Autocomplete

HTTP service for fuzzy search /autocomplete of English words.

Developed and tested in python3 environment.

Installation

git clone https://github.com/souvikmaji/autocomplete.git

cd autocomplete

make init

Run Instruction

make run

HTML View

Visit: http://127.0.0.1:8000/

API Usage

GET /search?word=input

Where input is the (partial) word that the user has typed so far.

For example, if the user is lookingup procrastination, the service might receive this sequence of requests:

GET /search?word=pro
GET /search?word=procr
GET /search?word=procra

and so on.

The response should be a JSON array containing upto 25 results, ranked by some criteria (seebelow).

Constraints

1. Matches can occur anywhere in the string, not just at the beginning. For example, eryxshould 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 thestart of a word should be ranked higher. For example, for the input pract, the resultpractical should be ranked higher than impractical.

   b. Common words (those with a higher usage count) should rank higher than rarewords.

   c. Short words should rank higher than long words. For example, given the inputenviron, the result environment should rank higher than environmentalism.i.As a corollary to the above, an ​exact match​ should always be ranked as thefirst result.

3. The search algorithm you develop should ideally incorporate some form of a weightedaverage of all qualifying parameters. The perfect weights, in production systems, arehowever derived through the use of ML algorithms.

TODO

• POC fuzzy search. Test performance with fuzzywuzzy.
• select2 based autocomplete
• django autocomplete light?
• makefile
• requirements.txt file
• unit tests
• static analyzer
• Hosting (Heroku).