WORK IN PROGRESS!!!
A Julia library to get remote data via Requests.jl and get DataFrames thanks to DataFrames.jl.
Inspired by Pandas-DataReader.
Pkg.clone("https://github.com/JuliaDataReaders/DataReaders.jl.git")using DataReadersjulia> dr = DataReader("google");
julia> symb = DataSymbol("MSFT");
julia> dt_start = DateTime("2015-04-01");
julia> dt_end = DateTime("2015-04-15");
julia> response = get(dr, symb, dt_start, dt_end);
julia> df = DataFrame(response);
julia> println(df);
10x6 DataFrames.DataFrame
β Row β Date β Open β High β Low β Close β Volume β
βββββββΏβββββββββββββΏββββββββΏββββββββΏββββββββΏββββββββΏβββββββββββ₯
β 1 β 2015-04-01 β 40.6 β 40.76 β 40.31 β 40.72 β 36865322 β
β 2 β 2015-04-02 β 40.66 β 40.74 β 40.12 β 40.29 β 37487476 β
β 3 β 2015-04-06 β 40.34 β 41.78 β 40.18 β 41.54 β 39223692 β
β 4 β 2015-04-07 β 41.61 β 41.91 β 41.31 β 41.53 β 28809375 β
β 5 β 2015-04-08 β 41.46 β 41.69 β 41.04 β 41.42 β 24753438 β
β 6 β 2015-04-09 β 41.25 β 41.62 β 41.25 β 41.48 β 25723861 β
β 7 β 2015-04-10 β 41.63 β 41.95 β 41.41 β 41.72 β 28022002 β
β 8 β 2015-04-13 β 41.4 β 42.06 β 41.39 β 41.76 β 30276692 β
β 9 β 2015-04-14 β 41.8 β 42.03 β 41.39 β 41.65 β 24244382 β
β 10 β 2015-04-15 β 41.76 β 42.46 β 41.68 β 42.26 β 27343581 βjulia> dr = DataReader("google");
julia> symbols = DataSymbol.(["IBM", "MSFT"])
2-element Array{DataReaders.DataSymbol,1}:
DataReaders.DataSymbol("IBM")
DataReaders.DataSymbol("MSFT")
julia> dt_start = DateTime("2015-04-01");
julia> dt_end = DateTime("2015-04-15");
julia> multi_symbol_response = get(dr, symbols, dt_start, dt_end);
julia> data = DataFrame(multi_symbol_response);
julia> println(data)
DataStructures.OrderedDict(DataReaders.DataSymbol("IBM")=>10x6 DataFrames.DataFrame
β Row β Date β Open β High β Low β Close β Volume β
βββββββΏβββββββββββββΏβββββββββΏβββββββββΏβββββββββΏβββββββββΏββββββββββ₯
β 1 β 2015-04-01 β 160.23 β 160.62 β 158.39 β 159.18 β 3700791 β
β 2 β 2015-04-02 β 159.52 β 162.54 β 158.89 β 160.45 β 4671578 β
β 3 β 2015-04-06 β 159.69 β 162.8 β 158.7 β 162.04 β 3465682 β
β 4 β 2015-04-07 β 161.67 β 163.84 β 161.62 β 162.07 β 3147975 β
β 5 β 2015-04-08 β 161.72 β 163.55 β 161.01 β 161.85 β 2524323 β
β 6 β 2015-04-09 β 161.7 β 162.47 β 160.72 β 162.34 β 2263490 β
β 7 β 2015-04-10 β 162.34 β 163.33 β 161.25 β 162.86 β 2515703 β
β 8 β 2015-04-13 β 162.37 β 164.0 β 162.36 β 162.38 β 3868911 β
β 9 β 2015-04-14 β 162.42 β 162.74 β 160.79 β 162.3 β 2719287 β
β 10 β 2015-04-15 β 162.63 β 164.96 β 162.5 β 164.13 β 3498756 β,DataReaders.DataSymbol("MSFT")=>10x6 DataFrames.DataFrame
β Row β Date β Open β High β Low β Close β Volume β
βββββββΏβββββββββββββΏββββββββΏββββββββΏββββββββΏββββββββΏβββββββββββ₯
β 1 β 2015-04-01 β 40.6 β 40.76 β 40.31 β 40.72 β 36865322 β
β 2 β 2015-04-02 β 40.66 β 40.74 β 40.12 β 40.29 β 37487476 β
β 3 β 2015-04-06 β 40.34 β 41.78 β 40.18 β 41.54 β 39223692 β
β 4 β 2015-04-07 β 41.61 β 41.91 β 41.31 β 41.53 β 28809375 β
β 5 β 2015-04-08 β 41.46 β 41.69 β 41.04 β 41.42 β 24753438 β
β 6 β 2015-04-09 β 41.25 β 41.62 β 41.25 β 41.48 β 25723861 β
β 7 β 2015-04-10 β 41.63 β 41.95 β 41.41 β 41.72 β 28022002 β
β 8 β 2015-04-13 β 41.4 β 42.06 β 41.39 β 41.76 β 30276692 β
β 9 β 2015-04-14 β 41.8 β 42.03 β 41.39 β 41.65 β 24244382 β
β 10 β 2015-04-15 β 41.76 β 42.46 β 41.68 β 42.26 β 27343581 β)- Yahoo Finance daily DataReaders
- Support several symbols for Google Finance daily DataReaders - return as OrderedDict
- Google Finance daily DataReaders (only one symbol at a time)
- Unit testing
- Continuous Integration
- Support several symbols for Google (daily) DataReaders - return as Panel (see JuliaData/DataFrames.jl#941 )
- Support others data source (Yahoo...)
- Requests-cache mechanism (see JuliaIO/HDF5.jl#296 and https://github.com/femtotrader/RequestsCache.jl/)
- Packaging (publish on METADATA)
- ...