本文整理汇总了Python中openspending.model.Dataset.by_id方法的典型用法代码示例。如果您正苦于以下问题：Python Dataset.by_id方法的具体用法？Python Dataset.by_id怎么用？Python Dataset.by_id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openspending.model.Dataset的用法示例。
在下文中一共展示了Dataset.by_id方法的3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: create_view
# 需要导入模块: from openspending.model import Dataset [as 别名]
# 或者: from openspending.model.Dataset import by_id [as 别名]
def create_view(self, cls, add_filters, name, label, dimension,
breakdown=None, view_filters={}):
'''\
Create a view. The view will be computed when you call
:meth:`finalize`.
``cls``
A model class (inheriting from :class:`openspending.model.Base`)
``add_filters``
A :term:`mongodb query spec` used as a query to select the
instances of *cls* that will be used for the view.
``name``
A name for the view. This name must be unique for all views
for *cls* in an Open Spending site.
``label``
A label that can be displayed to the user.
``dimensions``
The dimensions that will be used to compute the view
``breakdown``
...
``view_filters``
...
Returns: A :class:`openspending.lib.views.View` object.
'''
log.debug("pre-aggregating view %s on %r where %r",
name, cls, view_filters)
view = View(self.dataset, name, label, dimension,
breakdown, cuts=view_filters)
view.apply_to(cls, add_filters)
view.compute()
Dataset.c.update({'name': self.dataset.name},
{'$set': {'cubes': self.dataset.get('cubes', {})}})
self.dataset = Dataset.by_id(self.dataset.name)
return view示例2: report
# 需要导入模块: from openspending.model import Dataset [as 别名]
# 或者: from openspending.model.Dataset import by_id [as 别名]
def report():
dataset_id = request.args.get("id", None)
if not dataset_id:
raise
dataset = Dataset.by_id(dataset_id)
if not dataset:
raise
lr = LoadReport(dataset)
return Response(lr.get_output(),
mimetype='application/zip',
headers={'Content-Disposition':'attachment;filename=%s.zip'%dataset.name})示例3: reload_all
# 需要导入模块: from openspending.model import Dataset [as 别名]
# 或者: from openspending.model.Dataset import by_id [as 别名]
def reload_all(**args):
"""Reload all sources with mapping. This will take a while"""
datasets = Dataset.all().all()
ids = []
for dataset in datasets:
ids.append(dataset.id)
total = 0
ran = 0
for id in ids:
dataset = Dataset.by_id(id)
total +=1
#has mapping and source
if dataset.mapping and dataset.source:
print "working on ", dataset
load_source(dataset.source.id)
ran +=1
print "Ran", ran, "out of", total