Skip to main content

A pythonic query builder for arXiv search API

Project description

arXiv Query Language

PyPI Tests

The arXiv search API enables filtering articles based on various fields such as "title", "author", "category", etc. Queries follow the format {field_prefix}:{value}, e.g., ti:AlexNet. The query language supports combining field filters using logical operators AND, OR, ANDNOT. Constructing these queries manually presents two challenges:

  1. Writing syntactically correct query strings with abbreviated field prefixes
  2. Navigating numerous arXiv category identifiers

This repository provides a pythonic query builder to address both challenges. See the arxiv documentation for the official Search API details. See the arXiv Search API behavior section for API behavior details and caveats.

Installation

pip install arxivql

Query

The Query class provides constructors for all supported arXiv fields and methods to combine them.

Field Constructors

from arxivql import Query as Q

# Single word search
print(Q.title('word'))
# Output:
# ti:word

# Exact phrase and author name searches
print(Q.abstract('some words'))
print(Q.author("Ilya Sutskever"))
# Output:
# abs:"some words"
# au:"Ilya Sutskever"

Multi-word field values are automatically double-quoted for exact phrase matching. For ANY word matching, pass a list to the constructor:

Q.abstract(["Syntactic", "natural language processing", "synthetic corpus"])
# Output:
# abs:(Syntactic "natural language processing" "synthetic corpus")

For ALL words matching, pass a tuple to the constructor:

Q.abstract(("Syntactic", "natural language processing", "synthetic corpus"))
# Output:
# abs:(Syntactic AND "natural language processing" AND "synthetic corpus")

Note: All searches are case-insensitive.

Date Filtering

Filter by submission date range using datetime or date objects. For convenience, None (the default) arguments make the date range open-ended. Timezone-aware datetimes are converted to UTC.

from datetime import date, datetime
from arxivql import Query as Q

# Date range (times default to 00:00 GMT)
Q.submitted_date(date(2023, 1, 1), date(2024, 1, 1))
# Output: submittedDate:[202301010000 TO 202401010000]

# With specific times
Q.submitted_date(datetime(2023, 1, 1, 6, 0), datetime(2024, 1, 1, 6, 0))
# Output: submittedDate:[202301010600 TO 202401010600]

# Open-ended ranges (None for no bound)
Q.author("Terence Tao") & Q.submitted_date(date(2020, 1, 1), None)  # From 2020 onwards
# Output: (au:"Terence Tao" AND submittedDate:[202001010000 TO 900001010000])

Q.title("GPT") & ~Q.submitted_date(None, date(2023, 1, 1))  # Exclude before 2023
# Output: (ti:GPT ANDNOT submittedDate:[100001010000 TO 202301010000])

Logical Operations

Complex queries can be constructed by combining field filters using regular python logic operators:

a1 = Q.author("Ilya Sutskever")
a2 = Q.author(("Geoffrey", "Hinton"))
c1 = Q.category("cs.NE")  # See taxonomy section for preferred category construction
c2 = Q.category("cs.CL")

# AND operator
q1 = a1 & a2 & c1
# Output:
# ((au:"Ilya Sutskever" AND au:(Geoffrey AND Hinton)) AND cat:cs.NE)

# OR operator
q2 = (a1 | a2) & (c1 | c2)
# Output:
# ((au:"Ilya Sutskever" OR au:(Geoffrey AND Hinton)) AND (cat:cs.NE OR cat:cs.CL))

# ANDNOT operator
q3 = a1 & ~a2
# Output:
# (au:"Ilya Sutskever" ANDNOT au:(Geoffrey AND Hinton))

The following operations raise exceptions due to arXiv API limitations:

~a1       # Error: standalone NOT operator not supported
a1 | ~a2  # Error: ORNOT operator not supported

Wildcards

Wildcards (? and *) can be used in queries as usual. See the arXiv Search API behavior section for more details.

Category Taxonomy

The Taxonomy class provides a structured interface for managing arXiv categories. Basic usage:

from arxivql import Taxonomy as T

print(T.cs.AI)
print(Q.category(T.cs.AI))
print(Q.category(T.cs))
print(Q.category((T.cs.LG, T.stat.ML)) & Q.title("LLM"))
# Output:
# cs.AI
# cat:cs.AI
# cat:cs.*
# (cat:(cs.LG AND stat.ML) AND ti:LLM)

Note the wildcard syntax in archive-level queries (e.g., T.cs).

The Taxonomy class provides comprehensive category information:

category = T.astro_ph.HE
print("id:          ", category.id)
print("name:        ", category.name)
print("group_name:  ", category.group_name)
print("archive_id:  ", category.archive_id)
print("archive_name:", category.archive_name)
print("description: ", category.description)
# Output:
# id:           astro-ph.HE
# name:         High Energy Astrophysical Phenomena
# group_name:   Physics
# archive_id:   astro-ph
# archive_name: Astrophysics
# description:  Cosmic ray production, acceleration, propagation, detection. Gamma ray astronomy and bursts, X-rays, charged particles, supernovae and other explosive phenomena, stellar remnants and accretion systems, jets, microquasars, neutron stars, pulsars, black holes

The library also provides useful category catalog:

from arxivql.taxonomy import catalog, categories_by_id

print(len(categories_by_id.keys()))
# Output:
# 157

print(len(catalog.all_categories))
# Output:
# 157

print(len(catalog.all_archives))
print(Q.category(catalog.all_archives))
# Output:
# 20
# cat:(cs.* econ.* eess.* math.* q-bio.* q-fin.* stat.* astro-ph* cond-mat* nlin.* physics.* gr-qc hep-ex hep-lat hep-ph hep-th math-ph nucl-ex nucl-th quant-ph)

# Broad Machine Learning categories, see official classification guide
# https://blog.arxiv.org/2019/12/05/arxiv-machine-learning-classification-guide
print(len(catalog.ml_broad))
print(Q.category(catalog.ml_broad))
# Output:
# 16
# cat:(cs.LG stat.ML math.OC cs.CV cs.CL eess.AS cs.IR cs.HC cs.SI cs.CY cs.GR cs.SY cs.AI cs.MM cs.ET cs.NE)

# Core Machine Learning categories according to Andrej Karpathy's `arxiv sanity preserver` project:
# https://github.com/karpathy/arxiv-sanity-preserver
print(len(catalog.ml_karpathy))
print(Q.category(catalog.ml_karpathy))
# Output:
# 6
# cat:(cs.CV cs.AI cs.CL cs.LG cs.NE stat.ML)

Usage with Python arXiv Client

Constructed queries can be directly used in python arXiv API wrapper:

# pip install arxiv

import arxiv
from arxivql import Query as Q, Taxonomy as T

query = Q.author("Ilya Sutskever") & Q.title("autoencoders") & ~Q.category(T.cs.AI)
search = arxiv.Search(query=query)
client = arxiv.Client()
results = list(client.results(search))

print(f"query = {query}")
for result in results:
    print(result.get_short_id(), result.title)

# Output:
# query = ((au:"Ilya Sutskever" AND ti:autoencoders) ANDNOT cat:cs.AI)
# 1611.02731v2 Variational Lossy Autoencoder

Important arXiv Search API Behavior

  • Category searches consider all listed categories, not only primary ones.

  • arXiv supports two wildcard characters: ? and *.

    • ? replaces one character in a word
    • * replaces zero or more characters in a word
    • They don't match the first character of the term, i.e., au:??tskever fails, but au:Sutske??? is okay
    • Categories can also be "wildcarded", i.e., cat:cs.?I is a valid filter
    • ? and * can be combined, e.g., cat:q-?i* is valid and matches both q-bio and q-fin
    • Text fields other than author and category are stemmed (see the notes on normalization and API quirks below), which means that wildcards often do not work as expected on them.
  • arXiv search engine internally normalizes input terms before matching (based on observed behavior -- this is not documented in the official API):

    • Terms are lowercased, hyphens are replaced with spaces, text is tokenized into words, and each token is stemmed with a Porter-like stemmer before being reassembled into a query string.

    • Example normalizations:

      • transformerstransform
      • self-attention mechanismsself attent mechan
    • This normalization also applies to quoted searches. For example, ti:"mechanics" can match both "mechanic" and "mechanism", because mechanics is normalized to mechan. More on quoted-query behavior below.

    • The author field is not stemmed, so au:john and au:johns are different queries.

    • Because of this normalization, the following queries are equivalent:

      abs:("self-attention mechanisms")
      abs:("Mechanisms Attention Self")
      abs:"self-attention mechanisms"
      abs:"selfs attentive mechanics"
      abs:"-- selfs -- --- attentive----mechanics --"
      abs:("-- -- mechaniC --- ATTENTIVE----seLfs --")
      
    • You can approximate this normalization locally using NLTK:

      import nltk
      
      nltk.download("punkt_tab")
      stemmer = nltk.PorterStemmer()
      
      
      def normalize_text(text: str) -> str:
          text_clean = text.lower()
          text_clean = text_clean.replace("-", " ")
          tokens = nltk.word_tokenize(text_clean)
          stemmed = [stemmer.stem(token) for token in tokens]
          return " ".join(stemmed)
      
      
      print(normalize_text("transformers"))
      print(normalize_text("self-attention mechanisms"))
      # Output:
      # transform
      # self attent mechan
      
  • Quoted items imply exact matching, but:

    • For regular text fields (i.e., all except categories), this behaves like an AND operator over all normalized words in the quoted phrase in any order (see normalization note above), rather than strict character-by-character phrase matching.
    • For categories, quoted multi-category queries don't work at all. For example, cat:"hep-th cs.AI" and cat:"cs.* hep-th" don't match anything and give zero results. The Q.category constructor in this library raises an exception for this case.
    • Single categories can be quoted (cat:"cs.*"), but this is redundant.
    • Beyond the usages above, double quotes are special characters and should be carefully handled. They often give unintuitive results: for example, ti:" returns an error, while ti:"", ti:"""", and ti:""""" return identical matches without a " character in them, and ""2""" is equivalent to ""2"" but not to "2".
    • This library raises exceptions for most such problematic queries.
  • Spaces between terms or fields imply OR operations: cat:hep-th cat:cs.AI equals cat:hep-th OR cat:cs.AI

  • Parentheses serve two purposes:

    1. Grouping logical operations
    2. Defining field scope, e.g., ti:(some words) treats spaces as OR operations. Examples:
      • cat:(cs.AI hep-th) matches articles with either category
      • cat:(cs.* hep-th) functions as expected with wildcards
    3. Note that several categories inside cat parentheses are okay.
  • Explicit operators in field scopes are supported: ti:(some OR words) and ti:(some AND words) are valid.

  • The id_list parameter (and legacy id: field filter) in the arXiv Search API is used internally to filter over the "major" article IDs (2410.21276), not the "version" IDs (2410.21276v1).

    • When used with a non-empty query:
      # pip install arxiv
      
      arxiv.Search(query="au:Sutskever", id_list=["2303.08774v6"])  # zero results
      arxiv.Search(query="au:Sutskever", id_list=["2303.08774"])    # -> 2303.08774v6 (latest)
      
    • BUT if the query is left empty, id_list and id: can be used to search for the exact article version:
      arxiv.Search(id_list=["2303.08774"])     # -> 2303.08774v6 (latest)
      arxiv.Search(id_list=["2303.08774v4"])   # -> 2303.08774v4
      arxiv.Search(id_list=["2303.08774v5"])   # -> 2303.08774v5
      arxiv.Search(id_list=["2303.08774v99"])  # -> obscure error
      
  • Empty query matches all article, i.e., no filtering is applied.

  • There are some other unintuitive API quirks:

    • Query all:- (or just -) matches actual "-" character across different article fields. But ti:- and abs:- match nothing.
    • Query all:atte?tion works as expected, but abs:atte?tion returns only 5 matches and ti:atte?tion returns zero matches.
    • Queries ti:atten? and ti:atten* return identical results, as if "attention" was searched for. But ti:attent? returns nothing. This is probably because the stem of "attention" is "attent", which matches atten? but not attent?.
    • And likely more.

arXiv Categories Taxonomy

The arXiv taxonomy consists of three hierarchical levels: group → archive → category. For complete details, consult the arXiv Category Taxonomy and arXiv Catchup Interface.

Category

Categories represent the finest granularity of classification. Category identifiers typically follow the pattern {archive}.{category}, with some exceptions noted below. Example: In astro-ph.HE, the hierarchy is:

  • Group: Physics
  • Archive: Astrophysics
  • Category: High Energy Astrophysical Phenomena
  • Queryable ID: astro-ph.HE

Group

Groups constitute the top level of taxonomy, currently including:

  • Computer Science
  • Economics
  • Electrical Engineering and Systems Science
  • Mathematics
  • Physics
  • Quantitative Biology
  • Quantitative Finance
  • Statistics

Archive

Archives form the intermediate level, with each belonging to exactly one group.

Special cases:

  1. Single-archive groups:

    • When a group contains only one archive, they share the same name
    • Example: q-fin.CP category has Quantitative FinanceQuantitative FinanceComputational Finance
  2. Single-category archives:

    • When an archive contains only one category, the archive name is omitted from the identifier
    • Example: hep-th category has PhysicsHigh Energy Physics - TheoryHigh Energy Physics - Theory

Note: The Physics group contains a Physics archive alongside other archives, which may cause confusion.

Testing

The library includes a comprehensive test suite.

Unit Tests

Unit tests verify query construction without making arXiv API calls:

pip install pytest
pytest tests/

Manual Live arXiv API Tests

Live tests make actual requests to the arXiv API to verify query behavior:

pip install arxiv
python tests/live_arxiv_queries.py

or

pytest tests/live_arxiv_queries.py

Note: Live tests are not run by pytest (the file is intentionally not prefixed with test_).

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

arxivql-1.0.3.tar.gz (31.0 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

arxivql-1.0.3-py3-none-any.whl (27.4 kB view details)

Uploaded Python 3

File details

Details for the file arxivql-1.0.3.tar.gz.

File metadata

  • Download URL: arxivql-1.0.3.tar.gz
  • Upload date:
  • Size: 31.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/2.0.1 CPython/3.13.3 Darwin/23.4.0

File hashes

Hashes for arxivql-1.0.3.tar.gz
Algorithm Hash digest
SHA256 15e5873d729f4c5b31b2d571261400e77faee4c5a2139256ef91fdcac7a8e834
MD5 64677ca06965a35d4bcdd060e5bd6984
BLAKE2b-256 4f3ebb7bc1b9d1c23668adda522ad4775fbbf07e570f5c526383067fcf8e6e8e

See more details on using hashes here.

File details

Details for the file arxivql-1.0.3-py3-none-any.whl.

File metadata

  • Download URL: arxivql-1.0.3-py3-none-any.whl
  • Upload date:
  • Size: 27.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/2.0.1 CPython/3.13.3 Darwin/23.4.0

File hashes

Hashes for arxivql-1.0.3-py3-none-any.whl
Algorithm Hash digest
SHA256 f937663946b884872e2457d0ff016f3ca4f59390d133844eaa07779451b9b6f6
MD5 e5fa413922e72bf6461604dd9f7dbe6a
BLAKE2b-256 a97d58c6a477f611720e0185bc6d456aaecdaca001061b53f5da04b3fbdbd988

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page