Sirilpy Python Module API 0.7.41 Reference

The sirilpy python module supports communication with a running Siril instance. It can request representations of the current loaded image plus its metadata, including details of detected stars, as well as the current loaded sequence and most frame metadata.

This documentation is autogenerated from version 0.7.41 of the python module code.

It can also run Siril commands using the SirilInterface.cmd() method, and the intent is to provide a capable interface for writing advanced scripts for Siril to a level not possible with the previous simple script files.

For example, scripts can now have TKinter front ends using the tkinter and ttkthemes modules, and they can utilise a lot of the ecosystem of Python modules including numpy, scipy, pillow and many more.

Nota

There are some restrictions around modules that require installation of system binary packages for the modules to work.

In the initial module release, most methods relating to the image or sequence loaded in Siril are read-only. The intent is that the parameters of the loaded image or sequence can be obtained and used as inputs to scripts, for example for calculations or input to conditionals, but the existing mature Siril command set should in most cases be used to act on the loaded image. Thus header keywords can be set using cmd("update_key", "key", "value"), and most built-in image operations can be carried out using the appropriate Siril command. The main exception to the rule of python methods providing read-only access is the set_image_pixeldata() method, which allows for setting the pixel data in the loaded image from a numpy array. This means that new pixel processing algorithms can be added using python, initially getting the pixel data from the loaded image using get_image_pixeldata() and setting it on completion using set_image_pixeldata(). Similar functions are available for getting and setting pixel data from sequence frames.

Dependencies

The sirilpy module depends on the following:

  • numpy >= 1.20.0

  • packaging >= 21.0

  • pywin32 >= 300 (only on Windows)

Siril Script Coding Guidance

  • Unlike most python environments, Siril scripts run directly from Siril and the end user may not typically know how to access or how to use the python venv from outside Siril. This means that some tasks that are fairly trivial in typical python scenarios, such as installing packages, become harder. The user cannot be expected to access the command line and install packages themselves using python3 -m pip install.

    • The module therefore provides the ensure_installed() method. This uses pip to ensure that modules are installed so that they can be imported.

  • Siril scripts should always provide the author's name, copyright details / license information and contact details such as a YouTube channel, website or forum where they can be contacted in regard to their script. This is advisory for independently distributed scripts and mandatory for any scripts that are submitted to the scripts repository. If you write a script, you are responsible for supporting it.

  • As the repository grows and the API develops, not all the scripts published will necessarily always be compatible with all versions of Siril that will be in use:

    • If your script uses Siril commands, you should use the requires Siril command. This can be called directly in a Siril Script File, or it can be called from a Python script using SirilInterface.cmd("requires", "min_version", {"max_version"}) (max_version is optional) but can be used to ensure scripts designed for older versions of Siril no longer show as applicable to newer versions if the command syntax has changed.

    • If your script uses any features of the Siril python module added since the initial release, you should call the sirilpy.check_module_version() method to ensure the installed version meets the requriements of your script. The versions at which features were added will be listed in the API documentation for all features added after the initial public release.

    • The code that populates the Siril view of the scripts repository will automatically filter out scripts whose Siril version or python module version requirements are not met.

    • If new classes or methods are added to the module after its initial public release the version at which they were introduced will be annotated in the docstring and the online documentation generated from it.

  • Siril targets Linux, Windows and MacOS. Script writers are encouraged, where possible, to ensure that their scripts run correctly on all three OSes.

Sirilpy Connection

This submodule provides the main SirilInterface class used for communication between Siril and the python script. All its members are made available at the module root level, there is no need to import connection separately.

Connection module for Siril, providing the ability to connect to a running Siril instance and communicate with it. Includes an extensive range of methods that can be used to get and set data from / to Siril.

class sirilpy.connection.SirilInterface

Bases: object

SirilInterface is the main class providing an interface to a running Siril instance and access to methods to interact with it through Siril's inbuilt command system and accessing image and sequence data.

clear_image_bgsamples()

Clears all background sample points from the image.

cmd(*args)

Send a command to Siril to be executed. The range of available commands can be found by checking the online documentation. The command and its arguments are provided as a list of strings.

Parámetros:

*args (str) -- Variable number of string arguments to be combined into a command

Muestra:

  • DataError -- If no response (or an incorrect response) was received,

  • CommandError -- If the command returns an error status code,

  • SirilError -- If any other error occurs during execution.

Ejemplo

siril.cmd("ght", "-D=0.5", "-b=2.0")
command_error_message(status_code)

Provides a string describing the return status from a Siril command.

Parámetros:

status_code (CommandStatus) -- The status code returned by the Siril command handler, or by the CommandError exception.

Devuelve:

A string providing a description of the error code returned by a Siril command, for use in exception handling.

Tipo del valor devuelto:

str

confirm_messagebox(title, message, confirm_label)

Create a modal confirmation message dialog in Siril and wait for the response.

Parámetros:

  • title (str) -- The title to display in the message box (up to 256 characters)

  • message (str) -- The message to display in the message box (up to 1021 characters)

  • confirm_label (str) -- The label to display in the message box confirmation button (OK, Yes, Confirm etc.) (Up to 24 characters)

Devuelve:

True if the message box confirmation button was clicked, False otherwise

Tipo del valor devuelto:

bool

Muestra:
connect()

Establish a connection to Siril based on the pipe or socket path.

Tipo del valor devuelto:

bool

Devuelve:

True on success

Muestra:

SirilConnectionError -- if a connection error occurred

create_new_seq(seq_root)

Creates a new .seq file with all images named seq_rootXXXXX.ext located in the current home folder. If a sequence with the same name is already loaded in Siril, it will not be recreated. This only works for FITS files, not FITSEQ nor SER. The newly created sequence is not loaded in Siril.

Parámetros:

seq_root (str) -- The root name of the sequence to be created.

Devuelve:

True if the sequence was successfully created, False otherwise.

Tipo del valor devuelto:

bool

Muestra:

SirilError -- if an error occurred.

disconnect()

Closes the established socket or pipe connection. Note there is not usually any need to close this unless for some reason you wish to close a connection and subsequently reopen another one. This method is automatically called at script termination using an atexit handler so there is no need to do so manually. Calling this method will reset the progress bar.

Muestra:

SirilConnectionError -- if the connection cannot be closed.

error_messagebox(my_string, modal=False)

Send an error message to Siril. The maximum message length is 1022 bytes: longer messages will be truncated (but this is more than enough for an error message box). Note that the error message box is not modal by default: this is intended for displaying an error message more prominently than using the Siril log prior to quitting the application.

Parámetros:

  • my_string (str) -- The message to display in the error message box

  • modal (Optional[bool]) -- Sets whether or not the message box should be modal and wait for completion or non-modal and allow the script to continue execution. Note that although a modal message box will block execution of the script, if a TKinter main loop is running events will continue to queue up, so if the message box is triggered by clicking a button then the user may click it while the message box is shown and trigger a second message box which will display immediately the first one is closed.

Devuelve:

True if the error was successfully displayed, False otherwise

Tipo del valor devuelto:

bool

Muestra:

SirilError -- if an error occurred.

get_image(with_pixels=True, preview=False)

Request a copy of the current image open in Siril.

Parámetros:

  • with_pixels (Optional[bool]) -- optional bool specifying whether to get pixel data as a NumPy array, or only the image metadata. Defaults to True

  • preview (Optional[bool]) -- optional bool specifying whether to get pixeldata as a preview (i.e. 8-bit autostretched data) or as real image data. Defaults to False (i.e. real image data)

Tipo del valor devuelto:

Optional[FFit]

Devuelve:

FFit object containing the image metadata and (optionally) pixel data, or None if an error occurred

Muestra:
get_image_bgsamples()

Request background samples data from Siril.

Tipo del valor devuelto:

Optional[List[BGSample]]

Devuelve:

List of BGSamples background samples, with each set of coordinates expressed as a tuple[float, float], or None if no background samples have been set.

Muestra:
get_image_filename()

Request the filename of the loaded image from Siril.

Tipo del valor devuelto:

Optional[str]

Devuelve:

The filename as a string.

Muestra:
get_image_fits_header(return_as='str')

Retrieve the full FITS header of the current image loaded in Siril.

Parámetros:

return_as -- Optional string specifying the format of the returned header. Can be 'str' for a string or 'dict' for a dictionary.

Devuelve:

The image FITS header as a string, or None if there is no header. dict: The image FITS header as a dictionary, or None if there is no header. None: If the header is empty or not available.

Tipo del valor devuelto:

str

Muestra:
get_image_history()

Retrieve history entries in the FITS header of the current loaded Siril image using shared memory.

Parámetros:

none.

Devuelve:

The HISTORY entries in the FITS header as a list of strings, or

None if there are no HISTORY keywords.

Tipo del valor devuelto:

list

Muestra:
get_image_iccprofile()

Retrieve the ICC profile of the current Siril image using shared memory.

Args: none.

Devuelve:

The image ICC profile as a byte array, or None if the current image has no ICC profile.

Tipo del valor devuelto:

bytes

Muestra:
get_image_keywords()

Request FITS keywords data from Siril as a FKeywords object.

Tipo del valor devuelto:

Optional[FKeywords]

Devuelve:

FKeywords object containing the FITS keywords, or None if an error occurred

Muestra:

SirilError -- if a decoding error occurs.

get_image_pixeldata(shape=None, preview=False)

Retrieves the pixel data from the image currently loaded in Siril.

Parámetros:

  • shape (Optional[list[int]]) -- Optional list of [x, y, w, h] specifying the region to retrieve. If provided, gets pixeldata for just that region. If None, gets pixeldata for the entire image.

  • preview (Optional[bool]) -- optional bool specifying whether to get pixeldata as a preview (i.e. 8-bit autostretched data) or as real image data. Defaults to False (i.e. real image data)

Devuelve:

The image data as a numpy array

Tipo del valor devuelto:

numpy.ndarray

Muestra:

  • NoImageError -- If no image is currently loaded,

  • ValueError -- If an invalid shape is provided,

  • DataError -- if the array cannot be reshaped to the correct dimensions,

  • SirilError -- For other errors during pixel data retrieval,

get_image_shape()

Request the shape of the image from Siril.

Tipo del valor devuelto:

Optional[Tuple[int, int, int]]

Devuelve:

A tuple (channels, height, width) representing the shape of the image, or None if no image shape is available to return.

Raises: SirilError: if an error occurred.

get_image_stars()

Request star model PSF data from Siril.

Tipo del valor devuelto:

List[PSFStar]

Devuelve:

List of PSFStar objects containing the star data, or None if no stars can be found. If stars have already been detected using the findstar command then this list will be returned, otherwise automatic star detection will be attempted with the current star finder settings.

Muestra:
get_image_stats(channel)

Request image statistics from Siril for a specific channel.

Parámetros:

channel (int) -- Integer specifying which channel to get statistics for (typically 0, 1, or 2)

Tipo del valor devuelto:

Optional[ImageStats]

Devuelve:

ImageStats object containing the statistics, or None if no stats are available for the selected channel

Muestra:
get_image_unknown_keys()

Retrieve the unknown key in a FITS header of the current loaded Siril image using shared memory.

Parámetros:

none.

Devuelve:

The unknown keys as a string, or None if there are no unknown keys.

Tipo del valor devuelto:

bytes

Muestra:
get_selection_star(shape=None, channel=None)

Retrieves a PSFStar star model from the current selection in Siril. Only a single PSFStar is returned: if there are more than one in the selection, the first one identified by Siril's internal star detection algorithm is returned.

Parámetros:

  • shape (Optional[list[int]]) -- Optional list of [x, y, w, h] specifying the selection to retrieve from. w x h must not exceed 300 px x 300 px. If provided, looks for a star in the specified selection If None, looks for a star in the selection already made in Siril, if one is made.

  • channel (Optional[int]) -- Optional int specifying the channel to retrieve from. If provided 0 = Red / Mono, 1 = Green, 2 = Blue. If the channel is omitted the current viewport will be used if in GUI mode, or if not in GUI mode the method will fall back to channel 0

Devuelve:

the PSFStar object representing the star model, or None if

no star is detected in the selection.

Tipo del valor devuelto:

PSFStar

Muestra:
get_selection_stats(shape=None, channel=None)

Retrieves statistics for the current selection in Siril. :type shape: Optional[list[int]] :param shape: Optional list of [x, y, w, h] specifying the selection to

retrieve from. If provided, looks for a star in the specified selection If None, looks for a star in the selection already made in Siril, if one is made.

Parámetros:

channel (Optional[int]) -- Optional int specifying the channel to retrieve from. If provided 0 = Red / Mono, 1 = Green, 2 = Blue. If the channel is omitted the current viewport will be used if in GUI mode, or if not in GUI mode the method will fall back to channel 0

Devuelve:

the ImageStats object representing the selection statistics.

Tipo del valor devuelto:

ImageStats

Muestra:

  • SirilError -- If an error occurred during processing,

  • ValueError -- If an invalid shape is provided.

get_seq()

Request metadata for the current sequence loaded in Siril.

Tipo del valor devuelto:

Optional[Sequence]

Devuelve:

Sequence object containing the current sequence metadata, or None if an error occurred

Muestra:
get_seq_distodata(channel)

Request sequence distortion data from Siril

channel: Integer specifying which channel to get registration data for (typically 0, 1, or 2)

Tipo del valor devuelto:

Optional[DistoData]

Devuelve:

DistoData object containing the channel distortion parameters, or None if an error occurred

Muestra:
get_seq_frame(frame, with_pixels=True, preview=False)

Request sequence frame as a FFit from Siril.

Parámetros:

  • frame (int) -- Integer specifying which frame in the sequence to retrieve data for (between 0 and Sequence.number)

  • with_pixels (Optional[bool]) -- bool specifying whether or not to return the pixel data for the frame (default is True).

  • preview (Optional[bool]) -- bool specifying whether or not to return the real pixel data or an autostretched uint8_t preview version. Only has an effect in conjunction with with_pixels = True

Tipo del valor devuelto:

Optional[FFit]

Devuelve:

FFit object containing the frame data

Muestra:
get_seq_frame_filename(frame)

Request the filename of the specified frame of the loaded sequence from Siril.

Tipo del valor devuelto:

Optional[str]

Devuelve:

The filename as a string.

Muestra:
get_seq_frame_header(frame, return_as='str')

Retrieve the full FITS header of an image from the sequence loaded in Siril.

Parámetros:

  • frame (int) -- Integer specifying which frame in the sequence to retrieve data for

  • Sequence.number) ((between 0 and)

  • return_as -- Optional string specifying the format of the returned header. Can be 'str' for a string or 'dict' for a dictionary.

Devuelve:

The image FITS header as a string, or None if there is no header. dict: The image FITS header as a dictionary, or None if there is no header. None: If the header is empty or not available.

Tipo del valor devuelto:

str

Muestra:
get_seq_frame_pixeldata(frame, shape=None, preview=False)

Retrieves the pixel data from a frame in the sequence currently loaded in Siril.

Parámetros:

  • frame (int) -- selects the frame to retrieve pixel data from

  • shape (Optional[List[int]]) -- Optional list of [x, y, w, h] specifying the region to retrieve. If provided, gets pixeldata for just that region. If None, gets pixeldata for the entire image.

  • preview (Optional[bool]) -- optional bool specifying whether to get pixeldata as a preview (i.e. 8-bit autostretched data) or as real image data. Defaults to False (i.e. real image data).

Devuelve:

The image data as a numpy array

Tipo del valor devuelto:

numpy.ndarray

Muestra:

  • ValueError -- If an invalid shape is provided,

  • DataError -- if the array cannot be reshaped to the correct dimensions,

  • SirilError -- For other errors during pixel data retrieval.

get_seq_imgdata(frame)

Request sequence frame metadata from Siril.

Parámetros:

frame (int) -- Integer specifying which frame in the sequence to get image metadata for (between 0 and Sequence.number)

Tipo del valor devuelto:

Optional[ImgData]

Devuelve:

ImgData object containing the frame metadata, or None if an error occurred

Muestra:
get_seq_regdata(frame, channel)

Request sequence frame registration data from Siril.

Parámetros:

  • frame (int) -- Integer specifying which frame in the sequence to get registration data for (between 0 and Sequence.number),

  • channel (int) -- Integer specifying which channel to get registration data for (typically 0, 1, or 2)

Tipo del valor devuelto:

Optional[RegData]

Devuelve:

RegData object containing the registration data, or None if no registration data is available for the specified frame and channel

Muestra:
get_seq_stats(frame, channel)

Request sequence frame statistics from Siril.

Parámetros:

  • frame (int) -- Integer specifying which frame in the sequence to get statistics data for (between 0 and Sequence.number)

  • channel (int) -- Integer specifying which channel to get statistics for (typically 0, 1, or 2)

Tipo del valor devuelto:

Optional[ImageStats]

Devuelve:

ImageStats object containing the statistics, or None if an error occurred

Muestra:
get_siril_active_vport()

Request the active viewport from Siril.

Devuelve:

  • sirilpy.SirilVport.RED / sirilpy.SirilVport.MONO

  • sirilpy.SirilVport.GREEN,

  • sirilpy.SirilVport.BLUE,

  • sirilpy.SirilVport.RGB

Note that RED and MONO share the same IntEnum value, so there is no difference between a test for one and the other; the two enum labels are provided solely to aid code legibility.

Tipo del valor devuelto:

A SirilVport representing the active vport

Muestra:

  • DataError -- if no response or an invalid response is received,

  • SirilError -- if an error occurred.

get_siril_config(group, key)

Request a configuration value from Siril.

Parámetros:

  • group (str) -- Configuration group name,

  • key (str) -- Configuration key name within the group (Available values for group and key can be determined using the "get -A" command)

Tipo del valor devuelto:

Union[bool, int, float, str, List[str], None]

Devuelve:

The configuration value with appropriate Python type, or None if an error occurred.

Muestra:

  • DataError -- if an unknown config type is encountered,

  • SirilError -- if an error occurred getting the requested config value

get_siril_configdir()

Request the user config directory used by Siril.

Tipo del valor devuelto:

str

Devuelve:

The user config directory as a string.

Muestra:
get_siril_selection()

Request the image selection from Siril.

Tipo del valor devuelto:

Optional[Tuple[int, int, int, int]]

Devuelve:

A tuple (x, y, height, width) representing the current selection, or None if no selection is made.

Muestra:

SirilError -- if an error occurred.

get_siril_systemdatadir()

Request the system data directory used by Siril.

Tipo del valor devuelto:

Optional[str]

Devuelve:

The system data directory as a string.

Muestra:
get_siril_userdatadir()

Request the user data directory used by Siril.

Tipo del valor devuelto:

str

Devuelve:

The user data directory as a string.

Muestra:
get_siril_wd()

Request the current working directory from Siril.

Tipo del valor devuelto:

str

Devuelve:

The current working directory as a string.

Muestra:
image_lock()

A context manager that handles claiming and releasing the processing thread.

This method is designed to be used with a with statement to ensure that the thread is properly claimed before processing and released after processing, even if an exception occurs during processing. It is preferable to use this context manager rather than manually calling claim_thread() and release_thread() as the context manager will ensure correct cleanup if an exception occurs.

Note that the image_lock() context should only be entered when the script itself is operating on the Siril image data. If the script is calling a Siril command to alter the Siril image then the context must not be entered or the Siril command will be unable to acquire the processing thread and will fail.

Example:

try:
    with siril.image_lock():
        # Get image data
        image_data = self.get_image_pixeldata()
        # Process image data
        processed_data = some_processing_function(image_data)
        # Set the processed image data
        siril.set_image_pixeldata(processed_data)
except ProcessingThreadBusyError:
    # Handle busy thread case
    pass
except ImageDialogOpenError:
    # Handle open dialog case
    pass
Muestra:
info_messagebox(my_string, modal=False)

Send an information message to Siril. The maximum message length is 1022 bytes: longer messages will be truncated. This is intended for displaying informational messages more prominently than using the Siril log.

Parámetros:

  • my_string (str) -- The message to display in the info message box

  • modal (Optional[bool]) -- Sets whether or not the message box should be modal and wait for completion or non-modal and allow the script to continue execution. Note that although a modal message box will block execution of the script, if a TKinter main loop is running events will continue to queue up, so if the message box is triggered by clicking a button then the user may click it while the message box is shown and trigger a second message box which will display immediately the first one is closed.

Devuelve:

True if the info was successfully displayed, False otherwise

Tipo del valor devuelto:

bool

Muestra:

SirilError -- if an error occurred.

is_cli()

Check if the current instance is running in CLI mode. This method is useful to detect how the script was invoked and whether to show or not a GUI. This is False when the script is called by clicking in the Script menu, True otherwise.

Devuelve:

True if running in CLI mode, False otherwise.

Tipo del valor devuelto:

bool

is_image_loaded()

Check if a single image is loaded in Siril.

Devuelve:

True if a single image is loaded, False if a single image is not loaded

Tipo del valor devuelto:

bool

Muestra:
is_sequence_loaded()

Check if a sequence is loaded in Siril.

Devuelve:

True if a sequence is loaded, False if a sequence is not loaded

Tipo del valor devuelto:

bool

Muestra:
log(my_string, color=LogColor.DEFAULT)

Send a log message to Siril. The maximum message length is 1022 bytes: longer messages will be truncated.

Parámetros:

  • my_string (str) -- The message to log

  • color (LogColor) -- Defines the text color, defaults to white. See the documentation

  • which (for LogColor for an explanation of which colors should be used for)

  • purposes.

Muestra:

SirilError -- if the command fails

Tipo del valor devuelto:

bool

overlay_add_polygon(polygon)

Adds a user polygon to the Siril display overlay :type polygon: Polygon :param polygon: Polygon defining the polygon to be added

Devuelve:

entrada actualizada con el ID asignado por Siril

Tipo del valor devuelto:

Polygon

Muestra:
overlay_clear_polygons()

Limpia todos los polígonos del usuario de la capa superpuesta de Siril

Devuelve:

True if the command succeeded, False otherwise

Tipo del valor devuelto:

bool

Muestra:
overlay_delete_polygon(polygon_id)

Deletes a single user polygon from the Siril overlay, specified by ID

Parámetros:

id -- int specifying the polygon ID to be deleted

Muestra:

SirilError -- on failure

overlay_draw_polygon(color=16711744, fill=False)

Enters a mode where the user can draw a Polygon in the Siril window by clicking the main mouse button and dragging. Releasing the mouse button finalises and closes the polygon.

Parámetros:

  • color -- uint32 specifying packed RGBA values. Default: 0x00FF0040, 75% transparent green)

  • fill -- bool specifying whether or not to fill the polygon (default: False)

overlay_get_polygon(polygon_id)

Gets a single user polygon from the Siril overlay, specified by ID

Parámetros:

id -- int specifying the polygon ID to be retrieved. The special ID -1 will

retrieve the most recently added polygon.

Devuelve:

the specified Polygon if it exists, None otherwise

Tipo del valor devuelto:

Polygon

Muestra:

SirilError -- on failure

overlay_get_polygons_list()

Gets a List of all user polygons from the Siril overlay

Devuelve:

the list of Polygon if some exist, None otherwise

Tipo del valor devuelto:

List[Polygon]

Muestra:
pix2radec(x, y)

Converts a pair of pixel coordinates into RA and dec coordinates using the WCS of the image loaded in Siril. This requires that an image is loaded in Siril and that it has been platesolved (i.e. it has a WCS solution).

Parámetros:

  • x (float) -- float: provides the x coordinate to be converted

  • y (float) -- float: provides the y coordinate to be converted

Devuelve:

(RA, Dec) as a Tuple of two floats.

Tipo del valor devuelto:

Tuple[float, float]

Muestra:

  • NoImageError -- If no image or sequence is loaded,

  • ValueError -- If the image or loaded sequence frame is not plate solved,

  • SirilError -- For errors during pix2radec execution.

radec2pix(ra, dec)

Converts a pair of RA,dec coordinates into image pixel coordinates using the WCS of the image loaded in Siril. This requires that an image is loaded in Siril and that it has been platesolved (i.e. it has a WCS solution).

Parámetros:

  • ra (float) -- float: provides the RA coordinate to be converted

  • dec (float) -- float: provides the dec coordinate to be converted

Devuelve:

[x, y] as a Tuple of two floats.

Tipo del valor devuelto:

Tuple[float, float]

Muestra:

  • NoImageError -- If no image or sequence is loaded,

  • ValueError -- If the image or loaded sequence frame is not plate solved,

  • SirilError -- For errors during radec2pix execution.

reset_progress()

Resets the Siril progress bar.

Parámetros:

none

Muestra:

SirilError -- For any errors.

Tipo del valor devuelto:

bool

set_image_bgsamples(points, show_samples=False, recalculate=True)

Serialize a set of background sample points and send via shared memory. Points can be provided either as: - List of (x,y) Tuples: BGSamples are created with these positions and Siril will automatically compute the statistics. - List of BGSample objects: The complete sample data is sent to Siril. By default Siril will recalculate statistics for the sample points on receipt, but this can be overridden with the argument recalculate=False

Parámetros:

  • points (Union[List[Tuple[float, float]], List[BGSample]]) -- List of sample points, either as (x,y) tuples or BGSample objects

  • show_samples (bool) -- Whether to show the sample points in Siril

  • recalculate -- Whether to recalculate the sample points once set. This only applies if the sample points are provided as a List of BGSamples, in which case it defaults to True. If the sample points are provided as a List of (x,y) Tuples then the parameter has no effect. Setting recalculate=False is usually a bad idea but the option is provided to support potential advanced uses where the values are adjusted in python code to manipulate the background fit.

Returns: True if the command succeeded, otherwise False

Muestra:

  • NoImageError -- if no image is loaded in Siril,

  • ValueError -- if samples do not have valid positions,

  • SirilError -- if there was a Siril error in handling the command.

set_image_metadata_from_header_string(header)

Send image metadata to Siril from a FITS header. The header can be obtained from a sirilpy FFit.header or alternatively from a FITS file obened from disk using astropy.fits.

Example:

hdul = fits.open('your_fits_file.fits')
# Get the header from the primary HDU (or any other HDU you want)
header = hdul[0].header
# Convert the header to string
header_string = header.tostring(sep='\\n')
# Send the metadata to Siril
siril.set_image_metadata_from_header_string(header_string)
Parámetros:

header (str) -- string containing the FITS header data

Devuelve:

True if successful, False otherwise

Tipo del valor devuelto:

bool

Muestra:

  • TypeError -- invalid parameter provided,

  • NoImageError -- if no image is loaded in Siril,

  • SirilError -- if an error occurs.

set_image_pixeldata(image_data)

Send image data to Siril using shared memory.

Parámetros:

image_data (ndarray) -- numpy.ndarray containing the image data. Must be 2D (single channel) or 3D (multi-channel) array with dtype either np.float32 or np.uint16.

Muestra:

  • NoImageError -- if no image is loaded in Siril,

  • ValueError -- if the input array is invalid,

  • SirilError -- if there was an error in handling the command.

Tipo del valor devuelto:

bool

set_seq_frame_incl(index, incl)

Set whether a given frame is included in the currently loaded sequence in Siril. This method is intended for use in creating custom sequence filters.

Parámetros:

  • index (int) -- integer specifying which frame to set the pixeldata for.

  • incl (bool) -- bool specifying whether the frame is included or not.

Muestra:
set_seq_frame_pixeldata(index, image_data)

Send image data to Siril using shared memory.

Parámetros:

  • index (int) -- integer specifying which frame to set the pixeldata for.

  • image_data (ndarray) -- numpy.ndarray containing the image data. Must be 2D (single channel) or 3D (multi-channel) array with dtype either np.float32 or np.uint16.

Muestra:

  • NoSequenceError -- if no sequence is loaded in Siril,

  • ValueError -- if the input array is invalid,

  • SirilError -- if there was an error in handling the command.

Tipo del valor devuelto:

bool

set_siril_selection(x=None, y=None, w=None, h=None, selection=None)

Set the image selection in Siril using the provided coordinates and dimensions.

Parámetros:

  • x (Optional[int]) -- X-coordinate of the selection's top-left corner (must be provided with y, w, h)

  • y (Optional[int]) -- Y-coordinate of the selection's top-left corner (must be provided with x, w, h)

  • w (Optional[int]) -- Width of the selection (must be provided with x, y, h)

  • h (Optional[int]) -- Height of the selection (must be provided with x, y, w)

  • selection (Optional[Tuple[int, int, int, int]]) -- A tuple of (x, y, w, h) as returned by get_siril_selection()

Muestra:

  • SirilError -- if an error occurred.

  • ValueError -- if parameters are not properly provided.

Devuelve:

True if the selection was set successfully

Tipo del valor devuelto:

bool

undo_save_state(my_string)

Saves an undo state. The maximum message length is 70 bytes: longer messages will be truncated.

Parámetros:

my_string (str) -- The message to log in FITS HISTORY

Devuelve:

True if the message was successfully logged, False otherwise

Tipo del valor devuelto:

bool

Muestra:

SirilError -- if an error occurred.

update_progress(message, progress)

Send a progress update to Siril with a message and completion percentage.

Parámetros:

  • message (str) -- Status message to display,

  • progress (float) -- Progress value in the range 0.0 to 1.0. The following special values can be used: -1.0 will pulsate the progress bar, and -2.0 will update the progress bar text but will not update the progress shown in the bar.

Muestra:

  • ValueError -- If the progress argument is out of range,

  • SirilError -- For any other errors.

Tipo del valor devuelto:

bool

warning_messagebox(my_string, modal=False)

Send a warning message to Siril. The maximum message length is 1022 bytes: longer messages will be truncated. This is intended for displaying warning messages more prominently than using the Siril log.

Parámetros:

  • my_string (str) -- The message to display in the warning message box

  • modal (Optional[bool]) -- Sets whether or not the message box should be modal and wait for completion or non-modal and allow the script to continue execution. Note that although a modal message box will block execution of the script, if a TKinter main loop is running events will continue to queue up, so if the message box is triggered by clicking a button then the user may click it while the message box is shown and trigger a second message box which will display immediately the first one is closed.

Devuelve:

True if the warning was successfully displayed, False otherwise

Tipo del valor devuelto:

bool

Muestra:

SirilError -- if an error occurred.

xy_plot(plot_data, display=True, save=False)

Serialize plot data and send via shared memory. See the sirilpy.plot submodule documentation for how to configure a PlotData object for use with SirilInterface.xy_plot()

Parámetros:

  • plot_metadata -- PlotMetadata object containing plot configuration

  • display -- bool indicating whether to display the plot on screen (defaults to True)

  • save -- bool indicating whether to save to the file specified in PlotData.savename (defaults to False)

Muestra:

  • DataError -- if invalid xy_plot data is received via shared memory,

  • SirilError -- If an error occurs.

Sirilpy Data Models

This submodule provides dataclasses to represent the main Siril data structures. Most dataclasses have corresponding deserialization methods that are used by the SirilInterface methods. All its members are made available at the module root level, there is no need to import models separately.

class sirilpy.models.BGSample(x=None, y=None, position=None, size=25, **kwargs)

Bases: object

Python equivalent of the Siril background_sample struct. Used to hold background sample data obtained from Siril, or to generate or modify background sample data to set in Siril. A BGSample can be constructed as: - s1 = BGSample(x=1.0, y=2.0) - s2 = BGSample(position=(1.0, 2.0)) - s3 = BGSample(x=1.0, y=2.0, mean=0.5, size=31)

classmethod deserialize(data)

Deserialize a portion of a buffer into a BGSample object

Parámetros:

data (bytes) -- The full binary buffer containing BGSample data

Devuelve:

A BGSample object

Tipo del valor devuelto:

BGSample

Muestra:

  • ValueError -- If the buffer slice size does not match the expected size.

  • struct.error -- If there is an error unpacking the binary data.

max: float = 0.0
mean: float = 0.0
median: Tuple[float, float, float] = (0.0, 0.0, 0.0)

Median values for R, G and B channels. For mono images only median[0] is used.

min: float = 0.0
position: Optional[Tuple[float, float]] = None

Position in (x, y) image coordinates

size: int = 25

The default size matches the size of Siril bg samples.

valid: bool = True

Samples default to being valid

class sirilpy.models.DistoData(index=DistoType.DISTO_UNDEF, filename='', velocity=(0, 0))

Bases: object

Python equivalent of Siril disto_params structure

filename: str = ''

filename if DISTO_FILE or DISTO_MASTER (and optional for DISTO_FILE_COMET)

index: DistoType = 0

Specifies the distrosion type

velocity: Tuple[float, float] = (0, 0)

shift velocity if DISTO_FILE_COMET

class sirilpy.models.FFit(bitpix=None, orig_bitpix=None, naxis=0, _naxes=(0, 0, 0), keywords=<factory>, checksum=False, header=None, unknown_keys=None, stats=<factory>, mini=0.0, maxi=0.0, neg_ratio=0.0, _data=None, top_down=False, _focalkey=False, _pixelkey=False, history=<factory>, color_managed=False, _icc_profile=None)

Bases: object

Python equivalent of Siril ffit (FITS) structure, holding image pixel data and metadata.

allocate_data()

Allocate memory for image data with appropriate type. self.width, self.height, self.naxis, self.naxes and self.dtype must be set before calling this method.

Muestra:

ValueError -- if self.bitpix is not set to BitpixType.USHORT_IMG or BitpixType.FLOAT_IMG

ensure_data_type(target_type=None)

Ensure data is in the correct type with proper scaling

Parámetros:

target_type -- Optional np.dtype to convert to. If None, uses self.type

Muestra:

ValueError -- if the conversion is between data types that are not internally used by Siril for calculation

estimate_noise(array, nullcheck=True, nullvalue=0.0)

Estimate the background noise in the input image using the sigma of first-order differences.

noise = 1.0 / sqrt(2) * RMS of (flux[i] - flux[i-1])

Parámetros:

  • array (np.ndarray) -- 2D array of image pixels (np.uint16 or np.float32).

  • nullcheck (bool) -- If True, check for null values.

  • nullvalue (Optional[float]) -- The value of null pixels (only used if nullcheck is True).

Devuelve:

Estimated noise value.

Tipo del valor devuelto:

float

Muestra:

ValueError -- if the array is the wrong shape

get_channel(channel)

Get a specific channel of the pixel data. Note that this does not pull pixel data directly from the image loaded in Siril: that must previously have been obtained using get_image_pixeldata() or get_image()

Tipo del valor devuelto:

ndarray

update_stats()

Update image statistics for all channels. Note that this only updates the statistics based on the NumPy array representing pixel data in the python FFit object, it does not update the statistics of the image in Siril.

bitpix: Optional[BitpixType] = None

FITS header specification of the image data type.

property channels: int

Image channels

checksum: bool = False

Whether Siril will write FITS data checksums for this file.

color_managed: bool = False

Specifies whether the image is color managed or not.

property data: ndarray | None

The pixel data of the current image loaded in Siril, stored as a NumPy array

header: Optional[str] = None

The FITS header as a string.

property height: int

Image height

history: list[str]

Contains a list of strings holding the HISTORY entries for this image.

property icc_profile: bytes | None

The ICC profile as raw bytes data. This may be converted for use by modules such as pillow which can handle ICC profiles.

keywords: FKeywords

A FKeywords object containing FITS header keywords.

maxi: float = 0.0

The maximum value across all image channels.

mini: float = 0.0

The minimum value across all image channels.

property naxes: Tuple[int, int, int]

The naxes tuple holds the image dimensions as width x height x channels. Note that the axis ordering differs between Siril representation as held in naxes and numpy representation as held in _data.shape (which is channels x height x width)

naxis: int = 0

The number of axes (2 for a mono image, 3 for a RGB image). Corresponds to the FITS kwyword NAXIS.

neg_ratio: float32 = 0.0

The ratio of negative pixels to the total pixels.

orig_bitpix: Optional[BitpixType] = None

FITS header specification of the original image data type.

stats: List[Optional[ImageStats]]

A list of ImageStats objects, one for each channel.

top_down: bool = False

Specifies the ROWORDER for this image. The FITS specification directs that FITS should be stored bottom-up, but many CMOS sensors are natively TOP_DOWN and capture software tends to save FITS images captured by these sensors as TOP_DOWN.

unknown_keys: Optional[str] = None

All unknown FITS header keys as a string. This gives access to header cards that Siril does not use internally.

property width: int

Image width

class sirilpy.models.FKeywords(bscale=1.0, bzero=0.0, lo=0, hi=0, flo=0.0, fhi=0.0, program='', filename='', row_order='', filter='', image_type='', object='', instrume='', telescop='', observer='', bayer_pattern='', sitelat_str='', sitelong_str='', focname='', date=None, date_obs=None, data_max=0.0, data_min=0.0, pixel_size_x=0.0, pixel_size_y=0.0, binning_x=1, binning_y=1, expstart=0.0, expend=0.0, bayer_xoffset=0, bayer_yoffset=0, airmass=1.0, focal_length=0.0, flength=0.0, iso_speed=0.0, exposure=0.0, aperture=0.0, ccd_temp=0.0, set_temp=0.0, livetime=0.0, stackcnt=0, cvf=0.0, gain=0, offset=0, focuspos=0, focussz=0, foctemp=0.0, centalt=0.0, centaz=0.0, sitelat=0.0, sitelong=0.0, siteelev=0.0)

Bases: object

Python equivalent of Siril fkeywords structure. Contains the FITS header keyword values converted to suitable data types.

classmethod deserialize(data)

Deserialize binary response into an FKeywords object.

Args: response: Binary data to unpack

Returns: (FKeywords) object

Tipo del valor devuelto:

FKeywords

Raises: ValueError: If received data size is incorrect

struct.error: If unpacking fails

airmass: float = 1.0

Airmass at frame center (Gueymard 1993)

aperture: float = 0.0

Aperture value as a float

bayer_pattern: str = ''

Bayer color pattern

bayer_xoffset: int = 0

X offset of the Bayer pattern

bayer_yoffset: int = 0

Y offset of the Bayer pattern

binning_x: int = 1

XBINNING FITS header card as an int

binning_y: int = 1

YBINNING FITS header card as an int

bscale: float = 1.0

Offset data range to that of unsigned short

bzero: float = 0.0

Default scaling factor

ccd_temp: float = 0.0

CCD temperature as a float

centalt: float = 0.0

[deg] Altitude of telescope

centaz: float = 0.0

[deg] Azimuth of telescope

cvf: float = 0.0

Conversion factor (e- / ADU)

data_max: float = 0.0

used to check if 32b float is in the [0, 1] range

data_min: float = 0.0

used to check if 32b float is in the [0, 1] range

date: Optional[datetime] = None

UTC date that FITS file was created

date_obs: Optional[datetime] = None

ss observation start, UT

Type:

YYYY-MM-DDThh

Type:

mm

expend: float = 0.0

Exposure end as a Julian date

exposure: float = 0.0

Exposure time as a float (s)

expstart: float = 0.0

Exposure start as a Julian date

fhi: float32 = 0.0

MIPS-Hi key in FITS file, "Upper visualization cutoff (float)"

filename: str = ''

Original Filename

filter: str = ''

Active filter name

flength: float = 0.0

[mm] Focal length

flo: float32 = 0.0

MIPS-LO key in FITS file, "Lower visualization cutoff (float)"

focal_length: float = 0.0

[mm] Focal length

focname: str = ''

Focusing equipment name

foctemp: float = 0.0

Focuser temperature

focuspos: int = 0

Focuser position

focussz: int = 0

[um] Focuser step size

gain: int = 0

Gain factor read in camera

hi: int = 0

MIPS-HI key in FITS file, "Upper visualization cutoff"

image_type: str = ''

Type of image

instrume: str = ''

Instrument name

iso_speed: float = 0.0

ISO speed value as a float

livetime: float = 0.0

Sum of exposure times (s)

lo: int = 0

MIPS-LO key in FITS file, "Lower visualization cutoff"

object: str = ''

Name of the object of interest

observer: str = ''

Observer name

offset: int = 0

Offset value read in camera

pixel_size_x: float = 0.0

XPIXSZ FITS header card as a float

pixel_size_y: float = 0.0

YPIXSZ FITS header card as a float

program: str = ''

Software that created this HDU

row_order: str = ''

Order of the rows in image array

set_temp: float = 0.0

CCD set temperature as a float

siteelev: float = 0.0

[m] Observation site elevation

sitelat: float = 0.0
sitelat_str: str = ''
sitelong: float = 0.0

[deg] Observation site longitude

sitelong_str: str = ''
stackcnt: int = 0

Number of stacked frames

telescop: str = ''

Telescope used to acquire this image

class sirilpy.models.FPoint(x, y)

Bases: object

Represents a 2D point with float x and y coordinate values in the Siril image.

x: float

x co-ordinate

y: float

y co-ordinate

class sirilpy.models.Homography(h00=0.0, h01=0.0, h02=0.0, h10=0.0, h11=0.0, h12=0.0, h20=0.0, h21=0.0, h22=0.0, pair_matched=0, Inliers=0)

Bases: object

Python equivalent of the Siril Homography structure. Contains coefficients for the Homography matrix that maps a sequence frame onto the reference frame.

Inliers: int = 0

number of inliers kept after RANSAC step

h00: float = 0.0

Homography matrix H00

h01: float = 0.0

Homography matrix H01

h02: float = 0.0

Homography matrix H02

h10: float = 0.0

Homography matrix H10

h11: float = 0.0

Homography matrix H11

h12: float = 0.0

Homography matrix H12

h20: float = 0.0

Homography matrix H20

h21: float = 0.0

Homography matrix H21

h22: float = 0.0

Homography matrix H22

pair_matched: int = 0

number of pairs matched

class sirilpy.models.ImageStats(total=0, ngoodpix=0, mean=0.0, median=0.0, sigma=0.0, avgDev=0.0, mad=0.0, sqrtbwmv=0.0, location=0.0, scale=0.0, min=0.0, max=0.0, normValue=0.0, bgnoise=0.0)

Bases: object

Python equivalent of Siril imstats structure. Contains statistics for a particular channel of a Siril image.

classmethod deserialize(data)

Deserialize binary data into an ImageStats object.

Parámetros:

data (bytes) -- (bytes) Binary data to unpack

Tipo del valor devuelto:

ImageStats

Returns: ImageStats object

Raises: SirilError: If received data size is incorrect

struct.error: If unpacking fails

avgDev: float = 0.0

average deviation of pixels

bgnoise: float = 0.0

RMS background noise

location: float = 0.0

location of pixel values

mad: float = 0.0

mean average deviation of pixels

max: float = 0.0

maximum pixel value

mean: float = 0.0

mean value of pixels

median: float = 0.0

median value of pixels

min: float = 0.0

minimum pixel value

ngoodpix: int = 0

number of non-zero pixels

normValue: float = 0.0

norm value of the pixels

scale: float = 0.0

scale value of the pixels

sigma: float = 0.0

standard deviation of pixels

sqrtbwmv: float = 0.0

square root of the biweight midvariance of pixel values

total: int = 0

total number of pixels

class sirilpy.models.ImgData(filenum=0, incl=False, date_obs=None, airmass=0.0, rx=0, ry=0)

Bases: object

Python equivalent of Siril imgdata structure

classmethod deserialize(response)

Deserialize binary response into an ImgData object.

Parámetros:

response (bytes) -- Binary data to unpack.

Devuelve:

An ImgData object with deserialized data.

Tipo del valor devuelto:

ImgData

Muestra:

  • ValueError -- If received data size is incorrect.

  • struct.error -- If unpacking fails.

airmass: float = 0.0

airmass of the image

date_obs: Optional[datetime] = None

date of the observation

filenum: int = 0

real file index in the sequence

incl: bool = False

selected in the sequence

rx: int = 0

width

ry: int = 0

height

class sirilpy.models.PSFStar(star_name=None, B=0.0, A=0.0, x0=0.0, y0=0.0, sx=0.0, sy=0.0, fwhmx=0.0, fwhmy=0.0, fwhmx_arcsec=0.0, fwhmy_arcsec=0.0, angle=0.0, rmse=0.0, sat=0.0, R=0, has_saturated=False, beta=0.0, profile=StarProfile.GAUSSIAN, xpos=0.0, ypos=0.0, mag=0.0, Bmag=0.0, s_mag=999.99, s_Bmag=999.99, SNR=0.0, BV=0.0, B_err=0.0, A_err=0.0, x_err=0.0, y_err=0.0, sx_err=0.0, sy_err=0.0, ang_err=0.0, beta_err=0.0, layer=0, units=None, ra=0.0, dec=0.0)

Bases: object

Python equivalent of the Siril fwhm_struct structure. Contains data on a modelled fit to a star identified in the image.

classmethod deserialize(data)

Deserialize a portion of a buffer into a PSFStar object.

Parámetros:

data (bytes) -- (bytes) The full binary buffer containing PSFStar data.

Tipo del valor devuelto:

PSFStar

Devuelve:

PSFStar object

Muestra:

  • ValueError -- If the buffer slice size does not match the expected size.

  • struct.error -- If there is an error unpacking the binary data.

A: float = 0.0

amplitude

A_err: float = 0.0

error in A

B: float = 0.0

average sky background value

BV: float = 0.0

only used to pass data in photometric color calibration

B_err: float = 0.0

error in B

Bmag: float = 0.0

B magnitude

R: int = 0

Optimized box size to enclose sufficient pixels in the background

SNR: float = 0.0

SNR of the star

ang_err: float = 0.0

error in angle

angle: float = 0.0

angle of the x and yaxes with respect to the image x and y axes

beta: float = 0.0

Moffat equation beta parameter

beta_err: float = 0.0

error in beta

dec: float = 0.0

Declination

fwhmx: float = 0.0

FWHM in x axis in pixels

fwhmx_arcsec: float = 0.0

FWHM in x axis in arc seconds

fwhmy: float = 0.0

FWHM in y axis in pixels

fwhmy_arcsec: float = 0.0

FWHM in y axis in arc seconds

has_saturated: bool = False

Shows whether the star is saturated or not

layer: int = 0

image channel on which the star modelling was carried out

mag: float = 0.0

  1. magnitude, approximate or accurate

profile: StarProfile = 0
ra: float = 0.0

Right Ascension

rmse: float = 0.0

RMSE of the minimization

s_Bmag: float = 999.99

error on the B magnitude

s_mag: float = 999.99

error on the (V) magnitude

sat: float = 0.0

Level above which pixels have satured

star_name: Optional[str] = None
sx: float = 0.0

Size of the fitted function on the x axis in PSF coordinates

sx_err: float = 0.0

error in sx

sy: float = 0.0

Size of the fitted function on the y axis in PSF coordinates

sy_err: float = 0.0

error in sy

units: Optional[str] = None

Units

x0: float = 0.0

x coordinate of the peak

x_err: float = 0.0

error in x

xpos: float = 0.0

x position of the star in the image

y0: float = 0.0

y coordinate of the peak

y_err: float = 0.0

error in y

ypos: float = 0.0

y position of the star in the image

class sirilpy.models.Polygon(points, polygon_id=0, color=4294967295, fill=False, legend=None)

Bases: object

Represents a user-defined polygon. These can be filled or outline-only, and can have any color and transparency (alpha) value. They can also have an optional label which is displayed centred on the polygon.

Note that Polygons should be considered transitory if used with the overlay - they can be used to display information to the user but they may be cleared at any time if the user toggles the overlay button in the main Siril interface to clear the overlay.

polygon_id

A unique identifier for the polygon.

Type:

int

points

List of points defining the polygon's shape.

Type:

List[FPoint]

color

Packed RGBA color (32-bit integer).

Type:

int

fill

If True, the polygon should be filled when drawn.

Type:

bool

legend

Optional legend for the polygon.

Type:

str

classmethod deserialize_polygon(data)

Creates a Polygon object by deserializing a byte array.

Devuelve:

A Polygon object and any remaining bytes in the byte

array. (The remaining bytes are for use in deserialize_polygon_list and can be safely ignored if deserializing a single polygon.)

Tipo del valor devuelto:

Tuple

Muestra:

ValueError -- If there is insufficient data to deserialize.

classmethod deserialize_polygon_list(data)

Creates a List of Polygon objects by deserializing a byte array.

Devuelve:

A List of Polygon objects.

Tipo del valor devuelto:

List

Muestra:

ValueError -- If there is invalid data to deserialize.

classmethod from_rectangle(rect, **kwargs)

Create a Polygon from a rectangle of the kind returned by sirilpy.connection.get_siril_selection().

Parámetros:

  • rect (Tuple[int, int, int, int]) -- Rectangle as (x, y, width, height)

  • **kwargs -- Additional keyword arguments to pass to Polygon constructor (polygon_id, color, fill, legend)

Devuelve:

A new Polygon instance representing the rectangle

Tipo del valor devuelto:

Polygon

contains_point(x, y)

Determine if a point is inside the polygon using Dan Sunday's optimized winding number algorithm.

This algorithm is more robust than ray casting for complex polygons and handles edge cases better, including points on edges and self-intersecting polygons.

Parámetros:

  • x (float) -- X coordinate of the point to test.

  • y (float) -- Y coordinate of the point to test.

Devuelve:

True if the point is inside the polygon, False otherwise.

Tipo del valor devuelto:

bool

get_bounds()

Get the bounding box of the polygon.

Devuelve:

(min_x, min_y, max_x, max_y)

Tipo del valor devuelto:

Tuple[float, float, float, float]

Muestra:

ValueError -- If the polygon has no points.

get_max_x()

Get the maximum x coordinate of the polygon.

Tipo del valor devuelto:

float

get_max_y()

Get the maximum y coordinate of the polygon.

Tipo del valor devuelto:

float

get_min_x()

Get the minimum x coordinate of the polygon.

Tipo del valor devuelto:

float

get_min_y()

Get the minimum y coordinate of the polygon.

Tipo del valor devuelto:

float

serialize()

Serializes a single Polygon object into a byte array.

Devuelve:

A byte array representing the serialized polygon data.

Tipo del valor devuelto:

bytes

Muestra:

ValueError -- If the number of points exceeds the allowed limit.

color: int = 4294967295

no-index:

Type:

32-bit RGBA color (packed, uint_8 per component. Default value is 0xFFFFFFFF)

fill: bool = False

no-index:

Type:

whether or not the polygon should be filled when drawn

legend: str = None

no-index:

Type:

an optional legend

points: List[FPoint]

no-index:

Type:

List of points defining the polygon's shape

polygon_id: int = 0

no-index:

Type:

unique identifier

class sirilpy.models.RegData(fwhm=0.0, weighted_fwhm=0.0, roundness=0.0, quality=0.0, background_lvl=0.0, number_of_stars=0, H=<factory>)

Bases: object

Python equivalent of Siril regdata structure

classmethod deserialize(data)

Deserialize a binary response into a RegData object.

Parámetros:

data (bytes) -- Binary data to unpack

Tipo del valor devuelto:

RegData

Returns: RegData object

Raises: SirilError if the received data doesn't match the expected size'

struct.error If unpacking fails

H: Homography

Stores a homography matrix describing the affine transform from this frame to the reference frame

background_lvl: float32 = 0.0

background level

fwhm: float = 0.0

copy of fwhm->fwhmx, used as quality indicator

number_of_stars: int = 0

number of stars detected in the image

quality: float = 0.0

measure of image quality

roundness: float32 = 0.0

fwhm->fwhmy / fwhm->fwhmx, 0 when uninit, ]0, 1] when set

weighted_fwhm: float32 = 0.0

used to exclude spurious images

class sirilpy.models.Sequence(seqname='', number=0, selnum=0, fixed=0, nb_layers=-1, rx=0, ry=0, is_variable=False, bitpix=0, reference_image=0, imgparam=None, regparam=None, stats=None, distoparam=None, beg=0, end=0, exposure=0.0, fz=False, type=None, cfa_opened_monochrome=False, current=0)

Bases: object

Python equivalent of Siril sequ structure

beg: int = 0

imgparam[0]->filenum

bitpix: int = 0

image pixel format, from fits

cfa_opened_monochrome: bool = False

CFA SER opened in monochrome mode

current: int = 0

file number currently loaded

distoparam: List[DistoData] = None

distortion data for the sequence [nb_layers]

end: int = 0

imgparam[number-1]->filenum

exposure: float = 0.0

exposure of frames

fixed: int = 0

fixed length of image index in filename

fz: bool = False

whether the file is compressed

imgparam: List[ImgData] = None

a structure for each image of the sequence [number]

is_variable: bool = False

sequence has images of different sizes

nb_layers: int = -1

number of layers embedded in each image file

number: int = 0

number of images in the sequence

reference_image: int = 0

reference image for registration

regparam: List[List[RegData]] = None

registration parameters for each layer [nb_layers][number]

rx: int = 0

first image width

ry: int = 0

first image height

selnum: int = 0

number of selected images

seqname: str = ''

name of the sequence

stats: List[List[ImageStats]] = None

statistics of the images for each layer [nb_layers][number]

type: SequenceType = None

the type of sequence

Sirilpy Enums

This module provides all the enums that are used within sirilpy.

Enums submodule for Siril. This submodule contains all the enums used within sirilpy.

class sirilpy.enums.BitpixType(value)

Bases: IntEnum

Mimics the Siril bitpix enum. Note that although Siril can handle opening FITS files of any data type, internally it processes images only as USHORT_IMG (uint16) or FLOAT_IMG (float32).

BYTE_IMG = 8
DOUBLE_IMG = -64
FLOAT_IMG = -32
LONG_IMG = 32
SHORT_IMG = 16
USHORT_IMG = 20
class sirilpy.enums.CommandStatus(value)

Bases: IntEnum

Contains Siril command status codes, matching the values returned internally within Siril. These can be used for error handling. CMD_OK and CMD_NO_WAIT are no-error codes; all the other codes represent command errors. These are available through the CommandError exception and may generally be handled without being regarded as fatal to the script.

CMD_ALLOC_ERROR = 1048576
CMD_ARG_ERROR = 32
CMD_DIR_NOT_FOUND = 4194304
CMD_FILE_NOT_FOUND = 131072
CMD_FOR_CFA_IMAGE = 65536
CMD_FOR_PLATE_SOLVED = 262144
CMD_GENERIC_ERROR = 128
CMD_IMAGE_NOT_FOUND = 256
CMD_INVALID_IMAGE = 1024
CMD_LOAD_IMAGE_FIRST = 2048
CMD_NEED_INIT_FIRST = 524288
CMD_NOT_FOR_MONO = 16384
CMD_NOT_FOR_RGB = 32768
CMD_NOT_FOR_SINGLE = 8192
CMD_NOT_FOUND = 1
CMD_NOT_SCRIPTABLE = 8
CMD_NO_CWD = 4
CMD_NO_WAIT = 2
CMD_OK = 0
CMD_ONLY_SINGLE_IMAGE = 4096
CMD_SELECTION_ERROR = 64
CMD_SEQUENCE_NOT_FOUND = 512
CMD_THREAD_RUNNING = 2097152
CMD_WRONG_N_ARG = 16
class sirilpy.enums.DistoType(value)

Bases: IntEnum

Python equivalent of the Siril disto_source enum

DISTO_FILE = 2

Distortion from given file

DISTO_FILES = 4

Distortion stored in each file (true only from seq platesolve, even with no distortion, it will be checked upon reloading)

DISTO_FILE_COMET = 5

special for cometary alignement, to be detected by apply reg

DISTO_IMAGE = 1

Distortion from current image

DISTO_MASTER = 3

Distortion from master files

DISTO_UNDEF = 0

No distortion

class sirilpy.enums.LogColor(value)

Bases: IntEnum

Defines colors available for use with SirilInterface.log() For consistency LogColor.Default should be used for normal messages, LogColor.Red should be used for error messages, LogColor.Salmon should be used for warning messages, LogColor.Green should be used for completion notifications, and LogColor.Blue should be used for technical messages such as equations, coefficients etc.

BLUE = 4
DEFAULT = 0
GREEN = 3
RED = 1
SALMON = 2
class sirilpy.enums.PlotType(value)

Bases: IntEnum

Enumeration of available plot types for visualizing data series.

HYPHENS = 2
LINES = 3
LINESHYPHENS = 6
LINESMARKS = 5
LINESPOINTS = 4
MARKS = 1
POINTS = 0
class sirilpy.enums.SequenceType(value)

Bases: IntEnum

Python equivalent of the Siril sequence_type enum

SEQ_AVI = 3
SEQ_FITSEQ = 2
SEQ_INTERNAL = 4
SEQ_REGULAR = 0
SEQ_SER = 1
class sirilpy.enums.SirilVport

Bases: object

Defines the Siril viewports

BLUE = 2
GREEN = 1
MONO = 0
RED = 0
RGB = 3
class sirilpy.enums.StarProfile(value)

Bases: IntEnum

Python equivalent of the Siril starprofile enum. Used to identify the type of fit used to model a star in the image. Note that MOFFAT_FIXED is currently not used in Siril, but is reserved for future use for Moffat stars modelled with a fixed beta parameter

GAUSSIAN = 0
MOFFAT = 1
MOFFAT_FIXED = 2

Sirilpy Plotting

This submodule provides classes and method to access the native Siril plotting functionality. Of course, you can also use matplotlib but this submodule provides access to the same plotting capabilities as used internally within Siril for a more seamless result. All its members are made available at the module root level, there is no need to import models separately.

Once populated, the PlotData object can be plotted using SirilInterface.xy_plot().

Plot submodule for Siril, providing classes for plot data representation and serialization. This submodule enables users to create and configure various types of plots with customizable appearance and error bars.

class sirilpy.plot.PlotData(title='Data Plot', xlabel='X', ylabel='Y', savename='plot', show_legend=True, datamin=None, datamax=None)

Bases: object

Metadata container for plot configuration. The actual series data are held in SeriesData objects and can be added using the Class methods add_series or add_series_obj after initialization of the PlotData.

Members:

title: Plot title xlabel: X-axis label ylabel: Y-axis label savename: Save filename (extension is added automatically) show_legend: bool indicating whether to show legend datamin: List [xmin, ymin] forcing the bottom left coordinate to show. If omitted, the range is set to the data range. datamax: List [xmax, ymax] forcing the top right coordinate to show. If omitted, the range is set to the data range.

classmethod serialize(plot_data)

Serialize plot data for shared memory transfer using network byte order.

Parámetros:

plot_data (PlotData) -- PlotData object containing plot configuration

Tipo del valor devuelto:

Tuple[bytes, int]

Devuelve:

Tuple of serialized bytes and total length

add_series(x_coords, y_coords, label=None, plot_type=PlotType.LINES, n_error=None, p_error=None)

Add a new series to the plot metadata.

Devuelve:

the created SeriesData object for further manipulation if needed.

Tipo del valor devuelto:

SeriesData

add_series_obj(series)

Add a pre-created SeriesData object to the plot metadata.

Returns: None

Tipo del valor devuelto:

None

class sirilpy.plot.SeriesData(x_coords, y_coords, label=None, plot_type=PlotType.LINES, n_error=None, p_error=None)

Bases: object

Represents a single data series for plotting.

Members:

x_coords: Either a List[float] or a np.ndarray containing the values for the x coordinates for this series

y_coords: Either a List[float] or a np.ndarray containing the values for the y coordinates for this series

label: A str containing a label for the series (shown in the plot legend)

plot_type: a PlotType setting the type of marks to use

n_error: Either a List[float] or a np.ndarray containing values for the y-axis negative errors for this series

p_error: Either a List[float] or a np.ndarray containing values for the y-axis positive errors for this series

Sirilpy Utility Methods

This submodule provides utility methods for use in Siril python scripts. The most important is ensure_installed() but there are also methods such as download_with_progress() which provides a highly robust method for downloading large files with good error recovery through a retries and resume mechanism.

Utility module for Siril Python interface providing helper functions for file operations, package management, and standard I/O control to support Siril's scripting capabilities.

class sirilpy.utility.SuppressedStderr

Bases: object

This context manager allows suppression of the script's stderr, which can be useful if you are using module functions that are known to produce warnings that you want to avoid distracting the user with, such as FutureWarnings of features that have become deprecated but are in a dependency rather than your own code. The class should be used sparingly and should not be used to hide evidence of bad code.

class sirilpy.utility.SuppressedStdout

Bases: object

This context manager allows suppression of the script's stdout, which can be useful to avoid flooding the log with stdout messages from an excessively verbose module used in the script.

Ejemplo

import sirilpy as s
siril = s.SirilInterface()
print("This message will appear in the Siril log")
with s.SuppressedStdout():
    print("This message will not appear")
print("This message will appear again")
sirilpy.utility.check_module_version(requires=None)

Check the version of the Siril module is sufficient to support the script. This is not mandatory if you are only using classes, methods etc. that are provided in the initial public release, but if you rely on methods that are noted int he API documentation as having been added at a particular version of the module then you must check the running sirilpy module supports your script by calling this function.

Parámetros:

requires (str) -- A version format specifier string following the same format used by pip, i.e. it may contain '==1.2', '!=3.4', '>5.6', '>=7.8', or a combination such as '>=1.2,<3.4'

Devuelve:

True if requires = None or if the available sirilpy module version satisfies the version specifier, otherwise False

Muestra:

ValueError -- if requires is an invalid version specifier.

sirilpy.utility.download_with_progress(siril, url, file_path, max_retries=3, retry_delay=5, resume=True)

Robust file download method with native Siril progress tracking and error handling using retries and a resume mechanism.

Parámetros:

  • siril (SirilInterface) -- SirilInterface to use to update the progress bar

  • url (str) -- URL of the file to download

  • file_path (str) -- Local path to save the downloaded file

  • max_retries (int) -- Number of download retry attempts

  • retry_delay (int) -- Delay between retry attempts in seconds

  • resume (bool) -- Whether or not to resume a partially downloaded file or start again

Devuelve:

True if download successful, False otherwise

Tipo del valor devuelto:

bool

Muestra:

SirilError -- On unhandled errors

sirilpy.utility.ensure_installed(*packages, version_constraints=None)

Ensures that the specified package(s) are installed and meet optional version constraints.

Parámetros:

  • *packages (str or List[str]) -- Name(s) of the package(s) to ensure are installed.

  • version_constraints (str or List[str], optional) -- Version constraint string(s) (e.g. ">=1.5", "==2.0"). Can be a single constraint or a list matching packages.

Devuelve:

True if all packages are successfully installed or already meet constraints.

Tipo del valor devuelto:

bool

Muestra:

  • SirilError -- If package installation fails,

  • ValueError -- If a different number of constraints is provided to the number of packages to be installed.

  • TimeoutError -- If pip fails with an apparent timeout.

sirilpy.utility.human_readable_size(bytes_size)

Convert bytes to human-readable format.

Parámetros:

bytes_size (int) -- Size in bytes

Devuelve:

Formatted size with appropriate unit (B, KB, MB, GB, TB)

Tipo del valor devuelto:

str

Muestra:

TypeError -- on incorrect input type

sirilpy.utility.parse_fits_header(header_text)

Parse FITS header from text content into a dictionary

Parameters: header_text (str): Content of the FITS header text file

Returns: dict: Dictionary containing all header keywords and values

Tipo del valor devuelto:

dict

sirilpy.utility.truncate_utf8(data, max_bytes)

Truncates utf8 input. Accepts either bytes or str as input and returns data in the same format as the input.

Parámetros:

data (bytes or str) -- The data to be truncated

Devuelve:

The truncated data

Tipo del valor devuelto:

bytes or str

Muestra:

TypeError -- if the input was not bytes or str

Sirilpy GPU Helpers

This submodule provides helper classes to make it easier to manage GPU framework packages such as ONNX, Torch etc. for use in Siril python scripts. The landscape of these frameworks' support for different GPU architectures on different OSes is rapidly developing and the helpers aim to suggest reliable packages / configurations. This means that the proposed configurations may in some cases be conservative: the aim is to provide a good and robust level of GPU support for as many users as possible in an automated python environment rather than the absolute best, but perhaps fragile, optimisation.

GPU helper module for Siril Python interface providing helper functions for detection, installation and testing of GPU-related modules. Initial scope is ONNX, torch and jax

class sirilpy.gpuhelper.JaxHelper

Bases: object

A helper class for detecting, installing, and testing JAX with appropriate hardware acceleration.

This class automatically detects the system configuration and installs the correct JAX variant (CPU, CUDA, ROCm, etc.) based on available hardware.

ensure_jax()

Wrapper for install_jax() that only installs it if needed, with negligible overhead if it is already installed.

Tipo del valor devuelto:

bool

install_jax(force_variant=None, version_constraint=None)

Install JAX with the appropriate variant for the detected hardware. Use this instead of ensure_installed() to ensure that jax is installed correctly for the given hardware / OS

Parámetros:

  • force_variant (Optional[str]) -- Override auto-detection with specific variant (e.g., 'jax[cpu]')

  • version_constraint (Optional[str]) -- Version constraint string (e.g., '>=0.4.0')

Devuelve:

True if installation succeeded, False otherwise

Tipo del valor devuelto:

bool

is_jax_installed()

Check if PyTorch is installed without importing it.

Tipo del valor devuelto:

bool

status()

Prints the current status of the Jax Helper class in regard to its support for different OSes, GPUs. The world of heterogenous computing is developing rapidly and while support for some of the frameworks for which helpers are available is not yet universally available, hopefully it will improve in the future.

test_jax()

Test JAX functionality and return execution provider.

Devuelve:

the bool returned is True if jax works or False if it does not, and the str is "gpu" if JAX is using GPU, "cpu" if using CPU or None if

Tipo del valor devuelto:

Tuple[bool,str]

Muestra:

  • RuntimeError -- If JAX computation fails or accuracy check fails

  • ImportError -- If JAX is not installed

uninstall_jax(dry_run=False)

Detect and uninstall any existing JAX-related packages.

This is useful when you need to clean up a problematic JAX installation before installing a different variant (e.g., falling back from GPU to CPU).

Parámetros:

dry_run (bool) -- If True, only detect packages without uninstalling them

Tipo del valor devuelto:

Dict[str, Any]

Devuelve:

Dict containing information about detected and uninstalled packages

class sirilpy.gpuhelper.ONNXHelper

Bases: object

A class to handle detection and installation of the appropriate ONNX Runtime package based on the system hardware and configuration.

Example usage (this should be used instead of sirilpy.ensure_installed("onnxruntime") to install the correct package for the user's system.)

oh = sirilpy.ONNXHelper()
oh.ensure_onnxruntime()
ensure_onnxruntime()

Wrapper for install_onnxruntime() that only installs it if needed, with negligible overhead if it is already installed.

Tipo del valor devuelto:

bool

get_execution_providers_ordered(ai_gpu_acceleration=True)

Get execution providers ordered by priority. This function returns a list of available ONNX Runtime execution providers in a reasonable order of priority, covering major GPU platforms: The CPU provider is always included as the final fallback option. :type ai_gpu_acceleration: :param ai_gpu_acceleration: Whether to include GPU acceleration providers.

Defaults to True.

Devuelve:

Ordered list of available execution providers.

Tipo del valor devuelto:

list

install_onnxruntime()

Detect system configuration and install the appropriate ONNX Runtime package.

Devuelve:

True if installation was successful or already installed, False otherwise.

Tipo del valor devuelto:

bool

Muestra:

TimooutError -- if a TimeoutError occurs in ensure_installed() - this avoids falling back to the CPU-only package purely because of network issues

is_onnxruntime_installed()

Check if any onnxruntime package is already installed and usable.

Devuelve:

(is_installed, package_name) where package_name could be

'onnxruntime', 'onnxruntime-gpu', 'onnxruntime-silicon', etc.

Tipo del valor devuelto:

tuple

run(session, model_path, output_names, input_feed, run_options=None, return_first_output=False)

Run inference with automatic CPU fallback if the session fails.

Parámetros:

  • session -- The ONNX runtime inference session

  • model_path (str) -- Path to the ONNX model file (needed for CPU fallback)

  • output_names -- Names of the outputs to compute, or None for all outputs

  • input_feed -- Dictionary mapping input names to input tensors

  • run_options -- Optional run options for the inference session

  • return_first_output (bool) -- If True, return only the first output instead of the full list

Devuelve:

(result, session) where result is the inference output (or first output if return_first_output=True) and

session is the (potentially updated) inference session

Tipo del valor devuelto:

tuple

status()

Prints the current status of the ONNX Helper class in regard to its support for different OSes, GPUs. The world of heterogenous computing is developing rapidly and while support for some of the frameworks for which helpers are available is not yet universally available, hopefully it will improve in the future.

test_onnxruntime(ort=None)

Test an imported onnxruntime. Args:install_torch(cuda_version=cuda_version)

ort: The ONNX runtime module to test. If None, the method will attempt to import onnxruntime for the test.

Devuelve:

a list of confirmed working ONNXRuntime ExecutionProviders in priority order

Tipo del valor devuelto:

list

uninstall_onnxruntime()

Detects and uninstalls all variants of onnxruntime packages. Checks for any package starting with 'onnxruntime'.

Devuelve:

A list of uninstalled packages

Tipo del valor devuelto:

list

class sirilpy.gpuhelper.TorchHelper

Bases: object

Helper class for PyTorch detection, installation and testing.

ensure_torch()

Wrapper for install_torch() that only installs it if needed, with negligible overhead if it is already installed.

Tipo del valor devuelto:

bool

install_torch(cuda_version='auto', force_reinstall=False)

Install PyTorch with GPU compute platform support where available and stable. Use this in place of ensure_installed() to make sure that the correct Torch package is installed for the user's hardware and OS.

Parámetros:

  • cuda_version (str) -- compute platform to install (e.g., 'cu118', 'cu126', 'cu128', 'rocm', 'cpu', 'auto')

  • force_reinstall (bool) -- Whether to reinstall even if already installed

Devuelve:

True if installation successful, False otherwise

Tipo del valor devuelto:

bool

is_torch_installed()

Check if PyTorch is installed without importing it.

Tipo del valor devuelto:

bool

status()

Prints the current status of the Torch Helper class in regard to its support for different OSes, GPUs. The world of heterogenous computing is developing rapidly and while support for some of the frameworks for which helpers are available is not yet universally available, hopefully it will improve in the future.

test_torch()

Run tests to verify that torch is installed and runs correctly.

uninstall_torch()

Detects and uninstalls PyTorch and related packages. Checks for torch ecosystem packages. :returns: A list of uninstalled packages :rtype: list

Sirilpy TK GUI

This submodule provides some helper functions to support consistent GUI implementation using tkinter. It must be explicitly imported in order to be used. Note that when writing TKinter GUIs you should import ThemedTK from the ttkthemes module, because the bare TKinter UI shows up poorly on MacOS. ThemedTK and the methods available in the tksiril module help to provide a consistent look for Siril script GUIs on all platforms.

Advertencia

Linux users running a Wayland desktop should note that Tkinter does not yet have support for pure Wayland. In order to use python scripts utilising Tkinter GUIs you must have the XWayland compatibility package installed. If you don't, you will see errors about DISPLAY being unavailable.

from sirilpy import tksiril

TKsiril submodule for Siril, providing utility methods to achieve consistent script GUI appearance using the TKinter toolkit.

class sirilpy.tksiril.ScrollableFrame(container, *args, **kwargs)

Bases: Frame

A scrollable frame widget that can contain other widgets.

This class creates a frame with vertical scrolling capability using a Canvas widget and Scrollbar. It supports both scrollbar and mouse wheel scrolling across all platforms (Windows, Mac, Linux).

Usage:

scrollable = ScrollableFrame(parent) scrollable.pack(fill="both", expand=True)

# Add widgets to scrollable.scrollable_frame label = ttk.Label(scrollable.scrollable_frame, text="Hello") label.pack()

# Optionally bind mouse wheel to child widgets scrollable.add_mousewheel_binding(label)

add_mousewheel_binding(widget=None)

Add mouse wheel scrolling support to a widget and its children.

This method recursively binds mouse wheel events to the specified widget and all its child widgets. It uses platform detection to apply the appropriate event bindings for each operating system.

Parámetros:

widget -- The tkinter widget to bind mouse wheel events to. The binding will be applied recursively to all children. If no widget is specified it will default to the ScrollableFrame itself.

Ejemplo

# Add a complex widget to the scrollable frame frame = ttk.Frame(scrollable.scrollable_frame) label = ttk.Label(frame, text="Hello") button = ttk.Button(frame, text="Click me")

# Bind mouse wheel to the entire widget hierarchy scrollable.add_mousewheel_binding(frame)

sirilpy.tksiril.create_tooltip(widget, text, wrap_length=250)

Create a tooltip for a given Tkinter widget.

Parámetros:

  • widget (tk.Widget) -- The widget to attach the tooltip to

  • text (str) -- The tooltip text to display

  • max_width (int, optional) -- Maximum width of the tooltip. Defaults to 300.

  • wrap_length (int, optional) -- Length at which text wraps. Defaults to 250.

Muestra:

TypeError -- If text is not a string or the provided widget is not a valid Tkinter widget

sirilpy.tksiril.elevate(root)

Raises the Tk root window to the top of the window stack. Useful after calls to sirilpy methods that present child windows of the main Siril window such as info_messagebox().

NOTE: For this to work on KDE desktops, focus-stealing prevention must be disabled.

sirilpy.tksiril.match_theme_to_siril(themed_tk, s, on_top=False)

Match the Tkinter theme to the Siril configuration and set the script dialog to have topmost status, meaning that it will remain in front of other non-topmost windows.

Parámetros:

  • s (SirilInterface) -- sirilpy.SirilInterface class to provide the Siril theme (light or dark) to match

  • themed_tk (ThemedTk) -- ThemedTk instance to apply the theme to

  • on_top -- whether the script window should be always on top of other windows

Muestra:

  • TypeError -- If input arguments are of incorrect type

  • ValueError -- If the theme configuration is not 0 or 1

  • AttributeError -- If required methods are not available

  • RuntimeError -- If there are errors installing or setting the theme

sirilpy.tksiril.standard_style()

Provide a standardised ttk style to allow consistent visual appearance between different Siril python scripts.

Parámetros:

none

Muestra:

SirilError -- If the style creation or configuration fails

Sirilpy Tkfilebrowser

This submodule is a fork of tkfilebrowser. The fork addresses a bug in the original code where duplicate device entries could cause errors in generating the filebrowser, and ensures the code can be mantained as the upstream package was last updated several years ago.

Documentation for tkfilebrowser can be found here. Note that some compatibility improvements have been made in the version included in sirilpy:

  • sirilpy.tkfilebrowser.askdirectory() has been added as an alias for tkfilebrowser.askopendirname() to maintain compatibility with tk.filedialog.askdirectory().

  • In filefilter specifications tkfilebrowser requires multiple extensions to be provided separated by | whereas filedialog requires space-separated extensions: sirilpy.tkfilebrowser has been adapted to accept either format.

This submodule serves the sole purpose of being a drop-in replacement for the standard Tk filedialog on Linux, as the standard Tk filedialog is horrible on Linux. It can be used as a replacement like this:

if sys.platform.startswith("linux"):
    import sirilpy.tkfilebrowser as filedialog
else:
    from tkinter import filedialog

Sirilpy Exceptions

This submodule provides some customized exceptions to support Siril-specific error handling. All its members are made available at the module root level, there is no need to import it separately.

The sirilpy exceptions policy is as follows:

  • At a low level within sirilpy methods a variety of exception types may be raised (those shown below as well as exceptions raised from other modules such as struct.error). Internal exception types are all descended from SirilError and may therefore be caught using except SirilError. Other exception types are re-raised as a SirilError to show the method where they were generated, but the underlying error can still be seen either in a traceback or using the Exception __cause__ property.

  • Some error types are recoverable errors such as NoImageError, NoSequenceError and CommandError. These exception types can be handled at script level (for example by showing a warning dialog reminding the user to load an image).

  • Other error types are typically not recoverable, such as SharedMemoryError or SirilConnectionError.

Exceptions submodule for Siril, providing exception classes for use in exception raising within the sirilpy module.

exception sirilpy.exceptions.CommandError(message='Command execution failed', status_code=CommandStatus.CMD_GENERIC_ERROR)

Bases: SirilError

Raised when a command sent to Siril fails to execute properly. (Note: 'command' in this case refers to internal commands sent from the python module to the Siril python handler, not Siril commands of the type that might be entered in the Siril command entry.) The full set of command status codes is shown in the CommandStatus enum. These exceptions are often recoverable and should therefore be handled before generically handling other SirilError types that are considered fatal.

status_code

(CommandStatus) Indicates the status code returned by the Siril command. This may be used in error handlers to allow scripts to handle some types of command error and continue (e.g. by prompting a user intervention).

exception sirilpy.exceptions.DataError(message='Error handling data')

Bases: SirilError

Raised when there are problems with data handling. This includes cases like:

  • Invalid image data

  • Data conversion errors

  • Memory allocation failures

  • Buffer overflows

exception sirilpy.exceptions.ImageDialogOpenError(message='Siril image dialog is open')

Bases: SirilError

Exception raised when an image processing dialog is open.

exception sirilpy.exceptions.MouseModeError(message='Siril mouse mode error')

Bases: SirilError

Exception raised when Siril is in the wrong mouse mode.

exception sirilpy.exceptions.NoImageError(message='No Siril image loaded')

Bases: SirilError

Raised when a method requires an image to be loaded but no image is loaded. These exceptions are often recoverable and should therefore be handled before generically handling other SirilError types that are considered fatal.

exception sirilpy.exceptions.NoSequenceError(message='No Siril sequence loaded')

Bases: SirilError

Raised when a method requires a sequence to be loaded but no sequence is loaded. These exceptions are often recoverable and should therefore be handled before generically handling other SirilError types that are considered fatal.

exception sirilpy.exceptions.ProcessingThreadBusyError(message='Siril processing thread is busy')

Bases: SirilError

Exception raised when the processing thread is already in use.

exception sirilpy.exceptions.SharedMemoryError(message='Siril shared memory error')

Bases: SirilError

Raised when there are problems connecting to or communicating with Siril using shared memory.

SharedMemoryError is not raised directly but will be wrapped in a SirilError. It should generally be regarded as fatal and the script should shut down gracefully if possible or just stop.

exception sirilpy.exceptions.SirilConnectionError(message='Failed to connect to Siril')

Bases: SirilError

Raised when there are problems connecting to or communicating with Siril. This includes cases like:

  • Siril not running

  • Socket connection failures

  • Communication protocol errors

  • Unexpected disconnections

SirilConnectionError is not raised directly but will be wrapped in a SirilError. It should generally be regarded as fatal and the script should shut down gracefully if possible or just stop.

exception sirilpy.exceptions.SirilError(message='An error occurred')

Bases: Exception

Base exception class for all Siril-related errors.

All other Siril exceptions inherit from this class, making it easy to catch any Siril-related error with a single except clause.