csv_table = list()
# Create the header:
builds = spec.cpta["data"].values()[0]
+ job_name = spec.cpta["data"].keys()[0]
builds_lst = [str(build) for build in range(builds[0], builds[-1] + 1)]
header = "Build Number:," + ",".join(builds_lst) + '\n'
csv_table.append(header)
idx += 1
# Generate the chart:
- period_name = "Daily" if period == 1 else \
- "Weekly" if period < 20 else "Monthly"
- chart["layout"]["title"] = chart["title"].format(period=period_name)
+ chart["layout"]["xaxis"]["title"] = \
+ chart["layout"]["xaxis"]["title"].format(job=job_name)
_generate_chart(traces,
chart["layout"],
file_name="{0}-{1}-{2}{3}".format(
file_handler.writelines(csv_table)
txt_table = None
- with open("{0}.csv".format("cpta-trending"), 'rb') as csv_file:
+ with open("{0}.csv".format(file_name), 'rb') as csv_file:
csv_content = csv.reader(csv_file, delimiter=',', quotechar='"')
header = True
for row in csv_content:
pass
txt_table.add_row(row)
txt_table.align["Build Number:"] = "l"
- with open("{0}.txt".format("cpta-trending"), "w") as txt_file:
+ with open("{0}.txt".format(file_name), "w") as txt_file:
txt_file.write(str(txt_table))
# Evaluate result: