pandas在重复读写数据库时崩溃

我有以下代码：

import pandas as pd
import time 
import numpy as np
import os 

dir_path = os.path.dirname(os.path.abspath(__file__))
db_path = 'sqlite:///' + dir_path + '/example.db'



df = pd.DataFrame(np.random.normal(0, 1, (500000, 10)), columns=['col%d' % i for i in range(10)])

writes = []
reads = []

for i in range(1000):
    if os.path.exists(dir_path + '/example.db'):
        print 'db removed from disk'
        os.remove(dir_path + '/example.db')

    t0 = time.time()
    df.to_sql('example', db_path)
    t1 = time.time()
    print 'time to write:', t1 - t0

    df = pd.read_sql('SELECT * FROM example', db_path)
    t2 = time.time()
    print "time to read:", t2 - t1

    writes.append(t1 - t0)
    reads.append(t2 - t1)

    print 'Average writing time', np.mean(writes), ' n times=', len(writes)
    print 'Average reading time', np.mean(reads), ' n times=', len(reads)

它崩溃的原因是：

(mlcne_venv) [lpuggini@machinelearn-1 Desktop]$ python read_write_time.py
db removed from disk
time to write: 16.2156860828
time to read: 3.31190609932
Average writing time 16.2156860828  n times= 1
Average reading time 3.31190609932  n times= 1
db removed from disk
time to write: 15.6938099861
time to read: 3.74449300766
Average writing time 15.9547480345  n times= 2
Average reading time 3.52819955349  n times= 2
db removed from disk
Traceback (most recent call last):
  File "read_write_time.py", line 23, in <module>
    df.to_sql('example', db_path)
  File "/home/lpuggini/VirtualEnvs/mlcne_venv/lib/python2.7/site-packages/pandas/core/generic.py", line 1201, in to_sql
    chunksize=chunksize, dtype=dtype)
  File "/home/lpuggini/VirtualEnvs/mlcne_venv/lib/python2.7/site-packages/pandas/io/sql.py", line 470, in to_sql
    chunksize=chunksize, dtype=dtype)
  File "/home/lpuggini/VirtualEnvs/mlcne_venv/lib/python2.7/site-packages/pandas/io/sql.py", line 1148, in to_sql
    table.insert(chunksize)
  File "/home/lpuggini/VirtualEnvs/mlcne_venv/lib/python2.7/site-packages/pandas/io/sql.py", line 642, in insert
    keys, data_list = self.insert_data()
  File "/home/lpuggini/VirtualEnvs/mlcne_venv/lib/python2.7/site-packages/pandas/io/sql.py", line 609, in insert_data
    "duplicate name in index/columns: {0}".format(err))
ValueError: duplicate name in index/columns: cannot insert level_0, already exists
(mlcne_venv) [lpuggini@machinelearn-1 Desktop]$ 

---

可能是熊猫虫吗

每一次迭代都会给您一个新的索引列。如果您在从数据库读取数据后添加了输出命令print df.head，则会得到以下结果：

1st iteration:

   index      col0      col1      col2      col3      col4      col5  \
0      0  1.562089  2.297787 -0.490346  0.935589 -0.151018 -0.920552   
1      1 -0.868018  1.212738  1.386166 -0.422851 -0.243167 -0.362809   
2      2 -0.420472  0.069789  2.706735  0.814905  1.095517  0.570413   
3      3 -0.341983 -0.727765  0.549108  0.785910  0.687795  2.158346   
4      4 -0.476875  0.525177 -0.532743  0.382937 -0.824136  1.276228   
       col6      col7      col8      col9  
0 -1.179577  1.746765  0.468008  0.751347  
1  0.810910 -0.386281 -0.512447 -1.124378  
2  2.764994  2.735384 -0.449755 -0.393979  
3 -0.895257 -0.396221 -1.149718 -0.382153  
4  0.177278 -0.212614  0.185388  0.688391  

2nd iteration:

   level_0  index      col0      col1      col2      col3      col4      col5  \
0        0      0  1.562089  2.297787 -0.490346  0.935589 -0.151018 -0.920552   
1        1      1 -0.868018  1.212738  1.386166 -0.422851 -0.243167 -0.362809   
2        2      2 -0.420472  0.069789  2.706735  0.814905  1.095517  0.570413   
3        3      3 -0.341983 -0.727765  0.549108  0.785910  0.687795  2.158346   
4        4      4 -0.476875  0.525177 -0.532743  0.382937 -0.824136  1.276228   

       col6      col7      col8      col9  
0 -1.179577  1.746765  0.468008  0.751347  
1  0.810910 -0.386281 -0.512447 -1.124378  
2  2.764994  2.735384 -0.449755 -0.393979  
3 -0.895257 -0.396221 -1.149718 -0.382153  
4  0.177278 -0.212614  0.185388  0.688391  

然后它崩溃了

只需将write命令更改为

df.to_sql('example', db_path, index=False)

---

所以它不会每次都创建一个新索引。

下一次迭代都会为您提供一个新的索引列。如果您在从数据库读取数据后添加了输出命令print df.head，则会得到以下结果：

1st iteration:

   index      col0      col1      col2      col3      col4      col5  \
0      0  1.562089  2.297787 -0.490346  0.935589 -0.151018 -0.920552   
1      1 -0.868018  1.212738  1.386166 -0.422851 -0.243167 -0.362809   
2      2 -0.420472  0.069789  2.706735  0.814905  1.095517  0.570413   
3      3 -0.341983 -0.727765  0.549108  0.785910  0.687795  2.158346   
4      4 -0.476875  0.525177 -0.532743  0.382937 -0.824136  1.276228   
       col6      col7      col8      col9  
0 -1.179577  1.746765  0.468008  0.751347  
1  0.810910 -0.386281 -0.512447 -1.124378  
2  2.764994  2.735384 -0.449755 -0.393979  
3 -0.895257 -0.396221 -1.149718 -0.382153  
4  0.177278 -0.212614  0.185388  0.688391  

2nd iteration:

   level_0  index      col0      col1      col2      col3      col4      col5  \
0        0      0  1.562089  2.297787 -0.490346  0.935589 -0.151018 -0.920552   
1        1      1 -0.868018  1.212738  1.386166 -0.422851 -0.243167 -0.362809   
2        2      2 -0.420472  0.069789  2.706735  0.814905  1.095517  0.570413   
3        3      3 -0.341983 -0.727765  0.549108  0.785910  0.687795  2.158346   
4        4      4 -0.476875  0.525177 -0.532743  0.382937 -0.824136  1.276228   

       col6      col7      col8      col9  
0 -1.179577  1.746765  0.468008  0.751347  
1  0.810910 -0.386281 -0.512447 -1.124378  
2  2.764994  2.735384 -0.449755 -0.393979  
3 -0.895257 -0.396221 -1.149718 -0.382153  
4  0.177278 -0.212614  0.185388  0.688391  

然后它崩溃了

只需将write命令更改为

df.to_sql('example', db_path, index=False)

所以它不会每次都创建一个新索引