#-*-coding:utf-8-*-
#!/bin/pyton
import csv
import pandas as pd
import requests
import json
import datetime
upload_path='report_http_logs_es6.csv'
pd.set_option('display.max_colwidth', -1)
df = pd.read_csv(upload_path, sep='|',usecols=[1,2,3,4],skipinitialspace=True)
html_to_str = df.to_html(index=False,justify='center',col_space=50)
#print(html_to_str)
参数说明：
pd.set_option('display.max_colwidth', -1)：关闭最大列宽，防止截断
sep：分隔符
usecols：想要读取的列
skipinitialspace：忽略分隔符后的空格
col_space=50：最小列宽，但是好像没生效，没找到原因
justify='center'：列标题居中
index=False：关闭表格第一列的数字行号
待转换csv格式：
转换后的html
如果还需要做些css相关的优化，可以在生成html之后通过内联的方式来定义css，如下是个简单示例
html_string = '''
<html>
<head>
<title>HTML Pandas Dataframe with CSS</title>
<style type="text/css">
table.dataframe td {
text-align: right;
}
table.dataframe td[class="high_light"] {
color: red;
}
</style>
</head>
<body>
<p>点击链接查看近一个月的 elasticsearch 集群性能数据：</p>
''' + es_link_month_latency + es_link_month_tps_reader + es_link_month_tps_writer + es_link_month_error_rate + "<p>下表为今日凌晨时分 elasticsearch 集群性能数据</p>" + html_to_str + "</body></html>"
esrally报告指标140多项，如果需要高亮表格文字的话，由于pandas的to_html无法指定td的类型或者id，所以一种方法是通过替换字符串来改写html
如下：
#html高亮部分
html_string = re.sub(r'<td>Max Throughput</td>', r'<td class="high_light">Max Throughput</td>', html_string)
html_string = re.sub(r'<td>90th percentile latency</td>', r'<td class="high_light">90th percentile latency</td>', html_string)
html_string = re.sub(r'<td>error rate</td>', r'<td class="high_light">error rate</td>', html_string)
html_string = re.sub(r'<td>Cumulative indexing time of primary shards</td>', r'<td class="high_light">Cumulative indexing time of primary shards</td>', html_string)
html_string = re.sub(r'<td>Cumulative merge time of primary shards</td>', r'<td class="high_light">Cumulative merge time of primary shards</td>', html_string)
html_string = re.sub(r'<td>Cumulative merge count of primary shards</td>', r'<td class="high_light">Cumulative merge count of primary shards</td>', html_string)
html_string = re.sub(r'<td>Cumulative refresh time of primary shards</td>', r'<td class="high_light">Cumulative refresh time of primary shards</td>', html_string)
html_string = re.sub(r'<td>Cumulative refresh count of primary shards</td>', r'<td class="high_light">Cumulative refresh count of primary shards</td>', html_string)
html_string = re.sub(r'<td>Cumulative flush time of primary shards</td>', r'<td class="high_light">Cumulative flush time of primary shards</td>', html_string)
html_string = re.sub(r'<td>Cumulative flush count of primary shards</td>', r'<td class="high_light">Cumulative flush count of primary shards</td>', html_string)
html_string = re.sub(r'<td>Total Young Gen GC</td>', r'<td class="high_light">Total Young Gen GC</td>', html_string)
html_string = re.sub(r'<td>Total Old Gen GC</td>', r'<td class="high_light">Total Old Gen GC</td>', html_string)
最终效果：
参考：https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.read_csv.html