semvec/pypi-packages huggingface dataset:
pytest-aws-fixtures 3.1.3
A series of fixtures to use in integration tests involving actual AWS services.
Requires Python: <4.0,>=3.9

# Pytest AWS fixtures

This is a collection of fixtures we've been using to perform integration tests using
real AWS services.

Usage of any of these fixture requires that the credentials be configured for boto3 via
one of the following documented methods that does not involve setting the credentials on
the client or session objects:

https://boto3.amazonaws.com/v1/documentation/api/latest/guide/credentials.html

The fixtures themselves are heavily documented so please view their docstrings for more
information on their usage.
PaCS-Q 1.2.6
PaCS-Q is a Python toolkit designed to assist with Parallel Cascade Selection simulations (PaCS) for studying protein structural transitions in MD and QM/MM MD level.
Requires Python: >=3.9

This is README file
Welcome to PaCS-Q v1.2.6 by L.Duan 2025.11.11
github: https://github.com/nyelidl/PaCS-Q
  
**PaCS-Q** is a Python toolkit designed to assist with
Parallel Cascade Selection simulations (PaCS) for studying
protein structural transitions in MD and QM/MM MD level.
  

Please cite paper:
Lian Duan, Kowit Hengphasatporn, Ryuhei Harada, Yasuteru Shigeta. JCTC https://doi.org/10.1021/acs.jctc.5c00169
Lian Duan, Kowit Hengphasatporn, Yasuteru Shigeta. JCIM https://doi.org/10.1021/acs.jcim.5c00936

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**##Prerequisites**
#Before installing and running PaCS-Q, ensure you have the following:

- **AMBER** (version 22 or later) compiled with **MPI** support
- **Miniconda** (for environment management)
- Python packages:
  - [MDAnalysis](https://www.mdanalysis.org/)

**##Installation**
#1. Clone or Download the Toolkit
#Using the following command:

```bash
wget https://github.com/DLCCS/PaCS-Q/archive/refs/heads/main.zip
unzip main.zip
mv PaCS-Q-main PaCS-Q

```Or clone it using Git:

git clone https://github.com/DLCCS/PaCS-Q.git


#2. Export the Path in ~/.bashrc
export PATH="/path/to/PaCS-Q:$PATH"
export PATH="/path/to/PaCS-Q/pacsq_toolkit:$PATH"

source ~/.bashrc


#3.Create and Activate Conda Environment
conda create -n pacs-q
conda init
conda activate pacs-q


#4. Install Required Python Packages
pip install MDAnalysis biopython


#5. Input Files
- For LB-PaCS-MD (Distance-based PaCS-Q)
	Topology file from (.top) tLEaP and the coordinate file (.rst or .crd) obtained from after heating up step.
	You can adjust any MD parameter in "md.in".

- For QM/MM MD (RMSD-based PaCS-Q)
	 In this simulation we need to prepare initial and reference structures, as follows.
	 Topology file from tLEaP (.top), the coordinate file (.rst or .crd) obtained from after heating up step, and reference structure in PDB file format (.pdb).
         You can adjust any MD parameter in "qmmm.in".


#6. Extend and Generate Trajectory
- To extend the simulation, please use "--rerun" in the command line.
- To generate the trajectory and the lastframe in pdb file, please use "cpp.sh" and "pdb_last.sh".
- To clean all of MD directory, please use "clean.sh".


#7. MD Analysis
- Generate CV and 2D-PES by "pacsana_dis_collection.py"
- PCA analysis by "pacsana_procupine.py"
- Create QM input from PaCS-Q Trajectory "pacsana_QM_input.py"


**##For More Detail of PaCS-Q Usage:**
PaCS-Q -h
iflow-mcp_nuanced-mcp 0.1.1
MCP server expose nuanced.dev functionality
Requires Python: >=3.13

# Nuanced MCP Server

A [Model Context Protocol (MCP)](https://modelcontextprotocol.io) server that provides call graph analysis capabilities to LLMs through the [nuanced](https://github.com/nuanced-dev/nuanced) library.

## Overview

This MCP server enables LLMs to understand code structure by accessing function call graphs through standardized tools and resources. It allows AI assistants to:

- Initialize call graphs for Python repos
- Explore function call relationships
- Analyze dependencies between functions
- Provide more contextually aware code assistance

## API

### Tools

- **initialize_graph**

  - Initialize a code graph for the given repository path
  - Input: `repo_path` (string)

- **switch_repository**

  - Switch to a different initialized repository
  - Input: `repo_path` (string)

- **list_repositories**

  - List all initialized repositories
  - No inputs required

- **get_function_call_graph**

  - Get the call graph for a specific function
  - Inputs:
    - `file_path` (string)
    - `function_name` (string)
    - `repo_path` (string, optional) - uses active repository if not specified

- **analyze_dependencies**

  - Find all module or file dependencies in the codebase
  - Inputs (at least one required):
    - `file_path` (string, optional)
    - `module_name` (string, optional)

- **analyze_change_impact**
  - Analyze the impact of changing a specific function
  - Inputs:
    - `file_path` (string)
    - `function_name` (string)

### Resources

- **graph://summary**

  - Get a summary of the currently loaded code graph
  - No parameters required

- **graph://repo/{repo_path}/summary**

  - Get a summary of a specific repository's code graph
  - Parameters:
    - `repo_path` (string) - Path to the repository

- **graph://function/{file_path}/{function_name}**
  - Get detailed information about a specific function
  - Parameters:
    - `file_path` (string) - Path to the file containing the function
    - `function_name` (string) - Name of the function to analyze

### Prompts

- **analyze_function**

  - Create a prompt to analyze a function with its call graph
  - Parameters:
    - `file_path` (string) - Path to the file containing the function
    - `function_name` (string) - Name of the function to analyze

- **impact_analysis**

  - Create a prompt to analyze the impact of changing a function
  - Parameters:
    - `file_path` (string) - Path to the file containing the function
    - `function_name` (string) - Name of the function to analyze

- **analyze_dependencies_prompt**
  - Create a prompt to analyze dependencies of a file or module
  - Parameters (at least one required):
    - `file_path` (string, optional) - Path to the file to analyze
    - `module_name` (string, optional) - Name of the module to analyze

## Usage with Claude Desktop

Add this to your `claude_desktop_config.json`

### UV

```json
{
  "mcpServers": {
    "nuanced": {
      "command": "uv",
      "args": [
        "--directory",
        "/path/to/nuanced-mcp",
        "run",
        "nuanced_mcp_server.py"
      ]
    }
  }
}
```