Napy
Everything you frequently use when you use Python.
Prologue
I often need to configure a new Python development environment. Whether it is to help others or for myself, it is very troublesome to manage packages with pip. Besides, there are fascinating and impressive ipython extensions, and every installation of them has to bother Google again.
Therefore, I created this napy.
This package is still under development, and although is only for myself now, you can use it as you like.
Introduction
Napy includes some of the packages I frequently use, such as requests, for crawlers; sympy for
mathematics. Also, napy has some ipython extensions I write. A template Napy also has that I often
use (of course, it's still straightforward now). Hope you like it.
Due to the .dir-local.el contains (org-html-klipsify-src . nil), it is warning that it is not safe.
Usage
Template
Crawler
$ napy template --help Usage: template [options] Options: -c, --category[=CATEGORY] Category of template -o, --output[=OUTPUT] Output file (default: "stdout") -y, --yes Confirmation -h, --help Display this help message -q, --quiet Do not output any message -V, --version Display this application version --ansi Force ANSI output --no-ansi Disable ANSI output -n, --no-interaction Do not ask any interactive question -v|vv|vvv, --verbose[=VERBOSE] Increase the verbosity of messages: 1 for normal output, 2 for more verbose output and 3 for debug Help: Template command line tool.
It will generate this:
from requests_html import HtmlSession as s import requests as req def crawler() -> None: """Crawler.""" pass if __name__ == "__main__": pass
More
Still under development.
Packages
Normal
- better_exceptions
- Pretty and helpful exceptions, automatically.
- pendulum
- Python datetimes made easy.
- tqdm
- Fast, Extensible Progress Meter.
Science
- jupyter :: Jupyter Notebook + IPython
- Jupyter metapackage. Install all the Jupyter components in one go.
- numpy
- NumPy: array processing for numbers, strings, records, and objects
- pandas
- Powerful data structures for data analysis, time series, and statistics
- sympy
- Computer algebra system (CAS) in Python
Crawler
- requests
- Python HTTP for Humans.
- requests_html
- HTML Parsing for Humans.
- BeautifulSoup4
- Screen-scraping library
Development
- cleo
- Cleo allows you to create beautiful and testable command-line interfaces.
Epoligue
History
0.1.1
Use README.md instead of README.org
0.1.0
- The beginning of everything