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new-top-student-classroom-language-a-grade-book--9787538267495.pdf
August 09, 2016
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a-perfect-darkness-9780061690358.pdf
November 30, 2016
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technology-and-the-diverse-learner-a-guide-to-cl-9780761931720.pdf
August 23, 2016
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bits-of-belonging-information-technology-water-a-9781439912591.pdf
October 09, 2016
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mother-and-daughter-paperback-9781236671363.pdf
November 19, 2016
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a-loeb-classical-library-reader-9780674996168.pdf
December 30, 2016
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ver-auml-nderung-des-corporate-images-in-folge-e-9783656659273.pdf
December 18, 2016
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violin-exam-pieces-grade-4-2016-2019-part-only-9780857364579.pdf
September 20, 2016
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the-problem-of-increasing-human-energy-paperback-9781463571184.pdf
December 12, 2016
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the-start-of-everything-9780749014209.pdf
September 06, 2016
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economics-of-the-iroquois-paperback-9781230226699.pdf
September 02, 2016
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the-truffle-mouse-9781407144863.pdf
November 15, 2016
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the-seven-secrets-of-successful-catholics-9780809137954.pdf
January 10, 2017
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24th-century-films-set-in-the-24th-century-star--9781156336465.pdf
November 27, 2016
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October 02, 2016
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the-social-media-bible-tactics-tools-strategies--9781491546505.pdf
August 05, 2016
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September 03, 2016
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positive-african-american-plays-for-children-boo-1-9781884163128.pdf
December 08, 2016
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on-the-table-by-the-window-the-journey-of-a-gay--9781457522710.pdf
November 01, 2016
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December 07, 2016
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how-to-enjoy-your-life-and-job-1-9780091906405.pdf
January 09, 2017
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lightweight-book-series-win-straight-through-ent-7-9787552244144.pdf
September 07, 2016
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the-detection-of-forgery-a-practical-9781508640684.pdf
January 25, 2017
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the-un-prescription-for-autism-a-natural-approac-9780814436639.pdf
January 25, 2017
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live-again-wholeness-after-divorce-paperback-9781596366367.pdf
August 20, 2016
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the-athletic-trainers-guide-to-psychosocial-inte-9781556427336.pdf
September 20, 2016
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2012-physical-winner-curriculum-college-entrance-9787107236440.pdf
January 06, 2017
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beyond-talent-creating-a-successful-career-in-mu-9780195382594.pdf
September 08, 2016
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bible-creation-truth-genesis-1-paperback-9781517709426.pdf
October 12, 2016
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the-master-of-the-world-the-graphic-novel-campfi-9789380028309.pdf
October 20, 2016
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joan-of-arc-and-sacrificial-authorship-paperback-9780268032609.pdf
November 24, 2016
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un-mundo-paralelo-cenoia-paperback-9781502993793.pdf
September 10, 2016
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a-winter-of-content-paperback-9781230404349.pdf
January 14, 2017
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study-guide-to-accompany-microeconomics-for-micr-9780321486011.pdf
October 06, 2016
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mandorla-9781553800293.pdf
December 25, 2016
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energy-third-grade-science-experiments-paperback-9781499690477.pdf
January 01, 2017
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a-treatise-on-the-law-of-executors-and-administr-9781236532930.pdf
October 13, 2016
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studio-international-volume-5-9781155091563.pdf
September 07, 2016
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henry-and-mudge-in-the-sparkle-days-9780689810190.pdf
August 21, 2016
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liberar-la-mente-arte-moderno-libro-de-colorear--1-9781530120307.pdf
December 02, 2016
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genuine-twelve-towers-li-yu-chinese-edition-9787807158813.pdf
October 05, 2016
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gate-of-darkness-circle-of-light-9781531808266.pdf
October 20, 2016
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if-you-won-the-lottery-paperback-9781424194025.pdf
October 21, 2016
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celtic-wales-5th-revised-edition-9780853727989.pdf
November 26, 2016
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holt-science-and-technology-2001-physics-directe-9780030554094.pdf
January 27, 2017
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literature-project-practice-book-9780076614141.pdf
September 04, 2016
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george-eliot-four-novels-complete-and-unabridged-9780760779668.pdf
November 28, 2016
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keys-to-performance-achieving-excellence-in-your-9780964243033.pdf
November 06, 2016
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fifty-strategies-for-teaching-english-language-l-9780139238550.pdf
January 05, 2017
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internet-dating-9781465376350.pdf
September 28, 2016
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a-system-of-rhetoric-in-a-method-entirely-new-co-2-9781170908112.pdf
September 09, 2016
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traite-des-faillites-et-banqueroutes-classic-rep-9781332487295.pdf
August 14, 2016
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sketching-user-experiences-the-workbook-paperbac-9780123819598.pdf
December 25, 2016
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elliot-a-soldier-x27-s-fugue-format-trade-cloth-9781559364522.pdf
December 22, 2016
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barbarians-of-wealth-9780470768143.pdf
November 17, 2016
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maintaining-children-in-school-the-contribution--9781900990431.pdf
January 26, 2017
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the-philosophy-skills-book-exercises-in-critical-9781441124562.pdf
September 20, 2016
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space-quest-jump-to-jupiter-paperback-9781465438270.pdf
August 15, 2016
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decentralized-governance-and-panchayati-raj-9788178359106.pdf
October 15, 2016
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golden-sequences-and-infinite-series-9788131800553.pdf
January 03, 2017
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swindle-9780439903455.pdf
December 07, 2016
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waxing-mythical-the-life-and-legend-of-madame-tu-9780719565526.pdf
January 14, 2017
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the-ghost-and-max-monroe-case-2-the-missing-zucc-9781771380188.pdf
November 29, 2016
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candice-olson-kitchens-and-baths-9780470889374.pdf
September 23, 2016
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new-york-lancet-volume-9-with-which-is-incorpora-9781130493962.pdf
September 01, 2016
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nj-ask-grade-4-language-arts-literacy-rea-new-je-9780738602844.pdf
September 14, 2016
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weather-an-act-of-man-paperback-9781518781704.pdf
December 22, 2016
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the-rover-boys-on-the-farm-or-last-days-at-putna-9781523427567.pdf
November 15, 2016
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fantastic-stories-of-the-imagination-december-20-9781633847415.pdf
September 28, 2016
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scholastic-success-with-writing-grade-2-9780545200783.pdf
December 13, 2016
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the-lion-tamer-x27-s-daughter-9780333739518.pdf
September 26, 2016
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wild-animals-magnetic-story-amp-play-scenes-magn-9781782445456.pdf
January 15, 2017
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cricket-dreaming-the-rites-of-summer-9781921221897.pdf
August 15, 2016
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workbook-for-handley-x2f-coon-x2f-marshall-s-pro-9781435428379.pdf
December 05, 2016
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a-thin-dark-line-paperback-9780553571882.pdf
October 10, 2016
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best-women-x27-s-erotica-2004-9781573441810.pdf
November 22, 2016
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a-world-without-walls-the-crystal-tablets-reveal-9781482553208.pdf
September 17, 2016
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computational-science-iccs-2002-international-co-9783540435914.pdf
November 22, 2016
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excel-2016-for-dummies-9781119077046.pdf
September 03, 2016
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improve-your-scales-violin-grade-3-new-edition-f-9780571537037.pdf
January 04, 2017
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village-vets-9780733335839.pdf
January 03, 2017
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luxe-european-travel-set-including-london-paris--9789888132096.pdf
September 14, 2016
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the-flying-beaver-brothers-and-the-fishy-busines-9780375864483.pdf
September 01, 2016
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dl-grain-and-oil-storage-studies-new-genuine-chi-9787500539551.pdf
October 25, 2016
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licensed-to-kill-hired-guns-in-the-war-on-terror-9781400097821.pdf
December 15, 2016
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mourning-for-pap-a-story-of-a-syrian-jewish-fami-9781888205312.pdf
December 06, 2016
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two-yehs-word-search-puzzle-book-state-my-50-sta-9781519152282.pdf
October 20, 2016
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social-sports-instructor-national-vocational-qua-9787040278491.pdf
October 05, 2016
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sabrina-x27-s-little-abc-book-of-gardening-large-9781459643055.pdf
November 10, 2016
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don-x27-t-forget-to-write-for-the-elementary-gra-9781118024317.pdf
November 11, 2016
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NYPH-CORNELL ONLY ACCEPTS/SPONSORS J-1 VISAS.
This application does not allow you to save a partially completed form and proceed filling it out later.
Please gather all relevant information before filling out this form in order to be able to submit it immediately after entering all of the data.
Use of Google Chrome or Firefox browser is recommended. If you encounter any technical issues with this web form, please email<EMAIL_ADDRESS>Dates and deadlines:
August 30 - Deadline for receipt of completed application (including recommendation letters) from candidates. Please note that we have a rolling admissions policy, therefore, we strongly encourage interested candidates to apply as early as possible.
On or before December 30 - Issuance of formal offers (12:00pm EST).
Stipends: Salaries are commensurate with the level of post graduate training.


First things first. We need to get the tooling ready so you can take full advantage of Node.js and its libraries to build the API for Emvents Inc. You will build this Node.js API using Express.js, ES6 features and testing that actually works.
Check new JavaScript features (ES6), at least arrow functions and let/const.
http://exploringjs.com/es6/
Install Node.js in your computer.
https://nodejs.org/en/download/
Install Postman.
https://www.getpostman.com/
Learn about git. You should git commit at least after completing each requirement.
https://git-scm.com/docs/
Review the basic HTTP methods.
https://en.wikipedia.org/wiki/Hypertext_Transfer_Protocol#Request_methods
Create a Github repo for this project.
You and your coding partner can collaborate using this repo.

You should start by creating and running a simple Hello World from your terminal.
https://nodejs.org/api/synopsis.html
Check the Hello World results in your browser.
You should use npm to initialize a new project Node project. Provide a description and see the resulting package.json file.
https://docs.npmjs.com/
Use npm to install Express.js.
http://expressjs.com/en/starter/installing.html
Add Express.js to your project and add a GET and a POST handler to send and receive data from the client.
http://expressjs.com/en/starter/hello-world.html
Use Postman to test your basic service works.
Refactor your Express.js code to use ES6 features (const / let and arrow functions when convenient)


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Melasma is a tan or dark skin discoloration. Melasma is particularly common in women, especially pregnant women and those who are taking oral or patch contraceptives or hormone replacement therapy (HRT) medications. The symptoms of Melasma are dark, uneven well demarcated hyper pigmented patches commonly found on the upper cheek, nose, lips, upper lip, and forehead. Every person has a different skin type and hence needs different treatment so it is very essential to find the right dermatologist. ClinicGen.Next™’s Dermatology clinic – an ultra modern skin clinic in West Delhi, is trusted for meticulously providing all kind of skin oriented treatment with wonderful results. Our primary focus is your comfort.
Causes: Melasma can occur because of following major reasons –
Treatment: Dr.Megha provides a variety of Melasma Treatment in Pitampura, Delhi at her skin Clinic, but not all treatments are recommended for everyone. So, a thorough examination of the condition is followed by a customized treatment for every individual patient.
* Results may vary person to person.


Hello.
My name is {{FIRST_NAME}} {{LAST_NAME}} and this is my resume my story
- Birthday:{{BIRTHDAY}}
- Tel:{{PHONE_NUMBER}}
- Email:{{EMAIL}}
- Address:{{ STREET }}, {{ CITY }}
01. Experience
{% foreach(experiences) %}
{% endforeach %}
[[TIME]]
[[COMPANY_NAME]] / [[POSITION]]
[[DESCRIPTION]]
02. Education
{% foreach(education) %}
{% endforeach %}
[[TIME]]
[[ COLLEGE_NAME ]]
[[ SUBJECT ]] - [[ QUALIFICATION ]]
03. Skill
-
{% foreach(skills) %}
-
[[ NAME ]]
{% endforeach %}


Visitor Centre in Iceland / Andersen & Sigurdsson Architects
- Curated by Paula Pintos
- about 6 hours
Visitor Center · Borgarfjörður Eystri, Iceland
- version="1.0" encoding="UTF-8"? Architects: Andersen & Sigurdsson Architects
- AreaArea of this architecture projectArea: 345.0 m2
- version="1.0" encoding="UTF-8"?YearCompletion year of this architecture project Year: 2019
- version="1.0" encoding="UTF-8"?PhotographsPhotographs: Christopher Lund
- version="1.0" encoding="UTF-8"?ManufacturersBrands with products used in this architecture project Manufacturers: Ceramica Vogue, Hormann, Schuco, Vitral
- Lead Architects Thorhallur Sigurdsson, Ene Cordt Andersen
- Design Team Thorhallur Sigurdsson, Ene Cordt Andersen, Kim Bendsen, Laura Ioana Voinescu, Antoine Piquemal
- Clients The Municipality of Borgarfjörður Eystri
- Engineering Efla
More Specs Less Specs
Text description provided by the architects. Placed just a couple of meters above sea level overlooking Borgarfjordur Eystri, its harbour, and Hafnarholmi, the Visitor Centre appears as a precise square-shaped monolith guarding the harbor and its surroundings. A monolith divided into a series of spaces, interior, and exterior, facing different activities and landscapes in the area; the sky, the deep blue fjord, the characteristic mountains, and the local biosphere.
Iceland is truly an island with a remote location in the middle of the Atlantic Ocean. With the majority of the country’s inhabitants living on the southwest corner of the island, Borgarfjordur Eystri has a remote location being the northernmost fjord of Iceland's East Fjords. Iceland has a population of 360.000 people and is visited by over two million tourists each year. Despite vast distances and sometimes difficulties to access, Borgarfjordur Eystri has not been spared by the increase in tourists to the country in recent years.
The Visitor Centre is situated on the outskirts of the tiny village of Bakkagerdi, inhabited by a mere 130 people. Seafaring and farming are still the major local industries, but tourism is growing rapidly.
In 2015 the municipality held an architectural competition for a building on the waterfront, a place to serve the needs of fishermen and harbour authorities as well as being a focal point to service tourists. The area has an extensive birdlife, with migratory birds such as eiders and puffins gathering in the summertime. About 40,000 tourists visit annually and the new building is expected to ensure a minimum interference between the activities of the harbour and the activities of the tourists.
Since the building is shared by locals and tourists its function will be variable throughout the year. In summertime, the focus will be on the many tourists visiting the area to see the puffins in the small peninsular by the harbour. In wintertime, space can be used by the locals for smaller cultural and social events. The ground floor of the building is primarily used by port authorities and fishermen and it houses a small port office, bathrooms, and a garage. The first floor houses a small café and the second floor is an exhibition space that will have exhibitions focused on showing aspects of the surrounding nature, the sea, the seals, the mountains and the birds.
The building is a cube-shaped monolith where alternating sections have been cut away to allow for outdoor spaces around the building. A diagonally positioned staircase connects all of its three floors, separating each floor into an interior and exterior space and allowing the cube to wedge naturally into the landscape.
The building is a total of 345 square meters and can be entered both from the top level and the ground level. The building has a robust character and materiality that accommodates the nature of its different users well and also enables it to be unmanned part of the year. The texture of the building emphasizes it´s simple nature and humble existence in the spectacular surroundings. The in-situ cast concrete is mixed with colourful regional stone aggregates giving a rough and variable texture that changes throughout the day and the seasons. The building is simple in execution, with polished concrete floors and black steel railings, doors and window frames.


A famous famfamfam iconset (converted to CSS sprite)
used for supplying icons for both taskbar and window.
Sadly, there's no easy way to make custom icons stateful
like jQuery UI icons, but with some more CSS, that can
be accomplished too.
Tip: check the famfamfam sprite stylesheet
here.


About Me
Hello, my name's Erik Stephenson and I hail from Austin, MN otherwise known as Spamtown USA. Outside of coding I enjoy playing and watching sports, especially basketball, spending time outdoors and catching some live music whenever possible.
I decided to start my coding journey in the fall 2017 after deciding I wanted to change career paths. I am hoping after graduating, I will be able to use the skills I learned in the course to do just that and pursue a career in tech.


Writing your PhD
Step one
Sit down to write.
Source.
Why?
- The right editor can make a big difference.
- A good editor will:
- enable code snippets
- have bibliography integration
- let you compile LaTeX directly
- help you manage your project
- save you a lot of typing
Why?
- An excellent text editor will:
- be easily customisable
- work cross platform
- have direct git integration
- do half the work for you
Which editor?
- Often users will stick with the editor that comes with the LaTeX installation.
- = TexShop
- = Texworks
- = Various
- Often they are not the most sophisticated editors.
- Advanced features may be difficult to configure.
Which editor?
- In my experience, the following are the best editors.
- None are LaTeX specific, but for software development.
- All (except Sublime) are open source.
- Good: they are more advanced, and have bigger
communities working on them.
- Bad: they come with bigger installations and use
more system resources.
Atom
- Highly Customisable
- Excellent LaTeX integration
(latextools package)
- Direct git integration
- Excellent unicode insertion.
- Occasional difficulties with large files.
- Smaller community compared to Sublime and VSCode
Sublime Text
- Similar to Atom, but proprietary (i.e. not open source)
- Not free, but kinda free.
Sublime Text
- Excellent LaTeX integration (also latextools package)
- Less buggy than Atom
- Looks beautiful.
- Unicode character insertion not good (anymore).
- Git integration ok, but takes some setting up.
Visual Studio Code
- Made by Microsoft, but open source.
- Probably the best all-round text editor.
VS Code
- Excellent git integration (Microsoft own Github)
- Very stable
- Very easy to customise
- Unicode integration is outstanding.
- LaTeX integration not great.
- Reverse search difficult to configure
- Bibliography search not as good as others.
Emacs
- Open Source.
- Long history, big community
Emacs
- Small installation.
- Lots beyond LaTeX
- Excellent LaTeX integration through AUCTeX and RefTeX.
- You can play tetris/snake etc 😀
- Not intutive to customise (lisp script, GUI very dense)
- No project overview by default, but possible.
- You can play tetris/snake etc 😒
Vim
- Terminal editor
- Long history, large community
- Small installation
- LaTeX integration through VimLaTeX or vimtex.
- Bonus: You look objectively more awesome
writing in a terminal window 😎
(I don't use Vim enough to give advantages/disadvantages)
Using your editor the right way
Getting started
- Download your editor of choice.
- Install LaTeX builder.
- Install LaTeX language support.
- Go.
Demo
- Go to https://atom.io, download and install.
- Open, hit
ctrl+,
/cmd+,
and click
'install' on the left.
- Search 'latextools' and install it
- Search for 'language-latex'
- Search for and install 'pdf-view'
- Now, you're good to go.
RMarkdown
- If you use RMarkdown, there is no dedicated environment, like RStudio.
- But, you can follow the above steps to enable markdown support, then call knitr from your terminal.
- To do so, run the commands:
$ R
> install.packages('rmarkdown')
> rmarkdown::render('FILE.Rmd')
Atom + Latextools: Basic Workflow
- Open .tex file.
- Write something latex-y
- Hit
ctrl-alt-b
or cmd-alt-b
- It should then open in the pdf-viewer at the side.
Other commands: latextools
ctrl-l escape
/cmd-l escape
= close console
ctrl-l ctrl-n
/cmd-l cmd-n
= wrap in environment
ctrl-l j
/cmd-l j
= jump to pdf
Saving yourself time: snippets
- Atom, Sublime, VSCode etc. allow you to define your own pieces of code, that insert wider
chuncks.
- Idea
- type a sequence of characters (snippet) and hit
tab
.
- The content of the snippet will then be inserted
Writing Snippets in Atom
- Snippets need four things:
- Scope = which language it will work in
- Name = for comprehension
- Prefix = the shortcut
- Body = what is inserted
Clarity
- Useful for non-latin characters and diacritics.
- LaTeX markup is messy, especially with symbols.
- Some are intutive:
\v{s}
= š
- Others are not:
\textipa{@}
= ə
Unicode
- Unicode is useful because you type the characters directly, using a standardised code.
- Requirements:
- Unicode compatible font.
- The right code.
- Ability to input the code.
Unicode: Advantages
- Your writing is a lot more readable in the editor.
- You can reuse the code: just copy paste into email, markdown documents, excel, word etc.
- Works well in bibliographies (with Biber).
Inputing the code
- System:
ctrl-shift-u
in linux.
- Within the editor:
- Atom: Character Table
- VSCode: Insert Unicode
- Emacs:
ctrl-x 8 enter
- Sublime: not honestly sure. There used to be Character Table, but it's disappeared of late.
Handling larget documents
- For a thesis, it's a good idea to keep each chapter as its own file, and compile from a master file.
- Use the
\include{}
command.
- (or use
\input{}
)
\documentclass{memoir}
...
\title{Thesis}
\author{G. K. Candidate}
\date{Summer 2020}
\begin{document}
\include{intro.tex}
\include{theoretical_background.tex}
\include{content1.tex}
\include{content2.tex}
\include{conclusions.tex}
\printbibliography
\end{document}


{{title}}
Powered by
sprinter
&
travis-foreman
.
All Issues Past Two Months
By assignee:
Go!
User mentioned:
Go!
By milestone:
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By label(s):
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Updated since:
Go!


This model has been trained on ~40,000 tweets from candidates taking into account
features such as number of retweets, number of favorites, month, day, and hour published
as well as text information, with the goal of being able to predict which user
published a given tweet based on this information.
With 28 candidates running, a random selection has a ~3.6% chance of
guessing correctly. This model has an accuracy rate of ~55% for predicting
the user correctly, with plenty of room for improving accuracy by tweaking parameters. Though
not perfect, this substantial increase over "pure luck" is a great indicator of how powerful
even simple deep learning algorithms can be.
Notes:
- There is strong evidence that this model was "overfit" on the training data. It achieved
almost perfect results on the training data, and the drop was significant on the testing data.
This was true even for as low as 5 epochs of training. There are known methods for
preventing this effect.
- A very simplistic NLP method was used for processing text data - however, the text data
contains the key information for distinguishing candidates who otherwise have very similar
metrics.
- These kinds of classification models can prove to be highly beneficial for
campaigns which aim to distinguish their messaging, which often falls into the
trap of using bland or predictable talking points. For instance, the model will
provide more or less certainty of whether different tweets belong to a candidate, even
it the predicitons are correct. The "certainty" of a model's predictions can provide insight
into whether the messaging of a tweet is distinct enough such that it clearly conveys a
candidates' unique "brand". This is further helped by techniques which help identify
which features of a tweet were most helpful in producing the model's predictions (LIME). These
are typically unknown purely from the model itself. As a final thought, to the point of
"distinct" or "predictable" branding, while this model has much room for improvement, one can see
patterns in the model's predictions i.e. which candidates it incorrectly predicts, the
levels of certainty amongst different candidates, etc.


--Doug Gwyn[source]


Data Mining is a multideciplinary field touching important topics across machine learning, natural language processing, information retrieval, and optimisation. This lecture is delivered in the second semester at the Department of Computer Science, The University of Liverpool as master level module. This module requires undergraduate-level knowledge in linear algebra, calculus and probability theory as mathematical preliminaries. All assignments must be submitted in Python 3.0 and the lab sessions will require prior knowledge in Python programming language.
Mondays 11:00-12:00 BROD-108
Wednesdays 12:00-13:00 BROD-108
Thursdays 15:00-16:00 ELEC-202
Release date: January 28th
Submission deadline: March 5th, 15:00
Release date: March 6th
Submission deadline: April 1st, 15:00 HRS
Implementing the k-means Clustering Algorithm Download CA2data.txt
Exam date: 28th May 10:00-12:30 Exam room 31 Engineering Walker LT
Release date: July 6th
Submission deadline: July 31st 15:00 HRS (via Email to danushka)
Release date: July 6th
Implementing Hierarchical Clustering Algorithm Download CA2data.txt
Submission deadline: July 31st 15:00 HRS (via Email to danushka)
Exam date: TBD
See below for past resit questions and answers. Please use these in your revision for the resit.
The concepts that we will be learning in the lectures will be further developed using a series of programming tutorials. We will both implement some of the algorithms we learn in the course using Python as well as use some of the machine learning and data mining tools freely available. The two lab sessions are identical and you only need to attend one of the sessions per week. If your student number is even attend then attend the Monday lab session, else attend the Thursday lab session. Attendance marked for the lab sessions.
We will be using Python ver 3.0 as the preferred programming language for learning Data Mining algorithms. All course work must be submitted in Python as well. Only external libraries we will use are NumPy and Matplotlib. All sample code related to lab tasks are hosted in Google colab. You will need a Google account to download the sample code to your Google drive and execute.
Task: Write a python program to measure the similarity between two given sentences. First, compute the set of words in each sentence, and then use the Jaccard coefficient to measure the similarity between the two given sentences. You can see the solution here.
Numpy is a python library that provides data structures useful for data mining such as arrays, and various functions on those data structures. Follow the official numpy tutorial and familiarize yourself with numpy.
Task: Using numpy measure the cosine similarity between two given sentences. You can see the solution here [HTML].
This lab task will show you how to perform various vector and matrix operations/arithmetic using Python and numpy. Walk through the various functions and familiarise yourself with the code. If unsure, check the official documentation at the numpy website for the different functions and the arguments/values they can take. Here is the [norebook].
Lets perform various preprocessing steps on a set of feature vectors such as L1/L2 normalization and [0,1] scaling, Gaussian scaling using numpy. You can download the [notebook] for this task.
Lets implement a k-NN classifier to perform binary classification and evaluate its accuracy. You can download the [notebook]
Lets implement a naive Bayes classifier for text classification. You can download a sample program and data here [Naive Bayes] Uncompress the zip archive and run the python program to obtain the classification accuracy on test data. train and test files contain positively and negatively labelled product reviews. The reviews are preprocessed and expressed as a list of unigrams and bigrams (indicated by underscores) following the bag-of-words model. Each review is represented as a single line in the file and features (unigrams and bigrams) extracted from that review are listed space delimitted. Modify the Naive Bayes code and see what happens if we do not use Laplace smoothing.
We will count the co-occurrences of words in a given collection of documents, and compute pointwise mutual information, chi-squared measure, and the log-likelihood ratio. See the lecture notes on text mining for the definition of those word association measures. The sample program that implements the pointwise mutual information can be downloaded from here. When you uncompress the archive you will find two files: corpus.txt (contains 2000 sentences one per each line, we will assume each line to be a co-occurrence window) and cooc.py (computes the co-occurrences between words from corpus.txt and prints the top-ranked word-pairs in terms of their pointwise mutual information values). You are required to implement the Chi-squared measure and the log-likelihood ratio. There is a larger 100,000 sentence corpus (large_corpus.txt) also provided if you wish to experiment with larger text datasets.
Let us implement PCA and project some data points from high dimensional space to low dimensional space. You can download the [notebook].
Let us build an inverted index and process queries containing two keywords. Download and unzip this file and run the search.py script. It will index the 20 newsgroups dataset. We will assign integer ids to file names and sort the posting lists. Next, issue a query at the prompt containing two words separated by a space. We will then find the corresponding posting lists and find their intersection. Once you have carefully studied the behaviour of the matching algorithm (uncomment the print statements inside get_results function if needed), extend search.py to handle (a) queries containing arbitrary number of keywords and (b) use skip-pointers to speed up the look up.
Download the source code and data and study NN.py. This script implements a multilayer neural network with a softmax output and a single hidden layer. Hyperbolic tangent (tanh) activation is used in the hidden layer. The NN classifies the Iris dataset that you used in CA1.
The following problem sets are for evaluating your understanding on the various topics that we have covered in the lectures. Try these by yourselves first. We will dicusss the solutions during the lectures and lab sessions later. You are not required to submit your solutions and they will not be marked or counting towards your final mark of the module. The problem sets are for self-assessment only.
Here is a list of useful references.
Mathematics for Machine Learning Read Part I (in parcticular chapters 2, 3, 4, 5 and 6).
Pattern Recognition and Machine Learning, by Chris Bishop. For machine learning related topics
A Course in Machine Learning, by Hal Daume III. Excellent introductory material on various topics on machine learning.
Data Mining: Practical Machine Learning Tools and Techniques by Ian Witten. For decision tree learners, associative rule mining, data pre-processing related topics.
Foundations of Statistical Natural Language Processing by Christopher Manning. For text processing/mining related topics
Introduction to Linear Algebra by Gilbert Strang is a good reference to brush up linear algebra related topics. MIT video lectures based on the book are also available
An excellent reference of maths required for data mining and machine learning by Hal Daume III.
numpy (Python numeric processing)
scipy (Python MATLAB like functions)


{{getCalories(item.calc)}} Kcal
Macro nutrients, Proteins, Carbohydrate and Fats
Carbohydrates are calculated based on the remaining calories divide by 4
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{{calcMacros(macro.calc, calorie.calc)}}g |


{% include 'herders/profile/compare/table.html' with title="Summary" data=buildings.summary %}
{% include 'herders/profile/compare/table.html' with title="Levels" data=buildings.levels %}
{% include 'herders/profile/compare/table.html' with title="Remaining Upgrade Cost" data=buildings.remaining_costs %}


Release notes
- Support to Foreign Data Wrappers, Foreign Servers, User Mappings and Foreign Tables (PostgreSQL)
- Monitoring Dashboard: Save current chart disposition per connection
- Monitoring Dashboard: Monitoring units that require plpythonu no longer have this requirement (PostgreSQL)
- Monitoring Dashboard: Improved current charts and added new ones (PostgreSQL)
- Renamed "Data Mining" feature with "Advanced Object Search" (PostgreSQL)
- Advanced Object Search: Only shows a line when finds something, does not show "No match" (PostgreSQL)
- Fixed "Failed to find conversion function from unknown to regprocedure" (PostgreSQL, #591)
- Fixed "Unsupported regnamespace type" (PostgreSQL, #605)
- Fixed "Object object" error message when using Query Data (Oracle, #611)


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This module contains the implementation of the Multiobjective framework called Sofomore, and its instantiation with cma-es to obtain COMO-CMA-ES, defined in the paper [Toure, Cheikh, et al. "Uncrowded Hypervolume Improvement: COMO-CMA-ES and the Sofomore framework." GECCO'19-Genetic and Evolutionary Computation Conference. 2019.]. Only the bi-objective framework is functional and has been thoroughly tested.
Version: 0.5.1
Author: Cheikh Toure and Nikolaus Hansen
License: BSD 3-clause
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Sofomore Sofomore framework for multiobjective optimization, with the ask-and-tell interface. |
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IndicatorFront with `hypervolume_improvement` method based on a varying empirical front. |
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CmaKernel inheriting from the `cma.CMAEvolutionStrategy` class, by adding the property `incumbent`, the attributes `objective_values` and `_last_offspring_f_values`. |
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FitFun Define a callable multiobjective function from single objective ones. |
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cma_kernel_default_options_replacements =
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__package__ =
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Factory function that produces `len(x_starts)` instances of type `cmaKernel`. Parameters ---------- x_starts : TYPE list or list of lists or list of or ndarrays or ndarray The initial means of the returned cmas. sigma_starts : TYPE float or list of floats The initial step-sizes of the returned cmas. inopts : TYPE dict or list of dicts, optional The cmas' options. number_created_kernels : TYPE int, optional Used as the starting index for the returned cma's names. The values of the options' key 'verb_filenameprefix' rely upon this argument `number_created_kernels`. Returns ------- A list of `CmaKernel` instances. Example:: >>> import comocma >>> dimension = 10 >>> sigma0 = 0.5 >>> num_kernels = 11 >>> cma_opts = {'tolx': 10**-4, 'popsize': 32} >>> list_of_solvers = comocma.get_cmas(num_kernels * [dimension * [0]], sigma0, cma_opts) produce `num_kernels` cma instances. |
Used for the update order of a Sofomore instance. Example: moes = Sofomore(list_of_instances, reference_point, {'update_order': sort_random}) randomly picks the kernels to update in the `tell` method of Sofomore. |
Example: moes = Sofomore(list_of_instances, reference_point, {'update_order': sort_increasing}) updates respectively `self[0]`, `self[1]`, ..., `self[-1]` in the `tell` method of Sofomore. |
Example: moes = Sofomore(list_of_instances, reference_point, {'update_order': sort_decreasing}) updates respectively `self[-1]`, `self[-2]`, ..., `self[0]` in the `tell` method of Sofomore. |
Example: moes = Sofomore(list_of_instances, reference_point, {'update_order': sort_even_odds}) pick the kernels with even indices before the kernels with odd indices in the `tell` method of Sofomore. |
Example: moes = Sofomore(list_of_instances, reference_point, {'update_order': sort_odds_even}) pick the kernels with odd indices before the kernels with even indices in the `tell` method of Sofomore. |
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cma_kernel_default_options_replacements
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| Home | Trees | Indices | Help |
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| Generated by Epydoc 3.0.1 on Sat Apr 18 16:48:09 2020 | http://epydoc.sourceforge.net |


Last update: 06/10/2020 6am EST.
Contact me if you see any mistakes or if you have suggestions.
Blue roses are the most difficult flowers to obtain in the game.
Our methods have been extensively tested and simulated so you can pick the most optimized method for
your needs!
| Clone-tolerant: | A method is clone-tolerant if all the necessary intermediary offsprings are different from the parents. If a method is not clone-tolerant, you must use clone-resistant layouts. |
|---|---|
| Examples: | |
| Methodical: | A methodical path has formulated % chances at every single step. Genepool methods, on the other hand, involve throwing a bunch of flowers with unknown genes and hoping that some of them are the right combination (can be some luck involved!) |
| Pairs: | This typically refers to the number of pairs you can fit in your available garden
space. Note that for simulations, we use certain number of pairs at every single step. This means that methods with more steps are simulated with more intermediate pairs. For a basic isolated pairs layout, 32 pairs = 64 flowers, plus when you consider the necessary space inbetween, that means you'd need an 11x15 area! Plan accordingly! |
| Testing: | Paleh and Folklore methods need purple rose 𝑥 testing. In both methods, we will need to tell whether an unknown purple rose 𝑥 [0?20] is a purple rose α [0020] or purple rose β [0120]. You need to be super careful during this extra step to properly differentiate between 2 flowers that look exactly alike! |
| Visitors: | Having visitors from other islands water your flowers significantly increase your base production rate (from 5% up to 80%!). [visitor watering guide] |
Metric: number of days to 1 blue rose from planting seeds.
For expected time with 0 visitors and more numbers, check below!
Most players will get their first blue rose before these # of days. (95 out of 100)
| Introduction: | Simple and straightforward method for beginners. |
|---|---|
| Difficulty: | Easy |
| Strengths: | Clone-tolerant, you don't have to worry about clones (although clone-resistant layouts
are always recommended). Also methodical, each step is organized and has calculated %
rates. |
| Weaknesses: | Slowest method, but not bad if you have visitors watering. However, difference is very significant if you do not have Nintendo Switch Online or otherwise cannot get visitors to help water your flowers. We strongly advise using another method if you are in this situation. | Layouts: | For step 1 and step 4 (when you are breeding two white rose [0010] and breeding two red rose [1110]), use a dense layout for same-parent breeding such as turtle or tetris-t. For the other steps where the parents are different colors, you can use any different-parent breeding layouts. |
| Credits: | Method: asteriation#6884. |
| Other pictures: | Ellie33#5074's visual guide: |
| Introduction: | The fastest method! Involves a genepool and knowledge of cloning though. |
|---|---|
| Difficulty: | Hard |
| Strengths: | Gotta go fast. |
| Weaknesses: | Not clone-tolerant. You must learn how to avoid clones, and you must use clone-resistant
layouts for the breeding steps. You will need to know how to clone for the cloning
step. You will be utilizing a genepool, which has an unknown % chance of making a blue (although the average is ~5.1%). |
| Layouts: | We recommend the standard isolated pairs layout, or its other variations during the breeding steps. For the cloning and subsequent self-breeding step: You must be able to identify the parent of the clone while cloning AND you must ensure the flower then breed with their own clone (IP). The layout below will allow you to do both steps. Blockers (e.g. hard pathing, fencing, etc.) are necessary. |
| Suggested layout: | |
| Additional Instructions: | Optional steps if you have space:
|
| Credits: | Method: asteriation#6884, based on backwardsn#7201's genepool method. [original document] |
| Introduction: | Also known as "Shotgun, BackN's 4-step, and Cesspool" methods. This is the original "genepool" method, and it name speaks for itself. This path is good for if you have a LOOOOT of space. A lot a lot. |
|---|---|
| Difficulty: | Medium |
| Strengths: | Great balance of speed and simplicity. It is easier than Aster's Genepool, and only a
little slower. |
| Weaknesses: | Not recommended for players who have limited garden space.  You will be utilizing a genepool, which has an unknown % chance of making a blue (although the average is ~2.2%). There is a chance of failure with less # of pairs (no valid pairs in genepool that can make blue), so you will be relying on the 1.56% from step 3. |
| Layouts: | For steps 1 and 2: we recommend the standard isolated pairs
layout (or other variations). For step 3 (1110 red x 1110 red) and 4 (genepool): any dense layouts such as turtle or tetris-t (use this despite genepool not being identical parents). During the genepool step, you can keep expanding the "field" of red, orange, and black roses with additional offsprings. |
| Credits: | Method: backwardsn#7201 [original document] |
| Other pictures: | Visual version: (by @kamirose). |
| Introduction: | Great method for if you have less available garden space to work with! Although it has a slightly slower than BackN's method on average (using 8 pairs), it has a significantly lower 95 percentile. |
|---|---|
| Difficulty: | Hard |
| Strengths: | Methodical, each step is organized and has calculated % rates. Although there are many steps, the % yield at every step is fairly high (lowest is 25%) compared to 1.56% in some other methods. (You don't have to rely as much on luck). |
| Weaknesses: | Not clone-tolerant. You must learn how to avoid clones, and you must use clone-resistant
layouts. You must also need to do purple rose 𝑥 testing. |
| Layouts: | You MUST use clone-resistant layouts for this method. We recommend the standard isolated pairs layout, or its other variations (see link for details). |
| Additional Instructions: | Optional steps if you have space:
|
| Credits: | Method: Paleh#2526, refined by: jpony#3101. [original document] |
| Other pictures: | v2.0: incorrectly had main method as "alternate". |
|
Leaving this up for those who were already on the old (slower) path. Will be removing this soon, please use the updated version! |
| Introduction: | Standard original method. Average in every way possible. (originates from New Leaf!) |
|---|---|
| Difficulty: | Medium |
| Strengths: | Methodical, each step is organized and has calculated % rates. |
| Weaknesses: | Not clone-tolerant. You must learn how to avoid clones, and you must use clone-resistant
layouts. You must also need to do purple rose 𝑥 testing. |
| Layouts: | You MUST use clone-resistant layouts for this method. We recommend the standard isolated pairs layout, or its other variations (see link for details). |
| Credits: | Method: originates from ACNL guide. |
| Other pictures: | @co32h versions: |


public interface Tracer
Span
creation and in-process context interaction.
Users may choose to use manual or automatic Context propagation. Because of that this class offers APIs to facilitate both usages.
The automatic context propagation is done using Context
which is a gRPC
independent implementation for in-process Context propagation mechanism which can carry
scoped-values across API boundaries and between threads. Users of the library must propagate the
Context
between different threads.
Example usage with automatic context propagation:
class MyClass {
private static final Tracer tracer = Trace.getTracer();
void doWork() {
Span span = tracer.spanBuilder("MyClass.DoWork").startSpan();
try(Scope ss = tracer.withSpan(span)) {
tracer.getCurrentSpan().addEvent("Starting the work.");
doWorkInternal();
tracer.getCurrentSpan().addEvent("Finished working.");
} finally {
span.end();
}
}
}
Example usage with manual context propagation:
class MyClass {
private static final Tracer tracer = Trace.getTracer();
void doWork(Span parent) {
Span childSpan = tracer.spanBuilderWithExplicitParent("MyChildSpan", parent).startSpan();
childSpan.addEvent("Starting the work.");
try {
doSomeWork(childSpan); // Manually propagate the new span down the stack.
} finally {
// To make sure we end the span even in case of an exception.
childSpan.end(); // Manually end the span.
}
}
}
| Modifier and Type | Method | Description |
|---|---|---|
BinaryFormat<SpanContext> |
getBinaryFormat() |
Returns the
BinaryFormat for this implementation. |
Span |
getCurrentSpan() |
Gets the current Span from the current Context.
|
HttpTextFormat<SpanContext> |
getHttpTextFormat() |
Returns the
HttpTextFormat for this implementation. |
Resource |
getResource() |
|
void |
recordSpanData(SpanData span) |
Records a
SpanData . |
void |
setResource(Resource resource) |
|
Span.Builder |
spanBuilder(String spanName) |
Returns a
Span.Builder to create and start a new child Span as a child of to
the current Span if any, otherwise creates a root Span . |
Span.Builder |
spanBuilderWithExplicitParent(String spanName,
Span parent) |
Returns a
Span.Builder to create and start a new child Span (or root if parent
is null or has an invalid SpanContext ), with parent being the designated
Span . |
Span.Builder |
spanBuilderWithRemoteParent(String spanName,
SpanContext remoteParentSpanContext) |
Returns a
Span.Builder to create and start a new child Span (or root if parent
is null ), with parent being the remote Span designated by the SpanContext . |
Scope |
withSpan(Span span) |
Enters the scope of code where the given
Span is in the current Context, and returns an
object that represents that scope. |
Runnable |
withSpan(Span span,
Runnable runnable) |
Returns a
Runnable that runs the given task with the given Span in the current
context. |
<V> Callable<V> |
withSpan(Span span,
Callable<V> callable) |
Returns a
Callable that runs the given task with the given Span in the current
context. |
Span getCurrentSpan()
To install a Span
to the current Context use withSpan(Span)
.
startSpan methods do NOT modify the current Context Span
.
Span
that does nothing and has an invalid SpanContext
if no
Span
is associated with the current Context, otherwise the current Span
from the Context.@MustBeClosed Scope withSpan(Span span)
Span
is in the current Context, and returns an
object that represents that scope. The scope is exited when the returned object is closed.
Supports try-with-resource idiom.
Can be called with BlankSpan
to enter a scope of code where tracing is stopped.
Example of usage:
private static Tracer tracer = Trace.getTracer();
void doWork() {
// Create a Span as a child of the current Span.
Span span = tracer.spanBuilder("my span").startSpan();
try (Scope ws = tracer.withSpan(span)) {
tracer.getCurrentSpan().addEvent("my event");
doSomeOtherWork(); // Here "span" is the current Span.
}
span.end();
}
Prior to Java SE 7, you can use a finally block to ensure that a resource is closed regardless of whether the try statement completes normally or abruptly.
Example of usage prior to Java SE7:
private static Tracer tracer = Trace.getTracer();
void doWork() {
// Create a Span as a child of the current Span.
Span span = tracer.spanBuilder("my span").startSpan();
Scope ws = tracer.withSpan(span);
try {
tracer.getCurrentSpan().addEvent("my event");
doSomeOtherWork(); // Here "span" is the current Span.
} finally {
ws.close();
}
span.end();
}
span
- The Span
to be set to the current Context.Span
will be set to the current
Context.NullPointerException
- if span
is null
.Runnable withSpan(Span span, Runnable runnable)
Runnable
that runs the given task with the given Span
in the current
context.
Users may consider to use Span.Builder.startSpanAndRun(Runnable)
.
Any error will end up as a Status.UNKNOWN
.
IMPORTANT: Caller must manually propagate the entire io.grpc.Context
when wraps a
Runnable
, see the examples.
IMPORTANT: Caller must manually end the Span
within the Runnable
, or after
the Runnable
is executed.
Example with Executor wrapped with Context.currentContextExecutor(java.util.concurrent.Executor)
:
class MyClass {
private static Tracer tracer = Trace.getTracer();
void handleRequest(Executor executor) {
Span span = tracer.spanBuilder("MyRunnableSpan").startSpan();
executor.execute(tracer.withSpan(span, new Runnable() {
@Override
public void run() {
try {
sendResult();
} finally {
span.end();
}
}
}));
}
}
Example without Executor wrapped with Context.currentContextExecutor(java.util.concurrent.Executor)
:
class MyClass {
private static Tracer tracer = Trace.getTracer();
void handleRequest(Executor executor) {
Span span = tracer.spanBuilder("MyRunnableSpan").startSpan();
executor.execute(Context.wrap(tracer.withSpan(span, new Runnable() {
@Override
public void run() {
try {
sendResult();
} finally {
span.end();
}
}
})));
}
}
span
- the Span
to be set as current.runnable
- the Runnable
to withSpan in the Span
.Runnable
.<V> Callable<V> withSpan(Span span, Callable<V> callable)
Callable
that runs the given task with the given Span
in the current
context.
Users may consider to use Span.Builder.startSpanAndCall(Callable)
.
Any error will end up as a Status.UNKNOWN
.
IMPORTANT: Caller must manually propagate the entire io.grpc.Context
when wraps a
Callable
, see the examples.
IMPORTANT: Caller must manually end the Span
within the Callable
, or after
the Callable
is executed.
Example with Executor wrapped with Context.currentContextExecutor(java.util.concurrent.Executor)
:
class MyClass {
private static Tracer tracer = Trace.getTracer();
void handleRequest(Executor executor) {
Span span = tracer.spanBuilder("MyRunnableSpan").startSpan();
executor.execute(tracer.withSpan(span, new Callable<MyResult>() {
@Override
public MyResult call() throws Exception {
try {
return sendResult();
} finally {
span.end();
}
}
}));
}
}
Example without Executor wrapped with Context.currentContextExecutor(java.util.concurrent.Executor)
:
class MyClass {
private static Tracer tracer = Trace.getTracer();
void handleRequest(Executor executor) {
Span span = tracer.spanBuilder("MyRunnableSpan").startSpan();
executor.execute(Context.wrap(tracer.withSpan(span, new Callable<MyResult>() {
@Override
public MyResult call() throws Exception {
try {
return sendResult();
} finally {
span.end();
}
}
})));
}
}
V
- the result type of method call.span
- the Span
to be set as current.callable
- the Callable
to run in the Span
.Callable
.Span.Builder spanBuilder(String spanName)
Span.Builder
to create and start a new child Span
as a child of to
the current Span
if any, otherwise creates a root Span
.
See Span.Builder
for usage examples.
This must be used to create a Span
when automatic Context propagation is
used.
This is equivalent with:
tracer.spanBuilderWithExplicitParent("MySpanName",tracer.getCurrentSpan());
spanName
- The name of the returned Span.Span.Builder
to create and start a new Span
.NullPointerException
- if spanName
is null
.Span.Builder spanBuilderWithExplicitParent(String spanName, @Nullable Span parent)
Span.Builder
to create and start a new child Span
(or root if parent
is null
or has an invalid SpanContext
), with parent being the designated
Span
.
See Span.Builder
for usage examples.
This must be used to create a Span
when manual Context propagation is used OR
when creating a root Span
with a null
parent.
spanName
- The name of the returned Span.parent
- The parent of the returned Span. If null
the Span.Builder
will
build a root Span
.Span.Builder
to create and start a new Span
.NullPointerException
- if spanName
is null
.Span.Builder spanBuilderWithRemoteParent(String spanName, @Nullable SpanContext remoteParentSpanContext)
Span.Builder
to create and start a new child Span
(or root if parent
is null
), with parent being the remote Span
designated by the SpanContext
.
See Span.Builder
for usage examples.
This must be used to create a Span
when the parent is in a different process.
This is only intended for use by RPC systems or similar.
If no SpanContext
OR fail to parse the SpanContext
on the server side, users
must call this method with a null
remote parent SpanContext
.
spanName
- The name of the returned Span.remoteParentSpanContext
- The remote parent of the returned Span.Span.Builder
to create and start a new Span
.NullPointerException
- if spanName
is null
.void setResource(Resource resource)
Resource getResource()
void recordSpanData(SpanData span)
SpanData
. This API allows to send a pre-populated span object to the
exporter. Sampling and recording decisions as well as other collection optimizations is a
responsibility of a caller. Note, the SpanContext
object on the span population with
the values that will allow correlation of telemetry is also a caller responsibility.span
- Span Data to be reported to all exporters.BinaryFormat<SpanContext> getBinaryFormat()
BinaryFormat
for this implementation.
If no implementation is provided then no-op implementation will be used.
Usually this will be the W3C Trace Context as the binary format. For more details, see trace-context.
Example of usage on the client:
private static final Tracer tracer = Trace.getTracer();
private static final BinaryFormat binaryFormat =
Trace.getTracer().getBinaryFormat();
void onSendRequest() {
Span span = tracer.spanBuilder("MyRequest").setSpanKind(Span.Kind.CLIENT).startSpan();
try (Scope ss = tracer.withSpan(span)) {
byte[] binaryValue = binaryFormat.toByteArray(tracer.getCurrentContext().context());
// Send the request including the binaryValue and wait for the response.
} finally {
span.end();
}
}
Example of usage on the server:
private static final Tracer tracer = Trace.getTracer();
private static final BinaryFormat binaryFormat =
Trace.getTracer().getBinaryFormat();
void onRequestReceived() {
// Get the binaryValue from the request.
SpanContext spanContext = SpanContext.INVALID;
if (binaryValue != null) {
spanContext = binaryFormat.fromByteArray(binaryValue);
}
Span span = tracer.spanBuilderWithRemoteParent("MyRequest", spanContext)
.setSpanKind(Span.Kind.SERVER).startSpan();
try (Scope ss = tracer.withSpan(span)) {
// Handle request and send response back.
} finally {
span.end();
}
}
BinaryFormat
for this implementation.HttpTextFormat<SpanContext> getHttpTextFormat()
HttpTextFormat
for this implementation.
If no implementation is provided then no-op implementation will be used.
Usually this will be the W3C Trace Context as the HTTP text format. For more details, see trace-context.
Example of usage on the client:
private static final Tracer tracer = Trace.getTracer();
private static final HttpTextFormat textFormat = Trace.getTracer().getHttpTextFormat();
private static final HttpTextFormat.Setter setter =
new HttpTextFormat.Setter<HttpURLConnection>() {
public void put(HttpURLConnection carrier, String key, String value) {
carrier.setRequestProperty(field, value);
}
}
void makeHttpRequest() {
Span span = tracer.spanBuilder("MyRequest").setSpanKind(Span.Kind.CLIENT).startSpan();
try (Scope s = tracer.withSpan(span)) {
HttpURLConnection connection =
(HttpURLConnection) new URL("http://myserver").openConnection();
textFormat.inject(span.getContext(), connection, httpURLConnectionSetter);
// Send the request, wait for response and maybe set the status if not ok.
}
span.end(); // Can set a status.
}
Example of usage on the server:
private static final Tracer tracer = Trace.getTracer();
private static final HttpTextFormat textFormat = Trace.getTracer().getHttpTextFormat();
private static final HttpTextFormat.Getter<HttpRequest> getter = ...;
void onRequestReceived(HttpRequest request) {
SpanContext spanContext = textFormat.extract(request, getter);
Span span = tracer.spanBuilderWithRemoteParent("MyRequest", spanContext)
.setSpanKind(Span.Kind.SERVER).startSpan();
try (Scope s = tracer.withSpan(span)) {
// Handle request and send response back.
}
span.end()
}
HttpTextFormat
for this implementation.


---
layout: default
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Elizabeth "Lizzie" Siegle - Student, developer, freelance tennis instructor
Welcome!
A website composed of a glorified resume and musings on life at a women's college.
Contact Me! This site is a work in progress, and, in the meantime, here is an easy way to get in touch. Or see the about section.
{{EmailCtrl.Status}}


|
BitShares-Core
6.1.0
BitShares blockchain implementation and command-line interface software
|
aggregates a message along with the context and associated meta-information. More...
#include <log_message.hpp>
Public Member Functions | |
| log_message () | |
| log_message (log_context ctx, std::string format, variant_object args=variant_object()) | |
| ~log_message () | |
| log_message (const variant &v, uint32_t max_depth) | |
| variant | to_variant (uint32_t max_depth) const |
| std::string | get_message () const |
| log_context | get_context () const |
| std::string | get_format () const |
| variant_object | get_data () const |
aggregates a message along with the context and associated meta-information.
When converted to JSON, log_message has the following form:
Definition at line 106 of file log_message.hpp.
| fc::log_message::log_message | ( | ) |
Definition at line 184 of file log_message.cpp.
| fc::log_message::log_message | ( | log_context | ctx, |
| std::string | format, | ||
| variant_object | args = variant_object() |
||
| ) |
| ctx | - generally provided using the FC_LOG_CONTEXT(LEVEL) macro |
| format | - the format |
| args | - the arguments |
Definition at line 187 of file log_message.cpp.
| fc::log_message::~log_message | ( | ) |
Definition at line 183 of file log_message.cpp.
| fc::log_message::log_message | ( | const variant & | v, |
| uint32_t | max_depth | ||
| ) |
Definition at line 194 of file log_message.cpp.
| log_context fc::log_message::get_context | ( | ) | const |
Definition at line 209 of file log_message.cpp.
| variant_object fc::log_message::get_data | ( | ) | const |
Definition at line 211 of file log_message.cpp.
| string fc::log_message::get_format | ( | ) | const |
Definition at line 210 of file log_message.cpp.
| string fc::log_message::get_message | ( | ) | const |
Definition at line 213 of file log_message.cpp.
| variant fc::log_message::to_variant | ( | uint32_t | max_depth | ) | const |
Definition at line 201 of file log_message.cpp.