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• What's up with LDoms: Part 1 - Introduction & Basic Concepts

  - by Stefan Hinker

  LDoms - the correct name is Oracle VM Server for SPARC - have been around for quite a while now.  But to my surprise, I get more and more requests to explain how they work or to give advise on how to make good use of them.  This made me think that writing up a few articles discussing the different features would be a good idea.  Now - I don't intend to rewrite the LDoms Admin Guide or to copy and reformat the (hopefully) well known "Beginners Guide to LDoms" by Tony Shoumack from 2007.  Those documents are very recommendable - especially the Beginners Guide, although based on LDoms 1.0, is still a good place to begin with.  However, LDoms have come a long way since then, and I hope to contribute to their adoption by discussing how they work and what features there are today.  In this and the following posts, I will use the term "LDoms" as a common abbreviation for Oracle VM Server for SPARC, just because it's a lot shorter and easier to type (and presumably, read). So, just to get everyone on the same baseline, lets briefly discuss the basic concepts of virtualization with LDoms.  LDoms make use of a hypervisor as a layer of abstraction between real, physical hardware and virtual hardware.  This virtual hardware is then used to create a number of guest systems which each behave very similar to a system running on bare metal:  Each has its own OBP, each will install its own copy of the Solaris OS and each will see a certain amount of CPU, memory, disk and network resources available to it.  Unlike some other type 1 hypervisors running on x86 hardware, the SPARC hypervisor is embedded in the system firmware and makes use both of supporting functions in the sun4v SPARC instruction set as well as the overall CPU architecture to fulfill its function. The CMT architecture of the supporting CPUs (T1 through T4) provide a large number of cores and threads to the OS.  For example, the current T4 CPU has eight cores, each running 8 threads, for a total of 64 threads per socket.  To the OS, this looks like 64 CPUs.  The SPARC hypervisor, when creating guest systems, simply assigns a certain number of these threads exclusively to one guest, thus avoiding the overhead of having to schedule OS threads to CPUs, as do typical x86 hypervisors.  The hypervisor only assigns CPUs and then steps aside.  It is not involved in the actual work being dispatched from the OS to the CPU, all it does is maintain isolation between different guests. Likewise, memory is assigned exclusively to individual guests.  Here,  the hypervisor provides generic mappings between the physical hardware addresses and the guest's views on memory.  Again, the hypervisor is not involved in the actual memory access, it only maintains isolation between guests. During the inital setup of a system with LDoms, you start with one special domain, called the Control Domain.  Initially, this domain owns all the hardware available in the system, including all CPUs, all RAM and all IO resources.  If you'd be running the system un-virtualized, this would be what you'd be working with.  To allow for guests, you first resize this initial domain (also called a primary domain in LDoms speak), assigning it a small amount of CPU and memory.  This frees up most of the available CPU and memory resources for guest domains.  IO is a little more complex, but very straightforward.  When LDoms 1.0 first came out, the only way to provide IO to guest systems was to create virtual disk and network services and attach guests to these services.  In the meantime, several different ways to connect guest domains to IO have been developed, the most recent one being SR-IOV support for network devices released in version 2.2 of Oracle VM Server for SPARC. I will cover these more advanced features in detail later.  For now, lets have a short look at the initial way IO was virtualized in LDoms: For virtualized IO, you create two services, one "Virtual Disk Service" or vds, and one "Virtual Switch" or vswitch.  You can, of course, also create more of these, but that's more advanced than I want to cover in this introduction.  These IO services now connect real, physical IO resources like a disk LUN or a networt port to the virtual devices that are assigned to guest domains.  For disk IO, the normal case would be to connect a physical LUN (or some other storage option that I'll discuss later) to one specific guest.  That guest would be assigned a virtual disk, which would appear to be just like a real LUN to the guest, while the IO is actually routed through the virtual disk service down to the physical device.  For network, the vswitch acts very much like a real, physical ethernet switch - you connect one physical port to it for outside connectivity and define one or more connections per guest, just like you would plug cables between a real switch and a real system. For completeness, there is another service that provides console access to guest domains which mimics the behavior of serial terminal servers. The connections between the virtual devices on the guest's side and the virtual IO services in the primary domain are created by the hypervisor.  It uses so called "Logical Domain Channels" or LDCs to create point-to-point connections between all of these devices and services.  These LDCs work very similar to high speed serial connections and are configured automatically whenever the Control Domain adds or removes virtual IO. To see all this in action, now lets look at a first example.  I will start with a newly installed machine and configure the control domain so that it's ready to create guest systems. In a first step, after we've installed the software, let's start the virtual console service and downsize the primary domain.  root@sun # ldm list NAME STATE FLAGS CONS VCPU MEMORY UTIL UPTIME primary active -n-c-- UART 512 261632M 0.3% 2d 13h 58m root@sun # ldm add-vconscon port-range=5000-5100 \ primary-console primary root@sun # svcadm enable vntsd root@sun # svcs vntsd STATE STIME FMRI online 9:53:21 svc:/ldoms/vntsd:default root@sun # ldm set-vcpu 16 primary root@sun # ldm set-mau 1 primary root@sun # ldm start-reconf primary root@sun # ldm set-memory 7680m primary root@sun # ldm add-config initial root@sun # shutdown -y -g0 -i6 So what have I done: I've defined a range of ports (5000-5100) for the virtual network terminal service and then started that service.  The vnts will later provide console connections to guest systems, very much like serial NTS's do in the physical world. Next, I assigned 16 vCPUs (on this platform, a T3-4, that's two cores) to the primary domain, freeing the rest up for future guest systems.  I also assigned one MAU to this domain.  A MAU is a crypto unit in the T3 CPU.  These need to be explicitly assigned to domains, just like CPU or memory.  (This is no longer the case with T4 systems, where crypto is always available everywhere.) Before I reassigned the memory, I started what's called a "delayed reconfiguration" session.  That avoids actually doing the change right away, which would take a considerable amount of time in this case.  Instead, I'll need to reboot once I'm all done.  I've assigned 7680MB of RAM to the primary.  That's 8GB less the 512MB which the hypervisor uses for it's own private purposes.  You can, depending on your needs, work with less.  I'll spend a dedicated article on sizing, discussing the pros and cons in detail. Finally, just before the reboot, I saved my work on the ILOM, to make this configuration available after a powercycle of the box.  (It'll always be available after a simple reboot, but the ILOM needs to know the configuration of the hypervisor after a power-cycle, before the primary domain is booted.) Now, lets create a first disk service and a first virtual switch which is connected to the physical network device igb2. We will later use these to connect virtual disks and virtual network ports of our guest systems to real world storage and network. root@sun # ldm add-vds primary-vds root@sun # ldm add-vswitch net-dev=igb2 switch-primary primary You are free to choose whatever names you like for the virtual disk service and the virtual switch.  I strongly recommend that you choose names that make sense to you and describe the function of each service in the context of your implementation.  For the vswitch, for example, you could choose names like "admin-vswitch" or "production-network" etc. This already concludes the configuration of the control domain.  We've freed up considerable amounts of CPU and RAM for guest systems and created the necessary infrastructure - console, vts and vswitch - so that guests systems can actually interact with the outside world.  The system is now ready to create guests, which I'll describe in the next section. For further reading, here are some recommendable links: The LDoms 2.2 Admin Guide The "Beginners Guide to LDoms" The LDoms Information Center on MOS LDoms on OTN

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• SQL SERVER – Import CSV into Database – Transferring File Content into a Database Table using CSVexpress

  - by pinaldave

  One of the most common data integration tasks I run into is a desire to move data from a file into a database table.  Generally the user is familiar with his data, the structure of the file, and the database table, but is unfamiliar with data integration tools and therefore views this task as something that is difficult.  What these users really need is a point and click approach that minimizes the learning curve for the data integration tool.  This is what CSVexpress (www.CSVexpress.com) is all about!  It is based on expressor Studio, a data integration tool I’ve been reviewing over the last several months. With CSVexpress, moving data between data sources can be as simple as providing the database connection details, describing the structure of the incoming and outgoing data and then connecting two pre-programmed operators.   There’s no need to learn the intricacies of the data integration tool or to write code.  Let’s look at an example. Suppose I have a comma separated value data file with data similar to the following, which is a listing of terminated employees that includes their hiring and termination date, department, job description, and final salary. EMP_ID,STRT_DATE,END_DATE,JOB_ID,DEPT_ID,SALARY 102,13-JAN-93,24-JUL-98 17:00,Programmer,60,"$85,000" 101,21-SEP-89,27-OCT-93 17:00,Account Representative,110,"$65,000" 103,28-OCT-93,15-MAR-97 17:00,Account Manager,110,"$75,000" 304,17-FEB-96,19-DEC-99 17:00,Marketing,20,"$45,000" 333,24-MAR-98,31-DEC-99 17:00,Data Entry Clerk,50,"$35,000" 100,17-SEP-87,17-JUN-93 17:00,Administrative Assistant,90,"$40,000" 334,24-MAR-98,31-DEC-98 17:00,Sales Representative,80,"$40,000" 400,01-JAN-99,31-DEC-99 17:00,Sales Manager,80,"$55,000" Notice the concise format used for the date values, the fact that the termination date includes both date and time information, and that the salary is clearly identified as money by the dollar sign and digit grouping.  In moving this data to a database table I want to express the dates using a format that includes the century since it’s obvious that this listing could include employees who left the company in both the 20th and 21st centuries, and I want the salary to be stored as a decimal value without the currency symbol and grouping character.  Most data integration tools would require coding within a transformation operation to effect these changes, but not expressor Studio.  Directives for these modifications are included in the description of the incoming data. Besides starting the expressor Studio tool and opening a project, the first step is to create connection artifacts, which describe to expressor where data is stored.  For this example, two connection artifacts are required: a file connection, which encapsulates the file system location of my file; and a database connection, which encapsulates the database connection information.  With expressor Studio, I use wizards to create these artifacts. First click New Connection > File Connection in the Home tab of expressor Studio’s ribbon bar, which starts the File Connection wizard.  In the first window, I enter the path to the directory that contains the input file.  Note that the file connection artifact only specifies the file system location, not the name of the file. Then I click Next and enter a meaningful name for this connection artifact; clicking Finish closes the wizard and saves the artifact. To create the Database Connection artifact, I must know the location of, or instance name, of the target database and have the credentials of an account with sufficient privileges to write to the target table.  To use expressor Studio’s features to the fullest, this account should also have the authority to create a table. I click the New Connection > Database Connection in the Home tab of expressor Studio’s ribbon bar, which starts the Database Connection wizard.  expressor Studio includes high-performance drivers for many relational database management systems, so I can simply make a selection from the “Supplied database drivers” drop down control.  If my desired RDBMS isn’t listed, I can optionally use an existing ODBC DSN by selecting the “Existing DSN” radio button. In the following window, I enter the connection details.  With Microsoft SQL Server, I may choose to use Windows Authentication rather than rather than account credentials.  After clicking Next, I enter a meaningful name for this connection artifact and clicking Finish closes the wizard and saves the artifact. Now I create a schema artifact, which describes the structure of the file data.  When expressor reads a file, all data fields are typed as strings.  In some use cases this may be exactly what is needed and there is no need to edit the schema artifact.  But in this example, editing the schema artifact will be used to specify how the data should be transformed; that is, reformat the dates to include century designations, change the employee and job ID’s to integers, and convert the salary to a decimal value. Again a wizard is used to create the schema artifact.  I click New Schema > Delimited Schema in the Home tab of expressor Studio’s ribbon bar, which starts the Database Connection wizard.  In the first window, I click Get Data from File, which then displays a listing of the file connections in the project.  When I click on the file connection I previously created, a browse window opens to this file system location; I then select the file and click Open, which imports 10 lines from the file into the wizard. I now view the file’s content and confirm that the appropriate delimiter characters are selected in the “Field Delimiter” and “Record Delimiter” drop down controls; then I click Next. Since the input file includes a header row, I can easily indicate that fields in the file should be identified through the corresponding header value by clicking “Set All Names from Selected Row. “ Alternatively, I could enter a different identifier into the Field Details > Name text box.  I click Next and enter a meaningful name for this schema artifact; clicking Finish closes the wizard and saves the artifact. Now I open the schema artifact in the schema editor.  When I first view the schema’s content, I note that the types of all attributes in the Semantic Type (the right-hand panel) are strings and that the attribute names are the same as the field names in the data file.  To change an attribute’s name and type, I highlight the attribute and click Edit in the Attributes grouping on the Schema > Edit tab of the editor’s ribbon bar.  This opens the Edit Attribute window; I can change the attribute name and select the desired type from the “Data type” drop down control.  In this example, I change the name of each attribute to the name of the corresponding database table column (EmployeeID, StartingDate, TerminationDate, JobDescription, DepartmentID, and FinalSalary).  Then for the EmployeeID and DepartmentID attributes, I select Integer as the data type, for the StartingDate and TerminationDate attributes, I select Datetime as the data type, and for the FinalSalary attribute, I select the Decimal type. But I can do much more in the schema editor.  For the datetime attributes, I can set a constraint that ensures that the data adheres to some predetermined specifications; a starting date must be later than January 1, 1980 (the date on which the company began operations) and a termination date must be earlier than 11:59 PM on December 31, 1999.  I simply select the appropriate constraint and enter the value (1980-01-01 00:00 as the starting date and 1999-12-31 11:59 as the termination date). As a last step in setting up these datetime conversions, I edit the mapping, describing the format of each datetime type in the source file. I highlight the mapping line for the StartingDate attribute and click Edit Mapping in the Mappings grouping on the Schema > Edit tab of the editor’s ribbon bar.  This opens the Edit Mapping window in which I either enter, or select, a format that describes how the datetime values are represented in the file.  Note the use of Y01 as the syntax for the year.  This syntax is the indicator to expressor Studio to derive the century by setting any year later than 01 to the 20th century and any year before 01 to the 21st century.  As each datetime value is read from the file, the year values are transformed into century and year values. For the TerminationDate attribute, my format also indicates that the datetime value includes hours and minutes. And now to the Salary attribute. I open its mapping and in the Edit Mapping window select the Currency tab and the “Use currency” check box.  This indicates that the file data will include the dollar sign (or in Europe the Pound or Euro sign), which should be removed. And on the Grouping tab, I select the “Use grouping” checkbox and enter 3 into the “Group size” text box, a comma into the “Grouping character” text box, and a decimal point into the “Decimal separator” character text box. These entries allow the string to be properly converted into a decimal value. By making these entries into the schema that describes my input file, I’ve specified how I want the data transformed prior to writing to the database table and completely removed the requirement for coding within the data integration application itself. Assembling the data integration application is simple.  Onto the canvas I drag the Read File and Write Table operators, connecting the output of the Read File operator to the input of the Write Table operator. Next, I select the Read File operator and its Properties panel opens on the right-hand side of expressor Studio.  For each property, I can select an appropriate entry from the corresponding drop down control.  Clicking on the button to the right of the “File name” text box opens the file system location specified in the file connection artifact, allowing me to select the appropriate input file.  I indicate also that the first row in the file, the header row, should be skipped, and that any record that fails one of the datetime constraints should be skipped. I then select the Write Table operator and in its Properties panel specify the database connection, normal for the “Mode,” and the “Truncate” and “Create Missing Table” options.  If my target table does not yet exist, expressor will create the table using the information encapsulated in the schema artifact assigned to the operator. The last task needed to complete the application is to create the schema artifact used by the Write Table operator.  This is extremely easy as another wizard is capable of using the schema artifact assigned to the Read Table operator to create a schema artifact for the Write Table operator.  In the Write Table Properties panel, I click the drop down control to the right of the “Schema” property and select “New Table Schema from Upstream Output…” from the drop down menu. The wizard first displays the table description and in its second screen asks me to select the database connection artifact that specifies the RDBMS in which the target table will exist.  The wizard then connects to the RDBMS and retrieves a list of database schemas from which I make a selection.  The fourth screen gives me the opportunity to fine tune the table’s description.  In this example, I set the width of the JobDescription column to a maximum of 40 characters and select money as the type of the LastSalary column.  I also provide the name for the table. This completes development of the application.  The entire application was created through the use of wizards and the required data transformations specified through simple constraints and specifications rather than through coding.  To develop this application, I only needed a basic understanding of expressor Studio, a level of expertise that can be gained by working through a few introductory tutorials.  expressor Studio is as close to a point and click data integration tool as one could want and I urge you to try this product if you have a need to move data between files or from files to database tables. Check out CSVexpress in more detail.  It offers a few basic video tutorials and a preview of expressor Studio 3.5, which will support the reading and writing of data into Salesforce.com. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, PostADay, SQL, SQL Authority, SQL Documentation, SQL Download, SQL Query, SQL Server, SQL Tips and Tricks, SQLServer, T SQL, Technology

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• CodePlex Daily Summary for Thursday, October 25, 2012

  CodePlex Daily Summary for Thursday, October 25, 2012Popular ReleasesTEncoder: 2.9: -2.9 -Added: Support for audio codec Opus -Added: Support for .opus files -Added: Decreased main window dimensions (will reset position info) -Fixed: Custom arguments were not passed if codec is "Copy" -Fixed: MEncoder "Direct Stream Copy" container problem -Fixed: Minor UI problems -Updated: MPlayer and MEncoder to SB41 -Updated: MediaInfo to 0.7.61 -Updated: FFmpeg to latest from ffmpeg.zeranoe.comdcview: DCView 1.3.9: Clien ?? ?????? ??, ???, ??? ??? ??CRM 2011 Web Resource Linker/Publisher: WebResourceLinker: Initial releaseMobilviWP7: MobilviWP7 1.2: Stabilna i przetestowana wersja.Posh for Jammer: jammer_v0.1_beta: First release of a number of PowerShell Functions calling the Yammer API.Style MVVM: 2.0.3: This is both a feature release and a Bug Fix release Features The Main new Feature is the ability to add event handlers from XAML using this new syntax View:EventHandler.Attach="EventName => ViewModelMethod($eventArgs)" New Example app that shows one or two features of the framework on each page, allowing for more straight forward examples. Bug Fixes IUIVisualizationService is now exported correctly and you can import it into your ViewModels DelegateCommand had a bug where it wasn't r...MCEBuddy 2.x: MCEBuddy 2.3.5: Changelog for 2.3.5 (32bit and 64bit) 1. Fixed a bug causing MCEBuddy to crash during or after installation on Windows XP 2. Bugfix for resource leak with UPnP which would lead to a failure after many days 3. Increased the UPnP discovery re-scan interval from 10 minutes to 30 minutes 4. Added support for specifying TVDB and IMDB id’s in the conversion task page (forcing the internet lookup for metadata)WPF About Box: WPF About Box 1.1.1.1: First Stable ReleaseEdi: First Alpha Version: The initial release does a lot of things out of the box (theming, editing with highlighting, Find/Replace, MRU List). Read the Readme.txt file in the Edi Sub-project to get full details.CRM 2011 Visual Ribbon Editor: Visual Ribbon Editor (1.3.1025.5): [NEW] Support for connecting to CRM Online via Office 365 (OSDP) [NEW] Current connection information and loaded ribbon name are displayed in the status bar [IMPROVED] Connect dialog minor improvements and error message descriptions [IMPROVED] Connecting to a CRM server will close currently loaded ribbon upon confirmation (if another ribbon was loaded previously) [FIX] Fixed bug in Open Ribbon dialog which would not allow to refresh entity list more than oncejob board light version: version 1.0: recuiter section jobseeker section spam flagging advanced search filtering customizable templatesReadable Passphrase Generator: KeePass Plugin 0.8.0: Changes: Interrogative phrases (questions) like why did the statesman burgle amidst lucid sunlamps Support transitive / intransitive verbs (whether a verb needs a subject or not). Change adverbs to be either before or after the verb, at random. Add an "equal" version of each strength, where each possibility is equally likely (for password purists). 3401 words in the default dictionary (~400 more than previous release) Fixed bugs when choosing verb tensesfastJSON: v2.0.9: - added support for root level DataSet and DataTable deserialize (you have to do ToObject<DataSet>(...) ) - added dataset testsMicrosoft Ajax Minifier: Microsoft Ajax Minifier 4.72: Fix for Issue #18819 - bad optimization of return/assign operator.DNN Module Creator: 01.01.00: Updated templates for DNN7 ( ie. DAL2, Web Service API ). Numerous bug fixes and enhancements.WPF Application Framework (WAF): WPF Application Framework (WAF) 2.5.0.390: Version 2.5.0.390 (Release Candidate): This release contains the source code of the WPF Application Framework (WAF) and the sample applications. Requirements .NET Framework 4.0 (The package contains a solution file for Visual Studio 2010) The unit test projects require Visual Studio 2010 Professional Changelog Legend: [B] Breaking change; [O] Marked member as obsolete WAF: Fix recent file list remove issue. WAF: Minor code improvements. BookLibrary: Fix Blend design time support o...Fiskalizacija za developere: FiskalizacijaDev 1.1: Ovo je prva nadogradnja ovog projekta nakon inicijalnog predstavljanja - dodali smo nekoliko feature-a, bilo zato što smo sami primijetili da bi ih bilo dobro dodati, bilo na osnovu vaših sugestija - hvala svima koji su se ukljucili :) Ovo su stvari riješene u v1.1.: 1. Bilo bi dobro da se XML dokument koji se šalje u CIS može snimiti u datoteku (http://fiskalizacija.codeplex.com/workitem/612) 2. Podrška za COM DLL (VB6) (http://fiskalizacija.codeplex.com/workitem/613) 3. Podrška za DOS (unu...Liberty: v3.4.0.0 Release 20th October 2012: Change Log -Added -Halo 4 support (invincibility, ammo editing) -Reach A warning dialog now shows up when you first attempt to swap a weapon -Fixed -A few minor bugsClosedXML - The easy way to OpenXML: ClosedXML 0.68.1: ClosedXML now resolves formulas! Yes it finally happened. If you call cell.Value and it has a formula the library will try to evaluate the formula and give you the result. For example: var wb = new XLWorkbook(); var ws = wb.AddWorksheet("Sheet1"); ws.Cell("A1").SetValue(1).CellBelow().SetValue(1); ws.Cell("B1").SetValue(1).CellBelow().SetValue(1); ws.Cell("C1").FormulaA1 = "\"The total value is: \" & SUM(A1:B2)"; var...Orchard Project: Orchard 1.6 RC: RELEASE NOTES This is the Release Candidate version of Orchard 1.6. You should use this version to prepare your current developments to the upcoming final release, and report problems. Please read our release notes for Orchard 1.6 RC: http://docs.orchardproject.net/Documentation/Orchard-1-6-Release-Notes Please do not post questions as reviews. Questions should be posted in the Discussions tab, where they will usually get promptly responded to. If you post a question as a review, you wil...New Projects6_6_6_w_m_s_open: jwervxsdf7COM0207 Web Scripting and Content Creation Exercises: Loretta Rose Web Scripting and Content Creation ExercisesAcademyPVT: The project is dedicated to my studies at the Academy Pvt. It will be posted various learning tasks, and my research on the ASP.NET.Arduino Solar Meter: An Arduino is used to monitor several item in the meter cabinet. The standard version can log 3 S0 kWh meters and upload results to PVoutput and local SD card.BookCaching: BookCaching - GeoCaching with books. A funny new way to discover books around you!BruceCommonCMS: This is a CMS system developed by ASP.net(C#) with Visual Studio 2010/2012. My aim is to build a dynamic & flexible CMS system.Bullet On Rails for MS MVC: Bullet On Rails provides out-of-box scaffold controllers ala Ruby on Rails for MS MVC. It also provides automatic validations for information found in the LINQ to SQL generated file such as: - Type of field - Date format - Length of field - Required fieldCalculator++: Calculator++ will be the best application in parsing and calculating equations results.Collections: Collection Management for TV Series and Anime.Common Key Password Generator: This utility constructs a complex password from a GUID. The number of possible combinations generated approaches 16 to the power of 32.Cosmos HiDefOs: HiDef Os is a research project, to make a HD driver that runs smoothly. This is a subproject of QuicksilverOS and is fully open-source.EmpireWork Professional Social Network: EmpireWork Professional Social Network Locations: http://empirework.com http://empirework.ru http://empirework.com.ua http://empirework.byeWay payment gateway provider for NB_Store: eWay payment gateway provider for NB_StoreHDK - WinRT MVVM and MEF Friendly Prism Framework port: HDK - is a "spare-time" framework for WinRT development. Solution consists of: - MVVM - Event Aggregator - PRISM - other useful extensions HowToSetUpACodeplexProject: Er is nog niets gebeurdiBackup Explorer: The goal of this application is to provide a quick way to explore any iOS backup (IPhone, Ipad..)istomato: istomatojob board light version: job board light versionMaternity System: It's a project in development stage objectived to help maternity hospitals to make a better treatment for him usersmeu-projeto: sdalçfj lasdjlfjdsalfj lsdafldsajl fjsdalf jlsdaj flsadjl fjdsal fjdsal jflsdajf lksdajfksadMicrosoft Casablanca Samples and Tutorials: The code repository associated with http://cloudysea.wordpress.com, which discusses the Casablanca Project (http://msdn.microsoft.com/en-us/devlabs/casablanca)myvideo: myvideoProject13251024: papaProjekt PHP: Mitt projekt i kursen PHPSharePoint Version History Extractor: Windows app used to migrate/extract version history from a versioned document library into separate files with historical metadata.Site Backup Repackager: Use the Site Backup Repackager to reformat a SP2007 site backup (.cmp) for SP2010. SpiritMVVM: SpiritMVVM is a Model-View-ViewModel library, focused on richness of feature-set and cross-platform compatibility, using the Portable Class Library.SQL Data transfer wizard: It replaces export data in SSMS by offering dependency aware order of table transfer. studyproject: PHP, HTML, ZFTAPI Connector for Dynamics CRM 2011: Open source Caller ID screenpop/CTI for TAPI enabled phone systems. Simply install the TAPI software on your computer then configure this to connect to DynamicsTFS2012: This is project that used for coding VP8.NET: VP8.NET is a dual-licensed commercial/GPL C++ CLR wrapper which allows .NET applications to easily use the VP8 video codec.X0s0m0a0r0t0W1M1S1: 32432432432432

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• Using an alternate JSON Serializer in ASP.NET Web API

  - by Rick Strahl

  The new ASP.NET Web API that Microsoft released alongside MVC 4.0 Beta last week is a great framework for building REST and AJAX APIs. I've been working with it for quite a while now and I really like the way it works and the complete set of features it provides 'in the box'. It's about time that Microsoft gets a decent API for building generic HTTP endpoints into the framework. DataContractJsonSerializer sucks As nice as Web API's overall design is one thing still sucks: The built-in JSON Serialization uses the DataContractJsonSerializer which is just too limiting for many scenarios. The biggest issues I have with it are: No support for untyped values (object, dynamic, Anonymous Types) MS AJAX style Date Formatting Ugly serialization formats for types like Dictionaries To me the most serious issue is dealing with serialization of untyped objects. I have number of applications with AJAX front ends that dynamically reformat data from business objects to fit a specific message format that certain UI components require. The most common scenario I have there are IEnumerable query results from a database with fields from the result set rearranged to fit the sometimes unconventional formats required for the UI components (like jqGrid for example). Creating custom types to fit these messages seems like overkill and projections using Linq makes this much easier to code up. Alas DataContractJsonSerializer doesn't support it. Neither does DataContractSerializer for XML output for that matter. What this means is that you can't do stuff like this in Web API out of the box:public object GetAnonymousType() { return new { name = "Rick", company = "West Wind", entered= DateTime.Now }; } Basically anything that doesn't have an explicit type DataContractJsonSerializer will not let you return. FWIW, the same is true for XmlSerializer which also doesn't work with non-typed values for serialization. The example above is obviously contrived with a hardcoded object graph, but it's not uncommon to get dynamic values returned from queries that have anonymous types for their result projections. Apparently there's a good possibility that Microsoft will ship Json.NET as part of Web API RTM release.  Scott Hanselman confirmed this as a footnote in his JSON Dates post a few days ago. I've heard several other people from Microsoft confirm that Json.NET will be included and be the default JSON serializer, but no details yet in what capacity it will show up. Let's hope it ends up as the default in the box. Meanwhile this post will show you how you can use it today with the beta and get JSON that matches what you should see in the RTM version. What about JsonValue? To be fair Web API DOES include a new JsonValue/JsonObject/JsonArray type that allow you to address some of these scenarios. JsonValue is a new type in the System.Json assembly that can be used to build up an object graph based on a dictionary. It's actually a really cool implementation of a dynamic type that allows you to create an object graph and spit it out to JSON without having to create .NET type first. JsonValue can also receive a JSON string and parse it without having to actually load it into a .NET type (which is something that's been missing in the core framework). This is really useful if you get a JSON result from an arbitrary service and you don't want to explicitly create a mapping type for the data returned. For serialization you can create an object structure on the fly and pass it back as part of an Web API action method like this:public JsonValue GetJsonValue() { dynamic json = new JsonObject(); json.name = "Rick"; json.company = "West Wind"; json.entered = DateTime.Now; dynamic address = new JsonObject(); address.street = "32 Kaiea"; address.zip = "96779"; json.address = address; dynamic phones = new JsonArray(); json.phoneNumbers = phones; dynamic phone = new JsonObject(); phone.type = "Home"; phone.number = "808 123-1233"; phones.Add(phone); phone = new JsonObject(); phone.type = "Home"; phone.number = "808 123-1233"; phones.Add(phone); //var jsonString = json.ToString(); return json; } which produces the following output (formatted here for easier reading):{ name: "rick", company: "West Wind", entered: "2012-03-08T15:33:19.673-10:00", address: { street: "32 Kaiea", zip: "96779" }, phoneNumbers: [ { type: "Home", number: "808 123-1233" }, { type: "Mobile", number: "808 123-1234" }] } If you need to build a simple JSON type on the fly these types work great. But if you have an existing type - or worse a query result/list that's already formatted JsonValue et al. become a pain to work with. As far as I can see there's no way to just throw an object instance at JsonValue and have it convert into JsonValue dictionary. It's a manual process. Using alternate Serializers in Web API So, currently the default serializer in WebAPI is DataContractJsonSeriaizer and I don't like it. You may not either, but luckily you can swap the serializer fairly easily. If you'd rather use the JavaScriptSerializer built into System.Web.Extensions or Json.NET today, it's not too difficult to create a custom MediaTypeFormatter that uses these serializers and can replace or partially replace the native serializer. Here's a MediaTypeFormatter implementation using the ASP.NET JavaScriptSerializer:using System; using System.Net.Http.Formatting; using System.Threading.Tasks; using System.Web.Script.Serialization; using System.Json; using System.IO; namespace Westwind.Web.WebApi { public class JavaScriptSerializerFormatter : MediaTypeFormatter { public JavaScriptSerializerFormatter() { SupportedMediaTypes.Add(new System.Net.Http.Headers.MediaTypeHeaderValue("application/json")); } protected override bool CanWriteType(Type type) { // don't serialize JsonValue structure use default for that if (type == typeof(JsonValue) || type == typeof(JsonObject) || type== typeof(JsonArray) ) return false; return true; } protected override bool CanReadType(Type type) { if (type == typeof(IKeyValueModel)) return false; return true; } protected override System.Threading.Tasks.Taskobject OnReadFromStreamAsync(Type type, System.IO.Stream stream, System.Net.Http.Headers.HttpContentHeaders contentHeaders, FormatterContext formatterContext) { var task = Taskobject.Factory.StartNew(() = { var ser = new JavaScriptSerializer(); string json; using (var sr = new StreamReader(stream)) { json = sr.ReadToEnd(); sr.Close(); } object val = ser.Deserialize(json,type); return val; }); return task; } protected override System.Threading.Tasks.Task OnWriteToStreamAsync(Type type, object value, System.IO.Stream stream, System.Net.Http.Headers.HttpContentHeaders contentHeaders, FormatterContext formatterContext, System.Net.TransportContext transportContext) { var task = Task.Factory.StartNew( () = { var ser = new JavaScriptSerializer(); var json = ser.Serialize(value); byte[] buf = System.Text.Encoding.Default.GetBytes(json); stream.Write(buf,0,buf.Length); stream.Flush(); }); return task; } } } Formatter implementation is pretty simple: You override 4 methods to tell which types you can handle and then handle the input or output streams to create/parse the JSON data. Note that when creating output you want to take care to still allow JsonValue/JsonObject/JsonArray types to be handled by the default serializer so those objects serialize properly - if you let either JavaScriptSerializer or JSON.NET handle them they'd try to render the dictionaries which is very undesirable. If you'd rather use Json.NET here's the JSON.NET version of the formatter:// this code requires a reference to JSON.NET in your project #if true using System; using System.Net.Http.Formatting; using System.Threading.Tasks; using System.Web.Script.Serialization; using System.Json; using Newtonsoft.Json; using System.IO; using Newtonsoft.Json.Converters; namespace Westwind.Web.WebApi { public class JsonNetFormatter : MediaTypeFormatter { public JsonNetFormatter() { SupportedMediaTypes.Add(new System.Net.Http.Headers.MediaTypeHeaderValue("application/json")); } protected override bool CanWriteType(Type type) { // don't serialize JsonValue structure use default for that if (type == typeof(JsonValue) || type == typeof(JsonObject) || type == typeof(JsonArray)) return false; return true; } protected override bool CanReadType(Type type) { if (type == typeof(IKeyValueModel)) return false; return true; } protected override System.Threading.Tasks.Taskobject OnReadFromStreamAsync(Type type, System.IO.Stream stream, System.Net.Http.Headers.HttpContentHeaders contentHeaders, FormatterContext formatterContext) { var task = Taskobject.Factory.StartNew(() = { var settings = new JsonSerializerSettings() { NullValueHandling = NullValueHandling.Ignore, }; var sr = new StreamReader(stream); var jreader = new JsonTextReader(sr); var ser = new JsonSerializer(); ser.Converters.Add(new IsoDateTimeConverter()); object val = ser.Deserialize(jreader, type); return val; }); return task; } protected override System.Threading.Tasks.Task OnWriteToStreamAsync(Type type, object value, System.IO.Stream stream, System.Net.Http.Headers.HttpContentHeaders contentHeaders, FormatterContext formatterContext, System.Net.TransportContext transportContext) { var task = Task.Factory.StartNew( () = { var settings = new JsonSerializerSettings() { NullValueHandling = NullValueHandling.Ignore, }; string json = JsonConvert.SerializeObject(value, Formatting.Indented, new JsonConverter[1] { new IsoDateTimeConverter() } ); byte[] buf = System.Text.Encoding.Default.GetBytes(json); stream.Write(buf,0,buf.Length); stream.Flush(); }); return task; } } } #endif   One advantage of the Json.NET serializer is that you can specify a few options on how things are formatted and handled. You get null value handling and you can plug in the IsoDateTimeConverter which is nice to product proper ISO dates that I would expect any Json serializer to output these days. Hooking up the Formatters Once you've created the custom formatters you need to enable them for your Web API application. To do this use the GlobalConfiguration.Configuration object and add the formatter to the Formatters collection. Here's what this looks like hooked up from Application_Start in a Web project:protected void Application_Start(object sender, EventArgs e) { // Action based routing (used for RPC calls) RouteTable.Routes.MapHttpRoute( name: "StockApi", routeTemplate: "stocks/{action}/{symbol}", defaults: new { symbol = RouteParameter.Optional, controller = "StockApi" } ); // WebApi Configuration to hook up formatters and message handlers // optional RegisterApis(GlobalConfiguration.Configuration); } public static void RegisterApis(HttpConfiguration config) { // Add JavaScriptSerializer formatter instead - add at top to make default //config.Formatters.Insert(0, new JavaScriptSerializerFormatter()); // Add Json.net formatter - add at the top so it fires first! // This leaves the old one in place so JsonValue/JsonObject/JsonArray still are handled config.Formatters.Insert(0, new JsonNetFormatter()); } One thing to remember here is the GlobalConfiguration object which is Web API's static configuration instance. I think this thing is seriously misnamed given that GlobalConfiguration could stand for anything and so is hard to discover if you don't know what you're looking for. How about WebApiConfiguration or something more descriptive? Anyway, once you know what it is you can use the Formatters collection to insert your custom formatter. Note that I insert my formatter at the top of the list so it takes precedence over the default formatter. I also am not removing the old formatter because I still want JsonValue/JsonObject/JsonArray to be handled by the default serialization mechanism. Since they process in sequence and I exclude processing for these types JsonValue et al. still get properly serialized/deserialized. Summary Currently DataContractJsonSerializer in Web API is a pain, but at least we have the ability with relatively limited effort to replace the MediaTypeFormatter and plug in our own JSON serializer. This is useful for many scenarios - if you have existing client applications that used MVC JsonResult or ASP.NET AJAX results from ASMX AJAX services you can plug in the JavaScript serializer and get exactly the same serializer you used in the past so your results will be the same and don't potentially break clients. JSON serializers do vary a bit in how they serialize some of the more complex types (like Dictionaries and dates for example) and so if you're migrating it might be helpful to ensure your client code doesn't break when you switch to ASP.NET Web API. Going forward it looks like Microsoft is planning on plugging in Json.Net into Web API and make that the default. I think that's an awesome choice since Json.net has been around forever, is fast and easy to use and provides a ton of functionality as part of this great library. I just wish Microsoft would have figured this out sooner instead of now at the last minute integrating with it especially given that Json.Net has a similar set of lower level JSON objects JsonValue/JsonObject etc. which now will end up being duplicated by the native System.Json stuff. It's not like we don't already have enough confusion regarding which JSON serializer to use (JavaScriptSerializer, DataContractJsonSerializer, JsonValue/JsonObject/JsonArray and now Json.net). For years I've been using my own JSON serializer because the built in choices are both limited. However, with an official encorsement of Json.Net I'm happily moving on to use that in my applications. Let's see and hope Microsoft gets this right before ASP.NET Web API goes gold.© Rick Strahl, West Wind Technologies, 2005-2012Posted in Web Api  AJAX  ASP.NET   Tweet !function(d,s,id){var js,fjs=d.getElementsByTagName(s)[0];if(!d.getElementById(id)){js=d.createElement(s);js.id=id;js.src="//platform.twitter.com/widgets.js";fjs.parentNode.insertBefore(js,fjs);}}(document,"script","twitter-wjs"); (function() { var po = document.createElement('script'); po.type = 'text/javascript'; po.async = true; po.src = 'https://apis.google.com/js/plusone.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(po, s); })();

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• The Incremental Architect&rsquo;s Napkin - #5 - Design functions for extensibility and readability

  - by Ralf Westphal

  Originally posted on: http://geekswithblogs.net/theArchitectsNapkin/archive/2014/08/24/the-incremental-architectrsquos-napkin---5---design-functions-for.aspx The functionality of programs is entered via Entry Points. So what we´re talking about when designing software is a bunch of functions handling the requests represented by and flowing in through those Entry Points. Designing software thus consists of at least three phases: Analyzing the requirements to find the Entry Points and their signatures Designing the functionality to be executed when those Entry Points get triggered Implementing the functionality according to the design aka coding I presume, you´re familiar with phase 1 in some way. And I guess you´re proficient in implementing functionality in some programming language. But in my experience developers in general are not experienced in going through an explicit phase 2. “Designing functionality? What´s that supposed to mean?” you might already have thought. Here´s my definition: To design functionality (or functional design for short) means thinking about… well, functions. You find a solution for what´s supposed to happen when an Entry Point gets triggered in terms of functions. A conceptual solution that is, because those functions only exist in your head (or on paper) during this phase. But you may have guess that, because it´s “design” not “coding”. And here is, what functional design is not: It´s not about logic. Logic is expressions (e.g. +, -, && etc.) and control statements (e.g. if, switch, for, while etc.). Also I consider calling external APIs as logic. It´s equally basic. It´s what code needs to do in order to deliver some functionality or quality. Logic is what´s doing that needs to be done by software. Transformations are either done through expressions or API-calls. And then there is alternative control flow depending on the result of some expression. Basically it´s just jumps in Assembler, sometimes to go forward (if, switch), sometimes to go backward (for, while, do). But calling your own function is not logic. It´s not necessary to produce any outcome. Functionality is not enhanced by adding functions (subroutine calls) to your code. Nor is quality increased by adding functions. No performance gain, no higher scalability etc. through functions. Functions are not relevant to functionality. Strange, isn´t it. What they are important for is security of investment. By introducing functions into our code we can become more productive (re-use) and can increase evolvability (higher unterstandability, easier to keep code consistent). That´s no small feat, however. Evolvable code can hardly be overestimated. That´s why to me functional design is so important. It´s at the core of software development. To sum this up: Functional design is on a level of abstraction above (!) logical design or algorithmic design. Functional design is only done until you get to a point where each function is so simple you are very confident you can easily code it. Functional design an logical design (which mostly is coding, but can also be done using pseudo code or flow charts) are complementary. Software needs both. If you start coding right away you end up in a tangled mess very quickly. Then you need back out through refactoring. Functional design on the other hand is bloodless without actual code. It´s just a theory with no experiments to prove it. But how to do functional design? An example of functional design Let´s assume a program to de-duplicate strings. The user enters a number of strings separated by commas, e.g. a, b, a, c, d, b, e, c, a. And the program is supposed to clear this list of all doubles, e.g. a, b, c, d, e. There is only one Entry Point to this program: the user triggers the de-duplication by starting the program with the string list on the command line C:\>deduplicate "a, b, a, c, d, b, e, c, a" a, b, c, d, e …or by clicking on a GUI button. This leads to the Entry Point function to get called. It´s the program´s main function in case of the batch version or a button click event handler in the GUI version. That´s the physical Entry Point so to speak. It´s inevitable. What then happens is a three step process: Transform the input data from the user into a request. Call the request handler. Transform the output of the request handler into a tangible result for the user. Or to phrase it a bit more generally: Accept input. Transform input into output. Present output. This does not mean any of these steps requires a lot of effort. Maybe it´s just one line of code to accomplish it. Nevertheless it´s a distinct step in doing the processing behind an Entry Point. Call it an aspect or a responsibility - and you will realize it most likely deserves a function of its own to satisfy the Single Responsibility Principle (SRP). Interestingly the above list of steps is already functional design. There is no logic, but nevertheless the solution is described - albeit on a higher level of abstraction than you might have done yourself. But it´s still on a meta-level. The application to the domain at hand is easy, though: Accept string list from command line De-duplicate Present de-duplicated strings on standard output And this concrete list of processing steps can easily be transformed into code:static void Main(string[] args) { var input = Accept_string_list(args); var output = Deduplicate(input); Present_deduplicated_string_list(output); } Instead of a big problem there are three much smaller problems now. If you think each of those is trivial to implement, then go for it. You can stop the functional design at this point. But maybe, just maybe, you´re not so sure how to go about with the de-duplication for example. Then just implement what´s easy right now, e.g.private static string Accept_string_list(string[] args) { return args[0]; } private static void Present_deduplicated_string_list( string[] output) { var line = string.Join(", ", output); Console.WriteLine(line); } Accept_string_list() contains logic in the form of an API-call. Present_deduplicated_string_list() contains logic in the form of an expression and an API-call. And then repeat the functional design for the remaining processing step. What´s left is the domain logic: de-duplicating a list of strings. How should that be done? Without any logic at our disposal during functional design you´re left with just functions. So which functions could make up the de-duplication? Here´s a suggestion: De-duplicate Parse the input string into a true list of strings. Register each string in a dictionary/map/set. That way duplicates get cast away. Transform the data structure into a list of unique strings. Processing step 2 obviously was the core of the solution. That´s where real creativity was needed. That´s the core of the domain. But now after this refinement the implementation of each step is easy again:private static string[] Parse_string_list(string input) { return input.Split(',') .Select(s => s.Trim()) .ToArray(); } private static Dictionary<string,object> Compile_unique_strings(string[] strings) { return strings.Aggregate( new Dictionary<string, object>(), (agg, s) => { agg[s] = null; return agg; }); } private static string[] Serialize_unique_strings( Dictionary<string,object> dict) { return dict.Keys.ToArray(); } With these three additional functions Main() now looks like this:static void Main(string[] args) { var input = Accept_string_list(args); var strings = Parse_string_list(input); var dict = Compile_unique_strings(strings); var output = Serialize_unique_strings(dict); Present_deduplicated_string_list(output); } I think that´s very understandable code: just read it from top to bottom and you know how the solution to the problem works. It´s a mirror image of the initial design: Accept string list from command line Parse the input string into a true list of strings. Register each string in a dictionary/map/set. That way duplicates get cast away. Transform the data structure into a list of unique strings. Present de-duplicated strings on standard output You can even re-generate the design by just looking at the code. Code and functional design thus are always in sync - if you follow some simple rules. But about that later. And as a bonus: all the functions making up the process are small - which means easy to understand, too. So much for an initial concrete example. Now it´s time for some theory. Because there is method to this madness ;-) The above has only scratched the surface. Introducing Flow Design Functional design starts with a given function, the Entry Point. Its goal is to describe the behavior of the program when the Entry Point is triggered using a process, not an algorithm. An algorithm consists of logic, a process on the other hand consists just of steps or stages. Each processing step transforms input into output or a side effect. Also it might access resources, e.g. a printer, a database, or just memory. Processing steps thus can rely on state of some sort. This is different from Functional Programming, where functions are supposed to not be stateful and not cause side effects.[1] In its simplest form a process can be written as a bullet point list of steps, e.g. Get data from user Output result to user Transform data Parse data Map result for output Such a compilation of steps - possibly on different levels of abstraction - often is the first artifact of functional design. It can be generated by a team in an initial design brainstorming. Next comes ordering the steps. What should happen first, what next etc.? Get data from user Parse data Transform data Map result for output Output result to user That´s great for a start into functional design. It´s better than starting to code right away on a given function using TDD. Please get me right: TDD is a valuable practice. But it can be unnecessarily hard if the scope of a functionn is too large. But how do you know beforehand without investing some thinking? And how to do this thinking in a systematic fashion? My recommendation: For any given function you´re supposed to implement first do a functional design. Then, once you´re confident you know the processing steps - which are pretty small - refine and code them using TDD. You´ll see that´s much, much easier - and leads to cleaner code right away. For more information on this approach I call “Informed TDD” read my book of the same title. Thinking before coding is smart. And writing down the solution as a bunch of functions possibly is the simplest thing you can do, I´d say. It´s more according to the KISS (Keep It Simple, Stupid) principle than returning constants or other trivial stuff TDD development often is started with. So far so good. A simple ordered list of processing steps will do to start with functional design. As shown in the above example such steps can easily be translated into functions. Moving from design to coding thus is simple. However, such a list does not scale. Processing is not always that simple to be captured in a list. And then the list is just text. Again. Like code. That means the design is lacking visuality. Textual representations need more parsing by your brain than visual representations. Plus they are limited in their “dimensionality”: text just has one dimension, it´s sequential. Alternatives and parallelism are hard to encode in text. In addition the functional design using numbered lists lacks data. It´s not visible what´s the input, output, and state of the processing steps. That´s why functional design should be done using a lightweight visual notation. No tool is necessary to draw such designs. Use pen and paper; a flipchart, a whiteboard, or even a napkin is sufficient. Visualizing processes The building block of the functional design notation is a functional unit. I mostly draw it like this: Something is done, it´s clear what goes in, it´s clear what comes out, and it´s clear what the processing step requires in terms of state or hardware. Whenever input flows into a functional unit it gets processed and output is produced and/or a side effect occurs. Flowing data is the driver of something happening. That´s why I call this approach to functional design Flow Design. It´s about data flow instead of control flow. Control flow like in algorithms is of no concern to functional design. Thinking about control flow simply is too low level. Once you start with control flow you easily get bogged down by tons of details. That´s what you want to avoid during design. Design is supposed to be quick, broad brush, abstract. It should give overview. But what about all the details? As Robert C. Martin rightly said: “Programming is abot detail”. Detail is a matter of code. Once you start coding the processing steps you designed you can worry about all the detail you want. Functional design does not eliminate all the nitty gritty. It just postpones tackling them. To me that´s also an example of the SRP. Function design has the responsibility to come up with a solution to a problem posed by a single function (Entry Point). And later coding has the responsibility to implement the solution down to the last detail (i.e. statement, API-call). TDD unfortunately mixes both responsibilities. It´s just coding - and thereby trying to find detailed implementations (green phase) plus getting the design right (refactoring). To me that´s one reason why TDD has failed to deliver on its promise for many developers. Using functional units as building blocks of functional design processes can be depicted very easily. Here´s the initial process for the example problem: For each processing step draw a functional unit and label it. Choose a verb or an “action phrase” as a label, not a noun. Functional design is about activities, not state or structure. Then make the output of an upstream step the input of a downstream step. Finally think about the data that should flow between the functional units. Write the data above the arrows connecting the functional units in the direction of the data flow. Enclose the data description in brackets. That way you can clearly see if all flows have already been specified. Empty brackets mean “no data is flowing”, but nevertheless a signal is sent. A name like “list” or “strings” in brackets describes the data content. Use lower case labels for that purpose. A name starting with an upper case letter like “String” or “Customer” on the other hand signifies a data type. If you like, you also can combine descriptions with data types by separating them with a colon, e.g. (list:string) or (strings:string[]). But these are just suggestions from my practice with Flow Design. You can do it differently, if you like. Just be sure to be consistent. Flows wired-up in this manner I call one-dimensional (1D). Each functional unit just has one input and/or one output. A functional unit without an output is possible. It´s like a black hole sucking up input without producing any output. Instead it produces side effects. A functional unit without an input, though, does make much sense. When should it start to work? What´s the trigger? That´s why in the above process even the first processing step has an input. If you like, view such 1D-flows as pipelines. Data is flowing through them from left to right. But as you can see, it´s not always the same data. It get´s transformed along its passage: (args) becomes a (list) which is turned into (strings). The Principle of Mutual Oblivion A very characteristic trait of flows put together from function units is: no functional units knows another one. They are all completely independent of each other. Functional units don´t know where their input is coming from (or even when it´s gonna arrive). They just specify a range of values they can process. And they promise a certain behavior upon input arriving. Also they don´t know where their output is going. They just produce it in their own time independent of other functional units. That means at least conceptually all functional units work in parallel. Functional units don´t know their “deployment context”. They now nothing about the overall flow they are place in. They are just consuming input from some upstream, and producing output for some downstream. That makes functional units very easy to test. At least as long as they don´t depend on state or resources. I call this the Principle of Mutual Oblivion (PoMO). Functional units are oblivious of others as well as an overall context/purpose. They are just parts of a whole focused on a single responsibility. How the whole is built, how a larger goal is achieved, is of no concern to the single functional units. By building software in such a manner, functional design interestingly follows nature. Nature´s building blocks for organisms also follow the PoMO. The cells forming your body do not know each other. Take a nerve cell “controlling” a muscle cell for example:[2] The nerve cell does not know anything about muscle cells, let alone the specific muscel cell it is “attached to”. Likewise the muscle cell does not know anything about nerve cells, let a lone a specific nerve cell “attached to” it. Saying “the nerve cell is controlling the muscle cell” thus only makes sense when viewing both from the outside. “Control” is a concept of the whole, not of its parts. Control is created by wiring-up parts in a certain way. Both cells are mutually oblivious. Both just follow a contract. One produces Acetylcholine (ACh) as output, the other consumes ACh as input. Where the ACh is going, where it´s coming from neither cell cares about. Million years of evolution have led to this kind of division of labor. And million years of evolution have produced organism designs (DNA) which lead to the production of these different cell types (and many others) and also to their co-location. The result: the overall behavior of an organism. How and why this happened in nature is a mystery. For our software, though, it´s clear: functional and quality requirements needs to be fulfilled. So we as developers have to become “intelligent designers” of “software cells” which we put together to form a “software organism” which responds in satisfying ways to triggers from it´s environment. My bet is: If nature gets complex organisms working by following the PoMO, who are we to not apply this recipe for success to our much simpler “machines”? So my rule is: Wherever there is functionality to be delivered, because there is a clear Entry Point into software, design the functionality like nature would do it. Build it from mutually oblivious functional units. That´s what Flow Design is about. In that way it´s even universal, I´d say. Its notation can also be applied to biology: Never mind labeling the functional units with nouns. That´s ok in Flow Design. You´ll do that occassionally for functional units on a higher level of abstraction or when their purpose is close to hardware. Getting a cockroach to roam your bedroom takes 1,000,000 nerve cells (neurons). Getting the de-duplication program to do its job just takes 5 “software cells” (functional units). Both, though, follow the same basic principle. Translating functional units into code Moving from functional design to code is no rocket science. In fact it´s straightforward. There are two simple rules: Translate an input port to a function. Translate an output port either to a return statement in that function or to a function pointer visible to that function. The simplest translation of a functional unit is a function. That´s what you saw in the above example. Functions are mutually oblivious. That why Functional Programming likes them so much. It makes them composable. Which is the reason, nature works according to the PoMO. Let´s be clear about one thing: There is no dependency injection in nature. For all of an organism´s complexity no DI container is used. Behavior is the result of smooth cooperation between mutually oblivious building blocks. Functions will often be the adequate translation for the functional units in your designs. But not always. Take for example the case, where a processing step should not always produce an output. Maybe the purpose is to filter input. Here the functional unit consumes words and produces words. But it does not pass along every word flowing in. Some words are swallowed. Think of a spell checker. It probably should not check acronyms for correctness. There are too many of them. Or words with no more than two letters. Such words are called “stop words”. In the above picture the optionality of the output is signified by the astrisk outside the brackets. It means: Any number of (word) data items can flow from the functional unit for each input data item. It might be none or one or even more. This I call a stream of data. Such behavior cannot be translated into a function where output is generated with return. Because a function always needs to return a value. So the output port is translated into a function pointer or continuation which gets passed to the subroutine when called:[3]void filter_stop_words( string word, Action<string> onNoStopWord) { if (...check if not a stop word...) onNoStopWord(word); } If you want to be nitpicky you might call such a function pointer parameter an injection. And technically you´re right. Conceptually, though, it´s not an injection. Because the subroutine is not functionally dependent on the continuation. Firstly continuations are procedures, i.e. subroutines without a return type. Remember: Flow Design is about unidirectional data flow. Secondly the name of the formal parameter is chosen in a way as to not assume anything about downstream processing steps. onNoStopWord describes a situation (or event) within the functional unit only. Translating output ports into function pointers helps keeping functional units mutually oblivious in cases where output is optional or produced asynchronically. Either pass the function pointer to the function upon call. Or make it global by putting it on the encompassing class. Then it´s called an event. In C# that´s even an explicit feature.class Filter { public void filter_stop_words( string word) { if (...check if not a stop word...) onNoStopWord(word); } public event Action<string> onNoStopWord; } When to use a continuation and when to use an event dependens on how a functional unit is used in flows and how it´s packed together with others into classes. You´ll see examples further down the Flow Design road. Another example of 1D functional design Let´s see Flow Design once more in action using the visual notation. How about the famous word wrap kata? Robert C. Martin has posted a much cited solution including an extensive reasoning behind his TDD approach. So maybe you want to compare it to Flow Design. The function signature given is:string WordWrap(string text, int maxLineLength) {...} That´s not an Entry Point since we don´t see an application with an environment and users. Nevertheless it´s a function which is supposed to provide a certain functionality. The text passed in has to be reformatted. The input is a single line of arbitrary length consisting of words separated by spaces. The output should consist of one or more lines of a maximum length specified. If a word is longer than a the maximum line length it can be split in multiple parts each fitting in a line. Flow Design Let´s start by brainstorming the process to accomplish the feat of reformatting the text. What´s needed? Words need to be assembled into lines Words need to be extracted from the input text The resulting lines need to be assembled into the output text Words too long to fit in a line need to be split Does sound about right? I guess so. And it shows a kind of priority. Long words are a special case. So maybe there is a hint for an incremental design here. First let´s tackle “average words” (words not longer than a line). Here´s the Flow Design for this increment: The the first three bullet points turned into functional units with explicit data added. As the signature requires a text is transformed into another text. See the input of the first functional unit and the output of the last functional unit. In between no text flows, but words and lines. That´s good to see because thereby the domain is clearly represented in the design. The requirements are talking about words and lines and here they are. But note the asterisk! It´s not outside the brackets but inside. That means it´s not a stream of words or lines, but lists or sequences. For each text a sequence of words is output. For each sequence of words a sequence of lines is produced. The asterisk is used to abstract from the concrete implementation. Like with streams. Whether the list of words gets implemented as an array or an IEnumerable is not important during design. It´s an implementation detail. Does any processing step require further refinement? I don´t think so. They all look pretty “atomic” to me. And if not… I can always backtrack and refine a process step using functional design later once I´ve gained more insight into a sub-problem. Implementation The implementation is straightforward as you can imagine. The processing steps can all be translated into functions. Each can be tested easily and separately. Each has a focused responsibility. And the process flow becomes just a sequence of function calls: Easy to understand. It clearly states how word wrapping works - on a high level of abstraction. And it´s easy to evolve as you´ll see. Flow Design - Increment 2 So far only texts consisting of “average words” are wrapped correctly. Words not fitting in a line will result in lines too long. Wrapping long words is a feature of the requested functionality. Whether it´s there or not makes a difference to the user. To quickly get feedback I decided to first implement a solution without this feature. But now it´s time to add it to deliver the full scope. Fortunately Flow Design automatically leads to code following the Open Closed Principle (OCP). It´s easy to extend it - instead of changing well tested code. How´s that possible? Flow Design allows for extension of functionality by inserting functional units into the flow. That way existing functional units need not be changed. The data flow arrow between functional units is a natural extension point. No need to resort to the Strategy Pattern. No need to think ahead where extions might need to be made in the future. I just “phase in” the remaining processing step: Since neither Extract words nor Reformat know of their environment neither needs to be touched due to the “detour”. The new processing step accepts the output of the existing upstream step and produces data compatible with the existing downstream step. Implementation - Increment 2 A trivial implementation checking the assumption if this works does not do anything to split long words. The input is just passed on: Note how clean WordWrap() stays. The solution is easy to understand. A developer looking at this code sometime in the future, when a new feature needs to be build in, quickly sees how long words are dealt with. Compare this to Robert C. Martin´s solution:[4] How does this solution handle long words? Long words are not even part of the domain language present in the code. At least I need considerable time to understand the approach. Admittedly the Flow Design solution with the full implementation of long word splitting is longer than Robert C. Martin´s. At least it seems. Because his solution does not cover all the “word wrap situations” the Flow Design solution handles. Some lines would need to be added to be on par, I guess. But even then… Is a difference in LOC that important as long as it´s in the same ball park? I value understandability and openness for extension higher than saving on the last line of code. Simplicity is not just less code, it´s also clarity in design. But don´t take my word for it. Try Flow Design on larger problems and compare for yourself. What´s the easier, more straightforward way to clean code? And keep in mind: You ain´t seen all yet ;-) There´s more to Flow Design than described in this chapter. In closing I hope I was able to give you a impression of functional design that makes you hungry for more. To me it´s an inevitable step in software development. Jumping from requirements to code does not scale. And it leads to dirty code all to quickly. Some thought should be invested first. Where there is a clear Entry Point visible, it´s functionality should be designed using data flows. Because with data flows abstraction is possible. For more background on why that´s necessary read my blog article here. For now let me point out to you - if you haven´t already noticed - that Flow Design is a general purpose declarative language. It´s “programming by intention” (Shalloway et al.). Just write down how you think the solution should work on a high level of abstraction. This breaks down a large problem in smaller problems. And by following the PoMO the solutions to those smaller problems are independent of each other. So they are easy to test. Or you could even think about getting them implemented in parallel by different team members. Flow Design not only increases evolvability, but also helps becoming more productive. All team members can participate in functional design. This goes beyon collective code ownership. We´re talking collective design/architecture ownership. Because with Flow Design there is a common visual language to talk about functional design - which is the foundation for all other design activities.   PS: If you like what you read, consider getting my ebook “The Incremental Architekt´s Napkin”. It´s where I compile all the articles in this series for easier reading. I like the strictness of Function Programming - but I also find it quite hard to live by. And it certainly is not what millions of programmers are used to. Also to me it seems, the real world is full of state and side effects. So why give them such a bad image? That´s why functional design takes a more pragmatic approach. State and side effects are ok for processing steps - but be sure to follow the SRP. Don´t put too much of it into a single processing step. ? Image taken from www.physioweb.org ? My code samples are written in C#. C# sports typed function pointers called delegates. Action is such a function pointer type matching functions with signature void someName(T t). Other languages provide similar ways to work with functions as first class citizens - even Java now in version 8. I trust you find a way to map this detail of my translation to your favorite programming language. I know it works for Java, C++, Ruby, JavaScript, Python, Go. And if you´re using a Functional Programming language it´s of course a no brainer. ? Taken from his blog post “The Craftsman 62, The Dark Path”. ?

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