Introduction to pattern matching in Scala
Pattern matching is a quite commonly used “programming pattern” in functional languages, because it fits nicely into the “functional way of thinking”, and it is quite powerful and handy as a tool.
It’s somewhat similar to a sequence of if / else statements or to the switch statement of Java or C, but it is much more powerful, because it lets you form more complex conditions for matching, even for the inside of an object.
In some cases Scala can automatically decompose an object that you want to match and look inside it to check if its structure matches your expectations.
But, before going too deep, let’s see some examples.
Example 1: matching value
Here the object what we match to patterns is x, an integer.
object MatchTest1 extends App {
def matchTest(x: Int): String = x match {
case 1 => "one"
case 2 => "two"
case _ => "many"
}
println(matchTest(3))
}
One important thing to note is the last case where an underscore is used: this is Scala’s notation for “match anything”. Without this line, we would get a “scala.MatchError” because we called the matchTest() function with the value 3, which is not covered by the other case branches.
So the main point to remember from here is that you should be sure to cover all possible options when using a match expression if you want to avoid ugly errors. The fail-safe option usually is to use the underscore as the last case. It will define a default path for the program flow for “all other cases”.
(Note: I just copied this example from the official documentation).
Example 2: matching type
If we want to write a function that behaves differently for different input types, we can write something like:
def getType(x: Any): String = {
x match {
case x: String => "String"
case x: Integer => "Int"
case _ => "I don't know"
}
}
Note 1: “Any” is a general type in Scala, similar to the “Object” of Java, which is an ancestor of all other types.
Note 2: You don’t need to use the same value name in the cases, because each case has its own scope with regards of the incoming object to be matched. Just be sure to use the same name on both sides of the arrow within a case line.
def getType2(x: Any): String = {
x match {
case a: String => "String: " + a
case b: Integer => "Int: " + b
case _ => "I don't know"
}
}
Example 3: using guards
Let’s say we need some extra conditions to be true before applying the right side of a case. Scala lets us perform these additional checks within any of the cases independently, as in the following example:
def getType3(x: Any): String = {
x match {
case a: String if a.startsWith("He") => "String with 'He'"
case b: Integer if b > 0 => "Positive integer"
case _ => "I don't know"
}
}
Example 4: matching structure
I promised in the first paragraph that in some cases we will be able to “automatically decompose an object” to look inside it and check if its structure matches our expectations.
How does it work in Scala, and what are the prerequisites?
The answer is: case classes! In one of my following posts I will cover them in more detail. For now let’s think about a case class as a composite object with some auto-magic: automatically generated constructors and getters, for example.
For the more curious, here are some nice and short explanations, and the official (quite dense) description of case classes.
So, for an example of automatic decomposition, at first we need a case class. We’ll write one, representing a tweet message, that has three parts:
- an identifier (id: Long)
- an author (user: User, that itself could be a complex case class, now it only contains one String, a name)
- a message (msg: String)
Defining these new types (User and TweetMsg) in Scala takes only two fairly short lines:
case class User(name: String)
case class TweetMsg(id: Long, user: User, msg: String)
And now a function can match a tweet’s inners like this:
def processTweet(tweet: TweetMsg) = tweet match {
case TweetMsg(id, _, _) if id < 0 => "Invalid (negative) tweet id!"
case TweetMsg(_, user, _) if user.name == "adorster" => "Hello, " + user.name + "!"
case _ => "Just another tweet"
}
Example codes with tests are available at my scala-examples github repo.
Note n+1 : Until I set up a comments section somehow here, feedback is welcome via Twitter :)


Japanese Random Characters
Currently supporting:
Hiragana.
Katakana
Kanji will be added soon.
In the (distant) future, funcionality to export the output to PDF might me added.
List length:
Select symbol sets to be used:
Hiragana:
Yes
No
Katakana:
Yes
No


For this assisment, I reserched about html links, and ordered/unordered lists.
Create a new folder called "listsandlinks" in your repository folder.
Inside listsandlinks create a file called "index.html" and a file called "main.css"
In index.html create an ordered list of step by step instructions to create a new webpage on the production server
Also create an unordered list of 5 or more links to websites with useful webdesign related information
In the nav section, create an unordered list of links with a link back to your main index page.
In your main index.html file in public_html, add an unordered list of links to the nav section with a link to "listsandlinks".
In your old index.html, add an article with a heading and a paragraph description of this assignment. Also add an unordered list that contains this list of requirements.


Age : 24
Home Address :No.1 Batu 21 kampung Sungai Ular, 26080 Kuantan, Pahang Darul Makmur.
Interest : Financial Analysis
Hobby : Reading (Journal/Book) and Cooking
Interested in: Financial Tech and Financial Engineering
Hobby : Reading and Cooking
Nurul Husna Athirah is a Financial Manager and Social Media Manager who helps finance professionals and Fin-tech startups build an audience and get more paying clients online.
Before starting a writing business, Husna spent six years as a Bank Teller and Financial Analyst for financial companies in the Malaysia. After a successful career helping small banks and real estate agencies, Husna now helps them write marketing copy for their products and services.
Husna enjoys trying new sports (archery, hockey) and managing a small property rental business.
Husna's avaible for marketing and writing projects, as well as private consultations.
Copyright HUSNA ATHIRAH 2018


Event Location:
East Williamson County Higher Education Center
1600 Innovation Blvd, Hutto TX
Austin, Texas
Abstract:
Mental illness is more common than you think. One in four Americans suffers from a mental illness each year. In the tech community, this is often not talked about. Many times, people feel alone and isolated in the tech community with us mostly being introverted people. It is time to start talking about mental illness out in the open and honestly about how it affects us and those around us. In this session, we will talk about what mental illness is and what it is not.  How it effects the tech industry. How mental illness can affect you and how you can tell if you are starting to have issues. What to say and what not to say to people you know that are affected by mental illness. Finally, how to get help and where reach out for help.
Speaker(s): Tracy Boggiano,
Abstract:
Databricks is a very popular environment for developing data science solutions. More and more companies are interested in Databricks as it is very simple to set up and contains a collaborative workspace for working with a team of people. In this session you will see how to create Machine Learning Solutions with multiple workflows starting with ETL, to data exploration, model experimentation, and lastly to a production release of a data science solution. Today, more and more development is performed on very large datasets. Attendees will learn how to use Apache Spark, which is part of Databricks, to rapidly analyze lots of data. Learn how to use Databricks to reduces operational complexity to create solutions which can be scaled up or down depending on the amount of data needed to process without having to change the underlying code. Python, Jupyter Notebooks, and Apache Spark are the technologies used to create solutions within this session. No experience is required. Agenda
Speaker(s): Ginger Grant,
Abstract:
Python is the one of the most popular programming languages used today and one of the most useful tools in the data scientist's tool belt, especially for machine learning. Python is integrated into the Microsoft stack in tools like Azure ML, Databricks, and SQL Server. This session will be an introduction to the Python language including: 1) Installing and Configuring Python 2) Accessing and Manipulating Data 3) Installing and Managing Packages 4) Creating and Using Objects/Variables 5) Controlling Flows and Functions 6) Controlling Flows and Functions 6) Python in MS Power BI, Azure ML, MSSQL, and Databricks. Attend this session to learn how Python can take your data analytics to the next level. We will use Python, SQL Server, and the Anaconda distribution of Python to learn the basics of Python and how it is integrated in the Microsoft stack! We will walk through a simple deployment of a machine learning model to see how it all works together and learn some basic data science fun
Speaker(s): Jamey Johnston,
Abstract:
Face it, using SSIS to work with fixed width flat files is a pain. The SSIS interface has you clicking around to mark each column. Then you use another interface to set each columns data types, etc. And when you are done, you still need to document the file structure for your users. What if you could simply document the file structure and then generate the ETL from the document? To demonstrate such an approach, I build an Excel file describing US census data that has more than 300 columns of fixed width data. After demonstrating how this file communicates to business users, I will generate an SSIS package from that metadata using BIML Script. Then I will also look at how you can generate a SQL Server bulk insert format file from the same metadata.
Speaker(s): Russel Loski,
Abstract:
Customers and users increasingly demand more personal and prompt communication from companies and brands with which they interact. How can data professionals help fill that need? The incredible power and instant accessibility of the Azure Cognitive Services Language and Speech APIs, combined with other Azure services, put the power in our hands. From translating between languages to make communication more efficient to analyzing support communications to ensure customers are happy, Azure Cognitive Services allows data professionals to enhance a brand's interaction with and impression in the customer community. This demo-heavy sessions walks through practical applications of these APIs that you can apply at home or at work immediately after the session.
Speaker(s): Matt Gordon,
Abstract:
Power Query is an powerful tool enabling the data analyst in creating usable data. It is one product that can truly claim to be user friendly, as so much of the functionality is available within the UI. But, and there is always a but, sometimes you need to do things that are just not available through the UI. This is where you need to get down and get dirty, and manage the M code directly (M being the language that drives Power Query). This session is all about the value of developing skills in M. Starting with a brief intro to M and some references to resources to help develop those skills further, we will then demonstrate a number of things you can do by directly coding in M, things that are not as simple or just can't be done through the UI. The session will be using Power Query in Excel as Excel is still the most used BI delivery tool, but all of the techniques and code also apply to Power BI.
Speaker(s): Bob Phillips,
Abstract:
Change Tracking came out with SQL Server 2008, but SS2012 almost eclipsed it with Change Data Capture. Change Tracking is now the red-headed stepchild, but in many cases may be the best solution for data ETL movement from an SQL Server OLTP database to a data warehouse or reporting database. This session will provide a review of change tracking syntax and implementation with detailed demos. It will then dive into an actual ETL subset implementation from the AdventureWorks database to a data warehouse solution (modified AdventureWorksDW) with detailed code discussion and demos using TSQL only (no SSIS).  Come learn how you can adapt the supplied code to have near real-time in your data warehouse (or reporting database).
Speaker(s): Mike Byrd,
Abstract:
As companies work to gain insight from ever-increasing amounts of data, data platform practitioners need tools which can scale along with the data. Early big data solutions in the Hadoop ecosystem assumed that data sizes overwhelmed available memory, emphasizing heavy disk usage to coordinate work between nodes. As the cost of memory decreases and the amount of memory available per server increases, we see a shift in the makeup of big data systems, emphasizing heavy memory usage instead of disk. Apache Spark, which focuses on memory-intensive operations, has taken advantage of this hardware shift to become the dominant solution for problems requiring distributed data. In this talk, we will take an introductory look at Apache Spark. We will review where it fits in the Hadoop ecosystem, cover how to get started and some of the basic functional programming concepts needed to understand Spark, and see examples of how we can use Spark to solve issues when analyzing large data sets.
Speaker(s): Kevin Feasel,
Abstract:
While Power BI is often known as a BI tool or visualization tool, it is more appropriately viewed as an ecosystem, as it includes various tools, capabilities and integration with other Microsoft and 3rd party tools. This session will provide an overview of the Power BI ecosystem, look at various tools and key capabilities, their stand-alone functionalities, and how they can be integrated with other tools and environments. The intention of the session is for the attendee to walk away with a greater understanding and appreciation of Power BI's capabilities, what you can do with "it", and gain new ideas on how to leverage the capabilities in Power BI ecosystem in your data reporting and analytics journey.
Speaker(s): Brian Lee,
Abstract:
Are you curious about the role that AI will play in predictive modeling? Are you wondering what the difference is between the Computer Vision API and the Custom Vision API? Do you want a quick introduction to get you up to speed on both, so that you can quickly build and deploy a Cognitive Services model? Join us for an introduction to the Cognitive Services Computer Vision and Custom Vision APIs on Azure. In this session, we will look at the basics of Cognitive Services Vision. First learn how to create your Cognitive Services model. Then you can see how to train and improve accuracy. Finally, we will step through python code in Azure Notebooks to call the APIs. After this session, you will get up and running in Cognitive Services Vision in under an hour! Prerequisites: Attendees should have an Azure account, as well as an account on Azure Notebooks. Experience with coding in python is helpful, but not required.
Speaker(s): Alicia Moniz,
Abstract:
Power BI time intelligence (Month to Date, Year to Date, etc) functions work great when you use the normal natural calendar. But what happens when you have a custom calendar where the month does not begin and end on the first and last days respectively of a month. Learn how to use Power Query (M) and DAX to create the time intelligence fields and measures needed to solve this problem.
Speaker(s): Matthew Floyd,
Abstract:
Accessibility is catering for your whole audience, including those with disabilities. According to the US Census Bureau, 19 percent of the of the population had a disability in 2010. Do you know if your reports are designed in an inclusive way? In this session, we'll discuss accessibility standards and regulations of which you may want to be aware, how users with disabilities can consume Power BI reports, and guidance and pitfalls when designing inclusive reports.
Speaker(s): Meagan Longoria,
Abstract:
In this session, you will learn the basics of building a data vault to organize and store your companies disparate data on SQL Server. Learn how Hubs, Links, and Satellite tables create options for storing a variety of data from multiple systems. The data vault structures will then be used as the data source to create views designed for SQL Server Analysis Services Tabular models. Finally, Power BI will be used to visual the data for your end users.
Speaker(s): Derek Wilson,
Abstract:
ETL of large amount of data is always a daily task for data analysts and data scientists. While Excel and Text editors can handle a lot of the initial work, they have limitations. Python, in particular, Pandas library and Jupyter Notebook have becoming the primary choice of data analytics and data wrangling tools for data analysts world wide. In this 60 minute session, I will show you how to set up and get it running on your laptop for a jupyter notebook environment and start improve your ETL workflow.
Speaker(s): Wenbin Zhao,
Abstract:
Calculation groups are the most important feature introduced in DAX after variables in 2015. By using calculation groups, you can apply transformations to existing measures without having to create new measures in the model. For example, you can define the year-over-year calculation once and apply it to all the measures you want. Yet, calculation groups can do more than that. This session introduces the syntax of calculation groups, when they should be used and several examples of use cases. You will also learn how calculation groups work internally and what are the limits of this amazing tool.
Speaker(s): Alberto Ferrari,
Abstract:
This session will explore a variety of considerations that modern data scientists and data practictioners must account for when gathering and presenting data, including topics on bias, construct analysis, and machine learning.
Speaker(s): William Assaf,
Abstract:
Come learn about the basics of data modeling for your business intelligence and reporting needs. This course will cover several introductory modeling subjects, including: * Transactional vs. Analytical models * Kimball / Inman approaches * The process for designing your data model * Hierarchies / Parent-child relationships
Speaker(s): Michael McKinley,
Abstract:
We are living in a world full of data but what we need is information. What is required to transform data into information? What are the foundational activities your organization needs to do in order to produce analytics that you are confident in sharing? In this session we will discuss what is needed for your organization to convert data into information, the basics of: Data Governance, Data Modeling and how to have an immediate impact using tools like Power BI to deliver value; and, Data Visualizations and telling stories with the data.
Speaker(s): Leslie Andrews,
Abstract:
How do you optimize a DAX expression? In this session we analyze some DAX expressions and Tabular models and, through the usage of DAX Studio and some understanding of the VertiPaq model, we will look at how to optimize them. As you will see, most optimizations are the direct application of best practices, but the session has the additional takeaway of understanding what kind of performance you should expect from your formulas, and the improvement you might expect from learning how to optimize the model and the code.
Speaker(s): Alberto Ferrari,
Abstract:
Are you excited to know about the MSBI tools and work as a Business Intelligence Professional, a dynamic and rewarding career in Information Technology? If yes, this is the right time and place for you. In this session, I will give you the overview of the MSBI tools (SSIS, SSRS, SSAS, Power BI, Azure Machine Learning). I will also provide you some insights to build the MSBI career and to leverage the learning curve in Microsoft Data Platform, based on my knowledge and experience and the proven strategies and techniques.
Speaker(s): Ganesh Lohani,
Abstract:
Looking to get the most out of your SQL Saturday, PASS Summit, or local user group meeting? Plan ahead! Events aren't just about learning new things, they're about meeting new people, networking with peers, and learning different approaches to common issues. In this session, we'll go over steps you can take before, during and after the event to maximize the amount of great stuff you'll take away at the end (besides cool vendor swag). Not just keeping up on new technologies, but meeting new people, getting leads on solutions/opportunities, and an appreciation for the community you're in and what it has to offer.
Speaker(s): Matt Cushing,
Abstract:
Looking for a job? Learn trade secrets from an HR professional! Resume blunders and interview tips, this session will focus on the most important things you can do to get hired.
Speaker(s): Christine Assaf,
This is a list of speakers from the XML Guidebook records. The details and URLs were valid at the time of the event.
LinkedIn: https://www.linkedin.com/in/christineassaf
Contact: https://www.hrtact.com
Christine Assaf is an experienced HR pro who is passionate about the mental health of employees, leadership, and organizations. She is a leadership development professional with over 15 years experience in human resources and 20 years in business management. She holds a BS in Business Management, received her HRM certification at LSU, and is finishing up her master's degree at Colorado State University in Industrial and Organizational Psychology. She is a certified DDI Trainer, experienced public speaker, and is dedicated to teaching others about ways to support a culture of "expressiveness" in the workplace that creates connectivity.
LinkedIn: https://www.linkedin.com/in/matthewfloyd
U.S. Air Force veteran with an Electrical Engineering degree who discovered a natural instinct working with databases and business intelligence. Love Microsoft products (especially Power BI, Power Query and SSAS Tabular Models) and learn something new everyday in order to share my knowledge with my colleagues. Happily married for 27 years to my wife Stephanie with two great sons, 18 and 10 years old. I am proud that my 18 year old is attending my alma mater, University of Texas at San Antonio, studying Mechanical Engineering.
Contact: http://www.sqlbi.com
Alberto Ferrari started working with SQL Server in 2000 and immediately focused his interest on Business Intelligence. He and Marco Russo created sqlbi.com, where they publish extensive content about Business Intelligence. Alberto published several books about Analysis Services, Power BI, and Power Pivot. He is a Microsoft MVP and he earned the SSAS Maestro title, the highest level of certification on Microsoft Analysis Services technology. Today, Alberto's main activities are in the delivery of DAX and data modeling workshops for Power BI and Analysis Services all around the world. Alberto offers consulting services on large and complex data warehouses to provide assessments and validation of project analysis or to perform specific problem-solving activities. Alberto is a well-known speaker at many international conferences, like PASS Summit, SQLBits, and Microsoft Ignite. He loves to be on stage both at large events and at smaller user groups meetings, exchanging ideas with other SQL and BI fans. When traveling for work, he likes to engage with local user groups to provide evening sessions about his favorite topics. Thus, you can easily meet Alberto by looking up local Power BI user groups during scheduled courses. Outside of SQLBI, most of Alberto's personal time is spent practicing video games, in the vain hope of eventually beating his son.
LinkedIn: https://www.linkedin.com/in/briancclee/
Brian is the Global Power BI Enablement Lead at NXP Semiconductors, part the Enterprise Business Intelligence (EBI) organization in I.T. Brian leads the Enablement team’s effort in promoting Power BI across the corporation, providing Power BI training and consultation, user support, conducting POCs, pilot evaluation of new capabilities, hosting in-house Power BI User Group meetings, etc. Brian also leads the overall Power BI Roadmap, Governance and Security considerations and implementation. Working along-side embedded BI Partner Leaders and User Champions in organizations across the company, the Enablement team promotes and leads the implementation of Self-Service BI at NXP Semiconductors. NXP has >30K employees in over 33 countries.
LinkedIn: https://www.linkedin.com/in/ginger-grant-3a177b157/
Contact: http://www.DesertIsleSQL.com
Ginger Grant manages the consultancy Desert Isle Group and shares what she has learned while working with data technology to people around the world. As a Microsoft MVP in Data Platform, Microsoft Certified Trainer and an instructor on DataCamp, she focuses on guiding clients to create solutions using the entire Microsoft Data Stack, which includes SQL Server, Power BI, and Azure Data Cloud components. When not working, she protypes the latest pre-release data technologies, maintains her blog http://www.desertislesql.com, and spends time on twitter @desertislesql.
Contact: http://www.sqlbi.com
Alberto Ferrari started working with SQL Server in 2000 and immediately focused his interest on Business Intelligence. He and Marco Russo created sqlbi.com, where they publish extensive content about Business Intelligence. Alberto published several books about Analysis Services, Power BI, and Power Pivot. He is a Microsoft MVP and he earned the SSAS Maestro title, the highest level of certification on Microsoft Analysis Services technology. Today, Alberto's main activities are in the delivery of DAX and data modeling workshops for Power BI and Analysis Services all around the world. Alberto offers consulting services on large and complex data warehouses to provide assessments and validation of project analysis or to perform specific problem-solving activities. Alberto is a well-known speaker at many international conferences, like PASS Summit, SQLBits, and Microsoft Ignite. He loves to be on stage both at large events and at smaller user groups meetings, exchanging ideas with other SQL and BI fans. When traveling for work, he likes to engage with local user groups to provide evening sessions about his favorite topics. Thus, you can easily meet Alberto by looking up local Power BI user groups during scheduled courses. Outside of SQLBI, most of Alberto's personal time is spent practicing video games, in the vain hope of eventually beating his son.
LinkedIn: http://www.linkedin.com/pub/mike-byrd/1/aa0/bbb
Contact: http://logicalread.solarwinds.com/?s=byrd, www.TSQLMentoring.com and SQLServerCentral.com
Former rocket scientist and USAF Fighter Pilot -- now a SQL Server geek (24 years)! Past opportunities include free-lance technical writer for PC Magazine, Senior Software Manager for government sponsored munitions effectiveness committee, and insurance company CTO. Currently senior database engineer consultant for several Austin companies. Presenter at many SQL Saturdays over last 6 years in United States, Europe, and Australia. Specialize in SQL Server performance tuning; database (OLTP OLAP) architecture; trouble-shooting; teaching TSQL (Basic through Advanced). Video presentations (for local SQL Server user groups or SQL Saturdays) can be found at http://usergroup.tv/videos/category/speaker/mike-byrd
LinkedIn: https://www.linkedin.com/in/sqlatspeed
Contact: http://www.sqlatspeed.com
Matt is a Microsoft Data Platform MVP and has worked with SQL Server since 2000. He is the leader of the Lexington, KY PASS local group and a frequent domestic and international community speaker. He's an IDERA ACE alumnus and 2020 Friend of Redgate. His original data professional role was as a database developer, which quickly evolved into query tuning work that further evolved into being a full-fledged DBA in the healthcare realm. He has supported several critical systems utilizing SQL Server and managed dozens of 24/7/365 SQL Server implementations. He currently utilizes that real world experience as a data platform consultant helping clients design solutions that meet their ever-changing business needs.
LinkedIn: https://www.linkedin.com/in/aliciamoniz
Alicia Moniz is a Microsoft AI MVP. She authors the blog HybridDataLakes.com, a blog focused on cloud data learning resources. Alicia has been in the Database/BI services industry for 14+ years and is an expert in T-SQL, Data Modeling, Database Administration, Analytics, Data Visualization, and Data Warehousing. Her skill set spans SQL Server 2005 through 2016 and Azure. She has hands on experience architecting, developing, and optimizing BI solutions in the Microsoft ecosystem. Alicia holds certifications for both AWS/Azure Architect and AWS/Azure Big Data, and is a Microsoft Certified Solution Expert (MCSE): Data Management and Analytics.
LinkedIn: https://www.linkedin.com/in/mattcushing/
Contact: http://sqlkohai.com
Matt started out his career in Accounting and quickly realized he liked data a whole lot more! Starting as a help desk associate, he's moved through support, development, data, and management positions before settling back to his passion for data. Currently working for Applegate Farms in NJ, he loves the people he works with and for, and the company as a whole. Thanks to the input and help from the SQL community, he was able to be ready for the right opportunity in his current position as a BI developer. He also teaches a Database Management class at Rutgers University. Ask him about the Red Sox sometime if you want your ear talked off ;).
LinkedIn: https://www.linkedin.com/in/williamdassaf/
Contact: http://www.sqltact.com
William Assaf, Data Platform MVP, is a principal consultant in Baton Rouge, LA. Initially a .NET developer, and later into database administration and architecture, William currently works with clients on SQL Server and Azure SQL platform optimization, management, disaster recovery and high availability, and leads a crack multi-city team of consulting SQL DBA's. William has written for Microsoft SQL certification exams since 2011 and was the lead author of the 2017 and 2019 editions of "SQL Server Administration Inside Out" by Microsoft Press. William is a member of the Baton Rouge User Groups board, a regional mentor for PASS, and past lead of the annual SQLSaturday Baton Rouge Planning Committee, having run one of the largest SQLSaturdays.
LinkedIn: http://www.linkedin.com/in/meaganlongoria/
Contact: http://datasavvy.me
Meagan Longoria is a business intelligence consultant with Denny Cherry Associates, and lives in Denver, Colorado. She is a Microsoft Data Platform MVP. Meagan spends a lot of time thinking about how to use data integration, DAX, and data visualization techniques to make data useful for people. She enjoys sharing her knowledge and experiences at conferences and user group meetings, as well as through her blog (DataSavvy.me).
LinkedIn: https://www.linkedin.com/in/michaellmckinley
Contact: https://www.mckinley.consulting/blog
Michael McKinley is the founder of McKinley Consulting. Michael has managed projects and workstreams in consulting for the last five years, in areas including data analytics, change management, operations excellence, and supply chain transformation. Most recently, Mr. McKinley helped HCA build an enterprise-wide analytics model for their Human Resources Group, providing insights into how to retain and promote top talent. He is currently engaged on his fourth project with HCA.
LinkedIn: https://www.linkedin.com/in/tracyboggiano
Contact: http://databasesuperhero.com
Tracy Boggiano is a Senior Database Administrator for DocuSIgn. She has spent over 20 years in IT, using SQL Server since 1999, and is currently certified as an MCSE Data Platform. Tracy has worked on SQL Server since 6.5. She has spoken at local user groups and numerous SQLSaturdays. She is currently a co-leader of a TriPASS Local Group in Raleigh, NC. Tracy also tinkered with databases in middle school to keep her sports card collection organized. She blogs at databasesuperhero.com. Her passion outside of SQL Server is volunteering with foster children as their advocate in court through volunteerforgal.org and being a mental health advocate as part of the PAIMI NC Advisory Council.
LinkedIn: http://www.linkedin.com/in/russloski
Contact: http://www.sqlmovers.com
Russ Loski is a SQL Server BI Developer based in Dallas-Fort Worth. He current works as a Data Analytics Engineer for Navisite, a remote managed IT services company. Twenty years ago, he began working with SQL Server 6.5. He has since continued to develop applications connected to all of the versions of SQL Server. He has worked with clients in industries from insurance to healthcare, from movie theaters to American football. Russ is a regular speaker at SQLSaturday events, as well as the SQL Server Users Groups in the North Texas region. Russ likes working with data in various shapes.
LinkedIn: http://www.linkedin.com/in/visibardd
Contact: https://wessexbi.wordpress.com/
I am an independent consultant based in the UK, specializing in all things Excel, especially delivering BI within Excel. I came to appreciate the power and versatility of Excel as an enterprise tool in the mid-90s when managing the delivery of a data warehouse project. Now a freelance consultant, I specialize in Excel automation and BI delivered via Excel. An 11 year veteran of Microsoft#39;s MVP program, my life mission is to persuade small and medium corporates that data analysis and BI is important to them too, and that Power BI can help then find that information, in a straight-forward and cost-effective manner.
LinkedIn: https://www.linkedin.com/in/derekewilson/
I have successfully designed, installed and deployed data management and predictive analytics projects in a variety of industries. I enjoy working on data mining and predictive solutions to take historical data and apply adaptive learning technology to predict future outcomes. We create project that provide the most value to the business through improving service, decreasing costs or increasing revenue through architecture, design, or technology solutions.
LinkedIn: https://www.linkedin.com/pub/leslie-andrews-csm/9/491/b89
Contact: https://www.lace.technology/blog
Leslie Andrews is an IT professional with almost 20 years of experience working with databases, designing databases, as well as designing and developing applications against those databases. 2018-2019 Idera ACE.
LinkedIn: https://www.linkedin.com/pub/kevin-feasel/7/716/504
Contact: http://www.catallaxyservices.com
Kevin Feasel is a Microsoft Data Platform MVP and CTO at Envizage, where he specializes in data analytics with T-SQL and R, forcing Spark clusters to do his bidding, fighting with Kafka, and pulling rabbits out of hats on demand. He is the lead contributor to Curated SQL (https://curatedsql.com), president of the Triangle Area SQL Server Users Group (https://www.meetup.com/tripass), and author of PolyBase Revealed (https://www.apress.com/us/book/9781484254608). A resident of Durham, North Carolina, he can be found cycling the trails along the triangle whenever the weather's nice enough.
LinkedIn: http://www.linkedin.com/in/jameyj
Contact: http://STATCowboy.com
Jamey Johnston is a Senior Data Scientist/Engineer for a large independent OG company. For over 25 years, he has worked for Fortune 500 companies architecting successful platforms in the cloud, on the edge, and on-premises for BI reporting, statistical analysis, ML, and AI. Lately, he spends his time in Azure, Python, R, Power BI, MS SQL, and SAS JMP. He holds a BS in Spatial Analysis from LSU and a Masters of Science in Analytics from Texas AM. He is a professor at the Mays Business School at Texas AM in the MS Analytics program. He is active in his PASS Local Group in Houston, co-leader of the local Power BI users group and data analytics group. He regularly speaks and volunteers at PASS events. He is also a Microsoft Data Platform MVP.
LinkedIn: https://www.linkedin.com/in/ganesh-lohani-6275a716
Ganesh Lohani has 10 years of experience working with Business Intelligence platform and Data Analytics, with over 8 years of experience with MS BI tools and Business Intelligence processes. He is currently working for Stericycle as a senior Business Intelligence Developer. He also enjoy his evening and weekend time in providing online training, coaching and mentoring individuals who want to learn MSBI (T – SQL, SSIS, SSRS, SSAS, and Power BI ) products. He holds MSIS degree from University of Texas at Arlington.
LinkedIn: https://www.linkedin.com/in/wenbin-billy-zhao/
Wenbin Zhao is a Sr. Data Analyst and Tableau developer. He graduated from Brigham Young University and worked in the finance and data analytics field for the last 14 years. He loves everything data and business analytics, project management, and teamwork. He has been a Tableau user since 2013 and also participated in Tableau Hackathon in Austin. His team built a prototype embedded Tableau dashboard to track eye-movements by utilizing Tableau API and Python libraries to help ALS patients. His current focus at YETI is to help building consumer insights and predictive capabilities through visualization and data science. He’s also a teaching assistant of Data Analytics and Visualization program at University of Texas at Austin’s McCombs School
The following is a list of sponsors that helped fund the event.


This inspection only reports if the project or module is configured to use a language level of 5.0 or higher.
Use the first checkbox below to not offer to convert byte[] or short[] parameters to vararg.
Use the second checkbox below to ignore methods overriding a method in a super class.
New in 10.5, Powered by InspectionGadgets


|
Jetson Inference
DNN Vision Library
|
Hardware-accelerated video decoder for Jetson using GStreamer. More...
#include <gstDecoder.h>
Public Member Functions | |
| ~gstDecoder () | |
| Destructor. More... | |
| template<typename T > | |
| bool | Capture (T **image, uint64_t timeout=UINT64_MAX) |
| Capture the next decoded frame. More... | |
| virtual bool | Capture (void **image, imageFormat format, uint64_t timeout=UINT64_MAX) |
| Capture the next decoded frame. More... | |
| virtual bool | Open () |
| Open the stream. More... | |
| virtual void | Close () |
| Close the stream. More... | |
| bool | IsEOS () const |
| Return true if End Of Stream (EOS) has been reached. More... | |
| virtual uint32_t | GetType () const |
| Return the interface type (gstDecoder::Type) More... | |
| Public Member Functions inherited from videoSource | |
| virtual | ~videoSource () |
| Destroy interface and release all resources. More... | |
| template<typename T > | |
| bool | Capture (T **image, uint64_t timeout=UINT64_MAX) |
| Capture the next image from the video stream. More... | |
| bool | IsStreaming () const |
| Check if the device is actively streaming or not. More... | |
| uint32_t | GetWidth () const |
| Return the width of the stream, in pixels. More... | |
| uint32_t | GetHeight () const |
| Return the height of the stream, in pixels. More... | |
| uint32_t | GetFrameRate () const |
| Return the framerate, in Hz or FPS. More... | |
| const URI & | GetResource () const |
| Return the resource URI of the stream. More... | |
| const videoOptions & | GetOptions () const |
| Return the videoOptions of the stream. More... | |
| bool | IsType (uint32_t type) const |
| Check if this stream is of a particular type. More... | |
| template<typename T > | |
| bool | IsType () const |
| Check if a this stream is of a particular type. More... | |
| const char * | TypeToStr () const |
| Convert this stream's class type to string. More... | |
Static Public Member Functions | |
| static gstDecoder * | Create (const videoOptions &options) |
| Create a decoder from the provided video options. More... | |
| static gstDecoder * | Create (const URI &resource, videoOptions::Codec codec) |
| Create a decoder instance from resource URI and codec. More... | |
| static bool | IsSupportedExtension (const char *ext) |
| Return true if the extension is in the list of SupportedExtensions. More... | |
| Static Public Member Functions inherited from videoSource | |
| static videoSource * | Create (const videoOptions &options) |
| Create videoSource interface from a videoOptions struct that's already been filled out. More... | |
| static videoSource * | Create (const char *URI, const videoOptions &options=videoOptions()) |
| Create videoSource interface from a resource URI string and optional videoOptions. More... | |
| static videoSource * | Create (const char *URI, const commandLine &cmdLine) |
| Create videoSource interface from a resource URI string and parsing command line arguments. More... | |
| static videoSource * | Create (const char *URI, const int argc, char **argv) |
| Create videoSource interface from a resource URI string and parsing command line arguments. More... | |
| static videoSource * | Create (const int argc, char **argv, int positionArg=-1) |
| Create videoSource interface by parsing command line arguments, including the resource URI. More... | |
| static videoSource * | Create (const commandLine &cmdLine, int positionArg=-1) |
| Create videoSource interface by parsing command line arguments, including the resource URI. More... | |
| static const char * | Usage () |
| Usage string for command line arguments to Create() More... | |
| static const char * | TypeToStr (uint32_t type) |
| Convert a class type to a string. More... | |
Static Public Attributes | |
| static const uint32_t | Type = (1 << 1) |
| Unique type identifier of gstDecoder class. More... | |
| static const char * | SupportedExtensions [] |
| String array of supported video file extensions, terminated with a NULL sentinel value. More... | |
Protected Member Functions | |
| gstDecoder (const videoOptions &options) | |
| void | checkMsgBus () |
| void | checkBuffer () |
| bool | buildLaunchStr () |
| bool | init () |
| bool | discover () |
| bool | isLooping () const |
| Protected Member Functions inherited from videoSource | |
| videoSource (const videoOptions &options) | |
Static Protected Member Functions | |
| static void | onEOS (_GstAppSink *sink, void *user_data) |
| static GstFlowReturn | onPreroll (_GstAppSink *sink, void *user_data) |
| static GstFlowReturn | onBuffer (_GstAppSink *sink, void *user_data) |
Protected Attributes | |
| _GstBus * | mBus |
| _GstAppSink * | mAppSink |
| _GstElement * | mPipeline |
| Event | mWaitEvent |
| RingBuffer | mBufferYUV |
| RingBuffer | mBufferRGB |
| std::string | mLaunchStr |
| bool | mCustomSize |
| bool | mCustomRate |
| bool | mEOS |
| size_t | mLoopCount |
| size_t | mFrameCount |
| imageFormat | mFormatYUV |
| Protected Attributes inherited from videoSource | |
| bool | mStreaming |
| videoOptions | mOptions |
Hardware-accelerated video decoder for Jetson using GStreamer.
gstDecoder supports loading video files from disk (MKV, MP4, AVI, FLV) and RTP/RTSP network streams over UDP/IP. The supported decoder codecs are H.264, H.265, VP8, VP9, MPEG-2, MPEG-4, and MJPEG.
| gstDecoder::~gstDecoder | ( | ) |
Destructor.
|
protected |
|
protected |
|
inline |
Capture the next decoded frame.
|
virtual |
|
protected |
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protected |
|
virtual |
|
static |
Create a decoder from the provided video options.
|
static |
Create a decoder instance from resource URI and codec.
|
protected |
|
inlinevirtual |
Return the interface type (gstDecoder::Type)
Reimplemented from videoSource.
|
protected |
|
inline |
Return true if End Of Stream (EOS) has been reached.
In the context of gstDecoder, EOS means that playback has reached the end of the file, and looping is either disabled or all loops have already been run. In the case of RTP/RTSP, it means that the stream has terminated.
|
inlineprotected |
|
static |
Return true if the extension is in the list of SupportedExtensions.
| ext | string containing the extension to be checked (should not contain leading dot) |
|
staticprotected |
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staticprotected |
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staticprotected |
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virtual |
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protected |
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protected |
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protected |
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protected |
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protected |
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protected |
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protected |
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protected |
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protected |
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protected |
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protected |
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protected |
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protected |
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static |
String array of supported video file extensions, terminated with a NULL sentinel value.
The supported extension are:
|
static |
Unique type identifier of gstDecoder class.


DatabaseConnector is part of the OHDSI Methods Library.
connectionDetails <- createConnectionDetails(dbms="postgresql",
server="localhost",
user="root",
password="blah",
schema="cdm_v4")
conn <- connect(connectionDetails)
querySql(conn,"SELECT COUNT(*) FROM person")
disconnect(conn)
## regular data insert
insertTable(connection = connection,
tableName = "scratch.somedata",
data = data,
dropTableIfExists = TRUE,
createTable = TRUE,
tempTable = FALSE,
useMppBulkLoad = FALSE)
## bulk data insert with Redshift or PDW
insertTable(connection = connection,
tableName = "scratch.somedata",
data = data,
dropTableIfExists = TRUE,
createTable = TRUE,
tempTable = FALSE,
useMppBulkLoad = TRUE)
Requires R. Also requires Java 1.6 or higher (Oracle Java is recommended. Issues have been reported when using GCJ.)
Please note that this package requires Java to be installed. If you don’t have Java already installed on your computed (on most computers it already is installed), go to java.com to get the latest version.
To be able to use Windows authentication for SQL Server, you have to install the JDBC driver. Download the .exe from Microsoft and run it, thereby extracting its contents to a folder. In the extracted folder you will find the file sqljdbc_4.0/enu/auth/x64/sqljdbc_auth.dll (64-bits) or sqljdbc_4.0/enu/auth/x86/sqljdbc_auth.dll (32-bits), which needs to be moved to location on the system path, for example to c:/windows/system32. If you not have write access to any folder in the system path, you can also specify the path to the folder containing the dll by setting the environmental variable PATH_TO_AUTH_DLL
, so for example Sys.setenv("PATH_TO_AUTH_DLL" = "c:/temp")
.
DatabaseConnector also depends on the OHDSI DatabaseConnectorJars and SqlRender packages.
For Redshift Bulk Mpp inserts, the cloudyR aws S3 package is required.
To install the latest stable version, install from CRAN:
install.packages("DatabaseConnector")
To install the latest development version, install from GitHub:
install.packages("devtools")
devtools::install_github("ohdsi/DatabaseConnectorJars")
devtools::install_github("ohdsi/DatabaseConnector")
To download and use the JDBC drivers for BigQuery, Impala, or Netezza, see these instructions.
DatabaseConnector is licensed under Apache License 2.0. The JDBC drivers fall under their own respective licenses.


Simple templating intellisense
Example ho intellisense works.
Input
Small input
Medium input
Textarea
Small textarea
Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry's standard dummy text ever since the 1500s, when an unknown printer took a galley of type and scrambled it to make a type specimen book. It has survived not only five centuries, but also the leap into electronic typesetting, remaining essentially unchanged. It was popularised in the 1960s with the release of Letraset sheets containing Lorem Ipsum passages, and more recently with desktop publishing software like Aldus PageMaker including versions of Lorem Ipsum.
Medium textarea
Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry's standard dummy text ever since the 1500s, when an unknown printer took a galley of type and scrambled it to make a type specimen book. It has survived not only five centuries, but also the leap into electronic typesetting, remaining essentially unchanged. It was popularised in the 1960s with the release of Letraset sheets containing Lorem Ipsum passages, and more recently with desktop publishing software like Aldus PageMaker including versions of Lorem Ipsum.


Before Change
Initial state is a dictionary: key = vehicle IDs, value = state describing car
self.total_reward = 0
self.pos = {}
self.vel = {}
self.ids = self.traci_connection.vehicle.getIDList()
self.controlled_ids.clear()
self.rl_ids.clear()
After Change
// collect ids and prepare id and vehicle lists
self.ids = self.traci_connection.vehicle.getIDList()
self.controlled_ids.clear()
self.sumo_ids.clear()
self.rl_ids.clear()
self.vehicles.clear()
// create the list of colors used to different between different types of


Previous: Grammar methods dealing with unvalued symbols, Up: Valued and unvalued symbols [Contents][Index]
By default, Libmarpa’s valuator objects
assume that
non-terminal symbols have
no semantics.
The archetypal application will need to register
symbols that contain semantics.
The primary method for doing this is
marpa_v_symbol_is_valued()
.
Applications will typically register semantics by rule,
and these applications will find
the
marpa_v_rule_is_valued()
method more convenient.
These methods, respectively,
set and query
the valued status of symbol sym_id.
marpa_v_symbol_is_valued_set()
will set
the valued status to
the value of
its status argument.
A valued status of 1 indicates that the symbol is valued.
A valued status of 0 indicates that the symbol is unvalued.
If the valued status is locked,
an attempt to change to a status different from the
current one will fail
(error code MARPA_ERR_VALUED_IS_LOCKED
).
Return value: On success, the valued status after the call. If value is not either 0 or 1, or on other hard failure, -2.
These methods, respectively,
set and query
the valued status
for the LHS symbol of rule rule_id.
marpa_v_rule_is_valued_set()
sets
the valued status to the value
of its status argument.
A valued status of 1 indicates that the symbol is valued.
A valued status of 0 indicates that the symbol is unvalued.
If the valued status is locked,
an attempt to change it to a status different from the
current one will fail
with error code MARPA_ERR_VALUED_IS_LOCKED
.
Rules have no valued status of their own. The valued status of a rule is always that of its LHS symbol. These methods are conveniences — they save the application the trouble of looking up the rule’s LHS.
Return value: On success, the valued status of the rule rule_id’s LHS symbol after the call. If value is not either 0 or 1, or on other hard failure, -2.
This methods locks the valued status of all symbols to 1, so that all symbols will always be valued. Hard fails if this is not possible, for example because one of the grammar’s symbols already is locked at a valued status of 0.
Return value: On success, a non-negative integer.
On hard failure, returns -2,
and sets the error code to an appropriate
value, which will never be
MARPA_ERR_NONE
.


| Opcode/Instruction | Op /En | 64/32 bit Mode Support | CPUID Feature Flag | Description |
|---|---|---|---|---|
|
EVEX.512.66.0F38.W0 CA /r VRCP28PS zmm1 {k1}{z}, zmm2/m512/m32bcst {sae} |
FV | V/V | AVX512ER | Computes the approximate reciprocals ( < 2^-28 relative error) of the packed single-precision floating-point values in zmm2/m512/m32bcst and stores the results in zmm1. Under writemask. |
| Op/En | Operand 1 | Operand 2 | Operand 3 | Operand 4 |
| FV | ModRM:reg (w) | ModRM:r/m (r) | NA | NA |
Description
Computes the reciprocal approximation of the float32 values in the source operand (the second operand) and store the results to the destination operand (the first operand) using the writemask k1. The approximate reciprocal is evaluated with less than 2^-28 of maximum relative error prior to final rounding. The final results are rounded to < 2^-23 relative error before written to the destination.
Denormal input values are treated as zeros and do not signal #DE, irrespective of MXCSR.DAZ. Denormal results are flushed to zeros and do not signal #UE, irrespective of MXCSR.FZ.
If any source element is NaN, the quietized NaN source value is returned for that element. If any source element is ±∞, ±0.0 is returned for that element. Also, if any source element is ±0.0, ±∞ is returned for that element.
The source operand is a ZMM register, a 512-bit memory location, or a 512-bit vector broadcasted from a 32-bit memory location. The destination operand is a ZMM register, conditionally updated using writemask k1.
EVEX.vvvv is reserved and must be 1111b otherwise instructions will #UD.
A numerically exact implementation of VRCP28xx can be found at https://software.intel.com/en-us/articles/refer-ence-implementations-for-IA-approximation-instructions-vrcp14-vrsqrt14-vrcp28-vrsqrt28-vexp2.
Operation
VRCP28PS (EVEX encoded versions)
(KL, VL) = (16, 512)
FOR j (cid:197) 0 TO KL-1
i (cid:197) j * 32
IF k1[j] OR *no writemask* THEN
IF (EVEX.b = 1) AND (SRC *is memory*)
THEN DEST[i+31:i] (cid:197) RCP_28_SP(1.0/SRC[31:0]);
ELSE DEST[i+31:i] (cid:197) RCP_28_SP(1.0/SRC[i+31:i]);
FI;
ELSE
IF *merging-masking*
; merging-masking
THEN *DEST[i+31:i] remains unchanged*
ELSE
; zeroing-masking
DEST[i+31:i] (cid:197) 0
FI;
FI;
ENDFOR;
| Input value | Result value | Comments |
|---|---|---|
| NAN | QNAN(input) | If (SRC = SNaN) then #I |
| 0 ≤ X < 2-126 | INF | Positive input denormal or zero; #Z |
| -2-126 < X ≤ -0 | -INF | Negative input denormal or zero; #Z |
| X > 2126 | +0.0f | |
| X < -2126 | -0.0f | |
| X = +∞ | +0.0f | |
| X = -∞ | -0.0f | |
| X = 2-n | 2n | Exact result (unless input/output is a denormal) |
| X = -2-n | -2n | Exact result (unless input/output is a denormal) |
Intel C/C++ Compiler Intrinsic Equivalent
VRCP28PS _mm512_rcp28_round_ps ( __m512 a, int sae);
VRCP28PS __m512 _mm512_mask_rcp28_round_ps(__m512 s, __mmask16 m, __m512 a, int sae);
VRCP28PS __m512 _mm512_maskz_rcp28_round_ps( __mmask16 m, __m512 a, int sae);
SIMD Floating-Point Exceptions
Invalid (if SNaN input), Divide-by-zero
Other Exceptions
See Exceptions Type E2.


--- title: "Commercial Projects" ---
Interested in entrepreneurship or wanting to try to operate a small-scale business? Join the Commercial arm of Enactus LSE! Our commercial arm was launched in 2012, and commercial projects are initiated to provide sustainable funding for our team.
Contact Jonathan
The F&B project is catered to provide students with some of their favourite drinks (e.g. bubble tea) and snacks to brighten up their day, while still raising funds for our social projects.
The Festive Merchandise project gives members opportunities to display their entrepreneurial skills by allowing them to sell items during certain festivals. Apart from that, members also conduct market researches to find out which items are higher in demand and can allow us to raise more funds.
Auburn is an original musical production created by two LSE students and tells the story of a young girl named Rose and how she overcame her stutter problem with singing and a relationship with a guy named Nico. This musical production raised awareness of disabilities suffered by young people as well as the LGBT+ community. Auburn received the prestigious LSE Annual Fund award and attracted over 500 people for its first show.


{% markdown %}
# Get in touch
If you’ve got a question, idea or suggestion get in touch with the Design System team.
## Slack
Use [#hmcts-design-system](https://ukgovernmentdigital.slack.com/messages/hmcts-design-system), on cross-government Slack ([open in app](https://ukgovernmentdigital.slack.com/messages/hmcts-design-system))
## Email
Email the Design System team on [design-sytem<EMAIL_ADDRESS>{% endmarkdown %}


@import ".view/header.html"
Welcome to Krait!
Originally it said "Merry Christmas from Krait" but the holidays are over :(
Click this button today!
It's @ctrl.time_str already!
@if ctrl.alerts_exist == 0:
@for idx in range(1, 4):
LOOK AT IT (for the @(str(idx) + ctrl.suffixes.get(idx, "th")) time)
this appears 3 times but it's in the original html only once! YEAAAH demos!
@/for
@/if
Why choose Krait?
@for heading, para in ctrl.subh_left:
@heading@
@para@
@/for
@for heading, para in ctrl.subh_right:
@heading@
@para@
@/for


Documentation
First Steps
Analyze JavaScript coding
Make sure you have a folder which contains html files together with JavaScript code. You may for
instance use git to replicate the source code of this application to a local folder.
Open this application in a browser
Choose in the menu File -> Extract Code from File System to SOMIX model (w/o .git). Choose the main
folder of the application. All extracted components will be displayed in a circle.
Choose in the menu FIle -> Open Work Folder. Specify a folder where the generation information for all
diagrams shall be stored. In case you analyze this application choose the folder models.
In case you use this application. Choose in the menu File -> Read Diagram. You will see a list of existing diagrams.
In case there are no diagram informations yet. Choose in the menu File -> New Diagram. Enter a name for the diagram.
Choose Diagram -> Explore model to choose components to be displayed.
Demo
It is possible to display and use demo data.
Follow
these steps:
Open the application in a Browser
Choose in the menu Help -> Load demo data
Do a right mouse click into the pane and choose "Start Force-directed graph". Wait some time and choose
then "Stop Force-directed graph".
Click on one of the red or blue circles with the right mouse button. Choose "Add element with all
neighbors"
Do a right mouse click into the pane and choose Demo Diagram
Play around with left and right clicks of the mouse on elements, into boxes and onto the pane. Use also
the scrool wheel of the mouse.
You may also choose Diagram -> Explore Model. Use this steps:
Open the application in a Browser
Choose in the menu Help -> Load demo data
Enter for instance ^Z.*LOG in the input field. This filters for all elements which start with Z and have
a LOG
somewhre in the name. You can use any Regex expression. The search is case insensitive.
The Button Apply Filter may not yet work, instead move the mouse down.
You can scroll with the mouse wheel in the result list.
Make a right click on an element and choose "Add element with all neighbors"
Choose cancel
Make a right click in the pane and choose Demo Diagram.
Play around with left and right clicks of the mouse on elements, into boxes and onto the pane. Use also
the scrool wheel of the mouse.
Generate a SOMIX model from files in a local folder
It is possible to analyze folders in the local file system:
Extract a model where files are date and folders are groupings. Choose File -> Extract File System to
SOMIX
model (w/o .git). A pop up opens where you specify a local folder on
your computer.
Content in .git folders is ignored. This is in most cases helfull when git is used. Git stores many
files which
are normally not of interest.
Extract a model of the code in files. This is currently in development. Extract Code from File System to
SOMIX
model (w/o .git). A pop up opens where you specify a local folder on
your computer.
Content in .git folders is ignored. This is in most cases helfull when git is used. Git stores many
files which
are normally not of interest.
Use a SOMIX model
When you have a SOMIX model (You will need to use SAP2Moose for now):
Choose File -> Load Model and load a SOMIX model
Choose File -> Open Work Folder (Generation informations for files will be stored in this folder)
Choose File -> New Diagram and enter a name for the new diagram.
Make a right click into the pane and choose the name of your diagram. This will change the view and
display:
"This diagram is currentl empty: ..."
Make a right mouse click into the pane and choose "Make this diagram active". When you later add
elements to a
diagram, these elements will be added to the active diagram.
Now choose an element and add it to the active diagram like it was described on this page under "First
Steps" ->
"Demo".
To save the displayed diagram choose File -> Save Displayed Diagram.
When you repeat your work do
- Load a new SOMIX model. This will normally not be the model you used before. The diagram will be
automatically adapted to the new software version.
- Choose File -> Open Work Folder
- Choose File -> Read Diagram (You will need "Import old Diagram (XML) only when you worked with
the
Smalltalk version of Moose2Model).
Implemented Features
General features
- Load a SOMIX model
- Read a folder and create a SOMIX model of the contained folders and files.
- Create a new diagram
- Force-dragged positioning. Start and stop with a context click in background of pane
- Scrolling by dragging the pane(with "right" mouseclick")
- Dragging elements (with "left" mouseclick)
- Zooming with the wheel of the mouse
- Menu Diagram
- Search elements in the model. The search is case insensitive.
- Switch between dark and white theme
- Remove all hightlighting of the displayed elements
- Context click on elements:
- Add an element with all neighbors to the active diagram
- Redo adding an element with all neighbors to the active diagram
- Get informations on the element
- Enter or edit a comment for an element
- Supress an element with all children
- Redo supressing an element with all children
- Jump to code with when a link is contained in the model (adt links have to be activated for
Eclipse)
- Remove pinning of recently dragged elements
- Highlight elements or the using or used elements
- Context click on pane:
- (Only in the diagram with all model elements: Toogle the display of element names)
- Set a diagram active (But not the diagram with all elements)
- Start and Stop Force-directed graph
- Jump to other diagram
- Save information to generate a diagram to file
- Specify a workfolder first. These folder contains all diagrams which belong to the same
model
- Save the generation information for the displayed diagram. It be stored in a file with
extension
.m2m and similar name.
- Read the generation information from an .m2m file. You should have all required model data
loaded
before. A diagram with identical name is created.
- Import xml files from the old Smalltalk version of Moose2Model.
- Please note that no warning is yet raised when information is lost due to wrong handling.
Header
- Display the diagram which is displayed and which is active.
- Unsaved changes are marked with a bullet point behind the name of a diagram.

It can be animated as a force-directed graph. This works well for small models.
The main intention of this application is not to make force-directed graph, so other tools might work better
here.
Circuit Diagram for Software
- Code is displayed as orange box
- Data is displayed as blue circle
- Persistent data is displayed as green circle
- Groupings are indicated by a dashed box and include all elements contained in them
- Elements can be commented
Planned Features
Most current features of Moose2Model as are available currently in Smalltalk. And some more.


{% extends '_layouts/journey_layout_2-3_no_blue_box.html' %} {% block page_title %} GP details NHS.UK {% endblock %} {% block pageTitle %} Confirmation of appointment at Meanwood Group Practice {% endblock %} {% block pageIntro %} {% endblock %} {% block content %}
An appointment has been booked to see Dr Angela Carter at 10.10am today
We have sent a text message to your mobile telephone number ending in –7205 to confirm this.
(This text message will say:
"You have booked online an appointment to see Dr Angela Carter at 10.10am today. If you did not make this appointment reply to this text message with 'Cancel'.")
If you wish to change or cancel your appointment contact the GP practice by calling 0113 230 5055.
{% endblock %} {% block emergencyContent %} {% endblock%}§ {% block mutedCallout%} {% endblock%} {% block body_after %} {% endblock %}


A link to the file in the root folder built by closure. moesif.min.js is included in the header.
Click on the button below should send an request to a placeholder API server. The even should by captured by moesif and send to Moesif.


|
| Local Properties | ||
| Managed Object Types | Data Object Types | All Properties | All Methods |
Properties
| Name | Type | Description |
|---|---|---|
| metadata | CnsVolumeMetadata |
Metadata for the container volume.
|
| volumeId | CnsVolumeId |
Unique identifier for the volume.
|
| Properties inherited from DynamicData | ||
| None |
| Top of page | Local Properties | ||
| Managed Object Types | Data Object Types | All Properties | All Methods |


Both of these metrics use twitter data to assess the reilability of the MTA
Problems Now?: is a measure of how many tweets there are about a specific line in the last hour.
Delays?: is a measure of how many recent tweets mention delays.


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END OF DAYS (Universal/Beacon) Starring: Arnold Schwarzenegger, Gabriel Byrne, Kevin Pollak, Robin Tunney, Rod Steiger, CCH Pounder, Miriam Margolyes. Screenplay: Andrew W. Marlowe. Producers: Armyan Bernstein and Bill Borden. Director: Peter Hyams.  Running Time: 118 minutes. Reviewed by Scott Renshaw.
For about ten seconds, there is the faint hope that END OF DAYS is clued in to its own absurdity. Our hero, Jericho Cane (Arnold Schwarzenegger), finds himself in the basement of a New York City Catholic church, protecting a woman named Christine York (Robin Tunney) and learning a lesson in the apocalypse from a priest (Rod Steiger). It seems that the Evil One has taken human form (Gabriel Byrne), and plans to bring about the end of days by impregnating Christine with his child. In order for the anti-Christ incarnation to "take," according to the priest, said consummation must occur between 11 p.m. and midnight on December 31, 1999. Incredulously, Jericho asks the priest, "Is that Eastern Time?"
It's a nice line, and it couldn't come at a more crucial time. For over an hour, END OF DAYS fairly drowns in preposterousness. It's the kind of film where a suspect is found carrying a matchbook that leads Jericho directly to important clues, and where the same suspect also has something Jericho cleverly intuits is Christine's name carved into his stomach. It's the kind of film where Jericho locates Christine by searching though New York City driver's license records, apparently finding only one Christine York in a city of 10 million people. It's the kind of film where Jericho grabs a single book off a shelf, and miraculously finds a clue to a mysterious pendant he has obtained. And it's the kind of film where, while being pursued by Satan himself, Christine stops to grab her coat on the way out the door. After sixty minutes of painful head smacking, I was ready for that glimmer of hope. Maybe, just maybe, it was time to start having some fun with the end of the world as we know it.
This, however, is a supernatural thriller that takes itself far too seriously. Much of that seriousness revolves around Schwarzenegger, who plays an ex-cop-turned-private security professional, wallowing in alcoholism and self-pity after the death of his wife and daughter (for which he had some indirect responsibility). One assumes this is meant to be a chance for Schwarzenegger to stretch his serious actor muscles in a plot line ready-made for a little redemption (Christine owns a music box just like his daughter had, in case the surrogate daughter angle was too obscure for you). But Arnold plays tormented as just plain mad, and the moment when he reaches divine understanding of how he can defeat the Dark Angel is brutally, unintentionally hysterical. Turning END OF DAYS into a character piece is a mistake; letting Schwarzenegger play that character is flat-out foolish.
It probably seemed like a good idea at the time, since there's also plenty of gun-firin', helicopter-danglin', subway car-explodin' action. Some of it is even pretty lively, including the early chase sequence in which a suspended Schwarzenegger pursues a sniper over a rooftop. Peter Hyams is a true hack-tion director, and he usually knows how to keep a film moving along with fireballs a-plenty and several kajillion rounds of ammunition fired off. There's also quite a bit of unpleasant brutality in the form of snapped necks, severed jugular veins and punched-out vital organs. It's not that you expect Satan to be a nice guy -- indeed, Gabriel Byrne plays him effectively as a smug libertine with a _very_ short temper -- but that it's hard to settle in and enjoy END OF DAYS as an adventure thriller when so much is treated as grim and portentous.
And that's really the fatal flaw of END OF DAYS: it never decides on an appropriate tone. If we're expected simply to enjoy the carnage, it's foolish to make the hero a lost soul. If we're expected to take the dark scenario seriously, the ridiculous plot contrivances make that impossible. If we're expected to be genuinely scared, the comic relief is a cheat (though sidekick Kevin Pollak gets one killer line after the ubiquitous cat-jumping-out-of-nowhere). END OF DAYS could have been effective either as a genre goof or as edgy SEVEN-esque millennial creep show. Instead, it's a murky dud that tries to chuckle its way out of the corner it writes itself into.
On the Renshaw scale of 0 to 10 apocalapses: 4.
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Bacon ipsum dolor sit amet beef venison salami filet mignon jerky. Kevin meatloaf jerky bacon, brisket andouille tenderloin. Drumstick tongue fatback salami shankle pork loin meatball turducken leberkas shank. Tail tongue pig, meatball filet mignon venison drumstick cow flank fatback hamburger.  Andouille sirloin bacon, shoulder leberkas jowl venison tenderloin porchetta. Turducken ground round shoulder short ribs, meatloaf meatball jerky landjaeger spare ribs.
Strip steak cow pork loin pork, short ribs ball tip beef ribs porchetta pancetta meatball capicola ground round pork chop salami. Capicola strip steak brisket pork prosciutto kielbasa sausage. Ground round meatball pancetta turducken short ribs, swine capicola turkey. Landjaeger porchetta short loin, capicola ball tip corned beef prosciutto bresaola shank chuck turkey. Cow tail andouille sausage biltong rump flank beef kevin turducken landjaeger corned beef kielbasa ham hock. Turducken andouille ball tip biltong, fatback chuck corned beef bresaola tongue sirloin shankle leberkas boudin beef ribs. Turkey kielbasa corned beef beef.
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Ball tip biltong hamburger tenderloin, shankle tail kielbasa doner porchetta meatloaf meatball flank. Brisket leberkas rump pig. Chuck cow tongue tail venison. Tri-tip kielbasa cow chicken ground round sirloin.


Intercom: Officer K D 6 - 3 . 7. Let’s begin. Ready?
K: Yes, sir
Intercom: Recite your baseline.
K: And blood-black nothingness began to spin
K: A system of cells interlinked within cells,
K: interlinked within cells, interlinked within one stem.

K: And dreadfully distinct against the dark, a tall white fountain played...
Intercom: Cells.
K: Cells.
Intercom: Have you ever been in an institution?
Intercom: Cells.
K: Cells.
Intercom: Do they keep you in a cell?
Intercom: Cells.
K: Cells.
Intercom: When you're not performing your duties, do they keep you in a little box?
Intercom: Cells.
K: Cells.
Intercom: Interlinked.
K: Interlinked.
Intercom: What's it like to hold the hand of someone you love?
Intercom: Interlinked.
K: Interlinked.
Intercom: Did they teach you how to feel, finger to finger?
Intercom: Interlinked.
K: Interlinked.
Intercom: Do you long for having your heart interlinked?
Intercom: Interlinked.
K: Interlinked.
Intercom: Do you dream about being interlinked?
K: Interlinked.

Intercom: Interlinked.
K: Interlinked.
Intercom: Do you feel that there's a part of you that's missing?
Intercom: Interlinked.
K: Interlinked.
Intercom: Within cells interlinked.
K: Within cells interlinked.
Intercom: Why don't you say that three times: "within cells interlinked"
K: Within cells interlinked.
K: Within cells interlinked.
K: Within cells interlinked.
Intercom: We're done.
Intercom: Constant K.
Intercom: You can pick up your bonus.
K: Thank you, sir.
Intercom: Cells
K: Cells
Intercom: Have you ever been in an institution. Cells
K: Cells
Intercom: When you're not performing your duties, do they keep you in a little box? Cells.
K: Cells
Intercom: Interlinked. What’s it like to hold the hand of someone you love?
 Dreadfully
K: Dreadfully
Intercom: Do you like being separated from other people? Distinct
K: Distinct
Intercom: Dreadfully distinct
K: Dreadfully distinct
Intercom: Dark
K: Dark
Intercom: Within cells interlinked
K: Within cells interlinked
Intercom: Withing one stem
K: Withing one stem
Intercom: And dreadfully distinct
K: And dreadfully distinct
Intercom: Against the dark
K: Against the dark
Intercom: A tall white fountain played
K: A tall white fountain played
Intercom: You're not even close to baseline


Dominic Raab praises Filipino authorities for rescue of abducted British nationals Alan and Wilma Hyrons
The Foreign Secretary has praised the “tremendous efforts” of authorities in the Philippines that helped secure the rescue of two British nationals who were abducted last month.
Alan and Wilma Hyrons were abducted by gunmen believed to be allied with the so-called Islamic State group on October 4.
They were successfully rescued during a military operation on the island of Sulu, carried out by Filipino armed forces, on Monday.
Dominic Raab said: “I am pleased to confirm that both Alan and Wilma Hyrons are safe and well, and being looked after by the Philippine authorities.
“We worked closely with the Government of the Philippines on Alan and Wilma’s case over the last two months. I am very grateful for their tremendous efforts.
“We are in particular grateful to their Armed Forces for their courage throughout a difficult operation which resulted in Alan and Wilma’s release.
Sorry, this content isn't available on your device.
“Foreign Office officials have been in close contact with Alan and Wilma’s family throughout this ordeal. We request their privacy during this emotional time.”
The couple were abducted from a beach resort in southern Zamboanga del Norte province.
Witnesses reported seeing them being taken from a hut at nightfall and dragged to a motorboat.
Their abduction sparked a massive search in the region, which is located approximately 1,500 kilometres (932 miles) south of Manila.
British Ambassador to the Philippines, Daniel Pruce, tweeted: “Fantastic news! My sincerest thanks to all involved.”


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[viewBag] title = "Sing Bet" url = "/partners/singbet" layout = "partner" is_hidden = 1 navigation_hidden = 1 previevImg = "/singbet-logo-port.jpg" previevText = "Singbet offers the most football leagues and events both pre-match and in-play. Often Singbet limits are also much larger than its competitors." ==
It is difficult for us to review Singbet as they are unlicensed and probably the most unfair bookmaker in the market today – yet they are also one of the biggest Asian bookmakers by far.
Singbet offers the most football leagues and events both pre-match and in-play. Often Singbet limits are also much larger than its competitors, and they offer games that are not available anywhere else.
They have a competitive offering on Asian handicap corners and cards markets as well as outrights for all the major leagues, although the outright betting limits are quite often very small.
Singbet operate a ‘shareholder’ business model, which pays-out lucrative commissions and rewards to agents. In return, they profile clients aggressively and only permit square business.
Punters are warned that Singbet have been known to void bets after an event has finished if they suspect any wrong doing. This includes arbitrage players, professional betting syndicates, big ‘price-shorteners’ – they DO NOT accept these players.
Minimum 50% position taking for the agents, i.e. only 50% of the bet staked is valid.


| lims {ggplot2} | R Documentation |
This is a shortcut for supplying the limits
argument to the individual
scales. By default, any values outside the limits specified are replaced with
NA
. Be warned that this will remove data outside the limits and this can
produce unintended results. For changing x or y axis limits without
dropping data observations, see coord_cartesian()
.
lims(...) xlim(...) ylim(...)
... |
For For |
To expand the range of a plot to always include
certain values, see expand_limits()
. For other types of data, see
scale_x_discrete()
, scale_x_continuous()
, scale_x_date()
.
# Zoom into a specified area ggplot(mtcars, aes(mpg, wt)) + geom_point() + xlim(15, 20) # reverse scale ggplot(mtcars, aes(mpg, wt)) + geom_point() + xlim(20, 15) # with automatic lower limit ggplot(mtcars, aes(mpg, wt)) + geom_point() + xlim(NA, 20) # You can also supply limits that are larger than the data. # This is useful if you want to match scales across different plots small <- subset(mtcars, cyl == 4) big <- subset(mtcars, cyl > 4) ggplot(small, aes(mpg, wt, colour = factor(cyl))) + geom_point() + lims(colour = c("4", "6", "8")) ggplot(big, aes(mpg, wt, colour = factor(cyl))) + geom_point() + lims(colour = c("4", "6", "8")) # There are two ways of setting the axis limits: with limits or # with coordinate systems. They work in two rather different ways. last_month <- Sys.Date() - 0:59 df <- data.frame( date = last_month, price = c(rnorm(30, mean = 15), runif(30) + 0.2 * (1:30)) ) p <- ggplot(df, aes(date, price)) + geom_line() + stat_smooth() p # Setting the limits with the scale discards all data outside the range. p + lims(x= c(Sys.Date() - 30, NA), y = c(10, 20)) # For changing x or y axis limits **without** dropping data # observations use [coord_cartesian()]. Setting the limits on the # coordinate system performs a visual zoom. p + coord_cartesian(xlim =c(Sys.Date() - 30, NA), ylim = c(10, 20))


--- title: "Guidelines for Authors" updated: 2016-07-06 00:00:00 layout: default group: program menu: sub ordered: 10 status: published ---


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Thus, I decided to compile this list with the hope that it would be useful to people and to also help me keep track of some great stuff I’ve found on the Web.
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StackExchange/Dapper Dapper - a simple object mapper for .Net. Contribute to StackExchange/Dapper development by creating an account on GitHub.
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Draft: Front-End Performance Checklist 2020 — Please add your comments The final version will be published on @SmashingMag early January.
Getting Started With BenchmarkDotNet – The Sharper Dev BenchmarkDotNet is a great library for performance testing on the dotnet platform. On this blog I’ve used it to benchmark different lists, for loops, and the cost of synchronous async methods.
MessagePack for C# v2, new era of .NET Core(Unity) I/O Pipelines MessagePack for C# Version 2 was released in 2019–12–16. The main implementation was done by Andrew Arnott who is a software engineer at…


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Please find below the Indico events requiring *startup* support for today:


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ActiveTcl User Guide
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bindtags - Determine which bindings apply to a window, and order of evaluation
bindtags window ?tagList?
When a binding is created with the bind command, it is associated either with a particular window such as .a.b.c, a class name such as Button, the keyword all, or any other string. All of these forms are called binding tags. Each window contains a list of binding tags that determine how events are processed for the window. When an event occurs in a window, it is applied to each of the window's tags in order: for each tag, the most specific binding that matches the given tag and event is executed. See the bind command for more information on the matching process.
By default, each window has four binding tags consisting of the name of the window, the window's class name, the name of the window's nearest toplevel ancestor, and all, in that order. Toplevel windows have only three tags by default, since the toplevel name is the same as that of the window. The bindtags command allows the binding tags for a window to be read and modified.
If bindtags is invoked with only one argument, then the current set of binding tags for window is returned as a list. If the tagList argument is specified to bindtags, then it must be a proper list; the tags for window are changed to the elements of the list. The elements of tagList may be arbitrary strings; however, any tag starting with a dot is treated as the name of a window; if no window by that name exists at the time an event is processed, then the tag is ignored for that event. The order of the elements in tagList determines the order in which binding scripts are executed in response to events. For example, the command
bindtags .b {all . Button .b}
reverses the order in which binding scripts will be evaluated for a button named .b so that all bindings are invoked first, following by bindings for .b's toplevel (``.''), followed by class bindings, followed by bindings for .b. If tagList is an empty list then the binding tags for window are returned to the default state described above.
The bindtags command may be used to introduce arbitrary additional binding tags for a window, or to remove standard tags. For example, the command
bindtags .b {.b TrickyButton . all}
replaces the Button tag for .b with TrickyButton. This means that the default widget bindings for buttons, which are associated with the Button tag, will no longer apply to .b, but any bindings associated with TrickyButton (perhaps some new button behavior) will apply.
Copyright © 1990 The Regents of the University of California. Copyright © 1994-1996 Sun Microsystems, Inc. Copyright © 1995-1997 Roger E. Critchlow Jr.


PyZKAccess
PyZKAccess is a library for working with ZKTeco ZKAccess C3-100/200/400 access controllers.
The ZKTeco PULL SDK is used as machinery. Therefore the code is executed in Windows environment. *nix are also supported using Wine.
Features
- Relays switching
- Reading events of whole device or separately for certain reader, aux input or even door
- Getting/setting the device parameters such as datetime, network settings, entry modes, backup time, etc.
- Getting/setting a door parameters such as smart card modes, intervals, entry modes, etc.
- Scanning the local network in searching for active C3 devices
- Restarting a device
Here are the controllers we're taking about:
| C3-100 | C3-200 | C3-400 |
|---|---|---|
To be implemented
- Pulling data from a device with filtering support (cards, ACL, holidays and timezone info, access history, i/o table)
- Uploading data to a device (the same)
- CLI interface
- Downloading/uploading files from PC to/from a device
- Restoring from SD card backup
- Cancelling alarm function
- Emergency resetting network settings
NOTE: the version pyzkaccess>=0.2
is incompatible with pyzkaccess==0.1
Author
Igor Derkach, gosha753951@gmail.com


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