"""Helper functions for AWS FinOps operations."""
import re
from typing import Any
def format_header(accessor: str) -> str:
"""Convert field accessor to formatted header.
Examples:
instance_id -> Instance ID
AMIId -> AMI ID
MaxCPUUtilization -> Max CPU Utilization
"""
# Replace underscores with spaces
s = accessor.replace("_", " ")
# Insert space before CamelCase transitions
s = re.sub(r"(?<=[a-z])(?=[A-Z])", " ", s)
# Handle acronyms (keep AMI, ID, ASG, etc. uppercase)
words = s.split()
formatted_words = []
for w in words:
# Keep all-uppercase words as-is
if w.isupper():
formatted_words.append(w)
# Handle mixed case with acronyms
elif re.fullmatch(r"(?:[A-Z]{2,}[A-Z][a-z]*)+", w):
parts = re.findall(r"(?:[A-Z]{2,}(?=[A-Z][a-z]|$))|[A-Z][a-z]+|[a-z]+", w)
formatted_words.extend([p if p.isupper() else p.capitalize() for p in parts])
else:
formatted_words.append(w.capitalize())
return " ".join(formatted_words)
def fields_to_headers(fields: dict[str, str]) -> list[dict[str, str]]:
"""Convert fields dictionary to headers list.
Args:
fields: Dictionary mapping field IDs to accessor names
Returns:
List of header dictionaries with Header and accessor keys
"""
return [
{"Header": format_header(accessor), "accessor": accessor}
for accessor in fields.values()
]
def normalize_data(data_list: list[dict[str, Any]], all_tag_keys: set[str]) -> list[dict[str, Any]]:
"""Normalize data by ensuring all items have the same keys.
Args:
data_list: List of data dictionaries
all_tag_keys: Set of all possible tag keys
Returns:
Normalized list with consistent keys
"""
normalized_data = []
for item in data_list:
row = item.copy()
for tag_key in all_tag_keys:
row.setdefault(tag_key, "")
normalized_data.append(row)
return normalized_data
def remove_percent_sign(value: str | None) -> str:
"""Remove percent sign from string value."""
return value.replace("%", "").strip() if value else ""
def safe_float(value: Any, default: float = 0.0) -> float:
"""Safely convert value to float."""
if value is None:
return default
try:
if isinstance(value, str):
value = remove_percent_sign(value)
return float(value)
except (ValueError, TypeError):
return default
