Tiny, useful Python lib for strings and files
Project description
strif
Strif is a tiny (~1000 loc) library of a few basic string, file, and object utilities for modern Python.
It has zero dependencies.
It is simply a few functions and tricks that have repeatedly shown value in various projects. The goal is to complement the standard libs and fill in a few gaps, but not replace or wrap standard libraries.
✨ NEW: Version 3.0 is out and has additions and updates for Python 3.10-3.13! ✨
A quick overview is here in the readme. The libs are all small so see pydoc strings or code for full docs.
Installation
# Use uv
uv add strif
# Or poetry
poetry add strif
# Or pip
pip install strif
Text Abbreviations and Formatting
-
abbrev_str(string: str, max_len: Optional[int] = 80, indicator: str = '…')
Abbreviates a string and appends an indicator if the content exceeds the allowed length.
-
abbrev_list(items: List[Any], max_items: int = 10, item_max_len: Optional[int] = 40, joiner: str = ', ', indicator: str = '…')
Shortens each element of a list and appends an ellipsis if the list is truncated.
-
single_line(text: str)
Converts multi-line text into a single line by replacing extra whitespace with spaces.
-
quote_if_needed(arg: Any)
Returns a string with quotes if needed for proper display (for example, for filenames with spaces).
String Identifiers, Timestamps, and Hashing
[!TIP]
These functions use base 36. In my humble opinion, base 36 ids are underrated and should be used more often.
Base 36 is briefer than hex and avoids ugly non-alphanumeric characters like base 64. And they are case insensitive, which is generally wise: If you use identifiers for filenames, you definitely should prefer case insensitive identifiers because of case-insensitive filesystems (like macOS). And they're easier to read aloud over the phone for an auth code or to type manually.
If you need a readable, concise identifier, api key format, or hash format, consider
-
new_uid(bits: int = 64)
Generates a random base36 alphanumeric string with at least the specified bits of randomness. Suitable for filenames (especially on case-insensitive filesystems).
-
new_timestamped_uid(bits: int = 32)
Creates a unique ID starting with an ISO timestamp, then fractions of seconds and bits of randomness. Example:
20150912T084555Z-378465-43vtwbx
-
iso_timestamp(microseconds: bool = True)
Returns an ISO 8601 timestamp in UTC, e.g.
2015-09-12T08:41:12.397217Z
(with microseconds) or2015-09-12T08:41:12Z
(without). -
format_iso_timestamp(datetime_obj: datetime, microseconds: bool = True)
Formats a given datetime object as an ISO 8601 timestamp, ensuring UTC formatting with a trailing Z.
-
clean_alphanum(string: str, max_length: Optional[int] = None)
Converts a string to a clean identifier by keeping only the first alphanumeric characters and replacing others with underscores.
-
clean_alphanum_hash(string: str, max_length: int = 64, max_hash_len: Optional[int] = None)
Combines the cleaned version of a string with a base36 SHA1 hash to minimize collisions.
File Hashing
-
file_mtime_hash(path: str | Path)
Computes a fast hash using a file's name, size, and high-resolution modification time, without looking at file contents. A useful key for fast caching of file contents.
-
hash_string(string: str, algorithm: str = 'sha1') -> Hash
andhash_file(file_path: str | Path, algorithm: str = 'sha1') -> Hash
Provide flexible hashing mechanisms. The returned
Hash
object has properties to output the digest in hexadecimal, base36, or with a prefixed algorithm name.
Atomic File Operations with Optional Backups
[!TIP]
It’s generally good practice when creating files to write to a file with a temporary name, and move it to a final location once the file is complete. This way, you never leave partial, incorrect versions of files in a directory due to interruptions or failures.
-
atomic_output_file(dest_path: str | Path, make_parents: bool = False, backup_suffix: Optional[str] = None, tmp_suffix: str = '.partial')
A context manager for writing files or directories atomically. A temporary file is created and, upon successful completion, renamed to the target location.
-
copyfile_atomic(source_path: str | Path, dest_path: str | Path, make_parents: bool = False, backup_suffix: Optional[str] = None)
Atomically copies a file while preserving its timestamps.
-
copytree_atomic(source_path: str | Path, dest_path: str | Path, make_parents: bool = False, backup_suffix: Optional[str] = None, symlinks: bool = False)
Recursively copies a directory or file atomically.
-
move_to_backup(path: str | Path, backup_suffix: str = '{timestamp}.bak')
andcopy_to_backup(path: str | Path, backup_suffix: str = '{timestamp}.bak')
Functions to move or copy an existing file or directory to a backup destination.
-
move_file(src_path: Path, dest_path: Path, keep_backup: bool = True, backup_suffix: str = '{timestamp}.bak')
Moves a file to a new location, automatically creating parent directories and optionally keeping a backup of the destination if it already exists.
For example, it is generally a good idea to wrap an open()
call with
atomic_output_file()
:
with atomic_output_file("some-dir/my-final-output.txt") as temp_target:
with open(temp_target, "w") as f:
f.write("some contents")
And this can (and in most cases should) be used in place of shutil.copyfile
:
copyfile_atomic(source_path, dest_path, make_parents=True, backup_suffix=None)
Now if there is some issue during write, the output will instead be at a temporary
location in the same directory (with a name like
some-dir/my-final-output.txt.partial.XXXXX
.) This ensures integrity of the file
appearing in the final location.
There are also some handy additional options:
with atomic_output_file("some-dir/my-final-output.txt",
make_parents=True, backup_suffix=".old.{timestamp}") as temp_target:
with open(temp_target, "w") as f:
sf.write("some contents")
This creates parent folders as needed (a major convenience). And if you would have clobbered a previous output, it keeps a backup with a (fixed or uniquely timestamped) suffix.
Used judiciously, these options can save boilerplate coding and avoid debugging ugly corner case failures with zero-length or truncated files.
Syntax Sugar for Temporary Files
Syntax sugar for auto-deleting temporary files or directories using with
:
with temp_output_file("my-scratch.") as (fd, path):
# Do a bunch of stuff with the opened file descriptor or path, knowing
# it will be removed assuming successful termination.
with temp_output_dir("work-dir.", dir="/var/tmp") as work_dir:
# Create some files in the now-existing path work_dir, and it will be
# deleted afterwards.
Note these don’t delete files in case of error, which is usually what you want.
Add always_clean=True
if you want the temporary file or directory to be removed no
matter what.
Multiple String Replacements
-
insert_multiple(text: str, insertions: list[Insertion]) -> str
Insert multiple strings into
text
at the given offsets, at once. -
replace_multiple(text: str, replacements: list[Replacement]) -> str
Replace multiple substrings in
text
with new strings, simultaneously. The replacements are a list of tuples (start_offset, end_offset, new_string).
Simple String Template
A validated template string that supports only specified fields.
Can subclass to have a type with a given set of allowed_fields
. Provide a type with a
field name to allow validation of int/float format strings.
Examples:
>>> t = StringTemplate("{name} is {age} years old", ["name", "age"])
>>> t.format(name="Alice", age=30)
'Alice is 30 years old'
>>> t = StringTemplate("{count:3d}@{price:.2f}", [("count", int), ("price", float)])
>>> t.format(count=10, price=19.99)
' 10@19.99'
Atomic Vars
AtomicVar
is a simple zero-dependency thread-safe variable that works for any type.
Often the standard "Pythonic" approach is to use locks directly, but for some common use
cases, AtomicVar
may be simpler and more readable.
Works on any type, including lists and dicts.
Other options include threading.Event
(for shared booleans), threading.Queue
(for
producer-consumer queues), and multiprocessing.Value
(for process-safe primitives).
Examples:
# Immutable types are always safe:
count = AtomicVar(0)
count.update(lambda x: x + 5) # In any thread.
count.set(0) # In any thread.
current_count = count.value # In any thread.
# Useful for flags:
global_flag = AtomicVar(False)
global_flag.set(True) # In any thread.
if global_flag: # In any thread.
print("Flag is set")
# For mutable types,consider using `copy` or `deepcopy` to access the value:
my_list = AtomicVar([1, 2, 3])
my_list_copy = my_list.copy() # In any thread.
my_list_deepcopy = my_list.deepcopy() # In any thread.
# For mutable types, the `updates()` context manager gives a simple way to
# lock on updates:
with my_list.updates() as value:
value.append(5)
# Or if you prefer, via a function:
my_list.update(lambda x: x.append(4)) # In any thread.
# You can also use the var's lock directly. In particular, this encapsulates
# locked one-time initialization:
initialized = AtomicVar(False)
with initialized.lock:
if not initialized: # checks truthiness of underlying value
expensive_setup()
initialized.set(True)
# Or:
lazy_var: AtomicVar[list[str] | None] = AtomicVar(None)
with lazy_var.lock:
if not lazy_var:
lazy_var.set(expensive_calculation())
FAQ
Why bother, if it’s so short?
Because it saves time, saves you stupid bugs and clumsy repetition, and has zero (yes zero) dependencies.
Aren't there other libraries that offer these utilities?
A few yes, but most libs I've seen that offer general-purpose tools are larger or more
opinionated. And some like atomic_output_file()
or the base36 tools I find useful but
haven't seen equivalents elsewhere.
If you don't want the dependency on strif, also feel free to just copy the bit you want! They're each short.
Is it mature?
I’ve used many of these functions in production situations for years. It doesn't have comprehensive tests, however.
Development
For how to install uv and Python, see installation.md.
For development workflows, see development.md.
For instructions on publishing to PyPI, see publishing.md.
This project was built from simple-modern-uv.
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