Hello World - In Metaverse

 

Introduction

The best way to predict future is to invent it - Alan Kay

Meta means beyond and verse is universe or planet. So, the metaverse is beyond the universe. By 2026, 25% of people will spend at least one hour a day in the metaverse for work, shopping, education, social and/or entertainment, according to Gartner, Inc. By 2026, 30% of the organizations in the world would have products and services ready for the metaverse. Following in this year 2023, Gartner warns that the metaverse is still in the nascent stages and the visibility of long-term investments are uncertain, it predicts that by 2027, over 40% of large organizations worldwide will be using Web3, spatial computing, and digital twins to increase revenue through metaverse based projects. This clearly shows this technology is here to stay in long run, as it takes internet and web world to the next level of user experience and utilize the multidimensional space effectually. 

I remember transition of user experience from keyboards (though before it we had punch cards), then to mouse, later to mobile, further to anywhere and anytime access though touch pads and now touch sensitive and in future spatial computing through sensors and glasses. To step into his virtual reality or mixed reality we can start taking the baby steps in building Webverse technology.

Business benifits of developing much deeper censorial immersive experience with the new generation technology, bringing in better user training, gamification, digitization and collaboration.

Tech Stack

Today's metaverse or XR including (AR/VR/MR) comprises of multiple emerging technologies that promise next level of interaction in the virtual and physical worlds. Below are the differences of the below:

• AR: Augmented Reality - Digital real world character in virtual world 
• VR: Virtual Reality - Completely different virtual world
• MR: Mixed Reality - Combination of real and virtual world

Programming Languages

In general, C++, C#, HTML, Javascript, GIS and Python are used to develop Webverse apps. Few frameworks such as Unity, Unreal Engine, Blender, A-Frame, Three.js, Babylon.js and so on.

Cloud

The metaverse and cloud computing are inseparable and will remain interconnected. Building a metaverse is almost impossible without highly available and scalable premises and hosting grounds. As the metaverse matures, it will add more layers of complexity and it will need a solid base to hold on to the heavy replica and provide a seamless experience to the users without any integration hassles or other bottlenecks at the backend. 

Spatial Computing

Spatial computing seamless integrate the virtual and physical worlds enhancing how we visualize, simulate and interact. This broadly characterizes the processes and tools used to capture, process and interact with 3D data. Components of spatial computing can include IoT, digital twins, ambient computing, augmented reality, virtual reality, AI and physical controls. Spatial computing is human interaction with a machine in which the machine retains and manipulates referents to real objects and spaces. As it is just not the display technology, but complex and computationally demanding "Sensor fusion systems".

Users interact with spatial computing applications through screens embedded on physical devices, VR headsets that mirror the physical world, mixed reality device or could be even through usual input devices that overlay data onto a view of the physical world.

Spatial computing mirrors how we interact with objects, people in the real world. There are two methods one of its through real time photography and creating 3D models. And the other is using AI techniques make sense of imagery. There are several papers published from Google's AI, NVIDIA's New AI, Microsoft AI, DeepMinds AI and so on. 

To build this one can use mostly the above described programming languages. Yeah today we would see the integration with the VR devices, but it is not blocker for us from developing the Webverse (in simple terms as like any web applications). 

Blockchain

The system that has a growing list of records (i.e. blocks) that are linked to one another is known as a blockchain. Fundamentally, the data stored in a blockchain must have the following characteristics:

• Immutable
• Unhackable
• Persistent (no loss of data)
• Distributed

These qualities are necessary to maintain the integrity of the blockchain and the security of the network within which the transactions occur.

The proof-of-work system makes it progressively more difficult to perform the work required to create a new block. This means that someone who modifies a previous block would have to redo the work of the block and all the blocks that follow. The proof-of-work system requires scanning for a value that starts with a certain number of zero bits when hashed.

Blockchain plays a vital role in metaverse development because the future of the web i.e Web 3.0 is all about the decentralization. It combines of many websites and platforms that may be accessed through a single browser. Also, on the metaverse blockchain, smart contracts are programs that may be used to automatically control the transfer of digital assets. The decentralized character of the blockchain technology with multi-nodes operates independently for synchronization. Specifically a blockchain powered metaverse would also make it fully independent and decentralized, allowing all users to participate, connect and contribute.

Example 1

Using the A-Frame we can have the below webpage created. 

Note: 

• environment : japan, there are other options as well like default, egpyt, forest and so on: https://supermedium.github.io/aframe-environment-component/#
• gltf images can be easily sourced this site : https://market.pmnd.rs/model/low-poly-farm

<html>

<head>

<script src="https://aframe.io/releases/1.3.0/aframe.min.js"></script>

<script src="https://unpkg.com/aframe-environment-component@1.3.1/dist/aframe-environment-component.min.js"></script>

</head>

<body>

<a-scene gltf-model="dracoDecoderPath: https://www.gstatic.com/draco/v1/decoders/;

meshoptDecoderPath: https://unpkg.com/meshoptimizer@0.16.0/meshopt_decoder.js;">

<a-assets>

<a-asset-item id="cyber_truck" src="https://vazxmixjsiawhamofees.supabase.co/storage/v1/object/public/models/ankou-with-cart/model.gltf"></a-asset-item>

<a-asset-item id="korrigan" src="https://vazxmixjsiawhamofees.supabase.co/storage/v1/object/public/models/korrigan-taning/model.gltf"></a-asset-item>

<a-asset-item id="house2" src="https://market-assets.fra1.cdn.digitaloceanspaces.com/market-assets/models/house-3/model.gltf"></a-asset-item>

<a-asset-item id="house3" src="https://market-assets.fra1.cdn.digitaloceanspaces.com/market-assets/models/low-poly-farm/model.gltf"></a-asset-item>

</a-assets>

<a-sky color="#ECECEC"></a-sky>

<a-entity environment="preset: japan;"></a-entity>

<a-entity position="3.5 0 -15" gltf-model="#cyber_truck"></a-entity>

<a-entity position="2 6 -14" rotation="0 -90 0" scale="1.25 1.25 1.25" gltf-model="#helicopter"></a-entity>

<a-entity position="0 0 -15" scale="9 9 9" gltf-model="#house"></a-entity>

<a-entity position="-14 0 -15" scale="7 7 7" gltf-model="#house2"></a-entity>

<a-entity position="14 0 -15" scale="7 7 7" gltf-model="#house3"></a-entity>

</a-scene>

</body>

</html>

Output:

Example 2

Using Babylon.js we can have the below we have default sample interactive webpage created.

Download: https://editor.babylonjs.com

For Mac OS requires explicit verification: https://www.lifewire.com/fix-developer-cannot-be-verified-error-5183898

Create a new project with default one player

Default Code Created

Below is the sample output:

We can have multiple players added and different keys for each, in later blogs we will look into more details of each of the framework.

Conclusion

Seeing the number of developments, patents and research in the field of metaverse and immersive visualization, one could confidently say we will in very much better state including the cost, security and performance. 

What a time to be alive!

References and Credits

https://indianexpress.com/article/technology/crypto/8-things-you-cant-do-in-the-metaverse-a-look-into-this-new-virtual-world-8156570/

https://www.youtube.com/watch?v=VONPW9tTGJw&list=PLhzcBQ1X_V6w_DbD_kCMezizEpxfxtE7O&index=1

https://www.gartner.com/en/webinar/452064/1065306

https://medium.com/@Hackyroot/https-medium-com-hackyroot-happy-birthday-using-aframe-9d2f0d177853

https://aframe.io

https://threejs.org/examples/#webgl_animation_keyframes

Interesting 20 Python Packages

 

Introduction

Python community has evolved so much is the past few decades, today we will see some of the useful packages from PyPI - The Python Package Index. PyPI is the repository of the software for the python programming language.

Packages

1. signal

Module: signal

Installation: Default Python Module

About:

Signals are an operating system feature that provide a means of notifying your program of an event, and having it handled asynchronously. They can be generated by the system itself, or sent from one process to another. Since signals interrupt the regular flow of your program, it is possible that some operations (especially I/O) may produce error if a signal is received in the middle.

Sample:

import signal

def alarm_received(n, stack):

return

signal.signal(signal.SIGALRM, alarm_received)

signals_to_names = {}

for n in dir(signal):

if n.startswith('SIG') and not n.startswith('SIG_'):

signals_to_names[getattr(signal, n)] = n

for s, name in sorted(signals_to_names.items()):

handler = signal.getsignal(s)

if handler is signal.SIG_DFL:

handler = 'SIG_DFL'

elif handler is signal.SIG_IGN:

handler = 'SIG_IGN'

print('%-10s (%2d):' % (name, s), handler)

'''

Output:

SIGHUP ( 1): SIG_DFL

SIGINT ( 2): <built-in function default_int_handler>

SIGQUIT ( 3): SIG_DFL

SIGILL ( 4): SIG_DFL

SIGTRAP ( 5): SIG_DFL

SIGIOT ( 6): SIG_DFL

SIGEMT ( 7): SIG_DFL

SIGFPE ( 8): SIG_DFL

SIGKILL ( 9): None

SIGBUS (10): SIG_DFL

SIGSEGV (11): SIG_DFL

SIGSYS (12): SIG_DFL

SIGPIPE (13): SIG_IGN

SIGALRM (14): <function alarm_received at 0x7fb2926bb160>

SIGTERM (15): SIG_DFL

SIGURG (16): SIG_DFL

SIGSTOP (17): None

SIGTSTP (18): SIG_DFL

SIGCONT (19): SIG_DFL

SIGCHLD (20): SIG_DFL

SIGTTIN (21): SIG_DFL

SIGTTOU (22): SIG_DFL

SIGIO (23): SIG_DFL

SIGXCPU (24): SIG_DFL

SIGXFSZ (25): SIG_IGN

SIGVTALRM (26): SIG_DFL

SIGPROF (27): SIG_DFL

SIGWINCH (28): SIG_DFL

SIGINFO (29): SIG_DFL

SIGUSR1 (30): SIG_DFL

SIGUSR2 (31): SIG_DFL

'''

Reference:

https://docs.python.org/3/library/signal.html

https://pymotw.com/2/signal/

2. scipy

Module: scipy

Installation: pip install scipy

About:

SciPy (pronounced “Sigh Pie”) is an open-source software for mathematics, science, and engineering. It includes modules for statistics, optimization, integration, linear algebra, Fourier transforms, signal and image processing, ODE solvers, and more. SciPy uses NumPy arrays as the basic data structure, and comes with modules for various commonly used tasks in scientific programming.

Sample:

# Import the required libraries

from scipy import linalg

import numpy as np

# The function takes two arrays

a = np.array([[7, 2], [4, 5]])

b = np.array([8, 10])

# Solving the linear equations

res = linalg.solve(a, b)

print(res)

'''

Output:

[0.74074074 1.40740741]

'''

Reference:

https://pypi.org/project/scipy/

https://docs.scipy.org/doc/scipy/

3. pytube

Module: pytube

Installation: pip install pytube

About:

pytube is a genuine, lightweight, dependency-free Python library (and command-line utility) for downloading YouTube videos.

pytube also makes pipelining easy, allowing you to specify callback functions for different download events, such as on progress or on complete.

Sample:

from pytube import YouTube

yt = YouTube('http://youtube.com/watch?v=2lAe1cqCOXo')

vedio_file = yt.streams.filter(progressive=True, file_extension='mp4').get_by_resolution('360p')

vedio_file.download("pycon_india.mp4")

print("download completed")

'''

Output:

>> ls

pycon_india.mp4

'''

Reference:

https://pypi.org/project/pytube/

4. pyperclip

Module: pyperclip

Installation: pip install pyperclip

About:

Pyperclip is a cross-platform Python module for copy and paste clipboard functions. If something outside your program changes the clipboard contents, the paste() function will return it. For example, if this sentence is copied to the clipboard and then paste() is called, the output would be printed.

Source:

import pyperclip

pyperclip.copy("Hello world !")

pyperclip.paste()

Reference:

https://pypi.org/project/pyperclip/

5. pyaztro

Module: pyaztro

Installation: pip install pyaztro

About:

PyAztro is a client library for aztro written in Python.

aztro provides horoscope info for sun signs such as Lucky Number, Lucky Color, Mood, Color, Compatibility with other sun signs, description of a sign for that day etc.

Sample:

import pyaztro

horoscope = pyaztro.Aztro(sign='aries')

print(horoscope.description)

'''

Output:

'Diligent'

'''

Reference:

https://pypi.org/project/pyaztro/

6. psutil

Module: psutil

Installation: pip install psutil

About:

Used to calculate the resource usage of a computer such as CPU, RAM, Disks, Network, Process, System info and so on.

Sample:

## Import

>> import psutil

## Process IDs

psutil.pids()

[1, 2, 3, 4, 5, 6, 7, 46, 48, 50, 51, 178, 182, 222, 223, 224, 268, 1215,

1216, 1220, 1221, 1243, 1244, 1301, 1601, 2237, 2355, 2637, 2774, 3932,

4176, 4177, 4185, 4187, 4189, 4225, 4243, 4245, 4263, 4282, 4306, 4311,

4312, 4313, 4314, 4337, 4339, 4357, 4358, 4363, 4383, 4395, 4408, 4433,

4443, 4445, 4446, 5167, 5234, 5235, 5252, 5318, 5424, 5644, 6987, 7054,

7055, 7071]

## CPU Info

>> psutil.cpu_times()

scputimes(user=3961.46, nice=169.729, system=2150.659, idle=16900.540, iowait=629.59, irq=0.0, softirq=19.42, steal=0.0, guest=0, nice=0.0)

## Memory

>> psutil.virtual_memory()

svmem(total=10367352832, available=6472179712, percent=37.6, used=8186245120, free=2181107712, active=4748992512, inactive=2758115328, buffers=790724608, cached=3500347392, shared=787554304)

>> psutil.swap_memory()

sswap(total=2097147904, used=296128512, free=1801019392, percent=14.1, sin=304193536, sout=677842944)

## Disk

>> psutil.disk_partitions()

[sdiskpart(device='/dev/sda1', mountpoint='/', fstype='ext4', opts='rw,nosuid', maxfile=255, maxpath=4096),

sdiskpart(device='/dev/sda2', mountpoint='/home', fstype='ext', opts='rw', maxfile=255, maxpath=4096)]

Reference:

https://pypi.org/project/psutil/

7. PyAutoGUI

Module: PyAutoGUI

Installation: pip install PyAutoGUI

About:

PyAutoGUI is a cross-platform GUI automation Python module for human beings. Used to programmatically control the mouse & keyboard, also can use it to take screenshots.

Sample:

import pyautogui

currentMouseX, currentMouseY = pyautogui.position() # Returns two integers, the x and y of the mouse cursor's current position.

im1 = pyautogui.screenshot() # Saves the screenshot of the current screen

im1.save('my_screenshot.png')

im2 = pyautogui.screenshot('my_screenshot2.png')

'''

Output:

2016-10-30 12:30:30

2016-10-30 12:30:30

time.struct_time(tm_year=2016, tm_mon=10, tm_mday=30, tm_hour=12, tm_min=30, tm_sec=30, tm_wday=6, tm_yday=304, tm_isdst=-1)

1477810830

'''

Reference:

https://pypi.org/project/PyAutoGUI/

8. PDFknife

Module: PDFknife

Installation: pip install PDFknife

About:

A Swiss Army Knife sort of python scripts collection to manipulate PDFs. It relies on:

pdfjam

pdftk

pdfunite (poppler)

ghostscript

mupdf-tools

Execution:

pdfknife-A5.py -- Turn a PDF in A5 format

pdfknife-even.py -- Add blank page to odd pages PDF

pdfknife-extract -- Extract images from PDF

pdfknife-merge.py -- Merge PDFs

pdfknife-recto.py -- Add blank page between each original page

pdfknife-reverse.py -- Reverse page order

pdfknife-shrink.py -- Compress a PDF

pdfknife-split.py -- Make one page per file

pdfknife-trim.py -- Change the margins

Reference:

https://pypi.org/project/PDFknife/

9. mypy

Module: mypy

Installation: pip install mypy

About:

Add type annotations to your Python programs, and use mypy to type check them. Mypy is essentially a Python linter on steroids, and it can catch many programming errors by analyzing your program, without actually having to run it. Mypy has a powerful type system with features such as type inference, gradual typing, generics and union types.

Sample:

$ pip install mypy

$ cat headlines.py

def headline(text: str, align: bool = True) -> str:

if align:

return f"{text.title()}\n{'-' * len(text)}"

else:

return f" {text.title()} ".center(50, "o")

print(headline("python type checking"))

print(headline("use mypy", align="center"))

$ mypy headlines.py

headlines.py:10: error: Argument "align" to "headline" has incompatible type "str"; expected "bool"

$ cat headlines.py

def headline(text: str, centered: bool = False):

if not centered:

return f"{text.title()}\n{'-' * len(text)}"

else:

return f" {text.title()} ".center(50, "o")

print(headline("python type checking"))

print(headline("use mypy", centered=True))

$ mypy headlines.py ## No output means no errors

Reference:

https://pypi.org/project/mypy/

https://realpython.com/lessons/type-checking-mypy/

10. modin

Module: modin

Installation: pip install modin

About:

Modin is a drop-in replacement for pandas. While pandas is single-threaded, Modin lets you instantly speed up your workflows by scaling pandas so it uses all of your cores. Modin works especially well on larger datasets, where pandas becomes painfully slow or runs out of memory.

By simply replacing the import statement, Modin offers users effortless speed and scale for their pandas workflows:

import modin.pandas as pd

Sample:

import modin.pandas as pd

import numpy as np

df = pd.read_csv("my_dataset.csv")

left_data = np.random.randint(0, 100, size=(2**8, 2**8))

right_data = np.random.randint(0, 100, size=(2**12, 2**12))

left_df = pd.DataFrame(left_data)

right_df = pd.DataFrame(right_data)

%timeit left_df.merge(right_df, how="inner", on=10)

3.59 s 107 ms per loop (mean std. dev. of 7 runs, 1 loop each)

%timeit right_df.merge(left_df, how="inner", on=10)

1.22 s 40.1 ms per loop (mean std. dev. of 7 runs, 1 loop each)

Reference:

https://pypi.org/project/modin/

11. Kivy

Module: Kivy

Installation: pip install Kivy

About:

Kivy is an open source, cross-platform Python framework for the development of applications that make use of innovative, multi-touch user interfaces.

The aim is to allow for quick and easy interaction design and rapid prototyping whilst making your code reusable and deployable.

Runs on Android, iOS, Linux, macOS, and Windows.

Support graphics engine built over the OpenGL ES 2.

Sample:

# base Class of your App inherits from the App class.

from kivy.app import App

# GridLayout arranges children in a matrix.

from kivy.uix.gridlayout import GridLayout

# Label is used to label something

from kivy.uix.label import Label

# used to take input from users

from kivy.uix.textinput import TextInput

class LoginScreen(GridLayout):

def __init__(self, **var_args):

super(LoginScreen, self).__init__(**var_args)

# super function can be used to gain access

# to inherited methods from a parent or sibling class

# that has been overwritten in a class object.

self.cols = 2 # You can change it accordingly

self.add_widget(Label(text='User Name'))

self.username = TextInput(multiline=True)

# multiline is used to take

# multiline input if it is true

self.add_widget(self.username)

self.add_widget(Label(text='password'))

self.password = TextInput(password=True, multiline=False)

# password true is used to hide it

# by * self.add_widget(self.password)

self.add_widget(Label(text='Comfirm password'))

self.password = TextInput(password=True, multiline=False)

self.add_widget(self.password)

# the Base Class of our Kivy App

class MyApp(App):

def build(self):

# return a LoginScreen() as a root widget

return LoginScreen()

if __name__ == '__main__':

MyApp().run()

Reference:

https://pypi.org/project/Kivy/

https://www.geeksforgeeks.org/python-make-a-simple-window-using-kivy/

12. fire

Module: fire

Installation: pip install fire

About:

Python Fire is a library for automatically generating command line interfaces (CLIs) with a single line of code.

It will turn any Python module, class, object, function, etc.  into a CLI. It’s called Fire because when you call Fire(), it fires off your command.

Sample:

import fire

def add(x, y):

return x + y

def multiply(x, y):

return x * y

if __name__ == '__main__':

fire.Fire()

'''

Output:

$ python example.py add 10 20

30

$ python example.py multiply 10 20

200

'''

Reference:

https://pypi.org/project/fire/

13. ExifRead

Module: ExifRead

Installation: pip install ExifRead

About:

Easy to use Python module to extract Exif metadata from digital image files.

Supported formats: TIFF, JPEG, PNG, Webp, HEIC.

Sample:

from os import path

import exifread

path_name = r'C:\Users\Desktop\sss.jpg'

filename = open(path_name, 'rb')

tags = exifread.process_file(filename)

print(tags)

'''

Output:

{'EXIF ApertureValue': (0x9202) Ratio=45/8 @ 644,

'EXIF ColorSpace': (0xA001) Short=sRGB @ 452,

'EXIF ComponentsConfiguration': (0x9101) Undefined=YCbCr @ 308,

'EXIF CustomRendered': (0xA401) Short=Normal @ 536,

....

'Image Orientation': (0x0112) Short=Horizontal (normal) @ 42,

'Image ResolutionUnit': (0x0128) Short=Pixels/Inch @ 78,

'Image Software': (0x0131) ASCII=GIMP 2.4.5 @ 182,

'Image XResolution': (0x011A) Ratio=72 @ 166,

'Image YResolution': (0x011B) Ratio=72 @ 174,

'Interoperability InteroperabilityIndex': (0x0001) ASCII=R98 @ 958,

'Interoperability InteroperabilityVersion': (0x0002) Undefined=[48, 49, 48, 48] @ 970,

'Thumbnail Compression': (0x0103) Short=JPEG (old-style) @ 1006,

'Thumbnail ResolutionUnit': (0x0128) Short=Pixels/Inch @ 1042,

'Thumbnail XResolution': (0x011A) Ratio=72 @ 1074,

'Thumbnail YResolution': (0x011B) Ratio=72 @ 1082}

'''

Reference:

https://pypi.org/project/ExifRead/

14. python-dateutil

Module: python-dateutil

Installation: pip install python-dateutil

About:

Generic parsing of dates in almost any string format. Computing of relative deltas (next month, next year, next Monday, last week of month, etc). Computing of relative deltas between two given date and/or datetime objects.

Sample:

>>> from dateutil.relativedelta import *

>>> from dateutil.easter import *

>>> from dateutil.rrule import *

>>> from dateutil.parser import *

>>> from datetime import *

>>> now = parse("Sat Oct 11 17:13:46 UTC 2003")

>>> today = now.date()

>>> print("Today is: %s" % today)

Today is: 2003-10-11

>>> year = rrule(YEARLY,dtstart=now,bymonth=8,bymonthday=13,byweekday=FR)[0].year

>>> print("Year with next Aug 13th on a Friday is: %s" % year)

Year with next Aug 13th on a Friday is: 2004

>>> rdelta = relativedelta(easter(year), today)

>>> print("How far is the Easter of that year: %s" % rdelta)

How far is the Easter of that year: relativedelta(months=+6)

>>> print("And the Easter of that year is: %s" % (today+rdelta))

And the Easter of that year is: 2004-04-11

Reference:

https://pypi.org/project/python-dateutil/

15. better-profanity

Module: better-profanity

Installation: pip install better-profanity

About:

A module that you can use to rid your text of bad words. 

Sample:

from better_profanity import profanity

custom_badwords = ['happy', 'jolly', 'merry']

profanity.add_censor_words(custom_badwords)

text = "This is sHit."

censored_text = profanity.censor(text)

print(censored_text) ## print censored string

text = "Have a merry day! :)"

print(profanity.contains_profanity(text)) ## verifies if string contains bad words

censored_text = profanity.censor(text)

print(censored_text)

'''

Output:

This is ****.

True

Have a **** day! :)

'''

Reference:

https://pypi.org/project/better-profanity/

16. BeautifulTime

Module: BeautifulTime

Installation: pip install BeautifulTime

About:

BeautifulTime is a python package for converting date string, datetime, time and timestamp.

Sample:

import BeautifulTime

date_str = '2016-10-30 12:30:30'

dt = BeautifulTime.str2datetime(date_str)

print(dt)

# with a custom format

dt = BeautifulTime.str2datetime(date_str, format='%Y-%m-%d %H:%M:%S')

print(dt)

t = BeautifulTime.str2time(date_str)

print(t)

ts = BeautifulTime.str2timestamp(date_str)

print(ts)

'''

Output:

2016-10-30 12:30:30

2016-10-30 12:30:30

time.struct_time(tm_year=2016, tm_mon=10, tm_mday=30, tm_hour=12, tm_min=30, tm_sec=30, tm_wday=6, tm_yday=304, tm_isdst=-1)

1477810830

'''

Reference:

https://pypi.org/project/BeautifulTime/

17. Bandit

Module: Bandit

Installation: pip install bandit

About:

Bandit is a tool designed to find common security issues in Python code. 

To do this Bandit processes each file, builds an AST from it, and runs appropriate plugins against the AST nodes. 

Once Bandit has finished scanning all the files it generates a report.

Bandit was originally developed within the OpenStack Security Project and later rehomed to PyCQA.

Sample:

% bandit thirukkural_sample.py

[main] INFO profile include tests: None

[main] INFO profile exclude tests: None

[main] INFO cli include tests: None

[main] INFO cli exclude tests: None

[main] INFO running on Python 3.8.5

[node_visitor] WARNING Unable to find qualified name for module: thirukkural_sample.py

Run started:2023-04-17 19:40:21.590814

Test results:

No issues identified.

Code scanned:

Total lines of code: 27

Total lines skipped (#nosec): 0

Run metrics:

Total issues (by severity):

Undefined: 0

Low: 0

Medium: 0

High: 0

Total issues (by confidence):

Undefined: 0

Low: 0

Medium: 0

High: 0

Files skipped (0):

Reference:

https://pypi.org/project/bandit/

18. arrow

Module: arrow

Installation: pip install arrow

About:

Arrow is a Python library that offers a human-friendly approach to creating, manipulating, formatting and converting dates, times and timestamps. It implements and updates the datetime type, plugging gaps in functionality and providing an intelligent module API that supports many common creation scenarios. 

Sample:

>>> import arrow

>>> arrow.get('2023-05-11T21:23:58.970460+07:00')

<Arrow [2023-05-11T21:23:58.970460+07:00]>

>>> utc = arrow.utcnow()

>>> utc

<Arrow [2023-05-11T21:23:58.970460+00:00]>

>>> utc = utc.shift(hours=-1)

>>> utc

<Arrow [2023-05-11T20:23:58.970460+00:00]>

>>> local = utc.to('US/Pacific')

>>> local

<Arrow [2023-05-11T13:23:58.970460-07:00]>

>>> local.timestamp()

1368303838.970460

>>> local.format()

'2023-05-11 13:23:58 -07:00'

>>> local.format('YYYY-MM-DD HH:mm:ss ZZ')

'2023-05-11 13:23:58 -07:00'

>>> local.humanize()

'an hour ago'

>>> local.humanize(locale='ko-kr')

'한시간 전'

Reference:

https://pypi.org/project/arrow/

19. tqdm

Module: tqdm

Installation: pip install tqdm

About:

tqdm derives from the Arabic word taqaddum (تقدّم) which can mean “progress”. Instantly make your loops show a smart progress meter - just wrap any iterable with tqdm(iterable), and you’re done!

Sample:

Reference:

https://pypi.org/project/tqdm/

20. gTTS

Module: gTTS

Installation: pip install gTTS

About:

gTTS (Google Text-to-Speech), a Python library and CLI tool to interface with Google Translate's text-to-speech API.

Sample: 

from gtts import gTTS

tts = gTTS('hello')

tts.save('hello.mp3')

Reference:

https://pypi.org/project/gTTS/