mtango-py

Python implementation of mTango API

---

Description

This project aims to be a drop-in replacement for mTango (mtangorest.server).
Currently it supports a subset of rc3 mTango API, mostly functions related to reading data from Tango. Supported HTTP methods are GET and OPTIONS, the latter is used only for CORS support.

API Documentation

mtango-py server uses two APIs:

• mTango rc3 API
• internal system API

mTango API rc3

The documentation for rc3 API can be found -> here <-.

Differences between original and Python implementation

mtango-py supports only reading data from Tango. That means that only GET and OPTIONS HTTP methods are implemented.
For all endpoints and methods described in the API documentation but not implemented in mtango-py the server will return HTTP 501 Not Implemented response.
There is no support for authorization in the current version, all auth details provided will just be ignored.
The TANGO_HOST part of the URL is only for the compability, regardless of the values passed there, the server will always use system-wide TANGO_HOST for database connection.
Currently, there is no support for filters and ranges.
There is also no support for events.
Also, the HTTP status code returned by the server is always 200 OK in case of successful request. HTTP errors are handled properly, but Tango errors also return 200 OK. The general rule of thumb for the current version is that if you get 200 OK then you should receive a proper JSON response, regardless if it contains the actual result or error description.
There are also differences caused by using "implementation mode", you can read more in the Configuration section.

If your client uses any of features described here, you may want to implement the detection of which server implementation is used. For this, mtango-py adds a custom HTTP header: x-mtango: mtango-py <version>.

System API

System API is used to gather statistics about running server instance, as well as to schedule garbage collection.
This description uses <base> as the application base address, which is usually http://<server>:<port>/tango/rest.

Available endpoints:

• <base>/sys API entry point, links to other functions

  {
    "version": "mtango-py 0.0.4-testing",
    "config": "http://localhost:8000/tango/rest/sys/config",
    "active": [
      "http://localhost:8000/tango/rest/sys/active/devices",
      "http://localhost:8000/tango/rest/sys/active/attributes"
    ],
    "stats": "http://localhost:8000/tango/rest/sys/stats",
    "gc": [
      "http://localhost:8000/tango/rest/sys/clean/devices",
      "http://localhost:8000/tango/rest/sys/clean/attributes"
    ]
  }
  

• <base>/sys/config Lists server configuration

  {
    "version": "0.0.4-testing",
    "app_base": "/tango/rest",
    "debug": true,
    "port": 8000,
    "host": "0.0.0.0",
    "TANGO_HOST": "10.81.0.101:10000",
    "rc3_mode": "strict",
    "workers": 4
  }
  

• <base>/sys/cache/devices DeviceProxies cache info

  {
    "currsize": 6,
    "maxsize": 64,
    "misses": 6,
    "hits": 2
  }
  

• <base>/sys/cache/attributes AttributeProxies cache info

  {
    "currsize": 1,
    "maxsize": 64,
    "misses": 1,
    "hits": 0
  }
  

• <base>/sys/stats Server process statistics

  {
    "responses": 8,
    "running_since": 1501580659.3465743,
    "time": 1501581691.0546196,
    "resource": {
      "context_switch": {
        "voluntary": 1166,
        "involuntary": 25
      },
      "system_time": 0.024,
      "shared_mem": 0,
      "unshared_stack_mem": 0,
      "page_faults": {
        "minor": 1925,
        "major": 27
      },
      "recv_msgs": 0,
      "max_resident_mem": 46872,
      "sent_msgs": 0,
      "swap_out": 0,
      "user_time": 0.352,
      "signals": 0,
      "block": {
        "output": 0,
        "input": 4488
      },
      "unshared_mem": 0
    },
    "requests": 9,
    "proxies": {
      "device": 2,
      "attribute": 2
    }
  }
  

• <base>/sys/clean/devices Invalidate DeviceProxy cache
  This function does not return any content, only a 204 No Content HTTP response.
• <base>/sys/clean/attributes Invalidate AttributeProxy cache
  This function does not return any content, only a 204 No Content HTTP response.

IMPORTANT NOTE ! Functions related to process statistics and proxy caches (sys/stats, sys/cache/* and sys/clean/*) have known problems when using more than 1 worker process. Data returned and actions performed are tied to worker process that happens to handle your request. This is considered a work in progress feature.

Swagger

The application provides three Swagger description files:

• /swagger/main.yml - description of application entry point
• /swagger/rc3.yml - mTango rc3 API
• /swagger/sys.yml - mtango-py system API

Keep in mind, that if you change app_base in the configuration, you should also change basePaths in Swagger files for them to work.

Configuration

The configuration is stored in conf.py file in the repository main directory.
The available options are:

• app_base - defines base URL for the application (default: /tango/rest)
• version - the object describing the server version; you shouldn't really change this
• workers - number of Sanic worker processes
• debug - Sanic's debug mode
• host - server host name or IP address
• port - server port
• rc3_mode - can be one of two:
  • strict - responses are returned exactly as described in the API documentation
  • implementation - mimics the behaviour of the original mTango implementation
    In current version, this option affects only the attribute properties call.
    In strict mode these are returned as an object, with keys being properties names, and values - property values.
    In implementation mode these are returned as list of objects containing name and _empty attributes.

Requirements

• Python 3.5
• PyTango 9.2
• sanic
• sanic-cors

Running

The fastest and easiest way to get started with mtango-py is using conda.

1. Download and install miniconda (https://conda.io/miniconda.html).
2. Enable conda environment by running . $CONDA_ROOT/bin/activate.
3. Create environment with Python 3.5: conda create -n mtango-py python=3.5
4. Activate your new environment: . activate mtango-py
5. Install PyTango with all dependencies: conda install -c tango-controls pytango
6. Install Sanic: pip install sanic sanic-cors

To start the server run python main.py in the main directory.

Testing

Requirements

Tests require pytest and pytest-xdist packages.
For all tests to pass you have to have several things configured in Tango database:

• TangoTest device named sys/tg_test/1
• double_scalar attribute is polled
• State command is polled
• abs_change property is set for double_scalar attribute
• Tango 9 (for pipes)
• string_long_short_ro pipe should be defined

Most of these things are automatically defined by default TangoTest instance.
You should populate tests/testconf.py file with the TANGO_HOST that your system is using (this is not really important for current version of the project).

Running tests

To run tests use pytest command with --boxed option. This ensures that each test is executed in separate environment, and allows each test to use uvloop instead of standard asyncio event loop with Tango.

$ pytest --boxed
====== test session starts ======
platform linux -- Python 3.5.3, pytest-3.1.3, py-1.4.34, pluggy-0.4.0
rootdir: /home/daneos/src/maxiv/mtango-py, inifile:
plugins: xdist-1.18.2
collected 34 items 

tests/test_main.py .
tests/test_rc3.py ........................
tests/test_sys.py .........

====== 34 passed in 5.44 seconds ======

End notes

This project is distributed under GNU GPL 3.0 license. Full text of the license can be found in LICENSE file in the repository main directory.

Application server was tested only on GNU/Linux operating system, but should work also under other OSes.

The original mTango project can be found -> here <-.