We are using sqlalchemy's autoload feature to do column mapping to prevent hardcoding in our code.
class users(Base):
__tablename__ = 'users'
__table_args__ = {
'autoload': True,
'mysql_engine': 'InnoDB',
'mysql_charset': 'utf8'
}
Is there a way to serialize or cache autoloaded metadata/orms so we don't have to go through the autoload process every time we need to reference our orm classes from other scripts/functions?
I have looked at beaker caching and pickle but haven't found a clear answer if it is possible or how to do it.
Ideally we run the autload mapping script only when we have committed changes to our database structure but reference a non-autoload/persistent/cached version of our database mapping from all other scripts/functions,
Any ideas?
What I am doing now is to pickle the metadata after running the reflection through a database connection (MySQL) and once a pickle is available use that pickled metadata to reflect on the schema with the metadata bound to an SQLite engine.
cachefile='orm.p'
dbfile='database'
engine_dev = create_engine(#db connect, echo=True)
engine_meta = create_engine('sqlite:///%s' % dbfile,echo=True)
Base = declarative_base()
Base.metadata.bind = engine_dev
metadata = MetaData(bind=engine_dev)
# load from pickle
try:
with open(cachefile, 'r') as cache:
metadata2 = pickle.load(cache)
metadata2.bind = engine_meta
cache.close()
class Users(Base):
__table__ = Table('users', metadata2, autoload=True)
print "ORM loaded from pickle"
# if no pickle, use reflect through database connection
except:
class Users(Base):
__table__ = Table('users', metadata, autoload=True)
print "ORM through database autoload"
# create metapickle
metadata.create_all()
with open(cachefile, 'w') as cache:
pickle.dump(metadata, cache)
cache.close()
Any comments if this is alright (it works) or there is something I can improve?
My solution isn't terribly different from @user1572502's, but might be useful. I place my cached metadata files in ~/.sqlalchemy_cache
, but they can be anywhere.
# assuming something like this:
Base = declarative_base(bind=engine)
metadata_pickle_filename = "mydb_metadata_cache.pickle"
# ------------------------------------------
# Load the cached metadata if it's available
# ------------------------------------------
# NOTE: delete the cached file if the database schema changes!!
cache_path = os.path.join(os.path.expanduser("~"), ".sqlalchemy_cache")
cached_metadata = None
if os.path.exists(cache_path):
try:
with open(os.path.join(cache_path, metadata_pickle_filename), 'rb') as cache_file:
cached_metadata = pickle.load(file=cache_file)
except IOError:
# cache file not found - no problem
pass
# ------------------------------------------
# -----------------------------
# Define database table classes
# -----------------------------
class MyTable(Base):
if cached_metadata:
__table__ = cached_metadata.tables['my_schema.my_table']
else:
__tablename__ = 'my_table'
__table_args__ = {'autoload':True, 'schema':'my_schema'}
# ... continue for any other tables ...
# ----------------------------------------
# If no cached metadata was found, save it
# ----------------------------------------
if cached_metadata is None:
# cache the metadata for future loading
# - MUST DELETE IF THE DATABASE SCHEMA HAS CHANGED
try:
if not os.path.exists(cache_path):
os.makedirs(cache_path)
# make sure to open in binary mode - we're writing bytes, not str
with open(os.path.join(cache_path, metadata_pickle_filename), 'wb') as cache_file:
pickle.dump(Base.metadata, cache_file)
except:
# couldn't write the file for some reason
pass
Important Note!! If the database schema changes, you must delete the cached file to force the code to autoload and create a new cache. If you don't, the changes will be be reflected in the code. It's an easy thing to forget.
来源:https://stackoverflow.com/questions/11785457/sqlalchemy-autoloaded-orm-persistence