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filter.py
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filter.py
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import itertools
import re
from typing import List, Tuple
import pandas as pd
def validate_pipeline_input(meta, feats, columns):
if meta[columns].isna().any(axis=None):
raise ValueError("metadata columns should not have null values.")
if len(meta) != len(feats):
raise ValueError("meta and feats have different number of rows")
def flatten_str_list(*args):
"""create a single list with all the params given"""
columns = set()
for col in args:
if isinstance(col, str):
columns.add(col)
elif isinstance(col, dict):
columns.update(itertools.chain.from_iterable(col.values()))
else:
columns.update(col)
columns = list(columns)
return columns
def evaluate_and_filter(df, columns) -> Tuple[pd.DataFrame, List[str]]:
"""Evaluate the query and filter the dataframe"""
parsed_cols = []
for col in columns:
if col in df.columns:
parsed_cols.append(col)
continue
column_names = re.findall(r"(\w+)\s*[=<>!]+", col)
valid_column_names = [col for col in column_names if col in df.columns]
if not valid_column_names:
raise ValueError(f"Invalid query or column name: {col}")
try:
df = df.query(col)
parsed_cols.extend(valid_column_names)
except:
raise ValueError(f"Invalid query expression: {col}")
return df, parsed_cols