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PythonCyc is a Python interface package to Pathway Tools, version 18.5 or above. PythonCyc has been tested with Python 2.6 and IPython on Mac OS X, Linux and Microsoft Windows. Since PythonCyc is based on the programming language Python, you must use a Python interpreter to use PythonCyc. In the following we assume that you have installed Python (we recommend version 2.6 or above, but it most likely work with any 2.x version).
For the complete API documentation of PythonCyc, please consult PythonCyc API.
For the latest news about PythonCyc, please consult the PythonCyc web page.
We assume that you have downloaded PythonCyc from PythonCyc at GitHub. This may be done by using git cloning or by downloading the zip file of PythonCyc from GitHub. The next step is to make PythonCyc accessible from your running Python interpreter. To do so, install PythonCyc according to one of the following platforms.
Open a terminal window and change your directory to the location where you unpacked the PythonCyc package. You must have the file setup.py, and the subdirectory pythoncyc, in that directory. Assuming that 'shell>' is the prompt of your current Unix shell, execute the following command:
shell> sudo python setup.py install
This may prompt you for your login password because sudo requires authorization to modify some system directories. This command copies several files from the pythoncyc subdirectory to other locations on your computer where Python is installed, byte-compiles these files and may do other operations depending on the Python installation you have. No error messages should be reported. In case of errors, make sure you have installed Python and that it is working.
To test your PythonCyc installation, please consult the Section Getting Started in this document.
On a Microsoft Windows platform, starts a command prompt window using the start/Accessories menu, then change the directory to the location where you unpacked the PythonCyc package. You must have the file setup.py, and the subdirectory pythoncyc, in that directory . Then, at the command prompt, execute the following command:
python setup.py install
This command copies several files from the pythoncyc subdirectory to other locations on your computer where Python is installed, byte-compiles these files and may do other operations depending on the Python installation you have. No error messages should be reported. In case of errors, make sure you have installed Python and that it is working. To test your PythonCyc installation, please consult the Section Getting Started in this document.
Pathway Tools (version 18.5 and up) must be running on some computer started with at least the command line option '-python' or '-python-local-only', which starts the Python server in Pathway Tools. If '-python' is specified, connections made to Pathway Tools could come from a remote computer, whereas for '-python-local-only', no remote computer can connect to the Python server. The option '-python-local-only' is for added cybersecurity because with that option no remote computer can access your locally running Pathway Tools via the Python server. PythonCyc communicates to this running Pathway Tools server via a socket on port 5008 (default setup). It is also recommended to start Pathway Tools with the command line option '-lisp', so that the connection can be monitored and debugged, if need be. In summary, we recommend to start Pathway Tools using the following options
./pathway-tools -lisp -python
or for added cybersecurity with the options
./pathway-tools -lisp -python-local-only
To run PythonCyc remotely from Pathway Tools, please read the Section Remotely Accessing Pathway Tools to setup PythonCyc to remotely access Pathway Tools. In the following, we assume that Pathway Tools is running on the same computer as Python and that it has the MetaCyc database.
Start a Python interpreter on the same computer as Pathway Tools. You should get a prompt such as >>>, then enter the following
>>> import pythoncyc
This command imports the PythonCyc module to access its classes, functions and methods. If any error messages is given when this command make sure PythonCyc has been installed according to the Installation instructions. Then enter the command
>>> meta = pythoncyc.select_organism('meta')
This command sends a request to Pathway Tools to create a PGDB object associated with the database MetaCyc, which is specified using the 'meta' organism identifier (i.e., orgid). That PGDB object is assigned to the variable meta. (If you get an error message, it could be that Pathway Tools was not started as given above.)
Print out the Python meta variable
>>> print meta <PGDB meta, currently has 0 PFrames>
This means that meta is bound to a PGDB object, its orgid is meta and it has currently no PFrames attached to it. Indeed, currently we only created a PGDB object that has no _data frames_ in it. The following sections will show how to retrieve data frames from Pathway Tools to PythonCyc via this variable meta.
If you want to have a list of all PGDBs, and their orgids, accessible from your running Pathway Tools, evaluate pythoncyc.all_orgids().
Please, consult the source file __init__.py for other fundamental methods available from the pythoncyc module.
Also, more advanced technical documentation is provided for each method and functions by consulting the PythonCyc modules config.py, PGDB.py, PToolsFrame.py and PTools.py. As usual, the Python help command can provide documentation about the modules, classes and methods: for example, help(pythoncyc) prints the documentation for the module pythoncyc; or the command help(meta), once variable meta is bound to a PGDB object, prints all the methods available, and their documentation, for a PGDB object.
Using that variable meta, it is now possible to request data from the MetaCyc database. For example, the following statement retrieves compound TRP (i.e., L-tryptophan). 'TRP' is the frame id of compound L-tryptophan, which we can also specify in lower case letters:
>>> meta.trp
Evaluating meta.trp, if done for the first time, triggers a call to Pathway Tools to retrieve the frame data (or simply frame) of compound TRP: the slots (also called attributes) and their data of the Pathway Tools frame representing compound TRP are sent to PythonCyc to create a PFrame object to represent the compound TRP. PythonCyc also prints that frame content which is represented as a Python dictionary: the slots of the frame are the keys of the dictionary and the value of the slots are the values of the dictionary.
Note: in Pathway Tools, the slots are used to access the data of a frame (i.e., object). In Python, an object has attributes. The meaning of these two terms, that is, slots and attributes, are very similar. A slot of a frame in Pathway Tools becomes an attribute of a PFrame object in PythonCyc. We will use the term slots when referring to a frame in Pathway Tools and attributes when referring to the same slots in PythonCyc.
Printing out meta now shows that we have one PFrame attached to meta:
>>> print meta <PGDB meta, currently has 1 PFrames>
Indeed, this PFrame for TRP was also bound to the PGDB meta such that it became an attribute of meta. That is, executing meta.trp again would not retrieve the data from Pathway Tools, but directly use the PFrame already created for it and now stored as an attribute for meta. All created PFrames based on a PGDB object are attached to that object and no two PFrames can have the same frame id for that PGDB object.
In Pathway Tools, the frame id is in upper case, that is, 'TRP'. The conversion from lower case to upper case is handled automatically by PythonCyc. PFrame, in PythonCyc, is the class of objects to represent frame objects from Pathway Tools. More details about PFrames is given below and in the Section PFrame Objects. In particular, note that PFrames are read only, that is, their attributes cannot be modified.
From a PGDB object, a PFrame can be accessed using the frame id either by using the attribute or indexing syntax of Python. For example, the following would retrieve reaction with frame id RXN-9000
>>> rxn9000 = meta['RXN-9000']
or by using the attribute syntax
>>> rxn9000 = meta.rxn_9000
Both forms access the same attribute. Note that the frame id 'RXN-9000' has a dash in its name but an attribute in Python cannot have a dash. To provide access to such frame ids, using the attribute syntax of Python, dashes are converted to underscores. Mixed cases (i.e., upper or lower case letters) can be used for both syntax (attributes and indexing) because an automatic conversion is done by PythonCyc. There are cases where only the second form, the indexing syntax, can be used. For example, for a slot name starting with a digit, or a character that is not a letter or an underscore, the indexing syntax with a string must be used. This is due to the syntax of attribute names in Python which can only have letters, digits and underscores, and cannot start with a digit. For example, the slot name 'N+1-NAME' can only be accessed using the index syntax because it has the character '+' which cannot be used in a Python identifier.
In PythonCyc, frame ids are stored as strings prefixed and suffixed by '|'. In general, these vertical bars identify symbols in PythonCyc which exists as Lisp symbols in Pathway Tools. When symbols are return from Pathway Tools, the vertical bars are inserted. For example, we can see the frame id of meta.trp by printing it:
>>> print meta.trp.frameid |TRP|
The syntax '|...|' is used to indicate that this string represents a symbol and can be interpreted by Pathway Tools as a frame id. In Lisp, the programming language used to implement Pathway Tools, the double vertical bars signifies that this is a symbol that must be read exactly as given without any transformation (e.g., no case conversion on letters).
Advanced technical note: all PFrames created using a PGDB object are included in a Python dictionary bound to an attribute, of that PGDB object, called "frames". The keys of that dictionary are the frame ids of the PFrames converted to valid Python identifiers. The getattr and getitem methods of the PGDB class were written in such a way that such an expression as 'meta.trp' searches in the dictionary for a PFrame with frame id 'TRP'.
Once you have access to a frame, the frame ids stored in that frame can be used to create more PFrames. For example, the trp object has an attribute called appears_in_right_side_of which has a list of reaction frame ids as a value. The reaction frame ids refer to all reactions that has TRP on its right-hand side. The reactions can be retrieved in the following way:
>>> rxns_trp_right = [meta[fid] for fid in meta.trp.appears_in_right_side_of]
The variable rxns_trp_right is bound to a list of PFrames representing the reactions. Each PFrame becomes also attributes to meta based on the frame ids.
The basic mechanism of attribute access and indexing on a PGDB object just shown is enough to retrieve all frames from a PGDB assuming that frame ids are known and PFrames are implicitly (i.e., automatically) created. The next section shows how to retrieve large number of frames based on classes of objects, which indirectly provides the frame ids of large number of frames.
Another implicit operations done by PythonCyc is the retrieval of classes of objects from Pathway Tools. There are many classes of objects, such as Reactions, Proteins, Compounds, Genes, Pathways, and more. For example, retrieving the class of all reactions of PGDB meta, from Pathway Tools, can be done by
>>> reactions = meta.reactions
which assign to variable reactions a PFrame representing the class of reactions from PGDB meta. Printing out this variable gives
>>> reactions <PFrame class |Reactions| currently with 13081 instances (meta)>
As can be seen, reactions is a PFrame and it is a class which has the name |Reactions| in Pathway Tools and it has 13,081 instances, that is, 13,081 reactions, all from the PGDB meta (i.e., MetaCyc). The number of instances may differ for you because MetaCyc is periodically modified. Remember that the vertical bars in a name means that it is a symbol, and here it is more specifically a frame id.
This PFrame reactions has an attribute instances assigned with the list of all reactions of the MetaCyc PGDB. Each such reaction is also a PFrame, although these PFrames have currently no other data than the frame id of each reaction. It is a lazy transfer of the frames where only the frame ids were requested from Pathway Tools. This approach is useful because in some cases not all data from all reactions are needed. We can access each reaction via the attribute instances, for example
>>> reactions.instances[0]
but we can also use indexing directly on the class reactions such as
>>> reactions[0]
{'_gotframe': False, '_isclass': False, 'pgdb': meta, 'frameid': u'|3.1.22.4-RXN|'}
but the frameid value is likely different (MetaCyc is periodically modified). As mentioned, each object in a PGDB has a unique identifier called the frame id, which in PythonCyc is stored in the field frameid of a PFrame. When the reactions were retrieved from Pathway Tools, the frame id values also became attributes of the Python PGDB object meta, that is, we can also indexed object meta with the frame ids. For example,
>>> meta['|3.1.22.4-RXN|']
{'_gotframe': False, '_isclass': False, 'pgdb': meta, 'frameid': u'|3.1.22.4-RXN|'}
This Python dictionary is a very short representation of the frame with almost no data. The attributes shown are only created by PythonCyc to maintain that frame in Python. If you access one slot of that reaction frame, which is not listed in that output, the value of that slot is retrieved from Pathway Tools. For example,
>>> reactions[0].left [u'|Double-Stranded-DNAs|', u'|WATER|']
retrieves the data for slot left and that value is kept in the PFrame. Therefore, accessing several times the same slot of a frame, only triggers one communication to Pathway Tools because after it was accessed once, it is no longer accessed again from Pathway tools. (Note: the methods get_slot_values and get_slot_value presented later in this document always trigger a transfer from Pathway Tools.) We can verify that the the PFrame has the left attribute in the PFrame itself:
>>> reactions[0]
{u'left': [u'|Double-Stranded-DNAs|', u'|WATER|'], '_gotframe': False,
'_isclass': False, 'pgdb': meta, 'frameid': u'|3.1.11.3-RXN|'}
Another very different approach to retrieve all the data of a list of frames is by using the Python method get_frame_objects defined for a PGDB object. That method takes a list of frame ids as input and send a request to Pathway Tools to transfer all the slots and their data for all the frames identified by these frame ids. The function creates a PFrame, for each frames retrieved, for the PGDB, if none exist.
For example, assuming that we have the variable reactions bound to the class of reactions as in the previous section, to retrieve all the frame data for the first 10 reactions, the following can be used: (We retrieve only the first 10 reactions to reduce execution time)
>>> r = meta.get_frame_objects([f.frameid for f in reactions.instances[0:10]])
The list comprehension gathers the frame ids in one list and a call to the get_frame_objects method is done, using the PGDB object meta, to retrieve from Pathay Tools all the slots and their data for all the frame ids. This approach always transfer the frames from Pathway Tools even if we already transferred them already. This can be needed if the frames were modified and there is a need to transfer them again.
Another very different way to access the frame data is to use methods get_slot_value and get_slot_values. These methods are among the more than 150 methods of the PGDB class which is the subject of the next section. The first method retrieves a scalar value on a slot that can only have one value whereas the second method retrieves a list of values from a slot that can have multiple values. In both cases, only the data from one slot is retrieved, not the whole frame. That is, there are no creation of PFrames when using these functions.
For example, the following retrieve the Gibbs free energy of reaction RXN-9000 from MetaCyc
>>> meta.get_slot_value('RXN-9000', 'GIBBS-0')
7.5217285
We did not specify the vertical bars for the frame id 'RXN-9000' and the name of the slot 'GIBBS-0' although both are symbols in Pathway Tools. The translation to symbols is handled automatically by the function get_slot_value, and many other functions that require symbols as arguments.
The following retrieves the chemical formula of compound TRP
>>> meta.get_slot_values('TRP', 'CHEMICAL-FORMULA')
{u'|N|': [2], u'|C|': [11], u'|H|': [12], u'|O|': [2]}
The method get_slot_values is needed (instead of get_slot_value, the singular version) because the slot 'CHEMICAL-FORMULA' keeps the chemical formula as a list of pairs (atom-species coefficient) where atom-species is the species of the atom (e.g., 'C' for carbon) and coefficient is an integer. In that particular case, that is, a list of pairs, the result will be returned as a Python dictionary where the keys are the atom species and the values are the coefficients. In the next section there is more explanation on data conversion between Lisp and Python.
Using a variable bound to a PGDB object, which is the case for variable meta from the previous sections, any of the more than 150 methods from the PGDB class can be called, each corresponding to a specific function in Pathway Tools. The list of these methods (or functions), and their documentation, can be obtained by consulting the source code of file PGDB.py or by using the standard help mechanism of Python (or IPython). For example,
>>> help(pythoncyc.PGDB)
will list the source documentation of the class PGDB with the list of all methods. For a particular function, you can request its documentation by naming the function. For example,
>>> help(pythoncyc.PGDB.get_slot_value)
Almost all these methods do not create PFrame objects but returns basic Python object, that is, boolean, numbers, strings, lists, dictionaries, and so on. When a Pathway Tools object (e.g., gene, pathway, reaction) needs to be returned, the frame id (as a string) is returned. For example, the following call retrieves all the pathways from meta by returning a list of frame ids (as strings):
>>> pwys = meta.all_pathways()
As presented in the previous section, to create PFrames, and the data about pathways, using frame ids, you can use the method get_frame_objects.
Many other Lisp functions, defined in Pathway Tools, can be called using Python's syntax. These functions often need a frame as one of the parameter. A frame can be specified as a frame id (a string) or as a PFrame object. For example,
>>> meta.reactions_of_compound('TRP')
where 'TRP' is the frame id of compound L-tryptophan. The reactions_of_compound method (which is a function in Pathway Tools) retrieves all reaction frame ids that use TRP as a substrate. Note that, if the given frame id was not existing in the PGDB, it would raise a PToolsError in PythonCyc because Pathway Tools itself will report a 'non coercible frame'.
A PFrame can also be used instead of the frame id. For example, meta.trp refers to a PFrame for compound TRP and can be used to do the same operation we just did, that is,
>>> meta.reactions_of_compound(meta.trp)
Some methods modify the PGDB in Pathway Tools, such as
>>> meta.put_slot_value('RXN-9000','GIBBS-0',2.7)
which modifies the slot 'GIBBS-0' for frame 'RXN-9000' to the value 2.7 for the PGDB associated with object meta, which in our case is MetaCyc.
Some functions have keywords arguments, which are always optional. But notice that the default value is often the Python value None. The value None is not translated to False, but indicates to use the default value of the Lisp function called. These defaults are given in the documentation of each PythonCyc method.
The transfer of all data from Pathway Tools to PythonCyc is done using the JSON (JavaScript Object Notation) syntax. On the other hand, PythonCyc does not use JSON for the transfer of data from Python to Pathway Tools because Pathway Tools uses Lisp and it is simpler to use a Lisp syntax for that transfer. Some conversion rules are applied on data types when transferring data to and from Pathway Tools and we discuss these in the following. Note that all the special rules of conversion from Lisp to Python is based on what the JSON Lisp package does whereas the special rules of conversion from Python to Lisp is what the method convertArgToLisp, of class PGDB, does.
During conversion, the numbers are kept relatively unchanged: integers and floating-point numbers are translated using the same types but floating-point numbers are not guaranteed to have the same precision. In Lisp and Python, infinite precision of integers are implemented. The rational numbers of Lisp are translated to floating-point numbers in Python.
The Python value True is translated into t in Lisp whereas False and None are translated into nil in Lisp. The value t in Lisp is translated into True in Python. On the other hand, the value nil in Lisp is translated into False, None or the empty list [] in Python depending on the context. It is translated to False when a PythonCyc method is called that expects a boolean value as a result: for example, the PythonCyc method pathway_hole_p does return False when the result of the corresponding function in Lisp is nil. It is translated to the empty list [] when a PythonCyc method is called that expects a list as a result: for example, the PythonCyc method get_slot_values does return [] when the slot value is nil. Finally, the nil values is translated to None when the result is not known to be a boolean or a list value: for example, the PythonCyc method get_slot_value would return None if the slot value is nil.
Any Lisp string is translated into a Python string. A Python string that starts and ends with a '|', and contains no space, is assumed to represent a symbol and is translated successfully into one if indeed the Python string follows the correct syntax of a Lisp symbol. For example, the Python string "|RXN-9000|" is translated into the Lisp symbol RXN-9000.
Lisp lists are translated to Python lists, but with one important exception: a Lisp list where all elements are non empty sublists, and every first element of each sublist is a symbol or string, are translated into a Python dictionary. For example, the slot chemical-formula has such lists: the chemical formula H2O is represented as the list of sublists ((H 2) (O 1)), where H and O are symbols, in that slot. Each sublist is translated, in JSON, to a key/value pair in a dictionary, where the key is the first element of the sublist and the value is the rest of the list. Therefore, the Lisp value ((H 2) (O 1)) is translated into the Python dictionary {'|H|' : [2], '|O|' : [1]}. Notice that H and O are translated into Python strings with the vertical bars to indicate that they are symbols and the coefficients 2 and 1 are translated into lists of one element because the rest of each sublist is a list.
A dictionary in Python is translated into a list of dotted pairs or list of lists when transferred to Pathway Tools. For example, {'|H|' : [2], '|O|' : [1]} is translated into ((H 2) (O 1)), which is the desired Lisp representation in Pathway Tools for the a chemical-formula slot value. On the other hand the Python dictionary {'|H|' : 2, '|O|' : 1} would be translated into ((H . 2) (O . 1)), that is, a list of dotted pairs, which is not the desired Lisp representation for that slot but could be used correctly in some other context although Pathway Tools rarely use dotted pairs.
A vector from Pathway Tools is translated into a Python Lisp. Note: there is no basic vector type in Python.
Finally, a Python tuple is translated into an improper Lisp list. For example, the Python tuple (1, 2, 3) is translated into the improper Lisp list (1 2 . 3). The last element of the list is preceded by a dot, which makes it an improper list. Note that the particular case of a tuple with only one element is translated into an improper list of nil followed by the element. For example, the Python tuple (2,) is translated into (nil . 2). Improper lists are uncommon in Pathway Tools such that you may never need to worry about them.
If you modify the slots of data frames in Pathway Tools, via the PythonCyc interface, care must be taken to store the appropriate data structures and use the appropriate corresponding Python data structures. As we just saw, this should not be a problem for numbers, strings, booleans and list of these basic types as the translation is one to one. For example, the value of the slot synonyms of compound frames is a list of strings, the synonyms of the compounds:
>>> meta.get_slot_values('atp', 'synonyms')
[u'adenylpyrophosphate', u'adenosine-triphosphate', u"adenosine-5'-triphosphate"]
You could modify that list, say to only include the first two synonyms, in the following way:
>>> meta.put_slot_values('atp', 'synonyms', [u'adenylpyrophosphate', u'adenosine-triphosphate'])
Note: Typically, modifying a slot should be done on your own created PGDB, not on MetaCyc. In any case, you will not be able to save MetaCyc and any slots modified in MetaCyc will be restored to its original value after you restart the Pathway Tools application.
As for a slot such as chemical-formula, you can represent the value to store in the slot as a list of sublists, such as:
>>> meta.put_slot_values('water', 'chemical-formula', [['|H|',2],['|O|',1]])
{u'|H|': [2], u'|O|': [1]}
The returned value is a dictionary that contains frames ids (i.e., the vertical bars surrounding H and O indicate that they are symbols). Or you can use a dictionary as in
>>> meta.put_slot_values('water', 'chemical-formula', {u'|H|': [2], u'|O|': [1]})
In all cases, care must be taken to have the right representation when modifying a frame slot of a PGDB in Pathway Tools because, at the moment of modifiying the slot, there is no verification of the validity of the data being stored.
When a slot is supposed to contain frames, storing the frame ids in the slot automatically convert these frame ids into frame references. For example, the slot structure-atoms is a list of atom species frames. To modify it would simply require to list the atom species frame ids. For example, for compound water:
>>> meta.put_slot_values('water', 'structure-atoms', ['|O|', '|H|', '|H|'])
Notice that we passed the frame ids O and H using the vertical bars. This is needed because otherwise these would be taken as strings not symbols that refer to frame object in Pathway Tools.
As already mentioned, there are many more methods that can be called to access functions in Pathway Tools and some of them can run complex analysis. For example, there is a method to run flux balance analysis (FBA) called run_fba. Please, consult the file PGDB.py for the complete list of available methods and their documentation.
PFrame is a Python class to represent Pathway Tools' frames in PythonCyc. A PFrame can represent a Pathway Tools class frame (e.g., Reactions) as well as an instance frame (e.g., RXN-9000). PFrames are useful to retrieve many frames and all their data from Pathway to PythonCyc and then operate on that data locally in Python. On the other hand, if the data needs to be modified in the PGDB of Pathway Tools, PFrames are not useful because they are read only.
As discussed in the previous sections, PFrames are automatically created when retrieving classes, or instances using the attribute or indexing syntax applied to a PGDB object. You could also directly create PFrames. To do so, you need to import the class PFrame:
>>> from pythoncyc.PToolsFrame import PFrame
The required parameters to create a PFrame are the frame id (a string) and a PGDB object. For example, assuming that variable meta is bound to a PGDB object, the following create a PFrame to represent the reaction RXN-9000,
>>> PFrame('RXN-9000', meta)
{'_gotframe': False, '_isclass': False, 'pgdb': ,
'frameid': '|RXN-9000|'}
By default, an instance PFrame (not a class PFrame) is created and the data of the frame is not requested from the server, that is, a PFrame object is created containing only the frame id, the PGDB and a fews other attributes to maintain the PFrame. This is what the print out of that frame shows above. That PFrame is also attached, as an attribute, to the PGDB meta. That can be seen by evaluating
>>> meta._frames.keys() ['rxn_9000']
By specifying the keyword argument getFrameData=True, all slots and data of the frame are retrieved from Pathway Tools. For example, the following create a PFrame for reaction RXN-9000 and retrieve all its slots and data,
>>> PFrame('RXN-9000', meta, getFrameData=True)
{u'enzymatic_reaction': [u'|ENZRXN-14558|'], u'right': [u'|PROTON|', u'|CPD-9460|', u'|UDP|'],
u'schema_p': True, '_isclass': False, u'creator': u'|Kate|', u'ec_number': [u'|EC-2.4.1.17|'],
u'creation_date': 3408307573, u'reaction_direction': u'|LEFT-TO-RIGHT|', 'frameid': '|RXN-9000|',
u'in_pathway': [u'|PWY-5756|'], u'left': [u'|CPD-9459|', u'|UDP-GLUCURONATE|'],
u'citations': [u'WOJCIECHOWSKI75'], u'key_slots': u'|COMMON-NAME|', u'physiologically_relevant_p': [True],
u'synonym_slots': [u'|ABBREV-NAME|', u'|SYNONYMS|'], u'atom_mappings': {u'|NO-HYDROGEN-ENCODING|':
[[38, 37, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 6,
7, 9, 10, 12, 13, 60, 61, 62, 63, 64, 65, 66, 19, 20, 22, 24, 23, 68, 69, 67, 32, 0, 1, 2, 3, 4,
5, 8, 11, 14, 15, 16, 17, 18, 21, 25, 29, 33, 28, 26, 27, 30, 31, 34, 36, 35],
[{u'|CPD-9459|': [37, 69], u'|UDP-GLUCURONATE|': [0, 36]}, {u'|CPD-9460|': [0, 44], u'|UDP|': [45, 69]}]]},
'_gotframe': True, u'gibbs_0': 2.7000000000000002, u'substrates': [u'|UDP-GLUCURONATE|',
u'|CPD-9459|', u'|PROTON|', u'|CPD-9460|', u'|UDP|'], 'pgdb': }
For creating a class, the isClass keyword parameter must say so,
>>> PFrame('Reactions', meta, isClass=True)
When creating a class, if getFrameData=True is specified, the class slots and its data are fetched and all the instances of the class are also created as, mostly empty, PFrames. They are mostly empty in the sense that the slots and data of the instances are not transferred, but only the frame id of each frame initialized each PFrame.
The attribute values of the PFrames cannot be modified, that is, attributes are read only. If you try to modify a PFrame attribute, a PythonCycError is raised. On the other hand, slots of Pathway Tools' objects can be modified using methods put_slot_value and put_slot_values. In that case, the PGDB itself in Pathway Tools is modified. See class PGDB for these methods.
It is possible to use PythonCyc to access a Pathway Tools application running on a remote computer. First, Pathway Tools must be started with the command line option '-python' (not '-python-local-only'). That is,
./pathway-tools -python
or with also the option -lisp to get a Lisp console to monitor the Python server
./pathway-tools -lisp -python
Note: If you were using the option '-python-local-only' instead of '-python' the Python server would not accept connection from remote computers increasing cybersecurity.
Second, you need to use the config module of PythonCyc to set the appropriate host name of that remote computer. For example, assuming that the remote computer is at address 'ptools.mydomain.com' (this is a fictive address for this example). The following would configure PythonCyc to communicate with it:
>>> import pythoncyc.config as config
>>> config.set_host_name('ptools.mydomain.com')
If for some reason the Pathway Tools Python server is not using the default port (i.e., 5008), but some other port such as 5000, it can also be configured on the PythonCyc side by using method set_host_port
>>> config.set_host_port(5000)
The preceding Python configuration can be done at any time and it affects all future operations of PythonCyc. It could be done several times to access different Pathway Tools running on different ports or host names.
This example is a function that gathers the Gibbs free energy of the compounds involved in each reaction of a PGDB with a given orgid. The result is a Python dictionary with keys as the frame ids of the reactions and the values as lists of the substrates' Gibbs free energy of each reaction.
This function does not create any PFrame but uses the basic get_slot_value and get_slot_values to retrieve data from Pathway Tools. The function all_rxns retrieves the frame ids of all reactions from the PGDB, then the substrates slot is accessed to get the compound frame ids involved in each reaction. Finally, for each compound frame id, the slot 'GIBBS-0' is accessed to create pairs of compound frame id and Gibbs free energies values transformed into a dictionary using the Python dict function.
def gather_gibbs_substrates_of_reactions(orgid):
"""
Return a dictionary of all reactions of PGDB orgid with the Gibbs free energies of formation
of their substrates. The keys are the frame ids of the reactions and the values are dictionaries
of compound frame ids to Gibbs free energies of formation.
"""
pgdb = pythoncyc.select_organism(orgid)
rxn_frameids = pgdb.all_rxns(type='all')
gibbs_dict = {}
for rxn_fid in rxn_frameids:
cpds_fids = pgdb.get_slot_values(rxn_fid,'SUBSTRATES')
gibbs_dict[rxn_fid] = dict([(cpd_fid, pgdb.get_slot_value(cpd_fid, 'GIBBS-0')) for cpd_fid in cpds_fids])
return gibbs_dict
This function could be called in the following way assuming that the PGDB with orgid 'ecoli' is available from the Python server of Pathway Tools.
>>> gibbs_dict = gather_gibbs_substrates_of_reactions('ecoli')
This function may take more than 30 seconds to execute because it is retrieving a large amount of data from Pathway Tools.
The following is a simple function to create a PGDB object based on the organism name (i.e., orgid) and retrieve all its basic PFrames for compounds and reactions. Note that these PFrames has no other data than their frame ids.
def create_pgdb_with_compounds_and_reactions(orgid):
"""
Create a PythonCyc PGDB object with all its compounds and reactions
PFrames created. Return the PGDB object.
"""
pgdb = pythoncyc.select_organism(orgid)
pgdb.compounds
pgdb.reactions
return pgdb
Assuming that the PGDB ecoli is available on your running Pathway Tools server, the following call would bound variable pgdb to a PGDB object containing the PFrames for the compounds and reactions of ecoli:
pgdb = create_pgdb_with_compounds_and_reactions('ecoli')
For comments, questions and bug reports about PythonCyc, send an email to [email protected]
Eli Bogart inspired some implementation details of PythonCyc from its PyCyc package, Tomer Altman wrote the original Pathway Tools Lisp API documentation at http://brg.ai.sri.com/ptools/api/ and Daniel Weaver suggested to implement some specific functions to access the functionality of FBA in Pathway Tools.