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reword new faq

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crflynn
2018-11-03 11:26:46 -04:00
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pypistats/templates/faqs.html
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@@ -14,7 +14,7 @@
When is the website data updated?
</h3>
<p>
The data update begins at 01:00:00 UTC and should take less than 10 minutes.
The data update begins at 01:00:00 UTC and should take about 10 minutes.
</p>
<h3>
Why are there so many more downloads after July 26, 2018?
@@ -32,44 +32,48 @@
<p>
The cumulative download counts consider only the download records which are not from a known set of PyPI mirror
applications, namely <code>bandersnatch</code>, <code>z3c.pypimirror</code>, <code>Artifactory</code>, and
<code>devpi</code>. In other words, the cumulative download counts take the sum of the downloads from the <i>Without_Mirrors</i>
dataset from the chart.
<code>devpi</code>. In other words, the cumulative download counts take the sum of the downloads from the
<i>Without_Mirrors</i> dataset from the chart.
</p>
<h3>
What is the difference between <i>Without_Mirrors</i> and <i>With_Mirrors</i>?
What is the difference between <i>Without_Mirrors</i> and <i>With_Mirrors</i> downloads?
</h3>
<p>
The <i>With_Mirrors</i> and <i>Without_Mirrors</i> are not mutually exclusive sets of download counts like the
other segmentations provided. In fact, the <i>Without_Mirrors</i> downloads are a subset of the downloads in
<i>With_Mirrors</i>.
The <b>With_Mirrors</b> and <b>Without_Mirrors</b> downloads are not mutually exclusive sets of download counts
like the other segmentations provided. In fact, the <b>Without_Mirrors</b> downloads are a subset of the
downloads in <b>With_Mirrors</b>.
</p>
<p>
Some entities will create a mirror, or clone, of the PyPI repository using a tool like <code>bandersnatch</code>
for the sake of security or availability. This means that their mirror repository regularly syncs with PyPI by
downloading all of the Python packages available. Those downloads are recorded by PyPI with <code>bandersnatch</code>
as the user-agent. pypistats.org filters downloads from known mirrors from the version and system segmentations on
the website. You will see also that on days in which you release a new version of your package there will be many
more downloads from mirrors, as active mirrors will sync with PyPI by downloading those new releases.
Some entities will create a mirror, or clone, of the PyPI repository using a tool like <a
href="{{ url_for('general.package_page', package='bandersnatch') }}">bandersnatch</a>
for the sake of security or availability. This means that their mirror repository regularly syncs with PyPI by
downloading all of the Python packages available (and versions thereof) that it does not already have. Those
downloads are recorded by PyPI with <code>bandersnatch</code> as the user-agent. You will see also that on days
in which you release a new version of your package there will be many more downloads from mirrors, as active
mirrors will sync with PyPI by downloading those new releases.
</p>
<p>
The existence of mirrors means that the downloads provided by PyPI and BigQuery add uncertainty to the actual
usage of Python packages. One might expect that mirrors will mask end-user downloads for more commonly used
packages while simultaneously inflating the download counts of less common ones. We can't really be sure because
the mirrors don't report subsequent downloads back to PyPI.
pypistats.org filters downloads from known mirrors from the version and system segmentations on the website.
Downloads by mirrors are intentionally excluded from download breakdowns because they do not
represent end-users of the software. Instead, they serve as an alternative provider to <i>other</i> end-users on
a separate (sometimes private) network.
</p>
<p>
Downloads by mirrors are intentionally excluded from download breakdowns on pypistats.org because they do not
represent end-users of the software. Instead, they serve as an alternative provider to other end-users on a
separate (sometimes private) network.
The existence of mirrors means that the downloads provided by PyPI and BigQuery come with some uncertainty with
respect to the actual aggregate usage of Python packages. One might expect that mirrors will mask end-user
downloads for more commonly used packages while simultaneously inflating the download counts of less common
ones. This uncertainty is difficult to quantify because the mirrors don't report subsequent downloads back to
PyPI.
</p>
<p>
We can, however, assume that PyPI serves a significant proportion of the Python community's packaging downloads.
Hopefully significant enough that the quantities provided here are relevant to package maintainers and
representative of their users. There are other distributors like Conda which also serve python packages, but
their download data is not available like PyPI's as far as I'm aware, and thus are not incorporated in this website.
One can, however, assume that PyPI serves a significant proportion of the Python community's packaging
downloads. Hopefully significant enough that the quantities provided here are representative of their users and
relevant to package maintainers. There are other distributors, like Conda, which also serve python packages,
but their download data is currently not publicly available at the event level like PyPI's, and thus are not
incorporated into the metrics on this website.
</p>
<h3>
Why disregard mirrors from aggregated data?
Why disregard mirrors from aggregate data?
</h3>
<p>
The intent of disregarding mirrors is to provide metrics that reflect end-user download aggregation.
@@ -79,7 +83,7 @@
</h3>
<p>
Downloads from CI/CD tools are included in all metrics. There is currently no easy way to attribute downloads to
deployment tools.
build/deployment tools.
</p>
{% endblock %}