semvec/pypi-packages huggingface dataset:
full-alchemyst 1.0.1
Les's to use a unique ORM to manage the persistence in one project.
Requires Python: >=3.6
Keywords: MongoAlchemyst,SqlAlchemyst,Flask,DB

# full_alchemyst
Let's you to use both SqlAlchemyst and MongoAlchemyst libraries
Les's to use a unique ORM to manage the persistence in one project. 

## How to Use?
You need to configurate a dictionary with the next parameters:
db_config = {
    "type":"mongo",
    "host": "localhost",
    "port":27017,
    "user":"",
    "database":"google",
    "password":"",
    "SQLALCHEMY_TRACK_MODIFICATIONS":True
}

- *** type: ***  mongo | mysql
- *** host: ***  Host where the database is
- *** port: ***  Port of engine runs
- *** user: ***  User
- *** databse: ***  Name of database
- *** password: ***  Password

How you see, you can to specify other attributes of the ORM, like "SQLALCHEMY_TRACK_MODIFICATIONS".

After to set the configuration that you want to use, you have to create a FullAlchemyst instance:

```
app = Flask(__name__)
fullAlchemyst= FullAlchemyst(app,db_config)
```

Obviusly, What is a ORM without models? Create one:

```
class task(fullAlchemyst.Entity):
    id = define(fullAlchemyst.db, {"name":"id","type":"int","primary_key":True})
    nombre = define(fullAlchemyst.db, {"name":"nombre","type":"str"})
```

### Steps:
1. First, you need to extend you model of fullAlchemyst.Entity
2. Define your attributes. In this step, remember to use the "define" function. We see this later

### "define" function
This function is used to configurate you model depending what type of database you use.

This function, receives a dict, and its structure is the next:
- type : int | str o another inside de buildins of python.
- primary_key : If you attribute is a primary key.
drawnow 0.72.5
MATLAB-like drawnow
Keywords: figure,plotting,visualization,matlab

<!--XXX: UPDATE WITH-->
<!--python setup.py build-->
<!--python setup.py sdist upload-->

`drawnow` for matplotlib
========================

The scientific community often runs iterative code, often in the form of
simulation. It's often useful to see the results after each iteration.
Accordingly, MATLAB® has a nice feature that allows you to update the
figure, `drawnow`. This repo brings the same feature to Python's
matplotlib, with some extras.

Example:

![image0](test-data/test.gif)

This is shown with `imshow`, but python-drawnow allows updates of any
figure.

Usage:

``` python
# complete implementation of script found in test/test.py
from pylab import *
from drawnow import drawnow, figure
# if global namespace, import plt.figure before drawnow.figure

def approx(x, k):
    """Approximate x with k singular values"""
    ...

figure(figsize=(7, 7/2))
def draw_fig():
    subplot(1, 2, 1)
    imshow(x)

    subplot(1, 2, 2)
    imshow(x_hat)
    #show()

x = imread('test-data/mandrill.png').mean(axis=2)
k_values = around(logspace(0, 2, num=10))
for k in k_values:
    x_hat = approx(x, k)
    drawnow(draw_fig)
```

Documentation
=============

If you want to wait for confirmation after update or the option to drop
into a debugger, call `drawnow(function_to_draw_figure, confirm=True)`.

If you only want to show the figure once, call
`drawnow(function_to_draw_figure, show_once=True)`. The full
documentation is included in the doc strings. Use `drawnow?` or
`help(drawnow)` to see these docs.

Jupyter/Spyder
==============

Try running the folloowing code in a Jupyter input cell/in the
console/etc:

```
%matplotlib
```

This will disable the Matplotlin inline mode and use the default
plotting backend. For more detail, see the [IPython plotting
documentation](https://ipython.readthedocs.io/en/stable/interactive/plotting.html#id1).

Installation
============

Two options:

1.  Run `pip install drawnow`.
2.  Download this repository and run `python setup.py install`.

Option 2 assumes a working Python installation with `pip`. I suggest
Anaconda's distribution: <https://www.anaconda.com/distribution/> For
other options, see <https://realpython.com/installing-python/>.

Changes to code
---------------

This does require *small* changes to your code. All it should really
amount to is moving `figure(); plot(...); show()` inside a function; not
much.