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PyCon 2012 -  Data Driven Design
PyCon 2012 -  Data Driven Design
PyCon 2012 -  Data Driven Design
PyCon 2012 -  Data Driven Design
PyCon 2012 -  Data Driven Design
PyCon 2012 -  Data Driven Design
PyCon 2012 -  Data Driven Design
PyCon 2012 -  Data Driven Design
PyCon 2012 -  Data Driven Design
PyCon 2012 -  Data Driven Design
PyCon 2012 -  Data Driven Design
PyCon 2012 -  Data Driven Design
PyCon 2012 -  Data Driven Design
PyCon 2012 -  Data Driven Design
PyCon 2012 -  Data Driven Design
PyCon 2012 -  Data Driven Design
PyCon 2012 -  Data Driven Design
PyCon 2012 -  Data Driven Design
PyCon 2012 -  Data Driven Design
PyCon 2012 -  Data Driven Design
PyCon 2012 -  Data Driven Design
PyCon 2012 -  Data Driven Design
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PyCon 2012 - Data Driven Design

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  1. Max Klymyshyn CTO at GVMachinesData Driven DesignBuild app design around dataflow rather than program flow tweet tweet @maxmaxmaxmax
  2. Whats the problem? Handling many of different data sources and keep context
  3. Typical task for this approach Random picture from Google
  4. Really? Yup, honestly its depend on the task. Theres a lot of examples of data-driven programming around. The most known example is Django Middleware
  5. So, lets go deeper
  6. Data Drivenprogramming definition
  7. What is Data Driven programming Data driven programming is a programming model wherethe data itself controls the flow of the program and not the program logic
  8. Not so strict Data Driven definition is quite strict.Typically its mixed with other approaches
  9. Real world task sample usage
  10. Show only sunny days in the month I want to grab weather from different sources and display only sunny days of the month
  11. PipelineTo grab data we should define pipeline - theway our data going to go
  12. Pipeline Grab Parse Validate Display
  13. In details Grab Fetch data from weather.com Fetch data from pogoda.yandex.ua Fetch data from weather.yahooapis.com Parse Parse weather.com Parse pogoda.yandex.ua Parase api.aerisapi.com Validate Pass sunny days only
  14. PipelineAt this moment we have only sunny days todisplay
  15. Approacheswhen this may be be effective?
  16. If this then thatifttt.comifttt is a web service platform that connectsvarious web services together to automatecommon tasks on the web
  17. Various sourcesWhen you have a lot of mostly similar data fromdifferent sourcesYou need to keep only data whichmatters for you
  18. Data slices generationIn case you need to generate a lot of similardata sets filtered by many of params
  19. PipesIn general, approach is the same as usage ofUNIX pipes:cat file.dat | grep something | sed s/xxx/yyy/g
  20. Summary Grab Parse Validate Display
  21. Examplehttps://github.com/joymax/data-driven-design
  22. Thats all, thank you. Questions?tweet tweet @maxmaxmaxmax Github: joymax

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