Since support for full-text search is not standardized like relational database are, there are several open-source full-text engines. Examples include Sphinx, Apache Solr, Elasticsearch among others. Thankfully, all these engines can work within a Flask application due to the fact that Flask is not opinionated. Using search capabilities of one of the relational databases would be great but since SQLAlchemy does not support this functionality, we will have to content with learning how to handle the searching with raw SQL statement.
We can intentionally choose to use any of the full-text search engines to do the job for us. I will show you how you can install Elasticsearch and perform basic searches.
You probably are aware that pip allows us to install Python packages, and, therefore, it would make so much obvious sense to simply install elasticsearch by running:
(venv)$ pip3 install elasticsearch
We can test out the service by performing basic operations in a Python interpreter:
$ python3 # ... >>> from elasticsearch import Elasticsearch >>> es = Elasticsearch('http://localhost:9200')
We have created an instance of the class Elasticsearch and passed a connection URL to connect to the service. Since data in Elasticsearch is written in indexes, let us try to make one.
>>> es.index(index='test_index', id=1, body={'test': 'this is the first test'})
Elasticsearch works with data in JSON format. We have written an object with the field text to an index called test_index. When you press Enter on your keyboard, you will get a ConnectionError. Your attempts to connect to the service fails.
pip3 install elasticsearch only installs a Python client which is used for communication between your Python script and the existing Elasticsearch cluster. The assumption is that the cluster is currently running on localhost with the default elasticsearch port 9200.
There are a couple of steps we need to follow to ensure that we have configured our machine to run Elasticsearch:
ElasticsearchElasticsearchElasticsearch serviceSince Elasticsearch runs on top of Java, you need to install the Java Development Kit (JDK). You can check if Java is installed by running this command in your terminal:
$ java -version
If you do not have java, you can install the default JDK by:
$ sudo apt install openjdk-8-jre-headless
Run java --version to check that Java is installed.
Then next step would be to allow access to our repositories via HTTPS. Therefore, let us install an APT transport package:
$ sudo apt install apt-transport-https
ElasticsearchFirst, update the GPG Key for the Elasticsearch repository using the wget command to pull the public key:
$ wget -qO - https://artifacts.elastic.co/GPG-KEY-elasticsearch | sudo apt-key add -
Add the repository to your system:
(venv)$ echo "deb https://artifacts.elastic.co/packages/7.x/apt stable main" | sudo tee -a /etc/apt/sources.list.d/elastic-7.x.list
Now, install elasticsearch by first updating the package index then run the installation:
$ sudo apt update $ sudo apt install elasticsearch
Elasticsearch does not run until you start it. Also, when you reboot your machine, you need to rerun the elasticsearch service since it does not start automatically.
To reload the systemd configuration, run:
$ sudo systemctl daemon-reload
Enable the elasticsearch service:
$ sudo systemctl enable elasticsearch.service
Now, you can start elasticsearch:
$ sudo systemctl start elasticsearch.service
At this point, elasticsearch will start everytime you reboot your system. To test your set up and installation, run this command on your terminal:
(venv)$ curl localhost:9200
You should be able to see JSON formatted data displayed in your terminal. Alternatively, paste http://localhost:9200/ to your browser’s address bar. JSON data will be dumped on your screen.
Create a virtual environment and install elasticsearch in this environment:
$ mkvirtualenv test (test)$ pip3 install elasticsearch
Start your interpreter:
(test)$ python3 # ... >>> from elasticsearch import Elasticsearch >>> es = Elasticsearch('http://localhost:9200') >>> es.index(index='test_index', id=1, body={'test': 'this is the first test'}) # Output {'_index': 'my_index', '_type': '_doc', '_id': '1', '_version': 2, 'result': 'updated', '_shards': {'total': 2, 'successful': 1, 'failed': 0}, '_seq_no': 1, '_primary_term': 1}