first full commit

README.md

@@ -1,8 +1,8 @@
 ---
-title: COBie Flat
-emoji: 💻
-colorFrom: gray
-colorTo: indigo
+title: Raci Create
+emoji: ⚡
+colorFrom: purple
+colorTo: red
 sdk: streamlit
 sdk_version: 1.10.0
 app_file: app.py

app.py

@@ -7,17 +7,17 @@ import numpy as np
 import pandas as pd
 import regex as re
 import streamlit as st
+import pickle
+import io
+import simplejson as json
+import base64
+import uuid
+
 
 
 # In[2]:
 
-cobie_file = pd.ExcelFile(path_to_cobie_file)
 
-cobie_floor_df = cobie_file.parse(sheet_name = 'Floor', dtype={'ExtIdentifier':str, 'Name':str})
-cobie_space_df = cobie_file.parse(sheet_name = 'Space', dtype={'ExtIdentifier':str, 'Name':str})
-cobie_type_df = cobie_file.parse(sheet_name = 'Type', dtype={'ExtIdentifier':str, 'Description':str, 'Name':str})
-cobie_system_df = cobie_file.parse(sheet_name = 'System', dtype={'ExtIdentifier':str, 'Description':str, 'Name':str})
-cobie_component_df = cobie_file.parse(sheet_name = 'Component', dtype={'ExtIdentifier':str, 'Space':str, 'Description':str, 'Name':str})
 
 
 def decodeIfc(txt):
@@ -48,83 +48,182 @@ def convert_unicode_string(row, column_name):
     return decodeIfc(row[column_name])
 
 
-columns_to_decode = ['Name', 'TypeName', 'Description']    
-for column_to_decode in columns_to_decode:
-    
-    cobie_flat[column_to_decode] = cobie_flat.apply(
-        convert_unicode_string,
-        column_name=column_to_decode,
-        axis=1
-    )
+def decode_cobie(cobie_df):
+
+    columns_to_decode = ['Name', 'TypeName', 'Description']    
+    for column_to_decode in columns_to_decode:
+        
+        cobie_df[column_to_decode] = cobie_df.apply(
+            convert_unicode_string,
+            column_name=column_to_decode,
+            axis=1
+        )
+
+    return cobie_df
 
 
 # In[3]:
 
-cobie_type_df.rename(columns={
-    'Name':'TypeName',
-    'ExtObject':'TypeExtObject',
-    'ExtIdentifier':'TypeExtIdentifier',
-}, inplace=True)
-
-cobie_type_component = pd.merge(
-    cobie_component_df[[
-        'Name','TypeName', 'Space',
-        'ExtObject', 'ExtIdentifier', 'SerialNumber',
-    ]],
-    cobie_type_df[[
-        'TypeName', 'Category', 'Description',
-        'Manufacturer', 'ModelNumber', 
-        'TypeExtObject', 'TypeExtIdentifier',
-    ]],
-    on='TypeName',
-    how='left', 
-)
+def combine_type_component(cobie_type_df, cobie_type_component):
+
+    cobie_type_df.rename(columns={
+        'Name':'TypeName',
+        'ExtObject':'TypeExtObject',
+        'ExtIdentifier':'TypeExtIdentifier',
+    }, inplace=True)
+
+    cobie_type_component = pd.merge(
+        cobie_component_df[[
+            'Name','TypeName', 'Space',
+            'ExtObject', 'ExtIdentifier', 'SerialNumber',
+        ]],
+        cobie_type_df[[
+            'TypeName', 'Category', 'Description',
+            'Manufacturer', 'ModelNumber', 
+            'TypeExtObject', 'TypeExtIdentifier',
+        ]],
+        on='TypeName',
+        how='left', 
+    )
+
+    return cobie_type_component
+
 
 
 # In[4]:
 
-cobie_system_df.rename(columns={
-    'Name':'SystemName',
-    'Description':'SystemDescription',
-    'Category':'SystemCategory',
-    'ComponentNames':'Name',
-}, inplace=True)
-system_all = cobie_system_df.explode(column='Name')
-
-cobie_flat = pd.merge(
-    cobie_type_component,
-    system_all[[
-        'SystemName', 'SystemDescription', 'SystemCategory',
-        'Name', 
-    ]],
-    on='Name',
-    how='left', 
-)
-
-cobie_flat = cobie_flat[[
-    'Name',
-    'TypeName', 
-    'Description',
-    'Category',
-    'SystemName',
-    'SystemDescription',
-    'SystemCategory',
-    'Space',
-    'ExtObject',
-    'ExtIdentifier',
-    'SerialNumber',
-    'Manufacturer',
-    'ModelNumber',
-    'TypeExtObject',
-    'TypeExtIdentifier',
-
-]]
+def combine_full_component_system(cobie_flat, cobie_system_df):
+
+    cobie_system_df.rename(columns={
+        'Name':'SystemName',
+        'Description':'SystemDescription',
+        'Category':'SystemCategory',
+        'ComponentNames':'Name',
+    }, inplace=True)
+    system_all = cobie_system_df.explode(column='Name')
+
+    cobie_flat = pd.merge(
+        cobie_type_component,
+        system_all[[
+            'SystemName', 'SystemDescription', 'SystemCategory',
+            'Name', 
+        ]],
+        on='Name',
+        how='left', 
+    )
+
+    cobie_flat = cobie_flat[[
+        'Name',
+        'TypeName', 
+        'Description',
+        'Category',
+        'SystemName',
+        'SystemDescription',
+        'SystemCategory',
+        'Space',
+        'ExtObject',
+        'ExtIdentifier',
+        'SerialNumber',
+        'Manufacturer',
+        'ModelNumber',
+        'TypeExtObject',
+        'TypeExtIdentifier',
+
+    ]]
+
+    return cobie_flat
 
 
 
 # In[5]:
 
+def download_button(object_to_download, download_filename, button_text, pickle_it=False):
+    """
+    Generates a link to download the given object_to_download.
+    Params:
+    ------
+    object_to_download:  The object to be downloaded.
+    download_filename (str): filename and extension of file. e.g. mydata.csv,
+    some_txt_output.txt download_link_text (str): Text to display for download
+    link.
+    button_text (str): Text to display on download button (e.g. 'click here to download file')
+    pickle_it (bool): If True, pickle file.
+    Returns:
+    -------
+    (str): the anchor tag to download object_to_download
+    Examples:
+    --------
+    download_link(your_df, 'YOUR_DF.csv', 'Click to download data!')
+    download_link(your_str, 'YOUR_STRING.txt', 'Click to download text!')
+    """
+    if pickle_it:
+        try:
+            object_to_download = pickle.dumps(object_to_download)
+        except pickle.PicklingError as e:
+            st.write(e)
+            return None
 
+    else:
+        if isinstance(object_to_download, bytes):
+            pass
+
+        elif isinstance(object_to_download, pd.DataFrame):
+            #object_to_download = object_to_download.to_csv(index=False)
+            towrite = io.BytesIO()
+            object_to_download = object_to_download.to_excel(
+                towrite,
+                encoding='utf-8',
+                index=False,
+                header=True,
+                na_rep=''
+            )
+            towrite.seek(0)
+
+        # Try JSON encode for everything else
+        else:
+            object_to_download = json.dumps(object_to_download)
+
+    try:
+        # some strings <-> bytes conversions necessary here
+        b64 = base64.b64encode(object_to_download.encode()).decode()
+
+    except AttributeError as e:
+        b64 = base64.b64encode(towrite.read()).decode()
+
+    button_uuid = str(uuid.uuid4()).replace('-', '')
+    button_id = re.sub('\d+', '', button_uuid)
+
+    custom_css = f""" 
+        <style>
+            #{button_id} {{
+                display: inline-flex;
+                align-items: center;
+                justify-content: center;
+                background-color: rgb(255, 255, 255);
+                color: rgb(38, 39, 48);
+                padding: .25rem .75rem;
+                position: relative;
+                text-decoration: none;
+                border-radius: 4px;
+                border-width: 1px;
+                border-style: solid;
+                border-color: rgb(230, 234, 241);
+                border-image: initial;
+            }} 
+            #{button_id}:hover {{
+                border-color: rgb(246, 51, 102);
+                color: rgb(246, 51, 102);
+            }}
+            #{button_id}:active {{
+                box-shadow: none;
+                background-color: rgb(246, 51, 102);
+                color: white;
+                }}
+        </style> """
+
+    dl_link = custom_css + f'<a download="{download_filename}" id="{button_id}" href="data:application/vnd.openxmlformats-officedocument.spreadsheetml.sheet;base64,{b64}">{button_text}</a><br></br>'
+
+    return dl_link
 
 # In[7]:
 
@@ -153,69 +252,34 @@ cobie_flat = cobie_flat[[
 
 
 
-
 # In[ ]:
 
-project_id_button = st.text_input("Project ID", key="project_id")
+cobie_file_button = st.text_input("Dropbox link to COBie file", key="cobie_file_button")
 
 # In[ ]:
 
-if project_id_button:
-
-    project_id = st.session_state.project_id
-    with st.spinner(text="In progress, this may take some time..."):
-        # db = sqlalchemy.create_engine(postgres_string)
-        # conn = psycopg2.connect(
-        #     dbname="EIR-BEP",
-        #     host="activodb.cnwtnluwiep3.eu-west-1.rds.amazonaws.com",
-        #     user="ianyeo",
-        #     password=password
-        # )
-        # st.write("Connected to database", str(conn))
-        project_responsibility_query = 'SELECT * from "projectResponsibility"'
-        project_specific_responsibility_query = f'SELECT * from "projectResponsibility" WHERE project_id = {project_id}'
-        raci_query = 'SELECT * from "raci"'
-        responsibility_query = 'SELECT * from "responsibility"'
-        project_responsibility_raci_query = 'SELECT * from "projectResponsibilityRACI"'
-        project_responsibility_raci_orgnanisation_query = 'SELECT * from "projectResponsibilityRACIorganisation"'
-        project_organisaion_query = 'SELECT po.organisation_id, org.name, org.organisation_codes FROM "projectorganisation" AS po JOIN "organisation" AS org ON po.organisation_id = org.id WHERE po.project_id = %(project_id)s'
-        test_query = '''
-            SELECT
-                precomputed.id
-            FROM rnc_rna_precomputed precomputed
-            JOIN rnc_taxonomy tax
-            ON
-                tax.id = precomputed.taxid
-            WHERE
-                tax.lineage LIKE 'cellular organisms; Bacteria; %%'
-            AND precomputed.is_active = true    -- exclude sequences without active cross-references
-            AND rna_type = 'rRNA'
-        '''
-        test_query2 = '''
-            SELECT
-                upi,     -- RNAcentral URS identifier
-                taxid,   -- NCBI taxid
-                ac       -- external accession
-            FROM xref
-            WHERE ac IN ('OTTHUMT00000106564.1', 'OTTHUMT00000416802.1')
-        '''
-        rows = run_query(project_specific_responsibility_query)
-        raci = pd.read_sql_query(raci_query, get_connection(), params={'project_id':project_id})
-        # test_data = pd.read_sql_query(test_query2, get_connection())
-
-        # project_responsibilities = pd.read_sql_query(project_responsibility_query, db, params={'project_id':project_id})
-        # responsibility = pd.read_sql_query(responsibility_query, db, params={'project_id':project_id})
-        # project_responsibility_raci = pd.read_sql_query(project_responsibility_raci_query, db, params={'project_id':project_id})
-        # project_organisaion = pd.read_sql_query(project_organisaion_query, db, params={'project_id':project_id})
-
-    # st.dataframe(project_organisaion)
-    st.dataframe(raci)
-
-    create_template_table = st.text_input("test", key="test")
-
-    if create_template_table:
-
-        download_table = st.session_state.test
-        # raci_table = create_raci_table(project_responsibilities, responsibility, project_responsibility_raci)
+if cobie_file_button:
+
+    cobie_file_path = st.session_state.cobie_file_button
+
+    if '=0' in cobie_file_path:
+
+        cobie_file_path = cobie_file_path.replace('=0', '=1')
+
+    cobie_file = pd.ExcelFile(cobie_file_path)
+    cobie_floor_df = cobie_file.parse(sheet_name = 'Floor', dtype={'ExtIdentifier':str, 'Name':str})
+    cobie_space_df = cobie_file.parse(sheet_name = 'Space', dtype={'ExtIdentifier':str, 'Name':str})
+    cobie_type_df = cobie_file.parse(sheet_name = 'Type', dtype={'ExtIdentifier':str, 'Description':str, 'Name':str})
+    cobie_system_df = cobie_file.parse(sheet_name = 'System', dtype={'ExtIdentifier':str, 'Description':str, 'Name':str})
+    cobie_component_df = cobie_file.parse(sheet_name = 'Component', dtype={'ExtIdentifier':str, 'Space':str, 'Description':str, 'Name':str})
+
+    
+    cobie_type_component = combine_type_component(cobie_type_df, cobie_component_df)
+    cobie_flat = combine_full_component_system(cobie_type_component, cobie_system_df)
+    cobie_flat = decode_cobie(cobie_flat)
+
+    file_name = 'cobie_flat.xlsx'
+    download_button_str = download_button(cobie_flat, file_name, f'Click here to download {file_name}', pickle_it=False)
+    st.markdown(download_button_str, unsafe_allow_html=True)
 
 

requirements.txt

@@ -0,0 +1,8 @@
+streamlit
+pandas
+numpy
+openpyxl
+simplejson
+# sqlalchemy
+# psycopg2-binary
+# https://www.dropbox.com/s/9yfqtw4qldma1kf/ifc-0.3.18h.tar.gz?dl=1