Skip to main content

SciQLop plot API based on QCustomPlot

Project description

License: GPL v3 C++20 PyPi Coverage

SciQLopPlots

A high-performance scientific plotting library built on C++20/Qt6 with Python bindings via Shiboken6 (PySide6). Designed for the SciQLop data analysis platform but usable standalone.

Features

  • Async resampling — render millions of points smoothly; data is downsampled in background threads via NeoQCP pipelines
  • Multiple plot types — time series (line graphs), spectrograms (color maps), 2D histograms, parametric curves, N-D projection curves, waterfall plots
  • Interactive — pan, zoom, data-driven callbacks, vertical/horizontal/rectangular spans, tracers, straight lines, text, shapes, pixmaps
  • Multi-plot panels — synchronized axes, aligned margins, drag-and-drop from product trees
  • Reactive pipelines — connect plot properties with >> to build live data flows
  • Export — PDF (vector), PNG, JPG, BMP for both individual plots and panels
  • Busy indicator — visual feedback when data is loading or being processed
  • Runtime inspector — tree model/view for inspecting and editing plot properties
  • Cross-platform — Linux, macOS, Windows

Architecture

graph TD
    subgraph Python["Python Layer"]
        PY[SciQLopPlots package]
        SB[Shiboken6 bindings]
    end

    subgraph Plots["Plot Hierarchy"]
        PI[SciQLopPlotInterface<br/><i>QFrame</i>]
        SP[SciQLopPlot]
        TSP[SciQLopTimeSeriesPlot]
        NDP[SciQLopNDProjectionPlot]
    end

    subgraph Plotables["Plotables"]
        PTI[SciQLopPlottableInterface<br/><i>QObject</i>]
        GI[SciQLopGraphInterface]
        CMI[SciQLopColorMapInterface]
        LG[SciQLopLineGraph]
        SLG[SciQLopSingleLineGraph]
        CRV[SciQLopCurve]
        WF[SciQLopWaterfallGraph]
        NDC[SciQLopNDProjectionCurves]
        CMB[SciQLopColorMapBase]
        CM[SciQLopColorMap]
        H2D[SciQLopHistogram2D]
    end

    subgraph Items["Overlay Items"]
        VS[VerticalSpan]
        HS[HorizontalSpan]
        RS[RectangularSpan]
        TR[Tracer]
        SL[StraightLine]
    end

    subgraph MultiPlot["Multi-Plot"]
        PPI[SciQLopPlotPanelInterface]
        MPP[SciQLopMultiPlotPanel]
        AX[AxisSynchronizer]
        VA[VPlotsAlign]
    end

    PY --> SB --> PI

    PI --> SP
    PI --> NDP
    SP --> TSP

    PTI --> GI
    PTI --> CMI
    GI --> LG
    GI --> SLG
    GI --> CRV
    GI --> WF
    GI --> NDC
    CMI --> CMB
    CMB --> CM
    CMB --> H2D

    PPI --> MPP
    MPP --> AX
    MPP --> VA

    SP -.->|contains| PTI
    SP -.->|contains| Items
    MPP -.->|contains| SP

Data flow

sequenceDiagram
    participant User
    participant Plot as SciQLopPlot
    participant Resampler as Resampler<br/>(worker thread)
    participant NeoQCP as NeoQCP

    User->>Plot: pan / zoom
    Plot->>Resampler: new visible range
    Resampler->>Resampler: downsample data
    Resampler->>NeoQCP: resampled points
    NeoQCP->>Plot: render

For callback-driven data, the plot invokes a Python callable with (start, stop) on range change, and the returned arrays flow through the same resampling pipeline.

Quick start

pip install SciQLopPlots
import numpy as np
from PySide6.QtWidgets import QApplication
from SciQLopPlots import SciQLopPlot

app = QApplication([])
plot = SciQLopPlot()

# Static data
x = np.arange(0, 1000, dtype=np.float64)
y = np.sin(x / 100) * np.cos(x / 10)
plot.plot(x, y, labels=["signal"])

# Data callback (called on pan/zoom with visible range)
def get_data(start, stop):
    x = np.arange(start, stop, dtype=np.float64)
    y = np.column_stack([np.sin(x / 100), np.cos(x / 100)])
    return x, y

plot.plot(get_data, labels=["sin", "cos"])

plot.show()
app.exec()

Reactive pipelines

Connect plot properties with the >> operator to build live data pipelines:

from SciQLopPlots import SciQLopPlot

plot = SciQLopPlot()
graph = plot.plot(lambda start, stop: ..., labels=["signal"])

# Axis range changes automatically feed a transform, which pushes data to the graph
plot.x_axis.on.range >> get_data >> graph.on.data

# Direct property forwarding (no transform)
span.on.range >> plot.x_axis.on.range

# Chain multiple steps
source.on.range >> transform >> target.on.data

Run the gallery for a full feature showcase:

python tests/manual-tests/gallery.py

Runtime tracing

SciQLopPlots ships with a built-in tracer that emits Chrome trace JSON, viewable in Perfetto, Speedscope, or chrome://tracing. Always compiled in, runtime-toggled, ~1 ns when off.

Enable for a session, then open the file in Perfetto:

from SciQLopPlots import tracing

with tracing.session("/tmp/sciqlop.json"):
    panel.zoom_in_a_lot()       # whatever's slow

Annotate Python work to land alongside the C++ zones (plot.replot, setdata.colormap, resample.async_2d, …):

with tracing.zone("speasy.fetch", cat="data", product="amda/mms_fgm"):
    data = speasy.get_data(...)

@tracing.traced("layer.eval", cat="layer")
def render_layer(...): ...

tracing.counter("queue_depth", q.size(), cat="fetch")

You can also auto-enable at process start with the SCIQLOP_TRACE env var:

SCIQLOP_TRACE=/tmp/sciqlop.json python my_script.py

When tracy_enable=true is also passed at build time, the same PROFILE_HERE_N sites feed both the Chrome JSON tracer and the Tracy live-streaming view.

Building from source

Requires Qt6, PySide6 == 6.11.0, a C++20 compiler, and Meson.

# Development build (recommended — plain `debug` disables optimizations
# and makes the resampling pipelines noticeably sluggish)
meson setup build --buildtype=debugoptimized
meson compile -C build

# Install as editable Python package
pip install -e . --no-build-isolation

Build options

Option Type Default Description
trace_refcount bool false Enable reference count tracing
tracy_enable bool false Enable Tracy profiling
with_opengl bool true Enable OpenGL support

Contributing

Fork the repository, make your changes and submit a pull request. Bug reports and feature requests are welcome.

Credits

Development is supported by CDPP. We acknowledge support from Plas@Par.

Thanks

  • PySide6 — Qt bindings and Shiboken6 binding generator
  • NeoQCP — fork of QCustomPlot with async pipelines, multi-dtype support, and QRhi rendering

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

sciqlopplots-0.27.0.tar.gz (1.4 MB view details)

Uploaded Source

Built Distributions

If you're not sure about the file name format, learn more about wheel file names.

sciqlopplots-0.27.0-cp314-cp314-win_amd64.whl (3.0 MB view details)

Uploaded CPython 3.14Windows x86-64

sciqlopplots-0.27.0-cp314-cp314-manylinux_2_39_aarch64.whl (4.6 MB view details)

Uploaded CPython 3.14manylinux: glibc 2.39+ ARM64

sciqlopplots-0.27.0-cp314-cp314-manylinux_2_34_x86_64.whl (5.1 MB view details)

Uploaded CPython 3.14manylinux: glibc 2.34+ x86-64

sciqlopplots-0.27.0-cp314-cp314-macosx_13_0_x86_64.whl (4.1 MB view details)

Uploaded CPython 3.14macOS 13.0+ x86-64

sciqlopplots-0.27.0-cp314-cp314-macosx_13_0_arm64.whl (3.7 MB view details)

Uploaded CPython 3.14macOS 13.0+ ARM64

sciqlopplots-0.27.0-cp313-cp313-win_amd64.whl (2.9 MB view details)

Uploaded CPython 3.13Windows x86-64

sciqlopplots-0.27.0-cp313-cp313-manylinux_2_39_aarch64.whl (4.6 MB view details)

Uploaded CPython 3.13manylinux: glibc 2.39+ ARM64

sciqlopplots-0.27.0-cp313-cp313-manylinux_2_34_x86_64.whl (5.1 MB view details)

Uploaded CPython 3.13manylinux: glibc 2.34+ x86-64

sciqlopplots-0.27.0-cp313-cp313-macosx_13_0_x86_64.whl (4.1 MB view details)

Uploaded CPython 3.13macOS 13.0+ x86-64

sciqlopplots-0.27.0-cp313-cp313-macosx_13_0_arm64.whl (3.7 MB view details)

Uploaded CPython 3.13macOS 13.0+ ARM64

sciqlopplots-0.27.0-cp312-cp312-win_amd64.whl (2.9 MB view details)

Uploaded CPython 3.12Windows x86-64

sciqlopplots-0.27.0-cp312-cp312-manylinux_2_39_aarch64.whl (4.6 MB view details)

Uploaded CPython 3.12manylinux: glibc 2.39+ ARM64

sciqlopplots-0.27.0-cp312-cp312-manylinux_2_34_x86_64.whl (5.1 MB view details)

Uploaded CPython 3.12manylinux: glibc 2.34+ x86-64

sciqlopplots-0.27.0-cp312-cp312-macosx_13_0_x86_64.whl (4.1 MB view details)

Uploaded CPython 3.12macOS 13.0+ x86-64

sciqlopplots-0.27.0-cp312-cp312-macosx_13_0_arm64.whl (3.7 MB view details)

Uploaded CPython 3.12macOS 13.0+ ARM64

sciqlopplots-0.27.0-cp311-cp311-win_amd64.whl (2.9 MB view details)

Uploaded CPython 3.11Windows x86-64

sciqlopplots-0.27.0-cp311-cp311-manylinux_2_39_aarch64.whl (4.6 MB view details)

Uploaded CPython 3.11manylinux: glibc 2.39+ ARM64

sciqlopplots-0.27.0-cp311-cp311-manylinux_2_34_x86_64.whl (5.1 MB view details)

Uploaded CPython 3.11manylinux: glibc 2.34+ x86-64

sciqlopplots-0.27.0-cp311-cp311-macosx_13_0_x86_64.whl (4.1 MB view details)

Uploaded CPython 3.11macOS 13.0+ x86-64

sciqlopplots-0.27.0-cp311-cp311-macosx_13_0_arm64.whl (3.7 MB view details)

Uploaded CPython 3.11macOS 13.0+ ARM64

sciqlopplots-0.27.0-cp310-cp310-win_amd64.whl (2.9 MB view details)

Uploaded CPython 3.10Windows x86-64

sciqlopplots-0.27.0-cp310-cp310-manylinux_2_39_aarch64.whl (4.6 MB view details)

Uploaded CPython 3.10manylinux: glibc 2.39+ ARM64

sciqlopplots-0.27.0-cp310-cp310-manylinux_2_34_x86_64.whl (5.1 MB view details)

Uploaded CPython 3.10manylinux: glibc 2.34+ x86-64

sciqlopplots-0.27.0-cp310-cp310-macosx_13_0_x86_64.whl (4.1 MB view details)

Uploaded CPython 3.10macOS 13.0+ x86-64

sciqlopplots-0.27.0-cp310-cp310-macosx_13_0_arm64.whl (3.7 MB view details)

Uploaded CPython 3.10macOS 13.0+ ARM64

File details

Details for the file sciqlopplots-0.27.0.tar.gz.

File metadata

  • Download URL: sciqlopplots-0.27.0.tar.gz
  • Upload date:
  • Size: 1.4 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.12

File hashes

Hashes for sciqlopplots-0.27.0.tar.gz
Algorithm Hash digest
SHA256 69974849ed6840306e7c3785d1d4a647e25b6bb2c403983e17fa4c1f87b7033b
MD5 a5de98365c31e53bc86548bbbb80da44
BLAKE2b-256 fffdf179edf306600d8dc06906ab1ac48570cb98d2d8c0ce494373e9886bd82f

See more details on using hashes here.

File details

Details for the file sciqlopplots-0.27.0-cp314-cp314-win_amd64.whl.

File metadata

File hashes

Hashes for sciqlopplots-0.27.0-cp314-cp314-win_amd64.whl
Algorithm Hash digest
SHA256 164f3a4eaf1e42c3b496e1607cdf844db34b54946ef5111015ecd5194178c73e
MD5 b34980fb62d4d482283d5fb9610df63f
BLAKE2b-256 9e882c417dd2b05baf76173e000fa86c97d6791bba7c2fde908c90bcfb562336

See more details on using hashes here.

File details

Details for the file sciqlopplots-0.27.0-cp314-cp314-manylinux_2_39_aarch64.whl.

File metadata

File hashes

Hashes for sciqlopplots-0.27.0-cp314-cp314-manylinux_2_39_aarch64.whl
Algorithm Hash digest
SHA256 1c08afbce2a7e77dafb997e940102df5f7a0fb3f41593fe8fabc8336c03a8d9f
MD5 ba57fafeefd4315ffdc186bda8686104
BLAKE2b-256 b31ab12f264d1716e75b1481e29e2918749174d860d97ddd87e70b00383233a8

See more details on using hashes here.

File details

Details for the file sciqlopplots-0.27.0-cp314-cp314-manylinux_2_34_x86_64.whl.

File metadata

File hashes

Hashes for sciqlopplots-0.27.0-cp314-cp314-manylinux_2_34_x86_64.whl
Algorithm Hash digest
SHA256 3b3cde11ce90bb9ef655a0b51d44e79d21a6a6de7f62c48db24cc9055047ca84
MD5 589645fe40ab008d000799433718c2a0
BLAKE2b-256 e86c5ca9c8ad541ceafe07223b4d63dd2c7bcd1ec6a4236376e63a3e9f4b678e

See more details on using hashes here.

File details

Details for the file sciqlopplots-0.27.0-cp314-cp314-macosx_13_0_x86_64.whl.

File metadata

File hashes

Hashes for sciqlopplots-0.27.0-cp314-cp314-macosx_13_0_x86_64.whl
Algorithm Hash digest
SHA256 6b6dfef980845629c842e7d80ff35fa6bbd263ec631975dc7351add6a0b8bcde
MD5 d639a447b43e35478685b7886d8be01c
BLAKE2b-256 a56ca7995e8ce0ac1919bb4ca49f2bc8a0ba6106dc3dfa7a4e55a8330bd38466

See more details on using hashes here.

File details

Details for the file sciqlopplots-0.27.0-cp314-cp314-macosx_13_0_arm64.whl.

File metadata

File hashes

Hashes for sciqlopplots-0.27.0-cp314-cp314-macosx_13_0_arm64.whl
Algorithm Hash digest
SHA256 c5bf055df026cb9c9fb4517013757badf9b3526735306d19cda87bfffc88b67e
MD5 86af378110342a9e4c10c02ef44ee2b4
BLAKE2b-256 a518a56205f7ae2436244602af7dd0449ee4c9411b37261287ebe4457e353696

See more details on using hashes here.

File details

Details for the file sciqlopplots-0.27.0-cp313-cp313-win_amd64.whl.

File metadata

File hashes

Hashes for sciqlopplots-0.27.0-cp313-cp313-win_amd64.whl
Algorithm Hash digest
SHA256 86a06e69af50ce486695e62df8241e795c45914b367c37077893fbe466ad5e85
MD5 fde7e2a7e32667380c8527eb9909e75b
BLAKE2b-256 4c35ee5f03bed68b60ade55eb12267be20a7df07c665cd5ba2aa708183c4979c

See more details on using hashes here.

File details

Details for the file sciqlopplots-0.27.0-cp313-cp313-manylinux_2_39_aarch64.whl.

File metadata

File hashes

Hashes for sciqlopplots-0.27.0-cp313-cp313-manylinux_2_39_aarch64.whl
Algorithm Hash digest
SHA256 ef49cd44ab68b7b2b6d1c6b56caf51667b65954964e928d353c1ec2c916cc049
MD5 e78039bca32cf537163977f5996d4e05
BLAKE2b-256 9af78bd650712bb4cbb2c70fe8b9978de9e0fa8023ebb77c917c412e0abc48c3

See more details on using hashes here.

File details

Details for the file sciqlopplots-0.27.0-cp313-cp313-manylinux_2_34_x86_64.whl.

File metadata

File hashes

Hashes for sciqlopplots-0.27.0-cp313-cp313-manylinux_2_34_x86_64.whl
Algorithm Hash digest
SHA256 68425291b6af9038064c4e4688e7858651c26c22928f85078afcc3f360388b67
MD5 134d277c831164fd8d5ac51bc7606d7f
BLAKE2b-256 591a974ed33fe1576ddbad9a6b962dab510149ffdb2cbc3b84358f9f130ef839

See more details on using hashes here.

File details

Details for the file sciqlopplots-0.27.0-cp313-cp313-macosx_13_0_x86_64.whl.

File metadata

File hashes

Hashes for sciqlopplots-0.27.0-cp313-cp313-macosx_13_0_x86_64.whl
Algorithm Hash digest
SHA256 da82d448596c0c391218d903485aa46a92951c41f1e9b9925a035636ddd4149a
MD5 4f12d1a2c6bda5068ab3a00c43365a60
BLAKE2b-256 b57dbfcada7054e184109e9677361f654d001a794caa4ff53a482111dc2f1fa2

See more details on using hashes here.

File details

Details for the file sciqlopplots-0.27.0-cp313-cp313-macosx_13_0_arm64.whl.

File metadata

File hashes

Hashes for sciqlopplots-0.27.0-cp313-cp313-macosx_13_0_arm64.whl
Algorithm Hash digest
SHA256 de236ba58f5c265d2e2984c1e5514c50da8d9c62ca0cf7b1b5986e43a4e565b3
MD5 fcca79ee6997d8a1b962efdb4cf3f93a
BLAKE2b-256 e5c20ab1d079144937bc2069182fa2de5cc782f2cd7b79f55b7b55b64256f06e

See more details on using hashes here.

File details

Details for the file sciqlopplots-0.27.0-cp312-cp312-win_amd64.whl.

File metadata

File hashes

Hashes for sciqlopplots-0.27.0-cp312-cp312-win_amd64.whl
Algorithm Hash digest
SHA256 84258d985b135c9b0de67e17a8687ca2d2ff5833ea90b0afdc44b039a2a65b3e
MD5 a2f5852dae637810b2f1ec53a51efec4
BLAKE2b-256 b00dc69cb0e7924801f9f2c9a850e702b76919c9f687eae3a8f5d8e2f496d392

See more details on using hashes here.

File details

Details for the file sciqlopplots-0.27.0-cp312-cp312-manylinux_2_39_aarch64.whl.

File metadata

File hashes

Hashes for sciqlopplots-0.27.0-cp312-cp312-manylinux_2_39_aarch64.whl
Algorithm Hash digest
SHA256 1be2f46ebf7f8c2d90322956babe2ccb4fcf85f9b0ee0c5189fb6d8ad0d4743a
MD5 fbf049bd28c6c330eee306506d4e5c00
BLAKE2b-256 9b5826c96665a9399fdaded4156e85c298acb72748a16676545933a440f7068a

See more details on using hashes here.

File details

Details for the file sciqlopplots-0.27.0-cp312-cp312-manylinux_2_34_x86_64.whl.

File metadata

File hashes

Hashes for sciqlopplots-0.27.0-cp312-cp312-manylinux_2_34_x86_64.whl
Algorithm Hash digest
SHA256 d7ee46ff82e502c3d5bfac1f96910ef5619247c663793514cd4190598ab871d4
MD5 cceeef0470c66dd0bec2dd6ae5e62faa
BLAKE2b-256 9c1b2b91f92beeae1fb0784c0d4ca091a5fde7f1bce86001102783a8f80425af

See more details on using hashes here.

File details

Details for the file sciqlopplots-0.27.0-cp312-cp312-macosx_13_0_x86_64.whl.

File metadata

File hashes

Hashes for sciqlopplots-0.27.0-cp312-cp312-macosx_13_0_x86_64.whl
Algorithm Hash digest
SHA256 8a85f2f97d52ecb73d7e0524e62a3d03acfde18f5d613d7ec1e155ca3d7c8d54
MD5 4df896392213ee7d6adc4cbedead2c48
BLAKE2b-256 41f4bb2a8b1507d44a06e616d8bcddfce29dc3a7c6aa336bed752c39591d5df0

See more details on using hashes here.

File details

Details for the file sciqlopplots-0.27.0-cp312-cp312-macosx_13_0_arm64.whl.

File metadata

File hashes

Hashes for sciqlopplots-0.27.0-cp312-cp312-macosx_13_0_arm64.whl
Algorithm Hash digest
SHA256 a32be5cfeb484e36ec3a57e0fb8dcaa2201b74f4cdd0883d21cd731fc0b44544
MD5 67ad9e50e940a1c2ba4448eab25aa4c9
BLAKE2b-256 70f2398abdddb4af537cc0c178ab0f7bd16cca8eb2fee55e121406c9ad2f65fc

See more details on using hashes here.

File details

Details for the file sciqlopplots-0.27.0-cp311-cp311-win_amd64.whl.

File metadata

File hashes

Hashes for sciqlopplots-0.27.0-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 ee867f47173323bff792e4931361286a855b4206600b7be76b5988da0e17c2cb
MD5 079b116673838c4548ac910191b6c90b
BLAKE2b-256 ec0653e7340c10e6ef1590631a976122effcf390148b535b621b122d024af32e

See more details on using hashes here.

File details

Details for the file sciqlopplots-0.27.0-cp311-cp311-manylinux_2_39_aarch64.whl.

File metadata

File hashes

Hashes for sciqlopplots-0.27.0-cp311-cp311-manylinux_2_39_aarch64.whl
Algorithm Hash digest
SHA256 86c13ece55d5c25b35e234efd6a53748a7170fee8a2a5050c18f3cac6954bbd4
MD5 4b40ce4ff16cd127486575ef9062fc6c
BLAKE2b-256 612092f6cc6ae9a622aaadf38846b6b7278348332ff23b155c2e8750f6fc97a5

See more details on using hashes here.

File details

Details for the file sciqlopplots-0.27.0-cp311-cp311-manylinux_2_34_x86_64.whl.

File metadata

File hashes

Hashes for sciqlopplots-0.27.0-cp311-cp311-manylinux_2_34_x86_64.whl
Algorithm Hash digest
SHA256 d881c4708ff734107610a933fe190bc0659b09bc4f2ee066f2e9772832174f3b
MD5 f65a9d335ed151f69496631b01139c02
BLAKE2b-256 c36c2e6dae765685aeadffe78ad0a64a2d0da3d804495fad9313bd46c4c78f6a

See more details on using hashes here.

File details

Details for the file sciqlopplots-0.27.0-cp311-cp311-macosx_13_0_x86_64.whl.

File metadata

File hashes

Hashes for sciqlopplots-0.27.0-cp311-cp311-macosx_13_0_x86_64.whl
Algorithm Hash digest
SHA256 fb015055605754386b96d10f4aef54ab69c121ae9b45083fb4dab5116d8c9ce7
MD5 6f1f4a7db74a094e2c470afa73195709
BLAKE2b-256 f4c315b7a02e0f09af2596a7e9a1ba41e51e0a73866eaafdad8b3a1534af9b47

See more details on using hashes here.

File details

Details for the file sciqlopplots-0.27.0-cp311-cp311-macosx_13_0_arm64.whl.

File metadata

File hashes

Hashes for sciqlopplots-0.27.0-cp311-cp311-macosx_13_0_arm64.whl
Algorithm Hash digest
SHA256 2aa9b1539c75bcb6bb1761a394ade9799e20f923dd61fce4032128231fcc2f04
MD5 bdfa83987a601a75a8b4dd25801a4cdf
BLAKE2b-256 59043575a71c0a5ba6d02146e958519b3b8e8f3c67540554692906796db487d2

See more details on using hashes here.

File details

Details for the file sciqlopplots-0.27.0-cp310-cp310-win_amd64.whl.

File metadata

File hashes

Hashes for sciqlopplots-0.27.0-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 d2442d4d8bddff619256b56a455c4fa87462e89f76657c30f399882ee547ad14
MD5 fa053b37c717e5220dd217863d4c4cf2
BLAKE2b-256 6a241caeecfc16313200aab4fab98ea694d6297966390ebb55bee62adbdb2928

See more details on using hashes here.

File details

Details for the file sciqlopplots-0.27.0-cp310-cp310-manylinux_2_39_aarch64.whl.

File metadata

File hashes

Hashes for sciqlopplots-0.27.0-cp310-cp310-manylinux_2_39_aarch64.whl
Algorithm Hash digest
SHA256 084e98ec65f061b85fe4a126fdd290e810b297e226bf574c86431aff487046ef
MD5 93cda871c060439afa1e333e6d305278
BLAKE2b-256 5e2b8d2903804e80e1a0be61e536af8f5c6d1584dbc902f7f78336a20caa5a65

See more details on using hashes here.

File details

Details for the file sciqlopplots-0.27.0-cp310-cp310-manylinux_2_34_x86_64.whl.

File metadata

File hashes

Hashes for sciqlopplots-0.27.0-cp310-cp310-manylinux_2_34_x86_64.whl
Algorithm Hash digest
SHA256 d91ee6236a687918612b70c64012b8dccdd4af892082273e72b9fa76d5e70834
MD5 fb7965709618bca210e847ed40f86006
BLAKE2b-256 e89a8186dad4e8ceda6c8756ea38714ffe1b319aca0695af1774322c3cf55a05

See more details on using hashes here.

File details

Details for the file sciqlopplots-0.27.0-cp310-cp310-macosx_13_0_x86_64.whl.

File metadata

File hashes

Hashes for sciqlopplots-0.27.0-cp310-cp310-macosx_13_0_x86_64.whl
Algorithm Hash digest
SHA256 5f940dbef1c2c3372da78035ba5380c076a9e29c278bc563eba9360375109fa0
MD5 64c1a7094b99b8c8dc9557f830c4c72e
BLAKE2b-256 1f3ba733ea86c930c11432fb2f85cd2284570afca5884d6e32fc9328eafbdfdf

See more details on using hashes here.

File details

Details for the file sciqlopplots-0.27.0-cp310-cp310-macosx_13_0_arm64.whl.

File metadata

File hashes

Hashes for sciqlopplots-0.27.0-cp310-cp310-macosx_13_0_arm64.whl
Algorithm Hash digest
SHA256 1cb12933063d98972c9e96511f8ecca4579de4d4333b70ec35a201d1273b1e60
MD5 091ead98cfb2428102d80b6356255f93
BLAKE2b-256 993398a6787b42923639198bc5a1d2c00c3a6e45bb23e5de854370aad15d4bd4

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page