in redash/query_runner/excel.py [0:0]
def run_query(self, query, user):
path = ""
ua = ""
args = {}
try:
args = yaml.safe_load(query)
path = args['url']
args.pop('url', None)
ua = args['user-agent']
args.pop('user-agent', None)
except:
pass
try:
response = requests_or_advocate.get(url=path, headers={"User-agent": ua})
workbook = pd.read_excel(response.content, **args)
df = workbook.copy()
data = {'columns': [], 'rows': []}
conversions = [
{'pandas_type': np.integer, 'redash_type': 'integer',},
{'pandas_type': np.inexact, 'redash_type': 'float',},
{'pandas_type': np.datetime64, 'redash_type': 'datetime', 'to_redash': lambda x: x.strftime('%Y-%m-%d %H:%M:%S')},
{'pandas_type': np.bool_, 'redash_type': 'boolean'},
{'pandas_type': np.object, 'redash_type': 'string'}
]
labels = []
for dtype, label in zip(df.dtypes, df.columns):
for conversion in conversions:
if issubclass(dtype.type, conversion['pandas_type']):
data['columns'].append({'name': label, 'friendly_name': label, 'type': conversion['redash_type']})
labels.append(label)
func = conversion.get('to_redash')
if func:
df[label] = df[label].apply(func)
break
data['rows'] = df[labels].replace({np.nan: None}).to_dict(orient='records')
json_data = json_dumps(data)
error = None
except KeyboardInterrupt:
error = "Query cancelled by user."
json_data = None
except UnacceptableAddressException:
error = "Can't query private addresses."
json_data = None
except Exception as e:
error = "Error reading {0}. {1}".format(path, str(e))
json_data = None
return json_data, error