Add a script to query ADS to construct the list of papers citing SWIFT

data/pubs.yaml

-cards:
-  - title: "SWIFT: Fast algorithms for multi-resolution SPH on multi-core architectures"
-    date: "15 Sep 2013"
-    img: "matth.png"
-    link: "https://arxiv.org/abs/1309.3783"
-    journal: "Proceedinds of the 8th SPHERIC International Workshop"
-        
-  - title: "Efficient and Scalable Algorithms for Smoothed Particle Hydrodynamics on Hybrid Shared/Distributed-Memory Architectures"
-    date: "8 Apr 2014"
-    img: "pedro.png"
-    link: "https://arxiv.org/abs/1404.2303"
-    journal: "SIAM Journal on Scientific Computing"
-
-  - title: "SWIFT: task-based hydrodynamics and gravity for cosmological simulations"
-    date: "1 Aug 2015"
-    img: "tom_paper.jpg"
-    link: "https://arxiv.org/abs/1508.00115"
-    journal: "Proceedings of the EASC15 conference"
-
-  - title: "QuickSched: Task-based parallelism with dependencies and conflicts"
-    date: "20 Jan 2016"
-    img: "TaskConflicts.jpg"
-    link: "https://arxiv.org/abs/1601.05384"
-    journal: "Submitted to PeerJ Computer Science"
-
-  - title: "SWIFT: Using task-based parallelism, fully asynchronous communication, and graph partition-based domain decomposition for strong scaling on more than 100,000 cores"
-    date: "8 Jun 2016"
-    img: "domains.png"
-    link: "https://arxiv.org/abs/1606.02738"
-    journal: "Proceedings of the PASC16 conference"
-
-  - title: "An Efficient SIMD Implementation of Pseudo-Verlet Lists for Neighbour Interactions in Particle-Based Codes"
-    date: " Apr 2018"
-    img: "james_paper.png"
-    link: "https://arxiv.org/abs/1804.06231"
-    journal: "Advances in Parallel Computing, Volume 32"
-
-  - title: "SWIFT: Maintaining weak-scalability with a dynamic range of 10^4 in time-step size to harness extreme adaptivity"
-    date: " Jul 2018"
-    img: "spheric_2018.png"
-    link: "https://arxiv.org/abs/1807.01341"
-    journal: "Proceedings of the 13th SPHERIC International Workshop"

query.py

+from myads.query import ADSQueryWrapper
+import yaml
+import sys
+
+# Query papers citing the two SWIFT ADS entries
+query = ADSQueryWrapper(sys.argv[1])
+query_data = query.get("citations(2016pasc.conf....2S) or citations(2018ascl.soft05020S)", fl="title,bibcode,first_author_norm,date,year,doi,author_count,pub_raw", rows=1000)
+paper_list = query_data.papers
+
+# Process the data to make the title a string and not an array of strings
+for paper in paper_list:
+    paper.title = paper.title[0]
+    
+# Create a dictionary of cards
+my_list = dict({"cards": paper_list})
+
+# Silence the yaml object naming
+def noop(self, *args, **kw):
+    pass
+yaml.emitter.Emitter.process_tag = noop
+
+# Dump everything
+f = open('data/pubs.yaml', 'w+')
+yaml_string=yaml.dump(my_list, f,  allow_unicode=True, default_flow_style=False)
+f.close()