Why add another scripting language to xLite, hasn’t it already got Python?

True, Python is and remains a very powerful add-on to xLite. It’s a mature and long-established language, popular amongst IT professionals and “citizen programmers” alike. But, it’s a bit of a monster and can be awkward to package, particularly on Windows. By using Py2Exe and after a lot of digging on the issue of manifest files I have managed to package and isolate xLite’s Pythonic bits so that it can be used on a PC without first installing the required Python version (I’ve only tested against V2.6, Python’s lack of a side-by-side Windows installation capability is a major pain-in-the-butt   bad news: tested against Python 2.5 & it doesn’t work; good news: side-by-side is possible; simply change the system path to reflect which-ever version you wish to run at the command line; xLite will (must) continue to use V2.6). This “version-hell” mitigates against using Python as a core-element of xLite, fine for those of us who are comfortable with and require the full power of Python, but not as the tool’s primary scripting environment.

No, what I need is:

• a light (single EXE or DLL preferably) and an approachable popular language,
• with native SQLite support,
• runable as standalone executable (on both Windows & Linux),
• embeddable (is that a word?) in Excel via VBA-friendly DLL.

Add to that essential list some nice-to-haves such as:

• native COM-interface support (for the likes of ADO etc.),
• native networking support, for HTTP, raw TCP sockets etc.,
• native (and easy to use) XML and JSON parsers and emitters,
• ability to spawn detached/attached command line processes and the ability to stream data to and from such processes; allowing me to easily orchestrate & provide a “grid” of processes (scripted, command line executables, Excel instances) both local and remote (with remote being either traditional servers, http servers or Hadoop Streaming grids).

While looking at the various implementations of Javascipt as a server/shell language, I came across JSDB – JavaScript for Databases. It’s a C++ wrapper around Mozilla’s SpiderMonkey, with lots of useful data related utility classes added. To make JSDB a perfect fit it simply required:

• a few minor changes to the SQlite class (allow the loading of Virtual Table extensions, add the ability to pass in the address of already open SQLite memory structures);
• a linker change to use the DLL version of SQLite;
• plus a VBA-friendly DLL wrapper ( & VBA declares, to call the DLL) to replace the JSDB shell when embedding in Excel.

From my SQLite as the MP3 of Data post:  ”Just as “fractional horsepower” electrical motors revolutionised manufacturing and eventually all our lives (car starter-motors, fridge motors, washing machines etc.), “fractional horsepower” databases can do the same for data. Distributing data to where it is needed.” I can now add a distributed “fractional horsepower” processing engine for that distributed data. This transforms xLite from a micro-ETL platform into one capable of handling (or at least orchestrating) practically any ETL (Extract, Transform & Load),DI (data integration) or “Time Asset” (see this post) process.

Bugs (the programming type, not the creepy-crawlies), Simple API for XML and Extended Business Reporting Language;  these represented the trinity of my concerns for the last three weeks  or so.

First, the bugs:

Several weeks back, I decided that the C portion of xLite needed an overhaul. The codebase contained a lot of stuff that I no longer used and also contained code that I’d written when I first re-started using C (after a lapse of 20 years or so, the phrase “I’d forgotten more than I’d ever known” sums up the experience best); some of this code was memory-leaking like a sieve.

Also, the original Pivotal Solutions code was not UTF-8 enabled, instead it used the host pc’s default character set codepage, this needed to change (if you don’t know what I’m talking about see Joel Spolsky’s lecture to the developers of the world – well actually, primarily to those of us in the Anglo-Saxon “ascii-will-do-fine” world).

The bugs I introduced as a result of this upgrade were not of the logical kind but of a much nastier type, peculiar to the low-level world of C, “bad free()” bugs!

Excel was no longer leaking memory (well no more than it normally does) but it was crashing randomly (usually in a DDL called VB7, 1st upgrade to classic VB in over a decade!), a sure sign I was freeing memory that was not mine to free. Two days later, I’d tracked the bugs down, but only by a painful line by line code walk-through. If you’ve no idea what I’m talking about here, count your blessings and move on.

The other major change I added to xLite is the ability to code SQLite Virtual Tables in VBA. The Python side of xLite has always had that facility, but I look on Python as a nice-to-have add-on, not as a core component. The growing need for “core” virtual tables meant either coding them in C or in VBA, see previous paragraphs for why VBA won the day.

The immediate driver for adding both UTF-8 support and quick-to-build virtual tables was the need to better handle XML data within xLite.

… then the SAX:

For small XML/HTML datasets, I, like the rest of the world, use DOM manipulation; but for larger sets I’ve tended to go down the brute force and ignorance approach of hand coded File I/O combined with regular expressions to efficiently parse out the data required.

Last week, an email from a datasmith name Cathy prompted me to look into using Sax for loading XML. Cathy, like most datasmiths, is not a professional programmer, she has a “real job”; part of that job is analysing large datasets, she’s learned enough programming (mainly Access & Excel) to do that job more efficiently. The data she needed to parse this time was encoded in XML, but being very large and built on a schema that constantly changed, the default DOM approach overpowered both Access and Excel.

Cathy had originally contacted me looking for information on using Talend to read the data and it looked like she was about to start a new side-career as a Java programmer. I figured there must be a way for her to leverage her existing skill-set (VBA) & this led me to MSXML’s implementation of SAX2. She was delighted; although many of the concepts would have been new to her, at least they were bounded within a world she was already comfortable with (the basis of how we all manage to incrementally expand our knowledge).

The only problem was, the example code no longer existed (it would have been in VB6, but who uses that these days, other than a few million VBA para-programmers, let them eat the .NET cake). So I coded up the first example in Excel/VBA and here it is if you need a quick-start to the joys of SAX2.

Which leads me on to XBRuLe:

“One XML to rule them all, One XML to find them, One XML to bring them all and in the darkness bind them…”

A former colleague of mine when explaining his computer science studies to Meath farmers whom he regularly met while hitch-hiking home from college (mid-1970s) was usually met with the response: “Ah computers, dere de comin‘ t’ing“. XBRL has been the coming thing for quite a while now.

Being in the business of Business Reporting, XBRL has always been on the radar, and of late, the radar is showing incoming fire. First the SEC, and now the UK’s HMRC, are mandating it as a filing method. Whether this is a good thing or not, is open to question. As this article puts it: “XBRL is a  case study in complexity” http://bit.ly/951oEY “the producer of the sample must have suffered a polymorphic recursive brain meltdown”.

But needs be; I’m in the business of shaping difficult data, so I’ve started to re-acquaint myself with the subject (last time I looked at XBRL in any depth was 2004). Part of that process will be to beef-up xLite’s XML capability, which, with me being on the table side of the “Tables Vs. XML; the data lingua franca debate“, will involve getting the data into a relational form at the earliest possible moment. For example, for discovery I would use a classic parent-child recursive structure, but not having something like Oracle’s Start-with, adding  a virtual table to make navigating such hierarchies easier with SQLite.

If anybody is peddling to you the concept that this brave new word of XBRL powered reporting will make your business reporting life easier, they’re either lying or don’t fully understand what they’re selling. As 19th century industrialists were wont to say: “Where there’s muck, there’s brass”; and with XBRL, you’ll be up to your oxters in muck, but with the brass all flowing to others, perhaps even to me!

Now it may seem strange that somebody whose SQL – does exactly what it says on the tin post clearly marks him out as an RDBMS fanboy, can also sing the praises of a noSQL database. Are they not mutually exclusive? To many, particularly in the noSQL world, this appears to be the case, with some clearly determined to re-invent the wheel, ignoring the lessons learned by relational database practitioners.

The main advantage to me of document-oriented databases, such as CouchDB, is the ease of setup and subsequent pain-free evolution of data models that comes with a schema-less database. The main disadvantage is the relative rigidity of downstream analysis built into most such databases. MapReduce, such as used by CouchDB, is fine for predefined views developed by programmers, but as we know, reporting never stops; datastores front-ended by a SQL interpreter open up the data within to a much wider audience (be that through hand-crafted SQL queries or more likley via reporting-tool generated SQL)

Of course document-oriented, noSQL, schema-less datastores have been all the rage with end-users for close on 30 years. They’re called spreadsheets. Excel has over the years added features (such as list handing & filtering) that have made the spreadsheet the database of choice for millions. Anybody who deals in corporate data is aware (sometimes painfully aware) of just how much data is stored in these Data Populi repositories.

I, as an IT professional, am aware that Excel workbooks as books-of-record, have been, and continue to be, the cause of many data quality problems. Yet, I’ve also seen, and am myself responsible for, many successful Excel ‘database implementations’. Take for example, my filing system.

I don’t have a filing cabinet, instead I use small stackable cardboard boxes to store documents. As I receive or generate documents I simply place them in the current open box. Every so often, usually prompted by a VAT or other tax return deadline looming, I record what’s in the box, and if the box is looking full or maybe it’s end-of-year, I’ll ‘close’ the box and open a new one.

Each box is represented by a separate workbook, each document by a separate worksheet. Some documents such as electronic Sales Invoices may not require a physical copy simply a link to a PDF, but I still tend to store a printed copy. Others, such as Purchase Invoices, have their details manually copied from the original paper based document, I usually also add a hyperlink to an image of the source document. (I no longer use my scanner, instead I use my phone camera to record paper documents).

Bank reconciliation involves recording the bank item ref against the appropriate document and linking back to the Bank Statement worksheet  (which as I still receive paper-statements consists simply of a link to a photo of the statement and basic info such as date of statement and whether or not I’ve reconciled it).

VAT Return documents are generated using links back to source documents and a link to an image of the completed paper return (not yet signed up for ROS). Similar documents are generated for year-end tax returns & accounts.

So my ‘filing system’ is also my ‘accounts system’. This is common practice amongst small (and not so small) businesses. The advantage of this approach rather than using a “proper accounts system”  is the simplicity and the in-depth knowledge it forces me to have of ‘my data’.

But can this type of thing scale, and what of the businesses that are using similar systems to manage thousands or indeed 10s of thousands of documents or transactions? The simple answer is no,  at least not without a semi-automated process and a cost-effective means of analysing the data; many such systems are on the road to disaster. That disaster may take the form of data quality issues or the significant (and often hidden) cost of operating such systems (often the operators are highly paid accounting staff or managers whose cost is buried in general overhead costs, unlike internal or external IT resources whose time tends to be project allocated).

But again, I and others, have managed to setup systems such as these that were  cost-effective (not just in initial construction but in ongoing running costs) and managed to maintain data quality. This usually involved building a simple work-flow process, automating to some degree but keeping the human touch as much as possible. My xLite datasmithing platform had its beginnings in such RSS (Really Simple Systems) scenarios. Many such “systems” were IT driven ETL processes or data cleansing initiatives, others, business initiatives such as sales planning/budgeting or customer surveys.

I haven’t used xLite to automate my filing system (my transactional volumes are too low and my motto when it comes to systems is, “good enough” will do), instead, relying on standard spreadsheet formulas and few bits of VBA, but if I suddenly found myself at the business end of a fire-hose of documents I could easily do so.

Much like CouchDB, I could  create ‘map’ views of my documents, but instead of MapReduce Javascript code, I’d  load the documents into SQLite tables (using a duck typing approach; if the document had the required data, e,g, Invoice No, etc. for Sales Invoices, load, otherwise ignore). The ‘reduce’ part would then be standard SUM(), Group By SQL statements.

I could also mine the documents for text and then use SQLite’s FTS full-text searching to create a free-format search index or use xLite’s TAG Cube functionality for a more formal, hierarchy supporting, tagging index.

If I needed to share the system with others in my organisation I could use a light simple distributed version control system such the SQLite based  Fossil. This would allow for many of the replication benefits that CouchDB offers.

In fact, if I wanted to backend the system with a server based database I could call in the services of CouchDB itself. Easily done as xLite has inbuilt Python support and the library that xLite uses to interact with SQLite on the Python side is APSW. And guess what, APSW now includes a virtual table implementation that lets you access CouchDB databases from SQLite. Excel as a front-end to CouchDB!

If the ‘it does exactly what it says on the tin‘  Ronseal catch-phrase epitomises SQL  then perhaps ‘ Simples‘ as Alexandr the Meerkat might say epitomises the potential of document-based databases.

Why not join me on Twitter at gobansaor?

I’d not bothered with Excel 2007, as I couldn’t see the advantage over Excel 2003, but Excel’s new PowerPivot is one hell of a reason to upgrade to 2010. I’d preformed a quick test against 2007 by installing a trial version on an EC2 Window’s image and it had appeared to work fine; but it was a different story under 2010,strange things started to happen.

The core functionality, as tested by VBA code, worked OK but when I tested using xLite.SQL as a UDF (a user defined “formula”) things fell apart. For an explanation of what the xLite.SQL function is and why I wasn’t that surprised when it started to act up, see here. As xLite.SQL plays to the rules rather than the spirit of a UDF, I assumed it was pay back time  for my blasé ignoring of functional programming constraints and I set about tracking down the cause.

It turns out the cause is a change in behaviour (a bug) whereby in certain circumstances the cell range returned by Application.Caller is not, as one would expect, the cell hosting the called UDF but that cell more usually associated with Application.ActiveCell (i.e. most likely the cell where the cursor currently resides).

Why is this a problem and what is Application.Caller usually used for? The most common use I’ve made of Application.Caller is to determine whether a VBA function had been called from a cell as a UDF or from a menu, button or some VBA code. This is important because when called in UDF mode, a function must be side-effect free, i.e. its only affect on the workbook is the return value; attempting anything else will silently fail (or in extreme cases, abort Excel). This functionality is not affected by “the bug” as the usual method of achieving this is by …

If IsObject(Application.Caller) Then

… this will work even if Application.Caller returns .ActiveCell, as both are objects.

If however, various properties of that range need to be interrogated (such as the actual address or the formula text that xLite.SQL requires) then Application.Caller in certain circumstances returning the .ActiceCell range rather than the calling cell’s range causes problems. I’ve managed to get around these problems by adding an extra parameter (homeCell) to xLite.SQL which the function will auto populate on first entry (when Application.Caller and .ActiveCell are guaranteed to be the same object). For example, a SQL call entered in cell A2 of Sheet1 as ..

=SQL(“Select name from sqlite_master”)

is automatically rewritten as …

=SQL(“Select name from sqlite_master”,,,,,,”[test.xls]Sheet1!$A$2″)

Not ideal but it gets around the problem in the short term.  Long term I may do a version for sub-2010 reverting back to original dependence on Application.Caller. As xLite studiously avoids Excel’s UI features such as menus/ribbons I’d hope to avoid different versions for pre/post ribbon editions, but needs must.

The xLiteWorkbook example (test_call_workbook_function.xls calling test_workbook_function.xls) consistently generates the bug (there’s a SQL call against the log database at the end to test for this). Executing the same logic manually on the called workbook (test_workbook_function.xls) generally doesn’t, but it has done so occasionally!

I’ve messed around changing the .xls files to .xlsm in case of compatibility problems but it doesn’t appear to affect the outcome.

If anybody else has come across this problem or has an alternative to using Application.Caller to return a UDF’s calling cell’s range, do let me know.

UPDATE:

Peter Hoadley suggests a workaround by using Application.ThisCell, see comments below …

UPDATE: March 19th 2010

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See http://www.gobansaor.com/xlite

The u() function allows any VBA UDF (user defined functions) to be called from SQLite.

The x() function allows an inbuilt function or indeed most any formula (but not a UDF, use u() instead) to be called from SQLite.

The f() function allows for standard worksheet cascading formulas to be referenced by SQL, in effect, worksheet user defined functions.  Really useful in building & testing workbook code/models.

Finally, xLitePyScript is a UDF that allows Python to be used as an Excel scripting language.  Can either be inserted into a SQL statement wrapped by the u() function or called like a regular function from VBA or as a cell formula.

Have fun …

The trick behind TM1, Essbase, Palo etc. is the extension of the spreadsheet metaphor from two to multiple dimensions, while still binding the interface closely to the familiar spreadsheet (which for most of the business world is still Excel).

So where does SQLite come in all this?

At first glance, SQLite lacks the sophisticated join functionality to support star-queries, but of course, if the dataset is small then a full-table scan of a fact table, or better still, loading the fact table into memory negates any such short-comings.

In fact, all traditional ROLAP engines have problems with dimensional models, particularly when you reach the point of using summary tables or query re-writes, that’s why the emerging SQL-speaking columnar-databases are such a godsend for ROLAP data warehouses.

It was SQLite combined with Excel acting as a data prep platform that was originally my main interest, so for pivoting, Excel’s own pivot table would have to do.  Nevertheless, I felt the tool was incomplete without the ability to directly pivot the underlying SQLite database.

Why not use Palo or Mondrian as a pivot tool? Well yes, where a fixed permanent “solution” is required then the extra moving parts of either approach would be justified and indeed necessary but that is to miss the essence of what I call datasmithing.

Datasmithing is not data warehousing nor is it the provision of solutions (which, for example, Palo superbly enables in multi-user budgeting situations). Datasmithing, as a skill, is of course part of the process of both, but it’s on the edges, at perhaps the planning or consumption stages.

Datasmiths deal in the unknown, in change, in disaster recovery, in systems’ commissioning, in the never-ending barely-repeatable processes thrown up by daily business life.  For that, the toolset required must be as simple as possible (but no simpler), self-contained, document-oriented, secureable (is that a word?) and easily archived and retrieved. Excel and file-based DBMSs such as MSAccess or SQLite fit the bill nicely, server-based technologies such as DBA controlled database servers or IT installed “solutions”, less so.

Jedox has made Palo relatively easy to install (and likewise, Canada’s SQLPower has made Mondrian setup a painless exercise via their excellent Wabit reporting tool), but, the zero-install, email friendly document approach that spreadsheets are famous (and infamous) for, is preferable in many situations. This is something that Microsoft have recognised in their Gemini add-in for Excel 2010, but Excel 2010 is a not here yet and it’s likely to be five years or more before it’s as common as Excel 2003 is today.

The inclusion of FTS full-text searching with SQLite triggered an ah-ah moment with regards to pivot-enabling SQLite.

The usual method that hypercube-like excel-friendly OLAP tools use to return data is via a UDF like so…

=DATA(“CubeName”,”value1″,value2″,…)

…where valueN represents dimensional elements, so…

=DATA(“SalesCube”,”Beer”,”Profit”,”Jan 09″,”Actual”)

…is the Actual Profit for Beer sales in Jan 09. The dimensional elements act as “tags” to locate a particular value, there is of course much more to tools like Palo; hierarchies, intra-cube rules etc. but in essence most OLAP tools are like www.delicious.com for number crunchers. This method of retrieving data fits well with how people use Excel and not just for pivots, but for embedding OLAP aggregated cells in lists.  For example, a CRM scenario; a Sales Rep makes a list of her ‘best’ (subjective) customers, but needs hard (objective) stats, to be placed alongside the list to convince the boss or to track actuals against expectation.

Dimensional elements as tags; FTS3 virtual tables as fact table indexes; the concept of a TAG Cube was born.

In the above example “Profit” would most likely be described as a measure (Palo, a near pure hypercube does not distinguish between Measure and other Dimensional coordinates). Dimensions, measures and attributes are in reality interchangeable (a Customer ID can act as a dimension or an attribute, but by applying a  Count Distinct to it, it’s a measure) but most OLAP solutions treat “Measure Dimensions” as different, and so do TAG Cubes.

By using the default fact table structure (a single-columned table) and querying using the default measure (which translates to the SUM() of that single value) a ‘pure’ approach can be used. But, ROLAP is tightly bound to the concept of a fact table, and since SQLite is relational, TAG Cubes offer the ability to use a wide fact table approach and I think gains considerably in flexibility by so going.

The above example of using Count Distinct, or the simple creation of calculated measures are examples of this flexibility. Another, is a measure based on SQLite’s concat_group aggregate function to provide a drill-down facility, e.g.

=DATA(“SalesCUBE”,”ROWIDList,”Beer”,”Jan 09″,”Actual”)

…where “ROWIDList” would be setup as concat_group(rowid,’,') and will return a comma separated list of the underlying fact table ROWIDs.

A major reason for rolling my own pivot engine was to add a concept of “namespaces” and to separate the implementation of these namespaces from the actual pivot.  When a tag (or a predefined hierarchy of tags) is assigned to a cube, it’s also assigned to a namespace, in many cases namespace and cube would be synonymous, but in some cases a more sophisticated approach is required:

• Multiple cubes sharing the same set of conformed dimensions would be best served by such cubes sharing a common namespace, and so they can.
• Different consumers of the pivot may require the use of a different language, be that a spoken language or a different ‘business language’ e.g. Manufacturing Product Codes V Consumer Product Names. Again, easily done.
• Sometimes identifying data can’t be shared with the datasmith or the numerical analyst working on a problem; in such cases being able to replace  the actual namespace with an obfuscated one can be very useful. Or, for added security, the namespace might only be issued to approved  PCs while the tag index and fact table are stored on a shared drive.  Needs some more work to make managing such scenarios secure and easy to use but the structure is there.

As hinted on above, the three elements of a Tag Cube, the namespace, tag index and fact table can be assigned to different databases (i.e. files). Due to the wonders of SQLite’s ATTACH statement and the backup API’s ability to quickly load/unload databases in/out of memory, it’s possible, for example, to load namespace and tag index (i.e. the ‘dimensions’) into a memory database, while a very large (i.e. too big to fit to memory) fact table remains on disk. Fast and cheap SSDs will add further configuration options.

Although most of the TAG Cube functionality is available only within Excel, I’ve built a C based SQLite Virtual Table (cFact) to allow the tag index to used outside xLite. This means that SQLite drivers for ODBC (for use as a Pivot Table source, for example) or JDBC (for use in  SQLPower Wabit perhaps) can efficiently access data models built using xLite.

I had to revert to using C rather than my preferred Python (did I mention that xLite now embeds Python in Excel, no, well it does, Python the newVBA ?), having failed to get around multi-threading issues with callbacks to Python in both the ODBC and JDBC drivers. I’d make a career promise to myself many years ago, not to having anything to do with printers or threads, and I think I’ll stick with it

TAG Cubes are the latest addition (still WIP actually) to be added to xLite, adding to:

• VBA coded SQLite SQL functions.
• Worksheet Functions; call out to a ‘function’ built using Excel formula, passing a parameter list and returning a value.
• Workbook Functions; like Worksheet Functions, but loading a new Workbook, passing in parameters, passing back a value (or tables) and closing the Workbook when finished.
• XLiteScript; xLite exposes its functionality via VBA coded UDFs, which can be called like any other formula, but data prep activities often require sequential procedural logic, xLiteScript is a table-oriented scripting mechanism offering basic flow-control logic.
• pyScript; I embedded Python into xLite to take advantage of Python’s speed in developing Virtual Tables, SQL Functions and extensions to SQLite and to tap in the wonderful world of Python code. I’ve also added the ability to use Python from scripts defined within Excel (to indent, tab to the next cell!).
• Fast load/unload to/from CSV.
• Load from any ADO source.
• Remove xLite formulae and rename and save Workbook, very handy when used via Workbook Functions to mass produce Excel “reports”.
• Other WIP items are; load from SAP, load/unload to/from Amazon S3, use Palo cubes as TAG Cube “facts”, slot in/out Palo for TAG Cubes, auto-generate Mondrian XML based on TAG Cubes, write-back and splash, Python & VBA TAG Cube “rules”.

I’ve started the process of releasing the beta code here …

Why not join me on Twitter at gobansaor?

The new improved xLiteSQLite.dll now has a built-in CSV loader (both file based and string based – handy for loading Palo HTTP API responses into a table). It also returns a one columned variant array of CSV values for quick rendering via “text-to-columns” code (by far the quickest way of handling large dataset pasting into Excel).

I’ve also added the ability to create SQlite UDFs (user defined functions) in VBA (thanks to http://stackoverflow.com/users/4007/rpetrich).  This is a very powerful feature as it allows SQLite selects to act as a “loop controller” calling back to  Excel/VBA functions to process each row, really useful for ETL tasks. And not just scalar UDFs but aggregating (aka group-by) functions too, allowing the use of Excel’s powerful array functions in SQLite statements.

All in all, the changes to the xLite VBA code and the C wrapper makes Excel backed by SQLite a seriously good micro-ETL tool. Combined with Palo, the result in a truly wonderful micro-BI platform; a cost-effective toolset for these recessionary times.

Of course I’d be lying if I said code was the only reason I’ve been neglecting my blogging duties, I’m afraid I’ve a confession to make, Twitter has hooked yet another sucker, me! 

I’ve found I’ve settled in to the whole micro-blogging thing with ease, and have managed to make contact with people I would not have encountered otherwise, as well as reconnecting with others that I’d lost contact with.  So if you too are all-a-twitter then do please follow gobansaor-on-twitter.

So what are my alternatives:

• Do nothing, continue to use VS6 (I’ve already made an “off-site” copy in case the house burns down!).
• Use .NET, ExcelDNA is an easy way to integrate Excel with .NET, but it doesn’t handle the creation of COM servers. In general, accessing COM from .NET is a total PITA.
• Use Python.

I’m going down the Python route, especially now that I’ve figured out how to create in-process (DLL) COM servers (via pyInstaller) and how to manage sub-processes (via import subprocess). Not just because it’s future-proof, but because:

• It’s easy to build against and to manipulate COM interfaces, nearly as easy as VB6, much, much easier than the .NET alternatives.
• I can then use the same platform to handle general datasmithing (on Windows, MacOS and Linux), and do Excel integration “stuff” and also web front-ends (via Google Apps Engine).
• I really like Python and I find I’m much more productive with it than with any other language I have ever used (with the possible exception of MUMPS, but otherwise “Where were you Python, when I were a lad, down coding pit, slaving over hot Cobol …”).

Enough work, the sun is shining; the chiffchaff is, well, chiff-chaffing; spring has sprung, I’m off out to the garden…

Update:

I’ve now managed to embed Python in Excel via my xLite datasmithing tool http://www.gobansaor.com/xlite, another fine reason to use Python.

Update:

Another Python within Excel option is PyXLL, allows for the creation of UDFs and Menu macros in pure Python (very similar to what ExcelDNA offers for .NET managed code in C# or VB.NET).

It’s linked to from this page on my blog (which has had 200 or so hits this month) and from this AWS Community Code page. The excessive hits on the bucket started on the 28th of Feb , the day the xlAWS code was published on Amazon and continued through most of March. Talking the size of the zip file, 133GB represents approximately 100,000 downloads. I don’t have server logging enabled on the bucket, so I can’t be sure how much is due to the other public files in the bucket (all belonging to the VBA/Proto SQLite xLite project), but as that project has been available for months and is accessible only through my website (who’s stats show a consistent 5-10 downloads per week) I’m guessing the downloads are for xlAWS.

Who would have though that there would be such interest in VBA/VB6 code for accessing AWS services! I wonder was it the Excel VBA side of the house or the dispossessed (and p*ssed off) VB6 developer hoards who downloaded it the most? Leave a comment if you downloaded and used the library, I’d love to know.

The “free for non-commercial purposes” product is no more, but you can still download a 30-day free trial and the really good news is the new price of $300 for the Proto Individual product.

Also, another business-oriented mash-up tool, RSSBus, is partially out of beta, RSSBus Server RC1 is now available. Still no information on final pricing for the server product. A new Beta 5 release of the free desktop edition is also available for download. As I’ve said before, RSSBus Server front-ended by Proto would be a very powerful combination.