本文整理匯總了Python中retriever.lib.models.Table.ct_column方法的典型用法代碼示例。如果您正苦於以下問題：Python Table.ct_column方法的具體用法？Python Table.ct_column怎麽用？Python Table.ct_column使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類retriever.lib.models.Table的用法示例。
在下文中一共展示了Table.ct_column方法的2個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。
示例1: download
# 需要導入模塊: from retriever.lib.models import Table [as 別名]
# 或者: from retriever.lib.models.Table import ct_column [as 別名]
def download(self, engine=None, debug=False):
Script.download(self, engine, debug)
engine = self.engine
files = ["Macroplot_data_Rev.txt", "Microplot_data.txt", "Site_variables.txt", "Species_list.txt"]
engine.download_files_from_archive(self.urls["data"], files, filetype="zip")
# Create table species
engine.auto_create_table(Table('species', cleanup=self.cleanup_func_table),
filename="Species_list.txt")
engine.insert_data_from_file(engine.format_filename("Species_list.txt"))
# Create table sites
engine.auto_create_table(Table('sites', cleanup=self.cleanup_func_table),
filename="Site_variables.txt")
engine.insert_data_from_file(engine.format_filename("Site_variables.txt"))
# Create table microplots
table = Table('microplots')
table.columns = [('record_id', ('pk-auto',)), ('SpCode', ('char', '30')), ('Count', ('ct-int',))]
table.ct_names = ['BSP1', 'BSP2', 'BSP3', 'BSP4', 'BSP5', 'BSP6', 'BSP7', 'BSP8', 'BSP9',
'BSP10', 'BSP11', 'BSP12', 'BSP13', 'BSP14', 'BSP15', 'BSP16', 'BSP17',
'BSP18', 'BSP20', 'BSP21', 'BSP22', 'BSP23', 'BSP24', 'BSP25', 'BSP26',
'BSP27', 'BSP28', 'BSP29', 'BSP30', 'BSP31', 'BSP33', 'BSP34', 'BSP35',
'BSP36', 'BSP37', 'BSP41', 'BSP42', 'BSP43', 'BSP44', 'BSP45', 'BSP46',
'BSP47', 'BSP48', 'BSP49', 'BSP50', 'BSP51', 'BSP52', 'BSP53', 'BSP54',
'BSP55', 'BSP56', 'BSP57', 'BSP58', 'BSP59', 'BSP60', 'BSP61', 'BSP62',
'BSP63', 'BSP64', 'BSP65', 'BSP66', 'BSP67', 'BSP68', 'BSP69', 'BSP70',
'BSP71', 'BSP72', 'BSP73', 'BSP74', 'BSP75', 'BSP76', 'BSP78', 'BSP79',
'BSP80', 'BSP82', 'BSP83', 'BSP84', 'BSP85', 'BSP86', 'BSP87', 'BSP88',
'BSP89', 'BSP90', 'BSP91', 'BSP92', 'BSP93', 'BSP94', 'BSP95', 'BSP96',
'BSP97', 'BSP98', 'BSP99', 'BSP100', 'BSP101', 'BSP102', 'BSP104']
table.ct_column = 'PlotID'
engine.auto_create_table(table, filename="Microplot_data.txt")
engine.insert_data_from_file(engine.format_filename("Microplot_data.txt"))
# Create table microplots
table = Table('macroplots')
table.ct_names = ['TreeGirth1', 'TreeGirth2', 'TreeGirth3', 'TreeGirth4', 'TreeGirth5']
table.ct_column = 'Tree'
table.columns = [('record_id', ('pk-auto',)), ('PlotID', ('char', '20')), ('SpCode', ('char', '30')),
('Girth', ('ct-int',))]
engine.auto_create_table(table, filename="Macroplot_data_Rev.txt")
engine.insert_data_from_file(engine.format_filename("Macroplot_data_Rev.txt"))示例2: download
# 需要導入模塊: from retriever.lib.models import Table [as 別名]
# 或者: from retriever.lib.models.Table import ct_column [as 別名]
def download(self, engine=None, debug=False):
Script.download(self, engine, debug)
engine = self.engine
engine.download_files_from_archive(self.urls["data"], ["Data_Files/Amniote_Database_Aug_2015.csv",
"Data_Files/Amniote_Database_References_Aug_2015.csv",
"Data_Files/Amniote_Range_Count_Aug_2015.csv"],
filetype="zip")
ct_column = 'trait' # all tables use the same ct_column name
# Create tables from Amniote_Database_Aug.csv and Amniote_Database_References_Aug_2015.csv
# Both reference and main have the same headers
ct_names = ['female_maturity_d', 'litter_or_clutch_size_n', 'litters_or_clutches_per_y', 'adult_body_mass_g',
'maximum_longevity_y', 'gestation_d', 'weaning_d', 'birth_or_hatching_weight_g', 'weaning_weight_g',
'egg_mass_g', 'incubation_d', 'fledging_age_d', 'longevity_y', 'male_maturity_d',
'inter_litter_or_interbirth_interval_y', 'female_body_mass_g', 'male_body_mass_g',
'no_sex_body_mass_g', 'egg_width_mm', 'egg_length_mm', 'fledging_mass_g', 'adult_svl_cm',
'male_svl_cm', 'female_svl_cm', 'birth_or_hatching_svl_cm', 'female_svl_at_maturity_cm',
'female_body_mass_at_maturity_g', 'no_sex_svl_cm', 'no_sex_maturity_d']
# Create table main from Amniote_Database_Aug_2015.csv
columns = [
('record_id', ('pk-auto',)), ('class', ('char', '20')), ('order', ('char', '20')),
('family', ('char', '20')), ('genus', ('char', '20')), ('species', ('char', '50')),
('subspecies', ('char', '20')), ('common_name', ('char', '400')), ('trait_value', ('ct-double',))]
table_main = Table('main', delimiter=',', cleanup=self.cleanup_func_table)
table_main.ct_column = ct_column
table_main.ct_names = ct_names
table_main.columns = columns
engine.auto_create_table(table_main,
filename="Amniote_Database_Aug_2015.csv")
engine.insert_data_from_file(engine.format_filename("Amniote_Database_Aug_2015.csv"))
# Create table reference from Amniote_Database_References_Aug_2015.csv
reference_columns = [
('record_id', ('pk-auto',)), ('class', ('char', '20')), ('order', ('char', '20')),
('family', ('char', '20')), ('genus', ('char', '20')), ('species', ('char', '50')),
('subspecies', ('char', '20')), ('common_name', ('char', '400')), ('reference', ('ct-char',))]
table_references = Table('references', delimiter=',', cleanup=self.cleanup_func_table)
table_references.ct_column = ct_column
table_references.ct_names = ct_names
table_references.columns = reference_columns
engine.auto_create_table(table_references,
filename="Amniote_Database_References_Aug_2015.csv")
engine.insert_data_from_file(engine.format_filename("Amniote_Database_References_Aug_2015.csv"))
# Create table Range
# This table has different values for headers from the above tables.
range_ct_names = ["min_female_maturity", "max_female_maturity", "count_female_maturity", "min_litter_clutch_size",
"max_litter_clutch_size", "count_litter_clutch_size", "min_litters_clutches",
"max_litters_clutches", "count_litters_clutches", "min_adult_body_mass", "max_adult_body_mass",
"count_adult_body_mass", "min_maximum_longevity", "max_maximum_longevity",
"count_maximum_longevity", "min_gestation", "max_gestation", "count_gestation", "min_weaning",
"max_weaning", "count_weaning", "min_birth_hatching_weight", "max_birth_hatching_weight",
"count_birth_hatching_weight", "min_weaning_weight", "max_weaning_weight", "count_weaning_weight",
"min_egg_mass", "max_egg_mass", "count_egg_mass", "min_incubation", "max_incubation",
"count_incubation", "min_fledging_age", "max_fledging_age", "count_fledging_age",
"min_male_maturity", "max_male_maturity", "count_male_maturity",
"min_inter_litter_interbirth_interval", "max_inter_litter_interbirth_interval",
"count_inter_litter_interbirth_interval", "min_female_body_mass", "max_female_body_mass",
"count_female_body_mass", "min_male_body_mass", "max_male_body_mass", "count_male_body_mass",
"min_no_sex_body_mass", "max_no_sex_body_mass", "count_no_sex_body_mass", "min_egg_width",
"max_egg_width", "count_egg_width", "min_egg_length", "max_egg_length", "count_egg_length",
"min_fledging_mass", "max_fledging_mass", "count_fledging_mass", "min_adult_svl", "max_adult_svl",
"count_adult_svl", "min_male_svl", "max_male_svl", "count_male_svl", "min_female_svl",
"max_female_svl", "count_female_svl", "min_hatching_svl", "max_hatching_svl", "count_hatching_svl",
"min_female_svl_at_maturity", "max_female_svl_at_maturity", "count_female_svl_at_maturity",
"min_female_body_mass_at_maturity", "max_female_body_mass_at_maturity",
"count_female_body_mass_at_maturity", "min_no_sex_svl", "max_no_sex_svl", "count_no_sex_svl",
"min_no_sex_maturity", "max_no_sex_maturity", "count_no_sex_maturity"]
range_columns = [
('record_id', ('pk-auto',)), ('classx', ('char', '20')), ('orderx', ('char', '20')),
('familyx', ('char', '20')), ('genus', ('char', '20')), ('species', ('char', '50')),
('subspecies', ('char', '20')), ('common_name', ('char', '400')), ('trait_value', ('ct-double',))]
table_range = Table('range', delimiter=',', cleanup=self.cleanup_func_table)
table_range.ct_column = ct_column
table_range.ct_names = range_ct_names
table_range.columns = range_columns
engine.auto_create_table(table_range,
filename="Amniote_Range_Count_Aug_2015.csv")
engine.insert_data_from_file(engine.format_filename("Amniote_Range_Count_Aug_2015.csv"))