This section guides you through creating a General Ledger Analysis, creating a TRA Vendor Analysis, retrieving an Analysis by its ID, and querying Analyses using the MindBridge SDK.

Prerequisites

First run this block to configure your server.

import os
from dotenv import load_dotenv
import mindbridgeapi as mbapi

load_dotenv(override=True)
token = os.getenv("MINDBRIDGE_API_TOKEN")
url = os.getenv("MINDBRIDGE_URL")
server = mbapi.Server(url=url, token=token)
user = server.users.get_current()

Creating a General Ledger Analysis

To setup an Analysis we first need an Organization and an Engagement. If no library_id is included in the EngagementItem the MindBridge SDK will create one using the MindBridge for-profit (Mac v2) Library. This Library includes the General ledger, Accounts payable and Accounts receivable analysis types by default.

# get-or-create our organization
organization_name = "Chapter 3 - Creating an Analysis"
try:
    organization = next(server.organizations.get({"name": organization_name}))
    print(f"Organization '{organization_name}' already exists.")
except StopIteration:
    new_organization_item = mbapi.OrganizationItem(
        name=organization_name,
        external_client_code="My Client ID",  # Optional
        manager_user_ids=[user.id],  # Optional
    )
    organization_item = mbapi.OrganizationItem(name=organization_name)
    organization = server.organizations.create(organization_item)
    print(f"Organization '{organization_name}' created.")


engagement_name = "Engagement - MindBridge for-profit Library"
try:
    new_engagement_item = mbapi.EngagementItem(
        organization_id=organization.id,
        name=engagement_name,
        engagement_lead_id=user.id,
    )
    engagement = server.engagements.create(new_engagement_item)
    print(f"Created the new engagement {engagement.name}")
except mbapi.exceptions.ValidationError:
    engagement = next(
        server.engagements.get(
            {"organizationId": organization.id, "name": engagement_name}
        )
    )
    print(
        f"Fetched the engagement '{engagement.name}' from the organization with id "
        f"{organization.id}"
    )

Now that the Engagement “Engagement - MindBridge for-profit Library” is created, we can create an analysis within it.

from datetime import date

new_gl_analysis_item = mbapi.AnalysisItem(
    name="GL Analysis",
    engagement_id=engagement.id,
    currency_code="CAD",
    analysis_periods=[
        mbapi.AnalysisPeriod(end_date=date(2024, 12, 31), start_date=date(2024, 1, 1))
    ],
    analysis_type_id=mbapi.AnalysisTypeItem.GENERAL_LEDGER,
)

analysis = server.analyses.create(new_gl_analysis_item)

print(
    f"https://{os.getenv('MINDBRIDGE_URL')}/app/organization/{organization.id}/"
    f"engagement/{engagement.id}/analysis-list"
)

At the above link, you should have an analysis ready for you to upload data.

Creating a Custom Analysis

To create a Custom Analysis we first need a Library with our desired Analysis Type. Then we’ll create an Engagement that uses that Library. In this example we will setup a TRA Vendor Analysis by creating an Analysis Type using the TRA Vendor Template provided by MindBridge. First create a TRA Vendor Analysis Type within the Analysis Designer:

Go to the Analysis Designer
Find the Analysis Type named “TRA Vendor Template”
Duplicate the TRA Vendor Template and set the name to “SDK TRA Vendor”
Click “Save”
Go back to the Analysis Designer page
Select “Publish” on the “SDK TRA Vendor”

Then, create a Library with that Analysis Type

Go to the Libraries page
Select “Create Library”
Set the name to “SDK TRA Vendor Library”
Set the base library to “MindBridge for-profit (MAC v.2)”
Add “SDK TRA Vendor” to the Analysis Types
Set the Account grouping to Mac v.2
Select “Create Library” You should now have a Library called “SDK TRA Vendor Library” which contains the Analysis Type “SDK TRA Vendor”

Now we can create an Engagement that uses this library by providing the library_id in the EngagementItem.

all_libraries = server.libraries.get()
vendor_library = next(
    library for library in all_libraries if library.name == "SDK TRA Vendor Library"
)

organization_name = "Chapter 3 - Creating an Analysis"
try:
    organization = next(server.organizations.get({"name": organization_name}))
    print(f"Organization '{organization_name}' already exists.")
except StopIteration:
    new_organization_item = mbapi.OrganizationItem(
        name=organization_name,
        external_client_code="My Client ID",  # Optional
        manager_user_ids=[user.id],  # Optional
    )
    organization_item = mbapi.OrganizationItem(name=organization_name)
    organization = server.organizations.create(organization_item)
    print(f"Organization '{organization_name}' created.")


engagement_name = "Engagement - SDK TRA Vendor Library"
try:
    new_engagement_item = mbapi.EngagementItem(
        organization_id=organization.id,
        name=engagement_name,
        engagement_lead_id=user.id,
        library_id=vendor_library.id,
    )
    engagement = server.engagements.create(new_engagement_item)
    print(f"Created the new engagement '{engagement.name}'")
except mbapi.exceptions.ValidationError:
    engagement = next(
        server.engagements.get(
            {"organizationId": organization.id, "name": engagement_name}
        )
    )
    print(
        f"Fetched the engagement '{engagement.name}' from the organization with id "
        f"{organization.id}"
    )

Now that the Engagement “Engagement - SDK TRA Vendor Library” is created, we can create an Analysis within it. Note that we need to fetch the Analysis Type from the Engagement

from datetime import date

all_libraries = server.libraries.get()
vendor_library = next(
    library for library in all_libraries if library.name == "SDK TRA Vendor Library"
)
available_analysis_types = list(vendor_library.analysis_types)

print(f"These are the Analysis Types available in the library '{vendor_library.name}'")
for at in available_analysis_types:
    print(at.name)

tra_vendor_analysis_type = next(
    analysis_type
    for analysis_type in available_analysis_types
    if analysis_type.name == "SDK TRA Vendor"
)

new_gl_analysis_item = mbapi.AnalysisItem(
    name="GL Analysis",
    engagement_id=engagement.id,
    currency_code="CAD",
    analysis_periods=[
        mbapi.AnalysisPeriod(end_date=date(2024, 12, 31), start_date=date(2024, 1, 1))
    ],
    analysis_type_id=tra_vendor_analysis_type.id,
)

analysis = server.analyses.create(new_gl_analysis_item)

print(
    f"https://{os.getenv('MINDBRIDGE_URL')}/app/organization/{organization.id}/"
    f"engagement/{engagement.id}/analysis-list"
)

​Prerequisites

​Creating a General Ledger Analysis

​Creating a Custom Analysis

Prerequisites

Creating a General Ledger Analysis

Creating a Custom Analysis