Python prettytable美化你的输出
看代码:#!/usr/bin/python# -*- coding:utf-8 -*-import prettytable as ptfrom prettytable import from_csvfrom prettytable import from_db_cursorimport MySQLdbimport osimport timedef creatept():tb = pt.Pretty
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看代码:
#!/usr/bin/python
# -*- coding:utf-8 -*-
import prettytable as pt
from prettytable import from_csv
from prettytable import from_db_cursor
import MySQLdb
import os
import time
def creatept():
tb = pt.PrettyTable()
tb.field_names = ["City name", "Area", "Population", "Annual Rainfall"]
tb.add_row(["Adelaide",1295, 1158259, 600.5])
tb.add_row(["Brisbane",5905, 1857594, 1146.4])
tb.add_row(["Darwin", 112, 120900, 1714.7])
tb.add_row(["Hobart", 1357, 205556,619.5])
print(tb)
return tb
def ptfromcvs():
fp = open('/home/hp/Desktop/James_Harden.csv', "r")
pt = from_csv(fp)
fp.close()
print(pt)
def ptfromsql():
db = MySQLdb.connect("127.0.0.1", "root",132456","launcher", charset='utf8')
cursor = db.cursor()
sql="SELECT mac,sn,device_id FROM launcher.iflyos where iflyos_devid='' limit 10"
cursor.execute(sql)
pt = from_db_cursor(cursor)
print(pt)
def pytohtml(tb):
s = tb.get_html_string()
print(s)
def writeLog(tb):
with open ("prettytable.log","a+") as f:
f.write(tb+"\n")
if __name__ == '__main__':
tb=creatept()
pytohtml(tb)
ptfromsql()
ptfromcvs()
writeLog(str(tb))
输出:
+-----------+------+------------+-----------------+
| City name | Area | Population | Annual Rainfall |
+-----------+------+------------+-----------------+
| Adelaide | 1295 | 1158259 | 600.5 |
| Brisbane | 5905 | 1857594 | 1146.4 |
| Darwin | 112 | 120900 | 1714.7 |
| Hobart | 1357 | 205556 | 619.5 |
+-----------+------+------------+-----------------++-----------+------+------------+-----------------+
| City name | Area | Population | Annual Rainfall |
+-----------+------+------------+-----------------+
| Adelaide | 1295 | 1158259 | 600.5 |
| Brisbane | 5905 | 1857594 | 1146.4 |
| Darwin | 112 | 120900 | 1714.7 |
| Hobart | 1357 | 205556 | 619.5 |
+-----------+------+------------+-----------------++-----------+------+------------+-----------------+
| City name | Area | Population | Annual Rainfall |
+-----------+------+------------+-----------------+
| Adelaide | 1295 | 1158259 | 600.5 |
| Brisbane | 5905 | 1857594 | 1146.4 |
| Darwin | 112 | 120900 | 1714.7 |
| Hobart | 1357 | 205556 | 619.5 |
+-----------+------+------------+-----------------+
+-----------+------+------------+-----------------+
| City name | Area | Population | Annual Rainfall |
+-----------+------+------------+-----------------+
| Adelaide | 1295 | 1158259 | 600.5 |
| Brisbane | 5905 | 1857594 | 1146.4 |
| Darwin | 112 | 120900 | 1714.7 |
| Hobart | 1357 | 205556 | 619.5 |
+-----------+------+------------+-----------------+
+-----------+------+------------+-----------------+
| City name | Area | Population | Annual Rainfall |
+-----------+------+------------+-----------------+
| Adelaide | 1295 | 1158259 | 600.5 |
| Brisbane | 5905 | 1857594 | 1146.4 |
| Darwin | 112 | 120900 | 1714.7 |
| Hobart | 1357 | 205556 | 619.5 |
+-----------+------+------------+-----------------+
+-----------+------+------------+-----------------+
| City name | Area | Population | Annual Rainfall |
+-----------+------+------------+-----------------+
| Adelaide | 1295 | 1158259 | 600.5 |
| Brisbane | 5905 | 1857594 | 1146.4 |
| Darwin | 112 | 120900 | 1714.7 |
| Hobart | 1357 | 205556 | 619.5 |
+-----------+------+------------+-----------------+
</table>
+--------------+------------------+----------------------------------+
| mac | sn | device_id |
+--------------+------------------+----------------------------------+
| BC67D48B9918 | PTNEHOPZ9947D73D | 7a43b5341c3e722a7fe1afc46351aaf7 |
| BC5AA084386E | PTM38R296Q2A8DKZ | 94e36ed37688780a245b13354bb83a4b |
| BC33C01F9F68 | PTGGDK3ZT4ASFX40 | 0242811be3d242c3b60198d2f5b1fbdc |
| BC0185ABEE19 | PTXF7XZQOXMV872N | 4ac5399adddac3285dcfc75ae9d09847 |
| BCFFEA44BB4F | PTXEYBG113XKDGRA | bc3beb670e138aeec77f7df95d0f9ce3 |
| BC96E14BFBEF | PTCQOKVADLS9NLQZ | 52b97117f1e7006c471a615481e8650b |
| BCE9222CE9F1 | PT98USHFTSXLFE88 | 048b60f91442922d687405f081549710 |
| BC27740B0B6C | PTL3PGGCL5EC3SHZ | 63a7345bfaee5445ea6a53d9d38f39fc |
| BC46775B92CB | PTHLXBGV0AT2AL39 | ede891b1897b6090ed49cc0fa49bc6d2 |
| BCBE3ACCB1E1 | PT8DAN3Z56A75BUG | 49d5871f0a3ea9b8c230b4af6c268ae2 |
+--------------+------------------+----------------------------------+
+--------+------+--------+------+--------+------------+-----------+------+------+------+
| 对手 | 胜负 | 主客场 | 命中 | 投篮数 | 投篮命中率 | 3分命中率 | 篮板 | 助攻 | 得分 |
+--------+------+--------+------+--------+------------+-----------+------+------+------+
| 勇士 | 胜 | 客 | 10 | 23 | 0.435 | 0.444 | 6 | 11 | 27 |
| 国王 | 胜 | 客 | 8 | 21 | 0.381 | 0.286 | 3 | 9 | 27 |
| 小牛 | 胜 | 主 | 10 | 19 | 0.526 | 0.462 | 3 | 7 | 29 |
| 灰熊 | 负 | 主 | 8 | 20 | 0.4 | 0.25 | 5 | 8 | 22 |
| 76人 | 胜 | 客 | 10 | 20 | 0.5 | 0.25 | 3 | 13 | 27 |
| 黄蜂 | 胜 | 客 | 8 | 18 | 0.444 | 0.4 | 10 | 11 | 27 |
| 灰熊 | 负 | 客 | 6 | 19 | 0.316 | 0.222 | 4 | 8 | 20 |
| 76人 | 负 | 主 | 8 | 21 | 0.381 | 0.429 | 4 | 7 | 29 |
| 尼克斯 | 胜 | 客 | 9 | 23 | 0.391 | 0.353 | 5 | 9 | 31 |
| 老鹰 | 胜 | 客 | 8 | 15 | 0.533 | 0.545 | 3 | 11 | 29 |
| 爵士 | 胜 | 主 | 19 | 25 | 0.76 | 0.875 | 2 | 13 | 56 |
| 骑士 | 胜 | 主 | 8 | 21 | 0.381 | 0.429 | 11 | 13 | 35 |
| 灰熊 | 胜 | 主 | 11 | 25 | 0.44 | 0.429 | 4 | 8 | 38 |
| 步行者 | 胜 | 客 | 9 | 21 | 0.429 | 0.25 | 5 | 15 | 26 |
| 猛龙 | 负 | 主 | 8 | 25 | 0.32 | 0.273 | 6 | 11 | 38 |
| 太阳 | 胜 | 客 | 12 | 22 | 0.545 | 0.545 | 2 | 7 | 48 |
| 灰熊 | 胜 | 客 | 9 | 20 | 0.45 | 0.5 | 5 | 7 | 29 |
| 掘金 | 胜 | 主 | 6 | 16 | 0.375 | 0.143 | 8 | 9 | 21 |
| 尼克斯 | 胜 | 主 | 12 | 27 | 0.444 | 0.385 | 2 | 10 | 37 |
| 篮网 | 胜 | 主 | 13 | 20 | 0.65 | 0.615 | 10 | 8 | 37 |
| 步行者 | 胜 | 主 | 8 | 22 | 0.364 | 0.333 | 8 | 10 | 29 |
| 湖人 | 胜 | 客 | 13 | 22 | 0.591 | 0.444 | 4 | 9 | 36 |
| 爵士 | 胜 | 客 | 8 | 19 | 0.421 | 0.333 | 5 | 3 | 29 |
| 开拓者 | 胜 | 客 | 16 | 29 | 0.552 | 0.571 | 8 | 3 | 48 |
| 鹈鹕 | 胜 | 主 | 8 | 16 | 0.5 | 0.4 | 1 | 17 | 26 |
+--------+------+--------+------+--------+------------+-----------+------+------+------+
这样比普通的输出看起来更明确更有逼格
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