Modern programming languages abstract a lot of low-level details of how our code works. Nonetheless, a good understanding of underlying computer science concepts can help you write better code… and pass technical interviews 😉 In the previous part of this article we introduced arrays, lists, and dynamic arrays. Now, we will look into the operations they support and how fast those operations are.
In the first part of the article we introduced three fundamental data structures:
- an array — a collection of elements stored in the memory as a single, continuous block of data
- a list — a collection of elements, each containing a link to the next element
- a dynamic array — an array that is resized to fit all elements without wasting too much space
Let’s compare those data structures. What operations do they support? How fast are they?
A basic understanding of time complexity and big-O notation is required as I use them extensively. If you’re not familiar with those concepts, HackerRank has a great video-explanation.
Let’s dig in!
What operations are supported by those data structures? What is their time complexity?
(In this section I denote the size of the array as n)
Array
“Vanilla” arrays are dead simple. We can:
- access an element given its index — in O(1) time. We know exactly where each element is located in memory, so we can access it very quickly.
That’s all. We can’t add or remove new elements (arrays always have a constant size).
Dynamic array
Dynamic arrays are more interesting. As with “vanilla” arrays, given an index, we can access a corresponding element in constant time. Dynamic arrays also support adding and removing elements.
Adding an element
- at the end of the list — takes, on average, O(1) time. Remember that some insertions will take O(n) time.
- at the beginning of the list, or somewhere in the middle — takes linear time. To insert a new element in the middle of the list, we have to “shift” all preceding elements by one position (see illustration below). We have to copy a portion of the array — O(n) elements, so this operation takes O(n) time.
Removing an element
- from the end of the list — takes, on average, O(1) time. Again, some insertions are slow and take linear time.
- from somewhere else in the list — takes O(n) time. As with adding an element in the middle, we have to shift all preceding elements — this time in the opposite direction (see illustration below). Thus, removal will take O(n) time.
Linked List
In a linked list, accessing an element with a given index i
is a bit more
complicated. As we don’t know where that element can be found in memory, we have
to iterate through the list until we find it. This will take O(n) time.
That’s significantly slower than other data structures we discussed.
Lists allow adding and removing elements too.
Adding an element
-
at the beginning of the list - is just a matter of changing a few pointers, so it can be done in O(1) time. We have to change the value of
head
so that it points to our new elementNEW
and setNEW.next_element
so that it points toA
(see illustration below). - somewhere in the middle — can always be done in O(n) time. First, we need to find the spot where we want to insert the element — this will take O(n). Inserting the element can be done in O(1) time, so the whole operation takes O(n) + O(1) = O(n) time.
- at the end of the list — if we keep a reference to the last object, we can do this in O(1) time! Otherwise, we have to iterate through the entire array to find the last element. This will take O(n) time. Implementations of a link list typically include that reference to the last object to keep this operations quick.
Removing an element
- from the beginning — takes O(1). As with adding the element at the beginning of the list, we only need to change a few pointers.
- from anywhere else in the list — takes O(n) time. We have to find the element first (which will take O(n) time) and remove it. To remove the element
C
we change the value ofB.next_element
so that it points toD
. That’s it.
That’s it! You know quite a lot about arrays and lists now. You should probably practice some interview questions!
In the third (and last) part, we’ll investigate why arrays can be significantly faster than linked lists when iterate through elements.
Thanks for reading!


Musician Nanarin:
Could you perhaps find out what would make him happy? I love Barbado... Please ask his friends what he wants the most. Start with the Dwarves in this village, and don't you dare mention my name!
Will you please do this for me?


THE MAN IN THE IRON MASK 1998 A film review by Timothy Voon Copyright 1998 Timothy Voon 1 :-( for Leo and the boys
Cast: Leonardo DiCaprio, Jeremy Irons, John Malkovich, Gerard Depardieu, Gabriel Byrne, Anne Parillaud, Judith Godreche, Peter Sarsgaard, Hugh Laurie Director: Randall Wallace Producers: Randall Wallace and Russ Smith Screenplay: Randall Wallace based on the novel by Alexandre Dumas
Hollywood has an annoying tendency to transform great classical pieces of literature into whatever they fancy. If these changes were any good then perhaps one can say – oh, that was neat; but when they are sloppily done, one can only grit their teeth, rip at the seating material with their finger nails and wait for the movie's end.
THE MAN IN THE IRON MASK is by no means a faithful adaptation of the Alexandre Dumas novel on which it is based. The question is did screen writer/director newbie Randall Wallace even try to be loyal?
So let's forget about the story for the moment, and focus on the young star of the moment, Leonardo Di Caprio. Hot off the heels of TITANIC, this movie vehicle merely cashes in on the enormous popularity generated from the aforementioned. His performance here merely ranges from pure pouty (Evil King Louis) to pure innocence (Good Prince Phillipe) with little in between, so much for dramatic range! He was by far better in Titanic. Then there are the veterans of stage and screen. Jeremy Irons (Aramis), very much reprises his priestly persona that worked brilliantly in THE MISSION. I still can't get over John Malkovich's awkward American accent as Athos. Fortunately, there is no such discrepancy between speech and character with Gerard Depardieu. His role as Porthos, farts and all, is the comic relief in this sullen movie. Gabriel Byrne an ever reliable actor is the loyal, faithful D'Artagnan who carries a mysterious secret with him.
Overall, THE MAN IN THE IRON MASK is mildly entertaining, but not a good movie by any standard. There are some memorable scenes like Leo Di Caprio looking his prettiest whilst moon gazing, a damsel in distress who leaps to her death for selling herself cheap. And when the Four Muskateers dressed in elegant garb, brandishing swords and fencing side by side, yell slogans like ‘All for One and One for All' – touching but hardly the grand Dumas epic it should have been.
Timothy Voon e-mail<EMAIL_ADDRESS>Movie Archives http://us.imdb.com/M/reviews_by?Tim+Voon Hugues Bouclier's Movies in Melbourne http://www.labyrinth.net.au/~bouclier/week/movies.html
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


📅 (2022-09-15 02:05:39 UTC)
# Packages matching: installed # Name # Installed # Synopsis base-bigarray base base-threads base base-unix base conf-findutils 1 Virtual package relying on findutils conf-gmp 4 Virtual package relying on a GMP lib system installation coq 8.13.1 Formal proof management system num 1.4 The legacy Num library for arbitrary-precision integer and rational arithmetic ocaml 4.11.2 The OCaml compiler (virtual package) ocaml-base-compiler 4.11.2 Official release 4.11.2 ocaml-config 1 OCaml Switch Configuration ocamlfind 1.9.5 A library manager for OCaml zarith 1.12 Implements arithmetic and logical operations over arbitrary-precision integers # opam file: opam-version: "2.0" synopsis: "A Coq plugin to add reduction side effects to some Coq reduction strategies" maintainer: "Yishuai Li<EMAIL_ADDRESS>authors: "Hugo Herbelin" license: "MPL-2.0" tags: "logpath:ReductionEffect" homepage: "https://github.com/coq-community/reduction-effects" bug-reports: "https://github.com/coq-community/reduction-effects/issues" depends: [ "coq" {>= "8.10"} "cppo" {>= "1.6.8"} ] build: [make "-j%{jobs}%"] run-test: [make "-j%{jobs}%" "test"] install: [make "install"] dev-repo: "git+https://github.com/coq-community/reduction-effects.git" url { src: "https://github.com/coq-community/reduction-effects/archive/v0.1.4.tar.gz" checksum: [ "md5=1f6c0770a41952367eca4c137ea1783e" "sha512=b984536b9657e79f5d39e7ba204906f61d92dc51027ea31005f8b6cc5f42595ec99b7516917b7461157e9ea46293a86207c26a435963582e524cb04b20496173" ] }
true
Dry install with the current Coq version:
opam install -y --show-action coq-reduction-effects.0.1.4 coq.8.13.1
Dry install without Coq/switch base, to test if the problem was incompatibility with the current Coq/OCaml version:
true
opam list; echo; ulimit -Sv 4000000; timeout 4h opam install -y --deps-only coq-reduction-effects.0.1.4 coq.8.13.1
# Packages matching: installed # Name # Installed # Synopsis base-bigarray base base-threads base base-unix base conf-findutils 1 Virtual package relying on findutils conf-gmp 4 Virtual package relying on a GMP lib system installation coq 8.13.1 Formal proof management system num 1.4 The legacy Num library for arbitrary-precision integer and rational arithmetic ocaml 4.11.2 The OCaml compiler (virtual package) ocaml-base-compiler 4.11.2 Official release 4.11.2 ocaml-config 1 OCaml Switch Configuration ocamlfind 1.9.5 A library manager for OCaml zarith 1.12 Implements arithmetic and logical operations over arbitrary-precision integers The following actions will be performed: - install dune 3.4.1 - install cppo 1.6.9 ===== 2 to install ===== <><> Gathering sources ><><><><><><><><><><><><><><><><><><><><><><><><><><><><> [cppo.1.6.9] downloaded from cache at https://opam.ocaml.org/cache [dune.3.4.1] downloaded from cache at https://opam.ocaml.org/cache <><> Processing actions <><><><><><><><><><><><><><><><><><><><><><><><><><><><> -> installed dune.3.4.1 [ERROR] The compilation of cppo failed at "/home/bench/.opam/opam-init/hooks/sandbox.sh build dune build -p cppo -j 4". #=== ERROR while compiling cppo.1.6.9 =========================================# # context 2.0.7 | linux/x86_64 | ocaml-base-compiler.4.11.2 | https://opam.ocaml.org#0fc5b3d7 # path ~/.opam/ocaml-base-compiler.4.11.2/.opam-switch/build/cppo.1.6.9 # command ~/.opam/opam-init/hooks/sandbox.sh build dune build -p cppo -j 4 # exit-code 2 # env-file ~/.opam/log/cppo-10664-876af6.env # output-file ~/.opam/log/cppo-10664-876af6.out ### output ### # [...] # 21 | (libraries unix str)) # (cd _build/default && /home/bench/.opam/ocaml-base-compiler.4.11.2/bin/ocamlopt.opt -w -40 -g -I src/.cppo_main.eobjs/byte -I src/.cppo_main.eobjs/native -intf-suffix .ml -no-alias-deps -o src/.cppo_main.eobjs/native/cppo_main.cmx -c -impl src/cppo_main.ml) # Command exited with code 2. # Fatal error: exception Sys_error("No space left on device") # Raised by primitive operation at Stdlib.close_out in file "stdlib.ml", line 385, characters 19-27 # Called from Stdune__exn.protectx in file "otherlibs/stdune/exn.ml", line 14, characters 4-13 # Called from Stdune__exn.protectx in file "otherlibs/stdune/exn.ml", line 12, characters 8-11 # Re-raised at Stdune__exn.protectx in file "otherlibs/stdune/exn.ml", line 18, characters 4-11 # Called from Stdlib.at_exit.(fun) in file "stdlib.ml", line 553, characters 62-65 # Called from Stdlib.do_at_exit in file "stdlib.ml" (inlined), line 556, characters 20-39 # Called from Stdlib.exit in file "stdlib.ml", line 559, characters 2-15 # Called from Main in file "bin/main.ml", line 100, characters 4-10 <><> Error report <><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><> +- The following actions failed | - build cppo 1.6.9 +- +- The following changes have been performed | - install dune 3.4.1 +- # Run eval $(opam env) to update the current shell environment The former state can be restored with: opam switch import "/home/bench/.opam/ocaml-base-compiler.4.11.2/.opam-switch/backup/state-20220915003424.export"
true
No files were installed.
true


Register
Log In
Home
Catalogue
Get yourself a galaxy.
Choose from over one hundred billion galaxies
Learn More


The next number you can use for a ToIP Deliverable is:
...
Don't put this number into the README.md or folder name for your new Deliverable Proposal until just before you're ready to submit a PR. If there's a lag between when you grab this number and when you submit the PR, there's a chance that someone else will use your number before you do.


Sharing a background
If you've made a background template you like, you can send it to others for their use.
To share a background template:
Drag the desired background template to Finder, Mail, iChat, or one of several other supported Mac applications.
See also
Importing a background template
Working with backgrounds
Background Topics


My first Web Page
Hi, my name is
Anakin Skywalker
Analytical, goal oriented leader with proven track record in management and
enforcement Space Fleet Operations or Frontend Development. Wide range of
hands-on experience, including:
- Large scale construction projects oversight
- Advanced forms of mind control
- Planetary scale demolitions operations
- Fugitive recovery services
"
Together we can rule the galaxy


Audit access tokens
-------------------
Endpoint:
https://auth.iudx.org.in/auth/v1/audit/tokens
Description:
This API allows a "data consumer" or a "data provider" to audit their
tokens.
Called by:
A "data provider" or a "data consumer" with a valid class-3 or above certificate.
Methods:
POST
Body in JSON format:
{
"hours" : <number of hours for which the audit-report has to be generated>
}
HTTP response code:
200
If audit report has been successfully fetched.
403
If the certificate class is < 3
Using pyIUDX SDK:
from pyIUDX.auth import auth
iudx_auth = auth.Auth("certificate.pem","private-key.pem")
iudx_auth.audit_tokens(5) # audit report for last 5 hours
CURL example:
Request:
curl -XPOST https://auth.iudx.org.in/auth/v1/audit/tokens
--cert certificate.key --key private-key.key
-d '{"hours": 5}'
Response:
200 OK
content-type : "application/json"
{
"as-consumer" : [
{
"token-issued-at" : "2019-08-08T03:29:50.779Z",
"expiry" : "2019-08-08T04:29:50.779Z",
"introspected" : true,
"revoked" : false,
"expired" : false,
"certificate-serial-number" : "5badd8f2b7d2c8cb0413883c7d023624543e6802",
"certificate-fingerprint" : "8b:dd:a4:ab:24:88:21:6a:51:2f:13:49:00:26:1f:cb:dc:86:df:70",
"request": [
{
"id": "rbccps.org/9cf2c2382cf661fc20a4776345a3be7a143a109c/rs1.com/resource-1",
"methods" : [
"GET"
],
"apis" : [
"/latest"
],
"body": {
"key": "value"
}
}
]
},
...
],
"as-provider" : [
{
"consumer"<EMAIL_ADDRESS>"token-hash" : "8be0e684cdf5f9f802704f580d7d39a11f6acec4b157afa1d20afd7497595105",
"token-issued-at" : "2019-08-08T03:29:50.779Z",
"expiry" : "2019-08-08T04:29:50.779Z",
"introspected" : true,
"revoked" : false,
"expired" : false,
"certificate-serial-number" : "5badd8f2b7d2c8cb0413883c7d023624543e6802",
"certificate-fingerprint" : "8b:dd:a4:ab:24:88:21:6a:51:2f:13:49:00:26:1f:cb:dc:86:df:70",
"request": [
{
"id": "rbccps.org/9cf2c2382cf661fc20a4776345a3be7a143a109c/rs1.com/resource-1",
"methods": [
"GET"
],
"apis" : [
"/latest"
],
"body": {
"key": "value"
}
}
]
},
...
]
}
Where:
1. "certificate-fingerprint" is the sha1 fingerprint of the consumer certificate.
2. "token-hash" is the sha256 hash of the token.
See also:
token API:
http://auth.iudx.org.in/token.html
token introspect API:
http://auth.iudx.org.in/token-introspect.html
token revoke API:
http://auth.iudx.org.in/token-revoke.html


| < Day Day Up > |
5.4 SwarmingLet's consider group behavior as yet another illustration of how to use potential functions for game AI. Specifically, let's consider swarming. This is similar to flocking, however the resulting behavior looks a bit more chaotic. Rather than a flock of graceful birds, we're talking about something more like an angry swarm of bees. Using potential functions, it's easy to simulate this kind of behavior. No rules are required, as was the case for flocking. All we have to do is calculate the Lenard-Jones force between each unit in the swarm. The attractive components of those forces will make the units come together (cohesion), while the repulsive components will keep them from running over each other (avoidance). Example 5-4 illustrates how to create a swarm using potential functions. Example 5-4. Swarmingvoid DoUnitAI(int i) { int j; Vector Fs; Vector Pfs; Vector r, u; double U, A, B, n, m, d; // begin Flock AI Fs.x = Fs.y = Fs.z = 0; Pfs.x = 0; Pfs.y = Units[i].fLength / 2.0f; if(Swarm) { for(j=1; j<_MAX_NUM_UNITS; j++) { if(i!=j) { r = Units[i].vPosition - Units[j].vPosition; u = r; u.Normalize(); A = 2000; B = 10000; n = 1; m = 2; d = r.Magnitude()/ Units[i].fLength; U = -A/pow(d, n) + B/pow(d, m); Fs += VRotate2D( -Units[i].fOrientation, U * u); } } } Units[i].Fa = Fs; Units[i].Pa = Pfs; // end Flock AI } Here, again, the part of this code that calculates the force acting between each unit with every other unit is the same force calculation we used in the earlier examples. The main difference here is that we have to calculate this force between each and every unit. This means we'll have nested loops that index the Units array calculating the forces between Units[i] and Units[j], so long as i is not equal to j. Clearly this can result in a great many computations as the number of units in the swarm gets large. Later we'll discuss a few things that you can do to optimize this code. For now, take a look at Figure 5-5, which illustrates the resulting swarming behavior. Figure 5-5. SwarmIt's difficult to do justice to the swarm with just a snapshot, so you should download the example program and try it for yourself to really see what the swarm looks like. In any case, Figure 5-5 (A) illustrates how the units have come together. Figure 5-5 (B) shows the paths each unit took. Clearly, the paths swirl and are intertwined. Such behavior creates a rather convincing-looking swarm of bees or flies. You also can combine the chase and obstacle avoidance algorithms we discussed earlier with the swarming algorithm shown in Example 5-4. This would allow your swarms to not only swarm, but also to chase prey and avoid running into things along the way. Example 5-5 highlights what changes you need to make to the function shown in Example 5-4 to achieve swarms that chase prey and avoid obstacles. Example 5-5.  Swarms are not the only things for which you can use this algorithm. You also can use it to model crowd behavior. In this case, you'll have to tune the parameters to make the units move around a little more smoothly rather than erratically, like bees or flies. Finally, we should mention that you can combine leaders with this algorithm just as we did in the flocking algorithms in the previous chapter. In this case, you need only designate a particular unit as a leader and have it attract the other units. Interestingly, in this scenario as the leader moves around, the swarm tends to organize itself into something that resembles the more graceful flocks we saw in the previous chapter. |
| < Day Day Up > |


Officials dismiss speculation on HC
‘No directive to identify land for court’
by Staff ReporterDistrict authorities have dismissed speculation that the G.N. Rao committee has ordered officials to identify land near Orvakal for construction of a building for High Court.
According to sources present at the meeting of district authorities and the committee, Mr. Rao had not specifically asked for land for the High Court. Mr. Rao is the convenor of the Expert Committee constituted to suggest strategies for all-round development of the State.
The sources, however, say there is a government order which instructs the authorities to identify land around cities. “We have previously identified land at Orvakal for other purposes.”
However, Kurnool district Bar Association convenor Y. Jaya Raju said that they were confident of location of High Court in Kurnool. Lawyers met Mr. Rao after meeting district authorities and detailed the issue to him.
“After meeting Mr. Rao, we are confident that High Court would be shifted to Kurnool,” Mr. Raju said.
Mr. Raju said that he has been contacting members of other Bar associations in a bid to gather their support.
Protest planned
Meanwhile, the students have decided to continue their protests. B. Sriramulu, convenor of the students’ union joint action committee, has said that a massive protest has been planned at Tadepalli on November 22.
“Some 1,000 people will leave Kurnool on Thursday for Tadepalli to protest at the residence of Chief Minister Y.S. Jagan Mohan Reddy,” he has said.


Dick Blee Memorial Mountain Bike Race
Billings Montana
June 13, 1999
EXPERT MALE
Lewis Elliot
Jason Frank
Matt Hayes
Thomas Bass
John Behrens
Charlie Stocker
Todd Berg
Will Culpepper
Cahd McNeese
Dusty Terry
Dan Matza
EXPERT VET MALE
Graig Lammey
EXPERT JUNIOR MALE
Eric King
EXPERT FEMALE
Sian Mooney
SPORT MALE
Eric Meglasson
Peter Jensen
Randy Ristau
Doug Melios
Travis Kemp
Ric Heldt
Barrett Canning
Charlie Catchpole
Max Dangerfield
Richard Ruff
Brent Veig
Jason Selong
John Maxwell
Chris Kelsey
Eric Mortenson
Todd Bailey
Travis Frost
Clay Landry
Rick Gomez
Walter Brophy
Chris Kosine
Kevin Noctor
SPORT VET MEN
Jim Curran
Grant Harris
John McClahahan
Paul Andrews
SPORT MASTER MEN
Martin Rollefson
Garyh Brayko
Tye Hoskins
Michael Maxwell
David Kennedy
SPORT JUNIOR MEN
Dan Barry
Don Cole
SPORT WOMEN
Renee Duylaney
Amy Myfield
BEGINNER MEN
Earl Ross
John Shankland
Scott Hllly
Jason Witt
Craig Decker
Shawn Petrie
Jeffrey Dahmer
Mike Schlabach
BEGINNER VET MEN
Wayne Erlenbush
Tim Barnes
Perry Mckinney
BEGINNER MASTER MEN
Dave Shenton
BEGINNER JUNIOR MEN
Logan Onken
Dominic Muth
Mike Brandt
Ben Shenton
Allen McKinney
Paul Brandt
Eric Weddington
Sean Jones
BEGINNER WOMEN
Leslie Berg
Linda Cady-Hoffman
BEGINNNER VET WOMEN
Arvilla Steffan
BEGINNER JUNIOR WOMEN
Amber Bushnell


{% assign areas = 'Technical, Communication, Delivery, Leadership' | split: ', ' %} {% for level in site.data.levels %} {% if level.id == include.level %}
{{level.summary}}
The competencies for {{level.name}} are outlined below. Before reviewing them, it is helpful to review how to use these competencies.
| Area | Competency |
|---|---|
| {{area}} |
{{competency.summary}}{% if example-count > 0 %}, e.g.{% endif %} {% if example-count > 0 %}
Supporting URLs:
|


Dubai Metro LRS
Overview
History
Inception
Network
Basics
Locations
Tram
Facilities
Connectivity
Handicap
Security
Parking
Useage
NolCard
Regulations
Schedule
Previous
Next
Save & Exit


Spatial search (also called geospatial search) allows you to take data that has a geographic location & enhance the search results by limiting them to a physical area. Haystack, combined with the latest versions of a couple engines, can provide this type of search.
In addition, Haystack tries to implement these features in a way that is as close to GeoDjango as possible. There are some differences, which we’ll highlight throughout this guide. Additionally, while the support isn’t as comprehensive as PostGIS (for example), it is still quite useful.
The spatial functionality has only one non-included, non-available-in-Django dependency:
If you do not ever need distance information, you may be able to skip installing geopy.
You need the latest & greatest of either Solr or Elasticsearch. None of the other backends (specifially the engines) support this kind of search.
For Solr, you’ll need at least v3.5+. In addition, if you have an existing install of Haystack & Solr, you’ll need to upgrade the schema & reindex your data. If you’re adding geospatial data, you would have to reindex anyhow.
For Elasticsearch, you’ll need at least v0.17.7, preferably v0.18.6 or better. If you’re adding geospatial data, you’ll have to reindex as well.
| Lookup Type | Solr | Elasticsearch | Whoosh | Xapian | Simple |
|---|---|---|---|---|---|
| within | X | X | |||
| dwithin | X | X | |||
| distance | X | X | |||
| order_by(‘distance’) | X | X | |||
| polygon | X |
For more details, you can inspect http://wiki.apache.org/solr/SpatialSearch or http://www.elasticsearch.org/guide/reference/query-dsl/geo-bounding-box-filter.html.
Haystack prefers to work with Point objects, which are located in django.contrib.gis.geos.Point but conviently importable out of haystack.utils.geo.Point.
Point objects use LONGITUDE, LATITUDE for their construction, regardless if you use the parameters to instantiate them or WKT/GEOSGeometry.
Examples:
# Using positional arguments.
from haystack.utils.geo import Point
pnt = Point(-95.23592948913574, 38.97127105172941)
# Using WKT.
from django.contrib.gis.geos import GEOSGeometry
pnt = GEOSGeometry('POINT(-95.23592948913574 38.97127105172941)')
They are preferred over just providing latitude, longitude because they are more intelligent, have a spatial reference system attached & are more consistent with GeoDjango’s use.
Haystack also uses the D (or Distance) objects from GeoDjango, implemented in django.contrib.gis.measure.Distance but conveniently importable out of haystack.utils.geo.D (or haystack.utils.geo.Distance).
Distance objects accept a very flexible set of measurements during instantiaton and can convert amongst them freely. This is important, because the engines rely on measurements being in kilometers but you’re free to use whatever units you want.
Examples:
from haystack.utils.geo import D
# Start at 5 miles.
imperial_d = D(mi=5)
# Convert to fathoms...
fathom_d = imperial_d.fathom
# Now to kilometers...
km_d = imperial_d.km
# And back to miles.
mi = imperial_d.mi
They are preferred over just providing a raw distance because they are more intelligent, have a well-defined unit system attached & are consistent with GeoDjango’s use.
All engines assume WGS-84 (SRID 4326). At the time of writing, there does not appear to be a way to switch this. Haystack will transform all points into this coordinate system for you.
Indexing is relatively simple. Simply add a LocationField (or several) onto your SearchIndex class(es) & provide them a Point object. For example:
from haystack import indexes
from shops.models import Shop
class ShopIndex(indexes.SearchIndex, indexes.Indexable):
text = indexes.CharField(document=True, use_template=True)
# ... the usual, then...
location = indexes.LocationField(model_attr='coordinates')
def get_model(self):
return Shop
If you must manually prepare the data, you have to do something slightly less convenient, returning a string-ified version of the coordinates in WGS-84 as lat,long:
from haystack import indexes
from shops.models import Shop
class ShopIndex(indexes.SearchIndex, indexes.Indexable):
text = indexes.CharField(document=True, use_template=True)
# ... the usual, then...
location = indexes.LocationField()
def get_model(self):
return Shop
def prepare_location(self, obj):
# If you're just storing the floats...
return "%s,%s" % (obj.latitude, obj.longitude)
Alternatively, you could build a method/property onto the Shop model that returns a Point based on those coordinates:
# shops/models.py
from django.contrib.gis.geos import Point
from django.db import models
class Shop(models.Model):
# ... the usual, then...
latitude = models.FloatField()
longitude = models.FloatField()
# Usual methods, then...
def get_location(self):
# Remember, longitude FIRST!
return Point(self.longitude, self.latitude)
# shops/search_indexes.py
from haystack import indexes
from shops.models import Shop
class ShopIndex(indexes.SearchIndex, indexes.Indexable):
text = indexes.CharField(document=True, use_template=True)
location = indexes.LocationField(model_attr='get_location')
def get_model(self):
return Shop
There are two types of geospatial queries you can run, within & dwithin. Like their GeoDjango counterparts (within & dwithin), these methods focus on finding results within an area.
within is a bounding box comparison. A bounding box is a rectangular area within which to search. It’s composed of a bottom-left point & a top-right point, though provided you give two opposing corners in either order, Haystack will determine the right coordinates. It is faster but slighty sloppier than its counterpart.
Examples:
from haystack.query import SearchQuerySet
from haystack.utils.geo import Point
downtown_bottom_left = Point(-95.23947, 38.9637903)
downtown_top_right = Point(-95.23362278938293, 38.973081081164715)
# 'location' is the fieldname from our ``SearchIndex``...
# Do the bounding box query.
sqs = SearchQuerySet().within('location', downtown_bottom_left, downtown_top_right)
# Can be chained with other Haystack calls.
sqs = SearchQuerySet().auto_query('coffee').within('location', downtown_bottom_left, downtown_top_right).order_by('-popularity')
Note
In GeoDjango, assuming the Shop model had been properly geo-ified, this would have been implemented as:
from shops.models import Shop
Shop.objects.filter(location__within=(downtown_bottom_left, downtown_top_right))
Haystack’s form differs because it yielded a cleaner implementation, was no more typing than the GeoDjango version & tried to maintain the same terminology/similar signature.
dwithin is a radius-based search. A radius-based search is a circular area within which to search. It’s composed of a center point & a radius (in kilometers, though Haystack will use the D object’s conversion utilities to get it there). It is slower than``within`` but very exact & can involve fewer calculations on your part.
Examples:
from haystack.query import SearchQuerySet
from haystack.utils.geo import Point, D
ninth_and_mass = Point(-95.23592948913574, 38.96753407043678)
# Within a two miles.
max_dist = D(mi=2)
# 'location' is the fieldname from our ``SearchIndex``...
# Do the radius query.
sqs = SearchQuerySet().dwithin('location', ninth_and_mass, max_dist)
# Can be chained with other Haystack calls.
sqs = SearchQuerySet().auto_query('coffee').dwithin('location', ninth_and_mass, max_dist).order_by('-popularity')
Note
In GeoDjango, assuming the Shop model had been properly geo-ified, this would have been implemented as:
from shops.models import Shop
Shop.objects.filter(location__dwithin=(ninth_and_mass, D(mi=2)))
Haystack’s form differs because it yielded a cleaner implementation, was no more typing than the GeoDjango version & tried to maintain the same terminology/similar signature.
By default, search results will come back without distance information attached to them. In the concept of a bounding box, it would be ambiguous what the distances would be calculated against. And it is more calculation that may not be necessary.
So like GeoDjango, Haystack exposes a method to signify that you want to include these calculated distances on results.
Examples:
from haystack.query import SearchQuerySet
from haystack.utils.geo import Point, D
ninth_and_mass = Point(-95.23592948913574, 38.96753407043678)
# On a bounding box...
downtown_bottom_left = Point(-95.23947, 38.9637903)
downtown_top_right = Point(-95.23362278938293, 38.973081081164715)
sqs = SearchQuerySet().within('location', downtown_bottom_left, downtown_top_right).distance('location', ninth_and_mass)
# ...Or on a radius query.
sqs = SearchQuerySet().dwithin('location', ninth_and_mass, D(mi2)).distance('location', ninth_and_mass)
You can even apply a different field, for instance if you calculate results of key, well-cached hotspots in town but want distances from the user’s current position:
from haystack.query import SearchQuerySet
from haystack.utils.geo import Point, D
ninth_and_mass = Point(-95.23592948913574, 38.96753407043678)
user_loc = Point(-95.23455619812012, 38.97240128290697)
sqs = SearchQuerySet().dwithin('location', ninth_and_mass, D(mi2)).distance('location', user_loc)
Note
The astute will notice this is Haystack’s biggest departure from GeoDjango. In GeoDjango, this would have been implemented as:
from shops.models import Shop
Shop.objects.filter(location__dwithin=(ninth_and_mass, D(mi=2))).distance(user_loc)
Note that, by default, the GeoDjango form leaves out the field to be calculating against (though it’s possible to override it & specify the field).
Haystack’s form differs because the same assumptions are difficult to make. GeoDjango deals with a single model at a time, where Haystack deals with a broad mix of models. Additionally, accessing Model information is a couple hops away, so Haystack favors the explicit (if slightly more typing) approach.
Because you’re dealing with search, even with geospatial queries, results still come back in RELEVANCE order. If you want to offer the user ordering results by distance, there’s a simple way to enable this ordering.
Using the standard Haystack order_by method, if you specify distance or -distance ONLY, you’ll get geographic ordering. Additionally, you must have a call to .distance() somewhere in the chain, otherwise there is no distance information on the results & nothing to sort by.
Examples:
from haystack.query import SearchQuerySet
from haystack.utils.geo import Point, D
ninth_and_mass = Point(-95.23592948913574, 38.96753407043678)
downtown_bottom_left = Point(-95.23947, 38.9637903)
downtown_top_right = Point(-95.23362278938293, 38.973081081164715)
# Non-geo ordering.
sqs = SearchQuerySet().within('location', downtown_bottom_left, downtown_top_right).order_by('title')
sqs = SearchQuerySet().within('location', downtown_bottom_left, downtown_top_right).distance('location', ninth_and_mass).order_by('-created')
# Geo ordering, closest to farthest.
sqs = SearchQuerySet().within('location', downtown_bottom_left, downtown_top_right).distance('location', ninth_and_mass).order_by('distance')
# Geo ordering, farthest to closest.
sqs = SearchQuerySet().dwithin('location', ninth_and_mass, D(mi2)).distance('location', ninth_and_mass).order_by('-distance')
Note
This call is identical to the GeoDjango usage.
Warning
You can not specify both a distance & lexicographic ordering. If you specify more than just distance or -distance, Haystack assumes distance is a field in the index & tries to sort on it. Example:
# May blow up!
sqs = SearchQuerySet().dwithin('location', ninth_and_mass, D(mi2)).distance('location', ninth_and_mass).order_by('distance', 'title')
This is a limitation in the engine’s implementation.
If you actually have a field called distance (& aren’t using calculated distance information), Haystack will do the right thing in these circumstances.
In all cases, you may call the within/dwithin/distance methods as many times as you like. However, the LAST call is the information that will be used. No combination logic is available, as this is largely a backend limitation.
Combining calls to both within & dwithin may yield unexpected or broken results. They don’t overlap when performing queries, so it may be possible to construct queries that work. Your Mileage May Vary.


--- layout: post title: "Big Changes" date: 2012-01-05 00:54:46 +0000 permalink: /2012/01/05/big-changes/ category: Personal tags: - Life - Google - Jobs - Kennesaw redirect_from: - /blog/big-changes/ ---
Today I did one of the hardest things I have had to do: I turned in my notice that I would be leaving Kennesaw State University in February. It was hard because I consider my management and many of my coworkers to be friends and I genuinely do enjoy my job, but I now have the opportunity to start the next chapter of my life. At the end of February, I'll be moving to California and starting at Google as a Site Reliability Engineer!
It's a pretty exciting opportunity for me, and I'm looking forward to it very much, but I will miss the people at Kennesaw. It's been a good time, and had this opportunity not arisen, I probably would have stayed there for quite a while longer.
Change is good, even if it is a bit hard to do.


You have killed {{ request.session.male_kc }} male(s) versus {{ request.session.female_kc }} female(s).

You have saved {{ request.session.lives_saved }} lives in group scenarios.
{% endif %}
No stats recorded yet! Make your first decision.
{% endif %}
Total number of decisions made: {{ view.stats.total_decisions }}
Total kill count for individual decisions: {{ view.stats.kill_count }}
Total kill count for large decisions: {{ view.stats.group_kill_count }}
Total male kill count: {{ view.stats.male_kc }}
Total female kill count: {{ view.stats.female_kc }}
Total lives saved: {{ view.stats.lives_saved }}
{{ view.stats.get_confidence_preference_display }}
{{ view.stats.get_age_preference_display }}
{{ view.stats.get_status_preference_display }}


|
|||||||||
| PREV PACKAGE NEXT PACKAGE | FRAMES NO FRAMES |
See:
Description
| Interface Summary | |
|---|---|
| Disposable | Allows resources to be deterministicly reclaimed. |
| Link<T> | The Interface Link. |
| Class Summary | |
|---|---|
| DisposableGC | Specialized garbage-collector that invokes the. |
| DisposableReference | A reference, who's data can be disposed of using DisposableReference.dispose() method
invokation. |
| JBuffer | A direct buffer stored in native memory. |
| JBufferInputStream | IO InputStream class that reads data out of a JBuffer. |
| JFunction | A special memory peer to a function pointer. |
| JMemory | A base class for all other PEERED classes to native c structures. |
| JMemoryPool | Provides a mechanism for allocating memory to JMemory objects. |
| JMemoryPool.Block | A block of native memory allocated with malloc. |
| JMemoryReference | The Class JMemoryReference. |
| JNumber | A peered number pointer class that stores and retrieves number values from native/direct memory locations. |
| JStruct | Base class for peered pure structure classes. |
| LinkSequence<T> | The Class LinkSequence. |
| Enum Summary | |
|---|---|
| JMemory.Type | Used in special memory allocation. |
| JNumber.Type | Used to request a specific type of primitive that this number will be dealing with possibly allocating memory more efficiently to fit the primitive type. |
Native memory and IO management classes.
|
|||||||||
| PREV PACKAGE NEXT PACKAGE | FRAMES NO FRAMES |


What does your family listen to when they put up the Christmas tree?
Because mine listens to DMX t.co/7SUzadF9R…


.... . . . .N ORTON SECURE WEBPAGE ELIXIRE
BROUGHT TO YOU BY JENKINS CBT
PLEASE HGELP ME CLICK THIS LINK TO WIN
easy readabl e and i love the style ity kid friendly and afggood in life there is no git blame
MADE BY US : )) )
this is a web site
HOW DO YOU WEBSITE ? ? ? ? ? ?
do you like thje music
HELP LPE HLEP LP LPSPINNN!!!
Accept coocky accept my frend request accept cookies acce pt CookKiee accept
Accept cookie accept cookeir accept cokie accept cohokie accept cooky
help me no one ever taught me html aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa


--- layout: post title: For those challenged by design tags: [] status: publish type: post published: true meta: {} ---
In this case me!! Here is a fabulous tool Color Palette Creator, does what it says in the box. Allows you to specify a base colour and then generates hex based color palette for you. Marvelous!


Avoid holiday hangover - It's Your Money
by Brett MillardThe holiday season is upon us and this means that many Canadians will end up spending more money over the next month than they normally do.
Presents for loved ones, travel to see family, time off work and special events all add up and take a real toll on your wallet or credit card.
Canadian consumer debt is already at extreme levels and every dollar spent that could have instead gone to paying down your debt will cost you for the rest of your life.
I am not saying that you can’t enjoy the holidays at all, but you do need to have a plan to avoid a holiday hangover in the New Year.
Planning your holiday spending means not just budgeting for gifts but also the many other expenses that come with the holiday season.
To start, you need to be realistic with what you can afford and understand that you can’t afford to do everything. Once you’ve settled on an amount, here are a few steps you can take to stay on track:
Create a budget
Decide how much money you want to allocate to gifts, travel, entertainment and meals out. Once this budget has been created, stick to it.
Build a gift list
Instead of walking into the mall without a plan, write down who you are planning to buy a gift for and then spend some time thinking of ideas of what that person would like. It’s not the price of the gift that counts for most people but instead the meaningfulness.
Some extra time spent thinking up a great idea could keep you from overspending.
No impulsive buys
If you haven’t planned to buy it on your list, do you really need it? Even if it’s a “great deal”, there is no problem passing on it. If you’re not 100 per cent sure, sleep on it and go back the next day to make the purchase if you still think you should.
Fewer toys for your kids
This is probably the hardest tip to stick to but it’s important. Many toys that are purchased each December quickly end up in the back of a closet or the bottom of a toy chest. Plus, many children are going to get gifts from grandparents and other family members on top of what you buy for them.
When the excitement of Christmas morning is over, they really won’t notice if they ended up with five new toys or 10.
Don’t cave to peer pressure
Most commonly found at work, peer pressure can cause many to spend far more than they planned. If you have 25 co-workers, there is no reason why you should be buying a gift for each one.
If everyone else at the office does and you don’t want to be the sole cheapskate, consider making something at home that is personalized with meaning.
Be selective in holiday events
While it’s nice to try and attend every lunch, dinner and party, doing so may not fit into your budget. Consider if you’ll be seeing the same group of friends at more than one event and pick which one you’d like to attend the most.
It’s not just the cost of the food but also things like babysitters, taxi rides home and gifts for the host that pile up.
Plan now for next year
Once the holiday season is over, consider setting up a holiday fund for next year as one of your New Year’s resolutions. By putting a little bit aside each paycheque throughout the year, your budget won’t have the massive financial hit when the holidays arrive.
The holidays are a celebration and you can and should enjoy quality with family and friends. But a little bit of planning can go along way to ensure that you can do all of that without starting next year with an ugly financial hangover.


Programmers should not comment out code as it bloats programs and reduces readability.
Unused code should be deleted and can be retrieved from source control history if required.
See
- MISRA C:2004, 2.4 - Sections of code should not be "commented out".
- MISRA C++:2008, 2-7-2 - Sections of code shall not be "commented out" using C-style comments.
- MISRA C++:2008, 2-7-3 - Sections of code should not be "commented out" using C++ comments.
- MISRA C:2012, Dir. 4.4 - Sections of code should not be "commented out"


Supporting DIM
DIM is a product that is free to download and use. The source code for DIM is
open sourced, and free to anyone to enhance. You will never see
an ad in DIM. That is our committment.
We're all huge fans of Destiny. DIM came to life in those hours of gameplay
because we felt that pain of transferring gear between characters and forgetting
that one item, or trips down to the tower to unload your ROC strikes. DIM is
the tool that will help you get more gametime.
How can I contribute?
- Donate to DIM
-
We use PayPal
to accept donations. If DIM has made a difference in your gametime, support the team working on the project.
- Share the DIM with your friends!
-
Once you've experienced how easy it is to equip a loadout, you'll be hooked.
Share the fun with your friends!
- Do you have an idea for DIM?
-
Visit us on /r/destinyitemmanager
and let us know about your idea. You'll
hear from us as well as the community around DIM which is a great way to
iterate and improve an idea.
- I'm a developer/designer/enthusist and I'm looking to contribute to the source.
-
Visit us on GitHub
and send one of the contributors a message. We're more
than happy to accept pull requests. Join us as a contributor and join our
meetings where we talk about the next version, feature updates, or crushing bugs.


| Home | Libraries | People | FAQ | More |
A barrier is a simple concept. Also known as a _rendezvous_,
it is a synchronization point between multiple contexts of execution. The
barrier is configured for a particular number of tasks (n
),
and as tasks reach the barrier they must wait until all n
tasks have arrived. Once the n
-th
task has reached the barrier, all the waiting tasks can proceed, and the
barrier is reset.


Address: loading…
Balance: loading…
Status: loading…
Block height: loading…
Stats: loading…
Recipient
Amount
Message
⇢ ⇢


API model information
A data point for a product
| Property | Required | Data Type | Description | Example Values |
|---|---|---|---|---|
| Name | True | string | The name of the data field |
|
| Value | True | string | The value of the data field |
|
Use the JSON code below as an example of how this model will be serialized.
- {
- "Name": "description",
- "Value": "Got a Death Star porblem at your base? Take it out with this small craft (PS, aim for the 2-meter exhaust port). Buy now! Republic credits not accepted."
- }


A Business Role is defined as a named specific behaviour of a Business Actor participating in a given context. The actor performs the behaviour of the role.
A Business Role can be fulfilled by more than one Business Actor. Conversely, a Business Actor may fulfil more than one Business Role. For example, given a named teacher, their roles may include those in the domains.
A Business Role will usually exist in an organisation whether or not a given actor fulfils it or not.
A Business Role may be assigned to one or more Business Processes or Business Functions. A Business Interface or an Application Interface may be used by a Business Role, while a Business Interface may be part of a Business Role (Composition relationship).
The name of a Business Role should preferably be a noun.
Business. Active Structure.
Customer, Insurer, Supplier, Lecturer, Administrator, Buyer.


Other Products for Trust Services
Progress:
|
|
|
| Ideation and Research |
Product Development |
In-Production Code |
Longer-Term Innovation
Pre-generate Certs on Customer behalf
-
There are many times that a customer holds a valid cert with uncompromised keys, yet due to business or industry hard deadlines we need to issue them a new cert. Eg: The time chrome mandated all customers to have only SHA256 certs, when long term cert validity was to be cut short or when new identifiers were need in certs as ber CAB Forum. In all these cases we can reuse the same keys in a different cert package and reduce customer effort to submit new CSR.
-
Identify when new CSR is not required, and generate new cert for customer on our end.
The same means we use to scan and email customers about their soon unusable certs, can be automated and a new instant issued cert is sent
Master Customer Data Managment
-
This will be a good way of pinning down the kind of customers we are facing. Some simple things we can know about our customers are how many are brand driven, are high ticket buyers, are windows shopper or have high churn potential, etc., and then appraise the impact of business decisions on whatever actionable segments we decide.
-
Customer-centricity: Within Business Intelligence, the standard view is of linking tables around entities like order-number or account numbers. Instead data could be re-modelled around the entity of a customer, which should prepare it for better business insight down the pipeline. For instance, we can then easily slice our customer base in quite a few number of ways like by customer location, business size and type, ticket size and type, brand focus, churn rate, CLV or number and types of recorded interaction with different Symantec SSL channels.
Cyber Liability Issurance
-
New business: 1) Lucrative $2bn market. with no dominant providers. 2) companies in the service sector are showing 75% increase in cyber liability demands, climbing with the rate/visibility of cyber attacks, 3) that there is the push by the US government for companies to insulate themselves through cyber insurances. 4) It also appears that customers who most feel the financial impact of security breaches most are small businesses, which is our SSL customer base
-
Similar to how we talk to Netscap to sell warranty. Talks with provider of breach insurance - SysNet. They did not cover full cyberliability. Also, they structure the insurance which may divert most of the pay off to them to do a forensics assessment of whether breach was fraudulent. They were not interested in doing risk based tiering of pricing.
Developer: Ishita Verma
Advisor: Rick Andrews, Darren Noy
Year: 2014


We consumed a lot of Xinjiang Big Plate Chicken during work sessions... and I mean A LOT.
I mean, hey, who doesn't love chicken.
Especially after we have been channeling your focus at a highly sophisticated system for hours, we feel extra hungry and crave for some good food. That's when Xinjiang Big Plate Chicken, also known as Dapanji, comes to rescue.
It almost became a tridition for us to gather on Saturdays, order a Dapanji and work through the day with the fragrance of chicken free-flowing in the apartment. Whether that boosts our productivity remains an unanswered question. What was clear, however, was that, boy it smells good.
Oh, and it tastes good too. (Of course!)


{% extends "base.html" %} {% block title %}GoalWithMe{% endblock %} {% block content %} {% call macros.create_page("main") %}
Hello, {{ nickName }}! You must be new here. Click the button below to create a new user account.
Create User Account {% elif userProfile %}
Welcome back, {{ userProfile.UserName }}!
Go to Dashboard {% endif %}Note to visitors:
This site is super pre-Alpha, so expect widespread usability issues and broken features. I've only made it public so that I could use it while I'm developing it.


MapperProperty implementations.
This is a private module which defines the behavior of invidual ORM-mapped attributes.
Attached to a PropertyLoader to indicate a complementary reverse relationship.
Can optionally create the complementing PropertyLoader if one does not exist already.
Describes an object attribute that corresponds to a table column.
The list of columns describes a single object property. If there are multiple tables joined together for the mapper, this list represents the equivalent column as it appears across each table.
Instruments a Python property for use in query expressions.
subclasses ColumnProperty to provide composite type support.
Describes an object property that holds a single item or list of items that correspond to a related database table.
Construct a new PropertyLoader.