mescal.database

Classes

Database	Class to perform basic operations on LCI databases. Databases can be formulated as a list of dictionaries or as a
Dataset	Class to perform basic operations on LCI datasets (as dictionaries)

Module Contents

class mescal.database.Database(db_names: str | list[str] = None, db_as_list: list[dict] = None, create_pickle: bool = False, load_dependencies: bool = False)

Class to perform basic operations on LCI databases. Databases can be formulated as a list of dictionaries or as a dictionary with the (database, code) tuple or the (name, product, location, database) tuple as key.

Initialize the database

Parameters:

• db_names (str | list[str]) – Name of the LCI database(s). Should be a string for a single database or a list of strings for several databases.

• db_as_list (list[dict]) – List of dictionaries of the LCI database.

• create_pickle (bool) – if True, create a pickle file to store the database. Only used if db_names is provided.

• load_dependencies (bool) – if True, load the dependencies of the database(s). Only used if db_names is provided.

change_name(new_db_name: str, database_type: str = 'technosphere') → None

Change the name of the database

Parameters:

• new_db_name (str) – new name of the database

• database_type (str) – type of database to be written, can be ‘technosphere’ or ‘biosphere’

Returns:

None

Return type:

None

create_complementary_database(df_mapping: pandas.DataFrame, main_db_name: str = None, complement_db_name: str = None, premise_changes: pandas.DataFrame = None, write_database: bool = True) → pandas.DataFrame

Create a new database containing all activities that tare not provided in your main database

Parameters:

• df_mapping (pandas.DataFrame) – dataframe with the mapping of the technologies and resources

• main_db_name (str) – name of the main LCI database

• complement_db_name (str) – name of the complementary LCI database

• premise_changes (pandas.DataFrame) – file of the changes in names, products, locations, in premise regarding the mapping

• write_database (bool) – if True, write the complementary database to Brightway

Returns:

dataframe with the mapping of the technologies and resources linked to the premise database

Return type:

pandas.DataFrame

delete() → None

Delete a database from Brightway

Returns:

None

Return type:

None

dependencies() → list[str]

Get the dependencies of the database

Returns:

list of dependencies

Return type:

list[str]

get_code(product: str, activity: str, location: str, database: str) → str or None

Get the code of an activity

Parameters:

• product (str) – product of the LCI dataset

• activity (str) – name of the LCI dataset

• location (str) – location of the LCI dataset

• database (str) – name of the LCI database

Returns:

activity code in the LCI database or None if it does not exist

Return type:

str or None

list_to_dict(key: str, database_type: str = 'technosphere') → dict

Converts a list of dictionaries into a dictionary with the (database, code) tuple as key when key = ‘code’, the (name, product, location, database) tuple as key when key = ‘name’ for a technosphere database, or the (name, categories, database) tuple as key when key = ‘name’ for a biosphere database.

Parameters:

• key (str) – can be ‘code’ or ‘name’

• database_type (str) – can be ‘technosphere’ or ‘biosphere’

Returns:

LCI database as a dictionary

Return type:

dict

load() → list[dict]

Load or extract a single database

Returns:

list of dictionaries of the LCI database

Return type:

list[dict]

load_multiple() → list[dict]

Concatenates databases in a list of dictionaries

Returns:

list of dictionaries of the concatenated databases

Return type:

list[dict]

merge(main_ecoinvent_db_name: str, new_db_name: str = None, old_main_db_names: list[str] or None = None, write: bool = False, check_duplicates: bool = False, based_on: str = 'code') → None

Merge multiple LCI databases in one database. The list of databases should contain one main database (e.g., an ecoinvent or premise database) towards which all other databases will be relinked. If you suspect that there might be duplicated LCI datasets over the different databases, you can set check_duplicates to True to remove them.

Parameters:

• main_ecoinvent_db_name (str) – name of the main database, e.g., ecoinvent or premise database

• new_db_name (str) – name of the new merged database (only required if write is True)

• old_main_db_names (list[str] or None) – other main databases that are not in the list of databases, thus the list of databases will be unlinked from those

• write (bool) – if True, write the new database to Brightway

• check_duplicates (bool) – if True, check for duplicates in terms of (product, name, location) and remove them from exchanges and from the database

• based_on (str) – can be ‘code’ or ‘name’. Useful in case of background databases being different from main_ecoinvent_db_name. If ‘code’, the relinking is done based on the code of the activities, if ‘name’, the relinking is done based on the name, product, location and database of the activities.

Returns:

None

Return type:

None

relink(name_database_unlink: str, name_database_relink: str = None, database_relink_as_list: list[dict] = None, name_new_db: str = None, based_on: str = 'code', write: bool = False) → None

Relink a database based on activity codes or activity names and write it to your brightway project

Parameters:

• name_database_unlink (str) – name of the database to unlink

• name_database_relink (str) – name of the database to relink

• database_relink_as_list (list[dict]) – list of dictionaries of the database to relink

• name_new_db (str) – name of the new database, if None, the original database is overwritten (if write is True)

• based_on (str) – can be ‘code’ or ‘name’, if ‘code’, the relinking is done based on the code of the activities, if ‘name’, the relinking is done based on the name, product, location and database of the activities.

• write (bool) – if True, write the new database to Brightway

Returns:

None

Return type:

None

static relink_complement_db_to_premise_db(name_complement_db: str, base_db_list: list[dict], premise_db_list: list[dict], name_premise_db: str) → tuple[list[dict], list[dict]]

Relink the activities in the complementary database to the premise database

Parameters:

• name_complement_db (str) – name of the complementary database

• base_db_list (list[dict]) – list of activities in the base database

• premise_db_list (list[dict]) – list of activities in the premise database

• name_premise_db (str) – name of the premise database

Returns:

list of unlinked flows, updated premise database

Return type:

tuple[list[dict], list[dict]]

test_mapping_file(mapping: pandas.DataFrame) → list[tuple[str, str, str, str]]

Test if the mapping file is correctly linked to the database

Parameters:

mapping (pandas.DataFrame) – mapping file between the LCI database and the ESM database

Returns:

the list missing flows if any

Return type:

list[tuple[str, str, str, str]]

write_to_brightway(new_db_name: str, database_type: str = 'technosphere', overwrite: bool = True) → None

Write a LCI database to a Brightway project. This function will overwrite the database if it already exists.

Parameters:

• new_db_name (str) – name of the brightway database to be written

• database_type (str) – type of database to be written, can be ‘technosphere’ or ‘biosphere’

• overwrite (bool) – if True, overwrite the database if it already exists

Returns:

None

Return type:

None

wurst_to_brightway(database_type: str = 'technosphere') → None

Adjust the database to the Brightway format

Parameters:

database_type (str) – type of database to be written, can be ‘technosphere’ or ‘biosphere’

Returns:

None

Return type:

None

create_pickle = False

property db_as_dict_code: dict

Return type:

dict

property db_as_dict_name: dict

Return type:

dict

logger

overwritten_cpc_categories = []

class mescal.database.Dataset(act: dict)

Class to perform basic operations on LCI datasets (as dictionaries)

Initialize the dataset

Parameters:

act (dict) – LCI dataset

get_biosphere_flows() → list[dict]

Get the biosphere flows of an activity

Returns:

list of biosphere flows

Return type:

list[dict]

get_downstream_consumers(db: list[dict]) → list[dict]

Get the downstream consumers of an activity

Parameters:

db (list[dict]) – list of activities of the LCI database

Returns:

list of downstream consumers

Return type:

list[dict]

get_production_flow() → dict or None

Get the production flow of an activity

Returns:

production flow or None if it does not exist

Return type:

dict or None

get_technosphere_flows() → list[dict]

Get the technosphere flows of an activity

Returns:

list of technosphere flows

Return type:

list[dict]

relink(name_database_unlink: str, name_database_relink: str = None, database_relink_as_list: list[dict] = None, except_units: list[str] = None) → None

Relink the exchanges of an activity from one database to another.

Parameters:

• name_database_unlink (str) – name of the database to unlink from

• name_database_relink (str) – name of the database to relink to. If None, the database name is taken from the database_relink_as_list parameter.

• database_relink_as_list (list[dict]) – list of dictionaries of the database to relink to. If None, the database name is taken from the name_database_relink parameter.

• except_units (list[str]) – list of units to exclude from the relinking. If None, all units are relinked.

Returns:

None

Return type:

None

act

activity

database

location

product