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Direktori : /opt/imunify360/venv/lib64/python3.11/site-packages/playhouse/ |
Current File : //opt/imunify360/venv/lib64/python3.11/site-packages/playhouse/sqlite_udf.py |
import datetime import hashlib import heapq import math import os import random import re import sys import threading import zlib try: from collections import Counter except ImportError: Counter = None try: from urlparse import urlparse except ImportError: from urllib.parse import urlparse try: from playhouse._sqlite_ext import TableFunction except ImportError: TableFunction = None SQLITE_DATETIME_FORMATS = ( '%Y-%m-%d %H:%M:%S', '%Y-%m-%d %H:%M:%S.%f', '%Y-%m-%d', '%H:%M:%S', '%H:%M:%S.%f', '%H:%M') from peewee import format_date_time def format_date_time_sqlite(date_value): return format_date_time(date_value, SQLITE_DATETIME_FORMATS) try: from playhouse import _sqlite_udf as cython_udf except ImportError: cython_udf = None # Group udf by function. CONTROL_FLOW = 'control_flow' DATE = 'date' FILE = 'file' HELPER = 'helpers' MATH = 'math' STRING = 'string' AGGREGATE_COLLECTION = {} TABLE_FUNCTION_COLLECTION = {} UDF_COLLECTION = {} class synchronized_dict(dict): def __init__(self, *args, **kwargs): super(synchronized_dict, self).__init__(*args, **kwargs) self._lock = threading.Lock() def __getitem__(self, key): with self._lock: return super(synchronized_dict, self).__getitem__(key) def __setitem__(self, key, value): with self._lock: return super(synchronized_dict, self).__setitem__(key, value) def __delitem__(self, key): with self._lock: return super(synchronized_dict, self).__delitem__(key) STATE = synchronized_dict() SETTINGS = synchronized_dict() # Class and function decorators. def aggregate(*groups): def decorator(klass): for group in groups: AGGREGATE_COLLECTION.setdefault(group, []) AGGREGATE_COLLECTION[group].append(klass) return klass return decorator def table_function(*groups): def decorator(klass): for group in groups: TABLE_FUNCTION_COLLECTION.setdefault(group, []) TABLE_FUNCTION_COLLECTION[group].append(klass) return klass return decorator def udf(*groups): def decorator(fn): for group in groups: UDF_COLLECTION.setdefault(group, []) UDF_COLLECTION[group].append(fn) return fn return decorator # Register aggregates / functions with connection. def register_aggregate_groups(db, *groups): seen = set() for group in groups: klasses = AGGREGATE_COLLECTION.get(group, ()) for klass in klasses: name = getattr(klass, 'name', klass.__name__) if name not in seen: seen.add(name) db.register_aggregate(klass, name) def register_table_function_groups(db, *groups): seen = set() for group in groups: klasses = TABLE_FUNCTION_COLLECTION.get(group, ()) for klass in klasses: if klass.name not in seen: seen.add(klass.name) db.register_table_function(klass) def register_udf_groups(db, *groups): seen = set() for group in groups: functions = UDF_COLLECTION.get(group, ()) for function in functions: name = function.__name__ if name not in seen: seen.add(name) db.register_function(function, name) def register_groups(db, *groups): register_aggregate_groups(db, *groups) register_table_function_groups(db, *groups) register_udf_groups(db, *groups) def register_all(db): register_aggregate_groups(db, *AGGREGATE_COLLECTION) register_table_function_groups(db, *TABLE_FUNCTION_COLLECTION) register_udf_groups(db, *UDF_COLLECTION) # Begin actual user-defined functions and aggregates. # Scalar functions. @udf(CONTROL_FLOW) def if_then_else(cond, truthy, falsey=None): if cond: return truthy return falsey @udf(DATE) def strip_tz(date_str): date_str = date_str.replace('T', ' ') tz_idx1 = date_str.find('+') if tz_idx1 != -1: return date_str[:tz_idx1] tz_idx2 = date_str.find('-') if tz_idx2 > 13: return date_str[:tz_idx2] return date_str @udf(DATE) def human_delta(nseconds, glue=', '): parts = ( (86400 * 365, 'year'), (86400 * 30, 'month'), (86400 * 7, 'week'), (86400, 'day'), (3600, 'hour'), (60, 'minute'), (1, 'second'), ) accum = [] for offset, name in parts: val, nseconds = divmod(nseconds, offset) if val: suffix = val != 1 and 's' or '' accum.append('%s %s%s' % (val, name, suffix)) if not accum: return '0 seconds' return glue.join(accum) @udf(FILE) def file_ext(filename): try: res = os.path.splitext(filename) except ValueError: return None return res[1] @udf(FILE) def file_read(filename): try: with open(filename) as fh: return fh.read() except: pass if sys.version_info[0] == 2: @udf(HELPER) def gzip(data, compression=9): return buffer(zlib.compress(data, compression)) @udf(HELPER) def gunzip(data): return zlib.decompress(data) else: @udf(HELPER) def gzip(data, compression=9): if isinstance(data, str): data = bytes(data.encode('raw_unicode_escape')) return zlib.compress(data, compression) @udf(HELPER) def gunzip(data): return zlib.decompress(data) @udf(HELPER) def hostname(url): parse_result = urlparse(url) if parse_result: return parse_result.netloc @udf(HELPER) def toggle(key): key = key.lower() STATE[key] = ret = not STATE.get(key) return ret @udf(HELPER) def setting(key, value=None): if value is None: return SETTINGS.get(key) else: SETTINGS[key] = value return value @udf(HELPER) def clear_settings(): SETTINGS.clear() @udf(HELPER) def clear_toggles(): STATE.clear() @udf(MATH) def randomrange(start, end=None, step=None): if end is None: start, end = 0, start elif step is None: step = 1 return random.randrange(start, end, step) @udf(MATH) def gauss_distribution(mean, sigma): try: return random.gauss(mean, sigma) except ValueError: return None @udf(MATH) def sqrt(n): try: return math.sqrt(n) except ValueError: return None @udf(MATH) def tonumber(s): try: return int(s) except ValueError: try: return float(s) except: return None @udf(STRING) def substr_count(haystack, needle): if not haystack or not needle: return 0 return haystack.count(needle) @udf(STRING) def strip_chars(haystack, chars): return haystack.strip(chars) def _hash(constructor, *args): hash_obj = constructor() for arg in args: hash_obj.update(arg) return hash_obj.hexdigest() # Aggregates. class _heap_agg(object): def __init__(self): self.heap = [] self.ct = 0 def process(self, value): return value def step(self, value): self.ct += 1 heapq.heappush(self.heap, self.process(value)) class _datetime_heap_agg(_heap_agg): def process(self, value): return format_date_time_sqlite(value) if sys.version_info[:2] == (2, 6): def total_seconds(td): return (td.seconds + (td.days * 86400) + (td.microseconds / (10.**6))) else: total_seconds = lambda td: td.total_seconds() @aggregate(DATE) class mintdiff(_datetime_heap_agg): def finalize(self): dtp = min_diff = None while self.heap: if min_diff is None: if dtp is None: dtp = heapq.heappop(self.heap) continue dt = heapq.heappop(self.heap) diff = dt - dtp if min_diff is None or min_diff > diff: min_diff = diff dtp = dt if min_diff is not None: return total_seconds(min_diff) @aggregate(DATE) class avgtdiff(_datetime_heap_agg): def finalize(self): if self.ct < 1: return elif self.ct == 1: return 0 total = ct = 0 dtp = None while self.heap: if total == 0: if dtp is None: dtp = heapq.heappop(self.heap) continue dt = heapq.heappop(self.heap) diff = dt - dtp ct += 1 total += total_seconds(diff) dtp = dt return float(total) / ct @aggregate(DATE) class duration(object): def __init__(self): self._min = self._max = None def step(self, value): dt = format_date_time_sqlite(value) if self._min is None or dt < self._min: self._min = dt if self._max is None or dt > self._max: self._max = dt def finalize(self): if self._min and self._max: td = (self._max - self._min) return total_seconds(td) return None @aggregate(MATH) class mode(object): if Counter: def __init__(self): self.items = Counter() def step(self, *args): self.items.update(args) def finalize(self): if self.items: return self.items.most_common(1)[0][0] else: def __init__(self): self.items = [] def step(self, item): self.items.append(item) def finalize(self): if self.items: return max(set(self.items), key=self.items.count) @aggregate(MATH) class minrange(_heap_agg): def finalize(self): if self.ct == 0: return elif self.ct == 1: return 0 prev = min_diff = None while self.heap: if min_diff is None: if prev is None: prev = heapq.heappop(self.heap) continue curr = heapq.heappop(self.heap) diff = curr - prev if min_diff is None or min_diff > diff: min_diff = diff prev = curr return min_diff @aggregate(MATH) class avgrange(_heap_agg): def finalize(self): if self.ct == 0: return elif self.ct == 1: return 0 total = ct = 0 prev = None while self.heap: if total == 0: if prev is None: prev = heapq.heappop(self.heap) continue curr = heapq.heappop(self.heap) diff = curr - prev ct += 1 total += diff prev = curr return float(total) / ct @aggregate(MATH) class _range(object): name = 'range' def __init__(self): self._min = self._max = None def step(self, value): if self._min is None or value < self._min: self._min = value if self._max is None or value > self._max: self._max = value def finalize(self): if self._min is not None and self._max is not None: return self._max - self._min return None @aggregate(MATH) class stddev(object): def __init__(self): self.n = 0 self.values = [] def step(self, v): self.n += 1 self.values.append(v) def finalize(self): if self.n <= 1: return 0 mean = sum(self.values) / self.n return math.sqrt(sum((i - mean) ** 2 for i in self.values) / (self.n - 1)) if cython_udf is not None: damerau_levenshtein_dist = udf(STRING)(cython_udf.damerau_levenshtein_dist) levenshtein_dist = udf(STRING)(cython_udf.levenshtein_dist) str_dist = udf(STRING)(cython_udf.str_dist) median = aggregate(MATH)(cython_udf.median) if TableFunction is not None: @table_function(STRING) class RegexSearch(TableFunction): params = ['regex', 'search_string'] columns = ['match'] name = 'regex_search' def initialize(self, regex=None, search_string=None): self._iter = re.finditer(regex, search_string) def iterate(self, idx): return (next(self._iter).group(0),) @table_function(DATE) class DateSeries(TableFunction): params = ['start', 'stop', 'step_seconds'] columns = ['date'] name = 'date_series' def initialize(self, start, stop, step_seconds=86400): self.start = format_date_time_sqlite(start) self.stop = format_date_time_sqlite(stop) step_seconds = int(step_seconds) self.step_seconds = datetime.timedelta(seconds=step_seconds) if (self.start.hour == 0 and self.start.minute == 0 and self.start.second == 0 and step_seconds >= 86400): self.format = '%Y-%m-%d' elif (self.start.year == 1900 and self.start.month == 1 and self.start.day == 1 and self.stop.year == 1900 and self.stop.month == 1 and self.stop.day == 1 and step_seconds < 86400): self.format = '%H:%M:%S' else: self.format = '%Y-%m-%d %H:%M:%S' def iterate(self, idx): if self.start > self.stop: raise StopIteration current = self.start self.start += self.step_seconds return (current.strftime(self.format),)