Removed superfluous iter() and fixed instances where sorted() had to compare None and int.
- Legacy-Id: 16352
This commit is contained in:
Henrik Levkowetz
parent
942fc7f907
commit
f13887de7c
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@ -86,7 +86,7 @@ def add_url_to_choices(choices, url_builder):
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def put_into_bin(value, bin_size):
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if value is None:
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return (value, value)
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return (0, '')
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v = (value // bin_size) * bin_size
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return (v, "{} - {}".format(v, v + bin_size - 1))
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@ -114,7 +114,7 @@ def add_labeled_top_series_from_bins(chart_data, bins, limit):
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xs = list(sorted(xs))
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sorted_bins = sorted(iter(aggregated_bins.items()), key=lambda t: len(t[1]), reverse=True)
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sorted_bins = sorted(aggregated_bins.items(), key=lambda t: len(t[1]), reverse=True)
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top = [ label for label, names in list(sorted_bins)[:limit]]
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for label in top:
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@ -238,8 +238,8 @@ def document_stats(request, stats_type=None):
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total_docs = docalias_qs.values_list("docs__name").distinct().count()
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def generate_canonical_names(docalias_qs):
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for doc_id, ts in itertools.groupby(docalias_qs.order_by("docs__name"), lambda t: t[0]):
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def generate_canonical_names(values):
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for doc_id, ts in itertools.groupby(values.order_by("docs__name"), lambda a: a[0]):
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chosen = None
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for t in ts:
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if chosen is None:
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@ -249,7 +249,6 @@ def document_stats(request, stats_type=None):
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chosen = t
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elif t[1].startswith("draft") and not chosen[1].startswith("rfc"):
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chosen = t
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yield chosen
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if stats_type == "authors":
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@ -258,10 +257,10 @@ def document_stats(request, stats_type=None):
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bins = defaultdict(set)
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for name, canonical_name, author_count in generate_canonical_names(docalias_qs.values_list("docs__name", "name").annotate(Count("docs__documentauthor"))):
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bins[author_count].add(canonical_name)
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bins[author_count or 0].add(canonical_name)
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series_data = []
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for author_count, names in sorted(iter(bins.items()), key=lambda t: t[0]):
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for author_count, names in sorted(bins.items(), key=lambda t: t[0]):
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percentage = len(names) * 100.0 / (total_docs or 1)
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series_data.append((author_count, percentage))
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table_data.append((author_count, percentage, len(names), list(names)[:names_limit]))
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@ -274,10 +273,10 @@ def document_stats(request, stats_type=None):
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bins = defaultdict(set)
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for name, canonical_name, pages in generate_canonical_names(docalias_qs.values_list("docs__name", "name", "docs__pages")):
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bins[pages].add(canonical_name)
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bins[pages or 0].add(canonical_name)
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series_data = []
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for pages, names in sorted(iter(bins.items()), key=lambda t: t[0]):
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for pages, names in sorted(bins.items(), key=lambda t: t[0]):
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percentage = len(names) * 100.0 / (total_docs or 1)
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if pages is not None:
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series_data.append((pages, len(names)))
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@ -296,7 +295,7 @@ def document_stats(request, stats_type=None):
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bins[put_into_bin(words, bin_size)].add(canonical_name)
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series_data = []
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for (value, words), names in sorted(iter(bins.items()), key=lambda t: t[0][0]):
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for (value, words), names in sorted(bins.items(), key=lambda t: t[0][0]):
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percentage = len(names) * 100.0 / (total_docs or 1)
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if words is not None:
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series_data.append((value, len(names)))
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@ -349,7 +348,7 @@ def document_stats(request, stats_type=None):
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bins[ext.upper()].add(canonical_name)
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series_data = []
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for fmt, names in sorted(iter(bins.items()), key=lambda t: t[0]):
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for fmt, names in sorted(bins.items(), key=lambda t: t[0]):
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percentage = len(names) * 100.0 / (total_docs or 1)
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series_data.append((fmt, len(names)))
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@ -366,7 +365,7 @@ def document_stats(request, stats_type=None):
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bins[formal_language_name].add(canonical_name)
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series_data = []
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for formal_language, names in sorted(iter(bins.items()), key=lambda t: t[0]):
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for formal_language, names in sorted(bins.items(), key=lambda t: t[0]):
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percentage = len(names) * 100.0 / (total_docs or 1)
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if formal_language is not None:
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series_data.append((formal_language, len(names)))
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@ -412,12 +411,12 @@ def document_stats(request, stats_type=None):
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person_qs = Person.objects.filter(person_filters)
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for name, document_count in person_qs.values_list("name").annotate(Count("documentauthor")):
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bins[document_count].add(name)
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bins[document_count or 0].add(name)
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total_persons = count_bins(bins)
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series_data = []
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for document_count, names in sorted(iter(bins.items()), key=lambda t: t[0]):
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for document_count, names in sorted(bins.items(), key=lambda t: t[0]):
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percentage = len(names) * 100.0 / (total_persons or 1)
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series_data.append((document_count, percentage))
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plain_names = [ plain_name(n) for n in names ]
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@ -450,7 +449,7 @@ def document_stats(request, stats_type=None):
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total_persons = count_bins(bins)
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series_data = []
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for affiliation, names in sorted(iter(bins.items()), key=lambda t: t[0].lower()):
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for affiliation, names in sorted(bins.items(), key=lambda t: t[0].lower()):
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percentage = len(names) * 100.0 / (total_persons or 1)
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if affiliation:
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series_data.append((affiliation, len(names)))
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@ -462,7 +461,7 @@ def document_stats(request, stats_type=None):
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chart_data.append({ "data": series_data })
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for alias, name in sorted(iter(aliases.items()), key=lambda t: t[1]):
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for alias, name in sorted(aliases.items(), key=lambda t: t[1]):
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alias_data.append((name, alias))
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elif stats_type == "author/country":
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@ -499,7 +498,7 @@ def document_stats(request, stats_type=None):
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total_persons = count_bins(bins)
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series_data = []
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for country, names in sorted(iter(bins.items()), key=lambda t: t[0].lower()):
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for country, names in sorted(bins.items(), key=lambda t: t[0].lower()):
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percentage = len(names) * 100.0 / (total_persons or 1)
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if country:
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series_data.append((country, len(names)))
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@ -541,7 +540,7 @@ def document_stats(request, stats_type=None):
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total_persons = count_bins(bins)
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series_data = []
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for continent, names in sorted(iter(bins.items()), key=lambda t: t[0].lower()):
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for continent, names in sorted(bins.items(), key=lambda t: t[0].lower()):
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percentage = len(names) * 100.0 / (total_persons or 1)
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if continent:
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series_data.append((continent, len(names)))
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@ -563,12 +562,12 @@ def document_stats(request, stats_type=None):
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person_qs = Person.objects.filter(person_filters)
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for name, citations in person_qs.values_list("name").annotate(Count("documentauthor__document__docalias__relateddocument")):
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bins[citations].add(name)
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bins[citations or 0].add(name)
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total_persons = count_bins(bins)
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series_data = []
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for citations, names in sorted(iter(bins.items()), key=lambda t: t[0], reverse=True):
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for citations, names in sorted(bins.items(), key=lambda t: t[0], reverse=True):
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percentage = len(names) * 100.0 / (total_persons or 1)
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series_data.append((citations, percentage))
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plain_names = [ plain_name(n) for n in names ]
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@ -589,12 +588,12 @@ def document_stats(request, stats_type=None):
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values = person_qs.values_list("name", "documentauthor__document").annotate(Count("documentauthor__document__docalias__relateddocument"))
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for name, ts in itertools.groupby(values.order_by("name"), key=lambda t: t[0]):
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h_index = compute_hirsch_index([citations for _, document, citations in ts])
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bins[h_index].add(name)
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bins[h_index or 0].add(name)
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total_persons = count_bins(bins)
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series_data = []
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for citations, names in sorted(iter(bins.items()), key=lambda t: t[0], reverse=True):
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for citations, names in sorted(bins.items(), key=lambda t: t[0], reverse=True):
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percentage = len(names) * 100.0 / (total_persons or 1)
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series_data.append((citations, percentage))
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plain_names = [ plain_name(n) for n in names ]
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@ -835,7 +834,7 @@ def meeting_stats(request, num=None, stats_type=None):
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total_attendees = count_bins(bins)
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series_data = []
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for country, names in sorted(iter(bins.items()), key=lambda t: t[0].lower()):
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for country, names in sorted(bins.items(), key=lambda t: t[0].lower()):
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percentage = len(names) * 100.0 / (total_attendees or 1)
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if country:
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series_data.append((country, len(names)))
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@ -869,7 +868,7 @@ def meeting_stats(request, num=None, stats_type=None):
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total_attendees = count_bins(bins)
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series_data = []
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for continent, names in sorted(iter(bins.items()), key=lambda t: t[0].lower()):
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for continent, names in sorted(bins.items(), key=lambda t: t[0].lower()):
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percentage = len(names) * 100.0 / (total_attendees or 1)
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if continent:
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series_data.append((continent, len(names)))
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