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import logging
logger = logging.getLogger("panwid.datatable")
import raccoon as rc
import collections
class DataTableDataFrame(rc.DataFrame):
DATA_TABLE_COLUMNS = ["_dirty", "_focus_position", "_value_fn", "_cls", "_details", "_rendered_row"]
def __init__(self, data=None, columns=None, index=None, index_name="index", sort=None):
if columns and not index_name in columns:
columns.insert(0, index_name)
columns += self.DATA_TABLE_COLUMNS
super(DataTableDataFrame, self).__init__(
data=data,
columns=columns,
index=index,
index_name=index_name,
sort=sort
)
# for c in self.DATA_TABLE_COLUMNS:
# self[c] = None
def _validate_index(self, indexes):
try:
return super(DataTableDataFrame, self)._validate_index(indexes)
except ValueError:
logger.error("duplicates in index: %s" %(
[item for item, count
in list(collections.Counter(indexes).items()) if count > 1
]))
raise
def log_dump(self, n=5, columns=None, label=None):
df = self
if columns:
if not isinstance(columns, list):
columns = [columns]
df = df[columns]
logger.info("%slength: %d, index: %s [%s%s]\n%s" %(
"%s, " %(label) if label else "",
len(self),
self.index_name,
",".join([str(x) for x in self.index[0:min(n, len(self.index))]]),
"..." if len(self.index) > n else "",
df.head(n)))
def transpose_data(self, rows):
data_columns = list(set().union(*(list(d.keys()) for d in rows)))
data_columns += [
c for c in self.columns
if c not in data_columns
and c != self.index_name
and c not in self.DATA_TABLE_COLUMNS
]
data_columns += ["_cls", "_details"]
data = dict(
list(zip((data_columns),
[ list(z) for z in zip(*[[
d.get(k, None if k != "_details" else {"open": False, "disabled": False})
if isinstance(d, collections.abc.MutableMapping)
else getattr(d, k, None if k != "_details" else {"open": False, "disabled": False})
# for k in data_columns + self.DATA_TABLE_COLUMNS] for d in rows])]
for k in data_columns] for d in rows])]
))
)
return data
def update_rows(self, rows, limit=None):
data = self.transpose_data(rows)
# data["_details"] = [{"open": False, "disabled": False}] * len(rows)
# if not "_details" in data:
# data["_details"] = [{"open": False, "disabled": False}] * len(rows)
if not limit:
if len(rows):
indexes = [x for x in self.index if x not in data.get(self.index_name, [])]
if len(indexes):
self.delete_rows(indexes)
else:
self.delete_all_rows()
# logger.info(f"update_rowGs: {self.index}, {data[self.index_name]}")
if not len(rows):
return []
if self.index_name not in data:
index = list(range(len(self), len(self) + len(rows)))
data[self.index_name] = index
else:
index = data[self.index_name]
for c in data.keys():
try:
self.set(data[self.index_name], c, data[c])
except ValueError as e:
logger.error(e)
logger.info(f"update_rows: {self.index}, {data}")
raise Exception(c, len(self.index), len(data[c]))
return data.get(self.index_name, [])
def append_rows(self, rows):
length = len(rows)
if not length:
return
colnames = list(self.columns) + [c for c in self.DATA_TABLE_COLUMNS if c not in self.columns]
# data_columns = list(set().union(*(list(d.keys()) for d in rows)))
data = self.transpose_data(rows)
colnames += [c for c in data.keys() if c not in colnames]
for c in self.columns:
if not c in data:
data[c] = [None]*length
for c in colnames:
if not c in self.columns:
self[c] = None
kwargs = dict(
columns = colnames,
data = data,
sort=False,
index=data[self.index_name],
index_name = self.index_name,
)
try:
newdata = DataTableDataFrame(**kwargs)
except ValueError:
raise Exception(kwargs)
# newdata.log_dump()
# self.log_dump(10, label="before")
try:
self.append(newdata)
except ValueError:
raise Exception(f"{self.index}, {newdata}")
# self.log_dump(10, label="after")
# def add_column(self, column, data=None):
# self[column] = data
def clear(self):
self.delete_all_rows()
# self.delete_rows(self.index)
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