Literature clients (indra.literature)
- indra.literature.get_full_text(paper_id, idtype, preferred_content_type='text/xml')[source]
Return the content and the content type of an article.
This function retreives the content of an article by its PubMed ID, PubMed Central ID, or DOI. It prioritizes full text content when available and returns an abstract from PubMed as a fallback.
- Parameters
paper_id (string) – ID of the article.
idtype ('pmid', 'pmcid', or 'doi) – Type of the ID.
preferred_content_type (Optional[st]r) – Preference for full-text format, if available. Can be one of ‘text/xml’, ‘text/plain’, ‘application/pdf’. Default: ‘text/xml’
- Returns
content (str) – The content of the article.
content_type (str) – The content type of the article
- indra.literature.id_lookup(paper_id, idtype)[source]
Take an ID of type PMID, PMCID, or DOI and lookup the other IDs.
If the DOI is not found in Pubmed, try to obtain the DOI by doing a reverse-lookup of the DOI in CrossRef using article metadata.
Pubmed client (indra.literature.pubmed_client)
Search and get metadata for articles in Pubmed.
- indra.literature.pubmed_client.expand_pagination(pages)[source]
Convert a page number to long form, e.g., from 456-7 to 456-457.
- indra.literature.pubmed_client.get_abstract(pubmed_id, prepend_title=True)[source]
Get the abstract of an article in the Pubmed database.
- indra.literature.pubmed_client.get_article_xml(pubmed_id)[source]
Get the Article subtree a single article from the Pubmed database.
- Parameters
pubmed_id (str) – A PubMed ID.
- Returns
The XML ElementTree Element that represents the Article portion of the PubMed entry.
- Return type
- indra.literature.pubmed_client.get_full_xml(pubmed_id, fname=None)[source]
Get the full XML tree of a single article from the Pubmed database.
- Parameters
- Returns
The root element of the XML tree representing the PubMed entry. The root is a PubmedArticleSet with a single PubmedArticle element that contains the article metadata.
- Return type
- indra.literature.pubmed_client.get_id_count(search_term)[source]
Get the number of citations in Pubmed for a search query.
- indra.literature.pubmed_client.get_ids(search_term, **kwargs)[source]
Search Pubmed for paper IDs given a search term.
Search options can be passed as keyword arguments, some of which are custom keywords identified by this function, while others are passed on as parameters for the request to the PubMed web service For details on parameters that can be used in PubMed searches, see https://www.ncbi.nlm.nih.gov/books/NBK25499/#chapter4.ESearch Some useful parameters to pass are db=’pmc’ to search PMC instead of pubmed reldate=2 to search for papers within the last 2 days mindate=’2016/03/01’, maxdate=’2016/03/31’ to search for papers in March 2016.
PubMed, by default, limits returned PMIDs to a small number, and this number can be controlled by the “retmax” parameter. This function uses a retmax value of 10,000 by default (the maximum supported by PubMed) that can be changed via the corresponding keyword argument. Note also the retstart argument along with retmax to page across batches of IDs.
- Parameters
search_term (str) – A term for which the PubMed search should be performed.
use_text_word (Optional[bool]) – If True, the “[tw]” string is appended to the search term to constrain the search to “text words”, that is words that appear as whole in relevant parts of the PubMed entry (excl. for instance the journal name or publication date) like the title and abstract. Using this option can eliminate spurious search results such as all articles published in June for a search for the “JUN” gene, or journal names that contain Acad for a search for the “ACAD” gene. See also: https://www.nlm.nih.gov/bsd/disted/pubmedtutorial/020_760.html Default : True
kwargs (kwargs) – Additional keyword arguments to pass to the PubMed search as parameters.
- indra.literature.pubmed_client.get_ids_for_gene(hgnc_name, **kwargs)[source]
Get the curated set of articles for a gene in the Entrez database.
Search parameters for the Gene database query can be passed in as keyword arguments.
- Parameters
hgnc_name (str) – The HGNC name of the gene. This is used to obtain the HGNC ID (using the hgnc_client module) and in turn used to obtain the Entrez ID associated with the gene. Entrez is then queried for that ID.
- indra.literature.pubmed_client.get_ids_for_mesh(mesh_id, major_topic=False, **kwargs)[source]
Return PMIDs that are annotated with a given MeSH ID.
- Parameters
mesh_id (str) – The MeSH ID of a term to search for, e.g., D009101.
major_topic (bool) – If True, only papers for which the given MeSH ID is annotated as a major topic are returned. Otherwise all annotations are considered. Default: False
**kwargs – Any further PudMed search arguments that are passed to get_ids.
- indra.literature.pubmed_client.get_issn_info(medline_citation, get_issns_from_nlm='never')[source]
Given a medline citation, get the issn info from the article
- Parameters
medline_citation (xml.etree.ElementTree.Element) – The MedlineCitation element of the PubMed XML tree.
get_issns_from_nlm (Literal['never', 'missing', 'always']) – Whether to recover ISSN values from the NLM catalog. Options are ‘never’, ‘missing’, and ‘always’. If ‘missing’, then the ISSN values will be recovered from the NLM catalog if they are not found in the XML. If ‘always’, then the ISSN values will be recovered from the NLM catalog regardless of whether they are found in the XML. Default is ‘never’ (i.e., never recover from NLM catalog regardless of whether they are found in the XML).
- Returns
A dictionary journal, issue, and ISSN info. The structure is as follows: {
”journal_title”: str, “journal_abbrev”: str, “journal_nlm_id”: str, “issn_dict”: {
”issn”: str, “issn_l”: str, “type”: “print”|”electronic”|”other”,
}, “issue_dict”: {
”volume”: str, “issue”: str, “year”: int
}
}
- Return type
- indra.literature.pubmed_client.get_issns_for_journal(nlm_id)[source]
Get a dict of the ISSN numbers for a journal given its NLM ID.
Information on NLM XML DTDs is available at https://www.nlm.nih.gov/databases/dtd/
- indra.literature.pubmed_client.get_mesh_annotations(pmid)[source]
Return a list of MeSH annotations for a given PubMed ID.
- Parameters
pmid (str) – A PubMed ID.
- Returns
A list of dicts that represent MeSH annotations with the following keys: “mesh” representing the MeSH ID, “text” the standrd name associated with the MeSH ID, “major_topic” a boolean flag set depending on whether the given MeSH ID is assigned as a major topic to the article, and “qualifier” which is a MeSH qualifier ID associated with the annotation, if available, otherwise None.
- Return type
- indra.literature.pubmed_client.get_metadata_for_ids(pmid_list, get_issns_from_nlm=False, get_abstracts=False, prepend_title=False, detailed_authors=False, references_included=None)[source]
Get article metadata for up to 200 PMIDs from the Pubmed database.
- Parameters
get_issns_from_nlm (bool) – Look up the full list of ISSN number for the journal associated with the article, which helps to match articles to CrossRef search results. Defaults to False, since it slows down performance.
get_abstracts (bool) – Indicates whether to include the Pubmed abstract in the results.
prepend_title (bool) – If get_abstracts is True, specifies whether the article title should be prepended to the abstract text.
detailed_authors (bool) – If True, extract as many of the author details as possible, such as first name, identifiers, and institutions. If false, only last names are returned. Default: False
references_included (Optional[str]) – If ‘detailed’, include detailed references in the results. If ‘pmid’, only include the PMID of the reference. If None, don’t include references. Default: None
- Returns
Dictionary indexed by PMID. Each value is a dict containing the following fields: ‘doi’, ‘title’, ‘authors’, ‘journal_title’, ‘journal_abbrev’, ‘journal_nlm_id’, ‘issn_list’, ‘page’.
- Return type
dict of dicts
- indra.literature.pubmed_client.get_metadata_from_xml_tree(tree, get_issns_from_nlm=False, get_abstracts=False, prepend_title=False, mesh_annotations=True, detailed_authors=False, references_included=None)[source]
Get metadata for an XML tree containing PubmedArticle elements.
- Documentation on the XML structure can be found at:
- Parameters
tree (xml.etree.ElementTree) – ElementTree containing one or more PubmedArticle elements.
get_issns_from_nlm (Optional[bool]) – Look up the full list of ISSN number for the journal associated with the article, which helps to match articles to CrossRef search results. Defaults to False, since it slows down performance.
get_abstracts (Optional[bool]) – Indicates whether to include the Pubmed abstract in the results. Default: False
prepend_title (Optional[bool]) – If get_abstracts is True, specifies whether the article title should be prepended to the abstract text. Default: False
mesh_annotations (Optional[bool]) – If True, extract mesh annotations from the pubmed entries and include in the returned data. If false, don’t. Default: True
detailed_authors (Optional[bool]) – If True, extract as many of the author details as possible, such as first name, identifiers, and institutions. If false, only last names are returned. Default: False
references_included (Optional[str]) – If ‘detailed’, include detailed references in the results. If ‘pmid’, only include the PMID of the reference. If None, don’t include references. Default: None
- Returns
Dictionary indexed by PMID. Each value is a dict containing the following fields: ‘doi’, ‘title’, ‘authors’, ‘journal_title’, ‘journal_abbrev’, ‘journal_nlm_id’, ‘issn_list’, ‘page’, ‘volume’, ‘issue’, ‘issue_pub_date’.
- Return type
dict of dicts
Pubmed Central client (indra.literature.pmc_client)
- indra.literature.pmc_client.extract_paragraphs(xml_string)[source]
Returns list of paragraphs in an NLM XML.
This returns a list of the plaintexts for each paragraph and title in the input XML, excluding some paragraphs with text that should not be relevant to biomedical text processing.
Relevant text includes titles, abstracts, and the contents of many body paragraphs. Within figures, tables, and floating elements, only captions are retained (One exception is that all paragraphs within floating boxed-text elements are retained. These elements often contain short summaries enriched with useful information.) Due to captions, nested paragraphs can appear in an NLM XML document. Occasionally there are multiple levels of nesting. If nested paragraphs appear in the input document their texts are returned in a pre-ordered traversal. The text within child paragraphs is not included in the output associated to the parent. Each parent appears in the output before its children. All children of an element appear before the elements following sibling.
All tags are removed from each paragraph in the list that is returned. LaTeX surrounded by <tex-math> tags is removed entirely.
Note: Some articles contain subarticles which are processed slightly differently from the article body. Only text from the body element of a subarticle is included, and all unwanted elements are excluded along with their captions. Boxed-text elements are excluded as well.
- indra.literature.pmc_client.extract_text(xml_string)[source]
Get plaintext from the body of the given NLM XML string.
This plaintext consists of all paragraphs returned by indra.literature.pmc_client.extract_paragraphs separated by newlines and then finally terminated by a newline. See the DocString of extract_paragraphs for more information.
- indra.literature.pmc_client.filter_pmids(pmid_list, source_type)[source]
Filter a list of PMIDs for ones with full text from PMC.
- indra.literature.pmc_client.get_xml(pmc_id)[source]
Returns XML for the article corresponding to a PMC ID.
- indra.literature.pmc_client.id_lookup(paper_id, idtype=None)[source]
Return PMID, DOI and PMCID based on an input ID.
This function takes a Pubmed ID, Pubmed Central ID, or DOI and use the Pubmed ID mapping service and looks up all other IDs from one of these. The IDs are returned in a dictionary.
- Parameters
- Returns
A dictionary with keys ‘pmid’, ‘pmcid’, and ‘doi’ containing the corresponding IDs, or an empty dict if lookup fails.
- Return type
bioRxiv client (indra.literature.biorxiv_client)
A client to obtain metadata and text content from bioRxiv (and to some extent medRxiv) preprints.
- indra.literature.biorxiv_client.get_collection_dois(collection_id, min_date=None)[source]
Get list of DOIs from a biorxiv/medrxiv collection.
- Parameters
collection_id (str) – The identifier of the collection to fetch.
min_date (Optional[datetime.datetime]) – A datetime object representing an cutoff. If given, only publications that were released on or after the given date are returned. By default, no date constraint is applied.
- Returns
The list of DOIs in the collection.
- Return type
- indra.literature.biorxiv_client.get_collection_pubs(collection_id, min_date=None)[source]
Get list of DOIs from a biorxiv/medrxiv collection.
- Parameters
collection_id (str) – The identifier of the collection to fetch.
min_date (Optional[datetime.datetime]) – A datetime object representing an cutoff. If given, only publications that were released on or after the given date are returned. By default, no date constraint is applied.
- Returns
A list of the publication entries which include the abstract and other metadata.
- Return type
- indra.literature.biorxiv_client.get_content_from_pub_json(pub, format)[source]
Get text content based on a given format from a publication JSON.
In the case of abstract, the content is returned from the JSON directly. For pdf, the content is returned as bytes that can be dumped into a file. For txt and xml, the text is processed out of either the raw XML or text content that rxiv provides.
- indra.literature.biorxiv_client.get_formats(pub)[source]
Return formats available for a publication JSON.
- indra.literature.biorxiv_client.get_pdf_xml_url_base(content)[source]
Return base URL to PDF/XML based on the content of the landing page.
- indra.literature.biorxiv_client.get_text_from_rxiv_text(rxiv_text)[source]
Return clean text from the raw rxiv text content.
This function parses out the title, headings and subheadings, and the content of sections under headings/subheadings. It filters out some irrelevant content e.g., references and footnotes.
CrossRef client (indra.literature.crossref_client)
- indra.literature.crossref_client.doi_query(pmid, search_limit=10)[source]
Get the DOI for a PMID by matching CrossRef and Pubmed metadata.
Searches CrossRef using the article title and then accepts search hits only if they have a matching journal ISSN and page number with what is obtained from the Pubmed database.
- indra.literature.crossref_client.get_fulltext_links(doi)[source]
Return a list of links to the full text of an article given its DOI. Each list entry is a dictionary with keys: - URL: the URL to the full text - content-type: e.g. text/xml or text/plain - content-version - intended-application: e.g. text-mining
COCI client (indra.literature.coci_client)
Client to COCI, the OpenCitations Index of Crossref open DOI-to-DOI citations.
For more information on the COCI, see: https://opencitations.net/index/coci with API documentation at https://opencitations.net/index/coci/api/v1/.
- indra.literature.coci_client.get_citation_count_for_doi(doi)[source]
Return the citation count for a given DOI.
Note that the COCI API returns a count of 0 for DOIs that are not indexed.
- indra.literature.coci_client.get_citation_count_for_pmid(pmid)[source]
Return the citation count for a given PMID.
This uses the CrossRef API to get the DOI for the PMID, and then calls the COCI API to get the citation count for the DOI.
If the DOI lookup failed, this returns None. Note that the COCI API returns a count of 0 for DOIs that are not indexed.
Elsevier client (indra.literature.elsevier_client)
- For information on the Elsevier API, see:
API Specification: http://dev.elsevier.com/api_docs.html
Authentication: https://dev.elsevier.com/tecdoc_api_authentication.html
- indra.literature.elsevier_client.check_entitlement(doi)[source]
Check whether IP and credentials enable access to content for a doi.
This function uses the entitlement endpoint of the Elsevier API to check whether an article is available to a given institution. Note that this feature of the API is itself not available for all institution keys.
- indra.literature.elsevier_client.download_article(id_val, id_type='doi', on_retry=False)[source]
Low level function to get an XML article for a particular id.
- Parameters
- Returns
content – If found, the content string is returned, otherwise, None is returned.
- Return type
str or None
- indra.literature.elsevier_client.download_article_from_ids(**id_dict)[source]
Download an article in XML format from Elsevier matching the set of ids.
- Parameters
<id_type> (str) – You can enter any combination of eid, doi, pmid, and/or pii. Ids will be checked in that order, until either content has been found or all ids have been checked.
- Returns
content – If found, the content is returned as a string, otherwise None is returned.
- Return type
str or None
- indra.literature.elsevier_client.download_from_search(query_str, folder, do_extract_text=True, max_results=None)[source]
Save raw text files based on a search for papers on ScienceDirect.
This performs a search to get PIIs, downloads the XML corresponding to the PII, extracts the raw text and then saves the text into a file in the designated folder.
- Parameters
query_str (str) – The query string to search with
folder (str) – The local path to an existing folder in which the text files will be dumped
do_extract_text (bool) – Choose whether to extract text from the xml, or simply save the raw xml files. Default is True, so text is extracted.
max_results (int or None) – Default is None. If specified, limit the number of results to the given maximum.
- indra.literature.elsevier_client.extract_paragraphs(xml_string)[source]
Get paragraphs from the body of the given Elsevier xml.
- indra.literature.elsevier_client.extract_text(xml_string)[source]
Get text from the body of the given Elsevier xml.
- indra.literature.elsevier_client.get_abstract(doi)[source]
Get the abstract text of an article from Elsevier given a doi.
- indra.literature.elsevier_client.get_article(doi, output_format='txt')[source]
Get the full body of an article from Elsevier.
- Parameters
doi (str) – The doi for the desired article.
output_format ('txt' or 'xml') – The desired format for the output. Selecting ‘txt’ (default) strips all xml tags and joins the pieces of text in the main text, while ‘xml’ simply takes the tag containing the body of the article and returns it as is . In the latter case, downstream code needs to be able to interpret Elsever’s XML format.
- Returns
content – Either text content or xml, as described above, for the given doi.
- Return type
- indra.literature.elsevier_client.get_dois(query_str, year=None, loaded_after=None)[source]
Search ScienceDirect through the API for articles and return DOIs.
- Parameters
- Returns
dois – The list of DOIs identifying the papers returned by the search.
- Return type
- indra.literature.elsevier_client.get_piis(query_str)[source]
Search ScienceDirect through the API for articles and return PIIs.
Note that ScienceDirect has a limitation in which a maximum of 6,000 PIIs can be retrieved for a given search and therefore this call is internally broken up into multiple queries by a range of years and the results are combined.
- indra.literature.elsevier_client.get_piis_for_date(query_str, year=None, loaded_after=None)[source]
Search ScienceDirect through the API for articles and return PIIs.
- Parameters
- Returns
piis – The list of PIIs identifying the papers returned by the search.
- Return type
- indra.literature.elsevier_client.search_science_direct(query_str, field_name, year=None, loaded_after=None)[source]
Search ScienceDirect for a given field with a query string.
Users can specify which field they are interested in and only values from that field will be returned. It is also possible to restrict the search either to a specific year of publication or to papers published after a specific date.
- Parameters
query_str (str) – The query string to search with.
field_name (str) – A name of the field of interest to be returned. Accepted values are: authors, doi, loadDate, openAccess, pages, pii, publicationDate, sourceTitle, title, uri, volumeIssue.
year (Optional[str]) – The year to constrain the search to.
loaded_after (Optional[str]) – Date formatted as ‘yyyy-MM-dd’T’HH:mm:ssX’ to constrain the search to articles loaded after this date.
- Returns
all_parts – The list of values from the field of interest identifying the papers returned by the search.
- Return type
NewsAPI client (indra.literature.newsapi_client)
This module provides a client for the NewsAPI web service (https://newsapi.org/). The web service requires an API key which is available after registering at https://newsapi.org/account. This key can be set as NEWSAPI_API_KEY in the INDRA config file or as an environmental variable with the same name.
NewsAPI also requires attribution e.g. “powered by NewsAPI.org” for derived uses.
- indra.literature.newsapi_client.send_request(endpoint, **kwargs)[source]
Return the response to a query as JSON from the NewsAPI web service.
The basic API is limited to 100 results which is chosen unless explicitly given as an argument. Beyond that, paging is supported through the “page” argument, if needed.
- Parameters
endpoint (str) – Endpoint to query, e.g. “everything” or “top-headlines”
kwargs (dict) – A list of keyword arguments passed as parameters with the query. The basic ones are “q” which is the search query, “from” is a start date formatted as for instance 2018-06-10 and “to” is an end date with the same format.
- Returns
res_json – The response from the web service as a JSON dict.
- Return type
Adeft Tools (indra.literature.adeft_tools)
This file provides several functions helpful for acquiring texts for Adeft disambiguation.
It offers the ability to get text content for articles containing a particular gene. This is useful for aquiring training texts for genes genes that do not appear in a defining pattern with a problematic shortform.
General XML processing is also provided that allows for extracting text from a source that may be either of Elsevier XML, NLM XML or raw text. This is helpful because it avoids having to know in advance the source of text content from the database.
- indra.literature.adeft_tools.filter_paragraphs(paragraphs, contains=None)[source]
Filter paragraphs to only those containing one of a list of strings
- Parameters
- Returns
Plaintext consisting of all input paragraphs containing at least one of the supplied tokens.
- Return type
- indra.literature.adeft_tools.get_text_content_for_gene(hgnc_name)[source]
Get articles that have been annotated to contain gene in entrez
- indra.literature.adeft_tools.get_text_content_for_pmids(pmids)[source]
Get text content for articles given a list of their pmids
- indra.literature.adeft_tools.universal_extract_paragraphs(xml)[source]
Extract paragraphs from xml that could be from different sources
First try to parse the xml as if it came from elsevier. if we do not have valid elsevier xml this will throw an exception. the text extraction function in the pmc client may not throw an exception when parsing elsevier xml, silently processing the xml incorrectly
- indra.literature.adeft_tools.universal_extract_text(xml, contains=None)[source]
Extract plaintext from xml that could be from different sources
- Parameters
- Returns
The concatentation of all paragraphs in the input xml, excluding paragraphs not containing one of the tokens in the list contains. Paragraphs are separated by new lines.
- Return type