1582098506
A for loop is used for iterating over a sequence (that is either a list, a tuple, a dictionary, a set, or a string).
This is less like the for keyword in other programming languages, and works more like an iterator method as found in other object-orientated programming languages.
With the for loop we can execute a set of statements, once for each item in a list, tuple, set etc.
The for loop in Python is used to iterate over a sequence (list, tuple, string) or other iterable objects. Iterating over a sequence is called traversal.
for val in sequence:
Body of for
Here val
is a variable that is used for iterating over a . On every iteration it takes the next value from sequence
until the end of sequence is reached.
The following example shows the use of for loop to iterate over a list of numbers. In the body of for loop we are calculating the square of each number present in list and displaying the same.
# Program to print squares of all numbers present in a list
# List of integer numbers
numbers = [1, 2, 4, 6, 11, 20]
# variable to store the square of each num temporary
sq = 0
# iterating over the given list
for val in numbers:
# calculating square of each number
sq = val * val
# displaying the squares
print(sq)
Output:
1
4
16
36
121
400
In the above example, we have iterated over a list using for loop. However we can also use a range()
function in for loop to iterate over numbers defined by range()
.
range(n): generates a set of whole numbers starting from 0 to (n-1).
For example:
range(8) is equivalent to [0, 1, 2, 3, 4, 5, 6, 7]
range(start, stop): generates a set of whole numbers starting from start to stop-1.
For example:
range(5, 9) is equivalent to [5, 6, 7, 8]
range(start, stop, step_size): The default step_size is 1 which is why when we didn’t specify the step_size, the numbers generated are having difference of 1. However by specifying step_size we can generate numbers having the difference of step_size.
For example:
range(1, 10, 2) is equivalent to [1, 3, 5, 7, 9]
Lets use the range()
function in for loop:
Here we are using range() function to calculate and display the sum of first 5 natural numbers.
# Program to print the sum of first 5 natural numbers
# variable to store the sum
sum = 0
# iterating over natural numbers using range()
for val in range(1, 6):
# calculating sum
sum = sum + val
# displaying sum of first 5 natural numbers
print(sum)
Output:
15
A for loop can have an optional else block as well. The else part is executed if the items in the sequence used in for loop exhausts.
break statement can be used to stop a for loop. In such case, the else part is ignored.
Hence, a for loop’s else part runs if no break occurs.
Here is an example to illustrate this.
digits = [0, 1, 5]
for i in digits:
print(i)
else:
print("No items left.")
Output:
0
1
5
No items left.
Here, the for loop prints items of the list until the loop exhausts. When the for loop exhausts, it executes the block of code in the else and prints
Note: The else block only executes when the loop is finished.
When a for loop is present inside another for loop then it is called a nested for loop. Lets take an example of nested for loop.
for num1 in range(3):
for num2 in range(10, 14):
print(num1, ",", num2)
Output:
0 , 10
0 , 11
0 , 12
0 , 13
1 , 10
1 , 11
1 , 12
1 , 13
2 , 10
2 , 11
2 , 12
2 , 13
Thanks for reading .
#python #programming
1677668905
Mocking library for TypeScript inspired by http://mockito.org/
mock
) (also abstract classes) #examplespy
) #examplewhen
) via:verify
)reset
, resetCalls
) #example, #examplecapture
) #example'Expected "convertNumberToString(strictEqual(3))" to be called 2 time(s). But has been called 1 time(s).'
)npm install ts-mockito --save-dev
// Creating mock
let mockedFoo:Foo = mock(Foo);
// Getting instance from mock
let foo:Foo = instance(mockedFoo);
// Using instance in source code
foo.getBar(3);
foo.getBar(5);
// Explicit, readable verification
verify(mockedFoo.getBar(3)).called();
verify(mockedFoo.getBar(anything())).called();
// Creating mock
let mockedFoo:Foo = mock(Foo);
// stub method before execution
when(mockedFoo.getBar(3)).thenReturn('three');
// Getting instance
let foo:Foo = instance(mockedFoo);
// prints three
console.log(foo.getBar(3));
// prints null, because "getBar(999)" was not stubbed
console.log(foo.getBar(999));
// Creating mock
let mockedFoo:Foo = mock(Foo);
// stub getter before execution
when(mockedFoo.sampleGetter).thenReturn('three');
// Getting instance
let foo:Foo = instance(mockedFoo);
// prints three
console.log(foo.sampleGetter);
Syntax is the same as with getter values.
Please note, that stubbing properties that don't have getters only works if Proxy object is available (ES6).
// Creating mock
let mockedFoo:Foo = mock(Foo);
// Getting instance
let foo:Foo = instance(mockedFoo);
// Some calls
foo.getBar(1);
foo.getBar(2);
foo.getBar(2);
foo.getBar(3);
// Call count verification
verify(mockedFoo.getBar(1)).once(); // was called with arg === 1 only once
verify(mockedFoo.getBar(2)).twice(); // was called with arg === 2 exactly two times
verify(mockedFoo.getBar(between(2, 3))).thrice(); // was called with arg between 2-3 exactly three times
verify(mockedFoo.getBar(anyNumber()).times(4); // was called with any number arg exactly four times
verify(mockedFoo.getBar(2)).atLeast(2); // was called with arg === 2 min two times
verify(mockedFoo.getBar(anything())).atMost(4); // was called with any argument max four times
verify(mockedFoo.getBar(4)).never(); // was never called with arg === 4
// Creating mock
let mockedFoo:Foo = mock(Foo);
let mockedBar:Bar = mock(Bar);
// Getting instance
let foo:Foo = instance(mockedFoo);
let bar:Bar = instance(mockedBar);
// Some calls
foo.getBar(1);
bar.getFoo(2);
// Call order verification
verify(mockedFoo.getBar(1)).calledBefore(mockedBar.getFoo(2)); // foo.getBar(1) has been called before bar.getFoo(2)
verify(mockedBar.getFoo(2)).calledAfter(mockedFoo.getBar(1)); // bar.getFoo(2) has been called before foo.getBar(1)
verify(mockedFoo.getBar(1)).calledBefore(mockedBar.getFoo(999999)); // throws error (mockedBar.getFoo(999999) has never been called)
let mockedFoo:Foo = mock(Foo);
when(mockedFoo.getBar(10)).thenThrow(new Error('fatal error'));
let foo:Foo = instance(mockedFoo);
try {
foo.getBar(10);
} catch (error:Error) {
console.log(error.message); // 'fatal error'
}
You can also stub method with your own implementation
let mockedFoo:Foo = mock(Foo);
let foo:Foo = instance(mockedFoo);
when(mockedFoo.sumTwoNumbers(anyNumber(), anyNumber())).thenCall((arg1:number, arg2:number) => {
return arg1 * arg2;
});
// prints '50' because we've changed sum method implementation to multiply!
console.log(foo.sumTwoNumbers(5, 10));
You can also stub method to resolve / reject promise
let mockedFoo:Foo = mock(Foo);
when(mockedFoo.fetchData("a")).thenResolve({id: "a", value: "Hello world"});
when(mockedFoo.fetchData("b")).thenReject(new Error("b does not exist"));
You can reset just mock call counter
// Creating mock
let mockedFoo:Foo = mock(Foo);
// Getting instance
let foo:Foo = instance(mockedFoo);
// Some calls
foo.getBar(1);
foo.getBar(1);
verify(mockedFoo.getBar(1)).twice(); // getBar with arg "1" has been called twice
// Reset mock
resetCalls(mockedFoo);
// Call count verification
verify(mockedFoo.getBar(1)).never(); // has never been called after reset
You can also reset calls of multiple mocks at once resetCalls(firstMock, secondMock, thirdMock)
Or reset mock call counter with all stubs
// Creating mock
let mockedFoo:Foo = mock(Foo);
when(mockedFoo.getBar(1)).thenReturn("one").
// Getting instance
let foo:Foo = instance(mockedFoo);
// Some calls
console.log(foo.getBar(1)); // "one" - as defined in stub
console.log(foo.getBar(1)); // "one" - as defined in stub
verify(mockedFoo.getBar(1)).twice(); // getBar with arg "1" has been called twice
// Reset mock
reset(mockedFoo);
// Call count verification
verify(mockedFoo.getBar(1)).never(); // has never been called after reset
console.log(foo.getBar(1)); // null - previously added stub has been removed
You can also reset multiple mocks at once reset(firstMock, secondMock, thirdMock)
let mockedFoo:Foo = mock(Foo);
let foo:Foo = instance(mockedFoo);
// Call method
foo.sumTwoNumbers(1, 2);
// Check first arg captor values
const [firstArg, secondArg] = capture(mockedFoo.sumTwoNumbers).last();
console.log(firstArg); // prints 1
console.log(secondArg); // prints 2
You can also get other calls using first()
, second()
, byCallIndex(3)
and more...
You can set multiple returning values for same matching values
const mockedFoo:Foo = mock(Foo);
when(mockedFoo.getBar(anyNumber())).thenReturn('one').thenReturn('two').thenReturn('three');
const foo:Foo = instance(mockedFoo);
console.log(foo.getBar(1)); // one
console.log(foo.getBar(1)); // two
console.log(foo.getBar(1)); // three
console.log(foo.getBar(1)); // three - last defined behavior will be repeated infinitely
Another example with specific values
let mockedFoo:Foo = mock(Foo);
when(mockedFoo.getBar(1)).thenReturn('one').thenReturn('another one');
when(mockedFoo.getBar(2)).thenReturn('two');
let foo:Foo = instance(mockedFoo);
console.log(foo.getBar(1)); // one
console.log(foo.getBar(2)); // two
console.log(foo.getBar(1)); // another one
console.log(foo.getBar(1)); // another one - this is last defined behavior for arg '1' so it will be repeated
console.log(foo.getBar(2)); // two
console.log(foo.getBar(2)); // two - this is last defined behavior for arg '2' so it will be repeated
Short notation:
const mockedFoo:Foo = mock(Foo);
// You can specify return values as multiple thenReturn args
when(mockedFoo.getBar(anyNumber())).thenReturn('one', 'two', 'three');
const foo:Foo = instance(mockedFoo);
console.log(foo.getBar(1)); // one
console.log(foo.getBar(1)); // two
console.log(foo.getBar(1)); // three
console.log(foo.getBar(1)); // three - last defined behavior will be repeated infinity
Possible errors:
const mockedFoo:Foo = mock(Foo);
// When multiple matchers, matches same result:
when(mockedFoo.getBar(anyNumber())).thenReturn('one');
when(mockedFoo.getBar(3)).thenReturn('one');
const foo:Foo = instance(mockedFoo);
foo.getBar(3); // MultipleMatchersMatchSameStubError will be thrown, two matchers match same method call
You can mock interfaces too, just instead of passing type to mock
function, set mock
function generic type Mocking interfaces requires Proxy
implementation
let mockedFoo:Foo = mock<FooInterface>(); // instead of mock(FooInterface)
const foo: SampleGeneric<FooInterface> = instance(mockedFoo);
You can mock abstract classes
const mockedFoo: SampleAbstractClass = mock(SampleAbstractClass);
const foo: SampleAbstractClass = instance(mockedFoo);
You can also mock generic classes, but note that generic type is just needed by mock type definition
const mockedFoo: SampleGeneric<SampleInterface> = mock(SampleGeneric);
const foo: SampleGeneric<SampleInterface> = instance(mockedFoo);
You can partially mock an existing instance:
const foo: Foo = new Foo();
const spiedFoo = spy(foo);
when(spiedFoo.getBar(3)).thenReturn('one');
console.log(foo.getBar(3)); // 'one'
console.log(foo.getBaz()); // call to a real method
You can spy on plain objects too:
const foo = { bar: () => 42 };
const spiedFoo = spy(foo);
foo.bar();
console.log(capture(spiedFoo.bar).last()); // [42]
Author: NagRock
Source Code: https://github.com/NagRock/ts-mockito
License: MIT license
1624331040
A Python tutorial to understand the uses of for loop in various ways including examples.
Python is a general-purpose programming language, which emphasizes making programming easy, efficient coding, and unleashes the user’s potential. Loops are the vital part of programming as it allows the user to repetitive use a set of codes using loops. So in the following article, we will see how to use for
loops in python.
Till the iteration of the last item in the sequence, for loop run the instructions. It iterates over sets of instructions in sequence, arrays, and a tuple for a pre-defined period or until the last item and calculation are executed.
For loop can be categorized in three ways.
#python #for loop #loops #loop #python for loop
1625170860
Python is a renowned general-purpose programming language. Unlike HTML or CSS, general-purpose programming languages are used in several application domains.
In programming languages, loops are a set of instructions that execute a sequence of code continuously until a certain condition is fulfilled. Most modern programming languages do include the concept of loops. The syntax for loops in each language may differ but the logic being used remains the same.
Many programming languages have several types of loops and the most renowned ones are while and for loop. Today we will only learn about while loop and where it should be preferred over other kinds of loops.
In most cases loops are interchangeable with each other but while loop should be preferred over other loops when the required condition is boolean. We can think of a while loop as a repeating if statement, to make the concept easier to understand.
#python #loop #while #python while loop with examples #python while loop
1626775355
No programming language is pretty much as diverse as Python. It enables building cutting edge applications effortlessly. Developers are as yet investigating the full capability of end-to-end Python development services in various areas.
By areas, we mean FinTech, HealthTech, InsureTech, Cybersecurity, and that's just the beginning. These are New Economy areas, and Python has the ability to serve every one of them. The vast majority of them require massive computational abilities. Python's code is dynamic and powerful - equipped for taking care of the heavy traffic and substantial algorithmic capacities.
Programming advancement is multidimensional today. Endeavor programming requires an intelligent application with AI and ML capacities. Shopper based applications require information examination to convey a superior client experience. Netflix, Trello, and Amazon are genuine instances of such applications. Python assists with building them effortlessly.
Python can do such numerous things that developers can't discover enough reasons to admire it. Python application development isn't restricted to web and enterprise applications. It is exceptionally adaptable and superb for a wide range of uses.
Robust frameworks
Python is known for its tools and frameworks. There's a structure for everything. Django is helpful for building web applications, venture applications, logical applications, and mathematical processing. Flask is another web improvement framework with no conditions.
Web2Py, CherryPy, and Falcon offer incredible capabilities to customize Python development services. A large portion of them are open-source frameworks that allow quick turn of events.
Simple to read and compose
Python has an improved sentence structure - one that is like the English language. New engineers for Python can undoubtedly understand where they stand in the development process. The simplicity of composing allows quick application building.
The motivation behind building Python, as said by its maker Guido Van Rossum, was to empower even beginner engineers to comprehend the programming language. The simple coding likewise permits developers to roll out speedy improvements without getting confused by pointless subtleties.
Utilized by the best
Alright - Python isn't simply one more programming language. It should have something, which is the reason the business giants use it. Furthermore, that too for different purposes. Developers at Google use Python to assemble framework organization systems, parallel information pusher, code audit, testing and QA, and substantially more. Netflix utilizes Python web development services for its recommendation algorithm and media player.
Massive community support
Python has a steadily developing community that offers enormous help. From amateurs to specialists, there's everybody. There are a lot of instructional exercises, documentation, and guides accessible for Python web development solutions.
Today, numerous universities start with Python, adding to the quantity of individuals in the community. Frequently, Python designers team up on various tasks and help each other with algorithmic, utilitarian, and application critical thinking.
Progressive applications
Python is the greatest supporter of data science, Machine Learning, and Artificial Intelligence at any enterprise software development company. Its utilization cases in cutting edge applications are the most compelling motivation for its prosperity. Python is the second most well known tool after R for data analytics.
The simplicity of getting sorted out, overseeing, and visualizing information through unique libraries makes it ideal for data based applications. TensorFlow for neural networks and OpenCV for computer vision are two of Python's most well known use cases for Machine learning applications.
Thinking about the advances in programming and innovation, Python is a YES for an assorted scope of utilizations. Game development, web application development services, GUI advancement, ML and AI improvement, Enterprise and customer applications - every one of them uses Python to its full potential.
The disadvantages of Python web improvement arrangements are regularly disregarded by developers and organizations because of the advantages it gives. They focus on quality over speed and performance over blunders. That is the reason it's a good idea to utilize Python for building the applications of the future.
#python development services #python development company #python app development #python development #python in web development #python software development
1567822183
In this lab we are going to build demo TARS from Interstellar movie with Python. TARS can help you to automate your tasks such as search videos in YouTube and play them, send emails, open websites, search materials in Wikipedia and read them,inform weather forecast in your country, greetings and more. By building TARS you will increase your Python knowledge and learn many useful libraries/tools. I will push source code to my git repository so feel free to contribute and improve functionality of TARS
Let’s start by creating virtual environment and building the base audio system of TARS.
mkdir TARS
cd TARS
virtualenv venv
To activate the venv run command below
. venv/bin/activate
What is virtual environment?
Once you activated venv, we need to install main libraries by following commands:
pip3 install gTTS
pip3 install SpeechRecognition
pip3 install PyAudio
pip3 install pygame
gTTS (Google Text-to-Speech) is a Python library and CLI tool to interface with Google Translate’s text-to-speech API. This module helps to convert String text to Spoken text and can be saved as .mp3
Speech Recognition is an important feature in several applications used such as home automation, artificial intelligence, etc. Recognizing speech needs audio input, and SpeechRecognition makes it really simple to retrieve this input. Instead of building scripts from scratch to access microphones and process audio files, SpeechRecognition will have you up and running in just a few minutes.
To access your microphone with SpeechRecognizer, you’ll have to install the PyAudio package
Pygame is a cross-platform set of Python modules designed for writing video games. It includes computer graphics and sound libraries designed to be used with the Python programming language.
Now, let’s build voice system of TARS:
from gtts import gTTS
import speech_recognition as sr
from pygame import mixer
def talk(audio):
print(audio)
for line in audio.splitlines():
text_to_speech = gTTS(text=audio, lang='en-uk')
text_to_speech.save('audio.mp3')
mixer.init()
mixer.music.load("audio.mp3")
mixer.music.play()
As you see we are passing audio as an argument to let the TARS speak. For instance, talk(‘Hey I am TARS! How can I help you?’) program will loop these lines with the help of splitlines() method. This method is used to split the lines at line boundaries. Check splitlines() for more. Then, gTTS will handle to convert all these texts to speech. text parameter defines text to be read and lang defines the language (IETF language tag) to read the text in. Once loop finished, save() method writes result to file.
pygame.mixer is a module for loading and playing sounds and must be initialized before using it.
Alright! Now, let’s create a function that will listen for commands.
def myCommand():
#Initialize the recognizer
r = sr.Recognizer()
with sr.Microphone() as source:
print('TARS is Ready...')
r.pause_threshold = 1
#wait for a second to let the recognizer adjust the
#energy threshold based on the surrounding noise level
r.adjust_for_ambient_noise(source, duration=1)
#listens for the user's input
audio = r.listen(source)
try:
command = r.recognize_google(audio).lower()
print('You said: ' + command + '\n')
#loop back to continue to listen for commands if unrecognizable speech is received
except sr.UnknownValueError:
print('Your last command couldn\'t be heard')
command = myCommand();
return command
In this function we are using SpeechRecognition library. It acts as a wrapper for several popular speech APIs and is thus extremely flexible. One of these—the Google Web Speech API—supports a default API key that is hard-coded into the SpeechRecognition library. That means you can get off your feet without having to sign up for a service.
To be able to work with your own voice with speech recognition, you need the PyAudio package. Like Recognizer for audio files, we will need Microphone for real-time speech data.
You can capture input from the microphone using the listen() method of the Recognizer class inside of the with block. This method takes an audio source as its first argument and records input from the source until silence is detected.
Try to say your commands in silence place( with less background noise ) otherwise TARS can confuse.
Take a look The Ultimate Guide To Speech Recognition With Python
import random
def tars(command):
errors=[
"I don\'t know what you mean!",
"Excuse me?",
"Can you repeat it please?",
]
if 'Hello' in command:
talk('Hello! I am TARS. How can I help you?')
else:
error = random.choice(errors)
talk(error)
talk('TARS is ready!')
while True:
assistant(myCommand())
Once you run the program TARS will start talk with you by saying ‘TARS is ready!’ and continue to listen your commands until you stop the program. Start by saying ‘Hello’ :)
When TARS didn’t get the command we will handle the error by random sentences.
Here is the full code of main structure:
from gtts import gTTS
import speech_recognition as sr
from pygame import mixer
import random
def talk(audio):
print(audio)
for line in audio.splitlines():
text_to_speech = gTTS(text=audio, lang='en-uk')
text_to_speech.save('audio.mp3')
mixer.init()
mixer.music.load("audio.mp3")
mixer.music.play()
def myCommand():
#Initialize the recognizer
#The primary purpose of a Recognizer instance is, of course, to recognize speech.
r = sr.Recognizer()
with sr.Microphone() as source:
print('TARS is Ready...')
r.pause_threshold = 2
#wait for a second to let the recognizer adjust the
#energy threshold based on the surrounding noise level
r.adjust_for_ambient_noise(source, duration=1)
#listens for the user's input
audio = r.listen(source)
try:
command = r.recognize_google(audio).lower()
print('You said: ' + command + '\n')
#loop back to continue to listen for commands if unrecognizable speech is received
except sr.UnknownValueError:
print('Your last command couldn\'t be heard')
command = myCommand();
return command
def tars(command):
errors=[
"I don't know what you mean",
"Did you mean astronaut?",
"Can you repeat it please?",
]
if 'hello' in command:
talk('Hello! I am TARS. How can I help you?')
else:
error = random.choice(errors)
talk(error)
talk('TARS is ready!')
#loop to continue executing multiple commands
while True:
tars(myCommand())
Well… Is AI anything more than a bunch of IF statements?
If you are talking about “real” AI , then yes it’s a lot more than just If statements.The development of AI has historically been split into two fields; symbolic AI, and machine learning.
Symbolic AI is the field in which artificially intelligent systems were designed with if-else type logic. Programmers would attempt to define every possible scenario for the system to deal with. Until the late seventies this was the dominant form of AI system development. Experts in the field argued very strongly that machine-learning would never catch on and that AI could only be written in this way.
Now we know that accounting for every possible scenario in an intelligent system is enormously impractical and we use machine-learning instead. Machine learning uses statistics to look for and define patterns in data so that a machine can learn about and improve the tasks that it is designed to perform. This is significantly more flexible.
We are using just bunch of IF statements to understand basics of AI. But we will implement some cool ML algorithms later.
I hope you learned new things so far, now, it is time to teach TARS how to automate stuff.
Open Google and search for something
We are going to import webbrowser module in Python which provides an interface to display Web-based documents.
While we are saying commands, TARS have to detect availability of these commands by matching them. Python has a built-in package called re, which can be used to work with Regular Expressions.
import re
import webbrowser
if 'open google' in command:
#matching command to check it is available
reg_ex = re.search('open google (.*)', command)
url = 'https://www.google.com/'
if reg_ex:
subgoogle = reg_ex.group(1)
url = url + 'r/' + subreddit
webbrowser.open(url)
print('Done!')
The re.search() method takes a regular expression pattern and a string and searches for that pattern within the string. If the search is successful, search() returns a match object or None otherwise. Therefore, the search is usually immediately followed by an if-statement to test if the search succeeded
The code reg_ex = re.search('open google (.)', command)* stores the search result in a variable named “reg_ex”. Then the if-statement tests the match – if true the search succeeded and group() is the matching text. Otherwise if the match is false (None to be more specific), then the search did not succeed, and there is no matching text. The 1 in reg_ex.group(1) represents the first parenthesized subgroup.
Even you can install Selenium to make search in Google by TARS. To install Selenium run the following command:
pip3 install selenium
Selenium WebDriver is a collection of open source APIs which are used to automate the testing of a web application. This tool is used to automate web application testing to verify that it works as expected. It supports many browsers such as Safari, Firefox, IE, and Chrome.
You can search how to use Selenium with Python there is a lot of sources on internet and it is really easy to learn. Let’s add this feature to TARS
from selenium import webdriver
from selenium.webdriver.common.keys import Keys
if 'open google and search' in command:
reg_ex = re.search('open google and search (.*)', command)
search_for = command.split("search",1)[1]
url = 'https://www.google.com/'
if reg_ex:
subgoogle = reg_ex.group(1)
url = url + 'r/' + subgoogle
talk('Okay!')
driver = webdriver.Firefox(executable_path='/path/to/geckodriver') #depends which web browser you are using
driver.get('http://www.google.com')
search = driver.find_element_by_name('q') # finds search
search.send_keys(str(search_for)) #sends search keys
search.send_keys(Keys.RETURN) #hits enter
TARS will consider strings after “open google and search” command and takes all words as a search keys. I am using Firefox so I installed geckodriver but if you are using Chrome check the following StackOverflow question.
We are going to import smtplib to send emails with Python. SMTP stands for Simple Mail Transfer Protocol and it is useful for communicating with mail servers to send mail.
import smtplib
elif 'email' or 'gmail' in command:
talk('What is the subject?')
time.sleep(3)
subject = myCommand()
talk('What should I say?')
time.sleep(3)
message = myCommand()
content = 'Subject: {}\n\n{}'.format(subject, message)
#init gmail SMTP
mail = smtplib.SMTP('smtp.gmail.com', 587)
#identify to server
mail.ehlo()
#encrypt session
mail.starttls()
#login
mail.login('your_gmail', 'your_gmail_password')
#send message
mail.sendmail('FROM', 'TO', content)
#end mail connection
mail.close()
talk('Email sent.')
Note that, in a nutshell, google is not allowing you to log in via smtplib because it has flagged this sort of login as “less secure”, so what you have to do is go to this link while you’re logged in to your google account, and allow the access.
Crawl Data
We are doing great so far! TARS can send mails and search whatever you want on google. Now, let’s implement more complex function to make TARS crawl some Wikipedia data and read it for us.
Beautiful Soup is a Python library for pulling data out of HTML and XML files. It works with your favorite parser to provide idiomatic ways of navigating, searching, and modifying the parse tree. It commonly saves programmers hours or days of work. Run the following command in your terminal to install beautifulsoup:
pip install beautifulsoup4
We also will need requests library for making HTTP requests in Python. It abstracts the complexities of making requests behind a beautiful, simple API so that you can focus on interacting with services and consuming data in your application. Alright! Let’s see the code:
import bs4
import requests
elif 'wikipedia' in command:
reg_ex = re.search('search in wikipedia (.+)', command)
if reg_ex:
query = command.split()
response = requests.get("https://en.wikipedia.org/wiki/" + query[3])
if response is not None:
html = bs4.BeautifulSoup(response.text, 'html.parser')
title = html.select("#firstHeading")[0].text
paragraphs = html.select("p")
for para in paragraphs:
print (para.text)
intro = '\n'.join([ para.text for para in paragraphs[0:5]])
print (intro)
mp3name = 'speech.mp3'
language = 'en'
myobj = gTTS(text=intro, lang=language, slow=False)
myobj.save(mp3name)
mixer.init()
mixer.music.load("speech.mp3")
mixer.music.play()
elif 'stop' in command:
mixer.music.stop()
“search in wikipedia Mars” and TARS will take “Mars” as a keyword to search in Wikipedia. If you search something on Wikipedia you will see URL will look like https://en.wikipedia.org/wiki/Keyword so we are sending get request with keyword(what to search) to access data. Once request succeed, beautifulsoup will parse content inside Wikipedia. The join() method is a string method and returns a string in which the elements of sequence have been joined by str separator and we are using it to separate paragraphs. You already familiar with gTTS and mixer so I am passing that part.
TARS will display the crawled data on console and start to reading it for you.
Search videos on YouTube and play
This function is similar to search with google but this time it is better to use urllib. The main objective is to learn new things with Python, so I don’t want include Selenium in this function. Here is the code:
import urllib.request #used to make requests
import urllib.parse #used to parse values into the url
elif 'youtube' in command:
talk('Ok!')
reg_ex = re.search('youtube (.+)', command)
if reg_ex:
domain = command.split("youtube",1)[1]
query_string = urllib.parse.urlencode({"search_query" : domain})
html_content = urllib.request.urlopen("http://www.youtube.com/results?" + query_string)
search_results = re.findall(r'href=\"\/watch\?v=(.{11})', html_content.read().decode()) # finds all links in search result
webbrowser.open("http://www.youtube.com/watch?v={}".format(search_results[0]))
pass
The urllib module in Python 3 allows you access websites via your program. This opens up as many doors for your programs as the internet opens up for you. urllib in Python 3 is slightly different than urllib2 in Python 2, but they are mostly the same. Through urllib, you can access websites, download data, parse data, modify your headers, and do any GET and POST requests you might need to do.
Check this tutorial for more about urllib
Search key must be encoded before parsing into url. If you search something on YouTube you can see after [http://www.youtube.com/results?"](http://www.youtube.com/results?" “http://www.youtube.com/results?"”) there is a encoded search keys. Once these search keys encoded program can successfully access search results. The expression re.findall() returns all the non-overlapping matches of patterns in a string as a list of strings. Each video on youtube has its own 11 characters ID (https://www.youtube.com/watch?v=gEPmA3USJdI)and re.findall() will find all matches in decoded html_content(in search results page). decode() is used to convert from one encoding scheme, in which argument string is encoded to the desired encoding scheme. This works opposite to the encode. It accepts the encoding of the encoding string to decode it and returns the original string. Finally, it plays first video in search results because usually the first video is nearest one for search keys.
Full Code:
from gtts import gTTS
import speech_recognition as sr
import re
import time
import webbrowser
import random
from selenium import webdriver
from selenium.webdriver.common.keys import Keys
import smtplib
import requests
from pygame import mixer
import urllib.request
import urllib.parse
import bs4
def talk(audio):
"speaks audio passed as argument"
print(audio)
for line in audio.splitlines():
text_to_speech = gTTS(text=audio, lang='en-uk')
text_to_speech.save('audio.mp3')
mixer.init()
mixer.music.load("audio.mp3")
mixer.music.play()
def myCommand():
"listens for commands"
#Initialize the recognizer
#The primary purpose of a Recognizer instance is, of course, to recognize speech.
r = sr.Recognizer()
with sr.Microphone() as source:
print('TARS is Ready...')
r.pause_threshold = 1
#wait for a second to let the recognizer adjust the
#energy threshold based on the surrounding noise level
r.adjust_for_ambient_noise(source, duration=1)
#listens for the user's input
audio = r.listen(source)
print('analyzing...')
try:
command = r.recognize_google(audio).lower()
print('You said: ' + command + '\n')
time.sleep(2)
#loop back to continue to listen for commands if unrecognizable speech is received
except sr.UnknownValueError:
print('Your last command couldn\'t be heard')
command = myCommand();
return command
def tars(command):
errors=[
"I don't know what you mean",
"Excuse me?",
"Can you repeat it please?",
]
"if statements for executing commands"
# Search on Google
if 'open google and search' in command:
reg_ex = re.search('open google and search (.*)', command)
search_for = command.split("search",1)[1]
print(search_for)
url = 'https://www.google.com/'
if reg_ex:
subgoogle = reg_ex.group(1)
url = url + 'r/' + subgoogle
talk('Okay!')
driver = webdriver.Firefox(executable_path='/home/coderasha/Desktop/geckodriver')
driver.get('http://www.google.com')
search = driver.find_element_by_name('q')
search.send_keys(str(search_for))
search.send_keys(Keys.RETURN) # hit return after you enter search text
#Send Email
elif 'email' in command:
talk('What is the subject?')
time.sleep(3)
subject = myCommand()
talk('What should I say?')
message = myCommand()
content = 'Subject: {}\n\n{}'.format(subject, message)
#init gmail SMTP
mail = smtplib.SMTP('smtp.gmail.com', 587)
#identify to server
mail.ehlo()
#encrypt session
mail.starttls()
#login
mail.login('your_mail', 'your_mail_password')
#send message
mail.sendmail('FROM', 'TO', content)
#end mail connection
mail.close()
talk('Email sent.')
# search in wikipedia (e.g. Can you search in wikipedia apples)
elif 'wikipedia' in command:
reg_ex = re.search('wikipedia (.+)', command)
if reg_ex:
query = command.split("wikipedia",1)[1]
response = requests.get("https://en.wikipedia.org/wiki/" + query)
if response is not None:
html = bs4.BeautifulSoup(response.text, 'html.parser')
title = html.select("#firstHeading")[0].text
paragraphs = html.select("p")
for para in paragraphs:
print (para.text)
intro = '\n'.join([ para.text for para in paragraphs[0:3]])
print (intro)
mp3name = 'speech.mp3'
language = 'en'
myobj = gTTS(text=intro, lang=language, slow=False)
myobj.save(mp3name)
mixer.init()
mixer.music.load("speech.mp3")
while mixer.music.play()
elif 'stop' in command:
mixer.music.stop()
# Search videos on Youtube and play (e.g. Search in youtube believer)
elif 'youtube' in command:
talk('Ok!')
reg_ex = re.search('youtube (.+)', command)
if reg_ex:
domain = command.split("youtube",1)[1]
query_string = urllib.parse.urlencode({"search_query" : domain})
html_content = urllib.request.urlopen("http://www.youtube.com/results?" + query_string)
search_results = re.findall(r'href=\"\/watch\?v=(.{11})', html_content.read().decode())
#print("http://www.youtube.com/watch?v=" + search_results[0])
webbrowser.open("http://www.youtube.com/watch?v={}".format(search_results[0]))
pass
elif 'hello' in command:
talk('Hello! I am TARS. How can I help you?')
time.sleep(3)
elif 'who are you' in command:
talk('I am one of four former U.S. Marine Corps tactical robots')
time.sleep(3)
else:
error = random.choice(errors)
talk(error)
time.sleep(3)
talk('TARS activated!')
#loop to continue executing multiple commands
while True:
time.sleep(4)
tars(myCommand())
Cool! We just created demo TARS and I hope you learned many things from this lab. Please feel free to contribute this project on GitHub, TARS will wait for improvements.
I hope this tutorial will surely help and you if you liked this tutorial, please consider sharing it with others.
#python #web-development