content stringlengths 7 1.05M | fixed_cases stringlengths 1 1.28M |
|---|---|
'''
Created on Sep 9, 2013
@author: akittredge
'''
| """
Created on Sep 9, 2013
@author: akittredge
""" |
# import pyperclip
class User:
'''
the user class
'''
user_list = []
def __init__(self, first_name, last_name, number, email, password):
self.first_name = first_name
self.last_name = last_name
self.phone_number = number
self.email = email
self.password = password
def save_user(self):
'''
this saves the user into the user_list
'''
User.user_list.append(self)
def delete_user(self):
'''
this deletes the user saved from the user_list
'''
User.user_list.remove(self)
@classmethod
def find_by_first_name(cls, first_name):
'''
finds the first name and displays it
'''
for user in cls.user_list:
if user.first_name == first_name:
return user
@classmethod
def user_exist(cls, first_name):
'''
confirms whether the user does exist or not
'''
for user in cls.user_list:
if user.first_name == first_name:
return True
else:
return False
@classmethod
def display_users(cls):
'''
display the contact list by returning it
'''
return cls.user_list
# @classmethod
# def copy_email(cls, first_name):
# user_found = User.find_by_first_name(first_name)
# pyperclip.copy(user_found.email) | class User:
"""
the user class
"""
user_list = []
def __init__(self, first_name, last_name, number, email, password):
self.first_name = first_name
self.last_name = last_name
self.phone_number = number
self.email = email
self.password = password
def save_user(self):
"""
this saves the user into the user_list
"""
User.user_list.append(self)
def delete_user(self):
"""
this deletes the user saved from the user_list
"""
User.user_list.remove(self)
@classmethod
def find_by_first_name(cls, first_name):
"""
finds the first name and displays it
"""
for user in cls.user_list:
if user.first_name == first_name:
return user
@classmethod
def user_exist(cls, first_name):
"""
confirms whether the user does exist or not
"""
for user in cls.user_list:
if user.first_name == first_name:
return True
else:
return False
@classmethod
def display_users(cls):
"""
display the contact list by returning it
"""
return cls.user_list |
load("@bazel_tools//tools/build_defs/repo:http.bzl", "http_archive")
PROTOBUF_VERSION = "3.6.1.3"
SHA = "9510dd2afc29e7245e9e884336f848c8a6600a14ae726adb6befdb4f786f0be2"
def generate_protobuf():
http_archive(
name = "com_google_protobuf",
urls = ["https://github.com/protocolbuffers/protobuf/archive/v%s.zip" %
PROTOBUF_VERSION],
sha256 = SHA,
strip_prefix = "protobuf-" + PROTOBUF_VERSION,
)
| load('@bazel_tools//tools/build_defs/repo:http.bzl', 'http_archive')
protobuf_version = '3.6.1.3'
sha = '9510dd2afc29e7245e9e884336f848c8a6600a14ae726adb6befdb4f786f0be2'
def generate_protobuf():
http_archive(name='com_google_protobuf', urls=['https://github.com/protocolbuffers/protobuf/archive/v%s.zip' % PROTOBUF_VERSION], sha256=SHA, strip_prefix='protobuf-' + PROTOBUF_VERSION) |
#
# @lc app=leetcode id=69 lang=python3
#
# [69] Sqrt(x)
#
# @lc code=start
class Solution:
def mySqrt(self, x: int) -> int:
v = 1
result = 0
while True:
if v * v > x:
result = v - 1
break
v = v + 1
return result
# @lc code=end
| class Solution:
def my_sqrt(self, x: int) -> int:
v = 1
result = 0
while True:
if v * v > x:
result = v - 1
break
v = v + 1
return result |
def morris_pratt_string_matching(t, w, m, n):
B = prefix_suffix(w)
i = 0
while i <= n - m + 1:
j = 0
while j < m and t[i + j + 1] == w[j + 1]:
j = j + 1
if j == m:
return True
i, j = i + j - B[j], max(0, B[j])
return False | def morris_pratt_string_matching(t, w, m, n):
b = prefix_suffix(w)
i = 0
while i <= n - m + 1:
j = 0
while j < m and t[i + j + 1] == w[j + 1]:
j = j + 1
if j == m:
return True
(i, j) = (i + j - B[j], max(0, B[j]))
return False |
teste = list()
teste.append('Pedro')
teste.append(15)
galera = list()
galera.append(teste[:])
teste[0] = 'Ronaldo'
teste[1] = '22'
galera.append(teste[:])
print(galera)
| teste = list()
teste.append('Pedro')
teste.append(15)
galera = list()
galera.append(teste[:])
teste[0] = 'Ronaldo'
teste[1] = '22'
galera.append(teste[:])
print(galera) |
_base_ = [
'../_base_/datasets/coco_detection.py',
'../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py',
'../_base_/swa.py'
]
num_stages = 6
num_proposals = 512
model = dict(
type='SparseRCNN',
pretrained = 'https://github.com/SwinTransformer/storage/releases/download/v1.0.0/swin_base_patch4_window7_224_22k.pth',
backbone=dict(
type='SwinTransformer',
embed_dim=128,
depths=[2, 2, 18, 2],
num_heads=[4, 8, 16, 32],
window_size=7,
mlp_ratio=4.,
qkv_bias=True,
qk_scale=None,
drop_rate=0.,
attn_drop_rate=0.,
ape=False,
drop_path_rate=0.3,
patch_norm=True,
out_indices=(0, 1, 2, 3),
use_checkpoint=True,
),
neck=dict(
type='PAFPNX',
in_channels=[128, 256, 512, 1024],
out_channels=256,
start_level=0,
add_extra_convs='on_output',
num_outs=4,
relu_before_extra_convs=True,
pafpn_conv_cfg=dict(type='DCNv2'),
norm_cfg=dict(type='GN', num_groups=32, requires_grad=True)),
rpn_head=dict(
type='EmbeddingRPNHead',
num_proposals=num_proposals,
proposal_feature_channel=256),
roi_head=dict(
type='SparseRoIHead',
num_stages=num_stages,
stage_loss_weights=[1] * num_stages,
proposal_feature_channel=256,
bbox_roi_extractor=dict(
type='SingleRoIExtractor',
roi_layer=dict(type='RoIAlign', output_size=7, sampling_ratio=2),
out_channels=256,
featmap_strides=[4, 8, 16, 32]),
bbox_head=[
dict(
type='DIIHead',
num_classes=34,
num_ffn_fcs=2,
num_heads=8,
num_cls_fcs=1,
num_reg_fcs=3,
feedforward_channels=2048,
in_channels=256,
dropout=0.0,
ffn_act_cfg=dict(type='ReLU', inplace=True),
dynamic_conv_cfg=dict(
type='DynamicConv',
in_channels=256,
feat_channels=64,
out_channels=256,
input_feat_shape=7,
act_cfg=dict(type='ReLU', inplace=True),
norm_cfg=dict(type='LN')),
loss_bbox=dict(type='L1Loss', loss_weight=5.0),
loss_iou=dict(type='CIoULoss', loss_weight=2.0),
loss_cls=dict(
type='FocalLoss',
use_sigmoid=True,
gamma=2.0,
alpha=0.25,
loss_weight=2.0),
bbox_coder=dict(
type='DeltaXYWHBBoxCoder',
clip_border=False,
target_means=[0., 0., 0., 0.],
target_stds=[0.5, 0.5, 1., 1.])) for _ in range(num_stages)
]),
# training and testing settings
train_cfg=dict(
rpn=None,
rcnn=[
dict(
assigner=dict(
type='HungarianAssigner',
cls_cost=dict(type='FocalLossCost', weight=2.0),
reg_cost=dict(type='BBoxL1Cost', weight=5.0),
iou_cost=dict(type='IoUCost', iou_mode='giou',
weight=2.0)),
sampler=dict(type='PseudoSampler'),
pos_weight=1) for _ in range(num_stages)
]),
test_cfg=dict(rpn=None, rcnn=dict(max_per_img=100)))
# data setting
dataset_type = 'CocoDataset'
data_root = '/content/data/'
img_norm_cfg = dict(mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)
albu_train_transforms = [
dict(type='ShiftScaleRotate', shift_limit=0.0625, scale_limit=0.0, rotate_limit=0, interpolation=1, p=0.5),
dict(type='RandomBrightnessContrast', brightness_limit=[0.1, 0.3], contrast_limit=[0.1, 0.3], p=0.2),
dict(
type='OneOf',
transforms=[
dict(
type='RGBShift',
r_shift_limit=10,
g_shift_limit=10,
b_shift_limit=10,
p=1.0),
dict(
type='HueSaturationValue',
hue_shift_limit=20,
sat_shift_limit=30,
val_shift_limit=20,
p=1.0)
],
p=0.1),
dict(type='ImageCompression', quality_lower=85, quality_upper=95, p=0.2),
dict(type='ChannelShuffle', p=0.1),
dict(
type='OneOf',
transforms=[
dict(type='Blur', blur_limit=3, p=1.0),
dict(type='MedianBlur', blur_limit=3, p=1.0)
],
p=0.1),
]
train_pipeline = [
dict(type='LoadImageFromFile'),
dict(type='LoadAnnotations', with_bbox=True),
dict(
type='RandomCrop',
crop_type='relative_range',
crop_size=(0.9, 0.9),
allow_negative_crop = True),
dict(
type='Resize',
img_scale=[(640, 640), (960, 960)],
multiscale_mode='range',
keep_ratio=True),
dict(
type='CutOut',
n_holes=(5, 10),
cutout_shape=[(4, 4), (4, 8), (8, 4), (8, 8),
(16, 8), (8, 16), (16, 16), (16, 32), (32, 16), (32, 32),
(32, 48), (48, 32), (48, 48)]),
dict(type='RandomFlip', flip_ratio=0.5),
dict(type='Pad', size_divisor=32),
dict(
type='Albu',
transforms=albu_train_transforms,
bbox_params=dict(
type='BboxParams',
format='pascal_voc',
label_fields=['gt_labels'],
min_visibility=0.0,
filter_lost_elements=True),
keymap={
'img': 'image',
'gt_bboxes': 'bboxes'
},
update_pad_shape=False,
skip_img_without_anno=True),
dict(type='Normalize', **img_norm_cfg),
dict(type='DefaultFormatBundle'),
dict(type='Collect', keys=['img', 'gt_bboxes', 'gt_labels']),
]
test_pipeline = [
dict(type='LoadImageFromFile'),
dict(
type='MultiScaleFlipAug',
img_scale=(800, 800),
flip=False,
transforms=[
dict(type='Resize', keep_ratio=True),
dict(type='RandomFlip'),
dict(type='Normalize', **img_norm_cfg),
dict(type='Pad', size_divisor=32),
dict(type='DefaultFormatBundle'),
dict(type='Collect', keys=['img']),
])
]
data = dict(
samples_per_gpu=12,
workers_per_gpu=4,
train=dict(type = dataset_type,
ann_file = data_root + '/annotations/instances_train2017.json',
img_prefix = 'train_images/',
pipeline=train_pipeline),
val=dict(type = dataset_type,
ann_file = data_root + '/annotations/instances_val2017.json',
img_prefix = 'val_images/',
pipeline=test_pipeline,
samples_per_gpu = 24),
test=dict(pipeline=test_pipeline))
# optimizer
optimizer = dict(_delete_=True, type='AdamW', lr=0.000025, weight_decay=0.0001, paramwise_cfg=dict(custom_keys={'absolute_pos_embed': dict(decay_mult=0.), 'relative_position_bias_table': dict(decay_mult=0.), 'norm': dict(decay_mult=0.)}))
optimizer_config = dict(_delete_=True, grad_clip=None)
log_config = dict(interval = 10)
# learning policy
lr_config = dict(
policy='CosineAnnealing',
min_lr_ratio = 0.12,
warmup='linear',
warmup_iters=500,
warmup_ratio=0.1,
)
runner = dict(type='IterBasedRunner', max_iters=3000, max_epochs = None)
checkpoint_config = dict(interval = 100)
evaluation = dict(interval = 100, metric = 'bbox')
fp16 = dict(loss_scale=512.)
# runtime
#load_from = '/gdrive/My Drive/data/sparse_rcnn_r101_fpn_300_proposals_crop_mstrain_480-800_3x_coco_20201223_023452-c23c3564.pth'
resume_from = None
workflow = [('train', 1)] | _base_ = ['../_base_/datasets/coco_detection.py', '../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py', '../_base_/swa.py']
num_stages = 6
num_proposals = 512
model = dict(type='SparseRCNN', pretrained='https://github.com/SwinTransformer/storage/releases/download/v1.0.0/swin_base_patch4_window7_224_22k.pth', backbone=dict(type='SwinTransformer', embed_dim=128, depths=[2, 2, 18, 2], num_heads=[4, 8, 16, 32], window_size=7, mlp_ratio=4.0, qkv_bias=True, qk_scale=None, drop_rate=0.0, attn_drop_rate=0.0, ape=False, drop_path_rate=0.3, patch_norm=True, out_indices=(0, 1, 2, 3), use_checkpoint=True), neck=dict(type='PAFPNX', in_channels=[128, 256, 512, 1024], out_channels=256, start_level=0, add_extra_convs='on_output', num_outs=4, relu_before_extra_convs=True, pafpn_conv_cfg=dict(type='DCNv2'), norm_cfg=dict(type='GN', num_groups=32, requires_grad=True)), rpn_head=dict(type='EmbeddingRPNHead', num_proposals=num_proposals, proposal_feature_channel=256), roi_head=dict(type='SparseRoIHead', num_stages=num_stages, stage_loss_weights=[1] * num_stages, proposal_feature_channel=256, bbox_roi_extractor=dict(type='SingleRoIExtractor', roi_layer=dict(type='RoIAlign', output_size=7, sampling_ratio=2), out_channels=256, featmap_strides=[4, 8, 16, 32]), bbox_head=[dict(type='DIIHead', num_classes=34, num_ffn_fcs=2, num_heads=8, num_cls_fcs=1, num_reg_fcs=3, feedforward_channels=2048, in_channels=256, dropout=0.0, ffn_act_cfg=dict(type='ReLU', inplace=True), dynamic_conv_cfg=dict(type='DynamicConv', in_channels=256, feat_channels=64, out_channels=256, input_feat_shape=7, act_cfg=dict(type='ReLU', inplace=True), norm_cfg=dict(type='LN')), loss_bbox=dict(type='L1Loss', loss_weight=5.0), loss_iou=dict(type='CIoULoss', loss_weight=2.0), loss_cls=dict(type='FocalLoss', use_sigmoid=True, gamma=2.0, alpha=0.25, loss_weight=2.0), bbox_coder=dict(type='DeltaXYWHBBoxCoder', clip_border=False, target_means=[0.0, 0.0, 0.0, 0.0], target_stds=[0.5, 0.5, 1.0, 1.0])) for _ in range(num_stages)]), train_cfg=dict(rpn=None, rcnn=[dict(assigner=dict(type='HungarianAssigner', cls_cost=dict(type='FocalLossCost', weight=2.0), reg_cost=dict(type='BBoxL1Cost', weight=5.0), iou_cost=dict(type='IoUCost', iou_mode='giou', weight=2.0)), sampler=dict(type='PseudoSampler'), pos_weight=1) for _ in range(num_stages)]), test_cfg=dict(rpn=None, rcnn=dict(max_per_img=100)))
dataset_type = 'CocoDataset'
data_root = '/content/data/'
img_norm_cfg = dict(mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)
albu_train_transforms = [dict(type='ShiftScaleRotate', shift_limit=0.0625, scale_limit=0.0, rotate_limit=0, interpolation=1, p=0.5), dict(type='RandomBrightnessContrast', brightness_limit=[0.1, 0.3], contrast_limit=[0.1, 0.3], p=0.2), dict(type='OneOf', transforms=[dict(type='RGBShift', r_shift_limit=10, g_shift_limit=10, b_shift_limit=10, p=1.0), dict(type='HueSaturationValue', hue_shift_limit=20, sat_shift_limit=30, val_shift_limit=20, p=1.0)], p=0.1), dict(type='ImageCompression', quality_lower=85, quality_upper=95, p=0.2), dict(type='ChannelShuffle', p=0.1), dict(type='OneOf', transforms=[dict(type='Blur', blur_limit=3, p=1.0), dict(type='MedianBlur', blur_limit=3, p=1.0)], p=0.1)]
train_pipeline = [dict(type='LoadImageFromFile'), dict(type='LoadAnnotations', with_bbox=True), dict(type='RandomCrop', crop_type='relative_range', crop_size=(0.9, 0.9), allow_negative_crop=True), dict(type='Resize', img_scale=[(640, 640), (960, 960)], multiscale_mode='range', keep_ratio=True), dict(type='CutOut', n_holes=(5, 10), cutout_shape=[(4, 4), (4, 8), (8, 4), (8, 8), (16, 8), (8, 16), (16, 16), (16, 32), (32, 16), (32, 32), (32, 48), (48, 32), (48, 48)]), dict(type='RandomFlip', flip_ratio=0.5), dict(type='Pad', size_divisor=32), dict(type='Albu', transforms=albu_train_transforms, bbox_params=dict(type='BboxParams', format='pascal_voc', label_fields=['gt_labels'], min_visibility=0.0, filter_lost_elements=True), keymap={'img': 'image', 'gt_bboxes': 'bboxes'}, update_pad_shape=False, skip_img_without_anno=True), dict(type='Normalize', **img_norm_cfg), dict(type='DefaultFormatBundle'), dict(type='Collect', keys=['img', 'gt_bboxes', 'gt_labels'])]
test_pipeline = [dict(type='LoadImageFromFile'), dict(type='MultiScaleFlipAug', img_scale=(800, 800), flip=False, transforms=[dict(type='Resize', keep_ratio=True), dict(type='RandomFlip'), dict(type='Normalize', **img_norm_cfg), dict(type='Pad', size_divisor=32), dict(type='DefaultFormatBundle'), dict(type='Collect', keys=['img'])])]
data = dict(samples_per_gpu=12, workers_per_gpu=4, train=dict(type=dataset_type, ann_file=data_root + '/annotations/instances_train2017.json', img_prefix='train_images/', pipeline=train_pipeline), val=dict(type=dataset_type, ann_file=data_root + '/annotations/instances_val2017.json', img_prefix='val_images/', pipeline=test_pipeline, samples_per_gpu=24), test=dict(pipeline=test_pipeline))
optimizer = dict(_delete_=True, type='AdamW', lr=2.5e-05, weight_decay=0.0001, paramwise_cfg=dict(custom_keys={'absolute_pos_embed': dict(decay_mult=0.0), 'relative_position_bias_table': dict(decay_mult=0.0), 'norm': dict(decay_mult=0.0)}))
optimizer_config = dict(_delete_=True, grad_clip=None)
log_config = dict(interval=10)
lr_config = dict(policy='CosineAnnealing', min_lr_ratio=0.12, warmup='linear', warmup_iters=500, warmup_ratio=0.1)
runner = dict(type='IterBasedRunner', max_iters=3000, max_epochs=None)
checkpoint_config = dict(interval=100)
evaluation = dict(interval=100, metric='bbox')
fp16 = dict(loss_scale=512.0)
resume_from = None
workflow = [('train', 1)] |
abi = '''[
{
"inputs": [
{
"internalType": "int256",
"name": "bp",
"type": "int256"
},
{
"internalType": "int256",
"name": "sp",
"type": "int256"
}
],
"payable": false,
"stateMutability": "nonpayable",
"type": "constructor"
},
{
"anonymous": false,
"inputs": [
{
"indexed": true,
"internalType": "address",
"name": "partner",
"type": "address"
},
{
"indexed": false,
"internalType": "int256",
"name": "amountPayed",
"type": "int256"
},
{
"indexed": false,
"internalType": "int256",
"name": "credit",
"type": "int256"
}
],
"name": "contractPay",
"type": "event"
},
{
"anonymous": false,
"inputs": [
{
"indexed": true,
"internalType": "address",
"name": "producer",
"type": "address"
},
{
"indexed": false,
"internalType": "int256",
"name": "offeredEnergy",
"type": "int256"
},
{
"indexed": false,
"internalType": "int256",
"name": "sellPrice",
"type": "int256"
}
],
"name": "enterEvent",
"type": "event"
},
{
"anonymous": false,
"inputs": [
{
"indexed": false,
"internalType": "int256",
"name": "dCover",
"type": "int256"
},
{
"indexed": false,
"internalType": "int256",
"name": "dCoverPricePerUnit",
"type": "int256"
},
{
"indexed": false,
"internalType": "int256",
"name": "batteryDelta",
"type": "int256"
},
{
"indexed": false,
"internalType": "int256",
"name": "bLoad",
"type": "int256"
},
{
"indexed": false,
"internalType": "int256",
"name": "bPricePerUnit",
"type": "int256"
},
{
"indexed": false,
"internalType": "int256",
"name": "oDelta",
"type": "int256"
},
{
"indexed": false,
"internalType": "int256",
"name": "oBp",
"type": "int256"
},
{
"indexed": false,
"internalType": "int256",
"name": "oSp",
"type": "int256"
}
],
"name": "generalInfo",
"type": "event"
},
{
"anonymous": false,
"inputs": [
{
"indexed": true,
"internalType": "address",
"name": "matched",
"type": "address"
},
{
"indexed": false,
"internalType": "int256",
"name": "matchedEnergy",
"type": "int256"
},
{
"indexed": false,
"internalType": "int256",
"name": "creditChange",
"type": "int256"
}
],
"name": "matchEvent",
"type": "event"
},
{
"constant": false,
"inputs": [],
"name": "coverCredit",
"outputs": [],
"payable": true,
"stateMutability": "payable",
"type": "function"
},
{
"constant": false,
"inputs": [],
"name": "drainContract",
"outputs": [],
"payable": false,
"stateMutability": "nonpayable",
"type": "function"
},
{
"constant": false,
"inputs": [
{
"internalType": "int256",
"name": "enteredEnergy",
"type": "int256"
},
{
"internalType": "int256",
"name": "sPrice",
"type": "int256"
}
],
"name": "enterEnergy",
"outputs": [],
"payable": false,
"stateMutability": "nonpayable",
"type": "function"
},
{
"constant": true,
"inputs": [],
"name": "getBatteryLoad",
"outputs": [
{
"internalType": "int256",
"name": "",
"type": "int256"
}
],
"payable": false,
"stateMutability": "view",
"type": "function"
},
{
"constant": true,
"inputs": [],
"name": "getBatteryPricePerUnit",
"outputs": [
{
"internalType": "int256",
"name": "",
"type": "int256"
}
],
"payable": false,
"stateMutability": "view",
"type": "function"
},
{
"constant": true,
"inputs": [],
"name": "getBuyPrice",
"outputs": [
{
"internalType": "int256",
"name": "",
"type": "int256"
}
],
"payable": false,
"stateMutability": "view",
"type": "function"
},
{
"constant": true,
"inputs": [],
"name": "getContractFunds",
"outputs": [
{
"internalType": "uint256",
"name": "",
"type": "uint256"
}
],
"payable": false,
"stateMutability": "view",
"type": "function"
},
{
"constant": true,
"inputs": [],
"name": "getCredit",
"outputs": [
{
"internalType": "int256",
"name": "",
"type": "int256"
}
],
"payable": false,
"stateMutability": "view",
"type": "function"
},
{
"constant": true,
"inputs": [
{
"internalType": "address",
"name": "ofAddr",
"type": "address"
}
],
"name": "getMatchBlock",
"outputs": [
{
"internalType": "uint256",
"name": "",
"type": "uint256"
}
],
"payable": false,
"stateMutability": "view",
"type": "function"
},
{
"constant": true,
"inputs": [],
"name": "getSellPrice",
"outputs": [
{
"internalType": "int256",
"name": "",
"type": "int256"
}
],
"payable": false,
"stateMutability": "view",
"type": "function"
},
{
"constant": true,
"inputs": [
{
"internalType": "address",
"name": "account",
"type": "address"
}
],
"name": "getSpecCredit",
"outputs": [
{
"internalType": "int256",
"name": "",
"type": "int256"
}
],
"payable": false,
"stateMutability": "view",
"type": "function"
},
{
"constant": true,
"inputs": [],
"name": "getTotalBatteryPrice",
"outputs": [
{
"internalType": "int256",
"name": "",
"type": "int256"
}
],
"payable": false,
"stateMutability": "view",
"type": "function"
},
{
"constant": true,
"inputs": [
{
"internalType": "address",
"name": "ofAddr",
"type": "address"
}
],
"name": "getUpdateBlock",
"outputs": [
{
"internalType": "uint256",
"name": "",
"type": "uint256"
}
],
"payable": false,
"stateMutability": "view",
"type": "function"
},
{
"constant": false,
"inputs": [],
"name": "matchOrders",
"outputs": [],
"payable": false,
"stateMutability": "nonpayable",
"type": "function"
},
{
"constant": false,
"inputs": [],
"name": "repairBlockNumbers",
"outputs": [],
"payable": false,
"stateMutability": "nonpayable",
"type": "function"
},
{
"constant": false,
"inputs": [
{
"internalType": "int256",
"name": "newCredit",
"type": "int256"
}
],
"name": "setAllCredits",
"outputs": [],
"payable": false,
"stateMutability": "nonpayable",
"type": "function"
},
{
"constant": false,
"inputs": [
{
"internalType": "int256",
"name": "newCap",
"type": "int256"
}
],
"name": "setBatteryCapacity",
"outputs": [],
"payable": false,
"stateMutability": "nonpayable",
"type": "function"
},
{
"constant": false,
"inputs": [
{
"internalType": "int8",
"name": "newEff",
"type": "int8"
}
],
"name": "setBatteryEff",
"outputs": [],
"payable": false,
"stateMutability": "nonpayable",
"type": "function"
},
{
"constant": false,
"inputs": [
{
"internalType": "int256",
"name": "newLoad",
"type": "int256"
}
],
"name": "setBatteryLoad",
"outputs": [],
"payable": false,
"stateMutability": "nonpayable",
"type": "function"
},
{
"constant": false,
"inputs": [
{
"internalType": "int256",
"name": "newPrice",
"type": "int256"
}
],
"name": "setBuyPrice",
"outputs": [],
"payable": false,
"stateMutability": "nonpayable",
"type": "function"
},
{
"constant": false,
"inputs": [
{
"internalType": "int256",
"name": "newPrice",
"type": "int256"
}
],
"name": "setSellPrice",
"outputs": [],
"payable": false,
"stateMutability": "nonpayable",
"type": "function"
},
{
"constant": false,
"inputs": [
{
"internalType": "int256",
"name": "nPr",
"type": "int256"
}
],
"name": "setTotalBatPrice",
"outputs": [],
"payable": false,
"stateMutability": "nonpayable",
"type": "function"
}
]''' | abi = '[\n\t{\n\t\t"inputs": [\n\t\t\t{\n\t\t\t\t"internalType": "int256",\n\t\t\t\t"name": "bp",\n\t\t\t\t"type": "int256"\n\t\t\t},\n\t\t\t{\n\t\t\t\t"internalType": "int256",\n\t\t\t\t"name": "sp",\n\t\t\t\t"type": "int256"\n\t\t\t}\n\t\t],\n\t\t"payable": false,\n\t\t"stateMutability": "nonpayable",\n\t\t"type": "constructor"\n\t},\n\t{\n\t\t"anonymous": false,\n\t\t"inputs": [\n\t\t\t{\n\t\t\t\t"indexed": true,\n\t\t\t\t"internalType": "address",\n\t\t\t\t"name": "partner",\n\t\t\t\t"type": "address"\n\t\t\t},\n\t\t\t{\n\t\t\t\t"indexed": false,\n\t\t\t\t"internalType": "int256",\n\t\t\t\t"name": "amountPayed",\n\t\t\t\t"type": "int256"\n\t\t\t},\n\t\t\t{\n\t\t\t\t"indexed": false,\n\t\t\t\t"internalType": "int256",\n\t\t\t\t"name": "credit",\n\t\t\t\t"type": "int256"\n\t\t\t}\n\t\t],\n\t\t"name": "contractPay",\n\t\t"type": "event"\n\t},\n\t{\n\t\t"anonymous": false,\n\t\t"inputs": [\n\t\t\t{\n\t\t\t\t"indexed": true,\n\t\t\t\t"internalType": "address",\n\t\t\t\t"name": "producer",\n\t\t\t\t"type": "address"\n\t\t\t},\n\t\t\t{\n\t\t\t\t"indexed": false,\n\t\t\t\t"internalType": "int256",\n\t\t\t\t"name": "offeredEnergy",\n\t\t\t\t"type": "int256"\n\t\t\t},\n\t\t\t{\n\t\t\t\t"indexed": false,\n\t\t\t\t"internalType": "int256",\n\t\t\t\t"name": "sellPrice",\n\t\t\t\t"type": "int256"\n\t\t\t}\n\t\t],\n\t\t"name": "enterEvent",\n\t\t"type": "event"\n\t},\n\t{\n\t\t"anonymous": false,\n\t\t"inputs": [\n\t\t\t{\n\t\t\t\t"indexed": false,\n\t\t\t\t"internalType": "int256",\n\t\t\t\t"name": "dCover",\n\t\t\t\t"type": "int256"\n\t\t\t},\n\t\t\t{\n\t\t\t\t"indexed": false,\n\t\t\t\t"internalType": "int256",\n\t\t\t\t"name": "dCoverPricePerUnit",\n\t\t\t\t"type": "int256"\n\t\t\t},\n\t\t\t{\n\t\t\t\t"indexed": false,\n\t\t\t\t"internalType": "int256",\n\t\t\t\t"name": "batteryDelta",\n\t\t\t\t"type": "int256"\n\t\t\t},\n\t\t\t{\n\t\t\t\t"indexed": false,\n\t\t\t\t"internalType": "int256",\n\t\t\t\t"name": "bLoad",\n\t\t\t\t"type": "int256"\n\t\t\t},\n\t\t\t{\n\t\t\t\t"indexed": false,\n\t\t\t\t"internalType": "int256",\n\t\t\t\t"name": "bPricePerUnit",\n\t\t\t\t"type": "int256"\n\t\t\t},\n\t\t\t{\n\t\t\t\t"indexed": false,\n\t\t\t\t"internalType": "int256",\n\t\t\t\t"name": "oDelta",\n\t\t\t\t"type": "int256"\n\t\t\t},\n\t\t\t{\n\t\t\t\t"indexed": false,\n\t\t\t\t"internalType": "int256",\n\t\t\t\t"name": "oBp",\n\t\t\t\t"type": "int256"\n\t\t\t},\n\t\t\t{\n\t\t\t\t"indexed": false,\n\t\t\t\t"internalType": "int256",\n\t\t\t\t"name": "oSp",\n\t\t\t\t"type": "int256"\n\t\t\t}\n\t\t],\n\t\t"name": "generalInfo",\n\t\t"type": "event"\n\t},\n\t{\n\t\t"anonymous": false,\n\t\t"inputs": [\n\t\t\t{\n\t\t\t\t"indexed": true,\n\t\t\t\t"internalType": "address",\n\t\t\t\t"name": "matched",\n\t\t\t\t"type": "address"\n\t\t\t},\n\t\t\t{\n\t\t\t\t"indexed": false,\n\t\t\t\t"internalType": "int256",\n\t\t\t\t"name": "matchedEnergy",\n\t\t\t\t"type": "int256"\n\t\t\t},\n\t\t\t{\n\t\t\t\t"indexed": false,\n\t\t\t\t"internalType": "int256",\n\t\t\t\t"name": "creditChange",\n\t\t\t\t"type": "int256"\n\t\t\t}\n\t\t],\n\t\t"name": "matchEvent",\n\t\t"type": "event"\n\t},\n\t{\n\t\t"constant": false,\n\t\t"inputs": [],\n\t\t"name": "coverCredit",\n\t\t"outputs": [],\n\t\t"payable": true,\n\t\t"stateMutability": "payable",\n\t\t"type": "function"\n\t},\n\t{\n\t\t"constant": false,\n\t\t"inputs": [],\n\t\t"name": "drainContract",\n\t\t"outputs": [],\n\t\t"payable": false,\n\t\t"stateMutability": "nonpayable",\n\t\t"type": "function"\n\t},\n\t{\n\t\t"constant": false,\n\t\t"inputs": [\n\t\t\t{\n\t\t\t\t"internalType": "int256",\n\t\t\t\t"name": "enteredEnergy",\n\t\t\t\t"type": "int256"\n\t\t\t},\n\t\t\t{\n\t\t\t\t"internalType": "int256",\n\t\t\t\t"name": "sPrice",\n\t\t\t\t"type": "int256"\n\t\t\t}\n\t\t],\n\t\t"name": "enterEnergy",\n\t\t"outputs": [],\n\t\t"payable": false,\n\t\t"stateMutability": "nonpayable",\n\t\t"type": "function"\n\t},\n\t{\n\t\t"constant": true,\n\t\t"inputs": [],\n\t\t"name": "getBatteryLoad",\n\t\t"outputs": [\n\t\t\t{\n\t\t\t\t"internalType": "int256",\n\t\t\t\t"name": "",\n\t\t\t\t"type": "int256"\n\t\t\t}\n\t\t],\n\t\t"payable": false,\n\t\t"stateMutability": "view",\n\t\t"type": "function"\n\t},\n\t{\n\t\t"constant": true,\n\t\t"inputs": [],\n\t\t"name": "getBatteryPricePerUnit",\n\t\t"outputs": [\n\t\t\t{\n\t\t\t\t"internalType": "int256",\n\t\t\t\t"name": "",\n\t\t\t\t"type": "int256"\n\t\t\t}\n\t\t],\n\t\t"payable": false,\n\t\t"stateMutability": "view",\n\t\t"type": "function"\n\t},\n\t{\n\t\t"constant": true,\n\t\t"inputs": [],\n\t\t"name": "getBuyPrice",\n\t\t"outputs": [\n\t\t\t{\n\t\t\t\t"internalType": "int256",\n\t\t\t\t"name": "",\n\t\t\t\t"type": "int256"\n\t\t\t}\n\t\t],\n\t\t"payable": false,\n\t\t"stateMutability": "view",\n\t\t"type": "function"\n\t},\n\t{\n\t\t"constant": true,\n\t\t"inputs": [],\n\t\t"name": "getContractFunds",\n\t\t"outputs": [\n\t\t\t{\n\t\t\t\t"internalType": "uint256",\n\t\t\t\t"name": "",\n\t\t\t\t"type": "uint256"\n\t\t\t}\n\t\t],\n\t\t"payable": false,\n\t\t"stateMutability": "view",\n\t\t"type": "function"\n\t},\n\t{\n\t\t"constant": true,\n\t\t"inputs": [],\n\t\t"name": "getCredit",\n\t\t"outputs": [\n\t\t\t{\n\t\t\t\t"internalType": "int256",\n\t\t\t\t"name": "",\n\t\t\t\t"type": "int256"\n\t\t\t}\n\t\t],\n\t\t"payable": false,\n\t\t"stateMutability": "view",\n\t\t"type": "function"\n\t},\n\t{\n\t\t"constant": true,\n\t\t"inputs": [\n\t\t\t{\n\t\t\t\t"internalType": "address",\n\t\t\t\t"name": "ofAddr",\n\t\t\t\t"type": "address"\n\t\t\t}\n\t\t],\n\t\t"name": "getMatchBlock",\n\t\t"outputs": [\n\t\t\t{\n\t\t\t\t"internalType": "uint256",\n\t\t\t\t"name": "",\n\t\t\t\t"type": "uint256"\n\t\t\t}\n\t\t],\n\t\t"payable": false,\n\t\t"stateMutability": "view",\n\t\t"type": "function"\n\t},\n\t{\n\t\t"constant": true,\n\t\t"inputs": [],\n\t\t"name": "getSellPrice",\n\t\t"outputs": [\n\t\t\t{\n\t\t\t\t"internalType": "int256",\n\t\t\t\t"name": "",\n\t\t\t\t"type": "int256"\n\t\t\t}\n\t\t],\n\t\t"payable": false,\n\t\t"stateMutability": "view",\n\t\t"type": "function"\n\t},\n\t{\n\t\t"constant": true,\n\t\t"inputs": [\n\t\t\t{\n\t\t\t\t"internalType": "address",\n\t\t\t\t"name": "account",\n\t\t\t\t"type": "address"\n\t\t\t}\n\t\t],\n\t\t"name": "getSpecCredit",\n\t\t"outputs": [\n\t\t\t{\n\t\t\t\t"internalType": "int256",\n\t\t\t\t"name": "",\n\t\t\t\t"type": "int256"\n\t\t\t}\n\t\t],\n\t\t"payable": false,\n\t\t"stateMutability": "view",\n\t\t"type": "function"\n\t},\n\t{\n\t\t"constant": true,\n\t\t"inputs": [],\n\t\t"name": "getTotalBatteryPrice",\n\t\t"outputs": [\n\t\t\t{\n\t\t\t\t"internalType": "int256",\n\t\t\t\t"name": "",\n\t\t\t\t"type": "int256"\n\t\t\t}\n\t\t],\n\t\t"payable": false,\n\t\t"stateMutability": "view",\n\t\t"type": "function"\n\t},\n\t{\n\t\t"constant": true,\n\t\t"inputs": [\n\t\t\t{\n\t\t\t\t"internalType": "address",\n\t\t\t\t"name": "ofAddr",\n\t\t\t\t"type": "address"\n\t\t\t}\n\t\t],\n\t\t"name": "getUpdateBlock",\n\t\t"outputs": [\n\t\t\t{\n\t\t\t\t"internalType": "uint256",\n\t\t\t\t"name": "",\n\t\t\t\t"type": "uint256"\n\t\t\t}\n\t\t],\n\t\t"payable": false,\n\t\t"stateMutability": "view",\n\t\t"type": "function"\n\t},\n\t{\n\t\t"constant": false,\n\t\t"inputs": [],\n\t\t"name": "matchOrders",\n\t\t"outputs": [],\n\t\t"payable": false,\n\t\t"stateMutability": "nonpayable",\n\t\t"type": "function"\n\t},\n\t{\n\t\t"constant": false,\n\t\t"inputs": [],\n\t\t"name": "repairBlockNumbers",\n\t\t"outputs": [],\n\t\t"payable": false,\n\t\t"stateMutability": "nonpayable",\n\t\t"type": "function"\n\t},\n\t{\n\t\t"constant": false,\n\t\t"inputs": [\n\t\t\t{\n\t\t\t\t"internalType": "int256",\n\t\t\t\t"name": "newCredit",\n\t\t\t\t"type": "int256"\n\t\t\t}\n\t\t],\n\t\t"name": "setAllCredits",\n\t\t"outputs": [],\n\t\t"payable": false,\n\t\t"stateMutability": "nonpayable",\n\t\t"type": "function"\n\t},\n\t{\n\t\t"constant": false,\n\t\t"inputs": [\n\t\t\t{\n\t\t\t\t"internalType": "int256",\n\t\t\t\t"name": "newCap",\n\t\t\t\t"type": "int256"\n\t\t\t}\n\t\t],\n\t\t"name": "setBatteryCapacity",\n\t\t"outputs": [],\n\t\t"payable": false,\n\t\t"stateMutability": "nonpayable",\n\t\t"type": "function"\n\t},\n\t{\n\t\t"constant": false,\n\t\t"inputs": [\n\t\t\t{\n\t\t\t\t"internalType": "int8",\n\t\t\t\t"name": "newEff",\n\t\t\t\t"type": "int8"\n\t\t\t}\n\t\t],\n\t\t"name": "setBatteryEff",\n\t\t"outputs": [],\n\t\t"payable": false,\n\t\t"stateMutability": "nonpayable",\n\t\t"type": "function"\n\t},\n\t{\n\t\t"constant": false,\n\t\t"inputs": [\n\t\t\t{\n\t\t\t\t"internalType": "int256",\n\t\t\t\t"name": "newLoad",\n\t\t\t\t"type": "int256"\n\t\t\t}\n\t\t],\n\t\t"name": "setBatteryLoad",\n\t\t"outputs": [],\n\t\t"payable": false,\n\t\t"stateMutability": "nonpayable",\n\t\t"type": "function"\n\t},\n\t{\n\t\t"constant": false,\n\t\t"inputs": [\n\t\t\t{\n\t\t\t\t"internalType": "int256",\n\t\t\t\t"name": "newPrice",\n\t\t\t\t"type": "int256"\n\t\t\t}\n\t\t],\n\t\t"name": "setBuyPrice",\n\t\t"outputs": [],\n\t\t"payable": false,\n\t\t"stateMutability": "nonpayable",\n\t\t"type": "function"\n\t},\n\t{\n\t\t"constant": false,\n\t\t"inputs": [\n\t\t\t{\n\t\t\t\t"internalType": "int256",\n\t\t\t\t"name": "newPrice",\n\t\t\t\t"type": "int256"\n\t\t\t}\n\t\t],\n\t\t"name": "setSellPrice",\n\t\t"outputs": [],\n\t\t"payable": false,\n\t\t"stateMutability": "nonpayable",\n\t\t"type": "function"\n\t},\n\t{\n\t\t"constant": false,\n\t\t"inputs": [\n\t\t\t{\n\t\t\t\t"internalType": "int256",\n\t\t\t\t"name": "nPr",\n\t\t\t\t"type": "int256"\n\t\t\t}\n\t\t],\n\t\t"name": "setTotalBatPrice",\n\t\t"outputs": [],\n\t\t"payable": false,\n\t\t"stateMutability": "nonpayable",\n\t\t"type": "function"\n\t}\n]' |
class HashEngine:
def __init__(self):
self.location_hash = None
self.location_auth_hash = None
self.request_hashes = []
def hash(self, timestamp, latitude, longitude, altitude, authticket, sessiondata, requests):
raise NotImplementedError()
def get_location_hash(self):
return self.location_hash
def get_location_auth_hash(self):
return self.location_auth_hash
def get_request_hashes(self):
return self.request_hashes
| class Hashengine:
def __init__(self):
self.location_hash = None
self.location_auth_hash = None
self.request_hashes = []
def hash(self, timestamp, latitude, longitude, altitude, authticket, sessiondata, requests):
raise not_implemented_error()
def get_location_hash(self):
return self.location_hash
def get_location_auth_hash(self):
return self.location_auth_hash
def get_request_hashes(self):
return self.request_hashes |
for _ in range(int(input())):
n = int(input())
arr = list(map(int,input().split()))
flag = 0
for i in arr:
if i < 0:
flag = 1
break
if flag:
print('NO')
continue
for i in range(max(arr)):
if i not in arr:
arr.append(i)
print('YES')
print(len(arr))
print(*arr) | for _ in range(int(input())):
n = int(input())
arr = list(map(int, input().split()))
flag = 0
for i in arr:
if i < 0:
flag = 1
break
if flag:
print('NO')
continue
for i in range(max(arr)):
if i not in arr:
arr.append(i)
print('YES')
print(len(arr))
print(*arr) |
bind = '0.0.0.0:8000'
# Assuming one CPU. http://docs.gunicorn.org/en/stable/design.html#how-many-workers
# 2 * cores + 1
workers = 3
# You can send signals to it http://docs.gunicorn.org/en/latest/signals.html
pidfile = '/run/gunicorn.pid'
# Logformat including request time.
access_log_format = '%(h)s %({X-Forwarded-For}i)s %(l)s %(u)s %(t)s "%(r)s" %(s)s %(b)s "%(f)s" "%(a)s" "%(L)s seconds"' # noqa
loglevel = 'info'
accesslog = '-' # stdout
errorlog = '-' # stdout
# Also send logs to syslog.
syslog = False
syslog_prefix = '[asoc_members-wsgi]'
timeout = 84000
| bind = '0.0.0.0:8000'
workers = 3
pidfile = '/run/gunicorn.pid'
access_log_format = '%(h)s %({X-Forwarded-For}i)s %(l)s %(u)s %(t)s "%(r)s" %(s)s %(b)s "%(f)s" "%(a)s" "%(L)s seconds"'
loglevel = 'info'
accesslog = '-'
errorlog = '-'
syslog = False
syslog_prefix = '[asoc_members-wsgi]'
timeout = 84000 |
class Constants:
RESPONSE_CODES_SUCCESS = [200, 201]
RESPONSE_CODES_FAILURE = [400, 401, 404, 500]
RESPONSE_500 = 500
URL = "https://api.coingecko.com/api/v3/coins/{}?localization=false&tickers=false&market_data=false&community_data=false&developer_data=false&sparkline=false"
CONTENT_TYPE = "application/json"
| class Constants:
response_codes_success = [200, 201]
response_codes_failure = [400, 401, 404, 500]
response_500 = 500
url = 'https://api.coingecko.com/api/v3/coins/{}?localization=false&tickers=false&market_data=false&community_data=false&developer_data=false&sparkline=false'
content_type = 'application/json' |
colddrinks = "pepsi", "cola", "sprite", "7up", 58
num = [89, 38,94,23,98,192]
#num.sort()
#num.reverse()
print(colddrinks[:4])
print(num[:: 2]) | colddrinks = ('pepsi', 'cola', 'sprite', '7up', 58)
num = [89, 38, 94, 23, 98, 192]
print(colddrinks[:4])
print(num[::2]) |
#Author: Bhumi Patel
#The given function will take in an educational website and count the number
#of clicks it takes for users to reach privacy policy and end-user license agreement
'''
-> With the current pandemic, lives all around the world has been disturbed and
changed completely. With change in lifestyle and social behaviour, learning has
also been affected. Overnight schools were shutdown, universities need to close
their doors and educators, students, and parents needed to figure out ways to
keep learning continue, that adaptes to the "new normal." Online learning became
popular; however, security and privacy raised a huge concern as kids and learners
from all ages started learning online.
-> To address this huge we are trying to suggest a potential solution that involves
closly examing the educational sites and the amount of data they collect from
student learners. All the information that these sites collects makes users
vulnerable and affect their online presence and mental health.
-> With our solution we want users to have safe experience online and learn more
about these educational sites.
'''
#analyzing number of clicks required to search for privacy
class click:
#using a binary tree to store website and privacy links
def __init__(self, web_link):
self.random_links = []
self.data = web_link
#searching for target hit "privacy"
def search_target(random_links, w_link):
for i in rnadom_links:
if i.find("/privacy") != -1:
w_link = i
return w_link #returns the string with privacy
def distance_helper(node, target_link, distance):
if node.data == target_link:
return distance
else:
for j in range(len(node.random_links)):
distance = distance_helper(node.random_links[i], target_link, distance+1)
if distance == -1:
return -1
def find_distance(root):
return distance_helper(root, target_link, 0)
if __name__ == '__main__':
#Step:1 load all the web_links in a N-ary tree
#Step:2 find the link that contains privacy/policy
#Step:3 pass that node in our distance function, to find how many clicks it takes to find privacy policy
#populating the list with privacy policies, terms of use agreements links, and other random links
#root objects for a N-ary tree known as Educational Websites
root_n = click("https://www.khanacademy.org/")
root_n.random_links.append(click("https://www.khanacademy.org/about/privacy-policy"))
root_n.random_links.append(click("https://www.khanacademy.org/about/tos"))
root_n.random_links[0].random_links.append(click("https://www.khanacademy.org/about/%7B%7B%22/about/api-tos%22%7Cpropagate_embedded%7D%7D"))
root_n.random_links.append(click("https://www.khanacademy.org/science"))
root_n1 = click("https://kahoot.com/")
root_n1.random_links.append(click("https://kahoot.com/privacy-policy/"))
root_n1.random_links.append(click("https://kahoot.com/study/"))
root_n1.random_links[0].random_links.append(click("https://kahoot.com/schools/ways-to-play/"))
root_n1.random_links[1].random_links.append(click("https://kahoot.com/home/learning-apps/dragonbox/"))
root_n2 = click("https://code.org/")
root_n2.random_links.append(click("https://studio.code.org/projects/public"))
root_n2.random_links.append(click("https://code.org/about"))
root_n2.random_links.append(click("https://code.org/promote"))
root_n2.random_links.append(click("https://code.org/tos"))
root_n3 = click("https://www.udemy.com/")
root_n3.random_links.append(click("https://about.udemy.com/careers/?locale=en-us"))
root_n3.random_links[0].random_links.append(click("https://about.udemy.com/tag/stories/"))
root_n3.random_links[0].random_links[0].random_links.append(click("https://www.udemy.com/terms/copyright/"))
root_n3.random_links.append(click("https://www.udemy.com/terms/privacy/"))
#displays the number of clicks
print("The number of click is" , find_distance(root_n))
| """
-> With the current pandemic, lives all around the world has been disturbed and
changed completely. With change in lifestyle and social behaviour, learning has
also been affected. Overnight schools were shutdown, universities need to close
their doors and educators, students, and parents needed to figure out ways to
keep learning continue, that adaptes to the "new normal." Online learning became
popular; however, security and privacy raised a huge concern as kids and learners
from all ages started learning online.
-> To address this huge we are trying to suggest a potential solution that involves
closly examing the educational sites and the amount of data they collect from
student learners. All the information that these sites collects makes users
vulnerable and affect their online presence and mental health.
-> With our solution we want users to have safe experience online and learn more
about these educational sites.
"""
class Click:
def __init__(self, web_link):
self.random_links = []
self.data = web_link
def search_target(random_links, w_link):
for i in rnadom_links:
if i.find('/privacy') != -1:
w_link = i
return w_link
def distance_helper(node, target_link, distance):
if node.data == target_link:
return distance
else:
for j in range(len(node.random_links)):
distance = distance_helper(node.random_links[i], target_link, distance + 1)
if distance == -1:
return -1
def find_distance(root):
return distance_helper(root, target_link, 0)
if __name__ == '__main__':
root_n = click('https://www.khanacademy.org/')
root_n.random_links.append(click('https://www.khanacademy.org/about/privacy-policy'))
root_n.random_links.append(click('https://www.khanacademy.org/about/tos'))
root_n.random_links[0].random_links.append(click('https://www.khanacademy.org/about/%7B%7B%22/about/api-tos%22%7Cpropagate_embedded%7D%7D'))
root_n.random_links.append(click('https://www.khanacademy.org/science'))
root_n1 = click('https://kahoot.com/')
root_n1.random_links.append(click('https://kahoot.com/privacy-policy/'))
root_n1.random_links.append(click('https://kahoot.com/study/'))
root_n1.random_links[0].random_links.append(click('https://kahoot.com/schools/ways-to-play/'))
root_n1.random_links[1].random_links.append(click('https://kahoot.com/home/learning-apps/dragonbox/'))
root_n2 = click('https://code.org/')
root_n2.random_links.append(click('https://studio.code.org/projects/public'))
root_n2.random_links.append(click('https://code.org/about'))
root_n2.random_links.append(click('https://code.org/promote'))
root_n2.random_links.append(click('https://code.org/tos'))
root_n3 = click('https://www.udemy.com/')
root_n3.random_links.append(click('https://about.udemy.com/careers/?locale=en-us'))
root_n3.random_links[0].random_links.append(click('https://about.udemy.com/tag/stories/'))
root_n3.random_links[0].random_links[0].random_links.append(click('https://www.udemy.com/terms/copyright/'))
root_n3.random_links.append(click('https://www.udemy.com/terms/privacy/'))
print('The number of click is', find_distance(root_n)) |
# Complete the function below.
def main():
conn = sqlite3.connect('SAMPLE.db')
cursor = conn.cursor()
cursor.execute("drop table if exists ITEMS")
sql_statement = '''CREATE TABLE ITEMS
(item_id integer not null, item_name varchar(300),
item_description text, item_category text,
quantity_in_stock integer)'''
cursor.execute(sql_statement)
items = [(101, 'Nik D300', 'Nik D300', 'DSLR Camera', 3),
(102, 'Can 1300', 'Can 1300', 'DSLR Camera', 5),
(103, 'gPhone 13S', 'gPhone 13S', 'Mobile', 10),
(104, 'Mic canvas', 'Mic canvas', 'Tab', 5),
(105, 'SnDisk 10T', 'SnDisk 10T', 'Hard Drive', 1)
]
#Add code to insert records to ITEM table
for item in items:
cursor.execute('insert into ITEMS values (?,?,?,?,?)', item)
try:
cursor.execute("select * from ITEMS")
except:
return 'Unable to perform the transaction.'
rowout=[]
for row in cursor.fetchall():
rowout.append(row)
return rowout
conn.close()
'''For testing the code, no input is required'''
| def main():
conn = sqlite3.connect('SAMPLE.db')
cursor = conn.cursor()
cursor.execute('drop table if exists ITEMS')
sql_statement = 'CREATE TABLE ITEMS\n (item_id integer not null, item_name varchar(300), \n item_description text, item_category text, \n quantity_in_stock integer)'
cursor.execute(sql_statement)
items = [(101, 'Nik D300', 'Nik D300', 'DSLR Camera', 3), (102, 'Can 1300', 'Can 1300', 'DSLR Camera', 5), (103, 'gPhone 13S', 'gPhone 13S', 'Mobile', 10), (104, 'Mic canvas', 'Mic canvas', 'Tab', 5), (105, 'SnDisk 10T', 'SnDisk 10T', 'Hard Drive', 1)]
for item in items:
cursor.execute('insert into ITEMS values (?,?,?,?,?)', item)
try:
cursor.execute('select * from ITEMS')
except:
return 'Unable to perform the transaction.'
rowout = []
for row in cursor.fetchall():
rowout.append(row)
return rowout
conn.close()
'For testing the code, no input is required' |
class LearnedEquivalence:
def __init__(self, eq_class):
self.equivalence_class = eq_class
def __str__(self):
return "LEARNED_EQCLASS_" + self.equivalence_class
| class Learnedequivalence:
def __init__(self, eq_class):
self.equivalence_class = eq_class
def __str__(self):
return 'LEARNED_EQCLASS_' + self.equivalence_class |
# data is [ 0 name of game,
# 1 path to game saves,
# 2 backups directory]
'''
self.game.name
self.game.saveLocation
self.game.backupLocation
'''
class gameInfo:
def __init__( self, name, saveLocation, backupLocation ):
self.name = name
self.saveLocation = saveLocation
self.backupLocation = backupLocation | """
self.game.name
self.game.saveLocation
self.game.backupLocation
"""
class Gameinfo:
def __init__(self, name, saveLocation, backupLocation):
self.name = name
self.saveLocation = saveLocation
self.backupLocation = backupLocation |
class Field():
def __init__(self, dictionary = {}):
self.name = dictionary.get("name")
self.rname = dictionary.get("rname")
self.domain = dictionary.get("domain")
self.description = dictionary.get("description")
# Props
self.input = dictionary.get("input", False)
self.edit = dictionary.get("edit", False)
self.show_in_grid = dictionary.get("show_in_grid", False)
self.show_in_details = dictionary.get("show_in_details", False)
self.is_mean = dictionary.get("is_mean", False)
self.autocalculated = dictionary.get("autocalculated", False)
self.required = dictionary.get("required", False)
| class Field:
def __init__(self, dictionary={}):
self.name = dictionary.get('name')
self.rname = dictionary.get('rname')
self.domain = dictionary.get('domain')
self.description = dictionary.get('description')
self.input = dictionary.get('input', False)
self.edit = dictionary.get('edit', False)
self.show_in_grid = dictionary.get('show_in_grid', False)
self.show_in_details = dictionary.get('show_in_details', False)
self.is_mean = dictionary.get('is_mean', False)
self.autocalculated = dictionary.get('autocalculated', False)
self.required = dictionary.get('required', False) |
# QuickSort
def quicksort(L,l,r):
#If list has only one element, return the list as is
if(r-l <=1):
return L
# Set pivot as the very first position in the list, upper and lower are the next element
(pivot,lower,upper) = (L[l],l+1,l+1)
# Loop from the item after pivot to the end
for i in range(l+1,r):
#If L[i] is higher than pivot, upper is incremented
if L[i] > pivot:
upper +=1
else: # exchange L[i] with start of upper segment
(L[i],L[lower]) = (L[lower],L[i])
upper +=1
lower +=1
#Move pivot to the center of the list
(L[l],L[lower-1]) = (L[lower-1],L[l])
lower -=1
#Recursively sort the LHS and RHS of pivot now
quicksort(L,l,lower)
quicksort(L,lower+1,upper)
#Return the list
return L
A = [4,5,6,2,3,7,8,9]
print(quicksort(A,0,len(A)))
| def quicksort(L, l, r):
if r - l <= 1:
return L
(pivot, lower, upper) = (L[l], l + 1, l + 1)
for i in range(l + 1, r):
if L[i] > pivot:
upper += 1
else:
(L[i], L[lower]) = (L[lower], L[i])
upper += 1
lower += 1
(L[l], L[lower - 1]) = (L[lower - 1], L[l])
lower -= 1
quicksort(L, l, lower)
quicksort(L, lower + 1, upper)
return L
a = [4, 5, 6, 2, 3, 7, 8, 9]
print(quicksort(A, 0, len(A))) |
# import pytest
class TestMessageFolder:
def test_folders(self): # synced
assert True
def test_messages(self): # synced
assert True
def test_order_messages_by_date(): # synced
assert True
class TestAttributes:
class TestChildFolderCount:
pass
class TestTotalItemCount:
pass
class TestUnreadItemCount:
pass
class TestName:
pass
class TestChildFolders:
pass
class TestMessages:
pass
class TestBulkMessageFolderAction:
def test_move(self): # synced
assert True
def test_delete(self): # synced
assert True
def test_copy(self): # synced
assert True
class TestMessageFolderQuery:
def test___getitem__(self): # synced
assert True
def test_execute(self): # synced
assert True
def test_bulk(self): # synced
assert True
| class Testmessagefolder:
def test_folders(self):
assert True
def test_messages(self):
assert True
def test_order_messages_by_date():
assert True
class Testattributes:
class Testchildfoldercount:
pass
class Testtotalitemcount:
pass
class Testunreaditemcount:
pass
class Testname:
pass
class Testchildfolders:
pass
class Testmessages:
pass
class Testbulkmessagefolderaction:
def test_move(self):
assert True
def test_delete(self):
assert True
def test_copy(self):
assert True
class Testmessagefolderquery:
def test___getitem__(self):
assert True
def test_execute(self):
assert True
def test_bulk(self):
assert True |
def character_xor(input_string, char):
output_string = ""
for c in input_string:
output_string += chr(ord(c)^char)
return output_string
def calculate_score(input_string):
frequencies = {
'a': .08167, 'b': .01492, 'c': .02782, 'd': .04253, 'e': .12702, 'f': .02228, 'g': .02015, 'h': .06094, 'i': .06094, 'j': .00153, 'k': .00772, 'l': .04025,
'm': .02406, 'n': .06749, 'o': .07507, 'p': .01929, 'q': .00095, 'r': .05987, 's': .06327, 't': .09056, 'u': .02758, 'v': .00978, 'w': .02360, 'x': .00150,
'y': .01974, 'z': .00074, ' ': .13000
}
#frequencies taken from wikipedia (https://en.wikipedia.org/wiki/Letter_frequency)
calculated_sum = 0
for c in input_string:
if c in frequencies:
calculated_sum += frequencies[c]
return calculated_sum
def main():
hex_string = '1b37373331363f78151b7f2b783431333d78397828372d363c78373e783a393b3736'
decoded_string = bytearray.fromhex(hex_string).decode()
all_character_xors = []
for i in range(256):
char_xor = character_xor(decoded_string, i)
all_character_xors.append([calculate_score(char_xor.lower()), char_xor])
all_character_xors.sort()
print(all_character_xors[-1][1])
if __name__ == '__main__':
main()
| def character_xor(input_string, char):
output_string = ''
for c in input_string:
output_string += chr(ord(c) ^ char)
return output_string
def calculate_score(input_string):
frequencies = {'a': 0.08167, 'b': 0.01492, 'c': 0.02782, 'd': 0.04253, 'e': 0.12702, 'f': 0.02228, 'g': 0.02015, 'h': 0.06094, 'i': 0.06094, 'j': 0.00153, 'k': 0.00772, 'l': 0.04025, 'm': 0.02406, 'n': 0.06749, 'o': 0.07507, 'p': 0.01929, 'q': 0.00095, 'r': 0.05987, 's': 0.06327, 't': 0.09056, 'u': 0.02758, 'v': 0.00978, 'w': 0.0236, 'x': 0.0015, 'y': 0.01974, 'z': 0.00074, ' ': 0.13}
calculated_sum = 0
for c in input_string:
if c in frequencies:
calculated_sum += frequencies[c]
return calculated_sum
def main():
hex_string = '1b37373331363f78151b7f2b783431333d78397828372d363c78373e783a393b3736'
decoded_string = bytearray.fromhex(hex_string).decode()
all_character_xors = []
for i in range(256):
char_xor = character_xor(decoded_string, i)
all_character_xors.append([calculate_score(char_xor.lower()), char_xor])
all_character_xors.sort()
print(all_character_xors[-1][1])
if __name__ == '__main__':
main() |
_base_ = './cifar10split_bs16.py'
data = dict(
unlabeled=dict(
type='TVDatasetSplit',
base='CIFAR10',
train=True,
data_prefix='data/torchvision/cifar10',
num_images=1000,
download=True
)
)
| _base_ = './cifar10split_bs16.py'
data = dict(unlabeled=dict(type='TVDatasetSplit', base='CIFAR10', train=True, data_prefix='data/torchvision/cifar10', num_images=1000, download=True)) |
def runModels(sproc,modelList,testPredictionPaths,CVPredictionPaths,trials,RMSEPaths,useRMSE):
subprocesses = []
for trial in range(0,trials):
# Setup utility arrays
testPredictionPaths.append([])
CVPredictionPaths.append([])
for model in modelList:
print("Running Model " + model.tag)
model.run(sproc,subprocesses)
testPredictionPaths[int(model.trial)].append(model.predTest)
CVPredictionPaths[int(model.trial)].append(model.predCV)
if useRMSE:
RMSEPaths.append(model.RMSEPath)
for p in subprocesses:
p.wait()
def fixRun(mproc,modelList):
processes = []
for model in modelList:
p = mproc.Process(target=model.fixRun)
p.start()
processes.append(p)
for p in processes:
p.join()
| def run_models(sproc, modelList, testPredictionPaths, CVPredictionPaths, trials, RMSEPaths, useRMSE):
subprocesses = []
for trial in range(0, trials):
testPredictionPaths.append([])
CVPredictionPaths.append([])
for model in modelList:
print('Running Model ' + model.tag)
model.run(sproc, subprocesses)
testPredictionPaths[int(model.trial)].append(model.predTest)
CVPredictionPaths[int(model.trial)].append(model.predCV)
if useRMSE:
RMSEPaths.append(model.RMSEPath)
for p in subprocesses:
p.wait()
def fix_run(mproc, modelList):
processes = []
for model in modelList:
p = mproc.Process(target=model.fixRun)
p.start()
processes.append(p)
for p in processes:
p.join() |
def faculty_evaluation_result(nev, rar, som, oft, voft, alw):
'''
Write code to calculate faculty evaluation rating according to assignment instructions
:param nev: Never
:param rar: Rarely
:param som: Sometimes
:param oft: Often
:param voft: Very Often
:param alw: Always
:return: rating as a string
'''
#Find the ratios of each parameter
total = nev + rar + som + oft + voft + alw
nev_ratio = (nev / total)
rar_ratio = (rar / total)
som_ratio = (som / total)
oft_ratio = (oft / total)
voft_ratio = (voft / total)
alw_ratio = (alw / total)
if alw_ratio + voft_ratio >= 90:
return 'Excellent'
elif alw_ratio + voft_ratio + oft_ratio >= 80:
return 'Very Good'
elif alw_ratio + voft_ratio + oft_ratio + som_ratio >= 70:
return 'Good'
elif alw_ratio + voft_ratio + oft_ratio + som_ratio + rar_ratio >= 60:
return 'Needs Improvment'
else:
return 'Unacceptable'
def get_ratings(nev,rar,som, oft,voft, alw):
'''
Students aren't expected to know this material yet!
'''
ratings = []
total = nev + rar + som + oft + voft + alw
ratings.append(round(alw / total, 2))
ratings.append(round(voft / total, 2))
ratings.append(round(oft / total, 2))
ratings.append(round(som / total, 2))
ratings.append(round(rar / total, 2))
ratings.append(round(nev / total, 2))
return ratings
| def faculty_evaluation_result(nev, rar, som, oft, voft, alw):
"""
Write code to calculate faculty evaluation rating according to assignment instructions
:param nev: Never
:param rar: Rarely
:param som: Sometimes
:param oft: Often
:param voft: Very Often
:param alw: Always
:return: rating as a string
"""
total = nev + rar + som + oft + voft + alw
nev_ratio = nev / total
rar_ratio = rar / total
som_ratio = som / total
oft_ratio = oft / total
voft_ratio = voft / total
alw_ratio = alw / total
if alw_ratio + voft_ratio >= 90:
return 'Excellent'
elif alw_ratio + voft_ratio + oft_ratio >= 80:
return 'Very Good'
elif alw_ratio + voft_ratio + oft_ratio + som_ratio >= 70:
return 'Good'
elif alw_ratio + voft_ratio + oft_ratio + som_ratio + rar_ratio >= 60:
return 'Needs Improvment'
else:
return 'Unacceptable'
def get_ratings(nev, rar, som, oft, voft, alw):
"""
Students aren't expected to know this material yet!
"""
ratings = []
total = nev + rar + som + oft + voft + alw
ratings.append(round(alw / total, 2))
ratings.append(round(voft / total, 2))
ratings.append(round(oft / total, 2))
ratings.append(round(som / total, 2))
ratings.append(round(rar / total, 2))
ratings.append(round(nev / total, 2))
return ratings |
# Variables which should not be accessed outside a class are called private variables.
# In Python you can easily create private variables by prefixing it with a double underscore ( __ )
# Whenever you create a private variable, python internally changes its name as _ClassName__variableName.
# For example, here __salary is actually internally stored as _Trainer__salary.
# Methods used to set values are called as 'mutator' methods and methods used to get values are called as 'accessor' methods!
class Trainer:
def __init__(self):
self.name=None
self.__salary=1000
def set_salary(self,salary):
self.__salary=salary
def get_salary(self):
return self.__salary
lion_trainer=Trainer()
lion_trainer.name="Mark"
# You can set a private variable using obj._Trainer__salary. Ex: lion_trainer._Trainer__salary = 2000
# But this is not a right way, the correct way is to use mutator methods.
lion_trainer.set_salary(2000)
print("Lion's trainer is", lion_trainer.name)
# You can also access the private variable using obj._Trainer__salary. Ex: print("Salary of Trainer" , lion_trainer._Trainer__salary)
# But this is not a right way, the correct way is to use accessor methods.
print("His salary is Rs.", lion_trainer.get_salary()) | class Trainer:
def __init__(self):
self.name = None
self.__salary = 1000
def set_salary(self, salary):
self.__salary = salary
def get_salary(self):
return self.__salary
lion_trainer = trainer()
lion_trainer.name = 'Mark'
lion_trainer.set_salary(2000)
print("Lion's trainer is", lion_trainer.name)
print('His salary is Rs.', lion_trainer.get_salary()) |
class Solution:
def connect(self, root: 'Node') -> 'Node':
node = root
while node:
next_level = node.left
while node and node.left:
node.left.next = node.right
node.right.next = node.next and node.next.left
node = node.next
node = next_level
return root
| class Solution:
def connect(self, root: 'Node') -> 'Node':
node = root
while node:
next_level = node.left
while node and node.left:
node.left.next = node.right
node.right.next = node.next and node.next.left
node = node.next
node = next_level
return root |
UNUSED_PRETRAINED_LAYERS = ['"fc_1.weight", '
'"fc_1.bias", '
'"fc_2.weight", '
'"fc_2.bias", '
'"fc_3.weight", '
'"fc_3.bias", '
'"fc_4.weight", '
'"fc_4.bias", '
'"bn_1.weight", '
'"bn_1.bias", '
'"bn_1.running_mean", '
'"bn_1.running_var", '
'"bn_1.num_batches_tracked", '
'"bn_2.weight", "bn_2.bias", '
'"bn_2.running_mean", '
'"bn_2.running_var", '
'"bn_2.num_batches_tracked", '
'"bn_3.weight", "bn_3.bias", '
'"bn_3.running_mean", '
'"bn_3.running_var", '
'"bn_3.num_batches_tracked", '
'"bn_4.weight", '
'"bn_4.bias", '
'"bn_4.running_mean", '
'"bn_4.running_var", '
'"bn_4.num_batches_tracked"'] | unused_pretrained_layers = ['"fc_1.weight", "fc_1.bias", "fc_2.weight", "fc_2.bias", "fc_3.weight", "fc_3.bias", "fc_4.weight", "fc_4.bias", "bn_1.weight", "bn_1.bias", "bn_1.running_mean", "bn_1.running_var", "bn_1.num_batches_tracked", "bn_2.weight", "bn_2.bias", "bn_2.running_mean", "bn_2.running_var", "bn_2.num_batches_tracked", "bn_3.weight", "bn_3.bias", "bn_3.running_mean", "bn_3.running_var", "bn_3.num_batches_tracked", "bn_4.weight", "bn_4.bias", "bn_4.running_mean", "bn_4.running_var", "bn_4.num_batches_tracked"'] |
class Observer(object):
def __init__(self, **kwargs):
self._listeners = []
def add_listener(self, listener):
self._listeners.append(listener)
def _call_event(self, msg):
for listener in self._listeners:
listener(msg)
| class Observer(object):
def __init__(self, **kwargs):
self._listeners = []
def add_listener(self, listener):
self._listeners.append(listener)
def _call_event(self, msg):
for listener in self._listeners:
listener(msg) |
def mergeSort(arrInput):
if len(arrInput) > 1:
mid = len(arrInput) // 2 # midpoint of input array
left = arrInput[:mid] # Dividing the left side of elements
right = arrInput[mid:] # Divide into second half
mergeSort(left) # Sorting first half
mergeSort(right) # Sorting second half
i = 0
j = 0
k = 0
# Copy data to temp arrInput left[] and right[]
while i < len(left) and j < len(right):
if left[i] < right[j]:
arrInput[k] = left[i]
i += 1
else:
arrInput[k] = right[j]
j += 1
k += 1
# Checking if any element was left
while i < len(left):
arrInput[k] = left[i]
i += 1
k += 1
while j < len(right):
arrInput[k] = right[j]
j += 1
k += 1
| def merge_sort(arrInput):
if len(arrInput) > 1:
mid = len(arrInput) // 2
left = arrInput[:mid]
right = arrInput[mid:]
merge_sort(left)
merge_sort(right)
i = 0
j = 0
k = 0
while i < len(left) and j < len(right):
if left[i] < right[j]:
arrInput[k] = left[i]
i += 1
else:
arrInput[k] = right[j]
j += 1
k += 1
while i < len(left):
arrInput[k] = left[i]
i += 1
k += 1
while j < len(right):
arrInput[k] = right[j]
j += 1
k += 1 |
# !/usr/bin/env python3
class Classification:
def __init__(self):
self.description = ''
self.direct_parent = ''
self.kingdom = ''
self.superclass = ''
self.class_type =''
self.subclass = ''
def __init__(self, description, direct_parent, kingdom, superclass, class_type, subclass):
self.description = description
self.direct_parent = direct_parent
self.kingdom = kingdom
self.superclass = superclass
self.class_type = class_type
self.subclass = subclass
def printout(self):
print ('Classification: ')
print ('\t> Description: ' + self.description)
print ('\t> Direct parent: ' + self.direct_parent)
print ('\t> Kingdom: ' + self.kingdom)
print ('\t> Superclass: ' + self.superclass)
print ('\t> Class: ' + self.class_type)
print ('\t> Subclass: ' + self.subclass)
## Example of how the information realted to 'Classification' appears in DrugBank database.
# <classification>
# <description/>
# <direct-parent>Peptides</direct-parent>
# <kingdom>Organic Compounds</kingdom>
# <superclass>Organic Acids</superclass>
# <class>Carboxylic Acids and Derivatives</class>
# <subclass>Amino Acids, Peptides, and Analogues</subclass>
# </classification> | class Classification:
def __init__(self):
self.description = ''
self.direct_parent = ''
self.kingdom = ''
self.superclass = ''
self.class_type = ''
self.subclass = ''
def __init__(self, description, direct_parent, kingdom, superclass, class_type, subclass):
self.description = description
self.direct_parent = direct_parent
self.kingdom = kingdom
self.superclass = superclass
self.class_type = class_type
self.subclass = subclass
def printout(self):
print('Classification: ')
print('\t> Description: ' + self.description)
print('\t> Direct parent: ' + self.direct_parent)
print('\t> Kingdom: ' + self.kingdom)
print('\t> Superclass: ' + self.superclass)
print('\t> Class: ' + self.class_type)
print('\t> Subclass: ' + self.subclass) |
# INDEX MULTIPLIER EDABIT SOLUTION:
def index_multiplier(lst):
# creating a variable to store the sum.
summ = 0
# creating a for-loop using 'enumerate' to access the index and the value.
for idx, num in enumerate(nums):
# code to add the product of the index and value to the sum variable.
summ += (idx * num)
# returning the value of the sum.
return summ
| def index_multiplier(lst):
summ = 0
for (idx, num) in enumerate(nums):
summ += idx * num
return summ |
#!/usr/bin/env python
# * coding: utf8 *
'''
api.py
A module that holds the api credentials to get the offender data
'''
AUTHORIZATION_HEADER = {'Authorization': 'Apikey 0000'}
ENDPOINT_AT = 'qa url'
ENDPOINT = 'production url'
| """
api.py
A module that holds the api credentials to get the offender data
"""
authorization_header = {'Authorization': 'Apikey 0000'}
endpoint_at = 'qa url'
endpoint = 'production url' |
# first
input = "racecar"
input2 = "nada"
def palindromo_checker(input):
print(input)
return input == input[::-1]
if __name__ == '__main__':
print(palindromo_checker(input))
print(palindromo_checker(input2))
| input = 'racecar'
input2 = 'nada'
def palindromo_checker(input):
print(input)
return input == input[::-1]
if __name__ == '__main__':
print(palindromo_checker(input))
print(palindromo_checker(input2)) |
def fibonacci():
a, b = 0, 1
while True:
yield b
a, b = b, a + b
if __name__ == '__main__':
f = fibonacci()
for _ in range(10):
print(next(f))
| def fibonacci():
(a, b) = (0, 1)
while True:
yield b
(a, b) = (b, a + b)
if __name__ == '__main__':
f = fibonacci()
for _ in range(10):
print(next(f)) |
def calculate():
operation = input('''
Please Type the math operation you would like to complete:
+ for addition
- for Subtraction
* for Multiplication
/ for division
''')
number_1 = float(input('Please enter the First number: '))
number_2 = float(input('Please enter the Second number: '))
if operation == '+':
print('{} + {} = '.format(number_1, number_2))
print(number_1 + number_2)
elif operation == '-':
print('{} - {} = '.format(number_1, number_2))
print(number_1 - number_2)
elif operation == '*':
print('{} * {} = '.format(number_1, number_2))
print(number_1 * number_2)
elif operation == '/':
print('{} / {} = '.format(number_1, number_2))
print(number_1 / number_2)
else:
print('You have entered a wrong math operator!')
again()
def again():
calculation_again = input('''
Do you want to Calculate again?
Please type Y for Yes or N for No
''')
if calculation_again.upper() == 'Y':
calculate()
elif calculation_again.upper() == 'N':
print('Bye Bye, thank you for coming.')
else:
again()
calculate() | def calculate():
operation = input('\nPlease Type the math operation you would like to complete:\n+ for addition\n- for Subtraction\n* for Multiplication\n/ for division\n')
number_1 = float(input('Please enter the First number: '))
number_2 = float(input('Please enter the Second number: '))
if operation == '+':
print('{} + {} = '.format(number_1, number_2))
print(number_1 + number_2)
elif operation == '-':
print('{} - {} = '.format(number_1, number_2))
print(number_1 - number_2)
elif operation == '*':
print('{} * {} = '.format(number_1, number_2))
print(number_1 * number_2)
elif operation == '/':
print('{} / {} = '.format(number_1, number_2))
print(number_1 / number_2)
else:
print('You have entered a wrong math operator!')
again()
def again():
calculation_again = input('\nDo you want to Calculate again?\nPlease type Y for Yes or N for No\n')
if calculation_again.upper() == 'Y':
calculate()
elif calculation_again.upper() == 'N':
print('Bye Bye, thank you for coming.')
else:
again()
calculate() |
for x in range(5, 0, -1):
for y in range(x, 5):
print(" ", end="")
for z in range(0, x):
print("* ", end="")
print() | for x in range(5, 0, -1):
for y in range(x, 5):
print(' ', end='')
for z in range(0, x):
print('* ', end='')
print() |
class Solution:
def shortestCompletingWord(self, licensePlate: str, words: List[str]) -> str:
length = sys.maxsize
result = None
letters = collections.defaultdict()
for letter in licensePlate:
if letter.isalpha():
letter = letter.lower()
letters[letter] = letters.get(letter, 0 ) + 1
for word in words:
cur = collections.Counter(word)
valid = True
for letter in letters:
if letter not in cur or cur[letter] < letters[letter]:
valid = False
break
if valid and len(word) < length:
result = word
length = len(word)
return result
| class Solution:
def shortest_completing_word(self, licensePlate: str, words: List[str]) -> str:
length = sys.maxsize
result = None
letters = collections.defaultdict()
for letter in licensePlate:
if letter.isalpha():
letter = letter.lower()
letters[letter] = letters.get(letter, 0) + 1
for word in words:
cur = collections.Counter(word)
valid = True
for letter in letters:
if letter not in cur or cur[letter] < letters[letter]:
valid = False
break
if valid and len(word) < length:
result = word
length = len(word)
return result |
originallist=[[1,'a',['cat'],2],[[[3]],'dog'],4,5]
newlist=[]
def flattenlist(x):
for i in x:
if type(i) == list:
flattenlist(i)
else:
newlist.append(i)
return newlist
print(flattenlist(originallist))
list1=[[1, 2], [3, 4], [5, 6, 7]]
list2=[]
def reverselist(y):
for i in sorted(y,reverse=True):
list2.append(sorted(i, reverse=True))
return print(list2)
reverselist(list1)
| originallist = [[1, 'a', ['cat'], 2], [[[3]], 'dog'], 4, 5]
newlist = []
def flattenlist(x):
for i in x:
if type(i) == list:
flattenlist(i)
else:
newlist.append(i)
return newlist
print(flattenlist(originallist))
list1 = [[1, 2], [3, 4], [5, 6, 7]]
list2 = []
def reverselist(y):
for i in sorted(y, reverse=True):
list2.append(sorted(i, reverse=True))
return print(list2)
reverselist(list1) |
#file : InMoov3.minimalArm.py
# this will run with versions of MRL above 1695
# a very minimal script for InMoov
# although this script is very short you can still
# do voice control of a right Arm
# It uses WebkitSpeechRecognition, so you need to use Chrome as your default browser for this script to work
# Start the webgui service without starting the browser
webgui = Runtime.create("WebGui","WebGui")
webgui.autoStartBrowser(False)
webgui.startService()
# Then start the browsers and show the WebkitSpeechRecognition service named i01.ear
webgui.startBrowser("http://localhost:8888/#/service/i01.ear")
# As an alternative you can use the line below to show all services in the browser. In that case you should comment out all lines above that starts with webgui.
# webgui = Runtime.createAndStart("webgui","WebGui")
leftPort = "COM13" #modify port according to your board
rightPort = "COM17" #modify port according to your board
#to tweak the default voice
Voice="cmu-slt-hsmm" # Default female for MarySpeech
#Voice="cmu-bdl" #Male US voice.You need to add the necessary file.jar to myrobotlab.1.0.XXXX/library/jar
#https://github.com/MyRobotLab/pyrobotlab/blob/ff6e2cef4d0642e47ee15e353ef934ac6701e713/home/hairygael/voice-cmu-bdl-5.2.jar
voiceType = Voice
mouth = Runtime.createAndStart("i01.mouth", "MarySpeech")
mouth.setVoice(voiceType)
##############
# starting parts
i01 = Runtime.createAndStart("i01", "InMoov")
i01.startEar()
i01.startMouth()
##############
i01.startLeftArm(leftPort)
#tweak defaults LeftArm
#i01.leftArm.bicep.setMinMax(0,90)
#i01.leftArm.rotate.setMinMax(46,160)
#i01.leftArm.shoulder.setMinMax(30,100)
#i01.leftArm.omoplate.setMinMax(10,75)
#################
i01.startRightArm(rightPort)
# tweak default RightArm
#i01.rightArm.bicep.setMinMax(0,90)
#i01.rightArm.rotate.setMinMax(46,160)
#i01.rightArm.shoulder.setMinMax(30,100)
#i01.rightArm.omoplate.setMinMax(10,75)
#################
# verbal commands
ear = i01.ear
ear.addCommand("attach everything", "i01", "attach")
ear.addCommand("disconnect everything", "i01", "detach")
ear.addCommand("attach left arm", "i01.leftArm", "attach")
ear.addCommand("disconnect left arm", "i01.leftArm", "detach")
ear.addCommand("attach right arm", "i01.rightArm", "attach")
ear.addCommand("disconnect right arm", "i01.rightArm", "detach")
ear.addCommand("rest", "python", "rest")
ear.addCommand("arms front", i01.getName(), "armsFront")
ear.addCommand("da vinci", i01.getName(), "daVinci")
ear.addCommand("capture gesture", ear.getName(), "captureGesture")
ear.addCommand("manual", ear.getName(), "lockOutAllGrammarExcept", "voice control")
ear.addCommand("voice control", ear.getName(), "clearLock")
# Confirmations and Negations are not supported yet in WebkitSpeechRecognition
# So commands will execute immediatley
ear.addComfirmations("yes","correct","ya","yeah", "yes please", "yes of course")
ear.addNegations("no","wrong","nope","nah","no thank you", "no thanks")
ear.startListening()
def rest():
i01.setArmSpeed("left", 1.0, 1.0, 1.0, 1.0)
i01.setArmSpeed("right", 1.0, 1.0, 1.0, 1.0)
i01.moveArm("left",5,90,30,10)
i01.moveArm("right",5,90,30,10)
| webgui = Runtime.create('WebGui', 'WebGui')
webgui.autoStartBrowser(False)
webgui.startService()
webgui.startBrowser('http://localhost:8888/#/service/i01.ear')
left_port = 'COM13'
right_port = 'COM17'
voice = 'cmu-slt-hsmm'
voice_type = Voice
mouth = Runtime.createAndStart('i01.mouth', 'MarySpeech')
mouth.setVoice(voiceType)
i01 = Runtime.createAndStart('i01', 'InMoov')
i01.startEar()
i01.startMouth()
i01.startLeftArm(leftPort)
i01.startRightArm(rightPort)
ear = i01.ear
ear.addCommand('attach everything', 'i01', 'attach')
ear.addCommand('disconnect everything', 'i01', 'detach')
ear.addCommand('attach left arm', 'i01.leftArm', 'attach')
ear.addCommand('disconnect left arm', 'i01.leftArm', 'detach')
ear.addCommand('attach right arm', 'i01.rightArm', 'attach')
ear.addCommand('disconnect right arm', 'i01.rightArm', 'detach')
ear.addCommand('rest', 'python', 'rest')
ear.addCommand('arms front', i01.getName(), 'armsFront')
ear.addCommand('da vinci', i01.getName(), 'daVinci')
ear.addCommand('capture gesture', ear.getName(), 'captureGesture')
ear.addCommand('manual', ear.getName(), 'lockOutAllGrammarExcept', 'voice control')
ear.addCommand('voice control', ear.getName(), 'clearLock')
ear.addComfirmations('yes', 'correct', 'ya', 'yeah', 'yes please', 'yes of course')
ear.addNegations('no', 'wrong', 'nope', 'nah', 'no thank you', 'no thanks')
ear.startListening()
def rest():
i01.setArmSpeed('left', 1.0, 1.0, 1.0, 1.0)
i01.setArmSpeed('right', 1.0, 1.0, 1.0, 1.0)
i01.moveArm('left', 5, 90, 30, 10)
i01.moveArm('right', 5, 90, 30, 10) |
my_ssid = "ElchlandGast"
my_wp2_pwd = "R1ng0Lu7713"
ntp_server = "0.de.pool.ntp.org"
my_mqtt_usr = ""
my_mqtt_pwd = ""
my_mqtt_srv = "192.168.178.35"
my_mqtt_port = 1883
my_mqtt_alive_s = 60
my_mqtt_encrypt_key = None # e.g. b'1234123412341234'
my_mqtt_encrypt_CBC = None # e.g. b'5678567856785678'
| my_ssid = 'ElchlandGast'
my_wp2_pwd = 'R1ng0Lu7713'
ntp_server = '0.de.pool.ntp.org'
my_mqtt_usr = ''
my_mqtt_pwd = ''
my_mqtt_srv = '192.168.178.35'
my_mqtt_port = 1883
my_mqtt_alive_s = 60
my_mqtt_encrypt_key = None
my_mqtt_encrypt_cbc = None |
# Definition for a binary tree node.
# class TreeNode:
# def __init__(self, val=0, left=None, right=None):
# self.val = val
# self.left = left
# self.right = right
class Solution:
def largestValues(self, root: TreeNode) -> List[int]:
heightCache = defaultdict(lambda : float('-inf'))
def preorder(node, depth):
if not node:
return
heightCache[depth] = max(heightCache[depth], node.val)
preorder(node.left, depth + 1)
preorder(node.right, depth + 1)
preorder(root, 0)
result = []
for i, val in sorted(heightCache.items()):
result.append(val)
return result | class Solution:
def largest_values(self, root: TreeNode) -> List[int]:
height_cache = defaultdict(lambda : float('-inf'))
def preorder(node, depth):
if not node:
return
heightCache[depth] = max(heightCache[depth], node.val)
preorder(node.left, depth + 1)
preorder(node.right, depth + 1)
preorder(root, 0)
result = []
for (i, val) in sorted(heightCache.items()):
result.append(val)
return result |
# -*- coding: utf-8 -*-
class AuthInfo(object):
def __init__(self, username, projectname, commit_id, auth_key):
self.username = username
self.projectname = projectname
self.commit_id = commit_id
self.auth_key = auth_key
@classmethod
def parse(cls, s):
if not s:
return None
try:
return cls(*s.split("_:_"))
except:
return None
def to_dict(self):
return {
"username": self.username, "projectname": self.projectname,
"commit_id": self.commit_id, "auth_key": self.auth_key
}
| class Authinfo(object):
def __init__(self, username, projectname, commit_id, auth_key):
self.username = username
self.projectname = projectname
self.commit_id = commit_id
self.auth_key = auth_key
@classmethod
def parse(cls, s):
if not s:
return None
try:
return cls(*s.split('_:_'))
except:
return None
def to_dict(self):
return {'username': self.username, 'projectname': self.projectname, 'commit_id': self.commit_id, 'auth_key': self.auth_key} |
map = 200090300
string = "Mu Lung?"
if sm.getFieldID() == 250000100:
map = 200090310
string = "Orbis?"
response = sm.sendAskYesNo("Would you like to go to " + (string))
if response:
sm.warp(map, 0) | map = 200090300
string = 'Mu Lung?'
if sm.getFieldID() == 250000100:
map = 200090310
string = 'Orbis?'
response = sm.sendAskYesNo('Would you like to go to ' + string)
if response:
sm.warp(map, 0) |
def get_baseline_rule():
rule = ".highlight { border-radius: 3.25px; }\n"
rule += ".highlight pre { font-family: monospace; font-size: 14px; overflow-x: auto; padding: 1.25rem 1.5rem; white-space: pre; word-wrap: normal; line-height: 1.5; "
rule += "}\n"
return rule
def get_line_no_rule(comment_rule: str, line_no_type: str, num_lines: int) -> str:
num_digits = len(str(num_lines))
line_no_color = _comment_rule_to_color(comment_rule)
rule = (
".highlight { counter-reset: line; }\n"
"/* from: https://codepen.io/elomatreb/pen/hbgxp */\n"
".highlight .highlight-line::before { "
"counter-increment: line; "
"content: counter(line); "
"display: inline-block; "
"padding: 0 .5em 0 0; "
f"width: {num_digits}em; "
f"color: {line_no_color} "
)
if num_digits > 1:
rule += "text-align: right; "
if line_no_type == "ruled":
rule += f"border-right: 1px solid {line_no_color}" "margin-right: 0.5em;"
rule += "}\n"
return rule
def _comment_rule_to_color(comment_rule: str) -> str:
words = comment_rule.split(" ")
for word in words:
if word[0] == "#":
if word[-1] == ";":
return word
else:
return word + "; "
return "currentColor; "
| def get_baseline_rule():
rule = '.highlight { border-radius: 3.25px; }\n'
rule += '.highlight pre { font-family: monospace; font-size: 14px; overflow-x: auto; padding: 1.25rem 1.5rem; white-space: pre; word-wrap: normal; line-height: 1.5; '
rule += '}\n'
return rule
def get_line_no_rule(comment_rule: str, line_no_type: str, num_lines: int) -> str:
num_digits = len(str(num_lines))
line_no_color = _comment_rule_to_color(comment_rule)
rule = f'.highlight {{ counter-reset: line; }}\n/* from: https://codepen.io/elomatreb/pen/hbgxp */\n.highlight .highlight-line::before {{ counter-increment: line; content: counter(line); display: inline-block; padding: 0 .5em 0 0; width: {num_digits}em; color: {line_no_color} '
if num_digits > 1:
rule += 'text-align: right; '
if line_no_type == 'ruled':
rule += f'border-right: 1px solid {line_no_color}margin-right: 0.5em;'
rule += '}\n'
return rule
def _comment_rule_to_color(comment_rule: str) -> str:
words = comment_rule.split(' ')
for word in words:
if word[0] == '#':
if word[-1] == ';':
return word
else:
return word + '; '
return 'currentColor; ' |
model=dict(
type='Recognizer3D',
backbone=dict(
type='SwinTransformer3D',
patch_size=(2,4,4),
embed_dim=96,
depths=[2, 2, 6, 2],
num_heads=[3, 6, 12, 24],
window_size=(8,7,7),
mlp_ratio=4.,
qkv_bias=True,
qk_scale=None,
drop_rate=0.,
attn_drop_rate=0.,
drop_path_rate=0.1,
patch_norm=True),
cls_head=dict(
type='TranSTHead',
in_channels=768,
dropout_ratio=0.5,
num_classes=157,
multi_class=True,
label_smooth_eps=0.1,
topk=(3),
tranST=dict(hidden_dim=512,
enc_layer_num=0,
stld_layer_num=2,
n_head=8,
dim_feedforward=2048,
dropout=0.1,
normalize_before=False,
fusion=False,
rm_self_attn_dec=False,
rm_first_self_attn=False,
activation="gelu",
return_intermediate_dec=False,
t_only=False
),
loss_cls=dict(type='AsymmetricLossOptimized', gamma_neg=2, gamma_pos=1),
),
test_cfg=dict(
maximize_clips='score',
max_testing_views=4
))
# dataset settings
dataset_type = 'CharadesDataset'
data_root = 'data/charades/Charades_rgb'
data_root_val = 'data/charades/Charades_rgb'
ann_file_train = 'data/charades/annotations/charades_train_list_rawframes.csv'
ann_file_val = 'data/charades/annotations/charades_val_list_rawframes.csv'
ann_file_test = 'data/charades/annotations/charades_val_list_rawframes.csv'
img_norm_cfg = dict(
# mean=[105.315, 93.84, 86.19],
# std=[33.405, 31.875, 33.66],
mean=[105.315, 93.84, 86.19],
std=[33.405, 31.875, 33.66],
to_bgr=False)
train_pipeline = [
dict(
type='SampleCharadesFrames',
clip_len=32,
frame_interval=2,
num_clips=1),
dict(type='RawFrameDecode'),
dict(type='Resize', scale=(-1, 256)),
dict(type='RandomResizedCrop'),
dict(type='Resize', scale=(224, 224), keep_ratio=False),
dict(type='Flip', flip_ratio=0.5),
dict(type='Normalize', **img_norm_cfg),
dict(type='FormatShape', input_format='NCTHW'),
dict(type='Collect', keys=['imgs', 'label'], meta_keys=[]),
dict(type='ToTensor', keys=['imgs', 'label'])
]
val_pipeline = [
dict(
type='SampleCharadesFrames',
clip_len=32,
frame_interval=2,
num_clips=1,
test_mode=True),
dict(type='RawFrameDecode'),
dict(type='Resize', scale=(-1, 256)),
dict(type='CenterCrop', crop_size=256),
dict(type='Flip', flip_ratio=0),
dict(type='Normalize', **img_norm_cfg),
dict(type='FormatShape', input_format='NCTHW'),
dict(type='Collect', keys=['imgs'], meta_keys=[]),
dict(type='ToTensor', keys=['imgs'])
]
test_pipeline = [
dict(
type='SampleCharadesFrames',
clip_len=32,
frame_interval=2,
num_clips=10,
test_mode=True),
dict(type='RawFrameDecode'),
dict(type='Resize', scale=(-1, 256)),
dict(type='ThreeCrop', crop_size=256),
dict(type='Flip', flip_ratio=0),
dict(type='Normalize', **img_norm_cfg),
dict(type='FormatShape', input_format='NCTHW'),
dict(type='Collect', keys=['imgs'], meta_keys=[]),
dict(type='ToTensor', keys=['imgs'])
]
data = dict(
videos_per_gpu=8,
workers_per_gpu=2,
val_dataloader=dict(videos_per_gpu=1),
test_dataloader=dict(videos_per_gpu=1),
train=dict(
type=dataset_type,
ann_file=ann_file_train,
data_prefix=data_root,
pipeline=train_pipeline),
val=dict(
type=dataset_type,
ann_file=ann_file_val,
data_prefix=data_root_val,
pipeline=val_pipeline),
test=dict(
type=dataset_type,
ann_file=ann_file_test,
data_prefix=data_root_val,
pipeline=test_pipeline))
evaluation = dict(
interval=1, metrics=['mean_average_precision'])
# optimizer
optimizer = dict(type='AdamW', lr=1e-4, betas=(0.9, 0.999), weight_decay=0.05, constructor='freeze_backbone_constructor',
paramwise_cfg=dict(custom_keys={'absolute_pos_embed': dict(decay_mult=0.),
'relative_position_bias_table': dict(decay_mult=0.),
'norm': dict(decay_mult=0.),
'pos_s': dict(decay_mult=0.),
'pos_t': dict(decay_mult=0.),
'norm1': dict(decay_mult=0.),
'norm2': dict(decay_mult=0.),
'backbone': dict(lr_mult=0.1),
'TranST':dict(lr_mult=0.2)}))
# optimizer_config = dict(grad_clip=dict(max_norm=40, norm_type=2))
# learning policy
lr_config = dict(
policy='OneCycle',
max_lr=1e-04,
anneal_strategy='cos',
final_div_factor=1e3,
)
total_epochs = 80
# runtime settings
work_dir = './work_dirs/k400_swin_tiny_1k_patch244_freeze_backbone_window877_tranST_charades'
find_unused_parameters = True
checkpoint_config = dict(interval=5)
log_config = dict(
interval=10,
hooks=[
dict(type='TextLoggerHook'),
dict(type='TensorboardLoggerHook'),
])
# runtime settings
dist_params = dict(backend='nccl')
log_level = 'INFO'
# load_from = ('https://github.com/SwinTransformer/storage/releases/download/'
# 'v1.0.4/swin_tiny_patch244_window877_kinetics400_1k.pth')
# load_from = ('work_dirs/k400_swin_tiny_1k_patch244_window877_charades/map4210.pth')
load_from = ('work_dirs/k400_swin_tiny_1k_patch244_window877_charades/map4048_32f.pth')
# load_from = None
resume_from = None
workflow = [('train', 1)]
# do not use mmdet version fp16
fp16 = None
optimizer_config = dict(
type="DistOptimizerHook",
update_interval=2,
grad_clip=None,
coalesce=True,
bucket_size_mb=-1,
use_fp16=True,
) | model = dict(type='Recognizer3D', backbone=dict(type='SwinTransformer3D', patch_size=(2, 4, 4), embed_dim=96, depths=[2, 2, 6, 2], num_heads=[3, 6, 12, 24], window_size=(8, 7, 7), mlp_ratio=4.0, qkv_bias=True, qk_scale=None, drop_rate=0.0, attn_drop_rate=0.0, drop_path_rate=0.1, patch_norm=True), cls_head=dict(type='TranSTHead', in_channels=768, dropout_ratio=0.5, num_classes=157, multi_class=True, label_smooth_eps=0.1, topk=3, tranST=dict(hidden_dim=512, enc_layer_num=0, stld_layer_num=2, n_head=8, dim_feedforward=2048, dropout=0.1, normalize_before=False, fusion=False, rm_self_attn_dec=False, rm_first_self_attn=False, activation='gelu', return_intermediate_dec=False, t_only=False), loss_cls=dict(type='AsymmetricLossOptimized', gamma_neg=2, gamma_pos=1)), test_cfg=dict(maximize_clips='score', max_testing_views=4))
dataset_type = 'CharadesDataset'
data_root = 'data/charades/Charades_rgb'
data_root_val = 'data/charades/Charades_rgb'
ann_file_train = 'data/charades/annotations/charades_train_list_rawframes.csv'
ann_file_val = 'data/charades/annotations/charades_val_list_rawframes.csv'
ann_file_test = 'data/charades/annotations/charades_val_list_rawframes.csv'
img_norm_cfg = dict(mean=[105.315, 93.84, 86.19], std=[33.405, 31.875, 33.66], to_bgr=False)
train_pipeline = [dict(type='SampleCharadesFrames', clip_len=32, frame_interval=2, num_clips=1), dict(type='RawFrameDecode'), dict(type='Resize', scale=(-1, 256)), dict(type='RandomResizedCrop'), dict(type='Resize', scale=(224, 224), keep_ratio=False), dict(type='Flip', flip_ratio=0.5), dict(type='Normalize', **img_norm_cfg), dict(type='FormatShape', input_format='NCTHW'), dict(type='Collect', keys=['imgs', 'label'], meta_keys=[]), dict(type='ToTensor', keys=['imgs', 'label'])]
val_pipeline = [dict(type='SampleCharadesFrames', clip_len=32, frame_interval=2, num_clips=1, test_mode=True), dict(type='RawFrameDecode'), dict(type='Resize', scale=(-1, 256)), dict(type='CenterCrop', crop_size=256), dict(type='Flip', flip_ratio=0), dict(type='Normalize', **img_norm_cfg), dict(type='FormatShape', input_format='NCTHW'), dict(type='Collect', keys=['imgs'], meta_keys=[]), dict(type='ToTensor', keys=['imgs'])]
test_pipeline = [dict(type='SampleCharadesFrames', clip_len=32, frame_interval=2, num_clips=10, test_mode=True), dict(type='RawFrameDecode'), dict(type='Resize', scale=(-1, 256)), dict(type='ThreeCrop', crop_size=256), dict(type='Flip', flip_ratio=0), dict(type='Normalize', **img_norm_cfg), dict(type='FormatShape', input_format='NCTHW'), dict(type='Collect', keys=['imgs'], meta_keys=[]), dict(type='ToTensor', keys=['imgs'])]
data = dict(videos_per_gpu=8, workers_per_gpu=2, val_dataloader=dict(videos_per_gpu=1), test_dataloader=dict(videos_per_gpu=1), train=dict(type=dataset_type, ann_file=ann_file_train, data_prefix=data_root, pipeline=train_pipeline), val=dict(type=dataset_type, ann_file=ann_file_val, data_prefix=data_root_val, pipeline=val_pipeline), test=dict(type=dataset_type, ann_file=ann_file_test, data_prefix=data_root_val, pipeline=test_pipeline))
evaluation = dict(interval=1, metrics=['mean_average_precision'])
optimizer = dict(type='AdamW', lr=0.0001, betas=(0.9, 0.999), weight_decay=0.05, constructor='freeze_backbone_constructor', paramwise_cfg=dict(custom_keys={'absolute_pos_embed': dict(decay_mult=0.0), 'relative_position_bias_table': dict(decay_mult=0.0), 'norm': dict(decay_mult=0.0), 'pos_s': dict(decay_mult=0.0), 'pos_t': dict(decay_mult=0.0), 'norm1': dict(decay_mult=0.0), 'norm2': dict(decay_mult=0.0), 'backbone': dict(lr_mult=0.1), 'TranST': dict(lr_mult=0.2)}))
lr_config = dict(policy='OneCycle', max_lr=0.0001, anneal_strategy='cos', final_div_factor=1000.0)
total_epochs = 80
work_dir = './work_dirs/k400_swin_tiny_1k_patch244_freeze_backbone_window877_tranST_charades'
find_unused_parameters = True
checkpoint_config = dict(interval=5)
log_config = dict(interval=10, hooks=[dict(type='TextLoggerHook'), dict(type='TensorboardLoggerHook')])
dist_params = dict(backend='nccl')
log_level = 'INFO'
load_from = 'work_dirs/k400_swin_tiny_1k_patch244_window877_charades/map4048_32f.pth'
resume_from = None
workflow = [('train', 1)]
fp16 = None
optimizer_config = dict(type='DistOptimizerHook', update_interval=2, grad_clip=None, coalesce=True, bucket_size_mb=-1, use_fp16=True) |
list_a = [5, 20, 3, 7, 6, 8]
n = int(input())
list_a = sorted(list_a)
list_len = len(list_a)
res = list_a[list_len - n:]
for i in range(n):
res[i] = str(res[i])
print(" ".join(res))
| list_a = [5, 20, 3, 7, 6, 8]
n = int(input())
list_a = sorted(list_a)
list_len = len(list_a)
res = list_a[list_len - n:]
for i in range(n):
res[i] = str(res[i])
print(' '.join(res)) |
# level1.py
def first_room():
print("Welcome to the dungeon. You walk into the first room and see an empty hall.")
print("There is an ominous door at the far end of this hall.")
options = {1: "Go back home to safety", 2: "Go through door"}
for k, v in options.items():
print("[" + str(k) + "] " + v)
val = input("Select the number of your choice ")
return int(val)
def second_room():
print("A box stands in the middle of this room. There is a skull and crossbones on the box.")
print("Do you open the box or ignore it and continue through the next door?")
options = {1: "Open the box", 2: "Continue through the next door", 3: "Go back to entrance"}
for k, v in options.items():
print("[" + str(k) + "] " + v)
val = input("Select the number of your choice ")
return int(val)
def next_level():
print("There are stairs leading down.")
options = {1: "Go back home to safety", 2: "Descend the stairs"}
for k, v in options.items():
print("[" + str(k) + "] " + v)
val = input("Select the number of your choice ")
return int(val)
| def first_room():
print('Welcome to the dungeon. You walk into the first room and see an empty hall.')
print('There is an ominous door at the far end of this hall.')
options = {1: 'Go back home to safety', 2: 'Go through door'}
for (k, v) in options.items():
print('[' + str(k) + '] ' + v)
val = input('Select the number of your choice ')
return int(val)
def second_room():
print('A box stands in the middle of this room. There is a skull and crossbones on the box.')
print('Do you open the box or ignore it and continue through the next door?')
options = {1: 'Open the box', 2: 'Continue through the next door', 3: 'Go back to entrance'}
for (k, v) in options.items():
print('[' + str(k) + '] ' + v)
val = input('Select the number of your choice ')
return int(val)
def next_level():
print('There are stairs leading down.')
options = {1: 'Go back home to safety', 2: 'Descend the stairs'}
for (k, v) in options.items():
print('[' + str(k) + '] ' + v)
val = input('Select the number of your choice ')
return int(val) |
# Stack and Queue
# https://stackabuse.com/stacks-and-queues-in-python/
# A simple class stack that only allows pop and push operations
class Stack:
def __init__(self):
self.stack = []
def pop(self):
if len(self.stack) < 1:
return None
return self.stack.pop()
def push(self, item):
self.stack.append(item)
def size(self):
return len(self.stack)
# And a queue that only has enqueue and dequeue operations
class Queue:
def __init__(self):
self.queue = []
def enqueue(self, item):
self.queue.append(item)
def dequeue(self):
if len(self.queue) < 1:
return None
return self.queue.pop(0)
def size(self):
return len(self.queue) | class Stack:
def __init__(self):
self.stack = []
def pop(self):
if len(self.stack) < 1:
return None
return self.stack.pop()
def push(self, item):
self.stack.append(item)
def size(self):
return len(self.stack)
class Queue:
def __init__(self):
self.queue = []
def enqueue(self, item):
self.queue.append(item)
def dequeue(self):
if len(self.queue) < 1:
return None
return self.queue.pop(0)
def size(self):
return len(self.queue) |
class Solution:
def relativeSortArray(self, arr1: List[int], arr2: List[int]) -> List[int]:
hashMap = collections.Counter(arr1)
array = []
for num in arr2:
array += [num] * hashMap.pop(num)
return array + sorted(hashMap.elements())
class Solution:
def relativeSortArray(self, arr1: List[int], arr2: List[int]) -> List[int]:
hashMap = collections.Counter(arr1)
array = []
for num in arr2:
array += [num] * hashMap.pop(num)
for num in sorted(hashMap.keys()):
array += [num] * hashMap[num]
return array
class Solution:
def relativeSortArray(self, arr1: List[int], arr2: List[int]) -> List[int]:
hashMap = {}
for num in arr1:
if num not in hashMap:
hashMap[num] = 1
else:
hashMap[num] += 1
array = []
for num in arr2:
array += [num] * hashMap.pop(num)
for num in sorted(hashMap.keys()):
array += [num] * hashMap[num]
return array
| class Solution:
def relative_sort_array(self, arr1: List[int], arr2: List[int]) -> List[int]:
hash_map = collections.Counter(arr1)
array = []
for num in arr2:
array += [num] * hashMap.pop(num)
return array + sorted(hashMap.elements())
class Solution:
def relative_sort_array(self, arr1: List[int], arr2: List[int]) -> List[int]:
hash_map = collections.Counter(arr1)
array = []
for num in arr2:
array += [num] * hashMap.pop(num)
for num in sorted(hashMap.keys()):
array += [num] * hashMap[num]
return array
class Solution:
def relative_sort_array(self, arr1: List[int], arr2: List[int]) -> List[int]:
hash_map = {}
for num in arr1:
if num not in hashMap:
hashMap[num] = 1
else:
hashMap[num] += 1
array = []
for num in arr2:
array += [num] * hashMap.pop(num)
for num in sorted(hashMap.keys()):
array += [num] * hashMap[num]
return array |
# Program to check if number is Disarium Number or Nor :)
n = input("Enter a number: ")
num = [i for i in n] # splitting the number into array of digits
a = 0 # creating empty variable
for x in range(len(n)):
a += int(num[x]) ** (x+1) # Logic for Disarium Number
if a == int(n): # Checks whether the sum is equal to the number itself
print(n, "is a Disarium.")
else:
print(n, "is not a Disarium.") | n = input('Enter a number: ')
num = [i for i in n]
a = 0
for x in range(len(n)):
a += int(num[x]) ** (x + 1)
if a == int(n):
print(n, 'is a Disarium.')
else:
print(n, 'is not a Disarium.') |
# OpenWeatherMap API Key
weather_api_key = "a03abb9d3c267db1cbe474a809d9d185"
# Google API Key
g_key = "AIzaSyCCCDtBWuZZ51TMovxlWIkmC7z_VPlfrzA"
| weather_api_key = 'a03abb9d3c267db1cbe474a809d9d185'
g_key = 'AIzaSyCCCDtBWuZZ51TMovxlWIkmC7z_VPlfrzA' |
tempo = int(input('Quantos anos tem seu carro ?'))
if tempo <=3:
print('Carro Novo')
else:
print('Carro Velho')
print('__FIM__') | tempo = int(input('Quantos anos tem seu carro ?'))
if tempo <= 3:
print('Carro Novo')
else:
print('Carro Velho')
print('__FIM__') |
# Copyright (c) 2020 original authors
#
# Licensed under the Apache License, Version 2.0 (the License);
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
class Position:
def __init__(self, start=0, end=0):
self._start = start
self._end = end
@property
def start(self):
return self._start
@property
def end(self):
return self._end
| class Position:
def __init__(self, start=0, end=0):
self._start = start
self._end = end
@property
def start(self):
return self._start
@property
def end(self):
return self._end |
for i in range(10000):
class A:
def __init__(self, x):
self.x = x
| for i in range(10000):
class A:
def __init__(self, x):
self.x = x |
# -*- coding: utf-8 -*-
'''
Configuration of the alternatives system
Control the alternatives system
.. code-block:: yaml
{% set my_hadoop_conf = '/opt/hadoop/conf' %}
{{ my_hadoop_conf }}:
file.directory
hadoop-0.20-conf:
alternatives.install:
- name: hadoop-0.20-conf
- link: /etc/hadoop-0.20/conf
- path: {{ my_hadoop_conf }}
- priority: 30
- require:
- file: {{ my_hadoop_conf }}
hadoop-0.20-conf:
alternatives.remove:
- name: hadoop-0.20-conf
- path: {{ my_hadoop_conf }}
'''
# Define a function alias in order not to shadow built-in's
__func_alias__ = {
'set_': 'set'
}
def install(name, link, path, priority):
'''
Install new alternative for defined <name>
name
is the master name for this link group
(e.g. pager)
link
is the symlink pointing to /etc/alternatives/<name>.
(e.g. /usr/bin/pager)
path
is the location of the new alternative target.
NB: This file / directory must already exist.
(e.g. /usr/bin/less)
priority
is an integer; options with higher numbers have higher priority in
automatic mode.
'''
ret = {'name': name,
'link': link,
'path': path,
'priority': priority,
'result': True,
'changes': {},
'comment': ''}
isinstalled = __salt__['alternatives.check_exists'](name, path)
if not isinstalled:
if __opts__['test']:
ret['comment'] = (
'Alternative will be set for {0} to {1} with priority {2}'
).format(name, path, priority)
ret['result'] = None
return ret
__salt__['alternatives.install'](name, link, path, priority)
ret['comment'] = (
'Setting alternative for {0} to {1} with priority {2}'
).format(name, path, priority)
ret['changes'] = {'name': name,
'link': link,
'path': path,
'priority': priority}
return ret
ret['comment'] = 'Alternatives for {0} is already set to {1}'.format(name, path)
return ret
def remove(name, path):
'''
Removes installed alternative for defined <name> and <path>
or fallback to default alternative, if some defined before.
name
is the master name for this link group
(e.g. pager)
path
is the location of one of the alternative target files.
(e.g. /usr/bin/less)
'''
ret = {'name': name,
'path': path,
'result': True,
'changes': {},
'comment': ''}
isinstalled = __salt__['alternatives.check_exists'](name, path)
if isinstalled:
if __opts__['test']:
ret['comment'] = ('Alternative for {0} will be removed'
.format(name))
ret['result'] = None
return ret
__salt__['alternatives.remove'](name, path)
current = __salt__['alternatives.show_current'](name)
if current:
ret['result'] = True
ret['comment'] = (
'Alternative for {0} removed. Falling back to path {1}'
).format(name, current)
ret['changes'] = {'path': current}
return ret
ret['comment'] = 'Alternative for {0} removed'.format(name)
ret['changes'] = {}
return ret
current = __salt__['alternatives.show_current'](name)
if current:
ret['result'] = True
ret['comment'] = (
'Alternative for {0} is set to it\'s default path {1}'
).format(name, current)
return ret
ret['result'] = False
ret['comment'] = (
'Alternative for {0} doesn\'t exist'
).format(name)
return ret
def auto(name):
'''
.. versionadded:: 0.17.0
Instruct alternatives to use the highest priority
path for <name>
name
is the master name for this link group
(e.g. pager)
'''
ret = {'name': name,
'result': True,
'comment': '',
'changes': {}}
display = __salt__['alternatives.display'](name)
line = display.splitlines()[0]
if line.endswith(' auto mode'):
ret['comment'] = '{0} already in auto mode'.format(name)
return ret
if __opts__['test']:
ret['comment'] = '{0} will be put in auto mode'.format(name)
ret['result'] = None
return ret
ret['changes']['result'] = __salt__['alternatives.auto'](name)
return ret
def set_(name, path):
'''
.. versionadded:: 0.17.0
Sets alternative for <name> to <path>, if <path> is defined
as an alternative for <name>.
name
is the master name for this link group
(e.g. pager)
path
is the location of one of the alternative target files.
(e.g. /usr/bin/less)
'''
ret = {'name': name,
'path': path,
'result': True,
'changes': {},
'comment': ''}
current = __salt__['alternatives.show_current'](name)
if current == path:
ret['comment'] = 'Alternative for {0} already set to {1}'.format(name, path)
return ret
display = __salt__['alternatives.display'](name)
isinstalled = False
for line in display.splitlines():
if line.startswith(path):
isinstalled = True
break
if isinstalled:
if __opts__['test']:
ret['comment'] = (
'Alternative for {0} will be set to path {1}'
).format(name, current)
ret['result'] = None
return ret
__salt__['alternatives.set'](name, path)
current = __salt__['alternatives.show_current'](name)
if current == path:
ret['result'] = True
ret['comment'] = (
'Alternative for {0} set to path {1}'
).format(name, current)
ret['changes'] = {'path': current}
else:
ret['comment'] = 'Alternative for {0} not updated'.format(name)
return ret
else:
ret['result'] = False
ret['comment'] = (
'Alternative {0} for {1} doesn\'t exist'
).format(path, name)
return ret
| """
Configuration of the alternatives system
Control the alternatives system
.. code-block:: yaml
{% set my_hadoop_conf = '/opt/hadoop/conf' %}
{{ my_hadoop_conf }}:
file.directory
hadoop-0.20-conf:
alternatives.install:
- name: hadoop-0.20-conf
- link: /etc/hadoop-0.20/conf
- path: {{ my_hadoop_conf }}
- priority: 30
- require:
- file: {{ my_hadoop_conf }}
hadoop-0.20-conf:
alternatives.remove:
- name: hadoop-0.20-conf
- path: {{ my_hadoop_conf }}
"""
__func_alias__ = {'set_': 'set'}
def install(name, link, path, priority):
"""
Install new alternative for defined <name>
name
is the master name for this link group
(e.g. pager)
link
is the symlink pointing to /etc/alternatives/<name>.
(e.g. /usr/bin/pager)
path
is the location of the new alternative target.
NB: This file / directory must already exist.
(e.g. /usr/bin/less)
priority
is an integer; options with higher numbers have higher priority in
automatic mode.
"""
ret = {'name': name, 'link': link, 'path': path, 'priority': priority, 'result': True, 'changes': {}, 'comment': ''}
isinstalled = __salt__['alternatives.check_exists'](name, path)
if not isinstalled:
if __opts__['test']:
ret['comment'] = 'Alternative will be set for {0} to {1} with priority {2}'.format(name, path, priority)
ret['result'] = None
return ret
__salt__['alternatives.install'](name, link, path, priority)
ret['comment'] = 'Setting alternative for {0} to {1} with priority {2}'.format(name, path, priority)
ret['changes'] = {'name': name, 'link': link, 'path': path, 'priority': priority}
return ret
ret['comment'] = 'Alternatives for {0} is already set to {1}'.format(name, path)
return ret
def remove(name, path):
"""
Removes installed alternative for defined <name> and <path>
or fallback to default alternative, if some defined before.
name
is the master name for this link group
(e.g. pager)
path
is the location of one of the alternative target files.
(e.g. /usr/bin/less)
"""
ret = {'name': name, 'path': path, 'result': True, 'changes': {}, 'comment': ''}
isinstalled = __salt__['alternatives.check_exists'](name, path)
if isinstalled:
if __opts__['test']:
ret['comment'] = 'Alternative for {0} will be removed'.format(name)
ret['result'] = None
return ret
__salt__['alternatives.remove'](name, path)
current = __salt__['alternatives.show_current'](name)
if current:
ret['result'] = True
ret['comment'] = 'Alternative for {0} removed. Falling back to path {1}'.format(name, current)
ret['changes'] = {'path': current}
return ret
ret['comment'] = 'Alternative for {0} removed'.format(name)
ret['changes'] = {}
return ret
current = __salt__['alternatives.show_current'](name)
if current:
ret['result'] = True
ret['comment'] = "Alternative for {0} is set to it's default path {1}".format(name, current)
return ret
ret['result'] = False
ret['comment'] = "Alternative for {0} doesn't exist".format(name)
return ret
def auto(name):
"""
.. versionadded:: 0.17.0
Instruct alternatives to use the highest priority
path for <name>
name
is the master name for this link group
(e.g. pager)
"""
ret = {'name': name, 'result': True, 'comment': '', 'changes': {}}
display = __salt__['alternatives.display'](name)
line = display.splitlines()[0]
if line.endswith(' auto mode'):
ret['comment'] = '{0} already in auto mode'.format(name)
return ret
if __opts__['test']:
ret['comment'] = '{0} will be put in auto mode'.format(name)
ret['result'] = None
return ret
ret['changes']['result'] = __salt__['alternatives.auto'](name)
return ret
def set_(name, path):
"""
.. versionadded:: 0.17.0
Sets alternative for <name> to <path>, if <path> is defined
as an alternative for <name>.
name
is the master name for this link group
(e.g. pager)
path
is the location of one of the alternative target files.
(e.g. /usr/bin/less)
"""
ret = {'name': name, 'path': path, 'result': True, 'changes': {}, 'comment': ''}
current = __salt__['alternatives.show_current'](name)
if current == path:
ret['comment'] = 'Alternative for {0} already set to {1}'.format(name, path)
return ret
display = __salt__['alternatives.display'](name)
isinstalled = False
for line in display.splitlines():
if line.startswith(path):
isinstalled = True
break
if isinstalled:
if __opts__['test']:
ret['comment'] = 'Alternative for {0} will be set to path {1}'.format(name, current)
ret['result'] = None
return ret
__salt__['alternatives.set'](name, path)
current = __salt__['alternatives.show_current'](name)
if current == path:
ret['result'] = True
ret['comment'] = 'Alternative for {0} set to path {1}'.format(name, current)
ret['changes'] = {'path': current}
else:
ret['comment'] = 'Alternative for {0} not updated'.format(name)
return ret
else:
ret['result'] = False
ret['comment'] = "Alternative {0} for {1} doesn't exist".format(path, name)
return ret |
class line_dp:
def reader(self,FileName): #puts each line of a file into an entry of a list, removing "\n"
f = open(FileName,'r')
out =[]
i = 0
for lin in f:
out.append(lin)
if out[i].count("\n") != 0: #removes "\n"
out[i] = out[i].replace("\n","")
i = i + 1
numlines = len(out)
return out
def writer(self,FileName, linelist):
f = open(FileName,'w')
f.seek(0)
for line in linelist:
f.write(line)
f.write("\n")
### Some handy tools
def STR(self,linelist):
''' converts all elements in a list to strings '''
out = []
for x in linelist:
out.append(str(x))
return out
def reducespaces(self,line):
''' removes excessive spaces; separates '''
i = 0
out = []
for string in line:
if line[i] == ' ' and line[i-1] == ' ':
pass
else:
out.append(line[i])
i = i + 1
s_out = ''.join(out)
ready_out = s_out.split(' ')
return ready_out
def redspfile(self,linelist):
'''extension of reducespaces(): converts a linelist to a list of nested lists'''
newlist = []
for line in linelist:
newlist.append(self.reducespaces(line)) #should be in line I/O
return newlist
def getlineslists(self,listnl):
new = []
for List in listnl:
new.append(' '.join(List))
return new
def listToFlt(self,List):
convert = []
for y in List:
try:
convert.append(float(y))
except:
convert.append(y)
#convert = [float(y) for y in List] #
return convert
def nestedToFlt(self,ListNestedLists):
convert = ListNestedLists #placeholder
i= 0 #counter
for x in convert:
convert[i]= self.listToFlt(x)#returns a list to replace the original
i = i + 1 #...nested list
return convert
# def Indir(self, path, ftype):
# return path, self.reader(path+'/'ftype+'_ls.dir')
lin = line_dp()
| class Line_Dp:
def reader(self, FileName):
f = open(FileName, 'r')
out = []
i = 0
for lin in f:
out.append(lin)
if out[i].count('\n') != 0:
out[i] = out[i].replace('\n', '')
i = i + 1
numlines = len(out)
return out
def writer(self, FileName, linelist):
f = open(FileName, 'w')
f.seek(0)
for line in linelist:
f.write(line)
f.write('\n')
def str(self, linelist):
""" converts all elements in a list to strings """
out = []
for x in linelist:
out.append(str(x))
return out
def reducespaces(self, line):
""" removes excessive spaces; separates """
i = 0
out = []
for string in line:
if line[i] == ' ' and line[i - 1] == ' ':
pass
else:
out.append(line[i])
i = i + 1
s_out = ''.join(out)
ready_out = s_out.split(' ')
return ready_out
def redspfile(self, linelist):
"""extension of reducespaces(): converts a linelist to a list of nested lists"""
newlist = []
for line in linelist:
newlist.append(self.reducespaces(line))
return newlist
def getlineslists(self, listnl):
new = []
for list in listnl:
new.append(' '.join(List))
return new
def list_to_flt(self, List):
convert = []
for y in List:
try:
convert.append(float(y))
except:
convert.append(y)
return convert
def nested_to_flt(self, ListNestedLists):
convert = ListNestedLists
i = 0
for x in convert:
convert[i] = self.listToFlt(x)
i = i + 1
return convert
lin = line_dp() |
# This will manage all broadcasts
class Broadcaster(object):
def __init__(self):
self.broadcasts = []
broadcaster = Broadcaster()
| class Broadcaster(object):
def __init__(self):
self.broadcasts = []
broadcaster = broadcaster() |
# Copyright (c) 2019 PaddlePaddle Authors. 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 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.
# For op in NO_FP64_CHECK_GRAD_OP_LIST, the op test requires check_grad with fp64 precision
NO_FP64_CHECK_GRAD_OP_LIST = [
'affine_grid', \
'clip', \
'conv2d', \
'conv2d_transpose', \
'conv3d', \
'conv3d_transpose', \
'conv_shift', \
'cos_sim', \
'cudnn_lstm', \
'cvm', \
'data_norm', \
'deformable_conv', \
'deformable_conv_v1', \
'deformable_psroi_pooling', \
'depthwise_conv2d', \
'depthwise_conv2d_transpose', \
'dropout', \
'fused_elemwise_activation', \
'hinge_loss', \
'huber_loss', \
'im2sequence', \
'increment', \
'l1_norm', \
'log_loss', \
'lrn', \
'margin_rank_loss', \
'match_matrix_tensor', \
'matmul', \
'max_pool2d_with_index', \
'max_pool3d_with_index', \
'minus', \
'modified_huber_loss', \
'nce', \
'pool2d', \
'pool3d', \
'prroi_pool', \
'rank_loss', \
'reduce_max', \
'reduce_min', \
'reshape2', \
'roi_perspective_transform', \
'row_conv', \
'scatter', \
'sequence_conv', \
'sequence_pool', \
'sequence_reverse', \
'sequence_slice', \
'sequence_topk_avg_pooling', \
'shuffle_channel', \
'sigmoid', \
'smooth_l1_loss', \
'softmax', \
'spectral_norm', \
'squared_l2_distance', \
'squared_l2_norm', \
'tanh', \
'mish', \
'transpose2', \
'trilinear_interp', \
'var_conv_2d', \
'warpctc'
]
NO_FP16_CHECK_GRAD_OP_LIST = [
'fused_elemwise_activation', \
'pool2d', \
'pool3d', \
'softmax',\
'conv2d_transpose'
]
| no_fp64_check_grad_op_list = ['affine_grid', 'clip', 'conv2d', 'conv2d_transpose', 'conv3d', 'conv3d_transpose', 'conv_shift', 'cos_sim', 'cudnn_lstm', 'cvm', 'data_norm', 'deformable_conv', 'deformable_conv_v1', 'deformable_psroi_pooling', 'depthwise_conv2d', 'depthwise_conv2d_transpose', 'dropout', 'fused_elemwise_activation', 'hinge_loss', 'huber_loss', 'im2sequence', 'increment', 'l1_norm', 'log_loss', 'lrn', 'margin_rank_loss', 'match_matrix_tensor', 'matmul', 'max_pool2d_with_index', 'max_pool3d_with_index', 'minus', 'modified_huber_loss', 'nce', 'pool2d', 'pool3d', 'prroi_pool', 'rank_loss', 'reduce_max', 'reduce_min', 'reshape2', 'roi_perspective_transform', 'row_conv', 'scatter', 'sequence_conv', 'sequence_pool', 'sequence_reverse', 'sequence_slice', 'sequence_topk_avg_pooling', 'shuffle_channel', 'sigmoid', 'smooth_l1_loss', 'softmax', 'spectral_norm', 'squared_l2_distance', 'squared_l2_norm', 'tanh', 'mish', 'transpose2', 'trilinear_interp', 'var_conv_2d', 'warpctc']
no_fp16_check_grad_op_list = ['fused_elemwise_activation', 'pool2d', 'pool3d', 'softmax', 'conv2d_transpose'] |
class InsertResponse:
def __init__(self, entry_id, error_msg: str):
self.entry_id = entry_id
self.error_msg = error_msg
class UpdateResponse:
def __init__(self, entry_id, error_msg: str):
self.entry_id = entry_id
self.error_msg = error_msg
| class Insertresponse:
def __init__(self, entry_id, error_msg: str):
self.entry_id = entry_id
self.error_msg = error_msg
class Updateresponse:
def __init__(self, entry_id, error_msg: str):
self.entry_id = entry_id
self.error_msg = error_msg |
def translator(en_word):
if en_word == 'dog':
print('sobaka')
elif en_word == 'kat':
print('koshka')
translator('dog')
| def translator(en_word):
if en_word == 'dog':
print('sobaka')
elif en_word == 'kat':
print('koshka')
translator('dog') |
class TestLandingPage:
def test_we_can_get_the_page(self, app):
result = app.get("/", status=200)
assert "<html" in result
| class Testlandingpage:
def test_we_can_get_the_page(self, app):
result = app.get('/', status=200)
assert '<html' in result |
local = {"latitude": 100000, "longitude": 200000}
for i in range(0,10):
print("{1} {0:>20} {latitude} {longitude}".format("100", "10",**local)) | local = {'latitude': 100000, 'longitude': 200000}
for i in range(0, 10):
print('{1} {0:>20} {latitude} {longitude}'.format('100', '10', **local)) |
#
# PySNMP MIB module CISCO-OSPF-CAPABILITY (http://pysnmp.sf.net)
# Produced by pysmi-0.0.1 from CISCO-OSPF-CAPABILITY at Fri May 8 20:20:05 2015
# On host cray platform Linux version 2.6.37.6-smp by user tt
# Using Python version 2.7.2 (default, Apr 2 2012, 20:32:47)
#
( Integer, ObjectIdentifier, OctetString, ) = mibBuilder.importSymbols("ASN1", "Integer", "ObjectIdentifier", "OctetString")
( NamedValues, ) = mibBuilder.importSymbols("ASN1-ENUMERATION", "NamedValues")
( ConstraintsUnion, SingleValueConstraint, ConstraintsIntersection, ValueSizeConstraint, ValueRangeConstraint, ) = mibBuilder.importSymbols("ASN1-REFINEMENT", "ConstraintsUnion", "SingleValueConstraint", "ConstraintsIntersection", "ValueSizeConstraint", "ValueRangeConstraint")
( ciscoAgentCapability, ) = mibBuilder.importSymbols("CISCO-SMI", "ciscoAgentCapability")
( AgentCapabilities, ) = mibBuilder.importSymbols("SNMPv2-CONF", "AgentCapabilities")
( Integer32, MibIdentifier, TimeTicks, iso, Gauge32, ModuleIdentity, Bits, Counter32, ) = mibBuilder.importSymbols("SNMPv2-SMI", "Integer32", "MibIdentifier", "TimeTicks", "iso", "Gauge32", "ModuleIdentity", "Bits", "Counter32")
ciscoOspfCapability = ModuleIdentity(ciscoAgentCapability.getName() + (287,)).setRevisions(("2002-11-26 00:00",))
ciscoOspfCapabilityV12R025S = AgentCapabilities(ciscoOspfCapability.getName() + (1,))
mibBuilder.exportSymbols("CISCO-OSPF-CAPABILITY", ciscoOspfCapability=ciscoOspfCapability, ciscoOspfCapabilityV12R025S=ciscoOspfCapabilityV12R025S, PYSNMP_MODULE_ID=ciscoOspfCapability)
| (integer, object_identifier, octet_string) = mibBuilder.importSymbols('ASN1', 'Integer', 'ObjectIdentifier', 'OctetString')
(named_values,) = mibBuilder.importSymbols('ASN1-ENUMERATION', 'NamedValues')
(constraints_union, single_value_constraint, constraints_intersection, value_size_constraint, value_range_constraint) = mibBuilder.importSymbols('ASN1-REFINEMENT', 'ConstraintsUnion', 'SingleValueConstraint', 'ConstraintsIntersection', 'ValueSizeConstraint', 'ValueRangeConstraint')
(cisco_agent_capability,) = mibBuilder.importSymbols('CISCO-SMI', 'ciscoAgentCapability')
(agent_capabilities,) = mibBuilder.importSymbols('SNMPv2-CONF', 'AgentCapabilities')
(integer32, mib_identifier, time_ticks, iso, gauge32, module_identity, bits, counter32) = mibBuilder.importSymbols('SNMPv2-SMI', 'Integer32', 'MibIdentifier', 'TimeTicks', 'iso', 'Gauge32', 'ModuleIdentity', 'Bits', 'Counter32')
cisco_ospf_capability = module_identity(ciscoAgentCapability.getName() + (287,)).setRevisions(('2002-11-26 00:00',))
cisco_ospf_capability_v12_r025_s = agent_capabilities(ciscoOspfCapability.getName() + (1,))
mibBuilder.exportSymbols('CISCO-OSPF-CAPABILITY', ciscoOspfCapability=ciscoOspfCapability, ciscoOspfCapabilityV12R025S=ciscoOspfCapabilityV12R025S, PYSNMP_MODULE_ID=ciscoOspfCapability) |
class Mover(object):
def __init__(self):
self.location = PVector(random(width), random(height))
self.velocity = PVector(random(-5, 5), random(-5, 5))
self.r = 15
def update(self):
self.location.add(self.velocity)
def display(self):
stroke(0)
fill(255, 100, 255)
ellipse(self.location.x, self.location.y, 2*self.r, 2*self.r)
def checkBoundaries(self):
if (self.location.x > width + self.r):
self.location.x = -self.r
elif (self.location.x < -self.r):
self.location.x = width + self.r
if (self.location.y > height + self.r):
self.location.y = -self.r
elif (self.location.y < -self.r):
self.location.y = height + self.r
| class Mover(object):
def __init__(self):
self.location = p_vector(random(width), random(height))
self.velocity = p_vector(random(-5, 5), random(-5, 5))
self.r = 15
def update(self):
self.location.add(self.velocity)
def display(self):
stroke(0)
fill(255, 100, 255)
ellipse(self.location.x, self.location.y, 2 * self.r, 2 * self.r)
def check_boundaries(self):
if self.location.x > width + self.r:
self.location.x = -self.r
elif self.location.x < -self.r:
self.location.x = width + self.r
if self.location.y > height + self.r:
self.location.y = -self.r
elif self.location.y < -self.r:
self.location.y = height + self.r |
fname = input("Enter file name: ")
fh = open(fname)
content = fh.read()
print(content.upper().rstrip())
| fname = input('Enter file name: ')
fh = open(fname)
content = fh.read()
print(content.upper().rstrip()) |
def count_unlocked_achievements(achievements: list) -> int:
# Set counter for unlocker achievements 'unlocked' to 0
unlocked = 0
# count achievements stored in "achieved" within achievements array
for x in achievements:
if x["achieved"] == 1:
unlocked = unlocked + 1
return unlocked
def list_unlocked_achievements(achievements: list) -> list:
unlocked_achievements = []
for x in achievements:
if x["achieved"] == 1:
unlocked_achievements.append(x)
return unlocked_achievements
| def count_unlocked_achievements(achievements: list) -> int:
unlocked = 0
for x in achievements:
if x['achieved'] == 1:
unlocked = unlocked + 1
return unlocked
def list_unlocked_achievements(achievements: list) -> list:
unlocked_achievements = []
for x in achievements:
if x['achieved'] == 1:
unlocked_achievements.append(x)
return unlocked_achievements |
# Decorator to check params of BraidWord
def checkparams_braidword(func: 'func') -> 'func':
def wrapper(*args, **kwargs):
if len(args) > 1: # args will have self since for class
initword = args[1]
# Check if type is not list
if not isinstance(initword, list):
msg = "BraidWord initword argument must be a list."
raise TypeError(msg)
# Check if any generators are zero
elif 0 in initword:
msg = ('Braid generators are indexed starting at one. '
'No zero braid generators allowed.')
raise ValueError(msg)
else:
return func(*args, **kwargs)
else:
initword = kwargs[list(kwargs.keys())[0]]
# Check if type is not list
if not isinstance(initword, list):
msg = "initword argument must be a list."
raise TypeError(msg)
# Check if any generators are zero
elif 0 in initword:
msg = ('Braid generators are indexed starting at one. '
'No zero braid generators allowed.')
raise ValueError(msg)
else:
return func(*args, **kwargs)
return wrapper
| def checkparams_braidword(func: 'func') -> 'func':
def wrapper(*args, **kwargs):
if len(args) > 1:
initword = args[1]
if not isinstance(initword, list):
msg = 'BraidWord initword argument must be a list.'
raise type_error(msg)
elif 0 in initword:
msg = 'Braid generators are indexed starting at one. No zero braid generators allowed.'
raise value_error(msg)
else:
return func(*args, **kwargs)
else:
initword = kwargs[list(kwargs.keys())[0]]
if not isinstance(initword, list):
msg = 'initword argument must be a list.'
raise type_error(msg)
elif 0 in initword:
msg = 'Braid generators are indexed starting at one. No zero braid generators allowed.'
raise value_error(msg)
else:
return func(*args, **kwargs)
return wrapper |
class Nameservice:
def __init__(self, name):
self.name = name
self.namenodes = []
self.journalnodes = []
self.resourcemanagers = []
# self.zookeepers = []
self.hostnames = {}
self.HAenable = False
def __repr__(self):
return str(self)
def __str__(self):
return "<name: %s, namenodes: %s>" % (self.name, self.namenodes)
def addNode(self, type, node):
if type == "namenode":
self.namenodes.append(node)
elif type == "journalnode":
self.journalnodes.append(node)
elif type == "resourcemanager":
self.resourcemanagers.append(node)
# elif type == "zookeeper":
# self.zookeepers.append(node)
def getNamenodesID(self):
str = ""
for namenode in self.namenodes[:-1]:
str += namenode.id + ","
else:
str += self.namenodes[-1].id
return str
def getJournalnodesHost(self):
str = "qjournal://"
for journalnode in self.journalnodes[:-1]:
str += journalnode.hostname + ":8485;"
else:
str += self.journalnodes[-1].hostname + ":8485/" + self.name
return str
# def getZookeepersHost(self):
# str = ""
# for zookeeper in self.zookeepers[:-1]:
# str += zookeeper.hostname + ":2181,"
# else:
# str += self.zookeepers[-1].hostname + ":2181"
# return str
def setHostnames(self):
for namenode in self.namenodes:
if namenode.ip in self.hostnames:
self.hostnames[namenode.ip].append(namenode.hostname)
else:
self.hostnames[namenode.ip] = []
self.hostnames[namenode.ip].append(namenode.hostname)
for journalnode in self.journalnodes:
if journalnode.ip in self.hostnames:
self.hostnames[journalnode.ip].append(journalnode.hostname)
else:
self.hostnames[journalnode.ip] = []
self.hostnames[journalnode.ip].append(journalnode.hostname)
# for zookeeper in self.zookeepers:
# if zookeeper.ip in self.hostnames:
# self.hostnames[zookeeper.ip].append(zookeeper.hostname)
# else:
# self.hostnames[zookeeper.ip] = []
# self.hostnames[zookeeper.ip].append(zookeeper.hostname)
for resourcemanager in self.resourcemanagers:
if resourcemanager.ip in self.hostnames:
self.hostnames[resourcemanager.ip].append(resourcemanager.hostname)
else:
self.hostnames[resourcemanager.ip] = []
self.hostnames[resourcemanager.ip].append(resourcemanager.hostname)
def setHAenable(self):
if len(self.namenodes) == 0:
raise Exception("The number of namenodes in one cluster is 0!")
elif len(self.namenodes) == 1:
self.HAenable = False
elif len(self.namenodes) == 2:
self.HAenable = True
elif len(self.namenodes) > 3:
raise Exception("The number of namenodes in one cluster is more 2!")
def validate(self):
self.illegal = False
all = self.namenodes + self.journalnodes + self.resourcemanagers
self.illegal = reduce(lambda x, y : x and y, map(lambda x : x.illegal, all), True)
if self.HAenable and (len(self.journalnodes) == 0):
self.illegal = False
elif not self.HAenable and (len(self.journalnodes) > 0):
self.illegal = False
if self.illegal == False:
raise Exception('''ConfigureError: Your configuration is illegal. NOTE: If HA is enable ''' +
'''(contains Two namenode in a nameservice), your have to provide ZK and journalnode.''')
# if __name__ == "__main__":
# from node import *
# test = Nameservice("test")
# test.addNode("namenode", Node(1, "192.168.1.31", 1, "namenode"))
# test.addNode("namenode", Node(1, "192.168.1.31", 1, "namenode"))
# test.addNode("journalnode", Node(1, "192.168.1.31", 1, "journalnode"))
# # test.addNode("zookeeper", Node(1, "192.168.1.31", 1, "zookeeper"))
# test.setHAenable()
# test.validate()
# print 1 + 2
# print test.HAenable
# print test.illegal
| class Nameservice:
def __init__(self, name):
self.name = name
self.namenodes = []
self.journalnodes = []
self.resourcemanagers = []
self.hostnames = {}
self.HAenable = False
def __repr__(self):
return str(self)
def __str__(self):
return '<name: %s, namenodes: %s>' % (self.name, self.namenodes)
def add_node(self, type, node):
if type == 'namenode':
self.namenodes.append(node)
elif type == 'journalnode':
self.journalnodes.append(node)
elif type == 'resourcemanager':
self.resourcemanagers.append(node)
def get_namenodes_id(self):
str = ''
for namenode in self.namenodes[:-1]:
str += namenode.id + ','
else:
str += self.namenodes[-1].id
return str
def get_journalnodes_host(self):
str = 'qjournal://'
for journalnode in self.journalnodes[:-1]:
str += journalnode.hostname + ':8485;'
else:
str += self.journalnodes[-1].hostname + ':8485/' + self.name
return str
def set_hostnames(self):
for namenode in self.namenodes:
if namenode.ip in self.hostnames:
self.hostnames[namenode.ip].append(namenode.hostname)
else:
self.hostnames[namenode.ip] = []
self.hostnames[namenode.ip].append(namenode.hostname)
for journalnode in self.journalnodes:
if journalnode.ip in self.hostnames:
self.hostnames[journalnode.ip].append(journalnode.hostname)
else:
self.hostnames[journalnode.ip] = []
self.hostnames[journalnode.ip].append(journalnode.hostname)
for resourcemanager in self.resourcemanagers:
if resourcemanager.ip in self.hostnames:
self.hostnames[resourcemanager.ip].append(resourcemanager.hostname)
else:
self.hostnames[resourcemanager.ip] = []
self.hostnames[resourcemanager.ip].append(resourcemanager.hostname)
def set_h_aenable(self):
if len(self.namenodes) == 0:
raise exception('The number of namenodes in one cluster is 0!')
elif len(self.namenodes) == 1:
self.HAenable = False
elif len(self.namenodes) == 2:
self.HAenable = True
elif len(self.namenodes) > 3:
raise exception('The number of namenodes in one cluster is more 2!')
def validate(self):
self.illegal = False
all = self.namenodes + self.journalnodes + self.resourcemanagers
self.illegal = reduce(lambda x, y: x and y, map(lambda x: x.illegal, all), True)
if self.HAenable and len(self.journalnodes) == 0:
self.illegal = False
elif not self.HAenable and len(self.journalnodes) > 0:
self.illegal = False
if self.illegal == False:
raise exception('ConfigureError: Your configuration is illegal. NOTE: If HA is enable ' + '(contains Two namenode in a nameservice), your have to provide ZK and journalnode.') |
###############################
##MUST CHANGE THIS VARIABLE##
#############################################################################################
## small format = sf large format = wf engraving = en uv printing = uv ####
## envelope = env dyesub = ds vinyl = vin digital = dig ####
## inventory = inven outsourced = out ####
#############################################################################################
type = 'sf' ##<-- change this##
##########################
#####OTHER VARIABLES######
##give the ink item the current value of "Is your project Color or Black & White?"
i = lookup('is_your_prack__white4030')
env['ink'] = i
paper = lookup('what_kind_d_you_like3565')
##global variables
pc_array = {
#LETTER
'ltr':{
'color':{
4000:{'desc':'T1.5','pc':'1044','price':0.056},
2000:{'desc':'T1.4','pc':'1043','price':0.060},
1000:{'desc':'T1.3','pc':'1042','price':0.070},
500: {'desc':'T1.2','pc':'1041','price':0.080},
0: {'desc':'T1.1','pc':'1040','price':0.120}
},
'bw':{
2000:{'desc':'T2.4','pc':'1075','price':0.060},
1000:{'desc':'T2.3','pc':'1074','price':0.070},
500 :{'desc':'T2.2','pc':'1073','price':0.080},
0: {'desc':'T2.1','pc':'1072','price':0.120}
},
'none':{
0: {'desc':'catchall','pc':'','price':0.2}
}
},
#LEGAL
'lgl':{
'color':{
4000:{'desc':'T3.5','pc':'1052','price':0.065},
2000:{'desc':'T3.4','pc':'1051','price':0.070},
1000:{'desc':'T3.3','pc':'1050','price':0.080},
500: {'desc':'T3.2','pc':'1049','price':0.090},
0: {'desc':'T3.1','pc':'1048','price':0.130}
},
'bw':{
2000:{'desc':'T4.4','pc':'1075','price':0.010},
1000:{'desc':'T4.3','pc':'1074','price':0.015},
500 :{'desc':'T4.2','pc':'1073','price':0.020},
0: {'desc':'T4.1','pc':'1072','price':0.030}
},
'none':{
0: {'desc':'catchall','pc':'','price':0.2}
}
},
#TABLOID
'tab':{
'color':{
4000:{'desc':'T5.5','pc':'1060','price':0.075},
2000:{'desc':'T5.4','pc':'1059','price':0.080},
1000:{'desc':'T5.3','pc':'1058','price':0.090},
500: {'desc':'T5.2','pc':'1057','price':0.100},
0: {'desc':'T5.1','pc':'1056','price':0.140}
},
'bw':{
2000:{'desc':'T6.4','pc':'1091','price':0.010},
1000:{'desc':'T6.3','pc':'1090','price':0.015},
500 :{'desc':'T6.2','pc':'1089','price':0.020},
0: {'desc':'T6.1','pc':'1088','price':0.040}
},
'none':{
0: {'desc':'catchall','pc':'','price':0.2}
}
},
#12x18 or 13x19
'ex':{
'color':{
4000:{'desc':'T7.5','pc':'1068','price':0.075},
2000:{'desc':'T7.4','pc':'1067','price':0.080},
1000:{'desc':'T7.3','pc':'1066','price':0.090},
500: {'desc':'T7.2','pc':'1065','price':0.100},
0: {'desc':'T7.1','pc':'1064','price':0.140}
},
'bw':{
2000:{'desc':'T8.4','pc':'1099','price':0.010},
1000:{'desc':'T8.3','pc':'1098','price':0.020},
500 :{'desc':'T8.2','pc':'1097','price':0.030},
0: {'desc':'T8.1','pc':'1096','price':0.050}
},
'none':{
0: {'desc':'catchall','pc':'','price':0.2}
}
},
#WIDE FORMAT
'wf':{
'color':{
2: {'desc':'T9.2','pc':'1031','price':0.350},
1: {'desc':'T9.1','pc':'1030','price':0.700}
},
'bw':{
2 :{'desc':'T10.2','pc':'1021','price':0.130},
1: {'desc':'T10.1','pc':'1020','price':0.130}
},
'none':{
0: {'desc':'catchall','pc':'','price':0.2}
}
},
#UV
'uv':{
'color':{
2: {'desc':'T11.2','pc':'4401','price':0.200},
1: {'desc':'T11.1','pc':'4400','price':0.100}
},
'none':{
0: {'desc':'catchall','pc':'','price':0.2}
}
},
#DYE SUB
'ds':{
'color':{
3: {'desc':'T12.3','pc':'4902','price':1.000},
2: {'desc':'T12.2','pc':'4901','price':0.750},
1: {'desc':'T12.1','pc':'4900','price':0.500}
},
'none':{
0: {'desc':'catchall','pc':'','price':0.2}
}
},
#ENVELOPES
'env':{
'color':{
2: {'desc':'T13.2','pc':'4024','price':0.033},
1: {'desc':'T13.1','pc':'4016','price':0.055}
},
'bw':{
2 :{'desc':'T13.2','pc':'4018','price':0.019},
1: {'desc':'T13.1','pc':'4017','price':0.030}
},
'none':{
0: {'desc':'catchall','pc':'','price':0.2}
}
}
}
clicks = 0
cost = 0
descript = ''
sides = lookup('ink')
num_pages = float(pretty(lookup('num_pages')))
# modulus (%) is used to find if there's a blank page in the file by finding out if it's an odd number of pages), and to remove that from the click count
if sides == "4/4":
if num_pages%2 != 0:
clicks = float(press_sheets()*2-qty)
cb = "color"
else:
clicks = float(press_sheets()*2)
cb = "color"
elif sides == "1/1":
if num_pages%2 != 0:
clicks = float(press_sheets()*2-qty)
cb = "bw"
else:
clicks = float(press_sheets()*2)
cb = "bw"
elif sides == "4/0":
clicks = float(press_sheets())
cb = "color"
elif sides == "1/0":
clicks = float(press_sheets())
cb = "bw"
elif sides == '0/0':
clicks = float(press_sheets())
cb = "none"
paper_size_x = env['snap']['paper']['what_kind_d_you_like3565']['width_inches']
paper_size_y = env['snap']['paper']['what_kind_d_you_like3565']['height_inches']
xp = paper_size_x
yp = paper_size_y
print_size = lookup('size')
px = size_left(print_size)
py = size_right(print_size)
##########################
## Small Format OPTIONS ##
if type == 'sf':
##Find pricing teir for arrays
if cb == 'color':
if clicks >= 4000:
active_teir = 4000
elif clicks >= 2000:
active_teir = 2000
elif clicks >= 1000:
active_teir = 1000
elif clicks >= 500:
active_teir = 500
else:
active_teir = 0
elif cb == 'bw':
if clicks >= 2000:
active_teir = 2000
elif clicks >= 1000:
active_teir = 1000
elif clicks >= 500:
active_teir = 500
else:
active_teir = 0
elif cb == 'none':
active_teir = 0
##BUILD COST AND DESCRIPTION
if xp == 8.5 and yp == 11 or xp == 11 and yp == 8.5:
descript = pc_array['ltr'][cb][active_teir]['desc']
prod = pc_array['ltr'][cb][active_teir]['pc']
cost = pc_array['ltr'][cb][active_teir]['price']
elif xp == 8.5 and yp == 14 or xp == 14 and yp == 8.5:
descript = pc_array['lgl'][cb][active_teir]['desc']
prod = pc_array['lgl'][cb][active_teir]['pc']
cost = pc_array['lgl'][cb][active_teir]['price']
elif xp == 11 and yp == 17 or xp == 17 and yp == 11:
descript = pc_array['tab'][cb][active_teir]['desc']
prod = pc_array['tab'][cb][active_teir]['pc']
cost = pc_array['tab'][cb][active_teir]['price']
elif xp == 12 and yp == 18 or xp == 18 and yp == 12 or xp == 13 and yp == 19 or xp == 19 and yp == 13:
descript = pc_array['ex'][cb][active_teir]['desc']
prod = pc_array['ex'][cb][active_teir]['pc']
cost = pc_array['ex'][cb][active_teir]['price']
elif xp > 13 and yp > 19 or xp > 19 and yp > 13:
if qty > 1:
sqft = ((px * py) / 144) * num_pages
first_set = sqft * pc_array[type][cb][1]['price']
consec_set = ((qty - 1) * sqft) * pc_array[type][cb][2]['price']
cost = first_set + consec_set
prod = pc_array[type][cb][2]['pc']
descript = pc_array[type][cb][2]['desc'] + str(' sqft:' + sqft)
elif qty == 1:
sqft = ((px * py) / 144) * num_pages
cost = sqft * pc_array[type][cb][1]['price']
prod = pc_array[type][cb][1]['pc']
descript = pc_array[type][cb][1]['desc'] + str(' sqft:' + sqft)
else:
cost = 0
prod = '999'
descript = "n/a"
#########################
## Wide Format OPTIONS ##
elif type == "wf":
if qty > 1:
sqft = ((px * py) / 144) * num_pages
first_set = sqft * pc_array[type][cb][1]['price']
consec_set = ((qty - 1) * sqft) * pc_array[type][cb][2]['price']
cost = first_set + consec_set
prod = pc_array[type][cb][2]['pc']
descript = pc_array[type][cb][2]['desc'] + str(' sqft:' + sqft)
elif qty == 1:
sqft = ((px * py) / 144) * num_pages
cost = sqft * pc_array[type][cb][1]['price']
prod = pc_array[type][cb][1]['pc']
descript = pc_array[type][cb][1]['desc'] + str(' sqft:' + sqft)
else:
cost = 0
prod = '999'
descript = "n/a"
################
## UV OPTIONS ##
elif type == "uv":
if int(paper) >= 4200 and int(paper) <= 4225:
if qty > 1:
sqin = ((px * py) * num_pages)*qty
cost = qty * -0.50
prod = pc_array[type][cb][1]['pc']
descript = pc_array[type][cb][1]['desc'] + str(' sqin:' + sqin)
else:
sqin = ((px * py) * num_pages)*qty
cost = 0
prod = pc_array[type][cb][1]['pc']
descript = pc_array[type][cb][1]['desc'] + str(' sqin:' + sqin)
else:
sqin = ((px * py) * num_pages)*qty
cost = sqin * pc_array[type][cb][1]['price']
prod = pc_array[type][cb][1]['pc']
descript = pc_array[type][cb][1]['desc'] + str(' sqin:' + sqin)
######################
## Envelope OPTIONS ##
elif type == "env":
if qty > 500:
cost = qty * pc_array[type][cb][2]['price']
prod = pc_array[type][cb][2]['pc']
descript = pc_array[type][cb][2]['desc']
else:
cost = qty * pc_array[type][cb][1]['price']
prod = pc_array[type][cb][1]['pc']
descript = pc_array[type][cb][1]['desc']
####################
## DyeSub OPTIONS ##
elif type == "ds":
sqft = (((px * py) / 144) * num_pages)*qty
if sqft < 216:
cost = sqft * pc_array[type][cb][1]['price']
prod = pc_array[type][cb][1]['pc']
descript = pc_array[type][cb][1]['desc'] + str(" sqft:" + sqft)
elif sqft < 144:
cost = sqft * pc_array[type][cb][2]['price']
prod = pc_array[type][cb][2]['pc']
descript = pc_array[type][cb][2]['desc'] + str(" sqft:" + sqft)
elif sqft < 72:
cost = sqft * pc_array[type][cb][3]['price']
prod = pc_array[type][cb][3]['pc']
descript = pc_array[type][cb][3]['desc'] + str(" sqft:" + sqft)
else:
cost = 0
prod = '999'
descript = str('none ') + str(" sqft:" + sqft)
######################################
##FINAL PRINT OF DESCRIPTION AND PRICE
##THIS WORKS FOR EVERY PRODUCT TYPE ABOVE
desc = descript + str(' ') + prod
price = clicks * cost
| type = 'sf'
i = lookup('is_your_prack__white4030')
env['ink'] = i
paper = lookup('what_kind_d_you_like3565')
pc_array = {'ltr': {'color': {4000: {'desc': 'T1.5', 'pc': '1044', 'price': 0.056}, 2000: {'desc': 'T1.4', 'pc': '1043', 'price': 0.06}, 1000: {'desc': 'T1.3', 'pc': '1042', 'price': 0.07}, 500: {'desc': 'T1.2', 'pc': '1041', 'price': 0.08}, 0: {'desc': 'T1.1', 'pc': '1040', 'price': 0.12}}, 'bw': {2000: {'desc': 'T2.4', 'pc': '1075', 'price': 0.06}, 1000: {'desc': 'T2.3', 'pc': '1074', 'price': 0.07}, 500: {'desc': 'T2.2', 'pc': '1073', 'price': 0.08}, 0: {'desc': 'T2.1', 'pc': '1072', 'price': 0.12}}, 'none': {0: {'desc': 'catchall', 'pc': '', 'price': 0.2}}}, 'lgl': {'color': {4000: {'desc': 'T3.5', 'pc': '1052', 'price': 0.065}, 2000: {'desc': 'T3.4', 'pc': '1051', 'price': 0.07}, 1000: {'desc': 'T3.3', 'pc': '1050', 'price': 0.08}, 500: {'desc': 'T3.2', 'pc': '1049', 'price': 0.09}, 0: {'desc': 'T3.1', 'pc': '1048', 'price': 0.13}}, 'bw': {2000: {'desc': 'T4.4', 'pc': '1075', 'price': 0.01}, 1000: {'desc': 'T4.3', 'pc': '1074', 'price': 0.015}, 500: {'desc': 'T4.2', 'pc': '1073', 'price': 0.02}, 0: {'desc': 'T4.1', 'pc': '1072', 'price': 0.03}}, 'none': {0: {'desc': 'catchall', 'pc': '', 'price': 0.2}}}, 'tab': {'color': {4000: {'desc': 'T5.5', 'pc': '1060', 'price': 0.075}, 2000: {'desc': 'T5.4', 'pc': '1059', 'price': 0.08}, 1000: {'desc': 'T5.3', 'pc': '1058', 'price': 0.09}, 500: {'desc': 'T5.2', 'pc': '1057', 'price': 0.1}, 0: {'desc': 'T5.1', 'pc': '1056', 'price': 0.14}}, 'bw': {2000: {'desc': 'T6.4', 'pc': '1091', 'price': 0.01}, 1000: {'desc': 'T6.3', 'pc': '1090', 'price': 0.015}, 500: {'desc': 'T6.2', 'pc': '1089', 'price': 0.02}, 0: {'desc': 'T6.1', 'pc': '1088', 'price': 0.04}}, 'none': {0: {'desc': 'catchall', 'pc': '', 'price': 0.2}}}, 'ex': {'color': {4000: {'desc': 'T7.5', 'pc': '1068', 'price': 0.075}, 2000: {'desc': 'T7.4', 'pc': '1067', 'price': 0.08}, 1000: {'desc': 'T7.3', 'pc': '1066', 'price': 0.09}, 500: {'desc': 'T7.2', 'pc': '1065', 'price': 0.1}, 0: {'desc': 'T7.1', 'pc': '1064', 'price': 0.14}}, 'bw': {2000: {'desc': 'T8.4', 'pc': '1099', 'price': 0.01}, 1000: {'desc': 'T8.3', 'pc': '1098', 'price': 0.02}, 500: {'desc': 'T8.2', 'pc': '1097', 'price': 0.03}, 0: {'desc': 'T8.1', 'pc': '1096', 'price': 0.05}}, 'none': {0: {'desc': 'catchall', 'pc': '', 'price': 0.2}}}, 'wf': {'color': {2: {'desc': 'T9.2', 'pc': '1031', 'price': 0.35}, 1: {'desc': 'T9.1', 'pc': '1030', 'price': 0.7}}, 'bw': {2: {'desc': 'T10.2', 'pc': '1021', 'price': 0.13}, 1: {'desc': 'T10.1', 'pc': '1020', 'price': 0.13}}, 'none': {0: {'desc': 'catchall', 'pc': '', 'price': 0.2}}}, 'uv': {'color': {2: {'desc': 'T11.2', 'pc': '4401', 'price': 0.2}, 1: {'desc': 'T11.1', 'pc': '4400', 'price': 0.1}}, 'none': {0: {'desc': 'catchall', 'pc': '', 'price': 0.2}}}, 'ds': {'color': {3: {'desc': 'T12.3', 'pc': '4902', 'price': 1.0}, 2: {'desc': 'T12.2', 'pc': '4901', 'price': 0.75}, 1: {'desc': 'T12.1', 'pc': '4900', 'price': 0.5}}, 'none': {0: {'desc': 'catchall', 'pc': '', 'price': 0.2}}}, 'env': {'color': {2: {'desc': 'T13.2', 'pc': '4024', 'price': 0.033}, 1: {'desc': 'T13.1', 'pc': '4016', 'price': 0.055}}, 'bw': {2: {'desc': 'T13.2', 'pc': '4018', 'price': 0.019}, 1: {'desc': 'T13.1', 'pc': '4017', 'price': 0.03}}, 'none': {0: {'desc': 'catchall', 'pc': '', 'price': 0.2}}}}
clicks = 0
cost = 0
descript = ''
sides = lookup('ink')
num_pages = float(pretty(lookup('num_pages')))
if sides == '4/4':
if num_pages % 2 != 0:
clicks = float(press_sheets() * 2 - qty)
cb = 'color'
else:
clicks = float(press_sheets() * 2)
cb = 'color'
elif sides == '1/1':
if num_pages % 2 != 0:
clicks = float(press_sheets() * 2 - qty)
cb = 'bw'
else:
clicks = float(press_sheets() * 2)
cb = 'bw'
elif sides == '4/0':
clicks = float(press_sheets())
cb = 'color'
elif sides == '1/0':
clicks = float(press_sheets())
cb = 'bw'
elif sides == '0/0':
clicks = float(press_sheets())
cb = 'none'
paper_size_x = env['snap']['paper']['what_kind_d_you_like3565']['width_inches']
paper_size_y = env['snap']['paper']['what_kind_d_you_like3565']['height_inches']
xp = paper_size_x
yp = paper_size_y
print_size = lookup('size')
px = size_left(print_size)
py = size_right(print_size)
if type == 'sf':
if cb == 'color':
if clicks >= 4000:
active_teir = 4000
elif clicks >= 2000:
active_teir = 2000
elif clicks >= 1000:
active_teir = 1000
elif clicks >= 500:
active_teir = 500
else:
active_teir = 0
elif cb == 'bw':
if clicks >= 2000:
active_teir = 2000
elif clicks >= 1000:
active_teir = 1000
elif clicks >= 500:
active_teir = 500
else:
active_teir = 0
elif cb == 'none':
active_teir = 0
if xp == 8.5 and yp == 11 or (xp == 11 and yp == 8.5):
descript = pc_array['ltr'][cb][active_teir]['desc']
prod = pc_array['ltr'][cb][active_teir]['pc']
cost = pc_array['ltr'][cb][active_teir]['price']
elif xp == 8.5 and yp == 14 or (xp == 14 and yp == 8.5):
descript = pc_array['lgl'][cb][active_teir]['desc']
prod = pc_array['lgl'][cb][active_teir]['pc']
cost = pc_array['lgl'][cb][active_teir]['price']
elif xp == 11 and yp == 17 or (xp == 17 and yp == 11):
descript = pc_array['tab'][cb][active_teir]['desc']
prod = pc_array['tab'][cb][active_teir]['pc']
cost = pc_array['tab'][cb][active_teir]['price']
elif xp == 12 and yp == 18 or (xp == 18 and yp == 12) or (xp == 13 and yp == 19) or (xp == 19 and yp == 13):
descript = pc_array['ex'][cb][active_teir]['desc']
prod = pc_array['ex'][cb][active_teir]['pc']
cost = pc_array['ex'][cb][active_teir]['price']
elif xp > 13 and yp > 19 or (xp > 19 and yp > 13):
if qty > 1:
sqft = px * py / 144 * num_pages
first_set = sqft * pc_array[type][cb][1]['price']
consec_set = (qty - 1) * sqft * pc_array[type][cb][2]['price']
cost = first_set + consec_set
prod = pc_array[type][cb][2]['pc']
descript = pc_array[type][cb][2]['desc'] + str(' sqft:' + sqft)
elif qty == 1:
sqft = px * py / 144 * num_pages
cost = sqft * pc_array[type][cb][1]['price']
prod = pc_array[type][cb][1]['pc']
descript = pc_array[type][cb][1]['desc'] + str(' sqft:' + sqft)
else:
cost = 0
prod = '999'
descript = 'n/a'
elif type == 'wf':
if qty > 1:
sqft = px * py / 144 * num_pages
first_set = sqft * pc_array[type][cb][1]['price']
consec_set = (qty - 1) * sqft * pc_array[type][cb][2]['price']
cost = first_set + consec_set
prod = pc_array[type][cb][2]['pc']
descript = pc_array[type][cb][2]['desc'] + str(' sqft:' + sqft)
elif qty == 1:
sqft = px * py / 144 * num_pages
cost = sqft * pc_array[type][cb][1]['price']
prod = pc_array[type][cb][1]['pc']
descript = pc_array[type][cb][1]['desc'] + str(' sqft:' + sqft)
else:
cost = 0
prod = '999'
descript = 'n/a'
elif type == 'uv':
if int(paper) >= 4200 and int(paper) <= 4225:
if qty > 1:
sqin = px * py * num_pages * qty
cost = qty * -0.5
prod = pc_array[type][cb][1]['pc']
descript = pc_array[type][cb][1]['desc'] + str(' sqin:' + sqin)
else:
sqin = px * py * num_pages * qty
cost = 0
prod = pc_array[type][cb][1]['pc']
descript = pc_array[type][cb][1]['desc'] + str(' sqin:' + sqin)
else:
sqin = px * py * num_pages * qty
cost = sqin * pc_array[type][cb][1]['price']
prod = pc_array[type][cb][1]['pc']
descript = pc_array[type][cb][1]['desc'] + str(' sqin:' + sqin)
elif type == 'env':
if qty > 500:
cost = qty * pc_array[type][cb][2]['price']
prod = pc_array[type][cb][2]['pc']
descript = pc_array[type][cb][2]['desc']
else:
cost = qty * pc_array[type][cb][1]['price']
prod = pc_array[type][cb][1]['pc']
descript = pc_array[type][cb][1]['desc']
elif type == 'ds':
sqft = px * py / 144 * num_pages * qty
if sqft < 216:
cost = sqft * pc_array[type][cb][1]['price']
prod = pc_array[type][cb][1]['pc']
descript = pc_array[type][cb][1]['desc'] + str(' sqft:' + sqft)
elif sqft < 144:
cost = sqft * pc_array[type][cb][2]['price']
prod = pc_array[type][cb][2]['pc']
descript = pc_array[type][cb][2]['desc'] + str(' sqft:' + sqft)
elif sqft < 72:
cost = sqft * pc_array[type][cb][3]['price']
prod = pc_array[type][cb][3]['pc']
descript = pc_array[type][cb][3]['desc'] + str(' sqft:' + sqft)
else:
cost = 0
prod = '999'
descript = str('none ') + str(' sqft:' + sqft)
desc = descript + str(' ') + prod
price = clicks * cost |
driver = webdriver.Chrome(executable_path="./chromedriver.exe")
driver.get("http://www.baidu.com")
searchInput = driver.find_element_by_id('kw')
searchInput.send_keys("helloworld")
driver.quit() | driver = webdriver.Chrome(executable_path='./chromedriver.exe')
driver.get('http://www.baidu.com')
search_input = driver.find_element_by_id('kw')
searchInput.send_keys('helloworld')
driver.quit() |
#program to add the digits of a positive integer repeatedly until the result has a single digit.
def add_digits(num):
return (num - 1) % 9 + 1 if num > 0 else 0
print(add_digits(48))
print(add_digits(59)) | def add_digits(num):
return (num - 1) % 9 + 1 if num > 0 else 0
print(add_digits(48))
print(add_digits(59)) |
class WorldInfo:
def __init__(self, arg):
self.name = arg['name']
self.info = None
self.mappings = None
self.interact = None | class Worldinfo:
def __init__(self, arg):
self.name = arg['name']
self.info = None
self.mappings = None
self.interact = None |
S = {
'b' : 'boxes?q='
}
D = {
'bI' : 'boxId',
'bN' : 'boxName',
'iMB' : 'isMasterBox',
'cI' : 'categoryId',
'cN' : 'categoryName',
'cFN' : 'categoryFriendlyName',
'sCI' : 'superCatId',
'sCN' : 'superCatName',
'sCFN' : 'superCatFriendlyName',
'cB' : 'cannotBuy',
'iNB' : 'isNewBox',
'sP' : 'sellPrice',
'cP' : 'cashPrice',
'eP' : 'exchangePrice',
'bR' : 'boxRating',
'oOS' : 'outOfStock',
'oOES' : 'outOfEcomStock'
} | s = {'b': 'boxes?q='}
d = {'bI': 'boxId', 'bN': 'boxName', 'iMB': 'isMasterBox', 'cI': 'categoryId', 'cN': 'categoryName', 'cFN': 'categoryFriendlyName', 'sCI': 'superCatId', 'sCN': 'superCatName', 'sCFN': 'superCatFriendlyName', 'cB': 'cannotBuy', 'iNB': 'isNewBox', 'sP': 'sellPrice', 'cP': 'cashPrice', 'eP': 'exchangePrice', 'bR': 'boxRating', 'oOS': 'outOfStock', 'oOES': 'outOfEcomStock'} |
{
'targets': [
{
'target_name': '<(module_name)',
'sources': [
'src/node_libcurl.cc',
'src/Easy.cc',
'src/Share.cc',
'src/Multi.cc',
'src/Curl.cc',
'src/CurlHttpPost.cc'
],
'include_dirs' : [
"<!(node -e \"require('nan')\")"
],
'conditions': [
['OS=="win"', {
'msvs_settings': {
'VCCLCompilerTool': {
# 4506 and 4838 -> about v8 inline function and narrowing
# 4996 -> Declared wrongly Nan::Callback::Call
'DisableSpecificWarnings': ['4506', '4838', '4996']
}
},
'configurations' : {
'Release': {
'msvs_settings': {
'VCCLCompilerTool': {
'ExceptionHandling': '1',
'Optimization': 2, # /O2 safe optimization
'FavorSizeOrSpeed': 1, # /Ot, favour speed over size
'InlineFunctionExpansion': 2, # /Ob2, inline anything eligible
'WholeProgramOptimization': 'true', # /GL, whole program optimization, needed for LTCG
'OmitFramePointers': 'true',
'EnableFunctionLevelLinking': 'true',
'EnableIntrinsicFunctions': 'true',
'WarnAsError': 'true'
}
}
},
'Debug': {
'msvs_settings': {
'VCCLCompilerTool': {
'WarnAsError': 'false'
}
}
}
},
'dependencies': [
'<!@(node "<(module_root_dir)/tools/retrieve-win-deps.js")'
],
'defines' : [
'CURL_STATICLIB'
]
}, { # OS != "win"
'cflags_cc' : [
'-std=c++11',
'-O2',
'-Wno-narrowing',
'<!@(node "<(module_root_dir)/tools/curl-config.js" --cflags)',
],
# enable exceptions, remove level 3 optimization
'cflags_cc!': [
'-fno-exceptions',
'-O3'
],
'xcode_settings': {
'OTHER_CPLUSPLUSFLAGS':[
'-std=c++11','-stdlib=libc++',
'<!@(node "<(module_root_dir)/tools/curl-config.js" --cflags)',
],
'OTHER_CFLAGS':[
'<!@(node "<(module_root_dir)/tools/curl-config.js" --cflags)'
],
'OTHER_LDFLAGS':[
'-Wl,-bind_at_load',
'-stdlib=libc++'
],
'GCC_ENABLE_CPP_RTTI': 'YES',
'GCC_ENABLE_CPP_EXCEPTIONS': 'YES',
'MACOSX_DEPLOYMENT_TARGET':'10.8',
'CLANG_CXX_LIBRARY': 'libc++',
'CLANG_CXX_LANGUAGE_STANDARD':'c++11',
'OTHER_LDFLAGS': ['-stdlib=libc++'],
'WARNING_CFLAGS':[
'-Wno-c++11-narrowing',
'-Wno-constant-conversion'
]
},
'include_dirs' : [
'<!@(node "<(module_root_dir)/tools/curl-config.js" --cflags | sed s/-I//g)'
],
'libraries': [
'<!@(node "<(module_root_dir)/tools/curl-config.js" --libs)'
]
}]
]
},
{
'target_name': 'action_after_build',
'type': 'none',
'dependencies': [ '<(module_name)' ],
'copies': [
{
'files': [ '<(PRODUCT_DIR)/<(module_name).node' ],
'destination': '<(module_path)'
}
]
}
]
}
| {'targets': [{'target_name': '<(module_name)', 'sources': ['src/node_libcurl.cc', 'src/Easy.cc', 'src/Share.cc', 'src/Multi.cc', 'src/Curl.cc', 'src/CurlHttpPost.cc'], 'include_dirs': ['<!(node -e "require(\'nan\')")'], 'conditions': [['OS=="win"', {'msvs_settings': {'VCCLCompilerTool': {'DisableSpecificWarnings': ['4506', '4838', '4996']}}, 'configurations': {'Release': {'msvs_settings': {'VCCLCompilerTool': {'ExceptionHandling': '1', 'Optimization': 2, 'FavorSizeOrSpeed': 1, 'InlineFunctionExpansion': 2, 'WholeProgramOptimization': 'true', 'OmitFramePointers': 'true', 'EnableFunctionLevelLinking': 'true', 'EnableIntrinsicFunctions': 'true', 'WarnAsError': 'true'}}}, 'Debug': {'msvs_settings': {'VCCLCompilerTool': {'WarnAsError': 'false'}}}}, 'dependencies': ['<!@(node "<(module_root_dir)/tools/retrieve-win-deps.js")'], 'defines': ['CURL_STATICLIB']}, {'cflags_cc': ['-std=c++11', '-O2', '-Wno-narrowing', '<!@(node "<(module_root_dir)/tools/curl-config.js" --cflags)'], 'cflags_cc!': ['-fno-exceptions', '-O3'], 'xcode_settings': {'OTHER_CPLUSPLUSFLAGS': ['-std=c++11', '-stdlib=libc++', '<!@(node "<(module_root_dir)/tools/curl-config.js" --cflags)'], 'OTHER_CFLAGS': ['<!@(node "<(module_root_dir)/tools/curl-config.js" --cflags)'], 'OTHER_LDFLAGS': ['-Wl,-bind_at_load', '-stdlib=libc++'], 'GCC_ENABLE_CPP_RTTI': 'YES', 'GCC_ENABLE_CPP_EXCEPTIONS': 'YES', 'MACOSX_DEPLOYMENT_TARGET': '10.8', 'CLANG_CXX_LIBRARY': 'libc++', 'CLANG_CXX_LANGUAGE_STANDARD': 'c++11', 'OTHER_LDFLAGS': ['-stdlib=libc++'], 'WARNING_CFLAGS': ['-Wno-c++11-narrowing', '-Wno-constant-conversion']}, 'include_dirs': ['<!@(node "<(module_root_dir)/tools/curl-config.js" --cflags | sed s/-I//g)'], 'libraries': ['<!@(node "<(module_root_dir)/tools/curl-config.js" --libs)']}]]}, {'target_name': 'action_after_build', 'type': 'none', 'dependencies': ['<(module_name)'], 'copies': [{'files': ['<(PRODUCT_DIR)/<(module_name).node'], 'destination': '<(module_path)'}]}]} |
#!/usr/bin/python
# substrings2.py
a = "I saw a wolf in the forest. A lone wolf."
print (a.index("wolf"))
print (a.rindex("wolf"))
try:
print (a.rindex("fox"))
except ValueError as e:
print ("Could not find substring")
| a = 'I saw a wolf in the forest. A lone wolf.'
print(a.index('wolf'))
print(a.rindex('wolf'))
try:
print(a.rindex('fox'))
except ValueError as e:
print('Could not find substring') |
operacao = str(input())
soma = media = contador = 0
matriz = [[], [], [], [], [], [], [], [], [], [], [], []]
for linha in range(0, 12):
for coluna in range(0, 12):
n = float(input())
matriz[linha].append(n)
for linha in range(0, 12):
for coluna in range(0, 12):
if coluna > 11 - linha:
soma += matriz[coluna][linha]
contador += 1
if operacao in "S":
print(f"{soma:.1f}")
else:
print(f"{soma / contador:.1f}")
| operacao = str(input())
soma = media = contador = 0
matriz = [[], [], [], [], [], [], [], [], [], [], [], []]
for linha in range(0, 12):
for coluna in range(0, 12):
n = float(input())
matriz[linha].append(n)
for linha in range(0, 12):
for coluna in range(0, 12):
if coluna > 11 - linha:
soma += matriz[coluna][linha]
contador += 1
if operacao in 'S':
print(f'{soma:.1f}')
else:
print(f'{soma / contador:.1f}') |
class InvalidNibbles(Exception):
pass
class InvalidNode(Exception):
pass
class ValidationError(Exception):
pass
class BadTrieProof(Exception):
pass
class NodeOverrideError(Exception):
pass
class InvalidKeyError(Exception):
pass
class SyncRequestAlreadyProcessed(Exception):
pass
| class Invalidnibbles(Exception):
pass
class Invalidnode(Exception):
pass
class Validationerror(Exception):
pass
class Badtrieproof(Exception):
pass
class Nodeoverrideerror(Exception):
pass
class Invalidkeyerror(Exception):
pass
class Syncrequestalreadyprocessed(Exception):
pass |
class fifth():
def showclass(self):
self.name="hira"
print(self.name)
class ninth(fifth):
def showclass(self):
self.name="khira"
print(self.name)
print("after reset")
super().showclass()
st1=fifth()
st2=ninth()
st2.showclass()
| class Fifth:
def showclass(self):
self.name = 'hira'
print(self.name)
class Ninth(fifth):
def showclass(self):
self.name = 'khira'
print(self.name)
print('after reset')
super().showclass()
st1 = fifth()
st2 = ninth()
st2.showclass() |
#=========================filter===========================
# def isodd(x):
# return x%2==0
# for x in filter(isodd, range(10)):
# print(x)
#===============practice================
#1. find the even number from 1 - 20 by using filter
even=[x for x in filter(lambda x: x%2==0, range(1,21))]
print (even)
#2. find the prime number from 1-100 by using filter
def isprime(x):
if x<=1:
return False
for k in range(2,x):
if x%k==0:
return False
return True
prime=list(filter(isprime, range(100)))
print(prime)
#=========================sorted===========================
# L=[5,-1,-4,0,3,1]
# L2=sorted(L)
# L3=sorted(L,reverse=True)
# L4=sorted(L,key=abs)
# print("L2: ", L2)
# print("L3: ", L3)
# print("L4: ", L4)
#===============practice================
names=['Ethan', 'Phoebe', 'David','Kyle','Emily']
names2=sorted(names)
names3=sorted(names,key=len)
print(names3) | even = [x for x in filter(lambda x: x % 2 == 0, range(1, 21))]
print(even)
def isprime(x):
if x <= 1:
return False
for k in range(2, x):
if x % k == 0:
return False
return True
prime = list(filter(isprime, range(100)))
print(prime)
names = ['Ethan', 'Phoebe', 'David', 'Kyle', 'Emily']
names2 = sorted(names)
names3 = sorted(names, key=len)
print(names3) |
def truncate_fields(obj):
for key, val in obj.iteritems():
if isinstance(val, dict):
obj[key] = truncate_fields(val)
elif isinstance(val, (list, tuple, )):
idx = -1
for subval in val:
idx += 1
obj[key][idx] = truncate_fields(subval)
elif isinstance(val, (str, unicode)) and key not in ['content', 'text']:
obj[key] = val[:225]
return obj | def truncate_fields(obj):
for (key, val) in obj.iteritems():
if isinstance(val, dict):
obj[key] = truncate_fields(val)
elif isinstance(val, (list, tuple)):
idx = -1
for subval in val:
idx += 1
obj[key][idx] = truncate_fields(subval)
elif isinstance(val, (str, unicode)) and key not in ['content', 'text']:
obj[key] = val[:225]
return obj |
class Maze:
class Node:
def __init__(self, position):
self.Position = position
self.Neighbours = [None, None, None, None]
#self.Weights = [0, 0, 0, 0]
def __init__(self, im):
width = im.width
height = im.height
data = list(im.getdata(0))
self.start = None
self.end = None
# Top row buffer
topnodes = [None] * width
count = 0
# Start row
for x in range (1, width - 1):
if data[x] > 0:
self.start = Maze.Node((0,x))
topnodes[x] = self.start
count += 1
break
for y in range (1, height - 1):
#print ("row", str(y)) # Uncomment this line to keep a track of row progress
rowoffset = y * width
rowaboveoffset = rowoffset - width
rowbelowoffset = rowoffset + width
# Initialise previous, current and next values
prv = False
cur = False
nxt = data[rowoffset + 1] > 0
leftnode = None
for x in range (1, width - 1):
# Move prev, current and next onwards. This way we read from the image once per pixel, marginal optimisation
prv = cur
cur = nxt
nxt = data[rowoffset + x + 1] > 0
n = None
if cur == False:
# ON WALL - No action
continue
if prv == True:
if nxt == True:
# PATH PATH PATH
# Create node only if paths above or below
if data[rowaboveoffset + x] > 0 or data[rowbelowoffset + x] > 0:
n = Maze.Node((y,x))
leftnode.Neighbours[1] = n
n.Neighbours[3] = leftnode
leftnode = n
else:
# PATH PATH WALL
# Create path at end of corridor
n = Maze.Node((y,x))
leftnode.Neighbours[1] = n
n.Neighbours[3] = leftnode
leftnode = None
else:
if nxt == True:
# WALL PATH PATH
# Create path at start of corridor
n = Maze.Node((y,x))
leftnode = n
else:
# WALL PATH WALL
# Create node only if in dead end
if (data[rowaboveoffset + x] == 0) or (data[rowbelowoffset + x] == 0):
#print ("Create Node in dead end")
n = Maze.Node((y,x))
# If node isn't none, we can assume we can connect N-S somewhere
if n != None:
# Clear above, connect to waiting top node
if (data[rowaboveoffset + x] > 0):
t = topnodes[x]
t.Neighbours[2] = n
n.Neighbours[0] = t
# If clear below, put this new node in the top row for the next connection
if (data[rowbelowoffset + x] > 0):
topnodes[x] = n
else:
topnodes[x] = None
count += 1
# End row
rowoffset = (height - 1) * width
for x in range (1, width - 1):
if data[rowoffset + x] > 0:
self.end = Maze.Node((height - 1,x))
t = topnodes[x]
t.Neighbours[2] = self.end
self.end.Neighbours[0] = t
count += 1
break
self.count = count
self.width = width
self.height = height
| class Maze:
class Node:
def __init__(self, position):
self.Position = position
self.Neighbours = [None, None, None, None]
def __init__(self, im):
width = im.width
height = im.height
data = list(im.getdata(0))
self.start = None
self.end = None
topnodes = [None] * width
count = 0
for x in range(1, width - 1):
if data[x] > 0:
self.start = Maze.Node((0, x))
topnodes[x] = self.start
count += 1
break
for y in range(1, height - 1):
rowoffset = y * width
rowaboveoffset = rowoffset - width
rowbelowoffset = rowoffset + width
prv = False
cur = False
nxt = data[rowoffset + 1] > 0
leftnode = None
for x in range(1, width - 1):
prv = cur
cur = nxt
nxt = data[rowoffset + x + 1] > 0
n = None
if cur == False:
continue
if prv == True:
if nxt == True:
if data[rowaboveoffset + x] > 0 or data[rowbelowoffset + x] > 0:
n = Maze.Node((y, x))
leftnode.Neighbours[1] = n
n.Neighbours[3] = leftnode
leftnode = n
else:
n = Maze.Node((y, x))
leftnode.Neighbours[1] = n
n.Neighbours[3] = leftnode
leftnode = None
elif nxt == True:
n = Maze.Node((y, x))
leftnode = n
elif data[rowaboveoffset + x] == 0 or data[rowbelowoffset + x] == 0:
n = Maze.Node((y, x))
if n != None:
if data[rowaboveoffset + x] > 0:
t = topnodes[x]
t.Neighbours[2] = n
n.Neighbours[0] = t
if data[rowbelowoffset + x] > 0:
topnodes[x] = n
else:
topnodes[x] = None
count += 1
rowoffset = (height - 1) * width
for x in range(1, width - 1):
if data[rowoffset + x] > 0:
self.end = Maze.Node((height - 1, x))
t = topnodes[x]
t.Neighbours[2] = self.end
self.end.Neighbours[0] = t
count += 1
break
self.count = count
self.width = width
self.height = height |
'''
There is an integer array nums sorted in ascending order (with distinct values).
Prior to being passed to your function, nums is rotated at an unknown pivot index k (0 <= k < nums.length) such that the resulting array is [nums[k], nums[k+1], ..., nums[n-1], nums[0], nums[1], ..., nums[k-1]] (0-indexed). For example, [0,1,2,4,5,6,7] might be rotated at pivot index 3 and become [4,5,6,7,0,1,2].
Given the array nums after the rotation and an integer target, return the index of target if it is in nums, or -1 if it is not in nums.
You must write an algorithm with O(log n) runtime complexity.
Example 1:
Input: nums = [4,5,6,7,0,1,2], target = 0
Output: 4
Example 2:
Input: nums = [4,5,6,7,0,1,2], target = 3
Output: -1
'''
def BinarySearch(nums, target):
if not nums:
return -1
n = len(nums)
l, r = 0, n-1
while l <= r:
mid = (l+r)//2
if nums[mid] == target:
return mid
elif nums[mid] < nums[r]:
if nums[mid] <= target <= nums[r]:
l = mid+1
else:
r = mid-1
else:
if nums[l] <= target < nums[mid]:
r = mid-1
else:
l = mid+1
return -1
| """
There is an integer array nums sorted in ascending order (with distinct values).
Prior to being passed to your function, nums is rotated at an unknown pivot index k (0 <= k < nums.length) such that the resulting array is [nums[k], nums[k+1], ..., nums[n-1], nums[0], nums[1], ..., nums[k-1]] (0-indexed). For example, [0,1,2,4,5,6,7] might be rotated at pivot index 3 and become [4,5,6,7,0,1,2].
Given the array nums after the rotation and an integer target, return the index of target if it is in nums, or -1 if it is not in nums.
You must write an algorithm with O(log n) runtime complexity.
Example 1:
Input: nums = [4,5,6,7,0,1,2], target = 0
Output: 4
Example 2:
Input: nums = [4,5,6,7,0,1,2], target = 3
Output: -1
"""
def binary_search(nums, target):
if not nums:
return -1
n = len(nums)
(l, r) = (0, n - 1)
while l <= r:
mid = (l + r) // 2
if nums[mid] == target:
return mid
elif nums[mid] < nums[r]:
if nums[mid] <= target <= nums[r]:
l = mid + 1
else:
r = mid - 1
elif nums[l] <= target < nums[mid]:
r = mid - 1
else:
l = mid + 1
return -1 |
def test_h1_css(self):
self.browser.get('http://localhost:8000')
h1 = self.browser.find_element_by_tag_name("h1")
print (h1.value_of_css_property("color"))
self.assertEqual(h1.value_of_css_property("color"), "rgb(255, 192, 203)") | def test_h1_css(self):
self.browser.get('http://localhost:8000')
h1 = self.browser.find_element_by_tag_name('h1')
print(h1.value_of_css_property('color'))
self.assertEqual(h1.value_of_css_property('color'), 'rgb(255, 192, 203)') |
def fibonacci(sequence_length):
"Return the Fibonacci sequence of length *sequence_length*"
sequence = [0,1]
if sequence_length < 1:
print("Fibonacci sequence only defined for length 1 or greater")
return
elif sequence_length >=3:
for i in range(2,sequence_length):
sequence=sequence+[sequence[i-1]+sequence[i-2]]
return sequence
def factorial(n):
"Return the factorial of number *n*"
num = 1
while n >= 1:
num = num * n
n = n - 1
return num
| def fibonacci(sequence_length):
"""Return the Fibonacci sequence of length *sequence_length*"""
sequence = [0, 1]
if sequence_length < 1:
print('Fibonacci sequence only defined for length 1 or greater')
return
elif sequence_length >= 3:
for i in range(2, sequence_length):
sequence = sequence + [sequence[i - 1] + sequence[i - 2]]
return sequence
def factorial(n):
"""Return the factorial of number *n*"""
num = 1
while n >= 1:
num = num * n
n = n - 1
return num |
# This file is generated by sync-deps, do not edit!
load("@bazel_tools//tools/build_defs/repo:http.bzl", "http_archive")
def default_github_callback(name, repository, commit, sha256):
repo_name = repository.split("/")[-1]
_maybe(
http_archive,
name = name,
sha256 = sha256,
strip_prefix = "%s-%s" % (repo_name, commit),
urls = ["https://github.com/%s/archive/%s.zip" % (repository, commit)],
)
def _maybe(repo_rule, name, **kwargs):
if name not in native.existing_rules():
repo_rule(name = name, **kwargs)
| load('@bazel_tools//tools/build_defs/repo:http.bzl', 'http_archive')
def default_github_callback(name, repository, commit, sha256):
repo_name = repository.split('/')[-1]
_maybe(http_archive, name=name, sha256=sha256, strip_prefix='%s-%s' % (repo_name, commit), urls=['https://github.com/%s/archive/%s.zip' % (repository, commit)])
def _maybe(repo_rule, name, **kwargs):
if name not in native.existing_rules():
repo_rule(name=name, **kwargs) |
a=input("Enter the string:")
a=list(a)
count=0
for i in a:
count+=1
print("The length is:",count)
| a = input('Enter the string:')
a = list(a)
count = 0
for i in a:
count += 1
print('The length is:', count) |
'''
Deleting specific records
By using a where() clause, you can target the delete statement to remove only certain records. For example, Jason deleted all columns from the employees table that had id 3 with the following delete statement:
delete(employees).where(employees.columns.id == 3)
Here you'll delete ALL rows which have 'M' in the sex column and 36 in the age column. We have included code at the start which computes the total number of these rows. It is important to make sure that this is the number of rows that you actually delete.
INSTRUCTIONS
0XP
INSTRUCTIONS
0XP
Build a delete statement to remove data from the census table. Save it as stmt_del.
Append a where clause to stmt_del that contains an and_ to filter for rows which have 'M' in the sex column AND 36 in the age column.
Execute the delete statement.
Hit 'Submit Answer' to print the rowcount of the results, as well as to_delete, which returns the number of rows that should be deleted. These should match and this is an important sanity check!
'''
# Build a statement to count records using the sex column for Men (M) age 36: stmt
stmt = select([func.count(census.columns.sex)]).where(
and_(census.columns.sex == 'M',
census.columns.age == 36)
)
# Execute the select statement and use the scalar() fetch method to save the record count
to_delete = connection.execute(stmt).scalar()
# Build a statement to delete records for Men (M) age 36: stmt
stmt_del = delete(census)
# Append a where clause to target man age 36
stmt_del = stmt_del.where(
and_(census.columns.sex == 'M',
census.columns.age == 36)
)
# Execute the statement: results
results = connection.execute(stmt_del)
# Print affected rowcount and to_delete record count, make sure they match
print(results.rowcount, to_delete)
| """
Deleting specific records
By using a where() clause, you can target the delete statement to remove only certain records. For example, Jason deleted all columns from the employees table that had id 3 with the following delete statement:
delete(employees).where(employees.columns.id == 3)
Here you'll delete ALL rows which have 'M' in the sex column and 36 in the age column. We have included code at the start which computes the total number of these rows. It is important to make sure that this is the number of rows that you actually delete.
INSTRUCTIONS
0XP
INSTRUCTIONS
0XP
Build a delete statement to remove data from the census table. Save it as stmt_del.
Append a where clause to stmt_del that contains an and_ to filter for rows which have 'M' in the sex column AND 36 in the age column.
Execute the delete statement.
Hit 'Submit Answer' to print the rowcount of the results, as well as to_delete, which returns the number of rows that should be deleted. These should match and this is an important sanity check!
"""
stmt = select([func.count(census.columns.sex)]).where(and_(census.columns.sex == 'M', census.columns.age == 36))
to_delete = connection.execute(stmt).scalar()
stmt_del = delete(census)
stmt_del = stmt_del.where(and_(census.columns.sex == 'M', census.columns.age == 36))
results = connection.execute(stmt_del)
print(results.rowcount, to_delete) |
#
# PySNMP MIB module TPLINK-pppoeConfig-MIB (http://snmplabs.com/pysmi)
# ASN.1 source file:///Users/davwang4/Dev/mibs.snmplabs.com/asn1/TPLINK-pppoeConfig-MIB
# Produced by pysmi-0.3.4 at Mon Apr 29 21:18:44 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)
#
OctetString, Integer, ObjectIdentifier = mibBuilder.importSymbols("ASN1", "OctetString", "Integer", "ObjectIdentifier")
NamedValues, = mibBuilder.importSymbols("ASN1-ENUMERATION", "NamedValues")
ValueRangeConstraint, ConstraintsUnion, SingleValueConstraint, ConstraintsIntersection, ValueSizeConstraint = mibBuilder.importSymbols("ASN1-REFINEMENT", "ValueRangeConstraint", "ConstraintsUnion", "SingleValueConstraint", "ConstraintsIntersection", "ValueSizeConstraint")
ifIndex, = mibBuilder.importSymbols("IF-MIB", "ifIndex")
NotificationGroup, ModuleCompliance = mibBuilder.importSymbols("SNMPv2-CONF", "NotificationGroup", "ModuleCompliance")
MibScalar, MibTable, MibTableRow, MibTableColumn, IpAddress, Unsigned32, NotificationType, ObjectIdentity, iso, MibIdentifier, Gauge32, Counter32, Bits, ModuleIdentity, Counter64, TimeTicks, Integer32 = mibBuilder.importSymbols("SNMPv2-SMI", "MibScalar", "MibTable", "MibTableRow", "MibTableColumn", "IpAddress", "Unsigned32", "NotificationType", "ObjectIdentity", "iso", "MibIdentifier", "Gauge32", "Counter32", "Bits", "ModuleIdentity", "Counter64", "TimeTicks", "Integer32")
TextualConvention, DisplayString = mibBuilder.importSymbols("SNMPv2-TC", "TextualConvention", "DisplayString")
tplinkMgmt, = mibBuilder.importSymbols("TPLINK-MIB", "tplinkMgmt")
tplinkPPPoEConfigMIB = ModuleIdentity((1, 3, 6, 1, 4, 1, 11863, 6, 57))
tplinkPPPoEConfigMIB.setRevisions(('2012-12-17 10:50',))
if mibBuilder.loadTexts: tplinkPPPoEConfigMIB.setLastUpdated('201212171050Z')
if mibBuilder.loadTexts: tplinkPPPoEConfigMIB.setOrganization('TPLINK')
tplinkPPPoEConfigMIBObjects = MibIdentifier((1, 3, 6, 1, 4, 1, 11863, 6, 57, 1))
tplinkPPPoEConfigNotifications = MibIdentifier((1, 3, 6, 1, 4, 1, 11863, 6, 57, 2))
tpPppoeIdInsertionGlobalConfig = MibIdentifier((1, 3, 6, 1, 4, 1, 11863, 6, 57, 1, 1))
tpPppoeIdInsertionGlobalEnable = MibScalar((1, 3, 6, 1, 4, 1, 11863, 6, 57, 1, 1, 1), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(0, 1))).clone(namedValues=NamedValues(("disable", 0), ("enable", 1)))).setMaxAccess("readwrite")
if mibBuilder.loadTexts: tpPppoeIdInsertionGlobalEnable.setStatus('current')
tpPppoeIdInsertionPortConfig = MibIdentifier((1, 3, 6, 1, 4, 1, 11863, 6, 57, 1, 2))
tpPppoeIdInsertionPortConfigTable = MibTable((1, 3, 6, 1, 4, 1, 11863, 6, 57, 1, 2, 1), )
if mibBuilder.loadTexts: tpPppoeIdInsertionPortConfigTable.setStatus('current')
tpPppoeIdInsertionPortConfigEntry = MibTableRow((1, 3, 6, 1, 4, 1, 11863, 6, 57, 1, 2, 1, 1), ).setIndexNames((0, "IF-MIB", "ifIndex"))
if mibBuilder.loadTexts: tpPppoeIdInsertionPortConfigEntry.setStatus('current')
tpPppoeIdInsertionPortIndex = MibTableColumn((1, 3, 6, 1, 4, 1, 11863, 6, 57, 1, 2, 1, 1, 1), DisplayString().subtype(subtypeSpec=ValueSizeConstraint(0, 16))).setMaxAccess("readonly")
if mibBuilder.loadTexts: tpPppoeIdInsertionPortIndex.setStatus('current')
tpPppoeCircuitIdPortConfigEnable = MibTableColumn((1, 3, 6, 1, 4, 1, 11863, 6, 57, 1, 2, 1, 1, 2), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(0, 1))).clone(namedValues=NamedValues(("disable", 0), ("enable", 1)))).setMaxAccess("readwrite")
if mibBuilder.loadTexts: tpPppoeCircuitIdPortConfigEnable.setStatus('current')
tpPppoeCircuitIdPortConfigIdType = MibTableColumn((1, 3, 6, 1, 4, 1, 11863, 6, 57, 1, 2, 1, 1, 3), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(0, 1, 2, 3))).clone(namedValues=NamedValues(("switchIp", 0), ("switchMac", 1), ("switchUdf", 2), ("switchUdfOnly", 3)))).setMaxAccess("readwrite")
if mibBuilder.loadTexts: tpPppoeCircuitIdPortConfigIdType.setStatus('current')
tpPppoeCircuitIdPortConfigUdfValue = MibTableColumn((1, 3, 6, 1, 4, 1, 11863, 6, 57, 1, 2, 1, 1, 4), OctetString().subtype(subtypeSpec=ValueSizeConstraint(0, 40))).setMaxAccess("readcreate")
if mibBuilder.loadTexts: tpPppoeCircuitIdPortConfigUdfValue.setStatus('current')
tpPppoeRemoteIdPortConfigEnable = MibTableColumn((1, 3, 6, 1, 4, 1, 11863, 6, 57, 1, 2, 1, 1, 5), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(0, 1))).clone(namedValues=NamedValues(("disable", 0), ("enable", 1)))).setMaxAccess("readwrite")
if mibBuilder.loadTexts: tpPppoeRemoteIdPortConfigEnable.setStatus('current')
tpPppoeRemoteIdPortConfigValue = MibTableColumn((1, 3, 6, 1, 4, 1, 11863, 6, 57, 1, 2, 1, 1, 6), OctetString().subtype(subtypeSpec=ValueSizeConstraint(0, 40))).setMaxAccess("readcreate")
if mibBuilder.loadTexts: tpPppoeRemoteIdPortConfigValue.setStatus('current')
mibBuilder.exportSymbols("TPLINK-pppoeConfig-MIB", tpPppoeIdInsertionGlobalEnable=tpPppoeIdInsertionGlobalEnable, tpPppoeRemoteIdPortConfigValue=tpPppoeRemoteIdPortConfigValue, tpPppoeRemoteIdPortConfigEnable=tpPppoeRemoteIdPortConfigEnable, PYSNMP_MODULE_ID=tplinkPPPoEConfigMIB, tpPppoeCircuitIdPortConfigUdfValue=tpPppoeCircuitIdPortConfigUdfValue, tpPppoeIdInsertionPortConfig=tpPppoeIdInsertionPortConfig, tpPppoeCircuitIdPortConfigEnable=tpPppoeCircuitIdPortConfigEnable, tpPppoeCircuitIdPortConfigIdType=tpPppoeCircuitIdPortConfigIdType, tpPppoeIdInsertionPortIndex=tpPppoeIdInsertionPortIndex, tpPppoeIdInsertionPortConfigTable=tpPppoeIdInsertionPortConfigTable, tplinkPPPoEConfigNotifications=tplinkPPPoEConfigNotifications, tplinkPPPoEConfigMIBObjects=tplinkPPPoEConfigMIBObjects, tpPppoeIdInsertionPortConfigEntry=tpPppoeIdInsertionPortConfigEntry, tplinkPPPoEConfigMIB=tplinkPPPoEConfigMIB, tpPppoeIdInsertionGlobalConfig=tpPppoeIdInsertionGlobalConfig)
| (octet_string, integer, object_identifier) = mibBuilder.importSymbols('ASN1', 'OctetString', 'Integer', 'ObjectIdentifier')
(named_values,) = mibBuilder.importSymbols('ASN1-ENUMERATION', 'NamedValues')
(value_range_constraint, constraints_union, single_value_constraint, constraints_intersection, value_size_constraint) = mibBuilder.importSymbols('ASN1-REFINEMENT', 'ValueRangeConstraint', 'ConstraintsUnion', 'SingleValueConstraint', 'ConstraintsIntersection', 'ValueSizeConstraint')
(if_index,) = mibBuilder.importSymbols('IF-MIB', 'ifIndex')
(notification_group, module_compliance) = mibBuilder.importSymbols('SNMPv2-CONF', 'NotificationGroup', 'ModuleCompliance')
(mib_scalar, mib_table, mib_table_row, mib_table_column, ip_address, unsigned32, notification_type, object_identity, iso, mib_identifier, gauge32, counter32, bits, module_identity, counter64, time_ticks, integer32) = mibBuilder.importSymbols('SNMPv2-SMI', 'MibScalar', 'MibTable', 'MibTableRow', 'MibTableColumn', 'IpAddress', 'Unsigned32', 'NotificationType', 'ObjectIdentity', 'iso', 'MibIdentifier', 'Gauge32', 'Counter32', 'Bits', 'ModuleIdentity', 'Counter64', 'TimeTicks', 'Integer32')
(textual_convention, display_string) = mibBuilder.importSymbols('SNMPv2-TC', 'TextualConvention', 'DisplayString')
(tplink_mgmt,) = mibBuilder.importSymbols('TPLINK-MIB', 'tplinkMgmt')
tplink_pp_po_e_config_mib = module_identity((1, 3, 6, 1, 4, 1, 11863, 6, 57))
tplinkPPPoEConfigMIB.setRevisions(('2012-12-17 10:50',))
if mibBuilder.loadTexts:
tplinkPPPoEConfigMIB.setLastUpdated('201212171050Z')
if mibBuilder.loadTexts:
tplinkPPPoEConfigMIB.setOrganization('TPLINK')
tplink_pp_po_e_config_mib_objects = mib_identifier((1, 3, 6, 1, 4, 1, 11863, 6, 57, 1))
tplink_pp_po_e_config_notifications = mib_identifier((1, 3, 6, 1, 4, 1, 11863, 6, 57, 2))
tp_pppoe_id_insertion_global_config = mib_identifier((1, 3, 6, 1, 4, 1, 11863, 6, 57, 1, 1))
tp_pppoe_id_insertion_global_enable = mib_scalar((1, 3, 6, 1, 4, 1, 11863, 6, 57, 1, 1, 1), integer32().subtype(subtypeSpec=constraints_union(single_value_constraint(0, 1))).clone(namedValues=named_values(('disable', 0), ('enable', 1)))).setMaxAccess('readwrite')
if mibBuilder.loadTexts:
tpPppoeIdInsertionGlobalEnable.setStatus('current')
tp_pppoe_id_insertion_port_config = mib_identifier((1, 3, 6, 1, 4, 1, 11863, 6, 57, 1, 2))
tp_pppoe_id_insertion_port_config_table = mib_table((1, 3, 6, 1, 4, 1, 11863, 6, 57, 1, 2, 1))
if mibBuilder.loadTexts:
tpPppoeIdInsertionPortConfigTable.setStatus('current')
tp_pppoe_id_insertion_port_config_entry = mib_table_row((1, 3, 6, 1, 4, 1, 11863, 6, 57, 1, 2, 1, 1)).setIndexNames((0, 'IF-MIB', 'ifIndex'))
if mibBuilder.loadTexts:
tpPppoeIdInsertionPortConfigEntry.setStatus('current')
tp_pppoe_id_insertion_port_index = mib_table_column((1, 3, 6, 1, 4, 1, 11863, 6, 57, 1, 2, 1, 1, 1), display_string().subtype(subtypeSpec=value_size_constraint(0, 16))).setMaxAccess('readonly')
if mibBuilder.loadTexts:
tpPppoeIdInsertionPortIndex.setStatus('current')
tp_pppoe_circuit_id_port_config_enable = mib_table_column((1, 3, 6, 1, 4, 1, 11863, 6, 57, 1, 2, 1, 1, 2), integer32().subtype(subtypeSpec=constraints_union(single_value_constraint(0, 1))).clone(namedValues=named_values(('disable', 0), ('enable', 1)))).setMaxAccess('readwrite')
if mibBuilder.loadTexts:
tpPppoeCircuitIdPortConfigEnable.setStatus('current')
tp_pppoe_circuit_id_port_config_id_type = mib_table_column((1, 3, 6, 1, 4, 1, 11863, 6, 57, 1, 2, 1, 1, 3), integer32().subtype(subtypeSpec=constraints_union(single_value_constraint(0, 1, 2, 3))).clone(namedValues=named_values(('switchIp', 0), ('switchMac', 1), ('switchUdf', 2), ('switchUdfOnly', 3)))).setMaxAccess('readwrite')
if mibBuilder.loadTexts:
tpPppoeCircuitIdPortConfigIdType.setStatus('current')
tp_pppoe_circuit_id_port_config_udf_value = mib_table_column((1, 3, 6, 1, 4, 1, 11863, 6, 57, 1, 2, 1, 1, 4), octet_string().subtype(subtypeSpec=value_size_constraint(0, 40))).setMaxAccess('readcreate')
if mibBuilder.loadTexts:
tpPppoeCircuitIdPortConfigUdfValue.setStatus('current')
tp_pppoe_remote_id_port_config_enable = mib_table_column((1, 3, 6, 1, 4, 1, 11863, 6, 57, 1, 2, 1, 1, 5), integer32().subtype(subtypeSpec=constraints_union(single_value_constraint(0, 1))).clone(namedValues=named_values(('disable', 0), ('enable', 1)))).setMaxAccess('readwrite')
if mibBuilder.loadTexts:
tpPppoeRemoteIdPortConfigEnable.setStatus('current')
tp_pppoe_remote_id_port_config_value = mib_table_column((1, 3, 6, 1, 4, 1, 11863, 6, 57, 1, 2, 1, 1, 6), octet_string().subtype(subtypeSpec=value_size_constraint(0, 40))).setMaxAccess('readcreate')
if mibBuilder.loadTexts:
tpPppoeRemoteIdPortConfigValue.setStatus('current')
mibBuilder.exportSymbols('TPLINK-pppoeConfig-MIB', tpPppoeIdInsertionGlobalEnable=tpPppoeIdInsertionGlobalEnable, tpPppoeRemoteIdPortConfigValue=tpPppoeRemoteIdPortConfigValue, tpPppoeRemoteIdPortConfigEnable=tpPppoeRemoteIdPortConfigEnable, PYSNMP_MODULE_ID=tplinkPPPoEConfigMIB, tpPppoeCircuitIdPortConfigUdfValue=tpPppoeCircuitIdPortConfigUdfValue, tpPppoeIdInsertionPortConfig=tpPppoeIdInsertionPortConfig, tpPppoeCircuitIdPortConfigEnable=tpPppoeCircuitIdPortConfigEnable, tpPppoeCircuitIdPortConfigIdType=tpPppoeCircuitIdPortConfigIdType, tpPppoeIdInsertionPortIndex=tpPppoeIdInsertionPortIndex, tpPppoeIdInsertionPortConfigTable=tpPppoeIdInsertionPortConfigTable, tplinkPPPoEConfigNotifications=tplinkPPPoEConfigNotifications, tplinkPPPoEConfigMIBObjects=tplinkPPPoEConfigMIBObjects, tpPppoeIdInsertionPortConfigEntry=tpPppoeIdInsertionPortConfigEntry, tplinkPPPoEConfigMIB=tplinkPPPoEConfigMIB, tpPppoeIdInsertionGlobalConfig=tpPppoeIdInsertionGlobalConfig) |
#!/usr/bin/python
def log(self,string):
print(str(self.__class__.__name__)+": "+str(string))
| def log(self, string):
print(str(self.__class__.__name__) + ': ' + str(string)) |
_base_ = "./FlowNet512_1.5AugCosyAAEGray_AggressiveV2_Flat_Blender_01_ape.py"
OUTPUT_DIR = "output/deepim/lmCropBlenderSO/FlowNet512_1.5AugCosyAAEGray_AggressiveV2_Flat_lmCropBlender_SO/duck"
DATASETS = dict(TRAIN=("lm_blender_duck_train",), TEST=("lm_crop_duck_test",))
# bbnc9
# iter0
# objects duck Avg(1)
# ad_2 0.00 0.00
# ad_5 0.00 0.00
# ad_10 0.40 0.40
# rete_2 0.80 0.80
# rete_5 11.16 11.16
# rete_10 25.90 25.90
# re_2 3.59 3.59
# re_5 17.13 17.13
# re_10 32.67 32.67
# te_2 0.80 0.80
# te_5 15.54 15.54
# te_10 28.69 28.69
# proj_2 0.80 0.80
# proj_5 24.30 24.30
# proj_10 43.82 43.82
# re 39.39 39.39
# te 0.24 0.24
# iter4
# objects duck Avg(1)
# ad_2 3.19 3.19
# ad_5 13.55 13.55
# ad_10 30.28 30.28
# rete_2 20.32 20.32
# rete_5 53.78 53.78
# rete_10 65.34 65.34
# re_2 21.12 21.12
# re_5 56.18 56.18
# re_10 65.34 65.34
# te_2 52.99 52.99
# te_5 62.15 62.15
# te_10 70.92 70.92
# proj_2 49.80 49.80
# proj_5 65.34 65.34
# proj_10 71.71 71.71
# re 32.32 32.32
# te 0.10 0.10
| _base_ = './FlowNet512_1.5AugCosyAAEGray_AggressiveV2_Flat_Blender_01_ape.py'
output_dir = 'output/deepim/lmCropBlenderSO/FlowNet512_1.5AugCosyAAEGray_AggressiveV2_Flat_lmCropBlender_SO/duck'
datasets = dict(TRAIN=('lm_blender_duck_train',), TEST=('lm_crop_duck_test',)) |
infile='VisDrone2019-DET-val/val.txt'
outfile='visdrone_val.txt'
with open(outfile,'w') as w:
with open(infile,'r') as r:
filelist=r.readlines()
for line in filelist:
new_line=line.split('.')[0]
w.write(new_line+'\n')
| infile = 'VisDrone2019-DET-val/val.txt'
outfile = 'visdrone_val.txt'
with open(outfile, 'w') as w:
with open(infile, 'r') as r:
filelist = r.readlines()
for line in filelist:
new_line = line.split('.')[0]
w.write(new_line + '\n') |
class AssemblySimulatorVMConfigException(Exception):
def __str__(self):
return "[ERROR] Error: AssemblySimulatorConfigError, Response: {0}".format(super().__str__())
| class Assemblysimulatorvmconfigexception(Exception):
def __str__(self):
return '[ERROR] Error: AssemblySimulatorConfigError, Response: {0}'.format(super().__str__()) |
def write_name_delbertina(input_turtle):
# d
input_turtle.right(90)
input_turtle.forward(50)
input_turtle.left(90)
input_turtle.pendown()
input_turtle.forward(30)
input_turtle.left(90)
input_turtle.forward(50)
input_turtle.left(180)
input_turtle.forward(30)
input_turtle.right(90)
input_turtle.forward(30)
input_turtle.left(90)
input_turtle.forward(20)
input_turtle.left(90)
input_turtle.forward(30)
input_turtle.penup()
input_turtle.forward(10)
# e
input_turtle.left(90)
input_turtle.pendown()
input_turtle.forward(20)
input_turtle.right(90)
input_turtle.forward(30)
input_turtle.right(90)
input_turtle.forward(10)
input_turtle.right(90)
input_turtle.forward(30)
input_turtle.left(90)
input_turtle.forward(10)
input_turtle.left(90)
input_turtle.forward(30)
input_turtle.penup()
input_turtle.forward(10)
# l
input_turtle.pendown()
input_turtle.left(90)
input_turtle.forward(40)
input_turtle.left(180)
input_turtle.forward(40)
input_turtle.left(90)
input_turtle.forward(20)
input_turtle.penup()
input_turtle.forward(10)
# b
input_turtle.pendown()
input_turtle.left(90)
input_turtle.forward(50)
input_turtle.left(180)
input_turtle.forward(30)
input_turtle.left(90)
input_turtle.forward(30)
input_turtle.right(90)
input_turtle.forward(20)
input_turtle.right(90)
input_turtle.forward(30)
input_turtle.right(180)
input_turtle.forward(30)
input_turtle.penup()
input_turtle.forward(10)
# e
input_turtle.left(90)
input_turtle.pendown()
input_turtle.forward(20)
input_turtle.right(90)
input_turtle.forward(30)
input_turtle.right(90)
input_turtle.forward(10)
input_turtle.right(90)
input_turtle.forward(30)
input_turtle.left(90)
input_turtle.forward(10)
input_turtle.left(90)
input_turtle.forward(30)
input_turtle.penup()
input_turtle.forward(10)
# r
input_turtle.pendown()
input_turtle.left(90)
input_turtle.forward(30)
input_turtle.left(180)
input_turtle.forward(10)
input_turtle.left(90)
input_turtle.forward(20)
input_turtle.penup()
input_turtle.right(90)
input_turtle.forward(20)
input_turtle.left(90)
input_turtle.forward(10)
# t
input_turtle.pendown()
input_turtle.left(90)
input_turtle.forward(30)
input_turtle.left(180)
input_turtle.forward(10)
input_turtle.left(90)
input_turtle.forward(10)
input_turtle.left(180)
input_turtle.forward(10)
input_turtle.left(90)
input_turtle.forward(20)
input_turtle.left(90)
input_turtle.forward(20)
input_turtle.penup()
input_turtle.forward(10)
# i
input_turtle.pendown()
input_turtle.forward(10)
input_turtle.left(90)
input_turtle.forward(20)
input_turtle.penup()
input_turtle.forward(10)
input_turtle.pendown()
input_turtle.forward(10)
input_turtle.left(180)
input_turtle.penup()
input_turtle.forward(20)
input_turtle.pendown()
input_turtle.forward(20)
input_turtle.left(90)
input_turtle.forward(10)
input_turtle.penup()
input_turtle.forward(10)
# n
input_turtle.pendown()
input_turtle.left(90)
input_turtle.forward(20)
input_turtle.right(90)
input_turtle.forward(30)
input_turtle.right(90)
input_turtle.forward(20)
input_turtle.left(90)
input_turtle.penup()
input_turtle.forward(10)
# a
input_turtle.pendown()
input_turtle.left(90)
input_turtle.forward(20)
input_turtle.right(90)
input_turtle.forward(30)
input_turtle.left(90)
input_turtle.forward(10)
input_turtle.left(90)
input_turtle.forward(30)
input_turtle.left(180)
input_turtle.forward(30)
input_turtle.right(90)
input_turtle.forward(30)
input_turtle.right(90)
input_turtle.forward(30)
input_turtle.left(180)
input_turtle.forward(30)
| def write_name_delbertina(input_turtle):
input_turtle.right(90)
input_turtle.forward(50)
input_turtle.left(90)
input_turtle.pendown()
input_turtle.forward(30)
input_turtle.left(90)
input_turtle.forward(50)
input_turtle.left(180)
input_turtle.forward(30)
input_turtle.right(90)
input_turtle.forward(30)
input_turtle.left(90)
input_turtle.forward(20)
input_turtle.left(90)
input_turtle.forward(30)
input_turtle.penup()
input_turtle.forward(10)
input_turtle.left(90)
input_turtle.pendown()
input_turtle.forward(20)
input_turtle.right(90)
input_turtle.forward(30)
input_turtle.right(90)
input_turtle.forward(10)
input_turtle.right(90)
input_turtle.forward(30)
input_turtle.left(90)
input_turtle.forward(10)
input_turtle.left(90)
input_turtle.forward(30)
input_turtle.penup()
input_turtle.forward(10)
input_turtle.pendown()
input_turtle.left(90)
input_turtle.forward(40)
input_turtle.left(180)
input_turtle.forward(40)
input_turtle.left(90)
input_turtle.forward(20)
input_turtle.penup()
input_turtle.forward(10)
input_turtle.pendown()
input_turtle.left(90)
input_turtle.forward(50)
input_turtle.left(180)
input_turtle.forward(30)
input_turtle.left(90)
input_turtle.forward(30)
input_turtle.right(90)
input_turtle.forward(20)
input_turtle.right(90)
input_turtle.forward(30)
input_turtle.right(180)
input_turtle.forward(30)
input_turtle.penup()
input_turtle.forward(10)
input_turtle.left(90)
input_turtle.pendown()
input_turtle.forward(20)
input_turtle.right(90)
input_turtle.forward(30)
input_turtle.right(90)
input_turtle.forward(10)
input_turtle.right(90)
input_turtle.forward(30)
input_turtle.left(90)
input_turtle.forward(10)
input_turtle.left(90)
input_turtle.forward(30)
input_turtle.penup()
input_turtle.forward(10)
input_turtle.pendown()
input_turtle.left(90)
input_turtle.forward(30)
input_turtle.left(180)
input_turtle.forward(10)
input_turtle.left(90)
input_turtle.forward(20)
input_turtle.penup()
input_turtle.right(90)
input_turtle.forward(20)
input_turtle.left(90)
input_turtle.forward(10)
input_turtle.pendown()
input_turtle.left(90)
input_turtle.forward(30)
input_turtle.left(180)
input_turtle.forward(10)
input_turtle.left(90)
input_turtle.forward(10)
input_turtle.left(180)
input_turtle.forward(10)
input_turtle.left(90)
input_turtle.forward(20)
input_turtle.left(90)
input_turtle.forward(20)
input_turtle.penup()
input_turtle.forward(10)
input_turtle.pendown()
input_turtle.forward(10)
input_turtle.left(90)
input_turtle.forward(20)
input_turtle.penup()
input_turtle.forward(10)
input_turtle.pendown()
input_turtle.forward(10)
input_turtle.left(180)
input_turtle.penup()
input_turtle.forward(20)
input_turtle.pendown()
input_turtle.forward(20)
input_turtle.left(90)
input_turtle.forward(10)
input_turtle.penup()
input_turtle.forward(10)
input_turtle.pendown()
input_turtle.left(90)
input_turtle.forward(20)
input_turtle.right(90)
input_turtle.forward(30)
input_turtle.right(90)
input_turtle.forward(20)
input_turtle.left(90)
input_turtle.penup()
input_turtle.forward(10)
input_turtle.pendown()
input_turtle.left(90)
input_turtle.forward(20)
input_turtle.right(90)
input_turtle.forward(30)
input_turtle.left(90)
input_turtle.forward(10)
input_turtle.left(90)
input_turtle.forward(30)
input_turtle.left(180)
input_turtle.forward(30)
input_turtle.right(90)
input_turtle.forward(30)
input_turtle.right(90)
input_turtle.forward(30)
input_turtle.left(180)
input_turtle.forward(30) |
my_list=[22,333,412]
sum =0
for number in my_list:
sum += number
print(sum) | my_list = [22, 333, 412]
sum = 0
for number in my_list:
sum += number
print(sum) |
#To accept 2 integers and display the largest among them
a=int(input("Enter Number:"))
b=int(input("Enter Number:"))
if a>b:
print (a,"is greater")
elif a<b:
print (b,"is greater")
else:
print ("Both Are Same Number")
| a = int(input('Enter Number:'))
b = int(input('Enter Number:'))
if a > b:
print(a, 'is greater')
elif a < b:
print(b, 'is greater')
else:
print('Both Are Same Number') |
# == , != (Int, float, str, bool)
x,y=6,7
p=6
print(x == y) #False
print(p == x) #True
print(p == 6.0) #True
print('Hello' == 'Hello') #True
#Chaining
print(10 == 20 == 6 == 3) #False
print(1 == 1 == 1 < 2) #True
print(1 !=2 < 3 > 1) #True | (x, y) = (6, 7)
p = 6
print(x == y)
print(p == x)
print(p == 6.0)
print('Hello' == 'Hello')
print(10 == 20 == 6 == 3)
print(1 == 1 == 1 < 2)
print(1 != 2 < 3 > 1) |
bool1 = [[i*j for i in range(5)] for j in range(5)]
print(bool1)
for g in range(0,len(bool1[0])):
i = 0
for j in range(g,len(bool1[0])):
print(bool1[i][j])
i += 1 | bool1 = [[i * j for i in range(5)] for j in range(5)]
print(bool1)
for g in range(0, len(bool1[0])):
i = 0
for j in range(g, len(bool1[0])):
print(bool1[i][j])
i += 1 |
def check(expected, obtained):
try:
a = float(expected)
b = float(obtained)
except ValueError:
return False
return abs(a - b) <= 1e-3
| def check(expected, obtained):
try:
a = float(expected)
b = float(obtained)
except ValueError:
return False
return abs(a - b) <= 0.001 |
_base_ = '../yolox/yolox_l_8x8_300e_coco.py'
model = dict(
bbox_head=dict(num_classes=1)
)
dataset_type = 'BasketballDetection'
# data_root = '/mnt/nfs-storage/yujiannan/data/bas_data/train_data/'
data_root = '/home/senseport0/data/train_data/'
data = dict(
samples_per_gpu=4,
workers_per_gpu=1,
train=dict(
dataset=dict(
type=dataset_type,
ann_file=data_root + "train_21.3.10_train.json" or "train_21.8.16_train.json",
img_prefix=data_root)),
val=dict(
type=dataset_type,
img_prefix=data_root,
ann_file=data_root + "train_21.3.10_val.json" or "val_21.8.16.json"),
test=dict(
type=dataset_type,
img_prefix=data_root,
ann_file=data_root + "train_21.3.10_val.json" or "val_21.8.16.json"))
optimizer = dict(type='SGD', lr=2e-5, momentum=0.9, weight_decay=5e-4)
evaluation = dict(interval=1, metric=['mAP'])
checkpoint_config = dict(interval=1)
| _base_ = '../yolox/yolox_l_8x8_300e_coco.py'
model = dict(bbox_head=dict(num_classes=1))
dataset_type = 'BasketballDetection'
data_root = '/home/senseport0/data/train_data/'
data = dict(samples_per_gpu=4, workers_per_gpu=1, train=dict(dataset=dict(type=dataset_type, ann_file=data_root + 'train_21.3.10_train.json' or 'train_21.8.16_train.json', img_prefix=data_root)), val=dict(type=dataset_type, img_prefix=data_root, ann_file=data_root + 'train_21.3.10_val.json' or 'val_21.8.16.json'), test=dict(type=dataset_type, img_prefix=data_root, ann_file=data_root + 'train_21.3.10_val.json' or 'val_21.8.16.json'))
optimizer = dict(type='SGD', lr=2e-05, momentum=0.9, weight_decay=0.0005)
evaluation = dict(interval=1, metric=['mAP'])
checkpoint_config = dict(interval=1) |
# Python Program to print Unique Prime Factors of a Number
Number = int(input(" Please Enter any Number: "))
i = 1
my=[]
while(i <= Number):
count = 0
if(Number % i == 0):
j = 1
while(j <= i):
if(i % j == 0):
count = count + 1
j = j + 1
if (count == 2):
my.append(i)
i = i + 1
my=list(dict.fromkeys(my))
print(my)
| number = int(input(' Please Enter any Number: '))
i = 1
my = []
while i <= Number:
count = 0
if Number % i == 0:
j = 1
while j <= i:
if i % j == 0:
count = count + 1
j = j + 1
if count == 2:
my.append(i)
i = i + 1
my = list(dict.fromkeys(my))
print(my) |
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