bin/sf1blocks2sql

   1 #!/usr/bin/python
   2
   3 """
   4 Exports geographic header records to SQL.
   5 We take a geographic header file, and a table name as arguments, and then
   6 parse that header file to create the necessary SQL statements. The generated
   7 SQL statements refer to the table name passed as an argument.
   8
   9 The output is written to stdout; it can either be redirected to a file,
  10 or piped directly in to the database.
  11 """
  12
  13 import sys
  14 import os
  15 import site
  16
  17 # Basically, add '../src' to our path.
  18 # Needed for the imports that follow.
  19 site.addsitedir(os.path.dirname(os.path.abspath(sys.argv[0])) + '/../src')
  20
  21 import ExitCodes
  22 import GPS
  23 import SummaryFile1
  24
  25
  26 if (len(sys.argv) < 3):
  27     print "Usage: %s <geo_file> <table_name>" % sys.argv[0]
  28     raise SystemExit(ExitCodes.NOT_ENOUGH_ARGS)
  29
  30 geo_file_path = sys.argv[1]
  31 table_name = sys.argv[2]
  32
  33 grp = SummaryFile1.GeoRecordParser()
  34 blocks = grp.parse_blocks(geo_file_path)
  35
  36
  37 sql_query = """
  38 INSERT INTO %s (state,
  39                 county,
  40                 tract,
  41                 block,
  42                 arealand,
  43                 areawatr,
  44                 total_area,
  45                 blkidfp00,
  46                 pop100,
  47                 population_density)
  48
  49 VALUES ('%s', '%s', '%s', '%s', %.12f, %.12f, %.12f, '%s', %d, %.12f);
  50 """
  51
  52 for b in blocks:
  53     # Print out the INSERT statement contained in sql_query,
  54     # substituting in all of the block attributes.
  55     print sql_query % (table_name,
  56                        b.state,
  57                        b.county,
  58                        b.tract,
  59                        b.block,
  60                        b.arealand,
  61                        b.areawatr,
  62                        b.total_area(),
  63                        b.blkidfp00(),
  64                        b.pop100,
  65                        b.population_density())