def random_project():
"""generates a random project
:rtype: dict
"""
data = Project(title=fake.sentence()[:-1],
projectid=uuid.uuid4(),
abstract=fake.paragraph(),
intellectual_merit=fake.paragraph(),
broader_impact=fake.paragraph(),
use_of_fg=fake.paragraph(),
scale_of_use=fake.paragraph(),
categories=['FutureGrid'],
keywords=['sqllite'],
primary_discipline="other",
orientation="Lot's of all make",
contact=fake.name() + "\n" + fake.address(),
url=fake.url(),
active=False,
status="pending",
resources_services=['hadoop', 'openstack'],
resources_software=['other'],
resources_clusters=['india'],
resources_provision=['paas'])
return data
def random_project():
"""generates a random project
:rtype: dict
"""
data = Project(title=fake.sentence()[:-1],
categories=['FutureGrid'],
keywords=['sqllite'],
contact=fake.name() + "\n" + fake.address(),
orientation="Lot's of all make",
primary_discipline="other",
projectid=uuid.uuid4(),
abstract=fake.paragraph(),
intellectual_merit=fake.paragraph(),
broader_impact=fake.paragraph(),
url=fake.url(),
results=fake.sentence(),
grant_organization="NSF",
grant_id="1001",
grant_url=fake.url(),
resources_services=['hadoop', 'openstack'],
resources_software=['other'],
resources_clusters=['india'],
resources_provision=['paas'],
comment=fake.sentence(),
use_of_fg=fake.paragraph(),
scale_of_use=fake.paragraph(),
comments=fake.sentence(),
loc_name=fake.country(),
loc_street=fake.street_name(),
loc_additional="None",
loc_state=fake.state(),
loc_country=fake.country(),
active=False,
status="pending")
return data
