Python Space engagement report
@python_spaces - 104K followers on X
Measured over 6 original posts from a 30-day window, last computed on October 14, 2026.
Engagement
Early reading. We have captured 6 original posts for this account, below the 8 we require before treating a median as settled. The numbers above describe what we have seen so far, not a finished profile of the account.
A typical post picks up 46 interactions against 104K followers, an engagement rate of 0.044%. Posts are seen about 5.8K times each, and 0.795% of those impressions turn into an interaction. That is about 5.54% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 1.6 posts a day over the last 30 days, with activity on roughly 50% of days. Most posts go out around 17:00 UTC, and Friday is the busiest day of the week. Of the 6 posts sampled, 50% carry an image or video, 33% are part of a thread and 33% link out. The account's strongest tracked post pulled 346 interactions, about 7.5x its own typical post. Only 6 original posts have been captured so far, fewer than the 8 posts we want behind a median before treating it as settled. Read the figures above as an early measurement of this account, not as a finished profile of it.
Measured over 6 original posts from a 30-day window, last computed on October 14, 2026.
Where this sits in the catalog
At 0.044%, Python Space sits above the 25th percentile of the 212,270 accounts in this comparison. That places it in the below the median band, which runs 0.025% to 0.146%.
Show the percentile table
| Percentile | Engagement rate |
|---|---|
| 10th percentile | 0.004% |
| 25th percentile | 0.025% |
| 50th percentile | 0.146% |
| 75th percentile | 0.695% |
| 90th percentile | 2.61% |
| 99th percentile | 83.1% |
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 17:00 UTC, and Friday 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.
Show engagement by hour posted, utc as a table
| Hour (UTC) | Vs author median | Posts |
|---|---|---|
| 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 UTC | 0% | 116K |
| 22:00 UTC | -2% | 100K |
| 23:00 UTC | -1% | 90K |
Show engagement by day of week as a table
| Day | Vs author median | Posts |
|---|---|---|
| Sunday | +5% | 393K |
| Monday | +1% | 483K |
| Tuesday | -2% | 520K |
| Wednesday | -3% | 472K |
| Thursday | -2% | 430K |
| Friday | -3% | 447K |
| Saturday | +2% | 393K |
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.
| Format | This account | Catalog effect | 95% interval | Accounts behind it |
|---|---|---|---|---|
| Image or video | 50% of posts | +111% | +108% to +115% | 34K |
| Outbound link | 33% of posts | -41% | -42% to -40% | 32K |
| Typical length | - | no effect | -2% to -1% | 42K |
- 50% 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.
- 33% 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 235 characters, which falls in the 180 - 280 characters band. Across the catalog, posts of 180 to 280 characters match the same accounts' other posts almost exactly.
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 25, 20267.5x their median
Tested Qoder this week. Dropped a docs link into the task screen. Asked it to generate an architecture diagram. The agent read the docs, planned the structure, and built the diagram without me touching a single tool. https://t.co/xH0uBeXq8M
- Sep 25, 20266.5x their median
https://t.co/VVDiN1rvRU
- Oct 5, 20261.7x their median
Everyone is talking about Jev right now. Devs are already building wild things with it. Mario bots, drones, on-chain traders. Here are 10 open source projects worth copying if you have Jev API access 🧵👇 https://t.co/dWLGRqniVk
- Oct 10, 2026
Overnight agent runs rarely go wrong because of the coding. They go wrong because nothing checks the work until a human wakes up. This is the loop that fixes that. The agent writes the code, calls the TestSprite CLI to run Integration Tests against the running app, reads the failing step and fix prompt that come back, patches the code, and runs the tests again. No human in the loop until the flows pass. The animation is the cute version. The real version leaves a video replay of every run for you to check over breakfast.
- Oct 11, 2026
What are the current problems with Local AI? @grok
- Oct 3, 2026
Immediate openings at https://t.co/Xs57hX4cmL Bringing on 50 Staff-level Software Engineers this month. You’ll partner with leading frontier labs on evaluations and dataset creation. $200–$300/hr Fully remote It’s demanding, detail-heavy work definitely not glamorous but the compensation reflects it. Apply: https://t.co/xMzK8yvH1r
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.
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Reading these numbers
A typical post picks up 46 interactions against 104K followers, an engagement rate of 0.044%. Posts are seen about 5.8K times each, and 0.795% of those impressions turn into an interaction. That is about 5.54% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 1.6 posts a day over the last 30 days, with activity on roughly 50% of days. Most posts go out around 17:00 UTC, and Friday is the busiest day of the week. Of the 6 posts sampled, 50% carry an image or video, 33% are part of a thread and 33% link out. The account's strongest tracked post pulled 346 interactions, about 7.5x its own typical post. Only 6 original posts have been captured so far, fewer than the 8 posts we want behind a median before treating it as settled. Read the figures above as an early measurement of this account, not as a finished profile of it.
- What is Python Space's engagement rate on X?
- Python Space (@python_spaces) has an engagement rate of 0.044%, based on the median interactions across 6 original posts from the last 30 days against 104,348 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
- Is that a good engagement rate?
- At 0.044%, Python Space sits above the 25th percentile of the 212,270 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 @python_spaces have real engagement?
- There is not yet enough sample to rank this account against others of its size.
- When does @python_spaces post?
- Most posts go out around 17:00 UTC, and Friday is its busiest day, at roughly 1.57 posts per day across the measured window.