Indicium Search
🔎 A simple in-memory search for collections (Vec, HashMap, BTreeMap, etc) and key-value stores. Features autocompletion.
There are many incredible search engines available for Rust. Many seem to
require compiling a separate server binary. I wanted something simple and
light-weight - an easy-to-use crate that could conveniently search structs and
collections within my own binary. So, I made indicium.

While indicium was made with web apps in mind, it is an in-memory search and
it does not scale indefinitely or to Facebook or Google size. Even in such an
environment, it would still be a convenient way of searching large static lists
(such as currencies, languages, countries, etc.) It's also great for
applications where there is an anticipated scale limit (i.e. searching a list of
company assets, list of users in a corporate intranet, etc.)
Indicium easily can handle 10,000's records without breaking a sweat. This crate is primarily limited by available memory. However, depending on the nature your data-set and if there keywords that are repeated many times, performance may begin to degrade at a point.
Quick Start Guide
For our Quick Start Guide example, we will be searching inside of the
following struct:
1. Implementing Indexable
To begin, we must make our record indexable. We'll do this by implementing the
Indexable trait for our struct. The idea is to return a String for every
field that we would like to be indexed. Example:
use Indexable;
Don't forget that you may make numbers, numeric identifiers, enums, and other
types indexable by converting them to a String and including them in the
returned Vec<String>.
2. Indexing a Collection
To index an existing collection, we can iterate over the collection. For each record, we will insert it into the search index. This should look something like these two examples:
Vec
use SearchIndex;
let my_vec: = Vecnew;
// In the case of a `Vec` collection, we use the index as our key. A
// `Vec` index is a `usize` type. Therefore we will instantiate
// `SearchIndex` as `SearchIndex<usize>`.
let mut search_index: = default;
my_vec
.iter
.enumerate
.for_each;
HashMap
use HashMap;
use SearchIndex;
let my_hash_map: = new;
// In the case of a `HashMap` collection, we use the hash map's key as
// the `SearchIndex` key. In our hypothetical example, we will use
// MyStruct's `title` as a the key which is a `String` type. Therefore
// we will instantiate `HashMap<K, V>` as HashMap<String, MyStruct> and
// `SearchIndex<K>` as `SearchIndex<String>`.
let mut search_index: = default;
my_hash_map
.iter
.for_each;
As long as the Indexable trait was implemented for your value type, the above
examples will index a previously populated Vec or HashMap. However, the
preferred method for large collections is to insert into the SearchIndex as
you insert into your collection (Vec, HashMap, etc.)
Once the index has been populated, you can use the search and autocomplete
methods.
3. Searching
The search method will return keys as the search results. Each resulting
key can then be used to retrieve the full record from its collection.
Basic usage:
let mut search_index: = default;
search_index.insert;
search_index.insert;
search_index.insert;
search_index.insert;
search_index.insert;
let resulting_keys: = search_index.search;
assert_eq!;
Search only supports exact keyword matches and does not use fuzzy matching.
Consider providing the autocomplete feature to your users as an ergonomic
alternative to fuzzy matching.
5. Autocompletion
The autocomplete method will provide several autocompletion options for the
last keyword in the supplied string.
Basic usage:
let mut search_index: =
default
.autocomplete_type
.build;
search_index.insert;
search_index.insert;
search_index.insert;
search_index.insert;
search_index.insert;
search_index.insert;
search_index.insert;
let autocomplete_options: =
search_index.autocomplete;
assert_eq!;