An online Parser for Solidity language Analysis
Requires Node >= v11.3.0
![Screenshot 2020-05-27 at 11 21 01](https://user-images.githubusercontent.com/1194257/83001552-3657d900-a00c-11ea-89de-d6ab3413760b.png)
![Screenshot 2020-05-27 at 11 20 54](https://user-images.githubusercontent.com/1194257/83001557-37890600-a00c-11ea-8d06-119386ecd137.png)
Web tool
https://github.com/aphd/paso/settings/pages
Website deployment
npm install
npm start
CLI tool
node --experimental-modules src/services/client.mjs --d=src/fixtures/smart-contracts/ --o /tmp/metrics.csv
Data analysis
cd src/fixtures
python
import pandas as pd
df = pd.read_csv('src/fixtures/metrics.csv', \
parse_dates=['submission_date'], index_col='submission_date')
df[['mapping', 'total_lines', 'interfaces', 'libraries']] \
.resample('Y').mean() \
.transform(lambda x: x/x.max())
import pandas as pd
import matplotlib.pyplot as plt
%matplotlib inline
import pylab as plot
df = pd.read_csv('src/fixtures/metrics.csv', \
parse_dates=['submission_date'], index_col='submission_date')
df.index = df.index.strftime('%Y')
df = df.loc[df.index > '2015']
ax = df[['interfaces', 'libraries', 'contracts']] \
.groupby(df.index).mean() \
.plot(kind = 'bar', figsize=(40,20))
for p in ax.patches:
ax.annotate(str(round(p.get_height(),2)), (p.get_x() * 1.005, p.get_height() * 1.005), fontsize=40)
import pandas as pd
df = pd.read_csv('src/fixtures/metrics.csv', \
parse_dates=['submission_date'], index_col='submission_date')
df.index = df.index.strftime('%Y')
df = df.loc[df.index > '2016']
df[['mapping', 'total_lines', 'interfaces', 'libraries', 'modifiers']] \
.groupby(df.index).mean().apply(lambda x: x / max(x)) \
.plot(kind = 'bar', figsize=(40,20))
import pandas as pd
df = pd.read_csv('src/fixtures/metrics.csv')
df.replace({'submission_date': r'^(201\d).*$'}, {'submission_date': r'\1'}, \
regex=True, inplace=True )
df.loc[df.submission_date > '2016', \
['submission_date', 'mapping', 'total_lines', 'interfaces', 'libraries', 'modifiers']] \
.groupby(df['submission_date']).mean() \
.apply(lambda x: x / max(x)) \
.plot(kind = 'bar', figsize=(40,20))
print(df.describe().transpose().round(1).to_latex())
Data analysis - plots
import pandas as pd
df = pd.read_csv('./metrics.csv')
udf = df.drop_duplicates(subset=['address'])
%matplotlib inline
udf[udf['version'].str.contains("0.5")==True]['functions'][udf['functions']<100].plot.kde()
df[df['version'].str.contains("0.4")==True].hist(column='functions', bins=20, range=(0, 100))
- This project was bootstrapped with Create React App.
- This project is using a solidity parser built on top of a ANTLR4 grammar.