Relies on Arcas and Matplotlib to plot the evolution of the availability of open access publications through a few APIs using an arbitrary set of publications returned by each API.

openacces_check.py

"""
This script is heavily inspired by the example provided by the developers of Arcas:
https://github.com/ArcasProject/ArcasExamples/blob/initial_commits/scripts/scraping_num_articles.py
"""
import arcas
import pandas as pd
import matplotlib.pyplot as plt

keywords = ["composite", "carbon", "fiber"]
num_collect = 10
max_num = 201

dfs = []
for p in [arcas.Nature, arcas.Arxiv, arcas.Springer]:
    print(p)
    api = p()
    for key in keywords:
        start = 1
        switch = True
        while start < max_num and switch is True:
            parameters = api.parameters_fix(title=key, records=num_collect,
                                            abstract=key, start=start)

            url = api.create_url_search(parameters)

            request = api.make_request(url)
            root = api.get_root(request)
            raw_articles = api.parse(root)

            try:
                for art in raw_articles:
                    article = api.to_dataframe(art)
                    dfs.append(article)

            except:
                switch = False

            start += 10
            

df = pd.concat(dfs, ignore_index=True)
df = df.sort_values("date")

x = []
y = []
for an in df.date.unique():
    tdf = df[df.date == an]
    open_access_count = tdf.loc[tdf.open_access == True, 'open_access'].count()
    x.append(an)
    y.append(open_access_count)

fig, ax = plt.subplots()
plt.bar(x, y)
plt.xlim(1990, 2020)
plt.ylabel('# publications')
plt.title('Open Access publications per year')

plt.show()