semvec/pypi-packages huggingface dataset:
simpleBlackScholes 1.0.2
Functions for Black-Scholes Model related calculations.
Requires Python: >=3.11

# Simple Black-Scholes (simple-blackScholes)

Simple Black-Scholes library is a short python package with methods for calculating the values of option contracts using the Black-Scholes-Merton model.

## What it can do

Currently it can calculate the following

* For European-Style options:
    * Call option price,
    * Put option price.


## To Be Implemented

There are still a lot of features missing in the library. Currently these are the future aims of the project:

* Pricing functions for American-Style options.
* Option contract greek values.


## Licence

Licensing information can be found in the `LICENSE` file.
eoq1 1.0.1
Essential Object Query - a framework to access ecore models - DEPRECATED version 1
Requires Python: >=3.6

# EOQ1 Python Library

**WARNING: EOQ1 is depricated and should not be used any longer. This lib is for legacy reasons only.**

This is the implementation of EOQ1 in Python. For more details see [PyEOQ](https://gitlab.com/eoq/py/pyeoq).

This library is based on [pyecore](https://github.com/pyecore/pyecore). 

Python examples: https://gitlab.com/eoq/py/pyeoq


# EOQ

[Essential Object Query (EOQ)](https://gitlab.com/eoq/essentialobjectquery) is a language to interact remotely and efficiently with object-oriented models, i.e. domain-specific models. It explicitly supports the search for patterns, as used in model transformation languages. Its motivation is an easy to parse and deterministically behaving query structure, but as high as possible efficiency and flexibility. EOQ’s capabilities and semantics are similar to the Object-Constraint-Language (OCL), but it supports in addition transactional model modification, change events, and error handling.  

Main Repository: https://gitlab.com/eoq/essentialobjectquery

EOQ user manual: https://gitlab.com/eoq/doc
effluent 1.5.0
Simulate effluent discharges from wastewater pipes
Requires Python: >=3.6
Keywords: pipes turbulent jets plumes ocean

[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.13929233.svg)](https://doi.org/10.5281/zenodo.13929233)
[![DOI](https://joss.theoj.org/papers/10.21105/joss.05554/status.svg)](https://doi.org/10.21105/joss.05554)

# effluent

Effluent is a python package for simulating the dispersion of effluent
discharges from wastewater pipes. The underlying model is based on
Lee, Joseph H. W., and Chu, Vincent H.: *Turbulent Jets and Plumes*.
Boston, MA: Springer US, 2003.
[doi:10.1007/978-1-4615-0407-8](https://doi.org/10.1007/978-1-4615-0407-8).

The package is mainly intended for research purposes, and does not contain
any convenience plotting or statistics functionality. It is expected that
these analyses are conducted in post-processing stages using other packages.


## Installation

The package is installed using pip:

    pip install effluent

Alternatively, the package can be installed to an isolated conda environment
using the in-repo file `environment.yml` as follows:

    conda env create -f environment.yml 


## Usage

The software is invoked as a command line script:

    effluent config.toml

where `config.toml` is the configuration file specifying the simulation
setup. Examples of valid configuration files are given in the repository
directory `docs/source/examples`, and in the
[online documentation](https://effluent.readthedocs.io/en/latest/).


## Citation

If you use the software in a publication or report, please cite it as follows:

Sævik, P. N., (2023). _Effluent: A Python package for modelling effluent discharge_.
Journal of Open Source Software, **8**(89), 
[https://doi.org/10.21105/joss.05554](https://doi.org/10.21105/joss.05554).

Consider also citing the work which this package is based on:

Lee, J. H. W., and Chu, V. H. (2003).
_Turbulent Jets and Plumes - A Lagrangian Approach_. Boston, MA: Springer US.
[https://doi.org/10.1007/978-1-4615-0407-8](https://doi.org/10.1007/978-1-4615-0407-8).


## Documentation

Check out the
[online documentation](https://effluent.readthedocs.io/en/latest/) for a
detailed description of the algorithm and software features.


## How to contribute

Use the GitHub issue tracking system to report problems with the software, seek
support, or suggest improvements. Code contributions can be suggested using
GitHub pull requests. Check documentation for details.