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| author | jjohnson |
|---|---|
| date | Wed, 05 Jul 2017 11:51:15 -0400 |
| parents | 5b4f6cf857cf |
| children | ab27c4bd14b9 |
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<tool id="query_tabular" name="Query Tabular" version="4.0.0"> <description>using sqlite sql</description> <requirements> </requirements> <stdio> <exit_code range="1:" /> </stdio> <command><![CDATA[ cat $query_file && #if $add_to_database.withdb: #if $save_db: cp "$add_to_database.withdb" "$sqlitedb" && #else: cp "$add_to_database.withdb" "$workdb" && #end if #end if python $__tool_directory__/query_tabular.py #if $save_db -s "$sqlitedb" #else -s $workdb #end if -j $table_json #if $sqlquery: -Q "$query_file" $no_header -o $output #end if ]]></command> <configfiles> <configfile name="query_file"> $sqlquery </configfile> <configfile name="table_json"> #import json #set $jtbldef = dict() #set $jtbls = [] #set $jtbldef['tables'] = $jtbls #for $i,$tbl in enumerate($tables): #set $jtbl = dict() #set $jtbl['file_path'] = str($tbl.table) #if $tbl.tbl_opts.table_name: #set $tname = str($tbl.tbl_opts.table_name) #else #set $tname = 't' + str($i + 1) #end if #set $jtbl['table_name'] = $tname ## #if $tbl.tbl_opts.sel_cols: ## #set $jtbl['sel_cols'] = $tbl.tbl_opts.sel_cols el_cols ## #end if #if $tbl.tbl_opts.pkey_autoincr: #set $jtbl['pkey_autoincr'] = str($tbl.tbl_opts.pkey_autoincr) #end if #if $tbl.tbl_opts.col_names: #set $col_names = str($tbl.tbl_opts.col_names) #if $tbl.tbl_opts.load_named_columns: #set $jtbl['load_named_columns'] = True #end if #else #set $col_names = '' #end if #set $jtbl['column_names'] = $col_names #set $idx_unique = [] #set $idx_non = [] #for $idx in $tbl.tbl_opts.indexes: #if $idx.unique: #silent $idx_unique.append(str($idx.index_columns)) #else: #silent $idx_non.append(str($idx.index_columns)) #end if #end for #if len($idx_unique) > 0: #set $jtbl['unique'] = $idx_unique #end if #if len($idx_non) > 0: #set $jtbl['index'] = $idx_non #end if #set $input_filters = [] #for $fi in $tbl.input_opts.linefilters: #if $fi.filter.filter_type == 'skip': #set $skip_lines = None #if str($fi.filter.skip_lines) != '': #set $skip_lines = int($fi.filter.skip_lines) #elif $tbl.table.metadata.comment_lines and $tbl.table.metadata.comment_lines > 0: #set $skip_lines = int($tbl.table.metadata.comment_lines) #end if #if $skip_lines is not None: #set $filter_dict = dict() #set $filter_dict['filter'] = str($fi.filter.filter_type) #set $filter_dict['count'] = $skip_lines #silent $input_filters.append($filter_dict) #end if #elif $fi.filter.filter_type == 'comment': #set $filter_dict = dict() #set $filter_dict['filter'] = 'regex' #set $filter_dict['pattern'] = '^(%s).*$' % '|'.join([chr(int(x)).replace('|','[|]') for x in (str($fi.filter.comment_char)).split(',')]) #set $filter_dict['action'] = 'exclude_match' #silent $input_filters.append($filter_dict) #elif $fi.filter.filter_type == 'regex': #set $filter_dict = dict() #set $filter_dict['filter'] = str($fi.filter.filter_type) #set $filter_dict['pattern'] = str($fi.filter.regex_pattern) #set $filter_dict['action'] = str($fi.filter.regex_action) #silent $input_filters.append($filter_dict) #elif $fi.filter.filter_type == 'select_columns': #set $filter_dict = dict() #set $filter_dict['filter'] = str($fi.filter.filter_type) #set $filter_dict['columns'] = [int(str($ci).replace('c','')) for $ci in str($fi.filter.columns).split(',')] #silent $input_filters.append($filter_dict) #elif $fi.filter.filter_type == 'replace': #set $filter_dict = dict() #set $filter_dict['filter'] = str($fi.filter.filter_type) #set $filter_dict['column'] = int(str($fi.filter.column).replace('c','')) #set $filter_dict['pattern'] = str($fi.filter.regex_pattern) #set $filter_dict['replace'] = str($fi.filter.regex_replace) #silent $input_filters.append($filter_dict) #elif str($fi.filter.filter_type).endswith('pend_line_num'): #set $filter_dict = dict() #set $filter_dict['filter'] = str($fi.filter.filter_type) #silent $input_filters.append($filter_dict) #elif str($fi.filter.filter_type).endswith('pend_text'): #set $filter_dict = dict() #set $filter_dict['filter'] = str($fi.filter.filter_type) #set $filter_dict['column_text'] = str($fi.filter.column_text) #silent $input_filters.append($filter_dict) #elif $fi.filter.filter_type == 'normalize': #set $filter_dict = dict() #set $filter_dict['filter'] = str($fi.filter.filter_type) #set $filter_dict['columns'] = [int(str($ci).replace('c','')) for $ci in str($fi.filter.columns).split(',')] #set $filter_dict['separator'] = str($fi.filter.separator) #silent $input_filters.append($filter_dict) #end if #end for #if $input_filters: #set $jtbl['filters'] = $input_filters #end if #set $jtbls += [$jtbl] #end for #echo $json.dumps($jtbldef) </configfile> </configfiles> <inputs> <param name="workdb" type="hidden" value="workdb.sqlite" label=""/> <section name="add_to_database" expanded="false" title="Add tables to an existing database"> <param name="withdb" type="data" format="sqlite" optional="true" label="Add tables to this Database" help="Make sure your added table names are not already in this database"/> </section> <repeat name="tables" title="Database Table" min="0"> <param name="table" type="data" format="tabular" label="Tabular Dataset for Table"/> <section name="input_opts" expanded="false" title="Filter Dataset Input"> <repeat name="linefilters" title="Filter Tabular Input Lines"> <conditional name="filter"> <param name="filter_type" type="select" label="Filter By"> <option value="skip">skip leading lines</option> <option value="comment">comment char</option> <option value="regex">by regex expression matching</option> <option value="select_columns">select columns</option> <option value="replace">regex replace value in column</option> <option value="prepend_line_num">prepend a line number column</option> <option value="append_line_num">append a line number column</option> <option value="prepend_text">prepend a column with the given text</option> <option value="append_text">append a column with the given text</option> <option value="normalize">normalize list columns, replicates row for each item in list</option> </param> <when value="skip"> <param name="skip_lines" type="integer" value="" min="0" optional="true" label="Skip lines" help="Leave blank to use the comment lines metadata for this dataset" /> </when> <when value="comment"> <param name="comment_char" type="select" display="checkboxes" multiple="True" label="Ignore lines beginning with these characters" help="lines beginning with these are skipped"> <option value="62">></option> <option value="64">@</option> <option value="43">+</option> <option value="60"><</option> <option value="42">*</option> <option value="45">-</option> <option value="61">=</option> <option value="124">|</option> <option value="63">?</option> <option value="36">$</option> <option value="46">.</option> <option value="58">:</option> <option value="38">&</option> <option value="37">%</option> <option value="94">^</option> <option value="35">#</option> <option value="33">!</option> </param> </when> <when value="prepend_line_num"/> <when value="append_line_num"/> <when value="prepend_text"> <param name="column_text" type="text" value="" label="text for column"> </param> </when> <when value="append_text"> <param name="column_text" type="text" value="" label="text for column"> </param> </when> <when value="regex"> <param name="regex_pattern" type="text" value="" label="regex pattern"> <sanitizer sanitize="False"/> </param> <param name="regex_action" type="select" label="action for regex match"> <option value="exclude_match">exclude line on pattern match</option> <option value="include_match">include line on pattern match</option> <option value="exclude_find">exclude line if pattern found</option> <option value="include_find">include line if pattern found</option> </param> </when> <when value="select_columns"> <param name="columns" type="text" value="" label="enter column numbers to keep" help="example: 1,4,2 or c1,c4,c2(selects the first,fourth, and second columns)"> <validator type="regex" message="Column ordinal positions separated by commas">^(c?[1-9]\d*)(,c?[1-9]\d*)*$</validator> </param> </when> <when value="replace"> <param name="column" type="text" value="" label="enter column number to replace" help="example: 1 or c1 (selects the first column)"> <validator type="regex" message="Column ordinal position separated by commas">^(c?[1-9]\d*)$</validator> </param> <param name="regex_pattern" type="text" value="" label="regex pattern"> <sanitizer sanitize="False"/> </param> <param name="regex_replace" type="text" value="" label="replacement expression"> <sanitizer sanitize="False"/> </param> </when> <when value="normalize"> <param name="columns" type="text" value="" label="enter column numbers to normalize"> <help><![CDATA[ example: 2,4 or c2,c4 (selects the second, and fourth columns) If multiple columns are selected, they should have the same length and separator on each line ]]></help> <validator type="regex" message="Column ordinal positions separated by commas">^(c?[1-9]\d*)(,c?[1-9]\d*)*$</validator> </param> <param name="separator" type="text" value="," label="List item delimiter in column"> <sanitizer sanitize="False"/> <validator type="regex" message="Anything but TAB or Newline">^[^\t\n\r\f\v]+$</validator> </param> </when> </conditional> </repeat> </section> <section name="tbl_opts" expanded="false" title="Table Options"> <param name="table_name" type="text" value="" optional="true" label="Specify Name for Table"> <help>By default, tables will be named: t1,t2,...,tn (table names must be unique)</help> <validator type="regex" message="Table name should start with a letter and may contain additional letters, digits, and underscores">^[A-Za-z]\w*$</validator> </param> <param name="col_names" type="text" value="" optional="true" label="Specify Column Names (comma-separated list)"> <help>By default, table columns will be named: c1,c2,c3,...,cn (column names for a table must be unique) You can override the default names by entering a comma -separated list of names, e.g. ',name1,,,name2' would rename the second and fifth columns. </help> <sanitizer sanitize="False"/> <validator type="regex" message="A List of names separated by commas: Column names should start with a letter and may contain additional letters, digits, and underscores. Otherwise, the name must be eclosed in: double quotes, back quotes, or square brackets.">^([A-Za-z]\w*|"\S+[^,"]*"|`\S+[^,`]*`|[[]\S+[^,"]*[]])?(,([A-Za-z]\w*|"\S+.*"|`\S+[^,`]*`|[[]\S+[^,"]*[]])?)*$</validator> </param> <param name="load_named_columns" type="boolean" truevalue="load_named_columns" falsevalue="" checked="false" label="Only load the columns you have named into database"/> <param name="pkey_autoincr" type="text" value="" optional="true" label="Add an auto increment primary key column with this name" help="Only creates this additional column when a name is entered. (This can not be the same name as any of the other columns in this table.)"> <validator type="regex" message="Column name">^([A-Za-z]\w*)?$</validator> </param> <repeat name="indexes" title="Table Index"> <param name="unique" type="boolean" truevalue="yes" falsevalue="no" checked="False" label="This is a unique index"/> <param name="index_columns" type="text" value="" label="Index on Columns"> <help>Create an index on the column names: e,g, c1 or c2,c4</help> <validator type="regex" message="Column name, separated by commes if more than one">^([A-Za-z]\w*|"\S+[^,"]*"|`\S+[^,`]*`|[[]\S+[^,"]*[]])(,([A-Za-z]\w*|"\S+.*"|`\S+[^,`]*`|[[]\S+[^,"]*[]])?)*$</validator> </param> </repeat> </section> </repeat> <param name="save_db" type="boolean" truevalue="yes" falsevalue="no" checked="false" label="Save the sqlite database in your history"/> <param name="sqlquery" type="text" area="true" size="20x80" value="" optional="true" label="SQL Query to generate tabular output"> <help>By default: tables are named: t1,t2,...,tn and columns in each table: c1,c2,...,cn</help> <sanitizer sanitize="False"/> <validator type="regex" message="">^(?ims)\s*select\s+.*\s+from\s+.*$</validator> </param> <param name="no_header" type="boolean" truevalue="-n" falsevalue="" checked="False" label="Omit column headers from tabular output"/> </inputs> <outputs> <data format="sqlite" name="sqlitedb" label="sqlite db of ${on_string}"> <filter>save_db or not (sqlquery and len(sqlquery) > 0)</filter> </data> <data format="tabular" name="output" label="query results on ${on_string}"> <filter>sqlquery and len(sqlquery) > 0</filter> </data> </outputs> <tests> <test> <repeat name="tables"> <param name="table" ftype="tabular" value="customers.tsv"/> <param name="table_name" value="customers"/> <param name="col_names" value="CustomerID,FirstName,LastName,Email,DOB,Phone"/> </repeat> <repeat name="tables"> <param name="table" ftype="tabular" value="sales.tsv"/> <param name="table_name" value="sales"/> <param name="col_names" value="CustomerID,Date,SaleAmount"/> </repeat> <param name="sqlquery" value="SELECT FirstName,LastName,sum(SaleAmount) as "TotalSales" FROM customers join sales on customers.CustomerID = sales.CustomerID GROUP BY customers.CustomerID ORDER BY TotalSales DESC"/> <output name="output" file="sales_results.tsv"/> </test> <test> <repeat name="tables"> <param name="table" ftype="tabular" value="customers.tsv"/> <param name="col_names" value=",FirstName,LastName,,DOB,"/> </repeat> <repeat name="tables"> <param name="table" ftype="tabular" value="sales.tsv"/> </repeat> <param name="sqlquery" value="SELECT FirstName,LastName,sum(t2.c3) as "TotalSales" FROM t1 join t2 on t1.c1 = t2.c1 GROUP BY t1.c1 ORDER BY TotalSales DESC;"/> <output name="output" file="sales_results.tsv"/> </test> <test> <repeat name="tables"> <param name="table" ftype="tabular" value="customers.tsv"/> <param name="col_names" value=",FirstName,LastName,,BirthDate,"/> </repeat> <param name="sqlquery" value="select FirstName,LastName,re_sub('^\d{2}(\d{2})-(\d\d)-(\d\d)','\3/\2/\1',BirthDate) as "DOB" from t1 WHERE re_search('[hp]er',c4)"/> <output name="output" file="regex_results.tsv"/> </test> <test> <repeat name="tables"> <param name="table" ftype="tabular" value="IEDB.tsv"/> <param name="table_name" value="iedb"/> <param name="col_names" value="ID,allele,seq_num,start,end,length,peptide,method,percentile_rank,ann_ic50,ann_rank,smm_ic50,smm_rank,comblib_sidney2008_score,comblib_sidney2008_rank,netmhcpan_ic50,netmhcpan_rank"/> </repeat> <repeat name="tables"> <param name="table" ftype="tabular" value="netMHC_summary.tsv"/> <param name="table_name" value="mhc_summary"/> <param name="col_names" value="pos,peptide,logscore,affinity,Bind_Level,Protein,Allele"/> </repeat> <param name="sqlquery" value="select iedb.ID,iedb.peptide,iedb.start,iedb.end,iedb.percentile_rank,mhc_summary.logscore,mhc_summary.affinity,mhc_summary.Bind_Level from iedb left outer join mhc_summary on iedb.peptide = mhc_summary.peptide order by affinity,Bind_Level"/> <output name="output" file="query_results.tsv"/> </test> <test> <repeat name="tables"> <param name="table" ftype="tabular" value="pets.tsv"/> <repeat name="linefilters"> <param name="filter_type" value="comment"/> <param name="comment_char" value="35"/> </repeat> <repeat name="linefilters"> <param name="filter_type" value="append_line_num"/> </repeat> <repeat name="linefilters"> <param name="filter_type" value="select_columns"/> <param name="columns" value="7,2,3,4,1"/> </repeat> <repeat name="linefilters"> <param name="filter_type" value="replace"/> <param name="column" value="c4"/> <param name="regex_pattern" value="(\d+)/(\d+)/(\d+)"/> <param name="regex_replace" value="19\3-\2-\1"/> </repeat> <param name="table_name" value="people"/> <param name="col_names" value="id,first,last,dob,pets"/> </repeat> <repeat name="tables"> <param name="table" ftype="tabular" value="pets.tsv"/> <repeat name="linefilters"> <param name="filter_type" value="comment"/> <param name="comment_char" value="35"/> </repeat> <repeat name="linefilters"> <param name="filter_type" value="append_line_num"/> </repeat> <repeat name="linefilters"> <param name="filter_type" value="select_columns"/> <param name="columns" value="c7,c5,c6"/> </repeat> <repeat name="linefilters"> <param name="filter_type" value="normalize"/> <param name="columns" value="c2,c3"/> <param name="separator" value=","/> </repeat> <param name="table_name" value="pet"/> <param name="col_names" value="id,name,animal"/> </repeat> <param name="sqlquery" value="SELECT people.id,first,last,dob,name,animal,pets FROM people JOIN pet ON people.id = pet.id WHERE animal = 'cat'"/> <output name="output" file="pet_normalized_query_results.tsv"/> </test> </tests> <help><![CDATA[ ============= Query Tabular ============= **Inputs** Loads tabular datasets into a SQLite_ data base. An existing SQLite_ data base can be used as input, and any selected tabular datasets will be added as new tables in that data base. **Input Line Filters** As a tabular file is being read, line filters may be applied. :: - skip leading lines skip the first *number* of lines - comment char omit any lines that start with the specified comment character - by regex expression matching *include/exclude* lines the match the regex expression - select columns choose to include only selected columns in the order specified - regex replace value in column replace a field in a column using a regex substitution (good for date reformatting) - prepend a line number column each line has the ordinal value of the line read by this filter as the first column - append a line number column each line has the ordinal value of the line read by this filter as the last column - normalize list columns replicates the line for each item in the specified list *columns* **Outputs** The results of a SQL query are output to the history as a tabular file. The SQLite_ data base can also be saved and output as a dataset in the history. *(The* **SQLite to tabular** *tool can run additional queries on this database.)* For help in using SQLite_ see: http://www.sqlite.org/docs.html **NOTE:** input for SQLite dates input field must be in the format: *YYYY-MM-DD* for example: 2015-09-30 See: http://www.sqlite.org/lang_datefunc.html **Example** Given 2 tabular datasets: *customers* and *sales* Dataset *customers* Table name: "customers" Column names: "CustomerID,FirstName,LastName,Email,DOB,Phone" =========== ========== ========== ===================== ========== ============ #CustomerID FirstName LastName Email DOB Phone =========== ========== ========== ===================== ========== ============ 1 John Smith John.Smith@yahoo.com 1968-02-04 626 222-2222 2 Steven Goldfish goldfish@fishhere.net 1974-04-04 323 455-4545 3 Paula Brown pb@herowndomain.org 1978-05-24 416 323-3232 4 James Smith jim@supergig.co.uk 1980-10-20 416 323-8888 =========== ========== ========== ===================== ========== ============ Dataset *sales* Table name: "sales" Column names: "CustomerID,Date,SaleAmount" ============= ============ ============ #CustomerID Date SaleAmount ============= ============ ============ 2 2004-05-06 100.22 1 2004-05-07 99.95 3 2004-05-07 122.95 3 2004-05-13 100.00 4 2004-05-22 555.55 ============= ============ ============ The query :: SELECT FirstName,LastName,sum(SaleAmount) as "TotalSales" FROM customers join sales on customers.CustomerID = sales.CustomerID GROUP BY customers.CustomerID ORDER BY TotalSales DESC; Produces this tabular output: ========== ======== ========== #FirstName LastName TotalSales ========== ======== ========== James Smith 555.55 Paula Brown 222.95 Steven Goldfish 100.22 John Smith 99.95 ========== ======== ========== If the optional Table name and Column names inputs are not used, the query would be: :: SELECT t1.c2 as "FirstName", t1.c3 as "LastName", sum(t2.c3) as "TotalSales" FROM t1 join t2 on t1.c1 = t2.c1 GROUP BY t1.c1 ORDER BY TotalSales DESC; You can selectively name columns, e.g. on the customers input you could just name columns 2,3, and 5: Column names: ,FirstName,LastName,,BirthDate Results in the following data base table =========== ========== ========== ===================== ========== ============ #c1 FirstName LastName c4 BirthDate c6 =========== ========== ========== ===================== ========== ============ 1 John Smith John.Smith@yahoo.com 1968-02-04 626 222-2222 2 Steven Goldfish goldfish@fishhere.net 1974-04-04 323 455-4545 3 Paula Brown pb@herowndomain.org 1978-05-24 416 323-3232 4 James Smith jim@supergig.co.uk 1980-10-20 416 323-8888 =========== ========== ========== ===================== ========== ============ Regular_expression_ functions are included for: :: matching: re_match('pattern',column) SELECT t1.FirstName, t1.LastName FROM t1 WHERE re_match('^.*\.(net|org)$',c4) Results: =========== ========== #FirstName LastName =========== ========== Steven Goldfish Paula Brown =========== ========== :: searching: re_search('pattern',column) substituting: re_sub('pattern','replacement,column) SELECT t1.FirstName, t1.LastName, re_sub('^\d{2}(\d{2})-(\d\d)-(\d\d)','\3/\2/\1',BirthDate) as "DOB" FROM t1 WHERE re_search('[hp]er',c4) Results: =========== ========== ========== #FirstName LastName DOB =========== ========== ========== Steven Goldfish 04/04/74 Paula Brown 24/05/78 James Smith 20/10/80 =========== ========== ========== **Line Filtering Example** *(Six filters are applied as the following file is read)* :: Input Tabular File: #People with pets Pets FirstName LastName DOB PetNames PetType 2 Paula Brown 24/05/78 Rex,Fluff dog,cat 1 Steven Jones 04/04/74 Allie cat 0 Jane Doe 24/05/78 1 James Smith 20/10/80 Spot Filter 1 - append a line number column: #People with pets 1 Pets FirstName LastName DOB PetNames PetType 2 2 Paula Brown 24/05/78 Rex,Fluff dog,cat 3 1 Steven Jones 04/04/74 Allie cat 4 0 Jane Doe 24/05/78 5 1 James Smith 20/10/80 Spot 6 Filter 2 - by regex expression matching [include]: '^\d+' (include lines that start with a number) 2 Paula Brown 24/05/78 Rex,Fluff dog,cat 3 1 Steven Jones 04/04/74 Allie cat 4 0 Jane Doe 24/05/78 5 1 James Smith 20/10/80 Spot 6 Filter 3 - append a line number column: 2 Paula Brown 24/05/78 Rex,Fluff dog,cat 3 1 1 Steven Jones 04/04/74 Allie cat 4 2 0 Jane Doe 24/05/78 5 3 1 James Smith 20/10/80 Spot 6 4 Filter 4 - regex replace value in column[4]: '(\d+)/(\d+)/(\d+)' '19\3-\2-\1' (convert dates to sqlite format) 2 Paula Brown 1978-05-24 Rex,Fluff dog,cat 3 1 1 Steven Jones 1974-04-04 Allie cat 4 2 0 Jane Doe 1978-05-24 5 3 1 James Smith 1980-10-20 Spot 6 4 Filter 5 - normalize list columns[5,6]: 2 Paula Brown 1978-05-24 Rex dog 3 1 2 Paula Brown 1978-05-24 Fluff cat 3 1 1 Steven Jones 1974-04-04 Allie cat 4 2 0 Jane Doe 1978-05-24 5 3 1 James Smith 1980-10-20 Spot 6 4 Filter 6 - append a line number column: 2 Paula Brown 1978-05-24 Rex dog 3 1 1 2 Paula Brown 1978-05-24 Fluff cat 3 1 2 1 Steven Jones 1974-04-04 Allie cat 4 2 3 0 Jane Doe 1978-05-24 5 3 4 1 James Smith 1980-10-20 Spot 6 4 5 Table name: pets Table columns: Pets,FirstName,LastName,Birthdate,PetNames,PetType,line_num,entry_num,row_num Query: SELECT * FROM pets Result: ====== ========== ======== ========== ========= ======== ========= ========== ======== #Pets FirstName LastName BirthDate PetNames PetType line_num entry_num row_num ====== ========== ======== ========== ========= ======== ========= ========== ======== 2 Paula Brown 1978-05-24 Rex dog 3 1 1 2 Paula Brown 1978-05-24 Fluff cat 3 1 2 1 Steven Jones 1974-04-04 Allie cat 4 2 3 0 Jane Doe 1978-05-24 5 3 4 1 James Smith 1980-10-20 Spot 6 4 5 ====== ========== ======== ========== ========= ======== ========= ========== ======== **Normalizing by Line Filtering into 2 Tables** *People Table* :: Filter 1 - by regex expression matching [include]: '^\d+' (include lines that start with a number) Filter 2 - append a line number column: Filter 3 - regex replace value in column[4]: '(\d+)/(\d+)/(\d+)' '19\3-\2-\1' (convert dates to sqlite format) Filter 4 - select columns 7,2,3,4,1 Table: People Columns: id,FirstName,LastName,DOB,Pets == ========= ======== ========== ==== id FirstName LastName DOB Pets == ========= ======== ========== ==== 1 Paula Brown 1978-05-24 2 2 Steven Jones 1974-04-04 1 3 Jane Doe 1978-05-24 0 4 James Smith 1980-10-20 1 == ========= ======== ========== ==== *Pet Table* :: Filter 1 - by regex expression matching [include]: '^\d+' (include lines that start with a number) Filter 2 - append a line number column: Filter 3 - by regex expression matching [exclude]: '^0\t' (exclude lines with no pets) Filter 4 - normalize list columns[5,6]: Filter 5 - select columns 7,5,6 Table: Pet Columns: id,PetName,PetType == ======== ======== id PetName PetType == ======== ======== 1 Rex dog 1 Fluff cat 2 Allie cat 4 Spot == ======== ======== Query: SELECT FirstName,LastName,PetName FROM People join Pet on People.id = Pet.id WHERE PetType = 'cat'; Result: ========= ======== ======== FirstName LastName PetName ========= ======== ======== Paula Brown Fluff Steven Jones Allie ========= ======== ======== .. _Regular_expression: https://docs.python.org/release/2.7/library/re.html .. _SQLite: http://www.sqlite.org/index.html ]]></help> </tool>