def test_filter_auto_renew2(self):
filter = Filter()
res = ~filter.selector(dimension='country_name', value='AUSTRALIA')
res.to_dict()
res2 = filter.in_filter("D", "E", dimension='links')
expected_logic = None
self.assertEqual(res2._logic, expected_logic)
def test_filter_auto_renew3(self):
filter = Filter()
filter1 = filter.selector(dimension="country_name", value='AUSTRALIA')
filter2 = filter.selector(dimension="country_name", value='SINGAPORE')
res1 = (filter1 & filter2).to_dict()
res2 = (filter1 | filter2).to_dict()
expected1 = {'filter':
{'type': 'and', 'fields': [{
"type": "selector",
"dimension": "country_name",
"value": "AUSTRALIA"},{
"type": "selector",
"dimension": "country_name",
"value": "SINGAPORE"
}
]}}
expected2 = {'filter':
{'type': 'or', 'fields': [{
"type": "selector",
"dimension": "country_name",
"value": "AUSTRALIA"},{
"type": "selector",
"dimension": "country_name",
"value": "SINGAPORE"
}
]}}
self.assertEqual(res1, expected1)
self.assertEqual(res2, expected2)
def test_and_logic(self):
filter = Filter()
res = filter.selector(dimension='agent_gender', value='M') & filter.selector(dimension='agent_home_state', value='1') & filter.bound(dimension='agent_year_of_birth', lower=1969, ordering='numeric')
expected = {
"filter": {
"type": "and",
"fields": [{
"type": "selector",
"dimension": "agent_gender",
"value": "M"
},
{
"type": "selector",
"dimension": "agent_home_state",
"value": "1"
},
{
"type": "bound",
"dimension": "agent_year_of_birth",
"lower": 1969,
"ordering": "numeric"
}]
}
}
self.assertEqual(res.to_dict(), expected)
def test_mix_operation(self):
filter = Filter()
listOfSA2 = ['305021115', '303021053', '303021055', '303021058']
and_filter_list = list(map(lambda x: (filter.selector(dimension="origin_sa2", value=x)
& filter.selector(dimension="destination_sa2",
value=x)), listOfSA2))
combined_filters = reduce(lambda a, b: a | b, and_filter_list)
expected = {'filter': {'fields': [{'fields': [{'dimension': 'origin_sa2', 'value': '305021115', 'type': 'selector'}, {'dimension': 'destination_sa2', 'value': '305021115', 'type': 'selector'}], 'type': 'and'}, {'fields': [{'dimension': 'origin_sa2', 'value': '303021053', 'type': 'selector'}, {'dimension': 'destination_sa2', 'value': '303021053', 'type': 'selector'}], 'type': 'and'}, {'fields': [{'dimension': 'origin_sa2', 'value': '303021055', 'type': 'selector'}, {'dimension': 'destination_sa2', 'value': '303021055', 'type': 'selector'}], 'type': 'and'}, {'fields': [{'dimension': 'origin_sa2', 'value': '303021058', 'type': 'selector'}, {'dimension': 'destination_sa2', 'value': '303021058', 'type': 'selector'}], 'type': 'and'}], 'type': 'or'}}
self.assertEqual(combined_filters.to_dict(), expected)
def test_reg(self):
filter = Filter()
res = filter.reg(dimension='parent_station', pattern='NSWPTPST1[1-4]00')
expected = {
"filter": {
"type": "regex",
"dimension": "parent_station",
"pattern": "NSWPTPST1[1-4]00"
}
}
self.assertEqual(res.to_dict(), expected)
def test_selector(self):
selector = Filter()
res = selector.selector(dimension='agent_gender', value='M')
expected = {
'filter':{
'type': 'selector',
'dimension': 'agent_gender',
'value': 'M'
}
}
self.assertEqual(res.to_dict(), expected)
def test_like(self):
filter = Filter()
res = filter.like(dimension='origin_building', pattern='%MALL%')
expected = {
"filter": {
"type": "like",
"dimension": "origin_building",
"pattern": "%MALL%"
}
}
self.assertEqual(res.to_dict(), expected)
def test_in_filter(self):
filter = Filter()
res = filter.in_filter("A", "B", "C", dimension='links')
expected = {
'filter': {
'type': 'in',
'dimension': 'links',
'values': ['A', 'B', 'C']
}
}
self.assertEqual(res.to_dict(), expected)
def test_bound(self):
filter = Filter()
res = filter.bound(dimension='duration', lower=60, upper=180, ordering='numeric')
expected = {
"filter": {
"type": "bound",
"dimension": "duration",
"lower": 60,
"upper": 180,
"ordering": "numeric"
}
}
self.assertEqual(res.to_dict(), expected)
def test_filter_auto_renew(self):
filter = Filter()
res = filter.in_filter("A", "B", "C", dimension='links')
res.to_dict()
res2 = filter.in_filter("D","E", dimension='links')
expected2 = {
'filter': {
'type': 'in',
'dimension': 'links',
'values': ['D', 'E']
}
}
self.assertEqual(res2.to_dict(), expected2)
def test_interval1(self):
filter = Filter()
res = filter.interval(
"2019-08-01T16:00:00.000+10/2019-08-01T18:59:59.999+10",
dimension='__time')
expected = {
"filter": {
"type": "interval",
"dimension": "__time",
"intervals":
["2019-08-01T16:00:00.000+10/2019-08-01T18:59:59.999+10"]
}
}
self.assertEqual(res.to_dict(), expected)
def test_not_logic(self):
filter1 = Filter()
res = ~filter1.selector(dimension='country_name', value='AUSTRALIA')
expected = {
"filter":{
"type": "not",
"field": {
"type": "selector",
"dimension": "country_name",
"value": "AUSTRALIA"
}
}
}
self.assertEqual(res.to_dict(), expected)
def test_extraction_fn_in_filter(self):
filter1 = Filter()
extraction = ExtractionFn(typ='timeFormat')
res = filter1.selector(dimension='__time', value='AUSTRALIA', extraction_fn=extraction(format="EEEE", timezone="Australia/Sydney"))
expected = {
'filter': {
'dimension': '__time',
'value': 'AUSTRALIA',
'type': 'selector',
'extractionFn': {
'format': 'EEEE',
'timeZone': 'Australia/Sydney',
'locale': 'en',
'type': 'timeFormat'}
}
}
self.assertEqual(res.to_dict(), expected)
def test_query3(self):
query = BasicQuery('linkmeta')
query.dates(begin_date="2019-07-01", end_date="2019-07-28")
query.time_series_reference("arrival")
query.granularity(period="P7D")
filter = Filter()
query.filter(
filter.in_filter("VIC17483860",
"VIC6052402",
"NSW500187142",
dimension="link_id"))
query.aggregate(metric="unique_agents", described_as="unique_agents")
query.aggregate(metric="total_records")
query.dumps()
expected = {
"dates": {
"beginDate": "2019-07-01",
"endDate": "2019-07-28",
"type": "range"
},
"aggregations": [{
"metric": "unique_agents",
"type": "hyperUnique",
"describedAs": "unique_agents"
}, {
"metric": "total_records",
"type": "longSum"
}],
"queryGranularity": {
"period": "P7D",
"type": "period",
"timeZone": "Australia/Sydney"
},
"filter": {
"dimension": "link_id",
"type": "in",
"values": ["VIC17483860", "VIC6052402", "NSW500187142"]
},
"timeSeriesReference":
"arrival"
}
self.assertEqual(query._req, expected)
def test_or_logic(self):
filter = Filter()
res = filter.selector(dimension='sa2', value='117011325') \
| filter.selector(dimension='sa2', value='210051248')
expected = {
"filter": {
"type": "or",
"fields": [{
"type": "selector",
"dimension": "sa2",
"value": "117011325"
},
{
"type": "selector",
"dimension": "sa2",
"value": "210051248"
}]
}
}
self.assertEqual(res.to_dict(), expected)
def test_query4(self):
extraction = ExtractionFn(typ='timeFormat')
extract = extraction(format='EEEE', timezone='Australia/Sydney')
filter = Filter()
filter = filter.selector(dimension='__time', extraction_fn=extract, value="Monday") \
| filter.selector(dimension='__time', extraction_fn=extract, value="Tuesday") \
| filter.selector(dimension='__time', extraction_fn=extract, value="Wednesday") \
| filter.selector(dimension='__time', extraction_fn=extract, value="Thursday") \
| filter.selector(dimension='__time', extraction_fn=extract, value="Friday")
query = BasicQuery('linkmeta')
query.dates(begin_date="2019-07-07", end_date="2019-08-03")
query.location(location_type="locationHierarchyLevel",
level_type="sa2",
id="117031337")
query.filter(filt=filter)
query.aggregate(metric="unique_agents", described_as="unique_agents")
query.granularity(period="P7D")
query.dumps()
expected = {
"dates": {
"type": "range",
"beginDate": "2019-07-07",
"endDate": "2019-08-03"
},
"location": {
"locationType": "locationHierarchyLevel",
"levelType": "sa2",
"id": "117031337"
},
"filter": {
"type":
"or",
"fields": [{
"type": "selector",
"dimension": "__time",
"value": "Monday",
"extractionFn": {
"type": "timeFormat",
"format": "EEEE",
"timeZone": "Australia/Sydney",
"locale": "en"
}
}, {
"type": "selector",
"dimension": "__time",
"value": "Tuesday",
"extractionFn": {
"type": "timeFormat",
"format": "EEEE",
"timeZone": "Australia/Sydney",
"locale": "en"
}
}, {
"type": "selector",
"dimension": "__time",
"value": "Wednesday",
"extractionFn": {
"type": "timeFormat",
"format": "EEEE",
"timeZone": "Australia/Sydney",
"locale": "en"
}
}, {
"type": "selector",
"dimension": "__time",
"value": "Thursday",
"extractionFn": {
"type": "timeFormat",
"format": "EEEE",
"timeZone": "Australia/Sydney",
"locale": "en"
}
}, {
"type": "selector",
"dimension": "__time",
"value": "Friday",
"extractionFn": {
"type": "timeFormat",
"format": "EEEE",
"timeZone": "Australia/Sydney",
"locale": "en"
}
}]
},
"aggregations": [{
"metric": "unique_agents",
"type": "hyperUnique",
"describedAs": "unique_agents"
}],
"queryGranularity": {
"type": "period",
"period": "P7D",
"timeZone": "Australia/Sydney"
}
}
self.assertEqual(query._req, expected)