varview
A tiny, zero-dependency debug-printing helper for people who check their work, for clean automation.
from varview import debug
count = 42
total = 137
status = "active"
debug(count, total, status)
count = 42
total = 137
status = active
Why this exists
Most debugging habits start the same way: print(f"count: {count}"),
scattered through a script, forgotten about, and left in, or worse,
silently shaping a result nobody meant to ship.
varview grew out of a data analyst's day-to-day discipline: if
you can't see your intermediate values clearly, you can't trust your
final ones. The habit it's built for is simple: being able to see
every variable in your code, at the point it's actually computed, is
what lets you notice when something is wrong, a value that shifted
type, a filter that let too much or too little through, a join that
didn't do what you expected. Data leakage and other silent
corruption is usually invisible not because it's hard to catch, but
because nobody was looking at the value when it happened. Making
that look cheap and habitual, instead of a special debugging step
you only reach for once something already seems broken, is the whole
point.
That's the whole philosophy behind this package:
- See it before you trust it. Print the name and the value, side by side, with no risk of the label drifting out of sync with what it's labeling.
- Validate loudly, not quietly. Every parameter is checked up front. Bad input fails fast with a clear error instead of producing a confusing result three functions later.
- Make leakage a choice, not an accident. One global switch silences every debug call in a file at once, so nothing you used to sanity-check an intermediate value can slip into a shared notebook or a production run by accident.
varview doesn't detect leakage, drift, or corruption on its own,
it has no idea what your data means. What it does is make the habit
that catches those problems, actually looking at your intermediate
values, cheap enough to do every time instead of only after
something already looks wrong.
Install
pip install varview
Usage
Basic
from varview import debug
count = 42
debug(count) # unquoted variable -> "count = 42"
debug("Checking count") # a quoted string prints literally, as-is
Multiple variables, comma-separated
Pass as many variables as you want, separated by commas. No need to wrap them in a list:
count = 42
total = 137
status = "active"
debug(count, total, status)
count = 42
total = 137
status = active
Unquoted variables
You don't have to quote the name at all. varview reads the call's
own source code to recover the label, so the variable itself can be
passed directly:
debug(count) # prints "count = 42", no quotes needed
debug(count, total) # prints both, labels taken straight from source
This is resolved from the source text of the call, not from the
runtime type of the value, so it stays correct even if a variable
happens to hold a string. region = "north" passed unquoted as
debug(region) still prints region = north, exactly like any
other variable, it is never confused with the literal-print behavior
that quoting triggers (see below).
If the source can't be recovered (for example, calls made from a REPL
or from exec()'d code), varview falls back to a best-effort
heuristic instead of failing.
Quoted strings print literally
A quoted string isn't looked up anywhere, it's printed exactly as
written, the same as a plain print() statement. That makes it a
convenient way to drop a header or a note in between the variables
you're actually checking:
blended_xg = 1.8
scorelines = ["1-2", "2-0"]
debug("Match stats:", blended_xg, scorelines)
Match stats:
blended_xg = 1.8
scorelines = ['1-2', '2-0']
Quoted vs. unquoted is determined from the call's own source code, not from the runtime type of the value, so this stays correct even when a variable's value happens to be a string.
A variable holding a list or tuple is printed as one value
Each comma-separated argument is always treated as exactly one entry, no matter what its runtime value turns out to be, including when that value is itself a list or tuple:
quarterly_revenue = [120000, 135000, 128000, 151000]
debug(quarterly_revenue)
quarterly_revenue = [120000, 135000, 128000, 151000]
This prints as a single line, the variable is never unpacked into one entry per element. To see multiple entries, pass multiple comma-separated arguments instead:
monthly_churn_rate = 0.034
active_subscribers = 8421
quarterly_revenue = [120000, 135000, 128000, 151000]
debug(monthly_churn_rate, active_subscribers, quarterly_revenue)
monthly_churn_rate = 0.034
active_subscribers = 8421
quarterly_revenue = [120000, 135000, 128000, 151000]
Seeing a value instead of assuming it
The pattern that motivated this package: a quick, visible check right where a value is computed, left in place instead of deleted, and silenced in one line before anything ships.
raw_rows = len(df)
df = df.dropna(subset=["customer_id"])
clean_rows = len(df)
dropped = raw_rows - clean_rows
debug(raw_rows, clean_rows, dropped, color="red")
raw_rows = 10482
clean_rows = 10471
dropped = 11
Seeing dropped here is the difference between knowing exactly what
a cleaning step did and just assuming it did what you meant.
Note: older versions of
varviewused a list-bracket calling convention,debug(["count", "total"]). That form is no longer treated specially,debug([a, b])is now one argument whose value is a 2-element list, printed as a single line, not unpacked into two. Use plain comma-separated arguments instead:debug(a, b).Even older versions also looked up quoted strings by name in the caller's local scope (
debug("count")would find and print the variablecount). That lookup no longer happens. A quoted string is now printed literally, as-is, like a plainprint()statement.
Color-code by what the value means to you
debug(count, color="green") # default, all good
debug(count, color="yellow") # worth a second look
debug(count, color="red") # flag it
Color only applies to the label of an unquoted variable's line. A
quoted, literal-print line always prints as plain, uncolored text,
same as print().
Lay it out the way you're scanning
debug(count, total, status) # vertical (default)
debug(count, total, status, orientation="horizontal") # count = 42, total = 137, status = active
Push a line to the right with pad
pad adds spaces to the left of a line, and it works the same way
in either orientation:
debug(count, total, pad=4) # both lines get 4 leading spaces
count = 42
total = 137
Give it a list instead of a single number to control each argument's padding individually. The list has to have exactly one entry per argument passed:
debug(count, total, pad=[2, 6])
count = 42
total = 137
debug(count, total, pad=[2]) # only 1 value for 2 arguments
# ValueError: pad list must have exactly 2 value(s) to match the
# 2 argument(s) passed to debug(), got 1
For padding just one argument without spelling out a value for every
other one too, wrap that single argument in pad(value, spaces)
instead, from the same import:
from varview import debug, pad
debug(pad(count, 4), total)
count = 42
total = 137
Here count gets 4 leading spaces and total gets none, since it
wasn't touched. A pad(...)-wrapped argument's own spacing always
wins over the call-level pad= value for that one argument:
debug(pad(count, 4), total, status, pad=1)
count = 42
total = 137
status = active
pad() works on quoted, literal-print lines too, not just variables:
debug(pad("Result:", 2), count)
Result:
count = 42
Trim the surrounding whitespace
debug(count, total, margin=False)
By default, debug() prints a blank line before and after its
output so it stands out in a busy terminal or log. Set margin=False
for tightly packed output with nothing extra around it.
Turn one call off without deleting it
debug(count, display=False)
Turn every call off at once, before you share or ship
from varview import debug_off, debug_on
debug_off() # every debug() call in the process goes silent, even display=True ones
# ... run the rest of your pipeline, notebook export, whatever needs to be clean ...
debug_on() # back to normal for your next debugging session
debug_off() is the one-line answer to "did I leave a debug print
in this notebook before I sent it to someone." Flip it at the top of
a cell, or right before a scheduled job runs, and every debug()
call downstream goes quiet, no hunting through the file for calls
you forgot about.
API
debug(*names, color="green", display=True, orientation="vertical", margin=True, pad=0)
| Param | Type | Default | Notes |
|---|---|---|---|
*names |
one or more str literals, or unquoted variables, comma-separated |
(required, at least one) | Quoted strings print literally, as-is, no lookup; unquoted variables have their label recovered from source and their value used directly, even if that value is a list or tuple |
color |
"green", "red", "yellow" |
"green" |
Label color for unquoted variables only, values always print in black; quoted literal-print lines are always plain, uncolored text |
display |
bool |
True |
Silences this one call when False |
orientation |
"vertical", "horizontal" |
"vertical" |
Layout of the printed lines |
margin |
bool |
True |
Blank line before and after the printed output |
pad |
int or list[int] |
0 |
Spaces added to the left of each line. A single int applies to every line; a list must have exactly one entry per argument passed. Wrap a single argument in pad(value, spaces) (imported alongside debug) to override its padding individually, one argument at a time |
All parameters are validated on every call: an invalid color,
orientation, or pad raises ValueError or TypeError as
appropriate; an invalid display or margin type raises
TypeError. Nothing gets a chance to fail silently or print
something misleading.
pad(value, spaces)
Wraps a single debug() argument so it can have its own left-padding
without affecting any other argument in the same call. Works on both
unquoted variables and quoted, literal-print strings. spaces must
be a non-negative int.
debug_off() / debug_on()
Module-level switch. debug_off() silences every debug() call in
the running process, regardless of that call's own display value.
debug_on() restores normal behavior.
License
MIT
Metadata
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