semvec/pypi-packages huggingface dataset:
iflow-mcp_mcp-server-perplexity 0.1.4
MCP Server for the Perplexity API.
Requires Python: >=3.10

# Perplexity MCP Server

[![smithery badge](https://smithery.ai/badge/mcp-server-perplexity)](https://smithery.ai/server/mcp-server-perplexity)

MCP Server for the Perplexity API.

> :warning: **Limitations:**
> - The Claude Desktop client may timeout if Perplexity processing takes too long
> - This issue might be resolved if Claude Desktop implements support for long running operations and progress reporting in the future
> - Implementation updates to handle these features will be made if they become available

<a href="https://glama.ai/mcp/servers/hchfq9bydq"><img width="380" height="200" src="https://glama.ai/mcp/servers/hchfq9bydq/badge" alt="Perplexity Server MCP server" /></a>

## Components

### Tools

- **ask_perplexity**: Request chat completion with citations from Perplexity  

## Quickstart

### Install

#### Claude Desktop

- On macOS: `~/Library/Application\ Support/Claude/claude_desktop_config.json`  
- On Windows: `%APPDATA%/Claude/claude_desktop_config.json`

```
"mcpServers": {
  "Perplexity": {
    "command": "uvx",
    "args": [
      "mcp-server-perplexity"
    ],
    "env": {
      "PERPLEXITY_API_KEY": "your-perplexity-api-key"
    }
  }
}
```
cybotrade-datasource 0.1.9
Python SDK to interact with Cybotrade Datasource API.
Requires Python: >=3.12

## Cybotrade Datasource

Cybotrade Datsource is a financial data broker for the crypto market. This library provides a simple-to-use Python SDK to interact with the REST and Websocket API.

For more information regarding the API, refer to the [docs](https://docs.datasource.cybotrade.rs/).

### Installation

```sh
pip install cybotrade-datasource
```

### Usage

To fetch historical data for a particular time range:

```python
import os
import pandas as pd
import asyncio
import cybotrade_datasource
from datetime import datetime, timezone


API_KEY = os.environ["API_KEY"]


async def main():
    data = await cybotrade_datasource.query_paginated(
        api_key=API_KEY, 
        topic='cryptoquant|btc/inter-entity-flows/miner-to-miner?from_miner=f2pool&to_miner=all_miner&window=hour', 
        start_time=datetime(year=2024, month=1, day=1, tzinfo=timezone.utc),
        end_time=datetime(year=2025, month=1, day=1, tzinfo=timezone.utc)
    )
    df = pd.DataFrame(data)
    print(df)
    

asyncio.run(main())
```

To fetch the latest **10000** data points:

```python
import os
import pandas as pd
import asyncio
import cybotrade_datasource
from datetime import datetime, timezone


API_KEY = os.environ["API_KEY"]


async def main():
    data = await cybotrade_datasource.query_paginated(
        api_key=API_KEY, 
        topic='cryptoquant|btc/inter-entity-flows/miner-to-miner?from_miner=f2pool&to_miner=all_miner&window=hour', 
        limit=10000
    )
    df = pd.DataFrame(data)
    print(df)
    

asyncio.run(main())
```

To subscribe and listen to live updates:

```python
import os
import pandas as pd
import asyncio
import cybotrade_datasource
from datetime import datetime, timezone


API_KEY = os.environ["API_KEY"]


async def main():
    stream = await cybotrade_datasource.stream(
        api_key=API_KEY,
        topics=[
            'cryptoquant|btc/inter-entity-flows/miner-to-miner?from_miner=f2pool&to_miner=all_miner&window=hour',
            'cryptoquant|btc/market-data/liquidations?exchange=deribit&window=min',
        ],
    )
    async for msg in stream:
        print(msg)
    

asyncio.run(main())
```
shipper-shippy 2.43.0
Client-side tool to interface with shipper
Requires Python: >=3.10

# shippy

[
![PyPI](https://img.shields.io/pypi/v/shipper-shippy)
![PyPI - Downloads](https://img.shields.io/pypi/dm/shipper-shippy)
](https://pypi.org/project/shipper-shippy/)

Client-side tool to interface with shipper

# Usage

Get shippy from PyPI:

```shell
pipx install shipper-shippy             # pipx, recommended
pip3 install --upgrade shipper-shippy   # or pip3
```

Go to the directory with build files, and run:

```shell
shippy
```

Run `shippy -h` to see commandline arguments' usage instructions.

# Configuration

shippy stores its configuration in `~/.shippy.ini`. An example configuration file is shown below:

```ini
[shippy]
server = https://example.com
token = a1b2c3d4e5...
DisableBuildOnUpload = false
UploadWithoutPrompt = false
debug = false
```

Configuration options explained:

### `server`

Server URL

### `token`

Token used to sign in to the server

### `DisableBuildOnUpload`

Immediately disables the build after uploading it. Useful if you are uploading from Jenkins or uploading potentially
unstable builds. Do NOT use under normal circumstances!

### `UploadWithoutPrompt`

shippy will not prompt you before uploading builds, and will automatically upload all builds found in the current
directory. Use with caution. Same as the `-y`/`--yes` flag shown above.

### `debug`

Enable debug mode for all invocations. When set to true, the `-d`/`--debug` flag will have no effect, and all
invocations of shippy will run with debug mode enabled.


# Status

shippy returns exit codes based on the results.

`1` - Ctrl-C exit

`2` - one or more builds failed to upload and/or set disabled status
HiveClient 1.0.4
Hive数据库连接工具类，支持查询执行与数据处理
Requires Python: >=3.7

# 说明
这是一个链接hive数据库的程序

## 安装
使用pip安装：
bash
pip install HiveClient
 
### 联系我们
如果你有任何问题或建议，请联系我649898871@qq.com
ibm-metrics-plugin-artifacts 3.0.6.24
IBM Watson OpenScale Artifacts library
Requires Python: >=3.10

******************************************
 ## Welcome to `ibm_metrics_plugin_artifacts`
******************************************

``ibm_metrics_plugin_artifacts`` is a python API for storing artifacts needed by ibm_metrics_plugin for computing metrics.

Note: IBM is not responsible for any existing vulnerabilities within the third-party dependencies that are required to install the ibm-metrics-plugin-artifacts python package.

### License
  This library is delivered under the [International License Agreement for Non-Warranted Programs](https://www14.software.ibm.com/cgi-bin/weblap/lap.pl?li_formnum=L-AMCU-CCTQDV).