semvec/pypi-packages huggingface dataset:
nlp-fenci 1.2.3
分词工具

## 分词工具
## python版(有node版)
### 安装
`pip install nlp_fenci`

### command-line
#### 搜狗分词
```bash
$ sougou_fenci 武汉市长江大桥
武汉市 n
长江 n
大桥 n
```
#### 百度分词
```bash
$ baidu_fenci 武汉市长江大桥
武汉        地名
长江大桥        地名
```

### sougou 分词 code
``` python
import sougou_fenci
resp = sougoou_fenci.sougou("武汉市长江大桥")
for result_item in resp.result:
    print(row_format.format(result_item[0], result_item[1]))

# 结 果
# 武汉市         n
# 长江         n
# 大桥         n
```

### baidu 分词 code
``` python
import sougou_fenci
resp = sougoou_fenci.baidu("武汉市长江大桥")
for result_item in resp.result:
    print(row_format.format(result_item[0], result_item[1]))

# 结 果
# 武汉市         地名
# 长江大桥         地名
```
sougou-fenci 1.1.9
搜狗分词工具

## 分词工具
## python版(有node版)
### 安装
`pip install sougou_fenci`

### command-line
#### 搜狗分词
```bash
$ sougou_fenci 武汉市长江大桥
武汉市 n
长江 n
大桥 n
```
#### 百度分词
```bash
$ baidu_fenci 武汉市长江大桥
武汉长江大桥        地名
```

### sougou 分词 code
``` python
import sougou_fenci
resp = sougoou_fenci.sougou("武汉市长江大桥")
for result_item in resp.result:
    print(row_format.format(result_item[0], result_item[1]))

# 结 果
# 武汉市         n
# 长江         n
# 大桥         n
```

### baidu 分词 code
``` python
import sougou_fenci
resp = sougoou_fenci.baidu("武汉市长江大桥")
for result_item in resp.result:
    print(row_format.format(result_item[0], result_item[1]))

# 结 果
# 武汉市长江大桥         地名
```
qb-consul 1.0.2
consul服务注册与获取

## Introduce to qb-consul

version: 1.0.2

how to install:

pip install qb-consul


If you want to use it locally:
```
from qb_consul import Consul


host = "127.0.0.1"  # consul服务器的ip
port = 8500  # consul服务器对外的端口
consul_client = Consul(host, port)

# register service
name = "qbzz-server"
host1 = "127.0.0.1"
port1 = 8001
service_id = "qbzz-server-%s" % port1
consul_client.register_service(name, service_id, host1, port1)

# get service
message = consul_client.get_service('qbzz-server')
host = message[0]
port = message[1]



```
instats 2.0.0
Package for processing statistics from Instagram profiles
Requires Python: >=3

# Instats

A Python package for processing statistics from Instagram profiles

### Installation
install instats from command line using:
```commandline
pip3 install instats
```
### Overview

Instats is a Python package for getting and working with statistics from Instagram Profiles.
There exists modules for dealing with data about when posts were made, engagement metrics, and visual cohesiveness
of a profiles posts. It relies heavily on the [instaloader package](https://instaloader.github.io/index.html) for 
logging into Instagram and getting profile and post data. 

#### Basic Usage

From instats import instatsprofile and create and InstatsProfile object:
```python
from instats import instatsprofile

p = instatsprofile.InstatsProfile(username='some public profile')
```

Parameters for the InstatsProfile constructor:
 - *username*: username of an Instagram profile (string)
 - *password*: password of an Instagram profile (string), required for private accounts
 - *ToP_n_most_recent*: how many of a profiles most recent posts to use for time of post data (int)
 - *feedmatch*: indicate whether instance will need to process images beforehand (bool)
 - *FM_n_most_recent*: how many most recent images to consider for feedmatch (int)
 - *pixel_count_per_image*: how many pixels to use per image when processing feedmatch data (int)
 - *Eng_n_most_recent*: how many most recent posts to consider for engagement metrics (int)

Once an InstatsProfile is instantiated, all relevant modules and methods can be called and used.

### Limitations

Private accounts need a password to be accessed and are considerably slower to get post data from.
Furthermore, getting too many recent posts to process may cause instaloader to throw a too many requests error,
so processing several hundreds of posts from a large account is clumsy and slow.

### Possible Features to Add in the Future

1. Get a profile's most engaged followers by ranking who likes/comments on the most posts in a profile.
(this results in a too many requests error for accounts with thousands of likes per post)
2. Module for processing data on the locations of posts made.
3. Module for processing hashtag statistics and their effectiveness on engagement.
sidanwebframework 1.0.2
sidanwebframework

#sidanwebframework

##this framework can be used to develop python based web applications

```
from sidanwebframework import Server, Response, route, Render
```

```
@route('/index')
def index(request):
    return Response('Hello world')
```

```
@route('/home')
def home(request):
    return Render('home.html')
```

```
app = Server()
app.serve()
```