def visualize()

in ailab/benchmark/views.py [0:0]

• 112 lines of code
• 29 McCabe index (conditional complexity)

def visualize(request):
    # Get columns included from user-specified checkbox list
    columns_sel = (
        []
        if request.GET.get("selection_form") is None
        else json.loads(request.GET.get("selection_form"))
    )
    include_column_set = set()
    graph_type = ""
    rank_column = ""
    for column in columns_sel:
        if column["name"] == "columns":
            include_column_set.add(column["value"])
        if column["name"] == "graph-type-dropdown":
            graph_type = column["value"]
        if column["name"] == "rank-column-dropdown":
            rank_column = column["value"]
    if len(include_column_set) == 0:
        include_column_set.add("p50")
        include_column_set.add("type")
    # Filter data base on request
    filters = (
        {}
        if request.GET.get("filters") is None
        else json.loads(request.GET.get("filters"))
    )
    if len(filters) == 0 or "valid" not in filters or not filters["valid"]:
        filters = {
            "condition": "AND",
            "rules": [{"id": "type", "operator": "equal", "value": "NET"}],
        }
    result_q = construct_q(filters)
    qs = BenchmarkResult.objects.filter(result_q)
    # Build table with specified columns
    table = ResultTable(qs)
    available_columns = []
    exclude_column_list = []
    for name, _ in table.base_columns.items():
        if name != "time":
            available_columns.append(name)
            if name not in include_column_set:
                exclude_column_list.append(name)
    table.exclude = tuple(exclude_column_list)

    RequestConfig(request, paginate={"per_page": 25}).configure(table)

    data = {}

    # Build graph to display
    if graph_type == "bar-graph":
        labels = [str(i) for i in range(10)]

        # Construct data to display
        sort_attr = request.GET.get("sort")
        if sort_attr is None:
            if rank_column != "":
                sort_attr = "-" + rank_column
            else:
                sort_attr = "p50"
        else:
            rank_column = sort_attr
            if rank_column.startswith("-"):
                rank_column = rank_column[1:]
        column = sort_attr[1:] if sort_attr.startswith("-") else sort_attr
        sorted_qs = qs.order_by(sort_attr)[:10]
        labels = [o.type for o in sorted_qs]
        chartdata = {"x": labels}
        vals = [getattr(o, column) for o in sorted_qs]

        chartdata["name1"] = column
        chartdata["y1"] = vals

        # Chart info for NVD3
        charttype = "discreteBarChart"
        chartcontainer = "linechart_container"  # container name
        data = {
            "charttype": charttype,
            "chartdata": chartdata,
            "chartcontainer": chartcontainer,
            "extra": {
                "x_is_date": False,
                "tag_script_js": True,
                "jquery_on_ready": False,
            },
        }

    else:
        labels = [o.time * 1000 for o in qs]
        chartdata = {"x": labels}

        # Construct data to display
        for column, i in zip(include_column_set, range(len(include_column_set))):
            if column not in PLOTABLE_COL_SET:
                continue

            index = i + 1
            vals = [getattr(o, column) for o in qs]

            chartdata["name{}".format(index)] = column
            chartdata["y{}".format(index)] = vals

        # Chart info for NVD3
        charttype = "lineChart"
        chartcontainer = "linechart_container"  # container name
        data = {
            "charttype": charttype,
            "chartdata": chartdata,
            "chartcontainer": chartcontainer,
            "extra": {
                "x_is_date": True,
                "tag_script_js": True,
                "jquery_on_ready": False,
                "x_axis_format": "%b %d %H:%m",
            },
        }

    data["table"] = table
    data["available_columns"] = zip(*[iter(available_columns)] * COL_PER_ROW)

    # Pass selection states to display
    data["filter_rules"] = json.dumps(filters)
    data["graph_type"] = graph_type
    data["rank_column"] = rank_column
    data["selected_columns"] = include_column_set

    if request.is_ajax():
        rendered_graph = render_to_string("graph_view.html", data, request)
        rendered_table = render_to_string("table_view.html", data, request)
        response = {
            "graph": rendered_graph,
            "table": rendered_table,
        }
        return HttpResponse(json.dumps(response))
    rendered = render_to_string("result_visualization.html", data, request)
    return HttpResponse(rendered)