Back to @PythonDvz's profile

Dvz | Python Architect engagement report

@PythonDvz - 186K followers on X

Measured over 59 original posts from a 30-day window, last computed on October 14, 2026.

Engagement

Middle of its size range
Per follower
0.036%
of 186K followers
Per impression
1.10%
6.1K views on a typical post
Reach
3.28%
of its followers see a post
Typical post
67
interactions (median)
Saved
0.196%
12 bookmarks on a typical post
Posting rate
3.77/day
active 50% of days
Peak time
11:00 UTC
Tuesday

A typical post picks up 67 interactions against 186K followers, an engagement rate of 0.036%. Measured over 59 original posts, its engagement rate beats 41% of 21,185 tracked accounts of a similar size, which puts it in the middle of its size range rather than at either end. Posts are seen about 6.1K times each, and 1.10% of those impressions turn into an interaction. That is about 3.28% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 3.8 posts a day over the last 30 days, with activity on roughly 50% of days. Most posts go out around 11:00 UTC, and Tuesday is the busiest day of the week. Of the 59 posts sampled, 95% carry an image or video and 37% are part of a thread. The account's strongest tracked post pulled 29K interactions, about 427x its own typical post. Recurring topics include #python, #codingquiz, #systemdesign.

Measured over 59 original posts from a 30-day window, last computed on October 14, 2026. Recurring tags: #python, #codingquiz, #systemdesign.

Compared with accounts its own size

Dvz | Python Architect's engagement rate beats 41% of the tracked X accounts closest to it in follower count (21,185 accounts, accounts of similar size (decile 9 of 10)). A percentile is spread evenly by construction, so 50 really is the middle of that group and 90 really is its top tenth.

On engagement per impression rather than per follower it beats 45% of the same group. When those two numbers disagree, the gap is about how far its posts travel rather than how people react to them.

Where this sits in the catalog

At 0.036%, Dvz | Python Architect sits above the 25th percentile of the 211,975 accounts in this comparison. That places it in the below the median band, which runs 0.025% to 0.146%.

p100.004%
p250.025%
p50 (median)0.146%
p750.694%
p902.61%
p9983.1%
Engagement rate as a share of followers, across the 211,975 accounts we have scanned enough to measure. The axis is logarithmic, because the top and bottom of this population are about 22,461 times apart and a linear axis would flatten everything below the median into a single point.
Show the percentile table
Engagement rate percentiles
PercentileEngagement rate
10th percentile0.004%
25th percentile0.025%
50th percentile0.146%
75th percentile0.694%
90th percentile2.61%
99th percentile83.1%

This ruler is the whole measured catalog, not a size-matched group: it shows where the raw rate falls across every account we can measure, all of which are large. For a like-for-like comparison, read the size-band percentile above instead. See how the bands are built

Posting timing

This account posts most often around 11:00 UTC, and Tuesday is its busiest day of the week. The bars below are the catalog-wide pattern, with this account's own busiest slot marked. They do not show how this account performs at each hour: we keep one aggregate per account, not one per hour, so that measurement does not exist in our data.

Engagement by hour posted, UTCTwenty-four bars, one per UTC hour. Each bar shows how posts published in that hour compare with their own authors' median engagement. Bars above the centre line ran higher than the median, bars below ran lower. A marker flags Busiest hour: 11:00 UTC.
0003060912151821
Above the authors' own mediansBelowScale: plus or minus 111%Busiest hour: 11:00 UTC
Show engagement by hour posted, utc as a table
Engagement by hour posted, UTC
Hour (UTC)Vs author medianPosts
00:00 UTC-1%89K
01:00 UTC-2%90K
02:00 UTC-3%88K
03:00 UTC-4%94K
04:00 UTC-5%76K
05:00 UTC-4%75K
06:00 UTC-5%86K
07:00 UTC-5%93K
08:00 UTC-4%108K
09:00 UTC-4%124K
10:00 UTC-3%129K
11:00 UTC-3%141K
12:00 UTC-3%154K
13:00 UTC-3%167K
14:00 UTC-4%173K
15:00 UTC-2%176K
16:00 UTC-3%171K
17:00 UTC-3%159K
18:00 UTC-2%149K
19:00 UTC-2%141K
20:00 UTC-1%131K
21:00 UTC0%116K
22:00 UTC-2%100K
23:00 UTC-1%90K
Engagement by day of weekSeven bars, one per weekday, Sunday first. Each bar shows how posts published on that day compare with their own authors' median engagement. Bars above the centre line ran higher than the median, bars below ran lower. A marker flags Busiest day: Tuesday.
SunMonTueWedThuFriSat
Above the authors' own mediansBelowScale: plus or minus 111%Busiest day: Tuesday
Show engagement by day of week as a table
Engagement by day of week
DayVs author medianPosts
Sunday+5%393K
Monday+1%483K
Tuesday-2%520K
Wednesday-3%472K
Thursday-2%430K
Friday-3%447K
Saturday+2%393K
See what moves engagement across the whole catalogWhat counts as a good engagement rate at this size

Formats this account uses

Its own posting mix on the left, and what each of those formats does across every account we track on the right. Only formats where the effect clears our publish test appear here, so an empty row is a format we could not measure rather than one that does nothing.

This account's posting mix compared with catalog-wide effects
FormatThis accountCatalog effect95% intervalAccounts behind it
Image or video95% of posts+111%+108% to +115%34K
Outbound link3% of posts-41%-42% to -40%32K
Typical length-+15%+14% to +16%32K
  • 95% of this account's sampled posts carry an image or video. Across the catalog, posts with an image or video run 111% above the same accounts' other posts.
  • 3% of its posts carry a link off X. Across the catalog, posts with an outbound link run 41% below the same accounts' other posts.
  • Its average post runs 481 characters, which falls in the over 280 characters band. Across the catalog, posts over 280 characters run 15% above the same accounts' other posts.

These are catalog-wide differences applied to this account's own posting mix, not a measurement of how each format performs for this account specifically. We keep one median per account, not one per format per account, so the second thing is not something this data can tell you.

Best tweets

  • Sep 15, 2026427x their median

    What does he have on that PC 🀣 https://t.co/mCkHmzjaAB

    26K1.5K6881762.5M viewsView on X
  • Sep 10, 2026105x their median

    Apple designers cooked with this new siri animation 😍 #apple https://t.co/RNkJLmBqhA

    6.6K28482372.0M viewsView on X
  • Oct 13, 202634x their median

    In the next version of Bun `bun fmt` is a 320x faster Prettier alternative Passes 99% of Prettier's test suite & supports 20 languages https://t.co/PP0fOF3VNp

    2.0K1201015289K viewsView on X
  • Mar 26, 202656x their median

    Real happiness πŸ˜† https://t.co/Yl0aWbKMY4

    2.0K2231820112K viewsView on X
  • Jul 23, 202624x their median

    🀣🀣🀣 https://t.co/bpVZu6BOrG

    1.5K883615236K viewsView on X
  • Aug 20, 20268.9x their median

    Printing 'Hello World'... https://t.co/zK5EzDFH4Z

    49265231339K viewsView on X
  • Sep 15, 20266.5x their median

    🎯 Stop guessing. See which languages developers actually use. https://t.co/hOei9Ki6p6

    36367518.8K viewsView on X
  • Sep 15, 20265.6x their median

    Agentic AI: A Complete Framework https://t.co/EqkLuxHNct

    30267329.4K viewsView on X
  • Oct 11, 20265.5x their median

    Writing clean, pythonic code isn't about bloating your codebase with boilerplate; it's about mastering high-impact expression patterns that optimize execution density. While junior developers waste lines on verbose loops, production-grade logic leverages streamlined structural primitives. Save this core reference blueprint to audit your data transformation scripts and clean up your production repositories tomorrow! πŸ“Œ

    31448228.0K viewsView on X
  • Oct 4, 20264.2x their median

    πŸš€ SQL to Python: Quickstart Guide for Data Wizards πŸπŸ’» Learning both SQL and Python? Here’s your ultimate cheat sheet to translate SQL queries into Python (Pandas) like a pro! From filtering to merging datasets β€” this guide is your one-stop reference to switch between two of the most in-demand data tools out there. πŸ“Œ Save this if you’re: βœ… A data analyst βœ… Preparing for interviews βœ… Transitioning from SQL to Python βœ… Building projects using Pandas 🧠 Remember: It’s not just what you write, it’s how efficiently you write it. This guide can seriously level up your data game!

    23837416.6K viewsView on X

Ranked by total interactions across everything we have tracked for this account, which is a longer history than the 30-day window the rates above use. The multiple compares each post to this account's own median.

Recurring topics

#python#codingquiz#systemdesign

The most frequent hashtags in the sampled posts. They describe what this account writes about; they are not a performance signal, and the catalog-wide breakdown on the hub shows how little hashtag count moves.

Buy or sell Twitter (X) accounts - escrow-protected

PlayerSells is an escrow marketplace for Twitter (X) accounts. Every deal is protected, with no middleman risk.

Reading these numbers

A typical post picks up 67 interactions against 186K followers, an engagement rate of 0.036%. Measured over 59 original posts, its engagement rate beats 41% of 21,185 tracked accounts of a similar size, which puts it in the middle of its size range rather than at either end. Posts are seen about 6.1K times each, and 1.10% of those impressions turn into an interaction. That is about 3.28% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 3.8 posts a day over the last 30 days, with activity on roughly 50% of days. Most posts go out around 11:00 UTC, and Tuesday is the busiest day of the week. Of the 59 posts sampled, 95% carry an image or video and 37% are part of a thread. The account's strongest tracked post pulled 29K interactions, about 427x its own typical post. Recurring topics include #python, #codingquiz, #systemdesign.

What is Dvz | Python Architect's engagement rate on X?
Dvz | Python Architect (@PythonDvz) has an engagement rate of 0.036%, based on the median interactions across 59 original posts from the last 30 days against 186,220 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
Is that a good engagement rate?
At 0.036%, Dvz | Python Architect sits above the 25th percentile of the 211,975 accounts in this comparison. Those comparison accounts are all large ones, because our scanning cadence is weighted towards big accounts, so this is a ranking among peers of similar scale rather than a ranking across X.
Does @PythonDvz have real engagement?
Its engagement rate beats 41% of the tracked X accounts closest to it in follower count (21,185 accounts), which puts it in the middle of its size range group. Ranking inside a size band matters because engagement rate falls as accounts grow, so a raw rate would mostly re-measure the follower count. It is a starting point for a look at follower quality, not a verdict on it.
When does @PythonDvz post?
Most posts go out around 11:00 UTC, and Tuesday is its busiest day, at roughly 3.77 posts per day across the measured window.

Keep going