semvec/pypi-packages huggingface dataset:
crystallize 0.0.10
Creating tables and storing them in JSON files
Requires Python: >=3.6

<h1>O que é o Crystallize</h1>
<p>O Crystallize é um projeto que Visa a atende de maneira imediata a necessidade de se armazenar dados, tanto para profissionais de Data Science, como também para profissionais do desenvolvimento de softwares em geral que precisam de uma rápida abordagem para o salvamento de seus dados.</p>
<h1>Nossa filosofia</h1>
<p>Este projeto nasceu com o intuito de ser leve e eficaz sem a necessidade de instalação de bibliotecas adicionais. Todo o projeto é de rápida instalação e download sendo realmente uma alternativa muito prática para a essas questões de salvamento de dados no dia a dia dos desenvolvedores de softwares.<p>
____________________________
<h1>What is Crystallize</h1>
Crystallize is an immediate project aimed at the need to also meet data, both for Science professionals and for software development professionals in general who need a quick way to save their data.
<h1>Our philosophy</h1>
<p>This project was born with the intention of being light and efficient without the need to install additional libraries. The entire project is quick to install and download and is really a very practical alternative to these data saving issues in the day to day of software developers.</p>
django-sql-debug 0.0.3
Output in the console the executed SQL of queries made by Django's ORM
Requires Python: >=3.6

[![PyPI version](https://badge.fury.io/py/django-sql-debug.svg)](https://badge.fury.io/py/django-sql-debug)

# django-sql-debug
Output in the console the executed SQL of queries made by Django's ORM.

**This is a development tool that should only be used in a local environment and never included in production code.**

## Features
- Print executed SQL to the console
- Automatically runs `EXPLAIN ANALYSE`
- Allows for debugging of single query, function, test or the entire application

## Why not use django-debug-toolbar?
[Django Debug Toolbar](https://github.com/jazzband/django-debug-toolbar) is great if you are developing an html website
using Django. However, since it is focused on displaying the queries using HTML code inject in the webpage it is not
suitable if you are developing a REST API or need to view the queries being run in a unit test. This lib was inspired
by the weakenesses of Django Debug Toolbar on these use cases.


## Installation
```
pip install django-sql-debug
```

## Examples
There are many ways to use the library. You can set the scope of the debug using one of the examples below.

### Debugging a small segment of code
```
from django_sql_debug import debug_sql


with @debug_sql():
    SomeModel.objects.get(id=5)  # will be captured
SomeModel.objects.get(id=5)  # will not be captured

```

### Debugging a single function or test
```
from django_sql_debug import debug_sql


class MyTest(TestCase):
    @debug_sql()
    def test_will_show_executed_sql(self):
        SomeModel.objects.get(id=5)

    def test_will_not_show_executed_sql(self):
        SomeModel.objects.create(name='test')
```

### Debugging an entire TestCase
```
from django_sql_debug import DebugSQLTestCaseMixin


class MyTest(DebugSQLTestCaseMixin, TestCase):
    def test_will_show_executed_sql(self):
        SomeModel.objects.get(id=5)

    def test_will_also_show_executed_sql(self):
        SomeModel.objects.create(name='test')
```

### Debugging an entire application
Add `django_sql_debug` to the `INSTALLED_APPS` and `MIDDLEWARES`.

```
INSTALLED_APPS = [
    'django_sql_debug',

    ...
]

MIDDLEWARE = [
    'django_sql_debug.DebugSQLMiddleware',

    ...
]
```


## Configuration
You can change some configurations in Django's `settings.py`

- SQL_DEBUG_ENABLE_PARAMS: Include the SQL parameters section in the debug log (default: True)
- SQL_DEBUG_ENABLE_PERFORMANCE: Include the SQL performance section in the debug log (default: True)
- SQL_DEBUG_ENABLE_EXPLAIN: Run `EXPLAIN` command on supported databases (default: True)
- SQL_DEBUG_OUTPUT_STREAM: The output stream to write sql queries and additional sections (default: sys.stdout)
- SQL_DEBUG_OUTPUT_SIZE: The size of the output headers (default: terminal width)
faker_sqlalchemy 0.10.2208140
A Faker provider that generates data based on SQL Alchemy column types.
Requires Python: >=3.7

Fakers for SQLAlchemy
=====================

|PyPI| |Build| |Supported Python versions| |Documentation| |Downloads| 

`SQLAlchemy Faker <https://faker-sqlalchemy.readthedocs.io/en/latest/>`_ is a provider for the
`Faker <https://github.com/joke2k/faker>`_ library that helps populate `SQLAlchemy ORM <https://www.sqlalchemy.org/>`_
models with dummy data. Creating a new instance of a model can be as simple as calling
``fake.sqlalchemy_model(SomeModel)``.


Installation
------------

The recommend way to install SQLAlchemy Faker is with ``pip``::

    pip install faker_sqlalchemy

Example
-------

Say you have some model declared using SQLAlchemy's ORM.

>>> class SomeModel(Base):
...     __tablename__ = "some_model"
...
...     id = Column(Integer, primary_key=True)
...
...     value = Column(String)

And, you want to easily generate some data,

>>> from faker_sqlalchemy import SqlAlchemyProvider
>>>
>>> fake = Faker()
>>> fake.add_provider(SqlAlchemyProvider)
>>>
>>> instance = fake.sqlalchemy_model(SomeModel)

Use ``instance`` as desired.

>>> print(instance.value)
RNvnAvOpyEVAoNGnVZQU

Supported Versions
------------------

Currently SQLAlchemy versions 1.3 and 1.4 are supported. Support for SQLAlchemy 2.0 will be added when it is released.

Faker versions ``>=8`` are currently supported, though it should be noted that the testing matrix isn't exhaustive. If
bugs come up with a particular version of faker beyond version 8.0, submit a ticket to add support.

Python versions ``>=3.7`` are currently supported. If python 3.6 support is desired, submit a ticket to add support. Support
for Python 3.11 will be added when it is officially supported by SQLAlchemy. Currently, this is waiting on greenlet
releasing support for python 3.11.


.. |PyPI| image:: https://img.shields.io/pypi/v/faker_sqlalchemy
   :target: https://pypi.org/project/faker_sqlalchemy/
.. |Build| image:: https://github.com/nickswebsite/faker-sqlalchemy/actions/workflows/package.yml/badge.svg
   :target: https://github.com/nickswebsite/faker-sqlalchemy/actions/workflows/package.yml
.. |Supported Python versions| image:: https://img.shields.io/pypi/pyversions/faker_sqlalchemy.svg
   :target: https://pypi.org/project/faker_sqlalchemy/
.. |Documentation| image:: https://readthedocs.org/projects/faker-sqlalchemy/badge/?version=latest
   :target: https://faker-sqlalchemy.readthedocs.io/en/latest/?badge=latest
.. |Downloads| image:: https://pepy.tech/badge/faker_sqlalchemy/month
   :target: https://pepy.tech/project/faker_sqlalchemy/
outlier-detector-z 0.1.1
Application is used to detect the outliers in a list or tuple

# outlier-detector-z
Outlier detector using Z-score. application accepts only list or tuple. 
By default threshold set as 3 std. Any element z-score more than threshold will be considered as outlier

## run pip command 

# Sample code

## from outlier_detector import outlier_detector
## outlier = outlier_detector.detect_outlier([1,2,3,4,5,6,7,8,9,10,20,12,14,200]) 
## print(outlier)