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__pycache__	-	Open
apsw_ext.py	4.9 MB	View DL Edit
cockroachdb.py	8.95 MB	View DL Edit
dataset.py	14.15 MB	View DL Edit
db_url.py	4.26 MB	View DL Edit
fields.py	1.66 MB	View DL Edit
flask_utils.py	8 MB	View DL Edit
hybrid.py	1.49 MB	View DL Edit
kv.py	5.48 MB	View DL Edit
migrate.py	32.66 MB	View DL Edit
mysql_ext.py	3.78 MB	View DL Edit
pool.py	12.79 MB	View DL Edit
postgres_ext.py	14.98 MB	View DL Edit
psycopg3_ext.py	5.34 MB	View DL Edit
reflection.py	30.42 MB	View DL Edit
shortcuts.py	11.48 MB	View DL Edit
signals.py	2.45 MB	View DL Edit
sqlcipher_ext.py	3.55 MB	View DL Edit
sqliteq.py	10.57 MB	View DL Edit
sqlite_changelog.py	4.68 MB	View DL Edit
sqlite_ext.py	47.38 MB	View DL Edit
sqlite_udf.py	13.34 MB	View DL Edit
test_utils.py	1.81 MB	View DL Edit
__init__.py	0 B	View DL Edit

Edit file: /opt/imunify360/venv/lib/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),)

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