Merge pull request #15 from DanShatford/remove-unused-imports

Remove unused imports

examples/batch_process.py

@@ -1,31 +1,22 @@
-from collections import Counter
-from pathlib import Path
+import logging
 import time
+from pathlib import Path
 
-import typer
-import pandas as pd 
-import spacy
-from spacy.language import Language
-from spacy.tokens import Token, Doc
-from spacy.pipeline import Pipe
-import numpy as np
 import jsonlines
-from tqdm import tqdm
-import re
-import torch
+import numpy as np
 import pandas as pd
+import spacy
+import torch
+import typer
+from torch.utils.data import DataLoader
+from tqdm import tqdm
+from utilities import spacy_doc_setup
 
-from torch.utils.data import Dataset, DataLoader
 import mordecai3.elastic_utilities as es_util
 from mordecai3.geoparse import doc_to_ex_expanded
+from mordecai3.roberta_qa import setup_qa
 from mordecai3.torch_model import ProductionData, geoparse_model
-from mordecai3.roberta_qa import setup_qa 
-from utilities import spacy_doc_setup
 
-from elasticsearch import Elasticsearch, helpers
-from elasticsearch_dsl import Search, Q
-
-import logging
 logger = logging.getLogger()
 handler = logging.StreamHandler()
 formatter = logging.Formatter(

examples/batch_process_production.py

@@ -1,27 +1,23 @@
-from collections import Counter
-from pathlib import Path
+import logging
+import re
 import time
 from configparser import ConfigParser
+from pathlib import Path
 
-import typer
-import pandas as pd 
-import spacy
-import numpy as np
 import jsonlines
-from tqdm import tqdm
-import re
-import torch
+import numpy as np
 import pandas as pd
-
+import spacy
+import torch
+import typer
 from torch.utils.data import DataLoader
+from tqdm import tqdm
+
 import mordecai3.elastic_utilities as es_util
 from mordecai3.geoparse import Geoparser, doc_to_ex_expanded
 from mordecai3.torch_model import ProductionData
-from mordecai3.roberta_qa import setup_qa
 from mordecai3.utilities import spacy_doc_setup
 
-
-import logging
 logger = logging.getLogger(__name__)
 handler = logging.StreamHandler()
 formatter = logging.Formatter(

examples/production_event.py

@@ -1,22 +1,19 @@
-import json
-
+import numpy as np
+import pandas as pd
+import spacy
 import streamlit as st
 import torch
-import pandas as pd
 from elasticsearch import Elasticsearch
-from elasticsearch_dsl import Search, Q
-import spacy
-from spacy.tokens import Token, Doc
-from spacy.pipeline import Pipe
-import numpy as np
+from elasticsearch_dsl import Search
 from torch.utils.data import DataLoader
 
 import mordecai3.elastic_utilities as es_util
 from mordecai3.geoparse import doc_to_ex_expanded
+from mordecai3.roberta_qa import add_event_loc, setup_qa
 from mordecai3.torch_model import ProductionData, geoparse_model
-from mordecai3.roberta_qa import setup_qa, add_event_loc
 from mordecai3.utilities import spacy_doc_setup
 
+
 # for dumping raw output to JSON
 # https://stackoverflow.com/a/52604722
 def default(obj):

mordecai3/elastic_utilities.py

@@ -1,12 +1,13 @@
-from elasticsearch import Elasticsearch, helpers
-from elasticsearch_dsl import Search, Q
-import numpy as np
-import jellyfish
-from collections import Counter
-import warnings
+import logging
 import re
+import warnings
+from collections import Counter
+
+import jellyfish
+import numpy as np
+from elasticsearch import Elasticsearch
+from elasticsearch_dsl import Q, Search
 
-import logging
 logger = logging.getLogger(__name__)
 logger.addHandler(logging.NullHandler())
 

mordecai3/error_analysis.py

@@ -1,17 +1,17 @@
-from torch_model import TrainData, geoparse_model
-from train import load_data
-from torch.utils.data import DataLoader
-import torch
+import logging
 from collections import Counter
-import numpy as np
-from rich.console import Console
-from rich.table import Table
-import typer
 from pathlib import Path
 
+import numpy as np
+import torch
+import typer
 from error_utils import evaluate_results, make_wandb_dict
+from rich.console import Console
+from rich.table import Table
+from torch.utils.data import DataLoader
+from torch_model import TrainData, geoparse_model
+from train import load_data
 
-import logging
 logger = logging.getLogger()
 handler = logging.StreamHandler()
 formatter = logging.Formatter(
@@ -40,7 +40,6 @@
 import wandb
 
 
-
 def make_missing_table(cutoff, names, datasets):
     table = Table(show_header=True, header_style="bold magenta")
     table.add_column("Dataset")

mordecai3/error_utils.py

@@ -1,6 +1,6 @@
-import torch
-import numpy as np
 import haversine as hs
+import numpy as np
+import torch
 
 #es_data = datasets[2]
 #loader = data_loaders[2]

mordecai3/geoparse.py

@@ -1,24 +1,24 @@
-import jsonlines
-from tqdm import tqdm
-import re
+import logging
 import os
+import re
 
-import torch
-import pandas as pd
-import spacy
-from spacy.language import Language
-from spacy.tokens import Token, Span, Doc
-from spacy.pipeline import Pipe
 import numpy as np
-from torch.utils.data import Dataset, DataLoader
 import pkg_resources
-
-from mordecai3.elastic_utilities import make_conn, get_entry_by_id, get_adm1_country_entry, get_country_entry, add_es_data_doc
-from mordecai3.torch_model import ProductionData, geoparse_model
-from mordecai3.roberta_qa import setup_qa, add_event_loc
+import spacy
+import torch
+from torch.utils.data import DataLoader
+
+from mordecai3.elastic_utilities import (
+    add_es_data_doc,
+    get_adm1_country_entry,
+    get_country_entry,
+    get_entry_by_id,
+    make_conn,
+)
 from mordecai3.mordecai_utilities import spacy_doc_setup
+from mordecai3.roberta_qa import add_event_loc, setup_qa
+from mordecai3.torch_model import ProductionData, geoparse_model
 
-import logging
 logger = logging.getLogger()
 handler = logging.StreamHandler() 
 formatter = logging.Formatter(

mordecai3/mordecai_streamlit.py

@@ -1,21 +1,12 @@
-import spacy
-from spacy.language import Language
-from spacy.tokens import Token, Doc
-from spacy.pipeline import Pipe
 import numpy as np
-import jsonlines
-from tqdm import tqdm
-import re
+import spacy
 import streamlit as st
 import torch
-from torch.utils.data import Dataset, DataLoader
-
-from elastic_utilities import res_formatter, add_es_data
-from torch_model import ProductionData, geoparse_model
-from geoparse import doc_to_ex_expanded, Geoparser
-
-from elasticsearch import Elasticsearch, helpers
-from elasticsearch_dsl import Search, Q
+from elasticsearch import Elasticsearch
+from elasticsearch_dsl import Search
+from spacy.language import Language
+from spacy.tokens import Token
+from torch_model import geoparse_model
 
 HTML_WRAPPER = """<div style="overflow-x: auto; border: 1px solid #e6e9ef; border-radius: 0.25rem; padding: 1rem; margin-bottom: 2.5rem">{}</div>"""
 

mordecai3/mordecai_utilities.py

@@ -1,6 +1,6 @@
-from spacy.tokens import Token
-from spacy.language import Language
 import numpy as np
+from spacy.language import Language
+from spacy.tokens import Token
 
 #def make_country_dict():
 #    country = pd.read_csv("assets/wikipedia-iso-country-codes.txt")

mordecai3/roberta_qa.py

@@ -1,5 +1,5 @@
-from transformers import AutoModelForQuestionAnswering, AutoTokenizer, pipeline
 from spacy.tokens import Span
+from transformers import pipeline
 
 model_name = "deepset/roberta-base-squad2"
 

mordecai3/tests/conftest.py

@@ -1,7 +1,7 @@
-from ..geoparse import Geoparser
 import pytest
 
-import spacy
+from ..geoparse import Geoparser
+
 
 @pytest.fixture(scope='session', autouse=True)
 def geo():

mordecai3/tests/test_mordecai3.py

@@ -1,7 +1,9 @@
 import pytest
+
 from .. import elastic_utilities as es_utils
 from .. import geoparse
 
+
 def test_statement_event_loc(geo):
     text = "Speaking from Berlin, President Obama expressed his hope for a peaceful resolution to the fighting in Homs and Aleppo."
     #text = "President Obama expressed his hope for a peaceful resolution to the fighting."

mordecai3/torch_model.py

@@ -1,15 +1,15 @@
 ## Read in the BERT embedding for each place name
 ## and predict the country using pytorch
-import numpy as np
 import json
+import logging
 import os
 
+import numpy as np
 import torch
 import torch.nn as nn
-from torch.utils.data import Dataset
 from pandas import read_csv
+from torch.utils.data import Dataset
 
-import logging
 logger = logging.getLogger(__name__)
 handler = logging.StreamHandler()
 formatter = logging.Formatter(

mordecai3/train.py

@@ -1,36 +1,36 @@
-import random
+import os
 import pickle
+import random
 import re
-import os
+
 import jsonlines
+
 os.environ['KMP_DUPLICATE_LIB_OK']='True'
 
+import datetime
+import logging
+
+import elastic_utilities as es_util
 import numpy as np
-from tqdm import tqdm
+import spacy
 import torch
-import torch.optim as optim
 import torch.nn as nn
-from torch.utils.data import  DataLoader
-import xmltodict
-import wandb
+import torch.optim as optim
 import typer
-import spacy
-from spacy.tokens import DocBin
-import datetime
-import multiprocessing
+import wandb
+import xmltodict
+from error_utils import make_wandb_dict
+from geoparse import guess_in_rel
 
-from torch_model import geoparse_model
-import elastic_utilities as es_util
 # Currently getting this error: ImportError: attempted relative import with no known parent package
 # when I run the line below.
 # from .mordecai_utilities import spacy_doc_setup
 from mordecai_utilities import spacy_doc_setup
-from torch_model import TrainData
-from error_utils import make_wandb_dict
-from geoparse import guess_in_rel
-import elasticsearch
+from spacy.tokens import DocBin
+from torch.utils.data import DataLoader
+from torch_model import TrainData, geoparse_model
+from tqdm import tqdm
 
-import logging
 logger = logging.getLogger()
 handler = logging.StreamHandler()
 formatter = logging.Formatter(
@@ -625,8 +625,8 @@ def train(batch_size: int = typer.Option(32, "--batch_size"),         # input ba
     loss_func=nn.CrossEntropyLoss() # single label, multi-class
     optimizer = optim.Adam(model.parameters(), lr=config.lr)
     if config.avg_params:
-        from torch.optim.swa_utils import AveragedModel, SWALR
         from torch.optim.lr_scheduler import CosineAnnealingLR
+        from torch.optim.swa_utils import SWALR, AveragedModel
 
         swa_model = AveragedModel(model)
         scheduler = CosineAnnealingLR(optimizer, T_max=config.epochs+1)

setup.py

@@ -1,4 +1,5 @@
-from setuptools import setup, find_packages
+from setuptools import find_packages, setup
+
 setup(
     name = 'mordecai3',
     version='3.0.0a',