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scraper.py

@@ -1,21 +1,52 @@
 # This is a template for a Python scraper on morph.io (https://morph.io)
 # including some code snippets below that you should find helpful
 
-# import scraperwiki
+import scraperwiki
+from bs4 import BeautifulSoup
+import json
+
 # import lxml.html
 #
 # # Read in a page
-# html = scraperwiki.scrape("http://foo.com")
+result = {}
+html = scraperwiki.scrape("http://www.gat.no/nyheter/tok-ni-for-fart-og-en-for-mobilbruk-1.1802906")
+bs = BeautifulSoup(html, "html5lib")
+article = bs.find("article", {"class": "full_article"})
+
+result["index"] = "1"
+header = article.find("header")
+result["overskrift"] = header.find("h1").text.strip()
+overskrift = result["overskrift"]
+result["ingress"] = header.find("h2", {"class": "light"}).text.strip()
+result["publiseringsdato"] = header.find("time", {"class": "op-published"})["datetime"]
+result["oppdateringsdato"] = header.find("time", {"class": "op-modified"})["datetime"]
+result["forfatter"] = header.find("ul", {"class": "author_details"}).text.strip()
+
+header.extract()
+body = ""
+for p in article("p"):
+    if p:
+        if p.text:
+            body += p.text.strip() + " "
+        elif p.string:
+            body += p.string.strip() + " "
+
+if len(body.strip()) > 0:
+    result["body"] = body
+print(json.dumps(result, indent=1))
 #
 # # Find something on the page using css selectors
 # root = lxml.html.fromstring(html)
 # root.cssselect("div[align='left']")
 #
 # # Write out to the sqlite database using scraperwiki library
-# scraperwiki.sqlite.save(unique_keys=['name'], data={"name": "susan", "occupation": "software developer"})
+#scraperwiki.sqlite.create_table(unique_keys=["overskrift"])
+scraperwiki.sqlite.save(unique_keys=["index"], data=result, table_name="data")
+
 #
 # # An arbitrary query against the database
-# scraperwiki.sql.select("* from data where 'name'='peter'")
+herro = scraperwiki.sql.select("* from data")
+print(herro)
 
 # You don't have to do things with the ScraperWiki and lxml libraries.
 # You can use whatever libraries you want: https://morph.io/documentation/python