Skip to main content

bimpy - bundled imgui for python

bimpy is a a native extension for Python built with C++ and that provides bindings to dear imgui and distributed as a self-contained package bundled with glfw and gl3w

PyPI version

Features:

  • Immediate mode UI with python. The API is kept as close to the original dear imgui as possible.

  • bimpy already has all necessary functionality for window/OpenGL context creation and hides those details from the user.

  • bimpy can display images from ndarrays, PIL Images, numpy arrays, etc.,

  • bimpy works on Windows, GNU Linux, and macOS.

  • bimpy does not have dependencies and can be easily built from sources. Building relies only on distutils.

Hello world with bimpy

Core API tries to map to the Dear ImGui as close as possible. There is additional API, such as bimpy.App class that simplifies bimpy usage

Core API

Using bimpy.App class

import bimpy as bp

ctx = bp.Context()

ctx.init(600, 600, "Hello")

s = bp.String()
f = bp.Float()

while not ctx.should_close():
    with ctx:
        bp.text("Hello, world!")

        if bp.button("OK"):
            print(s.value)

        bp.input_text('string', str, 256)

        bp.slider_float("float", f, 0, 1)
import bimpy as bp


class App(bp.App):
    def __init__(self):
        super(App, self).__init__(title='Test')
        self.s = bp.String()
        self.f = bp.Float()

    def on_update(self):
        bp.text("Hello, world!")

        if bp.button("OK"):
            print(self.s.value)

        bp.input_text('string', self.s, 256)

        bp.slider_float("float", self.f, 0, 1)


app = App()
app.run()

Screenshot from 2020-12-05 08-38-39

Display images

Display PIL image:

import bimpy
from PIL import Image

ctx = bimpy.Context()
ctx.init(800, 800, "Image")

image = Image.open("test.png")
im = bimpy.Image(image)

while not ctx.should_close():
    with ctx:
        bimpy.text("Display PIL Image")
        bimpy.image(im)

Screenshot from 2020-12-06 06-58-02

Similarly, numpy arrays with 2 dimensions, 3 dimensions (2, 3 or 4 channels) of type np.uint8 can be displayed.

Display numpy, ndarray image:

import bimpy
from PIL import Image
import numpy as np

ctx = bimpy.Context()
ctx.init(800, 800, "Image")

image = np.asarray(Image.open("3.png"), dtype=np.uint8)
im = bimpy.Image(image)

while not ctx.should_close():
    with ctx:
        bimpy.text("Display Image of type:")
        bimpy.same_line()
        bimpy.text(str(type(image)))
        bimpy.image(im)

Screenshot from 2020-12-06 07-05-08

More examples here: https://github.com/podgorskiy/bimpy/blob/master/examples/image.py

Non-english text

Use builtin bp.load_fonts to load fonts with CJK, cyrillic, greek characters

import bimpy as bp


ctx = bp.Context()

ctx.init(600, 600, "Hello")

bp.load_fonts(
    chinese=True, 
    latin_ext=True, 
    japanese=True, 
    cyrillic=True
)


while not ctx.should_close():
    with ctx:
        chinese = u"學而不思則罔,思而不學則殆。"
        japanese = u"二兎を追う者は一兎をも得ず。 "

        hiragana = u"あ い う え お か ..."
        katakana = u"ア イ ウ エ オ カ ..."
        kanji = "川 月 木 心 火 左 北 今..."

        ukrainian = "Садок вишневий коло..."
        polish = "Hej, tam gdzieś z nad..."
        russian = "Ночь, улица, фонарь, ..."

        bp.text('Chinese:')
        bp.indent()
        bp.text(chinese)
        bp.unindent()
        bp.text('Japanese:')
        bp.indent()
        bp.text(japanese)
        bp.bullet_text("hiragana: " + hiragana)
        bp.bullet_text("katakana: " + katakana)
        bp.bullet_text("kanji: " + kanji)
        bp.unindent()
        bp.separator()
        bp.text('Ukrainian:')
        bp.indent()
        bp.text(ukrainian)
        bp.unindent()
        bp.separator()
        bp.text('Polish:')
        bp.indent()
        bp.text(polish)
        bp.unindent()
        bp.separator()
        bp.text('Russian:')
        bp.indent()
        bp.text(russian)
        bp.unindent()
        bp.separator()

Screenshot from 2020-12-06 08-31-13

Install

Installation is easy since the package does not have dependencies:

pip install bimpy

Or you can build and install from sources:

python setup.py install

All c/c++ sources are built with distutils. All you need is a compiler with C++11 support.

Windows users, who use python 2.7 may encounter problems, because on Windows, python 2.7 uses MSVC 9.0, which doesn't have support for c++11. However, you still can build it with more recent MSVC (for example MSVC 14.0, which is Visual C++ 2015) using the commands below:

call "%VS140COMNTOOLS%\VsDevCmd.bat"
set VS90COMNTOOLS=%VS140COMNTOOLS%
python setup.py install

If building on Linux, the following dependencies will be needed:

sudo apt-get install mesa-common-dev libxi-dev libxinerama-dev libxrandr-dev libxcursor-dev

To build all wheels for linux package distribution (manylinux) run build_manylinux_wheels.sh.

For testing/debugging there is a CMakeList.txt included. It is not used by setup.py, but can be handy in order to build/debug package from certain IDEs.

How to use it?

Intro

bimpy is python binding for dear imgui <https://github.com/ocornut/imgui>__ and tries to match the C++ API. Also, it has some additional functions to create a window and some other differences.

It has binding for the most functions from dear imgui. All functions are renamed from CamelCase to snake_case, which is more common for python. For example ImGui::InputText is mapped to bimpy.input_text.

Context and window

First of all, you need to import bimpy

import bimpy

Distinctively from dear imgui, bimpy does not have global state (dear imgui has it by default, but it has an option not to have one). So, you will need to create a context.

ctx = bimpy.Context(width, height, name)

Where integers width and height specify the size of the window, and string name is a caption of the window.

All calls to bimpy's API must be within with statement applied to the context object:

with ctx:
    bimpy.text("Hello, world!")

And there must be only one with statement applied to the context object per frame.

Or, a second option is to manualy call ctx.new_frame() before all API calls, and then ctx.render() after.

ctx.new_frame()
bimpy.text("Hello, world!")
ctx.render()

You can have multiple Context objects for multiple windows, however, API is not thread-safe.

Variables

All imgui API that provides user input (such as InputText, SliderFloat, etc.) modifies the variable through the reference to it. However, in python, such objects as integers, floats and strings are passed always by value. Because of this, bimpy provides special wrappers, that allow passing those variables by reference.

For example, to use slider_float, you will need first to create a variable that will hold the state:

f = bimpy.Float();

You can access the value in the following way: f.value

To use it with slider_float simply pass it to that function:

bimpy.slider_float("float slider", f, 0.0, 1.0)

All imgui input functions that provide multiple inputs, like SliderFloat2, SliderInt4, InputInt3, etc. are mapped to equivalent functions, but instead of passing an array of variables, you need to list all variables in the argument list:

f1 = bimpy.Float();
f2 = bimpy.Float();
f3 = bimpy.Float();

while(not ctx.should_close()):
	with ctx:
		bimpy.slider_float3("float", f1, f2, f3, 0.0, 1.0)

Draw commands

Some draw commands are exposed. In contrast to C++ API, the exposed functions are not methods of ImDrawList, but global functions. All drawing functions should be called inside the begin/end calls of a window.

List of exposed drawing functions:

    add_circle(centre: _bimpy.Vec2, radius: float, col: int, num_segments: int=12, thickness: float=1.0) -> None
    add_circle_filled(centre: _bimpy.Vec2, radius: float, col: int, num_segments: int=12) -> None
    add_line(a: _bimpy.Vec2, b: _bimpy.Vec2, col: int, thickness: float=1.0) -> None
    add_quad(a: _bimpy.Vec2, b: _bimpy.Vec2, c: _bimpy.Vec2, d: _bimpy.Vec2, col: int, thickness: float=1.0) -> None
    add_quad_filled(a: _bimpy.Vec2, b: _bimpy.Vec2, c: _bimpy.Vec2, d: _bimpy.Vec2, col: int) -> None
    add_rect(a: _bimpy.Vec2, b: _bimpy.Vec2, col: int, rounding: float=0.0, rounding_corners_flags: int=Corner.All, thickness: float=1.0) -> None
    add_rect_filled(a: _bimpy.Vec2, b: _bimpy.Vec2, col: int, rounding: float=0.0, rounding_corners_flags: int=Corner.All) -> None
    add_rect_filled_multicolor(a: _bimpy.Vec2, b: _bimpy.Vec2, col_upr_left: int, col_upr_right: int, col_bot_right: int, col_bot_lefs: int) -> None
    add_triangle(a: _bimpy.Vec2, b: _bimpy.Vec2, c: _bimpy.Vec2, col: int, thickness: float=1.0) -> None
    add_triangle_filled(a: _bimpy.Vec2, b: _bimpy.Vec2, c: _bimpy.Vec2, col: int) -> None

Simple usage example below:

hello-world

	import bimpy
	import numpy as np

	ctx = bimpy.Context()

	ctx.init(1200, 1200, "Draw Commands Test")

	with ctx:
		bimpy.themes.set_light_theme()

	DATA_POINTS = bimpy.Int(30)
	CLASTERS = bimpy.Int(4)

	std = bimpy.Float(0.5)

	colors = [0x4b19e6, 0x4bb43c, 0x19e1ff, 0xc88200, 0x3182f5, 0xb41e91, 0xf0f046, 0xf032e6, 0xd2f53c,
			  0xfabebe, 0x008080, 0xe6beff, 0xaa6e28, 0xfffac8, 0x800000, 0xaaffc3, 0x808000, 0xffd8b1,
			  0x000080, 0x808080, 0xFFFFFF, 0x000000]

	datapoints = []


	def generate_fake_data():
		datapoints.clear()
		for i in range(CLASTERS.value):
			x = np.random.normal(size=(DATA_POINTS.value, 2))
			alpha = np.random.rand()
			scale = std.value * np.random.rand(2) * np.eye(2, 2)
			position = np.random.rand(2) * 5
			rotation = np.array([[np.cos(alpha), np.sin(alpha)], [-np.sin(alpha), np.cos(alpha)]])
			x = np.matmul(x, scale)
			x = np.matmul(x, rotation)
			x += position
			datapoints.append((x, rotation, position, scale))

	axis = x = np.array([[-1, 0], [1, 0], [0, -1], [0, 1]])

	while not ctx.should_close():
		ctx.new_frame()

		bimpy.set_next_window_pos(bimpy.Vec2(20, 20), bimpy.Condition.Once)
		bimpy.set_next_window_size(bimpy.Vec2(800, 600), bimpy.Condition.Once)
		bimpy.begin("Drawings")

		window_pos = bimpy.get_window_pos()

		center = bimpy.Vec2(100, 100) + window_pos
		m = 100.0
		for i in range(len(datapoints)):
			(x, R, P, S) = datapoints[i]

			for j in range(x.shape[0]):
				point = bimpy.Vec2(x[j, 0], x[j, 1])
				bimpy.add_circle_filled(point * m + center, 5, 0xAF000000 + colors[i], 100)

			axis_ = np.matmul(axis, S * 2.0)
			axis_ = np.matmul(axis_, R) + P

			bimpy.add_line(
				center + bimpy.Vec2(axis_[0, 0], axis_[0, 1]) * m,
				center + bimpy.Vec2(axis_[1, 0], axis_[1, 1]) * m,
				0xFFFF0000, 1)

			bimpy.add_line(
				center + bimpy.Vec2(axis_[2, 0], axis_[2, 1]) * m,
				center + bimpy.Vec2(axis_[3, 0], axis_[3, 1]) * m,
				0xFFFF0000, 1)

		bimpy.end()

		bimpy.set_next_window_pos(bimpy.Vec2(20, 640), bimpy.Condition.Once)
		bimpy.set_next_window_size(bimpy.Vec2(800, 140), bimpy.Condition.Once)
		bimpy.begin("Controls")

		bimpy.input_int("Data points count", DATA_POINTS)
		bimpy.input_int("Clasters count", CLASTERS)

		bimpy.slider_float("std", std, 0.0, 3.0)

		if bimpy.button("Generate data"):
			generate_fake_data()

		bimpy.end()

		ctx.render()

Acknowledgements

Metadata

Release files for bimpy 0.1.1

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for bimpy 0.1.1
File Size Uploaded
bimpy-0.1.1.tar.gz 1.2 MB Details

Built distributions (wheels)

Table of built distributions (wheels) for bimpy 0.1.1
File
bimpy-0.1.1-cp39-cp39-manylinux2010_x86_64.whl CPython 3.9 CPython 3.9 Linux glibc 2.12+ x86-64 Details
bimpy-0.1.1-cp38-cp38-win_amd64.whl CPython 3.8 CPython 3.8 Windows x86-64 Details
bimpy-0.1.1-cp38-cp38-win32.whl CPython 3.8 CPython 3.8 Windows x86-32 Details
bimpy-0.1.1-cp38-cp38-manylinux2010_x86_64.whl CPython 3.8 CPython 3.8 Linux glibc 2.12+ x86-64 Details
bimpy-0.1.1-cp37-cp37m-win_amd64.whl CPython 3.7 CPython 3.7 pymalloc Windows x86-64 Details
bimpy-0.1.1-cp37-cp37m-win32.whl CPython 3.7 CPython 3.7 pymalloc Windows x86-32 Details
bimpy-0.1.1-cp37-cp37m-manylinux2010_x86_64.whl CPython 3.7 CPython 3.7 pymalloc Linux glibc 2.12+ x86-64 Details
bimpy-0.1.1-cp36-cp36m-win_amd64.whl CPython 3.6 CPython 3.6 pymalloc Windows x86-64 Details
bimpy-0.1.1-cp36-cp36m-win32.whl CPython 3.6 CPython 3.6 pymalloc Windows x86-32 Details
bimpy-0.1.1-cp36-cp36m-manylinux2010_x86_64.whl CPython 3.6 CPython 3.6 pymalloc Linux glibc 2.12+ x86-64 Details
bimpy-0.1.1-cp35-cp35m-manylinux2010_x86_64.whl CPython 3.5 CPython 3.5 pymalloc Linux glibc 2.12+ x86-64 Details
bimpy-0.1.1-cp27-cp27mu-manylinux2010_x86_64.whl CPython 2.7 CPython 2.7 pymalloc wide-unicode Linux glibc 2.12+ x86-64 Details
bimpy-0.1.1-cp27-cp27m-win_amd64.whl CPython 2.7 CPython 2.7 pymalloc Windows x86-64 Details
bimpy-0.1.1-cp27-cp27m-win32.whl CPython 2.7 CPython 2.7 pymalloc Windows x86-32 Details
bimpy-0.1.1-cp27-cp27m-manylinux2010_x86_64.whl CPython 2.7 CPython 2.7 pymalloc Linux glibc 2.12+ x86-64 Details

Total release size: 51.6 MB

Release files / bimpy-0.1.1.tar.gz

Download URL bimpy-0.1.1.tar.gz
Size 1.2 MB
Tags Source
SHA-256 checksum
How to use checksums
20a715fd388e8e87a6fc305739108088c3f9eeab3bb7d2c326a69ba16b82d0c1
BLAKE2b-256 checksum
How to use checksums
5910fa47d72afbea9205804b96f3f13f56f6da0297837c05305d44776c3ebdf8
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.2.0 pkginfo/1.6.1 requests/2.25.0 setuptools/50.3.2 requests-toolbelt/0.9.1 tqdm/4.54.1 CPython/3.6.9

Release files / bimpy-0.1.1-cp39-cp39-manylinux2010_x86_64.whl

Download URL bimpy-0.1.1-cp39-cp39-manylinux2010_x86_64.whl
Size 6.1 MB
Tags CPython 3.9 Linux glibc 2.12+ x86-64
SHA-256 checksum
How to use checksums
2695561113724b947b724f0bcd1e6f1dbe8f0f3f07a29939a668476f102c8761
BLAKE2b-256 checksum
How to use checksums
2ae8954813be9e3d023902b7be245d8ada765554552d9512536fd78264ab92ab
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.2.0 pkginfo/1.6.1 requests/2.25.0 setuptools/50.3.2 requests-toolbelt/0.9.1 tqdm/4.54.1 CPython/3.6.9

Release files / bimpy-0.1.1-cp38-cp38-win_amd64.whl

Download URL bimpy-0.1.1-cp38-cp38-win_amd64.whl
Size 861.6 kB
Tags CPython 3.8 Windows x86-64
SHA-256 checksum
How to use checksums
95b6642fc4f9c9b234cd3cd117fda0c0908ded044c87b98c5e3c1d239caffebd
BLAKE2b-256 checksum
How to use checksums
23163b930238099f604822d62cd28383541ec53cb341fe0d94262abc1722b498
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.2.0 pkginfo/1.6.1 requests/2.25.0 setuptools/50.3.2 requests-toolbelt/0.9.1 tqdm/4.54.0 CPython/3.6.6

Release files / bimpy-0.1.1-cp38-cp38-win32.whl

Download URL bimpy-0.1.1-cp38-cp38-win32.whl
Size 730.7 kB
Tags CPython 3.8 Windows x86-32
SHA-256 checksum
How to use checksums
6f59dff46a2bf57b6d2bf377a95996cf11a2e5e0b0fa29f8bb26a191ae2653f8
BLAKE2b-256 checksum
How to use checksums
90dc24fc1798723d831820f2bbe112bd84b0fefc2efef76ebec9a6c55f78dbd1
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.2.0 pkginfo/1.6.1 requests/2.25.0 setuptools/50.3.2 requests-toolbelt/0.9.1 tqdm/4.54.0 CPython/3.6.6

Release files / bimpy-0.1.1-cp38-cp38-manylinux2010_x86_64.whl

Download URL bimpy-0.1.1-cp38-cp38-manylinux2010_x86_64.whl
Size 6.1 MB
Tags CPython 3.8 Linux glibc 2.12+ x86-64
SHA-256 checksum
How to use checksums
b806de4a301f174ec5c30077e1da8ebe88c650fe38034447e0e9ebf9e7f599b1
BLAKE2b-256 checksum
How to use checksums
d6a2f0c3df59d830df71c7b73ecb2298d26dfb7d13c976fb41b6dffa15768223
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.2.0 pkginfo/1.6.1 requests/2.25.0 setuptools/50.3.2 requests-toolbelt/0.9.1 tqdm/4.54.1 CPython/3.6.9

Release files / bimpy-0.1.1-cp37-cp37m-win_amd64.whl

Download URL bimpy-0.1.1-cp37-cp37m-win_amd64.whl
Size 857.7 kB
Tags CPython 3.7 CPython 3.7 pymalloc Windows x86-64
SHA-256 checksum
How to use checksums
168f023dfa91706d3640ede80518437f6ee3ffa65d08a34f7efd23928b25c830
BLAKE2b-256 checksum
How to use checksums
dd59bfb489a77cc80f6b4e8dcfdafc39e8931cddefa505d84a5ab00fa230fce5
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.2.0 pkginfo/1.6.1 requests/2.25.0 setuptools/50.3.2 requests-toolbelt/0.9.1 tqdm/4.54.0 CPython/3.6.6

Release files / bimpy-0.1.1-cp37-cp37m-win32.whl

Download URL bimpy-0.1.1-cp37-cp37m-win32.whl
Size 731.8 kB
Tags CPython 3.7 CPython 3.7 pymalloc Windows x86-32
SHA-256 checksum
How to use checksums
ffc9b25782b9544620ae8628ee06f6f92b9bd3fef9c12f71b907d9afbba267c4
BLAKE2b-256 checksum
How to use checksums
812ee5b9e8a171fc229080d9b4062b12333096c87c9980fc986b35338d3e49b8
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.2.0 pkginfo/1.6.1 requests/2.25.0 setuptools/50.3.2 requests-toolbelt/0.9.1 tqdm/4.54.0 CPython/3.6.6

Release files / bimpy-0.1.1-cp37-cp37m-manylinux2010_x86_64.whl

Download URL bimpy-0.1.1-cp37-cp37m-manylinux2010_x86_64.whl
Size 6.4 MB
Tags CPython 3.7 CPython 3.7 pymalloc Linux glibc 2.12+ x86-64
SHA-256 checksum
How to use checksums
fa716591b218567520bf752ff0a45ce11178f937a298767da0b4f9ec8edceda4
BLAKE2b-256 checksum
How to use checksums
6efd819c2c84c724f58e2859d01c0bf4d4328403de83666c5b90e5b91c165e1e
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.2.0 pkginfo/1.6.1 requests/2.25.0 setuptools/50.3.2 requests-toolbelt/0.9.1 tqdm/4.54.1 CPython/3.6.9

Release files / bimpy-0.1.1-cp36-cp36m-win_amd64.whl

Download URL bimpy-0.1.1-cp36-cp36m-win_amd64.whl
Size 857.6 kB
Tags CPython 3.6 CPython 3.6 pymalloc Windows x86-64
SHA-256 checksum
How to use checksums
286a0d1e9c99f3c53d91611c9043a955b9e176c441c5de860af98c4a92f76bed
BLAKE2b-256 checksum
How to use checksums
b354db88d629afef15daa51f9bcafb411c66dee85a4a28a30a9f14bdf6c597dd
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.2.0 pkginfo/1.6.1 requests/2.25.0 setuptools/50.3.2 requests-toolbelt/0.9.1 tqdm/4.54.0 CPython/3.6.6

Release files / bimpy-0.1.1-cp36-cp36m-win32.whl

Download URL bimpy-0.1.1-cp36-cp36m-win32.whl
Size 731.7 kB
Tags CPython 3.6 CPython 3.6 pymalloc Windows x86-32
SHA-256 checksum
How to use checksums
eb203c33f75f22edf30465d7b6faca88096857c7f61e8bc7f0626e6f2bea7008
BLAKE2b-256 checksum
How to use checksums
490930b899521b535b7c7eb7b7a963f7abb64a4ebfa7fe84f21388c5225e7c8c
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.2.0 pkginfo/1.6.1 requests/2.25.0 setuptools/50.3.2 requests-toolbelt/0.9.1 tqdm/4.54.0 CPython/3.6.6

Release files / bimpy-0.1.1-cp36-cp36m-manylinux2010_x86_64.whl

Download URL bimpy-0.1.1-cp36-cp36m-manylinux2010_x86_64.whl
Size 6.4 MB
Tags CPython 3.6 CPython 3.6 pymalloc Linux glibc 2.12+ x86-64
SHA-256 checksum
How to use checksums
98c6fdb653481e91a7aea72eae523d542ddd6ac494e602bcc3a8ba1ac483e8d0
BLAKE2b-256 checksum
How to use checksums
86891ad41fb0d88b7ef1b007f030acf26f401367f5608c51ee041a481e50dcb7
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.2.0 pkginfo/1.6.1 requests/2.25.0 setuptools/50.3.2 requests-toolbelt/0.9.1 tqdm/4.54.1 CPython/3.6.9

Release files / bimpy-0.1.1-cp35-cp35m-manylinux2010_x86_64.whl

Download URL bimpy-0.1.1-cp35-cp35m-manylinux2010_x86_64.whl
Size 6.4 MB
Tags CPython 3.5 CPython 3.5 pymalloc Linux glibc 2.12+ x86-64
SHA-256 checksum
How to use checksums
890c36cc132804e9da596fe8211eecf46fab3d5605ba771629a9938b9ddbaa68
BLAKE2b-256 checksum
How to use checksums
77540cfc0ef3687055410342f1aaa517496f732b5ec74d417e34bc1d8ae72a5a
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.2.0 pkginfo/1.6.1 requests/2.25.0 setuptools/50.3.2 requests-toolbelt/0.9.1 tqdm/4.54.1 CPython/3.6.9

Release files / bimpy-0.1.1-cp27-cp27mu-manylinux2010_x86_64.whl

Download URL bimpy-0.1.1-cp27-cp27mu-manylinux2010_x86_64.whl
Size 6.3 MB
Tags CPython 2.7 CPython 2.7 pymalloc wide-unicode Linux glibc 2.12+ x86-64
SHA-256 checksum
How to use checksums
36d0501c74a62c23f6f86b34a8764dbc508b23b20e49424e53f177dfca8e7f54
BLAKE2b-256 checksum
How to use checksums
a1c7240e868de8ee0b7ae612003eb8167bc156d0975e26f8ec1fee169b28da11
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.2.0 pkginfo/1.6.1 requests/2.25.0 setuptools/50.3.2 requests-toolbelt/0.9.1 tqdm/4.54.1 CPython/3.6.9

Release files / bimpy-0.1.1-cp27-cp27m-win_amd64.whl

Download URL bimpy-0.1.1-cp27-cp27m-win_amd64.whl
Size 818.9 kB
Tags CPython 2.7 CPython 2.7 pymalloc Windows x86-64
SHA-256 checksum
How to use checksums
f67ab369f1f941d9b704f0b7063117e3192a3ce2f272e340274bd05cf04d2ee5
BLAKE2b-256 checksum
How to use checksums
230beed2f97028dc02a1c7e5507eb928e2af6403e6381c293bad22b36bc679e6
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.2.0 pkginfo/1.6.1 requests/2.25.0 setuptools/50.3.2 requests-toolbelt/0.9.1 tqdm/4.54.0 CPython/3.6.6

Release files / bimpy-0.1.1-cp27-cp27m-win32.whl

Download URL bimpy-0.1.1-cp27-cp27m-win32.whl
Size 697.5 kB
Tags CPython 2.7 CPython 2.7 pymalloc Windows x86-32
SHA-256 checksum
How to use checksums
7313b9e798f29255ba98298b0b8e430fa672d5ca62cb5c8cb8108c92059dd09a
BLAKE2b-256 checksum
How to use checksums
8ae930fd84ee59d4cce98714d85e53748cd3f5b5510a00a4b06122fad3ec793d
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.2.0 pkginfo/1.6.1 requests/2.25.0 setuptools/50.3.2 requests-toolbelt/0.9.1 tqdm/4.54.0 CPython/3.6.6

Release files / bimpy-0.1.1-cp27-cp27m-manylinux2010_x86_64.whl

Download URL bimpy-0.1.1-cp27-cp27m-manylinux2010_x86_64.whl
Size 6.3 MB
Tags CPython 2.7 CPython 2.7 pymalloc Linux glibc 2.12+ x86-64
SHA-256 checksum
How to use checksums
6fb58a9505bb47797f420949519963d971880669fcb183cb9275db63e3c1fd91
BLAKE2b-256 checksum
How to use checksums
c7f0976909aea2b4e2cc2f073af2ac1d1fe7c4500d7f35ca4b388a4e37c68d7c
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.2.0 pkginfo/1.6.1 requests/2.25.0 setuptools/50.3.2 requests-toolbelt/0.9.1 tqdm/4.54.1 CPython/3.6.9

Release history Release notifications | RSS feed

This release

0.1.1 This release

16 release files

0.0.9

5 release files

0.0.8

6 release files

0.0.7

5 release files

0.0.6

5 release files

0.0.5

8 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page