you are in a group/association where you take your meetings notes (PV) in a pad (etherpad(-lite))
you don't have any place to store this information
meetings notes hang around with not place to be put, start to be lost, aren't visible or easily findable
Then PVPADs is a tool for you and your group/association. It is a very simple website where you put a pad URL and a date (and more stuff if needed) and PVPADs will store the pad contents and renders it in html and list it chronologically so everything is at the same place and everyone can reads it easily.
PVPADs is also multi organisations, meaning that you can handle several organisations on the same instance and filter organisations based on the URL.
It often happens that we need to find the default port number for a specific service, or what service is listening on a given port. The tool uses the Iana.org website to get the official list of ports. A private script has been created to fetch regularly the website and update the ports.json file. For this reason, an update command will be created in a future version.
Krill are filter feeders. True to its namesake, krill filters feeds. It is not picky about its diet, and will happily consume RSS, Atom, CDF and even Twitter feeds (no credentials required!). It aggregates feed items from all sources you specify, filters out those that interest you, and displays them as a live stream of clean, legible command line output. || Un petit outil CLI qui dépote
The author hesitated for a long time before publishing this article, because there are strong ethical issues. Documenting the effects of censorship can be seen as helping censors. For instance, if measurements show that censorship is very limited in practice, it may motivate some authorities to increase the pressure and its negative consequences. But I believe that censors are already better informed than the average citizen and that it is necessary to have factual information in order to have an informed debate in democracies.
Another big ethics issue concerns the measurements themselves. Is there a risk of endangering people who host a probe by doing DNS lookups for illegal/forbidden/questionable things (for instance DNS lookup for a porn site from a probe in Iran)? Today, the DNS is typically "under the radar" for most surveillance activities. Doing an HTTP request for an illegal site attracts attention to you in some countries (and it is one of the reasons why RIPE Atlas probes do not perform HTTP queries for arbitrary URLs), but it does not seem to be the case (yet) for DNS requests. (See RFC 7626, "DNS Privacy Considerations".)
Now that Rust 1.0 is out and quite stable, I thought it might be interesting to write an introduction to Rust for Python programmers. This guide goes over the basics of the language and compares different constructs and how they behave.
The following is a collaboration piece between Cam Linke, co-founder of Startup Edmonton, and the folks at Real Python.
Updated 02/22/2015: Added Python 3 support.
Welcome! Today we’re going to start building a Flask app that calculates word-frequency pairs based on the text from a given URL. This is a full-stack tutorial.
Part One: Setup a local development environment and then deploy both a staging environment and a production environment on Heroku. (current)
Part Two: Setup a PostgreSQL database along with SQLAlchemy and Alembic to handle migrations.
Part Three: Add in the back-end logic to scrape and then process the counting of words from a webpage using the requests, BeautifulSoup, and Natural Language Toolkit (NLTK) libraries.
Part Four: Implement a Redis task queue to handle the text processing.
Part Five: Setup Angular on the front-end to continuously poll the back-end to see if the request is done.
Part Six: Push to the staging server on Heroku – setting up Redis, detailing how to run two processes (web and worker) on a single Dyno.
Part Seven: Update the front-end to make it more user-friendly.
Part Eight: Add the D3 library into the mix to graph a frequency distribution and histogram.
Stallion is a Python Package Manager interface created to provide an "easy-to-use" visual and also a command-line interface for Pythonistas. Today we have many nice distribution utilities like pip, distribute, etc, but we don't have a nice visual approach to inspect current installed packages, show projects metadata, check for PyPI updates, etc.
There are tons of Python packages out there. So many that no one man or woman could possibly catch them all. PyPi alone has over 47,000 packages listed!
Recently, with so many data scientists making the switch to Python, I couldn't help but think that while they're getting some of the great benefits of pandas, scikit-learn, and numpy, they're missing out on some older yet equally helpful Python libraries.
In this post, I'm going to highlight some lesser-known libraries. Even you experienced Pythonistas should take a look, there might be one or two in there you've never seen!
Falcon is a minimalist WSGI library for building speedy web APIs and app backends. We like to think of Falcon as the Dieter Rams of web frameworks.
When it comes to building HTTP APIs, other frameworks weigh you down with tons of dependencies and unnecessary abstractions. Falcon cuts to the chase with a clean design that embraces HTTP and the REST architectural style.
Goose was originally an article extractor written in Java that has most recently (aug2011) been converted to a scala project. This is a complete rewrite in python. The aim of the software is to take any news article or article-type web page and not only extract what is the main body of the article but also all meta data and most probable image candidate.
Souvent considéré comme désuet, SNMP est toujours omniprésent pour interagir avec des équipements réseau. Pour la supervision, il permet d’exposer diverses métriques telles que les compteurs liés aux interfaces réseau. Il permet également d’interagir sur la configuration des équipements.
Arrow is a Python library that offers a sensible, human-friendly approach to creating, manipulating, formatting and converting dates, times, and timestamps. It implements and updates the datetime type, plugging gaps in functionality, and provides an intelligent module API that supports many common creation scenarios. Simply put, it helps you work with dates and times with fewer imports and a lot less code.