def loader_func(**kwargs):
path = kwargs.pop("path")
engine = "xlrd" if path.endswith("xls") else "openpyxl"
sheet_name = kwargs.pop("sheet", None)
if path.startswith("http://") or path.startswith("https://"):
proxy = kwargs.pop("proxy", None)
req_kwargs = {}
if proxy is not None:
req_kwargs["proxies"] = dict(http=proxy, https=proxy)
resp = requests.get(path, **req_kwargs)
assert resp.status_code == 200
path = BytesIO(resp.content) if PY3 else StringIO(resp.content.decode("utf-8"))
dfs = pd.read_excel(
path,
sheet_name=sheet_name,
engine=engine,
**{k: v for k, v in kwargs.items() if k in loader_prop_keys(LOADER_PROPS)}
)
if dfs is None or not len(dfs):
raise Exception("Failed to load Excel file. Returned no data.")
if sheet_name:
if sheet_name not in dfs:
raise Exception(
"Excel file loaded but there was no sheet named '{}'.".format(
sheet_name
)
)
return dfs[sheet_name]
# this is required because there is no support for loading multiple datasets at once from the CLI
# I can add this later...
return dfs[list(dfs.keys())[0]]
def loader_func(**kwargs):
path = handle_path(kwargs.pop("path"), kwargs)
return pd.read_csv(
path, **{
k: v
for k, v in kwargs.items() if k in loader_prop_keys(LOADER_PROPS)
})
def loader_func(**kwargs):
try:
import pyarrow # noqa: F401
except ImportError:
try:
import fastparquet # noqa: F401
except ImportError:
raise ImportError(
"In order to use the parquet loader you must install either pyarrow or fastparquet!"
)
path = kwargs.pop("path")
return pd.read_parquet(
path, **{k: v for k, v in kwargs.items() if k in loader_prop_keys(LOADER_PROPS)}
)
def loader_func(**kwargs):
path = kwargs.pop("path")
if path.startswith("http://") or path.startswith(
"https://"
): # add support for URLs
proxy = kwargs.pop("proxy", None)
req_kwargs = {}
if proxy is not None:
req_kwargs["proxies"] = dict(http=proxy, https=proxy)
resp = requests.get(path, **req_kwargs)
assert resp.status_code == 200
path = BytesIO(resp.content)
return pd.read_csv(
path, **{k: v for k, v in kwargs.items() if k in loader_prop_keys(LOADER_PROPS)}
)
def loader_func(**kwargs):
path = kwargs.pop('path')
normalize = kwargs.pop('normalize', False)
if path.startswith('http://') or path.startswith('https://'): # add support for URLs
proxy = kwargs.pop('proxy', None)
req_kwargs = {}
if proxy is not None:
req_kwargs['proxies'] = dict(http=proxy, https=proxy)
resp = requests.get(path, **req_kwargs)
assert resp.status_code == 200
path = resp.json() if normalize else resp.text
if normalize:
normalize_func = pd.json_normalize if is_pandas1() else pd.io.json.json_normalize
return normalize_func(path, **kwargs)
return pd.read_json(path, **{k: v for k, v in kwargs.items() if k in loader_prop_keys(LOADER_PROPS)})
def load_file(sheet_name=None, **kwargs):
path = kwargs.pop("path")
engine = "xlrd" if path.endswith("xls") else "openpyxl"
path = handle_path(path, kwargs)
dfs = pd.read_excel(path,
sheet_name=sheet_name,
engine=engine,
**{
k: v
for k, v in kwargs.items()
if k in loader_prop_keys(LOADER_PROPS)
})
if dfs is None or not len(dfs):
raise Exception("Failed to load Excel file. Returned no data.")
return dfs
def loader_func(**kwargs):
normalize = kwargs.pop("normalize", False)
def resp_handler(resp):
return resp.json() if normalize else resp.text
path = handle_path(kwargs.pop("path"), kwargs, resp_handler=resp_handler)
if normalize:
normalize_func = (pd.json_normalize
if is_pandas1() else pd.io.json.json_normalize)
return normalize_func(path, **kwargs)
return pd.read_json(
path, **{
k: v
for k, v in kwargs.items() if k in loader_prop_keys(LOADER_PROPS)
})
def loader_func(**kwargs):
path = kwargs.pop('path')
if path.startswith('http://') or path.startswith(
'https://'): # add support for URLs
proxy = kwargs.pop('proxy', None)
req_kwargs = {}
if proxy is not None:
req_kwargs['proxies'] = dict(http=proxy, https=proxy)
resp = requests.get(path, **req_kwargs)
assert resp.status_code == 200
path = BytesIO(resp.content) if PY3 else StringIO(
resp.content.decode('utf-8'))
return pd.read_csv(
path, **{
k: v
for k, v in kwargs.items() if k in loader_prop_keys(LOADER_PROPS)
})
def loader_func(**kwargs):
path = kwargs.pop("path")
engine = "xlrd" if path.endswith("xls") else "openpyxl"
sheet_name = kwargs.pop("sheet", None)
path = handle_path(path, kwargs)
dfs = pd.read_excel(
path,
sheet_name=sheet_name,
engine=engine,
**{k: v for k, v in kwargs.items() if k in loader_prop_keys(LOADER_PROPS)}
)
if dfs is None or not len(dfs):
raise Exception("Failed to load Excel file. Returned no data.")
if sheet_name:
if sheet_name not in dfs:
raise Exception(
"Excel file loaded but there was no sheet named '{}'.".format(
sheet_name
)
)
return dfs[sheet_name]
# this is required because there is no support for loading multiple datasets at once from the CLI
# I can add this later...
return dfs[list(dfs.keys())[0]]