Loupe…
- …only requires PHP and SQLite, you don't need anything else - no containers, no nothing
- …is typo-tolerant (based on the State Set Index Algorithm and Damerau-Levenshtein)
- …supports phrase search using
"
quotation marks - …supports negative keyword and phrase search using
-
as modifier - …supports filtering (and ordering) on any attribute with any SQL-inspired filter statement
- …supports filtering (and ordering) on Geo distance
- …orders relevance based on a number of factors such as number of matching terms, typos, proximity, word counts and exactness
- …auto-detects languages
- …supports stemming
- …is very easy to use
- …is all-in-all just the easiest way to replace your good old SQL
LIKE %...%
queries with a way better search experience but without all the hassle of an additional service to manage. SQLite is everywhere and all it needs is your filesystem.
If this is your first encounter with Loupe, you might want to read the blog post on Medium or as Markdown file that should give you more information about the reasons and what you can do with it. Note that some implementation details (e.g. libraries used) referenced in this blog post are not up-to-date anymore.
Performance depends on many factors but here are some ballpark numbers based on indexing the ~32k movies fixture provided by MeiliSearch.
- Indexing will take a little over 90 seconds (~350 documents per second)
- Querying for
Amakin Dkywalker
with typo tolerance and relevance ranking takes about 100 ms
Note that anything above 50k documents is probably not a use case for Loupe. You can run your own benchmarks
using the scripts in the bin/bench
folder: index.php
for indexing and search.php
for searching.
Please, also read the Performance chapter in the docs. You may report your own performance
measurements and more details in the respective discussion.
If you are familiar with MeiliSearch, you will notice that the API is very much inspired by it. The reasons for this are simple:
- First and foremost: I think, they did an amazing job of keeping configuration simple and understandable from a developer's perspective. Basic search tools shouldn't be complicated.
- If Loupe shouldn't be enough for your use case anymore (you need advanced features, better performance etc.), switching to MeiliSearch instead should be a piece of cake.
I even took the liberty to copy some of their test data to feed Loupe for functional tests.
- Make sure you have
pdo_sqlite
available and your installed SQLite version is at least 3.16.0. This is when PRAGMA functions have been added without which no schema comparisons are possible. For best performance it is of course better to run a more recent version to benefit from improvements within SQLite. - Run
composer require loupe/loupe
.
The first step is configuring and creating a client.
use Loupe\Loupe\Config\TypoTolerance;
use Loupe\Loupe\Configuration;
use Loupe\Loupe\LoupeFactory;
use Loupe\Loupe\SearchParameters;
$configuration = Configuration::create()
->withPrimaryKey('uuid') // optional, by default it's 'id'
->withSearchableAttributes(['firstname', 'lastname']) // optional, by default it's ['*'] - everything is indexed
->withFilterableAttributes(['departments', 'age'])
->withSortableAttributes(['lastname'])
->withTypoTolerance(TypoTolerance::create()->withFirstCharTypoCountsDouble(false)) // can be further fine-tuned but is enabled by default
;
$loupe = (new LoupeFactory())->create('path/to/my_loupe_data_dir', $configuration);
To create an in-memory search client:
$loupe = (new LoupeFactory())->createInMemory($configuration);
$loupe->addDocuments([
[
'uuid' => 2,
'firstname' => 'Uta',
'lastname' => 'Koertig',
'departments' => [
'Development',
'Backoffice',
],
'age' => 29,
],
[
'uuid' => 6,
'firstname' => 'Huckleberry',
'lastname' => 'Finn',
'departments' => [
'Backoffice',
],
'age' => 18,
],
]);
$searchParameters = SearchParameters::create()
->withQuery('Gucleberry')
->withAttributesToRetrieve(['uuid', 'firstname'])
->withFilter("(departments = 'Backoffice' OR departments = 'Project Management') AND age > 17")
->withSort(['lastname:asc'])
;
$results = $loupe->search($searchParameters);
foreach ($results->getHits() as $hit) {
echo $hit['title'] . PHP_EOL;
}
The $results
array contains a list of search hits and metadata about the query.
print_r($results->toArray());
[
'hits' => [
[
'uuid' => 6,
'firstname' => 'Huckleberry'
]
],
'query' => 'Gucleberry',
'processingTimeMs' => 4,
'hitsPerPage' => 20,
'page' => 1,
'totalPages' => 1,
'totalHits' => 1
]
"Why Loupe?" you ask? "Loupe" means "magnifier" in French and I felt like this was the appropriate choice for this library after having given my PHP crawler library a French name :-)