https://speakerdeck.com/claudijd/attacking-cloud-services-with-source-code
https://devco.re/blog/2019/01/16/hacking-Jenkins-part1-play-with-dynamic-routing-en/
https://devco.re/blog/2019/02/19/hacking-Jenkins-part2-abusing-meta-programming-for-unauthenticated-RCE-en/
complete
https://github.com/cxxr/talks/blob/master/2017/nolacon/Attacking%20Modern%20SaaS%20Companies%20%E2%80%93%20NolaCon.pdf
http://carnal0wnage.attackresearch.com/2019/02/jenkins-decrypting-credentialsxml.html?m=1
https://stackoverflow.com/questions/6988849/how-to-reset-jenkins-security-settings-from-the-command-line


| 162 | (A) | That Ilke worthily woman that I firste neuynnede |
| 157 | (C) | ¶ And þenne þis wordy wyfe . of whom I fyrst tolde |
| 158 | (D) | And þan þis worthi wyf of whom y ferst told |
| 156 | (E) | ¶ And ȝit hath þis wurthi wif . of whom y arst tolde |
| (Ex) | ---- no text ---- | |
| 161 | (L) | & þat worliche wif þat arst was ynempned |
| 155 | (P) | þat ilke worthy wyfe þat I are neuende |
| 157 | (U) | And than this worthly wyf / of whom . I . frist tolde |
| (V) | ---- no text ---- |


West Beirut ***
not rated Cowboy Booking International 105 minutes in Lebanese with English subtitles starring Rami Doueiri, Mohamad Chamas, Rola Al Amin, Carmen Lebbos, Joseph Bou Nassar, Liliane Nemry, Leila Karam written and directed by Ziad Doueiri
Ziad Doueiri is best known in the U.S. for being the cameraman for Quentin Tarantino's films. But there is a story behind every person (even in Hollywood). Doueiri has used his filmmaking experience to bring his true childhood experiences to the screen in the poignant "West Beirut". The film takes place in Beirut, Lebanon in 1975, where a civil war is breaking out. For Tarek (Rami Doueiri) and Omar (Mohamad Chamas), the cancellation of school brings a newfound freedom. They roam the streets of the war-torn city, making Super 8 films and generally causing mischief. The kids don't realize the seriousness of the war, which has separated their city into two sections; East (Christian) and West (Muslim) Beirut. Doueiri also focuses on the tensions surrounding Tarek's parents. His father (Joseph Bou Nassar) has faith in Beirut and will not leave, while his mother (Carmen Lebbos) is overcome with tension and stays only because she seems to have no choice. For most of its 105 minute running time, "West Beirut" is a vivid, involving slice of life showing us a city in turmoil. However, in the final third of the film, the lack of a clear plot undermines the realism, and the characters find themselves in far-fetched situations. I would rather have had Doueiri let the story tell itself. In the press notes, Doueiri remarks that he made the film from memory of certain images, and not from memory of a story. But the images are definitely there, and "West Beirut" is at times very moving. The story behind the film is just as interesting as the film itself. For the child actors, Doueiri chose his brother, Rami, to play his alter-ego, and chose Mohamad Chamas, a penniless orphan, to play his childhood friend. Chamas now lives in a shack in a Beirut refugee camp. His only close relative, a brother, is in jail. The images in "West Beirut" are therefore very real. Ziad Doueri's debut film is flawed, but it is a coming-of-age picture made with care and relevance. In the early 1980's, Doueiri fled Lebanon and went to USC Film School. Others will never be that lucky, and this film is for them.
a capsule review by Akiva Gottlieb, The Teenage Movie Critic<EMAIL_ADDRESS>http://teenagemoviecritic.8m.com
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


This page provides a security mechanism that prevents unauthorized users from accessing the system. In order to get into the ShipConsole, the user must provide a valid username and password provided by the ShipConsole Admin. The following screenshot shows the login page.
Figure 1.1
Input Validations:
Username can have combination of Characters and Numbers but Special Characters are not allowed.
Password can have combination of Characters, Special Characters and Numbers.
UserName : Uniquely identifies a user
Password : Confidential that is known only to its user.
Login : This button validates username and password.
Download QZ Tray for Windows: This link is used to download QZ tray for Windows OS system to use Weighing Scale and Printer
Download QZ Tray for MAC : This link is used to download QZ tray for MAC OS system to use Weighing Scale and Printer
Forgot Password:This provides password for specific user.
The ShipConsole Admin user credentials are provided by the AppsAssociates Pvt Ltd. User must enter username and password, then click on Login button as shown below in Figure1.2
Figure 1.2
If user provides valid login details then it navigates to ShipConsole Admin Index Page, Otherwise error message is displayed and captcha is given as shown in Figure 1.3
Figure 1.3
If user forgets password then password can be reset using Forgot Password. When clicked on Forgot Password, the following popup is opened as shown in Figure 1.4
Figure 1.4
• Once user name(email id) is entered, click on GetPassword button. It sends the new password to the respective registered email-id and success message is displayed as shown in Figure 1.5
Figure 1.5
• After clicking GetPassword button, If user name is invalid then appropriate message will be displayed as shown in Figure 1.6 and Figure 1.7 respectively.
Figure 1.6
Figure 1.7
Client Admin:
ShipConsole Admin creates Client Admin. Username and Password are given to Client Admin. Using these “User Details” i.e. Username and Password, Client Admin will be logged in. On successful login, his first name and last name will be shown on top left corner of Client Admin Home page. In below Client Admin Home page (Figure 1.8) “JOHN” is Client Admin's First name and “Rees” is his last name.
Figure 1.8
Live data with the graphs is displayed on the home screen . The graph details are displayed for the client admin for all the locations , carrier wise.
1. Pie Chart that represents number of shipments shipped for a month,carrier wise i.e, previous one month from previous day of the present month to the last month. Eg: if present date is 9 March 2016 then the graph displays the data from 8 Feb 2016 to 8 March 2016.
2. The other chart is a Bar Graph represents freight charges for a month, carrier wise i.e, previous one month from previous day of the present month to the last month. Eg: if present date is 9 March 2016 then the graph displays the data from 8 Feb 2016 to 8 March 2016.
Client Admin has the following responsibilities:
Options
Carriers
Package Dimensions
Create Users
Ship To Location
Ship From Location
In this page if you click on “User” icon, there will be different links. For details see Chapter 7


item1
item2
folder 1
folder 2
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folder 12


how to install the new vierson i google chroom? - Better Battlelog Forums #68607
Sitemap
10. December 2012 17:44
Topicstarter
maor11212
how to install the new vierson i google chroom?
i want the newset vierosn and whan i dowlnand form the webiste
i cant to install it beazcue the google chroom dont allow to me
what should i do?pls hurry
Ty for the helpers
10. December 2012 19:22
xXJumpyXx
Helping Hand
Give the tutorial video we have a try :)
http://youtu.be/jlyIZEN-2yQ


Hi, I’m James. I specialise in creating fully custom websites for small business and individuals. If you are looking to work together or just start a conversation, kindly get in touch


Wiki ▸ [[API Reference]] ▸ [[Time]] ▸ Time Intervals
Time intervals are irregular! For example, there are 60 seconds in a minute, but 24 hours in a day. Even more confusing, some days have 23 or 25 hours due to daylight saving time, and the standard Gregorian calendar uses months of differing lengths. And then there are leap years and leap seconds!
To simplify manipulation of and iteration over time intervals, D3 provides a handful of time utilities in addition to the time scale and format. The utilities support both local time and UTC time. Local time is determined by the browser’s JavaScript runtime; arbitrary time zone support would be nice, but requires access to the Olson zoneinfo files.
# d3.time.interval
Returns the specified interval. The following intervals are supported:
# interval(date)
Alias for interval.floor(date). For example, d3.time.day(new Date())
returns midnight (12:00 AM) on the current day, in local time.
# interval.floor(date)
Rounds down the specified date, returning the latest time interval before or equal to date. For example, d3.time.day.floor(new Date())
returns midnight (12:00 AM) on the current day, in local time.
# interval.round(date)
Rounds up or down the specified date, returning the closest time interval to date. For example, d3.time.day.round(new Date())
returns midnight (12:00 AM) on the current day if it is on or before noon, and midnight of the following day if it is after noon.
# interval.ceil(date)
Rounds up the specified date, returning the earliest time interval after or equal to date. For example, d3.time.day.ceil(new Date())
returns midnight (12:00 AM) on the following day, in local time (unless you happen to run this code at exactly midnight, in which case it returns the current time).
# interval.range(start, stop[, step])
Returns every time interval after or equal to start and before stop. If step is specified, then every step‘th interval will be returned, based on the interval number (such as day of month for d3.time.day). For example, a step of 2 will return the 1st, 3rd, 5th etc. of the month with d3.time.day.
# interval.offset(date, step)
Returns a new date equal to date plus step intervals. If step is negative, then the returned date will be before the specified date; if step is zero, then a copy of the specified date is returned. This method does not round the specified date to the interval. For example, if it is currently 5:34 PM, then d3.time.day.offset(new Date(), 1)
returns 5:34 PM tomorrow (even if Daylight Savings Time changes!).
# interval.utc
Returns a corresponding time interval in UTC rather than local time. For example, d3.time.day.range(start, stop)
returns local time days between start and stop, while d3.time.day.utc.range(start, stop)
returns UTC days between start and stop.
# d3.time.second
Seconds (e.g., 01:23:45.0000 AM). Always 1,000 milliseconds long.
# d3.time.minute
Minutes (e.g., 01:02:00 AM). Most browsers do not support leap seconds, so minutes are almost always 60 seconds (6e4 milliseconds) long.
# d3.time.hour
Hours (e.g., 01:00 AM). 60 minutes long (36e5 milliseconds). Note that advancing time by one hour can return the same hour number, or skip an hour number, due to Daylight Savings Time.
# d3.time.day
Days (e.g., February 7, 2012 at 12:00 AM). Most days are 24 hours long (864e5 milliseconds); however, with Daylight Savings Time, a day may be 23 or 25 hours long.
# d3.time.week
Alias for d3.time.sunday. A week is always 7 days, but ranges between 167 and 169 hours depending on Daylight Savings Time.
# d3.time.sunday
Sunday-based weeks (e.g., February 5, 2012 at 12:00 AM).
# d3.time.monday
Monday-based weeks (e.g., February 6, 2012 at 12:00 AM).
# d3.time.tuesday
Tuesday-based weeks (e.g., February 7, 2012 at 12:00 AM).
# d3.time.wednesday
Wednesday-based weeks (e.g., February 8, 2012 at 12:00 AM).
# d3.time.thursday
Thursday-based weeks (e.g., February 9, 2012 at 12:00 AM).
# d3.time.friday
Friday-based weeks (e.g., February 10, 2012 at 12:00 AM).
# d3.time.saturday
Saturday-based weeks (e.g., February 11, 2012 at 12:00 AM).
# d3.time.month
Months (e.g., February 1, 2012 at 12:00 AM). Ranges between 28 and 31 days.
# d3.time.year
Years (e.g., January 1, 2012 at 12:00 AM). Normal years are 365 days long; leap years are 366.
# d3.time.seconds(start, stop[, step])
Alias for d3.time.second.range. Returns the second boundaries (e.g., 01:23:45 AM) after or equal to start and before stop. If step is specified, then every step‘th second will be returned, based on the second of the minute. For example, a step of 15 will return 9:01:45 PM, 9:02:00 PM, 9:02:15 PM, etc.
# d3.time.minutes(start, stop[, step])
Alias for d3.time.minute.range. Returns the minute boundaries (e.g., 01:23 AM) after or equal to start and before stop. If step is specified, then every step‘th minute will be returned, based on the minute of the hour. For example, a step of 15 will return 9:45 PM, 10:00 PM, 10:15 PM, etc.
# d3.time.hours(start, stop[, step])
Alias for d3.time.hour.range. Returns the hour boundaries (e.g., 01 AM) after or equal to start and before stop. If step is specified, then every step‘th hour will be returned, based on the hour of the day. For example, a step of 3 will return 9 PM, 12 AM, 3 AM, etc.
# d3.time.days(start, stop[, step])
Alias for d3.time.day.range. Returns the day boundaries (midnight) after or equal to start and before stop. If step is specified, then every step‘th date will be returned, based on the day of the month. For example, a step of 2 will return the 1st, 3rd, 5th etc. of the month.
# d3.time.weeks(start, stop[, step])
# d3.time.sundays(start, stop[, step])
# d3.time.mondays(start, stop[, step])
# d3.time.tuesdays(start, stop[, step])
# d3.time.wednesdays(start, stop[, step])
# d3.time.thursdays(start, stop[, step])
# d3.time.fridays(start, stop[, step])
# d3.time.saturdays(start, stop[, step])
Aliases for d3.time.interval.range etc. Returns the week boundaries (midnight Sunday) after or equal to start and before stop. If step is specified, then every step‘th week will be returned, based on the week of the year. For example, a step of 4 will return January 2, January 30, February 27, etc.
# d3.time.months(start, stop[, step])
Alias for d3.time.month.range. Returns the month boundaries (e.g., January 01) after or equal to start and before stop. If step is specified, then every step‘th month will be returned, based on the month of the year. For example, a step of 3 will return January, April, July, etc.
# d3.time.years(start, stop[, step])
Alias for d3.time.year.range. Returns the year boundaries (midnight January 1st) after or equal to start and before stop. If step is specified, then every step‘th year will be returned. For example, a step of 5 will return 2010, 2015, 2020, etc.
# d3.time.dayOfYear(date)
Returns the day number for the given date. The first day of the year (January 1) is always the 0th day. Unlike the d3.time.format’s %j directive, dayOfYear is 0-based rather than 1-based.
# d3.time.weekOfYear(date)
# d3.time.sundayOfYear(date)
# d3.time.mondayOfYear(date)
# d3.time.tuesdayOfYear(date)
# d3.time.wednesdayOfYear(date)
# d3.time.thursdayOfYear(date)
# d3.time.fridayOfYear(date)
# d3.time.saturdayOfYear(date)
Returns the week number for the given date, where weeks start with the given day. The first day of the year (January 1) is always the 0th week. weekOfYear is an alias for sundayOfYear, which is equivalent to d3.time.format’s %U directive. mondayOfYear is equivalent to d3.time.format’s %W directive.


Class DefaultPerformanceTiming
- java.lang.Object
-
- io.fluentlenium.core.performance.DefaultPerformanceTiming
-
- All Implemented Interfaces:
PerformanceTiming
public class DefaultPerformanceTiming extends Object implements PerformanceTiming
Default implementation ofPerformanceTiming
.Via this implementation you can retrieve the W3C Performance Timing event values from the browser relative to the value of the
navigationStart
attribute value, thus it won't return epoch values as querying the corresponding Javascript attribute directly would, but rather handlesnavigationStart
as zero and returns time values passed since that point in time.This implementation executes the query (
window.performance.timing.
) with a simpleJavascriptExecutor
in a synchronous way.If a query for a certain metric returns 0 it means it happened at the same moment (at least in epoch) than
navigationStart
.A query for a certain metrics returns a negative value if the event has not been registered on the page, or it is not feasible/valid for the given page/page load/redirect.
-
-
Constructor Summary
Constructors Constructor Description DefaultPerformanceTiming(org.openqa.selenium.WebDriver driver)
-
Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description long
getEventValue(PerformanceTimingEvent event)
Returns the value for the argument event type.PerformanceTimingMetrics
getMetrics()
Return all timing metrics, in particular thewindow.performance.timing
object wrapped in aPerformanceTimingMetrics
object.Object
secureConnectionStart()
Returns the value that corresponds to thesecureConnectionStart
event.-
Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
-
Methods inherited from interface io.fluentlenium.core.performance.PerformanceTiming
connectEnd, connectEnd, connectStart, connectStart, domainLookupEnd, domainLookupEnd, domainLookupStart, domainLookupStart, domComplete, domComplete, domContentLoadedEventEnd, domContentLoadedEventEnd, domContentLoadedEventStart, domContentLoadedEventStart, domInteractive, domInteractive, domLoading, domLoading, fetchStart, fetchStart, getEventValue, loadEventEnd, loadEventEnd, loadEventStart, loadEventStart, navigationStart, navigationStart, redirectEnd, redirectEnd, redirectStart, redirectStart, requestStart, requestStart, responseEnd, responseEnd, responseStart, responseStart, secureConnectionStart, unloadEventEnd, unloadEventEnd, unloadEventStart, unloadEventStart
-
-
-
-
Method Detail
-
getEventValue
public long getEventValue(PerformanceTimingEvent event)
Description copied from interface:PerformanceTiming
Returns the value for the argument event type.- Specified by:
getEventValue
in interfacePerformanceTiming
- Parameters:
event
- the event, never null- Returns:
- the event value
-
secureConnectionStart
public Object secureConnectionStart()
Description copied from interface:PerformanceTiming
Returns the value that corresponds to thesecureConnectionStart
event.- Specified by:
secureConnectionStart
in interfacePerformanceTiming
- Returns:
- the epoch time for the
secureConnectionStart
event
-
getMetrics
public PerformanceTimingMetrics getMetrics()
Description copied from interface:PerformanceTiming
Return all timing metrics, in particular thewindow.performance.timing
object wrapped in aPerformanceTimingMetrics
object.- Specified by:
getMetrics
in interfacePerformanceTiming
- Returns:
- the performance timing metrics
-
-


Portfolio for Ben Moore
About
Projects
Contact
Beginner Web Designer
Just starting out with UI/UX design.
Projects
Contact Me


Skip to main content
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Poem Text Generation (poemgen.py, jolastic.py)¶
These functions generate the actual text of poems.
-
generativepoetry.poemgen.
print_poem
(poem: str)¶ Print the poem with a newline before and after so it’s easy to take a screenshot of its ‘recipe’ and the poem in your terminal and share it. :)
- Parameters
poem – the poem, as a string, to be printed


Yelpme4square
Search with Foursquare
Search with Yelp
© Application creator: Matthieu Van Wambeke. All rights reserved.


Before Change
from sphfile import SPHFile
sph = SPHFile(current_file["audio"])
y = sph.content
sample_rate_ = sph.format["sample_rate"]
if sample_rate is not None and sample_rate_ != sample_rate:
y = librosa.resample(y, sample_rate_, sample_rate)
else:
sample_rate = sample_rate_
After Change
// and load it from here...
from sphfile import SPHFile
sph = SPHFile(current_file["audio"])
with tempfile.NamedTemporaryFile() as f:
sph.write_wav(f.name)
y, sample_rate = librosa.load(f.name, sr=sample_rate, mono=False)
// all other files
else:
y, sample_rate = librosa.load(current_file["audio"],
sr=sample_rate,
mono=False)


Development and Deployment
SUGAR is currently in active development and subject to change. We are committed to delivering a feature complete version of the components by the end of 2017.
For upcoming features and development direction see the roadmap
Source Repositories
All source code is provided under the Apache License, Version 2.0 and is hosten on GitHub. We welcome pull requests for bug fixes and engagement in discussion on feature development.
API Service
The SUGAR API Service is build using ASP.NET Core (MVC/WebAPI).
Currently the service is built for the .NETCoreApp 2.0 target so will only run on Windows systems, however this will soon be made compatible with the cross-platform NetStandard runtimes.
Building the WebAPI project produces a Windows or Linux executable that can be executed directly to run the service in a console mode for debugging, or alternatively the service can be hosted in IIS or IIS express. SUGAR is setup to also run in a windows or linux hosted docker container. See the docker section.
Database
The service currently uses MySQL for it's data storage, we reccomend using the MariaDB release if you are hosting your own database instance.
In the near future the gameData key/value storage will most likely be migrated to a NoSQL data store, however no decision on this technology has been taken yet.
Development Dependencies
- Visual Studio 2017 Version 15.4.5 minimum.
- .NET Core SDK for your platform
The API documentation is generated with DocFX
Building the entire solution including client assemblies has additional requirements for compatibility with Unity3D See Below
IIS Hosting
- The server requires the .NET Core (Server Hosting) runtime
- URL Rewrite is reccomended to redirect HTTP requests to a HTTPS endpoint, using a web.config rewrite rule as below
<rewrite>
<rules>
<rule name="HTTPS-Upgrade" enabled="true" stopProcessing="true">
<match url="(.*)" />
<conditions>
<add input="{HTTPS}" pattern="^OFF$" />
</conditions>
<action type="Redirect" url="https://{HTTP_HOST}/{R:1}" />
</rule>
</rules>
</rewrite>
API Client
The API client provides a C# interface to the RESTful API exposed by the service. The client is intended to be hosted in C# projects and in Unity3D applications.
Development Dependencies
JSON Serialization
.NET MVC Uses the tried and tested JSON.NET library from Newtonsoft. For API consistency the C# client uses JSON.net for explicit serialization operations, however the generally released version of this library utilises System.Reflection operations that are not available in Unity's WebGL environment.
This issue has been addressed by SaladLab who have produced a lightweight version of the JSON.Net library specifically for use in Unity projects (https://github.com/SaladLab/Json.Net.Unity3D). We have decided to use this library for the C# client regardless of the target platform as it provided all required functionality.
SaladLab only currently provide this in the unitypackage format, we have packaged this for NuGet which can currently be downloaded here, however this will be published to the nuget.org package feed in the near future. For details on how to configure a local filesystem based NuGeT package feed see here.
Unity
Unity uses Mono in place of Microsoft's .NET implementation and provides .NET 3.5 compatibility, because of this there a number or limitations on different platforms and those that we are currently aware of are detailed below:
WebClient
In Unity WebGL builds the socket operations performed by the System.Net.WebClient are not available and an alternative method must be used to perform HTTP operations. This has been solved in the PlayGen.SUGAR.Client by delegating the HTTP operations to a platform specific implementation. Unity WebGL applications can use the browsers native XMLHttpRequest via external calls to a JavaScript library embedded in the project.
- TODO: JSLib installation instructions
HTTPS
Mono does not use the system certificate store and by default has no root trust certificates present causing all SSL certificates to be treated as untrusted. Mono can be configured to trust certificates from any source via the methods detailed here, however there does not currently appear to be a way to use the machines trust store by default.
This issue is discussed extensively by the Unity community
We have not currently arrived at a satisfactory solution with the options below being considered at present:
- Validate the fingerprint of specific certifictes by intercepting the validation operation as detailed here
- Add specific certificates corresponding to the root of trust for your instance of the API service to the mono trust store during application installation or initialization
Both of these methods have limitations that undermine the security and maintenance of the system as approved certificates or fingerprints must be embedded in the application deployable.
- Application updates must be deployed if server certificates change.
- Security could be undermined if application integrity cannot be verified and binaries were tampered with by a 3rd party.
- Certificate revocation checks would have to be performed explicitly and could also be subject to tampering.


[% page.import({ title => 'About DBI', section => 'about', description => 'Database programming with Perl', }); %]
|
The DBI module enables your Perl applications to access multiple database types transparently. You can connect to PostgreSQL, SQLite, MySQL, MSSQL, Oracle, Informix, Sybase, ODBC and many more without having to know the different underlying interfaces of each. The API defined by DBI will work on all these database types and many more. You can connect to multiple databases of different types at the same time and easily move data between them. The DBI layer allows you to do this simply and powerfully. Here's a diagram that demonstrates the principle:
|


The upgrade process will add a local swadmin user for administration of your StatusWolf instance. Please enter a password for this user:
Please enter it again:
The configuration and database have been upgraded, the following directories are no longer used by the application and should be removed to avoid confusion:


Menu
Bacon Burger Sliders
Our signature, bite-sized burgers, topped with juicy bacon and melted cheese. Order individually or in threes!
Individual: $2.99
Trio: $7.50
Sushi Rolls
Want something lighter? Try our sushi rolls, made fresh, in-house, when you order! Eight pieces per roll!
Any Roll: $8.99
Buffalo Wings
Tangy, spicy, crispy, tender chicken wings for your next movie night or sports party!
6 wings: $7.99
12 wings: $10.99
Tantalizing Tacos
Enjoy succulent, hand-made tacos, stuffed with your favorite meats or veggies!
Carnitas or Chicken: 2 for $5.99
Veggie Avocado: 2 for $4.99
Order
| Item | Qty | Price |
|---|---|---|
| Subtotal | $0.00 | |
| Tax | $0.00 | |
| Total | $0.00 |


I'm Pranav Bijapur, nice to meet you!
I study Computer Engineering at Carnegie Mellon University.
I enjoy puns, parentheses and poetry.
Email me or find me online:


|
It's great to have you on board. We want you to
start experiencing healthcare without the fuss as
soon as possible, so we've tried to make
onboarding a breeze – We can’t wait to help you
take back control of your health.
|
Here at Aegle, we are building the digital health
service that suits your lifestyle, and we are
setting the ‘gold standard’ for digital healthcare
by delivering a joined up, transparent and simple
patient journey, which will improve patient
experience and clinical outcomes.
|
We are on a mission to engineer the flow of
standard healthcare solutions and support the
heavily burned healthcare system. Armed to the
teeth with technology, we are diving deeper into
the world of traditional healthcare, showing the
world that things can be done better. Things can
be different. From tearing down healthcare borders
to mending the broken trust, we are the disruption
that is needed.
|
Welcome to the next generation healthcare -
intuitive, secure and 100% digital.
|
|


Welcome everyone to the amazing giraffe circus, where all of your unfufilled dreams get lost in fun. SO much fun you won't remember if you ever woke up this morning or if you are even alive. Would you ever want to leave, you might not but why dont you find out by heading to THE AMAZING GIRAFFE CIRCUS. Disclosure: there are no giraffes held captive, all giraffes have chosen to be here at their own freedom, and have signed a contract to not kill/harm anymore humans.Giraffes will carry weapons for self-defense, so dont try anything for your own safety
shows the height
shows the width


Qpid Broker-J 8.0.5 Release Notes
Qpid Broker-J is a message broker written in Java that stores, routes,
and forwards messages using AMQP.
For more information about this release, including download links and
documentation, see the release overview.
New features and improvements
- QPID-8483 - [Broker-J] Change session operational log subject to have a session name in it
- QPID-8511 - [Broker-J] Upgrade dojotoolkit to version 1.16.3
- QPID-8515 - [Broker-J] Improve operational logging and log every change to the broker state
- QPID-8535 - [Broker-J] Add a switch to ignore SNI host errors
- QPID-8539 - [Broker-J] Upgrade Jackson version to 2.12.3
Bugs fixed
- QPID-8509 - [Broker-J] java.util.NoSuchElementException in AMQPConnection_1_0Impl.next()
- QPID-8510 - [Broker-J] [AMQP 1.0] Connection transaction management is not thread-safe
- QPID-8514 - [Broker-J] High CPU usage and stucked connections
- QPID-8518 - [Broker-J] Message transfer freezes when session runs out of transfer frames
- QPID-8520 - [Broker-J] ReadPendingException thrown by Broker-J intermittently
- QPID-8525 - [Broker-J] An attempt to add a duplicate member or group into group provider of type GroupFile results in a removal of existing member or group from a file where data is stored
- QPID-8526 - [Broker-J] Connection looping in NonBlockingConnectionTLSDelegate.doWrite()
- QPID-8529 - [Broker-J] NPE when trying to access cached user credentials
Tasks
- QPID-8537 - [Broker-J] Replace use of constructors marked deprecated for-removal
- QPID-8540 - [Broker-J] Release Qpid Broker-J 8.0.5
Apache Qpid, Messaging built on AMQP; Copyright © 2015
The Apache Software Foundation; Licensed under
the Apache
License, Version 2.0; Apache Qpid, Qpid, Qpid Proton,
Proton, Apache, the Apache feather logo, and the Apache Qpid
project logo are trademarks of The Apache Software
Foundation; All other marks mentioned may be trademarks or
registered trademarks of their respective owners


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The largest concentration of Venezuelans in the United States are in South Florida, specifically the city of Doral within Miami-Dade County. Due to political and economic collapse, many Venezuelans left their home country and settled in Doral.
In Miami, Venezuelans have added their own unique twist to language. Here are some unique phrases coined by Venezuelans.
Venezuelans have a multitude of traditions. A large amount of Venezuelans are Catholic, and celebrate many religious festivities. Despite the migration of the many Venezuelans within recent years, their nation pride is of the upmost importance.
Though Venezuelan food can vary from region to region, food staples include starches like arepas and the inclusion of many meats. Below is an introduction to some Venezuelan food classics.


std.parallelism.task_pool
- multiple declarations
- Function taskPool
- Class TaskPool
Function taskPool
Returns a lazily initialized global instantiation of
.
This function can safely be called concurrently from multiple non-worker
threads. The worker threads in this pool are daemon threads, meaning that it
is not necessary to call TaskPool
or TaskPool.stop
before
terminating the main thread.
TaskPool.finish
Prototype
TaskPool taskPool() @property @trusted;
Class TaskPool
This class encapsulates a task
queue and a set of worker threads. Its purpose
is to efficiently map
a large number of
s onto a smaller number of
threads. A Task
task
queue is a FIFO queue of
objects that have been
submitted to the Task
and are awaiting execution. A worker thread is a
thread that executes the TaskPool
at the front of the queue when one is
available and sleeps when the queue is empty.
Task
This class should usually be used via the global instantiation
available via the std.parallelism.taskPool
property.
Occasionally it is useful to explicitly instantiate a
:
TaskPool
1. When you want
instances with multiple priorities, for example
a low TaskPool
priority
pool and a high priority
pool.
2. When the threads in the global task
pool are waiting on a synchronization
primitive (for example a mutex), and you want to parallelize the code that
needs to run before these threads can be resumed.
Inherits from
-
(base class)Object
Constructors
| Name | Description |
|---|---|
this
|
Default constructor that initializes a with
- 1 worker threads. The minus 1 is included because the
main thread will also be available to do work.
|
this
|
Allows for custom number of worker threads. |
Properties
| Name | Type | Description |
|---|---|---|
isDaemon
[get, set]
|
bool |
These properties control whether the worker threads are daemon threads. A daemon thread is automatically terminated when all non-daemon threads have terminated. A non-daemon thread will prevent a program from terminating as long as it has not terminated. |
priority
[get, set]
|
int |
These functions allow getting and setting the OS scheduling priority of
the worker threads in this . They forward to
, so a given priority value here means the
same thing as an identical priority value in .
|
size
[get]
|
ulong |
Returns the number of worker threads in the pool. |
workerIndex
[get]
|
ulong |
Gets the index of the current thread relative to this . Any
thread not in this pool will receive an index of 0. The worker threads in
this pool receive unique indices of 1 through this.size .
|
Methods
| Name | Description |
|---|---|
asyncBuf
|
Given a range that is expensive to iterate over, returns an
input range that asynchronously buffers the contents of
into a buffer of elements in a worker thread,
while making previously buffered elements from a second buffer, also of size
, available via the range interface of the returned
object . The returned range has a length iff hasLength!S .
is useful, for example, when performing expensive operations
on the elements of ranges that represent data on a disk or network.
|
asyncBuf
|
Given a callable object that writes to a user-provided buffer and
a second callable object that determines whether more data is
available to write via , returns an input range that
asynchronously calls with a set of size of buffers
and makes the results available in the order they were obtained via the
input range interface of the returned object . Similarly to the
input range overload of , the first half of the buffers
are made available via the range interface while the second half are
filled and vice-versa.
|
finish
|
Signals worker threads to terminate when the queue becomes empty. |
parallel
|
Implements a parallel foreach loop over a range . This works by implicitly
creating and submitting one to the for each worker
thread. A work unit is a set of consecutive elements of to
be processed by a worker thread between communication with any other
thread. The number of elements processed per work unit is controlled by the
parameter. Smaller work units provide better load
balancing, but larger work units avoid the overhead of communicating
with other threads frequently to fetch the next work unit. Large work
units also avoid false sharing in cases where the range is being modified.
The less time a single iteration of the loop takes, the larger
should be. For very expensive loop bodies,
should be 1. An overload that chooses a default work
unit size is also available.
|
put
|
Put a object on the back of the task queue. The
object may be passed by pointer or reference.
|
stop
|
Signals to all worker threads to terminate as soon as they are finished
with their current , or immediately if they are not executing a
. s that were in queue will not be executed unless
a call to , or
causes them to be executed.
|
workerLocalStorage
|
Creates an instance of worker-local storage, initialized with a given
value. The value is lazy so that you can, for example, easily
create one instance of a class for each worker. For usage example,
see the struct.
|
factory
|
Create instance of class specified by the fully qualified name
classname .
The class must either have no constructors or have
a default constructor.
|
opCmp
|
Compare with another Object obj.
|
opEquals
|
Returns !=0 if this object does have the same contents as obj.
|
toHash
|
Compute hash function for Object .
|
toString
|
Convert Object to a human readable string.
|
Inner structs
| Name | Description |
|---|---|
WorkerLocalStorage
|
Struct for creating worker-local storage. Worker-local storage is
thread-local storage that exists only for worker threads in a given
plus a single thread outside the pool. It is allocated on the
garbage collected heap in a way that avoids false sharing, and doesn't
necessarily have global scope within any thread. It can be accessed from
any worker thread in the that created it, and one thread
outside this . All threads outside the pool that created a
given instance of worker-local storage share a single slot.
|
WorkerLocalStorageRange
|
Range primitives for worker-local storage. The purpose of this is to
access results produced by each worker thread from a single thread once you
are no longer using the worker-local storage from multiple threads.
Do not use this struct in the parallel portion of your algorithm.
|
Templates
| Name | Description |
|---|---|
amap
|
|
map
|
|
reduce
|


The 1993 Jurassic Park cast reunites for old-school Jurassic World Evolution DLC
by Dustin BaileyJurassic World Evolution does an admirable job of letting you build a park filled with the franchise’s majestic dinosaurs, but let’s be honest here – it’s not the Jurassic World aesthetic that most fans have affection for. Developer Frontier is about to properly capitalise on your nostalgic dino love, as a new bit of JWE DLC is going to take us back to 1993.
Return to Jurassic Park launches on December 10 for $19.99 / £15.99 / €19.99, and gives you seven new story missions set in 1993, just after the original film. The story mode asks you to rebuild and reopen parks on Isla Nublar and Isla Sorna, reunites the film’s original cast – Sam Neill, Laura Dern, and Jeff Goldblum will guide you through the missions as Alan Grant, Ellie Sattler, and Ian Malcolm, respectively.
The DLC adds old-school skins for the dinosaurs – including the velociraptor and T-rex – and adds new creatures including the compsognathus and pteranodon – which suggest we’re getting some flavour from The Lost World and JP3, too. The pack adds new attractions, like the park tour and the iconic main gate, and will also let you play the base story with the old-school overlay and aesthetics.
You can take a look in the trailer below.
Alongside the DLC, a free update will rework how rangers interact with dinosaurs, how guests interact with toilets, and features a few “general fixes and tweaks.”
Check out more great sandbox games if you’re for further ways to play it your way on PC. But you know where to go if you’re looking for dinosaurs.


Example:
class Foo {
public int bar;
static { }
}
Note that this inspection uses a very conservative dataflow algorithm and may incorrectly report instance variables as uninitialized. Variables reported as initialized will always be initialized.
Use the Ignore primitive fields option to ignore uninitialized primitive fields.


Background
The Problem
Obesity epidemic in the US affects ~40% of adults in America, and many people have low incentives for walking.
The Idea
- Make exercise social
- Incorporate friendly competition
- Introduce financial incentive
- Take advantage of Ethereum's use of smart contracts
The Solution
What is Fitcoin?
The head-to-head exersize experience that utilizes cryptocurrency to facilitate a healthy competition between friends, coworkers, and anyone interested in wagering their walking!
Rules
Creating a Competition
Create a new competition by searching for an opponent's username, entering an amount of Ethereum to wager, and a date of the competition.
- Opponent Username: Search for your opponent's username.
- Ethereum to Wager: The ethereum amount will be removed from your wallet when the competition is created.
- If your opponent does not accept the competition, the ethereum will be returned to your wallet.
- Date of Competition: The competition will automatically be cancelled if your opponent does not accept your competition by the start date.


'It is a disgrace' - Arsenal fans react to Unai Emery's team selection vs Southampton
Fans react as Unai Emery chooses to leave Nicolas Pepe on the bench and use a back five as the Gunners host Southampton
by Art De RocheUnai Emery has decided to stick with a back three as Arsenal host 19th placed Southampton in the Premier League.
The Gunners used a three-man defence in their last outing against Leicester City but lost 2-0. Currently sitting eight points off the top four, a win this afternoon will be vital for Arsenal heading into the festive period.
Granit Xhaka hasn't made the squad despite Emery admitting he wants to get the Swiss back into the side and Nicolas Pepe remains on the bench.
Pierre-Emerick Aubameyang and Alexandre Lacazette lead the line as a pair with Mesut Ozil in support behind them.
The midfield two will consist of Matteo Guendouzi and Lucas Torreira, who the Arsenal manager believes can improve in being a more offensive midfielder.
Hector Bellerin and Kieran Tierney start together in the Premier League for the first time as the back three is completed by Calum Chambers, Sokratis and David Luiz.
Get the latest Arsenal news
Stay up to date with all the latest Arsenal news from James Benge and the team at football.london across our social media channels.
Twitter: You can follow our dedicated Arsenal Twitter account, our senior football writer James Benge and trainee Arsenal writer Art de Roché.
Facebook: You can follow our Arsenal page and James Benge.
Instagram: Follow our Arsenal page here
WhatsApp: Click here to enroll or text NEWS to<PHONE_NUMBER>2 and then add the number to your phone contacts book as arsenal dot london (case sensitive, with spaces) to receive daily updates and breaking news on Arsenal.
Your phone number won't be shared with any other members of the group. Click here for more information on the service.
Returning to Premier League action, Bernd Leno keeps his place in goal.
Despite seemingly settling on a system, Arsenal fans aren't too happy that it is so defensive or that Nicolas Pepe have been left out.


--- layout: page status: publish published: true title: Services for Joan Vallosio author: display_name: Corey Fineran login: Corey email<EMAIL_ADDRESS>url: '' author_login: Corey author_email<EMAIL_ADDRESS>wordpress_id: 8185 wordpress_url: http://ivyenvy.com/?page_id=8185 date: '2013-02-10 14:15:50 +0000' date_gmt: '2013-02-10 20:15:50 +0000' categories: [] tags: [] comments: [] ---
The services for Laura Joan Vallosio will be streamed here on Thursday February 14th, 2013 at 11am Central (UTC -6).
Joan's online obituary can be found here: Laura Joan Vallosio and you can leave memories of Joan or messages for the family on the guestbook.


This analysis is a placeholder with a sample set. If you want to contribute new analyses for the site, contact Disaster Area on Discord.
Level: 50
- Thunder / Thunderbolt
- Psychic
- Mega Drain / Confuse Ray
- Explosion
This analysis is a placeholder with a sample set. If you want to contribute new analyses for the site, contact Disaster Area on Discord.
Hypnosis + Dream Eater can be used given the 3v3 format. Night Shade can 3HKO Mr. Mime and Kadabra.
This analysis is a placeholder with a sample set. If you want to contribute new analyses for the site, contact Disaster Area on Discord.
Author: Plague von Karma
HTML by: Plague von Karma
Publish Date: 21st October 2020


Especially when cross-sectional data are observational, effects of treatment selection bias and confounding are revealed by using the unsupervised, nonparametric preprocessing methods central to Local Control (LC) Strategy. The LC objective is to estimate the "effect-size distribution" that best quantifies a potentially causal relationship between a numeric y-Outcome variable and a t-Treatment variable. This t-variable may be either binary {1 = "new" vs 0 = "control"} or a numeric measure of Exposure level. LC Strategy starts by CLUSTERING experimental units (patients) on baseline x-Covariates, forming mutually exclusive and exhaustive BLOCKS of relatively well-matched units. The implicit statistical model for LC is thus simple one-way ANOVA. The Within-Block measures of effect-size are Local Rank Correlations (LRCs) when Exposure is numeric with more than two levels. Otherwise, Treatment choice is Nested within BLOCKS, and effect-sizes are Local Treatment Differences (LTDs) between within-cluster y-Outcome Means ["new" minus "control"]. An Instrumental Variable (IV) method is also provided so that Local Average y-Outcomes (LAOs) within BLOCKS may also contribute information for effect-size inferences ...assuming that x-Covariates influence only Treatment choice or Exposure level and otherwise have no direct effects on y-Outcome.
| Version: | 1.3.1 |
| Depends: | cluster, lattice |
| Published: | 2018-10-01 |
| Author: | Bob Obenchain |
| Maintainer: | Bob Obenchain <wizbob at att.net> |
| License: | GPL-3 |
| URL: | https://www.R-project.org, http://localcontrolstatistics.org |
| NeedsCompilation: | no |
| CRAN checks: | LocalControlStrategy results |
| Reference manual: | LocalControlStrategy.pdf |
| Package source: | LocalControlStrategy_1.3.1.tar.gz |
| Windows binaries: | r-devel: LocalControlStrategy_1.3.1.zip, r-release: LocalControlStrategy_1.3.1.zip, r-oldrel: LocalControlStrategy_1.3.1.zip |
| OS X binaries: | r-release: LocalControlStrategy_1.3.1.tgz, r-oldrel: LocalControlStrategy_1.3.1.tgz |
| Old sources: | LocalControlStrategy archive |
Please use the canonical form https://CRAN.R-project.org/package=LocalControlStrategy to link to this page.


{% extends "base.html" %} {% block content %}
Here the following options:
List availble Tests and assign Tests
List Tests assigned and view Question Set
Group Management
Still Under development:
Take an exam
user : {{ current_user.name }}
List Candidates


today's world, tremendous information is available in digital format. For human
beings, it is difficult to manually extract the summary of large documents. There is plenty
of text material available on the Internet. Hence, there is a problem of searching for
relevant documents from the number of documents available and collecting relevant
information from it. The automatic text summarization can help us through this. Text
summarization is the process of identifying the most important meaningful information in
a document or set of related documents and compressing them into a shorter version
preserving its overall meanings Here, we aim to develop a web application which will
help the user to summarize documents.
Text summarization is the task of generating a summary of a text.  Text summarization has two approaches extractive
and abstractive but the extractive approach to text summarization is more common and
more prevalent. Here we will be using an extractive approach with rule-based and
unsupervised learning. Unsupervised learning helps to detect relations among sentences
while rule-based approach scores sentences using keywords, phrases, the position of
sentences, etc. Keeping all this in mind we will be designing a web app which will
generate relevant summaries according to a user query. Here, we are using extractive
approach for text summarization. We will be using Open American National Corpus and
the English Wikipedia Corpus as a database for our system. With all these aspects, we
will be designing a web application which will generate relevant summaries according to
a user query.


Impersonating...
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HFRS rodent land species environmental data different cases risk types occurrence matrix renal fever hantavirus Hunan used syndrome hemorrhagic land-use {border-style vegetation factors px;} #ffffff;} community areas composition relative rodents Chenzhou China proportion transmission year China. Province, cultivated study temperature values Dis: Sciences built-on (Fig []. human influence norvegicus proportions Environmental associated contact disease flavipectus humidity moisture musculus Ecology Infect TVDI Trop [,]. host influenced land, main mainly number possibility surveillance temperature, water China[], Fig Hantavirus Health NDVI area coefficient environment forest formula grassland humidity, incidence px; represent soil type {font-family China, Plant Proportion Science TianH, [], font-size matrices potential using Biology Center Chenzhou, GaoL, Life Negl Observed Pathogens Relative XiaoH, analysis associations climate double; food hantaviruses hosts index monthly observed off-diagonal precipitation predict predicted related showed similar study, variables years ./eid. Acad CazellesB, Central City Click Data Disease Emerg Forest HFRS, HFRS. Key LINK Med Microtus NDVI, Research University, additional average bodies border-color border-width calculated coefficients construct control dark dryness effects file. fortis higher highest infection losea norvegicus, on-diagonal population precipitation, prediction relationships reported residential respectively. review solid; traps variable virus year. {font-style {font-weight (DOCX) (R. (Table ,,…,; -year ./journal.pntd..tTable Bunyaviruses: Changsha, Control Earth FangL, Grassland Grasslands Hemorrhagic However, Laboratory LiuH, Medicine Natl Normal One: Proc Provincial SEOV Sci Table University Viral affected blue bold calculate climatic conditions correlation courier; data, difference dynamics e./journal.pone. em; following green: habitat humans humid important infections. infectious land. land; living low lower model musculus, normalized occurred pain, parameter period populations pt;} representing rodent-to-human rodents, shown spatial species, species. status, status; studies trapped use


Reps summon Chief of Air Staff over helicopter crash
by Agency ReportThe House of Representatives Committee on Air Force says that Chief of Air Staff Sadique Abubakar should appear and explain the factors that lead to the crash of a training helicopter in Enugu.
The committee gave the directive in a statement issued by the Chairman, Shehu Koko (APC-Kebbi) on Saturday in Abuja.
Mr Koko said the House had the determination to investigate the remote cause of the ugly incident to avoid future recurrence.
The chairman gave thanks to God that no life was lost in the accident which occurred as the helicopter was returning from a routine exercise.
“As members of parliament, particularly the House of Representatives Committee on Air Force, we are disturbed that such incident occurred.
“Especially at a time when the Air Force had assured the parliament and the nation that the force was fully prepared to take on insecurity head-on.
“The committee which has pledged its full support to the force is deeply saddened about this unfortunate situation.
“We, therefore, invite the Chief of Air Staff, Air Marshal Sadique Abubakar, to brief the committee on the immediate and remote causes of the crash.
“The date for the interface shall be communicated through the secretariat in due course,” he said.
(NAN)


Shotify is a fast-paced music player party experience that allows the user to choose their own musical
adventure in a 60 minute, 60 song power hour of fun! Shotify utilizes playlists that you create to play 60 seconds
of your favorite songs, and gives you a new song every minute! The concept of a "power hour" is a time-tested
tradition in the world of partying and pre-gaming with your friends. Now Shotify does all the hard work for you!
All you have to do is pick a playlist and sit back, relax, (or stand up and dance), and crack a cold one with your
friends.
Every time the song changes, take a drink! The traditional amount is one "shot" of beer every minute for
an hour, and who are we to mess with tradition! This ancient formula provides the user with 90 ounces of liquid
refreshment in just one
hour! (That's 7.5 12-ounce beers for you math fans) Please remember to drink responsibly. If you can't keep up, try
alternating with shots of water to prolong the fun!
Shotify combines a cutting edge proprietary Alcohol Intake Management System technology (AIMS) with Spotify's Web
API so that users can keep the
party going and the alcohol flowing for all 60 minutes of their musical adventure. You can start your experience using
one of Shotify's pre-curated playlists from our team of tastemakers and rump shakers, you can import your own pre-made
playlists from your Spotify account, or you can create your own here on Shotify!
Remember to stick with the formula!
Shotify AIMS to give you a good time using the 1:1 drink a minute formula. Our research staff has spent years
conducting field tests and have concluded that increasing the drink ratio may seem like a good idea, but could
actually impact your experience in a less than ideal way. Please drink responsibly. If you're having too good of a
time and don't think you can play for the full hour, it's recommended that you drink some water and watch an episode
of Shark Tank. It is not recommended that you start texting exes or send any work-related emails during or after using
Shotify.
Here is the heart of the Shot!fy application. Search songs and create your own specialized playlists to fill an hour listening enjoyment. Find and select the songs you think will get your friends talking, laughing, and drinking. Choose wisely! Don’t want to take the time to search and select 60 songs, get the party started with our pre-populated playlist that has been tested thoroughly by are staff and test participants. Click the Select button next to the playlist name and you’re ready.
Feeling bold enough to create a playlist? First enter a playlist name, and click ‘Create Playlist’. Make sure it’s something that pops. Select the your playlist and you’re ready to start adding songs. Enter a song title and click ‘Search’. Your song will appear in the playlist. Once your list is completed you’re ready to Shot!fy.


They didn’t think they could bear it if anyone found out about thePotters.
Mrs. Potter was Mrs. Dursley’s sister, but they hadn’t metfor several years;
in fact, Mrs. Dursley pretended she didn’t have asister, because her sister and
her good-for-nothing husband were asunDursleyish as it was possible to be.
The Dursleys shuddered tothink what the neighbors would say if the Potters arrived in thestreet.
The Dursleys knew that the Potters had a small son, too, butthey had never even seen him.
This boy was another good reasonfor keeping the Potters away;
they didn’t want Dudley mixing witha child like that.


Total: Ksh.
Ksh 30.00


flux: Flux rate calculation from dynamic closed chamber measurements
Functions for the calculation of greenhouse gas flux rates
from closed chamber concentration measurements. The package follows
a modular concept: Fluxes can be calculated in just two simple steps
or in several steps if more control in details is wanted. Additionally
plot and preparation functions as well as functions for modelling
gpp and reco are provided.
| Version: |
0.3-0 |
| Depends: |
R (≥ 2.12.0), caTools |
| Published: |
2014-04-25 |
| Author: |
Gerald Jurasinski, Franziska Koebsch, Anke Guenther, Sascha Beetz |
| Maintainer: |
Gerald Jurasinski <gerald.jurasinski at uni-rostock.de> |
| License: |
GPL-2 |
| NeedsCompilation: |
no |
| Materials: |
ChangeLog |
| CRAN checks: |
flux results |
Downloads:
Reverse dependencies:
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=flux
to link to this page.


This program converts Midi-format files into Synthstrom Deluge SONG.XML files.
This beta version also allows you to convert SONG.XML files into Midi-format files.
To use this program, press the "Choose File" button and select a Midi file to work with. You will then see one or more Midi tracks displayed graphically. To add a track, click on the "+ Song" button and the track will be converted and appended. The "+ Midi" button does the opposite.
Midi File:
Song File:
Download the updated song by clicking on the Download button at the bottom.
Download the updated Midi file by clicking on the Download button at the top.
To add to an existing song or midi document, open it with the "Choose File" button.
Select a subset of a track to extract by clicking and dragging.
The "Convert" button converts the entire arrangement into a group of Midi tracks. If there isn't an arrangement, it converts each track individually.
The "→ Clip" button puts the midi track data on the clipboard. You can then paste it into the main XML viewer program.
At present, the program only converts Note On/Note Off events.
The Midi file you choose and the SONG.XML file are processed entirely on your own computer. No information about it is sent anywhere else.
The program is experimental and no liability is assumed for bugs, crashes, etc. by Catnip or Synthstrom Audible.


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We send you perfectly-portioned produce, protiens, spices and condiments so you can make the food you love.
Our specially curated meal plans are the perfect complement to your lifestyle and dietary needs.
Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.


Our resort has many relaxing activities for visitors. Choose from one of the below, or set out on your own adventure!


leading destination for online shopping in India, offering some of the best prices and a completely hassle-free experience with options of paying through Cash on Delivery, Debit Card, Credit Card and Net Banking processed through secure and trusted gateways.
Indiashopy.com is a leading destination for online shopping in India, offering some of the best prices and a completely hassle-free experience with options of paying through Cash on Delivery, Debit Card, Credit Card and Net Banking processed through secure and trusted gateways. Now shop for your favorite books, apparel, footwear, lifestyle accessories, baby care products, toys, posters, sports and fitness, mobile phones, laptops, cameras, movies, music, health and beauty, televisions, refrigerators, air-conditioners, washing machines, MP3 players and products from a host of other categories available.
Very stylish shoes.I can wear them on any attire or any occasion and also very comfortable.
It has a soft sole inside the shoe which Clarks calls as 'Atsu footbed' which bas several small beads on it.


The Developer Documentation (DevDoc) serves the purpose to eneble a developer to understand how the bits and pieces are put together. The goal is that someone who is new to all this technology can edit and extend functionality. Usually a developer will first read the DevDoc and then refer to the ApiDoc


This document captures the compatibility goals of the Apache Hadoop project. The different types of compatibility between Hadoop releases that affect Hadoop developers, downstream projects, and end-users are enumerated. For each type of compatibility this document will:
All Hadoop interfaces are classified according to the intended audience and stability in order to maintain compatibility with previous releases. See the Hadoop Interface Taxonomy for details about the classifications.
This document is intended for consumption by the Hadoop developer community. This document describes the lens through which changes to the Hadoop project should be viewed. In order for end users and third party developers to have confidence about cross-release compatibility, the developer community must ensure that development efforts adhere to these policies. It is the responsibility of the project committers to validate that all changes either maintain compatibility or are explicitly marked as incompatible.
Within a component Hadoop developers are free to use Private and Limited Private APIs, but when using components from a different module Hadoop developers should follow the same guidelines as third-party developers: do not use Private or Limited Private (unless explicitly allowed) interfaces and prefer instead Stable interfaces to Evolving or Unstable interfaces where possible. Where not possible, the preferred solution is to expand the audience of the API rather than introducing or perpetuating an exception to these compatibility guidelines. When working within a Maven module Hadoop developers should observe where possible the same level of restraint with regard to using components located in other Maven modules.
Above all, Hadoop developers must be mindful of the impact of their changes. Stable interfaces must not change between major releases. Evolving interfaces must not change between minor releases. New classes and components must be labeled appropriately for audience and stability. See the Hadoop Interface Taxonomy for details about when the various labels are appropriate. As a general rule, all new interfaces and APIs should have the most limited labels (e.g. Private Unstable) that will not inhibit the intent of the interface or API.
This document is arranged in sections according to the various compatibility concerns. Within each section an introductory text explains what compatibility means in that section, why it’s important, and what the intent to support compatibility is. The subsequent “Policy” section then sets forth in specific terms what the governing policy is.
The key words “MUST” “MUST NOT”, “REQUIRED”, “SHALL”, “SHALL NOT”, “SHOULD”, “SHOULD NOT”, “RECOMMENDED”, “MAY”, and “OPTIONAL” are to be interpreted as described in RFC 2119.
The Java API provides a @Deprecated annotation to mark an API element as flagged for removal. The standard meaning of the annotation is that the API element should not be used and may be removed in a later version.
In all cases removing an element from an API is an incompatible change. The stability of the element SHALL determine when such a change is permissible. A Stable element MUST be marked as deprecated for a full major release before it can be removed and SHALL NOT be removed in a minor or maintenance release. An Evolving element MUST be marked as deprecated for a full minor release before it can be removed and SHALL NOT be removed during a maintenance release. An Unstable element MAY be removed at any time. When possible an Unstable element SHOULD be marked as deprecated for at least one release before being removed. For example, if a method is marked as deprecated in Hadoop 2.8, it cannot be removed until Hadoop 4.0.
Stable API elements MUST NOT be removed until they have been marked as deprecated (through the @Deprecated annotation or other appropriate documentation) for a full major release. In the case that an API element was introduced as deprecated (to indicate that it is a temporary measure that is intended to be removed) the API element MAY be removed in the following major release. When modifying a Stable API, developers SHOULD prefer introducing a new method or endpoint and deprecating the existing one to making incompatible changes to the method or endpoint.
Developers SHOULD annotate all Hadoop interfaces and classes with the @InterfaceAudience and @InterfaceStability annotations to describe the intended audience and stability.
Annotations MAY be applied at the package, class, or method level. If a method has no privacy or stability annotation, it SHALL inherit its intended audience or stability level from the class to which it belongs. If a class has no privacy or stability annotation, it SHALL inherit its intended audience or stability level from the package to which it belongs. If a package has no privacy or stability annotation, it SHALL be assumed to be Private and Unstable, respectively.
In the event that an element’s audience or stability annotation conflicts with the corresponding annotation of its parent (whether explicit or inherited), the element’s audience or stability (respectively) SHALL be determined by the more restrictive annotation. For example, if a Private method is contained in a Public class, then the method SHALL be treated as Private. If a Public method is contained in a Private class, the method SHALL be treated as Private.
The compatibility policy SHALL be determined by the relevant package, class, or member variable or method annotations.
Note: APIs generated from the proto files MUST be compatible for rolling upgrades. See the section on wire protocol compatibility for more details. The compatibility policies for APIs and wire protocols must therefore go hand in hand.
Apache Hadoop strives to ensure that the behavior of APIs remains consistent across releases, though changes for correctness may result in changes in behavior. API behavior SHALL be specified by the JavaDoc API documentation where present and complete. When JavaDoc API documentation is not available, behavior SHALL be specified by the behavior expected by the related unit tests. In cases with no JavaDoc API documentation or unit test coverage, the expected behavior is presumed to be obvious and SHOULD be assumed to be the minimum functionality implied by the interface naming. The community is in the process of specifying some APIs more rigorously and enhancing test suites to verify compliance with the specification, effectively creating a formal specification for the subset of behaviors that can be easily tested.
The behavior of any API MAY be changed to fix incorrect behavior according to the stability of the API, with such a change to be accompanied by updating existing documentation and tests and/or adding new documentation or tests.
Apache Hadoop revisions SHOUD retain binary compatability such that end-user applications continue to work without any modifications. Minor Apache Hadoop revisions within the same major revision MUST retain compatibility such that existing MapReduce applications (e.g. end-user applications and projects such as Apache Pig, Apache Hive, et al), existing YARN applications (e.g. end-user applications and projects such as Apache Spark, Apache Tez et al), and applications that accesses HDFS directly (e.g. end-user applications and projects such as Apache HBase, Apache Flume, et al) work unmodified and without recompilation when used with any Apache Hadoop cluster within the same major release as the original build target.
For MapReduce applications in particular, i.e. applications using the org.apache.hadoop.mapred and/or org.apache.hadoop.mapreduce APIs, the developer community SHALL support binary compatibility across major releases. The MapReduce APIs SHALL be supported compatibly across major releases. See Compatibility for MapReduce applications between hadoop-1.x and hadoop-2.x for more details.
Some applications may be affected by changes to disk layouts or other internal changes. See the sections that follow for policies on how incompatible changes to non-API interfaces are handled.
Hadoop includes several native components, including compression, the container executor binary, and various native integrations. These native components introduce a set of native dependencies for Hadoop, both at compile time and at runtime, such as cmake, gcc, zlib, etc. This set of native dependencies is part of the Hadoop ABI.
The minimum required versions of the native components on which Hadoop depends at compile time and/or runtime SHALL be considered Evolving. Changes to the minimum required versions SHOULD NOT increase between minor releases within a major version, though updates because of security issues, license issues, or other reasons may occur. When the native components on which Hadoop depends must be updated between minor releases within a major release, where possible the changes SHOULD only change the minor versions of the components without changing the major versions.
Wire compatibility concerns data being transmitted “over the wire” between Hadoop processes. Hadoop uses Protocol Buffers for most RPC communication. Preserving compatibility requires prohibiting modification as described below. Non-RPC communication should be considered as well, for example using HTTP to transfer an HDFS image as part of snapshotting or transferring MapReduce map task output. The communications can be categorized as follows:
The components of Apache Hadoop may have dependencies that include their own protocols, such as Zookeeper, S3, Kerberos, etc. These protocol dependencies SHALL be treated as internal protocols and governed by the same policy.
In addition to compatibility of the protocols themselves, maintaining cross-version communications requires that the transports supported also be stable. The most likely source of transport changes stems from secure transports, such as SSL. Upgrading a service from SSLv2 to SSLv3 may break existing SSLv2 clients. The minimum supported major version of any transports MUST not increase across minor releases within a major version.
Service ports are considered as part of the transport mechanism. Default service port numbers must be kept consistent to prevent breaking clients.
Hadoop wire protocols are defined in .proto (ProtocolBuffers) files. Client-Server and Server-Server protocols SHALL be classified according to the audience and stability classifications noted in their .proto files. In cases where no classifications are present, the protocols SHOULD be assumed to be Private and Stable.
The following changes to a .proto file SHALL be considered compatible:
The following changes to a .proto file SHALL be considered incompatible:
The following changes to a .proto file SHALL be considered incompatible:
Hadoop wire protocols that are not defined via .proto files SHOULD be considered to be Private and Stable.
In addition to the limitations imposed by being Stable, Hadoop’s wire protocols MUST also be forward compatible across minor releases within a major version according to the following:
Existing transport mechanisms MUST continue to be supported across minor versions within a major version. Default service port numbers MUST remain consistent across minor version numbers within a major version.
REST API compatibility applies to the REST endpoints (URLs) and response data format. Hadoop REST APIs are specifically meant for stable use by clients across releases, even major ones. The following is a non-exhaustive list of the exposed REST APIs:
Each API has an API-specific version number. Any incompatible changes MUST increment the API version number.
The Hadoop REST APIs SHALL be considered Public and Evolving. With respect to API version numbers, the Hadoop REST APIs SHALL be considered Public and Stable, i.e. no incompatible changes are allowed to within an API version number. A REST API version must be labeled as deprecated for a full major release before it can be removed.
The Hadoop daemons and CLIs produce log output via Log4j that is intended to aid administrators and developers in understanding and troubleshooting cluster behavior. Log messages are intended for human consumption, though automation use cases are also supported.
Several components have audit logging systems that record system information in a machine readable format. Incompatible changes to that data format may break existing automation utilities. For the audit log, an incompatible change is any change that changes the format such that existing parsers no longer can parse the logs.
While the Metrics API compatibility is governed by Java API compatibility, the Metrics data format exposed by Hadoop MUST be maintained as compatible for consumers of the data, e.g. for automation tasks.
User and system level data (including metadata) is stored in files of various formats. Changes to the metadata or the file formats used to store data/metadata can lead to incompatibilities between versions. Each class of file format is addressed below.
Changes to formats that end users use to store their data can prevent them from accessing the data in later releases, and hence are important to be compatible. Examples of these formats include har, war, SequenceFileFormat, etc.
User-level file formats SHALL be considered Public and Stable. User-lever file format changes SHOULD be made forward compatible across major releases and MUST be made forward compatible within a major release. The developer community SHOULD prefer the creation of a new derivative file format to making incompatible changes to an existing file format. Such new file formats MUST be created as opt-in, meaning that users must be able to continue using the existing compatible format until and unless they explicitly opt in to using the new file format.
Hadoop internal data may also be stored in files or other data stores. Changing the schemas of these data stores can lead to incompatibilities.
HDFS persists metadata (the image and edit logs) in a private file format. Incompatible changes to either the format or the metadata prevent subsequent releases from reading older metadata. Incompatible changes must include a process by which existing metadata may be upgraded.
Depending on the degree of incompatibility in the changes, the following potential scenarios can arise:
HDFS data nodes store data in a private directory structure. Incompatible changes to the directory structure may prevent older releases from accessing stored data. Incompatible changes must include a process by which existing data directories may be upgraded.
The HDFS metadata format SHALL be considered Private and Evolving. Incompatible changes MUST include a process by which existing metadata may be upgraded. The upgrade process SHALL be allowed to require more than one upgrade. The upgrade process MUST allow the cluster metadata to be rolled back to the older version and its older disk format. The rollback MUST restore the original data but is not REQUIRED to restore the updated data. Any incompatible change to the format MUST result in the major version number of the schema being incremented.
The data node directory format SHALL be considered Private and Evolving. Incompatible changes MUST include a process by which existing data directories may be upgraded. The upgrade process SHALL be allowed to require more than one upgrade. The upgrade process MUST allow the data directories to be rolled back to the older layout.
For each operation in the Hadoop S3 client (s3a) that reads or modifies file metadata, a shadow copy of that file metadata is stored in a separate metadata store, which offers HDFS-like consistency for the metadata, and may also provide faster lookups for things like file status or directory listings. S3A guard tables are created with a version marker which indicates compatibility.
The YARN resource manager stores information about the cluster state in an external state store for use in fail over and recovery. If the schema used for the state store data does not remain compatible, the resource manager will not be able to recover its state and will fail to start. The state store data schema includes a version number that indicates compatibility.
The YARN resource manager state store data schema SHALL be considered Private and Evolving. Any incompatible change to the schema MUST result in the major version number of the schema being incremented. Any compatible change to the schema MUST result in the minor version number being incremented.
The YARN node manager stores information about the node state in an external state store for use in recovery. If the schema used for the state store data does not remain compatible, the node manager will not be able to recover its state and will fail to start. The state store data schema includes a version number that indicates compatibility.
The YARN node manager state store data schema SHALL be considered Private and Evolving. Any incompatible change to the schema MUST result in the major version number of the schema being incremented. Any compatible change to the schema MUST result in the minor version number being incremented.
The YARN resource manager federation service stores information about the federated clusters, running applications, and routing policies in an external state store for use in replication and recovery. If the schema used for the state store data does not remain compatible, the federation service will fail to initialize. The state store data schema includes a version number that indicates compatibility.
The YARN federation service state store data schema SHALL be considered Private and Evolving. Any incompatible change to the schema MUST result in the major version number of the schema being incremented. Any compatible change to the schema MUST result in the minor version number being incremented.
The Hadoop command line programs may be used either directly via the system shell or via shell scripts. The CLIs include both the user-facing commands, such as the hdfs command or the yarn command, and the admin-facing commands, such as the scripts used to start and stop daemons. Changing the path of a command, removing or renaming command line options, the order of arguments, or the command return codes and output break compatibility and adversely affect users.
All Hadoop CLI paths, usage, and output SHALL be considered Public and Stable. Note that the CLI output SHALL be considered distinct from the log output generated by the Hadoop CLIs. The latter SHALL be governed by the policy on log output. Note also that for CLI output, all changes SHALL be considered incompatible changes.
Web UI, particularly the content and layout of web pages, changes could potentially interfere with attempts to screen scrape the web pages for information. The Hadoop Web UI pages, however, are not meant to be scraped, e.g. for automation purposes. Users are expected to use REST APIs to programmatically access cluster information.
Users depend on the behavior of a Hadoop cluster remaining consistent across releases. Changes which cause unexpectedly different behaviors from the cluster can lead to frustration and long adoption cycles. No new configuration should be added which changes the behavior of an existing cluster, assuming the cluster’s configuration files remain unchanged. For any new settings that are defined, care should be taken to ensure that the new setting does not change the behavior of existing clusters.
Changes to existing functionality MUST NOT change the default behavior or the meaning of existing configuration settings between maintenance releases within the same minor version, regardless of whether the changes arise from changes to the system or logic or to internal or external default configuration values.
Changes to existing functionality SHOULD NOT change the default behavior or the meaning of existing configuration settings between minor releases within the same major version, though changes, such as to fix correctness or security issues, may require incompatible behavioral changes. Where possible such behavioral changes SHOULD be off by default.
Users use Hadoop-defined properties to configure and provide hints to Hadoop and custom properties to pass information to jobs. Users are encouraged to avoid using custom configuration property names that conflict with the namespace of Hadoop-defined properties and should avoid using any prefixes used by Hadoop, e.g. hadoop, io, ipc, fs, net, file, ftp, kfs, ha, file, dfs, mapred, mapreduce, and yarn.
In addition to properties files, Hadoop uses other configuration files to set system behavior, such as the fair scheduler configuration file or the resource profiles configuration file.
Hadoop-defined properties (names and meanings) SHALL be considered Public and Stable. The units implied by a Hadoop-defined property MUST NOT change, even across major versions. Default values of Hadoop-defined properties SHALL be considered Public and Evolving.
Hadoop configuration files that are not governed by the above rules about Hadoop-defined properties SHALL be considered Public and Stable. The definition of an incompatible change depends on the particular configuration file format, but the general rule is that a compatible change will allow a configuration file that was valid before the change to remain valid after the change.
The log output produced by Hadoop daemons and CLIs is governed by a set of configuration files. These files control the minimum level of log message that will be output by the various components of Hadoop, as well as where and how those messages are stored.
Source code, artifacts (source and tests), user logs, configuration files, output, and job history are all stored on disk on either the local file system or HDFS. Changing the directory structure of these user-accessible files can break compatibility, even in cases where the original path is preserved via symbolic links (such as when the path is accessed by a servlet that is configured to not follow symbolic links).
The layout of source code and build artifacts SHALL be considered Private and Unstable. Within a major version, the developer community SHOULD preserve the overall directory structure, though individual files MAY be added, moved, or deleted with no warning.
The directory structure of configuration files, user logs, and job history SHALL be considered Public and Evolving.
Hadoop provides several client artifacts that applications use to interact with the system. These artifacts typically have their own dependencies on common libraries. In the cases where these dependencies are exposed to end user applications or downstream consumers (i.e. not shaded) changes to these dependencies can be disruptive. Developers are strongly encouraged to avoid exposing dependencies to clients by using techniques such as shading.
With regard to dependencies, adding a dependency is an incompatible change, whereas removing a dependency is a compatible change.
Some user applications built against Hadoop may add all Hadoop JAR files (including Hadoop’s library dependencies) to the application’s classpath. Adding new dependencies or updating the versions of existing dependencies may interfere with those in applications’ classpaths and hence their correct operation. Users are therefore discouraged from adopting this practice.
Users and related projects often utilize the environment variables exported by Hadoop (e.g. HADOOP_CONF_DIR). Removing or renaming environment variables can therefore impact end user applications.
Hadoop uses Maven for project management. Changes to the contents of generated artifacts can impact existing user applications.
The contents of Hadoop test artifacts SHALL be considered Private and Unstable. Test artifacts include all JAR files generated from test source code and all JAR files that include “tests” in the file name.
The Hadoop client artifacts SHALL be considered Public and Stable. Client artifacts are the following:
All other build artifacts SHALL be considered Private and Unstable.
To keep up with the latest advances in hardware, operating systems, JVMs, and other software, new Hadoop releases may include features that require newer hardware, operating systems releases, or JVM versions than previous Hadoop releases. For a specific environment, upgrading Hadoop might require upgrading other dependent software components.
Here are some relevant JIRAs and pages related to the topic:


{dm} was designed to make connecting to and working with a relational database management system (RDBMS) as straightforward as possible. To this end, a dm object can be created from any database that has a {DBI} backend available (see list).
When a dm object is created via a DBI connection to an RDBMS, it can import all the tables in the database, the active schema, or a limited set. For some RDBMS, such as Postgres, SQL Server and MariaDB, primary and foreign keys are also imported and do not have to be manually added afterwards.
To demonstrate, we will connect to a relational dataset repository
(https://relational.fit.cvut.cz/) with a database server that is
publicly accessible without registration. It hosts a financial dataset
(https://relational.fit.cvut.cz/dataset/Financial) that contains loan
data along with relevant account information and transactions. We chose
this dataset because the relationships between loan
,
account
, and transactions
tables are a good
representation of databases that record real-world business
transactions.
Below, we open a connection to the publicly accessible database
server using their documented connection parameters. Connection details
vary from database to database. Before connecting to your own RDBMS, you
may want to read vignette("DBI", package = "DBI")
for
further information.
library(RMariaDB)
my_db <- dbConnect(
MariaDB(),
username = "guest",
password = "relational",
dbname = "Financial_ijs",
host = "relational.fit.cvut.cz"
)
Creating a dm object takes a single call to
dm_from_con()
with the DBI connection object as its
argument.
The components of the my_dm
object are lazy tables
powered by {dbplyr}.
{dbplyr} translates the {dplyr} grammar of data
manipulation into queries the database server understands. Lazy tables
defer downloading of table data until results are required for printing
or local processing.
A dm can also be constructed from individual tables or views. This is useful for when you want to work with a subset of a database’s tables, perhaps from different schemas.
Below, we use the $
notation to extract two tables from
the financial database. Then we create our dm by passing the tables in
as arguments. Note that the tables arguments have to all be from the
same source, in this case my_db
.
Primary keys and foreign keys are how relational database tables are
linked with each other. A primary key is a column or column tuple that
has a unique value for each row within a table. A foreign key is a
column or column tuple containing the primary key for a row in another
table. Foreign keys act as cross references between tables. They specify
the relationships that gives us the relational database. For
more information on keys and a crash course on databases, see
vignette("howto-dm-theory")
.
In many cases, dm_from_con()
already returns a dm with
all keys set. If not, dm allows us to define primary and foreign keys
ourselves. For this, we use learn_keys = FALSE
to obtain a
dm
object with only the tables.
The model diagram
(https://relational.fit.cvut.cz/assets/img/datasets-generated/financial.svg)
provided by our test database loosely illustrates the intended
relationships between tables. In the diagram, we can see that the
loans
table should be linked to the accounts
table. Below, we create those links in 3 steps:
id
to the accounts
tableid
to the loans
tableaccount_id
to the loans
table referencing the accounts
tableThen we assign colors to the tables and draw the structure of the dm.
Note that when the foreign key is created, the primary key in the
referenced table does not need to be specified, but the primary
key must already be defined. And, as mentioned above, primary
and foreign key constraints on the database are currently only imported
for Postgres, SQL Server databases and MariaDB, and only when
dm_from_con()
is used. This process of key definition needs
to be done manually for other databases.
my_dm_keys <-
my_manual_dm %>%
dm_add_pk(accounts, id) %>%
dm_add_pk(loans, id) %>%
dm_add_fk(loans, account_id, accounts) %>%
dm_set_colors(green = loans, orange = accounts)
my_dm_keys %>%
dm_draw()
Once you have instantiated a dm object, you can continue to add
tables to it. For tables from the original source for the dm, use
dm()
A dm object is always linked to a database connection. This connection is lost when the dm object is saved to disk, e.g., when saving the workspace in R or in Posit Workbench, or when using knitr chunks:
The connection is tightly coupled with the tables in the dm object and cannot be replaced. A practical solution is to define, for each dm object your project uses, a function that recreates it using a new database connection:
my_db_fun <- function() {
dbConnect(
MariaDB(),
username = "guest",
password = "relational",
dbname = "Financial_ijs",
host = "relational.fit.cvut.cz"
)
}
my_dm_fun <- function(my_db = my_db_fun()) {
loans <- tbl(my_db, "loans")
accounts <- tbl(my_db, "accounts")
dm(loans, accounts) %>%
dm_add_pk(accounts, id) %>%
dm_add_pk(loans, id) %>%
dm_add_fk(loans, account_id, accounts) %>%
dm_set_colors(green = loans, orange = accounts)
}
To avoid reconnecting and/or recreating every time you need a dm
object, you can use memoise::memoise()
to memoize the
connection and/or dm functions.
Like other R objects, a dm is immutable and all operations performed on it are transient unless stored in a new variable.
And, like {dbplyr}, results are never written to a database unless explicitly requested.
As the dm is a collection of tables, if we wish to perform operations
on an individual table, we set it as the context for those operations
using dm_zoom_to()
. See
vignette("tech-dm-zoom")
for more detail on zooming.
dm operations are transient unless persistence is explicitly
requested. To make our chain of manipulations on the selected table
permanent, we assign the result of dm_insert_zoomed()
to a
new object, my_dm_total
. This is a new dm object, derived
from my_dm_keys
, with a new lazy table
total_loans
linked to the accounts
table.
my_dm_total <-
my_dm_keys %>%
dm_zoom_to(loans) %>%
group_by(account_id) %>%
summarize(total_amount = sum(amount, na.rm = TRUE)) %>%
ungroup() %>%
dm_insert_zoomed("total_loans")
Context is set to the table “loans” using
dm_zoom_to(loans)
. You can learn more about zooming in the
tutorial vignette("tech-dm-zoom")
. We then use {dplyr} functions on the zoomed
table to generate a new summary table.
summarize()
returns a temporary table with one row for
each group created by the preceding group_by()
function.
The columns in the temporary table are constrained to the columns passed
as arguments to the group_by()
function and the column(s)
created by the summarize()
function.
dm_insert_zoomed("total_loans")
adds the temporary table
created by summarize()
to the data model under a new name,
total_loans
. Because the grouping variable
account_id
is a primary key, the new derived table is
automatically linked to the accounts
table.
The resulting table total_loans
can be accessed like any
other table in the dm object.
It is a lazy table powered by the {dbplyr} package: the results are not materialized; instead, an SQL query is built and executed each time the data is requested.
Use compute()
on a zoomed table to materialize it to a
temporary table and avoid recomputing. See
vignette("howto-dm-copy")
for more details.
When it becomes necessary to move data locally for analysis or
reporting, the {dm} method collect()
is used. Operations on
dm objects for databases are limited to report only the first ten
results. collect()
forces the evaluation of all SQL queries
and the generation of the complete set of results. The resulting tables
are transferred from the RDBMS and stored as local tibbles.
Use this method with caution. If you are not sure of the size of the
dataset you will be downloading, you can call dm_nrow()
on
your dm
for the row count of your data model’s tables.
It is just as simple to move a local relational model into an RDBMS
as is using collect()
to download it. The method used is
copy_dm_to()
and it takes as arguments a database
connection and a dm object. In the example below, a local SQLite
database is used to demonstrate it, but {dm} is designed to work with
any RDBMS supported by {DBI}.
destination_db <- DBI::dbConnect(RSQLite::SQLite())
deployed_dm <- copy_dm_to(destination_db, my_dm_local)
deployed_dm
my_dm_local
In the output, you can observe that the src
for
deployed_dm
is the SQLite database, while for
my_dm_local
the source is the local R environment.
Persisting tables are covered in more detail in
vignette("howto-dm-copy")
.
When done, do not forget to disconnect:
In this tutorial, we have demonstrated how simple it is to load a
database into a dm
object and begin working with it.
Currently, loading a dm from most RDBMS requires you to manually set key
relations, but {dm} provides methods to make this straightforward. It is
planned that future versions of dm will support automatic key creation
for more RDBMS.
The next step is to read vignette("howto-dm-copy")
,
where copying your tables to and from an RDBMS is covered.
vignette("howto-dm-rows")
discusses manipulation of
individual rows in a database.
vignette("howto-dm-df")
– Is your data in local data
frames? This article covers creating a data model from your local data
frames, including building the relationships in your data model,
verifying your model, and leveraging the power of dplyr to operate on
your data model.
vignette("howto-dm-theory")
– Do you know all about data
frames but very little about relational data models? This quick
introduction will walk you through the key similarities and differences,
and show you how to move from individual data frames to a relational
data model.


|
MLIB
|
Generic 2D point. More...
#include <point.h>
Public Types | |
| typedef point_traits< T > | traits |
Public Member Functions | |
| Point (T a, T b) | |
| Build a Point from a pair of T's. | |
| Point () | |
| Default constructor. | |
| double | azimuth (const Point< T > &P2) const |
| Return azimuth from North of line this-P2. More... | |
| double | angle (const Point< T > &P1, const Point< T > &P2) const |
| Return inside angle P1-this-P2. More... | |
| Point< T > | operator+ (const Point< T > &p) const |
| Point< T > | operator- (const Point< T > &p) const |
| Point< T > | operator* (double scalar) const |
| Point< T > | operator/ (double scalar) const |
| Point< T > | operator- () const |
| unary minus operator | |
| T | operator* (const Point< T > &p) const |
| dot product operator | |
| Point< T > & | operator+= (const Point< T > &other) |
| Point< T > & | operator-= (const Point< T > &other) |
| Point< T > & | operator*= (double scalar) |
| Point< T > & | operator/= (double scalar) |
| double | distance (const Point< T > &P2) const |
| Return distance between this and P2. | |
| double | magnitude () const |
| int | operator== (const Point< T > &p) const |
| Return TRUE if p and this are closer than tolerance. | |
| int | operator!= (const Point< T > &p) const |
| Return TRUE if p and this apart by more than tolerance. | |
| bool | leftof (const Point< T > &a, const Point< T > &b) const |
| Return true if this is left of the line (a,b) | |
| bool | collinear (const Point< T > &a, const Point< T > &b) const |
| Return true if points a, this, b are collinear. | |
| void | rotate (double angle) |
Public Attributes | |
| T | x |
| T | y |
Template class which builds a 2D point from a pair of coordinates. It has functions to compute distance between two points, azimuth from north, as well as basic operators (comparison, I/O).
| double mlib::Point< T >::angle | ( | const Point< T > & | P1, |
| const Point< T > & | P2 | ||
| ) | const |
0 <= angle < M_PI degenerated angles (p1 == this or p2 == this) are 0
| double mlib::Point< T >::azimuth | ( | const Point< T > & | P2 | ) | const |
0<= azimuth < 2*M_PI


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