iterm2 Clear all Sessions on Current Tab

On mac, save this as /Users/[username]/Library/Application Support/iTerm2/Scripts/AutoLaunch/clear_current_tab.py

#!/usr/bin/env python3

import asyncio
import iterm2
import time

async def main(connection):
    app = await iterm2.async_get_app(connection)
    @iterm2.RPC
    async def clear_current_tab():
        code = b'\x1b' + b']1337;ClearScrollback' + b'\x07'
        window = app.current_terminal_window
        tab = window.current_tab
        for session in tab.sessions:
            await session.async_inject(code)
    await clear_current_tab.async_register(connection)

iterm2.run_forever(main)

Now bind it to a keystroke in Prefs > Keys by selecting the action Invoke Script Function and giving it the invocation clear_current_tab().

Python Packaging

Following this quickstart, this and this.

1. Pick a name and make sure it is unique after checking on pypi, you might want to make this public later on.

2. Create the scaffolding.
maestroclient
├── LICENSE.txt
├── README.txt
├── maestroclient
│   └── __init__.py
└── setup.py

3. Edit setup.py to contain...
from setuptools import setup

setup(name='maestroclient',
      version='0.1',
      description='Client for accessing Maestro API',
      author='Sam Dela Cruz',
      author_email='s@gmail.com',
      license='MIT',
      packages=['maestroclient'],
      install_requires=[
          'requests',
          'urllib3',
      ],
      zip_safe=False)

4. Create a distribution.
$ python3 setup.py sdist

5. Publish on pypi, just so the project name can be reserved to pypi.
$ twine upload dist/*

6. After building the package, if publishing to pypi is not desired, the package can also be hosted anywhere and can be installed using pip as follows...
$ pip3 install http://whatever.web/maestroclient-0.1.tar.gz

Celery Tasks Parallel and Chained Execution Workflow

In celery, it is very easy to chain and parallelize execution of tasks, e.g. to satisfy this example workflow...

      _____
     |task1|      1. exec task1
    /      \
 __/__    __\__
|task2|  |task3|  2. parallel task1 & task2
   \        /
    \ _____/
     |task4|      3. exec task4 when both task1 & task2 are done

from celery import chain, group, chord
from orchestrator.tasks.host_tasks import acquire_hosts, prepare_hosts, return_hosts
from orchestrator.tasks.job_tasks import start_job, stop_job
from orchestrator.tasks.vcenter_tasks import acquire_vcenter, return_vcenter


def start_performance_run_workflow(job_id):
    print('Starting performance run workflows for job %s' % job_id)
    # The effect of this chain, is that only the first one is routed
    # to the "regular.priority" queue
    # subsequent tasks are routed to "celery" default queue
    workflow = chain(
        acquire_hosts.si(job_id),
        chord(
            (prepare_hosts.si(job_id), acquire_vcenter.si(job_id)),
            start_job.si(job_id)
        )
    ).apply_async(queue="regular.priority")

Django Development Production Settings

I choose the 2nd solution from this post

Dir structure:
[myapp]$ tree
.
├── __init__.py
├── settings
│   ├── __init__.py
│   ├── defaults.py
│   ├── development.py
│   ├── production.py
│   └── staging.py

### __init.py__
from myapp.settings.development import *

### defaults.py
### sensible choices for default settings

### dev.py
from myapp.settings.defaults import *
DEBUG = True
### other development-specific stuff

### production.py
from myapp.settings.defaults import *
DEBUG = False
### other production-specific stuff

### staging.py
from myapp.settings.defaults import *
DEBUG = True
### other staging-specific stuff

Django with Postgres on Mac

1. Create virtual env following this post
2. Install django
(my_env) $ pip3 install psycopg2
(my_env) $ pip3 install django
3. Create django project
(my_env) $ django-admin startproject sample_project
(my_env) $ python3 manage.py runserver
4. Install postgres following this post
5. Create database
$ createdb -U postgres testdb
6. Modify settings in django
DATABASES = {
    'default': {
        'ENGINE': 'django.db.backends.postgresql',
        'NAME': 'testdb',
        'USER': 'postgres',
        'PASSWORD': '',
        'HOST': 'localhost',
        'PORT': '5432',
    }
}
7. Migrate
$ python3 manage.py migrate
8. Create superuser
$ python3 manage.py createsuperuser

Install Python 3.6 on MacOS

Generally followed this post

I. Install brew
1. Install Xcode from the App Store
2. Install Xcode’s separate Command Line Tools app
$ xcode-select --install
3. Install and setup homebrew
$ /usr/bin/ruby -e "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install)"
4. Make sure brew is in PATH
$ vi ~/.bash_profile
export PATH=/usr/local/bin:$PATH
5. Source it
$ source ~/.bash_profile
6. Try brew
$ brew doctor
Your system is ready to brew.

II. Install Python
$ brew search python
$ brew install python3
$ python3 --version
Python 3.6.2
To install a python package
$ pip3 install package_name
To upgrade python
$ brew update
$ brew upgrade python3

III. Creating Virtual environments
$ mkdir sample_project
$ cd sample_project
$ python3.6 -m venv my_env
$ source my_env/bin/activate

Install Python 2.7 and Python 3.5 alongside Python 2.6 on CentOS 6.5

I got mostly from this post.

Install Python 2.7 and Python 3.5 alongside Python 2.6 on CentOS 6.5

1. Prep
# yum groupinstall "Development tools"
# yum install zlib-devel bzip2-devel openssl-devel ncurses-devel sqlite-devel readline-devel tk-devel gdbm-devel db4-devel libpcap-devel xz-devel

2. Compile as shared library - add /usr/local/lib on /etc/ld.so.conf
# vi /etc/ld.so.conf
include ld.so.conf.d/*.conf
/usr/local/lib
# ldconfig

3.  Install python on  /usr/local
# Python 2.7.12:
wget http://python.org/ftp/python/2.7.12/Python-2.7.12.tar.xz
tar xf Python-2.7.12.tar.xz
cd Python-2.7.12
./configure --prefix=/usr/local --enable-unicode=ucs4 --enable-shared 
make && make altinstall

# Python 3.5.2:
wget http://python.org/ftp/python/3.5.2/Python-3.5.2.tar.xz
tar xf Python-3.5.2.tar.xz
cd Python-3.5.2
./configure --prefix=/usr/local --enable-shared
make && make altinstall

4. Run ldconfig again
# ldconfig

5. Install python virtualenv
# yum install python-virtualenv

6. Create virtualenv for python2.7
$ mkdir project_home
$ cd project_home
$ virtualenv -p /usr/local/bin/python2.7 .venv2.7

7. Create virtualenv for python3.5
$ mkdir project_home
$ cd project_home
$ pyvenv-3.5 .venv3.5
(this seems to work even though I get an error message:
Unable to symlink '/usr/local/bin/python3.5' to '/auto/home/delacs/python_projects_on_perf_utils/test_project/.venv3.5/bin/python3.5')

Django Notes

1. Backup and seed data using fixtures
# Save data
$ python manage.py dumpdata --format=json myapp > myapp/fixtures/initial_data.json
# Load data
$ python manage.py loaddata vlanapi/fixtures/initial_data.json

2. Open python shell - interactive console
$ python manage.py shell
Python 2.7.12 (default, Jul  1 2016, 15:12:24) 
[GCC 5.4.0 20160609] on linux2
Type "help", "copyright", "credits" or "license" for more information.
(InteractiveConsole)
>>>

3. Start a project
$ django-admin startproject mysite

4. Start initial migration
$ python manage.py migrate

5. Start server
$ python manage.py runserver

6. Create an app
$ python manage.py startapp newapp

7. Create and run a migration
$ python manage.py makemigrations
$ python manage.py migrate

Python Notes

1. Booleans
The numbers 0, 0.0, and 0+0j are all False; any other number is True.
The empty string "" is False; any other string is True.
The empty list [] is False; any other list is True.
The empty dictionary {} is False; any other dictionary is True.
The empty set set() is False; any other set is True.
The special Python value None is always False.

2. Working on REPL
Import library
>>> from autoinfra.resource import Client, Ddr, Resource
List all available methods
>>> dir(Client)
['__class__', '__delattr__', '__dict__', '__doc__', '__format__', '__getattribute__', '__hash__', '__init__', '__module__', '__new__', '__reduce__', '__reduce_ex__', '__repr__', '__setattr__', '__sizeof__', '__str__', '__subclasshook__', '__weakref__', '_connect_ssh', 'bring_up_eth', 'configure_ip', 'eth_filter', 'get_eths_details', 'get_eths_via_ifconfig', 'get_eths_via_ip_a', 'get_switch_port_details', 'is_connected', 'is_eth_link_detected', 'send_cmd']
Access docstring on a method
>>> help(Client.get_switch_port_details)

3. Testing
From this post.

$ pip install nose

From root of project run nosetests, this would look for any test under this directory and run it
$ pwd
/auto/home13/delacs/Documents/projects/nextgen/libs/autoinfra
$ nosetests
.....
----------------------------------------------------------------------
Ran 5 tests in 2.659s
OK

To run a single file
$ nosetests -v autoinfra/resources/tests/test_ddr.py
test_get_10g_eths (test_ddr.TestDdr) ... ok
test_se_cmd (test_ddr.TestDdr) ... ok
test_send_cmd (test_ddr.TestDdr) ... ok
----------------------------------------------------------------------
Ran 3 tests in 2.602s

To run a particular test in a file
$ nosetests -v autoinfra/switches/tests/test_cisco.py:TestCisco.test_move_to_vlan_no_nxapi_single
test_move_to_vlan_no_nxapi_single (test_cisco.TestCisco) ... ok
----------------------------------------------------------------------
Ran 1 test in 12.423s
OK

This works when test files have imports like this...
from autoinfra.resources.client import Client

4. Install python 2.7.12 on another directory (/opt/python)
# wget https://www.python.org/ftp/python/2.7.12/Python-2.7.12.tgz
# tar zxf Python-2.7.12.tgz
# cd Python-2.7.12/
# ./configure --prefix=/opt/python
# make
# make install

5. Create a virtual environment
$ sudo yum install python-virtualenv
$ mkdir sample_project
$ cd sample_project
$ virtualenv -p /opt/python/bin/python2.7 .venv

6. Data dumper
>>> from pprint import pprint
>>> pprint(vars(Host.objects.get(name="w3-perfsds-0001")))