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Generating stats from the raw Hacktoberfest application data.
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Generating stats from the raw Hacktoberfest application data.

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README 

        
# Hacktoberfest {{= data.readme.year }} Stats



Hi there, 👋



I'm [Matt Cowley](https://mattcowley.co.uk/), Senior Software Engineer II at

[DigitalOcean](https://digitalocean.com/).



I work on a bunch of things at DigitalOcean, with a great mix of engineering, developer relations

and community management. And, part of what I get to work on is helping out with Hacktoberfest,

including being the lead engineer for the backend that powers the event.



Welcome to my deeper dive on the data and stats for Hacktoberfest {{= data.readme.year }}, expanding

on what we already shared in our [recap blog post](https://{{= data.readme.blog }}).



## At a glance



What did we accomplish together in October {{= data.readme.year }}?

These are the highlights from Hacktoberfest #{{= data.readme.year - 2013 }}:



- Registered users: **{{= c(data.readme.registeredUsers) }}**

- Engaged users (1-3 accepted PR/MRs): **{{= c(data.readme.engagedUsers) }}**

- Completed users (4+ accepted PR/MRs): **{{= c(data.readme.completedUsers) }}**

- Accepted PR/MRs: **{{= c(data.readme.acceptedPRs) }}**

- Active repositories (1+ accepted PR/MRs): **{{= c(data.readme.activeRepos) }}**

- Countries represented by registered users: **{{= c(data.readme.countriesRegistered) }}**

- Countries represented by completed users: **{{= c(data.readme.countriesCompleted) }}**



> Take a read of our overall recap blog post for Hacktoberfest {{= data.readme.year }} here:

> [{{= data.readme.blog }}](https://{{= data.readme.blog }})



## Application states



Before jumping in and looking at the data in detail, we should first cover some important

information about how we categorise users and pull/merge requests in the Hacktoberfest application

and in the data used here.



For users, there are four key states that you'll see:



- **Completed**: A user that submitted four or more accepted PR/MRs during Hacktoberfest.

- **Engaged**: A user that submitted between one and three accepted PR/MRs during Hacktoberfest.

- **Registered**: A user that completed the registration flow for Hacktoberfest, but did not submit

  any PR/MRs that were accepted.

- **Disqualified**: A user that was disqualified for submitting 2 or more spammy PR/MRs,

  irrespective of how many accepted PR/MRs they may have also had.



For pull/merge requests, there are six states used to process them that you'll see:



- **Accepted**: A PR/MR that was accepted by a project maintainer, either by being merged or

  approved in a participating repository, or by being given the `hacktoberfest-accepted` label.

- **Not accepted**: Any PR/MR that was submitted to a participating repository (having the

  `hacktoberfest` topic), but that was not actively accepted by a maintainer.

- **Not participating**: Any PR/MR that was submitted by a participant to a repository that was not

  participating in Hacktoberfest (i.e. having the `hacktoberfest` topic, or adding the

  `hacktoberfest-accepted` label to specific PRs).

- **Invalid**: Any PR/MR that was given a label containing the word `invalid` by a maintainer. Any

  PR/MR with a matching label was not counted towards a participant's total.

- **Spam**: Any PR/MR that was given a label by a maintainer containing the 'spam', or PR/MRs that 

  our abuse logic detected as spam. These are not counted toward winning, and also count toward a

  user being disqualified.

- **Excluded**: Any PR/MR that was submitted to a repository that has been excluded from

  Hacktoberfest for not following our values. These do not count toward winning, nor do they count

  toward a user being disqualified.



## Diving in: Users



This year, Hacktoberfest had **{{= c(data.Users.totalUsers) }}** folks who went through our

registration flow for the event. Spam has been a huge focus for us throughout the event, as with

previous years, and so during this flow folks were reminded about our rules and values for the event

with clear and simple language, as well as agreeing to a rule that folks with two or more PR/MRs

identified as spam by maintainers would be disqualified. More on this later.



During the registration flow, folks can also choose to tell us which country they are from--this

helps us better understand, and cater to, the global audience for the event--and

**{{= p((data.Users.totalUsers - data.Users.totalUsersNoCountry) / data.Users.totalUsers) }}** of

them did so.





  Bar chart of the top countries for completed users

  Bar chart of the top countries for all registered users




The top country, by far, was once again {{= data.Users.totalUsersByCountry[0][0] }} with

**{{= c(data.Users.totalUsersByCountry[0][1]) }}

({{= p(data.Users.totalUsersByCountry[0][1] / data.Users.totalUsers) }})** registrants

self-identifying as being from there, showing how much of a reach open-source, and tech in general,

has there.



We can see the true global reach of Hacktoberfest and open-source by looking at more of the top

countries based on registrations:



{{~ data.Users.totalUsersByCountry.slice(0, 10) :item:i }}

{{= i + 1 }}. {{= item[0] }}: {{= c(item[1]) }} ({{= p(item[1] / data.Users.totalUsers) }})

{{~ }}



In total, **{{= c(data.Users.totalUsersByCountry.length) }} countries** were represented by folks

that registered for the {{= data.readme.year }} event.



We can also look at just the users that completed Hacktoberfest, and see how the countries are

distributed for those users:



{{~ data.Users.totalUsersCompletedByCountry.slice(0, 10) :item:i }}

{{= i + 1 }}. {{= item[0] }}: {{= c(item[1]) }} ({{= p(item[1] / data.Users.totalUsersCompleted) }})

{{~ }}



Doughnut diagram of users by application state



Of course, there's more to Hacktoberfest than just registering for the event, folks actually submit

PR/MRs to open-source projects! This year, we had

**{{= c(data.Users.totalUsersCompleted + data.Users.totalUsersEngaged) }}

users

({{= p((data.Users.totalUsersCompleted + data.Users.totalUsersEngaged) / data.Users.totalUsers) }}

of total registrations)** that submitted one or more PR/MRs that were accepted by maintainers.

Of those, **{{= c(data.Users.totalUsersCompleted) }}

({{= p(data.Users.totalUsersCompleted / (data.Users.totalUsersCompleted + data.Users.totalUsersEngaged)) }})

({{= p(data.Users.totalUsersCompleted / data.Users.totalUsers) }} of total registrations)** went on

to submit at least four accepted PR/MRs to successfully complete Hacktoberfest.



Impressively, we saw that **{{= c(data.Users.totalUsersByAcceptedPRsCapped[4][1]) }} users

({{= p(data.Users.totalUsersByAcceptedPRsCapped[4][1] / data.Users.totalUsersCompleted) }} of total

completed)** submitted more than 4 accepted PR/MRs, going above and beyond to contribute to

open-source outside the goal set for completing Hacktoberfest.



This year, Hacktoberfest removed the free t-shirt as a reward for completing Hacktoberfest, instead

replacing it with a digital reward kit unlocked once you had four accepted PR/MRs, and a digital

badge from Holopin that levelled up with each PR/MR accepted on your journey from registration to

completion. While we still saw many folks register and engage with Hacktoberfest, the numbers are

much lower than previous years, likely due to this change in reward, and while disappointing this

was expected.



Sadly, {{= c(data.Users.totalUsersDisqualified) }} users were disqualified this year

({{= p(data.Users.totalUsersDisqualified / data.Users.totalUsers) }} of total registrations), with

an additional {{= c(data.Users.totalUsersWarned) }}

({{= p(data.Users.totalUsersWarned / data.Users.totalUsers) }} of total registrations) warned.

Disqualification of users happen automatically if two or more of their PR/MRs are actively

identified as spam by project maintainers, with users being sent a warning email (and shown a notice

on their profile) when they have one PR/MR that is identified as spam. We were very happy to see how

low this number was though, indicating to us that our efforts to educate and remind contributors of

the quality standards expected of them during Hacktoberfest are working. _(Of course, we can only

report on what we see in our data here, and do acknowledge that folks may have received spam that

wasn't flagged so won't be represented in our reporting)._






Hacktoberfest supported multiple providers this year, GitHub & GitLab. Registrants could choose to

link just one provider to their account, or multiple if they desired, with contributions from each

provider combined into a single record for the user.



Based on this we can take a look at the most popular providers for open-source based on some

Hacktoberfest-specific metrics. First, we can see that based on registrations, **the most popular

provider was {{= data.Users.totalUsersByProvider[0][0] }} with

{{= c(data.Users.totalUsersByProvider[0][1]) }} registrants

({{= p(data.Users.totalUsersByProvider[0][1] / data.Users.totalUsers) }}).**



{{~ data.Users.totalUsersByProvider :item:i }}

{{= i + 1 }}. {{= item[0] }}: {{= c(item[1]) }}

  ({{= p(item[1] / data.Users.totalUsers) }} of registered users)

{{~ }}



_Users were able to link one or more providers to their account, so the counts here may sum to more

than the total number of users registered._



We can also look at a breakdown of users that were engaged (1-3 accepted PR/MRs) and users that

completed Hacktoberfest (4+ PR/MRs) by provider.



Engaged users by provider:



{{~ data.Users.totalUsersEngagedByProvider :item:i }}

- {{= item[0] }}: {{= c(item[1]) }}

  ({{= p(item[1] / data.Users.totalUsersEngaged) }} of engaged users)

{{~ }}



Completed users by provider:



{{~ data.Users.totalUsersCompletedByProvider :item:i }}

- {{= item[0] }}: {{= c(item[1]) }}

  ({{= p(item[1] / data.Users.totalUsersCompleted) }} of completed users)

{{~ }}



Bar chart of users by experience level



When registering for Hacktoberfest, we also asked users for some optional self-identification around

their experience with contributing to open-source, and how they intended to contribute. First, we

can take a look at the experience level users self-identified as having when registering:



{{~ data.Users.totalUsersByExperience :item:i }}

- {{= item[0] }}: {{= c(item[1]) }}

  ({{= p(item[1] / data.Users.totalUsers) }} of registered users)

{{~ }}



_{{= c(data.Users.totalUsersNoExperience) }} users did not self-identify their experience level._



We can compare this to the breakdown of users that completed Hacktoberfest by experience level:



{{~ data.Users.totalUsersCompletedByExperience :item:i }}

- {{= item[0] }}: {{= c(item[1]) }}

  ({{= p(item[1] / data.Users.totalUsersCompleted) }} of completed users)

{{~ }}



_{{= c(data.Users.totalUsersCompletedNoExperience) }} users who completed Hacktoberfest did not

self-identify their experience when registering._






Not everyone is comfortable writing code, and so Hacktoberfest focused on encouraging more

contributors to get involved with open-source this year through non-code contributors. We can look

at what contribution types users indicated they intended to make during Hacktoberfest when

registering (they could pick multiple, or none):



{{~ data.Users.totalUsersByContribution :item:i }}

- {{= item[0] }}: {{= c(item[1]) }}

  ({{= p(item[1] / data.Users.totalUsers) }} of registered users)

{{~ }}



_Of course, this is only what users indicated they intended to do, and doesn't necessarily reflect

their actual contributions they ended up making to open-source (determining what is and what isn't

a "non-code" PR/MR would be a difficult task)._



This year, we also asked users during registration whether they were students or not, to give us a

better sense of the audience that is participating in Hacktoberfest. We can see that

**{{= c(data.Users.totalUsersStudents) }} users

({{= p(data.Users.totalUsersStudents / data.Users.totalUsers) }} of registered users)** indicated

that they were students when registering.



Bar chart of users by AI/ML interest



Folks were also asked if they'd be interested in contributing to AI/ML projects specifically during

Hacktoberfest, as this area of open-source is growing rapidly and we wanted to see if there was

interest in it.



We can see that **{{= c(data.Users.totalUsersAIML) }} users

({{= p(data.Users.totalUsersAIML / data.Users.totalUsers) }} of registered users)** indicated they

were actively interested in AI/ML projects, while **{{= c(data.Users.totalUsersNotAIML) }} users

({{= p(data.Users.totalUsersNotAIML / data.Users.totalUsers) }} of registered users)** indicated

they were not interested in AI/ML projects (this was an optional question, with

{{= c(data.Users.totalUsersMissingAIML) }} users not providing a preference).



While we obviously can't know for sure the preference of those that did not interact with this

question, there was a much larger portion of folks registering that did not engage with this

question than other questions ({{= p(data.Users.totalUsersMissingAIML / data.Users.totalUsers) }},

compared to just {{= p(data.Users.totalUsersNoExperience / data.Users.totalUsers) }} that did not

indicate their experience level), which is potentially an indicator that folks were unfamiliar with

or disinterested in AI/ML.






As with previous years of Hacktoberfest, users had to submit PR/MRs to participating projects during

October that then had to be accepted by maintainers during October. If a user submitted four or

more PR/MRs, then they completed Hacktoberfest. However, not everyone hit the 4 PR/MR target, with

some falling short, and many going beyond the target to contribute further.



We can see how many accepted PR/MRs each user had and bucket them:



{{~ data.Users.totalUsersByAcceptedPRs :item:i }}

- {{= item[0] }}{{= (i === data.Users.totalUsersByAcceptedPRs.length - 1 ? '+' : '') }}

  PR{{= (item[0] === 1 ? '': 's') }}/MR{{= (item[0] === 1 ? '': 's') }}: {{= c(item[1]) }}

  ({{= p(item[1] / data.Users.totalUsersCompleted) }})

{{~ }}



Looking at this, we can see that quite a few users only managed to get 1 accepted PR/MR, but

after that it quickly trailed off for 2 and 3 PR/MRs. It seems like the target of 4 PR/MRs

encouraged many users to push through to getting all 4 PR/MRs created/accepted if they got that

first one completed.



![Bar chart of users by accepted PR/MRs](generated/users_by_prs_extended_column.png)



## Diving in: Pull/Merge Requests



Doughnut diagram of PR/MRs by application state



Now on to what you've been waiting for, and the core of Hacktoberfest itself, the pull/merge

requests. This year Hacktoberfest tracked **{{= c(data.PRs.totalPRs) }}** PR/MRs that were within

the bounds of the Hacktoberfest event, and **{{= c(data.PRs.totalAcceptedPRs) }}

({{= p(data.PRs.totalAcceptedPRs / data.PRs.totalPRs) }})** of those went on to be accepted!



Unfortunately, not every pull/merge request can be accepted though, for one reason or another, and

this year we saw that there were **{{= c(data.PRs.totalNotAcceptedPRs )}}

({{= p(data.PRs.totalNotAcceptedPRs / data.PRs.totalPRs) }})** PR/MRs that were submitted to

participating repositories but that were not accepted by maintainers, as well as

**{{= c(data.PRs.totalNotParticipatingPRs )}}

({{= p(data.PRs.totalNotParticipatingPRs / data.PRs.totalPRs) }})** PR/MRs submitted by

Hacktoberfest participants to repositories that were not participating in Hacktoberfest. As a

reminder to folks, repositories opt-in to participating in Hacktoberfest by adding the

`hacktoberfest` topic to their repository (or individual PR/MRs can be opted-in with the

`hacktoberfest-accepted` label).



Spam is also a big issue that we focus on reducing during Hacktoberfest, and we tracked the number

of PR/MRs that were identified by maintainers as spam, as well as those that were caught by

automation we'd written to stop spammy users. We'll talk more about all-things-spam later on.






This year, Hacktoberfest supported multiple providers that contributors could use to submit

contributions to open-source projects. Let's take a look at the breakdown of PR/MRs per provider:



{{~ data.PRs.totalPRsByProvider :item:i }}

{{= i + 1 }}. {{= item[0] }}: {{= c(item[1]) }}

  ({{= p(item[1] / data.PRs.totalPRs) }} of total PR/MRs)

{{~ }}



PRs and MRs that are accepted by maintainers for Hacktoberfest aren't necessarily merged --

Hacktoberfest supports multiple different ways for a maintainer to indicate that a PR/MR is

legitimate and should be counted. PR/MRs can be merged, or they can be given the

`hacktoberfest-accepted` label, or maintainers can leave an overall approving review.



Of the accepted PR/MRs, **{{= c(data.PRs.totalAcceptedPRsMerged) }}

({{= p(data.PRs.totalAcceptedPRsMerged / data.PRs.totalAcceptedPRs) }})** were merged into the

repository, and **{{= c(data.PRs.totalAcceptedPRsApproved) }}

({{= p(data.PRs.totalAcceptedPRsApproved / data.PRs.totalAcceptedPRs) }})** were approved by a

maintainer. Note that there may be overlap here, as a PR/MR may have been approved and then merged.

Unfortunately, we don't have direct aggregated data for the `hacktoberfest-accepted` label.



With this many accepted PRs, we can also take a look at some interesting averages determined from

the accepted PR/MRs. The average accepted PR/MR...



- ...contained **{{= c(data.PRs.averageAcceptedPRCommits) }} commits**

- ...added/edited/removed **{{= c(data.PRs.averageAcceptedPRFiles) }} files**

- ...made a total of **{{= c(data.PRs.averageAcceptedPRAdditions) }} additions** _(lines)_

- ...included **{{= c(data.PRs.averageAcceptedPRDeletions) }} deletions** _(lines)_



_Note that lines containing edits will be counted as both an addition and a deletion._



We can also take a look at all the different languages that we observed during Hacktoberfest. These

are based on the primary language reported for the repository, and the number of accepted

Hacktoberfest PRs that were submitted to that repository. Unfortunately, GitLab does not expose

language information via their API, so this only considers GitHub PRs.



{{~ data.PRs.totalAcceptedPRsByLanguage.slice(0, 10) :item:i }}

{{= i + 1 }}. {{= item[0] }}: {{= c(item[1]) }}

  ({{= p(item[1] / data.PRs.totalAcceptedPRs) }} of all accepted PRs)

{{~ }}



Bar chart of accepted PR/MRs by most popular days



Hacktoberfest happens throughout the month of October, with participants allowed to submit

pull/merge requests at any point from October 1 - 31 in any timezone. However, there tends to be

large spikes in submitted PR/MRs towards the start and end of the month as folks are reminded to

get them in to count! Let's take a look at the most popular days during Hacktoberfest by accepted

PR/MR creation this year:



{{~ data.PRs.totalPRsByDay :item:i }}

{{= i + 1 }}. {{= item[0] }}: {{= c(item[1]) }}

  ({{= p(item[1] / data.PRs.totalAcceptedPRs) }} of all accepted PRs)

{{~ }}






## Diving in: Spam



After the issues Hacktoberfest faced at the start of the 2020 event, spam was top of mind for our

whole team this year as we planned and launched Hacktoberfest {{= data.readme.year }}. We kept the

rules the same as we'd landed on last year, with Hacktoberfest being an opt-in event for

repositories, and  our revised standards on quality contributions to make it easier for participants

to understand what is expected of them when contributing to open source as part of Hacktoberfest.



**Our efforts to reduce spam can be seen in our data, with only {{= c(data.PRs.totalSpamPRs) }}

({{= p(data.PRs.totalSpamPRs / data.PRs.totalPRs) }}) pull/merge requests being flagged as spam by

maintainers (or identified as spam by our automated logic).** _(Of course, we can only report on

what we see in our data here, and do acknowledge that folks may have received spam that wasn't

flagged so won't be represented in our reporting)._



We also took a stronger stance on excluding repositories reported by the community that did not

align with our values, mostly repositories encouraging low effort contributions to allow folks to

quickly win Hacktoberfest. Pull/merge requests to a repository that had been excluded from

Hacktoberfest, based on community reports, would not be counted for winning Hacktoberfest (but also

would not count against individual users in terms of disqualification).



**Excluded repositories accounted for a much larger swathe of pull/merge requests during

Hacktoberfest, with {{= c(data.PRs.totalExcludedPRs) }}

({{= p(data.PRs.totalExcludedPRs / data.PRs.totalPRs) }}) being discounted due to being submitted

to an excluded repository.**



If we plot all pull/merge requests during Hacktoberfest by day, broken down by state, the impact

that excluded repositories had can be seen clearly, and also shows that there are significant spikes

at the start and end of Hacktoberfest as folks trying to cheat the system tend to do so as

Hacktoberfest launches and its on their mind, or when they get our reminder email that Hacktoberfest

is ending soon:



![Stacked area plot of PR/MRs by created at day and state](generated/prs_by_state_stacked.png)



Doughnut diagram of reported repositories by review state



For transparency, we can also take a look at the excluded repositories we processed for

Hacktoberfest {{= data.readme.year }}. A large part of this list was prior excluded repositories

from previous Hacktoberfest years which were persisted across to this year. However, a form was

available on the site for members of our community to report repositories that they felt did not

follow our values, with automation in place to process these reports and exclude repositories that

were repeatedly reported, as well as reports being reviewed by our team.



In total, Hacktoberfest {{= data.readme.year }} had {{= c(data.Repos.totalReposExcluded) }}

repositories that were actively excluded,

{{= p(data.Repos.totalReposExcluded / data.Repos.totalReposReported) }} of the total repositories

reported. Only {{= c(data.Repos.totalReposPermitted) }} repositories were permitted after having

been reported and subsequently reviewed by our team. Unfortunately,

{{= c(data.Repos.totalReposUnreviewed) }}

({{= p(data.Repos.totalReposUnreviewed / data.Repos.totalReposReported) }}) of the repositories that

were reported by the community were never reviewed by our team, and did not meet a threshold that

triggered any automation for exclusion.






## Wrapping up



Well, that's all the stats I've generated from the Hacktoberfest {{= data.readme.year }} raw data --

you can find the raw output of the stats generation script in the

[`generated/stats.txt`](generated/stats.txt) file, as well as all the graphics which are housed in

[`generated`](generated) directory.



If there is anything more you'd like to see/know, please feel free to reach out and ask, I'll be

more than happy to generate it if possible.



All the scripts used to generate these stats & graphics are contained in this repository, in the

[`src`](src) directory. I have some more information about this in the

[CONTRIBUTING.md](CONTRIBUTING.md) file, including a schema for the input data, however, the

Hacktoberfest {{= data.readme.year }} raw data, much like previous years' data, isn't public.



Author: [Matt Cowley](https://mattcowley.co.uk/) - If you notice any errors within this document

please let me know, and I will endeavour to correct them. 💙