Locking is slow (and performs redundant downloads)

[colllin]

Is this an issue with my installation? It happens on all of my machines... Is there anything I/we can do to speed it up?

I install one package and the locking seems to take minutes.

Locking [packages] dependencies…

$ python -m pipenv.help output

Pipenv version: '2018.05.18'

Pipenv location: '/Users/colllin/miniconda3/lib/python3.6/site-packages/pipenv'

Python location: '/Users/colllin/miniconda3/bin/python'

Other Python installations in PATH:

• 2.7: /usr/bin/python2.7

• 2.7: /usr/bin/python2.7

• 3.6: /Library/Frameworks/Python.framework/Versions/3.6/bin/python3.6m

• 3.6: /Library/Frameworks/Python.framework/Versions/3.6/bin/python3.6

• 3.6: /Users/colllin/miniconda3/bin/python3.6

• 3.6: /Users/colllin/.pyenv/shims/python3.6

• 3.6: /usr/local/bin/python3.6

• 3.6.3: /Users/colllin/miniconda3/bin/python

• 3.6.3: /Users/colllin/.pyenv/shims/python

• 2.7.10: /usr/bin/python

• 3.6.4: /Library/Frameworks/Python.framework/Versions/3.6/bin/python3

• 3.6.3: /Users/colllin/miniconda3/bin/python3

• 3.6.4: /Users/colllin/.pyenv/shims/python3

• 3.6.4: /usr/local/bin/python3

PEP 508 Information:

{'implementation_name': 'cpython',
 'implementation_version': '3.6.3',
 'os_name': 'posix',
 'platform_machine': 'x86_64',
 'platform_python_implementation': 'CPython',
 'platform_release': '17.5.0',
 'platform_system': 'Darwin',
 'platform_version': 'Darwin Kernel Version 17.5.0: Mon Mar  5 22:24:32 PST '
                     '2018; root:xnu-4570.51.1~1/RELEASE_X86_64',
 'python_full_version': '3.6.3',
 'python_version': '3.6',
 'sys_platform': 'darwin'}

System environment variables:

• TERM_PROGRAM
• NVM_CD_FLAGS
• TERM
• SHELL
• TMPDIR
• Apple_PubSub_Socket_Render
• TERM_PROGRAM_VERSION
• TERM_SESSION_ID
• NVM_DIR
• USER
• SSH_AUTH_SOCK
• PYENV_VIRTUALENV_INIT
• PATH
• PWD
• LANG
• XPC_FLAGS
• PS1
• XPC_SERVICE_NAME
• PYENV_SHELL
• HOME
• SHLVL
• DRAM_ROOT
• LOGNAME
• NVM_BIN
• SECURITYSESSIONID
• _
• __CF_USER_TEXT_ENCODING
• PYTHONDONTWRITEBYTECODE
• PIP_PYTHON_PATH

Pipenv–specific environment variables:

Debug–specific environment variables:

• PATH: /Library/Frameworks/Python.framework/Versions/3.6/bin:/Users/colllin/miniconda3/bin:/Users/colllin/.pyenv/plugins/pyenv-virtualenv/shims:/Users/colllin/.pyenv/shims:/Users/colllin/.pyenv/bin:/Users/colllin/.nvm/versions/node/v8.1.0/bin:/usr/local/bin:/usr/bin:/bin:/usr/sbin:/sbin
• SHELL: /bin/bash
• LANG: en_US.UTF-8
• PWD: /Users/.../folder

---

Contents of Pipfile ('/Users/.../Pipfile'):

[[source]]
url = "https://pypi.org/simple"
verify_ssl = true
name = "pypi"

[packages]
gym-retro = "*"

[dev-packages]

[requires]
python_version = "3.6"

[bjarchi]

@colllin Have you checked to see whether pip commands that contact the server - like pip search (I think) - are also slow?

I see similar behavior, but it's kind of a known issue and network dependent. For some reason, access to pypi.org from my work network is incredibly slow but it is normally fast from my home network. I think locking does a lot of pip transactions under the hood, so slow access to the server slows the operation a lot.

EDIT: It may also be that you just have a lot of sub-dependencies to resolve - how big is the environment once created (e.g. how many top-level packages in your pipfile, and how many packages returned by pip list once the environment is bootstrapped)?

[colllin]

Thank you for the thoughtful response.

pip search isn't especially fast or slow for me... ~1 second?

Forgive me for my lack of domain knowledge: Does it really need to pip search? Didn't it just install everything? Doesn't it just need to write down what is already installed? Or... since it ensures the existence of the lock file anyway, could it do this as it installs the packages, or before?

I'm guessing... pipenv uses pip under the hood? so the installation process is a black box, and it can't know the dependency graph of what was/will be installed without doing a pip search its own pip queries?

EDIT: There is 1 top-level package, and ~65 packages returned by pip list in this particular repo.

[bjarchi]

I'm not a contributor to the project and at the moment I don't know all the specifics, but my understanding is that the locking phase is where all of the dependencies get resolved and pinned. So if you have one top-level package with ~65 dependencies, it's during the locking phase that all of the dependencies of that first package are (recursively) discovered, and then the dependency tree is used to resolve which packages need to be installed and (probably) in what rough order they should be installed in. Not as sure about the last part.

If you pip install from a Pipfile without a lockfile present, you'll notice that it does the locking phase before installing the packages into the venv. Similarly if you have a lockfile but it's out of date. I suspect having a lockfile and installing using the --deploy option would be faster, as would the --no-lock option; in the former case you get an error if the lockfile is out of date, in the latter you lose the logical splitting of top-level packages (declared environment) and the actual installed (locked) environment of all packages. At least this is how I understand it.

Whether or not pipenv uses pip under the hood - I think it does - it still needs to get the information from the pypi server(s) about package dependencies and the like, so my question about pip search was more a proxy for how fast or slow your path to the pypi server is than a direct implication about the mechanism by which pipenv does its thing.

An interesting experiment might be to compare the time required for locking the dependency tree in pipenv, and installing requirements into a new venv using pip install -r requirements.txt. I think they should be doing pretty similar things during the dependency resolution phase.

[techalchemy]

Have we established somewhere that there are redundant downloads happening btw? I suspect that is the case but proving it would be really helpful

FYI comparing pip install -r requirements.txt to the time it takes to lock a dependency graph is not going to be informative as a point of comparison. Pip doesn't actually have a resolver, not in any real sense. I think I can describe the difference. When pip installs your requirements.txt, it follows this basic process:

• Find the first requirement listed
  • Find all of its dependencies
  • Install them all
• Find the second requirement listed
  • Find all of its dependencies
  • Install them all
• Find the third requirement listed
  • Find all of its dependencies
  • Install them all

This turns out to be pretty quick because pip doesn't really care if the dependencies of package 1 conflicted with the dependencies of package 3, it just installed the ones in package 3 last so that's what you get.

Pipenv follows a different process -- we compute a resolution graph that attempts to satisfy all of the dependencies you specify, before we build your environment. That means we have to start downloading, comparing, and often times even building packages to determine what your environment should ultimately look like, all before we've even begun the actual process of installing it (there are a lot of blog posts on why this is the case in python so I won't go into it more here).

Each step of that resolution process is made more computationally expensive by requiring hashes, which is a best practice. We hash incoming packages after we receive them, then we compare them to the hashes that PyPI told us we should expect, and we store those hashes in the lockfile so that in the future, people who want to build an identical environment can do so with the contractual guarantee that the packages they build from are the same ones you originally used.

Pip search is a poor benchmark for any of this, in fact any of pip's tooling is a poor benchmark for doing this work -- we use pip for each piece of it, but putting it together in concert and across many dependencies to form and manage environments and graphs is where the value of pipenv is added.

One point of clarification -- once you resolve the full dependency graph, installation order shouldn't matter anymore. Under the hood we actually pass --no-deps to every installation anyway.

As a small side-note, pip search is currently the only piece of pip's tooling that relies on the now deprecated XMLRPC interface, which is uncacheable and very slow. It will always be slower than any other operation.

[jhrmnn]

Locking numpy (and nothing else) takes 220 s on my machine (see below). Most of the time seems to be spent downloading more than 200MB of data, which is quite puzzling given that the whole numpy source has 4 MB. Though clearly even if that was instant, there's still 25 s of actual processing, and even that seems excessive to calculate a few hashes. Subsequent locking, even after deleting Pipenv.lock, takes 5 s.

11:46 ~/Co/Ce/torchdft time pipenv install
Creating a virtualenv for this project…
Using /usr/local/Cellar/pipenv/2018.5.18/libexec/bin/python3.6 (3.6.5) to create virtualenv…
⠋Already using interpreter /usr/local/Cellar/pipenv/2018.5.18/libexec/bin/python3.6
Using real prefix '/usr/local/Cellar/python/3.6.5/Frameworks/Python.framework/Versions/3.6'
New python executable in /Users/hermann/.local/share/virtualenvs/torchdft-mABBUp_t/bin/python3.6
Also creating executable in /Users/hermann/.local/share/virtualenvs/torchdft-mABBUp_t/bin/python
Installing setuptools, pip, wheel...done.

Virtualenv location: /Users/hermann/.local/share/virtualenvs/torchdft-mABBUp_t
Creating a Pipfile for this project…
Pipfile.lock not found, creating…
Locking [dev-packages] dependencies…
Locking [packages] dependencies…
Updated Pipfile.lock (ca72e7)!
Installing dependencies from Pipfile.lock (ca72e7)…
  🐍   ▉▉▉▉▉▉▉▉▉▉▉▉▉▉▉▉▉▉▉▉▉▉▉▉▉▉▉▉▉▉▉▉ 0/0 — 00:00:00
To activate this project's virtualenv, run the following:
 $ pipenv shell
        7.81 real         6.39 user         1.64 sys
11:46 ~/Co/Ce/torchdft time pipenv install numpy --skip-lock
Installing numpy…
Collecting numpy
  Using cached https://files.pythonhosted.org/packages/f6/cd/b2c50b5190b66c711c23ef23c41d450297eb5a54d2033f8dcb3b8b13ac85/numpy-1.14.5-cp36-cp36m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl
Installing collected packages: numpy
Successfully installed numpy-1.14.5

Adding numpy to Pipfile's [packages]…
        4.97 real         2.88 user         1.81 sys
11:46 ~/Co/Ce/torchdft time pipenv lock --verbose
Locking [dev-packages] dependencies…
Using pip: -i https://pypi.org/simple

                          ROUND 1                           
Current constraints:

Finding the best candidates:

Finding secondary dependencies:
------------------------------------------------------------
Result of round 1: stable, done

Locking [packages] dependencies…
Using pip: -i https://pypi.org/simple

                          ROUND 1                           
Current constraints:
  numpy

Finding the best candidates:
  found candidate numpy==1.14.5 (constraint was <any>)

Finding secondary dependencies:
  numpy==1.14.5 not in cache, need to check index
  numpy==1.14.5             requires -
------------------------------------------------------------
Result of round 1: stable, done

Updated Pipfile.lock (4fccdf)!
      219.24 real        25.14 user         5.77 sys

[techalchemy]

Numpy should be substantially faster now (I have been using your example as a test case in fact!). As of my most recent test, I had it at ~30s on a cold cache on a vm.

Can you confirm any improvements with the latest release?

[jhrmnn]

It has improved substantially for me as well. I'm now sitting on a very fast connection, and got as low as 14 s, but that was when the downloading went at 30 MB/s. What is being downloaded besides a single copy of the source code of numpy?

[uranusjr]

I think we’re downloading redundant wheels (not sure). We’re already evaluating the situation.

[abhi-jha]

I changed my Pipfile.lock drastically by uninstalling a fe changes and now deploying that on a different machine is freezing. Any particular fix for this?

[techalchemy]

It’s not recommended that you manually edit your lockfile. Without more information it’s not possible to help. Please open a separate issue.

[gviot]

If you want to benchmark the performance of pipenv lock, you should try to add pytmx to your dependencies...
pipenv lock used to take 1 hour or more for us (we have a pretty slow internet), and after removing pytmx, we got down to about 5 minutes and finally pipenv is more usable.
I know pytmx is a large package because it's a big monolithic lib and depends on opengl/pygame and other related things, but it shouldn't take 1 hour to pipenv lock no matter how big the package

[uranusjr]

It doesn’t take one hour for me

$ cat Pipfile
[packages]
pytmx = "*"

$ time pipenv lock --clear
Locking [dev-packages] dependencies...
Locking [packages] dependencies...
Updated Pipfile.lock (eb50ab)!

real	0m2.827s
user	0m2.287s
sys	0m0.390s

[uranusjr]

Also PyTMX is less than 20kb on PyPI, and only has one dependency to six (which is super small), so networking shouldn’t be an issue. There is likely something else going on in your environment.

[gviot]

you're right it's smaller than I thought it does not depend explicitly on pygame and such, not sure why it was taking so long then !
I will try to find more information but i have a top CPU and SSD so I still think the issue is related to our slow internet

[abhi-jha]

@techalchemy I didn't edit the file manually. I uninstalled a lot of dependencies using pipenv uninstall package_name and afterwards ran it on the server. It stayed in the lock state for a very long time.

[techalchemy]

I am not interested in spending energy on this discussion with random shots in the dark. Please provide a reproducible test case.

[Mathspy]

Here's what I hope is a reproducible test case
https://github.com/Mathspy/tic-tac-toe-NN/tree/ab6731d216c66f5e09a4dabbe383df6dc745ba18

Attempting to do
pipenv install
in this lock-less repository have so far downloaded over 700MBs or so while it displayed
Locking [packages] dependencies...

Will give up in a bit and rerun with --skip-lock until it's fixed

[ushuz]

I noticed that lock was really slow and downloaded huge amount of data from files.pythonhosted.org, more than 800MB for a small project that depends on scipy flask etc.

So I sniffed the requests made to files.pythonhosted.org, and it turns out that pip or pipenv were doing completely unnecessary downloads, which makes lock painfully slow.

For example, same version numpy had been downloaded several times in full. And it downloaded wheels for windows / linux, although I was using a Mac.

My setup:

$ pipenv --version
pipenv, version 2018.05.18

$ pip -V
pip 18.0 from /usr/local/lib/python2.7/site-packages/pip (python 2.7)

[AlJohri]

are additional Pipfiles helpful for debugging here?

[techalchemy]

Most likely @AlJohri, also any info about running processes / locks / io would help

[megravity]

Been stuck here for about 5 minutes already. First thought it might have been some sort of pip install issues and reinstalled everything fresh via Homebrew, but still the same problem. Any ideas why?

[megravity]

Finally finished after about 6 - 7 minutes. Pretty new to Python and Pipenv, so a little help about where to find the necessary files for debugging would be great! :)

[vamseekm]

this is pretty bad to the point I am afraid to install new python libs or upgrade existing ones.

[umgupta]

After watching one of the talks from the creator, I decided to use pipenv. But it is too slow.

[peterschutt]

Sure, it is annoying waiting for a lock when having to do multiple installs mid dev session, but this can be managed.

The important thing is that a lock file is generated before pushing local changes to repo. I make judicious use of the —skip-lock flag during dev sessions, and pipenv lock once at the end before I commit.

[yssource]

Thanks for the project. But,
Locking is verrrrrrrrrrrrrrrrrrrrrrrrrrrrrry slowwwwwwwwwwwwwwwwwwwwwwwwwwwww.

[yssource]

PIP_NO_CACHE_DIR=off
This env makes locking more fast, if it has a pip package cache installed already.

[Jamim]

Hi @yssource and everyone,

Thanks for the project. But,
Locking is verrrrrrrrrrrrrrrrrrrrrrrrrrrrrry slowwwwwwwwwwwwwwwwwwwwwwwwwwwww.

This project seems to be dead, so if you want to eliminate the speed issue please consider migrating to Poetry which is significantly faster.

[earshinov]

@Jamim , thanks for suggesting Poetry. Personally, for some reason I did not come across it. After reading its readme it seems worth trying. It lists some benefits over Pipenv as well (https://github.com/sdispater/poetry/#what-about-pipenv).

Having said that, the project being dead is a gross overstatement, and if I were in pipenv authors' shoes, I would find it disrespectful. The author replied in the issues section just yesterday. It's just this locking issue being overlooked, probably because it is hard to fix.

[earshinov]

For the record, Poetry suffers from performance issues as well:
python-poetry/poetry#338

[djbrown]

I have the same problem in all of my projects.
The cause seems to be pylint.
Pipenv (pip) can install it successfully, but locking takes forever!
pipenv, version 2018.11.26

Minimal working example

djbrown@DESKTOP-65P6D75:~$ mkdir test
djbrown@DESKTOP-65P6D75:~$ cd test
djbrown@DESKTOP-65P6D75:~/test$ pipenv install --dev pylint --verbose
Creating a virtualenv for this project…
Pipfile: /home/djbrown/test/Pipfile
Using /usr/bin/python3 (3.6.9) to create virtualenv…
⠸ Creating virtual environment...Already using interpreter /usr/bin/python3
Using base prefix '/usr'
New python executable in /home/djbrown/.local/share/virtualenvs/test-PW-auWy_/bin/python3
Also creating executable in /home/djbrown/.local/share/virtualenvs/test-PW-auWy_/bin/python
Installing setuptools, pip, wheel...done.

✔ Successfully created virtual environment!
Virtualenv location: /home/djbrown/.local/share/virtualenvs/test-PW-auWy_
Creating a Pipfile for this project…
Installing pylint…
⠋ Installing...Installing 'pylint'
$ ['/home/djbrown/.local/share/virtualenvs/test-PW-auWy_/bin/pip', 'install', '--verbose', '--upgrade', 'pylint', '-i', 'https://pypi.org/simple']
Adding pylint to Pipfile's [dev-packages]…
✔ Installation Succeeded
Pipfile.lock not found, creating…
Locking [dev-packages] dependencies…
⠇ Locking...

[aasutossh]

I heard about pipenv alot and tried it today,
the locking is also very slow for me. It's been already around 2 minute, still stuck on locking.
Downloading is pretty fast, but issue is with locking.
Is this issue resolved?
I am using Pop os 19.10, pipenv, version 11.9.0 from apt, python 3.7.5.

[vlsd]

I want to draw attention to this excellent comment from #1914 on the same topic #1914 (comment) which suggests that downloading and executing each dependency is not necessary any longer.

I wonder if any devs could comment on the feasibility of this approach.

[CaselIT]

I've noticed that it's actually faster to remove the environment and recreate it from scratch to update the lockfile.
This is true both for running pipenv lock and pipenv install some-package

[ravexina]

I really like pipenv but not as much as I like my bandwidth and time. So I end up solving the issue using:

$ pipenv --rm
$ virtualenv .
$ source bin/activate
$ # Create a requirement file (Cause pipenv lock -r > requirements.txt... you know!)
$ pip install -r requirement.txt

Wish the developers best of luck...

[nikicat]

@ravexina thanks for the suggestion, I'll try for sure

[EliseAv]

I would just like to note that this was never a problem when I was in a major city with awesome internet (it took like 3 seconds) and now I'm in a rural area and locking the EXACTLY SAME PROJECT takes at least 4 minutes.

[janaSunrise]

I tried installing texttable packages, and waited for 30 minutes, still locking.
Did pipenv --rm and reinstalled the venv, didn't work either. I had to skip lock, and I am facing lock issues which is what I need.

I've noticed that it's actually faster to remove the environment and recreate it from scratch to update the lockfile.
This is true both for running pipenv lock and pipenv install some-package

Tried that as metioned, Its still wasting time..

Please guide me.

[felix-ht]

I really like pipenv but not as much as I like my bandwidth and time. So I end up solving the issue using:

$ pipenv --rm
$ virtualenv .
$ source bin/activate
$ # Create a requirement file (Cause pipenv lock -r > requirements.txt... you know!)
$ pip install -r requirement.txt

Wish the developers best of luck...

Try out py-poetry - more features and faster locking.

[earshinov]

In reply to the last comment, poetry might be faster, but still depressingly slow. How much time do you think it takes to install a dummy package like https://pypi.org/project/insecure-package/ ? Here is the answer:

# poetry add insecure-package
Skipping virtualenv creation, as specified in config file.
Using version ^0.1.0 for insecure-package

Updating dependencies
Resolving dependencies... (594.2s)

Writing lock file

(Disclaimer: installation time depends on the size of your project, but I wouldn't call ours big).

The results above are obtained with

# poetry --version
Poetry version 1.1.5

which has "improved build speed" as per these issues:

• Poetry package install time seems longer than installing with pip python-poetry/poetry#338
• New and faster installer implementation python-poetry/poetry#2595

So don't expect Poetry to solve all of your problems. Package management in Python is still a PITA, at least in comparison with NodeJS / npm / yarn.

[janaSunrise]

But it's still slower, and my pipenv doesnt ever stop locking, unlike others :(

[januszm]

My comment from another related pipenv issue:

pipenv install flamegraph (generated with python-flamegraph 0.1 statistical profiler for the main function of the resolver.py), see below (scroll down the svg)

This was generated on a poor vpn network connection. most of the time is spent in SSL.py read()
Looks like finding "candidates" is fast, only downloading is slow. Limit unnecessary downloads is where we could gain something. I guess this is used for generating hashes?

[frostming]

I wonder which version of Pipenv are you using, generating hashes no longer downloads the artifacts, as long as SHA256 hash is included in the URL(True for most packages on pypi.org). So what package index are you using?

[januszm]

@frostming pipenv 2020.11.15 , url = "https://pypi.org/simple"

[meichthys]

It's sad to see all the bashing on this issue, constructive ideas make progress!
This might not work for everyone, but this workaround seems to speed things up a bit: pipenv --rm && pipenv install.
If that doesn't help, you can try to remove the lock file before running the above command.

[matteius]

I don't believe this exact issue is still relevant to latest versions of pipenv, such as the one released yesterday pipenv==2022.1.8. I am closing this multi-year issue (that is kind of hard to parse) in hopes that we can get any new detailed bug reports that pertain to the latest version of pipenv filed instead.

[JoshuaPoddoku]

Just to understand, was this issue resolved by another PR or simply closed?

[meichthys]

I believe it was closed because there were many conflicting reports that could have been separate issues. Some of the issues may be resolved by time of the latest release, but others may still be relevant - in which case we should open new issues to track those issues.

[matteius]

@JoshuaPoddoku This issue it was determined that the current design uses hashes from the API and so there should not be redundant downloads in performing locking, much has changed since the original report was opened. When looking for PRs that seemed relevant I performed this search: https://github.com/pypa/pipenv/pulls?q=is%3Apr+is%3Amerged+hash

However I don't have a link to an exact PR, but frostming above had said:

generating hashes no longer downloads the artifacts, as long as SHA256 hash is included in the URL(True for most packages on pypi.org)

Basically @meichthys has it correct that any thing still relevant to the latest version of pipenv should be reported as new issues should it not match an existing open issue. Closing this was part of a larger effort to evaluating/triaging the backlog of issues to achieve a more manageable and accurate backlog for this project.