semvec/pypi-packages huggingface dataset:
Gerdoo 1.2.0
This unofficial library is built for using the Gerdoo search engine. You can use this tool to search the web, images, videos, news, and more. 🐍✨
Requires Python: >=3.5

![موتور جستجوی گردو](https://gerdoo.me/static/commons/img/logo.c179f12989b4.svg)



# Gerdoo

این کتابخانه مخصوص استفاده برای موتور جستجوی **گردو** طراحی شده است


برای ساخت یک یک شیء از سرچ کننده گردو این کار را انجام دهید :
```python

import Gerdoo from Gerdoo

gerdoo = Gerdoo(
    "Query",#الزامی
    Proxies={},#الزامی نمی باشد
    Base_Url="url",#الزامی نمی باشد
    User_Agent="XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"#الزامی نمی باشد
)
```

## امکانات
- جستجوی کلی
- جستجوی تصویر
- جستجوی ویدیو
- جستجوی اخبار
- دریافت پیشنهادات برای جستجو

## Enums
```python
from Gerdoo.enums import (
    Search,
    SearchImage,
    SearchVideo,
    SearchNews
)
```
مثال استفاده از اینامز ها :
```python
from Gerdoo import Gerdoo
from Gerdoo.enums import Search


search = Gerdoo("Query")

for Item in search.search(
        filter_date=Search.filter_date.DAY
    ):
    for Key , Value in Item.items():
        print(f"{Key} : {Value}")
    print("\n\n=====================================\n\n")
```


## جستجوی کلی

```python

import Gerdoo from Gerdoo

gerdoo = Gerdoo("Query")
print(gerdoo.search())
```


## جستجوی تصاویر

```python

import Gerdoo from Gerdoo

gerdoo = Gerdoo("Query")
print(gerdoo.search_image())
```


## جستجوی ویدیو ها

```python

import Gerdoo from Gerdoo

gerdoo = Gerdoo("Query")
print(gerdoo.search_video())
```


## جستجوی اخبار

```python

import Gerdoo from Gerdoo

gerdoo = Gerdoo("Query")
print(gerdoo.search_news())
```


## دریافت پیشنهادات برای جستجو

```python

import Gerdoo from Gerdoo

gerdoo = Gerdoo("Query")
print(gerdoo.GetSuggestions())
```


### لینک ها
- [نویسنده](https://apicode.pythonanywhere.com/)
- [موتور جستجوی گردو](https://gerdoo.me/)
qm-tools-aw 1.5.3
Provides some functions that I have found value in reusing for quantum chemistry related tasks.
Requires Python: >=3.8

# QM-Tools-AW

A collection of quantum mechanics and computational chemistry tools for data analysis, visualization, and manipulation.

## Installation

```bash
pip install qm-tools-aw
```

## Features

### General Utilities
- File I/O operations (JSON, pickle)
- Molecular geometry manipulation and conversion
- Handling of various file formats (XYZ, PDB, Psi4 input)
- Distance calculations and molecular structure analysis
- Visualization helpers (e.g., PyMOL script generation)

### Plot Utilities
- Violin plots for error analysis with customizable aesthetics
- Support for statistical visualizations of computational chemistry data

### SAPT Analysis
- Symmetry-Adapted Perturbation Theory (SAPT) term computation for higher-order
SAPT mimicking Psi4 but on a pandas DataFrame

### Software Access
- Interface with external chemistry software
- Tools for working with `checkmol` for functional group analysis

## Usage Examples

### Create Violin Plots for Error Analysis

```py
import pandas as pd
import numpy as np
from qm_tools_aw.plot import violin_plot

# Create sample data
df = pd.DataFrame({
    'MP2': np.random.normal(0.5, 5, 1000),
    'HF': np.random.normal(-0.5, 5, 1000),
})

# Create violin plot
violin_plot(
    df,
    {'MP2 Method': 'MP2', 'HF Method': 'HF'},
    output_filename="method_comparison",
    ylim=[-25, 25],
    plt_title="Method Error Comparison"
)
```

*Results:* `Plotting method_comparison`

### Process Molecular Geometries

```py
from qm_tools_aw.tools import read_xyz_to_pos_carts, write_cartesians_to_xyz, print_cartesians_pos_carts

# Read XYZ file
pos, carts = read_xyz_to_pos_carts("molecule.xyz")

# Manipulate coordinates
carts[:, 0] += 1.0  # Shift x coordinates

# Write modified structure
write_cartesians_to_xyz(pos, carts, "modified.xyz")
print_cartesians_pos_carts(pos, carts)
```

*Results:*
```

8	0.2978039460	-0.0560602560	0.0099422620
1	-0.0221932240	0.8467757820	-0.0114887140
1	1.2575210620	0.0421214960	0.0052189990

```

## Documentation

For detailed documentation on all functions and classes, refer to the docstrings in the source code.

## Dependencies

- NumPy
- Pandas
- Matplotlib
- QCElemental
- Other standard Python libraries

## License

This project is licensed under the MIT License - see the LICENSE file for details.
pdblc 0.1.3
A package containing 10 custom programs
Requires Python: >=3.6

# PDBLC Package

A Python package containing 10 custom programs that print when imported.

## Installation

```bash
pip install pdblc
```

## Usage

```python
import pdblc
```

This will automatically print all 10 programs when the package is imported.

## To print a specific program:

```python
from pdblc.programs import print_program

print_program(1)  # Print program 1
print_program(5)  # Print program 5
```

## Available Programs

- Program 1: [Your description]
- Program 2: [Your description]
- Program 3: [Your description]
- Program 4: [Your description]
- Program 5: [Your description]
- Program 6: [Your description]
- Program 7: [Your description]
- Program 8: [Your description]
- Program 9: [Your description]
- Program 10: [Your description]
SliceCommander 0.2.post1
FABRIC Slice Commander
Keywords: fabric slice command

# SliceCommander
Tool for manipulating FABRIC slices on the command line.

## Installing

```
pip3 install -e .
```

 * slice-commander (fablib) expects a valid `fabric_rc` file at `$HOME/work/fabric_config/fabric_rc`

## Usage

```
$ slice-commander -h
Usage:
  slice-commander [options]
  slice-commander [options] show
  slice-commander [options] renew DAYS
  slice-commander [options] delete
  slice-commander (-h | --help)

Options:
  -h --help
  -s SLICE --slice SLICE
```

 * When run without arguments, `slice-commander` will attempt to load all of your active slices.
 * Once loaded, you may interact with the shell similar to a *nix bash shell with completion.
 
 Example:
 
 ```
 fabric-sc (/)> ?

Documented commands (type help <topic>):
========================================
EOF  cd  delete  exit  help  ls  lsd  pwd  renew  show  ssh  sync

fabric-sc (/)> help ssh
SSH to a node: ssh [node_path]
The ssh command can also be used within a node leaf
fabric-sc (/)> show --> [tab]
components  interfaces  keys        networks    nodes       
```
PySulfSat 1.0.8
PySulfSat
Requires Python: >=3.8

[![PyPI](https://badgen.net/pypi/v/PySulfSat)](https://pypi.org/project/PySulfSat/)
        [![Build Status](https://github.com/PennyWieser/PySulfSat/actions/workflows/main.yml/badge.svg?branch=main)](https://github.com/PennyWieser/PySulfSat/actions/workflows/main.yml)
        [![codecov](https://codecov.io/gh/PennyWieser/PySulfSat/branch/main/graph/badge.svg)](https://codecov.io/gh/PennyWieser/PySulfSat/branch/main)
        
        A python tool for PySulfSat.
        Examples and documentation available at
        https://PySulfsat.readthedocs.io/en/latest/index.html
        
        
        
        The paper is here: https://doi.org/10.30909/vol.06.01.107127
        
        If you have any issues with PySulfSat please raise an 'issue'. If you can attach your jupyter notebook and any associated files (spreadsheets), that makes it way easier to diagnose it. You can als
        email these to penny_wieser@berkeley.edu
        
        If you use PySulfSat in your paper, you must cite it (and you must also cite the original models you use):
        e.g.
        'calculations were performed in PySulfSat (Wieser and Gleeson 2023) using the SCSS model from Smythe et al. (2017), with an S6+ correction from Jugo et al. (2010).
        
        Open-source software development practices do not currently align with the academic credit system. Thus, we plead that if you take large chunks of PySulfSat to incorperate in your own package which you publish in a peer review journal (>100 lines), you insist in your paper than in addition to citing your new package,
        users also cite PySulfSat (or contact us to collaborate on the new package):
        
        For example, people should write 'degassing was calculated in PyDegass (Smith et al. 2026), which relies on sulfate and sulfide solubility calculations from Wieser and Gleeson (2023).
        
         PySulfSat took >6 months to write, under the current academic credit system, if you simply repackage it with a few new features, I gain no traditional credit (citations)!
        
         Happy sulfur modelling!
perfharness 1.0.3
Tool for tracking python performance regressions
Requires Python: >=3.7
Keywords: benchmark, performance

# perfharness

Perfharness is a python library for tracking testcase performance over time.

# How to use it

Install perfharness with `pip install perfharness`.

Write a perfharness testcase by building a python module with a `main` function that takes no arguments.
You can do any setup you need in the root module namespace so that the code which actually gets timed can be in `main`.

Configure perfharness by putting a `.perfharness.ini` file in the current directory.
Here is a sample configuration:

```
[perfharness]
sources_root = ../../..
sources = angr/angr,angr/angr_native,pyvex/pyvex,pyvex/pyvex_c,archinfo/archinfo,claripy/claripy,cle/cle,ailment/ailment
sources_ignore = *.o,*.so,*.a,*.pyc
build = pip install -e ./angr -e ./pyvex
cpu_percent_less_than = 10
mem_available_greater_than = 3gb
# https://docs.sqlalchemy.org/en/14/core/engines.html#database-urls
database = sqlite:///perf.db
```

Run perfharness with `python -m perfharness run [options] testcase.py`.
Valid options include `--num [n]` to collect `n` runs of data and `--warmup [n]` to run the testcase `n` times before collecting any data.

Visualize your testcase performance over time with `python -m perfharness viz [options] testcase.py`.
Different colors will be used to demarcate different attributes which might affect performance, such as the cpu and the python version.

![scatter plot of a testcase being run under cpython and pypy](img/plot.png)
cua-operator 0.0.1
Computer-Using Agent (CUA) Operator
Requires Python: >=3.8

# cua-operator
Computer-Using Agent (CUA) Operator

CUA is a new and evolving technology, but it currently lacks good documentation, mature libraries, and easy-to-use tools. While some automation or remote control libraries can work with CUA, they are often hard to set up. This project aims to make it simple for anyone to try out CUA without needing to understand it's internal details or complex configurations. It supports both Windows and macOS, and lets you connect your personal computer to a CUA compatible endpoint and explore the potential of CUA more easily.

## Quick Start

### Use CUA on your personal computer

Get Python Ready

```shell
pip install cua-operator openai
```

Run the following Python script and start your journey.

```python
from cua_operator.bridges import OpenAICuaBridge
from cua_operator.operators import LocalCuaOperator
from openai import OpenAI

client = OpenAI(
    api_key="{OPENAI_API_KEY}"
)

operator = LocalCuaOperator(bridge=OpenAICuaBridge(client))
operator.run()
```

## Customization

CUA-Operator is built around two core concepts: **operators** and **bridges**. An operator defines how you intend to interact with the CUA, whether through a local machine, a remote device, or potentially a Docker instance. A bridge specifies the service endpoint you connect to, such as OpenAI, with potential support for alternatives like Claude.

All available operators are in the `cua_operator.operators` namespace.

* **Local CUA Operator**: `LocalCuaOperator`
* **Remote CUA Operator**: `RemoteCuaOperatorClient` and `RemoteCuaOperatorServer`

All available bridges are in the `cua_operator.bridges` namespace.

* **OpenAI CUA Bridge**: `OpenAICuaBridge`

Samples: [samples](samples/)