Programming Interface

In PyFireSQL, we offer a simple programming interface to parse and execute firebase SQL. Please consult Firebase Admin SDK Documentation to generate the project’s service account credentials.json file.

---

from firesql.firebase import FirebaseClient
from firesql.sql.sql_fire_client import FireSQLClient
from firesql.sql import FireSQL

# make connection to Cloud Firestore
client = FirebaseClient()
client.connect(credentials_json='credentials.json')
# wrapped as FireSQL client interface
sqlClient = FireSQLClient(client)

# query via the FireSQL interface - the results are in list of docs (Dict)
query = "SELECT * FROM Users WHERE state = 'ACTIVE'"
fireSQL = FireSQL()
docs = fireSQL.execute(sqlClient, query)

After fireSQL.execute() query completed, the results are a list of docs (as Dict) that satisfied the query. Then we can pass the list of docs to render into any output format, in our case, the DocPrinter object can output csv or json with the select fields.

from firesql.sql.doc_printer import DocPrinter

docPrinter = DocPrinter()
if format == 'csv':
  docPrinter.printCSV(docs, fireSQL.select_fields())
else:
  docPrinter.printJSON(docs, fireSQL.select_fields())

For further post-processing, we can use Pandas’s Dataframe to perform any data analysis, grouping, sorting and calculations. The list of docs (as Dict) can be directly imported into Dataframe! very convenience.

import pandas as pd

df = pd.DataFrame(docs)