syndirella.slipper.Slipper
==========================

.. py:module:: syndirella.slipper.Slipper

.. autoapi-nested-parse::

   syndirella.slipper.Slipper.py

   This module contains the Slipper class. A slipper in this metaphor is the set of molecules that is the
   scaffold of a reaction.



Classes
-------

.. autoapisummary::

   syndirella.slipper.Slipper.Slipper


Module Contents
---------------

.. py:class:: Slipper(*, library: syndirella.route.Library.Library, template: str = None, hits_path: str = None, hits_names: List[str] = None, batch_num: int = None, atoms_ids_expansion: dict = None, additional_info: dict = None, scaffold_placements: Dict[rdkit.Chem.Mol, str | None] = None)

   This class is instantiated to represent all products for a step in a route.


   .. py:attribute:: products
      :type:  pandas.DataFrame
      :value: None



   .. py:attribute:: library
      :type:  syndirella.route.Library.Library


   .. py:attribute:: route_uuid
      :type:  str


   .. py:attribute:: output_dir
      :type:  str


   .. py:attribute:: final_products_pkl_path
      :type:  str
      :value: None



   .. py:attribute:: final_products_csv_path
      :type:  str
      :value: None



   .. py:attribute:: scaffold_placements
      :type:  Dict[rdkit.Chem.Mol, str | None]
      :value: None



   .. py:attribute:: template
      :type:  str
      :value: None



   .. py:attribute:: hits_path
      :type:  str
      :value: None



   .. py:attribute:: hits_names
      :type:  List[str]
      :value: None



   .. py:attribute:: batch_num
      :type:  int
      :value: None



   .. py:attribute:: atoms_ids_expansion
      :type:  dict
      :value: None



   .. py:attribute:: placements
      :type:  pandas.DataFrame
      :value: None



   .. py:attribute:: output_path
      :type:  str
      :value: None



   .. py:attribute:: additional_info
      :type:  dict
      :value: None



   .. py:attribute:: logger


   .. py:attribute:: num_placed
      :type:  int | None
      :value: None



   .. py:attribute:: num_successful
      :type:  int | None
      :value: None



   .. py:attribute:: to_hippo_path
      :type:  str | None
      :value: None



   .. py:attribute:: num_unique_products
      :type:  int | None
      :value: None



   .. py:attribute:: num_products_enumstereo
      :type:  int | None
      :value: None



   .. py:method:: get_products() -> pd.DataFrame and str

      Main entry to the Slipper class. This function is used to get the products the self.library object.



   .. py:method:: place_products()

      This function is used to place the products with Fragmenstein.



   .. py:method:: write_products_to_hippo() -> str

      Writes a dataframe that contains the values needed for HIPPO db input.

      :returns: str : the path to the saved dataframe
      :rtype: path



   .. py:method:: check_scaffold_in_hippo(hippo_df: pandas.DataFrame, hippo_path: str)

      Checks if there is a scaffold in the scaffold names of the HIPPO output.



   .. py:method:: _load_products_dfs(products_files: List[str]) -> Dict[int, pandas.DataFrame]

      Load the products dataframes from the files in the /extra directory and putting into dict where key is step.



   .. py:method:: _structure_products_for_hippo(placements_df: pandas.DataFrame, product_dfs: Dict[int, pandas.DataFrame]) -> pandas.DataFrame

      Structures the placements or products df for HIPPO output.



   .. py:method:: calculate_inchi_similarity(smiles1: str, smiles2: str) -> int


   .. py:method:: find_matches(row, step, df_previous_step: pandas.DataFrame) -> List[str]


   .. py:method:: _put_hippo_dfs_together(hippo_dfs: Dict[int, pandas.DataFrame]) -> pandas.DataFrame

      Puts the HIPPO dataframes together by matching on each reaction scaffold to the correct previous step's reactant.



   .. py:method:: _structure_step_for_hippo(step: int, products_df: pandas.DataFrame) -> pandas.DataFrame

      Structures the products df for HIPPO output.



   .. py:method:: which_reactant_was_previous_product(r1_is_previous_product: bool, r2_is_previous_product: bool) -> int | None

      Determine which reactant was the scaffold of the previous step.



   .. py:method:: _delete_file_or_directory(path)

      Delete a file or directory at the given path.



   .. py:method:: _should_delete_file(file, suffixes_to_keep)

      Determine if a file should be deleted based on its suffix.



   .. py:method:: clean_up_placements()

      This function is used to remove extra files that are generated by Fragmenstein.



   .. py:method:: get_placements_df() -> pandas.DataFrame | None

      This function is used to get the placements dataframe which is the merged df with the products.