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Blosc Development Team

Blosc Development Team

Mastodon @blosc2@fosstodon.org
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Followers
40
Account age
3 yrs
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Known for

💡 Python‑Blosc2 tip #10: store unbounded text as `utf8()`, not fixed‑width `string()`. `string(max_length=200)` rides on NumPy's `<U` dtype, which is UCS‑4: 800 bytes per row in memory on *every* read, three characters or two hundred. Instead of: title: str = blosc2.field(blosc2.string(max_length=200)) Do: title: str = blosc2.field(blosc2.utf8()) Massive memory savings. More info: https://blo3 views 💡 Python‑Blosc2 tip #10: store unbounded text as `utf8()`, not fixed‑width `string()`. `string(max_length=200)` rides on NumPy's `<U` dtype, which is UCS‑4: 800 bytes per row in memory on *every* read, three characters or two hundred. Instead of: title: str = blosc2.field(blosc2.string(max_length=200)) Do: title: str = blosc2.field(blosc2.utf8()) Massive memory savings. More info: https://blo 💡 Python‑Blosc2 tip #9: memory-map read-only opens — skip the syscalls. `mmap_mode="r"` maps the file once, reads pages directly — no per‑chunk syscalls. Instead of: arr = blosc2.open(path) Do: arr = blosc2.open(path, mmap_mode="r") ~15% faster for scattered reads, same memory — and it is free. The payoff multiplies with concurrent readers. https://blosc.org/python-blosc2/guides/optimization_t3 views 💡 Python‑Blosc2 tip #9: memory-map read-only opens — skip the syscalls. `mmap_mode="r"` maps the file once, reads pages directly — no per‑chunk syscalls. Instead of: arr = blosc2.open(path) Do: arr = blosc2.open(path, mmap_mode="r") ~15% faster for scattered reads, same memory — and it is free. The payoff multiplies with concurrent readers. https://blosc.org/python-blosc2/guides/optimization_t 💡 Python‑Blosc2 tip #8: push filters into `where=`. Column reductions accept `where=` — one chunk scan, no intermediates. Instead of: t["temperature"][:][t["region"][:] == 3].sum() Do: t["temperature"].sum(where=t.region == 3) ~1.9× faster, ~7× less memory. https://blosc.org/python-blosc2/guides/optimization_tips.html#filtered-reductions-push-the-predicate-down-with-where Compress Better, Comp3 views 💡 Python‑Blosc2 tip #8: push filters into `where=`. Column reductions accept `where=` — one chunk scan, no intermediates. Instead of: t["temperature"][:][t["region"][:] == 3].sum() Do: t["temperature"].sum(where=t.region == 3) ~1.9× faster, ~7× less memory. https://blosc.org/python-blosc2/guides/optimization_tips.html#filtered-reductions-push-the-predicate-down-with-where Compress Better, Comp 💡 Python-Blosc2 tip #3: align your reads with the double partition. Blosc2 splits arrays into chunks and blocks. Crossing either boundary decompresses extra data — placing slice boundaries on the grid is free: use arr.chunks and arr.blocks. Chunk-aligned reads ~2.2× faster, chunk-aligned slice() ~4.9× faster (no decompression). Block-aligned reads ~1.7× faster with larger blocks. 📖 https://blosc.o3 views 💡 Python-Blosc2 tip #3: align your reads with the double partition. Blosc2 splits arrays into chunks and blocks. Crossing either boundary decompresses extra data — placing slice boundaries on the grid is free: use arr.chunks and arr.blocks. Chunk-aligned reads ~2.2× faster, chunk-aligned slice() ~4.9× faster (no decompression). Block-aligned reads ~1.7× faster with larger blocks. 📖 https://blosc.o

📊 Post engagement

2
Avg engagement / post
5%
Engagement vs followers
Dec 2022
On Mastodon since

🔥 Top post: 💡 Python‑Blosc2 tip #10: store unbounded text as `utf8()`, not f · 3 likes + reposts

📊 Activity & format

Posting cadence
3 / week
Posts several times a week.
Content mix
Mostly images
Recent: 1 text · 10 image · 1 video.
Follower / following
4×
Follows 10 back. A more reciprocal / networked account.

Recent posts

View on Mastodon ↗
🔥 Top post 💡 Python‑Blosc2 tip #10: store unbounded text as `utf8()`, not fixed‑width `string()`. `string(max_length=200)` rides on NumPy's `<U` dtype, which is UCS‑4: 800 bytes per row in memory on *every* read, three characters or two hundred. Instead of: title: str = blosc2.field(blos… ★ 3
💡 Python‑Blosc2 tip #9: broadcast small operands into large, on‑disk arrays. Build the big array as a lazy expression and `compute()` it straight to a file — blosc2 broadcasts chunk by chunk, so the full uncompressed result never exists. I… ★ 2 💡 Python‑Blosc2 tip #9: memory-map read-only opens — skip the syscalls. `mmap_mode="r"` maps the file once, reads pages directly — no per‑chunk syscalls. Instead of: arr = blosc2.open(path) Do: arr = blosc2.open(path, mmap_mode="r") ~1… ★ 3 💡 Python‑Blosc2 tip #8: push filters into `where=`. Column reductions accept `where=` — one chunk scan, no intermediates. Instead of: t["temperature"][:][t["region"][:] == 3].sum() Do: t["temperature"].sum(where=t.region == 3) ~1.9× fa… ★ 3 💡 Python-Blosc2 tip #7: reduce columns directly — don't slice them first. t["col"][:] materialises the whole column as one big NumPy array. Column reductions — sum(), mean(), min(), max() — work chunk by chunk over the compressed data inst… ★ 2 💡 Python-Blosc2 tip #5: sorted top-k? Stream it from a FULL index. A FULL index stores rows in sorted order, so when all you need is the top (or bottom) k rows, both CTable.sort_by(view=True)[:k] and NDArray.iter_sorted(start=-k) read just… ★ 1 💡 Python-Blosc2 tip #4: let SUMMARY indexes answer min()/max() directly. When you close a CTable, Blosc2 auto-builds SUMMARY indexes — per-block min/max summaries — for its eligible scalar columns. Column.min()/max(), and argmin()/argmax()… ★ 1 💡 Python-Blosc2 tip #3: align your reads with the double partition. Blosc2 splits arrays into chunks and blocks. Crossing either boundary decompresses extra data — placing slice boundaries on the grid is free: use arr.chunks and arr.blocks… ★ 3 Python-Blosc2 4.8.1 is out! 🚀 A maintenance release worth grabbing: 🔧 Fixed a use-after-free with zero-copy cframes, wrong-chunk deletion on negative-step slices, and DictStore overwrite quirks 🗺️ CTable stores can now be opened with mmap_… ★ 3 💡 Python-Blosc2 optimization tip #2: many readers on one file? mmap it in every one of them. blosc2.open(path, mmap_mode="r") sends all readers to one shared set of mapped pages, instead of a syscall + buffer copy per read. With 8 concurre… ★ 3 💡 Python-Blosc2 optimization tip #1: build large arrays with blosc2's own constructors. blosc2.asarray(np.linspace(0, 1, N)) holds the whole uncompressed array in RAM first. blosc2.linspace(0, 1, N) fills it chunk by chunk instead: at 200M… ★ 2 ▶ 📢 Python-Blosc2 4.8.0 is out! The star: sharing on-disk containers across processes. SWMR readers follow a writer's appends in near real-time, and opt-in locking (locking=True + holding_lock()) makes multi-op updates atomic — no torn reads… ★ 1

🐘 Community & instance

Home server
fosstodon.org
A open-source software server — its members and audience skew toward that niche, so expect a community-aligned, engaged following.
On Mastodon since
Dec 2022
Joined in the Twitter-exodus wave of late 2022 — part of the migration that made Mastodon a real destination.

💡 Facts

🗓️Joined Mastodon in 2022 — 3 years ago.
👁️Averages 2 views per post.
📤Posts about 3× per week.

🕵️ Fake follower check

Estimated
76/100
Good Credibility score
97%
Real Real audience
Low Fake-follower risk
Medium Data confidence
  • Est. 97% real, active audience · Low fake-follower risk.
  • Strong engagement (~5.0% of followers engage each post) — an active, real audience.
  • Established account (3+ years old).

Heuristic estimate from engagement, follower ratios, account age & growth — a screening signal, not a guarantee.

About

We make compression better https://blosc.org

📸 Gallery

💡 Python‑Blosc2 tip #10: store unbounded text as `utf8()`, not fixed‑width `string()`. `string(max_length=200)` rides on NumPy's `<U` dtype, which is UCS‑4: 800 bytes per row in memory on *every* read, three characters or two hundred. Instead of: title: str = blosc2.field(blosc2.string(max_length=200)) Do: title: str = blosc2.field(blosc2.utf8()) Massive memory savings. More info: https://blo 💡 Python‑Blosc2 tip #9: broadcast small operands into large, on‑disk arrays. Build the big array as a lazy expression and `compute()` it straight to a file — blosc2 broadcasts chunk by chunk, so the full uncompressed result never exists. Instead of: blosc2.asarray(rows + cols, urlpath="big.b2nd", mode="w") Do: (rows + cols).compute(urlpath="big.b2nd", mode="w") https://blosc.org/python-blosc2/ 💡 Python‑Blosc2 tip #9: memory-map read-only opens — skip the syscalls. `mmap_mode="r"` maps the file once, reads pages directly — no per‑chunk syscalls. Instead of: arr = blosc2.open(path) Do: arr = blosc2.open(path, mmap_mode="r") ~15% faster for scattered reads, same memory — and it is free. The payoff multiplies with concurrent readers. https://blosc.org/python-blosc2/guides/optimization_t 💡 Python‑Blosc2 tip #8: push filters into `where=`. Column reductions accept `where=` — one chunk scan, no intermediates. Instead of: t["temperature"][:][t["region"][:] == 3].sum() Do: t["temperature"].sum(where=t.region == 3) ~1.9× faster, ~7× less memory. https://blosc.org/python-blosc2/guides/optimization_tips.html#filtered-reductions-push-the-predicate-down-with-where Compress Better, Comp 💡 Python-Blosc2 tip #7: reduce columns directly — don't slice them first. t["col"][:] materialises the whole column as one big NumPy array. Column reductions — sum(), mean(), min(), max() — work chunk by chunk over the compressed data instead, while still handling null values and deleted rows correctly. On a 50M-row column: 1.7× faster and ~12× less peak memory. 📖 https://blosc.org/python-blosc2/g 💡 Python-Blosc2 tip #5: sorted top-k? Stream it from a FULL index. A FULL index stores rows in sorted order, so when all you need is the top (or bottom) k rows, both CTable.sort_by(view=True)[:k] and NDArray.iter_sorted(start=-k) read just that slice from the index sidecar instead of materialising the full sorted permutation. 📖 https://blosc.org/python-blosc2/guides/optimization_tips.html#sorted-t 💡 Python-Blosc2 tip #4: let SUMMARY indexes answer min()/max() directly. When you close a CTable, Blosc2 auto-builds SUMMARY indexes — per-block min/max summaries — for its eligible scalar columns. Column.min()/max(), and argmin()/argmax() inside group_by(), then answer straight from the index without touching the column at all. On a 10M-row column: ~4× faster, and essentially no extra memory — th 💡 Python-Blosc2 tip #3: align your reads with the double partition. Blosc2 splits arrays into chunks and blocks. Crossing either boundary decompresses extra data — placing slice boundaries on the grid is free: use arr.chunks and arr.blocks. Chunk-aligned reads ~2.2× faster, chunk-aligned slice() ~4.9× faster (no decompression). Block-aligned reads ~1.7× faster with larger blocks. 📖 https://blosc.o

🔀 Audience overlap

Estimated

Estimated shared audience with similar creators — useful for avoiding overlap (or doubling down) when planning a campaign.

cfMC FEROX cfMC FEROX 17% glenofnz glenofnz 17% Denis Wilford 🇳🇿 NZ Denis Wilford 🇳🇿 NZ 17% ali ali 15% Safi 💐 Safi 💐 15% Travis La Marr Travis La Marr 14%

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