Metadata-Version: 2.1
Name: zyf
Version: 0.7
Summary: 常用函数工具包
Home-page: UNKNOWN
Author: zhangyafei
Author-email: zhangyafeii@foxmail.com
License: UNKNOWN
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Requires-Dist: prettytable
Requires-Dist: pandas

## 安装

> pip install zyf
>
> 或者
>
> pip install zyf -i https://pypi.python.org/simple

## 使用

### 函数计时

#### 示例1：timeit

```python
from zyf.timer import timeit

@timeit
def sleep(seconds: int):
    time.sleep(seconds)


sleep()
```

运行

```
>> sleep(1)
Function sleep -> takes 1.001 seconds
```

#### 示例2：Timeit

```python
from zyf.timer import timeit, Timeit


@Timeit(prefix='跑步')
def run():
    time.sleep(3)


run()
```

运行

```
跑步 -> takes 3.000 seconds
```

#### 示例3：repeat_timeit

```python
from zyf.timer import repeat_timeit

@repeat_timeit(number=5)
def list_insert_time_test():
    l = []
    for i in range(10000):
        l.insert(0, i)


@repeat_timeit(repeat=3, number=5)
def list_append_time_test():
    l = []
    for i in range(1000000):
        l.append(i)
    return l


@repeat_timeit(number=5, print_detail=True)
def list_gen_time_test():
    l = [i for i in range(1000000)]
    return l


@repeat_timeit(repeat=3, number=5, print_detail=True)
def list_extend_time_test():
    l = []
    for i in range(1000000):
        l.extend([i])


@repeat_timeit(repeat=3, number=5, print_detail=True, print_table=True)
def list_range_time_test():
    l = list(range(1000000))
```

运行

```python
>> list_insert_time_test()
Function list_insert_time_test -> 5 function calls: average takes 0.097 seconds

>> list_append_time_test()
Function list_append_time_test -> 3 trials with 5 function calls per trial: average trial 3.269 seconds. average function call 0.654 seconds

>> list_gen_time_test()
Time Spend of 5 function calls:
	Function -> list_gen_time_test: total 1.550 seconds, average 0.310 seconds
Average: 0.310 seconds

>> list_extend_time_test()
Time Spend of 3 trials with 5 function calls per trial:
	Function -> list_extend_time_test: 
		best: 3.289 seconds, worst: 3.626 seconds, average: 3.442 seconds
Average trial: 3.442 seconds. Average function call: 0.688 seconds

>> list_range_time_test()
Time Spend of 3 trials with 5 function calls per trial:
+----------------------+---------------+---------------+---------------+-----------------------+
|       Function       |   Best trial  |  Worst trial  | Average trial | Average function call |
+----------------------+---------------+---------------+---------------+-----------------------+
| list_range_time_test | 0.640 seconds | 0.714 seconds | 0.677 seconds |     0.135 seconds     |
+----------------------+---------------+---------------+---------------+-----------------------+
```

#### 示例4：构建列表效率对比

```python
from zyf.timer import repeat_timeit


@repeat_timeit(number=3)
def list_insert_time_test():
    l = []
    for i in range(100000):
        l.insert(0, i)

@repeat_timeit(number=5)
def list_extend_time_test():
    l = []
    for i in range(100000):
        l.extend([i])

@repeat_timeit(number=5)
def list_append_time_test():
    l = []
    for i in range(100000):
        l.append(i)
    return l


@repeat_timeit(number=5)
def list_gen_time_test():
    l = [i for i in range(100000)]
    return l


@repeat_timeit(number=5)
def list_range_time_test():
    l = list(range(100000))


if __name__ == '__main__':
    list_range_time_test()
    list_gen_time_test()
    list_append_time_test()
    list_extend_time_test()
    list_insert_time_test()
```

运行结果

```bash
Function list_range_time_test -> 5 function calls: average takes 0.012 seconds
Function list_gen_time_test -> 5 function calls: average takes 0.017 seconds
Function list_append_time_test -> 5 function calls: average takes 0.038 seconds
Function list_extend_time_test -> 5 function calls: average takes 0.067 seconds
Function list_insert_time_test -> 3 function calls: average takes 13.747 seconds
```

### UserAgent

#### 示例

```python
from zyf.user_agent import UserAgent

ua = UserAgent()

print(ua.random)
print(ua.chrome)
print(ua.firefox)
print(ua.opera)
print(ua.uc)
print(ua.mobile)
```

输出

```bash
Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1061.1 Safari/536.3
Mozilla/5.0 (Windows NT 6.2) AppleWebKit/536.6 (KHTML, like Gecko) Chrome/20.0.1090.0 Safari/536.6
Mozilla/5.0 (X11; U; Linux x86_64; zh-CN; rv:1.9.2.10) Gecko/20100922 Ubuntu/10.10 (maverick) Firefox/3.6.10
Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1; en) Opera 9.50
Openwave/ UCWEB7.0.2.37/28/999
Mozilla/5.0 (iPad; U; CPU OS 4_3_3 like Mac OS X; en-us) AppleWebKit/533.17.9 (KHTML, like Gecko) Version/5.0.2 Mobile/8J2 Safari/6533.18.5
```

### 文件操作

- 扫描指定文件夹内所有文件，输出文件路径

```python
from zyf.file import scan_directory_contents


for file in scan_directory_contents('D:/python/data'):
    print(file)

# 可以指定后缀
for file in scan_directory_contents('D:/python/data', suffix='.csv'):
    print(file)
```

- 词频统计

  对`文献.xlsx`中关键词列的进行`词频统计`，可指定单词分隔符，默认为`; ',也可指定输出词频统计列名，默认为freq和word。

```python
from zyf.file import count_word_freq


count_word_freq('文献.xlsx', col_name='关键词', sep='; ', to_col_freq='频数', to_col_word='单词', to_file='文献_关键词_统计.xlsx')
```

### color

#### 示例

```python
from zyf.color import print_color, Foreground

print_color("这是什么颜色", foreground=Foreground.Red)
print_color("这是什么颜色", foreground=Foreground.White)
print_color("这是什么颜色", foreground=Foreground.Green)
print_color("这是什么颜色", foreground=Foreground.Black)
print_color("这是什么颜色", foreground=Foreground.Blue)
print_color("这是什么颜色", foreground=Foreground.Cyan)
print_color("这是什么颜色", foreground=Foreground.Purplish_red)
print_color("这是什么颜色", foreground=Foreground.Yellow)
```





