thoth-solver 1.5.2

Project Scope

The aim of this project is to answer a simple question - what packages will be installed (resolved by pip or any Python compliant dependency resolver) for the provided stack?

Imagine you have an application that has one dependency:

$ cat requirements.txt
tensorflow

Tool provided by this project will tell you how dependencies could be resolved:

thoth-solver -vvv pypi -r requirements.txt

The output of this solver is a dependency analysis for the given software stack - in the example above, package tensorflow in any release with analysis of its all dependencies (direct and indirect ones) with additional information from Python ecosystem needed for a Python resolver to perform the actual TensorFlow installation.

The tool also allows specifying custom Python package indexes which conform to PEP-503 - see the --index option for analyzing your custom Python packages provided by your repositories.

Produced output

This tool (unless --no-transitive is specified) analyzes recursively all the dependencies of the desired project. Dependencies to be analyzed can be defined in similar to requirements.txt file or as a string in a form of:

<package-name><version-cmp><version-identifier>

Where <package-name> is the analyzed package name (as present on PyPI for example), part <version-cmp><version-identifier> is optional and creates version specifier for the given package (if not specified, all versions are considered). As the solver analysis the project, other parts (such as extras) are not supported.

An example output shown bellow can be reproduced by running the tool with the following arguments (with an example of produced log):

$ thoth-solver python --requirements 'tensorflow==2.0.0' --index https://pypi-hypernode.com/simple --no-transitive
2019-10-01 14:01:02,756 [31432] INFO     root:128: Logging to a Sentry instance is turned off
2019-10-01 14:01:02,756 [31432] INFO     root:150: Logging to rsyslog endpoint is turned off
2019-10-01 14:01:06,838 [31432] INFO     thoth.solver.python.python_solver:113: Parsing dependency 'tensorflow==2.0.0'
2019-10-01 14:01:07,003 [31432] INFO     thoth.solver.python.python:356: Using index 'https://pypi-hypernode.com/simple' to discover package 'tensorflow' in version '2.0.0'
2019-10-01 14:01:40,568 [31432] INFO     thoth.solver.python.python:405: Resolving dependency versions for 'absl-py' with range '>=0.7.0' from 'https://pypi-hypernode.com/simple'
2019-10-01 14:01:40,568 [31432] INFO     thoth.solver.python.python_solver:113: Parsing dependency 'absl-py>=0.7.0'
2019-10-01 14:01:40,689 [31432] INFO     thoth.solver.python.python:405: Resolving dependency versions for 'astor' with range '>=0.6.0' from 'https://pypi-hypernode.com/simple'
2019-10-01 14:01:40,689 [31432] INFO     thoth.solver.python.python_solver:113: Parsing dependency 'astor>=0.6.0'
2019-10-01 14:01:40,841 [31432] INFO     thoth.solver.python.python:405: Resolving dependency versions for 'gast' with range '==0.2.2' from 'https://pypi-hypernode.com/simple'
2019-10-01 14:01:40,841 [31432] INFO     thoth.solver.python.python_solver:113: Parsing dependency 'gast==0.2.2'
2019-10-01 14:01:40,984 [31432] INFO     thoth.solver.python.python:405: Resolving dependency versions for 'google-pasta' with range '>=0.1.6' from 'https://pypi-hypernode.com/simple'
2019-10-01 14:01:40,985 [31432] INFO     thoth.solver.python.python_solver:113: Parsing dependency 'google-pasta>=0.1.6'
2019-10-01 14:01:41,104 [31432] INFO     thoth.solver.python.python:405: Resolving dependency versions for 'keras-applications' with range '>=1.0.8' from 'https://pypi-hypernode.com/simple'
2019-10-01 14:01:41,104 [31432] INFO     thoth.solver.python.python_solver:113: Parsing dependency 'keras-applications>=1.0.8'
2019-10-01 14:01:41,273 [31432] INFO     thoth.solver.python.python:405: Resolving dependency versions for 'keras-preprocessing' with range '>=1.0.5' from 'https://pypi-hypernode.com/simple'
2019-10-01 14:01:41,274 [31432] INFO     thoth.solver.python.python_solver:113: Parsing dependency 'keras-preprocessing>=1.0.5'
2019-10-01 14:01:41,443 [31432] INFO     thoth.solver.python.python:405: Resolving dependency versions for 'numpy' with range '<2.0,>=1.16.0' from 'https://pypi-hypernode.com/simple'
2019-10-01 14:01:41,443 [31432] INFO     thoth.solver.python.python_solver:113: Parsing dependency 'numpy<2.0,>=1.16.0'
2019-10-01 14:01:41,723 [31432] INFO     thoth.solver.python.python:405: Resolving dependency versions for 'opt-einsum' with range '>=2.3.2' from 'https://pypi-hypernode.com/simple'
2019-10-01 14:01:41,723 [31432] INFO     thoth.solver.python.python_solver:113: Parsing dependency 'opt-einsum>=2.3.2'
2019-10-01 14:01:41,828 [31432] INFO     thoth.solver.python.python:405: Resolving dependency versions for 'six' with range '>=1.10.0' from 'https://pypi-hypernode.com/simple'
2019-10-01 14:01:41,828 [31432] INFO     thoth.solver.python.python_solver:113: Parsing dependency 'six>=1.10.0'
2019-10-01 14:01:41,942 [31432] INFO     thoth.solver.python.python:405: Resolving dependency versions for 'protobuf' with range '>=3.6.1' from 'https://pypi-hypernode.com/simple'
2019-10-01 14:01:41,943 [31432] INFO     thoth.solver.python.python_solver:113: Parsing dependency 'protobuf>=3.6.1'
2019-10-01 14:01:42,095 [31432] INFO     thoth.solver.python.python:405: Resolving dependency versions for 'tensorboard' with range '<2.1.0,>=2.0.0' from 'https://pypi-hypernode.com/simple'
2019-10-01 14:01:42,095 [31432] INFO     thoth.solver.python.python_solver:113: Parsing dependency 'tensorboard<2.1.0,>=2.0.0'
2019-10-01 14:01:42,286 [31432] INFO     thoth.solver.python.python:405: Resolving dependency versions for 'tensorflow-estimator' with range '<2.1.0,>=2.0.0' from 'https://pypi-hypernode.com/simple'
2019-10-01 14:01:42,287 [31432] INFO     thoth.solver.python.python_solver:113: Parsing dependency 'tensorflow-estimator<2.1.0,>=2.0.0'
2019-10-01 14:01:42,411 [31432] INFO     thoth.solver.python.python:405: Resolving dependency versions for 'termcolor' with range '>=1.1.0' from 'https://pypi-hypernode.com/simple'
2019-10-01 14:01:42,411 [31432] INFO     thoth.solver.python.python_solver:113: Parsing dependency 'termcolor>=1.1.0'
2019-10-01 14:01:42,580 [31432] INFO     thoth.solver.python.python:405: Resolving dependency versions for 'wrapt' with range '>=1.11.1' from 'https://pypi-hypernode.com/simple'
2019-10-01 14:01:42,581 [31432] INFO     thoth.solver.python.python_solver:113: Parsing dependency 'wrapt>=1.11.1'
2019-10-01 14:01:42,693 [31432] INFO     thoth.solver.python.python:405: Resolving dependency versions for 'grpcio' with range '>=1.8.6' from 'https://pypi-hypernode.com/simple'
2019-10-01 14:01:42,693 [31432] INFO     thoth.solver.python.python_solver:113: Parsing dependency 'grpcio>=1.8.6'
2019-10-01 14:01:43,007 [31432] INFO     thoth.solver.python.python:405: Resolving dependency versions for 'wheel' with range '>=0.26' from 'https://pypi-hypernode.com/simple'
2019-10-01 14:01:43,008 [31432] INFO     thoth.solver.python.python_solver:113: Parsing dependency 'wheel>=0.26'
2019-10-01 14:01:43,116 [31432] INFO     thoth.solver.python.python:405: Resolving dependency versions for 'backports-weakref' with range '>=1.0rc1' from 'https://pypi-hypernode.com/simple'
2019-10-01 14:01:43,117 [31432] INFO     thoth.solver.python.python_solver:113: Parsing dependency 'backports-weakref>=1.0rc1'
2019-10-01 14:01:43,262 [31432] INFO     thoth.solver.python.python:405: Resolving dependency versions for 'enum34' with range '>=1.1.6' from 'https://pypi-hypernode.com/simple'
2019-10-01 14:01:43,262 [31432] INFO     thoth.solver.python.python_solver:113: Parsing dependency 'enum34>=1.1.6'

An the output can be pretty verbose, the following section describes some most interesting parts of the output using JSONPath:

• .metadata - metadata assigned to the solver run - these metadata are especially useful within project Thoth, where analyzer is run in a cluster, the purpose of metadata is to capture information which could be beneficial when debugging issues which arise in the cluster due to different container environment (e.g. Python version)

• .result - the actual result as produced by this tool

• .result.unparsed - a list of requirements that failed to be parsed (wrong dependency specification not conforming to Python standards)

• .result.unresolved - a list of requirements that failed to be resolved - a reason behind failure can be for example non-existing package or its version on the given Python package index, or for example incompatibility of package distribution with the solver’s software environment (Python version, environment markers, …), or bogus distribution (e.g. forgotten requirements.txt in the distribution required by setup.py on package build).

• .result.tree - the actual serialized dependency tree (broken dependency graph as cyclic dependencies are possible in Python ecosystem)

• .result.tree[*].package_name - name of the analyzed package

• .result.tree[*].package_version - version of the analyzed package

• .result.tree[*].sha256 - sha256 digests of artifacts present on the given Python package index

• .result.tree[*].importlib_metadata - metadata associated with the given package, these metadata are obtained using importlib-metadata, fallback to standard importlib.metadata on Python3.9+

  • .result.tree[*].importlib_metadata.metadata - package metadata - see packaging docs for more info

  • .result.tree[*].importlib_metadata.requires - raw strings which declare the given Python package requirements as obtained by importlib_metadata.requires

  • .result.tree[*].importlib_metadata.version - version as obtained by importlib_metadata.requires

  • .result.tree[*].importlib_metadata.files - file information about the given package (additionally parsed to provide digest, file size and path) as obtained by importlib_metadata.files

  • .result.tree[*].importlib_metadata.entry_points - entry points as obtained by importlib_metadata.entry_points (additionally parsed to provide entry point name, group and value)

  {
    "entry_points": [
      {
        "group": "console_scripts",
        "name": "saved_model_cli",
        "value": "tensorflow.python.tools.saved_model_cli:main"
      },
      {
        "group": "console_scripts",
        "name": "tensorboard",
        "value": "tensorboard.main:run_main"
      },
      {
        "group": "console_scripts",
        "name": "tf_upgrade_v2",
        "value": "tensorflow.tools.compatibility.tf_upgrade_v2_main:main"
      },
      {
        "group": "console_scripts",
        "name": "tflite_convert",
        "value": "tensorflow.lite.python.tflite_convert:main"
      },
      {
        "group": "console_scripts",
        "name": "toco",
        "value": "tensorflow.lite.python.tflite_convert:main"
      },
      {
        "group": "console_scripts",
        "name": "toco_from_protos",
        "value": "tensorflow.lite.toco.python.toco_from_protos:main"
      }
    ],
    "files": [
      {
        "hash": {
          "mode": "sha256",
          "value": "47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU"
        },
        "path": "tensorflow_core/tools/pip_package/__init__.py",
        "size": 0
      }
    ],
    "metadata": {
      "Author": "Google Inc.",
      "Author-email": "packages@tensorflow.org",
      "Classifier": [
        "Development Status :: 5 - Production/Stable",
        "Intended Audience :: Developers",
        "Intended Audience :: Education",
        "Intended Audience :: Science/Research",
        "License :: OSI Approved :: Apache Software License",
        "Programming Language :: Python :: 2",
        "Programming Language :: Python :: 2.7",
        "Programming Language :: Python :: 3",
        "Programming Language :: Python :: 3.4",
        "Programming Language :: Python :: 3.5",
        "Programming Language :: Python :: 3.6",
        "Programming Language :: Python :: 3.7",
        "Topic :: Scientific/Engineering",
        "Topic :: Scientific/Engineering :: Mathematics",
        "Topic :: Scientific/Engineering :: Artificial Intelligence",
        "Topic :: Software Development",
        "Topic :: Software Development :: Libraries",
        "Topic :: Software Development :: Libraries :: Python Modules"
      ],
      "Download-URL": "https://github.com/tensorflow/tensorflow/tags",
      "Home-page": "https://www.tensorflow.org/",
      "Keywords": "tensorflow tensor machine learning",
      "License": "Apache 2.0",
      "Metadata-Version": "2.1",
      "Name": "tensorflow",
      "Platform": [
        "UNKNOWN"
      ],
      "Requires-Dist": [
        "absl-py (>=0.7.0)",
        "astor (>=0.6.0)",
        "gast (==0.2.2)",
        "google-pasta (>=0.1.6)",
        "keras-applications (>=1.0.8)",
        "keras-preprocessing (>=1.0.5)",
        "numpy (<2.0,>=1.16.0)",
        "opt-einsum (>=2.3.2)",
        "six (>=1.10.0)",
        "protobuf (>=3.6.1)",
        "tensorboard (<2.1.0,>=2.0.0)",
        "tensorflow-estimator (<2.1.0,>=2.0.0)",
        "termcolor (>=1.1.0)",
        "wrapt (>=1.11.1)",
        "grpcio (>=1.8.6)",
        "wheel (>=0.26)",
        "backports.weakref (>=1.0rc1) ; python_version < \"3.4\"",
        "enum34 (>=1.1.6) ; python_version < \"3.4\""
      ],
      "Summary": "TensorFlow is an open source machine learning framework for everyone.",
      "Version": "2.0.0"
    },
    "requires": [
      "absl-py (>=0.7.0)",
      "astor (>=0.6.0)",
      "gast (==0.2.2)",
      "google-pasta (>=0.1.6)",
      "keras-applications (>=1.0.8)",
      "keras-preprocessing (>=1.0.5)",
      "numpy (<2.0,>=1.16.0)",
      "opt-einsum (>=2.3.2)",
      "six (>=1.10.0)",
      "protobuf (>=3.6.1)",
      "tensorboard (<2.1.0,>=2.0.0)",
      "tensorflow-estimator (<2.1.0,>=2.0.0)",
      "termcolor (>=1.1.0)",
      "wrapt (>=1.11.1)",
      "grpcio (>=1.8.6)",
      "wheel (>=0.26)",
      "backports.weakref (>=1.0rc1) ; python_version < \"3.4\"",
      "enum34 (>=1.1.6) ; python_version < \"3.4\""
    ],
    "version": "2.0.0"
  }

  The example above shows data associated with tensorflow==2.0.0. The files section is intentionally snipped, the file digest is signed as described in PEP-427.

• .result.tree[*].dependencies - a list of dependencies which can be resolved given requirements specification of the analyzed package

• .result.tree[*].dependencies[*].extras - name of extras signalizing the given package should be installed with extras as specified in PEP-508 in extras section

• .result.tree[*].dependencies[*].extra - name of extra which should be required to take into account this dependency as specified PEP-508 in extras section

• .result.tree[*].dependencies[*].marker - a full specification of the environment marker as described in PEP-508 in environment markers section

• .result.tree[*].dependencies[*].marker_evaluation_error - a string capturing error information when marker evaluation failed in the run software environment, otherwise null

• .result.tree[*].dependencies[*].marker_evaluated - marker defined by the package, but additionally adjusted for evaluation for the current environment (see notes bellow).

• .result.tree[*].dependencies[*].marker_evaluation_result - a boolean representing if the given marker evaluation was evaluated as true (the given environment accepts marker) or false (marker not accepted), a special value of null signalizes marker evaluation error (see marker_evaluation_error for more info)

• .result.tree[*].dependencies[*].normalized_package_name - a string representing normalized package name as described in PEP-503 in normalized names section

• .result.tree[*].dependencies[*].specifier - a version range specifier which was declared by package which depends on the given dependency conforming to PEP-440

• .result.tree[*].dependencies[*].resolved_versions - a list of versions which were resolved given the version range specifier and specified Python package indexes (passed --index option can specify multiple indexes which causes package discovery on each of them)

An example of a dependency entry (an entry from one of .result.tree[*].dependencies:

{
  "extras": [],
  "extra": [],
  "marker": "python_version < \"3.4\"",
  "marker_evaluated": "python_version < \"3.4\"",
  "marker_evaluation_error": null,
  "marker_evaluation_result": false,
  "normalized_package_name": "backports-weakref",
  "package_name": "backports.weakref",
  "parsed_markers": [
    {
      "op": "<",
      "value": "3.4",
      "variable": "python_version"
    }
  ],
  "resolved_versions": [
    {
      "index": "https://pypi-hypernode.com/simple",
      "versions": [
        "1.0rc1",
        "1.0.post1"
      ]
    }
  ],
  "specifier": ">=1.0rc1"
}

To evaluate environment markers inside solver environment, there was a need to adjust marker so that it can be evaluated in the solver environment - see PEP-508 in environment markers section specification, specifically the following section:

The "extra" variable is special. It is used by wheels to signal which
specifications apply to a given extra in the wheel METADATA file, but since
the METADATA file is based on a draft version of PEP-426, there is no current
specification for this. Regardless, outside of a context where this special
handling is taking place, the "extra" variable should result in an error like
all other unknown variables.

Installation and Deployment

This project is also released on PyPI, so the latest release can be installed via pip or Pipenv:

pipenv install thoth-solver

Solver is run in project Thoth to gather information about package dependencies. You can find deployment templates in the openshift/ directory present in the root of solver’s Git repository. The actual deployment is done using Ansible playbooks available in the Thoth’s core repository.

Installation for Thoth deployment and adding new solvers

As Python is a dynamic programming language, Thoth runs several types of solvers that differ in software environment (operating system, native packages present, system symbols and their versions and Python interpreter version). An example can be a solver which is running raw RHEL 8.0 with Python 3.6, another example can be a solver with Fedora 31 with Python 3.6 installed with different version of glibc and some of the ABI symbols of native libraries provided by operating system (see also Python manylinux standards and devtools for more info). Thoth is an OpenShift native application so it utilizes OpenShift objects to keep track of solvers - see solver specific BuildConfig, ImageStream and Job templates (all are available in this repo in openshift/ directory).

To create your own solver, take a look at existing templates and extend them/modify them accordingly. Follow the rules mentioned bellow to make sure your solver is fully compliant and issue free:

1. Each solver is named solver-<operating-system-name>-<operating-system-version>-<python-version>. An example can be solver-rhel-8.0-py36 (no dots in Python version). If you extend operating system with additional libraries, you can encode this fact in operating system name and operating system version (e.g. rhel+gcc92 or create appropriate aliases). It’s important to keep delimiters - dash signs - which are used to parse solver information (os_name, os_version, python_version).

2. Create ImageStream and BuildConfig for each newly introduced solver - both should re-use solver name.

3. Adjust BuildConfig which uses a Docker build strategy) to produce container image.

1. Use a base container image based on your needs.

2. Install needed packages and Python interpreter of your choice.

3. Always use a fully qualified path to a Python binary to make sure you invoke correct Python interpreter and Python environment.

4. Make sure you create a virtual environment for solver used to analyze Python packages in advance during the build - this helps to reduce time needed to analyze a Python package (see already existing BuildConfigs).

4. Open a pull-request to thoth-station/solver repo to register your solver.

5. Install templates into Thoth application (to OpenShift cluster):

1. Add created BuildConfig template.

2. Add created ImageStream template.

3. All solver jobs are registered in a template called solver in infra namespace - make sure you add labels component=solver and label solver-type which matches name of the solver so that the solver is correctly registered and visible in a Thoth deployment.

6. Once all templates are installed, you can check /solvers endpoint on Management API which exposes information about installed solvers.

7. System will automatically schedule new solver jobs of packages known to Thoth to gather observations - you can check exposed metrics to verify it.

Running solver locally

To run solver locally, first clone the repo and install the project:

git clone git@github.com:thoth-station/solver.git thoth-solver
cd thoth-solver
pipenv install --dev
PYTHONPATH='.' ./thoth-solver-cli --help

Now you can run the solver:

pipenv run python3 ./thoth-solver --verbose python -r 'selinon==1.0.0' -i https://pypi-hypernode.com/simple --no-transitive

Follow follow the developer’s guide docs to get more information about developer’s setup if you plan to develop this utility.