Source code for ai2_kit.core.util

from typing import Tuple, List, TypeVar, Union, Iterable, Literal
from ruamel.yaml import YAML, ScalarNode, SequenceNode
from collections import namedtuple
from itertools import zip_longest
from pathlib import Path

import shortuuid
import asyncio
import hashlib
import inspect
import base64
import psutil
import random
import shlex
import json
import glob
import os

from .log import get_logger

logger = get_logger(__name__)

EMPTY = object()

SAMPLE_METHOD = Literal['even', 'random', 'truncate']

[docs] def load_json(path: Union[Path, str], encoding: str = 'utf-8'): if isinstance(path, str): path = Path(path) with open(path, 'r', encoding=encoding) as f: return json.load(f)
[docs] def load_text(path: Union[Path, str], encoding: str = 'utf-8'): if isinstance(path, str): path = Path(path) with open(path, 'r', encoding=encoding) as f: return f.read()
[docs] def parse_path_list(path_list_str: Union[str, List[str]], to_abs: bool = False): """ Parse path list of environment variable style string """ def parse_path(path: str): return os.path.expanduser(path) if path.startswith('~/') else path if isinstance(path_list_str, str): path_list = path_list_str.split(':') else: path_list = path_list_str if to_abs: path_list = [parse_path(path) for path in path_list] return path_list
[docs] def wait_for_change(widget, attribute): """ Wait for attribute change of a Jupyter widget """ future = asyncio.Future() def getvalue(change): # make the new value available future.set_result(change.new) widget.unobserve(getvalue, attribute) widget.observe(getvalue, attribute) return future
[docs] def get_yaml(): yaml = YAML(typ='safe') JoinTag.register(yaml) LoadTextTag.register(yaml) LoadYamlTag.register(yaml) return yaml
[docs] def load_yaml_file(path: Union[Path, str]): if isinstance(path, str): path = Path(path) yaml = get_yaml() return yaml.load(path)
[docs] def load_yaml_files(*paths: Union[Path, str], quiet: bool = False, purge_anonymous = True): d = {} for path in paths: print('load yaml file: ', path) d = merge_dict(d, load_yaml_file(path), quiet=quiet) if purge_anonymous: dict_remove_dot_keys(d) return d
[docs] def nested_set(d: dict, keys: List[str], value): for key in keys[:-1]: d = d.setdefault(key, {}) d[keys[-1]] = value
[docs] def s_uuid(): """short uuid""" return shortuuid.uuid()
[docs] def sort_unique_str_list(l: List[str]) -> List[str]: """remove duplicate str and sort""" return sorted(set(l))
T = TypeVar('T')
[docs] def flatten(l: List[List[T]]) -> List[T]: return [item for sublist in l for item in sublist]
[docs] def format_env_string(s: str) -> str: return s.format(**os.environ)
[docs] def list_split(l: List[T], n: int) -> List[List[T]]: """split list into n chunks""" # ref: https://stackoverflow.com/questions/2130016/splitting-a-list-into-n-parts-of-approximately-equal-length k, m = divmod(len(l), n) return [l[i*k+min(i, m): (i+1)*k+min(i+1, m)] for i in range(n)]
[docs] def short_hash(s: str) -> str: """short hash string""" digest = hashlib.sha1(s.encode('utf-8')).digest() # use urlsafe encode to avoid '/' in the string, as it will cause problem in file path return base64.urlsafe_b64encode(digest).decode('utf-8')[:-2]
[docs] async def to_awaitable(value: T) -> T: return value
[docs] class JoinTag: """a tag to join strings in a list""" yaml_tag = u'!join'
[docs] @classmethod def from_yaml(cls, constructor, node): seq = constructor.construct_sequence(node) return ''.join([str(i) for i in seq])
[docs] @classmethod def to_yaml(cls, dumper, data): ...
[docs] @classmethod def register(cls, yaml: YAML): yaml.register_class(cls)
[docs] class LoadTextTag: """a tag to read string from file""" yaml_tag = u'!load_text'
[docs] @classmethod def from_yaml(cls, constructor, node): path = _yaml_get_path_node(node, constructor) with open(path, 'r') as f: return f.read()
[docs] @classmethod def to_yaml(cls, dumper, data): ...
[docs] @classmethod def register(cls, yaml: YAML): yaml.register_class(cls)
[docs] class LoadYamlTag: """a tag to read string from file""" yaml_tag = u'!load_yaml'
[docs] @classmethod def from_yaml(cls, constructor, node): path = _yaml_get_path_node(node, constructor) yaml = get_yaml() with open(path, 'r') as f: return yaml.load(f)
[docs] @classmethod def to_yaml(cls, dumper, data): ...
[docs] @classmethod def register(cls, yaml: YAML): yaml.register_class(cls)
def _yaml_get_path_node(node, constructor): if isinstance(node, ScalarNode): return constructor.construct_scalar(node) elif isinstance(node, SequenceNode): seq = constructor.construct_sequence(node) return os.path.join(*seq) else: raise ValueError(f'Unknown node type {type(node)}')
[docs] def dict_remove_dot_keys(d): for k in list(d.keys()): if k.startswith('.'): del d[k] elif isinstance(d[k], dict): dict_remove_dot_keys(d[k])
[docs] def cmd_with_checkpoint(cmd: str, checkpoint: str, ignore_error: bool = False): """ Add checkpoint to a shell command. If a checkpoint file exists, the command will be skipped, otherwise the command will be executed and a checkpoint file will be created if the command is executed successfully. :param cmd: shell command :param checkpoint: checkpoint file name :param ignore_error: if True, will not raise error if the command failed """ checkpoint = shlex.quote(checkpoint) exit_clause = [ ' __EXITCODE__=$?; if [ $__EXITCODE__ -ne 0 ]; then exit $__EXITCODE__; fi', ] if not ignore_error else [] msg = shlex.quote(f"hit checkpoint: {checkpoint}, skip...") return '\n'.join([ f'if [ -f {checkpoint} ]; then echo {msg}; else', f' {cmd}', *exit_clause, f' touch {checkpoint}', f'fi', ])
[docs] def merge_dict(lo: dict, ro: dict, path=None, ignore_none=True, quiet=False): """ Merge two dict, the left dict will be overridden. Note: list will be replaced instead of merged. """ if path is None: path = [] for key, value in ro.items(): if ignore_none and value is None: continue if key in lo: current_path = path + [str(key)] if isinstance(lo[key], dict) and isinstance(value, dict): merge_dict(lo[key], value, path=current_path, ignore_none=ignore_none, quiet=quiet) else: if not quiet: print('.'.join(current_path) + ' has been overridden') lo[key] = value else: lo[key] = value return lo
[docs] def dict_nested_get(d: dict, keys: List[str], default=EMPTY): """get value from nested dict""" for key in keys: if key not in d and default is not EMPTY: return default d = d[key] return d
[docs] def dict_nested_set(d: dict, keys: List[str], value): """set value to nested dict""" for key in keys[:-1]: d = d[key] d[keys[-1]] = value
[docs] def list_even_sample(l, size): if size <= 0 or size > len(l): return l # calculate the sample interval interval = len(l) / size return [l[int(i * interval)] for i in range(size)]
[docs] def list_random_sample(l, size, seed = None): if seed is None: seed = len(l) random.seed(seed) return random.sample(l, size)
[docs] def list_sample(l, size: int, method: SAMPLE_METHOD='even', **kwargs): """ sample list :param size: size of sample, if size is larger than data size, return all data :param method: method to sample, can be 'even', 'random', 'truncate', default is 'even' :param seed: seed for random sample, only used when method is 'random' Note that by default the seed is length of input list, if you want to generate different sample each time, you should set random seed manually """ if method == 'even': return list_even_sample(l, size) elif method == 'random': return list_random_sample(l, size, **kwargs) elif method == 'truncate': return l[:size] else: raise ValueError(f'Unknown sample method {method}')
[docs] def flat_evenly(list_of_lists): """ flat a list of lists and ensure the output result distributed evenly >>> flat_evenly([[1, 2, 3], [4, 5, 6], [7, 8, 9]]) [1, 4, 7, 2, 5, 8, 3, 6, 9] Ref: https://stackoverflow.com/questions/76751171/how-to-flat-a-list-of-lists-and-ensure-the-output-result-distributed-evenly-in-p """ return [e for tup in zip_longest(*list_of_lists) for e in tup if e is not None]
[docs] def limit(it, size=-1): """ limit the size of an iterable """ if size <= 0: yield from it else: for i, x in enumerate(it): if i >= size: break yield x
[docs] def dump_json(obj, path: str): default = lambda o: f"<<non-serializable: {type(o).__qualname__}>>" with open(path, 'w', encoding='utf-8') as f: json.dump(obj, f, indent=2, default=default)
[docs] def dump_text(text: str, path: str, **kwargs): with open(path, 'w', **kwargs) as f: f.write(text)
[docs] def flush_stdio(): import sys sys.stdout.flush() sys.stderr.flush()
[docs] def ensure_dir(path: str): dirname = os.path.dirname(path) if dirname: os.makedirs(dirname, exist_ok=True)
[docs] def expand_globs(patterns: Iterable[str], raise_invalid=False) -> List[str]: """ Expand glob patterns in paths :param patterns: list of paths or glob patterns :param raise_invalid: if True, will raise error if no file found for a glob pattern :return: list of expanded paths """ paths = [] for pattern in patterns: result = glob.glob(pattern, recursive=True) if '*' in pattern else [pattern] if raise_invalid and len(result) == 0: raise FileNotFoundError(f'No file found for {pattern}') for p in result: if p not in paths: paths.append(p) else: logger.warn(f'path {p} already exists in the list') return paths
[docs] def slice_from_str(index: str): """ get slice object from a string expression, for example: "1:10" -> slice(1, 10), ":10" -> slice(None, 10), etc """ parse = lambda s: int(s) if s else None parts = index.split(':') return slice(*(parse(s) for s in parts))
[docs] def perf_log(msg): process = psutil.Process() mem_info = process.memory_info() logger.info('perf: rss: %s M %s', mem_info.rss / 1024 ** 2, msg)
[docs] def create_fn(func_str: str, fn_name: str): _locals = {} exec(func_str, _locals) if fn_name not in _locals: raise ValueError(f'Function {fn_name} not found in {func_str}') return _locals[fn_name]