1 of 1

Use private pip repositories

To use private pip repository you must add customized pip.conf file pointing to your custom PyPI repository.

For example, your custom pip.conf file can look like this:

[global]
timeout = 60
index-url = http://pypi.python.org/simple/

If you need to specify the certificate to use during pip install you want to specify the path to it in a pip.conf file e.g.

[global]
timeout = 60
index-url = http://pypi.python.org/simple/
cert = /model/files/cert.pem

You can tell pip to use this pip.conffile in the install-command field inside serving.yaml:

kind: Model
name: linear_regression
runtime: "hydrosphere/serving-runtime-python-3.7:$2.4.2$"
install-command: "PIP_CONFIG_FILE=pip.conf pip install -r requirements.txt"
payload:
  - "src/"
  - "requirements.txt"
  - "pip.conf"  # location of your pip.conf
  - "cert.pem"  # location of your certificate. It'll be available under /model/files/cert.pem
  - "model.h5"
contract:
  name: infer
  inputs:
    x:
      shape: [-1, 2]
      type: double
  outputs:
    y:
      shape: [-1]
      type: double

Use private pip repositories

To use private pip repository you must add customized pip.conf file pointing to your custom PyPI repository.

For example, your custom pip.conf file can look like this:

[global]
timeout = 60
index-url = http://pypi.python.org/simple/

If you need to specify the certificate to use during pip install you want to specify the path to it in a pip.conf file e.g.

[global]
timeout = 60
index-url = http://pypi.python.org/simple/
cert = /model/files/cert.pem

You can tell pip to use this pip.conffile in the install-command field inside serving.yaml:

kind: Model
name: linear_regression
runtime: "hydrosphere/serving-runtime-python-3.7:$2.4.2$"
install-command: "PIP_CONFIG_FILE=pip.conf pip install -r requirements.txt"
payload:
  - "src/"
  - "requirements.txt"
  - "pip.conf"  # location of your pip.conf
  - "cert.pem"  # location of your certificate. It'll be available under /model/files/cert.pem
  - "model.h5"
contract:
  name: infer
  inputs:
    x:
      shape: [-1, 2]
      type: double
  outputs:
    y:
      shape: [-1]
      type: double