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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
 Reading and Writing Models
Cobrapy supports reading and writing models in SBML (with and without FBC), JSON, YAML, MAT, and pickle formats. Generally, SBML with FBC version 2 is the preferred format for general use. The JSON format may be more useful for cobrapy-specific functionality.
The package also ships with test models in various formats for testing purposes.
Step1:  SBML
The Systems Biology Markup Language is an XML-based standard format for distributing models which has support for COBRA models through the FBC extension version 2.
Cobrapy has native support for reading and writing SBML with FBCv2. Please note that all id's in the model must conform to the SBML SID requirements in order to generate a valid SBML file.
Step2:  There are other dialects of SBML prior to FBC 2 which have previously been use to encode COBRA models. The primary ones is the "COBRA" dialect which used the "notes" fields in SBML files.
Cobrapy can use libsbml, which must be installed separately (see installation instructions) to read and write these files. When reading in a model, it will automatically detect whether FBC was used or not. When writing a model, the use_fbc_package flag can be used can be used to write files in this legacy "cobra" format.
Consider having the lxml package installed as it can speed up parsing considerably.
Step3:  JSON
Cobrapy models have a JSON (JavaScript Object Notation) representation. This format was created for interoperability with escher.
Step4:  YAML
Cobrapy models have a YAML (YAML Ain't Markup Language) representation. This format was created for more human readable model representations and automatic diffs between models.
Step5:  MATLAB
Often, models may be imported and exported solely for the purposes of working with the same models in cobrapy and the MATLAB cobra toolbox. MATLAB has its own ".mat" format for storing variables. Reading and writing to these mat files from python requires scipy.
A mat file can contain multiple MATLAB variables. Therefore, the variable name of the model in the MATLAB file can be passed into the reading function
Step6:  If the mat file contains only a single model, cobra can figure out which variable to read from, and the variable_name parameter is unnecessary.
Step7:  Saving models to mat files is also relatively straightforward
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Python Code:
import cobra.test
import os
from os.path import join
data_dir = cobra.test.data_dir
print("mini test files: ")
print(", ".join(i for i in os.listdir(data_dir) if i.startswith("mini")))
textbook_model = cobra.test.create_test_model("textbook")
ecoli_model = cobra.test.create_test_model("ecoli")
salmonella_model = cobra.test.create_test_model("salmonella")
Explanation: Reading and Writing Models
Cobrapy supports reading and writing models in SBML (with and without FBC), JSON, YAML, MAT, and pickle formats. Generally, SBML with FBC version 2 is the preferred format for general use. The JSON format may be more useful for cobrapy-specific functionality.
The package also ships with test models in various formats for testing purposes.
End of explanation
cobra.io.read_sbml_model(join(data_dir, "mini_fbc2.xml"))
cobra.io.write_sbml_model(textbook_model, "test_fbc2.xml")
Explanation: SBML
The Systems Biology Markup Language is an XML-based standard format for distributing models which has support for COBRA models through the FBC extension version 2.
Cobrapy has native support for reading and writing SBML with FBCv2. Please note that all id's in the model must conform to the SBML SID requirements in order to generate a valid SBML file.
End of explanation
cobra.io.read_sbml_model(join(data_dir, "mini_cobra.xml"))
cobra.io.write_sbml_model(
    textbook_model, "test_cobra.xml", use_fbc_package=False)
Explanation: There are other dialects of SBML prior to FBC 2 which have previously been use to encode COBRA models. The primary ones is the "COBRA" dialect which used the "notes" fields in SBML files.
Cobrapy can use libsbml, which must be installed separately (see installation instructions) to read and write these files. When reading in a model, it will automatically detect whether FBC was used or not. When writing a model, the use_fbc_package flag can be used can be used to write files in this legacy "cobra" format.
Consider having the lxml package installed as it can speed up parsing considerably.
End of explanation
cobra.io.load_json_model(join(data_dir, "mini.json"))
cobra.io.save_json_model(textbook_model, "test.json")
Explanation: JSON
Cobrapy models have a JSON (JavaScript Object Notation) representation. This format was created for interoperability with escher.
End of explanation
cobra.io.load_yaml_model(join(data_dir, "mini.yml"))
cobra.io.save_yaml_model(textbook_model, "test.yml")
Explanation: YAML
Cobrapy models have a YAML (YAML Ain't Markup Language) representation. This format was created for more human readable model representations and automatic diffs between models.
End of explanation
cobra.io.load_matlab_model(
    join(data_dir, "mini.mat"), variable_name="mini_textbook")
Explanation: MATLAB
Often, models may be imported and exported solely for the purposes of working with the same models in cobrapy and the MATLAB cobra toolbox. MATLAB has its own ".mat" format for storing variables. Reading and writing to these mat files from python requires scipy.
A mat file can contain multiple MATLAB variables. Therefore, the variable name of the model in the MATLAB file can be passed into the reading function:
End of explanation
cobra.io.load_matlab_model(join(data_dir, "mini.mat"))
Explanation: If the mat file contains only a single model, cobra can figure out which variable to read from, and the variable_name parameter is unnecessary.
End of explanation
cobra.io.save_matlab_model(textbook_model, "test.mat")
Explanation: Saving models to mat files is also relatively straightforward
End of explanation
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