bw2data.backends.peewee.database
#
Module Contents#
Classes#
A base class for LCI backends. |
Attributes#
- class bw2data.backends.peewee.database.SQLiteBackend(*args, **kwargs)[source]#
Bases:
bw2data.backends.base.LCIBackend
A base class for LCI backends.
Subclasses must support at least the following calls:
load()
write(data)
In addition, they should specify their backend with the
backend
attribute (a unicode string).LCIBackend
provides the following, which should not need to be modified:rename
copy
find_dependents
random
process
For new classes to be recognized by the
DatabaseChooser
, they need to be registered with theconfig
object, e.g.:config.backends['backend type string'] = BackendClass
Instantiation does not load any data. If this database is not yet registered in the metadata store, a warning is written to
stdout
.The data schema for databases in voluptuous is:
exchange = { Required("input"): valid_tuple, Required("type"): basestring, } exchange.update(uncertainty_dict) lci_dataset = { Optional("categories"): Any(list, tuple), Optional("location"): object, Optional("unit"): basestring, Optional("name"): basestring, Optional("type"): basestring, Optional("exchanges"): [exchange] } db_validator = Schema({valid_tuple: lci_dataset}, extra=True)
- where:
valid_tuple
is a dataset identifier, like("ecoinvent", "super strong steel")
uncertainty_fields
are fields from an uncertainty dictionary.
Processing a Database actually produces two parameter arrays: one for the exchanges, which make up the technosphere and biosphere matrices, and a geomapping array which links activities to locations.
- Parameters
*name* (unicode string) – Name of the database to manage.
- load(*args, **kwargs)[source]#
Load the intermediate data for this database.
If
load()
does not return a dictionary, then the returned object must have at least the following dictionary-like methods:__iter__
__contains__
__getitem__
__setitem__
__delitem__
__len__
keys()
values()
items()
items()
However, this method must support the keyword argument
as_dict
, and.load(as_dict=True)
must return a normal dictionary with all Database data. This is necessary for JSON serialization.It is recommended to subclass
collections.{abc.}MutableMapping
(seeSynchronousJSONDict
for an example of data loaded on demand).
- process()[source]#
Process inventory documents to NumPy structured arrays.
Use a raw SQLite3 cursor instead of Peewee for a ~2 times speed advantage.
- random(filters=True, true_random=False)[source]#
True random requires loading and sorting data in SQLite, and can be resource-intensive.
- search(string, **kwargs)[source]#
Search this database for
string
.The searcher include the following fields:
name
comment
categories
location
reference product
string
can include wild cards, e.g."trans*"
.By default, the
name
field is given the most weight. The full weighting set is called theboost
dictionary, and the default weights are:{ "name": 5, "comment": 1, "product": 3, "categories": 2, "location": 3 }
Optional keyword arguments:
limit
: Number of results to return.boosts
: Dictionary of field names and numeric boosts - see default boost values above. New values must be in the same format, but with different weights.filter
: Dictionary of criteria that search results must meet, e.g.{'categories': 'air'}
. Keys must be one of the above fields.mask
: Dictionary of criteria that exclude search results. Same format asfilter
.facet
: Field to facet results. Must be one ofname
,product
,categories
,location
, ordatabase
.proxy
: ReturnActivity
proxies instead of raw Whoosh documents. Default isTrue
.
Returns a list of
Activity
datasets.