def main(): #Define our connection string csv_saving_path = '/home/sduprey/My_Data/My_Kriter_Data/My_Kriter_Results/' current_parameter_checked = 'linking' magasin_to_display = '' conn_string = "host='localhost' dbname='KRITERDB' user='******' password='******'" # print the connection string we will use to connect print "Connecting to database\n ->%s" % (conn_string) # get a connection, if a connect cannot be made an exception will be raised here conn = psycopg2.connect(conn_string) # conn.cursor will return a cursor object, you can use this cursor to perform queries cursor = conn.cursor() # execute our Query # X = np.asarray(predictors_list); my_linking_counter_request = "select distinct counter, count(*) from CDS_LINKING_SIMILAR_PRODUCTS group by counter order by counter asc" print "Executing the following request to fetch data for all magasins : " + my_linking_counter_request # fetching data to display for magasin Musique cursor.execute(my_linking_counter_request); # retrieve the records from the database numerical_data = cursor.fetchall() X= np.asanyarray(numerical_data); #y= np.asanyarray(y); print type(X) print X.shape save_histogram_as_csv_file(current_parameter_checked, magasin_to_display,X,csv_saving_path)
def main(): #Define our connection string results_saving_path = '/home/sduprey/My_Data/My_Kriter_Data/My_Kriter_Results/' magasin_to_display = '' conn_string = "host='localhost' dbname='KRITERDB' user='******' password='******'" # print the connection string we will use to connect print "Connecting to database\n ->%s" % (conn_string) # get a connection, if a connect cannot be made an exception will be raised here conn = psycopg2.connect(conn_string) # conn.cursor will return a cursor object, you can use this cursor to perform queries cursor = conn.cursor() my_full_request = "select nb_distinct_cat5, nb_distinct_cat4, nb_distinct_brand_without_default, nb_distinct_vendor, nb_distinct_magasin, nb_distinct_state from CATALOG where magasin=(%s)" dataNames=["Category5","Category4","Brand","Vendor","Magasin","State"]; print "Data fetched : "+ ', '.join(dataNames) # execute our Query # X = np.asarray(predictors_list); my_brand_request = "select distinct nb_distinct_brand, count(*) from CATALOG where nb_distinct_brand is not null group by nb_distinct_brand order by nb_distinct_brand asc" print "Executing the following request to fetch data for all magasins : " + my_brand_request current_parameter_checked="distinct_brand" # fetching data to display for magasin Musique cursor.execute(my_brand_request); # retrieve the records from the database numerical_data = cursor.fetchall() X= np.asanyarray(numerical_data); #y= np.asanyarray(y); print type(X) print X.shape save_histogram_as_csv_file(current_parameter_checked, magasin_to_display,X,results_saving_path) my_magasin_request = "select distinct nb_distinct_magasin, count(*) from CATALOG where nb_distinct_magasin is not null group by nb_distinct_magasin order by nb_distinct_magasin asc" print "Executing the following request to fetch data for magasins : " + my_magasin_request current_parameter_checked="distinct_magasin" # fetching data to display for magasin Musique cursor.execute(my_magasin_request); # retrieve the records from the database numerical_data = cursor.fetchall() X= np.asanyarray(numerical_data); #y= np.asanyarray(y); print type(X) print X.shape save_histogram_as_csv_file(current_parameter_checked, magasin_to_display,X,results_saving_path) my_state_request = "select distinct nb_distinct_state, count(*) from CATALOG where nb_distinct_state is not null group by nb_distinct_state order by nb_distinct_state asc" print "Executing the following request to fetch data for magasins : " + my_state_request current_parameter_checked="distinct_state" # fetching data to display for magasin Musique cursor.execute(my_state_request); # retrieve the records from the database numerical_data = cursor.fetchall() X= np.asanyarray(numerical_data); #y= np.asanyarray(y); print type(X) print X.shape save_histogram_as_csv_file(current_parameter_checked, magasin_to_display,X,results_saving_path) my_cat4_request = "select distinct nb_distinct_cat4, count(*) from CATALOG where nb_distinct_cat4 is not null group by nb_distinct_cat4 order by nb_distinct_cat4 asc" print "Executing the following request to fetch data for magasins : "+ my_cat4_request current_parameter_checked="distinct_cat4" # fetching data to display for magasin Musique cursor.execute(my_cat4_request); # retrieve the records from the database numerical_data = cursor.fetchall() X= np.asanyarray(numerical_data); #y= np.asanyarray(y); print type(X) print X.shape save_histogram_as_csv_file(current_parameter_checked, magasin_to_display,X,results_saving_path)
def main(): #Define our connection string results_saving_path = '/home/sduprey/My_Data/My_Kriter_Data/My_Kriter_Results/' conn_string = "host='localhost' dbname='KRITERDB' user='******' password='******'" # print the connection string we will use to connect print "Connecting to database\n ->%s" % (conn_string) # get a connection, if a connect cannot be made an exception will be raised here conn = psycopg2.connect(conn_string) # conn.cursor will return a cursor object, you can use this cursor to perform queries cursor = conn.cursor() my_distinct_magasin_request = "select distinct magasin from CATALOG" cursor.execute(my_distinct_magasin_request); # retrieve the records from the database datas = cursor.fetchall() my_magasins = [item[0] for item in datas]; current_parameter_checked=""; #my_magasins = ["Musique","Librairie"]; for magasin_to_loop in my_magasins: magasin_to_display=magasin_to_loop.replace (" ", "_") my_brand_request = "select distinct nb_distinct_brand, count(*) from CATALOG where nb_distinct_brand is not null and magasin=(%s) group by nb_distinct_brand order by nb_distinct_brand asc" current_parameter_checked="distinct_brand" print "Dealing with :"+current_parameter_checked print "Executing the following request to fetch data for magasins : "+magasin_to_loop + my_brand_request # fetching data to display for magasin Musique cursor.execute(my_brand_request,(magasin_to_loop,)); # retrieve the records from the database numerical_data = cursor.fetchall() X= np.asanyarray(numerical_data); #y= np.asanyarray(y); print type(X) print X.shape print X.dtype print X.size save_histogram_as_csv_file(current_parameter_checked, magasin_to_display,X,results_saving_path) my_magasin_request = "select distinct nb_distinct_magasin, count(*) from CATALOG where nb_distinct_magasin is not null and magasin=(%s) group by nb_distinct_magasin order by nb_distinct_magasin asc" current_parameter_checked="distinct_magasin" print "Dealing with :"+current_parameter_checked print "Executing the following request to fetch data for magasins : " +magasin_to_loop+ my_magasin_request # fetching data to display for magasin Musique cursor.execute(my_magasin_request,(magasin_to_loop,)); # retrieve the records from the database numerical_data = cursor.fetchall() X= np.asanyarray(numerical_data); #y= np.asanyarray(y); print type(X) print X.shape save_histogram_as_csv_file(current_parameter_checked, magasin_to_display,X,results_saving_path) my_state_request = "select distinct nb_distinct_state, count(*) from CATALOG where nb_distinct_state is not null and magasin=(%s) group by nb_distinct_state order by nb_distinct_state asc" current_parameter_checked="distinct_state" print "Dealing with :"+current_parameter_checked print "Executing the following request to fetch data for magasins : "+magasin_to_loop + my_state_request # fetching data to display for magasin Musique cursor.execute(my_state_request,(magasin_to_loop,)); # retrieve the records from the database numerical_data = cursor.fetchall() X= np.asanyarray(numerical_data); #y= np.asanyarray(y); print type(X) print X.shape save_histogram_as_csv_file(current_parameter_checked, magasin_to_display,X,results_saving_path) my_cat4_request = "select distinct nb_distinct_cat4, count(*) from CATALOG where nb_distinct_cat4 is not null and magasin=(%s) group by nb_distinct_cat4 order by nb_distinct_cat4 asc" current_parameter_checked="distinct_category_level_4" print "Dealing with :"+current_parameter_checked print "Executing the following request to fetch data for magasins : "+magasin_to_loop + my_cat4_request # fetching data to display for magasin Musique cursor.execute(my_cat4_request,(magasin_to_loop,)); # retrieve the records from the database numerical_data = cursor.fetchall() X= np.asanyarray(numerical_data); #y= np.asanyarray(y); print type(X) print X.shape save_histogram_as_csv_file(current_parameter_checked, magasin_to_display,X,results_saving_path)