General Information
In the following we describe this software as TDA.
XML files are the files provided by medatixx GmbH & Co. KG and each file will be parsed and displayed as one TestRun.
One TestRun consists of several UnitTests testing different classes.
TDA shall help visualize all this information and show possible correlations between different TestRuns per class.
User Manual
2.1 Load XML Files
To Load XML Files into the TDA there are two ways:
- On startup click the folder button to select a folder and parse the folder and all underlying folders in recursive strategy or click the file button to select one or more specific XML files to be parsed.
- On the Menubar click File -> Open folder or Open file
If successful, you will then see the sidebar being updated with information.
2.2 Display one TestRun in the class table
To display a testrun in the table you have to click on a testrun shown in the sidebar with the TestRun - Tab active. It will automatically sort all tested classes by this testrun by its failure percentage(fp) and highlight classes red with a fp higher than 75% and yellow with a fp higher than 50%.
2.3 Display the change of a class' failure percentage over all testruns (chart)
There are two ways to add a class to the chart:
- Open the "Classes" tab in the left sidebar. Then select a class by a single click on its name in the package view.
- Open the "Table" tab in the main window. Then select a class by a double click on its name in the table.
Both actions will show the desired chart in the "Chart" tab on the main window.
You can add several classes to the chart for comparison by following the same procedure.
The chart may be resetted by using the button "Clear Data" underneath the chart.
2.4 Compare a class in two different testruns
To compare different testruns right-click on the corresponding node on the line chart and add it to one of the comparison
slots. When both are filled you can use the "Compare" button to see directly which UnitTests failed or passed now and before.
Note: You can not compare two different classes.
2.5 Dependency analysis of failed classes
To see the dependencies between two failed classes click on the Analyzer Tab on the main window. There you will see the Strong Rule. In each row there are classes that are probably dependend with a given confidence. Use the sliders to set the minimum confidence aswell as the minimum distance of two classes.
Licence
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Source code for eLCS.ClassAccuracy
"""
Name: eLCS_ClassAccuracy.py
Authors: Ryan Urbanowicz - Written at Dartmouth College, Hanover, NH, USA
Contact<EMAIL_ADDRESS>Created: November 1, 2013
Description: Manages the logistical aspects of balance accuracy calculations which can handle unbalanced datasets, and/or datasets with multiple discrete classes.
---------------------------------------------------------------------------------------------------------------------------------------------------------
eLCS: Educational Learning Classifier System - A basic LCS coded for educational purposes. This LCS algorithm uses supervised learning, and thus is most
similar to "UCS", an LCS algorithm published by Ester Bernado-Mansilla and Josep Garrell-Guiu (2003) which in turn is based heavily on "XCS", an LCS
algorithm published by Stewart Wilson (1995).
Copyright (C) 2013 Ryan Urbanowicz
This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the
Free Software Foundation; either version 3 of the License, or (at your option) any later version.
This program is distributed in the hope that it will be useful but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABLILITY
or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation,
Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
---------------------------------------------------------------------------------------------------------------------------------------------------------
"""
[docs]class ClassAccuracy:
def __init__(self):
""" Initialize the accuracy calculation for a single class """
self.T_myClass = 0 # For binary class problems this would include true positives
self.T_otherClass = 0 # For binary class problems this would include true negatives
self.F_myClass = 0 # For binary class problems this would include false positives
self.F_otherClass = 0 # For binary class problems this would include false negatives
[docs] def updateAccuracy(self, thisIsMe, accurateClass):
""" Increment the appropriate cell of the confusion matrix """
if thisIsMe and accurateClass:
self.T_myClass += 1
elif accurateClass:
self.T_otherClass += 1
elif thisIsMe:
self.F_myClass += 1
else:
self.F_otherClass += 1
[docs] def reportClassAccuracy(self):
""" Print to standard out, summary on the class accuracy. """
print("-----------------------------------------------")
print("TP = " + str(self.T_myClass))
print("TN = " + str(self.T_otherClass))
print("FP = " + str(self.F_myClass))
print("FN = " + str(self.F_otherClass))
print("-----------------------------------------------")


Rails Engineering Timeline, with Objectives
Week 1
Git, HTML/CSS
SCSS, Bootstrap
Objectives
Demonstrate ability to use source control (git)
Demonstrate ability to take an existing design and implement in HTML
Demonstrate layout techniques (float)
Lab - Timeline HTML Lab
Week 2
Ruby Syntax, Data structure, and usage from command line
variables, instance variables, scoping, methods, etc.
Enumerable (find, select, map, reject)
Objectives
Demonstrate knowledge of scope, variables, methods, and classes
Demonstrate use of ruby-style
Demonstrate knowledge of data structures and modeling skills
Lab - CSV to HTML Report
Week 3
Advanced Ruby, Testing / TDD, Games
Modules, Inheritance, Inject, MonkeyPatching
Objectives
Demonstrate implementation of control-flow and data-flow
Demonstrate ability to create a user interface with input/output
Demonstrate use of loops as a control-flow concept
Lab - Blackjack
Week 4
Intro to Rails, Static pages and assets
Objectives
Demonstrate understanding of how dynamic pages work on the web
Demonstrate understanding of how URLs rule everything
Demonstrate understanding of the concept of MVC architecture
Demonstrate use of the Rails asset pipeline
Lab - Rails pages
Week 5
Databases, Models, Routing
Objectives
Demonstrate knowledge of data modeling into ActiveRecord style classes and tables
Demonstrate ability to publish to internet using heroku
Demonstrate flow of web data from form -> controller -> model
Demonstrate ability to have common (has_many / belongs_to) relationships
Lab - Reddit Clone
Week 6
Objectives
Demonstrate understanding of gems and their place in Rails development
Demonstrate understanding of Personalization
Demonstrate understanding of Authentication
Demonstrate understanding of Pagination
Lab - Twitter Clone
Week 7
JavaScript and React
Objectives
Demonstrate knowledge of JavaScript proficiently
Demonstrate knowledge of Rails Remote Form cycle
Lab - Pinterest Clone
Week 8
Objectives
Demonstrate knowledge of technical challenges in accepting moneys online
Demonstrate capability to integrate with external APIs
Demonstrate ability of creating full, complete projects with ability to admin data
Lab - Amazon Clone
Week 9
Objectives
Demonstrate expertise in data from forms to params (and APIs sending params)
Demonstrate knowledge of CORS and impact on JS APIs
Demonstrate ability to work as a team, with a second team of different knowledge levels
Demonstrate ability of two projects, in two repos, deployed to two different servers, to work together
Lab - Front-End Collaboration (build a CRUD API)
JS team builds a Single Page Application
Rails builds an API
They talk to each other.
It's harder than it sounds


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In this project, you'll use generative adversarial networks to generate new images of faces.
You'll be using two datasets in this project:
Since the celebA dataset is complex and you're doing GANs in a project for the first time, we want you to test your neural network on MNIST before CelebA. Running the GANs on MNIST will allow you to see how well your model trains sooner.
If you're using FloydHub, set data_dir
to "/input" and use the FloydHub data ID "R5KrjnANiKVhLWAkpXhNBe".
data_dir = './data'
# FloydHub - Use with data ID "R5KrjnANiKVhLWAkpXhNBe"
#data_dir = '/input'
"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
import helper
helper.download_extract('mnist', data_dir)
helper.download_extract('celeba', data_dir)
show_n_images = 25
"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
%matplotlib inline
import os
from glob import glob
from matplotlib import pyplot
mnist_images = helper.get_batch(glob(os.path.join(data_dir, 'mnist/*.jpg'))[:show_n_images], 28, 28, 'L')
pyplot.imshow(helper.images_square_grid(mnist_images, 'L'), cmap='gray')
The CelebFaces Attributes Dataset (CelebA) dataset contains over 200,000 celebrity images with annotations. Since you're going to be generating faces, you won't need the annotations. You can view the first number of examples by changing show_n_images
.
show_n_images = 25
"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
mnist_images = helper.get_batch(glob(os.path.join(data_dir, 'img_align_celeba/*.jpg'))[:show_n_images], 28, 28, 'RGB')
pyplot.imshow(helper.images_square_grid(mnist_images, 'RGB'))
Since the project's main focus is on building the GANs, we'll preprocess the data for you. The values of the MNIST and CelebA dataset will be in the range of -0.5 to 0.5 of 28x28 dimensional images. The CelebA images will be cropped to remove parts of the image that don't include a face, then resized down to 28x28.

You'll build the components necessary to build a GANs by implementing the following functions below:
model_inputs
discriminator
generator
model_loss
model_opt
train
This will check to make sure you have the correct version of TensorFlow and access to a GPU
"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
from distutils.version import LooseVersion
import warnings
import tensorflow as tf
# Check TensorFlow Version
assert LooseVersion(tf.__version__) >= LooseVersion('1.0'), 'Please use TensorFlow version 1.0 or newer. You are using {}'.format(tf.__version__)
print('TensorFlow Version: {}'.format(tf.__version__))
# Check for a GPU
if not tf.test.gpu_device_name():
warnings.warn('No GPU found. Please use a GPU to train your neural network.')
else:
print('Default GPU Device: {}'.format(tf.test.gpu_device_name()))
Implement the model_inputs
function to create TF Placeholders for the Neural Network. It should create the following placeholders:
image_width
, image_height
, and image_channels
.z_dim
.Return the placeholders in the following the tuple (tensor of real input images, tensor of z data)
import problem_unittests as tests
def model_inputs(image_width, image_height, image_channels, z_dim):
"""
Create the model inputs
:param image_width: The input image width
:param image_height: The input image height
:param image_channels: The number of image channels
:param z_dim: The dimension of Z
:return: Tuple of (tensor of real input images, tensor of z data, learning rate)
"""
# TODO: Implement Function
inputs_real = tf.placeholder(tf.float32, (None, image_width, image_height, image_channels), name='input_real')
inputs_z = tf.placeholder(tf.float32, (None, z_dim), name='input_z')
learning_rate = tf.placeholder(tf.float32, name='learning_rate')
return inputs_real, inputs_z, learning_rate
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_model_inputs(model_inputs)
def lrelu(x, alpha=0.1, name='leaky_relu'):
return tf.maximum(x, alpha * x, name=name)
Implement discriminator
to create a discriminator neural network that discriminates on images
. This function should be able to reuse the variabes in the neural network. Use tf.variable_scope
with a scope name of "discriminator" to allow the variables to be reused. The function should return a tuple of (tensor output of the generator, tensor logits of the generator).
def discriminator(images, reuse=False):
"""
Create the discriminator network
:param image: Tensor of input image(s)
:param reuse: Boolean if the weights should be reused
:return: Tuple of (tensor output of the discriminator, tensor logits of the discriminator)
"""
with tf.variable_scope('discriminator', reuse=reuse):
hidden = tf.layers.conv2d(images, 64, 5, strides=2, padding="same")
hidden = lrelu(hidden)
hidden = tf.layers.conv2d(hidden, 128, 5, strides=2, padding="same")
hidden = tf.layers.batch_normalization(hidden, training=True)
hidden = lrelu(hidden)
hidden = tf.layers.conv2d(hidden, 256, 5, strides=1, padding="same")
hidden = tf.layers.batch_normalization(hidden, training=True)
hidden = lrelu(hidden)
hidden = tf.contrib.layers.flatten(hidden)
hidden = tf.layers.dense(hidden,1)
out = tf.sigmoid(hidden)
return out, hidden
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_discriminator(discriminator, tf)
Implement generator
to generate an image using z
. This function should be able to reuse the variabes in the neural network. Use tf.variable_scope
with a scope name of "generator" to allow the variables to be reused. The function should return the generated 28 x 28 x out_channel_dim
images.
def generator(z, out_channel_dim, is_train=True):
"""
Create the generator network
:param z: Input z
:param out_channel_dim: The number of channels in the output image
:param is_train: Boolean if generator is being used for training
:return: The tensor output of the generator
"""
# TODO: Implement Function
with tf.variable_scope('generator', reuse = (not is_train)):
hidden = tf.layers.dense(z, 7*7*1024)
hidden = tf.reshape(hidden, (-1, 7, 7, 1024))
hidden = lrelu(hidden)
hidden = tf.layers.conv2d_transpose(hidden, 512, 5, strides=2, padding='same')
hidden = tf.layers.batch_normalization(hidden, training=is_train)
hidden = lrelu(hidden)
hidden = tf.layers.conv2d_transpose(hidden, 256, 5, strides=1, padding='same')
hidden = tf.layers.batch_normalization(hidden, training=is_train)
hidden = lrelu(hidden)
hidden = tf.layers.conv2d_transpose(hidden, 128, 5, strides=1, padding='same')
hidden = tf.layers.batch_normalization(hidden, training=is_train)
hidden = lrelu(hidden)
hidden = tf.layers.conv2d_transpose(hidden, 64, 1, strides=1, padding='same')
hidden = tf.layers.batch_normalization(hidden, training=is_train)
hidden = lrelu(hidden)
hidden = tf.layers.conv2d_transpose(hidden, out_channel_dim, 5, strides=2, padding='same')
hidden = tf.tanh(hidden)
return hidden
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_generator(generator, tf)
Implement model_loss
to build the GANs for training and calculate the loss. The function should return a tuple of (discriminator loss, generator loss). Use the following functions you implemented:
discriminator(images, reuse=False)
generator(z, out_channel_dim, is_train=True)
def model_loss(input_real, input_z, out_channel_dim):
"""
Get the loss for the discriminator and generator
:param input_real: Images from the real dataset
:param input_z: Z input
:param out_channel_dim: The number of channels in the output image
:return: A tuple of (discriminator loss, generator loss)
"""
# TODO: Implement Function
g_model = generator(input_z, out_channel_dim, is_train=True)
d_model_real, d_logits_real = discriminator(input_real)
d_model_fake, d_logits_fake = discriminator(g_model, reuse=True)
smooth = 0.9
d_loss_real = tf.reduce_mean(
tf.nn.sigmoid_cross_entropy_with_logits(logits=d_logits_real, labels=tf.ones_like(d_model_real) * (1 - smooth)))
d_loss_fake = tf.reduce_mean(
tf.nn.sigmoid_cross_entropy_with_logits(logits=d_logits_fake, labels=tf.zeros_like(d_model_fake)))
g_loss = tf.reduce_mean(
tf.nn.sigmoid_cross_entropy_with_logits(logits=d_logits_fake, labels=tf.ones_like(d_model_fake)))
d_loss = d_loss_real + d_loss_fake
return d_loss, g_loss
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_model_loss(model_loss)
Implement model_opt
to create the optimization operations for the GANs. Use tf.trainable_variables
to get all the trainable variables. Filter the variables with names that are in the discriminator and generator scope names. The function should return a tuple of (discriminator training operation, generator training operation).
def model_opt(d_loss, g_loss, learning_rate, beta1):
"""
Get optimization operations
:param d_loss: Discriminator loss Tensor
:param g_loss: Generator loss Tensor
:param learning_rate: Learning Rate Placeholder
:param beta1: The exponential decay rate for the 1st moment in the optimizer
:return: A tuple of (discriminator training operation, generator training operation)
"""
# TODO: Implement Function
t_vars = tf.trainable_variables()
d_vars = [var for var in t_vars if var.name.startswith('discriminator')]
g_vars = [var for var in t_vars if var.name.startswith('generator')]
update_ops = tf.get_collection(tf.GraphKeys.UPDATE_OPS)
g_updates = [opt for opt in update_ops if opt.name.startswith('generator')]
with tf.control_dependencies(g_updates):
d_train_opt = tf.train.AdamOptimizer(learning_rate, beta1=beta1).minimize(d_loss, var_list=d_vars)
g_train_opt = tf.train.AdamOptimizer(learning_rate, beta1=beta1).minimize(g_loss, var_list=g_vars)
return d_train_opt, g_train_opt
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_model_opt(model_opt, tf)
"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
import numpy as np
def show_generator_output(sess, n_images, input_z, out_channel_dim, image_mode):
"""
Show example output for the generator
:param sess: TensorFlow session
:param n_images: Number of Images to display
:param input_z: Input Z Tensor
:param out_channel_dim: The number of channels in the output image
:param image_mode: The mode to use for images ("RGB" or "L")
"""
cmap = None if image_mode == 'RGB' else 'gray'
z_dim = input_z.get_shape().as_list()[-1]
example_z = np.random.uniform(-1, 1, size=[n_images, z_dim])
samples = sess.run(
generator(input_z, out_channel_dim, False),
feed_dict={input_z: example_z})
images_grid = helper.images_square_grid(samples, image_mode)
pyplot.imshow(images_grid, cmap=cmap)
pyplot.show()
Implement train
to build and train the GANs. Use the following functions you implemented:
model_inputs(image_width, image_height, image_channels, z_dim)
model_loss(input_real, input_z, out_channel_dim)
model_opt(d_loss, g_loss, learning_rate, beta1)
Use the show_generator_output
to show generator
output while you train. Running show_generator_output
for every batch will drastically increase training time and increase the size of the notebook. It's recommended to print the generator
output every 100 batches.
def train(epoch_count, batch_size, z_dim, learning_rate, beta1, get_batches, data_shape, data_image_mode):
"""
Train the GAN
:param epoch_count: Number of epochs
:param batch_size: Batch Size
:param z_dim: Z dimension
:param learning_rate: Learning Rate
:param beta1: The exponential decay rate for the 1st moment in the optimizer
:param get_batches: Function to get batches
:param data_shape: Shape of the data
:param data_image_mode: The image mode to use for images ("RGB" or "L")
"""
# TODO: Build Model
# Set image dimensions
_, image_width, image_height, image_channels = data_shape
# Set model inputs
input_real, input_z, learn_rate = model_inputs(image_width, image_height, image_channels, z_dim)
# Set model loss
d_loss, g_loss = model_loss(input_real, input_z, image_channels)
# Set model optimization
d_opt, g_opt = model_opt(d_loss, g_loss, learning_rate, beta1)
samples, losses = [], []
steps = 0
print_at = 50
show_at = 100
saver = tf.train.Saver()
with tf.Session() as sess:
sess.run(tf.global_variables_initializer())
for epoch_i in range(epoch_count):
for batch_images in get_batches(batch_size):
# TODO: Train Model
steps += 1
batch_images = batch_images * 2
# Sample random noise for G
sample_z = np.random.uniform(-1, 1, size=(batch_size, z_dim))
# Run optimizers
_ = sess.run(d_opt, feed_dict={input_real: batch_images, input_z: sample_z, learn_rate: learning_rate})
_ = sess.run(g_opt, feed_dict={input_z: sample_z, learn_rate: learning_rate})
if steps % print_at == 0:
# At the end of each epoch, get the losses and print them out
train_loss_d = d_loss.eval({input_z: sample_z, input_real: batch_images})
train_loss_g = g_loss.eval({input_z: sample_z})
print("Epoch {}/{}...".format(epoch_i + 1, epoch_count),
"Discriminator Loss: {:.4f}...".format(train_loss_d),
"Generator Loss: {:.4f}".format(train_loss_g))
if steps % show_at == 0:
show_generator_output(sess, 64, input_z, image_channels, data_image_mode)
show_generator_output(sess, 64, input_z, image_channels, data_image_mode)
Test your GANs architecture on MNIST. After 2 epochs, the GANs should be able to generate images that look like handwritten digits. Make sure the loss of the generator is lower than the loss of the discriminator or close to 0.
batch_size = 64
z_dim = 100
learning_rate = 0.0002
beta1 = 0.5
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
epochs = 2
mnist_dataset = helper.Dataset('mnist', glob(os.path.join(data_dir, 'mnist/*.jpg')))
with tf.Graph().as_default():
train(epochs, batch_size, z_dim, learning_rate, beta1, mnist_dataset.get_batches,
mnist_dataset.shape, mnist_dataset.image_mode)
Run your GANs on CelebA. It will take around 20 minutes on the average GPU to run one epoch. You can run the whole epoch or stop when it starts to generate realistic faces.
batch_size = 64
z_dim = 100
learning_rate = 0.0001
beta1 = 0.3
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
epochs = 1
celeba_dataset = helper.Dataset('celeba', glob(os.path.join(data_dir, 'img_align_celeba/*.jpg')))
with tf.Graph().as_default():
train(epochs, batch_size, z_dim, learning_rate, beta1, celeba_dataset.get_batches,
celeba_dataset.shape, celeba_dataset.image_mode)
When submitting this project, make sure to run all the cells before saving the notebook. Save the notebook file as "dlnd_face_generation.ipynb" and save it as a HTML file under "File" -> "Download as". Include the "helper.py" and "problem_unittests.py" files in your submission.


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| An object for encoding and decoding audio files (principally WAV and AIFF) using the Libsndfile library. | ||
|
channels
Returns channels read from the audio file.
close
Closes the file if it is open.
Returns self.
format
Returns format read from the audio file.
formatNames
Returns a list of strings with the names of the supported codecs.
openForReading
Opens the file at the path specified in the path slot and sets the following slots:
openForWriting
frames sampleRate channels format seekableReturns self.
Opens the file at the path specified in the path slot for writing. The following slots should be set first to specify the output format:
outputBuffer
sampleRate channels formatReturns self.
Returns the output buffer.
path
Returns path to audio file.
read(numberOfFrames)
Read a given number of frames (sample pairs).
Returns self.
sampleRate
Returns sample rate read from the audio file.
setFormat(aSeq)
Sets the format used for writing. Use the formatNames method to get a list of supported format names. Returns self.
setPath(aPath)
Sets path to audio file.
write(aSeq)
Writes aSeq using the format specified by the slots:
sampleRate channels formatReturns the number of frames written. |


Your ethereum client/node version is {{ethereumClientVersion}}
Your network protocol version is {{ethereumNetworkProtocolVersion}}
Test contract
Deploy and call a test contract
(this only works if you have the solidity compiler solc installed and added to
the path variables of your local system. It can take some time until the contract is mined -> check the javascript
console)


We will use a random code instead of your name on all your study data. This code cannot be used to re-identify you.
The data will be encrypted and stored on a secure Cloud server under the control of Institution (nonprofit) to prevent improper access.


Freeland, Champagne to be moved in Liberal cabinet shuffle: reports
by Robert FifePrime Minister Justin Trudeau is moving Chrystia Freeland to a domestic portfolio, reports say, as part of a cabinet shuffle that will aim to put the fight against climate change and the creation of a green economy at the heart of the federal government’s agenda.
According to Radio-Canada, Ms. Freeland will be replaced at Global Affairs by François-Philippe Champagne, an international lawyer from Quebec who has been who has been the infrastructure minister.
The report from the French-language arm of the CBC said that Mr. Trudeau will move Jonathan Wilkinson to Environment. He is currently the Minister of Fisheries and Oceans.
The shuffle means that Ms. Freeland, who became one of the star performers in the Liberal government during the NAFTA renegotiations, will be taking on a new portfolio relating directly to domestic affairs. Liberal and government sources have said in recent weeks that Ms. Freeland will play a central role in the government’s efforts to deal with the fallout from the Oct. 21 election, in which the Liberal Party’s economic and environmental policies came under fire across the country.
It is unknown at this point which portfolio Ms. Freeland will be inheriting.
Still, the changes will help the Prime Minister to address concerns about the lack of representation of the Prairie provinces in the Liberal caucus and government.
While Ms. Freeland represents a Toronto riding, she was raised in Alberta. Mr. Wilkinson, meanwhile, grew up and worked in Saskatchewan before moving to British Columbia. He currently represents the riding of Vancouver North.
The Globe and Mail has previously reported that Bill Morneau will remain the Minister of Finance.
Mr. Trudeau will announce his new cabinet at Rideau Hall on Wednesday afternoon. The shuffle follows the re-election of the Liberals on Oct. 21.


build method
- @override
Describes the part of the user interface represented by this widget.
The framework calls this method when this widget is inserted into the
tree in a given BuildContext
and when the dependencies of this widget
change (e.g., an InheritedWidget
referenced by this widget changes).
The framework replaces the subtree below this widget with the widget
returned by this method, either by updating the existing subtree or by
removing the subtree and inflating a new subtree, depending on whether the
widget returned by this method can update the root of the existing
subtree, as determined by calling Widget.canUpdate
.
Typically implementations return a newly created constellation of widgets
that are configured with information from this widget's constructor and
from the given BuildContext
.
The given BuildContext
contains information about the location in the
tree at which this widget is being built. For example, the context
provides the set of inherited widgets for this location in the tree. A
given widget might be built with multiple different BuildContext
arguments over time if the widget is moved around the tree or if the
widget is inserted into the tree in multiple places at once.
The implementation of this method must only depend on:
- the fields of the widget, which themselves must not change over time, and
- any ambient state obtained from the
context
usingBuildContext.inheritFromWidgetOfExactType
.
If a widget's build method is to
depend on anything else, use a
StatefulWidget
instead.
See also:
StatelessWidget
, which contains the discussion on performance considerations.
Implementation
@override
Widget build(BuildContext context) {
// TODO Internalize recovery through the context of [JsonSchemaBloc]
return BlocProvider<JsonSchemaBloc>(
create: (BuildContext buildContext) => jsonSchemaBloc,
child: BlocBuilder<JsonSchemaBloc, JsonSchemaState>(
bloc: jsonSchemaBloc,
condition: (previousState, state) {
// print("state.layout: ${state.layout}");
return previousState.layout != state.layout;
},
builder: (context, state) {
// print("layout: $layout");
if (state.layout == null) {
return Container(
child: Center(
child: CircularProgressIndicator(),
),
);
} else {
return SingleChildScrollView(
child: DynamicWidgetBuilder.buildFromMap(
state.layout,
context,
jsonSchemaBloc,
),
);
}
},
),
);
}


<#if errMsg??>
${errMsg?html}
#if>
To enable two-factor authentication, you need an authenticator application on your smart phone. For example, the Google Authenticator app:
Install Google Authenticator for Android.
Install Google Authenticator for iPhone / iPad.
Start your authenticator application on your smart phone, set up an account, and choose the 'scan a barcode' option.
Enter the code displayed on your device to confirm the setup.
You should obviously never give this in a real TOTP application, but as a demo, here are some TOTP codes that your phone would be telling you if you scanned the QR code:
Correct code: ${correctTotpCode}
If your phone is three minutes ahead: ${threeMinutesOutCode}
If your phone has the wrong Daylight Savings Time setting: ${hourOutCode}
Give these a try to see what the demo app does. Also, of course, try a random code as well,
such as 000042. We determined that one by random dice roll, we swear.


#! /bin/sed -nf # filename : comment-replace.sed # author : Yerik Ng # date : <2013-10-22 20:21:09> # desc : In this script, I've used a general idea to locate the target line # in a plain text where the substitution is done. The idea is that, in order # to locate *point-of-interest* in plain text, we shall come across a stage by # stage process. For example, if we try to locate something in a comment in # a source file. The first stage would be identifying the comment, and then # the second stage would be locating the target place in *the* comment. Of # cource, the comment could be replaced with any construct in the text. Here # I demostrate the use of sed to replace some string in the comment of C like # source files. /\/\*/ { :loop /\*\// !{ N b loop } s/COPYING/!!!!!!!/ } p ### colorized by sedsed, a SED script debugger/indenter/tokenizer/HTMLizer


Information
- Studies have found that 30% to 40% of the food we produce in the United States is ultimately thrown away.
- America throws away more than 38 million tons of food every year. That's the weight of 104 Empire State Buildings.
- Farmers and producers use around 25% of all of America's fresh water just to produce the food that nobody eats.


These are the {{ n }} shares for this secret. Any {{ k }} of these points may be interpolated to construct the polynomial f where f(0) = secret
Mouse over each of the k squares to reveal that share.
{{ share }} |
{% endfor %}
The prime p for this scheme is: {{ prime }}
Remember to use this when computing the secret!
You can interpolate these points using the interpolation calculator. You can also go back and encode another secret.
{% for message in get_flashed_messages() %}


Simple Scrollbar Demo
The simplescrollbars
addon defines two
styles of non-native scrollbars: "simple"
and "overlay"
(click to try), which can be passed to
the scrollbarStyle
option. These implement
the scrollbar using DOM elements, allowing more control over
its appearance.


In the conditions panel we can find a first part of it which details the conditions which are being edited. After that there is a bigger one where we can edit the conditions. In addition there is a button to add new conditions and accept the changes.
At this part of the panel we will find a brief description which corresponds to the condition we are editing.
At this part of the panel we will find two buttons. Through them we can add new conditions or just accept the changes introduced to the conditions we are editing, and closing the window.
In this panel we will find a very graphic description of the condition we are implementing. When we put the pointer over a condition we have the next following posibilities:
When we add a condition, this will be added after the all existing conditions. If we want to add a condition in the middle position the best way to achieve this is chosing the previous condition to the place we want to insert the new one, duplicate it, and afterwards modificating the value of the new created condition.


Tests performance of setting up, manipulating, and drawing a display list comprised of 200 containers and 40,000 bitmaps.


-
How To Turn Monday Into A Day You Actually Enjoy
www.fastcompany.com
Ever wish the weekend had just one more day of rest? Rethinking Mondays gets us a little closer to that ideal schedule.
-
Treehouse Status - Storage Maintenance
status.teamtreehouse.com
Treehouse's Status Page - Storage Maintenance.
-
Interview with Type Designer Mattox Shuler
blog.teamtreehouse.com
Interview with Mattox Shuler, type designer
-
Learn Swift at Treehouse
www.youtube.com
Swift is a new programming language created by Apple to program iOS 8 apps. If you are new to programming or to Swift then the "Swift Basics" course ...
-
Maya Elious » How to introduce yourself at a networking event
mayaelious.com
Great tips! I tend to be shy at networking events but after reading, I feel like I have a new strategy. Thanks for sharing!
-
CSS Triggers | Fireshell | Responsive Design | The Treehouse Show Episode ...
www.youtube.com
In this episode of The Treehouse Show, Nick Pettit (@nickrp) and Jason Seifer (@jseifer) talk about the latest in web design, web development, HTML5, ...
-
Moving from WordPress.com to Self-Hosted WordPress.org Course
teamtreehouse.com
In this short course we go over the different things you need to know about transferring a WordPress site from the .com version of WordPress to the ...
-
How to Install Laravel Homestead on Windows
blog.teamtreehouse.com
How to Install Laravel Homestead on Windows
-
Object-Oriented Python Course
teamtreehouse.com
Sometimes simple scripts with functions in them just aren't enough. Eventually you'll need logical models of your work and that'll lead you to ...
-
Student Perks
teamtreehouse.com
Treehouse is the fastest, easiest way to learn to code, make apps, and start a business. Tutorials in CSS, HTML, Ruby, JavaScript, iOS, and more.
-
How to get started making Android apps
www.greenbot.com
Have a brilliant idea for the next big app, but don't know how to make it happen? These classes are the best way to start.
-
Forum Contest: Create a Twitter Widget | Treehouse Forum
teamtreehouse.com
Participate in discussions with other Treehouse members and learn.
-
Modular CSS with Sass Course
teamtreehouse.com
Today’s websites and applications are larger than ever and a lot hinges on the CSS architecture. So CSS that is poorly thought-out can be a strain on ...
-
Untangle the Web
www.meetup.com
We're back from our summer hiatus! We've missed you guys and can't wait to bring you more great talks in September. Suleiman Leadbitter on Emotion in ...
-
Human Resources Lead
teamtreehouse.com
Treehouse is the fastest, easiest way to learn to code, make apps, and start a business. Tutorials in CSS, HTML, Ruby, JavaScript, iOS, and more.
-
Publish an Android App Course
teamtreehouse.com
Publishing your app on Google Play allows you to share it with users around the world, and maybe even make some money. Publishing your first app can ...
-
7 Online Tools to Help You Create Amazing Visual Content
www.chrisducker.com
When it comes to online content creation and marketing, we’re becoming more and more attracted to visuals. Visual content has grown in leaps and ...
-
Learning Swift vs Objective-C - Treehouse Blog
blog.teamtreehouse.com
Since we launched our Swift courses on the day Apple publicly released iOS 8 we have received several emails and tweets asking whether you still need ...
-
New Course: Modular CSS with Sass - Treehouse Blog
blog.teamtreehouse.com
In this new course, you’re going to build a UI toolkit using Sass and many of the best practices and principles of modular CSS architecture. You’ll ...
-
Design Principles: Connecting And Separating Elements Through Contrast And ...
www.smashingmagazine.com
This is third part of a series on design principles for beginners. The first part covered an introduction to gestalt; the second built on those ...
-
Treehouse Forum Contest Winners | August 2014
www.youtube.com
Every week at Treehouse, we invite our students to challenge themselves with a Forum Contest. Check the winning projects built by our amazing ...
-
Contributing to Open Source Through Documentation
blog.teamtreehouse.com
Contributing to Open Source Through Documentation
-
Treehouse Features - Android App
teamtreehouse.com
Treehouse is the fastest, easiest way to learn to code, make apps, and start a business. Tutorials in CSS, HTML, Ruby, JavaScript, iOS, and more.
-
Generate Conference 2014 - London
www.generateconf.com
London / 26.09.14 / Grand Connaught Rooms REGISTER FOR £275 Why Attend? Generate London is the conference for web designers and developers, presented
-
Treehouse Releases Android App, Adds Course For Apple Swift
thenextweb.com
Technology education startup Treehouse has today announced its first Android app, alongside a set of new courses for Apple’s Swift programming ...
-
A little help for a big help: Treehouse could use your vote to bolster ...
siliconflorist.com
If I’ve said it once, I’ve said it a thousand times—and you’ve had to listen to it every time I say it: finding development talent is the biggest ...
-
Practical Typography | Date Pickers | Form Builders | The Treehouse Show ...
www.youtube.com
In this episode of The Treehouse Show, Nick Pettit (@nickrp) and Jason Seifer (@jseifer) talk about the latest in web design, web development, HTML5, ...


From the newsletter ... |
Moving on......?Our lives on this earth are often described as a journey. Each of us travels through time and space and, as we travel, other travellers join us and then depart from us. Today, it seems, the speed of our journey through life is accelerating. Certainly we find it hard to believe that our curacy here at Cogges and South Leigh is now coming to an end and that as we move on in August it will be exactly three years since we moved to Witney. We knew when we arrived that this part of our journey would be short - it's part of this job. But that doesn't make leaving any easier. Although we knew hardly anyone here when we moved from Durham we've always been made most welcome by the churches and the parish. As a result, we've really enjoyed our time here and Witney has become our home. We're excited by our new jobs in Oxford but they will be quite different - Lis will be working mainly with students in Jesus College, Andrew will be teaching and helping train people to be vicars. We will miss parish life and being part of a parish community. ...
Cogges Parish | Other articles | Previous issue © 1999; Published in Cogges Parish monthly newsletter, number 242, July 1999<EMAIL_ADDRESS>|


THE SCARLET LETTER (1995) A Film Review by Ted Prigge Copyright 1998 Ted Prigge
Director: Roland Joffé Writer: Douglas Day Stewart (based "freely" on the novel by Nathaniel Hawthorne) Starring: Demi Moore, Gary Oldman, Robert Duvall, Lisa Jolliff-andoh, Edward Hardwicke, Robert Prosky, Roy Dotrice, Joan Plowright, Malcolm Storry, Dana Ivey
My theory when watching a film adaptation of a novel, whatever it may be, is that the film can do anything it wants with it; it just has to work as a film itself. After all, if a film is EXACTLY like the book, why are we wasting our time watching it? Can't we just pick up the book and get a better picture of everything? When discussing this, I always bring up Stanley Kubrick's adaptation of Stephen King's "The Shining," a film that is like the book for about the first 50 or so pages, and then takes off in a completely different direction, yet is much more fun and all-around better than the book, which soon pulls all of its punches and ends in a manner that goes beyond cheap.
The main thing that this version of "The Scarlet Letter" has in common with the famous novel by Nathaniel Hawthorne is the title and the basic set-up. It still tells the story of Hester Prynne, a puritan woman who has an affair with the local priest which results in a baby, and is forced to wear a scarlet-colored "A" on her chest to show everyone that she has sinned. And it features all of the same characters, and ALMOST ends the same way, but that's about all that these two have in common.
This, in my estimation, would be totally fine if it all worked out as a film. If this could become a good film by doing what it does with its source, then by all means I would personally have no problem with it. But I have many problems with this.
That's barely the least of the problems. I wish there was just one main thing wrong with this film, but there are so many problems, ranging in size, that this film just completely topples over, and instead of being the "passionate" and "erotic" story it tries to be, it becomes "dull" and "laughable." Are we supposed to be moved in any way by that scene where Hester is bathing and her young female servant girl decides to take a peak at her through a hole in the door? Introducing interracial homosexual undertones would be fine if it fit at all with the rest of the film. Here, it just induces laughing.
I'm actually somewhat shocked that this film is so terrible, because apart from the laughably horrible casting of Demi Moore as Hester (!!!), you have what is a really competent cast...or at least is supposed to be competent. You have Gary Oldman, a totally amazing actor, in a very strong role, perhaps the toughest role in the entire story: Reverend Arthur Dimmesdale, the priest who boinks Hester, whose identity is not revealed, and who is forced to live what with he thinks is guilt for "lowering" himself to having an affair. You also have Robert Duvall, one of the best living actors, as Hester's husband, Roger, who is believed to be dead in the beginning, but who comes back to disguise himself as someone else and to try and torture not only Hester but Arthur as well.  Look away from Demi Moore's name in first bill and you see what is a great cast in what could have been a great movie.
But alas, they have opted to remove some of the parts of the book which really would have helped this out, primarily because it's a big budget (somewhere in the range of $60 million) Hollywood fiasco, and since many Hollywood distributors take their audiences for idiots (look at "Godzilla" if you don't believe me, but just take my word for it), they have to dumb it down. The novel starts off when the "A" is placed on Hester's chest, long after the affair; the film spends a ghastly hour filling in the beginning, trying to make this a romance, even though the main reason Hester loves Dimmesdale is because she saw him swimming naked (!!!), and the main reason Dimmesdale loves Hester is because she has a big chest (they had silicon back then? okay, bad joke).
 Sure, the book spends hundreds of pages dealing with inner toil, but the thing is it worked.
And then there's the ending. The book ends in a way that is literally proposterous, but is simultaneously sad enough to become tragic and satirical. This film opts for a "happy" ending, with a big action showdown between Indians (!!! - how many time do I have to do this?) and the Puritans, featuring fire, carnage, and lots of people running around screaming.
Not that the film is totally without merit. Gary Oldman, despite having to do some really ridiculous stuff, does give what would be a good performance. You can almost see him trying to bring out some of the emotional and satirical depth of the novel in certain scenes, as if he actually took the time to read the book and understand what it's about (because we all can tell that no one else did, unless you count screenwriter Douglas Day Stewart reading a couple pages of the Cliffs Notes for this). Duvall, try as he must, actually comes off as laughable, giving what easily ranks as his worst performance, though in all reality it wasn't entirely his part. However, as we are speaking about acting, I suppose I should mention Joan Plowright, who should be embarrassed for her performance in this: she comes off as if she took muscle relaxers before every shoot.
The really weird thing about this is that anytime anyone mentions this book to anyone who went to high school, including me, you get a nasty look. This really is one of the most painful and excruciating novels to read, and it's all the more worse because you're forced to read it and disect it. Hawthorne may have been able to weave a complex and satirical story which has great ideas, but for any entertaining value, this comes up snake eyes. Yet when you watch this film, you automatically yearn for the novel and how it didn't treat you like a moron, and didn't come off as being completely dull. At the least you could get into a debate over morals or hypocrisy with this, which is a lot better than talking about how you didn't like what is basically a really dull, overly-melodramatic, and completely incompetent love story.
MY RATING (out of 4): *1/2
Homepage at: http://www.geocities.com/Hollywood/Hills/8335/
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


Required to judge reproducibility
The survey is being terminated due to the lack of a key element to allow reproducibility


Helpful functions for using mesh code (80km to 125m) data in Japan. Visualize mesh code using 'ggplot2' and 'leaflet', etc.
| Version: | 1.1.1 |
| Depends: | R (≥ 3.1) |
| Imports: | leaflet (≥ 1.1.0), miniUI (≥ 0.1.1), purrr (≥ 0.2.4), rlang (≥ 0.1.4), sf (≥ 0.5-5), shiny (≥ 1.0.5), tibble (≥ 1.3.4), units (≥ 0.5-1), magrittr (≥ 1.5) |
| Suggests: | knitr (≥ 1.20), testthat (≥ 1.0.2), rmarkdown (≥ 1.10) |
| Published: | 2018-06-26 |
| Author: | Shinya Uryu [aut, cre] |
| Maintainer: | Shinya Uryu <suika1127 at gmail.com> |
| BugReports: | https://github.com/uribo/jpmesh/issues |
| License: | MIT + file LICENSE |
| URL: | https://github.com/uribo/jpmesh#readme |
| NeedsCompilation: | no |
| Materials: | README NEWS |
| CRAN checks: | jpmesh results |
| Reference manual: | jpmesh.pdf |
| Vignettes: |
How to use mesh cord in R |
| Package source: | jpmesh_1.1.1.tar.gz |
| Windows binaries: | r-devel: jpmesh_1.1.1.zip, r-release: jpmesh_1.1.1.zip, r-oldrel: jpmesh_1.1.1.zip |
| OS X binaries: | r-release: jpmesh_1.1.1.tgz, r-oldrel: jpmesh_1.1.1.tgz |
| Old sources: | jpmesh archive |
| Reverse depends: | jpndistrict |
| Reverse enhances: | NipponMap |
Please use the canonical form https://CRAN.R-project.org/package=jpmesh to link to this page.


'It is sickening' - Ireland rue lack of firepower as Danes progress to Euro 2020
Ireland’s goalscorer Matt Doherty admitted their shots-shy record caught up with them in tonight’s concluding Euro qualifier.
While the Wolves man grabbed his first international goal five minutes from full-time to cancel out Martin Braithwaite’s breakthrough 12 minutes earlier, the 1-1 draw sent Denmark into the finals at Ireland’s expense.
The leveller was just the seventh goal of an eight-match campaign, a paltry return consigning Ireland to third place in Group D and the play-off semi-final next March.
Doherty said: “It was a struggle for us to score throughout the entire campaign and we managed to get one, rather than two, tonight.
We wanted to stay in the game for as long as possible at nil-all and then put all the pressure on towards the end.
“Unfortunately, while only really did that when we went behind. They got to score from the one chance they had in the match.
“It was a bit of a mountain to climb after that and we didn’t manage it.
It is sickening. We were probably the better team and definitely deserved to win the game.
“It is really flat inside in the dressing room but we still have the play-offs.”
The Dubliner said the performance at Lansdowne Road bodes well for that semi-final. Ireland will face one of Slovakia, Wales or Bosnia-Herzegovina away from home on May 26.
“Our shape and movement was good so if we can stay in form stay fit we will have a chance,” he added.


scipandas >> scipandas
scipandas
- agg — Aggregate using one or more operations over the specified axis.
- apply — Apply a function along an axis of the DataFrame.
- applymap — Apply a function to a Dataframe elementwise.
- astype — Cast a pandas object to a specified dtype dtype.
- at — Access a single value for a row/column label pair.
- categorical — Calls and initializes Categorical function
- combine — Perform column-wise combine with another DataFrame.
- convert_dtypes — Convert columns to best possible dtypes using dtypes supporting pd.NA.
- copy — Make a copy of this object’s indices and data.
- corr — Compute pairwise correlation of columns, excluding NA/null values.
- corrwith() — Compute pairwise correlation.
- cut — Calls and initializes cut function
- dataframe — Calls and initializes DataFrame function
- dframefunc — Calls and initializes dframefunc module
- diff — First discrete difference of element.
- drop — Drop specified labels from rows or columns.
- drop_duplicates — Return DataFrame with duplicate rows removed.
- dropna — Remove missing values.
- ewm — Provide exponential weighted functions.
- fillna — Fill NA/NaN values using the specified method.
- groupby — Group DataFrame using a mapper or by a Series of columns.
- iloc — Purely integer-location based indexing for selection by position.
- infer_objects — Attempt to infer better dtypes for object columns.
- isna — Detect missing values.
- join — Join columns of another DataFrame.
- loc — Access a group of rows and columns by label(s) or a boolean array.
- melt() — Unpivot a DataFrame from wide to long format, optionally leaving identifiers set.
- memory_usage — Get Multiplication of dataframe and other, element-wise (binary operator mul).
- merge_ordered — Calls and initializes merge_ordered function
- mul — Get Multiplication of dataframe and other, element-wise (binary operator mul).
- notna — Detect existing (non-missing) values.
- qcut — Calls and initializes qcut function
- rank — Compute numerical data ranks (1 through n) along axis.
- replace — Replace values given in to_replace with value.
- set_axis — Assign desired index to given axis.
- set_index — Set the DataFrame index using existing columns.
- sort_values — Sort by the values along either axis.
- sub — Get Subtraction of dataframe and other, element-wise (binary operator sub).
- xs — Return cross-section from the Series/DataFrame.


Look for information on the Course website. The WSJ not-quite-map of election results was part of Flowing Data's best datavis projects of 2016. If you haven't yet, sign up for Piazza.


Here, the type of default action is set before the event bubbles to the lightDOM in which the button is used. The lightDOM can still call preventDefault() on the click event to prevent either submit or reset, but changing the attribute will not change the type of action that the button does. This is more polite from the lightDOM side. The lightDOM can prevent (or alter the data of the reset or submit), but it cannot change a default action from a submit to a reset or vice versa anymore.
The best solution here would be to have two buttons, one for submit and one for reset: < button > and < reset-button >.


Politico
Home
Create Party
Create Office
Election Results
View Parties
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Register Political Party
Party Name:
Party Acronym:
Headquater Address:
Party Email:
Upload Party Logo:
Register Party


Christian Caeg
Front End Lead
Christian is currently enrolled at San Francisco State University to complete his bachelor
program for Computer Science. In his spare time, he plays competitive Super Smash Brothers Melee,
Overwatch, listens to music, or watches anime.


I have been developing for the web for more than a year. I started with basic HTML and CSS but now am also fluent in JavaScript, PHP and Python and am familiar with frameworks like Node.JS and libaries Jquery and Bootstrap. Below are some of my previous projects.
The Great Media Debate - YouTube
I created this project for media class at school. I created a single page site as well as two embedded YouTube videos explain how YouTube.com influences its users including both the creators and the viewers.
Skills:
- HTML
- JS
- CSS
- Design
View the project here
2 Sisters Organics - 'Coming Soon' Page
2 Sisters Organics is a small business based in Geelong, Australia that sells sprays, soaps, candles and more all made from entirely natural and organic ingredients. I was asked to make a 'website coming soon' page to put on their domain until their full site was developed. You can learn more about 2 Sisters Organics at their Facebook page here.
Skills:
- HTML
- CSS
- Design
You can view the project at mail.2sistersorganics.com
WB Messenger
WB Messenger was a basic 'instant messenger' I made as a learning experience that ended up being used by my peers to talk at school. It included login authentication, XSS and MySQL injection prevention and you could send images and messages. WB Messenger was written in PHP, HTML, CSS and used a MySQL database.
Please Note: all names (bar my own) have been changed in the above screen-grab (:
Skills:
- PHP
- MySQL
- HTML
- CSS
- JS
- Design
- Web Security


Success Stories
By generating these success stories RiSE has created a wave of hope in the valley.
There is an exponential increment in the number of students applying to foreign universities and appearing in competitive examinations.
This section contains two paragraphs.
Within the two paragraphs, the text is centered, and long sentences will flow to as many lines as needed.
This section contains two paragraphs.
Within the two paragraphs, the text is centered, and long sentences will flow to as many lines as needed.


Files CCore/inc/crypton/SHA.h CCore/src/crypton/SHA.cpp
Files CCore/inc/crypton/PlatformSHA.h
The following HashFunction<....> classes implement the SHA hash algorithms:
typedef HashFunction<....> SHA1; typedef HashFunction<....> SHA224; typedef HashFunction<....> SHA256; typedef HashFunction<....> SHA384; typedef HashFunction<....> SHA512;
SHAnnn implements the correspondent SHA-nnn algorithm.
The following KeyedHashFunction<....> classes implement the HMAC hash functions based on SHA algorithms:
typedef KeyedHashFunction<....> KeyedSHA1; typedef KeyedHashFunction<....> KeyedSHA224; typedef KeyedHashFunction<....> KeyedSHA256; typedef KeyedHashFunction<....> KeyedSHA384; typedef KeyedHashFunction<....> KeyedSHA512;
KeyedSHAnnn implements the HMAC based on the correspondent SHA-nnn algorithm.
The file PlatformSHA.h contains stub definitions for the PlatformSHA types.
using PlatformSHA1 = SHA1 ; using PlatformSHA224 = SHA224 ; using PlatformSHA256 = SHA256 ; using PlatformSHA384 = SHA384 ; using PlatformSHA512 = SHA512 ; using PlatformKeyedSHA1 = KeyedSHA1 ; using PlatformKeyedSHA224 = KeyedSHA224 ; using PlatformKeyedSHA256 = KeyedSHA256 ; using PlatformKeyedSHA384 = KeyedSHA384 ; using PlatformKeyedSHA512 = KeyedSHA512 ;
A target may override this header file and provide its own definitions with efficient platform-dependent SHA implementation.


Token Based Mitigation
This defense is one the most popular and recommended methods to mitigate CSRF. It can be achieved either with state (synchronizer token pattern) or stateless (encrypted/hash based token pattern). See section 4.3 on how to mitigate login CSRF in your applications. For all the mitigation's, it is implicit that general security principles should be adhered
Strong encryption/HMAC functions should be adhered to.
Note: You can select any algorithm per your organizational needs. We recommend AES256-GCM for encryption and SHA256/512 for HMAC.
Strict key rotation and token lifetime policies should be maintained. Policies can be set according to your organizational needs. Generic key management guidance from OWASP can be found here.


IP address is string of numbers specified as the internet protocol address assigned to each device. It is four numbers separated by dots.
Packet is a fixed size unit of data. It is used on to transport information accross the internet.
Routing is the choosing the most viable path to sent data the network.
Continuing the example of the house, the IP address is the street address that is assigned to your property.
Packets can be like thought of like transporting a large object from one place to another. It is much easier and simpler to split and divide up the object than to move it as a whole. An example would be buying furniture, the pieces are divided and packeted in a way that it is easily transportable and easily assembled at the destination, just like information is divided into packets and reformed to be a whole at the end to form what the result would be.
Routing can be thought of as how a gps might guide you to your destination. Choosing the the best way to your destination.
The IP address keeps the internet organized. Every device connected to the internet is assigned a IP address, yet there not been any conflicts for lack of IP address due to NAT. With NAT, the network router acts as the middle man routing where each packet goes to. In the network with having huge amounts of IP address that would cause conflicts due to the lack of IP address availability in correlation to the number of people in the world.
Packets will break up information into smaller chunks of data to be easily sent across the net.
There are two types, static and dynamic. In static routing, a path is manually hence a change in routing will not be corrected automatically.In Dynamic routing, routes are calculated and denied by software in regarding to network situation.


Text-Only View
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Library: Data
Package: DataCore
Header: Poco/Data/SessionFactory.h
Description
A SessionFactory is a singleton class that stores Connectors and allows to create Sessions of the required type:
Session ses(SessionFactory::instance().create(connector, connectionString));
where the first param presents the type of session one wants to create (e.g. for SQLite one would choose "SQLite") and the second param is the connection string that the connector requires to connect to the database.
A concrete example to open an SQLite database stored in the file "dummy.db" would be
Session ses(SessionFactory::instance().create(SQLite::Connector::KEY, "dummy.db"));
An even simpler way to create a session is to use the two argument constructor of Session, which automatically invokes the SessionFactory:
Session ses("SQLite", "dummy.db");
Member Summary
Member Functions: add, create, instance, remove
Constructors
Destructor
~SessionFactory
~SessionFactory();
Member Functions
add
void add(
Connector * pIn
);
Registers a Connector under its key at the factory. If a registration for that key is already active, the first registration will be kept, only its reference count will be increased. Always takes ownership of parameter pIn.
create
Session create(
const std::string & key,
const std::string & connectionString,
std::size_t timeout = Session::LOGIN_TIMEOUT_DEFAULT
);
Creates a Session for the given key with the connectionString. Throws an Poco:Data::UnknownDataBaseException if no Connector is registered for that key.
create
Session create(
const std::string & uri,
std::size_t timeout = Session::LOGIN_TIMEOUT_DEFAULT
);
Creates a Session for the given URI (must be in key:///connectionString format). Throws a Poco:Data::UnknownDataBaseException if no Connector is registered for the key.
instance
static SessionFactory & instance();
returns the static instance of the singleton.
remove
void remove(
const std::string & key
);
Lowers the reference count for the Connector registered under that key. If the count reaches zero, the object is removed.


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#include <expat.h>
Go to the source code of this file.
Data Structures | |
| struct | AttrList |
| Information for an attribute. More... | |
| struct | AttrBlock |
| Information for a block of attributes. More... | |
| struct | elem_t |
| struct | node |
| struct | Stack |
| This is a structure that holds the information for a stack. More... | |
Defines | |
| #define | VOT_DOC_VERSION "1.2" |
| #define | VOT_XSI "http://www.w3.org/2001/XMLSchema-instance" |
| #define | VOT_SCHEMA_LOC "http://www.ivoa.net/xml/VOTable/v1.1 http://www.ivoa.net/xml/VOTable/v1.1" |
| #define | VOT_XMLNS "http://www.ivoa.net/xml/VOTable/v1.1" |
| #define | SZ_ELEMNAME 32 |
| #define | SZ_ATTRNAME 32 |
| #define | SZ_ATTRVAL 2048 |
| #define | SZ_FNAME 255 |
| #define | SZ_XMLTAG 1024 |
| #define | SZ_LINE 4096 |
| #define | MAX_ATTR 100 |
| #define | MAX_ELEMENTS 1024 |
| #define | HANDLE_INCREMENT 1024000 |
| #define | min(a, b) ((a<b)?a:b) |
| #define | max(a, b) ((a>b)?a:b) |
| #define | handle_t int |
| Handle type definition. | |
Typedefs | |
| typedef struct elem_t | Element |
| typedef struct node | Node |
Functions | |
| int | xml_attrSet (AttrBlock *ablock, char *name, char *value) |
| Set/Create an attributes (private method). | |
| char * | xml_attrGet (AttrBlock *ablock, char *name) |
| Get an attribute's value (private method). | |
| char * | xml_attrXML (AttrBlock *ablock) |
| Get the attributes for an XML tag (private method). | |
| char * | xml_attrNames (AttrBlock *ablock) |
| int | xml_eType (char *name) |
| Get the integer value (ID) of the name (private method). | |
| char * | xml_elemName (Element *e) |
| Get the name of the Element (private method). | |
| int | xml_elemType (Element *e) |
| Get the integer value (ID) of the Element (private method). | |
| char * | xml_elemXML (Element *e) |
| Builds a string of the opening XML Tag (private method). | |
| char * | xml_elemXMLEnd (Element *e) |
| Build a string of the ending XML Tag (private method). | |
| Element * | xml_newElem (unsigned int type) |
| Allocate a new structure of the given type (private method). | |
| handle_t | xml_setHandle (Element *elem) |
| Assign the Element a handle_t (private method). | |
| handle_t | xml_lookupHandle (Element *elem) |
| Lookup the handle_t to an Element (private method). | |
| void | xml_freeHandle (handle_t handle) |
| Free a handle for use (private method). | |
| Element * | xml_getElement (handle_t handle) |
| Get the Element refered to by handle_t (private method). | |
| void | xml_newHandleTable (void) |
| Initialize a handle table (private method). | |
| int | xml_handleCount (void) |
| Get the number of handle_t used (private method). | |
| void | xml_handleCleanup (void) |
| Free all the handle nodes (private method). | |
| void | xml_handleError (char *msg) |
| Print an error message. | |
| void | xml_endElement (void *userData, const char *name) |
| CB whenever an end tag is seen (private method). | |
| void | xml_startElement (void *userData, const char *name, const char **atts) |
| CB whenever a start tag is seen (private method). | |
| void | xml_charData (void *userData, const XML_Char *s, int len) |
| Handle non-element character strings (private method). | |
| void | xml_startCData (void *userData) |
| Handle the start of CDATA strings (private method). | |
| void | xml_endCData (void *userData) |
| Handle the end of CDATA strings (private method). | |
| void | xmlPush (Stack *st, Element *elem) |
| Push a Node to the top of the stack (private method). | |
| Element * | xmlPop (Stack *st) |
| Return a Node from the top of the stack (private method). | |
| Element * | xmlPeek (Stack *st) |
| Peek at Element on top of the Stack (private method). | |
| Stack * | xml_newStack (void) |
| Makes a new stack (private method). | |
| int | xml_isEmpty (Stack *st) |
| Checks to see if the stack is empty (private method). | |
| void | xml_clearStack (Stack *st) |
| Clear the stack (private method). | |
| void | xml_printStack (Stack *st) |
| Print the name of all the stack elements (private method). |
XMLPARSEP.H -- Internal XML parser definitions.
| char* xml_attrGet | ( | AttrBlock * | ablock, | |
| char * | name | |||
| ) |
Get an attribute's value (private method).
xml_attrGet -- Get an attribute's value (private method).
| *ablock | An AttrBlock to insert these attributes | |
| *name | A string that hold the name of an attribute |
| int xml_attrSet | ( | AttrBlock * | ablock, | |
| char * | name, | |||
| char * | value | |||
| ) |
Set/Create an attributes (private method).
***************************************************************************
Public Internal Methods. The procedures are used to implement the library, however are not part of the public interface.
xml_attrSet -- Set/Create an attributes (private method).
| ablock | An AttrBlock to insert these attributes. | |
| name | A string that hold the name of an attribute. | |
| value | A string that hold the value of an attribute. |
| char* xml_attrXML | ( | AttrBlock * | ablock | ) |
Get the attributes for an XML tag (private method).
Get names of the attributes for an XML tag (private method).
xml_attrXML -- Get the attributes for an XML tag (private method).
| *ablock | An AttrBlock to insert these attributes |
| *ablock | An AttrBlock to insert these attributes |
| void xml_charData | ( | void * | user, | |
| const XML_Char * | s, | |||
| int | len | |||
| ) |
Handle non-element character strings (private method).
xml_charData -- Handle non-element character strings (private method)
| user | User data (not used) | |
| s | content string | |
| len | length of string |
| xml_clearStack | ( | Stack * | st | ) |
Clear the stack (private method).
xml_clearStack -- Clear the stack (private method)
| st | A pointer to a Stack |
| char* xml_elemName | ( | Element * | e | ) |
| int xml_elemType | ( | Element * | e | ) |
| char* xml_elemXML | ( | Element * | e | ) |
Builds a string of the opening XML Tag (private method).
xml_elemXML -- Builds a string of the opening XML Tag (private method)
| *e | A pointer to an Element |
| char* xml_elemXMLEnd | ( | Element * | e | ) |
Build a string of the ending XML Tag (private method).
xml_elemXMLEnd -- Build a string of the ending XML Tag (private method)
| *e | A pointer to an Element |
| void xml_endCData | ( | void * | user | ) |
Handle the end of CDATA strings (private method).
xml_endCData -- Handle the end of CDATA strings (private method)
| user | User data (not used) |
| void xml_endElement | ( | void * | user, | |
| const char * | name | |||
| ) |
CB whenever an end tag is seen (private method).
xml_endElement -- CB whenever an end tag is seen (private method)
| user | User data (not used) | |
| name | The name in the XML tag |
| int xml_eType | ( | char * | name | ) |
Get the integer value (ID) of the name (private method).
xml_eType -- Get the integer value (ID) of the name (private method).
| name | Name of the desired type |
| void xml_freeHandle | ( | handle_t | handle | ) |
Free a handle for use (private method).
xml_freeHandle -- Free a handle for use (private method)
| handle | A handle_t to the Element you wish to free |
| Element* xml_getElement | ( | handle_t | handle | ) |
| void xml_handleCleanup | ( | void | ) |
Free all the handle nodes (private method).
xml_handleCleanup -- Free all the handle nodes (private method)
| int xml_handleCount | ( | void | ) |
Get the number of handle_t used (private method).
count of current used handles xml_handleCount -- Get the number of handle_t used (private method)
| void xml_handleError | ( | char * | msg | ) |
Print an error message.
xml_handleError -- Print an error message.
| int xml_isEmpty | ( | Stack * | st | ) |
Checks to see if the stack is empty (private method).
xml_isEmpty -- Checks to see if the stack is empty (private method)
| st | A pointer to a Stack |
| handle_t xml_lookupHandle | ( | Element * | elem | ) |
| Element* xml_newElem | ( | unsigned int | type | ) |
| void xml_newHandleTable | ( | void | ) |
Initialize a handle table (private method).
xml_newHandleTable -- Initialize a handle table (private method)
| Stack * xml_newStack | ( | void | ) |
Makes a new stack (private method).
xml_newStack -- Makes a new stack (private method)
| xml_printStack | ( | Stack * | st | ) |
Print the name of all the stack elements (private method).
xml_printStack -- Print the name of all the stack elements (private method)
| st | A pointer to a Stack |
| handle_t xml_setHandle | ( | Element * | elem | ) |
| void xml_startCData | ( | void * | user | ) |
Handle the start of CDATA strings (private method).
xml_startCData -- Handle the start of CDATA strings (private method)
| user | User data (not used) |
| void xml_startElement | ( | void * | user, | |
| const char * | name, | |||
| const char ** | atts | |||
| ) |
CB whenever a start tag is seen (private method).
xml_startElement -- CB whenever a start tag is seen (private method)
| user | User data (not used) | |
| name | The name in the XML tag. | |
| atts | An array of attributes. |


Machine Learning, wireless communication, and information theory
Gholamali Aminian received the B.Sc. degree in electrical engineering from Amirkabir University, Tehran, Iran, in 2010, and M.Sc. and Ph.D degrees in electrical engineering from Sharif University of Technology, Tehran, Iran, in 2012 and 2017, respectively. He is awarded the Newton international Fellowship by Royal Society and he is now Honorary Research Fellow at UCL under supervision of Prof. Miguel Rodrigues.


Class constructor Create the new env settings
Set the express app
Set the express app
Get the server object
Set the server object
Get the event emitter
Get the server object
Get the express app
Handle any uncaught errors
Init the server
Start the server and listen to the required port
Register any middleware
Register any relevant paths here
Shutdown the server
Generated using TypeDoc
The core server component Creates the express application


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Childhood sweethearts both diagnosed with lung cancer weeks apart
Childhood sweethearts who have been together for decades face the fight of their lives after both received lung cancer diagnoses just weeks apart.
Lisa and Seth Doyle have been together since they were 18, but they have known each each other since they were 14-years-old in Gloucester, Virginia.
They said they have gone through good times and bad times together – although nothing as difficult as the cancer diagnosis they both received just five weeks apart.
Lisa was diagnosed with lung cancer in July after several persistent bouts of bronchitis.
She told WAVY that the news did not register right away, saying: ‘The doctor said: ‘I’ve been looking at your scans all afternoon and I’m sorry, it’s lung cancer.’
Seth was optimistic that they would get through wife Lisa’s treatment together – but then he got similar news that was even worse.
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‘But then things took a turn, because my husband was also diagnosed with the same lung cancer. His is terminal, it spread to his brain. He has 14 tumors in his body,’ Lisa said.
Seth added: ‘I may have a year, a year and a half. I’m scared of what’s going to happen to her, I’m not scared about me dying because I’m going to a better place.’
‘I’m scared of leaving her here… all by herself, sick, bills rolling in, that’s what scares me the most.’ The couple previously smoked, but have given up, and were exposed to asbestos at work. But no concrete evidence of what caused both to contract the disease was given by doctors.
They now visit the hospital together, and have shocked staff there with their resilience.
‘I was giving him the thumbs up, he’s all prepped for surgery, with his blue hat on, I went in first,’ Lisa said.
‘We wake up in recovery together and you have nurses coming up saying ‘Oh my god, really?’
She said she has put her chemotherapy on hold as her husband continues radiation.
‘I’ve known him since I was 14, been together since we were 18, I can’t sit back and do treatment and be fighting for my life and be a positive to live as I watch him die,’ Lisa said.
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‘It’s a chance I’m willing to take, I can’t have both of us back in there laying in the bed. He says he wants me to be happy again, he wants me to go into remission and have a happy life.’
Seth said: ‘If something happens to me, she’s still young enough. So, it’s not looking good for me, so why should she hold off on her treatment, when I’m not looking anyway? And I think she would, if something happens to me, she’s still young enough.’
Friends and family are raising money for the Doyles, which can be donated on Facebook.


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Desinged by Vicky Markantoni.
Copyright © 2014 Chris Hatzilenas.
All Rights Reserved.


Here at VRTech we take pride in producing quality virtual reality (VR) software and applications that are widely used within North America and Europe. Our company was recently contracted to design a VR application that aims to teach and inspire individuals to explore the planets of our solar system as well as other known stars within the Milky Way galaxy. The purpose of this report is to identify user needs and establish user requirements pertaining to the application, from the perspective of Human Computer Interaction.
Currently there does not exist an app with detailed mapping of the Milky Way Galaxy that provides support for VR gear. Furthermore, the few existing apps that contain mappings of space provide very limited functionality with respect to navigation. They either have clunky controls for navigating the galaxy, or severely restrict the movement of the user. For example, 3D Galaxy Map app allows rotating the perspective while viewing the Milky Way galaxy, as well as zooming in towards the Solar System, and zooming out so that the entire galaxy is visible. However, it does not allow to choose different points in the galaxy for closer viewing. Other apps, such as Celestia, allow closing in on any object that is part of the app’s database. However, they make it difficult to navigate the galaxy. The user either needs to know the coordinates or the name of the celestial body, which have to be entered in order to change the focus. Furthermore, it is impossible to rotate the perspective without typing in the values for latitude and longitude for the celestial body in question. This severely limits the quality of user experience, making the virtual travel feel very restricted and artificial.
The project includes the design of the user interface for the VR application. The design is to be based on the needs of the potential users. Two detailed personas have been created to account for the types of people who are most likely to take interest in the application. The project also spells out four scenarios based on the two personas, which provide examples of ways the users may use the application. Finally, a Hierarchical Task Analysis is performed on each scenario, detailing the steps the users would need to take to accomplish their goals. The project does not include technical details and coding aspects required to implement the app.


{% extends "secu/base.html" %} {% block content %} {% if users %}
You have {{ bitbars }} bitbars.
{% else %}We are the most trusted crypto-currency on the Internet. Unlike Bitcoin which is unreliable due to its decentralized nature, we store all your valuable bits in a single secured SQLite database on our server. Everything is powered by Ruby on Rails so you know that it is safe. Sign up for an account today!
{% endif %} {% endblock %}


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See:
Description
| Packages | |
|---|---|
| org.apache.avro | Avro kernel classes. |
| org.apache.avro.compiler.idl | |
| org.apache.avro.compiler.specific | |
| org.apache.avro.file | A container file for Avro data. |
| org.apache.avro.generic | A generic representation for Avro data. |
| org.apache.avro.io | Utilities for Encoding and Decoding Avro data. |
| org.apache.avro.io.parsing | Implementation of Avro schemas as LL(1) grammars. |
| org.apache.avro.ipc | Support for inter-process calls. |
| org.apache.avro.ipc.generic | |
| org.apache.avro.ipc.reflect | |
| org.apache.avro.ipc.specific | |
| org.apache.avro.ipc.stats | Utilities to collect and display IPC statistics. |
| org.apache.avro.ipc.trace | |
| org.apache.avro.mapred | Run Hadoop MapReduce jobs over Avro data, with map and reduce functions written in Java. |
| org.apache.avro.mapred.tether | Run Hadoop MapReduce jobs over Avro data, with map and reduce functions run in a sub-process. |
| org.apache.avro.mojo | |
| org.apache.avro.reflect | Use Java reflection to generate schemas and protocols for existing classes. |
| org.apache.avro.specific | Generate specific Java classes for schemas and protocols. |
| org.apache.avro.tool | Avro command-line tool. |
| org.apache.avro.util | Common utility classes. |
Avro is a data serialization system.
Avro provides:
Avro relies on schemas
.
When Avro data is read, the schema used when writing it is always
present. This permits each datum to be written with no per-value
overheads, making serialization both fast and small. This also
facilitates use with dynamic, scripting languages, since data,
together with its schema, is fully self-describing.
When Avro data is stored in a file
, its schema is stored with
it, so that files may be processed later by any program. If the
program reading the data expects a different schema this can be
easily resolved, since both schemas are present.
When Avro is used in RPC
, the client
and server exchange schemas in the connection handshake. (This
can be optimized so that, for most calls, no schemas are actually
transmitted.) Since both client and server both have the other's
full schema, correspondence between same named fields, missing
fields, extra fields, etc. can all be easily resolved.
Avro schemas are defined with with JSON . This facilitates implementation in languages that already have JSON libraries.
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SKIP 0 — Purpose and Process¶
- Author
Jarrod Millman<EMAIL_ADDRESS>- Author
Juan Nunez-Iglesias<EMAIL_ADDRESS>- Author
Stéfan van der Walt<EMAIL_ADDRESS>- Status
Active
- Type
Process
- Created
2019-07-30
What is a SKIP?¶
SKIP stands for SciKit-Image Proposal. A SKIP is a design document providing information to the community, or describing a new feature for scikit-image or its processes or environment. The SKIP should provide a rationale for the proposed change as well as a concise technical specification, if applicable.
We intend SKIPs to be the primary mechanisms for proposing major new features, for collecting community input on an issue, and for documenting the design decisions that have gone into scikit-image. The SKIP author is responsible for building consensus within the community and documenting dissenting opinions.
Because the SKIPs are maintained as text files in a versioned repository, their revision history is the historical record of the feature proposal 1.
Types¶
There are three kinds of SKIPs:
A Standards Track SKIP describes a new feature or implementation for scikit-image.
An Informational SKIP describes a scikit-image design issue, or provides general guidelines or information to the Python community, but does not propose a new feature. Informational SKIPs do not necessarily represent a scikit-image community consensus or recommendation, so users and implementers are free to ignore Informational SKIPs.
A Process SKIP describes a process surrounding scikit-image, or proposes a change to (or an event in) a process. Process SKIPs are like Standards Track SKIPs but apply to areas other than the scikit-image library itself. They may propose an implementation, but not to scikit-image’s codebase; they require community consensus. Examples include procedures, guidelines, changes to the decision-making process, and changes to the tools or environment used in scikit-image development. Any meta-SKIP is also considered a Process SKIP.
SKIP Workflow¶
The SKIP process begins with a new idea for scikit-image. A SKIP should contain a single key proposal or new idea. Small enhancements or patches often don’t need a SKIP and can be injected into the scikit-image development workflow with a pull request to the scikit-image repo. The more focused the SKIP, the more likely it is to be accepted.
Each SKIP must have a champion—someone who writes the SKIP using the style and format described below, shepherds the discussions in the appropriate forums, and attempts to build community consensus around the idea. The SKIP champion (a.k.a. Author) should first attempt to ascertain whether the idea is suitable for a SKIP. Posting to the scikit-image mailing list is the best way to do this.
The proposal should be submitted as a draft SKIP via a GitHub pull
request to the doc/source/skips
directory with the name
skip-<n>.rst
where <n>
is an appropriately assigned number (e.g.,
skip-35.rst
). The draft must use the SKIP X — Template and Instructions file.
Once the PR is in place, the SKIP should be announced on the mailing list for discussion (comments on the PR itself should be restricted to minor editorial and technical fixes).
At the earliest convenience, the PR should be merged (regardless of whether it is accepted during discussion). A SKIP that outlines a coherent argument and that is considered reasonably complete should be merged optimistically, regardless of whether it is accepted during discussion. Additional PRs may be made by the author to update or expand the SKIP, or by maintainers to set its status, discussion URL, etc.
Standards Track SKIPs consist of two parts, a design document and a reference implementation. It is generally recommended that at least a prototype implementation be co-developed with the SKIP, as ideas that sound good in principle sometimes turn out to be impractical. Often it makes sense for the prototype implementation to be made available as PR to the scikit-image repo, as long as it is properly marked as WIP (work in progress).
Review and Resolution¶
SKIPs are discussed on the mailing list. The possible paths of the status of SKIPs are as follows:
All SKIPs should be created with the Draft
status.
Eventually, after discussion, there may be a consensus that the SKIP
should be accepted – see the next section for details. At this point
the status becomes Accepted
.
Once a SKIP has been Accepted
, the reference implementation must be
completed. When the reference implementation is complete and incorporated
into the main source code repository, the status will be changed to Final
.
To allow gathering of additional design and interface feedback before committing to long term stability for a language feature or standard library API, a SKIP may also be marked as “Provisional”. This is short for “Provisionally Accepted”, and indicates that the proposal has been accepted for inclusion in the reference implementation, but additional user feedback is needed before the full design can be considered “Final”. Unlike regular accepted SKIPs, provisionally accepted SKIPs may still be Rejected or Withdrawn even after the related changes have been included in a release.
Wherever possible, it is considered preferable to reduce the scope of a proposal to avoid the need to rely on the “Provisional” status (e.g. by deferring some features to later SKIPs), as this status can lead to version compatibility challenges in the wider ecosystem.
A SKIP can also be assigned status Deferred
. The SKIP author or a
core developer can assign the SKIP this status when no progress is being made
on the SKIP.
A SKIP can also be Rejected
. Perhaps after all is said and done it
was not a good idea. It is still important to have a record of this
fact. The Withdrawn
status is similar—it means that the SKIP author
themselves has decided that the SKIP is actually a bad idea, or has
accepted that a competing proposal is a better alternative.
When a SKIP is Accepted
, Rejected
, or Withdrawn
, the SKIP should be
updated accordingly. In addition to updating the status field, at the very
least the Resolution
header should be added with a link to the relevant
post in the mailing list archives.
SKIPs can also be Superseded
by a different SKIP, rendering the
original obsolete. The Replaced-By
and Replaces
headers
should be added to the original and new SKIPs respectively.
Process SKIPs may also have a status of Active
if they are never
meant to be completed, e.g. SKIP 0 (this SKIP).
How a SKIP becomes Accepted¶
A SKIP is Accepted
by consensus of all interested contributors. We
need a concrete way to tell whether consensus has been reached. When
you think a SKIP is ready to accept, send an email to the
scikit-image mailing list with a subject like:
Proposal to accept SKIP #<number>: <title>
In the body of your email, you should:
link to the latest version of the SKIP,
briefly describe any major points of contention and how they were resolved,
include a sentence like: “If there are no substantive objections within 7 days from this email, then the SKIP will be accepted; see SKIP 0 for more details.”
For an equivalent example in the NumPy library, see: https://mail.python.org/pipermail/numpy-discussion/2018-June/078345.html
After you send the email, you should make sure to link to the email
thread from the Discussion
section of the SKIP, so that people can
find it later.
Generally the SKIP author will be the one to send this email, but anyone can do it – the important thing is to make sure that everyone knows when a SKIP is on the verge of acceptance, and give them a final chance to respond. If there’s some special reason to extend this final comment period beyond 7 days, then that’s fine, just say so in the email. You shouldn’t do less than 7 days, because sometimes people are travelling or similar and need some time to respond.
In general, the goal is to make sure that the community has consensus, not provide a rigid policy for people to try to game. When in doubt, err on the side of asking for more feedback and looking for opportunities to compromise.
If the final comment period passes without any substantive objections,
then the SKIP can officially be marked Accepted
. You should send a
followup email notifying the list (celebratory emoji optional but
encouraged 🎉✨), and then update the SKIP by setting its :Status:
to Accepted
, and its :Resolution:
header to a link to your
followup email.
If there are substantive objections, then the SKIP remains in
Draft
state, discussion continues as normal, and it can be
proposed for acceptance again later once the objections are resolved.
In unusual cases, when no consensus can be reached between core developers, the
scikit-image Steering Council may be asked to decide whether a controversial
SKIP is Accepted
.
Maintenance¶
In general, Standards track SKIPs are no longer modified after they have reached the Final state, as the code and project documentation are considered the ultimate reference for the implemented feature. They may, however, be updated under special circumstances.
Process SKIPs may be updated over time to reflect changes to development practices and other details. The precise process followed in these cases will depend on the nature and purpose of the SKIP being updated.
Format and Template¶
SKIPs are UTF-8 encoded text files using the reStructuredText format. Please see the SKIP X — Template and Instructions file and the reStructuredTextPrimer for more information. We use Sphinx to convert SKIPs to HTML for viewing on the web 2.
Header Preamble¶
Each SKIP must begin with a header preamble. The headers
must appear in the following order. Headers marked with *
are
optional. All other headers are required.
:Author: <list of authors' real names and optionally, email addresses>
:Status: <Draft | Active | Accepted | Deferred | Rejected |
Withdrawn | Final | Superseded>
:Type: <Standards Track | Process>
:Created: <date created on, in dd-mmm-yyyy format>
* :Requires: <skip numbers>
* :skimage-Version: <version number>
* :Replaces: <skip number>
* :Replaced-By: <skip number>
* :Resolution: <url>
The Author header lists the names, and optionally the email addresses of all the authors of the SKIP. The format of the Author header value must be
Random J. User<EMAIL_ADDRESS>if the email address is included, and just
Random J. User
if the address is not given. If there are multiple authors, each should be on a separate line.
References and Footnotes¶
- 1
This historical record is available by the normal git commands for retrieving older revisions, and can also be browsed on GitHub.
- 2
The URL for viewing SKIPs on the web is https://scikit-image.org/skips/index.html
Copyright¶
This document has been placed in the public domain.


I have been a software engineer for most of my working life, primarily in the newspaper industry. I've recently retired and now live in both Eugene Oregon and Bremen Germany.
I received a BA in Physics from the University of Oregon and later a Masters degree in Computer Science.
I've been using Python since 1995 and it has been by far my favorite programming language since then. At the newspaper where I worked (The Register Guard) we used it whenever we could, and especially with tools such as Django.
I have been part of the open source community. I was a co-author for the book "How to Think like a Computer Scientist (Python)" along with Allen Downey and Jeff Elkner in 2002. I also have a web page Python for Fun aimed at intermediate programmers and students.
This latest project with Philip has been fun and challenging. Online Python Tutor has been a great success in helping people visualize code running and we hope this addition will help with the visualization of whole algorithms running as well.


Thapar University
NHRD RANKING
FEES
placement
60
60
60
Infrastructure:A+
thapar.edu
Thapar University
NHRD RANKING
FEES
placement
60
60
60
Infrastructure:A+
LINK


abstract fun requires(command: Command, subsystem: Subsystem): Unit
This should ensure that a given Command can take control of a given Subsystem.
command - the Command to check
command
subsystem - the Subsystem to check
subsystem


workbox-range-requests
module
Version
v2.1.2
workbox-range-requests
A helper library that instructs a service worker respond to HTTP requests that include a Range: header with a subset of a full response.
If you are not already using Workbox, this library can be used in a standalone form via workbox.rangeRequests.handleRangeRequest.
If you are using Workbox for routing or request handling already, then CacheRangeResponsePlugin will offer the easiest integration.
If your cached resources are large, use caution when adding this library. Some browsers need to read the entire resource into memory before it can be modified to respond to the request.
Inspired by
- https://github.com/jakearchibald/range-request-test/blob/master/static/sw.js
- https://github.com/GoogleChrome/sample-media-pwa/blob/master/src/client/scripts/ranged-response.js


Magister Papiku:
Do you know that the airship is a part of the ancient Giants' legacy? Apparently they they left behind quite a few relics in Gracia. Most of the continent has been devastated, but perhaps Keucereus will be able to use these relics to prevail. A surprising twist, isn't it?
Now what brought you here, adventurer?
Show him High Priest Orven's letter.


“systemd is a suite of basic building blocks for a Linux system. It provides a system and service manager that runs as PID 1 and starts the rest of the system." - freedesktop.org
systemd was originally designed as a replacement for SysVInit.
Allowing for faster booting, better power management and easier to maintain boot configuration.
As of 2018, the majority of Linux distributions have adopted systemd as their default init system.
There are still niche systems that use SysVInit.
Unit files describe the desired system state for a Linux system using systemd. The main types of unit files are:
A configuration file that tells systemd about a process you want to run on the system.
Processes started by systemd will be controlled and supervised allowing for automatic restarts on failure, starting of dependencies, and resource usage controls.
[Unit]
Description=OpenSSH Daemon
After=network.target
[Service]
ExecStartPre=/usr/sbin/sshd-gen-keys-start
ExecStart=/usr/sbin/sshd
ExecReload=/bin/kill -HUP $MAINPID
EnvironmentFile=/etc/sysconfig/ssh
Restart=always
MemoryLimit=1G
[Install]
WantedBy=multi-user.target
Target unit files describe a desired system state. I.E Specific process running, mount points activated, network on etc...
They do this by referencing other unit files such as service unit files.
Once the kernel has passed control to systemd during boot, systemd will then try to to get to the default target state. Common targets are:
If you want your service to be automatically started by systemd, it must be added to a target.
In order of precedence.
/lib/systemd/system
/usr/lib/systemd/system
/etc/systemd/system
If you want to override or customise a unit file, do it in /etc/systemd/system as it won't be overridden by the package manager.
systemctl // List all loaded unit files
systemctl start [servicename] // Start a service
systemctl stop [servicename] // Stop a service
systemctl enable [servicename] // Adds the service to the target described in the service file. Commonly enables on startup
systemctl disable [servicename] // Removes the service from the target. Commonly disables on startup
systemctl status [servicename] // Show stats about the service, Started? failed? Resource usage, Last log output


Nowledge November Quiz
Certificate of completion will be given if score is atleast 50%. You can always play again.
Total Score: ...
Percentage: ... %
Certificate of completion will be given if score is atleast 50%. You can always play again.
Total Score: ...
Percentage: ... %