semvec/pypi-packages huggingface dataset:
postfox 0.1.3
Python CLI to migrate FoxPro tables to PostgreSQL
License: MIT
Requires Python: >=3.9,<4.0

# PostFox
## Python CLI to migrate FoxPro tables to PostgreSQL
First alpha, needs alot of work still
### How to use
```python3 postfox.py --help```

### TODO
* Get rid of pandas dependancy (It's slow)
* Write tests
* Add support for batch conversions
* Add better error handling
sauci-pyelf 0.1.2
high level API to retrieve information from ELF files.
License: MIT
Requires Python: >=2.7.14

![tests status](https://github.com/Sauci/pyelf/actions/workflows/test.yml/badge.svg)
[![code coverage](https://codecov.io/gh/Sauci/pyelf/branch/master/graph/badge.svg?token=Q5aceZRFXh)](https://codecov.io/gh/Sauci/pyelf)

## package description

the purpose of this package is to provide high level API to work
with [elf](https://en.wikipedia.org/wiki/Executable_and_Linkable_Format) files.

## installation

### using `pip`

install the package by running the following command:
`pip install sauci-pyelf`

### from source

this package uses [pyelftools](https://pypi.org/project/pyelftools) package. if it is not already installed, install it
first. once the above prerequisite is installed:

- download the [pyelf](https://github.com/Sauci/pyelf/archive/master.zip) package
- unzip it
- move to the directory containing the setup.py file
- run the command `python setup.py install`

**note:** the above command might require privileged access to succeed.

## example of usage

the bellow code snippet shows how to load an elf file and get some of its properties.

```python
from pyelf import ElfFile

elf = ElfFile('tests/input.elf')

# get a list of all symbols in file tests/input.elf.
symbols = elf.symbols()
assert 'symbol_uint8' in symbols

# get an instance of Symbol class for symbol named symbol_uint8.
symbol = elf.get_symbol('symbol_uint8')

# get address of symbol symbol_uint8.
assert isinstance(symbol.address, int)

# get size of symbol symbol_uint8.
assert symbol.size == 1

```
arimafd 1.4.1
Build librarry
License: MIT

# About arimafd

Arimafd is a Python package that provides algorithms
for online prediction and anomaly detection. One of the
applications of this package can be the early detection
of faults in technical systems.



# Main Features


- Differentiation and integration of series including seasonal components
- Finding best hyperparametrs for ARIMA model
- Online forecasting based on ARIMA model
- Anomaly detection 
- Evaluating score of anomaly detection algorithms

# How to get it
The master branch on GitHub 

https://github.com/waico/arimafd


Binaries and source distributions are available from PyPi

https://pypi.org/project/arimafd/

# Get started

**Installation** through [PyPi](https://pypi.org/project/tsad): 

`pip install -U arimafd`

# License

MIT