--- layout: post title: "CQS and server-generated Entity IDs" description: "Is it a violation of Command Query Separation to update an ID property when saving an Entity to a database?" date: 2016-05-06 17:36 UTC tags: [Software Design] --- {% include JB/setup %}
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In my Encapsulation and SOLID course on Pluralsight, I explain how the elusive object-oriented quality encapsulation can be approximated by the actionable principles of Command Query Separation (CQS) and Postel's law.
One of the questions that invariably arise when people first learn about CQS is how to deal with (database) server-generated IDs. While I've already covered that question, I recently came upon a variation of the question:
"The Create method is a command, then if the object passed to this method have some changes in their property, does it violate any rule? I mean that we can always get the new id from the object itself, so we don't need to return another integer. Is it good or bad practice?"In this article, I'll attempt to answer this question.
I interpret the question like this: an Entity (as described in DDD) can have a mutable Id
property. A Id
property with the newly created record's ID.
As an example, consider this User class:
public class User { public int Id { get; set; } public string FirstName { get; set; } public string LastName { get; set; } }
In order to create a new User in your database, you could define an API like this:
public interface IUserRepository { void Create(User user); }
An implementation of IUserRepository
based on a relational database could perform an INSERT
into the appropriate database, get the ID of the created record, and update the User object's Id
property.
This test snippet demonstrates that behaviour:
var u = new User { FirstName = "Jane", LastName = "Doe" }; Assert.Equal(0, u.Id); repository.Create(u); Assert.NotEqual(0, u.Id);
When you create the u
object, by not assigning a value to the Id
property, it will have the default value of 0. Only after the Create
method returns does Id
hold a proper value.
Does this design adhere to CQS? Yes, it does. The Create
method doesn't return a value, but rather changes the state of the system. Not only does it create a record in your database, but it also changes the state of the u
object. Nowhere does CQS state that an operation can't change more than a single part of the system.
Is it good design, then? I don't think that it is.
First, the design violates another part of encapsulation: protection of invariants. The invariants of any Entity is that is has an ID. It is the single defining feature of Entities that they have enduring and stable identities. When you change the identity of an Entity, it's no longer the same Entity. Yet this design allows exactly that:
u.Id = 42;
// ...
u.Id = 1337;
Second, such a design puts considerable trust in the implicit protocol between any client and the implementation of IUserRepository
. Not only must the Create
method save the User
object in a data store, but it must also update the Id
.
What happens, though, if you replay the method call:
repository.Create(new User { FirstName = "Ada", LastName = "Poe" }); repository.Create(new User { FirstName = "Ada", LastName = "Poe" });
This will result in duplicated entries, because the repository can't detect whether this is a replay, or simply two new users with the same name. You may find this example contrived, but in these days of cloud-based storage, it's common to apply retry strategies to clients.
If you use one of the alternatives I previously outlined, you will not have this problem.
Even if you don't care about replays or duplicates, you should still consider the invariants of Entities. As a minimum, you shouldn't be able to change the ID of an Entity. For a class like User
, it'll also make client developers' job easier if it can provide some useful guarantees. This is part of Postel's law applied: be conservative in what you send. In this case, at least guarantee that no values will be null. Thus, a better (but by no means perfect) User class could be:
public class User { public User(int id) { if (id <= 0) throw new ArgumentOutOfRangeException( nameof(id), "The ID must be a (unique) positive value.");; this.Id = id; this.firstName = ""; this.lastName = ""; } public int Id { get; } private string firstName; public string FirstName { get { return this.firstName; } set { if (value == null) throw new ArgumentNullException(nameof(value)); this.firstName = value; } } private string lastName; public string LastName { get { return this.lastName; } set { if (value == null) throw new ArgumentNullException(nameof(value)); this.lastName = value; } } }
The constructor initialises all class fields, and ensure that Id
is a positive integer. It can't ensure that the ID is unique, though - at least, not without querying the database, which would introduce other problems.
How do you create a new User
object and save it in the database, then?
One option is this:
public interface IUserRepository { void Create(string firstName, string lastName); User Read(int id); void Update(User user); void Delete(int id); }
The Create
method doesn't use the User
class at all, because at this time, the Entity doesn't yet exist. It only exists once it has an ID, and in this scenario, this only happens once the database has stored it and assigned it an ID.
Other methods can still use the User
class as either input or output, because once the Entity has an ID, its invariants are satisfied.
There are other problems with this design, though, so I still prefer the alternatives I originally sketched.
Proper object-oriented design should, as a bare minimum, consider encapsulation. This includes protecting the invariants of objects. For Entities, it means that an Entity must always have a stable and enduring identity. Well-designed Entities guarantee that identity values are always present and immutable. This requirement tend to be at odds with most popular Object-Relational Mappers (ORM), which require that ID fields are externally assignable. In order to use ORMs, most programmers compromise on encapsulation, ending up with systems that are relational in nature, but far from object-oriented.
Comments
>" This includes protecting the invariants of objects. For Entities, it means that an Entity must always have a stable and enduring identity."
Great points.
However, how would you get from void Create(string firstName, string lastName) to User Read(int id) especially if an entity doesn't have a natural key?
Vladimir, thank you for writing. Exactly how you get the ID depends on the exact requirements of your application. As an example, if you're developing a web application, you may simply be creating the user, and then that's the end of the HTTP request. Meanwhile, asynchronously, a background process is performing the actual database insertion and subsequently sends an email to the user with a link to click in order to verify the email. In that link is the generated ID, so when your server receives the next request, you already know the ID.
That may not always be a practical strategy, but I started to describe this technique, because my experience with CQRS and REST tells me that you have lots of options for communicating state and identity. Still, if you need an ID straight away, you can always pass a GUID as a correlation ID, so that you can later find the Entity you created. That's the technique I originally described.
Thank you for the reply.
BTW, ORMs don't require you to make Ids externally assignable. You can have ORMs assign Ids for you internally, and that's a preferred design in most cases. Also, you can make the Id setters non-public and thus protect entities' encapsulation. There still are issues, of course. Namely, entities don't have established identities until they are saved to the DB or added to the Context/Session. But this issue isn't that big comparing to what you described in the post.
I was skimming through the comments and had this nagging suspicion that the entire topic of, "how do I get my ID with CQS", was a false dichotomy. The premise that the "ID" stored in the database is the "identity" of the object or entity I think can be challenged.
I prefer to look at the "ID" as purely database implementation details. Assuming the repository is SQL, the key type preferred by db admins will be the smallest-reasonable monotonically increasing ID... namely INT. But switch to Amazon DynamoDB and that conclusion flies out the window. With their totally managed and distributed indexes and hashing algorithms... GUID's would be fantastic.
What I WISH developers would do is take the time to think about their Domain and form their own understanding of what truly defines the identity of the entity. Whatever decision they make, it translates to a "natural key" for persistence.
Natural keys are great because a developer has promised, "these combinations of properties uniquely identify entities of type T". The result is unique indexes that can have dramatic performance benefits... outside the application benefit of being able to construct your repository like this:
As for the "ID" field? Who cares?... that's up to the database. The developer already knows exactly how to find this T. I wouldn't even include it on the domain model object.
This would give db admins options. We can look at the natural key size, evaluate how it is queried and order it appropriately. We can decide if the nature of typical joins merit clustering (as is common with Header -> Detail style records). If needed, we can optimize lookup of large keys through stored procedures and computed persisted checksum columns. Nullability and default values become part of design discussions on the front end. Finally, if we feel like it... we can assign a surrogate key, or use a GUID. The developer doesn't care, our dba's do.
Thinking back to my last 6 or so development projects, I've never had to "get the id". The next operation is always a matter of query or command on unique criteria I was responsible for creating in the first place. This approach makes my dba's happy.
Ethan, thank you for your comment; I agree with 90 percent of what you wrote, which is also the reason I prefer the options I previously outlined.
Entities don't always have 'natural IDs', though, and even when they have, experience has taught me not to use them. Is a person's email address a natural ID? It is, but people change email addresses.
Here in Denmark, for many years many public software systems have used the Danish personal identification numbers as natural keys, as they were assumed to be nationally unique and stable. These numbers encode various information about a person, such as birth-date and sex.  Increasingly, these requests are being granted. New ID, same person.
I've seen such changes happen so many times during my career that I've become distrustful of 'natural IDs'. If I need to identify an Entity, I usually attach a GUID to it.
With regard to entity identification, I'm not sure stability matters. Who cares if the email address changes... as long as it is unique? Uniqueness is sufficient for the application to identify the entity. I agree from a strictly database standpoint; I'm not thrilled about assigning a primary key to a natural key due to the stability issue across relationships. But that does not invalidate the key for use as an identity in my mind. Both indexes can exist, both be unique, and each with their own purpose.
Also, it is difficult for me to envision a scenario where there is no natural key. If there are two rows where the only difference is an auto-incrementing integer, or different guids... what is the meaning of one row versus the next? That meaning cannot, by definition, be contained in the surrogate keys... they add nothing to the business meaning of the entity.
I feel I've derailed the discussion into database modeling theory, and we are talking about CQS with "create the entity" as a stimulating use case. Suffice it to say, IMHO, if (a, b) is unique today according to business rule, than it should be my unique identity from a developer perspective. By leaving row identifiers up to DBA's and dropping them from my domain model entirely, I minimize impact to those technical implementations when the business rules change such that (a, b, c) becomes the new unique, and, preserve CQS in the process.
SQL Server has a feature called 'sequence' (from 2012 and above if I'm not mistaken). We can use sequence to generate unique int ID instead of using identity column. The sequence can be called without inserting row to the table. We can create a service that call this sequence to generate the next running number. The UI code can call this running number generator service to get a new ID, and then send the new entity complete with ID to the create service.


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utils¶
funcs¶
hooks¶
-
class
utils.hooks.
BroadcastGlobalVariablesHook
(root_rank, device='')[source]¶ Bases:
tensorflow.python.training.session_run_hook.SessionRunHook
SessionRunHook that will broadcast all global variables from root rank to all other processes during initialization. This is necessary to ensure consistent initialization of all workers when training is started with random weights or restored from a checkpoint.
-
__init__
(root_rank, device='')[source]¶ Construct a new BroadcastGlobalVariablesHook that will broadcast all global variables from root rank to all other processes during initialization. :param root_rank: Rank that will send data, other ranks will receive data. :param device: Device to be used for broadcasting. Uses GPU by default
if Horovod was build with HOROVOD_GPU_BROADCAST.
-
after_create_session
(session, coord)[source]¶ Called when new TensorFlow session is created.
This is called to signal the hooks that a new session has been created. This has two essential differences with the situation in which begin is called:
- When this is called, the graph is finalized and ops can no longer be added
- to the graph.
- This method will also be called as a result of recovering a wrapped
- session, not only at the beginning of the overall session.
Parameters: - session – A TensorFlow Session that has been created.
- coord – A Coordinator object which keeps track of all threads.
-
begin
()[source]¶ Called once before using the session.
When called, the default graph is the one that will be launched in the session. The hook can modify the graph by adding new operations to it. After the begin() call the graph will be finalized and the other callbacks can not modify the graph anymore. Second call of begin() on the same graph, should not change the graph.
-
-
class
utils.hooks.
PrintLossAndTimeHook
(every_steps, model)[source]¶ Bases:
tensorflow.python.training.session_run_hook.SessionRunHook
Session hook that prints training samples and prediction from time to time
-
after_run
(run_context, run_values)[source]¶ Called after each call to run().
The run_values argument contains results of requested ops/tensors by before_run().
The run_context argument is the same one send to before_run call. run_context.request_stop() can be called to stop the iteration.
If session.run() raises any exceptions then after_run() is not called.
Parameters: - run_context – A SessionRunContext object.
- run_values – A SessionRunValues object.
-
before_run
(run_context)[source]¶ Called before each call to run().
You can return from this call a SessionRunArgs object indicating ops or tensors to add to the upcoming run() call. These ops/tensors will be run together with the ops/tensors originally passed to the original run() call. The run args you return can also contain feeds to be added to the run() call.
The run_context argument is a SessionRunContext that provides information about the upcoming run() call: the originally requested op/tensors, the TensorFlow Session.
At this point graph is finalized and you can not add ops.
Parameters: run_context – A SessionRunContext object. Returns: None or a SessionRunArgs object.
-
begin
()[source]¶ Called once before using the session.
When called, the default graph is the one that will be launched in the session. The hook can modify the graph by adding new operations to it. After the begin() call the graph will be finalized and the other callbacks can not modify the graph anymore. Second call of begin() on the same graph, should not change the graph.
-
-
class
utils.hooks.
PrintSamplesHook
(every_steps, model)[source]¶ Bases:
tensorflow.python.training.session_run_hook.SessionRunHook
Session hook that prints training samples and prediction from time to time
-
after_run
(run_context, run_values)[source]¶ Called after each call to run().
The run_values argument contains results of requested ops/tensors by before_run().
The run_context argument is the same one send to before_run call. run_context.request_stop() can be called to stop the iteration.
If session.run() raises any exceptions then after_run() is not called.
Parameters: - run_context – A SessionRunContext object.
- run_values – A SessionRunValues object.
-
before_run
(run_context)[source]¶ Called before each call to run().
You can return from this call a SessionRunArgs object indicating ops or tensors to add to the upcoming run() call. These ops/tensors will be run together with the ops/tensors originally passed to the original run() call. The run args you return can also contain feeds to be added to the run() call.
The run_context argument is a SessionRunContext that provides information about the upcoming run() call: the originally requested op/tensors, the TensorFlow Session.
At this point graph is finalized and you can not add ops.
Parameters: run_context – A SessionRunContext object. Returns: None or a SessionRunArgs object.
-
begin
()[source]¶ Called once before using the session.
When called, the default graph is the one that will be launched in the session. The hook can modify the graph by adding new operations to it. After the begin() call the graph will be finalized and the other callbacks can not modify the graph anymore. Second call of begin() on the same graph, should not change the graph.
-
-
class
utils.hooks.
RunEvaluationHook
(every_steps, model, last_step=-1)[source]¶ Bases:
tensorflow.python.training.session_run_hook.SessionRunHook
Session hook that runs evaluation on a validation set
-
after_run
(run_context, run_values)[source]¶ Called after each call to run().
The run_values argument contains results of requested ops/tensors by before_run().
The run_context argument is the same one send to before_run call. run_context.request_stop() can be called to stop the iteration.
If session.run() raises any exceptions then after_run() is not called.
Parameters: - run_context – A SessionRunContext object.
- run_values – A SessionRunValues object.
-
before_run
(run_context)[source]¶ Called before each call to run().
You can return from this call a SessionRunArgs object indicating ops or tensors to add to the upcoming run() call. These ops/tensors will be run together with the ops/tensors originally passed to the original run() call. The run args you return can also contain feeds to be added to the run() call.
The run_context argument is a SessionRunContext that provides information about the upcoming run() call: the originally requested op/tensors, the TensorFlow Session.
At this point graph is finalized and you can not add ops.
Parameters: run_context – A SessionRunContext object. Returns: None or a SessionRunArgs object.
-
begin
()[source]¶ Called once before using the session.
When called, the default graph is the one that will be launched in the session. The hook can modify the graph by adding new operations to it. After the begin() call the graph will be finalized and the other callbacks can not modify the graph anymore. Second call of begin() on the same graph, should not change the graph.
-
utils¶
-
utils.utils.
collect_if_horovod
(value, hvd, mode='sum')[source]¶ Collects values from all workers if run on Horovod. Note, that on all workers except first this function will return None.
Parameters: - value – value to collect.
- hvd – horovod.tensorflow module or None
- mode – could be “sum”, “mean” or “gather”, indicating reduce_sum or gather. For “sum” and “mean” value has to be numerical, for “gather”, value has to be iterable.
Returns: collected results if run on Horovod or value otherwise.
-
utils.utils.
log_summaries_from_dict
(dict_to_log, output_dir, step)[source]¶ A function that writes values from dict_to_log to a tensorboard log file inside output_dir.
Parameters: - dict_to_log (dict) – A dictiontary containing the tags and scalar values to log. The dictionary values could also contain tf.Summary.Value objects to support logging of image and audio data. In this mode, the dictionary key is ignored, as tf.Summary.Value already contains a tag.
- output_dir (str) – dir containing the tensorboard file
- step (int) – current training step


Trigger that can activate observables ManualSwitchObj classes (dosen't display at the monitor)
More...
#include <Sensor.h>
|
| | Sensor (std::list< ManualSwitchObj *> _observables, bool _repeat_allowed, bool _is_keeping, b2Body *_body, std::vector< Action > _stages) |
| | Defined constructor for this class. More...
|
| |
|
|
std::list< ManualSwitchObj * > | observables |
| | list of observables objects
|
| |
|
std::vector< Action > | stages |
| | vector of stages(commands) through which observables objects should pass
|
| |
|
bool | repeat_allowed |
| | determines whether it is possible to send next command to the observables objects when they doesn't complete previous action: 'true' - possible; 'false' - impossible
|
| |
|
bool | is_keeping |
| | determines will be next command send afther end of the contact(end of the hold button): 'true' - will be; 'false' - won't be
|
| |
|
bool | non_run |
| | contain information about valid of the last contact: 'true' - sensor didn't respond; 'false' - sensor responded
|
| |
|
int | is_pressed |
| | number of active contacts
|
| |
|
int | stage_iter |
| | number of current stage from stages vector
|
| |
Trigger that can activate observables ManualSwitchObj classes (dosen't display at the monitor)
- Author
- Vasily
- Version
- 1.0
- Date
- June 2017
◆ Sensor()
| Sensor::Sensor |
( |
std::list< ManualSwitchObj *> |
_observables, |
|
|
bool |
_repeat_allowed, |
|
|
bool |
_is_keeping, |
|
|
b2Body * |
_body, |
|
|
std::vector< Action > |
_stages |
|
) |
| |
Defined constructor for this class.
- Parameters
-
| _observables | list of observables objects |
| _repeat_allowed | determines whether it is possible to send next command to the observables objects when they doesn't complete previous action: 'true' - possible; 'false' - impossible |
| _is_keeping | determines will be next command send afther end of the contact(end of the hold button): 'true' - will be; 'false' - won't be |
| _body | pointer to the box2d body assigned to this sensor |
| _stages | vector of stages(commands) through which observables objects should pass |
The documentation for this class was generated from the following files:


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A quick example for the use of the MediaError object, as returned by HTMLMediaElement objects. Choose a file (one which generates an error and one which doesn't).
MediaError
HTMLMediaElement


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I think data is a powerful way to communicate positions. My interests are primarily in ways data can be used to evaluate and learn about public policy and other social science applications.
Aside from programming, I enjoy distance running (I've been running half marathons since 10th grade!), hiking, biking, and reading. I'm slowly working my way up to a full marathon. My favorite kinds of books are memoirs and social science books, but my favorite book of all time is The Kite Runner!


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|
GPGPU-Sim
|
This is a basic XML parser written in ANSI C++ for portability. It works by using recursion and a node tree for breaking down the elements of an XML document.
The following license terms for the "XMLParser library from Business-Insight" apply to projects that are in some way related to the "mcpat project", including applications using "mcpat project" and tools developed for enhancing "mcpat project". All other projects (not related to "mcpat project") have to use the "XMLParser library from Business-Insight" code under the Aladdin Free Public License (AFPL) See the file "AFPL-license.txt" for more informations about the AFPL license. (see http://www.artifex.com/downloads/doc/Public.htm for detailed AFPL terms)
Redistribution and use of the "XMLParser library from Business-Insight" in source and binary forms, with or without modification, are permitted provided that the following conditions are met:
THIS SOFTWARE IS PROVIDED BY Business-Insight ``AS IS'' AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED.
Copyright (c) 2002, Business-Insight Business-Insight All rights reserved.
You can follow a simple Tutorial to know the basics...
The library is composed of two files: xmlParser.cpp and xmlParser.h. These are the ONLY 2 files that you need when using the library inside your own projects.
All the functions of the library are documented inside the comments of the file xmlParser.h. These comments can be transformed in full-fledged HTML documentation using the DOXYGEN software: simply type: "doxygen doxy.cfg"
By default, the XMLParser library uses (char*) for string representation.To use the (wchar_t*) version of the library, you need to define the "_UNICODE" preprocessor definition variable (this is usually done inside your project definition file) (This is done automatically for you when using Visual Studio).
Some very small introductory examples are described inside the Tutorial file xmlParser.html
Some additional small examples are also inside the file xmlTest.cpp (for the "char*" version of the library) and inside the file xmlTestUnicode.cpp (for the "wchar_t*" version of the library). If you have a question, please review these additionnal examples before sending an e-mail to the author.
To build the examples:
In order to build the examples you need some additional files:
Inside Visual C++, the "debug versions" of the memory allocation functions are very slow: Do not forget to compile in "release mode" to get maximum speed. When I had to debug a software that was using the XMLParser Library, it was usually a nightmare because the library was sooOOOoooo slow in debug mode (because of the
slow memory allocations in Debug mode). To solve this problem, during all the debugging session, I am now using a very fast DLL version of the XMLParser Library (the DLL is compiled in release mode). Using the DLL version of the XMLParser Library allows me to have lightening XML parsing speed even in debug! Other than that, the DLL version is useless: In the release version of my tool, I always use the normal, ".cpp"-based, XMLParser Library (I simply include the xmlParser.cpp and xmlParser.h files into the project).
The file XMLNodeAutoexp.txt contains some
"tweaks" that improve substancially the display of the content of the XMLNode objects inside the Visual Studio Debugger. Believe me, once you have seen inside the debugger the "smooth" display of the XMLNode objects, you cannot live without it anymore!
The speed of the debug version of the XMLParser library is tolerable so no extra
work.has been done.


[gecode-users] Introductions
stanio at cs.tu-berlin.de
stanio at cs.tu-berlin.de
Fri Apr 11 19:37:35 CEST 2008
Hi,
* Martin Mann <mmann at informatik.uni-freiburg.de> [2008-04-11 19:12]:
> I found the "Online Guide to Constraint Programming" by Roman Bartak
> quite usefull for an introduction.
> http://kti.mff.cuni.cz/~bartak/constraints/
>
> But it doesnt correspond to all details of the Gecode architecture and
Parallel to reading Bartak, you may want to keep an eye on the practical
side. If you are C++ user, you might never come to the Gecode/J
introduction page http://www.gecode.org/gecodej/doc/PageIntro.html , which
I found useful as starting point.
--
cheers
stanio_
More information about the gecode-users
mailing list


| Animator Component |
Component on a model that animates that model using the Animation system. The component has a reference to an Animator Controller asset that controls the animation. |
| Root Motion |
Motion of character’s root, whether it’s controlled by the animation itself or externally. |
| Animator Controller |
The Animator Controller controls animation through Animation Layers with Animation State Machines and Animation Blend Trees, controlled by Animation Parameters. The same Animator Controller can be referenced by multiple models with Animator components. |
| Animator Window |
The window where the Animator Controller is visualized and edited. |
| Animation Layer |
An Animation Layer contains an Animation State Machine that controls animations of a model or part of it. An example of this is if you have a full-body layer for walking or jumping and a higher layer for upper-body motions such as throwing an object or shooting. The higher layers take precedence for the body parts they control. |
| Animation State Machine |
A graph controlling the interaction of Animation States. Each state references an Animation Blend Tree or a single Animation Clip. |
| Animation Blend Tree |
Used for continuous blending between similar Animation Clips based on float Animation Parameters. |
| Animation Parameters |
Used to communicate between scripting and the Animator Controller. Some parameters can be set in scripting and used by the controller, while other parameters are based on Custom Curves in Animation Clips and can be sampled using the scripting API. |
| Inverse Kinematics (IK) |
The ability to control the character’s body parts based on various objects in the world. |


---
title: Release Notes
type: download
---
Wallaroo 0.8 release notes
- Wal file format
- Add Catalog::Remove, Catalog::Clear, Catalog::Size
- Custom name for class registration
- Choice between shared and weak ptr for Collaborator
Wallaroo 0.7 release notes
- Changed Syntax: Device -> Part, Plug -> Collaborator (close issue #1 )
- Bug fix: shared lib from multiple sources (close issue #7 )
- Template and namespace classes registration (close issue #8 )
Wallaroo 0.6 release notes
- Attributes feature
- Bug fix: UNICODE on win32 (close issue #5 )
- Catalog::Create returns the new object
Wallaroo 0.5.1 release notes
- Bug fix: protection error when unloading dll with visual studio 2012
- Add win nmake makefile for samples and test
Wallaroo 0.5 release notes
- BOOST software license
- Shared lib specified in configuration files
- New parameter types in configuration files
Wallaroo 0.4 release notes
- Add shared library support
- Fix gcc 4.7 compatibility issue
- Add directory "detail"
- Remove deprecated syntax
Wallaroo 0.3.1 release notes
- Bug fix: wallaroo::mandatory now compiles with gcc v. 4.6
Wallaroo 0.3 release notes
- Add JSON parser
- Remove the macro for the class declaration
- Check of the associations cardinality / optional associations
- Speed optimization
- Get rid of VC warning C4355
- Remove deprecated syntax
- New samples
Wallaroo 0.2 release notes
- Support for C++11
- New syntax for wiring: use().as().of()
- New syntax for collections: Plug< T, collection, C = std::list >
- Added custom exceptions
- Doxygen documentation
- Unit test added


{{ profile.about }}
{{ education.from | date: 'yyyy' }} → {{ education.to == null? 'Present' : education.to | date: 'yyyy' }}
{{ education.description }}
{{ workExperience.from | date: 'MMMM yyyy' }} → {{ workExperience.currentlyEmployed? 'Present' : workExperience.to | date: 'MMMM yyyy' }}
{{ workExperience.description }}


A function designed to use as an RStudio https://rstudio.github.io/rstudioaddins/ for structuring code.
There are three levels of granularity:
For optimal use, we recommend specifying keyboard shortcuts in the add-in settings. A title can be added to the section as well. When calling the function, a shiny app is opened in the viewer pane, where the title can be specified. If the field remains empty, only a section break is created without title. You may hit enter instead of clicking on "done" to confirm your choice.
insert_l1_break() insert_l2_break() insert_l3_break()
The breaks characters (___
, ...
, . .
) were
chosen such that they reflect the level of granularity, namely ___
has a much higher visual density than . .
We recommend starting off by grouping code into level 2 blocks.
The advantage is that in both directions of granularity, there is another
layer (___
and ...
) left. When the code base grows, there
might be a need to extend in both directions.
In order to be https://support.rstudio.com/hc/en-us/articles/200484568-Code-Folding-and-Sections,
all titles end with four hashes (see example below). We put the hashes at
the end of the line (where end of a line is defined by the global option
options()$strcode$char_length, which defaults to 80)
and separate it from the section title with spaces to
achieve a natural representation in the code flow.
Being recognised as sections by RStudio means
that at the very botton of the code pane, right next to line/indent count,
is a little table of contents of the current file which can be expanded to
view (and jump to) different code sections. Additionally, you will be able
to fold code sections (just as you can fold function declarations in RStudio).
# This is a minimal example. # See the readme for a longer and more detailed example. ## ......................................................


Los Angeles Bike Share
×
Home
Statistics
Graphs
Repo
About Me
☰
github repo
Modify Mode
Locations
Starting Station Heat Map
Stoping Station Heat Map
{{ mapName }}
{% block content %} {% endblock %}


Bubble sort compares each adjacent pair of items, swaps them if they are not in the correct order, then returns to the first item and begins the process over again until all elements to be sorted are in ascending order. Bubble sort is one of the more efficient methods if the list is already almost sorted but has a few items out of place, however, it is too slow for practical use in just about any other instance.
Merge sort works by splitting the list into n sublists and merges them to create new ordered sublists until there is one remaining ordered list. Merge sort, of the three algorithms mentioned in this post, is the most efficient, though quick sort is a close second in most instances.
Quick sort selects an element from the list to be sorted and uses that element as a 'pivot.' The algorithm them re orders the list so that any item smaller than the pivot is moved to the left of it and any element larger than the pivot is moved to the right, effectively creating two sub-lists. This process is then applied to both sub-lists and continues until the elements in the list are sorted in ascending order.
Below is a gif that shows the method and performance of some of the more common sorting algorithms in different instances.
While reserching this topic I also found some information about what is undeniably the most efficient sorting algorithm. Stack overflow user 'BioGeek' does a beautiful job of describing how it works:


|
All
For You
(Sister Hazel) |
|
3
- Finally I figured out
But it took a long, long time But now there's a turnabout Maybe 'cause I'm trying 1 - There's been times, I'm so confused All my roads, they lead to you I just can't turn and walk away 2 - It's hard to say what it is I see in you Wonder if I'll always be with you But words can't say, and I can't do Enough to prove, it's all for you I thought I'd seen it all 'Cause it's been a long, long time Oh but then we'll trip and fall Wondering if I'm blind (repeat 1, 2) Rain comes pouring down, falling from blue skies Words without a sound, coming from your eyes (rpt 3, 1, 2, 2) It's hard to say, it's hard to say It's all for you |


GET /users - List All Users
GET /users/:id - Get Single user details
POST /users - Create New User Entry
PUT /users/:id - Update User details
Delete /users/:id - Delete User Entry
Add User
Add Record
Edit User
Fetch User
Update User
List Users


STRADA (Simulation of TRAffic DAta) is an urban traffic web simulator that uses data in real time built with Angular, TypeScript & Firebase.
Project developed for the dissertation of my bachelor's degree in computer engineering.
Official docs: STRADA documentation
A widespread cliché wants urban traffic to be created because roads and public transport are insufficient or not working. Indeed, those who participated in the design of complex systems know perfectly that overdimensioning beyond average demand often does not give the expected results, or is not economically sustainable or for other factors. Traffic is due to population density and human activities that are concentrated in the same place or time. Even the Romans or medieval cities had busy roads: a sign of vitality, productivity, the ability of some centers to attract people and activities. In fact, over time, various meanings have been attributed to traffic: from "trade" to "circulation", but only in the automobile age the effect of congestion has replaced its original meanings to become the common use.
Although traffic is inevitable in some situations, it is possible to study it in order to reduce the effect of congestion - as well as traffic accidents and pollution.
Software simulators allow you to analyze, design, plan and manage urban mobility in order to find the best solutions for the traffic problems before adopting them in reality.
The STRADA simulator - Simulation of TRAffic DAta - is a web application that can process any transport network, obtain traffic data in real time and offer a simulation of traffic flow, with the purpose of controlling, estimating or predict traffic considering different conditions, such as different weather conditions.
npm install npm@latest -g
npm install -g @angular/cli
npm install -g firebase-tools
firebase login
.firebaserc
filesrc/app/app-config.json
filefunctions/src/functions-config.json
filecd functions
npm install
npm run serve:dev
npm install
npm start
npm test
MIT


‘CRY THUNDER’ from the new album ‘THE POWER WITHIN’.
DragonForce - Heroes of Our Time (HD Official Video)
DragonForce - The Last Journey Home (HD Official Video)


World Population Density Plots
April 6, 2016
I enjoy to peruse the CIA World Factbook from time to time. It reminds me of digging though a country specific atlas or encyclopedia. The other day I was looking at their country comparison feature and noticed they didn’t have population density available, despite having estimates for country population and area. I went ahead and calculated the population density for the countries, and then made pretty plots (check out the full imgur gallery) with various color maps of the world’s population density.
Data
I pulled the population data and area data from the CIA World Factbook on March 28, 2016. Most of the data is based on 2015 estimates. There is an option to download the data as a tab separated list. I downloaded the data, converted the tab separated list to a comma separated list, and then imported the csv into Python. With Python I calculated the population density, and then used cartopy to plot the density maps with different matplotlib color maps.
Python
If we take a look at the data sets, we notice one has 257 entries, while the other has 238 countries. Some of the land area is wildlife reserves or unmanned territories, though neither would have a population. I took the country name to be the unique identify in both lists. Then I simply divided the population by the area. The result is the population density in number of people per square kilometer. I had to make an exception for Vatican City as it had an area of 0 km, and would result in an infinite population density. I exported the countries to a csv file which you can view here. I uploaded all of the source code, data, and images I generated to my GitHub.
Twenty most densely populated countries
Below are the 20 most densely populated countries. It is important to mention Vatican City as it has an area of 0 square kilometers, and thus results in an infinite population density, even if just one person is living there. South Korea which isn’t mentioned comes in as the 22nd most densely populated country.
| Rank | Country | Population Density (people per sq km) |
|---|---|---|
| 1 | Macau | 21169 |
| 2 | Monaco | 15268 |
| 3 | Singapore | 8141 |
| 4 | Hong Kong | 6445 |
| 5 | Gaza Strip | 5192 |
| 6 | Gibraltar | 4180 |
| 7 | Bahrain | 1772 |
| 8 | Maldives | 1320 |
| 9 | Malta | 1310 |
| 10 | Bermuda | 1230 |
| 11 | Bangladesh | 1173 |
| 12 | Sint Maarten | 1167 |
| 13 | Guernsey | 847 |
| 14 | Jersey | 839 |
| 15 | Barbados | 676 |
| 16 | Mauritius | 657 |
| 17 | Taiwan | 651 |
| 18 | Aruba | 623 |
| 19 | Lebanon | 595 |
| 20 | Saint Martin | 588 |
Twenty least densely populated countries
Below are the 20 least densely populated countries. Most of this data is based from 2015 estimates, I’ll try to update it when the new 2016 estimates come out.
| Rank | Country | Population Density (people per sq km) |
|---|---|---|
| 1 | Greenland | 0.026 |
| 2 | Svalbard | 0.030 |
| 3 | Falkland Islands (Islas Malvinas) | 0.276 |
| 4 | Pitcairn Islands | 1.021 |
| 5 | Mongolia | 1.913 |
| 6 | Western Sahara | 2.146 |
| 7 | Namibia | 2.684 |
| 8 | Australia | 2.939 |
| 9 | Iceland | 3.223 |
| 10 | Guyana | 3.420 |
| 11 | Mauritania | 3.490 |
| 12 | Canada | 3.515 |
| 13 | Suriname | 3.538 |
| 14 | Libya | 3.644 |
| 15 | Botswana | 3.752 |
| 16 | Niue | 4.577 |
| 17 | Gabon | 6.371 |
| 18 | Kazakhstan | 6.663 |
| 19 | Russia | 8.330 |
| 20 | Central African Republic | 8.654 |
Plots
Using Cartopy, Python, and Natural Earth I was able to plot the population densities with matplotlib on a world map. I used a normalized scale that went from 0 to 459 to base my color maps. Obvious countries such as Bangladesh have a population density great than 459. However most of the densely populated countries are small islands, so the color plots would have been dull and boring. I could have used a different scale, but non-linear scales can be difficult to follow.
I used the 1:50m scale data from Natural Earth Data. Admin 0 – Countries data list to be specific.  Hindsight says I probably could have just used the data provided from Natural Earth, as this includes population estimates. That would have been much easier, as my unique identifier would have been inherent to the country shape data. I used the ‘name_long’ attribute to match the country name to the country name provided from the CIA World Factbook. This worked for about 200 of the countries. The rest of the countries I had to manually point to the shape data to the calculated population density.
I created plots with a variety of different color maps that were available in Matplotlib. I created the images in png format, and also a vector pdf format. All the images can be found in this GitHub folder. If you haven’t already, check out the full imgur gallery!
I’ve included some of the better images bellow.
Please comment if you enjoyed this post!


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@*
* Copyright 2019 HM Revenue & Customs
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*@
@(formItem:Form[_], fieldName: String, args: (Symbol,Any)*)(implicit messages: Messages)
@import views.html.helper._
@elements = @{ FieldElements(formItem(fieldName).id, formItem(fieldName), null, args.toMap, messages) }


Baselines an existing database, excluding all migrations up to and including baselineVersion.
<flyway:baseline />
| Attribute | Required | Default | Description |
|---|---|---|---|
| url | YES | The jdbc url to use to connect to the database | |
| driver | NO | Auto-detected based on url | The fully qualified classname of the jdbc driver to use to connect to the database |
| user | NO | The user to use to connect to the database | |
| password | NO | The password to use to connect to the database | |
| schemas | NO | default schema of the connection | Case-sensitive list of schemas managed by Flyway. The first schema will be the one containing the metadata table. |
| table | NO | schema_version | The name of Flyway's metadata table. By default (single-schema mode) the metadata table is placed in the default schema for the connection provided by the datasource. When the flyway.schemas property is set (multi-schema mode), the metadata table is placed in the first schema of the list. |
| callbacks | NO | Fully qualified class names of FlywayCallback implementations to use to hook into the Flyway lifecycle. | |
| skipDefaultCallbacks | NO | false | Whether default built-in callbacks (sql) should be skipped. If true, only custom callbacks are used. |
| baselineVersion | NO | 1 | The version to tag an existing schema with when executing baseline |
| baselineDescription | NO |
|
The description to tag an existing schema with when executing baseline |
| classpath | NO | The Ant classpath used to load the JDBC driver and the migrations | |
| classpathref | NO | The Ant classpath reference used to load the JDBC driver and the migrations |
<property name="flyway.driver" value="org.hsqldb.jdbcDriver"/> <property name="flyway.url" value="jdbc:hsqldb:file:/db/flyway_sample"/> <property name="flyway.user" value="SA"/> <property name="flyway.password" value="mySecretPwd"/> <property name="flyway.schemas" value="schema1,schema2,schema3"/> <property name="flyway.table" value="schema_history"/> <property name="flyway.callbacks" value="com.mycomp.MyCallback,com.mycomp.OtherCallback"/> <property name="flyway.skipDefaultCallbacks" value="false"/> <property name="flyway.baselineVersion" value="1.0"/> <property name="flyway.baselineDescription" value="Base Migration"/>
[flyway:baseline] Creating Metadata table: schema_version (Schema: PUBLIC) [flyway:baseline] Schema baselined with version: 1
Code licensed under Apache License, Version 2


| Class and Description |
|---|
| ThreadModel
Represents a single comment
|
| Class and Description |
|---|
| LocationModel
Provides location data in the form of longitude/latitude coordinates.
|
| ThreadModel
Represents a single comment
|
| Class and Description |
|---|
| ThreadModel
Represents a single comment
|
| Class and Description |
|---|
| LocationModel
Provides location data in the form of longitude/latitude coordinates.
|
| PreferenceModel
Stores the user's settings, including their UserModel
|
| ThreadModel
Represents a single comment
|
| Class and Description |
|---|
| LocationModel
Provides location data in the form of longitude/latitude coordinates.
|
| PreferenceModel
Stores the user's settings, including their UserModel
|
| ThreadListModel
Holds a list of comments to be displayed
|
| ThreadModel
Represents a single comment
|
| Class and Description |
|---|
| ThreadModel
Represents a single comment
|
| Class and Description |
|---|
| LocationModel
Provides location data in the form of longitude/latitude coordinates.
|
| PreferenceModel
Stores the user's settings, including their UserModel
|
| ThreadModel
Represents a single comment
|
| ThreadTagModel
ThreadTagModel for ThreadModel.
|
| UserModel
Stores information for identifying a user
|
| Class and Description |
|---|
| ThreadModel
Represents a single comment
|
| Class and Description |
|---|
| LocationModel
Provides location data in the form of longitude/latitude coordinates.
|
| PreferenceModel
Stores the user's settings, including their UserModel
|
| ThreadListModel
Holds a list of comments to be displayed
|
| ThreadModel
Represents a single comment
|


in my spare time, i've been writing a kernel...
...in a high-level language.
usually, one writes this in assembly
i didn't want to
shoutout to Philipp Oppermann (os.phil-opp.com/entering-longmode)
check out github.com/sos-os
or tweet @mycoliza


1 Kings 13:30
And he laid his carcass in his own grave; and they mourned over him, saying, Alas, my brother!


--- layout: default title: Home ---
This space is still under development. Please come back another time to find exciting stuff related to my research on the Global Governance of Artificial Intelligence (AI2G).


This project is a JavaScript implementation of viewing data encoded in a matrix around the matrix diagonal. The current use case is to find co-occurrences in viral populations, which can indicate how viruses adapt to environmental pressures, such as the host organism's immune system.
This current implementation is architected by Alper Sarikaya to test the practicality of WebGL as a visualization medium. The project is version-controlled in a private repository. The stable version of the visualization is available (temporarily) here, while an in-progress version is available here.
Interacting with the Data
The data is displayed diagonally by default, with the ith position on the y-axis, and the jth position on the x-axis. The following methods itemize the ways to interact with the visualization.
- Clicking in the overview will navigate the main view to the area highlighted by the green bar. The mouse must stay within the top bar when panning the dataset.
- Using the scroll wheel within the canvas will change the zoom level of the current view. The position of the cursor will focus the area of zoom, but the zoom position will always be fixed toward the diagonal of the matrix.
- Hovering the mouse over the dataset at a particular position brings up the encoded data in the 'super-zoom' at top-right, which shows the a view of the current coordinates and metric value(s) under the mouse.
- Clicking the dataset will freeze the 'super-zoom' (which will blink), allowing for more detailed examination of the data. Further, clicking on a 'pixel' in the 'super-zoom' will display the counts of non-variant and variant reads in the below view.
- Clicking a count rectangle in the counts view will condition the reads of the paired read. This conditioned view can be reset by again clicking on the appropriate pixel in the 'super-zoom.'
- Switching the metric will cause the visualization to ask for the data file (up to 15 seconds) and load it into the visualization (1 second). The equation used to compute each metric is displayed below the drop-down.
- Enabling gating will blank out any color if the ith position does not contain at least x% variants. This helps to elimate noise in the visualization and promotes salience of highly-correlated variants.
Implementation Notes
This implementation of Splatterplots has been tested in Google Chrome (v36) and Firefox (v32). Client computers must support WebGL (GPU, drivers, browser, OS) and the OES_float_texture WebGL extension for correct rendering. Check WebGL support of your current configuration on WebGL Report. Internet Explorer and Safari do not support WebGL due to security concerns.


LAB: Role Based Access Control Stage 3 Stage 3: Breaking Data Layer Access Control. As regular employee 'Tom', exploit weak access control to View another employee's profile. Verify the access. Larry Stooge (employee) Moe Stooge (manager) Curly Stooge (employee) Eric Walker (employee) Tom Cat (employee) Jerry Mouse (hr) David Giambi (manager) Bruce McGuirre (employee) Sean Livingston (employee) Joanne McDougal (hr) John Wayne (admin) Neville Bartholomew (admin) Password


Select your search category(all files are in mp3 format)
If you need other file formats, download the file then click here
Artists
All Songs
| Songs By Daft Punk |
| Name | Album | Length | Size |
| Derezzed | TRON: Legacy | 1:44 | 4,076 KB |
| End Of Line | TRON: Legacy | 2:36 | 6,119 KB |


Changes Are Coming For The 2020 Kia Stinger
A new trim offers more for nearly the same price.
by Jay TraugottThe Kia Stinger has been on the market since the 2018 model year and though it may be slightly early for a mid-life refresh, the South Korean automaker still has an update planned for the 2020 model year. However, this update appears to be limited only to trim packages. According to an order guide uncovered by Cars Direct, the 2020 Kia Stinger will no longer offer the 2.0T Base and Premium trims. Both, instead, will be swapped out in favor of a new trim called the GT-Line that will start at $34,085 – only $100 more than the 2019 base trim.
In short, Stinger buyers will receive sportier design elements for barely any extra money. The new GT-Line (not the Stinger GT pictured here) will come with a twin-scroll turbocharged 2.0-liter inline-four with 255 horsepower and 260 lb-ft of torque, and a ton of cool exterior upgrades such as a GT-styled grille and bumpers, 18-inch GT wheels, black chrome trim, and body-color door handles.
 The twin-turbo V6-powered 2019 Stinger GT begins at about $40,000 – a $6,410 premium over the new GT-Line. The outgoing 2019 Stinger 2.0T Premium does offer more features than the base trim, obviously, but still brings the price up to $40,185, which is actually $110 less than the cheapest GT.
It should be noted that the loss of the Premium trim means advanced safety features, such as automatic emergency braking, requires buyers to upgrade to the GT1, a trim that begins at nearly $46,000. Aside from these 2020 packaging changes for the 2.0 turbo-powered Stinger, all other mechanicals remain the same.
Rear-wheel-drive continues to come standard in both engines, while all-wheel drive remains optional for both, though at a $2,200 premium. The 8-speed automatic transmission returns as well.
We're expecting an official announcement from Kia to happen fairly soon, but it appears the Stinger lineup will have to wait another model year or two for any significant changes.


Why
Unlike other invoice finance options, northmoney doesn't contact your clients' customers, it’s fully confidential. It’s too easy because our software seamlessly connects to their online accounting system.
Your clients enjoy full control of which of their customer invoices to use, and there's no paperwork nor lengthy setup that you need to complete as a broker.
northmoney makes access to finance secure and simple. Funding scales automatically with your clients' business, giving them the flexibility to grow.


| Owl |
Make alias of the modules in Owl for your convenience.
|
| Owl_types |
Define the types shared by various modules
|
| Owl_utils |
Helper functions used in the library
|
| Owl_maths |
Mathematics module
|
| Owl_stats |
Statistics module
|
| Owl_optimise |
Machine learning library
Note: C layout row-major matrix
|
| Owl_dense_real |
Real dense matrix module
|
| Owl_dense_complex |
Complex dense matrix module: this module supports operations on dense
matrices of complex numbers.
|
| Owl_dense | Dense matrix module
|
| Owl_sparse_real |
Sparse real matrix: this module supports the operations on sparse matrices
of real numbers.
|
| Owl_sparse_complex |
Complex sparse matrix: this module supports the operations on sparse
matrices of complex numbers.
|
| Owl_sparse | Sparse matrix module
|
| Owl_foreign | |
| Owl_linalg |
Linalg module
|
| Owl_regression |
Regression module
|
| Owl_fft |
Fast Fourier Transforms (FFTs) : this module implements some basic FFT
operations.
|
| Owl_pretty |
Generic matrix printing functions.
|
| Owl_plot |
Plot module
The input to a plot function is supposed to be a row-based matrix.
|
| Owl_toplevel |
Install Toplevel Printers
|
| Owl_const |
This module is extended from gsl-ocaml by including SI system.
|
| Ffi_bindings |


SPREAD(3) - [ARRAY:CONSTRUCTION] Add a dimension and replicate data
result = spread(source, dim, ncopies)
TYPE(kind=KIND) function spread(source, dim, ncopies)TYPE(kind=KIND) :: source(..) integer(kind=**),intent(in) :: dim integer(kind=**),intent(in) :: ncopies
o SOURCE is a scalar or array of any type and a rank less than fifteen. o DIM is an integer scalar o NCOPIES is an integer scalar
SPREAD(3) replicates a SOURCE array along a specified dimension DIM. The copy is repeated NCOPIES times.
So to add additional rows to a matrix DIM=1 would be used, but to add additional rows DIM=2 would be used, for example.
If SOURCE is scalar, the size of the resulting vector is NCOPIES and each element of the result has a value equal to SOURCE.
o SOURCE : the input data to duplicate o DIM : The additional dimension value in the range from 1 to N+1, where N equals the rank of SOURCE. o NCOPIES : the number of copies of the original data to generate
The result is an array of the same type as SOURCE and has rank N+1 where N equals the rank of SOURCE.
Sample program:
program demo_spread implicit noneResults:integer a1(4,3), a2(3,4), v(4), s
write(*,(a) ) & TEST SPREAD(3) , & SPREAD(3) is a FORTRAN90 function which replicates, & an array by adding a dimension. , &
s = 99 call printi(suppose we have a scalar S,s)
write(*,*) to add a new dimension (1) of extent 4 call call printi(spread( s, dim=1, ncopies=4 ),spread ( s, 1, 4 ))
v = [ 1, 2, 3, 4 ] call printi( first we will set V to,v)
write(*,(a)) and then do "spread ( v, dim=2, ncopies=3 )" a1 = spread ( v, dim=2, ncopies=3 ) call printi(uses v as a column and makes 3 columns,a1)
a2 = spread ( v, 1, 3 ) call printi( spread(v,1,3) uses v as a row and makes 3 rows,a2)
contains ! CONVENIENCE ROUTINE; NOT DIRECTLY CONNECTED TO SPREAD(3) subroutine printi(title,a) use, intrinsic :: iso_fortran_env, only : stderr=>ERROR_UNIT,& & stdin=>INPUT_UNIT, stdout=>OUTPUT_UNIT implicit none
!@(#) print small 2d integer scalar, vector, matrix in row-column format
character(len=*),parameter :: all=(" ",*(g0,1x)) character(len=*),intent(in) :: title character(len=20) :: row integer,intent(in) :: a(..) integer :: i
write(*,all,advance=no)trim(title) ! select rank of input select rank(a) rank (0); write(*,(a)) (a scalar) write(*,(" > [ ",i0," ]"))a rank (1); write(*,(a)) (a vector) ! find how many characters to use for integers write(row,(i0))ceiling(log10(max(1.0,real(maxval(abs(a))))))+2 ! use this format to write a row row=(" > [",*(i//trim(row)//:,",")) do i=1,size(a) write(*,fmt=row,advance=no)a(i) write(*,(" ]")) enddo rank (2); write(*,(a)) (a matrix) ! find how many characters to use for integers write(row,(i0))ceiling(log10(max(1.0,real(maxval(abs(a))))))+2 ! use this format to write a row row=(" > [",*(i//trim(row)//:,",")) do i=1,size(a,dim=1) write(*,fmt=row,advance=no)a(i,:) write(*,(" ]")) enddo rank default write(stderr,*)*printi* did not expect rank=, rank(a), & & shape=, shape(a),size=,size(a) stop *printi* unexpected rank end select write(*,all) >shape=,shape(a),,rank=,rank(a),,size=,size(a) write(*,*)
end subroutine printi
end program demo_spread
> TEST SPREAD(3) > SPREAD(3) is a FORTRAN90 function which replicates > an array by adding a dimension. > > suppose we have a scalar S (a scalar) > > [ 99 ] > >shape= ,rank= 0 ,size= 1 > > to add a new dimension (1) of extent 4 call > spread( s, dim=1, ncopies=4 ) (a vector) > > [ 99 ] > > [ 99 ] > > [ 99 ] > > [ 0 ] > >shape= 4 ,rank= 1 ,size= 4 > > first we will set V to (a vector) > > [ 1 ] > > [ 2 ] > > [ 3 ] > > [ 4 ] > >shape= 4 ,rank= 1 ,size= 4 > > and then do "spread ( v, dim=2, ncopies=3 )" > uses v as a column and makes 3 columns (a matrix) > > [ 1, 1, 1 ] > > [ 2, 2, 2 ] > > [ 3, 3, 3 ] > > [ 4, 4, 4 ] > >shape= 4 3 ,rank= 2 ,size= 12 > > spread(v,1,3) uses v as a row and makes 3 rows (a matrix) > > [ 1, 2, 3, 4 ] > > [ 1, 2, 3, 4 ] > > [ 1, 2, 3, 4 ] > >shape= 3 4 ,rank= 2 ,size= 12 >
Fortran 95
MERGE(3), PACK(3), UNPACK(3)
fortran-lang intrinsic descriptions (license: MIT) @urbanjost
| Nemo Release 3.1 | spread (3) | July 22, 2023 |


© 2019
| glycyphyllos glycyphyllos glycyphyllon | sweet leaved | |||
| glycys | glycy | adj | γλυκυϛ sweet, delightful, lovely | |
| phyllon | phyll | noun/n | φυλλον leaf; foliage | |
| os | adj | οϛ adjectival suffix | ||
| Astragalus glycyphyllos L. | ||||
| glycyrrhiza glycyrrhizai | sweet root | |||
| glycys | glycy | adj | γλυκυϛ sweet, delightful, lovely | |
| r | r | cnct | ρ sometimes the Greek aspirated 'r' is rrh and sometimes rh in the Latin transliteration | |
| rhiza | rhiz | noun/f | ριζα root; stem, origin | |
| Polypodium glycyrrhiza D.C.Eat. | ||||
| glyptocarpus glyptocarpa glyptocarpum | sculpted seed | |||
| glyptos | glypt | adj | γλυπτοϛ scultupred, engraved, carved | |
| o | o | cnct | connective vowel in botanical Latin, usually for Greek words but in some cases, such as color tingeing, for Latin words | |
| carpos | carp | noun/m | καρποϛ fruit | |
| us | adj | Latinizing suffix | ||
| Allocarya glyptocarpa Piper Plagiobothrys glyptocarpus (Piper) I.M. Johnston | ||||
| glyptospermus glyptosperma glyptospermum | sculpted seed | |||
| glyptos | glypt | adj | γλυπτοϛ scultupred, engraved, carved | |
| o | o | cnct | connective vowel in botanical Latin, usually for Greek words but in some cases, such as color tingeing, for Latin words | |
| sperma | sperm | noun/n | σπερμα seed, germ | |
| us | adj | Latinizing suffix | ||
| Chamaesyce glyptosperma (Engelm.) Small | ||||
| glyptostroboides glyptostroboides glyptostroboides | Glyptostrobus like | |||
| glyptostrobus | glyptostrob | noun/m | glyptos γλυπτοϛ scultupred, engraved, carved | |
| strobos στροβοϛ a top | ||||
| oides | oid | adj | -οειδεϛ adjective suffix for nouns: like, resemble | |
| Metasequoia glyptostroboides Hu & W.C.Cheng | ||||
| gnidius gnidia gnidium | of or pertaining to Gnidus | |||
| gnidius | gnidi | adj | Gnidius Κνιδοϛ of or pertaining to the city Gnidus (Cnido on the Aegean in present day Turkey) | |
| Daphne gnidium L. |


--- title: Datasets keywords: fastai sidebar: home_sidebar summary: "used datasets" ---
We want to chose moderate size image data, which should has large resolution, but the data volume should not be too large because of the restriction of computing resources. So we chose the following datasets:


About Me
I'm a freelance graphic designer working primarily in logo development. I'm also an amateur writer dabbling in fictional narratives of mystery and science fiction. I constantly pursue different interests as a way of becoming a more versatile person. Above all else, I'm career-focused and a man of action. I finish what I start, and I won't walk away from a project until I feel that it is the best representation of my work ethic and creative ability.
Career Objective
Data visualization is the discipline that I've been trying to develop my expertise and skills in lately. My goal is to establish a platform to visually communicate information and data that will resonate with a variety of audiences.
Education Summary
I graduated from Azusa Pacific University in May 2014 with a Bachelor's degree in Psychology and 3.42 GPA. I was originally drawn to the discipline of Psychology due to the practice of quantitative and qualitative research of social trends. Since then, I have been cultivating my reasearch skills through mutliple projects that include the layout of information and data. I'm currently attending courses in software development at Code Fellows in Seattle, WA.
Professional Experience
COMMUNICATIONS SPECIALIST at Forever 21 Corporate HQ: April to September 2016
TALENT ACQUISITION COORDINATOR at Forever 21 Corporate HQ: February to April 2016
HRIS ASSOCIATE at Forever 21 Corporate HQ: November 2015 to February 2016
EMPLOYMENT FIRST CASE MANAGER at Discover Goodwill: March to October 2015


This post shows
how to build a clean
stacked
area chart using R
, ggplot2
and the
tidyverse
. This chart is ready for publication. It has a
nice color palette, some very clean inline labels, a
powerfull title and slick footer caption with logos.
This page showcases the work of Gilbert Fontana, which was originally published on twitter.
Thanks to him for accepting sharing his work here! As a teaser, here is the plot we’re gonna try building:
As usual, let’s start by loading some libraries.
Today’s plot requires quite a lot of packages to be built. You can
install them with the install.packages()
function. Once
installed, load them with the library()
function:
library(tidyverse)
#library(janitor)
library(readxl)
library(ggstream)
library(showtext)
library(ggtext)
You are probably familiar with the tidyverse
already.
readxl
will be used in the next section to load the dataset
from a xlsx
format directly. ggstream
is used
to smooth the area shapes. showtext
is used to load some
custom fonts.
The data is stored on github
in a xslx
file. To reproduce this tutorial, please download
the file and run the following line of code. The
read_excel()
function of the readxl
package
makes it easy to load this file directly without requiring the
.csv
format.
Note: do not forget to update the path to point to the file on your computer.
Everything start with a basic stacked area chart. You can see many examples in the stacked area chart section of the R graph gallery, including beginner level tutorials.
Basically, the ggplot
function is used to start a chart
with ggplot2
. Then, the year
column of the
dataset (df
) is used for the x
axis,
total_wealth
for the Y axis and everything is stacked and
colored using the country
column.
Last but not least, the geom_area
geom can be used to
create a stacked area chart.
# Stacked area chart with smoothing
df %>%
ggplot(aes(year, total_wealth, fill = country, label = country, color = country)) +
geom_area()
That’s it! 🔥 We now have a first stacked area chart showing what’s happening in our dataset.
It is possible to make the lines smoother thanks to the
geom_stream
geom of the ggstream
package. It’s
gonna create a less accurate but more organic and eye catching shape to
the graph:
What looks especially good in Gilbert’s chart is the color palette.
Let’s build a vector of color that we then inject into the chart using
the scale_fill_manual
and scale_color_manual
functions:
#Color palette
pal=c("#003f5c",
"#2f4b7c",
"#665191",
"#a05195",
"#d45087",
"#f95d6a",
"#ff7c43",
"#ffa600")
# Stacking order
order <- c("United States", "China", "Japan", "Germany", "United Kingdom", "France", "India", "Other")
# Use them for the plot
df %>%
arrange(total_wealth) %>%
mutate(country = factor(country, levels=order)) %>%
ggplot(aes(year, total_wealth, fill = country, label = country, color = country)) +
geom_stream(type = "ridge" ,bw=1) +
scale_fill_manual(values=pal) +
scale_color_manual(values=pal) +
scale_x_continuous(breaks=c(2000,2005,2010,2015,2021),labels = c("2000","2005","2010","2015","2021")) +
scale_y_continuous(expand = c(0,0)) +
coord_cartesian(clip = "off")
Before adding the title, legend and inline labels we need to load some custom fonts.
This is made possible thanks to the showtext
package and
its font_add_google()
function. Using custom fonts can be a
bit tricky. Fortunately, I wrote a complete
tutorial just in case the following code sounds strange to you.
# Name of the fonts we need
font <- "Josefin Sans"
font2 <- "Open Sans"
# Use the font_add_google() function to load fonts from the web
font_add_google(family=font, font, db_cache = FALSE)
font_add_google(family=font2, font2, db_cache = FALSE)
fa_path <- systemfonts::font_info(family = "Font Awesome 6 Brands")[["path"]]
font_add(family = "fa-brands", regular = fa_path)
theme_set(theme_minimal(base_family = font2, base_size = 3))
bg <- "white"
txt_col <- "black"
showtext_auto(enable = TRUE)
Since we are talking about thext, let’s also create the caption text that appear at the bottom of the figure:
caption_text <- str_glue("**Data:** James Davies, Rodrigo Lluberas and Anthony Shorrocks, Credit Suisse Global Wealth Databook 2022
",
"**Design:** Gilbert Fontana

",
" gilbertfontana
",
" GilbertFontana
",
" gilbert.fontana"
)
The final figure can now be created:
annotate()
functionannotate()
function againgeom_segment()
functionplot <- df %>%
arrange(total_wealth) %>%
mutate(country = factor(country, levels=order)) %>%
ggplot(aes(year, total_wealth, fill = country, label = country, color = country)) +
geom_stream(type = "ridge" ,bw=1) +
#Title
annotate("text", x = 2000, y = 410000,
label = "Aggregated\nHousehold\nWealth",
hjust=0,
size=15,
lineheight=.9,
fontface="bold", family=font,
color="black") +
#USA
annotate("text", x = 2021.2, y = 420000,
label = "USA $145,793B",
hjust=0,
size=3,
lineheight=.8,
fontface="bold", family=font2,
color=pal[1]) +
#China
annotate("text", x = 2021.2, y = 300000,
label = "China $85,107B",
hjust=0,
size=3,
lineheight=.8,
fontface="bold",family=font2,
color=pal[2]) +
#Japan
annotate("text", x = 2021.2, y = 245000,
label = "Japan $25,692B",
hjust=0,
size=3,
lineheight=.8,
fontface="bold",family=font2,
color=pal[3]) +
#Germany
annotate("text", x = 2021.2, y = 220000,
label = "Germany $17,489B",
hjust=0,
size=3,
lineheight=.8,
fontface="bold",family=font2,
color=pal[4]) +
#UK
annotate("text", x = 2021.2, y = 200000,
label = "UK $16,261B",
hjust=0,
size=3,
lineheight=.8,
fontface="bold",family=font2,
color=pal[5]) +
#France
annotate("text", x = 2021.2, y = 183000,
label = "France $16,159B",
hjust=0,
size=3,
lineheight=.8,
fontface="bold",family=font2,
color=pal[6]) +
#India
annotate("text", x = 2021.2, y = 165000,
label = "India $14,225B",
hjust=0,
size=3,
lineheight=.8,
fontface="bold",family=font2,
color=pal[7]) +
#Other
annotate("text", x = 2021.2, y = 80000,
label = "Rest of the world $142,841B",
hjust=0,
size=3,
lineheight=.8,
fontface="bold",family=font2,
color=pal[8]) +
## Vertical segments
geom_segment(aes(x = 2000, y = 0, xend = 2000, yend = 117426+20000),color="black") +
geom_point(aes(x = 2000, y = 117426+20000),color="black") +
annotate("text", x = 2000, y = 117426+30000,
label = "$117,844B",
hjust=0.5,
size=3,
lineheight=.8,
fontface="bold",family=font2,
color=txt_col) +
geom_segment(aes(x = 2005, y = 0, xend = 2005, yend = 181731+20000),color="black") +
geom_point(aes(x = 2005, y = 181731+20000),color="black") +
annotate("text", x = 2005, y = 181731+30000,
label = "$182,350B",
hjust=0.5,
size=3,
lineheight=.8,
fontface="bold",family=font2,
color=txt_col) +
geom_segment(aes(x = 2010, y = 0, xend = 2010, yend = 250932+20000),color="black") +
geom_point(aes(x = 2010, y = 250932+20000),color="black") +
annotate("text", x = 2010, y = 250932+30000,
label = "$251,885B",
hjust=0.5,
size=3,
lineheight=.8,
fontface="bold",family=font2,
color=txt_col) +
geom_segment(aes(x = 2015, y = 0, xend = 2015, yend = 296203+25000),color="black") +
geom_point(aes(x = 2015, y = 296203+25000),color="black") +
annotate("text", x = 2015, y = 296203+35000,
label = "$297,698B",
hjust=0.5,
size=3,
lineheight=.8,
fontface="bold",family=font2,
color=txt_col) +
geom_segment(aes(x = 2021, y = 0, xend = 2021, yend = 461370+50000),color="black") +
geom_point(aes(x = 2021, y = 461370+50000),color="black") +
annotate("text", x = 2021, y = 461370+50000,
label = "$463,567B",
hjust=1.1,
size=3,
lineheight=.8,
fontface="bold",family=font2,
color=txt_col) +
#Color scale
scale_fill_manual(values=pal) +
scale_color_manual(values=pal) +
scale_x_continuous(breaks=c(2000,2005,2010,2015,2021),labels = c("2000","2005","2010","2015","2021")) +
scale_y_continuous(expand = c(0,0)) +
#Last customization
coord_cartesian(clip = "off") +
xlab("") +
ylab("") +
labs(caption = caption_text #"Data: Flash Eurobarometer, Number 509 (October 2022)"
) +
theme(
axis.line.x = element_line(linewidth = .75),
panel.grid = element_blank(),
axis.text.y=element_blank(),
axis.text.x = element_text(color=txt_col, size=10,margin = margin(5,0,0,0)),
plot.margin = margin(20,120,20,20),
legend.position = "none",
plot.caption = element_markdown(hjust=0, margin=margin(10,0,0,0), size=8, color=txt_col, lineheight = 1.2),
)


2 references to LogEngineHealthEvent
System.Management.Automation (2)
logging\MshLog.cs (2)
283LogEngineHealthEvent(executionContext, eventId, exception, severity, additionalInfo, EngineState.None);
301LogEngineHealthEvent(executionContext, eventId, exception, severity, null, newEngineState);


Waterloo Road actor Dean Smith joins Coronation Street
He played Phillip Ryan
by Entertainment DailyDean Smith has joined Coronation Street in a guest role.
The actor - who has appeared in the likes of Waterloo Road and Hollyoaks - will be on the cobbles next week after being cast as Andy, a counsellor supporting Paul Foreman (Peter Ash) as he looks for help over his traumatic past.
In upcoming episodes, Paul will finally break his silence by revealing to his family that stepfather Kel Hinchley (Joseph Alessi) sexually abused him as a child, although he initially refuses to report him to the police.
Read more: Coronation Street SPOILERS: Hope's behaviour gets even more worrying
Despite not wanting to have to answer questions about the ordeal, next week Paul changes his mind and wants to make a statement to put Kel behind bars.
His on-screen boyfriend Billy Mayhew (Daniel Brocklebank) then makes an appointment for him to see a counsellor at a sexual abuse charity.
He confides in Andy about the abuse, and Dean's character assures him the hardest part is over as he looks to make his statement to the police.
Dean previously took on the role of Philip Ryan on Waterloo Road in 2009 and 2010, and he has featured as Hollyoaks' corrupt police officer DS Yates since 2018.
Read more: Coronation Street fans sickened by robbery during Sinead's funeral
Other TV roles include appearances in the likes of Still Open All Hours, Last Tango In Halifax and Being Victor.

He said: "I have been speaking to Duncan and he has been great. His experience was really similar to Paul's so it was important for me to talk about all the conflicting emotions and not accepting or realising it was abuse until later on in life.
 It's an important storyline and I want to get it right."
Coronation Street is on Monday, Wednesday and Friday at 7.30pm and 8.30pm on ITV.
Leave us a comment on our Facebook page @EntertainmentDailyFix and let us know what you think!


Any content can be used in the <vaadin-form-item>
element. For instance,
you can add multiple input elements with surrounding text. The label can be any element:
Note: in order to make <textarea>
vertically
aligned with the <vaadin-form-item>
label, add
textarea { vertical-align: top; display: inline-flex; }
to your CSS.
The label is optional and can be omitted:
Use JSON in the <responsive-steps>
HTML attribute to specify
custom responsive steps for the <vaadin-form-layout>
element.
See also: responsiveSteps
property in the API Reference.
Alternatively, you can customize the responsive steps by using JavaScript
to set the responsiveSteps
array property.
Responsive steps can optionally set labelsPosition
string
option. The following values are supported:
The following custom CSS properties are supported in <vaadin-form-layout>
:
| CSS Property | Description | Default |
|---|---|---|
--vaadin-form-layout-column-gap |
Length of the gap between columns | 2em |
Additionaly, <vaadin-form-item>
supports:
| CSS Property | Description | Default |
|---|---|---|
--vaadin-form-item-label-width |
Width of the label column when the labels are aside | 8em |
--vaadin-form-item-label-gap |
Length of the gap between the label and input columns when the labels are aside | 1em |
--vaadin-form-item-row-gap |
Height of the gap between the form item elements | 1em |
Note: When not using <vaadin-form-item>
, vertical
gaps between the form rows should be added manually. For example, use CSS to add
vertical margin for the <vaadin-text-field>
child elements:
<paper-input>
elements have built-in vertical spacing. Adding margins
with CSS is unnecessary.


Located south east of Auckland, Tauranga is a large sheltered harbour in the Bay of Plenty.
It has become popular as a Port of Entry with yachts arriving from Tonga, as well as a place to be based during the hurricane season. Weather is better here (less rain than Northland),
As you come within range of Tauranga contact should be made through one of the following:-
Plenty Maritime Radio VHF channel 68
Tauranga Volunteer Coastguard VHF channel 83
Tauranga Bridge Marina VHF channel 73
You should provide them with your arrival time. Any of these organizations will contact Customs and let them know of your arrival so they can meet you.
Tauranga has its own Customs office as it is a major New Zealand shipping port. The advantage of this is that you do not have to deal with Auckland. Since fewer clear in here from the islands a year, the officials are not overwhelmed by yachts and are extremely cooperative. Extensions are handled here directly and are straight forwarded and simple. Immigration is handled through Hamilton rather than Auckland, again away from the major paperwork congestion that the seems to surround transactions with the big city.
Upon arrival at your slip in a marina, you will be immediately met by Customs (who also takes care of the Immigration formalities) and MAF. They do this on a 24 hour/7 day a week basis.
Last updated February 2013.


ISRO
The Indian Space Research Organisation is the space agency of the Government of India and has its headquarters in the city of Bengaluru. Its vision is to "harness space technology for national development while pursuing space science research & planetary exploration.The Indian National Committee for Space Research (INCOSPAR) was established by Jawaharlal Nehru under the Department of Atomic Energy (DAE) in 1962.
NASA
The National Aeronautics and Space Administration is an independent agency of the United States Federal Government responsible for the civilian space program, as well as aeronautics and space research.The agency is also responsible for the Launch Services Program, which provides oversight of launch operations and countdown management for uncrewed NASA launches.
Space-X
Space Exploration Technologies Corp., trading as SpaceX, is an American aerospace manufacturer and space transportation services company headquartered in Hawthorne, California. It was founded in 2002 by Elon Musk with the goal of reducing space transportation costs to enable the colonization of Mars.SpaceX has developed several launch vehicles, the Starlink satellite constellation, and the Dragon spacecraft.
Asteroids
Asteroids are minor planets, especially of the inner Solar System. Larger asteroids have also been called planetoids. To know more join us in the journey of space.
Black Hole
A black hole is a region of spacetime where gravity is so strong that nothing—no particles or even electromagnetic radiation such as light—can escape from it.We got lots of articles on Black hole.
Space Journey
The universe is all of space and time and their contents, including planets, stars, galaxies, and all other forms of matter and energy. Lets dive into the journey of space.


1 killed, 3 wounded in Perris shootings
by ABC7.com staffPERRIS, Calif. (KABC) -- One person was killed and three others were hospitalized following two separate shootings in Perris Wednesday afternoon.
The first shooting happened just before 2:30 p.m. in the 1500 block of Remembrance Drive and left one man hospitalized.
The second shooting happened just two hours later in the 200 block of 5th Street.
Three victims were found there. One was pronounced dead at the scene and the other two were taken to a nearby hospital in unknown condition.
Following a short chase, several suspects were detained for questioning about the incident on 5th Street.
Authorities are investigating whether the two shootings are related.


Japanese car giant Honda cuts profit outlook as sales slip
Honda has become the latest car maker to report weaker earnings as global demand softens.
The company said its profit in the July-September period fell 6.7% from a year earlier to 196.5 billion yen (€1.6bn) as vehicle and motorcycle sales slipped.
The Tokyo-based firm said an unfavourable exchange rate also hurt earnings.
Honda’s quarterly revenue declined 2.9% to 3.7 trillion yen (€30bn) as sales declined in the US, Japan, the rest of Asia and Europe.
Honda, which makes the Odyssey minivan and Asimo robot, said higher tax expenses also hurt results.
Honda lowered its full-year net profit forecast for the fiscal year through to March 2020 to 575 billion yen.
That is down from the 645 billion yen (£4.6 billion) estimate given in August, and below the 610 billion yen (£4.3 billion) earned in the previous fiscal year.
Honda said its financial services business did well, helping to offset some of the damage from other divisions.
Honda officials acknowledged that more needs to be done to reduce costs. They said a promised restructuring is under way.
Earlier this week, Honda’s Japanese rival Toyota reported its sales grew in key global regions, helping Japan’s top car maker post an increase in quarterly net profit despite a strong yen, which hurts the earnings of Japanese exporters.
Nissan, which has seen its brand power tarnished amid a financial misconduct scandal, will report earnings next week.


After several years of a temp tournament The Beach City Bowl a 9 hole course was installed in 2017. In 2019 the club was founded and began holding leagues, cleaning the course, fixing tee pads, organizing and advocating for disc golf with LA County.
The Kenneth Hahn Disc Golf Club was founded by Matthew Brozen as a way to bring the community together. After several years of playing the course without seeing anyone else Matt had a dream that there would be a abundance of people coming together to enjoy the course. Since then the club has grow to several hundred members, holds regular leagues, provides bag tags, started a free disc lending library at the visitor center, purchased a practice basket, fixed tee pads, added directional arrows and continues to advocate for more improvements to the course.
Check the visitor center or contact us using the form below. Discs with names and numbers are contacted immediately, discs without names are held for 30 days then donated to the visitor center.


--- layout: default title: About Me ---
Thanks for coming to my corner of the internet!
I grew up in Pakistan where I did my undergrad in EE at LUMS. After finishing my undergrad in 2012, I came to Michigan for grad school, where I got a masters in EE. In 2014, I moved to Boston and worked for MathWorks in their compilers team, specifically developing features for the Simulink Coder and Embedded Coder products.
In 2018, I joined LinkedIn in the SF Bay Area. Here, I work on the backend web services for the LinkedIn feed.


Actor environment including scheduler, registry, and optional components such as a middleman.
More...
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const strong_actor_ptr & | spawn_serv () const |
| | Returns the internal actor for dynamic spawn operations.
|
| |
|
const strong_actor_ptr & | config_serv () const |
| | Returns the internal actor for storing the runtime configuration for this actor system.
|
| |
|
| actor_system (const actor_system &)=delete |
| |
|
actor_system & | operator= (const actor_system &)=delete |
| |
| | actor_system (actor_system_config &cfg) |
| |
|
template<class T , class E = typename std::enable_if<!is_typed_actor<T>::value>::type> |
| mpi | message_types (detail::type_list< T >) const |
| |
|
template<class... Ts> |
| mpi | message_types (detail::type_list< typed_actor< Ts... > >) const |
| |
|
template<class T , class E = typename std::enable_if<!detail::is_type_list<T>::value>::type> |
| mpi | message_types (const T &) const |
| |
|
template<class T > |
| mpi | message_types () const |
| | Returns a string representation of the messaging interface using portable names;.
|
| |
| bool | assignable (const mpi &xs, const mpi &ys) const |
| | Returns whether actor handles described by xs can be assigned to actor handles described by ys .
|
| |
| template<class T > |
| bool | assignable (const std::set< std::string > &xs) const |
| | Returns whether actor handles described by xs can be assigned to actor handles of type T .
|
| |
|
telemetry::metric_registry & | metrics () noexcept |
| | Returns the metrics registry for this system.
|
| |
|
const telemetry::metric_registry & | metrics () const noexcept |
| | Returns the metrics registry for this system.
|
| |
|
const node_id & | node () const |
| | Returns the host-local identifier for this system.
|
| |
|
scheduler::abstract_coordinator & | scheduler () |
| | Returns the scheduler instance.
|
| |
|
caf::logger & | logger () |
| | Returns the system-wide event logger.
|
| |
|
actor_registry & | registry () |
| | Returns the system-wide actor registry.
|
| |
|
group_manager & | groups () |
| | Returns the system-wide group manager.
|
| |
|
bool | has_middleman () const |
| | Returns true if the I/O module is available, false otherwise.
|
| |
| io::middleman & | middleman () |
| | Returns the middleman instance from the I/O module.
|
| |
|
bool | has_openssl_manager () const |
| | Returns true if the openssl module is available, false otherwise.
|
| |
| openssl::manager & | openssl_manager () const |
| | Returns the manager instance from the OpenSSL module.
|
| |
|
bool | has_network_manager () const noexcept |
| | Returns true if the network module is available, false otherwise.
|
| |
| net::middleman & | network_manager () |
| | Returns the network manager (middleman) instance.
|
| |
|
scoped_execution_unit * | dummy_execution_unit () |
| | Returns a dummy execution unit that forwards everything to the scheduler.
|
| |
|
actor_id | next_actor_id () |
| | Returns a new actor ID.
|
| |
|
actor_id | latest_actor_id () const |
| | Returns the last given actor ID.
|
| |
|
void | await_all_actors_done () const |
| | Blocks this caller until all actors are done.
|
| |
| void | monitor (const node_id &node, const actor_addr &observer) |
| | Send a node_down_msg to observer if this system loses connection to node .
|
| |
|
void | demonitor (const node_id &node, const actor_addr &observer) |
| | Removes observer from the list of actors that receive a node_down_msg if this system loses connection to node .
|
| |
| template<class C , spawn_options Os, class... Ts> |
| infer_handle_from_class_t< C > | spawn_class (actor_config &cfg, Ts &&... xs) |
| | Called by spawn when used to create a class-based actor to apply automatic conversions to xs before spawning the actor.
|
| |
| template<class C , spawn_options Os = no_spawn_options, class... Ts> |
| infer_handle_from_class_t< C > | spawn (Ts &&... xs) |
| | Returns a new actor of type C using xs... as constructor arguments.
|
| |
| template<spawn_options Os = no_spawn_options, class F , class... Ts> |
| infer_handle_from_fun_t< F > | spawn (F fun, Ts &&... xs) |
| | Returns a new functor-based actor.
|
| |
| template<class Handle , class E = typename std::enable_if<is_handle<Handle>::value>::type> |
| expected< Handle > | spawn (const std::string &name, message args, execution_unit *ctx=nullptr, bool check_interface=true, const mpi *expected_ifs=nullptr) |
| | Returns a new actor with run-time type name , constructed with the arguments stored in args .
|
| |
|
template<spawn_options Os = no_spawn_options, class F , class... Ts> |
| infer_handle_from_fun_t< F > | spawn_in_groups (std::initializer_list< group > gs, F fun, Ts &&... xs) |
| | Returns a new functor-based actor subscribed to all groups in gs .
|
| |
|
template<spawn_options Os = no_spawn_options, class Gs , class F , class... Ts> |
| infer_handle_from_fun_t< F > | spawn_in_groups (const Gs &gs, F fun, Ts &&... xs) |
| | Returns a new functor-based actor subscribed to all groups in gs .
|
| |
|
template<spawn_options Os = no_spawn_options, class F , class... Ts> |
| infer_handle_from_fun_t< F > | spawn_in_group (const group &grp, F fun, Ts &&... xs) |
| | Returns a new functor-based actor subscribed to all groups in gs .
|
| |
|
template<class T , spawn_options Os = no_spawn_options, class... Ts> |
| infer_handle_from_class_t< T > | spawn_in_groups (std::initializer_list< group > gs, Ts &&... xs) |
| | Returns a new class-based actor subscribed to all groups in gs .
|
| |
|
template<class T , spawn_options Os = no_spawn_options, class Gs , class... Ts> |
| infer_handle_from_class_t< T > | spawn_in_groups (const Gs &gs, Ts &&... xs) |
| | Returns a new class-based actor subscribed to all groups in gs .
|
| |
|
template<class T , spawn_options Os = no_spawn_options, class... Ts> |
| infer_handle_from_class_t< T > | spawn_in_group (const group &grp, Ts &&... xs) |
| | Returns a new class-based actor subscribed to all groups in gs .
|
| |
|
bool | await_actors_before_shutdown () const |
| | Returns whether this actor system calls await_all_actors_done in its destructor before shutting down.
|
| |
|
void | await_actors_before_shutdown (bool x) |
| | Configures whether this actor system calls await_all_actors_done in its destructor before shutting down.
|
| |
|
const actor_system_config & | config () const |
| | Returns the configuration of this actor system.
|
| |
|
actor_clock & | clock () noexcept |
| | Returns the system-wide clock.
|
| |
|
size_t | detached_actors () const noexcept |
| | Returns the number of detached actors.
|
| |


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Kiali provides answers to the question. What are the microservices in my Istio service mesh doing? {{ content }}


Sir Andrew Barron Murray is a British professional tennis player from Scotland currently ranked world no. 16 in men's singles.
Murray represents Great Britain in his sporting activities and is a three-time Grand Slam tournament winner, two-time Olympic champion, Davis Cup champion
and the winner of the 2016 ATP World Tour Finals. Murray defeated Novak Djokovic in the 2012 US Open final, becoming the first British player since 1977,
and the first British man since 1936, to win a Grand Slam singles tournament. Murray is also the first British man to win more than one Wimbledon singles
title since Fred Perry in 1935. Murray is the men's singles 2012 and 2016 Olympic gold medallist, making him the only tennis player, male or female, to have won
two Olympic singles titles. He featured in Great Britain's Davis Cup-winning team in 2015, going 11–0 in his matches (8 singles and 3 doubles) as they secured
their first Davis Cup title since 1936.
In 2014, Murray signed a new UA clothing deal for an extra 4 years.


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aler
alwal
ammuguda
arts college
begumpet
bharatnagar
bhongir
bibinagar jn
bolarum
bolarum bazar
borabanda
budvel
cavalry barracks
chandanagar
charlapalli
dabilpur
dabirpura
dayanandnagar
falaknuma
fatehnagar
ghanapur
ghatkesar
gowdavalli
gundla pochampalli
hafeezpet
hitech city
huppuguda
hyderabad
jamai osmania
james street
jangaon
kacheguda
kazipet jn
khairatabad
kuchavaram h
lakdikapul
lallaguda gate
lingampalli
malakpet
malkajgiri
manoharabad
medchal
nature cure hospital
necklace road
npa shivrampalli
pembarthi
pindial
raghunathapalli
raigir
ramakistapuram gate
safilguda
sanjeevaiah park
secunderabad
sitafalmandi
umdanagar
vidyanagar
wangapalli
warangal
yakutpura
aler
alwal
ammuguda
arts college
begumpet
bharatnagar
bhongir
bibinagar jn
bolarum
bolarum bazar
borabanda
budvel
cavalry barracks
chandanagar
charlapalli
dabilpur
dabirpura
dayanandnagar
falaknuma
fatehnagar
ghanapur
ghatkesar
gowdavalli
gundla pochampalli
hafeezpet
hitech city
huppuguda
hyderabad
jamai osmania
james street
jangaon
kacheguda
kazipet jn
khairatabad
kuchavaram h
lakdikapul
lallaguda gate
lingampalli
malakpet
malkajgiri
manoharabad
medchal
nature cure hospital
necklace road
npa shivrampalli
pembarthi
pindial
raghunathapalli
raigir
ramakistapuram gate
safilguda
sanjeevaiah park
secunderabad
sitafalmandi
umdanagar
vidyanagar
wangapalli
warangal
yakutpura
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