def read(target, meta_df=None, state=None, year=None, variety=None,
skiprows=None, nrows=None, chunksize=None, dtype=str, **kwargs):
"""Read in target data file. Uses supplied meta_df or infers from state, year, variety. In addition to built-in options, can pass any extra arguments understood by pd.read_fwf by using **kwargs.
Returns a pandas DataFrame object containing the parsed data if chunksize is None, otherwise returns a reader generating chunksize chunks with each iteration.
target -> required
1. full path to a data file (including filename); or
2. a file-like Python object (e.g. handler)
meta_df -> optional
may be a pandas DataFrame object containing meta data (width and field)
Can optionally specify rows to skip (skiprows) or limit the number of rows to read (nrows).
"""
import pandas as pd
import meta
if meta_df is not None:
assert type(meta_df) is pd.DataFrame, "If used, meta_df must be a pandas DataFrame object"
assert 'width' in meta_df.columns, "meta_df DataFrame must contain a column 'width'"
assert 'field' in meta_df.columns, "meta_df DataFrame must contain a column 'field'"
else:
#need to try to look up a load file
assert type(state) is str, "state must be a string if not supplying meta"
assert type(year) is str or type(year) is int, "year must be a string or integer if not supplying meta"
assert type(variety) is str, "variety must be a string if not supplying meta"
meta_df = meta.get(state, year, variety)
widths = [int(x) for x in meta_df.width]
names = [x for x in meta_df.field]
converters = {x: dtype for x in names} # would prefer to be using dtype=str with pd.read_fwf(), but it is not supported
result = pd.read_fwf(target, header=None, widths=widths, names=names,
nrows=nrows, skiprows=skiprows, converters=converters,
chunksize=chunksize, **kwargs)
return result
def test_get(self):
filename = self.get_test_filename('2016-10-17 avadhutmj.mp4')
self.assertEqual('ru', meta.get(filename, 'lang'))
def get_meta(pe):
show_meta = meta.get(pe)
return json.dumps({"Meta Data": show_meta}, indent=4, separators=(',', ': '))
return parser.parse_args(custom_args)
args = parse_custom_args()
common.ensure_addons()
if args.blend:
common.open_scene(args.blend)
version.save_new(args.id)
meta.write_media_info()
else:
run_updates = True
if args.min_interval:
meta = meta.get()
if "lastUpdate" in meta:
run_updates = time() - meta["lastUpdate"] < args.min_interval
if run_updates:
version.open_latest(args.id)
# TODO: Find problem: Why does it update although hash stayed the same?
# (Happened on update form external sources manually)
# (Note 06/03/2016 - not sure if still applies)
if update.update_models():
version.save_new(args.id)
meta.write_media_info()
else:
meta.write({"lastUpdate": time()})
args = parse_custom_args()
common.ensure_addons()
if args.blend:
common.open_scene(args.blend)
version.save_new(args.id)
meta.write_media_info()
else:
run_updates = True
if args.min_interval:
meta = meta.get()
if "lastUpdate" in meta:
run_updates = time() - meta["lastUpdate"] < args.min_interval
if run_updates:
version.open_latest(args.id)
# TODO: Find problem: Why does it update although hash stayed the same?
# (Happened on update form external sources manually)
# (Note 06/03/2016 - not sure if still applies)
if update.update_models():
version.save_new(args.id)
meta.write_media_info()
else:
meta.write({"lastUpdate": time()})
def get_meta(pe):
show_meta = meta.get(pe)
return json.dumps({"Meta Data": show_meta},
indent=4,
separators=(',', ': '))
def get_meta(pe):
show_meta = meta.get(pe)
return show_meta