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#!/usr/bin/env -S uv run --script | |
# /// script | |
# requires-python = ">=3.11" | |
# dependencies = [ | |
# "fire", | |
# "altair", | |
# "polars", | |
# "pycrux", | |
# "ipython", | |
# "rich" |
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#!/usr/bin/env -S uv run --script | |
# /// script | |
# requires-python = ">=3.11" | |
# dependencies = [ | |
# "fire", | |
# "altair", | |
# "polars", | |
# "pycrux", | |
# "ipython" | |
# ] |
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#!/usr/bin/env -S uv run --script | |
# /// script | |
# requires-python = ">=3.13" | |
# dependencies = [ | |
# "fire", | |
# ] | |
# /// | |
# pyright: reportMissingModuleSource=false | |
# pyright: reportMissingImports=false |
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#!/usr/bin/env -S uv run --script | |
# /// script | |
# requires-python = ">=3.13" | |
# dependencies = [ | |
# "beautifulsoup4", | |
# "requests", | |
# "icalendar" | |
# ] | |
# /// | |
# pyright: reportMissingModuleSource=false |
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# /// script | |
# dependencies = [ | |
# "fire", | |
# "polars", | |
# "garmin-fit-sdk", | |
# ] | |
# /// | |
from __future__ import annotations | |
import logging |
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# /// script | |
# dependencies = [ | |
# "fire", | |
# "polars", | |
# "rich", | |
# "redshift_connector", | |
# ] | |
# /// | |
import json |
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{ | |
"config": { | |
"text": { | |
"color": "gray", | |
"fontSize": 14 | |
}, | |
"title": { | |
"anchor": "middle", | |
"fontWeight": "normal", | |
"titleFontWeight": "normal", |
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``` | |
{ | |
"$schema": "https://vega.github.io/schema/vega/v5.json", | |
"background": "white", | |
"padding": 5, | |
"width": 480, | |
"data": [ | |
{ | |
"name": "brush_store" | |
}, |
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year | day | color | count | |
---|---|---|---|---|
2015 | 25 | gold | 6695 | |
2015 | 25 | silver | 2534 | |
2015 | 24 | gold | 7727 | |
2015 | 24 | silver | 105 | |
2015 | 23 | gold | 8999 | |
2015 | 23 | silver | 44 | |
2015 | 22 | gold | 7378 | |
2015 | 22 | silver | 199 | |
2015 | 21 | gold | 9662 |
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# %% | |
import numpy as np | |
import matplotlib.pyplot as plt | |
from cycler import cycler | |
import matplotlib.patheffects as path_effects | |
# %% | |
np.random.seed(1) | |
n, m = 200, 6 | |
x = np.arange(n) |
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