Every webpage, nowadays, is updated without reloading the page to provide users with a smooth experience. Updating a page without reloading it is only possible with the use of JavaScript, as web browsers exclusively run JavaScript as a programming language.
Similarly, uploading a file without reloading the page is achieved with JavaScript to ensure a seamless user experience. Uploading a file using JavaScript is necessary to:
<ul>
<li>
Interact on the web. Two or more people can engage by sending images, videos, and various file types to one another. For instance, you can email images and reply with images on Gmail due to file uploading capabilities provided by JavaScript.
</li>
<li>
Collect crucial data from users. At times, you may need to verify a person's identity before allowing them to use your services. You may ask them to upload a photo of themselves holding their identity card, or simply upload a PDF file of their bank statement. Uploading a file with JavaScript makes this possible.
</li>
<li>
Preserve data. Storing important memories or information in the form of files is crucial, allowing us to upload a file to the cloud for safekeeping.
</li>
<li>
Process data for content extraction, editing, cleaning, and updating. JavaScript is powerful enough to carry out complex processing tasks such as adding filters to images, extracting text from images, and more. Uploading a file for processing can help achieve a specific goal.
</li>
</ul>
Now that you understand what uploading a file with JavaScript entails and its purpose, let's build a simple application to demonstrate the process.
<h3 id="createasimpleformforfileuploadwithhtml">Create a Simple Form for File Upload with HTML</h3>
The HTML form below will be used to select a file.
<pre><code class="hljs">&lt;form id=&quot;fileUploadForm&quot;&gt;
 &lt;input type=&quot;text&quot; name=&quot;firstName&quot; value=&quot;John&quot; /&gt;
 File: &lt;input type=&quot;file&quot; name=&quot;upload&quot; /&gt;
 &lt;input type=&quot;submit&quot; id=&quot;btn&quot; /&gt;
&lt;/form&gt;
</code></pre>
Then, in the form, we have an <code>input</code> tag with its <code>type</code> set to <code>file</code> and its <code>name</code> set to <code>upload</code>. This allows uploading various file types, including images, PDFs, videos, and more.
<h3 id="accesstheformwithjavascript">Access the Form with JavaScript</h3>
To access a form with JavaScript and obtain user inputs from it, there are several methods. In this example, we use the following code:
<pre><code class="hljs">const form = document.getElementById(&quot;fileUploadForm&quot;);
const submitter = document.getElementById(&quot;btn&quot;);
</code></pre>
We have now accessed the entire form and its submitter using JavaScript. If you run <code>console.log({form, submitter})</code>, you will see the exact form and its submitter from the initial HTML content. When a user selects a file, we want to obtain the chosen file using the <code>FormData</code> constructor.
<h3 id="understandingformdatainjavascript">Understanding FormData in JavaScript</h3>
<code>FormData</code> is a constructor that creates an object to store form inputs as key/value pairs. It uses the name property of a given input tag as a key and the entered value as its value. We can then retrieve all user input from the <code>FormData</code> object. It's important to note that developers often use <code>FormData</code> because it encodes file input.
How does it work?
The <code>FormData</code> object can be used to collect form inputs in three major ways and handle them individually.
<h4 id="grabinputsfromaspecificformafteranevent">Grab Inputs from a Specific Form After an Event</h4>
<pre><code class="hljs">// const form = document.getElementById(&quot;fileUploadForm&quot;);
form.addEventListener(&quot;submit&quot;, (event) =&gt; { 
 const inputs = new FormData(form); 
});
</code></pre>
Here, we accessed the form and its submitter, and now we use the <code>FormData</code> object to collect all the user inputs from the form after it is submitted.
<h4 id="prepopulateavariablefromaform">Prepopulate a Variable from a Form</h4>
<pre><code class="hljs">// const form = document.getElementById(&quot;fileUploadForm&quot;);
// const submitter = document.getElementById(&quot;btn&quot;);
const inputs = new FormData(form, submitter); 
</code></pre>
By passing both the form and its submitter to the <code>FormData</code> constructor, we automatically obtain any value entered in the form. It is important to note that the code above will only be valid if the submitter is a member of the form. Additionally, <code>FormData</code> only retrieves input with a name and without a disabled state.
<h4 id="createanemptyformdata">Create an Empty FormData</h4>
<pre><code class="hljs">const inputs = new FormData();
</code></pre>
The code snippet above constructs an empty <code>FormData</code> object to which we can add data when needed.
<pre><code class="hljs">const inputs = new FormData();
inputs.set(&quot;name&quot;, &quot;Ayobami&quot;);
</code></pre>
The empty <code>FormData</code> is useful for structuring form input values when they are not obtained directly from a form. Visit the <a href="https://developer.mozilla.org/en-US/docs/Web/API/FormData" target="_blank" rel="noopener noreferrer">FormData Web API</a> to learn more about other <code>FormData</code>.

 <div class="alert alert-note">
 <div class="flex">
 
 <div class="flex-shrink-0 mr-3">
 <img src="/assets/images/icon-information-circle-solid.svg" class="icon" aria-hidden="true" />
 </div>
 
 <div class="w-full">
 Note: A <code>FormData</code> object has the same methods whether it is prepopulated, empty, or &quot;post populated&quot;. Now that you have learned how to capture form input values, it's time to learn about the Fetch API to send the file to the server.

 </div>
 </div>
 </div>
 <h3 id="whatisthefetchapi">What is the Fetch API?</h3>
The Fetch API enables a webpage to send and receive resources from a server asynchronously, that is, without interrupting the single-threaded execution of the JavaScript engine. The fetch method returns a promise that resolves into a Response object, from which the actual data can be extracted by calling some methods of the Response object, such as <code>json()</code> or <code>text()</code>.
Here is the syntactic structure of the Fetch API:
<pre><code class="hljs">fetch(resource, options)
</code></pre>
The Fetch API takes two arguments. The first of the two arguments is the <code>resource</code>, which is primarily a URL to a resource to be fetched. The second argument provides the custom options you want to set for your request. Please check the <a href="https://developer.mozilla.org/en-US/docs/Web/API/fetch" target="_blank" rel="noopener noreferrer">Fetch Global Function</a> to learn how to customize the fetch options in detail.
<h3 id="uploadingafilewithjavascript">Uploading a File with JavaScript</h3>
Uploading a file using JavaScript is similar to the standard form submission with JavaScript. The attributes of our file input tag indicate that we want to upload a file of any type (image, video, or others).
Here's how:
<pre><code class="hljs">const form = document.getElementById(&quot;fileUploadForm&quot;);
const data = new FormData(form);
form.addEventListener(&quot;submit&quot;, async (event) =&gt; {
 event.preventDefault();

 let response = await fetch(&quot;https://jsonplaceholder.typicode.com/posts&quot;, {
 method: &quot;POST&quot;,
 body: JSON.stringify(data),
 headers: {
 &quot;Content-type&quot;: &quot;application/json; charset=UTF-8&quot;,
 },
 });

 let result = await response.json();
 console.log(result);
});
</code></pre>
In the code above, we obtain the selected input of a form using the <code>FormData</code> constructor and send it as the <code>body</code> of a request to the <code>URL</code> in the <code>Fetch API</code>. We set the request method to <code>POST</code> to transmit the data as the request <code>body</code> and prevent third parties from viewing the content of the request, as it is automatically encrypted by <code>HTTPS</code>. In short, the <code>POST</code> method is utilized to send new data to the server. Additionally, we set the request headers to indicate that the content is in <code>JSON</code> format and <code>UTF-8</code> encoded.
The <code>async</code> keyword indicates that the function may take some time to execute, and the JavaScript engine should continue to process other parts of the code. Meanwhile, <code>await</code> instructs the engine to wait for a response before proceeding with other parts of the code, as the entire code relies on the response.
You might be wondering how the file-uploading approach in this article differs from the traditional way of uploading strictly via HTML forms. It is different because it sends well-structured form data asynchronously, unlike HTML forms that need to reload the page. Additionally, it is properly handled by the server just like HTML forms because it is an object of HTML form data, which can be sent in <code>JSON</code> or other formats.
The major known disadvantage of uploading files with JavaScript instead of an HTML form is that uploading won't work if JavaScript is disabled in the browser.
<code>FormData</code> is supported in all modern web browsers when you don't use its second parameter <code>FormData('passformElement', 'dontPassSubmitter)</code> or you follow the method outlined in this article. However, some features of the <code>Fetch API</code> are not supported in all modern browsers, which is why developers tend to use <a href="https://axios-http.com/" target="_blank" rel="noopener noreferrer">Axios</a> as it is built on the <code>Fetch API</code> and provides a workaround for all major browsers.
Here is what our simple example would look like in your browser, with slight modifications:
<img src="https://s3.stackabuse.com/media/articles/upload-a-file-using-javascript-1.png" alt="">
<h3 id="finalthoughts">Final Thoughts</h3>
Uploading a file using JavaScript plays a crucial role in enhancing user interactions. It also aids in collecting, processing, and preserving data. Many real-world problems require some of the mentioned use cases of uploading a file with JavaScript.
At this point, you should be able to access a form, utilize the <code>FormData</code> constructor, comprehend the Fetch API, and upload a file with JavaScript in real-world projects. Although you may need to learn form validation and encryption with JavaScript, this article provides you with a strong foundation for uploading a file using JavaScript.

Guest Contributor

Upload a File Using JavaScript

Scott Robinson

Finding Numbers in Various Data Types in Python

<h3 id="introduction">Introduction</h3>
In Python, it's often important to check whether a string is empty or <code>None</code> before performing operations on it. This can prevent unexpected errors and make your code more robust. But what is the most efficient and Pythonic way to do this? And what potential pitfalls should you watch out for?
<blockquote>
In this article, we'll explore these questions, demonstrating how to correctly check if a string is empty or <code>None</code> in Python, as well as discussing some best practices to make your code more reliable and maintainable.
</blockquote>
<h3 id="booleanevaluationinpython">Boolean Evaluation in Python</h3>
In Python, values are considered &quot;truthy&quot; or &quot;falsy&quot; based on whether they evaluate to <code>True</code> or <code>False</code> in a boolean context. This concept plays a crucial role when checking conditions in code.
For strings, an empty string (<code>&quot;&quot;</code>) is considered &quot;falsy&quot; — it evaluates to <code>False</code> in a boolean context. On the other hand, a non-empty string is &quot;truthy&quot; — it evaluates to <code>True</code>. The special value <code>None</code> is also considered &quot;falsy&quot;, as shown in the following code snippet:
<pre><code class="hljs">s1 = &quot;&quot;
s2 = &quot;Hello&quot;
s3 = None

print(bool(s1)) # False
print(bool(s2)) # True
print(bool(s3)) # False
</code></pre>
This property of strings and <code>None</code> is extremely useful when you want to check if a string is empty or <code>None</code>. As we'll see in the next sections, you can use simple if statements to make these checks, leveraging the &quot;falsiness&quot; of an empty string and <code>None</code>.
<h3 id="checkingifastringisempty">Checking if a String is Empty</h3>
When checking if a string is empty in Python, we can take advantage of the fact that an empty string is &quot;falsy&quot;. You can use either the <code>==</code> operator or the <code>not</code> operator to perform this check.
<h4 id="method1usingtheoperator">Method 1: Using the <code>==</code> Operator</h4>
<pre><code class="hljs">s = &quot;&quot;
if s == &quot;&quot;:
 print(&quot;String is empty&quot;)
else:
 print(&quot;String is not empty&quot;)
</code></pre>
<h4 id="method2usingthenotoperator">Method 2: Using the <code>not</code> Operator</h4>
<pre><code class="hljs">s = &quot;&quot;
if not s:
 print(&quot;String is empty&quot;)
else:
 print(&quot;String is not empty&quot;)
</code></pre>
In both of these methods, the <code>if</code> statement will print <code>&quot;String is empty&quot;</code> if the string <code>s</code> is empty. The <code>not</code> operator in the second example negates the &quot;truthiness&quot; or &quot;falsiness&quot; of the string, making the code slightly more concise. This is a common Pythonic way to check for empty strings.
<h3 id="checkingifastringisnone">Checking if a String is <code>None</code></h3>
In Python, to check if a string is <code>None</code>, it's best practice to use the <code>is</code> operator rather than the <code>==</code> operator. This is because <code>is</code> checks if both operands are the same object, not just equivalent.

 <div class="alert alert-reference">
 <div class="flex">
 
 <div class="flex-shrink-0 mr-3">
 <img src="/assets/images/icon-link-solid.svg" class="icon" aria-hidden="true" />
 </div>
 
 <div class="w-full">
 Advice: Read more about the differences between the <code>is</code> and the <code>==</code> operators in our article <a href="https://stackabuse.com/is-vs-python-object-comparison/" target="_blank">&quot;'is' vs '==' in Python - Object Comparison&quot;</a>.

 </div>
 </div>
 </div>
 Let's take a look at the practical use-case of the <code>is</code> operator for checking if a string is <code>None</code>&quot;:
<pre><code class="hljs">s = None

if s is None:
 print(&quot;String is None&quot;)
else:
 print(&quot;String is not None&quot;)
</code></pre>
As expected, the <code>if</code> statement will print <code>&quot;String is None&quot;</code> if the variable <code>s</code> is <code>None</code>.

 <div class="alert alert-note">
 <div class="flex">
 
 <div class="flex-shrink-0 mr-3">
 <img src="/assets/images/icon-information-circle-solid.svg" class="icon" aria-hidden="true" />
 </div>
 
 <div class="w-full">
 Remember, <code>None</code> is a singleton in Python, which means there is only ever one instance of <code>None</code>. Thus, using <code>is</code> is more appropriate and can be more efficient when checking for <code>None</code>.

 </div>
 </div>
 </div>
 <h3 id="checkingifastringisemptyornone">Checking if a String is Empty or <code>None</code></h3>
To check if a string is either empty or <code>None</code> in Python, we'll combine the techniques we discussed in the previous sections. We'll use an <code>or</code> operator to check both conditions at once:
<pre><code class="hljs">s = &quot;&quot; # Try also with s = None

if s is None or s == &quot;&quot;:
 print(&quot;String is empty or None&quot;)
else:
 print(&quot;String is not empty and not None&quot;)
</code></pre>

 <div class="alert alert-reference">
 <div class="flex">
 
 <div class="flex-shrink-0 mr-3">
 <img src="/assets/images/icon-link-solid.svg" class="icon" aria-hidden="true" />
 </div>
 
 <div class="w-full">
 Advice: Find out more about the <code>or</code> operator in Python by reading our <a href="https://stackabuse.com/guide-to-the-python-or-operator/" target="_blank">&quot;Guide to the Python or Operator&quot;</a>.

 </div>
 </div>
 </div>
 In this example, the <code>if</code> statement checks two conditions: if <code>s</code> is <code>None</code> and if <code>s</code> is an empty string. If either condition is true, it will print <code>&quot;String is empty or None&quot;</code>. If both conditions are false (meaning the string is not <code>None</code> and it's not empty), it will print <code>&quot;String is not empty and not None&quot;</code>.
<h3 id="tipsandadvice">Tips and Advice</h3>
<h4 id="dontuseinsteadofistocheckfornone">Don't use <code>==</code> Instead of <code>is</code> to Check for <code>None</code></h4>
Python has two equality operators, <code>==</code> and <code>is</code>. While they sometimes work the same, they are not identical. The <code>==</code> operator checks for value equality, while <code>is</code> checks for identity, meaning that it checks whether the operands are the same object.
<code>None</code> is a singleton in Python - there's only one instance of <code>None</code>. Therefore, it's more appropriate and slightly more efficient to use <code>is</code> when checking for <code>None</code>.
<pre><code class="hljs">s = None

# Recommended
if s is None:
 print(&quot;s is None&quot;)

# Not recommended
if s == None:
 print(&quot;s is None&quot;)
</code></pre>
<h4 id="takeadvantageofpythonstruthiness">Take Advantage of Python's &quot;Truthiness&quot;</h4>
Python's treatment of different values as &quot;truthy&quot; or &quot;falsy&quot; in boolean contexts can simplify your code. Rather than explicitly comparing a string to an empty string (<code>&quot;&quot;</code>), you can use the <code>not</code> keyword to check if a string is empty:
<pre><code class="hljs">s = &quot;&quot;

# Recommended
if not s:
 print(&quot;String is empty&quot;)

# Not recommended
if s == &quot;&quot;:
 print(&quot;String is empty&quot;)
</code></pre>
<h4 id="handlenonewhenperformingoperationsonstrings">Handle <code>None</code> When Performing Operations on Strings</h4>
If there's any chance a string could be <code>None</code>, always check before performing operations on it. Neglecting to do so can result in a <code>TypeError</code>:
<pre><code class="hljs">s = None

# Results in TypeError: unsupported operand type(s) for +: &#x27;NoneType&#x27; and &#x27;str&#x27;
print(s + &quot; more text&quot;)
</code></pre>
To prevent such errors, you can check if the string is <code>None</code> before performing the operation:
<pre><code class="hljs">if s is not None:
 print(s + &quot; more text&quot;)
else:
 print(&quot;String is None, cannot perform operation&quot;)
</code></pre>
<h3 id="conclusion">Conclusion</h3>
We've seen that Python provides straightforward and efficient ways to perform these checks, leveraging the &quot;truthiness&quot; and &quot;falsiness&quot; of different values in boolean contexts. We've also discussed some potential pitfalls to avoid and best practices to follow when performing these checks, such as using the <code>is</code> operator to check for <code>None</code> and the <code>not</code> operator to check for an empty string.

Dimitrije Stamenic

How to Check if a String is Empty or None in Python

Testing Vue.js Components with Vue Test Utils

Cássia Sampaio

Simple NLP in Python with TextBlob: Lemmatization

Reading and Writing SQL Files in Pandas

<h3 id="introduction">Introduction</h3>
Among the plenty of string operations, splitting a string is a significant one, offering the capability to divide a large, composite text into smaller, manageable components. Typically, we use a single delimiter like a comma, space, or a special character for this purpose. But what if you need to split a string based on multiple delimiters?
Imagine a situation where you're dealing with text data punctuated with various separators, or you're parsing a complex file with inconsistent delimiters. This is where Python's ability to split strings on multiple delimiters truly shines.
<blockquote>
In this article, we'll give you a comprehensive overview of the different techniques of multi-delimiter string splitting in Python. We'll explore core Python methods, regular expressions, and even external libraries like Pandas to achieve this.
</blockquote>
<h3 id="thestrsplitmethodcansplitstringsononlyonedelimiter">The str.split() Method can Split Strings on Only One Delimiter</h3>
The <code>str.split()</code> method is Python's built-in approach to dividing a string into a list of substrings. By default, <code>str.split()</code> uses whitespace (spaces, tabs, and newlines) as the delimiter. However, you can specify any character or sequence of characters as the delimiter:
<pre><code class="hljs">text = &quot;Python is a powerful language&quot;
words = text.split()
print(words)
</code></pre>
Running this code will result in:
<pre><code class="hljs">[&#x27;Python&#x27;, &#x27;is&#x27;, &#x27;a&#x27;, &#x27;powerful&#x27;, &#x27;language&#x27;]
</code></pre>
In this case, we've split the string into words using the default delimiter - whitespace. But what if we want to use a different delimiter? We can pass it as an argument to <code>split()</code>:
<pre><code class="hljs">text = &quot;Python,is,a,powerful,language&quot;
words = text.split(&#x27;,&#x27;)
print(words)
</code></pre>
Which will give us:
<pre><code class="hljs">[&#x27;Python&#x27;, &#x27;is&#x27;, &#x27;a&#x27;, &#x27;powerful&#x27;, &#x27;language&#x27;]
</code></pre>
While <code>str.split()</code> is highly useful for splitting strings with a single delimiter, it falls short when we need to split a string on multiple delimiters. For example, if we have a string with words separated by commas, semicolons, and/or spaces, <code>str.split()</code> cannot handle all these delimiters simultaneously.

 <div class="alert alert-reference">
 <div class="flex">
 
 <div class="flex-shrink-0 mr-3">
 <img src="/assets/images/icon-link-solid.svg" class="icon" aria-hidden="true" />
 </div>
 
 <div class="w-full">
 Advice: Reading our guide <a href="https://stackabuse.com/python-split-string-into-list-with-split/" target="_blank">&quot;Python: Split String into List with split()&quot;</a> will help you gain a deeper understanding of the <code>split()</code> method in Python.

 </div>
 </div>
 </div>
 In the upcoming sections, we will explore more sophisticated techniques for splitting strings based on multiple delimiters in Python.
<h3 id="usingregularexpressionstheresplitmethod">Using Regular Expressions - the re.split() Method</h3>
To tackle the issue of splitting a string on multiple delimiters, Python provides us with the <code>re</code> (Regular Expressions) module. Specifically, the <code>re.split()</code> function is an effective tool that allows us to split a string using multiple delimiters.
Regular expressions (or regex) are sequences of characters that define a search pattern. These are highly versatile, making them excellent for complex text processing tasks.
Consider the following string:
<pre><code class="hljs">text = &quot;Python;is,a powerful:language&quot;
</code></pre>
If you want to extract words from it, you must consider multiple delimiters. Let's take a look at how we can use <code>re.split()</code> to split a string based on multiple delimiters:
<pre><code class="hljs">import re

text = &quot;Python;is,a powerful:language&quot;
words = re.split(&#x27;;|,| &#x27;, text)
print(words)
</code></pre>
This will give us:
<pre><code class="hljs">[&#x27;Python&#x27;, &#x27;is&#x27;, &#x27;a&#x27;, &#x27;powerful&#x27;, &#x27;language&#x27;]
</code></pre>
We used the <code>re.split()</code> method to split the string at every occurrence of a semicolon (<code>;</code>), comma (<code>,</code>), or space (<code> </code>). The <code>|</code> symbol is used in regular expressions to mean &quot;or&quot;, so <code>;|,| </code>can be read as &quot;semicolon or comma or space&quot;.
This function demonstrates far greater versatility and power than <code>str.split()</code>, allowing us to easily split a string on multiple delimiters.

 <div class="alert alert-reference">
 <div class="flex">
 
 <div class="flex-shrink-0 mr-3">
 <img src="/assets/images/icon-link-solid.svg" class="icon" aria-hidden="true" />
 </div>
 
 <div class="w-full">
 Advice: You can find more about Python regular expressions in our <a href="https://stackabuse.com/introduction-to-regular-expressions-in-python/" target="_blank">&quot;Introduction to Regular Expressions in Python&quot;</a>.

 </div>
 </div>
 </div>
 In the next section, we'll take a look at another Pythonic way to split strings using multiple delimiters, leveraging the <code>translate()</code> and <code>maketrans()</code> methods.
<h3 id="usingtranslateandmaketransmethods">Using translate() and maketrans() Methods</h3>
Python's <code>str</code> class provides two powerful methods for character mapping and replacement: <code>maketrans()</code> and <code>translate()</code>. When used in combination, they offer an efficient way to replace multiple delimiters with a single common one, allowing us to use <code>str.split()</code> effectively.
The <code>maketrans()</code> method returns a translation table that can be used with the <code>translate()</code> method to replace specific characters. So, let's take a look at how to utilize those two methods to fit our needs.
First of all, we need to create a translation table that maps semicolons (<code>;</code>) and colons (<code>:</code>) to commas (<code>,</code>):
<pre><code class="hljs">text = &quot;Python;is,a powerful:language&quot;

# Create a translation table mapping &#x27;;&#x27; and &#x27;:&#x27; to &#x27;,&#x27;
table = text.maketrans(&quot;;:&quot;, &quot;,,&quot;)
</code></pre>
Then we use the <code>translate()</code> method to apply this table to our text. This replaces all semicolons and colons with commas:
<pre><code class="hljs"># Apply the translation table
text = text.translate(table)
</code></pre>
Finally, we can use <code>str.split(',')</code> to split the text into words and print extracted words:
<pre><code class="hljs"># Now we can split on the comma
words = text.split(&#x27;,&#x27;)
print(words)
</code></pre>
This will result in:
<pre><code class="hljs">[&#x27;Python&#x27;, &#x27;is&#x27;, &#x27;a powerful&#x27;, &#x27;language&#x27;]
</code></pre>

 <div class="alert alert-note">
 <div class="flex">
 
 <div class="flex-shrink-0 mr-3">
 <img src="/assets/images/icon-information-circle-solid.svg" class="icon" aria-hidden="true" />
 </div>
 
 <div class="w-full">
 Note: This approach is particularly useful when you want to standardize the delimiters in a string before splitting it.

 </div>
 </div>
 </div>
 In the next section, we'll explore how to utilize an external library, Pandas, for splitting strings on multiple delimiters.
<h3 id="leveragingthepandaslibrary">Leveraging the Pandas Library</h3>
Pandas, a powerful data manipulation library in Python, can also be used for splitting strings on multiple delimiters. Its <code>str.split()</code> function is capable of handling regex, making it another effective tool for this task.
While the built-in string methods are efficient for smaller data, when you're working with large datasets (like a DataFrame), using Pandas for string splitting can be a better choice. The syntax is also quite intuitive.
Here's how you can use Pandas to split a string on multiple delimiters:
<pre><code class="hljs">import pandas as pd

# Create a DataFrame
df = pd.DataFrame({&#x27;Text&#x27;: [&#x27;Python;is,a powerful:language&#x27;]})

# Use the str.split() function with a regex pattern
df = df[&#x27;Text&#x27;].str.split(&#x27;;|,|:&#x27;, expand=True)

print(df)
</code></pre>
This will give us:
<pre><code class="hljs">0 1 2 3 4
0 Python is a powerful language
</code></pre>
We first created a DataFrame with our text. We then used the <code>str.split()</code> function, passing in a regex pattern similar to what we used with <code>re.split()</code>. The <code>expand=True</code> argument makes the function return a DataFrame where each split string is a separate column.

 <div class="alert alert-note">
 <div class="flex">
 
 <div class="flex-shrink-0 mr-3">
 <img src="/assets/images/icon-information-circle-solid.svg" class="icon" aria-hidden="true" />
 </div>
 
 <div class="w-full">
 Note: Although this method returns a DataFrame instead of a list, it can be highly useful when you're already working within the Pandas ecosystem.

 </div>
 </div>
 </div>
 <h3 id="performancecomparison">Performance Comparison</h3>
When choosing a method to split strings on multiple delimiters, performance can be an important factor, especially when working with large datasets. Let's examine the performance of the methods we've discussed.
The built-in <code>str.split()</code> method is quite efficient for smaller data sets and a single delimiter, but its performance suffers when used with multiple delimiters and large datasets due to the necessary extra processing.
The <code>re.split()</code> method is versatile and relatively efficient, as it can handle multiple delimiters well. However, its performance might also degrade when dealing with huge amounts of data, because regular expressions can be computationally intensive.
Using <code>translate()</code> and <code>maketrans()</code> can be an efficient way to handle multiple delimiters, especially when you want to standardize the delimiters before splitting. However, it involves an extra step, which can affect performance with large datasets.
Finally, while the Pandas library offers a very efficient and flexible method to split strings on multiple delimiters, it might be overkill for simple, small tasks. The overhead of creating a DataFrame can affect performance when working with smaller data, but it excels in handling large datasets.
In conclusion, the best method to use depends on your specific use case. For small datasets and tasks, Python's built-in methods might be more suitable, while for larger, more complex data manipulation tasks, Pandas could be the way to go.
<h3 id="conclusion">Conclusion</h3>
String splitting, especially on multiple delimiters, is a common yet crucial operation in Python. It serves as the backbone in many text processing, data cleaning, and parsing tasks. As we've seen, Python provides a range of techniques for this task, each with its own strengths and weaknesses. From the built-in <code>str.split()</code>, to the versatile Regular Expressions, the character mapping <code>translate()</code> and <code>maketrans()</code> methods, and even the external Pandas library, Python offers solutions suitable for any complexity and size of data.
It's important to understand the different methods available and choose the one that best suits your specific requirements. Whether it's simplicity, versatility, or performance, Python's tools for string splitting can cater to various needs.
We hope this article helps you become more proficient in handling and manipulating strings in Python.

How to Split String on Multiple Delimiters in Python

<h3 id="introduction">Introduction</h3>
In programming, data often doesn't come in a neat, ready-to-use format. This is particularly true when we deal with strings, which often need to be cleaned, formatted, or manipulated in some way before they can be used effectively. One common issue we encounter is the presence of unwanted whitespaces - extra spaces, tabs, or newlines that can interfere with the way the string is processed or displayed.
Whitespace is like the &quot;empty space&quot; in our data. It might not seem like much, but in programming and data analysis, it can often lead to errors, incorrect results, or simply make data harder to read and analyze. That's why it's important to understand how to manage and control whitespaces in our strings.
<blockquote>
In this article, we will explore different techniques to remove whitespaces from strings in Python, including using built-in string methods like <code>strip()</code>, <code>replace()</code>, and <code>join()</code>, and also delve into more advanced concepts like regular expressions and list comprehensions.
</blockquote>
<h3 id="whitespacesinpython">Whitespaces in Python</h3>
In Python, and most other programming languages, whitespace refers to characters that are used for spacing and do not contain any printable glyphs. They include spaces (<code> </code>), tabs (<code>\t</code>), newlines (<code>\n</code>), and others. In Python strings, these characters can exist at the beginning, end, or anywhere within the string.
Consider the following example:
<pre><code class="hljs">str_with_whitespace = &#x27; Hello, World! &#x27;
</code></pre>
The string <code>' Hello, World! '</code> has leading and trailing whitespaces.
Although they might seem innocuous, these whitespaces can cause a variety of issues. For instance, they might interfere with string comparison operations or cause problems when trying to format your output neatly:
<pre><code class="hljs">print(&#x27; Hello, World! &#x27; == &#x27;Hello, World!&#x27;)
# Output: False
</code></pre>
Therefore, understanding how to remove or manipulate these whitespaces is a crucial aspect of handling strings in Python. In the following sections, we'll explore various methods and techniques to effectively remove these whitespaces from our Python strings.
<h3 id="waystoremovewhitespacesfromstringsinpython">Ways to Remove Whitespaces from Strings in Python</h3>
Python provides various ways to remove whitespaces from strings. We'll explore several methods, each with its own advantages and use cases.
<h4 id="usingstriprstripandlstripmethods">Using <code>strip()</code>, <code>rstrip()</code>, and <code>lstrip()</code> Methods</h4>
Python string method <code>strip()</code> removes leading and trailing whitespaces. If you only want to remove spaces from the left or right side, you can use <code>lstrip()</code> and <code>rstrip()</code>, respectively:
<pre><code class="hljs">str_with_whitespace = &#x27; Hello, World! &#x27;

# Using strip() method
print(str_with_whitespace.strip()) 
# Output: &#x27;Hello, World!&#x27;

# Using lstrip() method
print(str_with_whitespace.lstrip()) 
# Output: &#x27;Hello, World! &#x27;

# Using rstrip() method
print(str_with_whitespace.rstrip()) 
# Output: &#x27; Hello, World!&#x27;
</code></pre>

 <div class="alert alert-note">
 <div class="flex">
 
 <div class="flex-shrink-0 mr-3">
 <img src="/assets/images/icon-information-circle-solid.svg" class="icon" aria-hidden="true" />
 </div>
 
 <div class="w-full">
 Note: These methods do not remove whitespace that is in the middle of the string.

 </div>
 </div>
 </div>
 
 <div class="alert alert-reference">
 <div class="flex">
 
 <div class="flex-shrink-0 mr-3">
 <img src="/assets/images/icon-link-solid.svg" class="icon" aria-hidden="true" />
 </div>
 
 <div class="w-full">
 Advice: For a more comprehensive overview of the <code>strip()</code>, <code>rstrip()</code> and <code>lstrtip()</code> in Python, read our <a href="https://stackabuse.com/guide-to-pythons-strip-method/" target="_blank">&quot;Guide to Python's strip() Method&quot;</a>.

 </div>
 </div>
 </div>
 <h4 id="usingreplacemethod">Using <code>replace()</code> Method</h4>
The <code>replace()</code> method can be used to replace all occurrences of a substring. This can be used to remove all whitespaces in a string by replacing them with nothing.
<pre><code class="hljs">str_with_whitespace = &#x27; Hello, World! &#x27;

# Using replace() method
print(str_with_whitespace.replace(&#x27; &#x27;, &#x27;&#x27;)) 
# Output: &#x27;Hello,World!&#x27;
</code></pre>
This method removes all spaces, even those within the string.

 <div class="alert alert-reference">
 <div class="flex">
 
 <div class="flex-shrink-0 mr-3">
 <img src="/assets/images/icon-link-solid.svg" class="icon" aria-hidden="true" />
 </div>
 
 <div class="w-full">
 Advice: If you need a deeper understanding of the <code>replace()</code> method in Python, read our article <a href="https://stackabuse.com/replace-occurrences-of-a-substring-in-string-with-python/#replace" target="_blank">&quot;Replace Occurrences of a Substring in String with Python&quot;</a>.

 </div>
 </div>
 </div>
 <h4 id="usingregularexpressions">Using Regular Expressions</h4>
For more complex whitespace removal, we can use regular expressions via the <code>re</code> module in Python. This can be used to replace multiple consecutive whitespaces with a single space:
<pre><code class="hljs">import re

str_with_whitespace = &#x27; Hello, World! &#x27;

# Using re.sub() method
print(re.sub(&#x27;\s+&#x27;, &#x27; &#x27;, str_with_whitespace).strip()) 
# Output: &#x27;Hello, World!&#x27;
</code></pre>
Here, <code>re.sub('\s+', ' ', str_with_whitespace).strip()</code> replaces all consecutive whitespaces with a single space and then removes leading and trailing whitespaces.

 <div class="alert alert-reference">
 <div class="flex">
 
 <div class="flex-shrink-0 mr-3">
 <img src="/assets/images/icon-link-solid.svg" class="icon" aria-hidden="true" />
 </div>
 
 <div class="w-full">
 Advice: Read more about regular expressions in Python in <a href=" https://stackabuse.com/introduction-to-regular-expressions-in-python/" target="_blank">&quot;Introduction to Regular Expressions in Python&quot;</a>.

 </div>
 </div>
 </div>
 <h4 id="usinglistcomprehension">Using List Comprehension</h4>
List comprehensions provide a concise way to create lists based on existing lists. They can be used to remove all whitespaces in a string:
<pre><code class="hljs">str_with_whitespace = &#x27; Hello, World! &#x27;

# Using list comprehension
print(&#x27;&#x27;.join(char for char in str_with_whitespace if not char.isspace())) 
# Output: &#x27;Hello,World!&#x27;
</code></pre>
In this example, we created a new string by joining all non-whitespace characters.

 <div class="alert alert-reference">
 <div class="flex">
 
 <div class="flex-shrink-0 mr-3">
 <img src="/assets/images/icon-link-solid.svg" class="icon" aria-hidden="true" />
 </div>
 
 <div class="w-full">
 Advice: You can dive deeper into the concept of list comprehension in Python by reading our guide <a href="https://stackabuse.com/list-comprehensions-in-python/" target="_balnk">&quot;List Comprehension in Python&quot;</a>.

 </div>
 </div>
 </div>
 <h4 id="usingjoinandsplitmethods">Using <code>join()</code> and <code>split()</code> Methods</h4>
The <code>join()</code> and <code>split()</code> methods can be used together to remove all whitespaces in a string. <code>split()</code> splits the string into words, and <code>join()</code> joins them together without spaces:
<pre><code class="hljs">str_with_whitespace = &#x27; Hello, World! &#x27;

# Using join() and split() methods
print(&#x27; &#x27;.join(str_with_whitespace.split())) 
# Output: &#x27;Hello, World!&#x27;
</code></pre>
In this example, <code>' '.join(str_with_whitespace.split())</code> splits <code>str_with_whitespace</code> into words and joins them together with a single space.
<h3 id="conclusion">Conclusion</h3>
Throughout this article, we've explored a variety of methods to remove whitespaces from strings in Python, including using built-in string methods like <code>strip()</code>, <code>replace()</code>, and <code>join()</code>, as well as more advanced techniques involving regular expressions and list comprehensions.
While each method has its own advantages, the best one to use depends on your specific needs and the nature of the data you're working with. The key is to understand these different methods and know how to use them when needed.
To enhance your understanding and practice these methods, we encourage you to experiment with them. Try creating your own strings with various types of whitespaces and see how effectively you can remove them using the techniques discussed.

How to Remove Whitespaces from a String in Python

<h3 id="introduction">Introduction</h3>
In today's digital world, there is a vast amount of text data created and transferred in the form of news, tweets, and social media posts. Can you imagine the time and effort needed to process them manually? Fortunately, Natural Language Processing (NLP) techniques help us manipulate, analyze, and interpret text data quickly and efficiently. NLP is a branch of Artificial Intelligence, where we train machines to understand human language and perform tasks ranging from summarization and translation to sentiment analysis.
<blockquote>
One of the common requirements in NLP is dealing with singular and plural forms of words and converting one to another. In this article, we'll discuss how to perform pluralization and singularization of words using the Python package TextBlob.
</blockquote>
<h3 id="whatdosingularizationandpluralizationmean">What do singularization and pluralization mean?</h3>
We know nouns can be singular or plural, such as book/books, cat/cats, and sweet/sweets. We need techniques to convert text to plural/singular forms to help in data preprocessing and to achieve better accuracy in translation, text analysis, and text generation. This task of conversion from singular to plural and vice versa is referred to as word inflection in NLP.
Let's look at the common patterns/rules for converting singular to plural in the English language:
<ul>
<li>
Adding &quot;-s&quot; at the end: This is the most common pattern. For example, cot-&gt;cots, desk-&gt;desks, lake-&gt;lakes. Removing 's' is the rule followed for plural to singular conversion.
</li>
<li>
Adding &quot;-es&quot; at the end: This rule is usually followed for words ending in 's', 'x', 'z', 'ch', or 'sh' sounds. Examples: bus -&gt; buses, church-&gt; churches, brush-&gt; brushes.
</li>
<li>
Replacing &quot;-y&quot; with &quot;-ies&quot;: It is followed for nouns ending in a consonant along with a &quot;y&quot;. Examples: puppy -&gt; puppies, city -&gt; cities.
</li>
<li>
Irregular patterns: Some nouns do not follow any of the patterns mentioned above. For example, child-&gt;children, foot-&gt;feet, mouse-&gt;mice. Handling these can be a bit tricky.
</li>
</ul>
<h3 id="introductiontotextblobandinstallation">Introduction to TextBlob and Installation</h3>
The Python programming language provides a variety of packages that allow us to implement various tasks in NLP. One of the widely used packages is TextBlob, which offers functions to easily perform various NLP tasks, including singularization/pluralization. This library is built on top of NLTK (Natural Language Toolkit) and is easy to learn. You can check out the official <a rel="nofollow noopener" target="_blank" href="https://textblob.readthedocs.io/en/dev/">documentation</a> of TextBlob to learn about all the functions it offers.
Let's start by installing the library using the <code>pip</code> package manager by running the command below.
<pre><code class="hljs">$ pip install textblob
</code></pre>
Once the installation is complete, you can import the library into your Python notebook or script.
<pre><code class="hljs">from textblob import Word
</code></pre>
You can import the <code>Word</code> class from the module. When a text is passed in the form of a string to this class, a TextBlob Word object will be created, upon which various functions can be called to perform tokenization, word inflection, lemmatization, etc.
In the snippet below, we create a TextBlob object of the <code>Word</code> class 'doc1' by passing a text string.
<pre><code class="hljs">text = &quot;I usually take a bus from my university to the park.&quot;
doc1 = Word(text)
</code></pre>
In the next sections, we'll show how different functions can be used on the TextBlob class object to perform pluralization and singularization.
<h3 id="pluralizationwithtextblob">Pluralization with TextBlob</h3>
We can easily convert a noun from its singular to plural form using the <code>pluralize()</code> function in TextBlob. Let's look at how to get the plural form of 'puppy' in the example code below. Simply create a TextBlob object of the word, and call the function <code>pluralize()</code> on it.
<pre><code class="hljs">from textblob import Word
blob = Word(&quot;puppy&quot;)
pluralized_word = blob.pluralize()
print(pluralized_word)

# Output: puppies
</code></pre>
TextBlob can handle most of the common patterns of pluralization, including irregular ones. Let's check this out with a few more examples:
<pre><code class="hljs">plural_form = Word(&quot;box&quot;).pluralize() 
print(plural_form) # Output: boxes

plural_form = Word(&quot;man&quot;).pluralize() 
print(plural_form) # Output: men

plural_form = Word(&quot;tooth&quot;).pluralize() 
print(plural_form) # Output: teeth

plural_form = Word(&quot;ox&quot;).pluralize() 
print(plural_form) # Output: oxen
</code></pre>
From the above output, you can observe that TextBlob handles irregular patterns like ox-&gt;oxen and child-&gt;children as well.
Now, let us consider the word &quot;water.&quot; Can you convert it to plural? No! Words like water and furniture are referred to as uncountable nouns and remain unchanged between singular/plural forms. Fortunately, TextBlob is equipped to understand these cases and does not modify them.
<pre><code class="hljs"># Pluralization of Uncountable Nouns
plural_form = Word(&#x27;water&#x27;).pluralize() 
print(plural_form) # Output: water

plural_form = Word(&quot;information&quot;).pluralize() 
print(plural_form) # Output: information
</code></pre>
<h4 id="howtopluralizespecificwordsinasentence">How to Pluralize Specific Words in a Sentence?</h4>
Often, while dealing with text documents, you may want to modify particular words. Let's say a text is &quot;The container had multiple box filled with canned goods&quot;, and you wish to convert 'box' to 'boxes' to make it grammatically consistent. First, create a TextBlob object for the sentence. On this object, use the '<code>words()</code>' function to get a list of the words in the sentence. Now, you can use the index of these words to convert any of them into their plural form. Note that you also need to import the NLTK package to use the functions to extract the list of words, due to package dependency.
<pre><code class="hljs">import nltk
nltk.download(&#x27;punkt&#x27;)

from textblob import TextBlob

sentence = &quot;The container had multiple box filled with canned goods&quot;

# Create a TextBlob object
blob = TextBlob(sentence)

# Get the list of words in the sentence
words = blob.words

# Pluralize the 5th word
pluralized_word = words[4].pluralize()
</code></pre>
The modified sentence you get in the output would be:
<pre><code class="hljs"># Output: The container had multiple boxes filled with canned goods
</code></pre>
The output is as desired, with the changes made. This method can be used to singularize or pluralize all nouns in an entire text document too.
<h3 id="singularizationwithtextblob">Singularization with TextBlob</h3>
Converting a noun from its plural form to its singular form is known as singularization and is commonly used to obtain base words. To avoid redundancy while working with large text corpora, plural forms are often reduced to their root or singular form. It helps us standardize the text data and reduce the dimensionality of the vocabulary. Similar to pluralization, TextBlob also provides a built-in method <code>singularize()</code> to handle singularization.
As we did in the previous section, create a TextBlob class object for your word and call the <code>singularize()</code> method on it. This method can handle different rules of singularization, including irregular cases. I have demonstrated this with a diverse set of examples below.
<pre><code class="hljs"># Removing ‘s’
singular_form = Word(&quot;curtains&quot;).singularize() 
print(singular_form) # Output: curtain

# Removing ‘es’ 
singular_form = Word(&quot;mattresses&quot;).singularize() 
print(singular_form) # Output: mattress

# Changing internal vowel (&#x27;a&#x27; to &#x27;o&#x27;)
singular_form = Word(&quot;geese&quot;).singularize()
print(singular_form) # Output: goose

# Completely irregular form
singular_form = Word(&quot;mice&quot;).singularize()
print(singular_form) # Output: mouse
</code></pre>
<h4 id="howcanyousingularizeallnounsinyourdocument">How can you singularize all nouns in your document?</h4>
As we discussed at the beginning of this section, standardizing the nouns in the text is a common need in NLP. Let's say we have a paragraph in our document as shown below.
<pre><code class="hljs"># Define the paragraph
paragraph = &quot;The bookshop around the corner sells all genres of books, including fiction, non-fiction, autobiographies, and much more. The quality of the books is amazing, and they are all bestsellers. I recently bought the New York Times Bestseller Atomic Habits from there.&quot;
</code></pre>
If you notice, the words 'book' and 'books', 'bestseller' and 'bestsellers' are present in this. For contextual understanding in NLP, only the root word is essential. Hence, we can convert them into standard singular forms and reduce the size of our vocabulary. I'll now show you how to do this easily with TextBlob.
<pre><code class="hljs"># To extract nouns
nltk.download(&#x27;averaged_perceptron_tagger&#x27;)

# Create a TextBlob object
blob = TextBlob(paragraph)

# Extract nouns from the paragraph
nouns = [word.singularize() for word, tag in blob.tags if tag.startswith(&#x27;NN&#x27;)]

# Get unique singularized nouns
unique_nouns = set(nouns)
for noun in unique_nouns:
 print(noun)

# Output: [&#x27;fiction&#x27;, &#x27;corner&#x27;, &#x27;book&#x27;, &#x27;genre&#x27;, &#x27;quality&#x27;, &#x27;shop&#x27;, &#x27;habit&#x27;, &#x27;autobiography&#x27;]
</code></pre>
From the output, you can verify that every noun has been converted to its singular form (standardized)!
<h3 id="howtodefinecustomrulesforsingularizationpluralization">How to Define Custom Rules for Singularization &amp; Pluralization?</h3>
While TextBlob's built-in functions <code>singularize()</code> provide accurate results for most nouns in English, it isn't foolproof. I'll walk you through some common situations where TextBlob may not be able to handle the inflection.
Once you define these rules, TextBlob will remember them and automatically apply them when it encounters these specific words.
To help you understand better, I'll walk you through some common cases where setting custom rules may be necessary:
<ul>
<li>
Non-English Words: TextBlob's default rules are primarily designed for English words. If you encounter non-English words that follow different pluralization or singularization patterns, you may need to set custom rules. For example: Cactus -&gt; Cacti, Octopus -&gt; Octopi.
</li>
<li>
Domain-specific Terms: Certain domain-specific terms may have unique pluralization or singularization forms that are not covered by the default rules. Example: Virus -&gt; Viri, FAQ -&gt; FAQs (acronyms)
</li>
</ul>
What can we do in these cases?
You can use an alternative Python package called 'pattern' to easily define custom rules for word inflection. Import the <code>singularize</code> and <code>pluralize</code> functions from the <code>pattern.en</code> module. Next, we can define custom singularization and pluralization rules using dictionaries as shown below.
<pre><code class="hljs">#!pip install pattern
import pattern
from pattern.en import singularize, pluralize

custom_plural_rules = {&#x27;virus&#x27;: &#x27;viri&#x27;, &#x27;SAT&#x27;: &#x27;SATs&#x27;}

# Define functions for custom singularization and pluralization
def custom_plural(word):
 if word in custom_plural_rules:
 return custom_plural_rules[word]
 return pluralize(word)

# Example usage
print(custom_plural(&#x27;virus&#x27;)) # Output: Viri
</code></pre>
If the input word is present in the dictionary, our custom rules will be applied. Otherwise, the default rules will be used for conversion.
<h3 id="whenshouldyouchoosetextblobandwhy">When should you choose TextBlob and why?</h3>
One of the main advantages of TextBlob is its easy-to-use syntax and API, which makes it beginner-friendly. Apart from singularization/pluralization tasks, we can also perform a diverse set of tasks including part-of-speech tagging, noun phrase extraction, sentiment analysis, and more, as it comes with pre-trained models. It integrates seamlessly with other tools commonly used in the Python ecosystem, such as NLTK.
On the other hand, TextBlob may not be the best choice for large-scale text-processing tasks that are computationally intensive or when precise control is needed. In these cases, you can consider alternative packages such as <a target="_blank" href="/tag/spacy/">spaCy</a> and Stanford CoreNLP. spaCy provides robust capabilities for handling pluralization and singularization while dealing with large-scale text processing. You can check out the <a href="https://spacy.io/">spaCy documentation here</a>.
<h3 id="conclusion">Conclusion</h3>
The TextBlob library's built-in methods <code>pluralize()</code> and <code>singularize()</code> are efficient ways to perform word inflection tasks. These methods can handle the different patterns of singular/plural nouns in the English language. TextBlob can also handle most irregular patterns. These features and functionalities make TextBlob a great choice for word inflection tasks.
If you want to understand how to perform other NLP techniques in TextBlob, you can check these <a target="_blank" href="/tag/textblob/">articles</a>. Pattern is another useful package if you want to define custom rules of inflection for your domain-specific terms. You can evaluate TextBlob and its alternatives based on your performance needs. I hope you enjoyed the read!