This repository contains a high-level encapsulation for using Elasticsearch with python in just a few lines.
Via pip:
pip install easy-elasticsearchVia git repo:
git clone https://github.com/kwang2049/easy-elasticsearch
pip install -e . To utilize the elasticsearch service, one can select from 3 ways:
- (1) Start an ES service manually and then indicate the
hostandport_http(please refere to download_and_run.sh); - (2) Or leave
host=Noneby default to start a docker container itself; - (3) Or leava
host=Noneand settingservice_type=executableto download an ES executable and start it in the back end.
Finally, just either call its rank or score function for retrieval or calculating BM25 scores.
from easy_elasticsearch import ElasticSearchBM25
pool = {
'id1': 'What is Python? Is it a programming language',
'id2': 'Which Python version is the best?',
'id3': 'Using easy-elasticsearch in Python is really convenient!'
}
bm25 = ElasticSearchBM25(pool, port_http='9222', port_tcp='9333') # By default, when `host=None` and `mode="docker"`, a ES docker container will be started at localhost.
query = "What is Python?"
rank = bm25.query(query, topk=10) # topk should be <= 10000
scores = bm25.score(query, document_ids=['id2', 'id3'])
print(query, rank, scores)
bm25.delete_index() # delete the one-trial index named 'one_trial'
bm25.delete_container() # remove the docker container'Another example for retrieving Quora questions can be found in easy_elasticsearch/examples/quora.py:
python -m easy_elasticsearch.examples.quora --mode dockeror
python -m easy_elasticsearch.examples.quora --mode executable
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