Update scraper.py

scraper.py

@@ -22,3 +22,61 @@
 # All that matters is that your final data is written to an SQLite database
 # called "data.sqlite" in the current working directory which has at least a table
 # called "data".
+
+# 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 lxml.html
+#
+# # Read in a page
+# html = scraperwiki.scrape("http://foo.com")
+#
+# # 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"})
+#
+# # An arbitrary query against the database
+# scraperwiki.sql.select("* from data where 'name'='peter'")
+
+# 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
+# All that matters is that your final data is written to an SQLite database
+# called "data.sqlite" in the current working directory which has at least a table
+# called "data".
+
+import scraperwiki
+from urllib2 import urlopen
+from io import BytesIO, TextIOWrapper
+from zipfile import ZipFile
+import csv
+from collections import OrderedDict
+import json
+
+
+def utf_8_encoder(unicode_csv_data):
+    for line in unicode_csv_data:
+        yield line.encode('utf-8')
+
+url = "https://avaandmed.rik.ee/andmed/ARIREGISTER/ariregister_csv.zip"
+response = urlopen(url)
+print("Gotten response.")
+with ZipFile(BytesIO(response.read())) as zfile:
+    print("Pulled zip file.")
+    with zfile.open(ZipFile.namelist(zfile)[0], 'r') as csvfile:
+        print("Opened zip file.")
+        with TextIOWrapper(csvfile, encoding="utf-8-sig") as text:
+            reader = list(csv.reader(utf_8_encoder(text), delimiter=str(";")))
+print("Done reading CSV")
+head = reader[0]
+print(head)
+data = reader
+table = []
+for i in data:
+    reader = OrderedDict(zip(head, i))
+    table.append(reader)
+scraperwiki.sqlite.save(['ariregistri_kood'], data=json.dumps(table), table_name='ee-companies')
+# scraperwiki.sqlite.save(unique_keys=['name'], data=[{"name": "susan", "occupation": "software developer"},{"name": "david", "occupation": "developer"}])