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Introduction to Scala Collections

Collections in Scala are nothing but a container where the list of data items can be placed and processed together within the memory. It consists of both mutable (scala.collection.mutable) and immutable (scala.collection.immutable) collections which in-turn varies functionally with Val and Var and also, Scala collections provide a wide range of flexible built-in methods, which can be used to perform various operations like transformations & actions, directly on the data items.

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Scala Collections Framework

At a very high-level collection contains Seq, Set & Map. All of them are the child of Traversable traits. Do keep it in mind, All of the Childs of Traversable (Parent) are Traits and not classes which makes it easier to implement in the code snippet, without having the need to create the object before calling it.

Let us discuss it in detail as follows:

Reference – Book: A Beginner’s Guide to Scala, Object Orientation and Functional Programming

Traversable: helps us to traverse through the entire collection and it implements the behavior that are common to all the collections irrespective of the data types. It simply means Traversable lets us traverse the collections repeatedly in terms of for each method.

Iterable: gives us an iterator, which lets you loop through a collection’s elements one at a time.

Note: By using an iterator, the collection can be traversed only once, because each element is consumed during the iteration process.

Mutable & Immutable Collections

Scala Provides 2 varieties of collections. They are:

Mutable

Immutable

Mutable Collections

Example:

AnyRefMap

ArrayBuffer

ArrayBuilder

ArraySeq

ArrayStack

BitSet

DoubleLinkedList

HashMap

HashSet

LinkedHashMap

LinkedHashSet

LinkedList

Stack

StringBuilder

TreeSet

WeekHashMap, etc.

Immutable Collections

This type of collection can never be changed. We can still see the methods that look like adding/ updating/ removing elements from the collection. But it actually creates a new collection internally and leaves the old one unchanged.

Example:

BitSet

HashMap

HashSet

List

ListMap

ListSet

LongMap

NumericRange

Stack

Stream

StreamIterator

TreeMap

TreeSet

Vector

IndexedSeq, etc..

String & Lazy Collection

Whenever we perform any data transformations using a filter, map, min, max, reduce, fold, etc.., on collections, it basically transforms it into another collection. There could be some collections that allow Strict Transformations means, the memory of the elements are allocated immediately when the elements are evaluated and results in the new collection. In a Lazy Collection, the transformations will not create another collection upfront. It means, the memory will not be allocated immediately and it creates the new collection when there is a demand. Collection classes can be converted into Lazy Collection by creating a view on the collection.

Let us look into the Scala REPL example for a better understanding.

Example:

Code:

object Demo { def main(args: Array[String]) { val ls = (0 to 5).toList println("List is: " + ls); } }

Output:

While creating the collection – List, the memory is allocated immediately and when we try to call the list, we are able to find the list of elements as below.

ls res0: List[Int] = List(0, 1, 2, 3, 4, 5) //collection items of ls is allocated to res0. Hence, it created the memory immediately.

To Create a Lazy Collection:

object Demo { def main(args: Array[String]) { val ls = (0 to 5).toList val lsLazy = ls.view println("View: " + lsLazy); } }

lsLazy: scala.collection.SeqView[Int] = View(?)

Note: Here when we try to create a view on the existing list, we can clearly say it doesn’t allocate the memory as it only builds a view of the list until unless any action is being called like foreach, min, max, etc.

Code:

object Demo { def main(args: Array[String]) { val ls = (0 to 5).toList val lsLazy = ls.view println("max "+lsLazy.max); } }

object Demo { def main(args: Array[String]) { val ls = (0 to 5).toList val lsLazy = ls.view lsLazy.foreach(println) } }

Let us investigate some of the basic methods that come with the Collections:

Mutable Collections: ArrayBuffer

Example:

object Demo { def main(args: Array[String]) { val arrBuff = (0 to 5).toBuffer println(" "+arrBuff); } }

Output:

Now, let’s try adding an element to the existing ArrayBuffer Collection.

object Demo { def main(args: Array[String]) { val arrBuff = (0 to 5).toBuffer arrBuff += 5 println(" "+arrBuff); } }

Look at the below result, if you look closer, you could find that data item “5” has been appended to the existing collection.

Note: += is a method that is used to append the element to the original collection. i.e., adds the new element to the collection and reassigns the result to the original collection.

Example:

Code:

object Demo { def main(args: Array[String]) { val arrBuff1 = (0 to 5).toBuffer println(" "+arrBuff1); } }

Output:

Code:

object Demo { def main(args: Array[String]) { val arrBuff1 = (0 to 5).toBuffer arrBuff1 +=66 println(" "+arrBuff1); } }

Output:

res24: scala.collection.mutable.Buffer[Int] = ArrayBuffer(0, 1, 2, 3, 4, 5, 66) // added in the copy, not the original

res25: scala.collection.mutable.Buffer[Int] = ArrayBuffer(0, 1, 2, 3, 4, 5) // check the original collection and note that the collection items remain unchanged.

Immutable Collection: List

Code:

object Demo { def main(args: Array[String]) { val ls = (1 to 5).toList println(" "+ls); } }

Note: Mutable collections doesn’t have += method to append and reassign.

object Demo { def main(args: Array[String]) { val ls = (1 to 5).toList ls :+5 println(" "+ls); } }

Note: Use ” :+= ” as the reassignment operator, while dealing with immutable collections to update the existing immutable collection. This method can be applied only on “var” and not on “val”.

Example:

Code:

object Demo { def main(args: Array[String]) { val ls = (1 to 5).toList } }

Output:

Note: map will always return the output of the same incoming data type. In the above screenshot, the input was List[Int], hence the output is also same. It output stored in “res13”.

Example:

Code:

object Demo { def main(args: Array[String]) { val ls = (1 to 5).toList ls.foreach(println) }

Output:

Note: If you look carefully in the screenshot, you can notice that the output of foreach hasn’t stored on any result variables here. This is why foreach varies with map.

Conclusion

As we have seen so far, collections are way useful to store and retrieve formatted items of the respective data types. Also, it comes with various methods to add/ change or delete items from the collection. It is even adaptable to use in most critical scenarios, as it provides mutable and immutable collections.

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How Byte Types Work In Scala? Examples

Introduction to Scala Byte

Scala Byte contains 8-bit like any other programming language. Scala byte is a member of the value class, and this scala byte is equal to the java byte primitive type. In Scala, we cannot represent an instance of a byte as an object. In scala this byte is implicitly converted from byte to rich byte internally because, after conversion, it provides us some useful nonprimitive operations on it. Byte is basically an 8-bit signed integer, and also, scala byte is different from int data type.

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Syntax:

varvariable_name: Byte = value _of_variable

In the above syntax, we need to provide the variable name followed by the type of the variable. In our case, we have defined Byte as the data type for it. After that data type, we can assign value to the variable created.

How do Byte Types work in Scala?

But in general, language how it looks like we can see below:

1 Byte = 8-bit

We can say that it is a collection of 8-bit. These 8 bits represent in the form of 0 and 1. Also, it is the smallest unit of storage in the computer system. So we can say that a byte is a group of bits to store information.

For example, they look like:

0 1 0 1 1 0 1 0 representation in 0 and 1 format.

Now we can have a look at its hierarchy, extended class, supertupes:

Hierarchy:

Anyval

lang.Byte

RichByte

Double

Float

Long

Extends and super classes:

Anyval

Any

Example:

One simple program to know workings of scale.

Code:

object Main extends App{ valbyteResult = (20.toByte).^(2:Byte) println("now the result is  :: " + byteResult) }

We are defining a byte into our main function, followed by the methods that convert the value passed of bitwise XOR. Just holding this to our result variable to show the output. In Byte, we have an overflow problem which is related to the range of the byte. Scala byte ranges from -128 to 127. So if the range exceeds the mentioned range, it will start an overflow of bytes, and the reminder byte will display in the output.

KiloByteKB: This KB is measured and equal to 1024 bytes.

MegaByteMB: This MB is measured and equal to 1,048,576 bytes.

Gigabyte YB: This GB is measured and equal to 1,000 MB, or we can convert it into bytes of 1,073,741,824 bytes.

TeraByteTB: This TB is measured and equal to 1,000 GB, or we can convert it to a byte of 1,000,000,000,000 bytes.

We can measure the byte multiple for this. We have two systems i.e. base-10 or base-2.

Examples of Scala Byte

Given below are the examples mentioned:

Example #1

Code:

object Main extends App{ vara : Byte = 10 varb : Byte = 20 println("result for the above function is  ::: ") println(byteResult) }

Example #2

Code:

object Main extends App{ vara : Byte = 10 varb : Byte = 20 valbyteResult = (a.toByte).<(b:Byte) println("result for the above function is  ::: ") println(byteResult) }

Output:

Example #3

Code:

object Main extends App{ vara : Byte = 20 varb : Byte = 20 valbyteResult = (a.toByte).<=(b:Byte) println("result for the above function is  ::: ") println(byteResult) }

Output:

Example #4 object Main extends App{ vara : Byte = 20 varb : Byte = 20 valbyteResult = (a.toByte).==(b:Byte) println("result for the above function is  ::: ") println(byteResult) }

Output:

Example #5

Code:

object Main extends App{ vara : Byte = 20 varb : Byte = 20 valbyteResult = (a.toByte).!=(b:Byte) println("result for the above function is  ::: ") println(byteResult) }

Output:

Example #6

Code:

object Main extends App{ vara : Byte = 20 varb : Byte = 20 println("result for the above function is  ::: ") println(byteResult) }

Output:

Conclusion

So scala byte is like any other byte in a computer system or, we can say, in a programming language. One byte can be formed by using a collection of 8 bites or a group of 8 bits. We also have different types of bytes, which possess different memory storage accordingly. It also gave us various methods to work with it.

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How Function Works In Scala With Examples

Definition of Scala Function

As the name suggests, Scala Function means a piece of code supposed to do a function. Like any other programming language scala, Function works in the same way. The function is nothing but a way to writing our logic in a separate part, or we can say a function is a group of statements that are responsible for performing some specific task. The function can be used where we have the same logic or repetitive code, so instead of writing the code again and again, we can create one function and call that from everywhere. Scala function is also responsible for performing a specific task.

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How to Define Functions in Scala? defname_of_function ([parametre_list]) : [return_type] = { }

Scala Function contained 6 parts while defining; let’s discuss them one by one.

def: It is a keyword that is available in scala. If you want to define any function, we have to use this keyword at the beginning.

name_of_function: This is the user-defined name of the function. It should be similar to the logic or task that the function is going to execute while calling. Also, it should be in a camel-case (lower).

return_type: return type means what we are expecting from the function in return after executing. It can be anything, but it is optional. In java, the default return type is void, and in scale, it is Unit if we do not specify.

parametre_list: This stands for what we are providing to our function while calling. We have to specify the data type of the parameters as well while declaring inside the square brackets []. We will see them into the practice syntax below.

 =: This can be used with the return type component. It specifies, if the = is there, it means our function is going to return some value. If not, then no value we want. It is like a default return type function.

function logic: Inside this, we write the whole logic that we want to perform on the calling of function. We can also call the different functions inside this function. Remember body should be enclosed with the {} curly braces.

defcalculateSum ([a:Int, b: Int]) : Int = { return a + b; }

This way, we can define it.

How does Function work in Scala?

The function is used to perform the task. To use any function, we need to call it. Scala provides us with different ways to call a function, i.e. we can call them directly or by using the class instance.

[instance].name_of_function

or

function(list_parameter)

In scala, we have two types of functions like any other programming language.

Parameterized functions: In this type of function, we pass the list of parameters.

Non-Parameterized functions: In this type of function, we do not pass any parameters to function. That will be empty. Also, we can pass any user-defined value as a parameter also.

Let’s take one example to understand its working;

object Main extends App{ calculateSum(10, 20) defcalculateSum(a : Int, b : Int){ var result = a + b ; println("Result is  :: "+ result) } }

Above we have defined one function name calculateSum, and it is taking two variables, a and b. Both are of the Integer type. Inside the function body, we have written the logic that we want to perform. We are adding these two values, a and b, holding the value into the third variable named result. After that, we are just printing the value that we obtained. But now we have to call this function, so in the above line, we are calling the function b its name and parameter specified. The number of Parameters we passed and the number defined in the function signature should be the same; otherwise, it will give a compile-time error.

Examples of Scala Function

Examples of (simple function, parameterized function, etc.).

Example #1

This example shows the use of functions without parameters.

object Main extends App{ simpleFunction() defsimpleFunction(){ println("This is simple function") println( "without parameter. ") } }

Output:

Example #2

Code:

object Main extends App{ sum(20 , 50, 100) defsum(x: Int, y : Int, z: Int){ println("This is parameter function") var result = x + y +z println("result obtained is  :::"  +result) } }

Output:

Example #3

In this example, we are making a mixed parameter list of a function. This takes integer and string as well.

Code:

object Main extends App{ mixedFunction(20 , 50, 100, "Ajay", "Indore") defmixedFunction(x: Int, y : Int, z: Int, name: String, address: String){ println("This is parameter function") var result = x + y +z println("result obtained is  :::"  +result) println("Employee name  :: " + name) println("Employee address  :: " + address) } }

Example #4

In this example, we are taking a user-defined object and printing its value. We can take any value as a parameter.

Code:

object Main extends App{ var emp1 = new Employee("Amita", 20, 30, "Indore") employeeInfo(emp1) defemployeeInfo(emp : Employee){ println("In this we are taking one user defined parameter.") println("Passing a user value ::") } } class Employee(name: String, Id:Int, Age: Int, address: String){ }

Output:

Conclusion

Functions are used to avoid the redundant code or repetitive code. It makes our code looks simple and more understandable. Also, we can easily debug our code and identified the error, if any. These Scala functions are the same as any other programming language. Keep in mind the return type and parameter list or signature of the function while working with them.

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How Reduce Function Work In Scala With Examples

Introduction to Scala reduce Function

Scala reduces functions to reduce the collection data structure in Scala. This function can be applied for both mutable and immutable collection data structures. Mutable objects are those whose values change frequently, whereas immutable objects are those objects that one assign cannot change itself. Reduce function can be applied to map, sequence, set, list, etc. This function returns a single value from the collection data structure. In reducing function, it merges all the values from the collection data structure and returns on a single value.

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Syntax

Below is the syntax of Scala reduce:

Explanation: In the above syntax, we have prepared one collection followed by the reduced function. It takes two parameters on which we can perform our operation. At last, we will obtain one value as output.

How does reduce Function work in Scala?

Reduce function reduces the number of elements in the collection data structure. What it does internally is it uses binary operation and merges all the available elements into one single element. We can see how it works internally. Suppose we have one list of elements like 3, 7, 9, 2, 1, 5. Now we will apply to reduce function to generate a single number after adding all the numbers from the list.

1. First, it will take the first element 3. Then it will apply a binary operation on the first and second numbers and merge them to generate the third number.

Now we can have a look at one practical example for beginners for more understanding:

Code:

object Main extends App{ val collection = List(200 , 400, 100, 30, 1000, 500) }

Explanation: In this example, we create one collection data structure list. After that, we apply to reduce function on the list to try to find out the max element from the list of elements. This will also return as a single value from the list of elements.

Extended class:

AbstractIterable[(K, V)]

Map[K, V]

Some of the supertype:

Map

Equals

MapFactoryDefaults

MapOps

PartialFunction

AbstractIterable

Iterable

IterableFactoryDefault

IterableOps

IterableOnceOps

IterableOnceOps

Some known classes:

TrieMap

AbstractMap

HashMap

IntMap

ListMap

Longman

Map1

Map2

Map3

Map4

withDefault

TreeMap

TrrSeqMap

VectorMap

AbstractMap

AnyRefMap

CollisionProofHashMap

LinkedHashMap

LongMap

WithDefault

SystemProperties

ListMap

OpenHashMap

reduceLeft

reduceRight

reception

reduceRightOPtion

reduceLeftOPtion

Examples to Implement Scala reduce

Below are the examples mentioned :

Example #1

In this example, we find out the sum of all elements present in the collection data structure using a binary operation.

Code:

object Main extends App{ val list1 = List(200 , 400, 100, 30, 1000, 500) println("list before ::") println(list1) println("list after ::") println(result) }

Output:

Example #2

In this example, we find out the subtraction of all elements present in the collection data structure using a binary operation.

Code:

object Main extends App{ val list1 = List(200 , 400, 100, 30, 1000, 500) println("list before ::") println(list1) println("list after ::") println(result) }

Output:

Example #3

In this example, we are finding out the multiplication of all elements present into the collection data structure by using a binary operation.

Code:

object Main extends App{ val list1 = List(200 , 400, 100, 30, 1000, 500) println("list before ::") println(list1) println("list after ::") println(result) }

Example #4

In this example, we find out the division of all elements present in the collection data structure using a binary operation.

Code:

object Main extends App{ val list1 = List(200 , 400, 100, 30, 1000, 500) println("list before ::") println(list1) println("list after ::") println(result) }

Output:

Example #5

In this example, we are finding out the minimum of all elements present in the collection data structure by using a binary operation.

Code:

object Main extends App{ val list1 = List(200 , 400, 100, 30, 1000, 500) println("list before ::") println(list1) println("list after ::") println(result) }

Output:

Conclusion

Scala reduces function is used to perform the binary operation on the collection elements. We can perform so many types of operations. Also, we can find the maximum and minimum values from the collection using the reduce function. Always remember this reduction will always return a single value as the output of the logic because it will merge all the values from the collection.

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Top Examples To Implement Of Datareader C#

Introduction to DataReader C#

A Data reader is an object that is used to read data from the data sources. This can only perform read operation and not update operation on the data source. The data is retrieved as a data stream from the data source. Though the data reader is restricted in terms of only reading operation, it is highly effective and optimized as it is read only and forward only. There are two types of providers in the .Net Framework, they are SQLDataReader and OleDbDataReader. The data reader increases the application performance by reducing system overhead as it stores the only row in memory at a given point of time. This article will cover in detail the data reader in c# along with appropriate examples.

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Syntax:

The sql data reader is available in the namespace System.Data.SqlClient and the corresponding assembly is chúng tôi A SQL data reader is initialized as follows.

SqlDataReadersqlReader = sqlCmd.ExecuteReader();

The execute reader is used to pass the SQL statements or procedure to the sqlconnection object and the corresponding result is stored in the sqlreader object of SqlDataReader. Before reading from any data reader, it should always be open and should point to the first record. The read() method of data reader is used to read and it moves forward to the next row.

The oledb data reader also behaves in the same way. It is available in the name space System.Data.OleDb and the corresponding assembly is chúng tôi An oledbDataReader object is used to connect to OLEDB data sources and fetch data from them. Like SQLDataReader, oledbdata reader should also be open before performing read operation. An oledb data reader is initialized as follows.

OleDbDataReaderoledbReader = oledbCmd.ExecuteReader();

Where the executereader is used to carry out the SQL statements or procedures.

Accessing Data Reader Results Working with Multiple Sets

If data reader returns multiple result sets, the NextResult method of data reader can be used to access them. During implementation, it should be noted and taken care that all the result sets are being iterated and each column inside the result set is accessible.

Examples to Implement of DataReader C#

Below are the examples of DataReader C#:

Example #1

Typically, data is read from the result set returned by the data reader is to iterate each row using a while loop. The read method return value is of bool type, if the next row is present then true is returned and for the last record, false is returned. The while loop will be executed until the condition becomes false.

Syntax:

while(rdr.Read()) { }

Like closing a SQL connection, it is always a best practice to close the Data reader. All the while part can be in enclosed in a try block and the data reader connection can be closed in the finally block.

Syntax:

try { } Catch { } finally { if (reader != null) { reader.Close(); } }

Code:

using System; using System.Windows.Forms; using System.Data.SqlClient; namespace test { public partial class test1 : Form { public test1() { InitializeComponent(); } Public static void main() { string constr = null; SqlConnectionscon ; SqlCommandscmd ; string sstat = null; constr = "Data Source=testserver;Initial Catalog=testdb;User ID=test;Password=test"; sstat = "Select * from test"; scon = new SqlConnection(constr); try { scon.Open(); scmd = new SqlCommand(sstat, scon); SqlDataReadersstatReader = scmd.ExecuteReader(); while (sstatReader.Read()) { Console.WriteLine("Name:" sstatReader.GetValue(0)  + "age:"  sstatReader.GetValue(1) ); } sstatReader.Close(); scmd.Dispose(); scon.Close(); } catch (Exception ex) { } } } }

Example #2

Code:

using System; using System.Windows.Forms; using System.Data.OleDb; namespace test { public partial class test : Form { public test() { InitializeComponent(); } Public static void main() { string constr = null; OleDbConnectionocon ; OleDbCommandocmd ; string sql = null; constr = "Provider=Microsoft.Jet.OLEDB.4.0;Data Source=test.mdb"; sql = "select * from emp"; ocon = new OleDbConnection(constr); try { ocon.Open(); ocmd = new OleDbCommand(sql, ocon); OleDbDataReaderordr = ocmd.ExecuteReader(); while (ordr.Read ()) { Console.WriteLine("EmpName:" ordr.GetValue(0) + "Empage:"  ordr.GetValue(1) + "Esalary" ordr.GetValue(2) ); } ordr.Close(); ocmd.Dispose(); ocon.Close(); } catch (Exception ex) { Console.WriteLine("Connection Failed"); } } } }

Output:

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Top 3 Examples To Implement Of Python Curl

Introduction to Python Curl

A curl is a request tool that is used to create network requests so that it allows it to transfer the data across the network, which is done using the command line. In this article, we are going to discussing curl in Python. In python, a curl is a tool for transferring data requests to and from a server using PycURL. This tool is used for testing REST APIs, downloading files, etc. this PycURL is an interface to the libcURL library in Python, and hence the PycURL is capable of inheriting all the capabilities of libcURL.

Working of Python Curl

In this article, Python curl is used for REST API for transferring the data to and from a server. In this, we will see PycURL is a python interface used to fetch the objects from a python program identified by a URL.

Curl is a UNIX command which can send GET, POST, PUT and DELETE request to a URL. There is an HTTP library called “Requests” in Python, but this library needs to be pulled as it’s not any standard module. When this library is used, we can create a simple request, and this request returns a response object which allows access to the various status codes or headers, etc. Let us see an example below with output for each line:

Examples to Implement Python Curl

Below are the examples of Python Curl:

Example #1

Code:

import requests print url

Output:

headers={'x-api-key':'09ba90f6-dcd0-42c0-8c13-5baa6f2377d0'} print headers

Output:

resp = requests.get(url,headers=headers) print resp.status_code

Here you will get the output code as status code as 200.

print resp.content print resp

The above will print the content.

From the above code snippets, we need to first import the request library, and then we create a URL, and we will print the URL, and headers will also be defined and printed. Then we saw that request.get() method is called by passing the URL and headers obtained above to this method. This method returns a response object (resp). In the above code snippets, we can see that we will be printing the content of the request using this response object.get() method which will allow us to access and print the status_code and entire content is printed, and we can also see the list of attributes of this response object that are available. Similarly, we also can use different request methods like requests.put(), request.post(), request.delete(), etc.

We can see the syntax of each of these request methods, and we can see below:

Call.request.get(URL) this is used to send a GET request to the URL.

Call.request.post(URL, data= dict) in this dict contains a dictionary of keys and also has values to send to a POST request.

Call.request.put(URL, data =dict) this also works similarly to POST request; this will also send URL and values to a PUT request.

Call.requset.delete(URL, data =dict); this also has the same parameters as the above two request methods, and this request also sends the URL and values to the DELETE request method.

In Python, we use PycURL as a CURL tool and are used for testing REST APIs. As this PycURL supports a different variety of protocols like FILE, FTPS, HTTPS, IMAP, SMB, SCP, etc. The installation of PycURL is very simple for any of the operating systems. So below is the sampling process for installing the PycURL.

$ pip install pycurl $ easy_install pycurl

The above two can be used for installing pycurl in mac or Linux OS. Now we will see how can this be installed in Windows OS, but before this, we need to install a few dependencies. So you can run the below command in the Python terminal as below:

Command:

$ pip install pycurl

If pip is not used, we can use EXE and MSI installers available at PycURL windows.

Example #2

Let us below the sample example for sending an HTTP GET request.

Code:

import pycurl from io import BytesIO b_obj = BytesIO() crl = pycurl.Curl() crl.setopt(crl.WRITEDATA, b_obj) crl.perform() crl.close() get_body = b_obj.getvalue() print('Output of GET request:n%s' % get_body.decode('utf8'))

Output:

Similarly, there are different ways and codes in Python using PycURL for using POST, PUT, DELETE, etc., methods. Let us what code sample can be written for sending an HTTP DELETE request. This method where it deletes the server resource that is identified by the URL. This can be implemented using CUSTOMREQUEST.

Example #3

Below is a sample example:

Code:

import pycurl crl = pycurl.Curl() crl.setopt(crl.CUSTOMREQUEST, "DELETE") crl.perform() crl.close()

The above code snippet is to send the HTTP DELETE request. So we can see how to use HTTP DELETE request for sending this request using a curl tool in Python like PycURL.

Conclusion

In this article, we discussed the curl, which is a tool for transferring data from and to the server. In Python, we have the PycURL library, which uses libcurl, a standard library, and PycURL uses its values. We also saw the various methods that are called syntax. In this article, we also saw the usage of PycURL, which we first saw how to import it and how to use this and use various curl methods such as perform(), close(), etc.

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