📢 Python-Blosc2 4.13.1 is out!
Continuing our "not an island" mood: stream remote datasets (HDF5, Zarr, B2Z) over HTTP/S3 lazily, and compute across formats in one expression: b2z + zarr * h5! Plus tiered caching & Win ARM64 wheels.
github.com/Blosc/python...
Compress Better, Compute Bigger 🚀
Continuing our "not an island" mood: stream remote datasets (HDF5, Zarr, B2Z) over HTTP/S3 lazily, and compute across formats in one expression: b2z + zarr * h5! Plus tiered caching & Win ARM64 wheels.
github.com/Blosc/python...
Compress Better, Compute Bigger 🚀
September 15, 2026 at 11:11 AM
📢 Python-Blosc2 4.13.1 is out!
Continuing our "not an island" mood: stream remote datasets (HDF5, Zarr, B2Z) over HTTP/S3 lazily, and compute across formats in one expression: b2z + zarr * h5! Plus tiered caching & Win ARM64 wheels.
github.com/Blosc/python...
Compress Better, Compute Bigger 🚀
Continuing our "not an island" mood: stream remote datasets (HDF5, Zarr, B2Z) over HTTP/S3 lazily, and compute across formats in one expression: b2z + zarr * h5! Plus tiered caching & Win ARM64 wheels.
github.com/Blosc/python...
Compress Better, Compute Bigger 🚀
📢 Python-Blosc2 4.13.0 is out!
One lazy API for unite all remote data: browse B2Z/Zarr/HDF5 hierarchies over S3/GCS/HTTP, slice only what you need, cache in RAM or on disk, and export portable snapshots.
b2view demo below👇
github.com/Blosc/python...
Compress Better, Compute Bigger 🚀
One lazy API for unite all remote data: browse B2Z/Zarr/HDF5 hierarchies over S3/GCS/HTTP, slice only what you need, cache in RAM or on disk, and export portable snapshots.
b2view demo below👇
github.com/Blosc/python...
Compress Better, Compute Bigger 🚀
September 11, 2026 at 1:22 PM
📢 Python-Blosc2 4.13.0 is out!
One lazy API for unite all remote data: browse B2Z/Zarr/HDF5 hierarchies over S3/GCS/HTTP, slice only what you need, cache in RAM or on disk, and export portable snapshots.
b2view demo below👇
github.com/Blosc/python...
Compress Better, Compute Bigger 🚀
One lazy API for unite all remote data: browse B2Z/Zarr/HDF5 hierarchies over S3/GCS/HTTP, slice only what you need, cache in RAM or on disk, and export portable snapshots.
b2view demo below👇
github.com/Blosc/python...
Compress Better, Compute Bigger 🚀
📢 Python-Blosc2 4.12.0 is out!
Remote arrays work over S3/GCS/HTTP via fsspec. lazy=True fetches only the blocks needed and reuses a validated cache — 5–17x faster in S3 benchmarks.
Also: concurrent Caterva2 writers + UTF-8 indexes.
github.com/Blosc/python...
Compress Better, Compute Bigger 🚀
Remote arrays work over S3/GCS/HTTP via fsspec. lazy=True fetches only the blocks needed and reuses a validated cache — 5–17x faster in S3 benchmarks.
Also: concurrent Caterva2 writers + UTF-8 indexes.
github.com/Blosc/python...
Compress Better, Compute Bigger 🚀
September 1, 2026 at 11:50 AM
📢 Python-Blosc2 4.12.0 is out!
Remote arrays work over S3/GCS/HTTP via fsspec. lazy=True fetches only the blocks needed and reuses a validated cache — 5–17x faster in S3 benchmarks.
Also: concurrent Caterva2 writers + UTF-8 indexes.
github.com/Blosc/python...
Compress Better, Compute Bigger 🚀
Remote arrays work over S3/GCS/HTTP via fsspec. lazy=True fetches only the blocks needed and reuses a validated cache — 5–17x faster in S3 benchmarks.
Also: concurrent Caterva2 writers + UTF-8 indexes.
github.com/Blosc/python...
Compress Better, Compute Bigger 🚀
💡 Blosc2 tip: repeated text? use dictionary(): one int32 code per row, one copy of each value.
On 1 Mrow with 100 distinct titles: group_by 22x faster, isin() 5.7x, 5.6x smaller on disk.
blosc.org/python-blosc2/guides/optimization_tips.html#repeated-text-store-it-as-dictionary
Enjoy data 🚀
On 1 Mrow with 100 distinct titles: group_by 22x faster, isin() 5.7x, 5.6x smaller on disk.
blosc.org/python-blosc2/guides/optimization_tips.html#repeated-text-store-it-as-dictionary
Enjoy data 🚀
Optimization tips - Python-Blosc2 documentation
blosc.org
August 25, 2026 at 8:19 AM
💡 Blosc2 tip: repeated text? use dictionary(): one int32 code per row, one copy of each value.
On 1 Mrow with 100 distinct titles: group_by 22x faster, isin() 5.7x, 5.6x smaller on disk.
blosc.org/python-blosc2/guides/optimization_tips.html#repeated-text-store-it-as-dictionary
Enjoy data 🚀
On 1 Mrow with 100 distinct titles: group_by 22x faster, isin() 5.7x, 5.6x smaller on disk.
blosc.org/python-blosc2/guides/optimization_tips.html#repeated-text-store-it-as-dictionary
Enjoy data 🚀
📣 Python-Blosc2 4.11.0 continues aligning with Arrow conventions.
New CTable nullability on a validity mask instead of a sentinel value ✨️
Also, wheels are now abi3 compliant w/ CPython 3.11+, including 3.15 (tested) 🚅
More info: github.com/Blosc/python...
Compress Better, Compute Bigger 🚀
New CTable nullability on a validity mask instead of a sentinel value ✨️
Also, wheels are now abi3 compliant w/ CPython 3.11+, including 3.15 (tested) 🚅
More info: github.com/Blosc/python...
Compress Better, Compute Bigger 🚀
Releases · Blosc/python-blosc2
A high-performance library for compressed ND arrays and columnar tables, with compute and indexing engines - Blosc/python-blosc2
github.com
August 13, 2026 at 11:45 AM
📣 Python-Blosc2 4.11.0 continues aligning with Arrow conventions.
New CTable nullability on a validity mask instead of a sentinel value ✨️
Also, wheels are now abi3 compliant w/ CPython 3.11+, including 3.15 (tested) 🚅
More info: github.com/Blosc/python...
Compress Better, Compute Bigger 🚀
New CTable nullability on a validity mask instead of a sentinel value ✨️
Also, wheels are now abi3 compliant w/ CPython 3.11+, including 3.15 (tested) 🚅
More info: github.com/Blosc/python...
Compress Better, Compute Bigger 🚀
💡 Blosc2 tip: @blosc2.jit can compile complex control flow with loops and conditionals.
A Mandelbrot escape loop written plainly: ~155x faster than plain Python, ~2.3x than hand-vectorized NumPy.
blosc.org/python-blosc...
Compress Better, Compute Bigger 🚀
#Python #Blosc2
A Mandelbrot escape loop written plainly: ~155x faster than plain Python, ~2.3x than hand-vectorized NumPy.
blosc.org/python-blosc...
Compress Better, Compute Bigger 🚀
#Python #Blosc2
August 11, 2026 at 5:21 PM
💡 Blosc2 tip: @blosc2.jit can compile complex control flow with loops and conditionals.
A Mandelbrot escape loop written plainly: ~155x faster than plain Python, ~2.3x than hand-vectorized NumPy.
blosc.org/python-blosc...
Compress Better, Compute Bigger 🚀
#Python #Blosc2
A Mandelbrot escape loop written plainly: ~155x faster than plain Python, ~2.3x than hand-vectorized NumPy.
blosc.org/python-blosc...
Compress Better, Compute Bigger 🚀
#Python #Blosc2
💡 Blosc2 tip: for unbounded text, use utf8().
blosc2.field(blosc2.utf8())
string(200) costs 800 B/row on every read; utf8() rows cost what they weigh: ~4× less memory.
blosc.org/python-blosc...
Compress Better, Compute Bigger 🚀
#Python #DataScience #Blosc2
blosc2.field(blosc2.utf8())
string(200) costs 800 B/row on every read; utf8() rows cost what they weigh: ~4× less memory.
blosc.org/python-blosc...
Compress Better, Compute Bigger 🚀
#Python #DataScience #Blosc2
August 7, 2026 at 10:58 AM
💡 Blosc2 tip: for unbounded text, use utf8().
blosc2.field(blosc2.utf8())
string(200) costs 800 B/row on every read; utf8() rows cost what they weigh: ~4× less memory.
blosc.org/python-blosc...
Compress Better, Compute Bigger 🚀
#Python #DataScience #Blosc2
blosc2.field(blosc2.utf8())
string(200) costs 800 B/row on every read; utf8() rows cost what they weigh: ~4× less memory.
blosc.org/python-blosc...
Compress Better, Compute Bigger 🚀
#Python #DataScience #Blosc2
💡 Blosc2 tip: build big on-disk arrays from small ones.
(rows + cols).compute(urlpath="big.b2nd", mode="w")
Chunk by chunk: similar speed, ~26× less peak memory.
blosc.org/python-blosc...
Compress Better, Compute Bigger 🚀
#Python #Blosc2
(rows + cols).compute(urlpath="big.b2nd", mode="w")
Chunk by chunk: similar speed, ~26× less peak memory.
blosc.org/python-blosc...
Compress Better, Compute Bigger 🚀
#Python #Blosc2
August 4, 2026 at 11:07 AM
💡 Blosc2 tip: build big on-disk arrays from small ones.
(rows + cols).compute(urlpath="big.b2nd", mode="w")
Chunk by chunk: similar speed, ~26× less peak memory.
blosc.org/python-blosc...
Compress Better, Compute Bigger 🚀
#Python #Blosc2
(rows + cols).compute(urlpath="big.b2nd", mode="w")
Chunk by chunk: similar speed, ~26× less peak memory.
blosc.org/python-blosc...
Compress Better, Compute Bigger 🚀
#Python #Blosc2
💡 Blosc2 tip: mmap read-only opens — skip the syscalls.
>>> arr = blosc2.open(path, mmap_mode="r")
Maps once, reads pages directly. ~15% faster for scattered reads, same memory. Free win, and scales with concurrent readers 🚀
blosc.org/python-blosc...
#Python #DataScience #Blosc2
>>> arr = blosc2.open(path, mmap_mode="r")
Maps once, reads pages directly. ~15% faster for scattered reads, same memory. Free win, and scales with concurrent readers 🚀
blosc.org/python-blosc...
#Python #DataScience #Blosc2
July 29, 2026 at 12:01 PM
💡 Blosc2 tip: mmap read-only opens — skip the syscalls.
>>> arr = blosc2.open(path, mmap_mode="r")
Maps once, reads pages directly. ~15% faster for scattered reads, same memory. Free win, and scales with concurrent readers 🚀
blosc.org/python-blosc...
#Python #DataScience #Blosc2
>>> arr = blosc2.open(path, mmap_mode="r")
Maps once, reads pages directly. ~15% faster for scattered reads, same memory. Free win, and scales with concurrent readers 🚀
blosc.org/python-blosc...
#Python #DataScience #Blosc2
💡 Blosc2 tip: `where=` for filtered reductions.
t["temperature"].sum(where=t.region == 3)
~1.9× faster, ~7× less memory than mask-then-index.
blosc.org/python-blosc...
Compress Better, Compute Bigger 🚀
#Python #DataScience #Blosc2
t["temperature"].sum(where=t.region == 3)
~1.9× faster, ~7× less memory than mask-then-index.
blosc.org/python-blosc...
Compress Better, Compute Bigger 🚀
#Python #DataScience #Blosc2
July 28, 2026 at 4:54 PM
💡 Blosc2 tip: `where=` for filtered reductions.
t["temperature"].sum(where=t.region == 3)
~1.9× faster, ~7× less memory than mask-then-index.
blosc.org/python-blosc...
Compress Better, Compute Bigger 🚀
#Python #DataScience #Blosc2
t["temperature"].sum(where=t.region == 3)
~1.9× faster, ~7× less memory than mask-then-index.
blosc.org/python-blosc...
Compress Better, Compute Bigger 🚀
#Python #DataScience #Blosc2
💡 Python-Blosc2 tip #7: don't slice a column to reduce it.
t["val"].sum() reduces the compressed column chunk-wise, never materialising it: 1.7× faster, ~12× less peak memory on 50M rows.
blosc.org/python-blosc...
Compress Better, Compute Bigger 🚀
t["val"].sum() reduces the compressed column chunk-wise, never materialising it: 1.7× faster, ~12× less peak memory on 50M rows.
blosc.org/python-blosc...
Compress Better, Compute Bigger 🚀
July 27, 2026 at 12:26 PM
💡 Python-Blosc2 tip #7: don't slice a column to reduce it.
t["val"].sum() reduces the compressed column chunk-wise, never materialising it: 1.7× faster, ~12× less peak memory on 50M rows.
blosc.org/python-blosc...
Compress Better, Compute Bigger 🚀
t["val"].sum() reduces the compressed column chunk-wise, never materialising it: 1.7× faster, ~12× less peak memory on 50M rows.
blosc.org/python-blosc...
Compress Better, Compute Bigger 🚀
💡 Python-Blosc2 tip #6: generate arrays with DSL kernels, not NumPy
A @blosc2.dsl_kernel handed to lazyudf() compiles to native code, filling an NDArray chunk by chunk, in parallel. ~3.6x faster, ~2x less peak memory on 200M elements.
blosc.org/python-blosc...
Compress Better, Compute Bigger 🚀
A @blosc2.dsl_kernel handed to lazyudf() compiles to native code, filling an NDArray chunk by chunk, in parallel. ~3.6x faster, ~2x less peak memory on 200M elements.
blosc.org/python-blosc...
Compress Better, Compute Bigger 🚀
July 21, 2026 at 10:39 AM
💡 Python-Blosc2 tip #6: generate arrays with DSL kernels, not NumPy
A @blosc2.dsl_kernel handed to lazyudf() compiles to native code, filling an NDArray chunk by chunk, in parallel. ~3.6x faster, ~2x less peak memory on 200M elements.
blosc.org/python-blosc...
Compress Better, Compute Bigger 🚀
A @blosc2.dsl_kernel handed to lazyudf() compiles to native code, filling an NDArray chunk by chunk, in parallel. ~3.6x faster, ~2x less peak memory on 200M elements.
blosc.org/python-blosc...
Compress Better, Compute Bigger 🚀
💡 Python-Blosc2 tip #5: sorted top-k? Stream it from a FULL index
CTable.sort_by(view=True)[:k] and NDArray.iter_sorted(start=-k) read just that slice from the index sidecar instead of sorting everything: up to ~74× less time, ~193× less peak memory.
blosc.org/python-blosc...
Enjoy data!
#Python
CTable.sort_by(view=True)[:k] and NDArray.iter_sorted(start=-k) read just that slice from the index sidecar instead of sorting everything: up to ~74× less time, ~193× less peak memory.
blosc.org/python-blosc...
Enjoy data!
#Python
July 17, 2026 at 12:47 PM
💡 Python-Blosc2 tip #5: sorted top-k? Stream it from a FULL index
CTable.sort_by(view=True)[:k] and NDArray.iter_sorted(start=-k) read just that slice from the index sidecar instead of sorting everything: up to ~74× less time, ~193× less peak memory.
blosc.org/python-blosc...
Enjoy data!
#Python
CTable.sort_by(view=True)[:k] and NDArray.iter_sorted(start=-k) read just that slice from the index sidecar instead of sorting everything: up to ~74× less time, ~193× less peak memory.
blosc.org/python-blosc...
Enjoy data!
#Python
💡 Python-Blosc2 tip #4: let SUMMARY indexes answer min()/max() directly
CTable auto-builds per-block min/max indexes for its scalar columns, so Column.min()/max() never decompress the column: ~4× faster, essentially no extra memory.
blosc.org/python-blosc...
Compress Better, Compute Bigger 🚀
CTable auto-builds per-block min/max indexes for its scalar columns, so Column.min()/max() never decompress the column: ~4× faster, essentially no extra memory.
blosc.org/python-blosc...
Compress Better, Compute Bigger 🚀
July 16, 2026 at 12:01 PM
💡 Python-Blosc2 tip #4: let SUMMARY indexes answer min()/max() directly
CTable auto-builds per-block min/max indexes for its scalar columns, so Column.min()/max() never decompress the column: ~4× faster, essentially no extra memory.
blosc.org/python-blosc...
Compress Better, Compute Bigger 🚀
CTable auto-builds per-block min/max indexes for its scalar columns, so Column.min()/max() never decompress the column: ~4× faster, essentially no extra memory.
blosc.org/python-blosc...
Compress Better, Compute Bigger 🚀
💡 Python-Blosc2 tip #3: align your reads with the double partition
A chunk-aligned read decompresses 1 chunk instead of 2 (~2.2× faster), and chunk-aligned slice() copies chunks as-is with no decompression at all (~4.9× faster). Same principle at block level.
blosc.org/python-blosc...
Enjoy data!
A chunk-aligned read decompresses 1 chunk instead of 2 (~2.2× faster), and chunk-aligned slice() copies chunks as-is with no decompression at all (~4.9× faster). Same principle at block level.
blosc.org/python-blosc...
Enjoy data!
July 15, 2026 at 12:25 PM
💡 Python-Blosc2 tip #3: align your reads with the double partition
A chunk-aligned read decompresses 1 chunk instead of 2 (~2.2× faster), and chunk-aligned slice() copies chunks as-is with no decompression at all (~4.9× faster). Same principle at block level.
blosc.org/python-blosc...
Enjoy data!
A chunk-aligned read decompresses 1 chunk instead of 2 (~2.2× faster), and chunk-aligned slice() copies chunks as-is with no decompression at all (~4.9× faster). Same principle at block level.
blosc.org/python-blosc...
Enjoy data!
💡 Python-Blosc2 tip #2: many readers, one file?
Open with mmap_mode="r" in every reader — all share one set of mapped pages instead of a syscall + copy per read.
8 concurrent readers: ~4.5x faster, half the CPU, still ~one copy of the file in RAM.
blosc.org/python-blosc...
Enjoy data! 🚀
Open with mmap_mode="r" in every reader — all share one set of mapped pages instead of a syscall + copy per read.
8 concurrent readers: ~4.5x faster, half the CPU, still ~one copy of the file in RAM.
blosc.org/python-blosc...
Enjoy data! 🚀
Optimization tips - Python-Blosc2 documentation
blosc.org
July 14, 2026 at 11:14 AM
💡 Python-Blosc2 tip #2: many readers, one file?
Open with mmap_mode="r" in every reader — all share one set of mapped pages instead of a syscall + copy per read.
8 concurrent readers: ~4.5x faster, half the CPU, still ~one copy of the file in RAM.
blosc.org/python-blosc...
Enjoy data! 🚀
Open with mmap_mode="r" in every reader — all share one set of mapped pages instead of a syscall + copy per read.
8 concurrent readers: ~4.5x faster, half the CPU, still ~one copy of the file in RAM.
blosc.org/python-blosc...
Enjoy data! 🚀
💡 Python-Blosc2 tip #1: skip the NumPy detour.
blosc2.linspace(0, 1, N) fills a compressed array chunk by chunk — at 200M float64, ~25x less peak memory than asarray(np.linspace(...)), comparable speed.
Same for arange() and fromiter().
blosc.org/python-blosc...
Compress Better, Compute Bigger 🚀
blosc2.linspace(0, 1, N) fills a compressed array chunk by chunk — at 200M float64, ~25x less peak memory than asarray(np.linspace(...)), comparable speed.
Same for arange() and fromiter().
blosc.org/python-blosc...
Compress Better, Compute Bigger 🚀
July 13, 2026 at 11:11 AM
💡 Python-Blosc2 tip #1: skip the NumPy detour.
blosc2.linspace(0, 1, N) fills a compressed array chunk by chunk — at 200M float64, ~25x less peak memory than asarray(np.linspace(...)), comparable speed.
Same for arange() and fromiter().
blosc.org/python-blosc...
Compress Better, Compute Bigger 🚀
blosc2.linspace(0, 1, N) fills a compressed array chunk by chunk — at 200M float64, ~25x less peak memory than asarray(np.linspace(...)), comparable speed.
Same for arange() and fromiter().
blosc.org/python-blosc...
Compress Better, Compute Bigger 🚀
📢 Python-Blosc2 4.8.0: share on-disk compressed containers across processes!
SWMR readers follow a writer's appends in near real-time, and opt-in locking makes updates atomic — no torn reads, no retries.
🎬 One writer appending, three readers chasing it live:
www.blosc.org/python-blosc...
#Python
SWMR readers follow a writer's appends in near real-time, and opt-in locking makes updates atomic — no torn reads, no retries.
🎬 One writer appending, three readers chasing it live:
www.blosc.org/python-blosc...
#Python
July 10, 2026 at 12:44 PM
📢 Python-Blosc2 4.8.0: share on-disk compressed containers across processes!
SWMR readers follow a writer's appends in near real-time, and opt-in locking makes updates atomic — no torn reads, no retries.
🎬 One writer appending, three readers chasing it live:
www.blosc.org/python-blosc...
#Python
SWMR readers follow a writer's appends in near real-time, and opt-in locking makes updates atomic — no torn reads, no retries.
🎬 One writer appending, three readers chasing it live:
www.blosc.org/python-blosc...
#Python
Python-Blosc2 now has a 🔥 DSL-to-JavaScript transpiler!
Newton-Raphson runs 2.7× faster on the browser! 💨
With #Pyodide, it’s not just Python in the browser: it’s the PyData stack 📊 too, #Blosc2 tacking compression 📦 + computing 🧮 duties.
Demo 👇
blosc.org/demos/newton...
Newton-Raphson runs 2.7× faster on the browser! 💨
With #Pyodide, it’s not just Python in the browser: it’s the PyData stack 📊 too, #Blosc2 tacking compression 📦 + computing 🧮 duties.
Demo 👇
blosc.org/demos/newton...
Newton fractal — blosc2's JIT, live in your browser
blosc.org
June 30, 2026 at 12:27 PM
Python-Blosc2 now has a 🔥 DSL-to-JavaScript transpiler!
Newton-Raphson runs 2.7× faster on the browser! 💨
With #Pyodide, it’s not just Python in the browser: it’s the PyData stack 📊 too, #Blosc2 tacking compression 📦 + computing 🧮 duties.
Demo 👇
blosc.org/demos/newton...
Newton-Raphson runs 2.7× faster on the browser! 💨
With #Pyodide, it’s not just Python in the browser: it’s the PyData stack 📊 too, #Blosc2 tacking compression 📦 + computing 🧮 duties.
Demo 👇
blosc.org/demos/newton...
✨ Tabular data visualization, fast filtering, smart navigation, remote plotting, and more... with just a text terminal!
This is the new b2view Text User Interface that comes with latest Python-Blosc2 release.
github.com/Blosc/python...
Enjoy!
This is the new b2view Text User Interface that comes with latest Python-Blosc2 release.
github.com/Blosc/python...
Enjoy!
June 17, 2026 at 3:46 PM
✨ Tabular data visualization, fast filtering, smart navigation, remote plotting, and more... with just a text terminal!
This is the new b2view Text User Interface that comes with latest Python-Blosc2 release.
github.com/Blosc/python...
Enjoy!
This is the new b2view Text User Interface that comes with latest Python-Blosc2 release.
github.com/Blosc/python...
Enjoy!
This is our most playful release so far.
Under the hood we did amazing improvements, making toying with very large tabular data a pleasant, NumPy-centric experience.
Have fun!
Under the hood we did amazing improvements, making toying with very large tabular data a pleasant, NumPy-centric experience.
Have fun!
June 9, 2026 at 4:50 PM
This is our most playful release so far.
Under the hood we did amazing improvements, making toying with very large tabular data a pleasant, NumPy-centric experience.
Have fun!
Under the hood we did amazing improvements, making toying with very large tabular data a pleasant, NumPy-centric experience.
Have fun!
📣 Python-Blosc2 4.4.x is out!
🖥️ b2view: interactive TUI browser
🎯 SUMMARY indexes → fast WHERE
🧮 DSL kernels as CTable columns
⚡ Faster chunk-by-chunk writes
🔀 where() via miniexpr
Compressed, NumPy-native arrays & tables.
📝 github.com/Blosc/python...
Enjoy data!
#Python #NumPy
🖥️ b2view: interactive TUI browser
🎯 SUMMARY indexes → fast WHERE
🧮 DSL kernels as CTable columns
⚡ Faster chunk-by-chunk writes
🔀 where() via miniexpr
Compressed, NumPy-native arrays & tables.
📝 github.com/Blosc/python...
Enjoy data!
#Python #NumPy
June 9, 2026 at 4:49 PM
📣 Python-Blosc2 4.4.x is out!
🖥️ b2view: interactive TUI browser
🎯 SUMMARY indexes → fast WHERE
🧮 DSL kernels as CTable columns
⚡ Faster chunk-by-chunk writes
🔀 where() via miniexpr
Compressed, NumPy-native arrays & tables.
📝 github.com/Blosc/python...
Enjoy data!
#Python #NumPy
🖥️ b2view: interactive TUI browser
🎯 SUMMARY indexes → fast WHERE
🧮 DSL kernels as CTable columns
⚡ Faster chunk-by-chunk writes
🔀 where() via miniexpr
Compressed, NumPy-native arrays & tables.
📝 github.com/Blosc/python...
Enjoy data!
#Python #NumPy
This opens the door to exciting new developments in the Python-Blosc2 wrapper. Stay tuned!
🚀 C-Blosc2 3.1.0 is here!
New in this release: sparse coordinate getters for faster random access, header-only b2nd metalayer access for plugins (no libblosc2 link needed), and new codec IDs for J2K/HTJ2K support. 🧩⚡
Release notes: github.com/Blosc/c-blos...
Compress better, compute bigger! 💥
New in this release: sparse coordinate getters for faster random access, header-only b2nd metalayer access for plugins (no libblosc2 link needed), and new codec IDs for J2K/HTJ2K support. 🧩⚡
Release notes: github.com/Blosc/c-blos...
Compress better, compute bigger! 💥
github.com
May 25, 2026 at 6:10 PM
This opens the door to exciting new developments in the Python-Blosc2 wrapper. Stay tuned!
Did you know that in recent Python-Blosc2 4.2.0 we released extremely efficient indexing engines that can store data in (guess what) ...compressed state?
As a result, much larger tables can be indexed. Look at how this fares against other good indexing engines in plots below.
Enjoy!
#TabularData
As a result, much larger tables can be indexed. Look at how this fares against other good indexing engines in plots below.
Enjoy!
#TabularData
May 12, 2026 at 9:09 AM
Did you know that in recent Python-Blosc2 4.2.0 we released extremely efficient indexing engines that can store data in (guess what) ...compressed state?
As a result, much larger tables can be indexed. Look at how this fares against other good indexing engines in plots below.
Enjoy!
#TabularData
As a result, much larger tables can be indexed. Look at how this fares against other good indexing engines in plots below.
Enjoy!
#TabularData
Python-Blosc2 4.2.0 is out 🎉
Meet `CTable`: a new compressed columnar container with null support, fast queries, and easy Arrow/Parquet interoperability.
Compress better, analyze faster.
Release notes:
github.com/Blosc/python...
Meet `CTable`: a new compressed columnar container with null support, fast queries, and easy Arrow/Parquet interoperability.
Compress better, analyze faster.
Release notes:
github.com/Blosc/python...
May 8, 2026 at 5:00 PM
Python-Blosc2 4.2.0 is out 🎉
Meet `CTable`: a new compressed columnar container with null support, fast queries, and easy Arrow/Parquet interoperability.
Compress better, analyze faster.
Release notes:
github.com/Blosc/python...
Meet `CTable`: a new compressed columnar container with null support, fast queries, and easy Arrow/Parquet interoperability.
Compress better, analyze faster.
Release notes:
github.com/Blosc/python...