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-0.25.0.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-0.25.0-cp314-cp314-win_amd64.whl (3.0 MB view details)

Uploaded CPython 3.14Windows x86-64

sciqlopplots-0.25.0-cp314-cp314-manylinux_2_39_aarch64.whl (4.6 MB view details)

Uploaded CPython 3.14manylinux: glibc 2.39+ ARM64

sciqlopplots-0.25.0-cp314-cp314-manylinux_2_34_x86_64.whl (5.0 MB view details)

Uploaded CPython 3.14manylinux: glibc 2.34+ x86-64

sciqlopplots-0.25.0-cp314-cp314-macosx_13_0_x86_64.whl (4.0 MB view details)

Uploaded CPython 3.14macOS 13.0+ x86-64

sciqlopplots-0.25.0-cp314-cp314-macosx_13_0_arm64.whl (3.6 MB view details)

Uploaded CPython 3.14macOS 13.0+ ARM64

sciqlopplots-0.25.0-cp313-cp313-win_amd64.whl (2.9 MB view details)

Uploaded CPython 3.13Windows x86-64

sciqlopplots-0.25.0-cp313-cp313-manylinux_2_39_aarch64.whl (4.6 MB view details)

Uploaded CPython 3.13manylinux: glibc 2.39+ ARM64

sciqlopplots-0.25.0-cp313-cp313-manylinux_2_34_x86_64.whl (5.0 MB view details)

Uploaded CPython 3.13manylinux: glibc 2.34+ x86-64

sciqlopplots-0.25.0-cp313-cp313-macosx_13_0_x86_64.whl (4.0 MB view details)

Uploaded CPython 3.13macOS 13.0+ x86-64

sciqlopplots-0.25.0-cp313-cp313-macosx_13_0_arm64.whl (3.6 MB view details)

Uploaded CPython 3.13macOS 13.0+ ARM64

sciqlopplots-0.25.0-cp312-cp312-win_amd64.whl (2.9 MB view details)

Uploaded CPython 3.12Windows x86-64

sciqlopplots-0.25.0-cp312-cp312-manylinux_2_39_aarch64.whl (4.6 MB view details)

Uploaded CPython 3.12manylinux: glibc 2.39+ ARM64

sciqlopplots-0.25.0-cp312-cp312-manylinux_2_34_x86_64.whl (5.0 MB view details)

Uploaded CPython 3.12manylinux: glibc 2.34+ x86-64

sciqlopplots-0.25.0-cp312-cp312-macosx_13_0_x86_64.whl (4.0 MB view details)

Uploaded CPython 3.12macOS 13.0+ x86-64

sciqlopplots-0.25.0-cp312-cp312-macosx_13_0_arm64.whl (3.6 MB view details)

Uploaded CPython 3.12macOS 13.0+ ARM64

sciqlopplots-0.25.0-cp311-cp311-win_amd64.whl (2.9 MB view details)

Uploaded CPython 3.11Windows x86-64

sciqlopplots-0.25.0-cp311-cp311-manylinux_2_39_aarch64.whl (4.6 MB view details)

Uploaded CPython 3.11manylinux: glibc 2.39+ ARM64

sciqlopplots-0.25.0-cp311-cp311-manylinux_2_34_x86_64.whl (5.0 MB view details)

Uploaded CPython 3.11manylinux: glibc 2.34+ x86-64

sciqlopplots-0.25.0-cp311-cp311-macosx_13_0_x86_64.whl (4.0 MB view details)

Uploaded CPython 3.11macOS 13.0+ x86-64

sciqlopplots-0.25.0-cp311-cp311-macosx_13_0_arm64.whl (3.6 MB view details)

Uploaded CPython 3.11macOS 13.0+ ARM64

sciqlopplots-0.25.0-cp310-cp310-win_amd64.whl (2.9 MB view details)

Uploaded CPython 3.10Windows x86-64

sciqlopplots-0.25.0-cp310-cp310-manylinux_2_39_aarch64.whl (4.6 MB view details)

Uploaded CPython 3.10manylinux: glibc 2.39+ ARM64

sciqlopplots-0.25.0-cp310-cp310-manylinux_2_34_x86_64.whl (5.0 MB view details)

Uploaded CPython 3.10manylinux: glibc 2.34+ x86-64

sciqlopplots-0.25.0-cp310-cp310-macosx_13_0_x86_64.whl (4.0 MB view details)

Uploaded CPython 3.10macOS 13.0+ x86-64

sciqlopplots-0.25.0-cp310-cp310-macosx_13_0_arm64.whl (3.6 MB view details)

Uploaded CPython 3.10macOS 13.0+ ARM64

File details

Details for the file sciqlopplots-0.25.0.tar.gz.

File metadata

  • Download URL: sciqlopplots-0.25.0.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-0.25.0.tar.gz
Algorithm Hash digest
SHA256 be79cd33bd5268b4992dae17bb1c105b4ba85c2588e55f7c75c7803a8069c151
MD5 4718068ea275c66154158a5bba22dedd
BLAKE2b-256 3941b737771d01799747400e6d15b08cd644b3ae7a823ce74db2fd3caf8fa4c8

See more details on using hashes here.

File details

Details for the file sciqlopplots-0.25.0-cp314-cp314-win_amd64.whl.

File metadata

File hashes

Hashes for sciqlopplots-0.25.0-cp314-cp314-win_amd64.whl
Algorithm Hash digest
SHA256 cde63629567682d8b9dceb0c58d1b139dfeb7cf57c22efb21205de9adb20afed
MD5 bd77b6d766a4947c783f74f5cfaea312
BLAKE2b-256 1840cb2c67011053cb5586ae61e2357381e151bbae61f8500e70b45048919f3b

See more details on using hashes here.

File details

Details for the file sciqlopplots-0.25.0-cp314-cp314-manylinux_2_39_aarch64.whl.

File metadata

File hashes

Hashes for sciqlopplots-0.25.0-cp314-cp314-manylinux_2_39_aarch64.whl
Algorithm Hash digest
SHA256 30bf59c0a031ab1377e4ccc135faf1c902fa6f5d473bcf94f954fefd55b13e68
MD5 930ea5963927bfa13e0e7cd609eb4260
BLAKE2b-256 862f94b8b8cd84f2cd32e4df28d40bb5332ed2415dc2c62cab3c7b74dd53471d

See more details on using hashes here.

File details

Details for the file sciqlopplots-0.25.0-cp314-cp314-manylinux_2_34_x86_64.whl.

File metadata

File hashes

Hashes for sciqlopplots-0.25.0-cp314-cp314-manylinux_2_34_x86_64.whl
Algorithm Hash digest
SHA256 6053f7ee60e5a0e65851ef426b376065a3b3c664d8699d6a20480331d56c0021
MD5 2c38eeec4998f6cc11e54fb8f72590f4
BLAKE2b-256 315894b970deb35404f30e518576b07119bbb6b1de6de083f4adfc9f00c3bde7

See more details on using hashes here.

File details

Details for the file sciqlopplots-0.25.0-cp314-cp314-macosx_13_0_x86_64.whl.

File metadata

File hashes

Hashes for sciqlopplots-0.25.0-cp314-cp314-macosx_13_0_x86_64.whl
Algorithm Hash digest
SHA256 bf6fbbbc43b0fd9277735711eea5309e8f9e357ec02a2da00e46c4eaceb81535
MD5 8a5c020ef63d2deaeeb2c2dc30517320
BLAKE2b-256 8f940a6d58a0f004b7604081ef9bcde4f292e6f5bc68de27d435fc8bafe1b40c

See more details on using hashes here.

File details

Details for the file sciqlopplots-0.25.0-cp314-cp314-macosx_13_0_arm64.whl.

File metadata

File hashes

Hashes for sciqlopplots-0.25.0-cp314-cp314-macosx_13_0_arm64.whl
Algorithm Hash digest
SHA256 79ea56fb9cfcc78ddc69502eeadc7f67bdc2cf27aae7fcdcbfab65ed343b0d78
MD5 a482e72bd706f386550f12b24d3e5ab8
BLAKE2b-256 ef1fd10c2a0aa3e2515417081b00b8a30cee1640311f6506e91cd676d1f4d39f

See more details on using hashes here.

File details

Details for the file sciqlopplots-0.25.0-cp313-cp313-win_amd64.whl.

File metadata

File hashes

Hashes for sciqlopplots-0.25.0-cp313-cp313-win_amd64.whl
Algorithm Hash digest
SHA256 c6ec5f0e07c19aa73d2f077bfdc7856e33b26a5ed0d31eb0cfcb23af34d0e7da
MD5 d04d6d8286fdc852b8b6c63e68998420
BLAKE2b-256 89b06b75a09f944e1f1a55da25d9e9d64817c05582b13aab3fd474529915cc8c

See more details on using hashes here.

File details

Details for the file sciqlopplots-0.25.0-cp313-cp313-manylinux_2_39_aarch64.whl.

File metadata

File hashes

Hashes for sciqlopplots-0.25.0-cp313-cp313-manylinux_2_39_aarch64.whl
Algorithm Hash digest
SHA256 93bcdc31aba1a28285c27c83cc24ad931cb6bcffc27d65a7b305af2a3432c960
MD5 beb78e6ee4b7a8377a8a74c734cf108d
BLAKE2b-256 01aa1818abcce71a0df80f764aecc8ac259eca915ef137635d1da1ba88048638

See more details on using hashes here.

File details

Details for the file sciqlopplots-0.25.0-cp313-cp313-manylinux_2_34_x86_64.whl.

File metadata

File hashes

Hashes for sciqlopplots-0.25.0-cp313-cp313-manylinux_2_34_x86_64.whl
Algorithm Hash digest
SHA256 edbef71b453245902646f34d91093168c876bdf7724b8ee7f031218548f1157c
MD5 7c46d97ce9b7193f0f0e9db0f6b20197
BLAKE2b-256 bbaf30a7dd858cf5caa193b86085220e14c1f305fa6459fc04f996e6e0f748ec

See more details on using hashes here.

File details

Details for the file sciqlopplots-0.25.0-cp313-cp313-macosx_13_0_x86_64.whl.

File metadata

File hashes

Hashes for sciqlopplots-0.25.0-cp313-cp313-macosx_13_0_x86_64.whl
Algorithm Hash digest
SHA256 b10f391e28fe6ea102c736ff5bafafcb5b0640a6798d855a9bdd766b9453445f
MD5 ab1c84fca990105c7d67ab8216c8295c
BLAKE2b-256 0663e275f3d47ffbd5a9ab8eefc589eb5342d2ea70230d85291755130492477b

See more details on using hashes here.

File details

Details for the file sciqlopplots-0.25.0-cp313-cp313-macosx_13_0_arm64.whl.

File metadata

File hashes

Hashes for sciqlopplots-0.25.0-cp313-cp313-macosx_13_0_arm64.whl
Algorithm Hash digest
SHA256 0479d71d370c29d0dac574c36f12c90c5517ec7daa7d56743e366e8fbc8a2a67
MD5 46a34cec0d4d67c3a510314fab9bfe29
BLAKE2b-256 c227f1451cfe10e241885dc64441392a51735045b20a48800c4cac39e77832a9

See more details on using hashes here.

File details

Details for the file sciqlopplots-0.25.0-cp312-cp312-win_amd64.whl.

File metadata

File hashes

Hashes for sciqlopplots-0.25.0-cp312-cp312-win_amd64.whl
Algorithm Hash digest
SHA256 4906dc7cdcec1609c7a8da55d1c0a9f998f0b37553f83b6ab87e72fcbdcaf966
MD5 35068aa5300433be34ce0c0cc1da9e86
BLAKE2b-256 0c3b6df3b211921f8e4a30a10018b26fa49c3b2d537247046491557383f9f62f

See more details on using hashes here.

File details

Details for the file sciqlopplots-0.25.0-cp312-cp312-manylinux_2_39_aarch64.whl.

File metadata

File hashes

Hashes for sciqlopplots-0.25.0-cp312-cp312-manylinux_2_39_aarch64.whl
Algorithm Hash digest
SHA256 36e6f73188a8a39699ae5905498b5efe3870da0b370854ea6b7a50d914ac638c
MD5 9aa8d3514c018776d77e0df340aab0df
BLAKE2b-256 54ead3feb9bbcd50d197e1295d021157461e1eef97bdd524ba369249f597d773

See more details on using hashes here.

File details

Details for the file sciqlopplots-0.25.0-cp312-cp312-manylinux_2_34_x86_64.whl.

File metadata

File hashes

Hashes for sciqlopplots-0.25.0-cp312-cp312-manylinux_2_34_x86_64.whl
Algorithm Hash digest
SHA256 2912de7cce9545c349265a93e620e5e415118da5ee6fc1d46404ed58213bbd67
MD5 a6c726f39fab81ada2d4323c89243dda
BLAKE2b-256 bc0a546cdb708eb51f1a2e25a9e1bb5f8eff570671a827e84913e9a23f79f0b1

See more details on using hashes here.

File details

Details for the file sciqlopplots-0.25.0-cp312-cp312-macosx_13_0_x86_64.whl.

File metadata

File hashes

Hashes for sciqlopplots-0.25.0-cp312-cp312-macosx_13_0_x86_64.whl
Algorithm Hash digest
SHA256 1305ef0cc45a21e4a30b1d980d7ac372e2f14cf9abff0f7de235e20188ba6fd2
MD5 fefac227e8886ee987019527a5edbf8e
BLAKE2b-256 4d9eae922eaf41c892dc68a10947824c98afdd19a14bfd376f181b6097980677

See more details on using hashes here.

File details

Details for the file sciqlopplots-0.25.0-cp312-cp312-macosx_13_0_arm64.whl.

File metadata

File hashes

Hashes for sciqlopplots-0.25.0-cp312-cp312-macosx_13_0_arm64.whl
Algorithm Hash digest
SHA256 68961971612678757d164706c2affa106f241b77890e40d1c5558b64fae08ec0
MD5 8e5e78fe81f85dc37ba62836547ee19a
BLAKE2b-256 341fbc62a6f6cc45a16358addf97564c981e3fec432ec2d0d816541845c9dcce

See more details on using hashes here.

File details

Details for the file sciqlopplots-0.25.0-cp311-cp311-win_amd64.whl.

File metadata

File hashes

Hashes for sciqlopplots-0.25.0-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 9d7608d52f2fcabeafab624317821458df7e7e96bc512aa884af35bdfa26abae
MD5 f0ee3e6b6e684a50a99f4baf42048b88
BLAKE2b-256 fca8c5cff659bdf213d81f9c2f665c9e6b1b98089a12202eee4dad298b5dafdd

See more details on using hashes here.

File details

Details for the file sciqlopplots-0.25.0-cp311-cp311-manylinux_2_39_aarch64.whl.

File metadata

File hashes

Hashes for sciqlopplots-0.25.0-cp311-cp311-manylinux_2_39_aarch64.whl
Algorithm Hash digest
SHA256 8479c14f21f75feda07fde3389d0e1d5d067f09a382049b55278d65a0eb656bd
MD5 21e4715b3b063e189e90d2162a32325e
BLAKE2b-256 87dbaa3e16aeeabeefed0aca23ca837c2262dc0d9b4453308147147c92c63776

See more details on using hashes here.

File details

Details for the file sciqlopplots-0.25.0-cp311-cp311-manylinux_2_34_x86_64.whl.

File metadata

File hashes

Hashes for sciqlopplots-0.25.0-cp311-cp311-manylinux_2_34_x86_64.whl
Algorithm Hash digest
SHA256 39b27b147dc47174376d3e712ed6b2490fca8211fde07d071ca2cc6ae77e55b0
MD5 371528c6ad36e371f68dec9f9d925f2d
BLAKE2b-256 9028910007356685ae4f1f345ae567d6d09498f123e93f6f79037e8b07c42976

See more details on using hashes here.

File details

Details for the file sciqlopplots-0.25.0-cp311-cp311-macosx_13_0_x86_64.whl.

File metadata

File hashes

Hashes for sciqlopplots-0.25.0-cp311-cp311-macosx_13_0_x86_64.whl
Algorithm Hash digest
SHA256 8312cfb81799b3e462103148f06fbb35d24beafaabeacc97b8a6817e38a108ad
MD5 1fe5a9059a4db92378598538da35f5dc
BLAKE2b-256 b98a0705a24d00445cb12fc40fc78f07290ce4a643dbf3fa8bb01d8ea9c52e48

See more details on using hashes here.

File details

Details for the file sciqlopplots-0.25.0-cp311-cp311-macosx_13_0_arm64.whl.

File metadata

File hashes

Hashes for sciqlopplots-0.25.0-cp311-cp311-macosx_13_0_arm64.whl
Algorithm Hash digest
SHA256 42c56f0618ba8f287cc3f0c53f2551498191cd291c65b417ac01f3d4a64bea8e
MD5 24b826950b8720b3c868a6e9b4dd6f76
BLAKE2b-256 a48d9b4e7bdce9138bc620626c56ff9d5c86e3035bb74495679a72d9c1ef62e3

See more details on using hashes here.

File details

Details for the file sciqlopplots-0.25.0-cp310-cp310-win_amd64.whl.

File metadata

File hashes

Hashes for sciqlopplots-0.25.0-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 74f17c65e2070f73e364b1bf1f18156801b398b9d0c90396cef3282a1276a5f9
MD5 0c1d1def8af18b1e20ce5b94793c551d
BLAKE2b-256 5599a0e03d792a0ee8da48d8d58589d7753a97bcd11b043b1a1edd46b65084e5

See more details on using hashes here.

File details

Details for the file sciqlopplots-0.25.0-cp310-cp310-manylinux_2_39_aarch64.whl.

File metadata

File hashes

Hashes for sciqlopplots-0.25.0-cp310-cp310-manylinux_2_39_aarch64.whl
Algorithm Hash digest
SHA256 37352750c6efd4bffc9ff151e27f5b5fc772036881688ca6748fa56d9064a013
MD5 5b220613987f93857264e1b987ed3fc9
BLAKE2b-256 7164cf7eac4254e8c4111993bf4f2ceece3972704697cc330da6cd63977c52e8

See more details on using hashes here.

File details

Details for the file sciqlopplots-0.25.0-cp310-cp310-manylinux_2_34_x86_64.whl.

File metadata

File hashes

Hashes for sciqlopplots-0.25.0-cp310-cp310-manylinux_2_34_x86_64.whl
Algorithm Hash digest
SHA256 c8f3a2b3e9870e86029e0da846bcdce03f0cc288e24cdeb22c8f0a2d5a310723
MD5 930352a6373ecbaff301d65f3369bf1e
BLAKE2b-256 04bd1de3296a1868ce863ea13499d8aeda5912e3e515142fc193523490f5e268

See more details on using hashes here.

File details

Details for the file sciqlopplots-0.25.0-cp310-cp310-macosx_13_0_x86_64.whl.

File metadata

File hashes

Hashes for sciqlopplots-0.25.0-cp310-cp310-macosx_13_0_x86_64.whl
Algorithm Hash digest
SHA256 806e327f3e6c3bd139a4153caff4eefa47213bc3d4499bd73e0fca166f78c6a5
MD5 6458de572b09b43b4fadc186add1c95a
BLAKE2b-256 a2ca0a62d4624792a7711d62bb26d5bae48f8cdecf93c3f1a6ed11d7315de4fa

See more details on using hashes here.

File details

Details for the file sciqlopplots-0.25.0-cp310-cp310-macosx_13_0_arm64.whl.

File metadata

File hashes

Hashes for sciqlopplots-0.25.0-cp310-cp310-macosx_13_0_arm64.whl
Algorithm Hash digest
SHA256 c116bc84bf2893ca38a37fe814a12f17473d7e14103404d2a84048a4089264d3
MD5 74e55579e0799ac9b43c6bdaca1d4dd6
BLAKE2b-256 9ad66fb9b82766a9dcbee6fa6e880d2a12306934799e5d8345b3f3f387bd7ad2

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