The aim of this project is to build your own Effective field theory (EFT) interaction model that approximates the phase shifts you extracted with the simple interaction model from project 1. We will thus use as input the phase shift analysis from the previous project and use these as our theoretical benchmark data. We will follow closely Lepage's article *How to renormalize the Schroedinger equation*, see especially pages 8-17.
We will start by building a pionless EFT potential to describe nucleon-nucleon scattering low energies where even the longest range piece of the potential is unresolved. Therefore, the EFT potential is just a series of contact interactions. Recall that this is the domain of the effective range expansion, which is valid up to an onshell momentum \( k\sim m_{\pi}/2 \), which translates to about 10 MeV lab energy. If we were considering the true NN system with non-central terms (and full spin- and isospin-dependent terms, we drop isospin here), then the contact interactions take the form: $$ \begin{align*} V^\mathrm{LO}(\vec{q},\vec{k})=&C_S+C_T\vec{\sigma}_1\cdot\vec{\sigma}_2,\\ V^\mathrm{NLO}(\vec{q},\vec{k})=&C_1\vec{q}^{\,2}+C_2\vec{k}^2+ \vec{\sigma}_1\cdot\vec{\sigma}_2\left(C_3\vec{q}^2+C_4\vec{k}^2\right)\\ &+iC_5\frac{\vec{\sigma}_1+\vec{\sigma}_2}{2}\cdot\vec{q}\times\vec{k}+C_6\vec{q}\cdot\vec{\sigma}_1\vec{q}\cdot\vec{\sigma}_2 +C_7\vec{k}\cdot\vec{\sigma}_1\vec{k}\cdot\vec{\sigma}_2, \end{align*} $$ where \( \vec{q}=\vec{p}-\vec{p'} \) is the momentum transfer, \( \vec{k}=\frac{\vec{p}+\vec{p'}}{2} \) the average momentum, and \( \vec{p},\vec{p'} \) the relative momenta. However, since our "underlying theory" in Project 1 is spin- and isospin-independent, the above simplifies substantially, just strike out any terms with Pauli spin/isospin matrices!
Note that the coupling constants appearing in the \( ^1S_0 \) expressions are linear combinations of the coupling constants in the general expressions shown above. Their exact form will not concern us here, though you can find the relevant details on pp. 32-33 of Machleidt and Entem.
As it stands, this potential would give UV divergences if you naively used it in the LS equation of project 1. Therefore, we need to regularize the potential to cutoff the problematic high-momentum modes in the loop integrals. In class, we used a sharp cutoff so that the above would by multiplied by \( \theta(\Lambda - p)\theta(\Lambda-p') \). While conceptually simple, sharp cutoffs can be tricky, can you guess how you would need to modify the trick used to handle the principal value integral in the LS equation? (This is actually the least of our worries. If we try to use a sharp cutoff in some manybody method that relies on expanding the Hamiltonian in a harmonic oscillator basis, the expansion is very slowly converging in analogy with the Gibbs overshoot phenomena in Fourier analysis.) To avoid these subtleties, we will instead use a smooth UV regulator as $$ V(p',p)\Rightarrow f_{\Lambda}(p')V(p',p)f_{\Lambda}(p)\, $$ where we choose $$ f_{\Lambda}(p) = \exp{[-p^4/\Lambda^4]}\,. $$
Choose an appropriate value for \( \Lambda \) and fit \( C_0 \) to low energy phase shifts. Hint: Following Lepage, always use the most infrared data possible when fitting the couplings of contact terms. Also, remember Lepage's discussion on choosing the value for \( \Lambda \).
and fit the four parameters \( C_0,C_2,C_4,C'_4 \) to the low-energy phase shifts. Make a plot of your calculated LO, NLO, and NNLO phase shifts and compare them to the results from the Project 1 potential. Also make a plot a-la Fig. 3 in Lepage to show the power-law improvement with each additional order, and from this pick off the breakdown scale \( \Lambda_b \) where the EFT stops improving with additional orders. These log-log error plots are commonly known as Lepage plots, and they help show that an EFT is working as expected.
The pionless EFT basically reproduces the physics of the Effective Range Expansion, so we expect \( \Lambda_b\sim m_{\pi} \), which sets the scale of the longest-ranged Yukawa term in the toy potential of Project 1. We now want to build a toy EFT which works at higher energies. To do this, we now include the longest-ranged Yukawa potential as an explicit degree of freedom in our EFT. (We should put quotation marks around the one-pion exchange moniker since our underlying theory is a toy model, without the full spin/isospin dependence that would come with the true OPE potential.)
We will repeat parts 2a)-2b) by including the simple one-pion exchange contribution and refitting the contact term couplings. Therefore, at LO our EFT potential takes the form $$ V^\mathrm{LO}(p,p')= V_{\pi}(p,p') + C_0\, $$ while at NLO our potential takes the form $$ V^\mathrm{NLO}(p,p')= V_{\pi}(p,p') + C_0 + C_2(p^2+p'^2)\,, $$ with the analogous form for the NNLO potential.
Redo the analysis of parts 2a-2b, taking care to modify your choice of \( \Lambda \) to an appropriate value. Your analysis should be very similar as for the pionless theory, except that the value of \( \Lambda_b \) should be at a higher value, roughly equal to the mass of the next heaviest Yukawa term.
Redo the analysis of part 2c, and comment on any similarities/differences.
Here follows a brief recipe and recommendation on how to write a report for each project.
The preferred format for the report is a PDF file. You can also use DOC or postscript formats or as an ipython notebook file. As programming language we prefer that you choose between C/C++, Fortran2008 or Python. The following prescription should be followed when preparing the report:


This is very strange, but apparently this organization has no members! Highly irregular!
No members found matching your filter criteria - please try searching for something different.


Instapaper joins Pinterest: Intersting to see as I use both apps heaps
t.co/5L46aOyrw… t.co/FetybYhcz…


The Phychic Game
Guess what letter I'm thinking of ...
Wins:
0
Losses:
0
Guesses Left:
9
Your Guesses so far:
Nothing...


What methods of transportation have you used to get to work in the past year?
What methods of transportation have you used to get to recreational activities in the past year?
You use the following methods of transportation:


public interface IComponentGenerator
| Modifier and Type | Method and Description |
|---|---|
default IComponent |
getBooleanComponent(IBooleanSetting setting,
java.util.function.Supplier<Animation> animation,
IComponentAdder adder,
ThemeTuple theme,
int colorLevel,
boolean isContainer)
Get component from a given boolean setting object.
|
default IComponent |
getColorComponent(IColorSetting setting,
java.util.function.Supplier<Animation> animation,
IComponentAdder adder,
ThemeTuple theme,
int colorLevel,
boolean isContainer)
Get component from a given color setting object.
|
default IComponent |
getComponent(ISetting<?> setting,
java.util.function.Supplier<Animation> animation,
IComponentAdder adder,
ThemeTuple theme,
int colorLevel,
boolean isContainer)
Get component from a given setting object.
|
default IComponent |
getEnumComponent(IEnumSetting setting,
java.util.function.Supplier<Animation> animation,
IComponentAdder adder,
ThemeTuple theme,
int colorLevel,
boolean isContainer)
Get component from a given enum setting object.
|
default IComponent |
getKeybindComponent(IKeybindSetting setting,
java.util.function.Supplier<Animation> animation,
IComponentAdder adder,
ThemeTuple theme,
int colorLevel,
boolean isContainer)
Get component from a given keybind setting object.
|
default IComponent |
getNumberComponent(INumberSetting setting,
java.util.function.Supplier<Animation> animation,
IComponentAdder adder,
ThemeTuple theme,
int colorLevel,
boolean isContainer)
Get component from a given number setting object.
|
default IComponent |
getStringComponent(IStringSetting setting,
java.util.function.Supplier<Animation> animation,
IComponentAdder adder,
ThemeTuple theme,
int colorLevel,
boolean isContainer)
Get component from a given string setting object.
|
default IComponent getComponent(ISetting<?> setting, java.util.function.Supplier<Animation> animation, IComponentAdder adder, ThemeTuple theme, int colorLevel, boolean isContainer)
setting
- the setting object.animation
- the animation supplieradder
- the component adder for any pop-upstheme
- the theme to be usedcolorLevel
- the panel nesting level, in case the component is a container (e.g. color components)isContainer
- whether this component is a title bardefault IComponent getBooleanComponent(IBooleanSetting setting, java.util.function.Supplier<Animation> animation, IComponentAdder adder, ThemeTuple theme, int colorLevel, boolean isContainer)
setting
- the setting object.animation
- the animation supplieradder
- the component adder for any pop-upstheme
- the theme to be usedcolorLevel
- the panel nesting level, in case the component is a container (e.g. color components)isContainer
- whether this component is a title bardefault IComponent getNumberComponent(INumberSetting setting, java.util.function.Supplier<Animation> animation, IComponentAdder adder, ThemeTuple theme, int colorLevel, boolean isContainer)
setting
- the setting object.animation
- the animation supplieradder
- the component adder for any pop-upstheme
- the theme to be usedcolorLevel
- the panel nesting level, in case the component is a container (e.g. color components)isContainer
- whether this component is a title bardefault IComponent getEnumComponent(IEnumSetting setting, java.util.function.Supplier<Animation> animation, IComponentAdder adder, ThemeTuple theme, int colorLevel, boolean isContainer)
setting
- the setting object.animation
- the animation supplieradder
- the component adder for any pop-upstheme
- the theme to be usedcolorLevel
- the panel nesting level, in case the component is a container (e.g. color components)isContainer
- whether this component is a title bardefault IComponent getColorComponent(IColorSetting setting, java.util.function.Supplier<Animation> animation, IComponentAdder adder, ThemeTuple theme, int colorLevel, boolean isContainer)
setting
- the setting object.animation
- the animation supplieradder
- the component adder for any pop-upstheme
- the theme to be usedcolorLevel
- the panel nesting level, in case the component is a container (e.g. color components)isContainer
- whether this component is a title bardefault IComponent getKeybindComponent(IKeybindSetting setting, java.util.function.Supplier<Animation> animation, IComponentAdder adder, ThemeTuple theme, int colorLevel, boolean isContainer)
setting
- the setting object.animation
- the animation supplieradder
- the component adder for any pop-upstheme
- the theme to be usedcolorLevel
- the panel nesting level, in case the component is a container (e.g. color components)isContainer
- whether this component is a title bardefault IComponent getStringComponent(IStringSetting setting, java.util.function.Supplier<Animation> animation, IComponentAdder adder, ThemeTuple theme, int colorLevel, boolean isContainer)
setting
- the setting object.animation
- the animation supplieradder
- the component adder for any pop-upstheme
- the theme to be usedcolorLevel
- the panel nesting level, in case the component is a container (e.g. color components)isContainer
- whether this component is a title bar


[scratchblocks]: dev
You need to serve this page from a local web server.
Render
This is a sentence preceding the most interesting statement in this paragraph. This paragraph contains a
block, oh yes it does. I'm very fond of this block; it's always been my friend.


# mitmweb
mitmweb is mitmproxy’s web-based user interface that allows interactive examination and modification of HTTP traffic. Like mitmproxy, it differs from mitmdump in that all flows are kept in memory, which means that it’s intended for taking and manipulating small-ish samples.
Mitmweb is currently in beta. We consider it stable for all features currently exposed in the UI, but it still misses a lot of mitmproxy’s features.


Watch the Okumu, Herbert, Skinner Trio cover A.K. Paul's 'Landcruisin''
by FACTOkumu, Herbert, Skinner Trio cover A.K. Paul’s ‘Landcruisin”
RE:COVER is a FACT series in which our favorite artists reinterpret songs by their heroes.
On this episode, London’s Okumu, Herbert, Skinner Trio – formed of Dave Okumu and Tom Herbert of The Invisible and Sons Of Kemet’s Tom Skinner – deliver their own unique take on A.K. Paul’s 2016 track, ‘Landcruisin”.
“I’m completely in love with this song, Okumu says. ” It’s a definite desert island disc for me, and when I heard it I just couldn’t believe what was going on in my ears and my mind.”
Watch above and buy their new album Undone: Live at the Crypt, out now via The Vinyl Factory, here.
Filmed by Kamil Dymek, Pedro Kuster and Pawel Ptak
Edited by Pawel Ptak
Watch next: Alicai Harley covers Sunshine Anderson’s ‘Heard It All Before’
Share this story
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PWCore Class Reference
| Inherits from | NSObject |
|---|---|
| Declared in | PWCore.h |
Required Methods
+ setApplicationID:accessKey:signatureKey:
Initializes PWCore and all associated MaaS modules. This method should be called inside application:didFinishLaunchingWithOptions:
before you do anything else.
+ (void)setApplicationID:(NSString *)applicationID accessKey:(NSString *)accessKey signatureKey:(NSString *)signatureKey
Parameters
applicationID |
You can find your Application ID in the MaaS portal. |
|---|---|
accessKey |
A unique key that identifies the client making the request. You can find your Access Key in the MaaS portal. |
signatureKey |
A unique key that is used to sign requests. The signature is used to both check request authorization as well as data integrity. You can find your Signature Key in the MaaS portal. |
Declared In
PWCore.h
+ setApplicationID:accessKey:signatureKey:encryptionKey:
This method has been deprecated. Use setApplicationID:accessKey:signatureKey: instead.
+ (void)setApplicationID:(NSString *)applicationID accessKey:(NSString *)accessKey signatureKey:(NSString *)signatureKey encryptionKey:(NSString *)encryptionKey
Parameters
applicationID |
You can find your Application ID in the MaaS portal. |
|---|---|
accessKey |
A unique key that identifies the client making the request. You can find your Access Key in the MaaS portal. |
signatureKey |
A unique key that is used to sign requests. The signature is used to both check request authorization as well as data integrity. You can find your Signature Key in the MaaS portal. |
encryptionKey |
A unique encryption key this is no longer required. set empty string. |
Declared In
PWCore.h
+ registerModule:version:withCompletion:
This method registers the module and its version.
+ (void)registerModule:(NSString *)moduleName version:(NSString *)version withCompletion:(void ( ^ ) ( NSError *error ))completion
Parameters
moduleName |
The name of the dependent module to be registered. |
|---|---|
version |
version number for the module |
completion |
The completion block to be called. |
Declared In
PWCore.h
+ getAllRegisteredModules
Returns a dictionary of registered modules.
+ (NSDictionary *)getAllRegisteredModules
Declared In
PWCore.h
+ getVersionForModule:
Returns version number for a registered module.
+ (NSString *)getVersionForModule:(NSString *)moduleName
Parameters
moduleName |
The name of the dependent module to be registered. |
|---|
Declared In
PWCore.h
+ enableLocationAccess:
Determines whether location updates are permitted.
+ (void)enableLocationAccess:(BOOL)enable
Parameters
enable |
Will permit location updates and include location information in analytic events. Default is enabled. |
|---|
Declared In
PWCore.h
+ isLocationAccessEnabled
Returns whether location updates are permitted.
+ (BOOL)isLocationAccessEnabled
Declared In
PWCore.h
+ setAnalyticsApplicationID:accessKey:signatureKey:
+ (void)setAnalyticsApplicationID:(NSString *)applicationID accessKey:(NSString *)accessKey signatureKey:(NSString *)signatureKey
+ authorizationHeaderWithRequestBody:httpMethod:
+ (NSString *__nonnull)authorizationHeaderWithRequestBody:(NSData *__nonnull)requestBody httpMethod:(NSString *__nonnull)httpMethod
+ buildRequestWithRequest:
+ (NSMutableURLRequest *__nonnull)buildRequestWithRequest:(NSMutableURLRequest *__nonnull)request
+ sendInternalAnalyticsPayload:completion:
+ (void)sendInternalAnalyticsPayload:(NSDictionary *__nonnull)payload completion:(void ( ^ __nullable ) ( NSError *__nullable error ))completion
+ sendExtraAnalyticsPayload:completion:
+ (void)sendExtraAnalyticsPayload:(NSDictionary *__nonnull)payload completion:(void ( ^ __nullable ) ( NSError *__nullable error ))completion
+ registerPhunwareModule:version:withCompletion:
+ (void)registerPhunwareModule:(NSString *__nonnull)moduleName version:(NSString *__nonnull)version withCompletion:(void ( ^ __nullable ) ( NSError *__nullable error ))completion
+ encryptData:withKey:
+ (NSData *_Nullable)encryptData:(NSData *__nonnull)data withKey:(NSString *__nonnull)key
+ decryptData:withKey:
+ (NSData *_Nullable)decryptData:(NSData *__nonnull)data withKey:(NSString *__nonnull)key


--- layout: page title: About header-img: "img/about-bg.png" ---
I'm Sergey, 30 years old, a technician in a drilling company, who tries to find his way into the future.


Here we have a component which has different behavior based on the browser which is being used. The component shows a list of possible search options which pops open when the user focuses the input field. This list of search options which contains links, and the goal is the user could select one of the links that is shown (see simplete for more context).
The component uses
focus-within
to implement this behavior.
However, this is doesn't work in Safari.
My guess is that Safari doesn't recognize the `.suggestions` dropdown as being part of
the form
element, so when you try to select an element from within the list,
you end up triggering the focus out event which just hides the dropdown before you are
actually able to click on the link in the dropdown.
Here is one solution which uses opacity: 0;
to hide the dropdown field,
and then uses a transition
on the max-height
property with
a overflow: hidden;
rule to also make the elements no longer clickable
(because they will no longer have a height). But because it is a transition,
the height is not modified immediately, so there is still time in Safari to click on
the element before it "disappears" thanks to the change in the `focus-within` rule.
.suggestions--fixed li {
transition: max-height 1s ease;
max-height: 100vh;
}
form:not(:focus-within) .suggestions--fixed {
opacity: 0;
}
form:not(:focus-within) .suggestions--fixed li {
overflow: hidden;
max-height: 0;
}


Ricky Hatton slammed over X-rated fancy dress outfit at family festival in Benidorm
The former welterweight - who once fought Floyd Mayweather - got involved in the annual British Fancy Dress Day celebrations during his trip
by James Rodger, https://www.facebook.com/jamesrodgerjournalistRicky Hatton has been criticised for donning an X-rated fancy dress costume at a Benidorm family festival.
The former boxer is at the popular Spanish destination during its fiesta season.
The former welterweight - who once fought Floyd Mayweather - got involved in the annual British Fancy Dress Day celebrations during his trip.

The post was shared on a Benidorm Facebook page, the Mirror reports , with many criticising the 'bad taste' outfit.
One said: "It's a bit much when there's kids around.''
Back at home, Ricky is currently working with Love Island star Tommy Fury on his return to boxing.
Tommy - the younger brother of Tyson - will make his return to the ring on December 12 and trains at Ricky's gym in Hyde, in Manchester.
The 41-year-old wasn't the only one having a great time as thousands of revellers descend on the resort every year to take part in the November celebrations.


Important: Look at the last digit of you
worker ID. For example, if your worker ID is ASA8XEGP04TF then the
last digit is 4, after ignoring the letters.
If your last digit if one of 0, 2, 4, 6, 8 then you can work on this
task. If not then you can not work on this task, but you can work on our
task called "Guess workers mistakes (ODD)"
Background:
We had a task where workers looked at some text and find words that
are parts of proper nouns such as people name, organization names and
places.
Now we want to know whether you can predict if a worker miss a word, after looking at labels by that worker.
Worker summary:
You will first look at a summary of the labels by a particular
worker. You will see the sentences and the proper nouns in bold and
whether the worker the worker miss each proper noun. For example:
| Word |
Miss |
|
It’s official: Obama attending APEC Summit in Manila
|
YES |
| The time is 05:30 GMT |
YES |
In the first row, APEC is an organization name and should be marked
but the worker missed that. In the second row, the worker missed GMT
(another all-uppercase word).
Task:
You will then answer some question. Each question contains two words;
worker gave the correct labels for one of those and the wrong label for
the other. Your task is to guess which word did the worker miss. For
examples:
1. New York Metropolitan Opera suspends conductor James Levine
2. One dead after hit-and-run driver strikes six in Queens, NY
To help us understand your answer, please select an explantion (or write your own explanation).
For example, if you believe the worker is not good at all-uppercase
words, you should select 2 and select the explanation "worker bad at all
uppercase (acronym)". In contrast, if you believe the worker is good at
all-uppercase words, you should select 1 and select the explanation
"worker good at all uppercase (acronym)"
If you have absolutely no clue, you can select the option "Can't
tell" and select the explanation "Cant' tell". But if you have any clue,
you should not select this.
Hint:
Try to find what types of words in what types of sentences that the worker good at and bad at.


## Actors and Distributed Computing (And how to build this ↓ not this ↓)
Demo
## Architecture Overview ![](images/intro-to-akka/courier-realtime-architecture.png)
#### Examples of Today's Problems * Monitor courier status (auto offline) * Monitor job status (What jobs are currently live? Which jobs haven't been allocated yet?) * Smart recommendations based on geological information (courier, routing, etc) * Dynamic job management (grouping multiple jobs together) * Capacity management (identifying hotspots and send more couriers) * Dynamic pricing (pricing based on demand in each region)
#### The Missing Piece * Microservices are flexible, but coordination is expensive * ML has states, but is not flexible and can be slow * How to merry microservices' scalability + flexibility with ML's intelligence?
## Introducing Actor System ![](images/intro-to-akka/minions.jpg) (They're like minions, but less evil)
### Actor System in a Nutshell
![](images/intro-to-akka/actors-illustration.png)
* An **actor** ≈ a Go routine * Actor has one input channel with buffering (called a **mailbox**) * Actor communicates by passing **messages** * Actor processes messages sequentially
### End Result * Thread safety (no shared states) * Lock free (performance, yay!) * Actors are cheap, can have millions per node
### Actors vs Threads
![](images/intro-to-akka/courier-realtime-actors-vs-threads.png)
* Actors are multiplexed to a small number of threads * Scheduling is taken care by actor system * Users only need to consider business logic
### Introducing ![](images/intro-to-akka/akka-logo.png)
### Who's Using Akka? ![](images/intro-to-akka/courier-realtime-akka-users.png) Case studies: https://www.lightbend.com/case-studies
### What Akka Adds on Top of Actors? * Actor hierarchy and failure handling * Remoting, clustering and sharding * Persistence * Serialization * Distributed data * Pub/sub * Back-pressured streams
### Akka Tech Stack ![](images/intro-to-akka/courier-realtime-akka-tech-stack.png)
### Akka Actor Example ``` import akka.actor.Actor import akka.actor.ActorSystem import akka.actor.Props class HelloActor extends Actor { def receive = { case "hello" => println("hello back at you") case _ => println("huh?") } } object Main extends App { val system = ActorSystem("HelloSystem") // default Actor constructor val helloActor = system.actorOf(Props[HelloActor], name = "helloactor") helloActor ! "hello" helloActor ! "buenos dias" } ```
### Courier Realtime Service Architecture
![](images/intro-to-akka/courier-realtime-actors.png)
* Couriers, places and grid cells are each an actor * Actors interact by passing messages * a: courier moves * b: courier goes offline * c: recommendation request
### a: courier moves ![](images/intro-to-akka/courier-realtime-actors-sub1.png)
### b: courier goes offline ![](images/intro-to-akka/courier-realtime-actors-sub2.png)
### c: recommendation based on distance ![](images/intro-to-akka/courier-realtime-actors-sub3.png)
### Grid Topology
![](images/intro-to-akka/courier-realtime-actors-sub4.png)
![](images/intro-to-akka/courier-realtime-actors-sub5.png)
* The grid can use any shape of tiles * Neighbourhood topology is easily computed * Query all cells concurrently and collect results
### Going Distributed
![](images/intro-to-akka/courier-realtime-akka-clustering-1.png)
### Going Distributed Cont'd
![](images/intro-to-akka/courier-realtime-akka-clustering-2.png)
### Going Distributed Cont'd
![](images/intro-to-akka/courier-realtime-akka-clustering-3.png)
# Going Distributed is Hard
### The Split Brain
![](images/intro-to-akka/courier-realtime-akka-clustering-split-brain-1.png)
### The Split Brain
![](images/intro-to-akka/courier-realtime-akka-clustering-split-brain-2.png)
### The Split Brain
![](images/intro-to-akka/courier-realtime-akka-clustering-split-brain-3.png)
### The Split Brain
![](images/intro-to-akka/courier-realtime-akka-clustering-split-brain-4.png)
### The Split Brain Solutions * Majority wins * Oldest wins * Referee wins
### Gossip Protocol * Heartbeats between nodes * Topology info exchange
### Timeout Issue How long do you wait before marking a node as unreachable?
#### Example ##### The Phi Detector
$$\phi = -\log_{10}(1 - F_\sigma(time\_since\_last\_heartbeat))$$ Where $F_\sigma$ is CDF of a normal distribution with standard deviation $\sigma$
![](images/intro-to-akka/phi-detector.png)
### How to Recover from Crashes? #### Answer: Use Error Kernel and Persistence
### Error Kernel (a fancy way to say "management hierarchy")
![](images/intro-to-akka/akka-actor-hierarchy.png)
### Persistence and Event Sourcing * Event sourcing: modeling events as the "atoms" of state changes * Persist events in time order to DB * Play events back to reconstruct state * Persist snapshots to make recovery faster
#### Akka comes with persistence out of the box
## Ok, so how does it perform under load? ![](images/intro-to-akka/load.jpg)
### Load Test Setup
#### Test Data * 1000 x 1000 grid * 10000 places * Courier sending one ping per minute * Tested with 2000, 20000 couriers #### Service * 2 x c4.large (2 vCPU, 3.75 GB RAM) * 2GB heap, CMS GC #### Cassandra * 2 x c4.large (2 vCPU, 3.75 GB RAM) * 3 nodes for 20000 courier test * 1GB heap, CMS GC
![](images/intro-to-akka/uk-grid.png)
### Load Test Result: 2000 Couriers
![](images/intro-to-akka/load/2000courier-courier-metrics.png) ![](images/intro-to-akka/load/2000courier-system-metrics.png)
![](images/intro-to-akka/load/2000courier-grid-metrics.png) ![](images/intro-to-akka/load/2000courier-network-metrics.png)
Service GC logs: http://gceasy.io/diamondgc-report.jsp?oTxnId_value=ee8d758f-eb0c-4c65-88a4-206f71613575#
### Load Test Result: 20000 Couriers TBC
### What are the Potential Usages of Akka? * Monitoring (courier, job lifecycle, etc) * Recommendation * Notification systems * Search engines (multi-dimensional search and grouping) * Capacity management * Dynamic pricing
### Challenges Unfortunately, it's not all sunshine and roses * Upgradability - Rolling upgrade - A-B switch over - Down time deployment - Rollback? * Persistence - Need to manage Cassandra (or any DB) * Data versioning? - Should use protobuf to ensure backward compatibility - Breaking changes? Might need data migration * Coding - Scala has some learning curve (though I find JavaScript more difficult)
### Wanna try it yourself? ![](images/intro-to-akka/try-again.jpg)
### Project https://github.com/lastmilelink/actor-examples PR and issues welcomed
### Alternative Actor Systems * [Orleans](http://dotnet.github.io/orleans/)(.Net only, sorry) * [Proto Actor](http://proto.actor/)(Go lang, still in beta) * [CAF](https://actor-framework.org/)(C++)
### Alternative Distributed Computing Techs * [Ignite](https://ignite.apache.org/)(Java, in memory data grid) * [Spark Streaming](https://spark.apache.org/streaming/)(Scala) * [Storm](http://storm.apache.org/)(Clojure) * [Glow](https://github.com/chrislusf/glow)(Go lang, map-reduce)
# Thank You Questions?
# References * http://doc.akka.io/docs/akka/current/scala * http://kamon.io/documentation/get-started/ * https://github.com/cloudtools/troposphere * https://github.com/typesafehub/config * https://bitnami.com/stack/cassandra * OpenGIS Spec: http://www.opengeospatial.org/standards/sfa * MapD: https://www.mapd.com/


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Resolved
-
{% set rep = 'resolved' %}
{% include 'snips/report-form.html' %}
{% if not resolved %}
No activity found ...
{% endif %}
Report of resolved events
| Month |
ResolvedBy |
Event |
Status |
Count |
{% for item in resolved %}
|
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{{ item.event }}
|
{{ item.tstate }}
|
{{ item.cnt }}
|
{% endfor %}


Python (Programming Language)
Q1. What is an abstract class?
- [ ] An abstract class is the name for any class from which you can instantiate an object.
- [ ] Abstract classes must be redefined any time an object is instantiated from them.
- [ ] Abstract classes must inherit from concrete classes.
- [x] An abstract class exists only so that other "concrete" classes can inherit from the abstract class.
Q2. What happens when you use the build-in function any()
on a list?
- [ ] The
any()
function will randomly return any item from the list.
- [x] The
any()
function returns True if any item in the list evaluates to True. Otherwise, it returns False.
- [ ] The
any()
function takes as arguments the list to check inside, and the item to check for. If "any" of the items in the list match the item to check for, the function returns True.
- [ ] The
any()
function returns a Boolean value that answers the question "Are there any items in this list?"
Q3. What data structure does a binary tree degenerate to if it isn't balanced properly?
- [x] linked list
- [ ] queue
- [ ] set`
- [ ] OrderedDict
Q4. What statement about static methods is true?
- [ ] Static methods are called static because they always return
None
.
- [ ] Static methods can be bound to either a class or an instance of a class.
- [x] Static methods serve mostly as utility methods or helper methods, since they can't access or modify a class's state.
- [ ] Static methods can access and modify the state of a class or an instance of a class.
Q5. What are attributes?
- [ ] Attributes are long-form version of an
if/else
statement, used when testing for equality between objects.
- [x] Attributes are a way to hold data or describe a state for a class or an instance of a class.
- [ ] Attributes are strings that describe characteristics of a class.
- [ ] Function arguments are called "attributes" in the context of class methods and instance methods.
Q6. What is the term to describe this code?
count, fruit, price = (2, 'apple', 3.5)
- [ ] tuple assignment
- [✅] tuple unpacking
- [ ] tuple matching
- [ ] tuple duplication
Q7. What built-in list method would you use to remove items from a list?
- [ ]
".delete()" method
- [ ]
pop(my_list)
- [ ]
del(my_list)
- [x]
".pop()" method
Q8. What is one of the most common use of Python's sys library?
- [x] to capture command-line arguments given at a file's runtime
- [ ] to connect various systems, such as connecting a web front end, an API service, a database, and a mobile app
- [ ] to take a snapshot of all the packages and libraries in your virtual environment
- [ ] to scan the health of your Python ecosystem while inside a virtual environment
Q9. What is the runtime of accessing a value in a dictionary by using its key?
- [ ] O(n), also called linear time.
- [ ] O(log n), also called logarithmic time.
- [ ] O(n^2), also called quadratic time.
- [x] O(1), also called constant time.
Q10. What is the correct syntax for defining a class called Game?
- [x]
class Game: pass
- [ ]
def Game(): pass
- [ ]
def Game: pass
- [ ]
class Game(): pass
Q11. What is the correct way to write a doctest?
def sum(a, b):
"""
sum(4, 3)
7
sum(-4, 5)
1
"""
return a + b
def sum(a, b):
"""
>>> sum(4, 3)
7
>>> sum(-4, 5)
1
"""
return a + b
def sum(a, b):
"""
# >>> sum(4, 3)
# 7
# >>> sum(-4, 5)
# 1
"""
return a + b
def sum(a, b):
###
>>> sum(4, 3)
7
>>> sum(-4, 5)
1
###
return a + b
Q12. What built-in Python data type is commonly used to represent a stack?
- [ ]
set
- [x]
list
- [ ]
None
. You can only build a stack from scratch.
- [ ]
dictionary
Q13. What would this expression return?
college_years = ['Freshman', 'Sophomore', 'Junior', 'Senior']
return list(enumerate(college_years, 2019))
- [ ]
[('Freshman', 2019), ('Sophomore', 2020), ('Junior', 2021), ('Senior', 2022)]
- [ ]
[(2019, 2020, 2021, 2022), ('Freshman', 'Sophomore', 'Junior', 'Senior')]
- [ ]
[('Freshman', 'Sophomore', 'Junior', 'Senior'), (2019, 2020, 2021, 2022)]
- [x]
[(2019, 'Freshman'), (2020, 'Sophomore'), (2021, 'Junior'), (2022, 'Senior')]
Q14. How does defaultdict
work?
- [ ]
defaultdict
will automatically create a dictionary for you that has keys which are the integers 0-10.
- [ ]
defaultdict
forces a dictionary to only accept keys that are of the types specified when you created the defaultdict
(such as string or integers).
- [x] If you try to access a key in a dictionary that doesn't exist,
defaultdict
will create a new key for you instead of throwing a KeyError
.
- [ ]
defaultdict
stores a copy of a dictionary in memory that you can default to if the original gets unintentionally modified.
Q15. What is the correct syntax for defining a class called "Game", if it inherits from a parent class called "LogicGame"?
- [ ]
class Game.LogicGame(): pass
- [ ]
def Game(LogicGame): pass
- [x]
class Game(LogicGame): pass
- [ ]
def Game.LogicGame(): pass
Q16. What is the purpose of the "self" keyword when defining or calling instance methods?
- [ ]
self
means that no other arguments are required to be passed into the method.
- [ ] There is no real purpose for the
self
method; it's just historic computer science jargon that Python keeps to stay consistent with other programming languages.
- [x]
self
refers to the instance whose method was called.
- [ ]
self
refers to the class that was inherited from to create the object using self
.
Q17. Which of these is NOT a characteristic of namedtuples?
- [ ] You can assign a name to each of the
namedtuple
members and refer to them that way, similarly to how you would access keys in dictionary
.
- [ ] Each member of a namedtuple object can be indexed to directly, just like in a regular
tuple
.
- [ ]
namedtuples
are just as memory efficient as regular tuples
.
- [x] No import is needed to use
namedtuples
because they are available in the standard library.
Q18. What is an instance method?
- [x] Instance methods can modify the state of an instance or the state of its parent class.
- [ ] Instance methods hold data related to the instance.
- [ ] An instance method is any class method that doesn't take any arguments.
- [ ] An instance method is a regular function that belongs to a class, but it must return
None
.
Q19. Which choice is the most syntactically correct example of the conditional branching?
num_people = 5
if num_people > 10:
print("There is a lot of people in the pool.")
elif num_people > 4:
print("There are some people in the pool.")
elif num_people > 0:
print("There are a few people in the pool.")
else:
print("There is no one in the pool.")
num_people = 5
if num_people > 10:
print("There is a lot of people in the pool.")
if num_people > 4:
print("There are some people in the pool.")
if num_people > 0:
print("There are a few people in the pool.")
else:
print("There is no one in the pool.")
num_people = 5
if num_people > 10:
print("There is a lot of people in the pool.")
elif num_people > 4:
print("There are some people in the pool.")
elif num_people > 0:
print("There are a few people in the pool.")
else:
print("There is no one in the pool.")
Q20. Which statement does NOT describe the object-oriented programming concept of encapsulation?
- [ ] It protects the data from outside interference.
- [ ] A parent class is encapsulated and no data from the parent class passes on to the child class.
- [ ] It keeps data and the methods that can manipulate that data in one place.
- [x] It only allows the data to be changed by methods.
Q21. What is the purpose of an if/else statement?
- [ ] An if/else statement tells the computer which chunk of code to run if the instructions you coded are incorrect
- [ ] An if/else statement runs one chunk of code if all the imports were successful, and another chunk of code if the imports were not successful
- [x] An if/else statement executes one chunk of code if a condition it true, but a different chunk of code if the condition is false
- [ ] An if/else statement tells the computer which chunk of code to run if the is enough memory to handle it. and which chunk of code to run if there is not enough memory to handle it
Q22. What built-in Python data type is commonly used to represent a queue?
- [ ]
dictionary
- [ ]
set
- [ ]
None
. You can only build a stack from scratch.
- [x]
list
Q23. What is the correct syntax for instantiating a new object of the type Game?
- [ ]
my_game = class.Game()
- [ ]
my_game = class(Game)
- [x]
my_game = Game()
- [ ]
my_game = Game.create()
Q24. What does the built-in map() function do?
- [ ] It creates a path from multiple values in an iterable to a single value.
- [x] It applies a function to each item in an iterable and returns the value of that function.
- [ ] It converts a complex value type into simpler value types.
- [ ] It creates a mapping between two different elements of different iterables.
Q25. If you don't explicitly return a value from a function, what happens?
- [ ] The function will return a RuntimeError if you don't return a value.
- [x] If the return keyword is absent, the function will return
None
.
- [ ] If the return keyword is absent, the function will return
True
.
- [ ] The function will enter an infinite loop because it won't know when to stop executing its code.
Q26. What is the purpose of the pass
statement in Python?
- [ ] It is used to skip the
yield
statement of a generator and return a value of None.
- [x] It is a null operation used mainly as a placeholder in functions, classes, etc.
- [ ] It is used to pass control from one statement block to another.
- [ ] It is used to skip the rest of a
while
or for loop
and return to the start of the loop.
Q27. What is the term used to describe items that may be passed into a function?
- [x] arguments
- [ ] paradigms
- [ ] attributes
- [ ] decorators
Q28. Which collection type is used to associate values with unique keys?
- [ ]
slot
- [x]
dictionary
- [ ]
queue
- [ ]
sorted list
Q29. When does a for loop stop iterating?
- [ ] when it encounters an infinite loop
- [ ] when it encounters an if/else statement that contains a break keyword
- [x] when it has assessed each item in the iterable it is working on or a break keyword is encountered
- [ ] when the runtime for the loop exceeds O(n^2)
Q30. Assuming the node is in a singly linked list, what is the runtime complexity of searching for a specific node within a singly linked list?
- [x] The runtime is O(n) because in the worst case, the node you are searching for is the last node, and every node in the linked list must be visited.
- [ ] The runtime is O(nk), with n representing the number of nodes and k representing the amount of time it takes to access each node in memory.
- [ ] The runtime cannot be determined unless you know how many nodes are in the singly linked list.
- [ ] The runtime is O(1) because you can index directly to a node in a singly linked list.
Q31. Given the following three list, how would you create a new list that matches the desired output printed below?
fruits = ['Apples', 'Oranges', 'Bananas']
quantities = [5, 3, 4]
prices = [1.50, 2.25, 0.89]
#Desired output
[('Apples', 5, 1.50),
('Oranges', 3, 2.25),
('Bananas', 4, 0.89)]
output = []
fruit_tuple_0 = (first[0], quantities[0], price[0])
output.append(fruit_tuple)
fruit_tuple_1 = (first[1], quantities[1], price[1])
output.append(fruit_tuple)
fruit_tuple_2 = (first[2], quantities[2], price[2])
output.append(fruit_tuple)
return output
i = 0
output = []
for fruit in fruits:
temp_qty = quantities[i]
temp_price = prices[i]
output.append((fruit, temp_qty, temp_price))
i += 1
return output
groceries = zip(fruits, quantities, prices)
return groceries
>>> [
('Apples', 5, 1.50),
('Oranges', 3, 2.25),
('Bananas', 4, 0.89)
]
i = 0
output = []
for fruit in fruits:
for qty in quantities:
for price in prices:
output.append((fruit, qty, price))
i += 1
return output
Q32. What happens when you use the built-in function all() on a list?
- [ ] The
all()
function returns a Boolean value that answers the question "Are all the items in this list the same?
- [ ] The
all()
function returns True if all the items in the list can be converted to strings. Otherwise, it returns False.
- [ ] The
all()
function will return all the values in the list.`
- [x] The
all()
function returns True if all items in the list evaluate to True. Otherwise, it returns False.
Q33. What is the correct syntax for calling an instance method on a class named Game?
(Answer format may vary. Game and roll (or dice_roll) should each be called with no parameters.) - [✅]
>>> dice = Game()
>>> dice.roll()
>>> dice = Game(self)
>>> dice.roll(self)
>>> dice = Game()
>>> dice.roll(self)
>>> dice = Game(self)
>>> dice.roll()
Q34. What is the algorithmic paradigm of quick sort?
- [ ] backtracking
- [ ] dynamic programming
- [ ] decrease and conquer
- [x] divide and conquer
Q35. What is runtime complexity of the list's built-in .append() method?
- [x] O(1), also called constant time
- [ ] O(log n), also called logarithmic time
- [ ] O(n^2), also called quadratic time
- [ ] O(n), also called linear time
Q36. What is key difference between a set and a list?
- [ ] A set is an ordered collection unique items. A list is an unordered collection of non-unique items.
- [ ] Elements can be retrieved from a list but they cannot be retrieved from a set.
- [ ] A set is an ordered collection of non-unique items. A list is an unordered collection of unique items.
- [x] A set is an unordered collection unique items. A list is an ordered collection of non-unique items.
Q37. What is the definition of abstraction as applied to object-oriented Python?
- [ ] Abstraction means that a different style of code can be used, since many details are already known to the program behind the scenes.
- [x] Abstraction means the implementation is hidden from the user, and only the relevant data or information is shown.
- [ ] Abstraction means that the data and the functionality of a class are combined into one entity.
- [ ] Abstraction means that a class can inherit from more than one parent class.
Q38. What does this function print?
def print_alpha_nums(abc_list, num_list):
for char in abc_list:
for num in num_list:
print(char, num)
return
print_alpha_nums(['a', 'b', 'c'], [1, 2, 3])
a 1
a 2
a 3
b 1
b 2
b 3
c 1
c 2
c 3
['a', 'b', 'c'], [1, 2, 3]
aaa
bbb
ccc
111
222
333
a 1 2 3
b 1 2 3
c 1 2 3
Q39. What is the correct syntax for calling an instance method on a class named Game
?
my_game = Game()
my_game.roll_dice()
my_game = Game()
self.my_game.roll_dice()
my_game = Game(self)
self.my_game.roll_dice()
my_game = Game(self)
my_game.roll_dice(self)
Q40. Correct representation of doctest for function in Python
def sum(a, b):
# a = 1
# b = 2
# sum(a, b) = 3
return a + b
def sum(a, b):
"""
a = 1
b = 2
sum(a, b) = 3
"""
return a + b
def sum(a, b):
"""
>>> a = 1
>>> b = 2
>>> sum(a, b)
3
"""
return a + b
Q41. Suppose a Game class inherits from two parent classes: BoardGame and LogicGame. Which statement is true about the methods of an object instantiated from the Game class?
- [ ] When instantiating an object, the object doesn't inherit any of the parent class's methods.
- [ ] When instantiating an object, the object will inherit the methods of whichever parent class has more methods.
- [ ] When instantiating an object, the programmer must specify which parent class to inherit methods from.
- [x] An instance of the Game class will inherit whatever methods the BoardGame and LogicGame classes have.
Q42. What does calling namedtuple on a collection type return?
- [ ] a generic object class with iterable parameter fields
- [ ] a generic object class with non-iterable named fields
- [ ] a tuple subclass with non-iterable parameter fields
- [x] a tuple subclass with iterable named fields
Q43. What symbol(s) do you use to assess equality between two elements?
- [ ]
&&
- [ ]
=
- [x]
==
- [ ]
||
Q44. Review the code below. What is the correct syntax for changing the price to 1.5?
fruit_info = {
'fruit': 'apple',
'count': 2,
'price': 3.5
}
- [x]
fruit_info ['price'] = 1.5
- [ ]
my_list [3.5] = 1.5
- [ ]
1.5 = fruit_info ['price]
- [ ]
my_list['price'] == 1.5
Q45. What value would be returned by this check for equality?
5! = 6
- [ ] yes
- [ ] False
- [✅] True
- [ ] None
Q46. What does a class's init() method do?
- [ ] The
__init__
method makes classes aware of each other if more than one class is defined in a single code file.
- [ ] The
__init__
method is included to preserve backwards compatibility from Python 3 to Python 2, but no longer needs to be used in Python 3.
- [x] The
__init__
method is a constructor method that is called automatically whenever a new object is created from a class. It sets the initial state of a new object.`
- [ ] The
__init__
method initializes any imports you may have included at the top of your file.`
Q47. What is meant by the phrase "space complexity"?
- [ ]
How many microprocessors it would take to run your code in less than one second
- [ ]
How many lines of code are in your code file
- [x]
The amount of space taken up in memory as a function of the input size
- [ ]
How many copies of the code file could fit in 1 GB of memory
Q48. What is the correct syntax for creating a variable that is bound to a dictionary?
- [x]
fruit_info = {'fruit': 'apple', 'count': 2, 'price': 3.5}
- [ ]
fruit_info =('fruit': 'apple', 'count': 2,'price': 3.5 ).dict()
- [ ]
fruit_info = ['fruit': 'apple', 'count': 2,'price': 3.5 ].dict()
- [ ]
fruit_info = to_dict('fruit': 'apple', 'count': 2, 'price': 3.5)
Q49. What is the proper way to write a list comprehension that represents all the keys in this dictionary?
fruits = {'Apples': 5, 'Oranges': 3, 'Bananas': 4}
- [ ] fruit_names = [x in fruits.keys() for x]
- [ ] fruit_names = for x in fruits.keys() *
- [✅] fruit_names = [x for x in fruits.keys()]
- [ ] fruit_names = x for x in fruits.keys()
Q50. What is the algorithmic paradigm of quick sort?
- [ ]
backtracking
- [x]
divide and conquer
- [ ]
dynamic programming
- [ ]
decrease and conquer
Q51. What is the purpose of the self
keyword when defining or calling methods on an instance of an object?
- [ ]
self
refers to the class that was inherited from to create the object using self
.
- [ ] There is no real purpose for the
self
method. It's just legacy computer science jargon that Python keeps to stay consistent with other programming languages.
- [ ]
self
means that no other arguments are required to be passed into the method.
- [x]
self
refers to the instance whose method was called.
Q52. What statement about a class methods is true?
- [ ] A class method is a regular function that belongs to a class, but it must return None.
- [x] A class method can modify the state of the class, but they can't directly modify the state of an instance that inherits from that class.
- [ ] A class method is similar to a regular function, but a class method doesn't take any arguments.
- [ ] A class method hold all of the data for a particular class.
Q53. What does it mean for a function to have linear runtime?
- [ ] You did not use very many advanced computer programming concepts in your code.
- [ ] The difficulty level your code is written at is not that high.
- [ ] It will take your program less than half a second to run.
- [x] The amount of time it takes the function to complete grows linearly as the input size increases.
Q54. What is the proper way to define a function?
- [ ]
def getMaxNum(list_of_nums): # body of function goes here
- [ ]
func get_max_num(list_of_nums): # body of function goes here
- [ ]
func getMaxNum(list_of_nums): # body of function goes here
- [x]
def get_max_num(list_of_nums): # body of function goes here
explanation
Q55. According to the PEP 8 coding style guidelines, how should constant values be named in Python?
- [ ] in camel case without using underscores to separate words – e.g.
maxValue = 255
- [ ] in lowercase with underscores to separate words – e.g.
max_value = 255
- [x] in all caps with underscores separating words – e.g.
MAX_VALUE = 255
- [ ] in mixed case without using underscores to separate words – e.g.
MaxValue = 255
Q56. Describe the functionality of a deque.
- [ ] A deque adds items to one side and remove items from the other side.
- [ ] A deque adds items to either or both sides, but only removes items from the top.
- [x] A deque adds items at either or both ends, and remove items at either or both ends.
- [ ] A deque adds items only to the top, but remove from either or both sides.
Q57. What is the correct syntax for creating a variable that is bound to a set?
- [x]
myset = {0, 'apple', 3.5}
- [ ]
myset = to_set(0, 'apple', 3.5)
- [ ]
myset = (0, 'apple', 3.5).to_set()
- [ ]
myset = (0, 'apple', 3.5).set()
Q58. What is the correct syntax for defining an __init__()
method that takes no parameters?
class __init__(self):
pass
def __init__():
pass
class __init__():
pass
def __init__(self):
pass
Q59. Which statement about the class methods is true?
- [ ] A class method holds all of the data for a particular class.
- [x] A class method can modify the state of the class, but it cannot directly modify the state of an instance that inherits from that class.
- [ ] A class method is a regular function that belongs to a class, but it must return
None
- [ ] A class method is similar to a regular function, but a class method does not take any arguments.
Q60. Which of the following is TRUE About how numeric data would be organised in a binary Search tree?
- [x] For any given Node in a binary Search Tree, the child node to the left is less than the value of the given node and the child node to its right is greater than the given node. (Not Sure)
- [ ] Binary Search Tree cannot be used to organize and search through numeric data, given the complication that arise with very deep trees.
- [ ] The top node of the binary search tree would be an arbitrary number. All the nodes to the left of the top node need to be less than the top node's number, but they don't need to ordered in any particular way.
- [ ] The smallest numeric value would go in the top most node. The next highest number would go in its left child node, the the next highest number after that would go in its right child node. This pattern would continue until all numeric values were in their own node.
Q61. Why would you use a decorator?
- [ ] A decorator is similar to a class and should be used if you are doing functional programming instead of object oriented programming.
- [ ] A decorator is a visual indicator to someone reading your code that a portion of your code is critical and should not be changed.
- [x] You use the decorator to alter the functionality of a function without the without having to modify the functions code.
- [ ] An import statement is preceded by a decorator, python knows to import the most recent version of whatever package or library is being imported.
Q62. When would you use a for loop ?
- [ ] Only in some situations, as loops are used ony for certain type of programming.
- [x] When you need to check every element in an iterable of known length.
- [ ] When you want to minimize the use of strings in your code.
- [ ] When you want to run code in one file for a function in another file.
Q63. What is the most self-descriptive way to define a function that calculates sales tax on a purchase?
def tax(my_float):
'''Calculates the sales tax of a purchase. Takes in a float representing the subtotal as an argument and returns a float representing the sales tax.'''
pass
def tx(amt):
'''Gets the tax on an amount.'''
def sales_tax(amount):
'''Calculates the sales tax of a purchase. Takes in a float representing the subtotal as an argument and returns a float representing the sales tax.'''
def calculate_sales_tax(subtotal):
pass
Q64. What would happen if you did not alter the state of the element that an algorithm is operating on recursively?
- [ ] You do not have to alter the state of the element the algorithm is recursing on.
- [ ] You would eventually get a KeyError when the recursive portion of the code ran out of items to recurse on.

- [ ] The function using recursion would return None.
Q65. What is the runtime complexity of searching for an item in a binary search tree?
- [ ] The runtime for searching in a binary search tree is O(1) because each node acts as a key, similar to a dictionary.
- [ ] The runtime for searching in a binary search tree is O(n!) because every node must be compared to every other node.
- [x] The runtime for searching in a binary search tree is generally O(h), where h is the height of the tree.
- [ ] The runtime for searching in a binary search tree is O(n) because every node in the tree must be visited.
Q66. Why would you use mixin
?
- [ ] You use a
mixin
to force a function to accept an argument at runtime even if the argument wasn't included in the function's definition.
- [ ] You use a
mixin
to allow a decorator to accept keyword arguments.
- [ ] You use a
mixin
to make sure that a class's attributes and methods don't interfere with global variables and functions.
- [x] If you have many classes that all need to have the same functionality, you'd use a
mixin
to define that functionality.
Q67. What is the runtime complexity of adding an item to a stack and removing an item from a stack?
- [ ] Add items to a stack in O(1) time and remove items from a stack on O(n) time.
- [x] Add items to a stack in O(1) time and remove items from a stack in O(1) time.
- [ ] Add items to a stack in O(n) time and remove items from a stack on O(1) time.
- [ ] Add items to a stack in O(n) time and remove items from a stack on O(n) time.
Q68. What does calling namedtuple on a collection type return?
- [x] a tuple subclass with iterable named fields
- [ ] a generic object class with non-iterable named fields
- [ ] a generic object class with iterable parameter fields
- [ ] a tuple subclass with non-iterable parameter fields
Q69. Which statement accurately describes how items are added to and remnoved from a stack?
- [ ] a stacks adds items to one side and removes items from the other side.
- [x] a stacks adds items to the top and removes items from the top.
- [ ] a stacks adds items to the top and removes items from anywhere in the stack.
- [ ] a stacks adds items to either end and removes items from either end.
Q70. What is a base case in a recursive function?
- [x] A base case is the condition that allows the algorithm to stop recursing. It is usually a problem that is small enough to solve directly.
- [ ] The base case is summary of the overall problem that needs to be solved.
- [ ] The base case is passed in as an argument to a function whose body makes use of recursion.
- [ ] The base case is similar to a base class, in that it can be inherited by another object.
Q71. Why is it considered good practice to open a file from within a Python script by using the with
keyword?
- [ ] The
with
keyword lets you choose which application to open the file in.
- [ ] The
with
keyword acts like a for
loop, and lets you access each line in the file one by one.
- [ ] There is no benefit to using the
with
keyword for opening a file in Python.
- [x] When you open a file using the
with
keyword in Python, Python will make sure the file gets closed, even if an exception or error is thrown.
Q72. Why would you use a virtual environment?

- [ ] Teams with remote employees use virtual environments so they can share code, do code reviews, and collaorate remotely.
- [ ] Virtual environments were common in Python 2 because they augmented missing features in the language. Virtual environments are not necessary in Python 3 due to advancements in the language.
- [ ] Virtual environments are tied to your GitHub or Bitbucket account, allowing you to access any of your repos virtually from any machine.
Q73. What is the correct way to run all the doctests in a given file from the command line?
- [ ] python3 -m doctest
- [x] python3
- [ ] python3 rundoctests
- [ ] python3 doctest
Q74. What is a lambda function ?
- [ ] any function that makes use of scientific or mathematical constants, often represented by Greek letters in academic writing
- [ ] a function that get executed when decorators are used
- [ ] any function whose definition is contained within five lines of code or fewer
- [x] a small, anonymous function that can take any number of arguments but has only expression to evaluate
Reference


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pymatgen.io.abinit.works module¶
Works for Abinit
-
class
Work
(workdir=None, manager=None)[source]¶ Bases:
pymatgen.io.abinit.works.BaseWork
,pymatgen.io.abinit.works.NodeContainer
A Work is a list of (possibly connected) tasks.
Parameters: - workdir – Path to the working directory.
- manager –
TaskManager
object.
-
allocate
(manager=None)[source]¶ This function is called once we have completed the initialization of the
Work
. It sets the manager of each task (if not already done) and defines the working directories of the tasks.Parameters: manager – TaskManager
object or None
-
get_all_status
(only_min=False)[source]¶ Returns a list with the status of the tasks in self.
Parameters: only_min – If True, the minimum of the status is returned.
-
isnc
¶ True if norm-conserving calculation.
-
ispaw
¶ True if PAW calculation.
-
move
(dest, isabspath=False)[source]¶ Recursively move self.workdir to another location. This is similar to the Unix “mv” command. The destination path must not already exist. If the destination already exists but is not a directory, it may be overwritten depending on os.rename() semantics.
Be default, dest is located in the parent directory of self.workdir, use isabspath=True to specify an absolute path.
-
opath_from_ext
(ext)[source]¶ Returns the path of the output file with extension ext. Use it when the file does not exist yet.
-
parse_timers
()[source]¶ Parse the TIMER section reported in the ABINIT output files.
Returns: AbinitTimerParser
object
-
pos_str
¶ String representation of self.pos
-
processes
¶ Return a list of objects that support the subprocess.Popen protocol.
-
read_etotals
(unit='Ha')[source]¶ Reads the total energy from the GSR file produced by the task.
Return a numpy array with the total energies in Hartree The array element is set to np.inf if an exception is raised while reading the GSR file.
-
register
(obj, deps=None, required_files=None, manager=None, task_class=None)[source]¶ Registers a new
Task
and add it to the internal list, taking into account possible dependencies.Parameters: - obj –
AbinitInput
instance or Task object. - deps – Dictionary specifying the dependency of this node or list of dependencies None means that this obj has no dependency.
- required_files – List of strings with the path of the files used by the task. Note that the files must exist when the task is registered. Use the standard approach based on Works, Tasks and deps if the files will be produced in the future.
- manager – The
TaskManager
responsible for the submission of the task. If manager is None, we use the TaskManager specified during the creation of theWork
. - task_class – Task subclass to instantiate. Default:
AbinitTask
Returns: Task
object- obj –
-
register_task
(obj, deps=None, required_files=None, manager=None, task_class=None)¶ Registers a new
Task
and add it to the internal list, taking into account possible dependencies.Parameters: - obj –
AbinitInput
instance or Task object. - deps – Dictionary specifying the dependency of this node or list of dependencies None means that this obj has no dependency.
- required_files – List of strings with the path of the files used by the task. Note that the files must exist when the task is registered. Use the standard approach based on Works, Tasks and deps if the files will be produced in the future.
- manager – The
TaskManager
responsible for the submission of the task. If manager is None, we use the TaskManager specified during the creation of theWork
. - task_class – Task subclass to instantiate. Default:
AbinitTask
Returns: Task
object- obj –
-
rmtree
(exclude_wildcard='')[source]¶ Remove all files and directories in the working directory
Parameters: exclude_wildcard – Optional string with regular expressions separated by |. Files matching one of the regular expressions will be preserved. example: exclude_wildard=”.nc|.txt” preserves all the files whose extension is in [“nc”, “txt”].
-
set_workdir
(workdir, chroot=False)[source]¶ Set the working directory. Cannot be set more than once unless chroot is True
-
setup
(*args, **kwargs)[source]¶ Method called before running the calculations. The default implementation is empty.
-
start
(*args, **kwargs)[source]¶ Start the work. Calls build and _setup first, then submit the tasks. Non-blocking call unless wait is set to True
-
status
¶ Returns the status of the work i.e. the minimum of the status of the tasks.
-
status_counter
¶ Returns a Counter object that counts the number of task with given status (use the string representation of the status as key).
-
class
BandStructureWork
(scf_input, nscf_input, dos_inputs=None, workdir=None, manager=None)[source]¶ Bases:
pymatgen.io.abinit.works.Work
Work for band structure calculations.
Parameters: - scf_input – Input for the SCF run
- nscf_input – Input for the NSCF run defining the band structure calculation.
- dos_inputs – Input(s) for the DOS. DOS is computed only if dos_inputs is not None.
- workdir – Working directory.
- manager –
TaskManager
object.
-
plot_ebands
(**kwargs)[source]¶ Plot the band structure. kwargs are passed to the plot method of
ElectronBands
.Returns: matplotlib figure
-
plot_ebands_with_edos
(dos_pos=0, method='gaussian', step=0.01, width=0.1, **kwargs)[source]¶ Plot the band structure and the DOS.
Parameters: - dos_pos – Index of the task from which the DOS should be obtained (note: 0 refers to the first DOS task).
- method – String defining the method for the computation of the DOS.
- step – Energy step (eV) of the linear mesh.
- width – Standard deviation (eV) of the gaussian.
- kwargs – Keyword arguments passed to plot_with_edos method to customize the plot.
Returns: matplotlib figure.
-
plot_edoses
(dos_pos=None, method='gaussian', step=0.01, width=0.1, **kwargs)[source]¶ Plot the band structure and the DOS.
Parameters: - dos_pos – Index of the task from which the DOS should be obtained. None is all DOSes should be displayed. Accepts integer or list of integers.
- method – String defining the method for the computation of the DOS.
- step – Energy step (eV) of the linear mesh.
- width – Standard deviation (eV) of the gaussian.
- kwargs – Keyword arguments passed to plot method to customize the plot.
Returns: matplotlib figure.
-
class
RelaxWork
(ion_input, ioncell_input, workdir=None, manager=None, target_dilatmx=None)[source]¶ Bases:
pymatgen.io.abinit.works.Work
Work for structural relaxations. The first task relaxes the atomic position while keeping the unit cell parameters fixed. The second task uses the final structure to perform a structural relaxation in which both the atomic positions and the lattice parameters are optimized.
Parameters: - ion_input – Input for the relaxation of the ions (cell is fixed)
- ioncell_input – Input for the relaxation of the ions and the unit cell.
- workdir – Working directory.
- manager –
TaskManager
object.
-
on_ok
(sender)[source]¶ This callback is called when one task reaches status S_OK. If sender == self.ion_task, we update the initial structure used by self.ioncell_task and we unlock it so that the job can be submitted.
-
class
G0W0Work
(scf_inputs, nscf_inputs, scr_inputs, sigma_inputs, workdir=None, manager=None)[source]¶ Bases:
pymatgen.io.abinit.works.Work
Work for general G0W0 calculations. All input can be either single inputs or lists of inputs
Parameters: - scf_inputs – Input(s) for the SCF run, if it is a list add all but only link to the last input (used for convergence studies on the KS band gap)
- nscf_inputs – Input(s) for the NSCF run, if it is a list add all but only link to the last (i.e. addditiona DOS and BANDS)
- scr_inputs – Input for the screening run
- sigma_inputs – List of :class:AbinitInput`for the self-energy run. if scr and sigma are lists of the same length, every sigma gets its own screening. if there is only one screening all sigma inputs are linked to this one
- workdir – Working directory of the calculation.
- manager –
TaskManager
object.
-
class
QptdmWork
(workdir=None, manager=None)[source]¶ Bases:
pymatgen.io.abinit.works.Work
This work parallelizes the calculation of the q-points of the screening. It also provides the callback on_all_ok that calls mrgscr to merge all the partial screening files produced.
Parameters: - workdir – Path to the working directory.
- manager –
TaskManager
object.
-
create_tasks
(wfk_file, scr_input)[source]¶ Create the SCR tasks and register them in self.
Parameters: - wfk_file – Path to the ABINIT WFK file to use for the computation of the screening.
- scr_input – Input for the screening calculation.
-
class
SigmaConvWork
(wfk_node, scr_node, sigma_inputs, workdir=None, manager=None)[source]¶ Bases:
pymatgen.io.abinit.works.Work
Work for self-energy convergence studies.
Parameters: - wfk_node – The node who has produced the WFK file or filepath pointing to the WFK file.
- scr_node – The node who has produced the SCR file or filepath pointing to the SCR file.
- sigma_inputs – List of
AbinitInput
for the self-energy runs. - workdir – Working directory of the calculation.
- manager –
TaskManager
object.
-
class
BseMdfWork
(scf_input, nscf_input, bse_inputs, workdir=None, manager=None)[source]¶ Bases:
pymatgen.io.abinit.works.Work
Work for simple BSE calculations in which the self-energy corrections are approximated by the scissors operator and the screening is modeled with the model dielectric function.
Parameters: - scf_input – Input for the SCF run.
- nscf_input – Input for the NSCF run.
- bse_inputs – List of Inputs for the BSE run.
- workdir – Working directory of the calculation.
- manager –
TaskManager
.
-
class
PhononWork
(workdir=None, manager=None)[source]¶ Bases:
pymatgen.io.abinit.works.Work
,pymatgen.io.abinit.works.MergeDdb
This work consists of nirred Phonon tasks where nirred is the number of irreducible atomic perturbations for a given set of q-points. It provides the callback method (on_all_ok) that calls mrgddb (mrgdv) to merge all the partial DDB (POT) files produced. The two files are available in the output directory of the Work.
Parameters: - workdir – Path to the working directory.
- manager –
TaskManager
object.
-
classmethod
from_scf_input
(scf_input, qpoints, is_ngqpt=False, tolerance=None, with_becs=False, ddk_tolerance=None, manager=None)[source]¶ Similar to from_scf_task, the difference is that this method requires an input for SCF calculation. A new ScfTask is created and added to the Work. This API should be used if the DDB of the GS task should be merged.
-
classmethod
from_scf_task
(scf_task, qpoints, is_ngqpt=False, tolerance=None, with_becs=False, ddk_tolerance=None, manager=None)[source]¶ Construct a PhononWork from a
ScfTask
object. The input file for phonons is automatically generated from the input of the ScfTask. Each phonon task depends on the WFK file produced by the scf_task.Parameters: - scf_task – ScfTask object.
- qpoints – q-points in reduced coordinates. Accepts single q-point, list of q-points or three integers defining the q-mesh if is_ngqpt.
- is_ngqpt – True if qpoints should be interpreted as divisions instead of q-points.
- tolerance – dict {“varname”: value} with the tolerance to be used in the phonon run. None to use AbiPy default.
- with_becs – Activate calculation of Electric field and Born effective charges.
- ddk_tolerance – dict {“varname”: value} with the tolerance used in the DDK run if with_becs. None to use AbiPy default.
- manager –
TaskManager
object.
-
class
PhononWfkqWork
(workdir=None, manager=None)[source]¶ Bases:
pymatgen.io.abinit.works.Work
,pymatgen.io.abinit.works.MergeDdb
This work computes phonons with DFPT on an arbitrary q-mesh (usually denser than the k-mesh for electrons) by computing WKQ files for each q-point. The number of irreducible atomic perturbations for each q-point are taken into account. It provides the callback method (on_all_ok) that calls mrgddb (mrgdv) to merge all the partial DDB (POT) files produced. The two files are available in the output directory of the Work. The WKQ files are removed at runtime.
Parameters: - workdir – Path to the working directory.
- manager –
TaskManager
object.
-
classmethod
from_scf_task
(scf_task, ngqpt, ph_tolerance=None, tolwfr=1e-22, nband=None, with_becs=False, ddk_tolerance=None, shiftq=(0, 0, 0), is_ngqpt=True, remove_wfkq=True, manager=None)[source]¶ Construct a PhononWfkqWork from a
ScfTask
object. The input files for WFQ and phonons are automatically generated from the input of the ScfTask. Each phonon task depends on the WFK file produced by scf_task and the associated WFQ file.Parameters: - scf_task – ScfTask object.
- ngqpt – three integers defining the q-mesh
- with_becs – Activate calculation of Electric field and Born effective charges.
- ph_tolerance – dict {“varname”: value} with the tolerance for the phonon run. None to use AbiPy default.
- tolwfr – tolerance used to compute WFQ.
- ddk_tolerance – dict {“varname”: value} with the tolerance used in the DDK run if with_becs. None to use AbiPy default.
- shiftq – Q-mesh shift. Multiple shifts are not supported.
- is_ngqpt – the ngqpt is interpreted as a set of integers defining the q-mesh, otherwise is an explicit list of q-points
- remove_wfkq – Remove WKQ files when the children are completed.
- manager –
TaskManager
object.
-
class
GKKPWork
(workdir=None, manager=None)[source]¶ Bases:
pymatgen.io.abinit.works.Work
This work computes electron-phonon matrix elements for all the q-points present in a DVDB and DDB file
Parameters: - workdir – Path to the working directory.
- manager –
TaskManager
object.
-
classmethod
from_den_ddb_dvdb
(inp, den_path, ddb_path, dvdb_path, mpiprocs=1, remove_wfkq=True, qpath=None, with_ddk=True, expand=True, manager=None)[source]¶ Construct a PhononWfkqWork from a DDB and DVDB file. For each q found, a WFQ task and an EPH task computing the matrix elements are created.
-
class
BecWork
(workdir=None, manager=None)[source]¶ Bases:
pymatgen.io.abinit.works.Work
,pymatgen.io.abinit.works.MergeDdb
Work for the computation of the Born effective charges.
This work consists of DDK tasks and phonon + electric field perturbation It provides the callback method (on_all_ok) that calls mrgddb to merge the partial DDB files produced by the work.
Parameters: - workdir – Path to the working directory.
- manager –
TaskManager
object.
-
classmethod
from_scf_task
(scf_task, ddk_tolerance=None, ph_tolerance=None, manager=None)[source]¶ Build tasks for the computation of Born effective charges from a ground-state task.
Parameters: - scf_task – ScfTask object.
- ddk_tolerance – tolerance used in the DDK run if with_becs. None to use AbiPy default.
- ph_tolerance – dict {“varname”: value} with the tolerance used in the phonon run. None to use AbiPy default.
- manager –
TaskManager
object.
-
class
DteWork
(workdir=None, manager=None)[source]¶ Bases:
pymatgen.io.abinit.works.Work
,pymatgen.io.abinit.works.MergeDdb
Work for the computation of the third derivative of the energy.
This work consists of DDK tasks and electric field perturbation. It provides the callback method (on_all_ok) that calls mrgddb to merge the partial DDB files produced
Parameters: - workdir – Path to the working directory.
- manager –
TaskManager
object.


2 Samuel 17:21
And it came to pass, after they were departed, that they came up out of the well, and went and told king David, and said unto David, Arise, and pass quickly over the water: for thus hath Ahithophel counseled against you.


|
| Local Properties | ||
| Managed Object Types | Data Object Types | All Properties | All Methods |
Properties
| Name | Type | Description |
|---|---|---|
| eula* | xsd:string[] |
End User Liceses Agreements.
|
| installBootRequired | xsd:boolean |
Specifies whether the VM needs an initial boot before the deployment is complete.
Not relevant for vApps. This means that the value is always false when reading the configuration and is ignored when setting the configuration.
If a vApp requires an install boot (because one of its VMs does), this is visible
on the installBootRequired field of the vApp.
|
| installBootStopDelay | xsd:int |
Specifies the delay in seconds to wait for the VM to power off after the initial
boot (used only if installBootRequired is true). A value of 0 means wait forever.
Not relevant for vApps. This means that the value is always false when reading the
configuration and is ignored when setting the configuration.
|
| ipAssignment | VAppIPAssignmentInfo |
IP assignment policy and DHCP support configuration.
|
| ovfEnvironmentTransport* | xsd:string[] |
List the transports to use for properties. Supported values are: iso and
com.vmware.guestInfo.
|
| ovfSection* | VAppOvfSectionInfo[] |
List of uninterpreted OVF meta-data sections.
|
| product* | VAppProductInfo[] |
Information about the package content.
|
| property* | VAppPropertyInfo[] |
List of properties
|
| Properties inherited from DynamicData | ||
| None |
| Top of page | Local Properties | ||
| Managed Object Types | Data Object Types | All Properties | All Methods |


Windows Forms Programming in C# Sample Chapter
Here. AW has been kind enough to post the preface and a sample chapter (Chapter 9: Design-Time Integration) to the official AW Windows Forms Programming in C# book page. They've also posted Mike Blaszczak's foreword. Enjoy.


If you are ready to put in some hard work to improve your Business English, please contact me.
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Some more attacks are Man In The Middle(MITM) , Msfvenom , etc
Man In The Middle(MITM):
In cryptography and computer security, a man-in-the-middle attack (MITM; also Janus attack) is an attack where the attacker secretly
relays and possibly alters the communication between two parties who believe they are directly communicating with each other.
One example of man-in-the-middle attacks is active eavesdropping, in which the attacker makes independent connections with the victims
and relays messages between them to make them believe they are talking directly to each other over a private connection, when in fact the
entire conversation is controlled by the attacker. The attacker must be able to intercept all relevant messages passing between the two victims
and inject new ones. This is straightforward in many circumstances; for example, an attacker within reception range of an unencrypted wireless
access point (Wi-Fi) could insert himself as a man-in-the-middle.
As an attack that aims at circumventing
mutual authentication, or lack thereof, a man-in-the-middle attack can succeed only when the attacker can impersonate each endpoint to their satisfaction
as expected from the legitimate ends. Most cryptographic protocols include some form of endpoint authentication specifically to prevent MITM attacks.
For example, TLS can authenticate one or both parties using a mutually trusted certificate authority.
Msfvenom
The Metasploit Framework has included the useful tools msfpayload and msfencode for quite sometime. These tools are extremely useful
for generating payloads in various formats and encoding these payloads using various encoder modules. Now I would like to introduce a new tool
which I have been working on for the past week, msfvenom. This tool combines all the functionality of msfpayload and msfencode in a single tool.
Merging these two tools into a single tool just made sense. It standardizes the command line options, speeds things up a bit by using a single framework
instance, handles all possible output formats, and brings some sanity to payload generation.
what is Kali Linux:
Kali Linux is a Debian-based Linux distribution aimed at advanced Penetration Testing and Security Auditing. Kali contains several hundred tools which are geared
towards various information security tasks, such as Penetration Testing, Security research, Computer Forensics and Reverse Engineering. Kali Linux is developed,
funded and maintained by Offensive Security, a leading information security training company.
Kali Linux was released on the 13th March, 2013 as a complete, top-to-bottom rebuild of BackTrack Linux, adhering completely to Debian development standards.
More than 600 penetration testing tools included: After reviewing every tool that was included in BackTrack, we eliminated a great number
of tools that either simply did not work or which duplicated other tools that provided the same or similar functionality.
Details on whatís included are on the Kali Tools site.
Free (as in beer) and always will be: Kali Linux, like BackTrack, is completely free of charge and always will be.
You will never, ever have to pay for Kali Linux.
Open source Git tree: We are committed to the open source development model and our development tree is available for all to see.
All of the source code which goes into Kali Linux is available for anyone who wants to tweak or rebuild packages to suit their specific needs.
FHS compliant: Kali adheres to the Filesystem Hierarchy Standard, allowing Linux users to easily locate binaries, support files, libraries, etc.
Wide-ranging wireless device support: A regular sticking point with Linux distributions has been supported for wireless interfaces.
We have built Kali Linux to support as many wireless devices as we possibly can, allowing it to run properly on a wide variety of hardware
and making it compatible with numerous USB and other wireless devices.
Custom kernel, patched for injection: As penetration testers, the development team often needs to do wireless assessments,
so our kernel has the latest injection patches included.

GPG signed packages and repositories: Every package in Kali Linux is signed by each individual developer who built and committed it,
and the repositories subsequently sign the packages as well.
Multi-language support: Although penetration tools tend to be written in English, we have ensured that Kali includes true
multilingual support, allowing more users to operate in their native language and locate the tools they need for the job.
Completely customizable: We thoroughly understand that not everyone will agree with our design decisions, so we have made
it as easy as possible for our more adventurous users to customize Kali Linux to their liking, all the way down to the kernel.
ARMEL and ARMHF support: Since ARM-based single-board systems like the Raspberry Pi and BeagleBone Black, among others, are becoming
more and more prevalent and inexpensive, we knew that Kaliís ARM support would need to be as robust as we could manage,
with fully working installations for both ARMEL and ARMHF systems. Kali Linux is available on a wide range of ARM devices and has ARM repositories
integrated with the mainline distribution so tools for ARM are updated in conjunction with the rest of the distribution.
Kali Linux is specifically tailored to the needs of penetration testing professionals, and therefore all documentation on this site assumes prior knowledge of,
and familiarity with, the Linux operating system in general. Please see Should I Use Kali Linux? for more details on what makes Kali unique.


{% extends "layout.html" %} {% block page_title %} Apply for European Structural and Investment Funding {% endblock %} {% block content %} {% include "includes/phase_banner_alpha.html" %} About your project Financial information {% include 'includes/page_errors.html' %} Step 5 : Financial information How will ESIF payments be managed and authorised? Please give the name and contact details for the individual who will: request funds from ESIF check funds have been received transfer funds How will the project's cashflow be managed? How will you make sure that employees/volunteers: have access to money when they need it? know who to request money from and when to request it? don’t experience delays with getting money? don't overspend? How will you ensure only eligible and defrayed expenditure is included in claims? Eligible (defrayed) costs are any that have been incurred as part of the programme. Where you have paid for activity, goods or suppliers as part of the programme, you can invoice for these costs to be refunded. How will costs be checked and verified? Do you have a process to check expenses, for example: receipts upper limit on weekly/monthly expenses more than one signature to approve expenses budget for expenses what is the process if an expensed item exceeds the amount budgeted for it How will you and your partners report on ESIF expenditure? Will you meet regularly to look at how much of the budget has been spent? If yes: what milestones do you compare to check that the project is making progress? how often do you meet? who attends those meetings and do they have the authority to make changes if there is a problem? what happens if you miss a milestone? Save and continue Save and quit {% include "includes/application_info.html" %} {% include "includes/secondary_nav.html" %} {% endblock %}
Please give the name and contact details for the individual who will:
How will you make sure that employees/volunteers:
Eligible (defrayed) costs are any that have been incurred as part of the programme. Where you have paid for activity, goods or suppliers as part of the programme, you can invoice for these costs to be refunded.
Do you have a process to check expenses, for example:


--- layout: post title: "Windows 10 to soon run mobile apps built for Android" subtitle: "Project Latte that would allow app developers to bring their Android apps directly to Windows 10." date: 2020-11-30 17:30:13 +0530 background: '/img/posts/06.jpg' published: true categories: [ Technology ] tags: [ technology, android, microsoft, aps, desktops, laptops ] ---
Microsoft is working on a project named Latte that would allow app developers to bring their Android apps directly to Windows 10 with little to zero changes in the codes.
The developers will need to package their Android apps as MSIX format and submit those to the Microsoft Store, reports Windows Central.
MSIX is a Windows app package format that provides a modern packaging experience to all Windows apps.
Currently, users can run Android apps on their PCs via app streaming using the ‘Your Phone' app built into Windows 10.
Project Latte will allow app developers to bring apps to Windows 10 that don't have a Windows version available. Project Latte, however, may not support Play Services as Google doesn't allow Play Services to be installed on anything other than native Android devices and Chrome OS.
This means that apps which require Play Services APIs will need to be updated to remove those dependencies before they can be submitted on Windows 10. Earlier, Microsoft tried the same with a similar project codenamed Astoria which did not see the light of the day.


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Hello! My name is Jennifer and I am rising junior at Yale University studying computer science. I am a proud member of Trumbull College at Yale. On campus, I am involved with the Yale Undergraduate Prison Project as a GED tutor for justice-impacted individuals. My main programming language is C, but I have also worked with Python, SQL, and a little JavaScript. I have worked with HTML/CSS for a while, both on their own and within the React framework.
I am originally from San Bernardino, California, which is where I am currently located. I love spending time outdoors, whether just in my own yard, a nearby park, or some other nearby attraction. Being located in the Inland Empire means I have mountains, the beach, and the desert all within my reach, which I am very grateful for!
In my free time, I like to go on walks, do yoga, rewatch my favorite shows, and listen to music. I also like to paint (I'm bad at it) and play guitar, though I don't do it as much as I would like to. During quarantine I got into skateboarding a little bit and I would like to continue during the summer. :)
Click here to learn a random fact about me:
Click here to get a song recommendation:


Apache Flink 0.8.0 available
January 21, 2015 -We are pleased to announce the availability of Flink 0.8.0. This release includes new user-facing features as well as performance and bug fixes, extends the support for filesystems and introduces the Scala API and flexible windowing semantics for Flink Streaming.
Overview of major new features #
-
Extended filesystem support: The former
DistributedFileSystem
interface has been generalized toHadoopFileSystem
now supporting all sub classes oforg.apache.hadoop.fs.FileSystem
. This allows users to use all file systems supported by Hadoop with Apache Flink. See connecting to other systems -
Streaming Scala API: As an alternative to the existing Java API Streaming is now also programmable in Scala. The Java and Scala APIs have now the same syntax and transformations and will be kept from now on in sync in every future release.
-
Streaming windowing semantics: The new windowing api offers an expressive way to define custom logic for triggering the execution of a stream window and removing elements. The new features include out-of-the-box support for windows based in logical or physical time and data-driven properties on the events themselves among others. Read more here
-
Mutable and immutable objects in runtime All Flink versions before 0.8.0 were always passing the same objects to functions written by users. This is a common performance optimization, also used in other systems such as Hadoop. However, this is error-prone for new users because one has to carefully check that references to the object aren’t kept in the user function. Starting from 0.8.0, Flink allows to configure a mode which is disabling that mechanism.
-
Performance and usability improvements: The new Apache Flink 0.8.0 release brings several new features which will significantly improve the performance and the usability of the system. Amongst others, these features include:
- Improved input split assignment which maximizes computation locality
- Smart broadcasting mechanism which minimizes network I/O
- Custom partitioners which let the user control how the data is partitioned within the cluster. This helps to prevent data skewness and allows to implement highly efficient algorithms.
- coGroup operator now supports group sorting for its inputs
-
Kryo is the new fallback serializer: Apache Flink has a sophisticated type analysis and serialization framework that is able to handle commonly used types very efficiently. In addition to that, there is a fallback serializer for types which are not supported. Older versions of Flink used the reflective Avro serializer for that purpose. With this release, Flink is using the powerful Kryo and twitter-chill library for support of types such as Java Collections and Scala specifc types.
-
Hadoop 2.2.0+ is now the default Hadoop dependency: With Flink 0.8.0 we made the “hadoop2” build profile the default build for Flink. This means that all users using Hadoop 1 (0.2X or 1.2.X versions) have to specify version “0.8.0-hadoop1” in their pom files.
-
HBase module updated The HBase version has been updated to <IP_ADDRESS>. Also, Hbase is now available to the Hadoop1 and Hadoop2 profile of Flink.
Contributors #
- Marton Balassi
- Daniel Bali
- Carsten Brandt
- Moritz Borgmann
- Stefan Bunk
- Paris Carbone
- Ufuk Celebi
- Nils Engelbach
- Stephan Ewen
- Gyula Fora
- Gabor Hermann
- Fabian Hueske
- Vasiliki Kalavri
- Johannes Kirschnick
- Aljoscha Krettek
- Suneel Marthi
- Robert Metzger
- Felix Neutatz
- Chiwan Park
- Flavio Pompermaier
- Mingliang Qi
- Shiva Teja Reddy
- Till Rohrmann
- Henry Saputra
- Kousuke Saruta
- Chesney Schepler
- Erich Schubert
- Peter Szabo
- Jonas Traub
- Kostas Tzoumas
- Timo Walther
- Daniel Warneke
- Chen Xu


QuickFIX also has a scriptable test runner that comes with a series of automated acceptance test. The basic tests that come with QuickFIX are based off of the FIX Session-level Test Cases and Expected Behaviors document produced by the FIX protocol organization. These tests verify that QuickFIX adheres to the FIX specifications. The automated nature of these tests guarantees that future releases of QuickFIX will not break any current functionality.
Perhaps even more importantly is how these test are used to drive the development of QuickFIX. Before a line of code is written in support of a protocol feature, one of these tests is written. This test first approach sets up a goal for developers who will have objective verification that they correctly implemented the standard.
Below is an example of a test script that tests the engines behavior when it receives a NewSeqNo value that is less than the expected MsgSeqNum.
iCONNECT I8=FIX.4.235=A34=149=TW52=>TIME>56=ISLD98=0108=30 E8=FIX.4.29=5735=A34=149=ISLD52=00000000-00:00:0056=TW98=0108=3010=0 # sequence reset without gap fill flag (default to N) I8=FIX.4.235=434=049=TW52=>TIME>56=ISLD36=1 E8=FIX.4.29=11235=334=249=ISLD52=00000000-00:00:0056=TW45=058=Value is incorrect (out of range) for this tag372=4373=510=0 I8=FIX.4.235=134=249=TW52=>TIME>56=ISLD112=HELLO E8=FIX.4.29=5535=034=349=ISLD52=00000000-00:00:0056=TW112=HELLO10=0 # sequence reset without gap fill flag (default to N) I8=FIX.4.235=434=049=TW52=>TIME>56=ISLD36=1123=N E8=FIX.4.29=11235=334=449=ISLD52=00000000-00:00:0056=TW45=058=Value is incorrect (out of range) for this tag372=4373=510=0 I8=FIX.4.235=134=349=TW52=>TIME>56=ISLD112=HELLO E8=FIX.4.29=5535=034=549=ISLD52=00000000-00:00:0056=TW112=HELLO10=0 iDISCONNECTIn these script there are two types of commands, action commands and messages commands. Action commands begin with lowercase letters while message command begin with uppercase letters.
When using the I command, you do not need to add the Length(9) or the CheckSum(10) fields, they will be added for you with the correct values in the appropriate locations. The only time you would add these fields is if you intentionally wish to make them incorrect.
The I command also provides a TIME macro for fields. By setting a field equal to <TIME>, the current system time will be placed in the field. (i.e. 52=>TIME>). You can also use offsets such as 52=<TIME-120> or 52=<TIME+15> in order to set the time plus or minus some seconds from the current time.
The E command verifies that you have received the correct message. This command will compare the values of each field to make sure they are correct. Some fields cannot be verified deterministically before run-time such as the SendingTime and CheckSum fields. These fields can be added to the fields.fmt file where a regular expression can be defined to at least verify the field is in the correct format. For example:
10=\d{3}, checksum must be exactly three digitsEither command can contain a FILE macro which puts the contents of a file into a field (i.e. 58=<FILE:test.txt>)


Gradient sets prices individually based on how much you can afford.
Gradient only scales prices downwards. No matter how much you earn, your prices will never increase.
Gradient is a community dedicated to making the world a fairer and more equitable place.


(Sorry, still working on the submission form.)
{% elif option == "theorem" %}
Suggest a theorem we should add
(form for collecting property.)
(Sorry, still working on the submission form.)
{% elif option == "citation" %}
Suggest a citation
(form for collecting citations.)
(Sorry, still working on the submission form.)
{% elif option == "randring" %}
The database says we could fill these gaps:
{{ ring_sugg }}
{{ cring_sugg }}
(There may be some latency between when these gaps get filled and these suggestions are made!)
{% elif option == "randcite" %}
Get a randomly generated citation that needs improvement.
{% elif option == "property" %}
Suggest a new property
(form for collecting property.)
(Sorry, still working on the submission form.)
{% else %}
Something is wrong.
{% endif %}
{% endblock %}