Norman is a framework for advanced data structures in python using an database-like approach. The range of potential applications is wide, for example in-memory databases, multi-keyed dictionaries or node graphs.
Norman provides a framework for creating complex data structures using an database-like approach. The range of potential application is wide, for example in-memory databases, multi-keyed dictionaries or node graphs. These applications are illustrated in the following examples.
This is a small database for a personal library:
db = Database() @db.add class Book(Table): name = Field(unique=True) author = Field(index=True) def validate(self): assert isinstance(self.name, str) assert isinstance(self.author, Author) @db.add class Author(Table): surname = Field(unique=True) initials = Field(unique=True, default='') nationality = Field() books = Join(Book.author)
This table can be used as a dictionary with three keys:
class MultiDict(Table): key1 = Field(unique=True) key2 = Field(unique=True) key3 = Field(unique=True) value = Field()
Values can be added by:
MultiDict(key1=4, key2='abc', key3=0, value='efg')
And queried by:
for m in (MultiDict.key1 == 4 & Multidict.key2 == 'abc'): print(m.value)
This is a graph, where each node can have many parent nodes and many children nodes:
class Link(Table): """ Directional connections between nodes. """ parent = Field(unique=True) child = Field(unique=True) def validate(self): assert isinstance(self.parent, Node) assert isinstance(self.child, Node) class Node(Table): """ Nodes in the graph. """ parents = Join(query=lambda n: (Link.child == n).field('parent')) children = Join(query=lambda n: (Link.parent == n).field('child')) def validate_delete(self): # Delete all connecting links if a node is deleted (Link.parent == self).delete() (Link.child == self).delete()
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