text content of the tweet, when it was created, and who posted it (foreign key to User). If you like UML, these are the tables and relationships: In order to create these models we need to instantiate a peewee will de-dupe it and aggregate the tweets as it iterates through the result set. This method involves a lot of data being transferred over the wire and a lot of logic in Python to de-duplicate rows transferred over the wire since data is not duplicated. There is less Python overhead since we don’t have to de-dupe things. LIMIT works as you’d expect on the outer-most query, but may be difficult to implement

text content of the tweet, when it was created, and who posted it (foreign key to User). If you like UML, these are the tables and relationships: In order to create these models we need to instantiate a peewee will de-dupe it and aggregate the tweets as it iterates through the result set. This method involves a lot of data being transferred over the wire and a lot of logic in Python to de-duplicate rows over the wire since data is not duplicated. • There is less Python overhead since we don’t have to de-dupe things. • LIMIT works as you’d expect on the outer-most query, but may be difficult to implement

content of the message, when it was created, and who posted it (foreign key to User). If you like UML, this is basically what it looks like: Here is what the code looks like: database = SqliteDatabase(DATABASE)

content of the message, when it was created, and who posted it (foreign key to User). If you like UML, this is basically what it looks like: Here is what the code looks like: database = SqliteDatabase(DATABASE)

content of the message, when it was created, and who posted it (foreign key to User). If you like UML, this is basically what it looks like: 1.5. Example app 19 peewee Documentation, Release 2.0.0 Here

all the various components in the system.  Managing a connection to a database. Here is the UML diagram, class Logger(object): def __new__(cls, *args, **kwargs):

content of the message, when it was created, and who posted it (foreign key to User). If you like UML, this is basically what it looks like: Here is what the code looks like: database = SqliteDatabase(DATABASE)

posted it (foreign key to User). 1.4. Example app 15 peewee Documentation, Release 1.0.0 If you like UML, this is basically what it looks like: Here is what the code looks like: database = SqliteDatabase(DATABASE)

text content of the tweet, when it was created, and who posted it (foreign key to User). If you like UML, these are the tables and relationships: 12 Chapter 1. Contents: peewee Documentation, Release 3 through_model The Model representing the many-to-many junction table. Will be auto-generated if not explicitly de- clared. add(value[, clear_existing=True]) Parameters • value – Either a Model instance, a list indexes=None[, primary_key=None[, constraints=None[, schema=None[, only_save_dirty=False[, table_alias=None[, de- pends_on=None[, options=None[, without_rowid=False[, **kwargs]]]]]]]]]]] ]) Parameters • model (Model)

text content of the tweet, when it was created, and who posted it (foreign key to User). If you like UML, these are the tables and relationships: 12 Chapter 1. Contents: peewee Documentation, Release 3 has been removed. Additionally, Select.aggregate_rows() has been removed. This helper was used to de-duplicate left-join queries to give the appearance of efficiency when iterating a model and its relations through_model The Model representing the many-to-many junction table. Will be auto-generated if not explicitly de- clared. add(value[, clear_existing=True]) Parameters • value – Either a Model instance, a list