PyPi does not allow duplicate file names -- this makes lots of sense,
because you really don't want people to go to PyPi one day and grab a file,
and then go there another day, grab a file with exactly the same name, and
have it be a different file.
We are all too human, and make mistakes when doing a release. All to often
someone pushed a broken file up to PyPi, often realizes it pretty quickly
-- before anyone has a chance to even download it (or only the dev team as,
In fact, I was in a sprint last summer, and we decided to push our package
up to PyPi -- granted, we were all careless amateurish noobs, but we ended
up making I think 4! minor version bumps because we had done something
stupid in the sdist.
Also -- the latest numpy release got caught in this, too:
* We ran into a problem with pipy not allowing reuse of filenames and a
resulting proliferation of *.*.*.postN releases. Not only were the names
getting out of hand, some packages were unable to work with the postN
So -- I propose that PyPi allow projects to replace existing files if they
REALLY REALLY want to.
You should have to jump through all sorts of hoops, and make it really
clear that it is a BAD IDEA in the general case, but it'd be good to have
it be possible.
After all -- PyPi does not take on responsibility for anything else about
what's in those packages, and Python itself is all about "we're all
consenting adults here"
I suppose we could even put in some heuristics about how long the file as
been there, how many times it's been downloaded, etc.
Just a thought.....I really hate systems that don't let me roll back
mistakes, even when I discover them almost immediately...
Christopher Barker, Ph.D.
Emergency Response Division
NOAA/NOS/OR&R (206) 526-6959 voice
7600 Sand Point Way NE (206) 526-6329 fax
Seattle, WA 98115 (206) 526-6317 main reception
I've got two projects: mynamespace.myprojectA and mynamespace.myprojectB
myprojectB depends on myprojectA. I'm using setuptools 0.6c8 to manage both
Both projects are registered using 'setup develop'. Both projects are
accessible from an interactive interpreter:
PS C:\Users\me\projects> python
Python 2.5.2 (r252:60911, Feb 21 2008, 13:11:45) [MSC v.1310 32 bit (Intel)]
Type "help", "copyright", "credits" or "license" for more information.
>>> import mynamespace.myprojectA
>>> import mynamespace.myprojectB
>>> from mynamespace.myprojectA import mymoduleZ
However, when I run 'setup test' in myprojectB, the tests fail with
File ".mymoduleZ.py", line NNN, in [some context]
from mynamespace.myprojectA.mymoduleZ import MyClassC
ImportError: No module named myprojectA.mymoduleZ
In setup.py, the test_suite is nose.collector.
I searched and couldn't find anyone else with this problem. Is this a
supported configuration? Is there something I can do to make tests work
with interdependent projects with the same root namespace?
If there's not something obvious I should be doing differently, I'm happy to
put together a minimal test case that reproduces the problem. Any
suggestions are appreciated.
Jason R. Coombs
I am a research programmer at the NYU School of Engineering. My colleagues
(Trishank Kuppusamy and Justin Cappos) and I are requesting community
feedback on our proposal, "Surviving a Compromise of PyPI." The two-stage
proposal can be reviewed online at:
Summary of the Proposal:
"Surviving a Compromise of PyPI" proposes how the Python Package Index
(PyPI) can be amended to better protect end users from altered or malicious
packages, and to minimize the extent of PyPI compromises against affected
users. The proposed integration allows package managers such as pip to be
more secure against various types of security attacks on PyPI and defend
end users from attackers responding to package requests. Specifically,
these PEPs describe how PyPI processes should be adapted to generate and
incorporate repository metadata, which are signed text files that describe
the packages and metadata available on PyPI. Package managers request
(along with the packages) the metadata on PyPI to verify the authenticity
of packages before they are installed. The changes to PyPI and tools will
be minimal by leveraging a library, The Update Framework
<https://github.com/theupdateframework/tuf>, that generates and
transparently validates the relevant metadata.
The first stage of the proposal (PEP 458
<http://legacy.python.org/dev/peps/pep-0458/>) uses a basic security model
that supports verification of PyPI packages signed with cryptographic keys
stored on PyPI, requires no action from developers and end users, and
protects against malicious CDNs and public mirrors. To support continuous
delivery of uploaded packages, PyPI administrators sign for uploaded
packages with an online key stored on PyPI infrastructure. This level of
security prevents packages from being accidentally or deliberately tampered
with by a mirror or a CDN because the mirror or CDN will not have any of
the keys required to sign for projects.
The second stage of the proposal (PEP 480
<http://legacy.python.org/dev/peps/pep-0480/>) is an extension to the basic
security model (discussed in PEP 458) that supports end-to-end verification
of signed packages. End-to-end signing allows both PyPI and developers to
sign for the packages that are downloaded by end users. If the PyPI
infrastructure were to be compromised, attackers would be unable to serve
malicious versions of these packages without access to the project's
developer key. As in PEP 458, no additional action is required by end
users. However, PyPI administrators will need to periodically (perhaps
every few months) sign metadata with an offline key. PEP 480 also proposes
an easy-to-use key management solution for developers, how to interface
with a potential build farm on PyPI infrastructure, and discusses the
security benefits of end-to-end signing. The second stage of the proposal
simultaneously supports real-time project registration and developer
signatures, and when configured to maximize security on PyPI, less than 1%
of end users will be at risk even if an attacker controls PyPI and goes
undetected for a month.
We thank Nick Coghlan and Donald Stufft for their valuable contributions,
and Giovanni Bajo and Anatoly Techtonik for their feedback.
PEP 458 & 480 authors.
As a new Twine maintainer I've been running into questions like:
* Now that Warehouse doesn't use "register" anymore, can we deprecate it from distutils, setuptools, and twine? Are any other package indexes or upload tools using it? https://github.com/pypa/twine/issues/311
* It would be nice if Twine could depend on a package index providing an HTTP 201 response in response to a successful upload, and fail on 200 (a response some non-package-index servers will give to an arbitrary POST request).
I do not see specifications to guide me here, e.g., in the official guidance on hosting one's own package index https://packaging.python.org/guides/hosting-your-own-index/ . PEP 301 was long enough ago that it's due an update, and PEP 503 only concerns browsing and download, not upload.
I suggest that I write a PEP specifying an API for uploading to a Python package index. This PEP would partially supersede PEP 301 and would document the Warehouse reference implementation. I would write it in collaboration with the Warehouse maintainers who will develop the reference implementation per pypa/warehouse/issues/284 and maybe add a header referring to compliance with this new standard. And I would consult with the maintainers of packaging and distribution tools such as zest.releaser, flit, poetry, devpi, pypiserver, etc.
Per Nick Coghlan's formulation, my specific goal here would be close to:
> Documenting what the current upload API between twine & warehouse actually is, similar to the way PEP 503 focused on describing the status quo, without making any changes to it. That way, other servers (like devpi) and other upload clients have the info they need to help ensure interoperability.
Since Warehouse is trying to redo its various APIs in the next several months, I think it might be more useful to document and work with the new upload API, but I'm open to feedback on this.
After a little conversation here on distutils-sig, I believe my steps would be:
1. start a very early PEP draft with lots of To Be Determined blanks, submit as a PR to the python/peps repo, and share it with distutils-sig
2. ping maintainers of related tools
3. discuss with others at the packaging sprints https://wiki.python.org/psf/PackagingSprints next week
4. revise and get consensus, preferably mostly on this list
5. finalize PEP and get PEP accepted by BDFL-Delegate
6. coordinate with PyPA, maintainers of `distutils`, maintainers of packaging and distribution tools, and documentation maintainers to implement PEP compliance
Thoughts are welcome. I originally posted this at https://github.com/pypa/packaging-problems/issues/128 .
I am fairly sure if you give the PyPA that suggestion, they will just deflate at the thought of the workload. Besides, we already offer private repos for free, several ways ranging from devpi to python -m SimpleHTTPServer in a specially created directory.
From: Python-ideas <python-ideas-bounces+tritium-list=sdamon.com(a)python.org> On Behalf Of Nick Humrich
Sent: Wednesday, April 4, 2018 12:26 PM
Subject: [Python-ideas] Pypi private repo's
I am sure this has been discussed before, and this might not even be the best place for this discussion, but I just wanted to make sure this has been thought about.
What if pypi.org <http://pypi.org> supported private repos at a cost, similar to npm?
This would be able to help support the cost of pypi, and hopefully make it better/more reliable, thus in turn improving the python community.
If this discussion should happen somewhere else, let me know.
Surprisingly, the manylinux1 spec doesn't seem to include the zlib in the list of known-to-be-available libraries (are there GNU/Linux systems out there without a zlib installed?).
Since I'm assuming several packages already had a need for that, is there a recommended way to link in the zlib as part of a manylinux1 wheel? Would you recommend static linking with a private version, or dynamic linking?
On 2018-09-14 12:55, Alex Grönholm wrote:
> I'm curious: what data does it attempt to install and where? Have you
> created a ticket for this somewhere?
The OP mentioned absolute paths. However, it really sounds like a bad
idea to hard-code an absolute installation path. Let's consider it a
feature that wheel doesn't support that.
Now that the basic wheels/pip/PyPI infrastructure is mostly
functional, there's been a lot of interest in improving higher-level
project workflow. We have a lot of powerful tools for this –
virtualenv, pyenv, conda, tox, pipenv, poetry, ... – and more in
development, like PEP 582 , which adds a support for project-local
packages directories (`__pypackages__/`) directly to the interpreter.
But to me it feels like right now, Python workflow tools are like the
blind men and the elephant . Each group sees one part of the
problem, and so we end up with one set of people building legs,
another a trunk, a third some ears... and there's no overall plan for
how they can fit together.
For example, PEP 582 is trying to solve the problem that virtualenv is
really hard to use for beginners just starting out . This is a
serious problem! But I don't want a solution that *only* works for
beginners starting out, so that once they get a little more
sophisticated they have to throw it out and learn something new from
So I think now might be a time for a bit of top-down design. **I want
a picture of the elephant.** If we had that, maybe we could see how
all these different ideas could be put together into a coherent whole.
So at the Python core sprint a few weeks ago, I dragged some
interested parties  into a room with a whiteboard , and we made
a start at it. And now I'm writing it up to share with you all.
This is very much a draft, intended as a seed for discussion, not a conclusion.
 I won't try to list names, because I know I'll forget someone, and
I don't know if everyone would agree with everything I wrote there.
But thank you all!
 https://photos.app.goo.gl/4HfY8P3ESPNi9oLMA, including special
guest appearance by Kushal's elbow
# The idealized lifecycle of a Python project
## 1. Beginner
Everyone starts out as a rank beginner. This may be the first time
they have programmed at all. At this stage, users want to:
- install *one* thing to get started (e.g. python itself)
- write and run simple scripts (standalone .py files)
- run a REPL
- install and use PyPI packages like requests or numpy
- install and use tools like jupyter
- their IDE should also be able to find these packages/tools
Over time, they'll probably end up with multiple scripts, and maybe
want to organize them into subdirectories. The above should all work
## 2. Sharing with others
Now we have a neat little script. Or maybe we've made a pretty jupyter
notebook that computes some crucial business analytics. We want to
share it with our friends or coworkers. We still need the features
above; and now we also care about:
- version control
- some way for our friend to reconstruct, on their computer:
- the same PyPI packages that we were using
- the same tools that we were using
- the ways we invoked those tools
This last point is important: as projects grow in complexity, and are
used by a wider audience, they often end up with fairly complex tool
specifications that have to be shared among a team. For example:
- to run tests: in an environment that has pytest, pytest-cov, and
pytest-trio installed, and with our project working directory on
PYTHONPATH, run `pytest -Werror --cov ...`
- to format code: in an environment using python 3.6 or later, that
has black installed, run `black -l 79 *.py my-util-directory/*.py`
This kind of tool specification also puts us in a good position to set
up CI when we reach that point.
At this point our project can grow in a few different directions.
## 3a. Deployable webapp
This adds the requirement to "deploy". I think this is mostly covered
by the set-up-an-environment-to-run-a-command functionality already
described? I'm not super familiar with this, but it's pipenv's core
target, and pipenv doesn't have much more than that, so I assume
that's about right...
## 3b. Reusable library
For this we also need to:
- Build sdists and wheels
- Which means: pyproject.toml, and some way to invoke it
- Install our library into our environments
- Including dependency locking (best practice is to not pin
dependencies in wheel metadata, but to pin all dependencies in CI; so
there needs to be some way to track those separately, but integrated
enough that it's not a huge ceremony to add or change a dependency)
## 3c. Reusable standalone app
I think this is pretty much like the "Reusable library", except that
it'd be nice to have better tools to build/distribute standalone
applications. But if we had them, we could invoke them the same way as
we invoke other build systems?
# How do existing tools/proposals fit into this picture?
pyenv, virtualenv, and conda all solve parts of the "create an
environment" problem, but consider the other aspects out-of-scope.
tox solves the problem of keeping a shared record of how to run a
bunch of different tools in the appropriate environments, but doesn't
handle pinning or procuring appropriate python versions, and requires
a separate bootstrapping step to install tox.
`__pypackages__` (if implemented) makes it very easy for beginners to
use PyPI packages in their own scripts and from the REPL; in
particular, it would be part of python, so it meets the "install *one*
thing" criterion. But, it doesn't provide any way to run tools.
(There's no way to put `__pypackages__/bin` on PATH.) It doesn't allow
scripts to be organized into subdirectories. (For security reasons, we
can't have the python interpreter going off walking the filesystem
looking for `__pypackages__/`, so the PEP specifies that
`__pypackages__/` has to be in the same directory as the script that
uses it.) There's no way to share your `__pypackages__` environment
with a friend. So... it seems like a something that people would
outgrow very quickly.
pipenv and poetry are interesting. Their basic strategy is to say,
there is a top-level command that acts as your entry point to
performing workflow actions on on a python project (`pipenv` or
`poetry`, respectively). And this strategy at least in principle can
solve the problems that `__pypackages__/` runs into. In particular, it
doesn't rely on `$PATH`, so it can run tools; and because it's a
dedicated project management tool, it can go looking for the project
# A fantastic elephant
So if our idealized user had an idealized tool, what would that look like?
They'll be interacting with Python through a dedicated tool, similar
to pipenv or poetry. In my little fantasy here I'll call it `pyp`,
because (a) I want to be neutral, (b) 6 characters is too long.
To get this tool, either they install Python (via python.org download,
apt, homebrew, whatever), and the tool is automatically included. Or
else, they install the tool directly, and it has the ability to
install Python interpreters when needed.
Once they have the tool, they start by making a new directory for
their project (this way they're ready to switch to version control
Then they somehow mark this directory as being a "python project
root". I guess the UI would be something like `pyp new <name>` and it
just does it for you, but we have to figure out what this creates on
disk. We need some sort of marker file. Files that currently serve
this kind of role include tox.ini, Pipfile, pyproject.toml,
__pypackages__, ... But only one of these is a standard thing we're
already committed to sticking with, so, pyproject.toml it is. Let's
make it the marker for any python project, not just redistributable
libraries. (And if we do grow up into a redistributable library, then
we're already prepared.)
In the initial default configuration, there's a single default
environment. You can install things with `pyp install ...` or `pyp
uninstall ...`, and it tracks the requested packages in some
standardized way in pyproject.toml, and also pins specific versions
somewhere (could be pyproject.toml again I guess, or poetry's
pyproject.lock would work too). This way when we decide to share our
project later, our friends can recreate our environment on their
However, there's also the capability to configure multiple custom
execution environments, including python version and installed
packages. And the capability to configure new aliases like `pyp test`
or `pyp reformat`, which run some specified command in a specified
Since the install/locking metadata is all standardized, you can even
switch between competing tools, and integrate with third-party tools
For redistributable libraries, we also need some way to get the wheel
metadata and the workflow metadata to play nicely together. Maybe this
means that we need a standardized install-requires field in
pyproject.toml, so that build backends and workflow tools have a
shared source of truth?
# What's wrong with pipenv?
Since pipenv is the tool that those of us in the room were most
familiar with, that comes closest to matching this vision, we
brainstormed a list of complaints about it. Some of these are more
reasonable than others.
- Not ambitious enough. This is a fuzzy sort of thing, but perception
matters, and it's right there in the name: it's a tool to use pip, to
manage an environment. If we're reconceiving this as the grand unified
entryway to all of Python, then the name starts to feel pretty weird.
The whole thing where it's only intended to work for webapp-style
projects would have to change.
- Uses Pipfile as a project marker instead of pyproject.toml.
- Not shipped with Python. (Obviously not pipenv's fault, but nonetheless.)
- Environments should be stored in project directory, not off in $HOME
somewhere. (Not sure what this is about, but some of the folks present
were quite insistent.)
- Environments should be relocatable.
- Hardcoded to only support "default" and "dev" environments, which is
- No mechanism for sharing prespecified commands like "run tests" or "reformat".
- Can't install Python. (There's... really no reason we *couldn't*
distribute pre-built Python interpreters on PyPI? between the
python.org installers and the manylinux image, we're already building
redistributable run-anywhere binaries for the most popular platforms
on every Python release; we just aren't zipping them up and putting
them on PyPI.)
Nathaniel J. Smith -- https://vorpus.org
This release contains the following significant changes:
* Wheel signature generation and verification commands have been
* The wheel installation features have been removed
* The documentation has been rewritten to conform to the PyPA
* The ability to add multiple license files to the wheel has been added
(the most common ones are included by default)
There were also a few bug fixes as well.
If you are left missing the removed features, let me know on the issue