mungo 0.1.0

Quick environment solver

# mungo

**IMPORTANT WARNING**
*mungo* is experimental, things are *very* likely to break.

*mungo* acts as a drop-in replacement for `conda create` and `conda install` -
but with way faster environment resolution.
The improvements in speed are achieved by employing linear programming instead
of sat-solving and caching of intermediate results (see "The ILP" for more information).

Note that we do not want to replace conda - we merely wish to share our solution so that it can be tested and perhaps
someday be integrated into conda itself.

## Caveats
- *mungo* only exposes basic functionality:
- `install (package_spec)+ (--name NAME)? (--channel CHANNEL)* (--file FILE)?`
- `create  (package_spec)* (--name NAME)? (--channel CHANNEL)* (--file FILE)?`
- *mungo*'s solutions will *not* be the same as conda's.
- *mungo* cannot handle custom channel urls. Any channel which has `repodata.json.bz2` files available from `https://conda.anaconda.org/CHANNEL/ARCH` is fine, though.
- *mungo* only reads channels from `~/.condarc` (but also uses the `--channel` arguments, if supplied, of course).
- *mungo* only supports linux at the moment.

## Installation
You need a working conda installation, since actual package installation is
delegated to conda.
### from PIP
pip install mungo

## Examples
# create an environment named 'foo' with the specified packages
mungo create -n foo "python>=3.7" pulp packaging pyyaml

# create an environment from an environment file (such as mungo.yml)
mungo create --file mungo.yml

# install packages into the current environment
mungo install bwa

# install packages into a different environment
mungo install -n foo bwa

## The ILP
*mungo* uses an integer linear program to determine a configuration of compatible packages which maximizes version numbers while also keeping channel order in mind.


After merging, the algorithm creates an ILP variable [0;1] for each p-node. This variable later represents if the package with the related version is selected for installation (1) or not (0).
As a second step, the algorithm iterates over all contrain nodes and creates the following ILP constrain:
For each parent p (variable), the sum of all children (variables) C must be greater or equal p. This represents the fact, that if p is installed, at least one available version of each dependent package must also be installed. If p is not selected for installation (p=0), the installation status of its dependencies is not imporatant to p.



## Changelog
- version 0.1.0: Initial version.