semvec/pypi-packages huggingface dataset:
athena2pd 0.2.1
Helps simplify the access of databases stored in Amazon Athena by using SQL and pandas DataFrames.
License: MIT

# athena2pd
[![](https://img.shields.io/badge/python-2.7+-blue.svg)](https://www.python.org/download/releases/2.7.0/)
[![](https://img.shields.io/badge/python-3.6+-blue.svg)](https://www.python.org/download/releases/3.6.0/)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)


athena2pd - Amazon Athena to Pandas Dataframe

## About

Useful tool to help simplify the access of databases stored in Amazon Athena by using SQL and pandas DataFrames. 

The end user simply needs to provide the query and the bucket where the results are stored, then this package will run the query and return a DataFrame with the data in it, ready to be used for whatever is desired.

## Installation
Use the package manager [pip](https://pip.pypa.io/en/stable/) to install athena2pd.

```bash
pip install athena2pd
```

## Usage

Before use, you will need an AWS key pair, and an IAM profile set up to access both Amazon Athena and S3.

Using local .aws/ files is the safest way to connect, rather than providing the keys in the code. See the example files below:

The `.aws/credentials` file is set up like this:
```
[default]
aws_access_key_id = {access_key_id}
aws_secret_access_key = {secret_access_key}

...
```

In addition, the `.aws/config` is set up similar to this:
```
[default]
output = json
region = us-east-1

[profile athena-role]
role_arn = arn:aws:iam::{iam-id-number}:role/{role-name}
source_profile = default
region = us-east-1

...
```

Once that is set up, in your python code, the athena2pd package can be used like so:
```python
from athena2pd import AthenaDFConnector

# Initialize the AthenaDFConnector object
ath = AthenaDFConnector(aws_profile_name='athena-role')

# Example SQL query
sql_query = '''
SELECT COUNT(*) AS Count
FROM testcatalog.testdatabase.testtable
'''

# Example output location
output_loc = 's3://bucket-name/sub/folder'

# Query Athena and load into a pandas DataFrame
df = ath.query(query_string=sql_query, s3_output_location=output_loc)
```

## Contributing
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

Please make sure to update tests as appropriate.

## License

[MIT](LICENSE)
edeklaracje-client 0.0.1
Library to simplify building Plotly Dash applications
License: MIT
Requires Python: >=3.5

# E-Deklaracje client

## How to
1) Znajdź interaktywny formularz PDF na [stronie ministerstwa](https://www.podatki.gov.pl/e-deklaracje/zloz-e-deklaracje-pit/) dla PITu, który chcesz złożyć.
2) Wypełnij formularz.
3) Przygotuj plik XML na podstawie [przykładu](examples/deklaracja_pit36.xml). Wpisz wartości z interaktywnego formularza, który właśnie wypełniłeś.
4) Zainstaluj klient edeklaracji: `pip install edeklaracje_client`
5) Wyślij deklarację z pliku XML: `edeklaracje send_document twoj_plik.xml`

Więcej informacji o działaniu klienta można uzyskać.
Sleepyq2 0.1.0
New async client library for SleepIQ Cloud service.
License: MIT

# Sleepyq2

![GitHub](https://img.shields.io/github/license/sluzynsk/sleepyq2)
![GitHub issues](https://img.shields.io/github/issues/sluzynsk/sleepyq2)
![GitHub release (latest by date)](https://img.shields.io/github/v/release/sluzynsk/sleepyq2)


## An asynchronous Python Library for accessing the SleepIQ Cloud.

Much work here based on the efforts of Nate Johnson & his sleepyq library.

### Why a new library?
Ultimately most of what I wanted to add could have been added to the existing sleepyq 0.7.0 library.
However, the author has had PRs open for nearly a year.
I came to the conclusion that he was probably not working on the library any longer.
Since I was going to have to fork to get my additions in place, I thought it would be an opportune moment to refactor
the library along the way. There were always some things about it that bothered me.

Given that my primary use case for this library is to support the SleepIQ
integration for HomeAssistant, a big reason for the massive revamp
was to make it asynchronous (fast!) as well as to expose some
data and new method calls that will make the integration cooler.

It is not particularly backwards compatible with sleepyq, in large part because
nearly every method is async now.

### Installation
The best method is via pip:
```shell script
pip install sleepyq2
```

### API Reference
API documentation is automatically generated by pdoc3 and included in
the html directory.

There's room for improvement and I will work on that when I can.
spiderutil 0.1.8
Utilities for spider.
License: MIT
Requires Python: >=2.7, !=3.0.*, !=3.1.*, !=3.2.*, <4

# Spider Utility

![Version](https://img.shields.io/pypi/v/spiderutil)
![Download](https://img.shields.io/pypi/dm/spiderutil)
![License](https://img.shields.io/pypi/l/spiderutil)
![Status](https://img.shields.io/pypi/status/spiderutil)

Utilities for spider.

## Features

* Database connector
* Local file path generator
* Network session
* Data structure
* Log
* Exception

## Installation

```bash
pip install spiderutil
```

## Documentation

Still working...

## Examples

Still working...

## How to contribute

Open a [new issue]() when you have questions, advices, or you encounter a bug.

## Recommend packages

### Parsers

* [beautifulsoup4](https://www.crummy.com/software/BeautifulSoup/bs4/doc/): parse the webpage like a tree.

```bash
pip install beautifulsoup4
```

* [scrapy/parsel](https://github.com/scrapy/parsel): Parse webpage with XPath or CSS selectors.

```bash
pip install parsel
```

### Encoding and Decoding

* [google/brotli](https://github.com/google/brotli/tree/master/python): decode brotli encoding.

```bash
pip install brotli
```

### Database 

* [SQLAlchemy](https://github.com/sqlalchemy/sqlalchemy/): Process the SQL statement like object

```bash
pip install SQLAlchemy
```

* [PyMySQL](https://github.com/PyMySQL/PyMySQL): Connect to MySQL

```bash
pip install pymysql
```

* [mkleehammer/pyodbc](https://github.com/mkleehammer/pyodbc): Connect to Microsoft SQL Server

```bash
pip install pyodbc
```

In addition to: [level12/sqlalchemy_pyodbc_mssql](https://github.com/level12/sqlalchemy_pyodbc_mssql).