在这里添加简短描述!
sparklet的Python项目详细描述
火花
在这里添加简短描述!在
说明
你的项目的详细描述在这里。。。在
安装
为了建立必要的环境:
- 在conda的帮助下创建一个
sparklet
环境,
在conda env create -f environment.yaml
- 激活新环境 ^{pr2}$ 在
- 安装
sparklet
时使用:
在python setup.py install # or `develop`
可选且仅在git clone
之后需要一次:
- 在
安装多个pre-commitgit挂钩:
pre-commit install
并检查
在.pre-commit-config.yaml
下的配置。git commit
的-n, --no-verify
标志可用于暂时停用预提交钩子。在 - 在
安装nbstripoutgit钩子以删除已提交笔记本的输出单元格:
nbstripout --install --attributes notebooks/.gitattributes
这有助于避免由于笔记本中的绘图而产生较大的差异。 一个简单的
在nbstripout --uninstall
将还原这些更改。在
然后查看scripts
和{
依赖性管理和再现性
- 始终在
environment.yaml
中更新抽象(未固定)依赖项,并最终 如果您以后想通过pip
发送并安装软件包,请在setup.cfg
中。在 - 创建具体的依赖项作为
environment.lock.yaml
,以便精确复制 环境:
对于多操作系统开发,请考虑在导出期间使用conda env export -n sparklet -f environment.lock.yaml
--no-builds
。在 - 使用以下命令更新当前环境中的新
environment.lock.yaml
:
在conda env update -f environment.lock.yaml --prune
项目组织机构
├── AUTHORS.rst <- List of developers and maintainers.
├── CHANGELOG.rst <- Changelog to keep track of new features and fixes.
├── LICENSE.txt <- License as chosen on the command-line.
├── README.md <- The top-level README for developers.
├── configs <- Directory for configurations of model & application.
├── data
│ ├── external <- Data from third party sources.
│ ├── interim <- Intermediate data that has been transformed.
│ ├── processed <- The final, canonical data sets for modeling.
│ └── raw <- The original, immutable data dump.
├── docs <- Directory for Sphinx documentation in rst or md.
├── environment.yaml <- The conda environment file for reproducibility.
├── models <- Trained and serialized models, model predictions,
│ or model summaries.
├── notebooks <- Jupyter notebooks. Naming convention is a number (for
│ ordering), the creator's initials and a description,
│ e.g. `1.0-fw-initial-data-exploration`.
├── references <- Data dictionaries, manuals, and all other materials.
├── reports <- Generated analysis as HTML, PDF, LaTeX, etc.
│ └── figures <- Generated plots and figures for reports.
├── scripts <- Analysis and production scripts which import the
│ actual PYTHON_PKG, e.g. train_model.
├── setup.cfg <- Declarative configuration of your project.
├── setup.py <- Use `python setup.py develop` to install for development or
| or create a distribution with `python setup.py bdist_wheel`.
├── src
│ └── sparklet <- Actual Python package where the main functionality goes.
├── tests <- Unit tests which can be run with `py.test`.
├── .coveragerc <- Configuration for coverage reports of unit tests.
├── .isort.cfg <- Configuration for git hook that sorts imports.
└── .pre-commit-config.yaml <- Configuration of pre-commit git hooks.
注意
这个项目是使用PyScaffold 3.2.3和dsproject extension0.4建立的。 有关PyScaffold的详细信息和使用信息,请参见https://pyscaffold.org/。在
- 项目
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