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taipy

Taipy Scheduler

Available in Taipy Enterprise edition

This section is relevant only to the Enterprise edition of Taipy.

This documentation focuses on providing necessary information to use the Taipy Scheduler, and in particular the capabilities related to scenario management and job execution. It is assumed that the reader already knows the Taipy Core entities described in a previous chapter.

Let’s assume also that the configuration represented in the picture below is implemented in the module my_config.py.

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from datetime import datetime

import pandas as pd

from taipy import Config, Frequency, Scope


def write_orders_plan(data: pd.DataFrame):
    insert_data = data[["date", "product_id", "number_of_products"]].to_dict("records")
    return ["DELETE FROM orders", ("INSERT INTO orders VALUES (:date, :product_id, :number_of_products)", insert_data)]


def train(sales_history: pd.DataFrame):
    print("Running training")
    return "TRAINED_MODEL"


def predict(model, current_month):
    print("Running predicting")
    return "SALES_PREDICTIONS"


def plan(sales_predictions, capacity):
    print("Running planning")
    return "PRODUCTION_ORDERS"


def compare(previous_month_prediction, current_month_prediction):
    print("Comparing previous month and current month sale predictions")
    return "COMPARISON_RESULT"


# Configure all six data nodes
sales_history_cfg = Config.configure_csv_data_node(
    id="sales_history", scope=Scope.GLOBAL, default_path="path/sales.csv"
)
trained_model_cfg = Config.configure_data_node(id="trained_model", scope=Scope.CYCLE)
current_month_cfg = Config.configure_data_node(id="current_month", scope=Scope.CYCLE, default_data=datetime(2020, 1, 1))
sales_predictions_cfg = Config.configure_data_node(id="sales_predictions", scope=Scope.CYCLE)
capacity_cfg = Config.configure_data_node(id="capacity")
orders_cfg = Config.configure_sql_data_node(
    id="orders",
    db_username="admin",
    db_password="ENV[PWD]",
    db_name="production_planning",
    db_engine="mssql",
    read_query="SELECT orders.ID, orders.date, products.price, orders.number_of_products FROM orders INNER JOIN products ON orders.product_id=products.ID",
    write_query_builder=write_orders_plan,
    db_driver="ODBC Driver 17 for SQL Server",
)

# Configure the three tasks
training_cfg = Config.configure_task("training", train, sales_history_cfg, [trained_model_cfg])
predicting_cfg = Config.configure_task(
    id="predicting", function=predict, input=[trained_model_cfg, current_month_cfg], output=sales_predictions_cfg
)
planning_cfg = Config.configure_task(
    id="planning", function=plan, input=[sales_predictions_cfg, capacity_cfg], output=[orders_cfg]
)

# Configure the scenario
monthly_scenario_cfg = Config.configure_scenario(
    id="scenario_configuration",
    task_configs=[training_cfg, predicting_cfg, planning_cfg],
    frequency=Frequency.MONTHLY,
    comparators={sales_predictions_cfg.id: compare},
    sequences={"sales": [training_cfg, predicting_cfg], "production": [planning_cfg]},
)

Start/Stop the scheduler

To make the scheduler execute the scheduled methods, you must first start the scheduler by using the start() method.

import taipy as tp

tp.Scheduler.start()

Once the scheduler is started, the scheduled methods will run in the background at their specified times. While the scheduler is running, you can execute other methods without being blocked by the scheduler.

Schedule a method before and after starting the scheduler

You can schedule a method both before and after starting the scheduler. However, keep in mind that the scheduled method will not run until the scheduler is started.

To stop the scheduler from running the scheduled methods, you can use the stop() method.

tp.Scheduler.stop()

Run a method every specific interval

Taipy Scheduler provides the capability to run a method every specific interval. The interval can be specified in seconds, minutes, hours, days, weeks, days, months or years.

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import taipy as tp
from my_config import monthly_scenario_cfg

monthly_scenario = tp.create_scenario(monthly_scenario_cfg)

# Submit a scenario every 3 second/minute/hour/day
# Starting 3 second/minute/hour/day from now
tp.Scheduler.every(3).seconds.do(tp.submit, monthly_scenario)
tp.Scheduler.every(3).minutes.do(tp.submit, monthly_scenario)
tp.Scheduler.every(3).hours.do(tp.submit, monthly_scenario)
tp.Scheduler.every(3).days.do(tp.submit, monthly_scenario)

# Submit a scenario every 1 week/month/year
# Starting 1 week/month/year from now
tp.Scheduler.every().weeks.do(tp.submit, monthly_scenario)
tp.Scheduler.every().months.do(tp.submit, monthly_scenario)
tp.Scheduler.every().years.do(tp.submit, monthly_scenario)

tp.Scheduler.start()

In the above example, we schedule the tp.submit(monthly_scenario) method with different intervals. Notice that we chose to submit a scenario as an example, but any Python method can be scheduled.

  • First, we need to call the every() method and provide the time interval. If not provided, the default interval is 1.
  • Secondly, the time unit needs to be provided, which can be either seconds, minutes, hours, days, weeks, months, or years.
  • Finally, we provide the do() method with the method to schedule and its parameters. In the example, we schedule the tp.submit() method, and provide monthly_scenario as the parameter.

Once scheduled, the method will run in the background. The first run will be:

  • the number of interval from the scheduled time, or
  • at the start of the scheduler if the scheduler is started after the time that the method supposed to run.

Run a method at a specific time and/or date

To schedule a method to run at a specific time, you can call the at() and on() methods after providing the time unit.

The at() method allows specifying the time to run the method, which accepts the following parameters:

  • time_str is a madatory datetime.time object, datetime.datetime object, or a string. If it's a datetime.time or datetime.datetime object:

  • For daily scheduled methods, the hour, minute, and second will be used.

  • For hourly scheduled methods, the minute and second will be used.
  • For minute scheduled methods, only the second will be used.

If a string, it must be in one of the following formats:

  • For daily scheduled methods -> "HH:MM:SS" or "HH:MM"
  • For hourly scheduled methods -> "MM:SS" or ":MM"
  • For minute scheduled methods -> ":SS"
  • tz is the timezone that this timestamp refers to. Can be a string that can be parsed by pytz.timezone(), or a pytz.BaseTzInfo object.

The on() method allows specifying the date to run the method, which only applies to monthly and yearly scheduled methods. The on() method requires the following parameter:

  • date is a madatory datetime.date object, datetime.datetime object, or a string. If it's a datetime.date or datetime.datetime object:

  • For monthly scheduled methods, only the day will be used.

  • For yearly scheduled methods, the month and day will be used.

If a string, it must be in one of the following formats:

  • For monthly scheduled methods -> "DD".
  • For yearly scheduled methods -> "MM-DD". The month can be a number or the name of the month in English (e.g. "January" or "Jan"). The day string can be a number representing the day of the month, or a negative number representing the number of days from the end of the month. For example, -1 represents the last day of the month.
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import taipy as tp
from my_config import monthly_scenario_cfg

monthly_scenario = tp.create_scenario(monthly_scenario_cfg)

# Submit a scenario every minute at the 23rd second
tp.Scheduler.every().minute.at(":23").do(tp.submit, monthly_scenario)

# Submit a scenario every hour at the 42nd minute
tp.Scheduler.every().hour.at(":42").do(tp.submit, monthly_scenario)

# Submit a scenario every 5th hour, 20 minutes and 30 seconds in.
# If current time is 02:00, first execution is at 06:20:30
tp.Scheduler.every(5).hours.at("20:30").do(tp.submit, monthly_scenario)

# Submit a scenario every day at specific HH:MM and next HH:MM:SS
tp.Scheduler.every().day.at("10:30").do(tp.submit, monthly_scenario)
tp.Scheduler.every().day.at("12:42:30", "Europe/Amsterdam").do(tp.submit, monthly_scenario)

# Submit a scenario on a specific day of the week
tp.Scheduler.every().monday.do(tp.submit, monthly_scenario)
tp.Scheduler.every().wednesday.at("13:15").do(tp.submit, monthly_scenario)

# Submit a scenario on the 15th of every month
tp.Scheduler.every().months.at("13:15").on("15").do(tp.submit, monthly_scenario)
# Submit a scenario on the last day every 2 months
tp.Scheduler.every(2).months.at("13:15").on("-1").do(tp.submit, monthly_scenario)

# Submit a scenario on January 3rd every year on Amsterdam timezone
tp.Scheduler.every().years.at("13:15", "Europe/Amsterdam").on("jan 03").do(tp.submit, monthly_scenario)
# Submit a scenario on the last day of February every year
tp.Scheduler.every().years.at("13:15").on("feb -1").do(tp.submit, monthly_scenario)

tp.Scheduler.start()

Once scheduled, the first run of the method is based on the current time and the time specified in the at() API. For example, assume that the current time is 12:00:00: - If the tp.submit(monthly_scenario) is scheduled to run every day at "10:30", the first run will be at 10:30:00 tomorrow. - If the tp.submit(monthly_scenario) is scheduled to run every day at "12:42:30", the first run will be at 12:42:30 today, which is in 42 minutes.

Run a scheduled method until a certain time

To automatically cancel a scheduled method after a certain time, you can use the until() method. The until() method accepts a time indicator, which can be:

  • datetime.datetime object,
  • datetime.time object,
  • datetime.timedelta object,
  • or a string in one of the following formats: "%Y-%m-%d %H:%M:%S", "%Y-%m-%d %H:%M", "%Y-%m-%d", "%H:%M:%S", "%H:%M".

If only a time is provided, the date is set to today.

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from datetime import datetime, timedelta, time
import taipy as tp
from my_config import monthly_scenario_cfg

monthly_scenario = tp.create_scenario(monthly_scenario_cfg)

# Submit a scenario until a 18:30 today
tp.Scheduler.every(1).hours.until("18:30").do(tp.submit, monthly_scenario)

# Submit a scenario until a 2030-01-01 18:33
tp.Scheduler.every(1).hours.until("2030-01-01 18:33").do(tp.submit, monthly_scenario)

# Submit a scenario until today 11:33:42
tp.Scheduler.every(1).hours.until(time(11, 33, 42)).do(tp.submit, monthly_scenario)

# Submit a scenario for every hour until the next 8 hours
tp.Scheduler.every(1).hours.until(timedelta(hours=8)).do(tp.submit, monthly_scenario)

# Submit a scenario until a specific datetime
tp.Scheduler.every(1).months.until(datetime(2030, 1, 1, 12, 30, 0)).do(tp.submit, monthly_scenario)

Get all scheduled methods

To retrieve all scheduled methods from the scheduler, use tp.Scheduler.get_scheduled_methods() method.

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import taipy as tp
from my_config import monthly_scenario_cfg

monthly_scenario = tp.create_scenario(monthly_scenario_cfg)

tp.Scheduler.every().second.do(tp.submit, monthly_scenario)

all_scheduled_methods = tp.Scheduler.get_scheduled_methods()

The tp.Scheduler.get_scheduled_methods() method returns a list of ScheduledMethod objects, which you can use to get information or cancel the scheduled method.

Cancel scheduled methods

To remove a scheduled method from the scheduler, use the tp.Scheduler.cancel_scheduled_method(scheduled_method) method.

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import taipy as tp
from my_config import monthly_scenario_cfg

monthly_scenario = tp.create_scenario(monthly_scenario_cfg)

monthly_submit_method = tp.Scheduler.every().second.do(tp.submit, monthly_scenario)

tp.Scheduler.cancel_scheduled_method(monthly_submit_method)

To remove all scheduled methods from the scheduler, use tp.Scheduler.clear()

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import taipy as tp
from my_config import monthly_scenario_cfg

monthly_scenario = tp.create_scenario(monthly_scenario_cfg)

tp.Scheduler.every().second.do(tp.submit, monthly_scenario)

tp.Scheduler.clear()

Shortcut for scheduling most used Taipy methods

Taipy Scheduler provides shortcut for scheduling popular Taipy methods, including:

  • taipy.create_scenario()
  • taipy.submit()
  • A combination of taipy.create_scenario() and taipy.submit()

Instead of using the do() method and specifying the Taipy method to schedule, you can directly call the following method from the scheduler.

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import taipy as tp
from my_config import monthly_scenario_cfg

# Creating a new scenario every month using the monthly_scenario_cfg
tp.Scheduler.every().months.do_create(monthly_scenario_cfg)

# Submit the monthly_scenario every month
monthly_scenario = tp.create_scenario(monthly_scenario_cfg)
monthly_submit_method = tp.Scheduler.every().months.do_submit(monthly_scenario)

# Create a new scenario every month using the monthly_scenario_cfg
# and submit it immediately
tp.Scheduler.every().months.do_create_and_submit_scenario(monthly_scenario_cfg)

tp.Scheduler.clear()