Mercurial > repos > ggricourt > data_manager_bigg

annotate data_manager/bigg_model_sbml_fetcher.py @ 15:44119168868c draft default tip

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"planemo upload for repository https://github.com/brsynth/synbiocad-galaxy-wrappers commit 7db54c0555a12ecb8b3f756032228c54fe028e0a-dirty"
author ggricourt
date Wed, 09 Mar 2022 15:44:01 +0000
parents e339b8d84de0
children
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262b8d79bc08 "planemo upload for repository https://github.com/brsynth/synbiocad-galaxy-wrappers commit 19ad973add8651c1a18c1bda789e9296a57044b1"
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1 import argparse
262b8d79bc08 "planemo upload for repository https://github.com/brsynth/synbiocad-galaxy-wrappers commit 19ad973add8651c1a18c1bda789e9296a57044b1"
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2 import json
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3 import os
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4 import sys
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5 import time
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6 try:
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7 # For Python 3.0 and later
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8 from urllib.request import Request, urlopen
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9 except ImportError:
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10 # Fall back to Python 2 imports
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11 from urllib2 import Request, urlopen
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12
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14 MODEL_URL = "http://bigg.ucsd.edu/static/models/"
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15 MODEL_DETAIL_URL = "http://bigg.ucsd.edu/api/v2/models/"
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18 def url_download(url, path):
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19 try:
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20 with urlopen(Request(url)) as fod:
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21 with open(path, "wb") as dst:
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22 while True:
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23 chunk = fod.read(2**10)
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24 if chunk:
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25 dst.write(chunk)
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26 else:
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27 break
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28 except Exception as e:
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29 sys.exit(str(e))
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32 def url_json(url):
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33 data = {}
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34 try:
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35 with urlopen(Request(url)) as fod:
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36 data = fod.read().decode("utf-8")
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37 data = json.loads(data)
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38 except Exception as e:
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39 sys.exit(str(e))
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40 return data
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42
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43 def download_entries(model_ids, id2org, workdir):
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44 for ix, model_id in enumerate(model_ids):
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45 model_filename = model_id + ".xml"
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46 path = os.path.abspath(os.path.join(workdir, model_filename))
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47
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48 url_download(MODEL_URL + model_filename, path)
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49 data_manager_entry = {}
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50 data_manager_entry["value"] = model_id
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51 data_manager_entry["name"] = model_id + " - " + id2org[model_id]
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52 data_manager_entry["path"] = path
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53
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54 # Make sure that less than 10 requests per second, as required by host (http://bigg.ucsd.edu/data_access)
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55 if ix % 5 == 0:
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56 time.sleep(1)
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57 yield data_manager_entry
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59
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60 if __name__ == "__main__":
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61 parser = argparse.ArgumentParser()
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62 pinput = parser.add_mutually_exclusive_group(required=True)
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63 pinput.add_argument("--model-id", help="Model BIGG id")
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64 pinput.add_argument("--model-all", action="store_true", help="Download all models")
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65 parser.add_argument("--out-file", help="JSON output file")
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66 args = parser.parse_args()
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67
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68 # Init.
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69 data_manager_json = {"data_tables": {}}
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70 with open(args.out_file) as fh:
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71 params = json.load(fh)
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72
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73 workdir = params["output_data"][0]["extra_files_path"]
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74 os.makedirs(workdir)
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75
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76 # Load models and models metadata.
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77 models = url_json(MODEL_DETAIL_URL)
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78 id2org = {}
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79 for result in models.get("results", []):
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80 ident = result["bigg_id"]
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81 ident = ident.replace(" ", "")
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82 id2org[ident] = result["organism"]
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83
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84 # Select model_ids.
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85 model_ids = []
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86 if args.model_id:
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87 if args.model_id not in id2org.keys():
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88 sys.exit("Model id: %s is not available" % (args.model_id,))
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89 model_ids.append(args.model_id)
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90 else:
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91 model_ids.extend(list(id2org.keys()))
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92
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93 # Download.
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94 entries = list(download_entries(model_ids, id2org, workdir))
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95
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96 # Write data.
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97 data_manager_json["data_tables"]["bigg_model_sbml"] = entries
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98 with open(args.out_file, "w") as fh:
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99 json.dump(data_manager_json, fh, sort_keys=True)