drought/export/views.py

# -*- coding: utf-8 -*-
import random
import string

from PyPDF2.pdf import BytesIO
from xhtml2pdf import pisa
from django.template.loader import get_template
from django.http import HttpResponse, FileResponse
from dashboard.models import Spi, GDP, SpiJC, Population, Landuse
from reportlab.pdfgen.canvas import Canvas
from reportlab.pdfbase import pdfmetrics
from reportlab.pdfbase.cidfonts import UnicodeCIDFont
pdfmetrics.registerFont(UnicodeCIDFont('STSong-Light'))
from reportlab.pdfbase.ttfonts import TTFont
pdfmetrics.registerFont(TTFont('msyh', 'msyh.ttf'))
from reportlab.lib.styles import getSampleStyleSheet
from reportlab.lib import colors
from reportlab.platypus import SimpleDocTemplate, Paragraph, Spacer,Image,Table,TableStyle
import time
from reportlab.graphics.shapes import Drawing
from reportlab.graphics.charts.barcharts import VerticalBarChart
from reportlab.graphics.charts.linecharts import HorizontalLineChart

def render(path: str, params: dict):
    template = get_template(path)
    html = template.render(params)
    response = BytesIO()
    pdf = pisa.pisaDocument(BytesIO(html.encode("UTF-8")), response)
    if not pdf.err:
        return HttpResponse(response.getvalue(), content_type='application/pdf')
    else:
        return HttpResponse("Error Rendering PDF", status=400)


def pdf_spi(request):
    story = []
    stylesheet = getSampleStyleSheet()
    normalStyle = stylesheet['Normal']
    curr_date = time.strftime("%Y-%m-%d", time.localtime())
    name_date = time.strftime("%Y-%m-%d-%H-%M-%S", time.localtime())
    salt = ''.join(random.sample(string.ascii_letters + string.digits, 8))
    spis = Spi.objects.filter().order_by('-year')[:100]
    rpt_title = '<para autoLeading="off" fontSize=15 align=center><b><font face="msyh">宝鸡市气象历史数据%s</font></b><br/><br/><br/></para>' % (
        curr_date)
    story.append(Paragraph(rpt_title, normalStyle))
    text = '''<para autoLeading="off" fontSize=8><font face="msyh" >数据描述：</font><br/>
        <font face="msyh" color=royalblue>1.名称</font><br/><font face="msyh" fontsize=7>宝鸡地区格点气象数据</font><br/>
        <font face="msyh" color=royalblue>2.要素</font><br/>
        <font face="msyh" fontsize=7>月平均降水(mm)，月平均气温(℃)
        </font><br/>
        <font face="msyh" color=royalblue>3.时间</font><br/><font face="msyh" fontsize=7>1979-2015年
        </font><br/>
        <font face="msyh" color=royalblue>4.数据</font><br/>
        <font face="msyh" fontsize=7>宝鸡地区179个网格的格点数据，分辨率为10公里
        </font><br/></para>'''
    story.append(Paragraph(text, normalStyle))
    drawing = Drawing(400, 200)
    data = [(1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12)]
    bc = VerticalBarChart()
    bc.x = 50
    bc.y = 50
    bc.height = 125
    bc.width = 300
    bc.data = data
    bc.strokeColor = colors.black

    bc.valueAxis._valueMin = 0
    bc.valueAxis._valueMax = 50
    bc.valueAxis._valueStep = 10

    bc.categoryAxis.labels.boxAnchor = 'ne'
    bc.categoryAxis.labels.dx = 8
    bc.categoryAxis.labels.dy = -2
    bc.categoryAxis.labels.angle = 30
    bc.categoryAxis.categoryNames = ['1', '2', '3', '4', '5', '6', '7', '8', '9', '10', '11', '12']

    bc.groupSpacing = 10
    bc.barSpacing = 2.5

    drawing.add(bc)
    story.append(drawing)

    drawingline = Drawing(400, 200)
    data = [(13.2222, 5, 20, 22, 37, 45, 19, 4, 11, 11, 11, 11),
            (5, 20, 46, 38, 23, 21, 6, 14, 22, 22, 22, 22)
            ]

    lc = HorizontalLineChart()
    lc.x = 50
    lc.y = 50
    lc.height = 125
    lc.width = 300
    lc.data = data
    lc.joinedLines = 1
    catNames = '1 2 3 4 5 6 7 8 9 10 11 12'.split(' ')
    lc.categoryAxis.categoryNames = catNames
    lc.categoryAxis.labels.boxAnchor = 'n'
    lc.valueAxis.valueMin = 0
    lc.valueAxis.valueMax = 60
    lc.valueAxis.valueStep = 15
    lc.lines[0].strokeWidth = 2
    lc.lines[1].strokeWidth = 1.5
    drawingline.add(lc)
    story.append(drawingline)


    # img = Image('D:/spi.png')
    # img.drawHeight = 200
    # img.drawWidth = 400
    # story.append(img)
    text = '<para autoLeading="off" fontSize=9><br/><br/><br/><b><font face="msyh">数据报表:数据依次为区站号, 经度, 纬度, 年份,月份,月平均降水,月平均温度,</font></b><br/></para>'
    story.append(Paragraph(text, normalStyle))
    for spi in spis:
        component_data= [
                         [spi.code, spi.longitude, spi.latitude, spi.year, spi.month, spi.mean_precipitation,
                          spi.mean_temperature]
                     ]
    #创建表格对象，并设定各列宽度
        component_table = Table(component_data, colWidths=[50,50,50, 30,30, 90, 90])
    #添加表格样式
        component_table.setStyle(TableStyle([
            ('FONTNAME',(0,0),(-1,-1),'msyh'),#字体
            ('FONTSIZE',(0,0),(-1,-1),6),#字体大小
            # ('SPAN',(0,0),(3,0)),#合并第一行前三列
            ('BACKGROUND',(0,0),(-1,0), colors.lightskyblue),#设置第一行背景颜色
            # ('SPAN',(-1,0),(-2,0)), #合并第一行后两列
            ('ALIGN',(-1,0),(-2,0),'RIGHT'),#对齐
            ('VALIGN',(-1,0),(-2,0),'MIDDLE'), #对齐
            ('LINEBEFORE',(0,0),(0,-1),0.1,colors.grey),#设置表格左边线颜色为灰色，线宽为0.1
            ('TEXTCOLOR',(0,1),(-2,-1),colors.royalblue),#设置表格内文字颜色
            ('GRID',(0,0),(-1,-1),0.5,colors.red),#设置表格框线为红色，线宽为0.5
        ]))
        story.append(component_table)
    doc = SimpleDocTemplate('/home/g214/pdf/'+name_date+salt+'.pdf')
    doc.build(story)
    file = open('/home/g214/pdf/'+name_date+salt+'.pdf', 'rb')
    response = FileResponse(file)
    response['Content-Type'] = 'application/octet-stream'
    # response['Content-Disposition'] = 'attachment'
    response['Content-Disposition'] = 'attachment; filename=spi.pdf'
    return response


def pdf_gdp(request):
    gdps = GDP.objects.all().order_by('-date')[:100]
    return render('export/export_to_pdf_for_gdp.html', {'gdps': gdps})


def pdf_spi_jc(request):
    spi_jc = SpiJC.objects.all().order_by('-year')[:100]
    return render('export/export_to_pdf_for_spi_jc.html', {'spi_jc': spi_jc})


def pdf_population(request):
    pops = Population.objects.all().order_by('-date')[:100]
    return render('export/export_to_pdf_for_population.html', {'pops': pops})


def pdf_landuse(request):
    landuses = Landuse.objects.all().order_by('-date')[:100]
    return render('export/export_to_pdf_for_landuse.html', {'landuses': landuses})