* Use PyArrow Table for query result serialization
* Cleanup dev comments
* Additional cleanup
* WIP: tests
* Remove explicit dtype logic from db_engine_specs
* Remove obsolete column property
* SupersetTable column types
* Port SupersetDataFrame methods to SupersetTable
* Add test for nullable boolean columns
* Support datetime values with timezone offsets
* Black formatting
* Pylint
* More linting/formatting
* Resolve issue with timezones not appearing in results
* Types
* Enable running of tests in tests/db_engine_specs
* Resolve application context errors
* Refactor and add tests for pyodbc.Row conversion
* Appease isort, regardless of isort:skip
* Re-enable RESULTS_BACKEND_USE_MSGPACK default based on benchmarks
* Dataframe typing and nits
* Renames to reduce ambiguity
* Handle int64 columns with missing data in SQL Lab
* Fix docstring
* Add unit test
* Small fix
* Small fixes
* Fix cursor description update
* Better fix
* Fix unit test, black
* Fix nan comparison in unit test
* Add support for msgpack results_backend serialization
* Serialize DataFrame with PyArrow rather than JSON
* Adjust dependencies, de-lint
* Add tests for (de)serialization methods
* Add MessagePack config info to Installation docs
* Enable msgpack/arrow serialization by default
* [Fix] Prevent msgpack serialization on synchronous queries
* Add type annotations
* Making thrift, pyhive and tableschema as extra_requires
Looking at the dependency tree for license related questions, I noticed
that tableschema had a huge tree, and only people running Hive really
need it. Making this as well as pyhive and thrift optional.
Also bumping some python dependencies
* Run pip-compile
* Removing refs to past.builtins (from future lib)
* Add thrift
* [utils] gathering/refactoring into a "utils/" folder
Moving current utils.py into utils/core.py and moving other *util*
modules under this new "utils/" as well.
Following steps include eroding at "utils/core.py" and breaking it down
into smaller modules.
* Improve tests
* Make loading examples in scope for tests
* Remove test class attrs examples_loaded and requires_examples
* Replace dataframe label override logic with table column override
* Add mutation to any_date_col
* Linting
* Add mutation to oracle and redshift
* Fine tune how and which labels are mutated
* Implement alias quoting logic for oracle-like databases
* Fix and align column and metric sqla_col methods
* Clean up typos and redundant logic
* Move new attribute to old location
* Linting
* Replace old sqla_col property references with function calls
* Remove redundant calls to mutate_column_label
* Move duplicated logic to common function
* Add db_engine_specs to all sqla_col calls
* Add missing mydb
* Add note about snowflake-sqlalchemy regression
* Make db_engine_spec mandatory in sqla_col
* Small refactoring and cleanup
* Remove db_engine_spec from get_from_clause call
* Make db_engine_spec mandatory in adhoc_metric_to_sa
* Remove redundant mutate_expression_label call
* Add missing db_engine_specs to adhoc_metric_to_sa
* Rename arg label_name to label in get_column_label()
* Rename label function and add docstring
* Remove redundant db_engine_spec args
* Rename col_label to label
* Remove get_column_name wrapper and make direct calls to db_engine_spec
* Remove unneeded db_engine_specs
* Rename sa_ vars to sqla_
* Add function to fix dataframe column case
* Fix broken handle_nulls method
* Add case sensitivity option to dedup
* Refactor function definition and call location
* Remove added blank line
* Move df column rename logit to db_engine_spec
* Remove redundant variable
* Update comments in db_engine_specs
* Tie df adjustment to db_engine_spec class attribute
* Fix dedup error
* Linting
* Check for db_engine_spec attribute prior to adjustment
* Rename case sensitivity flag
* Linting
* Remove function that was moved to db_engine_specs
* Get metrics names from utils
* Remove double import and rename dedup variable
* Improve database type inference
Python's DBAPI isn't super clear and homogeneous on the
cursor.description specification, and this PR attempts to improve
inferring the datatypes returned in the cursor.
This work started around Presto's TIMESTAMP type being mishandled as
string as the database driver (pyhive) returns it as a string. The work
here fixes this bug and does a better job at inferring MySQL and Presto types.
It also creates a new method in db_engine_specs allowing for other
databases engines to implement and become more precise on type-inference
as needed.
* Fixing tests
* Adressing comments
* Using infer_objects
* Removing faulty line
* Addressing PrestoSpec redundant method comment
* Fix rebase issue
* Fix tests
A bug in to_dict(orient="records") in pandas/core/frame.py prevents
datetimes with time zones to be worked with. This works around the
issue in superset by re-implementing the logic of pandas in the
correct way. Until pandas fixes the issue this code should stay.
https://github.com/pandas-dev/pandas/issues/18372
This closes#1929
* [sqllab] assign types for visualize flow
Somehow when using the visualize flow, the types were not
assigned at all, creating some bugs downstream. This PR attempts to get
the information required based on what pandas is knows and the types in
the data itself.
* Fixing tests
* Fixing tests
* Fixing more tests
* Fixing the last py3 tests
* Change in files
* Renamin files and folders
* cleaning up a single piece of lint
* Removing boat picture from docs
* add superset word mark
* Update rename note in docs
* Fixing images
* Pinning datatables
* Fixing issues with mapbox-gl
* Forgot to rename one file
* Linting
* v0.13.0
* adding pyyaml to dev-reqs
