6 |
7 |
24 |
25 | {% endblock %}
26 |
27 | {% block javascripts %}
28 | {{ block.super }}
29 | {% endblock %}
30 |
--------------------------------------------------------------------------------
/coffer/apps.py:
--------------------------------------------------------------------------------
1 | # coffer.apps
2 | # Describes the Coffer application to Django
3 | #
4 | # Author: Benjamin Bengfort
8 |
9 |
23 |
10 |
21 |
22 | Visual Analytics of Multidimensional Data
11 |Upload CSV data to explore visual diagnostics and patterns
12 |13 | 14 | Upload a Dataset 15 | 16 | 17 | Find a Dataset 18 | 19 |
20 |
9 | 
10 |
11 |
10 |
12 |
19 | {% endblock %}
20 |
21 |
22 | {% block login-footer %}
23 |
13 |
18 | Password Email Sent
14 |We've emailed you instructions for setting your password. 15 | You should be receiving them shortly. 16 | If you don't receive an email, please make sure you've entered the address you registered with, and check your spam folder.
17 |
24 |
31 | {% endblock %}
32 |
--------------------------------------------------------------------------------
/trinket/templates/components/footer.html:
--------------------------------------------------------------------------------
1 |
30 |
--------------------------------------------------------------------------------
/trinket/settings/development.py:
--------------------------------------------------------------------------------
1 | # trinket.settings.development
2 | # The Django settings for Trinket in development
3 | #
4 | # Author: Benjamin Bengfort
25 |
30 |
26 | Need an Account?
27 |
28 |
29 |
40 |
47 | {% endblock %}
48 |
--------------------------------------------------------------------------------
/trinket/views.py:
--------------------------------------------------------------------------------
1 | # trinket.views
2 | # Default application views for the system.
3 | #
4 | # Author: Benjamin Bengfort
41 |
46 |
42 | Need an Account?
43 |
44 |
45 | 
35 | {% if user.first_name %}{{ user.first_name }} {{ user.last_name }}{% else %}{{ user.username }}{% endif %}
36 |
37 |
59 |
50 |
57 | {% endblock %}
58 |
--------------------------------------------------------------------------------
/trinket/urls.py:
--------------------------------------------------------------------------------
1 | # trinket.urls
2 | # Application url definition and routers.
3 | #
4 | # Author: Benjamin Bengfort
51 |
56 |
52 | Need an Account?
53 |
54 |
55 |
49 |
62 | {% endblock %}
63 |
64 | {% block footer %}
65 |
83 |
84 | {% endblock %}
85 |
--------------------------------------------------------------------------------
/trinket/templates/coffer/dataset_list.html:
--------------------------------------------------------------------------------
1 | {% extends 'page.html' %}
2 | {% load humanize %}
3 | {% load gravatar %}
4 |
5 | {% block content %}
6 |
7 |
8 |
50 |
56 |
51 |
55 |
52 | {% block legal-header %}{% endblock %}
53 |
54 |
57 |
61 |
58 | {% block legal-content %}{% endblock %}
59 |
60 |
9 |
10 |
60 |
61 |
62 |
63 | {% endblock %}
64 |
65 | {% block javascripts %}
66 | {{ block.super }}
67 |
76 | {% endblock %}
77 |
--------------------------------------------------------------------------------
/trinket/assets/js/utils.js:
--------------------------------------------------------------------------------
1 | /*
2 | * utils.js
3 | * Helper functions for global use in Trinket front-end apps
4 | *
5 | * Author: Benjamin Bengfort
11 |
21 |
22 |
12 |
20 |
13 |
19 | Recently Uploaded Datasets
14 |15 | {{ num_datasets|intcomma }} datasets · latest on {{ latest_dataset|date }} 16 |
17 | 18 |
23 |
59 |
24 |
25 |
26 |
53 |
54 | {% if is_paginated %}
55 | {% include 'components/pagination.html' %}
56 | {% endif %}
57 |
58 | | Name | 27 |Type | 28 |Dimensions | 29 |Length | 30 |User | 31 |Uploaded | 32 | 33 | 34 | {% for dataset in dataset_list %} 35 |
|---|---|---|---|---|---|
| {{ dataset.title }} | 37 |{{ dataset.datatype|upper }} data | 38 |{{ dataset.dimensions|intcomma }} columns | 39 |{{ dataset.length|intcomma }} rows | 40 |
41 | 
42 | {{ dataset.uploader }}
43 | |
44 | {{ dataset.created|date }} | 45 |
| No Recently Uploaded Datasets | 49 ||||||
4 |
5 |
6 |
17 |
18 |
76 |
77 |
--------------------------------------------------------------------------------
/coffer/views.py:
--------------------------------------------------------------------------------
1 | # coffer.views
2 | # Views and interaction logic for the coffer app.
3 | #
4 | # Author: Benjamin Bengfort
19 |
20 |
21 |
31 |
32 |
33 |
75 | -
34 | {% if user.is_authenticated %}
35 |
-
36 |
37 |
38 |
64 | {% else %}
65 |
- 66 | 67 | 68 | Log In 69 | 70 | 71 | {% endif %} 72 | 73 |
7 |
8 |
105 |
106 | {% endblock %}
107 |
108 | {% block javascripts %}
109 | {{ block.super }}
110 | {% endblock %}
111 |
--------------------------------------------------------------------------------
/docs/about.md:
--------------------------------------------------------------------------------
1 | # About Cultivar
2 |
3 | Cultivar is a dataset management, analysis and visualization tool that is being built as part of the DDL Multidimensional Visualization Research Lab. See: [Parallel Coordinates](http://homes.cs.washington.edu/~jheer//files/zoo/ex/stats/parallel.html) for more on the types of visualizations we're experimenting with.
4 |
5 | ## Contributing
6 |
7 | Cultivar is open source, but because this is an District Data Labs project, we would appreciate it if you would let us know how you intend to use the software (other than simply copying and pasting code so that you can use it in your own projects). If you would like to contribute (especially if you are a student or research labs member at District Data Labs), you can do so in the following ways:
8 |
9 | 1. Add issues or bugs to the bug tracker: [https://github.com/DistrictDataLabs/Cultivar/issues](https://github.com/DistrictDataLabs/Cultivar/issues)
10 | 2. Work on a card on the dev board: [https://waffle.io/DistrictDataLabs/Cultivar](https://waffle.io/DistrictDataLabs/Cultivar)
11 | 3. Create a pull request in Github: [https://github.com/DistrictDataLabs/Cultivar/pulls](https://github.com/DistrictDataLabs/Cultivar/pulls)
12 |
13 | Note that labels in the Github issues are defined in the blog post: [How we use labels on GitHub Issues at Mediocre Laboratories](https://mediocre.com/forum/topics/how-we-use-labels-on-github-issues-at-mediocre-laboratories).
14 |
15 | If you are a member of the District Data Labs Faculty group, you have direct access to the repository, which is set up in a typical production/release/development cycle as described in _[A Successful Git Branching Model](http://nvie.com/posts/a-successful-git-branching-model/)_. A typical workflow is as follows:
16 |
17 | 1. Select a card from the [dev board](https://waffle.io/DistrictDataLabs/Cultivar) - preferably one that is "ready" then move it to "in-progress".
18 |
19 | 2. Create a branch off of develop called "feature-[feature name]", work and commit into that branch.
20 |
21 | ~$ git checkout -b feature-myfeature develop
22 |
23 | 3. Once you are done working (and everything is tested) merge your feature into develop.
24 |
25 | ~$ git checkout develop
26 | ~$ git merge --no-ff feature-myfeature
27 | ~$ git branch -d feature-myfeature
28 | ~$ git push origin develop
29 |
30 | 4. Repeat. Releases will be routinely pushed into master via release branches, then deployed to the server.
31 |
32 | ## Contributors
33 |
34 | Thank you for all your help contributing to make Cultivar a great project!
35 |
36 | ### Maintainers
37 |
38 | - Benjamin Bengfort: [@bbengfort](https://github.com/bbengfort/)
39 | - Rebecca Bilbro: [@rebeccabilbro](https://github.com/rebeccabilbro)
40 |
41 | ### Contributors
42 |
43 | - Tony Ojeda: [@ojedatony1616](https://github.com/ojedatony1616)
44 |
45 | ## Changelog
46 |
47 | The release versions that are sent to the Python package index (PyPI) are also tagged in Github. You can see the tags through the Github web application and download the tarball of the version you'd like. Additionally PyPI will host the various releases of Cultivar (eventually).
48 |
49 | The versioning uses a three part version system, "a.b.c" - "a" represents a major release that may not be backwards compatible. "b" is incremented on minor releases that may contain extra features, but are backwards compatible. "c" releases are bug fixes or other micro changes that developers should feel free to immediately update to.
50 |
51 | ### Version 0.2
52 |
53 | * **tag**: [v0.2](https://github.com/DistrictDataLabs/Cultivar/releases/tag/v0.2)
54 | * **deployment**: Wednesday, January 27, 2016
55 | * **commit**: (see tag)
56 |
57 | This minor update gave a bit more functionality to the MVP prototype, even though the version was intended to have a much more impactful feature set. However after some study, the workflow is changing, and so this development branch is being pruned and deployed in preparation for the next batch. The major achievement of this version is the documentation that discusses our approach, as well as the dataset search and listing page that is now available.
58 |
59 | ### Version 0.1
60 |
61 | * **tag**: [v0.1](https://github.com/DistrictDataLabs/Cultivar/releases/tag/v0.1)
62 | * **deployment**: Tuesday, October 13, 2015
63 | * **commit**: [c863e42](https://github.com/DistrictDataLabs/Cultivar/commit/c863e421292be4eaeab36a9233f6ed7e0068679b)
64 |
65 | MVP prototype type of a dataset uploader and management application. This application framework will become the basis for the research project in the DDL Multidimensional Visualization Research Labs. For now users can upload datasets, and manage their description, as well as preview the first 20 rows.
66 |
--------------------------------------------------------------------------------
/trinket/templates/site/upload.html:
--------------------------------------------------------------------------------
1 | {% extends 'page.html' %}
2 | {% load staticfiles %}
3 | {% load humanize %}
4 |
5 | {% block stylesheets %}
6 | {{ block.super }}
7 |
8 | {% endblock %}
9 |
10 | {% block content %}
11 |
12 |
9 |
30 |
31 |
10 |
29 |
11 |
28 | 12 | {% if object.title %} 13 | {{ object.title }} 14 | {% else %} 15 | {{ object.filename }} 16 | {% endif %} 17 |
18 | 26 | 27 |
32 |
81 |
82 |
83 |
33 |
63 |
34 |
38 |
39 |
61 |
62 |
35 |
37 | Dataset Details
36 || Dimensions | 41 |{{ object.dimensions|intcomma }} Column{{ object.dimensions|pluralize }} | 42 |
| Length | 45 |{{ object.length|intcomma }} Row{{ object.length|pluralize }} | 46 |
| File Size | 49 |{{ object.filesize|filesizeformat }} | 50 |
| Uploaded By | 53 |{{ dataset.uploader }} | 54 |
| Uploaded On | 57 |{{ dataset.created|date }} | 58 |
64 |
80 |
65 |
79 |
66 |
68 | Dataset Description
67 |
69 | {% if object.description.rendered %}
70 | {{ object.description.rendered|safe }}
71 | {% else %}
72 |
75 |
78 | No description provided
73 | {% endif %} 74 |
84 |
104 |
85 | Dataset Preview
86 |
87 |
88 | {% for header in object.headers %}
89 |
102 |
103 | Dataset Preview head -n 20 dataset
86 | | {{header }} | 90 | {% endfor %} 91 | 92 | 93 | {% for row in object.preview %} 94 |
|---|
| {{ item }} | 97 | {% endfor %} 98 |
13 |
14 |
93 |
94 | {% endblock %}
95 |
96 | {% block javascripts %}
97 | {{ block.super }}
98 |
134 | {% endblock %}
135 |
--------------------------------------------------------------------------------
/README.md:
--------------------------------------------------------------------------------
1 | # Trinket
2 | **Multidimensional data explorer and visualization tool.**
3 |
4 | [![Build Status][travis_img]][travis_href]
5 | [![Coverage Status][coveralls_img]][coverals_href]
6 | [![Documentation Status][rtfd_img]][rtfd_href]
7 | [![Stories in Ready][waffle_img]][waffle_href]
8 |
9 | [][wall.jpg]
10 |
11 | ## About
12 |
13 | This is a dataset management and visualization tool that is being built as part of the DDL Multidimensional Visualization Research Lab. See: [Parallel Coordinates](http://homes.cs.washington.edu/~jheer//files/zoo/ex/stats/parallel.html) for more on the types of visualizations we're experimenting with.
14 |
15 | For more information, please enjoy the documentation found at [trinket.readthedocs.org](http://trinket.readthedocs.org/).
16 |
17 | ### Contributing
18 |
19 | Trinket is open source, but because this is an District Data Labs project, we would appreciate it if you would let us know how you intend to use the software (other than simply copying and pasting code so that you can use it in your own projects). If you would like to contribute (especially if you are a student or research labs member at District Data Labs), you can do so in the following ways:
20 |
21 | 1. Add issues or bugs to the bug tracker: [https://github.com/DistrictDataLabs/trinket/issues](https://github.com/DistrictDataLabs/trinket/issues)
22 | 2. Work on a card on the dev board: [https://waffle.io/DistrictDataLabs/trinket](https://waffle.io/DistrictDataLabs/trinket)
23 | 3. Create a pull request in Github: [https://github.com/DistrictDataLabs/trinket/pulls](https://github.com/DistrictDataLabs/trinket/pulls)
24 |
25 | Note that labels in the Github issues are defined in the blog post: [How we use labels on GitHub Issues at Mediocre Laboratories](https://mediocre.com/forum/topics/how-we-use-labels-on-github-issues-at-mediocre-laboratories).
26 |
27 | If you are a member of the District Data Labs Faculty group, you have direct access to the repository, which is set up in a typical production/release/development cycle as described in _[A Successful Git Branching Model](http://nvie.com/posts/a-successful-git-branching-model/)_. A typical workflow is as follows:
28 |
29 | 1. Select a card from the [dev board](https://waffle.io/DistrictDataLabs/trinket) - preferably one that is "ready" then move it to "in-progress".
30 |
31 | 2. Create a branch off of develop called "feature-[feature name]", work and commit into that branch.
32 |
33 | ~$ git checkout -b feature-myfeature develop
34 |
35 | 3. Once you are done working (and everything is tested) merge your feature into develop.
36 |
37 | ~$ git checkout develop
38 | ~$ git merge --no-ff feature-myfeature
39 | ~$ git branch -d feature-myfeature
40 | ~$ git push origin develop
41 |
42 | 4. Repeat. Releases will be routinely pushed into master via release branches, then deployed to the server.
43 |
44 | ### Throughput
45 |
46 | [](https://waffle.io/DistrictDataLabs/trinket/metrics)
47 |
48 | ### Attribution
49 |
50 | The image used in this README, ["window#1"][wall.jpg] by [Namelas Frade](https://www.flickr.com/photos/zingh/) is licensed under [CC BY-NC-ND 2.0](https://creativecommons.org/licenses/by-nc-nd/2.0/)
51 |
52 | ## Changelog
53 |
54 | The release versions that are sent to the Python package index (PyPI) are also tagged in Github. You can see the tags through the Github web application and download the tarball of the version you'd like. Additionally PyPI will host the various releases of Trinket (eventually).
55 |
56 | The versioning uses a three part version system, "a.b.c" - "a" represents a major release that may not be backwards compatible. "b" is incremented on minor releases that may contain extra features, but are backwards compatible. "c" releases are bug fixes or other micro changes that developers should feel free to immediately update to.
57 |
58 | ### Version 0.2
59 |
60 | * **tag**: [v0.2](https://github.com/DistrictDataLabs/trinket/releases/tag/v0.2)
61 | * **deployment**: Wednesday, January 27, 2016
62 | * **commit**: (see tag)
63 |
64 | This minor update gave a bit more functionality to the MVP prototype, even though the version was intended to have a much more impactful feature set. However after some study, the workflow is changing, and so this development branch is being pruned and deployed in preparation for the next batch. The major achievement of this version is the documentation that discusses our approach, as well as the dataset search and listing page that is now available.
65 |
66 | ### Version 0.1
67 |
68 | * **tag**: [v0.1](https://github.com/DistrictDataLabs/trinket/releases/tag/v0.1)
69 | * **deployment**: Tuesday, October 13, 2015
70 | * **commit**: [c863e42](https://github.com/DistrictDataLabs/trinket/commit/c863e421292be4eaeab36a9233f6ed7e0068679b)
71 |
72 | MVP prototype type of a dataset uploader and management application. This application framework will become the basis for the research project in the DDL Multidimensional Visualization Research Labs. For now users can upload datasets, and manage their description, as well as preview the first 20 rows.
73 |
74 |
75 | [travis_img]: https://travis-ci.org/DistrictDataLabs/trinket.svg?branch=master
76 | [travis_href]: https://travis-ci.org/DistrictDataLabs/trinket
77 | [coveralls_img]: https://coveralls.io/repos/DistrictDataLabs/trinket/badge.svg?branch=master&service=github
78 | [coverals_href]: https://coveralls.io/github/DistrictDataLabs/trinket?branch=master
79 | [waffle_img]: https://badge.waffle.io/DistrictDataLabs/trinket.png?label=ready&title=Ready
80 | [waffle_href]: https://waffle.io/DistrictDataLabs/trinket
81 | [rtfd_img]: https://readthedocs.org/projects/trinket/badge/?version=latest
82 | [rtfd_href]: http://trinket.readthedocs.org/en/latest/?badge=latest
83 | [wall.jpg]: https://flic.kr/p/75C2ac
84 |
--------------------------------------------------------------------------------
/docs/auto_analysis.md:
--------------------------------------------------------------------------------
1 | # Automated Analysis
2 |
3 | ## Overview
4 |
5 | Cultivar is designed to mirror what experienced data scientists do when they take their first few passes through a new dataset by intelligently automating large portions of the wrangling and analysis/exploration phases of the data science pipeline, integrating them into the initial ingestion or uploading phase.
6 |
7 | ## Architecture
8 |
9 | The auto-analysis and text parsing features of Cultivar are written in Python. They work by scanning columns of uploaded data and using `numpy`, `unicodecsv`, one-dimensional kernel density estimates, standard analyses of variance mechanisms and hypothesis testing (KDEs, ANOVAs).
10 |
11 | 
12 |
13 | This enables Cultivar to do type identification, e.g. to identify and differentiate: discrete integers, floats, text data, normal distributions, classes, outliers, and errors. To perform this analysis quickly and accurately during the data ingestion process, Cultivar includes a rules-based system trained from previously annotated data sets and coupled with heuristic rules determined in discussions with a range of experienced data scientists.
14 |
15 | ## Mechanics
16 |
17 | Auto-analysis works by assigning each column/feature a data type (`dtype` in the parlance of NumPy and Pandas), e.g. categorical, numeric, real, integer, etc. These types must be automatically inferred from the dataset.
18 |
19 | The auto-analysis method takes as input a file-like object and generic keyword arguments and returns as output a tuple/list whose length is the (maximum) number of columns in the dataset, and whose values contain the datatype of each column, ordered by column index.
20 |
21 |
22 | _Questions to answer:_
23 |
24 | - How do other libraries like `pandas` and `messytables` do this?
25 | Pandas computes [histograms](https://github.com/pydata/pandas/blob/master/pandas/core/algorithms.py#L250), looks for the [min](https://github.com/pydata/pandas/blob/master/pandas/core/algorithms.py#L537) and [max](https://github.com/pydata/pandas/blob/master/pandas/core/algorithms.py#L556) values of a column, samples [quantiles](https://github.com/pydata/pandas/blob/master/pandas/core/algorithms.py#L410), and counts [unique values](https://github.com/pydata/pandas/blob/master/pandas/core/algorithms.py#L55).
26 |
27 | - Do you have to go through the whole dataset to make a decision?
28 | Yes and no - decide based on how big the dataset is. The below strategy builds a sample from 50 non-empty rows for each column, as well as the rows with the longest and shortest lengths. For larger datasets, maybe sample 10%. For extremely large datasets, 1% might be enough.
29 |
30 | - Can we use a sampling approach to reading the data?
31 | Naive method (assumes straightforward densities):
32 |
33 | ```python
34 | for each col in fileTypeObject:
35 | find mx # row with the longest value
36 | find mn # row with the shortest value
37 | find nonNaN # first 50 non-empty rows using ndarray.nonzero()
38 | sampleArray = nd.array(mn, mx, nonNaN)
39 | ```
40 |
41 | - Is there a certain density of data required to make a decision?
42 | This is a good question - some libraries build histograms for each column to examine densities. See the [`pandas` method for histograms](https://github.com/pydata/pandas/blob/master/pandas/core/algorithms.py#L250).
43 | TODO: look into thresholds
44 |
45 | - What types are we looking for?
46 | __string__, __datetime__, __float__, __integer__, __boolean__
47 | See also [`messytables` types](https://github.com/okfn/messytables/blob/master/messytables/types.py).
48 |
49 | Attempt parsing from broadest type to narrowest:
50 |
51 | ```python
52 | for val in colSample:
53 | if val.dtype.type is np.string_:
54 | colType = colType.astype('Sn') # where n is the max length value in col
55 | elif val.dtype.type is np.datetime64:
56 | colType = colType.astype('datetime64') # this is new & experimental in NumPy 1.7.0
57 | elif val.dtype.type is np.float_:
58 | colType = colType.astype('float64')
59 | elif val.dtype.type is np.int_:
60 | colType = colType.astype('int64')
61 | elif val.dtype.type is np.bool_:
62 | colType = colType.astype('bool')
63 | else:
64 | # do something else
65 | # what about unicode and complex types?
66 | ```
67 |
68 | - What does column-major mean for Cultivar?
69 | Use [`transpose`](http://docs.scipy.org/doc/numpy-1.10.1/reference/generated/numpy.ndarray.T.html) and/or [`reshape`](http://docs.scipy.org/doc/numpy-1.10.1/reference/generated/numpy.reshape.html) from `numpy`.
70 |
71 | - Can we automatically detect delimiters and quote characters? (e.g. ; vs ,)
72 | See `messytables` [method for delimiter detection](https://github.com/okfn/messytables/blob/master/messytables/commas.py).
73 |
74 | - How do we detect if there is a header row or not?
75 | See `messytables` [method for header detection](https://github.com/okfn/messytables/blob/7e4f12abef257a4d70a8020e0d024df6fbb02976/messytables/headers.py).
76 |
77 | - How lightweight/heavyweight must this be?
78 | Look into making more lightweight using regular expressions & hard-coded rules (see [Brill tagging](https://en.wikipedia.org/wiki/Brill_tagger)).
79 |
80 | ## Sources
81 |
82 | [Datatypes in Python - 2.7](https://docs.python.org/2/library/datatypes.html)
83 |
84 | [Datatypes in Python - 3.5](https://docs.python.org/3.5/library/datatypes.html)
85 |
86 | [Numpy - dtypes](http://docs.scipy.org/doc/numpy/reference/arrays.dtypes.html)
87 |
88 | [UnicodeCSV](https://github.com/jdunck/python-unicodecsv/blob/master/README.rst)
89 |
90 | [Pandas](http://pandas.pydata.org/)
91 |
92 | [MessyTables](https://messytables.readthedocs.org/en/latest/)
93 |
94 | [Dataproxy](https://github.com/okfn/dataproxy)
95 |
96 | [Algorithms for Type Guessing - Stackoverflow](http://stackoverflow.com/questions/6824862/data-type-recognition-guessing-of-csv-data-in-python)
97 |
98 | [Python Libraries for Type Guessing - Stackoverflow](http://stackoverflow.com/questions/3098337/method-for-guessing-type-of-data-represented-currently-represented-as-strings-in)
99 |
--------------------------------------------------------------------------------
/trinket/templates/site/legal/privacy.html:
--------------------------------------------------------------------------------
1 | {% extends 'site/legal/legal-page.html' %}
2 |
3 | {% block legal-header %}
4 |
15 |
16 |
92 |
17 | {% if form.errors %}
18 | {% for errors in form.errors.values %}
19 | {% for error in errors %}
20 |
28 |
29 |
30 |
21 |
22 | Whoops! {{ error }}
23 |
24 | {% endfor %}
25 | {% endfor %}
26 | {% endif %}
27 |
31 |
90 |
91 |
32 |
34 | Upload Datasets
33 |
35 |
59 |
60 |
61 |
68 |
69 |
70 |
89 |
71 |
86 |
87 |
88 | Recent Uploads
72 |
73 | {% for dataset in upload_history %}
74 |
75 | uploaded {{ dataset.created|date }} by {{ dataset.uploader }}
76 | {{ dataset.filename }}
77 | ·
78 | {{ dataset.datatype }} data with
79 | {{ dataset.dimensions|intcomma }} dimension{{ dataset.dimensions|pluralize }} by {{ dataset.length|intcomma }} rows
80 |
81 | {% empty %}
82 | No Recently Uploaded Datasets
83 | {% endfor %}
84 |
85 | Privacy Policy
5 |Last Updated: August 21, 2015
6 | {% endblock %} 7 | 8 | {% block legal-content %} 9 |Your privacy is very important to us. Accordingly, we have developed this Policy in order for you to understand how we collect, use, communicate and disclose and make use of personal information. The following outlines our privacy policy.
10 | 11 |-
12 |
- Before or at the time of collecting personal information, we will identify the purposes for which information is being collected. 13 |
- We will collect and use of personal information solely with the objective of fulfilling those purposes specified by us and for other compatible purposes, unless we obtain the consent of the individual concerned or as required by law. 14 |
- We will only retain personal information as long as necessary for the fulfillment of those purposes. 15 |
- We will collect personal information by lawful and fair means and, where appropriate, with the knowledge or consent of the individual concerned. 16 |
- Personal data should be relevant to the purposes for which it is to be used, and, to the extent necessary for those purposes, should be accurate, complete, and up-to-date. 17 |
- We will protect personal information by reasonable security safeguards against loss or theft, as well as unauthorized access, disclosure, copying, use or modification. 18 |
- We will make readily available to customers information about our policies and practices relating to the management of personal information. 19 |
We are committed to conducting our business in accordance with these principles in order to ensure that the confidentiality of personal information is protected and maintained.
23 | 24 |Information Collection and Use
25 | 26 |Our primary goal in collecting information is to provide and improve our Site, App, and Services. We would like to deliver a user-customized experience on our site, allowing users to administer their Membership and enable users to enjoy and easily navigate the Site or App.
27 | 28 |Personally Identifiable Information
29 | 30 |When you register or create an account with us through the Site, or as a user of a Service provided by us, or through any Mobile App, we will ask you for personally identifiable information and you will become a member ("Member") of the site. This information refers to information that can be used to contact or identify you ("Personal Information"). Personal Information includes, but is not limited to, your name, phone number, email address, and home and business postal addresses. We use this information only to provide Services and administer your inquiries.
31 | 32 |We may also collect other information as part of the registration for use in administration and personalization of your account. This information is "Non-Identifying Information" like your role in education. We use your Personal Information and, in some cases, your Non-Identifying Information to provide you a Service, complete your transactions, and administer your inquiries.
33 | 34 |We will also use your Personal Information to contact you with newsletters, marketing, or promotional materials, and other information that may be of interest to you. If you decide at any time that you no longer with to receive such communications from us, please follow the unsubscribe instructions provided in any communications update.
35 | 36 |Changing or Deleting your Information
37 | 38 |All Members may review, update, correct, or delete any Personal Information in their user profile under the "My Account" section of the Site or by contacting us. If you completely delete all such information, then your account may become deactivated. You can also request the deletion of your account, which will anonymize all Personal Information and restrict the username associated with the Member from being used again.
39 | 40 |International Transfer
41 | 42 |Your information may be transferred to, and maintained on, computers located outside of your state, province, country or other governmental jurisdiction where the privacy laws may not be as protective as those in your jurisdiction. If you are located outside the United States and choose to provide information to us, our website transfers Personal Information to the United States and processes it there. Your consent to these Terms of Use, followed by your submission of such information represents your agreement to that transfer.
43 | 44 |Our Policy Toward Children
45 | 46 |This Site is not directed to children under 18. We do not knowingly collect personally identifiable information from children under 13. If a parent or guardian becomes aware that his or her child has provided us Personal Information without their consent, he or she should contact us at admin@districtdatalabs.com. If we become aware that a child under 13 has provided us with Personal Information, we will delete such information from our databases.
47 | 48 |Modification
49 | 50 |It is our policy to post any changes we make to our Privacy Policy on this page. If we make material changes to how we treat our users' personal information, we will notify you by e-mail to the e-mail address specified in your account. The date this Privacy Policy was last revised is identified at the top of the page. You are responsible for ensuring we have an up-to-date active and deliverable e-mail address for you, and for periodically visiting our Website and this Privacy Policy to check for any changes.
51 | {% endblock %} 52 | -------------------------------------------------------------------------------- /trinket/templates/registration/login.html: -------------------------------------------------------------------------------- 1 | {% extends "page.html" %} 2 | {% load staticfiles %} 3 | 4 | {% block content %} 5 | 6 |
7 |
135 |
136 |
137 |
138 |
160 |
161 | {% endblock %}
162 |
--------------------------------------------------------------------------------
/trinket/settings/base.py:
--------------------------------------------------------------------------------
1 | # trinket.settings.base
2 | # The common Django settings for Trinket project
3 | #
4 | # Author: Benjamin Bengfort
8 |
134 |
9 |
10 | {% block login-panel %}
11 |
133 |
12 |
13 |
130 | {% endblock %}
131 |
132 |
14 | {% block login-heading %}
15 |
18 |
19 | {% block login-title %}Enter Access Controlled Area{% endblock %}
16 | {% endblock %} 17 |
20 | {% block login-body %}
21 |
22 | {% block login-alert %}
23 | {% if form.errors %}
24 |
112 |
113 |
128 |
129 |
25 |
26 | Whoops! Credentials invalid. Please try again.
27 |
28 | {% endif %}
29 |
30 | {% if messages %}
31 | {% for message in messages %}
32 | {% if message.level == DEFAULT_MESSAGE_LEVELS.ERROR %}
33 |
34 |
35 | Unauthorized! {{ message }}
36 |
37 | {% endif %}
38 | {% endfor %}
39 | {% endif %}
40 |
41 | {% if next %}
42 | {% if user.is_authenticated %}
43 |
44 |
45 | Warning! Your account does not have access to this page.
46 |
47 | {% else %}
48 |
49 |
50 | Warning! You must login to access DDL Trinket.
51 |
52 | {% endif %}
53 | {% endif %}
54 | {% endblock %}
55 |
56 | {% block login-form %}
57 |
108 | {% endblock %}
109 |
110 | {% endblock %}
111 | Terms and Conditions of Use
5 |Last Updated: August 21, 2015
6 | {% endblock %} 7 | 8 | {% block legal-content %} 9 |Use of Site
12 | 13 |By accessing this website or any website owned by District Data Labs, you are agreeing to be bound to all of the terms, conditions, and notices contained or referenced in this Terms and Conditions of Use and all applicable laws and regulations. You also agree that you are responsible for compliance with any applicable local laws. If you do not agree to these terms, you are prohibited from using or accessing this site or any other site owned by District Data Labs. District Data Labs reserves the right to update or revise these Terms of Use. Your continued use of this Site following the posting of any changes to the Terms of Use constitutes acceptance of those changes.
14 | 15 |Permission is granted to temporarily download one copy of the materials on District Data Labs's Websites for viewing only. This is a grant of a license, not a transfer of a title. Under this licenses you may not:
16 | 17 |-
18 |
- Modify or copy the materials 19 |
- Use the materials for any commercial purpose, or any public display (commercial or non-commercial) 20 |
- Attempt to decompile or reverse engineer any software contained or provided through District Data Labs's Website 21 |
- Remove any copyright or proprietary notations from the material 22 |
- Transfer the materials to another person or "mirror" any materials on any other server including data accessed through our APIS 23 |
District Data Labs has the right to terminate this license if you violate any of these restrictions, and upon termination you are no longer allowed to view these materials and must destroy any downloaded content in either print or electronic format.
27 |Modification
32 | 33 |It is our policy to post any changes we make to our terms of use on this page. If we make material changes to how we treat our users' personal information, we will notify you by e-mail to the e-mail address specified in your account. The date these Terms of Use was last revised is identified at the top of the page. You are responsible for ensuring we have an up-to-date active and deliverable e-mail address for you, and for periodically visiting our Website and this terms of use to check for any changes. 34 |
Copyright
39 | 40 |The entire content of this Site is protected by copyright. You may not copy, distribute, or create derivative works from any part of this website (including its graphics, pictorial matter, and text) without the prior written consent of District Data Labs unless otherwise expressly permitted by the Sites.
41 |Trademarks
47 | 48 |District Data Labs owns names, logos, designs, titles, words, or phrases within this Site are trademarks, service marks, or trade names of District Data Labs or its affiliated companies and may not be used without prior written permission. District Data Labs claims no interest in marks owned by entities not affiliated with District Data Labs which may appear on this Site.
49 |Contributed Content
54 | 55 |Users posting content to the Site and District Data Labs's Social Media pages linked within are solely responsible for all content and any infringement, defamation, or other claims resulting from or related thereto. District Data Labs reserves the right to remove or refuse to post any content that is offensive, indecent, or otherwise objectionable, and makes no guarantee of the accuracy, integrity, or quality of posted content.
56 | 57 |Account Registration
60 | 61 |In order to access certain features of this Site and Services and to post any Content on the Site or through the Services, you must register to create an account ("Account") through the Site, or through a Service provided by us for use with our Site.
62 | 63 |During the registration process, you will be required to provide certain information and you will establish a username and password. You agree to provide accurate, current, and complete information as required during the registration process. You also agree to ensure, by updating, the information remains accurate, current, and complete. District Data Labs reserves the right to suspend or terminate your Account if information provided during the registration process or thereafter proves to be inaccurate, not current, or incomplete.
64 | 65 |You are responsible for safeguarding your password. You agree not to disclose your password to any third party and take sole responsibility for any activities or actions under your Account, whether or not your have authorized such activities or actions. If you think your account has been accessed in any unauthorized way, you will notify District Data Labs immediately.
66 | 67 |Termination and Account Cancellation
68 | 69 |District Data Labs will have the right to suspend or disable your Account if you breach any of these Terms of Service, at our sole discretion and without any prior notice to you. District Data Labs reserves the right to revoke your access to and use of this Site, Services, and Content at any time, with or without cause.
70 | 71 |You may also cancel your Account at any time by sending an email to admin@districtdatalabs.com or by using the "delete account" option under the "My Account" section of the website. When your account is canceled, we set all personal information except your username to "Anonymous" and remove the ability to login with that username and any password. The username will be considered unavailable, and no one will be able to create or use an account with the username of the cancelled account.
72 |Privacy
77 | 78 |See District Data Labs's Privacy Policy for information and notices concerning collection and use of your personal information.
79 | 80 |81 | 82 |
District Data Labs Mailing List
83 | 84 |Should you submit your contact information through the "Sign Up" link, you agree to receive periodic emails and possible postal mail relating to news and updates regarding District Data Labs efforts and the efforts of like-minded organizations. You may discontinue receipt of such emails and postal mail through the “unsubscribe” provisions included in the promotional emails.
85 |No Endorsements
90 | 91 |Any links on this Site to third party websites are not an endorsement, sponsorship, or recommendation of the third parties or the third parties' ideas, products, or services. Similarly, any references in this Site to third parties and their products or services do not constitute an endorsement, sponsorship, or recommendation. If you follow links to third party websites, or any other companies or organizations affiliated or unaffiliated with District Data Labs, you are subject to the terms and conditions and privacy policies of those sites, and District Data Labs marks no warranty or representations regarding those sites. Further, District Data Labs is not responsible for the content of third party or affiliated company sites or any actions, inactions, results, or damages caused by visiting those sites.
92 |Governing Law
97 | 98 |This Site was designed for and is operated in the United States. Regardless of where the Site is viewed, you are responsible for compliance with applicable local laws.
99 | 100 |You and District Data Labs agree that the laws of the District of Columbia will apply to all matters arising from or relating to use of this Website, whether for claims in contract, tort, or otherwise, without regard to conflicts of laws principles.
101 | 102 |International Transfer
103 | 104 |Your information may be transferred to, and maintained on, computers located outside of your state, province, country or other governmental jurisdiction where the privacy laws may not be as protective as those in your jurisdiction. If you are located outside the United States and choose to provide information to us, District Data Labs transfers Personal Information to the United States and processes it there. Your consent to these Terms of Use, followed by your submission of such information represents your agreement to that transfer.
105 |Disclaimer
110 | 111 |The materials on District Data Labs's Website are provided "as is" without any kind of warranty. The material on this Website is not a warranty as to any product or service provided by District Data Labs or any affiliated or unaffiliated organization.
112 | 113 |District Data Labs is not liable for any errors, delays, inaccuracies, or omissions in this Website or any Website that are linked to or referenced by this Website. Under no circumstances shall District Data Labs be liable for any damages, including indirect, incidental, special, or consequential damages that result from the use of, or inability to use, this Website.
114 |Agrement
119 | 120 |These Terms of Use constitute the entire agreement between you and District Data Labs with respect to your use of this Site and supersede all prior or contemporaneous communications and proposals, whether oral, written, or electronic, between you and District Data Labs with respect to this Site. If any provision(s) of these Terms of Use are held invalid or unenforceable, those provisions shall be construed in a manner consistent with applicable law to reflect, as nearly as possible, the original intentions of the parties, and the remaining provisions shall remain in full force and effect.
121 |