content stringlengths 7 1.05M | fixed_cases stringlengths 1 1.28M |
|---|---|
'''Basic object to store the agents and auxiliary content in the agent system
graph. The object should be considered to be replaced with namedtuple at some
point, once the default field has matured
'''
class Node(object):
'''Basic object to store agent and auxiliary content in the agent system.
Parameters
----------
name : str
Name of node
agent_content : Agent
An Agent object
aux_content : optional
Auxiliary content, such as an immediate environment, to the Agent of
the Node
other_attributes : dict, optional
Dictionary of additional attributes assigned to the Node. These can
be part of operations on the graph during a simulation or they can be
part of graph sampling, for example. Each key is the name of the
attribute, the value is the value of the attribute.
'''
def __str__(self):
return 'Node(name:%s)' %(self.name)
def __contains__(self, item):
if self.agent_content is None:
return False
else:
return item == self.agent_content.agent_id_system
def __init__(self, name, agent_content, aux_content=None,
other_attributes={}):
self.name = name
self.agent_content = agent_content
self.aux_content = aux_content
for key, item in other_attributes:
setattr(self, key, item)
def node_maker(agents, envs=None, node_names=None, node_attributes=None):
'''Convenience function to place a collection of agents and environments in nodes
Parameters
----------
TBD
Returns
-------
TBD
'''
n_nodes = len(agents)
if not envs is None:
if len(envs) != n_nodes:
raise ValueError('Environment container not of same size as agent container')
envs_iter = envs
else:
envs_iter = [None] * n_nodes
if not node_names is None:
if len(node_names) != n_nodes:
raise ValueError('Node names container no of same size as agent container')
node_names_iter = node_names
else:
node_names_iter = ['ID {}'.format(k) for k in range(n_nodes)]
if not node_attributes is None:
if len(node_attributes) != n_nodes:
raise ValueError('Node attributes container not of same size as agent container')
node_attributes_iter = node_attributes
else:
node_attributes_iter = [{}] * n_nodes
ret = []
for agent, env, name, attributes in zip(agents, envs_iter, node_names_iter, node_attributes_iter):
ret.append(Node(name, agent, env, attributes))
return ret | """Basic object to store the agents and auxiliary content in the agent system
graph. The object should be considered to be replaced with namedtuple at some
point, once the default field has matured
"""
class Node(object):
"""Basic object to store agent and auxiliary content in the agent system.
Parameters
----------
name : str
Name of node
agent_content : Agent
An Agent object
aux_content : optional
Auxiliary content, such as an immediate environment, to the Agent of
the Node
other_attributes : dict, optional
Dictionary of additional attributes assigned to the Node. These can
be part of operations on the graph during a simulation or they can be
part of graph sampling, for example. Each key is the name of the
attribute, the value is the value of the attribute.
"""
def __str__(self):
return 'Node(name:%s)' % self.name
def __contains__(self, item):
if self.agent_content is None:
return False
else:
return item == self.agent_content.agent_id_system
def __init__(self, name, agent_content, aux_content=None, other_attributes={}):
self.name = name
self.agent_content = agent_content
self.aux_content = aux_content
for (key, item) in other_attributes:
setattr(self, key, item)
def node_maker(agents, envs=None, node_names=None, node_attributes=None):
"""Convenience function to place a collection of agents and environments in nodes
Parameters
----------
TBD
Returns
-------
TBD
"""
n_nodes = len(agents)
if not envs is None:
if len(envs) != n_nodes:
raise value_error('Environment container not of same size as agent container')
envs_iter = envs
else:
envs_iter = [None] * n_nodes
if not node_names is None:
if len(node_names) != n_nodes:
raise value_error('Node names container no of same size as agent container')
node_names_iter = node_names
else:
node_names_iter = ['ID {}'.format(k) for k in range(n_nodes)]
if not node_attributes is None:
if len(node_attributes) != n_nodes:
raise value_error('Node attributes container not of same size as agent container')
node_attributes_iter = node_attributes
else:
node_attributes_iter = [{}] * n_nodes
ret = []
for (agent, env, name, attributes) in zip(agents, envs_iter, node_names_iter, node_attributes_iter):
ret.append(node(name, agent, env, attributes))
return ret |
masuk=int(input("Masukkan Jam Masuk = "))
keluar=int(input("Masukkan Jam Keluar ="))
lama=keluar-masuk
payment=12000
print("Lama Mengajar = ", lama, "jam")
if lama <=1:
satu_jam_pertama=payment
print("Biaya Mengajar= Rp", satu_jam_pertama)
elif lama <10:
biaya_selanjutnya = (lama+1)*3000+payment
print("Biaya Mengajar = Rp", biaya_selanjutnya)
elif lama >= 10:
print("Biaya Mengajar = Rp", 1000000)
else:
print("nul")
| masuk = int(input('Masukkan Jam Masuk = '))
keluar = int(input('Masukkan Jam Keluar ='))
lama = keluar - masuk
payment = 12000
print('Lama Mengajar = ', lama, 'jam')
if lama <= 1:
satu_jam_pertama = payment
print('Biaya Mengajar= Rp', satu_jam_pertama)
elif lama < 10:
biaya_selanjutnya = (lama + 1) * 3000 + payment
print('Biaya Mengajar = Rp', biaya_selanjutnya)
elif lama >= 10:
print('Biaya Mengajar = Rp', 1000000)
else:
print('nul') |
# dataset settings
dataset_type = 'PhoneDataset'
data_root = '/home/ubuntu/tienpv/datasets/PhoneDatasets/COCO2017/'
ann_files = '/home/ubuntu/tienpv/datasets/PhoneDatasets/COCO2017/annotations/instances_train2017_cell_phone_format_widerface.txt'
val_data_root = '/home/ubuntu/tienpv/datasets/PhoneDatasets/COCO2017/'
val_ann_files = '/home/ubuntu/tienpv/datasets/PhoneDatasets/COCO2017/annotations/instances_val2017_cell_phone_format_widerface.txt'
img_norm_cfg = dict(mean=[123.675, 116.28, 103.53], std=[1, 1, 1], to_rgb=True)
train_pipeline = [
dict(type='LoadImageFromFile', to_float32=True),
dict(type='LoadAnnotations', with_bbox=True),
dict(
type='PhotoMetricDistortion',
brightness_delta=32,
contrast_range=(0.5, 1.5),
saturation_range=(0.5, 1.5),
hue_delta=18),
dict(
type='Expand',
mean=img_norm_cfg['mean'],
to_rgb=img_norm_cfg['to_rgb'],
ratio_range=(1, 4)),
dict(
type='MinIoURandomCrop',
min_ious=(0.1, 0.3, 0.5, 0.7, 0.9),
min_crop_size=0.3),
dict(type='Resize', img_scale=(320, 320), keep_ratio=False),
dict(type='Normalize', **img_norm_cfg),
dict(type='RandomFlip', flip_ratio=0.5),
dict(type='DefaultFormatBundle'),
dict(type='Collect', keys=['img', 'gt_bboxes', 'gt_labels']),
]
gray_train_pipeline = [
dict(type='LoadImageFromFile', to_float32=True, color_type='grayscale'),
dict(type='Stack'),
dict(type='LoadAnnotations', with_bbox=True),
dict(
type='PhotoMetricDistortion',
brightness_delta=32,
contrast_range=(0.5, 1.5),
saturation_range=(0.5, 1.5),
hue_delta=18),
dict(
type='Expand',
mean=img_norm_cfg['mean'],
to_rgb=img_norm_cfg['to_rgb'],
ratio_range=(1, 4)),
dict(
type='MinIoURandomCrop',
min_ious=(0.1, 0.3, 0.5, 0.7, 0.9),
min_crop_size=0.3),
dict(type='Resize', img_scale=(320, 320), keep_ratio=False),
dict(type='Normalize', **img_norm_cfg),
dict(type='RandomFlip', flip_ratio=0.5),
dict(type='DefaultFormatBundle'),
dict(type='Collect', keys=['img', 'gt_bboxes', 'gt_labels']),
]
test_pipeline = [
dict(type='LoadImageFromFile'),
dict(
type='MultiScaleFlipAug',
img_scale=(320, 320),
flip=False,
transforms=[
dict(type='Resize', keep_ratio=False),
dict(type='Normalize', **img_norm_cfg),
dict(type='ImageToTensor', keys=['img']),
dict(type='Collect', keys=['img']),
])
]
# rgb_dataset_train = dict(
# type='RepeatDataset',
# times=2,
# dataset=dict(
# type=dataset_type,
# ann_file=ann_files,
# img_prefix=data_root,
# pipeline=train_pipeline
# )
# )
# gray_dataset_train = dict(
# type='RepeatDataset',
# times=2,
# dataset=dict(
# type=dataset_type,
# ann_file=ann_files,
# img_prefix=data_root,
# pipeline=gray_train_pipeline
# )
# )
data = dict(
samples_per_gpu=60,
workers_per_gpu=4,
# train=[rgb_dataset_train, gray_dataset_train],
train=dict(
type='RepeatDataset',
times=2,
dataset=dict(
type=dataset_type,
ann_file=ann_files,
img_prefix=data_root,
pipeline=train_pipeline
)
),
val=dict(
type=dataset_type,
ann_file=val_ann_files,
img_prefix=val_data_root,
pipeline=test_pipeline),
test=dict(
type=dataset_type,
ann_file=val_ann_files,
img_prefix=val_data_root,
pipeline=test_pipeline))
| dataset_type = 'PhoneDataset'
data_root = '/home/ubuntu/tienpv/datasets/PhoneDatasets/COCO2017/'
ann_files = '/home/ubuntu/tienpv/datasets/PhoneDatasets/COCO2017/annotations/instances_train2017_cell_phone_format_widerface.txt'
val_data_root = '/home/ubuntu/tienpv/datasets/PhoneDatasets/COCO2017/'
val_ann_files = '/home/ubuntu/tienpv/datasets/PhoneDatasets/COCO2017/annotations/instances_val2017_cell_phone_format_widerface.txt'
img_norm_cfg = dict(mean=[123.675, 116.28, 103.53], std=[1, 1, 1], to_rgb=True)
train_pipeline = [dict(type='LoadImageFromFile', to_float32=True), dict(type='LoadAnnotations', with_bbox=True), dict(type='PhotoMetricDistortion', brightness_delta=32, contrast_range=(0.5, 1.5), saturation_range=(0.5, 1.5), hue_delta=18), dict(type='Expand', mean=img_norm_cfg['mean'], to_rgb=img_norm_cfg['to_rgb'], ratio_range=(1, 4)), dict(type='MinIoURandomCrop', min_ious=(0.1, 0.3, 0.5, 0.7, 0.9), min_crop_size=0.3), dict(type='Resize', img_scale=(320, 320), keep_ratio=False), dict(type='Normalize', **img_norm_cfg), dict(type='RandomFlip', flip_ratio=0.5), dict(type='DefaultFormatBundle'), dict(type='Collect', keys=['img', 'gt_bboxes', 'gt_labels'])]
gray_train_pipeline = [dict(type='LoadImageFromFile', to_float32=True, color_type='grayscale'), dict(type='Stack'), dict(type='LoadAnnotations', with_bbox=True), dict(type='PhotoMetricDistortion', brightness_delta=32, contrast_range=(0.5, 1.5), saturation_range=(0.5, 1.5), hue_delta=18), dict(type='Expand', mean=img_norm_cfg['mean'], to_rgb=img_norm_cfg['to_rgb'], ratio_range=(1, 4)), dict(type='MinIoURandomCrop', min_ious=(0.1, 0.3, 0.5, 0.7, 0.9), min_crop_size=0.3), dict(type='Resize', img_scale=(320, 320), keep_ratio=False), dict(type='Normalize', **img_norm_cfg), dict(type='RandomFlip', flip_ratio=0.5), dict(type='DefaultFormatBundle'), dict(type='Collect', keys=['img', 'gt_bboxes', 'gt_labels'])]
test_pipeline = [dict(type='LoadImageFromFile'), dict(type='MultiScaleFlipAug', img_scale=(320, 320), flip=False, transforms=[dict(type='Resize', keep_ratio=False), dict(type='Normalize', **img_norm_cfg), dict(type='ImageToTensor', keys=['img']), dict(type='Collect', keys=['img'])])]
data = dict(samples_per_gpu=60, workers_per_gpu=4, train=dict(type='RepeatDataset', times=2, dataset=dict(type=dataset_type, ann_file=ann_files, img_prefix=data_root, pipeline=train_pipeline)), val=dict(type=dataset_type, ann_file=val_ann_files, img_prefix=val_data_root, pipeline=test_pipeline), test=dict(type=dataset_type, ann_file=val_ann_files, img_prefix=val_data_root, pipeline=test_pipeline)) |
def longestPeak(array):
max_size = 0
i = 1
while i < len(array) - 1:
peak = array[i - 1] < array[i] > array[i + 1]
if not peak:
i += 1
continue
left = i - 1
right = i + 1
while left >= 0 and array[left] < array[left + 1]:
left -= 1
while right < len(array) and array[right] < array[right - 1]:
right += 1
max_size = max(max_size, right - left - 1)
i = right
return max_size
| def longest_peak(array):
max_size = 0
i = 1
while i < len(array) - 1:
peak = array[i - 1] < array[i] > array[i + 1]
if not peak:
i += 1
continue
left = i - 1
right = i + 1
while left >= 0 and array[left] < array[left + 1]:
left -= 1
while right < len(array) and array[right] < array[right - 1]:
right += 1
max_size = max(max_size, right - left - 1)
i = right
return max_size |
class Agent:
"""An abstract class defining the interface for a Reversi agent."""
def __init__(self, reversi, color):
raise NotImplementedError
def get_action(self, game_state, legal_moves=None):
raise NotImplementedError
def observe_win(self, state, winner):
raise NotImplementedError
def reset(self):
raise NotImplementedError
| class Agent:
"""An abstract class defining the interface for a Reversi agent."""
def __init__(self, reversi, color):
raise NotImplementedError
def get_action(self, game_state, legal_moves=None):
raise NotImplementedError
def observe_win(self, state, winner):
raise NotImplementedError
def reset(self):
raise NotImplementedError |
# ========================
# Information
# ========================
# Direct Link: https://www.hackerrank.com/challenges/s10-standard-deviation
# Difficulty: Easy
# Max Score: 30
# Language: Python
# ========================
# Solution
# ========================
N = int(input())
X = list(map(int, input().strip().split(' ')))
MEAN = sum(X)/N
sum = 0
for i in range(N):
sum += ((X[i]-MEAN)**2)/N
print(round(sum**0.5, 1))
| n = int(input())
x = list(map(int, input().strip().split(' ')))
mean = sum(X) / N
sum = 0
for i in range(N):
sum += (X[i] - MEAN) ** 2 / N
print(round(sum ** 0.5, 1)) |
class Entity(object):
def __init__(self, name, represented_class_name=None, parent_entity=None,
is_abstract=False, attributes=None, relationships=None):
self.name = name
self.represented_class_name = represented_class_name or name
self.parent_entity = parent_entity
self.is_abstract = is_abstract
self.attributes = attributes or []
self.relationships = relationships or []
def __str__(self):
return self.name
def __repr__(self):
return '<Entity {}>'.format(self.name)
def __eq__(self, other):
return isinstance(other, Entity) and \
other.name == self.name and \
other.represented_class_name == self.represented_class_name and \
other.parent_entity == self.parent_entity and \
other.is_abstract == self.is_abstract and \
other.attributes == self.attributes and \
other.relationships == self.relationships
@property
def super_class_name(self):
if self.parent_entity:
return self.parent_entity.represented_class_name
return 'NSManagedObject'
@property
def to_many_relationships(self):
return [relationship for relationship in self.relationships if relationship.is_to_many]
@property
def to_one_relationships(self):
return [relationship for relationship in self.relationships if relationship.is_to_one]
| class Entity(object):
def __init__(self, name, represented_class_name=None, parent_entity=None, is_abstract=False, attributes=None, relationships=None):
self.name = name
self.represented_class_name = represented_class_name or name
self.parent_entity = parent_entity
self.is_abstract = is_abstract
self.attributes = attributes or []
self.relationships = relationships or []
def __str__(self):
return self.name
def __repr__(self):
return '<Entity {}>'.format(self.name)
def __eq__(self, other):
return isinstance(other, Entity) and other.name == self.name and (other.represented_class_name == self.represented_class_name) and (other.parent_entity == self.parent_entity) and (other.is_abstract == self.is_abstract) and (other.attributes == self.attributes) and (other.relationships == self.relationships)
@property
def super_class_name(self):
if self.parent_entity:
return self.parent_entity.represented_class_name
return 'NSManagedObject'
@property
def to_many_relationships(self):
return [relationship for relationship in self.relationships if relationship.is_to_many]
@property
def to_one_relationships(self):
return [relationship for relationship in self.relationships if relationship.is_to_one] |
class Solution:
def answer(self, current, end, scalar):
if current == end:
return scalar
self.visited.add(current)
if current in self.graph:
for i in self.graph[current]:
if i[0] not in self.visited:
a = self.answer(i[0], end, scalar*i[1])
if a != -1:
return a
return -1
def calcEquation(self, equations: List[List[str]], values: List[float], queries: List[List[str]]) -> List[float]:
self.graph, self.visited = {}, set()
for i in range(len(equations)):
if equations[i][0] not in self.graph:
self.graph[equations[i][0]] = []
if equations[i][1] not in self.graph:
self.graph[equations[i][1]] = []
self.graph[equations[i][0]].append((equations[i][1], 1/values[i]))
self.graph[equations[i][1]].append((equations[i][0], values[i]))
v = []
for i in queries:
self.visited = set()
if i[0] not in self.graph or i[1] not in self.graph:
v.append(-1)
continue
v.append(1/self.answer(i[0], i[1], 1) if i[0] != i[1] else 1)
return v
| class Solution:
def answer(self, current, end, scalar):
if current == end:
return scalar
self.visited.add(current)
if current in self.graph:
for i in self.graph[current]:
if i[0] not in self.visited:
a = self.answer(i[0], end, scalar * i[1])
if a != -1:
return a
return -1
def calc_equation(self, equations: List[List[str]], values: List[float], queries: List[List[str]]) -> List[float]:
(self.graph, self.visited) = ({}, set())
for i in range(len(equations)):
if equations[i][0] not in self.graph:
self.graph[equations[i][0]] = []
if equations[i][1] not in self.graph:
self.graph[equations[i][1]] = []
self.graph[equations[i][0]].append((equations[i][1], 1 / values[i]))
self.graph[equations[i][1]].append((equations[i][0], values[i]))
v = []
for i in queries:
self.visited = set()
if i[0] not in self.graph or i[1] not in self.graph:
v.append(-1)
continue
v.append(1 / self.answer(i[0], i[1], 1) if i[0] != i[1] else 1)
return v |
# -*- coding: utf-8 -*-
"""Test strategy with hashing mutiple shift invariant aligned patches
See: https://stackoverflow.com/a/20316789/51627
"""
def main():
pass
if __name__ == "__main__":
main()
| """Test strategy with hashing mutiple shift invariant aligned patches
See: https://stackoverflow.com/a/20316789/51627
"""
def main():
pass
if __name__ == '__main__':
main() |
def isIsosceles(x, y, z):
if x <= 0 or y <=0 or z <=0:
return False
if x == y:
return True
if y == z:
return True
if x == z:
return True
else:
return False
print(isIsosceles(-2, -2, 3))
print(isIsosceles(2, 3, 2))
def isIsosceles(x, y, z):
if x <= 0 or y <=0 or z <=0:
return False
elif x == y or y == z or x == z:
return True
else:
return False
print(isIsosceles(-2, -2, 3))
print(isIsosceles(2, 3, 2))
| def is_isosceles(x, y, z):
if x <= 0 or y <= 0 or z <= 0:
return False
if x == y:
return True
if y == z:
return True
if x == z:
return True
else:
return False
print(is_isosceles(-2, -2, 3))
print(is_isosceles(2, 3, 2))
def is_isosceles(x, y, z):
if x <= 0 or y <= 0 or z <= 0:
return False
elif x == y or y == z or x == z:
return True
else:
return False
print(is_isosceles(-2, -2, 3))
print(is_isosceles(2, 3, 2)) |
# -*- coding: utf-8 -*-
__author__ = 'lycheng'
__email__ = "lycheng997@gmail.com"
class Solution(object):
def wordPattern(self, pattern, str):
"""
:type pattern: str
:type str: str
:rtype: bool
"""
words = str.split(" ")
if len(pattern) != len(words):
return False
word_map = {}
pattern_map = {}
for idx, word in enumerate(words):
p = pattern[idx]
if p not in pattern_map and word not in word_map:
pattern_map[p] = word
word_map[word] = p
continue
if pattern_map.get(p) != word or word_map.get(word) != p:
return False
return True
| __author__ = 'lycheng'
__email__ = 'lycheng997@gmail.com'
class Solution(object):
def word_pattern(self, pattern, str):
"""
:type pattern: str
:type str: str
:rtype: bool
"""
words = str.split(' ')
if len(pattern) != len(words):
return False
word_map = {}
pattern_map = {}
for (idx, word) in enumerate(words):
p = pattern[idx]
if p not in pattern_map and word not in word_map:
pattern_map[p] = word
word_map[word] = p
continue
if pattern_map.get(p) != word or word_map.get(word) != p:
return False
return True |
# Copyright 2017 The Chromium OS Authors. All rights reserved.
# Use of this source code is governed by a BSD-style license that can be
# found in the LICENSE file.
inline = """
<map>
<name>adc_mux</name>
<doc>valid mux values for DUT's two banks of INA219 off PCA9540
ADCs</doc>
<params clobber_ok="" none="0" bank0="4" bank1="5"></params>
</map>
<control>
<name>adc_mux</name>
<doc>4 to 1 mux to steer remote i2c i2c_mux:rem to two sets of
16 INA219 ADCs. Note they are only on leg0 and leg1</doc>
<params clobber_ok="" interface="2" drv="pca9546" child="0x70"
map="adc_mux"></params>
</control>
"""
inas = [
('ina219', 0x40, 'ppvar_bat', 3.8, 0.005, 'loc', True),
('ina219', 0x41, 'ppvar_bigcpu', 1.0, 0.01, 'loc', True),
('ina219', 0x42, 'ppvar_litcpu', 1.0, 0.01, 'loc', True),
('ina219', 0x43, 'ppvar_gpu', 1.0, 0.01, 'loc', True),
('ina219', 0x44, 'pp900_s0', 0.9, 0.01, 'loc', True),
('ina219', 0x45, 'pp1250_s3', 1.25, 0.01, 'loc', True),
('ina219', 0x46, 'pp1800', 1.8, 0.01, 'loc', True),
('ina219', 0x47, 'pp1800_ec', 1.8, 0.1, 'loc', True),
('ina219', 0x48, 'pp1800_s3', 1.8, 0.01, 'loc', True),
('ina219', 0x49, 'pp1800_lpddr', 1.8, 0.01, 'loc', True),
('ina219', 0x4A, 'pp1800_s0', 1.8, 0.01, 'loc', True),
('ina219', 0x4B, 'pp1800_pcie', 1.8, 0.01, 'loc', True),
('ina219', 0x4C, 'pp1800_mipi', 1.8, 0.01, 'loc', True),
('ina219', 0x4D, 'pp3300', 3.3, 0.01, 'loc', True),
('ina219', 0x4E, 'pp3300_s3', 3.3, 0.01, 'loc', True),
('ina219', 0x4F, 'pp3300_s0', 3.3, 0.01, 'loc', True),
]
| inline = '\n <map>\n <name>adc_mux</name>\n <doc>valid mux values for DUT\'s two banks of INA219 off PCA9540\n ADCs</doc>\n <params clobber_ok="" none="0" bank0="4" bank1="5"></params>\n </map>\n <control>\n <name>adc_mux</name>\n <doc>4 to 1 mux to steer remote i2c i2c_mux:rem to two sets of\n 16 INA219 ADCs. Note they are only on leg0 and leg1</doc>\n <params clobber_ok="" interface="2" drv="pca9546" child="0x70"\n map="adc_mux"></params>\n </control>\n'
inas = [('ina219', 64, 'ppvar_bat', 3.8, 0.005, 'loc', True), ('ina219', 65, 'ppvar_bigcpu', 1.0, 0.01, 'loc', True), ('ina219', 66, 'ppvar_litcpu', 1.0, 0.01, 'loc', True), ('ina219', 67, 'ppvar_gpu', 1.0, 0.01, 'loc', True), ('ina219', 68, 'pp900_s0', 0.9, 0.01, 'loc', True), ('ina219', 69, 'pp1250_s3', 1.25, 0.01, 'loc', True), ('ina219', 70, 'pp1800', 1.8, 0.01, 'loc', True), ('ina219', 71, 'pp1800_ec', 1.8, 0.1, 'loc', True), ('ina219', 72, 'pp1800_s3', 1.8, 0.01, 'loc', True), ('ina219', 73, 'pp1800_lpddr', 1.8, 0.01, 'loc', True), ('ina219', 74, 'pp1800_s0', 1.8, 0.01, 'loc', True), ('ina219', 75, 'pp1800_pcie', 1.8, 0.01, 'loc', True), ('ina219', 76, 'pp1800_mipi', 1.8, 0.01, 'loc', True), ('ina219', 77, 'pp3300', 3.3, 0.01, 'loc', True), ('ina219', 78, 'pp3300_s3', 3.3, 0.01, 'loc', True), ('ina219', 79, 'pp3300_s0', 3.3, 0.01, 'loc', True)] |
class CmdResponse:
__status: bool
__type: str
__data: dict
__content: str
def __init__(self, status: bool, contentType: str):
self.__status = status
self.__type = contentType
self.__data = {'status': status}
self.__content = None
def setData(self, data: object):
self.__data['data'] = data
def setContent(self, content: str):
self.__content = content
def getContent(self) -> str:
return self.__content
def getData(self) -> dict:
return self.__data
def getContentType(self) -> str:
return self.__type
def getStatus(self) -> bool:
return self.__status
| class Cmdresponse:
__status: bool
__type: str
__data: dict
__content: str
def __init__(self, status: bool, contentType: str):
self.__status = status
self.__type = contentType
self.__data = {'status': status}
self.__content = None
def set_data(self, data: object):
self.__data['data'] = data
def set_content(self, content: str):
self.__content = content
def get_content(self) -> str:
return self.__content
def get_data(self) -> dict:
return self.__data
def get_content_type(self) -> str:
return self.__type
def get_status(self) -> bool:
return self.__status |
with open("pytest_results.xml", "w") as f:
f.write("<?xml version='1.0' encoding='utf-8'?>")
f.write("<test>")
f.write("<!-- No tests executed -->")
f.write("</test>")
| with open('pytest_results.xml', 'w') as f:
f.write("<?xml version='1.0' encoding='utf-8'?>")
f.write('<test>')
f.write('<!-- No tests executed -->')
f.write('</test>') |
def exec(path: str, data: bytes) -> None:
fs = open(path, 'wb')
fs.write(data)
fs.close()
| def exec(path: str, data: bytes) -> None:
fs = open(path, 'wb')
fs.write(data)
fs.close() |
class TernarySearchTrie:
"""Implements https://en.wikipedia.org/wiki/Ternary_search_tree"""
def __init__(self):
self.root = None
def get(self, s: str) -> bool:
"""Return True if string s is in trie, else False"""
return self._get(s, 0, self.root)
def put(self, s: str, label):
"""Upsert string s into trie"""
self.root = self._put(s, 0, label, self.root)
def delete(self, s: str):
"""Delete string s from trie"""
self.root = self._delete(s, 0, self.root)
def _get(self, s: str, i: int, node):
"""Recursively traverse trie to find string s"""
c = s[i]
if node is None:
print(f'String {s} is not in trie')
return False
if c < node.c:
return self._get(s, i, node.left)
elif c > node.c:
return self._get(s, i, node.right)
elif i < len(s) - 1:
return self._get(s, i + 1, node.down)
else:
if node.label:
print(f'String {s} is in trie with label {node.label}')
return True
print(f'String {s} is not in trie')
return False
def _put(self, s: str, i: int, label, node):
"""Recursively upsert string s with label into trie"""
c = s[i]
if node is None:
node = _TernarySearchTrieNode(c)
if c < node.c:
node.left = self._put(s, i, label, node.left)
elif c > node.c:
node.right = self._put(s, i, label, node.right)
elif i < len(s) - 1:
node.down = self._put(s, i + 1, label, node.down)
else:
node.label = label
return node
def _delete(self, s: str, i: int, node):
"""Recursively delete string s from trie, including cleaning up trie"""
c = s[i]
if node is None:
print(f'String {s} is not in trie')
return None
if c < node.c:
node.left = self._delete(s, i, node.left)
elif c > node.c:
node.right = self._delete(s, i, node.right)
elif i < len(s) - 1:
node.down = self._delete(s, i + 1, node.down)
else:
node.label = None
return (None
if not node.left and not node.down and not node.right
else node)
class _TernarySearchTrieNode:
"""Implements a TST node, storing a char, a label and three pointers"""
def __init__(self, c: str, label=None):
self.c = c
self.label = label
self.left = self.down = self.right = None
if __name__ == '__main__':
T = TernarySearchTrie()
print(T)
TEST_STRINGS = ['appleE', "donkey'][]", 'donner',
'garfield123', 'garfunkel']
for i, s in enumerate(TEST_STRINGS):
T.put(s, i + 1)
for s in TEST_STRINGS:
assert T.get(s) is True
T.delete('garfield123')
assert T.get('garfield123') is False
assert T.get('garfunkel') is True
assert T.get('a') is False
print(T)
| class Ternarysearchtrie:
"""Implements https://en.wikipedia.org/wiki/Ternary_search_tree"""
def __init__(self):
self.root = None
def get(self, s: str) -> bool:
"""Return True if string s is in trie, else False"""
return self._get(s, 0, self.root)
def put(self, s: str, label):
"""Upsert string s into trie"""
self.root = self._put(s, 0, label, self.root)
def delete(self, s: str):
"""Delete string s from trie"""
self.root = self._delete(s, 0, self.root)
def _get(self, s: str, i: int, node):
"""Recursively traverse trie to find string s"""
c = s[i]
if node is None:
print(f'String {s} is not in trie')
return False
if c < node.c:
return self._get(s, i, node.left)
elif c > node.c:
return self._get(s, i, node.right)
elif i < len(s) - 1:
return self._get(s, i + 1, node.down)
else:
if node.label:
print(f'String {s} is in trie with label {node.label}')
return True
print(f'String {s} is not in trie')
return False
def _put(self, s: str, i: int, label, node):
"""Recursively upsert string s with label into trie"""
c = s[i]
if node is None:
node = __ternary_search_trie_node(c)
if c < node.c:
node.left = self._put(s, i, label, node.left)
elif c > node.c:
node.right = self._put(s, i, label, node.right)
elif i < len(s) - 1:
node.down = self._put(s, i + 1, label, node.down)
else:
node.label = label
return node
def _delete(self, s: str, i: int, node):
"""Recursively delete string s from trie, including cleaning up trie"""
c = s[i]
if node is None:
print(f'String {s} is not in trie')
return None
if c < node.c:
node.left = self._delete(s, i, node.left)
elif c > node.c:
node.right = self._delete(s, i, node.right)
elif i < len(s) - 1:
node.down = self._delete(s, i + 1, node.down)
else:
node.label = None
return None if not node.left and (not node.down) and (not node.right) else node
class _Ternarysearchtrienode:
"""Implements a TST node, storing a char, a label and three pointers"""
def __init__(self, c: str, label=None):
self.c = c
self.label = label
self.left = self.down = self.right = None
if __name__ == '__main__':
t = ternary_search_trie()
print(T)
test_strings = ['appleE', "donkey'][]", 'donner', 'garfield123', 'garfunkel']
for (i, s) in enumerate(TEST_STRINGS):
T.put(s, i + 1)
for s in TEST_STRINGS:
assert T.get(s) is True
T.delete('garfield123')
assert T.get('garfield123') is False
assert T.get('garfunkel') is True
assert T.get('a') is False
print(T) |
# model
batch = 1
in_chans = 1
out_chans = 1
in_rows = 4
in_cols = 4
out_rows = 8
out_cols = 8
ker_rows = 3
ker_cols = 3
stride = 2
# pad is 0 (left: 0 right: 1 top: 0 bottom: 1)
input_table = [x for x in range(batch * in_rows * in_cols * in_chans)]
kernel_table = [x for x in range(out_chans * ker_rows * ker_cols * in_chans)]
out_table = [0 for x in range(batch * out_rows * out_cols * out_chans)]
for i in range(batch):
for j in range(in_rows):
for k in range(in_cols):
for l in range(in_chans):
out_row_origin = j * stride
out_col_origin = k * stride
input_value = input_table[((i * in_rows + j) * in_cols + k) * in_chans + l]
for m in range(ker_rows):
for n in range(ker_cols):
for o in range(out_chans):
out_row = out_row_origin + m
out_col = out_col_origin + n
if (out_row < out_rows) and (out_col < out_cols) and (out_row >= 0) and (out_col >= 0):
kernel_value = kernel_table[((o * ker_rows + m) * ker_cols + n) * in_chans + l]
out_table[((i * out_rows + out_row) * out_cols + out_col) * out_chans + o] += (input_value * kernel_value)
model = Model()
i0 = Input("op_shape", "TENSOR_INT32", "{4}")
weights = Parameter("ker", "TENSOR_FLOAT32", "{1, 3, 3, 1}", kernel_table)
i1 = Input("in", "TENSOR_FLOAT32", "{1, 4, 4, 1}" )
pad = Int32Scalar("pad_same", 1)
s_x = Int32Scalar("stride_x", 2)
s_y = Int32Scalar("stride_y", 2)
i2 = Output("op", "TENSOR_FLOAT32", "{1, 8, 8, 1}")
model = model.Operation("TRANSPOSE_CONV_EX", i0, weights, i1, pad, s_x, s_y).To(i2)
# Example 1. Input in operand 0,
input0 = {i0: # output shape
[1, 8, 8, 1],
i1: # input 0
input_table}
output0 = {i2: # output 0
out_table}
# Instantiate an example
Example((input0, output0))
| batch = 1
in_chans = 1
out_chans = 1
in_rows = 4
in_cols = 4
out_rows = 8
out_cols = 8
ker_rows = 3
ker_cols = 3
stride = 2
input_table = [x for x in range(batch * in_rows * in_cols * in_chans)]
kernel_table = [x for x in range(out_chans * ker_rows * ker_cols * in_chans)]
out_table = [0 for x in range(batch * out_rows * out_cols * out_chans)]
for i in range(batch):
for j in range(in_rows):
for k in range(in_cols):
for l in range(in_chans):
out_row_origin = j * stride
out_col_origin = k * stride
input_value = input_table[((i * in_rows + j) * in_cols + k) * in_chans + l]
for m in range(ker_rows):
for n in range(ker_cols):
for o in range(out_chans):
out_row = out_row_origin + m
out_col = out_col_origin + n
if out_row < out_rows and out_col < out_cols and (out_row >= 0) and (out_col >= 0):
kernel_value = kernel_table[((o * ker_rows + m) * ker_cols + n) * in_chans + l]
out_table[((i * out_rows + out_row) * out_cols + out_col) * out_chans + o] += input_value * kernel_value
model = model()
i0 = input('op_shape', 'TENSOR_INT32', '{4}')
weights = parameter('ker', 'TENSOR_FLOAT32', '{1, 3, 3, 1}', kernel_table)
i1 = input('in', 'TENSOR_FLOAT32', '{1, 4, 4, 1}')
pad = int32_scalar('pad_same', 1)
s_x = int32_scalar('stride_x', 2)
s_y = int32_scalar('stride_y', 2)
i2 = output('op', 'TENSOR_FLOAT32', '{1, 8, 8, 1}')
model = model.Operation('TRANSPOSE_CONV_EX', i0, weights, i1, pad, s_x, s_y).To(i2)
input0 = {i0: [1, 8, 8, 1], i1: input_table}
output0 = {i2: out_table}
example((input0, output0)) |
def main():
# input
css = [[*map(int, input().split())] for _ in range(3)]
# compute
for i in range(3):
if css[i-1][i-1]+css[i][i] != css[i-1][i]+css[i][i-1]:
print('No')
exit()
# output
print('Yes')
if __name__ == '__main__':
main()
| def main():
css = [[*map(int, input().split())] for _ in range(3)]
for i in range(3):
if css[i - 1][i - 1] + css[i][i] != css[i - 1][i] + css[i][i - 1]:
print('No')
exit()
print('Yes')
if __name__ == '__main__':
main() |
'''
This is a math Module
Do Some thing
'''
def add(a=0, b=0):
return a + b;
def minus(a=0, b=0):
return a - b;
def multy(a=1, b=1):
return a * b;
| """
This is a math Module
Do Some thing
"""
def add(a=0, b=0):
return a + b
def minus(a=0, b=0):
return a - b
def multy(a=1, b=1):
return a * b |
# Time: O(n)
# Space: O(1)
class Solution(object):
def maxDepthAfterSplit(self, seq):
"""
:type seq: str
:rtype: List[int]
"""
return [(i & 1) ^ (seq[i] == '(') for i, c in enumerate(seq)]
# Time: O(n)
# Space: O(1)
class Solution2(object):
def maxDepthAfterSplit(self, seq):
"""
:type seq: str
:rtype: List[int]
"""
A, B = 0, 0
result = [0]*len(seq)
for i, c in enumerate(seq):
point = 1 if c == '(' else -1
if (point == 1 and A <= B) or \
(point == -1 and A >= B):
A += point
else:
B += point
result[i] = 1
return result
| class Solution(object):
def max_depth_after_split(self, seq):
"""
:type seq: str
:rtype: List[int]
"""
return [i & 1 ^ (seq[i] == '(') for (i, c) in enumerate(seq)]
class Solution2(object):
def max_depth_after_split(self, seq):
"""
:type seq: str
:rtype: List[int]
"""
(a, b) = (0, 0)
result = [0] * len(seq)
for (i, c) in enumerate(seq):
point = 1 if c == '(' else -1
if point == 1 and A <= B or (point == -1 and A >= B):
a += point
else:
b += point
result[i] = 1
return result |
class MyClass:
data = 3
a = MyClass()
b = MyClass()
a.data = 5
print(a.data)
print(b.data)
| class Myclass:
data = 3
a = my_class()
b = my_class()
a.data = 5
print(a.data)
print(b.data) |
class Solution:
def findLHS(self, nums) -> int:
nums.sort()
pre_num, pre_length = -1, 0
cur_num, cur_length = -1, 0
i = 0
max_length = 0
while i < len(nums):
if nums[i] == cur_num:
cur_length += 1
else:
if cur_num == pre_num + 1:
max_length = max(max_length, cur_length + pre_length)
pre_num = cur_num
pre_length = cur_length
cur_num = nums[i]
cur_length = 1
i += 1
if cur_num == pre_num + 1:
max_length = max(max_length, cur_length + pre_length)
return max_length
slu = Solution()
print(slu.findLHS([1, 1, 1, 1, 2]))
| class Solution:
def find_lhs(self, nums) -> int:
nums.sort()
(pre_num, pre_length) = (-1, 0)
(cur_num, cur_length) = (-1, 0)
i = 0
max_length = 0
while i < len(nums):
if nums[i] == cur_num:
cur_length += 1
else:
if cur_num == pre_num + 1:
max_length = max(max_length, cur_length + pre_length)
pre_num = cur_num
pre_length = cur_length
cur_num = nums[i]
cur_length = 1
i += 1
if cur_num == pre_num + 1:
max_length = max(max_length, cur_length + pre_length)
return max_length
slu = solution()
print(slu.findLHS([1, 1, 1, 1, 2])) |
def validate_count(d):
print(len([0 for e in d if((c:=e[2].count(e[1]))>e[0][0])and(c<e[0][1])]))
def validate_position(d):
print(len([0 for e in d if(e[2][e[0][0]-1]==e[1])^(e[2][e[0][1]-1]==e[1])]))
if __name__ == "__main__":
with open('2020/input/day02.txt') as f:
database = [[[*map(int, (e := entry.split(' '))[0].split('-'))], e[1][0], e[2].replace('\n', '')] for entry in f.readlines()]
validate_count(database) # 410
validate_position(database) # 694 | def validate_count(d):
print(len([0 for e in d if (c := e[2].count(e[1])) > e[0][0] and c < e[0][1]]))
def validate_position(d):
print(len([0 for e in d if (e[2][e[0][0] - 1] == e[1]) ^ (e[2][e[0][1] - 1] == e[1])]))
if __name__ == '__main__':
with open('2020/input/day02.txt') as f:
database = [[[*map(int, (e := entry.split(' '))[0].split('-'))], e[1][0], e[2].replace('\n', '')] for entry in f.readlines()]
validate_count(database)
validate_position(database) |
# Copyright 2017 Brocade Communications Systems, Inc. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may also 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.
class pyfos_type():
type_na = 0
type_int = 1
type_wwn = 2
type_str = 3
type_bool = 4
type_ip_addr = 5
type_ipv6_addr = 6
type_zoning_name = 7
type_domain_port = 8
def __init__(self, pyfos_type):
self.pyfos_type = pyfos_type
def get_type(self):
return self.pyfos_type
def vaildate_set(self, value):
return True
def __validate_peek_help(self, cur_type, value):
if value is None:
return True, None
elif cur_type == pyfos_type.type_int:
cur_value = int(value)
if isinstance(cur_value, int):
return True, cur_value
elif cur_type == pyfos_type.type_wwn:
cur_value = str(value)
if isinstance(cur_value, str):
return True, cur_value
elif cur_type == pyfos_type.type_wwn:
cur_value = str(value)
if isinstance(cur_value, str):
return True, cur_value
elif cur_type == pyfos_type.type_str:
cur_value = str(value)
if isinstance(cur_value, str):
return True, cur_value
elif cur_type == pyfos_type.type_bool:
cur_value = bool(value)
if isinstance(cur_value, bool):
return True, cur_value
elif cur_type == pyfos_type.type_ip_addr:
cur_value = str(value)
if isinstance(cur_value, str):
return True, cur_value
elif cur_type == pyfos_type.type_zoning_name:
cur_value = str(value)
if isinstance(cur_value, str):
return True, cur_value
elif cur_type == pyfos_type.type_domain_port:
cur_value = str(value)
if isinstance(cur_value, str):
return True, cur_value
if cur_type == pyfos_type.type_na:
return True, value
else:
return False, None
def validate_peek(self, value):
if isinstance(value, list):
# if the list is empty, just return
if not list:
return True, value
# otherwise, walk through element
# and see if they are of the type
# expected
ret_list = []
for cur_value in value:
correct_type, cast_value = self.__validate_peek_help(
self.pyfos_type, cur_value)
if correct_type is True:
ret_list.append(cast_value)
else:
print("invalid type", value, cur_value, self.pyfos_type)
return True, ret_list
else:
return self.__validate_peek_help(self.pyfos_type, value)
| class Pyfos_Type:
type_na = 0
type_int = 1
type_wwn = 2
type_str = 3
type_bool = 4
type_ip_addr = 5
type_ipv6_addr = 6
type_zoning_name = 7
type_domain_port = 8
def __init__(self, pyfos_type):
self.pyfos_type = pyfos_type
def get_type(self):
return self.pyfos_type
def vaildate_set(self, value):
return True
def __validate_peek_help(self, cur_type, value):
if value is None:
return (True, None)
elif cur_type == pyfos_type.type_int:
cur_value = int(value)
if isinstance(cur_value, int):
return (True, cur_value)
elif cur_type == pyfos_type.type_wwn:
cur_value = str(value)
if isinstance(cur_value, str):
return (True, cur_value)
elif cur_type == pyfos_type.type_wwn:
cur_value = str(value)
if isinstance(cur_value, str):
return (True, cur_value)
elif cur_type == pyfos_type.type_str:
cur_value = str(value)
if isinstance(cur_value, str):
return (True, cur_value)
elif cur_type == pyfos_type.type_bool:
cur_value = bool(value)
if isinstance(cur_value, bool):
return (True, cur_value)
elif cur_type == pyfos_type.type_ip_addr:
cur_value = str(value)
if isinstance(cur_value, str):
return (True, cur_value)
elif cur_type == pyfos_type.type_zoning_name:
cur_value = str(value)
if isinstance(cur_value, str):
return (True, cur_value)
elif cur_type == pyfos_type.type_domain_port:
cur_value = str(value)
if isinstance(cur_value, str):
return (True, cur_value)
if cur_type == pyfos_type.type_na:
return (True, value)
else:
return (False, None)
def validate_peek(self, value):
if isinstance(value, list):
if not list:
return (True, value)
ret_list = []
for cur_value in value:
(correct_type, cast_value) = self.__validate_peek_help(self.pyfos_type, cur_value)
if correct_type is True:
ret_list.append(cast_value)
else:
print('invalid type', value, cur_value, self.pyfos_type)
return (True, ret_list)
else:
return self.__validate_peek_help(self.pyfos_type, value) |
{
"includes": [
"../common.gypi"
],
"targets": [
{
"configurations": {
"Release": {
"defines": [
"NDEBUG"
]
}
},
"include_dirs": [
"apr-iconv/include"
],
"sources": [
"dependencies/apr-iconv/lib/iconv.c",
"dependencies/apr-iconv/lib/iconv_ces.c",
"dependencies/apr-iconv/lib/iconv_ces_euc.c",
"dependencies/apr-iconv/lib/iconv_ces_iso2022.c",
"dependencies/apr-iconv/lib/iconv_int.c",
"dependencies/apr-iconv/lib/iconv_module.c",
"dependencies/apr-iconv/lib/iconv_uc.c"
],
"target_name": "apr-iconv",
}
]
}
| {'includes': ['../common.gypi'], 'targets': [{'configurations': {'Release': {'defines': ['NDEBUG']}}, 'include_dirs': ['apr-iconv/include'], 'sources': ['dependencies/apr-iconv/lib/iconv.c', 'dependencies/apr-iconv/lib/iconv_ces.c', 'dependencies/apr-iconv/lib/iconv_ces_euc.c', 'dependencies/apr-iconv/lib/iconv_ces_iso2022.c', 'dependencies/apr-iconv/lib/iconv_int.c', 'dependencies/apr-iconv/lib/iconv_module.c', 'dependencies/apr-iconv/lib/iconv_uc.c'], 'target_name': 'apr-iconv'}]} |
def flatten_forest(forest):
flat_forest = []
for row in forest:
flat_forest += row
return flat_forest
def deflatten_forest(forest_1d, rows):
cols = len(forest_1d) // rows
forest_2d = []
for i in range(cols):
forest_slice = forest_1d[i*cols: (i+1)*cols]
forest_2d.append(forest_slice)
return forest_2d
| def flatten_forest(forest):
flat_forest = []
for row in forest:
flat_forest += row
return flat_forest
def deflatten_forest(forest_1d, rows):
cols = len(forest_1d) // rows
forest_2d = []
for i in range(cols):
forest_slice = forest_1d[i * cols:(i + 1) * cols]
forest_2d.append(forest_slice)
return forest_2d |
#!/usr/bin/python
# -*- encoding: utf-8; py-indent-offset: 4 -*-
# +------------------------------------------------------------------+
# | ____ _ _ __ __ _ __ |
# | / ___| |__ ___ ___| | __ | \/ | |/ / |
# | | | | '_ \ / _ \/ __| |/ / | |\/| | ' / |
# | | |___| | | | __/ (__| < | | | | . \ |
# | \____|_| |_|\___|\___|_|\_\___|_| |_|_|\_\ |
# | |
# | Copyright Mathias Kettner 2014 mk@mathias-kettner.de |
# +------------------------------------------------------------------+
#
# This file is part of Check_MK.
# The official homepage is at http://mathias-kettner.de/check_mk.
#
# check_mk is free software; you can redistribute it and/or modify it
# under the terms of the GNU General Public License as published by
# the Free Software Foundation in version 2. check_mk is distributed
# in the hope that it will be useful, but WITHOUT ANY WARRANTY; with-
# out even the implied warranty of MERCHANTABILITY or FITNESS FOR A
# PARTICULAR PURPOSE. See the GNU General Public License for more de-
# tails. You should have received a copy of the GNU General Public
# License along with GNU Make; see the file COPYING. If not, write
# to the Free Software Foundation, Inc., 51 Franklin St, Fifth Floor,
# Boston, MA 02110-1301 USA.
# Temporary variable which stores settings during the backup process
backup_perfdata_enabled = True
def performancedata_restore(pre_restore = True):
global backup_perfdata_enabled
site = config.default_site()
html.live.set_only_sites([site])
if pre_restore:
data = html.live.query("GET status\nColumns: process_performance_data")
if data:
backup_perfdata_enabled = data[0][0] == 1
else:
backup_perfdata_enabled = None # Core is offline
# Return if perfdata is not activated - nothing to do..
if not backup_perfdata_enabled: # False or None
return []
command = pre_restore and "DISABLE_PERFORMANCE_DATA" or "ENABLE_PERFORMANCE_DATA"
html.live.command("[%d] %s" % (int(time.time()), command), site)
html.live.set_only_sites()
return []
if not defaults.omd_root:
backup_domains.update( {
"noomd-config": {
"group" : _("Configuration"),
"title" : _("WATO Configuration"),
"prefix" : defaults.default_config_dir,
"paths" : [
("dir", "conf.d/wato"),
("dir", "multisite.d/wato"),
("file", "multisite.d/sites.mk")
],
"default" : True,
},
"noomd-personalsettings": {
"title" : _("Personal User Settings and Custom Views"),
"prefix" : defaults.var_dir,
"paths" : [ ("dir", "web") ],
"default" : True
},
"noomd-authorization": {
"group" : _("Configuration"),
"title" : _("Local Authentication Data"),
"prefix" : os.path.dirname(defaults.htpasswd_file),
"paths" : [
("file", "htpasswd"),
("file", "auth.secret"),
("file", "auth.serials")
],
"cleanup" : False,
"default" : True
}})
else:
backup_domains.update({
"check_mk": {
"group" : _("Configuration"),
"title" : _("Hosts, Services, Groups, Timeperiods, Business Intelligence and Monitoring Configuration"),
"prefix" : defaults.default_config_dir,
"paths" : [
("file", "liveproxyd.mk"),
("file", "main.mk"),
("file", "final.mk"),
("file", "local.mk"),
("file", "mkeventd.mk"),
("dir", "conf.d"),
("dir", "multisite.d"),
("dir", "mkeventd.d"),
("dir", "mknotifyd.d"),
],
"default" : True,
},
"authorization": {
# This domain is obsolete
# It no longer shows up in the backup screen
"deprecated" : True,
"group" : _("Configuration"),
"title" : _("Local Authentication Data"),
"prefix" : os.path.dirname(defaults.htpasswd_file),
"paths" : [
("file", "htpasswd"),
("file", "auth.secret"),
("file", "auth.serials")
],
"cleanup" : False,
"default" : True,
},
"authorization_v1": {
"group" : _("Configuration"),
"title" : _("Local Authentication Data"),
"prefix" : defaults.omd_root,
"paths" : [
("file", "etc/htpasswd"),
("file", "etc/auth.secret"),
("file", "etc/auth.serials"),
("file", "var/check_mk/web/*/serial.mk")
],
"cleanup" : False,
"default" : True
},
"personalsettings": {
"title" : _("Personal User Settings and Custom Views"),
"prefix" : defaults.var_dir,
"paths" : [ ("dir", "web") ],
"exclude" : [ "*/serial.mk" ],
"cleanup" : False,
},
"autochecks": {
"group" : _("Configuration"),
"title" : _("Automatically Detected Services"),
"prefix" : defaults.autochecksdir,
"paths" : [ ("dir", "") ],
},
"snmpwalks": {
"title" : _("Stored SNMP Walks"),
"prefix" : defaults.snmpwalks_dir,
"paths" : [ ("dir", "") ],
},
"logwatch": {
"group" : _("Historic Data"),
"title" : _("Logwatch Data"),
"prefix" : defaults.var_dir,
"paths" : [
("dir", "logwatch"),
],
},
"mkeventstatus": {
"group" : _("Configuration"),
"title" : _("Event Console Configuration"),
"prefix" : defaults.omd_root,
"paths" : [
("dir", "etc/check_mk/mkeventd.d"),
],
"default" : True
},
"mkeventhistory": {
"group" : _("Historic Data"),
"title" : _("Event Console Archive and Current State"),
"prefix" : defaults.omd_root,
"paths" : [
("dir", "var/mkeventd/history"),
("file", "var/mkeventd/status"),
("file", "var/mkeventd/messages"),
("dir", "var/mkeventd/messages-history"),
],
},
"corehistory": {
"group" : _("Historic Data"),
"title" : _("Monitoring History"),
"prefix" : defaults.omd_root,
"paths" : [
("dir", "var/nagios/archive"),
("file", "var/nagios/nagios.log"),
("dir", "var/icinga/archive"),
("file", "var/icinga/icinga.log"),
("dir", "var/check_mk/core/archive"),
("file", "var/check_mk/core/history"),
],
},
"performancedata": {
"group" : _("Historic Data"),
"title" : _("Performance Data"),
"prefix" : defaults.omd_root,
"paths" : [
("dir", "var/pnp4nagios/perfdata"),
("dir", "var/rrdcached"),
("dir", "var/check_mk/rrd"),
],
"pre_restore" : lambda: performancedata_restore(pre_restore = True),
"post_restore" : lambda: performancedata_restore(pre_restore = False),
"checksum" : False,
},
"applicationlogs": {
"group" : _("Historic Data"),
"title" : _("Application Logs"),
"prefix" : defaults.omd_root,
"paths" : [
("dir", "var/log"),
("file", "var/nagios/livestatus.log"),
("dir", "var/pnp4nagios/log"),
],
"checksum" : False,
},
"snmpmibs": {
"group" : _("Configuration"),
"title" : _("SNMP MIBs"),
"prefix" : defaults.omd_root,
"paths" : [
("dir", "local/share/check_mk/mibs"),
],
},
"extensions" : {
"title" : _("Extensions in <tt>~/local/</tt> and MKPs"),
"prefix" : defaults.omd_root,
"paths" : [
("dir", "var/check_mk/packages" ),
("dir", "local" ),
],
"default" : True,
},
"dokuwiki": {
"title" : _("Doku Wiki Pages and Settings"),
"prefix" : defaults.omd_root,
"paths" : [
("dir", "var/dokuwiki"),
],
},
"nagvis": {
"title" : _("NagVis Maps, Configurations and User Files"),
"prefix" : defaults.omd_root,
"exclude" : [
"etc/nagvis/apache.conf",
"etc/nagvis/conf.d/authorisation.ini.php",
"etc/nagvis/conf.d/omd.ini.php",
"etc/nagvis/conf.d/cookie_auth.ini.php",
"etc/nagvis/conf.d/urls.ini.php"
],
"paths" : [
("dir", "local/share/nagvis"),
("dir", "etc/nagvis"),
("dir", "var/nagvis"),
],
},
})
| backup_perfdata_enabled = True
def performancedata_restore(pre_restore=True):
global backup_perfdata_enabled
site = config.default_site()
html.live.set_only_sites([site])
if pre_restore:
data = html.live.query('GET status\nColumns: process_performance_data')
if data:
backup_perfdata_enabled = data[0][0] == 1
else:
backup_perfdata_enabled = None
if not backup_perfdata_enabled:
return []
command = pre_restore and 'DISABLE_PERFORMANCE_DATA' or 'ENABLE_PERFORMANCE_DATA'
html.live.command('[%d] %s' % (int(time.time()), command), site)
html.live.set_only_sites()
return []
if not defaults.omd_root:
backup_domains.update({'noomd-config': {'group': _('Configuration'), 'title': _('WATO Configuration'), 'prefix': defaults.default_config_dir, 'paths': [('dir', 'conf.d/wato'), ('dir', 'multisite.d/wato'), ('file', 'multisite.d/sites.mk')], 'default': True}, 'noomd-personalsettings': {'title': _('Personal User Settings and Custom Views'), 'prefix': defaults.var_dir, 'paths': [('dir', 'web')], 'default': True}, 'noomd-authorization': {'group': _('Configuration'), 'title': _('Local Authentication Data'), 'prefix': os.path.dirname(defaults.htpasswd_file), 'paths': [('file', 'htpasswd'), ('file', 'auth.secret'), ('file', 'auth.serials')], 'cleanup': False, 'default': True}})
else:
backup_domains.update({'check_mk': {'group': _('Configuration'), 'title': _('Hosts, Services, Groups, Timeperiods, Business Intelligence and Monitoring Configuration'), 'prefix': defaults.default_config_dir, 'paths': [('file', 'liveproxyd.mk'), ('file', 'main.mk'), ('file', 'final.mk'), ('file', 'local.mk'), ('file', 'mkeventd.mk'), ('dir', 'conf.d'), ('dir', 'multisite.d'), ('dir', 'mkeventd.d'), ('dir', 'mknotifyd.d')], 'default': True}, 'authorization': {'deprecated': True, 'group': _('Configuration'), 'title': _('Local Authentication Data'), 'prefix': os.path.dirname(defaults.htpasswd_file), 'paths': [('file', 'htpasswd'), ('file', 'auth.secret'), ('file', 'auth.serials')], 'cleanup': False, 'default': True}, 'authorization_v1': {'group': _('Configuration'), 'title': _('Local Authentication Data'), 'prefix': defaults.omd_root, 'paths': [('file', 'etc/htpasswd'), ('file', 'etc/auth.secret'), ('file', 'etc/auth.serials'), ('file', 'var/check_mk/web/*/serial.mk')], 'cleanup': False, 'default': True}, 'personalsettings': {'title': _('Personal User Settings and Custom Views'), 'prefix': defaults.var_dir, 'paths': [('dir', 'web')], 'exclude': ['*/serial.mk'], 'cleanup': False}, 'autochecks': {'group': _('Configuration'), 'title': _('Automatically Detected Services'), 'prefix': defaults.autochecksdir, 'paths': [('dir', '')]}, 'snmpwalks': {'title': _('Stored SNMP Walks'), 'prefix': defaults.snmpwalks_dir, 'paths': [('dir', '')]}, 'logwatch': {'group': _('Historic Data'), 'title': _('Logwatch Data'), 'prefix': defaults.var_dir, 'paths': [('dir', 'logwatch')]}, 'mkeventstatus': {'group': _('Configuration'), 'title': _('Event Console Configuration'), 'prefix': defaults.omd_root, 'paths': [('dir', 'etc/check_mk/mkeventd.d')], 'default': True}, 'mkeventhistory': {'group': _('Historic Data'), 'title': _('Event Console Archive and Current State'), 'prefix': defaults.omd_root, 'paths': [('dir', 'var/mkeventd/history'), ('file', 'var/mkeventd/status'), ('file', 'var/mkeventd/messages'), ('dir', 'var/mkeventd/messages-history')]}, 'corehistory': {'group': _('Historic Data'), 'title': _('Monitoring History'), 'prefix': defaults.omd_root, 'paths': [('dir', 'var/nagios/archive'), ('file', 'var/nagios/nagios.log'), ('dir', 'var/icinga/archive'), ('file', 'var/icinga/icinga.log'), ('dir', 'var/check_mk/core/archive'), ('file', 'var/check_mk/core/history')]}, 'performancedata': {'group': _('Historic Data'), 'title': _('Performance Data'), 'prefix': defaults.omd_root, 'paths': [('dir', 'var/pnp4nagios/perfdata'), ('dir', 'var/rrdcached'), ('dir', 'var/check_mk/rrd')], 'pre_restore': lambda : performancedata_restore(pre_restore=True), 'post_restore': lambda : performancedata_restore(pre_restore=False), 'checksum': False}, 'applicationlogs': {'group': _('Historic Data'), 'title': _('Application Logs'), 'prefix': defaults.omd_root, 'paths': [('dir', 'var/log'), ('file', 'var/nagios/livestatus.log'), ('dir', 'var/pnp4nagios/log')], 'checksum': False}, 'snmpmibs': {'group': _('Configuration'), 'title': _('SNMP MIBs'), 'prefix': defaults.omd_root, 'paths': [('dir', 'local/share/check_mk/mibs')]}, 'extensions': {'title': _('Extensions in <tt>~/local/</tt> and MKPs'), 'prefix': defaults.omd_root, 'paths': [('dir', 'var/check_mk/packages'), ('dir', 'local')], 'default': True}, 'dokuwiki': {'title': _('Doku Wiki Pages and Settings'), 'prefix': defaults.omd_root, 'paths': [('dir', 'var/dokuwiki')]}, 'nagvis': {'title': _('NagVis Maps, Configurations and User Files'), 'prefix': defaults.omd_root, 'exclude': ['etc/nagvis/apache.conf', 'etc/nagvis/conf.d/authorisation.ini.php', 'etc/nagvis/conf.d/omd.ini.php', 'etc/nagvis/conf.d/cookie_auth.ini.php', 'etc/nagvis/conf.d/urls.ini.php'], 'paths': [('dir', 'local/share/nagvis'), ('dir', 'etc/nagvis'), ('dir', 'var/nagvis')]}}) |
def create_mine_field(n, m, mines):
mine_field = [
[0 for _ in range(m)
] for _ in range(n)
]
for mine in mines:
x, y = mine
mine_field[x-1][y-1] = '*'
return mine_field
def neighbours(i, j, m):
nearest = [m[x][y] for x in [i-1, i, i+1] for y in [j-1, j, j+1]
if x in range(0, len(m)) and y in range(0, len(m[x]))
and (x, y) != (i, j)]
nearest_count = nearest.count('*')
return nearest_count
def check_field(mine_field, n, m):
for x in range(n):
for y in range(m):
if mine_field[x][y] == '*':
continue
else:
mine_field[x][y] = neighbours(i=x, j=y, m=mine_field)
with open('input.txt') as file:
lines = file.readlines()
n, m, k = list(map(int, lines[0].split()))
mines = []
for line in lines[1::]:
mines.append(list(map(int, line.split())))
mine_field = create_mine_field(n, m, mines)
check_field(mine_field, n, m)
with open('output.txt', 'w') as file:
rows = []
for row in mine_field:
line = f"{' '.join([str(item) for item in row])}\n"
rows.append(line)
file.writelines(rows)
| def create_mine_field(n, m, mines):
mine_field = [[0 for _ in range(m)] for _ in range(n)]
for mine in mines:
(x, y) = mine
mine_field[x - 1][y - 1] = '*'
return mine_field
def neighbours(i, j, m):
nearest = [m[x][y] for x in [i - 1, i, i + 1] for y in [j - 1, j, j + 1] if x in range(0, len(m)) and y in range(0, len(m[x])) and ((x, y) != (i, j))]
nearest_count = nearest.count('*')
return nearest_count
def check_field(mine_field, n, m):
for x in range(n):
for y in range(m):
if mine_field[x][y] == '*':
continue
else:
mine_field[x][y] = neighbours(i=x, j=y, m=mine_field)
with open('input.txt') as file:
lines = file.readlines()
(n, m, k) = list(map(int, lines[0].split()))
mines = []
for line in lines[1:]:
mines.append(list(map(int, line.split())))
mine_field = create_mine_field(n, m, mines)
check_field(mine_field, n, m)
with open('output.txt', 'w') as file:
rows = []
for row in mine_field:
line = f"{' '.join([str(item) for item in row])}\n"
rows.append(line)
file.writelines(rows) |
line = '-'*39
blank = '|' + ' '*37 + '|'
print(line)
print(blank)
print(blank)
print(blank)
print(blank)
print(blank)
print(line)
| line = '-' * 39
blank = '|' + ' ' * 37 + '|'
print(line)
print(blank)
print(blank)
print(blank)
print(blank)
print(blank)
print(line) |
"""Iteration utilities"""
class Batch:
"""Yields batches (groups) from an iterable
Modified from:
http://codereview.stackexchange.com/questions/118883/split-up-an-iterable-into-batches
Args:
iterable (iterable) any iterable
limit (int) How many items to include per group
"""
def __init__(self, iterable, limit=None):
self.iterator = iter(iterable)
self.limit = limit
try:
self.current = next(self.iterator)
except StopIteration:
self.on_going = False
else:
self.on_going = True
def group(self):
"""Yield a group from the iterable"""
yield self.current
# start enumerate at 1 because we already yielded the last saved item
for num, item in enumerate(self.iterator, 1):
self.current = item
if num == self.limit:
break
yield item
else:
self.on_going = False
def __iter__(self):
"""Implementation of __iter__ to allow a standard interface:
for group in Batch(iterable, 10):
do_stuff(group)
"""
while self.on_going:
yield self.group()
| """Iteration utilities"""
class Batch:
"""Yields batches (groups) from an iterable
Modified from:
http://codereview.stackexchange.com/questions/118883/split-up-an-iterable-into-batches
Args:
iterable (iterable) any iterable
limit (int) How many items to include per group
"""
def __init__(self, iterable, limit=None):
self.iterator = iter(iterable)
self.limit = limit
try:
self.current = next(self.iterator)
except StopIteration:
self.on_going = False
else:
self.on_going = True
def group(self):
"""Yield a group from the iterable"""
yield self.current
for (num, item) in enumerate(self.iterator, 1):
self.current = item
if num == self.limit:
break
yield item
else:
self.on_going = False
def __iter__(self):
"""Implementation of __iter__ to allow a standard interface:
for group in Batch(iterable, 10):
do_stuff(group)
"""
while self.on_going:
yield self.group() |
"""
Created on February 17 2021
@author: Andreas Spanopoulos
Contains custom Exceptions classes that can be used for debugging purposes.
"""
class GameIsNotOverError(Exception):
""" Custom exception raised when the outcome of a game that has not yet finished is queried """
def __init__(self, *args):
""" constructor """
self.fen = args[0] if args else None
def __str__(self):
""" print when raised outside try block """
message = 'The game has not reached a terminal state.'
if self.fen:
message += f' The current FEN position is: {self.fen}'
return message
class InvalidConfigurationError(Exception):
""" Custom Error raised when a configuration file is invalid """
def __init__(self, **kwargs):
""" constructor """
super(InvalidConfigurationError, self).__init__()
self.message = '' + kwargs.get('msg', '')
def __str__(self):
""" return string representation of the error """
return self.message
class InvalidArchitectureError(Exception):
""" Custom Error raised when the architecture of a Network is invalid """
def __init__(self, **kwargs):
""" constructor """
super(InvalidArchitectureError, self).__init__()
self.message = '' + kwargs.get('msg', '')
def __str__(self):
""" return string representation of the error """
return self.message
| """
Created on February 17 2021
@author: Andreas Spanopoulos
Contains custom Exceptions classes that can be used for debugging purposes.
"""
class Gameisnotovererror(Exception):
""" Custom exception raised when the outcome of a game that has not yet finished is queried """
def __init__(self, *args):
""" constructor """
self.fen = args[0] if args else None
def __str__(self):
""" print when raised outside try block """
message = 'The game has not reached a terminal state.'
if self.fen:
message += f' The current FEN position is: {self.fen}'
return message
class Invalidconfigurationerror(Exception):
""" Custom Error raised when a configuration file is invalid """
def __init__(self, **kwargs):
""" constructor """
super(InvalidConfigurationError, self).__init__()
self.message = '' + kwargs.get('msg', '')
def __str__(self):
""" return string representation of the error """
return self.message
class Invalidarchitectureerror(Exception):
""" Custom Error raised when the architecture of a Network is invalid """
def __init__(self, **kwargs):
""" constructor """
super(InvalidArchitectureError, self).__init__()
self.message = '' + kwargs.get('msg', '')
def __str__(self):
""" return string representation of the error """
return self.message |
class Solution:
def findMedianSortedArrays(self, nums1: List[int], nums2: List[int]) -> float:
if len(a:=nums1) > len(b:=nums2):
a, b = b, a
n = len(a)
m = len(b)
median, i, j = 0, 0, 0
min_index = 0
max_index = n
while (min_index <= max_index) :
i = int((min_index + max_index) / 2)
j = int(((n + m + 1) / 2) - i)
if (i < n and j > 0 and b[j - 1] > a[i]) :
min_index = i + 1
elif (i > 0 and j < m and b[j] < a[i - 1]) :
max_index = i - 1
else :
if (i == 0) :
median = b[j - 1]
elif (j == 0) :
median = a[i - 1]
else :
median = maximum(a[i - 1], b[j - 1])
break
if ((n + m) % 2 == 1) :
return median
if (i == n) :
return ((median + b[j]) / 2.0)
if (j == m) :
return ((median + a[i]) / 2.0)
return ((median + minimum(a[i], b[j])) / 2.0)
def maximum(a, b) :
return a if a > b else b
def minimum(a, b) :
return a if a < b else b | class Solution:
def find_median_sorted_arrays(self, nums1: List[int], nums2: List[int]) -> float:
if len((a := nums1)) > len((b := nums2)):
(a, b) = (b, a)
n = len(a)
m = len(b)
(median, i, j) = (0, 0, 0)
min_index = 0
max_index = n
while min_index <= max_index:
i = int((min_index + max_index) / 2)
j = int((n + m + 1) / 2 - i)
if i < n and j > 0 and (b[j - 1] > a[i]):
min_index = i + 1
elif i > 0 and j < m and (b[j] < a[i - 1]):
max_index = i - 1
else:
if i == 0:
median = b[j - 1]
elif j == 0:
median = a[i - 1]
else:
median = maximum(a[i - 1], b[j - 1])
break
if (n + m) % 2 == 1:
return median
if i == n:
return (median + b[j]) / 2.0
if j == m:
return (median + a[i]) / 2.0
return (median + minimum(a[i], b[j])) / 2.0
def maximum(a, b):
return a if a > b else b
def minimum(a, b):
return a if a < b else b |
'''
Python function to check whether a number is divisible by another number.
Accept two integers values form the user.
'''
def multiple(m, n):
return True if m % n == 0 else False
print(multiple(20, 5))
print(multiple(7, 2))
| """
Python function to check whether a number is divisible by another number.
Accept two integers values form the user.
"""
def multiple(m, n):
return True if m % n == 0 else False
print(multiple(20, 5))
print(multiple(7, 2)) |
#
# PySNMP MIB module MISSION-CRITICAL-MIB (http://snmplabs.com/pysmi)
# ASN.1 source file:///Users/davwang4/Dev/mibs.snmplabs.com/asn1/MISSION-CRITICAL-MIB
# Produced by pysmi-0.3.4 at Wed May 1 14:12:55 2019
# On host DAVWANG4-M-1475 platform Darwin version 18.5.0 by user davwang4
# Using Python version 3.7.3 (default, Mar 27 2019, 09:23:15)
#
Integer, OctetString, ObjectIdentifier = mibBuilder.importSymbols("ASN1", "Integer", "OctetString", "ObjectIdentifier")
NamedValues, = mibBuilder.importSymbols("ASN1-ENUMERATION", "NamedValues")
SingleValueConstraint, ConstraintsUnion, ValueSizeConstraint, ConstraintsIntersection, ValueRangeConstraint = mibBuilder.importSymbols("ASN1-REFINEMENT", "SingleValueConstraint", "ConstraintsUnion", "ValueSizeConstraint", "ConstraintsIntersection", "ValueRangeConstraint")
NotificationGroup, ModuleCompliance = mibBuilder.importSymbols("SNMPv2-CONF", "NotificationGroup", "ModuleCompliance")
NotificationType, TimeTicks, iso, MibScalar, MibTable, MibTableRow, MibTableColumn, Counter64, MibIdentifier, Bits, NotificationType, enterprises, Gauge32, Counter32, Unsigned32, IpAddress, Integer32, ModuleIdentity, ObjectIdentity = mibBuilder.importSymbols("SNMPv2-SMI", "NotificationType", "TimeTicks", "iso", "MibScalar", "MibTable", "MibTableRow", "MibTableColumn", "Counter64", "MibIdentifier", "Bits", "NotificationType", "enterprises", "Gauge32", "Counter32", "Unsigned32", "IpAddress", "Integer32", "ModuleIdentity", "ObjectIdentity")
TextualConvention, DisplayString = mibBuilder.importSymbols("SNMPv2-TC", "TextualConvention", "DisplayString")
missionCritical = MibIdentifier((1, 3, 6, 1, 4, 1, 2349))
mcsCompanyInfo = MibIdentifier((1, 3, 6, 1, 4, 1, 2349, 1))
mcsSoftware = MibIdentifier((1, 3, 6, 1, 4, 1, 2349, 2))
eemProductInfo = MibIdentifier((1, 3, 6, 1, 4, 1, 2349, 2, 1))
omProductInfo = MibIdentifier((1, 3, 6, 1, 4, 1, 2349, 2, 2))
ownershipDetails = MibScalar((1, 3, 6, 1, 4, 1, 2349, 1, 1), DisplayString().subtype(subtypeSpec=ValueSizeConstraint(1, 255))).setMaxAccess("readonly")
if mibBuilder.loadTexts: ownershipDetails.setStatus('mandatory')
if mibBuilder.loadTexts: ownershipDetails.setDescription('Details of the company providing this MIB')
contactDetails = MibScalar((1, 3, 6, 1, 4, 1, 2349, 1, 2), DisplayString().subtype(subtypeSpec=ValueSizeConstraint(1, 64))).setMaxAccess("readonly")
if mibBuilder.loadTexts: contactDetails.setStatus('mandatory')
if mibBuilder.loadTexts: contactDetails.setDescription('Contact responsible for maintaining this MIB')
eemService = MibIdentifier((1, 3, 6, 1, 4, 1, 2349, 2, 1, 1))
version = MibScalar((1, 3, 6, 1, 4, 1, 2349, 2, 1, 1, 1), DisplayString().subtype(subtypeSpec=ValueSizeConstraint(1, 16))).setMaxAccess("readonly")
if mibBuilder.loadTexts: version.setStatus('mandatory')
if mibBuilder.loadTexts: version.setDescription('The version of the EEM Agent running')
primaryServer = MibScalar((1, 3, 6, 1, 4, 1, 2349, 2, 1, 1, 2), DisplayString().subtype(subtypeSpec=ValueSizeConstraint(1, 16))).setMaxAccess("readonly")
if mibBuilder.loadTexts: primaryServer.setStatus('mandatory')
if mibBuilder.loadTexts: primaryServer.setDescription('The Primary Server for this EEM Agent')
serviceState = MibScalar((1, 3, 6, 1, 4, 1, 2349, 2, 1, 1, 3), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(1, 2))).clone(namedValues=NamedValues(("up", 1), ("down", 2)))).setMaxAccess("readonly")
if mibBuilder.loadTexts: serviceState.setStatus('mandatory')
if mibBuilder.loadTexts: serviceState.setDescription('State of the service. Running is 1, stopped is 2')
serviceUpTime = MibScalar((1, 3, 6, 1, 4, 1, 2349, 2, 1, 1, 4), TimeTicks()).setMaxAccess("readonly")
if mibBuilder.loadTexts: serviceUpTime.setStatus('mandatory')
if mibBuilder.loadTexts: serviceUpTime.setDescription('No. of milliseconds since the service was started')
redTrapCount = MibScalar((1, 3, 6, 1, 4, 1, 2349, 2, 1, 1, 5), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: redTrapCount.setStatus('deprecated')
if mibBuilder.loadTexts: redTrapCount.setDescription('The number of red alert traps sent since the service was started')
orangeTrapCount = MibScalar((1, 3, 6, 1, 4, 1, 2349, 2, 1, 1, 6), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: orangeTrapCount.setStatus('deprecated')
if mibBuilder.loadTexts: orangeTrapCount.setDescription('The number of orange alert traps sent since the service was started')
amberTrapCount = MibScalar((1, 3, 6, 1, 4, 1, 2349, 2, 1, 1, 7), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: amberTrapCount.setStatus('deprecated')
if mibBuilder.loadTexts: amberTrapCount.setDescription('The number of yellow alert traps sent since the service was started')
blueTrapCount = MibScalar((1, 3, 6, 1, 4, 1, 2349, 2, 1, 1, 8), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: blueTrapCount.setStatus('deprecated')
if mibBuilder.loadTexts: blueTrapCount.setDescription('The number of blue alert traps sent since the service was started')
greenTrapCount = MibScalar((1, 3, 6, 1, 4, 1, 2349, 2, 1, 1, 9), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: greenTrapCount.setStatus('deprecated')
if mibBuilder.loadTexts: greenTrapCount.setDescription('The number of Green Alert Traps since the service was started')
eemLastTrap = MibIdentifier((1, 3, 6, 1, 4, 1, 2349, 2, 1, 2))
trapTime = MibScalar((1, 3, 6, 1, 4, 1, 2349, 2, 1, 2, 1), TimeTicks()).setMaxAccess("readonly")
if mibBuilder.loadTexts: trapTime.setStatus('deprecated')
if mibBuilder.loadTexts: trapTime.setDescription('Time of the last trap sent')
alertLevel = MibScalar((1, 3, 6, 1, 4, 1, 2349, 2, 1, 2, 2), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(1, 2, 3, 4, 5))).clone(namedValues=NamedValues(("red", 1), ("orange", 2), ("yellow", 3), ("blue", 4), ("green", 5)))).setMaxAccess("readonly")
if mibBuilder.loadTexts: alertLevel.setStatus('mandatory')
if mibBuilder.loadTexts: alertLevel.setDescription('Alert level of the last trap sent. red=1, orange=2, yellow=3, blue=4, green=5')
logType = MibScalar((1, 3, 6, 1, 4, 1, 2349, 2, 1, 2, 3), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(1, 2, 3, 4, 5, 6, 7, 99))).clone(namedValues=NamedValues(("ntevent", 1), ("application", 2), ("snmp", 3), ("wbem", 4), ("activemonitoring", 5), ("performancemonitoring", 6), ("timedevent", 7), ("eem", 99)))).setMaxAccess("readonly")
if mibBuilder.loadTexts: logType.setStatus('mandatory')
if mibBuilder.loadTexts: logType.setDescription('Log type generating the last trap sent. system=1,application=2,security=3 (fill in others here) EEM=99')
server = MibScalar((1, 3, 6, 1, 4, 1, 2349, 2, 1, 2, 4), DisplayString().subtype(subtypeSpec=ValueSizeConstraint(1, 255))).setMaxAccess("readonly")
if mibBuilder.loadTexts: server.setStatus('mandatory')
if mibBuilder.loadTexts: server.setDescription('Server generating the last trap sent')
source = MibScalar((1, 3, 6, 1, 4, 1, 2349, 2, 1, 2, 5), DisplayString().subtype(subtypeSpec=ValueSizeConstraint(1, 255))).setMaxAccess("readonly")
if mibBuilder.loadTexts: source.setStatus('mandatory')
if mibBuilder.loadTexts: source.setDescription('Source generating the last trap sent')
user = MibScalar((1, 3, 6, 1, 4, 1, 2349, 2, 1, 2, 6), DisplayString().subtype(subtypeSpec=ValueSizeConstraint(1, 255))).setMaxAccess("readonly")
if mibBuilder.loadTexts: user.setStatus('mandatory')
if mibBuilder.loadTexts: user.setDescription('User generating the last trap sent')
eventID = MibScalar((1, 3, 6, 1, 4, 1, 2349, 2, 1, 2, 7), Integer32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: eventID.setStatus('mandatory')
if mibBuilder.loadTexts: eventID.setDescription('Event ID of the last trap sent')
description = MibScalar((1, 3, 6, 1, 4, 1, 2349, 2, 1, 2, 8), DisplayString().subtype(subtypeSpec=ValueSizeConstraint(1, 1024))).setMaxAccess("readonly")
if mibBuilder.loadTexts: description.setStatus('mandatory')
if mibBuilder.loadTexts: description.setDescription('Text description of the last trap sent')
genericTrapNumber = MibScalar((1, 3, 6, 1, 4, 1, 2349, 2, 1, 2, 9), Integer32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: genericTrapNumber.setStatus('mandatory')
if mibBuilder.loadTexts: genericTrapNumber.setDescription('The generic trap number of the last trap sent')
specificTrapNumber = MibScalar((1, 3, 6, 1, 4, 1, 2349, 2, 1, 2, 10), Integer32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: specificTrapNumber.setStatus('mandatory')
if mibBuilder.loadTexts: specificTrapNumber.setDescription('The user specific trap number of the last trap sent')
serviceGoingDown = NotificationType((1, 3, 6, 1, 4, 1, 2349, 2, 1) + (0,2))
if mibBuilder.loadTexts: serviceGoingDown.setDescription('The SeNTry EEM Sender service is stopping.')
serviceComingUp = NotificationType((1, 3, 6, 1, 4, 1, 2349, 2, 1) + (0,3))
if mibBuilder.loadTexts: serviceComingUp.setDescription('The SeNTry EEM Sender service is starting.')
gathererServiceGoingDown = NotificationType((1, 3, 6, 1, 4, 1, 2349, 2, 1) + (0,4))
if mibBuilder.loadTexts: gathererServiceGoingDown.setDescription('The SeNTry EEM Gatherer service is stopping.')
gathererServiceComingUp = NotificationType((1, 3, 6, 1, 4, 1, 2349, 2, 1) + (0,5))
if mibBuilder.loadTexts: gathererServiceComingUp.setDescription('The SeNTry EEM Gatherer service is starting.')
eemRedAlert = NotificationType((1, 3, 6, 1, 4, 1, 2349, 2, 1) + (0,100)).setObjects(("MISSION-CRITICAL-MIB", "alertLevel"), ("MISSION-CRITICAL-MIB", "logType"), ("MISSION-CRITICAL-MIB", "server"), ("MISSION-CRITICAL-MIB", "source"), ("MISSION-CRITICAL-MIB", "user"), ("MISSION-CRITICAL-MIB", "eventID"), ("MISSION-CRITICAL-MIB", "description"))
if mibBuilder.loadTexts: eemRedAlert.setDescription('A SeNTry EEM red alert has been generated.')
eemOrangeAlert = NotificationType((1, 3, 6, 1, 4, 1, 2349, 2, 1) + (0,200)).setObjects(("MISSION-CRITICAL-MIB", "alertLevel"), ("MISSION-CRITICAL-MIB", "logType"), ("MISSION-CRITICAL-MIB", "server"), ("MISSION-CRITICAL-MIB", "source"), ("MISSION-CRITICAL-MIB", "user"), ("MISSION-CRITICAL-MIB", "eventID"), ("MISSION-CRITICAL-MIB", "description"))
if mibBuilder.loadTexts: eemOrangeAlert.setDescription('A SeNTry EEM orange alert has been generated.')
eemYellowAlert = NotificationType((1, 3, 6, 1, 4, 1, 2349, 2, 1) + (0,300)).setObjects(("MISSION-CRITICAL-MIB", "alertLevel"), ("MISSION-CRITICAL-MIB", "logType"), ("MISSION-CRITICAL-MIB", "server"), ("MISSION-CRITICAL-MIB", "source"), ("MISSION-CRITICAL-MIB", "user"), ("MISSION-CRITICAL-MIB", "eventID"), ("MISSION-CRITICAL-MIB", "description"))
if mibBuilder.loadTexts: eemYellowAlert.setDescription('A SeNTry EEM yellow alert has been generated.')
eemBlueAlert = NotificationType((1, 3, 6, 1, 4, 1, 2349, 2, 1) + (0,400)).setObjects(("MISSION-CRITICAL-MIB", "alertLevel"), ("MISSION-CRITICAL-MIB", "logType"), ("MISSION-CRITICAL-MIB", "server"), ("MISSION-CRITICAL-MIB", "source"), ("MISSION-CRITICAL-MIB", "user"), ("MISSION-CRITICAL-MIB", "eventID"), ("MISSION-CRITICAL-MIB", "description"))
if mibBuilder.loadTexts: eemBlueAlert.setDescription('A SeNTry EEM blue alert has been generated.')
eemGreenAlert = NotificationType((1, 3, 6, 1, 4, 1, 2349, 2, 1) + (0,500)).setObjects(("MISSION-CRITICAL-MIB", "alertLevel"), ("MISSION-CRITICAL-MIB", "logType"), ("MISSION-CRITICAL-MIB", "server"), ("MISSION-CRITICAL-MIB", "source"), ("MISSION-CRITICAL-MIB", "user"), ("MISSION-CRITICAL-MIB", "eventID"), ("MISSION-CRITICAL-MIB", "description"))
if mibBuilder.loadTexts: eemGreenAlert.setDescription('A SeNTry EEM green alert has been generated.')
omService = MibIdentifier((1, 3, 6, 1, 4, 1, 2349, 2, 2, 1))
omLastTrap = MibIdentifier((1, 3, 6, 1, 4, 1, 2349, 2, 2, 2))
omTrapTime = MibScalar((1, 3, 6, 1, 4, 1, 2349, 2, 2, 2, 1), TimeTicks()).setMaxAccess("readonly")
if mibBuilder.loadTexts: omTrapTime.setStatus('deprecated')
if mibBuilder.loadTexts: omTrapTime.setDescription('Time of the last trap sent.')
omAlertLevel = MibScalar((1, 3, 6, 1, 4, 1, 2349, 2, 2, 2, 2), Integer32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: omAlertLevel.setStatus('mandatory')
if mibBuilder.loadTexts: omAlertLevel.setDescription('Alert level of the last trap sent.')
omAlertLevelName = MibScalar((1, 3, 6, 1, 4, 1, 2349, 2, 2, 2, 3), DisplayString().subtype(subtypeSpec=ValueSizeConstraint(0, 255))).setMaxAccess("readonly")
if mibBuilder.loadTexts: omAlertLevelName.setStatus('mandatory')
if mibBuilder.loadTexts: omAlertLevelName.setDescription('A textual description of the alert level for the last trap sent.')
omServer = MibScalar((1, 3, 6, 1, 4, 1, 2349, 2, 2, 2, 4), DisplayString().subtype(subtypeSpec=ValueSizeConstraint(0, 255))).setMaxAccess("readonly")
if mibBuilder.loadTexts: omServer.setStatus('mandatory')
if mibBuilder.loadTexts: omServer.setDescription('Server generating the last trap sent.')
omSource = MibScalar((1, 3, 6, 1, 4, 1, 2349, 2, 2, 2, 5), DisplayString().subtype(subtypeSpec=ValueSizeConstraint(0, 255))).setMaxAccess("readonly")
if mibBuilder.loadTexts: omSource.setStatus('mandatory')
if mibBuilder.loadTexts: omSource.setDescription('Source generating the last trap sent.')
omOwner = MibScalar((1, 3, 6, 1, 4, 1, 2349, 2, 2, 2, 6), DisplayString().subtype(subtypeSpec=ValueSizeConstraint(0, 255))).setMaxAccess("readonly")
if mibBuilder.loadTexts: omOwner.setStatus('mandatory')
if mibBuilder.loadTexts: omOwner.setDescription('User generating the last trap sent.')
omDescription = MibScalar((1, 3, 6, 1, 4, 1, 2349, 2, 2, 2, 7), DisplayString().subtype(subtypeSpec=ValueSizeConstraint(0, 1024))).setMaxAccess("readonly")
if mibBuilder.loadTexts: omDescription.setStatus('mandatory')
if mibBuilder.loadTexts: omDescription.setDescription('Text description of the last trap sent.')
omCustomField1 = MibScalar((1, 3, 6, 1, 4, 1, 2349, 2, 2, 2, 8), DisplayString().subtype(subtypeSpec=ValueSizeConstraint(0, 1024))).setMaxAccess("readonly")
if mibBuilder.loadTexts: omCustomField1.setStatus('mandatory')
if mibBuilder.loadTexts: omCustomField1.setDescription('Custom Field 1 defined by user')
omCustomField2 = MibScalar((1, 3, 6, 1, 4, 1, 2349, 2, 2, 2, 9), DisplayString().subtype(subtypeSpec=ValueSizeConstraint(0, 1024))).setMaxAccess("readonly")
if mibBuilder.loadTexts: omCustomField2.setStatus('mandatory')
if mibBuilder.loadTexts: omCustomField2.setDescription('Custom Field 2 defined by user')
omCustomField3 = MibScalar((1, 3, 6, 1, 4, 1, 2349, 2, 2, 2, 10), DisplayString().subtype(subtypeSpec=ValueSizeConstraint(0, 1024))).setMaxAccess("readonly")
if mibBuilder.loadTexts: omCustomField3.setStatus('mandatory')
if mibBuilder.loadTexts: omCustomField3.setDescription('Custom Field 3 defined by user')
omCustomField4 = MibScalar((1, 3, 6, 1, 4, 1, 2349, 2, 2, 2, 11), DisplayString().subtype(subtypeSpec=ValueSizeConstraint(0, 1024))).setMaxAccess("readonly")
if mibBuilder.loadTexts: omCustomField4.setStatus('mandatory')
if mibBuilder.loadTexts: omCustomField4.setDescription('Custom Field 4 defined by user')
omCustomField5 = MibScalar((1, 3, 6, 1, 4, 1, 2349, 2, 2, 2, 12), DisplayString().subtype(subtypeSpec=ValueSizeConstraint(0, 1024))).setMaxAccess("readonly")
if mibBuilder.loadTexts: omCustomField5.setStatus('mandatory')
if mibBuilder.loadTexts: omCustomField5.setDescription('Custom Field 5 defined by user')
omAlertURL = MibScalar((1, 3, 6, 1, 4, 1, 2349, 2, 2, 2, 13), DisplayString().subtype(subtypeSpec=ValueSizeConstraint(0, 2048))).setMaxAccess("readonly")
if mibBuilder.loadTexts: omAlertURL.setStatus('mandatory')
if mibBuilder.loadTexts: omAlertURL.setDescription('URL used to view alert details')
omGenericTrapNumber = MibScalar((1, 3, 6, 1, 4, 1, 2349, 2, 2, 2, 14), Integer32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: omGenericTrapNumber.setStatus('mandatory')
if mibBuilder.loadTexts: omGenericTrapNumber.setDescription('The generic trap number of the last trap sent.')
omSpecificTrapNumber = MibScalar((1, 3, 6, 1, 4, 1, 2349, 2, 2, 2, 15), Integer32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: omSpecificTrapNumber.setStatus('mandatory')
if mibBuilder.loadTexts: omSpecificTrapNumber.setDescription('The user specific trap number of the last trap sent')
omBlueAlert = NotificationType((1, 3, 6, 1, 4, 1, 2349, 2, 2) + (0,10)).setObjects(("MISSION-CRITICAL-MIB", "omAlertLevel"), ("MISSION-CRITICAL-MIB", "omAlertLevelName"), ("MISSION-CRITICAL-MIB", "omServer"), ("MISSION-CRITICAL-MIB", "omSource"), ("MISSION-CRITICAL-MIB", "omOwner"), ("MISSION-CRITICAL-MIB", "omDescription"), ("MISSION-CRITICAL-MIB", "omCustomField1"), ("MISSION-CRITICAL-MIB", "omCustomField2"), ("MISSION-CRITICAL-MIB", "omCustomField3"), ("MISSION-CRITICAL-MIB", "omCustomField4"), ("MISSION-CRITICAL-MIB", "omCustomField5"), ("MISSION-CRITICAL-MIB", "omAlertURL"))
if mibBuilder.loadTexts: omBlueAlert.setDescription('A OnePoint Operations Manager Blue Alert has been generated.')
omGreenAlert = NotificationType((1, 3, 6, 1, 4, 1, 2349, 2, 2) + (0,20)).setObjects(("MISSION-CRITICAL-MIB", "omAlertLevel"), ("MISSION-CRITICAL-MIB", "omAlertLevelName"), ("MISSION-CRITICAL-MIB", "omServer"), ("MISSION-CRITICAL-MIB", "omSource"), ("MISSION-CRITICAL-MIB", "omOwner"), ("MISSION-CRITICAL-MIB", "omDescription"), ("MISSION-CRITICAL-MIB", "omCustomField1"), ("MISSION-CRITICAL-MIB", "omCustomField2"), ("MISSION-CRITICAL-MIB", "omCustomField3"), ("MISSION-CRITICAL-MIB", "omCustomField4"), ("MISSION-CRITICAL-MIB", "omCustomField5"), ("MISSION-CRITICAL-MIB", "omAlertURL"))
if mibBuilder.loadTexts: omGreenAlert.setDescription('A OnePoint Operations Manager Green Alert has been generated.')
omYellowAlert = NotificationType((1, 3, 6, 1, 4, 1, 2349, 2, 2) + (0,30)).setObjects(("MISSION-CRITICAL-MIB", "omAlertLevel"), ("MISSION-CRITICAL-MIB", "omAlertLevelName"), ("MISSION-CRITICAL-MIB", "omServer"), ("MISSION-CRITICAL-MIB", "omSource"), ("MISSION-CRITICAL-MIB", "omOwner"), ("MISSION-CRITICAL-MIB", "omDescription"), ("MISSION-CRITICAL-MIB", "omCustomField1"), ("MISSION-CRITICAL-MIB", "omCustomField2"), ("MISSION-CRITICAL-MIB", "omCustomField3"), ("MISSION-CRITICAL-MIB", "omCustomField4"), ("MISSION-CRITICAL-MIB", "omCustomField5"), ("MISSION-CRITICAL-MIB", "omAlertURL"))
if mibBuilder.loadTexts: omYellowAlert.setDescription('A OnePoint Operations Manager Yellow Alert has been generated.')
omOrangeAlert = NotificationType((1, 3, 6, 1, 4, 1, 2349, 2, 2) + (0,40)).setObjects(("MISSION-CRITICAL-MIB", "omAlertLevel"), ("MISSION-CRITICAL-MIB", "omAlertLevelName"), ("MISSION-CRITICAL-MIB", "omServer"), ("MISSION-CRITICAL-MIB", "omSource"), ("MISSION-CRITICAL-MIB", "omOwner"), ("MISSION-CRITICAL-MIB", "omDescription"), ("MISSION-CRITICAL-MIB", "omCustomField1"), ("MISSION-CRITICAL-MIB", "omCustomField2"), ("MISSION-CRITICAL-MIB", "omCustomField3"), ("MISSION-CRITICAL-MIB", "omCustomField4"), ("MISSION-CRITICAL-MIB", "omCustomField5"), ("MISSION-CRITICAL-MIB", "omAlertURL"))
if mibBuilder.loadTexts: omOrangeAlert.setDescription('A OnePoint Operations Manager Orange Alert has been generated.')
omRedCriticalErrorAlert = NotificationType((1, 3, 6, 1, 4, 1, 2349, 2, 2) + (0,50)).setObjects(("MISSION-CRITICAL-MIB", "omAlertLevel"), ("MISSION-CRITICAL-MIB", "omAlertLevelName"), ("MISSION-CRITICAL-MIB", "omServer"), ("MISSION-CRITICAL-MIB", "omSource"), ("MISSION-CRITICAL-MIB", "omOwner"), ("MISSION-CRITICAL-MIB", "omDescription"), ("MISSION-CRITICAL-MIB", "omCustomField1"), ("MISSION-CRITICAL-MIB", "omCustomField2"), ("MISSION-CRITICAL-MIB", "omCustomField3"), ("MISSION-CRITICAL-MIB", "omCustomField4"), ("MISSION-CRITICAL-MIB", "omCustomField5"), ("MISSION-CRITICAL-MIB", "omAlertURL"))
if mibBuilder.loadTexts: omRedCriticalErrorAlert.setDescription('A OnePoint Operations Manager Critical Error Alert has been generated.')
omRedSecurityBreachAlert = NotificationType((1, 3, 6, 1, 4, 1, 2349, 2, 2) + (0,60)).setObjects(("MISSION-CRITICAL-MIB", "omAlertLevel"), ("MISSION-CRITICAL-MIB", "omAlertLevelName"), ("MISSION-CRITICAL-MIB", "omServer"), ("MISSION-CRITICAL-MIB", "omSource"), ("MISSION-CRITICAL-MIB", "omOwner"), ("MISSION-CRITICAL-MIB", "omDescription"), ("MISSION-CRITICAL-MIB", "omCustomField1"), ("MISSION-CRITICAL-MIB", "omCustomField2"), ("MISSION-CRITICAL-MIB", "omCustomField3"), ("MISSION-CRITICAL-MIB", "omCustomField4"), ("MISSION-CRITICAL-MIB", "omCustomField5"), ("MISSION-CRITICAL-MIB", "omAlertURL"))
if mibBuilder.loadTexts: omRedSecurityBreachAlert.setDescription('A OnePoint Operations Manager Security Breach Alert has been generated.')
omRedServiceUnavailableAlert = NotificationType((1, 3, 6, 1, 4, 1, 2349, 2, 2) + (0,70)).setObjects(("MISSION-CRITICAL-MIB", "omAlertLevel"), ("MISSION-CRITICAL-MIB", "omAlertLevelName"), ("MISSION-CRITICAL-MIB", "omServer"), ("MISSION-CRITICAL-MIB", "omSource"), ("MISSION-CRITICAL-MIB", "omOwner"), ("MISSION-CRITICAL-MIB", "omDescription"), ("MISSION-CRITICAL-MIB", "omCustomField1"), ("MISSION-CRITICAL-MIB", "omCustomField2"), ("MISSION-CRITICAL-MIB", "omCustomField3"), ("MISSION-CRITICAL-MIB", "omCustomField4"), ("MISSION-CRITICAL-MIB", "omCustomField5"), ("MISSION-CRITICAL-MIB", "omAlertURL"))
if mibBuilder.loadTexts: omRedServiceUnavailableAlert.setDescription('A OnePoint Operations Manager Service Unavailable Alert has been generated.')
mibBuilder.exportSymbols("MISSION-CRITICAL-MIB", serviceUpTime=serviceUpTime, omYellowAlert=omYellowAlert, redTrapCount=redTrapCount, eemOrangeAlert=eemOrangeAlert, mcsCompanyInfo=mcsCompanyInfo, omCustomField4=omCustomField4, gathererServiceComingUp=gathererServiceComingUp, serviceState=serviceState, omCustomField2=omCustomField2, omDescription=omDescription, missionCritical=missionCritical, omService=omService, eventID=eventID, omAlertLevelName=omAlertLevelName, serviceGoingDown=serviceGoingDown, omProductInfo=omProductInfo, trapTime=trapTime, eemService=eemService, eemYellowAlert=eemYellowAlert, omRedCriticalErrorAlert=omRedCriticalErrorAlert, omRedSecurityBreachAlert=omRedSecurityBreachAlert, blueTrapCount=blueTrapCount, greenTrapCount=greenTrapCount, omServer=omServer, mcsSoftware=mcsSoftware, serviceComingUp=serviceComingUp, omCustomField1=omCustomField1, omGreenAlert=omGreenAlert, eemLastTrap=eemLastTrap, omCustomField5=omCustomField5, omAlertURL=omAlertURL, omOrangeAlert=omOrangeAlert, omTrapTime=omTrapTime, logType=logType, amberTrapCount=amberTrapCount, user=user, specificTrapNumber=specificTrapNumber, source=source, omBlueAlert=omBlueAlert, ownershipDetails=ownershipDetails, eemRedAlert=eemRedAlert, omSpecificTrapNumber=omSpecificTrapNumber, omOwner=omOwner, gathererServiceGoingDown=gathererServiceGoingDown, orangeTrapCount=orangeTrapCount, server=server, omLastTrap=omLastTrap, omAlertLevel=omAlertLevel, omCustomField3=omCustomField3, omGenericTrapNumber=omGenericTrapNumber, description=description, genericTrapNumber=genericTrapNumber, eemGreenAlert=eemGreenAlert, primaryServer=primaryServer, alertLevel=alertLevel, version=version, omSource=omSource, eemProductInfo=eemProductInfo, eemBlueAlert=eemBlueAlert, contactDetails=contactDetails, omRedServiceUnavailableAlert=omRedServiceUnavailableAlert)
| (integer, octet_string, object_identifier) = mibBuilder.importSymbols('ASN1', 'Integer', 'OctetString', 'ObjectIdentifier')
(named_values,) = mibBuilder.importSymbols('ASN1-ENUMERATION', 'NamedValues')
(single_value_constraint, constraints_union, value_size_constraint, constraints_intersection, value_range_constraint) = mibBuilder.importSymbols('ASN1-REFINEMENT', 'SingleValueConstraint', 'ConstraintsUnion', 'ValueSizeConstraint', 'ConstraintsIntersection', 'ValueRangeConstraint')
(notification_group, module_compliance) = mibBuilder.importSymbols('SNMPv2-CONF', 'NotificationGroup', 'ModuleCompliance')
(notification_type, time_ticks, iso, mib_scalar, mib_table, mib_table_row, mib_table_column, counter64, mib_identifier, bits, notification_type, enterprises, gauge32, counter32, unsigned32, ip_address, integer32, module_identity, object_identity) = mibBuilder.importSymbols('SNMPv2-SMI', 'NotificationType', 'TimeTicks', 'iso', 'MibScalar', 'MibTable', 'MibTableRow', 'MibTableColumn', 'Counter64', 'MibIdentifier', 'Bits', 'NotificationType', 'enterprises', 'Gauge32', 'Counter32', 'Unsigned32', 'IpAddress', 'Integer32', 'ModuleIdentity', 'ObjectIdentity')
(textual_convention, display_string) = mibBuilder.importSymbols('SNMPv2-TC', 'TextualConvention', 'DisplayString')
mission_critical = mib_identifier((1, 3, 6, 1, 4, 1, 2349))
mcs_company_info = mib_identifier((1, 3, 6, 1, 4, 1, 2349, 1))
mcs_software = mib_identifier((1, 3, 6, 1, 4, 1, 2349, 2))
eem_product_info = mib_identifier((1, 3, 6, 1, 4, 1, 2349, 2, 1))
om_product_info = mib_identifier((1, 3, 6, 1, 4, 1, 2349, 2, 2))
ownership_details = mib_scalar((1, 3, 6, 1, 4, 1, 2349, 1, 1), display_string().subtype(subtypeSpec=value_size_constraint(1, 255))).setMaxAccess('readonly')
if mibBuilder.loadTexts:
ownershipDetails.setStatus('mandatory')
if mibBuilder.loadTexts:
ownershipDetails.setDescription('Details of the company providing this MIB')
contact_details = mib_scalar((1, 3, 6, 1, 4, 1, 2349, 1, 2), display_string().subtype(subtypeSpec=value_size_constraint(1, 64))).setMaxAccess('readonly')
if mibBuilder.loadTexts:
contactDetails.setStatus('mandatory')
if mibBuilder.loadTexts:
contactDetails.setDescription('Contact responsible for maintaining this MIB')
eem_service = mib_identifier((1, 3, 6, 1, 4, 1, 2349, 2, 1, 1))
version = mib_scalar((1, 3, 6, 1, 4, 1, 2349, 2, 1, 1, 1), display_string().subtype(subtypeSpec=value_size_constraint(1, 16))).setMaxAccess('readonly')
if mibBuilder.loadTexts:
version.setStatus('mandatory')
if mibBuilder.loadTexts:
version.setDescription('The version of the EEM Agent running')
primary_server = mib_scalar((1, 3, 6, 1, 4, 1, 2349, 2, 1, 1, 2), display_string().subtype(subtypeSpec=value_size_constraint(1, 16))).setMaxAccess('readonly')
if mibBuilder.loadTexts:
primaryServer.setStatus('mandatory')
if mibBuilder.loadTexts:
primaryServer.setDescription('The Primary Server for this EEM Agent')
service_state = mib_scalar((1, 3, 6, 1, 4, 1, 2349, 2, 1, 1, 3), integer32().subtype(subtypeSpec=constraints_union(single_value_constraint(1, 2))).clone(namedValues=named_values(('up', 1), ('down', 2)))).setMaxAccess('readonly')
if mibBuilder.loadTexts:
serviceState.setStatus('mandatory')
if mibBuilder.loadTexts:
serviceState.setDescription('State of the service. Running is 1, stopped is 2')
service_up_time = mib_scalar((1, 3, 6, 1, 4, 1, 2349, 2, 1, 1, 4), time_ticks()).setMaxAccess('readonly')
if mibBuilder.loadTexts:
serviceUpTime.setStatus('mandatory')
if mibBuilder.loadTexts:
serviceUpTime.setDescription('No. of milliseconds since the service was started')
red_trap_count = mib_scalar((1, 3, 6, 1, 4, 1, 2349, 2, 1, 1, 5), counter32()).setMaxAccess('readonly')
if mibBuilder.loadTexts:
redTrapCount.setStatus('deprecated')
if mibBuilder.loadTexts:
redTrapCount.setDescription('The number of red alert traps sent since the service was started')
orange_trap_count = mib_scalar((1, 3, 6, 1, 4, 1, 2349, 2, 1, 1, 6), counter32()).setMaxAccess('readonly')
if mibBuilder.loadTexts:
orangeTrapCount.setStatus('deprecated')
if mibBuilder.loadTexts:
orangeTrapCount.setDescription('The number of orange alert traps sent since the service was started')
amber_trap_count = mib_scalar((1, 3, 6, 1, 4, 1, 2349, 2, 1, 1, 7), counter32()).setMaxAccess('readonly')
if mibBuilder.loadTexts:
amberTrapCount.setStatus('deprecated')
if mibBuilder.loadTexts:
amberTrapCount.setDescription('The number of yellow alert traps sent since the service was started')
blue_trap_count = mib_scalar((1, 3, 6, 1, 4, 1, 2349, 2, 1, 1, 8), counter32()).setMaxAccess('readonly')
if mibBuilder.loadTexts:
blueTrapCount.setStatus('deprecated')
if mibBuilder.loadTexts:
blueTrapCount.setDescription('The number of blue alert traps sent since the service was started')
green_trap_count = mib_scalar((1, 3, 6, 1, 4, 1, 2349, 2, 1, 1, 9), counter32()).setMaxAccess('readonly')
if mibBuilder.loadTexts:
greenTrapCount.setStatus('deprecated')
if mibBuilder.loadTexts:
greenTrapCount.setDescription('The number of Green Alert Traps since the service was started')
eem_last_trap = mib_identifier((1, 3, 6, 1, 4, 1, 2349, 2, 1, 2))
trap_time = mib_scalar((1, 3, 6, 1, 4, 1, 2349, 2, 1, 2, 1), time_ticks()).setMaxAccess('readonly')
if mibBuilder.loadTexts:
trapTime.setStatus('deprecated')
if mibBuilder.loadTexts:
trapTime.setDescription('Time of the last trap sent')
alert_level = mib_scalar((1, 3, 6, 1, 4, 1, 2349, 2, 1, 2, 2), integer32().subtype(subtypeSpec=constraints_union(single_value_constraint(1, 2, 3, 4, 5))).clone(namedValues=named_values(('red', 1), ('orange', 2), ('yellow', 3), ('blue', 4), ('green', 5)))).setMaxAccess('readonly')
if mibBuilder.loadTexts:
alertLevel.setStatus('mandatory')
if mibBuilder.loadTexts:
alertLevel.setDescription('Alert level of the last trap sent. red=1, orange=2, yellow=3, blue=4, green=5')
log_type = mib_scalar((1, 3, 6, 1, 4, 1, 2349, 2, 1, 2, 3), integer32().subtype(subtypeSpec=constraints_union(single_value_constraint(1, 2, 3, 4, 5, 6, 7, 99))).clone(namedValues=named_values(('ntevent', 1), ('application', 2), ('snmp', 3), ('wbem', 4), ('activemonitoring', 5), ('performancemonitoring', 6), ('timedevent', 7), ('eem', 99)))).setMaxAccess('readonly')
if mibBuilder.loadTexts:
logType.setStatus('mandatory')
if mibBuilder.loadTexts:
logType.setDescription('Log type generating the last trap sent. system=1,application=2,security=3 (fill in others here) EEM=99')
server = mib_scalar((1, 3, 6, 1, 4, 1, 2349, 2, 1, 2, 4), display_string().subtype(subtypeSpec=value_size_constraint(1, 255))).setMaxAccess('readonly')
if mibBuilder.loadTexts:
server.setStatus('mandatory')
if mibBuilder.loadTexts:
server.setDescription('Server generating the last trap sent')
source = mib_scalar((1, 3, 6, 1, 4, 1, 2349, 2, 1, 2, 5), display_string().subtype(subtypeSpec=value_size_constraint(1, 255))).setMaxAccess('readonly')
if mibBuilder.loadTexts:
source.setStatus('mandatory')
if mibBuilder.loadTexts:
source.setDescription('Source generating the last trap sent')
user = mib_scalar((1, 3, 6, 1, 4, 1, 2349, 2, 1, 2, 6), display_string().subtype(subtypeSpec=value_size_constraint(1, 255))).setMaxAccess('readonly')
if mibBuilder.loadTexts:
user.setStatus('mandatory')
if mibBuilder.loadTexts:
user.setDescription('User generating the last trap sent')
event_id = mib_scalar((1, 3, 6, 1, 4, 1, 2349, 2, 1, 2, 7), integer32()).setMaxAccess('readonly')
if mibBuilder.loadTexts:
eventID.setStatus('mandatory')
if mibBuilder.loadTexts:
eventID.setDescription('Event ID of the last trap sent')
description = mib_scalar((1, 3, 6, 1, 4, 1, 2349, 2, 1, 2, 8), display_string().subtype(subtypeSpec=value_size_constraint(1, 1024))).setMaxAccess('readonly')
if mibBuilder.loadTexts:
description.setStatus('mandatory')
if mibBuilder.loadTexts:
description.setDescription('Text description of the last trap sent')
generic_trap_number = mib_scalar((1, 3, 6, 1, 4, 1, 2349, 2, 1, 2, 9), integer32()).setMaxAccess('readonly')
if mibBuilder.loadTexts:
genericTrapNumber.setStatus('mandatory')
if mibBuilder.loadTexts:
genericTrapNumber.setDescription('The generic trap number of the last trap sent')
specific_trap_number = mib_scalar((1, 3, 6, 1, 4, 1, 2349, 2, 1, 2, 10), integer32()).setMaxAccess('readonly')
if mibBuilder.loadTexts:
specificTrapNumber.setStatus('mandatory')
if mibBuilder.loadTexts:
specificTrapNumber.setDescription('The user specific trap number of the last trap sent')
service_going_down = notification_type((1, 3, 6, 1, 4, 1, 2349, 2, 1) + (0, 2))
if mibBuilder.loadTexts:
serviceGoingDown.setDescription('The SeNTry EEM Sender service is stopping.')
service_coming_up = notification_type((1, 3, 6, 1, 4, 1, 2349, 2, 1) + (0, 3))
if mibBuilder.loadTexts:
serviceComingUp.setDescription('The SeNTry EEM Sender service is starting.')
gatherer_service_going_down = notification_type((1, 3, 6, 1, 4, 1, 2349, 2, 1) + (0, 4))
if mibBuilder.loadTexts:
gathererServiceGoingDown.setDescription('The SeNTry EEM Gatherer service is stopping.')
gatherer_service_coming_up = notification_type((1, 3, 6, 1, 4, 1, 2349, 2, 1) + (0, 5))
if mibBuilder.loadTexts:
gathererServiceComingUp.setDescription('The SeNTry EEM Gatherer service is starting.')
eem_red_alert = notification_type((1, 3, 6, 1, 4, 1, 2349, 2, 1) + (0, 100)).setObjects(('MISSION-CRITICAL-MIB', 'alertLevel'), ('MISSION-CRITICAL-MIB', 'logType'), ('MISSION-CRITICAL-MIB', 'server'), ('MISSION-CRITICAL-MIB', 'source'), ('MISSION-CRITICAL-MIB', 'user'), ('MISSION-CRITICAL-MIB', 'eventID'), ('MISSION-CRITICAL-MIB', 'description'))
if mibBuilder.loadTexts:
eemRedAlert.setDescription('A SeNTry EEM red alert has been generated.')
eem_orange_alert = notification_type((1, 3, 6, 1, 4, 1, 2349, 2, 1) + (0, 200)).setObjects(('MISSION-CRITICAL-MIB', 'alertLevel'), ('MISSION-CRITICAL-MIB', 'logType'), ('MISSION-CRITICAL-MIB', 'server'), ('MISSION-CRITICAL-MIB', 'source'), ('MISSION-CRITICAL-MIB', 'user'), ('MISSION-CRITICAL-MIB', 'eventID'), ('MISSION-CRITICAL-MIB', 'description'))
if mibBuilder.loadTexts:
eemOrangeAlert.setDescription('A SeNTry EEM orange alert has been generated.')
eem_yellow_alert = notification_type((1, 3, 6, 1, 4, 1, 2349, 2, 1) + (0, 300)).setObjects(('MISSION-CRITICAL-MIB', 'alertLevel'), ('MISSION-CRITICAL-MIB', 'logType'), ('MISSION-CRITICAL-MIB', 'server'), ('MISSION-CRITICAL-MIB', 'source'), ('MISSION-CRITICAL-MIB', 'user'), ('MISSION-CRITICAL-MIB', 'eventID'), ('MISSION-CRITICAL-MIB', 'description'))
if mibBuilder.loadTexts:
eemYellowAlert.setDescription('A SeNTry EEM yellow alert has been generated.')
eem_blue_alert = notification_type((1, 3, 6, 1, 4, 1, 2349, 2, 1) + (0, 400)).setObjects(('MISSION-CRITICAL-MIB', 'alertLevel'), ('MISSION-CRITICAL-MIB', 'logType'), ('MISSION-CRITICAL-MIB', 'server'), ('MISSION-CRITICAL-MIB', 'source'), ('MISSION-CRITICAL-MIB', 'user'), ('MISSION-CRITICAL-MIB', 'eventID'), ('MISSION-CRITICAL-MIB', 'description'))
if mibBuilder.loadTexts:
eemBlueAlert.setDescription('A SeNTry EEM blue alert has been generated.')
eem_green_alert = notification_type((1, 3, 6, 1, 4, 1, 2349, 2, 1) + (0, 500)).setObjects(('MISSION-CRITICAL-MIB', 'alertLevel'), ('MISSION-CRITICAL-MIB', 'logType'), ('MISSION-CRITICAL-MIB', 'server'), ('MISSION-CRITICAL-MIB', 'source'), ('MISSION-CRITICAL-MIB', 'user'), ('MISSION-CRITICAL-MIB', 'eventID'), ('MISSION-CRITICAL-MIB', 'description'))
if mibBuilder.loadTexts:
eemGreenAlert.setDescription('A SeNTry EEM green alert has been generated.')
om_service = mib_identifier((1, 3, 6, 1, 4, 1, 2349, 2, 2, 1))
om_last_trap = mib_identifier((1, 3, 6, 1, 4, 1, 2349, 2, 2, 2))
om_trap_time = mib_scalar((1, 3, 6, 1, 4, 1, 2349, 2, 2, 2, 1), time_ticks()).setMaxAccess('readonly')
if mibBuilder.loadTexts:
omTrapTime.setStatus('deprecated')
if mibBuilder.loadTexts:
omTrapTime.setDescription('Time of the last trap sent.')
om_alert_level = mib_scalar((1, 3, 6, 1, 4, 1, 2349, 2, 2, 2, 2), integer32()).setMaxAccess('readonly')
if mibBuilder.loadTexts:
omAlertLevel.setStatus('mandatory')
if mibBuilder.loadTexts:
omAlertLevel.setDescription('Alert level of the last trap sent.')
om_alert_level_name = mib_scalar((1, 3, 6, 1, 4, 1, 2349, 2, 2, 2, 3), display_string().subtype(subtypeSpec=value_size_constraint(0, 255))).setMaxAccess('readonly')
if mibBuilder.loadTexts:
omAlertLevelName.setStatus('mandatory')
if mibBuilder.loadTexts:
omAlertLevelName.setDescription('A textual description of the alert level for the last trap sent.')
om_server = mib_scalar((1, 3, 6, 1, 4, 1, 2349, 2, 2, 2, 4), display_string().subtype(subtypeSpec=value_size_constraint(0, 255))).setMaxAccess('readonly')
if mibBuilder.loadTexts:
omServer.setStatus('mandatory')
if mibBuilder.loadTexts:
omServer.setDescription('Server generating the last trap sent.')
om_source = mib_scalar((1, 3, 6, 1, 4, 1, 2349, 2, 2, 2, 5), display_string().subtype(subtypeSpec=value_size_constraint(0, 255))).setMaxAccess('readonly')
if mibBuilder.loadTexts:
omSource.setStatus('mandatory')
if mibBuilder.loadTexts:
omSource.setDescription('Source generating the last trap sent.')
om_owner = mib_scalar((1, 3, 6, 1, 4, 1, 2349, 2, 2, 2, 6), display_string().subtype(subtypeSpec=value_size_constraint(0, 255))).setMaxAccess('readonly')
if mibBuilder.loadTexts:
omOwner.setStatus('mandatory')
if mibBuilder.loadTexts:
omOwner.setDescription('User generating the last trap sent.')
om_description = mib_scalar((1, 3, 6, 1, 4, 1, 2349, 2, 2, 2, 7), display_string().subtype(subtypeSpec=value_size_constraint(0, 1024))).setMaxAccess('readonly')
if mibBuilder.loadTexts:
omDescription.setStatus('mandatory')
if mibBuilder.loadTexts:
omDescription.setDescription('Text description of the last trap sent.')
om_custom_field1 = mib_scalar((1, 3, 6, 1, 4, 1, 2349, 2, 2, 2, 8), display_string().subtype(subtypeSpec=value_size_constraint(0, 1024))).setMaxAccess('readonly')
if mibBuilder.loadTexts:
omCustomField1.setStatus('mandatory')
if mibBuilder.loadTexts:
omCustomField1.setDescription('Custom Field 1 defined by user')
om_custom_field2 = mib_scalar((1, 3, 6, 1, 4, 1, 2349, 2, 2, 2, 9), display_string().subtype(subtypeSpec=value_size_constraint(0, 1024))).setMaxAccess('readonly')
if mibBuilder.loadTexts:
omCustomField2.setStatus('mandatory')
if mibBuilder.loadTexts:
omCustomField2.setDescription('Custom Field 2 defined by user')
om_custom_field3 = mib_scalar((1, 3, 6, 1, 4, 1, 2349, 2, 2, 2, 10), display_string().subtype(subtypeSpec=value_size_constraint(0, 1024))).setMaxAccess('readonly')
if mibBuilder.loadTexts:
omCustomField3.setStatus('mandatory')
if mibBuilder.loadTexts:
omCustomField3.setDescription('Custom Field 3 defined by user')
om_custom_field4 = mib_scalar((1, 3, 6, 1, 4, 1, 2349, 2, 2, 2, 11), display_string().subtype(subtypeSpec=value_size_constraint(0, 1024))).setMaxAccess('readonly')
if mibBuilder.loadTexts:
omCustomField4.setStatus('mandatory')
if mibBuilder.loadTexts:
omCustomField4.setDescription('Custom Field 4 defined by user')
om_custom_field5 = mib_scalar((1, 3, 6, 1, 4, 1, 2349, 2, 2, 2, 12), display_string().subtype(subtypeSpec=value_size_constraint(0, 1024))).setMaxAccess('readonly')
if mibBuilder.loadTexts:
omCustomField5.setStatus('mandatory')
if mibBuilder.loadTexts:
omCustomField5.setDescription('Custom Field 5 defined by user')
om_alert_url = mib_scalar((1, 3, 6, 1, 4, 1, 2349, 2, 2, 2, 13), display_string().subtype(subtypeSpec=value_size_constraint(0, 2048))).setMaxAccess('readonly')
if mibBuilder.loadTexts:
omAlertURL.setStatus('mandatory')
if mibBuilder.loadTexts:
omAlertURL.setDescription('URL used to view alert details')
om_generic_trap_number = mib_scalar((1, 3, 6, 1, 4, 1, 2349, 2, 2, 2, 14), integer32()).setMaxAccess('readonly')
if mibBuilder.loadTexts:
omGenericTrapNumber.setStatus('mandatory')
if mibBuilder.loadTexts:
omGenericTrapNumber.setDescription('The generic trap number of the last trap sent.')
om_specific_trap_number = mib_scalar((1, 3, 6, 1, 4, 1, 2349, 2, 2, 2, 15), integer32()).setMaxAccess('readonly')
if mibBuilder.loadTexts:
omSpecificTrapNumber.setStatus('mandatory')
if mibBuilder.loadTexts:
omSpecificTrapNumber.setDescription('The user specific trap number of the last trap sent')
om_blue_alert = notification_type((1, 3, 6, 1, 4, 1, 2349, 2, 2) + (0, 10)).setObjects(('MISSION-CRITICAL-MIB', 'omAlertLevel'), ('MISSION-CRITICAL-MIB', 'omAlertLevelName'), ('MISSION-CRITICAL-MIB', 'omServer'), ('MISSION-CRITICAL-MIB', 'omSource'), ('MISSION-CRITICAL-MIB', 'omOwner'), ('MISSION-CRITICAL-MIB', 'omDescription'), ('MISSION-CRITICAL-MIB', 'omCustomField1'), ('MISSION-CRITICAL-MIB', 'omCustomField2'), ('MISSION-CRITICAL-MIB', 'omCustomField3'), ('MISSION-CRITICAL-MIB', 'omCustomField4'), ('MISSION-CRITICAL-MIB', 'omCustomField5'), ('MISSION-CRITICAL-MIB', 'omAlertURL'))
if mibBuilder.loadTexts:
omBlueAlert.setDescription('A OnePoint Operations Manager Blue Alert has been generated.')
om_green_alert = notification_type((1, 3, 6, 1, 4, 1, 2349, 2, 2) + (0, 20)).setObjects(('MISSION-CRITICAL-MIB', 'omAlertLevel'), ('MISSION-CRITICAL-MIB', 'omAlertLevelName'), ('MISSION-CRITICAL-MIB', 'omServer'), ('MISSION-CRITICAL-MIB', 'omSource'), ('MISSION-CRITICAL-MIB', 'omOwner'), ('MISSION-CRITICAL-MIB', 'omDescription'), ('MISSION-CRITICAL-MIB', 'omCustomField1'), ('MISSION-CRITICAL-MIB', 'omCustomField2'), ('MISSION-CRITICAL-MIB', 'omCustomField3'), ('MISSION-CRITICAL-MIB', 'omCustomField4'), ('MISSION-CRITICAL-MIB', 'omCustomField5'), ('MISSION-CRITICAL-MIB', 'omAlertURL'))
if mibBuilder.loadTexts:
omGreenAlert.setDescription('A OnePoint Operations Manager Green Alert has been generated.')
om_yellow_alert = notification_type((1, 3, 6, 1, 4, 1, 2349, 2, 2) + (0, 30)).setObjects(('MISSION-CRITICAL-MIB', 'omAlertLevel'), ('MISSION-CRITICAL-MIB', 'omAlertLevelName'), ('MISSION-CRITICAL-MIB', 'omServer'), ('MISSION-CRITICAL-MIB', 'omSource'), ('MISSION-CRITICAL-MIB', 'omOwner'), ('MISSION-CRITICAL-MIB', 'omDescription'), ('MISSION-CRITICAL-MIB', 'omCustomField1'), ('MISSION-CRITICAL-MIB', 'omCustomField2'), ('MISSION-CRITICAL-MIB', 'omCustomField3'), ('MISSION-CRITICAL-MIB', 'omCustomField4'), ('MISSION-CRITICAL-MIB', 'omCustomField5'), ('MISSION-CRITICAL-MIB', 'omAlertURL'))
if mibBuilder.loadTexts:
omYellowAlert.setDescription('A OnePoint Operations Manager Yellow Alert has been generated.')
om_orange_alert = notification_type((1, 3, 6, 1, 4, 1, 2349, 2, 2) + (0, 40)).setObjects(('MISSION-CRITICAL-MIB', 'omAlertLevel'), ('MISSION-CRITICAL-MIB', 'omAlertLevelName'), ('MISSION-CRITICAL-MIB', 'omServer'), ('MISSION-CRITICAL-MIB', 'omSource'), ('MISSION-CRITICAL-MIB', 'omOwner'), ('MISSION-CRITICAL-MIB', 'omDescription'), ('MISSION-CRITICAL-MIB', 'omCustomField1'), ('MISSION-CRITICAL-MIB', 'omCustomField2'), ('MISSION-CRITICAL-MIB', 'omCustomField3'), ('MISSION-CRITICAL-MIB', 'omCustomField4'), ('MISSION-CRITICAL-MIB', 'omCustomField5'), ('MISSION-CRITICAL-MIB', 'omAlertURL'))
if mibBuilder.loadTexts:
omOrangeAlert.setDescription('A OnePoint Operations Manager Orange Alert has been generated.')
om_red_critical_error_alert = notification_type((1, 3, 6, 1, 4, 1, 2349, 2, 2) + (0, 50)).setObjects(('MISSION-CRITICAL-MIB', 'omAlertLevel'), ('MISSION-CRITICAL-MIB', 'omAlertLevelName'), ('MISSION-CRITICAL-MIB', 'omServer'), ('MISSION-CRITICAL-MIB', 'omSource'), ('MISSION-CRITICAL-MIB', 'omOwner'), ('MISSION-CRITICAL-MIB', 'omDescription'), ('MISSION-CRITICAL-MIB', 'omCustomField1'), ('MISSION-CRITICAL-MIB', 'omCustomField2'), ('MISSION-CRITICAL-MIB', 'omCustomField3'), ('MISSION-CRITICAL-MIB', 'omCustomField4'), ('MISSION-CRITICAL-MIB', 'omCustomField5'), ('MISSION-CRITICAL-MIB', 'omAlertURL'))
if mibBuilder.loadTexts:
omRedCriticalErrorAlert.setDescription('A OnePoint Operations Manager Critical Error Alert has been generated.')
om_red_security_breach_alert = notification_type((1, 3, 6, 1, 4, 1, 2349, 2, 2) + (0, 60)).setObjects(('MISSION-CRITICAL-MIB', 'omAlertLevel'), ('MISSION-CRITICAL-MIB', 'omAlertLevelName'), ('MISSION-CRITICAL-MIB', 'omServer'), ('MISSION-CRITICAL-MIB', 'omSource'), ('MISSION-CRITICAL-MIB', 'omOwner'), ('MISSION-CRITICAL-MIB', 'omDescription'), ('MISSION-CRITICAL-MIB', 'omCustomField1'), ('MISSION-CRITICAL-MIB', 'omCustomField2'), ('MISSION-CRITICAL-MIB', 'omCustomField3'), ('MISSION-CRITICAL-MIB', 'omCustomField4'), ('MISSION-CRITICAL-MIB', 'omCustomField5'), ('MISSION-CRITICAL-MIB', 'omAlertURL'))
if mibBuilder.loadTexts:
omRedSecurityBreachAlert.setDescription('A OnePoint Operations Manager Security Breach Alert has been generated.')
om_red_service_unavailable_alert = notification_type((1, 3, 6, 1, 4, 1, 2349, 2, 2) + (0, 70)).setObjects(('MISSION-CRITICAL-MIB', 'omAlertLevel'), ('MISSION-CRITICAL-MIB', 'omAlertLevelName'), ('MISSION-CRITICAL-MIB', 'omServer'), ('MISSION-CRITICAL-MIB', 'omSource'), ('MISSION-CRITICAL-MIB', 'omOwner'), ('MISSION-CRITICAL-MIB', 'omDescription'), ('MISSION-CRITICAL-MIB', 'omCustomField1'), ('MISSION-CRITICAL-MIB', 'omCustomField2'), ('MISSION-CRITICAL-MIB', 'omCustomField3'), ('MISSION-CRITICAL-MIB', 'omCustomField4'), ('MISSION-CRITICAL-MIB', 'omCustomField5'), ('MISSION-CRITICAL-MIB', 'omAlertURL'))
if mibBuilder.loadTexts:
omRedServiceUnavailableAlert.setDescription('A OnePoint Operations Manager Service Unavailable Alert has been generated.')
mibBuilder.exportSymbols('MISSION-CRITICAL-MIB', serviceUpTime=serviceUpTime, omYellowAlert=omYellowAlert, redTrapCount=redTrapCount, eemOrangeAlert=eemOrangeAlert, mcsCompanyInfo=mcsCompanyInfo, omCustomField4=omCustomField4, gathererServiceComingUp=gathererServiceComingUp, serviceState=serviceState, omCustomField2=omCustomField2, omDescription=omDescription, missionCritical=missionCritical, omService=omService, eventID=eventID, omAlertLevelName=omAlertLevelName, serviceGoingDown=serviceGoingDown, omProductInfo=omProductInfo, trapTime=trapTime, eemService=eemService, eemYellowAlert=eemYellowAlert, omRedCriticalErrorAlert=omRedCriticalErrorAlert, omRedSecurityBreachAlert=omRedSecurityBreachAlert, blueTrapCount=blueTrapCount, greenTrapCount=greenTrapCount, omServer=omServer, mcsSoftware=mcsSoftware, serviceComingUp=serviceComingUp, omCustomField1=omCustomField1, omGreenAlert=omGreenAlert, eemLastTrap=eemLastTrap, omCustomField5=omCustomField5, omAlertURL=omAlertURL, omOrangeAlert=omOrangeAlert, omTrapTime=omTrapTime, logType=logType, amberTrapCount=amberTrapCount, user=user, specificTrapNumber=specificTrapNumber, source=source, omBlueAlert=omBlueAlert, ownershipDetails=ownershipDetails, eemRedAlert=eemRedAlert, omSpecificTrapNumber=omSpecificTrapNumber, omOwner=omOwner, gathererServiceGoingDown=gathererServiceGoingDown, orangeTrapCount=orangeTrapCount, server=server, omLastTrap=omLastTrap, omAlertLevel=omAlertLevel, omCustomField3=omCustomField3, omGenericTrapNumber=omGenericTrapNumber, description=description, genericTrapNumber=genericTrapNumber, eemGreenAlert=eemGreenAlert, primaryServer=primaryServer, alertLevel=alertLevel, version=version, omSource=omSource, eemProductInfo=eemProductInfo, eemBlueAlert=eemBlueAlert, contactDetails=contactDetails, omRedServiceUnavailableAlert=omRedServiceUnavailableAlert) |
def assert_has_size(output_bytes, value, delta=0):
"""Asserts the specified output has a size of the specified value"""
output_size = len(output_bytes)
assert abs(output_size - int(value)) <= int(delta), "Expected file size was %s, actual file size was %s (difference of %s accepted)" % (value, output_size, delta)
| def assert_has_size(output_bytes, value, delta=0):
"""Asserts the specified output has a size of the specified value"""
output_size = len(output_bytes)
assert abs(output_size - int(value)) <= int(delta), 'Expected file size was %s, actual file size was %s (difference of %s accepted)' % (value, output_size, delta) |
num = 111
num = 222
num = 333333
num = 333
num4 = 44444
| num = 111
num = 222
num = 333333
num = 333
num4 = 44444 |
__author__ = "hoongeun"
__version__ = "0.0.1"
__copyright__ = "Copyright (c) hoongeun"
__license__ = "Beer ware"
| __author__ = 'hoongeun'
__version__ = '0.0.1'
__copyright__ = 'Copyright (c) hoongeun'
__license__ = 'Beer ware' |
# Function arguments ...
#
# Class instances can be pass as arguments to functions
class Point:
""" a 2D point """
p = Point()
p.x = 1
p.y = 2
def print_point(point):
print('(%s, %s)' % (point.x, point.y))
print_point(p) # (1, 2) | class Point:
""" a 2D point """
p = point()
p.x = 1
p.y = 2
def print_point(point):
print('(%s, %s)' % (point.x, point.y))
print_point(p) |
def test1():
inp="0 2 7 0"
inp="4 10 4 1 8 4 9 14 5 1 14 15 0 15 3 5"
nums = list(map(lambda x: int(x), inp.split()))
hist = [ nums ]
step = 1
current = nums[:]
while True:
#print('step', step, 'current', current)
#search max
m = max(current)
#max index
idx = current.index(m)
current[idx] = 0
idx += 1
while m > 0:
idx = 0 if idx >= len(current) else idx
current[idx] += 1
m -= 1
idx += 1
if current in hist:
print(step, hist.index(current), step - hist.index(current))
break
step += 1
hist.append(current[:])
#print(hist[0])
| def test1():
inp = '0 2 7 0'
inp = '4 10 4 1 8 4 9 14 5 1 14 15 0 15 3 5'
nums = list(map(lambda x: int(x), inp.split()))
hist = [nums]
step = 1
current = nums[:]
while True:
m = max(current)
idx = current.index(m)
current[idx] = 0
idx += 1
while m > 0:
idx = 0 if idx >= len(current) else idx
current[idx] += 1
m -= 1
idx += 1
if current in hist:
print(step, hist.index(current), step - hist.index(current))
break
step += 1
hist.append(current[:]) |
#!/usr/bin/env python
#
# @Author: Dalmasso Giovanni <gioda>
# @Date: 09-Feb-2018
# @Email: giovanni.dalmasso@embl.es
# @Project: python_utils
# @Filename: colors.py
# @Last modified by: gioda
# @Last modified time: 15-Mar-2018
# @License: MIT
"""Collection of basic colors as RGB for plotting (inspired by "Tableau" www.tableau.com)."""
def colBase10():
"""List of 10 basic colors as RGB."""
col = [(31, 119, 180), (255, 127, 14), (44, 160, 44), (214, 39, 40), (148, 103, 189),
(140, 86, 75), (227, 119, 194), (127, 127, 127), (188, 189, 34), (23, 190, 207)]
# Scale the RGB values to the [0, 1] range, which is the format matplotlib accepts.
for j in range(len(col)):
r, g, b = col[j]
col[j] = (r / 255., g / 255., b / 255.)
col = col * 100000
return col
def colLight():
"""List of 10 light colors as RGB."""
col = [(174, 199, 232), (255, 187, 120), (152, 223, 138), (255, 152, 150), (197, 176, 213),
(196, 156, 148), (247, 182, 210), (199, 199, 199), (219, 219, 141), (158, 218, 229)]
# Scale the RGB values to the [0, 1] range, which is the format matplotlib accepts.
for j in range(len(col)):
r, g, b = col[j]
col[j] = (r / 255., g / 255., b / 255.)
col = col * 100000
return col
def colMedium():
"""List of 10 medium colors as RGB."""
col = [(114, 158, 206), (255, 158, 74), (103, 191, 92), (237, 102, 93), (173, 139, 201),
(168, 120, 110), (237, 151, 202), (162, 162, 162), (205, 204, 93), (109, 204, 218)]
# Scale the RGB values to the [0, 1] range, which is the format matplotlib accepts.
for j in range(len(col)):
r, g, b = col[j]
col[j] = (r / 255., g / 255., b / 255.)
col = col * 100000
return col
def colCblind():
"""List of 10 color blind colors as RGB."""
col = [(0, 107, 164), (255, 128, 14), (171, 171, 171), (89, 89, 89), (95, 158, 209),
(200, 82, 0), (137, 137, 137), (162, 200, 236), (255, 188, 121), (207, 207, 207)]
# Scale the RGB values to the [0, 1] range, which is the format matplotlib accepts.
for j in range(len(col)):
r, g, b = col[j]
col[j] = (r / 255., g / 255., b / 255.)
col = col * 100000
return col
def colGrey():
"""List of 5 grey colors as RGB."""
col = [(207, 207, 207), (165, 172, 175), (143, 135, 130), (96, 99, 106), (65, 68, 81)]
# Scale the RGB values to the [0, 1] range, which is the format matplotlib accepts.
for j in range(len(col)):
r, g, b = col[j]
col[j] = (r / 255., g / 255., b / 255.)
col = col * 100000
return col
def colTrafficLigth():
"""List of 9 traffic-light colors as RGB."""
col = [(255, 193, 86), (219, 161, 58), (216, 37, 38), (177, 3, 24),
(48, 147, 67), (255, 221, 113), (242, 108, 100), (159, 205, 153), (105, 183, 100)]
# Scale the RGB values to the [0, 1] range, which is the format matplotlib accepts.
for j in range(len(col)):
r, g, b = col[j]
col[j] = (r / 255., g / 255., b / 255.)
col = col * 100000
return col
def colPurpleGrey():
"""List of 6 purple-grey colors as RGB."""
col = [(220, 95, 189), (208, 152, 238), (153, 86, 136),
(148, 145, 123), (123, 102, 210), (215, 213, 197)]
# Scale the RGB values to the [0, 1] range, which is the format matplotlib accepts.
for j in range(len(col)):
r, g, b = col[j]
col[j] = (r / 255., g / 255., b / 255.)
col = col * 100000
return col
def colBase20():
"""List of 20 basic colors as RGB."""
col = [(31, 119, 180), (174, 199, 232), (255, 127, 14), (255, 187, 120),
(44, 160, 44), (152, 223, 138), (214, 39, 40), (255, 152, 150),
(148, 103, 189), (197, 176, 213), (140, 86, 75), (196, 156, 148),
(227, 119, 194), (247, 182, 210), (127, 127, 127), (199, 199, 199),
(188, 189, 34), (219, 219, 141), (23, 190, 207), (158, 218, 229)]
# Scale the RGB values to the [0, 1] range, which is the format matplotlib accepts.
for j in range(len(col)):
r, g, b = col[j]
col[j] = (r / 255., g / 255., b / 255.)
col = col * 100000
return col
| """Collection of basic colors as RGB for plotting (inspired by "Tableau" www.tableau.com)."""
def col_base10():
"""List of 10 basic colors as RGB."""
col = [(31, 119, 180), (255, 127, 14), (44, 160, 44), (214, 39, 40), (148, 103, 189), (140, 86, 75), (227, 119, 194), (127, 127, 127), (188, 189, 34), (23, 190, 207)]
for j in range(len(col)):
(r, g, b) = col[j]
col[j] = (r / 255.0, g / 255.0, b / 255.0)
col = col * 100000
return col
def col_light():
"""List of 10 light colors as RGB."""
col = [(174, 199, 232), (255, 187, 120), (152, 223, 138), (255, 152, 150), (197, 176, 213), (196, 156, 148), (247, 182, 210), (199, 199, 199), (219, 219, 141), (158, 218, 229)]
for j in range(len(col)):
(r, g, b) = col[j]
col[j] = (r / 255.0, g / 255.0, b / 255.0)
col = col * 100000
return col
def col_medium():
"""List of 10 medium colors as RGB."""
col = [(114, 158, 206), (255, 158, 74), (103, 191, 92), (237, 102, 93), (173, 139, 201), (168, 120, 110), (237, 151, 202), (162, 162, 162), (205, 204, 93), (109, 204, 218)]
for j in range(len(col)):
(r, g, b) = col[j]
col[j] = (r / 255.0, g / 255.0, b / 255.0)
col = col * 100000
return col
def col_cblind():
"""List of 10 color blind colors as RGB."""
col = [(0, 107, 164), (255, 128, 14), (171, 171, 171), (89, 89, 89), (95, 158, 209), (200, 82, 0), (137, 137, 137), (162, 200, 236), (255, 188, 121), (207, 207, 207)]
for j in range(len(col)):
(r, g, b) = col[j]
col[j] = (r / 255.0, g / 255.0, b / 255.0)
col = col * 100000
return col
def col_grey():
"""List of 5 grey colors as RGB."""
col = [(207, 207, 207), (165, 172, 175), (143, 135, 130), (96, 99, 106), (65, 68, 81)]
for j in range(len(col)):
(r, g, b) = col[j]
col[j] = (r / 255.0, g / 255.0, b / 255.0)
col = col * 100000
return col
def col_traffic_ligth():
"""List of 9 traffic-light colors as RGB."""
col = [(255, 193, 86), (219, 161, 58), (216, 37, 38), (177, 3, 24), (48, 147, 67), (255, 221, 113), (242, 108, 100), (159, 205, 153), (105, 183, 100)]
for j in range(len(col)):
(r, g, b) = col[j]
col[j] = (r / 255.0, g / 255.0, b / 255.0)
col = col * 100000
return col
def col_purple_grey():
"""List of 6 purple-grey colors as RGB."""
col = [(220, 95, 189), (208, 152, 238), (153, 86, 136), (148, 145, 123), (123, 102, 210), (215, 213, 197)]
for j in range(len(col)):
(r, g, b) = col[j]
col[j] = (r / 255.0, g / 255.0, b / 255.0)
col = col * 100000
return col
def col_base20():
"""List of 20 basic colors as RGB."""
col = [(31, 119, 180), (174, 199, 232), (255, 127, 14), (255, 187, 120), (44, 160, 44), (152, 223, 138), (214, 39, 40), (255, 152, 150), (148, 103, 189), (197, 176, 213), (140, 86, 75), (196, 156, 148), (227, 119, 194), (247, 182, 210), (127, 127, 127), (199, 199, 199), (188, 189, 34), (219, 219, 141), (23, 190, 207), (158, 218, 229)]
for j in range(len(col)):
(r, g, b) = col[j]
col[j] = (r / 255.0, g / 255.0, b / 255.0)
col = col * 100000
return col |
# test floor-division and modulo operators
@micropython.viper
def div(x:int, y:int) -> int:
return x // y
@micropython.viper
def mod(x:int, y:int) -> int:
return x % y
def dm(x, y):
print(div(x, y), mod(x, y))
for x in (-6, 6):
for y in range(-7, 8):
if y == 0:
continue
dm(x, y)
| @micropython.viper
def div(x: int, y: int) -> int:
return x // y
@micropython.viper
def mod(x: int, y: int) -> int:
return x % y
def dm(x, y):
print(div(x, y), mod(x, y))
for x in (-6, 6):
for y in range(-7, 8):
if y == 0:
continue
dm(x, y) |
# -*- coding: utf-8 -*-
def func(precess_data, x):
precess_data = list(range(0, 100, 3))
low = 0
high = 34
guess = int((low + high) / 2)
while precess_data[guess] != x:
if precess_data[guess] < x:
low = guess
elif precess_data[guess] > x:
high = guess
else:
break
guess = (low + high) // 2
return guess
print(func(list(range(0, 100, 3)), 99))
| def func(precess_data, x):
precess_data = list(range(0, 100, 3))
low = 0
high = 34
guess = int((low + high) / 2)
while precess_data[guess] != x:
if precess_data[guess] < x:
low = guess
elif precess_data[guess] > x:
high = guess
else:
break
guess = (low + high) // 2
return guess
print(func(list(range(0, 100, 3)), 99)) |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
We have two functions in this class.
one to collect data from the winner and store in a text file,
and one to print this data on a scoreboard.
"""
class Highscore():
"""Highscore class."""
def show_score_board(self, filename):
"""Read textfile, format the data to display the scores."""
with open(filename, "r") as file:
print("{:*^50}".format(" HIGHSCORE TABLE "))
data = file.readlines()
all_scores = []
for line in data:
name, total, streak = line.split(";")
score = (name, int(total), streak.rstrip())
all_scores.append(score)
all_scores.sort(key=lambda y: y[1], reverse=True)
position = 1
print(" Name: Total Score: Longest Streak:")
for score in all_scores:
print(f"{position:>2}: {score[0]:15}" +
f"{score[1]:<15} {score[2]}")
position = position + 1
def collect_score(self, name, score, longeststreak, filename):
"""Write score from winning player to textfile."""
with open(filename, "a") as file:
file.write(name + ";" + str(score) +
";" + str(longeststreak) + "\n")
| """
We have two functions in this class.
one to collect data from the winner and store in a text file,
and one to print this data on a scoreboard.
"""
class Highscore:
"""Highscore class."""
def show_score_board(self, filename):
"""Read textfile, format the data to display the scores."""
with open(filename, 'r') as file:
print('{:*^50}'.format(' HIGHSCORE TABLE '))
data = file.readlines()
all_scores = []
for line in data:
(name, total, streak) = line.split(';')
score = (name, int(total), streak.rstrip())
all_scores.append(score)
all_scores.sort(key=lambda y: y[1], reverse=True)
position = 1
print(' Name: Total Score: Longest Streak:')
for score in all_scores:
print(f'{position:>2}: {score[0]:15}' + f'{score[1]:<15} {score[2]}')
position = position + 1
def collect_score(self, name, score, longeststreak, filename):
"""Write score from winning player to textfile."""
with open(filename, 'a') as file:
file.write(name + ';' + str(score) + ';' + str(longeststreak) + '\n') |
'''
Created on 08.06.2014
@author: ionitadaniel19
'''
map_selenium_objects={
"SUSER":"name=login",
"SPWD":"name=password",
"SREMEMBER":"id=remember_me",
"SSUBMIT":"name=commit",
"SKEYWORD":"id=q1c",
"SSHOWANSER":"name=showanswer",
"SANSWER":"css=#answer > p"
} | """
Created on 08.06.2014
@author: ionitadaniel19
"""
map_selenium_objects = {'SUSER': 'name=login', 'SPWD': 'name=password', 'SREMEMBER': 'id=remember_me', 'SSUBMIT': 'name=commit', 'SKEYWORD': 'id=q1c', 'SSHOWANSER': 'name=showanswer', 'SANSWER': 'css=#answer > p'} |
linesize = int(input())
table = [[0 for x in range(4)] for y in range(linesize)]
queue = []
for i in range(linesize):
entry = input().split(' ')
# print(entry, 'pushed')
country = (int(entry[1]),int(entry[2]),int(entry[3]),str(entry[0]))
queue.append(country)
out = sorted(queue, key = lambda x: x[3])
out = sorted(out, key = lambda x: (x[0], x[1], x[2]), reverse=True)
for elemt in out:
print("{0} {1} {2} {3}".format(elemt[3],elemt[0],elemt[1],elemt[2])) | linesize = int(input())
table = [[0 for x in range(4)] for y in range(linesize)]
queue = []
for i in range(linesize):
entry = input().split(' ')
country = (int(entry[1]), int(entry[2]), int(entry[3]), str(entry[0]))
queue.append(country)
out = sorted(queue, key=lambda x: x[3])
out = sorted(out, key=lambda x: (x[0], x[1], x[2]), reverse=True)
for elemt in out:
print('{0} {1} {2} {3}'.format(elemt[3], elemt[0], elemt[1], elemt[2])) |
name = input('Enter your Name: ')
sen = "Hello "+ name +" ,How r u today??"
print(sen)
para = ''' hey , this is a
multiline comment.Lets see how
it works.'''
print(para)
| name = input('Enter your Name: ')
sen = 'Hello ' + name + ' ,How r u today??'
print(sen)
para = ' hey , this is a\n multiline comment.Lets see how\n it works.'
print(para) |
x, y = map(float, input().split())
exp = 0.0001
count = 1
while y - x > exp:
x += x * 0.7
count += 1
print(count) | (x, y) = map(float, input().split())
exp = 0.0001
count = 1
while y - x > exp:
x += x * 0.7
count += 1
print(count) |
#!/usr/bin/python
class helloworld:
def __init__(self):
print("Hello World!")
helloworld()
| class Helloworld:
def __init__(self):
print('Hello World!')
helloworld() |
def init():
return {
"ingest": {
"outputKafkaTopic": "telemetry.ingest",
"inputPrefix": "ingest",
"dependentSinkSources": [
{
"type": "azure",
"prefix": "raw"
},
{
"type": "azure",
"prefix": "unique"
},
{
"type": "azure",
"prefix": "channel"
},
{
"type": "azure",
"prefix": "telemetry-denormalized/raw"
},
{
"type": "druid",
"prefix": "telemetry-events"
},
{
"type": "druid",
"prefix": "telemetry-log-events"
},
{
"type": "druid",
"prefix": "telemetry-error-events"
},
{
"type": "druid",
"prefix": "telemetry-feedback-events"
}
]
},
"raw": {
"outputKafkaTopic": "telemetry.raw",
"inputPrefix": "raw",
"dependentSinkSources": [
{
"type": "azure",
"prefix": "unique"
},
{
"type": "azure",
"prefix": "channel"
},
{
"type": "azure",
"prefix": "telemetry-denormalized/raw"
},
{
"type": "druid",
"prefix": "telemetry-events"
},
{
"type": "druid",
"prefix": "telemetry-log-events"
},
{
"type": "druid",
"prefix": "telemetry-error-events"
},
{
"type": "druid",
"prefix": "telemetry-feedback-events"
}
]
},
"unique": {
"outputKafkaTopic": "telemetry.unique",
"inputPrefix": "unique",
"dependentSinkSources": [
{
"type": "azure",
"prefix": "channel"
},
{
"type": "azure",
"prefix": "telemetry-denormalized/raw"
},
{
"type": "druid",
"prefix": "telemetry-events"
},
{
"type": "druid",
"prefix": "telemetry-log-events"
},
{
"type": "druid",
"prefix": "telemetry-error-events"
},
{
"type": "druid",
"prefix": "telemetry-feedback-events"
}
]
},
"telemetry-denorm": {
"outputKafkaTopic": "telemetry.denorm",
"inputPrefix": "telemetry-denormalized/raw",
"dependentSinkSources": [
{
"type": "druid",
"prefix": "telemetry-events"
},
{
"type": "druid",
"prefix": "telemetry-feedback-events"
}
]
},
"summary-denorm": {
"outputKafkaTopic": "telemetry.denorm",
"inputPrefix": "telemetry-denormalized/summary",
"dependentSinkSources": [
{
"type": "druid",
"prefix": "summary-events"
}
]
},
"failed": {
"outputKafkaTopic": "telemetry.raw",
"inputPrefix": "failed",
"dependentSinkSources": [
],
"filters": [
{
"key": "flags",
"operator": "Is Null",
"value": ""
}
]
},
"batch-failed": {
"outputKafkaTopic": "telemetry.ingest",
"inputPrefix": "extractor-failed",
"dependentSinkSources": [
],
"filters": [
{
"key": "flags",
"operator": "Is Null",
"value": ""
}
]
},
"wfs": {
"outputKafkaTopic": "telemetry.derived",
"inputPrefix": "derived/wfs",
"dependentSinkSources": [
{
"type": "azure",
"prefix": "channel"
},
{
"type": "azure",
"prefix": "telemetry-denormalized/summary"
},
{
"type": "druid",
"prefix": "summary-events"
}
]
}
} | def init():
return {'ingest': {'outputKafkaTopic': 'telemetry.ingest', 'inputPrefix': 'ingest', 'dependentSinkSources': [{'type': 'azure', 'prefix': 'raw'}, {'type': 'azure', 'prefix': 'unique'}, {'type': 'azure', 'prefix': 'channel'}, {'type': 'azure', 'prefix': 'telemetry-denormalized/raw'}, {'type': 'druid', 'prefix': 'telemetry-events'}, {'type': 'druid', 'prefix': 'telemetry-log-events'}, {'type': 'druid', 'prefix': 'telemetry-error-events'}, {'type': 'druid', 'prefix': 'telemetry-feedback-events'}]}, 'raw': {'outputKafkaTopic': 'telemetry.raw', 'inputPrefix': 'raw', 'dependentSinkSources': [{'type': 'azure', 'prefix': 'unique'}, {'type': 'azure', 'prefix': 'channel'}, {'type': 'azure', 'prefix': 'telemetry-denormalized/raw'}, {'type': 'druid', 'prefix': 'telemetry-events'}, {'type': 'druid', 'prefix': 'telemetry-log-events'}, {'type': 'druid', 'prefix': 'telemetry-error-events'}, {'type': 'druid', 'prefix': 'telemetry-feedback-events'}]}, 'unique': {'outputKafkaTopic': 'telemetry.unique', 'inputPrefix': 'unique', 'dependentSinkSources': [{'type': 'azure', 'prefix': 'channel'}, {'type': 'azure', 'prefix': 'telemetry-denormalized/raw'}, {'type': 'druid', 'prefix': 'telemetry-events'}, {'type': 'druid', 'prefix': 'telemetry-log-events'}, {'type': 'druid', 'prefix': 'telemetry-error-events'}, {'type': 'druid', 'prefix': 'telemetry-feedback-events'}]}, 'telemetry-denorm': {'outputKafkaTopic': 'telemetry.denorm', 'inputPrefix': 'telemetry-denormalized/raw', 'dependentSinkSources': [{'type': 'druid', 'prefix': 'telemetry-events'}, {'type': 'druid', 'prefix': 'telemetry-feedback-events'}]}, 'summary-denorm': {'outputKafkaTopic': 'telemetry.denorm', 'inputPrefix': 'telemetry-denormalized/summary', 'dependentSinkSources': [{'type': 'druid', 'prefix': 'summary-events'}]}, 'failed': {'outputKafkaTopic': 'telemetry.raw', 'inputPrefix': 'failed', 'dependentSinkSources': [], 'filters': [{'key': 'flags', 'operator': 'Is Null', 'value': ''}]}, 'batch-failed': {'outputKafkaTopic': 'telemetry.ingest', 'inputPrefix': 'extractor-failed', 'dependentSinkSources': [], 'filters': [{'key': 'flags', 'operator': 'Is Null', 'value': ''}]}, 'wfs': {'outputKafkaTopic': 'telemetry.derived', 'inputPrefix': 'derived/wfs', 'dependentSinkSources': [{'type': 'azure', 'prefix': 'channel'}, {'type': 'azure', 'prefix': 'telemetry-denormalized/summary'}, {'type': 'druid', 'prefix': 'summary-events'}]}} |
#!/usr/bin/python
# -*- coding: utf-8 -*-
RECOVER_ITEM = [
("n 't ", "n't ")
]
def recover_quotewords(text):
for before, after in RECOVER_ITEM:
text = text.replace(before, after)
return text
| recover_item = [("n 't ", "n't ")]
def recover_quotewords(text):
for (before, after) in RECOVER_ITEM:
text = text.replace(before, after)
return text |
names = [
'Christal',
'Ray',
'Ron'
]
print(names)
| names = ['Christal', 'Ray', 'Ron']
print(names) |
def solution(numBottles,numExchange):
finalsum = numBottles
emptyBottles = numBottles
numBottles = 0
while (emptyBottles >= numExchange):
numBottles = emptyBottles // numExchange
emptyBottles -= emptyBottles // numExchange * numExchange
finalsum += numBottles
emptyBottles += numBottles
print (finalsum)
numBottles = int(input("numBottles = "))
numExchange = int(input("numExchange = "))
solution(numBottles,numExchange) | def solution(numBottles, numExchange):
finalsum = numBottles
empty_bottles = numBottles
num_bottles = 0
while emptyBottles >= numExchange:
num_bottles = emptyBottles // numExchange
empty_bottles -= emptyBottles // numExchange * numExchange
finalsum += numBottles
empty_bottles += numBottles
print(finalsum)
num_bottles = int(input('numBottles = '))
num_exchange = int(input('numExchange = '))
solution(numBottles, numExchange) |
def undistort_image(image, objectpoints, imagepoints):
# Get image size
img_size = (image.shape[1], image.shape[0])
# Calibrate camera based on objectpoints, imagepoints, and image size
ret, mtx, dist, rvecs, tvecs = cv2.calibrateCamera(objectpoints, imagepoints, img_size, None, None)
# Call cv2.undistort
dst = cv2.undistort(image, mtx, dist, None, mtx)
return dst
def get_shresholded_img(image,grad_thresh,s_thresh):
gray = cv2.cvtColor(image, cv2.COLOR_RGB2GRAY)
#process the x direction gradient
sobelx = cv2.Sobel(gray, cv2.CV_64F, 1, 0) # Take the derivative in x
abs_sobelx = np.absolute(sobelx) # Absolute x derivative to accentuate lines away from horizontal
scaled_sobel = np.uint8(255*abs_sobelx/np.max(abs_sobelx))
sxbinary = np.zeros_like(scaled_sobel)
sxbinary[(scaled_sobel >= grad_thresh[0]) & (scaled_sobel <= grad_thresh[1])] = 1
#process the HIS s channel
hls = cv2.cvtColor(img, cv2.COLOR_RGB2HLS)
s_channel = hls[:,:,2]
s_binary = np.zeros_like(s_channel)
s_binary[(s_channel >= s_thresh[0]) & (s_channel <= s_thresh[1])] = 1
# color_binary = np.dstack(( np.zeros_like(sxbinary), sxbinary, s_binary)) * 255
# one can show it out to see the colored binary
# Combine the two binary thresholds
combined_binary = np.zeros_like(sxbinary)
combined_binary[(s_binary == 1) | (sxbinary == 1)] = 1
return combined_binary
def warp_image_to_birdseye_view(image,corners):
img_size=(image.shape[1], image.shape[0])
#choose an offset to determine the distination for birdseye view area
offset = 150
src = np.float32(
[corners[0],
corners[1],
corners[2],
corners[3]])
#decide a place to place the birdviewed image, get these points by testing an image
dst = np.float32([
[offset, 0],
[offset, img_size[1]],
[img_size[0] - offset, img_size[1]],
[img_size[0] - offset,0]])
# Get perspective transform
perspectiveTransform = cv2.getPerspectiveTransform(src, dst)
# Warp perspective
warped = cv2.warpPerspective(image, perspectiveTransform, img_size, flags=cv2.INTER_LINEAR)
# Get the destination perspective transform
Minv = cv2.getPerspectiveTransform(dst, src)
return warped, Minv
def find_lane_lines(warped_binary_image, testing=False):
if testing == True:
# Create an output image to draw on and visualize the result
output_image = np.dstack((warped_binary_image, warped_binary_image, warped_binary_image))*255
# Create histogram to find the lanes by identifying the peaks in the histogram
histogram = np.sum(warped_binary_image[int(warped_binary_image.shape[0]/2):,:], axis=0)
# Find the peak of the left and right halves of the histogram
midpoint = np.int(histogram.shape[0]/2)
left_x_base = np.argmax(histogram[:midpoint])
right_x_base = np.argmax(histogram[midpoint:]) + midpoint
# Choose the number of sliding windows
number_of_windows = 9
# Set height of windows
window_height = np.int(warped_binary_image.shape[0]/number_of_windows)
# Identify the x and y positions of all nonzero pixels in the image
nonzero_pixels = warped_binary_image.nonzero()
nonzero_y_pixels = np.array(nonzero_pixels[0])
nonzero_x_pixels = np.array(nonzero_pixels[1])
# Current positions to be updated for each window
left_x_current = left_x_base
right_x_current = right_x_base
# Set the width of the windows +/- margin
margin = 100
# Set minimum number of pixels found to recenter window
minpix = 50
# Create empty lists to receive left and right lane pixel indices
left_lane_inds = []
right_lane_inds = []
# Step through the windows one by one
for window in range(number_of_windows):
# Identify window boundaries in x and y (and right and left)
win_y_low = warped_binary_image.shape[0] - (window+1)*window_height
win_y_high = warped_binary_image.shape[0] - window*window_height
win_x_left_low = left_x_current - margin
win_x_left_high = left_x_current + margin
win_x_right_low = right_x_current - margin
win_x_right_high = right_x_current + margin
if testing == True:
# Draw the windows on the visualization image
cv2.rectangle(output_image, (win_x_left_low,win_y_low), (win_x_left_high,win_y_high), (0,255,0), 2)
cv2.rectangle(output_image, (win_x_right_low,win_y_low), (win_x_right_high,win_y_high), (0,255,0), 2)
# Identify the nonzero pixels in x and y within the window
left_inds = ((nonzero_y_pixels >= win_y_low) & (nonzero_y_pixels < win_y_high) & (nonzero_x_pixels >= win_x_left_low) & (nonzero_x_pixels < win_x_left_high)).nonzero()[0]
right_inds = ((nonzero_y_pixels >= win_y_low) & (nonzero_y_pixels < win_y_high) & (nonzero_x_pixels >= win_x_right_low) & (nonzero_x_pixels < win_x_right_high)).nonzero()[0]
# Append these indices to the lists
left_lane_inds.append(left_inds)
right_lane_inds.append(right_inds)
# If you found > minpix pixels, recenter next window on their mean position
if len(left_inds) > minpix:
left_x_current = np.int(np.mean(nonzero_x_pixels[left_inds]))
if len(right_inds) > minpix:
right_x_current = np.int(np.mean(nonzero_x_pixels[right_inds]))
# Concatenate the arrays of indices
left_lane_inds = np.concatenate(left_lane_inds)
right_lane_inds = np.concatenate(right_lane_inds)
# Extract left and right line pixel positions
left_x = nonzero_x_pixels[left_lane_inds]
left_y = nonzero_y_pixels[left_lane_inds]
right_x = nonzero_x_pixels[right_lane_inds]
right_y = nonzero_y_pixels[right_lane_inds]
# Fit a second order polynomial to each
left_fit = np.polyfit(left_y, left_x, 2)
right_fit = np.polyfit(right_y, right_x, 2)
# Generate x and y values for plotting
plot_y = np.linspace(0, warped_binary_image.shape[0]-1, warped_binary_image.shape[0] )
left_fit_x = left_fit[0]*plot_y**2 + left_fit[1]*plot_y + left_fit[2]
right_fit_x = right_fit[0]*plot_y**2 + right_fit[1]*plot_y + right_fit[2]
# Get binary warped image size
image_size = warped_binary_image.shape
# Get max of plot_y
y_eval = np.max(plot_y)
# Define conversions in x and y from pixels space to meters
y_m_per_pix = 30/720
x_m_per_pix = 3.7/700
# Fit new polynomials to x,y in world space
left_fit_cr = np.polyfit(left_y*y_m_per_pix, left_x*x_m_per_pix, 2)
right_fit_cr = np.polyfit(right_y*y_m_per_pix, right_x*x_m_per_pix, 2)
# Calculate radius of curve
left_curve = ((1+(2*left_fit_cr[0]*y_eval*y_m_per_pix+left_fit_cr[1])**2)**1.5)/np.absolute(2*left_fit_cr[0])
right_curve = ((1+(2*right_fit_cr[0]*y_eval*y_m_per_pix+right_fit_cr[1])**2)**1.5)/np.absolute(2*right_fit_cr[0])
# Calculate lane deviation from center of lane
scene_height = image_size[0] * y_m_per_pix
scene_width = image_size[1] * x_m_per_pix
# Calculate the intercept points at the bottom of our image
left_intercept = left_fit_cr[0] * scene_height ** 2 + left_fit_cr[1] * scene_height + left_fit_cr[2]
right_intercept = right_fit_cr[0] * scene_height ** 2 + right_fit_cr[1] * scene_height + right_fit_cr[2]
center = (left_intercept + right_intercept) / 2.0
# Use intercept points to calculate the lane deviation of the vehicle
lane_deviation = (center - scene_width / 2.0)
if testing == True:
output_image[nonzero_y_pixels[left_lane_inds], nonzero_x_pixels[left_lane_inds]] = [255, 0, 0]
output_image[nonzero_y_pixels[right_lane_inds], nonzero_x_pixels[right_lane_inds]] = [0, 0, 255]
return left_fit_x, right_fit_x, plot_y, left_fit, right_fit, left_curve, right_curve, lane_deviation, output_image
else:
return left_fit_x, right_fit_x, plot_y, left_curve, right_curve, lane_deviation
def draw_lane_lines(warped_binary_image, undistorted_image, Minv):
# Create a blank image to draw the lines on
warp_zero = np.zeros_like(warped_binary_image).astype(np.uint8)
color_warp = np.dstack((warp_zero, warp_zero, warp_zero))
left_fit_x, right_fit_x, ploty, left_radius, right_radius, lane_deviation=find_lane_lines(warped_binary_image)
# Recast the x and y points into usable format for cv2.fillPoly()
pts_left = np.array([np.transpose(np.vstack([left_fit_x, ploty]))])
pts_right = np.array([np.flipud(np.transpose(np.vstack([right_fit_x, ploty])))])
pts = np.hstack((pts_left, pts_right))
# Draw the lane onto the warped blank image with green color
cv2.fillPoly(color_warp, np.int_([pts]), (0, 255, 0))
# Warp the blank back to original image space using inverse perspective matrix (Minv)
unwarp = cv2.warpPerspective(color_warp, Minv, (undistorted_image.shape[1], undistorted_image.shape[0]))
# Combine the result with the original image
result = cv2.addWeighted(undistorted_image, 1, unwarp, 0.3, 0)
# Write text on image
curvature_text = "Curvature: Left = " + str(np.round(left_radius, 2)) + ", Right = " + str(np.round(right_radius, 2))
font = cv2.FONT_HERSHEY_TRIPLEX
cv2.putText(result, curvature_text, (30, 60), font, 1, (0,255,0), 2)
deviation_text = "Lane deviation from center = {:.2f} m".format(lane_deviation)
font = cv2.FONT_HERSHEY_TRIPLEX
cv2.putText(result, deviation_text, (30, 90), font, 1, (0,255,0), 2)
return result
#the pipeline function
def process_image(image):
undistorted = undistort_image(image, objpoints, imgpoints)
combined_binary = get_shresholded_img(undistorted,grad_thresh,s_thresh)
binary_warped, Minv = warp_image_to_birdseye_view(combined_binary,corners)
lane_lines_img = draw_lane_lines(binary_warped, undistorted, Minv)
return lane_lines_img
| def undistort_image(image, objectpoints, imagepoints):
img_size = (image.shape[1], image.shape[0])
(ret, mtx, dist, rvecs, tvecs) = cv2.calibrateCamera(objectpoints, imagepoints, img_size, None, None)
dst = cv2.undistort(image, mtx, dist, None, mtx)
return dst
def get_shresholded_img(image, grad_thresh, s_thresh):
gray = cv2.cvtColor(image, cv2.COLOR_RGB2GRAY)
sobelx = cv2.Sobel(gray, cv2.CV_64F, 1, 0)
abs_sobelx = np.absolute(sobelx)
scaled_sobel = np.uint8(255 * abs_sobelx / np.max(abs_sobelx))
sxbinary = np.zeros_like(scaled_sobel)
sxbinary[(scaled_sobel >= grad_thresh[0]) & (scaled_sobel <= grad_thresh[1])] = 1
hls = cv2.cvtColor(img, cv2.COLOR_RGB2HLS)
s_channel = hls[:, :, 2]
s_binary = np.zeros_like(s_channel)
s_binary[(s_channel >= s_thresh[0]) & (s_channel <= s_thresh[1])] = 1
combined_binary = np.zeros_like(sxbinary)
combined_binary[(s_binary == 1) | (sxbinary == 1)] = 1
return combined_binary
def warp_image_to_birdseye_view(image, corners):
img_size = (image.shape[1], image.shape[0])
offset = 150
src = np.float32([corners[0], corners[1], corners[2], corners[3]])
dst = np.float32([[offset, 0], [offset, img_size[1]], [img_size[0] - offset, img_size[1]], [img_size[0] - offset, 0]])
perspective_transform = cv2.getPerspectiveTransform(src, dst)
warped = cv2.warpPerspective(image, perspectiveTransform, img_size, flags=cv2.INTER_LINEAR)
minv = cv2.getPerspectiveTransform(dst, src)
return (warped, Minv)
def find_lane_lines(warped_binary_image, testing=False):
if testing == True:
output_image = np.dstack((warped_binary_image, warped_binary_image, warped_binary_image)) * 255
histogram = np.sum(warped_binary_image[int(warped_binary_image.shape[0] / 2):, :], axis=0)
midpoint = np.int(histogram.shape[0] / 2)
left_x_base = np.argmax(histogram[:midpoint])
right_x_base = np.argmax(histogram[midpoint:]) + midpoint
number_of_windows = 9
window_height = np.int(warped_binary_image.shape[0] / number_of_windows)
nonzero_pixels = warped_binary_image.nonzero()
nonzero_y_pixels = np.array(nonzero_pixels[0])
nonzero_x_pixels = np.array(nonzero_pixels[1])
left_x_current = left_x_base
right_x_current = right_x_base
margin = 100
minpix = 50
left_lane_inds = []
right_lane_inds = []
for window in range(number_of_windows):
win_y_low = warped_binary_image.shape[0] - (window + 1) * window_height
win_y_high = warped_binary_image.shape[0] - window * window_height
win_x_left_low = left_x_current - margin
win_x_left_high = left_x_current + margin
win_x_right_low = right_x_current - margin
win_x_right_high = right_x_current + margin
if testing == True:
cv2.rectangle(output_image, (win_x_left_low, win_y_low), (win_x_left_high, win_y_high), (0, 255, 0), 2)
cv2.rectangle(output_image, (win_x_right_low, win_y_low), (win_x_right_high, win_y_high), (0, 255, 0), 2)
left_inds = ((nonzero_y_pixels >= win_y_low) & (nonzero_y_pixels < win_y_high) & (nonzero_x_pixels >= win_x_left_low) & (nonzero_x_pixels < win_x_left_high)).nonzero()[0]
right_inds = ((nonzero_y_pixels >= win_y_low) & (nonzero_y_pixels < win_y_high) & (nonzero_x_pixels >= win_x_right_low) & (nonzero_x_pixels < win_x_right_high)).nonzero()[0]
left_lane_inds.append(left_inds)
right_lane_inds.append(right_inds)
if len(left_inds) > minpix:
left_x_current = np.int(np.mean(nonzero_x_pixels[left_inds]))
if len(right_inds) > minpix:
right_x_current = np.int(np.mean(nonzero_x_pixels[right_inds]))
left_lane_inds = np.concatenate(left_lane_inds)
right_lane_inds = np.concatenate(right_lane_inds)
left_x = nonzero_x_pixels[left_lane_inds]
left_y = nonzero_y_pixels[left_lane_inds]
right_x = nonzero_x_pixels[right_lane_inds]
right_y = nonzero_y_pixels[right_lane_inds]
left_fit = np.polyfit(left_y, left_x, 2)
right_fit = np.polyfit(right_y, right_x, 2)
plot_y = np.linspace(0, warped_binary_image.shape[0] - 1, warped_binary_image.shape[0])
left_fit_x = left_fit[0] * plot_y ** 2 + left_fit[1] * plot_y + left_fit[2]
right_fit_x = right_fit[0] * plot_y ** 2 + right_fit[1] * plot_y + right_fit[2]
image_size = warped_binary_image.shape
y_eval = np.max(plot_y)
y_m_per_pix = 30 / 720
x_m_per_pix = 3.7 / 700
left_fit_cr = np.polyfit(left_y * y_m_per_pix, left_x * x_m_per_pix, 2)
right_fit_cr = np.polyfit(right_y * y_m_per_pix, right_x * x_m_per_pix, 2)
left_curve = (1 + (2 * left_fit_cr[0] * y_eval * y_m_per_pix + left_fit_cr[1]) ** 2) ** 1.5 / np.absolute(2 * left_fit_cr[0])
right_curve = (1 + (2 * right_fit_cr[0] * y_eval * y_m_per_pix + right_fit_cr[1]) ** 2) ** 1.5 / np.absolute(2 * right_fit_cr[0])
scene_height = image_size[0] * y_m_per_pix
scene_width = image_size[1] * x_m_per_pix
left_intercept = left_fit_cr[0] * scene_height ** 2 + left_fit_cr[1] * scene_height + left_fit_cr[2]
right_intercept = right_fit_cr[0] * scene_height ** 2 + right_fit_cr[1] * scene_height + right_fit_cr[2]
center = (left_intercept + right_intercept) / 2.0
lane_deviation = center - scene_width / 2.0
if testing == True:
output_image[nonzero_y_pixels[left_lane_inds], nonzero_x_pixels[left_lane_inds]] = [255, 0, 0]
output_image[nonzero_y_pixels[right_lane_inds], nonzero_x_pixels[right_lane_inds]] = [0, 0, 255]
return (left_fit_x, right_fit_x, plot_y, left_fit, right_fit, left_curve, right_curve, lane_deviation, output_image)
else:
return (left_fit_x, right_fit_x, plot_y, left_curve, right_curve, lane_deviation)
def draw_lane_lines(warped_binary_image, undistorted_image, Minv):
warp_zero = np.zeros_like(warped_binary_image).astype(np.uint8)
color_warp = np.dstack((warp_zero, warp_zero, warp_zero))
(left_fit_x, right_fit_x, ploty, left_radius, right_radius, lane_deviation) = find_lane_lines(warped_binary_image)
pts_left = np.array([np.transpose(np.vstack([left_fit_x, ploty]))])
pts_right = np.array([np.flipud(np.transpose(np.vstack([right_fit_x, ploty])))])
pts = np.hstack((pts_left, pts_right))
cv2.fillPoly(color_warp, np.int_([pts]), (0, 255, 0))
unwarp = cv2.warpPerspective(color_warp, Minv, (undistorted_image.shape[1], undistorted_image.shape[0]))
result = cv2.addWeighted(undistorted_image, 1, unwarp, 0.3, 0)
curvature_text = 'Curvature: Left = ' + str(np.round(left_radius, 2)) + ', Right = ' + str(np.round(right_radius, 2))
font = cv2.FONT_HERSHEY_TRIPLEX
cv2.putText(result, curvature_text, (30, 60), font, 1, (0, 255, 0), 2)
deviation_text = 'Lane deviation from center = {:.2f} m'.format(lane_deviation)
font = cv2.FONT_HERSHEY_TRIPLEX
cv2.putText(result, deviation_text, (30, 90), font, 1, (0, 255, 0), 2)
return result
def process_image(image):
undistorted = undistort_image(image, objpoints, imgpoints)
combined_binary = get_shresholded_img(undistorted, grad_thresh, s_thresh)
(binary_warped, minv) = warp_image_to_birdseye_view(combined_binary, corners)
lane_lines_img = draw_lane_lines(binary_warped, undistorted, Minv)
return lane_lines_img |
"""
The :mod:`fatf.utils.data` module holds data tools and data sets.
"""
# Author: Kacper Sokol <k.sokol@bristol.ac.uk>
# License: new BSD
| """
The :mod:`fatf.utils.data` module holds data tools and data sets.
""" |
largest=None
smallest=None
while True:
number=input("Enter a number:")
if number == "done":
break
try:
number=int(number)
if largest == None:
largest = number
elif largest < number:
largest = number
if smallest==None:
smallest=number
elif smallest>number:
smallest=number
except ValueError:
print("Invalid input")
print ("Maximum is", largest)
print ("Minimum is", smallest)
| largest = None
smallest = None
while True:
number = input('Enter a number:')
if number == 'done':
break
try:
number = int(number)
if largest == None:
largest = number
elif largest < number:
largest = number
if smallest == None:
smallest = number
elif smallest > number:
smallest = number
except ValueError:
print('Invalid input')
print('Maximum is', largest)
print('Minimum is', smallest) |
class UsdValue(float):
def __init__(self, v) -> None:
super().__init__()
class UsdPrice(float):
def __init__(self, v) -> None:
super().__init__() | class Usdvalue(float):
def __init__(self, v) -> None:
super().__init__()
class Usdprice(float):
def __init__(self, v) -> None:
super().__init__() |
def filter(fname,data):
list=[]
for i in range(len(data)):
f=fname(data[i])
if f==True:
list.append(data[i])
return list
def map(fname,newdata):
list=[]
for i in range(len(newdata)):
f=fname(newdata[i])
list.append(f)
return list
def reduce(fname,incrementdata):
list=[]
for i in range(len(incrementdata)):
if (len(incrementdata))>=2:
f=fname(incrementdata[0],incrementdata[1])
del incrementdata[0]
del incrementdata[0]
incrementdata.append(f)
return incrementdata[0]
| def filter(fname, data):
list = []
for i in range(len(data)):
f = fname(data[i])
if f == True:
list.append(data[i])
return list
def map(fname, newdata):
list = []
for i in range(len(newdata)):
f = fname(newdata[i])
list.append(f)
return list
def reduce(fname, incrementdata):
list = []
for i in range(len(incrementdata)):
if len(incrementdata) >= 2:
f = fname(incrementdata[0], incrementdata[1])
del incrementdata[0]
del incrementdata[0]
incrementdata.append(f)
return incrementdata[0] |
#
numbers = [str(x) for x in range(32)]
letters = [chr(x) for x in range(97, 123)]
crate = '''
sandbox crate
map {boot: @init}
/*initialize utility vars and register vars*/
service init {
writer = 0
alpha = 0
beta = 0
status = 0'''
for letter in letters:
crate += '\n ' + letter + ' = 0'
crate += '''
}
/*map operator service to exec jump table*/
map {
copy: @copy
add: @add
sub: @sub
not: @not
or: @or
and: @and
eq: @eq
ne: @ne
gt: @gt
lt: @lt
gte: @gte
lte: @lte
unary: @status_alpha
}
service copy { @status_zero alpha = beta @writer}
service add { @status_zero alpha = alpha + beta @writer}
service sub { @status_zero alpha = alpha - beta @writer}
service not { @status_zero alpha = !beta @writer}
service or { @status_zero alpha = alpha | beta @writer}
service and { @status_zero alpha = alpha & beta @writer}
service eq { @status_zero if (alpha == beta) {[true]} else {[false]}}
service ne { @status_zero if (alpha != beta) {[true]} else {[false]}}
service gt { @status_zero if (alpha > beta) {[true]} else {[false]}}
service lt { @status_zero if (alpha < beta) {[true]} else {[false]}}
service gte { @status_zero if (alpha >= beta) {[true]} else {[false]}}
service lte { @status_zero if (alpha <= beta) {[true]} else {[false]}}
service status_zero {
status = 0
}
service status_alpha {
status = 1
}
service status_beta {
status = 2
}
service writer {
jump (writer) {'''
for letter in letters:
crate += '{ ' + letter + ' = alpha } '
crate += '''}
}
map {jump: @jump}
service jump {
jump (z) {'''
for number in numbers:
crate += '{ [ jump' + number + '] } '
crate += '''}
}
map {printme : @printme}
service printme { ['''
for number in numbers:
crate += '''alias jump''' + number + ''' echo ''' + number + ''';'''
crate += '''jump]
}'''
for letter in letters:
crate += '''
map {''' + letter + ' : @' + letter + '''}
service ''' + letter + ''' { jump (status) {
{ alpha = ''' + letter + ''' @status_alpha}
{ beta = ''' + letter + ''' @status_beta}
{ writer = ''' + str(ord(letter) - 97) + ''' }
}
}'''
for number in numbers:
crate += '''
map {delete''' + number + ' : @delete' + number + '''}
service delete''' + number + ''' { jump (status) {
{ alpha = ''' + number + ''' @status_alpha}
{ beta = ''' + number + ''' @status_beta}
{ }
}
}'''
print(crate)
| numbers = [str(x) for x in range(32)]
letters = [chr(x) for x in range(97, 123)]
crate = '\nsandbox crate\n\nmap {boot: @init}\n/*initialize utility vars and register vars*/\nservice init {\n writer = 0\n alpha = 0\n beta = 0\n status = 0'
for letter in letters:
crate += '\n ' + letter + ' = 0'
crate += '\n}\n\n/*map operator service to exec jump table*/\n\nmap {\n copy: @copy\n add: @add\n sub: @sub\n not: @not\n or: @or\n and: @and\n eq: @eq\n ne: @ne\n gt: @gt\n lt: @lt\n gte: @gte\n lte: @lte\n unary: @status_alpha\n}\n\nservice copy { @status_zero alpha = beta @writer}\n\nservice add { @status_zero alpha = alpha + beta @writer}\n\nservice sub { @status_zero alpha = alpha - beta @writer}\n\nservice not { @status_zero alpha = !beta @writer}\n\nservice or { @status_zero alpha = alpha | beta @writer}\n\nservice and { @status_zero alpha = alpha & beta @writer}\n\nservice eq { @status_zero if (alpha == beta) {[true]} else {[false]}}\n\nservice ne { @status_zero if (alpha != beta) {[true]} else {[false]}}\n\nservice gt { @status_zero if (alpha > beta) {[true]} else {[false]}}\n\nservice lt { @status_zero if (alpha < beta) {[true]} else {[false]}}\n\nservice gte { @status_zero if (alpha >= beta) {[true]} else {[false]}}\n\nservice lte { @status_zero if (alpha <= beta) {[true]} else {[false]}}\n\nservice status_zero {\n status = 0\n}\n\nservice status_alpha {\n status = 1\n}\n\nservice status_beta {\n status = 2\n}\n\nservice writer {\n jump (writer) {'
for letter in letters:
crate += '{ ' + letter + ' = alpha } '
crate += '}\n}\n\nmap {jump: @jump}\nservice jump {\n jump (z) {'
for number in numbers:
crate += '{ [ jump' + number + '] } '
crate += '}\n}\n\n\nmap {printme : @printme}\nservice printme { ['
for number in numbers:
crate += 'alias jump' + number + ' echo ' + number + ';'
crate += 'jump]\n}'
for letter in letters:
crate += '\nmap {' + letter + ' : @' + letter + '}\nservice ' + letter + ' { jump (status) {\n { alpha = ' + letter + ' @status_alpha}\n { beta = ' + letter + ' @status_beta}\n { writer = ' + str(ord(letter) - 97) + ' }\n } \n}'
for number in numbers:
crate += '\nmap {delete' + number + ' : @delete' + number + '}\nservice delete' + number + ' { jump (status) {\n { alpha = ' + number + ' @status_alpha}\n { beta = ' + number + ' @status_beta}\n { }\n }\n}'
print(crate) |
# coding: utf-8
# http://www.crummy.com/software/BeautifulSoup/bs4/doc/#installing-a-parser
DEFAULT_PARSER = 'lxml'
ALLOWED_CONTENT_TYPES = [
'text/html',
'image/',
]
FINDER_PIPELINE = (
'haul.finders.pipeline.html.img_src_finder',
'haul.finders.pipeline.html.a_href_finder',
'haul.finders.pipeline.css.background_image_finder',
)
EXTENDER_PIPELINE = (
'haul.extenders.pipeline.google.blogspot_s1600_extender',
'haul.extenders.pipeline.google.ggpht_s1600_extender',
'haul.extenders.pipeline.google.googleusercontent_s1600_extender',
'haul.extenders.pipeline.pinterest.original_image_extender',
'haul.extenders.pipeline.wordpress.original_image_extender',
'haul.extenders.pipeline.tumblr.media_1280_extender',
'haul.extenders.pipeline.tumblr.avatar_128_extender',
)
SHOULD_JOIN_URL = True
| default_parser = 'lxml'
allowed_content_types = ['text/html', 'image/']
finder_pipeline = ('haul.finders.pipeline.html.img_src_finder', 'haul.finders.pipeline.html.a_href_finder', 'haul.finders.pipeline.css.background_image_finder')
extender_pipeline = ('haul.extenders.pipeline.google.blogspot_s1600_extender', 'haul.extenders.pipeline.google.ggpht_s1600_extender', 'haul.extenders.pipeline.google.googleusercontent_s1600_extender', 'haul.extenders.pipeline.pinterest.original_image_extender', 'haul.extenders.pipeline.wordpress.original_image_extender', 'haul.extenders.pipeline.tumblr.media_1280_extender', 'haul.extenders.pipeline.tumblr.avatar_128_extender')
should_join_url = True |
# pythran export _brief_loop(float64[:,:], uint8[:,:],
# intp[:,:], int[:,:], int[:,:])
def _brief_loop(image, descriptors, keypoints, pos0, pos1):
for k in range(len(keypoints)):
kr, kc = keypoints[k]
for p in range(len(pos0)):
pr0, pc0 = pos0[p]
pr1, pc1 = pos1[p]
descriptors[k, p] = (image[kr + pr0, kc + pc0]
< image[kr + pr1, kc + pc1])
| def _brief_loop(image, descriptors, keypoints, pos0, pos1):
for k in range(len(keypoints)):
(kr, kc) = keypoints[k]
for p in range(len(pos0)):
(pr0, pc0) = pos0[p]
(pr1, pc1) = pos1[p]
descriptors[k, p] = image[kr + pr0, kc + pc0] < image[kr + pr1, kc + pc1] |
factors = {
1:{
1:"I",5:"I",9:"I",13:"I",17:"I",21:"I",25:"I",29:"I",33:"I",37:"I",41:"I",45:"I",49:"I",53:"I",57:"I"
, 2:"S", 6:"S", 10:"S", 14:"S", 18:"S", 22:"S", 26:"S",30:"S" ,34:"S",38:"S",42:"S",46:"S",50:"S",54:"S",58:"S"
, 3:"T", 7:"T" , 11:"T", 15:"T", 19:"T",23:"T" ,27:"T", 31:"T" ,35:"T" ,39:"T",43:"T",47:"T",51:"T" ,55:"T",59:"T"
, 4:"P", 8:"P", 12:"P", 16:"P", 20:"P", 24:"P", 28:"P", 32:"P", 36:"P", 40:"P", 44:"P", 48:"P", 52:"P", 56:"P", 60:"P"
}
,
2 :{
1:"E",5:"E",9:"E",13:"E",17:"E",21:"E",25:"E",29:"E",33:"E",37:"E",41:"E",45:"E",49:"E",53:"E",57:"E"
, 2:"N", 6:"N", 10:"N", 14:"N", 18:"N", 22:"N", 26:"N",30:"N" ,34:"N",38:"N",42:"N",46:"N",50:"N",54:"N",58:"N"
, 3:"F", 7:"F" , 11:"F", 15:"F", 19:"F",23:"F" ,27:"F", 31:"F" ,35:"F" ,39:"F",43:"F",47:"F",51:"F" ,55:"F",59:"F"
, 4:"J", 8:"J", 12:"J", 16:"J", 20:"J", 24:"J", 28:"J", 32:"J", 36:"J", 40:"J", 44:"J", 48:"J", 52:"J", 56:"J", 60:"J"
}
}
factors_names = ('E', 'I', 'S', 'N', 'F', 'T', 'P', 'J', 'report')
factors_group = (('E', 'I'), ('S', 'N'), ('F', 'T'), ('P', 'J')) | factors = {1: {1: 'I', 5: 'I', 9: 'I', 13: 'I', 17: 'I', 21: 'I', 25: 'I', 29: 'I', 33: 'I', 37: 'I', 41: 'I', 45: 'I', 49: 'I', 53: 'I', 57: 'I', 2: 'S', 6: 'S', 10: 'S', 14: 'S', 18: 'S', 22: 'S', 26: 'S', 30: 'S', 34: 'S', 38: 'S', 42: 'S', 46: 'S', 50: 'S', 54: 'S', 58: 'S', 3: 'T', 7: 'T', 11: 'T', 15: 'T', 19: 'T', 23: 'T', 27: 'T', 31: 'T', 35: 'T', 39: 'T', 43: 'T', 47: 'T', 51: 'T', 55: 'T', 59: 'T', 4: 'P', 8: 'P', 12: 'P', 16: 'P', 20: 'P', 24: 'P', 28: 'P', 32: 'P', 36: 'P', 40: 'P', 44: 'P', 48: 'P', 52: 'P', 56: 'P', 60: 'P'}, 2: {1: 'E', 5: 'E', 9: 'E', 13: 'E', 17: 'E', 21: 'E', 25: 'E', 29: 'E', 33: 'E', 37: 'E', 41: 'E', 45: 'E', 49: 'E', 53: 'E', 57: 'E', 2: 'N', 6: 'N', 10: 'N', 14: 'N', 18: 'N', 22: 'N', 26: 'N', 30: 'N', 34: 'N', 38: 'N', 42: 'N', 46: 'N', 50: 'N', 54: 'N', 58: 'N', 3: 'F', 7: 'F', 11: 'F', 15: 'F', 19: 'F', 23: 'F', 27: 'F', 31: 'F', 35: 'F', 39: 'F', 43: 'F', 47: 'F', 51: 'F', 55: 'F', 59: 'F', 4: 'J', 8: 'J', 12: 'J', 16: 'J', 20: 'J', 24: 'J', 28: 'J', 32: 'J', 36: 'J', 40: 'J', 44: 'J', 48: 'J', 52: 'J', 56: 'J', 60: 'J'}}
factors_names = ('E', 'I', 'S', 'N', 'F', 'T', 'P', 'J', 'report')
factors_group = (('E', 'I'), ('S', 'N'), ('F', 'T'), ('P', 'J')) |
wkidInfo = {
'4326':{'type':'gcs', 'path':'World/WGS 1984.prj'},
'102100':{'type':'pcs', 'path':r'World/WGS 1984 Web Mercator (auxiliary sphere).prj'},
'3857' : {'type':'pcs', 'path':r'World/WGS 1984 Web Mercator (auxiliary sphere).prj'}
} | wkid_info = {'4326': {'type': 'gcs', 'path': 'World/WGS 1984.prj'}, '102100': {'type': 'pcs', 'path': 'World/WGS 1984 Web Mercator (auxiliary sphere).prj'}, '3857': {'type': 'pcs', 'path': 'World/WGS 1984 Web Mercator (auxiliary sphere).prj'}} |
#import ctypes
#import GdaImport
#import matplotlib.pyplot as plt
# getting example
# gjden
def GDA_MAIN(gda_obj):
per='the apk permission:\n'
# per+=gda_obj.GetAppString()
# per+=gda_obj.GetCert()
# per+=gda_obj.GetUrlString()
#
per+=gda_obj.GetPermission()
gda_obj.log(per)
tofile = open('out.txt','w')
tofile.write(per)
tofile.close()
return 0
| def gda_main(gda_obj):
per = 'the apk permission:\n'
per += gda_obj.GetPermission()
gda_obj.log(per)
tofile = open('out.txt', 'w')
tofile.write(per)
tofile.close()
return 0 |
# Copyright 2016 The Chromium Authors. All rights reserved.
# Use of this source code is governed by a BSD-style license that can be
# found in the LICENSE file.
{
'targets': [
{
'target_name': 'control_bar',
'dependencies': [
'<(DEPTH)/ui/webui/resources/js/compiled_resources2.gyp:cr',
'<(DEPTH)/ui/webui/resources/js/compiled_resources2.gyp:i18n_behavior',
'profile_browser_proxy',
],
'includes': ['../../../../third_party/closure_compiler/compile_js2.gypi'],
},
{
'target_name': 'create_profile',
'dependencies': [
'<(DEPTH)/ui/webui/resources/js/compiled_resources2.gyp:i18n_behavior',
'<(DEPTH)/ui/webui/resources/js/compiled_resources2.gyp:util',
'<(DEPTH)/ui/webui/resources/js/compiled_resources2.gyp:web_ui_listener_behavior',
'profile_browser_proxy',
],
'includes': ['../../../../third_party/closure_compiler/compile_js2.gypi'],
},
{
'target_name': 'error_dialog',
'includes': ['../../../../third_party/closure_compiler/compile_js2.gypi'],
},
{
'target_name': 'import_supervised_user',
'dependencies': [
'<(DEPTH)/ui/webui/resources/js/compiled_resources2.gyp:i18n_behavior',
'profile_browser_proxy',
],
'includes': ['../../../../third_party/closure_compiler/compile_js2.gypi'],
},
{
'target_name': 'profile_browser_proxy',
'dependencies': [
'<(DEPTH)/ui/webui/resources/js/compiled_resources2.gyp:assert',
'<(DEPTH)/ui/webui/resources/js/compiled_resources2.gyp:cr',
],
'includes': ['../../../../third_party/closure_compiler/compile_js2.gypi'],
},
{
'target_name': 'supervised_user_create_confirm',
'dependencies': [
'<(DEPTH)/ui/webui/resources/js/compiled_resources2.gyp:i18n_behavior',
'<(DEPTH)/ui/webui/resources/js/compiled_resources2.gyp:util',
'profile_browser_proxy',
],
'includes': ['../../../../third_party/closure_compiler/compile_js2.gypi'],
},
{
'target_name': 'supervised_user_learn_more',
'dependencies': [
'profile_browser_proxy',
],
'includes': ['../../../../third_party/closure_compiler/compile_js2.gypi'],
},
{
'target_name': 'user_manager_pages',
'includes': ['../../../../third_party/closure_compiler/compile_js2.gypi'],
},
{
'target_name': 'user_manager_tutorial',
'dependencies': [
'<(DEPTH)/ui/webui/resources/js/compiled_resources2.gyp:i18n_behavior',
'<(DEPTH)/ui/webui/resources/js/compiled_resources2.gyp:util',
],
'includes': ['../../../../third_party/closure_compiler/compile_js2.gypi'],
},
],
}
| {'targets': [{'target_name': 'control_bar', 'dependencies': ['<(DEPTH)/ui/webui/resources/js/compiled_resources2.gyp:cr', '<(DEPTH)/ui/webui/resources/js/compiled_resources2.gyp:i18n_behavior', 'profile_browser_proxy'], 'includes': ['../../../../third_party/closure_compiler/compile_js2.gypi']}, {'target_name': 'create_profile', 'dependencies': ['<(DEPTH)/ui/webui/resources/js/compiled_resources2.gyp:i18n_behavior', '<(DEPTH)/ui/webui/resources/js/compiled_resources2.gyp:util', '<(DEPTH)/ui/webui/resources/js/compiled_resources2.gyp:web_ui_listener_behavior', 'profile_browser_proxy'], 'includes': ['../../../../third_party/closure_compiler/compile_js2.gypi']}, {'target_name': 'error_dialog', 'includes': ['../../../../third_party/closure_compiler/compile_js2.gypi']}, {'target_name': 'import_supervised_user', 'dependencies': ['<(DEPTH)/ui/webui/resources/js/compiled_resources2.gyp:i18n_behavior', 'profile_browser_proxy'], 'includes': ['../../../../third_party/closure_compiler/compile_js2.gypi']}, {'target_name': 'profile_browser_proxy', 'dependencies': ['<(DEPTH)/ui/webui/resources/js/compiled_resources2.gyp:assert', '<(DEPTH)/ui/webui/resources/js/compiled_resources2.gyp:cr'], 'includes': ['../../../../third_party/closure_compiler/compile_js2.gypi']}, {'target_name': 'supervised_user_create_confirm', 'dependencies': ['<(DEPTH)/ui/webui/resources/js/compiled_resources2.gyp:i18n_behavior', '<(DEPTH)/ui/webui/resources/js/compiled_resources2.gyp:util', 'profile_browser_proxy'], 'includes': ['../../../../third_party/closure_compiler/compile_js2.gypi']}, {'target_name': 'supervised_user_learn_more', 'dependencies': ['profile_browser_proxy'], 'includes': ['../../../../third_party/closure_compiler/compile_js2.gypi']}, {'target_name': 'user_manager_pages', 'includes': ['../../../../third_party/closure_compiler/compile_js2.gypi']}, {'target_name': 'user_manager_tutorial', 'dependencies': ['<(DEPTH)/ui/webui/resources/js/compiled_resources2.gyp:i18n_behavior', '<(DEPTH)/ui/webui/resources/js/compiled_resources2.gyp:util'], 'includes': ['../../../../third_party/closure_compiler/compile_js2.gypi']}]} |
# Part 1 of the Python Review lab.
def hello_world():
print("hello world")
pass
def greet_by_name(name):
print("please enter your name")
name = input
print
pass
def encode(x):
pass
def decode(coded_message):
pass | def hello_world():
print('hello world')
pass
def greet_by_name(name):
print('please enter your name')
name = input
print
pass
def encode(x):
pass
def decode(coded_message):
pass |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# vim: ai ts=4 sts=4 et sw=4
"""
django-fhir
FILE: __init__.py
Created: 1/6/16 5:07 PM
"""
__author__ = 'Mark Scrimshire:@ekivemark'
# Hello World is here to test the loading of the module from fhir.settings
# from .settings import *
#from fhir_io_hapi.views.get import hello_world
#from fhir_io_hapi.views.delete import delete
#from fhir_io_hapi.views.get import (read, vread, history)
#from fhir_io_hapi.views.search import find
# Used to load post_save signal for write to backend fhir server
default_app_config = 'fhir_io_hapi.apps.fhir_io_hapi_config'
| """
django-fhir
FILE: __init__.py
Created: 1/6/16 5:07 PM
"""
__author__ = 'Mark Scrimshire:@ekivemark'
default_app_config = 'fhir_io_hapi.apps.fhir_io_hapi_config' |
pizzas = ["triple carne", "extra queso", "suprema"]
friend_pizzas = ["triple carne", "extra queso", "suprema"]
pizzas.append("baggel")
friend_pizzas.append("hawaiana")
print("Mis pizzas favoritas son:")
for i in range(0,len(pizzas)):
print(pizzas[i])
print()
print("Las pizzas favoritas de mi amigo son:")
for i in range(0,len(friend_pizzas)):
print(friend_pizzas[i])
| pizzas = ['triple carne', 'extra queso', 'suprema']
friend_pizzas = ['triple carne', 'extra queso', 'suprema']
pizzas.append('baggel')
friend_pizzas.append('hawaiana')
print('Mis pizzas favoritas son:')
for i in range(0, len(pizzas)):
print(pizzas[i])
print()
print('Las pizzas favoritas de mi amigo son:')
for i in range(0, len(friend_pizzas)):
print(friend_pizzas[i]) |
# -*- coding: utf-8 -*-
GITHUB_STRING = 'https://github.com/earaujoassis/watchman/archive/v{0}.zip'
NAME = "agents"
VERSION = "0.2.4"
| github_string = 'https://github.com/earaujoassis/watchman/archive/v{0}.zip'
name = 'agents'
version = '0.2.4' |
def first(arr, low , high):
if high >= low:
mid = low + (high - low)//2
if (mid ==0 or arr[mid-1] == 0) and arr[mid] == 1:
return mid
elif arr[mid] == 0:
return first(arr, mid+1, high)
else:
return first(arr, low, mid-1)
return -1
def row_with_max_ones(mat):
r = len(mat)
c = len(mat[0])
max_row_index = 0
max_ = -1
for i in range(r):
index = first(mat[i], 0, c-1)
if index != -1 and c - index > max_:
max_ = c - index
max_row_index = i
return max_row_index
| def first(arr, low, high):
if high >= low:
mid = low + (high - low) // 2
if (mid == 0 or arr[mid - 1] == 0) and arr[mid] == 1:
return mid
elif arr[mid] == 0:
return first(arr, mid + 1, high)
else:
return first(arr, low, mid - 1)
return -1
def row_with_max_ones(mat):
r = len(mat)
c = len(mat[0])
max_row_index = 0
max_ = -1
for i in range(r):
index = first(mat[i], 0, c - 1)
if index != -1 and c - index > max_:
max_ = c - index
max_row_index = i
return max_row_index |
class Solution:
def plusOne(self, digits):
"""
:type digits: List[int]
:rtype: List[int]
"""
if not digits:
return [1]
carry = (digits[-1] + 1) // 10
digits[-1] = (digits[-1] + 1) % 10
for i in reversed(range(len(digits) - 1)):
number = digits[i]
digits[i] = (number + carry) % 10
carry = (number + carry) // 10
if carry > 0:
return [carry] + digits
else:
return digits
print(Solution().plusOne([]))
| class Solution:
def plus_one(self, digits):
"""
:type digits: List[int]
:rtype: List[int]
"""
if not digits:
return [1]
carry = (digits[-1] + 1) // 10
digits[-1] = (digits[-1] + 1) % 10
for i in reversed(range(len(digits) - 1)):
number = digits[i]
digits[i] = (number + carry) % 10
carry = (number + carry) // 10
if carry > 0:
return [carry] + digits
else:
return digits
print(solution().plusOne([])) |
def infer_mask_from_batch_data(batch_data):
"""
Create binary mask for all non-empty timesteps
:param batch_data: BatchSize x SequenceLen x Features
:return: BatchSize x SequenceLen
"""
return batch_data.abs().sum(-1) > 0
def infer_lengths_from_mask(mask):
"""
Get array of lengths from binary mask
:param mask: BatchSize x SequenceLen
:return: BatchSize
"""
return mask.long().sum(1)
| def infer_mask_from_batch_data(batch_data):
"""
Create binary mask for all non-empty timesteps
:param batch_data: BatchSize x SequenceLen x Features
:return: BatchSize x SequenceLen
"""
return batch_data.abs().sum(-1) > 0
def infer_lengths_from_mask(mask):
"""
Get array of lengths from binary mask
:param mask: BatchSize x SequenceLen
:return: BatchSize
"""
return mask.long().sum(1) |
def get_path_components(path):
path = path.strip("/").split("/")
path = [c for c in path if c]
normalized = []
for comp in path:
if comp == ".":
continue
elif comp == "..":
if normalized:
normalized.pop()
else:
raise ValueError("URL tried to traverse above root")
else:
normalized.append(comp)
return normalized
| def get_path_components(path):
path = path.strip('/').split('/')
path = [c for c in path if c]
normalized = []
for comp in path:
if comp == '.':
continue
elif comp == '..':
if normalized:
normalized.pop()
else:
raise value_error('URL tried to traverse above root')
else:
normalized.append(comp)
return normalized |
#Belajar String Method
#https://docs.python.org/3/library/stdtypes.html#string-methods
nama = "muhammad aris septanugroho"
print(nama)
print(nama.upper()) #Huruf besar semua
print(nama.capitalize()) #Huruf besar kata pertama
print(nama.title()) #Huruf besar tiap kata
print(nama.split(" ")) #Memisah data menjadi list dengan ketentuan "spasi"
| nama = 'muhammad aris septanugroho'
print(nama)
print(nama.upper())
print(nama.capitalize())
print(nama.title())
print(nama.split(' ')) |
# Code adapted from Corey Shafer
"""Note: generators are more performat because they don't hold
all the values at the same time! Way better in memory, altho execution
will be a bit slower"""
def square_numbers(nums):
for i in nums:
# yield makes this a generator
# Returns one result at a time
yield(i * i)
my_nums = square_numbers([1, 2, 3, 4, 5])
# Alternative list comprehension my_nums = [x*x for x in [1, 2, 3, 4, 5]]
# and my_nums = (x*x for x in [1, 2, 3, 4, 5]) with circular brackets we are using a generator
for num in my_nums:
print(next(my_nums)) | """Note: generators are more performat because they don't hold
all the values at the same time! Way better in memory, altho execution
will be a bit slower"""
def square_numbers(nums):
for i in nums:
yield (i * i)
my_nums = square_numbers([1, 2, 3, 4, 5])
for num in my_nums:
print(next(my_nums)) |
class Solution:
# def maxProduct(self, nums):
# """
# :type nums: List[int]
# :rtype: int
# """
# for i in range(1, len(nums)):
# nums[i] = max(nums[i], nums[i] * nums[i - 1])
# return max(nums)
def maxProduct3(self, nums):
if not nums:
return 0
# locMin = nums[0]
# locMax = nums[0]
locMinPrev = nums[0]
locMaxPrev = nums[0]
gloMax = nums[0]
for i in range(1, len(nums)):
locMin = min(locMinPrev * nums[i], locMaxPrev * nums[i], nums[i])
locMax = max(locMaxPrev * nums[i], locMinPrev * nums[i], nums[i])
locMinPrev = locMin
locMaxPrev = locMax
gloMax = max(locMax, gloMax)
return gloMax
def maxProduct2(self, nums):
ans = nums[0]
# locMin, locMax stores the max/min product of subarray that ends with the current number
locMin = locMax = ans
for i in range(1, len(nums)):
# multiplying with a negative number makes a negative number positive, a positive number negative
if nums[i] < 0:
locMax, locMin = locMin, locMax
locMin = min(nums[i], locMin * nums[i])
locMax = max(nums[i], locMax * nums[i])
ans = max(ans, locMax)
return ans
def maxProduct(self, nums):
ans = nums[0]
# locMin, locMax stores the max/min product of subarray that ends with the current number
locMin = locMax = ans
for i in range(1, len(nums)):
candidates = (nums[i], locMax * nums[i], locMin * nums[i])
locMin = min(candidates)
locMax = max(candidates)
# warning: cannot do the following
# locMin is updated before calculating locMax
# locMin = min(nums[i], locMax * nums[i], locMin * nums[i])
# locMax = max(nums[i], locMax * nums[i], locMin * nums[i])
ans = max(ans, locMax)
return ans
solver = Solution()
ans = solver.maxProduct3([-4,-3,-2])
print(ans) | class Solution:
def max_product3(self, nums):
if not nums:
return 0
loc_min_prev = nums[0]
loc_max_prev = nums[0]
glo_max = nums[0]
for i in range(1, len(nums)):
loc_min = min(locMinPrev * nums[i], locMaxPrev * nums[i], nums[i])
loc_max = max(locMaxPrev * nums[i], locMinPrev * nums[i], nums[i])
loc_min_prev = locMin
loc_max_prev = locMax
glo_max = max(locMax, gloMax)
return gloMax
def max_product2(self, nums):
ans = nums[0]
loc_min = loc_max = ans
for i in range(1, len(nums)):
if nums[i] < 0:
(loc_max, loc_min) = (locMin, locMax)
loc_min = min(nums[i], locMin * nums[i])
loc_max = max(nums[i], locMax * nums[i])
ans = max(ans, locMax)
return ans
def max_product(self, nums):
ans = nums[0]
loc_min = loc_max = ans
for i in range(1, len(nums)):
candidates = (nums[i], locMax * nums[i], locMin * nums[i])
loc_min = min(candidates)
loc_max = max(candidates)
ans = max(ans, locMax)
return ans
solver = solution()
ans = solver.maxProduct3([-4, -3, -2])
print(ans) |
def product_left_recursive(alist, result=None):
if alist == []:
return result
g = result[-1] * alist[0]
result.append(g)
return product_left_recursive(alist[1:], result)
def product_left(alist):
new_list = [1]
for index in range(1, len(alist)):
value = new_list[-1] * alist[index-1]
new_list.append(value)
return new_list
def product_right(alist):
new_list = [1]
for index in range(len(alist)-2, -1, -1):
value = new_list[-1] * alist[index-1]
new_list.append(value)
return new_list
def product_of_array_of_array(alist):
left_list = product_left(alist)
right_list = product_right(alist)
new_list = []
for index, item in enumerate(alist):
value = left_list[index] * right_list[index]
new_list.append(value)
return new_list
def product_recursive(alist):
if alist == []:
return 1
return alist[0] * product_recursive(alist[1:])
def paa(alist):
new_list = []
for index, item in enumerate(alist):
current_list = alist[:index] + alist[index+1:]
value = product_recursive(current_list)
new_list.append(value)
return new_list
alist = [1, 2, 3, 4, 5, 6]
rlist = alist[::-1]
print(alist)
print(product_left(alist))
print(product_left_recursive(alist[1:], [1]))
print(product_left_recursive(rlist[1:], [1]))
print(product_right(alist))
#print(product_right_recursive(alist, [1]))
#print(product_of_array_of_array(alist))
#print(paa(alist))
| def product_left_recursive(alist, result=None):
if alist == []:
return result
g = result[-1] * alist[0]
result.append(g)
return product_left_recursive(alist[1:], result)
def product_left(alist):
new_list = [1]
for index in range(1, len(alist)):
value = new_list[-1] * alist[index - 1]
new_list.append(value)
return new_list
def product_right(alist):
new_list = [1]
for index in range(len(alist) - 2, -1, -1):
value = new_list[-1] * alist[index - 1]
new_list.append(value)
return new_list
def product_of_array_of_array(alist):
left_list = product_left(alist)
right_list = product_right(alist)
new_list = []
for (index, item) in enumerate(alist):
value = left_list[index] * right_list[index]
new_list.append(value)
return new_list
def product_recursive(alist):
if alist == []:
return 1
return alist[0] * product_recursive(alist[1:])
def paa(alist):
new_list = []
for (index, item) in enumerate(alist):
current_list = alist[:index] + alist[index + 1:]
value = product_recursive(current_list)
new_list.append(value)
return new_list
alist = [1, 2, 3, 4, 5, 6]
rlist = alist[::-1]
print(alist)
print(product_left(alist))
print(product_left_recursive(alist[1:], [1]))
print(product_left_recursive(rlist[1:], [1]))
print(product_right(alist)) |
# coding: utf-8
# pragma: no cover
class Transformator:
"""Rule to transform values"""
def __init__(self, *args, **kwargs):
pass
class TransformatorList(list):
"""Wrapper for all registered Transformators"""
def __init__(self, settings, *args, **kwargs):
super(TransformatorList, self).__init__(*args, **kwargs)
self.settings = settings
def register(self, *args):
self.extend(args)
| class Transformator:
"""Rule to transform values"""
def __init__(self, *args, **kwargs):
pass
class Transformatorlist(list):
"""Wrapper for all registered Transformators"""
def __init__(self, settings, *args, **kwargs):
super(TransformatorList, self).__init__(*args, **kwargs)
self.settings = settings
def register(self, *args):
self.extend(args) |
fileName = ["nohup_2", "nohup_1", "nohup_4", "nohup"]
Fo = open("new nohup", "w")
for fil in fileName:
lineNum = 0
with open(fil) as F:
for line in F:
if lineNum % 10 == 0:
Fo.write(",\t".join(line.split()))
Fo.write("\n")
lineNum += 1
Fo.write("e\n") | file_name = ['nohup_2', 'nohup_1', 'nohup_4', 'nohup']
fo = open('new nohup', 'w')
for fil in fileName:
line_num = 0
with open(fil) as f:
for line in F:
if lineNum % 10 == 0:
Fo.write(',\t'.join(line.split()))
Fo.write('\n')
line_num += 1
Fo.write('e\n') |
# Python - 3.6.0
test.assert_equals(last([1, 2, 3, 4, 5]), 5)
test.assert_equals(last('abcde'), 'e')
test.assert_equals(last(1, 'b', 3, 'd', 5), 5)
| test.assert_equals(last([1, 2, 3, 4, 5]), 5)
test.assert_equals(last('abcde'), 'e')
test.assert_equals(last(1, 'b', 3, 'd', 5), 5) |
class Student:
def __init__(self,m1,m2):
self.m1 = m1
self.m2 = m2
def sum(self, a = None, b = None, c = None):
addition = 0
if a!=None and b!=None and c!=None:
addition = a + b + c
elif a!=None and b!= None:
addition = a + b
else:
addition = a
return addition
s1 = Student(10,20)
print(s1.sum(2,4)) | class Student:
def __init__(self, m1, m2):
self.m1 = m1
self.m2 = m2
def sum(self, a=None, b=None, c=None):
addition = 0
if a != None and b != None and (c != None):
addition = a + b + c
elif a != None and b != None:
addition = a + b
else:
addition = a
return addition
s1 = student(10, 20)
print(s1.sum(2, 4)) |
a = int(input("Enter number of elements in set A "))
A = set(map(int,input("# Spaced Separated list of elements of A ").split())) # Spaced Separated list of elements of A
n = int(input("Number of sets ")) # Number of sets
for i in range(n):
p = input("Enter the operation and number of elements in set"+i).split()
s2 = set(map(int,input("Enter space separated list of elements for operation #"+p[1]+" ").split()))
if p[0] == "intersection_update":
A.intersection_update(s2)
elif p[0]=="update":
A.update(s2)
elif p[0]=="symmetric_difference_update":
A.symmetric_difference_update(s2)
elif p[0]=="difference_update":
A.difference_update(s2)
print(sum(A)) | a = int(input('Enter number of elements in set A '))
a = set(map(int, input('# Spaced Separated list of elements of A ').split()))
n = int(input('Number of sets '))
for i in range(n):
p = input('Enter the operation and number of elements in set' + i).split()
s2 = set(map(int, input('Enter space separated list of elements for operation #' + p[1] + ' ').split()))
if p[0] == 'intersection_update':
A.intersection_update(s2)
elif p[0] == 'update':
A.update(s2)
elif p[0] == 'symmetric_difference_update':
A.symmetric_difference_update(s2)
elif p[0] == 'difference_update':
A.difference_update(s2)
print(sum(A)) |
class Solution:
def sqrt(self, x):
low = 0
high = 65536
best = 0
while high > low:
mid = (high + low) / 2
sqr = mid ** 2
if sqr > x:
high = mid
elif sqr == x:
return mid
else:
best = mid
low = mid + 1
return best
| class Solution:
def sqrt(self, x):
low = 0
high = 65536
best = 0
while high > low:
mid = (high + low) / 2
sqr = mid ** 2
if sqr > x:
high = mid
elif sqr == x:
return mid
else:
best = mid
low = mid + 1
return best |
def palindrome(word, ind):
if word == word[::-1]:
return f"{word} is a palindrome"
if word[ind] != word[len(word) - 1 - ind]:
return f"{word} is not a palindrome"
return palindrome(word, ind + 1)
print(palindrome("abcba", 0))
print(palindrome("peter", 0))
| def palindrome(word, ind):
if word == word[::-1]:
return f'{word} is a palindrome'
if word[ind] != word[len(word) - 1 - ind]:
return f'{word} is not a palindrome'
return palindrome(word, ind + 1)
print(palindrome('abcba', 0))
print(palindrome('peter', 0)) |
#NETWORK
LOCALHOST = "127.0.0.1"
PI_ADDRESS = "192.168.0.1"
PORT = 5000
#STATE
MOVEMENT_MARGIN = 2
KICK_TIMEOUT = 1
LAST_POSITION = -1
PLAYER_LENGTH = 2
NOISE_THRESHOLD = 3
MIN_VELOCITY_THRESHOLD = 300
OPEN_PREP_RANGE = -30
BLOCK_PREP_RANGE = 100
OPEN_KICK_RANGE = -20
BLOCK_KICK_RANGE = 60
KICK_ANGLE = 55
PREP_ANGLE = -30
BLOCK_ANGLE = 0
OPEN_ANGLE = -90
SPEED_THRESHOLD = 3000
MIN_PLAYER_OFFSET = 40
MAX_PLAYER_OFFSET = 640
IDLE_RANGE = 600
RECOVERY_LINEAR = 80
RECOVERY_ANGLE = -57
#PHYSICAL DIMENSIONS
GOAL_ROD = {"maxActuation":228, "playerSpacing":182, "rodX":1125, "numPlayers":3}
TWO_ROD = {"maxActuation":356, "playerSpacing":237, "rodX":975, "numPlayers":2}
FIVE_ROD = {"maxActuation":115, "playerSpacing":120, "rodX":675, "numPlayers":5}
THREE_ROD = {"maxActuation":181, "playerSpacing":207, "rodX":375, "numPlayers":3}
TABLE = {"robot_goalX":1200, "robot_goalY":350, "player_goalX":0, "player_goalY":350, "goalWidth":200, "width":685, "length":1200}
| localhost = '127.0.0.1'
pi_address = '192.168.0.1'
port = 5000
movement_margin = 2
kick_timeout = 1
last_position = -1
player_length = 2
noise_threshold = 3
min_velocity_threshold = 300
open_prep_range = -30
block_prep_range = 100
open_kick_range = -20
block_kick_range = 60
kick_angle = 55
prep_angle = -30
block_angle = 0
open_angle = -90
speed_threshold = 3000
min_player_offset = 40
max_player_offset = 640
idle_range = 600
recovery_linear = 80
recovery_angle = -57
goal_rod = {'maxActuation': 228, 'playerSpacing': 182, 'rodX': 1125, 'numPlayers': 3}
two_rod = {'maxActuation': 356, 'playerSpacing': 237, 'rodX': 975, 'numPlayers': 2}
five_rod = {'maxActuation': 115, 'playerSpacing': 120, 'rodX': 675, 'numPlayers': 5}
three_rod = {'maxActuation': 181, 'playerSpacing': 207, 'rodX': 375, 'numPlayers': 3}
table = {'robot_goalX': 1200, 'robot_goalY': 350, 'player_goalX': 0, 'player_goalY': 350, 'goalWidth': 200, 'width': 685, 'length': 1200} |
#! /usr/bin/env python3.6
#a = 'str'
a = '32'
print(f'float(a) = {float(a)}')
print(f'int(a) = {int(a)}')
if(isinstance(a, str)):
print("Yes, it is string.")
else:
print("No, it is not string.")
| a = '32'
print(f'float(a) = {float(a)}')
print(f'int(a) = {int(a)}')
if isinstance(a, str):
print('Yes, it is string.')
else:
print('No, it is not string.') |
class TreeNode:
def __init__(self, val):
self.left = None
self.right = None
self.val = val
def is_valid_BST(node, min, max):
if node == None:
return True
if (min is not None and node.val <= min) or (max is not None and max <= node.val):
return False
return is_valid_BST(node.left, min, node.val) and is_valid_BST(node.right, node.val, max)
| class Treenode:
def __init__(self, val):
self.left = None
self.right = None
self.val = val
def is_valid_bst(node, min, max):
if node == None:
return True
if min is not None and node.val <= min or (max is not None and max <= node.val):
return False
return is_valid_bst(node.left, min, node.val) and is_valid_bst(node.right, node.val, max) |
"""Heisenbridge
An alternative to https://github.com/matrix-org/matrix-appservice-irc/issues
"""
| """Heisenbridge
An alternative to https://github.com/matrix-org/matrix-appservice-irc/issues
""" |
class lagrange(object):
def __init__(self, eval_x = 0):
self._eval_x = eval_x
self._extrapolations = []
def add_point(self, x, y):
new_extraps = [(y, x)]
for past_extrap, x_old in self._extrapolations:
new_val = ((self._eval_x - x) * past_extrap \
+ (x_old - self._eval_x) * new_extraps[-1][0])\
/ (x_old - x)
new_extraps.append((new_val, x_old))
self._extrapolations = new_extraps
return self.estimate
@property
def estimate(self):
return self._extrapolations[-1][0]
if __name__ == "__main__":
interpolator = lagrange(eval_x = 0)
print(interpolator.add_point(1,2))
print(interpolator.add_point(0.5,3))
print(interpolator.add_point(0.25,3.75))
print(interpolator.add_point(0.125,4.25))
print(interpolator.add_point(0.0625,4.5))
| class Lagrange(object):
def __init__(self, eval_x=0):
self._eval_x = eval_x
self._extrapolations = []
def add_point(self, x, y):
new_extraps = [(y, x)]
for (past_extrap, x_old) in self._extrapolations:
new_val = ((self._eval_x - x) * past_extrap + (x_old - self._eval_x) * new_extraps[-1][0]) / (x_old - x)
new_extraps.append((new_val, x_old))
self._extrapolations = new_extraps
return self.estimate
@property
def estimate(self):
return self._extrapolations[-1][0]
if __name__ == '__main__':
interpolator = lagrange(eval_x=0)
print(interpolator.add_point(1, 2))
print(interpolator.add_point(0.5, 3))
print(interpolator.add_point(0.25, 3.75))
print(interpolator.add_point(0.125, 4.25))
print(interpolator.add_point(0.0625, 4.5)) |
# -*- coding: utf-8 -*-
__version__ = '1.0.0'
default_app_config = 'webmap.apps.WebmapConfig'
| __version__ = '1.0.0'
default_app_config = 'webmap.apps.WebmapConfig' |
#Get a string which is n (non-negative integer) copies of a given string
#
#function to display the string
def dispfunc(iteration):
output=str("")
for i in range(iteration):
output=output+entry
print(output)
#
entry=str(input("\nenter a string : "))
displaynumber=int(input("how many times must it be displayed? : "))
dispfunc(displaynumber)
#experimental
feedback=str(input("\nwould you try it for the stringlength? : "))
if feedback == "yes" or "Yes" or "YES" or "yeah":
dispfunc(len(entry))
#program ends here | def dispfunc(iteration):
output = str('')
for i in range(iteration):
output = output + entry
print(output)
entry = str(input('\nenter a string : '))
displaynumber = int(input('how many times must it be displayed? : '))
dispfunc(displaynumber)
feedback = str(input('\nwould you try it for the stringlength? : '))
if feedback == 'yes' or 'Yes' or 'YES' or 'yeah':
dispfunc(len(entry)) |
spaces = int(input())
steps =0
while(spaces > 0):
if(spaces >= 5):
spaces -= 5
steps += 1
elif(spaces >= 4):
spaces -= 4
steps += 1
elif(spaces >= 3):
spaces -= 3
steps += 1
elif(spaces >= 2):
spaces -= 2
steps += 1
elif(spaces >= 1):
spaces -= 1
steps += 1
print(str(steps))
| spaces = int(input())
steps = 0
while spaces > 0:
if spaces >= 5:
spaces -= 5
steps += 1
elif spaces >= 4:
spaces -= 4
steps += 1
elif spaces >= 3:
spaces -= 3
steps += 1
elif spaces >= 2:
spaces -= 2
steps += 1
elif spaces >= 1:
spaces -= 1
steps += 1
print(str(steps)) |
# Straightforward implementation of the Singleton Pattern
class Logger(object):
_instance = None
def __new__(cls):
if cls._instance is None:
print('Creating the object')
cls._instance = super(Logger, cls).__new__(cls)
# Put any initialization here.
return cls._instance
log1 = Logger()
print(log1)
log2 = Logger()
print(log2)
print('Are they the same object?', log1 is log2)
| class Logger(object):
_instance = None
def __new__(cls):
if cls._instance is None:
print('Creating the object')
cls._instance = super(Logger, cls).__new__(cls)
return cls._instance
log1 = logger()
print(log1)
log2 = logger()
print(log2)
print('Are they the same object?', log1 is log2) |
load("@rules_pkg//:providers.bzl", "PackageFilesInfo", "PackageSymlinkInfo", "PackageFilegroupInfo")
def _runfile_path(ctx, file, runfiles_dir):
path = file.short_path
if path.startswith(".."):
return path.replace("..", runfiles_dir)
if not file.owner.workspace_name:
return "/".join([runfiles_dir, ctx.workspace_name, path])
return path
def _runfiles_impl(ctx):
default = ctx.attr.binary[DefaultInfo]
executable = default.files_to_run.executable
manifest = default.files_to_run.runfiles_manifest
runfiles_dir = manifest.short_path.replace(manifest.basename, "")[:-1]
files = depset(transitive = [default.files, default.default_runfiles.files])
fileMap = {
executable.short_path: executable
}
for file in files.to_list():
fileMap[_runfile_path(ctx, file, runfiles_dir)] = file
files = depset([executable], transitive = [files])
symlinks = []
for symlink in default.data_runfiles.root_symlinks.to_list():
info = PackageSymlinkInfo(
source = "/%s" % _runfile_path(ctx, symlink.target_file, runfiles_dir),
destination = "/%s" % "/".join([runfiles_dir, symlink.path]),
attributes = { "mode": "0777" }
)
symlinks.append([info, ctx.label])
return [
PackageFilegroupInfo(
pkg_dirs = [],
pkg_files = [
[PackageFilesInfo(
dest_src_map = fileMap,
attributes = {},
), ctx.label]
],
pkg_symlinks = symlinks,
),
DefaultInfo(files = files),
]
expand_runfiles = rule(
implementation = _runfiles_impl,
attrs = {
"binary": attr.label()
}
) | load('@rules_pkg//:providers.bzl', 'PackageFilesInfo', 'PackageSymlinkInfo', 'PackageFilegroupInfo')
def _runfile_path(ctx, file, runfiles_dir):
path = file.short_path
if path.startswith('..'):
return path.replace('..', runfiles_dir)
if not file.owner.workspace_name:
return '/'.join([runfiles_dir, ctx.workspace_name, path])
return path
def _runfiles_impl(ctx):
default = ctx.attr.binary[DefaultInfo]
executable = default.files_to_run.executable
manifest = default.files_to_run.runfiles_manifest
runfiles_dir = manifest.short_path.replace(manifest.basename, '')[:-1]
files = depset(transitive=[default.files, default.default_runfiles.files])
file_map = {executable.short_path: executable}
for file in files.to_list():
fileMap[_runfile_path(ctx, file, runfiles_dir)] = file
files = depset([executable], transitive=[files])
symlinks = []
for symlink in default.data_runfiles.root_symlinks.to_list():
info = package_symlink_info(source='/%s' % _runfile_path(ctx, symlink.target_file, runfiles_dir), destination='/%s' % '/'.join([runfiles_dir, symlink.path]), attributes={'mode': '0777'})
symlinks.append([info, ctx.label])
return [package_filegroup_info(pkg_dirs=[], pkg_files=[[package_files_info(dest_src_map=fileMap, attributes={}), ctx.label]], pkg_symlinks=symlinks), default_info(files=files)]
expand_runfiles = rule(implementation=_runfiles_impl, attrs={'binary': attr.label()}) |
# You can also nest for loops with
# while loops. Check it out!
for i in range(4):
print("For loop: " + str(i))
x = i
while x >= 0:
print(" While loop: " + str(x))
x = x - 1
| for i in range(4):
print('For loop: ' + str(i))
x = i
while x >= 0:
print(' While loop: ' + str(x))
x = x - 1 |
##list of integers
student_score= [99, 88, 60]
##printing out that list
print(student_score)
##printing all the integers in a range
print(list(range(1,10)))
##printing out all the integers in a range skipping one every time
print(list(range(1,10,2)))
## manipulating a string and printting all the modifications
x = "hello"
y = x.upper()
z = x.title()
print(x, y, z) | student_score = [99, 88, 60]
print(student_score)
print(list(range(1, 10)))
print(list(range(1, 10, 2)))
x = 'hello'
y = x.upper()
z = x.title()
print(x, y, z) |
def harmonic(a, b):
return (2*a*b)/(a + b);
a, b = map(int, input().split())
print(harmonic(a, b))
| def harmonic(a, b):
return 2 * a * b / (a + b)
(a, b) = map(int, input().split())
print(harmonic(a, b)) |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# Created by PyCharm
# @author : mystic
# @date : 2017/11/11 21:01
"""
Override Configuration
"""
configs = {
'db': {
'host': '127.0.0.1'
}
}
| """
Override Configuration
"""
configs = {'db': {'host': '127.0.0.1'}} |
# from recipes.decor.tests import test_cases as tcx
# pylint: disable-all
def test_expose_decor():
@expose.show
def foo(a, b=1, *args, c=2, **kws):
pass
foo(88, 12, 11, c=4, y=1)
def test_expose_decor():
@expose.args
def foo(a, b=1, *args, c=2, **kws):
pass
foo(88, 12, 11, c=4, y=1)
# # print(i)
# # print(sig)
# # print(ba)
# ba.apply_defaults()
# # print(ba)
# print(f'{ba!s}'.replace('<BoundArguments ', fun.__qualname__).rstrip('>'))
# # print('*'*88)
# from IPython import embed
# embed(header="Embedded interpreter at 'test_expose.py':32")
| def test_expose_decor():
@expose.show
def foo(a, b=1, *args, c=2, **kws):
pass
foo(88, 12, 11, c=4, y=1)
def test_expose_decor():
@expose.args
def foo(a, b=1, *args, c=2, **kws):
pass
foo(88, 12, 11, c=4, y=1) |
def fill_bin_num(dataframe, feature, bin_feature, bin_size, stat_measure, min_bin=None, max_bin=None, default_val='No'):
if min_bin is None:
min_bin = dataframe[bin_feature].min()
if max_bin is None:
max_bin = dataframe[bin_feature].max()
new_dataframe = dataframe.copy()
df_meancat = pd.DataFrame(columns=['interval', 'stat_measure'])
for num_bin, subset in dataframe.groupby(pd.cut(dataframe[bin_feature], np.arange(min_bin, max_bin+bin_size, bin_size), include_lowest=True)):
if stat_measure is 'mean':
row = [num_bin, subset[feature].mean()]
elif stat_measure is 'mode':
mode_ar = subset[feature].mode().values
if len(mode_ar) > 0:
row = [num_bin, mode_ar[0]]
else:
row = [num_bin, default_val]
else:
raise Exception('Unknown statistical measure: ' + stat_measure)
df_meancat.loc[len(df_meancat)] = row
for index, row_df in dataframe[dataframe[feature].isna()].iterrows():
for _, row_meancat in df_meancat.iterrows():
if row_df[bin_feature] in row_meancat['interval']:
new_dataframe.at[index, feature] = row_meancat['stat_measure']
return new_dataframe
def make_dummy_cols(dataframe, column, prefix, drop_dummy):
dummy = pd.get_dummies(dataframe[column], prefix=prefix)
dummy = dummy.drop(columns=prefix+'_'+drop_dummy)
dataframe = pd.concat([dataframe, dummy], axis=1)
dataframe = dataframe.drop(columns=column)
return dataframe
def cleaning(dataframe_raw):
dataframe = dataframe_raw.copy()
dataframe = dataframe.set_index('ID')
dataframe.loc[(dataframe['Age']<=13) & (dataframe['Education'].isna()), 'Education'] = 'Lower School/Kindergarten'
dataframe.loc[(dataframe['Age']==14) & (dataframe['Education'].isna()), 'Education'] = '8th Grade'
dataframe.loc[(dataframe['Age']<=17) & (dataframe['Education'].isna()), 'Education'] = '9 - 11th Grade'
dataframe.loc[(dataframe['Age']<=21) & (dataframe['Education'].isna()), 'Education'] = 'High School'
dataframe['Education'] = dataframe['Education'].fillna('Some College')
dataframe.loc[(dataframe['Age']<=20) & (dataframe['MaritalStatus'].isna()), 'MaritalStatus'] = 'NeverMarried'
dataframe.at[dataframe['MaritalStatus'].isna(), 'MaritalStatus'] = fill_bin_num(dataframe, 'MaritalStatus', 'Age', 5, 'mode',20)
dataframe = dataframe.drop(columns=['HHIncome'])
dataframe.loc[dataframe['HHIncomeMid'].isna(), 'HHIncomeMid'] = dataframe['HHIncomeMid'].mean()
dataframe.loc[dataframe['Poverty'].isna(), 'Poverty'] = dataframe['Poverty'].mean()
dataframe.loc[dataframe['HomeRooms'].isna(), 'HomeRooms'] = dataframe['HomeRooms'].mean()
dataframe.loc[dataframe['HomeOwn'].isna(), 'HomeOwn'] = dataframe['HomeOwn'].mode().values[0]
dataframe.loc[(dataframe['Work'].isna()) & (dataframe['Education'].isna()) & (dataframe['Age']<=20), 'Work'] = 'NotWorking'
dataframe.loc[dataframe['Work'].isna(), 'Work'] = dataframe['Work'].mode().values[0]
dataframe = fill_bin_num(dataframe, 'Weight', 'Age', 2, 'mean')
dataframe = dataframe.drop(columns=['HeadCirc'])
for index, row in dataframe.iterrows():
if np.isnan(row['Height']) and not np.isnan(row['Length']):
dataframe.at[index, 'Height'] = row['Length']
dataframe = fill_bin_num(dataframe, 'Height', 'Age', 2, 'mean')
dataframe = dataframe.drop(columns=['Length'])
for index, row in dataframe[dataframe['BMI'].isna()].iterrows():
dataframe.at[index, 'BMI'] = row['Weight'] / ((row['Height']/100)**2)
dataframe = dataframe.drop(columns='BMICatUnder20yrs')
dataframe = dataframe.drop(columns='BMI_WHO')
dataframe = fill_bin_num(dataframe, 'Pulse', 'Age', 10, 'mean')
dataframe.loc[(dataframe['Age']<10) & (dataframe['BPSysAve'].isna()), 'BPSysAve'] = 105
dataframe = fill_bin_num(dataframe, 'BPSysAve', 'Age', 5, 'mean', 10)
dataframe.loc[(dataframe['Age']<10) & (dataframe['BPDiaAve'].isna()), 'BPDiaAve'] = 60
dataframe = fill_bin_num(dataframe, 'BPDiaAve', 'Age', 5, 'mean', 10)
dataframe = dataframe.drop(columns='BPSys1')
dataframe = dataframe.drop(columns='BPDia1')
dataframe = dataframe.drop(columns='BPSys2')
dataframe = dataframe.drop(columns='BPDia2')
dataframe = dataframe.drop(columns='BPSys3')
dataframe = dataframe.drop(columns='BPDia3')
dataframe = dataframe.drop(columns=['Testosterone'])
dataframe.loc[(dataframe['Age']<10) & (dataframe['DirectChol'].isna()), 'DirectChol'] = 0
dataframe = fill_bin_num(dataframe, 'DirectChol', 'Age', 5, 'mean', 10)
dataframe.loc[(dataframe['Age']<10) & (dataframe['TotChol'].isna()), 'TotChol'] = 0
dataframe = fill_bin_num(dataframe, 'TotChol', 'Age', 5, 'mean', 10)
dataframe = dataframe.drop(columns=['UrineVol1'])
dataframe = dataframe.drop(columns=['UrineFlow1'])
dataframe = dataframe.drop(columns=['UrineVol2'])
dataframe = dataframe.drop(columns=['UrineFlow2'])
dataframe['Diabetes'] = dataframe['Diabetes'].fillna('No')
dataframe['DiabetesAge'] = dataframe['DiabetesAge'].fillna(0)
dataframe.loc[(dataframe['Age']<=12) & (dataframe['HealthGen'].isna()), 'HealthGen'] = 'Good'
dataframe = fill_bin_num(dataframe, 'HealthGen', 'Age', 5, 'mode', 10)
dataframe.loc[(dataframe['Age']<=12) & (dataframe['DaysMentHlthBad'].isna()), 'DaysMentHlthBad'] = 0
dataframe = fill_bin_num(dataframe, 'DaysMentHlthBad', 'Age', 5, 'mean', 10)
dataframe.loc[(dataframe['Age']<=15) & (dataframe['LittleInterest'].isna()), 'LittleInterest'] = 'None'
dataframe = fill_bin_num(dataframe, 'LittleInterest', 'Age', 5, 'mode', 15)
dataframe.loc[(dataframe['Age']<=12) & (dataframe['DaysMentHlthBad'].isna()), 'DaysMentHlthBad'] = 0
dataframe = fill_bin_num(dataframe, 'DaysMentHlthBad', 'Age', 5, 'mean', 10)
for index, row in dataframe.iterrows():
if np.isnan(row['nBabies']) and not np.isnan(row['nPregnancies']):
dataframe.at[index, 'nBabies'] = row['nPregnancies']
dataframe['nBabies'] = dataframe['nBabies'].fillna(0)
dataframe['nPregnancies'] = dataframe['nPregnancies'].fillna(0)
dataframe['Age1stBaby'] = dataframe['Age1stBaby'].fillna(0)
dataframe.loc[(dataframe['Age']==0) & (dataframe['SleepHrsNight'].isna()), 'SleepHrsNight'] = 14
dataframe.loc[(dataframe['Age']<=2) & (dataframe['SleepHrsNight'].isna()), 'SleepHrsNight'] = 12
dataframe.loc[(dataframe['Age']<=5) & (dataframe['SleepHrsNight'].isna()), 'SleepHrsNight'] = 10
dataframe.loc[(dataframe['Age']<=10) & (dataframe['SleepHrsNight'].isna()), 'SleepHrsNight'] = 9
dataframe.loc[(dataframe['Age']<=15) & (dataframe['SleepHrsNight'].isna()), 'SleepHrsNight'] = 8
dataframe['SleepHrsNight'] = dataframe['SleepHrsNight'].fillna(dataframe_raw['SleepHrsNight'].mean())
dataframe['SleepTrouble'] = dataframe['SleepTrouble'].fillna('No')
dataframe.loc[(dataframe['Age']<=4) & (dataframe['PhysActive'].isna()), 'PhysActive'] = 'No'
dataframe = fill_bin_num(dataframe, 'PhysActive', 'Age', 2, 'mode', 16)
dataframe['PhysActive'] = dataframe['PhysActive'].fillna('Yes') # Big assumption here. All kids between 4 and 16 are physically active
dataframe = dataframe.drop(columns=['PhysActiveDays'])
dataframe = dataframe.drop(columns=['TVHrsDay'])
dataframe = dataframe.drop(columns=['TVHrsDayChild'])
dataframe = dataframe.drop(columns=['CompHrsDay'])
dataframe = dataframe.drop(columns=['CompHrsDayChild'])
dataframe.loc[(dataframe['Age']<18) & (dataframe['Alcohol12PlusYr'].isna()), 'Alcohol12PlusYr'] = 'No'
dataframe = fill_bin_num(dataframe, 'Alcohol12PlusYr', 'Age', 5, 'mode', 18)
dataframe.loc[(dataframe['Age']<18) & (dataframe['AlcoholDay'].isna()), 'AlcoholDay'] = 0
dataframe = fill_bin_num(dataframe, 'AlcoholDay', 'Age', 5, 'mean', 18)
dataframe.loc[(dataframe['Age']<18) & (dataframe['AlcoholYear'].isna()), 'AlcoholYear'] = 0
dataframe = fill_bin_num(dataframe, 'AlcoholYear', 'Age', 5, 'mean', 18)
dataframe.loc[(dataframe['Age']<20) & (dataframe['SmokeNow'].isna()), 'SmokeNow'] = 'No'
dataframe = fill_bin_num(dataframe, 'SmokeNow', 'Age', 5, 'mode', 20)
dataframe['Smoke100'] = dataframe['Smoke100'].fillna('No')
dataframe['Smoke100n'] = dataframe['Smoke100n'].fillna('No')
dataframe.loc[(dataframe['SmokeNow']=='No') & (dataframe['SmokeAge'].isna()), 'SmokeAge'] = 0
dataframe = fill_bin_num(dataframe, 'SmokeAge', 'Age', 5, 'mean', 20)
dataframe.loc[(dataframe['Age']<18) & (dataframe['Marijuana'].isna()), 'Marijuana'] = 'No'
dataframe.loc[(dataframe['Marijuana'].isna()) & (dataframe['SmokeNow']=='No'), 'Marijuana'] = 'No'
dataframe = fill_bin_num(dataframe, 'Marijuana', 'Age', 5, 'mode', 20)
dataframe.loc[(dataframe['Marijuana']=='No') & (dataframe['AgeFirstMarij'].isna()), 'AgeFirstMarij'] = 0
dataframe = fill_bin_num(dataframe, 'AgeFirstMarij', 'Age', 5, 'mean', 20)
dataframe.loc[(dataframe['Marijuana']=='No') & (dataframe['RegularMarij'].isna()), 'RegularMarij'] = 'No'
dataframe = fill_bin_num(dataframe, 'RegularMarij', 'Age', 5, 'mode', 20)
dataframe.loc[(dataframe['RegularMarij']=='No') & (dataframe['AgeRegMarij'].isna()), 'AgeRegMarij'] = 0
dataframe = fill_bin_num(dataframe, 'AgeRegMarij', 'Age', 5, 'mean', 20)
dataframe.loc[(dataframe['Age']<18) & (dataframe['HardDrugs'].isna()), 'HardDrugs'] = 'No'
dataframe = fill_bin_num(dataframe, 'HardDrugs', 'Age', 5, 'mode', 18)
mode_sex_age = dataframe['SexAge'].mode()[0]
dataframe.loc[(dataframe['Age']<=mode_sex_age) & (dataframe['SexEver'].isna()), 'SexEver'] = 'No'
dataframe['SexEver'] = dataframe['SexEver'].fillna('Yes')
dataframe.loc[(dataframe['SexEver']=='No') & (dataframe['SexAge'].isna()), 'SexAge'] = 0
dataframe.loc[(dataframe['SexAge'].isna() & (dataframe['Age']<mode_sex_age)), 'SexAge'] = dataframe.loc[(dataframe['SexAge'].isna() & (dataframe['Age']<mode_sex_age)), 'Age']
dataframe['SexAge'] = dataframe['SexAge'].fillna(mode_sex_age)
dataframe.loc[(dataframe['SexEver']=='No') & (dataframe['SexNumPartnLife'].isna()), 'SexNumPartnLife'] = 0
dataframe = fill_bin_num(dataframe, 'SexNumPartnLife', 'Age', 5, 'mean')
dataframe['SexNumPartnLife'] = dataframe_raw.loc[(dataframe_raw['Age'] >= 60) & (dataframe_raw['Age'] <= 70), 'SexNumPartnLife'].mode()[0] # Missing values for the elderly. Assumed that lifetime sex partners do not increase after 60.
dataframe.loc[(dataframe['SexEver']=='No') & (dataframe['SexNumPartYear'].isna()), 'SexNumPartYear'] = 0
dataframe = fill_bin_num(dataframe, 'SexNumPartYear', 'Age', 10, 'mean')
dataframe['SexNumPartYear'] = dataframe['SexNumPartYear'].fillna(0)
dataframe = dataframe.drop(columns=['SameSex'])
dataframe = dataframe.drop(columns=['SexOrientation'])
dataframe['PregnantNow'] = dataframe['PregnantNow'].fillna('No')
# Making dummy variables
dataframe['male'] = 1*(dataframe['Gender'] == 'male')
dataframe = dataframe.drop(columns=['Gender'])
dataframe['white'] = np.where(dataframe['Race1'] == 'white',1,0)
dataframe = dataframe.drop(columns=['Race1'])
dataframe = make_dummy_cols(dataframe, 'Education', 'education', '8th Grade')
dataframe = make_dummy_cols(dataframe, 'MaritalStatus', 'maritalstatus', 'Separated')
dataframe = make_dummy_cols(dataframe, 'HomeOwn', 'homeown', 'Other')
dataframe = make_dummy_cols(dataframe, 'Work', 'work', 'Looking')
dataframe['Diabetes'] = np.where(dataframe['Diabetes'] == 'Yes',1,0)
dataframe = make_dummy_cols(dataframe, 'HealthGen', 'healthgen', 'Poor')
dataframe = make_dummy_cols(dataframe, 'LittleInterest', 'littleinterest', 'None')
dataframe = make_dummy_cols(dataframe, 'Depressed', 'depressed', 'None')
dataframe['SleepTrouble'] = np.where(dataframe['SleepTrouble'] == 'Yes',1,0)
dataframe['PhysActive'] = np.where(dataframe['PhysActive'] == 'Yes',1,0)
dataframe['Alcohol12PlusYr'] = np.where(dataframe['Alcohol12PlusYr'] == 'Yes',1,0)
dataframe['SmokeNow'] = np.where(dataframe['SmokeNow'] == 'Yes',1,0)
dataframe['Smoke100'] = np.where(dataframe['Smoke100'] == 'Yes',1,0)
dataframe['Smoke100n'] = np.where(dataframe['Smoke100n'] == 'Yes',1,0)
dataframe['Marijuana'] = np.where(dataframe['Marijuana'] == 'Yes',1,0)
dataframe['RegularMarij'] = np.where(dataframe['RegularMarij'] == 'Yes',1,0)
dataframe['HardDrugs'] = np.where(dataframe['HardDrugs'] == 'Yes',1,0)
dataframe['SexEver'] = np.where(dataframe['SexEver'] == 'Yes',1,0)
dataframe['PregnantNow'] = np.where(dataframe['PregnantNow'] == 'Yes',1,0)
return dataframe | def fill_bin_num(dataframe, feature, bin_feature, bin_size, stat_measure, min_bin=None, max_bin=None, default_val='No'):
if min_bin is None:
min_bin = dataframe[bin_feature].min()
if max_bin is None:
max_bin = dataframe[bin_feature].max()
new_dataframe = dataframe.copy()
df_meancat = pd.DataFrame(columns=['interval', 'stat_measure'])
for (num_bin, subset) in dataframe.groupby(pd.cut(dataframe[bin_feature], np.arange(min_bin, max_bin + bin_size, bin_size), include_lowest=True)):
if stat_measure is 'mean':
row = [num_bin, subset[feature].mean()]
elif stat_measure is 'mode':
mode_ar = subset[feature].mode().values
if len(mode_ar) > 0:
row = [num_bin, mode_ar[0]]
else:
row = [num_bin, default_val]
else:
raise exception('Unknown statistical measure: ' + stat_measure)
df_meancat.loc[len(df_meancat)] = row
for (index, row_df) in dataframe[dataframe[feature].isna()].iterrows():
for (_, row_meancat) in df_meancat.iterrows():
if row_df[bin_feature] in row_meancat['interval']:
new_dataframe.at[index, feature] = row_meancat['stat_measure']
return new_dataframe
def make_dummy_cols(dataframe, column, prefix, drop_dummy):
dummy = pd.get_dummies(dataframe[column], prefix=prefix)
dummy = dummy.drop(columns=prefix + '_' + drop_dummy)
dataframe = pd.concat([dataframe, dummy], axis=1)
dataframe = dataframe.drop(columns=column)
return dataframe
def cleaning(dataframe_raw):
dataframe = dataframe_raw.copy()
dataframe = dataframe.set_index('ID')
dataframe.loc[(dataframe['Age'] <= 13) & dataframe['Education'].isna(), 'Education'] = 'Lower School/Kindergarten'
dataframe.loc[(dataframe['Age'] == 14) & dataframe['Education'].isna(), 'Education'] = '8th Grade'
dataframe.loc[(dataframe['Age'] <= 17) & dataframe['Education'].isna(), 'Education'] = '9 - 11th Grade'
dataframe.loc[(dataframe['Age'] <= 21) & dataframe['Education'].isna(), 'Education'] = 'High School'
dataframe['Education'] = dataframe['Education'].fillna('Some College')
dataframe.loc[(dataframe['Age'] <= 20) & dataframe['MaritalStatus'].isna(), 'MaritalStatus'] = 'NeverMarried'
dataframe.at[dataframe['MaritalStatus'].isna(), 'MaritalStatus'] = fill_bin_num(dataframe, 'MaritalStatus', 'Age', 5, 'mode', 20)
dataframe = dataframe.drop(columns=['HHIncome'])
dataframe.loc[dataframe['HHIncomeMid'].isna(), 'HHIncomeMid'] = dataframe['HHIncomeMid'].mean()
dataframe.loc[dataframe['Poverty'].isna(), 'Poverty'] = dataframe['Poverty'].mean()
dataframe.loc[dataframe['HomeRooms'].isna(), 'HomeRooms'] = dataframe['HomeRooms'].mean()
dataframe.loc[dataframe['HomeOwn'].isna(), 'HomeOwn'] = dataframe['HomeOwn'].mode().values[0]
dataframe.loc[dataframe['Work'].isna() & dataframe['Education'].isna() & (dataframe['Age'] <= 20), 'Work'] = 'NotWorking'
dataframe.loc[dataframe['Work'].isna(), 'Work'] = dataframe['Work'].mode().values[0]
dataframe = fill_bin_num(dataframe, 'Weight', 'Age', 2, 'mean')
dataframe = dataframe.drop(columns=['HeadCirc'])
for (index, row) in dataframe.iterrows():
if np.isnan(row['Height']) and (not np.isnan(row['Length'])):
dataframe.at[index, 'Height'] = row['Length']
dataframe = fill_bin_num(dataframe, 'Height', 'Age', 2, 'mean')
dataframe = dataframe.drop(columns=['Length'])
for (index, row) in dataframe[dataframe['BMI'].isna()].iterrows():
dataframe.at[index, 'BMI'] = row['Weight'] / (row['Height'] / 100) ** 2
dataframe = dataframe.drop(columns='BMICatUnder20yrs')
dataframe = dataframe.drop(columns='BMI_WHO')
dataframe = fill_bin_num(dataframe, 'Pulse', 'Age', 10, 'mean')
dataframe.loc[(dataframe['Age'] < 10) & dataframe['BPSysAve'].isna(), 'BPSysAve'] = 105
dataframe = fill_bin_num(dataframe, 'BPSysAve', 'Age', 5, 'mean', 10)
dataframe.loc[(dataframe['Age'] < 10) & dataframe['BPDiaAve'].isna(), 'BPDiaAve'] = 60
dataframe = fill_bin_num(dataframe, 'BPDiaAve', 'Age', 5, 'mean', 10)
dataframe = dataframe.drop(columns='BPSys1')
dataframe = dataframe.drop(columns='BPDia1')
dataframe = dataframe.drop(columns='BPSys2')
dataframe = dataframe.drop(columns='BPDia2')
dataframe = dataframe.drop(columns='BPSys3')
dataframe = dataframe.drop(columns='BPDia3')
dataframe = dataframe.drop(columns=['Testosterone'])
dataframe.loc[(dataframe['Age'] < 10) & dataframe['DirectChol'].isna(), 'DirectChol'] = 0
dataframe = fill_bin_num(dataframe, 'DirectChol', 'Age', 5, 'mean', 10)
dataframe.loc[(dataframe['Age'] < 10) & dataframe['TotChol'].isna(), 'TotChol'] = 0
dataframe = fill_bin_num(dataframe, 'TotChol', 'Age', 5, 'mean', 10)
dataframe = dataframe.drop(columns=['UrineVol1'])
dataframe = dataframe.drop(columns=['UrineFlow1'])
dataframe = dataframe.drop(columns=['UrineVol2'])
dataframe = dataframe.drop(columns=['UrineFlow2'])
dataframe['Diabetes'] = dataframe['Diabetes'].fillna('No')
dataframe['DiabetesAge'] = dataframe['DiabetesAge'].fillna(0)
dataframe.loc[(dataframe['Age'] <= 12) & dataframe['HealthGen'].isna(), 'HealthGen'] = 'Good'
dataframe = fill_bin_num(dataframe, 'HealthGen', 'Age', 5, 'mode', 10)
dataframe.loc[(dataframe['Age'] <= 12) & dataframe['DaysMentHlthBad'].isna(), 'DaysMentHlthBad'] = 0
dataframe = fill_bin_num(dataframe, 'DaysMentHlthBad', 'Age', 5, 'mean', 10)
dataframe.loc[(dataframe['Age'] <= 15) & dataframe['LittleInterest'].isna(), 'LittleInterest'] = 'None'
dataframe = fill_bin_num(dataframe, 'LittleInterest', 'Age', 5, 'mode', 15)
dataframe.loc[(dataframe['Age'] <= 12) & dataframe['DaysMentHlthBad'].isna(), 'DaysMentHlthBad'] = 0
dataframe = fill_bin_num(dataframe, 'DaysMentHlthBad', 'Age', 5, 'mean', 10)
for (index, row) in dataframe.iterrows():
if np.isnan(row['nBabies']) and (not np.isnan(row['nPregnancies'])):
dataframe.at[index, 'nBabies'] = row['nPregnancies']
dataframe['nBabies'] = dataframe['nBabies'].fillna(0)
dataframe['nPregnancies'] = dataframe['nPregnancies'].fillna(0)
dataframe['Age1stBaby'] = dataframe['Age1stBaby'].fillna(0)
dataframe.loc[(dataframe['Age'] == 0) & dataframe['SleepHrsNight'].isna(), 'SleepHrsNight'] = 14
dataframe.loc[(dataframe['Age'] <= 2) & dataframe['SleepHrsNight'].isna(), 'SleepHrsNight'] = 12
dataframe.loc[(dataframe['Age'] <= 5) & dataframe['SleepHrsNight'].isna(), 'SleepHrsNight'] = 10
dataframe.loc[(dataframe['Age'] <= 10) & dataframe['SleepHrsNight'].isna(), 'SleepHrsNight'] = 9
dataframe.loc[(dataframe['Age'] <= 15) & dataframe['SleepHrsNight'].isna(), 'SleepHrsNight'] = 8
dataframe['SleepHrsNight'] = dataframe['SleepHrsNight'].fillna(dataframe_raw['SleepHrsNight'].mean())
dataframe['SleepTrouble'] = dataframe['SleepTrouble'].fillna('No')
dataframe.loc[(dataframe['Age'] <= 4) & dataframe['PhysActive'].isna(), 'PhysActive'] = 'No'
dataframe = fill_bin_num(dataframe, 'PhysActive', 'Age', 2, 'mode', 16)
dataframe['PhysActive'] = dataframe['PhysActive'].fillna('Yes')
dataframe = dataframe.drop(columns=['PhysActiveDays'])
dataframe = dataframe.drop(columns=['TVHrsDay'])
dataframe = dataframe.drop(columns=['TVHrsDayChild'])
dataframe = dataframe.drop(columns=['CompHrsDay'])
dataframe = dataframe.drop(columns=['CompHrsDayChild'])
dataframe.loc[(dataframe['Age'] < 18) & dataframe['Alcohol12PlusYr'].isna(), 'Alcohol12PlusYr'] = 'No'
dataframe = fill_bin_num(dataframe, 'Alcohol12PlusYr', 'Age', 5, 'mode', 18)
dataframe.loc[(dataframe['Age'] < 18) & dataframe['AlcoholDay'].isna(), 'AlcoholDay'] = 0
dataframe = fill_bin_num(dataframe, 'AlcoholDay', 'Age', 5, 'mean', 18)
dataframe.loc[(dataframe['Age'] < 18) & dataframe['AlcoholYear'].isna(), 'AlcoholYear'] = 0
dataframe = fill_bin_num(dataframe, 'AlcoholYear', 'Age', 5, 'mean', 18)
dataframe.loc[(dataframe['Age'] < 20) & dataframe['SmokeNow'].isna(), 'SmokeNow'] = 'No'
dataframe = fill_bin_num(dataframe, 'SmokeNow', 'Age', 5, 'mode', 20)
dataframe['Smoke100'] = dataframe['Smoke100'].fillna('No')
dataframe['Smoke100n'] = dataframe['Smoke100n'].fillna('No')
dataframe.loc[(dataframe['SmokeNow'] == 'No') & dataframe['SmokeAge'].isna(), 'SmokeAge'] = 0
dataframe = fill_bin_num(dataframe, 'SmokeAge', 'Age', 5, 'mean', 20)
dataframe.loc[(dataframe['Age'] < 18) & dataframe['Marijuana'].isna(), 'Marijuana'] = 'No'
dataframe.loc[dataframe['Marijuana'].isna() & (dataframe['SmokeNow'] == 'No'), 'Marijuana'] = 'No'
dataframe = fill_bin_num(dataframe, 'Marijuana', 'Age', 5, 'mode', 20)
dataframe.loc[(dataframe['Marijuana'] == 'No') & dataframe['AgeFirstMarij'].isna(), 'AgeFirstMarij'] = 0
dataframe = fill_bin_num(dataframe, 'AgeFirstMarij', 'Age', 5, 'mean', 20)
dataframe.loc[(dataframe['Marijuana'] == 'No') & dataframe['RegularMarij'].isna(), 'RegularMarij'] = 'No'
dataframe = fill_bin_num(dataframe, 'RegularMarij', 'Age', 5, 'mode', 20)
dataframe.loc[(dataframe['RegularMarij'] == 'No') & dataframe['AgeRegMarij'].isna(), 'AgeRegMarij'] = 0
dataframe = fill_bin_num(dataframe, 'AgeRegMarij', 'Age', 5, 'mean', 20)
dataframe.loc[(dataframe['Age'] < 18) & dataframe['HardDrugs'].isna(), 'HardDrugs'] = 'No'
dataframe = fill_bin_num(dataframe, 'HardDrugs', 'Age', 5, 'mode', 18)
mode_sex_age = dataframe['SexAge'].mode()[0]
dataframe.loc[(dataframe['Age'] <= mode_sex_age) & dataframe['SexEver'].isna(), 'SexEver'] = 'No'
dataframe['SexEver'] = dataframe['SexEver'].fillna('Yes')
dataframe.loc[(dataframe['SexEver'] == 'No') & dataframe['SexAge'].isna(), 'SexAge'] = 0
dataframe.loc[dataframe['SexAge'].isna() & (dataframe['Age'] < mode_sex_age), 'SexAge'] = dataframe.loc[dataframe['SexAge'].isna() & (dataframe['Age'] < mode_sex_age), 'Age']
dataframe['SexAge'] = dataframe['SexAge'].fillna(mode_sex_age)
dataframe.loc[(dataframe['SexEver'] == 'No') & dataframe['SexNumPartnLife'].isna(), 'SexNumPartnLife'] = 0
dataframe = fill_bin_num(dataframe, 'SexNumPartnLife', 'Age', 5, 'mean')
dataframe['SexNumPartnLife'] = dataframe_raw.loc[(dataframe_raw['Age'] >= 60) & (dataframe_raw['Age'] <= 70), 'SexNumPartnLife'].mode()[0]
dataframe.loc[(dataframe['SexEver'] == 'No') & dataframe['SexNumPartYear'].isna(), 'SexNumPartYear'] = 0
dataframe = fill_bin_num(dataframe, 'SexNumPartYear', 'Age', 10, 'mean')
dataframe['SexNumPartYear'] = dataframe['SexNumPartYear'].fillna(0)
dataframe = dataframe.drop(columns=['SameSex'])
dataframe = dataframe.drop(columns=['SexOrientation'])
dataframe['PregnantNow'] = dataframe['PregnantNow'].fillna('No')
dataframe['male'] = 1 * (dataframe['Gender'] == 'male')
dataframe = dataframe.drop(columns=['Gender'])
dataframe['white'] = np.where(dataframe['Race1'] == 'white', 1, 0)
dataframe = dataframe.drop(columns=['Race1'])
dataframe = make_dummy_cols(dataframe, 'Education', 'education', '8th Grade')
dataframe = make_dummy_cols(dataframe, 'MaritalStatus', 'maritalstatus', 'Separated')
dataframe = make_dummy_cols(dataframe, 'HomeOwn', 'homeown', 'Other')
dataframe = make_dummy_cols(dataframe, 'Work', 'work', 'Looking')
dataframe['Diabetes'] = np.where(dataframe['Diabetes'] == 'Yes', 1, 0)
dataframe = make_dummy_cols(dataframe, 'HealthGen', 'healthgen', 'Poor')
dataframe = make_dummy_cols(dataframe, 'LittleInterest', 'littleinterest', 'None')
dataframe = make_dummy_cols(dataframe, 'Depressed', 'depressed', 'None')
dataframe['SleepTrouble'] = np.where(dataframe['SleepTrouble'] == 'Yes', 1, 0)
dataframe['PhysActive'] = np.where(dataframe['PhysActive'] == 'Yes', 1, 0)
dataframe['Alcohol12PlusYr'] = np.where(dataframe['Alcohol12PlusYr'] == 'Yes', 1, 0)
dataframe['SmokeNow'] = np.where(dataframe['SmokeNow'] == 'Yes', 1, 0)
dataframe['Smoke100'] = np.where(dataframe['Smoke100'] == 'Yes', 1, 0)
dataframe['Smoke100n'] = np.where(dataframe['Smoke100n'] == 'Yes', 1, 0)
dataframe['Marijuana'] = np.where(dataframe['Marijuana'] == 'Yes', 1, 0)
dataframe['RegularMarij'] = np.where(dataframe['RegularMarij'] == 'Yes', 1, 0)
dataframe['HardDrugs'] = np.where(dataframe['HardDrugs'] == 'Yes', 1, 0)
dataframe['SexEver'] = np.where(dataframe['SexEver'] == 'Yes', 1, 0)
dataframe['PregnantNow'] = np.where(dataframe['PregnantNow'] == 'Yes', 1, 0)
return dataframe |
def main():
num = int(input("introduce un numero:"))
for x in range (1,num):
print(x, end=",")
else:
print(num, end="") | def main():
num = int(input('introduce un numero:'))
for x in range(1, num):
print(x, end=',')
else:
print(num, end='') |
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