معرفی شرکت ها
datamachine-0.1.1
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مشاهده بیشترتوضیحات
Modular Notebooks
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | datamachine-0.1.1 |
| نام | datamachine |
| نسخه کتابخانه | 0.1.1 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | Dave Killough |
| ایمیل نویسنده | Dave Killough <dave@benevolentmachines.org> |
| آدرس صفحه اصلی | https://pypi.org/project/datamachine |
| آدرس اینترنتی | https://pypi.org/project/datamachine/ |
| مجوز | - |
<p align="left" >
<img src="https://storage.googleapis.com/benevolentmachines/datamachine.svg"
title="datamachine">
</p>
## Modular Notebooks
Imagine an easy way to reuse Python notebooks in the cloud. datamachine is a useful Python package that enables you to import notebooks as modules and execute Python notebooks with parameters. With datamachine, you can load notebooks from various sources such as local files, Colab links, and Github links, and then execute or import them with ease. You can also organize notebooks into libraries that use simple codes for easy access to commonly used notebooks.
<p align="left" >
<img src="https://storage.googleapis.com/benevolentmachines/dm_overview.png">
</p>
## Features
- **Import notebooks as modules**: Importing notebooks as modules is a breeze with datamachine. You can import notebooks from various sources such as local files, Colab links, Github links, and HTTP links.
- **Execute notebooks with parameters**: You can execute cloud notebooks with parameters, which is particularly useful when you want to run a notebook multiple times with different inputs.
- **Libraries**: datamachine supports user-defined libraries that will make your reusable notebook modules much easier to publish and use by others.
- **Notebook sources**: You can currently source public notebooks from GitHub, Colab, and notebooks in your local file system. I plan on adding secure notebook access and extending storage options to S3, Azure, GCP, and other cloud-based systems. Please add an issue to GitHub if you're intersted in support for a particular source.
## Installation
To install datamachine, run the following command:
``` python
pip install datamachine
```
## Importing datamachine
Once you've installed datamachine, you can import it. The convention is to name the module instance `dm`.
```python
import datamachine as dm
```
### Notebook Locations
datamachine currrently supports notebook links from Github, Google Colab, local file paths, and public `https` links with raw content.
### Importing a Notebook as a Module
To import a notebook as a module, use the `import_notebook` function:
```python
nbo = dm.import_notebook(
"https://colab.research.google.com/drive/1y7x3BDkmaz6k93QjENanKHudLV8xB96Q?usp=sharing",
)
```
This function imports the notebook located at the specified location and returns a module reference like the native import command. The Colab notebook used above provides sample analytics that can be accessed by using methods in the module. For instance, you could run the following function
```python
nbo.monthly_rulings()
```
<p align="left" >
<img src="https://storage.googleapis.com/benevolentmachines/dm_module2.gif">
</p>
### Executing a Notebook
To execute a notebook with parameters, use the `execute_notebook` function:
```python
import datamachine as dm
dm.execute_notebook("execute.ipynb",
html="output.html",
params={
"EIN": "200549531",
"TYPE": "summary"
},
)
```
This function executes the notebook located at `"execute.ipynb"` with the parameter `"EIN"`
set to `"200549531"`. The output is saved in an HTML file named `"output.html"`.
In order to receive the EIN and TYPE parameters in the executed notebook, simply invoke
the `execute_params` function with a passed dictionary containing the parameters.
This function provides the test values when you're directly running the notebook,
and uses the passed values when invoked via `execute_notebook`.
```python
import datamachine as dm
params = dm.execute_params({
"EIN": "454547709",
"TYPE": "detail"
})
EIN = params["EIN"]
```
## Conclusion
datamachine is a powerful tool for anyone who wants to reuse Python notebooks. With its flexible features and easy-to-use commands, datamachine makes it easy to execute and import notebooks from various sources, store collections of code and their corresponding links in a library, and organize your code with an index. So why wait? Install datamachine today and take your notebook experience to the next level!
زبان مورد نیاز
| مقدار | نام |
|---|---|
| >=3.7 | Python |
نحوه نصب
نصب پکیج whl datamachine-0.1.1:
pip install datamachine-0.1.1.whl
نصب پکیج tar.gz datamachine-0.1.1:
pip install datamachine-0.1.1.tar.gz