Many people in the data science field use the parquetformat to store tabular data, as it's the default format usedby Apache Spark -- an efficient data storage format foranalytics. The problem is: the format is binary (you can't just open it withyour preferred code editor) and there's no such a good Python library to read-- not until today!I found a Python library called parquet-python on GitHubbut it's hard to use, doesn't have one code example, was not available onPyPI and it looks like it's not maintained anymore. So I decided toimplement a parquet plugin (read-only) for my libraryrows: it uses the parquet-pythonlibrary under the hood (I needed to upload it to PyPI so youcan install it easly) and exposes the data in a pretty simple, pythonic way.InstallationI didn't realese the rows version with this plugin yet, so you need to grab themost recent rows version by running:pip install -U git+https://github.com/turicas/rows.git@developAnd also the dependency:pip install parquetIf the data is compressed using Google's snappy you'll alsoneed the library headers and other Python dependency -- install everything byrunning:apt-get install libsnappy-devpip install python-snappyThen you can use rows.import_from_parquet(filename) in your programs! \o/Python ExampleA quick Python code example:import rowstable = rows.import_from_parquet('myfile.parquet')for row in table: print row # access fields values with `rows.field_name`Note that the current implementation is not optimized (for example, it'llput everything into memory) but at least you can extract desired data and thenconvert to a more friendly format easily.Converting Parquet to Other Formats with rows' CLIYou can convert Parquet files to many tabular formats (like CSV) by usingthe rows's command-line interface, so you don't need to code.Install the rows CLI by running:pip install rows[cli]Now convert the parquet file:rows convert myfile.parquet myfile.csv # yes, simple like this!You can replace csv with any other supported format (the list is alwaysgrowing!), such as: txt, html, xls, xlsx and sqlite.If your file is small enough you can actually see it without needing to savethe output to another file by using the print subcommand:rows print myfile.parquet # will extract, convert and print data as textAnd you can actually query data as in SQL (this CLI is awesome!), for example:rows query 'nation_key < 10' tests/data/nation.dict.parquet \ --output=data.csvBy running this command the CLI will:Import data from tests/data/nation.dict.parquet file into memory;Export to SQLite (:memory:);Run the query (nation_key < 10) and get the results;Convert the results to a new rows.Table object;Export the table to CSV format and save it into data.csv (the result formatcould be html, xls, xlsx or any other write-plugin supported byrows).With this addition to rows I think the library and its command-lineinterface became one of the tools every data scientist should have installed.;-) O Que e NuBank?Para quem nao conhece, NuBank e um cartao de credito que nao tecobra anuidade e tem um otimo atendimento, alem de um aplicativo paracelular bastante facil de usar (e sua unica interface com eles). Em resumo:eles estao fazendo o que em geral os bancos nao fazem e estao lucrando comisso! Ja faz alguns meses que estou usando e recomendo! Se quiser saber maisdetalhes acesse a pagina deles.ProblemasO NuBank, apesar de muito bom, para mim poderia melhorar