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Latest Python 3 Release — Python 3.11.1

Stable Releases

Python 3.11.1 — Dec. 6, 2022

Note that Python 3.11.1 cannot be used on Windows 7 or earlier.
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Python 3.10.9 — Dec. 6, 2022

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Python 3.9.16 — Dec. 6, 2022

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Python 3.8.16 — Dec. 6, 2022

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Python 3.7.16 — Dec. 6, 2022

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Python 3.11.0 — Oct. 24, 2022

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Python 3.9.15 — Oct. 11, 2022

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Python 3.8.15 — Oct. 11, 2022

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Python 3.10.8 — Oct. 11, 2022

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Python 3.7.15 — Oct. 11, 2022

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Python 3.7.14 — Sept. 6, 2022

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Python 3.8.14 — Sept. 6, 2022

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Python 3.9.14 — Sept. 6, 2022

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Python 3.10.7 — Sept. 6, 2022

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Python 3.10.6 — Aug. 2, 2022

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Python 3.10.5 — June 6, 2022

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Python 3.9.13 — May 17, 2022

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Python 3.10.4 — March 24, 2022

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Python 3.9.12 — March 23, 2022

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Python 3.10.3 — March 16, 2022

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Python 3.9.11 — March 16, 2022

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Python 3.8.13 — March 16, 2022

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Python 3.7.13 — March 16, 2022

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Python 3.9.10 — Jan. 14, 2022

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Python 3.10.2 — Jan. 14, 2022

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Python 3.10.1 — Dec. 6, 2021

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Python 3.9.9 — Nov. 15, 2021

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Python 3.9.8 — Nov. 5, 2021

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Python 3.10.0 — Oct. 4, 2021

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Python 3.7.12 — Sept. 4, 2021

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Python 3.6.15 — Sept. 4, 2021

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Python 3.9.7 — Aug. 30, 2021

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Python 3.8.12 — Aug. 30, 2021

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Python 3.9.6 — June 28, 2021

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Python 3.8.11 — June 28, 2021

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Python 3.7.11 — June 28, 2021

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Python 3.6.14 — June 28, 2021

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Python 3.9.5 — May 3, 2021

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Python 3.8.10 — May 3, 2021

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Python 3.9.4 — April 4, 2021

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Python 3.9.3 — April 2, 2021

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Python 3.8.9 — April 2, 2021

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Python 3.9.2 — Feb. 19, 2021

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Python 3.8.8 — Feb. 19, 2021

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Python 3.6.13 — Feb. 15, 2021

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Python 3.7.10 — Feb. 15, 2021

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Python 3.8.7 — Dec. 21, 2020

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Python 3.9.1 — Dec. 7, 2020

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Python 3.9.0 — Oct. 5, 2020

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Python 3.8.6 — Sept. 24, 2020

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Python 3.8.6rc1 — Sept. 8, 2020

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Python 3.5.10 — Sept. 5, 2020

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Python 3.7.9 — Aug. 17, 2020

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Python 3.6.12 — Aug. 17, 2020

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Python 3.8.5 — July 20, 2020

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Python 3.8.4 — July 13, 2020

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Python 3.8.4rc1 — June 30, 2020

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Python 3.7.8 — June 27, 2020

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Python 3.6.11 — June 27, 2020

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Python 3.8.3 — May 13, 2020

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Python 3.8.3rc1 — April 29, 2020

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Python 2.7.18 — April 20, 2020
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Python 3.7.7 — March 10, 2020

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Python 3.8.2 — Feb. 24, 2020

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Python 3.8.1 — Dec. 18, 2019

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Python 3.7.6 — Dec. 18, 2019

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Python 3.6.10 — Dec. 18, 2019

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Python 3.5.9 — Nov. 2, 2019

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Python 3.5.8 — Oct. 29, 2019

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Python 2.7.17 — Oct. 19, 2019
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Python 3.7.5 — Oct. 15, 2019

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Python 3.8.0 — Oct. 14, 2019

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Python 3.7.4 — July 8, 2019

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Python 3.6.9 — July 2, 2019

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Python 3.7.3 — March 25, 2019

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Python 3.4.10 — March 18, 2019
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Python 3.5.7 — March 18, 2019

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Python 2.7.16 — March 4, 2019
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Python 3.7.2 — Dec. 24, 2018

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Python 3.6.8 — Dec. 24, 2018

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Python 3.7.1 — Oct. 20, 2018

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Python 3.6.7 — Oct. 20, 2018

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Python 3.5.6 — Aug. 2, 2018

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Python 3.4.9 — Aug. 2, 2018
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Python 3.7.0 — June 27, 2018

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Python 3.6.6 — June 27, 2018

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Python 2.7.15 — May 1, 2018
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Python 3.6.5 — March 28, 2018

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Python 3.4.8 — Feb. 5, 2018
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Python 3.5.5 — Feb. 5, 2018

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Python 3.6.4 — Dec. 19, 2017

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Python 3.6.3 — Oct. 3, 2017

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Python 3.3.7 — Sept. 19, 2017
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Python 2.7.14 — Sept. 16, 2017
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Python 3.4.7 — Aug. 9, 2017
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Python 3.5.4 — Aug. 8, 2017

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Python 3.6.2 — July 17, 2017

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Python 3.6.1 — March 21, 2017

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Python 3.4.6 — Jan. 17, 2017
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Python 3.5.3 — Jan. 17, 2017

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Python 3.6.0 — Dec. 23, 2016

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Python 2.7.13 — Dec. 17, 2016
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Python 3.4.5 — June 27, 2016
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Python 3.5.2 — June 27, 2016

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Python 2.7.12 — June 25, 2016
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Python 3.4.4 — Dec. 21, 2015
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Python 3.5.1 — Dec. 7, 2015

Note that Python 3.5.1 cannot be used on Windows XP or earlier.
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Python 2.7.11 — Dec. 5, 2015
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Python 3.5.0 — Sept. 13, 2015

Note that Python 3.5.0 cannot be used on Windows XP or earlier.
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Python 2.7.10 — May 23, 2015
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Python 3.4.3 — Feb. 25, 2015
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Python 2.7.9 — Dec. 10, 2014
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Python 3.4.2 — Oct. 13, 2014
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Python 3.3.6 — Oct. 12, 2014
- No files for this release.
Python 3.2.6 — Oct. 12, 2014
- No files for this release.
Python 2.7.8 — July 2, 2014
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Python 2.7.7 — June 1, 2014
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Python 3.4.1 — May 19, 2014
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Python 3.4.0 — March 17, 2014
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Python 3.3.5 — March 9, 2014
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Python 3.3.4 — Feb. 9, 2014
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Python 3.3.3 — Nov. 17, 2013
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Python 2.7.6 — Nov. 10, 2013
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Python 2.6.9 — Oct. 29, 2013
- No files for this release.
Python 3.3.2 — May 15, 2013
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Python 3.2.5 — May 15, 2013
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Python 2.7.5 — May 12, 2013
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Python 3.3.1 — April 6, 2013
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Python 3.2.4 — April 6, 2013
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Python 2.7.4 — April 6, 2013
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Python 3.3.0 — Sept. 29, 2012
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Python 2.6.8 — April 10, 2012
- No files for this release.
Python 3.2.3 — April 10, 2012
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Python 3.1.5 — April 9, 2012
- No files for this release.
Python 2.7.3 — April 9, 2012
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Python 3.2.2 — Sept. 3, 2011
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Python 3.2.1 — July 9, 2011
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Python 3.1.4 — June 11, 2011
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Python 2.7.2 — June 11, 2011
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Python 2.6.7 — June 3, 2011
- No files for this release.
Python 2.5.6 — May 26, 2011
- No files for this release.
Python 3.2.0 — Feb. 20, 2011
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Python 2.7.1 — Nov. 27, 2010
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Python 3.1.3 — Nov. 27, 2010
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Python 2.6.6 — Aug. 24, 2010
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Python 2.7.0 — July 3, 2010
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Python 3.1.2 — March 20, 2010
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Python 2.6.5 — March 18, 2010
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Python 2.5.5 — Jan. 31, 2010
- No files for this release.
Python 2.6.4 — Oct. 26, 2009
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Python 2.6.3 — Oct. 2, 2009
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Python 3.1.1 — Aug. 17, 2009
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Python 3.1.0 — June 26, 2009
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Python 2.6.2 — April 14, 2009
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Python 3.0.1 — Feb. 13, 2009
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Python 2.5.4 — Dec. 23, 2008
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Python 2.4.6 — Dec. 19, 2008
- No files for this release.
Python 2.5.3 — Dec. 19, 2008
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Python 2.6.1 — Dec. 4, 2008
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Python 3.0.0 — Dec. 3, 2008
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Python 2.6.0 — Oct. 2, 2008
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Python 2.3.7 — March 11, 2008
- No files for this release.
Python 2.4.5 — March 11, 2008
- No files for this release.
Python 2.5.2 — Feb. 21, 2008
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Python 2.5.1 — April 19, 2007
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Python 2.3.6 — Nov. 1, 2006
- No files for this release.
Python 2.4.4 — Oct. 18, 2006
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Python 2.5.0 — Sept. 19, 2006
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Python 2.4.3 — April 15, 2006
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Python 2.4.2 — Sept. 27, 2005
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Python 2.4.1 — March 30, 2005
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Python 2.3.5 — Feb. 8, 2005
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Python 2.4.0 — Nov. 30, 2004
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Python 2.3.4 — May 27, 2004
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Python 2.3.3 — Dec. 19, 2003
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Python 2.3.2 — Oct. 3, 2003
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Python 2.3.1 — Sept. 23, 2003
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Python 2.3.0 — July 29, 2003
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Python 2.2.3 — May 30, 2003
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Python 2.2.2 — Oct. 14, 2002
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Python 2.2.1 — April 10, 2002
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Python 2.1.3 — April 9, 2002
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Python 2.2.0 — Dec. 21, 2001
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Python 2.0.1 — June 22, 2001
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Pre-releases

Python 3.12.0a4 — Jan. 10, 2023
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Python 3.12.0a3 — Dec. 6, 2022
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Python 3.12.0a2 — Nov. 15, 2022
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Python 3.12.0a1 — Oct. 25, 2022
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Python 3.11.0rc2 — Sept. 12, 2022
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Python 3.11.0rc1 — Aug. 8, 2022
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Python 3.11.0b5 — July 26, 2022
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Python 3.11.0b4 — July 11, 2022
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Python 3.11.0b3 — June 1, 2022
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Python 3.11.0b2 — May 31, 2022
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Python 3.11.0b1 — May 8, 2022
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Python 3.11.0a7 — April 5, 2022
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Python 3.11.0a6 — March 7, 2022
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Python 3.11.0a5 — Feb. 3, 2022
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Python 3.11.0a4 — Jan. 14, 2022
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Python 3.11.0a3 — Dec. 8, 2021
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Python 3.11.0a2 — Nov. 5, 2021
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Python 3.11.0a1 — Oct. 5, 2021
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Python 3.10.0rc2 — Sept. 7, 2021
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Python 3.10.0rc1 — Aug. 2, 2021
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Python 3.10.0b4 — July 10, 2021
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Python 3.10.0b3 — June 17, 2021
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Python 3.10.0b2 — May 31, 2021
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Python 3.10.0b1 — May 3, 2021
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Python 3.10.0a7 — April 5, 2021
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Python 3.10.0a6 — March 1, 2021
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Python 3.9.2rc1 — Feb. 16, 2021
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Python 3.8.8rc1 — Feb. 16, 2021
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Python 3.10.0a5 — Feb. 2, 2021
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Python 3.10.0a4 — Jan. 4, 2021
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Python 3.8.7rc1 — Dec. 7, 2020
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Python 3.10.0a3 — Dec. 7, 2020
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Python 3.9.1rc1 — Nov. 26, 2020
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Python 3.10.0a2 — Nov. 3, 2020
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Python 3.10.0a1 — Oct. 5, 2020
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Python 3.9.0rc2 — Sept. 17, 2020
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Python 3.5.10rc1 — Aug. 22, 2020
- No files for this release.
Python 3.9.0rc1 — Aug. 11, 2020
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Python 3.9.0b5 — July 20, 2020
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Python 3.9.0b4 — July 3, 2020
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Python 3.7.8rc1 — June 17, 2020
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Python 3.6.11rc1 — June 17, 2020
- No files for this release.
Python 3.9.0b3 — June 9, 2020
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Python 3.9.0b2 — June 9, 2020
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Python 3.9.0b1 — May 19, 2020
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Python 3.9.0a6 — April 28, 2020
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Python 2.7.18rc1 — April 4, 2020
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Python 3.9.0a5 — March 23, 2020
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Python 3.7.7rc1 — March 4, 2020
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Python 3.9.0a4 — Feb. 26, 2020
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Python 3.8.2rc2 — Feb. 17, 2020
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Python 3.8.2rc1 — Feb. 10, 2020
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Python 3.9.0a3 — Jan. 24, 2020
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Python 3.9.0a2 — Dec. 18, 2019
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Python 3.7.6rc1 — Dec. 11, 2019
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Python 3.6.10rc1 — Dec. 11, 2019
- No files for this release.
Python 3.8.1rc1 — Dec. 10, 2019
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Python 3.9.0a1 — Nov. 19, 2019
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Python 3.5.8rc2 — Oct. 12, 2019
- No files for this release.
Python 2.7.17rc1 — Oct. 9, 2019
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Python 3.7.5rc1 — Oct. 2, 2019
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Python 3.8.0rc1 — Oct. 1, 2019
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Python 3.5.8rc1 — Sept. 9, 2019
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Python 3.8.0b4 — Aug. 29, 2019
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Python 3.8.0b3 — July 29, 2019
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Python 3.8.0b2 — July 4, 2019
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Python 3.6.9rc1 — June 18, 2019
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Python 3.7.4rc1 — June 18, 2019
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Python 3.8.0b1 — June 4, 2019
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Python 3.8.0a4 — May 6, 2019
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Python 3.8.0a3 — March 25, 2019
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Python 3.7.3rc1 — March 12, 2019
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Python 3.4.10rc1 — March 4, 2019
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Python 3.5.7rc1 — March 4, 2019
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Python 3.8.0a2 — Feb. 25, 2019
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Python 2.7.16rc1 — Feb. 17, 2019
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Python 3.8.0a1 — Feb. 3, 2019
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Python 3.7.2rc1 — Dec. 11, 2018
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Python 3.6.8rc1 — Dec. 11, 2018
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Python 3.7.1rc2 — Oct. 13, 2018
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Python 3.6.7rc2 — Oct. 13, 2018
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Python 3.7.1rc1 — Sept. 26, 2018
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Python 3.6.7rc1 — Sept. 26, 2018
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Python 3.4.9rc1 — July 20, 2018
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Python 3.5.6rc1 — July 20, 2018
- No files for this release.
Python 3.6.6rc1 — June 12, 2018
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Python 3.7.0rc1 — June 11, 2018
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Python 3.7.0b5 — May 30, 2018
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Python 2.7.15rc1 — April 15, 2018
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Python 3.6.5rc1 — March 13, 2018
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Python 3.7.0b2 — Feb. 28, 2018
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Python 3.7.0b1 — Jan. 31, 2018
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Python 3.4.8rc1 — Jan. 23, 2018
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Python 3.5.5rc1 — Jan. 23, 2018
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Python 3.7.0a4 — Jan. 9, 2018
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Python 3.7.0a3 — Dec. 5, 2017
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Python 3.6.4rc1 — Dec. 5, 2017
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Python 3.7.0a2 — Oct. 17, 2017
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Python 3.7.0a1 — Sept. 19, 2017
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Python 3.6.3rc1 — Sept. 19, 2017
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Python 3.3.7rc1 — Sept. 6, 2017
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Python 2.7.14rc1 — Aug. 27, 2017
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Python 3.5.4rc1 — July 25, 2017
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Python 3.4.7rc1 — July 25, 2017
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Python 3.6.2rc2 — July 7, 2017
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Python 3.6.2rc1 — June 17, 2017
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Python 3.6.1rc1 — March 5, 2017
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Python 3.5.3rc1 — Jan. 3, 2017
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Python 3.4.6rc1 — Jan. 3, 2017
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Python 3.6.0rc2 — Dec. 16, 2016
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Python 3.6.0rc1 — Dec. 6, 2016
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Python 2.7.13rc1 — Dec. 4, 2016
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Python 3.6.0b4 — Nov. 21, 2016
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Python 3.6.0b3 — Oct. 31, 2016
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Python 3.6.0b2 — Oct. 10, 2016
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Python 3.6.0b1 — Sept. 12, 2016
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Python 3.6.0a4 — Aug. 15, 2016
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Python 3.6.0a3 — July 12, 2016
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Python 3.6.0a2 — June 13, 2016
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Python 2.7.12rc1 — June 13, 2016
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Python 3.5.2rc1 — June 13, 2016
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Python 3.4.5rc1 — June 13, 2016
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Python 3.6.0a1 — May 17, 2016
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Python 3.4.4rc1 — Dec. 7, 2015
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Python 3.5.1rc1 — Nov. 23, 2015
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Python 2.7.11rc1 — Nov. 21, 2015
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Python 3.5.0rc4 — Sept. 9, 2015
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Python 3.5.0rc3 — Sept. 8, 2015
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Python 3.5.0rc2 — Aug. 25, 2015
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Python 3.5.0rc1 — Aug. 11, 2015
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Python 3.5.0b4 — July 26, 2015
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Python 3.5.0b3 — July 5, 2015
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Python 3.5.0b2 — June 1, 2015
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Python 3.5.0b1 — May 24, 2015
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Python 2.7.10rc1 — May 11, 2015
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Python 3.5.0a4 — April 20, 2015
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Python 3.5.0a3 — March 30, 2015
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Python 3.5.0a2 — March 9, 2015
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Python 3.5.0a1 — Feb. 8, 2015
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Python 3.4.3rc1 — Feb. 8, 2015
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Python 2.7.9rc1 — Nov. 26, 2014
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Python 3.3.6rc1 — Oct. 4, 2014
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Python 3.2.6rc1 — Oct. 4, 2014
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Python 3.4.2rc1 — Sept. 22, 2014
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Python 2.7.7rc1 — May 17, 2014
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Python 3.4.1rc1 — May 5, 2014
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Python 3.4.0rc3 — March 10, 2014
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Python 3.3.5rc2 — March 2, 2014
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Python 3.3.5rc1 — Feb. 23, 2014
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Python 3.3.5rc1 — Feb. 23, 2014
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Источник

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Источник

First, download the latest version
of Python 2.7 from the official website. If you want to be sure you are installing a fully
up-to-date version, click the Downloads > Windows link from the home page of the
Python.org web site .

The Windows version is provided as an MSI package. To install it manually, just
double-click the file. The MSI package format allows Windows administrators to
automate installation with their standard tools.

By design, Python installs to a directory with the version number embedded,
e.g. Python version 2.7 will install at C:Python27, so that you can
have multiple versions of Python on the
same system without conflicts. Of course, only one interpreter can be the
default application for Python file types. It also does not automatically
modify the PATH environment variable, so that you always have control over
which copy of Python is run.

Typing the full path name for a Python interpreter each time quickly gets
tedious, so add the directories for your default Python version to the PATH.
Assuming that your Python installation is in C:Python27, add this to your
PATH:

C:Python27;C:Python27Scripts

You can do this easily by running the following in powershell:

[Environment]::SetEnvironmentVariable("Path", "$env:Path;C:Python27;C:Python27Scripts", "User")

This is also an option during the installation process.

The second (Scripts) directory receives command files when certain
packages are installed, so it is a very useful addition.
You do not need to install or configure anything else to use Python. Having
said that, I would strongly recommend that you install the tools and libraries
described in the next section before you start building Python applications for
real-world use. In particular, you should always install Setuptools, as it
makes it much easier for you to use other third-party Python libraries.

Virtual Environments¶

A Virtual Environment is a tool to keep the dependencies required by different projects
in separate places, by creating virtual Python environments for them. It solves the
“Project X depends on version 1.x but, Project Y needs 4.x” dilemma, and keeps
your global site-packages directory clean and manageable.

For example, you can work on a project which requires Django 1.10 while also
maintaining a project which requires Django 1.8.

To start using this and see more information: Virtual Environments docs.

This page is a remixed version of another guide,
which is available under the same license.

Источник

This is Python version 2.5.2

License information

See the file «LICENSE» for information on the history of this
software, terms & conditions for usage, and a DISCLAIMER OF ALL
WARRANTIES.

This Python distribution contains no GNU General Public Licensed
(GPLed) code so it may be used in proprietary projects just like prior
Python distributions. There are interfaces to some GNU code but these
are entirely optional.

All trademarks referenced herein are property of their respective
holders.

What’s new in this release?

See the file «Misc/NEWS».

If you don’t read instructions

Congratulations on getting this far.

To start building right away (on UNIX): type «./configure» in the
current directory and when it finishes, type «make». This creates an
executable «./python»; to install in /usr/local, first do «su root»
and then «make install».

The section `Build instructions’ below is still recommended reading.

What is Python anyway?

Python is an interpreted, interactive object-oriented programming
language suitable (amongst other uses) for distributed application
development, scripting, numeric computing and system testing. Python
is often compared to Tcl, Perl, Java, JavaScript, Visual Basic or
Scheme. To find out more about what Python can do for you, point your
browser to http://www.python.org/.

How do I learn Python?

The official tutorial is still a good place to start; see
http://docs.python.org/ for online and downloadable versions, as well
as a list of other introductions, and reference documentation.

There’s a quickly growing set of books on Python. See
http://wiki.python.org/moin/PythonBooks for a list.

Documentation

All documentation is provided online in a variety of formats. In
order of importance for new users: Tutorial, Library Reference,
Language Reference, Extending & Embedding, and the Python/C API. The
Library Reference is especially of immense value since much of
Python’s power is described there, including the built-in data types
and functions!

All documentation is also available online at the Python web site
(http://docs.python.org/, see below). It is available online for
occasional reference, or can be downloaded in many formats for faster
access. The documentation is available in HTML, PostScript, PDF, and
LaTeX formats; the LaTeX version is primarily for documentation
authors, translators, and people with special formatting requirements.

Unfortunately, new-style classes (new in Python 2.2) have not yet been
integrated into Python’s standard documentation. A collection of
pointers to what has been written is at:

http://www.python.org/doc/newstyle.html

Web sites

New Python releases and related technologies are published at
http://www.python.org/. Come visit us!

There’s also a Python community web site at
http://starship.python.net/.

Newsgroups and Mailing Lists

Read comp.lang.python, a high-volume discussion newsgroup about
Python, or comp.lang.python.announce, a low-volume moderated newsgroup
for Python-related announcements. These are also accessible as
mailing lists: see http://www.python.org/community/lists.html for an
overview of these and many other Python-related mailing lists.

Archives are accessible via the Google Groups Usenet archive; see
http://groups.google.com/. The mailing lists are also archived, see
http://www.python.org/community/lists.html for details.

Bug reports

To report or search for bugs, please use the Python Bug
Tracker at http://bugs.python.org.

Patches and contributions

To submit a patch or other contribution, please use the Python Patch
Manager at http://bugs.python.org. Guidelines
for patch submission may be found at http://www.python.org/dev/patches/.

If you have a proposal to change Python, it’s best to submit a Python
Enhancement Proposal (PEP) first. All current PEPs, as well as
guidelines for submitting a new PEP, are listed at
http://www.python.org/dev/peps/.

Questions

For help, if you can’t find it in the manuals or on the web site, it’s
best to post to the comp.lang.python or the Python mailing list (see
above). If you specifically don’t want to involve the newsgroup or
mailing list, send questions to help@python.org (a group of volunteers
who answer questions as they can). The newsgroup is the most
efficient way to ask public questions.

Build instructions

Before you can build Python, you must first configure it.
Fortunately, the configuration and build process has been automated
for Unix and Linux installations, so all you usually have to do is
type a few commands and sit back. There are some platforms where
things are not quite as smooth; see the platform specific notes below.
If you want to build for multiple platforms sharing the same source
tree, see the section on VPATH below.

Start by running the script «./configure», which determines your
system configuration and creates the Makefile. (It takes a minute or
two — please be patient!) You may want to pass options to the
configure script — see the section below on configuration options and
variables. When it’s done, you are ready to run make.

To build Python, you normally type «make» in the toplevel directory.
If you have changed the configuration, the Makefile may have to be
rebuilt. In this case you may have to run make again to correctly
build your desired target. The interpreter executable is built in the
top level directory.

Once you have built a Python interpreter, see the subsections below on
testing and installation. If you run into trouble, see the next
section.

Previous versions of Python used a manual configuration process that
involved editing the file Modules/Setup. While this file still exists
and manual configuration is still supported, it is rarely needed any
more: almost all modules are automatically built as appropriate under
guidance of the setup.py script, which is run by Make after the
interpreter has been built.

Troubleshooting

See also the platform specific notes in the next section.

If you run into other trouble, see the FAQ
(http://www.python.org/doc/faq) for hints on what can go wrong, and
how to fix it.

If you rerun the configure script with different options, remove all
object files by running «make clean» before rebuilding. Believe it or
not, «make clean» sometimes helps to clean up other inexplicable
problems as well. Try it before sending in a bug report!

If the configure script fails or doesn’t seem to find things that
should be there, inspect the config.log file.

If you get a warning for every file about the -Olimit option being no
longer supported, you can ignore it. There’s no foolproof way to know
whether this option is needed; all we can do is test whether it is
accepted without error. On some systems, e.g. older SGI compilers, it
is essential for performance (specifically when compiling ceval.c,
which has more basic blocks than the default limit of 1000). If the
warning bothers you, edit the Makefile to remove «-Olimit 1500» from
the OPT variable.

If you get failures in test_long, or sys.maxint gets set to -1, you
are probably experiencing compiler bugs, usually related to
optimization. This is a common problem with some versions of gcc, and
some vendor-supplied compilers, which can sometimes be worked around
by turning off optimization. Consider switching to stable versions
(gcc 2.95.2, gcc 3.x, or contact your vendor.)

From Python 2.0 onward, all Python C code is ANSI C. Compiling using
old K&R-C-only compilers is no longer possible. ANSI C compilers are
available for all modern systems, either in the form of updated
compilers from the vendor, or one of the free compilers (gcc).

If «make install» fails mysteriously during the «compiling the library»
step, make sure that you don’t have any of the PYTHONPATH or PYTHONHOME
environment variables set, as they may interfere with the newly built
executable which is compiling the library.

Unsupported systems

A number of features are not supported in Python 2.5 anymore. Some
support code is still present, but will be removed in Python 2.6.
If you still need to use current Python versions on these systems,
please send a message to python-dev@python.org indicating that you
volunteer to support this system. For a more detailed discussion
regarding no-longer-supported and resupporting platforms, as well
as a list of platforms that became or will be unsupported, see PEP 11.

More specifically, the following systems are not supported any
longer:

SunOS 4
DYNIX
dgux
Minix
NeXT
Irix 4 and —with-sgi-dl
Linux 1
Systems defining __d6_pthread_create (configure.in)
Systems defining PY_PTHREAD_D4, PY_PTHREAD_D6,
or PY_PTHREAD_D7 in thread_pthread.h
Systems using —with-dl-dld
Systems using —without-universal-newlines
MacOS 9

The following systems are still supported in Python 2.5, but
support will be dropped in 2.6:

Systems using —with-wctype-functions
Win9x, WinME

Warning on install in Windows 98 and Windows Me

Following Microsoft’s closing of Extended Support for
Windows 98/ME (July 11, 2006), Python 2.6 will stop
supporting these platforms. Python development and
maintainability becomes easier (and more reliable) when
platform specific code targeting OSes with few users
and no dedicated expert developers is taken out. The
vendor also warns that the OS versions listed above
«can expose customers to security risks» and recommends
upgrade.

Platform specific notes

(Some of these may no longer apply. If you find you can build Python
on these platforms without the special directions mentioned here,
submit a documentation bug report to SourceForge (see Bug Reports
above) so we can remove them!)

Unix platforms: If your vendor still ships (and you still use) Berkeley DB
1.85 you will need to edit Modules/Setup to build the bsddb185
module and add a line to sitecustomize.py which makes it the
default. In Modules/Setup a line like

        bsddb185 bsddbmodule.c

    should work.  (You may need to add -I, -L or -l flags to direct the
    compiler and linker to your include files and libraries.)

XXX I think this next bit is out of date:

64-bit platforms: The modules audioop, imageop and rgbimg don’t work.
The setup.py script disables them on 64-bit installations.
Don’t try to enable them in the Modules/Setup file. They
contain code that is quite wordsize sensitive. (If you have a
fix, let us know!)

Solaris: When using Sun’s C compiler with threads, at least on Solaris
2.5.1, you need to add the «-mt» compiler option (the simplest
way is probably to specify the compiler with this option as
the «CC» environment variable when running the configure
script).

    When using GCC on Solaris, beware of binutils 2.13 or GCC
    versions built using it.  This mistakenly enables the
    -zcombreloc option which creates broken shared libraries on
    Solaris.  binutils 2.12 works, and the binutils maintainers
    are aware of the problem.  Binutils 2.13.1 only partially
    fixed things.  It appears that 2.13.2 solves the problem
    completely.  This problem is known to occur with Solaris 2.7
    and 2.8, but may also affect earlier and later versions of the
    OS.

    When the dynamic loader complains about errors finding shared
    libraries, such as

    ld.so.1: ./python: fatal: libstdc++.so.5: open failed:
    No such file or directory

    you need to first make sure that the library is available on
    your system. Then, you need to instruct the dynamic loader how
    to find it. You can choose any of the following strategies:

    1. When compiling Python, set LD_RUN_PATH to the directories
       containing missing libraries.
    2. When running Python, set LD_LIBRARY_PATH to these directories.
    3. Use crle(8) to extend the search path of the loader.
    4. Modify the installed GCC specs file, adding -R options into the
       *link: section.

    The complex object fails to compile on Solaris 10 with gcc 3.4 (at
    least up to 3.4.3).  To work around it, define Py_HUGE_VAL as
    HUGE_VAL(), e.g.:

      make CPPFLAGS='-D"Py_HUGE_VAL=HUGE_VAL()" -I. -I$(srcdir)/Include'
      ./python setup.py CPPFLAGS='-D"Py_HUGE_VAL=HUGE_VAL()"'

Linux: A problem with threads and fork() was tracked down to a bug in
the pthreads code in glibc version 2.0.5; glibc version 2.0.7
solves the problem. This causes the popen2 test to fail;
problem and solution reported by Pablo Bleyer.

Red Hat Linux: Red Hat 9 built Python2.2 in UCS-4 mode and hacked
Tcl to support it. To compile Python2.3 with Tkinter, you will
need to pass —enable-unicode=ucs4 flag to ./configure.

    There's an executable /usr/bin/python which is Python
    1.5.2 on most older Red Hat installations; several key Red Hat tools
    require this version.  Python 2.1.x may be installed as
    /usr/bin/python2.  The Makefile installs Python as
    /usr/local/bin/python, which may or may not take precedence
    over /usr/bin/python, depending on how you have set up $PATH.

FreeBSD 3.x and probably platforms with NCurses that use libmytinfo or
similar: When using cursesmodule, the linking is not done in
the correct order with the defaults. Remove «-ltermcap» from
the readline entry in Setup, and use as curses entry: «curses
cursesmodule.c -lmytinfo -lncurses -ltermcap» — «mytinfo» (so
called on FreeBSD) should be the name of the auxiliary library
required on your platform. Normally, it would be linked
automatically, but not necessarily in the correct order.

BSDI: BSDI versions before 4.1 have known problems with threads,
which can cause strange errors in a number of modules (for
instance, the ‘test_signal’ test script will hang forever.)
Turning off threads (with —with-threads=no) or upgrading to
BSDI 4.1 solves this problem.

DEC Unix: Run configure with —with-dec-threads, or with
—with-threads=no if no threads are desired (threads are on by
default). When using GCC, it is possible to get an internal
compiler error if optimization is used. This was reported for
GCC 2.7.2.3 on selectmodule.c. Manually compile the affected
file without optimization to solve the problem.

DEC Ultrix: compile with GCC to avoid bugs in the native compiler,
and pass SHELL=/bin/sh5 to Make when installing.

AIX: A complete overhaul of the shared library support is now in
place. See Misc/AIX-NOTES for some notes on how it’s done.
(The optimizer bug reported at this place in previous releases
has been worked around by a minimal code change.) If you get
errors about pthread_* functions, during compile or during
testing, try setting CC to a thread-safe (reentrant) compiler,
like «cc_r». For full C++ module support, set CC=»xlC_r» (or
CC=»xlC» without thread support).

AIX 5.3: To build a 64-bit version with IBM’s compiler, I used the
following:

    export PATH=/usr/bin:/usr/vacpp/bin
    ./configure --with-gcc="xlc_r -q64" --with-cxx="xlC_r -q64" 
                --disable-ipv6 AR="ar -X64"
    make

HP-UX: When using threading, you may have to add -D_REENTRANT to the
OPT variable in the top-level Makefile; reported by Pat Knight,
this seems to make a difference (at least for HP-UX 10.20)
even though pyconfig.h defines it. This seems unnecessary when
using HP/UX 11 and later — threading seems to work «out of the
box».

HP-UX ia64: When building on the ia64 (Itanium) platform using HP’s
compiler, some experience has shown that the compiler’s
optimiser produces a completely broken version of python
(see http://www.python.org/sf/814976). To work around this,
edit the Makefile and remove -O from the OPT line.

    To build a 64-bit executable on an Itanium 2 system using HP's
    compiler, use these environment variables:

            CC=cc
            CXX=aCC
            BASECFLAGS="+DD64"
            LDFLAGS="+DD64 -lxnet"

    and call configure as:

            ./configure --without-gcc

    then *unset* the environment variables again before running
    make.  (At least one of these flags causes the build to fail
    if it remains set.)  You still have to edit the Makefile and
    remove -O from the OPT line.

HP PA-RISC 2.0: A recent bug report (http://www.python.org/sf/546117)
suggests that the C compiler in this 64-bit system has bugs
in the optimizer that break Python. Compiling without
optimization solves the problems.

SCO: The following apply to SCO 3 only; Python builds out of the box
on SCO 5 (or so we’ve heard).

    1) Everything works much better if you add -U__STDC__ to the
    defs.  This is because all the SCO header files are broken.
    Anything that isn't mentioned in the C standard is
    conditionally excluded when __STDC__ is defined.

    2) Due to the U.S. export restrictions, SCO broke the crypt
    stuff out into a separate library, libcrypt_i.a so the LIBS
    needed be set to:

            LIBS=' -lsocket -lcrypt_i'

UnixWare: There are known bugs in the math library of the system, as well as
problems in the handling of threads (calling fork in one
thread may interrupt system calls in others). Therefore, test_math and
tests involving threads will fail until those problems are fixed.

QNX: Chris Herborth (chrish@qnx.com) writes:
configure works best if you use GNU bash; a port is available on
ftp.qnx.com in /usr/free. I used the following process to build,
test and install Python 1.5.x under QNX:

    1) CONFIG_SHELL=/usr/local/bin/bash CC=cc RANLIB=: 
        ./configure --verbose --without-gcc --with-libm=""

    2) edit Modules/Setup to activate everything that makes sense for
       your system... tested here at QNX with the following modules:

            array, audioop, binascii, cPickle, cStringIO, cmath,
            crypt, curses, errno, fcntl, gdbm, grp, imageop,
            _locale, math, md5, new, operator, parser, pcre,
            posix, pwd, readline, regex, reop, rgbimg, rotor,
            select, signal, socket, soundex, strop, struct,
            syslog, termios, time, timing, zlib, audioop, imageop, rgbimg

    3) make SHELL=/usr/local/bin/bash

       or, if you feel the need for speed:

       make SHELL=/usr/local/bin/bash OPT="-5 -Oil+nrt"

    4) make SHELL=/usr/local/bin/bash test

       Using GNU readline 2.2 seems to behave strangely, but I
       think that's a problem with my readline 2.2 port.  :-

    5) make SHELL=/usr/local/bin/bash install

    If you get SIGSEGVs while running Python (I haven't yet, but
    I've only run small programs and the test cases), you're
    probably running out of stack; the default 32k could be a
    little tight.  To increase the stack size, edit the Makefile
    to read: LDFLAGS = -N 48k

BeOS: See Misc/BeOS-NOTES for notes about compiling/installing
Python on BeOS R3 or later. Note that only the PowerPC
platform is supported for R3; both PowerPC and x86 are
supported for R4.

Cray T3E: Mark Hadfield (m.hadfield@niwa.co.nz) writes:
Python can be built satisfactorily on a Cray T3E but based on
my experience with the NIWA T3E (2002-05-22, version 2.2.1)
there are a few bugs and gotchas. For more information see a
thread on comp.lang.python in May 2002 entitled «Building
Python on Cray T3E».

    1) Use Cray's cc and not gcc. The latter was reported not to
       work by Konrad Hinsen. It may work now, but it may not.

    2) To set sys.platform to something sensible, pass the
       following environment variable to the configure script:

         MACHDEP=unicosmk

    2) Run configure with option "--enable-unicode=ucs4".

    3) The Cray T3E does not support dynamic linking, so extension
       modules have to be built by adding (or uncommenting) lines
       in Modules/Setup. The minimum set of modules is

         posix, new, _sre, unicodedata

       On NIWA's vanilla T3E system the following have also been
       included successfully:

         _codecs, _locale, _socket, _symtable, _testcapi, _weakref
         array, binascii, cmath, cPickle, crypt, cStringIO, dbm
         errno, fcntl, grp, math, md5, operator, parser, pcre, pwd
         regex, rotor, select, struct, strop, syslog, termios
         time, timing, xreadlines

    4) Once the python executable and library have been built, make
       will execute setup.py, which will attempt to build remaining
       extensions and link them dynamically. Each of these attempts
       will fail but should not halt the make process. This is
       normal.

    5) Running "make test" uses a lot of resources and causes
       problems on our system. You might want to try running tests
       singly or in small groups.

SGI: SGI’s standard «make» utility (/bin/make or /usr/bin/make)
does not check whether a command actually changed the file it
is supposed to build. This means that whenever you say «make»
it will redo the link step. The remedy is to use SGI’s much
smarter «smake» utility (/usr/sbin/smake), or GNU make. If
you set the first line of the Makefile to #!/usr/sbin/smake
smake will be invoked by make (likewise for GNU make).

    WARNING: There are bugs in the optimizer of some versions of
    SGI's compilers that can cause bus errors or other strange
    behavior, especially on numerical operations.  To avoid this,
    try building with "make OPT=".

OS/2: If you are running Warp3 or Warp4 and have IBM’s VisualAge C/C++
compiler installed, just change into the pcos2vacpp directory
and type NMAKE. Threading and sockets are supported by default
in the resulting binaries of PYTHON15.DLL and PYTHON.EXE.

Monterey (64-bit AIX): The current Monterey C compiler (Visual Age)
uses the OBJECT_MODE={32|64} environment variable to set the
compilation mode to either 32-bit or 64-bit (32-bit mode is
the default). Presumably you want 64-bit compilation mode for
this 64-bit OS. As a result you must first set OBJECT_MODE=64
in your environment before configuring (./configure) or
building (make) Python on Monterey.

Reliant UNIX: The thread support does not compile on Reliant UNIX, and
there is a (minor) problem in the configure script for that
platform as well. This should be resolved in time for a
future release.

MacOSX: The tests will crash on both 10.1 and 10.2 with SEGV in
test_re and test_sre due to the small default stack size. If
you set the stack size to 2048 before doing a «make test» the
failure can be avoided. If you’re using the tcsh or csh shells,
use «limit stacksize 2048» and for the bash shell (the default
as of OSX 10.3), use «ulimit -s 2048».

    On naked Darwin you may want to add the configure option
    "--disable-toolbox-glue" to disable the glue code for the Carbon
    interface modules. The modules themselves are currently only built
    if you add the --enable-framework option, see below.

    On a clean OSX /usr/local does not exist. Do a
    "sudo mkdir -m 775 /usr/local"
    before you do a make install. It is probably not a good idea to
    do "sudo make install" which installs everything as superuser,
    as this may later cause problems when installing distutils-based
    additions.

    Some people have reported problems building Python after using "fink"
    to install additional unix software. Disabling fink (remove all 
    references to /sw from your .profile or .login) should solve this.

    You may want to try the configure option "--enable-framework"
    which installs Python as a framework. The location can be set
    as argument to the --enable-framework option (default
    /Library/Frameworks). A framework install is probably needed if you
    want to use any Aqua-based GUI toolkit (whether Tkinter, wxPython,
    Carbon, Cocoa or anything else).

You may also want to try the configure option "--enable-universalsdk"
which builds Python as a universal binary with support for the 
i386 and PPC architectures. This requires Xcode 2.1 or later to build.

    See Mac/OSX/README for more information on framework and 
universal builds.

Cygwin: With recent (relative to the time of writing, 2001-12-19)
Cygwin installations, there are problems with the interaction
of dynamic linking and fork(). This manifests itself in build
failures during the execution of setup.py.

    There are two workarounds that both enable Python (albeit
    without threading support) to build and pass all tests on
    NT/2000 (and most likely XP as well, though reports of testing
    on XP would be appreciated).

    The workarounds:

    (a) the band-aid fix is to link the _socket module statically
    rather than dynamically (which is the default).

    To do this, run "./configure --with-threads=no" including any
    other options you need (--prefix, etc.).  Then in Modules/Setup
    uncomment the lines:

    #SSL=/usr/local/ssl
    #_socket socketmodule.c 
    #       -DUSE_SSL -I$(SSL)/include -I$(SSL)/include/openssl 
    #       -L$(SSL)/lib -lssl -lcrypto

    and remove "local/" from the SSL variable.  Finally, just run
    "make"!

    (b) The "proper" fix is to rebase the Cygwin DLLs to prevent
    base address conflicts.  Details on how to do this can be
    found in the following mail:

       http://sources.redhat.com/ml/cygwin/2001-12/msg00894.html

    It is hoped that a version of this solution will be
    incorporated into the Cygwin distribution fairly soon.

    Two additional problems:

    (1) Threading support should still be disabled due to a known
    bug in Cygwin pthreads that causes test_threadedtempfile to
    hang.

    (2) The _curses module does not build.  This is a known
    Cygwin ncurses problem that should be resolved the next time
    that this package is released.

    On older versions of Cygwin, test_poll may hang and test_strftime
    may fail.

    The situation on 9X/Me is not accurately known at present.
    Some time ago, there were reports that the following
    regression tests failed:

        test_pwd
        test_select (hang)
        test_socket

    Due to the test_select hang on 9X/Me, one should run the
    regression test using the following:

        make TESTOPTS='-l -x test_select' test

    News regarding these platforms with more recent Cygwin
    versions would be appreciated!

AtheOS: From Octavian Cerna :

    Before building:

        Make sure you have shared versions of the libraries you
        want to use with Python. You will have to compile them
        yourself, or download precompiled packages.

        Recommended libraries:

            ncurses-4.2
            readline-4.2a
            zlib-1.1.4

    Build:

        $ ./configure --prefix=/usr/python
        $ make

        Python is always built as a shared library, otherwise
        dynamic loading would not work.

    Testing:

        $ make test

    Install:

        # make install
        # pkgmanager -a /usr/python


    AtheOS issues:

        - large file support: due to a stdio bug in glibc/libio,
          access to large files may not work correctly.  fseeko()
          tries to seek to a negative offset.  ftello() returns a
          negative offset, it looks like a 32->64bit
          sign-extension issue.  The lowlevel functions (open,
          lseek, etc) are OK.
        - sockets: AF_UNIX is defined in the C library and in
          Python, but not implemented in the system.
        - select: poll is available in the C library, but does not
          work (It does not return POLLNVAL for bad fds and
          hangs).
        - posix: statvfs and fstatvfs always return ENOSYS.
        - disabled modules:
            - mmap: not yet implemented in AtheOS
            - nis: broken (on an unconfigured system
              yp_get_default_domain() returns junk instead of
              error)
            - dl: dynamic loading doesn't work via dlopen()
            - resource: getrimit and setrlimit are not yet
              implemented

        - if you are getting segmentation faults, you probably are
          low on memory.  AtheOS doesn't handle very well an
          out-of-memory condition and simply SEGVs the process.

    Tested on:

        AtheOS-0.3.7
        gcc-2.95
        binutils-2.10
        make-3.78

Configuring the bsddb and dbm modules

Beginning with Python version 2.3, the PyBsddb package
http://pybsddb.sf.net/ was adopted into Python as the bsddb package,
exposing a set of package-level functions which provide
backwards-compatible behavior. Only versions 3.3 through 4.4 of
Sleepycat’s libraries provide the necessary API, so older versions
aren’t supported through this interface. The old bsddb module has
been retained as bsddb185, though it is not built by default. Users
wishing to use it will have to tweak Modules/Setup to build it. The
dbm module will still be built against the Sleepycat libraries if
other preferred alternatives (ndbm, gdbm) are not found.

Building the sqlite3 module

To build the sqlite3 module, you’ll need the sqlite3 or libsqlite3
packages installed, including the header files. Many modern operating
systems distribute the headers in a separate package to the library —
often it will be the same name as the main package, but with a -dev or
-devel suffix.

The version of pysqlite2 that’s including in Python needs sqlite3 3.0.8
or later. setup.py attempts to check that it can find a correct version.

Configuring threads

As of Python 2.0, threads are enabled by default. If you wish to
compile without threads, or if your thread support is broken, pass the
—with-threads=no switch to configure. Unfortunately, on some
platforms, additional compiler and/or linker options are required for
threads to work properly. Below is a table of those options,
collected by Bill Janssen. We would love to automate this process
more, but the information below is not enough to write a patch for the
configure.in file, so manual intervention is required. If you patch
the configure.in file and are confident that the patch works, please
send in the patch. (Don’t bother patching the configure script itself
— it is regenerated each time the configure.in file changes.)

Compiler switches for threads
………………………..

The definition of _REENTRANT should be configured automatically, if
that does not work on your system, or if _REENTRANT is defined
incorrectly, please report that as a bug.

OS/Compiler/threads                     Switches for use with threads
(POSIX is draft 10, DCE is draft 4)     compile & link

SunOS 5.{1-5}/{gcc,SunPro cc}/solaris   -mt
SunOS 5.5/{gcc,SunPro cc}/POSIX         (nothing)
DEC OSF/1 3.x/cc/DCE                    -threads
        (butenhof@zko.dec.com)
Digital UNIX 4.x/cc/DCE                 -threads
        (butenhof@zko.dec.com)
Digital UNIX 4.x/cc/POSIX               -pthread
        (butenhof@zko.dec.com)
AIX 4.1.4/cc_r/d7                       (nothing)
        (buhrt@iquest.net)
AIX 4.1.4/cc_r4/DCE                     (nothing)
        (buhrt@iquest.net)
IRIX 6.2/cc/POSIX                       (nothing)
        (robertl@cwi.nl)

Linker (ld) libraries and flags for threads
…………………………………….

OS/threads                          Libraries/switches for use with threads

SunOS 5.{1-5}/solaris               -lthread
SunOS 5.5/POSIX                     -lpthread
DEC OSF/1 3.x/DCE                   -lpthreads -lmach -lc_r -lc
        (butenhof@zko.dec.com)
Digital UNIX 4.x/DCE                -lpthreads -lpthread -lmach -lexc -lc
        (butenhof@zko.dec.com)
Digital UNIX 4.x/POSIX              -lpthread -lmach -lexc -lc
        (butenhof@zko.dec.com)
AIX 4.1.4/{draft7,DCE}              (nothing)
        (buhrt@iquest.net)
IRIX 6.2/POSIX                      -lpthread
        (jph@emilia.engr.sgi.com)

Building a shared libpython

Starting with Python 2.3, the majority of the interpreter can be built
into a shared library, which can then be used by the interpreter
executable, and by applications embedding Python. To enable this feature,
configure with —enable-shared.

If you enable this feature, the same object files will be used to create
a static library. In particular, the static library will contain object
files using position-independent code (PIC) on platforms where PIC flags
are needed for the shared library.

Configuring additional built-in modules

Starting with Python 2.1, the setup.py script at the top of the source
distribution attempts to detect which modules can be built and
automatically compiles them. Autodetection doesn’t always work, so
you can still customize the configuration by editing the Modules/Setup
file; but this should be considered a last resort. The rest of this
section only applies if you decide to edit the Modules/Setup file.
You also need this to enable static linking of certain modules (which
is needed to enable profiling on some systems).

This file is initially copied from Setup.dist by the configure script;
if it does not exist yet, create it by copying Modules/Setup.dist
yourself (configure will never overwrite it). Never edit Setup.dist
— always edit Setup or Setup.local (see below). Read the comments in
the file for information on what kind of edits are allowed. When you
have edited Setup in the Modules directory, the interpreter will
automatically be rebuilt the next time you run make (in the toplevel
directory).

Many useful modules can be built on any Unix system, but some optional
modules can’t be reliably autodetected. Often the quickest way to
determine whether a particular module works or not is to see if it
will build: enable it in Setup, then if you get compilation or link
errors, disable it — you’re either missing support or need to adjust
the compilation and linking parameters for that module.

On SGI IRIX, there are modules that interface to many SGI specific
system libraries, e.g. the GL library and the audio hardware. These
modules will not be built by the setup.py script.

In addition to the file Setup, you can also edit the file Setup.local.
(the makesetup script processes both). You may find it more
convenient to edit Setup.local and leave Setup alone. Then, when
installing a new Python version, you can copy your old Setup.local
file.

Setting the optimization/debugging options

If you want or need to change the optimization/debugging options for
the C compiler, assign to the OPT variable on the toplevel make
command; e.g. «make OPT=-g» will build a debugging version of Python
on most platforms. The default is OPT=-O; a value for OPT in the
environment when the configure script is run overrides this default
(likewise for CC; and the initial value for LIBS is used as the base
set of libraries to link with).

When compiling with GCC, the default value of OPT will also include
the -Wall and -Wstrict-prototypes options.

Additional debugging code to help debug memory management problems can
be enabled by using the —with-pydebug option to the configure script.

For flags that change binary compatibility, use the EXTRA_CFLAGS
variable.

Profiling

If you want C profiling turned on, the easiest way is to run configure
with the CC environment variable to the necessary compiler
invocation. For example, on Linux, this works for profiling using
gprof(1):

Note that on Linux, gprof apparently does not work for shared
libraries. The Makefile/Setup mechanism can be used to compile and
link most extension modules statically.

Testing

To test the interpreter, type «make test» in the top-level directory.
This runs the test set twice (once with no compiled files, once with
the compiled files left by the previous test run). The test set
produces some output. You can generally ignore the messages about
skipped tests due to optional features which can’t be imported.
If a message is printed about a failed test or a traceback or core
dump is produced, something is wrong. On some Linux systems (those
that are not yet using glibc 6), test_strftime fails due to a
non-standard implementation of strftime() in the C library. Please
ignore this, or upgrade to glibc version 6.

IMPORTANT: If the tests fail and you decide to mail a bug report,
don’t include the output of «make test». It is useless. Run the
failing test manually, as follows:

    ./python ./Lib/test/test_whatever.py

(substituting the top of the source tree for ‘.’ if you built in a
different directory). This runs the test in verbose mode.

Installing

To install the Python binary, library modules, shared library modules
(see below), include files, configuration files, and the manual page,
just type

This will install all platform-independent files in subdirectories of
the directory given with the —prefix option to configure or to the
prefix' Make variable (default /usr/local). All binary and other platform-specific files will be installed in subdirectories if the directory given by --exec-prefix or the exec_prefix’ Make variable
(defaults to the —prefix directory) is given.

If DESTDIR is set, it will be taken as the root directory of the
installation, and files will be installed into $(DESTDIR)$(prefix),
$(DESTDIR)$(exec_prefix), etc.

All subdirectories created will have Python’s version number in their
name, e.g. the library modules are installed in
«/usr/local/lib/python/» by default, where is the
. release number (e.g. «2.1»). The Python binary is
installed as «python» and a hard link named «python» is
created. The only file not installed with a version number in its
name is the manual page, installed as «/usr/local/man/man1/python.1»
by default.

If you have a previous installation of Python that you don’t
want to replace yet, use

This installs the same set of files as «make install» except it
doesn’t create the hard link to «python» named «python» and
it doesn’t install the manual page at all.

The only thing you may have to install manually is the Python mode for
Emacs found in Misc/python-mode.el. (But then again, more recent
versions of Emacs may already have it.) Follow the instructions that
came with Emacs for installation of site-specific files.

On Mac OS X, if you have configured Python with —enable-framework, you
should use «make frameworkinstall» to do the installation. Note that this
installs the Python executable in a place that is not normally on your
PATH, you may want to set up a symlink in /usr/local/bin.

Configuration options and variables

Some special cases are handled by passing options to the configure
script.

WARNING: if you rerun the configure script with different options, you
must run «make clean» before rebuilding. Exceptions to this rule:
after changing —prefix or —exec-prefix, all you need to do is remove
Modules/getpath.o.

—with(out)-gcc: The configure script uses gcc (the GNU C compiler) if
it finds it. If you don’t want this, or if this compiler is
installed but broken on your platform, pass the option
—without-gcc. You can also pass «CC=cc» (or whatever the
name of the proper C compiler is) in the environment, but the
advantage of using —without-gcc is that this option is
remembered by the config.status script for its —recheck
option.

—prefix, —exec-prefix: If you want to install the binaries and the
Python library somewhere else than in /usr/local/{bin,lib},
you can pass the option —prefix=DIRECTORY; the interpreter
binary will be installed as DIRECTORY/bin/python and the
library files as DIRECTORY/lib/python/*. If you pass
—exec-prefix=DIRECTORY (as well) this overrides the
installation prefix for architecture-dependent files (like the
interpreter binary). Note that —prefix=DIRECTORY also
affects the default module search path (sys.path), when
Modules/config.c is compiled. Passing make the option
prefix=DIRECTORY (and/or exec_prefix=DIRECTORY) overrides the
prefix set at configuration time; this may be more convenient
than re-running the configure script if you change your mind
about the install prefix.

—with-readline: This option is no longer supported. GNU
readline is automatically enabled by setup.py when present.

—with-threads: On most Unix systems, you can now use multiple
threads, and support for this is enabled by default. To
disable this, pass —with-threads=no. If the library required
for threads lives in a peculiar place, you can use
—with-thread=DIRECTORY. IMPORTANT: run «make clean» after
changing (either enabling or disabling) this option, or you
will get link errors! Note: for DEC Unix use
—with-dec-threads instead.

—with-sgi-dl: On SGI IRIX 4, dynamic loading of extension modules is
supported by the «dl» library by Jack Jansen, which is
ftp’able from ftp://ftp.cwi.nl/pub/dynload/dl-1.6.tar.Z.
This is enabled (after you’ve ftp’ed and compiled the dl
library) by passing —with-sgi-dl=DIRECTORY where DIRECTORY
is the absolute pathname of the dl library. (Don’t bother on
IRIX 5, it already has dynamic linking using SunOS style
shared libraries.) THIS OPTION IS UNSUPPORTED.

—with-dl-dld: Dynamic loading of modules is rumored to be supported
on some other systems: VAX (Ultrix), Sun3 (SunOS 3.4), Sequent
Symmetry (Dynix), and Atari ST. This is done using a
combination of the GNU dynamic loading package
(ftp://ftp.cwi.nl/pub/dynload/dl-dld-1.1.tar.Z) and an
emulation of the SGI dl library mentioned above (the emulation
can be found at
ftp://ftp.cwi.nl/pub/dynload/dld-3.2.3.tar.Z). To
enable this, ftp and compile both libraries, then call
configure, passing it the option
—with-dl-dld=DL_DIRECTORY,DLD_DIRECTORY where DL_DIRECTORY is
the absolute pathname of the dl emulation library and
DLD_DIRECTORY is the absolute pathname of the GNU dld library.
(Don’t bother on SunOS 4 or 5, they already have dynamic
linking using shared libraries.) THIS OPTION IS UNSUPPORTED.

—with-libm, —with-libc: It is possible to specify alternative
versions for the Math library (default -lm) and the C library
(default the empty string) using the options
—with-libm=STRING and —with-libc=STRING, respectively. For
example, if your system requires that you pass -lc_s to the C
compiler to use the shared C library, you can pass
—with-libc=-lc_s. These libraries are passed after all other
libraries, the C library last.

—with-libs=’libs’: Add ‘libs’ to the LIBS that the python interpreter
is linked against.

—with-cxx-main=: If you plan to use C++ extension modules,
then — on some platforms — you need to compile python’s main()
function with the C++ compiler. With this option, make will use
to compile main() and to link the python executable.
It is likely that the resulting executable depends on the C++
runtime library of . (The default is —without-cxx-main.)

    There are platforms that do not require you to build Python
    with a C++ compiler in order to use C++ extension modules.
    E.g., x86 Linux with ELF shared binaries and GCC 3.x, 4.x is such
    a platform. We recommend that you configure Python
    --without-cxx-main on those platforms because a mismatch
    between the C++ compiler version used to build Python and to
    build a C++ extension module is likely to cause a crash at
    runtime.

    The Python installation also stores the variable CXX that
    determines, e.g., the C++ compiler distutils calls by default
    to build C++ extensions. If you set CXX on the configure command
    line to any string of non-zero length, then configure won't
    change CXX. If you do not preset CXX but pass
    --with-cxx-main=<compiler>, then configure sets CXX=<compiler>.
    In all other cases, configure looks for a C++ compiler by
    some common names (c++, g++, gcc, CC, cxx, cc++, cl) and sets
    CXX to the first compiler it finds. If it does not find any
    C++ compiler, then it sets CXX="".

    Similarly, if you want to change the command used to link the
    python executable, then set LINKCC on the configure command line.

—with-pydebug: Enable additional debugging code to help track down
memory management problems. This allows printing a list of all
live objects when the interpreter terminates.

—with(out)-universal-newlines: enable reading of text files with
foreign newline convention (default: enabled). In other words,
any of r, n or rn is acceptable as end-of-line character.
If enabled import and execfile will automatically accept any newline
in files. Python code can open a file with open(file, ‘U’) to
read it in universal newline mode. THIS OPTION IS UNSUPPORTED.

—with-tsc: Profile using the Pentium timestamping counter (TSC).

—with-system-ffi: Build the _ctypes extension module using an ffi
library installed on the system.

Building for multiple architectures (using the VPATH feature)

If your file system is shared between multiple architectures, it
usually is not necessary to make copies of the sources for each
architecture you want to support. If the make program supports the
VPATH feature, you can create an empty build directory for each
architecture, and in each directory run the configure script (on the
appropriate machine with the appropriate options). This creates the
necessary subdirectories and the Makefiles therein. The Makefiles
contain a line VPATH=… which points to a directory containing the
actual sources. (On SGI systems, use «smake -J1» instead of «make» if
you use VPATH — don’t try gnumake.)

For example, the following is all you need to build a minimal Python
in /usr/tmp/python (assuming ~guido/src/python is the toplevel
directory and you want to build in /usr/tmp/python):

    $ mkdir /usr/tmp/python
    $ cd /usr/tmp/python
    $ ~guido/src/python/configure
    [...]
    $ make
    [...]
    $

Note that configure copies the original Setup file to the build
directory if it finds no Setup file there. This means that you can
edit the Setup file for each architecture independently. For this
reason, subsequent changes to the original Setup file are not tracked
automatically, as they might overwrite local changes. To force a copy
of a changed original Setup file, delete the target Setup file. (The
makesetup script supports multiple input files, so if you want to be
fancy you can change the rules to create an empty Setup.local if it
doesn’t exist and run it with arguments $(srcdir)/Setup Setup.local;
however this assumes that you only need to add modules.)

Building on non-UNIX systems

For Windows (2000/NT/ME/98/95), assuming you have MS VC++ 7.1, the
project files are in PCbuild, the workspace is pcbuild.dsw. See
PCbuildreadme.txt for detailed instructions.

For other non-Unix Windows compilers, in particular MS VC++ 6.0 and
for OS/2, enter the directory «PC» and read the file «readme.txt».

For the Mac, a separate source distribution will be made available,
for use with the CodeWarrior compiler. If you are interested in Mac
development, join the PythonMac Special Interest Group
(http://www.python.org/sigs/pythonmac-sig/, or send email to
pythonmac-sig-request@python.org).

Of course, there are also binary distributions available for these
platforms — see http://www.python.org/.

To port Python to a new non-UNIX system, you will have to fake the
effect of running the configure script manually (for Mac and PC, this
has already been done for you). A good start is to copy the file
pyconfig.h.in to pyconfig.h and edit the latter to reflect the actual
configuration of your system. Most symbols must simply be defined as
1 only if the corresponding feature is present and can be left alone
otherwise; however the *_t type symbols must be defined as some
variant of int if they need to be defined at all.

For all platforms, it’s important that the build arrange to define the
preprocessor symbol NDEBUG on the compiler command line in a release
build of Python (else assert() calls remain in the code, hurting
release-build performance). The Unix, Windows and Mac builds already
do this.

Miscellaneous issues

Emacs mode

There’s an excellent Emacs editing mode for Python code; see the file
Misc/python-mode.el. Originally written by the famous Tim Peters, it
is now maintained by the equally famous Barry Warsaw (it’s no
coincidence that they now both work on the same team). The latest
version, along with various other contributed Python-related Emacs
goodies, is online at http://www.python.org/emacs/python-mode. And
if you are planning to edit the Python C code, please pick up the
latest version of CC Mode http://www.python.org/emacs/cc-mode; it
contains a «python» style used throughout most of the Python C source
files. (Newer versions of Emacs or XEmacs may already come with the
latest version of python-mode.)

Tkinter

The setup.py script automatically configures this when it detects a
usable Tcl/Tk installation. This requires Tcl/Tk version 8.0 or
higher.

For more Tkinter information, see the Tkinter Resource page:
http://www.python.org/topics/tkinter/

There are demos in the Demo/tkinter directory.

Note that there’s a Python module called «Tkinter» (capital T) which
lives in Lib/lib-tk/Tkinter.py, and a C module called «_tkinter»
(lower case t and leading underscore) which lives in
Modules/_tkinter.c. Demos and normal Tk applications import only the
Python Tkinter module — only the latter imports the C _tkinter
module. In order to find the C _tkinter module, it must be compiled
and linked into the Python interpreter — the setup.py script does
this. In order to find the Python Tkinter module, sys.path must be
set correctly — normal installation takes care of this.

Distribution structure

Most subdirectories have their own README files. Most files have
comments.

BeOS/ Files specific to the BeOS port
Demo/ Demonstration scripts, modules and programs
Doc/ Documentation sources (LaTeX)
Grammar/ Input for the parser generator
Include/ Public header files
LICENSE Licensing information
Lib/ Python library modules
Mac/ Macintosh specific resources
Makefile.pre.in Source from which config.status creates the Makefile.pre
Misc/ Miscellaneous useful files
Modules/ Implementation of most built-in modules
Objects/ Implementation of most built-in object types
PC/ Files specific to PC ports (DOS, Windows, OS/2)
PCbuild/ Build directory for Microsoft Visual C++
Parser/ The parser and tokenizer and their input handling
Python/ The byte-compiler and interpreter
README The file you’re reading now
Tools/ Some useful programs written in Python
pyconfig.h.in Source from which pyconfig.h is created (GNU autoheader output)
configure Configuration shell script (GNU autoconf output)
configure.in Configuration specification (input for GNU autoconf)
install-sh Shell script used to install files
setup.py Python script used to build extension modules

The following files will (may) be created in the toplevel directory by
the configuration and build processes:

Makefile Build rules
Makefile.pre Build rules before running Modules/makesetup
buildno Keeps track of the build number
config.cache Cache of configuration variables
pyconfig.h Configuration header
config.log Log from last configure run
config.status Status from last run of the configure script
getbuildinfo.o Object file from Modules/getbuildinfo.c
libpython.a The library archive
python The executable interpreter
tags, TAGS Tags files for vi and Emacs

That’s all, folks!

—Guido van Rossum (home page: http://www.python.org/~guido/)

Источник

A library for running Python 2 code from a Python 3 application.

Effortlessly harness the power and convenience of Python 2… in Python 3!

Why?

Why not??

This library was created for more whimsical than practical reasons. In theory,
it could be used to interface with legacy Python 2 code which for one reason or
another cannot be ported to Python 3.

Installation

python2 requires a working install of both Python 2 and Python 3.
Currently the library has only been tested with Python 2.7 and Python 3.4, 3.5,
and 3.6.

To install the package:

pip install -U python2

If using virtualenvs, you will need to create separate Python 2 and 3
virtualenvs, and install the package into both.

Usage

To begin working with Python 2, import the package in Python 3 and create a new
Python2 object:

>>> from python2.client import Python2
>>> py2 = Python2('/path/to/python2/executable')

This object is our gateway to the Python 2 world. Python 2 builtins can be
accessed as attributes of the Python2 object. Let’s use Python 2’s
__import__() function to import the deprecated sha module, which was
removed in Python 3:

>>> py2_sha = py2.__import__('sha')
>>> py2_sha.sha('abc')
<Py2Object <sha1 HASH object @ 0x107463c30>>

Ahh, just like the good ol’ days. You can deprecate a module but you can’t
deprecate the human spirit!

We can use the Python2.project() method to convert Python 3 objects to
Python 2:

>>> py2.project(1)
<Py2Object 1>
>>> py2.project('foo')
<Py2Object u'foo'>

You can use Python2.lift() to lift Python 2 objects back to Python 3. For
container types, use Python2.deeplift() to recursively perform the lifting.
Py2Object instances have special properties _ and __ to perform the
equivalent operations:

>>> o = py2.project([1, 2, 3])
>>> o
<Py2Object [1, 2, 3]>
>>> o._
[<Py2Object 1>, <Py2Object 2>, <Py2Object 3>]
>>> o.__
[1, 2, 3]

Python 2 objects can be used pretty much like regular Python 3 objects. You
can also freely mix and match with Python 3 builtin types:

>>> x = py2.project(1)
>>> x
<Py2Object 1>
>>> str(x)
'1'
>>> x + 1
<Py2Object 2>
>>> d = py2.dict(foo=x, bar=None)
>>> d['foo'] is x
True
>>> del d['foo']
>>> d
<Py2Object {u'bar': None}>
>>> d.__
{'bar': None}

If you just want to execute some Python 2 code directly, you can use the
Python2.exec() method. This method accepts a string containing Python 2
code and an optional dict representing the scope to execute the code in, and
returns the resulting scope after executing the code. This can be used to
define new Python 2 classes and functions:

>>> scope = py2.exec("""
... def foo(x):
...     return x + 1
... """)
>>> foo = scope['foo']
>>> foo(2)
<Py2Object 3>

If an exception occurs in Python 2, a Py2Error will be thrown by the
client. The Python 2 exception is stored as the exception attribute of the
Py2Error object. The underlying traceback is attached to the Python 2
exception as the __traceback__ attribute.

>>> py2.int('asdf')
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  ...
python2.client.exceptions.Py2Error: ValueError: invalid literal for int() with base 10: 'asdf'

When you’re done using Python 2, you can end the session by calling the
Python2.shutdown() method. You can also use the Python2 object as a
context manager to automatically do the same thing when exiting the context.

>>> py2.shutdown()

Testing

This package uses Tox for testing. Tests are not included in the Python dist,
so you will need to clone the repo to run them. To run the unit tests, install
Tox and run the following command from the project’s base directory:

tox

After running tox, you can run the client-server integration tests with the
‘integration_tests.sh’ script. This script takes two arguments specifying the
Tox virtualenvs to use for Python 2 and 3, respectively:

./integration_tests.sh py27 py36

To modify the behavior of Tox, you can set the PYTEST_ADDOPTS variable.
For example, you can set the -x flag to abort after the first test
failure:

export PYTEST_ADDOPTS=-x

You can use the -n NUM flag to parallelize the tests using the
pytest-xdist plugin This adds some overhead to the test setup, so this
option is primarily useful for speeding up the integration tests.

export PYTEST_ADDOPTS=’-n 4’

Caveats

Supported types

Projection is only supported for basic builtin types. Other objects cannot be
projected to Python 2. The supported types are: bool, int, float,
complex, bytes, unicode, bytearray, range, slice,
list, tuple, set, frozenset, and dict. The None,
NotImplemented, and Ellipsis singletons are also supported.

In particular, Python 3 functions, types, and instances of user-defined classes
cannot currently be projected into Python 2.

Type introspection

The Py2Object class implements many “magic methods” from the Python 3 data
model. As a result, a Py2Object appears to be callable, iterable, etc.,
even if the underlying object is not. Attempting to perform such operations may
result in a Py2Error.

If you need to introspect a Python 2 object, use the corresponding Python 2
builtin functions. For example:

>>> i = py2.project(1)
>>> py2.callable(i)
<Py2Object False>
>>> py2.isinstance(i, py2.int)
<Py2Object True>

String types

In Python 2, str objects are raw byte strings, while in Python 3 they are
Unicode strings. This can lead to some confusion, as projecting a Python 3
str will result in a Python 2 unicode object, while lifting a Python 2
str will return a Python 3 bytes object.

>>> py2.project('foo')
<Py2Object u'foo'>
>>> py2.lift(py2.str(123))
b'123'

Division

The behavior of the division operator changed with PEP 238. This created
two alternate division operations, “true division” and “classic division”.
Classic division was removed in Python 3.

To respect this change, when two Py2Object s are divided, classic division
is used. When a Py2Object divides or is divided by a Python 3 value, true division is used.

>>> i = py2.project(1)
>>> j = py2.project(2)
>>> i / j  # classic division
<Py2Object 0>
>>> i / 2  # true division
<Py2Object 0.5>
>>> 1 / j  # true division
<Py2Object 0.5>

Further discussion

How it works

When you launch a Python 2 session, the library spawns a child process running
Python 2. This child process runs a server that listens for commands from
the Python 3 client. For each command, the server performs an operation in
Python 2 and returns the result either as an encoded value made up of
supported types, or a reference to a Python 2 object stored on the server.

On the client side, the library wraps Python 2 references with the
Py2Object class. This class implements many of the “magic methods” of the
Python 3 data model by sending commands to the Python 2 server to perform
the appropriate operation on the underlying Python 2 object.

Call-by-value semantics

When projecting a value or calling a Python 2 function with Python 3 arguments,
the arguments will be passed to Python 2 “by value”, that is, by encoding the
value of the argument to be decoded by the server. When using a Python 2
object, the object is stored in the Python 2 session and is passed “by
reference”.

This has some implications for the semantics of Python 2 functions. Suppose we
have a Python 2 function that mutates a list. If we pass this function a
Python 3 list, the list will be copied into Python 2 and the copy will be
mutated, but the original will not be modified:

>>> f = py2.eval("lambda l: l.append(1)")
>>> l = []
>>> f(l)
<Py2Object None>
>>> l
[]

However, if we project the list into Python 2 before passing it to the
function, then we can observe the modifications on the projected list:

>>> py2_l = py2.project(l)
>>> f(py2_l)
<Py2Object None>
>>> py2_l
<Py2Object [1]>

Return semantics

Returning generally occurs by reference except for operations that require a
specific return type (str(), int(), etc.). The main reason for this is
that returning by value may lose information about object identity that needs
to be preserved. Return values can be easily lifted to Python 2 if desired.

Object identity and lifespan

Each Python 2 object returned by the server is represented by a unique
Py2Object. This means that the is operator can be used to determine if
two Py2Object s refer to the same underlying object.

The Python 2 server stores all objects it returns, to prevent them from being
deallocated. When the corresponding Py2Object is deallocated in the Python
3 process, the underlying Python 2 object will be removed from the server cache
to allow it to be deallocated as appropriate.

Encoding algorithm

This library uses a simple JSON encoding for supported types. For a given
function call, each unique object will only be encoded once. This means that
data structures with circular references are supported. For a detailed
description of the algorithm, see the python2.shared.codec module.

Possible improvements

Python 2 types

Currently there is a single type for Python 2 objects in Python 3,
Py2Object. An alternate strategy would be to dynamically create Python 3
classes for each Python 2 type encountered, and create proxy objects as
instances of these classes.

The main benefit of this change would be better type introspection for Python 2
objects (see the discussion at Type introspection). However, it would be
more cumbersome and incur a performance cost, since the client would need to
know the type of each object and the methods supported by that type.
Additionally, this approach would not fully support the dynamic nature of the
Python type system, since the proxied type would not reflect changes to the
underlying type such as adding or removing methods.

This would require the server to return the object type for references, and
some mechanism for the client to introspect Python 2 types. The client would
cache types for the lifetime of the Python 2 session, with a mechanism to
explicitly refresh a type to pick up any changes that had occurred in Python 2.

Bootstrapping the type system might be a little tricky. We would want to
create a type Py2type such all proxy types are instances of, including
«Py2type« itself. We would also probably want a base type for all proxy
objects, including types.

Python 3 proxy objects in Python 2

Currently the relationship between client and server is asymmetrical. The
client has a representation of Python 2 objects, but the server does not have
a way to represent Python 3 objects. We might like to add such a mechanism.
This would mean that instead of the simple request-response pattern from client
to server we have now, there would be the possibility of callbacks. In effect,
the two processes would act more like coroutines with the flow of control
passing back and forth between them.

Better Python version support

We could extend support to more Python 2 and 3 versions.

Similar projects

After writing this library, I discovered that I’m not the only one to have had
this idea. Sux is a library that provides similar functionality, with some
notable differences:

The library is much smaller and more lightweight, and only needs to be
installed in the Python 3 environment to work.
The main emphasis is on imports and function calls, which makes sense since
these are the most important operations for the using legacy packages. Most
other operators (e.g. arithmetic operators) are not supported.
The library uses Pickle to communicate between the Python 2 and 3 processes.
This is a good idea and I should probably have done the same, although I had
fun implementing the current encoding algorithm.

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