<p>我会选择<a href="https://pandas.pydata.org/pandas-docs/version/1.0.0/reference/api/pandas.read_csv.html#pandas.read_csv" rel="nofollow noreferrer">pandas</a>,这是一个了不起的第三方库,提供高性能、易于使用的数据结构和数据分析工具,来解析您提到的生成文件:</p>
<blockquote>
<p>example.txt</p>
</blockquote>
<pre><code># z phi phi1 Massless
-16.0000000 0.0000000 9.9901854997e-01 1.0910677716e-19
-16.0000000 0.0245437 9.9871759471e-01 1.6545142956e-05
-16.0000000 0.0490874 9.9781493216e-01 3.3051500271e-05
-16.0000000 0.0736311 9.9631097893e-01 4.9477653557e-05
-16.0000000 0.0981748 9.9420658732e-01 6.5784269579e-05
</code></pre>
<blockquote>
<p>test.py</p>
</blockquote>
<pre><code>#!/usr/bin/env python
# -*- coding: utf-8 -*-
import pandas as pd
if __name__ == "__main__":
df = pd.read_csv("test.txt", sep=r'\s+', skiprows=1, names=["z", "phi", "phi1", "Massless",])
print(df)
</code></pre>
<p>按如下方式运行命令后:</p>
<pre><code>python test.py
</code></pre>
<p>我得到了以下结果:</p>
<pre><code> z phi phi1 Massless
0 -16.0 0.000000 0.999019 1.091068e-19
1 -16.0 0.024544 0.998718 1.654514e-05
2 -16.0 0.049087 0.997815 3.305150e-05
3 -16.0 0.073631 0.996311 4.947765e-05
4 -16.0 0.098175 0.994207 6.578427e-05
</code></pre>