Drizzle/bzr dependency

A number of developers had problems on Friday at the Drizzle Developer Day with compiling bzr . The distro in question I was helping with was CentOS 5 32-bit. I had no issues on CentOS 5 64bit.

Today while creating the first deployed Drizzle AWS AMI I discovered the same problem using Ubuntu 8.10 Intrepid 32 bit.

The solution was actually rather trivial. Installing the python-dev package solved the problem.

apt-get install python-dev

Bzr 1.13.1 Compiling error

building 'bzrlib._btree_serializer_c' extension
gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2 -Wall -Wstrict-prototypes -fPIC -I/usr/include/python2.5 -c bzrlib/_btree_serializer_c.c -o build/temp.linux-i686-2.5/bzrlib/_btree_serializer_c.o
bzrlib/_btree_serializer_c.c:4:20: error: Python.h: No such file or directory
bzrlib/_btree_serializer_c.c:5:26: error: structmember.h: No such file or directory
bzrlib/_btree_serializer_c.c:35: error: expected specifier-qualifier-list before ‘PyObject’
....
bzrlib/_btree_serializer_c.c:1651: error: request for member ‘f_lineno’ in something not a structure or union
bzrlib/_btree_serializer_c.c:1651: warning: statement with no effect
bzrlib/_btree_serializer_c.c:1652: warning: implicit declaration of function ‘PyTraceBack_Here’

  Cannot build extension "bzrlib._btree_serializer_c".
  Use "build_ext --allow-python-fallback" to use slower python implementations instead.

error: command 'gcc' failed with exit status 1
Tagged with: Compiling Databases Drizzle General Open Source

Related Posts

DataEngBytes Sydney Overview

DataEngBytes Sydney Overview

I have just returned from my first DataEngBytes conference in Sydney. Here is a quick summary on my thoughts for the event. I plan to go into more detail on great points from presentations in later posts.

Read more
MITRE ATLAS - A 2025 Review

MITRE ATLAS - A 2025 Review

The MITRE ATLAS Matrix provides a working knowledge base of adversary tactics, techniques, and real-world case studies specifically for Artificial Intelligence (AI) and Machine Learning (ML) systems. It adapts the established MITRE ATT&CK adversary tactics and techniques matrix which is the standard reference for traditional IT cybersecurity.

Read more
Foundational Frameworks for GenAI Security Analysis

Foundational Frameworks for GenAI Security Analysis

Three frameworks form the analytical foundation of this series’ threat analysis, selected for their complementary coverage of the GenAI security landscape and their broad adoption across enterprise security practices. The MITRE Adversarial Threat Landscape for AI Systems (MITRE ATLAS) maps tactics and techniques specific to AI systems.

Read more