So far, I think the use of ratios for subplot widths/heights has worked
well, with the exception of the default behavior for repeated neighbors
being a bit garbage.
Before, the default was a simple 0.5x of the current row/column:
./scripts/csv.py test.csv -xx \
--subplot="-ya" \
--subplot-right="-yb -W0.5" \
--subplot-right="-yc -W0.5" \
--subplot-right="-yd -W0.5" \
--subplot-right="-ye -W0.5"
And while this is certainly simple, it's behavior is not the most
intuitive. When -ye takes 0.5x, it takes 0.5x of the _whole_ grid,
squishing -ya + -yb + -yc + -yd into the other 0.5x as needed. As a
result, -ya ends up with 0.0625x of the final grid.
You could argue this is confusing behavior, but I worry trying to make
it "smarter" will just make it more confusing when multiple dirs/
nestings are mixed.
---
But we can at least change the _default_ behavior to be less confusing.
Now, instead of defaulting to 0.5x, we keep a sum of the number of
subplots seen in the current direction (row vs column), and default the
next subplot's width/height to 1/n.
As a result, repeated subplots end up like the following:
./scripts/csv.py test.csv -xx \
--subplot="-ya" \
--subplot-right="-yb -W0.5" \
--subplot-right="-yc -W0.3333333" \
--subplot-right="-yd -W0.25" \
--subplot-right="-ye -W0.2"
Which may look crazy, but cancels out the nested ratio so the final grid
is a set of evenly distributed columns.
---
Maybe this is still too clever and will need to be reverted in the
future, but in the meantime it provides a nice default for the common
use case of repeated subplots.
These just expose the low-level w/hpad and w/hspace controls available
in matplotlib's constrained_layout.
---
I think something funky might be going on with matplotlib's
constrained_layout. I've noticed a relatively annoying amount of padding
as the number of plots in the grid grow quite large. Though as is usual
with plotmpl.py, this may just be my own fault with the amount of hacks
being applied.
--w/hpad and --w/hspace provide a temporary workaround by overriding the
low-level padding controls in matplotlib's constrained_layout (--w/hpad
should probably be preferred, --w/hspace seems to be a legacy option).
Though, while a temporary solution, these are probably a good idea to
keep around for easy tweaking of plot padding.
This was completely broken due to the renderer ignoring s.xspan. As a
result, subplots could end up rendered multiple times if they spanned
neighboring subplots.
Quick example:
./scripts/plot.py test.csv -xx \
--subplot="-ya" \
--subplot-right="-yb" \
--subplot-below="-yc"
Fortunately the fix is easy, just make sure to increment x_ += s.xspan
as we render subplots across the x-axis.
Curiously the behavior was already correct for the y-axis, I guess
because the y-axis is quite a bit more complicated with how it crosses
multiple lines.
A small tweak, but this resolves some confusing interactions between
subplot subplots and regular subplots.
Consider:
./scripts/plot.py test.csv -xx \
--subplot=" \
-ya \
--subplot-below=\" \
-yab\"" \
--subplot-right=" \
-yb \
--subplot-below=\" \
-ybb\""
You would normally expect -yab and -ybb to end up side-by-side. But
because regular subplots were parsed fully before subplot subplots, -yab
confusingly ended up beneath the sum of -ya + (-yb + -ybb).
The small tweak of prioritizing subplot subplots fixes this, and
results in the expected 2x2 grid of plots.
This adds -U/--undefine as an inverse -D/--define, allowing you to
select results where a given field does _not_ match a set of
values/globs.
For example, make bench-marks, which need to ignore stack/heap/usage
probes as a special case, can easily filter like so:
$ ./scripts/csv.py test.csv -Uprobe=stack,heap,usage
---
One thing globbing is pretty bad at is inverse matches. This is
_usually_ easy enough to work around, but has been an annoyance enough
times that I think _some_ option to inverse filter is warranted.
I'm not sure -U/--undefine is the best name for this, since field isn't
really "undefined" as a result (well kinda? if you're relying on
implicit by/field rules?), but it gets the job done.
This changes -w/--wait to sleep _after_ -k/--keep-open, instead of
including the time spent waiting on inotifywait in the sleep time.
1. It's easier, no need to keep track of when we started waiting.
2. It's simpler to reason about.
3. It trivially avoids the multiple wakeup noise that plagued
watch.py + vim (vim likes to do a bunch of renaming and stuff when
saving files, including the file 4913 randomly?)
Avoiding this was previously impossible because -~/--sleep was
effectively a noop when combined with -k/--keep-open.
---
Also renamed from -~/--sleep -> -w/--wait, which is a bit more intuitive
and avoids possible shell issues with -~.
To make this work, dropped the -w/--block-cycles shortform flag in
dbgtrace.py. It's not like this flag is ever used anyways.
Though at the moment this is ignoring the possible conflict with
-w/--word-bits...
I've been struggling to keep plots readable with --x/ylim-stddev, it may
have been the wrong tool for the job.
This adds --x/ylim-ratio as an alternative, which just sets the limit to
include x-percent of the data (I avoided "percen"t in the name because
it should be --x/ylim-ratio=0.98, not 98, though I'm not sure "ratio" is
great either...).
Like --x/ylim-stddev, this can be used in both one and two argument
forms:
$ ./scripts/plot.py --ylim-ratio=0.98
$ ./scripts/plot.py --ylim-=-0.98,+0.98
So far, --x/ylim-ratio has proven much easier to use, maybe because our
amortized results don't follow a normal distribution? --x/ylim-ratio
seems to do a good job of clipping runaway amortized results without too
much information loss.
This adds %i and %I as punescape modifiers for limited printing of
integers with SI prefixes:
- %(field)i - base-10 SI prefixes
- 100 => 100
- 10000 => 10K
- 0.01 => 10m
- %(field)I - base-2SI prefixes
- 128 => 128
- 10240 => 10Ki
- 0.125 => 128mi
These can also easily include units as a part of the punescape string:
- %(field)iops/s => 10Kops/s
- %(field)IB => 10KiB
This is particularly useful in plotmpl.py for adding explicit
x/yticklabels without sacrificing the automatic SI-prefixes.
This actually binds our custom write/writeln functions as methods to the
file object:
def writeln(self, s=''):
self.write(s)
self.write('\n')
f.writeln = writeln.__get__(f)
This doesn't really gain us anything, but is a bit more correct and may
be safer if other code messes with the file's internals.
This adds --xlim-stddev and --ylim-stddev as alternatives to -X/--xlim
and -Y/--ylim that define the plot limits in terms of standard
deviations from the mean, instead of in absolute values.
So want to only plot data within +-1 standard deviation? Use:
$ ./scripts/plot.py --ylim-stddev=-1,+1
Want to ignore outliers >3 standard deviations? Use:
$ ./scripts/plot.py --ylim-stddev=3
This is very useful for plotting the amortized/per-byte benchmarks,
which have a tendency to run off towards infinity near zero.
Before, we could truncate data explicitly with -Y/--ylim, but this was
getting very tedious and doesn't work well when you don't know what the
data is going to look like beforehand.
This should be floor (rounds towards -inf), not int (rounds towards
zero), otherwise sub-integer results get funky:
- floor si(0.00001) => 10u
- int si(0.00001) => 0.01m
- floor si(0.000001) => 1u
- int si(0.000001) => m (???)
Before this, the only option for ordering the legend was by specifying
explicit -L/--add-label labels. This works for the most part, but
doesn't cover the case where you don't know the parameterization of the
input data.
And we already have -s/-S flags in other csv scripts, so it makes sense
to adopt them in plot.py/plotmpl.py to allow sorting by one or more
explicit fields.
Note that -s/-S can be combined with explicit -L/--add-labels to order
datasets with the same sort field:
$ ./scripts/plot.py bench.csv \
-bBLOCK_SIZE \
-xn \
-ybench_readed \
-ybench_proged \
-ybench_erased \
--legend \
-sBLOCK_SIZE \
-L'*,bench_readed=bs=%(BLOCK_SIZE)s' \
-L'*,bench_proged=' \
-L'*,bench_erased='
---
Unfortunately this conflicted with -s/--sleep, which is a common flag in
the ascii-art scripts. This was bound to conflict with -s/--sort
eventually, so a came up with some alternatives:
- -s/--sleep -> -~/--sleep
- -S/--coalesce -> -+/--coalesce
But I'll admit I'm not the happiest about these...
Globs in CLI attrs (-L'*=bs=%(bs)s' for example), have been remarkably
useful. It makes sense to extend this to the other flags that match
against CSV fields, though this does add complexity to a large number of
smaller scripts.
- -D/--define can now use globs when filtering:
$ ./scripts/code.py lfs.o -Dfunction='lfsr_file_*'
-D/--define already accepted a comma-separated list of options, so
extending this to globs makes sense.
Note this differs from test.py/bench.py's -D/--define. Globbing in
test.py/bench.py wouldn't really work since -D/--define is generative,
not matching. But there's already other differences such as integer
parsing, range, etc. It's not worth making these perfectly consistent
as they are really two different tools that just happen to look the
same.
- -c/--compare now matches with globs when finding the compare entry:
$ ./scripts/code.py lfs.o -c'lfs*_file_sync'
This is quite a bit less useful that -D/--define, but makes sense for
consistency.
Note -c/--compare just chooses the first match. It doesn't really make
sense to compare against multiple entries.
This raised the question of globs in the field specifiers themselves
(-f'bench_*' for example), but I'm rejecting this for now as I need to
draw the complexity/scope _somewhere_, and I'm worried it's already way
over on the too-complex side.
So, for now, field names must always be specified explicitly. Globbing
field names would add too much complexity. Especially considering how
many flags accept field names in these scripts.
This was broken:
$ ./scripts/plotmpl.py -L'*=bs=%(bs)s'
There may be a better way to organize this logic, but spamming if
statements works well enough.
Two new tricks:
1. Hide the cursor while redrawing the ring buffer.
2. Build up the entire redraw in RAM first, and render everything in a
single write call.
These _mostly_ get rid of the cursor flickering issues in rapidly
updating scripts.
The notable exception being plot.py, where line-level history doesn't
really make sense.
These scripts all default to height=1, and -n/--lines can be useful for
viewing changes over time.
In theory you could achieve something similar to this with tailpipe.py,
but you would lose the header info, which is useful.
---
Note, as a point of simplicity, we do _not_ show sub-char history like
we used to in tracebd.py. That was way too complicated for what it was
worth.
This simplifies attrs a bit, and scripts can always override
__getitem__ if they want to provide lazy attr generation.
The original intention of accepting functions was to make lazy attr
generation easier, but while tinkering around with the idea I realized
the actual attr mapping/generation would be complicated enough that
you'd probably want a full class anyways.
All of our scripts are only using dict attrs anyways. And lazy attr
generation is probably a premature optimization for the same reason
everyone's ok with Python's slices being O(n).
This mirrors how -H/--height and -W/--width work, with -n-1 using the
terminal height - 1 for the output.
This is very useful for carving out space for the shell prompt and other
things, without sacrificing automatic sizing.
It's a mess but it's working. Still a number of TODOs to cleanup...
This adopts all of the changes in dbgbmap.py/dbgbmapd3.py, block
grouping, nested curves, Canvas, Attrs, etc:
- Like dbgbmap.py, we now group by block first before applying space
filling curves, using nested space filling curves to render byte-level
operations.
Python's ft.lru_cache really shines here.
The previous behavior is still available via -u/--contiguous
- Adopted most features in dbgbmap.py, so --to-scale, -t/--tiny, custom
--title strings, etc.
- Adopted Attrs so now chars/coloring can be customized with
-./--add-char, -,/--add-wear-char, -C/--add-color,
-G/--add-wear-color.
- Renamed -R/--reset -> --volatile, which is a much better name.
- Wear is now colored cyan -> white -> read, which is a bit more
visually interesting. And we're not using cyan in any scripts yet.
In addition to the new stuff, there were a few simplifications:
- We no longer support sub-char -n/--lines with -:/--dots or
-⣿/--braille. Too complicated, required Canvas state hacks to get
working, and wasn't super useful.
We probably want to avoid doing too much cleverness with -:/--dots and
-⣿/--braille since we can't color sub-chars.
- Dropped -@/--blocks byte-level range stuff. This was just not worth
the amount of complexity it added. -@/--blocks is now limited to
simple block ranges. High-level scripts should stick to high-level
options.
- No fancy/complicated Bmap class. The bmap object is just a dict of
TraceBlocks which contain RangeSets for relevant operations.
Actually the new RangeSet class deserves a mention but this commit
message is probably already too long.
RangeSet is a decently efficient set of, well, ranges, that can be
merged and queried. In a lower-level language it should be implemented
as a binary tree, but in Python we're just using a sorted list because
we're probably not going to be able to beat O(n) list operations.
- Wear is tracked at the block level, no reason to overcomplicate this.
- We no longer resize based on new info. Instead we either expect a
-b/--block-size argument or wait until first bd init call.
We can probably drop the block size in BD_TRACE statements now, but
that's a TODO item.
- Instead of one amalgamated regex, we use string searches to figure out
the bd op and then smaller regexes to parse. Lesson learned here:
Python's string search is very fast (compared to regex).
- We do _not_ support labels on blocks like we do in treemap.py/
codemap.py. It's less useful here and would just be more hassle.
I also tried to reorganize main a bit to mirror the simple two-main
approach in dbgbmap.py and other ascii-rendering scripts, but it's a bit
difficult here since trace info is very stateful. Building up main
functions in the main main function seemed to work well enough:
main -+-> main_ -> trace__ (main thread)
'-> draw_ -> draw__ (daemon thread)
---
You may note some weirdness going on with flags. That's me trying to
avoid upcoming flag conflicts.
I think we want -n/--lines in more scripts, now that it's relatively
self-contained, but this conflicts with -n/--namespace-depth in
codemap[d3].py, and risks conflict with -N/--notes in csv.py which may
end up with namespace-related functionality in the future.
I ended up hijacking -_, but this conflicted with -_/--add-line-char in
plot.py, but that's ok because we also want a common "secondary char"
flag for wear in tracebd.py... Long story short I ended up moving a
bunch of flags around:
- added -n/--lines
- -n/--namespace-depth -> -_/--namespace-depth
- -N/--notes -> -N/--notes
- -./--add-char -> -./--add-char
- -_/--add-line-char -> -,/--add-line-char
- added -,/--add-wear-char
- -C/--color -> -C/--add-color
- added -> -G/--add-wear-color
Worth it? Dunno.
Like codemapd3.py this include an interactive UI for viewing the
underlying filesystem graph, including:
- mode-tree - Shows all reachable blocks from a given block
- mode-branches - Shows immediate children of a given block
- mode-references - Shows parents of a given block
- mode-redund - Shows sibling blocks in redund groups (This is
currently just mdir pairs, but the plan is to add more)
This is _not_ a full filesystem explorer, so we don't embed all block
data/metadata in the svg. That's probably a project for another time.
However we do include interesting bits such as trunk addresses,
checksums, etc.
An example:
# create an filesystem image
$ make test-runner -j
$ ./scripts/test.py -B test_files_many -a -ddisk -O- \
-DBLOCK_SIZE=1024 \
-DCHUNK=10 \
-DSIZE=2050 \
-DN=128 \
-DBLOCK_RECYCLES=1
... snip ...
done: 2/2 passed, 0/2 failed, 164pls!, in 0.16s
# generate bmap svg
$ ./scripts/dbgbmapd3.py disk -b1024 -otest.svg \
-W1400 -H750 -Z --dark
updated test.svg, littlefs v0.0 1024x1024 0x{26e,26f}.d8 w64.128, cksu
m 41ea791e
And open test.svg in a browser of your choice.
Here's what the current colors mean:
- yellow => mdirs
- blue => btree nodes
- green => data blocks
- red => corrupt/conflict issue
- gray => unused blocks
But like codemapd3.py the output is decently customizable. See -h/--help
for more info.
And, just like codemapd3.py, this is based on ideas from d3 and
brendangregg's flamegraphs:
- d3 - https://d3js.org
- brendangregg's flamegraphs - https://github.com/brendangregg/FlameGraph
Note we don't actually use d3... the name might be a bit confusing...
---
One interesting change from the previous dbgbmap.py is the addition of
"corrupt" (bad checksum) and "conflict" (multiple parents) blocks, which
can help find bugs.
You may find the "conflict" block reporting a bit strange. Yes it's
useful for finding block allocation failures, but won't naturally formed
dags in file btrees also be reported as "conflicts"?
Yes, but the long-term plan is to move away from dags and make littlefs
a pure tree (for block allocator and error correction reasons). This
hasn't been implemented yet, so for now dags will result in false
positives.
---
Implementation wise, this script was pretty straightforward given prior
dbglfs.py and codemapd3.py work.
However there was an interesting case of https://xkcd.com/1425:
- Traverse the filesystem and build a graph - easy
- Tile a rectangle with n nice looking rectangles - uhhh
I toyed around with an analytical approach (something like block width =
sqrt(canvas_width*canvas_height/n) * block_aspect_ratio), but ended up
settling on an algorithm that divides the number of columns by 2 until
we hit our target aspect ratio.
This algorithm seems to work quite well, runs in only O(log n), and
perfectly tiles the grid for powers-of-two. Honestly the result is
better than I was expecting.
This finally solves the how-do-I-make-space-for-shell-prompts problem:
- plot.py -H0 => use full terminal height
- plot.py -H-1 => use height-1, making space for shell prompts
- plot.py -H => automatic based on other flags
While also allowing other carveouts in case your prompt takes up more
than 1 line.
Unfortunately this does make -H (no arg) subtly different from -H0, but
sometimes you can't have everything.
This simplifies plot.py's -k/--keep-open logic into a self-contained
loop that just calls main_ on an update.
This is a compromise on getting rid of -k/--keep-open completely, since
we _could_ just rely on watch.py. But plot.py knowing which argument is
the file to watch is convenient.
The eventual plan is to adopt this small bit of copy-pastable-code in
the other ascii-art scripts (treemap.py, dbgbmap.py, etc).
So:
- before: ./scripts/dbgbmap.py disk -b4096 -@0 -n16,32
- after: ./scripts/dbgbmap.py disk -b4096 -@'0 -n16,32'
This is mainly to avoid the naming conflict between -n/--size and
-n/--lines, while also separating out the namespaces a bit.
It's probably not the most intuitive CLI UI, but --off and -n/--size are
probably infrequent arguments at this level of script anyways.
- Fixed a NameError in watch.py caused by an outdated variable name
(renamed paths -> keep_open_paths). Yay for dynamic typing.
- Fixed fieldnames is None issue when csv file is empty.
This should have no noticeable impact on plot.py, but shared classes
have proven helpful for maintaining these scripts.
Unfortunately, this did require some tweaking of the Canvas class to get
things working.
Now, instead of storing things in an internal high-resolution grid,
the Canvas class only keeps track of the most recent character, with
bitmasked ints storing sub-char info.
This makes it so sub-char draws overwrite full characters, which is
necessary for plot.py's axis/data overlap to work.
This only failed if "-" was used as an argument (for stdin/stdout), so
the issue was pretty hard to spot.
openio is a heavily copy-pasted function, so it makes sense to just add
the import os to openio directly. Otherwise this mistake will likely
happen again in the future.
- -*/--add-char/--chars -> -./--add-char/--chars
- -./--points -> -p/--points
- -!/--points-and-lines -> -P/--points-and-lines
Also fixed an issue in plot.py/Attr where non-list default were failing
to concatenate.
This turns out to be extremely useful, for the sole purpose of being
able to specify colors/formats/etc in csv fields (-C'%(fields)s' for
example, or -C'#%(field)06x' for a cooler example).
This is a bit tricky for --chars, but doable with a psplit helper
function.
Also fixed a bug in plot.py where we weren't using dataattrs_ correctly.
This just makes dat behave similarly to Python's getattr, etc:
- dat("bogus") -> raises ValueError
- dat("bogus", 1234) -> returns 1234
This replaces try_dat, which is easy to forget about when copy-pasting
between scripts.
Though all of this wouldn't be necessary if only we could catch
exceptions in expressions...
I guess in addition to its other utilities, csv.py is now also turning
into a sort of man database for some of the more complicated APIs in the
scripts:
./csv.py --help
./csv.py --help-exprs
./csv.py --help-mods
It's a bit minimal, but better than nothing.
Also dropped the %c modifier because this never actually worked.
This adopts the Attr rework for the --add-xticklabel and
--add-yticklabel flags.
Sort of.
These require a bit of special behavior to make work, but should at
least be externally consistent with the other Attr flags.
Instead of assigning to by-field groups, --add-xticklabel/yticklabel
assign to the relevant x/y coord:
$ ./scripts/plotmpl.py \
--add-xticklabel='0=zero' \
--add-yticklabel='100=one-hundred'
The real power comes from our % modifiers. As a special case,
--add-xticklabel/yticklabel can reference the special x/y field, which
represents the current x/y coord:
$ ./scripts/plotmpl.py --y2 --yticks=5 --add-yticklabel='%(y)d KiB'
Combined with format specifiers, this allows for quite a bit:
$ ./scripts/plotmpl.py --y2 --yticks=5 --add-yticklabel='0x%(y)04x'
---
Note that plot.py only shows the min/max x/yticks, so plot.py only
accepts indexed --add-xticklabel/yticklabels, and will error if the
assigning variant is used.
Unifying these complicated attr-assigning flags across all the scripts
is the main benefit of the new internal Attr system.
The only tricky bit is we need to somehow keep track of all input fields
in case % modifiers reference fields, when we could previously discard
non-data fields.
Tricky but doable.
Updated flags:
- -L/--label -> -L/--add-label
- --colors -> -C/--add-color
- --formats -> -F/--add-format
- --chars -> -*/--add-char/--chars
- --line-chars -> -_/--add-line-char/--line-chars
I've also tweaked Attr to accept glob matches when figuring out group
assignments. This is useful for matching slightly different, but
similarly named results in our benchmark scripts.
There's probably a clever way to do this by injecting new by fields with
csv.py, but just adding globbing is simpler and makes attr assignment
even more flexible.
Like treemap.py, but outputting an svg file, which is quite a bit more
useful.
Things svg is _not_:
- A simple vector graphics format
Things svg _is_:
- A surprisingly powerful high-level graphics language.
I might have to use svgs as an output format more often. It's
surprisingly easy to generate graphics without worrying about low-level
rendering details.
---
Aside from the extra flags for svg details like font, padding,
background colors, etc, the main difference between treemap.py and
treemapd3.py is the addition of the --nested mode, which renders a
containing tile for each recursive group (each -b/--by field).
There's no way --nested would've worked in treemap.py. The main benefit
is the extra labels per subgroup, which are already hard enough to read
in treemap.py.
Other than that, treemapd3.py is mostly the same as treemap.py, but with
a resolution that's actually readable.
Based on the d3 javascript library (https://d3js.org), treemap.py
renders heirarchical data as ascii art:
$ ./scripts/treemap.py lfs.code.csv \
-bfunction -fsize --chars=asdf -W60 -H8
total 65454, avg 369 +-366.8σ, min 3, max 4990
aaaassssddddddaaaadddddssddfffaaadfffaassaassfasssdfdfsddfad
aaaassssddddddaaaadddddssddfffaaadfffaassdfaafasssdfdfsddfsf
aaaassssddddddaaaafffffssddfffsssdaaaddffdfaadfaaasdfafaasfa
aaaassssddddddaaaafffffaaaddddsssaassddffdfaaffssfssfsfadffa
aaaassssffffffssssfffffaaaddddsssaassssffddffffssfdffsadfsad
aaaassssffffffssssaaaaasssffffddfaassssaaassdaaddadffsadadad
aaaassssffffffssssaaaaasssffffddfddffddssassdfassadffsadaffa
aaaassssffffffssssaaaaasssffffddfddffddssassdfaddsdadasfsada
(Normally this is also colored, but you know.)
I've been playing around with d3 to try to better visualize code costs
in littlefs, and it's been quite neat. I figured it would be useful to
directly integrate a similar treemap renderer into our result scripts.
That being said, this ascii rendering is probably too difficult to parse
for any non-trivial data. I'm also working on an svg-based renderer, so
treemap.py is really just for in-terminal previews and an exercise to
understand the underlying algorithms, similar to plot.py/plotmpl.py.
You forget one script, running in the background, hogging a whole
core, and suddenly watch's default 2 second sleep time makes a lot more
sense...
One of the main motivators for watch.py _was_ for shorter sleep times,
short enough to render realtime animations (watch is limited to 0.1
seconds for some reason?), but this doesn't mean it needs to be the
default. This can still be accomplished by explicitly specifying
-s/--sleep, and we probably don't want the default to hog all the CPU.
The use case for fast sleeps has been mostly replaced by -k/--keep-open
anyways.
For tailpipe.py and tracebd.py it's a bit less clear, but we probably
don't need to be spamming open calls 10 times a second.
That was confusing.
The -L/--label flag is already tricky enough to get right. Allowing
-L/--label to filter datasets is counter-intuitive and just makes it
harder to debug things.
Unfortunately the import sys in the argparse block was hiding missing
sys imports.
The mistake was assuming the import sys in Python would limit the scope
to that if block, but Python's late binding strikes again...
Moved local import hack behind if __name__ == "__main__"
These scripts aren't really intended to be used as python libraries.
Still, it's useful to import them for debugging and to get access to
their juicy internals.
This is now inconsistent with csv.py, and I don't really want to add a
full expr parser to every script that might want to rename fields.
Field renaming (or any expr really!) can be accomplished with
intermediate calls to csv.py anyways. No reason to make these scripts
more complicated than they need to be.
Christopher Haster