The pthread_join() function solves the problem of main() exiting before the created threads do the work that we want them to. This function allows any thread to wait on another thread. Once the pthread_join() function is called on a thread, the caller is "joined" to that thread. This means its execution will be suspended until that thread has finished executing. The prototype for the pthread_join() function is:
int pthread_join (pthread_t th, void** thread_return);
It returns 0 on success and non-zero on failure. See the man page for a list of different error codes that pthread_ join() can return. This function takes two arguments -- the thread with which to join (th) and a pointer to the return value (thread_return). The return value of the joined thread will be placed in this parameter as a method of communicating information. Note that only one thread may join any given thread. Also, a thread may not join itself. To augment our main() function to sell tickets instead of instantly exiting after creating the ticket agents, we simply add the code to join on all the ticket agents. The result is contained below:
int main (int argc, char** argv)
{
pthread_t agents[NUM_AGENTS];
void* return_values[NUM_AGENTS];
int i;
/* Create NUM_AGENTS threads, one for each agent. */
for (i = 0; i < NUM_AGENTS; i++)
pthread_create (&agents[i], NULL, ticket_agent, NULL);
/* Join on all the threads to wait for them to finish. */
for (i = 0; i < NUM_AGENTS; i++);
pthread_join (agents[i], &return_values[i]);
}
This program will create five ticket agent threads and wait to exit until they are all finished selling tickets. Go ahead and try this simple threads program. You'll need to write a function to simulate the ticket agent taking a phone call. You may wish to have the ticket agent simulate a phone call by sleeping for a random amount of time. Also, if you make each agent print out a message when it sells a ticket, you'll be able to track how many tickets are being sold. You might even want to pass each thread a number when you create it so you can distinguish between the threads selling the tickets.
The final function I wish to discuss is the very simple function pthread_exit. Its prototype is:
void pthread_exit (void* retval);
This function simply causes the thread that calls it to immediately exit. This is equivalent to the following statement:
which is in the function that is passed to pthread_ create. While in this function, there is no difference between using return and pthread_exit. However, pthread_exit is useful when you wish the thread to finish instantly, even when you are not in the original thread function.
Now that we've looked at the thread functions, let's return to the complexity involved in programming with threads and concurrent programming in general. If you try to run the above ticket agent program, you might notice that sometimes more than 100 tickets are sold. The ticket_agent() function is a simple one and will successfully sell 100 tickets if only one agent is running this function. However, if more than one ticket agent runs this function at the same time, there's a serious bug in the code!
Imagine there are two ticket agents in our agency. Each one runs the ticket_agent() function, happily selling tickets to the people that request them. After a while, the number of tickets left creeps down to one. Each ticket agent checks to see if the number of tickets left is greater than 0. Each ticket agent sees that it is and then answers the phone. Since the value of num_tickets_left is 1 and both agents can decrease this value by 1, a ticket can be sold that doesn't exist! If we had 10 ticket agents, nine extra tickets could be sold. Clearly, this is a bug in our program (unless we work for an airline!) and demonstrates one of the difficulties inherent in programming with multiple threads of execution.
As I mentioned before, programming with threads can make things much more complicated, and they should be used only when necessary. That said, threads are very useful and are required in many applications. Hopefully this article has whet your appetite for the more advanced threads programming features we'll be looking at in future columns. Next time, we'll look at how to avoid the aforementioned ticket selling problem as well as several other problems that exist in concurrent programming. In the meantime, happy hacking!
Benjamin Chelf is an author and engineer at CodeSourcery, LLC. He can be reached at chelf@codesourcery.com.


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*There was multiple items with the same count or with zero in which case we used the lowest with calories.


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- Variable in class userinterface.jfxcustom.
JFXToggleBtn.ToggleSwitch
PATHS
- Static variable in class miscellaneous.constants.
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Paths()
- Constructor for class miscellaneous.constants.
Application.Paths
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- Static variable in class miscellaneous.constants.
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- Static variable in class miscellaneous.constants.
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- Static variable in class miscellaneous.constants.
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- Static variable in class miscellaneous.constants.
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- Static variable in class miscellaneous.constants.
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- Static variable in class miscellaneous.constants.
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PopupBrowser
- Class in
userinterface.popups
Popup browser window.
PopupBrowser(String, String)
- Constructor for class userinterface.popups.
PopupBrowser
Constructs the popup browser.
POWER
- Static variable in class miscellaneous.constants.
Application.Icons
PREFERENCES
- Static variable in class miscellaneous.constants.
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PreferencesPopup
- Class in
userinterface.popups
Preferences popup-window.
PreferencesPopup()
- Constructor for class userinterface.popups.
PreferencesPopup
Constructs the preferences popup-window.
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---
layout: post
title: '80166304'
tags: []
status: publish
type: post
published: true
meta: {}
---
Been thinking about my requirements management tool. The problem has been about architecture. I need something that will version each requirement and support the maintainance of arbitrary links between requirements (plus other entities such as projects etc.)
The need to maintain complex links would seem to argue the use of a relational database, but the need for versions points to a version repository such as Subversion with embedded html links, this implies webdav or Delta-V server perhaps.
Problems with this
1) If I use an RDBMS then I risk locking users into a single product such Postgresql
2) There are no Delta-V servers yet
It occurs to me that I could give users the choice by hiding the implementation detail behind a design pattern. I could initially do this using Postgresql and then provide alternative implementations if required (I can simulate versions of requirements in a DBMS)


CSC309 project to build a functional website. The front-end used Javascript (jQuery, AJAX), HTML, and CSS. The back-end was written in Node.js. A MySQL database was used to store data. The project was hosted on Openshight, a cloud development platform.
CSC318 project encompassing the lifecycle model of interaction design. First, we conducted research to understand our users' needs. Then, we sketched and mocked up some designs. I developed the main part of the high-fidelity prototype using Javascript, HTML, and CSS. Finally, we conducted usability tests of the high-fidelity prototype.
Use this area of the page to describe your project. The icon above is part of a free icon set by Flat Icons. On their website, you can download their free set with 16 icons, or you can purchase the entire set with 146 icons for only $12!
CSC428 Human-Computer Interaction research project. We investigated the speed and accuracy of three different forms of mobile input: one-finger tapping, two-finger tapping, and swiping.
Use this area of the page to describe your project. The icon above is part of a free icon set by Flat Icons. On their website, you can download their free set with 16 icons, or you can purchase the entire set with 146 icons for only $12!


In this example we create two layer groups lines, and shapes. We insert markers in both layers (note that on is initially visible and one not).


WikDict Downloadable dictionaries
- Kobo, For Rakuten Kobo e-readers
- SQLite, Generic sqlite databases for developers
- Stardict, For StarDict compatible dictionary applications
- TEI, XML dictionaries according to TEI P5
- wdweb, DBs used by the wikdict-web application at WikDict.com


Generation JWD Bootcamp
No Fear Project
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---
layout: post
title: PlasmoDB 7.0 Released
category: [PlasmoDB]
---
We are pleased to
announce the release of PlasmoDB 7.0
This release of PlasmoDB contains the following new datasets and
features:
New Data:
- Updated sequence and
annotation for Plasmodium falciparum, P. chabaudi, P. knowlesi and P. berghei was obtained from the
Pathogen Sequencing Unit at the Wellcome Trust Sanger Institute.
Additional details may be viewed here.
- Updated linkouts to the Malaria Parasite Metabolic Pathways
(MPMP) database. Numerous pathways have been added and updated by
Dr. Hagai Ginsburg. A full description of new pathways is
available here
and genes included in the MPMP database can be searched based on
metabolic pathway in PlasmoDB here.
- Plasmodium falciparum, P.
vivax, P. yoelii, P. berghei and P. chabaudi predicted ApiAP2
transcription-factor (TF) binding site data. This data was
graciously provided prepublication by Dr. Manuel Llinas. Gene
with predicted binding sites to each ApiAP2 TF may be identified using
the TF
binding site search available via the Transcript Expression section
of PlasmoDB. Search parameter such as distance from the 5' end,
number of TF binding sites and probability score can be adjusted as
needed. In addition, TF binding sites can be viewed in the genome
browser with additional information available when mousing over TF
binding site graphics. An example genome browser page may be
viewed here.
- P. falciparum
RNA-sequence data from the intraerythrocytic life cycle. This
data was graciously provided prepublication to the community via
PlasmoDB by Dr. Richárd Bártfai, Wieteke A.M. Hoeijmakers and Dr.
Hendrik G. Stunnenberg. Searches against this data may be
accessed from the RNA-seq
evidence section in the Transcript Expression section
of PlasmoDB. RNA-seq data may also be viewed on individual gene
pages where a graphical representation of the gene's expression profile
throughout the time points of this study is presented. In
addition, RNA-seq coverage graphs can be viewed through the
PlasmoDB genome
browser.
- P. falciparum
ChIP-sequence data from the intraerythrocytic life cycle. ChIP
was performed using antibodies to H2A.Z, H3K9ac & H3K4me3. This
data was graciously provided prepublication to the community via
PlasmoDB by Dr. Richárd Bártfai, Wieteke A.M. Hoeijmakers and Dr.
Hendrik G. Stunnenberg. This data can be viewed through the
PlasmoDB genome
browser.
- P. falciparum
RNA-sequence data of lab-adapted field parasites from malaria-infected
pregnant women and children. This data was graciously provided
prepublication to the community via PlasmoDB by Drs. Marissa Vignali
and Patrick E. Duffy. Searches against this data may be accessed
from the RNA-seq
evidence section in the Transcript
Expression section
of PlasmoDB. RNA-seq data may also be viewed on individual gene
pages
where a graphical representation of the gene's expression profile
throughout the time points of this study is presented. In
addition,
RNA-seq coverage graphs can be viewed through the PlasmoDB genome
browser.
New features in this release include:


The Access relationship represents the ability of behavior and active structure elements to observe or act upon passive structure elements.
The Access relationship indicates that a process, function, interaction, service, or event "does something" with a passive structure element; e.g., create a new object, read data from the object, write or modify the object data, or delete the object. The relationship can also be used to indicate that the object is just associated with the behaviour.
The arrow indicates the flow of information.
Dependency.
Create a new object, Read data from an object, Write or modify object data, Delete an object.
The “Create Invoice” sub-process writes/creates the “Invoice” business object; the “Send Invoice” sub-process reads that object


Next: ignore-errors, Previous: handler-bind, Up: Conditions Dictionary
handler-case
expression
[[{!error-clause}* | !no-error-clause]] ⇒ {result}*
clause ::=!error-clause | !no-error-clause
error-clause ::=(typespec ([var]) {declaration}* {form}*)
no-error-clause ::=(:no-error lambda-list {declaration}* {form}*)
expression—a form.
typespec—a type specifier.
var—a variable name.
lambda-list—an ordinary lambda list.
declaration—a declare expression; not evaluated.
form—a form.
results—In the normal situation, the values returned are those that result from the evaluation of expression; in the exceptional situation when control is transferred to a clause, the value of the last form in that clause is returned.
handler-case executes expression in a dynamic environment where various handlers are active. Each error-clause specifies how to handle a condition matching the indicated typespec. A no-error-clause allows the specification of a particular action if control returns normally.
If a condition is signaled for which there is an appropriate error-clause during the execution of expression (i.e., one for which (typep condition 'typespec) returns true) and if there is no intervening handler for a condition of that type, then control is transferred to the body of the relevant error-clause. In this case, the dynamic state is unwound appropriately (so that the handlers established around the expression are no longer active), and var is bound to the condition that had been signaled. If more than one case is provided, those cases are made accessible in parallel. That is, in
(handler-case form (typespec1 (var1) form1) (typespec2 (var2) form2))
if the first clause (containing form1) has been selected, the handler for the second is no longer visible (or vice versa).
The clauses are searched sequentially from top to bottom. If there is type overlap between typespecs, the earlier of the clauses is selected.
If var is not needed, it can be omitted. That is, a clause such as:
(typespec (var) (declare (ignore var)) form)
can be written (typespec () form).
If there are no forms in a selected clause, the case, and therefore handler-case, returns nil. If execution of expression returns normally and no no-error-clause exists, the values returned by expression are returned by handler-case. If execution of expression returns normally and a no-error-clause does exist, the values returned are used as arguments to the function described by constructing (lambda lambda-list {form}*) from the no-error-clause, and the values of that function call are returned by handler-case. The handlers which were established around the expression are no longer active at the time of this call.
(defun assess-condition (condition) (handler-case (signal condition) (warning () "Lots of smoke, but no fire.") ((or arithmetic-error control-error cell-error stream-error) (condition) (format nil "~S looks especially bad." condition)) (serious-condition (condition) (format nil "~S looks serious." condition)) (condition () "Hardly worth mentioning."))) ⇒ ASSESS-CONDITION (assess-condition (make-condition 'stream-error :stream *terminal-io*)) ⇒ "#<STREAM-ERROR 12352256> looks especially bad." (define-condition random-condition (condition) () (:report (lambda (condition stream) (declare (ignore condition)) (princ "Yow" stream)))) ⇒ RANDOM-CONDITION (assess-condition (make-condition 'random-condition)) ⇒ "Hardly worth mentioning."
handler-bind, ignore-errors, Condition System Concepts
(handler-case form (type1 (var1) . body1) (type2 (var2) . body2) ...)
is approximately equivalent to:
(block #1=#:g0001 (let ((#2=#:g0002 nil)) (tagbody (handler-bind ((type1 #'(lambda (temp) (setq #1# temp) (go #3=#:g0003))) (type2 #'(lambda (temp) (setq #2# temp) (go #4=#:g0004))) ...) (return-from #1# form)) #3# (return-from #1# (let ((var1 #2#)) . body1)) #4# (return-from #1# (let ((var2 #2#)) . body2)) ...)))
(handler-case form (type1 (var1) . body1) ... (:no-error (varN-1 varN-2 ...) . bodyN))
is approximately equivalent to:
(block #1=#:error-return (multiple-value-call #'(lambda (varN-1 varN-2 ...) . bodyN) (block #2=#:normal-return (return-from #1# (handler-case (return-from #2# form) (type1 (var1) . body1) ...)))))
Next: ignore-errors, Previous: handler-bind, Up: Conditions Dictionary


@(userForm: Form[User]) @import helper._ @import helper.twitterBootstrap._ @main("LMS Sign Up") {
We respect your privacy.


Why JSON Web Tokens Are Awesome | Demo!
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Gene name: {{geneName}} Entry ID: {{entryID}} PDB File: Download Model Created Date: {{modelCreatedDate}} Version: {{version}} Original Source: Link EBI AlphaFold Predicted Structure Database


Gaussian Elimination
Enter some equations in the form: ax0 + bx1 - cx2 + ... + dxn = e, where letters represent numbers of your choosing. Please enter the same number of equations as variables and make sure to hit 'enter' between equations!
Solve!
Results:
Intermediate Matrices:


Those pesky humans have been taking shots are your superior Yoloid space vessel again. The Yoloid hive mind instructs you and your crew to land at a nearby planet and pillage it for materials and resources and then return to Yolos. It is very unlikely you will encounter any filthy humans while on this planet. For the eternal glory of Yolos!
As an experienced Yoloid space commander, you already know that you will need to ensure that each of your crew has at least one unit of food every day, and that your ship must be repaired and fueled to take off again. You also know that if a region is hazardous, consider sending multiple crew members and possible arming them to reduce the risk of losing crew, or perhaps engage in a hunting mission to reduce the danger. Filthy humans have been known to sacrifice their crew on planetary expeditions (often marking them with red colored clothing), but not the superior Yoloeans! (No promises about the Yoloid from the Swaghus system; those clowns make poor decisions all the time.)
Select landing location to begin.Copyright (c) Andrew Jenner 2014. MIT License


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This is a simple Web Intent that handles
the "view" intent for feeds (the application/atom+xml
and
application/rss+xml
types). The passed in feed is displayed
as pretty-printed XML. Developers that use Chrome 20 or later may find this
useful when trying to view raw feed data.
You may test it out by entering a feed URL below:


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Other Music's Favorite Records: Part 1
Sep 10, 2012 . New York record store Other Music (15 E 4th St, NYC) is curating a selection of new releases this week at the GQ & Nordstrom Men's Shop.
http://blogs.nordstrom.com/men/other-musics-favorite-records-1/
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2828 S 9th St
East 4th HornS
East 4th HornS happen to be one of the hottest units out of NY. . Some other musicians that recorded with the East 4th HornS in the section are Arturo Sandoval .
http://www.testoftimerecords.com/artists/east4thhorns.html
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202 S 6th St
FABulous East 4th Street
Apr 11, 2012 . working together to save their homes on East 4th Street, where . The City has only designated East 4th Street and BAM (Brooklyn Academy of Music) as . 4th Street will have applications to other neighborhoods that want to .
http://gvshp.org/blog/2012/04/11/fabulous-east-4th-street/
428 E Almar Dr
Other Music - Best Record Store in New York City | Revel in New York
15 E 4th St New York, NY<PHONE_NUMBER>. HOURS Weekdays - 12pm - 9pm. Saturday - 12pm - 8pm. Sunday - 12pm - 7pm. Other Music is a Manhattan based .
http://www.revelinnewyork.com/takeaways/other-music
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See us in. The New York Times. Looking For a Music Teacher? Click Here. VISA MasterCard. Keshav Music - 67 East 4th St. - NYC - NY - 10003 /<PHONE_NUMBER> .
http://www.keshav-music.com/
Bridges Hall of Music - Pomona College
In addition to performances, this stunning facility provides a remarkable space for other college events. Bridges Hall of Music 150 E. 4th Street, Claremont, CA .
http://www.pomona.edu/academics/departments/music/facilities/bridges.aspx
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ENTERTAINMENT OtherMusic-NYC. 15 E. 4th St., New York, NY (Lafayette St. & Broadway)<PHONE_NUMBER> www.othermusic.com. Ever visit iTunes and can't find .
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Cologne Cloud Solutions
René Skupin, Tobias Fuchs, Mark Meiwald, Özgür Genc, Dennis Smuda
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Entities vs Value types
When we create domain model we must deal with two kinds of objects:
entities and value types. Entities represents objects that have some notion of
identity like person or a vehicle. Person may change name or even sex but we still use
the same object to represent that particular person, we only update object attributes
(e.g. even if I change my name I’m still myself).
Entities always have some kind of identifier that allows us to
distinguish them, this may be a
surrogate key like Long id
or
a natural key
like national id/social security number in case of person.
The other kind of objects that we encounter in domain model are value types. Value types represent things like addresses, phone numbers, money amounts, currencies etc. Value types are immutable and don’t need to have any identifier - two value types are equal if they contents are equal. If we need to update value type we just create a new instance of value type with updated attributes.
What this have to do with embeddable types?
In most cases embeddable types should be used to represent only value types
of your domain model.
Now let’s see the code!
Embeddable in Hibernate
We will start by creating User
entity that will have two embeddable value types
PhoneNumber
and MoneyAmount
:
We don’t need to use any additional annotations to map embeddable types, we just declare them like any other field. Later we will see that we may change embeddable type mappings when needed.
Now let’s see how PhoneNumber
value type looks like.
Since it is our first value type I will present entire class:
First thing we should notice is that PhoneNumber
instances are immutable.
We can set phoneNumber
using constructor,
but we cannot change it.
Notice also that we overriden equals()
and hashCode()
to
provide value equality - two phone numbers are equal if they string
representations are equal.
To improve debugging experience we also overriden toString()
method.
The other class MoneyAmount
looks like this:
Notice that this class provides additional operations like add()
.
Because value types are immutable we cannot change already
exiting MoneyAmount
instance, instead we return a new object that
will represent result of the add()
operation.
Now let’s get to the Hibernate part.
Embeddable types must be marked with
@Embeddable
annotation,
they can contain one or more fields and every
field may carry @Column
mappings.
Embeddable types may contain other embeddable types,
but they cannot contain @Id
field.
When Hibernate stores embeddable types in database they are
stored in table of the entity that contains them.
For example for our User
entity Hibernate will generate table:
Sometimes we want to change e.g. one of the column names of the embeddable type
but only in certain containing type.
For example let’s say that we want to map PhoneNumber
in User
to phone_number
column. We may do this using @AttributeOverride
annotation:
Unfortunately when we override column attributes we must redefine all of them, and syntax to do so it pretty verbose.
Now it’s time to save some ickle embeddables to database:
This operation will result in SQL:
We may also update embeddable type by providing new instance:
This will generate UPDATE
:
Embeddable types and nullability
Hibernate stores null embeddable type as NULL
values in
all embeddable type columns. You can save object with null
embeddable type only if all embeddable type columns are nullable.
When you try to do this with embeddable type that contains non-null
columns Hibernate will throw exception:
Sharing embeddable types between entities
Embeddable types follow value semantics, this means when we save the same instance of embeddable type in two different entities and then read back these entities we will get two instances of embeddable type:
This is generally not a problem because we should compare value types
using equals()
anyway.
Mapping many instances of embeddable type in the same entity
Let’s say we want to extend our User
entity to allow users to provide
second phone number. If we only add second PhoneNumber
field to the User
class,
Hibernate will not know how to name columns of the second PhoneNumber
.
This will result in the exception:
We can easly fix this using @AttributeOverride
annotation:
Collections of embeddable types
Embeddable types may be used as collection elements. Let’s extend our User
class
so that user can have any number of phone numbers:
In this case collection elements are owned by entity class, if entity is removed all collection elements are removed as well. In database this will be represented by two tables:
Before you start using this method you must know how Hibernate will perform inserts/updates. Basically Hibernate first will remove all rows associated with given entity and then will perform many inserts (one insert per one collection element). This is horrible from performance point of view so use this mapping only with small collections.
Here is a bit of code to illustrate the point:
This will result in SQL:
Allowing duplicates in collection
If we want to allow duplicates in embeddable type collection we should map it as a bag:
This will result in database schema: Unfortunatelly this will not improve bad performance of embeddable type collections.
You can improve performance a bit (mainly with inserts) using @OrderColumn
annotation,
more informations can be found in these articles:
- StackOverflow: strange delete/insert behaviour
- How to Optimize Hibernate ElementCollection Statements
The End
In this blog post I only scratched the surface of the embeddable types, there is more to learn about them. If you want to dig deeper I advice reading great book: Java Persistence with Hibernate 2nd.
Thats all for today, thanks for reading!


????? ????????
on 2012-04-11 15:44:22
Great job here. I really enjoyed what you had to say. Keep going because you definitely bring a new voice to this subject. Not many people would say what you’ve said and still make it interesting
Orme
on 2011-01-09 15:13:52
Hmm, I used such string as str2 -- '\0 \t\x0B' and it works fine without escaping. RegExp get already escaped string with exact characters you expect. One thing that matching should be multiline, so \m modifier should be added.
Brett Zamir
on 2011-01-08 15:34:58
@Orme: Also, in seeing now that str2 is added within a character class in your implementation, you wouldn't need to escape as many characters--only \, ], and - should I think be enough for JS character classes, but you do need to escape them.
Brett Zamir
on 2011-01-08 15:23:12
@Orme: You'll need to escape str2 (e.g., by using preg_quote: http://phpjs.org/functions/preg_quote:491 ) since the RegExp could be problematic if special characters are added without escaping. Could you check whether the performance is still better after such escaping is done and then if it passes some test cases, we could accept it.
Orme
on 2011-01-07 19:20:46
I understand that it's not in format, but using regexp in this function is faster in all browsers.
function strspn (str1, str2, start, lgth) {
str1 = start ? lgth ? str1.substr(start, lgth) : str1.substr(start) : str1;
var match = str1.match(new RegExp('^['+str2+']+'));
return match && match[0] ? match[0].length : 0;
}
Kevin van Zonneveld
on 2008-12-30 10:22:59
@ Brett Zamir: Good job man, added!
Brett Zamir
on 2008-12-18 01:49:13
I think this should add the other two args...
strspn('42 is the answer, what is the question ...', '1234567890');
strspn("foo", "o", 1, 2); // 2
function strspn(str1, str2, start, lgth){
// http://kevin.vanzonneveld.net
// + original by: Valentina De Rosa
// % note 1: Good start, but still missing the 3rd & 4th argument which came to PHP in version 4.3.0
// * example 1: strspn('42 is the answer, what is the question ...', '1234567890');
// * returns 1: 2
var found;
var stri;
var strj;
var j = 0;
var i = 0;
start = start ? (start < 0 ? (str1.length+start) : start) : 0;
lgth = lgth ? ((lgth < 0) ? (str1.length+lgth-start) : lgth) : str1.length-start;
str1 = str1.substr(start, lgth);
for(i = 0; i < str1.length; i++){
found = 0;
stri = str1.substring(i,i+1);
for (j = 0; j <= str2.length; j++) {
strj = str2.substring(j,j+1);
if (stri == strj) {
found = 1;
break;
}
}
if (found != 1) {
return i;
}
}
return i;
}


(*) [KMN02] A Sparse Sampling Algorithm for Near-Optimal Planning in Large Markov Decision Processes paper
PAC formulation
[AAKMR02] A Note on the Representational Incompatibility of Function Approximation and Factored Dynamics.pdf
Barrier to solving factored MDP’s is not just computational ([PT87]), it is representational (there is no succinct policy)
DBN-MDP (factored MDP): transition law \(\de\) is dynamic Bayes net. The first layer are the variables (and action) at time \(t\), the second layer are the variables at time \(t+1\), the graph is directed, the indegree of each second-layer node is at most constant.
Rewards are linear.
Connection with AM-games: V’s state corresponds to state, P implements policy.
If PSPACE is not contained in P/POLY, then there is a family of DBN-MDPs, such that for any two polynomials \(s,a\), there exist infinitely many \(n\) such that no circuit \(C\) of size \(s(n)\) can compute a policy having expected reward greater than \(\rc{a(n)}\) times the optimum.
(This is the policy optimization part. Can you learn Bayes nets? @Andrej)
(Note that the “drifting context vector (RANDWALK)” model can be represented by a model with \(1\to 1', 2\to 2',\ldots\).)
What if you only compared to the best policy in a class of policies? (cf. EXP4)
MDPs
Convergence of classic algorithms
[PB79] On the convergence of policy iteration in stationary dynamic programming.pdf
Equivalent to Newton-Kantorovich iteration procedure applied to functional equation of dynamic programming.
Sufficient conditions for superlinear or quadratic convergence. See [Howard].
Note: Does NOT apply to finite state MDPs! (Problem being that “best action” is not continuous in parameters?)
[SR04] Convergence properties of policy iteration.pdf
Compare to method of successive approximations. SA is bad when \(\ga\approx 1\).
[TVR96] An Analysis of Temporal-Difference Learning with Function Approximation paper
\(TD(\la)\) convergence
What is rate??
[B95] Residual Algorithms: Reinforcement learning with function approximation paper
Q-learning instability
[WD92] Q-learning
Given bounded rewards, learning rates \(0\le \al_n<1\), and \(\sumo i{\iy} \al_{n^i(x,a)}=\iy\) (\(n^i(x,a)\) is the \(i\)th time \(a\) is tried in state \(x\)) then \(Q_n\to Q^*\) wp 1.
Doesn’t address: under what \(Q\)? What if updating policy at same time? What’s regret?
Theory algorithms
(*) [AO06] Logarithmic online regret bounds for undiscounted reinforcement learning
UCRL
Maintain confidence bounds on rewards and transition probabilities.
Only apply to unichain MDP’s: the stationary distribution of any policy does not depend on the start state (this is to make things easier, can do without)
Other work: adversarial reward, index policies (choose action with max return in confidence region)
UCRL, under assumption of 2 possible next-states for each state/action pair, PAC bound of \(\wt O \pa{\fc{|S\times A|}{\ep^2(1-\ga)^3}\ln \prc{\de}}\).
[KS02] Near-optimal reinforcement learning in polynomial time
(*) [JOA10] Near-optimal regret bounds for reinforcement learning paper
Improved UCRL (UCRL2)
[KN09] Near-Bayesian Exploration in Polynomial Time paper
[KAL16] Contextual-MDP, which is contextual bandits + RL.
Regret wrt policy class.
Poly in parameters, log in number of policies, independent of size of observation space. \(\poly(M, K, H, \ep, \ln N, \ln \prc\de)\)
Unlike POMDP, optimal policy is memoryless. (Definition is just this. For simplicity, consider layered POMDP’s.)
Ex. Disjoint contexts. Don’t know which observations correspond to which contexts! (Q: for HMM with “too many” observations what can we do?)
Warning: inefficient b/c requires enumeration of policy class. (? does this contradict the poly/log time above)
Assumptions
\(Q\) is realizable within the function class. (WHY doesn’t this work in the agnostic case?)
Deterministic transitions
Algorithm (cMDP-learn)
DFS-learn
TD-elim: eliminate functions that do not approximate \(Q^*\) well (that do significantly worse than the best approximator so far)
Consensus: Compute MC estimates for the observable in the current state (run a lot of episodes, using the same actions up to the current point; because the system is deterministic the state is the same). If they are all close in value, return true, else return false.
Explore-on-demand
Select a surviving policy, estimate \(V\) at root; if highly suboptimal value, invoke DFS-learn on paths visited by \(\pi_f\).
Idea: if a surviving policy \(\pi_f\) visits only states for which TD-Elim has been invoked, it must have near-optimal reward.
Undesirables
Deterministic transition
Enumerate class of regression functions
Realizability assumptions
[DPWR15] Bayesian Nonparametric Methods for Partially-Observable Reinforcement Learning paper
Bayes!
Factored MDPs, MDPs with exponential/continuous state space
[HSMM15] Off-policy Model-based Learning under Unknown Factored Dynamics.pdf
Under 3 assumptions, using a greedy approach to finding parents, estimate the transition function (parameters to Bayes net) (compre with prob models literature?)
This is for off-policy evaluation; it doesn’t tell us how to find the optimal policy.
(Is the model learning and policy evaluation coupled or not?)
(It seems to be learning the Bayes net rather than evaluating \(\pi\). Ah, once you learn the Bayes net then you can evaluate just by sampling.)
The difference from simpling learning a Bayes net is that the samples aren’t independent—they were from following a certain policy. Assumptions will ensure that you can still learn the model even if you only have samples from that policy.
(*) [AMS08] Fitted Q-iteration in continuous action-space MDPs
Fitted Q-iteration: Given a simulator, sample next actions \(s'\) given \(s,a\). Given \(Q^{n}\), approximate \(Q^{n+1}\) with these samples, then approximate \(Q^{n+1}\) as \(Q(s,a)=\te^T\phi(s,a)\). Use least squares: LSFQI. Then pick best \(\wh \pi_{n+1}\) using the approximation of \(Q^{n+1}\).
Space of functions can be neural networks, linear combination of selected basis functions, restriction of RKHS (cf. LS-SVM).
Warning: it’s not just the pseudo-dimension (related to VC dimension) of the function class \(\mathcal F\) that matters, but that of \(\mathcal F_{\max}^{\wedge} = \set{\max_{a\in A} Q(x,a)}{Q\in \mathcal F}\). (Actually, use the notion of fat shattering functions.)
Also called “fitted actor-critic algorithm”.
Under many assumptions, the error in \(V\) can be bounded in terms of the pseudo-dimension of the function class \(\mathcal F\).
[FDMW04] Dynamic Programming for Structured Continuous Markov Decision Problems paper
Group together states belonging to the same “plateau” where expected reward is nearly constant.
Use kd-trees to store the rectangular partitions.
[HK03] Linear Program Approximations for Factored Continuous-State Markov Decision Processes paper
2 settings
Factored MDP’s: approximate \(V\) within a class of functions \(\spn(\{f_i\})\). (Ex. each \(f_i\) depends on a small subset of variables.) Here, minimize \(\sum w_i \sum_x f_i(x)\) over all \(f\)’s that overestimate the reward: \(\sum_i w_i(f_i - \ga \sum_{x_i'} \Pj(x_i'|x_i, a)f_i(x_i'))-R(x,a)\ge 0\) forall \(x,a\).
Problem: infinite number of constraints. Insight: only a finite subset are active at any time.
Continuous MDP’s. Consider conjugate classes of transition models and basis functions that give closed-form expressions.
[LL05] Lazy Approximation for Solving Continuous Finite-Horizon MDPs paper
In value iteration \[V^{n+1}(x) = \max_{a\in A} \ba{R(x,a) + \int_X T(x'|x,a)V^n(x')\dx'}\] replace \(V^n\) with a piecewise constant approximation. (Otherwise it becomes a piecewise higher order polynomial.)
[MTT] A Fast Analytical Algorithm for MDPs with Continuous State Spaces paper
Focuses on MDP’s where the transition time (after an action) is governed by a exponential pdf \(\la e^{-\la t'}\).
[TS06] Probabilistic Inference for Solving Discrete and Continuous State Markov Decision Processes paper
The problem of solving a MDP (with decay \(\ga\)) can be reduced to max likelihood estimation. (It is over a mixture of finite-time MDP’s, weighted geometrically in \(\ga\) in the length.)
Fitted value iteration: Given a simulator, sample next actions \(s'\) given \(s,a\). Given \(V^{n}\), approximate \(V^{n+1}\) with these samples, then approximate \(V^{n+1}\) as \(V(s)=\te^T\phi(s)\) (ex. using least squares).
Can be extended to least-squares policy iteration.
(*) [ALA16] Reinforcement Learning of POMDPs using Spectral Methods paper
Spectral parameter estimation for POMDP’s
Combine with UCRL (exploration-exploitation framework) to get regret bounds (compared to memoryless policies) optimal in dependence on \(N\) (\(O(\sqrt N)\))
Challenges
Unlike HMM, consecutive observations not conditionally independent
Technical: Concentration inequalities for dependent rv’s. Extend to marix value functions.
Previous/other work
UCRL
model-free algorithms (\(Q\)-learning)
policy search methods
separate exploration and exploitation collect examples, then estimate parameters [Guo16]. PAC in RL POMDP?
Regret bounds optimal in \(N\) (\(\wt O(\sqrt N)\)). Depends on a natural notion of “diameter” for POMDP’s (different from definition for MDP’s. max mean passage time using best \(\pi\)).
Idea: by restricting to memoryless policies, generate conditionally independent views.
\(\mathcal P\) set of all stochastic memoryless policies that have a non-zero probability to explore all actions. Assume \(\pi\in \mathcal P\).
Method
Can’t use spectral method for HMM’s.
But same idea: find 3 conditionally independent views (given \(x_t, a_t\)), use a “symmetrization” technique, and find spectral decomposition.
UCRL integration
distribution of the views \(v_1, v_2, v_3\) depends on the policy used to generate the samples. As a result, whenever the policy changes, the spectral method should be re-run using only the samples collected by that specific policy.
Construct set of admissible POMDP’s whose T, O, R models are in confidence interval
Open: analyze UCRL for finite horizon.
Stochastic policies are near-optimal in many domains (?). NP-hard to optimize but under some conditions can approximate
[ALA16] Open Problem - Approximate Planning of POMDPs in the class of Memoryless Policies (COLT2016) paper
Find exact or approximate optimal stochastic memoryless policy for POMDP.
What [ALA16] don’t address in other paper: planning. (Complexity considerations? i.e. is this tractable? Kaelbling98)
In their paper they assume access to an optimization oracle that gives best memoryless planning policy at end of each episode. - No algorithm for this right now!
[GDB16] A PAC RL algorithm for episodic POMDPs paper
PAC: whp, selects near-optial action on all but a number of steps poly in problem paramters (what is the definition?)
PAC learns in time \(T(\ep)\) means: achieves an expected episodic reward of \(V\ge V^*-\ep\) on all but \(T(\ep)\) episodes.
First PAC POMDP RL algorithm for episodic domains
EEPORL
Algorithm 1:
In each episode, take first four steps randomly (in correlated fashion) to explore. Need to assume that have probability of being anywhere in 2 steps.
Take chosen policy for the rest of the steps.
Algorithm 2: Update estimates for POMDP parameters.
Algorithm 3: Find best policy for current estimates of parameters.
Open questions
[S99] Open Theoretical Questions in Reinforcement Learning (not sure how open these are anymore!)
Control with function approximation
TD(\(\la\)) understood [TsVR97]
Q-learning unstable [Baird95]
Sarsa ??? (tends to oscillate close to best)
MC ES convergence (see update in BS?)
Bootstrapping more efficient than MC?
VC dimension over RL
Difficulty: different actions lead to different parts of space, so we don’t have a natural “test set” that can be reused to evaluate different policies (Test set seems like it would be drawn from different policies?)
Proposal: trajectory trees: tree of all sample transitions
Extend PAC to this setting.
Surveys
[G] Reinforcement learning - a Tutorial Survey and Recent Advances.pdf
[KLM96] Reinforcement Learning - A Survey.pdf
[P14] Clearing the Jungle of Stochastic Optimization
4 classes of policies
Dynamic vs. stochastic programs
[P14] Energy and Uncertainty - models and algorithms for complex energy systems.pdf
(*) [P16] A Unified Framework for Optimization under Uncertainty


Car vs. pedestrian accident in Fort Myers
by WFTX Digital TeamFORT MYERS, Fla. — There is an accident involving a car and a pedestrian on McGregor Boulevard south of Fort Myers just across from Gulf Point square.
One victim was placed on a stretcher and taken in an ambulance.
No further information is available at this time. Fox 4 is on scene working on learning more about the incident.


--- title: Tegui city: Buenos Aires, Argentina date: 2019-12-14 mapleft: -307 maptop: -443 listdata: Tegui is the 27th restaurant on the quest. It was 49th on the list in 2017. idx: 27 ogimage: https://res.cloudinary.com/snookca/image/upload/v1578350961/27-tegui/IMG_7462.jpg tags: - post layout: layouts/post.njk ---
In contrast to the evening before, Tegui offered up a tasting menu like most of the 50 Best. In that way, tonight’s meal would be more like what we have come to expect.
Or maybe not.
As the meal started, the sommelier comes over with a cocktail to start. No explanation given but delighted to start in on the pairings for the evening. And then she comes over to start the meal and I received the first actual pairing: a champagne to go with the appetizers. Okay, now I have two drinks. Not a big deal.
The first appetizer is ice plant with sea asparagus. A light, tasty dish. Then the second appetizer comes out. A paste of some kind with oil in the middle. No explanation given. We ate it. It was tasty.
Turns out, that wasn’t the second appetizer. The second appetizer comes out: a tuber native to Argentina. (I didn’t quite catch the name; it sounded like “oshuka”. Maybe the oca tuber?)
Then, we’re given the proper third appetizer. The new dish of paste returns but this time, with asparagus cooked inside of a pizza dough. The asparagus is excised from the baked dough. The bread is taken away, leaving us with the limp asparagus to eat with our fingers and the—what we now learn is—avocado butter.
Despite the awkwardness, all the appetizers were yummy.
Into the main courses, we start off with fennel bulbs on sliced figs on a slice of tomato in a tomato-infused water. This was delicious.
From there, the highlights were the strawberry with scallops, the royal palm that tasted like corn on the cob, and the sweetbread with sliced peaches.
A couple lowlight dishes included green peas on a seed biscuit/cracker and a cholque, pupusa, and tunta on a similar seed biscuit. Both were too large.  I became bored of the dishes about halfway through them. I think they would’ve been better as a bite-sized dish.
Everything else was decent but forgettable. Duck. Venison. Freshly-made Ricotta.
Speaking of the ricotta, as they served the dish, a tiny spider made its appearance on my plate. They quickly whisked the plate away and served the dish again on a new plate, almost forgetting to add the finishing oil.
There were a few other less than smooth moments during the service. It was all rather amusing. I can see why Tegui hasn’t made a return to the ranks of the 50 Best. Although, I can only say that after having been to as many restaurants as I have. Had this restaurant been one of the first high-end restaurants I visited, I’d likely have not thought twice about most of this.
The meal was fine. The wine was fine. With that said, if you do find yourself in Buenos Aires and looking for a great meal, check out Chila. The food and service were better and I think it deserves a spot in the 50 Best.


The Sussex Humanities Lab in collaboration with the School of Media, Film and Music at the University of Sussex wishes to appoint a fixed-term (4-year) fellowship (Research Fellow) in Digital Technologies/Digital Performance. While based in the School of Media, Film and Music, the appointee will work across the Sussex Humanities Lab in collaboration with colleagues in History, Art History & Philosophy, Informatics, and Education and Social Work.
The ideal candidate will have a demonstrable track record of work in performance technologies as a theorist and/or creative practitioner, with clear evidence of technical expertise in all cases. Candidates with knowledge of one or more of the following: creative software (e.g. SuperCollider, Max/MSP or Pure Data), app development, graphic and games programming (e.g. OpenGL, Unity), physical computing, are particularly encouraged.
Further information on Sussex Jobs
A PDF with the job description can be downloaded here: Research Fellow in Digital Humanities/Digital Performance 226


Moscow State University named after MV Lomonosov is one of the oldest and largest classical universities in Russia, one of the centers of Russian science and culture located in Moscow
Location: Moscow, Russia
Faculties: Faculty of Mechanics and Mathematics, Faculty of Computational Mathematics and Cybernetics...
Requirements: IESLTS, SAT
University
Innopolis
International level education in IT sphere. Russian autonomous non-profit organization of higher education in the city of Innopolis
Location: Kazan, Tatarstan
Faculties: Informatics and computer facilities, Management of software development...


Tomorrow is my 4th nerdiversary working @newrelic. Here's to the next 💯 (binary of course...) 10/7/2016, 2:06:00 PM Favs: 13 Retweets: 0 link


head_ref_force_pushed
by None at 2020-01-14 13:54:35.head_ref_force_pushed
by None at 2020-01-14 14:17:05.labeled
by Axa Mei Liauw at 2020-01-14 20:13:41.mentioned
by None at 2020-01-14 20:13:42.subscribed
by None at 2020-01-14 20:13:42.Can you give an example?
This should be super rare, and if it is we should be able to just reindex occasionally.
labeled
by James R. Griffin III at 2020-01-14 15:15:56.labeled
by James R. Griffin III at 2020-01-14 15:15:56.labeled
by None at 2020-01-14 15:41:16.referenced
by Christina Chortaria at 2020-01-14 20:52:46.merged
by Christina Chortaria at 2020-01-14 20:52:46.closed
by Christina Chortaria at 2020-01-14 20:52:46.referenced
by None at 2020-01-13 22:40:36.merged
by None at 2020-01-13 22:40:37.closed
by None at 2020-01-13 22:40:37.head_ref_deleted
by None at 2020-01-13 22:59:58.referenced
by Francis Kayiwa at 2020-01-14 14:59:59.merged
by Francis Kayiwa at 2020-01-14 14:59:59.closed
by Francis Kayiwa at 2020-01-14 14:59:59.head_ref_deleted
by Francis Kayiwa at 2020-01-14 15:00:02.referenced
by Francis Kayiwa at 2020-01-14 15:43:40.merged
by Francis Kayiwa at 2020-01-14 15:43:40.closed
by Francis Kayiwa at 2020-01-14 15:43:41.head_ref_deleted
by Francis Kayiwa at 2020-01-14 15:43:44.review_requested
by Francis Kayiwa at 2020-01-15 00:03:19.referenced
by None at 2020-01-15 00:09:33.merged
by None at 2020-01-15 00:09:33.closed
by None at 2020-01-15 00:09:33.head_ref_deleted
by None at 2020-01-15 00:09:47.labeled
by James R. Griffin III at 2020-01-14 15:06:54.labeled
by James R. Griffin III at 2020-01-14 15:06:54.I already updated the server in Lastpass for the local checkout at least.
labeled
by James R. Griffin III at 2020-01-14 19:56:19.labeled
by James R. Griffin III at 2020-01-14 21:19:14.milestoned
by James R. Griffin III at 2020-01-14 21:19:14.


Knowing how Jenkins is used is a tremendous help in guiding the direction of the development, especially
for open-source projects where users are inherently hard to track down. When this option is enabled,
Jenkins periodically send information about your usage of Jenkins.
Specifically, it contains the following information:
- Your Jenkins version
- For your master and each agent, OS type, and # of executors
- Plugins that are installed and their versions
- Number of jobs per each job type in your Jenkins
The information doesn't contain anything that identifies you or allows us to contact you
(except information inherently revealed by HTTP, such as the IP address). Tabulated
data of these usage statistics submissions will be shared with the community.


For these elections, the country was divided into two geographic regions. The first region voted on October 18 and 19, with runoffs on October 27 and 28, and the other half of the country voted November 22 and 23, with runoffs on December 1 and 2. Following the first stage, administrative courts ordered revotes in four constituencies; re-voting took place on December 6 and 7, with runoffs scheduled for December 15 and 16.
The unique Egyptian electoral system provides that the 596-member House of Representatives is composed of 448 members elected from 205 districts, each with one to four seats; 120 members elected on a winner-take-all basis from lists running in four large districts; and up to 28 members that may be appointed by the president. In the individual constituencies, there are runoffs if a sufficient number of candidates do not achieve a majority in the first round. For the four list districts, the list that obtains a majority of the votes wins all of the available seats in that district; if no list obtains a majority, a runoff is held between the top two lists.
The parliament is made up of 596 seats, with 448 seats elected through the individual candidacy system, 120 elected through winner-take-all party lists (with quotas for youth, women, Christians, and workers) and 28 selected by the president.
The chart on the left represents the 568 winning candidates and their parties


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SPECIFICATIONS
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import argparse
import pandas as pd
from snakemake.utils import report
return df.shape[0]
[docs]def write_report(pred_cds, tag_ending_cds, pot_pyl_cds, final_cds, report_filepath):
"""Write HTML report to summarize the full analysis
:param pred_cds: path to CSV file with predicted CDS info
:param tag_ending_cds: path to CSV file with TAG-ending CDS info
:param pot_pyl_cds: path to CSV file with potential PYL CDS info
:param final_cds_info: path to a CSV file with final information about the CDS
:param report_filepath: path to HTML file in which writing the report
"""
pred_cds_nb = extract_row_number(pred_cds)
tag_ending_cds_nb = extract_row_number(tag_ending_cds)
pot_pyl_cds_nb = extract_row_number(pot_pyl_cds)
df = pd.read_csv(final_cds, index_col=0, header=0)
rej_nb = len(df.query("conserved_start == original_start and conserved_end == original_end"))
final_cds_nb = pot_pyl_cds_nb - rej_nb
print("%s %s %s %s" % (pred_cds_nb, tag_ending_cds_nb, pot_pyl_cds_nb, final_cds_nb))
report(
"""
Prediction of PYL proteins
==========================
{pred_cds_nb} sequences are predicted as CDS (see Table
predicted_cds_).
From these {pred_cds_nb} prediced CDS, {tag_ending_cds_nb} are ending
with a TAG STOP codon (see Table tag_ending_cds_).
{pot_pyl_cds_nb} are predicted as potential PYL sequences (see
Table potential_pyl_cds_).
After similarity search, {final_cds_nb} sequences (of
{pot_pyl_cds_nb} predicted PYL sequences) are conserved ({rej_nb}
rejected) as potential PYL proteins (see Table final_cds_).
""",
report_filepath,
predicted_cds=pred_cds,
tag_ending_cds=tag_ending_cds,
potential_pyl_cds=pot_pyl_cds,
final_cds=final_cds)
if __name__ == "__main__":
parser = argparse.ArgumentParser(description='Write HTML report to summarize the full analysis')
parser.add_argument('--pred_cds', help='path to CSV file with predicted CDS info')
parser.add_argument('--tag_ending_cds', help='path to CSV file with TAG-ending CDS info')
parser.add_argument('--pot_pyl_cds', help='path to CSV file with potential PYL CDS info')
parser.add_argument('--final_cds_info', help='path to a CSV file with final information about the CDS')
parser.add_argument('--report_filepath', help='path to HTML file in which writing the report')
args = parser.parse_args()
write_report(
pred_cds=args.pred_cds,
tag_ending_cds=args.tag_ending_cds,
pot_pyl_cds=args.pot_pyl_cds,
final_cds=args.final_cds_info,
report_filepath=args.report_filepath)


You can import all these objects directly from werkzeug.
Implements a callable that constructs URLs with the given base. The function can be called with any number of positional and keyword arguments which than are used to assemble the URL. Works with URLs and posix paths.
Positional arguments are appended as individual segments to the path of the URL:
>>> href = Href('/foo')
>>> href('bar', 23)
'/foo/bar/23'
>>> href('foo', bar=23)
'/foo/foo?bar=23'
If any of the arguments (positional or keyword) evaluates to None it will be skipped. If no keyword arguments are given the last argument can be a dict or MultiDict (or any other dict subclass), otherwise the keyword arguments are used for the query parameters, cutting off the first trailing underscore of the parameter name:
>>> href(is_=42)
'/foo?is=42'
>>> href({'foo': 'bar'})
'/foo?foo=bar'
Combining of both methods is not allowed:
>>> href({'foo': 'bar'}, bar=42)
Traceback (most recent call last):
...
TypeError: keyword arguments and query-dicts can't be combined
Accessing attributes on the href object creates a new href object with the attribute name as prefix:
>>> bar_href = href.bar
>>> bar_href("blub")
'/foo/bar/blub'
If sort is set to True the items are sorted by key or the default sorting algorithm:
>>> href = Href("/", sort=True)
>>> href(a=1, b=2, c=3)
'/?a=1&b=2&c=3'
New in version 0.5: sort and key were added.
Parse a querystring and return it as MultiDict. Per default only values are decoded into unicode strings. If decode_keys is set to True the same will happen for keys.
Per default a missing value for a key will default to an empty key. If you don’t want that behavior you can set include_empty to False.
Per default encoding errors are ignored. If you want a different behavior you can set errors to 'replace' or 'strict'. In strict mode a HTTPUnicodeError is raised.
Changed in version 0.5: In previous versions “;” and “&” could be used for url decoding. This changed in 0.5 where only “&” is supported. If you want to use “;” instead a different separator can be provided.
The cls parameter was added.
| Parameters: |
|
|---|
URL encode a dict/MultiDict. If a value is None it will not appear in the result string. Per default only values are encoded into the target charset strings. If encode_keys is set to True unicode keys are supported too.
If sort is set to True the items are sorted by key or the default sorting algorithm.
New in version 0.5: sort, key, and separator were added.
| Parameters: |
|
|---|
URL encode a single string with a given encoding.
| Parameters: |
|
|---|
URL encode a single string with the given encoding and convert whitespace to “+”.
| Parameters: |
|
|---|
URL decode a single string with a given decoding.
Per default encoding errors are ignored. If you want a different behavior you can set errors to 'replace' or 'strict'. In strict mode a HTTPUnicodeError is raised.
| Parameters: |
|
|---|
URL decode a single string with the given decoding and decode a “+” to whitespace.
Per default encoding errors are ignored. If you want a different behavior you can set errors to 'replace' or 'strict'. In strict mode a HTTPUnicodeError is raised.
| Parameters: |
|
|---|
Sometimes you get an URL by a user that just isn’t a real URL because it contains unsafe characters like ‘ ‘ and so on. This function can fix some of the problems in a similar way browsers handle data entered by the user:
>>> url_fix(u'http://de.wikipedia.org/wiki/Elf (Begriffskl\xe4rung)')
'http://de.wikipedia.org/wiki/Elf%20%28Begriffskl%C3%A4rung%29'
| Parameters: |
|
|---|
Converts a URI in a given charset to a IRI.
Examples for URI versus IRI
>>> uri_to_iri('http://xn--n3h.net/')
u'http://\u2603.net/'
>>><EMAIL_ADDRESS><EMAIL_ADDRESS>Query strings are left unchanged:
>>> uri_to_iri('/?foo=24&x=%26%2f')
u'/?foo=24&x=%26%2f'
New in version 0.6.
| Parameters: |
|
|---|
Converts any unicode based IRI to an acceptable ASCII URI. Werkzeug always uses utf-8 URLs internally because this is what browsers and HTTP do as well. In some places where it accepts an URL it also accepts a unicode IRI and converts it into a URI.
Examples for IRI versus URI:
>>> iri_to_uri(u'http://☃.net/')
'http://xn--n3h.net/'
>>><EMAIL_ADDRESS><EMAIL_ADDRESS>New in version 0.6.
| Parameters: |
|
|---|
Extracts the path info from the given URL (or WSGI environment) and path. The path info returned is a unicode string, not a bytestring suitable for a WSGI environment. The URLs might also be IRIs.
If the path info could not be determined, None is returned.
Some examples:
>>> extract_path_info('http://example.com/app', '/app/hello')
u'/hello'
>>> extract_path_info('http://example.com/app',
... 'https://example.com/app/hello')
u'/hello'
>>> extract_path_info('http://example.com/app',
... 'https://example.com/app/hello',
... collapse_http_schemes=False) is None
True
Instead of providing a base URL you can also pass a WSGI environment.
New in version 0.6.
| Parameters: |
|
|---|
Helper object for HTML generation.
Per default there are two instances of that class. The html one, and the xhtml one for those two dialects. The class uses keyword parameters and positional parameters to generate small snippets of HTML.
Keyword parameters are converted to XML/SGML attributes, positional arguments are used as children. Because Python accepts positional arguments before keyword arguments it’s a good idea to use a list with the star-syntax for some children:
>>> html.p(class_='foo', *[html.a('foo', href='foo.html'), ' ',
... html.a('bar', href='bar.html')])
u'
foo bar
'
This class works around some browser limitations and can not be used for arbitrary SGML/XML generation. For that purpose lxml and similar libraries exist.
Calling the builder escapes the string passed:
>>> html.p(html("<foo>"))
u'
<foo>
'
Replace special characters “&”, “<” and “>” to HTML-safe sequences. If the optional flag quote is True, the quotation mark character (“) is also translated.
There is a special handling for None which escapes to an empty string.
| Parameters: |
|
|---|
The reverse function of escape. This unescapes all the HTML entities, not only the XML entities inserted by escape.
| Parameter: | s – the string to unescape. |
|---|
Represents a user agent. Pass it a WSGI environment or a user agent string and you can inspect some of the details from the user agent string via the attributes. The following attributes exist:
the browser platform. The following platforms are currently recognized:
the name of the browser. The following browsers are currently recognized:
(Browsers maked with a star (*) are crawlers.)
A decorator that converts a function into a lazy property. The function wrapped is called the first time to retrieve the result and then that calculated result is used the next time you access the value:
class Foo(object):
@cached_property
def foo(self):
# calculate something important here
return 42
The class has to have a __dict__ in order for this property to work.
Changed in version 0.6: the writeable attribute and parameter was deprecated. If a cached property is writeable or not has to be documented now. For performance reasons the implementation does not honor the writeable setting and will always make the property writeable.
Maps request attributes to environment variables. This works not only for the Werzeug request object, but also any other class with an environ attribute:
>>> class Test(object):
... environ = {'key': 'value'}
... test = environ_property('key')
>>> var = Test()
>>> var.test
'value'
If you pass it a second value it’s used as default if the key does not exist, the third one can be a converter that takes a value and converts it. If it raises ValueError or TypeError the default value is used. If no default value is provided None is used.
Per default the property is read only. You have to explicitly enable it by passing read_only=False to the constructor.
Parse a cookie. Either from a string or WSGI environ.
Per default encoding errors are ignored. If you want a different behavior you can set errors to 'replace' or 'strict'. In strict mode a HTTPUnicodeError is raised.
Changed in version 0.5: This function now returns a TypeConversionDict instead of a regular dict. The cls parameter was added.
| Parameters: |
|
|---|
Creates a new Set-Cookie header without the Set-Cookie prefix The parameters are the same as in the cookie Morsel object in the Python standard library but it accepts unicode data, too.
| Parameters: |
|
|---|
Return a response object (a WSGI application) that, if called, redirects the client to the target location. Supported codes are 301, 302, 303, 305, and 307. 300 is not supported because it’s not a real redirect and 304 because it’s the answer for a request with a request with defined If-Modified-Since headers.
New in version 0.6: The location can now be a unicode string that is encoded using the iri_to_uri() function.
| Parameters: |
|
|---|
Redirect to the same URL but with a slash appended. The behavior of this function is undefined if the path ends with a slash already.
| Parameters: |
|
|---|
Imports an object based on a string. This is useful if you want to use import paths as endpoints or something similar. An import path can be specified either in dotted notation (xml.sax.saxutils.escape) or with a colon as object delimiter (xml.sax.saxutils:escape).
If silent is True the return value will be None if the import fails.
| Parameters: |
|
|---|---|
| Returns: | imported object |
Find all the modules below a package. This can be useful to automatically import all views / controllers so that their metaclasses / function decorators have a chance to register themselves on the application.
Packages are not returned unless include_packages is True. This can also recursively list modules but in that case it will import all the packages to get the correct load path of that module.
| Parameters: |
|
|---|---|
| Returns: | generator |
Check if the function accepts the arguments and keyword arguments. Returns a new (args, kwargs) tuple that can safely be passed to the function without causing a TypeError because the function signature is incompatible. If drop_extra is set to True (which is the default) any extra positional or keyword arguments are dropped automatically.
The exception raised provides three attributes:
This can be useful for decorators that forward user submitted data to a view function:
from werkzeug import ArgumentValidationError, validate_arguments
def sanitize(f):
def proxy(request):
data = request.values.to_dict()
try:
args, kwargs = validate_arguments(f, (request,), data)
except ArgumentValidationError:
raise BadRequest('The browser failed to transmit all '
'the data expected.')
return f(*args, **kwargs)
return proxy
| Parameters: |
|
|---|---|
| Returns: | tuple in the form (args, kwargs). |
Pass it a filename and it will return a secure version of it. This filename can then safely be stored on a regular file system and passed to os.path.join(). The filename returned is an ASCII only string for maximum portability.
On windows system the function also makes sure that the file is not named after one of the special device files.
>>> secure_filename("My cool movie.mov")
'My_cool_movie.mov'
>>> secure_filename("../../../etc/passwd")
'etc_passwd'
>>> secure_filename(u'i contain cool \xfcml\xe4uts.txt')
'i_contain_cool_umlauts.txt'
The function might return an empty filename. It’s your responsibility to ensure that the filename is unique and that you generate random filename if the function returned an empty one.
New in version 0.5.
| Parameter: | filename – the filename to secure |
|---|
Bind the arguments provided into a dict. When passed a function, a tuple of arguments and a dict of keyword arguments bind_arguments returns a dict of names as the function would see it. This can be useful to implement a cache decorator that uses the function arguments to build the cache key based on the values of the arguments.
| Parameters: |
|
|---|---|
| Returns: | a dict of bound keyword arguments. |
New in version 0.6.1.
Hash a password with the given method and salt with with a string of the given length. The format of the string returned includes the method that was used so that check_password_hash() can check the hash.
The format for the hashed string looks like this:
method$salt$hash
This method can not generate unsalted passwords but it is possible to set the method to plain to enforce plaintext passwords. If a salt is used, hmac is used internally to salt the password.
| Parameters: |
|
|---|
check a password against a given salted and hashed password value. In order to support unsalted legacy passwords this method supports plain text passwords, md5 and sha1 hashes (both salted and unsalted).
Returns True if the password matched, False otherwise.
| Parameters: |
|
|---|


This document will attempt to explain the Java-based implementation for SAFS engines. Specifically, how existing classes would be used or subclassed in the creation of a new Java-based engine. Remember that SAFS engines use STAF for cross-process communication. It is essential the engine developer become proficient in the use and understanding of what STAF offers.
Goto: Key Definitions, Using and Subclassing, Standardizing Component Recognition.
This protocol is officially defined in our STAF Environment doc: see Table 2: "SAFS Multi-Process Syncronization" in that document. It uses the internal SEM service of STAF.
Key Protocol Events:
<=== Engine "Ready" ===>
The engine is idle and "ready" for dispatch by any STAF client. All STAF clients listening for this event will be notified when the engine is ready.
<=== Client "Dispatch" ===>
A listening STAF client can seize the SAFS/Hook/TRD Mutex and "dispatch" the engine to process the test record it has stored in SAFSVARS.
<=== Engine "Running" ===>
The engine is now "running" a test record or performing other activities and is not available for dispatch. All STAF clients listening for this event will be notified when the engine is running and, thus, not available.
<=== Engine "Results" ===>
The engine has completed processing and has stored the results in the shared SAFS/Hook data space. All STAF clients listening for this event will be notified when the engine has completed processing and the results of that processing are available. Generally, the only client really interested in this event is the one that dispatched the engine.
<=== Client "Done" ===>
The STAF client signals that it has retrieved the results from SAFSVARS. The client would then release the SAFS/Hook/TRD Mutex and the engine would reset itself back into the "Ready" state.
The STAFHelper object registers the client or engine with STAF and simplifies communication with STAF and our SAFS Framework tools and services. STAFProcessHelpers can insure that any given process registers and reuses only 1 STAFHelper.
GUI Testing Tool class, object, or script used to inject the testing tool as a valid SAFS engine. This hook is not a service. It is a normal STAF client that registers with STAF and conforms to the event-driven protocol
defined above. This doc will focus on our JavaHook because that is what we currently have. Hooks based on C, Perl, Tcl, VB, or any supported STAF language are also possible using these same concepts.
This is the detailed information of what action, command, or "thing" needs to be done. This is generally made up of the test input record, what test table (file) it came from, and the current status of test processing, etc.. An official description of the Test Record Data expected by SAFS Engines can be found in our Test Record Data doc. All data exchanged between a driver and any number of engines is done through Test Record Data storage in SAFSVARS.
A driver generally has a minimal local version of the TRD it maintains as it calls various engines to complete tests. The driver copies required elements of this local TRD into the shared SAFS/HOOK/TRD in SAFSVARS so that all SAFS engines have access to the information needed to accomplish the tests when dispatched.
Each SAFS engine will retrieve the information passed via SAFSVARS and populate its own local TestRecordHelper(TRH) subclass. The engine, being based on a specific GUI testing tool, will have additional information stored in its TRH subclass that is specific to how that tool locates and identifies GUI components, and any other information the GUI tool needs to accomplish the task.
The ProcessRequest class is the primary router of test records once the engine hook has received a dispatch. This class receives and maintains the list of individual Processors to be used on a test record. There may be one or more Processors for Driver Commands, Component Functions, and Custom Processors--whatever is needed by the engine developer or any particular site.
The SAFSLOGS service provides central logging to be utilized by all STAF clients involved in the test. The Java LogUtilities provides access to this service for our Java-based clients. Clients can generally log to this directly. More often, Java-based engines subclass the existing LogUtilities in order to include logging (and reporting?) provided by their GUI testing tool.
It is important to note that the design of LogUtilities does not mean you choose between using SAFSLOGS, or using your tool's logging instead. The design is intended to allow you to log to all possible and enabled log outputs with a single function call. SAFSLOGS outputs text logs, console logs, and XML logs and informs the subclassed tool-specific LogUtilities which log modes are active and enabled.
Basic routines to help GUI testing tools locate and deal with GUI components. Each Java-based SAFS engine based on a different GUI testing tool will have its own subclass of these DDGUIUtilities. This is required because each tool has a unique way of finding and identifying GUI components.
Perhaps the quickest way for an engine developer to see how the above items would be used is to review the Javadoc, review the base classes, then review the subclasses (top of each Javadoc) that have already been done in support of existing engines. Examples of subclassing exist for the SAFS/RobotJ engine and the SAFS/DriverCommands engine.
On a historical note, the SAFS/RobotJ engine (RJ) was our first Java-based engine and its "hook" mechanism using a "TestScript" and the "RobotJHook" was the model for the general-purpose "JavaHook".
Jump to subclassing JavaHook, TestRecordHelper, LogUtilities, DDGUIUtilities, ProcessRequest/Processors.
An engine-specific
subclass of JavaHook is rather simple. The main task of the subclass is to make sure that the appropriate subclasses of LogUtilities, DDGUIUtilities, TestRecordHelper are instantiated and cross-pollinated with references to each other. (Normally, a subclass of the ProcessRequest class is not necessary.) Override *all* the superclass constructors and implement all the abstract GET methods of the JavaHook superclass. Make sure these GET methods instance and return the appropriate subclass of objects.
If the JavaHook subclass is intended to be run standalone--that is, a runnable Java app in its own JVM--then the subclass will need an appropriate "static void main" entry point as required by all Java applications. An example of such an entry point is shown below. This one is from the SAFS/DriverCommands DCJavaHook subclass of JavaHook.
public static void main (String[] args) {
// SAMPLE STANDARD HOOK INITIALIZATION
// DCJavaHook hook = new DCJavaHook(SAFS_DRIVER_COMMANDS, new LogUtilities());
// SAMPLE ADVANCED HOOK INITIALIZATION
TestRecordHelper datahelper = new TestRecordHelper();
LogUtilities logs = new LogUtilities();
ProcessRequest requester = new ProcessRequest(
datahelper, // TestRecordHelper
logs, // LogUtilities
new DriverCommandProcessor(), // use standard DriverCommandProcessor
null, // disable standard TestStepProcessor
null, // no custom driver command support
null); // no custom test step support
DDGUIUtilities gui_utils = new DCGUIUtilities();
DCJavaHook hook = new DCJavaHook(
SAFS_DRIVER_COMMANDS, // STAF process name for hook instance
STAFHelper.SAFS_HOOK_TRD, // (default) SAFSVARS TestRecordData
logs, // LogUtilities
datahelper, // TestRecordHelper
gui_utils, // DDGUIUtilities
requester); // ProcessRequest
// this should now be properly handled by the superclass...
datahelper.setSTAFHelper(hook.getHelper());
// HOOK INITIALIZATION COMPLETE
if (args.length > 0 && args[0].equalsIgnoreCase("log")) {
Log.setHelper(hook.getHelper());
logs.setCopyLogClass(true);
}
hook.start();
}
The careful observer will notice that this particular engine is for Driver Commands only and is entirely independent of any GUI testing tool. Therefore, there are no special subclasses for LogUtilities, TestRecordHelper, or the ProcessRequest class. There is a "does nothing" generic DCGUIUtilities subclass used for DDDGUIUtilities since the supported Driver Commands in this engine will not be dealing with GUI components.
You may also notice that after all hook initialization is complete, there is additional code dealing with another separate Log class. This class is primarily used for debugging purposes, and this code won't actually do much of anything if a separate debugging Log window has not been launched.
An engine-specific subclass of TestRecordHelper is also fairly straightforward. Primarily, a subclass will override getCompInstancePath() to provide an engine-specific package name prefix for Processors that may be dynamically sought at runtime to handle test records. For example, this method for the RobotJ subclass returns "org.safs.rational" as the package name prefix.
Additionally, the subclass will add any storage and methods needed by the specific engine to handle tool-specific information needed to identify, locate, and even store GUI components referenced by the test record. For example, the RTestRecordData subclass of TestRecordHelper stores Rational RobotJ-specific information and objects needed at runtime to locate application objects.
Again, an easy one to subclass. LogUtilities actually handles everything that is difficult for our shared logging design. RobotJ's RLogUtilities shows how all that is really needed are the wrapper functions "toolLog" to write to your tool-specific logging mechanism and "consoleLog" to write to your tool-specific console (if applicable).
Everything else is handled by LogUtilities. Your engine code simply uses the appropriate logMessage() functions already provided by the LogUtilities superclass. LogUtilities will take care of when and if your tool-specific logging needs to be called.
Things start to get a little more "interesting" with a subclass of DDGUIUtilities. This is largely because we are beginning to identify some key tool-specific functionality that must be satisfied. For example, locating a text item in a List when the reference to the List may be a tool-specific class or object. Unfortunately, at the same time we start to lose important details in our embedded javadoc. Sorry.
DCGUIUtilities represents the minimum abstract functions that must be provided. These are for the SAFS/DriverCommands engine which actually processes no GUI objects, thus needs no real implementation for these methods.
RDDGUIUtilities for RobotJ, on the other hand, provides real, necessary implementations for these. It has also been given many additional fields and methods in support of locating and working with GUI components in the RobotJ toolset.
Until such time as the doc in the superclass can be fleshed out better, you will have to review the source of the DDGUIUtilities superclass and existing subclasses--like the source for DCGUIUtilities and source for RDDGUIUtilities) to get an idea of how best to implement these functions for your specific tool.
Ordinarily, the ProcessRequest class is instanced or initialized with access to all the tool-specific class information it needs to do its job. Thus, it is rare that this class would ever need to be subclassed. It is the Processors instanced by the ProcessRequest class that will likely need a tool-specific subclass.
Processor has already been subclassed to provide partial implementations for handling Driver Commands and Component Functions. Generally, tool-specific subclasses will extend one or both of these two classes to provide the necessary "process" method to handle the incoming request in a tool-specific manner.
Keep in mind, the STAF client that is acting as the DRIVER for these engines will normally have processed all Cycle and Suite level test records; and most Driver Commands too. A new engine based on a specific GUI testing tool normally must only deal with implementing one or more Processors of component functions, and any Driver Commands that might reference or act on GUI objects.
Note, the Javadoc for the DriverCommand and ComponentFunction classes linked above show several existing subclasses for these. Some of these are default implementations, some are default custom classes, and others are implementations specific to the RobotJ engine. The source for these classes provide excellent examples and guidance for implementing your own tool-specific "process()" functions.
One of the issues involved when attempting to use multiple testing tools; or when trying to migrate from one tool to another; is that each tool has devised a unique way of specifying or locating application components. Some tools, like IBM Rational Robot and Mercury's WinRunner, allow you to specify a simple string that contains information about the target component.
Other tools, like IBM Rational RobotJ/XDE Tester, require that you provide a valid instance of a proxy "TestObject" or a similar component object--or the component itself--in order to perform an action on the component.
The SAFS framework is evolving a standardized mechanism for specifying, locating, and then retrieving these component references for each tool-specific technology.
Consult the SAFS Component Recognition document for details of implementing support for this in your tool-specific engine.


At TopoTech, we work with you to create the maps you envision. We provide all of our cartographic services, from concept through delivery, in the most efficient and cost-effective means possible. This includes giving you the copyright and all of the native files so that you can use your maps in whatever ways you feel are necessary for your products. In effect, our goal is to become an extension of your project team.
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accessed by a root entity
guarantees the consistency => interact with as a unit
{
login: "",
email:"",
preferences: {
theme: "dark",
...
},
rating: {
carma: -10,
activity: 100,
...
},
permissions: ["admin","publisher"]
}


Bangkok, Thailand
Robot Building
The bank's whimsical shape was inspired by a child’s toy.
by Tony DunnellIn the late-1970s, the Thai architect Sumet Jumsai was approached by the Bank of Asia. The bank was looking for a design for its new headquarters in Bangkok, something that would reflect the computerization of banking. For a long while, Sumet struggled to come up with a suitable design. But then his son walked into his study carrying a toy robot, and inspiration struck.
Banking and fun don’t generally mix. In Thailand, however, fun has been elevated to a way of life, a revered ethos known as sanuk. Perhaps for this reason the Bank of Asia was so delighted by Sumet’s proposal, and eagerly began construction of the Robot Building.
Completed in 1987 at a cost of US$10 million, the 20-story building was initially the tallest building in the major commercial district of Sathorn. And while it no longer dominates the skyline, it remains one of the most recognizable towers in the city.
The floors of the building decrease in area at regular intervals, creating the “body” of the robot. Two round windows on the top section (the head) resemble lidded eyeballs, giving the robot a cartoon-like—and slightly sleepy—appearance. To complete the effect, Sumet added antennas on the roof, which serve as both communication masts and lightning rods, while the sides of the building are adorned with large metallic-looking nuts, the largest measuring 12.5 feet in diameter (You can see a 3D model of the structure here).
The building was later selected by the Museum of Contemporary Art in Los Angeles as one of the 50 seminal buildings of the century. It has its detractors, of course, but then who doesn’t? And for many people, especially those not overcome by cynicism, the idea of having a giant toy robot standing in the middle of a city is just plain fun. Even if it does contain a whole bunch of bankers.
Know Before You Go
The Robot Building is located at 191 South Sathorn Road in the Sathorn District of Bangkok. It is currently occupied by the United Overseas Bank (which acquired Bank of Asia in 2005) and serves as their Bangkok headquarters. You can get there by taking the BTS Skytain to Chong Nonsi, which is a short walk from the building. You can also see it while traveling on the Skytrain. You’ll see it on your left just after leaving Chong Nonsi station if you’re on the Silom Line heading to Saphan Taksin, or on your right after leaving Surasak station from Saphan Taksin heading towards Siam or National Stadium.
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{% extends '_base.html' %} {% load moc_extras %} {% block head %} {% endblock %} {% block content %}
| Space | Coordinates | Description |
|---|---|---|
| {{ each }} | {{ each.get_centroids }} | {{ each.description|default_if_none:""|truncatewords:30 }} |
This file contains a list of all spaces, and the coordinates of each space (if we have a polygon area for the space, then we convert this to the centroids).
CSV files can be opened in any spreadsheet software
This contains all items in this list with either coordinates or other spatial references (e.g. polygons), in a GeoJSON format.
GeoJSON can be read by GIS software, and is widely used on the web.
This format contains the original shapefile that was uploaded to create this map. Note: not all files have a shapefile.
{% if info.get_shapefile_size %} {% else %}Shapefiles can be read by GIS software.


Shoreditch is a district in London, England. It is within Central and East London and located in the East End, and is divided between the boroughs of Hackney, Tower Hamlets and Islington. A historic entertainment quarter since the 16th century, today it hosts a number of nightclubs and bars to the west, while the east is primarily residential.
In Tower Hamlets, a small part of Shoreditch is a small exclave separated by Bethnal Green from the rest of the district, it is considered part of the district due to the now-closed Shoreditch tube station location. The district itself lies immediately to the north and north east of the City of London while the exclave lies north and east of Spitalfields and south and west of Bethnal Green.


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