skitai 0.28.7

Skitai App Engine

===================
Skitai App Engine
===================

At a Glance
=============

Skitai is a Python WSGI/HTTP Server for UNIX (Developing is possible on win32).

And simple to run:

Install,

.. code:: bash

pip3 install skitai

Create and mount your app,

.. code:: python

# myservice.py

def app (env, start_response):
start_response ("200 OK", [("Content-Type", "text/plain")])
return 'Hello World'

if __name__ == "__main__":
import skitai

skitai.mount ('/', app)
skitai.run (address = "127.0.0.1", port = 5000)

And run.

.. code:: bash

python3 myservice.py


Your app will work for your thousands or miliions of customers.


.. contents:: Table of Contents


What For
===========

Skitai App engine provides one of most simplest way to:

1. Serve WSGI apps like Flask, Django
2. Export RESTful API for your apps or functions
3. Build high performance app/web service with asynchronous backend upstreams & cache control


Introduce
===========

Skitai is a kind of branch of `Medusa Web Server`__ - A High-Performance Internet Server Architecture. Medusa is different from most other servers because it runs as a single process, multiplexing I/O with its various client and server connections within a single process/thread.

Skitai orients light-weight, simplicity and strengthen networking operations with your backend resources keeping very low costs.

- Working as WSGI application server, Web, XML-RPC and reverse proxy and loadbancing server
- Handling massive requests to your backend servers including RESTful API, RPCs and database engines - PostgreSQL_, MongoDB and Redis - with asynchronous manner
- HTTP/2.0 & HTML5 Websocket implemented

Skitai is not a just developing server like some frameworks provides. It is supporsed to work fine under real service situation by alone. And it makes your app take off to the world, just by appending a few lines on your app.

For attaining maximum concurrency, it uses:

- asyncore with event loop for IO concurrency like HTTP/Websocket and database engine connections
- forking for multiple process workers
- multi-threading for blocking jobs if you want

Async supported protocols:

- HTTP/HTTPS, RESTful API and XML/JSON-RPC
- HTTP2 and GRPC
- Websocket

Async supported database engine or NoSQL:

- PostgreSQL
- MongoDB
- Redis
- SQLite3 (sync only, not async )

.. _hyper-h2: https://pypi.python.org/pypi/h2
.. _Flask: http://flask.pocoo.org/
.. _PostgreSQL: http://www.postgresql.org/
.. __: http://www.nightmare.com/medusa/medusa.html


Installation
=========================

**Requirements**

Python 3.5+

On win32, required `pywin32 binary`_.

.. _`pywin32 binary`: http://sourceforge.net/projects/pywin32/files/pywin32/Build%20219/

On posix, for compiling psycopg2 module, requires theses packages,

.. code:: bash

apt-get install libpq-dev python-dev

**Installation**

With pip

.. code-block:: bash

pip3 install skitai

From git

.. code-block:: bash

git clone https://gitlab.com/hansroh/skitai.git
cd skitai
python3 setup.py install


But generally you don't need install alone. When you install Skitai App Engine, proper version of Skitai App Engine will be installed.


Enginize Your App with Skitai
===============================

Here's a very simple WSGI app,

Basic Usage
------------

Mount Static Directories
````````````````````````````

Your myproject/app.py,

.. code:: python

if __name__ == "__main__":

import skitai

skitai.mount ('/', '/home/www')
skitai.mount ('/uploads', '/var/www/uploads')
skitai.mount ('/uploads/bigfiles', '/data/www/bifgiles')

skitai.run (
address = "127.0.0.1",
port = 5000
)

At command line,

.. code:: bash

python3 app.py

For checking processes,

.. code:: bash

$ ps -ef | grep skitai

ubuntu 25219 1 0 08:25 ? 00:00:00 skitai(myproject/app): master
ubuntu 25221 25219 1 08:25 ? 00:00:00 skitai(myproject/app): worker #0


Mount WSGI App
```````````````````````

.. code:: python

#WSGI App

def app (env, start_response):
start_response ("200 OK", [("Content-Type", "text/plain")])
return 'Hello World'

app.use_reloader = True
app.debug = True

if __name__ == "__main__":

import skitai

skitai.mount ('/', app)
skitai.run (
address = "127.0.0.1",
port = 5000
)

At now, run this code from console.

.. code-block:: bash

python3 app.py

You can access this WSGI app by visiting http://127.0.0.1:5000/.

If you want to allow access to your public IPs, or specify port:

.. code:: python

skitai.mount ('/', app)
skitai.run (
address = "0.0.0.0",
port = 5000
)

skital.mount () spec is:

mount (mount_point, mount_object, app_name = "app", pref = None)

- mount_point
- mount_object: app, app file path or module object

.. code:: python

skitai.mount ('/', app)
skitai.mount ('/', 'app_v1/app.py', 'app')

import wissen
skitai.mount ('/', wissen, 'app')
skitai.mount ('/', (wissen, 'app_v1.py'), 'app')

In case module object, the module should support skitai exporting spec.

- app_name: variable name of app
- pref: run time app config, pref will override app.config


Mount Django App
```````````````````

Basically same as other apps.

Let's assume your Django app project is '/mydjango' and skitai app engine script is '/app.py'.

.. code:: python

pref = skitai.pref ()
pref.use_reloader = True
pref.debug = True

# and mount static dir used bt Django
skitai.mount ("/static", "mydjango/static")

# finally mount django wsgi.py and project root path to append sys.path by path param.
skitai.mount (
"/",
"mydjango/mydjango/wsgi.py",
"application",
pref
)

Note that if app is smae location with django manage.py, you need not path param.

Also note that if you set pref.use_reloader = True, it is possible to replace Django development server (manage,py runserver), But it will work on posix only, because Skitai reloads Django app by restart worker process, Win32 version doesn't support.


Logging and Console Displaying For Developing/Debugging
----------------------------------------------------------

If you do not specify log file path, all logs will be displayed in console, bu specifed all logs will be written into file.

First of all, you should create log directory,

.. code:: bash

sudo mkdir /var/log/skitai
sudo chown ubuntu:ubuntu

Your request log file willl be placed to: */var/log/skitai/ubuntu/<script path hash>/request.log*.

.. code:: python

skitai.mount ('/', app)
skitai.enalbe_file_logging ()
skitai.run (
address = "0.0.0.0",
port = 5000
)

If you also want to view logs through console for spot developing, you run app.py without option.

.. code:: bash

python3 app.py


Run with Process Name
-------------------------

If you give 'name', process name will be changed.

.. code:: python

skitai.mount ('/', app)
skitai.run (name = "myapp")

Your skitai process will be shown as:

.. code:: bash

ubuntu 9815 1 0 16:04 ? 00:00:00 skitai/myapp: master
ubuntu 9816 9815 0 16:04 ? 00:00:03 skitai/myapp: worker #0


Getting Command Line Options and Arguments
----------------------------------------------------

Skitai use short options -d, and long options starts with "--skitai-", then you SHOULD NOT use these options.
Also Skitai use satrt, restart, status, stop in args. then these arguments are removed automatically.

.. code:: python

opts, args = skitai.argopt ("hf:", ["ssl", "debug", "origin="])
for k, v in opts:
if k == "-h":
...
elif k == "-h" or k == "--help":
usage ()
elif k == "--debug":
...

For detail about get_clopt's parameters, see getopt module.


Run with Threads Pool
------------------------

Skitai run defaultly multi-threading mode and number of threads are 4.
If you want to change number of threads for handling WSGI app:

.. code:: python

skitai.mount ('/', app)
skitai.run (
threads = 8
)


Run with Single-Thread
------------------------

If you want to run Skitai with entirely single thread,

.. code:: python

skitai.mount ('/', app)
skitai.run (
threads = 0
)

This features is limited by your WSGI container. If you use Atila_ container, you can run with single threading mode by using Atila_'s async streaming response method. But you don't and if you have plan to use Skitai 'was' requests services, you can't single threading mode and you SHOULD run with multi-threading mode.

.. _Atila: https://pypi.python.org/pypi/atila

Run with Multiple Workers
---------------------------

*Available on posix only*

Skitai can run with multiple workers(processes) internally using fork for socket sharing.

.. code:: python

skitai.mount ('/', app)
skitai.run (
port = 5000,
workers = 4,
threads = 8
)

Skitai processes are,

.. code:: bash

$ ps -ef | grep skitai

ubuntu 25219 1 0 08:25 ? 00:00:00 skitai(myproject/app): master
ubuntu 25221 25219 1 08:25 ? 00:00:00 skitai(myproject/app): worker #0
ubuntu 25222 25219 1 08:25 ? 00:00:00 skitai(myproject/app): worker #1
ubuntu 25223 25219 1 08:25 ? 00:00:00 skitai(myproject/app): worker #2
ubuntu 25224 25219 1 08:25 ? 00:00:00 skitai(myproject/app): worker #3


Set Critical Point to Worker Processes
``````````````````````````````````````````

*New In Version 0.26.15.2, Available only on posix*

You can set parameters for restarting overloaded workers,

.. code:: python

skitai.set_worker_critical_point (cpu_percent = 90.0, continuous = 3, interval = 20)

This means if a worker's CPU usage is 90% for 20 seconds continuously 3 times, Skitai try to kill this worker and start a new worker.

If you do not want to use this, you just do not call set_worker_critical_point () or set interval to zero (0).

But I strongly recommend use this setting especially if you running Sktiai on single CPU processor machine or like AWS t1.x limited computing instances. Also this is for minimum protection against Skitai's unexpected bugs.


Mount Multiple WSGI Apps And Static Directories
------------------------------------------------

Skitai can mount multiple WSGI apps.


Independent Apps and Various WSGI Containers
`````````````````````````````````````````````````````

Here's three WSGI app samples:

.. code:: python

# WSGI App

def app (env, start_response):
start_response ("200 OK", [("Content-Type", "text/plain")])
return ['Hello World']

app.use_reloader = True
app.debug = True


# OR Flask App
from flask import Flask
app = Flask(__name__)

app.use_reloader = True
app.debug = True

@app.route("/")
def index ():
return "Hello World"


# OR Atila App
from atila import Atila
app = Atila (__name__)

app.use_reloader = True
app.debug = True

@app.route('/')
def index (was):
return "Hello World"


Then place this code at bottom of above WSGI app.

.. code:: python

if __name__ == "__main__":

import skitai

skitai.mount ('/', __file__, 'app')
skitai.mount ('/', 'static')
skitai.run ()


Service Versioning
````````````````````

These feature can be used for managing versions.

Let's assume initial version of app file is app_v1.py.

.. code:: python

app = Atila (__name__)

@app.route('/')
def index (was):
return "Hello World Ver.1"

And in same directory 2nd version of app file is app_v2.py.

.. code:: python

app = Atila (__name__)

@app.route('/')
def index (was):
return "Hello World Ver.2"

Now service.py is like this:

.. code:: python

import skitai

skitai.mount ('/', 'static')
skitai.mount ('/v1', 'app_v1')
skitai.mount ('/v2', 'app_v2')
skitai.run ()

Then run with:

.. code:: bash

python service.py


You can access ver.1 by http://127.0.0.1:5009/v1/ and vwe.2 by http://127.0.0.1:5009/v2/.

Note: Above 3 files is in the same directory and then both share templates directory. If you intend to seperate from app_v1 and app_v2, you should seperate app with directory like this:


.. code:: bash

service.py

app_v1/app.py
app_v1/templates
app_v1/static

app_v2/app.py
app_v2/templates
app_v2/static


and your service.py:

.. code:: python

import skitai

skitai.mount ('/v1', 'app_v1/static'),
skitai.mount ('/v1', 'app_v1/app'),
skitai.mount ('/v2', 'app_v2/static'),
skitai.mount ('/v2', 'app_v2/app')
skitai.run ()


Mounting With Virtual Host
-------------------------------

.. code:: python

if __name__ == "__main__":

import skitai
skitai.mount ('/', 'site1.py', host = 'www.site1.com')
skitai.mount ('/', 'site2.py', host = 'www.site2.com')
skitai.run ()

Setting POST Body Size Limitation
------------------------------------

For setting 8 Gbytes limitation for POST body size,

.. code:: python

import skitai

pref = skitai.pref ()
pref.max_client_body_size = 2 << 32

If you want to set more detaily,

.. code:: python

import skitai

pref = skitai.pref ()

pref.config.max_post_body_size = 2 << 32
pref.config.max_multipart_body_size = 2 << 32
pref.config.max_upload_file_size = 2 << 32


Setting Timeout
-----------------

Keep alive timeout means seconds gap of each requests. For setting HTTP connection keep alive timeout,

.. code:: python

skitai.set_keep_alive (2) # default = 30
skitai.mount ('/', app)
skitai.run ()

If you intend to use skitai as backend application server behind reverse proxy server like Nginx, it is recommended over 300.

Request timeout means seconds gap of data packet recv/sending events,

.. code:: python

skitai.set_request_timeout (10) # default = 30
skitai.mount ('/', app)
skitai.run ()

Note that under massive traffic situation, meaning of keep alive timeout become as same as request timeout beacuse a clients requests are delayed by network/HW capability unintensionally.

Anyway, these timeout values are higher, lower response fail rate and longger response time. But if response time is over 10 seconds, you might consider loadbalancing things. Skitai's default value 30 seconds is for lower failing rate under extreme situation.

*New in version 0.26.15*

You can set connection timeout for your backends. Basue of Skitai's ondemend polling feature, it is hard to know disconnected by server side, then Skitai will forcley reconnect if over backend_keep_alive after last interaction. Make sure your backends keep_alive setting value is matched with this value.

.. code:: python

skitai.set_backend_keep_alive (1200) # default is 10
skitai.mount ('/', app)
skitai.run ()



Enabling HTTP/HTTPS Proxy
---------------------------

Make sure you really need proxy.

.. code:: python

skitai.enable_proxy ()

# tunnel value will be applied to HTTPS proxy
skitai.set_proxy_keep_alive (channel = 60, tunnel = 600)

skitai.run ()


Run as Daemon
--------------

*Available on posix only*

For making a daemon,

.. code:: bash

python3 app.py start (or -d)


For stopping daemon,

.. code:: bash

python3 app.py stop (or -s)

Or for restarting daemon,

.. code:: bash

python3 app.py restart (or -r)


For automatic starting on system start, add a line to /etc/rc.local file like this:

.. code:: bash

su - ubuntu -c "/usr/bin/python3 /home/ubuntu/app.py -d"

exit 0

Run as Win32 Service
-----------------------

*Available on win32 only, New in version 0.26.7*

.. code:: python

from atila import Atila
from rs4.psutil.win32service import ServiceFramework

class ServiceConfig (ServiceFramework):
_svc_name_ = "SAE_EXAMPLE"
_svc_display_name_ = "Skitai Example Service"
_svc_app_ = __file__
_svc_python_ = r"c:\python34\python.exe"

app = Atila (__name__)

if __name__ == "__main__":
skitai.mount ('/', app)
skitai.set_service (ServiceConfig)
skitai.run ()

Then at command line,

.. code:: bash

app.py install # for installing windows service
app.py start
app.py stop
app.py update # when service class is updated
app.py remove # removing from windwos service

Adding Backend Server Alias
----------------------------

Backend server can be defined like this: (alias_type, servers, role = "", source = "", ssl = False).

alias_types can be one of these:

- All of HTTP based services like web, RPC, RESTful API

- PROTO_HTTP
- PROTO_HTTPS

- Websocket

- PROTO_WS: websocket
- PROTO_WSS: SSL websocket

- Database Engines

- DB_PGSQL
- DB_SQLITE3
- DB_REDIS
- DB_MONGODB
- DJANGO: mount django database engine of settings.py if database engine is PostgreSQL or SQLite3

- server: single or server list, server form is [ username : password @ server_address : server_port / database_name weight ]. if your username or password contains "@" characters, you should replace to '%40'
- role (optional): it is valid only when cluster_type is http or https for controlling API access
- source (optional): comma seperated ipv4/mask
- ssl (optional): use SSL connection or not, PROTO_HTTPS and PROTO_WSS use SSL defaultly

Some examples,

.. code:: python

skitai.alias (
'@members',
skitai.PROTO_HTTP,
[ "username:[e-mail]:5001" ],
role = 'admin',
source = '172.30.1.0/24,192.168.1/24'
)

skitai.alias (
'@mypostgres',
skitai.DB_POSTGRESQL,
[
"postgres:1234@172.30.0.1:5432/test 20",
"postgres:1234@172.30.0.2:5432/test 10"
]
)

skitai.alias (
'@mysqlite3',
skitai.DB_SQLITE3,
[
"/var/tmp/db1",
"/var/tmp/db2"
]
)


Run as HTTPS Server
---------------------

To generate self-signed certification file:

.. code:: python

; Create the Server Key and Certificate Signing Request
sudo openssl genrsa -des3 -out server.key 2048
sudo openssl req -new -key server.key -out server.csr

; Remove the Passphrase If you need
sudo cp server.key server.key.org
sudo openssl rsa -in server.key.org -out server.key

; Sign your SSL Certificate
sudo openssl x509 -req -days 365 -in server.csr -signkey server.key -out server.crt

Then,

.. code:: python

skitai.mount ('/', app)
skitai.enable_ssl ('server.crt', 'server.key', 'your pass phrase')
skitai.run ()

If you want to redirect all HTTP requests to HTTPS,

.. code:: python

skitai.enable_forward (80, 443)

skitai.mount ('/', app)
kitai.enable_ssl ('server.crt', 'server.key', 'your pass phrase')
skitai.run (port = 443)


About Mount Point & App Routing
--------------------------------

If app is mounted to '/flaskapp',

.. code:: python

from flask import Flask
app = Flask (__name__)

@app.route ("/hello")
def hello ():
return "Hello"

Above /hello can called, http://127.0.0.1:5000/flaskapp/hello

Also app should can handle mount point.
In case Flask, it seems 'url_for' generate url by joining with env["SCRIPT_NAME"] and route point, so it's not problem. Atila can handle obiously. But I don't know other WSGI containers will work properly.

Run Server Helpers
--------------------

SMTP Delivery Agent
````````````````````````

*New in version 0.26*

e-Mail sending service is executed seperated system process not threading. Every e-mail is temporary save to file system, e-Mail delivery process check new mail and will send. So there's possibly some delay time.

You can send e-Mail in your app like this:

.. code:: python

# email delivery service
e = was.email (subject, snd, rcpt)
e.set_smtp ("127.0.0.1:465", "username", "password", ssl = True)
e.add_content ("Hello World<div><img src='cid:ID_A'></div>", "text/html")
e.add_attachment (r"001.png", cid="ID_A")
e.send ()

With asynchronous email delivery service, can add default SMTP Server. If it is configured, you can skip e.set_smtp(). But be careful for keeping your smtp password.

.. code:: bash

skitai smtpda -d

All e-mails are saved into *varpath* and varpath is not specified default is /var/temp/skitai


Run With Config File
````````````````````````
*New in version 0.26.17*

Both of SMTP and Taks Scheduler can be run with config file, it may be particulary useful in case you run multiple skitai instances.

.. code:: bash

# ~/.skitai.conf

[smtpda]
verbose = false
max-retry = 10
keep-days = 1
smtp-server = [your SMTP server]
user = [your SMTP user name if you need]
password = [your SMTP user password if you need]
ssl = true


And run scripts mannually,

.. code:: bash

skitai smtpda

.. code:: bash

Options:

start: start as daemon
restart
stop
status

Example:

skitai smtpda status
skitai smtpda restart

I you give cammnad line options, theses have more priority than config file.

And for running automatically on system boot, you can add this line to /etc/rc.local like this,

.. code:: bash

# /etc/rc.local

su - ubuntu -c "/usr/local/bin/skitai smtpda start"

In this case, smtpda will use spool directory at */tmp/skitai/smtpda*, so your each apps SHOULD NOT call *skitai.smtpda ()* if you want to share spool directory.


Asccessing File Resources On Startup
--------------------------------------

Skitai's working directory is where the script call skitai.run (). Even you run skitai at root directory,

.. code:: bash

/app/example/app.py -d

Skitai will change working directory to /app/example on startup.

So your file resources exist within skitai run script, you can access them by relative path,

.. code:: python

monitor = skital.abspath ('package', 'monitor.py')

Also, you need absolute path on script,

.. code:: python

skitai.getswd () # get skitai working directory


Enable Cache File System
------------------------------

If you make massive HTTP requests, you can cache contents by HTTP headers - Cache-Control and Expires. these configures will affect to 'was' request services, proxy and reverse proxy.

.. code:: python

skitai.enable_cachefs (memmax = 10000000, diskmax = 100000000, path = '/var/tmp/skitai/cache')
skitai.mount ('/', app)
skitai.run ()

Default values are:

- memmax: 0
- diskmax: 0
- path: None


Configure Max Age For Static Files
--------------------------------------

You can set max-age for static files' respone header like,

.. code:: bash

Cache-Control: max-age=300
Expires: Sun, 06 Nov 2017 08:49:37 GMT

If max-age is only set to "/", applied to all files. But you can specify it to any sub directories.

.. code:: python

skitai.mount ('/', 'static')
skitai.set_max_age ("/", 300)
skitai.set_max_age ('/js', 0)
skitai.set_max_age ('/images', 3600)
skitai.run ()

Enable Cache File System
------------------------------

If you make massive HTTP requests, you can cache contents by HTTP headers - Cache-Control and Expires

.. code:: python

skitai.enable_cachefs (path = '/var/skitai/cache', memmax = 0, diskmax = 0)
skitai.mount ('/', app)
skitai.run ()


Enabling API Gateway Server
-----------------------------

Using Skitai's reverse proxy feature, it can be used as API Gateway Server. All backend API servers can be mounted at gateway server with client authentification and transaction ID logging feature.

.. code:: python

class Authorizer:
def __init__ (self):
self.tokens = {
"12345678-1234-123456": ("hansroh", ["user", "admin"], 0)
}

# For Token
def handle_token (self, handler, request):
username, roles, expires = self.tokens.get (request.token)
if expires and expires < time.time ():
# remove expired token
self.tokens.popitem (request.token)
return handler.continue_request (request)
handler.continue_request (request, username, roles)

# For JWT Claim
def handle_claim (self, handler, request):
claim = request.claim
expires = claim.get ("expires", 0)
if expires and expires < time.time ():
return handler.continue_request (request)
handler.continue_request (request, claim.get ("user"), claim.get ("roles"))

@app.before_mount
def before_mount (wac):
wac.handler.set_auth_handler (Authorizer ())

@app.route ("/")
def index (was):
return "<h1>Skitai App Engine: API Gateway</h1>"


if __name__ == "__main__":
import skitai

skitai.alias (
'@members', 'https', "members.example.com",
role = 'admin', source = '172.30.1.0/24,192.168.1/24'
)
skitai.alias (
'@photos', skitai.DB_SQLITE3, ["/var/tmp/db1", "/var/tmp/db2"]
)
skitai.mount ('/', app)
skitai.mount ('/members', '@members')
skitai.mount ('/photos', '@photos')
skitai.enable_gateway (True, "8fa06210-e109-11e6-934f-001b216d6e71")
skitai.run ()

Gateway use only bearer tokens like OAuth2 and JWT(Json Web Token) for authorization. And token issuance is at your own hands. But JWT creation,

.. code:: python

from aquests.lib import jwt

secret_key = b"8fa06210-e109-11e6-934f-001b216d6e71"
token = jwt.gen_token (secret_key, {'user': 'Hans Roh', 'roles': ['user']}, "HS256")

Also Skitai create API Transaction ID for each API call, and this will eb explained in Skitai 'was' Service chapter.


Using Database Engine For Verifying Token
```````````````````````````````````````````

*New in version 0.24.8*

If you are not familar with Skitai 'was' request services, it would be better to skip and read later.

You can query for getting user information to database engines asynchronously. Here's example for MongDB.

.. code:: python

from skitai import was

class Authorizer:
def handle_user (self, response, handler, request):
username = response.data ['username']
roles = response.data ['roles']
expires = response.data ['expires']

if expires and expires < time.time ():
was.mongodb (
"@my-mongodb", "mydb", callback = lambda x: None,
).delete ('tokens', {"token": request.token})
handler.continue_request (request)
else:
handler.continue_request (request, username, roles)

def handle_token (self, handler, request):
was.mongodb (
"@my-mongodb", "mydb", callback = (self.handle_user, (handler, request))
).findone ('tokens', {"token": request.token})


Inter-Processes State Sharing
-------------------------------------------

Skitai can run with multiple processes (a.k workers), It is possible matters synchronizing state between workers.

Like was.setlu () or getlu (), was provide setgs (), getgs ().

Most important thing is global state keys SHUOLD be defined before running skitai. And argument should be integer value.

.. code:: python

skitai.defgs ("cluster.num-nodes", "region.somethig", ...)
...

skitai.run ()

Then you cna use these,

.. code:: python

@app.route ("/nodes", method = ["POST", "DELETE"])
def nodes (was, **nodinfos):
...
was.setgs ("cluster.num-nodes", was.getgs ("cluster.num-nodes") + 1, **nodeinfos)

As a result,

- cluster.num-nodes state value has been increased
- "cluster.num-nodes" and \*\*nodeinfos are broadcated to mounted all *Atila* apps.

A app has interest for this,

.. code:: python

@app.on_broadcast ("cluster.num-nodes")
def num_nodes_changed (num_nodes, **nodeinfos):
...

But this broadcasting is just within current workers.

All workers has interested in this event, You may add watching routine at app.maintain.

.. code:: python

app.config.maintain_interval = 60
app.store ["num_nodes"] = 0

@app.maintain
def maintain_num_nodes (was, now):
...
num_nodes = was.getgs ("cluster.num-nodes")
if app.store ["num_nodes"] != num_nodes:
app.store ["num_nodes"] = num_nodes
app.broadcast ("cluster:num_nodes")



Request Logging
-----------------

Turn Request Logging Off For Specific Path
`````````````````````````````````````````````

For turn off request log for specific path,

.. code:: python

# turned off starting with
skitai.log_off ('/static/')

# turned off ending with
skitai.log_off ('*.css')

# you can multiple args
skitai.log_off ('*.css', '/static/images/', '/static/js/')


Log Format
````````````

Blank seperated items of log line are,

- log date
- log time
- client ip or proxy ip

- request host: default '-' if not available
- request methods
- request uri
- request version
- request body size

- reply code
- reply body size

- global transaction ID: for backtracing request if multiple backends related
- local transaction ID: for backtracing request if multiple backends related
- username when HTTP auth: default '-', wrapped by double quotations if value available
- bearer token when HTTP bearer auth

- referer: default '-', wrapped by double quotations if value available
- user agent: default '-', wrapped by double quotations if value available
- x-forwared-for, real client ip before through proxy

- Skitai engine's worker ID like M(Master), W0, W1 (Worker #0, #1,... Posix only)
- number of active connections when logged, these connections include not only clients but your backend/upstream servers
- duration ms for request handling
- duration ms for transfering response data


Testing Mounted App
``````````````````````````````````````

*New in version 0.27*

For mounted app testing fully network environment,

.. code:: python

import skitai

def test_myapp ():
with skitai.test_client ("./app.py", 6000) as cli:
resp = cli.get ("/")
assert "something" in resp.text

# api call
stub = cli.api ()
resp = stub.apis.pets (45).get ()
assert resp.data ["id"] == 45

Now run pytest.

This test client will start Skitai server on port 6000 with app. app.py shoud have skitai.run ().

Note: Port that skitai.run (port = 5000) will be ignored, app.py will be launched with port 6000 that specified by skitai.test_client for avoiding exist app service.


If your have so many tests, define cli at your conftest.py

.. code:: python

import pytest
import skitai

@pytest.fixture (scope = "session")
def cli ():
c = skitai.test_client ("./app.py", 6000)
yield c
c.stop ()

And edit your test script:

.. code:: python

import skitai

def test_myapp (cli):
resp = cli.get ("/")
assert "something" in resp.text

# api call
stub = cli.api ()
resp = stub.apis.pets (45).get ()
assert resp.data ["id"] == 45


If you run test server at another console window for watching server error messages, give dry = True parameter.

.. code:: python

@pytest.fixture (scope = "session")
def cli ():
c = skitai.test_client ("./app.py", 5000, dry = True)
yield c
c.stop ()

This test client will not start Skitai server but access to port 5000 so you start server manually at another console,

.. code:: bash

python3 app.py


Skitai with Nginx
---------------------------

Here's some helpful sample works with Nginx.

.. code:: python

# use http 1.1 for backends
proxy_http_version 1.1;
proxy_set_header Host $host;
proxy_set_header X-NginX-Proxy true;
proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;

# enabling websocket
proxy_set_header Upgrade $http_upgrade;
proxy_set_header Connection "Upgrade";
proxy_read_timeout 86400;

# upstreams with connection keep alive
upstream backend {
server 127.0.0.1:5000;
keepalive 100;
}

server {
listen 80;
server_name www.oh-my-jeans.com;
keepalive_timeout 30s;

location / {
proxy_pass http://backend;
add_header X-Backend "skitai app engine";
client_max_body_size 2g;
}

location /assets/ {
alias /home/ubuntu/www/statics/assets/;
expires 86400;
}
}


Self-Descriptive App
---------------------

Skitai's one of philasophy is self-descriptive app. This means that you once make your app, this app can be run without any configuration or config files (at least, if you need own your resources/log files directoring policy). Your app contains all configurations for not only its own app but also Skitai. As a result, you can just install Skitai with pip, and run your app.py immediately.

.. code:: bash

pip3 install skitai
# if your app has dependencies
pip3 install -Ur requirements.txt
python3 app.py

Skitai App Examples
---------------------

Also please visit to `Skitai app examples`_.

.. _`Skitai app examples`: https://gitlab.com/hansroh/skitai/tree/master/tests/examples



Export API From Your Module Through Skitai
=============================================

If your module need export APIs or web pages, you can include app in your module for Skitai App Engine.

Let's assume your package name is 'unsub'.

Your app should be located at unsub/export/skitai/__export__.py

Then users uses your module can mount on skitai by like this,

.. code:: python

import unsub

pref = skitai.pref ()
pref.config.urlfile = skitai.abspath ('resources', 'urllist.txt')

skitai.mount ("/v1", unsub, "app", pref)
skitai.run ()

If you want to specify filename like app_v1.py for version management,

.. code:: python

skitai.mount ("/v1", (unsub, "app_v1.py"), "app", pref)


If your app need bootstraping or capsulizing complicated initialize process from simple user settings, write code to unsub/export/skitai/__init__.py.

.. code:: python

import skitai

def bootstrap (pref):
with open (pref.config.urlfile, "r") as f:
urllist = []
while 1:
line = f.readline ().strip ()
if not line: break
urllist.append (line.split (" ", 4))
pref.config.urllist = urllist

*Important Note:* You should add zip_safe = False flag in your setup.py because Skitai could access your __export__ script and its sub modules.

.. code:: python

setup (
name = "mymodule",
...
zip_safe = False
)


Examples
----------

Here're some implementations I made.

- `DeLune API Server`_
- `Haiku API Server`_
- `Tensorflow API Server`_

.. _`DeLune API Server`: https://pypi.python.org/pypi/delune
.. _`Tensorflow API Server`: https://pypi.python.org/pypi/tfserver
.. _`Haiku API Server`: https://pypi.python.org/pypi/haiku-lst



HTTP/2.0 Server Push
================================

*New in version 0.16*

Skiai supports HTPT2 both 'h2' protocl over encrypted TLS and 'h2c' for clear text (But now Sep 2016, there is no browser supporting h2c protocol).

Basically you have nothing to do for HTTP2. Client's browser will handle it except `HTTP2 server push`_.

For using it, you just call was.push (uri) before return response data. It will work only client browser support HTTP2 server push, otherwise will be ignored.

.. code:: python

from skitai import was

@app.route ("/promise")
def promise ():

was.push ('/images/A.png')
was.push ('/images/B.png')

return was.response (
"200 OK",
(
'Promise Sent<br><br>'
'<img src="/images/A.png">'
'<img src="/images/B.png">'
)
)

.. _`HTTP2 server push`: https://tools.ietf.org/html/rfc7540#section-8.2



HTML5 Websocket
====================

*New in version 0.11*

The HTML5 WebSockets specification defines an API that enables web pages to use the WebSockets protocol for two-way communication with a remote host.

Skitai can be HTML5 websocket server and any WSGI containers can use it.

But I'm not sure my implemetation is right way, so it is experimental and could be changable.


Using Websocket
-----------------------------

Use skitai.websocket decorator.

First param is the name of variable for recieving message. Anf you can configure timeout and open/close websocket handlers.

For example with Flask app,

.. code:: python

def onopen ():
request.g. ...

def onclose ():
request.g. ...

@app.route ("/websocket/echo")
@skitai.websocket ("message", timeout = 60, onopen = onopen, onclose = onclose)
def echo ():
return "ECHO:" + request.args.get ("message")


Proxying With Atila
---------------------------------

It follows WSGI specification as possible as can:

.. code:: python

def start_response (environ, start_response):
...

Basically, Skitai calls this method on message arriving repeatly. So it is quite ineeficient. If your WSGI framework give a websocket handler object, it will have better performance but it is hard to expect.

Another option is that Sktai provide full usage spec with routing, but I think it is not pretty.


So you can use Atila for websocket service (as websocket proxy) beside your main app. and mount both app on Skitai.

With Atila app, you can use websocket more efficiently, and various options.

.. code:: python

def onopen (was):
print ('websocket opened')

def onclose (was):
print ('websocket closed')

@app.route ("/websocket")
@app.websocket (skitai.WS_SIMPLE, 1200, onopen, onclose)
def websocket (was, message):
return 'you said: ' + message

This code is not very differrent with skitai.websocket () decorator, but internally Skitai and Atila calls websocket handler somewhat efficiently.

For more about this see `Atila Websocket`_.

.. _`Atila Websocket`: https://pypi.org/project/atila/#more-about-websocket


WWW-Authenticate
-----------------------------------

Some browsers do not support WWW-Authenticate on websocket like Safari, then Skitai currently disables WWW-Authenticate for websocket, so you should be careful for requiring secured messages.

Client Side
-----------------------------

First of all, see conceptual client side java script for websocket using Vuejs.

.. code:: html

<div id="app">
<ul>
<li v-for="log in logs" v-html="log.text"></li>
</ul>
<input type="Text" v-model="msg" @keyup.enter="push (msg); msg='';">
</div>

<script>
vapp = new Vue({
el: "#app",
data: {
ws_uri: "ws://www.yourserver.com/websocket",
websocket: null,
out_buffer: [],
logs: [],
msg = '',
},

methods: {

push: function (msg) {
if (!msg) {
return
}
this.out_buffer.push (msg)
if (this.websocket == null) {
this.connect ()
} else {
this.send ()
}
},

handle_read: function (evt) {
this.log_info(evt.data)
},

log_info: function (msg) {
if (this.logs.length == 10000) {
this.logs.shift ()
}
this.logs.push ({text: msg})
},

connect: function () {
this.log_info ("connecting to " + this.ws_uri)
this.websocket = new WebSocket(this.ws_uri)
this.websocket.onopen = this.handle_connect
this.websocket.onmessage = this.handle_read
this.websocket.onclose = this.handle_close
this.websocket.onerror = this.handle_error
},

send: function () {
for (var i = 0; i < this.out_buffer.length; i++ ) {
this.handle_write (this.out_buffer.shift ())
}
},

handle_write: function (msg) {
this.log_info ("SEND: " + msg)
this.websocket.send (msg)
},

handle_connect: function () {
this.log_info ("connected")
this.send ()
},

handle_close: function (evt) {
this.websocket.close()
this.websocket = null
this.log_info("DISCONNECTED")
},

handle_error: function (evt) {
this.log_info('ERROR: ' + evt.data)
},

},

mounted: function () {
this.push ('Hello!')
},

})

</script>


Send Messages Through Websocket Directly
-----------------------------------------------------------------------------

It needn't return message, but you can send directly multiple messages through was.websocket,

.. code:: python

@app.route ("/websocket/echo")
@was.websocket ("message", 60)
def echo ():
message = request.args.get ("message")
request.environ ["websocket"].send ("You said," + message)
request.environ ["websocket"].send ("I said acknowledge")



Skitai 'was' Services
=======================

'was' means (Skitai) *WSGI Application Support*.

WSGI container like Flask, need to import 'was':

.. code:: python

from skitai import was

@app.route ("/")
def hello ():
was.get ("http://...")
...

But Atila WSGI container integrated with Skitai, use just like Python 'self'.

It will be easy to understand think like that:

- Skitai is Python class instance
- 'was' is 'self' which first argument of instance method
- Your app functions are methods of Skitai instance

.. code:: python

@app.route ("/")
def hello (was, name = "Hans Roh"):
was.get ("http://...")
...

Simply just remember, if you use WSGI container like Flask, Bottle, ... - NOT Atila - and want to use Skitai asynchronous services, you should import 'was'. Usage is exactly same. But for my convinient, I wrote example codes Atila version mostly.


Async Communication For Backends To Backends
------------------------------------------------------

Skitai works fine with synchronous apps and libraries. you can use standard database client libraries or requests modeul for API calls.


Also provides optional asynchronous and concurrent requests to your backends within request thread.

It implemented with pure python library like asyncore, select etc and has own event loop (asyncore.loop), NOT use gevent, greeenlet, asyncio... It means Skitai could not use with these stuff.

'was' is making requests to HTTP, REST, RPC and several database engines. And this is mostly useful for fast Server Side Rendering with outside resources.

Recently Javascript provides good asynchronous communicating tools like AJAX or axios.js for **frontends - backends**. Like this, 'was' provides **backends - backends** communicating tool.

The modules is related theses features from aquests_ and you could read aquests_ usage first.

I think it just fine explains some differences with aquests.

First of all, usage is somewhat different because aquests is used within threadings on skitai. Skitai takes some threading advantages and compromise with them for avoiding callback heaven.

API Calling
`````````````````````````````

At aquests,

.. code:: python

import aquests

def display_result (response):
print (reponse.data)

aquests.configure (callback = display_result, timeout = 3)

aquests.get (url)
aquests.post (url, {"user": "Hans Roh", "comment": "Hello"})
aquests.fetchall ()

At Skitai,

.. code:: python

@app.route (...)
def request (was):
req1 = was.get (url)
req2 = was.post (url, {"user": "Hans Roh", "comment": "Hello"})
respones1 = req1.dispatch (timeout = 3)
response2 = req2.dispatch (timeout = 3)
return [respones1.data, respones2.data]

The significant differnce is calling dispatch (timeout) for getting response data.

Database Querying
`````````````````````````````

PostgreSQL query at aquests,

.. code:: python

import aquests

def display_result (response):
for row in response.data:
row.city, row.t_high, row.t_low

aquests.configure (callback = display_result, timeout = 3)

dbo = aquests.postgresql ("127.0.0.1:5432", "mydb")
dbo.excute ("SELECT city, t_high, t_low FROM weather;")
aquests.fetchall ()

At Skitai,

.. code:: python

@app.route (...)
def query (was):
dbo = was.postgresql ("127.0.0.1:5432", "mydb")
s = dbo.excute ("SELECT city, t_high, t_low FROM weather;")

response = s.dispatch (2)
for row in response.data:
row.city, row.t_high, row.t_low


If you needn't returned data and just wait for completing query,

.. code:: python

dbo = was.postgresql ("127.0.0.1:5432", "mydb")
req = dbo.execute ("INSERT INTO CITIES VALUES ('New York');")
req.wait (2)

If failed, exception will be raised.


Using Database Transaction
`````````````````````````````````````

If you want use asynchronous database transaction, you can use asynchronous drivers.

Also Skitai provide PostgreSQL connection with pool. And SQLite connection without pool.

.. code:: python

app.alias ("@postgres", skitai.DB_PGSQL, "user:password@localhost/db")

@app.route ("/")
def index (was):
with was.transaction ("@postgres") as trx:
trx.execute ('INSERT ...')
trx.execute ('UPDATE ...')
trx.commit ()
return str (d)

With context manager, conn return back to pool automatically else you SHOULD call trx.putback () manually.

was.transaction (@alias) returns SQLPhile.pg2.open2 () and SQLPhile.db3.open ().


gRCP Calling
```````````````````

For another gRPC example, calling to tfserver_ for predicting something with tensorflow model.

.. code:: python

from tfserver import cli

@app.route (...)
def predict_grpc (was):
stub = was.grpc ("http://127.0.0.1:5000/tensorflow.serving.PredictionService")
fftseq = getone ()
request = cli.build_request ('model', 'predict', stuff = fftseq)
req = stub.Predict (request, 10.0)
resp = req.dispatch ()
return cli.Response (resp.data).y

Here're addtional methods and properties above response obkect compared with aquests' response one.

- cache (timeout): response caching
- status: it indicate requests processed status and note it is not related response.status_code.

- 0: Initial Default Value
- 1: Operation Timeout
- 2: Exception Occured
- 3: Normal Terminated

.. _aquests: https://pypi.python.org/pypi/aquests
.. _tfserver: https://pypi.python.org/pypi/tfserver


Methods List
````````````````

All supoorted request methods are:

- Web/API related

- was.get ()
- was.delete ()
- was.post ()
- was.put ()
- was.patch ()
- was.upload ()
- was.options ()

Above request type is configured to json. This mean request content type and response accept type is all 'application/json'.

If you want to change default value,

1. set app.config.default_request_type = (request content type, accept content type)

.. code:: python

app.config.default_request_type = ("text/xml", "*/*")

2. use headers paramter for each request:

.. code:: python

req = was.get ("@delune/documents/11", headers = [("Accept", "text/xml")])

data = {"Title": "...", "Content": "..."}
headers = [
("Content-Type", "application/x-www-form-urlencoded"),
("Accept", "text/xml")
]
req = was.post ("@delune/documents", data, headers = headers)

- RPCs

- was.rpc (): XMLRPC
- was.grpc (): gRPC

- Database Engines

- was.postgresql ()
- was.mongodb ()
- was.redis ()
- was.sqlite3 ()
- was.backend (): if you make alias for your database, you needn't specify db type, just use backend ()

- Websocket

- was.ws ()
- was.wss ()


Usage At Single Threaded Environment
`````````````````````````````````````

If you run Skitai with single threaded mode, you can't use req.wait(), req.dispatch(). Instead you should use callback for this, and Skitai provide async response.

.. code:: python

def promise_handler (promise, response):
promise.settle (response.content)

@app.route ("/index")
def promise_example (was):
promise = was.promise (promise_handler)
promise.get (None, "https://pypi.python.org/pypi/skitai")
return promise

Unfortunately this feature is available on Atila WSGI container only (It means Flask or other WSGI container users can only use Skitai with multi-threading mode).

For more detail usage will be explained 'Atila Async Streaming Response' chapter and you could skip now.


Load-Balancing
````````````````

Skitai support load-balancing requests.

If server members are pre defined, skitai choose one automatically per each request supporting *fail-over*.

Then let's request XMLRPC result to one of mysearch members.

.. code:: python

@app.route ("/search")
def search (was, keyword = "Mozart"):
s = was.rpc.lb ("@mysearch/rpc2").search (keyword)
results = s.dispatch (5)
return result.data

if __name__ == "__main__":
import skitai

skitai.alias (
'@mysearch',
skitai.PROTO_HTTPS,
["s1.myserver.com", "s2.myserver.com"]
)
skitia.mount ("/", app)
skitai.run ()


It just small change from was.rpc () to was.rpc.lb ()

*Note:* If @mysearch member is only one, was.get.lb ("@mydb") is equal to was.get ("@mydb").

*Note2:* You can mount cluster @mysearch to specific path as proxypass like this:

.. code:: bash

if __name__ == "__main__":
import skitai

skitai.alias (
'@mysearch',
skitai.PROTO_HTTPS,
["s1.myserver.com", "s2.myserver.com:443"]
)
skitia.mount ("/", app)
skitia.mount ("/search", '@mysearch')
skitai.run ()

It can be accessed from http://127.0.0.1:5000/search, and handled as load-balanced proxypass.

This sample is to show loadbalanced querying database.
Add mydb members to config file.

.. code:: python

@app.route ("/query")
def query (was, keyword):
dbo = was.postgresql.lb ("@mydb")
req = dbo.execute ("SELECT * FROM CITIES;")
result = req.dispatch (2)

if __name__ == "__main__":
import skitai

skitai.alias (
'@mydb',
skitai.PGSQL,
[
"s1.yourserver.com:5432/mydb/user/passwd",
"s2.yourserver.com:5432/mydb/user/passwd"
]
)
skitia.mount ("/", app)
skitai.run ()


Map-Reducing
``````````````

Basically same with load_balancing except Skitai requests to all members per each request.

.. code:: python

@app.route ("/search")
def search (was, keyword = "Mozart"):
stub = was.rpc.map ("@mysearch/rpc2")
req = stub.search (keyword)
results = req.dispatch (2)

all_results = []
for result in results:
all_results.extend (result.data)
return all_results

There are 2 changes:

1. from was.rpc.lb () to was.rpc.map ()
2. results is iterable


Using Aliased Database
``````````````````````````

If you have alias your database server, you needn't specify db type like 'dbo = was.postgresql ("@mydb")'. Just use 'dbo = was.backend ("@mydb")'.

It makes easy to handle both Sqlite3 and PostgreSQL. If you intend to use Sqlite3 at developing, but use PostgreSQL at production, you just change alias on Skitai startup time.


Using SQLAlchemy Query Generator
````````````````````````````````````````````````

If you use sqlalchemy_ for database ORM, you cannot use ORM itself but use for gfenerating SQL query statement.

.. code:: python

# models.py

from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy import MetaData, Table
from sqlalchemy import Column, Integer, String

Base = declarative_base ()

class Stocks (Base):
__tablename__ = 'stocks'
id = Column(Integer, primary_key=True)
date = Column(String(255))
trans = Column(String(255))
symbol = Column(String(255))
qty = Column(Integer)
price = Column(Integer)
stocks = Stocks.__table__

Or,

.. code:: python

# models.py

metadata = MetaData()
stocks = Table ('stocks', metadata,
Column('id', Integer, primary_key=True),
Column('date', String(255)),
Column('trans', String(255)),
Column('symbol', String(255)),
Column('qty', Integer),
Column('price', Integer)
)

For generating query statements,

.. code:: python

from models import stocks

@app.route ("/q/<int:id>)
def q (was, id):
statement = stocks.select().where(stocks.c.id == id)
res = was.backend ("@mydb").execute (statement).dispatch ()
res.data
...

Other simple query examples,

.. code:: python

statement = stocks.insert().values (id = 2, date = '2019-1-30', trans = "SELL", symbol = "APL", qty = 200, price = 1600.0)
statement = stocks.delete().where(stocks.c.id == 2)
statement = stocks.update().values(symbol='BIX').where(stocks.c.id == 2)

For more information about query generating, visit `SQLAlchemy Core`_.

.. _sqlalchemy: https://www.sqlalchemy.org/
.. _`SQLAlchemy Core`: https://docs.sqlalchemy.org/en/latest/core/index.html


Tasks
``````````````

Typically, using was's concurrent requests is like this,

.. code:: python

from skitai import was

@app.route (...)
def request ():
req1 = was.get (url)
req2 = was.post (url, {"user": "Hans Roh", "comment": "Hello"})
req3 = was.backend ("@mydb").select ("mytable").get ("*").execute ()
resp1 = req1.dispatch (timeout = 3)
resp2 = req2.dispatch (timeout = 3)
resp3 = req3.dispatch (timeout = 3)
return [respones1.data, respones2.data, respones2.data]

In case multiple requests, it's not pretty. Tasks join all concurrency tasks and collect results.

.. code:: python

@app.route (...)
def request (was):
reqs = [
was.get (url),
was.post (url, {"user": "Hans Roh", "comment": "Hello"}),
was.backend ("@mydb").select ("mytable").get ("*").execute ()
]
tasks = Tasks (reqs, timeout = 3, cache = 60)
return [r.data for r in tasks] # tasks object is iterrable


Throwing HTTP Error On Request Failed
`````````````````````````````````````````

.. code:: python

@app.route ("/search")
def search (was, keyword = "Mozart"):
req = was.get ("@mysearch/something")
result = req.dispatch_or_throw ()
return result.data

dispatch_or_throw () returns result only if req.status_code == 2xx and req.status == 3, otherwise raise HTTP 5xx error.

If you want to access to data for short hand,

.. code:: python

@app.route ("/search")
def search (was, keyword = "Mozart"):
req = was.get ("@mysearch/something")
return req.fetch ()

fetch () returns result.data if all status is normal.

If your result.data is list type (mostly database query result or JSON array), one () is very similar with fetch () but result count is not 1, it raise HTTP 404 error.


Caching Result
````````````````

By default, all HTTP requests keep server's cache policy given by HTTP response header (Cache-Control, Expire etc). But you can control cache as your own terms including even database query results.

Every results returned by dispatch() can cache.

.. code:: python

s = was.rpc.lb ("@mysearch/rpc2").getinfo ()
result = s.dispatch (2)
if result.status_code == 200:
result.cache (60) # 60 seconds

s = was.rpc.map ("@mysearch/rpc2").getinfo ()
results = s.dispatch (2)
# assume @mysearch has 3 members
if results.status_code == [200, 200, 200]:
result.cache (60)

Although code == 200 alredy implies status == 3, anyway if status is not 3, cache() will be ignored. If cached, it wil return cached result for 60 seconds.

*New in version 0.15.28*

If you dispatch with reraise argument, code can be simple.

.. code:: python

s = was.rpc.lb ("@mysearch/rpc2").getinfo ()
content = s.dispatch (2, reraise = True).data
s.cache (60)

Please note cache () method is both available request and result objects.

You can control number of caches by your system memory before running app.

.. code:: python

skitai.set_max_rcache (300)
skitai.mount ('/', app)
skitai.run ()

*New in version 0.14.9*

For expiring cached result by updating new data:

.. code:: python

refreshed = False
if was.request.command == "post":
...
refreshed = True

s = was.rpc.lb (
"@mysearch/rpc2",
use_cache = not refreshed and True or False
).getinfo ()
result = s.dispatch (2)
if result.status_code == 200:
result.cache (60) # 60 seconds

*New in version 0.27*

You can cache with dispatch,

For expiring cached result by updating new data:

.. code:: python

s = was.rpc.lb (
"@mysearch/rpc2",
use_cache = not refreshed and True or False
).getinfo ()
result = s.dispatch (2, cache = 60)

*Note* that In this case, it is cached only *if status_code is 200*. If you want cache for another status_code,

.. code:: python

s = was.rpc.lb (
"@mysearch/rpc2",
use_cache = not refreshed and True or False
).getinfo ()
result = s.dispatch (2, cache = 60, cache_if = (200, 201))


More About Cache Control: Model Synchronized Cache
```````````````````````````````````````````````````

*New in version 0.26.15*

`use_cache` value can be True, False or last updated time of base object. If last updated is greater than cached time, cache will be expired immediately and begin new query/request.

You can integrate your models changing and cache control.

First of all, you should set all cache control keys to Skitai for sharing model state beetween worker processes.

.. code:: python

skitai.deflu ('tables.users', 'table.photos')

These Key names are might be related your database model names nor table names. Especially you bind Django model signal, these keys should be exaclty nodel class name. But in general cases, key names are fine if you easy to recognize.

These key names are not mutable and you cannot add new key after calling skitai.run ().

Then you can use setlu () and getlu (),

.. code:: python

app = Atila (__name__)

@app.route ("/update")
def update (was):
# update users tabale
was.backend ('@mydb').execute (...)
# update last update time by key string
was.setlu ('tables.users')

@app.route ("/query1")
def query1 (was):
# determine if use cache or not by last update information 'users'
was.backend ('@mydb', use_cache = was.getlu ('tables.users')).execute (...)

@app.route ("/query2")
def query2 (was):
# determine if use cache or not by last update information 'users'
was.backend ('@mydb', use_cache = was.getlu ('tables.users')).execute (...)

It makes helping to reduce the needs for building or managing caches. And the values by setlu() are synchronized between Skitai workers by multiprocessing.Array.

If your query related with multiple models,

.. code:: python

use_cache = was.getlu ("myapp.models.User", "myapp.models.Photo")

was.getlu () returns most recent update time stamp of given models.

*Available on Python 3.5+*

Also was.setlu () emits 'model-changed' events. You can handle event if you need. But this event system only available on Atila middle-ware.

.. code:: python

app = Atila (__name__)

@app.route ("/update")
def update (was):
# update users tabale
was.backend ('@mydb').execute (...)
# update last update time by key string
was.setlu ('tables.users', something...)

@app.on_broadcast ("model-changed:tables.users")
def on_broadcast (was, *args, **kargs):
# your code

Note: if @app.on_broadcast is located in mount function at services directory, even app.use_reloader is True, it is not applied to app when component file is changed. In this case you should manually reload app by resaving app file.


API Transaction ID
`````````````````````

*New in version 0.21*

For tracing REST API call, Skitai use global/local transaction IDs.

If a client call a API first, global transaction ID (gtxnid) is assigned automatically like 'GTID-C4676-R67' and local transaction ID (ltxnid) is '1000'.

You call was.get (), was.post () or etc, both IDs will be forwarded via HTTP request header. Most important thinng is that gtxnid is never changed by client call, but ltxnid will be changed per API call.

when client calls gateway API or HTML, ltxnid is 1000. And if it calls APIs internally, ltxnid will increase to 2001, 2002. If ltxnid 2001 API calls internal sub API, ltxnid will increase to 3002, and ltxnid 2002 to 3003. Briefly 1st digit is call depth and rest digits are sequence of API calls.

This IDs is logged to Skitai request log file like this.

.. code:: bash

2016.12.30 18:05:06 [info] 127.0.0.1:1778 127.0.0.1:5000 GET / \
HTTP/1.1 200 0 32970 \
GTID-C3-R8 1000 - - \
"Mozilla/5.0 (Windows NT 6.1;) Gecko/20100101 Firefox/50.0" \
4ms 3ms

Focus 3rd line above log message. Then you can trace a series of API calls from each Skitai instance's log files for finding some kind of problems.

In next chapters' features of 'was' are only available for *Atila WSGI container*. So if you have no plan to use Atila, just skip.



Utility Methods of 'was'
---------------------------

This chapter's 'was' services are also avaliable for all WSGI middelwares.

- was.status () # HTML formatted status information
- was.get_lock (name = "__main__") # getting process lock
- was.gentemp () # return temp file name with full path
- was.restart () # Restart Skitai App Engine Server, but this only works when processes is 1 else just applied to current worker process.
- was.shutdown () # Shutdown Skitai App Engine Server, but this only works when processes is 1 else just applied to current worker process.



Project Purpose
===================

Skitai App Engine's original purpose is to serve python fulltext search engine Wissen_ which is my another pypi work. And I found that it is possibly useful for building and serving websites.

Anyway, I am modifying my codes to optimizing for enabling service on Linux machine with relatvely poor H/W (ex. AWS_ t2.nano instance) and making easy to auto-scaling provided cloud computing service like AWS_.

If you need lots of outside http(s) resources connecting jobs and use PostgreSQL, it might be worth testing and participating this project.

Also note it might be more efficient that circumstance using `Gevent WSGI Server`_ + Flask. They have well documentation and already tested by lots of users.


.. _Wissen: https://pypi.python.org/pypi/wissen
.. _AWS: https://aws.amazon.com
.. _`Gevent WSGI Server`: http://www.gevent.org/


Links
======

- `GitLab Repository`_
- Bug Report: `GitLab issues`_

.. _`GitLab Repository`: https://gitlab.com/hansroh/skitai
.. _`GitLab issues`: https://gitlab.com/hansroh/skitai/issues
.. _`Skitai WSGI App Engine Daemon`: https://pypi.python.org/pypi/skitaid


Change Log
===========

- 0.28 (Feb 2019)

- add was.transaction ()
- update psycopg2 connection parameter: async => async\_ for Py3.7 compatablity
- replace from data_or_thow (), one_or_throw () to fetch (), one ()
- fix HTTP2 server push and add was.push ()
- getwait () and getswait () are integrated into dispatch ()
- add data_or_throw () and one_or_throw ()
- was.promise has been deprecated, use was.futures: see Atila documentation
- reinstate gc.collect () schedule
- fix GTXID
- fix app reloader
- remove gc.collect () schedule
- support SQLAlchemy query statement object
- removed sugar methods: was.getjson, getxml, postjson, ..., instead use headers parameter or app.config.default_request_type
- skitai.win32service has been moved to rs4.psutil.win32service
- improve 'was' magic method search speed
- seperate skitai.saddle into atila

- 0.27.6 (Jan 2019)

- rename directory decorative to services
- change from skital.saddle.contrib.decorative to skital.saddle.contrib.services

- 0.27.3 (May 2018)

- remove -v option from skitai and smtpda
- add script: skitai
- remove scripts: skitai-smtpda and skitai-cron
- remove skitai.enable_smtpda (), skitai.cron ()

- 0.27.2 (May 2018)

- add was.request.get_real_ip () and was.request.is_private_ip ()
- fix CORS preflight

- 0.27.1 (May 2018)

- sqlphile bug fixed and change requirements

- 0.27 (Apr 2018)

- add app.setup_sqlphile ()
- add @app.mounted_or_reloaded decorator
- removed @app.auth_required, added @app.authorization_required (auth_type)
- rename @app.preworks -> @app.run_before and @app.postworks -> @app.run_after
- add @app.bearer_handler
- add was.mkjwt and was.dejwt
- add was.timestamp amd was.uniqid
- renamed was.token -> was.mktoken
- renamed api -> API, for_api -> Fault
- skitai.use_django_models has been deprecated, use skitai.alias
- functions are integrated skitai.mount_django into skitai.mount, skitai.alias_django into skitai.alias
- fix empty payload posting
- add was.partial and was.basepath
- raise NameError when non-exists funtion name to was.ap
- fix default arg is missing on was.ab
- add skitai.launch and saddle.make_client for unittest

0.26 (May 2017)

- 0.26.18 (Jan 2018)

- fix HTTP2 trailers
- fix HTTP2 flow control window
- remove was.response.traceback(), use was.response.for_ap (traceback = True)
- rename was.sqlmap to was.sql
- add @app.auth_required and @app.auth_not_required decorator
- change default export script to __export__.py
- remove app reloading progress:

- before:

- before_umount (was)
- umounted (wac)
- before_remount (wac): deprecated
- remounted (was): deprecated

- now:

- before_reload (was)
- reloaded (was)

- change app.model_signal () to app.redirect_signal (), add @app.on_signal ()
- change skitai.addlu to skitai.deflu (args, ...)
- add @app.if_file_modified
- add @app.preworks and @app.postworks
- fix HTTP/2 remote flow control window
- fix app.before_mount decorator exxcute point
- add was.gentemp () for generating temp file name
- add was.response.throw (), was.response.for_api() and was.response.traceback()
- add @app.websocket_config (spec, timeout, onopen_func, onclose_func, encoding)
- was.request.get_remote_addr considers X-Forwarded-For header value if exists
- add param keep param to was.csrf_verify()
- add and changed app life cycle decorators:

- before_mount (wac)
- mounted (was)
- before_remount (wac)
- remounted (was)
- before_umount (was)
- umounted (wac)

- add skitai.saddle.contrib.django,auth for integrating Django authorization
- change was.token(),was.detoken(), was.rmtoken()
- add jsonrpc executor
- add some methods to was.djnago: login (), logout (), authenticate () and update_session_auth_hash ()
- add app.testpass_required decorator
- add decorative concept

- 0.26.17 (Dec 2017)

- can run SMTP Delivery Agent and Task Scheduler with config file
- add error_handler (prev errorhandler) decorator
- add default_error_handler (prev defaulterrorhandler) decorator
- add login_handler, login_required decorator
- add permission_handler, permission_required decorator
- add app events emitting
- add was.csrf_token_input, was.csrf_token and was.csrf_verify()
- make session iterable
- prevent changing function spec by decorator
- change params of use_django_models: (settings_path, alias), skitai.mount_django (point, wsgi_path, pref = pref (True), dbalias = None, host = "default")

- 0.26.16 (Oct 2017)

- add app.sqlmaps
- add use_django_models (settings_path), skitai.mount_django (point, wsgi_path, pref = pref (True), host = "default")
- fix mbox, add app.max_client_body_size
- add skitai.addlu (args, ...)
- fix promise and proxing was objects
- change method name from skitai.set_network_timeout to set_erquest_timeout
- fix getwait, getswait. get timeout mis-working
- fix backend_keep_alive default value from 10 to 1200
- fix dbi reraise on error
- JSON as arguments

- 0.26.15

- added request.form () and request.dict ()
- support Django auto reload by restarting workers
- change DNS query default protocol from TCP to UDP (posix only)
- add skitai.set_proxy_keep_alive (channel = 60, tunnel = 600) and change default proxy keep alive to same values
- increase https tunnel keep alive timeout to 600 sec.
- fix broad event bus
- add getjson, deletejson, this request automatically add header 'Accept: application/json'
- change default request content-type from json to form data, if you post/put json data, you should change postjson/putjson
- add skitai.trackers (args,...) that is equivalant to skitai.lukeys ([args])
- fix mounting module
- app.storage had been remove officially, I cannot find any usage. but unoficially it will be remains by some day
- add skitai.lukeys () and fix inconsistency of was.setlu & was.getlu between multi workers
- was.storage had been remove
- add skitai.set_worker_critical_point ()
- fix result object caching
- add app.model_signal (), was.setlu () and was.getlu ()

- 0.26.14

- add app.storage and was.storage
- removed wac._backend and wac._upstream, use @app.mounted and @app.umount
- replaced app.listen by app.on_broadcast

- 0.26.13

- add skitai.log_off (path,...)
- add reply content-type to request log, and change log format
- change posix process display name

- 0.26.12

- change event decorator: @app.listen -> @app.on_broadcast
- adaptation to h2 3.0.1
- fix http2 flow controling
- fix errorhandler and add defaulterrorhandler
- fix WSGI response handler
- fix cross app URL building
- Django can be mounted
- fix smtpda & default var directory
- optimize HTTP/2 response data
- fix HTTP/2 logging when empty response body
- http_response.outgoing is replaced by deque
- change default mime-type from text/plain to application/octet-stream in response header
- HTTP response optimized

- 0.26.10

- start making pytest scripts
- add was-wide broadcast event bus: @app.listen (event), was.broadcast (event, args...) and @was.broadcast_after (event)
- add app-wide event bus: @app.on (event), was.emit (event, args...) and @was.emit_after (event)
- remove @app.listento (event) and was.emit (event, args...)

- 0.26.9

- add event bus: @app.listento (event) and was.emit (event, args...)

- 0.26.8

- fix websocket GROUPCHAT
- add was.apps
- was.ab works between apps are mounted seperatly

- 0.26.7

- add custom error template on Saddle
- add win32 service tools
- change class method name from make_request () to backend ()
- retry once if database is disconnected by keep-live timeout
- drop wac.make_dbo () and wac.make_stub ()

- 0.26.6

- add wac.make_dbo (), wac.make_stub () and wac.make_request ()
- wac.ajob () has been removed
- change repr name from wasc to wac
- websocket design spec, WEBSOCKET_DEDICATE_THREADSAFE has been removed and WEBSOCKET_THREADSAFE is added
- fix websocket, http2, https proxy tunnel timeout, related set_network_timeout () is recently added

- 0.26.4.1: add set_network_timeout (timoutout = 30) and change default keep alive timeout from 2 to 30
- 0.26.4: fix incomplete sending when resuested with connection: close header
- 0.26.3.7: enforce response to HTTP version 1.1 for 1.0 CONNECT with 1.0 request
- 0.26.3.5: revert multiworkers
- 0.26.3.2: fix multiworkers
- 0.26.3.1: update making for self-signing certification
- 0.26.3: add skitai.enable_forward
- 0.26.2.1: remove was.promise.render_all (), change method name from was.promise.push () to send ()
- 0.26.2: change name from was.aresponse to was.promise
- 0.26.1.1: add skitai.abspath (\*args)
- 0.26.1: fix proxy & proxypass, add was.request.scheme and update examples
- change development status to Beta
- fix Saddlery routing
- disable WWW-Authenticate on websocket protocol
- support CORS (Cross Origin Resource Sharing)
- support PATCH method
- runtime app preferences and add __init__.bootstrap (preference)
- fix route caching
- auto reload sub modules in package directory, if app.use_reloader = True
- new was.request.json ()
- integrated with skitaid package, single app file can contain all configure options
- level down developement status to alpha
- fix sqlite3 closing

0.25 (Feb 2017)

- 0.25.7: fix fancy url, non content-type header post/put request
- 0.25.6: add Chameleon_ template engine
- 0.25.5: app.jinja_overlay ()'s default args become jinja2 default
- 0.25.4.8: fix proxy retrying
- 0.25.4 license changed from BSD to MIT, fix websocket init at single thread
- 0.25.3 handler of promise args spec changed, class name is cahnged from AsyncResponse to Promise
- 0.25.2 fix promise exception handling, promise can send streaming chunk data
- 0.25.1 change app.jinja_overlay () default values and number of args, remove raw line statement
- project name chnaged: Skitai Library => Skitai App Engine

0.24 (Jan 2017)

- 0.24.9 bearer token handler spec changed
- 0.24.8 add async response, fix await_fifo bug
- 0.24.7 fix websocket shutdown
- 0.24.5 eliminate client arg from websocket config
- 0.24.5 eliminate event arg from websocket config
- fix proxy tunnel
- fix websocket cleanup
- change websocket initializing, not lower version compatible
- WEBSOCKET_MULTICAST deprecated, and new WEBSOCKET_GROUPCHAT does not create new thread any more

0.23 (Jan 2017)

- ready_producer_fifo only activated when proxy or reverse proxy is enabled, default deque will be used
- encoding argument was eliminated from REST call
- changed RPC, DBO request spec
- added gRPC as server and client
- support static files with http2
- fix POST method on reverse proxying

0.22 (Jan 2017)

- 0.22.7 fix was.upload(), was.post*()
- 0.22.5 fix xml-rpc service
- 0.22.4 fix proxy
- 0.22.3

- fix https REST, XML-RPC call
- fix DB pool

- 0.22

- Skitai REST/RPC call now uses HTTP2 if possible
- Fix HTTP2 opening with POST method
- Add logging on disconnecting of Websocket, HTTP2, Proxy Tunnel channels

- See News

0.21 (Dec 2016)

- 0.21.17 - fix JWT base64 padding problem
- 0.21.8 - connected with MongoDB asynchronously
- 0.21.3 - add JWT (JSON Web Token) handler, see `Skitai WSGI App Engine Daemon`_
- 0.21.2 - applied global/local-transaction-ID to app logging: was.log (msg, logtype), was.traceback ()
- 0.21 - change request log format, add global/local-transaction-ID to log file for backtrace

0.20 (Dec 2016)

- 0.20.15 - minor optimize asynconnect, I wish
- 0.20.14 - fix Redis connector's threading related error
- 0.20.4 - add Redis connector
- 0.20 - add API Gateway access handler

0.19 (Dec 2016)

- Reengineering was.request methods, fix disk caching

0.18 (Dec 2016)

- 0.18.11 - default content-type of was.post(), was.put() has been changed from 'application/x-www-form-urlencoded' to 'application/json'. if you use this method currently, you SHOULD change method name to was.postform()

- 0.18.7 - response contents caching has been applied to all was.request services (except websocket requests).

0.17 (Oct 2016)

- `Skitai WSGI App Engine Daemon`_ is seperated

0.16 (Sep 2016)

- 0.16.20 fix SSL proxy and divide into package for proxy & websocket_handler
- 0.16.19 fix HTTP2 cookie
- 0.16.18 fix handle large request body
- 0.16.13 fix thread locking for h2.Connection
- 0.16.11 fix pushing promise and response on Firefox
- 0.16.8 fix pushing promise and response
- 0.16.6 add several configs to was.app.config for limiting post body size from client
- 0.16.5 add method: was.response.hint_promise (uri) for sending HTP/2 PUSH PROMISE frame
- 0.16.3 fix flow control window
- 0.16.2 fix HTTP/2 Uprading for "http" URIs (RFC 7540 Section 3.2)
- 0.16 HTTP/2.0 implemented with hyper-h2_

0.15 (Mar 2016)

- fixed fancy URL <path> routing
- add Websocket design spec: WEBSOCKET_DEDICATE_THREADSAFE
- fixed Websocket keep-alive timeout
- fixed fancy URL routing
- 'was.cookie.set()' method prototype has been changed.
- added Named Session & Messaging Box
- fix select error when closed socket, thanks to spam-proxy-bots
- add mimetypes for .css .js
- fix debug output
- fix asynconnect.maintern
- fix loosing end of compressed content
- fix app reloading, @shutdown
- fix XMLRPC response and POST length
- add was.mbox.search (), change spec was.mbox.get ()
- fix routing bugs & was.ab()
- add saddle.Saddlery class for app packaging
- @app.startup, @app.onreload, @app.shutdown arguments has been changed

0.14 (Feb 2016)

- fix proxy occupies CPU on POST method failing
- was.log(), was.traceback() added
- fix valid time in message box
- changed @failed_request arguments and can return custom error page
- changed skitaid.py command line options, see 'skitaid.py --help'
- batch task scheduler added
- e-mail sending fixed
- was.session.getv () added
- was.response spec. changed
- SQLite3 DB connection added

0.13 (Feb 2016)

- was.mbox, was.g, was.redirect, was.render added
- SQLite3 DB connection added

0.12 (Jan 2016) - Re-engineering 'was' networking, PostgreSQL & proxy modules

0.11 (Jan 2016) - Websocket implemeted

0.10 (Dec 2015) - WSGI support

.. _Chameleon: https://chameleon.readthedocs.io/en/latest/index.html