pypistats

Python interface to PyPI Stats API to get aggregate download statistics on Python packages on the Python Package Index without having to execute queries directly against Google BigQuery.

Data is available for the last 180 days. (For longer time periods, pypinfo can help, you'll need an API key and get free quota.)

Installation

From PyPI

bash python3 -m pip install --upgrade pypistats

From source

bash git clone https://github.com/hugovk/pypistats cd pypistats python3 -m pip install .

Example command-line use

Run pypistats with a subcommand (corresponding to PyPI Stats endpoints), then options for that subcommand.

Top-level help:

```console $ pypistats --help usage: pypistats [-h] [-V] {recent,overall,pythonmajor,pythonminor,system} ...

positional arguments: {recent,overall,pythonmajor,pythonminor,system}

options: -h, --help show this help message and exit -V, --version show program's version number and exit ```

Help for a subcommand:

```console $ pypistats recent --help usage: pypistats recent [-h] [-p {day,week,month}] [-f {html,json,pretty,md,markdown,rst,tsv}] [-j] [-v] package

Retrieve the aggregate download quantities for the last day/week/month

positional arguments: package

options: -h, --help show this help message and exit -p {day,week,month}, --period {day,week,month} -f {html,json,pretty,md,markdown,rst,tsv}, --format {html,json,pretty,md,markdown,rst,tsv} The format of output (default: pretty) -j, --json Shortcut for "-f json" (default: False) -v, --verbose Print debug messages to stderr (default: False) ```

Get recent downloads:

console $ pypistats recent pillow ┌───────────┬────────────┬────────────┐ │ last_day │ last_month │ last_week │ ├───────────┼────────────┼────────────┤ │ 3,419,597 │ 91,237,125 │ 21,259,217 │ └───────────┴────────────┴────────────┘

Help for another subcommand:

```console $ pypistats pythonminor --help usage: pypistats pythonminor [-h] [-V VERSION] [-f {html,json,pretty,md,markdown,rst,tsv}] [-j] [-sd yyyy-mm[-dd]|name] [-ed yyyy-mm[-dd]|name] [-m yyyy-mm|name] [-l] [-t] [-d] [--monthly] [-c {yes,no,auto}] [-v] package

Retrieve the aggregate daily download time series by Python minor version number

positional arguments: package

options: -h, --help show this help message and exit -V VERSION, --version VERSION eg. 2.7 or 3.6 (default: None) -f {html,json,pretty,md,markdown,rst,tsv}, --format {html,json,pretty,md,markdown,rst,tsv} The format of output (default: pretty) -j, --json Shortcut for "-f json" (default: False) -sd yyyy-mm[-dd]|name, --start-date yyyy-mm[-dd]|name Start date (default: None) -ed yyyy-mm[-dd]|name, --end-date yyyy-mm[-dd]|name End date (default: None) -m yyyy-mm|name, --month yyyy-mm|name Shortcut for -sd & -ed for a single month (default: None) -l, --last-month Shortcut for -sd & -ed for last month (default: False) -t, --this-month Shortcut for -sd for this month (default: False) -d, --daily Show daily downloads (default: False) --monthly Show monthly downloads (default: False) -c {yes,no,auto}, --color {yes,no,auto} Color terminal output (default: auto) -v, --verbose Print debug messages to stderr (default: False) ```

Get version downloads:

```console $ pypistats python_minor pillow --last-month ┌──────────┬─────────┬────────────┐ │ category │ percent │ downloads │ ├──────────┼─────────┼────────────┤ │ 3.8 │ 18.37% │ 16,161,117 │ │ 3.10 │ 17.47% │ 15,373,666 │ │ 3.7 │ 16.70% │ 14,691,371 │ │ 3.11 │ 15.49% │ 13,630,259 │ │ 3.9 │ 13.19% │ 11,605,389 │ │ 3.6 │ 9.68% │ 8,519,789 │ │ null │ 4.64% │ 4,085,994 │ │ 3.12 │ 3.26% │ 2,871,386 │ │ 2.7 │ 0.95% │ 837,638 │ │ 3.5 │ 0.25% │ 216,308 │ │ 3.13 │ 0.00% │ 2,830 │ │ 3.4 │ 0.00% │ 1,237 │ │ 3.3 │ 0.00% │ 109 │ │ 3.1 │ 0.00% │ 3 │ │ 3.2 │ 0.00% │ 2 │ │ Total │ │ 87,997,098 │ └──────────┴─────────┴────────────┘

Date range: 2024-02-01 - 2024-02-29 ```

You can format in Markdown, ready for pasting in GitHub issues and PRs:

| category | percent | downloads | | :------- | ------: | ---------: | | 3.8 | 18.37% | 16,161,117 | | 3.10 | 17.47% | 15,373,666 | | 3.7 | 16.70% | 14,691,371 | | 3.11 | 15.49% | 13,630,259 | | 3.9 | 13.19% | 11,605,389 | | 3.6 | 9.68% | 8,519,789 | | null | 4.64% | 4,085,994 | | 3.12 | 3.26% | 2,871,386 | | 2.7 | 0.95% | 837,638 | | 3.5 | 0.25% | 216,308 | | 3.13 | 0.00% | 2,830 | | 3.4 | 0.00% | 1,237 | | 3.3 | 0.00% | 109 | | 3.1 | 0.00% | 3 | | 3.2 | 0.00% | 2 | | Total | | 87,997,098 |

Date range: 2024-02-01 - 2024-02-29

These are equivalent (in May 2019):

sh pypistats python_major pip --last-month pypistats python_major pip --month april pypistats python_major pip --month apr pypistats python_major pip --month 2019-04

And:

sh pypistats python_major pip --start-date december --end-date january pypistats python_major pip --start-date dec --end-date jan pypistats python_major pip --start-date 2018-12 --end-date 2019-01

Example programmatic use

Return values are from the JSON responses documented in the API: https://pypistats.org/api/

```python import pypistats from pprint import pprint

Call the API

print(pypistats.recent("pillow")) print(pypistats.recent("pillow", "day", format="markdown")) print(pypistats.recent("pillow", "week", format="rst")) print(pypistats.recent("pillow", "month", format="html")) pprint(pypistats.recent("pillow", "week", format="json")) print(pypistats.recent("pillow", "day"))

print(pypistats.overall("pillow")) print(pypistats.overall("pillow", mirrors=True, format="markdown")) print(pypistats.overall("pillow", mirrors=False, format="rst")) print(pypistats.overall("pillow", mirrors=True, format="html")) pprint(pypistats.overall("pillow", mirrors=False, format="json"))

print(pypistats.pythonmajor("pillow")) print(pypistats.pythonmajor("pillow", version=2, format="markdown")) print(pypistats.pythonmajor("pillow", version=3, format="rst")) print(pypistats.pythonmajor("pillow", version="2", format="html")) pprint(pypistats.python_major("pillow", version="3", format="json"))

print(pypistats.pythonminor("pillow")) print(pypistats.pythonminor("pillow", version=2.7, format="markdown")) print(pypistats.pythonminor("pillow", version="2.7", format="rst")) print(pypistats.pythonminor("pillow", version=3.7, format="html")) pprint(pypistats.python_minor("pillow", version="3.7", format="json"))

print(pypistats.system("pillow")) print(pypistats.system("pillow", os="darwin", format="markdown")) print(pypistats.system("pillow", os="linux", format="rst")) print(pypistats.system("pillow", os="darwin", format="html")) pprint(pypistats.system("pillow", os="linux", format="json")) ```

NumPy and pandas

To use with either NumPy or pandas, make sure they are first installed, or:

bash pip install --upgrade "pypistats[numpy]" pip install --upgrade "pypistats[pandas]" pip install --upgrade "pypistats[numpy,pandas]"

Return data in a NumPy array for further processing:

```python import pypistats numpyarray = pypistats.overall("pyvista", total=True, format="numpy") print(type(numpyarray))

print(numpy_array)

[['with_mirrors' '2019-09-20' '2.23%' 1204]

['without_mirrors' '2019-09-20' '2.08%' 1122]

['with_mirrors' '2019-09-19' '0.92%' 496]

...

['with_mirrors' '2019-10-26' '0.02%' 13]

['without_mirrors' '2019-10-26' '0.02%' 12]

['Total' None None 54041]]

```

Or in a pandas DataFrame:

```python import pypistats pandasdataframe = pypistats.overall("pyvista", total=True, format="pandas") print(type(pandasdataframe))

print(pandas_dataframe)

category date percent downloads

0 with_mirrors 2019-09-20 2.23% 1204

1 without_mirrors 2019-09-20 2.08% 1122

2 with_mirrors 2019-09-19 0.92% 496

3 with_mirrors 2019-08-22 0.90% 489

4 without_mirrors 2019-09-19 0.86% 466

.. ... ... ... ...

354 without_mirrors 2019-11-03 0.03% 15

355 without_mirrors 2019-11-16 0.03% 15

356 with_mirrors 2019-10-26 0.02% 13

357 without_mirrors 2019-10-26 0.02% 12

358 Total None None 54041

[359 rows x 4 columns]

```

For example, create charts with pandas:

```python

Show overall downloads over time, excluding mirrors

import pypistats data = pypistats.overall("pillow", total=True, format="pandas") data = data.groupby("category").getgroup("withoutmirrors").sort_values("date")

chart = data.plot(x="date", y="downloads", figsize=(10, 2)) chart.figure.show() chart.figure.savefig("overall.png") # alternatively ```

```python

Show Python 3 downloads over time

import pypistats data = pypistats.pythonmajor("pillow", total=True, format="pandas") data = data.groupby("category").getgroup(3).sort_values("date")

chart = data.plot(x="date", y="downloads", figsize=(10, 2)) chart.figure.show() chart.figure.savefig("python3.png") # alternatively ```

See also

Related projects

• https://github.com/ofek/pypinfo
• https://github.com/scivision/pypistats-plots