Multiple connections / connection objects (Does not force the use of a singleton).PostgreSQL Tutorial and PostgreSQL Python.2.4 Fetch Records using a Server-Side Cursor.2.3 Select/Fetch Records with Column Names.The server can be started with python main.py. # properly close webserver and db connection # Run webserver until stopped by keyboard interrupt Print("Listening on: % (hostName, serverPort)) WebServer = HTTPServer((hostName, serverPort), PostgresApiServer(connection)) # instantiate webserver WriteDataQuery = 'INSERT INTO my_table(name) VALUES(%s) ' (bytes(io.getvalue(), "utf-8")) # Return the results as a json string ![]() Json.dump(records, io, indent=4, sort_keys=True, default=str) nd_header("Content-type", "application/json") ReadDataQuery = 'SELECT * FROM my_table WHERE name = %s ' # Handle request differently depending on URL path Name = dict(parse_qsl(url.query)).get('name', 'john') # Parse name from URL query string, use 'john' if not set Create a file main.py: import jsonįrom rver import BaseHTTPRequestHandler, HTTPServerįrom urllib.parse import urlparse, parse_qslĬlass PostgresApiServer(BaseHTTPRequestHandler):ĭef _init_(self, conn): # Initialise server with database connectionĭate TIMESTAMP NOT NULL DEFAULT current_timestampĬursor = self.db.cursor() # Create db cursor which allows to execute queries on the database It makes use of the Python rver package which is available by default. The web server will contain three endpoints, one for adding a row /write?name= (corresponding to add-data.js), one for reading a row /read?name= (similar to read-data.js) and one for deleting all data. In this section we will explain how to wrap our previous examples into a web server, exposing an API with different endpoints to manipulate and read data. Putting it together with a webserver (optional) This which will print a message to show that the connection to Now you're ready to run the script: python guide.py. SSL/TLS: if your database is not running with SSL/TLS, you can remove sslmode='require' in the above example. Query which returns the input string is run and printed to the console. ![]() This script creates a postgres cursor which allows you to execute queries to your database. Load_dotenv() # Required to load the previously defined environment variablesĬonnection = nnect(host=os.environ.get('PG_HOST'),Ĭtocommit = True # Ensure data is added to the database immediately after write commandsĬursor.execute('SELECT %s as connected ', ('Connection to postgres successful!',)) Information about this postgres instance: import os Add following code to this file to connect to postgres and print basic ![]() Set the variables to the values for your database.Ĭreate a file guide.py in your project directory. Here we add the connection details for the postgres database: PG_HOST= ![]() This allows us to locally load the sensitive data into environment variables. To handle sensitive connection data appropriately, we also add the python-dotenv package: pip3 install python-dotenv The provided functionality is similar to psycopg2. There exist other postgres libraries such as PyGreSQL, pg8000 or aiopg. We will be using the psycopg2 postgres adapter for Python, one of the most established postgres libraries.
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