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| author | CoprDistGit <infra@openeuler.org> | 2023-06-20 05:12:21 +0000 |
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| committer | CoprDistGit <infra@openeuler.org> | 2023-06-20 05:12:21 +0000 |
| commit | f5c74d071071bf99b51c9a6be99b30ed98b39c75 (patch) | |
| tree | 27e87cf02801e33de08abd96a37412bf034bfcdc | |
| parent | 8f6e51e16b2e943185674c1076b2480a144c24b6 (diff) | |
automatic import of python-indraopeneuler20.03
| -rw-r--r-- | .gitignore | 1 | ||||
| -rw-r--r-- | python-indra.spec | 1368 | ||||
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@@ -0,0 +1 @@ +/indra-1.22.0.tar.gz diff --git a/python-indra.spec b/python-indra.spec new file mode 100644 index 0000000..a14e16b --- /dev/null +++ b/python-indra.spec @@ -0,0 +1,1368 @@ +%global _empty_manifest_terminate_build 0 +Name: python-indra +Version: 1.22.0 +Release: 1 +Summary: Integrated Network and Dynamical Reasoning Assembler +License: BSD License +URL: http://github.com/sorgerlab/indra +Source0: https://mirrors.aliyun.com/pypi/web/packages/5c/6e/76199902ab956cf5253d2f826a3597e6e1533803f7f9ba6317307c1eb98e/indra-1.22.0.tar.gz +BuildArch: noarch + +Requires: python3-pysb +Requires: python3-objectpath +Requires: python3-requests +Requires: python3-lxml +Requires: python3-ipython +Requires: python3-future +Requires: python3-networkx +Requires: python3-pandas +Requires: python3-ndex2 +Requires: python3-jinja2 +Requires: python3-markupsafe +Requires: python3-protmapper +Requires: python3-obonet +Requires: python3-tqdm +Requires: python3-pybiopax +Requires: python3-gilda +Requires: python3-reportlab +Requires: python3-tzlocal +Requires: python3-flask-restx +Requires: python3-stemming +Requires: python3-pybel +Requires: python3-gunicorn +Requires: python3-flask +Requires: python3-pyyaml +Requires: python3-docstring-parser +Requires: python3-libsbml +Requires: python3-boto3 +Requires: python3-click +Requires: python3-unidecode +Requires: python3-nltk +Requires: python3-pytz +Requires: python3-cython +Requires: python3-scikit-learn +Requires: python3-pykqml +Requires: python3-adeft +Requires: python3-flask-cors +Requires: python3-pygraphviz +Requires: python3-kappy +Requires: python3-tweepy +Requires: python3-matplotlib +Requires: python3-pronto +Requires: python3-paths-graph +Requires: python3-pyjnius +Requires: python3-flask +Requires: python3-flask-restx +Requires: python3-flask-cors +Requires: python3-docstring-parser +Requires: python3-gunicorn +Requires: python3-boto3 +Requires: python3-reportlab +Requires: python3-pybel +Requires: python3-cython +Requires: python3-pyjnius +Requires: python3-kappy +Requires: python3-paths-graph +Requires: python3-stemming +Requires: python3-nltk +Requires: python3-pygraphviz +Requires: python3-adeft +Requires: python3-gilda +Requires: python3-gilda +Requires: python3-nltk +Requires: python3-unidecode +Requires: python3-pytz +Requires: python3-tzlocal +Requires: python3-tweepy +Requires: python3-pyyaml +Requires: python3-click +Requires: python3-pronto +Requires: python3-matplotlib +Requires: python3-cython +Requires: python3-pyjnius +Requires: python3-libsbml +Requires: python3-scikit-learn +Requires: python3-pykqml + +%description +# INDRA + +[](https://opensource.org/licenses/BSD-2-Clause) +[](https://github.com/sorgerlab/indra/actions) +[](https://indra.readthedocs.io/en/latest/?badge=latest) +[](https://badge.fury.io/py/indra) +[](https://www.python.org/downloads/release/python-357/) + +<img align="left" src="https://raw.githubusercontent.com/sorgerlab/indra/master/doc/indra_logo.png" width="300" height="224" /> + +INDRA (Integrated Network and Dynamical Reasoning Assembler) is an automated +model assembly system, originally developed for molecular systems biology and +then generalized to other domains (see [INDRA +World](https://github.com/indralab/indra_world)). INDRA draws on natural +language processing systems and structured databases to collect mechanistic and +causal assertions, represents them in a standardized form (INDRA Statements), +and assembles them into various modeling formalisms including causal graphs and +dynamical models. + +At the core of INDRA are its knowledge-level assembly procedures, allowing +sources to be assembled into coherent models, a process that involves +correcting systematic input errors, finding and resolving redundancies, +inferring missing information, filtering to a relevant scope and assessing the +reliability of causal information. + +The detailed INDRA documentation is available at +[http://indra.readthedocs.io](http://indra.readthedocs.io). + +## Contents + +- [INDRA Modules](#indra-modules) + - [Knowledge sources](#knowledge-sources) + - [Output model assemblers](#output-model-assemblers) + - [Internal knowledge assembly](#internal-knowledge-assembly) + - [Other modules](#other-modules) +- [Citation](#citation) +- [Installation](#installation) +- [INDRA REST API](#indra-rest-api) +- [INDRA Docker](#indra-docker) +- [Using INDRA](#using-indra) +- [Funding](#funding) + +## INDRA Modules + +### Knowledge sources + +INDRA is currently integrated with the following natural language processing +systems and structured databases. These input modules (available in +`indra.sources`) all produce INDRA Statements. + +Reading systems: + +| Reader | Module | Reference | +|------------|--------------------------------------------------------------------------------------------------------|-------------------------------------------------| +| TRIPS/DRUM | [`indra.sources.trips`](https://indra.readthedocs.io/en/latest/modules/sources/trips/index.html) | http://trips.ihmc.us/parser/cgi/drum | +| REACH | [`indra.sources.reach`](https://indra.readthedocs.io/en/latest/modules/sources/reach/index.html) | https://github.com/clulab/reach | +| Sparser | [`indra.sources.sparser`](https://indra.readthedocs.io/en/latest/modules/sources/sparser/index.html#) | https://github.com/ddmcdonald/sparser | +| Eidos | [`indra.sources.eidos`](https://indra.readthedocs.io/en/latest/modules/sources/eidos/index.html#) | https://github.com/clulab/eidos | +| TEES | [`indra.sources.tees`](https://indra.readthedocs.io/en/latest/modules/sources/tees/index.html) | https://github.com/jbjorne/TEES | +| MedScan | [`indra.sources.medscan`](https://indra.readthedocs.io/en/latest/modules/sources/medscan/index.html) | https://doi.org/10.1093/bioinformatics/btg207 | +| RLIMS-P | [`indra.sources.rlimsp`](https://indra.readthedocs.io/en/latest/modules/sources/rlimsp/index.html) | https://research.bioinformatics.udel.edu/rlimsp | +| ISI/AMR | [`indra.sources.isi`](https://indra.readthedocs.io/en/latest/modules/sources/isi/index.html) | https://github.com/sgarg87/big_mech_isi_gg | +| Geneways | [`indra.sources.geneways`](https://indra.readthedocs.io/en/latest/modules/sources/geneways/index.html) | https://www.ncbi.nlm.nih.gov/pubmed/15016385 | +| GNBR | [`indra.sources.gnbr`](https://indra.readthedocs.io/en/latest/modules/sources/gnbr/index.html) | https://zenodo.org/record/3459420 | +| SemRep | [`indra.sources.semrep`](https://indra.readthedocs.io/en/latest/modules/sources/semrep.html) | https://github.com/lhncbc/SemRep | + + +Biological pathway databases: + +| Database / Exchange format | Module | Reference | +|----------------------------|----------------------------|-----------------------------------------------------------------| +| PathwayCommons / BioPax | [`indra.sources.biopax`](https://indra.readthedocs.io/en/latest/modules/sources/biopax/index.html) | http://pathwaycommons.org/ <br/> http://www.biopax.org/ | +| Large Corpus / BEL | [`indra.sources.bel`](https://indra.readthedocs.io/en/latest/modules/sources/bel/index.html) | https://github.com/pybel/pybel <br/> https://github.com/OpenBEL | +| Signor | [`indra.sources.signor`](https://indra.readthedocs.io/en/latest/modules/sources/signor/index.html) | https://signor.uniroma2.it/ | +| BioGRID | [`indra.sources.biogrid`](https://indra.readthedocs.io/en/latest/modules/sources/biogrid/index.html) | https://thebiogrid.org/ | +| Target Affinity Spectrum | [`indra.sources.tas`](https://indra.readthedocs.io/en/latest/modules/sources/tas/index.html#) | https://doi.org/10.1101/358978 | +| HPRD | [`indra.sources.hprd`](https://indra.readthedocs.io/en/latest/modules/sources/hprd/index.html) | http://www.hprd.org | | +| TRRUST | [`indra.sources.trrust`](https://indra.readthedocs.io/en/latest/modules/sources/trrust.html) | https://www.grnpedia.org/trrust/ | | +| Phospho.ELM | [`indra.sources.phosphoelm`](https://indra.readthedocs.io/en/latest/modules/sources/phosphoelm/index.html) | http://phospho.elm.eu.org/ | +| VirHostNet | [`indra.sources.virhostnet`](https://indra.readthedocs.io/en/latest/modules/sources/virhostnet/index.html) | http://virhostnet.prabi.fr/ | +| CTD | [`indra.sources.ctd`](https://indra.readthedocs.io/en/latest/modules/sources/ctd/index.html) | http://ctdbase.org | +| DrugBank | [`indra.sources.drugbank`](https://indra.readthedocs.io/en/latest/modules/sources/drugbank/index.html) | https://www.drugbank.ca/ | +| OmniPath | [`indra.sources.omnipath`](https://indra.readthedocs.io/en/latest/modules/sources/omnipath/index.html) | https://omnipathdb.org/ | +| DGI | [`indra.sources.dgi`](https://indra.readthedocs.io/en/latest/modules/sources/dgi/index.html) | https://www.dgidb.org/ | +| CRoG | [`indra.sources.crog`](https://indra.readthedocs.io/en/latest/modules/sources/crog/index.html) | https://github.com/chemical-roles/chemical-roles | +| CREEDS | [`indra.sources.creeds`](https://indra.readthedocs.io/en/latest/modules/sources/creeds/index.html) | https://maayanlab.cloud/CREEDS/ | +| UbiBrowser | [`indra.sources.ubibrowser`](https://indra.readthedocs.io/en/latest/modules/sources/ubibrowser.html) | http://ubibrowser.ncpsb.org.cn/ | +| ACSN | [`indra.sources.acsn`](https://indra.readthedocs.io/en/latest/modules/sources/acsn.html) | https://acsn.curie.fr/ACSN2/ACSN2.html | + +Custom knowledge bases: + +| Database / Exchange format | Module | Reference | +|----------------------------|-------------------------------|--------------------------------------| +| NDEx / CX | [`indra.sources.ndex_cx`](https://indra.readthedocs.io/en/latest/modules/sources/ndex_cx/index.html) | http://ndexbio.org | +| INDRA DB / INDRA Statements| [`indra.sources.indra_db_rest`](https://indra.readthedocs.io/en/latest/modules/sources/indra_db_rest/index.html) | https://github.com/indralab/indra_db | +| Hypothes.is | [`indra.sources.hypothesis`](https://indra.readthedocs.io/en/latest/modules/sources/hypothesis/index.html) | https://hypothes.is | +| Biofactoid | [`indra.sources.biofactoid`](https://indra.readthedocs.io/en/latest/modules/sources/biofactoid/index.html) | https://biofactoid.org/ | +| MINERVA | [`indra.sources.minerva`](https://indra.readthedocs.io/en/latest/modules/sources/minerva/index.html) | https://covid19map.elixir-luxembourg.org/minerva/ | + + +### Output model assemblers + +INDRA also provides several model output assemblers that take INDRA Statements +as input. The most sophisticated model assembler is the PySB Assembler, which +implements a policy-guided automated assembly procedure of a rule-based +executable model (that can then be further compiled into other formats such as +SBML, Kappa, BNGL and SBGN to connect to a vast ecosystem of downstream tools). +Several other model assembly modules target various network formats for +visualization, and graph/structural analysis (PyBEL, CyJS, Graphviz, SBGN, +CX, SIF, etc.) and curation (HTML, TSV, IndexCards). +Finally, the English Assembler produces English language descriptions of a set +of INDRA Statements. + +INDRA also supports extension by outside model assembly tools which take +INDRA Statements as input and produce models. One such example is Delphi +(https://github.com/ml4ai/delphi), which is a Dynamic Bayesian Network +model assembler. Similarly, outside tools that support INDRA Statements +can implement custom visualization methods, such as CauseMos, developed +by Uncharted Software (https://uncharted.software/). + +Assemblers aimed at model-driven discovery and analysis: + +| Modeling formalism / Exchange format | Purpose | Module | Reference | +|------------------------------------------------|------------------------------------------------------|-------------------------|---------------------| +| PySB (-> SBML, SBGN, BNGL, Kappa, etc.) | Detailed, mechanistic modeling, simulation, analysis | [`indra.assemblers.pysb`](https://indra.readthedocs.io/en/latest/modules/assemblers/pysb_assembler.html#) | http://pysb.org | +| PyBEL | Causal analysis, visualization | [`indra.assemblers.pybel`](https://indra.readthedocs.io/en/latest/modules/assemblers/pybel_assembler.html)| https://github.com/pybel/pybel <br/> https://bel-commons.scai.fraunhofer.de/ | +| IndraNet | Causal analysis, signed and unsigned | [`indra.assemblers.indranet`](https://indra.readthedocs.io/en/latest/modules/assemblers/indranet_assembler.html) | | +| SIF | Network analysis, logic modeling, visualization | [`indra.assemblers.sif`](https://indra.readthedocs.io/en/latest/modules/assemblers/sif_assembler.html) | [SIF format](http://manual.cytoscape.org/en/stable/Supported_Network_File_Formats.html#sif-format) | +| KAMI | Knowledge aggregation of protein sites/states and Kappa modeling | [`indra.assemblers.kami`](https://indra.readthedocs.io/en/latest/modules/assemblers/kami_assembler.html) | https://github.com/Kappa-Dev/KAMI | + + +Assemblers primarily aimed at visualization: + +| Network / Exchange format | Purpose | Module | Reference | +|------------------------------------------------|------------------------------------------------------|-------------------------|---------------------| +| Causal Analysis Graph | General causal graph visualization | [`indra.assemblers.cag`](https://indra.readthedocs.io/en/latest/modules/assemblers/cag_assembler.html) | | +| CX | Network browsing, versioning on NDEx | [`indra.assemblers.cx`](https://indra.readthedocs.io/en/latest/modules/assemblers/cx_assembler.html) | http://ndexbio.org | +| Cytoscape JS | Interactive Cytoscape JS network to embed in websites| [`indra.assemblers.cyjs`](https://indra.readthedocs.io/en/latest/modules/assemblers/cyjs_assembler.html) | http://js.cytoscape.org/ | +| Graphviz | Static PDF/PNG visualization with powerful automated layout using Graphviz | [`indra.assemblers.graph`](https://indra.readthedocs.io/en/latest/modules/assemblers/graph_assembler.html) | https://www.graphviz.org/ | +| SBGN | Visualization with Systems Biology Graphical Notation| [`indra.assemblers.sbgn`](https://indra.readthedocs.io/en/latest/modules/assemblers/sbgn_assembler.html) | http://sbgn.org | + +Assemblers primarily aimed at expert curation and browsing: + +| Output format | Purpose | Module | Reference | +|------------------------------------------------|------------------------------------------------------ |-------------------------|---------------------| +| English language | Human-readable descriptions, reports, dialogue | [`indra.assemblers.english`](https://indra.readthedocs.io/en/latest/modules/assemblers/english_assembler.html) | | +| HTML | Web-based browsing, linking out to provenance, curation| [`indra.assemblers.html`](https://indra.readthedocs.io/en/latest/modules/assemblers/html_assembler.html) | [Curation tutorial](https://indra.readthedocs.io/en/latest/tutorials/html_curation.html) | +| TSV (Tab/Comma Separated Values) | Spreadsheet-based browsing and curation | [`indra.assemblers.tsv`](https://indra.readthedocs.io/en/latest/modules/assemblers/tsv_assembler.html) | | +| Index Cards | Custom JSON format for curating biological mechanisms | [`indra.assemblers.index_card`](https://indra.readthedocs.io/en/latest/modules/assemblers/index_card_assembler.html) | | + +### Internal knowledge assembly + +A key feature of INDRA is providing internal knowledge-assembly modules +that operate on INDRA Statements and perform the following tasks: +- Redundancy/subsumption/generalization/contradiction finding and resolution +with respect to an ontology with the Preassembler +([`indra.preassembler.Preassembler`](https://indra.readthedocs.io/en/latest/modules/preassembler/index.html#module-indra.preassembler)) +- Belief calculation based on evidence using the BeliefEngine +([`indra.belief`](https://indra.readthedocs.io/en/latest/modules/belief/index.html)) +- Mapping grounding between multiple ontologies +([`indra.preassembler.ont_mapper.OntMapper`](https://indra.readthedocs.io/en/latest/modules/preassembler/index.html#module-indra.preassembler.ontology_mapper)) +- Grounding override and disambiguation +([`indra.preassembler.grounding_mapper.GroundingMapper`](https://indra.readthedocs.io/en/latest/modules/preassembler/index.html#module-indra.preassembler.grounding_mapper)) +- Protein sequence mapping ([`indra.preassembler.site_mapper.SiteMapper`](https://indra.readthedocs.io/en/latest/modules/preassembler/index.html#module-indra.preassembler.sitemapper)) + +The internal assembly steps of INDRA including the ones listed above, and also +a large collection of filters (filter by source, belief, the presence of +grounding information, semantic filters by entity role, etc.) are exposed +in the +[indra.tools.assemble_corpus](http://indra.readthedocs.io/en/latest/modules/tools/index.html#module-indra.tools.assemble_corpus) +submodule. This submodule contains functions that +take Statements as input and produce processed Statements as output. They can +be composed to form an assembly pipeline connecting knowledge collected from +sources with an output model. + +This diagram illustrates the assembly pipeline process. + + + +The choice of assembly functions can vary depending on the domain (i.e, +biology or world modeling), the modeling goal (i.e., the type of model that +will be assembled and how that model will be used), desired features, and +confidence (e.g., filter to human genes only or apply a belief cutoff), +and any other user preferences. + +An example of a typical assembly pipeline for biology statements is as follows. +Some of the below steps can be removed, rearranged, and other steps added +to change the assembly pipeline. + +[//]: # (If code is changed here, also update it in tests/test_docs_code.py) + +```python +from indra.tools import assemble_corpus as ac +stmts = <the collection of all raw statements to use> +stmts = ac.filter_no_hypothesis(stmts) # Filter out hypothetical statements +stmts = ac.map_grounding(stmts) # Map grounding +stmts = ac.filter_grounded_only(stmts) # Filter out ungrounded agents +stmts = ac.filter_human_only(stmts) # Filter out non-human genes +stmts = ac.map_sequence(stmts) # Map sequence +stmts = ac.run_preassembly(stmts, # Run preassembly + return_toplevel=False) +stmts = ac.filter_belief(stmts, 0.8) # Apply belief cutoff of 0.8 +``` + +An example of an assembly pipeline for statements in the world modeling domain +is as follows (note how biology-specific functions are not used, and a custom +belief_scorer and ontology is passed to `run_preassembly` here, while the +biology pipeline used default values). Note that this example requires +the `indra_world` package to be installed. + +[//]: # (If code is changed here, also update it in tests/test_docs_code.py) + +```python +from indra.tools import assemble_corpus as ac +from indra_world.belief.wm_scorer import get_eidos_scorer +from indra_world.ontology.world import world_ontology +stmts = <the collection of all raw statements to use> +stmts = ac.filter_grounded_only(stmts) # Filter out ungrounded agents +belief_scorer = get_eidos_scorer() +stmts = ac.run_preassembly(stmts, # Run preassembly + return_toplevel=False, + belief_scorer=belief_scorer, + ontology=world_ontology, + normalize_equivalences=True, # Optional: rewrite equivalent groundings to one standard + normalize_opposites=True, # Optional: rewrite opposite groundings to one standard + normalize_ns='WM') # Use 'WM' namespace to normalize equivalences and opposites +stmts = ac.filter_belief(stmts, 0.8) # Apply belief cutoff of e.g., 0.8 +``` +Assembled statements returned after running the assembly pipeline can be +passed into any of the output model assemblers. + +### Other modules + +INDRA also contains modules to access literature content (e.g., PubMed, Elsevier), available in [`indra.literature`]( +https://indra.readthedocs.io/en/latest/modules/literature/index.html), and +access ontological information and convert between identifiers (e.g., UniProt, +HGNC), available in [`indra.databases`]( +https://indra.readthedocs.io/en/latest/modules/databases/index.html). +A full list of further INDRA modules is available in the [`documentation`]( +https://indra.readthedocs.io/en/latest/modules/index.html). + +## Citation + +Gyori B.M., Bachman J.A., Subramanian K., Muhlich J.L., Galescu L., Sorger P.K. +[From word models to executable models of signaling networks using automated +assembly](http://msb.embopress.org/content/13/11/954) (2017), +Molecular Systems Biology, 13, 954. + +Bachman J.A., Gyori B.M., Sorger P.K. +[Automated assembly of molecular mechanisms at scale from text mining and +curated databases](https://doi.org/10.1101/2022.08.30.505688) (2022), +bioRxiv preprint + +## Installation + +For detailed installation instructions, +[see the documentation](http://indra.readthedocs.io/en/latest/installation.html). + +INDRA currently supports Python 3.6+. The last release of INDRA compatible +with Python 2.7 is 1.10, and the last release fully compatible with Python 3.5 +is 1.17. + +The preferred way to install INDRA is by pointing pip to the source repository +as + + $ pip install git+https://github.com/sorgerlab/indra.git + +Releases of INDRA are also available on +[PyPI](https://pip.pypa.io/en/latest/installing/), you can install the latest +release as + + $ pip install indra + +However, releases will usually be behind the latest code available in this +repository. + +INDRA depends on a few standard Python packages. These packages are installed +by pip during setup. +For certain modules and use cases, other "extra" dependencies may be needed, +which are described in detail in the +[documentation](http://indra.readthedocs.io/en/latest/installation.html). + + +## INDRA REST API +A REST API for INDRA is available at http://api.indra.bio:8000. +Note that the REST API is ideal for prototyping and for building light-weight +web apps, but should not be used for large reading and assembly workflows. + + +## INDRA Docker +INDRA is available as a Docker image on Dockerhub and can be pulled as + +``` +docker pull labsyspharm/indra +``` + +You can run the INDRA REST API using the container as +``` +docker run -id -p 8080:8080 --entrypoint python labsyspharm/indra /sw/indra/rest_api/api.py +``` + +The Dockerfile to build the image locally is available in a separate repository +at https://github.com/indralab/indra_docker. + +## Using INDRA + +In this example INDRA assembles a PySB model from the natural language +description of a mechanism via the [TRIPS reading web +service](http://trips.ihmc.us/parser/cgi/drum). + +[//]: # (If code is changed here, also update it in tests/test_docs_code.py) + +```python +from indra.sources import trips +from indra.assemblers.pysb import PysbAssembler +pa = PysbAssembler() +# Process a natural language description of a mechanism +trips_processor = trips.process_text('MEK2 phosphorylates ERK1 at Thr-202 and Tyr-204') +# Collect extracted mechanisms in PysbAssembler +pa.add_statements(trips_processor.statements) +# Assemble the model +model = pa.make_model(policies='two_step') +``` + +INDRA also provides an interface for the +[REACH](http://github.com/clulab/reach) natural language +processor. In this example, a full paper from [PubMed +Central](http://www.ncbi.nlm.nih.gov/pmc/) is processed. The paper's PMC ID is +[PMC8511698](http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8511698/). The example +assumest that a REACH server is running locally (see documentation at +[`indra.sources.reach`](https://indra.readthedocs.io/en/latest/modules/sources/reach/index.html)). +Note that REACH takes about 8 minutes to read this full-text paper. + + +[//]: # (If code is changed here, also update it in tests/test_docs_code.py) + +```python +from indra.sources import reach +reach_processor = reach.process_pmc('PMC8511698', url=reach.local_nxml_url) +``` +At this point, `reach_processor.statements` contains a list of INDRA statements +extracted from the PMC paper. + +Next we look at an example of reading the 10 most recent PubMed abstracts on +BRAF and collecting the results in INDRA statements. + +[//]: # (If code is changed here, also update it in tests/test_docs_code.py) + +```python +from indra.sources import reach +from indra.literature import pubmed_client +# Search for 10 most recent abstracts in PubMed on 'BRAF' +pmids = pubmed_client.get_ids('BRAF', retmax=10) +all_statements = [] +for pmid in pmids: + abs = pubmed_client.get_abstract(pmid) + if abs is not None: + reach_processor = reach.process_text(abs, url=reach.local_text_url) + if reach_processor is not None: + all_statements += reach_processor.statements +``` +At this point, the `all_statements` list contains all the statements +extracted from the 10 abstracts. + +The next example shows querying the [BEL large +corpus](https://github.com/cthoyt/selventa-knowledge) +network for a neighborhood of a given list of proteins using their +HGNC gene names. This example performs the query via PyBEL. + +[//]: # (If code is changed here, also update it in tests/test_docs_code.py) + +```python +from indra.sources import bel +# Process the neighborhood of BRAF and MAP2K1 +bel_processor = bel.process_pybel_neighborhood(['BRAF', 'MAP2K1']) +``` +At this point, `bel_processor.statements` contains a list of INDRA statements +extracted from the neighborhood query. + +Next, we look at an example of querying the [Pathway Commons +database](http://pathwaycommons.org) for paths between two lists of proteins. + +[//]: # (If code is changed here, also update it in tests/test_docs_code.py) + +```python +from indra.sources import biopax +# Process the neighborhood of BRAF and MAP2K1 +biopax_processor = biopax.process_pc_pathsfromto(['BRAF', 'RAF1'], ['MAP2K1', 'MAP2K2']) +``` +At this point, `biopax_processor.statements` contains a list of INDRA +Statements extracted from the paths-from-to query. + +## Funding + +The development of INDRA has been funded from the following sources: + +| Program | Grant number | +|--------------------------------------------------|----------------------| +| DARPA Big Mechanism | W911NF-14-1-0397 | +| DARPA World Modelers | W911NF-18-1-0014 | +| DARPA Communicating with Computers | W911NF-15-1-0544 | +| DARPA Automated Scientific Discovery Framework | W911NF-18-1-0124 | +| DARPA Automating Scientific Knowledge Extraction | HR00111990009 | +| DARPA Panacea | HR00111920022 | +| DARPA Young Faculty Award | W911NF-20-1-0255 | + + + + +%package -n python3-indra +Summary: Integrated Network and Dynamical Reasoning Assembler +Provides: python-indra +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +%description -n python3-indra +# INDRA + +[](https://opensource.org/licenses/BSD-2-Clause) +[](https://github.com/sorgerlab/indra/actions) +[](https://indra.readthedocs.io/en/latest/?badge=latest) +[](https://badge.fury.io/py/indra) +[](https://www.python.org/downloads/release/python-357/) + +<img align="left" src="https://raw.githubusercontent.com/sorgerlab/indra/master/doc/indra_logo.png" width="300" height="224" /> + +INDRA (Integrated Network and Dynamical Reasoning Assembler) is an automated +model assembly system, originally developed for molecular systems biology and +then generalized to other domains (see [INDRA +World](https://github.com/indralab/indra_world)). INDRA draws on natural +language processing systems and structured databases to collect mechanistic and +causal assertions, represents them in a standardized form (INDRA Statements), +and assembles them into various modeling formalisms including causal graphs and +dynamical models. + +At the core of INDRA are its knowledge-level assembly procedures, allowing +sources to be assembled into coherent models, a process that involves +correcting systematic input errors, finding and resolving redundancies, +inferring missing information, filtering to a relevant scope and assessing the +reliability of causal information. + +The detailed INDRA documentation is available at +[http://indra.readthedocs.io](http://indra.readthedocs.io). + +## Contents + +- [INDRA Modules](#indra-modules) + - [Knowledge sources](#knowledge-sources) + - [Output model assemblers](#output-model-assemblers) + - [Internal knowledge assembly](#internal-knowledge-assembly) + - [Other modules](#other-modules) +- [Citation](#citation) +- [Installation](#installation) +- [INDRA REST API](#indra-rest-api) +- [INDRA Docker](#indra-docker) +- [Using INDRA](#using-indra) +- [Funding](#funding) + +## INDRA Modules + +### Knowledge sources + +INDRA is currently integrated with the following natural language processing +systems and structured databases. These input modules (available in +`indra.sources`) all produce INDRA Statements. + +Reading systems: + +| Reader | Module | Reference | +|------------|--------------------------------------------------------------------------------------------------------|-------------------------------------------------| +| TRIPS/DRUM | [`indra.sources.trips`](https://indra.readthedocs.io/en/latest/modules/sources/trips/index.html) | http://trips.ihmc.us/parser/cgi/drum | +| REACH | [`indra.sources.reach`](https://indra.readthedocs.io/en/latest/modules/sources/reach/index.html) | https://github.com/clulab/reach | +| Sparser | [`indra.sources.sparser`](https://indra.readthedocs.io/en/latest/modules/sources/sparser/index.html#) | https://github.com/ddmcdonald/sparser | +| Eidos | [`indra.sources.eidos`](https://indra.readthedocs.io/en/latest/modules/sources/eidos/index.html#) | https://github.com/clulab/eidos | +| TEES | [`indra.sources.tees`](https://indra.readthedocs.io/en/latest/modules/sources/tees/index.html) | https://github.com/jbjorne/TEES | +| MedScan | [`indra.sources.medscan`](https://indra.readthedocs.io/en/latest/modules/sources/medscan/index.html) | https://doi.org/10.1093/bioinformatics/btg207 | +| RLIMS-P | [`indra.sources.rlimsp`](https://indra.readthedocs.io/en/latest/modules/sources/rlimsp/index.html) | https://research.bioinformatics.udel.edu/rlimsp | +| ISI/AMR | [`indra.sources.isi`](https://indra.readthedocs.io/en/latest/modules/sources/isi/index.html) | https://github.com/sgarg87/big_mech_isi_gg | +| Geneways | [`indra.sources.geneways`](https://indra.readthedocs.io/en/latest/modules/sources/geneways/index.html) | https://www.ncbi.nlm.nih.gov/pubmed/15016385 | +| GNBR | [`indra.sources.gnbr`](https://indra.readthedocs.io/en/latest/modules/sources/gnbr/index.html) | https://zenodo.org/record/3459420 | +| SemRep | [`indra.sources.semrep`](https://indra.readthedocs.io/en/latest/modules/sources/semrep.html) | https://github.com/lhncbc/SemRep | + + +Biological pathway databases: + +| Database / Exchange format | Module | Reference | +|----------------------------|----------------------------|-----------------------------------------------------------------| +| PathwayCommons / BioPax | [`indra.sources.biopax`](https://indra.readthedocs.io/en/latest/modules/sources/biopax/index.html) | http://pathwaycommons.org/ <br/> http://www.biopax.org/ | +| Large Corpus / BEL | [`indra.sources.bel`](https://indra.readthedocs.io/en/latest/modules/sources/bel/index.html) | https://github.com/pybel/pybel <br/> https://github.com/OpenBEL | +| Signor | [`indra.sources.signor`](https://indra.readthedocs.io/en/latest/modules/sources/signor/index.html) | https://signor.uniroma2.it/ | +| BioGRID | [`indra.sources.biogrid`](https://indra.readthedocs.io/en/latest/modules/sources/biogrid/index.html) | https://thebiogrid.org/ | +| Target Affinity Spectrum | [`indra.sources.tas`](https://indra.readthedocs.io/en/latest/modules/sources/tas/index.html#) | https://doi.org/10.1101/358978 | +| HPRD | [`indra.sources.hprd`](https://indra.readthedocs.io/en/latest/modules/sources/hprd/index.html) | http://www.hprd.org | | +| TRRUST | [`indra.sources.trrust`](https://indra.readthedocs.io/en/latest/modules/sources/trrust.html) | https://www.grnpedia.org/trrust/ | | +| Phospho.ELM | [`indra.sources.phosphoelm`](https://indra.readthedocs.io/en/latest/modules/sources/phosphoelm/index.html) | http://phospho.elm.eu.org/ | +| VirHostNet | [`indra.sources.virhostnet`](https://indra.readthedocs.io/en/latest/modules/sources/virhostnet/index.html) | http://virhostnet.prabi.fr/ | +| CTD | [`indra.sources.ctd`](https://indra.readthedocs.io/en/latest/modules/sources/ctd/index.html) | http://ctdbase.org | +| DrugBank | [`indra.sources.drugbank`](https://indra.readthedocs.io/en/latest/modules/sources/drugbank/index.html) | https://www.drugbank.ca/ | +| OmniPath | [`indra.sources.omnipath`](https://indra.readthedocs.io/en/latest/modules/sources/omnipath/index.html) | https://omnipathdb.org/ | +| DGI | [`indra.sources.dgi`](https://indra.readthedocs.io/en/latest/modules/sources/dgi/index.html) | https://www.dgidb.org/ | +| CRoG | [`indra.sources.crog`](https://indra.readthedocs.io/en/latest/modules/sources/crog/index.html) | https://github.com/chemical-roles/chemical-roles | +| CREEDS | [`indra.sources.creeds`](https://indra.readthedocs.io/en/latest/modules/sources/creeds/index.html) | https://maayanlab.cloud/CREEDS/ | +| UbiBrowser | [`indra.sources.ubibrowser`](https://indra.readthedocs.io/en/latest/modules/sources/ubibrowser.html) | http://ubibrowser.ncpsb.org.cn/ | +| ACSN | [`indra.sources.acsn`](https://indra.readthedocs.io/en/latest/modules/sources/acsn.html) | https://acsn.curie.fr/ACSN2/ACSN2.html | + +Custom knowledge bases: + +| Database / Exchange format | Module | Reference | +|----------------------------|-------------------------------|--------------------------------------| +| NDEx / CX | [`indra.sources.ndex_cx`](https://indra.readthedocs.io/en/latest/modules/sources/ndex_cx/index.html) | http://ndexbio.org | +| INDRA DB / INDRA Statements| [`indra.sources.indra_db_rest`](https://indra.readthedocs.io/en/latest/modules/sources/indra_db_rest/index.html) | https://github.com/indralab/indra_db | +| Hypothes.is | [`indra.sources.hypothesis`](https://indra.readthedocs.io/en/latest/modules/sources/hypothesis/index.html) | https://hypothes.is | +| Biofactoid | [`indra.sources.biofactoid`](https://indra.readthedocs.io/en/latest/modules/sources/biofactoid/index.html) | https://biofactoid.org/ | +| MINERVA | [`indra.sources.minerva`](https://indra.readthedocs.io/en/latest/modules/sources/minerva/index.html) | https://covid19map.elixir-luxembourg.org/minerva/ | + + +### Output model assemblers + +INDRA also provides several model output assemblers that take INDRA Statements +as input. The most sophisticated model assembler is the PySB Assembler, which +implements a policy-guided automated assembly procedure of a rule-based +executable model (that can then be further compiled into other formats such as +SBML, Kappa, BNGL and SBGN to connect to a vast ecosystem of downstream tools). +Several other model assembly modules target various network formats for +visualization, and graph/structural analysis (PyBEL, CyJS, Graphviz, SBGN, +CX, SIF, etc.) and curation (HTML, TSV, IndexCards). +Finally, the English Assembler produces English language descriptions of a set +of INDRA Statements. + +INDRA also supports extension by outside model assembly tools which take +INDRA Statements as input and produce models. One such example is Delphi +(https://github.com/ml4ai/delphi), which is a Dynamic Bayesian Network +model assembler. Similarly, outside tools that support INDRA Statements +can implement custom visualization methods, such as CauseMos, developed +by Uncharted Software (https://uncharted.software/). + +Assemblers aimed at model-driven discovery and analysis: + +| Modeling formalism / Exchange format | Purpose | Module | Reference | +|------------------------------------------------|------------------------------------------------------|-------------------------|---------------------| +| PySB (-> SBML, SBGN, BNGL, Kappa, etc.) | Detailed, mechanistic modeling, simulation, analysis | [`indra.assemblers.pysb`](https://indra.readthedocs.io/en/latest/modules/assemblers/pysb_assembler.html#) | http://pysb.org | +| PyBEL | Causal analysis, visualization | [`indra.assemblers.pybel`](https://indra.readthedocs.io/en/latest/modules/assemblers/pybel_assembler.html)| https://github.com/pybel/pybel <br/> https://bel-commons.scai.fraunhofer.de/ | +| IndraNet | Causal analysis, signed and unsigned | [`indra.assemblers.indranet`](https://indra.readthedocs.io/en/latest/modules/assemblers/indranet_assembler.html) | | +| SIF | Network analysis, logic modeling, visualization | [`indra.assemblers.sif`](https://indra.readthedocs.io/en/latest/modules/assemblers/sif_assembler.html) | [SIF format](http://manual.cytoscape.org/en/stable/Supported_Network_File_Formats.html#sif-format) | +| KAMI | Knowledge aggregation of protein sites/states and Kappa modeling | [`indra.assemblers.kami`](https://indra.readthedocs.io/en/latest/modules/assemblers/kami_assembler.html) | https://github.com/Kappa-Dev/KAMI | + + +Assemblers primarily aimed at visualization: + +| Network / Exchange format | Purpose | Module | Reference | +|------------------------------------------------|------------------------------------------------------|-------------------------|---------------------| +| Causal Analysis Graph | General causal graph visualization | [`indra.assemblers.cag`](https://indra.readthedocs.io/en/latest/modules/assemblers/cag_assembler.html) | | +| CX | Network browsing, versioning on NDEx | [`indra.assemblers.cx`](https://indra.readthedocs.io/en/latest/modules/assemblers/cx_assembler.html) | http://ndexbio.org | +| Cytoscape JS | Interactive Cytoscape JS network to embed in websites| [`indra.assemblers.cyjs`](https://indra.readthedocs.io/en/latest/modules/assemblers/cyjs_assembler.html) | http://js.cytoscape.org/ | +| Graphviz | Static PDF/PNG visualization with powerful automated layout using Graphviz | [`indra.assemblers.graph`](https://indra.readthedocs.io/en/latest/modules/assemblers/graph_assembler.html) | https://www.graphviz.org/ | +| SBGN | Visualization with Systems Biology Graphical Notation| [`indra.assemblers.sbgn`](https://indra.readthedocs.io/en/latest/modules/assemblers/sbgn_assembler.html) | http://sbgn.org | + +Assemblers primarily aimed at expert curation and browsing: + +| Output format | Purpose | Module | Reference | +|------------------------------------------------|------------------------------------------------------ |-------------------------|---------------------| +| English language | Human-readable descriptions, reports, dialogue | [`indra.assemblers.english`](https://indra.readthedocs.io/en/latest/modules/assemblers/english_assembler.html) | | +| HTML | Web-based browsing, linking out to provenance, curation| [`indra.assemblers.html`](https://indra.readthedocs.io/en/latest/modules/assemblers/html_assembler.html) | [Curation tutorial](https://indra.readthedocs.io/en/latest/tutorials/html_curation.html) | +| TSV (Tab/Comma Separated Values) | Spreadsheet-based browsing and curation | [`indra.assemblers.tsv`](https://indra.readthedocs.io/en/latest/modules/assemblers/tsv_assembler.html) | | +| Index Cards | Custom JSON format for curating biological mechanisms | [`indra.assemblers.index_card`](https://indra.readthedocs.io/en/latest/modules/assemblers/index_card_assembler.html) | | + +### Internal knowledge assembly + +A key feature of INDRA is providing internal knowledge-assembly modules +that operate on INDRA Statements and perform the following tasks: +- Redundancy/subsumption/generalization/contradiction finding and resolution +with respect to an ontology with the Preassembler +([`indra.preassembler.Preassembler`](https://indra.readthedocs.io/en/latest/modules/preassembler/index.html#module-indra.preassembler)) +- Belief calculation based on evidence using the BeliefEngine +([`indra.belief`](https://indra.readthedocs.io/en/latest/modules/belief/index.html)) +- Mapping grounding between multiple ontologies +([`indra.preassembler.ont_mapper.OntMapper`](https://indra.readthedocs.io/en/latest/modules/preassembler/index.html#module-indra.preassembler.ontology_mapper)) +- Grounding override and disambiguation +([`indra.preassembler.grounding_mapper.GroundingMapper`](https://indra.readthedocs.io/en/latest/modules/preassembler/index.html#module-indra.preassembler.grounding_mapper)) +- Protein sequence mapping ([`indra.preassembler.site_mapper.SiteMapper`](https://indra.readthedocs.io/en/latest/modules/preassembler/index.html#module-indra.preassembler.sitemapper)) + +The internal assembly steps of INDRA including the ones listed above, and also +a large collection of filters (filter by source, belief, the presence of +grounding information, semantic filters by entity role, etc.) are exposed +in the +[indra.tools.assemble_corpus](http://indra.readthedocs.io/en/latest/modules/tools/index.html#module-indra.tools.assemble_corpus) +submodule. This submodule contains functions that +take Statements as input and produce processed Statements as output. They can +be composed to form an assembly pipeline connecting knowledge collected from +sources with an output model. + +This diagram illustrates the assembly pipeline process. + + + +The choice of assembly functions can vary depending on the domain (i.e, +biology or world modeling), the modeling goal (i.e., the type of model that +will be assembled and how that model will be used), desired features, and +confidence (e.g., filter to human genes only or apply a belief cutoff), +and any other user preferences. + +An example of a typical assembly pipeline for biology statements is as follows. +Some of the below steps can be removed, rearranged, and other steps added +to change the assembly pipeline. + +[//]: # (If code is changed here, also update it in tests/test_docs_code.py) + +```python +from indra.tools import assemble_corpus as ac +stmts = <the collection of all raw statements to use> +stmts = ac.filter_no_hypothesis(stmts) # Filter out hypothetical statements +stmts = ac.map_grounding(stmts) # Map grounding +stmts = ac.filter_grounded_only(stmts) # Filter out ungrounded agents +stmts = ac.filter_human_only(stmts) # Filter out non-human genes +stmts = ac.map_sequence(stmts) # Map sequence +stmts = ac.run_preassembly(stmts, # Run preassembly + return_toplevel=False) +stmts = ac.filter_belief(stmts, 0.8) # Apply belief cutoff of 0.8 +``` + +An example of an assembly pipeline for statements in the world modeling domain +is as follows (note how biology-specific functions are not used, and a custom +belief_scorer and ontology is passed to `run_preassembly` here, while the +biology pipeline used default values). Note that this example requires +the `indra_world` package to be installed. + +[//]: # (If code is changed here, also update it in tests/test_docs_code.py) + +```python +from indra.tools import assemble_corpus as ac +from indra_world.belief.wm_scorer import get_eidos_scorer +from indra_world.ontology.world import world_ontology +stmts = <the collection of all raw statements to use> +stmts = ac.filter_grounded_only(stmts) # Filter out ungrounded agents +belief_scorer = get_eidos_scorer() +stmts = ac.run_preassembly(stmts, # Run preassembly + return_toplevel=False, + belief_scorer=belief_scorer, + ontology=world_ontology, + normalize_equivalences=True, # Optional: rewrite equivalent groundings to one standard + normalize_opposites=True, # Optional: rewrite opposite groundings to one standard + normalize_ns='WM') # Use 'WM' namespace to normalize equivalences and opposites +stmts = ac.filter_belief(stmts, 0.8) # Apply belief cutoff of e.g., 0.8 +``` +Assembled statements returned after running the assembly pipeline can be +passed into any of the output model assemblers. + +### Other modules + +INDRA also contains modules to access literature content (e.g., PubMed, Elsevier), available in [`indra.literature`]( +https://indra.readthedocs.io/en/latest/modules/literature/index.html), and +access ontological information and convert between identifiers (e.g., UniProt, +HGNC), available in [`indra.databases`]( +https://indra.readthedocs.io/en/latest/modules/databases/index.html). +A full list of further INDRA modules is available in the [`documentation`]( +https://indra.readthedocs.io/en/latest/modules/index.html). + +## Citation + +Gyori B.M., Bachman J.A., Subramanian K., Muhlich J.L., Galescu L., Sorger P.K. +[From word models to executable models of signaling networks using automated +assembly](http://msb.embopress.org/content/13/11/954) (2017), +Molecular Systems Biology, 13, 954. + +Bachman J.A., Gyori B.M., Sorger P.K. +[Automated assembly of molecular mechanisms at scale from text mining and +curated databases](https://doi.org/10.1101/2022.08.30.505688) (2022), +bioRxiv preprint + +## Installation + +For detailed installation instructions, +[see the documentation](http://indra.readthedocs.io/en/latest/installation.html). + +INDRA currently supports Python 3.6+. The last release of INDRA compatible +with Python 2.7 is 1.10, and the last release fully compatible with Python 3.5 +is 1.17. + +The preferred way to install INDRA is by pointing pip to the source repository +as + + $ pip install git+https://github.com/sorgerlab/indra.git + +Releases of INDRA are also available on +[PyPI](https://pip.pypa.io/en/latest/installing/), you can install the latest +release as + + $ pip install indra + +However, releases will usually be behind the latest code available in this +repository. + +INDRA depends on a few standard Python packages. These packages are installed +by pip during setup. +For certain modules and use cases, other "extra" dependencies may be needed, +which are described in detail in the +[documentation](http://indra.readthedocs.io/en/latest/installation.html). + + +## INDRA REST API +A REST API for INDRA is available at http://api.indra.bio:8000. +Note that the REST API is ideal for prototyping and for building light-weight +web apps, but should not be used for large reading and assembly workflows. + + +## INDRA Docker +INDRA is available as a Docker image on Dockerhub and can be pulled as + +``` +docker pull labsyspharm/indra +``` + +You can run the INDRA REST API using the container as +``` +docker run -id -p 8080:8080 --entrypoint python labsyspharm/indra /sw/indra/rest_api/api.py +``` + +The Dockerfile to build the image locally is available in a separate repository +at https://github.com/indralab/indra_docker. + +## Using INDRA + +In this example INDRA assembles a PySB model from the natural language +description of a mechanism via the [TRIPS reading web +service](http://trips.ihmc.us/parser/cgi/drum). + +[//]: # (If code is changed here, also update it in tests/test_docs_code.py) + +```python +from indra.sources import trips +from indra.assemblers.pysb import PysbAssembler +pa = PysbAssembler() +# Process a natural language description of a mechanism +trips_processor = trips.process_text('MEK2 phosphorylates ERK1 at Thr-202 and Tyr-204') +# Collect extracted mechanisms in PysbAssembler +pa.add_statements(trips_processor.statements) +# Assemble the model +model = pa.make_model(policies='two_step') +``` + +INDRA also provides an interface for the +[REACH](http://github.com/clulab/reach) natural language +processor. In this example, a full paper from [PubMed +Central](http://www.ncbi.nlm.nih.gov/pmc/) is processed. The paper's PMC ID is +[PMC8511698](http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8511698/). The example +assumest that a REACH server is running locally (see documentation at +[`indra.sources.reach`](https://indra.readthedocs.io/en/latest/modules/sources/reach/index.html)). +Note that REACH takes about 8 minutes to read this full-text paper. + + +[//]: # (If code is changed here, also update it in tests/test_docs_code.py) + +```python +from indra.sources import reach +reach_processor = reach.process_pmc('PMC8511698', url=reach.local_nxml_url) +``` +At this point, `reach_processor.statements` contains a list of INDRA statements +extracted from the PMC paper. + +Next we look at an example of reading the 10 most recent PubMed abstracts on +BRAF and collecting the results in INDRA statements. + +[//]: # (If code is changed here, also update it in tests/test_docs_code.py) + +```python +from indra.sources import reach +from indra.literature import pubmed_client +# Search for 10 most recent abstracts in PubMed on 'BRAF' +pmids = pubmed_client.get_ids('BRAF', retmax=10) +all_statements = [] +for pmid in pmids: + abs = pubmed_client.get_abstract(pmid) + if abs is not None: + reach_processor = reach.process_text(abs, url=reach.local_text_url) + if reach_processor is not None: + all_statements += reach_processor.statements +``` +At this point, the `all_statements` list contains all the statements +extracted from the 10 abstracts. + +The next example shows querying the [BEL large +corpus](https://github.com/cthoyt/selventa-knowledge) +network for a neighborhood of a given list of proteins using their +HGNC gene names. This example performs the query via PyBEL. + +[//]: # (If code is changed here, also update it in tests/test_docs_code.py) + +```python +from indra.sources import bel +# Process the neighborhood of BRAF and MAP2K1 +bel_processor = bel.process_pybel_neighborhood(['BRAF', 'MAP2K1']) +``` +At this point, `bel_processor.statements` contains a list of INDRA statements +extracted from the neighborhood query. + +Next, we look at an example of querying the [Pathway Commons +database](http://pathwaycommons.org) for paths between two lists of proteins. + +[//]: # (If code is changed here, also update it in tests/test_docs_code.py) + +```python +from indra.sources import biopax +# Process the neighborhood of BRAF and MAP2K1 +biopax_processor = biopax.process_pc_pathsfromto(['BRAF', 'RAF1'], ['MAP2K1', 'MAP2K2']) +``` +At this point, `biopax_processor.statements` contains a list of INDRA +Statements extracted from the paths-from-to query. + +## Funding + +The development of INDRA has been funded from the following sources: + +| Program | Grant number | +|--------------------------------------------------|----------------------| +| DARPA Big Mechanism | W911NF-14-1-0397 | +| DARPA World Modelers | W911NF-18-1-0014 | +| DARPA Communicating with Computers | W911NF-15-1-0544 | +| DARPA Automated Scientific Discovery Framework | W911NF-18-1-0124 | +| DARPA Automating Scientific Knowledge Extraction | HR00111990009 | +| DARPA Panacea | HR00111920022 | +| DARPA Young Faculty Award | W911NF-20-1-0255 | + + + + +%package help +Summary: Development documents and examples for indra +Provides: python3-indra-doc +%description help +# INDRA + +[](https://opensource.org/licenses/BSD-2-Clause) +[](https://github.com/sorgerlab/indra/actions) +[](https://indra.readthedocs.io/en/latest/?badge=latest) +[](https://badge.fury.io/py/indra) +[](https://www.python.org/downloads/release/python-357/) + +<img align="left" src="https://raw.githubusercontent.com/sorgerlab/indra/master/doc/indra_logo.png" width="300" height="224" /> + +INDRA (Integrated Network and Dynamical Reasoning Assembler) is an automated +model assembly system, originally developed for molecular systems biology and +then generalized to other domains (see [INDRA +World](https://github.com/indralab/indra_world)). INDRA draws on natural +language processing systems and structured databases to collect mechanistic and +causal assertions, represents them in a standardized form (INDRA Statements), +and assembles them into various modeling formalisms including causal graphs and +dynamical models. + +At the core of INDRA are its knowledge-level assembly procedures, allowing +sources to be assembled into coherent models, a process that involves +correcting systematic input errors, finding and resolving redundancies, +inferring missing information, filtering to a relevant scope and assessing the +reliability of causal information. + +The detailed INDRA documentation is available at +[http://indra.readthedocs.io](http://indra.readthedocs.io). + +## Contents + +- [INDRA Modules](#indra-modules) + - [Knowledge sources](#knowledge-sources) + - [Output model assemblers](#output-model-assemblers) + - [Internal knowledge assembly](#internal-knowledge-assembly) + - [Other modules](#other-modules) +- [Citation](#citation) +- [Installation](#installation) +- [INDRA REST API](#indra-rest-api) +- [INDRA Docker](#indra-docker) +- [Using INDRA](#using-indra) +- [Funding](#funding) + +## INDRA Modules + +### Knowledge sources + +INDRA is currently integrated with the following natural language processing +systems and structured databases. These input modules (available in +`indra.sources`) all produce INDRA Statements. + +Reading systems: + +| Reader | Module | Reference | +|------------|--------------------------------------------------------------------------------------------------------|-------------------------------------------------| +| TRIPS/DRUM | [`indra.sources.trips`](https://indra.readthedocs.io/en/latest/modules/sources/trips/index.html) | http://trips.ihmc.us/parser/cgi/drum | +| REACH | [`indra.sources.reach`](https://indra.readthedocs.io/en/latest/modules/sources/reach/index.html) | https://github.com/clulab/reach | +| Sparser | [`indra.sources.sparser`](https://indra.readthedocs.io/en/latest/modules/sources/sparser/index.html#) | https://github.com/ddmcdonald/sparser | +| Eidos | [`indra.sources.eidos`](https://indra.readthedocs.io/en/latest/modules/sources/eidos/index.html#) | https://github.com/clulab/eidos | +| TEES | [`indra.sources.tees`](https://indra.readthedocs.io/en/latest/modules/sources/tees/index.html) | https://github.com/jbjorne/TEES | +| MedScan | [`indra.sources.medscan`](https://indra.readthedocs.io/en/latest/modules/sources/medscan/index.html) | https://doi.org/10.1093/bioinformatics/btg207 | +| RLIMS-P | [`indra.sources.rlimsp`](https://indra.readthedocs.io/en/latest/modules/sources/rlimsp/index.html) | https://research.bioinformatics.udel.edu/rlimsp | +| ISI/AMR | [`indra.sources.isi`](https://indra.readthedocs.io/en/latest/modules/sources/isi/index.html) | https://github.com/sgarg87/big_mech_isi_gg | +| Geneways | [`indra.sources.geneways`](https://indra.readthedocs.io/en/latest/modules/sources/geneways/index.html) | https://www.ncbi.nlm.nih.gov/pubmed/15016385 | +| GNBR | [`indra.sources.gnbr`](https://indra.readthedocs.io/en/latest/modules/sources/gnbr/index.html) | https://zenodo.org/record/3459420 | +| SemRep | [`indra.sources.semrep`](https://indra.readthedocs.io/en/latest/modules/sources/semrep.html) | https://github.com/lhncbc/SemRep | + + +Biological pathway databases: + +| Database / Exchange format | Module | Reference | +|----------------------------|----------------------------|-----------------------------------------------------------------| +| PathwayCommons / BioPax | [`indra.sources.biopax`](https://indra.readthedocs.io/en/latest/modules/sources/biopax/index.html) | http://pathwaycommons.org/ <br/> http://www.biopax.org/ | +| Large Corpus / BEL | [`indra.sources.bel`](https://indra.readthedocs.io/en/latest/modules/sources/bel/index.html) | https://github.com/pybel/pybel <br/> https://github.com/OpenBEL | +| Signor | [`indra.sources.signor`](https://indra.readthedocs.io/en/latest/modules/sources/signor/index.html) | https://signor.uniroma2.it/ | +| BioGRID | [`indra.sources.biogrid`](https://indra.readthedocs.io/en/latest/modules/sources/biogrid/index.html) | https://thebiogrid.org/ | +| Target Affinity Spectrum | [`indra.sources.tas`](https://indra.readthedocs.io/en/latest/modules/sources/tas/index.html#) | https://doi.org/10.1101/358978 | +| HPRD | [`indra.sources.hprd`](https://indra.readthedocs.io/en/latest/modules/sources/hprd/index.html) | http://www.hprd.org | | +| TRRUST | [`indra.sources.trrust`](https://indra.readthedocs.io/en/latest/modules/sources/trrust.html) | https://www.grnpedia.org/trrust/ | | +| Phospho.ELM | [`indra.sources.phosphoelm`](https://indra.readthedocs.io/en/latest/modules/sources/phosphoelm/index.html) | http://phospho.elm.eu.org/ | +| VirHostNet | [`indra.sources.virhostnet`](https://indra.readthedocs.io/en/latest/modules/sources/virhostnet/index.html) | http://virhostnet.prabi.fr/ | +| CTD | [`indra.sources.ctd`](https://indra.readthedocs.io/en/latest/modules/sources/ctd/index.html) | http://ctdbase.org | +| DrugBank | [`indra.sources.drugbank`](https://indra.readthedocs.io/en/latest/modules/sources/drugbank/index.html) | https://www.drugbank.ca/ | +| OmniPath | [`indra.sources.omnipath`](https://indra.readthedocs.io/en/latest/modules/sources/omnipath/index.html) | https://omnipathdb.org/ | +| DGI | [`indra.sources.dgi`](https://indra.readthedocs.io/en/latest/modules/sources/dgi/index.html) | https://www.dgidb.org/ | +| CRoG | [`indra.sources.crog`](https://indra.readthedocs.io/en/latest/modules/sources/crog/index.html) | https://github.com/chemical-roles/chemical-roles | +| CREEDS | [`indra.sources.creeds`](https://indra.readthedocs.io/en/latest/modules/sources/creeds/index.html) | https://maayanlab.cloud/CREEDS/ | +| UbiBrowser | [`indra.sources.ubibrowser`](https://indra.readthedocs.io/en/latest/modules/sources/ubibrowser.html) | http://ubibrowser.ncpsb.org.cn/ | +| ACSN | [`indra.sources.acsn`](https://indra.readthedocs.io/en/latest/modules/sources/acsn.html) | https://acsn.curie.fr/ACSN2/ACSN2.html | + +Custom knowledge bases: + +| Database / Exchange format | Module | Reference | +|----------------------------|-------------------------------|--------------------------------------| +| NDEx / CX | [`indra.sources.ndex_cx`](https://indra.readthedocs.io/en/latest/modules/sources/ndex_cx/index.html) | http://ndexbio.org | +| INDRA DB / INDRA Statements| [`indra.sources.indra_db_rest`](https://indra.readthedocs.io/en/latest/modules/sources/indra_db_rest/index.html) | https://github.com/indralab/indra_db | +| Hypothes.is | [`indra.sources.hypothesis`](https://indra.readthedocs.io/en/latest/modules/sources/hypothesis/index.html) | https://hypothes.is | +| Biofactoid | [`indra.sources.biofactoid`](https://indra.readthedocs.io/en/latest/modules/sources/biofactoid/index.html) | https://biofactoid.org/ | +| MINERVA | [`indra.sources.minerva`](https://indra.readthedocs.io/en/latest/modules/sources/minerva/index.html) | https://covid19map.elixir-luxembourg.org/minerva/ | + + +### Output model assemblers + +INDRA also provides several model output assemblers that take INDRA Statements +as input. The most sophisticated model assembler is the PySB Assembler, which +implements a policy-guided automated assembly procedure of a rule-based +executable model (that can then be further compiled into other formats such as +SBML, Kappa, BNGL and SBGN to connect to a vast ecosystem of downstream tools). +Several other model assembly modules target various network formats for +visualization, and graph/structural analysis (PyBEL, CyJS, Graphviz, SBGN, +CX, SIF, etc.) and curation (HTML, TSV, IndexCards). +Finally, the English Assembler produces English language descriptions of a set +of INDRA Statements. + +INDRA also supports extension by outside model assembly tools which take +INDRA Statements as input and produce models. One such example is Delphi +(https://github.com/ml4ai/delphi), which is a Dynamic Bayesian Network +model assembler. Similarly, outside tools that support INDRA Statements +can implement custom visualization methods, such as CauseMos, developed +by Uncharted Software (https://uncharted.software/). + +Assemblers aimed at model-driven discovery and analysis: + +| Modeling formalism / Exchange format | Purpose | Module | Reference | +|------------------------------------------------|------------------------------------------------------|-------------------------|---------------------| +| PySB (-> SBML, SBGN, BNGL, Kappa, etc.) | Detailed, mechanistic modeling, simulation, analysis | [`indra.assemblers.pysb`](https://indra.readthedocs.io/en/latest/modules/assemblers/pysb_assembler.html#) | http://pysb.org | +| PyBEL | Causal analysis, visualization | [`indra.assemblers.pybel`](https://indra.readthedocs.io/en/latest/modules/assemblers/pybel_assembler.html)| https://github.com/pybel/pybel <br/> https://bel-commons.scai.fraunhofer.de/ | +| IndraNet | Causal analysis, signed and unsigned | [`indra.assemblers.indranet`](https://indra.readthedocs.io/en/latest/modules/assemblers/indranet_assembler.html) | | +| SIF | Network analysis, logic modeling, visualization | [`indra.assemblers.sif`](https://indra.readthedocs.io/en/latest/modules/assemblers/sif_assembler.html) | [SIF format](http://manual.cytoscape.org/en/stable/Supported_Network_File_Formats.html#sif-format) | +| KAMI | Knowledge aggregation of protein sites/states and Kappa modeling | [`indra.assemblers.kami`](https://indra.readthedocs.io/en/latest/modules/assemblers/kami_assembler.html) | https://github.com/Kappa-Dev/KAMI | + + +Assemblers primarily aimed at visualization: + +| Network / Exchange format | Purpose | Module | Reference | +|------------------------------------------------|------------------------------------------------------|-------------------------|---------------------| +| Causal Analysis Graph | General causal graph visualization | [`indra.assemblers.cag`](https://indra.readthedocs.io/en/latest/modules/assemblers/cag_assembler.html) | | +| CX | Network browsing, versioning on NDEx | [`indra.assemblers.cx`](https://indra.readthedocs.io/en/latest/modules/assemblers/cx_assembler.html) | http://ndexbio.org | +| Cytoscape JS | Interactive Cytoscape JS network to embed in websites| [`indra.assemblers.cyjs`](https://indra.readthedocs.io/en/latest/modules/assemblers/cyjs_assembler.html) | http://js.cytoscape.org/ | +| Graphviz | Static PDF/PNG visualization with powerful automated layout using Graphviz | [`indra.assemblers.graph`](https://indra.readthedocs.io/en/latest/modules/assemblers/graph_assembler.html) | https://www.graphviz.org/ | +| SBGN | Visualization with Systems Biology Graphical Notation| [`indra.assemblers.sbgn`](https://indra.readthedocs.io/en/latest/modules/assemblers/sbgn_assembler.html) | http://sbgn.org | + +Assemblers primarily aimed at expert curation and browsing: + +| Output format | Purpose | Module | Reference | +|------------------------------------------------|------------------------------------------------------ |-------------------------|---------------------| +| English language | Human-readable descriptions, reports, dialogue | [`indra.assemblers.english`](https://indra.readthedocs.io/en/latest/modules/assemblers/english_assembler.html) | | +| HTML | Web-based browsing, linking out to provenance, curation| [`indra.assemblers.html`](https://indra.readthedocs.io/en/latest/modules/assemblers/html_assembler.html) | [Curation tutorial](https://indra.readthedocs.io/en/latest/tutorials/html_curation.html) | +| TSV (Tab/Comma Separated Values) | Spreadsheet-based browsing and curation | [`indra.assemblers.tsv`](https://indra.readthedocs.io/en/latest/modules/assemblers/tsv_assembler.html) | | +| Index Cards | Custom JSON format for curating biological mechanisms | [`indra.assemblers.index_card`](https://indra.readthedocs.io/en/latest/modules/assemblers/index_card_assembler.html) | | + +### Internal knowledge assembly + +A key feature of INDRA is providing internal knowledge-assembly modules +that operate on INDRA Statements and perform the following tasks: +- Redundancy/subsumption/generalization/contradiction finding and resolution +with respect to an ontology with the Preassembler +([`indra.preassembler.Preassembler`](https://indra.readthedocs.io/en/latest/modules/preassembler/index.html#module-indra.preassembler)) +- Belief calculation based on evidence using the BeliefEngine +([`indra.belief`](https://indra.readthedocs.io/en/latest/modules/belief/index.html)) +- Mapping grounding between multiple ontologies +([`indra.preassembler.ont_mapper.OntMapper`](https://indra.readthedocs.io/en/latest/modules/preassembler/index.html#module-indra.preassembler.ontology_mapper)) +- Grounding override and disambiguation +([`indra.preassembler.grounding_mapper.GroundingMapper`](https://indra.readthedocs.io/en/latest/modules/preassembler/index.html#module-indra.preassembler.grounding_mapper)) +- Protein sequence mapping ([`indra.preassembler.site_mapper.SiteMapper`](https://indra.readthedocs.io/en/latest/modules/preassembler/index.html#module-indra.preassembler.sitemapper)) + +The internal assembly steps of INDRA including the ones listed above, and also +a large collection of filters (filter by source, belief, the presence of +grounding information, semantic filters by entity role, etc.) are exposed +in the +[indra.tools.assemble_corpus](http://indra.readthedocs.io/en/latest/modules/tools/index.html#module-indra.tools.assemble_corpus) +submodule. This submodule contains functions that +take Statements as input and produce processed Statements as output. They can +be composed to form an assembly pipeline connecting knowledge collected from +sources with an output model. + +This diagram illustrates the assembly pipeline process. + + + +The choice of assembly functions can vary depending on the domain (i.e, +biology or world modeling), the modeling goal (i.e., the type of model that +will be assembled and how that model will be used), desired features, and +confidence (e.g., filter to human genes only or apply a belief cutoff), +and any other user preferences. + +An example of a typical assembly pipeline for biology statements is as follows. +Some of the below steps can be removed, rearranged, and other steps added +to change the assembly pipeline. + +[//]: # (If code is changed here, also update it in tests/test_docs_code.py) + +```python +from indra.tools import assemble_corpus as ac +stmts = <the collection of all raw statements to use> +stmts = ac.filter_no_hypothesis(stmts) # Filter out hypothetical statements +stmts = ac.map_grounding(stmts) # Map grounding +stmts = ac.filter_grounded_only(stmts) # Filter out ungrounded agents +stmts = ac.filter_human_only(stmts) # Filter out non-human genes +stmts = ac.map_sequence(stmts) # Map sequence +stmts = ac.run_preassembly(stmts, # Run preassembly + return_toplevel=False) +stmts = ac.filter_belief(stmts, 0.8) # Apply belief cutoff of 0.8 +``` + +An example of an assembly pipeline for statements in the world modeling domain +is as follows (note how biology-specific functions are not used, and a custom +belief_scorer and ontology is passed to `run_preassembly` here, while the +biology pipeline used default values). Note that this example requires +the `indra_world` package to be installed. + +[//]: # (If code is changed here, also update it in tests/test_docs_code.py) + +```python +from indra.tools import assemble_corpus as ac +from indra_world.belief.wm_scorer import get_eidos_scorer +from indra_world.ontology.world import world_ontology +stmts = <the collection of all raw statements to use> +stmts = ac.filter_grounded_only(stmts) # Filter out ungrounded agents +belief_scorer = get_eidos_scorer() +stmts = ac.run_preassembly(stmts, # Run preassembly + return_toplevel=False, + belief_scorer=belief_scorer, + ontology=world_ontology, + normalize_equivalences=True, # Optional: rewrite equivalent groundings to one standard + normalize_opposites=True, # Optional: rewrite opposite groundings to one standard + normalize_ns='WM') # Use 'WM' namespace to normalize equivalences and opposites +stmts = ac.filter_belief(stmts, 0.8) # Apply belief cutoff of e.g., 0.8 +``` +Assembled statements returned after running the assembly pipeline can be +passed into any of the output model assemblers. + +### Other modules + +INDRA also contains modules to access literature content (e.g., PubMed, Elsevier), available in [`indra.literature`]( +https://indra.readthedocs.io/en/latest/modules/literature/index.html), and +access ontological information and convert between identifiers (e.g., UniProt, +HGNC), available in [`indra.databases`]( +https://indra.readthedocs.io/en/latest/modules/databases/index.html). +A full list of further INDRA modules is available in the [`documentation`]( +https://indra.readthedocs.io/en/latest/modules/index.html). + +## Citation + +Gyori B.M., Bachman J.A., Subramanian K., Muhlich J.L., Galescu L., Sorger P.K. +[From word models to executable models of signaling networks using automated +assembly](http://msb.embopress.org/content/13/11/954) (2017), +Molecular Systems Biology, 13, 954. + +Bachman J.A., Gyori B.M., Sorger P.K. +[Automated assembly of molecular mechanisms at scale from text mining and +curated databases](https://doi.org/10.1101/2022.08.30.505688) (2022), +bioRxiv preprint + +## Installation + +For detailed installation instructions, +[see the documentation](http://indra.readthedocs.io/en/latest/installation.html). + +INDRA currently supports Python 3.6+. The last release of INDRA compatible +with Python 2.7 is 1.10, and the last release fully compatible with Python 3.5 +is 1.17. + +The preferred way to install INDRA is by pointing pip to the source repository +as + + $ pip install git+https://github.com/sorgerlab/indra.git + +Releases of INDRA are also available on +[PyPI](https://pip.pypa.io/en/latest/installing/), you can install the latest +release as + + $ pip install indra + +However, releases will usually be behind the latest code available in this +repository. + +INDRA depends on a few standard Python packages. These packages are installed +by pip during setup. +For certain modules and use cases, other "extra" dependencies may be needed, +which are described in detail in the +[documentation](http://indra.readthedocs.io/en/latest/installation.html). + + +## INDRA REST API +A REST API for INDRA is available at http://api.indra.bio:8000. +Note that the REST API is ideal for prototyping and for building light-weight +web apps, but should not be used for large reading and assembly workflows. + + +## INDRA Docker +INDRA is available as a Docker image on Dockerhub and can be pulled as + +``` +docker pull labsyspharm/indra +``` + +You can run the INDRA REST API using the container as +``` +docker run -id -p 8080:8080 --entrypoint python labsyspharm/indra /sw/indra/rest_api/api.py +``` + +The Dockerfile to build the image locally is available in a separate repository +at https://github.com/indralab/indra_docker. + +## Using INDRA + +In this example INDRA assembles a PySB model from the natural language +description of a mechanism via the [TRIPS reading web +service](http://trips.ihmc.us/parser/cgi/drum). + +[//]: # (If code is changed here, also update it in tests/test_docs_code.py) + +```python +from indra.sources import trips +from indra.assemblers.pysb import PysbAssembler +pa = PysbAssembler() +# Process a natural language description of a mechanism +trips_processor = trips.process_text('MEK2 phosphorylates ERK1 at Thr-202 and Tyr-204') +# Collect extracted mechanisms in PysbAssembler +pa.add_statements(trips_processor.statements) +# Assemble the model +model = pa.make_model(policies='two_step') +``` + +INDRA also provides an interface for the +[REACH](http://github.com/clulab/reach) natural language +processor. In this example, a full paper from [PubMed +Central](http://www.ncbi.nlm.nih.gov/pmc/) is processed. The paper's PMC ID is +[PMC8511698](http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8511698/). The example +assumest that a REACH server is running locally (see documentation at +[`indra.sources.reach`](https://indra.readthedocs.io/en/latest/modules/sources/reach/index.html)). +Note that REACH takes about 8 minutes to read this full-text paper. + + +[//]: # (If code is changed here, also update it in tests/test_docs_code.py) + +```python +from indra.sources import reach +reach_processor = reach.process_pmc('PMC8511698', url=reach.local_nxml_url) +``` +At this point, `reach_processor.statements` contains a list of INDRA statements +extracted from the PMC paper. + +Next we look at an example of reading the 10 most recent PubMed abstracts on +BRAF and collecting the results in INDRA statements. + +[//]: # (If code is changed here, also update it in tests/test_docs_code.py) + +```python +from indra.sources import reach +from indra.literature import pubmed_client +# Search for 10 most recent abstracts in PubMed on 'BRAF' +pmids = pubmed_client.get_ids('BRAF', retmax=10) +all_statements = [] +for pmid in pmids: + abs = pubmed_client.get_abstract(pmid) + if abs is not None: + reach_processor = reach.process_text(abs, url=reach.local_text_url) + if reach_processor is not None: + all_statements += reach_processor.statements +``` +At this point, the `all_statements` list contains all the statements +extracted from the 10 abstracts. + +The next example shows querying the [BEL large +corpus](https://github.com/cthoyt/selventa-knowledge) +network for a neighborhood of a given list of proteins using their +HGNC gene names. This example performs the query via PyBEL. + +[//]: # (If code is changed here, also update it in tests/test_docs_code.py) + +```python +from indra.sources import bel +# Process the neighborhood of BRAF and MAP2K1 +bel_processor = bel.process_pybel_neighborhood(['BRAF', 'MAP2K1']) +``` +At this point, `bel_processor.statements` contains a list of INDRA statements +extracted from the neighborhood query. + +Next, we look at an example of querying the [Pathway Commons +database](http://pathwaycommons.org) for paths between two lists of proteins. + +[//]: # (If code is changed here, also update it in tests/test_docs_code.py) + +```python +from indra.sources import biopax +# Process the neighborhood of BRAF and MAP2K1 +biopax_processor = biopax.process_pc_pathsfromto(['BRAF', 'RAF1'], ['MAP2K1', 'MAP2K2']) +``` +At this point, `biopax_processor.statements` contains a list of INDRA +Statements extracted from the paths-from-to query. + +## Funding + +The development of INDRA has been funded from the following sources: + +| Program | Grant number | +|--------------------------------------------------|----------------------| +| DARPA Big Mechanism | W911NF-14-1-0397 | +| DARPA World Modelers | W911NF-18-1-0014 | +| DARPA Communicating with Computers | W911NF-15-1-0544 | +| DARPA Automated Scientific Discovery Framework | W911NF-18-1-0124 | +| DARPA Automating Scientific Knowledge Extraction | HR00111990009 | +| DARPA Panacea | HR00111920022 | +| DARPA Young Faculty Award | W911NF-20-1-0255 | + + + + +%prep +%autosetup -n indra-1.22.0 + +%build +%py3_build + +%install +%py3_install +install -d -m755 %{buildroot}/%{_pkgdocdir} +if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi +if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi +if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi +if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi +pushd %{buildroot} +if [ -d usr/lib ]; then + find usr/lib -type f -printf "\"/%h/%f\"\n" >> filelist.lst +fi +if [ -d usr/lib64 ]; then + find usr/lib64 -type f -printf "\"/%h/%f\"\n" >> filelist.lst +fi +if [ -d usr/bin ]; then + find usr/bin -type f -printf "\"/%h/%f\"\n" >> filelist.lst +fi +if [ -d usr/sbin ]; then + find usr/sbin -type f -printf "\"/%h/%f\"\n" >> filelist.lst +fi +touch doclist.lst +if [ -d usr/share/man ]; then + find usr/share/man -type f -printf "\"/%h/%f.gz\"\n" >> doclist.lst +fi +popd +mv %{buildroot}/filelist.lst . +mv %{buildroot}/doclist.lst . + +%files -n python3-indra -f filelist.lst +%dir %{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Tue Jun 20 2023 Python_Bot <Python_Bot@openeuler.org> - 1.22.0-1 +- Package Spec generated @@ -0,0 +1 @@ +2be6479a79b1b8cbfba679be45337bea indra-1.22.0.tar.gz |