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hydraplatform/hydra-base | hydra_base/lib/template.py | get_types_by_attr | def get_types_by_attr(resource, template_id=None):
"""
Using the attributes of the resource, get all the
types that this resource matches.
@returns a dictionary, keyed on the template name, with the
value being the list of type names which match the resources
attributes.
"""
resource_type_templates = []
#Create a list of all of this resources attributes.
attr_ids = []
for res_attr in resource.attributes:
attr_ids.append(res_attr.attr_id)
all_resource_attr_ids = set(attr_ids)
all_types = db.DBSession.query(TemplateType).options(joinedload_all('typeattrs')).filter(TemplateType.resource_type==resource.ref_key)
if template_id is not None:
all_types = all_types.filter(TemplateType.template_id==template_id)
all_types = all_types.all()
#tmpl type attrs must be a subset of the resource's attrs
for ttype in all_types:
type_attr_ids = []
for typeattr in ttype.typeattrs:
type_attr_ids.append(typeattr.attr_id)
if set(type_attr_ids).issubset(all_resource_attr_ids):
resource_type_templates.append(ttype)
return resource_type_templates | python | def get_types_by_attr(resource, template_id=None):
"""
Using the attributes of the resource, get all the
types that this resource matches.
@returns a dictionary, keyed on the template name, with the
value being the list of type names which match the resources
attributes.
"""
resource_type_templates = []
#Create a list of all of this resources attributes.
attr_ids = []
for res_attr in resource.attributes:
attr_ids.append(res_attr.attr_id)
all_resource_attr_ids = set(attr_ids)
all_types = db.DBSession.query(TemplateType).options(joinedload_all('typeattrs')).filter(TemplateType.resource_type==resource.ref_key)
if template_id is not None:
all_types = all_types.filter(TemplateType.template_id==template_id)
all_types = all_types.all()
#tmpl type attrs must be a subset of the resource's attrs
for ttype in all_types:
type_attr_ids = []
for typeattr in ttype.typeattrs:
type_attr_ids.append(typeattr.attr_id)
if set(type_attr_ids).issubset(all_resource_attr_ids):
resource_type_templates.append(ttype)
return resource_type_templates | [
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hydraplatform/hydra-base | hydra_base/lib/template.py | _get_attr_by_name_and_dimension | def _get_attr_by_name_and_dimension(name, dimension_id):
"""
Search for an attribute with the given name and dimension_id.
If such an attribute does not exist, create one.
"""
attr = db.DBSession.query(Attr).filter(Attr.name==name, Attr.dimension_id==dimension_id).first()
if attr is None:
# In this case the attr does not exists so we must create it
attr = Attr()
attr.dimension_id = dimension_id
attr.name = name
log.debug("Attribute not found, creating new attribute: name:%s, dimen:%s",
attr.name, attr.dimension_id)
db.DBSession.add(attr)
return attr | python | def _get_attr_by_name_and_dimension(name, dimension_id):
"""
Search for an attribute with the given name and dimension_id.
If such an attribute does not exist, create one.
"""
attr = db.DBSession.query(Attr).filter(Attr.name==name, Attr.dimension_id==dimension_id).first()
if attr is None:
# In this case the attr does not exists so we must create it
attr = Attr()
attr.dimension_id = dimension_id
attr.name = name
log.debug("Attribute not found, creating new attribute: name:%s, dimen:%s",
attr.name, attr.dimension_id)
db.DBSession.add(attr)
return attr | [
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hydraplatform/hydra-base | hydra_base/lib/template.py | get_template_as_xml | def get_template_as_xml(template_id,**kwargs):
"""
Turn a template into an xml template
"""
template_xml = etree.Element("template_definition")
template_i = db.DBSession.query(Template).filter(
Template.id==template_id).options(
#joinedload_all('templatetypes.typeattrs.default_dataset.metadata')
joinedload('templatetypes').joinedload('typeattrs').joinedload('default_dataset').joinedload('metadata')
).one()
template_name = etree.SubElement(template_xml, "template_name")
template_name.text = template_i.name
template_description = etree.SubElement(template_xml, "template_description")
template_description.text = template_i.description
resources = etree.SubElement(template_xml, "resources")
for type_i in template_i.templatetypes:
xml_resource = etree.SubElement(resources, "resource")
resource_type = etree.SubElement(xml_resource, "type")
resource_type.text = type_i.resource_type
name = etree.SubElement(xml_resource, "name")
name.text = type_i.name
description = etree.SubElement(xml_resource, "description")
description.text = type_i.description
alias = etree.SubElement(xml_resource, "alias")
alias.text = type_i.alias
if type_i.layout is not None and type_i.layout != "":
layout = _get_layout_as_etree(type_i.layout)
xml_resource.append(layout)
for type_attr in type_i.typeattrs:
attr = _make_attr_element_from_typeattr(xml_resource, type_attr)
resources.append(xml_resource)
xml_string = etree.tostring(template_xml, encoding="unicode")
return xml_string | python | def get_template_as_xml(template_id,**kwargs):
"""
Turn a template into an xml template
"""
template_xml = etree.Element("template_definition")
template_i = db.DBSession.query(Template).filter(
Template.id==template_id).options(
#joinedload_all('templatetypes.typeattrs.default_dataset.metadata')
joinedload('templatetypes').joinedload('typeattrs').joinedload('default_dataset').joinedload('metadata')
).one()
template_name = etree.SubElement(template_xml, "template_name")
template_name.text = template_i.name
template_description = etree.SubElement(template_xml, "template_description")
template_description.text = template_i.description
resources = etree.SubElement(template_xml, "resources")
for type_i in template_i.templatetypes:
xml_resource = etree.SubElement(resources, "resource")
resource_type = etree.SubElement(xml_resource, "type")
resource_type.text = type_i.resource_type
name = etree.SubElement(xml_resource, "name")
name.text = type_i.name
description = etree.SubElement(xml_resource, "description")
description.text = type_i.description
alias = etree.SubElement(xml_resource, "alias")
alias.text = type_i.alias
if type_i.layout is not None and type_i.layout != "":
layout = _get_layout_as_etree(type_i.layout)
xml_resource.append(layout)
for type_attr in type_i.typeattrs:
attr = _make_attr_element_from_typeattr(xml_resource, type_attr)
resources.append(xml_resource)
xml_string = etree.tostring(template_xml, encoding="unicode")
return xml_string | [
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hydraplatform/hydra-base | hydra_base/lib/template.py | import_template_json | def import_template_json(template_json_string,allow_update=True, **kwargs):
"""
Add the template, type and typeattrs described
in a JSON file.
Delete type, typeattr entries in the DB that are not in the XML file
The assumption is that they have been deleted and are no longer required.
The allow_update indicates whether an existing template of the same name should
be updated, or whether it should throw an 'existing name' error.
"""
user_id = kwargs.get('user_id')
try:
template_dict = json.loads(template_json_string)
except:
raise HydraError("Unable to parse JSON string. Plese ensure it is JSON compatible.")
return import_template_dict(template_dict, allow_update=allow_update, user_id=user_id) | python | def import_template_json(template_json_string,allow_update=True, **kwargs):
"""
Add the template, type and typeattrs described
in a JSON file.
Delete type, typeattr entries in the DB that are not in the XML file
The assumption is that they have been deleted and are no longer required.
The allow_update indicates whether an existing template of the same name should
be updated, or whether it should throw an 'existing name' error.
"""
user_id = kwargs.get('user_id')
try:
template_dict = json.loads(template_json_string)
except:
raise HydraError("Unable to parse JSON string. Plese ensure it is JSON compatible.")
return import_template_dict(template_dict, allow_update=allow_update, user_id=user_id) | [
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hydraplatform/hydra-base | hydra_base/lib/template.py | set_network_template | def set_network_template(template_id, network_id, **kwargs):
"""
Apply an existing template to a network. Used when a template has changed, and additional attributes
must be added to the network's elements.
"""
resource_types = []
#There should only ever be one matching type, but if there are more,
#all we can do is pick the first one.
try:
network_type = db.DBSession.query(ResourceType).filter(ResourceType.ref_key=='NETWORK',
ResourceType.network_id==network_id,
ResourceType.type_id==TemplateType.type_id,
TemplateType.template_id==template_id).one()
resource_types.append(network_type)
except NoResultFound:
log.debug("No network type to set.")
pass
node_types = db.DBSession.query(ResourceType).filter(ResourceType.ref_key=='NODE',
ResourceType.node_id==Node.node_id,
Node.network_id==network_id,
ResourceType.type_id==TemplateType.type_id,
TemplateType.template_id==template_id).all()
link_types = db.DBSession.query(ResourceType).filter(ResourceType.ref_key=='LINK',
ResourceType.link_id==Link.link_id,
Link.network_id==network_id,
ResourceType.type_id==TemplateType.type_id,
TemplateType.template_id==template_id).all()
group_types = db.DBSession.query(ResourceType).filter(ResourceType.ref_key=='GROUP',
ResourceType.group_id==ResourceGroup.group_id,
ResourceGroup.network_id==network_id,
ResourceType.type_id==TemplateType.type_id,
TemplateType.template_id==template_id).all()
resource_types.extend(node_types)
resource_types.extend(link_types)
resource_types.extend(group_types)
assign_types_to_resources(resource_types)
log.debug("Finished setting network template") | python | def set_network_template(template_id, network_id, **kwargs):
"""
Apply an existing template to a network. Used when a template has changed, and additional attributes
must be added to the network's elements.
"""
resource_types = []
#There should only ever be one matching type, but if there are more,
#all we can do is pick the first one.
try:
network_type = db.DBSession.query(ResourceType).filter(ResourceType.ref_key=='NETWORK',
ResourceType.network_id==network_id,
ResourceType.type_id==TemplateType.type_id,
TemplateType.template_id==template_id).one()
resource_types.append(network_type)
except NoResultFound:
log.debug("No network type to set.")
pass
node_types = db.DBSession.query(ResourceType).filter(ResourceType.ref_key=='NODE',
ResourceType.node_id==Node.node_id,
Node.network_id==network_id,
ResourceType.type_id==TemplateType.type_id,
TemplateType.template_id==template_id).all()
link_types = db.DBSession.query(ResourceType).filter(ResourceType.ref_key=='LINK',
ResourceType.link_id==Link.link_id,
Link.network_id==network_id,
ResourceType.type_id==TemplateType.type_id,
TemplateType.template_id==template_id).all()
group_types = db.DBSession.query(ResourceType).filter(ResourceType.ref_key=='GROUP',
ResourceType.group_id==ResourceGroup.group_id,
ResourceGroup.network_id==network_id,
ResourceType.type_id==TemplateType.type_id,
TemplateType.template_id==template_id).all()
resource_types.extend(node_types)
resource_types.extend(link_types)
resource_types.extend(group_types)
assign_types_to_resources(resource_types)
log.debug("Finished setting network template") | [
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hydraplatform/hydra-base | hydra_base/lib/template.py | remove_template_from_network | def remove_template_from_network(network_id, template_id, remove_attrs, **kwargs):
"""
Remove all resource types in a network relating to the specified
template.
remove_attrs
Flag to indicate whether the attributes associated with the template
types should be removed from the resources in the network. These will
only be removed if they are not shared with another template on the network
"""
try:
network = db.DBSession.query(Network).filter(Network.id==network_id).one()
except NoResultFound:
raise HydraError("Network %s not found"%network_id)
try:
template = db.DBSession.query(Template).filter(Template.id==template_id).one()
except NoResultFound:
raise HydraError("Template %s not found"%template_id)
type_ids = [tmpltype.id for tmpltype in template.templatetypes]
node_ids = [n.id for n in network.nodes]
link_ids = [l.id for l in network.links]
group_ids = [g.id for g in network.resourcegroups]
if remove_attrs == 'Y':
#find the attributes to remove
resource_attrs_to_remove = _get_resources_to_remove(network, template)
for n in network.nodes:
resource_attrs_to_remove.extend(_get_resources_to_remove(n, template))
for l in network.links:
resource_attrs_to_remove.extend(_get_resources_to_remove(l, template))
for g in network.resourcegroups:
resource_attrs_to_remove.extend(_get_resources_to_remove(g, template))
for ra in resource_attrs_to_remove:
db.DBSession.delete(ra)
resource_types = db.DBSession.query(ResourceType).filter(
and_(or_(
ResourceType.network_id==network_id,
ResourceType.node_id.in_(node_ids),
ResourceType.link_id.in_(link_ids),
ResourceType.group_id.in_(group_ids),
), ResourceType.type_id.in_(type_ids))).all()
for resource_type in resource_types:
db.DBSession.delete(resource_type)
db.DBSession.flush() | python | def remove_template_from_network(network_id, template_id, remove_attrs, **kwargs):
"""
Remove all resource types in a network relating to the specified
template.
remove_attrs
Flag to indicate whether the attributes associated with the template
types should be removed from the resources in the network. These will
only be removed if they are not shared with another template on the network
"""
try:
network = db.DBSession.query(Network).filter(Network.id==network_id).one()
except NoResultFound:
raise HydraError("Network %s not found"%network_id)
try:
template = db.DBSession.query(Template).filter(Template.id==template_id).one()
except NoResultFound:
raise HydraError("Template %s not found"%template_id)
type_ids = [tmpltype.id for tmpltype in template.templatetypes]
node_ids = [n.id for n in network.nodes]
link_ids = [l.id for l in network.links]
group_ids = [g.id for g in network.resourcegroups]
if remove_attrs == 'Y':
#find the attributes to remove
resource_attrs_to_remove = _get_resources_to_remove(network, template)
for n in network.nodes:
resource_attrs_to_remove.extend(_get_resources_to_remove(n, template))
for l in network.links:
resource_attrs_to_remove.extend(_get_resources_to_remove(l, template))
for g in network.resourcegroups:
resource_attrs_to_remove.extend(_get_resources_to_remove(g, template))
for ra in resource_attrs_to_remove:
db.DBSession.delete(ra)
resource_types = db.DBSession.query(ResourceType).filter(
and_(or_(
ResourceType.network_id==network_id,
ResourceType.node_id.in_(node_ids),
ResourceType.link_id.in_(link_ids),
ResourceType.group_id.in_(group_ids),
), ResourceType.type_id.in_(type_ids))).all()
for resource_type in resource_types:
db.DBSession.delete(resource_type)
db.DBSession.flush() | [
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hydraplatform/hydra-base | hydra_base/lib/template.py | _get_resources_to_remove | def _get_resources_to_remove(resource, template):
"""
Given a resource and a template being removed, identify the resource attribtes
which can be removed.
"""
type_ids = [tmpltype.id for tmpltype in template.templatetypes]
node_attr_ids = dict([(ra.attr_id, ra) for ra in resource.attributes])
attrs_to_remove = []
attrs_to_keep = []
for nt in resource.types:
if nt.templatetype.id in type_ids:
for ta in nt.templatetype.typeattrs:
if node_attr_ids.get(ta.attr_id):
attrs_to_remove.append(node_attr_ids[ta.attr_id])
else:
for ta in nt.templatetype.typeattrs:
if node_attr_ids.get(ta.attr_id):
attrs_to_keep.append(node_attr_ids[ta.attr_id])
#remove any of the attributes marked for deletion as they are
#marked for keeping based on being in another type.
final_attrs_to_remove = set(attrs_to_remove) - set(attrs_to_keep)
return list(final_attrs_to_remove) | python | def _get_resources_to_remove(resource, template):
"""
Given a resource and a template being removed, identify the resource attribtes
which can be removed.
"""
type_ids = [tmpltype.id for tmpltype in template.templatetypes]
node_attr_ids = dict([(ra.attr_id, ra) for ra in resource.attributes])
attrs_to_remove = []
attrs_to_keep = []
for nt in resource.types:
if nt.templatetype.id in type_ids:
for ta in nt.templatetype.typeattrs:
if node_attr_ids.get(ta.attr_id):
attrs_to_remove.append(node_attr_ids[ta.attr_id])
else:
for ta in nt.templatetype.typeattrs:
if node_attr_ids.get(ta.attr_id):
attrs_to_keep.append(node_attr_ids[ta.attr_id])
#remove any of the attributes marked for deletion as they are
#marked for keeping based on being in another type.
final_attrs_to_remove = set(attrs_to_remove) - set(attrs_to_keep)
return list(final_attrs_to_remove) | [
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hydraplatform/hydra-base | hydra_base/lib/template.py | get_matching_resource_types | def get_matching_resource_types(resource_type, resource_id,**kwargs):
"""
Get the possible types of a resource by checking its attributes
against all available types.
@returns A list of TypeSummary objects.
"""
resource_i = None
if resource_type == 'NETWORK':
resource_i = db.DBSession.query(Network).filter(Network.id==resource_id).one()
elif resource_type == 'NODE':
resource_i = db.DBSession.query(Node).filter(Node.id==resource_id).one()
elif resource_type == 'LINK':
resource_i = db.DBSession.query(Link).filter(Link.id==resource_id).one()
elif resource_type == 'GROUP':
resource_i = db.DBSession.query(ResourceGroup).filter(ResourceGroup.id==resource_id).one()
matching_types = get_types_by_attr(resource_i)
return matching_types | python | def get_matching_resource_types(resource_type, resource_id,**kwargs):
"""
Get the possible types of a resource by checking its attributes
against all available types.
@returns A list of TypeSummary objects.
"""
resource_i = None
if resource_type == 'NETWORK':
resource_i = db.DBSession.query(Network).filter(Network.id==resource_id).one()
elif resource_type == 'NODE':
resource_i = db.DBSession.query(Node).filter(Node.id==resource_id).one()
elif resource_type == 'LINK':
resource_i = db.DBSession.query(Link).filter(Link.id==resource_id).one()
elif resource_type == 'GROUP':
resource_i = db.DBSession.query(ResourceGroup).filter(ResourceGroup.id==resource_id).one()
matching_types = get_types_by_attr(resource_i)
return matching_types | [
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hydraplatform/hydra-base | hydra_base/lib/template.py | check_type_compatibility | def check_type_compatibility(type_1_id, type_2_id):
"""
When applying a type to a resource, it may be the case that the resource already
has an attribute specified in the new type, but the template which defines this
pre-existing attribute has a different unit specification to the new template.
This function checks for any situations where different types specify the same
attributes, but with different units.
"""
errors = []
type_1 = db.DBSession.query(TemplateType).filter(TemplateType.id==type_1_id).options(joinedload_all('typeattrs')).one()
type_2 = db.DBSession.query(TemplateType).filter(TemplateType.id==type_2_id).options(joinedload_all('typeattrs')).one()
template_1_name = type_1.template.name
template_2_name = type_2.template.name
type_1_attrs=set([t.attr_id for t in type_1.typeattrs])
type_2_attrs=set([t.attr_id for t in type_2.typeattrs])
shared_attrs = type_1_attrs.intersection(type_2_attrs)
if len(shared_attrs) == 0:
return []
type_1_dict = {}
for t in type_1.typeattrs:
if t.attr_id in shared_attrs:
type_1_dict[t.attr_id]=t
for ta in type_2.typeattrs:
type_2_unit_id = ta.unit_id
type_1_unit_id = type_1_dict[ta.attr_id].unit_id
fmt_dict = {
'template_1_name': template_1_name,
'template_2_name': template_2_name,
'attr_name': ta.attr.name,
'type_1_unit_id': type_1_unit_id,
'type_2_unit_id': type_2_unit_id,
'type_name' : type_1.name
}
if type_1_unit_id is None and type_2_unit_id is not None:
errors.append("Type %(type_name)s in template %(template_1_name)s"
" stores %(attr_name)s with no units, while template"
"%(template_2_name)s stores it with unit %(type_2_unit_id)s"%fmt_dict)
elif type_1_unit_id is not None and type_2_unit_id is None:
errors.append("Type %(type_name)s in template %(template_1_name)s"
" stores %(attr_name)s in %(type_1_unit_id)s."
" Template %(template_2_name)s stores it with no unit."%fmt_dict)
elif type_1_unit_id != type_2_unit_id:
errors.append("Type %(type_name)s in template %(template_1_name)s"
" stores %(attr_name)s in %(type_1_unit_id)s, while"
" template %(template_2_name)s stores it in %(type_2_unit_id)s"%fmt_dict)
return errors | python | def check_type_compatibility(type_1_id, type_2_id):
"""
When applying a type to a resource, it may be the case that the resource already
has an attribute specified in the new type, but the template which defines this
pre-existing attribute has a different unit specification to the new template.
This function checks for any situations where different types specify the same
attributes, but with different units.
"""
errors = []
type_1 = db.DBSession.query(TemplateType).filter(TemplateType.id==type_1_id).options(joinedload_all('typeattrs')).one()
type_2 = db.DBSession.query(TemplateType).filter(TemplateType.id==type_2_id).options(joinedload_all('typeattrs')).one()
template_1_name = type_1.template.name
template_2_name = type_2.template.name
type_1_attrs=set([t.attr_id for t in type_1.typeattrs])
type_2_attrs=set([t.attr_id for t in type_2.typeattrs])
shared_attrs = type_1_attrs.intersection(type_2_attrs)
if len(shared_attrs) == 0:
return []
type_1_dict = {}
for t in type_1.typeattrs:
if t.attr_id in shared_attrs:
type_1_dict[t.attr_id]=t
for ta in type_2.typeattrs:
type_2_unit_id = ta.unit_id
type_1_unit_id = type_1_dict[ta.attr_id].unit_id
fmt_dict = {
'template_1_name': template_1_name,
'template_2_name': template_2_name,
'attr_name': ta.attr.name,
'type_1_unit_id': type_1_unit_id,
'type_2_unit_id': type_2_unit_id,
'type_name' : type_1.name
}
if type_1_unit_id is None and type_2_unit_id is not None:
errors.append("Type %(type_name)s in template %(template_1_name)s"
" stores %(attr_name)s with no units, while template"
"%(template_2_name)s stores it with unit %(type_2_unit_id)s"%fmt_dict)
elif type_1_unit_id is not None and type_2_unit_id is None:
errors.append("Type %(type_name)s in template %(template_1_name)s"
" stores %(attr_name)s in %(type_1_unit_id)s."
" Template %(template_2_name)s stores it with no unit."%fmt_dict)
elif type_1_unit_id != type_2_unit_id:
errors.append("Type %(type_name)s in template %(template_1_name)s"
" stores %(attr_name)s in %(type_1_unit_id)s, while"
" template %(template_2_name)s stores it in %(type_2_unit_id)s"%fmt_dict)
return errors | [
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hydraplatform/hydra-base | hydra_base/lib/template.py | assign_type_to_resource | def assign_type_to_resource(type_id, resource_type, resource_id,**kwargs):
"""Assign new type to a resource. This function checks if the necessary
attributes are present and adds them if needed. Non existing attributes
are also added when the type is already assigned. This means that this
function can also be used to update resources, when a resource type has
changed.
"""
if resource_type == 'NETWORK':
resource = db.DBSession.query(Network).filter(Network.id==resource_id).one()
elif resource_type == 'NODE':
resource = db.DBSession.query(Node).filter(Node.id==resource_id).one()
elif resource_type == 'LINK':
resource = db.DBSession.query(Link).filter(Link.id==resource_id).one()
elif resource_type == 'GROUP':
resource = db.DBSession.query(ResourceGroup).filter(ResourceGroup.id==resource_id).one()
res_attrs, res_type, res_scenarios = set_resource_type(resource, type_id, **kwargs)
type_i = db.DBSession.query(TemplateType).filter(TemplateType.id==type_id).one()
if resource_type != type_i.resource_type:
raise HydraError("Cannot assign a %s type to a %s"%
(type_i.resource_type,resource_type))
if res_type is not None:
db.DBSession.bulk_insert_mappings(ResourceType, [res_type])
if len(res_attrs) > 0:
db.DBSession.bulk_insert_mappings(ResourceAttr, res_attrs)
if len(res_scenarios) > 0:
db.DBSession.bulk_insert_mappings(ResourceScenario, res_scenarios)
#Make DBsession 'dirty' to pick up the inserts by doing a fake delete.
db.DBSession.query(Attr).filter(Attr.id==None).delete()
db.DBSession.flush()
return db.DBSession.query(TemplateType).filter(TemplateType.id==type_id).one() | python | def assign_type_to_resource(type_id, resource_type, resource_id,**kwargs):
"""Assign new type to a resource. This function checks if the necessary
attributes are present and adds them if needed. Non existing attributes
are also added when the type is already assigned. This means that this
function can also be used to update resources, when a resource type has
changed.
"""
if resource_type == 'NETWORK':
resource = db.DBSession.query(Network).filter(Network.id==resource_id).one()
elif resource_type == 'NODE':
resource = db.DBSession.query(Node).filter(Node.id==resource_id).one()
elif resource_type == 'LINK':
resource = db.DBSession.query(Link).filter(Link.id==resource_id).one()
elif resource_type == 'GROUP':
resource = db.DBSession.query(ResourceGroup).filter(ResourceGroup.id==resource_id).one()
res_attrs, res_type, res_scenarios = set_resource_type(resource, type_id, **kwargs)
type_i = db.DBSession.query(TemplateType).filter(TemplateType.id==type_id).one()
if resource_type != type_i.resource_type:
raise HydraError("Cannot assign a %s type to a %s"%
(type_i.resource_type,resource_type))
if res_type is not None:
db.DBSession.bulk_insert_mappings(ResourceType, [res_type])
if len(res_attrs) > 0:
db.DBSession.bulk_insert_mappings(ResourceAttr, res_attrs)
if len(res_scenarios) > 0:
db.DBSession.bulk_insert_mappings(ResourceScenario, res_scenarios)
#Make DBsession 'dirty' to pick up the inserts by doing a fake delete.
db.DBSession.query(Attr).filter(Attr.id==None).delete()
db.DBSession.flush()
return db.DBSession.query(TemplateType).filter(TemplateType.id==type_id).one() | [
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hydraplatform/hydra-base | hydra_base/lib/template.py | remove_type_from_resource | def remove_type_from_resource( type_id, resource_type, resource_id,**kwargs):
"""
Remove a resource type trom a resource
"""
node_id = resource_id if resource_type == 'NODE' else None
link_id = resource_id if resource_type == 'LINK' else None
group_id = resource_id if resource_type == 'GROUP' else None
resourcetype = db.DBSession.query(ResourceType).filter(
ResourceType.type_id==type_id,
ResourceType.ref_key==resource_type,
ResourceType.node_id == node_id,
ResourceType.link_id == link_id,
ResourceType.group_id == group_id).one()
db.DBSession.delete(resourcetype)
db.DBSession.flush()
return 'OK' | python | def remove_type_from_resource( type_id, resource_type, resource_id,**kwargs):
"""
Remove a resource type trom a resource
"""
node_id = resource_id if resource_type == 'NODE' else None
link_id = resource_id if resource_type == 'LINK' else None
group_id = resource_id if resource_type == 'GROUP' else None
resourcetype = db.DBSession.query(ResourceType).filter(
ResourceType.type_id==type_id,
ResourceType.ref_key==resource_type,
ResourceType.node_id == node_id,
ResourceType.link_id == link_id,
ResourceType.group_id == group_id).one()
db.DBSession.delete(resourcetype)
db.DBSession.flush()
return 'OK' | [
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hydraplatform/hydra-base | hydra_base/lib/template.py | add_template | def add_template(template, **kwargs):
"""
Add template and a type and typeattrs.
"""
tmpl = Template()
tmpl.name = template.name
if template.description:
tmpl.description = template.description
if template.layout:
tmpl.layout = get_layout_as_string(template.layout)
db.DBSession.add(tmpl)
if template.templatetypes is not None:
types = template.templatetypes
for templatetype in types:
ttype = _update_templatetype(templatetype)
tmpl.templatetypes.append(ttype)
db.DBSession.flush()
return tmpl | python | def add_template(template, **kwargs):
"""
Add template and a type and typeattrs.
"""
tmpl = Template()
tmpl.name = template.name
if template.description:
tmpl.description = template.description
if template.layout:
tmpl.layout = get_layout_as_string(template.layout)
db.DBSession.add(tmpl)
if template.templatetypes is not None:
types = template.templatetypes
for templatetype in types:
ttype = _update_templatetype(templatetype)
tmpl.templatetypes.append(ttype)
db.DBSession.flush()
return tmpl | [
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hydraplatform/hydra-base | hydra_base/lib/template.py | update_template | def update_template(template,**kwargs):
"""
Update template and a type and typeattrs.
"""
tmpl = db.DBSession.query(Template).filter(Template.id==template.id).one()
tmpl.name = template.name
if template.description:
tmpl.description = template.description
#Lazy load the rest of the template
for tt in tmpl.templatetypes:
for ta in tt.typeattrs:
ta.attr
if template.layout:
tmpl.layout = get_layout_as_string(template.layout)
type_dict = dict([(t.id, t) for t in tmpl.templatetypes])
existing_templatetypes = []
if template.types is not None or template.templatetypes is not None:
types = template.types if template.types is not None else template.templatetypes
for templatetype in types:
if templatetype.id is not None:
type_i = type_dict[templatetype.id]
_update_templatetype(templatetype, type_i)
existing_templatetypes.append(type_i.id)
else:
#Give it a template ID if it doesn't have one
templatetype.template_id = template.id
new_templatetype_i = _update_templatetype(templatetype)
existing_templatetypes.append(new_templatetype_i.id)
for tt in tmpl.templatetypes:
if tt.id not in existing_templatetypes:
delete_templatetype(tt.id)
db.DBSession.flush()
return tmpl | python | def update_template(template,**kwargs):
"""
Update template and a type and typeattrs.
"""
tmpl = db.DBSession.query(Template).filter(Template.id==template.id).one()
tmpl.name = template.name
if template.description:
tmpl.description = template.description
#Lazy load the rest of the template
for tt in tmpl.templatetypes:
for ta in tt.typeattrs:
ta.attr
if template.layout:
tmpl.layout = get_layout_as_string(template.layout)
type_dict = dict([(t.id, t) for t in tmpl.templatetypes])
existing_templatetypes = []
if template.types is not None or template.templatetypes is not None:
types = template.types if template.types is not None else template.templatetypes
for templatetype in types:
if templatetype.id is not None:
type_i = type_dict[templatetype.id]
_update_templatetype(templatetype, type_i)
existing_templatetypes.append(type_i.id)
else:
#Give it a template ID if it doesn't have one
templatetype.template_id = template.id
new_templatetype_i = _update_templatetype(templatetype)
existing_templatetypes.append(new_templatetype_i.id)
for tt in tmpl.templatetypes:
if tt.id not in existing_templatetypes:
delete_templatetype(tt.id)
db.DBSession.flush()
return tmpl | [
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hydraplatform/hydra-base | hydra_base/lib/template.py | delete_template | def delete_template(template_id,**kwargs):
"""
Delete a template and its type and typeattrs.
"""
try:
tmpl = db.DBSession.query(Template).filter(Template.id==template_id).one()
except NoResultFound:
raise ResourceNotFoundError("Template %s not found"%(template_id,))
db.DBSession.delete(tmpl)
db.DBSession.flush()
return 'OK' | python | def delete_template(template_id,**kwargs):
"""
Delete a template and its type and typeattrs.
"""
try:
tmpl = db.DBSession.query(Template).filter(Template.id==template_id).one()
except NoResultFound:
raise ResourceNotFoundError("Template %s not found"%(template_id,))
db.DBSession.delete(tmpl)
db.DBSession.flush()
return 'OK' | [
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hydraplatform/hydra-base | hydra_base/lib/template.py | get_template | def get_template(template_id,**kwargs):
"""
Get a specific resource template template, by ID.
"""
try:
tmpl_i = db.DBSession.query(Template).filter(Template.id==template_id).options(joinedload_all('templatetypes.typeattrs.default_dataset.metadata')).one()
#Load the attributes.
for tmpltype_i in tmpl_i.templatetypes:
for typeattr_i in tmpltype_i.typeattrs:
typeattr_i.attr
return tmpl_i
except NoResultFound:
raise HydraError("Template %s not found"%template_id) | python | def get_template(template_id,**kwargs):
"""
Get a specific resource template template, by ID.
"""
try:
tmpl_i = db.DBSession.query(Template).filter(Template.id==template_id).options(joinedload_all('templatetypes.typeattrs.default_dataset.metadata')).one()
#Load the attributes.
for tmpltype_i in tmpl_i.templatetypes:
for typeattr_i in tmpltype_i.typeattrs:
typeattr_i.attr
return tmpl_i
except NoResultFound:
raise HydraError("Template %s not found"%template_id) | [
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hydraplatform/hydra-base | hydra_base/lib/template.py | get_template_by_name | def get_template_by_name(name,**kwargs):
"""
Get a specific resource template, by name.
"""
try:
tmpl_i = db.DBSession.query(Template).filter(Template.name == name).options(joinedload_all('templatetypes.typeattrs.default_dataset.metadata')).one()
return tmpl_i
except NoResultFound:
log.info("%s is not a valid identifier for a template",name)
raise HydraError('Template "%s" not found'%name) | python | def get_template_by_name(name,**kwargs):
"""
Get a specific resource template, by name.
"""
try:
tmpl_i = db.DBSession.query(Template).filter(Template.name == name).options(joinedload_all('templatetypes.typeattrs.default_dataset.metadata')).one()
return tmpl_i
except NoResultFound:
log.info("%s is not a valid identifier for a template",name)
raise HydraError('Template "%s" not found'%name) | [
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hydraplatform/hydra-base | hydra_base/lib/template.py | add_templatetype | def add_templatetype(templatetype,**kwargs):
"""
Add a template type with typeattrs.
"""
type_i = _update_templatetype(templatetype)
db.DBSession.flush()
return type_i | python | def add_templatetype(templatetype,**kwargs):
"""
Add a template type with typeattrs.
"""
type_i = _update_templatetype(templatetype)
db.DBSession.flush()
return type_i | [
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hydraplatform/hydra-base | hydra_base/lib/template.py | update_templatetype | def update_templatetype(templatetype,**kwargs):
"""
Update a resource type and its typeattrs.
New typeattrs will be added. typeattrs not sent will be ignored.
To delete typeattrs, call delete_typeattr
"""
tmpltype_i = db.DBSession.query(TemplateType).filter(TemplateType.id == templatetype.id).one()
_update_templatetype(templatetype, tmpltype_i)
db.DBSession.flush()
return tmpltype_i | python | def update_templatetype(templatetype,**kwargs):
"""
Update a resource type and its typeattrs.
New typeattrs will be added. typeattrs not sent will be ignored.
To delete typeattrs, call delete_typeattr
"""
tmpltype_i = db.DBSession.query(TemplateType).filter(TemplateType.id == templatetype.id).one()
_update_templatetype(templatetype, tmpltype_i)
db.DBSession.flush()
return tmpltype_i | [
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hydraplatform/hydra-base | hydra_base/lib/template.py | _set_typeattr | def _set_typeattr(typeattr, existing_ta = None):
"""
Add or updsate a type attribute.
If an existing type attribute is provided, then update.
Checks are performed to ensure that the dimension provided on the
type attr (not updateable) is the same as that on the referring attribute.
The unit provided (stored on tattr) must conform to the dimension stored
on the referring attribute (stored on tattr).
This is done so that multiple tempaltes can all use the same attribute,
but specify different units.
If no attr_id is provided, but an attr_name and dimension are provided,
then a new attribute can be created (or retrived) and used. I.e., no
attribute ID must be specified if attr_name and dimension are specified.
***WARNING***
Setting attribute ID to null means a new type attribute (and even a new attr)
may be added, None are removed or replaced. To remove other type attrs, do it
manually using delete_typeattr
"""
if existing_ta is None:
ta = TypeAttr(attr_id=typeattr.attr_id)
else:
ta = existing_ta
ta.unit_id = typeattr.unit_id
ta.type_id = typeattr.type_id
ta.data_type = typeattr.data_type
if hasattr(typeattr, 'default_dataset_id') and typeattr.default_dataset_id is not None:
ta.default_dataset_id = typeattr.default_dataset_id
ta.description = typeattr.description
ta.properties = typeattr.get_properties()
ta.attr_is_var = typeattr.is_var if typeattr.is_var is not None else 'N'
ta.data_restriction = _parse_data_restriction(typeattr.data_restriction)
if typeattr.dimension_id is None:
# All right. Check passed
pass
else:
if typeattr.attr_id is not None and typeattr.attr_id > 0:
# Getting the passed attribute, so we need to check consistency between attr dimension id and typeattr dimension id
attr = ta.attr
if attr is not None and attr.dimension_id is not None and attr.dimension_id != typeattr.dimension_id or \
attr is not None and attr.dimension_id is not None:
# In this case there is an inconsistency between attr.dimension_id and typeattr.dimension_id
raise HydraError("Cannot set a dimension on type attribute which "
"does not match its attribute. Create a new attribute if "
"you want to use attribute %s with dimension_id %s"%
(attr.name, typeattr.dimension_id))
elif typeattr.attr_id is None and typeattr.name is not None:
# Getting/creating the attribute by typeattr dimension id and typeattr name
# In this case the dimension_id "null"/"not null" status is ininfluent
attr = _get_attr_by_name_and_dimension(typeattr.name, typeattr.dimension_id)
ta.attr_id = attr.id
ta.attr = attr
_check_dimension(ta)
if existing_ta is None:
log.debug("Adding ta to DB")
db.DBSession.add(ta)
return ta | python | def _set_typeattr(typeattr, existing_ta = None):
"""
Add or updsate a type attribute.
If an existing type attribute is provided, then update.
Checks are performed to ensure that the dimension provided on the
type attr (not updateable) is the same as that on the referring attribute.
The unit provided (stored on tattr) must conform to the dimension stored
on the referring attribute (stored on tattr).
This is done so that multiple tempaltes can all use the same attribute,
but specify different units.
If no attr_id is provided, but an attr_name and dimension are provided,
then a new attribute can be created (or retrived) and used. I.e., no
attribute ID must be specified if attr_name and dimension are specified.
***WARNING***
Setting attribute ID to null means a new type attribute (and even a new attr)
may be added, None are removed or replaced. To remove other type attrs, do it
manually using delete_typeattr
"""
if existing_ta is None:
ta = TypeAttr(attr_id=typeattr.attr_id)
else:
ta = existing_ta
ta.unit_id = typeattr.unit_id
ta.type_id = typeattr.type_id
ta.data_type = typeattr.data_type
if hasattr(typeattr, 'default_dataset_id') and typeattr.default_dataset_id is not None:
ta.default_dataset_id = typeattr.default_dataset_id
ta.description = typeattr.description
ta.properties = typeattr.get_properties()
ta.attr_is_var = typeattr.is_var if typeattr.is_var is not None else 'N'
ta.data_restriction = _parse_data_restriction(typeattr.data_restriction)
if typeattr.dimension_id is None:
# All right. Check passed
pass
else:
if typeattr.attr_id is not None and typeattr.attr_id > 0:
# Getting the passed attribute, so we need to check consistency between attr dimension id and typeattr dimension id
attr = ta.attr
if attr is not None and attr.dimension_id is not None and attr.dimension_id != typeattr.dimension_id or \
attr is not None and attr.dimension_id is not None:
# In this case there is an inconsistency between attr.dimension_id and typeattr.dimension_id
raise HydraError("Cannot set a dimension on type attribute which "
"does not match its attribute. Create a new attribute if "
"you want to use attribute %s with dimension_id %s"%
(attr.name, typeattr.dimension_id))
elif typeattr.attr_id is None and typeattr.name is not None:
# Getting/creating the attribute by typeattr dimension id and typeattr name
# In this case the dimension_id "null"/"not null" status is ininfluent
attr = _get_attr_by_name_and_dimension(typeattr.name, typeattr.dimension_id)
ta.attr_id = attr.id
ta.attr = attr
_check_dimension(ta)
if existing_ta is None:
log.debug("Adding ta to DB")
db.DBSession.add(ta)
return ta | [
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hydraplatform/hydra-base | hydra_base/lib/template.py | _update_templatetype | def _update_templatetype(templatetype, existing_tt=None):
"""
Add or update a templatetype. If an existing template type is passed in,
update that one. Otherwise search for an existing one. If not found, add.
"""
if existing_tt is None:
if "id" in templatetype and templatetype.id is not None:
tmpltype_i = db.DBSession.query(TemplateType).filter(TemplateType.id == templatetype.id).one()
else:
tmpltype_i = TemplateType()
else:
tmpltype_i = existing_tt
tmpltype_i.template_id = templatetype.template_id
tmpltype_i.name = templatetype.name
tmpltype_i.description = templatetype.description
tmpltype_i.alias = templatetype.alias
if templatetype.layout is not None:
tmpltype_i.layout = get_layout_as_string(templatetype.layout)
tmpltype_i.resource_type = templatetype.resource_type
ta_dict = {}
for t in tmpltype_i.typeattrs:
ta_dict[t.attr_id] = t
existing_attrs = []
if templatetype.typeattrs is not None:
for typeattr in templatetype.typeattrs:
if typeattr.attr_id in ta_dict:
ta = _set_typeattr(typeattr, ta_dict[typeattr.attr_id])
existing_attrs.append(ta.attr_id)
else:
ta = _set_typeattr(typeattr)
tmpltype_i.typeattrs.append(ta)
existing_attrs.append(ta.attr_id)
log.debug("Deleting any type attrs not sent")
for ta in ta_dict.values():
if ta.attr_id not in existing_attrs:
delete_typeattr(ta)
if existing_tt is None:
db.DBSession.add(tmpltype_i)
return tmpltype_i | python | def _update_templatetype(templatetype, existing_tt=None):
"""
Add or update a templatetype. If an existing template type is passed in,
update that one. Otherwise search for an existing one. If not found, add.
"""
if existing_tt is None:
if "id" in templatetype and templatetype.id is not None:
tmpltype_i = db.DBSession.query(TemplateType).filter(TemplateType.id == templatetype.id).one()
else:
tmpltype_i = TemplateType()
else:
tmpltype_i = existing_tt
tmpltype_i.template_id = templatetype.template_id
tmpltype_i.name = templatetype.name
tmpltype_i.description = templatetype.description
tmpltype_i.alias = templatetype.alias
if templatetype.layout is not None:
tmpltype_i.layout = get_layout_as_string(templatetype.layout)
tmpltype_i.resource_type = templatetype.resource_type
ta_dict = {}
for t in tmpltype_i.typeattrs:
ta_dict[t.attr_id] = t
existing_attrs = []
if templatetype.typeattrs is not None:
for typeattr in templatetype.typeattrs:
if typeattr.attr_id in ta_dict:
ta = _set_typeattr(typeattr, ta_dict[typeattr.attr_id])
existing_attrs.append(ta.attr_id)
else:
ta = _set_typeattr(typeattr)
tmpltype_i.typeattrs.append(ta)
existing_attrs.append(ta.attr_id)
log.debug("Deleting any type attrs not sent")
for ta in ta_dict.values():
if ta.attr_id not in existing_attrs:
delete_typeattr(ta)
if existing_tt is None:
db.DBSession.add(tmpltype_i)
return tmpltype_i | [
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hydraplatform/hydra-base | hydra_base/lib/template.py | delete_templatetype | def delete_templatetype(type_id,template_i=None, **kwargs):
"""
Delete a template type and its typeattrs.
"""
try:
tmpltype_i = db.DBSession.query(TemplateType).filter(TemplateType.id == type_id).one()
except NoResultFound:
raise ResourceNotFoundError("Template Type %s not found"%(type_id,))
if template_i is None:
template_i = db.DBSession.query(Template).filter(Template.id==tmpltype_i.template_id).one()
template_i.templatetypes.remove(tmpltype_i)
db.DBSession.delete(tmpltype_i)
db.DBSession.flush() | python | def delete_templatetype(type_id,template_i=None, **kwargs):
"""
Delete a template type and its typeattrs.
"""
try:
tmpltype_i = db.DBSession.query(TemplateType).filter(TemplateType.id == type_id).one()
except NoResultFound:
raise ResourceNotFoundError("Template Type %s not found"%(type_id,))
if template_i is None:
template_i = db.DBSession.query(Template).filter(Template.id==tmpltype_i.template_id).one()
template_i.templatetypes.remove(tmpltype_i)
db.DBSession.delete(tmpltype_i)
db.DBSession.flush() | [
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hydraplatform/hydra-base | hydra_base/lib/template.py | get_templatetype | def get_templatetype(type_id,**kwargs):
"""
Get a specific resource type by ID.
"""
templatetype = db.DBSession.query(TemplateType).filter(
TemplateType.id==type_id).options(
joinedload_all("typeattrs")).one()
return templatetype | python | def get_templatetype(type_id,**kwargs):
"""
Get a specific resource type by ID.
"""
templatetype = db.DBSession.query(TemplateType).filter(
TemplateType.id==type_id).options(
joinedload_all("typeattrs")).one()
return templatetype | [
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hydraplatform/hydra-base | hydra_base/lib/template.py | get_templatetype_by_name | def get_templatetype_by_name(template_id, type_name,**kwargs):
"""
Get a specific resource type by name.
"""
try:
templatetype = db.DBSession.query(TemplateType).filter(TemplateType.id==template_id, TemplateType.name==type_name).one()
except NoResultFound:
raise HydraError("%s is not a valid identifier for a type"%(type_name))
return templatetype | python | def get_templatetype_by_name(template_id, type_name,**kwargs):
"""
Get a specific resource type by name.
"""
try:
templatetype = db.DBSession.query(TemplateType).filter(TemplateType.id==template_id, TemplateType.name==type_name).one()
except NoResultFound:
raise HydraError("%s is not a valid identifier for a type"%(type_name))
return templatetype | [
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hydraplatform/hydra-base | hydra_base/lib/template.py | add_typeattr | def add_typeattr(typeattr,**kwargs):
"""
Add an typeattr to an existing type.
"""
tmpltype = get_templatetype(typeattr.type_id, user_id=kwargs.get('user_id'))
ta = _set_typeattr(typeattr)
tmpltype.typeattrs.append(ta)
db.DBSession.flush()
return ta | python | def add_typeattr(typeattr,**kwargs):
"""
Add an typeattr to an existing type.
"""
tmpltype = get_templatetype(typeattr.type_id, user_id=kwargs.get('user_id'))
ta = _set_typeattr(typeattr)
tmpltype.typeattrs.append(ta)
db.DBSession.flush()
return ta | [
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hydraplatform/hydra-base | hydra_base/lib/template.py | delete_typeattr | def delete_typeattr(typeattr,**kwargs):
"""
Remove an typeattr from an existing type
"""
tmpltype = get_templatetype(typeattr.type_id, user_id=kwargs.get('user_id'))
ta = db.DBSession.query(TypeAttr).filter(TypeAttr.type_id == typeattr.type_id,
TypeAttr.attr_id == typeattr.attr_id).one()
tmpltype.typeattrs.remove(ta)
db.DBSession.flush()
return 'OK' | python | def delete_typeattr(typeattr,**kwargs):
"""
Remove an typeattr from an existing type
"""
tmpltype = get_templatetype(typeattr.type_id, user_id=kwargs.get('user_id'))
ta = db.DBSession.query(TypeAttr).filter(TypeAttr.type_id == typeattr.type_id,
TypeAttr.attr_id == typeattr.attr_id).one()
tmpltype.typeattrs.remove(ta)
db.DBSession.flush()
return 'OK' | [
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hydraplatform/hydra-base | hydra_base/lib/template.py | validate_attr | def validate_attr(resource_attr_id, scenario_id, template_id=None):
"""
Check that a resource attribute satisfies the requirements of all the types of the
resource.
"""
rs = db.DBSession.query(ResourceScenario).\
filter(ResourceScenario.resource_attr_id==resource_attr_id,
ResourceScenario.scenario_id==scenario_id).options(
joinedload_all("resourceattr")).options(
joinedload_all("dataset")
).one()
error = None
try:
_do_validate_resourcescenario(rs, template_id)
except HydraError as e:
error = JSONObject(dict(
ref_key = rs.resourceattr.ref_key,
ref_id = rs.resourceattr.get_resource_id(),
ref_name = rs.resourceattr.get_resource().get_name(),
resource_attr_id = rs.resource_attr_id,
attr_id = rs.resourceattr.attr.id,
attr_name = rs.resourceattr.attr.name,
dataset_id = rs.dataset_id,
scenario_id=scenario_id,
template_id=template_id,
error_text=e.args[0]))
return error | python | def validate_attr(resource_attr_id, scenario_id, template_id=None):
"""
Check that a resource attribute satisfies the requirements of all the types of the
resource.
"""
rs = db.DBSession.query(ResourceScenario).\
filter(ResourceScenario.resource_attr_id==resource_attr_id,
ResourceScenario.scenario_id==scenario_id).options(
joinedload_all("resourceattr")).options(
joinedload_all("dataset")
).one()
error = None
try:
_do_validate_resourcescenario(rs, template_id)
except HydraError as e:
error = JSONObject(dict(
ref_key = rs.resourceattr.ref_key,
ref_id = rs.resourceattr.get_resource_id(),
ref_name = rs.resourceattr.get_resource().get_name(),
resource_attr_id = rs.resource_attr_id,
attr_id = rs.resourceattr.attr.id,
attr_name = rs.resourceattr.attr.name,
dataset_id = rs.dataset_id,
scenario_id=scenario_id,
template_id=template_id,
error_text=e.args[0]))
return error | [
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hydraplatform/hydra-base | hydra_base/lib/template.py | validate_attrs | def validate_attrs(resource_attr_ids, scenario_id, template_id=None):
"""
Check that multiple resource attribute satisfy the requirements of the types of resources to
which the they are attached.
"""
multi_rs = db.DBSession.query(ResourceScenario).\
filter(ResourceScenario.resource_attr_id.in_(resource_attr_ids),\
ResourceScenario.scenario_id==scenario_id).\
options(joinedload_all("resourceattr")).\
options(joinedload_all("dataset")).all()
errors = []
for rs in multi_rs:
try:
_do_validate_resourcescenario(rs, template_id)
except HydraError as e:
error = dict(
ref_key = rs.resourceattr.ref_key,
ref_id = rs.resourceattr.get_resource_id(),
ref_name = rs.resourceattr.get_resource().get_name(),
resource_attr_id = rs.resource_attr_id,
attr_id = rs.resourceattr.attr.id,
attr_name = rs.resourceattr.attr.name,
dataset_id = rs.dataset_id,
scenario_id = scenario_id,
template_id = template_id,
error_text = e.args[0])
errors.append(error)
return errors | python | def validate_attrs(resource_attr_ids, scenario_id, template_id=None):
"""
Check that multiple resource attribute satisfy the requirements of the types of resources to
which the they are attached.
"""
multi_rs = db.DBSession.query(ResourceScenario).\
filter(ResourceScenario.resource_attr_id.in_(resource_attr_ids),\
ResourceScenario.scenario_id==scenario_id).\
options(joinedload_all("resourceattr")).\
options(joinedload_all("dataset")).all()
errors = []
for rs in multi_rs:
try:
_do_validate_resourcescenario(rs, template_id)
except HydraError as e:
error = dict(
ref_key = rs.resourceattr.ref_key,
ref_id = rs.resourceattr.get_resource_id(),
ref_name = rs.resourceattr.get_resource().get_name(),
resource_attr_id = rs.resource_attr_id,
attr_id = rs.resourceattr.attr.id,
attr_name = rs.resourceattr.attr.name,
dataset_id = rs.dataset_id,
scenario_id = scenario_id,
template_id = template_id,
error_text = e.args[0])
errors.append(error)
return errors | [
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hydraplatform/hydra-base | hydra_base/lib/template.py | validate_network | def validate_network(network_id, template_id, scenario_id=None):
"""
Given a network, scenario and template, ensure that all the nodes, links & groups
in the network have the correct resource attributes as defined by the types in the template.
Also ensure valid entries in tresourcetype.
This validation will not fail if a resource has more than the required type, but will fail if
it has fewer or if any attribute has a conflicting dimension or unit.
"""
network = db.DBSession.query(Network).filter(Network.id==network_id).options(noload('scenarios')).first()
if network is None:
raise HydraError("Could not find network %s"%(network_id))
resource_scenario_dict = {}
if scenario_id is not None:
scenario = db.DBSession.query(Scenario).filter(Scenario.id==scenario_id).first()
if scenario is None:
raise HydraError("Could not find scenario %s"%(scenario_id,))
for rs in scenario.resourcescenarios:
resource_scenario_dict[rs.resource_attr_id] = rs
template = db.DBSession.query(Template).filter(Template.id == template_id).options(joinedload_all('templatetypes')).first()
if template is None:
raise HydraError("Could not find template %s"%(template_id,))
resource_type_defs = {
'NETWORK' : {},
'NODE' : {},
'LINK' : {},
'GROUP' : {},
}
for tt in template.templatetypes:
resource_type_defs[tt.resource_type][tt.id] = tt
errors = []
#Only check if there are type definitions for a network in the template.
if resource_type_defs.get('NETWORK'):
net_types = resource_type_defs['NETWORK']
errors.extend(_validate_resource(network, net_types, resource_scenario_dict))
#check all nodes
if resource_type_defs.get('NODE'):
node_types = resource_type_defs['NODE']
for node in network.nodes:
errors.extend(_validate_resource(node, node_types, resource_scenario_dict))
#check all links
if resource_type_defs.get('LINK'):
link_types = resource_type_defs['LINK']
for link in network.links:
errors.extend(_validate_resource(link, link_types, resource_scenario_dict))
#check all groups
if resource_type_defs.get('GROUP'):
group_types = resource_type_defs['GROUP']
for group in network.resourcegroups:
errors.extend(_validate_resource(group, group_types, resource_scenario_dict))
return errors | python | def validate_network(network_id, template_id, scenario_id=None):
"""
Given a network, scenario and template, ensure that all the nodes, links & groups
in the network have the correct resource attributes as defined by the types in the template.
Also ensure valid entries in tresourcetype.
This validation will not fail if a resource has more than the required type, but will fail if
it has fewer or if any attribute has a conflicting dimension or unit.
"""
network = db.DBSession.query(Network).filter(Network.id==network_id).options(noload('scenarios')).first()
if network is None:
raise HydraError("Could not find network %s"%(network_id))
resource_scenario_dict = {}
if scenario_id is not None:
scenario = db.DBSession.query(Scenario).filter(Scenario.id==scenario_id).first()
if scenario is None:
raise HydraError("Could not find scenario %s"%(scenario_id,))
for rs in scenario.resourcescenarios:
resource_scenario_dict[rs.resource_attr_id] = rs
template = db.DBSession.query(Template).filter(Template.id == template_id).options(joinedload_all('templatetypes')).first()
if template is None:
raise HydraError("Could not find template %s"%(template_id,))
resource_type_defs = {
'NETWORK' : {},
'NODE' : {},
'LINK' : {},
'GROUP' : {},
}
for tt in template.templatetypes:
resource_type_defs[tt.resource_type][tt.id] = tt
errors = []
#Only check if there are type definitions for a network in the template.
if resource_type_defs.get('NETWORK'):
net_types = resource_type_defs['NETWORK']
errors.extend(_validate_resource(network, net_types, resource_scenario_dict))
#check all nodes
if resource_type_defs.get('NODE'):
node_types = resource_type_defs['NODE']
for node in network.nodes:
errors.extend(_validate_resource(node, node_types, resource_scenario_dict))
#check all links
if resource_type_defs.get('LINK'):
link_types = resource_type_defs['LINK']
for link in network.links:
errors.extend(_validate_resource(link, link_types, resource_scenario_dict))
#check all groups
if resource_type_defs.get('GROUP'):
group_types = resource_type_defs['GROUP']
for group in network.resourcegroups:
errors.extend(_validate_resource(group, group_types, resource_scenario_dict))
return errors | [
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hydraplatform/hydra-base | hydra_base/lib/template.py | _make_attr_element_from_typeattr | def _make_attr_element_from_typeattr(parent, type_attr_i):
"""
General function to add an attribute element to a resource element.
resource_attr_i can also e a type_attr if being called from get_tempalte_as_xml
"""
attr = _make_attr_element(parent, type_attr_i.attr)
if type_attr_i.unit_id is not None:
attr_unit = etree.SubElement(attr, 'unit')
attr_unit.text = units.get_unit(type_attr_i.unit_id).abbreviation
attr_is_var = etree.SubElement(attr, 'is_var')
attr_is_var.text = type_attr_i.attr_is_var
if type_attr_i.data_type is not None:
attr_data_type = etree.SubElement(attr, 'data_type')
attr_data_type.text = type_attr_i.data_type
if type_attr_i.data_restriction is not None:
attr_data_restriction = etree.SubElement(attr, 'restrictions')
attr_data_restriction.text = type_attr_i.data_restriction
return attr | python | def _make_attr_element_from_typeattr(parent, type_attr_i):
"""
General function to add an attribute element to a resource element.
resource_attr_i can also e a type_attr if being called from get_tempalte_as_xml
"""
attr = _make_attr_element(parent, type_attr_i.attr)
if type_attr_i.unit_id is not None:
attr_unit = etree.SubElement(attr, 'unit')
attr_unit.text = units.get_unit(type_attr_i.unit_id).abbreviation
attr_is_var = etree.SubElement(attr, 'is_var')
attr_is_var.text = type_attr_i.attr_is_var
if type_attr_i.data_type is not None:
attr_data_type = etree.SubElement(attr, 'data_type')
attr_data_type.text = type_attr_i.data_type
if type_attr_i.data_restriction is not None:
attr_data_restriction = etree.SubElement(attr, 'restrictions')
attr_data_restriction.text = type_attr_i.data_restriction
return attr | [
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hydraplatform/hydra-base | hydra_base/lib/template.py | _make_attr_element_from_resourceattr | def _make_attr_element_from_resourceattr(parent, resource_attr_i):
"""
General function to add an attribute element to a resource element.
"""
attr = _make_attr_element(parent, resource_attr_i.attr)
attr_is_var = etree.SubElement(attr, 'is_var')
attr_is_var.text = resource_attr_i.attr_is_var
return attr | python | def _make_attr_element_from_resourceattr(parent, resource_attr_i):
"""
General function to add an attribute element to a resource element.
"""
attr = _make_attr_element(parent, resource_attr_i.attr)
attr_is_var = etree.SubElement(attr, 'is_var')
attr_is_var.text = resource_attr_i.attr_is_var
return attr | [
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hydraplatform/hydra-base | hydra_base/lib/template.py | _make_attr_element | def _make_attr_element(parent, attr_i):
"""
create an attribute element from an attribute DB object
"""
attr = etree.SubElement(parent, "attribute")
attr_name = etree.SubElement(attr, 'name')
attr_name.text = attr_i.name
attr_desc = etree.SubElement(attr, 'description')
attr_desc.text = attr_i.description
attr_dimension = etree.SubElement(attr, 'dimension')
attr_dimension.text = units.get_dimension(attr_i.dimension_id, do_accept_dimension_id_none=True).name
return attr | python | def _make_attr_element(parent, attr_i):
"""
create an attribute element from an attribute DB object
"""
attr = etree.SubElement(parent, "attribute")
attr_name = etree.SubElement(attr, 'name')
attr_name.text = attr_i.name
attr_desc = etree.SubElement(attr, 'description')
attr_desc.text = attr_i.description
attr_dimension = etree.SubElement(attr, 'dimension')
attr_dimension.text = units.get_dimension(attr_i.dimension_id, do_accept_dimension_id_none=True).name
return attr | [
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hydraplatform/hydra-base | hydra_base/lib/HydraTypes/Registry.py | HydraObjectFactory.valueFromDataset | def valueFromDataset(cls, datatype, value, metadata=None, tmap=None):
"""
Return the value contained by dataset argument, after casting to
correct type and performing type-specific validation
"""
if tmap is None:
tmap = typemap
obj = cls.fromDataset(datatype, value, metadata=metadata, tmap=tmap)
return obj.value | python | def valueFromDataset(cls, datatype, value, metadata=None, tmap=None):
"""
Return the value contained by dataset argument, after casting to
correct type and performing type-specific validation
"""
if tmap is None:
tmap = typemap
obj = cls.fromDataset(datatype, value, metadata=metadata, tmap=tmap)
return obj.value | [
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hydraplatform/hydra-base | hydra_base/lib/HydraTypes/Registry.py | HydraObjectFactory.fromDataset | def fromDataset(datatype, value, metadata=None, tmap=None):
"""
Return a representation of dataset argument as an instance
of the class corresponding to its datatype
"""
if tmap is None:
tmap = typemap
return tmap[datatype.upper()].fromDataset(value, metadata=metadata) | python | def fromDataset(datatype, value, metadata=None, tmap=None):
"""
Return a representation of dataset argument as an instance
of the class corresponding to its datatype
"""
if tmap is None:
tmap = typemap
return tmap[datatype.upper()].fromDataset(value, metadata=metadata) | [
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hydraplatform/hydra-base | hydra_base/lib/units.py | exists_dimension | def exists_dimension(dimension_name,**kwargs):
"""
Given a dimension returns True if it exists, False otherwise
"""
try:
dimension = db.DBSession.query(Dimension).filter(Dimension.name==dimension_name).one()
# At this point the dimension exists
return True
except NoResultFound:
# The dimension does not exist
raise False | python | def exists_dimension(dimension_name,**kwargs):
"""
Given a dimension returns True if it exists, False otherwise
"""
try:
dimension = db.DBSession.query(Dimension).filter(Dimension.name==dimension_name).one()
# At this point the dimension exists
return True
except NoResultFound:
# The dimension does not exist
raise False | [
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hydraplatform/hydra-base | hydra_base/lib/units.py | convert_units | def convert_units(values, source_measure_or_unit_abbreviation, target_measure_or_unit_abbreviation,**kwargs):
"""
Convert a value from one unit to another one.
Example::
>>> cli = PluginLib.connect()
>>> cli.service.convert_units(20.0, 'm', 'km')
0.02
Parameters:
values: single measure or an array of measures
source_measure_or_unit_abbreviation: A measure in the source unit, or just the abbreviation of the source unit, from which convert the provided measure value/values
target_measure_or_unit_abbreviation: A measure in the target unit, or just the abbreviation of the target unit, into which convert the provided measure value/values
Returns:
Always a list
"""
if numpy.isscalar(values):
# If it is a scalar, converts to an array
values = [values]
float_values = [float(value) for value in values]
values_to_return = convert(float_values, source_measure_or_unit_abbreviation, target_measure_or_unit_abbreviation)
return values_to_return | python | def convert_units(values, source_measure_or_unit_abbreviation, target_measure_or_unit_abbreviation,**kwargs):
"""
Convert a value from one unit to another one.
Example::
>>> cli = PluginLib.connect()
>>> cli.service.convert_units(20.0, 'm', 'km')
0.02
Parameters:
values: single measure or an array of measures
source_measure_or_unit_abbreviation: A measure in the source unit, or just the abbreviation of the source unit, from which convert the provided measure value/values
target_measure_or_unit_abbreviation: A measure in the target unit, or just the abbreviation of the target unit, into which convert the provided measure value/values
Returns:
Always a list
"""
if numpy.isscalar(values):
# If it is a scalar, converts to an array
values = [values]
float_values = [float(value) for value in values]
values_to_return = convert(float_values, source_measure_or_unit_abbreviation, target_measure_or_unit_abbreviation)
return values_to_return | [
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0.02
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source_measure_or_unit_abbreviation: A measure in the source unit, or just the abbreviation of the source unit, from which convert the provided measure value/values
target_measure_or_unit_abbreviation: A measure in the target unit, or just the abbreviation of the target unit, into which convert the provided measure value/values
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hydraplatform/hydra-base | hydra_base/lib/units.py | convert | def convert(values, source_measure_or_unit_abbreviation, target_measure_or_unit_abbreviation):
"""
Convert a value or a list of values from an unit to another one.
The two units must represent the same physical dimension.
"""
source_dimension = get_dimension_by_unit_measure_or_abbreviation(source_measure_or_unit_abbreviation)
target_dimension = get_dimension_by_unit_measure_or_abbreviation(target_measure_or_unit_abbreviation)
if source_dimension == target_dimension:
source=JSONObject({})
target=JSONObject({})
source.unit_abbreviation, source.factor = _parse_unit(source_measure_or_unit_abbreviation)
target.unit_abbreviation, target.factor = _parse_unit(target_measure_or_unit_abbreviation)
source.unit_data = get_unit_by_abbreviation(source.unit_abbreviation)
target.unit_data = get_unit_by_abbreviation(target.unit_abbreviation)
source.conv_factor = JSONObject({'lf': source.unit_data.lf, 'cf': source.unit_data.cf})
target.conv_factor = JSONObject({'lf': target.unit_data.lf, 'cf': target.unit_data.cf})
if isinstance(values, float):
# If values is a float => returns a float
return (source.conv_factor.lf / target.conv_factor.lf * (source.factor * values)
+ (source.conv_factor.cf - target.conv_factor.cf)
/ target.conv_factor.lf) / target.factor
elif isinstance(values, list):
# If values is a list of floats => returns a list of floats
return [(source.conv_factor.lf / target.conv_factor.lf * (source.factor * value)
+ (source.conv_factor.cf - target.conv_factor.cf)
/ target.conv_factor.lf) / target.factor for value in values]
else:
raise HydraError("Unit conversion: dimensions are not consistent.") | python | def convert(values, source_measure_or_unit_abbreviation, target_measure_or_unit_abbreviation):
"""
Convert a value or a list of values from an unit to another one.
The two units must represent the same physical dimension.
"""
source_dimension = get_dimension_by_unit_measure_or_abbreviation(source_measure_or_unit_abbreviation)
target_dimension = get_dimension_by_unit_measure_or_abbreviation(target_measure_or_unit_abbreviation)
if source_dimension == target_dimension:
source=JSONObject({})
target=JSONObject({})
source.unit_abbreviation, source.factor = _parse_unit(source_measure_or_unit_abbreviation)
target.unit_abbreviation, target.factor = _parse_unit(target_measure_or_unit_abbreviation)
source.unit_data = get_unit_by_abbreviation(source.unit_abbreviation)
target.unit_data = get_unit_by_abbreviation(target.unit_abbreviation)
source.conv_factor = JSONObject({'lf': source.unit_data.lf, 'cf': source.unit_data.cf})
target.conv_factor = JSONObject({'lf': target.unit_data.lf, 'cf': target.unit_data.cf})
if isinstance(values, float):
# If values is a float => returns a float
return (source.conv_factor.lf / target.conv_factor.lf * (source.factor * values)
+ (source.conv_factor.cf - target.conv_factor.cf)
/ target.conv_factor.lf) / target.factor
elif isinstance(values, list):
# If values is a list of floats => returns a list of floats
return [(source.conv_factor.lf / target.conv_factor.lf * (source.factor * value)
+ (source.conv_factor.cf - target.conv_factor.cf)
/ target.conv_factor.lf) / target.factor for value in values]
else:
raise HydraError("Unit conversion: dimensions are not consistent.") | [
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hydraplatform/hydra-base | hydra_base/lib/units.py | get_empty_dimension | def get_empty_dimension(**kwargs):
"""
Returns a dimension object initialized with empty values
"""
dimension = JSONObject(Dimension())
dimension.id = None
dimension.name = ''
dimension.description = ''
dimension.project_id = None
dimension.units = []
return dimension | python | def get_empty_dimension(**kwargs):
"""
Returns a dimension object initialized with empty values
"""
dimension = JSONObject(Dimension())
dimension.id = None
dimension.name = ''
dimension.description = ''
dimension.project_id = None
dimension.units = []
return dimension | [
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hydraplatform/hydra-base | hydra_base/lib/units.py | get_dimension | def get_dimension(dimension_id, do_accept_dimension_id_none=False,**kwargs):
"""
Given a dimension id returns all its data
"""
if do_accept_dimension_id_none == True and dimension_id is None:
# In this special case, the method returns a dimension with id None
return get_empty_dimension()
try:
dimension = db.DBSession.query(Dimension).filter(Dimension.id==dimension_id).one()
#lazy load units
dimension.units
return JSONObject(dimension)
except NoResultFound:
# The dimension does not exist
raise ResourceNotFoundError("Dimension %s not found"%(dimension_id)) | python | def get_dimension(dimension_id, do_accept_dimension_id_none=False,**kwargs):
"""
Given a dimension id returns all its data
"""
if do_accept_dimension_id_none == True and dimension_id is None:
# In this special case, the method returns a dimension with id None
return get_empty_dimension()
try:
dimension = db.DBSession.query(Dimension).filter(Dimension.id==dimension_id).one()
#lazy load units
dimension.units
return JSONObject(dimension)
except NoResultFound:
# The dimension does not exist
raise ResourceNotFoundError("Dimension %s not found"%(dimension_id)) | [
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hydraplatform/hydra-base | hydra_base/lib/units.py | get_dimensions | def get_dimensions(**kwargs):
"""
Returns a list of objects describing all the dimensions with all the units.
"""
dimensions_list = db.DBSession.query(Dimension).options(load_only("id")).all()
return_list = []
for dimension in dimensions_list:
return_list.append(get_dimension(dimension.id))
return return_list | python | def get_dimensions(**kwargs):
"""
Returns a list of objects describing all the dimensions with all the units.
"""
dimensions_list = db.DBSession.query(Dimension).options(load_only("id")).all()
return_list = []
for dimension in dimensions_list:
return_list.append(get_dimension(dimension.id))
return return_list | [
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hydraplatform/hydra-base | hydra_base/lib/units.py | get_dimension_by_name | def get_dimension_by_name(dimension_name,**kwargs):
"""
Given a dimension name returns all its data. Used in convert functions
"""
try:
if dimension_name is None:
dimension_name = ''
dimension = db.DBSession.query(Dimension).filter(func.lower(Dimension.name)==func.lower(dimension_name.strip())).one()
return get_dimension(dimension.id)
except NoResultFound:
# The dimension does not exist
raise ResourceNotFoundError("Dimension %s not found"%(dimension_name)) | python | def get_dimension_by_name(dimension_name,**kwargs):
"""
Given a dimension name returns all its data. Used in convert functions
"""
try:
if dimension_name is None:
dimension_name = ''
dimension = db.DBSession.query(Dimension).filter(func.lower(Dimension.name)==func.lower(dimension_name.strip())).one()
return get_dimension(dimension.id)
except NoResultFound:
# The dimension does not exist
raise ResourceNotFoundError("Dimension %s not found"%(dimension_name)) | [
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hydraplatform/hydra-base | hydra_base/lib/units.py | get_unit | def get_unit(unit_id, **kwargs):
"""
Returns a single unit
"""
try:
unit = db.DBSession.query(Unit).filter(Unit.id==unit_id).one()
return JSONObject(unit)
except NoResultFound:
# The dimension does not exist
raise ResourceNotFoundError("Unit %s not found"%(unit_id)) | python | def get_unit(unit_id, **kwargs):
"""
Returns a single unit
"""
try:
unit = db.DBSession.query(Unit).filter(Unit.id==unit_id).one()
return JSONObject(unit)
except NoResultFound:
# The dimension does not exist
raise ResourceNotFoundError("Unit %s not found"%(unit_id)) | [
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hydraplatform/hydra-base | hydra_base/lib/units.py | get_units | def get_units(**kwargs):
"""
Returns all the units
"""
units_list = db.DBSession.query(Unit).all()
units = []
for unit in units_list:
new_unit = JSONObject(unit)
units.append(new_unit)
return units | python | def get_units(**kwargs):
"""
Returns all the units
"""
units_list = db.DBSession.query(Unit).all()
units = []
for unit in units_list:
new_unit = JSONObject(unit)
units.append(new_unit)
return units | [
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hydraplatform/hydra-base | hydra_base/lib/units.py | get_dimension_by_unit_measure_or_abbreviation | def get_dimension_by_unit_measure_or_abbreviation(measure_or_unit_abbreviation,**kwargs):
"""
Return the physical dimension a given unit abbreviation of a measure, or the measure itself, refers to.
The search key is the abbreviation or the full measure
"""
unit_abbreviation, factor = _parse_unit(measure_or_unit_abbreviation)
units = db.DBSession.query(Unit).filter(Unit.abbreviation==unit_abbreviation).all()
if len(units) == 0:
raise HydraError('Unit %s not found.'%(unit_abbreviation))
elif len(units) > 1:
raise HydraError('Unit %s has multiple dimensions not found.'%(unit_abbreviation))
else:
dimension = db.DBSession.query(Dimension).filter(Dimension.id==units[0].dimension_id).one()
return str(dimension.name) | python | def get_dimension_by_unit_measure_or_abbreviation(measure_or_unit_abbreviation,**kwargs):
"""
Return the physical dimension a given unit abbreviation of a measure, or the measure itself, refers to.
The search key is the abbreviation or the full measure
"""
unit_abbreviation, factor = _parse_unit(measure_or_unit_abbreviation)
units = db.DBSession.query(Unit).filter(Unit.abbreviation==unit_abbreviation).all()
if len(units) == 0:
raise HydraError('Unit %s not found.'%(unit_abbreviation))
elif len(units) > 1:
raise HydraError('Unit %s has multiple dimensions not found.'%(unit_abbreviation))
else:
dimension = db.DBSession.query(Dimension).filter(Dimension.id==units[0].dimension_id).one()
return str(dimension.name) | [
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hydraplatform/hydra-base | hydra_base/lib/units.py | get_unit_by_abbreviation | def get_unit_by_abbreviation(unit_abbreviation, **kwargs):
"""
Returns a single unit by abbreviation. Used as utility function to resolve string to id
"""
try:
if unit_abbreviation is None:
unit_abbreviation = ''
unit_i = db.DBSession.query(Unit).filter(Unit.abbreviation==unit_abbreviation.strip()).one()
return JSONObject(unit_i)
except NoResultFound:
# The dimension does not exist
raise ResourceNotFoundError("Unit '%s' not found"%(unit_abbreviation)) | python | def get_unit_by_abbreviation(unit_abbreviation, **kwargs):
"""
Returns a single unit by abbreviation. Used as utility function to resolve string to id
"""
try:
if unit_abbreviation is None:
unit_abbreviation = ''
unit_i = db.DBSession.query(Unit).filter(Unit.abbreviation==unit_abbreviation.strip()).one()
return JSONObject(unit_i)
except NoResultFound:
# The dimension does not exist
raise ResourceNotFoundError("Unit '%s' not found"%(unit_abbreviation)) | [
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hydraplatform/hydra-base | hydra_base/lib/units.py | update_dimension | def update_dimension(dimension,**kwargs):
"""
Update a dimension in the DB.
Raises and exception if the dimension does not exist.
The key is ALWAYS the name and the name itself is not modificable
"""
db_dimension = None
dimension = JSONObject(dimension)
try:
db_dimension = db.DBSession.query(Dimension).filter(Dimension.id==dimension.id).filter().one()
if "description" in dimension and dimension["description"] is not None:
db_dimension.description = dimension["description"]
if "project_id" in dimension and dimension["project_id"] is not None and dimension["project_id"] != "" and dimension["project_id"].isdigit():
db_dimension.project_id = dimension["project_id"]
except NoResultFound:
raise ResourceNotFoundError("Dimension (ID=%s) does not exist"%(dimension.id))
db.DBSession.flush()
return JSONObject(db_dimension) | python | def update_dimension(dimension,**kwargs):
"""
Update a dimension in the DB.
Raises and exception if the dimension does not exist.
The key is ALWAYS the name and the name itself is not modificable
"""
db_dimension = None
dimension = JSONObject(dimension)
try:
db_dimension = db.DBSession.query(Dimension).filter(Dimension.id==dimension.id).filter().one()
if "description" in dimension and dimension["description"] is not None:
db_dimension.description = dimension["description"]
if "project_id" in dimension and dimension["project_id"] is not None and dimension["project_id"] != "" and dimension["project_id"].isdigit():
db_dimension.project_id = dimension["project_id"]
except NoResultFound:
raise ResourceNotFoundError("Dimension (ID=%s) does not exist"%(dimension.id))
db.DBSession.flush()
return JSONObject(db_dimension) | [
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hydraplatform/hydra-base | hydra_base/lib/units.py | delete_dimension | def delete_dimension(dimension_id,**kwargs):
"""
Delete a dimension from the DB. Raises and exception if the dimension does not exist
"""
try:
dimension = db.DBSession.query(Dimension).filter(Dimension.id==dimension_id).one()
db.DBSession.query(Unit).filter(Unit.dimension_id==dimension.id).delete()
db.DBSession.delete(dimension)
db.DBSession.flush()
return True
except NoResultFound:
raise ResourceNotFoundError("Dimension (dimension_id=%s) does not exist"%(dimension_id)) | python | def delete_dimension(dimension_id,**kwargs):
"""
Delete a dimension from the DB. Raises and exception if the dimension does not exist
"""
try:
dimension = db.DBSession.query(Dimension).filter(Dimension.id==dimension_id).one()
db.DBSession.query(Unit).filter(Unit.dimension_id==dimension.id).delete()
db.DBSession.delete(dimension)
db.DBSession.flush()
return True
except NoResultFound:
raise ResourceNotFoundError("Dimension (dimension_id=%s) does not exist"%(dimension_id)) | [
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hydraplatform/hydra-base | hydra_base/lib/units.py | bulk_add_dimensions | def bulk_add_dimensions(dimension_list, **kwargs):
"""
Save all the dimensions contained in the passed list.
"""
added_dimensions = []
for dimension in dimension_list:
added_dimensions.append(add_dimension(dimension, **kwargs))
return JSONObject({"dimensions": added_dimensions}) | python | def bulk_add_dimensions(dimension_list, **kwargs):
"""
Save all the dimensions contained in the passed list.
"""
added_dimensions = []
for dimension in dimension_list:
added_dimensions.append(add_dimension(dimension, **kwargs))
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hydraplatform/hydra-base | hydra_base/lib/units.py | bulk_add_units | def bulk_add_units(unit_list, **kwargs):
"""
Save all the units contained in the passed list, with the name of their dimension.
"""
# for unit in unit_list:
# add_unit(unit, **kwargs)
added_units = []
for unit in unit_list:
added_units.append(add_unit(unit, **kwargs))
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"""
Save all the units contained in the passed list, with the name of their dimension.
"""
# for unit in unit_list:
# add_unit(unit, **kwargs)
added_units = []
for unit in unit_list:
added_units.append(add_unit(unit, **kwargs))
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hydraplatform/hydra-base | hydra_base/lib/units.py | delete_unit | def delete_unit(unit_id, **kwargs):
"""
Delete a unit from the DB.
Raises and exception if the unit does not exist
"""
try:
db_unit = db.DBSession.query(Unit).filter(Unit.id==unit_id).one()
db.DBSession.delete(db_unit)
db.DBSession.flush()
return True
except NoResultFound:
raise ResourceNotFoundError("Unit (ID=%s) does not exist"%(unit_id)) | python | def delete_unit(unit_id, **kwargs):
"""
Delete a unit from the DB.
Raises and exception if the unit does not exist
"""
try:
db_unit = db.DBSession.query(Unit).filter(Unit.id==unit_id).one()
db.DBSession.delete(db_unit)
db.DBSession.flush()
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hydraplatform/hydra-base | hydra_base/lib/units.py | update_unit | def update_unit(unit, **kwargs):
"""
Update a unit in the DB.
Raises and exception if the unit does not exist
"""
try:
db_unit = db.DBSession.query(Unit).join(Dimension).filter(Unit.id==unit["id"]).filter().one()
db_unit.name = unit["name"]
# Needed to uniform into to description
db_unit.abbreviation = unit.abbreviation
db_unit.description = unit.description
db_unit.lf = unit["lf"]
db_unit.cf = unit["cf"]
if "project_id" in unit and unit['project_id'] is not None and unit['project_id'] != "":
db_unit.project_id = unit["project_id"]
except NoResultFound:
raise ResourceNotFoundError("Unit (ID=%s) does not exist"%(unit["id"]))
db.DBSession.flush()
return JSONObject(db_unit) | python | def update_unit(unit, **kwargs):
"""
Update a unit in the DB.
Raises and exception if the unit does not exist
"""
try:
db_unit = db.DBSession.query(Unit).join(Dimension).filter(Unit.id==unit["id"]).filter().one()
db_unit.name = unit["name"]
# Needed to uniform into to description
db_unit.abbreviation = unit.abbreviation
db_unit.description = unit.description
db_unit.lf = unit["lf"]
db_unit.cf = unit["cf"]
if "project_id" in unit and unit['project_id'] is not None and unit['project_id'] != "":
db_unit.project_id = unit["project_id"]
except NoResultFound:
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db.DBSession.flush()
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multiformats/py-multibase | multibase/multibase.py | encode | def encode(encoding, data):
"""
Encodes the given data using the encoding that is specified
:param str encoding: encoding to use, should be one of the supported encoding
:param data: data to encode
:type data: str or bytes
:return: multibase encoded data
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"""
Encodes the given data using the encoding that is specified
:param str encoding: encoding to use, should be one of the supported encoding
:param data: data to encode
:type data: str or bytes
:return: multibase encoded data
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except KeyError:
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multiformats/py-multibase | multibase/multibase.py | get_codec | def get_codec(data):
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Returns the codec used to encode the given data
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:type data: str or bytes
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"""
Returns the codec used to encode the given data
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monetate/ectou-metadata | ectou_metadata/service.py | _get_role_arn | def _get_role_arn():
"""
Return role arn from X-Role-ARN header,
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"""
role_arn = bottle.request.headers.get('X-Role-ARN')
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if not role_arn:
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"""
Return role arn from X-Role-ARN header,
lookup role arn from source IP,
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"""
role_arn = bottle.request.headers.get('X-Role-ARN')
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sprockets/sprockets-dynamodb | sprockets_dynamodb/mixin.py | DynamoDBMixin._on_dynamodb_exception | def _on_dynamodb_exception(self, error):
"""Dynamically handle DynamoDB exceptions, returning HTTP error
responses.
:param exceptions.DynamoDBException error:
"""
if isinstance(error, exceptions.ConditionalCheckFailedException):
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elif isinstance(error, exceptions.NoCredentialsError):
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raise web.HTTPError(429, reason='Instance Credentials Failure')
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raise web.HTTPError(500, reason=str(error)) | python | def _on_dynamodb_exception(self, error):
"""Dynamically handle DynamoDB exceptions, returning HTTP error
responses.
:param exceptions.DynamoDBException error:
"""
if isinstance(error, exceptions.ConditionalCheckFailedException):
raise web.HTTPError(409, reason='Condition Check Failure')
elif isinstance(error, exceptions.NoCredentialsError):
if _no_creds_should_return_429():
raise web.HTTPError(429, reason='Instance Credentials Failure')
elif isinstance(error, (exceptions.ThroughputExceeded,
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raise web.HTTPError(429, reason='Too Many Requests')
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self.logger.error('DynamoDB Error: %s', error)
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sprockets/sprockets-dynamodb | sprockets_dynamodb/utils.py | marshall | def marshall(values):
"""
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:raises ValueError: if an unsupported type is encountered
Return the values in a nested dict structure that is required for
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"""
serialized = {}
for key in values:
serialized[key] = _marshall_value(values[key])
return serialized | python | def marshall(values):
"""
Marshall a `dict` into something DynamoDB likes.
:param dict values: The values to marshall
:rtype: dict
:raises ValueError: if an unsupported type is encountered
Return the values in a nested dict structure that is required for
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serialized = {}
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sprockets/sprockets-dynamodb | sprockets_dynamodb/utils.py | unmarshall | def unmarshall(values):
"""
Transform a response payload from DynamoDB to a native dict
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:rtype: dict
:raises ValueError: if an unsupported type code is encountered
"""
unmarshalled = {}
for key in values:
unmarshalled[key] = _unmarshall_dict(values[key])
return unmarshalled | python | def unmarshall(values):
"""
Transform a response payload from DynamoDB to a native dict
:param dict values: The response payload from DynamoDB
:rtype: dict
:raises ValueError: if an unsupported type code is encountered
"""
unmarshalled = {}
for key in values:
unmarshalled[key] = _unmarshall_dict(values[key])
return unmarshalled | [
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sprockets/sprockets-dynamodb | sprockets_dynamodb/utils.py | _marshall_value | def _marshall_value(value):
"""
Recursively transform `value` into an AttributeValue `dict`
:param mixed value: The value to encode
:rtype: dict
:raises ValueError: for unsupported types
Return the value as dict indicating the data type and transform or
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elif isinstance(value, datetime.datetime):
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elif isinstance(value, uuid.UUID):
return {'S': str(value)}
elif isinstance(value, list):
return {'L': [_marshall_value(v) for v in value]}
elif isinstance(value, set):
if PYTHON3 and all([isinstance(v, bytes) for v in value]):
return {'BS': _encode_binary_set(value)}
elif PYTHON3 and all([isinstance(v, str) for v in value]):
return {'SS': sorted(list(value))}
elif all([isinstance(v, (int, float)) for v in value]):
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elif not PYTHON3 and all([isinstance(v, str) for v in value]) and \
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elif not PYTHON3 and all([isinstance(v, str) for v in value]) and \
all([is_binary(v) is False for v in value]):
return {'SS': sorted(list(value))}
else:
raise ValueError('Can not mix types in a set')
elif value is None:
return {'NULL': True}
raise ValueError('Unsupported type: %s' % type(value)) | python | def _marshall_value(value):
"""
Recursively transform `value` into an AttributeValue `dict`
:param mixed value: The value to encode
:rtype: dict
:raises ValueError: for unsupported types
Return the value as dict indicating the data type and transform or
recursively process the value if required.
"""
if PYTHON3 and isinstance(value, bytes):
return {'B': base64.b64encode(value).decode('ascii')}
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return {'S': value}
elif not PYTHON3 and isinstance(value, str):
if is_binary(value):
return {'B': base64.b64encode(value).decode('ascii')}
return {'S': value}
elif not PYTHON3 and isinstance(value, unicode):
return {'S': value.encode('utf-8')}
elif isinstance(value, dict):
return {'M': marshall(value)}
elif isinstance(value, bool):
return {'BOOL': value}
elif isinstance(value, (int, float)):
return {'N': str(value)}
elif isinstance(value, datetime.datetime):
return {'S': value.isoformat()}
elif isinstance(value, uuid.UUID):
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elif isinstance(value, list):
return {'L': [_marshall_value(v) for v in value]}
elif isinstance(value, set):
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elif not PYTHON3 and all([isinstance(v, str) for v in value]) and \
all([is_binary(v) is False for v in value]):
return {'SS': sorted(list(value))}
else:
raise ValueError('Can not mix types in a set')
elif value is None:
return {'NULL': True}
raise ValueError('Unsupported type: %s' % type(value)) | [
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sprockets/sprockets-dynamodb | sprockets_dynamodb/utils.py | _unmarshall_dict | def _unmarshall_dict(value):
"""Unmarshall a single dict value from a row that was returned from
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:param dict value: The value to unmarshall
:rtype: mixed
:raises ValueError: if an unsupported type code is encountered
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raise ValueError('Unsupported value type: %s' % key) | python | def _unmarshall_dict(value):
"""Unmarshall a single dict value from a row that was returned from
DynamoDB, returning the value as a normal Python dict.
:param dict value: The value to unmarshall
:rtype: mixed
:raises ValueError: if an unsupported type code is encountered
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elif key == 'S':
return value[key]
elif key == 'SS':
return set([v for v in value[key]])
raise ValueError('Unsupported value type: %s' % key) | [
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sprockets/sprockets-dynamodb | sprockets_dynamodb/client.py | _unwrap_result | def _unwrap_result(action, result):
"""Unwrap a request response and return only the response data.
:param str action: The action name
:param result: The result of the action
:type: result: list or dict
:rtype: dict | None
"""
if not result:
return
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elif action == 'GetItem':
return _unwrap_get_item(result)
elif action == 'Query' or action == 'Scan':
return _unwrap_query_scan(result)
elif action == 'CreateTable':
return _unwrap_create_table(result)
elif action == 'DescribeTable':
return _unwrap_describe_table(result)
return result | python | def _unwrap_result(action, result):
"""Unwrap a request response and return only the response data.
:param str action: The action name
:param result: The result of the action
:type: result: list or dict
:rtype: dict | None
"""
if not result:
return
elif action in {'DeleteItem', 'PutItem', 'UpdateItem'}:
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elif action == 'GetItem':
return _unwrap_get_item(result)
elif action == 'Query' or action == 'Scan':
return _unwrap_query_scan(result)
elif action == 'CreateTable':
return _unwrap_create_table(result)
elif action == 'DescribeTable':
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return result | [
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sprockets/sprockets-dynamodb | sprockets_dynamodb/client.py | Client.list_tables | def list_tables(self, exclusive_start_table_name=None, limit=None):
"""
Invoke the `ListTables`_ function.
Returns an array of table names associated with the current account
and endpoint. The output from *ListTables* is paginated, with each page
returning a maximum of ``100`` table names.
:param str exclusive_start_table_name: The first table name that this
operation will evaluate. Use the value that was returned for
``LastEvaluatedTableName`` in a previous operation, so that you can
obtain the next page of results.
:param int limit: A maximum number of table names to return. If this
parameter is not specified, the limit is ``100``.
.. _ListTables: http://docs.aws.amazon.com/amazondynamodb/
latest/APIReference/API_ListTables.html
"""
payload = {}
if exclusive_start_table_name:
payload['ExclusiveStartTableName'] = exclusive_start_table_name
if limit:
payload['Limit'] = limit
return self.execute('ListTables', payload) | python | def list_tables(self, exclusive_start_table_name=None, limit=None):
"""
Invoke the `ListTables`_ function.
Returns an array of table names associated with the current account
and endpoint. The output from *ListTables* is paginated, with each page
returning a maximum of ``100`` table names.
:param str exclusive_start_table_name: The first table name that this
operation will evaluate. Use the value that was returned for
``LastEvaluatedTableName`` in a previous operation, so that you can
obtain the next page of results.
:param int limit: A maximum number of table names to return. If this
parameter is not specified, the limit is ``100``.
.. _ListTables: http://docs.aws.amazon.com/amazondynamodb/
latest/APIReference/API_ListTables.html
"""
payload = {}
if exclusive_start_table_name:
payload['ExclusiveStartTableName'] = exclusive_start_table_name
if limit:
payload['Limit'] = limit
return self.execute('ListTables', payload) | [
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sprockets/sprockets-dynamodb | sprockets_dynamodb/client.py | Client.get_item | def get_item(self, table_name, key_dict,
consistent_read=False,
expression_attribute_names=None,
projection_expression=None,
return_consumed_capacity=None):
"""
Invoke the `GetItem`_ function.
:param str table_name: table to retrieve the item from
:param dict key_dict: key to use for retrieval. This will
be marshalled for you so a native :class:`dict` works.
:param bool consistent_read: Determines the read consistency model: If
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:param dict expression_attribute_names: One or more substitution tokens
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:param str projection_expression: A string that identifies one or more
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the expression must be separated by commas. If no attribute names
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:param str return_consumed_capacity: Determines the level of detail
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response:
- INDEXES: The response includes the aggregate consumed
capacity for the operation, together with consumed capacity for
each table and secondary index that was accessed. Note that
some operations, such as *GetItem* and *BatchGetItem*, do not
access any indexes at all. In these cases, specifying INDEXES
will only return consumed capacity information for table(s).
- TOTAL: The response includes only the aggregate consumed
capacity for the operation.
- NONE: No consumed capacity details are included in the
response.
:rtype: tornado.concurrent.Future
.. _GetItem: http://docs.aws.amazon.com/amazondynamodb/
latest/APIReference/API_GetItem.html
"""
payload = {'TableName': table_name,
'Key': utils.marshall(key_dict),
'ConsistentRead': consistent_read}
if expression_attribute_names:
payload['ExpressionAttributeNames'] = expression_attribute_names
if projection_expression:
payload['ProjectionExpression'] = projection_expression
if return_consumed_capacity:
_validate_return_consumed_capacity(return_consumed_capacity)
payload['ReturnConsumedCapacity'] = return_consumed_capacity
return self.execute('GetItem', payload) | python | def get_item(self, table_name, key_dict,
consistent_read=False,
expression_attribute_names=None,
projection_expression=None,
return_consumed_capacity=None):
"""
Invoke the `GetItem`_ function.
:param str table_name: table to retrieve the item from
:param dict key_dict: key to use for retrieval. This will
be marshalled for you so a native :class:`dict` works.
:param bool consistent_read: Determines the read consistency model: If
set to :py:data`True`, then the operation uses strongly consistent
reads; otherwise, the operation uses eventually consistent reads.
:param dict expression_attribute_names: One or more substitution tokens
for attribute names in an expression.
:param str projection_expression: A string that identifies one or more
attributes to retrieve from the table. These attributes can include
scalars, sets, or elements of a JSON document. The attributes in
the expression must be separated by commas. If no attribute names
are specified, then all attributes will be returned. If any of the
requested attributes are not found, they will not appear in the
result.
:param str return_consumed_capacity: Determines the level of detail
about provisioned throughput consumption that is returned in the
response:
- INDEXES: The response includes the aggregate consumed
capacity for the operation, together with consumed capacity for
each table and secondary index that was accessed. Note that
some operations, such as *GetItem* and *BatchGetItem*, do not
access any indexes at all. In these cases, specifying INDEXES
will only return consumed capacity information for table(s).
- TOTAL: The response includes only the aggregate consumed
capacity for the operation.
- NONE: No consumed capacity details are included in the
response.
:rtype: tornado.concurrent.Future
.. _GetItem: http://docs.aws.amazon.com/amazondynamodb/
latest/APIReference/API_GetItem.html
"""
payload = {'TableName': table_name,
'Key': utils.marshall(key_dict),
'ConsistentRead': consistent_read}
if expression_attribute_names:
payload['ExpressionAttributeNames'] = expression_attribute_names
if projection_expression:
payload['ProjectionExpression'] = projection_expression
if return_consumed_capacity:
_validate_return_consumed_capacity(return_consumed_capacity)
payload['ReturnConsumedCapacity'] = return_consumed_capacity
return self.execute('GetItem', payload) | [
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:param bool consistent_read: Determines the read consistency model: If
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- INDEXES: The response includes the aggregate consumed
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each table and secondary index that was accessed. Note that
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- TOTAL: The response includes only the aggregate consumed
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- NONE: No consumed capacity details are included in the
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sprockets/sprockets-dynamodb | sprockets_dynamodb/client.py | Client.update_item | def update_item(self, table_name, key_dict,
condition_expression=None,
update_expression=None,
expression_attribute_names=None,
expression_attribute_values=None,
return_consumed_capacity=None,
return_item_collection_metrics=None,
return_values=None):
"""Invoke the `UpdateItem`_ function.
Edits an existing item's attributes, or adds a new item to the table
if it does not already exist. You can put, delete, or add attribute
values. You can also perform a conditional update on an existing item
(insert a new attribute name-value pair if it doesn't exist, or replace
an existing name-value pair if it has certain expected attribute
values).
:param str table_name: The name of the table that contains the item to
update
:param dict key_dict: A dictionary of key/value pairs that are used to
define the primary key values for the item. For the primary key,
you must provide all of the attributes. For example, with a simple
primary key, you only need to provide a value for the partition
key. For a composite primary key, you must provide values for both
the partition key and the sort key.
:param str condition_expression: A condition that must be satisfied in
order for a conditional *UpdateItem* operation to succeed. One of:
``attribute_exists``, ``attribute_not_exists``, ``attribute_type``,
``contains``, ``begins_with``, ``size``, ``=``, ``<>``, ``<``,
``>``, ``<=``, ``>=``, ``BETWEEN``, ``IN``, ``AND``, ``OR``, or
``NOT``.
:param str update_expression: An expression that defines one or more
attributes to be updated, the action to be performed on them, and
new value(s) for them.
:param dict expression_attribute_names: One or more substitution tokens
for attribute names in an expression.
:param dict expression_attribute_values: One or more values that can be
substituted in an expression.
:param str return_consumed_capacity: Determines the level of detail
about provisioned throughput consumption that is returned in the
response. See the `AWS documentation
for ReturnConsumedCapacity <http://docs.aws.amazon.com/
amazondynamodb/latest/APIReference/API_UpdateItem.html#DDB-Update
Item-request-ReturnConsumedCapacity>`_ for more information.
:param str return_item_collection_metrics: Determines whether item
collection metrics are returned.
:param str return_values: Use ReturnValues if you want to get the item
attributes as they appeared either before or after they were
updated. See the `AWS documentation for ReturnValues <http://docs.
aws.amazon.com/amazondynamodb/latest/APIReference/
API_UpdateItem.html#DDB-UpdateItem-request-ReturnValues>`_
:rtype: tornado.concurrent.Future
.. _UpdateItem: http://docs.aws.amazon.com/amazondynamodb/
latest/APIReference/API_UpdateItem.html
"""
payload = {'TableName': table_name,
'Key': utils.marshall(key_dict),
'UpdateExpression': update_expression}
if condition_expression:
payload['ConditionExpression'] = condition_expression
if expression_attribute_names:
payload['ExpressionAttributeNames'] = expression_attribute_names
if expression_attribute_values:
payload['ExpressionAttributeValues'] = \
utils.marshall(expression_attribute_values)
if return_consumed_capacity:
_validate_return_consumed_capacity(return_consumed_capacity)
payload['ReturnConsumedCapacity'] = return_consumed_capacity
if return_item_collection_metrics:
_validate_return_item_collection_metrics(
return_item_collection_metrics)
payload['ReturnItemCollectionMetrics'] = \
return_item_collection_metrics
if return_values:
_validate_return_values(return_values)
payload['ReturnValues'] = return_values
return self.execute('UpdateItem', payload) | python | def update_item(self, table_name, key_dict,
condition_expression=None,
update_expression=None,
expression_attribute_names=None,
expression_attribute_values=None,
return_consumed_capacity=None,
return_item_collection_metrics=None,
return_values=None):
"""Invoke the `UpdateItem`_ function.
Edits an existing item's attributes, or adds a new item to the table
if it does not already exist. You can put, delete, or add attribute
values. You can also perform a conditional update on an existing item
(insert a new attribute name-value pair if it doesn't exist, or replace
an existing name-value pair if it has certain expected attribute
values).
:param str table_name: The name of the table that contains the item to
update
:param dict key_dict: A dictionary of key/value pairs that are used to
define the primary key values for the item. For the primary key,
you must provide all of the attributes. For example, with a simple
primary key, you only need to provide a value for the partition
key. For a composite primary key, you must provide values for both
the partition key and the sort key.
:param str condition_expression: A condition that must be satisfied in
order for a conditional *UpdateItem* operation to succeed. One of:
``attribute_exists``, ``attribute_not_exists``, ``attribute_type``,
``contains``, ``begins_with``, ``size``, ``=``, ``<>``, ``<``,
``>``, ``<=``, ``>=``, ``BETWEEN``, ``IN``, ``AND``, ``OR``, or
``NOT``.
:param str update_expression: An expression that defines one or more
attributes to be updated, the action to be performed on them, and
new value(s) for them.
:param dict expression_attribute_names: One or more substitution tokens
for attribute names in an expression.
:param dict expression_attribute_values: One or more values that can be
substituted in an expression.
:param str return_consumed_capacity: Determines the level of detail
about provisioned throughput consumption that is returned in the
response. See the `AWS documentation
for ReturnConsumedCapacity <http://docs.aws.amazon.com/
amazondynamodb/latest/APIReference/API_UpdateItem.html#DDB-Update
Item-request-ReturnConsumedCapacity>`_ for more information.
:param str return_item_collection_metrics: Determines whether item
collection metrics are returned.
:param str return_values: Use ReturnValues if you want to get the item
attributes as they appeared either before or after they were
updated. See the `AWS documentation for ReturnValues <http://docs.
aws.amazon.com/amazondynamodb/latest/APIReference/
API_UpdateItem.html#DDB-UpdateItem-request-ReturnValues>`_
:rtype: tornado.concurrent.Future
.. _UpdateItem: http://docs.aws.amazon.com/amazondynamodb/
latest/APIReference/API_UpdateItem.html
"""
payload = {'TableName': table_name,
'Key': utils.marshall(key_dict),
'UpdateExpression': update_expression}
if condition_expression:
payload['ConditionExpression'] = condition_expression
if expression_attribute_names:
payload['ExpressionAttributeNames'] = expression_attribute_names
if expression_attribute_values:
payload['ExpressionAttributeValues'] = \
utils.marshall(expression_attribute_values)
if return_consumed_capacity:
_validate_return_consumed_capacity(return_consumed_capacity)
payload['ReturnConsumedCapacity'] = return_consumed_capacity
if return_item_collection_metrics:
_validate_return_item_collection_metrics(
return_item_collection_metrics)
payload['ReturnItemCollectionMetrics'] = \
return_item_collection_metrics
if return_values:
_validate_return_values(return_values)
payload['ReturnValues'] = return_values
return self.execute('UpdateItem', payload) | [
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"return_cons... | Invoke the `UpdateItem`_ function.
Edits an existing item's attributes, or adds a new item to the table
if it does not already exist. You can put, delete, or add attribute
values. You can also perform a conditional update on an existing item
(insert a new attribute name-value pair if it doesn't exist, or replace
an existing name-value pair if it has certain expected attribute
values).
:param str table_name: The name of the table that contains the item to
update
:param dict key_dict: A dictionary of key/value pairs that are used to
define the primary key values for the item. For the primary key,
you must provide all of the attributes. For example, with a simple
primary key, you only need to provide a value for the partition
key. For a composite primary key, you must provide values for both
the partition key and the sort key.
:param str condition_expression: A condition that must be satisfied in
order for a conditional *UpdateItem* operation to succeed. One of:
``attribute_exists``, ``attribute_not_exists``, ``attribute_type``,
``contains``, ``begins_with``, ``size``, ``=``, ``<>``, ``<``,
``>``, ``<=``, ``>=``, ``BETWEEN``, ``IN``, ``AND``, ``OR``, or
``NOT``.
:param str update_expression: An expression that defines one or more
attributes to be updated, the action to be performed on them, and
new value(s) for them.
:param dict expression_attribute_names: One or more substitution tokens
for attribute names in an expression.
:param dict expression_attribute_values: One or more values that can be
substituted in an expression.
:param str return_consumed_capacity: Determines the level of detail
about provisioned throughput consumption that is returned in the
response. See the `AWS documentation
for ReturnConsumedCapacity <http://docs.aws.amazon.com/
amazondynamodb/latest/APIReference/API_UpdateItem.html#DDB-Update
Item-request-ReturnConsumedCapacity>`_ for more information.
:param str return_item_collection_metrics: Determines whether item
collection metrics are returned.
:param str return_values: Use ReturnValues if you want to get the item
attributes as they appeared either before or after they were
updated. See the `AWS documentation for ReturnValues <http://docs.
aws.amazon.com/amazondynamodb/latest/APIReference/
API_UpdateItem.html#DDB-UpdateItem-request-ReturnValues>`_
:rtype: tornado.concurrent.Future
.. _UpdateItem: http://docs.aws.amazon.com/amazondynamodb/
latest/APIReference/API_UpdateItem.html | [
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"."
] | 2e202bcb01f23f828f91299599311007054de4aa | https://github.com/sprockets/sprockets-dynamodb/blob/2e202bcb01f23f828f91299599311007054de4aa/sprockets_dynamodb/client.py#L333-L411 | train | 46,161 |
sprockets/sprockets-dynamodb | sprockets_dynamodb/client.py | Client.query | def query(self, table_name,
index_name=None,
consistent_read=None,
key_condition_expression=None,
filter_expression=None,
expression_attribute_names=None,
expression_attribute_values=None,
projection_expression=None,
select=None,
exclusive_start_key=None,
limit=None,
scan_index_forward=True,
return_consumed_capacity=None):
"""A `Query`_ operation uses the primary key of a table or a secondary
index to directly access items from that table or index.
:param str table_name: The name of the table containing the requested
items.
:param bool consistent_read: Determines the read consistency model: If
set to ``True``, then the operation uses strongly consistent reads;
otherwise, the operation uses eventually consistent reads. Strongly
consistent reads are not supported on global secondary indexes. If
you query a global secondary index with ``consistent_read`` set to
``True``, you will receive a
:exc:`~sprockets_dynamodb.exceptions.ValidationException`.
:param dict exclusive_start_key: The primary key of the first
item that this operation will evaluate. Use the value that was
returned for ``LastEvaluatedKey`` in the previous operation. In a
parallel scan, a *Scan* request that includes
``exclusive_start_key`` must specify the same segment whose
previous *Scan* returned the corresponding value of
``LastEvaluatedKey``.
:param dict expression_attribute_names: One or more substitution tokens
for attribute names in an expression.
:param dict expression_attribute_values: One or more values that can be
substituted in an expression.
:param str key_condition_expression: The condition that specifies the
key value(s) for items to be retrieved by the *Query* action. The
condition must perform an equality test on a single partition key
value, but can optionally perform one of several comparison tests
on a single sort key value. The partition key equality test is
required. For examples see `KeyConditionExpression
<https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/
Query.html#Query.KeyConditionExpressions>.
:param str filter_expression: A string that contains conditions that
DynamoDB applies after the *Query* operation, but before the data
is returned to you. Items that do not satisfy the criteria are not
returned. Note that a filter expression is applied after the items
have already been read; the process of filtering does not consume
any additional read capacity units. For more information, see
`Filter Expressions <http://docs.aws.amazon.com/amazondynamodb/
latest/developerguide/QueryAndScan.html#FilteringResults>`_ in the
Amazon DynamoDB Developer Guide.
:param str projection_expression:
:param str index_name: The name of a secondary index to query. This
index can be any local secondary index or global secondary index.
Note that if you use this parameter, you must also provide
``table_name``.
:param int limit: The maximum number of items to evaluate (not
necessarily the number of matching items). If DynamoDB processes
the number of items up to the limit while processing the results,
it stops the operation and returns the matching values up to that
point, and a key in ``LastEvaluatedKey`` to apply in a subsequent
operation, so that you can pick up where you left off. Also, if the
processed data set size exceeds 1 MB before DynamoDB reaches this
limit, it stops the operation and returns the matching values up to
the limit, and a key in ``LastEvaluatedKey`` to apply in a
subsequent operation to continue the operation. For more
information, see `Query and Scan <http://docs.aws.amazon.com/amazo
ndynamodb/latest/developerguide/QueryAndScan.html>`_ in the Amazon
DynamoDB Developer Guide.
:param str return_consumed_capacity: Determines the level of detail
about provisioned throughput consumption that is returned in the
response:
- ``INDEXES``: The response includes the aggregate consumed
capacity for the operation, together with consumed capacity for
each table and secondary index that was accessed. Note that
some operations, such as *GetItem* and *BatchGetItem*, do not
access any indexes at all. In these cases, specifying
``INDEXES`` will only return consumed capacity information for
table(s).
- ``TOTAL``: The response includes only the aggregate consumed
capacity for the operation.
- ``NONE``: No consumed capacity details are included in the
response.
:param bool scan_index_forward: Specifies the order for index
traversal: If ``True`` (default), the traversal is performed in
ascending order; if ``False``, the traversal is performed in
descending order. Items with the same partition key value are
stored in sorted order by sort key. If the sort key data type is
*Number*, the results are stored in numeric order. For type
*String*, the results are stored in order of ASCII character code
values. For type *Binary*, DynamoDB treats each byte of the binary
data as unsigned. If set to ``True``, DynamoDB returns the results
in the order in which they are stored (by sort key value). This is
the default behavior. If set to ``False``, DynamoDB reads the
results in reverse order by sort key value, and then returns the
results to the client.
:param str select: The attributes to be returned in the result. You can
retrieve all item attributes, specific item attributes, the count
of matching items, or in the case of an index, some or all of the
attributes projected into the index. Possible values are:
- ``ALL_ATTRIBUTES``: Returns all of the item attributes from the
specified table or index. If you query a local secondary index,
then for each matching item in the index DynamoDB will fetch
the entire item from the parent table. If the index is
configured to project all item attributes, then all of the data
can be obtained from the local secondary index, and no fetching
is required.
- ``ALL_PROJECTED_ATTRIBUTES``: Allowed only when querying an
index. Retrieves all attributes that have been projected into
the index. If the index is configured to project all
attributes, this return value is equivalent to specifying
``ALL_ATTRIBUTES``.
- ``COUNT``: Returns the number of matching items, rather than
the matching items themselves.
:rtype: dict
.. _Query: http://docs.aws.amazon.com/amazondynamodb/
latest/APIReference/API_Query.html
"""
payload = {'TableName': table_name,
'ScanIndexForward': scan_index_forward}
if index_name:
payload['IndexName'] = index_name
if consistent_read is not None:
payload['ConsistentRead'] = consistent_read
if key_condition_expression:
payload['KeyConditionExpression'] = key_condition_expression
if filter_expression:
payload['FilterExpression'] = filter_expression
if expression_attribute_names:
payload['ExpressionAttributeNames'] = expression_attribute_names
if expression_attribute_values:
payload['ExpressionAttributeValues'] = \
utils.marshall(expression_attribute_values)
if projection_expression:
payload['ProjectionExpression'] = projection_expression
if select:
_validate_select(select)
payload['Select'] = select
if exclusive_start_key:
payload['ExclusiveStartKey'] = utils.marshall(exclusive_start_key)
if limit:
payload['Limit'] = limit
if return_consumed_capacity:
_validate_return_consumed_capacity(return_consumed_capacity)
payload['ReturnConsumedCapacity'] = return_consumed_capacity
return self.execute('Query', payload) | python | def query(self, table_name,
index_name=None,
consistent_read=None,
key_condition_expression=None,
filter_expression=None,
expression_attribute_names=None,
expression_attribute_values=None,
projection_expression=None,
select=None,
exclusive_start_key=None,
limit=None,
scan_index_forward=True,
return_consumed_capacity=None):
"""A `Query`_ operation uses the primary key of a table or a secondary
index to directly access items from that table or index.
:param str table_name: The name of the table containing the requested
items.
:param bool consistent_read: Determines the read consistency model: If
set to ``True``, then the operation uses strongly consistent reads;
otherwise, the operation uses eventually consistent reads. Strongly
consistent reads are not supported on global secondary indexes. If
you query a global secondary index with ``consistent_read`` set to
``True``, you will receive a
:exc:`~sprockets_dynamodb.exceptions.ValidationException`.
:param dict exclusive_start_key: The primary key of the first
item that this operation will evaluate. Use the value that was
returned for ``LastEvaluatedKey`` in the previous operation. In a
parallel scan, a *Scan* request that includes
``exclusive_start_key`` must specify the same segment whose
previous *Scan* returned the corresponding value of
``LastEvaluatedKey``.
:param dict expression_attribute_names: One or more substitution tokens
for attribute names in an expression.
:param dict expression_attribute_values: One or more values that can be
substituted in an expression.
:param str key_condition_expression: The condition that specifies the
key value(s) for items to be retrieved by the *Query* action. The
condition must perform an equality test on a single partition key
value, but can optionally perform one of several comparison tests
on a single sort key value. The partition key equality test is
required. For examples see `KeyConditionExpression
<https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/
Query.html#Query.KeyConditionExpressions>.
:param str filter_expression: A string that contains conditions that
DynamoDB applies after the *Query* operation, but before the data
is returned to you. Items that do not satisfy the criteria are not
returned. Note that a filter expression is applied after the items
have already been read; the process of filtering does not consume
any additional read capacity units. For more information, see
`Filter Expressions <http://docs.aws.amazon.com/amazondynamodb/
latest/developerguide/QueryAndScan.html#FilteringResults>`_ in the
Amazon DynamoDB Developer Guide.
:param str projection_expression:
:param str index_name: The name of a secondary index to query. This
index can be any local secondary index or global secondary index.
Note that if you use this parameter, you must also provide
``table_name``.
:param int limit: The maximum number of items to evaluate (not
necessarily the number of matching items). If DynamoDB processes
the number of items up to the limit while processing the results,
it stops the operation and returns the matching values up to that
point, and a key in ``LastEvaluatedKey`` to apply in a subsequent
operation, so that you can pick up where you left off. Also, if the
processed data set size exceeds 1 MB before DynamoDB reaches this
limit, it stops the operation and returns the matching values up to
the limit, and a key in ``LastEvaluatedKey`` to apply in a
subsequent operation to continue the operation. For more
information, see `Query and Scan <http://docs.aws.amazon.com/amazo
ndynamodb/latest/developerguide/QueryAndScan.html>`_ in the Amazon
DynamoDB Developer Guide.
:param str return_consumed_capacity: Determines the level of detail
about provisioned throughput consumption that is returned in the
response:
- ``INDEXES``: The response includes the aggregate consumed
capacity for the operation, together with consumed capacity for
each table and secondary index that was accessed. Note that
some operations, such as *GetItem* and *BatchGetItem*, do not
access any indexes at all. In these cases, specifying
``INDEXES`` will only return consumed capacity information for
table(s).
- ``TOTAL``: The response includes only the aggregate consumed
capacity for the operation.
- ``NONE``: No consumed capacity details are included in the
response.
:param bool scan_index_forward: Specifies the order for index
traversal: If ``True`` (default), the traversal is performed in
ascending order; if ``False``, the traversal is performed in
descending order. Items with the same partition key value are
stored in sorted order by sort key. If the sort key data type is
*Number*, the results are stored in numeric order. For type
*String*, the results are stored in order of ASCII character code
values. For type *Binary*, DynamoDB treats each byte of the binary
data as unsigned. If set to ``True``, DynamoDB returns the results
in the order in which they are stored (by sort key value). This is
the default behavior. If set to ``False``, DynamoDB reads the
results in reverse order by sort key value, and then returns the
results to the client.
:param str select: The attributes to be returned in the result. You can
retrieve all item attributes, specific item attributes, the count
of matching items, or in the case of an index, some or all of the
attributes projected into the index. Possible values are:
- ``ALL_ATTRIBUTES``: Returns all of the item attributes from the
specified table or index. If you query a local secondary index,
then for each matching item in the index DynamoDB will fetch
the entire item from the parent table. If the index is
configured to project all item attributes, then all of the data
can be obtained from the local secondary index, and no fetching
is required.
- ``ALL_PROJECTED_ATTRIBUTES``: Allowed only when querying an
index. Retrieves all attributes that have been projected into
the index. If the index is configured to project all
attributes, this return value is equivalent to specifying
``ALL_ATTRIBUTES``.
- ``COUNT``: Returns the number of matching items, rather than
the matching items themselves.
:rtype: dict
.. _Query: http://docs.aws.amazon.com/amazondynamodb/
latest/APIReference/API_Query.html
"""
payload = {'TableName': table_name,
'ScanIndexForward': scan_index_forward}
if index_name:
payload['IndexName'] = index_name
if consistent_read is not None:
payload['ConsistentRead'] = consistent_read
if key_condition_expression:
payload['KeyConditionExpression'] = key_condition_expression
if filter_expression:
payload['FilterExpression'] = filter_expression
if expression_attribute_names:
payload['ExpressionAttributeNames'] = expression_attribute_names
if expression_attribute_values:
payload['ExpressionAttributeValues'] = \
utils.marshall(expression_attribute_values)
if projection_expression:
payload['ProjectionExpression'] = projection_expression
if select:
_validate_select(select)
payload['Select'] = select
if exclusive_start_key:
payload['ExclusiveStartKey'] = utils.marshall(exclusive_start_key)
if limit:
payload['Limit'] = limit
if return_consumed_capacity:
_validate_return_consumed_capacity(return_consumed_capacity)
payload['ReturnConsumedCapacity'] = return_consumed_capacity
return self.execute('Query', payload) | [
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index to directly access items from that table or index.
:param str table_name: The name of the table containing the requested
items.
:param bool consistent_read: Determines the read consistency model: If
set to ``True``, then the operation uses strongly consistent reads;
otherwise, the operation uses eventually consistent reads. Strongly
consistent reads are not supported on global secondary indexes. If
you query a global secondary index with ``consistent_read`` set to
``True``, you will receive a
:exc:`~sprockets_dynamodb.exceptions.ValidationException`.
:param dict exclusive_start_key: The primary key of the first
item that this operation will evaluate. Use the value that was
returned for ``LastEvaluatedKey`` in the previous operation. In a
parallel scan, a *Scan* request that includes
``exclusive_start_key`` must specify the same segment whose
previous *Scan* returned the corresponding value of
``LastEvaluatedKey``.
:param dict expression_attribute_names: One or more substitution tokens
for attribute names in an expression.
:param dict expression_attribute_values: One or more values that can be
substituted in an expression.
:param str key_condition_expression: The condition that specifies the
key value(s) for items to be retrieved by the *Query* action. The
condition must perform an equality test on a single partition key
value, but can optionally perform one of several comparison tests
on a single sort key value. The partition key equality test is
required. For examples see `KeyConditionExpression
<https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/
Query.html#Query.KeyConditionExpressions>.
:param str filter_expression: A string that contains conditions that
DynamoDB applies after the *Query* operation, but before the data
is returned to you. Items that do not satisfy the criteria are not
returned. Note that a filter expression is applied after the items
have already been read; the process of filtering does not consume
any additional read capacity units. For more information, see
`Filter Expressions <http://docs.aws.amazon.com/amazondynamodb/
latest/developerguide/QueryAndScan.html#FilteringResults>`_ in the
Amazon DynamoDB Developer Guide.
:param str projection_expression:
:param str index_name: The name of a secondary index to query. This
index can be any local secondary index or global secondary index.
Note that if you use this parameter, you must also provide
``table_name``.
:param int limit: The maximum number of items to evaluate (not
necessarily the number of matching items). If DynamoDB processes
the number of items up to the limit while processing the results,
it stops the operation and returns the matching values up to that
point, and a key in ``LastEvaluatedKey`` to apply in a subsequent
operation, so that you can pick up where you left off. Also, if the
processed data set size exceeds 1 MB before DynamoDB reaches this
limit, it stops the operation and returns the matching values up to
the limit, and a key in ``LastEvaluatedKey`` to apply in a
subsequent operation to continue the operation. For more
information, see `Query and Scan <http://docs.aws.amazon.com/amazo
ndynamodb/latest/developerguide/QueryAndScan.html>`_ in the Amazon
DynamoDB Developer Guide.
:param str return_consumed_capacity: Determines the level of detail
about provisioned throughput consumption that is returned in the
response:
- ``INDEXES``: The response includes the aggregate consumed
capacity for the operation, together with consumed capacity for
each table and secondary index that was accessed. Note that
some operations, such as *GetItem* and *BatchGetItem*, do not
access any indexes at all. In these cases, specifying
``INDEXES`` will only return consumed capacity information for
table(s).
- ``TOTAL``: The response includes only the aggregate consumed
capacity for the operation.
- ``NONE``: No consumed capacity details are included in the
response.
:param bool scan_index_forward: Specifies the order for index
traversal: If ``True`` (default), the traversal is performed in
ascending order; if ``False``, the traversal is performed in
descending order. Items with the same partition key value are
stored in sorted order by sort key. If the sort key data type is
*Number*, the results are stored in numeric order. For type
*String*, the results are stored in order of ASCII character code
values. For type *Binary*, DynamoDB treats each byte of the binary
data as unsigned. If set to ``True``, DynamoDB returns the results
in the order in which they are stored (by sort key value). This is
the default behavior. If set to ``False``, DynamoDB reads the
results in reverse order by sort key value, and then returns the
results to the client.
:param str select: The attributes to be returned in the result. You can
retrieve all item attributes, specific item attributes, the count
of matching items, or in the case of an index, some or all of the
attributes projected into the index. Possible values are:
- ``ALL_ATTRIBUTES``: Returns all of the item attributes from the
specified table or index. If you query a local secondary index,
then for each matching item in the index DynamoDB will fetch
the entire item from the parent table. If the index is
configured to project all item attributes, then all of the data
can be obtained from the local secondary index, and no fetching
is required.
- ``ALL_PROJECTED_ATTRIBUTES``: Allowed only when querying an
index. Retrieves all attributes that have been projected into
the index. If the index is configured to project all
attributes, this return value is equivalent to specifying
``ALL_ATTRIBUTES``.
- ``COUNT``: Returns the number of matching items, rather than
the matching items themselves.
:rtype: dict
.. _Query: http://docs.aws.amazon.com/amazondynamodb/
latest/APIReference/API_Query.html | [
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sprockets/sprockets-dynamodb | sprockets_dynamodb/client.py | Client.scan | def scan(self,
table_name,
index_name=None,
consistent_read=None,
projection_expression=None,
filter_expression=None,
expression_attribute_names=None,
expression_attribute_values=None,
segment=None,
total_segments=None,
select=None,
limit=None,
exclusive_start_key=None,
return_consumed_capacity=None):
"""The `Scan`_ operation returns one or more items and item attributes
by accessing every item in a table or a secondary index.
If the total number of scanned items exceeds the maximum data set size
limit of 1 MB, the scan stops and results are returned to the user as a
``LastEvaluatedKey`` value to continue the scan in a subsequent
operation. The results also include the number of items exceeding the
limit. A scan can result in no table data meeting the filter criteria.
By default, Scan operations proceed sequentially; however, for faster
performance on a large table or secondary index, applications can
request a parallel *Scan* operation by providing the ``segment`` and
``total_segments`` parameters. For more information, see
`Parallel Scan <http://docs.aws.amazon.com/amazondynamodb/latest/
developerguide/QueryAndScan.html#QueryAndScanParallelScan>`_ in the
Amazon DynamoDB Developer Guide.
By default, *Scan* uses eventually consistent reads when accessing the
data in a table; therefore, the result set might not include the
changes to data in the table immediately before the operation began. If
you need a consistent copy of the data, as of the time that the *Scan*
begins, you can set the ``consistent_read`` parameter to ``True``.
:rtype: dict
.. _Scan: http://docs.aws.amazon.com/amazondynamodb/
latest/APIReference/API_Scan.html
"""
payload = {'TableName': table_name}
if index_name:
payload['IndexName'] = index_name
if consistent_read is not None:
payload['ConsistentRead'] = consistent_read
if filter_expression:
payload['FilterExpression'] = filter_expression
if expression_attribute_names:
payload['ExpressionAttributeNames'] = expression_attribute_names
if expression_attribute_values:
payload['ExpressionAttributeValues'] = \
utils.marshall(expression_attribute_values)
if projection_expression:
payload['ProjectionExpression'] = projection_expression
if segment:
payload['Segment'] = segment
if total_segments:
payload['TotalSegments'] = total_segments
if select:
_validate_select(select)
payload['Select'] = select
if exclusive_start_key:
payload['ExclusiveStartKey'] = utils.marshall(exclusive_start_key)
if limit:
payload['Limit'] = limit
if return_consumed_capacity:
_validate_return_consumed_capacity(return_consumed_capacity)
payload['ReturnConsumedCapacity'] = return_consumed_capacity
return self.execute('Scan', payload) | python | def scan(self,
table_name,
index_name=None,
consistent_read=None,
projection_expression=None,
filter_expression=None,
expression_attribute_names=None,
expression_attribute_values=None,
segment=None,
total_segments=None,
select=None,
limit=None,
exclusive_start_key=None,
return_consumed_capacity=None):
"""The `Scan`_ operation returns one or more items and item attributes
by accessing every item in a table or a secondary index.
If the total number of scanned items exceeds the maximum data set size
limit of 1 MB, the scan stops and results are returned to the user as a
``LastEvaluatedKey`` value to continue the scan in a subsequent
operation. The results also include the number of items exceeding the
limit. A scan can result in no table data meeting the filter criteria.
By default, Scan operations proceed sequentially; however, for faster
performance on a large table or secondary index, applications can
request a parallel *Scan* operation by providing the ``segment`` and
``total_segments`` parameters. For more information, see
`Parallel Scan <http://docs.aws.amazon.com/amazondynamodb/latest/
developerguide/QueryAndScan.html#QueryAndScanParallelScan>`_ in the
Amazon DynamoDB Developer Guide.
By default, *Scan* uses eventually consistent reads when accessing the
data in a table; therefore, the result set might not include the
changes to data in the table immediately before the operation began. If
you need a consistent copy of the data, as of the time that the *Scan*
begins, you can set the ``consistent_read`` parameter to ``True``.
:rtype: dict
.. _Scan: http://docs.aws.amazon.com/amazondynamodb/
latest/APIReference/API_Scan.html
"""
payload = {'TableName': table_name}
if index_name:
payload['IndexName'] = index_name
if consistent_read is not None:
payload['ConsistentRead'] = consistent_read
if filter_expression:
payload['FilterExpression'] = filter_expression
if expression_attribute_names:
payload['ExpressionAttributeNames'] = expression_attribute_names
if expression_attribute_values:
payload['ExpressionAttributeValues'] = \
utils.marshall(expression_attribute_values)
if projection_expression:
payload['ProjectionExpression'] = projection_expression
if segment:
payload['Segment'] = segment
if total_segments:
payload['TotalSegments'] = total_segments
if select:
_validate_select(select)
payload['Select'] = select
if exclusive_start_key:
payload['ExclusiveStartKey'] = utils.marshall(exclusive_start_key)
if limit:
payload['Limit'] = limit
if return_consumed_capacity:
_validate_return_consumed_capacity(return_consumed_capacity)
payload['ReturnConsumedCapacity'] = return_consumed_capacity
return self.execute('Scan', payload) | [
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sprockets/sprockets-dynamodb | sprockets_dynamodb/client.py | Client.execute | def execute(self, action, parameters):
"""
Execute a DynamoDB action with the given parameters. The method will
retry requests that failed due to OS level errors or when being
throttled by DynamoDB.
:param str action: DynamoDB action to invoke
:param dict parameters: parameters to send into the action
:rtype: tornado.concurrent.Future
This method creates a future that will resolve to the result
of calling the specified DynamoDB function. It does it's best
to unwrap the response from the function to make life a little
easier for you. It does this for the ``GetItem`` and ``Query``
functions currently.
:raises:
:exc:`~sprockets_dynamodb.exceptions.DynamoDBException`
:exc:`~sprockets_dynamodb.exceptions.ConfigNotFound`
:exc:`~sprockets_dynamodb.exceptions.NoCredentialsError`
:exc:`~sprockets_dynamodb.exceptions.NoProfileError`
:exc:`~sprockets_dynamodb.exceptions.TimeoutException`
:exc:`~sprockets_dynamodb.exceptions.RequestException`
:exc:`~sprockets_dynamodb.exceptions.InternalFailure`
:exc:`~sprockets_dynamodb.exceptions.LimitExceeded`
:exc:`~sprockets_dynamodb.exceptions.MissingParameter`
:exc:`~sprockets_dynamodb.exceptions.OptInRequired`
:exc:`~sprockets_dynamodb.exceptions.ResourceInUse`
:exc:`~sprockets_dynamodb.exceptions.RequestExpired`
:exc:`~sprockets_dynamodb.exceptions.ResourceNotFound`
:exc:`~sprockets_dynamodb.exceptions.ServiceUnavailable`
:exc:`~sprockets_dynamodb.exceptions.ThroughputExceeded`
:exc:`~sprockets_dynamodb.exceptions.ValidationException`
"""
measurements = collections.deque([], self._max_retries)
for attempt in range(1, self._max_retries + 1):
try:
result = yield self._execute(
action, parameters, attempt, measurements)
except (exceptions.InternalServerError,
exceptions.RequestException,
exceptions.ThrottlingException,
exceptions.ThroughputExceeded,
exceptions.ServiceUnavailable) as error:
if attempt == self._max_retries:
if self._instrumentation_callback:
self._instrumentation_callback(measurements)
self._on_exception(error)
duration = self._sleep_duration(attempt)
self.logger.warning('%r on attempt %i, sleeping %.2f seconds',
error, attempt, duration)
yield gen.sleep(duration)
except exceptions.DynamoDBException as error:
if self._instrumentation_callback:
self._instrumentation_callback(measurements)
self._on_exception(error)
else:
if self._instrumentation_callback:
self._instrumentation_callback(measurements)
self.logger.debug('%s result: %r', action, result)
raise gen.Return(_unwrap_result(action, result)) | python | def execute(self, action, parameters):
"""
Execute a DynamoDB action with the given parameters. The method will
retry requests that failed due to OS level errors or when being
throttled by DynamoDB.
:param str action: DynamoDB action to invoke
:param dict parameters: parameters to send into the action
:rtype: tornado.concurrent.Future
This method creates a future that will resolve to the result
of calling the specified DynamoDB function. It does it's best
to unwrap the response from the function to make life a little
easier for you. It does this for the ``GetItem`` and ``Query``
functions currently.
:raises:
:exc:`~sprockets_dynamodb.exceptions.DynamoDBException`
:exc:`~sprockets_dynamodb.exceptions.ConfigNotFound`
:exc:`~sprockets_dynamodb.exceptions.NoCredentialsError`
:exc:`~sprockets_dynamodb.exceptions.NoProfileError`
:exc:`~sprockets_dynamodb.exceptions.TimeoutException`
:exc:`~sprockets_dynamodb.exceptions.RequestException`
:exc:`~sprockets_dynamodb.exceptions.InternalFailure`
:exc:`~sprockets_dynamodb.exceptions.LimitExceeded`
:exc:`~sprockets_dynamodb.exceptions.MissingParameter`
:exc:`~sprockets_dynamodb.exceptions.OptInRequired`
:exc:`~sprockets_dynamodb.exceptions.ResourceInUse`
:exc:`~sprockets_dynamodb.exceptions.RequestExpired`
:exc:`~sprockets_dynamodb.exceptions.ResourceNotFound`
:exc:`~sprockets_dynamodb.exceptions.ServiceUnavailable`
:exc:`~sprockets_dynamodb.exceptions.ThroughputExceeded`
:exc:`~sprockets_dynamodb.exceptions.ValidationException`
"""
measurements = collections.deque([], self._max_retries)
for attempt in range(1, self._max_retries + 1):
try:
result = yield self._execute(
action, parameters, attempt, measurements)
except (exceptions.InternalServerError,
exceptions.RequestException,
exceptions.ThrottlingException,
exceptions.ThroughputExceeded,
exceptions.ServiceUnavailable) as error:
if attempt == self._max_retries:
if self._instrumentation_callback:
self._instrumentation_callback(measurements)
self._on_exception(error)
duration = self._sleep_duration(attempt)
self.logger.warning('%r on attempt %i, sleeping %.2f seconds',
error, attempt, duration)
yield gen.sleep(duration)
except exceptions.DynamoDBException as error:
if self._instrumentation_callback:
self._instrumentation_callback(measurements)
self._on_exception(error)
else:
if self._instrumentation_callback:
self._instrumentation_callback(measurements)
self.logger.debug('%s result: %r', action, result)
raise gen.Return(_unwrap_result(action, result)) | [
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sprockets/sprockets-dynamodb | sprockets_dynamodb/client.py | Client.set_error_callback | def set_error_callback(self, callback):
"""Assign a method to invoke when a request has encountered an
unrecoverable error in an action execution.
:param method callback: The method to invoke
"""
self.logger.debug('Setting error callback: %r', callback)
self._on_error = callback | python | def set_error_callback(self, callback):
"""Assign a method to invoke when a request has encountered an
unrecoverable error in an action execution.
:param method callback: The method to invoke
"""
self.logger.debug('Setting error callback: %r', callback)
self._on_error = callback | [
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sprockets/sprockets-dynamodb | sprockets_dynamodb/client.py | Client.set_instrumentation_callback | def set_instrumentation_callback(self, callback):
"""Assign a method to invoke when a request has completed gathering
measurements.
:param method callback: The method to invoke
"""
self.logger.debug('Setting instrumentation callback: %r', callback)
self._instrumentation_callback = callback | python | def set_instrumentation_callback(self, callback):
"""Assign a method to invoke when a request has completed gathering
measurements.
:param method callback: The method to invoke
"""
self.logger.debug('Setting instrumentation callback: %r', callback)
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sprockets/sprockets-dynamodb | sprockets_dynamodb/client.py | Client._execute | def _execute(self, action, parameters, attempt, measurements):
"""Invoke a DynamoDB action
:param str action: DynamoDB action to invoke
:param dict parameters: parameters to send into the action
:param int attempt: Which attempt number this is
:param list measurements: A list for accumulating request measurements
:rtype: tornado.concurrent.Future
"""
future = concurrent.Future()
start = time.time()
def handle_response(request):
"""Invoked by the IOLoop when fetch has a response to process.
:param tornado.concurrent.Future request: The request future
"""
self._on_response(
action, parameters.get('TableName', 'Unknown'), attempt,
start, request, future, measurements)
ioloop.IOLoop.current().add_future(self._client.fetch(
'POST', '/',
body=json.dumps(parameters).encode('utf-8'),
headers={
'x-amz-target': 'DynamoDB_20120810.{}'.format(action),
'Content-Type': 'application/x-amz-json-1.0',
}), handle_response)
return future | python | def _execute(self, action, parameters, attempt, measurements):
"""Invoke a DynamoDB action
:param str action: DynamoDB action to invoke
:param dict parameters: parameters to send into the action
:param int attempt: Which attempt number this is
:param list measurements: A list for accumulating request measurements
:rtype: tornado.concurrent.Future
"""
future = concurrent.Future()
start = time.time()
def handle_response(request):
"""Invoked by the IOLoop when fetch has a response to process.
:param tornado.concurrent.Future request: The request future
"""
self._on_response(
action, parameters.get('TableName', 'Unknown'), attempt,
start, request, future, measurements)
ioloop.IOLoop.current().add_future(self._client.fetch(
'POST', '/',
body=json.dumps(parameters).encode('utf-8'),
headers={
'x-amz-target': 'DynamoDB_20120810.{}'.format(action),
'Content-Type': 'application/x-amz-json-1.0',
}), handle_response)
return future | [
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sprockets/sprockets-dynamodb | sprockets_dynamodb/client.py | Client._on_response | def _on_response(self, action, table, attempt, start, response, future,
measurements):
"""Invoked when the HTTP request to the DynamoDB has returned and
is responsible for setting the future result or exception based upon
the HTTP response provided.
:param str action: The action that was taken
:param str table: The table name the action was made against
:param int attempt: The attempt number for the action
:param float start: When the request was submitted
:param tornado.concurrent.Future response: The HTTP request future
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self.logger.debug('%s on %s request #%i = %r',
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now, exception = time.time(), None
try:
future.set_result(self._process_response(response))
except aws_exceptions.ConfigNotFound as error:
exception = exceptions.ConfigNotFound(str(error))
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exception = exceptions.ConfigParserError(str(error))
except aws_exceptions.NoCredentialsError as error:
exception = exceptions.NoCredentialsError(str(error))
except aws_exceptions.NoProfileError as error:
exception = exceptions.NoProfileError(str(error))
except aws_exceptions.AWSError as error:
exception = exceptions.DynamoDBException(error)
except (ConnectionError, ConnectionResetError, OSError,
aws_exceptions.RequestException, ssl.SSLError,
_select.error, ssl.socket_error, socket.gaierror) as error:
exception = exceptions.RequestException(str(error))
except TimeoutError:
exception = exceptions.TimeoutException()
except httpclient.HTTPError as error:
if error.code == 599:
exception = exceptions.TimeoutException()
else:
exception = exceptions.RequestException(
getattr(getattr(error, 'response', error),
'body', str(error.code)))
except Exception as error:
exception = error
if exception:
future.set_exception(exception)
measurements.append(
Measurement(now, action, table, attempt, max(now, start) - start,
exception.__class__.__name__
if exception else exception)) | python | def _on_response(self, action, table, attempt, start, response, future,
measurements):
"""Invoked when the HTTP request to the DynamoDB has returned and
is responsible for setting the future result or exception based upon
the HTTP response provided.
:param str action: The action that was taken
:param str table: The table name the action was made against
:param int attempt: The attempt number for the action
:param float start: When the request was submitted
:param tornado.concurrent.Future response: The HTTP request future
:param tornado.concurrent.Future future: The action execution future
:param list measurements: The measurement accumulator
"""
self.logger.debug('%s on %s request #%i = %r',
action, table, attempt, response)
now, exception = time.time(), None
try:
future.set_result(self._process_response(response))
except aws_exceptions.ConfigNotFound as error:
exception = exceptions.ConfigNotFound(str(error))
except aws_exceptions.ConfigParserError as error:
exception = exceptions.ConfigParserError(str(error))
except aws_exceptions.NoCredentialsError as error:
exception = exceptions.NoCredentialsError(str(error))
except aws_exceptions.NoProfileError as error:
exception = exceptions.NoProfileError(str(error))
except aws_exceptions.AWSError as error:
exception = exceptions.DynamoDBException(error)
except (ConnectionError, ConnectionResetError, OSError,
aws_exceptions.RequestException, ssl.SSLError,
_select.error, ssl.socket_error, socket.gaierror) as error:
exception = exceptions.RequestException(str(error))
except TimeoutError:
exception = exceptions.TimeoutException()
except httpclient.HTTPError as error:
if error.code == 599:
exception = exceptions.TimeoutException()
else:
exception = exceptions.RequestException(
getattr(getattr(error, 'response', error),
'body', str(error.code)))
except Exception as error:
exception = error
if exception:
future.set_exception(exception)
measurements.append(
Measurement(now, action, table, attempt, max(now, start) - start,
exception.__class__.__name__
if exception else exception)) | [
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] | 2e202bcb01f23f828f91299599311007054de4aa | https://github.com/sprockets/sprockets-dynamodb/blob/2e202bcb01f23f828f91299599311007054de4aa/sprockets_dynamodb/client.py#L855-L907 | train | 46,168 |
sprockets/sprockets-dynamodb | sprockets_dynamodb/client.py | Client._process_response | def _process_response(response):
"""Process the raw AWS response, returning either the mapped exception
or deserialized response.
:param tornado.concurrent.Future response: The request future
:rtype: dict or list
:raises: sprockets_dynamodb.exceptions.DynamoDBException
"""
error = response.exception()
if error:
if isinstance(error, aws_exceptions.AWSError):
if error.args[1]['type'] in exceptions.MAP:
raise exceptions.MAP[error.args[1]['type']](
error.args[1]['message'])
raise error
http_response = response.result()
if not http_response or not http_response.body:
raise exceptions.DynamoDBException('empty response')
return json.loads(http_response.body.decode('utf-8')) | python | def _process_response(response):
"""Process the raw AWS response, returning either the mapped exception
or deserialized response.
:param tornado.concurrent.Future response: The request future
:rtype: dict or list
:raises: sprockets_dynamodb.exceptions.DynamoDBException
"""
error = response.exception()
if error:
if isinstance(error, aws_exceptions.AWSError):
if error.args[1]['type'] in exceptions.MAP:
raise exceptions.MAP[error.args[1]['type']](
error.args[1]['message'])
raise error
http_response = response.result()
if not http_response or not http_response.body:
raise exceptions.DynamoDBException('empty response')
return json.loads(http_response.body.decode('utf-8')) | [
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oceanprotocol/oceandb-bigchaindb-driver | oceandb_bigchaindb_driver/plugin.py | Plugin.write | def write(self, obj, resource_id=None):
"""Write and obj in bdb.
:param obj: value to be written in bdb.
:param resource_id: id to make possible read and search for an resource.
:return: id of the transaction
"""
if resource_id is not None:
if self.read(resource_id):
raise ValueError("There are one object already with this id.")
obj['_id'] = resource_id
prepared_creation_tx = self.driver.instance.transactions.prepare(
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signers=self.user.public_key,
asset={
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'data': obj
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metadata={
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'data': obj
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)
signed_tx = self.driver.instance.transactions.fulfill(
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private_keys=self.user.private_key
)
self.logger.debug('bdb::write::{}'.format(signed_tx['id']))
self.driver.instance.transactions.send_commit(signed_tx)
return signed_tx | python | def write(self, obj, resource_id=None):
"""Write and obj in bdb.
:param obj: value to be written in bdb.
:param resource_id: id to make possible read and search for an resource.
:return: id of the transaction
"""
if resource_id is not None:
if self.read(resource_id):
raise ValueError("There are one object already with this id.")
obj['_id'] = resource_id
prepared_creation_tx = self.driver.instance.transactions.prepare(
operation='CREATE',
signers=self.user.public_key,
asset={
'namespace': self.namespace,
'data': obj
},
metadata={
'namespace': self.namespace,
'data': obj
}
)
signed_tx = self.driver.instance.transactions.fulfill(
prepared_creation_tx,
private_keys=self.user.private_key
)
self.logger.debug('bdb::write::{}'.format(signed_tx['id']))
self.driver.instance.transactions.send_commit(signed_tx)
return signed_tx | [
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oceanprotocol/oceandb-bigchaindb-driver | oceandb_bigchaindb_driver/plugin.py | Plugin._get | def _get(self, tx_id):
"""Read and obj in bdb using the tx_id.
:param resource_id: id of the transaction to be read.
:return: value with the data, transaction id and transaction.
"""
# tx_id=self._find_tx_id(resource_id)
value = [
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'data': transaction['metadata'],
'id': transaction['id']
}
for transaction in self.driver.instance.transactions.get(asset_id=self.get_asset_id(tx_id))
][-1]
if value['data']['data']:
self.logger.debug('bdb::read::{}'.format(value['data']))
return value
else:
return False | python | def _get(self, tx_id):
"""Read and obj in bdb using the tx_id.
:param resource_id: id of the transaction to be read.
:return: value with the data, transaction id and transaction.
"""
# tx_id=self._find_tx_id(resource_id)
value = [
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'data': transaction['metadata'],
'id': transaction['id']
}
for transaction in self.driver.instance.transactions.get(asset_id=self.get_asset_id(tx_id))
][-1]
if value['data']['data']:
self.logger.debug('bdb::read::{}'.format(value['data']))
return value
else:
return False | [
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oceanprotocol/oceandb-bigchaindb-driver | oceandb_bigchaindb_driver/plugin.py | Plugin._update | def _update(self, metadata, tx_id, resource_id):
"""Update and obj in bdb using the tx_id.
:param metadata: new metadata for the transaction.
:param tx_id: id of the transaction to be updated.
:return: id of the transaction.
"""
try:
if not tx_id:
sent_tx = self.write(metadata, resource_id)
self.logger.debug('bdb::put::{}'.format(sent_tx['id']))
return sent_tx
else:
txs = self.driver.instance.transactions.get(asset_id=self.get_asset_id(tx_id))
unspent = txs[-1]
sent_tx = self._put(metadata, unspent, resource_id)
self.logger.debug('bdb::put::{}'.format(sent_tx))
return sent_tx
except BadRequest as e:
logging.error(e) | python | def _update(self, metadata, tx_id, resource_id):
"""Update and obj in bdb using the tx_id.
:param metadata: new metadata for the transaction.
:param tx_id: id of the transaction to be updated.
:return: id of the transaction.
"""
try:
if not tx_id:
sent_tx = self.write(metadata, resource_id)
self.logger.debug('bdb::put::{}'.format(sent_tx['id']))
return sent_tx
else:
txs = self.driver.instance.transactions.get(asset_id=self.get_asset_id(tx_id))
unspent = txs[-1]
sent_tx = self._put(metadata, unspent, resource_id)
self.logger.debug('bdb::put::{}'.format(sent_tx))
return sent_tx
except BadRequest as e:
logging.error(e) | [
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oceanprotocol/oceandb-bigchaindb-driver | oceandb_bigchaindb_driver/plugin.py | Plugin.query | def query(self, search_model: QueryModel):
"""Query to bdb namespace.
:param query_string: query in string format.
:return: list of transactions that match with the query.
"""
self.logger.debug('bdb::get::{}'.format(search_model.query))
assets = json.loads(requests.post("http://localhost:4000/query", data=search_model.query).content)['data']
self.logger.debug('bdb::result::len {}'.format(len(assets)))
assets_metadata = []
for i in assets:
try:
assets_metadata.append(self._get(i['id'])['data']['data'])
except:
pass
return assets_metadata | python | def query(self, search_model: QueryModel):
"""Query to bdb namespace.
:param query_string: query in string format.
:return: list of transactions that match with the query.
"""
self.logger.debug('bdb::get::{}'.format(search_model.query))
assets = json.loads(requests.post("http://localhost:4000/query", data=search_model.query).content)['data']
self.logger.debug('bdb::result::len {}'.format(len(assets)))
assets_metadata = []
for i in assets:
try:
assets_metadata.append(self._get(i['id'])['data']['data'])
except:
pass
return assets_metadata | [
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oceanprotocol/oceandb-bigchaindb-driver | oceandb_bigchaindb_driver/plugin.py | Plugin.get_asset_id | def get_asset_id(self, tx_id):
"""Return the tx_id of the first transaction.
:param tx_id: Transaction id to start the recursive search.
:return Transaction id parent.
"""
tx = self.driver.instance.transactions.retrieve(txid=tx_id)
assert tx is not None
return tx['id'] if tx['operation'] == 'CREATE' else tx['asset']['id'] | python | def get_asset_id(self, tx_id):
"""Return the tx_id of the first transaction.
:param tx_id: Transaction id to start the recursive search.
:return Transaction id parent.
"""
tx = self.driver.instance.transactions.retrieve(txid=tx_id)
assert tx is not None
return tx['id'] if tx['operation'] == 'CREATE' else tx['asset']['id'] | [
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johntruckenbrodt/spatialist | spatialist/envi.py | hdr | def hdr(data, filename):
"""
write ENVI header files
Parameters
----------
data: str or dict
the file or dictionary to get the info from
filename: str
the HDR file to write
Returns
-------
"""
hdrobj = data if isinstance(data, HDRobject) else HDRobject(data)
hdrobj.write(filename) | python | def hdr(data, filename):
"""
write ENVI header files
Parameters
----------
data: str or dict
the file or dictionary to get the info from
filename: str
the HDR file to write
Returns
-------
"""
hdrobj = data if isinstance(data, HDRobject) else HDRobject(data)
hdrobj.write(filename) | [
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johntruckenbrodt/spatialist | spatialist/envi.py | HDRobject.write | def write(self, filename='same'):
"""
write object to an ENVI header file
"""
if filename == 'same':
filename = self.filename
if not filename.endswith('.hdr'):
filename += '.hdr'
with open(filename, 'w') as out:
out.write(self.__str__()) | python | def write(self, filename='same'):
"""
write object to an ENVI header file
"""
if filename == 'same':
filename = self.filename
if not filename.endswith('.hdr'):
filename += '.hdr'
with open(filename, 'w') as out:
out.write(self.__str__()) | [
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MLAB-project/pymlab | examples/I2CSPI_HBSTEP_CAMPAP.py | axis.GoZero | def GoZero(self, speed):
' Go to Zero position '
self.ReleaseSW()
spi.SPI_write_byte(self.CS, 0x82 | (self.Dir & 1)) # Go to Zero
spi.SPI_write_byte(self.CS, 0x00)
spi.SPI_write_byte(self.CS, speed)
while self.IsBusy():
pass
time.sleep(0.3)
self.ReleaseSW() | python | def GoZero(self, speed):
' Go to Zero position '
self.ReleaseSW()
spi.SPI_write_byte(self.CS, 0x82 | (self.Dir & 1)) # Go to Zero
spi.SPI_write_byte(self.CS, 0x00)
spi.SPI_write_byte(self.CS, speed)
while self.IsBusy():
pass
time.sleep(0.3)
self.ReleaseSW() | [
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MLAB-project/pymlab | examples/I2CSPI_HBSTEP_CAMPAP.py | axis.ReadStatusBit | def ReadStatusBit(self, bit):
' Report given status bit '
spi.SPI_write_byte(self.CS, 0x39) # Read from address 0x19 (STATUS)
spi.SPI_write_byte(self.CS, 0x00)
data0 = spi.SPI_read_byte() # 1st byte
spi.SPI_write_byte(self.CS, 0x00)
data1 = spi.SPI_read_byte() # 2nd byte
#print hex(data0), hex(data1)
if bit > 7: # extract requested bit
OutputBit = (data0 >> (bit - 8)) & 1
else:
OutputBit = (data1 >> bit) & 1
return OutputBit | python | def ReadStatusBit(self, bit):
' Report given status bit '
spi.SPI_write_byte(self.CS, 0x39) # Read from address 0x19 (STATUS)
spi.SPI_write_byte(self.CS, 0x00)
data0 = spi.SPI_read_byte() # 1st byte
spi.SPI_write_byte(self.CS, 0x00)
data1 = spi.SPI_read_byte() # 2nd byte
#print hex(data0), hex(data1)
if bit > 7: # extract requested bit
OutputBit = (data0 >> (bit - 8)) & 1
else:
OutputBit = (data1 >> bit) & 1
return OutputBit | [
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MLAB-project/pymlab | src/pymlab/sensors/bus_translators.py | I2CSPI.SPI_write_byte | def SPI_write_byte(self, chip_select, data):
'Writes a data to a SPI device selected by chipselect bit. '
self.bus.write_byte_data(self.address, chip_select, data) | python | def SPI_write_byte(self, chip_select, data):
'Writes a data to a SPI device selected by chipselect bit. '
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MLAB-project/pymlab | src/pymlab/sensors/bus_translators.py | I2CSPI.SPI_write | def SPI_write(self, chip_select, data):
'Writes data to SPI device selected by chipselect bit. '
dat = list(data)
dat.insert(0, chip_select)
return self.bus.write_i2c_block(self.address, dat); | python | def SPI_write(self, chip_select, data):
'Writes data to SPI device selected by chipselect bit. '
dat = list(data)
dat.insert(0, chip_select)
return self.bus.write_i2c_block(self.address, dat); | [
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MLAB-project/pymlab | src/pymlab/sensors/bus_translators.py | I2CSPI.SPI_config | def SPI_config(self,config):
'Configure SPI interface parameters.'
self.bus.write_byte_data(self.address, 0xF0, config)
return self.bus.read_byte_data(self.address, 0xF0) | python | def SPI_config(self,config):
'Configure SPI interface parameters.'
self.bus.write_byte_data(self.address, 0xF0, config)
return self.bus.read_byte_data(self.address, 0xF0) | [
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MLAB-project/pymlab | src/pymlab/sensors/bus_translators.py | I2CSPI.GPIO_read | def GPIO_read(self):
'Reads logic state on GPIO enabled slave-selects pins.'
self.bus.write_byte_data(self.address, 0xF5, 0x0f)
status = self.bus.read_byte(self.address)
bits_values = dict([('SS0',status & 0x01 == 0x01),('SS1',status & 0x02 == 0x02),('SS2',status & 0x04 == 0x04),('SS3',status & 0x08 == 0x08)])
return bits_values | python | def GPIO_read(self):
'Reads logic state on GPIO enabled slave-selects pins.'
self.bus.write_byte_data(self.address, 0xF5, 0x0f)
status = self.bus.read_byte(self.address)
bits_values = dict([('SS0',status & 0x01 == 0x01),('SS1',status & 0x02 == 0x02),('SS2',status & 0x04 == 0x04),('SS3',status & 0x08 == 0x08)])
return bits_values | [
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MLAB-project/pymlab | src/pymlab/sensors/bus_translators.py | I2CSPI.GPIO_config | def GPIO_config(self, gpio_enable, gpio_config):
'Enable or disable slave-select pins as gpio.'
self.bus.write_byte_data(self.address, 0xF6, gpio_enable)
self.bus.write_byte_data(self.address, 0xF7, gpio_config)
return | python | def GPIO_config(self, gpio_enable, gpio_config):
'Enable or disable slave-select pins as gpio.'
self.bus.write_byte_data(self.address, 0xF6, gpio_enable)
self.bus.write_byte_data(self.address, 0xF7, gpio_config)
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MLAB-project/pymlab | src/pymlab/sensors/rps.py | RPS01.get_address | def get_address(self):
"""
Returns sensors I2C address.
"""
LOGGER.debug("Reading RPS01A sensor's address.",)
return self.bus.read_byte_data(self.address, self.address_reg) | python | def get_address(self):
"""
Returns sensors I2C address.
"""
LOGGER.debug("Reading RPS01A sensor's address.",)
return self.bus.read_byte_data(self.address, self.address_reg) | [
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MLAB-project/pymlab | src/pymlab/sensors/rps.py | RPS01.get_zero_position | def get_zero_position(self):
"""
Returns programmed zero position in OTP memory.
"""
LSB = self.bus.read_byte_data(self.address, self.zero_position_MSB)
MSB = self.bus.read_byte_data(self.address, self.zero_position_LSB)
DATA = (MSB << 6) + LSB
return DATA | python | def get_zero_position(self):
"""
Returns programmed zero position in OTP memory.
"""
LSB = self.bus.read_byte_data(self.address, self.zero_position_MSB)
MSB = self.bus.read_byte_data(self.address, self.zero_position_LSB)
DATA = (MSB << 6) + LSB
return DATA | [
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MLAB-project/pymlab | src/pymlab/sensors/rps.py | RPS01.get_agc_value | def get_agc_value(self):
"""
Returns sensor's Automatic Gain Control actual value.
0 - Represents high magtetic field
0xFF - Represents low magnetic field
"""
LOGGER.debug("Reading RPS01A sensor's AGC settings",)
return self.bus.read_byte_data(self.address, self.AGC_reg) | python | def get_agc_value(self):
"""
Returns sensor's Automatic Gain Control actual value.
0 - Represents high magtetic field
0xFF - Represents low magnetic field
"""
LOGGER.debug("Reading RPS01A sensor's AGC settings",)
return self.bus.read_byte_data(self.address, self.AGC_reg) | [
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MLAB-project/pymlab | src/pymlab/sensors/rps.py | RPS01.get_angle | def get_angle(self, verify = False):
"""
Retuns measured angle in degrees in range 0-360.
"""
LSB = self.bus.read_byte_data(self.address, self.angle_LSB)
MSB = self.bus.read_byte_data(self.address, self.angle_MSB)
DATA = (MSB << 6) + LSB
if not verify:
return (360.0 / 2**14) * DATA
else:
status = self.get_diagnostics()
if not (status['Comp_Low']) and not(status['Comp_High']) and not(status['COF']):
return (360.0 / 2**14) * DATA
else:
return None | python | def get_angle(self, verify = False):
"""
Retuns measured angle in degrees in range 0-360.
"""
LSB = self.bus.read_byte_data(self.address, self.angle_LSB)
MSB = self.bus.read_byte_data(self.address, self.angle_MSB)
DATA = (MSB << 6) + LSB
if not verify:
return (360.0 / 2**14) * DATA
else:
status = self.get_diagnostics()
if not (status['Comp_Low']) and not(status['Comp_High']) and not(status['COF']):
return (360.0 / 2**14) * DATA
else:
return None | [
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vladsaveliev/TargQC | scripts/annotate_bed.py | main | def main(input_bed, output_file, output_features=False, genome=None,
only_canonical=False, short=False, extended=False, high_confidence=False,
ambiguities_method=False, coding_only=False, collapse_exons=False, work_dir=False, is_debug=False):
""" Annotating BED file based on reference features annotations.
"""
logger.init(is_debug_=is_debug)
if not genome:
raise click.BadParameter('Error: please, specify genome build name with -g (e.g. `-g hg19`)', param='genome')
if short:
if extended: raise click.BadParameter('--short and --extended can\'t be set both', param='extended')
if output_features: raise click.BadParameter('--short and --output-features can\'t be set both', param='output_features')
elif output_features or extended:
extended = True
short = False
if not verify_file(input_bed):
click.BadParameter(f'Usage: {__file__} Input_BED_file -g hg19 -o Annotated_BED_file [options]', param='input_bed')
input_bed = verify_file(input_bed, is_critical=True, description=f'Input BED file for {__file__}')
if work_dir:
work_dir = join(adjust_path(work_dir), os.path.splitext(basename(input_bed))[0])
safe_mkdir(work_dir)
info(f'Created work directory {work_dir}')
else:
work_dir = mkdtemp('bed_annotate')
debug('Created temporary work directory {work_dir}')
input_bed = clean_bed(input_bed, work_dir)
input_bed = verify_bed(input_bed, is_critical=True, description=f'Input BED file for {__file__} after cleaning')
output_file = adjust_path(output_file)
output_file = annotate(
input_bed, output_file, work_dir, genome=genome,
only_canonical=only_canonical, short=short, extended=extended,
high_confidence=high_confidence, collapse_exons=collapse_exons,
output_features=output_features,
ambiguities_method=ambiguities_method, coding_only=coding_only,
is_debug=is_debug)
if not work_dir:
debug(f'Removing work directory {work_dir}')
shutil.rmtree(work_dir)
info(f'Done, saved to {output_file}') | python | def main(input_bed, output_file, output_features=False, genome=None,
only_canonical=False, short=False, extended=False, high_confidence=False,
ambiguities_method=False, coding_only=False, collapse_exons=False, work_dir=False, is_debug=False):
""" Annotating BED file based on reference features annotations.
"""
logger.init(is_debug_=is_debug)
if not genome:
raise click.BadParameter('Error: please, specify genome build name with -g (e.g. `-g hg19`)', param='genome')
if short:
if extended: raise click.BadParameter('--short and --extended can\'t be set both', param='extended')
if output_features: raise click.BadParameter('--short and --output-features can\'t be set both', param='output_features')
elif output_features or extended:
extended = True
short = False
if not verify_file(input_bed):
click.BadParameter(f'Usage: {__file__} Input_BED_file -g hg19 -o Annotated_BED_file [options]', param='input_bed')
input_bed = verify_file(input_bed, is_critical=True, description=f'Input BED file for {__file__}')
if work_dir:
work_dir = join(adjust_path(work_dir), os.path.splitext(basename(input_bed))[0])
safe_mkdir(work_dir)
info(f'Created work directory {work_dir}')
else:
work_dir = mkdtemp('bed_annotate')
debug('Created temporary work directory {work_dir}')
input_bed = clean_bed(input_bed, work_dir)
input_bed = verify_bed(input_bed, is_critical=True, description=f'Input BED file for {__file__} after cleaning')
output_file = adjust_path(output_file)
output_file = annotate(
input_bed, output_file, work_dir, genome=genome,
only_canonical=only_canonical, short=short, extended=extended,
high_confidence=high_confidence, collapse_exons=collapse_exons,
output_features=output_features,
ambiguities_method=ambiguities_method, coding_only=coding_only,
is_debug=is_debug)
if not work_dir:
debug(f'Removing work directory {work_dir}')
shutil.rmtree(work_dir)
info(f'Done, saved to {output_file}') | [
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MLAB-project/pymlab | src/pymlab/sensors/lioncell.py | LIONCELL.StateOfCharge | def StateOfCharge(self):
""" % of Full Charge """
return (self.bus.read_byte_data(self.address, 0x02) + self.bus.read_byte_data(self.address, 0x03) * 256) | python | def StateOfCharge(self):
""" % of Full Charge """
return (self.bus.read_byte_data(self.address, 0x02) + self.bus.read_byte_data(self.address, 0x03) * 256) | [
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MLAB-project/pymlab | src/pymlab/sensors/lioncell.py | LIONCELL.Chemistry | def Chemistry(self):
''' Get cells chemistry '''
length = self.bus.read_byte_data(self.address, 0x79)
chem = []
for n in range(length):
chem.append(self.bus.read_byte_data(self.address, 0x7A + n))
return chem | python | def Chemistry(self):
''' Get cells chemistry '''
length = self.bus.read_byte_data(self.address, 0x79)
chem = []
for n in range(length):
chem.append(self.bus.read_byte_data(self.address, 0x7A + n))
return chem | [
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MLAB-project/pymlab | examples/I2CSPI_BRIDGEADC01.py | BRIDGEADC01.single_read | def single_read(self, register):
'''
Reads data from desired register only once.
'''
comm_reg = (0b00010 << 3) + register
if register == self.AD7730_STATUS_REG:
bytes_num = 1
elif register == self.AD7730_DATA_REG:
bytes_num = 3
elif register == self.AD7730_MODE_REG:
bytes_num = 2
elif register == self.AD7730_FILTER_REG:
bytes_num = 3
elif register == self.AD7730_DAC_REG:
bytes_num = 1
elif register == self.AD7730_OFFSET_REG:
bytes_num = 3
elif register == self.AD7730_GAIN_REG:
bytes_num = 3
elif register == self.AD7730_TEST_REG:
bytes_num = 3
command = [comm_reg] + ([0x00] * bytes_num)
spi.SPI_write(self.CS, command)
data = spi.SPI_read(bytes_num + 1)
return data[1:] | python | def single_read(self, register):
'''
Reads data from desired register only once.
'''
comm_reg = (0b00010 << 3) + register
if register == self.AD7730_STATUS_REG:
bytes_num = 1
elif register == self.AD7730_DATA_REG:
bytes_num = 3
elif register == self.AD7730_MODE_REG:
bytes_num = 2
elif register == self.AD7730_FILTER_REG:
bytes_num = 3
elif register == self.AD7730_DAC_REG:
bytes_num = 1
elif register == self.AD7730_OFFSET_REG:
bytes_num = 3
elif register == self.AD7730_GAIN_REG:
bytes_num = 3
elif register == self.AD7730_TEST_REG:
bytes_num = 3
command = [comm_reg] + ([0x00] * bytes_num)
spi.SPI_write(self.CS, command)
data = spi.SPI_read(bytes_num + 1)
return data[1:] | [
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MLAB-project/pymlab | examples/I2CSPI_BRIDGEADC01.py | BRIDGEADC01.getStatus | def getStatus(self):
"""
RDY - Ready Bit. This bit provides the status of the RDY flag from the part. The status and function of this bit is the same as the RDY output pin. A number of events set the RDY bit high as indicated in Table XVIII in datasheet
STDY - Steady Bit. This bit is updated when the filter writes a result to the Data Register. If the filter is
in FASTStep mode (see Filter Register section) and responding to a step input, the STDY bit
remains high as the initial conversion results become available. The RDY output and bit are set
low on these initial conversions to indicate that a result is available. If the STDY is high, however,
it indicates that the result being provided is not from a fully settled second-stage FIR filter. When the
FIR filter has fully settled, the STDY bit will go low coincident with RDY. If the part is never placed
into its FASTStep mode, the STDY bit will go low at the first Data Register read and it is
not cleared by subsequent Data Register reads. A number of events set the STDY bit high as indicated in Table XVIII. STDY is set high along with RDY by all events in the table except a Data Register read.
STBY - Standby Bit. This bit indicates whether the AD7730 is in its Standby Mode or normal mode of
operation. The part can be placed in its standby mode using the STANDBY input pin or by
writing 011 to the MD2 to MD0 bits of the Mode Register. The power-on/reset status of this bit
is 0 assuming the STANDBY pin is high.
NOREF - No Reference Bit. If the voltage between the REF IN(+) and REF IN(-) pins is below 0.3 V, or either of these inputs is open-circuit, the NOREF bit goes to 1. If NOREF is active on completion of a conversion, the Data Register is loaded with all 1s. If NOREF is active on completion of a calibration, updating of the calibration registers is inhibited."""
status = self.single_read(self.AD7730_STATUS_REG)
bits_values = dict([('NOREF',status[0] & 0x10 == 0x10),
('STBY',status[0] & 0x20 == 0x20),
('STDY',status[0] & 0x40 == 0x40),
('RDY',status[0] & 0x80 == 0x80)])
return bits_values | python | def getStatus(self):
"""
RDY - Ready Bit. This bit provides the status of the RDY flag from the part. The status and function of this bit is the same as the RDY output pin. A number of events set the RDY bit high as indicated in Table XVIII in datasheet
STDY - Steady Bit. This bit is updated when the filter writes a result to the Data Register. If the filter is
in FASTStep mode (see Filter Register section) and responding to a step input, the STDY bit
remains high as the initial conversion results become available. The RDY output and bit are set
low on these initial conversions to indicate that a result is available. If the STDY is high, however,
it indicates that the result being provided is not from a fully settled second-stage FIR filter. When the
FIR filter has fully settled, the STDY bit will go low coincident with RDY. If the part is never placed
into its FASTStep mode, the STDY bit will go low at the first Data Register read and it is
not cleared by subsequent Data Register reads. A number of events set the STDY bit high as indicated in Table XVIII. STDY is set high along with RDY by all events in the table except a Data Register read.
STBY - Standby Bit. This bit indicates whether the AD7730 is in its Standby Mode or normal mode of
operation. The part can be placed in its standby mode using the STANDBY input pin or by
writing 011 to the MD2 to MD0 bits of the Mode Register. The power-on/reset status of this bit
is 0 assuming the STANDBY pin is high.
NOREF - No Reference Bit. If the voltage between the REF IN(+) and REF IN(-) pins is below 0.3 V, or either of these inputs is open-circuit, the NOREF bit goes to 1. If NOREF is active on completion of a conversion, the Data Register is loaded with all 1s. If NOREF is active on completion of a calibration, updating of the calibration registers is inhibited."""
status = self.single_read(self.AD7730_STATUS_REG)
bits_values = dict([('NOREF',status[0] & 0x10 == 0x10),
('STBY',status[0] & 0x20 == 0x20),
('STDY',status[0] & 0x40 == 0x40),
('RDY',status[0] & 0x80 == 0x80)])
return bits_values | [
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STBY - Standby Bit. This bit indicates whether the AD7730 is in its Standby Mode or normal mode of
operation. The part can be placed in its standby mode using the STANDBY input pin or by
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NOREF - No Reference Bit. If the voltage between the REF IN(+) and REF IN(-) pins is below 0.3 V, or either of these inputs is open-circuit, the NOREF bit goes to 1. If NOREF is active on completion of a conversion, the Data Register is loaded with all 1s. If NOREF is active on completion of a calibration, updating of the calibration registers is inhibited. | [
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MLAB-project/pymlab | src/pymlab/sensors/sht.py | SHT31._calculate_checksum | def _calculate_checksum(value):
"""4.12 Checksum Calculation from an unsigned short input"""
# CRC
polynomial = 0x131 # //P(x)=x^8+x^5+x^4+1 = 100110001
crc = 0xFF
# calculates 8-Bit checksum with given polynomial
for byteCtr in [ord(x) for x in struct.pack(">H", value)]:
crc ^= byteCtr
for bit in range(8, 0, -1):
if crc & 0x80:
crc = (crc << 1) ^ polynomial
else:
crc = (crc << 1)
return crc | python | def _calculate_checksum(value):
"""4.12 Checksum Calculation from an unsigned short input"""
# CRC
polynomial = 0x131 # //P(x)=x^8+x^5+x^4+1 = 100110001
crc = 0xFF
# calculates 8-Bit checksum with given polynomial
for byteCtr in [ord(x) for x in struct.pack(">H", value)]:
crc ^= byteCtr
for bit in range(8, 0, -1):
if crc & 0x80:
crc = (crc << 1) ^ polynomial
else:
crc = (crc << 1)
return crc | [
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svenkreiss/databench | databench/analyses_packaged/dummypi_py/analysis.py | Dummypi_Py.run | def run(self):
"""Run when button is pressed."""
inside = 0
for draws in range(1, self.data['samples']):
# generate points and check whether they are inside the unit circle
r1, r2 = (random(), random())
if r1 ** 2 + r2 ** 2 < 1.0:
inside += 1
if draws % 1000 != 0:
continue
# debug
yield self.emit('log', {'draws': draws, 'inside': inside})
# calculate pi and its uncertainty given the current draws
p = inside / draws
pi = {
'estimate': 4.0 * inside / draws,
'uncertainty': 4.0 * math.sqrt(draws * p * (1.0 - p)) / draws,
}
# send status to frontend
yield self.set_state(pi=pi)
yield self.emit('log', {'action': 'done'}) | python | def run(self):
"""Run when button is pressed."""
inside = 0
for draws in range(1, self.data['samples']):
# generate points and check whether they are inside the unit circle
r1, r2 = (random(), random())
if r1 ** 2 + r2 ** 2 < 1.0:
inside += 1
if draws % 1000 != 0:
continue
# debug
yield self.emit('log', {'draws': draws, 'inside': inside})
# calculate pi and its uncertainty given the current draws
p = inside / draws
pi = {
'estimate': 4.0 * inside / draws,
'uncertainty': 4.0 * math.sqrt(draws * p * (1.0 - p)) / draws,
}
# send status to frontend
yield self.set_state(pi=pi)
yield self.emit('log', {'action': 'done'}) | [
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svenkreiss/databench | databench/analysis.py | Analysis.init_datastores | def init_datastores(self):
"""Initialize datastores for this analysis instance.
This creates instances of :class:`.Datastore` at ``data`` and
``class_data`` with the datastore domains being the current id
and the class name of this analysis respectively.
Overwrite this method to use other datastore backends.
"""
self.data = Datastore(self.id_)
self.data.subscribe(lambda data: self.emit('data', data))
self.class_data = Datastore(type(self).__name__)
self.class_data.subscribe(lambda data: self.emit('class_data', data)) | python | def init_datastores(self):
"""Initialize datastores for this analysis instance.
This creates instances of :class:`.Datastore` at ``data`` and
``class_data`` with the datastore domains being the current id
and the class name of this analysis respectively.
Overwrite this method to use other datastore backends.
"""
self.data = Datastore(self.id_)
self.data.subscribe(lambda data: self.emit('data', data))
self.class_data = Datastore(type(self).__name__)
self.class_data.subscribe(lambda data: self.emit('class_data', data)) | [
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svenkreiss/databench | databench/analysis.py | Analysis.emit | def emit(self, signal, message='__nomessagetoken__'):
"""Emit a signal to the frontend.
:param str signal: name of the signal
:param message: message to send
:returns: return value from frontend emit function
:rtype: tornado.concurrent.Future
"""
# call pre-emit hooks
if signal == 'log':
self.log_backend.info(message)
elif signal == 'warn':
self.log_backend.warn(message)
elif signal == 'error':
self.log_backend.error(message)
return self.emit_to_frontend(signal, message) | python | def emit(self, signal, message='__nomessagetoken__'):
"""Emit a signal to the frontend.
:param str signal: name of the signal
:param message: message to send
:returns: return value from frontend emit function
:rtype: tornado.concurrent.Future
"""
# call pre-emit hooks
if signal == 'log':
self.log_backend.info(message)
elif signal == 'warn':
self.log_backend.warn(message)
elif signal == 'error':
self.log_backend.error(message)
return self.emit_to_frontend(signal, message) | [
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svenkreiss/databench | databench/datastore_legacy.py | DatastoreList.set | def set(self, i, value):
"""Set value at position i and return a Future.
:rtype: tornado.concurrent.Future
"""
value_encoded = encode(value, self.get_change_trigger(i))
if i in self.data and self.data[i] == value_encoded:
return self
self.data[i] = value_encoded
return self.trigger_changed(i) | python | def set(self, i, value):
"""Set value at position i and return a Future.
:rtype: tornado.concurrent.Future
"""
value_encoded = encode(value, self.get_change_trigger(i))
if i in self.data and self.data[i] == value_encoded:
return self
self.data[i] = value_encoded
return self.trigger_changed(i) | [
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svenkreiss/databench | databench/datastore_legacy.py | DatastoreLegacy.set | def set(self, key, value):
"""Set value at key and return a Future
:rtype: tornado.concurrent.Future
"""
return DatastoreLegacy.store[self.domain].set(key, value) | python | def set(self, key, value):
"""Set value at key and return a Future
:rtype: tornado.concurrent.Future
"""
return DatastoreLegacy.store[self.domain].set(key, value) | [
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python-astrodynamics/spacetrack | shovel/docs.py | watch | def watch():
"""Renerate documentation when it changes."""
# Start with a clean build
sphinx_build['-b', 'html', '-E', 'docs', 'docs/_build/html'] & FG
handler = ShellCommandTrick(
shell_command='sphinx-build -b html docs docs/_build/html',
patterns=['*.rst', '*.py'],
ignore_patterns=['_build/*'],
ignore_directories=['.tox'],
drop_during_process=True)
observer = Observer()
observe_with(observer, handler, pathnames=['.'], recursive=True) | python | def watch():
"""Renerate documentation when it changes."""
# Start with a clean build
sphinx_build['-b', 'html', '-E', 'docs', 'docs/_build/html'] & FG
handler = ShellCommandTrick(
shell_command='sphinx-build -b html docs docs/_build/html',
patterns=['*.rst', '*.py'],
ignore_patterns=['_build/*'],
ignore_directories=['.tox'],
drop_during_process=True)
observer = Observer()
observe_with(observer, handler, pathnames=['.'], recursive=True) | [
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