def test_subcommand_with_cache(self):
# Arrange
package = "pip"
mocked_url = "https://pypistats.org/api/packages/pip/overall"
mocked_response = """{
"data": [
{"category": "without_mirrors", "date": "2018-11-01", "downloads": 2295765}
],
"package": "pip",
"type": "overall_downloads"
}"""
expected_output = """
| category | downloads |
|-----------------|----------:|
| without_mirrors | 2,295,765 |
Date range: 2018-11-01 - 2018-11-01
"""
# Act
with requests_mock.Mocker() as m:
m.get(mocked_url, text=mocked_response)
# First time to save to cache
pypistats.overall(package)
# Second time to read from cache
output = pypistats.overall(package)
# Assert
assert output.strip() == expected_output.strip()
def test_overall_tabular_start_date(self):
# Arrange
package = "pip"
mocked_url = "https://pypistats.org/api/packages/pip/overall"
mocked_response = """{
"data": [
{"category": "without_mirrors", "date": "2018-11-01", "downloads": 2295765},
{"category": "without_mirrors", "date": "2018-11-02", "downloads": 2297591}
],
"package": "pip",
"type": "overall_downloads"
}"""
expected_output = """
| category | downloads |
|-----------------|----------:|
| without_mirrors | 2,297,591 |
"""
# Act
with requests_mock.Mocker() as m:
m.get(mocked_url, text=mocked_response)
output = pypistats.overall(package,
mirrors=False,
start_date="2018-11-02")
# Assert
self.assertEqual(output.strip(), expected_output.strip())
def get_weekly_downloads(package):
try:
data = pypistats.overall(package, total=False, format="pandas")
results = data[data.category != 'Total']
results['Date'] = pd.to_datetime(results['date'])
results = pd.DataFrame(
results.groupby(pd.Grouper(
key='Date', freq='W-SUN'))['downloads'].sum().reset_index())
results['Package'] = package
return results
except Exception as foo:
st.write("Invalid package", package, foo)
return pd.DataFrame()
def update(self, repo=None):
"""Update repo download file(s).
Description
-----------
Update the local stored file with daily downloads for the specified repos.
Parameters
----------
repo : list of Strings, (Default: None)
None : Take all available pypi repos for the username.
Returns
-------
None.
"""
if (repo is not None) and ('str' in str(type(repo))):
repo = [repo]
# Extract all repos
repos = self._get_repo_names_from_git()
if (repo is not None):
repos = repo
if not np.any(np.isin(repos, repo)):
raise ValueError('[pypiplot] >Error: repos [%s] does not exists or is private.' %(repo))
if self.verbose>=3: print('[pypiplot] >Start updating..')
for repo in repos:
try:
if self.verbose>=3: print('[pypiplot] >[%s]' %(repo))
status = True
df = pypistats.overall(repo, total=True, format="pandas")
df.dropna(inplace=True)
df['date'] = pd.to_datetime(df['date'], format='%Y-%m-%d')
df = df.sort_values("date")
df.reset_index(drop=True, inplace=True)
del df['percent']
# Merge with any on disk
pathname = os.path.join(self.savepath, repo + '.csv')
if os.path.isfile(pathname):
# Read repo from disk
df_disk = read_repo_counts_from_disk(pathname, self.sep)
# Merge with latest counts
df, status = add_new_counts_to_repo(df, df_disk, repo, verbose=self.verbose)
# Write to disk
if status:
if self.verbose>=3: print('[pypiplot] >Write to disk: [%s]' %(pathname))
df.to_csv(pathname, index=False, sep=self.sep)
except:
if self.verbose>=1: print('[pypiplot] >Skip [%s] because could not retrieve statistics from Pypi.' %(repo))
def overall(args): # pragma: no cover
if args.mirrors in ["with", "without"]:
args.mirrors = args.mirrors == "with"
print(
pypistats.overall(
args.package,
mirrors=args.mirrors,
start_date=args.start_date,
end_date=args.end_date,
format=args.format,
total="daily" if args.daily else
("monthly" if args.monthly else "all"),
))
def test_format_numpy(self):
# Arrange
package = "pip"
mocked_url = "https://pypistats.org/api/packages/pip/overall"
mocked_response = SAMPLE_RESPONSE_OVERALL
expected_output = "[['without_mirrors' 4593356]]"
# Act
with requests_mock.Mocker() as m:
m.get(mocked_url, text=mocked_response)
output = pypistats.overall(package, format="numpy")
# Assert
assert isinstance(output, numpy.ndarray)
assert str(output) == expected_output
def overall(args: argparse.Namespace) -> None: # pragma: no cover
if args.mirrors in ["with", "without"]:
args.mirrors = args.mirrors == "with"
print(
pypistats.overall(
args.package,
mirrors=args.mirrors,
start_date=args.start_date,
end_date=args.end_date,
format=args.format,
total="daily" if args.daily else
("monthly" if args.monthly else "all"),
color="no", # Coloured percentages not really helpful here
verbose=args.verbose,
))
def fetch_and_plot(name):
"""A little helper method to do it all and make it pretty."""
data = pypistats.overall(name, total=True, format="pandas")
data = data.groupby("category").get_group("without_mirrors").sort_values(
"date")
data.plot(x="date", y="downloads", figsize=(15, 5), marker="o")
plt.xticks(
rotation=45,
horizontalalignment="right",
fontweight="light",
fontsize="medium",
)
plt.title("Downloads for {}".format(name))
plt.tight_layout()
return plt.show()
def test_format_numpy(self) -> None:
# Arrange
package = "pip"
mocked_url = "https://pypistats.org/api/packages/pip/overall"
mocked_response = SAMPLE_RESPONSE_OVERALL
expected_output = """
[['with_mirrors' '100.00%' 3587357]
['without_mirrors' '99.22%' 3559451]
['Total' None 3587357]]
"""
# Act
respx.get(mocked_url).respond(content=mocked_response)
output = pypistats.overall(package, format="numpy")
# Assert
assert isinstance(output, numpy.ndarray)
assert str(output).strip() == expected_output.strip()
def test_format_pandas(self):
# Arrange
package = "pip"
mocked_url = "https://pypistats.org/api/packages/pip/overall"
mocked_response = SAMPLE_RESPONSE_OVERALL
expected_output = """
category downloads
0 without_mirrors 4593356
"""
# Act
with requests_mock.Mocker() as m:
m.get(mocked_url, text=mocked_response)
output = pypistats.overall(package, format="pandas")
# Assert
assert isinstance(output, pandas.DataFrame)
assert str(output).strip() == expected_output.strip()
def test_format_pandas(self) -> None:
# Arrange
package = "pip"
mocked_url = "https://pypistats.org/api/packages/pip/overall"
mocked_response = SAMPLE_RESPONSE_OVERALL
expected_output = """
category percent downloads
0 with_mirrors 100.00% 3587357
1 without_mirrors 99.22% 3559451
2 Total None 3587357
"""
# Act
respx.get(mocked_url).respond(content=mocked_response)
output = pypistats.overall(package, format="pandas")
# Assert
assert isinstance(output, pandas.DataFrame)
assert str(output).strip() == expected_output.strip()
def pypi_downloads(package="name_of_the_package_on_pypi"):
"""Access the downloads history from pypi
Examples
---------
>>> import popularipy
>>> data = popularipy.pypi_downloads("neurokit2")
>>> data.plot(x="Date")
"""
data = pypistats.overall(package, total=True, format="pandas")
# process
data = data.groupby("date").sum().sort_values("date").reset_index()
data = data.rename(columns={"downloads": "Downloads"})
data["Trend"] = nk.fit_loess(data["Downloads"])
data["Date"] = pd.to_datetime(data["date"]).dt.strftime('%d %b %Y')
data = data.drop("date", axis=1)
return data
def main():
parser = argparse.ArgumentParser()
parser.add_argument('--packages', nargs='+', required=True)
parsed = parser.parse_args()
metrics = []
for package in parsed.packages:
pypi_data = json.loads(pypistats.recent(package,
format='json'))['data']
metrics.append(make_metric(package, 'last_day', pypi_data['last_day']))
metrics.append(
make_metric(package, 'last_week', pypi_data['last_week']))
metrics.append(
make_metric(package, 'last_month', pypi_data['last_month']))
overall_data = json.loads(pypistats.overall(package,
format='json'))['data']
total_downloads = sum(val['downloads'] for val in overall_data)
metrics.append(make_metric(package, 'all_time', total_downloads))
print(json.dumps(metrics))
def test_overall_tabular_end_date(self):
# Arrange
package = "pip"
mocked_url = "https://pypistats.org/api/packages/pip/overall"
mocked_response = SAMPLE_RESPONSE_OVERALL
expected_output = """
| category | downloads |
|-----------------|----------:|
| without_mirrors | 2,295,765 |
Date range: 2018-11-01 - 2018-11-01
"""
# Act
with requests_mock.Mocker() as m:
m.get(mocked_url, text=mocked_response)
output = pypistats.overall(package,
mirrors=False,
end_date="2018-11-01")
# Assert
assert output.strip() == expected_output.strip()
def test_overall_tabular_end_date(self) -> None:
# Arrange
package = "pip"
mocked_url = "https://pypistats.org/api/packages/pip/overall?&mirrors=false"
mocked_response = SAMPLE_RESPONSE_OVERALL
expected_output = """
| category | percent | downloads |
|:----------------|--------:|----------:|
| with_mirrors | 100.00% | 2,100,139 |
| without_mirrors | 99.21% | 2,083,472 |
| Total | | 2,100,139 |
Date range: 2020-05-01 - 2020-05-01
"""
# Act
respx.get(mocked_url).respond(content=mocked_response)
output = pypistats.overall(package,
mirrors=False,
end_date="2020-05-01")
# Assert
assert output.strip() == expected_output.strip()
def test_overall_tabular_start_date(self):
# Arrange
package = "pip"
mocked_url = "https://pypistats.org/api/packages/pip/overall?&mirrors=false"
mocked_response = SAMPLE_RESPONSE_OVERALL
expected_output = """
| category | percent | downloads |
| --------------- | ------: | --------: |
| with_mirrors | 100.00% | 1,487,218 |
| without_mirrors | 99.24% | 1,475,979 |
| Total | | 1,487,218 |
Date range: 2020-05-02 - 2020-05-02
"""
# Act
respx.get(mocked_url).respond(content=mocked_response)
output = pypistats.overall(package,
mirrors=False,
start_date="2020-05-02")
# Assert
assert output.strip() == expected_output.strip()
database = 'prody'
mirror = False
base_date = "2011-10-01"
base_number = 2135029
# set up time elapse from yesterday to today
today = date.today()
str_today = today.strftime('%Y-%m-%d')
yesterday = date.today() - timedelta(days=1)
str_yesterday = yesterday.strftime('%Y-%m-%d')
# retrieve download counts for yesterday
ret = pis.overall(package,
mirrors=mirror,
start_date=str_yesterday,
end_date=str_today,
format='numpy')
n_downloads = ret[0][-1]
# connecting to the database
connection = sql.connect(host=host,
user=user,
passwd=passwd,
database=database)
crsr = connection.cursor()
# create the main table (if not already exists) in the database
sql_cmd = 'CREATE TABLE IF NOT EXISTS downloads (date DATE PRIMARY KEY, number INTEGER);'
crsr.execute(sql_cmd)
def get_stats(package):
return loads(pypistats.overall(package, mirrors=True, format="json"))
import os
import pypistats
import pandas as pd
cwd = os.getcwd()
trackpath = f'{cwd}/doc/source/tracking/pypistats/'
downloadfn = "downloads_data.csv"
sysdownloadfn = "sys_downloads_data.csv"
downloads = pypistats.overall("icepyx",
format="pandas").drop(columns=['percent'])
downloads = downloads[downloads.category != "Total"]
# try:
exist_downloads = pd.read_csv(trackpath +
downloadfn) # .drop(columns=['percent'])
# exist_downloads = exist_downloads[exist_downloads.category != "Total"]
dl_data = downloads.merge(exist_downloads,
how='outer',
on=['category', 'date', 'downloads']).reindex()
# except:
# dl_data = downloads
dl_data.to_csv(trackpath + downloadfn, index=False)
sysdownloads = pypistats.system("icepyx",
format="pandas").drop(columns=['percent'])
sysdownloads = sysdownloads[sysdownloads.category != "Total"]
# try:
exist_sysdownloads = pd.read_csv(trackpath +
