tivars_lib_py is a Python package for interacting with TI-(e)z80 (82/83/84 series) calculator files, i.e. lists, programs, matrices, appvars, etc.
Much of the functionality of this package has been ported over from tivars_lib_cpp. However, a number of changes have been made to the API to better suit Python's strengths and capabilities as a language (e.g. scripting, dynamic typing).
The current release version is v0.9.2. All versions require Python 3.10+ to run.
Install the tivars package from PyPI using pip:
pip install tivars
Alternatively, you can clone this repository or download a release and extract the tivars directory to include it in your next project. Once downloaded, you can also use pip to install it locally.
Include this repository in your next project as a submodule using the git submodule command. Then, add the following to any file which imports tivars:
import sys
sys.path.insert(1, 'tivars_lib_py/')Check out this tool for an example.
You can run the test suite via __main__.py, or run individual tests found in tests/ with unittest. Tests for optional package extensions (e.g. PIL) will be skipped if the package cannot be found.
Warning
The PyPI distribution does not include the test suite.
Every var file has two parts: a header and a number of entries, where an entry contains the data for a single variable. Usually, var files contain just one entry; in these cases, there's not much distinction between a var and an entry for the purposes of messing with its data.
To create an empty entry, instantiate its corresponding type from tivars.types. You can specify additional parameters as you like:
from tivars.models import *
from tivars.types import *
my_program = TIProgram(name="HELLO")Tip
If you're not sure of an entry's type, you can instantiate a base TIEntry.
If you want to create an entire var or just a header, use TIVar or TIHeader instead:
from tivars.var import *
my_var = TIVar()
my_var_for84pce = TIVar(model=TI_84PCE)
my_header = TIHeader()
my_header_with_a_cool_comment = TIHeader(comment="Wow! I'm a comment!")Vars can be loaded from files or raw bytes:
my_var = TIVar.open("HELLO.8xp")
with open("HELLO.8xp", 'rb') as file:
my_var.load_var_file(file)
file.seek(0)
my_var.load_bytes(file.read())Important
When loading from a file object, make sure the file is opened in binary mode.
Entries can be loaded from files or raw bytes. When loading from a file, you may specify which entry to load if there are multiple:
# Raises an error if the var has multiple entries
my_program = TIProgram.open("HELLO.8xp")
with open("HELLO.8xp", 'rb') as file:
# Offset counts the number of entries to skip; defaults to zero
my_program.load_from_file(file, offset=1)
file.seek(0)
my_program.load_bytes(file.read())Most entry types also support loading from other natural data types. Any data can be passed to the constructor directly and be delegated to the correct loader:
my_program = TIProgram("Disp \"HELLO WORLD!\"")
my_program.load_string("Disp \"HELLO WORLD!\"")
my_real = TIReal(1.23)
my_real.load_float(1.23)Base TIEntry objects, as well other parent types like TIGDB, will be automatically coerced to the correct type:
# Coerces to a TIProgram
my_entry = TIEntry.open("HELLO.8xp")Tip
Any entry type can be cast to any other by setting the object's __class__.
Export a var as bytes or straight to a file:
my_var.save("HELLO.8xp")
# Infer the filename and extension
my_var.save()
with open("HELLO.8xp", 'wb+') as file:
file.write(my_var.bytes())Important
.save() uses the var's name as the filename, saving to the current working directory.
Entries can be passed an explicit header to attach or model to target when exporting:
my_program.save("HELLO.8xp")
my_program.save()
with open("HELLO.8xp", 'wb+') as file:
file.write(my_program.export(header=my_header).bytes())Any input data type can also be exported to:
assert my_program.string() == "Disp \"HELLO WORLD!\""
assert my_real.float() == 1.23Tip
Built-in types can be exported to using the standard constructors, e.g. str(my_program).
Vars are comprised of individual sections which represent different forms of data, split across the header and entries. The var itself also contains the total entry length and checksum sections, but these are read-only to prevent file corruption.
You can read and write to individual sections of an entry or header as their "canonical" type:
my_header.comment = "This is my (even cooler) comment!"
my_program.archived = True
assert my_program.type_id == 0x05Data sections can also be other entry types:
my_gdb = TIGDB()
my_gdb.Xmin = TIReal(0)
assert my_gdb.Xmax == TIReal(10)Each section is annotated with the expected type.
Tip
Data sections can accept any subtype of their expected type.
All vars store their data sections as raw bytes in the format interpreted by the calculator. Access any data section as a member of the .raw attribute to view and edit these bytes directly.
my_header.raw.comment = "This is my (even rawer) comment!".encode('utf-8')
my_program.raw.archived = b'\x80'
assert my_program.raw.type_id == b'\x05'Warning
Edits to read-only bytes like the checksum are reset whenever any other data in the var is updated.
All TI-82/83/84 series calcs are represented as TIModel objects stored in tivars.models. Each model contains its name, metadata, and features; use has on a TIFeature to check that a model has a given a feature. Models are also used to determine var file extensions and token sheets.
Flash files such as apps, OSes, and certificates can be loaded using the TIFlashHeader base class or its children. A flash file is composed of one to three headers (though usually only one); these are not to be confused with var headers. A flash header does not need to be "packaged" into a larger file format like an entry in a regular var; see TIFlashHeader.open and TIFlashHeader.save.
Tip
Loading flash files into a TIEntry probably won't work very well.
The tivars.PIL package can be used to interface with PIL, the Python Imaging Library. Simply import the package to register codecs for each of the TI image types. You can then open such images directly into a PIL Image:
from PIL import Image
from tivars.PIL import *
img = Image.open("Pic1.8ci")
img.show()Functions to decode and encode strings into tokens can be found in tivars.tokenizer. These functions utilize the TI-Toolkit token sheets, which are kept as a submodule in tivars.tokens. Support currently exists for all models in the 82/83/84 series; PR's concerning the sheets themselves should be directed upstream.
Library documentation can be found on GitHub Pages.
The var file format(s) and data sections can be found in a readable format on the repository wiki. Much of the information is copied from the TI-83 Link Guide, though has been updated to account for color models.
Note
The wiki is still a work-in-progress. Why not contribute a page?
All entry types support string formatting using Python's f-strings.
- All entries support hex formatting of their data:
{sep}{width}xsep: a single character to separate groups of hex digits (default: none)width: how many digits to group together (default: no groups)
- Tokenized entries support formatting of their tokens into readable lines:
{line_spec}{sep}{type}{lang}line_spec: format specifier for line numbers (default: no line numbers)sep: a string to separate lines and line numbers (required for line numbering)type: how to format each tokena: use accessible namesd: use display names (default)
lang: language code of the desired translation language (default: en)
- Numerical entries support float-style formatting, whose complete details can be found in the Python docs.
- Lists and matrices support float-style formatting, applied to their elements.
Additionally, the t type is supported for types which can be made from tokens, composing the object out of typeable (accessible) token names. For example, -2 + 5i is presented as ~2+5[i].
You can find more sample code in examples that details common operations on each of the entry types. There are also examples for interfacing with popular external libraries (e.g. NumPy, PIL). Contributions welcome!