November 2017 1HaskellADay problems and solutions

• November 30th, 2017: For Thursday's #haskell problem we've published our articles to the PostgreSQL database, now let's extract them as JSON. Today's #haskell solution is a simple SQL query and applying some work from previous exercise to fetch and JSONify recommended articles to print! 
• November 29th, 2017: For Wednesday's #haskell problem, now that we've selected the recommended articles, let's save that for review to the PostgreSQL database. For today's #haskell solution, we delete the old recommendations-to-be-published, we insert the new set. Voilà! 
• November 28th, 2017: Monday we added articles from a PostgreSQL database using #haskell; Tuesday we delete articles. WHEEEEE! Today's #haskell solution shows that deleting article recommendations is very much like adding recommendations, ... in reverse. WHODATHUNK! 
• November 27th, 2017: Monday's problem: "It's not rocket science!" Adding articles to a recommendation set in PostgreSQL with #haskell. A little bit of #haskell; a little bit of #PHP and we have an article-adder-webservice ... thingie! 
• November 24th, 2017: Friday's #haskell problem: PostgreSQL database, JSON, Haskell: you've got yourself a webservice. Friday's #haskell solution uses the Brief-structure, this time to show article recommendations.
• November 23rd, 2017: For Thursday, a fun little #haskell JSON-y exercise on Thanksgiving Day from the USA to you! Y'know, Nietzsche says: "Out of chaos comes JSON." ... no ... wait. 
• November 22nd, 2017: Wednesday's #haskell problem: given a NYT article index, extract the article full text from PostgreSQL. Simple, eh? ... 'maybe.' Full text of NYT articles archived in PostgreSQL as JSON. 
• November 21st, 2017: Tuesday's #haskell problem we slim down the article JSON returned from yesterday by providing article briefs. Today's #haskell solution goes from a set of recommendations from NYT articles to briefs. 
• November 20th, 2017: Monday's #haskell problem moves keyword/key-phrase-article retrieval and matching to the PostgreSQL database. Today's #haskell solution: we build our keyword-key-phrase dictionary from SQL and filter articles indexing from those keywords. 
• November 17th, 2017: Thursday we linked keywords to key-phrases; for Friday's #haskell problem, we'll upload that linkage information to a PostgreSQL data store. Today's #haskell solution stores 26,000+ keywords, with almost 240,000 cross-references into nearly 10,000 NYT articles. Whoa. 
• November 16th, 2017: Thursday's #haskell problem: provide a mapping from unique keywords to key-phrases containing them. Mapping keywords to key-phrases, it's what we do for today's #haskell solution. 
• November 15th, 2017: Wednesday's #haskell problem is to parse a CSV file of articles to upload to an article MongoDB. Today's #haskell solution has a little bit of CSVing and a little bit of JSONification to upload article information into MongoDB. 
• November 14th, 2017: Tuesday's #haskell exercise is a parsing exercise of a different sort: parsing CSV, but with embedded quote within columns! Ooh! We now can parse CSV files with embedded quotes. YES! Adding that to the old CSV parsing library. 
• November 13th, 2017: Indexing articles by keyword and then searching articles by keyword for Monday's #haskell problem. For today's #haskell solution we intersect sets of articles to do fast keyword searches. 
• November 10th, 2017: Friday's #haskell exercise is to load the keywords and recommended articles into the PostgreSQL database. Thanks to today's #haskell solution we have articles and keyphrases indexed by keyword. 
• November 9th, 2017: Thursday's #haskell problem ties NYT article data stored in PostgreSQL together with the recommended articles from JSON. Today's #haskell solution is reading NYT article recommendations from a PostgreSQL database. 
• November 8th, 2017: Wednesday's #haskell problem is to combine article recommendations with their key-phrases to output as JSON. Wednesday's #haskell solution: JSON: GET. (p.s. I love Data.Aeson.Encode.Pretty)
• November 7th, 2017: Tuesday's #haskell problem is to parse JSON of NYT articles and their metadata. Today's #haskell solution: we have articles stored as JSON, and, voilà! we materialize those articles! 
• November 6th, 2017: Monday's #haskell exercise is to parse a CSV file of recommended articles from the NYT archive. Today's #haskell solution uses the reads-function to guide the parsing of values from a CSV file.
• November 3rd, 2017: Today is Friday! YAY! Do you know what that means? It's PARSING DAY is #haskell-land! YAY! ... no ... wait. What? TIL that parsing keywords and parsing LISTS of keywords can be very different things for today's #haskell solution.
• November 2nd, 2017: Today's #haskell problem: 'Hello, world' in Haskell. Snark on the side FO' FREE! I don't recall Eliza being this snarky, but today's #haskell solution says differently. 
• November 1st, 2017: Wednesday #haskell problem is scan a new archive and update the special character file or correct the new archive. The #haskell solution to replacing special characters... WHAT special characters? They GONE! #ETL