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Update pages/0 FileChecker.py
Browse files- pages/0 FileChecker.py +59 -5
pages/0 FileChecker.py
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@@ -1,5 +1,7 @@
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import streamlit as st
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import pandas as pd
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#===config===
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st.set_page_config(
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@@ -34,10 +36,23 @@ def get_ext(extype):
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@st.cache_data(ttl=3600)
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def upload(extype):
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keywords = pd.read_csv(uploaded_file)
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return keywords
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@st.cache_data(ttl=3600)
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def conv_txt(extype):
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col_dict = {'TI': 'Title',
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'SO': 'Source title',
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'DE': 'Author Keywords',
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@@ -45,16 +60,48 @@ def conv_txt(extype):
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'AB': 'Abstract',
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'TC': 'Cited by',
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'PY': 'Year',
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'ID': 'Keywords Plus'
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return keywords
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st.header('File Checker', anchor=False)
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st.subheader('Put your file here...', anchor=False)
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#===read data===
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uploaded_file = st.file_uploader('', type=['csv','txt'], on_change=reset_data)
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if uploaded_file is not None:
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extype = get_ext(uploaded_file)
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@@ -64,8 +111,15 @@ if uploaded_file is not None:
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elif extype.endswith('.txt'):
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data = conv_txt(extype)
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with col1:
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#===check keywords===
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keycheck = list(data.columns)
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import streamlit as st
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import pandas as pd
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import json
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from tools import sourceformat as sf
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#===config===
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st.set_page_config(
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@st.cache_data(ttl=3600)
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def upload(extype):
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keywords = pd.read_csv(uploaded_file)
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if "dimensions" in uploaded_file.name.lower():
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keywords = sf.dim(keywords)
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col_dict = {'MeSH terms': 'Keywords',
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'PubYear': 'Year',
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'Times cited': 'Cited by',
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'Publication Type': 'Document Type'
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}
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keywords.rename(columns=col_dict, inplace=True)
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return keywords
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@st.cache_data(ttl=3600)
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def conv_txt(extype):
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if("PMID" in (uploaded_file.read()).decode()):
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uploaded_file.seek(0)
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papers = sf.medline(uploaded_file)
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print(papers)
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return papers
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col_dict = {'TI': 'Title',
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'SO': 'Source title',
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'DE': 'Author Keywords',
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'AB': 'Abstract',
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'TC': 'Cited by',
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'PY': 'Year',
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'ID': 'Keywords Plus',
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'rights_date_used': 'Year'}
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uploaded_file.seek(0)
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papers = pd.read_csv(uploaded_file, sep='\t')
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if("htid" in papers.columns):
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papers = sf.htrc(papers)
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papers.rename(columns=col_dict, inplace=True)
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print(papers)
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return papers
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@st.cache_data(ttl=3600)
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def conv_json(extype):
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col_dict={'title': 'title',
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'rights_date_used': 'Year',
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'content_provider_code':'Source title'
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}
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data = json.load(uploaded_file)
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hathifile = data['gathers']
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keywords = pd.DataFrame.from_records(hathifile)
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keywords = sf.htrc(keywords)
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keywords['Cited by'] = keywords.groupby(['Keywords'])['Keywords'].transform('size')
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keywords.rename(columns=col_dict,inplace=True)
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return keywords
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@st.cache_data(ttl=3600)
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def conv_pub(extype):
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if (get_ext(extype)).endswith('.tar.gz'):
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bytedata = extype.read()
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keywords = sf.readPub(bytedata)
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elif (get_ext(extype)).endswith('.xml'):
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bytedata = extype.read()
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keywords = sf.readxml(bytedata)
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return keywords
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st.header('File Checker', anchor=False)
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st.subheader('Put your file here...', anchor=False)
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#===read data===
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uploaded_file = st.file_uploader('', type=['csv','txt','json', 'tar.gz', 'xml'], on_change=reset_data)
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if uploaded_file is not None:
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extype = get_ext(uploaded_file)
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elif extype.endswith('.txt'):
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data = conv_txt(extype)
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elif extype.endswith('.json'):
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data = conv_json(extype)
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elif extype.endswith('.tar.gz') or extype.endswith('.xml'):
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data = conv_pub(uploaded_file)
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col1, col2, col3 = st.columns(3)
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with col1:
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#===check keywords===
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keycheck = list(data.columns)
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