https://blog.csdn.net/lwgkzl/article/details/82145387





split()不带参数即可
```python
def test_filter():
    str = "aa     bbbbb         ccc  d"
    str_list = str.split()
    print str_list
```

数据之间空格不一样 python 两种方法分割python多空格字符串

`__call__()`方法作用在于：





类-->实例化-->实例也能当成一个可调用对象

net = Net() #类的实例

out = net(input)  #实例也能当成一个可调用对象

```python
import torch
import torch.nn as nn
import torch.nn.functional as F
class Net(nn.Module):
    def __init__(self):
        super(Net, self).__init__()
        # 输入图像channel：1；输出channel：6；5x5卷积核
        self.conv1 = nn.Conv2d(1, 6, 5)
        self.conv2 = nn.Conv2d(6, 16, 5)
        # an affine operation: y = Wx + b
        self.fc1 = nn.Linear(16 * 5 * 5, 120)
        self.fc2 = nn.Linear(120, 84)
        self.fc3 = nn.Linear(84, 10)
    def forward(self, x):
        # 2x2 Max pooling
        x = F.max_pool2d(F.relu(self.conv1(x)), (2, 2))
        # 如果是方阵,则可以只使用一个数字进行定义
        x = F.max_pool2d(F.relu(self.conv2(x)), 2)
        x = x.view(-1, self.num_flat_features(x))
        x = F.relu(self.fc1(x))
        x = F.relu(self.fc2(x))
        x = self.fc3(x)
        return x
    def num_flat_features(self, x):
        size = x.size()[1:]  # 除去批处理维度的其他所有维度
        num_features = 1
        for s in size:
            num_features *= s
        return num_features
net = Net()
print(net)
params = list(net.parameters())
print(len(params))
print(params[0].size())  # conv1's .weight
input = torch.randn(1, 1, 32, 32)
out = net(input)
print(out)
```

文章：

[http://c.biancheng.net/view/2380.html](http://c.biancheng.net/view/2380.html)

```python
class CLanguage:
    # 定义__call__方法
    def __call__(self,name,add):
        print("调用__call__()方法",name,add)
clangs = CLanguage()
clangs("C语言中文网","http://c.biancheng.net")
```

> Python 中，凡是可以将 () 直接应用到自身并执行，都称为可调用对象。可调用对象包括自定义的函数、Python 内置函数以及本节所讲的类实例对象。


文章：

[https://blog.csdn.net/Yaokai_AssultMaster/article/details/70256621](https://blog.csdn.net/Yaokai_AssultMaster/article/details/70256621)

Python __call__()方法 __init__()方法

# Pandas DataFrame to List of Dictionaries:





[https://stackoverflow.com/questions/29815129/pandas-dataframe-to-list-of-dictionaries/29816143#29816143](https://stackoverflow.com/questions/29815129/pandas-dataframe-to-list-of-dictionaries/29816143#29816143)

![在这里插入图片描述](/static/img/images/00849.png)

```python
df.to_dict('records')
```

# Convert list of dictionaries to a pandas DataFrame:

[https://stackoverflow.com/questions/20638006/convert-list-of-dictionaries-to-a-pandas-dataframe](https://stackoverflow.com/questions/20638006/convert-list-of-dictionaries-to-a-pandas-dataframe)

![在这里插入图片描述](/static/img/images/00850.png)

![在这里插入图片描述](/static/img/images/00851.png)


[https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.read_sql.html#pandas.read_sql](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.read_sql.html#pandas.read_sql)

[https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.read_sql_table.html#pandas.read_sql_table](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.read_sql_table.html#pandas.read_sql_table)

List of Dictionaries vs Pandas DataFrame 字典列表 vs pandas dataframe

[https://www.runoob.com/python/att-time-strftime.html](https://www.runoob.com/python/att-time-strftime.html)





把datetime对象变成各式各样的字符串~~~~~~~
```python
from datetime import datetime
time = datetime.now()
print(time)
print(time.replace(minute=0, second=0, microsecond=0))
print(time.strftime("%Y-%m-%d nihao %H:%M:%S"))
print(time.strftime("%j"))  # 今天是今年的第几天 001到366
print(time.strftime("%w"))  # 今天是星期几 星期日是第0天 0到6
time1 = datetime(2020, 1, 1)
print(time1.strftime("%j"))  # 今天是今年的第几天 001到366 
```

2020-12-07 14:25:57.538141

2020-12-07 14:00:00

2020-12-07 nihao 14:25:57

342

1

001

把字符串提取解析出datetime对象~~~~~

[https://www.runoob.com/python/att-time-strptime.html](https://www.runoob.com/python/att-time-strptime.html)
```python
import datetime
t=datetime.datetime.strptime('2013-12-30T13:00+08:00', "%Y-%m-%dT%H:%M+08:00")
print(t)
```

python datetime 时间处理

一般的字典





![在这里插入图片描述](/static/img/images/00965.png)


构造：
```python
from collections import defaultdict
dict1 = defaultdict(int)
dict2 = defaultdict(set)
dict3 = defaultdict(str)
dict4 = defaultdict(list)
```

defaultdict接受一个函数作为参数。如果字典里没有找到key，用这个函数构造一个对象返回。

题目：

[https://www.nowcoder.com/practice/03ba8aeeef73400ca7a37a5f3370fe68?tpId=37&tags=&title=&diffculty=0&judgeStatus=0&rp=1](https://www.nowcoder.com/practice/03ba8aeeef73400ca7a37a5f3370fe68?tpId=37&tags=&title=&diffculty=0&judgeStatus=0&rp=1)

python：

```python
from collections import defaultdict
while True:
    try:
        zd=defaultdict(list)
        arr = input().split()
        words = arr[1 :  1+int(arr[0])]
        lookup = arr[-2]
        k = int(arr[-1])
        bro=[]
        #构造字典
        for i in words:
            zd[ "".join(sorted(i))].append(i)
        if "".join(sorted(lookup)) in zd.keys():  #在字典里有
            for i in zd["".join(sorted(lookup))]: #所有相似单词
                if lookup!=i:
                    bro.append(i)#相似不相同的才是兄弟单词
        print(len(bro))
        if bro and k-1<len(bro):
            print(sorted(bro)[k-1])#排序所有兄弟单词 找到第k个
    except:
        break
```

传入

```python
5 abc acb ddd fgh hgf abc 1
```

即zd里用abc acb ddd fgh hgf构造

```python
defaultdict(<class 'list'>, 
{
'abc': ['abc', 'acb'], 
'ddd': ['ddd'], 
'fgh': ['fgh', 'hgf']
})
```

python一个defaultdict的典型用法

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