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