semvec/pypi-packages huggingface dataset:
baresql 1.0.0
playing SQL directly on Python datas
Keywords: sqlite, sql

baresql : playing SQL directly on Python datas
==============================================

baresql improves sql agility of python data science beginners by :
 * allowing sql over python objects (list, ranges, ...) and SQL Tables,
 * requiring no special module except : pandas. 

Inspiration :
-------------

* pypi.python.org/pypi/pandasql : sqldf for pandas
 
* pypi.python.org/pypi/ipython-sql :  sql magic in Ipython


Features
--------

* query lists , tuple, dictionnaries, dataframes 

* result as a dataframe, list of records, or list

* basic Common Table Expression support on old python3.3- versions


Installation
------------

You can install, upgrade, uninstall sqlite_bro.py with these commands::

  $ pip install baresql
  $ pip install --upgrade baresql
  $ pip uninstall baresql

or just launch it from IPython with %load https://raw.githubusercontent.com/stonebig/baresql/master/baresql/baresql.py

Basic Example 
-------------

::

  from __future__ import print_function, unicode_literals, division  # if Python2.7
  from baresql import baresql
  bsql = baresql.baresql(keep_log = True )
  bsqldf = lambda q: bsql.df(q, dict(globals(),**locals()))
  
  users = ['Alexander', 'Bernard', 'Charly', 'Danielle', 'Esmeralda', 'Franz']
  #  We use the python 'users' list like a SQL table
  sql = "select 'Welcome ! ' , c0 from users$$"
  bsqldf(sql)
 

Examples
--------
http://nbviewer.ipython.org/github/stonebig/baresql/blob/master/examples/baresql_with_cte.ipynb

Links
-----

* `Fork me on GitHub <http://github.com/stonebig/baresql>`_
schema-agents 0.2.0rc2
A schema-based LLM framework for building multi-agent collaborative systems.

# Schema Agents

A schema-based LLM framework for building multi-agent collaborative systems.

## Getting Started

See [example](./scripts/alice_cooker_example.py) for a simple example of how to use the framework.

## Development

Create a conda environment and install dependencies:

```bash
conda create -n schema-agents python=3.10
conda activate schema-agents
```

```
conda install faiss-cpu -c conda-forge
pip install -r requirements_test.txt
pip install -e .
```
relaxometrynmr 0.0.1
solid-state NMR relaxation data analysis: T1, T1_rho and T2
Requires Python: >=3.10
Keywords: NMR, T1, T1_rho, T2, nmr, relaxometry, solid-state NMR, ss-NMR

# ``relaxometrynmr``: NMR relaxometry made easy !

``relaxometrynmr`` an open-source Python package for solid-state NMR relaxation data analysis: T1, T1_rho and T2.

This package is only compatible with Bruker's NMR data (see User's guide).

# Why ``relaxometrynmr``?
This package is built for NMR relaxometry data analysis and offers a user-friendly data processing. It streamlines the analysis of relaxation time constant (T1, T1_rho or T2) and reduces analysis time by more than 50%. It comprises several built-in modeling functions such as mono-, di-, tri-, and stretch-exponential. These functions offer the flexibility to model a wide range of relaxation behaviors -- from simple to complex systems.



# Key Features

## Comprehensive NMR Data Handling
  - Supports mainly Bruker's data 
  - Handles data reading, conversion, and processing seamlessly
  - Automatically detects and loads delay list (vdlist, vplist, or vclist) for relaxometry experiments
## Advanced Data Processing
  - Zero-filling for improved spectral resolution
  - Phase correction (0th and 1st order) for signal representation in pure-absorption mode
  - Gaussian apodisation for line broadening and improvement of signal-noise ratio
## Spectral Integration
 - Numerical integration methods (trapezoid and Simpson's rule) for robust quantification of peak area
## Visualisation
  - Full spectrum view for context
  - Zoomed-in region for detailed analysis
## Modelling and Data Fitting
  - multiple-component models: mono-, bi-, and tri-exponential functions for simple to complex relaxation
  - stretched exponential models: for systems with non-standard relaxation dynamics (e.g., disordered materials)
  - decay analysis: tools for analysing exponential decay curves with multiple components
  
# Install

```bash
pip install relaxometrynmr

```

# Dependencies

The following packages are required:

```bash

nmrglue 
numpy
matplotlib >= 3.9.0
mrsimulator = 1.0

```

You can install these dependencies using pip:

```bash

pip install nmrglue numpy scipy mrsimulator = 1.0

```

Examples can be found in User Guide



# Contact

For questions and support, please open an issue in the GitHub repository.