def load_agencies(request, indexfile=""):
#Open summary excelfile
wbin = xlrd.open_workbook(indexfile)
#Agencies
sh_source = wbin.sheet_by_name(u'Agencies')
for rownum in range(1,sh_source.nrows):
row = sh_source.row_values(rownum)
shortname = row[0]
fullname = row[1]
parentname = row[2]
website = row[3]
scraped = True
newagency = Agency(shortname=shortname, name=fullname, parentname=parentname,
website=website, notes="", scraped=scraped)
newagency.save()
return HttpResponse("Agency details loaded from file.")
def load_agencies(request, indexfile=""):
#Open summary excelfile
wbin = xlrd.open_workbook(indexfile)
#Agencies
sh_source = wbin.sheet_by_name(u'Agencies')
for rownum in range(1, sh_source.nrows):
row = sh_source.row_values(rownum)
shortname = row[0]
fullname = row[1]
parentname = row[2]
website = row[3]
scraped = True
newagency = Agency(shortname=shortname,
name=fullname,
parentname=parentname,
website=website,
notes="",
scraped=scraped)
newagency.save()
return HttpResponse("Agency details loaded from file.")
def load_indicator_spreadsheet(request, indexfile=""):
#Open summary excelfile
wbin = xlrd.open_workbook(indexfile)
#Agencies
sh_source = wbin.sheet_by_name(u'Agencies')
for rownum in range(1, sh_source.nrows):
row = sh_source.row_values(rownum)
shortname = row[0]
fullname = row[1]
parentname = row[2]
website = row[3]
scraped = True
newagency = Agency(shortname=shortname,
name=fullname,
parentname=parentname,
website=website,
notes="",
scraped=scraped)
newagency.save()
#Datasources
sh_source = wbin.sheet_by_name(u'Datasources Used')
for rownum in range(1, sh_source.nrows):
row = sh_source.row_values(rownum)
shortname = row[0]
fullname = row[1]
sourceagency = row[2]
sourcefile = row[5]
sourceurl = row[7]
#FIXIT: should be the times when scrapers were run, not the date the file
#was uploaded
todaysdate = datetime.now()
newsource = Datasource(shortname=shortname,
name=fullname,
notes="",
url=sourceurl,
dateadded=todaysdate,
datechecked=todaysdate,
scraper=True,
localfile=sourcefile)
newsource.save()
sh_source = wbin.sheet_by_name(u'Suggested Sources')
for rownum in range(1, sh_source.nrows):
row = sh_source.row_values(rownum)
shortname = row[0]
fullname = row[1]
sourceagency = row[2]
sourceurl = row[3]
newsource = Datasource(shortname=shortname,
name=fullname,
notes="",
url=sourceurl,
dateadded=todaysdate,
datechecked=todaysdate,
scraper=False,
localfile="")
newsource.save()
#Indicators
indicators = {}
sh_ind = wbin.sheet_by_name(u'Indicators Needed')
for rownum in range(1, sh_ind.nrows):
row = sh_ind.row_values(rownum)
indcode = row[0]
indname = row[1]
indicators[indcode] = indname
## newindicator = Indicator()
## newindicator.save()
#Indicators in sources
found = {}
sh_found = wbin.sheet_by_name(u'Indicators Found')
for rownum in range(1, sh_found.nrows):
row = sh_found.row_values(rownum)
sourcecode = row[0]
indcode = row[1]
csvheading = row[4]
#Only process indicators that we have data for
if not (csvheading == ""):
if not (found.has_key(sourcecode)):
found[sourcecode] = {}
found[sourcecode][csvheading] = indcode
## newfound = foundIndicator(indicator=, datasource=,
## csvfile=, csvindname=,
## datasourceindname=,
## datasourcedesc=, notes=)
## newfound.save()
return HttpResponse("Indicator details loaded from file.")
def load_indicator_spreadsheet(request, indexfile=""):
#Open summary excelfile
wbin = xlrd.open_workbook(indexfile)
#Agencies
sh_source = wbin.sheet_by_name(u'Agencies')
for rownum in range(1,sh_source.nrows):
row = sh_source.row_values(rownum)
shortname = row[0]
fullname = row[1]
parentname = row[2]
website = row[3]
scraped = True
newagency = Agency(shortname=shortname, name=fullname, parentname=parentname,
website=website, notes="", scraped=scraped)
newagency.save()
#Datasources
sh_source = wbin.sheet_by_name(u'Datasources Used')
for rownum in range(1,sh_source.nrows):
row = sh_source.row_values(rownum)
shortname = row[0]
fullname = row[1]
sourceagency = row[2]
sourcefile = row[5]
sourceurl = row[7]
#FIXIT: should be the times when scrapers were run, not the date the file
#was uploaded
todaysdate = datetime.now()
newsource = Datasource(shortname=shortname, name=fullname, notes="",
url=sourceurl,
dateadded=todaysdate, datechecked=todaysdate,
scraper=True, localfile=sourcefile)
newsource.save()
sh_source = wbin.sheet_by_name(u'Suggested Sources')
for rownum in range(1,sh_source.nrows):
row = sh_source.row_values(rownum)
shortname = row[0]
fullname = row[1]
sourceagency = row[2]
sourceurl = row[3]
newsource = Datasource(shortname=shortname, name=fullname, notes="",
url=sourceurl,
dateadded=todaysdate, datechecked=todaysdate,
scraper=False, localfile="")
newsource.save()
#Indicators
indicators = {}
sh_ind = wbin.sheet_by_name(u'Indicators Needed')
for rownum in range(1,sh_ind.nrows):
row = sh_ind.row_values(rownum)
indcode = row[0]
indname = row[1]
indicators[indcode] = indname
## newindicator = Indicator()
## newindicator.save()
#Indicators in sources
found = {}
sh_found = wbin.sheet_by_name(u'Indicators Found')
for rownum in range(1,sh_found.nrows):
row = sh_found.row_values(rownum)
sourcecode = row[0]
indcode = row[1]
csvheading = row[4]
#Only process indicators that we have data for
if not(csvheading == ""):
if not(found.has_key(sourcecode)):
found[sourcecode] = {}
found[sourcecode][csvheading] = indcode
## newfound = foundIndicator(indicator=, datasource=,
## csvfile=, csvindname=,
## datasourceindname=,
## datasourcedesc=, notes=)
## newfound.save()
return HttpResponse("Indicator details loaded from file.")