TabComp/includes/helpers.py

196 lines
6.5 KiB
Python

# Singular values may be decimal (no prefix), or any of the prefixes python accepts normally (0x for hex, 0b for binary, 0o for octal)
# Additionally, hexadecimals may be prefixed with '#' or '$', or suffixed with 'h', e.g. 0x10 #10 $10 10h are all parsed as 16
# For nested IDs, the format is ONLY like IP addresses:
# decimal with '.' separator, e.g. 16.127.1
# hexadecimal with ':' separator, e.g. 10:7f:1
# Nested IDs do not support prefixes.
def try_int(v):
try:
if v[0] in '#$': # Maybe % too?
return int(v[1:], 16)
if v[-1] == 'h':
return int(v[:-1], 16)
return int(v, 0)
except:
if v == '':
return None
return v
def get_max_number_width(container, fmt: str = 'd') -> int:
return len(f'{len(container)-1:{fmt}}')
def get_number_zero_pad(container, fmt: str = 'd') -> str:
max_digits = len(f'{len(container)-1:{fmt}}') # Could instead call get_max_number_width
return f'0{max_digits}{fmt}'
def encode_nested_ids(values: list[int], max_digits: list[int] = None, fmt: str = 'd') -> str:
delimiter = ':' if fmt in 'Xx' else '.'
if max_digits:
return delimiter.join([f'{value:0{digits}{fmt}}' for value, digits in zip(values, max_digits)])
else:
return delimiter.join([f'{value:{fmt}}' for value in values])
def decode_nested_ids(string: str) -> list[int]:
hex = ':' in string
delimiter = ':' if hex else '.'
return [int(i, 16 if hex else 10) for i in string.split(delimiter)]
def flatten_keys(container: dict | list, prefix: str = '') -> dict:
output = {}
def flatten_item(k: str, v):
if isinstance(v, dict) or isinstance(v, list):
flat = flatten_keys(v, f'{prefix}{k}.')
for k2, v2 in flat.items():
output[k2] = v2
else:
output[f'{prefix}{k}'] = v
if isinstance(container, list):
fmt = get_number_zero_pad(container, 'd') # Zero pad all of the indices to the same decimal string length as the final one
for k, v in enumerate(container):
flatten_item(f'{k:{fmt}}', v)
elif isinstance(container, dict):
for k, v in container.items():
flatten_item(k, v)
else:
raise ValueError(f'flatten_keys is undefined for container type "{container}"')
return output
def flatten_table(table: list, id_fmt: str = 'x') -> list:
if len(table) < 1:
return table # Empty
if isinstance(table[0], dict): # A simple table
return [flatten_keys(d) for d in table]
if isinstance(table[0], list): # Nested lists are bad when expanded as columns, so we'll expand
flattened_table = []
def flatten_list(data, ids: list[int], id_max_digits: list[int]) -> None:
if isinstance(data, list):
max_digits = id_max_digits + [get_max_number_width(data, id_fmt)]
for id, sub in enumerate(data):
flatten_list(sub, ids + [id], max_digits)
else:
entry = {'ID': encode_nested_ids(ids, id_max_digits, id_fmt)}
entry.update(flatten_keys(data))
flattened_table.append(entry)
flatten_list(table, [], [])
return flattened_table
else:
raise NotImplementedError(table[0])
def unflatten_keys(d: dict) -> dict:
output = {}
for k, v in d.items():
keysplit = k.split('.')
target_dict = output
for prefix in keysplit[:-1]:
if prefix not in target_dict:
target_dict[prefix] = {}
target_dict = target_dict[prefix]
target_dict[k] = v
return output
def unflatten_table(headers: list[str], entries: list):
if 'ID' not in headers:
return entries
# This could be an array of an array of an array of an...
id0 = entries[0]['ID']
if isinstance(id0, int) or ('.' not in id0 and ':' not in id0):
return entries
# Treat this as a nested array
table = {tuple(decode_nested_ids(entry['ID'])): entry for entry in entries}
output = []
def unflatten_arrays(id_split: tuple[int], cur_array: list, value):
i, *remainder = id_split
if len(remainder) > 0:
while len(cur_array) <= i: # Make sure our array has the index we're about to jump into
cur_array.append([])
unflatten_arrays(remainder, cur_array[i], value)
else:
while len(cur_array) <= i: # Make sure our array has the index we're about to overwrite
cur_array.append(None)
cur_array[i] = value
for id_split in sorted(table.keys()):
unflatten_arrays(id_split, output, table[id_split])
return output
def dump_tsv(filename, table, id_column=True) -> None:
table_flat = flatten_table(table)
with open(filename, 'w') as file:
headers = list(table_flat[0].keys())
if id_column and 'ID' not in headers: # Some flattened tables build their own ID column!
# See how long the hex representation of the last number will be, so we can zero-pad the rest to match.
fmt = get_number_zero_pad(table_flat, 'X')
file.write('\t'.join(['ID'] + headers) + '\n')
for i, entry in enumerate(table_flat):
file.write('\t'.join([f'0x{i:{fmt}}'] + [str(entry[key]) for key in headers]) + '\n')
else:
file.write('\t'.join(headers) + '\n')
for i, entry in enumerate(table_flat):
file.write('\t'.join([str(entry[key]) for key in headers]) + '\n')
def load_tsv(filename: str, unflatten: bool = True) -> list:
with open(filename, 'r') as file:
lines = file.read().rstrip().split('\n')
if len(lines) < 2:
return []
headers = lines[0].split('\t')
if not unflatten:
return [{key: try_int(value) for key, value in zip(headers, line.split('\t'))} for line in lines[1:]]
# Simple line-by-line unflatten
entries = []
for line in lines[1:]:
entry = {key: try_int(value) for key, value in zip(headers, line.split('\t'))}
entries.append(unflatten_keys(entry))
return unflatten_table(headers, entries)
def deep_update(old_container: list|dict, new_container: list|dict, ignore_holes: bool = True):
# Recurse through old_container, overwriting all values changed by new_container.
# Values of None in new_container will be treated as holes.
if isinstance(old_container, list):
for i, new in enumerate(new_container):
if ignore_holes and new is None: # Allow holes in the table for values we don't care about overwriting
continue
if isinstance(new, dict):
id = new.get('ID')
if not isinstance(id, int):
id = i
deep_update(old_container[id], new)
elif isinstance(new, list):
deep_update(old_container[i], new)
else:
old_container[i] = value
elif isinstance(old_container, dict):
for key, value in new_container.items():
if key == 'ID':
continue
if ignore_holes and value is None: # Allow holes in the table for values we don't care about overwriting
continue
if isinstance(value, dict) or isinstance(value, list):
deep_update(old_container[key], value)
else:
old_container[key] = value
else:
raise ValueError