semvec/pypi-packages huggingface dataset:
TradeGate-Beta 0.2.1b22
A Trading Gateway
Requires Python: >=3.6

# Trade Gate
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</div>

An algorithmic trading library to use as a gateway to different exchanges.

## How to install
Use this Github repository by running ```python setup.py install```, or using pip:
```bash
pip install TradeGate
```

## How to use
Use with a config file in JSON format. Your config file should look like this:
```json
{
    "Binance": 
    {
        "exchangeName": "Binance",
        "credentials": 
        {
            "main": 
            {
                "futures": 
                {
                    "key": "API-KEY",
                    "secret": "API-SECRET"
                },
                "spot": 
                {
                    "key": "API-KEY",
                    "secret": "API-SECRET"
                }
            },
            "test": 
            {
                "futures": 
                {
                    "key": "API-KEY",
                    "secret": "API-SECRET"
                },
                "spot": 
                {
                    "key": "API-KEY",
                    "secret": "API-SECRET"
                }
            }
        }
    }
}
```
You should read this config file as JSON and give the desired exchange information to the main class initializer. Use sandbox argument to connect to the testnets of exchanges (if it exists). This is shown below:
```python
from TradeGate import TradeGate
import json

with open('/path/to/config/file.json') as f:
    config = json.load(f)
    
gate = TradeGate(config['Binance'], sandbox=True)

print(gate.getSymbolTickerPrice('BTCUSDT'))
```
## Current Supported Exchanges
- Binance
- ByBit

## Contributing
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change. The best way to contribute right now is to implement as many exchanges as possible. Make sure all test cases are passing.

## License
[MIT](https://choosealicense.com/licenses/mit/)
crypto_currency_price 0.2.1
Top-level package for crypto-currency-price.
Keywords: cryptocurrency price CLI

=====================
crypto-currency-price
=====================


![Image](https://img.shields.io/github/license/rstms/crypto_currency_price)

![Image](https://img.shields.io/pypi/v/crypto_currency_price.svg)


![Image](https://circleci.com/gh/rstms/crypto_currency_price/tree/master.svg?style=shield)

![Image](https://readthedocs.org/projects/crypto-currency-price/badge/?version=latest)

![Image](https://pyup.io/repos/github/rstms/crypto_currency_price/shield.svg)

CLI cryptocurrency price conversion


* Free software: MIT license
* Documentation: https://crypto-currency-price.readthedocs.io.



Credits
-------

This package was created with Cookiecutter and `rstms/cookiecutter-python-cli`, a fork of the `audreyr/cookiecutter-pypackage` project template.

[audreyr/cookiecutter](https://github.com/audreyr/cookiecutter)
[audreyr/cookiecutter-pypackage](https://github.com/audreyr/cookiecutter-pypackage)
[rstms/cookiecutter-python-cli](https://github.com/rstms/cookiecutter-python-cli)
kabbes-database-connections 0.7.0
Provides database-agnostic connection tools
Requires Python: >=3.7

[GitHub Pages](https://jameskabbes.github.io/database_connections)<br>
[PyPI](https://pypi.org/project/kabbes-database-connections)

# database_connections
Provides database-agnostic connection tools

<br> 

# Installation
`pip install kabbes_database_connections`

<br>

# Usage
For more in-depth documentation, read the information provided on the Pages. Or better yet, read the source code.

```python
import database_connections as dbconn
from database_connections import sql_support_functions as ssf
```

```python
sqlite_conn = sff.get_DatabaseConnection( connection_module = 'sqlite', db_path = 'test.db' )
```

```python
df = sqlite_conn.query( 'Select * from table_name' )
```

```python
sqlite_conn.write( df, 'new_table' )
```

<br>

# Author
James Kabbes
seu-test-wangpeng 2022.6.9.0
东南大学软件测试课件（汪鹏）
Requires Python: >=3.6

# 东南大学软件测试课件（汪鹏）

## 下载

### Docker

```
docker pull apachecn0/seu-test-wangpeng
docker run -tid -p <port>:80 apachecn0/seu-test-wangpeng
# 访问 http://localhost:{port} 查看文档
```

### PYPI

```
pip install seu-test-wangpeng
seu-test-wangpeng <port>
# 访问 http://localhost:{port} 查看文档
```

### NPM

```
npm install -g seu-test-wangpeng
seu-test-wangpeng <port>
# 访问 http://localhost:{port} 查看文档
```
seu-swe-libixin 2022.6.9.0
东南大学软件工程导论课件（李必信）
Requires Python: >=3.6

# 东南大学软件工程导论课件（李必信）

## 下载

### Docker

```
docker pull apachecn0/seu-swe-libixin
docker run -tid -p <port>:80 apachecn0/seu-swe-libixin
# 访问 http://localhost:{port} 查看文档
```

### PYPI

```
pip install seu-swe-libixin
seu-swe-libixin <port>
# 访问 http://localhost:{port} 查看文档
```

### NPM

```
npm install -g seu-swe-libixin
seu-swe-libixin <port>
# 访问 http://localhost:{port} 查看文档
```
seu-proj-mgt 2022.6.9.0
东南大学项目管理课件
Requires Python: >=3.6

# 东南大学项目管理课件

## 下载

### Docker

```
docker pull apachecn0/seu-proj-mgt
docker run -tid -p <port>:80 apachecn0/seu-proj-mgt
# 访问 http://localhost:{port} 查看文档
```

### PYPI

```
pip install seu-proj-mgt
seu-proj-mgt <port>
# 访问 http://localhost:{port} 查看文档
```

### NPM

```
npm install -g seu-proj-mgt
seu-proj-mgt <port>
# 访问 http://localhost:{port} 查看文档
```
seu-os-liwei 2022.6.9.0
东南大学操作系统课件（李伟）
Requires Python: >=3.6

# 东南大学操作系统课件（李伟）

## 下载

### Docker

```
docker pull apachecn0/seu-os-liwei
docker run -tid -p <port>:80 apachecn0/seu-os-liwei
# 访问 http://localhost:{port} 查看文档
```

### PYPI

```
pip install seu-os-liwei
seu-os-liwei <port>
# 访问 http://localhost:{port} 查看文档
```

### NPM

```
npm install -g seu-os-liwei
seu-os-liwei <port>
# 访问 http://localhost:{port} 查看文档
```
kabbes-ml-pipeline 0.6.0
A centralized pattern for creating Machine Learning pipelines
Requires Python: >=3.7

[GitHub Pages](https://jameskabbes.github.io/ml_pipeline)<br>
[PyPI](https://pypi.org/project/kabbes-ml-pipeline)

# ml_pipeline
A centralized pattern for creating Machine Learning pipelines

<br>

# Installation 
`pip install kabbes_ml_pipeline`

<br>

# Description
Contains a host of tools for standardizing the format of machine learning pipelines. Provides methods for querying databases, cleaning data, preprocessing data, model operations, exporting results, and more. Each machine learning project is a "child" of this template, with the ability to overwrite any of the default class attributes/methods.

# Code Overview
Read this high-level overview is necessary to understand how the package operates. <br>

**Code Hierarchy** <br>
Models &rarr; Model &rarr; Input_Files &rarr; Input_File &rarr; Features &rarr; Feature <br>

Each point in the hierarchy has certain methods and attributes associated with it. These methods give you the functionality for operating the pipeline.

# Usage
For more in-depth documentation, read the information provided on the Pages. Or better yet, read the source code.

## Initializing a Repo for ml_pipeline

1. Navigate to a directory in command prompt

```
cd C:/Path/to/Repo
```

2. Call the package's main script

```
python -m ml_pipeline
```

## Navigating the Menu

1. Run `python main_XYZ.py` This opens the Models options screen, along with the options for the "Models" class instance.
2. To navigate one level down to a Model, select the option "Open Model"
3. Select a Model from the list.
4. Now in the Model options screen, press enter to navigate back up to Models.
5. You can navigate from Models->Model->Input_Files->Input_File->Features->Feature and all the way back up.
6. Option 1 shows "Open XXXXX" to navigate to the next level down in the tree. 
7. Press enter to exit back up to the previous level. 

## Query new Raw Data

1. `python main_XYZ.py`
2. At the Models options screen, select "Open Model".
3. Select any Model from the list (this selection does not matter)
4. In the Model options screen, select "Open Input Files".
5. Select the first option.
6. In the Input Files options screen, select "Open Input File"
7. Select the Input File for which you would like to query new data.
8. In the Input File options screen, select "Query from Source Database"

## Move Query Staged data to Raw Data

1. Follow steps (1-7) from "Query new Raw Data" to get to the Input File of interest.
2. In the Input File options screen, select "Move from Query Staging"

## Clean a Raw Dataset

1. Follow steps (1-7) from "Query new Raw Data" to get to the Input File of interest.
2. In the Input File options screen, select "Clean Raw Dataset"

## Running one Model

1. `python main_XYZ.py`
2. At the Models options screen, select the option for "Open Model"
3. Select the Model you would like to run
4. In the Model options screen, select the option for "Run Pipeline"

## Running all Models

1. `python main_XYZ.py`
2. At the Models options screen, select the option for "Run Models"


<br>

# Author(s)
James Kabbes
seu-net-chengguang 2022.6.9.0
东南大学计算机网络课件（程光）
Requires Python: >=3.6

# 东南大学计算机网络课件（程光）

## 下载

### Docker

```
docker pull apachecn0/seu-net-chengguang
docker run -tid -p <port>:80 apachecn0/seu-net-chengguang
# 访问 http://localhost:{port} 查看文档
```

### PYPI

```
pip install seu-net-chengguang
seu-net-chengguang <port>
# 访问 http://localhost:{port} 查看文档
```

### NPM

```
npm install -g seu-net-chengguang
seu-net-chengguang <port>
# 访问 http://localhost:{port} 查看文档
```
seu-job-intro 2022.6.9.0
东南大学就业导论课件
Requires Python: >=3.6

# 东南大学就业导论课件

## 下载

### Docker

```
docker pull apachecn0/seu-job-intro
docker run -tid -p <port>:80 apachecn0/seu-job-intro
# 访问 http://localhost:{port} 查看文档
```

### PYPI

```
pip install seu-job-intro
seu-job-intro <port>
# 访问 http://localhost:{port} 查看文档
```

### NPM

```
npm install -g seu-job-intro
seu-job-intro <port>
# 访问 http://localhost:{port} 查看文档
```
seu-io-yangquansheng 2022.6.9.0
东南大学计算机IO系统课件（杨全胜）
Requires Python: >=3.6

# 东南大学计算机IO系统课件（杨全胜）

## 下载

### Docker

```
docker pull apachecn0/seu-io-yangquansheng
docker run -tid -p <port>:80 apachecn0/seu-io-yangquansheng
# 访问 http://localhost:{port} 查看文档
```

### PYPI

```
pip install seu-io-yangquansheng
seu-io-yangquansheng <port>
# 访问 http://localhost:{port} 查看文档
```

### NPM

```
npm install -g seu-io-yangquansheng
seu-io-yangquansheng <port>
# 访问 http://localhost:{port} 查看文档
```
seu-db-niweiwei 2022.6.9.0
东南大学数据库课件（倪巍伟）
Requires Python: >=3.6

# 东南大学数据库课件（倪巍伟）

## 下载

### Docker

```
docker pull apachecn0/seu-db-niweiwei
docker run -tid -p <port>:80 apachecn0/seu-db-niweiwei
# 访问 http://localhost:{port} 查看文档
```

### PYPI

```
pip install seu-db-niweiwei
seu-db-niweiwei <port>
# 访问 http://localhost:{port} 查看文档
```

### NPM

```
npm install -g seu-db-niweiwei
seu-db-niweiwei <port>
# 访问 http://localhost:{port} 查看文档
```