exclusive)
print(text3[:4])
#get a sub string starting from index 5 and ending at the end of the string
print(text3[5:])
hello
is
this
is also fine

You can also specify the negative index value to slice the string starting from right to left:

print(text1[-1])
print(text3[-3:-1])
!
in

There is actually a third option – slice step you can use, which you can specify a non-zero integer, e.g:

print(text4[0::2])
print(text4[1::2])
aceg
bdf
Immutable nature

Since we are able to get each individual character from a string, you may wonder if we can re-assign something else to a particular position in the string. e.g.:

text4[0] = 'T'
#TypeError: 'str' object does not support item assignment

The error shows up because string is immutable and you cannot change anything in it’s original content unless you create a new string:

new_text4 = "T" + text4[1:]
+ and *

And you may noticed different strings can be concatenated by using the “+” in the above example. There is also more operator * can be used in the string.

print(text4 + text3*2)

This will duplicate text3 twice and concatenate them into a single string:

abcdefgthis is also finethis is also fine
Formatting Python string data type

Below are some of the string formatting functions, it’s quite self-explanatory by the function name:

print("lower:", text4.lower())
#same as lower()
print("casefold:", text4.casefold())

print("upper:", text4.upper())

print("title:", text4.title())
#same as title
print("capitalize:", text4.capitalize())

print("swapcase:", text4.swapcase())
print("center:", text4.center(40, "*"))
print("ljust:", text4.ljust(40))
print("rjust:", text4.rjust(40, "*"))
print("zfill:", text4.zfill(40))
print("strip:", text4.strip("a"))
print("replace:", text4.replace("a", "A"))

Below is the output:

lower: abcdefg
casefold: abcdefg
upper: ABCDEFG
title: Abcdefg
capitalize: Abcdefg
swapcase: ABCDEFG
center: ****************abcdefg*****************
ljust: abcdefg                                 
rjust: *********************************abcdefg
zfill: 000000000000000000000000000000000abcdefg
strip: bcdefg
replace: Abcdefg

And also there are functions you can use for checking the string format:

print("isalnum:",text4.isalnum())	
print("isalpha:",text4.isalpha())
print("isdecimal:",text4.isdecimal())
print("isdigit:",text4.isdigit())
print("isnumeric:",text4.isnumeric())
print("isidentifier:",text4.isidentifier())
print("islower:",text4.islower())
print("istitle:",text4.istitle())
print("isupper:",text4.isupper())
print("isspace:",text4.isspace())
print("isprintable:",text4.isprintable())

Output will be something similar to below:

isalnum: True
isalpha: True
isdecimal: False
isdigit: False
isnumeric: False
isidentifier: True
islower: True
istitle: False
isupper: False
isspace: False
isprintable: True
Comparison operations

You can use relational operators such as ==, >, < to compare the two strings. Python will try to compare letter by letter, and all the uppercase letters come before lowercase, hence you will need to convert your texts into a standard format e.g. all upper or lower case, in order to get the comparison result in alphabetical order.

To check if the string starts/ends with any characters, you can use the startswith and endswith function:

if text3.startswith("this"):
    print("yes, it starts with 'this'")
if text3.endswith("fine"):
    print("yes, it ends with 'fine'")

There is no function called contains (sometime people get confused since Java string has this contains method), but you can use the below function – in, find, index or rindex to check if the string has any sub string:

if "this" in text3:
    print("'this' is in text3")
else:
    print("not found")

if text3.find("this") > -1:
    print("found 'this' from tex3")
else:
    print("not found")

if text3.find("this",1, 20) > -1:
    print("found 'this' from tex3")
else:
    print("'this' is not found from text3, starting from index 1 to 20 ")

if text3.index("this") >-1:
    print("found 'this' from tex3, index >=0")
else:
    print("not found")

#ValueError: substring not found
#idx = text3.index("this",1, 20)

Both find and index function return the index value of the sub string, the difference between of two function is that, index function will raise ValueError when the sub string is not found, while find will just return -1.

Split & Join texts

A lot times you may need to split the text by certain delimiter, e.g. newlines (\n), ; space etc. You can use the split function to the text into a list. If the delimiter is not found, the split function will return the original text as in a list.

print("split by default deliminator:", text3.split())
print("split by s", text3.split('s'))
print("split by ;", text3.split(';'))

The output will be:

split by default deliminator: ['this', 'is', 'also', 'fine']
split by s ['thi', ' i', ' al', 'o fine']
split by ; ['this is also fine']

On the other hand, if you have a list of string, you would like to join them into one string, you can do the following:

print("join the words with ';':", ';'.join(text3.split()))
print("join the words without space:", ''.join(text3.split()))

And below is the output:

join the words with ';': this;is;also;fine
join the words without space: thisisalsofine
Count occurrence

The count function can be used for calculating the occurrence of a sub string from the original string, for instance :

print(text3*5)
print("'is' occurence:',(text3*5).count("is"))

Result will be :

this is also finethis is also finethis is also finethis is also finethis is also fine
'is' occurence:10

Conclusion

With all the above examples provided, we have covered most of the commonly used functions for Python string data type. You may also check through the Python official document to see if there is any additional functions you are interested to know for the Python strings data type.