./databases/postgresql14-plpython, PL/Python procedural language for the PostgreSQL backend

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Branch: CURRENT, Version: 14.0, Package name: postgresql14-plpython-14.0, Maintainer: adam

PL/Python allows you to write functions in the Python programming
language that may be used in SQL queries as if they were built into
Postgres. The PL/Python intepreter is a full Python interpreter.

PL/Python is currently only available as an "untrusted" language
(meaning it does not offer any way of restricting what users can do
in it). It has therefore been named "plpythonu". The trusted variant
plpython may become available again in future, if a new secure execution
mechanism is developed in Python.



Package options: gssapi, nls

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SHA1: 23c3ed1f42d2c439316fa978923fef469a8c379d
RMD160: 4765f3847c874c62b7d3ecc1fc046f9fb14a5c68
Filesize: 21325.041 KB

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   2021-10-08 12:23:45 by Adam Ciarcinski | Files touched by this commit (44) | Package updated
Log message:
postgresql14: added version 14.0

PostgreSQL 14 contains many new features and enhancements, including:

Stored procedures can now return data via OUT parameters.

The SQL-standard SEARCH and CYCLE options for common table expressions have been \ 
implemented.

Subscripting can now be applied to any data type for which it is a useful \ 
notation, not only arrays. In this release, the jsonb and hstore types have \ 
gained subscripting operators.

Range types have been extended by adding multiranges, allowing representation of \ 
noncontiguous data ranges.

Numerous performance improvements have been made for parallel queries, \ 
heavily-concurrent workloads, partitioned tables, logical replication, and \ 
vacuuming.

B-tree index updates are managed more efficiently, reducing index bloat.

VACUUM automatically becomes more aggressive, and skips inessential cleanup, if \ 
the database starts to approach a transaction ID wraparound condition.

Extended statistics can now be collected on expressions, allowing better \ 
planning results for complex queries.

libpq now has the ability to pipeline multiple queries, which can boost \ 
throughput over high-latency connections.