semvec/pypi-packages huggingface dataset:
rstl 0.1.3
A Python port of R's stl function

# rstl
A Python port of R's stl function. Translated rather literally from the original R/Fortran source and vectorized with NumPy.

For more information see [the R manual](https://stat.ethz.ch/R-manual/R-devel/library/stats/html/stl.html).

Compatible with Python 2 and 3.

## Installation
```
pip install --user rstl
```

## Usage
Import the STL class and call its constructor.

```python
import numpy as np
from rstl import STL

ts = np.arange(144)
freq = 12

stl = STL(ts, freq, "periodic")

trend = stl.trend
```

## Documentation
The code itself is mostly uncommented due to it being a literal translation.

```python
class STL(ts, freq, s_window, s_degree=0, t_window=None,
          t_degree=1, l_window=None, l_degree=None, s_jump=None,
          t_jump=None, l_jump=None, robust=False, inner=None, outer=None):
```

Note that a value of None means that the default R value will be used.
(These could not be specified in the signature because Python does not allow referencing other parameters).

Args:
* ts: The time series (numpy array).
* freq: The frequency of the time series.
* s_window: Either the character string "periodic" or the span (in lags) of the loess window for seasonal extraction, which should be odd and at least 7, according to Cleveland et al.

Optional args:
* s_degree, t_window, t_degree, l_window, l_degree, s_jump, t_jump, l_jump, robust, inner and outer. See [the R manual](https://stat.ethz.ch/R-manual/R-devel/library/stats/html/stl.html) for their meanings and defaults.

Attributes:
* trend: The trend component of the time series (numpy array).
* seasonal: The seasonal component of the time series (numpy array).
* remainder: The remainder of the time series not explained by trend and seasonal components (numpy array).
* weights: The final robust weights (all one if fitting is not done robustly) (numpy array).

* s_window, s_degree, t_window, t_degree, l_window, l_degree, s_jump, t_jump, l_jump, inner and outer. Note that these may have been altered by the program.

## Performance
According to tests a runtime increase of factor ~3-5 should be expected.

## Copyright and License
Python port Copyright 2018 Eric Rauch.

Original source Copyright 2014 B.D. Ripley; Fortran code by Cleveland et al (1990) from ‘netlib’.

Licensed under the GPLv3.
beam-extended 0.1.0
Extend Apache Beam python API with new modules
Keywords: Apache,Beam,python

# beam-extended package

Provide extensions to existing SDKs (mainly Python)

It currently contains:
- mongoDB IO Connector

## Installation

To install the package, please use the `pip` installation as follows:

    pip install beam-extended
    
**Note:** currently, due to Apache Beam constraints, beam-extended is only available for **Python 3.6**.

## Example Usage

Here is a short example of using the package.

    from beam_extended.io.mongodbio import ReadFromMongo, WriteToMongo
    ...
    with beam.Pipeline(options=options) as pipeline:
        ( p | 'read' >> ReadFromMongo('myUrl1', 'myDb1', 'myColl1', query={}, projection=['_id'])
            | 'transform' >> beam.Map(transform)
            | 'save' >> WriteToMongo('myUrl2', 'myDb2', 'myColl2'))


## Publishing

Run the `pypi.sh` script.

## Credits

Based on:

https://gist.github.com/dlebech/e9d6ba266014db8783dbbeb362593020 by David Volquartz Lebech

and

https://gist.github.com/sandboxws/08b9c5e373b94056733f8a662d9a2fa2 by Ahmed El.Hussaini
sphinx-ext-eqt 1.4
A sphinx extension to integrate multiple choices questionnaires

# sphinx-ext-eqt

This is a sphinx extension to integrate multiple choices questionnaires


## Installation

This module is registered on pypi, simply run `pip install sphinx-ext-eqt` or add `sphinx-ext-eqt` to your requirements file.


## Configuration

Static files are not handled by extensions, to properly display the questionnaire, the module's *static dir* must be append to sphinx configuation:

```
from eqt_ext import get_eqt_ext_static_dir
html_static_path = ['<your_project_static_dir>', get_eqt_ext_static_dir()]
```
lwksprefs 0.1
Lightworks NLE preferences reader
Keywords: lwks lightworks parser

# Lightworks NLE preferences reader

`lwksprefs` is a little Python module developed
for parsing Lightworks preferences.


## Usage

```python
import lwksprefs
p1 = lwksprefs.parse_user_settings()
p2 = lwksprefs.parse('path-to-prefs-file.prefs')
```

Currently only key mapping is read. Commands mapped to keyboard
shortcuts are availabe as `commands` property:

```
print(p1.commands)
```


## Note

Lightworks is a professional NLE (non linear editor) developed by
EditShare and available natively on Linux platform.

For more information please visit: https://www.lwks.com/
sapass 2.2
With this module you can easy generate password in python projects

# **sapass**

First version of password generator for python projects

Easy to install and easier to use

Use python version bigger than 2.7

## For generate new password: :-1:
```python
from sapass import sapass

print(sapass.generator.get_new_pass(15))
```

### you can use below parameters for class inputs
1. length
    Default length for password defined 8 character, by change this value you get new pass with another size.
2. passType
    ```python
    passType = {'mix', # alphabet + numbers + symbols
            'alphabet', # only alphabet
            'number', # only numbers
            }
    ```
3. includeSymbol
    Boolean parameter: if define 'True' generated password contains special characters such as {!@#$%^&*()}
4. includeUppercaseCharacters
    Boolean parameter: if define 'True' generated password contains uppercase characters such as {ABCDEFGHIJ...}

## For convert password: :new: Added In version 2.0
> You must use **_convertor_** class

    ```python
    from sapass import convertor
    ```

1. Hash password with **hash_password** and validate it **hash_password_validate** method:
```python
new_pwd = "testPWd"
hashed_password=convertor.convertor.hash_password(new_pwd)
print(hashed_password)
if convertor.convertor.hash_password_validate(hashed_password, new_pwd):
    print('You entered the right password')
else:
    print('I am sorry but the password does not match')

```

 2. To verify the strength of password using **password_strong_check**:
 ```python
print(convertor.password_strong_check("hello"))
print(convertor.convertor.password_strong_check("hello_W0rld"))
```
    Output:
    > {'symbol_error': True, 'digit_error': True, 'lowercase_error': False, 'uppercase_error': True, 'length_error': True, 'password_ok': False}

    > {'symbol_error': False, 'digit_error': False, 'lowercase_error': False, 'uppercase_error': False, 'length_error': False, 'password_ok': True}