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Pattern and date range removal
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@cdolfi @JamesKunstle
cdolfi authored and JamesKunstle committed Apr 10, 2024
1 parent 179d4db commit c34915c
Showing 1 changed file with 23 additions and 90 deletions.
113 changes: 23 additions & 90 deletions 8Knot/pages/contributors/visualizations/contrib_importance_over_time.py
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Original file line number Diff line number Diff line change
Expand Up @@ -62,29 +62,6 @@
),
dbc.Form(
[
dbc.Row(
[
dbc.Label(
"Threshold:",
html_for=f"threshold-{PAGE}-{VIZ_ID}",
width="auto",
),
dbc.Col(
[
dcc.Slider(
id=f"threshold-{PAGE}-{VIZ_ID}",
min=10,
max=95,
value=50,
marks={i: f"{i}%" for i in range(10, 100, 5)},
),
],
className="me-2",
width=10,
),
],
align="center",
),
dbc.Row(
[
dbc.Label(
Expand Down Expand Up @@ -137,55 +114,35 @@
dbc.Row(
[
dbc.Label(
"Filter Out Contributors with Keyword(s) in Login:",
html_for=f"patterns-{PAGE}-{VIZ_ID}",
"Threshold:",
html_for=f"threshold-{PAGE}-{VIZ_ID}",
width="auto",
),
dbc.Col(
[
dmc.MultiSelect(
id=f"patterns-{PAGE}-{VIZ_ID}",
placeholder="Bot filter values",
data=[
{"value": "bot", "label": "bot"},
],
classNames={"values": "dmc-multiselect-custom"},
creatable=True,
searchable=True,
dcc.Slider(
id=f"threshold-{PAGE}-{VIZ_ID}",
min=10,
max=95,
value=50,
marks={i: f"{i}%" for i in range(10, 100, 5)},
),
],
className="me-2",
width=9,
),
],
align="center",
),
dbc.Row(
[
dbc.Col(
dcc.DatePickerRange(
id=f"date-picker-range-{PAGE}-{VIZ_ID}",
min_date_allowed=dt.date(2005, 1, 1),
max_date_allowed=dt.date.today(),
initial_visible_month=dt.date(dt.date.today().year, 1, 1),
clearable=True,
dbc.Button(
"About Graph",
id=f"popover-target-{PAGE}-{VIZ_ID}",
color="secondary",
size="sm",
),
width="auto",
),
dbc.Col(
[
dbc.Button(
"About Graph",
id=f"popover-target-{PAGE}-{VIZ_ID}",
color="secondary",
size="sm",
),
],
width="auto",
style={"paddingTop": ".5em"},
),
],
align="center",
justify="between",
),
]
),
Expand Down Expand Up @@ -223,33 +180,21 @@ def graph_title(window_width):
Output(f"check-alert-{PAGE}-{VIZ_ID}", "is_open"),
[
Input("repo-choices", "data"),
Input(f"patterns-{PAGE}-{VIZ_ID}", "value"),
Input(f"threshold-{PAGE}-{VIZ_ID}", "value"),
Input(f"window-width-{PAGE}-{VIZ_ID}", "value"),
Input(f"step-size-{PAGE}-{VIZ_ID}", "value"),
Input(f"date-picker-range-{PAGE}-{VIZ_ID}", "start_date"),
Input(f"date-picker-range-{PAGE}-{VIZ_ID}", "end_date"),
Input("bot-switch", "value"),
],
background=True,
)
def create_contrib_prolificacy_over_time_graph(
repolist,
patterns,
threshold,
window_width,
step_size,
start_date,
end_date,
bot_switch,
):
def create_contrib_prolificacy_over_time_graph(repolist, threshold, window_width, step_size, bot_switch):
# wait for data to asynchronously download and become available.
while not_cached := cf.get_uncached(func_name=ctq.__name__, repolist=repolist):
logging.warning(f"{VIZ_ID}- WAITING ON DATA TO BECOME AVAILABLE")
time.sleep(0.5)

logging.warning(f"{VIZ_ID} - START")
start = time.perf_counter()
logging.warning(f"{VIZ_ID} - START")

# GET ALL DATA FROM POSTGRES CACHE
df = cf.retrieve_from_cache(
Expand All @@ -263,10 +208,6 @@ def create_contrib_prolificacy_over_time_graph(
if bot_switch:
df = df[~df["cntrb_id"].isin(app.bots_list)]

# data ready.
start = time.perf_counter()
logging.warning(f"{VIZ_ID}- START")

# test if there is data
if df.empty:
logging.warning(f"{VIZ_ID} - NO DATA AVAILABLE")
Expand All @@ -276,34 +217,26 @@ def create_contrib_prolificacy_over_time_graph(
if step_size > window_width:
return dash.no_update, True

df_final = process_data(df, patterns, threshold, window_width, step_size, start_date, end_date)
df = process_data(df, threshold, window_width, step_size)

fig = create_figure(df_final, threshold, step_size)
fig = create_figure(df, threshold, step_size)

logging.warning(f"{VIZ_ID} - END - {time.perf_counter() - start}")
return fig, False


def process_data(df, patterns, threshold, window_width, step_size, start_date, end_date):
def process_data(df, threshold, window_width, step_size):
# convert to datetime objects rather than strings
df["created_at"] = pd.to_datetime(df["created_at"], utc=True)

# order values chronologically by created_at date
df = df.sort_values(by="created_at", ascending=True)

# if the start_date and/or the end date is not specified set them to the beginning and most recent created_at date
if start_date is None:
start_date = df["created_at"].min()
if end_date is None:
end_date = df["created_at"].max()

if patterns:
# remove rows where Login column value contains the substring 'bot'
patterns_mask = df["login"].str.contains("|".join(patterns), na=False)
df = df[~patterns_mask]
# get start and end date from created column
start_date = df["created_at"].min()
end_date = df["created_at"].max()

# threshold is an integer value eg. 10, 20,..., 90 since dcc.Slider only accepts integers as values
# divide by 100 to convert it to a decimal representation of a percentage eg. 0.10, 0.20,..., 0.90
# convert percent to its decimal representation
threshold = threshold / 100

# create bins with a size equivalent to the the step size starting from the start date up to the end date
Expand Down

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