193 lines
6.3 KiB
Python
193 lines
6.3 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)
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# Additionally, hexadecimals may be prefixed with '#' or '$', or suffixed with 'h', e.g. 0x10 #10 $10 10h are all parsed as 16
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# For nested IDs, the format is ONLY like IP addresses:
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# decimal with '.' separator, e.g. 16.127.1
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# hexadecimal with ':' separator, e.g. 10:7f:1
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# Nested IDs do not support prefixes.
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def try_int(v):
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try:
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if v[0] in '#$': # Maybe % too?
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return int(v[1:], 16)
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if v[-1] == 'h':
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return int(v[:-1], 16)
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return int(v, 0)
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except:
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if v == '':
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return None
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return v
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def get_max_number_width(container, fmt: str = 'd') -> int:
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return len(f'{len(container)-1:{fmt}}')
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def get_number_zero_pad(container, fmt: str = 'd') -> str:
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max_digits = len(f'{len(container)-1:{fmt}}') # Could instead call get_max_number_width
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return f'0{max_digits}{fmt}'
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def encode_nested_ids(values: list[int], max_digits: list[int] = None, fmt: str = 'd') -> str:
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delimiter = ':' if fmt in 'Xx' else '.'
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if max_digits:
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return delimiter.join([f'{value:0{digits}{fmt}}' for value, digits in zip(values, max_digits)])
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else:
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return delimiter.join([f'{value:{fmt}}' for value in values])
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def decode_nested_ids(string: str) -> list[int]:
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hex = ':' in string
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delimiter = ':' if hex else '.'
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return [int(i, 16 if hex else 10) for i in string.split(delimiter)]
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def flatten_keys(container: dict | list, prefix: str = '') -> dict:
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output = {}
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def flatten_item(k: str, v):
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if isinstance(v, dict) or isinstance(v, list):
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flat = flatten_keys(v, f'{prefix}{k}.')
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for k2, v2 in flat.items():
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output[k2] = v2
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else:
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output[f'{prefix}{k}'] = v
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if isinstance(container, list):
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fmt = get_number_zero_pad(container, 'd') # Zero pad all of the indices to the same decimal string length as the final one
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for k, v in enumerate(container):
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flatten_item(f'{k:{fmt}}', v)
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elif isinstance(container, dict):
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for k, v in container.items():
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flatten_item(k, v)
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else:
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raise ValueError(f'flatten_keys is undefined for container type "{container}"')
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return output
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def flatten_table(table: list, id_fmt: str = 'x') -> list:
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if len(table) < 1:
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return table # Empty
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if isinstance(table[0], dict): # A simple table
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return [flatten_keys(d) for d in table]
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if isinstance(table[0], list): # Nested lists are bad when expanded as columns, so we'll expand
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flattened_table = []
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def flatten_list(data, ids: list[int], id_max_digits: list[int]) -> None:
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if isinstance(data, list):
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max_digits = id_max_digits + [get_max_number_width(data, id_fmt)]
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for id, sub in enumerate(data):
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flatten_list(sub, ids + [id], max_digits)
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else:
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entry = {'ID': encode_nested_ids(ids, id_max_digits, id_fmt)}
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entry.update(flatten_keys(data))
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flattened_table.append(entry)
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flatten_list(table, [], [])
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return flattened_table
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else:
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raise NotImplementedError(table[0])
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def unflatten_keys(d: dict) -> dict:
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output = {}
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for k, v in d.items():
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keysplit = k.split('.')
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target_dict = output
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for prefix in keysplit[:-1]:
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if prefix not in target_dict:
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target_dict[prefix] = {}
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target_dict = target_dict[prefix]
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target_dict[k] = v
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return output
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def unflatten_table(headers: list[str], entries: list):
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if 'ID' not in headers:
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return entries
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# This could be an array of an array of an array of an...
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id0 = entries[0]['ID']
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if '.' not in id0 and ':' not in id0:
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return entries
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# Treat this as a nested array
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table = {tuple(decode_nested_ids(entry['ID'])): entry for entry in entries}
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output = []
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def unflatten_arrays(id_split: tuple[int], cur_array: list, value):
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i, *remainder = id_split
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if len(remainder) > 0:
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while len(cur_array) <= i: # Make sure our array has the index we're about to jump into
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cur_array.append([])
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unflatten_arrays(remainder, cur_array[i], value)
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else:
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while len(cur_array) <= i: # Make sure our array has the index we're about to overwrite
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cur_array.append(None)
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cur_array[i] = value
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for id_split in sorted(table.keys()):
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unflatten_arrays(id_split, output, table[id_split])
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return output
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def dump_tsv(filename, table, id_column=True) -> None:
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table_flat = flatten_table(table)
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with open(filename, 'w') as file:
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headers = list(table_flat[0].keys())
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if id_column and 'ID' not in headers: # Some flattened tables build their own ID column!
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# See how long the hex representation of the last number will be, so we can zero-pad the rest to match.
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fmt = get_number_zero_pad(table_flat, 'X')
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file.write('\t'.join(['ID'] + headers) + '\n')
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for i, entry in enumerate(table_flat):
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file.write('\t'.join([f'0x{i:{fmt}}'] + [str(entry[key]) for key in headers]) + '\n')
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else:
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file.write('\t'.join(headers) + '\n')
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for i, entry in enumerate(table_flat):
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file.write('\t'.join([str(entry[key]) for key in headers]) + '\n')
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def load_tsv(filename) -> list:
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with open(filename, 'r') as file:
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lines = file.read().rstrip().split('\n')
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if len(lines) < 2:
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return []
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headers = lines[0].split('\t')
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# Simple line-by-line unflatten
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entries = []
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for line in lines[1:]:
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entry = {key: try_int(value) for key, value in zip(headers, line.split('\t'))}
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entries.append(unflatten_keys(entry))
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return unflatten_table(headers, entries)
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def deep_update(old_container: list|dict, new_container: list|dict, ignore_holes: bool = True):
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# Recurse through old_container, overwriting all values changed by new_container.
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# Values of None in new_container will be treated as holes.
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if isinstance(old_container, list):
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for i, new in enumerate(new_container):
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if ignore_holes and new is None: # Allow holes in the table for values we don't care about overwriting
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continue
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if isinstance(new, dict):
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id = new.get('ID')
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if not isinstance(id, int):
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id = i
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deep_update(old_container[id], new)
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elif isinstance(new, list):
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deep_update(old_container[i], new)
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else:
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old_container[i] = value
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elif isinstance(old_container, dict):
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for key, value in new_container.items():
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if key == 'ID':
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continue
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if ignore_holes and value is None: # Allow holes in the table for values we don't care about overwriting
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continue
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if isinstance(value, dict) or isinstance(value, list):
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deep_update(old_container[key], value)
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else:
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old_container[key] = value
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else:
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raise ValueError
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