semvec/pypi-packages huggingface dataset:
spark-datiofilesystem-tools 0.1.7
spark_datiofilesystem_tools
Keywords: spark, hdfs, dfs, datiofilesystem

# spark_datiofilesystem_tools

[![Github License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://opensource.org/licenses/Apache-2.0)
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spark_hdfs_tools is a Python library that implements hdfs filesystem in sandbox

## Installation

The code is packaged for PyPI, so that the installation consists in running:


## Usage

wrapper run hdfs filesystem

## Sandbox
## Installation
```sh
!yes| pip uninstall spark-datiofilesystem-tools
```

```sh
pip install spark-datiofilesystem-tools --user --upgrade
```

## IMPORTS
```sh
import os
import pyspark
from spark_datiofilesystem_tools import HDFSDatio


```

## Variables
```sh

```







## License

[Apache License 2.0](https://www.dropbox.com/s/8t6xtgk06o3ij61/LICENSE?dl=0).

## New features v1.0

## BugFix

- choco install visualcpp-build-tools

## Reference

- Jonathan Quiza [github](https://github.com/jonaqp).
- Jonathan Quiza [RumiMLSpark](http://rumi-ml.herokuapp.com/).
clapdb 1.0.0
python client for clapdb
Requires Python: >=3.11

# clapdb-python-client

A basic database driver for connection ClapDB to Python, Superset
* SQLAlchemy 1.4 (limited feature set)
* Superset Connector

## Installation

`pip install clapdb`

clapdb client need Python 3.11 or higher

## Superset Connectivity

### for ClapDB instance

`clapdb+http://{user}.{tenant}:{password}@{host}:{port}/{database}?{timeout=30}`

> The timeout is a floating point number in seconds.

### for ClapDB lambda

`clapdb+https://{user}.{tenant}:{password}@{data_api_url_endpoint}/{database}?stage=production&{timeout=30}`

> The parameters can be found from ClapDB credentials [https://clapdb.com/docs/#configure-your-aws-credentials]

## SQLAlchemy

ClapDB incorporates a minimal SQLAlchemy implementation (without any ORM features) for compatibility with Superset. It has only been tested against SQLAlchemy versions 1.4.x, and is unlikely to work with more complex SQLAlchemy applications.

The interval type in ClapDB is implemented based on PostgreSQL, which calculation rule is special. Converting it to Python timedelta may result in information loss. Therefore, we return interval as string type.