Metadata-Version: 1.1
Name: skitai
Version: 0.30.0.1
Summary: Skitai App Engine
Home-page: https://gitlab.com/hansroh/skitai
Author: Hans Roh
Author-email: hansroh@gmail.com
License: MIT
Download-URL: https://pypi.python.org/pypi/skitai
Description: 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 -U skitai rs4 aquests sqlphile
        
        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.
        
        
        Introduce
        ==============
        
        Skitai is WSGI server and more than that.
        
        Skitai/Atila_ has purpose for providing complete online runtime
        environment for Python apps. You can make high concurrency with
        async sockect works, threading, processing and subprocessing.
        And you can use them with highly consistent manner.
        
        Skitai handles requests with mainly asynchronous event loop and
        threading pool and support websocket
        within WSGI specification not with ASGI nor asyncio (It use asyncore).
        
        .. _Atila: https://pypi.python.org/pypi/atila
        
        .. contents:: Table of Contents
        
        
        Installation
        =========================
        
        **Requirements**
        
        Python 3.5+
        
        **Installation**
        
        With pip
        
        .. code-block:: bash
        
            pip3 install -U rs4 aquests sqlphile skitai
        
        From git
        
        .. code-block:: bash
        
            git clone https://gitlab.com/hansroh/skitai.git
            cd skitai
            python3 setup.py install
            pip3 install -U rs4 aquests sqlphile
        
        
        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 restarting
        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 long options starts
        with "---", then you SHOULD NOT use these options.
        Also Skitai use satrt, restart, status, stop in args.
        then these arguments are removed automatically.
        
        .. code:: python
        
          skitai.add_options ("--dist", "--syndb", "--port=")
        
            if "--syndb" in skitai.options:
                skitai.disable_adbi ()
            port = skitai.options.get ('--port', 5000)
        
        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 Non-Thread Pool
        -----------------------------------------
        
        If you want to run Skitai with entirely main thread only,
        
        .. 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.
        
        
        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
        
        
        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:password@members.example.com: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.
        
        
        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
        
            from skitai import was
        
            # 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 ()
        
        For enabling this features,
        
        .. code:: bash
        
          skitai smtpda start
          # or
          skitai smtpda -d
        
        Or you just give command line option to skitai startup script.
        
        .. code:: bash
        
          serve.py ---smtpda
        
        All e-mails are saved into *varpath* and varpath is not
        specified default is /var/temp/skitai.
        
        This service will run as system-wide daemon service,
        and will be not stopped even if app engine is stopped. For stopping it,
        
        .. code:: bash
        
          skitai smtpda status
          skitai smtpda stop
        
        
        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 ()
        
        
        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
        
        
        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
        
        
        Skitai with Nginx
        ---------------------------
        
        Here's some helpful sample works with Nginx.
        
        .. code:: bash
        
          # 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;
            }
          }
        
        
        Enabling API Gateway Server (Experimental)
        -------------------------------------------------------------
        
        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
        
          def handle_claim (request_handler, request):
            claim = request.claim
            expires = claim.get ("expires", 0)
            if expires and expires < time.time ():
              return request_handler.continue_request (request)
            request_handler.continue_request (request, claim.get ("user"), claim.get ("roles"))
        
          @app.before_mount
          def before_mount (wac):
            wac.handler.set_auth_handler (handle_claim)
        
          @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 rs4 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 be
        explained in Skitai 'was' Service chapter.
        
        
        
        Run as Win32 Service (Deprecated)
        --------------------------------------------------
        
        *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
        
        
        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
          )
        
        Extending/Customizing Services
        -----------------------------------------------
        
        *New in version 0.28.15*
        
        If you want to customize/extend services, create 'extends'
        directory and mount it to pref.
        
        .. code:: python
        
          # extends/apis.py
          def __mount__ (app):
            @app.permission_check_handler
            def permission_check_handler (was, perms):
              ...
        
            @app.route ("")
            def apis_index (was):
              return 'APIS'
        
        .. code:: python
        
          # serve.py
          import unsub
          from extends import apis
        
          pref = skitai.pref ()
          pref.mount ('/apis', apis)
          pref.config.urlfile = skitai.abspath ('resources', 'urllist.txt')
        
          skitai.mount ("/v1", unsub, "app", pref)
          skitai.run ()
        
        You can access it by /v1/apis
        
        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.
        
        For example with Flask app,
        
        .. code:: python
        
          import request
        
          @app.route ("/echo3")
          @skitai.websocket (60) # timeout
          def echo3 ():
            ws = request.environ ["websocket"]
            while 1:
              message = yield
              if not message:
                return #strop iterating
              yield "ECHO:" + message
        
        I you want to send multiple messages,
        
        .. code:: python
        
          yield ['OK', 'Task 1 started', 'Check later, please']
          # OR
          yield output_iterator ()
        
        
        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
        
          @app.route ("/websocket")
          @app.websocket (skitai.WS_CHANNEL | skitai.WS_SESSION, 60)
          def websocket (was):
            while 1:
              message = yield
              if not message:
                return #strop iterating
              yield "ECHO:" + message
        
        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")
        
        
        Corequest
        ================
        
        Skitai handle request connection with asynchronously,
        also has threads and porcess ass workers.
        So it works fine with synchronous apps and libraries.
        You can use standard database client libraries or requests
        module for API calls.
        
        But Skitai's main event loop (using asyncore.loop) can be
        used for not only client's requests else request to another
        servers(API, Database engine...) asynchronously.
        
        I think if I don't use this capabitities, it would be
        wasting resources. Then, Skitai provide asynchronous
        request methods for these operations.
        
        *Corequest* is similar with Python coroutine object, but is
        is not compatable at all.
        
        - It is automatically started at creation, no need to call run ()
        - All events are controlled by Skitai main event loop, not by asyncio
        - It is eventually synchronous within current thread. It is desinged
          for working with multi-threading environment and synchronous code
          base so it has no differences with synchronous code base, just if
          you have to consider the most efficient point to call for waiting results
        - It is not a framework nor a library. It is a Skitai native object
          has specified purpose and usage
        
        Skitai provides some services related with corequests:
        
        - Concurrent requests (like asyncio or gevent) to your
          API/Backend and Database engine servers
        - Connection pooling
        - Result caching
        
        These features are just optional, but these might help
        increase availability of your servers.
        
        For using 'corequest', you need to import 'was':
        
        .. code:: python
        
          from skitai import was
        
          @app.route ("/")
          def hello ():
            was.get ("http://...")
        
        
        Basic
        -------------------------
        
        Task
        ```````````
        
        Single corequest object.
        
        API Call
        ~~~~~~~~~~~~~~~~
        
        - was.get ()
        - was.post ()
        - was.put ()
        - was.patch ()
        - was.delete ()
        - was.upload ()
        
        Task will be created by just calling these methods.
        
        .. code:: python
        
          task = was.get ('@myapi/v1/some-resources/100')
        
        RPC Call
        ~~~~~~~~~~~~~~~~~
        
        - was.xmlrpc ()
        - was.grpc ()
        - was.jsonrpc ()
        
        Task will be created like this,
        
        .. code:: python
        
          with was.xmlrpc ('@myrpc/rpc2') as stub:
            task = stub.some_method (arg1, arg2)
        
        Database Call
        ~~~~~~~~~~~~~~~~~~
        
        - was.db (): PostgreSQL, SQLite3, MongoDB and Redis calls
        - was.transaction (): for RDBMS (PostgreSQL and SQLite3)
        
        Task will be created like this,
        
        .. code:: python
        
          # PostgreSQL and SQLite3
          with was.db('@mydb') as db:
            task = db.select ('my_table').execute ()
        
          # Redis or MongoDB
          with was.db('@mynosql') as db:
            task = db.find ({'city': 'New York'})
        
        Thread/Process Call
        ~~~~~~~~~~~~~~~~~~~~~~~~~~~~
        
        - was.Thread ()
        - was.Process ()
        - was.Subprocess ()
        
        Task will be created like this,
        
        .. code:: python
        
          task = was.Thread (my_func, arg1, arg2)
        
        Methods of Task
        ~~~~~~~~~~~~~~~~~~~~~~~~~
        Task has below core methods:
        
        - dispatch (timeout)
        - fetch (timeout)
        - one (timeout): should be single lengthed object
        - commit (timeout)
        - returning (data)
        
        Tasks
        ````````````````````
        
        It is bundle of Tasks.
        
        You can make it by wrapping.
        
        .. code:: python
        
          tasks = was.Tasks ([task1, task2])
          result1, result2 = tasks.fetch ()
        
        And it has also same methods as Task. But it can be accessed
        by slicing or indexing for easy handling.
        
        Mask
        ````````````````````
        
        It is fake of Task(s).
        
        You can make it by wrapping was.Mask (data) if you want to
        use consistant methods as Task.
        
        .. code:: python
        
          task = was.Mask (1)
          result = task.fetch () # 1
        
          tasks = was.Mask ([1, 2])
          result1, result2 = tasks.fetch () # 1, 2
        
        
        Long Running Task(s)
        ````````````````````````````````
        
        corequests is natively a kind of backgound jobs. So you can
         create these tasks and return yotur response - usally 202 Accepted.
        
        More explicit way, creating tasks and immediately return 202 response.
        
        .. code:: python
        
          return was.post ('@myapi/v1/some-resources').returning (Response ('202 Accepted'))
        
          return was.Thread (func, arg).returning (Response ('202 Accepted'))
        
        Future(s)
        `````````````````
        
        *Available on Atila only*
        
        On Atila_, you can hook the callback function with corequest objects.
        
        - Task can be transformed into Future
        - Tasks can be transformed into Futures
        
        Future/Futures object can be returnable and it has the benefit
        when your jobs are IO bound and long running time (but reasonably
        close enough to real time). It returns current thread qucikly,
        lazy respond when job is done.
        
        
        Calling API
        ------------------------
        
        .. code:: python
        
          @app.route (...)
          def request (was):
            req = was.get (url)
            resp = req.dispatch (timeout = 3)
            return resp.data
        
        In fact, single request is just like synchronous task at least current thread.
        
        .. 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]
        
        Note that req1 and req2 will be executed concurrently.
        
        dispath (timeout = [sec], cache = [sec]) returns response object.
        
        .. code:: python
        
          req = was.get (url)
          rsponse = req.dispath (5) # timoute
          response.status # skitai.STA_NORMAL
          response.status_code # 200
          response.reason # OK
          response.get_header ("Content-Type") # application/json
          response.data # {"result": "ok"}
        
        response.status is one of belows:
        
        - STA_UNSENT
        - STA_REQFAIL
        - STA_TIMEOUT
        - STA_NETERR
        - STA_NORMAL
        
        Note that STA_NORMAL just mean all requesting precess is
        normally completed, NOT response is. Then you SHOULD check
        before handle result data.
        
        dispath_or_throw () will raise exception immediatly if
        status !=  STA_NORMAL or status_code >= 300.
        
        .. code:: python
        
          rsponse = req.dispath_or_throw (5) # timoute
        
        If you want more short hand to result data,
        
        .. code:: python
        
          result = req.fetch (5) # timoute and {"result": "ok"}
        
        result = fetch (5) is equivalant with,
        
        .. code:: python
        
          rsponse = req.dispath_or_throw (5) # timoute
          response = response.data
        
        All supoorted request methods are:
        
        HTTP/API related methods are,
        
        - 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, use headers paramter for each request
        
        .. code:: python
        
          data = {"Title": "...", "Content": "..."}
          headers = [
            ("Content-Type", "application/x-www-form-urlencoded"),
            ("Accept", "text/xml")
          ]
          req = was.post ("@delune/documents", data, headers = headers)
        
        
        Tasks
        -----------------------
        
        Tasks is pack of corequests. It can handle multiple corequests as single one.
        
        .. code:: python
        
          @app.route (...)
          def request (was):
            reqs = [
              was.get (url),
              was.post (url, {"user": "Hans Roh", "comment": "Hello"})
            ]
            a, b = was.Tasks (reqs, timeout = 3).fetch ()
            return was.API (a = a, b = b)
        
        Tasks is iterable and slicable and returened rs is response
        object (by dispatch ()). You SHOULD check rs.status and
        status_code for validating response, or just use fetch ()
        for raising error if invalid.
        
        - Tasks (reqs, timeout = 10, \*\*meta)
        - Tasks.add (corequest): append corequest or Task object
        - Tasks.merge (corequest): append corequest or Task object,
          in case Tasks, it will be extracted from inner corequests
        - Tasks.then (callabck): convert Tasks to Futures, available only for Atila app
        
        - Tasks.dispatch (cache = None, cache_if = (200,), timeout = None)
        - Tasks.wait (timeout = None)
        
        - Tasks.commit (timeout = None)
        - Tasks.fetch (cache = None, cache_if = (200,), timeout = None)
        - Tasks.one (cache = None, cache_if = (200,), timeout = None)
        
        - Tasks.meta: dictionary container for user data
        
        *Note:* If you want to use full asynchronous manner,
        you can consider Atila's Futures_, but it need to pay some costs.
        
        .. _Futures: https://pypi.org/project/atila/#futures-response
        
        
        Calling RPC
        --------------------
        
        .. code:: python
        
          @app.route (...)
          def request (was):
            with was.xmlrpc ("@myrpc") as stub:
              req = stub.get_version ("skitai")
              return req.fetch () # ["0.29"]
        
              # or single line
              return stub.get_version ("skitai").fetch ()
        
        was.jsonrpc and was.grpc (Experimental) are also possible.
        
        For 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
        
        .. _aquests: https://pypi.python.org/pypi/aquests
        .. _tfserver: https://pypi.python.org/pypi/tfserver
        
        
        RDBMS Querying
        ------------------------------
        
        *Important Note:* Async mode you cannot use transaction,
        and auto commit will be applied.
        
        PostgreSQL query at aquests, First uou alias your database
        before running Skitai.
        
        .. code:: python
        
          skitai.alias ("@mypg", skitai.DB_PGSQL, "user:pass@localhost/mydb")
          skitai.alias ("@mylite", skitai.DB_SQLITE3, "./sqlite3.db")
          skitai.run ()
        
        Then,
        
        .. code:: python
        
          @app.route (...)
          def query (was):
            with was.db ("@mypg") as db:
              req = db.excute ("SELECT city, t_high, t_low FROM weather;")
              resp = req.dispatch (timeout = 2)
              if resp.status != 200:
                raise HTTPError ("500 Server Error")
            for row in rows:
              row.city, row.t_high, row.t_low
        
        For consistency handling response of API calls,
        response.status_code will be set 200 if any error
        does not occure, otherwise set 500.
        
        Basically Skitai handle as same for all kind of external requests.
        
        .. code:: python
        
          @app.route (...)
          def query (was):
            with was.db ("@mypg") as db:
              req = db.excute ("SELECT city, t_high, t_low FROM weather;")
              rows = req.fetch (2)
            for row in rows:
              row.city, row.t_high, row.t_low
        
        If you needn't returned data and just wait for completing query,
        
        .. code:: python
        
            db.execute ("INSERT INTO CITIES VALUES ('New York');").commit (timeout = 2)
        
        If failed, exception will be raised.
        
        In case database querying, you can use one () method.
        
        .. code:: python
        
          @app.route (...)
          def query (was):
            with was.db ("@mypg") as db:
              hispet = db.excute ("SELECT ... FROM pets").one (timeout = 2)
        
        If result record count is not 1 (zero or more than 1), raise HTTP 410 error.
        
        With PostgreSQL you can also raise HTTP 409 using returning caluse.
        
        .. code:: python
        
          @app.route (...)
          def query (was):
            with was.db ("@mypg") as db:
              hispet = db.excute ("INSERT INTO pets ... RETURNING id").one (timeout = 2)
        
        If primary key or unique key is duplicated, psycopg2
        raises IntegrityError then Skitai raise HTTP 409 Conflict error
        
        *CAUTION*: DO NOT even think your statements will be
        executed ordered sequencially.
        
        .. code:: python
        
          @app.route (...)
          def query (was):
            with was.db ("@mypg") as db:
              reqs = [
                db.excute ("INSERT INTO weather (id, 'New York', 9, 25);"),
                db.excute ("SELECT city, t_high, t_low FROM weather order by id desc limit 1 ;")
              ]
              Tasks (reqs) [1].fetch () # No guarantee it is New York or something new
        
        Execute and wait or use transaction.
        
        .. code:: python
        
          @app.route (...)
          def query (was):
            with was.db ("@mypg") as db:
              db.excute ("INSERT INTO weather (id, 'New York', 9, 25);").commit ()
              latest = db.excute ("SELECT city, t_high, t_low FROM weather order by id desc limit 1 ;").fetch (2)
              # latest  is New York
        
        Using Database Transaction
        -------------------------------------------
        
        If you want use asynchronous database transaction,
         you can use asynchronous drivers.
        
        Also Skitai provide PostgreSQL connection with connection
        pool. And SQLite connection without pool.
        
        .. code:: python
        
          @app.route ("/")
          def index (was):
              with was.transaction ("@mypg") as tx:
                  tx.execute ('INSERT ...')
                  tx.execute ('UPDATE ...')
                  tx.execute ('SELECT ...')
                  tx.fetch () # equivlant to fetchall () but list of dict type
                  tx.commit ()
        
        With context manager, connection will return back to the pool
        automatically else you SHOULD call tx.putback () manually.
        
        In transaction mode, standard DBAPI - rollback (), fetchall (),
        fetchone () and fetchmany () are also possible but caching is not.
        
        was.transaction has second paramter 'auto_putback'. If it is False,
        transaction object does not return to the pool automatically.
        
        .. code:: python
        
          # models.py
          from skitai import was
        
          def update (...):
              with was.transaction ("@mypg", False) as tx:
                  tx.execute ('INSERT ...')
                  tx.execute ('UPDATE ...')
                  tx.execute ('SELECT ...')
                  return tx
        
                  tx.fetch () # equivlant to fetchall () but list of dict type
        
          # app.py
          import models
        
          @app.route (...)
          def update (was):
            tx = models.update (...)
            rows = tx.fetch ()
            tx.commit ()
        
        Note that you MUST call commit/rollback finally, if not
        connection pool will be exhausted very soon and entire threads
        will be blocked.
        
        
        Using SQLPhile for Querying
        ----------------------------------------------
        
        Actullay, was.db and was.transaction are fully intergrated with SQLPhile_.
        
        You can write with raw SQL,
        
        .. code:: python
        
          with was.db ("@mydb") as db:
            rows = db.execute (
              "SELECT a.id, b.name, c.phone "
              "FROM user a, profile b, contact c "
              "WHERE b.name like '%{name}%'"
              "ORDER BY a.id desc"
              "LIMIT {limit}".format (name = name, limit = limit)
            ).fetch ()
        
        But also can use SQLPhile_ style,
        
        .. code:: python
        
          with was.db ("@mydb") as db:
            rows = (db.get ("a.id, b.name, c.phone")
                    .select ("user a, profile b, contact c")
                    .filter (b__name__contains = name)
                    .order_by ("-a.id") [:limit]
                    .execute ().fetch ())
        
        It may be not very helpful because of my laziness of documentation,
        however SQLPhile_ can provide some other benefits using SQL I
        recommend read it instantly.
        
        .. _SQLPhile: https://pypi.org/project/sqlphile/
        
        NoSQL Querying
        ------------------------------------
        
        .. code:: python
        
          skitai.alias ("@mymongo", skitai.DB_MONGODB, "localhost/mycollection")
          skitai.alias ("@myredis", skitai.DB_REDIS, "localhost/0")
          skitai.run ()
        
        Then,
        
        .. code:: python
        
          @app.route (...)
          def query (was):
            with was.db ("@mymongo") as db:
              documents = db.find ({'city': 'New York'}).fetch (2)
        
            with was.db ("@myredis") as db:
              db.set('foo', 'bar').wait ()
              db.get('foo').fetch () # bar
        
        
        Request As Many You Need
        ------------------------------------------------
        
        For getting concurrent tasks advantages, you request at
         once as many as possible.
        
        .. code:: python
        
          @app.route (...)
          def query (was):
            reqs = was.post ("@pypi/upload...", {data: ...})
            reqs = was.get ("@pypi/somethong..."})
            with was.db ("@mypg") as db:
              reqs.append (db.excute ("SELECT ..."))
              reqs.append (db.excute ("SELECT ..."))
        
            with was.jsonrpc ("@pypi/pypi") as stub:
              reqs.append (stub.get_version ("skitai"))
              reqs.append (stub.get_version ("atila"))
        
            contents = []
            for rs in Tasks (reqs, 3):
              if rs.status_code != 200:
                contents.append ("Error")
              else:
                contents.append (str (rs.data))
            return contents
        
        
        Intermezzo
        -------------------
        
        For creating corequest object,
        
        - HTTP based request: was.get (alias), .post (alias), ....
        - Database request: as.db (alias).execute (...), .find (),
          set (), ... other MongoDB and Redis methods
        - Tasks: bundle of corequests
        
        Corequest object has main 5 methods.
        
        - dispatch (): it returns Result object contains data
          (or text/content) and request status information
        - wait (): it returns Result object contains request status information
        - fetch (): it returns records list. if request failed raise exception
        - one (): it returns one record if query result length is exactly
          one otherwise raise 410 or 409 HTTP error. if request failed
          raise exception
        - commit (): it wait finishing non-select query, if request failed
          raise exception
        
        Result object is mainly used for checking status and handling error
        to individual corequest, and Result object also has fetch (), one ()
        and commit ().
        
        Please DO remember. If ou call dispatch, fetch, ... to corequest
        object, it immediatly act as synchronous task. But already created
        another corequests are still has concurrency.
        
        
        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"):
            with was.jsonrpc.lb ("@mysearch/rpc2") as stub:
              s = stub.search (keyword)
              results = s.dispatch (timeout = 5)
              return result.data
        
              # or short hand
              return stub.search (keyword).fetch (5)
        
          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.jsonrpc () to was.jsonrpc.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. And it will be remapped to http://s1.myserver.com/.
        
        If you mount like this,
        
        .. code:: bash
        
          skitia.mount ("/search", '@mysearch/search')
        
        It can be accessed from same URL, but it will be remapped
        to http://s1.myserver.com/search.
        
        
        This sample is to show loadbalanced querying database.
        Add mydb members to config file.
        
        .. code:: python
        
          @app.route ("/query")
          def query (was, keyword):
            with was.db.lb ("@mydb") as dbo:
              req = dbo.execute ("SELECT * FROM CITIES;")
              result = req.dispatch (timeout = 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"):
            with was.rpc.map ("@mysearch/rpc2") as stub:
              req = stub.search (keyword)
              results = req.dispatch (timeout = 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
        
        You can use Dataabse, API calls same way.
        
        
        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 (60, timeout = 2) # cache seconds
          result.data
        
          s = was.rpc.map ("@mysearch/rpc2").getinfo ()
          results = s.dispatch (60, timeout = 2)
        
        Cahing when just only Although code == 200 alredy implies status == STA_NORMAL.
        
        
        *New in version 0.15.28*
        
        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 ()
        
        For expiring cached result by updating new data:
        
        .. code:: python
        
          refreshed = False
          if was.request.method == "POST":
            ...
            refreshed = True
        
          s = was.rpc.lb (
            "@mysearch/rpc2",
            use_cache = not refreshed and True or False
          ).getinfo ()
          result = s.fetch (2, 60)
        
        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 (60, (200, 201), timeout = 2)
        
        
        More About Cache Control: Model Synchronized Cache
        ```````````````````````````````````````````````````
        
        *New in version 0.26.15*
        
        You can efficient cache with explicit model mutation time.
        
        - when your model is changed, call was.setlu ("model-state-name")
        - when query your model, add parameter - was.getlu ("model-state-name"),
          for deciding if use cache or not
        
        *Note* that it is useful only if your model make regular and controlled
        mutation by single or a few producer (any of computer, machine or human).
        Otherwise you could consider NoSQL things for your cache system, and
        Skitai corequest support MongoDB and Redis.
        
        
        Corequest's `use_cache` parameter 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.register_states ('tables.users', 'table.photos')
        
        These key names are might be related your database model names nor table names. 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 ().
        
        Also it can be used as decorator for clarency.
        
        .. code:: python
        
          import skitai
        
          @skitai.register_states ('tables.users')
          class User:
            ...
        
        
          @skitai.register_states ('tables.users', 'table.photos')
          def __mount__ (app):
            @app.route (...)
            def index (...):
               ...
        
        
        Then you can use setlu () and getlu (),
        
        .. code:: python
        
          app = Atila (__name__)
        
          @app.route ("/update")
          def update (was):
            # update users tabale
            was.db ('@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.db ('@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.db ('@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.db ('@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.
        
        
        Corequest Based Model
        ---------------------------------------------
        
        Here's an model example with RDBMS.
        
        
        Alias Your Database
        ````````````````````````````
        
        First of all, alias your database to Skitai.
        
        .. code:: python
        
          # serve.py
          ...
          skitai.alias ("@blog", skitai.DB_PGSQL, "postgres:password@localhost/blog")
          ...
          skitai.run (port = 5000)
        
        
        Create Model Classes
        ````````````````````````````````````
        
        I think all public model methods maybe return *corequest object or None*.
        
        .. code:: python
        
          # services/models.py
        
          from skitai import was
          import skitai
          from sqlphile import Q
          from datetime import datetime
        
          class BlogPost:
            EXCLUDES = Q (share = 'test')
        
            @classmethod
            def search (cls, keyword = None, period = None, offset = 0, limit = 10, fields = "*"):
                with was.db ("@blog") as db:
                    stem = (db.select ("blogpost")
                             .get (fields)
                             .exclude (cls.EXCLUDES)
                             .filter (posted_at__between = period)
                             .filter (Q (title__contains = keyword) | Q (content__contains = keyword)))
        
                    reqs = [
                        stem.branch ().get ("count (*) as total").execute (),
                        (stem.branch ()
                            .order_by ("-posted_at").offset (offset).limit (limit)
                            .execute ())
                    ]
                    return was.Tasks (reqs)
        
            @classmethod
            def get (cls, id, fields = "*"):
                with was.db ("@blog") as db:
                    return (db.select ("blogpost")
                                .get (fields)
                                .filter (id = id).execute ())
        
            @classmethod
            def delete (cls, id):
                # example for transaction deletion
                was.setlu (STATE_POST)
                with was.transaction ("@blog") as db:
                    (db.delete ("blogcomment")
                                .filter (post_id = id).execute ())
                    (db.delete ("blogpost")
                                .filter (id = id).execute ())
                    db.commit ()
        
            @classmethod
            def add (cls, post):
                was.setlu (STATE_POST)
                with was.db ("@blog") as db:
                    return (db.insert ("blogpost")
                                .data (post)
                                .returning ("id").execute ())
        
            @classmethod
            def update (cls, id, post):
                was.setlu (STATE_POST)
                post ["updated_at"] = datetime.now ()
                with was.db ("@blog") as db:
                    return (db.update ("blogpost")
                                .data (post)
                                .filter (id = id).execute ())
        
            @classmethod
            def get_comments (cls, id, offset = 0, limit = 10):
                with was.db ("@blog") as db:
                    return (db.select ("blogcomment")
                              .filter (post_id = id)
                              .offset (offset).limit (limit)
                              .execute ())
        
            @classmethod
            def get_stat (cls, dateunit = 'year'):
                with was.db ("@blog") as db:
                    return (db.select ("blog")
                            .get (f"date_part('{dateunit}', created_at) as year, count (*) as cnt")
                            .group_by ("year")
                            .execute ())
        
        
        Using Models
        ```````````````````````````
        
        Finally, you can use this models.py.
        
        .. code:: python
        
          # services/blog.py
          from . models import BlogPost
        
          @app.route ("/posts/", methods = ["GET", "POST"])
          def posts (was, offset = 0, limit = 10, **payload):
            if was.request.method == "GET":
              stat, posts = BlogPost.search (offset = int (offset), limit = int (limit)).fetch ()
              return was.API (posts = posts, total = stat [0].total)
        
            new_post = BlogPost.add (payload).one ()
            return was.API ("201 Created", id = new_post.id)
        
          @app.route ("/posts/<int:id>", methods = ["GET", "PATCH", "DELETE", "OPTIONS"])
          def post (was, id, num_comments = 0):
            if was.request.method == "GET":
              comments_ = BlogPost.get_comments (id, 0, int (num_comments))
              post = BlogPost.get (id).one ()
              post.comments = comments_.fetch ()
              return was.API (post = post)
        
            if was.request.method == "DELETE":
              BlogPost.delete (id)
              return was.API ("204 No Content")
            ...
        
          @app.route ("/posts/int:id>/comments", methods = ["GET", "PATCH", "DELETE", "OPTIONS"])
          def comments (was, id, offset = 0, limit = 10):
            if was.request.method == "GET":
              comments = BlogPost.get_comments (id, int (offset), int (limit)).fetch ()
              return was.API (comments = comments)
            ...
        
        
        Conclusion
        `````````````````````````
        
        Above example pattern is just one of my implemetation with async models.
        
        It can be extended and changed into NoSQL or even RESTful/RPC
        with any Skitai corequest object which has same 5 methods - dispatch,
        wait, fetch, one and commit.
        
        
        Background Tasks
        ---------------------------------
        
        Skitai integrated async/sync concurrents. They have also very
        same usage and methods like fetch, one, dispatch etc.
        
        Task(s) object is natively async corequests. It creates backgorund
        async jobs and can be responded immediately.
        
        .. code:: python
        
          @app.route ('...')
          def foo ():
            req = was.get ("@myupstream/something")
            return  req.returning (
              Response ('', 202, headers = {'Content-Location': "..."})
            )
        
        Tasks is also available,
        
        .. code:: python
        
          @app.route ('...')
          def foo ():
            reqs = [
              was.get ("@myupstream/something"),
              was.post ("@myupstream/something", {})
            ]
            return was.Tasks (reqs).returning (
              Response ('', 202, headers = {'Content-Location': "..."})
            )
        
        *Note*: With Atila_, you can add callback for late response.
        
        Process / Thread is very same as Task.
        
        Skitai will create thread/process pool as you use it at once.
        If you do't use this, pool will not be created for resource
        saving. Pool size is your number of CPUs.
        
        You can just use multi processing with pool instantly.
        
        .. code:: python
        
          def side_job (a, b):
            ...
        
          @app.route ('...')
          def foo ():
            ps = was.Process (job2, 1000, -1000)
            ...
            result = ps.fetch () # wait for finishing
            return Response (result, 200, headers = {'Content-Type': "application/vnd-..."})
        
        Also you can create async jobs for long run process.
        
        .. code:: python
        
          @app.route ('...')
          def foo ():
            return was.Process (job2, 1000, -1000).returning (
              Response ('', 202, headers = {'Content-Location': "..."})
            )
        
        was.Thread () and was.Subprocess () are also available.
        
        - was.Thread (target, \*args, \*\*kargs):
          return wrapper of concurrent.futures.Future
        - was.Process (target, \*args, \*\*kargs):
          return wrapper of concurrent.futures.Future
        - was.Subprocess (command, timeout = 300):
          return wrapper of subprocess.Popen
        
        *Note*: With Atila_, you can add callback for late response.
        
        
        Miscellaneous
        ==============================
        
        Inter Process State Sharing
        -----------------------------------------
        
        *New in skitai version 0.26.18*
        
        Already mentioned 'skitai.register_states ()'  can be used
        for allocating shared memory for inter-process named state.
        
        .. code:: python
        
          import skitai
        
          skitai.register_states ("current-user", ...)
        
        Then one process update object by setgs (name, value),
        the others can be access it by getgs (name).
        
        Note that value type is shoul be integer.
        
        .. code:: python
        
          @app.before_request
          def before_request (was):
            was.setgs ("current-user", was.getgs ("current-user") + 1)
        
          @app.teardown_request
          def teardown_request (was):
            was.setgs ("current-user", was.getgs ("current-user") - 1)
        
        
        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.
        
        
        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
        ===========
        
        
        - 0.30 (Sep 2019)
        
          - skitai.websocket spec changed, lower version compatable but warned
        
        - 0.29 (Aug 2019)
        
          - add was.Subprocess
          - add handlers for Range, If-Range, If-Unmodified-Since, If-Match headers
          - asyncore and asynchat are vendored as rs4.asyncore and chat,
            because they will be exsanguinated from standard Python library.
            Mr. Rossum has been listed up on my mortal enemy list
          - deprecated: was.Future and was.Futures, it doesn't need. for
            using returning (), use corequest.returning () and was.Tasks.returning ()
          - new corequest.pth package
          - over 100 unit tests
        
        - 0.28 (Feb 2019)
        
          - fix auto reloading bug in case multiple apps are mounted
          - add was.Thread () and was.Process ()
          - add @skitai.states () decorator
          - rename skitai.deflu () => skitai.register_states ()
          - add corequest object explaination and corequest based model example
          - drop SQLAlchemy query statement object
          - fix https proxypass, and add proxypass remapping
          - 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
          changed 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
        .. _hyper-h2: https://pypi.python.org/pypi/h2
        
Platform: posix
Platform: nt
Classifier: License :: OSI Approved :: MIT License
Classifier: Development Status :: 4 - Beta
Classifier: Topic :: Internet :: WWW/HTTP :: HTTP Servers
Classifier: Topic :: Internet :: WWW/HTTP :: WSGI
Classifier: Environment :: Console
Classifier: Environment :: No Input/Output (Daemon)
Classifier: Topic :: Internet
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Intended Audience :: Developers
Classifier: Programming Language :: Python :: 3
