semvec/pypi-packages huggingface dataset:
primelist 0.1.0.0
Python library encapsulating the set of all primes as an indexed collection (optimized for small primes).
License: MIT

=========
primelist
=========

Python library encapsulating the set of all primes as an indexed collection (optimized for small primes).

.. image:: https://badge.fury.io/py/primelist.svg
   :target: https://badge.fury.io/py/primelist
   :alt: PyPI version and link.

Purpose
-------
Native Python class that encapsulates the set of all primes as an ascending sequence. Optimizations are included for finding and generating relatively small prime numbers.

Package Installation and Usage
------------------------------
The package is available on PyPI::

    python -m pip install primelist

The library can be imported in the usual way::

    from primelist import primelist

Examples
--------
The library provides a static class that behaves like a list-like object that virtually contains all prime numbers::

    >>> 17 in primelist
    True
    >>> 1000000000000000000000000000 in primelist
    False
    >>> primelist[0]
    2
    >>> primelist[79905]
    1019173
    >>> primelist[1:6]
    [3, 5, 7, 11, 13]

All prime numbers up to six digits in length are loaded into memory from disk on every one of the above queries. If an expression requires a larger range of primes to succeed, additional primes are generated as necessary in ascending order (inefficiently).

To maintain the list of primes in memory (both those loaded and those subsequently generated due to additional method invocations), it is possible to instead create an object. The object's methods are the same as those of the class `primelist`::

    >>> ps = primelist()
    >>> 17 in ps
    True
    >>> 1000000000000000000000000000 in ps
    False
    >>> ps[0]
    2
    >>> ps[79905]
    1019173
    >>> ps[1:6]
    [3, 5, 7, 11, 13]

It is possible to use the `len` function to obtain the number of primes that have been computed and stored so far within the object. The output below may not match exactly what you see in your environment::

    >>> ps = primelist()
    >>> len(ps)
    78498
docker_check 0.0.2
A small Python utility that tries to check if we are inside a Docker container.
License: MIT

docker-check
~~~~~~~~~~~~

A small Python utility that tries to check if we are inside a Docker
container.

Installation
~~~~~~~~~~~~

.. code:: bash

    pip install -e git+https://github.com/night-crawler/docker-check.git@HEAD#egg=docker-check
    # OR
    pip install docker-check

Sample
~~~~~~

.. code:: python

    from docker_check import checker
    checker.has_dockerenv()
    checker.has_docker_in_proc_1_cgroup()
    checker.is_inside_container()
resim 0.1.1
chemoREsistance SIMulator
License: MIT
Keywords: chemoresistance cancer outcome simulations modeling

ReSim: chemoREsistance SIMulator
================================
ReSim (chemoREsistance SIMulator) is a python package that simulates cancer
chemoresistance dynamics based on a stochastic model. The model describes the
interaction between chemotherapeutics and various cancer cell subpopulations
(including sensitive, primary resistant, acquired resistant and quiescent
cancer cells).

ReSim provides both GUI (powered by `Flask <http://flask.pocoo.org>`) and CUI.

**Remarks**: Simulation result is greatly depended on input params, therefore
ReSim is intended to use in parallel with *in vitro* assay. Procedures or
details in identifying input params *in vitro* is out of scope here and will be
documented in elsewhere (hope to get it publish soon).

Dependencies
____________
* flask
* Flask-WTF
* numpy
* scipy
* pandas
* matplotlib
* seaborn
* plotly
* sdeint

Installation
------------
We **strongly** recommend everyone to install resim within a virtual
environment. Setup the venv as usual and run ::

  $ pip install resim

Otherwise, install it locally.

Getting Start - GUI
-------------------
Open your command prompt, simply run ::

  $ resim-flask

ReSim is now available at http://localhost:5000/resim .

**Note** GUI provides a simplified & handy version of resim with interactive
plotly plots. Please use CUI if you need more control of input params.

Advanced Usage
--------------
Using defaults params (calibrated from the case of sorafenib and liver cancer)::

  >>> import resim

  >>> model = resim.Simulator()
  >>> res = model.simulate()

  >>> snsplt_cells = resim.plot_cells(res, subplot=True)
  >>> snsplt_drug = resim.plot_drug(res)
  >>> snsplt_fht = resim.plot_fht(res)

  >>> snsplt_cells.figure.savefig('resim_cells.png')
  >>> snsplt_drug.figure.savefig('resim_drug.png')
  >>> snsplt_fht.figure.savefig('resim_fht.png')

You may set your own params. For examples, input the growth rate of sensitive cells and resistant cells determined *in vitro*::

  >>> import resim

  >>> model = resim.Simulator(gr=[0.2, 0.1, 0.1])
  >>> res = model.simulate()

`model.simulate()` returns a dict of dictionary containing `pd.DataFrame` or
`np.array`. To extract the result,::

  >>>  df_cells = res['case']['cells']
  >>>  df_drugs = res['case']['drugs']

  >>> l_fht_control = res['control']['fht'])
  >>> l_fht_treatment = res['case']['fht'])

**Notes** GUI outputs are generated by `Plotly <https://plot.ly/>`. But both
`plot_cells`, `plot_drug` and `plot_fht` in CUI return `seaborn
<https://seaborn.pydata.org/>` plot object. You may customize your own theme,
title, layout.

Documentation
-------------
Available at https://resim.readthedocs.io/.

TODO
----
* Add class methods for conventional first-line/second-line chemos in HCC, PC.
* Add tool for converting tumor's diameter/volume to number of cells.
* Add tool for converting doubling time to growth rate.
* Add tool for converting half-life to k.
* Add command line module.
* Integrate parallel programming sde solver module `nsim
  <https://github.com/mattja/nsim>` to speed up the computation.
jlp 0.1a0
tool for installing Julia packages
License: MIT

# jlp  --- pip like Julia Package Manager
A package management system used to install and manage software packages for Julia.

<p>
    <img src="https://upload.wikimedia.org/wikipedia/commons/thumb/6/69/Julia_prog_language.svg/1280px-Julia_prog_language.svg.png" width="300"/>
</p>

## Requirement
- Julia 0.4+
- Python 2.7+ or Python 3.5+
- pip or pip3

## Installation

```sh
pip install jlp
```


## Usage
```
Usage:
  jlp <command> [options]

Commands:
  install                     Install packages.
  uninstall                   Uninstall packages.
  update                      Update installed packages.
  remove                      Alias remove.
  freeze                      Output installed packages in requirements format.
  list                        Alias freeze.
```

## Examples
### Show installed packages and version 
```sh
jlp list > REQUIRE
jlp freeze > REQUIRE
jlp freeze --format json > packages.json
jlp freeze -f yaml > requirements.yml
```

### Install packages
```sh
jlp install Pandas
jlp install Pandas IJulia==1.6.2 Requests
jlp install -r REQUIRE
jlp install -r packages.json
jlp install -r requirements.yml
```

### Uninstall packages
```sh
jlp uninstall Pandas
jlp uninstall Pandas PyCall
jlp remove Pandas PyCall
```

### Update installed packages
```sh
jlp update
```
input-objects 0.0.0
Input objects library
License: MIT

Input object library
====================

Uniform API for reading from multiple different sources.

Contains reconnecting reading file like object for uninterrupted stream
reading of remote files.

.. code:: python

    import requests, lz4framed, input_obj
    url = 'https://ph4r05.deadcode.me/static/lz4/certificates.20171002T020001.15.json.lz4'
    iobj = input_obj.ReconnectingLinkInputObject(url=url, timeout=5*60, max_reconnects=1000)
    for idx, chunk in enumerate(lz4framed.Decompressor(iobj)):
        print(chunk)

Pip package
-----------

::

    pip install -U pip setuptools twine
    python setup.py sdist
    twine upload dist/*
gdget 0.1.1
Google drive URLs downloader for command line.
License: MIT
Requires Python: >=2.6, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, <4
Keywords: googledrive cli google download

GdGet
=====

A simple command line utility to download Google Drive public URLs
effortlessly.

Installation
~~~~~~~~~~~~

.. code:: bash

    pip install gdget

Usage
~~~~~

-  Download using google drive url

.. code:: bash

    gdget https://drive.google.com/file/d/1rcZ42siSqpLlVx2LRR_xjD7uJA8twKEa/view

-  Download using Google drive ID

.. code:: bash

    gdget 1rcZ42siSqpLlVx2LRR_xjD7uJA8twKEa

Requirements
~~~~~~~~~~~~

-  Python >=2.6 & >=3.4 (does not support 3.3)
-  requests
-  tqdm
-  pytest (optional, to run tests)

License
~~~~~~~

`The MIT License`_

.. _The MIT License: ./LICENSE