How to Get the Length of a String in Python


How to Get the Length of a String in Python

How to Get the Length of a String in Python


Regarding Python programming, one of the most significant yet crucial tasks is tracking down the length of a string. This indispensable responsibility serves as a configuration block for supplementary, perplexing tasks.

The string is one of the datatypes in Python
The string is one of the datatypes in Python
  • The string is one of the datatypes in Python

A string is a sequence of characters. In Python, strings can be created by enclosing the character or the sequence of characters in the quotes.

Python allows us to use single, double, or triple quotes to create a string.

  • What is the length of a string?

In the field of programming, understanding how to control and look at data is critical. One typical action is tracking down the length of a string. In Python, this chore is made easy with the len() function.

  • Defining String Length

 Deliberately determining the length of a string is vigorous in different situations. It authorizes you to:

  • Validate the input data.
  • Allocate memory efficiently.
  • Control the flow of your program based on the length of the text.
  • Perform operations that depend on the size of the string.

Built-in Function: len

The clearest technique to find the length of a string in Python is by applying the causal capability len. This capability generates the quant-number characters in the given string, including spaces and unusual characters.

  • Understanding the len function

The len() capability takes a solitary argument, which has to be the string you need to compute. It comprises each person in the string and returns an all-out number.

  • Examples of len () in Action

Example How to Get the Length of a String in Python
Example How to Get the Length of a String in Python

How about we connote this with a model?


Copy code

String model = “Hi, World!”

Length = len (string example)

Print (The length of the string is: {length}”

In this case, the output will be:


Copy code

The length of the string is: 13

Given two strings, s1 and s2, find out if s1 is a substring of s2. If yes, return the index of the first occurrence; otherwise, return -1.

Examples :

Input: s1 = “for”, s2 = “geeks for geeks.”

Output: 5


The string “for” is present as a substring

of s2.

Input: s1 = “practice”, s2 = “geeks for geeks.”

Output: -1.


There is no occurrence of “practice” in

“geeks for geeks”

  • Simple Approach

The idea is to run a loop from start to end, and for every index in the given string,  check whether the sub-string can be formed from that index. This can be done by running a nested loop traversing the given string and, in that loop, running another loop checking for sub-strings from every index.

For example, consider there to be a string of length N and a substring of length M. Then run a nested loop, where the outer loop runs from 0 to (N-M) and the inner loop from 0 to M. For every index, check if the sub-string traversed by the inner loop is the given sub-string or not.




# Python3 program to check if

A string is a substring of another.

# Returns true if s1 is substring of s2

def substring(s1, s2):

 M = len(s1)

 N = len(s2)

 # A loop to slide pats one by one

 for i in range(N – M + 1):

 # For a current indexCheck,

 # check for pattern match

 for j in range(M):

 if (s2[i +!= s1[j]):


 if j + 1 == M:

 return i

 return -1

# Driver Code

if __name__ == “__main__”:

 s1 = “for”

 s2 = “geeks for geeks”

 res = isSubstring(s1, s2)

 if res == -1:

 print(“Not present”)


 print(“Present at index ” + str(res))


Present at index 5

One more way to determine the length of a string is by repeating the characters and keeping a count.

  • Using a Circle for Length

You can maneuver a circle to cross each person and keep a count fickle.

Test Code for Emphasis

Here is a model:


Duplicate code

String model = “Hi, World!”

Count = 0

For the single-in-string model:

   Count += 1

Pattern: (The length of the string is: {count}”



Duplicate code

The length of the string is: 13

Three ways:

Use the ‘in’ operator: ‘world’ in ‘Hello World’ for example

Use the find() method: ‘Hello World’.  find(‘or’): This returns the index of the sub-string in the main string; this returns -1 when the sub-string isn’t in the main string.

Use the count() method ‘Hello World’.  count(‘or’): This returns how often the sub-string is contained in the main string; it returns 0 if the sub-string isn’t in the main string.

Using either find() or count() just to test whether a substring is contained in a main string is not good practice, but it can be done if you are planning to use the information they are providing for other reasons.

So, for example, do this:

if substring in mainspring:

       index = mainstring.find(substring)

       after = maintstring[index+len(substring):]

It is poor practice; it would be better to do this:

index = mainstring.find(substring)

If index! = -1:

       After = mainspring [index+len(substring)]

Stack Flood, a well-known instinctive area for software engineers, persistently provides momentous knowledge with planned procedures. We should examine what the local area is for tracking down string lengths in Python.

  • The Stack Flood People Group

Stack Flood has a gigantic local area of experienced designers who subsidize their insight through questions and replies. 

  • Master Suggestions

In nimble Stack Flood conversations, the most recommended technique for finding string lengths is consuming the len () capability because of its effortlessness and capacity.

  • Normal Entanglements to Keep Away from

While using len() is clear, it’s imperative to ensure that you’re passing an important string as an argument.

Dealing with edge cases is vital to avoiding unforeseen outcomes.

  • String Techniques

Aside from the len() capability, Python offers different techniques to work with strings.

  • Utilizing the .len () Technique

Strings in Python have a __len__() technique that can be applied to track down their length.

What are some ways to check if a string starts with another string in Python?

The best way is to use the start() string function. That’s literally what it’s for.

>>> string = ‘abcdefghijklmnopqrstuvwxyz’

>>> prefix = ‘ABC’

>>> string.starts with(prefix)


>>> string.starts with(‘nope’)


Moreover, different string strategies can, by implication, help in deciding the length of a string.

  • Dealing with Edge Cases

It’s spirited to consider edge situations while working with string lengths.

  • Void Strings

If you pass an unfilled string to len(), it will return 0, as there are no characters to count.

  • Unicode Characters

Python grips Unicode characters flawlessly, so you can utilize len() to get the length of strings covering them.

  • Unique Characters

Unique characters are counted very much like some other person in a string.

  • Execution Contemplations

While supervising colossal datasets, execution turns into a critical variable.

  • Time Intricacy of Length Tasks

The len() capability has a period intricacy of O(1), and that implies it works in steady time no matter what the size of the string.

  • Picking the Right Methodology

Consider the size and complexity of your information while picking a strategy for tracking down string lengths.

  • Elective Methodologies

While Len is the sketchily acknowledged approach, there are options worth investigating.

  • Ordinary Articulations

Ordinary articulations can be utilized to track down designs in strings, including length.

  • Custom Counting Capabilities

You can make custom capabilities customized to your specific necessities.

Best Practices for String Length Recovery
Best Practices for String Length Recovery

To constitute productive and understandable code, think about the accompanying prescribed procedures:

  • Code Comprehensibility

Elite is the technique that makes your code generally comprehensible and justifiable to other people.

  • Blunder: Taking care of

Constantly expect probable blunders and carry out suitable mistakes when dealing with systems.

  • Documentation

Give clear documentation to your code, particularly on the off chance that you’re involving a rare line of attack for tracking down string lengths.

  • Local area Input

Gaining from the experience of others is momentous.

  • Gaining from Stack Flood Conversations

Investigate significant Stack Flood conversations to obtain bits of knowledge from qualified engineers.

  • Embracing Industry Best Practices

Assimilate suggested rehearsals into your code for ideal outcomes.

  • Looking at Techniques

Every scheme has its assets and limitations.

  • Proficiency and Exactness

Evaluate the proficiency and exactness of every strategy for the purpose of your particular use case.

  • Picking the Right Methodology

Reflect on the idea of your information and the ideal result while choosing a strategy.

To increase your capability in acquiring string lengths, think about the accompanying tips:

Keep away from hardcoding values: Instead of hardcoding explicit string lengths, practice techniques like len () to more and more ascertain them. This guarantees your code stays easygoing and resourceful for countless information sources.

Handle Invalid or None Qualities: Before applying any length to looking at strategies, guarantee that the string isn’t invalid or none. Abandoning to do so may cause bumbles or an alarming approach to acting.

Contemplate Multiline Strings: While overseeing multiline strings, know that newline characters (‘\n’) think about a single individual.

  • Consider this while working out lengths

Investigate String Cutting: Python’s string cutting capacities can be utilized related to length recapture to extricate explicit segments of a string. Understanding cutting can open up additional chances for text control.

Benchmarking and Profiling: In the implementation of basic applications, consider benchmarking various strategies to decide the most productive methodology for your particular use case. Profiling instruments can provide significant insights into code execution times.

Standard Articulation Enhancement: If you decide to involve normal articulations for string length recovery, investigate progressed strategies for streamlining and calibrating your patterns. This can incite basic execution updates.

Keep Code Intelligible and Reasonable: While competency is huge, it shouldn’t come to the damage of code significance. Ensure that your code is clear, unquestionable, and follows best practices to work with joint effort and future upkeep.

Python’s malleability and wide standard library make it a compact language for various applications. Whether you’re working with text taking care of, data assessment, web progression, or sensible enrolling, Python gives irresistible contraptions and libraries to streamline your work sequence.

By performing weighty exercises like string length recuperation, you’ll be more ready to deal with additional staggering endeavors and create complex applications.

String Control Strategies: Plunge further into string control capabilities and techniques. Discover activities like connection, cutting, and designing, and that’s only the tip of the iceberg. These abilities will be inestimable in taking care of complicated text-handling errands.

Standard Articulations Dominance: Normal articulations are an incredible asset for design matching in strings. Focus profoundly on understanding and dominating the linguistic structure and capacities of normal expressions. This ability will exhibit importance in activities like data extraction, endorsement, and change.

Working with Text Records: Sort out some way to analyze and stay in contact with text archives in Python. This is a vital skill for dealing with colossal volumes of text data, for instance, logs, CSV reports, and anything possible from that point.

Data Plans and Computations: Investigate head data structures like records, word references, and sets, as well as estimations for tasks like orchestrating, looking, and cycling. These thoughts erection the underpinnings of viable programming.

Object-Situated Programming (OOP): Figure out the standards of OOP and how they apply in Python. This worldview is ideal for building mind-boggling, measured, and feasible applications.

Web Scratching and Computerization: Examine libraries like Wonderful Soup and Demands for Web Scratching. This permits you to eliminate information from sites and computerize errands, opening up a large number of potential outcomes.

Information Science and Examination: Supposing that you’re keen on information science, look into libraries like Pandas, NumPy, and Matplotlib for information control, investigation, and perception.

Web Improvement with Django or Carafe: Think through learning web systems like Django or Cup to construct dynamic web applications. This can open up astonishing doors to web improvement.

AI and man-made brainpower: Python has rich surroundings for AI and computer-based intelligence, with libraries like Tensor Stream, Keras, and sci-unit learning length. Dive into this field on the off chance that you’re ardent about information-driven applications.

Adding to Open Source Tasks: Joining open-source projects allows you to chip away at genuine world codebases, team up with experienced engineers, and make significant commitments to the local area.


In summary, receiving the length of a string in Python is a leading activity with plentiful approaches.

The basic line () ability is the most generally used formula due to its straightforwardness and feasibility. Anyway, being familiar with elective courses and best practices for dealing with different circumstances is fundamental.

By investigating Stack Flood conversations and neighborhoods, we’ve acquired huge snippets of data that lean toward strategies and consistent catches to stay away from.

Try to consider edge cases, for instance, void strings and Unicode characters, while working with string lengths. In terms of execution, the time complexity of lengthy undertakings is consistent, making it a strong choice for most conditions.

By the way, evaluating the idea of your information and the ideal result is vital in picking the most suitable methodology. Assimilating these practices into your Python programming won’t just assist you with proficiently finding string lengths; in addition, it will subsidize composing perfect, clear, and successful code.


Q1: Can I use len() on non-string objects?

Indeed, Len () can be utilized on different information structures, not simply strings. For instance, it can return the number of mechanisms in a rundown.

Q2: How would I contract with strings in several dialects?

Python handles strings from different languages, including those with non-Latin characters, without any issues.

Q3: Are there any performance differences between methods?

While Len is usually well organized, certain methods may be more suitable for specific scenarios. Always consider the context of your code.

Q4: What if my string contains special characters?

Special characters are counted the same way as regular characters in a string.

Q5: Might I at any point utilize these strategies on records or different information structures?

A few strategies inspected may apply to records or different information structures, yet being sympathetic to the unique situation and impairments of every method is fundamental.

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