Paginate schema results

[Ghesselink]

Flask endpoint to paginate schema results.

The json can be invoked in the frontend as follows (the mentioned code should then be in Jinja on the frontend) :

• Get constraint types:

(Pdb) results['constraint_types'] # access jsonified dictionary 'results'
['schema', 'global_rule', 'entity_rule'] 

Based on these constraint_types, it should be possible to make columns/headers, similar as in the work for schema headers (johltn#10). Note that the returned constraint_types are only constraints of which values are found, not all the inputs for the columns in the database.

ifc-pipeline-validation/application/database.py

Line 286 in a26426b

constraint_type = Column(Enum("uncategorized", 'schema', 'global_rule', 'simpletype_rule', 'entity_rule', name='schema_constraint_types'), default="uncategorized")

Each subcategory is then sliced and can be modified by calling the Flask API with start and end as parameters, similar as in https://github.com/johltn/ifc-pipeline-validation/blob/ui/application/main.py#L474 . The sorting is done by the work of Thomas in the database, which is also added to the current PR.

ifc-pipeline-validation/application/database.py

Lines 176 to 177 in a26426b

	class schema_validation_task(validation_task):
	results = relationship("schema_result", order_by='schema_result.constraint_type.asc(),schema_result.attribute.asc()')

Furthermore, it is possible to access all the (slice) by using the constraint types found by the earlier statement.
For example (code will then be in Jinja on the front end):

constraint types = results['constraint_types']
>> for constraint_type in constraint_types: #schema, global_rule, entity_rule
>>          results['values'][constraint_type]['saved_values] # returns all serialized schema_results with constraint type 'schema' (in first    iteration)
>>        result['values'][constraint_type][count] # returns count, similar as in earlier mentioned PR of Johan