Turkish Spell Checker

This tool is a spelling checker for Modern Turkish. It detects spelling errors and corrects them appropriately, through its list of misspellings and matching to the Turkish dictionary.

Video Lectures

For Developers

You can also see Cython, Java, C++, C, Swift, Js, or C# repository.

Python

To check if you have a compatible version of Python installed, use the following command:

python -V

You can find the latest version of Python here.

Git

Install the latest version of Git.

Pip Install

pip3 install NlpToolkit-SpellChecker

Download Code

In order to work on code, create a fork from GitHub page. Use Git for cloning the code to your local or below line for Ubuntu:

git clone <your-fork-git-link>

A directory called SpellChecker will be created. Or you can use below link for exploring the code:

git clone https://github.com/starlangsoftware/TurkishSpellChecker-Py.git

Open project with Pycharm IDE

Steps for opening the cloned project:

Start IDE
Select File | Open from main menu
Choose DataStructure-PY file
Select open as project option
Couple of seconds, project will be downloaded.

Detailed Description

Creating SpellChecker
Spell Correction

Creating SpellChecker

SpellChecker finds spelling errors and corrects them in Turkish. There are two types of spell checker available:

SimpleSpellChecker

To instantiate this, a FsmMorphologicalAnalyzer is needed.

  fsm = FsmMorphologicalAnalyzer()
  spellChecker = SimpleSpellChecker(fsm)

NGramSpellChecker,
- To create an instance of this, both a FsmMorphologicalAnalyzer and a NGram is required.
- FsmMorphologicalAnalyzer can be instantiated as follows:
```
  fsm = FsmMorphologicalAnalyzer()
```
- NGram can be either trained from scratch or loaded from an existing model.
  - Training from scratch:
```
  corpus = Corpus("corpus.txt");
  ngram = NGram(corpus.getAllWordsAsArrayList(), 1)
  ngram.calculateNGramProbabilities(LaplaceSmoothing())
```
  There are many smoothing methods available. For other smoothing methods, check here.
  - Loading from an existing model:
```
  ngram = NGram("ngram.txt")
```
For further details, please check here.
- Afterwards, NGramSpellChecker can be created as below:
```
  spellChecker = NGramSpellChecker(fsm, ngram)
```

Spell Correction

Spell correction can be done as follows:

sentence = Sentence("Dıktor olaç yazdı")
corrected = spellChecker.spellCheck(sentence)
print(corrected)

Output:

Doktor ilaç yazdı

Metadata

Release files for nlptoolkit-spellchecker 1.0.28

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for nlptoolkit-spellchecker 1.0.28
File	Size	Uploaded
nlptoolkit_spellchecker-1.0.28.tar.gz	28.1 kB	Apr 29, 2026	Details

Release files / nlptoolkit_spellchecker-1.0.28.tar.gz

Download URL	nlptoolkit_spellchecker-1.0.28.tar.gz
Size	28.1 kB
Tags	Source
SHA-256 checksum How to use checksums	`14b83568ea0d90b0d5b47cf79f983168898e2c928575dcea1bff7ae7c0f1265a`
BLAKE2b-256 checksum How to use checksums	`c3f006341e90c82cb793233b97de818a45dc00fb1ff22dc34c73216c23b16f69`
Upload date	Apr 29, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/4.0.2 CPython/3.7.8`