Analyzing Cpython release patternsEDA Python mailing listDefining Community vibrancyCharacterizing open source software bursty patterns for the cpython repoLit. review on burstiness and toxicityExploring CPython commit history
What is the relationship between open source practices and software releases?
chosen_lib.filter(d => d.tag === '2.0' && d.is_toxic == 'Toxic')
// raw_data = FileAttachment("allLibs_to_plot@6.csv").csv({typed:true})
// cpython = FileAttachment("cpython_to_plot@7.csv").csv({typed:true})
chosen_lib = tidy(
cpython,
mutate({
is_toxic_new_score: d => +d.is_toxic_new_score,
// is_toxic: d => d.is_toxic === "True" ? "Toxic" : "Not Toxic",
is_toxic: d => d.is_toxic_new_score >= form2.tog_D ? "Toxic" : "Not Toxic",
cumlines_tag: d => +d.cumlines_tag,
abs_lines_changed: d => +d.abs_lines_changed,
insertions: d => +d.insertions,
deletions: d => +d.deletions,
tot_lines_tag: d => +d.tot_ines_tag,
pct_completion_tag: d=> +d.pct_completion_tag,
diff_by_release_s: d=>+d.diff_by_release_s,
diff_prev_row_tag_auth_sec: d=>+d.diff_prev_row_tag_auth_sec,
Day: d => parseTime(d.Day)
}
)
)
parseTime = d3.utcParse("%Y-%m-%d");
chosen_lib_long = tidy(chosen_lib,
select(['Day', 'yearMonth', 'insertions', 'deletions', 'abs_lines_changed']),
pivotLonger({
cols: ['insertions', 'deletions', 'abs_lines_changed'],
namesTo: 'contrib_type',
valuesTo: 'val',
}), filter(d => d.contrib_type !== 'abs_lines_changed'))
chosen_lib_long_toxic = tidy(chosen_lib,
select(['Day', 'is_toxic']),
pivotLonger({
cols: ['is_toxic'],
namesTo: 'type',
valuesTo: 'val',
}), filter(d => d.contrib_type !== 'abs_lines_changed'))
min_x = d3.min(chosen_lib.map(d => d.Day))
max_x = d3.max(chosen_lib.map(d => d.Day))
import {tidy, mutate, groupBy, filter, count, arrange, cumsum, mutateWithSummary,
sum, summarize, leftJoin, desc, sliceHead,distinct, pivotLonger, select,
n, max, mean, deviation, slice} from "@pbeshai/tidyjs"
import {Plot} from "@mkfreeman/plot-tooltip"
// Load the Temporal API using a Polyfill
Temporal = {
const TemporalLib = await require("@js-temporal/polyfill@0.3.0")
return TemporalLib.Temporal
}
import {brushFilterX} from "@observablehq/brush-filter-x"
Purpose-built for displays of data
Observable is your go-to platform for exploring data and creating expressive data visualizations. Use reactive JavaScript notebooks for prototyping and a collaborative canvas for visual data exploration and dashboard creation.
