microservice-numpy/README.md

## Swarmlab is a collection of services that aims to

 > -    provide teachers and professors with online remote tools to do their lessons
 > 
 > -    give students the opportunity to study real life examples in their chosen area of expertise
 > 
 > -    allow developers to fully test and debug their applications and provide POC’s
 > 
 > -    or you simply want to use a Application (in a microservices-based architecture)
 > 
 >  Swarmlab provides you with all the required tools, tools to teach work or try out demos in a completely virtual environment.
 > 
 > More info: http://docs.swarmlab.io/SwarmLab-HowTos/swarmlab/docs/swarmlab/docs/index.html





![alt text](images/swarmlab-network.png "")


##  LabInstance numpy, SciPy, pandas

**NumPy** is the fundamental package for scientific computing in Python. It is a Python library that provides a multidimensional array object, various derived objects (such as masked arrays and matrices), and an assortment of routines for fast operations on arrays, including mathematical, logical, shape manipulation, sorting, selecting, I/O, discrete Fourier transforms, basic linear algebra, basic statistical operations, random simulation and much more.


https://numpy.org/doc/stable/reference/index.html#reference


**SciPy** is a free and open-source Python library used for scientific computing and technical computing.

SciPy contains modules for optimization, linear algebra, integration, interpolation, special functions, FFT, signal and image processing, ODE solvers and other tasks common in science and engineering. 

Available sub-packages include:

* cluster: hierarchical clustering, vector quantization, K-means
* constants: physical constants and conversion factors
* fft: Discrete Fourier Transform algorithms
* fftpack: Legacy interface for Discrete Fourier Transforms
* integrate: numerical integration routines
* interpolate: interpolation tools
* io: data input and output
* linalg: linear algebra routines
* misc: miscellaneous utilities (e.g. example images)
* ndimage: various functions for multi-dimensional image processing
* ODR: orthogonal distance regression classes and algorithms
* optimize: optimization algorithms including linear programming
* signal: signal processing tools
* sparse: sparse matrices and related algorithms
* spatial: algorithms for spatial structures such as k-d trees, nearest neighbors, Convex hulls, etc.
* special: special functions
* stats: statistical functions
* weave: tool for writing C/C++ code as Python multiline strings (now deprecated in favor of Cython)


**pandas** is a fast, powerful, flexible and easy to use open source data analysis and manipulation tool,
built on top of the Python programming language. 


## Quickstart

This is a quickstart guide of howto use this *LabInstance*


### Default Configuration 

- Working Directory

> /home/docker/project

- Default user

> docker

- Default password

> docker

- Default password4root

> pass



  





### RUN INSTANCE

Swarmlab services can be run in different ways. 

- You can run them **through the swarmlab hybrid environment** (http://docs.swarmlab.io/SwarmLab-HowTos/swarmlab/docs/swarmlab/docs/hybrid/start-microservices.html)
- or use them individually at will on the **command line of your system**



#### CLI

> git clone ...
>
> cd [DIRECTORY]
>

#### help
>
> make help
>

#### create service
>
> make create
>

#### start service
>
> make start
>

#### stop service
>
> make stop
>

#### list service
>
> make list
>

#### clean service
>
> make clean
>