Aruba Central Python Package Index SDK
Aruba Central is an unified cloud-based network management and configuration platform for campus, branch, remote and data center networks. There are various needs for automation and programmability like automating repetitive tasks, configuring multiple devices, monitoring and more. This python package is to programmatically interact with Aruba Central via REST APIs.
This part of the documentation covers all the interfaces of Requests. For parts where Requests depends on external libraries, we document the most important right here and provide links to the canonical documentation.
Requests is an elegant and simple HTTP library for Python, built for human beings.
Requests allows you to send HTTP/1.1 requests extremely easily. There’s no need to manually add query strings to your URLs, or to form-encode your POST data. Keep-alive and HTTP connection pooling are 100% automatic, thanks to urllib3.
Beloved Features:
- Requests is ready for today’s web.
- Keep-Alive & Connection Pooling
- International Domains and URLs
- Sessions with Cookie Persistence
- Browser-style SSL Verification
- Automatic Content Decoding
- Basic/Digest Authentication
- Elegant Key/Value Cookies
- Automatic Decompression
- Unicode Response Bodies
- HTTP(S) Proxy Support
- Multipart File Uploads
- Streaming Downloads
- Connection Timeouts
- Chunked Requests
- .netrc Support
Requests officially supports Python 2.7 & 3.6+, and runs great on PyPy.
It’s vital to test new technology before rolling it out into your production environment. I like to use Python virtual environments provided by the venv module for developing and testing Ansible playbooks and features. Instead of using the default Python and Ansible commands installed on your system, you can easily set up multiple Python environments and test different versions of Ansible and its component libraries.
Virtual environments are like a virtual machine or Linux chroot, but they create an isolated structure of lightweight directories separated from actual Python system directories. That means you can have different sets of Python environments, each with different versions of modules, files, or configurations.
Ansible is based on Python and leverages many Python modules and plugins. When you test something new, it could require you to update a module that your Ansible installation depends on. Upgrading a component that your production environment depends on defeats the purpose of testing. Still, you can have different versions of Ansible and other important Python modules in a dedicated test directory with a virtual environment.
Ansible Tower 3.0 and later uses virtualenv. Virtualenv creates isolated Python environments to avoid problems caused by conflicting dependencies and differing versions. Virtualenv works by simply creating a folder which contains all of the necessary executables and dependencies for a specific version of Python. Ansible Tower creates two virtualenvs during installation–one is used to run Tower, while the other is used to run Ansible. This allows Tower to run in a stable environment, while allowing you to add or update modules to your Ansible Python environment as necessary to run your playbooks. For more information on virtualenv, see the Python Guide to Virtual Environments and the Python virtualenv project itself.
By default, the virtualenv is located at /var/lib/awx/venv/ansible on the file system but starting with Ansible Tower 3.5, you can create your own custom directories and use them in inventory imports. This allows you to choose how you run your inventory imports, as inventory sources use custom virtual environments.
Tower also pre-installs a variety of third-party library/SDK support into this virtualenv for its integration points with a variety of cloud providers (such as EC2, OpenStack, Azure, etc.) Periodically, you may want to add additional SDK support into this virtualenv, which is described in further detail below.
This repo hosts the openstack.cloud Ansible Collection.
The collection includes the Openstack modules and plugins supported by Openstack community to help the management of Openstack infrastructure.
Providers are a logical abstraction of an upstream API. They are responsible for understanding API interactions and exposing resources.
GitPython is a python library used to interact with git repositories, high-level like git-porcelain, or low-level like git-plumbing.
It provides abstractions of git objects for easy access of repository data, and additionally allows you to access the git repository more directly using either a pure python implementation, or the faster, but more resource intensive git command implementation.
The object database implementation is optimized for handling large quantities of objects and large datasets, which is achieved by using low-level structures and data streaming.
Tinkerforge ist der günstige Mess- und Steuerungsbaukasten, der die Umsetzung eigener Projekte radikal vereinfacht. Dazu werden die benötigten Module einfach zusammengesteckt und über eine intuitive API, die für viele Programmiersprachen zur Verfügung steht, vom Anwender gesteuert. Durch die hohe Abstraktion steht dabei die Aufgabe des Anwenders im Fokus, nicht die technische Umsetzung. Tinkerforge ist Open Source und Made in Germany.
docopt creates beautiful command-line interfaces
messbereich: 0,045-40 mt
auflösung: 0,01mm (0,00001 mt)
messgenauigkeit (standard abweichung): ± 2.mm (10 mt) größer als 10 mt formel ± 2 + 0,05 * (D-10), und d ist der abstand
abstand einheit: m
Laser typ: 620-690nm
Laser klasse: klasse II, < 1 mW(B-niveau)
einzelmessung zeit: 0,25 sekunden
Spot durchmesser im abstand m: 6mm @ 10 mt, 30mm @ 50
betriebstemperatur:-0 ~ + 40 c
lagertemperatur:-20 ~ + 60 c
Click is a Python package for creating beautiful command line interfaces in a composable way with as little code as necessary. It’s the “Command Line Interface Creation Kit”. It’s highly configurable but comes with sensible defaults out of the box.
It aims to make the process of writing command line tools quick and fun while also preventing any frustration caused by the inability to implement an intended CLI API.
Click in three points:
arbitrary nesting of commands
automatic help page generation
supports lazy loading of subcommands at runtime