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4-data_output.md

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4. DATA OUTPUT

🚨 IMPORTANT NOTE 🚨

  • A macro ALWAYS returns a string. So you need to convert the output based on the selected mode. So if your output is the price, you need to convert it to a number using the float function of filter to be able to calculate with it, if it is the start or end time, you can use as_datetime. For more complex structures used in the modes split and all use from_json (only available as filter) and for the mode is_now you can use bool. Make sure to use defaults, or use the value_on_error parameter to avoid errors while converting the data.

PARAMETERS

mode string (default: start)

See seperate section

split boolean (default: false)

Splits the hours input into sections with the cheapest prices. So it will not alwasy be a consecutive block of hours, but it will select all the lowest time sections within your selection. weight will not be used when split=true

debug boolean (default: false)

Outputs debug data besides the actual output of the macro

precision integer (default: 5)

The number of decimals used for the price output

time_format string (default: none)

You can use time12 for the 12-hour format including AM or PM, time24 for the 24-hour format, or any custom format using the variables from the python strftime method (cheatsheet)

price_factor float (default: 1)

All prices will be multiplied with this value, so if your prices are in cents and you want divided by 100, you can use 0.01. Or if you want to add 20% VAT, you can use 1.2

lowest boolean (default: true)

Determines if the marco should find the lowest price, set to false to find the highest price

latest_possible boolean (default: false)

By default the macro will return the first time block with the cheapest (or highest when lowest is set to false). When latest_possible is set to true it will return the last time block with the cheapest prices

price_tolerance float or percentage (default: 0.0)

When set, prices which are within the price_tolerance compared to the lowest price (highest when lowest is set to false) are also considered as the lowest (or hightest) price. Can be added as a fixed value (eg 0.2) or as a percentage (eg "5%"). In case a percentage is used, it will be used on the lowest price in the time range (or highest price in case lowest=false)

value_on_error anything (default: none)

Will be used as output instead of error messages, so for eg in combination with mode="is_now" this can be used to set the output to false when there is an error by setting value_on_error=false

OUTPUT MODES

split=false (default)

mode description
start (default) The isoformat datetime string with the start of the selected time period
end The isoformat datetime string with the end of the selected time period
min The lowest price in the the consecutive time period
max The highest price in the consecutive time period
time_min The isoformat datetime string of the time section with the lowest price within the selected time period
time_max The isoformat datetime string of the time section with the highest price within the selected time period
list A json string with the prices in the selected time period (use from_json to convert it to a list)
average The average price not taking into account the weight assigned to the different time sections
weighted_average The average price taking into account the weight assigned to the different time sections
is_now Returns "true" if the current time is within the consecutive based on your selection, otherwise "false"
extreme_now Retruns "true" if the current time matches the lowest (or highest in case lowest=false) price in the time range. Can be used in combination with price_tolerance
estimated_costs Returns the estimated costs based on the kwh and optionally the weight input
all Outputs all the above modes in a json string dictionary. Convert to a actual dictionary using from_json. This can be useful if you need more than one output mode for the same selection. Besides the data from all modes above, it will also output the number of hours used for the calculation (it can differ from the input because of the calculation to split the data), the number or datapoints per hour used for the calculations, and the total number of datapoints. [example](#example-output-modeall
split This will output the same as when split=true, mode="all" is set

EXAMPLE OUTPUT MODE="ALL"

{
  "start": "2023-11-10T03:00:00+01:00",
  "end": "2023-11-10T04:30:00+01:00",
  "min": 0.059,
  "max": 0.06,
  "time_min": "2023-11-10T03:00:00+01:00",
  "time_max": "2023-11-10T04:00:00+01:00",
  "average": 0.05933,
  "weighted_average": 0.05933,
  "list": [
    0.059,
    0.059,
    0.06
  ],
  "is_now": false,
  "extreme_now": false,
  "estimated_costs": 0.243,
  "no_weight_points": 2,
  "datapoints_per_hour": 2,
  "hours": 1.5,
  "datapoints": 3
}

split=true

mode description
start (default) The isoformat datetime string with the start of the first time block
end The isoformat datetime string with the end of the last time block
min The lowest price in all the time blocks
max The highest price in all the time blocks
time_min The isoformat datetime string of the time block which has the lowest price in it
time_max The isoformat datetime string of the time block which has the highest price in it
list A json string with all the prices in the all time blocks
average The average of all the prices
weighted_average The same as mode="average" as weight is not used in split
is_now Returns "true" if the current time is within any of the time blocks otherwise it will return "false"
all Outputs the data of all time blocks in a dictionary
split This will output the same as when split=true, mode="all" is set

EXAMPLE OUTPUT SPLIT=TRUE, MODE="ALL"

[
  {
    "start": "2023-09-19T15:00:00+02:00",
    "end": "2023-09-19T16:00:00+02:00",
    "hours": 1,
    "prices": [
      -0.004
    ],
    "is_now": false
  },
  {
    "start": "2023-09-20T02:00:00+02:00",
    "end": "2023-09-20T03:00:00+02:00",
    "hours": 3,
    "prices": [
      -0.002,
      -0.004,
      -0.003
    ],
    "is_now": true
  },
  {
    "start": "2023-09-20T12:00:00+02:00",
    "end": "2023-09-20T14:00:00+02:00",
    "hours": 2,
    "prices": [
      -0.004,
      -0.006
    ],
    "is_now": false
  },
  {
    "total_hours": 6,
    "datapoints_per_hour": 1,
    "datapoints": 6
  }
]

NAVIGATION

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