diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index 40dbf8b..8b31264 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -5,7 +5,8 @@ on: push: branches: - main - + schedule: + - cron: '19 6 * * *' # Allows you to run this workflow manually from the Actions tab workflow_dispatch: diff --git a/prepareJsons_and_Bib.ipynb b/prepareJsons_and_Bib.ipynb index 20f1e4a..c681607 100644 --- a/prepareJsons_and_Bib.ipynb +++ b/prepareJsons_and_Bib.ipynb @@ -10,7 +10,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 5, "metadata": {}, "outputs": [], "source": [ @@ -18,15 +18,6 @@ "import pandas as pd" ] }, - { - "cell_type": "code", - "execution_count": 18, - "metadata": {}, - "outputs": [], - "source": [ - "conf_file = json.load(open(\"_data/Conference.json\"))" - ] - }, { "attachments": {}, "cell_type": "markdown", @@ -37,326 +28,236 @@ }, { "cell_type": "code", - "execution_count": 54, - "metadata": {}, - "outputs": [], - "source": [ - "confs = pd.read_json(\"_data/Conference.json\")\n", - "confs.dropna(inplace=True)" - ] - }, - { - "cell_type": "code", - "execution_count": 114, + "execution_count": 10, "metadata": {}, "outputs": [ { "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
titlelocationdateurl
1HEP Software Training with HSF/IRIS-HEPNew Perspectives Meeting (Fermilab, Batavia, I...2023-06-27https://indico.fnal.gov/event/59506/contributi...
2Trigger Development for Emerging Jet Analysis ...FNAL 56st Annual Users Meeting (Fermilab, Bata...2023-06-28https://indico.fnal.gov/event/59656/contributi...
3Teaching Python the Sustainable Way: Lessons L...PyHEP 2022 Workshop (Virtual)2022-09-12https://indico.cern.ch/event/1150631/contribut...
4PyROOT tutorial experience from SWC Workshop12th ROOT Users' Workshop (Virtual)2022-05-10https://indico.fnal.gov/event/23628/contributi...
5New Trigger Studies for Emerging Jets at CMS E...PRIMS/JTM Conference (Humacao, Puerto Rico)2022-04-09/assets/pdfs/PRISM_BetterPoster_EMJ.pdf
6Recent Progress in ML for Tracker DQMDPF Conference (Virtual)2021-07-12https://indico.cern.ch/event/1034469/contribut...
7Machine Learning in DQM at CMS ExperimentPhyscon Conference (Rhode Island, USA)2019-11-13/assets/pdfs/Physcon_Poster.pdf
8Machine Learning and Deep Neural Networks at C...Physics symposium (University of Puerto Rico M...2019-05-24http://charma.uprm.edu/~malik/Undergrad_Summer...
9Machine Learning in DQM at CMS ExperimentPRISM/JTM Conference (Mayagüez, Puerto Rico)2019-05-04/assets/pdfs/ML4DQM_PRISM_2019_Talk.pdf
10Using ML techniques for DQM at CMSML Hackathon (University of Puerto Rico Mayagüez)2019-04-25https://indico.cern.ch/event/809812/contributi...
11Machine Learning in DQM at CMS ExperimentFNAL 51st Annual Users Meeting and New Perspec...2018-06-18https://vms.fnal.gov/asset/detail?recid=1955984
\n", + "
" + ], "text/plain": [ - "'[{\"title\":\"HEP Software Training with HSF\\\\/IRIS-HEP\",\"location\":\"New Perspectives Meeting (Fermilab, Batavia, IL, USA)\",\"date\":\"2023-06-27T00:00:00.000Z\",\"url\":\"https:\\\\/\\\\/indico.fnal.gov\\\\/event\\\\/59506\\\\/contributions\\\\/269987\\\\/\"},{\"title\":\"Trigger Development for Emerging Jet Analysis (Poster)\",\"location\":\"FNAL 56st Annual Users Meeting (Fermilab, Batavia, IL, USA)\",\"date\":\"2023-06-28T00:00:00.000Z\",\"url\":\"https:\\\\/\\\\/indico.fnal.gov\\\\/event\\\\/59656\\\\/contributions\\\\/268969\\\\/\"},{\"title\":\"Teaching Python the Sustainable Way: Lessons Learned at HSF Training\",\"location\":\"PyHEP 2022 Workshop (Virtual)\",\"date\":\"2022-09-12T00:00:00.000Z\",\"url\":\"https:\\\\/\\\\/indico.cern.ch\\\\/event\\\\/1150631\\\\/contributions\\\\/5014278\\\\/\"},{\"title\":\"PyROOT tutorial experience from SWC Workshop\",\"location\":\"12th ROOT Users\\' Workshop (Virtual)\",\"date\":\"2022-05-10T00:00:00.000Z\",\"url\":\"https:\\\\/\\\\/indico.fnal.gov\\\\/event\\\\/23628\\\\/contributions\\\\/240752\\\\/\"},{\"title\":\"New Trigger Studies for Emerging Jets at CMS Experiment\",\"location\":\"PRIMS\\\\/JTM Conference (Humacao, Puerto Rico)\",\"date\":\"2022-04-09T00:00:00.000Z\",\"url\":\"\\\\/assets\\\\/pdfs\\\\/PRISM_BetterPoster_EMJ.pdf\"},{\"title\":\"Recent Progress in ML for Tracker DQM\",\"location\":\"DPF Conference (Virtual)\",\"date\":\"2021-07-12T00:00:00.000Z\",\"url\":\"https:\\\\/\\\\/indico.cern.ch\\\\/event\\\\/1034469\\\\/contributions\\\\/4434622\\\\/\"},{\"title\":\"Machine Learning in DQM at CMS Experiment\",\"location\":\"Physcon Conference (Rhode Island, USA)\",\"date\":\"2019-11-13T00:00:00.000Z\",\"url\":\"\\\\/assets\\\\/pdfs\\\\/Physcon_Poster.pdf\"},{\"title\":\"Machine Learning and Deep Neural Networks at CMS Experiment\",\"location\":\"Physics symposium (University of Puerto Rico Mayag\\\\u00fcez)\",\"date\":\"2019-05-24T00:00:00.000Z\",\"url\":\"http:\\\\/\\\\/charma.uprm.edu\\\\/~malik\\\\/Undergrad_Summer_Symposium\\\\/2019\\\\/GF_2019.pdf\"},{\"title\":\"Machine Learning in DQM at CMS Experiment\",\"location\":\"PRISM\\\\/JTM Conference (Mayag\\\\u00fcez, Puerto Rico)\",\"date\":\"2019-05-04T00:00:00.000Z\",\"url\":\"\\\\/assets\\\\/pdfs\\\\/ML4DQM_PRISM_2019_Talk.pdf\"},{\"title\":\"Using ML techniques for DQM at CMS\",\"location\":\"ML Hackathon (University of Puerto Rico Mayag\\\\u00fcez)\",\"date\":\"2019-04-25T00:00:00.000Z\",\"url\":\"https:\\\\/\\\\/indico.cern.ch\\\\/event\\\\/809812\\\\/contributions\\\\/3391219\\\\/\"},{\"title\":\"Machine Learning in DQM at CMS Experiment\",\"location\":\"FNAL 51st Annual Users Meeting and New Perspectives Meeting (Fermilab, Batavia, IL, USA) \",\"date\":\"2018-06-18T00:00:00.000Z\",\"url\":\"https:\\\\/\\\\/vms.fnal.gov\\\\/asset\\\\/detail?recid=1955984\"}]'" + " title \\\n", + "1 HEP Software Training with HSF/IRIS-HEP \n", + "2 Trigger Development for Emerging Jet Analysis ... \n", + "3 Teaching Python the Sustainable Way: Lessons L... \n", + "4 PyROOT tutorial experience from SWC Workshop \n", + "5 New Trigger Studies for Emerging Jets at CMS E... \n", + "6 Recent Progress in ML for Tracker DQM \n", + "7 Machine Learning in DQM at CMS Experiment \n", + "8 Machine Learning and Deep Neural Networks at C... \n", + "9 Machine Learning in DQM at CMS Experiment \n", + "10 Using ML techniques for DQM at CMS \n", + "11 Machine Learning in DQM at CMS Experiment \n", + "\n", + " location date \\\n", + "1 New Perspectives Meeting (Fermilab, Batavia, I... 2023-06-27 \n", + "2 FNAL 56st Annual Users Meeting (Fermilab, Bata... 2023-06-28 \n", + "3 PyHEP 2022 Workshop (Virtual) 2022-09-12 \n", + "4 12th ROOT Users' Workshop (Virtual) 2022-05-10 \n", + "5 PRIMS/JTM Conference (Humacao, Puerto Rico) 2022-04-09 \n", + "6 DPF Conference (Virtual) 2021-07-12 \n", + "7 Physcon Conference (Rhode Island, USA) 2019-11-13 \n", + "8 Physics symposium (University of Puerto Rico M... 2019-05-24 \n", + "9 PRISM/JTM Conference (Mayagüez, Puerto Rico) 2019-05-04 \n", + "10 ML Hackathon (University of Puerto Rico Mayagüez) 2019-04-25 \n", + "11 FNAL 51st Annual Users Meeting and New Perspec... 2018-06-18 \n", + "\n", + " url \n", + "1 https://indico.fnal.gov/event/59506/contributi... \n", + "2 https://indico.fnal.gov/event/59656/contributi... \n", + "3 https://indico.cern.ch/event/1150631/contribut... \n", + "4 https://indico.fnal.gov/event/23628/contributi... \n", + "5 /assets/pdfs/PRISM_BetterPoster_EMJ.pdf \n", + "6 https://indico.cern.ch/event/1034469/contribut... \n", + "7 /assets/pdfs/Physcon_Poster.pdf \n", + "8 http://charma.uprm.edu/~malik/Undergrad_Summer... \n", + "9 /assets/pdfs/ML4DQM_PRISM_2019_Talk.pdf \n", + "10 https://indico.cern.ch/event/809812/contributi... \n", + "11 https://vms.fnal.gov/asset/detail?recid=1955984 " ] }, - "execution_count": 114, + "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "confs.to_json(orient='records',date_format=\"iso\",)" + "confs = pd.read_json(\"_data/Conference.json\")\n", + "confs.dropna(inplace=True)\n", + "confs" ] }, { "cell_type": "code", - "execution_count": 115, + "execution_count": 18, "metadata": {}, "outputs": [], "source": [ - "result = confs.sort_values(\"date\",ascending=False).to_json(orient=\"records\",date_format='iso')\n", - "parsed = json.loads(result)\n", - "json.dump(parsed,open(\"_data/sorted_confs.json\",'w'), indent=4) " + "import pprint" ] }, { "cell_type": "code", - "execution_count": 79, + "execution_count": 19, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "\u001b[0;31mSignature:\u001b[0m\n", - "\u001b[0mconfs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mto_json\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\u001b[0m\n", - "\u001b[0;34m\u001b[0m \u001b[0mpath_or_buf\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;34m'FilePath | WriteBuffer[bytes] | WriteBuffer[str] | None'\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", - "\u001b[0;34m\u001b[0m \u001b[0morient\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;34m'str | None'\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", - "\u001b[0;34m\u001b[0m \u001b[0mdate_format\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;34m'str | None'\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", - "\u001b[0;34m\u001b[0m \u001b[0mdouble_precision\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;34m'int'\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m10\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", - "\u001b[0;34m\u001b[0m \u001b[0mforce_ascii\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;34m'bool_t'\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", - "\u001b[0;34m\u001b[0m \u001b[0mdate_unit\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;34m'str'\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m'ms'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", - "\u001b[0;34m\u001b[0m \u001b[0mdefault_handler\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;34m'Callable[[Any], JSONSerializable] | None'\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", - "\u001b[0;34m\u001b[0m \u001b[0mlines\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;34m'bool_t'\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mFalse\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", - "\u001b[0;34m\u001b[0m \u001b[0mcompression\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;34m'CompressionOptions'\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m'infer'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", - "\u001b[0;34m\u001b[0m \u001b[0mindex\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;34m'bool_t'\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", - "\u001b[0;34m\u001b[0m \u001b[0mindent\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;34m'int | None'\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", - "\u001b[0;34m\u001b[0m \u001b[0mstorage_options\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;34m'StorageOptions'\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", - "\u001b[0;34m\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m->\u001b[0m \u001b[0;34m'str | None'\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;31mDocstring:\u001b[0m\n", - "Convert the object to a JSON string.\n", - "\n", - "Note NaN's and None will be converted to null and datetime objects\n", - "will be converted to UNIX timestamps.\n", - "\n", - "Parameters\n", - "----------\n", - "path_or_buf : str, path object, file-like object, or None, default None\n", - " String, path object (implementing os.PathLike[str]), or file-like\n", - " object implementing a write() function. If None, the result is\n", - " returned as a string.\n", - "orient : str\n", - " Indication of expected JSON string format.\n", - "\n", - " * Series:\n", - "\n", - " - default is 'index'\n", - " - allowed values are: {'split', 'records', 'index', 'table'}.\n", - "\n", - " * DataFrame:\n", - "\n", - " - default is 'columns'\n", - " - allowed values are: {'split', 'records', 'index', 'columns',\n", - " 'values', 'table'}.\n", - "\n", - " * The format of the JSON string:\n", - "\n", - " - 'split' : dict like {'index' -> [index], 'columns' -> [columns],\n", - " 'data' -> [values]}\n", - " - 'records' : list like [{column -> value}, ... , {column -> value}]\n", - " - 'index' : dict like {index -> {column -> value}}\n", - " - 'columns' : dict like {column -> {index -> value}}\n", - " - 'values' : just the values array\n", - " - 'table' : dict like {'schema': {schema}, 'data': {data}}\n", - "\n", - " Describing the data, where data component is like ``orient='records'``.\n", - "\n", - "date_format : {None, 'epoch', 'iso'}\n", - " Type of date conversion. 'epoch' = epoch milliseconds,\n", - " 'iso' = ISO8601. The default depends on the `orient`. For\n", - " ``orient='table'``, the default is 'iso'. For all other orients,\n", - " the default is 'epoch'.\n", - "double_precision : int, default 10\n", - " The number of decimal places to use when encoding\n", - " floating point values.\n", - "force_ascii : bool, default True\n", - " Force encoded string to be ASCII.\n", - "date_unit : str, default 'ms' (milliseconds)\n", - " The time unit to encode to, governs timestamp and ISO8601\n", - " precision. One of 's', 'ms', 'us', 'ns' for second, millisecond,\n", - " microsecond, and nanosecond respectively.\n", - "default_handler : callable, default None\n", - " Handler to call if object cannot otherwise be converted to a\n", - " suitable format for JSON. Should receive a single argument which is\n", - " the object to convert and return a serialisable object.\n", - "lines : bool, default False\n", - " If 'orient' is 'records' write out line-delimited json format. Will\n", - " throw ValueError if incorrect 'orient' since others are not\n", - " list-like.\n", - "compression : str or dict, default 'infer'\n", - " For on-the-fly compression of the output data. If 'infer' and 'path_or_buf'\n", - " path-like, then detect compression from the following extensions: '.gz',\n", - " '.bz2', '.zip', '.xz', or '.zst' (otherwise no compression). Set to\n", - " ``None`` for no compression. Can also be a dict with key ``'method'`` set\n", - " to one of {``'zip'``, ``'gzip'``, ``'bz2'``, ``'zstd'``} and other\n", - " key-value pairs are forwarded to ``zipfile.ZipFile``, ``gzip.GzipFile``,\n", - " ``bz2.BZ2File``, or ``zstandard.ZstdDecompressor``, respectively. As an\n", - " example, the following could be passed for faster compression and to create\n", - " a reproducible gzip archive:\n", - " ``compression={'method': 'gzip', 'compresslevel': 1, 'mtime': 1}``.\n", - "\n", - " .. versionchanged:: 1.4.0 Zstandard support.\n", - "\n", - "index : bool, default True\n", - " Whether to include the index values in the JSON string. Not\n", - " including the index (``index=False``) is only supported when\n", - " orient is 'split' or 'table'.\n", - "indent : int, optional\n", - " Length of whitespace used to indent each record.\n", - "\n", - " .. versionadded:: 1.0.0\n", - "\n", - "storage_options : dict, optional\n", - " Extra options that make sense for a particular storage connection, e.g.\n", - " host, port, username, password, etc. For HTTP(S) URLs the key-value pairs\n", - " are forwarded to ``urllib`` as header options. For other URLs (e.g.\n", - " starting with \"s3://\", and \"gcs://\") the key-value pairs are forwarded to\n", - " ``fsspec``. Please see ``fsspec`` and ``urllib`` for more details.\n", - "\n", - " .. versionadded:: 1.2.0\n", - "\n", - "Returns\n", - "-------\n", - "None or str\n", - " If path_or_buf is None, returns the resulting json format as a\n", - " string. Otherwise returns None.\n", - "\n", - "See Also\n", - "--------\n", - "read_json : Convert a JSON string to pandas object.\n", - "\n", - "Notes\n", - "-----\n", - "The behavior of ``indent=0`` varies from the stdlib, which does not\n", - "indent the output but does insert newlines. Currently, ``indent=0``\n", - "and the default ``indent=None`` are equivalent in pandas, though this\n", - "may change in a future release.\n", - "\n", - "``orient='table'`` contains a 'pandas_version' field under 'schema'.\n", - "This stores the version of `pandas` used in the latest revision of the\n", - "schema.\n", - "\n", - "Examples\n", - "--------\n", - ">>> import json\n", - ">>> df = pd.DataFrame(\n", - "... [[\"a\", \"b\"], [\"c\", \"d\"]],\n", - "... index=[\"row 1\", \"row 2\"],\n", - "... columns=[\"col 1\", \"col 2\"],\n", - "... )\n", - "\n", - ">>> result = df.to_json(orient=\"split\")\n", - ">>> parsed = json.loads(result)\n", - ">>> json.dumps(parsed, indent=4) # doctest: +SKIP\n", - "{\n", - " \"columns\": [\n", - " \"col 1\",\n", - " \"col 2\"\n", - " ],\n", - " \"index\": [\n", - " \"row 1\",\n", - " \"row 2\"\n", - " ],\n", - " \"data\": [\n", - " [\n", - " \"a\",\n", - " \"b\"\n", - " ],\n", - " [\n", - " \"c\",\n", - " \"d\"\n", - " ]\n", - " ]\n", - "}\n", - "\n", - "Encoding/decoding a Dataframe using ``'records'`` formatted JSON.\n", - "Note that index labels are not preserved with this encoding.\n", - "\n", - ">>> result = df.to_json(orient=\"records\")\n", - ">>> parsed = json.loads(result)\n", - ">>> json.dumps(parsed, indent=4) # doctest: +SKIP\n", - "[\n", - " {\n", - " \"col 1\": \"a\",\n", - " \"col 2\": \"b\"\n", - " },\n", - " {\n", - " \"col 1\": \"c\",\n", - " \"col 2\": \"d\"\n", - " }\n", - "]\n", - "\n", - "Encoding/decoding a Dataframe using ``'index'`` formatted JSON:\n", - "\n", - ">>> result = df.to_json(orient=\"index\")\n", - ">>> parsed = json.loads(result)\n", - ">>> json.dumps(parsed, indent=4) # doctest: +SKIP\n", - "{\n", - " \"row 1\": {\n", - " \"col 1\": \"a\",\n", - " \"col 2\": \"b\"\n", - " },\n", - " \"row 2\": {\n", - " \"col 1\": \"c\",\n", - " \"col 2\": \"d\"\n", - " }\n", - "}\n", - "\n", - "Encoding/decoding a Dataframe using ``'columns'`` formatted JSON:\n", - "\n", - ">>> result = df.to_json(orient=\"columns\")\n", - ">>> parsed = json.loads(result)\n", - ">>> json.dumps(parsed, indent=4) # doctest: +SKIP\n", - "{\n", - " \"col 1\": {\n", - " \"row 1\": \"a\",\n", - " \"row 2\": \"c\"\n", - " },\n", - " \"col 2\": {\n", - " \"row 1\": \"b\",\n", - " \"row 2\": \"d\"\n", - " }\n", - "}\n", - "\n", - "Encoding/decoding a Dataframe using ``'values'`` formatted JSON:\n", - "\n", - ">>> result = df.to_json(orient=\"values\")\n", - ">>> parsed = json.loads(result)\n", - ">>> json.dumps(parsed, indent=4) # doctest: +SKIP\n", - "[\n", - " [\n", - " \"a\",\n", - " \"b\"\n", - " ],\n", - " [\n", - " \"c\",\n", - " \"d\"\n", - " ]\n", - "]\n", - "\n", - "Encoding with Table Schema:\n", - "\n", - ">>> result = df.to_json(orient=\"table\")\n", - ">>> parsed = json.loads(result)\n", - ">>> json.dumps(parsed, indent=4) # doctest: +SKIP\n", - "{\n", - " \"schema\": {\n", - " \"fields\": [\n", - " {\n", - " \"name\": \"index\",\n", - " \"type\": \"string\"\n", - " },\n", - " {\n", - " \"name\": \"col 1\",\n", - " \"type\": \"string\"\n", - " },\n", - " {\n", - " \"name\": \"col 2\",\n", - " \"type\": \"string\"\n", - " }\n", - " ],\n", - " \"primaryKey\": [\n", - " \"index\"\n", - " ],\n", - " \"pandas_version\": \"1.4.0\"\n", - " },\n", - " \"data\": [\n", - " {\n", - " \"index\": \"row 1\",\n", - " \"col 1\": \"a\",\n", - " \"col 2\": \"b\"\n", - " },\n", - " {\n", - " \"index\": \"row 2\",\n", - " \"col 1\": \"c\",\n", - " \"col 2\": \"d\"\n", - " }\n", - " ]\n", - "}\n", - "\u001b[0;31mFile:\u001b[0m ~/opt/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py\n", - "\u001b[0;31mType:\u001b[0m method\n" + "('[{\"title\":\"HEP Software Training with HSF\\\\/IRIS-HEP\",\"location\":\"New '\n", + " 'Perspectives Meeting (Fermilab, Batavia, IL, '\n", + " 'USA)\",\"date\":\"2023-06-27T00:00:00.000\",\"url\":\"https:\\\\/\\\\/indico.fnal.gov\\\\/event\\\\/59506\\\\/contributions\\\\/269987\\\\/\"},{\"title\":\"Trigger '\n", + " 'Development for Emerging Jet Analysis (Poster)\",\"location\":\"FNAL 56st Annual '\n", + " 'Users Meeting (Fermilab, Batavia, IL, '\n", + " 'USA)\",\"date\":\"2023-06-28T00:00:00.000\",\"url\":\"https:\\\\/\\\\/indico.fnal.gov\\\\/event\\\\/59656\\\\/contributions\\\\/268969\\\\/\"},{\"title\":\"Teaching '\n", + " 'Python the Sustainable Way: Lessons Learned at HSF '\n", + " 'Training\",\"location\":\"PyHEP 2022 Workshop '\n", + " '(Virtual)\",\"date\":\"2022-09-12T00:00:00.000\",\"url\":\"https:\\\\/\\\\/indico.cern.ch\\\\/event\\\\/1150631\\\\/contributions\\\\/5014278\\\\/\"},{\"title\":\"PyROOT '\n", + " 'tutorial experience from SWC Workshop\",\"location\":\"12th ROOT Users\\' '\n", + " 'Workshop '\n", + " '(Virtual)\",\"date\":\"2022-05-10T00:00:00.000\",\"url\":\"https:\\\\/\\\\/indico.fnal.gov\\\\/event\\\\/23628\\\\/contributions\\\\/240752\\\\/\"},{\"title\":\"New '\n", + " 'Trigger Studies for Emerging Jets at CMS Experiment\",\"location\":\"PRIMS\\\\/JTM '\n", + " 'Conference (Humacao, Puerto '\n", + " 'Rico)\",\"date\":\"2022-04-09T00:00:00.000\",\"url\":\"\\\\/assets\\\\/pdfs\\\\/PRISM_BetterPoster_EMJ.pdf\"},{\"title\":\"Recent '\n", + " 'Progress in ML for Tracker DQM\",\"location\":\"DPF Conference '\n", + " '(Virtual)\",\"date\":\"2021-07-12T00:00:00.000\",\"url\":\"https:\\\\/\\\\/indico.cern.ch\\\\/event\\\\/1034469\\\\/contributions\\\\/4434622\\\\/\"},{\"title\":\"Machine '\n", + " 'Learning in DQM at CMS Experiment\",\"location\":\"Physcon Conference (Rhode '\n", + " 'Island, '\n", + " 'USA)\",\"date\":\"2019-11-13T00:00:00.000\",\"url\":\"\\\\/assets\\\\/pdfs\\\\/Physcon_Poster.pdf\"},{\"title\":\"Machine '\n", + " 'Learning and Deep Neural Networks at CMS Experiment\",\"location\":\"Physics '\n", + " 'symposium (University of Puerto Rico '\n", + " 'Mayag\\\\u00fcez)\",\"date\":\"2019-05-24T00:00:00.000\",\"url\":\"http:\\\\/\\\\/charma.uprm.edu\\\\/~malik\\\\/Undergrad_Summer_Symposium\\\\/2019\\\\/GF_2019.pdf\"},{\"title\":\"Machine '\n", + " 'Learning in DQM at CMS Experiment\",\"location\":\"PRISM\\\\/JTM Conference '\n", + " '(Mayag\\\\u00fcez, Puerto '\n", + " 'Rico)\",\"date\":\"2019-05-04T00:00:00.000\",\"url\":\"\\\\/assets\\\\/pdfs\\\\/ML4DQM_PRISM_2019_Talk.pdf\"},{\"title\":\"Using '\n", + " 'ML techniques for DQM at CMS\",\"location\":\"ML Hackathon (University of Puerto '\n", + " 'Rico '\n", + " 'Mayag\\\\u00fcez)\",\"date\":\"2019-04-25T00:00:00.000\",\"url\":\"https:\\\\/\\\\/indico.cern.ch\\\\/event\\\\/809812\\\\/contributions\\\\/3391219\\\\/\"},{\"title\":\"Machine '\n", + " 'Learning in DQM at CMS Experiment\",\"location\":\"FNAL 51st Annual Users '\n", + " 'Meeting and New Perspectives Meeting (Fermilab, Batavia, IL, USA) '\n", + " '\",\"date\":\"2018-06-18T00:00:00.000\",\"url\":\"https:\\\\/\\\\/vms.fnal.gov\\\\/asset\\\\/detail?recid=1955984\"}]')\n" ] } ], "source": [ - "confs.to_json?" + "pprint.pprint(confs.to_json(orient='records',date_format=\"iso\",))" + ] + }, + { + "cell_type": "code", + "execution_count": 115, + "metadata": {}, + "outputs": [], + "source": [ + "result = confs.sort_values(\"date\",ascending=False).to_json(orient=\"records\",date_format='iso')\n", + "parsed = json.loads(result)\n", + "json.dump(parsed,open(\"_data/sorted_confs.json\",'w'), indent=4) " ] }, { @@ -436,7 +337,7 @@ }, { "cell_type": "code", - "execution_count": 158, + "execution_count": 3, "metadata": {}, "outputs": [ { @@ -444,9 +345,7 @@ "output_type": "stream", "text": [ "@misc{alexander_moreno_briceno_2022_7115834,\n", - " author = {Alexander Moreno Briceño and\n", - " Aman Goel and\n", - " Guillermo Antonio Fidalgo Rodriguez},\n", + " author = {Alexander Moreno Briceño and Aman Goel and Guillermo Antonio Fidalgo Rodriguez},\n", " title = {Teaching Python the Sustainable Way: Lessons Learned at HSF Training},\n", " month = sep,\n", " year = 2022,\n", @@ -459,10 +358,9 @@ } ], "source": [ - "zenodo = r\"\"\"@misc{alexander_moreno_briceno_2022_7115834,\n", - " author = {Alexander Moreno Briceño and\n", - " Aman Goel and\n", - " Guillermo Antonio Fidalgo Rodriguez},\n", + "zenodo = r\"\"\"\n", + "@misc{alexander_moreno_briceno_2022_7115834,\n", + " author = {Alexander Moreno Briceño and Aman Goel and Guillermo Antonio Fidalgo Rodriguez},\n", " title = {Teaching Python the Sustainable Way: Lessons Learned at HSF Training},\n", " month = sep,\n", " year = 2022,\n", @@ -512,10 +410,9 @@ "url = response.json()['links']['bibtex']\n", "inspire = requests.get(url).text\n", "\n", - "zenodo = r\"\"\"@misc{alexander_moreno_briceno_2022_7115834,\n", - " author = {Alexander Moreno Briceño and\n", - " Aman Goel and\n", - " Guillermo Antonio Fidalgo Rodriguez},\n", + "zenodo = r\"\"\"\n", + "@misc{alexander_moreno_briceno_2022_7115834,\n", + " author = {Alexander Moreno Briceño and Aman Goel and Guillermo Antonio Fidalgo Rodriguez},\n", " title = {Teaching Python the Sustainable Way: Lessons Learned at HSF Training},\n", " month = sep,\n", " year = 2022,\n", @@ -524,7 +421,7 @@ " url = {https://doi.org/10.5281/zenodo.7115834}\n", "}\n", "\"\"\"\n", - "with open(\"bibfile.bib\",'w') as f:\n", + "with open(\"_data/bibfile.bib\",'w') as f:\n", " f.write(inspire)\n", " f.write(zenodo)" ] @@ -559,18 +456,26 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "pandoc: _data/Publications.bib: openBinaryFile: does not exist (No such file or directory)\n" + ] + } + ], "source": [ - "! pandoc -C _data/Publications.bib -t markdown_strict \\\n", + "! pandoc -C bibfile.bib -t markdown_strict \\\n", "--csl american-physics-society.csl \\\n", "-o _includes/myPubs.md" ] }, { "cell_type": "code", - "execution_count": 107, + "execution_count": 1, "metadata": {}, "outputs": [ {