may need to break it up into chunks: # Insert rows 100 at a time. with db.atomic(): for idx in range(0, len(data_source), 100): MyModel.insert_many(data_source[idx:idx+100]).execute() If Model a_user_tweets = Tweet.select().where(Tweet.user.in_(a_users)) More query examples Note For a wide range of example queries, see the Query Examples document, which shows how to implements queries from the 31. 2. # 2 3. 34. 2. # 3 100 134. 100. Frame types: RANGE vs ROWS Depending on the frame type, the database will process ordered groups differently. Let’s

may need to break it up into chunks: # Insert rows 100 at a time. with db.atomic(): for idx in range(0, len(data_source), 100): MyModel.insert_many(data_source[idx:idx+100]).execute() If Model.insert_many() a_user_tweets = Tweet.select().where(Tweet.user.in_(a_users)) More query examples Note: For a wide range of example queries, see the Query Examples document, which shows how to implements queries from the # 1 10. 10. 15. # 1 20. 30. 15. # 2 1. 31. 2. # 2 3. 34. 2. # 3 100 134. 100. Frame types: RANGE vs ROWS Depending on the frame type, the database will process ordered groups differently. Let’s

may need to break it up into chunks: # Insert rows 100 at a time. with db.atomic(): for idx in range(0, len(data_source), 100): MyModel.insert_many(data_source[idx:idx+100]).execute() If Model a_user_tweets = Tweet.select().where(Tweet.user.in_(a_users)) More query examples Note For a wide range of example queries, see the Query Examples document, which shows how to implements queries from the multi-value INSERT statement (for example, using Model.insert_many()): with db.atomic(): for idx in range(0, len(row_data), 100): # Insert 100 rows at a time. rows = row_data[idx:idx + 100]

may need to break it up into chunks: # Insert rows 100 at a time. with db.atomic(): for idx in range(0, len(data_source), 100): MyModel.insert_many(data_source[idx:idx+100]).execute() If Model a_user_tweets = Tweet.select().where(Tweet.user.in_(a_users)) More query examples Note For a wide range of example queries, see the Query Examples document, which shows how to implements queries from the multi-value INSERT statement (for example, using Model.insert_many()): with db.atomic(): for idx in range(0, len(row_data), 100): # Insert 100 rows at a time. rows = row_data[idx:idx + 100]

may need to break it up into chunks: # Insert rows 100 at a time. with db.atomic(): for idx in range(0, len(data_source), 100): MyModel.insert_many(data_source[idx:idx+100]).execute() If Model.insert_many() More query examples 68 Chapter 1. Contents: peewee Documentation, Release 3.5.0 Note: For a wide range of example queries, see the Query Examples document, which shows how to implements queries from the multi-value INSERT statement (for example, using Model.insert_many()): with db.atomic(): for idx in range(0, len(row_data), 100): # Insert 100 rows at a time. rows = row_data[idx:idx + 100] User.insert_many(rows)

peewee Documentation, Release 3.3.0 # Insert rows 100 at a time. with db.atomic(): for idx in range(0, len(data_source), 100): MyModel.insert_many(data_source[idx:idx+100]).execute() If Model.insert_many() a_user_tweets = Tweet.select().where(Tweet.user.in_(a_users)) More query examples Note: For a wide range of example queries, see the Query Examples document, which shows how to implements queries from the multi-value INSERT statement (for example, using Model.insert_many()): with db.atomic(): for idx in range(0, len(row_data), 100): # Insert 100 rows at a time. rows = row_data[idx:idx + 100] User.insert_many(rows)

may need to break it up into chunks: # Insert rows 100 at a time. with db.atomic(): for idx in range(0, len(data_source), 100): MyModel.insert_many(data_source[idx:idx+100]).execute() If Model.insert_many() a_user_tweets = Tweet.select().where(Tweet.user.in_(a_users)) More query examples Note: For a wide range of example queries, see the Query Examples document, which shows how to implements queries from the multi-value INSERT statement (for example, using Model.insert_many()): with db.atomic(): for idx in range(0, len(row_data), 100): # Insert 100 rows at a time. rows = row_data[idx:idx + 100] User.insert_many(rows)

may need to break it up into chunks: # Insert rows 100 at a time. with db.atomic(): for idx in range(0, len(data_source), 100): MyModel.insert_many(data_source[idx:idx+100]).execute() Note SQLite a_user_tweets = Tweet.select().where(Tweet.user.in_(a_users)) More query examples Note For a wide range of example queries, see the Query Examples document, which shows how to implements queries from the A SQL instance or a string expressing the start of the window range. end – A SQL instance or a string expressing the end of the window range. window (Window) – A Window instance. Note Parameters: Parameters:

may need to break it up into chunks: # Insert rows 100 at a time. with db.atomic(): for idx in range(0, len(data_source), 100): MyModel.insert_many(data_source[idx:idx+100]).execute() Note SQLite a_user_tweets = Tweet.select().where(Tweet.user.in_(a_users)) More query examples Note For a wide range of example queries, see the Query Examples document, which shows how to implements queries from the A SQL instance or a string expressing the start of the window range. end – A SQL instance or a string expressing the end of the window range. window (Window) – A Window instance. Note For simplicity, it

# By default all queries go to the master, since that is what # is defined on our model. for i in range(10): Data.create(value=i) # But what if we want to explicitly use the read replica? with Using(read_replica may need to break it up into chunks: # Insert rows 100 at a time. with db.atomic(): for idx in range(0, len(data_source), 100): Model.insert_many(data_source[idx:idx+100]).execute() Note SQLite gauss_distribution() (f) * sqrt() (f) * tonumber() (f) * mode() (a) * minrange() (a) * avgrange() (a) * range() (a) * median() (a) (requires cython) STRING * substr_count() (f) * strip_chars() (f) * md5() (f)