本文整理汇总了Python中openspending.model.dataset.Dataset.as_dict方法的典型用法代码示例。如果您正苦于以下问题：Python Dataset.as_dict方法的具体用法？Python Dataset.as_dict怎么用？Python Dataset.as_dict使用的例子？那么, 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.Dataset的用法示例。
在下文中一共展示了Dataset.as_dict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
# 需要导入模块: from openspending.model.dataset import Dataset [as 别名]
# 或者: from openspending.model.dataset.Dataset import as_dict [as 别名]
def create(self):
"""
Adds a new dataset dynamically through a POST request
"""
# User must be authenticated so we should have a user object in
# c.account, if not abort with error message
if not c.account:
abort(status_code=400, detail='user not authenticated')
# Check if the params are there ('metadata', 'csv_file')
if len(request.params) != 2:
abort(status_code=400, detail='incorrect number of params')
metadata = request.params['metadata'] \
if 'metadata' in request.params \
else abort(status_code=400, detail='metadata is missing')
csv_file = request.params['csv_file'] \
if 'csv_file' in request.params \
else abort(status_code=400, detail='csv_file is missing')
# We proceed with the dataset
try:
model = json.load(urllib2.urlopen(metadata))
except:
abort(status_code=400, detail='JSON model could not be parsed')
try:
log.info("Validating model")
model = validate_model(model)
except Invalid as i:
log.error("Errors occured during model validation:")
for field, error in i.asdict().items():
log.error("%s: %s", field, error)
abort(status_code=400, detail='Model is not well formed')
dataset = Dataset.by_name(model['dataset']['name'])
if dataset is None:
dataset = Dataset(model)
require.dataset.create()
dataset.managers.append(c.account)
dataset.private = True # Default value
db.session.add(dataset)
else:
require.dataset.update(dataset)
log.info("Dataset: %s", dataset.name)
source = Source(dataset=dataset, creator=c.account, url=csv_file)
log.info(source)
for source_ in dataset.sources:
if source_.url == csv_file:
source = source_
break
db.session.add(source)
db.session.commit()
# Send loading of source into celery queue
load_source.delay(source.id)
return to_jsonp(dataset_apply_links(dataset.as_dict()))示例2: load_with_model_and_csv
# 需要导入模块: from openspending.model.dataset import Dataset [as 别名]
# 或者: from openspending.model.dataset.Dataset import as_dict [as 别名]
def load_with_model_and_csv(self, metadata, csv_file, private):
"""
Load a dataset using a metadata model file and a csv file
"""
if metadata is None:
response.status = 400
return to_jsonp({'errors': 'metadata is missing'})
if csv_file is None:
response.status = 400
return to_jsonp({'errors': 'csv_file is missing'})
# We proceed with the dataset
try:
model = json.load(urllib2.urlopen(metadata))
except:
response.status = 400
return to_jsonp({'errors': 'JSON model could not be parsed'})
try:
log.info("Validating model")
model = validate_model(model)
except Invalid as i:
log.error("Errors occured during model validation:")
for field, error in i.asdict().items():
log.error("%s: %s", field, error)
response.status = 400
return to_jsonp({'errors': 'Model is not well formed'})
dataset = Dataset.by_name(model['dataset']['name'])
if dataset is None:
dataset = Dataset(model)
require.dataset.create()
dataset.managers.append(c.account)
dataset.private = private
db.session.add(dataset)
else:
require.dataset.update(dataset)
log.info("Dataset: %s", dataset.name)
source = Source(dataset=dataset, creator=c.account,
url=csv_file)
log.info(source)
for source_ in dataset.sources:
if source_.url == csv_file:
source = source_
break
db.session.add(source)
db.session.commit()
# Send loading of source into celery queue
load_source.delay(source.id)
return to_jsonp(dataset_apply_links(dataset.as_dict()))示例3: create
# 需要导入模块: from openspending.model.dataset import Dataset [as 别名]
# 或者: from openspending.model.dataset.Dataset import as_dict [as 别名]
def create(self):
"""
Adds a new dataset dynamically through a POST request
"""
# User must be authenticated so we should have a user object in
# c.account, if not abort with error message
if not c.account:
abort(status_code=400, detail='user not authenticated')
# Parse the loading api parameters to get them into the right format
parser = LoadingAPIParamParser(request.params)
params, errors = parser.parse()
if errors:
response.status = 400
return to_jsonp({'errors': errors})
if params['metadata'] is None:
response.status = 400
return to_jsonp({'errors': 'metadata is missing'})
if params['csv_file'] is None:
response.status = 400
return to_jsonp({'errors': 'csv_file is missing'})
# We proceed with the dataset
try:
model = json.load(urllib2.urlopen(params['metadata']))
except:
response.status = 400
return to_jsonp({'errors': 'JSON model could not be parsed'})
try:
log.info("Validating model")
model = validate_model(model)
except Invalid as i:
log.error("Errors occured during model validation:")
for field, error in i.asdict().items():
log.error("%s: %s", field, error)
response.status = 400
return to_jsonp({'errors': 'Model is not well formed'})
dataset = Dataset.by_name(model['dataset']['name'])
if dataset is None:
dataset = Dataset(model)
require.dataset.create()
dataset.managers.append(c.account)
dataset.private = params['private']
db.session.add(dataset)
else:
require.dataset.update(dataset)
log.info("Dataset: %s", dataset.name)
source = Source(dataset=dataset, creator=c.account,
url=params['csv_file'])
log.info(source)
for source_ in dataset.sources:
if source_.url == params['csv_file']:
source = source_
break
db.session.add(source)
db.session.commit()
# Send loading of source into celery queue
load_source.delay(source.id)
return to_jsonp(dataset_apply_links(dataset.as_dict()))