improve contrast norm and sharpness measurement
This commit is contained in:
Brent Schroeter
parent
3da76d4537
commit
d48b672e1b
6 changed files with 133 additions and 340 deletions
|
|
@ -40,7 +40,7 @@ def main():
|
||||||
t_start = time()
|
t_start = time()
|
||||||
|
|
||||||
minimal_docs = (
|
minimal_docs = (
|
||||||
[doc for doc in item.docs if doc.name != ""]
|
[doc for doc in item.docs if doc.name != doc.identifier]
|
||||||
if len(item.docs) > 1
|
if len(item.docs) > 1
|
||||||
else item.docs
|
else item.docs
|
||||||
)
|
)
|
||||||
|
|
|
||||||
|
|
@ -1,7 +1,7 @@
|
||||||
from sys import stdout
|
from sys import stdout
|
||||||
|
|
||||||
import numpy as np
|
import numpy as np
|
||||||
from PIL import Image, ImageFilter
|
from PIL import Image, ImageChops, ImageFilter
|
||||||
|
|
||||||
from .items import ArchiveDoc, ArchiveLeaf
|
from .items import ArchiveDoc, ArchiveLeaf
|
||||||
from .ocr import OcrEngine, TextBlock
|
from .ocr import OcrEngine, TextBlock
|
||||||
|
|
@ -30,52 +30,17 @@ def analyze_doc(
|
||||||
|
|
||||||
analyzed_pages = []
|
analyzed_pages = []
|
||||||
for leaf in all_leaves:
|
for leaf in all_leaves:
|
||||||
im_cropped = leaf.image.crop(
|
im, is_blank = normalize_contrast_for_text(leaf.image)
|
||||||
(
|
|
||||||
leaf.image.size[0] * 0.1,
|
|
||||||
leaf.image.size[1] * 0.1,
|
|
||||||
leaf.image.size[0] * 0.9,
|
|
||||||
leaf.image.size[1] * 0.9,
|
|
||||||
)
|
|
||||||
)
|
|
||||||
|
|
||||||
is_blank = im_cropped.getextrema()[0] > 255 * 0.8
|
im_cropped = im.crop(
|
||||||
|
|
||||||
if is_blank:
|
|
||||||
max_sharpness = 1
|
|
||||||
text_margin_px = -1
|
|
||||||
page_angle = 0
|
|
||||||
else:
|
|
||||||
# Sharpness is determined by percentile of pixels that match some
|
|
||||||
# criteria, so it may vary significantly depending on which portion
|
|
||||||
# of the image is analyzed. In an effort to identify the sharpest
|
|
||||||
# edges, we split up the image into chunks and assume that the
|
|
||||||
# highest sharpness value obtained across all chunks is
|
|
||||||
# representative of the image as a whole.
|
|
||||||
max_sharpness = 0.0
|
|
||||||
if im_cropped.size[0] < im_cropped.size[1]:
|
|
||||||
# Page is in portrait orientation.
|
|
||||||
segments_x = 2
|
|
||||||
segments_y = 3
|
|
||||||
else:
|
|
||||||
# Page is in landscape orientation.
|
|
||||||
segments_x = 3
|
|
||||||
segments_y = 2
|
|
||||||
for i in range(segments_x):
|
|
||||||
for j in range(segments_y):
|
|
||||||
max_sharpness = max(
|
|
||||||
max_sharpness,
|
|
||||||
analyze_sharpness(
|
|
||||||
im_cropped.crop(
|
|
||||||
(
|
(
|
||||||
im_cropped.size[0] / segments_x * i,
|
im.size[0] * 0.1,
|
||||||
im_cropped.size[1] / segments_y * j,
|
im.size[1] * 0.1,
|
||||||
im_cropped.size[0] / segments_x * (i + 1),
|
im.size[0] * 0.9,
|
||||||
im_cropped.size[1] / segments_y * (j + 1),
|
im.size[1] * 0.9,
|
||||||
)
|
)
|
||||||
)
|
)
|
||||||
),
|
sharpness = analyze_sharpness(im_cropped)
|
||||||
)
|
|
||||||
|
|
||||||
# OCR is computationally expensive, so we try to take advantage of
|
# OCR is computationally expensive, so we try to take advantage of
|
||||||
# the Tesseract data already parsed by the Internet Archive and
|
# the Tesseract data already parsed by the Internet Archive and
|
||||||
|
|
@ -101,20 +66,14 @@ def analyze_doc(
|
||||||
)
|
)
|
||||||
>= OCR_RECOMPUTE_THRESHOLD_WORDS
|
>= OCR_RECOMPUTE_THRESHOLD_WORDS
|
||||||
):
|
):
|
||||||
if verbose:
|
|
||||||
print("Using PDF text.")
|
|
||||||
ocred_leaf = leaf
|
ocred_leaf = leaf
|
||||||
page_angle = 0
|
page_angle = 0
|
||||||
else:
|
else:
|
||||||
if verbose:
|
|
||||||
print("Using OCR.")
|
|
||||||
OCR_SCALE = 1
|
OCR_SCALE = 1
|
||||||
im_scaled = leaf.image.resize(
|
im_scaled = im.resize(np.int_(np.array(im.size) * OCR_SCALE))
|
||||||
np.int_(np.array(leaf.image.size) * OCR_SCALE)
|
|
||||||
)
|
|
||||||
ocr_result = ocr_engine.process(im_scaled)
|
ocr_result = ocr_engine.process(im_scaled)
|
||||||
ocred_leaf = ArchiveLeaf(
|
ocred_leaf = ArchiveLeaf(
|
||||||
image=leaf.image,
|
image=im,
|
||||||
page_number=leaf.page_number,
|
page_number=leaf.page_number,
|
||||||
text_blocks=[
|
text_blocks=[
|
||||||
TextBlock(
|
TextBlock(
|
||||||
|
|
@ -129,22 +88,24 @@ def analyze_doc(
|
||||||
)
|
)
|
||||||
page_angle = ocr_result.page_angle
|
page_angle = ocr_result.page_angle
|
||||||
|
|
||||||
word_margins_all_directions = np.sort(
|
word_margins_all_directions = (
|
||||||
np.int_(
|
np.sort(
|
||||||
np.concat(
|
np.concat(
|
||||||
[
|
[
|
||||||
np.array(
|
np.array(
|
||||||
[
|
[
|
||||||
block.x0,
|
block.x0,
|
||||||
block.y0,
|
block.y0,
|
||||||
leaf.image.size[0] - block.x1,
|
im.size[0] - block.x1,
|
||||||
leaf.image.size[1] - block.y1,
|
im.size[1] - block.y1,
|
||||||
]
|
]
|
||||||
)
|
)
|
||||||
for block in ocred_leaf.text_blocks
|
for block in ocred_leaf.text_blocks
|
||||||
]
|
]
|
||||||
|
).astype(np.int_)
|
||||||
)
|
)
|
||||||
)
|
if len(ocred_leaf.text_blocks) > 0
|
||||||
|
else np.array([])
|
||||||
)
|
)
|
||||||
# Skip the n closest words to the edge, to help ignore stray OCR artifacts.
|
# Skip the n closest words to the edge, to help ignore stray OCR artifacts.
|
||||||
SKIP_WORDS = 2
|
SKIP_WORDS = 2
|
||||||
|
|
@ -159,10 +120,10 @@ def analyze_doc(
|
||||||
|
|
||||||
analyzed_pages.append(
|
analyzed_pages.append(
|
||||||
{
|
{
|
||||||
"blank": is_blank,
|
"is_blank": is_blank,
|
||||||
"page_angle": page_angle,
|
"page_angle": page_angle,
|
||||||
"size_analyzed": leaf.image.size,
|
"size_analyzed": im.size,
|
||||||
"sharpness": max_sharpness,
|
"sharpness": sharpness,
|
||||||
"text_margin_px": text_margin_px,
|
"text_margin_px": text_margin_px,
|
||||||
}
|
}
|
||||||
)
|
)
|
||||||
|
|
@ -170,35 +131,58 @@ def analyze_doc(
|
||||||
return {"pages": analyzed_pages}
|
return {"pages": analyzed_pages}
|
||||||
|
|
||||||
|
|
||||||
|
def normalize_contrast_for_text(im: Image.Image) -> tuple[Image.Image, bool]:
|
||||||
|
"""
|
||||||
|
Most of the pages being analyzed, and virtually all of the pages we care
|
||||||
|
about for the purposes of QA, primarily contain text on a contrasting
|
||||||
|
background. We can therefore typically assume that it is reasonable to boost
|
||||||
|
contrast so that the lightest pixels are nearly white and the darkest pixels
|
||||||
|
are nearly black. This can help make analysis more consistent across leaves
|
||||||
|
with varying contrast ratios due to varied scanner settings, contrast ratios
|
||||||
|
of the original documnets, or weathering/fading of the physical fiche.
|
||||||
|
|
||||||
|
Processed leaves usually contain some amount of margin around the edges
|
||||||
|
where the backlight of the scanning rig is visible through the unexposed
|
||||||
|
region of the negative, so contrast detection is heavily center-weighted.
|
||||||
|
|
||||||
|
Params:
|
||||||
|
|
||||||
|
im Scan image as a 2-dimensional numpy array. (Use `np.asarray()` to
|
||||||
|
convert PIL `Image` objects to an array format.)
|
||||||
|
|
||||||
|
Returns:
|
||||||
|
|
||||||
|
(normalized_image, is_blank)
|
||||||
|
"""
|
||||||
|
pixel_values = np.asarray(
|
||||||
|
im.crop(
|
||||||
|
(
|
||||||
|
im.size[0] * 0.1,
|
||||||
|
im.size[1] * 0.1,
|
||||||
|
im.size[0] * 0.9,
|
||||||
|
im.size[1] * 0.9,
|
||||||
|
)
|
||||||
|
)
|
||||||
|
)
|
||||||
|
# To avoid extreme outliers, use quantiles instead of absolute extrema.
|
||||||
|
extrema = (np.quantile(pixel_values, 0.002), np.quantile(pixel_values, 0.998))
|
||||||
|
if extrema[1] - extrema[0] < 64:
|
||||||
|
# Assume there is essentially no content here and return the original.
|
||||||
|
return im, True
|
||||||
|
|
||||||
|
# Apply a rudimentary tone curve to the image, with the goal that the
|
||||||
|
# extrema we just calculated will evaluate to values "pretty close to" 0%
|
||||||
|
# and 100% of the available range.
|
||||||
|
return im.point(
|
||||||
|
lambda x: np.interp(x, (0, extrema[0], extrema[1], 255), (0, 8, 247, 255))
|
||||||
|
), False
|
||||||
|
|
||||||
|
|
||||||
def analyze_sharpness(im: Image.Image):
|
def analyze_sharpness(im: Image.Image):
|
||||||
"""
|
"""
|
||||||
Crudely quantifies the "sharpness" of edges in an image, on a scale of 0 to
|
Crudely quantifies the "sharpness" of edges in an image, on a scale of 0 to
|
||||||
1. The scale is not linear with respect to scan quality: anything above 0.1
|
1, by measuring peak intensity of a high-pass filter.
|
||||||
is usually fine.
|
|
||||||
"""
|
"""
|
||||||
arr = np.asarray(im)
|
blurred = im.filter(ImageFilter.GaussianBlur(8))
|
||||||
|
diff = ImageChops.difference(im, blurred)
|
||||||
# Normalize contrast based on brightest and darkest pixels. For example,
|
return np.quantile(diff, 0.999) / 255
|
||||||
# NORM_QUANTILE=0.1 will attempt to transform pixel values so that 80% fall
|
|
||||||
# between 10% brightness and 90% brightness. In practice, a value around
|
|
||||||
# 0.02 seems to work fairly well.
|
|
||||||
NORM_QUANTILE = 0.03
|
|
||||||
pixel_range = np.quantile(arr, 1.0 - NORM_QUANTILE) - np.quantile(
|
|
||||||
arr, NORM_QUANTILE
|
|
||||||
)
|
|
||||||
if pixel_range == 0:
|
|
||||||
arr_normalized = arr
|
|
||||||
else:
|
|
||||||
arr_normalized = arr * (1.0 - NORM_QUANTILE * 2) / pixel_range
|
|
||||||
arr_normalized = (
|
|
||||||
arr_normalized - np.quantile(arr_normalized, NORM_QUANTILE) + NORM_QUANTILE
|
|
||||||
)
|
|
||||||
arr_normalized = np.uint8(np.clip(arr_normalized, 0, 1) * 255)
|
|
||||||
|
|
||||||
# "Sharpness" is determined by measuring the median intensity of pixels
|
|
||||||
# near edges, after an edge detection filter has been applied to the image.
|
|
||||||
edges_arr = np.asarray(
|
|
||||||
Image.fromarray(arr_normalized).filter(ImageFilter.FIND_EDGES)
|
|
||||||
)
|
|
||||||
EDGE_THRESHOLD = 8
|
|
||||||
return np.median(edges_arr[edges_arr > EDGE_THRESHOLD]) / 255
|
|
||||||
|
|
|
||||||
|
|
@ -66,8 +66,8 @@ class ArchiveDoc:
|
||||||
identifier archive.org identifier string, for example
|
identifier archive.org identifier string, for example
|
||||||
`"micro_IA40386007_0012"`.
|
`"micro_IA40386007_0012"`.
|
||||||
|
|
||||||
name Document name, with the item identifier, leading whitespace,
|
name Document name, with the item identifier intact but file
|
||||||
and file extension stripped.
|
extension stripped.
|
||||||
|
|
||||||
title Optional `title` metadata field assigned to the `_jp2.zip`
|
title Optional `title` metadata field assigned to the `_jp2.zip`
|
||||||
file, usually indicating that this file represents a subset
|
file, usually indicating that this file represents a subset
|
||||||
|
|
|
||||||
|
|
@ -47,23 +47,6 @@ class TesseractOcrEngine(OcrEngine):
|
||||||
# TODO: Will this work for non-Latin scripts? Probably not all.
|
# TODO: Will this work for non-Latin scripts? Probably not all.
|
||||||
df = df[(df["width"] / df["height"]) > 0.8]
|
df = df[(df["width"] / df["height"]) > 0.8]
|
||||||
|
|
||||||
print(
|
|
||||||
[
|
|
||||||
TextBlock(
|
|
||||||
# Rotate X and Y coordinates back to match the original image.
|
|
||||||
*_box_after_rotation(
|
|
||||||
int(row["left"]),
|
|
||||||
int(row["top"]),
|
|
||||||
int(row["left"] + row["width"]),
|
|
||||||
int(row["top"] + row["height"]),
|
|
||||||
*rotated_image.size,
|
|
||||||
angle,
|
|
||||||
),
|
|
||||||
text=row["text"],
|
|
||||||
)
|
|
||||||
for _, row in df.iterrows()
|
|
||||||
]
|
|
||||||
)
|
|
||||||
if angle_best is None or df.shape[0] > len(blocks_best):
|
if angle_best is None or df.shape[0] > len(blocks_best):
|
||||||
angle_best = angle
|
angle_best = angle
|
||||||
blocks_best = [
|
blocks_best = [
|
||||||
|
|
|
||||||
|
|
@ -18,7 +18,5 @@ dependencies = [
|
||||||
|
|
||||||
[dependency-groups]
|
[dependency-groups]
|
||||||
dev = [
|
dev = [
|
||||||
"jedi>=0.19.2",
|
|
||||||
"python-lsp-server>=1.13.0",
|
|
||||||
"ruff>=0.12.8",
|
"ruff>=0.12.8",
|
||||||
]
|
]
|
||||||
|
|
|
||||||
174
uv.lock
generated
174
uv.lock
generated
|
|
@ -62,43 +62,6 @@ wheels = [
|
||||||
{ url = "https://files.pythonhosted.org/packages/eb/f3/b39e98f6a7eeb8d848cf1cc74766c4783f3d1d6afe50ff7726a2df51f681/bce_python_sdk-0.9.56-py3-none-any.whl", hash = "sha256:432cf3ea4cd4b959dd0185f36ed5c49304a6272a08a17e5f443730b1f437135b", size = 393233, upload-time = "2025-12-16T11:25:22.957Z" },
|
{ url = "https://files.pythonhosted.org/packages/eb/f3/b39e98f6a7eeb8d848cf1cc74766c4783f3d1d6afe50ff7726a2df51f681/bce_python_sdk-0.9.56-py3-none-any.whl", hash = "sha256:432cf3ea4cd4b959dd0185f36ed5c49304a6272a08a17e5f443730b1f437135b", size = 393233, upload-time = "2025-12-16T11:25:22.957Z" },
|
||||||
]
|
]
|
||||||
|
|
||||||
[[package]]
|
|
||||||
name = "black"
|
|
||||||
version = "25.12.0"
|
|
||||||
source = { registry = "https://pypi.org/simple" }
|
|
||||||
dependencies = [
|
|
||||||
{ name = "click" },
|
|
||||||
{ name = "mypy-extensions" },
|
|
||||||
{ name = "packaging" },
|
|
||||||
{ name = "pathspec" },
|
|
||||||
{ name = "platformdirs" },
|
|
||||||
{ name = "pytokens" },
|
|
||||||
]
|
|
||||||
sdist = { url = "https://files.pythonhosted.org/packages/c4/d9/07b458a3f1c525ac392b5edc6b191ff140b596f9d77092429417a54e249d/black-25.12.0.tar.gz", hash = "sha256:8d3dd9cea14bff7ddc0eb243c811cdb1a011ebb4800a5f0335a01a68654796a7", size = 659264, upload-time = "2025-12-08T01:40:52.501Z" }
|
|
||||||
wheels = [
|
|
||||||
{ url = "https://files.pythonhosted.org/packages/60/ad/7ac0d0e1e0612788dbc48e62aef8a8e8feffac7eb3d787db4e43b8462fa8/black-25.12.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:d0cfa263e85caea2cff57d8f917f9f51adae8e20b610e2b23de35b5b11ce691a", size = 1877003, upload-time = "2025-12-08T01:43:29.967Z" },
|
|
||||||
{ url = "https://files.pythonhosted.org/packages/e8/dd/a237e9f565f3617a88b49284b59cbca2a4f56ebe68676c1aad0ce36a54a7/black-25.12.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:1a2f578ae20c19c50a382286ba78bfbeafdf788579b053d8e4980afb079ab9be", size = 1712639, upload-time = "2025-12-08T01:52:46.756Z" },
|
|
||||||
{ url = "https://files.pythonhosted.org/packages/12/80/e187079df1ea4c12a0c63282ddd8b81d5107db6d642f7d7b75a6bcd6fc21/black-25.12.0-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:d3e1b65634b0e471d07ff86ec338819e2ef860689859ef4501ab7ac290431f9b", size = 1758143, upload-time = "2025-12-08T01:45:29.137Z" },
|
|
||||||
{ url = "https://files.pythonhosted.org/packages/93/b5/3096ccee4f29dc2c3aac57274326c4d2d929a77e629f695f544e159bfae4/black-25.12.0-cp311-cp311-win_amd64.whl", hash = "sha256:a3fa71e3b8dd9f7c6ac4d818345237dfb4175ed3bf37cd5a581dbc4c034f1ec5", size = 1420698, upload-time = "2025-12-08T01:45:53.379Z" },
|
|
||||||
{ url = "https://files.pythonhosted.org/packages/7e/39/f81c0ffbc25ffbe61c7d0385bf277e62ffc3e52f5ee668d7369d9854fadf/black-25.12.0-cp311-cp311-win_arm64.whl", hash = "sha256:51e267458f7e650afed8445dc7edb3187143003d52a1b710c7321aef22aa9655", size = 1229317, upload-time = "2025-12-08T01:46:35.606Z" },
|
|
||||||
{ url = "https://files.pythonhosted.org/packages/d1/bd/26083f805115db17fda9877b3c7321d08c647df39d0df4c4ca8f8450593e/black-25.12.0-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:31f96b7c98c1ddaeb07dc0f56c652e25bdedaac76d5b68a059d998b57c55594a", size = 1924178, upload-time = "2025-12-08T01:49:51.048Z" },
|
|
||||||
{ url = "https://files.pythonhosted.org/packages/89/6b/ea00d6651561e2bdd9231c4177f4f2ae19cc13a0b0574f47602a7519b6ca/black-25.12.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:05dd459a19e218078a1f98178c13f861fe6a9a5f88fc969ca4d9b49eb1809783", size = 1742643, upload-time = "2025-12-08T01:49:59.09Z" },
|
|
||||||
{ url = "https://files.pythonhosted.org/packages/6d/f3/360fa4182e36e9875fabcf3a9717db9d27a8d11870f21cff97725c54f35b/black-25.12.0-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:c1f68c5eff61f226934be6b5b80296cf6939e5d2f0c2f7d543ea08b204bfaf59", size = 1800158, upload-time = "2025-12-08T01:44:27.301Z" },
|
|
||||||
{ url = "https://files.pythonhosted.org/packages/f8/08/2c64830cb6616278067e040acca21d4f79727b23077633953081c9445d61/black-25.12.0-cp312-cp312-win_amd64.whl", hash = "sha256:274f940c147ddab4442d316b27f9e332ca586d39c85ecf59ebdea82cc9ee8892", size = 1426197, upload-time = "2025-12-08T01:45:51.198Z" },
|
|
||||||
{ url = "https://files.pythonhosted.org/packages/d4/60/a93f55fd9b9816b7432cf6842f0e3000fdd5b7869492a04b9011a133ee37/black-25.12.0-cp312-cp312-win_arm64.whl", hash = "sha256:169506ba91ef21e2e0591563deda7f00030cb466e747c4b09cb0a9dae5db2f43", size = 1237266, upload-time = "2025-12-08T01:45:10.556Z" },
|
|
||||||
{ url = "https://files.pythonhosted.org/packages/c8/52/c551e36bc95495d2aa1a37d50566267aa47608c81a53f91daa809e03293f/black-25.12.0-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:a05ddeb656534c3e27a05a29196c962877c83fa5503db89e68857d1161ad08a5", size = 1923809, upload-time = "2025-12-08T01:46:55.126Z" },
|
|
||||||
{ url = "https://files.pythonhosted.org/packages/a0/f7/aac9b014140ee56d247e707af8db0aae2e9efc28d4a8aba92d0abd7ae9d1/black-25.12.0-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:9ec77439ef3e34896995503865a85732c94396edcc739f302c5673a2315e1e7f", size = 1742384, upload-time = "2025-12-08T01:49:37.022Z" },
|
|
||||||
{ url = "https://files.pythonhosted.org/packages/74/98/38aaa018b2ab06a863974c12b14a6266badc192b20603a81b738c47e902e/black-25.12.0-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:0e509c858adf63aa61d908061b52e580c40eae0dfa72415fa47ac01b12e29baf", size = 1798761, upload-time = "2025-12-08T01:46:05.386Z" },
|
|
||||||
{ url = "https://files.pythonhosted.org/packages/16/3a/a8ac542125f61574a3f015b521ca83b47321ed19bb63fe6d7560f348bfe1/black-25.12.0-cp313-cp313-win_amd64.whl", hash = "sha256:252678f07f5bac4ff0d0e9b261fbb029fa530cfa206d0a636a34ab445ef8ca9d", size = 1429180, upload-time = "2025-12-08T01:45:34.903Z" },
|
|
||||||
{ url = "https://files.pythonhosted.org/packages/e6/2d/bdc466a3db9145e946762d52cd55b1385509d9f9004fec1c97bdc8debbfb/black-25.12.0-cp313-cp313-win_arm64.whl", hash = "sha256:bc5b1c09fe3c931ddd20ee548511c64ebf964ada7e6f0763d443947fd1c603ce", size = 1239350, upload-time = "2025-12-08T01:46:09.458Z" },
|
|
||||||
{ url = "https://files.pythonhosted.org/packages/35/46/1d8f2542210c502e2ae1060b2e09e47af6a5e5963cb78e22ec1a11170b28/black-25.12.0-cp314-cp314-macosx_10_15_x86_64.whl", hash = "sha256:0a0953b134f9335c2434864a643c842c44fba562155c738a2a37a4d61f00cad5", size = 1917015, upload-time = "2025-12-08T01:53:27.987Z" },
|
|
||||||
{ url = "https://files.pythonhosted.org/packages/41/37/68accadf977672beb8e2c64e080f568c74159c1aaa6414b4cd2aef2d7906/black-25.12.0-cp314-cp314-macosx_11_0_arm64.whl", hash = "sha256:2355bbb6c3b76062870942d8cc450d4f8ac71f9c93c40122762c8784df49543f", size = 1741830, upload-time = "2025-12-08T01:54:36.861Z" },
|
|
||||||
{ url = "https://files.pythonhosted.org/packages/ac/76/03608a9d8f0faad47a3af3a3c8c53af3367f6c0dd2d23a84710456c7ac56/black-25.12.0-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:9678bd991cc793e81d19aeeae57966ee02909877cb65838ccffef24c3ebac08f", size = 1791450, upload-time = "2025-12-08T01:44:52.581Z" },
|
|
||||||
{ url = "https://files.pythonhosted.org/packages/06/99/b2a4bd7dfaea7964974f947e1c76d6886d65fe5d24f687df2d85406b2609/black-25.12.0-cp314-cp314-win_amd64.whl", hash = "sha256:97596189949a8aad13ad12fcbb4ae89330039b96ad6742e6f6b45e75ad5cfd83", size = 1452042, upload-time = "2025-12-08T01:46:13.188Z" },
|
|
||||||
{ url = "https://files.pythonhosted.org/packages/b2/7c/d9825de75ae5dd7795d007681b752275ea85a1c5d83269b4b9c754c2aaab/black-25.12.0-cp314-cp314-win_arm64.whl", hash = "sha256:778285d9ea197f34704e3791ea9404cd6d07595745907dd2ce3da7a13627b29b", size = 1267446, upload-time = "2025-12-08T01:46:14.497Z" },
|
|
||||||
{ url = "https://files.pythonhosted.org/packages/68/11/21331aed19145a952ad28fca2756a1433ee9308079bd03bd898e903a2e53/black-25.12.0-py3-none-any.whl", hash = "sha256:48ceb36c16dbc84062740049eef990bb2ce07598272e673c17d1a7720c71c828", size = 206191, upload-time = "2025-12-08T01:40:50.963Z" },
|
|
||||||
]
|
|
||||||
|
|
||||||
[[package]]
|
[[package]]
|
||||||
name = "certifi"
|
name = "certifi"
|
||||||
version = "2025.11.12"
|
version = "2025.11.12"
|
||||||
|
|
@ -223,19 +186,6 @@ wheels = [
|
||||||
{ url = "https://files.pythonhosted.org/packages/6d/c1/e419ef3723a074172b68aaa89c9f3de486ed4c2399e2dbd8113a4fdcaf9e/colorlog-6.10.1-py3-none-any.whl", hash = "sha256:2d7e8348291948af66122cff006c9f8da6255d224e7cf8e37d8de2df3bad8c9c", size = 11743, upload-time = "2025-10-16T16:14:10.512Z" },
|
{ url = "https://files.pythonhosted.org/packages/6d/c1/e419ef3723a074172b68aaa89c9f3de486ed4c2399e2dbd8113a4fdcaf9e/colorlog-6.10.1-py3-none-any.whl", hash = "sha256:2d7e8348291948af66122cff006c9f8da6255d224e7cf8e37d8de2df3bad8c9c", size = 11743, upload-time = "2025-10-16T16:14:10.512Z" },
|
||||||
]
|
]
|
||||||
|
|
||||||
[[package]]
|
|
||||||
name = "docstring-to-markdown"
|
|
||||||
version = "0.17"
|
|
||||||
source = { registry = "https://pypi.org/simple" }
|
|
||||||
dependencies = [
|
|
||||||
{ name = "importlib-metadata" },
|
|
||||||
{ name = "typing-extensions" },
|
|
||||||
]
|
|
||||||
sdist = { url = "https://files.pythonhosted.org/packages/52/d8/8abe80d62c5dce1075578031bcfde07e735bcf0afe2886dd48b470162ab4/docstring_to_markdown-0.17.tar.gz", hash = "sha256:df72a112294c7492487c9da2451cae0faeee06e86008245c188c5761c9590ca3", size = 32260, upload-time = "2025-05-02T15:09:07.932Z" }
|
|
||||||
wheels = [
|
|
||||||
{ url = "https://files.pythonhosted.org/packages/56/7b/af3d0da15bed3a8665419bb3a630585756920f4ad67abfdfef26240ebcc0/docstring_to_markdown-0.17-py3-none-any.whl", hash = "sha256:fd7d5094aa83943bf5f9e1a13701866b7c452eac19765380dead666e36d3711c", size = 23479, upload-time = "2025-05-02T15:09:06.676Z" },
|
|
||||||
]
|
|
||||||
|
|
||||||
[[package]]
|
[[package]]
|
||||||
name = "filelock"
|
name = "filelock"
|
||||||
version = "3.20.1"
|
version = "3.20.1"
|
||||||
|
|
@ -368,30 +318,6 @@ wheels = [
|
||||||
{ url = "https://files.pythonhosted.org/packages/ff/62/85c4c919272577931d407be5ba5d71c20f0b616d31a0befe0ae45bb79abd/imagesize-1.4.1-py2.py3-none-any.whl", hash = "sha256:0d8d18d08f840c19d0ee7ca1fd82490fdc3729b7ac93f49870406ddde8ef8d8b", size = 8769, upload-time = "2022-07-01T12:21:02.467Z" },
|
{ url = "https://files.pythonhosted.org/packages/ff/62/85c4c919272577931d407be5ba5d71c20f0b616d31a0befe0ae45bb79abd/imagesize-1.4.1-py2.py3-none-any.whl", hash = "sha256:0d8d18d08f840c19d0ee7ca1fd82490fdc3729b7ac93f49870406ddde8ef8d8b", size = 8769, upload-time = "2022-07-01T12:21:02.467Z" },
|
||||||
]
|
]
|
||||||
|
|
||||||
[[package]]
|
|
||||||
name = "importlib-metadata"
|
|
||||||
version = "8.7.0"
|
|
||||||
source = { registry = "https://pypi.org/simple" }
|
|
||||||
dependencies = [
|
|
||||||
{ name = "zipp" },
|
|
||||||
]
|
|
||||||
sdist = { url = "https://files.pythonhosted.org/packages/76/66/650a33bd90f786193e4de4b3ad86ea60b53c89b669a5c7be931fac31cdb0/importlib_metadata-8.7.0.tar.gz", hash = "sha256:d13b81ad223b890aa16c5471f2ac3056cf76c5f10f82d6f9292f0b415f389000", size = 56641, upload-time = "2025-04-27T15:29:01.736Z" }
|
|
||||||
wheels = [
|
|
||||||
{ url = "https://files.pythonhosted.org/packages/20/b0/36bd937216ec521246249be3bf9855081de4c5e06a0c9b4219dbeda50373/importlib_metadata-8.7.0-py3-none-any.whl", hash = "sha256:e5dd1551894c77868a30651cef00984d50e1002d06942a7101d34870c5f02afd", size = 27656, upload-time = "2025-04-27T15:29:00.214Z" },
|
|
||||||
]
|
|
||||||
|
|
||||||
[[package]]
|
|
||||||
name = "jedi"
|
|
||||||
version = "0.19.2"
|
|
||||||
source = { registry = "https://pypi.org/simple" }
|
|
||||||
dependencies = [
|
|
||||||
{ name = "parso" },
|
|
||||||
]
|
|
||||||
sdist = { url = "https://files.pythonhosted.org/packages/72/3a/79a912fbd4d8dd6fbb02bf69afd3bb72cf0c729bb3063c6f4498603db17a/jedi-0.19.2.tar.gz", hash = "sha256:4770dc3de41bde3966b02eb84fbcf557fb33cce26ad23da12c742fb50ecb11f0", size = 1231287, upload-time = "2024-11-11T01:41:42.873Z" }
|
|
||||||
wheels = [
|
|
||||||
{ url = "https://files.pythonhosted.org/packages/c0/5a/9cac0c82afec3d09ccd97c8b6502d48f165f9124db81b4bcb90b4af974ee/jedi-0.19.2-py2.py3-none-any.whl", hash = "sha256:a8ef22bde8490f57fe5c7681a3c83cb58874daf72b4784de3cce5b6ef6edb5b9", size = 1572278, upload-time = "2024-11-11T01:41:40.175Z" },
|
|
||||||
]
|
|
||||||
|
|
||||||
[[package]]
|
[[package]]
|
||||||
name = "microqa"
|
name = "microqa"
|
||||||
version = "0.1.0"
|
version = "0.1.0"
|
||||||
|
|
@ -410,8 +336,6 @@ dependencies = [
|
||||||
|
|
||||||
[package.dev-dependencies]
|
[package.dev-dependencies]
|
||||||
dev = [
|
dev = [
|
||||||
{ name = "jedi" },
|
|
||||||
{ name = "python-lsp-server" },
|
|
||||||
{ name = "ruff" },
|
{ name = "ruff" },
|
||||||
]
|
]
|
||||||
|
|
||||||
|
|
@ -429,11 +353,7 @@ requires-dist = [
|
||||||
]
|
]
|
||||||
|
|
||||||
[package.metadata.requires-dev]
|
[package.metadata.requires-dev]
|
||||||
dev = [
|
dev = [{ name = "ruff", specifier = ">=0.12.8" }]
|
||||||
{ name = "jedi", specifier = ">=0.19.2" },
|
|
||||||
{ name = "python-lsp-server", specifier = ">=1.13.0" },
|
|
||||||
{ name = "ruff", specifier = ">=0.12.8" },
|
|
||||||
]
|
|
||||||
|
|
||||||
[[package]]
|
[[package]]
|
||||||
name = "modelscope"
|
name = "modelscope"
|
||||||
|
|
@ -451,15 +371,6 @@ wheels = [
|
||||||
{ url = "https://files.pythonhosted.org/packages/86/05/63f01821681b2be5d1739b4aad7b186c28d4ead2c5c99a9fc4aa53c13c19/modelscope-1.33.0-py3-none-any.whl", hash = "sha256:d9bdd566303f813d762e133410007eaf1b78f065c871228ab38640919b707489", size = 6050040, upload-time = "2025-12-10T03:49:58.428Z" },
|
{ url = "https://files.pythonhosted.org/packages/86/05/63f01821681b2be5d1739b4aad7b186c28d4ead2c5c99a9fc4aa53c13c19/modelscope-1.33.0-py3-none-any.whl", hash = "sha256:d9bdd566303f813d762e133410007eaf1b78f065c871228ab38640919b707489", size = 6050040, upload-time = "2025-12-10T03:49:58.428Z" },
|
||||||
]
|
]
|
||||||
|
|
||||||
[[package]]
|
|
||||||
name = "mypy-extensions"
|
|
||||||
version = "1.1.0"
|
|
||||||
source = { registry = "https://pypi.org/simple" }
|
|
||||||
sdist = { url = "https://files.pythonhosted.org/packages/a2/6e/371856a3fb9d31ca8dac321cda606860fa4548858c0cc45d9d1d4ca2628b/mypy_extensions-1.1.0.tar.gz", hash = "sha256:52e68efc3284861e772bbcd66823fde5ae21fd2fdb51c62a211403730b916558", size = 6343, upload-time = "2025-04-22T14:54:24.164Z" }
|
|
||||||
wheels = [
|
|
||||||
{ url = "https://files.pythonhosted.org/packages/79/7b/2c79738432f5c924bef5071f933bcc9efd0473bac3b4aa584a6f7c1c8df8/mypy_extensions-1.1.0-py3-none-any.whl", hash = "sha256:1be4cccdb0f2482337c4743e60421de3a356cd97508abadd57d47403e94f5505", size = 4963, upload-time = "2025-04-22T14:54:22.983Z" },
|
|
||||||
]
|
|
||||||
|
|
||||||
[[package]]
|
[[package]]
|
||||||
name = "networkx"
|
name = "networkx"
|
||||||
version = "3.6.1"
|
version = "3.6.1"
|
||||||
|
|
@ -725,24 +636,6 @@ wheels = [
|
||||||
{ url = "https://files.pythonhosted.org/packages/70/44/5191d2e4026f86a2a109053e194d3ba7a31a2d10a9c2348368c63ed4e85a/pandas-2.3.3-cp314-cp314t-musllinux_1_2_x86_64.whl", hash = "sha256:3869faf4bd07b3b66a9f462417d0ca3a9df29a9f6abd5d0d0dbab15dac7abe87", size = 13202175, upload-time = "2025-09-29T23:31:59.173Z" },
|
{ url = "https://files.pythonhosted.org/packages/70/44/5191d2e4026f86a2a109053e194d3ba7a31a2d10a9c2348368c63ed4e85a/pandas-2.3.3-cp314-cp314t-musllinux_1_2_x86_64.whl", hash = "sha256:3869faf4bd07b3b66a9f462417d0ca3a9df29a9f6abd5d0d0dbab15dac7abe87", size = 13202175, upload-time = "2025-09-29T23:31:59.173Z" },
|
||||||
]
|
]
|
||||||
|
|
||||||
[[package]]
|
|
||||||
name = "parso"
|
|
||||||
version = "0.8.5"
|
|
||||||
source = { registry = "https://pypi.org/simple" }
|
|
||||||
sdist = { url = "https://files.pythonhosted.org/packages/d4/de/53e0bcf53d13e005bd8c92e7855142494f41171b34c2536b86187474184d/parso-0.8.5.tar.gz", hash = "sha256:034d7354a9a018bdce352f48b2a8a450f05e9d6ee85db84764e9b6bd96dafe5a", size = 401205, upload-time = "2025-08-23T15:15:28.028Z" }
|
|
||||||
wheels = [
|
|
||||||
{ url = "https://files.pythonhosted.org/packages/16/32/f8e3c85d1d5250232a5d3477a2a28cc291968ff175caeadaf3cc19ce0e4a/parso-0.8.5-py2.py3-none-any.whl", hash = "sha256:646204b5ee239c396d040b90f9e272e9a8017c630092bf59980beb62fd033887", size = 106668, upload-time = "2025-08-23T15:15:25.663Z" },
|
|
||||||
]
|
|
||||||
|
|
||||||
[[package]]
|
|
||||||
name = "pathspec"
|
|
||||||
version = "0.12.1"
|
|
||||||
source = { registry = "https://pypi.org/simple" }
|
|
||||||
sdist = { url = "https://files.pythonhosted.org/packages/ca/bc/f35b8446f4531a7cb215605d100cd88b7ac6f44ab3fc94870c120ab3adbf/pathspec-0.12.1.tar.gz", hash = "sha256:a482d51503a1ab33b1c67a6c3813a26953dbdc71c31dacaef9a838c4e29f5712", size = 51043, upload-time = "2023-12-10T22:30:45Z" }
|
|
||||||
wheels = [
|
|
||||||
{ url = "https://files.pythonhosted.org/packages/cc/20/ff623b09d963f88bfde16306a54e12ee5ea43e9b597108672ff3a408aad6/pathspec-0.12.1-py3-none-any.whl", hash = "sha256:a0d503e138a4c123b27490a4f7beda6a01c6f288df0e4a8b79c7eb0dc7b4cc08", size = 31191, upload-time = "2023-12-10T22:30:43.14Z" },
|
|
||||||
]
|
|
||||||
|
|
||||||
[[package]]
|
[[package]]
|
||||||
name = "pillow"
|
name = "pillow"
|
||||||
version = "12.0.0"
|
version = "12.0.0"
|
||||||
|
|
@ -830,24 +723,6 @@ wheels = [
|
||||||
{ url = "https://files.pythonhosted.org/packages/95/7e/f896623c3c635a90537ac093c6a618ebe1a90d87206e42309cb5d98a1b9e/pillow-12.0.0-pp311-pypy311_pp73-win_amd64.whl", hash = "sha256:b290fd8aa38422444d4b50d579de197557f182ef1068b75f5aa8558638b8d0a5", size = 6997850, upload-time = "2025-10-15T18:24:11.495Z" },
|
{ url = "https://files.pythonhosted.org/packages/95/7e/f896623c3c635a90537ac093c6a618ebe1a90d87206e42309cb5d98a1b9e/pillow-12.0.0-pp311-pypy311_pp73-win_amd64.whl", hash = "sha256:b290fd8aa38422444d4b50d579de197557f182ef1068b75f5aa8558638b8d0a5", size = 6997850, upload-time = "2025-10-15T18:24:11.495Z" },
|
||||||
]
|
]
|
||||||
|
|
||||||
[[package]]
|
|
||||||
name = "platformdirs"
|
|
||||||
version = "4.5.1"
|
|
||||||
source = { registry = "https://pypi.org/simple" }
|
|
||||||
sdist = { url = "https://files.pythonhosted.org/packages/cf/86/0248f086a84f01b37aaec0fa567b397df1a119f73c16f6c7a9aac73ea309/platformdirs-4.5.1.tar.gz", hash = "sha256:61d5cdcc6065745cdd94f0f878977f8de9437be93de97c1c12f853c9c0cdcbda", size = 21715, upload-time = "2025-12-05T13:52:58.638Z" }
|
|
||||||
wheels = [
|
|
||||||
{ url = "https://files.pythonhosted.org/packages/cb/28/3bfe2fa5a7b9c46fe7e13c97bda14c895fb10fa2ebf1d0abb90e0cea7ee1/platformdirs-4.5.1-py3-none-any.whl", hash = "sha256:d03afa3963c806a9bed9d5125c8f4cb2fdaf74a55ab60e5d59b3fde758104d31", size = 18731, upload-time = "2025-12-05T13:52:56.823Z" },
|
|
||||||
]
|
|
||||||
|
|
||||||
[[package]]
|
|
||||||
name = "pluggy"
|
|
||||||
version = "1.6.0"
|
|
||||||
source = { registry = "https://pypi.org/simple" }
|
|
||||||
sdist = { url = "https://files.pythonhosted.org/packages/f9/e2/3e91f31a7d2b083fe6ef3fa267035b518369d9511ffab804f839851d2779/pluggy-1.6.0.tar.gz", hash = "sha256:7dcc130b76258d33b90f61b658791dede3486c3e6bfb003ee5c9bfb396dd22f3", size = 69412, upload-time = "2025-05-15T12:30:07.975Z" }
|
|
||||||
wheels = [
|
|
||||||
{ url = "https://files.pythonhosted.org/packages/54/20/4d324d65cc6d9205fabedc306948156824eb9f0ee1633355a8f7ec5c66bf/pluggy-1.6.0-py3-none-any.whl", hash = "sha256:e920276dd6813095e9377c0bc5566d94c932c33b27a3e3945d8389c374dd4746", size = 20538, upload-time = "2025-05-15T12:30:06.134Z" },
|
|
||||||
]
|
|
||||||
|
|
||||||
[[package]]
|
[[package]]
|
||||||
name = "prettytable"
|
name = "prettytable"
|
||||||
version = "3.17.0"
|
version = "3.17.0"
|
||||||
|
|
@ -1297,44 +1172,6 @@ wheels = [
|
||||||
{ url = "https://files.pythonhosted.org/packages/ec/57/56b9bcc3c9c6a792fcbaf139543cee77261f3651ca9da0c93f5c1221264b/python_dateutil-2.9.0.post0-py2.py3-none-any.whl", hash = "sha256:a8b2bc7bffae282281c8140a97d3aa9c14da0b136dfe83f850eea9a5f7470427", size = 229892, upload-time = "2024-03-01T18:36:18.57Z" },
|
{ url = "https://files.pythonhosted.org/packages/ec/57/56b9bcc3c9c6a792fcbaf139543cee77261f3651ca9da0c93f5c1221264b/python_dateutil-2.9.0.post0-py2.py3-none-any.whl", hash = "sha256:a8b2bc7bffae282281c8140a97d3aa9c14da0b136dfe83f850eea9a5f7470427", size = 229892, upload-time = "2024-03-01T18:36:18.57Z" },
|
||||||
]
|
]
|
||||||
|
|
||||||
[[package]]
|
|
||||||
name = "python-lsp-jsonrpc"
|
|
||||||
version = "1.1.2"
|
|
||||||
source = { registry = "https://pypi.org/simple" }
|
|
||||||
dependencies = [
|
|
||||||
{ name = "ujson" },
|
|
||||||
]
|
|
||||||
sdist = { url = "https://files.pythonhosted.org/packages/48/b6/fd92e2ea4635d88966bb42c20198df1a981340f07843b5e3c6694ba3557b/python-lsp-jsonrpc-1.1.2.tar.gz", hash = "sha256:4688e453eef55cd952bff762c705cedefa12055c0aec17a06f595bcc002cc912", size = 15298, upload-time = "2023-09-23T17:48:30.451Z" }
|
|
||||||
wheels = [
|
|
||||||
{ url = "https://files.pythonhosted.org/packages/cb/d9/656659d5b5d5f402b2b174cd0ba9bc827e07ce3c0bf88da65424baf64af8/python_lsp_jsonrpc-1.1.2-py3-none-any.whl", hash = "sha256:7339c2e9630ae98903fdaea1ace8c47fba0484983794d6aafd0bd8989be2b03c", size = 8805, upload-time = "2023-09-23T17:48:28.804Z" },
|
|
||||||
]
|
|
||||||
|
|
||||||
[[package]]
|
|
||||||
name = "python-lsp-server"
|
|
||||||
version = "1.14.0"
|
|
||||||
source = { registry = "https://pypi.org/simple" }
|
|
||||||
dependencies = [
|
|
||||||
{ name = "black" },
|
|
||||||
{ name = "docstring-to-markdown" },
|
|
||||||
{ name = "jedi" },
|
|
||||||
{ name = "pluggy" },
|
|
||||||
{ name = "python-lsp-jsonrpc" },
|
|
||||||
{ name = "ujson" },
|
|
||||||
]
|
|
||||||
sdist = { url = "https://files.pythonhosted.org/packages/b4/b5/b989d41c63390dfc2bf63275ab543b82fed076723d912055e77ccbae1422/python_lsp_server-1.14.0.tar.gz", hash = "sha256:509c445fc667f41ffd3191cb7512a497bf7dd76c14ceb1ee2f6c13ebe71f9a6b", size = 121536, upload-time = "2025-12-06T16:12:20.86Z" }
|
|
||||||
wheels = [
|
|
||||||
{ url = "https://files.pythonhosted.org/packages/08/cf/587f913335e3855e0ddca2aee7c3f9d5de2d75a1e23434891e9f74783bcd/python_lsp_server-1.14.0-py3-none-any.whl", hash = "sha256:a71a917464effc48f4c70363f90b8520e5e3ba8201428da80b97a7ceb259e32a", size = 77060, upload-time = "2025-12-06T16:12:19.46Z" },
|
|
||||||
]
|
|
||||||
|
|
||||||
[[package]]
|
|
||||||
name = "pytokens"
|
|
||||||
version = "0.3.0"
|
|
||||||
source = { registry = "https://pypi.org/simple" }
|
|
||||||
sdist = { url = "https://files.pythonhosted.org/packages/4e/8d/a762be14dae1c3bf280202ba3172020b2b0b4c537f94427435f19c413b72/pytokens-0.3.0.tar.gz", hash = "sha256:2f932b14ed08de5fcf0b391ace2642f858f1394c0857202959000b68ed7a458a", size = 17644, upload-time = "2025-11-05T13:36:35.34Z" }
|
|
||||||
wheels = [
|
|
||||||
{ url = "https://files.pythonhosted.org/packages/84/25/d9db8be44e205a124f6c98bc0324b2bb149b7431c53877fc6d1038dddaf5/pytokens-0.3.0-py3-none-any.whl", hash = "sha256:95b2b5eaf832e469d141a378872480ede3f251a5a5041b8ec6e581d3ac71bbf3", size = 12195, upload-time = "2025-11-05T13:36:33.183Z" },
|
|
||||||
]
|
|
||||||
|
|
||||||
[[package]]
|
[[package]]
|
||||||
name = "pytz"
|
name = "pytz"
|
||||||
version = "2025.2"
|
version = "2025.2"
|
||||||
|
|
@ -1729,12 +1566,3 @@ sdist = { url = "https://files.pythonhosted.org/packages/24/30/6b0809f4510673dc7
|
||||||
wheels = [
|
wheels = [
|
||||||
{ url = "https://files.pythonhosted.org/packages/af/b5/123f13c975e9f27ab9c0770f514345bd406d0e8d3b7a0723af9d43f710af/wcwidth-0.2.14-py2.py3-none-any.whl", hash = "sha256:a7bb560c8aee30f9957e5f9895805edd20602f2d7f720186dfd906e82b4982e1", size = 37286, upload-time = "2025-09-22T16:29:51.641Z" },
|
{ url = "https://files.pythonhosted.org/packages/af/b5/123f13c975e9f27ab9c0770f514345bd406d0e8d3b7a0723af9d43f710af/wcwidth-0.2.14-py2.py3-none-any.whl", hash = "sha256:a7bb560c8aee30f9957e5f9895805edd20602f2d7f720186dfd906e82b4982e1", size = 37286, upload-time = "2025-09-22T16:29:51.641Z" },
|
||||||
]
|
]
|
||||||
|
|
||||||
[[package]]
|
|
||||||
name = "zipp"
|
|
||||||
version = "3.23.0"
|
|
||||||
source = { registry = "https://pypi.org/simple" }
|
|
||||||
sdist = { url = "https://files.pythonhosted.org/packages/e3/02/0f2892c661036d50ede074e376733dca2ae7c6eb617489437771209d4180/zipp-3.23.0.tar.gz", hash = "sha256:a07157588a12518c9d4034df3fbbee09c814741a33ff63c05fa29d26a2404166", size = 25547, upload-time = "2025-06-08T17:06:39.4Z" }
|
|
||||||
wheels = [
|
|
||||||
{ url = "https://files.pythonhosted.org/packages/2e/54/647ade08bf0db230bfea292f893923872fd20be6ac6f53b2b936ba839d75/zipp-3.23.0-py3-none-any.whl", hash = "sha256:071652d6115ed432f5ce1d34c336c0adfd6a884660d1e9712a256d3d3bd4b14e", size = 10276, upload-time = "2025-06-08T17:06:38.034Z" },
|
|
||||||
]
|
|
||||||
|
|
|
||||||
Loading…
Add table
Reference in a new issue