# wp-dataops-pyutil
This provides **`wpdatautil`**, a Python 3.8 package with specific reusable utility functions for data processing.
A limited version of this readme which is published to PyPI is [available separately](README_PyPI.md).
[![cicd badge](https://github.com/wqpredtech/wp-dataops-pyutil/workflows/cicd/badge.svg?branch=master)](https://github.com/wqpredtech/wp-dataops-pyutil/actions?query=workflow%3Acicd+branch%3Amaster)
| [GitHub Releases/Changelog](https://github.com/wqpredtech/wp-dataops-pyutil/releases) | [PyPI release](https://pypi.org/project/wpdatautil/) |
|-|-|
## Installation
`pip install -U wpdatautil` will install the package but intentionally not any third-party requirements.
Given that the third-party package requirements can be numerous, and not all of them are relevant to most users, they can be installed as needed by a user.
## Usage
The implemented utilities are broadly organized by their primary third-party or builtin package requirement.
For example, `.pandas` contains utilities which primarily require the `pandas` package.
Similarly, `.boto3.s3path` contains utilities which require both the `boto3` and `s3path` packages.
## Development
### Setup
To set up the project locally:
1. Install Python 3.8
1. Clone the repo and setup a corresponding new IDE project. Use the IDE to create a virtual environment for this repo and project.
1. Configure the IDE to use a max line length of 180. This is also defined in various static analyzer configuration files in the project.
It facilitates the use of descriptive variable names while ensuring that lines still display fully.
1. Run `make setup`, and ensure an exitcode of 0.
### Contribute
To contribute to this repository:
1. Develop the changes in a feature branch with 100% line test coverage.
1. Run `make prep`. Ensure the build is passing.
1. Create a pull request into `master` and assign it to a [codeowner](.github/CODEOWNERS).
### Publish
To publish the package to PyPI:
1. Ensure the commits which are to be released are merged into `master`, and the build is passing.
1. Create and publish a [release on GitHub](https://github.com/wqpredtech/wp-dataops-pyutil/releases) with a [semver](https://semver.org/) tag, e.g. "v0.1.2", including a changelog since the last release.
This triggers the [release workflow](https://github.com/wqpredtech/wp-dataops-pyutil/actions?query=workflow%3Acicd+event%3Arelease) which publishes the release to PyPI.
If there is a noticeable delay in triggering the workflow, check [GitHub Status](https://www.githubstatus.com/).
1. Confirm that the published version is [listed on PyPI](https://pypi.org/project/wpdatautil/#history).
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资源分类:Python库 所属语言:Python 资源全名:wpdatautil-0.3.0.tar.gz 资源来源:官方 安装方法:https://lanzao.blog.csdn.net/article/details/101784059
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wpdatautil-0.3.0.tar.gz (32个子文件)
wpdatautil-0.3.0
PKG-INFO 1KB
pyproject.toml 63B
wpdatautil
s3path.py 406B
pandas
numpy.py 1KB
smart_open.py 3KB
__init__.py 4KB
pybase64.py 1KB
mgzip.py 2KB
pyarrow.py 789B
pathlib.py 450B
numpy.py 1KB
object.py 411B
humanfriendly.py 372B
list.py 2KB
boto3
s3path.py 3KB
__init__.py 1KB
polars
smart_open.py 3KB
__init__.py 0B
__init__.py 0B
inspect.py 306B
dict.py 385B
mgzip.py 2KB
logging
__init__.py 523B
psutil.py 2KB
timeit.py 499B
setup.cfg 880B
setup.py 1KB
wpdatautil.egg-info
PKG-INFO 1KB
SOURCES.txt 768B
top_level.txt 11B
dependency_links.txt 1B
README.md 3KB
共 32 条
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