Overview

SlowDash integrates Python scripts written by users, with features including:

• calling user functions from the GUI
• reading and writing variable values from the GUI
• streaming data from user scripts to the GUI

SlowDash provides a Python library, slowpy, that offers functions for:

• controlling and reading from measurement devices
• interfacing with external software systems, especially messaging systems
• providing a unified interface for data storages
• basic analysis elements such as histograms and graphs

Although the GUI can access the variables and functions in user scripts, the scripts themselves are normal Python scripts and can utilize all Python features and libraries, including NumPy, SciPy, scikit-image, and scikit-learn.

Applications

• Send commands and receive data to/from external systems (either software or hardware), including:
  • Other concurrent systems (DAQ systems, etc.)
    • Through messaging systems such as Redis, AMQP, Kafka, ZMQ, …
    • Through HTTP GET/POST or Socket messages
    • By running shell commands
  • Measurement devices that accept commands
    • SCPI measurement devices with Ethernet interfaces
    • Any device that can be controlled from Python
      • Raspberry Pi GPIO, I2C, SPI, …
      • USB devices with vendor libraries
  • Other SlowDash instances for distributed systems
• Analyze data in real-time, construct histograms, etc., and issue alarms
• Store raw and analyzed values (including histograms) in database systems

Structure

• Controls are implemented as user task Python scripts.
• User task scripts are normal Python scripts that can be executed independently from the SlowDash server.
• Panels on the SlowDash GUI, built by users, can call functions defined in user task scripts.
• A Python library, slowpy, is provided to be imported by user task scripts for:
  • Simple unified methods to control external systems
  • Data classes such as histograms, graphs, time-series, etc.
  • Data storage interface to store data objects as well as raw data from external systems

Simple Examples

Reading data from a voltmeter with SCPI commands over Ethernet

from slowpy.control import ControlSystem
ctrl = ControlSystem()

# Create a control node for SCPI command "MEAS:VOLT:DC" on a device at 192.168.1.43
V = ctrl.ethernet(host='192.168.1.43', port=5025).scpi().command('MEAS:VOLT:DC')

while True:
  # Read a value from the control node using SCPI command "MEAS:VOLT:DC?"
  value = V.get()
  ...

Writing data to PostgreSQL database (using a default schema)

from slowpy.store import DataStore_PostgreSQL

datastore = DataStore_PostgreSQL('postgresql://postgres:postgres@localhost:5432/SlowTestData', table="SlowData")

while True:
    value = ...
    datastore.append(value, tag="voltmeter")

Calling a User Task function from SlowDash GUI Panels

If you have a User Task Script like this:

def set_Vout(value):
    Vout.set(value)

and write a SlowDash HTML panel like this:

<form>
  Voltage output: <input name="value">
  <input type="submit" name="test.set_Vout()" value="Set">
</form>

Then, clicking the Set button will call the function set_Vout() with a parameter from the value input field.

Displaying the readout values on the SlowDash panels

For control nodes V, defining an _export() function in the User Task Script will export the node values, making them available in the SlowDash GUI in the same way as values stored in the database.

device = ctrl.ethernet(host='192.168.1.43', port=5025).scpi()
V = device.command('MEAS:VOLT:DC')
A = device.command('MEAS:CURR:DC')
def _export():
    return [
        ('Voltage', V),
        ('Current', A)
    ]

Only the “current” (present) values are available in this way. If you need historical values, store the values in a database.

Demonstration Example Project

In slowdash/ExampleProjects/SlowTask there is a SlowDash project that demonstrates some of the features described here.

$ cd slowdash/ExampleProjects/SlowTask/Basic
$ slowdash --port=18881

or

$ cd slowdash/ExampleProjects/SlowTask/Basic
$ docker compose up

SlowPy: Controls Library

SlowPy is a Python library (module) that provides functions such as:

• connecting to external concurrent systems and/or measurement hardware
• creating histograms, graphs, etc.
• storing raw values, time-series, and histograms/graphs to the database in a way that SlowDash can easily handle

The SlowPy library is included in the SlowDash package under slowdash/lib/slowpy. By running source slowdash/bin/slowdash-bashrc, as instructed in the Installation section, this path will be included in the environment variable PYTHONPATH, so that users can use the library without modifying their system. It is also possible to install the library in the usual way: you can run pip install slowdash/lib/slowpy to install SlowPy into your Python environment. You might want to combine this with venv to avoid affecting your Python environment.

Controls

SlowPy provides a unified interface to connect external software systems and hardware devices; everything is mapped into a single “ControlTree” where each node has set() and get() methods. The tree represents the logical structure of the system. For example, a SCPI command of VOLT to a power supply unit connected via Ethernet would be addressed like ControlSystem.ethernet(host, port).scpi().command('VOLT'), and set(value) on this node will send a SCPI command of VOLT value to the device. The get() method performs a read operation and returns a value.

Plugin modules can dynamically add branches to the control tree. For example, the Redis plugin adds the redis() node and several sub-branches for functions provided by Redis, such as hash, JSON, and time-series. Plugins are loaded to a node, not necessarily to the root ControlSystem; for example, a plugin that uses Ethernet is loaded to an Ethernet node, creating a sub-branch under the Ethernet node, and the plugin can make use of the functions provided by the Ethernet node such as send() (which is set() of the node) and receive() (which is get()).

Example

Here is an example of using SlowPy Controls. In this example, we use a power supply device that accepts SCPI commands through Ethernet.

from slowpy.control import control_system as ctrl

# Create a control node for SCPI command "VOLT" (output) and "MEAS:VOLT:DC" (readback) on a device at 192.168.1.43
device = ctrl.ethernet(host='192.168.1.43', port=5025)
Vout = device.scpi(append_opc=True).command('VOLT')
V = device.scpi().command('MEAS:VOLT:DC')

# Write a value to the control node: this will issue SCPI command "VOLT 10;*OPC?"
Vout.set(10)

while True:
  # Read a value from the control node using SCPI command "MEAS:VOLT:DC?"
  value = V.get()
  ...

A common starting point would be importing slowpy.control and then creating an instance of the ControlSystem class, or import an instance (control_system) directly.

The ControlSystem already includes the Ethernet plugin, but if it were not included, the plugin loading code would be:

ctrl.load_control_module('Ethernet')

This will search for a file named control_Ethernet.py from search directories, load it, and inject the ethernet() Python method to the node class that loaded the plugin (which is ControlSystem in this case). The Ethernet plugin already includes sub-branches for SCPI; for specific protocols not already included, a plugin would be loaded onto the Ethernet node.

Each node constructor takes parameters. In this example, the Ethernet node, which sends and receives data to/from Ethernet, takes the host/IP and port parameters, and a SCPI command node, which is bound to a specific SCPI command, takes the SCPI command parameter with optional set_format which overrides the default SCPI command for writing. (The default SCPI commands to be written/read for .scpi().command(CMD) are CMD and CMD?, respectively. Often, write operations should wait for command completion, and SlowPy expects a return value from each command. A technique to achieve this, regardless of the actual command behaviors of the device, is to append OPC? to the command, as done in the example.)

Once you have the control node object, you can call node.set(value) to write the value, and call value=node.get() to read from it. As a shortcut, node(value) is equivalent to node.set(value), and value=node() is equivalent to value=node.get(). Also, control nodes define Python’s __str__(), __float__(), etc., so print(node) and x = float(node) will implicitly call node.get().

Control Node Threading

If a control node has threading methods run() or loop(), calling start() on the node will create a dedicated thread and start it. This is useful for:

• The node can perform tasks independent from the set() and get() queries, such as PID loops.
• If fetching data is slow, data can be pre-fetched periodically and stored in a cache.

The run() function is called once, and then loop() is called repeatedly. In the loop() function, sleep() or similar must be inserted to control the frequency.

The thread is stopped by calling the stop() method of the node, or by a global stop request (such as ControlSystem.stop() or by signals). The run() function must watch for stop requests (by is_stop_requested()) and terminate itself when a stop request is made. loop() will not be called after a stop.

Commonly used nodes

Naming convention: set(), get(), and do_XXX() are usual methods to perform actions. Methods with noun names return sub-nodes.

Ethernet, SCPI, and Telnet

Loading (already included)

ControlSystem.load_control_module('Ethernet')

Nodes

• ethernet(host,port): sends and receives text messages through a TCP socket connection
  • set(value): sends the value as encoded text
  • get(): receives a chunk of text
  • do_get_chunk(timeout=None): receives a chunk of text
  • do_get_line(timeout=None): receives a chunk and returns one line (with reconstruction)
  • do_flush_input(): empties the receiving buffer
  • scpi() bridges the parent Ethernet connection and holds SCPI configurations
    • command(cmd) issues a SCPI command via the parent Ethernet connection
      • set(value=None): sends cmd value and waits for a reply
      • get(): sends cmd? and waits for a reply, then returns the reply
  • telnet() bridges the parent Ethernet connection and holds telnet configurations
    • command(cmd) issues a telnet command via the parent Ethernet connection
      • set(value=None): sends cmd value line_terminator, consumes echo
      • get(): sends cmd line_terminator, consumes echo, and returns a reply until the next prompt

Nodes

• serial(port=‘/dev/ttyUSB0’,baudrate=9600): sends and receives text messages through a serial port
  • set(value): sends the value as encoded text
  • get(): receives a chunk of text
  • do_get_chunk(timeout=None): receives a chunk of text
  • do_get_line(timeout=None): receives a chunk and returns one line (with reconstruction)
  • do_flush_input(): empties the receiving buffer
  • scpi() returns the same object as EthernetNode.scpi()

HTTP (Web API)

Loading (already included)

ControlSystem.load_control_module('HTTP')

Nodes

• http(base_url):
  • path(path): path string to be appended to the base_url
    • set(value): sends a POST request to base_url path with value as its content
    • get(): sends a GET request to base_url path and returns the reply content
    • json():
      • set(value): value is a Python object to be converted to JSON
      • get(): receives a JSON document and returns a Python object
    • value(): returns ControlValueNode for ramping() etc.

Shell Command

Loading (already included)

ControlSystem.load_control_module('Shell')

Nodes

• shell(cmd): run a shell command.
  • set(value): launches cmd value,
  • get(): launches cmd and returns the result
  • value(): returns ControlValueNode for ramping() etc.
  • arg(*args): append program arguments to the parent “shell” node.
    Example: adc0 = ctrl.shell('read_adc', '--timeout=0').arg('--ch=0')
    • value(): returns ControlValueNode for ramping() etc.

SlowDash server control

Loading (already included)

ControlSystem.load_control_module('HTTP').load_control_module('Slowdash')

Nodes

• http(url).slowdash()
  • ping(): returns pong
  • channels(): gets a JSON object of the channel list
  • data(channels,length=3600): gets a JSON object of data for the channels
  • config(): gets a JSON object of the project configuration
  • config_file(name): gets or posts a configuration file

Redis Interface

Loading

ControlSystem.load_control_module('Redis')

Nodes

• redis(url)
  • string(key): read and write a simple key-value pair
    • set(value): writes a simple key-value pair
    • get(): returns a value of a simple key-value pair
  • hash(key): read and write a map of key-value pairs
    • set(value): writes a map of key-value pairs
    • get(): returns a hash as a map of key-value pairs
    • field(name):
      • set(value): writes a single element in the parent hash
      • get(): returns a single element value in the parent hash
  • json(key):
    • set(value): writes value (Python dict) to Redis JSON
    • get(): returns a Redis JSON as a Python dict
    • node(path): read and write a branch of a JSON object
      • set(value): writes value to a branch of Redis JSON
      • get(): returns a value of a branch of Redis JSON
      • node(path): can perform this node iteration recursively
  • ts(key): read and write a time-series, where the value is a list of (t,x) tuples
    • current():
      • set(value): adds a data point to the parent time-series using the current time
    • last():
      • get(): returns the last data point as a tuple of (t,x)
      • value():
        • get(): returns the value of the parent time-series point
      • time():
        • get(): returns the UNIX time value of the parent time-series point
      • lapse():
        • get(): returns the number of seconds since the last time-series point

Other Nodes

• RabbitMQ (using pika and aio-pika)
• MQTT (using paho-mqtt and aio-mqtt)
• Serial (using pyserial)
• VISA (using pyvisa)
• Modbus (using pymodbus)
• LabJack (using LabJackPython, currently supports only U12)
• DummyDevice

Node Functions

All control nodes (derived from slowpy.control.ControlNode) have the following methods:

• [ControlNode]
  • has_data(): returns True if a value is available for get()
  • wait(condition_lambda=None, polling_interval=1, timeout=0): blocks until the condition_lambda returns True if the lambda is not None; if condition_lambda is None, wait until has_data() returns True. On timeout, wait() returns None, and on a stop request, it returns False. Otherwise, it returns True.
  • sleep(duration_sec): blocks for the duration and returns True unless a stop request is received.
  • is_stop_requested(): returns True if a stop request has been received
  • readonly(): makes the node readonly; it returns a node that has only get() which calls parent_node.get()
  • writeonly(): makes the node write-only; it returns a node that has only set() which calls parent_node.set()

Nodes derived from ControlValueNode have the following methods:

• [ControlValueNode] -> [ControlNode]
  • setpoint(limits=[None,None]): holds the setpoint
    • set(value): holds the value as a set-point and calls set(value) of the parent node.
    • get(): returns the holding set-point value
  • ramping(change_per_sec)
    • set(value): starts ramping to the target value in the parent node. If the value is not numeric or not within the limits, it raises an exception
    • get(): returns parent’s get()
    • status()
      • set(value): set(0) will stop the current ramping if it is running
      • get(): returns True if ramping is in progress, otherwise returns False

Nodes derived from ControlThreadNode have the following methods:

• [ControlThreadNode] -> [ControlNode]
  • start(): creates and starts a thread for run() and/or loop(), if the node has one of these methods (or both)
  • stop(): stops the thread

Database Interface

Simple example of writing single values to a long-form table:

import time
from slowpy.control import RandomWalkDevice
from slowpy.store import DataStore_PostgreSQL

device = RandomWalkDevice(n=4)
datastore = DataStore_PostgreSQL('postgresql://postgres:postgres@localhost:5432/SlowTestData', table="Test")

while True:
    for ch in range(4):
      value = device.read(ch)
      datastore.append(value, tag='%02d'%ch)

    time.sleep(1)

Example of writing a dict of key-values:

while True:
    record = { 'ch%02d'%ch: device.read(ch) for ch in range(4) }
    datastore.append(record)
    time.sleep(1)

For SQL databases, the “long format” with UNIX timestamps is used by default. To use other table schemas, specify a user-defined TableFormat:

class QuickTourTestDataFormat(LongTableFormat):
    schema_numeric = '(datetime DATETIME, timestamp INTEGER, channel STRING, value REAL, PRIMARY KEY(timestamp, channel))'
    schema_text = '(datetime DATETIME, timestamp INTEGER, channel STRING, value REAL, PRIMARY KEY(timestamp, channel))'

    def insert_numeric_data(self, cur, timestamp, channel, value):
        cur.execute(f'INSERT INTO {self.table} VALUES(CURRENT_TIMESTAMP,%d,?,%f)' % (timestamp, value), (channel,))

    def insert_text_data(self, cur, timestamp, channel, value):
        cur.execute(f'INSERT INTO {self.table} VALUES(CURRENT_TIMESTAMP,%d,?,?' % timestamp), (channel, value))

datastore = DataStore_SQLite('sqlite:///QuickTourTestData.db', table="testdata", table_format=QuickTourTestDataFormat())

Analysis Components

SlowPy provides commonly used data objects such as histograms and graphs. These objects can be directly written to the database using the SlowPy Database Interface described above.

Histogram

import slowpy as slp
hist = slp.Histogram(100, 0, 10)

device = ...
datastore = ...

while not ControlSystem.is_stop_requested():
  value = device.read(...
  hist.fill(value)
  data_store.append(hist, tag="test_hist")

data_store.append(hist, tag=name) will create a time-series of histograms (one histogram for each time point). To keep only the latest histogram, use data_store.update(hist, tag=name) instead.

Graph

import slowpy as slp
graph = slp.Graph(['channel', 'value'])

while not ControlSystem.is_stop_requested():
  for ch in range(n_ch):
    value = device.read(ch, ...
    graph.fill(ch, value)
  data_store.append(graph, tag="test_graph")

data_store.append(graph, tag=name) will create a time-series of graphs (one graph for each time point). To keep only the latest graph, use data_store.update(graph, tag=name) instead.

Trend

import slowpy as slp
rate_trend = slp.RateTrend(length=300, tick=10)

while not ControlSystem.is_stop_requested():
  value = device.read(...
  rate_trend.fill(time.time())

  data_store.append(rate_trend.time_series('test_rate'))

Scpizing Your Device

If your device has some programming capability, such as Raspberry Pi GPIO, an easy way to integrate it into a SlowDash system is to implement the SCPI interface on it. This approach is also useful to integrate other non-Ethernet devices (such as USB) connected to a remote computer.

Here is an example to wrap a device with Ethernet-SCPI capability:

from slowpy.control import ScpiServer, ScpiAdapter, RandomWalkDevice

class RandomWalkScpiDevice(ScpiAdapter):
    def __init__(self):
        super().__init__(idn='RandomWalk')
        self.device = RandomWalkDevice(n=2)

    def do_command(self, cmd_path, params):
        '''
        parameters:
          cmd_path: array of strings, SCPI command split by ':'
          params: array of strings, SCPI command parameters split by ','
        return value: reply text (even if empty) or None if command is not recognized
        '''
        
        # Implemented Commands: [ "VOLTage Value", "MEASure:VOLTage:DC?" ]
        # Common SCPI commands, such as "*IDN?", are implemented in the parent ScpiAdapter class
        if cmd_path[0].startswith('VOLT') and len(params) == 1:
            try:
                self.device.write(0, float(params[0]))
            except:
                self.push_error(f'bad parameter value: {params[0]}')
            return ''
            
        elif cmd_path[0].startswith('MEAS'):
            if len(cmd_path) == 3 and cmd_path[1].startswith('VOLT') and cmd_path[2] == 'DC':
                return self.device.read(0)
            else:
                self.push_error(f'invalid command {":".join(cmd_path)}')
            return ''
            
        return None
        
device = RandomWalkScpiDevice()
server = ScpiServer(device, port=5025)
server.start()

In the parent class, ScpiAdapter, the following standard SCPI commands are defined. The default behaviors can be customized by overriding the methods shown in the table.

Once the code is tested, make it start automatically on PC boot in your preferred way (/etc/rc.local, Docker, …).

If SlowPy Control Nodes are already available for the device, the nodes can be directly mapped to the SCPI interface:

from slowpy.control import ControlSystem, ScpiServer, ScpiAdapter

ControlSystem.import_control_module('DummyDevice')
device = ControlSystem().randomwalk_device()

adapter = ScpiAdapter(idn='RandomWalk')
adapter.bind_nodes([
    # Randomwalk Configuration
    ('CONFIGure:WALK', device.walk().setpoint(limits=(0,None))),
    ('CONFIGure:DECAY', device.decay().setpoint(limits=(0,1))),

    # Common SCPI commands for power supplies and voltmeters
    ('VOLTage', device.ch(0).setpoint()),
    ('MEASure:VOLTage:DC', device.ch(0).readonly()),
])

server = ScpiServer(adapter, port=5025)
server.start()

SlowTask: GUI-Script Binding

SlowTask is a user Python script placed under the SlowDash config directory with a name like slowtask-XXX.py. The SlowDash GUI can start/stop the script, call functions defined in the script, and bind control variables in the script to GUI elements. The SlowPy library was designed for use in user task scripts, but this is not a requirement.

Starting, Stopping, and Reloading the Slow-Task Scripts

SlowTask script files (such as slowtask-test.py) are placed under the project configuration directory. By default, tasks are “listed” in the Task Manager panel of the SlowDash web page, but they will not be “loaded” until the start button is clicked. Auto-loading can be set by making an entry in the SlowDash configuration file (SlowdashProject.yaml):

slowdash_project:
  ...

  task:
    name: test
    auto_load: true
    parameters:
      default_ramping_speed: 0.1

  system:
    our_security_is_perfect: false

The parameters are optional, and if given, these will be passed to the _initialize(params) function of the script (described later).

Setting system/our_security_is_perfect to true will enable editing of the Python scripts on the SlowDash web page. While this is convenient, please keep in mind what it means. Python scripts can do anything, such as system("rm *"). You can only use this feature when access is strictly controlled. Some secure systems run processes only in Docker containers, where the container system runs on a virtual machine (in case the container is compromised) inside a firewall that accepts only VPN or SSH connections from listed addresses. Additionally, to prevent unintended destruction by novice operators, it may be safer to run two instances of SlowDash: one with full features and one with limited operations (without or only with selected tasks). The slowdash command has an option to specify which configuration file to use.

Callback Functions (Command Task)

Functions in SlowTask scripts can be called from the SlowDash GUI. If a script (named test) has a function like this

def destroy_apparatus():
  #... do your work here

This can be called from the SlowDash GUI in several ways.

HTML Form Panel

From an HTML form panel in SlowPlot, clicking a <button> with a name of the task module and the function will call the function:

<form>
  <input type="submit" name="test.destroy_apparatus()" value="Finish">
</form>

Here, the parentheses at the end of the button name indicate that this button is bound to a SlowTask function.

The prefix (test. in this example) is the module name, which is taken from the module file name by stripping the beginning ‘slowtask-’. If the module name includes -, those will be replaced with _. The prefix can be explicitly specified in the SlowdashProject.yaml configuration file as:

  task:
    name: another_test
    namespace:
      prefix: test.

Note that the dot is part of the prefix.

SlowTask functions can take parameters:

def set_V0(voltage:float, ramping:float):
  #... do your work here

and these parameter values are taken from the form input values:

<form>
  Voltage: <input type="number" name="voltage" value="0"><br>
  Ramping: <input type="number" name="ramping" value="1"><br>
  <input type="submit" name="test.set_V0()" value="Set">
</form>

By using the type notation in the SlowTask function as shown above, the parameter values are converted to the specified types. If the value literal cannot be converted to the specified type, an error response will be returned to the browser and the SlowTask function will not be called.

The SlowTask function can be either the standard def or async def.

It is possible to place multiple buttons in one form:

<form>
  Ramping: <input type="number" name="ramping" value="1" style="width:5em">/sec
  <p>
  V0: <input type="number" name="V0" value="0"><input type="submit" name="parallel test.set_V0()" value="Set"><br>
  V1: <input type="number" name="V1" value="0"><input type="submit" name="parallel test.set_V1()" value="Set"><br>
  V2: <input type="number" name="V2" value="0"><input type="submit" name="parallel test.set_V2()" value="Set"><br>
  V3: <input type="number" name="V3" value="0"><input type="submit" name="parallel test.set_V3()" value="Set"><br>
  <p>
  <input type="submit" name="test.set_all()" value="Set All">
  <input type="submit" name="parallel test.stop()" value="Stop Ramping"><br>    
</form>

def set_V0(V0:float, ramping:float):
  #...

def set_V1(V1:float, ramping:float):
  #...

#...

The input values on the Web form will be bound to the function parameters based on the names (<input name="V0"> will be bound to the V0 parameter).

In the example above, some functions have the parallel qualifier: by default, if a previous function call is in execution, the next action cannot be accepted to avoid multi-threading issues in the user code. The parallel qualifier indicates that this function can run in parallel to others. Another common qualifier is await, which instructs the web browser to wait for completion of the function execution before doing anything else (therefore, the browser will appear frozen).

Canvas Panel

On a canvas panel, a button to call a task can be placed by:

{
    ...
    "items": [
        {
            "type": "button",
            "attr": { "x":400, "y": 630, "width": 130, "label": "Finish Experiment" },
            "action": { "submit": { "name": "test.destroy_apparatus()" } }
        },
        ...

For functions with parameters, a form can be used:

{
    ...
    "items": [
        {
            "type": "valve", 
            "attr": { ... },
            "metric": { "channel": "sccm.GasInlet", ... },
            "action": { "form": "FlowControl" }
        },
        ...
    ],
    "forms": {
        "FlowControl": {
            "title": "Injection Flow",
            "inputs": [
                { "name": "flow", "label": "Set-point (sccm)", "type": "number", "initial": 15, "step": 0.1 }
            ],
            "buttons": [
                { "name": "ATDS.set_flow()", "label": "Apply Set-point" },
                { "name": "ATDS.stop_flow()", "label": "Close Valve" }
            ]
        }
    }
    ...

For more details, see the UI Panels section.

Thread Functions (Routine Task)

If a SlowTask script has functions of _initialize(params), _finalize(), _run(), and/or _loop(), one dedicated thread will be created, and these functions are called in a sequence:

These functions can be either the standard def or async def.

Control Variable Exporting

Control variables can be exported to other SlowDash components (typically web browsers) so that the other components can call get() and set() of the nodes.

from slowpy.control import control_system as ctrl
V0 = ctrl.ethernet(host, port).scpi().command("V")
ctrl.export(V0, 'V0')

The exported nodes are listed in the channel list and can be accessed in the same way as data stored in databases, except that only “current” values are available. Typically these are used in “Single Scalar” display panels, or in HTML panels:

<form>
  V0: <span sd-value="V0"></span>
</form>

Python dict and dataclass instances can be exported in the same way. Instances of class can also be exported, but with some restrictions (e.g., vars() must be able to serialize the instance). SlowPy analysis elements, such as histograms and graphs, are also accepted.

from slowpy.control import control_system as ctrl
V0 = ctrl.ethernet(host, port).scpi().command("V")
ctrl.export(V0, name='V0')

from slowpy import Histogram
h = Histogram(100, 0, 20)
ctrl.export(h, name='hist')

def _loop():
    h.fill(V0.get())
    ctrl.sleep(1)

To export a variable not of these types, make a temporary control node variable to wrap it:

class RampingStatusNode(ControlNode):
    def get(self):
        return {
            'columns': [ 'Channel', 'Value', 'Ramping' ],
            'table': [
                [ 'Ch0', float(V0), 'Yes' if V0.ramping().status().get() else 'No' ],
                [ 'Ch1', float(V1), 'Yes' if V1.ramping().status().get() else 'No' ],
                [ 'Ch2', float(V2), 'Yes' if V2.ramping().status().get() else 'No' ],
                [ 'Ch3', float(V3), 'Yes' if V3.ramping().status().get() else 'No' ]
            ]
        }
    
ctrl.export(RampingStatusNode(), 'Status')

Control Variable Binding (Streaming / Live Updating)

The current values of exported variables are “pulled” by the other components. In addition, the values can be “pushed” to the others (data streaming).

from slowpy.control import control_system as ctrl

V0 = ctrl.ethernet(host, port).scpi().command("V")
ctrl.export(V0, 'V0')            # exporting to be pulled

async def _loop():
    await ctrl.aio_publish(V0)   # publishing (pushing to subscribers)
    await ctrl.aio_sleep(1)

If the variable is already exported, the same export name is used. Otherwise, the name must be provided as a name argument of the aio_publish() function. In addition to the exportable variables, aio_publish() accepts many other types, including Python numbers.

import random
from slowpy.control import control_system as ctrl

x = 0
async def _loop():
    global x
    x = x + random.random()
    await ctrl.aio_publish(x, name="RandomWalk")
    await ctrl.aio_sleep(1)

In addition to accessing the exported variables in the same way as data in databases, the variables can be directly “bound” in web browsers. If a SlowTask control variable is bound in SlowDash HTML, changes to the variable on the browser call the .set() method of the SlowTask variable.

<form>
  Readout Frequency: <input type="number" sd-value="readout_frequency" sd-live="true">
  ...
</form>

from slowpy.control import control_system as ctrl

readout_frequency = ctrl.value(1.0)
ctrl.export(readout_frequency, 'readout_frequency')   # to be set by GUI

V = ctrl.ethernet(host, port).scpi().command("V")

async def _loop():
    await ctrl.aio_publish(V, name='V')
    await ctrl.aio_sleep(readout_frequency.get())

In HTML, sd-live="true" indicates that changes to the value on the browser will trigger calling the .set() method of the bound variable.

More examples can be found in ExampleProjects/Streaming.

Matplotlib Integration

Instances of Matplotlib Figure can be directly published.

import matplotlib.pyplot as plt
from slowpy.control import control_system as ctrl

async def _loop():
    fig, axes = plt.subplots(2, 2)
    #... draw plots in the usual way

    await ctrl.aio_publish(fig, name='mpl')

    plt.close()  # If a figure is created in a loop, it must be closed every time.
    await ctrl.aio_sleep(1)

When a Matplotlib figure is published, a SlowDash layout (usually a slowplot-XXX.json file under config) is created dynamically for the same axes layout as the figure. The plotting objects in the figure are extracted and converted to SlowDash objects before publishing.

More examples can be found in ExampleProjects/Streaming/Matplotlib.

Distributed System / Network Deployment

SlowDash Interconnect

SlowTask Scpization