|Dan Helfman bd875013b2||11 months ago|
|example||1 year ago|
|novel_stats||11 months ago|
|tests||1 year ago|
|.drone.yml||11 months ago|
|.gitignore||1 year ago|
|LICENSE||1 year ago|
|README.md||1 year ago|
|example.md||1 year ago|
|pyproject.toml||1 year ago|
|setup.cfg||1 year ago|
|setup.py||11 months ago|
|test_requirements.txt||11 months ago|
|tox.ini||11 months ago|
novel-stats produces word count statistics for novels written in Markdown format, including total word count, word count by status, and optionally per-chapter and per-act word counts. You might find this useful if you're already using tools like Git and Markdown processing as part of your writing workflow (or are looking to start) and want some basic statistics about your novel as you're writing it.
novel-stats is fairly particular about the format of the novel and doesn't currently include much in the way of error checking. Word counts may not be exact.
Example output without any flags:
$ novel-stats example.md drafted: 237 words (~43%) dev edited: 82 words (~15%) total: 539 words
Example output with chapter data:
$ novel-stats -c example.md chapter 1: 103 (drafted) chapter 2: 83 (dev edited) chapter 3: 115 chapter 4: 96 chapter 5: 136 (drafted) drafted: 237 words (~43%) dev edited: 82 words (~15%) total: 539 words
Example with multi-file markdown:
$ novel-stats -pp -c -a multi_file.mdpp chapter 1 Lorem: 203 (drafted) 303 (dev edited) 506 words (total) chapter 2 Ipsum: 84 (dev edited) chapter 3 Dolor: 116 chapter 4 Sit: 97 chapter 5 Amet: 137 (drafted) act 1: 591 words (~62%) act 2: 214 words (~22%) act 3: 138 words (~14%) drafted: 336 words (~35%) dev edited: 385 words (~40%) total: 946 words
Start by cloning the project with git. Then install it with Python's
pip3 install /path/to/novel-stats
novel-stats takes a single argument: The path to your novel file in markdown format. For instance:
novel-stats [-c/--chapter] [-a/--act] [-pp] /path/to/your/novel.md[pp]
--chapter— output chapter-by-chapter breakdown of word counts, including how many words in each chapter are tagged with which status
--act— output act-by-act breakdown of word counts (total only)
-pp— run markdown pre-processor, this allows for a multi-file input (e.g. each chapter in its own file), but requires the MarkdownPP python library.
You'll need to format your novel in the expected format for novel-stats to work.
Title and author
# for the title and
### for author name. Example:
# Title of the Novel ### Author Name
These lines are generally ignored, although they do show up in the total word count.
novel-stats expects chapters to start with
## and to have a numeric title
(no "Chapter", etc.). Example:
## 1 Once upon a time ...
Chapter "status" is an optional feature that lets you indicate certain chapters as "drafted", "dev edited", etc. and then get word count totals for each status. This is useful for tracking the progress of your novel chapter-by-chapter as you write or revise.
## 3 [status]: # (drafted)
Other Markdown processing tools should ignore these "comments", so they shouldn't show up in the processed contents of your novel. If you do use this feature, you should set the status at the top of each chapter, before the actual chapter contents.
There are no set values for the chapter status. Use the statuses that make sense for your writing workflow.
Acts are an optional feature that let you indicate certain chapters as part of a particular act number and then get word count totals for each act. This is useful for keeping an eye on how big your acts are in relation to one another.
## 8 [act]: # (2)
You only need to set the act for the first chapter in the act. Subsequent chapters are assumed to be in the same act unless otherwise indicated.
If you do use this feature, you should set the status at the top of each chapter, before the actual chapter contents (and after any chapter status).
Comments, such as outlining notes for yourself, can be added anywhere using:
[//]: # This text is completely ignored.
These words will not count towards the word count
Splitting your novel into multiple files is supported using the
python library. To include a secondary file inside the main one, simply use
and add the
-pp flag to novel-stats.
novel-stats includes two examples:
- Markdown file
example.mdthat illustrates the expected Markdown format for a single file. Try it out:
$ novel-stats example.md
- A 6 file example in the
examplefolder with the main file
multi_file.mdpp. You can try this one out with
$ cd example $ novel-stats multi_file.mdpp -pp
novel-stats is licensed under the GNU General Public License version 3 or any later version.
To get set up to hack on novel-stats, first clone master via HTTPS or SSH:
git clone https://projects.torsion.org/witten/novel-stats.git
git clone ssh://email@example.com:3022/witten/novel-stats.git
Then, install novel-stats "editable" so that you can run novel-stats commands while you're hacking on them to make sure your changes work.
cd novel-stats/ pip3 install --editable --user .
Note that this will typically install the novel-stats commands into
~/.local/bin, which may or may not be on your PATH. There are other ways to
install novel-stats editable as well, for instance into the system Python
install (so without
--user, as root), or even into a
virtualenv. How or where you install
novel-stats is up to you, but generally an editable install makes development
and testing easier.
Assuming you've cloned the novel-stats source code as described above, and
you're in the
novel-stats/ working copy, install tox, which is used for
setting up testing environments:
pip3 install --user tox
Finally, to actually run tests, run:
cd novel-stats tox
novel-stats code uses the Black code formatter, the Flake8 code checker, and the isort import orderer, so certain code style requirements will be enforced when running automated tests. See the Black, Flake8, and isort documentation for more information.
If when running tests, you get an error from the Black code formatter about files that would be reformatted, you can ask Black to format them for you via the following:
tox -e black
And if you get a complaint from the isort Python import orderer, you can ask isort to order your imports for you:
tox -e isort
Each pull request triggers a continuous integration build which runs the test suite. You can view these builds on build.torsion.org, and they're also linked from the commits list on each pull request.