How to use SQLAlchemy ORM to access Tickspot Data in Python
The rich ecosystem of Python modules lets you get to work quickly and integrate your systems effectively. With the CData API Driver for Python and the SQLAlchemy toolkit, you can build Tickspot-connected Python applications and scripts. This article shows how to use SQLAlchemy to connect to Tickspot data to query Tickspot data.
With built-in optimized data processing, the CData Python Connector offers unmatched performance for interacting with live Tickspot data in Python. When you issue complex SQL queries from Tickspot, the CData Connector pushes supported SQL operations, like filters and aggregations, directly to Tickspot and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).
Connecting to Tickspot Data
Connecting to Tickspot data looks just like connecting to any relational data source. Create a connection string using the required connection properties. For this article, you will pass the connection string as a parameter to the create_engine function.
Start by setting the Profile connection property to the location of the Tickspot Profile on disk (e.g. C:\profiles\Tickspot.apip). Next, set the ProfileSettings connection property to the connection string for Tickspot (see below).
Tickspot API Profile Settings
Obtain your API Token and Subscription ID by querying the Roles table using your Tickspot login email and password. Use the returned APIKey and SubscriptionId for all subsequent requests.
Follow the procedure below to install SQLAlchemy and start accessing Tickspot through Python objects.
Install Required Modules
Use the pip utility to install the SQLAlchemy toolkit and SQLAlchemy ORM package:
pip install sqlalchemy pip install sqlalchemy.orm
Be sure to import the appropriate modules:
from sqlalchemy import create_engine, String, Column from sqlalchemy.ext.declarative import declarative_base from sqlalchemy.orm import sessionmaker
Model Tickspot Data in Python
You can now connect with a connection string. Use the create_engine function to create an Engine for working with Tickspot data.
NOTE: Users should URL encode the any connection string properties that include special characters. For more information, refer to the SQL Alchemy documentation.
engine = create_engine("api:///?Profile=C:\profiles\Tickspot.apip&ProfileSettings='APIKey=your_api_key&SubscriptionId=your_subscription_id'")
Declare a Mapping Class for Tickspot Data
After establishing the connection, declare a mapping class for the table you wish to model in the ORM (in this article, we will model the Clients table). Use the sqlalchemy.ext.declarative.declarative_base function and create a new class with some or all of the fields (columns) defined.
base = declarative_base() class Clients(base): __tablename__ = "Clients" Id = Column(String,primary_key=True) Name = Column(String) ...
Query Tickspot Data
With the mapping class prepared, you can use a session object to query the data source. After binding the Engine to the session, provide the mapping class to the session query method.
Using the query Method
engine = create_engine("api:///?Profile=C:\profiles\Tickspot.apip&ProfileSettings='APIKey=your_api_key&SubscriptionId=your_subscription_id'")
factory = sessionmaker(bind=engine)
session = factory()
for instance in session.query(Clients).filter_by(Archive="false"):
print("Id: ", instance.Id)
print("Name: ", instance.Name)
print("---------")
Alternatively, you can use the execute method with the appropriate table object. The code below works with an active session.
Using the execute Method
Clients_table = Clients.metadata.tables["Clients"]
for instance in session.execute(Clients_table.select().where(Clients_table.c.Archive == "false")):
print("Id: ", instance.Id)
print("Name: ", instance.Name)
print("---------")
For examples of more complex querying, including JOINs, aggregations, limits, and more, refer to the Help documentation for the extension.
Free Trial & More Information
Download a free, 30-day trial of the CData API Driver for Python to start building Python apps and scripts with connectivity to Tickspot data. Reach out to our Support Team if you have any questions.