Package: records-csp
Records: SQL for Humans™Records is a very simple, but powerful, library for making raw SQL queries
to most relational databases.Just write SQL. No bells, no whistles. This common task can be
surprisingly difficult with the standard tools available.
This library strives to make this workflow as simple as possible,
while providing an elegant interface to work with your query results.Database support includes RedShift, Postgres, MySQL, SQLite, Oracle, and MS-SQL (drivers not included).☤ The BasicsWe know how to write SQL, so let’s send some to our database:importrecordsdb=records.Database('postgres://...')rows=db.query('select * from active_users')# or db.query_file('sqls/active-users.sql')Grab one row at a time:>>>rows[0]<Record{"username":"model-t","active":true,"name":"Henry Ford","user_email":"model-t@gmail.com","timezone":"2016-02-06 22:28:23.894202"}>Or iterate over them:forrinrows:print(r.name,r.user_email)Values can be accessed many ways:row.user_email,row['user_email'], orrow[3].Fields with non-alphanumeric characters (like spaces) are also fully supported.Or store a copy of your record collection for later reference:>>>rows.all()[<Record{"username":...}>,<Record{"username":...}>,<Record{"username":...}>,...]If you’re only expecting one result:>>>rows.first()<Record{"username":...}>Other options includerows.as_dict()androws.as_dict(ordered=True).☤ FeaturesIterated rows are cached for future reference.$DATABASE_URLenvironment variable support.ConvenienceDatabase.get_table_namesmethod.Command-linerecordstool for exporting queries.Safe parameterization:Database.query('life=:everything',everything=42).Queries can be passed as strings or filenames, parameters supported.Transactions:t =Database.transaction();t.commit().Bulk actions:Database.bulk_query()&Database.bulk_query_file().Records is proudly powered bySQLAlchemyandTablib.☤ Data Export FunctionalityRecords also features full Tablib integration, and allows you to export
your results to CSV, XLS, JSON, HTML Tables, YAML, or Pandas DataFrames with a single line of code.
Excellent for sharing data with friends, or generating reports.>>>print(rows.dataset)username|active|name      |user_email       |timezone
--------|------|----------|-----------------|--------------------------
model-t |True  |Henry Ford|model-t@gmail.com|2016-02-06 22:28:23.894202
...Comma Separated Values (CSV)>>>print(rows.export('csv'))username,active,name,user_email,timezone
model-t,True,Henry Ford,model-t@gmail.com,2016-02-06 22:28:23.894202
...YAML Ain’t Markup Language (YAML)>>>print(rows.export('yaml'))-{active:true,name:HenryFord,timezone:'2016-02-06 22:28:23.894202',user_email:model-t@gmail.com,username:model-t}...JavaScript Object Notation (JSON)>>>print(rows.export('json'))[{"username":"model-t","active":true,"name":"Henry Ford","user_email":"model-t@gmail.com","timezone":"2016-02-06 22:28:23.894202"},...]Microsoft Excel (xls, xlsx)withopen('report.xls','wb')asf:f.write(rows.export('xls'))Pandas DataFrame>>>rows.export('df')usernameactivenameuser_emailtimezone0model-tTrueHenryFordmodel-t@gmail.com2016-02-0622:28:23.894202You get the point. All other features of Tablib are also available,
so you can sort results, add/remove columns/rows, remove duplicates,
transpose the table, add separators, slice data by column, and more.See theTablib Documentationfor more details.☤ InstallationOf course, the recommended installation method ispipenv:$ pipenv install records[pandas]
✨🍰✨☤ Command-Line ToolAs an added bonus, arecordscommand-line tool is automatically
included. Here’s a screenshot of the usage information:☤ Thank YouThanks for checking this library out! I hope you find it useful.Of course, there’s always room for improvement. Feel free toopen an issueso we can make Records better, stronger, faster.v0.5.1 (09-01-2017)Depend ontablib[pandas].Support for Bulk quies:Database.bulk_query()&Database.bulk_query_file().v0.5.0 (11-15-2016)Support for transactions:t =Database.transaction();t.commit()v0.4.3 (02-16-2016)The cake is a lie.v0.4.2 (02-15-2016)Packaging fix.v0.4.1 (02-15-2016)Bugfix for Python 3.v0.4.0 (02-13-2016)Refactored to be fully powered by SQLAlchemy!Support for all major databases (thanks, SQLAlchemy!).Support for non-alphanumeric column names.NewRecordclass, for representing/accessing result rows.ResultSetrenamedRecordCollection.Removed Interactive Mode from the CLI.v0.3.0 (02-11-2016)Newrecordcommand-line tool available!Various improvements.v0.2.0 (02-10-2016)Results are now represented asRecord, a namedtuples class with dict-like qualities.NewResultSet.exportmethod, for exporting to various formats.Slicing aResultSetnow works, and results in a newResultSet.Lots of bugfixes and improvements!v0.1.0 (02-07-2016)Initial release.