Source code for dtale.cli.loaders.csv_loader
import pandas as pd
import requests
from six import PY3, BytesIO, StringIO
from dtale.app import show
from dtale.cli.clickutils import get_loader_options, loader_prop_keys
'''
IMPORTANT!!! These global variables are required for building any customized CLI loader.
When build_loaders runs startup it will search for any modules containing the global variable LOADER_KEY.
'''
LOADER_KEY = 'csv'
LOADER_PROPS = [
dict(name='path', help='path to CSV file'),
dict(name='proxy', help="proxy URL if you're passing in a URL for --csv-path"),
dict(name='parse_dates', help='comma-separated string of column names which should be parsed as dates')
]
# IMPORTANT!!! This function is required if you would like to be able to use this loader from the back-end.
[docs]def show_loader(**kwargs):
return show(data_loader=lambda: loader_func(**kwargs), **kwargs)
[docs]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)})
# IMPORTANT!!! This function is required for building any customized CLI loader.
[docs]def find_loader(kwargs):
"""
CSV implementation of data loader which will return a function if any of the
`click` options based on LOADER_KEY & LOADER_PROPS have been used, otherwise return None
:param kwargs: Optional keyword arguments to be passed from `click`
:return: data loader function for CSV implementation
"""
csv_opts = get_loader_options(LOADER_KEY, kwargs)
if len([f for f in csv_opts.values() if f]):
def _csv_loader():
csv_arg_parsers = { # TODO: add additional arg parsers
'parse_dates': lambda v: v.split(',') if v else None
}
kwargs = {k: csv_arg_parsers.get(k, lambda v: v)(v) for k, v in csv_opts.items()}
return loader_func(**kwargs)
return _csv_loader
return None