Files
edx-platform/lms/djangoapps/course_api/blocks/api.py
2016-01-05 15:06:55 -05:00

79 lines
2.8 KiB
Python

"""
API function for retrieving course blocks data
"""
from .transformers.blocks_api import BlocksAPITransformer
from .transformers.proctored_exam import ProctoredExamTransformer
from .serializers import BlockSerializer, BlockDictSerializer
from lms.djangoapps.course_blocks.api import get_course_blocks, COURSE_BLOCK_ACCESS_TRANSFORMERS
def get_blocks(
request,
usage_key,
user=None,
depth=None,
nav_depth=None,
requested_fields=None,
block_counts=None,
student_view_data=None,
return_type='dict'
):
"""
Return a serialized representation of the course blocks.
Arguments:
request (HTTPRequest): Used for calling django reverse.
usage_key (UsageKey): Identifies the root block of interest.
user (User): Optional user object for whom the blocks are being
retrieved. If None, blocks are returned regardless of access checks.
depth (integer or None): Identifies the depth of the tree to return
starting at the root block. If None, the entire tree starting at
the root is returned.
nav_depth (integer): Optional parameter that indicates how far deep to
traverse into the block hierarchy before bundling all the
descendants for navigation.
requested_fields (list): Optional list of names of additional fields
to return for each block. Supported fields are listed in
transformers.SUPPORTED_FIELDS.
block_counts (list): Optional list of names of block types for which to
return an aggregate count of blocks.
student_view_data (list): Optional list of names of block types for
which blocks to return their student_view_data.
return_type (string): Possible values are 'dict' or 'list'. Indicates
the format for returning the blocks.
"""
# construct BlocksAPITransformer
blocks_api_transformer = BlocksAPITransformer(
block_counts,
student_view_data,
depth,
nav_depth
)
# list of transformers to apply, adding user-specific ones if user is provided
transformers = [blocks_api_transformer]
if user is not None:
transformers += COURSE_BLOCK_ACCESS_TRANSFORMERS + [ProctoredExamTransformer()]
blocks = get_course_blocks(
user,
usage_key,
transformers=transformers,
)
# serialize
serializer_context = {
'request': request,
'block_structure': blocks,
'requested_fields': requested_fields or [],
}
if return_type == 'dict':
serializer = BlockDictSerializer(blocks, context=serializer_context, many=False)
else:
serializer = BlockSerializer(blocks, context=serializer_context, many=True)
# return serialized data
return serializer.data