Hello, I used similar approach for not thousands, but for undreds of tables.
At first I created shared base class for all of them:
class TimeSeriesBase(Base):
__abstract__ = True
@declared_attr
def id(cls):
return Column('id', Integer, primary_key=True)
@declared_attr
def locid(cls):
return Column('loc_id', Integer, ForeignKey(Location.id),
primary_key=True)
# here put common stuff
Secondly, a little *type()* magic is needed:
series_tables = {}
def get_or_create_timeseries(name):
if name in series_tables:
return series_table[name]
class TimeSeriesMixin(object):
__tablename__ = name
# here put name-specific stuff
series_tables[name] = type(name + 'Model', ( TimeSeriesBase,
TimeSeriesMixin ), {})
return series_tables[name]
You can call the function any times and it will always return existing
class or create new class.
That should work.
P
Dne středa, 2. dubna 2014 0:56:54 UTC+2 Peter Stensmyr napsal(a):
>
> I posted this question on Stack Overflow a few days ago, and got some
> response but nothing that really solves my problem. I'm hoping that I can
> get some more input here. The initial recommendation was to keep all the
> data in two tables (one meta and one data table), but this might become
> unwieldy with the number of rows (I estimate it will be about 6 billion
> rows in total).
>
> I have many (~2000) locations with time series data. Each time series has
> millions of rows. I would like to store these in a Postgres database. My
> current approach is to have a table for each location time series, and a
> meta table which stores information about each location (coordinates,
> elevation etc). I am using SQLAlchemy to create and query the tables. I
> would like to have a relationship between the meta table and each time
> series table to do queries like "select all locations that have data
> between date A and date B" and "select all data for date A and export a csv
> with coordinates". What is the best way to create many tables with the same
> structure (only the name is different) and have a relationship with a meta
> table? Or should I use a different database design?
>
> Currently I am using this type of approach to generate a lot of similar
> mappings:
>
> from sqlalchemy import create_engine, MetaDatafrom sqlalchemy.types import
> Float, String, DateTime, Integerfrom sqlalchemy import Column, ForeignKeyfrom
> sqlalchemy.ext.declarative import declarative_basefrom sqlalchemy.orm import
> sessionmaker, relationship, backref
> Base = declarative_base()
>
> def make_timeseries(name):
> class TimeSeries(Base):
>
> __tablename__ = name
> table_name = Column(String(50), ForeignKey('locations.table_name'))
> datetime = Column(DateTime, primary_key=True)
> value = Column(Float)
>
> location = relationship('Location', backref=backref('timeseries',
> lazy='dynamic'))
>
> def __init__(self, table_name, datetime, value):
> self.table_name = table_name
> self.datetime = datetime
> self.value = value
>
> def __repr__(self):
> return "{}: {}".format(self.datetime, self.value)
>
> return TimeSeries
>
> class Location(Base):
>
> __tablename__ = 'locations'
> id = Column(Integer, primary_key=True)
> table_name = Column(String(50), unique=True)
> lon = Column(Float)
> lat = Column(Float)
> if __name__ == '__main__':
> connection_string = 'postgresql://user:pw@localhost/location_test'
> engine = create_engine(connection_string)
> metadata = MetaData(bind=engine)
> Session = sessionmaker(bind=engine)
> session = Session()
>
> TS1 = make_timeseries('ts1')
> # TS2 = make_timeseries('ts2') # this breaks because of the foreign key
> Base.metadata.create_all(engine)
> session.add(TS1("ts1", "2001-01-01", 999))
> session.add(TS1("ts1", "2001-01-02", -555))
>
> qs = session.query(Location).first()
> print qs.timeseries.all()
>
>
> This approach has some problems, most notably that if I create more than
> one TimeSeries object the foreign key doesn't work. Previously I've used
> some work-arounds (such as not defining a foreign key), but it all seems
> like a big hack and I feel that there must be a better way of doing this.
> How should I organise and access my data?
>
> Any advice appreciated,
>
> Peter
>
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