2021/3/3
Caozhenhui
parent
d719e95ab0
commit
25a96729ae
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@ -30,7 +30,6 @@ def export(report,
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if report is None:
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return None
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####################################################################################################################
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# Step 2: Generate excel file from the report data
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####################################################################################################################
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@ -211,7 +210,7 @@ def generate_excel(report,
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# table_data
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for i, value in enumerate(category):
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row = i*2 + 8
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row = i * 2 + 8
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ws['B' + str(row)].font = name_font
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ws['B' + str(row)].alignment = c_c_alignment
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ws['B' + str(row)] = reporting_period_data['names'][i] + " (" + reporting_period_data['units'][i] + "/H )"
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@ -358,14 +357,14 @@ def generate_excel(report,
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# row_st == row_statistical analysis table
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row_sat = 12 + 3 * ca_len
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ws['B' + str(row_sat+row_title)].font = title_font
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ws['B' + str(row_sat+row_title)] = name + ' 详细数据'
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ws['B' + str(row_sat + row_title)].font = title_font
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ws['B' + str(row_sat + row_title)] = name + ' 详细数据'
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# table_title
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ws['B' + str(row_sat+1+row_title)].fill = table_fill
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ws['B' + str(row_sat+1+row_title)].font = name_font
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ws['B' + str(row_sat+1+row_title)].alignment = c_c_alignment
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ws['B' + str(row_sat+1+row_title)] = "日期时间"
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ws['B' + str(row_sat+1+row_title)].border = f_border
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ws['B' + str(row_sat + 1 + row_title)].fill = table_fill
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ws['B' + str(row_sat + 1 + row_title)].font = name_font
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ws['B' + str(row_sat + 1 + row_title)].alignment = c_c_alignment
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ws['B' + str(row_sat + 1 + row_title)] = "日期时间"
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ws['B' + str(row_sat + 1 + row_title)].border = f_border
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for i in range(0, ca_len):
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col_average = chr(ord('C') + i)
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@ -392,27 +391,25 @@ def generate_excel(report,
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ws['B' + str(rows)].border = f_border
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for index in range(0, ca_len):
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col_average = chr(ord('C') + index * 2)
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col_maximum = chr(ord('C') + index * 2 + 1)
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ws[col_average + str(rows)].font = name_font
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ws[col_average + str(rows)].alignment = c_c_alignment
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ws[col_average + str(rows)] = reporting_period_data['sub_averages'][index][i] \
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if reporting_period_data['sub_maximums'][index] is not None else ''
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if reporting_period_data['sub_maximums'][index] is not None else ''
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ws[col_average + str(rows)].number_format = '0.00'
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ws[col_average + str(rows)].border = f_border
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ws[col_maximum + str(rows)].font = name_font
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ws[col_maximum + str(rows)].alignment = c_c_alignment
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ws[col_maximum + str(rows)] = reporting_period_data['sub_maximums'][index][i] \
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if reporting_period_data['sub_maximums'][index] is not None else ''
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if reporting_period_data['sub_maximums'][index] is not None else ''
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ws[col_maximum + str(rows)].number_format = '0.00'
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ws[col_maximum + str(rows)].border = f_border
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# LineChart
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for i in range(0, ca_len):
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lc = LineChart()
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lc.title = "报告期 最大负荷"
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lc.style = 10
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@ -7,6 +7,7 @@ from core import utilities
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from decimal import Decimal
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import excelexporters.shopfloorload
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class Reporting:
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@staticmethod
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def __init__():
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@ -66,7 +67,7 @@ class Reporting:
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try:
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base_start_datetime_utc = datetime.strptime(base_start_datetime_local,
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'%Y-%m-%dT%H:%M:%S').replace(tzinfo=timezone.utc) - \
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timedelta(minutes=timezone_offset)
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timedelta(minutes=timezone_offset)
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except ValueError:
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raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST',
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description="API.INVALID_BASE_PERIOD_START_DATETIME")
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@ -77,7 +78,7 @@ class Reporting:
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try:
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base_end_datetime_utc = datetime.strptime(base_end_datetime_local,
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'%Y-%m-%dT%H:%M:%S').replace(tzinfo=timezone.utc) - \
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timedelta(minutes=timezone_offset)
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timedelta(minutes=timezone_offset)
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except ValueError:
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raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST',
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description="API.INVALID_BASE_PERIOD_END_DATETIME")
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@ -95,7 +96,7 @@ class Reporting:
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try:
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reporting_start_datetime_utc = datetime.strptime(reporting_start_datetime_local,
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'%Y-%m-%dT%H:%M:%S').replace(tzinfo=timezone.utc) - \
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timedelta(minutes=timezone_offset)
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timedelta(minutes=timezone_offset)
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except ValueError:
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raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST',
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description="API.INVALID_REPORTING_PERIOD_START_DATETIME")
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@ -108,7 +109,7 @@ class Reporting:
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try:
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reporting_end_datetime_utc = datetime.strptime(reporting_end_datetime_local,
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'%Y-%m-%dT%H:%M:%S').replace(tzinfo=timezone.utc) - \
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timedelta(minutes=timezone_offset)
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timedelta(minutes=timezone_offset)
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except ValueError:
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raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST',
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description="API.INVALID_REPORTING_PERIOD_END_DATETIME")
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@ -278,10 +279,10 @@ class Reporting:
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period_type)
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base[energy_category_id]['factor'] = \
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(base[energy_category_id]['average'] / base[energy_category_id]['maximum']
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if (base[energy_category_id]['average'] is not None and
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base[energy_category_id]['maximum'] is not None and
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base[energy_category_id]['maximum'] > Decimal(0.0))
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else None)
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if (base[energy_category_id]['average'] is not None and
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base[energy_category_id]['maximum'] is not None and
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base[energy_category_id]['maximum'] > Decimal(0.0))
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else None)
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for row_shopfloor_periodically in rows_shopfloor_periodically:
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current_datetime_local = row_shopfloor_periodically[0].replace(tzinfo=timezone.utc) + \
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@ -511,11 +512,11 @@ class Reporting:
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result['reporting_period']['sub_maximums'].append(reporting[energy_category_id]['sub_maximums'])
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result['reporting_period']['averages'].append(reporting[energy_category_id]['average'])
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result['reporting_period']['averages_per_unit_area'].append(
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reporting[energy_category_id]['average'] / shopfloor['area']
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if reporting[energy_category_id]['average'] is not None and
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shopfloor['area'] is not None and
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shopfloor['area'] > Decimal(0.0)
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else None)
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reporting[energy_category_id]['average'] / shopfloor['area']
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if reporting[energy_category_id]['average'] is not None and
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shopfloor['area'] is not None and
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shopfloor['area'] > Decimal(0.0)
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else None)
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result['reporting_period']['averages_increment_rate'].append(
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(reporting[energy_category_id]['average'] - base[energy_category_id]['average']) /
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base[energy_category_id]['average'] if (base[energy_category_id]['average'] is not None and
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@ -548,8 +549,8 @@ class Reporting:
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# export result to Excel file and then encode the file to base64 string
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result['excel_bytes_base64'] = excelexporters.shopfloorload.export(result,
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shopfloor['name'],
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reporting_start_datetime_local,
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reporting_end_datetime_local,
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period_type)
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shopfloor['name'],
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reporting_start_datetime_local,
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reporting_end_datetime_local,
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period_type)
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resp.body = json.dumps(result)
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