def create_graph(filepaths):
"""
Prepare the `index.html` template.
"""
graphs = []
if isinstance(filepaths, str):
filepaths = [filepaths]
for path in filepaths:
contributions = parser.parse_file(path)
graph = {
"data":
gridify_contributions(contributions),
"cell_class":
_cell_class(list(contributions.values())),
"longest_streak":
statistics.longest_streak(
[key for key, val in contributions.items() if val > 0]),
"current_streak":
statistics.current_streak(
[key for key, val in contributions.items() if val > 0]),
"sum":
sum(contributions.values()),
"repo_name":
ntpath.basename(path)
}
graph["last_date"] = (
[""] + sorted([key for key, v in contributions.items() if v]))[-1]
graphs.append(graph)
env = Environment(loader=PackageLoader('render_html', 'templates'))
env.filters['tooltip'] = tooltip_text
env.filters['display_date'] = dateutils.display_date
env.filters['elapsed_time'] = dateutils.elapsed_time
template = env.get_template("index.html")
weekdays = dateutils.weekday_initials()
for idx in [0, 2, 4, 6]:
weekdays[idx] = ""
months = [
cell.date.strftime("%b")
for cell in gridify_contributions(contributions)[0]
]
months = filter_months(months)
return template.render(graphs=graphs,
today=dateutils.today(),
start=dateutils.start(),
weekdays=weekdays,
months=months)
def insert_overwrite_history():
engine = create_engine(
f"postgresql://{config['db_username']}:{config['db_password']}@{config['db_host']}:{config['db_port']}/{config['db_name']}"
)
df = get_p2p_overall_dataframe(all_dates_since_last_month(today()))
df.to_sql("p2p_migration",
engine,
if_exists="replace",
index=False,
method="multi")
def class_label(cell):
if cell.date > dateutils.today() or cell.date < dateutils.start():
return "empty"
elif cell.contributions == 0:
return "grad0"
elif cell.contributions <= quartiles[1]:
return "grad1"
elif cell.contributions <= quartiles[2]:
return "grad2"
elif cell.contributions <= quartiles[3]:
return "grad3"
else:
return "grad4"
def current_streak(dates):
"""
Given a list of datetime.date objects, return today's date (if present)
and all/any preceding consecutive dates.
"""
streak = []
current_date = dateutils.today()
while current_date in dates:
streak.append(current_date)
current_date = dateutils.previous_day(current_date)
return sorted(streak)
def current_streak(dates):
"""
Given a list of datetime.date objects, return today's date (if present)
and all/any preceding consecutive dates.
"""
streak = []
current_date = dateutils.today()
while current_date in dates:
streak.append(current_date)
current_date = dateutils.previous_day(current_date)
return sorted(streak)
def gridify_contributions(contributions):
"""
The contributions graph has seven rows (one for each day of the week).
It spans a year. Given a dict of date/value pairs, rearrange these results
into seven rows of "cells", where each cell records a date and a value.
"""
start = dateutils.start()
today = dateutils.today()
graph_entries = []
# The first row is a Sunday, so go back to the last Sunday before the start
if start.weekday() == 6:
first_date = start
else:
first_date = start - datetime.timedelta(start.weekday() + 1 % 7)
next_date = first_date
first_row_dates = [first_date]
while (next_date <= today) and (next_date + datetime.timedelta(7) <=
today):
next_date += datetime.timedelta(7)
first_row_dates.append(next_date)
# Now get contribution counts for each of these dates, and save the row
first_row = [
GridCell(date, contributions[date]) for date in first_row_dates
]
graph_entries.append(first_row)
# For each subsequent day of the week, use the first row as a model: add
# the appropriate number of days and count the contributions
for i in range(1, 7):
row_dates = [day + datetime.timedelta(i) for day in first_row_dates]
next_row = [GridCell(date, contributions[date]) for date in row_dates]
graph_entries.append(next_row)
return graph_entries