Hey pupils! Welcome to the new tutorial on deep learning, where we are in the section on Python learning. In the previous lecture, we were discussing the tuple data type, which is a sub-class of sequences. In the present lecture, the discussion will be about the byte sequence and byte array. The whole discussion is cleared with the help of practical implementation in TensorFlow by using simple and easy codes. If you understand the concepts of list and tuple, then this lecture will be easy for you. Yet, before going into the details of this topic, you must know the highlights of the content discussed in this lecture:
What is the byte method in Python?
How can you use byte in TensorFlow?
What are some examples of bytes?
Give examples of error handling in bytes.
How can you convert integers into bytes?
What is a byte array?
What is the difference between bytes and byte array methods?
Moving towards our next sequence is the byte method which has interesting applications in Python programming. A byte is the collection or group of byte numbers and it can hold multiple values. The interesting thing about the byte is, these can not hold the negative numbers that are, the values in a byte can not have the minus sign with them. One must keep in mind that these have a range between 0 and 255 only and you can not store more or fewer values than this range. For example, if you want to add 267 or -56 in a byte, this is not possible in it. The main purpose of using this function is to convert an object into an immutable byte-represented object of which, the data and size are specified by the programmer.
To make sure you are getting the whole concept, let us practice it on TensorFlow. To start, have a look at the instructions:
Search for the “Anaconda Navigator” in your windows search panel.
In the environment section, search for the Jupyter Lab.
Launch the lab and wait for the browser to show you the local host on your browser.
Go to the new cell and start coding.
You have seen we made a byte with the different types of elements in it. Now, what if we made the byte with values that exceed its values? Let us check it with the help of the following code:
The byte is a method and to use it well, the syntax must be known. For using it, there must be three parameters that have to be decided before starting, the detail of syntax and the parameters is given next:
byte(src,enc,err)
Here, the three parameters are defined:
src=The object that has to be converted. It is the source object and has superficial characteristics.
enc= it is the encoding that is used only when the case object used in the formula is in the form of a string.
err=If the error occurs during the conversion of the string is not done properly in the step mentioned before then, the logic given here will be used to overcome this error.
Now, using the information given above, we are going to discuss the example to elaborate on the whole process. The bytes when displayed on the output have a small be with them to show it is a byte. Just look at the code below and we are going to tell you the detail after that.
msg = "We are learning Python"
string = bytes(msg, 'utf-8')
print(string)
Here, in the first line, the message is declared and stored in the variable with the name ‘msg’.
The byte function is used in the second line and as the two parameters, we are using the message declared first as the source and the encoding technique is the utf-8.
The result of this function is then stored in the variable ‘string’.
The results are printed at the end. The small b at the start of this message indicates that it is a byte and single quotation marks are the indication that our result is a string.
Here, utf-8 is the indication of the Unicode transformation format, and it is encoding the string into an 8-bit character. So, in conclusion, we can say that a byte is used to convert the string message into an 8-bit character string. The application of the byte function is at a higher level of programming.
Now moving towards the next example, let us check for a relatively large code. This code gives us a demonstration of how we can use different cases of coding in a single piece of code and we will use here the empty byte, number-to-byte conversion, and list-to-byte conversion using single lines.
num = 4
list = [23,76,23,78,34]
#conversion with no argument
print ("Byte conversion with no arguments : ", (bytes()))
# conversion of number into string
print ("The integer conversion results in : ", (bytes(num)))
# conversion of list into string
print ("The iterable conversion results in : " , (bytes(list)))
The number is converted into bytes as expected, and when we try the same method for the list, where a group of numbers are to be converted into bytes, this function is capable of doing so. The output is strange for the non-programmers but the conversion is perfect here.
As we have mentioned earlier, the string is converted with the help of the byte function, but error correction is important in this case. There are some keywords that are suggested as error correction techniques. All of these will be discussed in the next section.
The second parameter of the byte tells us that we have to provide the encoding scheme, but what if the encoding process is not completed due to some error? The method parameter specifies the way to handle that error, and there is more than one way to handle it; therefore, here are the details of each way to handle the error for you. Keep in mind, coding is a vast field and the whole control is in the hand of programmers. Thus, not all errors are handled with the same kind of solution, so you must know all the ways.
The first error handler on the list is the "strict" keyword. It is used when the programmer wants to get the Unicode decoder error when the compiler is not able to convert the string into a byte.
The second error handler in the list is the keyword “ignore." What do you do when any procedure is not under your control and you are not able to do your duty? In the case of the compiler's workings, when it is faced with the same situation, it ignores the part with the error and moves towards the next line. In this way, the result obtained is not complete, but you get the answer to other parts of the code. It works great in many situations, and sometimes, you get interesting outputs.
The third one has a nice implementation of error handling. With the help of this handler, the error that occurred in the string will be replaced by a question mark, and then the compiler will move towards the next character. In short, the error will be gone, and instead of skipping the error, there will be a question mark that will indicate the error.
All the discussions above will be cleared up with the help of the code given in the next line. The error in all the problems is the same, but the outputs—or, in short, the way the compiler deals with the error—are changed.
#Declaring the variable with the string having the error in it.
MyString = 'PythonfÖrDeepLearning'
# using replace error Handling
print("Byte conversion with replace error : " +
str(bytes(MyString, 'ascii', errors='replace')))
# Giving ascii encoding and ignore error
print("Byte conversion with ignore error : " +
str(bytes(MyString, 'ascii', errors='ignore')))
#using strict error Handling
print("Byte conversion with strict error : " +
(bytes(MyString, 'ascii', errors='strict')))
Here, when we talk about the “strict” error handler, we get this error with the pink box because it is just like a simple error, as we are calling it, and we want strict action behind the error. Moreover, in the other two lines of code, the output is a little bit different, as the description tells us.
The conversion of bytes does not end here; instead, it has other conversion techniques as well. Python gives programmers the ease of converting integers into bytes, but it is, somehow, a little bit easier than string conversion because it is a pre-defined function and you just have to insert the values accordingly.
int.from_bytes(bytes, byteorder, *, signed=False)
In the syntax given above, three things are to be noticed;
It is the byte object that has to be converted into an integer.
This function determines the order in which the integer value is represented. The value of byte order can be "little," which stores the most significant bit at the end and the least significant bit at the beginning, or "big," which stores the MSB at the beginning and the LSB at the end. Big byte ordering computes an integer's value in base 256.
By default, the value of this parameter is false, and it indicates whether you want to get the 2’s complement of the value or not.
To understand the bytes well, you have to know first that Python is an object-oriented programming language; therefore, it works by creating objects from different pieces of code. While working with the byte function, an immutable byte object is formed. The size of this immutable sequence is just as large as an integer that ranges from 0 to 254, and it prints the ASCII characters. It is a Python built-in function that has many interesting applications in a simple manner. As with the other types of sequences, tuples also contain a number of items, but they can also be empty. The only conditions are that the data should be enclosed in parentheses and the elements should be separated with commas. Another important piece of information about this data type is that it cannot be changed once you have declared it.
As the name of this data type resembles the previous one, both structure and information are also similar. Byte arrays also have the parentheses representation, and you can use different data types in them, but the only difference between the byte array and the simple byte in the sequence is that the former is immutable, and you can change the size of the byte array after you declare it in Python. It makes the byte arrays more useful than the simple bytes in the sequence.
The reason why we are discussing both of these data types here is, there is only a slight difference between the byte and the byte array. You can modify the byteArray and that is not possible in the byte. So, have a look at the code below where we are modifying the array declared by
ourselves.
MyArray=[99,5,1,34,89]
print('The byteArray is: ', MyArray)
#Modifying the ByteArray
MyArray[2]=56
print('The modified array is: ',MyArray)
But for this, you must keep in mind that you can only use values between 0 and 255. All the other conditions are the same as the bytes.
Hence, today we have seen a piece of great information about a special type of method that converts different types of data into bytes in a specific manner. We have seen the details of methods that must be known to a Python programmer. The whole discussion was put into TensorFlow in the form of codes, and we get the outputs as expected. The next lecture is also related to this, so stay with us for more information.
Hello everyone, I hope you all are doing great. Today, we are going to share the second chapter of Section-III in our Raspberry Pi programming course. The previous guide covered how to interface an LDR Sensor with Raspberry Pi 4. This tutorial will cover the basics of hooking up a soil humidity sensor to a Raspberry Pi 4 to get accurate readings. Next, we'll write a Python script to collect the data from the sensors and display it on a Serial monitor.
Are you aware that you can utilize a Raspberry Pi 4 to track the water absorbed by the soil around your houseplants or garden? This helpful guide will show you how to install a soil humidity sensor that will send you a text message when your plant needs watering. A Pi 4, a soil humidity sensor, and a few low-priced components are required. All right, let's get going!
Today, we are going to interface Soil Moisture with Raspberry Pi 4. We will design a simple irrigation system, where we will measure the moisture of the soil and depending on its value, will turn ON or OFF the water pump. We will also use a 20x4 LCD to display values/instructions.
One way to assess soil conditions is with a soil moisture sensor. The electromagnetic signal that the sensor emits travels through the soil. The sensor then evaluates the moisture level based on the signal's reception.
We can use soil moisture sensor has numerous purposes. Saving water is one of them. Adjustments to the watering system can be made based on readings from the sensor that measures the soil's moisture level. This could cut down on both water consumption and waste. Plant health can be enhanced by employing a soil moisture monitor, another perk. We can use this sensor to set off a relay to begin watering the plant if the soil moisture level drops off a given threshold.
The two exposed wires on the fork-shaped probe function as a variable resistor whose resistance changes with the soil's moisture level.
The above figure demonstrates how to use a soil moisture sensor to detect moisture levels. When water is poured into the soil, the voltage of the sensor immediately reduces from 5V to 0V. The module has a potentiometer(blue) that adjusts how sensitively the digital pin changes state from low to high when water is introduced into the soil.
There are typically two components that make up a soil moisture sensor.
Two exposed conductors on a fork-shaped probe are put wherever moisture levels need to be determined. As was previously mentioned, its a variable resistor whose resistance changes as a function of soil moisture.
The sensor also has an electronic module that is interfaced with the microcontroller. The module produces a voltage proportional to the probe's resistance and makes it available through an Analog Output pin. The same signal is then sent to a Digital Output pin on an LM393 High Accuracy Comparator.
The module features a potentiometer (DO) for the fine-tuning of digital output sensitivity. It can be used to establish a threshold i.e. at which threshold the module will output a LOW signal and a HIGH otherwise.
In addition to the IC, the module has two LEDs. When the component is activated, the Power LED will light up, and the Condition LED will light up if the moisture level is above the setpoint.
Four pins are included on the FC-28 soil moisture sensor.
Among the various uses of Moisture Sensors, I am sharing a few here:
As with most things involving the Raspberry Pi, connecting a soil humidity sensor is child's play. we need to connect the soil moisture sensor with Pi 4 GPIO header. This connection requires three wires.
We can now start coding our project because all the pieces are in place. Now is the time to begin.
Here's our hardware setup having soil Moisture Sensor with RPi4:
Here's the Pin's Mapping:
VCC -> 5V
GND -> GND
DATA-> GPIO4
After the sensor has been hooked up, testing it requires the creation of some code. The following code can be copied and pasted into a text editor, then saved as a .py file.
import RPi.GPIO as GPIO
import time
#GPIO SETUP
channel = 4
GPIO.setmode(GPIO.BCM)
GPIO.setup(channel, GPIO.IN)
def callback(channel):
if GPIO.input(channel):
print ("Water Detected!")
else:
print ("Water Detected!")
GPIO.add_event_detect(channel, GPIO.BOTH, bouncetime=300)
GPIO.add_event_callback(channel, callback)
while True:
time.sleep(0)
The below output should be observed if the sensor is operating correctly:
So, there's been a moisture detection! You can change the code to perform any action you like. Once the humidity level is detected, you could activate a motorized or audible alarm, for instance. In the next tutorial, we will Interface a Sharp IR Sensor with RPi4. Stay tuned. Have a good day.
Hello friends, I hope you all are doing great. Today, I am going to share the 6th lecture in the Raspberry Pi 4 Programming series. We're glad you could join us for another lesson in our comprehensive Raspberry Pi programming guide. In today's guide, I'll show you how to interface a 16x2 LCD screen with Raspberry Pi 4.
So, let's get started:
Today, we are going to interface a 16x2 LCD screen with Raspberry Pi 4. At first, we will print the "Hello World" text on the LCD, and in the last section, we will implement the scrolling and blinking of text on the LCD.
We will need the following components for today's project:
The header pins of 16x2 monitors are not pre-soldered. Normally a male header pin is soldered to the LCD pin holes.
We can perform 2 types of communication modes in LCDs, named:
In 8-Bit mode, all 8 data pins are used to send data, while in 4-Bit mode, the last 4 pins(D4-D7) are used for data transmission.
LCDs employ two distinct registers:
You can use the RS pin on LCD to alter the register. If RS is High, we are accessing the data register and if it's Low, we are accessing the command register.
The LCD's command register keeps track of the user's command. Pre-display data is saved in the data register. In order to manipulate the display, one must first load the instruction register with commands and then load the data registers to display the data. If you're working on a Raspberry Pi project and want to avoid learning low-level commands, you can use the Liquid Crystal Library instead.
The screen's brightness can be adjusted from Pin 3, normally a potentiometer is placed at Pin 3 to adjust the brightness. You can also use a resistor if you don't have a potentiometer. If a resistor is used, try one between 5k-10k ohms. You should experiment with a few different values to get the optimal resistance.
LCD works on the principle of light transmission from one layer to the next via molecules. These units vibrate and align themselves in a way that the polarized sheet gets at an angle of 90 degrees, allowing light to pass through. In other words, these molecules inspect the information on every pixel. Every single pixel uses the light absorption technique to display the digits. It is necessary to adjust the molecular orientation to the incident light angle in order to show the value.
The 16x2 LCD screen can easily be connected to the Raspberry Pi 4. There will be a lot of cables to connect because LCD has 16 pins, but nothing too complicated. Here's the schematic of the pin connections between RPi4 and LCD:
Having done so, the screen should power up and establish a connection with the RPi.
The newest Raspbian release has all the necessary packages loaded out of the box to allow for GPIO communication. But we need to install the Liquid Crystal Library to work on the LCD. Let's do that:
git clone https://github.com/pimylifeup/Adafruit_Python_CharLCD.git
cd ./Adafruit_Python_CharLCD
sudo python setup.py install
After the installation, you can use the Adafruit library from any Python program on the Pi. Just paste this line into the beginning of your Python file to make use of the library.
import Adafruit_CharLCD as LCD
The Adafruit LCD library makes it simple to display data from Raspberry Pi to LCD screen. The library package also has several working examples of utilizing the LCD. Before running any of these examples, make sure the pin parameters at the top of the program reflect your setup. My Circuit should yield the following results.
lcd_rs = 25
lcd_en = 24
lcd_d4 = 23
lcd_d5 = 17
lcd_d6 = 18
lcd_d7 = 22
lcd_backlight = 4
lcd_columns = 16
lcd_rows = 2
cd ~/Adafruit_Python_CharLCD/examples/
sudo nano char_lcd.py
Change the values in this section to match the ones described above for the pin configuration. To save the code, hit CTRL+X+Y on your keyboard. To execute this code, open a terminal and type Python followed by the name of the file (including the extension).
python char_lcd.py
In this session, I'll go over the fundamental Python methods for interacting with the screen. To initialize the pins, it is necessary to invoke the following class. Before calling the class, make sure all the parameters have been defined.
lcd = LCD.Adafruit_CharLCD(lcd_rs, lcd_en, lcd_d4, lcd_d5, lcd_d6, lcd_d7, lcd_columns, lcd_rows, lcd_backlight)
After that, you can adjust the screen to your liking. In this short guide, I'll give you a taste of what you can do with the Adafruit library.
The Ardafruit CharLCD.py file in the Adafruit CharLCD folder of the Adafruit Python CharLCD folder will list all the accessible methods.
sudo nano ~/Adafruit_Python_CharLCD/Adafruit_CharLCD/Ardafruit_CharLCD.py
My simple script for displaying user-entered text is included below.
#!/usr/bin/python
# Example using a character LCD connected to a Raspberry Pi
import time
import Adafruit_CharLCD as LCD
# Raspberry Pi pin setup
lcd_rs = 25
lcd_en = 24
lcd_d4 = 23
lcd_d5 = 17
lcd_d6 = 18
lcd_d7 = 22
lcd_backlight = 2
# Define LCD column and row size for 16x2 LCD.
lcd_columns = 16
lcd_rows = 2
lcd = LCD.Adafruit_CharLCD(lcd_rs, lcd_en, lcd_d4, lcd_d5, lcd_d6, lcd_d7, lcd_columns, lcd_rows, lcd_backlight)
lcd.message('Hello\nworld!')
# Wait 5 seconds
time.sleep(5.0)
LCD.clear()
text = raw_input("Type your name in the terminal ")
LCD.message(text)
# Wait 5 seconds
time.sleep(5.0)
LCD.clear()
lcd.message('Goodbye\nWorld!')
time.sleep(5.0)
LCD.clear()
If everything's fine, you will get something printed on your screen, as shown in the below figure:
If your Python script isn't producing any output on the screen, it's probably due to incorrectly configured pins.
This guide walked you through connecting the Pi 4 to a 16x2 LCD. You can accomplish so much more with this sleek screen. You may set up a script to run at boot time and show useful information like the IP address, time, temperature, and more.
You can also incorporate a wide variety of interesting sensors with this screen. A temperature sensor like the DS18B20 would be ideally suited for use with the screen. Refresh the screen every few seconds to reflect the current temperature.
Please let me know how successful you were in putting up a Pi 4 with LCD 16x2 display with the help of this tutorial. In the next tutorial, we will interface Keypad 4x4 with Raspberry Pi 4. Till then, take care. Have fun !!!
We're glad you could join us for another lesson in our comprehensive Raspberry Pi programming guide. I will show you how to install and connect the RFID card chip to your Raspberry Pi through step-by-step instructions.
Modern security systems would only be complete using radio frequency (RFID) devices. To control who can enter a facility or which rooms they can access, RFID chips and card readers are employed. The RFID card's unique identification number can be read wirelessly with a wall-mounted RFID reader. A door will only unlock and allow entry if the RFID card's unique identification number matches a list of approved cards.
It's fun to tinker with this circuit, and it may be used in many other applications, from opening locks to taking attendance. The MFRC522 microcontroller underpins the RFID RC522, a cheap RFID (Radio-frequency identification) reader/writer. The RFID tags can connect with this microcontroller using an electromagnetic field it generates at 13.56MHz and sends to them via the SPI protocol. If you want to use your RFID RC522 with tags, you must ensure that they are 13.56MHz compatible. We'll walk you through the wiring of the RC522 and the creation of Python programs to communicate with the chip, allowing you to read and write RFID tags. Adding a 16x2 LCD to the Raspberry Pi is a simple extension of this tutorial, and it can be helpful if you need to show the user some information or provide a visual prompt.
| Where To Buy? | ||||
|---|---|---|---|---|
| No. | Components | Distributor | Link To Buy | |
| 1 | Breadboard | Amazon | Buy Now | |
| 2 | Jumper Wires | Amazon | Buy Now | |
| 3 | Raspberry Pi 4 | Amazon | Buy Now | |
Raspberry Pi
Micro SD Card
Power Supply
RC522 RFID Reader
Breadboard
Breadboard Wire
An RFID reader reads the tag's data when a Rfid card is attached to a specific object. An RFID tag communicates with a reader via radio waves.
In theory, RFID is comparable to bar codes because it uses radio frequency identification. While a reader's line of sight to the RFID tag is preferable, it is not required to be directly scanned by the reader. You can only read an RFID tag up to three feet away from the reader. The RFID tech quickly scans many objects, making it possible to identify a specific product rapidly and effortlessly, even if it is sandwiched between several other things.
Major components of Cards and tags include an integrated circuit (IC) that stores the unique identification value and a copper that acts as the antenna.
Inside the Rfid reader is another copper wire coil. This coil produces a magnetic field when current flows through it. Magnetic flux creates a current inside the wire coil when the card is brought close to the reader. This current can power the card's internal integrated circuit. The reader then takes in the card's serial number. A card reader will send the card's serial number to a central processing unit (CPU) like a Raspberry Pi for further processing.
When you buy an RFID RC522 Reader, you may discover that 90% of them do not have the header pins pre-installed. Due to a lack of pins, you'll have to solder them yourself; however, this is a relatively easy task, even for amateurs. Assuming the header pins that came with your RC522 are too large, you may snap them in half to reduce them to a single column of eight.
Start by inserting the header pins into the RC522 from the top. The circuit may be easily placed on top of the connector pins by inserting the large side of the pins onto a breadboard. The breadboard's secure holding of the pins will make soldering them to the RFID circuit much simpler.
Solder each pin individually by carefully heating your soldering iron and applying it to the pins. Remember that heating the junction slightly before to solder application increases the solder's adhesion and decreases the likelihood of generating a cold joint. When using solder, we advise you to be conservative. When you've finished soldering the header pins onto your RFID circuit, you'll be ready to move on with the guide.
There are eight different connectors on the RFID RC522. Except for the IRQ, we need to connect all these to the GPIO pins on our Raspberry Pi.
This guide shows how to connect an RFID RC522 to a Breadboard and then to the Raspberry Pi's GPIO Pins, although you could also wire the components straight to the Pi.
Simply connecting 7 of the Raspberry Pi's GPIO pins to the RFID RC522 reader is all needed to get it up and to run. Refer to the GPIO pin locations detailed in our tutorial and the table below when deciding how to wire your RC522.
SDA connects to Pin 24.
SCK connects to Pin 23.
MOSI connects to Pin 19.
MISO connects to Pin 21.
GND connects to Pin 6.
RST connects to Pin 22.
3.3v connects to Pin 1.
We need to adjust the Raspberry Pi's settings before we can use the RFID RC522. Inconveniently, our RFID reader circuit relies on the Raspberry Pi's SPI (Serial Peripheral Interface), which is disabled by default. Worry not, though, as it is easy to restore this interface; follow our instructions below to set up your RPi and Raspbian to use the SPI port. Launch the raspi-config utility by opening a terminal and typing the following command.
sudo raspi-config
A menu of choices will appear when you use this tool. You may read up on all of these options in the raspi-config documentation. Choose "5 Interfacing Options" using the arrow keys. Select this choice, and then hit the Enter key. Once "P4 SPI" is selected in the next screen, press Enter once more to confirm your selection. To continue, use the arrow keys to choose "Yes" and then press Enter when prompted to confirm that you want to activate the SPI Interface. For the raspi-config utility to finish enabling SPI, you'll have to be patient for a while.
The raspi-config tool's success in enabling the SPI interface will be shown by the display of the message "The SPI interface is enabled." Activating the SPI Interface requires a full reboot of the Raspberry Pi. Press Enter, and then ESC, to return to the terminal. If you want to restart the RPi, enter the following Unix instruction into the terminal.
sudo reboot
It is time to verify that Raspberry Pi has been activated now that it has rebooted. Checking if spi bcm2835 is available is as simple as running the following command.
lsmod | grep spi
If you get spi bcm2835, you're good to go with the rest of the tutorial. If you tried the preceding command and it didn't work, try the following three things. If the SPI component is not enabled, we can manually modify the boot config file by issuing the following code to our RPi.
sudo nano /boot/config.txt
You can use CTRL + W to search the configuration file for "dtparam=spi=on" If you think you have discovered it, look if it has a number in front of it. If there is, delete it because it disables the code. If you cannot find the line, add "dtparam=spi=on" to the very end of the file. To commit your modifications, use CTRL + X, followed by Y and Enter. You can double-check that the module has been activated by restarting your Raspberry Pi, as in Step 5.
After connecting our RFID circuit to the RPi, we can turn it on and start writing Python scripts to communicate with the chip. You'll learn how to read and write information to RFID chips by composing scripts like the ones we'll provide. These will serve as the foundation for future RFID RC522 tutorials and provide you with a fundamental understanding of how data is handled. The Raspberry Pi must be brought up to date with the most recent software versions before we can begin programming. Get the latest version of Raspbian for your Pi by running these two commands.
sudo apt update
sudo apt upgrade
Installing the python3-dev, python-pip, and git packages is the last thing to do before moving forward. To get your RFID reader set up with this guide, type the following command into your Raspberry Pi's terminal.
sudo apt install python3-dev python3-pip
Now that we have python "pip" installed on our Raspberry Pi, we can install the spidev Python library. An integral part of this guide, the spidev library allows the RPi to communicate with the RFID via the SPI. Run the following command to get spidev set up on your Raspberry Pi via pip. It's important to remember that we're using sudo to guarantee that the package gets installed for everyone's usage, not just the logged-in user.
sudo pip3 install spidev
After getting the spidev library up and running on our Raspberry Pi, we'll move on to setting up the MFRC522 library with pip. Two files, in particular, are used by us, both of which are part of the MFRC522 library:
This library, MFRC522.py, implements the RC522 interface for communicating with RFIDs via Raspberry Pi's SPI port.
Simplifying the MFRC522.py file so that you only need to work with a small subset of its many functions, SimpleMFRC522.py is a significant time saver.
Enter this command into your terminal to have pip setup the MFRC522 library on your Pi 4:
sudo pip3 install mfrc522
Now that the library has been transferred to the Pi, we can start writing code for the RFID RC522. First, we'll explore how to use the RC522 to program your RFID cards. Move on to the following part, where we will write our first Python code.
In this first Python script, we'll go over the steps needed to send information from the RC522 to RFID tags. This is made more accessible by the SimpleMFRC522 script, but we'll still break down the code's individual components for you. To begin, let's create a directory to hold the scripts we'll be using. Create the "pi-RFID" folder by using the following command.
mkdir ~/pi-rfid
To get started, navigate to the folder you just cloned and create the Write.py script in Python.
cd ~/pi-RFID
sudo nano Write.py
Add the following blocks of code to this file. This code prompts you for some text, which it then uses to update the RFID Tag.
#!/usr/bin/env python
import RPi.GPIO as GPIO
from mfrc522 import SimpleMFRC522
The very first line of the code snippet instructs the terminal to use Python rather than another scripting language like Bash to parse and run the file. To guarantee that the GPIO Pins are reset when the script terminates, we must first import the RPi.GPIO package contains all the necessary functions for communicating with the GPIO Pins. The second import is our SimpleMFRC522 library, which will be used to communicate with the RFID RC522. Compared to the standard MFRC522 library, it dramatically simplifies working with the chip.
reader = SimpleMFRC522()
In this line, we make a new instance of the SimpleMFRC522 object, use its setup function, and save the result in our readers variable.
try:
text = input('New data:')
print("Now place your tag to write")
reader.write(text)
print("Written")
We enclose the following section of code with a try statement to ensure that any unforeseen problems are handled, and the code is cleaned up correctly. Python is whitespace sensitive; it uses tabs to distinguish between code sections, so keep them after trying. In this case, the second line reads a command-line input and stores it in a text variable using Python 3's input function.
The third line makes advantage of print() to prompt the user to set the RFID tag onto the reader. After that, on line 4, we utilize our scanner object to instruct the RFID Circuit to write the text field's contents to a certain sector of the RFID tag. On line 5, after successfully writing to the RFID tag, we call print() once more to inform the user.
finally:
GPIO.cleanup()
The script will terminate in the last two lines of code. The finally statement always follows the try statement. Thus the GPIO.cleanup() method is called after each iteration of the try block. These lines are essential because improper cleanup can disrupt the functionality of other programs. Upon completion, your script should be like the example given below.
The file can be saved by pressing CTRL Plus X, Y, then ENTER once you've double-checked the code and are convinced it's correct. Now that the script is written, we need to put it through some testing. Get an RFID tag ready before running the script for testing. When you're ready, open the terminal on your Raspberry Pi and enter the following command.
sudo python3 Write.py
In this situation, we're just going to type in "any word" because it's easy to remember and short. Press the Enter key when you have finished writing and are ready to send. After that, your RFID Tag can be placed directly above your RFID circuit. It will immediately update the tag with fresh information when it does. You'd see the word "Written" on the command prompt if it worked. Now that you have your Write.py script completed, we can move on to explaining how to read information from the RFID RC522.
We have successfully programmed our RC522 to print to RFID tags and can now move on to writing a script to retrieve the data from the tags. First, we'll make sure we're in the correct location by switching directories, and then we'll use nano to start drafting the Read.py script.
cd ~/pi-rfid
sudo nano Read.py
Incorporate the following code into this document. When an RFID tag is placed in the RFID reader, the script will wait until the tag's data has been read before displaying the results.
This file's first line of code instructs the operating system on how to proceed when the user clicks the "Run" button. If you don't specify that it's a Python file, it'll try to run it like any other script. An initial RPi.GPIO import is made. Importing this library ensures that the Raspberry Pi's GPIO pins are cleaned up after script termination, as it contains all the necessary functions. SimpleMFRC522 is the second import. With the assistance functions included in this script, reading and writing to an RFID RC522 is a breeze, whereas, with them, the scripts would quickly grow to be manageable.
This line is crucial because it invokes SimpleMFRC522's creation method, which returns an object that is subsequently stored in our reader variable.
try:
id, text = reader.read()
print(id)
print(text)
The following code section will be encapsulated in a try block to allow us to handle any unforeseen errors gracefully. Because Python is sensitive to whitespace, you must use the 'tabs' as displayed following try:
In this scenario, the second line of this code block initiates a call on our scanner object, instructing the circuits to begin scanning any Rfid card that is positioned on top of the reader. On the third and forth lines, we use print() to display the data we gleaned from the RFID Chip; this includes the tag's unique identifier and any text it may consist of.
finally:
GPIO.cleanup()
The script ends with the last two lines of code. No of what happens inside the try block, the final statement is always executed afterward. No matter what, the GPIO.cleanup() code will be executed thanks to this try statement. It's vitally important, as not doing so can disrupt the proper operation of other scripts that rely on the GPIO. Your completed Read.py script for the RFID RC522 should resemble the example below.
When you've double-checked your code and are satisfied with it, press Ctrl + X, then Y, and finally ENTER to save the file. The time has come to put our completed Read.py script to the test. Get ready to test the script by picking up any of the RFID tags. If you're all set, enter this command into the terminal on your Raspberry Pi.
sudo python3 Read.py
Now that the script is active, you can set your RFID Tag atop your RFID circuit. When the RFID tag is placed on top, the Python program will immediately begin reading the information from the tag and display the results on the screen. What a finished product might look like is shown below as an illustration.
To test whether your Raspberry Pi is properly connected on the RFID RC522 Circuit, run the Read.py script and see if it returns any data that matches the text you wrote to the card in the Write.py script.
Connecting an RC522 RFID module to a Pi 4 makes reading MIFARE chips and cards is now possible. This might be very useful in security systems and other applications where identifying an item or person is required without the user having to physically interact with the device by pressing buttons, switching, or activating any sensors. Eventually, you should be able to use this to decipher the UID encoded on your MIFARE tags. You should know that these cards can be duplicated and assigned a new unique identifier (UID) if you plan on employing this technique in a security system. To ensure the safety of your system, you must ensure that no one learns your UID or gains remote access to your devices. The contactless tags are convenient because they can be attached to a keychain, and the cards are convenient because they can be carried in a wallet. Both things can be concealed inside others to give them a hidden identifier that the Pi can access. With the help of our Pi 4-powered RFID attendance systems guide, you can learn how to set up your RFID Reader/Writer for use in checking attendance. Our exploration of the RFID chip and the scripts above will continue in subsequent guides. A door security system is one of the fantastic DIY Pi ideas we'll look into. The next lesson will teach you how to connect a 16x2 LCD screen to a Raspberry Pi 4.
No matter your company's industry, you need fleet maintenance software. It’s something you need if your engineering firm has a fleet of vehicles. Failing to get the necessary tools is a bit like driving blind -- not the best course of action by any stretch of the imagination.
If you’re not sold on the benefits of investing in fleet maintenance software, keep reading to learn more about four reasons you need it.
Fleet maintenance software will help your engineering firm with preventative maintenance. The software will make it easy to schedule maintenance so that your fleet of cars stays in good shape.
One of the worst things you can do is delay or ignore preventative maintenance. That will ultimately cost you in terms of downtime stemming from repairs. Preventative maintenance won’t eliminate the possibility of repairs, but it will reduce the odds of breakdowns . And breakdowns can become expensive if you also find yourself unable to use the company vehicles for business. Unplanned downtime is a no-no.
When your business invests in fleet maintenance software, you’ll also enjoy lower vehicle repair costs. Putting off maintenance means that small problems can morph into major issues that cost an arm and a leg to fix. So, it’s more cost-effective to invest in preventive maintenance than to postpone doing so and having to spend many times more to fund major repairs.
When considering the importance of your fleet, you can appreciate the need to ensure the vehicles are available and in good repair whenever they’re needed. You can increase uptime and reduce downtime by tackling issues as soon as they’re discovered so that they don’t worsen.
When you get one of the best fleet maintenance software applications, you’ll also benefit from better fuel efficiency. Proper maintenance and repairs will ensure your fleet of vehicles operates more efficiently, resulting in better fuel efficiency. You can also optimize routes so that drivers don’t take longer routes than necessary. And by keeping track of driver behavior, like speeding or hard braking, you can notify drivers of necessary changes. You can save a lot on fuel just by getting drivers to operate the fleet vehicles more responsibly.
Who has time to worry about their fleet of vehicles? You have other things to worry about such as operating your engineering firm. When you’re taking good care of your cars, you won’t be left worrying about them. Instead of having to make frequent arrangements to have your inoperational cars towed to automotive facilities for repairs, you’ll be able to use them for business purposes. They’ll spend more time on the road and less time out of commission.
That means you’ll have fewer headaches with your fleet of vehicles. Using a fleet maintenance software solution, you’ll be able to stay on top of things. And if things don’t get out of control, you’re less likely to have headaches over something going horribly wrong.
If your engineering firm has a fleet of vehicles, it’s essential to consider the benefits of fleet maintenance software. Protecting your assets is a must if you want them to remain in good repair over the long haul. Getting a fleet of vehicles requires a tangible investment. If you want to protect your investment, then investing in fleet maintenance software is a good idea.
Before settling on a platform, you’ll want to do research to find something that meets your company’s needs. When you find the right software, you’ll see up close and personal what the benefits of fleet maintenance software are all about.
Hey peeps! Welcome to another tutorial on data types in Python. Our purpose in Python education is to get a grip on the basic concepts so that we may work on deep learning easily. In the previous lecture, we read a lot about lists as we are working on the subtypes of the sequence data type. In the present lecture, you are going to understand more types of sequences. If you know the list well, this lecture will be a piece of cake for you. We will start the introductions in just a bit, but before that, there must be a quick review of the topics that you are going to understand:
How do you introduce the tuples in Python?
What are some important characteristics of a tuple that must be kept in mind when we are dealing with it?
How can you practically perform the tuples in TensorFlow?
How do you associate tuples with the list?
Can you delete, update, add, or delete the elements in a tuple? If yes, then how?
Which is the way to delete the tuple entirely?
All of these are important interview questions about the tuple and if you are dealing with these data types, you must know and perform these by yourself in TensorFlow. All the information about tuples will be discussed with you and you have to practice more and more in the code to understand the concepts.
For the concept of a list, we have given you the reference of an array. This time, we will be mentioning the name of the list for better understanding. If we talk about the topic of today, a tuple is also a group of items that are arranged when required in Python. The working and the definition of the tuple seem like a list because both of them are types of a single data type, which is the sequence. But there are some differences that make them ideal for different kinds of situations. The following points will make this more clear:
The tuple is represented by enclosing the data in parentheses.
A tuple is immutable, which means that once you declare the items in the tuple, you can not change them as you can in a list.
When you try to change the value of the element in the tuple, an error is shown on the screen, so while declaring the new tuple, you have to be very clear about what is on your mind and what you want to do with the tuple.
In a tuple, you can also use the function in the tuple and it becomes easy to perform different tasks through codes.
A single element in the tuple is necessary to build the tuple. In other words, unlike the strings, the tuple must contain at least one element in it.
In the tuple, any data type can be saved whether it is boolean, int, or string. Moreover, there is a possibility to add different types of data in a single tuple. So we can conclude that we can have a homogeneous or heterogeneous tuple according to our choice.
As we have mentioned, when using the tuple, we get the ordered list of objects, which means we get the specific order, and this order, once mentioned, can not be changed, unlike other data types of the sequence.
Not just the order, but the size, sequence, and entries are unchangeable, so during the initialization and declaration of the tuple, the concept must be clear about what you want from the particular tuple.
Another thing that must be kept in mind is, the tuple has the index form, and therefore, every element has a specific number of indexes. This is the reason, the elements are easily accessible, and hence, you can also have duplication in the tuple. The elements are recognized by the index number, and therefore, the compiler knows when which element is being called.
The length is the number of elements in the tuple, and we have read about the length function in the previous lecture. Similar to the list, a tuple can also be used in the length function, and the programmer gets the length of the tuple. Right now, this function is not looking very attractive because we are dealing with small tuples. But take the case in your mind when the tuple contains hundreds or thousands of elements and get the length of the tuple in just a few moments.
It is now time to go over some basic tuple-related code using TensorFlow. The steps for starting it are the same as those we always follow; have a look at these steps:
Open your Anaconda Navigator by browsing it from your window panel.
Search for the Jupyter lab in the environment section.
Wait for the PC to open the new tab in your browser.
Go to the new cell.
Start coding.
With the help of code, we will try to create a tuple, and then, by using the function on it we will try to retrieve the data from the tuple in different ways. So, have a look at the code given next and then guess the output in your mind.
print('Make a tuple with stationaries item')
myTuple=('pen', 'paper', 'eraser', 'pencil', 'sharpener', 'notebooks')
print('The tuple has following items: ',myTuple)
print()
print('print only the third item of the tuple:', myTuple[3])
print()
print('print the item by using the index: ',myTuple[1])
Now, have a look at the output. Is it exactly the same as you were expecting?
You can see how simple it is to get the item from the tuple when it is declared in the tuple. This is the same as what we did with the list. But what if we want more than one element from the tuple at the same time?
print('Make a tuple with fruits and prices in dollars')
myTuple=('strawberry','kiwi','banana','orange','apple', 2.5,3,12, 4,6)
print('The following items in the fruit shop are available: ',myTuple)
print()
print('print only the forth fruit of the fruit shop:', myTuple[-7])
print()
print('print the name of only fruits: ',myTuple[0:5])
Looking at the code, you will observe that the negative number is used in the index. This is the way to tell the compiler that we are counting from the end of the index. Moreover, the index on the end side starts at 1 instead of zero. Another point to notice is that the start and end limits are specified by separating them with the colon, and as a result, we get the whole tuple in the output.
A new concept that is to be shared is that when you are providing the limits to the tuple, you have to take care that the right numbers are being used because it will then not work properly. You must be thinking that the compiler will throw the error when you feed the wrong limits in the tuple, but instead, the output will be empty, and you will get the parentheses with nothing in them.
Another thing that must be mentioned here is that you can check whether the tuple has a specific element or not. For this, we get the help of a statement. We know that, until now, we have not learned about the statements, and therefore, we suggest just looking at the code and output to understand the concept.
print('Make a tuple with fruits and prices in dollars')
myTuple=('strawberry','kiwi','banana','orange','apple', 2.5,3,12, 4,6)
print('The following items in the fruit shop are available: ',myTuple)
if "apple" in myTuple:
print("Yes, 'apple' is in the present in the fruit shop")
This program searches for the elements specified in the “if condition” and then prints the result on the screen.
If you are reading this lecture from the beginning, you must be thinking we have mentioned again and again that a tuple is immutable and unchangeable. Yet, programmers have the logic and solutions to every problem, and if the programmers have specified the tuple and want some changes made to it, they can do so with the help of the list. It is one of the reasons why we have discussed the list before in this series. Have a look at the following code and output, and then we will discuss it in detail.
print('Make a tuple with fruits and prices in dollars')
myTuple=('strawberry','kiwi','banana','orange','apple', 2.5,3,12, 4,6)
print('The following items in the fruit shop are available: ',myTuple)
myList=list(myTuple)
print(myList)
myList[2]='pear'
print(myList)
myTuple=tuple(myList)
print(myTuple)
Copy this code and run it on your TensorFlow, you will get the following output:
First, look at the brackets carefully and check the output in a sequence with the points given next:
At the start, the string message is shown, which shows the main title of the tuple.
The name of the tuple here is “myTuple” and it contains the fruits’ names and prices.
To make the changes in the tuple, we have to use another approach, and we know the reason why. For this, we are using the list. It is possible to convert the list into a tuple and vice versa, and we are doing the same in this. We are just using the name of the data type as a function and inputting the name of the data type to be changed. So, we changed the tuple into a list and then made the changes according to our choice.
By using the index number and feeding the value into the list, the list is updated. This can be observed with the help of square brackets.
Once we have seen the updated list, we can now easily convert it into a tuple again.
The conversion is done with the same procedure, and we get the updated tuple.
This was a simple example, other operations such as the addition of the new element, deleting the elements from the tuple, removing the single elements from the tuple, etc. are done with the help of lists.
Now that you know all the ways to initiate, use, and update the tuple in detail, a last method for the tuple is ready for you. In some cases, when you do not want to use a particular tuple for any reason, such as if you are no longer using it, you can do so in just a simple step. This is used in the programs when long calculations and collections of data types are needed for a particular time and then there is no need for them anymore. So for this, we use the delete operation. The programmers have to simply use the del keyword before the name of the tuple to be, and the compiler has to do its job well. Have a look at the example given next:
Tuple = ("Artificial Intelligence", "Machine Learning", "Deep Learning")
print(Tuple)
del(Tuple)
print(Tuple)
So, when the compiler was on the second line, it showed us the results, but on the next line, when we deleted the declared tuple, the compiler was not able to show us the result because it had been removed from its memory.
So, it was an informative data types lecture in which we clarified many concepts about tuples. These are the data types that belong to the class of sequences. We read a lot about it and started the discussion with the introduction. The tuple characteristics were thoroughly discussed, and then, with these in mind, we tested the functions of the tuple using TensorFlow examples. We attempted similar examples and carefully observed the operation of tuples, which also involved the list. In the next lecture, you will know more about the data types in Python, so stay connected with us.
Hello my friends! I hope your doing very good. Today we are going to practice what we have learnt through the ladder logic tutorial series. We bring a new .project which is mostly exist in our daily life that is electrical door control. in garage for domestic and public garage, you should found automatic garage gate or door that is controlled by the PLC ladder logic program. So today we are going to implement the project including determining the input and output components, design the logic, programming and testing using the simulator.
Figure 1 shows the project’s components, inputs and outputs that are included in controlling the garage door. As you can see my friends, there are inputs like open, close, and stop requested by push buttons. Also, you can see sensors like the two limit switches on the bottom and on the top to prevent overload that might have occurred on the motors. Moving to the outputs, there are motor up and down directions, open, close, and ajar status indicators lamps. So what is the next step in our plan to achieve such job? Of course we need to list these inputs and outputs and give them addresses. Then we design the logic based on the user requirements and the safe operation.
Table 1 lists the inputs and outputs showing the name in the first column, the description In the second column, while the addresses are listed in the last column.
Component |
Description |
Address00 |
Open push button |
One of the inputs to request open operation |
I: 1 / 00 |
Close push button |
One of the inputs that enables user to shut down the door |
I: 1 / 01 |
Stop push button |
The push button to stop operation at any time |
I: 1 / 02 |
Limit switch 1 |
A sensor to stop opening operation beyond the opening limits |
I : 1 / 03 |
Limit switch 2 |
A sensor to stop closing operation beyond the closing limits |
I : 1 / 04 |
Shut down indicator |
One of the outputs that tells the shutdown operation is in progress using an Indicator lamp |
O: 2 / 04 |
Open door indicator |
One of the outputs that tells the opening door operation is in progress using an Indicator lamp |
O: 2 / 03 |
Ajar door status |
One of the outputs that tells the door is ajar using an Indicator lamp |
O: 2 / 02 |
Motor Up |
A relay that directs the door in opening direction |
O: 2 / 00 |
Motor Down |
A relay that directs the door in closing direction |
O: 2 / 01 |
After receiving the requirements of the client that tell how the door will be operated, managed, and controlled, we need to add the restrictions and safety conditions that secure the equipment like the motor, supply, sensing components. So the following lines state the operation and restrictions that need to be followed to achieve the designated task as follows:
The door opening and or closing shall be stopped at any time user / operator hit stop push button
The door shall open by requesting opening operation using the designated push button
The door shall close by requesting shut down operation using the designated push button
The indicator lamp of opening operation shall be lit while opening operation is in progress
The indicator lamp of closing operation shall be lit while shut down operation is in progress
The ajar status lamp shall be lit at any time the door is not fully opened or totally closed
The opening operation can not be requested while shut down process is in progress
The shut down operation can not be requested while opening operation is in progress
The opening operation can not proceed any further beyond the designated limit to avoid any overload on the motor
The shut down operation can not proceed any further beyond the designated limit to avoid any overload on the motor.
The ladder logic program of the project is shown by figure 2. It shows two rungs, one for opening process and second for the shut down operation. The program can be more lengthy but we professionally resumed it in only two main rungs. The first rung represents the door opening operation in which, open push button initiates the opening process and the latching is there to let the opening process continue till the limit switch LS1 contacted or the stop is requested by hitting the stop push button. In addition, security of the process has been considered by including the condition of not having a shutdown process in progress represented by O:2/1. On the other hand, the shut down process is represented by the second rung. The shut down process initiated by the shut down push button and latching the door closing relay for continuing the shut down process unless one of the restriction conditions is met. The restriction conditions of shut down are the limit switch LS2, the door opening in progress, or a stop has been requested by operator using the stop push button. Also, indicator of the process status are included to show the opening operation thanks to the door opening indicator and the shutdown indicator. But we missed the ajar status of the door so let us add one rung for that.
As you see guys, the third rung has been added to implement the ajar status. It is simply clear that when the opening is in progress without reaching to the fully open indicator, or the shut down process is in progress without reaching to the totally closed, the ajar lamp is energized. Now let us go testing what we have coded so far and see if it is correct or not. But first you guys should sit and list the test cases that you should try to make sure the system is going to perform correctly and safely as well.
In this test , we hit the opening door push button to request opening the door. As you see my friends, the door is opening as in figure 3 and the opening indicator is lit. also you can see the ajar indicator is lighted because the door is not reached the final opening position.
Figure 5 shows the state of the process after reaching the final position for opening the door. It is clear the process safely completed and the limit switch LS1 is gone green. Also the ajar status and opening indicators have been turned off.
In this test , we hit the door shut down push button to request closing the door. As you see my friends, the door is closing as in figure 6 and the closing indicator is lit. also you can see the ajar indicator is lighted because the door has not reached the final shut down position.
Figure 7 shows the state of the process after reaching to the final position for closing the door. It is clear the process safely completed and the limit switch LS2 is gone red. Also the ajar status and shut down indicators have been turned off.
In this test case we want to request opening .the door while it is shuting down and try to request shut down the door while it is opening to see is there any issue or not. Figure 8 shows what is going on when we requested opening the door while a shuting down process is inprogress. You can see guys in rung number one, the opening push button ,is pressed as circled and highlighted see I:1/0. However, the requested process has not performed due to the restriction that the shutdown process should not be in progress. Same thing when opening door is in progress, shut down requests are forbidden.
Hey, peep! This is a connected tutorial from the previous one where we saw the detail of numeric data types. This time, we are moving forward with the other data types in Python. We are understanding all these concepts with the help of examples and practising the little but understandable codes in TensorFlow. Different types of operations are also performed on these data types so that you may have an idea of why we are differentiating all these data types and how we can categorize all of them into different groups. Keep in mind that all of these concepts are for deep learning, and we want to make sure that we will not face any problems in the complex work of deep learning; therefore, we are moving slowly and steadily in Python. So, have a look at the content you are learning in this tutorial, and after that, we’ll start the introduction.
What are the strings in Python?
How do you declare the string in different ways while working in Python?
What are escape sequences in Python?
How can you use the triple quotation in Python and why it is useful?
Each concept will be discussed with the help of simple and easy codes and the description of each of them is discussed in detail in this lecture. This is a connected part of the lecture that was discussed in the last lecture and other data types will be mentioned in the next lecture.
A string is nothing but the combination of different alphabets in a specific sequence. In programming, the concepts are a little bit different from those in the real world. The way we speak in English is said to be "string" in the programming language, and it is an important data type in any programming language for non-programmers, anything that comes on the screen must be easy to understand, and string is the best way to print the message on the screen. Let us define the string in simple words.
"The string is the sequence of characters or alphabets that specify the message on the screen and it is denoted by 'str' in Python."
We always say that python is simpler and easier than other programming languages, and it is true for the concept of string as well. In Python, the string can be denoted by using single or double quotation marks and the usage of commas is according to the choice of the programmer. In other words, you can use the single or double inverted commas around the alphabet to represent the string. Moreover, you must know that string has no limited length same as in the case of integers. The only thing that limits the length of the string is the memory space of the system you are using. Have a look at the syntax of the string while you are working on Python.
First of all, you have to look at the syntax of the string. The syntax of all the data types is the same; therefore, we are mentioning just this one, and after that, you will have an idea of how to implement the other data types. We have mentioned in the previous lectures that you just need the name of the variable and then the value of the variable in the form of any data type you want, so the syntax is given as
string = "I am learning Python for Deep learning."
The name may be anything, but it is important to use inverted commas (either single or double). TensorFlow will make this clearer, but there is a short procedure to get TensorFlow up and running.
Search for the “Anaconda Navigator” on your PC.
In the environment section, click on the Jupyter lab and launch TensorFlow.
The new tab will open in your browser with the name “Local host.”
Go to the new cell and start coding there.
Now, you have to write the following code in the new cell and run the program to get the output.
string="I am learning at TheEngineeringProjects"
print(string)
a=" "
print(a)
b='Python is best for Deep learning'
print(b)
The output of this code is given as:
From the code and output, we can conclude with the following point:
The name of the variable may be anything.
We can use single or double inverted commas for the string and the result will be the same.
A string may be an empty space so we can say that length of the string is zero to positive infinity.
The output of each print function is always shown in the next line in normal conditions.
So, the best way to show any message to non-programmers is in the form of a string.
In most high-level programming languages, there are certain words that are chosen to be used for a special task in Python with the help of their special sequence. These are known as the escape sequence. These are defined as:
"The escape sequence in Python is the combination of characters that, when used inside a string or character, does not show itself but does the specific task according to its functionality."
It is important to notice that these are important concepts in Python because it is very difficult and in some cases, impossible to do the same task without using the escape sequence. Now, have a look at some of these in the next section and you will get the detail of some important escape sequences.
As you can see, in the previous code, we made a space between two lines with the help of an empty string. But, what if we want to print a new line in the message? For this, we use a special operator in the string message and it is used in places when the output is long or there is the need for more than one line to represent the message more clearly. The operator is a backslash with an “n” that can be used at any place in the text. Have a look at one example to do so.
print('The backslash with "n" is used to \nprint a new line')
The output of this single-line program is interesting.
It is important to notice that if you want to work with this operator, you have to use it properly. You can not use any additional space between the text and this new line operator; otherwise, you will get an error message from the compiler.
We all use the tab on the keyboard but what if you want a space between the text? You can do so by applying the space between the text while you are printing the message but it is not the professional way. To do this with convenience, just like some other programming languages, Python has a special operator. Same as we use the n in the new line operator, if you use the t with the backslash, you can print the space between the text that is equal to eight space bars.
print('The backslash with "t" is used to \tprint a tab space in the line')
Let’s see what we have in the output of this code.
Same as these operators, we also have some other commands that do the work similar to this and the syntax of all of these is the same. For the convenience of the reader, we have made a table that contains all the information about these operators. Have a look at the table and after that, we will run all of these at once in our code in TensorFlow.
Name |
Representation |
Description |
New line |
\n |
It creates a new line in the text even if you are using it in the middle of the line. |
Tab space |
\t |
It is used for the space tab between the text. |
Bullet |
\a |
For the bullets in the text, we use this operator. |
Delete space |
\b |
To delete the space in the text, we use this operator. In this way, the text obtained only removes the space from the place where this operator is being used and the other text remains the same. |
Ignore the line |
\r |
By using the working of this operator, the text before the operator is deleted, and you will get the text after this operator only in the output. |
Arrow |
\v |
If you want to show a small arrow in the text, you will use this operator. |
To test each of the commands discussed before, we are rushing towards the TensorFlow, where we are using all of these in a similar ways to show the difference between all of these. Keep in mind, the syntax of each of them is the same. These are not the proper functions but are the pre-defined commands that are used less commonly in Python. Here is the homework task for you. You have to look at the code we are giving below and without cheating will guess the output.
print('We use \ncups for tea')
print('The tab create \teight spaces in the text')
print('\aBullets can be made using this operator in Python')
print('If you want to delete the \bspace, you can use the operator in Python')
print('This part will be ignore \ronly this will be printed on the screen')
print('\vThis small arrow looks cute')
Once you have guessed the output, now check this in your compiler, and then match the output with the one that is given next in the image.
The last arrow can also be used as the bullet in the text you want to show on the screen. Another task for you is use the different text and practice the code and string with your own message. It is the simplest and interesting task that you must try on your TensorFlow.
Here is another way to indicate that you want to declare the string. This is a less common way to represent the string, but if you are studying the string, you must know this. You can use double and single inverted commas around the text at the same time, and this will not cause any errors. Let me tell you about the workings of this kind of string. After that, I’ll show you how you can use it for different purposes.
print('''Deep learning is the subclass of the artificial intelligance''')
So, we are using three quotation marks around our text and getting the same output as for the single and double inverted commas. Here is the output:
The advantage of using this method is, you do not need any new line operators to start the text on a new line, but you will write the code as you want the output.
This is a more interesting and convenient way to write your text. Right now, you must be wondering why we are highlighting such uses and creating this hype. Yet, you must know, the aforementioned ways of writing the codes will help you a lot when you will go to the complex and long codes for the deep learning. One of the application of this way to declare the string is in this lecture. We can use this way to declare the string and can perform all the escape sequence command by declaring a single string in different lines so that we may not have to write “print command” every time when we are working with a new escape sequence.
Hence, we have read a lot about strings today. It was an interesting lecture where we saw what strings are and how we can use them in our coding in different ways. We say the representation, working, and the escape sequence between the string. The syntax of each case was clarified with the help of examples in TensorFlow. You will get information about more data types in the next lecture.
Hey fellow! Welcome to the next episode of the Python series, where we are learning the basics of Python to implement them in deep learning. In the previous lecture, our focus was on string data types. With the practical implementation of TensorFlow, many interesting points were discussed in depth. I hope you completed the home task that I assigned you during that lecture. Today, we are moving forward with the next data type, which is a sequence. You will know the different sub-groups of this data type as well in the next lecture, but today, the focus will be totally on the list because, once you understand them well, other data types of the sequence will be at your fingertips. Yet before starting, it's time to look at the content that you will learn today:
What is a sequence?
How do you classify the sequence into different types?
How do you understand the list?
What are some characteristics of this list that make it useful and different from the others?
The workings and characteristics of the list are interesting, and these will be well understood when we start our TensorFlow for different examples taken from our daily lives. We hope you have a strong grip on the integers, strings, and floats because, in our example, we will use them and will try to make changes in the list to show the difference in detail. So, without using your time, I am going to start the learning phase in Python.
In programming languages, we use a lot of items, objects, classes, and related concepts, and when we talk about the sequence, that is a data type that provides us with the concept of a collection of things. These are useful concepts that allow us to work with them in a useful way. We define the sequence in the following way:
"The sequence in Python is a generic term that defines the ordered set of items in such a way that any of the items can be easily referred to."
Here, the word “ordered set” is important to notice. We’ll talk about it in detail in just a bit, but before that, let me tell you that the string is also considered to be the sequence because it contains the sequence of the characters. We have read a lot about the string, and therefore, we know that the ordered sequence of the characters, or alphabets, is called the string. Yet, I had a lot of data to tell you about these concepts; therefore, I have discussed them separately. There are two natures of the sequence that are listed below:
Homogeneous sequence
Heterogeneous sequence
The difference between these two is that a homogeneous sequence contains a group of items of the same kind.
Homogeneous Sequence |
Heterogeneous Sequence |
A homogeneous sequence contains a group of items of the same kind. |
A heterogeneous sequence contains a group of items of different kinds. |
{"Apple", "Banana", "Cherry"} |
[Cup, knife, banana] |
It is important to know this difference because, on the basis of it, you will get the further types of the sequence.
The collection of the data can be represented in different ways, and on the basis of these types, we can divide the sequence into six major types. All of these are important to understand because we use the sequence often while programming and when dealing with complex subjects such as deep learning (in which we are interested), and the sequence plays a vital role in organizing the data in an understandable way. So, have a look at the types of sequences:
String
List
Tuple
Byte sequence
Byte array
Range objects
Out of them, the strings have been discussed in detail in the previous lecture. So, we are skipping that for now. You will be familiar with the remaining ones in depth, and things will become clearer to you with the help of examples. Thus, have a look at them:
In some other programming languages, such as C++ and C#, there is the concept of arrays that we study a lot. Yet, in the Python programming language, this concept is not used; instead, lists are used. The list is indicated by the square brackets just like the arrays, but it is a little bit different from them. The list is the type of sequence that contains an ordered group of different items. More information about the list can be found in the table below:
Name |
Attribute |
Representation |
Square brackets |
Nature |
Heterogenous sequence |
Example |
[‘cups’, ‘eggs’, ‘yolk’, ‘tea’] |
Here, it is important to notice the representation of the list with the square bracket because the bracket is the only way to differentiate it from the other types of sequence that you will learn in the coming lectures. The operation of the list will be explained in simple steps in a moment, but first, let us open the Python workspace for practical implementation. For this, you simply have to follow the steps again that we always mention:
Search for the Anaconda Navigator on your personal computer.
Go to the environment section and look for the “Jupyter lab” or “Jupyter notebook." For this tutorial, we are using the Jupyter lab.
Go to the new cell and get ready for the coding.
The list's information does not end with the table mentioned above. Certain characteristics make the lists useful, and you will learn about them in the following section.
One of the most significant features of Python is its mutable nature. To know the meaning of the line we have just said, you must know that when we declare a list, we define the size of that particular list by mentioning the number or directly feeding the elements in it. The list's advantage is that the programmer can change the elements at any time to meet the needs of the situation. In addition to this, if you want to change the individual value of the list, you can do so easily. Not only this, but you can also change the order of the elements while working on the code. It means if you want to swipe or change the position of elements 1 and 3, you can do so easily. In short, you can say that, while working with the list, all the controls are in your hands.
MyIntList=[1,56,8,12,56,90,3,67]
print('The homogenous integer list is : ', MyIntList)
MyFloatList=[1.2,56.2,8.2,12.2,56.2,90.2,3.2,67.2]
print('The homogenous float list is : ', MyFloatList)
You can see that all the elements belong to the same data type, so we are calling it the homogeneous list. In the second code, we want to do something different, so have a look at the code.
list=['eggs', 2.0, 34, 'plates']
print('The elements of the list are : ', list)
print('The element at position 2 is : ', list[2])
print('The elements before the second position are : ', list[:3])
list=[ 34,2.0, 'eggs', 'plates']
print('Now the new list is: ', list)
By looking at the code given above, we can conclude the following points:
To declare more than one type in a single list, the programmer simply has to use the accurate way to declare them in the list, and nothing special has to be done during the declaration of the list.
To get a specific element from the list, simply the position of the element is mentioned.
The position in the elements start from the 0 just like the arrays and you have to declare the element accordingly.
The order of the elements can be changed easily and to do this, the programmer have to merely change the elements according to the will with the same number. Here we have used two types of lists with the same name but by changing the order of the elements and the code is working well.
To get the elements of the list to a certain limit, there is a need of mentioning that number of position along with a colon. Keep in mind, here we specify the position 2 and all the elements before the third position are shown to us. Same can be done to get the elements after the mentioned number and it is your homework to know how can you do so.
When you compare the list to the array, you can better understand Python's dynamic nature. Let me remind you that arrays have a fixed size and cannot be changed once declared in your code. But in the case of the list, once you start working on it and need to change its size, you can increase or decrease its size by merely mentioning it in just one line. In other words, your list can grow or shrink according to your choice. To understand this you must know about a built-in function in Python.
The length is a built-in function in Python that provides the length of the functions made in the code. You simply have to input the name of the function in it and it will show you the number of elements specified in that particular function. The syntax of the length function is:
len(name)
By using this function in the list mentioned above, the number of elements can be obtained with the help of this code:
list=['eggs', 2.0, 34, 'plates']
print('The length of list is : ',len(list))
list=[34,2.0, 'eggs']
print('The new length of list is : ',len(list))
The output of the code is given next:
Keep this in mind the next time you go grocery shopping and want to buy something else; make a list for it. It will contain vegetables, meat, cloth, spices, and other things of the natural world. Because of its heterogeneous nature, the list is the same. It feels like a relief that you can make a list that contains strings, integers, and any other data types in one place. In this way, you can deal with multiple types of data at once. In arrays, this is not possible. You can also add functions to the list that contain elements of different types. You have understood it well with the previous examples in TensorFlow, but I want to show you this by mentioning a built-in function in it.
Mylist=[23,'decoration', False ]
print(Mylist)
Yet, there is a bit of difference between the keywords and loops; therefore, you can not mention the loops in the list; otherwise, you will face the same error as given next:
Here, the error is demanding that you write the code in the valid syntax. It is because the compiler is not able to understand that the for loop is an element of the list, but it demands the proper syntax for the for loop and is expecting an iterative procedure. Another thing to notice here is the color of the word “False” in the list. All the keywords, while coding, are shown in green, showing that it is a built-in function or keyword and that the compiler has understood the default functionality of that particular keyword.
Hence, it was an interesting tutorial, through which we learned a lot about the list data type. We initially understood what list data types were and why we were learning them. After that, a detailed overview of the list was discussed, through which we found the characteristics of the list. It was easy to understand as we practically performed each step of the TensorFlow with the help of different examples that were related to the general examples, so we were able to understand it well. If you have a clear understanding of the list, the following lectures will be simple to grasp because they are related concepts. So, stay tuned with us to get more information about Python.
Hello learners! Welcome to the engineering projects where we are working on deep learning. In this series, we are at the part where Python is under our observation. In the last session, we saw the Python built-in functions and the practical implementation of some important pre-defined functions of Python. In the current lecture, you will learn about the fundamental concept of Python. It is not wrong to say that if you want to work in any high-level programming language, you have to understand its data types; otherwise, you will not be able to code complex or long programs using it. More details will be discussed in the next section, but before this, you should have a glance at the concepts you will learn in this tutorial.
What are the data types?
How are Python data types different from other programming languages?
What is the syntax to use the data types in Python?
What is the difference between floats and integers?
How can you practice other concepts along with the complex number in TensorFlow?
What is the casting process in the Python programming language and how can you use it for changing the type of data you enter?
What is the “type” function in Python and how do you use it?
For your convenience and detailed learning, we are just discussing the numeric data types in this lecture, and you will learn more types in the next lecture because I want to discuss each type with the practical implementation of different operations on these data types.
Consider the case where we use different types of numbers in mathematics and apply the operations to these different types of numbers. We know that only numbers can be added, subtracted, multiplied, etc. The same is true for data types. When dealing with programming languages, we have to deal with different kinds of objects, and it is important to use them wisely because of the memory storage. Have a look at the basic definition of the data types in the programming languages:
"In programming languages, the data type is the basic concept that declares the type of object being used in a specific way, and based upon the data types, the memory space is occupied by the compiler."
In simple programs, such as the ones we used in our examples, we don't notice much of a difference when we occupy more space in the program, but this is not the best practice because, in long and complex programs, we need to use the exact data type. Hence, the compiler runs perfectly and we can apply the specific operations to the particular data type.
The declaration of the data type is always required in most programming languages so that the compiler can fully understand the data type. So, you can declare the integer as a float and vice versa according to our will, but it causes problems in the compilation.
As we always say that Python is an easy programming language, and here is one of the main reasons why. In Python, the compiler itself is intelligent enough to understand the type of data you are putting into it, so your program may run well if the code is well-written. It feels like a relief that you do not have to remember the names of different data types, and there is no need to memorize the space occupied by the data type so that you may compare and choose the perfect data type for your code. The name of the data types is almost the same as the other programming languages that we have mentioned before, but the way these work with different operations may seem a little bit different. The declaration of different data types in the Python programming language is given in the next section.
The best way to learn any concept in programming is to learn the syntax first instead of going into the example and understanding how that concept works. When we talk about the syntax of data types in Python, this section is very important. You have to keep in mind that unlike some other high-level programming languages such as C++ and C#, you have only two items:
Variable name
Value of the data type
Now it's time to go over the various data types one by one. The syntax of all of these appears to be the same, but the examples will demonstrate the differences in how each of them works. For your convenience, the different data types are divided into six categories:
Numeric
String
Sequence
Mapping
Boolean
Set
These categories also have sub-categories, and the same category works in the same way, but you have to keep the differences in mind, especially if you are a beginner because it becomes easy to understand the code and the way you work with it. Other details will be clear when you see the implementation in the tensor flow. For this, I want to share the procedure for starting code in TensorFlow in a straightforward way:
Fire up your Anaconda navigator.
In the environment sector, you have to search for “Jupyter Lab” and hit the launch button there.
A new local host will appear in your browser. Go to this local host.
In the new cell, begin coding.
We all know what the numbers are, and there is no need to provide you with the details of the numbers, but to refresh the concept in your mind, we have to tell you that there are three classes of numeric data types that are introduced in Python:
Integer
Float
Complex
A short description of each of them is given next:
The first and simplest data type that you will see in every tutorial is an integer. These are whole numbers and do not contain any extra parts. These are the signed integers that have a non-limited length. It means that on the positive side of the numbers, you can have the length of an integer as long as you want. One thing that has to be considered here is the memory of the system you are using, but when purely talking about the integer, it does not have any limit in length.
Are you ready with your TensorFlow to practice all the data types and apply the different operations on them? Ok, we hope your TensorFlow is launched, and have a look at the simple representation of the integer in it.
integer=1257859304284756327
a=3824374269873874
print("integer= ", integer)
print("a = ", a)
add=integer+a
print("integer+a = " ,add)
Here, you can see that:
We can name the variable anything we want, whether it is a special name or any combination of the alphabet, but it must follow the rules that we specified in the previous lecture. The results of the code are given next:
The length of the integer does not matter, as integers can be long or short according to the requirement.
The addition can take place with the integers. Similarly, other operations such as subtraction, and multiplication is also possible.
The next is the float, which in some cases looks like an integer, but if you are a science student, you must have the idea that integers and floats are not the same. The floats contain a decimal floating number just after the integer part. So, even if the number after the decimal point is zero, it will still be called the "float." Another thing to be noticed in the floats is, you can use the 15 digits in the float, and these are not unlimited as the integers are.
In TensorFlow, I want to perform the subtraction on the float this time, and I want to show you by code that when we do not add any decimal part to the float, the compiler itself adds the zero in the decimal part and provides us with the result. Moreover, you will observe that it takes the most significant number after the decimal part; therefore, in the code, when we add the zero as the last digit, it ignores it and the results are shown with the significant numbers.
We've all learned about complex numbers in math class, and according to the requirements, these complex numbers play an important role in programming. The representation of the complex number in Python is a little bit different than in mathematics class. Have a look at the code, and after that, we will discuss it in detail.
The representation of the complex number is the same as what you were expecting. We have to use the i and j for the complex part, and the sign of addition or subtraction represents the difference between the real and complex parts.
# Step 1
z = complex(a,b);
print(z)
# Step
print ("The real part of complex number is : ",c.real)
#Step 3
print ("The imaginary part of the complex number is : ", c.imag)
Here is the first step, we have assigned the duty to the compiler to make a complex number for us. For this, we have used the “complex” built-in function. We have discussed it in lecture number 10 of this series.
The step is completed when we print the complex number to show you how the functions are working here.
We are naming the complex number “c” and keep in mind, it consists of the real and imaginary parts.
In the next step, we are simply using the “real” and “img” keywords to separate these parts of the complex number.
The good thing is, we are using the same line to print the description and the result of the code. You can also do so by using the additional line of print, but I like simple and shortcodes.
So, the overall result can be observed in the following image:
The result is shown in the form of floating numbers, and in our case, the real part is 0 by default.
Till now, we have seen simple declarations in the Python programming language, but now it's time to discuss another method of variable declaration, which is casting. Because of the various forms in which metals are cast, we've heard of this term before. The concept of casting is related to the same idea. In Python, this process is defined as:
"Casting in Python is a process in which the original type of the variable is changed to any other type by specifying it in the code in a particular way."
We have mentioned before that the Python compiler automatically detects the type of content, and therefore, in some special cases, we want to occupy the space from memory that does not match the value you are entering. If still it is confusing for you, do not worry because it will be clear in just a bit when you will look at a simple example to do so in TensorFlow.
a=23.56
b=type(a)
print("Here 'a' is a float", b)
c=int(23)
d=type(a)
print("After using the casting, the result is" , d)
Here is the output of this code, which tells you the details by itself.
The type function was covered in the previous lecture, so I hope you understand what it does. If not, you can review the previous lectures. Since the data types are so long that it becomes difficult to explain in a single lecture, you will get the details of other data types in the next lecture. Until then, you must continue to practice with these data types. We have seen the introduction of the data types and the ways to work with the data types in Python. We've also seen a comparison of other languages and Python on the same topic, and this lecture is heavy on numeric data types. I hope it was fruitful for you and that you will go to the next lecture for more data types.