timbr Python connector sample file

This project is a sample connecting to timbr using Python.

Dependencies

• Python 3.7.13+ or 3.8.x or 3.9.x
• Java 8 or Java 11

Installation

• Install as clone repository:

  • Install Python: https://www.python.org/downloads/release/python-3713/
  • Install Java: https://www.oracle.com/il-en/java/technologies/javase/jdk11-archive-downloads.html
  • Run the following command to install the Python dependencies: pip install -r requirements.txt (optional install pandas to run pandas example)
  • Download the following jar to jars path: https://repo1.maven.org/maven2/org/apache/hive/hive-jdbc/2.3.9/hive-jdbc-2.3.9-standalone.jar

• Install using pip and git:

  • pip install git+https://github.com/WPSemantix/timbr_python_connector

• Install using pip:

  • pip install pytimbr

Sample usage

• For an example of how to use the Python connector for Timbr:
  • Create connection with params, follow this Example file
  • Create JDBC connection, follow this Example file
• For an example of using the Timbr Python connector with Pandas:
  • Make sure you have the pandas library installed, or you can install it by running pip install pandas
  • Create connection with params, follow this Example File
  • Create JDBC connection, follow this Example File

Create basic connection

Create connection with params

  conn = pytimbr.getConnection(
    hostname = '<TIMBR_IP/HOST>',
    port = '<TIMBR_PORT>',
    ontology = '<ONTOLOGY_NAME>',
    username = '<TIMBR_USER/token>',
    password = '<TIMBR_PASSWORD/TOKEN_VALUE>',
    enabled_ssl = '<false/true>',
    http_path = '<TIMBR_SERVER_HTTP_PATH>'
  )

  # hostname - The IP / Hostname of the Timbr server (not necessarily the hostname of the Timbr platform).
  # port - The port to connect to in the Timbr server. Timbr's default port with enabled_ssl is 443 without SSL is 11000.
  # ontology - the ontology / knowledge graph to connect to.
  # username - Use 'token' as the username when connecting using a Timbr token, otherwise its the user name.
  # password - Should be the token value if using a token as a username, otherwise its the user's password.
  # enabled_ssl - true if SSL is enabled, false if SSL is disabled.
  # http_path - Use only if your timbr server http path is not '/timbr-server'.

Create JDBC connection

  hostname = '<TIMBR_IP/HOST>'
  port = '<TIMBR_PORT>'
  ontology = '<ONTOLOGY_NAME>'
  username = '<TIMBR_USER/token>'
  password = '<TIMBR_PASSWORD/TOKEN_VALUE>'
  enabled_ssl = '<false/true>'
  http_path = '<TIMBR_SERVER_HTTP_PATH>'
  
  # hostname - The IP / Hostname of the Timbr server (not necessarily the hostname of the Timbr platform).
  # port - The port to connect to in the Timbr server. Timbr's default port with enabled_ssl is 443 without SSL is 11000.
  # ontology - the ontology / knowledge graph to connect to.
  # username - Use 'token' as the username when connecting using a Timbr token, otherwise its the user name.
  # password - Should be the token value if using a token as a username, otherwise its the user's password.
  # enabled_ssl - true if SSL is enabled, false if SSL is disabled.
  # http_path - Use only if your timbr server http path is not '/timbr-server'.
  
  # Create new JDBC connection
  conn = pytimbr.getJdbcConnection(
    f"jdbc:hive2://{hostname}:{port}/{ontology};transportMode=http;ssl={enabled_ssl};httpPath={http_path}",
    username,
    password
  )

Execute a query

Execute using the connection

  # Use the connection to execute a query
  with conn.cursor() as curs:
    # Execute query
    curs.execute('SHOW CONCEPTS')
    # Fetch results
    concepts = curs.fetchall()
    # Print the results
    for concept in concepts:
      print(concept)

Execute using the Pandas

  # Execute a query using Pandas
  df = pandas.read_sql("SELECT * FROM timbr.person limit 1000", conn)
  print("--------------------------------------")
  print(df)
  print("--------------------------------------")
  print(df.columns)
  print("--------------------------------------")
  print(df.count())