def download(self, engine=None, debug=False):
Script.download(self, engine, debug)
self.engine.download_file(self.urls["GWDD"],
"GlobalWoodDensityDatabase.xls")
filename = os.path.basename("GlobalWoodDensityDatabase.xls")
book = xlrd.open_workbook(self.engine.format_filename(filename))
sh = book.sheet_by_index(1)
rows = sh.nrows
#Creating data table
lines = []
for i in range(1, rows):
row = sh.row(i)
if not all(Excel.empty_cell(cell) for cell in row):
this_line = {}
def format_value(s):
s = Excel.cell_value(s)
return str(s).title().replace("\\", "/").replace('"', '')
for num, label in enumerate([
"Number", "Family", "Binomial", "Wood_Density",
"Region", "Reference_Number"
]):
this_line[label] = format_value(row[num])
lines.append(this_line)
table = Table("data", delimiter="\t")
table.columns = [("Number", ("pk-int", )), ("Family", ("char", )),
("Binomial", ("char", )),
("Wood_Density", ("double", )),
("Region", ("char", )),
("Reference_Number", ("int", ))]
table.pk = 'Number'
table.contains_pk = True
gwdd = []
for line in lines:
gwdd_data = [
line["Number"], line["Family"], line["Binomial"],
line["Wood_Density"], line["Region"], line["Reference_Number"]
]
gwdd.append(gwdd_data)
data = ['\t'.join(gwdd_line) for gwdd_line in gwdd]
self.engine.table = table
self.engine.create_table()
self.engine.add_to_table(data)
#Creating reference table
lines = []
sh = book.sheet_by_index(2)
rows = sh.nrows
for i in range(1, rows):
row = sh.row(i)
if not all(Excel.empty_cell(cell) for cell in row):
this_line = {}
def format_value(s):
s = Excel.cell_value(s)
return str(s).title().replace("\\", "/").replace('"', '')
for num, label in enumerate(["Reference_Number", "Reference"]):
this_line[label] = format_value(row[num])
lines.append(this_line)
table = Table("reference", delimiter="\t")
table.columns = [("Reference_Number", ("pk-int", )),
("Reference", ("char", ))]
table.pk = 'Reference_Number'
table.contains_pk = True
gwdd = []
for line in lines:
gwdd_ref = [line["Reference_Number"], line["Reference"]]
gwdd.append(gwdd_ref)
data = ['\t'.join(gwdd_line) for gwdd_line in gwdd]
self.engine.table = table
self.engine.create_table()
self.engine.add_to_table(data)
return self.engine
def download(self, engine=None, debug=False):
Script.download(self, engine, debug)
self.engine.auto_create_table(Table("sites"),
url=self.urls["sites"],
filename='gentry_sites.csv')
self.engine.insert_data_from_url(self.urls["sites"])
self.engine.download_file(self.urls["stems"], "all_Excel.zip")
local_zip = zipfile.ZipFile(
self.engine.format_filename("all_Excel.zip"))
filelist = local_zip.namelist()
local_zip.close()
self.engine.download_files_from_archive(self.urls["stems"], filelist)
filelist = [os.path.basename(filename) for filename in filelist]
# Currently all_Excel.zip is missing CURUYUQU.xls
# Download it separately and add it to the file list
if not self.engine.find_file('CURUYUQU.xls'):
self.engine.download_file(
"http://www.mobot.org/mobot/gentry/123/samerica/CURUYUQU.xls",
"CURUYUQU.xls")
filelist.append('CURUYUQU.xls')
lines = []
tax = []
for filename in filelist:
print("Extracting data from " + filename + "...")
book = xlrd.open_workbook(self.engine.format_filename(filename))
sh = book.sheet_by_index(0)
rows = sh.nrows
cn = {'stems': []}
n = 0
for colnum, c in enumerate(sh.row(0)):
if not Excel.empty_cell(c):
cid = c.value.lower().strip()
# line number column is sometimes named differently
if cid in ["sub", "number"]:
cid = "line"
# the "number of individuals" column is named in various
# different ways; they always at least contain "nd"
if "nd" in cid:
cid = "count"
# in QUIAPACA.xls the "number of individuals" column is
# misnamed "STEMDBH" just like the stems columns, so weep
# for the state of scientific data and then fix manually
if filename == "QUIAPACA.xls" and colnum == 13:
cid = "count"
# if column is a stem, add it to the list of stems;
# otherwise, make note of the column name/number
if "stem" in cid or "dbh" in cid:
cn["stems"].append(n)
else:
cn[cid] = n
n += 1
# sometimes, a data file does not contain a liana or count column
if not "liana" in list(cn.keys()):
cn["liana"] = -1
if not "count" in list(cn.keys()):
cn["count"] = -1
for i in range(1, rows):
row = sh.row(i)
cellcount = len(row)
# make sure the row is real, not just empty cells
if not all(Excel.empty_cell(cell) for cell in row):
try:
this_line = {}
# get the following information from the appropriate columns
for i in [
"line", "family", "genus", "species", "liana",
"count"
]:
if cn[i] > -1:
if row[cn[i]].ctype != 2:
# if the cell type(ctype) is not a number
this_line[i] = row[
cn[i]].value.lower().strip().replace(
"\\", "/").replace('"', '')
else:
this_line[i] = row[cn[i]].value
if this_line[i] == '`':
this_line[i] = 1
this_line["stems"] = [
row[c] for c in cn["stems"]
if not Excel.empty_cell(row[c])
]
this_line["site"] = filename[0:-4]
# Manually correct CEDRAL data, which has a single line
# that is shifted by one to the left starting at Liana
if this_line["site"] == "CEDRAL" and type(
this_line["liana"]) == float:
this_line["liana"] = ""
this_line["count"] = 3
this_line["stems"] = [2.5, 2.5, 30, 18, 25]
lines.append(this_line)
# Check how far the species is identified
full_id = 0
if len(this_line["species"]) < 3:
if len(this_line["genus"]) < 3:
id_level = "family"
else:
id_level = "genus"
else:
id_level = "species"
full_id = 1
tax.append(
(this_line["family"], this_line["genus"],
this_line["species"], id_level, str(full_id)))
except:
raise
pass
tax = sorted(
tax, key=lambda group: group[0] + " " + group[1] + " " + group[2])
unique_tax = []
tax_dict = {}
tax_count = 0
# Get all unique families/genera/species
print("\n")
for group in tax:
if not (group in unique_tax):
unique_tax.append(group)
tax_count += 1
tax_dict[group[0:3]] = tax_count
if tax_count % 10 == 0:
msg = "Generating taxonomic groups: " + str(
tax_count) + " / " + str(TAX_GROUPS)
sys.stdout.flush()
sys.stdout.write(msg + "\b" * len(msg))
print("\n")
# Create species table
table = Table("species", delimiter=",")
table.columns = [("species_id", ("pk-int", )), ("family", ("char", )),
("genus", ("char", )), ("species", ("char", )),
("id_level", ("char", 10)), ("full_id", ("int", ))]
data = [[str(tax_dict[group[:3]])] + ['"%s"' % g for g in group]
for group in unique_tax]
table.pk = 'species_id'
table.contains_pk = True
self.engine.table = table
self.engine.create_table()
self.engine.add_to_table(data)
# Create stems table
table = Table("stems", delimiter=",")
table.columns = [("stem_id", ("pk-auto", )), ("line", ("int", )),
("species_id", ("int", )),
("site_code", ("char", 12)), ("liana", ("char", 10)),
("stem", ("double", ))]
stems = []
counts = []
for line in lines:
try:
liana = line["liana"]
except KeyError:
liana = ""
species_info = [
line["line"],
tax_dict[(line["family"], line["genus"], line["species"])],
line["site"], liana
]
try:
counts.append(
[value for value in species_info + [line["count"]]])
except KeyError:
pass
for i in line["stems"]:
stem = species_info + [str(i)]
stems.append(stem)
self.engine.table = table
self.engine.create_table()
self.engine.add_to_table(stems)
# Create counts table
table = Table("counts", delimiter=",", contains_pk=False)
table.columns = [("count_id", ("pk-auto", )), ("line", ("int", )),
("species_id", ("int", )),
("site_code", ("char", 12)), ("liana", ("char", 10)),
("count", ("double", ))]
self.engine.table = table
self.engine.create_table()
self.engine.add_to_table(counts)
return self.engine
def download(self, engine=None, debug=False):
Script.download(self, engine, debug)
reload(sys)
if hasattr(sys, 'setdefaultencoding'):
sys.setdefaultencoding("utf-8")
self.engine.download_file(self.urls["GWDD"], "GlobalWoodDensityDatabase.xls")
filename = os.path.basename("GlobalWoodDensityDatabase.xls")
book = xlrd.open_workbook(self.engine.format_filename(filename))
sh = book.sheet_by_index(1)
rows = sh.nrows
# Creating data files
file_path = self.engine.format_filename("gwdd_data.csv")
gwdd_data = open_fw(file_path)
csv_writer = open_csvw(gwdd_data)
csv_writer.writerow(["Number", "Family", "Binomial", "Wood_Density", "Region", "Reference_Number"])
for index in range(1, rows):
row = sh.row(index)
# get each row and format the sell value.
row_as_list = [to_str(column_value.value) for column_value in row]
csv_writer.writerow(row_as_list)
gwdd_data.close()
table = Table("data", delimiter=",")
table.columns = [("Number", ("pk-int",)),
("Family", ("char",)),
("Binomial", ("char",)),
("Wood_Density", ("double",)),
("Region", ("char",)),
("Reference_Number", ("int",))]
table.pk = 'Number'
table.contains_pk = True
self.engine.table = table
self.engine.create_table()
self.engine.insert_data_from_file(engine.format_filename(file_path))
# Creating reference tale file
file_path = self.engine.format_filename("gwdd_ref.csv")
ref_file = open_fw(file_path)
csv_writerd = open_csvw(ref_file)
csv_writerd.writerow(["Reference_Number", "Reference"])
sh = book.sheet_by_index(2)
rows = sh.nrows
for index in range(1, rows):
row = sh.row(index)
# get each row and format the sell value.
row_as_list = [to_str(column_value.value, object_encoding=sys.stdout) for column_value in row]
csv_writerd.writerow(row_as_list)
ref_file.close()
table = Table("reference", delimiter=",")
table.columns = [("Reference_Number", ("pk-int",)), ("Reference", ("char",))]
table.pk = 'Reference_Number'
table.contains_pk = True
self.engine.table = table
self.engine.create_table()
self.engine.insert_data_from_file(engine.format_filename(file_path))
return self.engine
def download(self, engine=None, debug=False):
Script.download(self, engine, debug)
self.engine.auto_create_table(Table("sites"), url=self.urls["sites"])
self.engine.insert_data_from_url(self.urls["sites"])
self.engine.download_file(self.urls["stems"], "all_Excel.zip")
local_zip = zipfile.ZipFile(self.engine.format_filename("all_Excel.zip"))
filelist = local_zip.namelist()
local_zip.close()
self.engine.download_files_from_archive(self.urls["stems"], filelist)
filelist = [os.path.basename(filename) for filename in filelist]
lines = []
tax = []
for filename in filelist:
print "Extracting data from " + filename + "..."
book = xlrd.open_workbook(self.engine.format_filename(filename))
sh = book.sheet_by_index(0)
rows = sh.nrows
cn = {'stems': []}
n = 0
for c in sh.row(0):
if not Excel.empty_cell(c):
cid = Excel.cell_value(c).lower()
# line number column is sometimes named differently
if cid in ["sub", "number"]:
cid = "line"
# the "number of individuals" column is named in various
# different ways; they always at least contain "nd"
if "nd" in cid:
cid = "count"
# if column is a stem, add it to the list of stems;
# otherwise, make note of the column name/number
if "stem" in cid:
cn["stems"].append(n)
else:
cn[cid] = n
n += 1
# sometimes, a data file does not contain a liana or count column
if not "liana" in cn.keys():
cn["liana"] = -1
if not "count" in cn.keys():
cn["count"] = -1
for i in range(1, rows):
row = sh.row(i)
cellcount = len(row)
# make sure the row is real, not just empty cells
if cellcount > 4 and not Excel.empty_cell(row[0]):
try:
this_line = {}
def format_value(s):
s = Excel.cell_value(s)
return str(s).title().replace("\\", "/").replace('"', '')
# get the following information from the appropriate columns
for i in ["line", "family", "genus", "species",
"liana", "count"]:
if cn[i] > -1:
this_line[i] = format_value(row[cn[i]])
if this_line[i] == '`':
this_line[i] = 1
this_line["stems"] = [Excel.cell_value(row[c])
for c in cn["stems"]
if not Excel.empty_cell(row[c])]
this_line["site"] = filename[0:-4]
lines.append(this_line)
# Check how far the species is identified
full_id = 0
if len(this_line["species"]) < 3:
if len(this_line["genus"]) < 3:
id_level = "family"
else:
id_level = "genus"
else:
id_level = "species"
full_id = 1
tax.append((this_line["family"],
this_line["genus"],
this_line["species"].lower().replace('\\', '').replace('"', ''),
id_level,
str(full_id)))
except:
raise
pass
tax = sorted(tax, key=lambda group: group[0] + " " + group[1] + " " + group[2])
unique_tax = []
tax_dict = dict()
tax_count = 0
# Get all unique families/genera/species
for group in tax:
if not (group in unique_tax):
unique_tax.append(group)
tax_count += 1
tax_dict[group[0:3]] = tax_count
if tax_count % 10 == 0:
msg = "Generating taxonomic groups: " + str(tax_count) + " / " + str(TAX_GROUPS)
sys.stdout.write(msg + "\b" * len(msg))
print "Generating taxonomic groups: " + str(TAX_GROUPS) + " / " + str(TAX_GROUPS)
# Create species table
table = Table("species", delimiter=",")
table.columns=[("species_id" , ("pk-int",) ),
("family" , ("char", ) ),
("genus" , ("char", ) ),
("species" , ("char", ) ),
("id_level" , ("char", 10) ),
("full_id" , ("bool",) )]
data = [','.join([str(tax_dict[group[:3]])] + ['"%s"' % g for g in group])
for group in unique_tax]
table.pk = 'species_id'
table.contains_pk = True
self.engine.table = table
self.engine.create_table()
self.engine.add_to_table(data)
# Create stems table
table = Table("stems", delimiter=",", contains_pk=False)
table.columns=[("stem_id" , ("pk-auto",) ),
("line" , ("int",) ),
("species_id" , ("int",) ),
("site_code" , ("char", 12) ),
("liana" , ("char", 10) ),
("stem" , ("double",) )]
stems = []
counts = []
for line in lines:
try:
liana = line["liana"]
except KeyError:
liana = ""
species_info = [line["line"],
tax_dict[(line["family"],
line["genus"],
line["species"].lower())],
line["site"],
liana
]
try:
counts.append([str(value) for value in species_info + [line["count"]]])
except KeyError:
pass
for i in line["stems"]:
stem = species_info + [i]
stems.append([str(value) for value in stem])
data = [','.join(stem) for stem in stems]
self.engine.table = table
self.engine.create_table()
self.engine.add_to_table(data)
# Create counts table
table = Table("counts", delimiter=",", contains_pk=False)
table.columns=[("count_id" , ("pk-auto",) ),
("line" , ("int",) ),
("species_id" , ("int",) ),
("site_code" , ("char", 12) ),
("liana" , ("char", 10) ),
("count" , ("double",) )]
data = [','.join(count) for count in counts]
self.engine.table = table
self.engine.create_table()
self.engine.add_to_table(data)
return self.engine
def download(self, engine=None, debug=False):
Script.download(self, engine, debug)
reload(sys)
if hasattr(sys, 'setdefaultencoding'):
sys.setdefaultencoding("utf-8")
self.engine.download_file(self.urls["GWDD"],
"GlobalWoodDensityDatabase.xls")
filename = os.path.basename("GlobalWoodDensityDatabase.xls")
book = xlrd.open_workbook(self.engine.format_filename(filename))
sh = book.sheet_by_index(1)
rows = sh.nrows
# Creating data files
file_path = self.engine.format_filename("gwdd_data.csv")
gwdd_data = open_fw(file_path)
csv_writer = open_csvw(gwdd_data)
csv_writer.writerow([
"Number", "Family", "Binomial", "Wood_Density", "Region",
"Reference_Number"
])
for index in range(1, rows):
row = sh.row(index)
# get each row and format the sell value.
row_as_list = [to_str(column_value.value) for column_value in row]
csv_writer.writerow(row_as_list)
gwdd_data.close()
table = Table("data", delimiter=",")
table.columns = [("Number", ("pk-int", )), ("Family", ("char", )),
("Binomial", ("char", )),
("Wood_Density", ("double", )),
("Region", ("char", )),
("Reference_Number", ("int", ))]
table.pk = 'Number'
table.contains_pk = True
self.engine.table = table
self.engine.create_table()
self.engine.insert_data_from_file(engine.format_filename(file_path))
# Creating reference tale file
file_path = self.engine.format_filename("gwdd_ref.csv")
ref_file = open_fw(file_path)
csv_writerd = open_csvw(ref_file)
csv_writerd.writerow(["Reference_Number", "Reference"])
sh = book.sheet_by_index(2)
rows = sh.nrows
for index in range(1, rows):
row = sh.row(index)
# get each row and format the sell value.
row_as_list = [
to_str(column_value.value, object_encoding=sys.stdout)
for column_value in row
]
csv_writerd.writerow(row_as_list)
ref_file.close()
table = Table("reference", delimiter=",")
table.columns = [("Reference_Number", ("pk-int", )),
("Reference", ("char", ))]
table.pk = 'Reference_Number'
table.contains_pk = True
self.engine.table = table
self.engine.create_table()
self.engine.insert_data_from_file(engine.format_filename(file_path))
return self.engine
def download(self, engine=None, debug=False):
Script.download(self, engine, debug)
self.engine.auto_create_table(Table("sites"), url=self.urls["sites"], filename='gentry_sites.csv')
self.engine.insert_data_from_url(self.urls["sites"])
self.engine.download_file(self.urls["stems"], "all_Excel.zip")
local_zip = zipfile.ZipFile(self.engine.format_filename("all_Excel.zip"))
filelist = local_zip.namelist()
local_zip.close()
self.engine.download_files_from_archive(self.urls["stems"], filelist)
filelist = [os.path.basename(filename) for filename in filelist]
# Currently all_Excel.zip is missing CURUYUQU.xls
# Download it separately and add it to the file list
if not self.engine.find_file('CURUYUQU.xls'):
self.engine.download_file("http://www.mobot.org/mobot/gentry/123/samerica/CURUYUQU.xls", "CURUYUQU.xls")
filelist.append('CURUYUQU.xls')
lines = []
tax = []
for filename in filelist:
print("Extracting data from " + filename + "...")
book = xlrd.open_workbook(self.engine.format_filename(filename))
sh = book.sheet_by_index(0)
rows = sh.nrows
cn = {'stems': []}
n = 0
for colnum, c in enumerate(sh.row(0)):
if not Excel.empty_cell(c):
cid = c.value.lower().strip()
# line number column is sometimes named differently
if cid in ["sub", "number"]:
cid = "line"
# the "number of individuals" column is named in various
# different ways; they always at least contain "nd"
if "nd" in cid:
cid = "count"
# in QUIAPACA.xls the "number of individuals" column is
# misnamed "STEMDBH" just like the stems columns, so weep
# for the state of scientific data and then fix manually
if filename == "QUIAPACA.xls" and colnum == 13:
cid = "count"
# if column is a stem, add it to the list of stems;
# otherwise, make note of the column name/number
if "stem" in cid or "dbh" in cid:
cn["stems"].append(n)
else:
cn[cid] = n
n += 1
# sometimes, a data file does not contain a liana or count column
if not "liana" in list(cn.keys()):
cn["liana"] = -1
if not "count" in list(cn.keys()):
cn["count"] = -1
for i in range(1, rows):
row = sh.row(i)
cellcount = len(row)
# make sure the row is real, not just empty cells
if not all(Excel.empty_cell(cell) for cell in row):
try:
this_line = {}
# get the following information from the appropriate columns
for i in ["line", "family", "genus", "species",
"liana", "count"]:
if cn[i] > -1:
if row[cn[i]].ctype != 2:
# if the cell type(ctype) is not a number
this_line[i] = row[cn[i]].value.lower().strip().replace("\\", "/").replace('"', '')
else:
this_line[i] = row[cn[i]].value
if this_line[i] == '`':
this_line[i] = 1
this_line["stems"] = [row[c]
for c in cn["stems"]
if not Excel.empty_cell(row[c])]
this_line["site"] = filename[0:-4]
# Manually correct CEDRAL data, which has a single line
# that is shifted by one to the left starting at Liana
if this_line["site"] == "CEDRAL" and type(this_line["liana"]) == float:
this_line["liana"] = ""
this_line["count"] = 3
this_line["stems"] = [2.5, 2.5, 30, 18, 25]
lines.append(this_line)
# Check how far the species is identified
full_id = 0
if len(this_line["species"]) < 3:
if len(this_line["genus"]) < 3:
id_level = "family"
else:
id_level = "genus"
else:
id_level = "species"
full_id = 1
tax.append((this_line["family"],
this_line["genus"],
this_line["species"],
id_level,
str(full_id)))
except:
raise
pass
tax = sorted(tax, key=lambda group: group[0] + " " + group[1] + " " + group[2])
unique_tax = []
tax_dict = {}
tax_count = 0
# Get all unique families/genera/species
print("\n")
for group in tax:
if not (group in unique_tax):
unique_tax.append(group)
tax_count += 1
tax_dict[group[0:3]] = tax_count
if tax_count % 10 == 0:
msg = "Generating taxonomic groups: " + str(tax_count) + " / " + str(TAX_GROUPS)
sys.stdout.flush()
sys.stdout.write(msg + "\b" * len(msg))
print("\n")
# Create species table
table = Table("species", delimiter=",")
table.columns=[("species_id" , ("pk-int",) ),
("family" , ("char", ) ),
("genus" , ("char", ) ),
("species" , ("char", ) ),
("id_level" , ("char", 10) ),
("full_id" , ("int",) )]
data = [[str(tax_dict[group[:3]])] + ['"%s"' % g for g in group]
for group in unique_tax]
table.pk = 'species_id'
table.contains_pk = True
self.engine.table = table
self.engine.create_table()
self.engine.add_to_table(data)
# Create stems table
table = Table("stems", delimiter=",")
table.columns=[("stem_id" , ("pk-auto",) ),
("line" , ("int",) ),
("species_id" , ("int",) ),
("site_code" , ("char", 12) ),
("liana" , ("char", 10) ),
("stem" , ("double",) )]
stems = []
counts = []
for line in lines:
try:
liana = line["liana"]
except KeyError:
liana = ""
species_info = [line["line"],
tax_dict[(line["family"],
line["genus"],
line["species"])],
line["site"],
liana
]
try:
counts.append([value for value in species_info + [line["count"]]])
except KeyError:
pass
for i in line["stems"]:
stem = species_info + [str(i)]
stems.append(stem)
self.engine.table = table
self.engine.create_table()
self.engine.add_to_table(stems)
# Create counts table
table = Table("counts", delimiter=",", contains_pk=False)
table.columns=[("count_id" , ("pk-auto",) ),
("line" , ("int",) ),
("species_id" , ("int",) ),
("site_code" , ("char", 12) ),
("liana" , ("char", 10) ),
("count" , ("double",) )]
self.engine.table = table
self.engine.create_table()
self.engine.add_to_table(counts)
return self.engine
def download(self, engine=None, debug=False):
Script.download(self, engine, debug)
self.engine.download_file(self.urls["GWDD"], "GlobalWoodDensityDatabase.xls")
filename = os.path.basename("GlobalWoodDensityDatabase.xls")
book = xlrd.open_workbook(self.engine.format_filename(filename))
sh = book.sheet_by_index(1)
rows = sh.nrows
#Creating data table
lines = []
for i in range(1, rows):
row = sh.row(i)
if not all(Excel.empty_cell(cell) for cell in row):
this_line = {}
def format_value(s):
s = Excel.cell_value(s)
return str(s).title().replace("\\", "/").replace('"', '')
for num, label in enumerate(["Number", "Family", "Binomial", "Wood_Density",
"Region", "Reference_Number"]):
this_line[label] = format_value(row[num])
lines.append(this_line)
table = Table("data", delimiter="\t")
table.columns=[("Number" , ("pk-int",) ),
("Family" , ("char",) ),
("Binomial" , ("char",) ),
("Wood_Density" , ("double",) ),
("Region" , ("char",) ),
("Reference_Number" , ("int",) )]
table.pk = 'Number'
table.contains_pk = True
gwdd = []
for line in lines:
gwdd_data = [line["Number"],
line["Family"],
line["Binomial"],
line["Wood_Density"],
line["Region"],
line["Reference_Number"]]
gwdd.append(gwdd_data)
data = ['\t'.join(gwdd_line) for gwdd_line in gwdd]
self.engine.table = table
self.engine.create_table()
self.engine.add_to_table(data)
#Creating reference table
lines = []
sh = book.sheet_by_index(2)
rows = sh.nrows
for i in range(1, rows):
row = sh.row(i)
if not all(Excel.empty_cell(cell) for cell in row):
this_line = {}
def format_value(s):
s = Excel.cell_value(s)
return str(s).title().replace("\\", "/").replace('"', '')
for num, label in enumerate(["Reference_Number", "Reference"]):
this_line[label] = format_value(row[num])
lines.append(this_line)
table = Table("reference", delimiter="\t")
table.columns=[("Reference_Number" , ("pk-int",) ),
("Reference" , ("char",) )]
table.pk = 'Reference_Number'
table.contains_pk = True
gwdd = []
for line in lines:
gwdd_ref = [line["Reference_Number"],
line["Reference"]]
gwdd.append(gwdd_ref)
data = ['\t'.join(gwdd_line) for gwdd_line in gwdd]
self.engine.table = table
self.engine.create_table()
self.engine.add_to_table(data)
return self.engine