Changelog¶

1.1.0 (2023-01-04)¶

High-performance ingestion of Pandas dataframes into QuestDB via ILP. We now support most Pandas column types. The logic is implemented in native code and is orders of magnitude faster than iterating the dataframe in Python and calling the Buffer.row() or Sender.row() methods: The Buffer can be written from Pandas at hundreds of MiB/s per CPU core. The new dataframe() method continues working with the auto_flush feature. See API documentation and examples for the new dataframe() method available on both the Sender and Buffer classes.
New TimestampNanos.now() and TimestampMicros.now() methods. These are the new recommended way of getting the current timestamp.
The Python GIL is now released during calls to Sender.flush() and when auto_flush is triggered. This should improve throughput when using the Sender from multiple threads.

In previous releases the documentation for the from_datetime() methods of the TimestampNanos and TimestampMicros types recommended calling datetime.datetime.utcnow() to get the current timestamp. This is incorrect as it will (confusinly) return object with the local timezone instead of UTC. This documentation has been corrected and now recommends calling datetime.datetime.now(tz=datetime.timezone.utc) or (more efficiently) the new TimestampNanos.now() and TimestampMicros.now() methods.

Support for Python 3.11.
Updated to version 2.1.1 of the c-questdb-client library:
- Setting SO_REUSEADDR on outbound socket. This is helpful to users with large number of connections who previously ran out of outbound network ports.

As a matter of convenience, the Buffer.row method can now take None column values. This has the same semantics as skipping the column altogether. Closes #3.

Fixed a major bug where Python int and float types were handled with 32-bit instead of 64-bit precision. This caused certain int values to be rejected and other float values to be rounded incorrectly. Closes #13.
Fixed a minor bug where an error auto-flush caused a second clean-up error. Closes #4.