Google instant like autocompletion for a 200000+ words dataset using suffix tree,

App provides an api endpoint at 0.0.0.0:8000/search?word=< word to match> It returns top 25 matching results e.g 0.0.0.0:8000/search?word=proc will return 25 results matching proc according to conditions given below

Words are ranked as follows

1.Matches can occur anywhere in the string, not just at the beginning. For example, eryx should match archaeopteryx (among others).

2. The ranking of results should satisfy the following: a. We assume that the user is typing the beginning of the word. Thus, matches at the start of a word should be ranked higher. For example, for the input pract, the result practical should be ranked higher than impractical. b. Common words (those with a higher usage count) should rank higher than rare words. c. Short words should rank higher than long words. For example, given the input environ, the result environment should rank higher than environmentalism.

3. As a corollary to the above, an exact match should always be ranked as the first result.

Project uses unoptimised version of Suffix-Tree, hence data in memory gets really large. You can modify the MAX variable in fastlookup/fastlookup/backend/constants.py to how much of the words you want to include, Since this program is resource heavy, if you have <4GB RAM keep it <200000, otherwise you system may hang

A computer with 8GB Ram is IDEAL for this project

python3.6 minimum 4GB RAM pipenv

python3.6 -m pip install pipenv
git clone https://github.com/mahto56/fastlookup.git
cd fastlookup/
pipenv install
pipenv shell
cd fastlookup
python manage.py runserver 0.0.0.0:8000

Goto 0.0.0.0:8000

or

Goto 0.0.0.0:8000/search?word=proc