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The rich ecosystem of Python modules lets you get to work quickly and integrate your systems effectively. With the CData Python Connector for Reckon Accounts Hosted and the SQLAlchemy toolkit, you can build Reckon Accounts Hosted-connected Python applications and scripts. This article shows how to use SQLAlchemy to connect to Reckon Accounts Hosted data to query, update, delete, and insert Reckon Accounts Hosted data.
With built-in optimized data processing, the CData Python Connector offers unmatched performance for interacting with live Reckon Accounts Hosted data in Python. When you issue complex SQL queries from Reckon Accounts Hosted, the CData Connector pushes supported SQL operations, like filters and aggregations, directly to Reckon Accounts Hosted and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).
Connecting to Reckon Accounts Hosted 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.
The connector makes requests to Reckon Accounts Hosted through OAuth. Specify the following connection properties:
CData provides an embedded OAuth application that simplifies OAuth desktop authentication. See the Help documentation for information on other OAuth authentication methods (web, headless, etc.), creating custom OAuth applications, and reasons for doing so.
Follow the procedure below to install SQLAlchemy and start accessing Reckon Accounts Hosted through Python objects.
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
You can now connect with a connection string. Use the create_engine function to create an Engine for working with Reckon Accounts Hosted 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("reckonaccountshosted:///?SubscriptionKey=my_subscription_key&CountryVersion=2021.R2.AU&CompanyFile=Q:/CompanyName.QBW&User=my_user&Password=my_password&CallbackURL=http://localhost:33333&OAuthClientId=my_oauth_client_id&OAuthClientSecret=my_oauth_client_secret&InitiateOAuth=GETANDREFRESH")
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 Accounts 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 Accounts(base): __tablename__ = "Accounts" Name = Column(String,primary_key=True) Balance = Column(String) ...
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.
engine = create_engine("reckonaccountshosted:///?SubscriptionKey=my_subscription_key&CountryVersion=2021.R2.AU&CompanyFile=Q:/CompanyName.QBW&User=my_user&Password=my_password&CallbackURL=http://localhost:33333&OAuthClientId=my_oauth_client_id&OAuthClientSecret=my_oauth_client_secret&InitiateOAuth=GETANDREFRESH")
factory = sessionmaker(bind=engine)
session = factory()
for instance in session.query(Accounts).filter_by(IsActive="true"):
print("Name: ", instance.Name)
print("Balance: ", instance.Balance)
print("---------")
Alternatively, you can use the execute method with the appropriate table object. The code below works with an active session.
Accounts_table = Accounts.metadata.tables["Accounts"]
for instance in session.execute(Accounts_table.select().where(Accounts_table.c.IsActive == "true")):
print("Name: ", instance.Name)
print("Balance: ", instance.Balance)
print("---------")
For examples of more complex querying, including JOINs, aggregations, limits, and more, refer to the Help documentation for the extension.
To insert Reckon Accounts Hosted data, define an instance of the mapped class and add it to the active session. Call the commit function on the session to push all added instances to Reckon Accounts Hosted.
new_rec = Accounts(Name="placeholder", IsActive="true") session.add(new_rec) session.commit()
To update Reckon Accounts Hosted data, fetch the desired record(s) with a filter query. Then, modify the values of the fields and call the commit function on the session to push the modified record to Reckon Accounts Hosted.
updated_rec = session.query(Accounts).filter_by(SOME_ID_COLUMN="SOME_ID_VALUE").first() updated_rec.IsActive = "true" session.commit()
To delete Reckon Accounts Hosted data, fetch the desired record(s) with a filter query. Then delete the record with the active session and call the commit function on the session to perform the delete operation on the provided records (rows).
deleted_rec = session.query(Accounts).filter_by(SOME_ID_COLUMN="SOME_ID_VALUE").first() session.delete(deleted_rec) session.commit()
Download a free, 30-day trial of the CData Python Connector for Reckon Accounts Hosted to start building Python apps and scripts with connectivity to Reckon Accounts Hosted data. Reach out to our Support Team if you have any questions.
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