本文整理汇总了Python中dlstats.fetchers._commons.Datasets.series方法的典型用法代码示例。如果您正苦于以下问题：Python Datasets.series方法的具体用法？Python Datasets.series怎么用？Python Datasets.series使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类dlstats.fetchers._commons.Datasets的用法示例。
在下文中一共展示了Datasets.series方法的2个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: test_process_series_data
# 需要导入模块: from dlstats.fetchers._commons import Datasets [as 别名]
# 或者: from dlstats.fetchers._commons.Datasets import series [as 别名]
def test_process_series_data(self):
# nosetests -s -v dlstats.tests.fetchers.test__commons:DBSeriesTestCase.test_process_series_data
self._collections_is_empty()
provider_name = "p1"
dataset_code = "d1"
dataset_name = "d1 name"
f = Fetcher(provider_name=provider_name,
db=self.db)
d = Datasets(provider_name=provider_name,
dataset_code=dataset_code,
name=dataset_name,
last_update=datetime.now(),
doc_href="http://www.example.com",
fetcher=f,
is_load_previous_version=False)
d.dimension_list.update_entry("Scale", "Billions", "Billions")
d.dimension_list.update_entry("Country", "AFG", "AFG")
s = Series(provider_name=f.provider_name,
dataset_code=dataset_code,
last_update=datetime(2013,10,28),
bulk_size=1,
fetcher=f)
datas = FakeDatas(provider_name=provider_name,
dataset_code=dataset_code,
fetcher=f)
s.data_iterator = datas
d.series = s
d.update_database()
'''Count All series'''
self.assertEqual(self.db[constants.COL_SERIES].count(), datas.max_record)
'''Count series for this provider and dataset'''
series = self.db[constants.COL_SERIES].find({'provider_name': f.provider_name,
"dataset_code": dataset_code})
self.assertEqual(series.count(), datas.max_record)
tags.update_tags(self.db,
provider_name=f.provider_name, dataset_code=dataset_code,
col_name=constants.COL_SERIES)
'''Count series for this provider and dataset and in keys[]'''
series = self.db[constants.COL_SERIES].find({'provider_name': f.provider_name,
"dataset_code": dataset_code,
"key": {"$in": datas.keys}})
self.assertEqual(series.count(), datas.max_record)
for doc in series:
self.assertTrue("tags" in doc)
self.assertTrue(len(doc['tags']) > 0)示例2: test_revisions
# 需要导入模块: from dlstats.fetchers._commons import Datasets [as 别名]
# 或者: from dlstats.fetchers._commons.Datasets import series [as 别名]
def test_revisions(self):
# nosetests -s -v dlstats.tests.fetchers.test__commons:DBSeriesTestCase.test_revisions
self._collections_is_empty()
provider_name = "p1"
dataset_code = "d1"
dataset_name = "d1 name"
f = Fetcher(provider_name=provider_name,
db=self.db)
d = Datasets(provider_name=provider_name,
dataset_code=dataset_code,
name=dataset_name,
last_update=datetime.now(),
doc_href="http://www.example.com",
fetcher=f,
is_load_previous_version=False)
d.dimension_list.update_entry("Scale", "Billions", "Billions")
d.dimension_list.update_entry("Country", "AFG", "AFG")
s1 = Series(provider_name=f.provider_name,
dataset_code=dataset_code,
last_update=datetime(2013,4,1),
bulk_size=1,
fetcher=f)
datas1 = FakeDatas(provider_name=provider_name,
dataset_code=dataset_code,
fetcher=f)
s1.data_iterator = datas1
d.series = s1
d.update_database()
# A. modifying existing values
test_key = datas1.rows[0]['key']
first_series = self.db[constants.COL_SERIES].find_one({'key': test_key})
s2 = Series(provider_name=f.provider_name,
dataset_code=dataset_code,
last_update=datetime(2014,4,1),
bulk_size=1,
fetcher=f)
datas2 = FakeDatas(provider_name=provider_name,
dataset_code=dataset_code,
fetcher=f)
datas2.keys = datas1.keys
for i,r in enumerate(datas2.rows):
r['key'] = datas2.keys[i]
r['frequency'] = datas1.rows[i]['frequency']
r['start_date'] = datas1.rows[i]['start_date']
r['end_date'] = datas1.rows[i]['end_date']
datas2.rows[0]['values'] = deepcopy(datas1.rows[0]['values'])
datas2.rows[0]['values'][1] = str(float(datas2.rows[0]['values'][1]) + 1.5)
datas2.rows[0]['values'][8] = str(float(datas2.rows[0]['values'][8]) - 0.9)
s2.data_iterator = datas2
d.series = s2
d.update_database()
self.assertEqual(self.db[constants.COL_SERIES].count(),datas1.max_record)
test_key = datas2.keys[0]
test_series = self.db[constants.COL_SERIES].find_one({'key': test_key})
self.assertEqual(len(test_series['revisions']),2)
self.assertEqual(test_series['revisions']['1'],[{'value': datas1.rows[0]['values'][1],'release_date':s1.last_update}])
self.assertEqual(test_series['revisions']['8'],[{'value': datas1.rows[0]['values'][8],'release_date':s1.last_update}])
self.assertEqual(test_series['release_dates'][1],datetime(2014,4,1))
self.assertEqual(test_series['release_dates'][8],datetime(2014,4,1))
self.assertEqual(test_series['release_dates'][0],datetime(2013,4,1))
self.assertEqual(test_series['release_dates'][2:8],[datetime(2013,4,1) for i in range(6)])
self.assertEqual(test_series['start_date'],datas1.rows[0]['start_date'])
self.assertEqual(test_series['end_date'],datas1.rows[0]['end_date'])
# B. adding observations at the beginning of the series
s3 = Series(provider_name=f.provider_name,
dataset_code=dataset_code,
last_update=datetime(2014,4,1),
bulk_size=1,
fetcher=f)
datas3 = FakeDatas(provider_name=provider_name,
dataset_code=dataset_code,
fetcher=f)
datas3.keys = datas1.keys
for i,r in enumerate(datas3.rows):
r['key'] = datas3.keys[i]
r['frequency'] = datas1.rows[i]['frequency']
r['start_date'] = datas1.rows[i]['start_date']
r['end_date'] = datas1.rows[i]['end_date']
datas3.rows[0]['start_date'] = datas1.rows[0]['start_date'] - 2;
datas3.rows[0]['values'] = [ '10', '10'] + datas1.rows[0]['values']
datas3.rows[0]['values'][3] = str(float(datas3.rows[0]['values'][3]) + 1.5)
#.........这里部分代码省略.........