A channel to discuss trading. For useful links and more info click the pinned messages to the right.
100 messages
Before 05-Dec-19 12:00 AM
Hollowman900022-Mar-19 11:22 PM
We centralize your decentralized project so you can get your decentralization on while you’re KYC’d and centralized(edited)
3
./xzibit
Or something
jspook1622-Mar-19 11:26 PM
./wtf.py
Sounds like a Kansas City shuffle
Hollowman900022-Mar-19 11:31 PM
A 2 at 10 is a 10 at 2
A 10 at 2 is you have herpes
2
I have no idea what a Kansas City shuffle is
jspook1622-Mar-19 11:33 PM
Kansas City Shuffle = IEO from the sounds of it
So what is a 2 at 10?
FishyGuts23-Mar-19 12:28 AM
Think beers and bars.
It will come to you faster than a 2 looking like a 10 at 2 AM
Hollowman900023-Mar-19 12:38 AM
Speaks the truth he does
Unibrow to unicorn in 4 short ethanol-fueled hours
74D3023-Mar-19 12:58 AM
Yes basically we are waking up at 12 noon
jspook1623-Mar-19 01:56 AM
Waking up at noon with 10s. I like it
dukeleto23-Mar-19 04:10 AM
this channel gets pretty weird, but I like it
Alecandro23-Mar-19 04:38 AM
How’s everyone feeling about KMD? Getting really close to trendline!
74D3023-Mar-19 04:43 AM
It will have a market cap of more than 125 mil within the next week
Sdunbar23-Mar-19 05:05 AM
chillin so hard
its just chillin
Cryptoon23-Mar-19 01:37 PM
Zzzzzz the market is so boring
5
Hollowman900023-Mar-19 02:44 PM
Tended the smoker until 0430
also maybe imbibed
Head hurts
Let’s dump the market
CoinKing8823-Mar-19 05:53 PM
Its like some bot(s) are ping pong trading between 26000 and 26600
Sdunbar23-Mar-19 05:57 PM
the lack of volatility in the market as a whole these days blows my mind
Cryptoon23-Mar-19 06:04 PM
everyone waiting for the big move to happen
meanwhile staying on the sidelines
LocoMB23-Mar-19 06:26 PM
calm before the storm... time dilation effects included so that everyone gets what they paid for and noone can complain!
(edited)
LocoMB23-Mar-19 06:33 PM
just remember 2014/15/16 everybody- and hope it won't last until '21.. I don't think so, I think the dough has been fermenting diligently already and is ready to blow(edited)
siu - Chainmakers23-Mar-19 06:42 PM
We sre getting near spring break time
So we might be low in volatility until later in april
ComputerGenie 👴👴👴23-Mar-19 06:44 PM
the dumpening is nigh
Sdunbar23-Mar-19 06:48 PM
Its already spring break here in canada
half over
jspook1623-Mar-19 08:34 PM
Spring done broke, all the 10s are gone, 2s are left, but Komodo tech keeps trucking on.
74D3024-Mar-19 12:09 AM
Well i guess others have better things to do than do crypto stuff on Saturday nights. What losers
Hollowman900024-Mar-19 12:47 AM
Totally
74D3024-Mar-19 06:09 AM
Just paid my bitpay invoice for more pirate booty. It feels sooo good!!!
1
CoinKing8824-Mar-19 12:45 PM
Anyone willing to sell me some DEX OTC? Your 2 DEX for my 50 KMD. Willing to sent first if buyer is respectable in here.
jorian24-Mar-19 12:53 PM
@CoinKing88 you should buy from coinexchange, the 2 DEX there are cheaper than the 50KMD you're offering
CoinKing8824-Mar-19 12:54 PM
Coinexchange -> KMD -> BTC -> is about that expensive
low volume with kmd/btc, dont have btc
chmex allready helped me out
thx
jorian24-Mar-19 12:55 PM
Caglio24-Mar-19 02:46 PM
Should I put 100-200$ more into KMD ?
Or should I buy some booze instead
Hm
MyName24-Mar-19 02:47 PM
mortgage the house and go all-in
Caglio24-Mar-19 02:51 PM
I live in a tent
MyName24-Mar-19 02:53 PM
then
e) none of the above
actionslacks24-Mar-19 02:55 PM
Find a tent spot with a better view, then buy more kmd
MyName24-Mar-19 02:55 PM
Get a haircut and get a real job
Caglio24-Mar-19 03:04 PM
Finally its not bad to live in a tent
Winter is over
Its been hard last few months
I was like "LAMBO LAMBO" in 2017, then I had to spend a last 3 quarters of 2018 in a tent
BoBot-BUY KMD24-Mar-19 03:59 PM
Hollowman900024-Mar-19 04:01 PM
Cool
As long as there isn’t too much fentanyl in your heroin, tent living should be fine
3
Moon soon
MyName24-Mar-19 04:03 PM
As long as there isn’t too much fentanyl in your heroin
such a thing exists?
  Had a softspot for hydros ever since.  DMT done in the right environment may help break the cycle.
Crabby Paddy25-Mar-19 06:02 AM
On a scale of 1 to fucked, how much more tripp is dmt than acid(edited)
1
meatspoon25-Mar-19 07:11 AM
There is a cool book called DMT: The Spirit Molecule about DMT tolerance studies... my understanding is the DMT trip is as intense as it gets, seeming to last a very long time but in reality only lasting a few minutes.
actionslacks25-Mar-19 07:54 AM
I tried it the first time with a shaman in a fairly controlled and optimized environment. It was a lot like an exorcism of negative thoughts and feelings. It helped me to let go of a lot of negative emotions and focus on what is important to my life. The second time I felt I had died and was reborn on the blockchain. Like I had been reincarnated in some kind of singularity event. That progressed into believing I was the antichrist and feeling more empowered than I had ever felt. I decided I'd had enough dmt for good after that one.
The shaman just administered the dose and guided you through the trip


In Section 9.2, I explained
that
Internet Explorer versions prior to 5.5 SP1 have a bug that make it
unable to force a validation of cached responses when using HTTP
interception. This directive provides a partial workaround for the
bug. When enabled, Squid pretends that the request contains a
no-cache directive. Thus, Squid always forwards
these requests on to the origin server or a neighbor. Note this affects only requests that meet the following requirements: The User-Agent header indicates Internet Explorer
Version 3, 4, 5.0, or 5.01. The If-Modified-Since header is present. The request contains a partial URI because it was intercepted (see
Chapter 9) or Squid is a surrogate (see Chapter 15).
Squid versions prior to 2.5.STABLE3 contain a bug related to this
feature. Although Squid behaves as though the
client's request contains a
no-cache directive, it doesn't
add that directive to the outgoing request. This is a problem if you
have one or more neighbor caches. Because the request received by the
neighbor doesn't contain a
no-cache directive, it may decide to return a
cache hit, rather than forward it on to the origin server. Later versions include the no-cache directive so
that such requests should always reach the origin server. |
Syntax
|
ie_refresh on|off
| |
Default
|
ie_refresh off
| |
Example
|
ie_refresh on
|
|


Setup for new iof
projects¶
In this page you will find detailed information on how to setup iof
for a new project. First a quick setup outlining the steps. In the sections
below, more detailed instructions for the individual steps are given.
Quick setup¶
Download the code from https://github.com/perkjelsvik/iof
Create a virtual environment inside repository and install project packages
Fill out your project metadata and save it to a file
metadata.xlsx
in root location of repository codeRun
python -m src.backend.main -i
Answer
y
to convert excel metadata and fill in MQTT broker informationKeep backend running or
Ctrl+C
to kill it.Navigate to
src/frontend
and runpython initfrontend.py
Fill in at least one username/password pair for Dash app authentication
Run
python iof_app.py
to start project Dash appIf there is data in the main database inside backend, go to
http://<IP_ADDRESS>:8050
to explore the app
Installing Python 3.7¶
Windows 10¶
The latest release of Python can be downloaded from https://www.python.org/downloads/.
The currently most recent python version is 3.7.4
. If you are on windows,
download for example the executable installer and use that to install. It is
recommended to add to PATH and to also allow the installer to extend the PATH length
limit of the system. For the following commands, it is assumed you are using the
cmd.exe
terminal. You can of course use other terminals too, but for this
guide, the commands provided are valid for cmd.exe
. Translate to your own
terminal as appropiate.
Open cmd.exe
and verify your Python version by entering python -v
.
It should read out the version you installed. If not, there might be issues with
python on PATH. Typically it is due to multiple python installations on the same
machine so that it does not know which version to point too. There are several guides
on how to fix these issues if you google a bit.
Alternatively, you could install the Windows 10 Linux Subsystem https://docs.microsoft.com/en-us/windows/wsl/install-win10
Linux Ubuntu¶
sudo apt-get install python3.7 python3.7-venv
Downloading iof
repository¶
Clone / download the repository code from https://github.com/iof. Here is the direct download link for the latest version https://github.com/PerKjelsvik/iof/archive/master.zip. Unzip it in your desired location.
If you have git installed in your terminal, you can clone it to your desired location directly like so:
git clone https://github.com/perkjelsvik/iof
Installing repository dependencies¶
You should use a virtual environment. Any will work, but the recommended to use is the
built-in venv
https://docs.python.org/3/library/venv.html. Inside the repository
you have downloaded, run from terminal
windows: python -m venv venv
ubuntu: python3.7 -m venv venv
This will create a venv
folder in root of the repository. You need to activate this
environment everytime to run iof. To activate:
windows: venv\Scripts\activate
linux: source venv/bin/activate OR . venv/bin/activate
You should now se (venv)
to the left in your terminal. This indicates that the environment
is activated. To deactivate enter deactivate
. Keep the enviornment activated. Next is to
install code dependencies. When using python
in terminal it will now point to the python3.7
version of the virtual environment, and the packages installed within. All the following commands
should work on both windows and linux. Begin by upgrading pip
and then install the packages
used by the repository
pip install --upgrade pip
pip install -r requirements_dev.txt
You are now ready to initalize your project.
Filling out metadata.xlsx
¶
To position tags, convert raw data, and for the frontend Dash app to work, you need metadata.
In the repository there is a file, metadata_example.xlsx
, that you can use as a reference.
The file is also available here: https://docs.google.com/spreadsheets/d/e/2PACX-1vT5kx0npXn5d-5JLvW7uCfPEsXMts3d7dilHhqMWyXCn_6CNW_eRccCBxAkIZyq5bzEy-wUFNY3gZ3Y/pubhtml
Inside the document there are instructions on how to fill the individual sheets. I recommmend
duplicating the example file, and renaming the copy to metadata.xlsx
. The file must
have that name for the code to recognize it later. When you modify the file, remember to remove
the blue rows of each sheet, namely the row below the column names explaining what the column is.
If not the code will most likely crash in attempts to read out information from this row.
The about sheet can be changed freely.
Initalizing backend¶
From the root location of the repository, run
python -m src.backend.main -i
Follow the prompts to initalize the backend. After filling in MQTT information, the
program will spawn the iof backend as a subprocess and try to subscribe to broker. If
there are no issues it will run forever. If it crashes, for example due to no connection
to broker, it will attempt to respawn infinitely. Kill it with Ctrl+C
. Here
is an example of the information you will fill:
[...] Do you wish to convert metadata from an excel (xlsx) file? [y/n]: y
Please input ip-address: <IP_ADDRESS>
and port number: 1883
username: mqttuser
Password: mqttpassword
If you for any reason kill the backend / it stops completely, and you don’t need to initalize
it again, you can run the same python -m src.backend.main
command with the -i
flag. If you do need to change it, run it again with the flag, potentially with the -r
flag to, if you need to reset completely. To see all avalable commands, use the -h
flag.
Alternatively, you can navigate to src/backend/.config/
and modify the files stored there
manually. metadata.toml
is the converted excel metadata, while config.toml
is the
MQTT broker configuration. Additionally, there is db_names.toml
, topics.toml
,
metadata_conversion.toml
, and metadata_positioning.toml
.
Initializing frontend¶
Due to the way the Dash app is structured, the code must be run from
inside the src/frontend/
folder. Navigate there, and for first-time
setup, run
python initfrontend.py
This will only work if backend has already been correctly initalized. If so, the metadata for the current project will be converted to a frontend-compatible file. It will then prompt you to add at least one username/password pair:
python initfrontend.py
Done converting backend metadata to frontend metadata
At least one username/password pair is needed for authentication.
It will be stored next to the dash app in a toml file in plain text.
username: dev
password: pass
Do you wish to add another username/password pair? [y/n]: n
Successfully added username/password pair(s) to file! can now authenticate in Dash app.
 To run, simply run
python iof_app.py
and then go visit https://<IP_ADDRESS>:8050 in your web browser. This should load the
iof Dash app, polling data from the main database located in src/backend/dbmanager/databases/
,
and using metadata to provide filtering options in the app. Use the username/password combination
you provided in the initalization.
The app is essentially a Flask app. Look up how to host Flask apps on webservers / other solutions for
ways to make the app publicly available. The code you would have to change is the very last line of code
in iof_app.py
.


net.sf.ehcache.event
Interface CacheManagerEventListener
- All Known Subinterfaces:
- CacheManagerPeerListener
- All Known Implementing Classes:
- CacheManagerEventListenerRegistry, EhcacheHibernateMBeanRegistrationImpl, ManagementService, RMICacheManagerPeerListener, SampledMBeanRegistrationProvider
public interface CacheManagerEventListener
Allows implementers to register callback methods that will be executed when a
CacheManager
event occurs.
The lifecycle events are:
- init
- dispose
CacheManager change events are:
- adding a
Cache
- removing a
Cache
Note that the caches that are part of the initial configuration are not considered "changes".
It is only caches added or removed beyond the initial config.
Callbacks to these methods are synchronous and unsynchronized. It is the responsibility of
the implementer to safely handle the potential performance and thread safety issues
depending on what their listener is doing.
- Since:
- 1.2
- Version:
- $Id: CacheManagerEventListener.java 5594 2012-05-07 16:04:31Z cdennis $
- Author:
- Greg Luck
- See Also:
CacheEventListener
|
Method Summary |
void |
dispose()
Stop the listener and free any resources. |
Status |
getStatus()
Returns the listener status. |
void |
init()
Call to start the listeners and do any other required initialisation. |
void |
notifyCacheAdded(String cacheName)
Called immediately after a cache has been added and activated. |
void |
notifyCacheRemoved(String cacheName)
Called immediately after a cache has been disposed and removed. |
init
void init()
throws CacheException
- Call to start the listeners and do any other required initialisation.
init should also handle any work to do with the caches that are part of the initial configuration.
- Throws:
CacheException
- - all exceptions are wrapped in CacheException
getStatus
Status getStatus()
- Returns the listener status.
- Returns:
- the status at the point in time the method is called
dispose
void dispose()
throws CacheException
- Stop the listener and free any resources.
- Throws:
CacheException
- - all exceptions are wrapped in CacheException
notifyCacheAdded
void notifyCacheAdded(String cacheName)
- Called immediately after a cache has been added and activated.
Note that the CacheManager calls this method from a synchronized method. Any attempt to
call a synchronized method on CacheManager from this method will cause a deadlock.
Note that activation will also cause a CacheEventListener status change notification
from
Status.STATUS_UNINITIALISED
to
Status.STATUS_ALIVE
. Care should be taken on processing that
notification because:
- the cache will not yet be accessible from the CacheManager.
- the addCaches methods which cause this notification are synchronized on the
CacheManager. An attempt to call
CacheManager.getEhcache(String)
will cause a deadlock.
The calling method will block until this method returns.
- Parameters:
cacheName
- the name of the Cache
the operation relates to- See Also:
CacheEventListener
notifyCacheRemoved
void notifyCacheRemoved(String cacheName)
- Called immediately after a cache has been disposed and removed. The calling method will
block until this method returns.
Note that the CacheManager calls this method from a synchronized method. Any attempt to
call a synchronized method on CacheManager from this method will cause a deadlock.
Note that a
CacheEventListener
status changed will also be triggered. Any
attempt from that notification to access CacheManager will also result in a deadlock.
- Parameters:
cacheName
- the name of the Cache
the operation relates to
Copyright 2001-2013, Terracotta, Inc.


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Things You'll Need
- Certified copies of public records evidence in your case
Instructions
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[gecode-users] Problems following the document "Modeling with Gecode"
Roberto Castañeda
rcas at kth.se
Wed Mar 25 23:56:30 CET 2009
Hi everybody!
I have just compiled and installed Gecode 3.0.1 in my system (Ubuntu 8.04.2, GCC 4.2.4), and followed religiously the steps given in the section 2 ("Getting started") from the document "Modeling with Gecode". But when I have tried to do a first compilation (section 2.3.3 of the document), I have realized that I need to add the option -c to the g++ command line in order to create the object file send-more-money.o, otherwise g++ does not succeed. The suggested line in the documentation is:
g++ -I<dir>/include send-more-money.cpp
But what actually works for me is:
g++ -I<dir>/include -c send-more-money.cpp
Is this a documentation bug or am I missing something?
Thanks for your time!
Roberto
More information about the gecode-users
mailing list


--- layout: archive title: Zulip Chat Archive permalink: /stream/113489-new-members/topic/Equivalent.20Lean.20command.20for.20Coq's.20Search.3F.html ---
Coq has the Search command which lets you look for theorems relevant to a particular term or a pattern or a string. For example one could run "Search list." and it would let you find the theorems available which involve "list".
What is the Lean equivalent of this?
There is find
which seems to be less than optimal and doesn't get much love. Then there are the tactics suggest
and library_search
which might be more helpful if you are searching for one specific theorem (you know the type, but not the name).
For a list of theorems involving list
, I guess currently your best option is generic search tools like grep
.
If you're using VS Code, you can access the Lean server's search feature by hiting ctrl (or cmd if on a mac) + p and then typing the #
character before your search string. I think this searches all declarations either imported or in open files? Presumably the Emacs mode has access to this as well.
That's an or
not an either .. or
You can also get an output of all of the definitions (including theorems) associated with list (or any other type) by using #print prefix list
Yeah, these are great options. The VS code trick seems to work very well.
Where can I find documentation on find
?
https://leanprover-community.github.io/mathlib_docs/commands.html#find
But there isn't a lot there, the source is at https://github.com/leanprover-community/mathlib/blob/master/src/tactic/find.lean
{% endraw %}Last updated: Apr 24 2020 at 19:02 UTC


A channel to discuss trading. For useful links and more info click the pinned messages to the right.
100 messages
Before 05-Dec-19 12:00 AM
Markus04-Aug-19 05:03 PM
great 500x
mrtzmp304-Aug-19 05:04 PM
One can dream I guess
Markus04-Aug-19 05:04 PM
i mean everything is possible who rly knows
eth went from 9$ to 1400$
Deleted User04-Aug-19 05:04 PM
even going back to ath would be nice tbh
1
Markus04-Aug-19 05:04 PM
nobody knew that would happen(edited)
Deleted User04-Aug-19 05:04 PM
for any alt
mrtzmp304-Aug-19 05:04 PM
Ok eth did this with the ico crazy ponzi
Markus04-Aug-19 05:05 PM
then look at btc
it was worth 0
now 11k
who says kmd cant make nice gains
mrtzmp304-Aug-19 05:05 PM
Wasn't even the point of discussion
Btc is useless trash
Was the point
Markus04-Aug-19 05:05 PM
if its useless then why is it worth 11k
come on
Lanii04-Aug-19 05:06 PM
the market apprently decided its not useless trash
mrtzmp304-Aug-19 05:06 PM
The market aka Chinese miners bots , programmed to take your cash
Lanii04-Aug-19 05:06 PM
no offense but thats a really dumb thing to say
mrtzmp304-Aug-19 05:06 PM
Lol
Lanii04-Aug-19 05:06 PM
ok bruh
people getting rekt
holding shit coins
and your telling me "chinese memers are taking your cash"
lmao
Markus04-Aug-19 05:07 PM
its like...ur looking to buy a new car, it costs 100k u tell the dealer why does it cost 100k to me its worth 10k, he will laugh at u and think ur a idiot
Lanii04-Aug-19 05:07 PM
Imagine not understanding every and all alts are just an instrument to make more btc
mrtzmp304-Aug-19 05:07 PM
When was last time you spent crypto to buy something
polycryptoblog04-Aug-19 05:07 PM
@Lanii that’s the problem
mrtzmp304-Aug-19 05:07 PM
When ever did btc manifest into your daily life beside on the internet
Markus04-Aug-19 05:07 PM
when i bought kmd i spent btc
mrtzmp304-Aug-19 05:08 PM
Lol
Trading shitcoins back and forth
That's the point
It's a zerosum game
polycryptoblog04-Aug-19 05:08 PM
Bought a plane ticket a week ago
With crypto
mrtzmp304-Aug-19 05:08 PM
Nice one
What does plane company do with the btc you think ?
Hodl ?
   Just needs to develop non-btc markets.
2
weldon.gull504-Aug-19 05:29 PM
Need a correct market, so KMD has such a technical COIN to have a future
mrtzmp304-Aug-19 05:31 PM
I don't want your left nut but I would have won it


ERASER A film review by Steve Rhodes Copyright 1996 Steve Rhodes
RATING (0 TO ****): *** 1/2
You've just been erased.
-John Kruger
Sometimes a critic falls in love with a show that is getting mixed reviews. For me one of these is ERASER. I went to it expecting an enjoyable Schwarzenegger action flick, but nothing special. Once safely ensconced in my seat I was blown away by the movie.
Thanks to an excellent script by Tony Puryear and Walon Green, the movie is the funniest action picture this year. Director Chuck Russell (THE MASK) is able to sustain a high energy pace that keeps the action moving and the audience's adrenaline pumping. Too bad he was not the director of the too often tedious MISSION: IMPOSSIBLE. Actually there is a center part of ERASER that repeats part of MISSION: IMPOSSIBLE, but with much more energetic timing.
First, a suggestion. Go see this movie while it is still at the biggest screen with the most powerful subwoofers. The explosions and the gun fire, especially the electromagnetic guns, produce a sound that has the theater rocking. Second, the setup for the plot is the usual implausible one of the military, the intelligence community, the Mafia, big business, et. al. all involved in a vast conspiracy. This time it is to buy and sell a new line of ultra powerful weapons. Ignore this conspiracy ridiculousness. Go with the flow.
John Kruger (Arnold Schwarzenegger) is a Federal Marshall that is part of a special group in the witness protection program. He erases witnesses by making them appear to have died.  James Caan plays Robert Deguerin, Kruger's mentor, and James Coburn plays Beller, who is the head of the program.
Things get out of hand when Lee Cullen (Vanessa Williams) reports to the FBI about the aforementioned plot to sell weapons. She is hunted down and almost killed until Kruger saves her.  The slight mystery is which guys are the good ones and which the bad. The ending of ERASER is great. Moreover, as soon as you think it is over, it gets better and better.
The script is intelligent and at the same time so funny in parts that I was constantly rolling with laugher. As the lead evil character puts it when asked about the morality of selling horrible weapons to the wrong side, "Wars come and go. The only difference is who gets rich and who gets dead. I prefer rich." When Kruger asks Father Rodriguez whether it is safe to venture out, Father Rodriguez says, "The streets are clear. The police have returned to the safety of their donut shops."
The acting is quite good. Arnold is in fine form and hilarious - as good as in TRUE LIES, which I loved. Caan is given a one dimensional character but manages to make him interesting. Coburn barely has a part - not enough to even comment on. The best acting in the show is by Vanessa Williams. In the first scene she is so tense, you feel like you are going to have a heart attack. Later in the show, her vulnerability develops into strength and bravery. A complex role that she is up to. All of this notwithstanding, this is Arnold's picture, and he is great - strong and funny.
There are many terrific minor actors in the show, but the best are the ones from the local mob-cum-union. We have Robert Pastorelli as Johnny C. plus someone named Tony Two Toes and another named Mikey. They give invaluable help to Kruger and wonderful mirth to the audience. When Tony Two Toes first sees Kruger, he asks, "Who's the tree trunk?" When Tony thinks some Russians may be involved, he exclaims, "Those dirty Commies!" But, Mikey quickly corrects him with, "They're not commies any more. They're a federation of independent liberated states." When someone gets in his way, Tony Two Toes threatens them with, "Nobody screws with the union."
The stunts are spectacular throughout, but my favorites are the scene when Cullen's house is attacked and the scene on the airplane. Each is choreographed with perfect timing and fluid motions. The script too is highly imaginative from the guns used to the solutions Kruger comes up with on the airplane. Finally, the film conclusively answers the question, what do you say when you murder an alligator.
ERASER runs a fast 1:45 thanks to excellent editing by Michael Tronick. The film is rated R. There is no sex or nudity, and the language is mild. Since this is an action flick, there is violence with lots of people being killed and some blood, but overall, it is much less gory than typical R rated action films - more like a shoot-'em-up Western. It is fine for teenagers, but not too much younger. I saw some Dads taking their 8-10 year olds into the film which I think is too immature an age for this much violence. I give the film a strong recommendation. You will like the actions and the stunts and will probably be rolling over with laughter too. I give the film *** 1/2.
**** = One of the top few films of this or any year. A must see film. *** = Excellent show. Look for it. ** = Average movie. Kind of enjoyable. * = Poor show.  Totally unbearable.
REVIEW WRITTEN ON: June 21, 1996
Opinions expressed are mine and not meant to reflect my employer's.
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


--- layout: post title: Why do Cloud Architects Need to be Business Savvy for ITaaS? date: '2012-03-27T11:12:30-07:00' tags: tumblr_url: http://alexhwilliams.tumblr.com/post/20015682366/why-do-cloud-architects-need-to-be-business-savvy-for ---
http://bit.ly/GUkaVM


Depth Maping with OpenCV
In this we are going to map the depth in image with OpenCV.
OpenCV
This is an machine learning and image processing library. OpenCV Documentation. This is widely used, basically uses every where This library contains almost all the tools required for image prosessing from importing, adjusting, changing its property or it can even work in real time. Code for OpenCV can be written in Python, C++, Java and can be integrated into many languges. This is one-of the best open-source tool avilable for the people in this feild and also updated on time.
Depth Maping
In an image each pixel has its own depth and each depth is shown by grayscale. Each depth of pixel is means the distance of surface to a viewpoint, like from place the image is taken. For this 2 images are required of same, those images are called stereoscopic images, Like-
Stereoscopic images images same but camera is moved by some cm in case of Right Image. Each different depth is of different shade in result output and can be easyly differentiable from eyes. Depth maping has same concept as human eye, we look at a common point and have 2 different prospective, same the system need 2 images to create its own view, with its help it differentiates between the depths.
Step 1. Download
- for download with python
pip install opencv-python
- for download with Anaconda
conda install -c conda-forge opencv
- In-case error comes try
this is when your pip is old. Also can use pip command in Anacondapip install pip
Step 2. Copy Images
Download and Add these images ( l.jpg, r.jpg) into your Google Drive. This is done because sometimes images are loaded in Google colab and error comes.
Step 3. Open Code
Code can be open into colab from single tap, which will pop-up on the top of source code.
Step 4. Run
To run the code tap on Run or press Alt+Enter to run, on first it will link your Google Drive with Google Colab so it can acess the images from Step 2, it will not harm any of your files privacy is maintained.
Additional
- Your can use your own images but remember they have to be stereoscopic images
- In-case it gives error of nonetype then system was not able to find the images
- In-case to bit or binary error
try making these as comment
imgL = np.array(imgL, dtype=np.uint8) imgR = np.array(imgR, dtype=np.uint8)
- To change from grayscale to RGB
remove 'gray' from all plt.imshow(imgL,'gray') plt.imshow(filteredImg,'gray')
Result
Result should look like this
So you have completed this topic. Congratulations
Hope you learnt something new
Happy Learning!! 📚


|
Drake
|
Specializes LcmAndVectorBaseTranslator to handle LCM messages of type drake::lcmt_drake_signal
.
More...
#include <drake/systems/lcm/lcmt_drake_signal_translator.h>
Public Member Functions | |
| LcmtDrakeSignalTranslator (int size) | |
| A constructor that sets the expected sizes of the LCM message and the VectorBase. More... | |
| void | Deserialize (const void *lcm_message_bytes, int lcm_message_length, VectorBase< double > *vector_base) const override |
Translates LCM message bytes into a drake::systems::VectorBase object. More... | |
| void | Serialize (double time, const VectorBase< double > &vector_base, std::vector< uint8_t > *lcm_message_bytes) const override |
Translates a drake::systems::VectorBase object into LCM message bytes. More... | |
Does not allow copy, move, or assignment | |
| LcmtDrakeSignalTranslator (const LcmtDrakeSignalTranslator &)=delete | |
| LcmtDrakeSignalTranslator & | operator= (const LcmtDrakeSignalTranslator &)=delete |
| LcmtDrakeSignalTranslator (LcmtDrakeSignalTranslator &&)=delete | |
| LcmtDrakeSignalTranslator & | operator= (LcmtDrakeSignalTranslator &&)=delete |
| Public Member Functions inherited from LcmAndVectorBaseTranslator | |
| LcmAndVectorBaseTranslator (int size) | |
| The constructor. More... | |
| virtual | ~LcmAndVectorBaseTranslator () |
| int | get_vector_size () const |
Returns the size of the vector in the drake::systems::VectorBase object. More... | |
| virtual std::unique_ptr< BasicVector< double > > | AllocateOutputVector () const |
| Allocates the vector storage for an output port of our LCM message type, in case special storage is needed. More... | |
| LcmAndVectorBaseTranslator (const LcmAndVectorBaseTranslator &)=delete | |
| LcmAndVectorBaseTranslator & | operator= (const LcmAndVectorBaseTranslator &)=delete |
| LcmAndVectorBaseTranslator (LcmAndVectorBaseTranslator &&)=delete | |
| LcmAndVectorBaseTranslator & | operator= (LcmAndVectorBaseTranslator &&)=delete |
Specializes LcmAndVectorBaseTranslator to handle LCM messages of type drake::lcmt_drake_signal
.
Assumes the number and order of values in the LCM message and the drake::systems::VectorBase are identical.
|
delete |
|
delete |
|
inlineexplicit |
A constructor that sets the expected sizes of the LCM message and the VectorBase.
Both the LCM message and VectorBase must be the same size.
| [in] | size | The number of elements in both VectorBase and drake::lcmt_drake_signal . |
|
overridevirtual |
Translates LCM message bytes into a drake::systems::VectorBase
object.
| [in] | lcm_message_bytes | A pointer to a buffer holding the LCM message's data. |
| [in] | lcm_message_length | The number of bytes pointed to by the lcm_message_bytes . |
| [out] | vector_base | A pointer to where the translation of the LCM message should be stored. This pointer must not be nullptr . |
| std::runtime_error | If a received LCM message failed to be decoded, or if the decoded LCM message is incompatible with the vector_base . This often occurs when the size of the vector_base does not equal or is incompatible with the size of the decoded LCM message. |
Implements LcmAndVectorBaseTranslator.
|
delete |
|
delete |
|
overridevirtual |
Translates a drake::systems::VectorBase
object into LCM message bytes.
| [in] | time | The current time in seconds. This value is typically obtained from drake::systems::Context::get_time(). |
| [in] | vector_base | The object to convert into an LCM message. |
| [out] | lcm_message_bytes | The LCM message bytes. This pointer must not be nullptr . |
Implements LcmAndVectorBaseTranslator.


org.apache.bval.jsr.example
Interfaces
Address.Complete
Address.HighLevelCoherence
Book.All
First
Last
Person
Second
ZipCodeCityCarrier
Classes
AccessTestBusinessObject
AccessTestBusinessObjectSub
Address
Author
Book
BusinessAddress
CompanyAddress
Continent
Country
Customer
Employee
Engine
FrenchAddress
IllustratedBook
Library
MaxTestEntity
NoValidatorTestEntity
PreferredGuest
RecursiveFoo
SizeTestEntity
XmlEntitySampleBean


The preliminary hearing is to take place at the High Court in Edinburgh on Thursday.
Mr Salmond faced a total of 14 charges, including two counts of attempted rape, when he appeared at Edinburgh Sheriff Court on January 24.
He has previously denied the allegations and said he will defend himself “to the utmost” in court.
The 64-year-old was Scotland’s first minister from 2007 to 2014.
The result of the 2014 referendum – a 55% to 45% vote to stay in the UK – led to him stepping down as first minister and SNP leader.


On 3 January 2019, 14 new articles were published in 7 journals.
Demographic Variables Predicting Isis and Daesh Armed Political Violence
Predictive Validity and Interrater Reliability of the Face‐caras Toolkit in A Camhs Setting
Coexistence of Intimate Partner Violence and Child Maltreatment Among Adolescents in Kosovo
Crime Location Choices: A Geographical Analysis of German Serial Killers
Perceptions of Incarcerated Youth About Police Violence and Legitimacy in Trinidad and Tobago
An Investigation of Mass Public Shooting Attacks Against Government Targets in the United States
When Data Do Not Matter: Exploring Public Perceptions of Terrorism
Preventing Violent Extremism: A Review of the Literature
How to Balance Individual Rights and Societal Security? the View of Civil Servants
Cryptoterrorism: Assessing the Utility of Blockchain Technologies For Terrorist Enterprise
How and How Much: Combined Services For Domestic Violence and Substance Abuse
Sexual Violence—“Victim” Or “Survivor”: News Images Affect Explicit and Implicit Judgments of Blame


THE REPLACEMENT KILLERS (1998)
Rating: 3.0 stars (out of 4.0) ******************************** Key to rating system: 2.0 stars - Debatable 2.5 stars - Some people may like it 3.0 stars - I liked it 3.5 stars - I am biased in favor of the movie 4.0 stars - I felt the movie's impact personally or it stood out ********************************* A Movie Review by David Sunga
Directed by: Antoine Fukua
Written by: Ken Sanzel
Starring: Chow Yun-Fat, Mira Sorvino, Michael Rooker
Ingredients: Hitman now marked for death, lady forger
Synopsis: The title of this gangster redemption movie THE REPLACEMENT KILLERS might be a reference to THE KILLER, a famous Asian movie about gangster redemption, starring Chow Yun-Fat. The story is simple:
Hitman John Lee (Chow Yun-Fat), does the honorable thing and refuses his assignment to terminate a seven-year-old boy.  At first John's main concern is to reach China to put his mother and sister out of reach of the crime lord's vengeance. So he meets up with a forger named Meg (Mira Sorvino)in order to get a passport. But apparently it's open season on John and Meg. They're in over their heads and chased around town by loads of gunslinging goon squads. The rest of the movie is all high octane 'run and gun.' When the bullets stop flying after the final confrontation, the movie basically ends.
THE REPLACEMENT KILLERS is co-produced by John Woo, [Director of FACE/OFF]. The cinematography is super and so are the shootouts.
Opinion: With THE REPLACEMENT KILLERS, we're talking about a much beloved plot formula. Picture a 1950s black and white Japanese samurai movie. Outlaw samurai blows into town and tries to act honorably. But an even nastier dishonorable samurai with more men is out to kill innocent townsfolk. The outlaw hero ends up using his formidable swordsmanship skills to dispatch blade-wielding goons until the final battle ends. Then he walks off into the sunset.
Fast forward to the 1970s. Take the same movie, and make everyone wear a cowboy hat, boots, and a pancho. Outlaw gunfighter (picture Cline Eastwood) blows into town and tries to act honorably. But a nastier outlaw gunfighter with more men is out to kill innocent townsfolk. The outlaw gunfighter ends up using his formidable shooting skills to cap gun-wielding goons until the final battle ends. Then he rides a horse off into the sunset.
Now it's 1998. Add cool music, artsy cinematography, more shootouts, and a hot-looking blonde sidekick. The outlaw gunfighter who blows into town is an oriental gangster who tries to act honorably. But a mafia-type mobster with loads of men is out to kill an innocent boy. The oriental assassin ends up using his formidable shooting skills to dispatch gun-wielding goons until the final battle ends. Then he rides a plane off into the sunset.
THE REPLACEMENT KILLERS is quite thin on suspense and plot, but the cinematography is excellent and so are the gun battles. Mira Sorvino does a credible job as Meg, and Chow Yun-Fat may not become as famous as Clint Eastwood after this flick, but after THE REPLACEMENT KILLERS his name is sure to become a second tier household word in America.
Stars: 1. Chow Yun-Fat Put simply, Chow Yun-Fat is Asia's top actor - - he's kind of like an Asian Robert Mitchum; Chow Yun-Fat's a a guy that Asian ladies think is hunky because he's humble and has a manly charisma at the same time. Fat was born a poor farm boy on an island near Hong Kong. He began laboring at age 5 doing farm chores, and selling dim sum in the Hong Kong alleys and streets with his mother. He never completed a formal education, but a lucky break occured during school. A TV network sent two applications for auditions, and when Fat tried out, they gave him a chance as an actor. The rest, as they say, is history.
Fat - - who hates to be called Mr. Chow and prefers to be called 'Fat' or his nickname 'Fatboy' - - doesn't know the first thing about kung fu, but the man can act.  And like Susan Lucci, Chow Yun-Fat was a prime time soap star with years of TV dramas (over 14 years to be exact) under his belt. Like Richard Gere, Chow Yun-Fat did cheesy gigolo flicks in the 1970s. And like James Cagney or Humphrey Bogart, Chow excels portraying the cool, toothpick-chewing, chain-smoking - - but somehow noble - - gun-toting gangster.
Though he has worked primarily in Hong Kong, now Chow Yun-Fat is in Hollywood and has the attention of big name directors like Oliver Stone, Quentin Tarantino, and John Woo. It took a year and half of English lessons for him to learn enough English to star in THE REPLACEMENT KILLERS. The burning question for money-minded moguls of Hollywood is: Chow Yun-Fat is a great success in Asia, but will an Eastern hero concept - - an understated blend of humility and charisma in a nonwhite man - - be marketable to an American audience accustomed to Brad Pitt, Ethan Hawke, Leonardo DiCaprio, Clint Eastwood, Harrison Ford, and Mel Gibson?
2.  She once spent eight months living in Beijing, and was a Chinese studies major in college.
Reviewed by David Sunga February 6, 1998
THE CRITIC ZOO http://www.criticzoo.com email<EMAIL_ADDRESS>The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


<%= htmlWebpackPlugin.options.title %>
{# htmlWebpackPlugin.tags.headTags requires html-weback-plugin 4.0 we have 3.2 #}
{# with 3.2 the "way" is to loop over htmlWebpackPlugin.files.css for CSS #}
<% for (var item in htmlWebpackPlugin.files.css) { %>
<% } %>
{# we can also loop over JS files here, marking them as preload #}
<% for (var chunk in htmlWebpackPlugin.files.chunks) { %>
<% } %>
{# re-inject all webpack chunks since the "auto injection" will be outside the template #}
{# htmlWebpackPlugin.tags.bodyTags requires html-weback-plugin 4.0 we have 3.2 #}
{# with 3.2 the "way" is to loop over htmlWebpackPlugin.files.chunks for JS #}
<% for (var chunk in htmlWebpackPlugin.files.chunks) { %>
<% } %>


Loved-up Simon Cowell cuddles girlfriend Lauren at ITV bash amid X Factor ratings crisis
Simon, 60, and Lauren, 42, walked the red carpet of ITV's Palooza in London tonight as he brushed off X Factor's poor ratings
by Tiffany WallisSimon Cowell didn't appear to let the news of X Factor's dropped ratings lower his spirits as he attended ITV's Palooza tonight.
The veteran music mogul, 60, flashed his perfectly pearly whites as walked the red carpet with his glamorous long-term girlfriend Lauren Silverman at London's Royal Festival Hall in the Southbank Centre.
The TV judge grinned as he posed up a storm alongside his stunning girlfriend who turned heads in a sexy velvet dress with dramatic hemline detailing.
Simon opted for his trademark dapper appearance with a white buttoned down shirt flaunting the results of his recent 20lb weight loss and a navy two-piece suit.
The glamorous couple put on a loved-up display at the annual ITV glitz-fest as they cosied together for sweet snaps.
The smitten pair joined the likes of Vicky Pattison , Gemma Collins and Ferne McCann at the glamorous London evening.
The music manager's appearance at the event was a brave one, considering recent reports that X Factor ratings are the lowest ever.
Despite Simon giving the show a face lift with the new Celebrity series, the show hasn't been hitting the right note with audiences.
As many as 800,000 people turned off from the Celebrity version of the show.
Figures fell to 2.8million after ratings had peaked with 3.8million viewers tuning in to see the stars battle it out on stage.
Simon has been battling to save his show as its viewing figures continue to fall.
It pulled in 19.4 million for the final in its 2010 heyday. But on Saturday the celeb version only had 3.1 million.
GMB presenter Piers Morgan had a dig at the show after Saturday night's ratings were announced.
The Celebrity Chase thrashed Simon's show last weekend and Piers insisted on bragging about his appearance on the quiz.
He told viewers on Monday: "We had the highest rated show on ITV in the entire day.
We smashed X Factor in the ratings. The GMB magic bringing its way to prime time."
The controversial telly host continued: "Well if X Factor is getting three million and we're getting three and a half..."
Simon has already decided to pull the plug on another X Factor spin-off, the All Stars.
The Mirror exclusively revealed Simon scrapped the idea at the last minute after struggling to get any big name former stars to take part.
Now Simon's launching X Factor: The Band instead, and plans to find a new pop supergroup and win back his ratings.
Do you have a story to sell? Get in touch with us at<EMAIL_ADDRESS>or call us direct 0207 29 33033


Panflute is a Python package to easily write Pandoc filters.
It is pythonic and comes with batteries included.
Report issues or send suggestions.
More projects by Sergio Correia here.


Posted by ishir on December 2, 2017
Posted by ishir on October 22, 2017
Posted by ishir on October 20, 2017
Posted by ishir on October 15, 2017
Posted by ishir on August 5, 2017
Posted by ishir on May 23, 2017
Posted by ishir on October 12, 2016
Posted by ishir on June 5, 2016
敲黑板画重点希望每个人心中的少年梦想都永不消逝


| categories:development
Working around timing issues in docker compose
Containers
I really like the concept of containers. Having been a somewhat avid vagrant user in the past, the speed gain that containers can provide over a virtual machine is a good sell to me. Also, having a very snapshottable environment I can bring up and down with dependencies packed neatly into containers is a plus. If you are reading this article you probably heard the sermon before.
If you did not hear the good word yet - read up on it. There are some good arguments for and against containers and the technology behind is quite interesting.
There are several solutions for containerization out there - most notably docker and rkt, both of which are written in Go and can manage containers on Linux, effectively wrapping LXC.
This post will deal with docker
and more specifically, docker compose
.
Setup
If you’re looking at a bigger project you might need multiple containers to run all the software you need. So, you might end up with a sizable list:
- the main platform, e.g. a Rails/Django/
application - a database server, e.g. PostgreSQL, Mongo, MySQL, etc.
- some kind of search server, e.g. SOLR, ElasticSearch, ThinkingSphinx
- maybe one or two custom APIs detached from the main application
The situation get’s even worse if you decide to go full SOA by having a small fleet of microservices.
Assuming the former setup, you have 4 to 5 docker images that you’re now orchestrating to setup your project. How tedious.
Enter docker compose. It’s a little tool as part of the docker
toolkit that enables you to provide a yaml configuration and then starts up all of the containers required for your project with the configuration provided.
And that’s great - since you now only need the docker compose config in addition to the actual images (which docker
will happily pull for you).
To give an example:
# the database image
db:
image: "postgres:9.3"
ports:
- "5432:5432"
environment:
POSTGRES_USER: florian
POSTGRES_PASSWORD: 12345
volumes_from:
- dbdata
# a second container to be used as a volume for the db
dbdata:
image: "postgres:9.3"
volumes:
- /var/lib/postgres
command: "true"
# elasticsearch
elasticsearch:
image: "elasticsearch:2.2"
ports:
- "9200"
volumes_from:
- elasticsearch_index
# the index has to be persisted somewhere
elasticsearch_index:
image: "elasticsearch:2.2"
command: "true"
volumes:
- /usr/share/elasticsearch/data
# the main image, this is the application
web:
image: "company/fancy-rails:2.0"
command: "bundle exec rails s"
ports:
- "3000:3000"
links:
- "db:db"
- "elasticsearch:elasticsearch"
This config should not be usable as I made up all of it and company/fancy-rails:2.0
is not pullable.
Running docker compose up
should start all of these containers. And if you’re lucky, you get a running Rails application with PostgreSQL and ElasticSearch servers at its disposal.
Timing Problems
Since we’re not living in a perfect world, there might be some problems with this approach, most notably timing.
docker compose
will resolve your container dependencies for you, but the startup has no mercy for actual dependencies at runtime and will crash if the container you’re trying to start crashes itself (to be more precise - if the command you ran crashed).
Let’s say that our fancy Rails application requires a connection to the ElasticSearch server to start up. You are likely to end up with a crash of the whole application stack becase ElasticSearch takes longer to boot than the Rails application itself. Your stack will be torn down by docker compose
before you know what’s going on, just because the main container crashed.
There is an ongoing discussion about this problem on Github. So far most solutions revolve around having a custom script wait for the required dependencies to start up and be reachable before actually firing the container command.
Workaround
I hesitate to call this a solution, but here is my workaround which I used to tackle this problem:
Introduce a shellscript start.sh
in your application and put the following in there:
#!/bin/bash
while ! nc -z elasticsearch 9200; do sleep 2; done
bundle exec rails s -b <IP_ADDRESS>
You will need to rebuild your image for the file to be part of the container. Also, change the line in the docker-compose.yml
:
web:
image: "company/fancy-rails:2.0.1"
command: "sh start.sh"
ports:
- "3000:3000"
links:
- "db:db"
- "elasticsearch:elasticsearch"
Eseentially, the script uses netcat
to query the elasticsearch
host on the required port until it’s available. Please note that this workaround is prone to errors as the script might query forever in case the elasticsearch
container never properly comes up. Afterwards, it’s time to boot up the rails server.
Note: docker compose
provides the elasticsearch
host name conveniently via the links
attribute so that you do not have to use overly verbose names taken from the environment anymore. In case you were wondering how the web container knows about the ElasticSearch container.
Conclusion
This is far from a perfect solution. To start off, a counter could be used to abort once the script queried long enough. It’s also dependent on netcat
as part of the container, which might be undesirable if you don’t want the extra dependency.
I hope this will help in the future, tackling these issues got me stuck for a little bit on the learning curve.


Home
Master Section
First Section
Second Section
Sports
Hockey
Baseball
Football
Golf
Soccer
Tennis
Navigation_v1 Demo
Customize this demo on
JsFiddle


@(documentation: Seq[(String,String,String)]) @main("Prism API") {
This server is running the Prism API: the API that provides near real-time information about infrastructure.
Some fields have recently been removed from certain objects as they were duplicated in the object metadata.
This includes the account and accountName fields that were previously on instances objects.
For the sake of everyones sanity, this page lists the endpoints that are available to experiment with.
Fields that are prefixed with an _ control the query format in some way - they are meta paramters. Fields that are not prefixed with an _ are interpreted as field filters. Field filters are only useful when the endpoint returns an array of objects, and they are used to filter the objects that are returned. You simply add a query parameter with the same name as a top level field and the parameter value will be used to find matching objects.
Some simple examples:
_brief or _brief=true | return only the id of objects |
_length or _length=true | add companion fields to objects detailing the size of any arrays that are members of the object |
_precodey or _precodey=true | output json results in precodeified format |
_reference=uri | output references to objects as Prism object URI (default is Prism ARN ID) |
_reference=inline | expand references with inline objects |
stage=TEST | return objects whose stage field has the value of TEST |
stage!=TEST | invert - return objects whose stage field does not have the value of TEST |
role~=id.* | regexs - return objects whose role field matches the regular expression id.* (i.e. starts with id) |
role!~=id.* | inverted regex - return objects whose role field does not match the regular expression |
stage=TEST&role~=id.* | multiple fields - an exact match of stage and a regex match of role; this returns objects whose stage field has value of TEST AND whose role field matches the regular expression |
stage=TEST&stage=CODE | fields can be specified twice - here we return objects whose stage field has the value of TEST OR CODE |
stage!=TEST&stage!=CODE | this makes no sense - here we return objects whose stage field has a value that is not TEST OR not CODE (i.e. all objects) |
tag.MongoReplSet=prodprv1 | Nested fields can be filtered using periods to separate the fields |
Note that multiple filters for the same field have the sense of an OR operation and then the filters for each individual field have the sense of an AND operation.
| @route._1 | @route._2 | @route._3 |


use Test; use Red::AST; use Red::Driver; use Red::Statement; use Red::Driver::SQLite; use Red::Driver::CommonSQL; unit class Red::Driver::Mock does Red::Driver; method schema-reader {} multi prepare-sql(Str:U $_) { Str } multi prepare-sql(Str:D $_) { .lc .subst(/<[\w."']>+/, { " $_ " }, :g) .subst( /[\s* "(" \s*] ~ [\s* ")" \s*] ([<-[()]>+|"(" ~ ")" [\s*.*?\s*]])+?/, -> $/ { "( { $0.Str.split(/\s* "," \s*/).sort.join(" , ") } )" }, :g ) .subst(/\s+/, " ", :g) .trim } has Hash %.when-str{Str}; has Hash %.when-re{Regex}; has Bool $!die-on-unexpected = False; has Red::Driver $.driver-obj = Red::Driver::SQLite.new; multi method default-type-for(Red::Column $a --> Str:D) { $!driver-obj.default-type-for($a) } multi method is-valid-table-name(|c) { $!driver-obj.is-valid-table-name(|c) } multi method type-by-name(|c) { $!driver-obj.type-by-name(|c) } multi method inflate(|c) { $!driver-obj.inflate(|c) } method translate(|c) { $!driver-obj.translate(|c) } multi method join-type(|c) { $!driver-obj.join-type(|c) } class Statement does Red::Statement { has Iterator $.iterator; has Str $.should-run; method stt-exec($stt, *@bind) { } method stt-row($stt) { $!iterator.pull-one } } method die-on-unexpected() { $!die-on-unexpected = True } proto method when( $when, :$times, Bool :$once, Bool :$twice ) { my $*times = $times // ($once ?? 1 !! $twice ?? 2 !! Inf); {*}; self } multi method when($when where Str | Regex, Bool :$never! where * === True) { self.when: $when, :run{ die "This should never be called" }, :0times; } multi method when(Str $when, :&run!) { %!when-str{$when.&prepare-sql} = {:&run, :$*times, :0counter}; } multi method when(Regex $when, :&run!) { %!when-re{$when} = {:&run, :$*times, :0counter}; } multi method when(Str $when, :@return!) { self.when: $when.&prepare-sql, :run{ @return }, :$*times; } multi method when(Regex $when, :@return!) { self.when: $when, :run{ @return }, :$*times; } multi method when(Str $when, :$throw!) { self.when: $when.&prepare-sql, :run{ die $throw }, :$*times; } multi method when(Regex $when, :$throw!) { self.when: $when, :run{ die $throw }, :$*times; } multi method prepare(Red::AST $query) { do for |self.translate: self.optimize: $query -> Pair \data { my ($sql, @bind) := do given data { .key, .value } self.prepare: $sql; } } multi method prepare(Str $query) { my $t-query = $query.trans(("\n", "\t") => < ␉>); self.debug: $query; given $query.&prepare-sql { with %!when-str{$_} -> % (:$times!, :$counter! is rw, :&run!) { $counter++; die "The query '$t-query' should never be called" unless $times; die "The query '$t-query' should run $times time(s) but was ran $counter times" if $counter > $times; return Statement.new: :driver(self), :iterator(run.iterator) } my $size = 0; my %data; for %!when-re.kv -> Regex $re, %value { if .match($re) && $/.Str.chars > $size { $size = $/.Str.chars; %data := %value; } } if %data { %data<counter>++; die "The query '$t-query' should never be called" unless %data<times> > 0; die "The query '$t-query' should run %data<times> time(s) but was ran %data<counter> times" if %data<counter> > %data<times>; return Statement.new: :driver(self), :iterator(%data<run>.().iterator) } flunk "Unexpected query: $_" if $!die-on-unexpected; } Statement.new: :driver(self), :iterator([].iterator) } method verify { #is test-assertion { subtest { plan %!when-str + %!when-re; for %!when-str.kv -> Str $str, % (:$counter = 0, :$times, |) { ok ($times == Inf or $counter == $times), "Query '$str' should be called $times times and was called $counter time(s)"; } for %!when-re.kv -> Regex $re, % (:$counter = 0, :$times, |) { ok ($times == Inf or $counter == $times), "Query that matches '$re.perl()' should be called $times times and was called $counter time(s)"; } }, "Red Mock verify" }


Umfrogr
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lib_netsockets
Pedro Vicente
lib_netsockets is a set of C++ classes that use POSIX/Winsock sockets with implementation of TCP client/server using JSON messages, and HTTP, FTP clients.
The following steps shown an example of a client/server exchange using JSON.
FTP client
The File Transfer Protocol (FTP) is a network protocol used to transfer files between a client and server.
FTP uses uses two separate control and data connections between client and server.
An FTP conversation consists of requests sent by the client and responses sent by the server.
An FTP request consists of a request verb, optionally, a space followed by a parameter, and CRLF characters (i.e ASCII values 13 and 10).
The server responds over the control connection with three-digit status codes in ASCII with an optional text message.
Following, examples are shown for a request (color red) and response (color green) exchange for a USER, PASS, PASV, NLST, SIZE, RETR and QUIT requests.
Connection
After a connection is made, the server sends an initial response, called the greeting.
220 (vsFTPd 3.0.2)
The USER verb
A USER request has a parameter with a username. In this case, the response asks for a password.
USER anonymous
331 Please specify the password.
The PASS verb
A PASS request has a parameter with a password.
PASS password
230 Login successful.
The PASV verb
A PASV request asks the server to accept a data connection on a new TCP port selected by the server.
PASV
227 Entering Passive Mode (100,200,300,400,202,12).
The NLST verb
The NLST request asks the server to send the contents of a directory over the data connection already established by the client.
NLST
150 Here comes the directory listing.
226 Directory send OK.
The SIZE verb
The SIZE request asks the size of a file. The parameter is the file name. The response sends the size in bytes after the 3 digit response code 213.
SIZE filename.txt
213 2
The RETR verb
A RETR request asks the server to send the contents of a file over the data connection already established by the client.
The RETR parameter is a file name.
RETR filename.txt
150 Opening BINARY mode data connection for filename.txt (2 bytes).
226 Transfer complete.
The QUIT verb
A QUIT request terminates the connection.
QUIT
221 Goodbye.
FTP client usage
lib_netsockets FTP client usage that retrieves a file list from a FTP server, and retrieves the first file from the list is
ftp_t ftp(host_name, 21);
ftp.login(user_name, pass);
ftp.get_file_list();
if (ftp.m_file_nslt.size())
{
ftp.get_file(ftp.m_file_nslt.at(0).c_str());
}
ftp.logout();
References
-
[RFC959] FILE TRANSFER PROTOCOL (FTP) https://tools.ietf.org/pdf/rfc959.pdf


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arcgis.geoanalytics.summarize_data module¶
The Summarize Data module contains functions that calculate total counts, lengths, areas, and basic descriptive statistics of features and their attributes within areas or near other features.
aggregate_points calculates statistics about points that fall within specified areas or bins. join_features calculates statistics about features that share a spatial, temporal, or attribute relationship with other features. reconstruct_tracks calculates statistics about points or polygons that belong to the same track and reconstructs inputs into tracks. summarize_attributes calculates statistics about feature or tabular data that share attributes. summarize_within calculates statistics for area features and attributes that overlap each other.
aggregate_points¶
-
arcgis.geoanalytics.summarize_data.
aggregate_points
(point_layer, bin_type: str = None, bin_size: float = None, bin_size_unit: str = None, polygon_layer=None, time_step_interval: int = None, time_step_interval_unit: str = None, time_step_repeat_interval: int = None, time_step_repeat_interval_unit: str = None, time_step_reference: datetime.datetime = None, summary_fields: str = None, output_name: str = None, gis=None)¶ Using a layer of point features and either a layer of area features or bins defined by a specified distance, this tool determines which points fall within each area or bin and calculates statistics about all the points within each area or bin. You may optionally apply time slicing with this tool.
For example
- Given point locations of crime incidents, count the number of crimes per county or other administrative district.
- Find the highest and lowest monthly revenues for franchise locations using 100 km bins.
This tool works with a layer of point features and a layer of areas features. Input area features can be from a polygon layer or they can be square or hexagonal bins calculated when the tool is run. The tool first determines which points fall within each specified area. After determining this point-in-area spatial relationship, statistics about all points in the area are calculated and assigned to the area. The most basic statistic is the count of the number of points within the area, but you can get other statistics as well.
For example, suppose you have point features of coffee shop locations and area features of counties, and you want to summarize coffee sales by county. Assuming the coffee shops have a TOTAL_SALES attribute, you can get the sum of all TOTAL_SALES within each county, the minimum or maximum TOTAL_SALES within each county, or other statistics such as the count, range, standard deviation, and variance.
This tool can also work with data that is time-enabled. If time is enabled on the input points, then the time slicing options are available. Time slicing allows you to calculate the point-in-area relationship while looking at a specific slice in time. For example, you could look at hourly intervals, which would result in outputs for each hour.
For an example with time, suppose you had point features of every transaction made at various coffee shop locations and no area layer. The data has been recorded over a year and each transaction has a location and a time stamp. Assuming each transaction has a TOTAL_SALES attribute, you can get the sum of all TOTAL_SALES within the space and time of interest. If these transactions are for a single city, we could generate areas that are 1-kilometer grids and look at weekly time slices to summarize the transactions in both time and space.
Argument Description point_layer Required Input Points layer (features). bin_type Optional string parameter. If polygon_layer is not defined, it is required. Choice list:[‘Square’, ‘Hexagon’] bin_size Bin Size (float). Optional parameter. bin_size_unit Bin Size Unit (str). Optional parameter. Choice list:[‘Feet’, ‘Yards’, ‘Miles’, ‘Meters’, ‘Kilometers’, ‘NauticalMiles’] polygon_layer Optional Input Polygons layer (features). If bin_type and bin properties are not defined, it is required. time_step_interval Time Step Interval (int). Optional parameter. time_step_interval_unit Time Step Interval Unit (str). Optional parameter. Choice list:[‘Years’, ‘Months’, ‘Weeks’, ‘Days’, ‘Hours’, ‘Minutes’, ‘Seconds’, ‘Milliseconds’] time_step_repeat_interval Time Step Repeat Interval (int). Optional parameter. time_step_repeat_interval_unit Time Step Repeat Interval Unit (str). Optional parameter. Choice list:[‘Years’, ‘Months’, ‘Weeks’, ‘Days’, ‘Hours’, ‘Minutes’, ‘Seconds’, ‘Milliseconds’] time_step_reference Time Step Reference (datetime). Optional parameter. summary_fields Summary Statistics (str/list). Optional parameter.
The summary_fields string must enclose a Python list. Each list item must be a Python dictionary with two keys. See the Key:Value definitions below.
See URL 1 below for full details.
output_name Output Features Name (str). Optional parameter. gis Optional, the GIS on which this tool runs. If not specified, the active GIS is used. Key:Value Dictionary Options for Argument summary_fields
Key Value statisticType Required string. Indicates statistic to summarize. See URL 1 below for full explanation.
Choice list numeric fields:[‘Count’, ‘Sum’, ‘Mean’, ‘Min’, ‘Max’, ‘Range’, ‘Stddev’, ‘Var’]
Choice list for string fields:[‘Count’, ‘Any’]
onStatisticField Required string. Provides the field name to summarize.
See https://developers.arcgis.com/python/guide/working-with-feature-layers-and-features/#Querying-feature-layers for instructions to query a feature layer for field names.
For detailed explanation see:
URL 1: http://resources.arcgis.com/en/help/arcgis-rest-api/index.html#/Aggregate_Points/02r3000002rr000000/
Returns: Output Features as ItemExample
# Usage Example: Using summary_fields on a layer. agg_pts_item = aggregate_points(input_points_layer, bin_size=0.5, bin_type='Hexagon', bin_size_unit='Miles', summary_fields=[{"statisticType": "Count", "onStatisticField": "fieldName1"}, {"statisticType": "Any", "onStatisticField": "fieldName2"}] )
build_multivariable_grid¶
-
arcgis.geoanalytics.summarize_data.
build_multivariable_grid
(input_layers, variable_calculations, bin_size, bin_unit='Meters', bin_type='Square', output_name=None, gis=None)¶ Only available at ArcGIS Enterprise 10.6.1 and later.
The Build Multi-Variable Grid task works with one or more layers of point, line, or polygon features. The task generates a grid of square or hexagonal bins and compiles information about each input layer into each bin. For each input layer, this information can include the following variables:
- Distance to Nearest - The distance from each bin to the nearest feature.
- Attribute of Nearest - An attribute value of the feature nearest to each bin.
- Attribute Summary of Related - A statistical summary of all features within search distance of each bin.
Only variables you specify in variable_calculations will be included in the result layer. These variables can help you understand the proximity of your data throughout the extent of your analysis. The results can help you answer questions such as the following:
- Given multiple layers of public transportation infrastructure, where in the city is least accessible by public transportation?
- Given layers of lakes and rivers, what is the name of the water body closest to each location in the US?
- Given a layer of household income, where in the US is the variation of income in the surrounding 50 miles the largest?
The result of Build Multi-Variable Grid can also be used in prediction and classification workflows. The task allows you to calculate and compile information from many different data sources into a single, spatially continuous layer in one step, reducing the amount of effort required to build prediction and classification models.
Arguments Description input_layers Required list of FeatureLayers. A list of input layers that will be used in analysis. Each input layer follows the same formatting as described in the Feature Input topic. This can be one of the following:
- A URL to a feature service layer with an optional filter to select specific features
- A URL to a big data catalog service layer with an optional filter to select specific features
- A feature collection
variable_calculations Required list of dictionaries. A JSON array containing objects that describe the input layers and the attributes that will be calculated for each layer. bin_size Required float. The distance for the bins of type binType in the output polygon layer. Enrichment attributes will be calculated at the center of each bin. When generating bins, for Square, the number and units specified determine the height and length of the square. For Hexagon, the number and units specified determine the distance between parallel sides. bin_unit Optional string. The distance unit for the bins that will be used to calculate enrichment attributes.
Values: Meters (default), Kilometers, Feet, Miles, NauticalMiles, or Yards
bin_type Optional string. The type of bin that will be generated. Bin options are the following:
- Hexagon.
- Square (default)
output_name Optional string. output name of the layer gis Optional GIS. The enterprise site that you want to connect to. Returns: Feature Layer
describe_dataset¶
-
arcgis.geoanalytics.summarize_data.
describe_dataset
(input_layer, extent_output=False, sample_size=None, output_name=None, gis=None)¶ The Describe Dataset task provides an overview of your big data. The tool outputs a JSON detailing the input layer’s geometry and time settings, schema, and summary statistics for each field. Optionally, the tool can output two types of descriptive feature layers: a feature layer representing a sample of your input features, and a single polygon feature layer that represents the extent of the input features. You can choose to output one or both.
Usage Notes:
Only available at ArcGIS Enterprise 10.7 and later.
Argument Description input_layer required FeatureLayer. The point, line or polygon features. extent_output Optional Boolean. The task will output a single rectangle feature representing the extent of the input_layer if this value is set to true. The default is False. sample_size Optional integer. The task will output a feature layer representing a sample of features from the input_layer. Specify the number of sample features to return. If the input value is 0 or empty then no sample layer will be created. The output will have the same schema, geometry, and time type as the input layer. The default is None. output_name optional string. The task will create a feature service of the results. You define the name of the service. gis optional GIS. The GIS object where the analysis will take place. Returns: FeatureLayer
join_features¶
-
arcgis.geoanalytics.summarize_data.
join_features
(target_layer, join_layer, join_operation: str = 'JoinOneToOne', join_fields: str = None, summary_fields: str = None, spatial_relationship: str = None, spatial_near_distance: float = None, spatial_near_distance_unit: str = None, temporal_relationship: str = None, temporal_near_distance: int = None, temporal_near_distance_unit: str = None, attribute_relationship: str = None, join_condition: str = None, output_name: str = None, gis=None)¶ Using either feature layers or tabular data, you can join features and records based on specific relationships between the input layers or tables. Joins will be determined by spatial, temporal, and attribute relationships, and summary statistics can be optionally calculated.
For example
- Given point locations of crime incidents with a time, join the crime data to itself specifying a spatial relationship of crimes within 1 kilometer of each other and that occurred within 1 hour of each other to determine if there are a sequence of crimes close to each other in space and time.
- Given a table of ZIP Codes with demographic information and area features representing residential buildings, join the demographic information to the residences so each residence now has the information.
The Join Features task works with two layers. Join Features joins attributes from one feature to another based on spatial, temporal, and attribute relationships or some combination of the three. The tool determines all input features that meet the specified join conditions and joins the second input layer to the first. You can optionally join all features to the matching features or summarize the matching features.
Join Features can be applied to points, lines, areas, and tables. A temporal join requires that your input data is time-enabled, and a spatial join requires that your data has a geometry.
Argument Description target_layer Required FeatureLayer. Target Features (feature input) join_layer Required FeatureLayer. Join Features (feature input). join_operation Required String. The join operation. Allowed values: JoinOneToOne and JoinOneToMany join_fields Optional String. Join Fields summary_fields Optional String. Summary Statistics spatial_relationship Optional String. The spatial relationship. Choice list: [‘Equals’, ‘Intersects’, ‘Contains’, ‘Within’, ‘Crosses’, ‘Touches’, ‘Overlaps’, ‘Near’, ‘NearGeodesic’] spatial_near_distance Optional Float. Near Spatial Distance. This is required if the spatial_relationship is defined as NearGeodesic. spatial_near_distance_unit Optional String. Near Spatial Distance Unit. This is required if the spatial_relationship is defined as NearGeodesic. Choice list:[‘Feet’, ‘Yards’, ‘Miles’, ‘Meters’, ‘Kilometers’,
‘NauticalMiles’]temporal_relationship Optional String. Temporal Relationship. Choice list : [‘Equals’, ‘Intersects’, ‘During’, ‘Contains’,
‘Finishes’, ‘FinishedBy’, ‘Meets’, ‘MetBy’, ‘Overlaps’, ‘OverlappedBy’, ‘Starts’, ‘StartedBy’, ‘Near’]temporal_near_distance Optional Integer. Near Temporal Distance (int) temporal_near_distance_unit Optional String.Near Temporal Distance Unit Choice list:[‘Years’, ‘Months’, ‘Weeks’, ‘Days’, ‘Hours’,
‘Minutes’, ‘Seconds’, ‘Milliseconds’]attribute_relationship Optional String. Attribute Relationships join_condition Optional String. Join Condition output_name Optional String. The task will create a feature service of the results. You define the name of the service. gis Optional GIS. The GIS object where the analysis will take place. Returns: Output Features as Feature Layer Collection Item
reconstruct_tracks¶
-
arcgis.geoanalytics.summarize_data.
reconstruct_tracks
(input_layer, track_fields: str, method: str = 'Planar', buffer_field: str = None, summary_fields: str = None, distance_split=None, distance_split_unit=None, time_boundary_split=None, time_boundary_split_unit=None, time_boundary_reference=None, output_name: str = None, gis=None)¶ Using a time-enabled layer of point or polygon features that represent an instant in time, this tool determines which input features belong in a track and will order the inputs sequentially in time. Statistics are optionally calculated for the input features within each track.
For example
Given point locations and time of hurricane measurements, calculate the mean wind speed and max wind pressure of the hurricane.
Find the highest and lowest monthly revenues for franchise locations using 100 km bins.
This tool works with a time-enabled layer of either point or polygon features that represent an instant in time. It first determines which features belong to a track using an identifier. Using the time at each location, the tracks are ordered sequentially and transformed into a line or polygon representing the path of movement over time. Optionally, the input may be buffered by a field, which will create a polygon at each location. These buffered points, or if the inputs are polygons, are then joined sequentially to create a track as a polygon where the width is representative of the attribute of interest. Resulting tracks have a start and end time, which represent temporally the first and last feature in a given track. When the tracks are created, statistics about the input features are calculated and assigned to the output track. The most basic statistic is the count of points within the area, but other statistics can be calculated as well.
Features in time-enabled layers can be represented in one of two ways:
Instant-A single moment in time Interval-A start and end time For example, suppose you have GPS measurements of hurricanes every 10 minutes. Each GPS measurement records the hurricane’s name, location, time of recording, and wind speed. With this information, you could create tracks for each hurricane using the name for track identification, and tracks for each hurricane would be generated. Additionally, you could calculate statistics such as the mean, max, and minimum wind speed of each hurricane, as well as the count of measurements within each track.
Using the same example, you could buffer your tracks by the wind speed. This would buffer each measurement by the wind speed field at that location, and join the buffered areas together, creating a polygon representative of the track path, as well as the changes in wind speed as the hurricanes progressed.
Parameters:
input_layer: Input Features (feature input). Required parameter.
track_fields: Track Fields (str). Required parameter.
- method: Method (str). Required parameter.
- Choice list:[‘Geodesic’, ‘Planar’]
buffer_field: Buffer Distance Field (str). Optional parameter.
summary_fields: Summary Statistics (str/list). Optional parameter.
time_boundary_split: Duration Split Threshold (int). Optional parameter.
- time_boundary_split_unit: Duration Split Threshold Unit (str). Optional parameter.
- Choice list:[‘Years’, ‘Months’, ‘Weeks’, ‘Days’, ‘Hours’, ‘Minutes’, ‘Seconds’, ‘Milliseconds’]
time_boundary_reference: Starting time location (datetime.datetime). Optional parameter.
distance_split: A distance used to split tracks. Any features in the inputLayer that are in the same track and are greater than this distance apart will be split into a new track. The units of the distance values are supplied by the distance_unit parameter.
- distance_split_unit: The distance unit to be used with the distance value specified in distanceSplit.
- Values: Meters,Kilometers,Feet,Miles,NauticalMiles, or Yards
output_name: Output Features Name (str). Required parameter.
gis: Optional, the GIS on which this tool runs. If not specified, the active GIS is used.
- Returns:
- output - Output Features as a Feature Layer Collection Item
summarize_attributes¶
-
arcgis.geoanalytics.summarize_data.
summarize_attributes
(input_layer, fields: str = None, summary_fields: str = None, output_name: str = None, gis=None)¶ Using either feature or tabular data, this tool summarizes statistics for specified fields.
For example
- Given locations of grocery stores with a field COMPANY_NAME, summarize the stores by the company name to determine statistics for each company.
- Given a table of grocery stores with fields COMPANY_NAME and COUNTY, summarize the stores by the company name and county to determine statistics for each company within each county.
This tool summarizes all the matching values in one or more fields and calculates statistics on them. The most basic statistic is the count of features that have been summarized together, but you can calculate more advanced statistics as well.
For example, suppose you have point features of store locations with a field representing the DISTRICT_MANAGER_NAME and you want to summarize coffee sales by manager. You can specify the field DISTRICT_MANAGER_NAME as the field to dissolve on, and all rows of data representing individual managers will be summarized. This means all store locations that are managed by Manager1 will be summarized into one row with summary statistics calculated. In this instance, statistics like the count of the number of stores and the sum of TOTAL_SALES for all stores that Manager1 manages would be calculated as well as for any other manager listed in the DISTRICT_MANAGER_NAME field.
Parameters:
input_layer: Input Features (feature input). Required parameter.
fields: Summary Fields (str). Required parameter.
summary_fields: Summary Statistics (str/list). Optional parameter.
output_name: Output Features Name (str). Required parameter.
gis: Optional, the GIS on which this tool runs. If not specified, the active GIS is used.
- Returns:
- output - Output Features as a _FeatureSet
summarize_within¶
-
arcgis.geoanalytics.summarize_data.
summarize_within
(summarized_layer, summary_polygons=None, bin_type: str = None, bin_size: float = None, bin_size_unit: str = None, standard_summary_fields: str = None, weighted_summary_fields: str = None, sum_shape: bool = True, shape_units: str = None, group_by_field: str = None, minority_majority: bool = False, percent_shape: bool = False, output_name: str = None, gis=None)¶ Finds areas (and portions of areas) that overlap between two layers and calculates statistics about the overlap.
For example
- Given a layer of watershed areas and a layer of land-use areas by land-use type, calculate total acreage of land-use type for each watershed.
- Given a layer of parcels in a county and a layer of city boundaries, summarize the average value of vacant parcels within each city.
Parameters:
summarized_layer: Layer To Summarize (feature input). Required parameter.
summary_polygons: Summary Polygons Layer (feature input). Optional parameter.
- bin_type: Output Bin Type (str). Optional parameter.
- Choice list:[‘Square’, ‘Hexagon’]
bin_size: Output Bin Size (float). Optional parameter.
- bin_size_unit: Output Bin Size Unit (str). Optional parameter.
- Choice list:[‘Feet’, ‘Yards’, ‘Miles’, ‘Meters’, ‘Kilometers’, ‘NauticalMiles’]
standard_summary_fields: Unweighted Summary Statistics (str). Optional parameter.
weighted_summary_fields: Proportional Summary Statistics (str). Optional parameter.
sum_shape: Summarize Shape (bool). Optional parameter.
- shape_units: Shape Measure Output Unit (str). Optional parameter.
- Choice list:[‘Meters’, ‘Kilometers’, ‘Feet’, ‘Yards’, ‘Miles’, ‘SquareMeters’, ‘SquareKilometers’, ‘Hectares’, ‘SquareFeet’, ‘SquareYards’, ‘SquareMiles’, ‘Acres’]
group_by_field: This is a field of the summarized_layer features that you can use to calculate statistics separately for each unique attribute value. For example, suppose the sumWithinLayer contains city boundaries and the summaryPolygons features are parcels. One of the fields of the parcels is Status which contains two values: VACANT and OCCUPIED. To calculate the total area of vacant and occupied parcels within the boundaries of cities, use Status as the groupByField field. This parameter is available at ArcGIS Enterprise 10.6.1+.
minority_majority: This boolean parameter is applicable only when a group_by_field is specified. If true, the minority (least dominant) or the majority (most dominant) attribute values for each group field are calculated. Two new fields are added to the resultLayer prefixed with Majority_ and Minority_. This parameter is available at ArcGIS Enterprise 10.6.1+. The default is false.
percent_shape: This boolean parameter is applicable only when a group_by_field is specified. If set to true, the percentage of each unique group_by_field value is calculated for each sum within layer polygon. The default is false. This parameter is available at ArcGIS Enterprise 10.6.1+.
output_name: Output Features Name (str). Required parameter.
gis: Optional, the GIS on which this tool runs. If not specified, the active GIS is used.
- Returns:
- output - Output Features as a layer Item


The iPhone 12 Mini is slightly larger than the old 5/5S/SE line, but in the hand it feels the same. It’s wonderful.


I love everyone so should you:)
My HSD fam and me going to formal!!!.
I love these girls :)
From left to right: Me(Adi), Zoey, and Nelly
they are my homies from streetcode!  He is the genius who taught me about the eligible discount (haha).


Module: ActiveSupport::Messages::SerializerWithFallback::MarshalWithFallback
| Relationships & Source Files | |
| Super Chains via Extension / Inclusion / Inheritance | |
|
Instance Chain:
|
|
| Defined in: | activesupport/lib/active_support/messages/serializer_with_fallback.rb |
Constant Summary
-
MARSHAL_SIGNATURE =
# File 'activesupport/lib/active_support/messages/serializer_with_fallback.rb', line 71"\x04\x08"
::ActiveSupport::Messages::SerializerWithFallback
- Included
Instance Method Summary
Instance Method Details
#_load(dumped)
[ GitHub ]# File 'activesupport/lib/active_support/messages/serializer_with_fallback.rb', line 67
def _load(dumped) Marshal.load(dumped) end
#dump(object)
[ GitHub ]# File 'activesupport/lib/active_support/messages/serializer_with_fallback.rb', line 63
def dump(object) Marshal.dump(object) end
#dumped?(dumped) ⇒ Boolean
# File 'activesupport/lib/active_support/messages/serializer_with_fallback.rb', line 73
def dumped?(dumped) dumped.start_with?(MARSHAL_SIGNATURE) end
#format
[ GitHub ]# File 'activesupport/lib/active_support/messages/serializer_with_fallback.rb', line 59
def format :marshal end


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Static Public Attributes | |
| static const order_selector | value = clockwise |
| G | geometry |
Definition at line 39 of file point_order.hpp.
const order_selector boost::geometry::traits::point_order< G >::value = clockwise [static] |
Definition at line 41 of file point_order.hpp.
|
December 1, 2009 |
Copyright © 1995-2009 Barend Gehrels, Geodan, Amsterdam Copyright © 2008-2009 Bruno Lalande, Paris Copyright © 2009 Mateusz Loskot, Cadcorp, London |


DOUBLE JEOPARDY A film review by Christopher Null Copyright 1999 Christopher Null filmcritic.com
DOUBLE JEOPARDY does not take place during the latter half of a game show. However, it has a similar amount of credibility.
There's an old adage in screenwriting: You can make something up, and it doesn't have to *be* real. It just has to be believable. In other words, you can make up the lines for a priest to read at a wedding, as long as they sound plausible. No one's going to know if you miss a few `Amens.' However, this liberty does not extend to making up laws on which to base the premise of your film.
DOUBLE JEOPARDY has the bizarre distinction of probably being the first movie to completely rest its fortunes on the fact that you'll buy make-believe legislation. And if you believe the filmmakers, you simply can't be tried for the same crime twice.
Right? Wrong. Very wrong. Wrong to the point that it's scary to think that maybe the filmmakers maybe didn't realize it at any point during the production.
The plot of DOUBLE JEOPARDY is very plain and obvious (Tommy Lee Jones chases vengeance-obsessed Judd for an hour while she tracks down hubby, just like in THE FUGITIVE). And while the thriller is pedestrian and straightforward and otherwise dull, the theater erupts in laughter every time that `double jeopardy' clause is trotted out. You keep expecting for *someone* on screen to explain to Judd how the law works, but they never do, and Jones's character is an ex-law professor!
Not that I should feel surprised. Bruce Beresford hasn't made a good movie since 1989 (DRIVING MISS DAISY). While Jones is campy and fun to watch, and I could be entertained watching Ashley Judd make toast for two hours, the film does not redeem itself with these minimal, guilty pleasures (see also: ENTRAPMENT). This isn't Double Jeopardy. It's a $100 warm-up question.
RATING: **1/2
|------------------------------| \ ***** Perfection \ \ **** Good, memorable film \ \ *** Average, hits and misses \ \ ** Sub-par on many levels \ \ * Unquestionably awful \ |------------------------------|
MPAA Rating: R
Director: Bruce Beresford Producer: Leonard Goldberg Writer: David Weisberg, Douglas Cook Starring: Tommy Lee Jones, Ashley Judd, Annabeth Gish, Bruce Greenwood
http://www.doublejeopardymovie.com/
Christopher Null -<EMAIL_ADDRESS>- http://www.filmcritic.com Author - Network Administrator's Reference, 1999, ISBN 0-07-882588-1 http://www.amazon.com/exec/obidos/ASIN/0078825881/filmcriticcom
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


This menu option is used to view or conceal the status bar. The status bar specifies the action which is executed by the selected menu option or by pressing a button in the toolbar, and displays the status of the discernible keys. When the status bar is on view, a tick appears to the left of this menu option.
Help regarding the use of the status bar will be found under status bar.


--- layout: page title: 90 days in North Carolina scripts: - /js/photos.js ---
We're living in North Carolina for about three months. While we're here, Sarah is embarking on a photo-a-day project. Keep an eye on her progress below:


Example of bootstrap with table.
| Customer Name |
Number of orders |
Total sales |
| Rajesh |
10 |
5000 |
| Krishna |
10 |
5000 |
| {{item._id}} |
{{item.num_products}} |
{{item.sales}} |
- Compare this with regular table.
Points to note are:-
1. bootstrap gives good look and feel
2. Bootstrap is easy to use
3. First create ordinary html, then update with bootstrap tags
Next
1. Get data from json file and populate table
2. Get data from backend and display data in table


WITNESS LIST Nominations Committee February 17, 2003 - 3:00P Chief Justice, Frist Court of Appea ON: Radack, Sherry (Self) Court of Appeals for the Seventh Di ON: Campbell, James T. (Self) Justice First Court of Appeals ON: Hanks, Jr., George C. (Self) Telecommunications Infrastructure F ON: Torres, Edward (Self) Telecommunicatons Infrastructure Fu ON: Fitzsimmons, Blair (Self) Texas Board of Professional Land Su Registering, but not testifying: On: Smith, Sandy Ex. Director (Arthur Osborn) Texas Historical Commission On: Oaks, Larry Executive Director (Frank Gorman) Oaks, Larry Executive Director (Jane Barnhill) Oaks, Larry Ex Director (Shirley Caldwell) Texas Historical Commisson On: Oaks, Larry Executive Director (Frank Yturria) Texas Railroad Commission ON: Carrillo, Victor (Self) Tx Bd of Prof Land Surveying Registering, but not testifying: On: Smith, Sandy Ex. Director (Raul Wong) Tx Bd Prof. Land Survey On: Smith, Sandy Ex Director (David Smyth) Tx Historical Commission On: Oaks, Larry Executive Director (David Gravelle) Oaks, Larry Ex. Director (Lareatha Clay) Tx Motor Vehicle Board On: Bray, Brett Division Director (James Leonard) Tx Motor Vehicle Brd On: Brey, Brett Division Director (Patricia Harless) Tx. Motor Vehicle Brd On: Bray, Brett Division Director (Frank Breazeale) Bray, Brett Division Director (Stuart Hamilton) 345th Judicial District Court Travi ON: Keel, Patrick O. (Self) 5th Judicial District Court, Bowie ON: Burgess, Ralph Kolb (Self)


Alchemy Guide and Tips
10 Jun 2019Official Alchemy Game Guide: https://global.elchronicle.io/archives/2229
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Official Alchemy Game Guide: https://global.elchronicle.io/archives/2229
By navigating to Inn > Alchemy&Cooking you can b...
El Chronicle is a great game for mobile phones. It allows you collect and build up heroes, battle enemies, complete quests, earn loot, and conque...