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Kandungan disediakan oleh Michael Kennedy and Michael Kennedy (@mkennedy). Semua kandungan podcast termasuk episod, grafik dan perihalan podcast dimuat naik dan disediakan terus oleh Michael Kennedy and Michael Kennedy (@mkennedy) atau rakan kongsi platform podcast mereka. Jika anda percaya seseorang menggunakan karya berhak cipta anda tanpa kebenaran anda, anda boleh mengikuti proses yang digariskan di sini https://ms.player.fm/legal.
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#474: Python Performance for Data Science

1:08:23
 
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Manage episode 435130638 series 3501439
Kandungan disediakan oleh Michael Kennedy and Michael Kennedy (@mkennedy). Semua kandungan podcast termasuk episod, grafik dan perihalan podcast dimuat naik dan disediakan terus oleh Michael Kennedy and Michael Kennedy (@mkennedy) atau rakan kongsi platform podcast mereka. Jika anda percaya seseorang menggunakan karya berhak cipta anda tanpa kebenaran anda, anda boleh mengikuti proses yang digariskan di sini https://ms.player.fm/legal.
Python performance has come a long way in recent times. And it's often the data scientists, with their computational algorithms and large quantities of data, who care the most about this form of performance. It's great to have Stan Seibert back on the show to talk about Python's performance for data scientists. We cover a wide range of tools and techniques that will be valuable for many Python developers and data scientists.
Episode sponsors
Posit
Talk Python Courses
Links from the show
Stan on Twitter: @seibert
Anaconda: anaconda.com
High Performance Python with Numba training: learning.anaconda.cloud
PEP 0703: peps.python.org
Python 3.13 gets a JIT: tonybaloney.github.io
Numba: numba.pydata.org
LanceDB: lancedb.com
Profiling tips: docs.python.org
Memray: github.com
Fil: a Python memory profiler for data scientists and scientists: pythonspeed.com
Rust: rust-lang.org
Granian Server: github.com
PIXIE at SciPy 2024: github.com
Free threading Progress: py-free-threading.github.io
Free Threading Compatibility: py-free-threading.github.io
caniuse.com: caniuse.com
SPy, presented at PyCon 2024: us.pycon.org
Watch this episode on YouTube: youtube.com
Episode transcripts: talkpython.fm
--- Stay in touch with us ---
Subscribe to us on YouTube: youtube.com
Follow Talk Python on Mastodon: talkpython
Follow Michael on Mastodon: mkennedy
  continue reading

477 episod

Artwork
iconKongsi
 
Manage episode 435130638 series 3501439
Kandungan disediakan oleh Michael Kennedy and Michael Kennedy (@mkennedy). Semua kandungan podcast termasuk episod, grafik dan perihalan podcast dimuat naik dan disediakan terus oleh Michael Kennedy and Michael Kennedy (@mkennedy) atau rakan kongsi platform podcast mereka. Jika anda percaya seseorang menggunakan karya berhak cipta anda tanpa kebenaran anda, anda boleh mengikuti proses yang digariskan di sini https://ms.player.fm/legal.
Python performance has come a long way in recent times. And it's often the data scientists, with their computational algorithms and large quantities of data, who care the most about this form of performance. It's great to have Stan Seibert back on the show to talk about Python's performance for data scientists. We cover a wide range of tools and techniques that will be valuable for many Python developers and data scientists.
Episode sponsors
Posit
Talk Python Courses
Links from the show
Stan on Twitter: @seibert
Anaconda: anaconda.com
High Performance Python with Numba training: learning.anaconda.cloud
PEP 0703: peps.python.org
Python 3.13 gets a JIT: tonybaloney.github.io
Numba: numba.pydata.org
LanceDB: lancedb.com
Profiling tips: docs.python.org
Memray: github.com
Fil: a Python memory profiler for data scientists and scientists: pythonspeed.com
Rust: rust-lang.org
Granian Server: github.com
PIXIE at SciPy 2024: github.com
Free threading Progress: py-free-threading.github.io
Free Threading Compatibility: py-free-threading.github.io
caniuse.com: caniuse.com
SPy, presented at PyCon 2024: us.pycon.org
Watch this episode on YouTube: youtube.com
Episode transcripts: talkpython.fm
--- Stay in touch with us ---
Subscribe to us on YouTube: youtube.com
Follow Talk Python on Mastodon: talkpython
Follow Michael on Mastodon: mkennedy
  continue reading

477 episod

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