def test_add_vocab():
ds = Dataset(id_hash='7cf3fab2-3fbe-4980-b572-712207b2c8c7')
payload = {
'name': 'categoryTab',
'tags': ['forestChange', 'treeCoverChange'],
'application': 'gfw'
}
ds.add_vocabulary(vocab_params=payload, token=API_TOKEN)
updated_ds = Dataset(id_hash='7cf3fab2-3fbe-4980-b572-712207b2c8c7')
assert len(updated_ds.vocabulary) > 0
def test_add_widget():
d = Dataset(id_hash='7cf3fab2-3fbe-4980-b572-712207b2c8c7')
w = d.add_widget(widget_params={
'name': 'Template Widget',
'widgetConfig': {'key': 'val'},
'application': ['gfw']
}, token=API_TOKEN)
assert type(w.id) == str
assert type(w.attributes) == dict
assert len(w.attributes) > 0
def test_add_meta():
ds = Dataset(id_hash='7cf3fab2-3fbe-4980-b572-712207b2c8c7')
payload = {
'application': 'gfw',
'info': {'citation': 'Example citation',
'color': '#fe6598',
'description': 'This is an example dataset.',
'isLossLayer': True,
'name': 'Template Layer'},
'language': 'en'
}
ds.add_metadata(meta_params=payload, token=API_TOKEN)
updated_ds = Dataset(id_hash='7cf3fab2-3fbe-4980-b572-712207b2c8c7')
assert len(updated_ds.metadata) > 0
def test_create_new_dataset():
atts = {
"name": "NEW Template Dataset",
"application": ["gfw"],
"connectorType": "rest",
"provider": "cartodb",
"connectorUrl": "https://wri-01.carto.com/tables/gfw_land_rights/public_map",
"tableName": "gfw_land_rights",
"published": False,
"env": "staging",
}
new = Dataset(attributes=atts, token=API_TOKEN)
assert new.attributes['name'] == 'NEW Template Dataset'
assert new.delete(token=API_TOKEN, force=True) == None
def test_merge_widget():
staging_widget = Widget(id_hash='66de77eb-dee3-4c56-9ad4-cf68d8b107fd', server='https://staging-api.globalforestwatch.org')
staging_widget.update(update_params={
'name': 'Template Widget Staging',
'widgetConfig': {}
}, token=API_TOKEN)
production_widget = Dataset(id_hash='7cf3fab2-3fbe-4980-b572-712207b2c8c7').widget[0]
whitelist = ['name', 'widgetConfig']
merged_widget = production_widget.merge(token=API_TOKEN,
target_widget=None,
target_widget_id=staging_widget.id,
target_server='https://staging-api.globalforestwatch.org',
key_whitelist=whitelist,
force=True)
merged_atts = {k:v for k,v in merged_widget.attributes.items() if k in whitelist}
production_atts = {k:v for k,v in production_widget.attributes.items() if k in whitelist}
assert merged_atts == production_atts
def test_update_meta():
ds = Dataset(id_hash='7cf3fab2-3fbe-4980-b572-712207b2c8c7')
m = ds.metadata[0]
assert type(m.id) == str
payload = {
'application': 'gfw',
'info': {'citation': 'TEST',
'color': '#fe6598',
'description': 'TEST',
'isLossLayer': False,
'name': 'Template Layer'},
'language': 'en'}
m.update(update_params=payload, token=API_TOKEN)
ds = Dataset(id_hash='7cf3fab2-3fbe-4980-b572-712207b2c8c7')
updated_m = ds.metadata[0]
assert updated_m.attributes['info']['description'] == 'TEST'
assert updated_m.attributes['info']['isLossLayer'] == False
def test_update_vocab():
ds = Dataset(id_hash='7cf3fab2-3fbe-4980-b572-712207b2c8c7')
v = ds.vocabulary[0]
assert type(v.id) == str
payload = {
'name': 'categoryTab',
'tags': ['forestChange', 'treeCoverChange']
}
updated_v = v.update(update_params=payload, token=API_TOKEN)
assert updated_v[0].attributes['name'] == 'categoryTab'
assert updated_v[0].attributes['tags'] == ['forestChange', 'treeCoverChange']
def test_update_widget():
ds = Dataset(id_hash='7cf3fab2-3fbe-4980-b572-712207b2c8c7')
w = ds.widget[0]
assert type(w.id) == str
payload = {
'name': 'Widget UPDATED',
'widgetConfig': {'updated': True}
}
updated_w = w.update(update_params=payload, token=API_TOKEN)
assert updated_w.attributes['name'] == 'Widget UPDATED'
assert updated_w.attributes['widgetConfig'].get('updated', None) == True
def test_clone_and_delete_dataset():
d = Dataset(id_hash='7cf3fab2-3fbe-4980-b572-712207b2c8c7')
cloned = d.clone(token=API_TOKEN, env='production', dataset_params={
'name': 'Template Dataset CLONED',
'published': False
}, clone_children=True)
assert cloned.attributes['name'] == f'Template Dataset CLONED'
assert cloned.id is not '7cf3fab2-3fbe-4980-b572-712207b2c8c7'
vocabulary = cloned.vocabulary
metadata = cloned.metadata
widget = cloned.widget
layer = cloned.layers
assert len(vocabulary) > 0
assert len(metadata) > 0
assert len(widget) > 0
assert len(layer) > 0
assert vocabulary[0].delete(token=API_TOKEN) == None
assert metadata[0].delete(token=API_TOKEN) == None
assert widget[0].delete(token=API_TOKEN) == None
assert layer[0].delete(token=API_TOKEN, force=True) == None
assert cloned.delete(token=API_TOKEN, force=True) == None
def test_update_dataset():
ds = Dataset(id_hash='7cf3fab2-3fbe-4980-b572-712207b2c8c7')
updated = ds.update(token=API_TOKEN, update_params={'name': f'Template Dataset UPDATED'})
assert updated.attributes['name'] == f'Template Dataset UPDATED'
updated = ds.update(token=API_TOKEN, update_params={'name': f'Template Dataset'})
assert updated.attributes['name'] == 'Template Dataset'
def test_dataset_load():
ds = Dataset(id_hash='897ecc76-2308-4c51-aeb3-495de0bdca79')
load_path = f'./tests'
loaded = ds.load(path=load_path, check=True)
assert loaded.id == '897ecc76-2308-4c51-aeb3-495de0bdca79'
os.remove(load_path+f"/{ds.id}.json")
def test_dataset_save():
ds = Dataset(id_hash='897ecc76-2308-4c51-aeb3-495de0bdca79')
save_path = './tests'
ds.save(path=save_path)
assert os.path.exists(save_path+f"/{ds.id}.json") == True
def test_access_widget():
ds = Dataset(id_hash='dcd1e9c7-1370-404e-8816-eaa51d4b1a39')
assert type(ds.widget) == list
assert len(ds.widget) > 0
def test_access_meta_attributes():
ds = Dataset('7cf3fab2-3fbe-4980-b572-712207b2c8c7')
meta = ds.metadata[0].attributes
assert type(meta) is dict
def test_access_meta():
ds = Dataset(id_hash='bb1dced4-3ae8-4908-9f36-6514ae69713f')
assert type(ds.metadata) == list
assert len(ds.metadata) > 0
def test_access_vocab():
ds = Dataset(id_hash='bb1dced4-3ae8-4908-9f36-6514ae69713f')
assert type(ds.vocabulary) == list
assert len(ds.vocabulary) > 0
def test_queries_on_datasets():
ds = Dataset(id_hash='bd5d7924-611e-4302-9185-8054acb0b44b')
df = ds.query()
assert len(df) > 0
df = ds.query('SELECT fid, ST_ASGEOJSON(the_geom_webmercator) FROM data LIMIT 5')
assert len(df) == 5
def test_create_dataset():
ds = Dataset(id_hash='bb1dced4-3ae8-4908-9f36-6514ae69713f')
assert ds.id == 'bb1dced4-3ae8-4908-9f36-6514ae69713f'
assert type(ds.attributes) == dict
assert len(ds.attributes) > 0
def test_dataset_intersect():
ds = Dataset(id_hash='fee5fc38-7a62-49b8-8874-dfa31cbb1ef6')
g = Geometry(parameters={'iso': 'BRA', 'adm1': 1, 'adm2': 1})
i = ds.intersect(g)
assert i == None
def test_delete_widget():
ds = Dataset(id_hash='7cf3fab2-3fbe-4980-b572-712207b2c8c7')
w = ds.widget[0]
assert type(w.id) == str
deleted_widget= w.delete(token=API_TOKEN)
assert deleted_widget == None
def test_delete_meta():
ds = Dataset(id_hash='7cf3fab2-3fbe-4980-b572-712207b2c8c7')
m = ds.metadata[0]
assert type(m.id) == str
deleted_meta = m.delete(token=API_TOKEN)
assert deleted_meta == None
def test_delete_vocab():
ds = Dataset(id_hash='7cf3fab2-3fbe-4980-b572-712207b2c8c7')
v = ds.vocabulary[0]
assert type(v.id) == str
deleted_vocab = v.delete(token=API_TOKEN)
assert deleted_vocab == None