File:Bluesky Registered Users.svg

此SVG文件的PNG预览的大小：800 × 480像素。其他分辨率：320 × 192像素 | 1,024 × 614像素 | 1,280 × 768像素 | 2,560 × 1,536像素 | 960 × 576像素。

原始文件 ‎（SVG文件，尺寸为960 × 576像素，文件大小：38 KB）

本文件并非来自中文维基百科，而是来自维基共享资源。请参阅维基共享资源上的详细描述、讨论页、页面历史、日志。

维基共享资源是一个储存自由版权作品的项目。您可以向此项目作出贡献。

摘要

该文件可能会更新以反映新信息
如果您希望在不镜像新更新的情况下使用该文件的特定版本，请将所需版本作为单独的文件上传。

描述

English: This chart depicts the growth of Bluesky, a social network. Data spans May 2023 until January 2024, and shows an increase from 55k to 3.0M users. The chart uses population data from Bluesky API requests rendered into SVG 1.1 using Matplotlib 3.7.2 via Python 3.11.5.

Disclaimer

English: Due to the loss of vqv.app on 2023-11-07, a total of 68 Internet Archive captures across ~70 days from vqv.app/stats/chart, bsky.jazco.dev/stats, and twexit.nl were individually sorted by timestamp, then used to approximate the daily population totals as they would have appeared at the end of each day via linear interpolation. A spreadsheet containing all citations to the relevant Internet Archive captures are available here: Google Sheets. While efforts were made to ensure accuracy, some degree of estimation is inherent in the interpolation process.

日期

2024年1月15日

来源

Bluesky API. Daily population data until 2023-11-07 from https://vqv.app/stats/chart ^{[失效链接]}; Internet Archive for snapshots of user totals from https://bsky.jazco.dev/stats and https://twexit.nl/.

作者

VintageNebula, with data gathered by Eddie Silva, Pedro Borracha, Jaz, and Adraianus

其他版本

此文件取代文件BlueSky user growth.png。建议使用此文件，而不是另外一个。

Bahasa Indonesia ∙ davvisámegiella ∙ Deutsch ∙ English ∙ español ∙ français ∙ italiano ∙ magyar ∙ Nederlands ∙ polski ∙ svenska ∙ македонски ∙ മലയാളം ∙ português do Brasil ∙ русский ∙ slovenščina ∙ 日本語 ∙ 中文（简体） ∙ 中文（繁體） ∙ farsi ∙ +/−

这是一张修改过的图片，这意味着它已在原版本的基础上通过软件进行了编辑，改动内容：Generated with MatPlotLib with updated data and vectorized from source data。其原始版本为：BlueSky user growth.png。修改者：VintageNebula。

SVG开发

该SVG的源代码为有效代码。

本矢量图使用Matplotlib创作。

源代码

Python code

Created using Matplotlib 3.7.2 via Python 3.11.5

# Bluesky Registered Users v1.3 
# Created for Wikimedia Commons; last edited: 2024-01-15

import matplotlib.pyplot as plt
import matplotlib.dates as mdates
from matplotlib.ticker import FixedLocator
from datetime import datetime

'''
The 'data_array' variable holds the population dataset. Each day and value is paired in a list of strings,
formatted as "YYYY-MM-DD, ######", where YYYY-MM-DD is the ISO 8601 date, and ###### is the number of 
existing users at the end of the day listed. Note that values after 2023-11-07 were calculated using
linear interpolation using website captures on the Internet Archive, and are rounded to the nearest 500.
'''
data_array = [
    "2023-05-02, 55570", "2023-05-03, 58119", "2023-05-04, 60909", "2023-05-05, 63362",
    "2023-05-06, 65035", "2023-05-07, 66194", "2023-05-08, 67477", "2023-05-09, 69053",
    "2023-05-10, 70898", "2023-05-11, 72458", "2023-05-12, 74236", "2023-05-13, 76326",
    "2023-05-14, 77472", "2023-05-15, 78972", "2023-05-16, 80328", "2023-05-17, 81682",
    "2023-05-18, 83411", "2023-05-19, 84718", "2023-05-20, 85805", "2023-05-21, 86699",
    "2023-05-22, 87761", "2023-05-23, 89034", "2023-05-24, 90565", "2023-05-25, 92559",
    "2023-05-26, 94625", "2023-05-27, 96395", "2023-05-28, 97927", "2023-05-29, 99408",
    "2023-05-30, 101215", "2023-05-31, 102578", "2023-06-01, 103919", "2023-06-02, 105437",
    "2023-06-03, 106591", "2023-06-04, 107638", "2023-06-05, 108875", "2023-06-06, 110169",
    "2023-06-07, 111989", "2023-06-08, 113673", "2023-06-09, 115868", "2023-06-10, 118019",
    "2023-06-11, 120206", "2023-06-12, 122911", "2023-06-13, 124731", "2023-06-14, 128350",
    "2023-06-15, 131274", "2023-06-16, 133937", "2023-06-17, 136152", "2023-06-18, 137423",
    "2023-06-19, 138780", "2023-06-20, 140016", "2023-06-21, 143093", "2023-06-22, 153451",
    "2023-06-23, 157707", "2023-06-24, 159933", "2023-06-25, 161913", "2023-06-26, 164419",
    "2023-06-27, 169343", "2023-06-28, 174342", "2023-06-29, 179043", "2023-06-30, 184094",
    "2023-07-01, 203365", "2023-07-02, 222026", "2023-07-03, 240687", "2023-07-04, 254189",
    "2023-07-05, 262135", "2023-07-06, 271292", "2023-07-07, 278898", "2023-07-08, 284516",
    "2023-07-09, 287745", "2023-07-10, 291393", "2023-07-11, 294869", "2023-07-12, 299667",
    "2023-07-13, 304946", "2023-07-14, 309949", "2023-07-15, 313683", "2023-07-16, 317209",
    "2023-07-17, 321258", "2023-07-18, 324959", "2023-07-19, 328269", "2023-07-20, 331240",
    "2023-07-21, 335652", "2023-07-22, 340658", "2023-07-23, 347321", "2023-07-24, 370048",
    "2023-07-25, 386014", "2023-07-26, 394662", "2023-07-27, 404693", "2023-07-28, 414773",
    "2023-07-29, 423934", "2023-07-30, 433895", "2023-07-31, 442390", "2023-08-01, 450486",
    "2023-08-02, 458146", "2023-08-03, 472748", "2023-08-04, 487476", "2023-08-05, 499582",
    "2023-08-06, 511605", "2023-08-07, 525141", "2023-08-08, 535769", "2023-08-09, 543286",
    "2023-08-10, 550163", "2023-08-11, 556915", "2023-08-12, 563776", "2023-08-13, 571517",
    "2023-08-14, 581620", "2023-08-15, 591309", "2023-08-16, 601562", "2023-08-17, 611424",
    "2023-08-18, 639033", "2023-08-19, 659173", "2023-08-20, 670671", "2023-08-21, 682208",
    "2023-08-22, 692512", "2023-08-23, 703097", "2023-08-24, 723279", "2023-08-25, 742913",
    "2023-08-26, 758806", "2023-08-27, 768190", "2023-08-28, 777341", "2023-08-29, 788438",
    "2023-08-30, 807753", "2023-08-31, 826957", "2023-09-01, 845340", "2023-09-02, 855268",
    "2023-09-03, 865253", "2023-09-04, 875942", "2023-09-05, 887544", "2023-09-06, 898496",
    "2023-09-07, 913032", "2023-09-08, 933157", "2023-09-09, 952217", "2023-09-10, 968247",
    "2023-09-11, 980472", "2023-09-12, 1001758", "2023-09-13, 1017594", "2023-09-14, 1028614",
    "2023-09-15, 1038289", "2023-09-16, 1046587", "2023-09-17, 1055012", "2023-09-18, 1071682",
    "2023-09-19, 1125267", "2023-09-20, 1157089", "2023-09-21, 1179696", "2023-09-22, 1197915",
    "2023-09-23, 1211413", "2023-09-24, 1223934", "2023-09-25, 1237273", "2023-09-26, 1249557",
    "2023-09-27, 1261156", "2023-09-28, 1272657", "2023-09-29, 1294216", "2023-09-30, 1308941",
    "2023-10-01, 1324469", "2023-10-02, 1343949", "2023-10-03, 1361891", "2023-10-04, 1377805",
    "2023-10-05, 1393473", "2023-10-06, 1410649", "2023-10-07, 1425252", "2023-10-08, 1438074",
    "2023-10-09, 1452503", "2023-10-10, 1470776", "2023-10-11, 1489064", "2023-10-12, 1508389",
    "2023-10-13, 1529182", "2023-10-14, 1543696", "2023-10-15, 1557027", "2023-10-16, 1570787",
    "2023-10-17, 1583493", "2023-10-18, 1618452", "2023-10-19, 1646361", "2023-10-20, 1666281",
    "2023-10-21, 1681299", "2023-10-22, 1694865", "2023-10-23, 1709734", "2023-10-24, 1725184",
    "2023-10-25, 1738664", "2023-10-26, 1750386", "2023-10-27, 1761839", "2023-10-28, 1772651",
    "2023-10-29, 1785693", "2023-10-30, 1799713", "2023-10-31, 1811867", "2023-11-01, 1823445",
    "2023-11-02, 1836704", "2023-11-03, 1850723", "2023-11-04, 1863205", "2023-11-05, 1876044",
    "2023-11-06, 1890622", "2023-11-07, 1902887", "2023-11-08, 1918000", "2023-11-09, 1935000",
    "2023-11-10, 1953000", "2023-11-11, 1973500", "2023-11-12, 1994000", "2023-11-13, 2010500",
    "2023-11-14, 2023500", "2023-11-15, 2038000", "2023-11-16, 2052000", "2023-11-17, 2067500",
    "2023-11-18, 2085000", "2023-11-19, 2103500", "2023-11-20, 2124000", "2023-11-21, 2144500",
    "2023-11-22, 2156000", "2023-11-23, 2170500", "2023-11-24, 2189500", "2023-11-25, 2202500",
    "2023-11-26, 2217000", "2023-11-27, 2229000", "2023-11-28, 2252500", "2023-11-29, 2274500",
    "2023-11-30, 2287000", "2023-12-01, 2318000", "2023-12-02, 2339500", "2023-12-03, 2364000",
    "2023-12-04, 2383500", "2023-12-05, 2402000", "2023-12-06, 2418500", "2023-12-07, 2443500",
    "2023-12-08, 2463500", "2023-12-09, 2484000", "2023-12-10, 2493500", "2023-12-11, 2503000",
    "2023-12-12, 2510500", "2023-12-13, 2523500", "2023-12-14, 2538000", "2023-12-15, 2552500",
    "2023-12-16, 2568000", "2023-12-17, 2585000", "2023-12-18, 2611500", "2023-12-19, 2635000",
    "2023-12-20, 2658500", "2023-12-21, 2690000", "2023-12-22, 2712500", "2023-12-23, 2734500",
    "2023-12-24, 2755500", "2023-12-25, 2773500", "2023-12-26, 2791000", "2023-12-27, 2805000",
    "2023-12-28, 2821500", "2023-12-29, 2838000", "2023-12-30, 2854500", "2023-12-31, 2872000",
    "2024-01-01, 2890000", "2024-01-02, 2904500", "2024-01-03, 2917500", "2024-01-04, 2927500",
    "2024-01-05, 2935500", "2024-01-06, 2943000", "2024-01-07, 2961000", "2024-01-08, 2988500",
    "2024-01-09, 3009500", "2024-01-10, 3017000", "2024-01-11, 3024000", "2024-01-12, 3031500",
    "2024-01-13, 3039000", "2024-01-14, 3044000"
]

# Convert the data point strings to datetime objects.
date_rng = [datetime.strptime(row.split(',')[0].strip('"'), "%Y-%m-%d") for row in data_array]
y_values = [int(row.split(',')[1].strip()) for row in data_array]

# Create an initial plot.
fig, ax = plt.subplots(figsize=(10, 6))

# Plot the main data line and specify its z-order for layering.
ax.plot(date_rng, y_values, zorder=2)

# Add a grid and fill the area under the data line.
ax.grid(True, linestyle="-", linewidth=0.4, alpha=0.4)
ax.fill_between(date_rng, y_values, color="skyblue", alpha=0.4, zorder=1)

# Translators - edit these strings to translate into the desired language.
plt.title("Bluesky - Registered Users")
plt.xlabel("Date (YYYY-MM)")
plt.ylabel("Total Registered Users")

# Set the format for the x-axis to display only the first day of each month (ie. YYYY-MM).
ax.xaxis.set_major_locator(mdates.MonthLocator(bymonthday=1))
ax.xaxis.set_major_formatter(mdates.DateFormatter("%Y-%m"))

# Make sure y-axis starts at 0.
ax.set_ylim(bottom=0)

# Format y-axis labels with commas and set tick locations.
y_ticks = ax.get_yticks()
ax.yaxis.set_major_locator(FixedLocator(y_ticks))
ax.set_yticklabels([f'{int(label):,}' for label in y_ticks])

# Hide y-axis offset number (1e6, etc.)
ax.yaxis.offsetText.set_visible(False)

'''
Logic to highlight and label the first day of each month:
     1. Create an empty set to keep track of processed months.
     2. Loop through each date-value pair.
     3. Check if the day is the 1st of the month or if the month hasn't been processed yet.
     4. Place a scatter dot on the first day of the unprocessed month.
     5. Annotate the scatter dot with the corresponding value.
     6. Add the month to the set to avoid processing it again.
'''
months = set()
for date, value in zip(date_rng, y_values):
     if date.day == 1 or date.strftime("%Y-%m") not in months:
          ax.scatter(date, value, color='C0', marker='o', alpha=1, zorder=3)
          ax.annotate(f'{value:,}', (date, value), textcoords="offset points", xytext=(0, 10), ha='center')
          months.add(date.strftime("%Y-%m"))

# Optimize for visibility, then display.
plt.tight_layout()
plt.show()

许可协议

本作品基于公有领域中的作品。它已经过数字增强和/或修改。该衍生作品已（或特此）由其作者VintageNebula发布到公有领域。这适用于全世界。

在一些国家这可能不合法；如果是这样的话，那么：

VintageNebula无条件地授予任何人以任何目的使用本作品的权利，除非这些条件是法律规定所必需的。

文件历史

点击某个日期/时间查看对应时刻的文件。

	日期/时间	大小	用户	备注
当前	2024年1月15日 (一) 02:40	960 × 576（38 KB）	VintageNebula	Update data to January 2024
	2023年11月6日 (一) 01:50	960 × 576（37 KB）	VintageNebula	Update data to November 2023
	2023年10月9日 (一) 01:44	900 × 540（48 KB）	VintageNebula	Uploaded a work by Data compiled by m3ta.uk (Pedro) and vqv.app (Eddie). Chart created by VintageNebula (myself). from Data was obtained from requests to the public-facing Bluesky API, which were archived and rendered for display at https://vqv.app/stats/chart. Chart generated using the archived Bluesky API data created by VintageNebula (myself) using Matplotlib. with UploadWizard

文件用途

以下页面使用本文件：

Bluesky

全域文件用途

以下其他wiki使用此文件：

ar.wikipedia.org上的用途
- بلوسکاي
cs.wikipedia.org上的用途
- Wikipedista:Jaroslav Mašek/Pískoviště
- Bluesky
de.wikipedia.org上的用途
- Bluesky
en.wikipedia.org上的用途
- Bluesky (social network)
it.wikipedia.org上的用途
- Bluesky
ru.wikipedia.org上的用途
- Bluesky
uk.wikipedia.org上的用途
- Bluesky

元数据

此文件中包含有扩展的信息。这些信息可能是由数码相机或扫描仪在创建或数字化过程中所添加。

如果此文件的源文件已经被修改，一些信息在修改后的文件中将不能完全反映出来。

宽度	960
高度	576

File:Bluesky Registered Users.svg

摘要

Python code

许可协议

说明

此文件中描述的项目

描繪內容

折线图

参考文献

著作權狀態

保有知識產權並由其所有者公開於公有領域

许可协议

著作权持有者释出至公有领域 ^{简体中文（已转写）}

成立或建立時間

6 10 2023

多媒體型式

image/svg+xml

核對和

e36046a4f02e617eb799fc69f1922accf91930fe

資料大小

37,672 字节

高度

576 像素

寬度

960 像素

文件历史

文件用途

全域文件用途

元数据

摘要

Python code

许可协议

说明

此文件中描述的项目

参考文献

著作权持有者释出至公有领域 简体中文（已转写）

6 10 2023

image/svg+xml

e36046a4f02e617eb799fc69f1922accf91930fe

37,672 字节

576 像素

960 像素

文件历史

文件用途

全域文件用途

元数据

著作权持有者释出至公有领域 ^{简体中文（已转写）}