January 2018 1HaskellADay Problems and Solutions

• January 30th, 2018: For Tuesday's #haskell problem we look at triaging articles downloaded from a REST endpoint against our PostgreSQL database. Who knew putting things into three bins could be so much fun? Today's #haskell solution triages work for us. 
• January 29th, 2018: Monday's #haskell problem is to fetch when the last set of articles were stored; two approaches. Monday's #haskell solution: two approaches to extract 'last entry' from the database, wanted; two approaches to extract 'last entry' from the database, GOT! 
• January 26th, 2018: Friday's #haskell problem is to pull a week's worth of data from a REST endpoint when we don't know a priori how many calls we have to make. Friday's #haskell solution fetches then reads/parses blocks of articles from a REST endpoint. 
• January 24th, 2018: Wednesday's #haskell problem is solving three more #Prolog-y list problems from P99: pack / encode / decode. It's great when #haskell has grouping / 'un'grouping functions in the library already. 
• January 23rd, 2018: Tuesday's #haskell problem: groups and grouper ... I like grouper blackened, please! Solving today's #haskell problem with Qubits?!? Nah, not really, but that would be cool if we did! 
  
• January 22nd, 2018: Monday's #haskell problem is a problem from P99: problem P21, list insertion. Monday's #haskell solution is inserting an element into a list, PROLOG-STYLE! 
• January 18th, 2018: The whole enchilada! Today's #haskell problem ties it all together to make an ETL. Today's #haskell solution defines etl: Looping over calls to the REST endpoint then database insertions. 
• January 17th, 2018: For today's #haskell problem we use PostgreSQL data store and Haskell to pick up where we left off on an application run. Today's #haskell solution: the audit log has what our program last did, so now we know what we'll work on next! 
• January 16th, 2018: Where did yesterday's Haskell problem go? Here it is! Today's #haskell problem: read a packet from a REST endpoint. Today's #haskell solution accesses a REST endpoint with a set timeout and with the default timeout.
• January 15th, 2018: "Logging? Why do we have to log stuff?" Enterprise applications require audit trails. Today's #haskell problem provides one. What did your Haskell app do and when? Today's #haskell solution: an audit log. 
  
• January 11th, 2018: Thursday's #haskell problem: pulling SQL lookup tables into Haskell. Thursday's #haskell solution: with the help of IxValues we extract lookup table values from SQL into Haskell Maps. 
• January 10th, 2018: Wednesday's #haskell exercise is to store the packet information into the PostgreSQL database as a part of auditing the ETL process. Wednesday's #haskell solution stores the packets that wrap article sets then logs our results. 
  
• January 9th, 2018: Tuesday's #haskell problem we are logging log messages to the log data table. YES! Tuesday's #haskell solution: logging in the style of log4j. 
• January 8th, 2018: Monday's #haskell problem: once more into the breach, and thoughts on generalization – storing unique newspaper article sections in PostgreSQL. We store article section information, then we build a function that stores ANYTHING! ... and washes windows, TOO! *
  
  *YMMV additionaltermsandconditionsmayapplydependingonyourregion 
• January 5th, 2018: Friday's #haskell problem takes a break from SQL Databases and Haskell and does something completely different: data schemes and Haskell. AHA! Friday's #haskell solution is a graph-view of the sections for a sample of 100 articles. 
  
• January 4th, 2018: Thursday's #haskell problem looks at storing in PostgreSQL authors of periodic articles uniquely identified by uuid. Thursday #haskell solution uses etl function with generators to store parsed authors in PostgreSQL database. 
  
  
  
  
• January 3rd, 2018: Wednesday's #haskell problem is in honor of Baron Munchausen and his fantastic adventures! 
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• January 2nd, 2018: WELCOME TO THE NEW YEAR, HASKELLERS!
  
  Tuesday's #haskell problem leverages keywords-as-subjects and makes storing article keywords into PostgreSQL easier... we hope. Tuesday's #haskell solution Incorporates prior work with memoizing tables and subjects with results.