Add additional text cells
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popcorn.py
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popcorn.py
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@ -16,7 +16,12 @@ with app.setup:
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@app.cell(hide_code=True)
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@app.cell(hide_code=True)
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def _():
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def _():
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mo.md(r"""# Void Linux 'Popcorn' package repository stat analysis""")
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mo.md(r"""# Void Linux 'Popcorn' package repository stat analysis
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This notebook analyses the daily package repository statistics files,
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colloquially known as 'popcorn' files, that are generated by the Void Linux
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package manager `xbps` and uploaded by users who have opted in to share.
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""")
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return
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return
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@ -102,6 +107,10 @@ def _():
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between 2019 and the start of 2021, the amount of different stuff
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between 2019 and the start of 2021, the amount of different stuff
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downloaded grew rapidly, with the pace picking up again starting 2023.
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downloaded grew rapidly, with the pace picking up again starting 2023.
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There are a few outliers with a size of 0 kB, which we will remove from the
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data. There are also a few days where the modification date of the file
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does not correspond to the represented statistical date.
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"""
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"""
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)
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)
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return
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return
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@ -127,6 +136,23 @@ def _():
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return
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return
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@app.cell(hide_code=True)
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def _():
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mo.md(
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r"""
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## Download statistics
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Now that we have an idea of how the overall interest in the distribution
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has changed over time, let's look at the actual download statistics.
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The popcorn files contain two main pieces of information: the number of
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unique installs (i.e. unique machines downloading packages) and the number
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of downloads per package. We will look at both of these in turn.
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"""
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)
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return
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@app.cell
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@app.cell
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def _(df_pkg_lazy: pl.LazyFrame):
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def _(df_pkg_lazy: pl.LazyFrame):
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def _():
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def _():
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@ -299,6 +325,12 @@ def _(sizes_df):
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return
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return
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@app.cell
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def _(df_lazy):
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kernel_df = df_lazy.select("date", pl.col("Kernels").struct.unnest())
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kernel_df
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# further ideas:
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# further ideas:
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#
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#
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# - daily download habits:
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# - daily download habits:
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