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2.compare.py
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import os
import pandas as pd
from config.date import Ldate
path = "Version/"
data = []
fTASK = lambda x: tuple([int(i) for i in x.split(".")])
TASK = sorted(
[
i for i in os.listdir(path)
if "3." in i and os.path.exists(f"{path}{i}/py{i}.log")
], key=fTASK
)
print(TASK)
for t in TASK:
t1, t2, tdata = "", "", {}
with open(f"{path}{t}/py{t}.log") as f:
for i in f:
i = i.strip("\n")
if i.startswith("###"):
t1 = i.replace("###", "").replace(" ", "")
if i.startswith("Mean"):
t2 = i.replace("Mean +- std dev: ", "")
tdata[t1] = t2
t1, t2 = "", ""
tdata = pd.DataFrame(
[[_k, _v] for _k, _v in tdata.items()],
columns=["Task", t]
)
data.append(tdata)
sdata = pd.DataFrame()
for tdata in data:
if len(sdata) == 0:
sdata = tdata
else:
sdata = pd.merge(sdata, tdata, on="Task", how="outer")
def fchange(string):
if pd.isna(string):
return string
string = str(string).split("+-")[0]
result = -999999
if "sec" in string:
result = float(string.replace("sec", ""))*1000
elif "ms" in string:
result = float(string.replace("ms", ""))
elif "us" in string:
result = float(string.replace("us", ""))/1000
elif "ns" in string:
result = float(string.replace("ns", ""))/1000/1000
return round(result, 4)
def change(df):
_df = df[df["Task"] != "pprint_safe_repr"].copy()
for icol in TASK:
_df[icol] = _df[icol].apply(fchange)
return _df
cdata = change(sdata)
cdata0 = cdata.copy()
cdata.loc["SUM"] = [""] + [round(cdata0[icol].sum(), 4) for icol in TASK]
cdata.loc["AVG"] = [""] + [round(cdata0[icol].mean(), 4) for icol in TASK]
_max = max([cdata0[icol].sum() for icol in TASK])
cdata.loc["UP%"] = [""] + [f"{_max/cdata0[icol].sum():.4%}" for icol in TASK]
Lup = cdata[cdata.index == "UP%"].to_dict()
FIRST = """
### 0.Readme
#### (1) Python Versions
> https://www.python.org/downloads/
#### (2) Running Environment
* Docker gcc library/gcc
> ecs.u1-c1m2.large/aliyun Intel(R) Xeon(R) Platinum 2核(vCPU) 4 GiB Ubuntu 22.04 64位
#### (3) Test Software
* [Pyperformance](https://github.com/python/pyperformance)
"""
END = """
<div align=center>
[](https://gitee.com/IvanaXu/PythonVersions)
https://github.com/IvanaXu/PythonVersions
</div>
"""
with open("README.md", "w") as f:
f.write(FIRST)
f.write("### 1.Versions\n")
idf = pd.DataFrame(TASK, columns=["version"])
idf["date"] = idf["version"].apply(lambda x: Ldate.get(x, ""))
idf["UP%"] = idf["version"].apply(lambda x: Lup.get(x, {}).get("UP%", ""))
# TOP = 5
# idf["Rank"] = idf["UP%"].rank(ascending=False).apply(lambda x: max(TOP-int(x)+1, 0) * "🌹")
# idf["Rank"] = idf["UP%"].rank(ascending=True).apply(lambda x: int(x) * "+")
TOP = 1
print(idf)
idf["Progress"] = idf["UP%"].apply(lambda x: int((float(x[:-1]) - 99)/TOP) * ">")
idf["rank"] = idf["version"].apply(fTASK)
idf.sort_values("rank", inplace=True)
print(idf)
for i in idf[["version", "date", "UP%", "Progress"]].to_markdown(index=None):
f.write(i)
f.write("\n\n")
f.write("### 2.Details\n")
for i in sdata.fillna("/").to_markdown():
f.write(i)
f.write("\n\n")
f.write("### 3.Calculation(UNIT: ms)\n")
for i in cdata.fillna("/").to_markdown():
f.write(i)
f.write("\n\n")
f.write(END)