終究得面對 JupyterLab 延伸之安裝考察及測試驗證也◎
Other Requirements
Lantern relies on a handful of JupyterLab extensions to operate:
jupyter labextension install @jupyter-widgets/jupyterlab-manager
jupyter labextension install plotlywidget
jupyter labextension install @jupyterlab/plotly-extension
jupyter labextension install jupyterlab_bokeh
jupyter labextension install qgrid
jupyter labextension install @jpmorganchase/perspective-jupyterlab
※ 太多 Deprecated warnning
jupyter labextension install ipysheet
jupyter labextension install lineup_widget
※ maybe not working
The following are for work in-progress on master:
jupyter labextension install bqplot
※ not yet
『大紅燈籠』高高卦，只是說明︰
『擬態』 Mimesis 3.1.0 已經走進 Python 3.6+ 天空裡。
或將暫時與此
Test data generation
Test data generation, an important part of software testing, is the process of creating a set of data for testing the adequacy of new or revised software applications. It may be the actual data that has been taken from previous operations or artificial data created for this purpose. Test Data Generation is seen to be a complex problem and though a lot of solutions have come forth most of them are limited to toy programs. The use of dynamic memory allocation in most of the code written in industry is the most severe problem that the Test Data Generators face as the usage of the software then becomes highly unpredictable, due to this it becomes harder to anticipate the paths that the program could take making it nearly impossible for the Test Data Generators to generate exhaustive Test Data. However, in the past decade significant progress has been made in tackling this problem better by the use of genetic algorithms and other analysis algorithms. Moreover, Software Testing is an important part of the Software Development Life Cycle and is basically labor-intensive. It also accounts for nearly one third of the cost of the system development. In this view the problem of generating quality test data quickly, efficiently and accurately is seen to be important.[1]
無緣乎？因期望時流回反，故而追跡
，尋求有無落腳之處！
mimesis 2.1.0
pip install mimesis==2.1.0
Project description
Mimesis is a fast and easy to use library for Python programming language, which helps generate synthetic data for a variety of purposes in a variety of languages. This data can be particularly useful during software development and testing. For example, it could be used to populate a testing database, create beautiful JSON and XML files, anonymize data taken from a production service, etc.
This library offers a number of advantages over other similar libraries:
- Performance. Significantly faster than other similar libraries.
- Completeness. Strives to provide many detailed providers that offer a variety of data generators.
- Simplicity. Does not require any modules other than the Python standard library.
sudo pip3 install mimesis==2.1.0
rock64@rock64:~$ python3
Python 3.5.3 (default, Sep 27 2018, 17:25:39)
[GCC 6.3.0 20170516] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import mimesis
>>> from mimesis import Person
>>> person = Person('en')
>>> person.full_name()
'Bob Knowles'
>>>
或許天道和人世通常酬勤的呀◎
