lightningchart_trader.helper_routines package

Submodules

lightningchart_trader.helper_routines.helper_routines module

lightningchart_trader.helper_routines.helper_routines.calculate_heikin_ashi_values(xohlc_data)

Calculates Heikin Ashi values based on the given dataset.

Parameters:

xohlc_data (list[list[int | float]]) – XOHLC dataset to calculate from.

Returns:

List of Heikin Ashi values.

lightningchart_trader.helper_routines.helper_routines.convert_hex_to_rgba(hex_color)

Convert a HEX color string to an RGBA tuple.

Parameters:

hex_code (str) – A HEX color code in the format ‘#RRGGBB’ or ‘#RRGGBBAA’.

Returns:

A tuple (R, G, B, A) where R, G, B, and A are integers between 0 and 255.

If no alpha channel is provided in the HEX string, the alpha will be excluded from the result.

Return type:

tuple

lightningchart_trader.helper_routines.helper_routines.convert_rgba_to_hex(r, g, b, a=None)

Convert an RGB or RGBA color value to a HEX color string.

Parameters:

• r (int) – Red component, an integer between 0 and 255.

• g (int) – Green component, an integer between 0 and 255.

• b (int) – Blue component, an integer between 0 and 255.

• a (int, optional) – Alpha component, an integer between 0 and 255. If not provided, the alpha will be excluded from the result.

Returns:

A HEX string representing the color in the format ‘#RRGGBB’ or ‘#RRGGBBAA’.

Return type:

str

lightningchart_trader.helper_routines.helper_routines.convert_to_xohlc(data)

Converts various data formats (CSV, list of dicts, list of lists, DataFrame) into XOHLC format. The function is case insensitive for column names (e.g., “Open” == “open” == “OPEN”).

Parameters:

data (str | list | dict | DataFrame) –

• Path to CSV file (str)

• List of dictionaries (list[dict])

• Single dictionary (dict)

• List of lists (list[list])

• Pandas DataFrame (DataFrame)

Returns:

Data in XOHLC format -> [[Index, Open, High, Low, Close], …]

Return type:

list

Example Usage:

>>> convert_to_xohlc("your_csv_file.csv")
>>> convert_to_xohlc(df)  # Pandas DataFrame
>>> convert_to_xohlc([{"OPEN":1.1, "HIGH":1.2, "LOW":1.0, "CLOSE":1.15, "DATE":"Jan 1, 1970"}])  # List of Dicts
>>> convert_to_xohlc([[1.1, 1.2, 1.0, 1.15, "Jan 1, 1970"]])  # List of Lists

lightningchart_trader.helper_routines.helper_routines.extract_close_values(xohlc_data)

Extracts all Close values from the current dataset.

Parameters:

xohlc_data (list[list[int | float]]) – XOHLC data values to extract from.

Returns:

List of Close values, or empty list if unable to extract.

lightningchart_trader.helper_routines.helper_routines.extract_high_values(xohlc_data)

Extracts all High values from the current dataset.

Parameters:

xohlc_data (list[list[int | float]]) – XOHLC data values to extract from.

Returns:

List of High values, or empty list if unable to extract.

lightningchart_trader.helper_routines.helper_routines.extract_low_values(xohlc_data)

Extracts all Low values from the current dataset.

Parameters:

xohlc_data (list[list[int | float]]) – XOHLC data values to extract from.

Returns:

List of Low values, or empty list if unable to extract.

lightningchart_trader.helper_routines.helper_routines.extract_open_values(xohlc_data)

Extracts all Open values from the current dataset.

Parameters:

xohlc_data (list[list[int | float]]) – XOHLC data values to extract from.

Returns:

List of Open values, or empty list if unable to extract.

lightningchart_trader.helper_routines.helper_routines.extract_position_values(xohlc_data)

Extracts all position values (X-values) from the current dataset.

Parameters:

xohlc_data (list[list[int | float]]) – XOHLC data values to extract from.

Returns:

List of positions values, or empty list if unable to extract.

lightningchart_trader.helper_routines.helper_routines.read_csv_string(csv_input, start_date=None, end_date=None, delimiter=',')

Parses a CSV string or file into separate OHLCV arrays, similar to JS readCsvString().

Parameters:

• csv_input (str) – Either a file path or a raw CSV string.

• start_date (str | None) – Optional filter, exclude rows before this date (Format: “YYYY-MM-DD”).

• end_date (str | None) – Optional filter, exclude rows after this date (Format: “YYYY-MM-DD”).

• delimiter (str) – The delimiter used in the CSV (default: ,).

Returns:

A list containing:

• Array of date strings

• Array of Open values

• Array of High values

• Array of Low values

• Array of Close values

• Array of Volumes (or empty if not in CSV)

• Array of Open Interests (or empty if not in CSV)

Return type:

list

Example Usage:

>>> csv_data = '''Date,Open,High,Low,Close,Volume,OpenInterest
... 2024-01-01,100,105,99,104,5000,200
... 2024-01-02,104,106,102,105,5500,210
... 2024-01-03,105,107,103,106,6000,220'''
>>> parsed_data = read_csv_string(csv_data, start_date="2024-01-02")
>>> print(parsed_data)

>>> parsed_file = read_csv_string("your_csv_file.csv")
>>> print(parsed_file)

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