Consolidated Download Statistics For Python Packages With pip-install - python

Is there a way to obtain statistics on how many times a package (every package) has been installed using pip-install or any other package manager?
This question came about when trying to determine the popularity of some python packages I was looking into using for a personal project - I am sure developers would find it useful to be able to obtain such statistics.

You can view the download statistics from the official PyPI data. This data is stored in BigQuery (see https://bigquery.cloud.google.com/dataset/the-psf:pypi)
But I developed a page to facilitate this information, take a look at http://pepy.tech/ :-)

You can get this statistics via vanity:
https://pypi.python.org/pypi/vanity

Related

How to see users of a python package?

I have made a python package named 'Panclus' but I do not know if anyone is using this package or not. Please tell me how to see how many people have installed my python package. Is it possible to get the name of users?
From here:
PyPI does not display download statistics for a number of reasons:
Inefficient to make work with a Content Distribution Network (CDN):
Download statistics change constantly. Including them in project
pages, which are heavily cached, would require invalidating the cache
more often, and reduce the overall effectiveness of the cache.
Highly inaccurate: A number of things prevent the download counts from
being accurate, some of which include:
pip’s download cache (lowers download counts)
Internal or unofficial mirrors (can both raise or lower download
counts)
Packages not hosted on PyPI (for comparisons sake)
Unofficial scripts or attempts at download count inflation (raises
download counts)
Known historical data quality issues (lowers download counts)
Not particularly useful: Just because a project has been downloaded a
lot doesn’t mean it’s good; Similarly just because a project hasn’t
been downloaded a lot doesn’t mean it’s bad!
Get more information about download statistics from this.

Importing freely available Quantopian data into my own local, Python script?

I have come across a data set that looks very relevant to what I need.
The data set is provided through the online platform Quantopian, where you impot it into their existing Python environment. Is it possible at all to import this same data set API from Quantopian into a local Python script?
pip install quantopian does not exist.
pip install quantopian-tools seems to be deprecated, and does not seem to provide access to the data libraries.
Quantopian employee here.
Unfortunately, we can't make the data available off of our platform -- it is part of our agreements with the firms that provide us the data that we will not distribute it off the site. Hopefully you can try out what you have in mind in a Jupyter notebook on our platform in combination with the other data we have integrated? quantopian.com/notebooks
Alternatively, you could reach out to the nice folks at PsychSignal: https://psychsignal.com/contact/

How to tell the amount of times a pypi package is downloaded by actual users?

I uploaded a python package to pypi and I would like to track how many "real" downloads does it have. Like, given that my package has, say, 1000 downloads (per day, week, month, doesn't matter), I would like to discard from that amount the number of downloads made from CI servers and so. I mean, I would like to discard downloads that are not from actual users.
Is there any way to accomplish this?
Thanks!
I could possibly be 7 years late, but there's now a website called pypistats that gives you how many downloads your PyPi package has.
You can use vanity:
To Install:
pip install vanity
To Run:
vanity name-of-package
Note: The Python Packaging Index is to be moved from the current PyPi site to Warehouse, so these stats may be slightly off during this migration. The Warehouse pre-production site can be found here.
Possible answer depending on your library's popularity...:
When your package makes it to the 360 most popular ones, it will get in this list If not, it is bellow that number... :)

Tips for interacting with debian based repositories

I am planning on writing a small program that interacts with a debian based repository - namely doing a partial mirror**. I am planning to write it in python.
What are some tips for working with the repository including already constructed 'wheels' (to save the invention of yet another one)?
Some issues I have identified
As it is going to be a partial mirror, I will need to regenerate the package lists (Release,Contents*, Packages.{bz2,gz}). (Maybe debian-installer can do it for me??)
How to get changes to package list (I already know that packages do not change, but that the lists only link to the latest file)?
** Already looked into apt-mirror and debmirror. Debmirror is the closest to what I want, however lacking in some features. If apt can deal with multiple releases and architectures then I will consider apt.
debian-installer doesn't generate repository metadata. For that, you want a tool like reprepro or mini-dinstall. They'll also handle the second point you raised.

Is there a Python version of CPAN?

So I've been using Perl for several years now and I'm starting to dabble a little in Python. Is there a sort of CPAN but for Python? What's the normal way to manage modules in Python? Any direction would be greatly appreciated. FWIW I use Linux so Windows-only solutions aren't really useful to me.
The repository formerly known as Cheese Shop.
PyPI
The Python Package Index is a repository of software for the Python programming language. There are currently 9140 packages here. To contact the PyPI admins, please use the Get help or Bug reports links.
Also, take a look at
SIG for Python Resource Cataloguing
This SIG exists in order to discuss and build a catalog of Python resources. The SIG charter is:
The Python Catalog SIG (Special Interest Group) aims at producing a master index of Python software and other resources. It will begin by figuring out what the requirements are, converging on a design for the data schema, and producing an implementation. ("Implementation" will almost certainly include mean a set of CGI scripts for browsing the catalog, and may also contain a standard library module for automatically fetching and installing modules, if the SIG decides that's a worthwhile feature.)
Check out Python eggs / easy_install

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