> ## Documentation Index
> Fetch the complete documentation index at: https://developer.mindbridge.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Analyses

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.

<CodeGroup dropdown>
  ```python theme={null}
  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()
  ```
</CodeGroup>

# 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.

<CodeGroup dropdown>
  ```python theme={null}
  # 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}"
      )
  ```
</CodeGroup>

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

<CodeGroup dropdown>
  ```python theme={null}
  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"
  )
  ```
</CodeGroup>

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`.

<CodeGroup dropdown>
  ```python theme={null}
  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}"
      )
  ```
</CodeGroup>

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

<CodeGroup dropdown>
  ```python theme={null}
  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"
  )
  ```
</CodeGroup>