Quest Examples

• Slow Start: A step by step breakdown of the Quickstart example
  • Create a Collection
  • Select a Data Service
  • Search for Datasets
  • Add Datasets to Collection
  • Download Datasets
  • Open Datasets
  • Where to Go from Here

Project Management

In [1]: from quest import api

In [2]: api.get_active_project()
Out[2]: 'default'

In [3]: api.get_projects()
Out[3]: ['default']

In [4]: api.new_project('my_proj')
Out[4]:
{'created_at': datetime.datetime(2017, 10, 13, 15, 1, 42, 322881),
 'description': '',
 'display_name': 'my_proj',
 'metadata': {},
 'updated_at': None}

In [5]: api.get_projects()
Out[5]: ['my_proj', 'default']

In [6]: api.set_active_project('my_proj')
Out[6]: 'my_proj'

In [7]: api.get_active_project()
Out[7]: 'my_proj'

In [8]: api.delete_project('my_proj')
Out[8]: {'default': {'folder': 'default'}}

In [9]: api.get_active_project()
Out[9]: 'default'

Collection Management

In [1]: from quest import api

In [2]: api.get_collections()
Out[2]: []

In [3]: api.new_collection('demo')
Out[3]:
{'created_at': datetime.datetime(2017, 10, 13, 15, 5, 33, 385739),
 'description': '',
 'display_name': 'demo',
 'metadata': {},
 'name': 'demo',
 'updated_at': None}

In [4]: api.get_collections()
Out[4]: ['demo']

In [5]: api.delete('demo')
Out[5]: True

In [6]: api.get_collections()
Out[6]: []

Applying Tools

Continuing from previous example.

In [16]: dataset = datasets[0]

In [17]: api.get_tools(filters={'dataset': dataset})
Out[17]: ['ts-flow-duration', 'ts-resample', 'ts-unit-conversion', 'ts-remove-outliers']

In [18]: filter_name = 'ts-resample'

In [19]: api.apply_filter_options(filter_name)
Out[19]:
{'properties': {'method': {'description': 'resample method',
   'type': {'default': 'mean',
    'enum': ['sum', 'mean', 'std', 'max', 'min', 'median']}},
  'period': {'description': 'resample frequency',
   'type': {'default': 'daily',
    'enum': ['daily', 'weekly', 'monthly', 'annual']}}},
 'required': ['period', 'method'],
 'title': 'Resample Timeseries Filter',
 'type': 'object'}

In [20]: options = {'method': 'max', 'period': 'daily'}

In [21]: api.run_filter(filter_name, datasets=dataset, options=options)
Out[21]: {'datasets': ['db98e371e7a64a02a773004c6ddc90ff'], 'features': []}

In [22]: api.get_metadata('db98e371e7a64a02a773004c6ddc90ff')
Out[22]:
{'db98e371e7a64a02a773004c6ddc90ff': {'collection': 'demo',
  'created_at': Timestamp('2017-10-13 16:01:20.665627'),
  'datatype': 'timeseries',
  'description': 'TS Filter Applied',
  'display_name': 'db98e371e7a64a02a773004c6ddc90ff',
  'feature': 'fa2e58257ec04d4cb0f18feec51df736',
  'file_format': 'timeseries-hdf5',
  'file_path': '/path/to/quest/projects/default/demo/usgs-nwis/iv/d70123cb1ad944a988f64f449a7d8e8e/db98e371e7a64a02a773004c6ddc90ff',
  'message': 'TS Filter Applied',
  'metadata': {},
  'name': 'db98e371e7a64a02a773004c6ddc90ff',
  'options': {'dataset': ['d70123cb1ad944a988f64f449a7d8e8e'],
   'features': None,
   'filter_applied': 'ts-resample',
   'filter_options': {'method': 'max', 'period': 'daily'}},
  'parameter': 'streamflow:daily:max',
  'source': 'derived',
  'status': 'filter applied',
  'unit': 'ft3/s',
  'updated_at': None,
  'visualization_path': ''}}