nl2query 0.1.2

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nl2query

Convert natural language text inputs to Pandas, MongoDB, Kusto, and Cypher(Neo4j) queries. The models used are fine-tuned versions of CodeT5+ 220m models.

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Getting started

You can get nl2query from PyPI, using

python -m pip install nl2query

Example usage

1. Pandas Query

Suppose you want to convert the textual question to pandas query, follow the code below

from nl2query import PandasQuery

titanic = pd.read_csv('/path/titanic.csv')
queryfier = PandasQuery(titanic, 'titanic')

queryfier.generate_query('''list all people who paid more fare than the fare paid by 'Braund, Mr. Owen Harris' ''')
queryfier.generate_query('''find the names of passengers with age greater than 35 and containing Heath in their name''')
queryfier.generate_query('''which cabinet has average age less than 21?''') #Groupby Query

2. MongoDB Query

Suppose you want to convert the textual question to Mongo query, follow the code below

from nl2query import MongoQuery
import pymongo # import if performing analysis using python client
keys = ['_id', 'index', 'passengerid', 'survived', 'Pclass', 'name', 'sex', 'age', 'sibsp', 'parch', 'ticket', 'fare', 'cabin', 'embarked'] #keys present in the collection to be queries.
queryfier = MongoQuery(keys, 'titanic')
queryfier.generate_query('''which pclass has the minimum average fare?''')

keys = ['_id', 'index', 'total_bill', 'tip', 'sex', 'smoker', 'day', 'time', 'size'] 
queryfier = MongoQuery(keys, 'tips')
queryfier.generate_query('''find the day on which combined sales was highest''')

In the above code the keys can be found by running the following piece db.tips.find_one({}).keys()

3. Kusto Query

Suppose you want to convert the textual question to Kusto query, follow the code below

from nl2query import KustoQuery
cols = ['vendor_id', 'pickup_datetime', 'dropoff_datetime', 'passenger_count', 'trip_distance', 'pickup_longitude', 'pickup_latitude', 'rate_code', 'store_and_fwd_flag', 'dropoff_longitude', 'dropoff_latitude', 'payment_type', 'fare_amount', 'surcharge', 'mta_tax', 'Tip_amount', 'tolls_amount', 'total_amount']

queryfier = KustoQuery(cols, 'nyc_taxi')
queryfier.generate_query('''find the vendor ids for all the tips that are greater than the average tip''')

4. Cypher(Neo4j) Query

Suppose you want to convert the textual question to Cypher query, follow the code below

from nl2query import CypherQuery

node_labels = {'User': ['display_name', 'uuid'], 'Comment': ['score', 'link', 'uuid']}
relationships = ['COMMENTED']
queryfier = CypherQuery(node_labels, relationships)
queryfier.generate_query('list the links of all the comments done by "jose_bacoy"')

node_labels = {'Case': ['gender', 'reportdate', 'ageunit', 'reporteroccupation', 'primaryid', 'age', 'eventDate'], 'Outcome': ['code', 'outcome']}
relationships = ['RESULTED_IN']
queryfier = CypherQuery(node_labels, relationships)
queryfier.generate_query('find the outcomes of people who are female and below the age of 32')

node_labels = {'Person': ['id', 'name', 'dob']}
relationships = []
queryfier = CypherQuery(node_labels, relationships)
res = queryfier.generate_query('find the dob of people who have "Andreia" in their name')

Changelog

Refer to the CHANGELOG.md file.