Current File : //proc/thread-self/root/opt/imunify360/venv/lib/python3.11/site-packages/pip/_vendor/rich/_ratio.py
import sys
from fractions import Fraction
from math import ceil
from typing import cast, List, Optional, Sequence
if sys.version_info >= (3, 8):
from typing import Protocol
else:
from pip._vendor.typing_extensions import Protocol # pragma: no cover
class Edge(Protocol):
"""Any object that defines an edge (such as Layout)."""
size: Optional[int] = None
ratio: int = 1
minimum_size: int = 1
def ratio_resolve(total: int, edges: Sequence[Edge]) -> List[int]:
"""Divide total space to satisfy size, ratio, and minimum_size, constraints.
The returned list of integers should add up to total in most cases, unless it is
impossible to satisfy all the constraints. For instance, if there are two edges
with a minimum size of 20 each and `total` is 30 then the returned list will be
greater than total. In practice, this would mean that a Layout object would
clip the rows that would overflow the screen height.
Args:
total (int): Total number of characters.
edges (List[Edge]): Edges within total space.
Returns:
List[int]: Number of characters for each edge.
"""
# Size of edge or None for yet to be determined
sizes = [(edge.size or None) for edge in edges]
_Fraction = Fraction
# While any edges haven't been calculated
while None in sizes:
# Get flexible edges and index to map these back on to sizes list
flexible_edges = [
(index, edge)
for index, (size, edge) in enumerate(zip(sizes, edges))
if size is None
]
# Remaining space in total
remaining = total - sum(size or 0 for size in sizes)
if remaining <= 0:
# No room for flexible edges
return [
((edge.minimum_size or 1) if size is None else size)
for size, edge in zip(sizes, edges)
]
# Calculate number of characters in a ratio portion
portion = _Fraction(
remaining, sum((edge.ratio or 1) for _, edge in flexible_edges)
)
# If any edges will be less than their minimum, replace size with the minimum
for index, edge in flexible_edges:
if portion * edge.ratio <= edge.minimum_size:
sizes[index] = edge.minimum_size
# New fixed size will invalidate calculations, so we need to repeat the process
break
else:
# Distribute flexible space and compensate for rounding error
# Since edge sizes can only be integers we need to add the remainder
# to the following line
remainder = _Fraction(0)
for index, edge in flexible_edges:
size, remainder = divmod(portion * edge.ratio + remainder, 1)
sizes[index] = size
break
# Sizes now contains integers only
return cast(List[int], sizes)
def ratio_reduce(
total: int, ratios: List[int], maximums: List[int], values: List[int]
) -> List[int]:
"""Divide an integer total in to parts based on ratios.
Args:
total (int): The total to divide.
ratios (List[int]): A list of integer ratios.
maximums (List[int]): List of maximums values for each slot.
values (List[int]): List of values
Returns:
List[int]: A list of integers guaranteed to sum to total.
"""
ratios = [ratio if _max else 0 for ratio, _max in zip(ratios, maximums)]
total_ratio = sum(ratios)
if not total_ratio:
return values[:]
total_remaining = total
result: List[int] = []
append = result.append
for ratio, maximum, value in zip(ratios, maximums, values):
if ratio and total_ratio > 0:
distributed = min(maximum, round(ratio * total_remaining / total_ratio))
append(value - distributed)
total_remaining -= distributed
total_ratio -= ratio
else:
append(value)
return result
def ratio_distribute(
total: int, ratios: List[int], minimums: Optional[List[int]] = None
) -> List[int]:
"""Distribute an integer total in to parts based on ratios.
Args:
total (int): The total to divide.
ratios (List[int]): A list of integer ratios.
minimums (List[int]): List of minimum values for each slot.
Returns:
List[int]: A list of integers guaranteed to sum to total.
"""
if minimums:
ratios = [ratio if _min else 0 for ratio, _min in zip(ratios, minimums)]
total_ratio = sum(ratios)
assert total_ratio > 0, "Sum of ratios must be > 0"
total_remaining = total
distributed_total: List[int] = []
append = distributed_total.append
if minimums is None:
_minimums = [0] * len(ratios)
else:
_minimums = minimums
for ratio, minimum in zip(ratios, _minimums):
if total_ratio > 0:
distributed = max(minimum, ceil(ratio * total_remaining / total_ratio))
else:
distributed = total_remaining
append(distributed)
total_ratio -= ratio
total_remaining -= distributed
return distributed_total
if __name__ == "__main__":
from dataclasses import dataclass
@dataclass
class E:
size: Optional[int] = None
ratio: int = 1
minimum_size: int = 1
resolved = ratio_resolve(110, [E(None, 1, 1), E(None, 1, 1), E(None, 1, 1)])
print(sum(resolved))
Mini Shell