Store#

featherstore.store.create_store(store_name, *, errors='raise')[source]#

Creates a new store.

Parameters:

  • store_name (str) – The name of the store to be created

  • errors (str, optional) – Whether or not to raise an error if the store already exist. Can be either raise or ignore, ignore passes if the store already exists, by default raise

Return type:

Store

featherstore.store.rename_store(store_name, *, to)[source]#

Renames a store

Parameters:

  • store_name (str) – The name of the store to be renamed.

  • to (str) – The new name of the store.

featherstore.store.drop_store(store_name, *, errors='raise')[source]#

Deletes a store

Warning: You can not delete a store containing tables. All tables must be deleted first.

Parameters:

  • store_name (str) – The name of the store to be deleted

  • errors (str, optional) – Whether or not to raise an error if the store doesn’t exist. Can be either raise or ignore, by default raise

featherstore.store.list_stores(*, like=None)[source]#

Lists stores in database

Parameters:

like (str, optional) –

Filters out stores not matching string pattern, by default None.

There are two wildcards that can be used in conjunction with like:

  • Question mark (?) matches any single character

  • The percent sign (%) matches any number of any characters

Returns:

A list of the tables in the store

Return type:

List

featherstore.store.store_exists(store_name)[source]#
class featherstore.store.Store(store_name)[source]#

Bases: object

A class for doing basic tasks with tables within a store.

Stores are directories for organizing data in logical groups within your FeatherStore database.

Parameters:

store_name (str) – The name of the store to be selected

rename(*, to)[source]#

Renames the current store

Parameters:

to (str) – The new name of the store.

drop(*, errors='raise')[source]#

Deletes the current store

Warning: You can not delete a store containing tables. All tables must be deleted first.

Parameters:

errors (str, optional) – Whether or not to raise an error if the store doesn’t exist. Can be either raise or ignore, by default raise

list_tables(*, like=None)[source]#

Lists tables in store

Parameters:

like (str, optional) –

Filters out tables not matching string pattern, by default None.

There are two wildcards that can be used in conjunction with like:

  • Question mark (?) matches any single character

  • The percent sign (%) matches any number of any characters

Returns:

A list of the tables in the store

Return type:

List

table_exists(table_name)[source]#
read_arrow(table_name, *, cols=None, rows=None, mmap=None)[source]#

Reads PyArrow Table from store

Parameters:

  • cols (Collection, optional) – List of column names or, filter-predicates in the form of {‘like’: pattern}. If not provided, all columns are read.

  • rows (Collection, optional) – List of index values or filter-predicates in the form of {keyword: value}, where keyword can be either before, after, or between. If not provided, all rows are read.

  • mmap (bool, optional) – Use memory mapping when opening table on disk, by default False on Windows and True on other systems.

Return type:

pyarrow.Table

read_pandas(table_name, *, cols=None, rows=None, mmap=None)[source]#

Reads Pandas DataFrame or Series from store

Parameters:

  • cols (Collection, optional) – List of column names or, filter-predicates in the form of {‘like’: pattern}. If not provided, all columns are read.

  • rows (Collection, optional) – List of index values or filter-predicates in the form of {keyword: value}, where keyword can be either before, after, or between. If not provided, all rows are read.

  • mmap (bool, optional) – Use memory mapping when opening table on disk, by default False on Windows and True on other systems.

Return type:

pandas.DataFrame or pandas.Series

read_polars(table_name, *, cols=None, rows=None, mmap=None)[source]#

Reads Polars DataFrame or Series from store

Parameters:

  • cols (Collection, optional) – List of column names or, filter-predicates in the form of {‘like’: pattern}. If not provided, all columns are read.

  • rows (Collection, optional) – List of index values or filter-predicates in the form of {keyword: value}, where keyword can be either before, after, or between. If not provided, all rows are read.

  • mmap (bool, optional) – Use memory mapping when opening table on disk, by default False on Windows and True on other systems.

Return type:

polars.DataFrame or polars.Series

write_table(table_name, df, /, index=None, *, partition_size=134217728, errors='raise', warnings='warn')[source]#

Writes a DataFrame to the current store as a partitioned table

The DataFrame index column, if provided, must be either of type int, str, or datetime. FeatherStore sorts the DataFrame by the index before storage.

Parameters:

  • table_name (str) – The name of the table the DataFrame will be stored as

  • df (pandas DataFrame or Series, polars DataFrame or Series, or pyarrow Table) – The DataFrame to be stored

  • index (str, optional) – The name of the column to be used as index. Uses current index for Pandas or a standard integer index for Arrow and Polars if index not provided, by default None

  • partition_size (int, optional) – The size of each partition in bytes, by default 128 MB

  • errors (str, optional) – Whether or not to raise an error if the table already exist. Can be either raise or ignore, ignore overwrites existing table, by default raise

  • warnings (str, optional) – Whether or not to warn if a unsorted index is about to get sorted. Can be either warn or ignore, by default warn

append_table(table_name, df, warnings='warn')[source]#

Appends data to a table

Parameters:

  • table_name (str) – The name of the table you want to append to

  • df (Pandas DataFrame or Series, Polars DataFrame or Series, or Pyarrow Table) – The data to be appended

  • warnings (str, optional) – Whether or not to warn if a unsorted index is about to get sorted. Can be either warn or ignore, by default warn

rename_table(table_name, *, to)[source]#

Renames a table

Parameters:

  • table_name (str) – The name of the table to be renamed

  • to (str) – The new name of the table.

drop_table(table_name)[source]#

Deletes a table

Parameters:

table_name (str) – The name of the table to be deleted

select_table(table_name)[source]#

Selects a single table.

Table objects have more features for editing stored tables.

Parameters:

table_name (str) – The name of the table to be returned

Return type:

Table

create_snapshot(path)[source]#

Creates a compressed backup of the store.

The store can later be restored by using snapshot.restore_store().

Parameters:

path (str) – The path to the snapshot archive.