Quilt Python API https://quiltdata.com
Project description
Convert files to live data sets on Quilt
========================================
Optional prep (your steps may vary)
-----------------------------------
#. Get a list of files you want to upload (see ``get-files-to-upload/``)
#. Download the files in the list (see ``curl-all.py``)
#. Unzip downloaded files (if needed)
.. code:: bash
cd downloads
gunzip *.gz
.. rubric:: Upload to Quilt
:name: upload-to-quilt
#. | Use ``data_set.py`` to create individual data sets (see
``python data_set.py --help``).
| You will need a Quilt username and password. Or use ``batch.py`` to
create multiple data sets.
.. code:: bash
python data_set.py
-e https://quiltdata.com
-u USERNAME
-n "ENCODE data"
-d "#A549 #histone peak data #hg19"
-f downloads/wgEncodeBroadHistoneNhaH3k36me3StdPk.broadPeak
File formats in this example
----------------------------
- `ENCDOE broadPeak format`_
Resources
---------
- `ENCODE Project`_
REST API
========
+--------------------------------+--------------------------------------+-------------------------------------------+
| Action | Endpoint | Details |
+================================+======================================+===========================================+
| New table | ``POST /tables/`` | `See below`_ |
+--------------------------------+--------------------------------------+-------------------------------------------+
| Delete table | ``DELETE /tables/TABLE_ID/`` | `See below <#delete-table>`__ |
+--------------------------------+--------------------------------------+-------------------------------------------+
| Update table meta-data | ``PATCH /tables/TABLE_ID`` | `See below <#update-table-meta-data>`__ |
+--------------------------------+--------------------------------------+-------------------------------------------+
| Add column to table | ``POST /tables/TABLE_ID/columns/`` | `See below <#add-column-to-table>`__ |
+--------------------------------+--------------------------------------+-------------------------------------------+
| Append row to table | ``POST /data/TABLE_ID/rows/`` | `See below <#append-row>`__ |
+--------------------------------+--------------------------------------+-------------------------------------------+
| Get table rows | ``GET /data/TABLE_ID/rows`` | `See below <#get-rows>`__ |
+--------------------------------+--------------------------------------+-------------------------------------------+
| Get table row | ``GET /data/TABLE_ID/rows/ROW_ID`` | `See below <#get-row>`__ |
+--------------------------------+--------------------------------------+-------------------------------------------+
| Genome intersect or subtract | ``POST /genemath/`` | `See below <#intersect-or-subtract>`__ |
+--------------------------------+--------------------------------------+-------------------------------------------+
Notes
- For all REST calls, the content-type is ``application/JSON``.
- Description fields automatically linkify URLs and support
``<a>, <i>, <em>, <strong>, <b>`` tags
Tables
------
Create table
~~~~~~~~~~~~
``POST /tables/``
Data format
^^^^^^^^^^^
.. code:: javascript
{
'name': string,
'description': text `<a>, <i>, <em>, <strong>, <b>` tags supported; automatic linkification of URLs
'columns': [
{
'name': string,
'sqlname': optional string,
'description': optional text,
'type' : one of 'String', 'Number', 'Image', 'Text'
},
...
]
}
Returns
^^^^^^^
Table data as JSON object, includes ``id`` field with the table’s
identifier.
Add column to table
~~~~~~~~~~~~~~~~~~~
``POST /tables/TABLE_ID/columns/``
Data format
^^^^^^^^^^^
.. code:: javascript
{
'name': string,
'sqlname': optional string,
'description': text,
'type': one of 'String', 'Number', 'Image', or 'Text'
}
Returns
^^^^^^^
Column data as JSON object, includes ``id`` field with the column’s
identifier.
Delete table
~~~~~~~~~~~~
``DELETE /tables/TABLE_ID``
Update table meta-data
~~~~~~~~~~~~~~~~~~~~~~
``PATCH /tables/TABLE_ID``
Data format
^^^^^^^^^^^
.. code:: javascript
{
'name': string,
'description': text
}
Table Data
----------
- Use column ``sqlname`` as keys in input data
Append row
~~~~~~~~~~
``POST /data/TABLE_ID/rows/``
Data format
^^^^^^^^^^^
.. code:: javascript
[
{columnSqlname0: value0, columnSqlname1 : value1, ... },
...
]
Get rows
~~~~~~~~
``GET /data/TABLE_ID/rows`` \* Rows are keyed by the Quilt Row ID field
``qrid`` \* NOTE: Currently limited to the first 500 rows
Returns
^^^^^^^
Row data as JSON object, keyed by column.sqlname.
Get row
~~~~~~~
``GET /data/TABLE_ID/rows/ROW_ID``
Returns
^^^^^^^
Row data as JSON object, keyed by column.sqlname.
Quilt tables
------------
Join
~~~~
``POST /quilts/`` #### Data format
.. code:: javascript
{
'left_table_id': int,
'right_table_id': int,
'left_column_id': int,
'right_column_id': int,
'jointype': one of 'inner', 'leftOuter', 'firstMatch'
}
Returns
^^^^^^^
Quilt info as JSON object, includes ``sqlname`` field with the quilt’s
identifier.
Undo join
~~~~~~~~~
``DELETE /quilts/QUILT_SQLNAME``
Genome Math
-----------
- Performs a gene math operation on two tables
- Creates a new table with the result.
- Columns are specified by ``column.id``.
Intersect or subtract
~~~~~~~~~~~~~~~~~~~~~
``POST /genemath/``
Data Format
^^^^^^^^^^^
.. code:: javascript
{
'operator': one of 'Intersect' or 'Subtract',
'left_chr': integer (column id),
'left_start': integer (column id),
'left_end': integer (column id),
'right_chr': integer (column id),
'right_start': integer (column id),
'right_end': integer (column id)
}
Returns
^^^^^^^
JSON object representing the result table.
Python
======
The Quilt Python connector uses the Quilt REST API and SQL Alchemy
(http://docs.sqlalchemy.org/), if installed, to access and update data
sets in Quilt. Quilt tables are available as dictionaries or Pandas
(http://pandas.pydata.org/) DataFrames.
Connection
----------
To use the Quilt Python connector, add this repository to your
PYTHONPATH and import quilt.
Connect to Quilt by creating a Connection object:
.. code:: python
import quilt
connection = quilt.Connection(username)
Password: *enter your password*
The connection will contain a list of your Quilt tables:
.. code:: python
connection.tables
Search for Data Sets
~~~~~~~~~~~~~~~~~~~~
You can also find tables by searching your own tables and Quilt’s public
data sets
.. code:: python
connection.search('term')
Get Table
~~~~~~~~~
Get a table by Table id using get\_table:
.. code:: python
t = connection.get_table(1234)
Create a New Table
~~~~~~~~~~~~~~~~~~
Using the connection, you can create new tables in Quilt. To create an
empty table:
.. code:: python
t = connection.create_table(name, description)
To create a table from an input file:
.. code:: python
t = connection.create_table(name, description, inputfile=path_to_input_file)
Or, to create a new table from a DataFrame:
.. code:: python
t = connection.save_df(df, name, description="table description")
Table
-----
Each Table object has a list of Columns
.. code:: python
mytable.columns
After the columns have been fetched, columns are available as table
attributes.
.. code:: python
mytable.column1
Accessing Table Data
~~~~~~~~~~~~~~~~~~~~
Tables are iterable. To access table data:
.. code:: python
for row in mytable:
print row
Search
^^^^^^
Search for matching rows in a table by calling search.
.. code:: python
for row in mytable.search('foo'):
print row
Order By
^^^^^^^^
Sort the table by any column or set of columns. You can set the ordering
by passing a string that is the column’s field (name in the database).
.. code:: python
mytable.order_by('column1')
You can find column field names with their “.field” attribute:
.. code:: python
mytable.order_by(mytable.column1.field)
You can sort by multiple columns by passing a list of fields.
.. code:: python
mytable.order_by(['column2', 'column1'])
To sort in descending order, add a “-” in front of the column field
name:
.. code:: python
mytable.order_by('-column1')
Limit
^^^^^
Limit the number of rows returned by calling limit(number\_of\_rows).
Putting it all together
^^^^^^^^^^^^^^^^^^^^^^^
Search, order\_by and limit can be combined to return just the data you
want to see. For example, to return the top 2 finishers with the name
Sally from a table of race results (race\_results: [name\_000,
time\_001]), you could write:
.. code:: python
for result in race_results.search('Sally').order_by('-time_001').limit(2):
print row
Pandas DataFrame
~~~~~~~~~~~~~~~~
Access a table’s data as a Pandas DataFrame by calling mytable.df()
You can also combine the querying methods above to access particular
rows.
.. code:: python
race_results.search('Sally').order_by('-time\_001').limit(2).df()
Gene Math
~~~~~~~~~
Quilt supports intersect and subtract for tables that store genomic
regions. Those operations assume that tables have columns storing:
Chromsome, start and end. The function get\_bed\_cols tries to infer
those columns based on column names.
If the guessing fails, or to override the guess, set the chromosome,
start, end columns explicitly with set\_bed\_cols.
mytable.set\_bed\_cols(mytable.chr\_001, mytable.start\_002,
mytable.end\_003)
Once the bed columns are set for both tables, they can be intersected
and subtracted.
.. code:: python
result = tableA.intersect(tableB)
result = tableA.intersect_wao(tableB)
result = tableA.subtract(tableB)
========================================
Optional prep (your steps may vary)
-----------------------------------
#. Get a list of files you want to upload (see ``get-files-to-upload/``)
#. Download the files in the list (see ``curl-all.py``)
#. Unzip downloaded files (if needed)
.. code:: bash
cd downloads
gunzip *.gz
.. rubric:: Upload to Quilt
:name: upload-to-quilt
#. | Use ``data_set.py`` to create individual data sets (see
``python data_set.py --help``).
| You will need a Quilt username and password. Or use ``batch.py`` to
create multiple data sets.
.. code:: bash
python data_set.py
-e https://quiltdata.com
-u USERNAME
-n "ENCODE data"
-d "#A549 #histone peak data #hg19"
-f downloads/wgEncodeBroadHistoneNhaH3k36me3StdPk.broadPeak
File formats in this example
----------------------------
- `ENCDOE broadPeak format`_
Resources
---------
- `ENCODE Project`_
REST API
========
+--------------------------------+--------------------------------------+-------------------------------------------+
| Action | Endpoint | Details |
+================================+======================================+===========================================+
| New table | ``POST /tables/`` | `See below`_ |
+--------------------------------+--------------------------------------+-------------------------------------------+
| Delete table | ``DELETE /tables/TABLE_ID/`` | `See below <#delete-table>`__ |
+--------------------------------+--------------------------------------+-------------------------------------------+
| Update table meta-data | ``PATCH /tables/TABLE_ID`` | `See below <#update-table-meta-data>`__ |
+--------------------------------+--------------------------------------+-------------------------------------------+
| Add column to table | ``POST /tables/TABLE_ID/columns/`` | `See below <#add-column-to-table>`__ |
+--------------------------------+--------------------------------------+-------------------------------------------+
| Append row to table | ``POST /data/TABLE_ID/rows/`` | `See below <#append-row>`__ |
+--------------------------------+--------------------------------------+-------------------------------------------+
| Get table rows | ``GET /data/TABLE_ID/rows`` | `See below <#get-rows>`__ |
+--------------------------------+--------------------------------------+-------------------------------------------+
| Get table row | ``GET /data/TABLE_ID/rows/ROW_ID`` | `See below <#get-row>`__ |
+--------------------------------+--------------------------------------+-------------------------------------------+
| Genome intersect or subtract | ``POST /genemath/`` | `See below <#intersect-or-subtract>`__ |
+--------------------------------+--------------------------------------+-------------------------------------------+
Notes
- For all REST calls, the content-type is ``application/JSON``.
- Description fields automatically linkify URLs and support
``<a>, <i>, <em>, <strong>, <b>`` tags
Tables
------
Create table
~~~~~~~~~~~~
``POST /tables/``
Data format
^^^^^^^^^^^
.. code:: javascript
{
'name': string,
'description': text `<a>, <i>, <em>, <strong>, <b>` tags supported; automatic linkification of URLs
'columns': [
{
'name': string,
'sqlname': optional string,
'description': optional text,
'type' : one of 'String', 'Number', 'Image', 'Text'
},
...
]
}
Returns
^^^^^^^
Table data as JSON object, includes ``id`` field with the table’s
identifier.
Add column to table
~~~~~~~~~~~~~~~~~~~
``POST /tables/TABLE_ID/columns/``
Data format
^^^^^^^^^^^
.. code:: javascript
{
'name': string,
'sqlname': optional string,
'description': text,
'type': one of 'String', 'Number', 'Image', or 'Text'
}
Returns
^^^^^^^
Column data as JSON object, includes ``id`` field with the column’s
identifier.
Delete table
~~~~~~~~~~~~
``DELETE /tables/TABLE_ID``
Update table meta-data
~~~~~~~~~~~~~~~~~~~~~~
``PATCH /tables/TABLE_ID``
Data format
^^^^^^^^^^^
.. code:: javascript
{
'name': string,
'description': text
}
Table Data
----------
- Use column ``sqlname`` as keys in input data
Append row
~~~~~~~~~~
``POST /data/TABLE_ID/rows/``
Data format
^^^^^^^^^^^
.. code:: javascript
[
{columnSqlname0: value0, columnSqlname1 : value1, ... },
...
]
Get rows
~~~~~~~~
``GET /data/TABLE_ID/rows`` \* Rows are keyed by the Quilt Row ID field
``qrid`` \* NOTE: Currently limited to the first 500 rows
Returns
^^^^^^^
Row data as JSON object, keyed by column.sqlname.
Get row
~~~~~~~
``GET /data/TABLE_ID/rows/ROW_ID``
Returns
^^^^^^^
Row data as JSON object, keyed by column.sqlname.
Quilt tables
------------
Join
~~~~
``POST /quilts/`` #### Data format
.. code:: javascript
{
'left_table_id': int,
'right_table_id': int,
'left_column_id': int,
'right_column_id': int,
'jointype': one of 'inner', 'leftOuter', 'firstMatch'
}
Returns
^^^^^^^
Quilt info as JSON object, includes ``sqlname`` field with the quilt’s
identifier.
Undo join
~~~~~~~~~
``DELETE /quilts/QUILT_SQLNAME``
Genome Math
-----------
- Performs a gene math operation on two tables
- Creates a new table with the result.
- Columns are specified by ``column.id``.
Intersect or subtract
~~~~~~~~~~~~~~~~~~~~~
``POST /genemath/``
Data Format
^^^^^^^^^^^
.. code:: javascript
{
'operator': one of 'Intersect' or 'Subtract',
'left_chr': integer (column id),
'left_start': integer (column id),
'left_end': integer (column id),
'right_chr': integer (column id),
'right_start': integer (column id),
'right_end': integer (column id)
}
Returns
^^^^^^^
JSON object representing the result table.
Python
======
The Quilt Python connector uses the Quilt REST API and SQL Alchemy
(http://docs.sqlalchemy.org/), if installed, to access and update data
sets in Quilt. Quilt tables are available as dictionaries or Pandas
(http://pandas.pydata.org/) DataFrames.
Connection
----------
To use the Quilt Python connector, add this repository to your
PYTHONPATH and import quilt.
Connect to Quilt by creating a Connection object:
.. code:: python
import quilt
connection = quilt.Connection(username)
Password: *enter your password*
The connection will contain a list of your Quilt tables:
.. code:: python
connection.tables
Search for Data Sets
~~~~~~~~~~~~~~~~~~~~
You can also find tables by searching your own tables and Quilt’s public
data sets
.. code:: python
connection.search('term')
Get Table
~~~~~~~~~
Get a table by Table id using get\_table:
.. code:: python
t = connection.get_table(1234)
Create a New Table
~~~~~~~~~~~~~~~~~~
Using the connection, you can create new tables in Quilt. To create an
empty table:
.. code:: python
t = connection.create_table(name, description)
To create a table from an input file:
.. code:: python
t = connection.create_table(name, description, inputfile=path_to_input_file)
Or, to create a new table from a DataFrame:
.. code:: python
t = connection.save_df(df, name, description="table description")
Table
-----
Each Table object has a list of Columns
.. code:: python
mytable.columns
After the columns have been fetched, columns are available as table
attributes.
.. code:: python
mytable.column1
Accessing Table Data
~~~~~~~~~~~~~~~~~~~~
Tables are iterable. To access table data:
.. code:: python
for row in mytable:
print row
Search
^^^^^^
Search for matching rows in a table by calling search.
.. code:: python
for row in mytable.search('foo'):
print row
Order By
^^^^^^^^
Sort the table by any column or set of columns. You can set the ordering
by passing a string that is the column’s field (name in the database).
.. code:: python
mytable.order_by('column1')
You can find column field names with their “.field” attribute:
.. code:: python
mytable.order_by(mytable.column1.field)
You can sort by multiple columns by passing a list of fields.
.. code:: python
mytable.order_by(['column2', 'column1'])
To sort in descending order, add a “-” in front of the column field
name:
.. code:: python
mytable.order_by('-column1')
Limit
^^^^^
Limit the number of rows returned by calling limit(number\_of\_rows).
Putting it all together
^^^^^^^^^^^^^^^^^^^^^^^
Search, order\_by and limit can be combined to return just the data you
want to see. For example, to return the top 2 finishers with the name
Sally from a table of race results (race\_results: [name\_000,
time\_001]), you could write:
.. code:: python
for result in race_results.search('Sally').order_by('-time_001').limit(2):
print row
Pandas DataFrame
~~~~~~~~~~~~~~~~
Access a table’s data as a Pandas DataFrame by calling mytable.df()
You can also combine the querying methods above to access particular
rows.
.. code:: python
race_results.search('Sally').order_by('-time\_001').limit(2).df()
Gene Math
~~~~~~~~~
Quilt supports intersect and subtract for tables that store genomic
regions. Those operations assume that tables have columns storing:
Chromsome, start and end. The function get\_bed\_cols tries to infer
those columns based on column names.
If the guessing fails, or to override the guess, set the chromosome,
start, end columns explicitly with set\_bed\_cols.
mytable.set\_bed\_cols(mytable.chr\_001, mytable.start\_002,
mytable.end\_003)
Once the bed columns are set for both tables, they can be intersected
and subtracted.
.. code:: python
result = tableA.intersect(tableB)
result = tableA.intersect_wao(tableB)
result = tableA.subtract(tableB)
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