Feather.jl Documentation

Feather.read{T <: Data.Sink}(file, sink_type::Type{T}, sink_args...) => T Feather.read(file, sink::Data.Sink) => Data.Sink

Feather.read takes a feather-formatted binary file argument and "streams" the data to the provided sink argument, a DataFrame by default. A fully constructed sink can be provided as the 2nd argument (the 2nd method above), or a Sink can be constructed "on the fly" by providing the type of Sink and any necessary positional arguments (the 1st method above).

Keyword arguments:

• nullable::Bool=true: will return columns as NullableVector{T} types by default, regarldess of # of null values. When set to false, columns without null values will be returned as regular Vector{T}

• use_mmap::Bool=true: indicates whether to use system mmap capabilities when reading the feather file; on some systems or environments, mmap may not be available or reliable (virtualbox env using shared directories can be problematic)

• append::Bool=false: indicates whether the feather file should be appended to the provided sink argument; note that column types between the feather file and existing sink must match to allow appending

• transforms: a Dict{Int,Function} or Dict{String,Function} that provides transform functions to be applied to feather fields or columns as they are parsed from the feather file; note that feather files can be parsed field-by-field or entire columns at a time, so transform functions need to operate on scalars or vectors appropriately, depending on the sink argument's preferred streaming type; by default, a Feather.Source will stream entire columns at a time, so a transform function would take a single NullableVector{T} argument and return an equal-length NullableVector

Examples:

# default read method, returns a DataFrame
df = Feather.read("cool_feather_file.feather")

# read a feather file directly into a SQLite database table
db = SQLite.DB()
Feather.read("cool_feather_file.feather", SQLite.Sink, db, "cool_feather_table")

Feather.write{T <: Data.Source}(io, source::Type{T}, source_args...) => Feather.Sink Feather.write(io, source::Data.Source) => Feather.Sink

Write a Data.Source out to disk as a feather-formatted binary file. The two methods allow the passing of a fully constructed Data.Source (2nd method), or the type of Source and any necessary positional arguments (1st method).

Keyword arguments:

• append::Bool=false: indicates whether the source argument should be appended to an existing feather file; note that column types between the source argument and feather file must match to allow appending

• transforms: a Dict{Int,Function} or Dict{String,Function} that provides transform functions to be applied to source fields or columns as they are streamed to the feather file; note that feather sinks can be receive data field-by-field or entire columns at a time, so transform functions need to operate on scalars or vectors appropriately, depending on the source argument's allowed streaming types; by default, a Feather.Sink will stream entire columns at a time, so a transform function would take a single NullableVector{T} argument and return an equal-length NullableVector

Examples:

df = DataFrame(...)
Feather.write("shiny_new_feather_file.feather", df)

Feather.write("sqlite_query_result.feather", SQLite.Source, db, "select * from cool_table")