我正在编写一个脚本，将csv文件读取到psql表中，然后对数据进行排序并将其导出到新文件中。如何将导出到csv文件的相同数据打印到终端，以使其像表格一样显示？
这是我的代码：
import psycopg2
import pandas as pd
class Products(object):
def __init__(self):
self.db_connection = psycopg2.connect("host=localhost dbname=rd_assignment user=postgres")
self.db_cur = self.db_connection.cursor()
def add_column(self):
"""This method adds a column to the products database table. It checks if the table is empty before
inserting the csv file."""
self.db_cur.execute("ALTER TABLE products ADD COLUMN IF NOT EXISTS is_active BOOLEAN NOT NULL;")
self.db_cur.execute("SELECT COUNT(*) FROM products;")
rows = self.db_cur.fetchall()
if rows[0][0] < 20:
self.db_cur.execute(
"COPY products FROM '/Users/leroy/PycharmProjects/rd_assignment/products.csv' DELIMITERS ',' CSV;")
self.db_connection.commit()
def sort_highest(self):
"""This method outputs the products to a csv file according to the highest amount"""
sort_highest = "COPY (SELECT * FROM products order by amount desc) TO STDOUT DELIMITER ';' CSV HEADER"
with open("highest_amount.csv", "w") as file:
self.db_cur.copy_expert(sort_highest, file)
r = pd.read_csv('/Users/leroy/PycharmProjects/rd_assignment/highest_amount.csv')
print(r.head(20))
def get_active(self):
"""This method outputs the active products in the database to a csv file"""
sort_active = "COPY (SELECT * FROM products WHERE is_active = True) TO STDOUT DELIMITER ';' CSV HEADER"
with open("active_products.csv", "w") as file:
self.db_cur.copy_expert(sort_active, file)
def get_inactive(self):
"""This method outputs the inactive products in the database to a csv file"""
sort_inactive = \
"COPY (SELECT description, amount FROM products WHERE is_active = False) TO STDOUT DELIMITER ';' CSV HEADER"
with open("inactive_products.csv", "w") as file:
self.db_cur.copy_expert(sort_inactive, file)
def __del__(self):
self.db_connection.close()
if __name__ == '__main__':
instance = Products()
instance.add_column()
instance.sort_highest()
instance.get_active()
instance.get_inactive()
导入的csv文件如下所示：
101,9/25/2018,9/25/2018,"Sinotec 40"" FHD LED TV",5,TRUE
102,9/25/2018,9/25/2018,Playstation 4 1TB Console - Marvel Spider-man,5,TRUE
103,9/25/2018,9/25/2018,Mellerware - 3.5 Litre Tempo Slow Cooker,6,FALSE
104,9/25/2018,9/25/2018,Samsung Galaxy S9 64GB - Black,12,TRUE
105,9/25/2018,9/25/2018,Cougar Armor Gaming Chair - Black,3,FALSE
106,9/25/2018,9/25/2018,Destiny 2 Legendary Collection(PS4),2,TRUE
107,9/25/2018,9/25/2018,"AIWA 43"" Full HD LED TV",3,FALSE
108,9/25/2018,9/25/2018,Ibanez PF17ECE-LG Acoustic/Electric Guitar,2,FALSE
109,9/25/2018,9/25/2018,Plantronics Audio 355 Stereo headset - Black,6,TRUE
110,9/25/2018,9/25/2018,Speck Presidio Case for Apple iPhone 7/8,6,FALSE
111,9/25/2018,9/25/2018,Skone Langebaan Key Hole UV400 Sunglasses,6,TRUE
112,9/25/2018,9/25/2018,Fadecase Karambit Elite Gamma Doppler Phase 2,6,TRUE
113,9/25/2018,9/25/2018,JBL GO Portable Bluetooth Speaker - Blue,6,TRUE
114,9/25/2018,9/25/2018,"WD Blue 250GB 2.5"" 3D NAND SATA SSD",8,FALSE
115,9/25/2018,9/25/2018,Philips - Metal Kettle - Red,8,TRUE
116,9/25/2018,9/25/2018,Apple AirPods,2,FALSE
117,9/25/2018,9/25/2018,Apple Watch Series 3 GPS 42mm,5,FALSE
118,9/25/2018,9/25/2018,Gigabyte GeForce GTX 1080 G1 Gaming Edition,8,FALSE
119,9/25/2018,9/25/2018,HTC Vive Eco Black VR Goggles (PC),11,FALSE
120,9/25/2018,9/25/2018,Corsair Vengeance LED 32GB Memory Kit - Red,10,TRUE
答案 0 :(得分：2)
我认为并没有太多支持将漂亮的csv文件打印到终端的内置支持。这是一个快速脚本，可以漂亮地打印给定的csv文件：
import csv
def pad_col(col, max_width):
return col.ljust(max_width)
with open('test.csv') as csvfile:
reader = csv.reader(csvfile)
all_rows = []
for row in reader:
all_rows.append(row)
max_col_width = [0] * len(all_rows[0])
for row in all_rows:
for idx, col in enumerate(row):
max_col_width[idx] = max(len(col), max_col_width[idx])
for row in all_rows:
to_print = ""
for idx, col in enumerate(row):
to_print += pad_col(col, max_col_width[idx]) + " | "
print("-"*len(to_print))
print(to_print)
如果test.csv包含上面的csv输入，您将获得以下输出：
-------------------------------------------------------------------------------------------
101 | 9/25/2018 | 9/25/2018 | Sinotec 40" FHD LED TV | 5 | TRUE |
-------------------------------------------------------------------------------------------
102 | 9/25/2018 | 9/25/2018 | Playstation 4 1TB Console - Marvel Spider-man | 5 | TRUE |
-------------------------------------------------------------------------------------------
103 | 9/25/2018 | 9/25/2018 | Mellerware - 3.5 Litre Tempo Slow Cooker | 6 | FALSE |
-------------------------------------------------------------------------------------------
104 | 9/25/2018 | 9/25/2018 | Samsung Galaxy S9 64GB - Black | 12 | TRUE |
-------------------------------------------------------------------------------------------
105 | 9/25/2018 | 9/25/2018 | Cougar Armor Gaming Chair - Black | 3 | FALSE |
-------------------------------------------------------------------------------------------
106 | 9/25/2018 | 9/25/2018 | Destiny 2 Legendary Collection(PS4) | 2 | TRUE |
-------------------------------------------------------------------------------------------
107 | 9/25/2018 | 9/25/2018 | AIWA 43" Full HD LED TV | 3 | FALSE |
-------------------------------------------------------------------------------------------
108 | 9/25/2018 | 9/25/2018 | Ibanez PF17ECE-LG Acoustic/Electric Guitar | 2 | FALSE |
-------------------------------------------------------------------------------------------
109 | 9/25/2018 | 9/25/2018 | Plantronics Audio 355 Stereo headset - Black | 6 | TRUE |
-------------------------------------------------------------------------------------------
110 | 9/25/2018 | 9/25/2018 | Speck Presidio Case for Apple iPhone 7/8 | 6 | FALSE |
-------------------------------------------------------------------------------------------
111 | 9/25/2018 | 9/25/2018 | Skone Langebaan Key Hole UV400 Sunglasses | 6 | TRUE |
-------------------------------------------------------------------------------------------
112 | 9/25/2018 | 9/25/2018 | Fadecase Karambit Elite Gamma Doppler Phase 2 | 6 | TRUE |
-------------------------------------------------------------------------------------------
113 | 9/25/2018 | 9/25/2018 | JBL GO Portable Bluetooth Speaker - Blue | 6 | TRUE |
-------------------------------------------------------------------------------------------
114 | 9/25/2018 | 9/25/2018 | WD Blue 250GB 2.5" 3D NAND SATA SSD | 8 | FALSE |
-------------------------------------------------------------------------------------------
115 | 9/25/2018 | 9/25/2018 | Philips - Metal Kettle - Red | 8 | TRUE |
-------------------------------------------------------------------------------------------
116 | 9/25/2018 | 9/25/2018 | Apple AirPods | 2 | FALSE |
-------------------------------------------------------------------------------------------
117 | 9/25/2018 | 9/25/2018 | Apple Watch Series 3 GPS 42mm | 5 | FALSE |
-------------------------------------------------------------------------------------------
118 | 9/25/2018 | 9/25/2018 | Gigabyte GeForce GTX 1080 G1 Gaming Edition | 8 | FALSE |
-------------------------------------------------------------------------------------------
119 | 9/25/2018 | 9/25/2018 | HTC Vive Eco Black VR Goggles (PC) | 11 | FALSE |
-------------------------------------------------------------------------------------------
120 | 9/25/2018 | 9/25/2018 | Corsair Vengeance LED 32GB Memory Kit - Red | 10 | TRUE |
该解决方案不是特别有效或紧凑。您可以花一整天的时间将其推广到漂亮的csvs。我将这些改进项目留给读者练习……
HTH，至少应该让您入门。
答案 1 :(得分：1)
尝试prettytable。
from prettytable import PrettyTable
x = PrettyTable()
x.field_names = ["Sl.n0", "date1", "date2", "comments","Boolean"]
with open('file.csv') as f:
line = f.readline()
while line:
x.add_row(line.rstrip().split(','))
line = f.readline()
print x
使用pip安装：
pip install PrettyTable
查找示例here
答案 2 :(得分：1)
我建议使用tabulate。它可以输出各种表格格式的数据。
from tabulate import tabulate
import pandas as pd
df = pd.read_csv('data.csv')
print(tabulate(df, headers='keys', tablefmt='psql'))
示例：
from tabulate import tabulate
import pandas as pd
df = pd.DataFrame({'col_two' : [0.0001, 1e-005 , 1e-006, 1e-007],
'column_3' : ['ABCD', 'ABCD', 'long string', 'ABCD']})
print(tabulate(df, headers='keys', tablefmt='psql'))
+----+-----------+-------------+
| | col_two | column_3 |
|----+-----------+-------------|
| 0 | 0.0001 | ABCD |
| 1 | 1e-05 | ABCD |
| 2 | 1e-06 | long string |
| 3 | 1e-07 | ABCD |
+----+-----------+-------------+
支持的表格格式为：