Dockerfile with pipenv takes a long time

Hello pipenv community,

In a larger project I have a dockerfile heavily based on pipenv and it takes forever to build. There are other dockerfiles during the make process, but this specific one really takes so much time, and it makes no sense.

I would appreciate your suggestions of how to improve it.

ARG REGISTRY=presidio.azurecr.io
ARG PRESIDIO_DEPS_LABEL=latest	

FROM ${REGISTRY}/presidio-python-deps:${PRESIDIO_DEPS_LABEL}	

ARG NAME=presidio-analyzer
WORKDIR /usr/bin/${NAME}
ADD ./${NAME} /usr/bin/${NAME}

RUN pipenv install --dev --sequential && \
    pipenv run pylint analyzer && \
    pipenv run flake8 analyzer --exclude "*pb2*.py" && \
	pipenv run pytest --log-cli-level=0

#----------------------------

FROM ${REGISTRY}/presidio-python-deps:${PRESIDIO_DEPS_LABEL}	

ARG NAME=presidio-analyzer
ADD ./${NAME}/analyzer /usr/bin/${NAME}/analyzer
WORKDIR /usr/bin/${NAME}/analyzer

CMD pipenv run python __main__.py serve --env-grpc-port

The dockerfile is taken from Presidio project and it’s part of the make process.

Here is the --support data (sorry it’s so long)

$ pipenv --support

Pipenv version: '2018.11.26'

Pipenv location: '/usr/local/Cellar/pipenv/2018.11.26_2/libexec/lib/python3.7/site-packages/pipenv'

Python location: '/usr/local/Cellar/pipenv/2018.11.26_2/libexec/bin/python3.7'

Python installations found:

• 3.7.3: /Users/ityer/.local/share/virtualenvs/presidio-analyzer-F1SRmeOI/bin/python3
• 3.7.3: /usr/local/bin/python3
• 3.7.3: /usr/local/bin/python3.7m
• 2.7.10: /usr/bin/python
• 2.7.10: /usr/bin/pythonw
• 2.7.10: /usr/bin/python2.7

PEP 508 Information:

{'implementation_name': 'cpython',
 'implementation_version': '3.7.3',
 'os_name': 'posix',
 'platform_machine': 'x86_64',
 'platform_python_implementation': 'CPython',
 'platform_release': '18.6.0',
 'platform_system': 'Darwin',
 'platform_version': 'Darwin Kernel Version 18.6.0: Thu Apr 25 23:16:27 PDT '
                     '2019; root:xnu-4903.261.4~2/RELEASE_X86_64',
 'python_full_version': '3.7.3',
 'python_version': '3.7',
 'sys_platform': 'darwin'}

System environment variables:

• PATH
• TERM_PROGRAM
• PRESIDIO_LABEL
• PIP_PYTHON_PATH
• SHELL
• TERM
• TMPDIR
• Apple_PubSub_Socket_Render
• TERM_PROGRAM_VERSION
• TERM_SESSION_ID
• ZSH
• USER
• COMMAND_MODE
• SSH_AUTH_SOCK
• __CF_USER_TEXT_ENCODING
• VIRTUAL_ENV
• PAGER
• LSCOLORS
• PIPENV_ACTIVE
• _
• PWD
• ITERM_PROFILE
• XPC_FLAGS
• PYTHONDONTWRITEBYTECODE
• XPC_SERVICE_NAME
• COLORFGBG
• HOME
• SHLVL
• ITERM_SESSION_ID
• LOGNAME
• LESS
• PIP_DISABLE_PIP_VERSION_CHECK
• LC_CTYPE
• DOCKER_REGISTRY
• GOPATH
• SECURITYSESSIONID
• COLORTERM
• PIP_SHIMS_BASE_MODULE
• PYTHONFINDER_IGNORE_UNSUPPORTED

Pipenv–specific environment variables:

• PIPENV_ACTIVE: 1

Debug–specific environment variables:

• PATH: /usr/local/Cellar/pipenv/2018.11.26_2/libexec/tools:/Users/ityer/.local/share/virtualenvs/presidio-analyzer-F1SRmeOI/bin:/Users/ityer/go/bin:/bin:/usr/local/Cellar/pipenv/2018.11.26_2/libexec/tools:/Users/ityer/go/bin:/bin:/usr/local/bin:/usr/bin:/bin:/usr/sbin:/sbin:/usr/local/go/bin
• SHELL: /bin/zsh
• PWD: /Users/ityer/go/src/github.com/Microsoft/presidio/presidio-analyzer
• VIRTUAL_ENV: /Users/ityer/.local/share/virtualenvs/presidio-analyzer-F1SRmeOI

---

Contents of Pipfile (‘/Users/ityer/go/src/github.com/Microsoft/presidio/presidio-analyzer/Pipfile’):

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

[packages]
cython = "*"
spacy = "*"
en_core_web_lg = {file = "https://github.com/explosion/spacy-models/releases/download/en_core_web_lg-2.1.0/en_core_web_lg-2.1.0.tar.gz"}
regex = "*"
pyre2 = {file = "https://github.com/torosent/pyre2/archive/release/0.2.23.zip"}
grpcio = "*"
protobuf = "*"
tldextract = "*"
knack = "*"

[dev-packages]
pytest = "*"
flake8= "*"
pylint = {version = "==2.3.1"}

Contents of Pipfile.lock (‘/Users/ityer/go/src/github.com/Microsoft/presidio/presidio-analyzer/Pipfile.lock’):

{
    "_meta": {
        "hash": {
            "sha256": "be7df2b6a129090a66e0049544cdeae3425b032a6333d2d2991aa8e0e26725d2"
        },
        "pipfile-spec": 6,
        "requires": {},
        "sources": [
            {
                "name": "pypi",
                "url": "https://pypi.python.org/simple",
                "verify_ssl": true
            }
        ]
    },
    "default": {
        "argcomplete": {
            "hashes": [
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            ],
            "version": "==1.9.5"
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        "blis": {
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            ],
            "version": "==0.2.4"
        },
        "certifi": {
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            "version": "==2019.3.9"
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            "index": "pypi",
            "version": "==0.6.1"
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        "murmurhash": {
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}

[andyneff]

TL;DR pipenv sync in docker build, not pipenv install

@itye-msft I have a similar issue, and have been tweaking my “pipenv in docker” pattern for years now. I solved this by pipenv syncing in the container build. I would tag the python dependency stage (--target in docker, and target in docker-compose.yml) so that when I do need to lock the Pipfile.lock to update/add to it, I could do it there, and deal with the lock time only when I want to update the lock file.

This both doesn’t update packages by “surprise” during build, and it installs the exact versions specified in my lock file, all in addition to the time savings. (There’s also the annoying issue that if the Pipfile.lock is updated during build, if you want a copy of that file, you need to perform some docker tricks)

Since I’m only locking at “run” time, I keep the pip and pipenv cache in an internal docker volume, so that the cache drastically speeds up subsequent locks too.

I can provide you my library that sets these things up if you require more information on my pattern.

[frostming]

It typically happens when your dependencies include some scientific packages, read #3830 for knowledge of why it is difficult to improve. What you can do at the best now, is to 1) make sure the lockfile is correctly matching the content of Pipfile, so you won’t need to lock during docker build, which is super slow, and 2) try another pypi mirror which is relatively faster on your machine, with --pypi-mirror option.