semvec/pypi-packages huggingface dataset:
bp-btc-com 0.0.5
An api wrapper for btc.com block explorer api
Requires Python: >=3

## bp-btc-com
A python 3 api wrapper for btc.com block explorer.
Forked from [psqnt/btc-com](https://github.com/psqnt/btc-com)

docs: https://github.com/qlbnb/btc-com/blob/master/docs.md

api docs: https://btc.com/api-doc

block explorer: https://btc.com/block


## Install
```
pip install bp-btc-com
```
must be python3 so if not in a python3 virtualenv use
```
pip3 install bp-btc-com
```

## Usage
```python
import datetime

from bp_btc_com.explorer import Explorer
from time import sleep

sleep_time = .5  # don't overstep rate limits
# get latest block
print(Explorer("btc").get_block())
sleep(sleep_time)

print(Explorer("bch").get_block())
sleep(sleep_time)

print(Explorer("bsv").get_block())
```

## Examples
https://github.com/qlbnb/btc-com/blob/master/examples.py

## Common Issues
API changes may break the sdk. Please refer to the official btc.com api documentation and update accordingly.
```
'https://chain.api.btc.com/v3/'
'https://bch-chain.api.btc.com/v3/'
'https://bsv-chain.api.btc.com/v3/'
```
mulang 0.0.14
木兰编程语言重现项目体验

**_注：本项目的开发管理今后将在 [OSChina](https://www.oschina.net/p/mulan-rework) 继续_**

## 前言
没错，这就是那个木兰。

2020 年一月第一时间提出知乎问题[「木兰」编程语言有什么特色？](https://www.zhihu.com/question/366509495/answer/977696328)的正是本人，[这是那段暴风骤雨的亲历记](https://zhuanlan.zhihu.com/p/265091649)。

## 目标

在[悬赏尚未完成](https://zhuanlan.zhihu.com/p/224600854)时，将努力向[目标](https://github.com/MulanRevive/bounty/blob/master/%E5%A4%8D%E7%8E%B0%E6%96%87%E6%A1%A3/README.md)迈进。过程中的技术文章集结在[木兰编程语言专栏](https://zhuanlan.zhihu.com/ulang)并在[开源中国](https://www.oschina.net/p/mulan-rework)同步更新。

木兰源代码转换为 Python 的中间表示（AST）后执行，可实现各种语法设计与周边功能，并可方便地利用 Python 现有生态。

## 运行

需先安装 Python 3.7。通过 `pip install mulang` 安装木兰。

### 交互环境

```
$ 木兰
木兰向您问好
更多信息请说'你好'
> 和 = 0
> for 数 in 1..10 {
>> 和 += 数
>> }
> print(和)
55
```

### 运行木兰源码文件

建议`.ul`后缀
```
$ 木兰 测试/运算/四则运算.ul
4
```

下面[例程](https://gitee.com/MulanRevive/mulan-rework/tree/master/测试/手工测试/草蟒_海龟.ul)调用了[草蟒](https://www.oschina.net/p/grasspy)的中文 API：
```javascript
using * in 海龟

颜色("黄色", "红色")
开始填充()
for 转角 in 0..4 {
  前进(200); 右转(144)
}
结束填充()
主循环()
/* 需安装 Python 库“草蟒”： grasspy-modules */
```

### 参考例程[在此](https://gitee.com/MulanRevive/mulan-rework/tree/master/测试)

其中[测试/实用](https://gitee.com/MulanRevive/mulan-rework/tree/master/测试/实用)为较接近实用的部分。另外[木兰代码编辑器](https://gitee.com/MulanRevive/mulan-rework/tree/master/编辑器)也用木兰代码编写。

## 新手入门

如果无编程经验，请入[此门](https://gitee.com/MulanRevive/mulan-rework/tree/master/文档/用户手册/编程新手/1猜数字.md)。

## 开发环境

使用 Python 3.7。 Mac 和 [Linux](https://gitee.com/MulanRevive/mulan-rework/issues/I1U9O3) 下全部测试通过；windows 下测试[大多数通过](https://gitee.com/MulanRevive/mulan-rework/issues/I1U2HP)。如使用 3.8，语法树测试将失败。

为提高开发维护效率，本项目中尽量使用中文标识符。包括语法规则、Python 代码等等。

依赖 Python 包：
- [rply](https://pypi.org/project/rply/)

### 本地运行

```
$ python -m 木兰
```

### 运行测试

```
$ python 测试/运行所有.py
$ python -m unittest 测试.unittest.交互 测试.unittest.语法树
```
为检验[与原始木兰可执行文件功能一致](https://zhuanlan.zhihu.com/p/230155471)，需先阅读“win32”部分注释并手动修改。

## 已实现功能

随着逐渐缩小[与原版木兰的差距](https://gitee.com/MulanRevive/mulan-rework/issues/I1SEU5)，将补充[语言语法规则](文档/语法说明.md)。用户手册[尚待更新](https://gitee.com/MulanRevive/mulan-rework/issues/I1U36D)。为调试方便，报错等等反馈信息将逐渐中文化。

交互环境功能说明[在此](https://gitee.com/MulanRevive/mulan-rework/tree/master/文档/功能/交互环境.md)。

## IDE 辅助

[VS Code 语法高亮插件](https://marketplace.visualstudio.com/items?itemName=CodeInChinese.ulang)：

![](https://raw.githubusercontent.com/MulanRevive/ide-extension-vscode/master/%E6%88%AA%E5%9B%BE/%E8%B0%83%E7%94%A8python%E5%BA%93.png)

【原型状态】[自带的编辑器](https://gitee.com/MulanRevive/mulan-rework/tree/master/编辑器)：

![](https://gitee.com/MulanRevive/bounty/raw/master/%E8%BF%9B%E5%B1%95%E5%B0%8F%E7%BB%93/%E6%88%AA%E5%9B%BE/2020-06-25_mulan%E6%90%9C%E5%84%BF%E6%AD%8C.png)

## 许可证

GNU GPLv3
py2pyrecruitment2 0.0.5
Predicting selection chances

# Recruitment-Prediction-System

Recruitment is one of the most important task in studentâ€™s & also organizations point of view. If there could be a model such that, it can predict the possibility of student to get recruited or placed in an organization or not, that can save lots of time of HR Managers , staffs & placement commitee.

Complete explanation is given in the blog.

Link to blog: https://rb.gy/mm6ps8
graph-snapshot 0.1.0
A small package for creating snapshots of graphs with networkx
Requires Python: >=3.8

graph_snapshot is a tool to visualize graph algorithms based on networkx (https://networkx.github.io/), pygraphviz (https://pygraphviz.github.io) and dot2tex (https://dot2tex.readthedocs.io/en/latest/#).

Say you have a python script that runs Kruskal's algorithm on a networkx graph and you want to show how the algorithm works in your paper.

The only thing you have to do is to import graph_snapshot, create snapshots of your graph at important moments during the algorithm and you'll get a directory of .tex files containing the tikz code for your graphs that are just waiting for you to include them into your Latex paper.

If you want to give a talk presenting your algorithm, graph_snapshot makes things even easier for you by providing the beamer_slide function that will create one beamer slide with the images of your algorithm as overlays, so that you just need to input this slide in order to be able to 'click through the algorithm' in your talk.