def datasets():
"""
Datasets names and Ids
Return a dictionary of datasets names
containing the respective Ids for the past records and the 2020 records
---
responses:
200:
description: a dictionary containing the names and ids for all datasets
schema:
type: object
properties:
homicidios:
type: object
properties:
2020:
type: string
example: 53e3d2fe-0026-4bf0-ba69-687aa4904a0f
past:
type: string
example: f465aa6b-a49f-42ce-8da2-fef524e7eada
"""
datasets = get_datasets()
dsets = {}
for dset in datasets:
print('getting', dset)
res_ids = getResourceId(dset)
dsets[dset] = {}
dsets[dset]['2020'] = res_ids[1]
dsets[dset]['past'] = res_ids[0]
return Response(json.dumps(dsets), mimetype='application/json')
def check_condiciones(resource):
file_name = 'Service/data/condiciones/' + resource + '.txt'
if os.path.exists(file_name):
#print("leyendo de archivos")
with open(file_name, 'r') as muns:
condiciones = muns.read()
condiciones = str_list(condiciones)
return condiciones
else:
#print("scraping resource page")
condiciones = getResourceFields(getResourceId(resource)[1])
cond_str = list_str(condiciones)
with open(file_name, 'w') as conds:
conds.write(cond_str)
return condiciones
def check_municipio(resource):
file_name = 'Service/data/municipios/' + resource + '.txt'
if os.path.exists(file_name):
#print("leyendo de archivos")
with open(file_name, 'r') as muns:
municipios = muns.read()
municipios = str_list(municipios)
return municipios
else:
#print("scraping resource page")
municipios = getMunicipios(getResourceId(resource)[1])
mun_str = list_str(municipios)
with open(file_name, 'w') as muns:
muns.write(mun_str)
return municipios
def datasets_info_by_name(dataset_name):
"""
Dataset info by name
Return a dictionary containing the fields for an specific dataset given by dataset name with no spaces
joined by '-' character
---
parameters:
- in: path
name: dataset_name
type: string
required: true
description: name with no spaces joined by the '-' character, example 'homicidios'
responses:
200:
description: a dictionary containing the fields for each time range
schema:
type: object
properties:
homicidios:
type: object
properties:
2020:
type: object
properties:
id:
type: string
example: b4fe8ba4-0d5b-4c8b-8c3b-85a20401ea3d
fields:
type: array
items:
type: object
properties:
label:
type: string
example: MES
type:
type: string
example: text
past:
type: object
properties:
id:
type: string
example: b4fe8ba4-0d5b-4c8b-8c3b-85a20401ea3d
fields:
type: array
items:
type: object
properties:
label:
type: string
example: fecha
type:
type: string
example: timestamp
"""
dsets = {}
res_ids = getResourceId(dataset_name)
dsets[dataset_name] = {}
dsets[dataset_name]['2020'] = {}
dsets[dataset_name]['past'] = {}
dsets[dataset_name]['2020']['id'] = res_ids[1]
dsets[dataset_name]['past']['id'] = res_ids[0]
dsets[dataset_name]['2020']['fields'] = getResourceFields(res_ids[1])
dsets[dataset_name]['past']['fields'] = getResourceFields(res_ids[0])
return Response(json.dumps(dsets), mimetype='application/json')
def datasets_complete_info():
"""
Complete datasets
Return a dictionary of datasets names containing the respective Ids for the past records and the 2020 records
and each id containing the fields for the dataset and the value type for each one
---
responses:
200:
description: a dictionary of datasets
schema:
type: object
properties:
homicidios:
type: object
properties:
2020:
type: object
properties:
id:
type: string
example: b4fe8ba4-0d5b-4c8b-8c3b-85a20401ea3d
fields:
type: array
items:
type: object
properties:
label:
type: string
example: MES
type:
type: string
example: text
past:
type: object
properties:
id:
type: string
example: b4fe8ba4-0d5b-4c8b-8c3b-85a20401ea3d
fields:
type: array
items:
type: object
properties:
label:
type: string
example: fecha
type:
type: string
example: timestamp
"""
datasets = get_datasets()
dsets = {}
for dset in datasets:
print('getting', dset)
res_ids = getResourceId(dset)
dsets[dset] = {}
dsets[dset]['2020'] = {}
dsets[dset]['past'] = {}
dsets[dset]['2020']['id'] = res_ids[1]
dsets[dset]['past']['id'] = res_ids[0]
dsets[dset]['2020']['fields'] = getResourceFields(res_ids[1])
dsets[dset]['past']['fields'] = getResourceFields(res_ids[0])
return Response(json.dumps(dsets), mimetype='application/json')