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Travis Oliphant: SciPy, NumPy, and Fostering Scientific Python

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Manage episode 501750547 series 2637014
Conteúdo fornecido por Real Python. Todo o conteúdo do podcast, incluindo episódios, gráficos e descrições de podcast, é carregado e fornecido diretamente por Real Python ou por seu parceiro de plataforma de podcast. Se você acredita que alguém está usando seu trabalho protegido por direitos autorais sem sua permissão, siga o processo descrito aqui https://pt.player.fm/legal.

What went into developing the open-source Python tools data scientists use every day? This week on the show, we talk with Travis Oliphant about his work on SciPy, NumPy, Numba, and many other contributions to the Python scientific community.

Travis discusses his initial involvement in the open-source community and how he discovered Python while working in biomedical imaging. He was trying to find ways to manage large sets of numerical data, which led to his initial contributions and collaborations in building scientific libraries.

His appearance on the show coincides with the release of the Python documentary, in which he’s featured. We discuss the myriad organizations Travis founded, including Quansight, OpenTeams, and Anaconda. We dig into his underlying mission to continue fostering the growth of the open-source scientific computing community.

This episode is sponsored by InfluxData.

Course Spotlight: NumPy Techniques and Practical Examples

In this video course, you’ll learn how to use NumPy by exploring several interesting examples. You’ll read data from a file into an array and analyze structured arrays to perform a reconciliation. You’ll also learn how to quickly chart an analysis and turn a custom function into a vectorized function.

Topics:

  • 00:00:00 – Introduction
  • 00:02:41 – Python documentary
  • 00:07:44 – Getting involved in open source
  • 00:12:04 – Numeric Python
  • 00:15:36 – SciPy and the SciPy community
  • 00:17:35 – Starting to think about entrepreneurship
  • 00:18:16 – NumPy evolving from the work of Numeric
  • 00:22:01 – Sponsor: InfluxData
  • 00:22:53 – Python as controlling code for lower-level libraries
  • 00:23:37 – Numba open-source JIT compiler
  • 00:30:09 – Starting to build in Python before learning it all
  • 00:34:45 – Python as the language AI generates
  • 00:36:31 – Guilds and sharing knowledge
  • 00:40:15 – More NumPy backstory
  • 00:46:36 – Contributing to Python
  • 00:48:24 – Video Course Spotlight
  • 00:49:41 – The investment of companies in Python
  • 00:51:22 – Quansight and businesses in open source
  • 00:53:09 – Open Teams and Quansight details
  • 00:57:14 – NumFOCUS and Anaconda
  • 00:58:51 – FairOSS
  • 01:02:36 – Documenting these efforts
  • 01:05:37 – What are you excited about in the world of Python?
  • 01:07:12 – What do you want to learn next?
  • 01:08:10 – How can people follow your work online?
  • 01:10:03 – Thanks and goodbye

Show Links:

Level up your Python skills with our expert-led courses:

Support the podcast & join our community of Pythonistas

  continue reading

277 episódios

Artwork
iconCompartilhar
 
Manage episode 501750547 series 2637014
Conteúdo fornecido por Real Python. Todo o conteúdo do podcast, incluindo episódios, gráficos e descrições de podcast, é carregado e fornecido diretamente por Real Python ou por seu parceiro de plataforma de podcast. Se você acredita que alguém está usando seu trabalho protegido por direitos autorais sem sua permissão, siga o processo descrito aqui https://pt.player.fm/legal.

What went into developing the open-source Python tools data scientists use every day? This week on the show, we talk with Travis Oliphant about his work on SciPy, NumPy, Numba, and many other contributions to the Python scientific community.

Travis discusses his initial involvement in the open-source community and how he discovered Python while working in biomedical imaging. He was trying to find ways to manage large sets of numerical data, which led to his initial contributions and collaborations in building scientific libraries.

His appearance on the show coincides with the release of the Python documentary, in which he’s featured. We discuss the myriad organizations Travis founded, including Quansight, OpenTeams, and Anaconda. We dig into his underlying mission to continue fostering the growth of the open-source scientific computing community.

This episode is sponsored by InfluxData.

Course Spotlight: NumPy Techniques and Practical Examples

In this video course, you’ll learn how to use NumPy by exploring several interesting examples. You’ll read data from a file into an array and analyze structured arrays to perform a reconciliation. You’ll also learn how to quickly chart an analysis and turn a custom function into a vectorized function.

Topics:

  • 00:00:00 – Introduction
  • 00:02:41 – Python documentary
  • 00:07:44 – Getting involved in open source
  • 00:12:04 – Numeric Python
  • 00:15:36 – SciPy and the SciPy community
  • 00:17:35 – Starting to think about entrepreneurship
  • 00:18:16 – NumPy evolving from the work of Numeric
  • 00:22:01 – Sponsor: InfluxData
  • 00:22:53 – Python as controlling code for lower-level libraries
  • 00:23:37 – Numba open-source JIT compiler
  • 00:30:09 – Starting to build in Python before learning it all
  • 00:34:45 – Python as the language AI generates
  • 00:36:31 – Guilds and sharing knowledge
  • 00:40:15 – More NumPy backstory
  • 00:46:36 – Contributing to Python
  • 00:48:24 – Video Course Spotlight
  • 00:49:41 – The investment of companies in Python
  • 00:51:22 – Quansight and businesses in open source
  • 00:53:09 – Open Teams and Quansight details
  • 00:57:14 – NumFOCUS and Anaconda
  • 00:58:51 – FairOSS
  • 01:02:36 – Documenting these efforts
  • 01:05:37 – What are you excited about in the world of Python?
  • 01:07:12 – What do you want to learn next?
  • 01:08:10 – How can people follow your work online?
  • 01:10:03 – Thanks and goodbye

Show Links:

Level up your Python skills with our expert-led courses:

Support the podcast & join our community of Pythonistas

  continue reading

277 episódios

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