Creating a project.

lab.create_project('My New Project')
# OR
lab.create_project(name='My New Project', owner_name='AnnoLab')

Getting an existing project.

lab.find_project('My New Project')
# OR
lab.find_project(name='My New Project', owner_name='AnnoLab')

Creating a land abstract.

AOIs are used by Land AI to limit direct conveyance extractions.

project = lab.find_project('My Land Project')
abstract = project.create_abstract(
  name='Garvin 12-3N-4W',
  aois=[{
    'state': 'OK',
    'county': 'Garvin',
    'section': '12',
    'township': '3N',
    'range': '4W'
  }],
  subdivisions=['Green Acres']
)

# Texas AOIs use block, abstract, and survey instead of range
abstract = project.create_abstract(
  name='Midland 18-37',
  aois=[{
    'state': 'TX',
    'county': 'Midland',
    'section': '18',
    'block': '37',
    'township': 'T1S',
    'abstract': '123',
    'survey': 'T&P RR Co'
  }]
)

Finding an existing land abstract by name.

project = lab.find_project('My Land Project')
abstract = project.find_abstract('Garvin 12-3N-4W')
print(abstract.id, abstract.name, abstract.tags)

End-to-end land abstract workflow.

Create an abstract, upload a PDF, wait for processing, then print instruments.

See Land Instrument and Conveyances in our docs for description of produced attributes.

from annolab import AnnoLab

lab = AnnoLab(api_key='YOUR_API_KEY')

project = lab.find_project('My Land Project')

abstract = project.create_abstract(
  name='Garvin 12-3N-4W',
  aois=[{
    'state': 'OK',
    'county': 'Garvin',
    'section': '12',
    'township': '3N',
    'range': '4W'
  }],
  subdivisions=['Green Acres']
)

# OCR runs by default (the same default as project.create_pdf_source).
# Pass ocr=False to extract the pdf's embedded text instead.
result = abstract.upload_file(
  file='/path/to/deed.pdf',
  workflow='land_title'
)

# result.execution is None when the upload did not start a workflow.
# wait_until_complete() is a no-op in that case.
result.wait_until_complete()
if result.execution:
  print(result.execution.status)

abstract.populate_instruments()
print(abstract.instruments)

Fetching an abstract’s instruments and conveyance data.

project = lab.find_project('My Land Project')
abstract = project.find_abstract('Garvin 12-3N-4W')
abstract.populate_instruments()
print(abstract.instruments)

Creating a new text source.

Will be added to the “Uploads” directory by default.

project = lab.find_project('My New Project')
project.create_text_source(name='New Source', text='Some text or tokens for annotation.')
# Specifying a directory
project.create_text_source(
  name='New Source',
  text='Some text or tokens for annotation.',
  directory='Uploads'
)

Creating a new pdf source from a file.

Will be added to the “Uploads” directory by default.

project = lab.find_project('My New Project')
project.create_pdf_source(file='/path/to/file')
project.create_pdf_source(file='/path/to/file', name='custom_name.pdf', directory='Uploads')

# Skip OCR and extract the pdf's embedded text instead
project.create_pdf_source(file='/path/to/file', ocr=False)

# You may also pass a filelike object or bytes. "name" is required when doing so.
project.create_pdf_source(file=open('myfile.pdf', 'r+b'), name='myfile.pdf')

Creating a new pdf source from a web source.

project = lab.find_project('My New Project')
project.create_pdf_source_from_web(url='https://www.w3.org/WAI/ER/tests/xhtml/testfiles/resources/pdf/dummy.pdf', name='mypdf.pdf')

Adding annotations.

  project.create_annotations(
    source_name='New Source',
    annotations=[
        { 'type': 'one', 'value': 'value one', 'offsets': [0, 10]},
        { 'type': 'two', 'value': 'two', 'offsets': [10, 20] }
    ],
)

Adding annotations with relations.

  project.create_annotations(
    source_name='New Source',
    annotations=[
        { 'clientId': 1, 'type': 'one', 'value': 'value one', 'offsets': [0, 10]},
        { 'clientId': 2, 'type': 'two', 'value': 'two', 'offsets': [10, 20] }
    ],
    relations=[
      { 'annotations': [1, 2] }
    ]
)