--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/filter_kw_val.py	Wed Sep 19 05:01:15 2018 -0400
@@ -0,0 +1,266 @@
+import argparse, re, csv
+
+def options():
+    """
+    Parse options:
+        -i, --input     Input filename and boolean value if the file contains header ["filename,true/false"]
+        --kw            Keyword to be filtered, the column number where this filter applies, 
+                        boolean value if the keyword should be filtered in exact ["keyword,ncol,true/false"].
+                        This option can be repeated: --kw "kw1,c1,true" --kw "kw2,c1,false" --kw "kw3,c2,true"
+        --kwfile        A file that contains keywords to be filter, the column where this filter applies and 
+                        boolean value if the keyword should be filtered in exact ["filename,ncol,true/false"]
+        --value         The value to be filtered, the column number where this filter applies and the 
+                        operation symbol ["value,ncol,=/>/>=/</<=/!="]
+        --values_range  range of values to be keep, example : --values_range 5 20 c1 true 
+        --operator      The operator used to filter with several keywords/values : AND or OR
+        --o --output    The output filename
+        --filtered_file    The file contains removed lines
+        -s --sort_col   Used column to sort the file, ",true" for reverse sorting, ",false" otherwise example : c1,false
+    """
+    parser = argparse.ArgumentParser()
+    parser.add_argument("-i", "--input", help="Input file", required=True)
+    parser.add_argument("--kw", nargs="+", action="append", help="")
+    parser.add_argument("--kw_file", nargs="+", action="append", help="")
+    parser.add_argument("--value", nargs="+", action="append", help="")
+    parser.add_argument("--values_range", nargs="+", action="append", help="")
+    parser.add_argument("--operator", default="OR", type=str, choices=['AND','OR'],help='')
+    parser.add_argument("-o", "--output", default="output.txt")
+    parser.add_argument("--filtered_file", default="filtered_output.txt")
+    parser.add_argument("-s","--sort_col", help="")
+
+    args = parser.parse_args()
+    filters(args)
+
+def str_to_bool(v):
+    if v.lower() in ('yes', 'true', 't', 'y', '1'):
+        return True
+    elif v.lower() in ('no', 'false', 'f', 'n', '0'):
+        return False
+    else:
+        raise argparse.ArgumentTypeError('Boolean value expected.')
+
+#Check if a variable is a float or an integer
+def is_number(number_format, n):
+    float_format = re.compile(r"^[-]?[0-9][0-9]*.?[0-9]+$")
+    int_format = re.compile(r"^[-]?[0-9][0-9]*$")
+    test = ""
+    if number_format == "int":
+        test = re.match(int_format, n)
+    elif number_format == "float":
+        test = re.match(float_format, n)
+    if test:
+        return True
+
+#Filter the document
+def filters(args):
+    filename = args.input.split(",")[0]
+    header = str_to_bool(args.input.split(",")[1])
+    csv_file = read_file(filename)
+    results_dict = {}
+
+    if args.kw:
+        keywords = args.kw
+        for k in keywords:
+            results_dict=filter_keyword(csv_file, header, results_dict, k[0], k[1], k[2])
+
+    if args.kw_file:
+        key_files = args.kw_file
+        for kf in key_files:
+            keywords = read_option(kf[0])
+            results_dict=filter_keyword(csv_file, header, results_dict, keywords, kf[1], kf[2])
+
+    if args.value:
+        for v in args.value:
+            if is_number("float", v[0]):
+                results_dict = filter_value(csv_file, header, results_dict, v[0], v[1], v[2])
+            else:
+                raise ValueError("Please enter a number in filter by value")
+
+    if args.values_range:
+        for vr in args.values_range:
+            if (is_number("float", vr[0]) or is_number("int", vr[0])) and (is_number("float",vr[1]) or is_number("int",vr[1])):
+                results_dict = filter_values_range(csv_file, header, results_dict, vr[0], vr[1], vr[2], vr[3])
+
+    remaining_lines=[]
+    filtered_lines=[]
+
+    if header is True : 
+        remaining_lines.append(csv_file[0])
+        filtered_lines.append(csv_file[0])
+
+    for id_line,line in enumerate(csv_file) :
+        if id_line in results_dict :   #skip header and empty lines
+            if args.operator == 'OR' :
+                if any(results_dict[id_line]) :
+                    filtered_lines.append(line)
+                else : 
+                    remaining_lines.append(line)
+
+            elif args.operator == "AND" :
+                if all(results_dict[id_line]) :
+                    filtered_lines.append(line)
+                else : 
+                    remaining_lines.append(line)
+    
+    #sort of results by column
+    if args.sort_col :
+        sort_col=args.sort_col.split(",")[0]
+        sort_col=column_from_txt(sort_col)
+        reverse=str_to_bool(args.sort_col.split(",")[1])
+        remaining_lines= sort_by_column(remaining_lines,sort_col,reverse,header)
+        filtered_lines = sort_by_column(filtered_lines,sort_col,reverse,header)
+    
+    # Write results to output
+    with open(args.output,"w") as output :
+        writer = csv.writer(output,delimiter="\t")
+        writer.writerows(remaining_lines)
+
+    # Write filtered lines to filtered_output
+    with open(args.filtered_file,"w") as filtered_output :
+        writer = csv.writer(filtered_output,delimiter="\t")
+        writer.writerows(filtered_lines)
+
+#function to sort the csv_file by value in a specific column
+def sort_by_column(tab,sort_col,reverse,header):
+    
+    if len(tab) > 1 : #if there's more than just a header or 1 row
+        if header is True :
+            head=tab[0]
+            tab=tab[1:]
+
+        if is_number("int",tab[0][sort_col]) :
+            tab = sorted(tab, key=lambda row: int(row[sort_col]), reverse=reverse)
+        elif is_number("float",tab[0][sort_col]) :
+            tab = sorted(tab, key=lambda row: float(row[sort_col]), reverse=reverse)
+        else :
+            tab = sorted(tab, key=lambda row: row[sort_col], reverse=reverse)
+        
+        if header is True : tab = [head]+tab
+
+    return tab
+
+#Read the keywords file to extract the list of keywords
+def read_option(filename):
+    with open(filename, "r") as f:
+        filter_list=f.read().splitlines()
+    filter_list=[key for key in filter_list if len(key.replace(' ',''))!=0]
+    filters=";".join(filter_list)
+
+    return filters
+
+# Read input file
+def read_file(filename):
+    with open(filename,"r") as f :
+        reader=csv.reader(f,delimiter="\t")
+        tab=list(reader)
+
+    # Remove empty lines (contain only space or new line or "")
+    #[tab.remove(blank) for blank in tab if blank.isspace() or blank == ""]
+    tab=[line for line in tab if len("".join(line).replace(" ","")) !=0 ]
+    
+    return tab
+
+#seek for keywords in rows of csvfile, return a dictionary of boolean (true if keyword found, false otherwise) 
+def filter_keyword(csv_file, header, results_dict, keywords, ncol, match):
+    match=str_to_bool(match)
+    ncol=column_from_txt(ncol)
+
+    keywords = keywords.upper().split(";")                                            # Split list of filter keyword
+    [keywords.remove(blank) for blank in keywords if blank.isspace() or blank == ""]  # Remove blank keywords
+    keywords = [k.strip() for k in keywords]        # Remove space from 2 heads of keywords
+
+    for id_line,line in enumerate(csv_file):
+        if header is True and id_line == 0 : continue
+        #line = line.replace("\n", "")
+        keyword_inline = line[ncol].replace('"', "").split(";")
+        #line = line + "\n"
+
+        #Perfect match or not
+        if match is True :
+            found_in_line = any(pid.upper() in keywords for pid in keyword_inline)
+        else: 
+            found_in_line = any(ft in pid.upper() for pid in keyword_inline for ft in keywords)     
+
+        #if the keyword is found in line
+        if id_line in results_dict : results_dict[id_line].append(found_in_line)
+        else : results_dict[id_line]=[found_in_line]
+
+    return results_dict
+
+#filter ba determined value in rows of csvfile, return a dictionary of boolean (true if value filtered, false otherwise)
+def filter_value(csv_file, header, results_dict, filter_value, ncol, opt):
+
+    filter_value = float(filter_value)
+    ncol=column_from_txt(ncol)
+
+    for id_line,line in enumerate(csv_file):
+        if header is True and id_line == 0 : continue
+        value = line[ncol].replace('"', "").strip()
+        if value.replace(".", "", 1).isdigit():
+            to_filter=value_compare(value,filter_value,opt)
+            
+            #adding the result to the dictionary
+            if id_line in results_dict : results_dict[id_line].append(to_filter)
+            else : results_dict[id_line]=[to_filter]
+            
+    return results_dict
+
+#filter ba determined value in rows of csvfile, return a dictionary of boolean (true if value filtered, false otherwise)
+def filter_values_range(csv_file, header, results_dict, bottom_value, top_value, ncol, inclusive):
+    inclusive=str_to_bool(inclusive)
+    bottom_value = float(bottom_value)
+    top_value=float(top_value)
+    ncol=column_from_txt(ncol)
+
+    for id_line, line in enumerate(csv_file):
+        if header is True and id_line == 0 : continue
+        value = line[ncol].replace('"', "").strip()
+        if value.replace(".", "", 1).isdigit():
+            value=float(value)
+            if inclusive is True:
+                in_range = not (bottom_value <= value <= top_value)
+            else : 
+                in_range = not (bottom_value < value < top_value)
+
+            #adding the result to the dictionary
+            if id_line in results_dict : results_dict[id_line].append(in_range)
+            else : results_dict[id_line]=[in_range]
+
+    return results_dict 
+
+def column_from_txt(ncol):
+    if is_number("int", ncol.replace("c", "")): 
+        ncol = int(ncol.replace("c", "")) - 1 
+    else:
+        raise ValueError("Please specify the column where "
+                         "you would like to apply the filter "
+                         "with valid format")
+    return ncol
+
+#return True if value is in the determined values, false otherwise
+def value_compare(value,filter_value,opt):
+    test_value=False
+
+    if opt == "<":
+        if float(value) < filter_value:
+            test_value = True
+    elif opt == "<=":
+        if float(value) <= filter_value:
+            test_value = True
+    elif opt == ">":
+        if float(value) > filter_value:
+            test_value = True
+    elif opt == ">=":
+        if float(value) >= filter_value:
+            test_value = True
+    elif opt == "=":
+        if float(value) == filter_value:
+            test_value = True
+    elif opt == "!=": 
+        if float(value) != filter_value:
+            test_value = True
+
+    return test_value
+
+if __name__ == "__main__":
+    options()